The Biometrics of Non-Timber Forest Product Resource Assessment

The biometrics of non-timber forest product resource assessment:

A review of current methodology

J.L.G. Wong

April 2000

i This report comprises a review of the biometric qualities of current non-timber forest product assessment methods comissioned under the ZF0077 pre-project of the Forest Research Programme of the United Kingdom Department for International Development. It forms the background paper for a research workshop hosted by the European Tropical Forest Research Network (ETFRN). Developing needs-based inventory methods for non-timber forest products: Application and development of current research to identify practical solutions for developing countries. Rome, Italy, 4 – 5 May 2000. Companion documents are the Issues and options paper for discussion at the workshop, the Workshop Proceedings. The intention is to publish the material contained in this report as a contribution to the new FAO Forestry Manual and as a volume in the FAO Non-wood Series.

This publication is an output from a research project funded by the United Kingdom Department for International Development (DFID) for the benefit of developing countries. The views expressed are not necessarily those of DFID. ZF0077 Forest Research Programme.

Dr Jenny Wong, Ynys Uchaf, Mynydd Llandegai, Bangor, Gwynedd LL57 4BZ, UK with contributions from Ms Nell Baker, 7 Newman Road, Oxford OX4 3UJ, UK.

ii Executive summary The study undertook a review of anglophone literature concerned with non-timber forest product (NTFP) resource assessment. The intention was to examine the biometric quality of current methods and make recommendations for a programme of research to address any gaps. The focus of the research will be the provision of methods suitable for use in the tropics and sub-tropics but the literature review includes material from temperate and boreal forests. In all, 126 case studies were reviewed. Of these, 97 directly concerned the quantification of NTFP resource abundance, yield or growth. The papers were drawn from a wide range of disciplines and included work on exploited trees, herbs, fungi, fruit, mammals and birds.

Inadequate reporting of protocols meant that only 62 % of the 97 papers reported the data collection protocols in sufficient detail to permit an assessment of the biometric qualities of the methods used. The biometric quality of the studies was judged against 2 criteria: whether the sampling design was unbiased i.e. random or systematic and whether there was adequate plot replication. Altogether, 35 % of the studies used subjective sampling designs mostly the placement of plots in ‘representative’ sites. Studies generally tended to have less than five plot replicates or hundreds and even thousands. Studies with low numbers of plots tended to be undertaken by people coming from a social development or ethnobotanical background while those with large numbers were usually part of national scale forest inventories. It seems that the use of low levels of replication is something of a norm in current work as 49 % of the studies used less than 20 replicates and 12 % used only a single plot. Overall, only 38% of the 126 studies could be judged as being biometrically rigorous.

Many protocols especially in the context of multi-pupose resource inventories and for larger woody plants (trees, bamboos and rattan) are based on those developed for timber inventory and there are a number of apparently successful animal assessment protocols. Unfortunately, there is apparently little transfer of experience between forestry and wildlife management and no cross-disciplinary studies.

The main obstacles to the development of biometrically sound protocols for NTFPs relate both to the sheer diversity of NTFPs and the fact that often they represent only a very small part of the forest and are therefore sparce and often clumped. The problem can be compared to looking for the proverbial needle-in-a-haystack when one doesn’t even know what size or shape the needle will be. Compounding these difficulties are the need to make assessments very cheap and accessible to illiterate people in remote communities.

Most existing protocols are based on conventional forest or ethnobotanical inventory and do not address the particular needs of NTFPs. There is a real methodological gap in readily available advice tailored for sparce and clumped distributions typical of NTFPs and capable of delivering extreme cost- efficiency in operationally straightforward and intuitive protocols. Addressing this problem will require substantial theoretical and methodological development of novel techniques and new approaches to the assessment of plants and animals in tropical forests. The following six topics are proposed as a framework for research into the biometrics of NTFPs: 1. Evaluation of novel sampling designs for use in NTFP inventory 2. Development of measurement techniques for non-wood products 3. Development of NTFP resource monitoring protocols 4. Development of methods to determine optimal harvesting levels 5. Documentation and dissemination of statistical advice for NTFP assessment 6. Linking indigenous and scientific knowledge

The physical and logistical difficulties of working in forests means that methods developed in other environments need to be adapted and, most importantly, field tested for use in tropical forests. All research should be undertaken by cross-disciplinary teams of researchers, field workers and local communities to ensure the effective assimilation of existing experience and relevance to the pracitical contraints and information needs of those wishing to manage NTFPs.

iii Contents Executive summary ...... iii Contents...... iv 1. Introduction ...... 1 2. Background to NTFP resource assessment ...... 1 2.1 Definitions 1 2.2 Role of resource assessment in sustainable NTFP exploitation 3 2.3 NTFP typologies and resource assessment 5 3. Review of NTFP resource assessment methods ...... 7 3.1 Distribution, scope and scale of reviewed NTFP assessments 7 3.1.1 Location of studies 7 3.1.2 Life-form 8 3.1.3 Harvested part 9 3.1.4 Scale of assessments 10 3.2 Biodiversity inventory 11 3.3 Social science techniques 12 3.3.1 Local knowledge 12 3.3.2 The value of local knowldge to inventory methodology 12 3.3.3 Participatory approaches and data collection 13 3.3.4 The importance of involving local people 14 3.3.5 Field methods 15 3.3.6 Interview types 16 3.3.7 The reliability of informal methods 17 3.4 Anthropological methods 19 3.4.1 Ethnobiology 19 3.4.2 Classic ethnobotanical inventory 20 3.4.3 Quantitative ethnobotany 21 3.4.4 Other anthropological approaches to human-natural resource interactions 22 3.5 Economic methods 23 3.5.1 Market and income studies 23 3.5.2 Cost-benefit and valuation studies 24 3.6 Quantitative inventory 25 3.6.1 Single resource inventory 27 3.6.2 Single purpose multi-resource inventory 29 3.6.3 Multi-purpose resource inventory 30 3.6.4 Post-hoc use of timber inventory 33 3.6.5 Methodological studies 33 3.7 Yield assessment 36 3.7.1 Product enumeration 37 3.8 Growth and productivity studies 40 3.8.1 Permanent sample plot methods 41 3.8.2 Experimental harvests 42 3.8.3 Observations at paired sites 42 3.8.4 Individual-based observations of growth rates 43 3.9 Determining sustainable harvest levels 44 3.9.1 Rapid vulnerability assessment 45 3.9.2 Periodic harvest adjustments 46 3.9.3 Matrix models 47 3.9.4 Demographic methods for determining sustainability of hunting 49 3.9.5 Egg of sustainability 51 3.10 Monitoring 52 3.10.1 Monitoring exploited forest 53 3.10.2 Harvest records 54 3.10.3 Participatory monitoring 55 3.11 Criteria, indicators and certification 57 4. Review of current practice...... 59 4.1 Participatory issues 59 4.2 Linking local and scientific knowledge 61

iv 4.3 Demand for biometric rigour 63 4.4 Elements of a biometrically sound resource assessment 67 4.5 Biometric evaluation of reviewed studies 68 4.5.1 Reporting of protocols 69 4.5.2 Sampling design – randomisation 69 4.5.3 Plot configuration - independence 71 4.5.4 Number of observations - replication 72 4.6 Overview 73 5. Designing biometrically rigorous NTFP resource assessments ...... 75 5.1 Using objectives to design resource assessments 75 5.2 NTFP typology for inventory design 77 5.3 Sampling design 79 5.4 Plot configuration 81 5.5 Enumeration protocols 82 5.6 Yield measurement 82 5.7 Growth and productivity 83 6. Research issues...... 84 6.1 Evaluation of novel sampling designs for use in NTFP inventory 84 6.2 Development of resource measurement techniques for non-tree products 85 6.3 Development of NTFP resource monitoring protocols 86 6.4 Development of methods to determine optimal harvesting levels 87 6.5 Documentation and dissemination of statistical advice for NTFP assessment 88 6.6 Linking indigenous and scientific knowledge 89 7. Conclusions...... 91 7.1 Revisiting the definition of NTFPs 92

References...... 94

Appendices 1 Terms of reference...... 110 2 List of people contacted ...... 113 3 NTFP typologies...... 115 4 Summary of reviewed studies ...... 118 5 Sources for quanitative inventory methods...... 166 6 TROPIS search of NTFP PSP plots ...... 169 7 Summary of newer sampling methods with potential for NTFP inventory ...... 170 8 Folk classification and local names ...... 172

Figures 1 Flow chart of a basic strategy for managing NTFPs on a sustained-yield basis 5 2 Flow chart of basic strategy for monitoring sustainable management of NTFP 52 plant resources

Tables 1 Number of reviewed studies by country and region 7 2 Number of reviewed studies by life-form 8 3 Representation of NTFP plant resource categories and plant parts in review 9 4 Scale of reviewed studies 10 5 Examples of areas of local knowledge and their possible uses in NTFP inventory. 12

v 6 Degrees of participation 14 7 Methods for quantifying species use values 22 8 Externally lead behavioural research methods 23 9 Summary of quantitative inventory methods used in reviewed studies 26 10 Inventory methodology used by single resource studies 28 11 Examples of techniques used for quantifying product yield 37 12 Productivity studies undertaken on paired study sites 43 13 Criteria used in Rapid Vulnerability Assessment 46 14 Summary of main failings of NTFP resource assessments for valuation studies 64 15 Objectives and the need for biometric rigour 67 16 NTFP sampling designs in reviewed studies 69 17 Plot configurations in reviewed studies 72 18 Number of plot replicates in reviewed studies 73 19 Biometric qualities of reviewed studies 74 20 Decision model for assessing biometric rigour required in inventory design 77 21 Framework for NTFP inventory design 79 22 Sampling design and population characteristics 80 23 Use of plot configuration for NTFP resource assessment 81 24 Example possible enumeration protocols for NTFP resource assessment 82

Boxes 1 Enumerating NTFPs in the Philippine national forest inventory 31 2 Including NTFPs in the Ghana national forest inventory 31 3 Developing plot layout and measurement techniques for rattan inventory 33 4 Developing protocols for mushroom monitoring 34 5 Trial of local knowledge for inventory stratification for Pacific Yew 35 6 Trying to find Brachystegia saplings 35 7 Lianas – how to inventory them? 36 8 Multi-stage bamboo enumeration protocol 39 9 Forecast system and inventory of wild berry yields for Finland 40 10 PSP protocols used for fruit production 42 11 Harvest adjustment method for assessing sustainable yield from trees 46 12 Robinson & Redford (1991) method for assessing sustainability 50 13 Setting quotas for the Mount Cameroon Prunus bark harvest 65 14 Formal consultative approach to the survey planning process 76

vi 1. Introduction Many products have traditionally been extracted from forests, but over time they became increasingly marginalised as the emphasis in forest management shifted to timber production. This has been fuelled by three processes: the substitution of natural products such as rubber, chicle, gum copal and pau rosa by synthetics; the establishment of large-scale plantations for others e.g. oil palm, rubber, cocoa etc.; and the increasing alienation of local people resulting from a general institutional disregard for small-scale rural industry and subsistence use. Technological substitution and plantation development are inevitable and will continue to erode the practical income generating potential of natural forest. It is the institutional rediscovery of the value of supporting community subsistence and livelihoods that has prompted the resurgence of interest in products other than timber from the forest. This has been evidenced in a rapid rise in interest in non-timber products (NTFPs) among conservationists, foresters, protected area managers, social development advisors and indigenous rights groups. This has in turn resulted in a proliferation of studies into the potential of NTFPs for income generation and as a means of involving local people in forest management and benefit sharing. A basic premise of these initiatives is that the resources, be they animals or plants, should be exploited on a sustainable basis.

To be sustainable, harvest levels need to be based on a sound knowledge of the reproductive biology, distribution and abundance of the resource species. Such information can be obtained from a number of sources including knowledge acquired by indigenous peoples as well as formal scientific enquiry. Resource assessment for NTFP resources in the tropics is relatively new and has received little formal study; consequently methodologies have been developed by individual researchers in response to local circumstances and the peculiarities of the resources under study. Meanwhile sociologists stress that at the community level methods need to be devised that can be carried out by the community and respond to their management needs. It is argued that these may need to be very simple and need not necessarily have any biometric component (Schreckenberg pers comm.).

The present report was commissioned as the background paper for the ZF0077 pre-project of the Forest Research Programme of the UK Government Department for International Development (see Appendix 1 for terms of reference). It forms the background paper for the project and is the first stage in a programme of research intended to develop biometrically adequate methods for assessing the standing stock, production dynamics, harvestable components and actual harvests of the main types of NTFPs in the tropics and sub-tropics. The report is based on a review of the biometrics of current methods of NTFP resource assessment drawn from the anglophone literature supplemented by correspondence and meetings with key researchers both in the UK and abroad as listed in Appendix 2.

2. Background to NTFP resource assessment Before embarking on consideration of the biometrics of NTFP resource assessment it is first necessary to understand what is meant by an NTFP. This is not straightforward given the convergence of interest from a number of mutually unfamiliar sources and a general lack of identity for the ‘NTFP-community’. Many of those interested in NTFPs do not come from a natural science background so it is also necessary to demonstrate the role and significance of resource assessment in the achievement of sustainable management or exploitation.

2.1 Definitions The study of non-timber products is represented by initiatives arising from varied fields of study such as forestry, ethnobiology, economic botany, social development, natural resource economics, conservation biology, protected area management, agro-forestry, marketing, commercial development, ecological anthropology, cultural geography and human ecology. This has led to much discussion and no agreement

1 on a universally acceptable terminology to describe the products of interest (see biocultural-digest list server1 and bulletin board).

The only term with a definition defined by the FAO/IUFRO committee on forest bibliography and terminology is ‘minor forest products’ (Chandrasekharan 1995). This has many shortcomings and more or less passed out of general use in the early 1990s. In its stead a plethora of alternative terms has grown up with single terms sometimes having a range of interpretations, none of which are universally recognised. For example; AFP alternative forest products – on the grounds that they are not ‘minor’, wood or timber use should not be excluded and what is harvested is very often a raw material not ‘products’ so ‘resources’ better (Messerschmidt & Hammett 1998) MFP minor forest products, miscellaneous forest products since timber is the major product all other products are by definition ‘minor’ (Falconer 1990) NTFP non-timber forest products “any non-timber product that is dependant on a forest environment” (Arnold & Ruiz-Perez 1996) “all products, with the exception of timber, that can be harvested from a forest ecosystem” (Mallet 1999) “all tangible animal and plant products other than industrial wood, coming from natural forests, including managed secondary forests and enriched forests” (Ros-Tonen et al. 1998) NTPP non-timber plant products (Cotton 1996) NTRV non-timber resources and values NWFB non-wood forest benefits ‘benefits’ equated to advantage, favourable effect, output, profit and includes non-tangible products such as recreation, landscape values etc. (Chandrasekharan 1995) NWFP non-wood forest products “include all goods of biological origin, as well as services, derived from forest or any land under similar use, and exclude wood in all its forms” (Chandrasekharan 1995) NWFR non-wood forest resources “all resources found or originating on forest lands regardless if they are currently recognised as goods, as products, or as providing a service” (Lund 1997, 1998c) NWGB non-wood goods and benefits NWGS non-wood goods and services SFP special forest products (Vance & Thomas 1997).

A forest is a vegetation type dominated by trees; this maybe pristine natural rainforest, scrub woodland, palm savanna or plantations. A product is anything produced or obtained as a result of some operation of work, as by generation, growth, labour, study or skill (Lund 1997, 1998c).

For the purposes of the present study the following definition is used: NTFP – ‘all products derived from biological resources found on forest land but not including timber, fuelwood, lac or medicinal plants harvested as whole plants’. The restrictions are designed to exclude large-volume commercial products and the special case of medicinal herb collection in line with the TORs for this study (see Appendix 1).

1 E-mail [email protected] and put in the body of the e-mail for welcome page and subscription information. Bulletin board = http://www.anthrotech.com/ice/ntfp/messboard/

2 Beyond the confusion over the definition of the scope of what is meant by ‘NTFP’ there are also discrepancies in the use of terms such as ‘inventory’ and ‘survey’. It is evident from the literature that these terms mean different things depending on the researcher’s background. Three types of ‘inventory’ can be distinguished: floristic, ethnobotanical and quantitative. ‘Systematic’ is another term which has three alternative meanings (1) regular layout of plots such as on the nodes of a regular grid (2) using or showing order e.g. plant systematics is the study of plant classification and naming (3) methodical. This can cause some misinterpretation when reading across disciplinary boundaries e.g. Peters et al.(1989) say they use a systematic 1 ha plot since it is not possible to layout a regular pattern with one plot this reference should presumably be interpreted as ‘methodically searched’, sense (3) rather than sense (1).

The use of each term is consistent within a discipline but can be confusing to people from other disciplines. For clarity, there is therefore a need to introduce definitions for these terms. The following are adopted for the purpose of this study: Inventory - an itemised list of current assets (finished goods, components or raw material on hand) (Lund 1997). This may or may not include the quantity or other characteristics of the assests. Forest inventory – a sample-based survey of the forest resource (Burkhart & Gregoire 1994). The intention being to quantify the abundance of biological resources in the forest. The species lists are a sub- set of an inventory of biodiversity. Survey - to examine as to the condition, situation or value. To query in order to collect data for the analysis of some aspect of a group or area (Lund 1997). Monitoring is the process of observing changes in a resource base. It requires making the same observations at the same location but at different points in time (Lund 1997).

2.2 Role of resource assessment in sustainable NTFP exploitation The main feature common to all definitions of NTFPs is that they exclude timber, and the product, benefit or services should come from a forest. A key concept is that what is of interest is something useful to human society. It can therefore be surmised that before any plant or animal can be classified as a product it must be actively sought and collected for a particular purpose. Thus, a listing of all plants and animals in a forest is not a NTFP assessment but a biodiversity inventory. NTFPs are a sub-set of diversity that has utility to humans. Therefore the first step in the assessment of NTFPs has to be the identification of a plant or animal whole or part that is collected for some particular use.

Biological products of the forest have many diverse uses ranging from the manufacture of highly processed anti-cancer drugs, to ropes made from the stems of climbers for tying bundles of firewood. In subsistence economies and traditional forest societies the forest provides many of the essentials of life such as food, utensils, clothing, shelter, medicines and objects of spiritual or cultural significance. Each product often comes from preferred species of plant or animal and the depth of ecological knowledge of forest dwellers is such that nearly everything can be used for some purpose by someone. For example, Prance et al.(1987) showed that of plants enumerated in a 1 ha plot, 77% were useful to the Ka’apor, 61% to the Tembé, 79% to the Chácobo and 49% to the Panare peoples of Peru. While Salick (1991) reports that 94% of species and 76% of species in mature and logged forest respectively were useful to the Amuesha people of Peru. Inventory and description of all uses of a plant with perhaps some scoring of relative value (see below) is the particular interest of ethnobotanists and is important. However, only a few species and uses are potentially commercial. The first stage of a NTFP assessment that is interested in commercial produce is the identification of suitable species and market assessment of their potential. Unfortunately many projects stop after this point and commence marketing and promotion without formal consideration of the consequences for the welfare of the harvesters and resource sustainability (e.g. Richards 1993). Some species, exploited with the best of intentions may end up being over- exploited (e.g. Brazil nuts, Richards 1993). It is therefore important to establish the role of resource assessment and management in NTFP development.

3 Lund (1997 1998c) has identified four types of study that are needed for the successful and sustainable development of NTFPs; (1) biodiversity inventories (lists of species), (2) cultural studies, (3) user, market or product surveys, (4) resource inventories.

This approach takes a market-centric view of possibilities and does not consider the abundance of supply or the potential for sustainability until step (4). Other schemes are more resource-centric and seek to identify those products that can be marketed from a list which has already been shown to be sustainable (Wild & Mutebi 1996). Many authors describe an ideal development process that commences with the selection of species and progresses through market research, resource inventory, yield forecasting, determination of sustainable harvest practices and intensities, management planning and monitoring (e.g. Peters 1994, 1996a, Hall & Bawa 1993, Gould et al.1998, Ros-Tonen et al.1998). Whichever approach is taken it is clear that resource assessment plays an important role in NTFP development.

Figure 1 illustrates a conceptual flow chart based on that by Peters (1996a) for a basic strategy for managing NTFPs2. In Figure 1, the bold text boxes indicate analyses that, ideally should be statistically based, requiring biometrically rigorous resource assessment indicated in the shaded boxes. It can be seen that these cover the quantification of resource quantities, yield determination, forest productivity, and monitoring in the form of regeneration surveys and permanent growth plots.

Any NTFP development programme requires all of the studies in Figure 1. However some may not require formal work, or the information required may already be available (perhaps from a tree inventory for tree fruits). All stages can be commissioned and undertaken by a range of people such as the Forestry Department, external aid personnel, local communities etc.. So far most studies have been insular, resulting in an uneven development of methodology by different disciplines, much of which is unknown to other specialists. Furthermore, poor or scant attention has been paid to unfamiliar subjects in single- disciplinary studies. Examples of this are the omission of properly conducted resource assessments on the part of rural development workers and the omission of animals from forestry studies, despite there being appropriate established techniques in other disciplines. This needs to be addressed by interdisciplinary studies done where sociologists, rural development specialists, economists and resource scientists could collaborate to provide optimal methodology for each stage in the process.

The need for an established methodology for NTFP inventory was recognised by a Working Group at an FAO meeting on NTFPs (FAO 1996) which attempted to define a standard for assessing NTFPs. However, the Group concluded that it is ‘virtually impossible and therefore perhaps futile to search for a generalised technique for NTFP resource assessment’ because of major differences in: • intended use of the survey results, • the groups of NTFPs to be included, • spatial scale, and • temporal scale. To this list the resources available for the inventory in terms of technologies, skill levels and finances should be added.

Despite these complexities the present study reviews the biometric adequacy of current practice for each of those aspects of resource quantification indicated in Figure 1. On the basis of this, recommendations are made for the development of a framework to guide the further development of NTFP sampling methodology.

2 This framework is only concerned with the biological aspects of sustainable management, which is the focus of this paper. It should be understood that there are many socio-economic and political, especially tenurial aspects to sustainability that provide the context and facilitating environment for the development of viable NTFP management and use.

4 Figure 1 Flow chart of a basic strategy for managing NTFPs on a sustained-yield basis

Species/product selection

Delineation of management area

Preliminary forest type mapping Field survey Forest inventory Statistical analysis Yield studies

Forest productivity

Define production units

Estimate sustainable yield

Demographic monitooring Periodic monitoring of harvest impacts Demographic modelling

Adjust harvest

(After Peters 1994)

2.3 NTFP typologies and resource assessment It was requested that a typology of NTFPs should be developed for the purpose of evaluating the biometric adequacy for the present study (see Appendix 1). A typology is a classification of things into groups. NTFPs have been classified on many occasions though there is no concensus for either reporting, monitoring or as a basis for inventory and research. The current review has indicated that each study contains a unique classification devised for its own purposes, though there are some similarities between typologies within a discipline. Five approaches to NTFP classification can be identified from the literature as follows; • International reporting - Customs and excise – group according to product type (Appendix 3A) and end-uses (Appendix 3B) • Biodiversity inventories tend to group plants and animals according to family and genera. • Ethnobotanists classify according to end use for valuation studies (Appendix 3C) • Foresters and those undertaking in-forest resource assessment group according to plant form and parts used (Appendix 3D, 3E, 3F) • Wildlife ecologists tend to group according to family (which is closely linked to gross morphology i.e. life-form) and size (Appendix 3F) • Managers may wish to group according to management characteristics (Appendix 3G)

Of these it is only the first that is formalised as a numerical classification and is required for national and international reporting on the quantities and values of products in trade. At present there are several alternative classification schemes in use under ISIC (International Standard Industrial Classification or all economic activities) such as SITC (Standard International Trade Classification), HS (Harmonised Commodity Description and Coding System issued by Customs Co-operation Council) and CPC (Provisional Central Product Classification). These classifications are only concerned with product characteristics (i.e. degree of processing or edible foodstuff, etc) without any regard for the plant or animal that provided the raw material, so solvents will be grouped together regardless of whether they

5 are derived from a plant or animal secretion. Although it may seem that such classifications need not concern a forest manager, Chandrasekharan (1995) points out that rationalisation of these codes will make it easier to track and account for NTFPs in trade and thereby demonstrate their significance to national and international economies. Such classifications, because of a dearth of good national statistics will also necessarily be used in forest resource accounting such as required by the FAO FRA2000. Deficiencies in existing classifications have prompted the preparation of one specifically for NTFPs by Chandrasekharan (1995) which he proposed should be harmonised with existing classifications and used for trade statistics and national economic and environmental accounts.

Another classification intended for reporting is that prepared by Wyatt (1991) for Ghana, though this is more for national comparison between forest reserves (see Appendix 3B). This classification proposes a three level hierarchy; the top two being grouped according to usage and the lowest by botanical species. It is not clear if species with multiple-products will appear twice in the list and it is perhaps an uncomfortable compromise between a botanical and a product approach.

These less formal classifications serve specific purposes and facilitate data collection and analysis within each discipline but are not ideal for the purpose of selecting the most suitable quantitative inventory methodology. It is only recently that there has been much general interest in NTFP typology as a first step in the development of standardised advice on enumeration protocols (Brown pers comm., Brown & Sheil in Healey 1998) for NTFPs.

Examination of the available literature revealed a few studies that have produced typologies for inventory purposes. Kleinn et al.1996 (see Appendix 3D) were only concerned with non-wood plant products and proposed three groups based on how much they differed from trees. Tree products are the easiest to assess as existing forest inventory protocols can be used with product quantity estimated using predictive equations based on tree size (usually diameter). ‘Tree-like’ plants can also be assessed using modified forms of tree protocols, and productivity can also be related to straightforward stem measurements. Kleinn et al.(1996) note that inventory of the last group of non-tree-like plants is problematic because the scale, spatial distribution, botanical identification, detectability and lack of known relationships between productivity and easily enumerated characteristics of the plant can be highly variable or pose quite severe difficulties.

An alternative classification has been proposed by McCormack (1998) which is more detailed and distinguishes plants on the basis of life form and the impact of harvesting (see Appendix 3E). McCormack notes that the “distinction between her groups is significant in terms of how they have to be inventoried” but provides little guidance on how to go about designing an appropriate inventory scheme for the groups.

Stockdale & Corbett (1999) have prepared a field manual for inventory of NTFPs but this only deals with trees, shrubs, palms, bamboo and rattan in any detail, with only a brief mention of size measurements for herbs. They propose that all plant NTFPs should be enumerated using a single, standardised plot layout. The differences between the groups are therefore only in botanical specimen preparation and size measurement.

It seems apparent that there is no simple means of devising a typology of NTFPs as a framework for the elaboration of inventory methods and this approach was discarded. However, it is not possible to simply list all possible types of NTFPs with recommended methods, as almost every part of any plant or animal in the forest could potentially be an NTFP. The approach taken was to consider which features of NTFP resource populations are most relevant to inventory design and to classify them into groups which would require similar advice (see Chapter 5).

6 3. Review of NTFP resource assessment methods

3.1 Distribution, scope and scale of reviewed NTFP assessments A literature review of NTFP resource assessment methodology was undertaken over a four month period and supplemented with personal interviews and correspondence. It proved very difficult to obtain grey literature and to access material that are not in English. Consequently the material reviewed has a bias towards anglophone and published material and is not in any sense bibliographic. In total, reports of 95 NTFP assessments around the world were obtained and used as the basis for the biometric review. They are summarised in Appendix 4.

3.1.1 Location of studies The studies selected for review were not restricted to tropics and sub-tropics as it was discovered that there is much to learn from the experience of temperate researchers, so a selection of available papers from North America and Europe were included in the review. Table 1 lists the countries in which the reviewed NTFP studies were located. Table 1 Number of reviewed studies by country and region

Region Country N Region Country N Region Country N Africa Benin 1 Central Belize 4 North Canada 1 Cameroon 8 America Columbia 1 America USA 6 CAR 1 & Columbia / 1 USA / Canada 1 Central Africa 1 Caribbean Ecuador / Peru 8 Equatorial Guinea 1 Costa Rica 1 South Amazon 2 Gabon 2 Mexico 2 America Andean countries 1 Ghana 5 Nicaragua 2 Bolivia 1 Kenya 1 Panama 1 Brazil 5 Malawi 2 Venezuela 1 Ecuador 1 Namibia 1 13 Guyana 1 Nigeria 1 Europe Czech Republic 1 Peru 7 South Africa 4 Estonia 2 18 Sudan 1 Finland 7 South- Indonesia 12 Uganda 2 Lithuania 2 East Malaysia 5 Zaire (Congo) 1 Poland 2 Asia PNG 1 Zambia 1 Russia 2 Philippines 3 Zimbabwe 1 Sweden 1 21 34 17 Asia Lao 1 Indian India 9 TOTAL 126 1 Sub- Nepal 4 continent Sri Lanka 1 14

Despite the long history of inventory of NTFPs from European temperate forest this has only recently become accessible in English. It is now apparent that there is a considerable body of experience and long-term research on berries and mushrooms collected from cold temperate and boreal forest in northern and eastern Europe (Lund et al.1998). This corpus of work probably represents the state of the art in wild fruit research. There is also a growing awareness of the significance of NTFPs from the forested areas of the Pacific Northwest of the USA (Molina et al.1993, Vance & Thomas 1997) and Virginia (Bailey pers comm.). This in turn is generating demand for inventory, research, monitoring and management of a range of NTFPs including mushrooms and medicinal herbs. Given the lack of established techniques for biometric study of such products there is a small though growing body of work on NTFP assessment methodology being developed in the USA. The process of developing a biometrically adequate methodology for inventory and study of mushrooms in the Pacific Northwest is reported in great detail (Molina et al. 1994, Pilz & Molina et al.1996, Pilz & Fischer et al.1996, Pilz et al.1997, Pilz & Molina 1998). Mushrooms are an important, though often overlooked, product of tropical forests and this work should be relevant to tropical researchers. The continual refinement of the methods and the eventual acceptance of local collectors as voluntary enumerators has many interesting parallels with experience in the tropics.

7 There is a proliferation of research into NTFPs in the neotropics e.g. Anderson (1990), Redford & Padoch (1991), Plotkin & Famolare (1992). This led Ros-Tonen et al.(1995) to assert that there is a bias towards Latin America in NTFP research, however, this is not reflected in Table 1. This is because much of the work in the neotropics is concerned with either ethnobotanical research or large scale commercial exploitation in the context of extractive reserves3 and not quantitative resource inventory. Most neotropical quantitative work has been directed at the determination of sustainable yields of fruit from oligarchic forests (Peters, Balick & Anderson 1989, Peters 1990 & 1991, Peters & Hammond 1990, Pollack et al.1995, Phillips 1993). There has also been work on hunting, particularly the determination of overexploitation and subsistence use (Robinson & Redford, eds. 1991).

It is interesting to note that Africa, where NTFP use is largely at subsistence or local market level, has the highest number of studies in the review. Much of this research emanates from a desire to stabilise protected areas through collaborative forest management for NTFPs. This is typified by the work in National Parks in Uganda (Scott 1998, Cunningham 1996a and Wild & Mutebi 1996) and Forest Reserves in Ghana (Falconer 1992b) and Nigeria (Dunn et al.1994). Africa also has a small body of work on hunting and subsistence use of wildlife particularly in central Africa (Infield 1988, Marks 1994 & 1996, Noss 1998, FitzGibbon et al.1995, Fa et al.1994).

India has a prolific forestry literature and an Institute of Non-Timber Products but much of this is concerned with pharmacological analysis of medicinal plants or with species being cultivated in agro- forestry or community forests. Both of these are outside the scope of the present review and are not included. The relatively few studies that quantify NTFPs have been undertaken for commercially exploited rattans and bamboo by the Forestry Department.

There are relatively few NTFP studies in South East Asia given the commercial importance of rattans, bamboo and illipe nut. Indonesia has the highest number of reviewed studies but these nearly all relate to the inventory of rattans.

3.1.2 Life-form NTFPs encompass the whole range of plant and animal life-forms as illustrated in Table 2. Table 2 Number of reviewed studies by life-form

Group Life form No. Group Life form No. Animals Mammals 6 Fungi Mushrooms 10 Ungulates 5 Truffles 1 Primates 4 Rodents 3 Plants Trees 31 Generic ‘animals’ 3 Shrub 20 Carnivores 2 Palm 18 Insects 2 Generic ‘plants’ 16 Bats 1 Rattan 16 Birds 1 Herbs 13 Fish 1 Bamboo 10 Insectivores 1 Climbers 5 Marsupials 1 Epiphytes 1 Shrews 1 Squirrels 1 Snails 1

It is apparent from Table 2 that most studies have been done on trees, followed in descending order by palms, rattans and shrubs. The emphasis on trees is a result of several factors including the pre-eminence of foresters in NTFP inventory and also because they define the forest. Although many NTFP trees are enumerated in ‘timber’ inventories only two studies (Johnston 1998, Gunatilleke & Gunatilleke 1993) undertook NTFP interpretations of existing inventories. Palms, rattans and bamboo are traditional NTFPs and have been regarded as a useful secondary products of many forests for a long time. For example, in

3 Although there is a legal requirements for resource inventory in the establishment of Extractive Reserves in Brazil (Murrieta & Rueda 1995).

8 India bamboo has been inventoried by the Forestry Department since 1965 (Rai & Chauhan 1998). There are very few innovative or successful assessments of plants that are less like trees.

To date, academic interest in NTFPs has been driven by plant-based disciplines and fauna is generally under-represented given its dietary significance. Although NTFPs are generally defined as including animals there are only a few studies that consider both plants and animal exploitation on the same site (Gronow & Safo 1996, Grossmann 1998) or include animals in the context of an NTFP study (Falconer 1992b). Generally, for all practical purposes, a NTFP is a plant. However, there is increasing recognition that animals are significant (if not the most important) forest products to local people and that foresters need to consider animals an integral part of any NTFP management scheme and become confident in wildlife assessment (Bird pers comm., Brown pers comm.). A search revealed that there is in fact a significant body of work done by zoologists on the quantification of animal hunting and especially on the assessment of sustainable yields and detection of over-harvesting. Furthermore, there is a large and long- established literature on faunal inventory methods for tropical forests (see Appendix 4). All of this is relevant to any broader consideration of NTFP assessment methodology and a selection of this material has been included in the present review. The review of faunal NTFP studies was complicated by the fact that zoologists do not use the term ‘NTFP’ which appears only to be in common usage among foresters and botanists, though it is clear that studies of sustainable harvesting levels for forest animals are relevant. The large body of work on the effects of logging on forest animals (see Johns 1997) was specifically excluded as although relevant to a wider consideration of multi-use forest management, it focuses on the conservation rather than use of animals. It is only relatively recently (since 1991) that biologists, applied anthropologists and “those interested in human use of resources” have turned their attention to the study of hunting (Redford 1993). It is in these studies that animals are most fully treated as ‘products’ of the forest i.e. as NTFPs. The review includes 12 hunting studies. These papers are a serendipitous selection as a full review of zoological literature was not undertaken and the papers have been included principally to demonstrate the existence of NTFP-relevant faunal studies and to provide a basis for consideration of faunal NTFP enumeration issues. Texts on faunal survey techniques for use in tropical forests have been included in Appendix 4.

3.1.3 Harvested part NTFP use of an organism can range from destructive harvesting of an individual to non-destructive removal of a small part such as a flower or snake venom. Peters (1994, 1996a) developed a list of plant resource categories and plant parts which is given in Table 3. The majority of studies focus on fruit and stem fibre with very few or no resource quantification studies specifically directed at root or exudate products. There are a number of studies that include all products from all or a number of plants but these only enumerate the occurrence of individuals and do not quantify the yield per plant or per ha of particular parts or products. Table 3 Representation of NTFP plant resource categories and plant parts in review

Resource category Plant part Studies Reproductive Fruit 24 Propagules Nut/seed 2 Oilseed 1 Plant exudates Latex - Resin 1 Floral nectar - Sap 1 Vegetative structures Stem 20 Leaves 7 Root 2 Bark 5 Tuber 1 Apical bud 1 (after Peters 1994, 1996a)

9 3.1.4 Scale of assessments NTFP assessment can take place on a wide range of scales from research studies on single 1 ha plots to supra-national studies of species distributions. However, as revealed in Table 4 there is a marked concentration of studies for smaller scale areas of less than around 10,000 ha with very few quantitative studies at national scales. This reflects the focus in NTFP work on community management and NTFPs as part of reserved forest management. The research-scale studies are usually at the smallest scales and are often undertaken on single 1 ha sites. However, most are multi-site studies of some aspect of the life- history of a particular NTFP species or species response to management interventions. As such they are not designed to provide management orientated information for a particular site but for insights into the ecology or biology of a species.

Active management takes place at the local scale, on community lands or within a forested area earmarked for collaborative management or NTFP exploitation. The majority of studies have taken place at these local scales and are intended to provide the information required to define the potential for sustainable exploitation or for management planning. However, most of these small scale studies are experimental in nature and are not institutionalised. The CAMPFIRE programme in Zimbabwe and the Joint Forest Management (JFM) initiatives in Nepal and India represent larger scale up-take of active management for NTFPs and each contains elements of participatory quantification of resource levels and harvests (CAMPFIRE - Child 1996; JFM - Branney 1994a, Poffenberger et al.1992). There are few other examples of established protocols for local scale resource assessment that could be used as the basis for wider adoption of NTFP management. This has been recognised by a few researchers such as Stockdale & Corbett (1999) who have prepared a manual for participatory resource assessment while the work reported by Gronow & Safo (1996) for Ghana and Watts et al. (1996) for Uganda have potential for development into generic methodologies. At present, NTFP management initiatives are treated as one- offs with the issues of resource assessment and management guidelines being tackled afresh each time, which requires substantial external i.e. national, or more usually external support.

National scale studies are required for strategic and policy planning. This is generally the purview of government acting under advice from national institutions such as Forestry and Wildlife Departments. At present the interest in NTFPs at this level has mostly come from export development to identify new export products, from treasuries looking to increase foreign exchange earnings, for compliance with international agreements (e.g. FRA2000, UNCED) and for monitoring and regulation of trade in endangered species (e.g. CITES). The data on which policy and strategic decisions are based generally comes from trade (export statistics), market surveys or statutory regulations (e.g. permits, quotas). Decisions are often based on such secondary data without much checking of their veracity, e.g. american ginseng has apparently been listed under CITES Appendix 2 based on trade data and intuition rather than resource inventory (Bailey pers comm., Gagnon 1999b). Biometrically rigorous resource data is most often collected only once the forestry agency has accepted responsibility for inventory of NTFPs as part of its statutory responsibility (e.g. as in USA where Forest Service is increasingly concerned that it should be monitoring NTFPs – Hosford et al.1997). All of the national level studies in Table 4 have been undertaken by national Forestry Departments (six in Europe, two in India and one in Africa) combined with timber inventory within forest authority jurisdictions as part of multi-purpose resource inventory (MRI, sensu Lund et al.1998). Table 4 Scale of reviewed studies

Scale % studies Research (sites chosen to examine some characteristic or management 18.4 response of specific NTFPs) Local (studies to represent resource use/availability within village lands, 24.0 administrative districts etc.) Compartment 0.8 Reserve (studies within protected forest, concessions etc.) 25.6 Regional (part of country e.g. State-wide) 15.2 National (estimates for whole country or part of country covered by relevant 14.4 forest types) International (studies across more than one country) 2.4

10 3.2 Biodiversity inventory Stork & Davies (1996) define biodiversity inventory as ‘a list of biological entities from a particular site or area’. Biodiversity inventory therefore is concerned with listing as many species as possible. However, more recent texts e.g. Watt et al.(1998) include quantitative techniques and abundance measures as an adjunct to the lists principally for management purposes. The Smithsonian manuals of standard methods for amphibians (Heyer et al.1994) and mammals (Wilson et al.1996) also contain sufficient material to undertake quantitative inventory.

The raw data of a biodiversity inventory is a checklist of the taxa identified at the sample locality or plot. For older, reference collection material, the locality can be a whole forest, indicated as lands adjacent to a named village, within an administrative district or within a country (as recorded in herbarium and museum gazetteers). In general, voucher specimens are collected for all individuals found in the inventory which are named and archived in herbaria and museums. Scientific names from such studies are therefore reliable. The results of a biodiversity inventory are generally presented as checklists of species by family and genera for the locality. Analyses of these data are generally between site comparisons using biodiversity indices. Collation of all published and herbarium/museum records for a species are used to prepare the species distribution maps that appear in floras and identification guides.

Another form of plant diversity inventory for which the term ‘botanic survey’ has been proposed (Hawthorne pers comm.) is one that seeks to investigate landscape scale patterns in diversity for the primary purposes of identifying botanical diversity hotspots and/or conservation priorities (Healey et al.1998). In such an inventory many plots either of fixed size or dimensionless are located across the landscape with all species in each plot named and if necessary collected (see Hawthorne & Abu-Juam 1995 for protocols used in Ghana high forest survey). The data that is generated by such surveys are numerous species lists present at known and precise locations. This data is not strictly quantitative as the records consist of species lists for a large number of precise locations without any measure of abundance within a plot. However, the data can be analysed to produce vegetation classification via ordination analyses (e.g. Hall & Swaine 1981), distribution maps, ecological profiles of the species and an understanding of environmental and evolutionary relationships as exemplified by Hawthorne (1996). Computer tools such as FROGGIE (Hawthorne 1995a), BRAHMS, TREMA (http\\:www.trema.co.uk) and equivalent software developed by the Smithsonian etc. are available to assist with the organisation, analysis and mapping of such data.

Since NTFPs are a sub-set of all plants and animals, biodiversity surveys are often a useful source of information on the distribution and ecology of NTFPs. Unfortunately, standard biodiversity inventories do not distinguish useful taxa and more significantly rarely quantify population abundance. A biodiversity inventory is therefore most useful for detecting whether a particular taxa known to be useful occurs in the locality being surveyed (though an absence of a record should not be taken as indicating it does not exist). For non-georeferenced data this may be a very crude representation of the distribution of a species. However, much more can be obtained from plot-based biodiversity work as indicated above. It is interesting to note that there is a link between the scale of study and the degree to which location specific species lists can be considered as quantitative data. If the area of interest only contains a few collected locations (as may be the case with older data or smaller areas) then it must be considered non- quantitative as there will be insufficient replications for generalisations. However, if there are a large number of locations (replications) within the area of interest then the data can be treated as quantitative with the potential for statistical analyses. It would be interesting to undertake an analysis to determine the number of such plots that would be required for statistically robust generalisations.

On balance, biodiversity inventories can provide important sources of data for NTFP studies and the more recent developments in methodologies may be directly applicable to NTFP inventory.

11 3.3 Social science techniques

3.3.1 Local knowledge Many of the NTFP inventory cases studied in this report have used local (sometimes termed indigenous) knowledge. However the reasons for using such knowledge and the level of reliance placed upon it vary greatly. The purpose of utilising local knowledge tends to vary from enhancing the efficiency of the inventory to enhancing local people’s understanding of and involvement in resource inventory for their own benefit.

3.3.2 The value of local knowldge to inventory methodology The collection of local knowledge is often the quickest and cheapest means of obtaining basic information about a resource. Such information can be used firstly to decide if an inventory is required and secondly to decide on an appropriate sampling design and enumeration methodology. Examples of the kinds of local knowledge that have been used in the past are provided in Table 5 (Hot Springs Working Group 1995, Carter 1996, Guijt & Hinchcliffe 1998, Martin 1994). Carter (1996) notes that density and abundance in different forest types and size-class distribution require formal inventory but life-cycle characteristics and type of resource produced can be determined from interviewing locals. Table 5 Examples of areas of local knowledge and their possible uses in NTFP inventory.

Local knowledge Use in inventory Species identification. Local tree spotters can be useful in the field (but see section below on taxonomy) Important economic species Species to include in inventory (e.g. Wild and Mutebi 1996, rapid vulnerability assessment) Vegetation classification Can be used for stratification Micro-climate types and distribution Can be used for stratification Soil types and distribution Can be used for stratification Harvesting techniques and frequency Affect enumeration methods and frequency History of availability Prioritise species to include Current estimation of availability Prioritise species to include – influence decision on whether inventory is necessary. Ecology and distribution of species Sampling method Human interaction with environment (e.g. existing Influence inventory objectives & design management) Forest and resource value Influence management objectives and hence inventory objectives. Socio-economic factors affecting NTFP Influence decision to have an inventory and its objectives. management Influence interpretation of inventory results. Note that this table is not comprehensive and that the above uses of local knowledge are case specific, i.e. the types of local knowledge listed cannot always be used in inventory in the manner described.

Some may question the reliability of local knowledge for making decisions about inventory design, for two reasons. Firstly, one would be concerned whether the information has been collected and interpreted adequately to portray a true understanding of the local knowledge available. Secondly, there is the question of whether local knowledge is a true reflection of reality.

The collection of local knowledge for forestry development projects varies from formal social surveys, anthropological and enthnobotanical techniques, rapid rural appraisal, participatory rural appraisal and participatory learning and action (Nichols 1991, Chambers & Guijt 1995, IIED 1997). These methods are discussed in the following sections.

The question of whether local knowledge provides a true reflection of reality is a largely philosophical which is beyond the scope of this report. In short, all stakeholders will have different ways of understanding their environment and different perspectives of change (Abbot & Guijt 1998). No one perspective can be considered absolute (Chambers 1997). Experience has shown that local perspectives often serve a practical purpose and are a sensible starting point for understanding and/or classifying the ecological environment.

12 In utilising local (anecdotal) knowledge the design of the inventory should account for the need to scientifically verify aspects of knowledge where there is still some doubt (e.g. if local vegetation classification is used for stratification). In addition, the efficacy of the design should be reviewed after an appropriate period of data collection. The latter may coincide with a conventional pilot study used to assess sampling errors or it may serve to alter the design for regular monitoring subsequent to an initial inventory. Obviously, when indigenous knowledge is not available or it is clearly unreliable, it cannot be used.

3.3.3 Participatory approaches and data collection Rapid Rural Appraisal (RRA), Participatory Rural Appraisal (PRA) and Participatory Learning and Action (PLA) are approaches rather than formalised methodologies. In practice, each of them comprises a set of communication and development tools, different combinations and permutations of which are used depending upon the objectives and stage of the project or process. One could argue that as methodologies they have evolved one from the other (RRA > PRA > PLA) (Havel 1996, Carter 1996), each taking the tools from the previous one but incorporating the principle of participation in a more comprehensive manner. RRA was developed in the late 1970s as a rapid means of collecting indigenous knowledge. Key features of the process are the involvement of multi-disciplinary researchers and the use of a suite of different methods across a range of informants. The information collection methods used are derived from a broad range of social and biological disciplines, e.g. ethnobotany, agroecology, human ecology etc. (Chambers 1989). A key principle in the process is triangulation i.e. daily discussion of results amongst researchers; a flexible, responsive work programme; and the utilisation of a variety of information gathering methods enabling detailed cross-verification of the data in the field. PRA was developed soon after RRA, adding further tools for information collection and the concept that local people (and not the outside experts alone) could and should participate in the analysis of their situation and collective knowledge. As part of this process, the outside researcher becomes both a facilitator and analyst and less of a data collector. This is a key difference between RRA and PRA, as the former tended to be an extractive data collection exercise with data analysis and problem solving undertaken by the outside experts. Although RRA is still considered appropriate in particular circumstances the development of PRA came as a recognition that in many instances local people were better placed than outside researchers to analyse and seek solutions to their problems. PLA takes this further and includes the concept that local people can and should be involved in learning from each other, developing research programmes to fill locally identified information gaps and determining the direction of and being actively involved in their own community development. This also includes aspects of managing institutional linkages and collecting and managing funds. PLA is much less focused on information collection than the previous two methods and more attuned to Friere’s (1970) concept of rural development through participation.

PRA, RRA and PLA are only three of a whole host of overlapping participatory approaches or methodologies. Havel (1996) lists and describes several participatory methods and refers to each method as ‘…a combination of tools, held together by a guiding principle’. The methods include: Appreciation-Influence-Control (AIC) Objectives-Oriented Project Planning (ZOPP) TeamUP Participatory rural appraisal Beneficiary assessment Systematic client consultation Social assessment Gender analysis These methodologies share many of the tools for data collection/discussion. See section below for further information on tools.

13 3.3.4 The importance of involving local people Many practitioners argue that where the purpose of undertaking an NTFP inventory relates to improving the sustainability of local livelihoods it is strongly recommended that local people are involved at all stages of decision making (Carter 1996, Stiglitz 1999). They should be active participants in the decision to undertake the inventory, their ideas should be incorporated into the objectives and design of the inventory and they should be actively involved in the fieldwork and the data analysis. The main reasons for this are the opportunity for a two-way learning process and the fact that involvement helps to develop a sense of responsibility for the environment (Salick 1991, Shanley et al.1997, Scott 1998). In addition, active involvement helps people to understand how and why decisions are made; without this understanding people will usually not accept the decisions over the long term (Stiglitz 1999). This ultimately improves the potential for developing a sustainable participatory management system. Another reason for local participation is to ensure that the data collected will actually be useful for management and that it is integrated with work on resource use and economics (Abbot & Guijt 1998, Shanley et al.1997). The different levels of participation are provided in Table 6). Table 6 Degrees of participation (adapted from Cornwall 1995 in Carter 1996)

Mode of local Type of participation Outsider Potential for Role of local people’s control sustaining local people in participation action and research and ownership action Co-option Tokenism – representatives are chosen but have no real input of power *********** Subjects Co-operation Tasks are assigned, with incentives; outsiders decide agenda and direct the ********* Employees/ process. subordinates Consultation Opinions asked; outsiders analyse information and decide on a course of ******* Clients action. Collaboration Local people work together with outsiders to determine priorities; ***** *** Collaborators outsiders have responsibility for directing the process. Co-learning Local people and outsiders share their knowledge to create new *** ****** Partners understanding and work together to form action plans; outsiders facilitate Collective action Local people set and implement their own agenda; outsiders absent ********* Directors (adapted from Cornwall 1995 in Carter 1996)

Case studies indicate that where local people’s ideas and decisions are incorporated into inventory design and implementation, the biometric adequacy of the inventory may be compromised. It has also been shown (see examples below) that local communities may initially select methodologies where the information collected is very general but move towards the collection of more detailed information as they realise that their questions are not being answered (Abbot & Guijt 1998). The degree to which such a learning process is engendered depends upon the objectives of the inventory and the urgency of acquiring scientifically reliable data. In all cases it is important to be painstakingly aware of the applicability and possible sources of error in the data when using it in making management decisions. Any risks involved regarding the reliability of the data, should be clearly understood by both the outsiders and the local people. If people do not clearly understand the implications of their decisions about inventory design, they are likely to be disappointed with the results and may possibly lose interest in the process altogether (Carter-Lengeler & Jones 1998).

A few examples will serve to illustrate these points: - Local communities may only be interested in inventorying collecting areas (e.g. Wyatt 1991). Information gained from this will be very useful for immediate management. An outside researcher may, however, recommend a more evenly distributed inventory as they may be interested in verifying local knowledge about distribution and in obtaining figures for the whole population of the species under study (Salick et al.1995). Where the resource is under severe threat it might be

14 advisable to heed the outsider’s concerns but where this is not so urgent it might be advisable for the community to undertake the inventory their way. At a later stage they may decide that they need more information about the population outside of regular collection areas. - Local people may decide that they prefer to measure yield per tree than yield per ha (Shanley et al. 1996). If at a later stage they decide to manage the resource on an area basis they will discover that this information is not adequate and will change their methods accordingly. - Local people may decide that an indirect measure of the health of the resource is easier to assess and is sufficient – e.g. ease of finding the resource (average walking time) or harvest statistics. Where the resource is relatively abundant these may be adequate methods but if a decline is indicated and the community wants to respond by developing harvest control systems they will need to collect more quantitative information about the resource (see below for further discussion). An important issue when inviting local participation in inventory, management and knowledge elicitation is who the data or information belongs to. There is increasing disquiet about the intellectual property rights issues surrounding the information collected during outsider-led projects (Schreckenberg pers comm.). Who will own and have the rights to use the information is something that needs to be negotiated early in the participatory process (Lund 1998).

3.3.5 Field methods There are a broad range of methods, tools or techniques that can be used in the field for collecting local information and for exploring local problems. Texts providing detailed information on these include (Nichols 1991, Carter 1996, Alexiades 1996, Davis-Case 1990, Macgillivray et al.1998, Lewis et al.1998, Lewis 1998). Tools for information gathering and analysis include a range of interview types and different games, visual aids or activities. Nichols (1991) states;

“There are no strict rules for the choice of methods. Generally, you need to strike a balance between the money and time available, and the depth and breadth of the information needed. Formal methods work best when you want more precise, statistical answers to carefully defined questions on topics which are thoroughly understood; they are powerful tools for collecting a broad range of standard information on a large population. Statistical methods give precise estimates and you can assess their reliability. This gives support to your findings and interpretation.”

Informal methods are often chosen when time and money are short. They give a rapid feel for a problem. But they are also essential in exploring community attitudes and priorities and when dealing with sensitive topics in depth. They can give a rich understanding of community life, and help to set up a dialogue between planners and the community.’

Hentschel (1998) provides an analysis of the quantitative and qualitative debate in social data collection. Many fields of the social sciences have been engaged for years -- if not decades --in what has come to be known as the ‘ quantitative-qualitative’ debate. The debate concerns itself with the question, which of the approaches is better suited to record social phenomena, and to what degree the two should -- and can -- be integrated. In recent times, the ‘ voices of segregation’ as those of Pedersen (1992, p.39), who questions the usefulness of quantitative methods because ‘the complex network of factors and the human experience is lost in the search for establishing empirical generalisations for the sake of presenting reliable results’, have lost considerable support; the debate has shifted considerably towards a broad mainstream calling for sensible integration of quantitative and qualitative approaches very much along the lines of Mechanic (1989, p.154) who maintains ‘the strong view that research questions should dictate methodology’ and he particularly endorses ‘combining the advantages of a survey (its scope and its sampling opportunities) with the smaller qualitative study.’ Hentschel argues further that both informal and formal methods can be used to collect both qualitative and quantitative data but that informal methods tend to provide more contextual data than formal methods.

15 3.3.6 Interview types According to Alexiades (1996):

“The interview, in its various forms, constitutes the basis of most ethnobotanical data collection. Insofar as an interview consists of two or more people talking to each other, the process has a simple and straightforward appearance. In reality, the way in which the interview is conducted, how questions are constructed and presented, and the answers recorded, all have significant impact on the quality, quantity, and meaning of the data collected. It is through the interview that the fieldworker can record the different epistemological, symbolic, and pragmatic aspects of plant use and situate this information in a meaningful context.

The art of interviewing depends on the delicate balance of curiosity and respect and on finding the thin line between showing interest and asking too many questions. The best information is obtained over extended periods of time, where mutual trust and understanding can develop, allowing the researcher to cross-check his or her observations repeatedly.”

Alexiades (1996) defines four types of interview: Informal interview: A completely informal interaction between two or more people. The researcher might take notes during or after the ‘interview’. Unstructured interview: A discussion where one person is gathering information from another on a particular topic but no specific or guiding questions are used after the initial enquiry (e.g. ‘tell me about the plants in the forest’). The informant(s) is aware that it is an interview but the choice of topics to discuss and the direction of the conversation are mostly controlled by the informant. Semi-structured interview: The interviewer has a list of open ended questions or topics to discuss (usually 6-10 key questions). The amount of information provided on a topic is largely controlled by the informant and the interviewer is free to follow leads. This type of interview is generally used once specific research topics have been identified. Structured interview. The interviewer has a fixed length questionnaire. Questions are not open ended but have a limited range of possible responses. Understanding what would be a locally meaningful question is a pre-requisite to designing a questionnaire form. This is because inappropriate closed questions will invariably introduce interviewer bias. Formal surveys are generally used to obtain quantitative information regarding a problem. For example there would be no point in designing a formal survey on water quality if you knew nothing about how your informants define water quality and the range of qualities they experience. Such information would best be obtained through informal methods then a formal survey could be designed to determine the extent of certain pre-defined water quality problems. A formal survey would permit biometrically appropriate analysis of the extent of such problems with results such as ‘We are 95 % confident that 75% ± 4.5 % of households in Kujinga area experience water quality problems’. Nichols (1991) states that ‘In order to design a good structured interview survey, you need a full knowledge of the problem you are studying. This in itself limits their use. In a new area one needs methods that are more suitable for exploratory study’. See Nichols (1991) for more information on formal questionnaire design.

Formal questionnaires can also be designed for recording observational data. Where the researcher records his/her observations of the local activities (e.g. number of people using water facilities at different times of day etc.).

Interviews may be held with key informants, randomly or systematically selected individuals of the population under study or with groups of people (focus group interviews). Key informants are people with specialist knowledge on a topic. They are usually identified by senior or other community members. Key informant interviews are often held with elders or community leaders to learn about general

16 demographic features of a community (e.g. number of schools, households, water points, religious groups etc.).

Individual interviews tend to have a wider scope than key informant interviews and tend to be more open-ended (Nichols 1991).

Individual and group interviews tend to complement each other. Certain topics may be more appropriate for group discussion and others for one to one interviews. In addition certain people may feel more comfortable discussing certain issues in groups than on their own, or vice versa. In groups people will often prime each other to provide certain information and a wealth and range of information on certain topic can be elicited (Alexiades 1996).

Focus group discussions are usually undertaken with a group of 6-12 people (Lewis 1998, Nichols 1991). The discussion is usually steered by the interviewer in a semi-structured manner. It is usually advisable to select members of a group so that they will be comfortable in discussion with each other. For example, same sex groups, age groups, wealth or class groups or groups of people with similar skills or who engage in similar activities. It is important to undertake a certain degree of replication of group interviews as results from one group discussion will often be influenced by the specific dynamics of that group. For more detailed information on focus group interviews see Lewis (1998).

Workshops and meetings with larger groups are useful for presenting and verifying the results of a study (Chambers 1989).

A wide variety of tools and techniques can be used to encourage and assist people to participate in data collection, analysis and problem solving. These tools tend to make interviews or group meetings more interesting as they often use visual aids and require people to actively (as opposed to verbally) participate. Some improve understanding and communication whilst others stimulate creative thinking and analysis. Some of the tools include: brainstorming, drawing pictures/maps, timelines or historical mapping, ranking rating and sorting, matrix ranking, walks (transect walk and mapping, research plot walk, forest walk etc.), role play, seasonal calendars, labour division charts, theatre, murals and posters, flannel boards, open-ended stories, unserialized posters, logframe, Venn diagrams and community case studies etc. For more information about these methods see Davis-Case (1990), Lewis et al.(1998), Havel (1996). Further tools are available on http://www.oac.uoguelph.ca/~pi/pdrc/facbox.html.

3.3.7 The reliability of informal methods There has been a series of discussions amongst social scientists and others regarding the reliability of RRA and PRA methodologies for data collection as these do not conform to traditionally accepted statistical norms (Gilling & Cropley 1993, Chambers 1983, Inglis 1991, Gill 1993). In RRA, PRA and PLA verification of the reliability of information collected is undertaken as part of the process rather than via data analysis after collection. It has been shown that appropriate utilisation of PRA methodology with careful triangulation and cross verification in the field can yield reliable, trustworthy results (Guijt & Hinchcliffe 1998, Chambers 1997). As Gill (1993) points out ‘Participatory methods for local level analysis and planning yields positive results that are largely verified by subsequent formal surveys’. Obtaining ‘good’ data using these methods, however, relies upon the skills of the facilitators who must have a clear understanding of the participatory concept, a good analytical capacity and outstanding personal skills in working with people (Gilling & Cropley 1993). It is clear that if information collected in this manner is to be relied upon there needs to be some assurance of the quality of the facilitator/researcher i.e. with regard to their qualifications and abilities.

As informal methods of data collection are perfectly acceptable for certain purposes it would seem that criticism of studies relate to inappropriate or poor utilisation of the methods and development of conclusions that cannot be drawn from such methods. For example, it is noted that many forestry related PRA or RRA exercises have been undertaken or facilitated by a team of one or two researchers and therefore are unlikely to provide adequate information on the full range of topics that might be of

17 concern in a natural resource management oriented exercise (areas of expertise that may be vital could include forestry, hydrology, agricultural systems, livestock, wildlife, education, economics, small business, health etc.).

The concerns expressed by social scientists regarding the inappropriate use of informal data collection methods can be gleaned from the following excerpt (Hentschel 1998).

“Contextual (i.e. informal) methods play a unique and singular role to understand specific aspects of health care utilisation. Understanding the importance of ethno-medical beliefs, the conceptualisation of disease by local populations, and the role of trust, corruption and conflict as determinants of health demand and provider choice all fall into this category. To require studies in these areas to be ‘ nationally representative’ or to produce ‘ statistically significant results’ would either be false (because some aspects might be inherently local and/or unquantifiable) or uneconomic - often separate and independent case studies in a country show that corruption in rural health centres is a problem for access, policy-makers might be well advised to react to this finding via inductive conclusion rather than to wait for another 90 case studies to meet a representability criterion.

Given such a unique role in informing policy and planning in these areas, contextual methods need to be of very high quality. And as World Bank chief sociologist Michael Cernea observed with respect to the spread of rapid assessment procedures, such scientific quality is sometimes lacking: “In other words, Rapid Assessment Procedures run the risk of sliding into little more than the quick and unreliable amateurish manner of misgathering social information that they wanted to replace in the first place. It is not an abstract risk: I have seen it at work, wreaking havoc. And I have seen it lurking in the pages of some glossy consultant firms’ field reports, marketed now under the newly fashionable RAP label” (Cernea 1992, p.17).

One criterion for achieving such quality standards in studies built on contextual methods is for them to probe for internal validity through triangulation. Different tools are apt for triangulation, or cross-checking and controlling, if they measure the same construct but do not share the same sources of error variance (Sechrist and Sedani 1995, p. 85). For example, information on ethno-medical beliefs of local populations can be gathered from focus group discussions, open-ended individual conversations, direct observation of health behaviour or key informant interviews with traditional healers. Results from using these tools can then be compared and the degree to which they support each other analysed.

A second quality criterion of contextual studies -- and much harder to achieve -- is replicability. Even simple aggregation or coding of the original raw data is very difficult to confirm independently since they are often based on the researcher’s personal evaluations and interpretations of what respondents answered or how they reacted. While the best quality assurance lies with the selection of experienced social scientists whose interpretations are insight- and meaningful, a growing number of tools exist which allow to cross-check the assessment of researchers and thereby make the replicability of results easier. First, answers (e.g. from focus group discussions) can be recorded, coded and transcribed by several researchers independently. Going even further, multiple coding of answers makes analysis and interpretation with specifically designed software packages possible. Second, while staying within the local context, the quantification of qualitative data can be employed. Many types of qualitative data can, if applied carefully, be quantified in a sensible way, e.g. through explicit scale scores or Likert and Gutman scales. Within the local setting, this can permit an important combination of data that would allow for the statistical probing of the influence of e.g. cultural variables on health utilisation behaviour.” (Hentschel, 1998)

Sinclair & Walker (1999) have developed a formal methodology for collecting, representing, verifying, analysing and retrieving local knowledge in powerful expert systems. This disaggregates sentences or concepts into precise units of knowledge permitting objective comparison (and thus cross verification) of qualitative information that is delivered in normal language statements. It retains the linkages between units of knowledge in a way that permits retrieval of the overall concepts rather than lists of the specific units of knowledge collected. This method is not yet widely used but may have the potential to provide a more objective verification of qualitative ecological information informally collected from local people (Sinclair & Walker 1998). It is also a more satisfactory means of collecting and storing knowledge for possible use in solving problems that are identified after the data collection exercise (i.e. the data becomes less context specific). Note, however, that the knowledge retrieved using the expert system, and the means of retrieval is likely to be more relevant to researchers and development workers than to local people who wish to analyse and seek solutions to their own problems. For development purposes, it is therefore likely to complement PRA and PLA methods.

18 3.4 Anthropological methods Anthropology is the study of human origins, institutions and beliefs. This includes the interaction between people and their environment including the plants and animals used by man. Anthropological work on human use of resources differs from ‘scientific’ work by taking a human perspective. Anthropologists do not often study their own societies and this results in there being two perspectives, emic or etic, from which a society can be studied. Zent (1996) defines these as: “An emic point of view corresponds to the perceptions, nomenclature, classifications, knowledge, beliefs, rules and ethics of the local plant world as defined by a native of the local cultural community.” “An etic perspective denotes the conceptual categories and organisation of the ethnobotanical environment according to the researcher, who is often an alien of the local culture and whose conceptual system ideally derives from the language and rules of science.”

Or perhaps more simply, an emic view describes the world as seen by a local person while an etic one describes the world in terms of Western science. Zent (1996) points out that these are not mutually exclusive but occupy two ends of a continuum and the researcher should employ emic and etic methods whenever they advance the research objectives. The distinction between emic and etic approaches is central to the study of NTFPs especially where this concerns subsistence or traditional use by indigenous communities. Emic approaches are most relevant where a co-learning or participatory study is desired while etic approaches can help to ensure that some objectivity enters into management targets especially where there are etic considerations such as conservation of a particular animal that needs to be accommodated.

3.4.1 Ethnobiology Ethnobiology can be defined as: ‘devoted to the study, in the broadest possible sense, of the complex set of relationships of plants and animals to present and past human societies’ (Berlin 1992). Within this broad scope, plants have received the most attention with ethnobotany as a discipline dating from 1895 when it was described as the study of the interface between aboriginal peoples and the natural world. Over the years the definition and scope of ethnobotany has changed considerably as understanding and respect for traditional knowledge and commercial interest in indigenous knowledge (e.g. bioprospecting for medicinal plants) have increased. There is no generally agreed definition for ethnobotany (Cotton 1996) and indeed texts published in the mid 1990’s give a range of alternative definitions: Ethno – implies that researchers are exploring local people’s perspectives of cultural and scientific knowledge (Martin 1994). Ethnoecology – “all studies which describe local people’s interactions with the natural environment” (Martin 1994). Ethnobotany - “that part of ethnoecology which concerns plants” (Martin 1995), “the study of the relationships between people and plants” (Given & Harris 1994), “all studies which concern the mutual relationships between plants and traditional peoples” (Cotton 1996),

19 “the study of the direct interrelations between humans and plants; including all human societies and all types of interrelations (ecological, evolutionary and symbolic) and recognising the reciprocal and dynamic nature of the relationship between humans and plants” (Alexiades 1996).

From the above it is clear that ethnobotany in particular is both highly relevant to the study of NTFPs and in a state of flux. Ethnobotany in particular appears to be in a process of evolving from a purely descriptive discipline into a more quantifiable science through the acquisition of quantitative sampling methods and statistical hypothesis testing (Alexiades 1996, Phillips 1996). It is also developing an interest in the use of acquired local knowledge for the benefit of local people (Martin 1995) and in the consequences of local actions on the wider environment (Peters 1996c).

Although nearly all the components of ethnobiology are relevant to the study of NTFPs only the few that are directly relevant to the problem of NTFP resource assessment are reviewed here. The many texts on ethnobotany in particular should be consulted for a more complete overview (e.g. Given & Harris 1994, Martin 1994, Cotton 1996, Alexiades 1996).

Ethnobotanists are increasingly finding themselves requested to become involved with resource management recommendations (Cunningham 1996b). This is attributed to renewed interest in promoting the use of NTFPs as a development alternative and because local people’s use of plants are increasingly being taken into account is resource-sharing arrangements in or around conservation areas (Cunningham 1996b). Examples of such management-orientated work on the part of ethnobotanists are; Cunningham & Mbenkum (1993), Elisabetsky (1996), Cunningham (1996a), Wild & Mutebi (1996). Cunningham (1996b) makes the ethical point that researchers have a responsibility to avoid making poorly founded recommendations for multiple-use or commercial harvesting as it may lead to destructive, species- selective harvesting and depletion of wild populations. However, as Peters (1996c) points out this is very difficult to do without ecological information on the species in question which requires quantitative methodology with which ethnobotanists are generally unfamiliar.

3.4.2 Classic ethnobotanical inventory Classic ethnobotany has been concerned with the inventory of the plants used by traditional peoples. In this case inventory should be understood to mean the compilation of lists of the plant species used by different cultural groups (Peters 1996c). Data are also not necessarily quantitative and is defined as “information recorded in many different forms – collections of plants and animals, recorded interviews, laboratory analyses, photographs, market surveys etc.” (Martin 1994). A dataset is also not something that is necessarily susceptible to statistical analysis and is understood to be “a collection of information gathered in a systematic way” (Martin 1994). Systematic in this context should be interpreted as ‘methodical’ or ‘ordered’ rather than anything to do with regularly spaced sample plots. The information itself is gathered from the local people using classic emic anthropological techniques including long sojourn and language learning, various interview methods and direct observation. Scientific naming is of paramount concern and vouchers are taken of all named plants and lodged in herbaria where the researchers often have affiliations. For a description of the methodologies used see Alexiades (1996) and Given & Harris (1994).

The outputs of such studies are sometimes rather disparagingly termed ‘laundry lists’ (Cotton 1996, Zent 1996) as they do little other than document names and uses without any objective indication of the relative importance of the named plant to society. However, these lists are often all that is available and provide a useful overview of the plants used by a local community. The scope of a particular study can range from an exhaustive listing of all plants and uses to those focused on domains of use such as medicinal plants, food plants or for specific life-forms such as trees. Examples of various domains of study are: Medicinal plants; Kulip 1997, Manandhar 1995 Tree products; Papadopulos & Gordon 1997, Edwards 1991, Irvine 1961 All vascular plants used by traditional people; Boom 1989, Boom 1990, Salick 1992

20 All plants used nationally; Abbiw 1990 Regional food plants; Peters et al. 1984 Plants used for craftwork; Cunningham 1987

Published ethnobotanical lists are often used by third party researchers attempting a NTFP assessment or valuation of a forest. For example, Johnston (1998) used ethnobotanical lists to attempt a NTFP interpretation of timber inventories for Guyana.

Classic ethnobotany techniques require a substantial investment in time, often years and are therefore generally beyond the time frame of development projects and assessments. However, there are some initiatives to develop ethnobotanical techniques suitable for use in rapid assessments (e.g. Malhotra et al.1991) but these are not yet well developed.

3.4.3 Quantitative ethnobotany Quantitative ethnobotany is a recent development and is ‘the direct application of quantitative techniques to the analysis of contemporary plant use data’ (Phillips 1996). Since ethnobotany is concerned with the description of plant uses, it is the reduction of folk knowledge to relative use values that has been the focus of methodological development. Use values have been quantified at the folk generic/species level and also as values for a forest as a whole. Quantification provides two advantages over a purely descriptive approach, firstly it permits replication of studies (two researchers will arrive at the same conclusions from the same data) and secondly, it permits statistical hypothesis testing (Phillips 1996). The types of hypotheses that have been examined are relative values e.g. how significant is sp. x , sp. y or community z to people? Quantification is noted as being a plant-centric approach suitable for use in conservation, or pharmaceutical use rather than anthropology (Phillips 1996) though it provides little actual information about the plant itself.

Although this branch of ethnobotany is termed ‘quantitative’ it is not biometrically rigorous as most studies do not undertake any formal sampling, have very few or no replicates and undertake no statistical compilation of analysis of data collected. However, Martin (1994) argues that subjective selection of a few plots is necessary for ethnobotanical work because more scientific ways of locating plots are time- consuming and plots are expensive. He does concede that more scientific rigour is required when setting up PSPs or where assessment is needed of the resource potential of a large area that is proposed as an extractive reserve or protected area (my italics). Likewise Given & Harris (1994) suggest that if maintenance of biodiversity is the objective then there is a need to collect from a diversity of sites and from within these sites in a methodological manner. However, although they list standard objective sampling designs they include biased sampling in the list. The manuals of ecological study techniques for ethnobotanists prepared by Peters (1994, 1996a, 1996c) refer to standard biometric sampling schemes but fail to recognise that contiguous plots cannot be treated as independent observations. It therefore appears that although ethnobotanists recognise situations requiring statistical rigour they are not very conversant with either biometric sampling techniques or their theoretical bases.

There has been some work on the application of statistical analyses to ethnobotanical data. Johnston (1998) used ANOVA analysis to examine differences in the number of species per utilisation category by vegetation type. Without further information on the intensity of harvesting, the degree of demand for particular products or possible substitution within each category it is difficult to see what useful information can result from such analyses.

Species use values Several methods for generating relative use values for a species have been developed but it appears that there is as yet no standardised methodological terminology as Martin (1994), Phillips (1996) and Cotton (1996) use different terms for methods exemplified by the same key papers (see Table 7). See Phillips & Gentry 1993a for a comparison of the three methods summarised in Table 7).

21 Table 7 Methods for quantifying species use values a) Typology of methods Cotton 1996 Martin 1995 Phillips 1996c Examples Preference ranking Relative cultural value Subjective allocation Prance et al. 1987 (total or mean of ranks) Informant indexing Informant consensus Phillips & Gentry 1993 a&b - Uses totalled Salick et al.1995 b) Summary of methods (after Phillips 1996) Method Data required Calculations Subjective Several types of interview Relative importance of each use is subjectively assigned by allocation technique and/or direct the researcher on the basis of his or her assessment of the observation cultural significance of each plant or use Informant Independent interviews of Importance of each use calculated directly from the degree of consensus individual informants concensus in informants responses Uses totalled Interviews, sometimes by Number of uses summed by category of plant use, taxon or direct observation vegetation type. Not very good because, all uses given equal weights and total number of uses may be a function of research effort rather than true significance of plant, vegetation type etc. See entry for papers in Appendix 4 for specifics of methodology

Although generating species use values is touted as being quantitative and plant-centric (Phillips 1996) there are conceptual problems with these types of data. The values are based on the recall of uses for a specific plant by informants on a single day (termed data events) which must be influenced by their mood on that day, though a mean of several events should still rank species in order of relative usability. User group means of informant use values probably reveal more about the distribution and variability of knowledge between members of the group than about the usefulness of the species per se. Also it is assumed that a plant with several uses is more useful than one with a single use and the quantity and regularity and value of collection are ignored. This means that a plant used occasionally as a remedy for several illnesses would rank as more useful than a staple food consumed in quantity for several months of the year but with no other uses. Likewise it is possible to miss NTFPs which are important to only a few members of the community (Schreckenberg pers comm.).

Use value of the forest The basic element in this approach is the delimitation of measured plots in which researchers and local people quantify the number and importance of useful species (Martin 1994). The use values for the species found on the plot are aggregated to yield a plot use value. Martin (1994) notes that determining the use value of measured plots is very costly so only a few can usually be sampled and that they need to be easily accessible. Sometimes the work is reduced by utilising long-term monitoring plots (PSPs) established by ecologists (e.g. Phillips & Gentry 1993a, Edwards 1991, Valkenberg 1997) as this eliminates the need for voucher collection and plant identification. Plots established for an ethnobotanical survey can be used to represent local perspectives using locations chosen with local people (e.g. Peters 1996a, Peters & Hammond 1990), in externally (scientifically) recognised forest types (e.g. Salick 1991) or objectively, for example, at set distances from the village or time since logging (Salick et al.1995). Plots are generally 1 ha in size and derived plot values are often extrapolated across forest types, community lands or even nationally (Peters 1996c).

22 3.4.4 Other anthropological approaches to human-natural resource interactions Ethnobotany is not the only discipline to be concerned with the interaction of human societies on the natural world. Ecological anthropology, cultural geography and human ecology have all developed methodologies for studying human use of the natural world. Zent (1996) suggests that the difference between these approaches and ethnobotany is that ethnobotany is concerned with the investigation of indigenous knowledge of plant uses which basically seeks to describe and understand emic or local views of the natural world. Ecological anthropology uses tools from behavioural anthropology which stresses the sampling of people’s behaviour i.e. looks at what the culture is doing from the outside – an etic or external standpoint. These tools are inherently concerned with systematic sampling of people’s behaviour, quantitative data collection and hypothesis testing through statistical analysis. This in turns leads to a more microscopic and empirical as well as more macroscopic and theoretical understanding of ethnic-botanical relationships. Table 8 illustrates the types of behavioural methodologies that are available. Table 8 Externally lead behavioural research methods (after Zent 1996)

Method General description and Example methodologies Uses of information purpose Spatial distribution Describe and explain spatial Landscape mapping & remote Various descriptive and analysis relationships between sensing analytical operations dealing human and resource Ground mapping with spatial relationships communities Extrapolating resource between human and plant production communities Spatial distribution of resource production and productivity Human activity Record the time spent at Time and motion studies Statistical description and studies various resource-related Time allocation studies analysis of activity patterns of behaviours through a community; necessary systematic observation component of input-output techniques; compare time studies spent at different activities Resource Keep records of resource Dietary survey (weighed Derive measures of the accounting types and amounts procured inventory, dietary recall, food importance of different or utilised by the study frequency, weighted intake) resource species and the community during a given Marketing survey level of exploitation pressure period Ethnopharmacological survey on these resource; necessary component of input-output studies Input-output Cost-benefit type of analysis Rational choice models Describe or explain the analysis of different activities using Optimal foraging analysis interactive relationships time allocation and resource Linear program analysis between populations and accounting data resources

Zent (1996) points out that quantitative resource assessment and spatial mapping are relevant to an understanding of the relationship between human populations and plant resources. Furthermore, Zent proposes activity significance as a behaviour-based approach for quantifying the cultural significance of plants. The activity significance of a plant is defined as the set of all observed behavioural interactions between the human community and the plant and would have some utility as a tool for NTFP analysis but unfortunately Zent does not give any examples of such an index.

Table 8 includes wide-ranging tools many of which would be familiar to a forester, economist and commercial development advisor. The unique perspective of the ecological anthropologist is that although based in the natural sciences it is still the human perspective and use of the environment which is the focus of interest. There are few papers from the field of human ecology in the review principally because the geography/anthropology literature was excluded from the search, not because of any intentional bias but because this study was undertaken from a forestry perspective.

3.5 Economic methods There is considerable interest in the use of NTFPs to develop new industries, markets and export earnings. This has resulted in the economic assessment of the actual and potential contribution of NTFPs to local and macro economies and of studies into the marketing and value addition of NTFPs. There is

23 also the need within wider sustainable forest management to evaluate the costs and benefits of including NTFPs in the management plans.

Econometrics is the science of economic assessment, data collection and analysis and is the corollary of biometrics for the natural sciences and is outside the remit of the present report. However, a brief review of the type of studies that have been discovered during the source of the literature search has been included for completeness and as an introduction to the literature.

3.5.1 Market and income studies Although subsistence use is important there is most interest in the commercial use of NTFPs which is reflected in the large number of paper on markets and trade (see Vance & Thomas 1997, Nepstad & Schwartzman 1992). There is much interest in the use of NTFPs to bolster local economies and to provide export income generating opportunities at a range of scales from small-scale co-operatives to international distributors. However, before a product can be successfully launched on a new market a considerable amount of market research is required to ensure the right product, at the right price in sufficient quantities reaches the market place. At larger scales this can be dealt with by conventional market research methods while at the local scale the manual by Koppell (1995) gives a participatory methodology for small-scale market research. Although such studies are quantitative they are outside the remit of the present study as they generally do not include direct resource assessment.

A different type of market study investigates the patterns and quantities of products in the trading networks. This information is most often used to highlight particular supply problems (Cunningham 1987) or to facilitate an understanding of trade relationships (Falconer 1992b). Both of these studies estimated the amounts of product involved in various enterprises. Cunningham (1987) estimated the quantity of raw material used in items of craftwork and used production records to estimate gross raw material demand. Falconer (1992b) used a range of methods to estimate the quantities of raw material and products circulating in the Ghanaian NTFP trade network which cannot be traced to forest sources nor gross raw material demand. There are strong affinities between such studies and the use of harvest records.

There have been a number of studies of the relationship between local incomes and the use of NTFPs. For example, Townson (1995a) used a questionnaire and interview techniques to investigate the income and livelihoods generated by NTFP enterprises in rural southern Ghana. Cunningham (1990) recorded the palm sap collected daily by one tapper and used this with local prices to estimate the average annual income for a palm tapper. Townson (1995b) provides a bibliography of studies of household incomes generated from NTFPs. Methods used to collect data on incomes should be designed using techniques from the field of econometrics rather than biometrics and are outside the scope of this paper.

3.5.2 Cost-benefit and valuation studies An extensive review was not undertaken of socio-economic valuation studies and related economic analyses. However, formal and informal economic analyses for NTFPs provide quantitative information for use in strategic management decisions and therefore may be of some interest to the inventory designer. Most valuation studies appear to examine the current value4 of a resource to all or a subset of stakeholders (local users, businesses, the nation etc.). Comparative valuation of NTFPs and other uses of the forest, say for timber or agriculture has often been used as a case for forest conservation and sustainable use (see Peters, Gentry & Mendelsohn 1989 for the classic study on Amazonia and Grimes et al 1994 for a study in Ecuador).

It is generally recognised that data on the resource base and its growth is necessary in determining potential extractive value or to analyse cost-benefit under different management regimes. Many valuation studies utilise resource inventory data in their analyses (Pollack et al.1995, Hot Springs Working Group

4 Values assessed under different studies vary but may include direct use values (products and recreational), indirect values (e.g. environmental services) and existence values.

24 1995, Balick & Mendelsohn 1992). However, valuation studies and resource base studies are often undertaken separately although it is clear that both are required for the development of effective systems for the sustainable management of NTFPs (Aglionby & Whiteman 1996). Economic studies are particularly useful in determining the potential for commercialisation (or protection) of the resource from an economic perspective and will identify barriers to such development that are not related to resource availability (May 1990, Godoy et al.1995, Aglionby & Whiteman 1996).

Cost-benefit analysis is potentially a useful tool in demonstrating the economic importance of NTFPs and related livelihoods. The simple project-orientated cost-benefit analysis of developing a copal industry in Papua New Guinea which included translocation of indigenous peoples, building of an airstrip, roads, schools and a health clinic (Zieck 1975) is interesting from an historical perspective and illustrates the type of frontier thinking typical of the colonial approach to forest exploitation. The study by Sharawi (1986) is very different and is a cost-benefit analysis of a scheme intended to increase the value of gum arabic to local women collectors.

There is an extensive literature on valuation and cost-benefit analysis methodologies that remains outside the boundaries of this paper, see Clusener-Godt & Sachs 1994, Wibe 1995 and Guijt & Hinchcliffe 1998 for further reading. In particular, the paper by Godoy et al.1993 is a useful summary of the rigour required of source data for valid valuation studies and is specifically concerned with the valuation of NTFPs.

3.6 Quantitative inventory Quantification means different things to different people. Campbell (1989) describes quantitative ecological inventory as ‘enumeration of individuals and species of trees in a small patch of forest, the measurement of several important parameters of those individuals and the analysis of the abundance and distribution of those individuals as functions of their physical and biotic environments’. This is subtly different from the foresters definition of ‘a sample-based survey of the forest resource’ (Burkhart & Gregoire 1994) because of the emphasis on ecology in the former and on sample based observations in the latter. For the purposes of this study quantitative inventory is defined as a biometrically rigorous enumeration of the abundance and distribution of resource populations.

The review of NTFP assessment revealed a plethora of methodologies with each assessment using an unique assemblage of plots and enumeration techniques. Since NTFPs can be plants or animals it is necessary to review methodologies for each. Although, at first glance these look very different they have the same underlying structure. This structure is envisaged as a hierarchy of design features. At the highest/largest level is the sampling design itself, whether the plots are to be located using random or systematic, stratified or uniform layouts etc. The next level down5 is the plot scale at which decisions about plot dimensions have to be made. Conventionally, the term plot is taken as meaning a measured area on the ground. However, observations at a point are area-less and therefore one-dimensional, also timed observations (e.g. for bird calls) are defined in terms of time rather than area. ‘Plot’ should therefore be understood to be any observational unit for enumerating the target species at the local scale (i.e. over metres and hours). Within each plot the enumeration that is undertaken is dependent on the target and product being investigated. Table 9 illustrates the range of methods used for NTFP assessments.

The range of available methodologies in the plant and zoological sciences that have been utilised in NTFP assessments are relatively limited. There are several reasons for this, including the relatively recent development of NTFP assessment, the nature of the resources that have attracted studies (e.g. the

5 This separation between levels is something of an artefact as there are several plot designs that can be viewed either as a sampling design or as a plot configuration. For example, a line-plot layout can be interpreted as a systematic sample or as a cluster of smaller plots. However, there are statistical implications associated with each of these interpretations. The mean of systematic plots is calculated from all the plots while the mean of clustered plots are determined as the pooled means of each cluster which supports the case for recognising the distinction between design and plot decisions from the start.

25 disproportionate number of studies on fruit) and also the context in which studies have been undertaken. The status of NTFPs in an inventory largely determines how closely methodology is adapted to the peculiarities of the target species and products and the level of resources available. Single resource studies should be best placed to undertake methodological development of specific protocols for assessment of enumeration, but as shown below, this seldom happens. Inclusion of NTFPs into multi- purpose resource inventories places very severe constraints on NTFP methodology though there are opportunities which often are not utilised. Methodological studies of optimal inventory design for a range of plant NTFPs are rare. In contrast, methodology for animal inventory is already well developed and requires application rather than further methodological work (Bibby & Moss 1998).

For the purposes of this study, three contextual settings for NTFP inventory are distinguished. These are single resource, single purpose multiple resource and multi-purpose resource inventories. The distinction between these is the focus of the inventory and the extent to which protocols can be tailored to specifics of the NTFPs in question. Single resource studies are focused exclusively on a particular product and provide the best opportunity for development of tailored protocols and should set the standards for NTFP studies. Single-purpose multi-resource inventories are generally designed to provide management information on NTFPs for a defined area and have as their focus the potential of the land in terms of the species and quantities of NTFPs present and they use land-centric methodology, and differ from multi- purpose inventory in that they are undertaken by one institution within the context of a management structure. Multi-purpose resource inventories (MRI) are often multi-institutional and NTFPs are often a small component of the inventory and consequently the development of protocols is heavily constrained by the need to compromise with the needs of other elements of the inventory. Table 9 Summary of quantitative inventory methods used in reviewed studies a) Sampling design Sampling design Summary NTFP examples from review Author Target Cruise Rapid survey of large area e.g. by air Zieck 1968 Tree (single spp) Census 100% enumeration of small area (e.g. as in Gronow & Safo 1996 All useful plants forestry stock survey) and animals Simple random Selection of plots using random number Salick 1992 Useful plants sampling tables (probability of sampling any plot Smith 1995 Plants equal) Systematic Location of plots on a fixed grid, normally Lund 1998b Tree (single spp) sampling with randomly selected origin for grid. Salo 1993 Mushrooms Acworth et al. 1998 Tree (single spp) Line-plot sampling – Plots located at fixed Cevallos undated Perennial herb distances along a transect line Peham 1996 Saplings Stratified sampling Area divided into strata and sampling Rai & Chauhan 1998 Bamboo undertaken independently in each strata FitzGibbon et al. 1995 Mammals Multi-stage Hierarchy of nested sample plots: sample of Saastamoinen et al. Shrub sampling largest plots selected with further selection 1998 of smaller plots within chosen plots. Sharma & Bhatt 1982 Rattan b) Plot configuration Plot configuration Description NTFP examples from review Author Target Measured plots with Square Munthali & Mughogho 1992 Insect larvae fixed dimensions Rectangular Stockdale 1994 Rattan Circular Cevallos undated Perennial herb 2-D plane at fixed height from ground or Parren et al. 1998 Liana orientated vertically Sheil 1997 Rattan Fixed volume Parren et al. 1998 Liana Plotless sampling Point-centred quarter method Schreckenberg 1996 Trees Lescure et al. 1992 Palms Sample fixed number of individuals closest Singh & Dogra 1996 Shrub to sample point or within sample area Individuals sampled within timed walk from Pinard 1993 Palm house Cluster sampling Systematic group of sub-plots in fixed Serna 1990 Rattan pattern used at each plot location. Point and line Observations are made while standing on White 1994, Bodmer et al. Mammals transects (variable the point or walking along the line. 1994, Bodmer 1995 width transects) Perpendicular distance from point or line to observed individuals measured.

26 Plot configuration Description NTFP examples from review Author Target Silva & Strahl 1991 Birds Line-intercept Observations made of intercepts (tracks, Fragoso 1991 Large transects signs, plant clumps) with a line or plan mammal projected above line. (single spp) DISTANCE Record distance from observation point to Silva & Strahl 1991 Birds sampling target and use of Fourier analysis to estimate target population Strip transects Narrow, very long transects treated as a FitzGibbon et al. 1995 Mammals fixed sample area. Lahm 1993 Game animals Torus Strip arranged around geometric shape Jong & Bonner 1995 Tree (single (square etc. - space inside not enumerated) spp) c) Enumeration method Method Description NTFP examples from review Author Target Presence/absence Record occurrence of target in plot Salick 1991 Useful plants Tally Counts of target individuals in plot Dunn et al. 1994 Useful plants Size measurement Measure size of all individuals in plot Rock 1996 Herb (single spp) Cover Record percentage of plot covered by target species Cevallos Herb (single spp) undated Subjective scores Score features of target into subjective classes Cunningham & Tree bark (single Liebenberg spp) 1998 Mark-recapture Capture individuals, mark, release and re-capture, Runk 1998 Palm fruit use numbers re-captured to estimate population size Indirect / Index Record observable signs of occurrence and use FitzGibbon et al. Mammals methods regression methods to estimate size of target 1995 population.

3.6.1 Single resource inventory The objective of a single resource inventory is the quantification of the abundance and distribution of a single product. Such an inventory is unfettered by considerations of other products or purposes and one would expect methodology to be closely tailored to the characteristics of the species from which the product is derived. However, there are very few single product studies that have quantification of the in- situ resource as an objective. This could be because a NTFP has to be either very valuable, or subject to legislation for it to justify a species-specific inventory. Therefore most species specific studies have been done for species that are traditionally important for export such as rattan. Although there are few true inventories for single species there are a number of studies that use inventory methodology to address resource related questions and it is these which are examined here.

Six reasons for undertaking a single resource inventory were discovered in the review. These are: • to provide knowledge of the effects of exploitation of a species for which no other work has been done, e.g. tree fruit (Shankar et al.1996), palm fibre (Lescure et al.1992), rattan (Stockdale 1994), herb fibre (Cevallos undated), birds (Silva & Strahl 1991), tapir (Fragoso 1991), • to assess the potential of particular products for which increased commercialisation is sought at either the national or local level, e.g. gum copal from Agathis (Zieck 1968), palm products (Sullivan et al.1995, Konstant et al.1995), • to assess the potential of a specific area for exploitation of a known commercial product, e.g. rattans on Barateng Island (Sharma & Bhatt 1982) and in Indonesia (by implication from Siswanto & Soemarna 1988, Siswanto & Soemarna 1990 and Siswanto 1991), • to investigate the spatial distribution of an exploited product, e.g. savanna fruit trees (Schreckenberg 1996), • to provide supporting data for the determination of quotas, this is required for several products under national legislation or international treaty such as CITES (e.g. caiman skins from Venezuela - Velasco et al. 1996, white tailed deer and wild turkey in the USA – Flather et al.1989, Prunus africana bark from Cameroon – Acworth et al.1998, American ginseng roots from the USA – Gagnon 1999b),

27 • for academic inquiry e.g. historical understanding of role of wild yams in historical human diet (Hladick & Dounias 1993).

Only the inventory methodology used by these studies is under consideration here as the biometric quality of the data largely determines the scope and validity of any further analyses or interpretation of the data. Details of the inventory methodology used by the above studies is given in Table 10 There are only 11 studies in Table 10, this highlights the low priority given to the quantification of NTFPs within forests. Most studies are for trees or the traditional tree-like NTFPs (palms and rattans) with only two studies on non-tree-like plants and two for animals. The analysis of biometric rigour could only be undertaken for three studies due to a lack of sufficient detail in reported protocols (Acworth et al.1998, Sharma & Bhatt 1982 and Fragoso 1991). Many of the studies have some inadequacies for the estimation of population densities as most methods were intended for use in between site comparisons6. Other studies are inadequate for resource quantification for a number of reasons including subjective location of plots and use of what amounts to a single plot (see below).

No study documents why particular designs were used though a relatively wide range of methods were employed. It is interesting that two studies use the point centred quarter method which is taken from plant ecology and is little used by foresters. A distance to point method relies on being able to see and identify the nearest target specimen from the centre point which is often not possible in dense tropical forest, both of the studies encountered are for open woodland or parkland environments. Table 10 Inventory methodology used by single resource studies Product type Sampling design Plot configuration Enumeration Author Tree bark Systematic (1%) 50 x 50 m square Diameter of trees > 10 Acworth et al. 1998 cm d Tree exudate Aerial cruise, 2 flights 11 possible locations Visual estimates Zieck 1968 Tree fruit ? 10 m wide transects Diameter of trees > 10 Shankar et al. 1996 up to 1 km long cm d 6 systematic radial line-plot Point centred quarter Diameter for trees > 3 Schreckenberg 1996 transects (plots every 100 m cm and stumps > 50 cm on transect 3 km long) Palm fibre Stratified: Oxisols & podsols: Height measured for all Lescure et al. 1992 Oxisols & podsols: unreported 100 x 50 m stems in plot plot layout rectangular Gleys: line-plot 600 m long, 20 Gleys: point quarter m between plots method Rattans Subjective site selection Single 3 ha (300 x 100 Tally of clumps and Stockdale 1994 m) plot divided into 10 stems x 10 m subplots Multi-stage sampling 3 secondary 1 ha Tally of commercial and Sharma & Bhatt Random selection of 32 from blocks selected from non-commercial culms 1982 123 primary blocks each selected primary per plot block Herb fibre Line-plot transects, unreported Circular 50 m² plots Tally and % cover of Cevallos undated distribution every 10 m. plants in plot Tubers Four sites – unreported plot Transects 4 m x up to Tally of yam stems Hladik & Dounias location of 4-9 transects in 2.5 km long 1993 each Large birds Available trails and tracks 180 variable width Tallies of individuals Silva & Strahl 1991 (haphazard – biased) transects Tapir Randomly located line Line-intercept Indirect (tracks) Fragoso 1991 transects transects River transects

In conclusion, although single resource inventory offers the best opportunity for development of inventory protocols it has not yet produced any real breakthroughs in NTFP quantification for the simple reason that there are very few studies of this type.

6 For example, the radial transect method of Schreckenberg (1996) will provide a good characterisation of village lands but a somewhat inaccurate estimate of overall stocking. While the trail-based study of Silva & Strahl (1991) requires a relaxation of the strict methodology for variable-width transects which could also compromise the accuracy of the results but since number of transects is large (180) can probably be justified on pragmatic grounds.

28 Note that historically, many forests were surveyed and even gazetted for minor forest product exploitation, both to supply export markets and for domestic, subsistence use (Dawkins & Philip 1998). There were many diverse products extracted from these forests, for example, chicle, rubber, brazil nuts, cocoa, freshwater turtles and even river manatee hides were formerly extracted in large quantities from South America, while cola, rubber, oil palm, indigo, shea butter and gum arabic were taken from Africa. Over time many of these products were either substituted with synthetic alternatives or the trees were domesticated and moved into plantations (e.g. cocoa and rubber). Through the later part of the 20th century forest management became increasingly focussed on timber management and minor forest products slipped into obscurity. However, during the early years, although attention was principally on reservation and export promotion there were several resource inventories undertaken for NTFPs e.g. gum copal from Agathis in Papua New Guinea (Zieck 1968) and for Ricinodendron rautanenii in Angola (Coelho 1966). There may be much to learn from an examination of these older studies with regard to methodology and also as baselines from which to compare present resource levels.

3.6.2 Single purpose multi-resource inventory Several studies in the review are intended to provide a range of information on several NTFPs for a single purpose. The studies reviewed under this heading are all intended to provide quantitative information for the purpose of management planning. As such they are area based and attempt to record the presence and abundance of a range of species that occur on a particular portion of land.

In selection timber management the forest is divided into compartments (~ 100 ha – 1 km²). Immediately before logging the compartment is subjected to a stock survey which involves the location, identification, numbering and measurement of every timber tree in the compartment. Yield formulae are used to determine the sustainable yield of timber from the compartment based on the stock survey data. Trees are selected from the stock survey map to make up the allocated yield according to rules designed to protect the environment and the future potential of the forest. Stock survey protocols are generally 100% surveys with the area covered by consecutive enumeration strips. The integration of NTFPs into conventional forest management has resulted in attempts to incorporate NTFPs in timber stock surveys. For example, in Belize, Smith (1995) experimented with a 10% random sample of 1 ha stock survey blocks for a range of products including thatch, edible nuts, palm heart, chicle, incense resin, all spice and decorative epiphytes (Orchids and Bromeliads). Enumeration protocols were developed for each species involved but unfortunately the report does not include results or analyses.

Although it is difficult, in the absence of any data to make a judgement of this methodology, it would seem to be a sound and pragmatic means of discovering the distribution, abundance and NTFP management potential of the area to be logged. The only disadvantage is that non-tree NTFPs may be adversely affected by logging and consequently not be available after logging and the stock surveys would need to be complemented by species specific studies to determine optimal sustainable harvesting strategies for each species. This information could then be used to develop management plans for all resources available in each compartment. For example, densities of a logging-sensitive palm above a threshold established by profitable harvesting returns may indicate that part of a compartment should not be logged but designated as a palm management area. Similar ideas for the inclusion of NTFPs in routine stock survey are also being developed in Ghana (pers obs.).

The principles and protocols for stock survey have also been adopted by a community forestry initiative in Ghana. Detailed information on a range of resources including timber, other plant products and bushmeat has been acquired by the Adwenaase and Namtee communities using techniques derived from those used for timber stock survey (Gronow & Safo 1996). The methodology is a 100% enumeration with the results presented as simple counts of abundance in different land use types. However, measures of abundance are more than adequate to indicate relative abundances and are probably all that are required to guide community management decisions.

As a census this methodology is biometrically sound but there are concerns. No account has been taken of the imperfect detectability of animal signs, small herbs, epiphytes etc. for which careful searches will

29 need to be made. Therefore, simple summaries of census data of this type are likely to be underestimates and may not represent true densities. The lack of replicates means that it is impossible to determine errors and therefore the precision and accuracy of the estimates. Censuses are also as a rule very expensive to operate except over small areas.

Methods derived from PRA techniques have been employed as a diagnostic tool in support of Joint Forest Management (JFM) in India by Poffenberger et al.(1992). The interpretation of this work is confused by the fact that the methods described are of relative abundances based on scoring systems but quadrats and point-centred quarter methods for studying vegetation status and change are also described. The recommendations made by Poffenberger et al.(1992) are sound but are general in nature and do not include specific protocols. Unfortunately, the review was not able to include any examples of assessments undertaken using the manual so it is difficult to judge its efficacy.

A trial of a method designed to permit quantification of key plant resources to support National Park management planning was undertaken in the Bwindi Impenetrable National Park in Uganda (Cunningham 1996a). The design is based on a few small sample plots and uses basic forestry techniques to enumerate the number and size distributions of trees and bamboo. This methodology is intended to provide information to support management decisions but the small number of replicates leads to imprecision and incomplete coverage leads to bias and inaccuracy suggesting that the information is not adequate for detailed planning and is best used as a guide for strategic planning.

Dijk (1999a) describes an interesting study that set out to gain an insight into the abundance and distribution of NTFP plants in forest and non-forest lands in southern Cameroon. The study located 32 plots in seven strata identified from air photo interpretation. The data collected were presented in the form of NTFP stand tables of average plant density grouped by product type and degree of commercialisation. Distribution patterns for each species according to habitat type and topography were also produced. This study is a rare example that attempts to profile NTFP species across a range of land use types as it includes non-forest lands. Falconer (1992a & b) and Townson (1995a & b) demonstrated that it is ‘farmbush’ that provides the main NTFP source in Ghana but there has been little work done to quantify the abundance of this resource. The inventory of trees and NTFPs outside the ‘forest’ or ‘on- farms’ is outside the scope of the present report which focuses on in-forest assessments. This is because a wider range of participatory techniques could be used for on-farm assessments and there is already work underway to document methods for on-farm trees (Gauthier pers comm.).

3.6.3 Multi-purpose resource inventory Many resource assessments for NTFPs take place as a component of a multi-purpose resource inventory (MRI). MRIs have been defined as ‘data collection efforts designed to meet all or part of the information requirements for two or more products, functions (such as timber management and watershed protection) or sectors (such as forestry and agriculture)’ (Lund 1998b). NTFPs originate from forests which generally fall under the jurisdiction of a state forest authority which often have statutory responsibility for maintaining up-to-date forest resource data. Once the forest authority has accepted a responsibility for specific NTFPs they are generally included in routine resource inventory and monitoring. For example, the US Forest Service now includes special forest products as part of forest resource plans in accordance with the National Forest Management Act, the National Environmental Policy Act etc. (Molina et al.1993). Likewise, berry bearing shrubs and mushrooms are included in national forest inventories in Sweden (Eriksson et al.1979), Lithuania (Rutkauskas 1998), Poland (Glowacki 1988) and Finland (Salo 1993). In addition, Lund (1998a) lists further national scale MRI with NTFPs for the Russian Federation. Norway and Turkey. In northern and eastern Europe NTFPs in the form of berries and mushrooms have been recognised and included in recurrent inventory (statutory national inventories usually based around compartments undertaken every 10 years) for almost a hundred years. In Russia industrial scale interest in NTFPs led to the development of a journal (Plant Resources Journal established in 1967) and technical committee (Committee of Wild Berry Research established in 1975) dedicated to plant resources (Rutkauskas 1998). Plant resources of interest to the Eastern Europeans include; berries, medicinal herbs, mushrooms and resins. Unfortunately, the majority of this considerable body of experience and research

30 is unavailable in English (some summaries in Hagan et al.1996) and is little known outside eastern Europe. Notwithstanding the existence of these inventories, Langner (1998) reports insufficient national data and a lack of common methodology for reporting on NTFPs for the European FRA-2000.

In the tropics there are two thrusts to NTFP inventory; that for traditional export products and that for traditional subsistence or small scale products in response to increasing awareness of the social value for NTFP exploitation. Exploitation of traditional products such as bamboo and rattan is intense especially in South-East Asia and this has prompted an increasing interest in resource assessment methodology. Some forest authorities have been enumerating these traditional products for many years e.g. bamboo has been part of the Indian national inventory since 1965 (Rai & Chauhan 1998). However, over-exploitation and increased demand for bamboo and rattans in particular are driving new initiatives for state-level inventory for these products. For example rattans are included in many state-level inventories in India (e.g. Kerala State, Sharma & Bhatt 1982). Bamboo and rattan inventory are also underway in Indonesia, Malaysia, Lao PDR, the Philippines (see Box 1) and Thailand (Stockdale 1995a). There is also increasing interest in national MRI in West Africa (e.g. Wong 1993, Wong 1998). Box 1 Enumerating NTFPs in the Philippine national forest inventory An example of NTFP enumeration from sub-plots is the Philippines MRI which included rattans, palms and bamboo (Serna 1990). Here a national-scale stratified inventory used quite different plot configurations in different regions (presumably, partially as a result of different donor/advisory support). The basic design was cluster sampling on an 8 x 8 km systematic grid. In regions 10 & 11, the clusters were four 20 x 250 m strips arranged on the arms of a swastika 1 km across. In these plots rattans were sampled in a 10 x 10 m sub-plot centred on the plot mid-line at the start and every 100 m along the strips. In all other regions the cluster was a triangular arrangement of 6 Bitterlich point samples at 50 m intervals. In this design rattans were sampled from a 5 m radius plot at the corner points of the triangle. Given the large quantities of data for each configuration it would be interesting to compare their performance in terms of the precision and accuracy of rattan densities.

The increasing interest in the inclusion of NTFPs in forest and protected area management has fuelled the inclusion of NTFPs into routine forest inventory, in effect turning them into MRI. Large-scale MRI including NTFPs have been undertaken in Ghana (see Box 2) and Cross River State in Nigeria (pers obs.). Lund (1998a & b) lists national scale MRIs for Ethiopia, Senegal, Uganda and Mexico but it is not possible, from the available literature, to determine which species these contain or which methods were used. Box 2 Including NTFPs in the Ghana national forest inventory In Ghana NTFPs were enumerated from the whole timber plot (20 x 500 m) and a wider range of life-forms was included (rattans, climbers and herbs). In this case, as plants became less like trees the enumeration methods, due to the absence of botanical survey advice, became increasingly crude. For example, rattan stems and clumps were counted and tallied into juvenile, mature and cut categories while abundance of herbs was represented as a simple tally of clumps. The herb data are unreliable as it is difficult to determine clump boundaries in dense stands and the size of clumps varies widely between species. As a consequence the herb data had to be reduced to presence/absence of the species (Wong 1998). With hindsight % cover or even relative abundance would have been a better measure of quantities.

The information derived from this inventory was intended for use by policy makers and for national and international reporting requirements who required management-orientated interpretations. This was provided in Wong (1998) as tables and graphs illustrating the distribution and abundances of NTFPs across the country. Unfortunately, it seems this type of analysis and presentation of inventory data is relatively rare.

Although Lund et al. (1998) shows that MRI can include many products and sectors including recreation, agriculture etc. it appears that the majority of MRI that include NTFPs are undertaken almost exclusively by forestry staff for a restricted range of purposes, usually; standing timber volumes, NTFP distribution and abundance and plant diversity. In most cases, timber remains the primary purpose of the inventory.

Studies of NTFPs that form part of a MRI are constrained by available field skills (forestry staff are only familiar with tree enumeration techniques), botanical identification skills (Kleinn et al.1996 estimates that only 20 non-familiar species can be accommodated without the assistance of a botanist) and field time or personnel (normally plot enumeration is kept within one day). This means that only limited

31 species and habits can be accommodated. The species to be included are often chosen from those which are best known, traded in large quantities and which maybe experiencing unsustainable harvesting (e.g. as in the Ghana inventory, Falconer 1992a & b) or are established products such as bamboo and rattan.

The most basic quantitative forest inventory is a count of the numbers of individuals of interest in each plot or transect. The plot totals are then used to derive an estimate of the mean density of individuals per unit area. In the case of tree inventory the size of each tree is usually measured at a standard height (1.3 m =breast height). These data are used directly to calculate basal area and through a regression relationship the bole volume or biomass of the tree and hence mean basal area and volume per unit area of the forest. The design, implementation and analyses of data from this type of inventory are well understood and most forestry training includes timber inventory methodology. This has meant that NTFP assessments undertaken by foresters have most often adapted or grafted NTFPs onto conventional timber inventory as is the case for the MRI of Cross River State (pers obs.), Ghana (Bird pers comm.) and the Philippines (Tandug in Stockdale 1995a). The choice of sampling design and plot configuration are therefore determined by the needs of the conventional timber inventory and there is little scope for adapting designs to meet the specific needs of NTFPs. Enumeration of NTFPs is often confined to a limited number of sub-plots with the main concession being that specific features of the plants are enumerated e.g. rattan length, or clump number are recorded.

Although it would be desirable to include a greater range of NTFPs into MRI, there are many groups such as animals, fungi, herbs etc. that are not amenable to simple inclusion in traditional inventory. This is because observation is not possible during normal work; animals take fright if a large group of people approach them and many are crepuscular or nocturnal, are seasonal7, cryptic or difficult to measure or identify. Furthermore the optimum inventory design for single species of trees (rather than all trees) may be very different from a conventional timber inventory (usually systematic with large ~1 ha plots) as they may be highly clumped or very rare. The ideal of separate plots or enumeration teams for different NTFP groups would greatly increase the logistics and cost but synergy between the elements of the MRI should mean that the information effectiveness of the inventory is greatly enhanced.

For any study in tropical forest, access is difficult and time consuming (progress is generally about 1-2 km per day through trackless forest) and difficult, with the cost of cutting lines to locate plots being at least equal to costs of actual enumeration. Access lines are ephemeral and remain open for only a few months but during this time they could potentially be used for a range of observations rather than just the one trip to enumerate the plot. Notably, forestry cut lines could be used to enumerate animals in the forest, with some co-ordination of when various teams were to be given access to the lines. For example, the Ghana forest inventory enumerated more than 3,000 plots on a 2 x 2 km grid at a cost of more than £3 million. Over the seven years of the inventory, more than 5,800 km of cut line were created. At the same time an NTFP study undertook a market-based survey of bushmeat consumption which revealed the significance of animals in the diet of people in southern Ghana (Falconer 1992b). Dickinson (1990), working on a very limited budget, was able to survey 27.8 km (around 0.5%) of inventory cut line for elephants in western Ghana. The results of the survey indicated that forestry cut lines could yield data comparable with purpose made lines. This study, despite its small scale, was able to provide estimates of elephant density in a part of the country that had never been formally surveyed before. Even if a fully developed MRI is not feasible it seems a lost opportunity not to share or make more use of expensive, ephemeral resources such as cut lines. This is a particular loss for animal surveys which are generally under-resourced and rarely funded at the national-scale i.e. as a NTFP rather than for conservation purposes.

In conclusion, it seems that most of the protocols thus far developed for tropical NTFPs are unsatisfactory and require further development. Kleinn et al.(1996) report considerable problems of detectability. They note that small scale clumping and botanical identification confounds the integration

7 Seasonality is a particular problem in MRI which often continue all year, especially for products such as mushrooms which are both seasonal and cryptic.

32 of herbs into conventional forest inventory and conclude that this requires methodological research. There are also few yield tables for particular products available and few tropical MRI have set aside time for yield studies. As a consequence data are reported as simple measures of species or stem numbers rather than yield availability. Analysis and presentation of results to multiple-audiences remains a problem which must be overcome.

3.6.4 Post-hoc use of timber inventory Several single-purpose timber inventories have been given another dimension through a NTFP re- analysis or interpretation of the tree data. Both Johnston (1998) and Valkenberg (1997) used published TSP or PSP and ethnobotanical data to compare use values between families and sites. Johnston’s (1998) use of 2-way ANOVA to test for differences between vegetation type and utilisation categories is perhaps not the most straightforward means of identifying key species for development. It does at least demonstrate that there is useful NTFP data in older timber inventories. Gunatilleke & Gunatilleke (1993) also make use of a prior phytosociological inventory (Gunatilleke & Gunatilleke 1985) to provide summary ecological profiles of NTFP species and detailed descriptions of the ecology of seven important NTFP species. Perhaps the most complete species-level analysis of a timber inventory is the presentation of the ecological profiles of nearly 300 tree species from the forest inventory of southern Ghana (Hawthorne 1995b). This is an exemplary piece of work and provides invaluable information on many NTFP species. It is apparent that single-purpose timber inventories provide useful data on NTFP trees as well as a general impression of the environs in which particular NTFPs are located. As an example of the latter Dickinson (1990) used the Ghana timber inventory to provide a picture of fruiting tree density in areas known to be frequented by elephants.

Perhaps the greatest failing in tropical MRI is that they tend not to include animals. It is well known that bushmeat forms a substantial part of the protein intake of rural and urban people particularly in West Africa (Falconer 1990, Falconer 1992b, Dijk 1998). Animals are generally widely utilised and valued for meat, hides, scent, venom, remedies etc. across the tropics but are nearly always disregarded by the forest authorities that control forests outside protected areas (National Parks etc.). It is surmised that this is because traditional foresters do not have the training, infrastructure or institutional awareness of wildlife, its utilisation or training in appropriate inventory techniques. Furthermore, cross-sectoral linkages with Wildlife Departments are often poor.

3.6.5 Methodological studies The dearth of established methodology for inventory is particularly noticeable for non-tree-like plants principally because they fall through the institutional cracks, e.g. between the Division of Natural Resources (wildlife) and Division of Forestry in Virginia (Bailey pers comm.). Consequently, many of the studies described above have some element of research and methodological development. In addition, there are few studies which are more overtly concerned with methodology and the efficiency of different approaches. Examples of methodological studies for plant NTFP are given in Boxes 3 to 7. Box 3 Developing plot layout and measurement techniques for rattan inventory

Rattans are the subject of a relatively large number of studies (12.6% of reviewed studies, see Table 6 and there is a small group of researchers who have been investigating the relative efficiency of different plot sizes and shapes. Tandug (1978), Siswanto & Soemarna (1988, 1990), Siswanto (1991), Stockdale (1994) and Stockdale & Wright (1996) have all used basically similar techniques to determine optimal plot size and shape for rattan inventory. The technique used is to demarcate areas (ranging from 1 ha to 16 ha) into small (5 x 5 m or 10 x 10 m) square quadrats and to enumerate all rattan stems in the quadrats. The quadrat data is then aggregated to represent plots of different sizes and shapes and the relative efficiency of the different plot configurations compared in terms of accuracy (minimising sampling error) and cost efficiency. This is an efficient means of determining optimal plot dimensions but has a few drawbacks and some significant pitfalls. Although the chosen study site is large it is effectively a single plot so the applicability of the results will depend on the representativeness of the study site which, in the absence of replication is unknowable.

Tandug (1978) measured cost-efficiency of different plot configurations by comparing the sampling error for the number of plots that could be enumerated within three hours in a one ha study area. The sample plots were laid out on a systematic grid to cover the area so that more time was spend travelling between plots as the plots became

33 smaller. The optimal plot size emerged as a 10 x 10 m square plot at a 50% sampling intensity. However, later recommendations of Tandug (1988) suggest using two 10 x 200 m strips arranged in a cross formation at a sampling intensity of between one and three percent. Unfortunately, it was not possible to locate a larger scale application of these recommendations to judge their relative merit.

Identical studies were undertaken in West (Siswanto & Soemarna 1988), Central (Siswanto & Soemarna 1990) and South (Siswanto 1991) Kalimantan. The methodology employed was to sub-divide a 16 ha study area into 10 x 10 m quadrats and to form these into a range of strip and line-plot configurations at a range of sampling intensities from 10 to 25%. and in each case a 10 m wide continuous strip at sampling intensities of 25 or 20%.

Stockdale (1994) and Stockdale & Wright (1996) used a similar technique to that of Tandug (1978) and sub-divided a 1.5 ha (300 x 50 m) study site into 10 x 10 m quadrats. However, there is an significant difference between Stockdale’s work and that of Tandug, Siswanto and Soemarna in that Stockdale’s trial plots are contiguous while the others used non-contiguous plots. Consequently, in Stockdale’s study the variation in sampling efficiency is more a function of spatial pattern in the rattan clumps and their coincidence with plot shape and size than a true test of the efficiency of different plot configurations. Stockdale & Wright (1996) found that strip plots were more efficient that square plots and recommend that 5 m wide strips forming plots of 0.005 to 0.025 ha for enumerating stems per ha.

Nandakumar & Menon (1992) developed a protocol for rattan inventory in Kerala State, India and recommended that 4 x 20 m strips be used in strips 100 m apart to give a 4% sampling intensity. However, they do not report any field work so it is not possible to judge the efficiency of their recommendations.

A similar investigation of optimal plot sizes and shapes in Lao (Evans submitted) arrived at similar plot sizes using 6 replicates randomly located along a transect line. This overcomes the problem of contiguous plots but the level of replication is still not sufficient for work of this kind.

A methodology for estimating the length of rattan stems using a ruler hypsometer was developed (Stockdale 1994, Stockdale & Power 1994). This was tested against various other methods for estimating lengths and was found to be cheap, relatively easy to learn and significantly more accurate than visual estimation, internode counts (as used by Nur Supardi (1993) and clinometer readings.

Box 4 Developing protocols for mushroom monitoring

A team at the USDA Forest Service Pacific Northwest Research Station in Corvallis has been developing methodology to inventory, assess yields and monitor production of edible wild mushrooms since 1993. Their experience and process of development of ideas is very well documented in a series of publications and provides an informative case study of the problems of inventorying non-tree forest products.

The major problems facing the design team is that the target fungi (Masutake, chanterelle and morels) occur as scattered colonies with patchiness at a range of spatial scales as well as being cryptic (largely invisible on the surface) and seasonal. It was recognised from the beginning that the patchy distribution would require the development of novel sampling schemes and analyses (Molina et al.1994). The first attempt at inventory used methods borrowed from fungus diversity surveys in three study forests (Molina et al.1994, Pilz et al.1996a, Hosford et al.1997). In each forest, three locations were selected to represent the three most productive vegetation types within the forest. At each location, three 225 x 225 m (5 ha) study sites were chosen to represent altitudinal, aspect and accessibility variations across the vegetation type giving nine study sites in each of the three study forests. Each site was surrounded by restricted access notices and within each six permanently marked strip plots 2 x 50 m were located systematically on a random orientation. The plots were located during the period when the fungi were not fruiting so as to avoid conscious bias. Mushrooms were enumerated by measuring cap and stem diameters, vertical distance from veil to cap, distance to nearest tree and volume predated. Measured caps were marked to avoid repeat enumeration. The plots were re-surveyed weekly through the fruiting period. After a couple of years experience this method was largely abandoned as it was too expensive and time consuming, the sample area was also found to be far too small to adequately sample any individual species, the plots had been compromised by illegal picking and vandalism, pickers were intimidated and did not harvest the plots normally. In addition off-site weather records did not correlate with yields. After this experience it was decided to change the sampling methodology. Japanese experience suggested that shiro (individual mycelium body or ‘castle’ in Japanese) monitoring would be a useful for Masutake mushrooms (Hosford 1996). However, this methodology is very time consuming and could only be considered for research work and not for routine monitoring. There have been two developments in methodology based on this early experience.

It is proposed that regional monitoring should utilise volunteer enumerators drawn from the local pickers and a proposal to this effect has been circulated (Pilz & Molina 1998). The plan is to use exclusive use agreements as an incentive for volunteering to make detailed harvest records from marked sample plots. Regional systematic stratified sampling based is to be used to select local monitoring sites and the data used to investigate the relationship between forest management and mushroom productivity. Control sites are to be monitored by Forest Service staff.

34 The program is intended to be voluntary and based on flexible, decentralised collaboration encouraging volunteer ownership of the program.

For Matsutake, a mapping approach has been adopted with mushrooms mapped to reference trees which are located using GPS (Pilz & Molina et al. 1996). A cluster of mushrooms is taken to include mushrooms no further than 0.5 m apart and distances between clusters being at least 2 m. The demarcated clusters were assigned to experimental harvest treatments and monitored by Forestry staff with the co-operation of local pickers who keep the surrounding area well picked to discourage opportunistic collectors. The method of selecting reference trees is not given but if this is biometrically acceptable this would appear to be an efficient means of sampling for mushrooms.

The search is still on for a suitable protocol for monitoring mushrooms (Pilz et al.1997, Pilz & Molina in press, Pilz et al. in press). A manual describing present experience and best advice is under preparation (Pilz pers comm.).

Box 5 Trial of local knowledge for inventory stratification for Pacific Yew

Another interesting North American study that contains some lessons for tropical NTFP assessment is the work that has been done in Canada on inventory for Pacific Yew (Taxus brevifolia, bark harvested to manufacture a breast cancer drug) (Jong & Bonner 1995). As a preliminary to large scale inventory a decision needed to be made about which of two available forest maps (an ecosystem map and a forest cover map) would provide the best stratification and whether local knowledge could be used to select which strata should be sampled for yew. A questionnaire was sent to local foresters and ecologists to elicit their knowledge about the occurrence and distribution of yew among the mapped units on each map. The questionnaire data was compiled and used to identify high and low probability strata for yew on each map. Field sampling was weighted so that 80% and 20% of samples were placed in high and low probability strata respectively. Analysis of the data showed that overall estimates of yew populations produced using either map as a basis for stratification were not statistically different but the standard errors for the ecosystem map were much smaller indicating that it is more precise and hence a more efficient stratification. The validity of the high and low yew occurrences strata as determined by the questionnaire was not challenged or tested in the analysis of results. Presumably this is because they were confirmed as accurate. If this is the case then the local knowledge was reliable even though a diverse range of individual opinions on yew distribution were expressed by the questionnaire respondents. This study demonstrates a means of using local knowledge in the context of a biometrically sound sampling scheme that does not compromise its integrity and may offer useful lessons for the use of indigenous knowledge in tropical NTFP inventory.

Box 6 Trying to find Brachystegia saplings The study by Peham (1996) of Brachystegia spp. saplings whose bark is used as a source of weaving fibre inadvertently became a study of sampling problems because the methodology used kept failing to produce reliable results. Initially Peham undertook six transect walks along footpaths enumerating saplings in 5 x 20 m plots every 50 m along the paths. However, this system only located a few individuals so the plot size was increased to 20 x 200 m spaced 200 m apart which still only located five Brachystegia trees. In an effort to locate trees, in the next attempt sampling was directed at known fibre collecting areas. In these areas five cruises were undertaken using 10 x 50 m plots spaced 100 m apart or at changes in vegetation type as identified from air photos. This finally yielded sufficient individuals to derive a reliable mean for the area. However, in the process the sampling design had progressed from something akin to simple systematic sampling along randomly(?) selected footpaths (most likely biased by proximity of footpaths) to stratified sampling using local knowledge and air photo interpretation to direct sampling at high density areas. The apparent frustrations of this study illustrates well the difficulties of sampling low density or clumped species and the temptation of compromising sampling integrity in an effort to locate specimens to study. The use of local knowledge in this study results in biased estimates of sapling densities which should not be extrapolated outside the high density sites so that overall densities cannot be determined. This use of local knowledge differs from the Canadian study (Jong & Bonner 1995) principally because it only looked at high density areas rather than allocating some plots to low probability areas and that the strata areas over which the data could be interpolated was known by Jong & Bonner (1995) while it is not clear if Peham (1996) knew this though the existence of air photos is mentioned. The degree of transparency in the Canadian use of written responses to questionnaires also increases confidence in the results. There is a need to provide some methodological guidance for the use of local knowledge in the choice of sampling strata for inventory of clustered species.

35 Box 7 Lianas – how to inventory them?

Parren et al.(1998) pose the question ‘Lianas – how to inventory them?’ and presents a range of techniques that have been used to enumerate lianas. Unfortunately, Parren et al.(1998) conclude that all extant methods for liana study have problems for inventory and were equally unsatisfactory. The main problems were given as: - identification of the individual – without excavation and tracing of all stems it is difficult to determine the extent of a genetic individual, - although leaf fall data can be used as a estimate of extent it can be difficult to collect, - diameter of stems is not directly related to plant biomass, - counts of stems cutting imaginary planes say at 1.3 m give an overestimate of density as a single stem can loop through such a plane several times, - it is almost impossible to measure length of stems in situ and height of host tree is not related to the length/size/age of liana, - species identification is problematic as leaves and fruit are difficult to collect and few field keys exist. The conclusion of the Parren et al.(1998) review is “what are the most problematic aspects, what problems are very specific for lianas? How can we overcome these?”. Lianas provide many significant NTFPs including rattan, fruits, stems, bark etc. and are an important component of many tropical forests. The lack of established techniques for this important group of plants highlights the problems encountered in inventory of non-tree-like plants.

3.7 Yield assessment For the purposes of this study yield assessment is taken as being the quantification of the amount of a particular product that can be obtained from an area of forest. Estimating the yield of a particular product usually requires the enumeration of certain characteristics of the individuals making up the parent population. Enumerating the quantity of product directly for each individual in the inventory would generally be time consuming, possibly difficult and often cannot be afforded. As a compromise, detailed measurements of product quantity are undertaken for a small sample of individuals and quantity related to some easily measurable feature of individuals enumerated in the general inventory using predictive models such as regression equations.

In the context of NTFPs what constitutes the ‘yield’ is open to interpretation. Total yield is a measure of the biological potential of the species. The useful or commercial yield is that which is available for collection. The distinction between these is often not made and can make a considerable difference to conclusions drawn from a study. For example, Peters, Balick & Anderson (1989) and Peters, Gentry & Mendlesohn (1989) calculated the yield of fruit from oligarchic species in Amazonia disregarding the fact that some species can be up to12 m tall, they then went on to use the figures to argue that the value of forest fruits exceeds that of timber. Phillips (1993) challenged these figures as being unrepresentative and misleading on the grounds that questionable extrapolations were used and that not all fruit on trees and palms that can be more than 12 m tall are accessible to harvesters. Phillips (1993) own study attempted to determine the ‘access-weighted production’ of the trees and discovered that on a per hectare rather than per species basis that the yield of preferred and accessible fruit was between 15 and 25 % of the total edible fruit. The conclusion was that all forms of Amazonian agriculture produce more food that the collection of forest fruits. A later study in Ecuador (Grimes et al 1994) used detailed questioning of local harvesters to obtain tree-by-tree estimates of the quantity of product that can be harvested as the basis for forest valuation.

36 An alternative approach is to consider the economic potential of stands of varying density and accessibility and to use this to define production areas as is done for forest berries in Lithuania (Rutkauskas 1998) while Saastamoinen et al.(1998) report that the collectable yield of berries is about 30% of the biological yield but unfortunately do not give the methodology used.

3.7.1 Product enumeration NTFPs can be just about any part of a plant or animal and each part may require a different measurement technique. It is therefore difficult to anticipate the plethora of techniques which may be used for NTFPs and no attempt is made to catalogue the possible enumeration methodologies. Table 11 illustrates a range of techniques for different products. Table 11 Examples of techniques used for quantifying product yield

Variable Methodology Source Fruit yield Ground level traps. 4 isolated trees selected, 15 1 m² plots randomly located Peters per season beneath crown. Number of intact, predated, immature and mature fruit recorded (1996a) every 7-10 days. Fruit yield Fruit counted in situ on sample trees at frequent (weekly) intervals. Counted fruit left Peters per season in situ and marked with paint to avoid repeat counts. (1990) Fruit, leaves Randomised branch sampling. Branching pattern defined as numbered segments Gregoire et etc. between branching nodes. Path from trunk to branch tip selected using random al. (1995) selection at each node. Fruit/leaf/etc. counts undertaken at distal end of path. Pooled Jessen results from several randomly selected branches is a non-destructive, precise and (1955) statistically reliable method of estimating fruit yield of tree. There are several Nguvulu refinements of method e.g. path selection proportional to size of available segments (1997) at a node, importance sampling etc. Leaves Pipe model. Non-destructive regression technique for estimating leaf biomass and Nygren et al. area from branch cross-sectional area. Pipe model based on observation that 1993 transpiration rate of canopy is proportional to leaf area, sapwood cross-sectional area and conductivity of water transporting tissue. Therefore size of stem is proportional to leaf mass and area. So can estimate leaf mass and area from measurement of stem cross-sectional area (nb needs to be very accurate ~mm). Sample branches selected systematically to represent different branch heights. Regression analysis without constant. Palm leaves All leaves measured. Partially open leaves counted as fraction of open leaf. Leaf Cunningham length measured monthly to track growth. 1988 Palm stem Leaf scars counted at monthly intervals. Stem growth quantified as height increment Olmstead & increment (cm) per leaf scar. Alvarez- Buylla 1995 Palm age Count of leaf scars, assume constant rate of leaf production to give estimates of age Pinard 1993 and numbers of years to reach critical heights. Bulb size Measurement of maximum width of largest leaf on each plant. Regression analysis Rock 1996 performed on a random sample of 50 plants at each site indicated that the largest leaf’s maximum width is strongly correlated to total leaf area. Total leaf area already shown to be an indicator of bulb size. Bamboo Measure clump dimensions on orthogonal axes at ground level, 1 m and full canopy Widmer biomass extent. Map these as concentric ellipses. Determine biomass as volume of cone (1998) projected upwards from the base of the clump. Site index = Σ clump volume / clump density in plot. Site clump area = Σ clump area. Bushmeat Opportunistic records of weights of captured animals in 3 villages used to Lahm (1993) weight supplement animal census.

There are relatively few specific methods for quantifying the amount of product available in the forest and little standardisation of methodology. For example, Table 11 gives three alternative methods for measuring fruit yields. In this case different methods are used to accommodate differences in forest and tree structure and also the objectives of the study. For example, marking and repeat counts is the only alternative for fruit which do not fall when ripe, when it is necessary not to disturb normal predation or it is thought that harvesting may stimulate fruit production or ripening (as is the case for Hamelia patens, Zurovchak 1997). Conversely, randomised branch sampling can only be done where all branches are accessible from the ground while the use of litter traps, although inaccurate, is the only alternative for inaccessible and inconspicuous fruit. The requirements of legislation, controls and external monitoring can also have an impact on quantification needs. For example, rattan in India needs to be quantified in terms of dry weight and the number of billets of standard length (Sharma & Bhatt 1982) as it is the dry weight of rattan that is used for permits. In Indonesia rattan is quantified in length (Stockdale & Power 1994) or number of commercial lengths (Stockdale 1994).

37 Where trees are clearly owned by harvesters there is always the possibility of requesting that they count ripening fruit. This is a simple and effective technique and has been used to good effect in farmlands (Schreckenberg 1996) and in the forest (Shanley in prep.).

The choice of measurement technique is therefore determined by the type of product, the characteristics of the source population, pragmatism and the objectives of the study. Therefore it is very difficult to be prescriptive even for the most commonly studied NTFPs.

Sampling schemes for product yield Although there are a plethora of possible techniques for measuring the yield of NTFPs there are a relatively restricted set of sampling schema in which the measurements take place. Enumerating all individuals sampled in an inventory for product yield is generally not an option due to cost, time constraints and difficulty. Consequently sub-sampling for detailed measurements of yield on a smaller number of individuals is usually employed.

Product yield sampling, independent of the main inventory is termed double sampling and can use a range of different designs. Double sampling is perhaps the norm for estimating yields of NTFPs. The results of the yield study are generally formed into models describing yields against size. The models are applied to the inventory data to provide bulked up estimates of total yield per unit area. The only constraints on double sampling are that it needs to be statistically sound and have some predictive variable in common with the main inventory, ideally it should also have a similar spatial distribution to the main inventory though this is often not practical. Examples of double sampling for NTFP yield are the survey of bark thickness for Prunus which was independent of the main inventory (Acworth et al.1998), animal inventories which use data of bodyweights derived from harvest records or secondary sources (Lahm 1993, FitzGibbon et al.1995) and berry yields measured on research plots and applied to static inventory in Finland (Raatikainen et al.1984).

Yield sampling that takes place alongside the main inventory but utilises sub-samples to reduce the work involved is a type of multi-stage sampling. In this case the yield sampling uses the same design and plots as the main inventory but only a sub-sample of individuals is measured in detail i.e. there is a multi-level, hierarchical structure to the overall sampling design. This type of structure has the advantage of distributing the yield sample evenly across the area being sampled which means site-specific yield estimation is possible. The disadvantage is that detailed measurements may not be possible due to constraints such as restricted mobility of equipment. Without adequate testing or supervision it may also be that insufficient samples will be obtained to permit adequate replication in rarer size classes e.g. larger sized trees may become very rare but contribute disproportionately to yield. In this case it may be necessary to augment the sample with additional observations in deficient size classes in order to obtain adequate replication for statistical analysis. If this type of problem is known to occur then double sampling would be more appropriate. The data derived from multi-stage sampling can be employed to give both general yield models or site-specific conversion factors. The latter is an advantage where site type is known to vary within the study area and have an influence on yield. For example, green volume to dry weight conversion factors will vary with soil type and conditions on the day so it would be best to derive a conversion factor for each plot as it is being sampled (e.g. as in Sharma & Bhatt 1982, see Box 8). The practicalities of measurement also influence sampling decisions. For example, oven drying samples may be difficult to arrange so sampling for dry weights only takes place in areas with high densities to ensure that sufficient samples can be obtained in a short period and processed at the same time (e.g. yams, Hladik & Dounias 1993).

38 Box 8 Multi-stage bamboo enumeration protocol

Clumping species: three levels of sampling Whole plot – all clumps counted N-W quadrant (1/4 of plot) clump diameters measured 1 in 8 clumps – culm number, age, soundness, size, condition, average culm height and quality recorded

Non-clumping species 1/8 plot – condition, age, average height, total number of culms etc. recorded

Utilisable green to dry weight relationship 1 mature culm from each culm diameter class cut from the first clump in each plot. Length is measured 25 cm from ground to 1 cm diameter. Whole culm weighted in field and 30 cm section taken from bottom, middle and top of cut culm for determination of dry weight. (Rai & Chauhan 1998)

A common feature of the NTFP studies reviewed is their relatively small scale. It is notable that fruit production in ethnobotanical studies (e.g. Peters 1990, 1991, Peters & Hammond 1990 and Phillips 1993) use relatively low numbers of replicates both of ground level traps per tree and of sample trees. Often these studies only use one or two trees per size class and only have 8 –15 litter traps per tree with perhaps 8 sample trees in all. Such designs can, at best only provide a guide to the magnitude of the crop and are not adequate for extrapolation beyond the immediate study area. Studies undertaken for management purposes have a sounder biometrical basis e.g. 200 trees were sampled for bark thickness in Cameroon (Acworth et al.1998). Autoecological studies are also characterised by large number of observations e.g. Piñero & Sarukán (1982) sample 414 trees distributed among two replicates in three sites.

Extrapolation of yields There are several methods for applying the results of a yield study to the data from an inventory of population densities to give gross product yield for the study area. The simplest is to derive a single conversion factor, usually the mean amount per individual and to multiply this by the estimated total number of individuals in the population. Refinements would be to only consider accessible individuals or only those of a commercial size. This type of approach is best used when the product amount is not related to the size of the individual or size does not vary very much. Examples of simple conversion factors are those for bushmeat biomass where single average bodyweights for each species are applied to the whole population (Lahm 1993).

Where yield of an individual is strongly related to size (e.g. for products derived from large trees, palms etc) some means of estimating yield as a function of size is generally used. At its simplest this can mean tallying individuals into size classes with a conversion factor for each class. More sophisticated methods use regression equations that relate yield to some easily measurable indicator of size, such as diameter at breast height for trees. A straightforward example of the calculations involved using a simple linear regression is the method used to estimate bark weight by Jong & Bonner (1995) for Pacific Yew.

Calculation of bark yield per tree (Jong & Bonner 1995) Assume tree bole is conical. Bark area calculated as surface area of cone. Bark volume = area x thickness. Thickness (cm) = 0.2 + (0.005 d), where d is diameter at breast height in cm. Bark weight = volume x 0.4 (dry weight / green volume conversion factor). With more data and longer studies it is possible to increase the sophistication of the models used to estimate yield. Yield prediction models for NTFPs have been most fully developed for berry yields in northern and eastern Europe. Here long term studies based around long-term recurrent forest inventory or growth and yield plots (PSPs) have permitted the development of multiple regression models to predict areal yields from site and climate variables (see Saastamoinen et al.1998, Glowacki 1988, Grochowski &

39 Ostalski 1981, Raatikainen et al.1984, Salo 1993). An example of the use of multiple-regression models is the system devised for estimation of berry yields for central Finland is given in Box 9). Box 9 Forecast system and inventory of wild berry yields for Finland

Saastamoinen et al. (1998) and Salo (1999) describe what is termed the Marsi Enquiry which is a volunteer-based national berry prouction monitoring system. Berries = cowberry (Vaccinium vitis-idaea), bilberry (Vaccinium myrtillus) and cloudberry (Rubus chamaemorus) Yields of target species are observed in 1110 permanent experimental plots in 57 municipalities across the country. In each compartment five plots of 1 m³ for berry yield were located in suitable vegetation types or where shrubs occurred and permanently marked. Enumeration Berries – species, count of flowers, raw and ripe berries. Site characters – timing of flowering and ripening, type of growing site, proportions of tree species, development class of trees. Sites visited several times throughout the flowering and fruiting seasons. Modelling Models are yet to be developed as there are insufficient years of observation to characterise annual yield variability. [Previous models for Finland (Raatikainen et al. 1984) are: V. vitis-idaea ∝ vegetation type, shrub cover, shrub height, stand age class, crown density and weather conditions V. myrtillus ∝ vegetation type, stand age class, tree crown density, method and degree of coppice control and weather conditions.] Dissemination Information sent in electronic form to Joensuu Research Station where it was processed using the MASI (=Berry and mushroom system) and presented as theme maps. These maps are intended to inform the berry pickers about the time of flowering and the development of raw and ripe berries across Finland. The maps and notes describe the kind of sites on which the main yields were to occur and the level of yield for each species during 1997. Maps were distributed to media as five situation reports and were cited widely by press, radio and appeared as part of evening news and morning television broadcasts.

Although the system described in Box 9 is perhaps too complex and costly for use in the tropics there are several features of this system which are relevant. Berries are fruit and as such have high variability in yield from year to year which is reflected in the Finnish yield models by the inclusion of weather conditions and the reluctance to develop yield models without sufficient observations of good, medium and poor yields. Although high annual variability in tropical fruit has been repeatedly observed (Peters 1994, 1996a, Shanley in prep.) this has not as yet been accommodated in any yield functions for tropical species. Indeed most models are simple in the extreme and predict fruit yield solely on the basis of tree size and data for a single season (e.g. Peters et al.1989, Peters & Hammond 1990, Peters 1990, Peters 1996b, Phillips 1993). Ideally studies of yield of ephemeral products such as fruit, leaves or offspring should be undertaken over a number of seasons and include some measure of site quality and antecedent and concurrent climate, especially rainfall. Such yield forecast models are well developed and familiar to agronomists. Appropriation of some of these methodologies for NTFPs could greatly enhance the prediction and explanation of NTFP yields.

3.8 Growth and productivity studies In order for management to be considered sustainable it needs to be based on reliable data covering the dynamics of the target species. The ideal would be to have data on population dynamics (recruitment, mortality, migration etc.), the growth rates and patterns of individuals in the population and a measure of productivity for the product being harvested. Peters (1994, 1996a) stresses the importance of considering the impacts of harvesting on the life-cycle of the species under consideration over long time periods. The short time frame of most tropical NTFP studies has mitigated against long-term work and most reviewed growth and productivity studies are research orientated, local in scale and of short duration. There are relatively few methodologies for determining the dynamics and growth of NTFPs, despite their diverse nature. This is because methodology has been largely borrowed from forestry and, as such, is most

40 suitable for trees and perennial plants. Measuring animal productivity in the wild can only be carried out indirectly using life table data derived from captured animals. Direct measurements on captive animals is possible, but it is difficult to ensure that conditions, especially foodstuff, are comparable to those in the forest. The growth and productivity methods discovered in the review are briefly described below.

3.8.1 Permanent sample plot methods The conventional means of determining productivity of timber is the establishment of permanent sample plots (PSPs), in which the individual trees are tagged, mapped, identified and measured for size (diameter) at fixed points (breast height, marked by paint) at periodic intervals (2-5 years) over long periods of time (> 15 years) (see Alder & Synott 1992). Such methods are ideally suited to long-lived trees being managed for timber which accumulates very slowly (e.g. mm per year). The objective of the PSP protocol is the quantification of as many life stages of the target species as possible. In timber PSPs phenology, seed, seedling and sapling dynamics are often omitted because of the long intervals between enumerations and also because it is the growth performance of established trees that is the primary concern.

A search of the TROPIS database (Vanclay pers comm., output in Appendix 6) which contains records of 13,000 forestry-style PSP, plots revealed 244 plots where NTFP enumeration was mentioned. These are spread across nine studies in seven countries (Cameroon, China, Colombia, Malaysia, Nepal, Singapore and Uganda). Only one of these is included in this review; that by Phillips (1993) in Peru. Several involve plots where everything is recorded and are not specifically concerned with NTFP productivity (e.g. Malaysian 50 ha plots). However, it was not possible to find out more about the studies in Nepal, China and Uganda for this review.

Several studies have adapted tree PSP protocols for use with NTFPs. Most NTFP studies are more concerned with phenology (especially fruit and seed yields), and early establishment and are less interested in adult growth rates. This is reflected in the inclusion of phenological observations in the protocols and the use of very short observation periods (a week is not uncommon) to capture fruit dynamics. Notable among the NTFP orientated PSP studies are those concerned with fruit production in neotropical trees, shrubs and palms. Although the protocols used in these studies vary (see Appendix 4) they have the same basic structure, summarised in Box 10. These protocols are becoming something of a standard for fruit production and have been employed by Phillips (1993), Zea (pers comm.) and Olmsted & Alvarez-Buylla (1995). The majority of these studies have been undertaken on oligarchic species with the plots generally containing monospecific stands of the target species. In these studies it is likely that there is little other than the target species to enumerate. In the case of Shorea atrinervosa (Peters 1996b), which does not form monospecific stands, it seems that only Shorea trees were measured. Current practice in forestry PSPs is to measure all trees within the plot, regardless of species. This is because it has been found that older protocols that only considered ‘timber’ trees (e.g. using the ‘leading desirable’ concept) are difficult to analyse and tended to omit species destined to become timber trees in the future (Alder 1995). In order to provide the context for performance of the NTFP tree it is valuable to map and record the species, diameter and growth of all trees in the plot.

41 Box 10 PSP protocols used for fruit production

Target species: oligarchic species in monospecific stands Sampling design: single plot subjectively located in dense stands of target species Plot configuration: arrangement of 20 x 20 m contiguous subplots into a 1 ha square or rectangle Enumeration: Adult trees tagged, mapped and measured for diameter and height Seedlings counted in a number of random 1 m² quadrats within main plot and measured for height Phenology – direct observations of small numbers of tagged trees spread across size range at frequent (weekly) intervals Fruit – several protocols including fruit marking in situ and ground level traps (see Table 11), observations repeated at frequent intervals (weekly). Study period: one to two year study (though the intention is that several will be longer term studies). (Peters et al. 1989, Peters 1990, Peters & Hammond 1990, Peters 1996b)

PSPs can also be used to assess the growth of non-tree species, such as the study of rattan growth by Valkenberg (1997). This study used PSPs that had already been established for an ecological study of forest gradients, so the plots were arranged as topo-sequences from ridge-top to valley-floor. In each plot, all rattan plants with stems longer than 50 cm were identified, tagged and stems tallied into four growth stages (sucker, juvenile, immature and mature). Growth was recorded every 12 months for a period of two years and defined as the passage of stems from one growth stage to the next, rather than as actual height increment which is difficult to measure directly.

Double sampling and multi-stage sampling are often employed in PSP studies because of cost and time constraints. Nested sub-plots (= multi-stage design) are often used for seedlings and saplings while phenological observations are made on a sample of adult trees. The small size of plots sometimes means that there are insufficient adults for phenological observations and in these cases the sample of adults can be augmented from outside the study plot (=double sampling).

An example of a long term autecological study of a single palm species (Astrocaryum mexicanum) (not a NTFP) used data from biannual observations over seven years and recorded mortality at all stages (e.g. fruit predation by squirrels on the tree) with large numbers of replicates (e.g. 50 palms sampled for biomass) on three sites (Piñero & Sarukán 1982, Piñero et al.1982, Piñero et al.1984). Likewise, the smaller scale non-NTFP study by Oyama (1990) of growth and reproduction of a Mexican dioecious palm (Chamaedorea tepejilote) recorded data from four years worth of biannual observations on three sites. There is much that NTFP researchers can learn from the work of plant population biologists concerning the quantification of the life cycle of NTFP plants.

3.8.2 Experimental harvests The objective of many NTFP studies is the determination of the impact of harvesting intensity and technique on the productivity and dynamics of the exploited population. The most direct way of addressing this problem is to undertake experimental harvests and to compare the productivity of different treatments with unexploited controls. This experimental approach is popular especially for heavily exploited commercial products, and has been employed for a range of species e.g. a vernal bulb (Rock 1996), rattans (Valkenberg 1997, Ros-Tonen et al. 1998), palms (O’Brien & Kinnard 1996, Gómez 1998) and a herb (Cevallos undated). The design of harvesting studies should follow standard procedures for experimental studies and include adequate replication of treatments and a control. Most of these studies use purpose-made protocols and are often only interested in measuring the target species.

3.8.3 Observations at paired sites PSP-style plots can also be used as a basis for experiments such as harvesting studies on paired sites. Often one site is subject to normal harvesting whilst the other, matched for vegetation and topography etc. is an unharvested control. These studies differ from experimental set-ups because the level and type of harvesting is not under the control of the researchers, but left open for ‘normal’ exploitation by local

42 people. These studies, therefore, offer a better view of reality, but are not ideal for determining the best management practices, as often the actual management ‘regime’ being imposed may be undetermined and novel practices cannot be evaluated. Examples of paired studies in the review (see Appendix 4) are summarised in Table 12. Table 12 Productivity studies undertaken on paired study sites

Author Product Sites Sampling Replicates Duration design Waters et al.. Truffles Two sites representing old Systematic 4 plots at each site 2 years 1997 growth & Mature plantation Olmstead & Palm leaves Four sites representing Subjective No replication, 1 2 years Alvarez-Buylla harvested and unharvested plot per site 1995 secondary forest Runk 1998 Palm leaves Three management regimes Subjective No replication, 1 1 year and seeds stratified by degree of plot per site inundation Konstant et al. Palm Two sites representing high Systematic 10 plots at each Not 1995 & Sullivan and low human and site reported et al. 1995 livestock densities

The advantage of studies of this type is that they permit statistical testing of differences between management regimes. However, for differences to be convincing they need to be observed over a period of time and need to be adequately replicated.

3.8.4 Individual-based observations of growth rates Cunningham (1988) used PSP-type method to directly record the productivity of marked palms in the palmvelds of southern Africa. In Cunningham’s (1988) study, two high palm density areas of veld, where commercial harvesting was likely, were selected on the basis of ease of access and relocation. At each site, a number of palms were marked for study (16 and 32 respectively). Leaf lengths on each palm was measured monthly for an unspecified period of time and growth calculated as the annual production of new leaves for palms grouped into 3 size classes, defined on the basis of leaf length. Pinard (1993) used a similar systems for palm leaf productivity in Brazil.

Freeing the selection of sampled individuals from the constraints of plot-based methods has a number of advantages and disadvantages. One advantage is that it facilitates the rapid identification of pre- determined numbers of trees. Another is that there is no need to permanently mark plots. The disadvantages are that there will be no detailed information on the context of the specimens in terms of competing vegetation, and sampling of this type is often opportunistic and therefore is not done according to biometric principles.

On balance, observations of this type on plants are best suited to environments where the target species is either; widely scattered, easily observed or in a matrix where inter-vegetation interactions are not of great concern, as an explanatory variable, as is perhaps the case in a farmbush situation. It is also useful as a low-cost and straightforward means of obtaining information on growth. The mechanisms used to select the sample trees are critical in determining the discriminatory power of any tests on the data. The ideal would be random selection of specimens, perhaps in strata defined according to size, which could be achieved through list sampling (all available specimens would need to be listed) or through selection of specimens closest to random points, which converges with point-centre and nearest neighbour methods.

Direct observations of animals generally use methodology based on observations of individually selected, marked individuals. Because of the difficulties of marking and re-capturing animals for repeat measurements of size over longer periods of time growth of individuals in the wild is not often attempted.

43 3.9 Determining sustainable harvest levels Sustainable management of forest products, timber as well as NTFPs is an objective of most who involve themselves with resource management. Sustainability is a complex concept that has many interpretations. Hall & Bawa (1993) make the following definition of sustainable NTFP extraction: “In ecological terms, extraction is considered sustainable if the harvest has no long term deleterious effect on the reproduction and regeneration of populations being harvested in comparison to equivalent non-harvested natural populations. Furthermore, sustainable harvest should have no discernible adverse effect on other species in the community, or on ecosystem structure and function.” This definition encapsulates most of the ideals of sustainability, but as pointed out by Boot & Gullison (1995) is unrealistic in its demands. Given the closely interwoven nature of natural forests it is virtually impossible to remove anything without creating noticeable changes, especially if a life cycle approach to assessment of change is taken (Peters 1994, 1996a). Boot & Gullison (1995) suggest that a more pragmatic indicator of sustainability would be to require that there is no loss in species and no irreversible changes in ecosystem processes.

In practical terms the ideals of sustainability are translated into certain principles. A central premise used to determine the allowable harvest level is that harvest quotas for wild populations should not exceed a level that can be supplied by the population in perpetuity without damaging its vitality. Through analogy with natural forest management this is often taken as meaning that annual harvests should be constant and available in perpetuity. However, foresters deliberately manage the forest for sustainable yields by making adjustments to the extent and intensity of cutting and constant supplies are an artefact of the management regime. Trees are long-lived and slow-growing so growth variation from year to year is averaged over long periods giving an illusion of constant, invariable productivity. For many NTFPs, extensive, highly regulated management is not the norm and the productivity of ephemeral products is highly variable from year to year. Consequently, the concept of constant annual yields is inappropriate. Indeed, defining a ‘sustainable harvest’ for many NTFPs requires innovative interpretations of detailed ecological knowledge supported by novel methodologies for studies of productivity and its successful exploitation. However, the point often made that extraction rates must be linked to productivity and inventory data (Peters 1990, 1991, 1994, 1996a, Hall & Bawa 1993, Gould et al. 1998, Shanker et al. 1996), has resulted in only a few methodological developments. The approaches that have been employed to judge the sustainability of exploitation in the reviewed NTFP studies are briefly described and discussed with regard to the issues raised here.

Many NTFP studies use simple matrix models of population dynamics to assess the sustainability of present harvesting levels (Robinson & Redford 1991b) or to determine harvest levels (e.g. Peters 1990). Simpler methods use ‘thumb rules’ as a guide against which the sustainability of a prescribed cut is judged (Branney 1994b).

Both of these approaches judge sustainability in terms of the dynamics of the exploited population. However, Boot & Gullison (1995) point out demographic models can only identify the upper biological bounds of sustainable harvests, while the selection of an appropriate harvest also depends on economic returns and the impacts on the ecosystem. Many studies have combined resource-based assessments with socio-economic surveys (e.g. Fa et al. 1994, Silva & Strahl 1991, Cunningham 1998, Munthali & Mughogho 1992, Lund 1998), but most of these have focused on examining harvesting practices or estimating revenues and very few have used socio-economic data or models to determine the level of commercially sustainable harvests. Unfortunately, the one study that appears to have addressed this problem (Grossmann 1998) is not yet completed, so the methodology used is not available.

The northern and eastern European work on berry production is perhaps the best basis for determining sustainability, especially when combined with the delineation of production areas as in Lithuania (Rutakauskas 1998). However, this work has apparently not been used to set harvesting quotas as present exploitation is so far short of the available yield that harvest restrictions are not required (e.g. 5-10% of

44 biological yield of berries collected in Finland –Saastamoinen et al.1998). The study by Bodmer et al.(1994) also examined economic aspects of implementing sustainable hunting, but considered the cost of implementing sustainable management rather than determining optimal harvesting levels.

Work by Gould et al.(1998) attempted to address the feasibility and cost of instituting sustainable management for dye trees for a certified export product (Gatherings™ pot pouri). Gould et al.(1998) envisage a methodology for determining sustainable harvests using eight steps: (1) delineate the current supply area [proposed forest concession], (2) determine current supply [from previous inventories and interviews], (3) estimate growth and yield of target species [assumed growth=0 because of a lack of data], (4) determine current demand [factory records], (5) compare short-term supply and demand and evaluate management options, (6) assess secondary ecological effects, (7) repeat process for future time periods, (8) summarise results. Disappointingly, they were not able to apply their method because of severe data limitations (they only had crude density estimates derived from small-scale forest inventory).

3.9.1 Rapid vulnerability assessment This is a method developed by Cunningham (1987, 1991, 1994, 1996) and formalised by Wild & Mutebi (1996). Rapid vulnerability assessment (RVA) was developed as a protocol for collecting available knowledge, indigenous as well as scientific, about a resource species and does not itself generate any new data. The method requires the integration of indigenous information and scientific data and depends on being able to match folk and scientific names to form the link between the two bodies of information. The collated information is used to identify species, resources or sites that may be vulnerable to over- exploitation. The method has been successfully used to make recommendations of the suitability of resources and species for sustainable use (Watts et al.1996). The assessment of sustainability commences with the completion of a set of standardised field sheets for each species, which is then used to collect the following information about a species: life form, habitat specificity, abundance and distribution, growth rate, response to harvesting, parts used, pattern of selection and use, demand, seasonal harvesting, traditional conservation practices, commercialisation and substitutes. A standard summary sheet is prepared and the information evaluated according to a set of criteria of sustainability (see Table 13 for example criteria) drawn from ecology, socio-economics and economics. On the basis of the assessment, each species is assigned to one of eight management categories; Mentioned, Demanded, Outside forest, Utilisation, Non-utilisation, Monitoring (minimal, moderate or maximal), Research or Substitution. Appropriate management actions are recommended for each category.

45 Table 13 Criteria used in Rapid Vulnerability Assessment Criteria Potential for sustainable use Low High Ecology Low abundance High abundance Slow growth Fast growth Slow reproduction Fast reproduction Sexual reproduction only Vegetative reproduction Habitat-specific Habitat non-specific High habitat diversity Low habitat diversity High life form diversity Low life form diversity Life form Use of grasses an forbs is likely to be more sustainable than trees Parts used The use of leaves/fruit/stem is more sustainable than of the roots (if damaging) or the whole plant Method of harvesting Potential for sustainable harvesting is higher if size/age classes are not selected Table taken from Watts et al. 1996

The information required for RVA is comprehensive and provides a systematic checklist for collating and integrating information from a wide range of sources. However, the assessment is only as good as the information available which is often lacking. RVA does not include any protocols for inventory as the method is intended to be a rapid first assessment of the species. However, Wild & Mutebi (1996) recommend that inventory is carried out, once time and funding become available.

As described, the integration of the information to determine management categories is non-quantitative and therefore subject to some degree of interpretation and subjectivity. This is not a serious problem as the information is available for re-assessment, modification and up-dating. However, to guide less experienced assessors it should be possible to develop a scoring system for each criteria and simple, transparent means for combining criteria into management categories.

3.9.2 Periodic harvest adjustments Peters (1994, 1996a) propose that sustainability of tree fruit production can be ensured through a process of periodic harvest adjustments (see Box 11 and Figures 1 & 2). This is a simple and attractive method that integrates harvesting impacts by monitoring the health of regeneration. Unfortunately, the reasoning suffers from several flaws. Firstly, how can one be certain that the initial regeneration density used is a suitable threshold value for judging sustainability. As Peters (1994, 1996a) notes, fruit production is notoriously variable from year, so the threshold value set from only one years data may in fact represent a mast year and give the possibly erroneous impression that harvesting in most years is unsustainable. Secondly, there is no indication of how the initial harvesting level is determined. Presumably, the methodology intends that a pre-project harvest level is continued with adjustments made if necessary. Thirdly, the method depends on an implicit assumption that productivity rates will remain stable over long time periods, i.e. annual yields will be the same at five yearly observation intervals. This may not be the case as there are periodic fluctuations in productivity across several temporal scales in the tropics (e.g. the El Niño). Box 11 Harvest adjustment method for assessing sustainable yield from trees

Regeneration survey. Network of permanent, small (5x5 or 10x10 m) regeneration plots. Total number of desired seedlings and saplings of the required species less than minimum diameter for inventory tallied into four size classes and recorded. These data represent the threshold values by which sustainability is measured. These plots are enumerated at five year intervals. If at a subsequent enumeration seedling or sapling density drops below the threshold value the harvest intensity is reduced. If levels rise then harvesting levels can be increased. Successive approximations are used to try and stabilise seedling and sapling densities preferably at the original threshold level. Harvest assessments. Visual appraisals of the behaviour and condition of adult trees conducted along with harvesting activities. During routine harvests the health, flower and seed abundance and harvesting impacts are recorded for marked trees in yield plots. Information collated and tracked for the individual trees. If specific problems are identified, e.g. loss in vigour, increased seed predation, drop in productivity etc. this should also initiate harvest adjustments. (Peters 1994, 1996a) 46 A more realistic methodology for using successive approximations to arrive at a sustainable harvesting level would be to firstly determine the magnitude and patterns of year-to-year variability in productivity. This would require annual observations of fruit production over a number of consecutive years and complimentary records of climate variable such as rainfall. This data could provide the basis for forecast models of fruit production, such as those developed in Scandanavia (see Box 9). Harvest levels could be set in relation to either long-term yields, to maintain the population into the future, a fraction of the forecast annual yield etc.. Perhaps more important that being able to set a harvesting level is the ability to forecast the current years harvests so people can make considered choices of whether to harvest and make the necessary preparations (Belonogova 1988). Monitoring of species and ecosystem health would be a useful tool to assess whether impact levels were satisfactory, judged against some criteria of acceptability.

3.9.3 Matrix models Peters (1994, 1996a) notes that the impact of harvesting needs to be evaluated across the entire life cycle of an exploited species as long-term productivity depends on continued recruitment of new individuals, as well as the productivity of the adults. In a number of studies models to represent the life-cycle dynamics of a species have been used as a first step in the determination of the sustainability of harvest levels. Growth and yield modelling are well developed for timber species (see Vanclay 1994, Alder 1995), but have only recently been adopted for NTFP species.

Matrix methods8 which model the demography or life cycle of an organism are the most widely used tool for the determination of sustainable harvesting levels for NTFPs. They are recommended for use by Hall & Bawa (1993), Peters (1994, 1996a) and Martin (1994) and have been used by Peters (1990, 1991), Pinard (1993), Olmsted & Alarez-Buylla (1995) and Zea (pers comm.). All of these studies have been on oligarchic shrubs, trees or palms principally in Central and South America.

The elements of the life cycle dynamics of a population can be described by the action of growth, fecundity and mortality on the population. These can be summarised for each life stage as the net effect of growth and mortality between time intervals with fecundity providing new recruits. The data is arranged into a matrix as a life table model to simulate the state of future population of a species. Life table models (as described by Peters 1996a) are composed of a square transition matrix, which describes the behaviour of the population, and a columnar state vector, which gives the number of individuals in each life stage at any one time. Multiplying the transition matrix by the column vector yields the state of the population at one time step into the future. Repeating the process with the column vector for Time 1 gives the state at Time 2, etc.. The rows in both matrices represent the life stages of the organism with the first row representing seeds and the last, decrepit adults. The transition matrix is square with the columns also representing life stages. The first row of the matrix is fecundity and the data represents the numbers of seeds produced by an average individual of each life stage. Obviously this is 0 for the younger stages and is usually size-dependent in adults. The principal diagonal in the matrix is the probability of remaining in the same life stage from one iteration to the next and is calculated from growth and mortality rates. The sub-diagonal represents the probability of movement into the next higher stage at each iteration. Harvesting of different plant parts is simulated by changing fecundity (if fruits or seeds are removed) or mortality (if sap, leaves etc. are removed) and the model is run to determine if the population can withstand harvesting (Peters 1996a).

8 The first matrix models were devised by Leslie in 1945 for use with animal populations. The technique was adopted for use with insect populations by Leftovitch in 1965 and for forestry using diameter classes by Usher in 1966 (Vanclay 1994). Peters (1996a) describes his model as being based on that by Leftovitch, because he uses size classes rather than age. However, Peter’s models have more similarities with Usher’s model as this is based on diameter size classes for trees and permits retention within a class from one time period to another whereas Leslie’s and Leftovitch’s matrices forced all individuals to move to the next class at each iteration. See Vanclay (1994) and Alder (1995) for a more complete discussion of the use of matrix models in forestry.

47 Sustainability is judged by deriving the dominant latent root9 (λ) of the transition matrix which represents the intrinsic population growth rate. Stable populations have λ = 1, growing populations are represented by λ > 1 (getting denser) and diminishing populations by λ < 1. Theoretically the maximum sustainable harvest from a population will be at the highest positive λ when the population should be stable (Vanclay 1994 quoting Usher 1966) and would ideally be λ = 1. Peters (1996a) therefore postulates that a population with a λ ≥ 1 should be able to maintain itself under varying degrees of exploitation with only minimal management inputs, while one with λ < 1 will require a greater intensity of management to ensure long-term sustainability of harvesting. Sensitivity analysis of λ to changes in mortality or fecundity is also used to gauge the relative resilience of the population to different patterns and intensities of exploitation (Peters 1996a). However, there are some reservations about this type of modelling. Vanclay (1994) suggests that the life history of plants can influence the value of λ, such that, in an undisturbed forest, pioneer and light demanding species should have λ < 1, whilst shade tolerants should have λ > 1. It is also not clear if λ values are a characteristic of a species, of the present state of the forest or an artefact of the method.

Life cycle models require enumeration of flowers, fruit, seed stores and seedlings as well as consideration of the dynamics of processes such as pollination, fruit dispersal, fruit and flower predation, seed longevity and germination. The data required necessitates PSP plots with frequent observation intervals to capture flower and fruit production and germination which are often seasonal or periodic. Most life-cycle PSPs for NTFPs have focused on oligarchic fruit (see Box 10) and as noted in Section 3.8 have only been conducted for around 1-2 years. This is far from satisfactory as phenology and germination are highly variable, both between seasons and spatially within a single season. However, it was discovered that most of the studies were biometrically weak, on the grounds of insufficient replication and randomisation for determining a representative productivity for the species and can only be used to gain an indication of potential yields on the site chosen.

Boot & Gullison (1995) criticise the use of matrix models for NTFPs on the basis that they are empirical and need to be calibrated for all management scenarios, that the demographic data used has been collected over a short time period, the models do not incorporate density dependence functions and that no existing model have been calibrated. Boot & Gullison (1995) suggest that spatially explicit mechanistic models (such as those now being developed for timber – see Vanclay 1994), based on an understanding of the recruitment process and the ecology of the species are needed for the design of silvicultural systems or for modelling species response to management interventions. They suggest that the key issue in predicting the response of a species to harvesting is whether it occupies a distinct ecological niche, or shares it with a guild of largely undifferentiated species. If the former then regeneration may be density dependent and increase in response to harvesting, which would permit sustainable harvesting and perhaps species specific management. If the latter, then the species may lose out as it will become a proportionately smaller part of the guild which competes for available niche spaces. It would be possible to manage for the appropriate guild (e.g. shade tolerants) but this may not be sufficient to maintain the target species in the forest. This sort of ecological information is generally lacking for NTFPs.

The only NTFP study that uses a different approach to growth modelling is that undertaken by Runk (1998), which used an individual growth model (POMIB) based on size-specific growth and survivorship, to determine the sustainability of vegetable ivory production. This model suffers from the same drawbacks as the matrix models mentioned above and is based on observations over only one year.

9 Square matrices have eigenvalues (also known as the dominant latent root), λ, and eigenvectors, V, which satisfy the relationship M V = λ V where M is the square matrix (transition matrix) and V is a column vector. If the matrix is n x n then there will be n eigenvalues λ each with its associated eigenvector, V (Vanclay 1994). The value of, λ, is determined by sequential exponentiation of the transition matrix to the kth power of 2 (Peters 1996a) and the resultant V represents the stable size class distribution of the population.

48 An alternative approach that borrows from population viability modelling developed by conservation biologists is that proposed by Gagnon (1999a & b) for American ginseng and Goldenseal, both low- growing herbs in temperate forests exploited for their roots. What is proposed is to develop a stochastic model made up of matrices of transition probability for a number of years, one vector matrix for each year. A random series of 100 years worth of transitions is set up and run on the population. This simulation is run many times to determine the probability the initial population surviving 100 years. Harvesting levels can be simulated by increasing mortality in the transistions and the optimal level is that which gives an acceptable probability of survival. This is an attractive means of determining a yield and should have potential for tropical NTFPs, especially those in areas that suffer periodic extreme events such as hurricanes.

3.9.4 Demographic methods for determining sustainability of hunting Wildlife management, not surprisingly, does not use the same reasoning as sustained yield timber management. There is a considerable body of work on what is termed the maximum sustained yield (MSY) concept for fish, birds and mammals (see Caughley & Sinclair 1994, Bolton 1997, Milner- Gulland & Mace 1998). Animal populations respond to a reduction in numbers from a static carrying capacity with increasing recruitment rate, this may be effected by an actual increase in litter size or through reduced risks of early mortality. However, if populations fall below the minimum viable population size, recruitment falls off as males and females become so spread out they are not able to find mates etc.. The trick is to maintain the population at the size which gives the maximum recruitment rate and yield. In practice, determining the demography of the population in sufficient detail is problematic. There are also increasing objections to the use of the MSY concept though it appears there is little available to replace it.

Matrix models were originally devised for animals (Leslie matrices) and can be used to determine the MSY. However, the collection of sufficient demographic data is time consuming and difficult. Unlike plants there is a reasonable published body of knowledge on large animals, so that it is possible to acquire estimates of population parameters such as mean body weight, longevity, mean litter size and average population densities from the literature. A number of simple methods that use minimal demographic data taken from the literature, together with field estimates of actual densities, have been devised to enable first guess judgements to be made of the possible sustainability of current or projected hunting levels. Robinson & Redford’s (1991) method is perhaps the most commonly used of these models.

The Robinson & Redford method assumes that there are two objectives for management of the population; (1) that the maximum production from the population for human use is achieved, and (2) that wildlife populations are not reduced to levels at the which the species is vulnerable to local extinction, or that ecosystem function is affected. It is argued that reproduction is density dependent, such that it is at a maximum at a population density of 60% of the carrying capacity. The method (see Box 12) determines the intrinsic population growth rate using Cole’s formula and uses this together with the population density in the study area (usually obtained by sampling) to estimate annual production. A sustainable offtake is taken as being any level less than 20 or 40% of annual production, depending on the longevity of the species concerned. Robinson & Redford (1991b) stress that the maximum sustained yield calculated by their method can only provide a first assessment of the impact of hunting on wildlife populations and should not be used to prescribe hunting quotas. The Robinson & Redford method is popular and has been used in several studies of wildlife hunting using various methods (net hunting, shooting and trapping) in Africa by Fa et al.(1994), FitzGibbon et al.(1995) and Noss (1998) and in Amazonia by Bodmer (1995). Noss (1998) also uses two other methods for calculating the intrinsic population growth rate.

Slade et al.(1998) reveal a number of limitations in Robinson & Redford’s method and propose an alternative, also based on minimal life table data, which gives more realistic survivorship models and has the advantage that better data can be included if it is available. Robinson & Redford’s method assumed that mortality for animals before the age of first reproduction is 0 which over-estimates the growth of the

49 population as mortality is generally U-shaped with high mortality in young and old animals. However, estimates of juvenile mortality are difficult to obtain, so Slade et al.(1998) invert the method and calculate the mortality rate required to keep production just above harvest rates and then judge whether the derived rates are realistic. Slade et al.(1998) did a review of Fa et al.(1994) and FitzGibbon et al.(1995) using the new method and discovered that more species than originally supposed were being over-exploited. Box 12 Robinson & Redford (1991) method for assessing sustainability

(1) Calculate maximum production in animals km-2

Model variables (actual density measured; the other parameter values estimated or taken from literature) Actual density (D) – nos km-2

Predicted density (D2) – predicted from linear regression of log10 population density against log10 body mass by dietary categories.

Intrinsic rate of natural increase (rmax) – highest possible without any limitations estimated using Cole’s (1954) equation:

1 = e-rmax + be-rmax(a) – be-rmax W+1 where: a = age of first reproduction, w = age of last reproduction, b = annual rate of female births.

Cole’s formula assumes no mortality (error small if mortality is not significant before age of first reproduction).

Maximum finite rate of increase (λmax) – exponential of the intrinsic rate of natural increase (ermax) and is the increase in population size from time t to time t+1. Production (P) – addition to population = (birth + immigration) – (death + outmigration) + survival (to end of specified time period i.e. 1 year) Assume: - Predicted densities are better than observed and that the predicted densities are close to, or at carrying capacity for the species. - Maximum production will be achieved when the population density is at 60% of carrying capacity. Subtracting 0.6 D2 maintains the population at the same density.

Production Pmax = (0.6 D2 x λmax)- 0.6 D2

(2) Estimate of potential harvest It is assumed that the average life span of a sp. is a good index of the extent to which the harvest takes animals that would have died anyway. Thus harvest levels are set according to the longevity= age of last reproduction of the species: for very short-lived spp, < 5 years, harvest levels = 0.6 P; for short-lived species, between 5-10 years, harvest = 0.4 P; long lived spp, > 10 years, harvest = 0.2 P.

Most significant assumptions are: • Model assumes density dependence in production i.e. production increase with decreasing density such that it is at a maximum at 0.6 of the carrying capacity. • The proportion of production that can be harvested without depleting the standing population. Indirect confirmation could be to compare the weight distribution of harvested and nunhunted populations, if they are the same then can argue that hunting is taking animals that would have died anyway and hunting can take a higher proportion of total production.

NEED to have the following to use R&R method: average body mass, food preferences (if using predictive equation), age of first reproduction, age of last reproduction, annual birth rate of female offspring, (average population density for study site – if not using predictive equation).

Model should NOT be used to generate single species harvesting schedules. It CAN provide a first assessment of the impact of hunting on wildlife populations.

Bodmer (1995) did a study of game choice i.e. the animals captured rather than preferred by non-tribal hunters in Peru. This study correlated harvest levels with hunters preferences and population parameters of the prey species. For each species, the captured biomass was recorded and the resource availability

50 determined in terms of density and the intrinsic rate of population increase (rmax using Robinson & Redford method) based on the results of extensive transect surveys. The results indicate that rmax is most closely correlated with harvested biomass. This is interpreted as suggesting that hunters are unintentionally extracting animals according to their productive potential. This supports the use of rmax and models such as Robinson & Redfords method for the determination of sustainable harvesting levels.

Winterhalder & Lu (1997) combined population ecology and optimal foraging theory to model how individual-level foraging tactics and success affect the long-term stability and survival of hunter- gatherers and the resource populations on which they depend. Foraging models lie at the junction of economic and ecological analyses and describe hunting choices in terms of the energetic profits of capturing any particular prey. The animal part of the model is a logistic equation of population growth derived from a life-table matrix and describes how well prey can recover from exploitation. The human population is ascribed certain hunting tactics in the form of an encounter-contingent foraging model (need to encounter the prey before deciding to capture rather than selective searching for a particular prey). The model simulates a small range of hypothetical resource species (four) modelled on a mix of animals such as rare medium sized ungulates, intermediate sized prey and high-density fruit etc.. Each prey is assigned a calorific value and prey are selected so that more profitable types are captured until the next ranked item returns less net energy that would be gained by ignoring it. The population dynamics of the human foraging group is also modelled using a variant of a logistic equation. The model is run as a closed system so human population levels are linked to the abundance of prey; if the hunters can capture more than they need their population grows while the prey species declines. The model was run using different numbers and mixes of prey types and revealed that a prey’s vulnerability to local depletion or extinction may depend on the demographic characteristics of the suite of resource harvested along with it. It also suggested that whether prey species survive depends on human foraging behaviour and the dynamics of the prey species hunted alongside it. These results are interpreted as suggesting that sustainable management in such situations should be informed by features of the foraging economy such as prey growth rates and hunters game choices. This model calibrated for a real multi-resource situation could be a useful tool for determining the potential sustainability of a multiple-use forest though it may prove too expensive and complex to parametise.

3.9.5 Egg of sustainability Since the Rio World Summit there has been a huge surge of interest in the use of criteria and indicators to judge sustainable development. In response to this the IUCN Specialist Group on Sustainable Use of Wild Species (comprising about 300 members) commissioned a review of methods for assessing sustainable exploitation which was prepared as a report by Prescott-Allen & Prescott-Allen (1996). These recommendations have not been widely taken up which is unfortunate as they contain much that is worthwhile. The main point made by Prescott-Allen & Prescott-Allen (1996) is that the use of wild species takes place in a biotic and social context and that each has to be stable or improving for human use of the species to be sustainable. The biotic environment is visualised as the yolk and the social context as the white of an ‘egg of sustainability’. The well-being of both parts has to be considered in order to sustain the egg.

Through the presentation of a number of case studies Prescott-Allen & Prescott-Allen (1996) demonstrate that the use of broad criteria that judge the well-being of the exploiting society as well as the ecosystem can be effectively used to rank NTFP projects on the grounds of potential sustainability. The system is flexible enough to permit short-term depreciations or even over-exploitation for the sake of longer-term improvements but can apparently discriminate unsustainable projects. The method is not strictly quantitative and the reader is referred to the text for a fuller account of the steps involved.

51 3.10 Monitoring Monitoring is the stage in the management process that provides for the process of reflection on the success of interventions in achieved objectives (see Figure 2). Monitoring is an integral part of management, it is a process that commences with a baseline survey, ideally undertaken before any interventions take place and continuing at frequent intervals with the data used to revise management prescriptions as necessary. Monitoring of any and every aspect of management including the ecological, social and economic elements can be done, though this report is only concerned with resource monitoring. Without quantitative and biometrically rigorous inventory it is not possible to say with any confidence that changes in the resource base are occurring (Bailey pers comm.). However, in some cases indirect indicators of NTFP stocks (e.g. market surveys, harvest levels, basal area sweeps) will be an appropriate basis for making management decisions (Abbot & Guijt 1998, Cunningham 1996a, Waitkuwait 1994). For example, through market surveys Vasquez & Gentry (1989) were able to alert conservationists to the advent of destructive harvesting. Note that different stakeholders will have different perceptions of change and therefore will consider different indicators to be appropriate (Abbot & Guijt 1998).

Figure 2 Flow chart of basic strategy for monitoring sustainable management of NTFP plant resources (after Peters 1995)

Species selection

Forest inventory Baseline data

Yield studies

Periodic Periodic regeneration harvest surveys assessments Yes Yes Monitoring Adequate Adequate productivity? cycle regeneration? Harvest controls effective?

No No

Harvest adjustments

There is no specific methodology fo resource monitoring and most of the techniques and methodology discussed above can be used within the context of a monitoring scheme for NTFP extraction. An important biometric issue in the design of monitoring programmes is the consideration of the ‘power’ of the design (Evans submitted). This is the programme’s ability to distinguish trends from random errors in the estimates. Generally, the finer the resolution of trends the lower the sampling error at each enumeration must be. Getting sampling errors low requires large numbers of plots and is therefore

52 costly. Cost is an important issue for routine monitoring and as a consequence there is much interest in the use of simple, easy and cheap indirect indicators of resource condition.

Although indicators are attractive, care must be taken to ensure that they do indeed measure or reflect the state of the resource. Some indicators are not particularly easy to measure but are used to monitor the state of the whole population e.g. regeneration assessment as proposed by Peters (1994) is used to monitor the health of the resource population without the need to undertake a complete inventory. Adequate representation of the resource in terms of the sampling design and the time interval between assessments is also important. Many monitoring schemes do not pay sufficient attention to these details but a more serious failing is if the information collected is not used to modify or inform management decisions. There are only a few recorded examples where monitoring has been used to refine harvesting quotas for specific products e.g. Lokta cutting quotas were reduced on the basis of an inventory (Chitrakar & Prescott-Allen 1995). However, this may be an unfair judgement, as scientific papers do not generally document the management process. Furthermore, most NTFP management schemes are in their infancy e.g. mushroom monitoring in the US which is still being negotiated (see Pilz & Molina 1998, Pilz & Molina in press, Pilz et al. in press) and monitoring for the Kibale and Semuliki National parks in Uganda which is still in a design phase (Sheil 1997). Grey literature on the monitoring and management process are both rarely written and difficult to locate though this is changing with the emergence of adaptive management with its emphasis on monitoring. Examples of adaptive monitoring are those developed by Gibbs et al. (1999) and Ringold et al. (1999).

The review of available literature suggests that there are two general approaches to monitoring NTFP harvesting. These are monitoring the health of residual populations which is forest-based (e.g. methods proposed by Sheil 1997, Pilz & Molina 1998, Gagnon 1999a) and monitoring the size and quality of the harvest which is harvester or market based (e.g. Watts et al.1996). Ideally both approaches should be used in tandem (such as for caimen, Velasco et al.1996) and at the local scale to permit the development of an understanding of the interaction between resource availability, harvest intensity and market values.

3.10.1 Monitoring exploited forest Many PSPs programmes were originally developed as tools for monitoring post-logging timber growth and forest health. Unfortunately, there are few instances of baseline conditions being measured prior to first logging and many plots were established post-logging as a condition of exploitation. For example in the past in Ghana and presently in Papua New Guinea. As a consequence there are often few non-logged control plots. Repeat measurements of PSPs are a monitoring activity though the analysis of the resultant data has often focussed on predicting the future, through growth modelling, rather than seeking to explain regenerative processes.

Several NTFP monitoring schemes have focused on the monitoring of the post-exploitation forest (measurement of all species). The establishment of such a monitoring system should ideally be done according to strict biometric principles in order to maximise the utility of the data in terms of representativeness and to permit spatial extrapolation. There are few well worked out or documented protocols for in-situ monitoring. Although they are not yet in use the proposal made by Sheil (1997) for monitoring NTFP extraction from in Kibale and Semuliki National Parks illustrates the type of methodology being considered.

It is important to ensure that either the pre-exploitation state be determined by baseline surveys or paired controls be established to measure the impact of exploitation. Baseline surveys should be done at the earliest possible opportunity, a point which is often overlooked until management activities are about to commence. Although there is much discussion about the use of indicators in monitoring, the establishment of baselines against which indicators can be judged and the verification that they do indeed measure pertinent features of the species or forest are relatively neglected. This is an area that needs urgent development. Social surveys are often the first stage of a participatory management approach (e.g. as used in PRA or PLA) and this often includes forest-based interview techniques such as the ‘walk-in- the-woods’ favoured by ethnobotanists. Some consideration of suitable quantitative or mapping

53 technology for using these opportunities for baseline data collection could well provide a useful link between the social and ecological approaches to NTFP utilisation.

Forest-based monitoring is generally considered to be a high-technology, high-input technique and is restricted in application to National Parks and other areas under regulatory control (e.g. as proposed for Kibale and Semuliki National Parks in Uganda, Sheil 1997). However, there are increasing numbers of resource-based (i.e. only the species of interest are measured rather than all species in the forest) monitoring programmes which are participatory in nature (Berchemia bark, Cunningham & Liebenberg 1998; mushrooms in US, Pilz & Molina 1998; proposals for american ginseng, Gagnon 1999b). The use of indicators of forest condition such as tree density, presence of indicator species etc. can be used as surrogates for detailed assessment and still provide a forest-based picture of change.

3.10.2 Harvest records Harvest records are a popular means of monitoring NTFPs and are relatively quick and straightforward to collect. Such records are simply a measure of the quantity of product which has been collected. The measure can be quantitative (e.g. weight in kgs) or qualitative (many, few etc.). An important consideration is the location of the recording which can be in the forest (e.g. Watts et al.1996, Scott 1998), in the village (e.g. Infield 1988), at a local or national market (e.g. Falconer 1992b) or in international trade as customs and excise or CITES import and export statistics. The proportion of the actual harvest captured by the records declines with distance of observations from the source. In addition the link between the product and particular sources is lost once the product leaves the village.

Harvest records have the advantage of measuring directly the value of the extracted harvest, especially if market prices are recorded concurrently. Thus the data becomes of interest to socio-economists and market researchers. Harvest data is also collected by statutory agencies for taxation or export monitoring purposes by Customs and Excise agencies. This latter data is used for compiling international trade statistics and should be collected under a unified coding scheme based on processed product types (Chandrasekharan 1995).

Detailed harvest monitoring is common for wildlife harvests where record keeping is a legal requirement as it is for deer and wild turkey (Flather et al.1989) and american ginseng (Bailey pers comm.) in the USA and caiman in Venezuela (Velasco et al.1996). In these cases, direct assessments of population levels along with the previous years harvest records are used to determine the quota for the current year. One of the problems with this approach is the ability to distinguish wild from cultivated specimens otherwise resource depletion will still occur disguised by increasing amounts of cultivated products (Gagnon 1999b).

Harvest records are often used in the absence of forest-based resource inventories as an indicator of the status of the resource (e.g. elephant ivory seizures used as an indication of population levels by TRAFFIC, Burns pers comm.). If sustainability is an issue then there are two implicit assumptions in the use of harvest records as an indicator of resource health.

Fundamentally it is assumed that harvest levels reflect resource population levels and are sensitive to relatively small changes in abundance. This needs to be established on a case by case basis as there are many reasons why harvest levels may change. For example, Bailey (pers comm.) reports that dealers in American Ginseng who sell out of State (Virginia) have to report sales every 30 days during the harvest season to the Division of Forestry. These data are supposed to serve as a proxy for the species’ population status but in reality they are most closely correlated (80%) to unemployment figures: when unemployment is up, so is the harvest (it acts an economic cushion for the rural poor); when people have jobs, the harvest is down (they have less time to harvest and need the money less). This is particularly true for West Virginia which has a large (proportionately) rural and poor population, and an economy that has been dependant on boom-and-bust cycles associated with coal mining.

54 Furthermore, actual level of damage or mortality inflicted on the resource population by a certain quantity of product in trade should remain constant and be known. This assumption needs to be monitored. There are numerous examples of increased commercialisation resulting in the influx of new collectors who do not observe local harvesting conventions and for example they may collect fruit by felling trees rather than picking fruit or waiting for natural fruit fall (Vasquez & Gentry 1989). Such changes, unnoticed, would result in the conclusion that yields were sustainable when, in fact, that had ceased to be the case.

However, harvest or market records are an appropriate indicator of changes in resource use and therefore could be used to flag a need for more ecological studies if traded quantities become a concern. Such an approach could be used to flag new products entering the market-place as well as reveal increases in existing products to a level that might cause concern for the resource (as proposed by Cunningham 1996).

Harvest records are used for expediency as they provide a quantitative measure when it is not possible to get any closer to the forest or finances for monitoring are limited and are widely and often indiscriminately used. Harvest levels, especially of commercial products will be influenced by many factors outside the forest such as changes in income levels among harvesters, macro-economics in the country, demand fluctuations etc. The classic supply and demand economic models also suggest that a resource will be harvested until it is no longer profitable to do so and that as a resource becomes scarcer so its price will rise, justifying higher levels of effort in harvesting. This may have the effect of maintaining relatively high harvest levels until the resource and market catastrophically collapses over a relatively short period of time. If harvest records are going to be used without independent resource assessments then it is important to determine their sensitivity to resource availability which should be calibrated at periodic intervals by field survey.

It is the intention of the FAO to include NTFPs in FRA2000. Since there are very few national NTFP resource inventories it is likely that the only data available will come from harvest and trade statistics. However, without validation these data will only indicate the relative size and origins of international traded NTFPs and will not identify if these come from forests or are sustainable and take no account of local consumption. Problems with the use of trade data for inferring past animal population trends are also problematic and seldom reliable (Milner-Gulland & Mace 1998).

3.10.3 Participatory monitoring Many NTFP studies have been initiated with the intention of providing local involvement in forest management and as the basis for sustainable local livelihoods. Several of the reviewed studies are intended to foster community or locally-directed management of resources. In these circumstances it is important that local people understand the need to monitor the impact of their actions and to act on the findings of appropriate and effective monitoring schemes. Even where local people are not the managers but undertake NTFP harvesting it is still efficient and important in fostering understanding to involve harvesters in the monitoring of their impact on the resource. Consequently there is much interest in the development of participatory monitoring techniques tailored for harvesters. This is as true in the USA (Pilz & Molina 1998) as it may be in Uganda (Watts et al.1996, Scott 1998). Gould et al.(1998), Peters (1996a) both suggest that monitoring should be designed so that user-communities can collect and analyse data with minimal outside technical support or funds.

Local people can be effective collaborators in both forest and resource based monitoring. The only constraint is that methods should be relatively simple to learn and recording should be straightforward and effective. This does not mean that methods or designs need be unsophisticated, it will just mean that the advisors will have to work harder at the presentation and training for sophisticated designs. Waitkuwait et al.(1995) has developed a sophisticated and complicated protocol for faunal monitoring which takes 24 hours to complete that is successfully and reliably performed by teams of semi-literate ex-hunters. The contributions of local ideas and insights into the resource may also suggest novel indicators for measuring condition as discovered Ghana (CFMU 1995).

55 Illiteracy has often been viewed as an obstacle to local collaboration in monitoring and data collection. However, advances in palm-top computer technology have been successfully used to capture data by illiterate villagers using icons instead of words (Cunningham & Liebenburg 1998). Computers are often seen as something which alienates villagers from decision-making but this example shows that this need not be the case. Older technology for data collection e.g. relascopes and computer analysis on main frame computers did indeed require substantial training and were inaccessible to villagers. However, the development of user-friendly interfaces and small hand-held computers have reversed this trend and as the CyberTracker development shows, it is now possible to make the most sophisticated technology transparent and accessible to villagers. With some further development it should even be possible to put on-the-spot calculation of results into the hands of villagers. Likewise, the replacement of theodolites, compasses, chains etc. for surveying with hand-held GPS can make mapping more interactive, more direct, faster and therefore cheaper (Stockdale & Ambrose 1996).

The work by Shanley (1998) and Marks (1994) demonstrates that well negotiated participatory data collection protocols can become wholly assimilated by local participants who then continue monitoring on their own initiative. This level of ownership of monitoring is relatively unusual but should perhaps be an objective, or indeed indicator, of participatory monitoring initiatives.

Participation in monitoring and management is sometimes traded for access to the resource where the managers and harvesters are different and perhaps opposing groups of stakeholders. This seems to be a successful means of fulfilling the need for security of access on the part of harvesters and for monitoring and management controls on the part of statutory management agencies such as National Park authorities. This approach is proposed in Ghana (CFMU 1995b), Oregon (Pilz & Molina 1998) and Uganda (Watts et al.1996). There is insufficient experience of such approaches to judge their actual effectiveness and long-term stability but they are attractive and will probably gain prominence as more reserves are opened for collaborative management of NTFPs.

Recent developments in Joint Forest Management (JFM) in India and Nepal have re-asserted the local use and reliance on forest resources especially fruit, fodder and fuelwood. Statutory JFM agreements in Nepal require the resource to be inventoried, management plans to be approved and routine monitoring established (Ingles et al.1996). The development of JFM has been largely facilitated by social foresters and social development advisors who have (rightly) focused on tenure, equity and income dispersal issues. This has resulted in the development of a range of non- or semi-quantitative methodologies for describing forest resources, often as part of Participatory Rural Appraisal (PRA) exercises. A key feature of JFM resource assessments is that it should be readily understood by a range of forest users with the objective of fostering local involvement in the process of assessment and management. At an extreme this can lead to a possible over-valuation of local skills, e.g. Poffenberger et al.(1992) contend that ‘community members can often identify more plants and animals, more quickly and accurately, than botanists’. This may be true using folk taxa but not if scientific names are required. Branney (1994a) issues an injunction for Forestry staff NOT to carry out inventory in community forests, eschewing scientific rigour in favour of a simple, subjective means of assessing the sustainability of extraction. However, Branney (1994b) also developed a manual for baseline monitoring surveys which include random number tables and detailed protocols and forms for recording plant information for use by forestry staff in community forests but this time to fulfil Forestry Department monitoring needs. This apparent dichotomy of ideas reflects the need for methodology to be adaptive and sensitive to both local involvement and wider needs for replicable, standard methodology for monitoring. Carter (1996) notes that over time the requirement for systematic information from JFM forests is likely to increase and the gradual evolution of predominantly qualitative assessments into a somewhat more formal quantification of resources will probably continue.

A key issue in participatory monitoring is the adoption of locally relevant indicators of resource condition. Once local people understand the principles and purpose of monitoring it is possible that they could devise indicators from their knowledge of the species and forest which are easier, cheaper or just

56 more locally relevant. However, before these can be adopted they should be verified and perhaps calibrated against the baseline data collected at the commencement of the project.

3.11 Criteria, indicators and certification Over the past few years there has been much interest in the development of Criteria and Indicators (C&I) for sustainable forestry, generated mostly by international bodies such as the UN Commission on Sustainable Development (CSD), the Intergovernmental Panel on Forests (IPF), the International Tropical Timber Organisation (ITTO) etc.. A strong push for the development of C&I has also come from bodies interested in promoting the use of certification as a market-based tool incentive for sustainable forest management practices (see Upton & Bass 1995). Certification has mainly been for timber but there are now moves to certify NTFPs (Mallet 1999).

The framework for C&I is hierarchical (see Prabhu et al.1996 for examples of C&I lists). At the highest level is sustainable management which is defined as ‘a set of objectives, activities and outcomes consistent with maintaining or improving the forest’s ecological integrity and contributing to people’s well-being both now and in the future’. From this assertion emanate principles which are the critical components of the management system and which operationalise sustainability and are represented by broad concepts such as ‘human well-being is assured’ or ‘sustainability of the forest and its multiple functions is a high political priority’. Criteria sit on the next level down as second order principles or standards against which performance is judged. Indicators are variables or components of the forest or management systems which can be measured. Verifiers are actual performance thresholds which can be used to judge whether a measured indicator contributes to sustainability or not. In essence the C&I approach is simply a highly formalised monitoring system which attempts to include social and political aspects of human use of forests for consumption by the international community.

Considerable efforts on the part of many international agencies are directed towards the prescriptive identification of criteria and indicators against which to judge sustainability (e.g. ITTO, CIFOR, CSD, FSC etc.). The difficulties in the use of C&I is not devising biometrically adequate monitoring protocols but rather in establishing a politically acceptable minimum set of criteria and appropriate and sensitive indicators against which achievement of the criteria can be judged. By 1995 the CIFOR study of C&I drawn from just five lists had to consider 1095 individual criteria statements (Prabhu et al.1995). It seems a shame that work on a more holistic and process orientated approach sponsored by IUCN in which the quality of the natural systems and human sub-systems are judged together in a local context (Prescott-Allen & Prescott-Allen 1996) has not seen wider consideration.

NTFPs are an element within wider forest certification both on the ecological (any exploitation within the forest should be sustainable) and social front (as part of the equitable distribution of benefits to local communities etc.). Although fair trade and organic standards are relevant to timber production they are of more concern to those seeking to certify NTFPs. Aspirations for NTFP certification standards therefore have to reconcile, ecological, social, fair trade, organic and agroforestry standards. Fair trade standards consider the health and well-being of workers and harvesters of NTFPs while organic standards address issues of soil management and chemical residues (say used for pest control during storage). This greatly complicates the identification of common C&I and present initiatives are focussed on providing a framework for increasing collaboration between the many (55 different NTFP-relevant standards documents exist) systems of certification (Mallet 1999). The workshop reported by Mallet (1999) concludes that a key element of institutional criteria are monitoring and survey of natural processes and management impacts. The criteria often require that monitoring should cover both ecological and economic impacts and involve public input by stakeholders. Furthermore the results of monitoring should be used to modify and update management plans.

Most criteria sets, even when considering ecology, encompass a broad range of criteria including measures of ecosystem health, biodiversity, soil and water quality and harvesting impacts on long-term productivity. Although the details of what is required varies among criteria sets and there is as yet no concensus on common standards, it is clear that the scope of monitoring and corresponding baseline

57 surveys is increasing. This presents new challenges which in due course will need to be addressed in terms of sampling strategies and designs. The only existing proposal that may be able to take on the type of monitoring required for certification are those of Sheil (1997) which still await refinement and field testing. It is therefore imperative that more work is undertaken in NTFP resource assessment to meet the demands for information and monitoring imposed by management systems and subsequent certification.

58 4. Review of current practice There are a number of issues that are currently being debated among NTFP practitioners in relation to the necessity for strict adherence to biometric principles in NTFP assessment. There is also increasing concern over the difficulties of linking local to scientific knowledge. These two issues are discussed below to provide some context for the review of the biometric rigour of NTFP resource assessment.

4.1 Participatory issues There are two bodies of opinion on the relevance of biometric principles in NTFP work. On the one hand it is argued that participatory or socially orientated work need not be biometrically rigorous because it would require techniques too sophisticated for local use and it is important that methods be participatory and preferably developed collaboratively. On the other hand, traditional foresters have suggested that participatory methods are not scientific enough for resource management. The conclusion seems to be that these approaches should therefore be kept separate (McCormack 1998). Though this dichotomy between social and natural science approaches is not borne out by the experience reported in the review studies, as both have produced both good and bad case studies. Indeed, interpreting these difficulties as a dichotomy between social and natural science methods is too simplistic. The debate actually centres around three main issues; the relative value and usefulness of qualitative versus quantitative data, the use of formal (i.e. statistically rigorous) versus informal (verification via triangulation) methods for data collection, and the relative utility of context versus non-context specific data. In short, the methods used to collect data must relate clearly to the context and manner in which they will be used. The challenge is to develop methods that can produce data for more than one objective, or type of use and can therefore be generalised without compromising achieving the primary objectives of the study. Clearly, single objective studies are easier to plan and execute but multiple purpose studies are likely to provide a more efficient use of effort in the long run.

There are relatively few participatory inventories in the review but there is no indication that these need be less than biometrically rigorous. In Ghana, villagers undertook a complete census of useful plants and animals (Gronow & Safo 1996), this is both simple to do, albeit in a small area, and the most accurate methodology of all. A manual of participatory NTFP inventory methods (Stockdale & Corbett 1999) describes in painstaking detail the application of a biometrically considered design principally for use in Indonesia. Increasingly local communities in Indonesia “seek scientific backing for their efforts to improve or stabilise the economic basis of their lives and to halt further deterioration of the forest environment” Beer (1999). Responding to this demand would necessitate the use of rigorous methods that can withstand scientific or at least unsympathetic inspection.

At the other end of the spectrum there is a movement among foresters towards the use of participatory methodology including the use of local volunteers, key informants, stakeholder analysis and participatory monitoring in ‘scientific’ inventory and monitoring (e.g. USA -Pilz et al.1998, Sweden -Eriksson et al.1979). Pilz & Molina (1998) give a range of reasons for advocating a collaborative methodology for mushrooms in Oregon including: cost reduction, provision of more reliable and locally useful information; the fostering of confidence in results as well as the basis for a more direct involvement of pickers in management planning. Pilz & Molina (1998) also note that “significant involvement by interested publics in a monitoring program is a social research topic in its own right”. This parallels the arguments put forward for collaborative management in the tropics and suggests that a process of convergence between the tropics and temperate regions and between disciplines (especially forestry and social science) is underway. Several of the research recommendations in the current report are intended to foster this convergence.

Local participation in management requires considerable incentives and the people need to be confident that the time they contribute to the project is worthwhile and will bring benefits to themselves and their communities. Carter-Lengeler & Jones (1998) observe that mistakes in the design or execution of a NTFP assessment can result in the need for a highly demoralising re-survey. Indeed, this was the experience of Gronow & Safo (1996) who report that the use of a ‘rough and ready’ approach led to

59 problems which necessitated a complete re-survey, wasting a lot of time and goodwill. If villagers are to give up precious time to be involved in non-subsistence (at least not in the short-term) activities, then their technical advisors need to ensure that the tasks undertaken are truly worthwhile. Carter-Lengeler & Jones (1998) and Gronow & Safo (1996) point out that this means the adoption of rigorous and professional approach to survey design. The responsibility here clearly lies with the technical facilitators, for the inventory and statistical design need not itself be participatory. For example, Stockdale & Corbett (1998) advocate a participatory approach to decisions about the products to be included and the measurements to be taken, but do not invite participation in the sampling design as they provide detailed instructions for a single sampling design and plot configuration to be used for all products. In the case of assessments using daily diaries (e.g. Marks 1994), the level of participation in data collection is high but the decision on the level of replication needed and choice of collaborators is the researchers prerogative.

The degree of potential collaboration in inventory design obviously depends on factors such as the abilities of potential collaborators, the competency of technical facilitators, time available and the significance of the inventory in the collaborative management process10. Carter-Lengeler & Jones (1998) report that local people can become highly competent in conducting inventories and that statistical issues are not necessarily ‘beyond the comprehension’ of local people. Rather they suggest that the clear and simple presentation of statistical issues can facilitate local collaboration in the statistical design. The methodology suggested by Myers & Shelton (1980) (see Box 14 below) represents a formalisation of the participatory design process. It demonstrates that involvement in design need not require biometric understanding from all participants, as the alternative designs (Step 3) are developed by specialists.

Often the choice of method and sampling design are strongly influenced by the views of advising experts. Thus a social scientist approaching a resource assessment will adapt social survey techniques to the problem, a forester will adapt timber inventory and a botanist will use ecological plots. This is not really a problem as long as the sampling method developed can achieve the objectives set for the inventory, is relevant to the type of product being studied and is appropriate to local capability and resources. Problems arise when the methods being developed are not able to efficiently provide the necessary data quality.

A common objection to the use of biometrically rigorous methods is that the data require sophisticated analysis and perhaps access to a computer and that this is beyond the reach of local communities (Stockdale & Corbett 1998). However, even the simplest calculations (e.g. mean) still require sampling designs to be robust and reliable. Furthermore, carefully designed proforma such as those presented in Stockdale & Corbett (1998) can be used to undertake quite complex analysis as was commonplace prior to the invention of pocket calculators. Of course computers greatly enhance the analyses that can be done and these are often beyond the resources of local communities. Nevertheless this should not mean that they are denied access to the latest technology as a matter of principle. In many communities the opportunity to be trained to use computers is valued as offering access to employment opportunties. Not knowing how a computer or analysis works is not an impediment to their use, otherwise no-one except computer scientists would be able to use them. It is also possible that a community could contract out analysis of their data either to an NGO or perhaps even a commercial company using some of their profits, as is the case for timber inventory in Quintana Roo (Lawrence & Román 1996). Technology is a malleable tool and can be moulded to a wide range of circumstances. Ideally technology should be attractive because it reduces the effort in data collection or analysis rather than presenting yet another obstacle. The CyberTracker system (Cunningham & Leibenberg 1998) uses carefully designed icon- based programs on a palm-top computer to permit illiterate people to record observations. The resulting data is downloaded into a central computer and used to produce maps and perform analyses. GPS units are also proving to be an efficient and reliable means of replacing ranging poles, sighting compasses and considerable survey skills for participatory mapping of community land (Stockdale & Ambrose 1996). In

10 Willingness to participate in an inventory is often the first real commitment to management that is requested of the local people (e.g. Gronow & Safo 1996, Dunn & Otu 1996). It is therefore of paramount importance that this is a constructive experience and provides information of real value to them and provide a sound basis for subsequent discussions and management planning.

60 fact there is greater potential for crafting simple interfaces and creating simple-to-use tools that undertake powerful analyses with more rather than less sophisticated machines. There is of course the proviso that this can be prohibitively expensive, inappropriate and difficult to maintain and service in remote areas and in difficult environments.

It is also argued that local people are not able to understand results of conventional inventory and that this should therefore be avoided (Branney 1994a). However, Shanley (pers comm.) makes the point that the economics and ecological significance of NTFPs must be understood not only by northern scientists but also by local communities and citizenry. This ‘give back’ of data is ethically important especially when local people have participated in the study. This is equally true for any study undertaken on resources that belong to someone else but particularly when they have been asked to participate in the study. Larsen (1999) also points out that local people are often in the position of not having generated the demand for an inventory but being considered as the main users of the data. This means that they require assistance to assimilate the data collected and relate it to their own abundant knowledge and experience of the resource. However, there are few examples of effective communication of results to local communities. An exemplary example is the work reported by Shanley et al.(1996), Shanley (1998 and in prep.). In this case small group meetings, cross community exchange, technical assistance, forest theatre, posters and illustrated booklets were all used to convey quantitative information and their significance to the management and value of forests. Presenting information in a form accessible to the local communities necessitated re-analysis of some of the data, as conventional density measures i.e. kg of fruit per ha was not relevant to local people who were interested in mean fruit yield per tree. Interestingly the only textbook that deals with these issues in any depth is that of Myers & Shelton (1980) which was written for use by the US Forest Service (see Box 14, Step 5). Also, if local people can be involved in the data analysis itself, then the results will be intelligible at least to the people involved e.g. stock survey style map preparation in Adwenaase was done by villagers who then ‘owned’ the maps (Gronow & Safo 1996).

4.2 Linking local and scientific knowledge NTFPs are plants and animals used by people often from a wide range of cultural and ethnic backgrounds each of which have their own naming systems and knowledge of NTFP species and products. Often in situ resource assessment is done in collaboration with local people and their names for the plants, animals and products are often adopted for field data recording by the inventory, as was done in Ghana (Falconer 1992a) and Nigeria (Dunn et al.1994). Local (folk) names are often used in field survey because local staff or collaborators may find it easier to record familiar names rather than codes or latin names. There are also circumstances where it is easier to adopt a local name, such as when there are no available keys or guides from which the species can be reliably identified, when the parts required for identification are not available (e.g. flowers or fruits), or collections and specialist equipment are needed for reliable determination (e.g. microscope for insects). It may also be appropriate to use local names when the study is user-led or collaborative (Branney 1994b, IDRC et al.1998), as was done in the study in Uganda (Cunningham 1996a, Scott 1998).

In the literature there are many lists of botanical names being matched with a single local name in one or more languages. These are found in field guides (e.g. Hawthorne 1990, Everett 1997), lists of NTFPs for a particular area (e.g. Abbiw 1990, Papadopulos & Gordon 1997) or the results of ethnobotanical surveys (e.g. Edwards 1991, Kulip 1997, Boom 1989, Salick 1991, Manandhar 1995). Such lists have been used to identify NTFP plants in independent inventories e.g. (Rai 1983, Gunatilleke & Gunatilleke 1985, 1993, Johnston 1998). Even though it is well known that there is considerable variability in local names (e.g. Hawthorne 1990, Dijk 1999b) one name is usually taken as the ‘correct’ or ‘standard’ name and given precedence over variants, thereby suggesting that local names can be used as synonyms for scientific species. However, reality is not as simple as this and problems with local and formal (scientific) names for resource species lists have been reported by Hawthorne (pers comm.), Harris (pers comm.), Wilkie (pers comm.), Gronow & Safo (1996), Cunningham (1996a), Dijk (1999b), Stockdale (1995b) and Sunderland (1999).

61 It seems there are three basic problems in reliably naming resource species: • Incomplete and inconsistent use of names by local informants. Wilkie (1998a & b) used two informants rated as the most knowledgeable by the local community to name trees in a 1 ha plot. He observed that only 12-22% of the local names used were applied consistently and of the consistent names, 80% were exactly the same with the remaining 20% only having some common elements. The consistently named taxa were noted as being either distinctive or having utility to the informants. Grossmann (pers comm.) also reports that informants for local names frequently shifted between collective product names and individual species names. • Mis-match between local and scientific names. Cunningham (1996a) criticises work in Bwindi (see Scott 1998) which only reported local names because local names sometimes refer to scientific genera rather than species. He cites the following examples: ‘bitindi’ corresponding to two Memecylon species, M. jasminoides and an undescribed endemic to Bwindi, ‘omushabarara’ applied to three Drypetes species including a rare one and ‘omurara’ to at least four Macaranga species. • Taxonomic difficulties The taxonomic description and naming of species in tropical forest is notably incomplete. Trees are perhaps the best known group but even here there are new species or new records discovered on most biodiversity surveys. This means that it is often not possible to give a taxonomic identity to a locally named NTFP. There are considerable taxonomic identification problems for many groups of NTFPs including many that are common, large, perennial and well-known. For example, rattan taxonomy is difficult and species identification in countries other than Malaysia, India and Sri Lanka can often only be taken as far as genera using local names (Stockdale 1995a).

From the observations made above it appears that many in the NTFP community are unaware of the theory of folk classification developed by ethnobiologists (see Appendix 8) which would at least provide an explanation for the apparent inconsistencies noted above.

If it is important that data can be used with other datasets i.e. compared to data from another area, with published research results, or with entries in a flora etc., it is essential to determine formal (i.e. taxonomic latin names) identities for local names. This requires that the correspondence of local to latin names be known. Unfortunately, identification of specimens in the field can be problematic as there are few field guides or keys available and inaccessible or seasonal parts are often required for identification (e.g. flowers and fruits). For rarer specimens, consultation with experts often in Europe or North America is often needed to determine the correct botanical name. Collection, preparation and dispatch of voucher specimens is laborious, costly and often results in considerable delays (measured in years) before naming is complete. Ethnobotanists understand this well and make a point of botanical collections to verify the identity of the plants they work with. Ethnobotanical texts (e.g. Given & Harris 1994, Martin 1994, Cotton 1996, Alexiades 1996, Elizabetsky et al.1996) emphasise the importance of voucher collection to ethnobotany. Classic ethnobotany is very much part of the work of the large botanical gardens (Kew, Missouri, New York etc.) and the direct link with herbaria ensures a high level of competence in the collection of vouchers and reliable scientific naming. There have been many NTFP studies which superficially resemble ethnobotanical methods but which do not use vouchers or verifiable naming of species. Both social and forestry orientated studies have fallen into this trap and there are studies that do not contain reliable local and scientific name matching or identities (e.g. Papadopulos & Gordon 1997, Watts et al.1996, Scott 1998). Attempts at post-hoc matching of identities is problematic and seldom reliable (see Wong 1998).

Besides the classification and use of NTFPs, local people also possess a wealth of knowledge (often termed indigenous knowledge) on the ecology, yield variation and harvesting impacts of resource species. If a management system is to based on all available knowledge then the development of a synergy between local and scientific knowledge is desirable. This often happens informally in the context of participatory or collaborative settings. However, there are instances where it can prove beneficial to make more formal representations of knowledge to permit a a deeper appreciation of the essence of the

62 knowledge held and its relationship to natural scientific investigations. Such formal systems are those described by Sinclair & Walker (1999). These systems have been demonstrated to be effective in representing three alternative farmer classifications (and therefore names) for fodder trees in Nepal (Walker & Sinclair 1998). Such methods may have applications to the understanding of the relationships between folk names, uses and autecological knowledge for NTFPs.

4.3 Demand for biometric rigour The demand for data on the abundance, growth rates and sustainability of NTFPs is intense. Whether the inventories need be statistical rigorous depends on the objectives of the assessment and the expectations and requirements of the users of the data collected. The pursuit of biometric rigour is not an end in itself but a means of producing good quality data. This means that the precision and accuracy of the results can be calculated. Precision is high when variances and consequently errors are small. Accuracy is high when the estimate of the mean calculated from the sample data is close to that of the whole population. Ideally resource assessments should be both precise and accurate. A lack of good data is a serious impediment to planning and management as noted by Temu (1995), ‘Africa in particular, has not been able to plan for rational management of its forest resources, primarily due to the lack of reliable inventories.’

There are also ethical considerations in undertaking any forest survey. Myers & Patil (1995) stress scientific ethics and comment that “it is a social wrong to be simplistic in dealing with complexity. Forest ecosystems are inherently complex and must be dealt with accordingly.” Cunningham (1996b) takes a different approach and contends that it is unethical for ethnobotanists to make recommendations which are poor. Ethics is at its most imperative when decisions that may affect the long-term survival of species and livelihoods are being taken. Carter-Lengeler & Jones (1998) expand on this ethical point and comment that the onus is on the community advisor to ensure that resource data collected by community and participatory projects is of real utility (also see Section 4.1). With the increasing interest in the extension of intellectual property rights to local knowledge there is also an increasing ethical element to the collection and use of local or indigenous knowledge (Schreckenberg pers comm., Lund 1998b).

In situations where commercialisation or new NTFP-based enterprises are being considered it is also important that decisions are based on good quality resource abundance and productivity data. It is vital to guard against decisions which may endanger the resource species and to ensure that new ventures are sustainable in at least the medium term. Although many new NTFP enterprises have been established in the past few years, few have been backed up by in-forest resource surveys let alone biometrically valid inventories. Clay (1997) depends on the opinion of non-local botanists. Gould et al.(1998) undertook a post-hoc evaluation of an existing NTFP export development which discovered that several species were unsustainably exploited by the project, and furthermore the evaluation was itself based on incomplete secondary data. Peters, Balick & Anderson (1989) makes a case for increasing the harvest and commercialisation of a number of Amazonian fruits based on data derived from very few plots. The Centre for Arid Zone Studies (1998) have prepared a useful method for examining the feasibility of sites for increased lac production but do not include a biometrically sound means of quantifying the abundance of host trees or lac insects.

Since it is inevitable that pragmatic or best-guess decisions on harvesting intensity, methods or impacts will have to be made, responsibility shifts to ensuring that sufficiently robust monitoring systems are in place to detect any adverse consequences of management in sufficient time for corrective action. These ideas have recently become to emerge in the North-west USA under the term adaptive management. The experience of developing adaptive monitoring systems by Gibbs et al. 1999 in the Galapogos and Ringold et al. 1999 in northwest USA.

Good quality data are highly sought after for third party uses but only if the protocols are sufficiently robust for the data to be representative and suitable for incorporation into other quantitative frameworks. The demand for NTFP data for use in valuation of tropical forest resources is particularly well expressed by Godoy et al.(1993). A summary of their findings is relevant to all third party use of NTFP data and is presented in Table 14. The main failings identified are a lack of standardisation and inability to

63 generalise from case studies because of failings in inventory design. They suggest methodologies that could be used in resource assessment to alleviate these problems, pointing to a need for greater biometric rigour in design, execution and reporting. Table 14 Summary of main failings of NTFP resource assessment for valuation studies

Information required Main failing Suggested methodology Data representative of forest Many studies only use one site and Ideally a sample of study sites (to allow reasons for choice not given so not calculation of variance) or failing this possible to use data for comparison presentation of reasons for site choice or generalisation Population profiles suitable Informants in anthropological studies Identification of main attributes of extractors (e.g. for generalisation not randomised and sample sizes age, technology, income). Stratified random small sampling of people in identified strata Data representative of Few studies include more than 1 Random selection of same number of weeks and seasonal pattern of NTFP years data days from each month through at least one year. use Careful examination of climate and other variable e.g. larger economy to understand representativeness of study period Quantification of product Some studies value the stock Identify, count, weigh and measure products as flows (quantities used by (inventory) which relates to neither they enter the village each day. people) present or sustainable flows Assess random sample of villages and households and either ask extractors or randomly observe and record their consumption Product weight Weights may not be measured If products too difficult to weigh in bulk, take seasonal sub-samples for mean weights Product identification Irregular use of scientific names or Collect specimens (vouchers, skulls, use of local names hinders photographs) for definitive scientific identification comparison between studies Catchment area for product Many studies do not record Direct observation, participatory mapping, travel extraction catchment area so not possible to time assessment, aerial photographs, GPS etc determine yields per ha. Sufficient observations Insufficient if reliant on single Train and use extractors to collect information or researcher undertaking all keep personal diaries (be aware of possible observations biases) Value of product Some researchers use expenditure Use prices that exist for the commodity of labour or energy as a measure of concerned or that prevail in related markets e.g. value which is not consistent with use marketed good bartered for non-market modern valuation theory product, use value of close substitute. Use contingent valuation (willingness to pay) methods Share of harvest going to Few studies have done this but it is Random sample of households asked to keep the household and to the important as household and market log books of daily income, expenses and market goods are priced differently amounts of NTFPs consumed or sold Shadow prices Important in providing an economic Adjust for taxes and subsidies that cause price rationale for NTFPs that may not be to deviate from opportunity cost of resource financially profitable Required to estimate valuation from a national viewpoint Environmental externalities No study has done this which means No suggestions made that conventional valuations underestimate economic benefits of NTFPs Marginal costs of extraction No assessment of search times, cost Interviews, direct observation (instantaneous and processing of tools etc. made for plant collection sampling, focal subject sampling), extractors (has been done for animals in diaries/records, log movements out of and into studies based on optimal-foraging village. theory) Wage rates Some researchers have used Determine what people actually pay each other. country’s official wage rate but this Note that rural wages vary by season, age, sex should not be done uncritically and type of work. Cost of capital Not often measured Use social discount rate – may be calculated Use of market rate inappropriate. locally otherwise use 4-5%. Sustainability Three views Indirect: comparison of distance, frequency and a) Indigenous people manage duration of collection forays, recall of yields over forest sustainability time etc. b) Indigenous people don’t Direct: comparisons of extraction and rates of manage sustainability reproduction/growth in the forest c) Sustainability is result of special conditions that must be identified in each case Use of plant and animal Not possible as botanists use Multi-disciplinary team comprising natural

64 Information required Main failing Suggested methodology extraction in single valuation returns per ha while zoologists use resource economist/economic anthropologist, returns per unit of labour botanist, zoologist; as well as indigenous people and local scholars (after Godoy et al. 1993)

The FAO are presently preparing guidelines for collection of NTFP resource data for incorporation into FRA2000 (Preto pers comm.). Although these guidelines are not yet complete it is clear that data will need to be vetted and graded along the lines of that done for FRA1990 (see http://www.fao.org/waicent/faoinfo/forestry/FO124E/MT2GEP51.htm). Furthermore, as demonstrated by the results of this literature review, there are relatively few studies suitable for extrapolation of national statistics on NTFP abundance available for inclusion in data compilation exercises such as FRA2000. There is increasing interest in the use of existing datasets in what is termed meta-analysis to provide strategic, regional and national overviews. Such analyses move beyond the mere compilation of data to the amalgamation of datasets and the performance of new analyses and interpretations. In the USA, this is viewed as an important new initiative in data analysis principally because it is cost effective and gives a rapid response to questions to maximise the use of existing data (Myers & Patil 1995). Obviously, for all these demands, higher quality data are preferred.

As a final point, the contribution of biometrically sound methodology can often be critical to securing political credibility for the recommendations being made and not just because strategic advice should be sound. This is particularly the case when resource exploitation is regulated by government agencies which are open to lobbying from extractive and conservation interests. Recommendations based on well- designed inventories are more likely to be indisputable and therefore implemented than those where the inventory is open to criticism. A good case study of the role of biometrics in political battles related to sustainable annual quotas is illustrated in Box 13 for Prunus africana from Mount Cameroon. Unfortunately the consequence of these procrastinations have been prolonged overcutting and the expense of yet another resource inventory. Box 13 Setting quotas for the Mount Cameroon Prunus bark harvest

Prunus africana is a tropical afro-montane tree that forms a significant proportion of the canopy in higher altitude forest on Mount Cameroon. Bark is stripped from the tree for export to Europe for the manufacture of a drug to treat prostrate cancer. Plantecam Medicam a Cameroon subsidiary of the French company Laboratoires Debat has been processing and exporting Prunus bark since 1972. The Ministry of Environment and Forestry (MINEF) regulates harvesting of bark through an annual quota and recommended harvesting practices. Best harvesting practice, removal of 50% of bark from opposing sides of the tree once every five years has been shown to be sustainable but unlicensed collectors tend to remove all bark (which kills the trees) or fell the tree thereby compromising the resource. There are grave concerns about the long term survival of the species and repeated attempts have been made to reduce the level of harvesting and promote cultivation of the species. The table below documents attempts to introduce new quotas and the role of resource assessment in the debate about sustainable harvesting levels.

Year Resource assessment Information Response ~1972 None - Quota set at 1,500 tonnes per year 1976 - Concern with over-exploitation Nursery and large scale enrichment planting started 1984-5 Forestry Dept. study for Mt Oku, Measurement of 7,717 exploited Yield per tree = 55 kg per tree Bui Division trees + 1985- Plantecam records to MINEF Total harvest of 4,478 tonnes over Average annual harvest = 448 tonnes 1995 period yr-1 1986- Plantecam records Total harvest of 11,537 tonnes Average annual harvest = 1,923 1991 over period tonnes yr-1 1987 ICBP draw attention to threat to - Partial ban on trade from Feb 1991- mountain environments posed Feb 1992

65 1991 Forestry Department Average density of trees > 20 cm d No quota set based on this inventory. 25x500 m plots at 6 subjectively = 5.5 ha-1 Results biased towards high density located sites around Mt Lack of regeneration, seedling areas and would have suggested very Cameroon density at 5 ha-1 high quotas. (sample area=45 ha) 1994 MINEF records Plantecam harvest ~ 926 tonnes Annual harvest at 1,400 tonnes and yr-1 unsustainable. Illegal harvest ~ 590 tonnes yr-1 1995 Kenya makes listing proposal Listing on CITES Appendix 2 1996 ONADEF* Average density of live trees > 30 Plantecam contend that this inventory 1% inventory for Mt Cameroon cm d = 0.76 ha-1 is ‘insufficiently intensive, inaccurate, Yield = 68 kg per tree was not completed in some areas and Annual quota = 300 tonnes per that average yields per tree are year ± 50% higher‘. Claim that ONADEF and MCP All stakeholders collaborated in biased. Plantecam lobbied for higher inventory design and verified a quota but Cross-Ministerial round table 10% subset of the inventory in the committee confirmed they were field. confident in the ONADEF quota. 1996? Plantecam records Yield per tree = 100 kg per tree Need 1,500 tonnes yr-1 nationally and 700 tonnes yr-1 from Mt Cameroon to supply factory. 1998 ‘Independent professional Independent information available Renewal of Plantecam’s licence with a forestry body’ 1999? quota of 1,500 tonnes per annum in 5% inventory commencing MINEF committed to adjusting April 1998. November future quota even if insufficient for Plantecam 1999 CITES Plants committee Representatives of Plantecam and meeting (June) MCP to attend to present alternative cases for Prunus. 2000 Trial of adaptive sampling for Prunus underway on Mount Cameroon Box 13 continued

*Office National de Développement des Forêts - Parastatal with responsibility for forest inventory + Ministry of Environment and Forestry Taken from: Acworth et al.1998, Cunningham & Mbenkum 1993, Acworth pers comm.

Notwithstanding the external demands for rigour, the extent to which statistical considerations need influence the design of any particular study is determined by the objectives set. To illustrate this point, Table 15 summarises the importance of biometric rigour to the objectives of the reviewed studies11. Three levels of need are identified. The need for rigour is highest for objectives which require quantitative data especially if this is required at the national level or for decision-making. Statistical issues are not an issue for studies which only require value judgements or can be addressed non- quantitatively. Studies with high rigour are those with formal statistically founded designs such as traditional timber inventory, medium rigour is represented by mapping studies that indicate the relative abundance of resources while low rigour could be PRA-style mapping with field verification. High rigour studies are not necessarily better than low rigour studies in the right context. The important point is that the most efficient tools are used to provide the information required by the objective. It is a waste of resources to undertake a highly detailed study when a simple participatory cruise will do.

11 These are based on the author’s personal opinions and experience and are offered to demonstrate the relationship between objectives and biometric considerations. A more complete work could be developed as a preliminary stage of biometric design guidelines.

66 Table 15 Objectives and the need for biometric rigour

Classes of Summary objectives Number Need for objectives of studies rigour Resource Quantification of NTFP resources (quantity, distribution and extent) 10 High characteristics Study of population characteristics of NTFP species (biology, habitat, demographics etc) 7 High Investigation of relationship between forest type and quantity or diversity of useful species 5 High Status of exploited population 4 Medium Study of utilisation characteristics of NTFP species (nutritional value, existence of good 3Medium ecotypes etc.) Investigation of relationship between environmental variables and productivity of useful 2Medium species (weather, seasonality etc) Description of habitat preferences of particular species 2 Medium Resource Impact of harvesting on exploited populations 12 High supply and Production potential / resource availability 7 High demand Determination of sustainable yield of products 6 High Assessment of ability of supply to meet demand 5 Low Quantification of forest utilisation 2 Medium Accessibility of product to collectors 1 Low Assessment of extent of subsistence use (hunting) 1 Low Identification of vulnerability to over-exploitation 1 Low Determination of productivity 1 High Assessment of potential ecological sustainability (using existing information) 1 None Policy/strategic National yield estimates 3 High Information Provision of quantitative data for strategic planning 2 Medium Demonstration of national importance of NTFPs 2 Medium Provision of quantitative data for policy development 1 Medium Assignment of conservation priorities for rare species and ecosystems 1 Low Assess contribution of NTFP collection to forest conservation 1 Low Monitoring Provision of baseline data for future monitoring 2 High Re-current inventory 2 High Monitoring of extraction 1 Medium Statutory monitoring 1 High Social aspects Involvement of local people in protected area management 2 Low Contribution of NTFPs to socio-economic development 1 Medium Overview of land use patterns 1 Medium To secure tenure and land and rights to resources 1 High Assessment of impact of creation of protected area on local community NTFP activities and 1Medium economy Analysis of hunters game choice 1 Low Collection of quantitative data on local food preferences 1 Low Economics Provision of data for economic valuation of forest 2 Medium /valuation Economics of sustainable extraction 2 High Valuation of resources for compensation 1 High Costs of implementing sustainable use 1 Medium Documentation of economic aspects of exploitation of particular species 1 Medium Management Provision of data as a basis for sustainable management of harvesting activities 6 Medium Impact of non-NTFP activities / forest management practices on NTFPs (logging, grazing) 3 Medium Determination of management options for NTFPs 3 High Integration of NTFP production with natural timber production management 2 Medium Impacts of alternative management schemes on NTFPs 2 Medium Predict possible population changes due to heavy exploitation 1 High Methodological Development of NTFP enumeration protocols (plot size, use of aerial photography etc.) 8 High development Development of participatory survey/inventory/monitoring methods 3 High Development of methods to assess sustainability of NTFP extraction 1 High Development of methodology to assess feasibility of community management 1 Medium Test protocol to quantify environment/productivity relationships 1 High Listing of Collection of indigenous botanical knowledge (medicinal / general uses) 4 Low NTFPs List of products for potential commercial exploitation 1 Low

4.4 Elements of a biometrically sound resource assessment Biometric rigour in resource assessment is not simply a matter of quantifying findings but of satisfying certain statistical principles in the design of the data collection exercise. For the purpose of this study four standards have been identified against which the reviewed studies were evaluated. These are; randomisation, replication and independence of observations. Since it is impossible to judge a study in

67 the absence of a report of the protocols used the fourth standard is whether a study is adequately reported. Randomisation – the distribution of plots should be objectively determined according to rules. The aim is to use rules in which all individuals in the target population have an equal chance of being selected or that the probability of an individual occurring in the sample is known. This is fulfilled best in randomised designs where plots are selected according to random number tables. Randomisation is intended to avoid bias in the results and while systematic designs based on grids could be biased (grid locations may align with some regular feature of the landscape or species distribution pattern) they can be used successfully with a random origin and careful search for possible sources of bias. Systematic sampling provides a regular distribution of observations which is a better basis for mapping than random samples and is often chosen over random sampling for this reason. The deliberate choice of plot locations in areas subjectively deemed to be representative is not acceptable, nor are haphazard plot selection techniques such as throwing a quadrat over ones’ shoulder.

Replication – there needs to be a number of plots in a study, strata, site, or size class for the calculation of errors and determination of the representativeness of the results. The actual number of replicates needed is difficult to determine without (a) some idea of the precision required (usually expressed as a percent sampling error e.g. wanting the estimate of the mean to be within 10% of the true value), (b) some information on the variability of the resource and (c) the costs of enumerating each plot. There are several methods for determining the optimal number of replicates, most of which try to determine the number of plots required to achieve a target sampling precision preferably using a variance derived from a pilot study (see forestry texts such as Boon 1963, Freese 1984, Shiver & Borders 1996, Sheil 1998 and other texts listed in Appendix 4). Variance-mean relationships which approximate a power law (Taylor 1961) can also be used to estimate the number of observations required to achieve a target sampling precision (Burn pers comm.). There are a few NTFP studies, notably for rattan which use these sample size optimising methods (see Section 3.6.5 above). It is difficult to be prescriptive about the number of replicates required. Sheil (1998) presents a useful guide to the types of testable hypotheses, a selection of test procedures and an indication of the number of observations required. In general, four to six observations are the minimum number for each population being compared.

Independence – there should be no association between separate observations. This means that plots should be sufficiently far apart so that the presence or absence of the target species in one will not influence the probability of the species occurring in any other plot. This means that plots should not touch (edge trees will be in both and the presence of a large tree in one could influence the presence or absence of saplings in the contiguous plot).

Protocols – all the pertinent design features of a study need to be reported in sufficient detail to judge whether the study fulfils the biometric criteria given above. The reported protocols should also be sufficiently detailed to permit a third party to repeat the study.

Data derived from a biometrically robust study can be used to calculate unbiased estimates of means etc. with sampling errors. This can then lead to other statistical hypothesis testing of differences between sites, harvesting techniques etc.. However, care should still be taken to ensure that comparative tests are only performed on statistically comparable samples.

4.5 Biometric evaluation of reviewed studies This section reviews the performance of the studies listed in Appendix 4 against the biometric criteria outlined above. The review only considers the biometric characteristics of a study NOT its overall merit nor attempts to judge whether any particular study used appropriate methods or achieved its objectives.

The review includes a wide range of studies from different disciplines and for diverse objectives. For several categories statistical rigour is less of a concern or is outside the scope of the present review i.e. are econometric rather than biometric. The evaluation therefore was only undertaken on a sub-set of 97

68 of the studies covering five types of study (resource species demography; harvesting impact and experimental harvesting; inventory; monitoring and yield studies).

4.5.1 Reporting of protocols Resource surveys are comparatively expensive and there are relatively few opportunities to collect in- forest data and good quality data are often sought by third party researchers and statisticians for use in other studies. However, before data can be used they first need to be documented in sufficient detail to permit an evaluation of their suitability for alternative uses and also to permit others to learn from the methodology and replicate the study elsewhere. Publication of protocols to permit replication of a study is an established standard for scientific reporting.

The present work required that information on the sampling design, plot dimensions and number and enumeration techniques be available for evaluation. Unfortunately, it was discovered that many reports and papers, even in peer reviewed journals, had insufficiently detailed protocols to enable a satisfactory review of the biometric qualities of the study.

Of the 97 studies, 14 (14.4 %) did not give any details of how plots were located. In the absence of more detailed information the only recourse is to assume that the studies were to some extent subjective in nature and consequently not biometrically rigorous.

In 25 studies (25.8 %), although the authors were obviously describing a quantitative plot-based study, the number of plots was not given. In several reports this is excusable as the design is systematic and the distance between plots and the sampling intensity is given. However, some of these reports sometimes omit to report either the plot area sampled or inventoried area so it is still not possible to derive the number of plots used. For example, a typical paper states that ‘Transects were ten metres wide and up to 1000 m long. Ten hectares were sampled in deciduous forest, 4 ha in scrub forest and 2 ha in shola forest.’ Although this is obviously a formal inventory it is not clear how many transects were used in each forest type, nor how they were located.

Altogether only 60 of the 97 papers (61.8 %) gave sufficient information to determine how plots were located and gave the number that were enumerated.

4.5.2 Sampling design – randomisation The range of sampling designs used in the reviewed studies are listed in Table 16. The first four listed are standard biometric designs which pose few statistical difficulties. The experimental designs were used in studies of alternative harvesting regimes or intensities and are blocked as replicates of treatments on a small number of sites (e.g. Rock 1996). Table 16 NTFP sampling designs in reviewed studies

Design Number % of studies* Census 5 6.0 Random 18 21.7 Systematic 24 28.9 Experimental designs 3 3.6 Stratified 21 25.3 Subjective 18 21.7 Opportunistic 11 13.2 * Percent of the 83 studies which reported sampling designs. Note percentages do not add to 100 as many studied compbined designs i.e. stratified random etc.

Stratified designs are those where the area or population of interest is divided into a priori sub- populations which are then sampled separately either for the purpose of comparison or to improve overall sampling efficiency. Stratified designs always require a second-stage sampling method such as random sampling within the strata. Many of the studies classified as having stratified designs are actually studies on two contrasting sites rather than on formally defined strata (e.g. from remote sensing interpretation).

69 Text books generally make much of the desirability of random designs but they are often deemed impractical in the large, difficult and poorly mapped terrains of tropical forests. Random designs are most often used within smaller scale study sites where locating the plots is not such a big issue. They are also used to select individuals for monitoring or yield measurement from the sampled population.

The preference in tropical forests is to use systematic designs as they reportedly can make it easier and cheaper to locate plots, have advantages for mapping and are easy to learn. Many systematic designs are used by default in MRI in which NTFPs have been added to a timber inventory (i.e. as in Wong 1998 and Dunn et al.1994). Systematic designs have theoretical statistical problems but are generally viewed as acceptable as long as steps are taken to ensure that there are no underlying periodicities in the populations (Cochran 1977, Shiver & Borders 1996).

A relatively large proportion of the studies used plots that had been subjectively located. Several forest inventory texts mention subjective or selective sampling but mostly as a method to avoid, since the accuracy of estimates is unknown, as no valid variance and therefore no confidence interval can be calculated. However, Sheil (1995, 1998) lists a few exceptions when subjective sampling can be efficient; these include species detection (e.g. in biodiversity inventory, Stork & Davies 1996), to determine the correlation between obviously different sites, quick descriptive surveys and for the siting of a small number of expensive PSP plots. Species detection was the objective in classic ethnobotanical studies where a single plot was sited in ‘representative’ forest. Unfortunately,the use of the single plot has been extended to ‘quantitative’ studies by ethnobotanists where this design is less than ideal. In the reviewed studies, four justifications for the use of subjective plot designs can be discerned. Each has its merits, but the end result is that all yield data is of doubtful representativeness, i.e. only representative of the plot itself, and should therefore not be used for generalisations, extrapolation or between study comparisons. It will also be of limited usefulness to third party researchers.

Martin (1994) argues that one plot per strata should be used to minimise costs and that it should be placed so as to be ‘representative’ of the area of study. Shiver & Borders (1996) mention that this was the reasoning used for the use of selective plots in early (pre 19th century) forest inventory and that the accuracy of the estimates depended on the skill of the cruiser choosing the plot locations.

Other studies chose sites based on local information of occurrence of the target species (e.g. a dense stand of rattan, Stockdale 1994) or stands exhibiting particular characteristics (e.g. Peters 1996b, chose a site where local information indicated unusual annual fruiting of illipe trees). Peters & Hammond (1990) located sample populations through interviews and exploration, while site selection was based on distribution & abundance, distance to town, accessibility and probability of logging. Given that many species are widely scattered throughout the forest and studies have limited resources, using local knowledge to find suitable study sites is only sensible. If plots are located objectively (random, systematic etc.) within the chosen site then the data can be deemed representative of that type of site (e.g. Sullivan et al.1995). However, most studies which report using local information for site choice do not give details of the sampling strategy used within the sites so it has to be presumed that these were also subjective.

Terrain and access problems at a site can contrive to make use of randomly located plots so problematic that a form of ‘blind’ subjective plot location is sometimes used. For example, Pilz et al.(1998) chose plots for ease of access but at a time when the mushrooms they were sampling were not visible so there was no prior knowledge of whether mushrooms were present or their abundance. Although this is a good compromise in that there will be no subjective bias towards higher densities of mushrooms, it is quite possible that sites with easier access will not be representative of the whole forest (for example, such sites may experience heavier picking pressure).

Gunatilleke & Gunatilleke (1985, 1993) subjectively located plots within strata defined from remote sensing in order to minimise within-plot topographic heterogeneity; in other words, the plots were chosen so that they did not cross topographic boundaries. This is highly subjective and likely to be biased.

70 The term ‘opportunistic’ has been used to describe samples which are selected by virtue of being visible either because they are the only sites known or because they are adjacent to an access route. There are three studies that used trails as the sampling framework, one is a bird survey (Silva & Strahl 1991) which used the trails as line-transects, one is for saplings (Peham 1996) which placed plots along the trail and one was used to locate palms growing alongside footpaths within 10 minutes walk of habitation (Pinard 1993). Such methods do not subjectively select the population to be sampled on the basis of a visual appraisal of representativeness but nonetheless are likely to be biased.

4.5.3 Plot configuration - independence Good sampling designs should endeavour to ensure that observations are independent of each other. This involves both careful plot distribution and configuration.

Theoretically, systematic samples are not independent as each observation is fixed once the location of the first plot is determined. However, a systematic collection of plots can be viewed as one large cluster sample (Thompson 1992) which suggests that means can be calculated within the cluster (presumably more than one cluster should be used though this is rarely done). Furthermore, unless there is some periodicity or trends in the area being sampled the normally large distances between plots (1-7 km) means that there is little chance that there will be little correlation between plots which can be viewed as independent. The closer plots are to each other the greater the chance of correlation.

Cluster sampling has the characteristic that each plot is made up of a number of component sub-plots. The data from each sub-plot are not independent, thus the data from the sub-plots should be amalgamated and the mean used as a single datum for the plot. Many plots are divided into sub-plots for a variety of reasons, from easing the task of booking to facilitating enumeration of smaller individuals in the population. In the case of several, nested sub-plots they should be treated as clusters whether they be located systematically or randomly and the data analysed accordingly. Often large plots are regularly divided into smaller contiguous sub-plots; in this case the subdivisions are usually made for logistical reasons and the plot datum is the sum of the observations in each sub-plot. In such cases it is not strictly acceptable to use the sub-plots as if they were independent (i.e. in post-stratification), though this is often done. Post-stratification groups sub-plots of similar character and then performs an analysis of the grouped sub-plots and does not attempt to investigate the differences between contiguous sub-plots. However, there are examples of analyses that have been done on contiguous sub-plots as if they were independent. Contiguous plots can never be independent as the existence of an individual in one plot will influence the occurrence or absence of individuals in the next plot. There is therefore a high degree of correlation between them which violates the basic assumption of independence behind most statistical tests and calculations. However, this has been overlooked by several researchers who have performed analyses on what are essentially contiguous sub-plots of a single plot12.

Several of the studies on optimal plot shapes and sizes also fall into the trap of not considering correlation between contiguous plots. The studies by Tandug (1978), Stockdale & Wright (1996) and Laurance et al.(1998) all form plots of different shapes and sizes from a grid of small sub-plots in such a way that the plots thus formed are contiguous. Such plots may be correlated so that what appears to be

12 The most extreme example of this is the study by Phillips et al. (1994) where mean data from 20 x 50 m sub- plots in single 1 ha plots was used to test for differences between forest types (presumably to gain enough observations for statistical testing). In order to test whether sub-plots could be used as independent samples the similarity of use-values between sub-plots was tested. The difference between each pair of sub-plots was calculated and assigned to four proximity classes (from adjacent to 40 m separation). The differences between sub-plots was then tested using the Kruskall-Wallis non-parametric test. This revealed that there was little difference in the similarity between sub-plots in the four proximity classes except in three of the seven plots where a slight decrease in similarity with distance was detected. These results were interpreted as demonstrating that the sub-plots were essentially independent which was expected as the plots were ‘chosen to include a reasonably homogeneous and representative sample of the forest distinct forest type’. However, an alternative interpretation would be that the sub-plots were highly correlated and not independent.

71 the optimal plot size and shape (that which minimises between plot variance) could be influenced by underlying clumping patterns in the population being sampled.

Some of the confusion seems to have originated from a misunderstanding of the distinction between plots and sub-plots. For example, several studies report replicated plots which are, on closer examination, contiguous, and therefore should strictly be regarded as sub-plots of a single plot (e.g. plots for Spondias mombin as used by Peters & Hammond 1990). These misconceptions have been perpetuated through texts such as those by Peters (1994, 1996a, 1996c) and Stockdale & Corbett (1999). The latter recommends that 10 x 500 m plots be divided into 10 x 100 m subplots and that these ‘plots’ be placed end-to-end along a transect line. Obviously correlation between strip plots placed end-to-end is at a minimum but should not be ignored. The design as described is actually a transect divided into regular 10 x 100 m sections and should be more properly analysed as a variable length transect (see de Vries 1986). Alternatively, the plots (either 10 x 500 m or 10 x 100 m) could be spaced along the transect to give a grid arrangement which would make computation of means and other statistics simple.

For the record, in the 93 studies that gave plot sizes and shapes the most popular plot shapes are given in Table 17 below. Of the measured area plots the most popular size was 1 ha arranged either as squares, rectangles or strips. Table 17 Plot configurations in reviewed studies

Plot shape Number Comments Arealess 1 Circular 6 Household 1 Households taken from village usually for interview s Square 18 Rectangular 14 Length greater than width but not excessively so Strip 8 Long, thin plot of pre-determined length Transect 7 Fixed width and variable length Line transect 7 No width or variable width and variable length Line plot 3 Plots spaced along a line Cluster 6 Groups of plots at a sample location or ‘plot’ Compartment 3 Forestry management units People 5 Individual plants 2 Trees etc. selected from sample for measurement of yield or growth Torus 1 Arrangment of strips around a square Timed 1 Days 3 Days on which observations made i.e. as in hunter diaries Interviews 1 Interview occasions – maybe with the same people Net hunt trips 1 Informal cruise 2

4.5.4 Number of observations - replication Table 18 illustrates the number of studies of various types that reported a range of plot replicates used. There is a marked bimodal distribution in the overall numbers of replicates used with few studies using 40-100 plots. This is a reflection of the low numbers of replicates used in certain types of study (i.e. those with experimental designs) and the local scale of many of the studies (cf Table 4). Most studies with large numbers of replicates are national or regional in scope and are generally resource inventories or social surveys (e.g. household survey in the Czech Republic, Sisak 1998).

72 Table 18 Number of plot replicates in reviewed studies Number of plots reported Total Type of study 1 2-19 20-39 40-59 60-79 80-99 100- >500 Many 499 Demographic 3 1 1 2 7 Ethnobotany 3 2 1 1 7 Experimental 2 1 1 4 Harvesting 3 1 1 5 Inventory 1 10 6 1 6 6 6 36 Market 1 1 2 Methodology 1 3 2 1 1 8 Monitoring 1 5 1 1 8 Social 112 Yield 2 6 1 2 11 Total 11 33 12 3 1 1 11 10 8 90

Of the 111 studies of the types listed in Table 18, only 79 (71.2 %) quote the actual number of plots enumerated. Of these, 13.5 % used single plots and only 24.6 % used more than 100 plots (Table 18). Poor reporting of protocols meant that 8.2 % of the reports that obviously had adequate replication (‘Many’ in Table 18) did not quote the number of plots enumerated, causing the proportion of well replicated studies to be underestimated. Nevertheless, the relatively large number of studies based on single plots suggests that there are a significant proportion of NTFP researchers who are either unaware of, or disregard biometric principles in sample design.

Studies that use single plots are typically undertaken by ethnobotanists where the use of single, 1 ha plots is standard and recommended by leading, recent texts (Cotton 1996, Martin 1994, Peters 1994, Peters 1996a, Peters 1996c). The reliance on single plots probably results from early use of species-area curves in botanical survey to determine the optimal area for collections which showed that 1 ha was generally sufficient to capture most of the flora of a region. Within the discipline and for the purpose of describing a general flora such designs have their place. However, it is when such protocols are used as the basis of collecting other data for ecological or management purposes that problems arise. Often such plots are located subjectively to ‘represent’ a type of forest or species (in oligarchic stands) but the degree of representativeness is rarely tested. Stohlgren (1995) reported that a single 1 ha or even 3 ha plot cannot be used to characterise even small groves of 55-80 ha of Sequoiadendron giganteum. This was because the centre of the groves had different structural properties to the periphery. He therefore concluded that reference plots may contribute to knowledge of a particular micro-site but would not greatly add to general knowledge of landscape ecology. Sheil (1997) emphasised that objective methods always require replication. Wilson (pers comm.) suggests that many studies do not properly consider replication at the highest levels of a sampling frame e.g. in a regional project only one or two countries may be selected for study and these are often chosen subjectively rather than objectively.

4.6 Overview Table 19 illustrates the overall performance of the various types of study with regard to their biometric qualities. The judgement of the quality of the reported protocols and biometrics were made on the basis of two criteria; use of random or systematic designs and the use of more than one replicate. Table 19 illustrates both the dangers of opportunistic sampling and low replication – the fact that two papers that referred to satellite image interpretation did not report the protocols used in ground truthing should not be interpreted as meaning that all satellite image interpretation papers would do the same thing. However, this is the inference from many of the NTFP studies with few replicates.

73 Table 19 Biometric qualities of reviewed studies

Study type Studies Protocols Biometrically Comments reported (%) ‘good’ (%) Biodiversity 3 66 0 Often subjective but justifiable? Demographic 9 44 22 Often based on single study plots or stands Ethnobotany 10 50 20 Including quantitative ethnobotany Experiments 5 80 80 Insufficient replication of treatments Harvesting studies 5 80 60 Insufficient replication of treatments Resource inventory 42 69 57 Insufficient plots Mapping 3 0 33 Biometric sampling not a major concern? Market studies 2 50 0 Econometric not biometric criteria apply Methodology 11 64 55 Problems with contiguous sub-plots Monitoring 12 50 25 Different biometric criteria also apply Rapid assesment 1 100 0 Rapidity and rigour not compatible Remote sensing 2 0 0 Did not report protocol for ground truthing Use of secondary data 6 10 17 Did not report protocols for original dataset Social surveys 2 50 50 Sociometric not biometric criteria apply Yield studies 13 46 8 Subjective selection of sample individuals TOTAL 126 56 38

Perhaps the most pressing concern in Table 19 is the observation that 43 % of reviewed resource inventories and 90 % of yield studies fail to report protocols or have design failings so that it is difficult to generalise from their results. These are both areas which are intended to provide sound data to inform management decisions and have much reduced credability if this is not achieved.

As a final point the review revealed that there are several developments across the natural sciences that are applicable to NTFPs but are not yet widely used. For example, in geography, the new field of landscape ecology is described as an emerging science that seeks to investigate ecological processes on large spatial scales (landscapes) in a holistic manner that includes socio-economic perspectives (Farina 1998). Within this field the use of a spatial framework for ecological study permits the integration of geobotany, island theory, hierarchy theory, metapopulation models and source-sink models in the study of human interaction with the natural environment. The GIS model-based study of hunting impact on babirusa in Sulawesi (Clayton et al 1997) demonstrates what is possible with these technologies. There is a need to search widely through the natural sciences for methods that may by applicable to NTFPs.

74 5. Designing biometrically rigorous NTFP resource assessments Earlier sections of this paper report on current practice in NTFP assessment. Consideration of the range of methods in use for NTFPs (see Table 9) reveals that there are too few examples to be able to judge the appropriateness or efficiency of methods for more than a limited group of plant products (trees, palms, bamboo and rattans). The review indicates that there are few methods that could be proposed for adoption as generic methods. This is principally because of the problems of replication and subjectivity highlighted above. The statistically sound methods developed for rattans and bamboos have been based on forest inventory techniques and have not been optimised for use with non-tree species other than changes to the size of the sub-plot and enumerated characters. ‘Useful’ (=hunted) animal censuses have focused on mammals and there are several good examples of the use of line-transect methods which are biometrically sound (e.g. White 1994, Bodmer 1995). Caughley & Sinclair (1994) give advice on the choice and application of a range of sampling methods for wildlife management but the review turned up few examples of the practical application of many of these methods in tropical forests. On balance it seems that there is insufficient understanding of the performance of different assessment techniques in the field for authoritative statements on the appropriateness of any technique over another to be made. Further work is required to develop and test a range of generic assessment protocols which could then be adaptated to local conditions.

Notwithstanding the comments above, there are a number of researchers who are developing systems for assisting in the selection of appropriate techniques. Sheil (1995) has developed a table indicating suggested methodologies for different plant populations and levels of sophistication required. Brown & Sheil (Brown pers comm., Healey 1998) have proposed that a computer-based decision-tree system would be an appopriate means to provide advice on the selection of appropriate assessment techniques. The remainder of this section is concerned with developing a draft framework to support the design of NTFP inventory methodology.

The problem can be simplified to; • how to determine what needs to be known, and • the choice of the most efficient method to obtain the data.

5.1 Using objectives to design resource assessments An early stage in any resource assessment should be the production of a clear and concise statement of the objectives’ context and direction for the study. Most of the 126 studies in the review have two or more objectives. These are often hierarchical with a general purpose for the study under which are more specific objectives for the inventory itself. Ideally, specific objectives should include a statement of the required accuracy of the results i.e. ‘determine the volume of harvestable bark per ha ± 20 %’.

Ideally the objectives together with the priorities, resources and constraints should define the survey strategy to be used (Sheil 1995, 1998). For example, the objective ‘to determine stocking levels of product x in forest y’ will lead to quite different sampling designs under different financial or skill constraints. Where funding is low and skill constraints are present the approach, required will be different from a study which has access to funding and a priority to provide estimates within 20 % sampling error for informing strategic planning. Generally more accurate assessments require higher levels of funding and skills. A structure for the selection of NTFP inventory methods has been envisaged (Healey 1998) as possibly containing the following elements: - the purpose of the inventory (for whom, for conservation, sustainable management etc.), - the NTFP information-need to meet this purpose (distribution, density, size class distribution etc.), - the current status of the NTFP (distribution, level of threat), - level of recorded indigenous knowledge (IK) for the NTFP, - level of unrecorded IK about the NTFP, - time available, - funds available,

75 - level of technical expertise and of local expertise available for the inventory.

Although the classical approach to inventory design requires an explicit statement of objectives as a basis for inventory design, most textbooks do not provide much guidance on how to make these links. This is particularly a concern when wide identification and ownership of the inventory and results is all important e.g. as in community inventory (Schreckenberg pers comm.). A full consideration of all of these elements of inventory design are beyond the scope of the present paper. There are, however, a small number of techniques that have been developed to assist the process of designing an inventory which are presented for consideration.

Myers & Shelton (1980) developed a detailed semi-quantitative and participatory approach to survey design. This advocated as a first step deciding on the users of the information and ended with designing reports and outputs that would communicate results efficiently to these users (see Box 14). Although Myers & Shelton’s system was developed for the USA Forest Service, its emphasis on participation and dissemination of outputs accords with developments in participatory resource assessment (Carter 1996), and the sympathetic delivery of results to local people (Shanley et al. 1996, Shanley 1998). There may be potential for this methodology to be adapted for use in participatory resource assessment with the addition of an evaluation of the skills/training needs for specific methods. Box 14 Formal consultative approach to the survey planning process

Step 1- Determine who the users are. Step 2- Obtain from each user (using participatory methods e.g. consultations and review meetings to set importance values) a clear specification of objectives; also information needed to satisfy objectives with some sort of priority rating including required limits of accuracy. Develop objectives-needs table to deal with interaction between management objectives, information needs and priorities in a quantified and consistent manner. Example Objectives-Needs Table for impoundment project Objectives Prepare construction Prepare environmental plan impact statement % importance: 80 20 Information need Importance index (%) Topographic maps 70 30 62 Soil maps 25 10 22 Vegetation maps 0 25 5 Animal census 0 25 5 Airphotos 5 10 6 100 100 100 Importance index = (70 x 80) + (30 x 20) = 5600 + 600 = 62% for topographic maps 100 100 Step 3 Consider where data can come from e.g. existing data, remote sensing, field surveys. Design field surveys to meet specific information needs at required accuracy levels. Step 4 Develop needs-methods table to assist in the selection of survey methods to be used. Example Needs-Methods Table for impoundment project Information Priority Survey methods Needs of need A B C D B,C & D Topographic maps 62 62 62 62 Soil maps 22 22 22 22 Vegetation maps 5 5 5 5 Animal census 5 5 5 5 Airphotos 6 6 6 Effectiveness 94 62 32 6 100 Cost 2000 1000 500 50 1550 Cost/effectiveness 21.3 16.1 15.6 8.3 15.5 Letters used instead of actual methods which could be field survey, air photo interpretation etc. Step 5 Design outputs Consider the users and plan for different types of data presentation: maps, tabulations, distribution graphs, statistical summaries, statistical expressions for relationships between variables. Offer users a choice of output formats and allow them to have a say in what these choices will be. Written guidebooks to the interpretation of available products are essential. (Myers & Shelton 1980)

76 Schreuder (1995) focuses on the particular problem of determining the optimal sampling strategy. Standard inventory texts provide a plethora of techniques for comparing the cost-efficiency but the decision to use a particular design is also informed by a range of other factors. Schreuder (1995) tackles this bigger problem using a simple linear decision model. The model works by weighting a range of factors for alternative designs and comparing total scores with the optimal design having the highest overall score. The weights used are 1 or 0 depending on whether the design under consideration would be relevant to each factor. In the final analysis it is not always the most sophisticated or biometrically rigorous methodology that is chosen. Table 20 lists the sampling factors considered by Schreuder (1995) and illustrates how they affect the need for biometric rigour. Table 20 Decision model for assessing biometric rigour required in inventory design

Factor Rigour required More important Less important Number of objectives Many Few Type of objectives Broad Narrow User group understanding Critical Not critical Scientific defensibility Yes No Need for continuity Critical Not critical Need for renewal i.e. start Critical not critical from the beginning Political defensibility Yes No (Schreuder 1995)

The model can be tailored for specific projects by adding or subtracting factors and modifying weights. Although the use of such models may only give the same answer that would be arrived at intuitively it does provide a standardised and transparent vehicle for recording decisions.

Stohlgren (1995) introduces the GOSSIP framework for planning of long-term landscape-scale studies. GOSSIP is Goals, Objectives, Scale, Sampling design, Intensity of sampling and Pattern of sampling. The framework is used to guide the inventory planner through the various stages of decision-making to arrive at an optimal design for a particular study, and is not as quantitative as Myers & Shelton (1980) or Schreuder’s (1995) methods. Sheil (1998), Stockdale & Corbett (1999), Lund (1998b), Sutherland (1996) and Poffenberger et al.(1992) also provide useful descriptive summaries and checklists of the stages involved in inventory design.

The sampling design used for a specific study depends to a large extent on who is advising the inventory (Carter-Lengeler & Jones 1998). Foresters have a predilection for systematic plots, social development people lean towards PRA mapping and household surveys while botanists take lots of vouchers but in general do not enumerate population levels etc.. Each draws on their experience and specialism to address the question of NTFP assessment. At present there is no common language for quickly and unambiguously communicating the type of assessment that has been undertaken with some terms such as ‘inventory’ having quite different inter-disciplinary interpretations. If the various strands of NTFP resource assessment are to coalesce, it is necessary for there to be some generally accepted classification of objectives and statistical interpretation of key terms and issues along the lines proposed by Sheil (1995, 1998) for biodiversity studies.

5.2 NTFP typology for inventory design An inventory design has to fit the purpose of the inventory. In many textbooks the description of purposes forms the main framework for designing appropriate inventory (see Sheil 1998 for a discussion of biodiversity inventory purposes). However, for NTFPs this paper considers only a rather limited set of purposes aimed at the assessment of abundance and distribution of selected NTFP species for the purposes of making management decisions on sustainable utilisation, In this case variation in methods depends upon the species selected for exploitation. Therefore it is features of the species distribution, size and life-history which have the most influence on the choice of methods. Any framework to guide the

77 design process therefore needs to be based on species characteristics. The typology developed in this section therefore illustrates how species population characters influence the choice of inventory design.

A number of biological characteristics exist which have a bearing on inventory design and that need to be considered. Foremost among these are: the life-form of the resource - tree, fungi, bird, rattan etc. seasonality, whether a part or the whole of the resource is harvested, whether harvesting is fatal or not, motility - different techniques are required for motile and sessile resources, the distribution of the resources - scale of dispersal.

Life-form is perhaps the most obvious feature and has been used as the basis for most NTFP typologies. However, life-form affinities alone do not always help identify the most appropriate methods for derived products. For example, it might be imagined that all birds, being motile, would require similar techniques. However, this would be inadequate for enumeration of, for example, cave-dwelling birds’ nests (linings used as ‘birds nest soup’) or young parrots which are non-motile which may require techniques more familiar to plant biologists. Indeed, plot-based methods similar to those for plants were used to inventory Mopane worms although these are the caterpillars of a motile moth (Munthali & Mughogho 1992). Thus it is important to consider the characteristics of the life-stage or product, where this may be relevant. Similar considerations for plants are the need for different enumeration techniques for various plant parts in order to estimate the yield of particular products. The enumeration of very diverse products suggests the development of a hierarchical typology, with each life form sub-divided by the parts that are used. For example, a group for shrubs would need to be divided into fruit, bark, stems, leaves, root etc. and an appropriate methodology devised for each. However, it is likely that protocols for fruit would be much the same across a range of life-forms, e.g. palms, lianas, shrubs, trees etc. which would result in a lot of redundancy in the typology. One solution to this problem would be to develop parallel typologies for life-forms and parts used. Thus one could choose an appropriate method for estimating, for example, liana population density and then select an effective method to measure, say, bark yields.

Life and growth-form affinities are most relevant to decisions about enumeration of sampled individuals. This is demonstrated by the few studies which have undertaken multi-species inventories. These studies (see Appendix 3F) devised groupings of species according to life-form for the purposes of enumeration, analysis and presentation of results. Each group had different enumeration protocols. For example, in the Ghana inventory, herbs were recorded as presence/absence while the numbers of rattan stems and clumps in a range of sizes were counted (Wong 1998). Similarly, FitzGibbon et al.(1995) in Kenya counted primate classes within earshot of the transect and counted duiker droppings within 1m either side of the line. Although these studies were usually working within the confines of a MRI (see above) each used a single plot configuration and the same sampling design for all groups. However, it is clear that the concept of a ‘plot’ is quite different for the plants on the Ghana inventory (20 x 500 m plot) and animals in Kenya (repeated use of 1 km transects for timed walks and trapping etc.). This suggests that life-form, especially the distinction between animals and plants is relevant to plot layout as well as species enumeration and product yield.

The choice of sampling design depends more on the distribution of the population than its life-form per se. This is acknowledged by Sheil (1998) who points out that different designs are best for different types of distributions and also implicit in the development of specific protocols for particular distributions e.g. guided transect sampling for sparce distributions (Ståhl et al. 2000). Nur Supardi (1993) also mentions that for rattans one needs to know the distribution patterns of the species before the sampling design, intensity or the shape and size of samples can be determined.

78 At the plot level Freese (1974) distinguishes between the ‘unit’ on which the observation is made and the ‘value’ being the characteristic measured on each unit. For example, in a study of fruit availability, the trees would be the units while fruit weight would be the value to be measured for each tree.

Different characteristics of the target population have a bearing on decisions and design features at each level of the inventory design. Population density and distribution has a bearing on sampling design, the life-form and size of the target species are relevant to plot layout and population density, while the harvested part of the species used determines how yield is measured.

Putting all of these strands together suggests that there are specific characteristics of the resources under investigation that should inform different elements of the inventory protocol. A suggested framework to guide inventory design is given in Table 21 below for consideration. Table 21 Framework for NTFP inventory design

Inventory design Protocol for: Relevant target characteristic element Sampling design Plot number and spatial or Spatial distribution of population temporal pattern Plot layout Size and shape of plot Life form e.g. tree, bird, fungi etc. Population Means of quantifying abundance Growth form e.g. clonal, diffuse or enumeration discrete organism Product quantification Measurment of product yield Part of organism exploited e.g. resin, leaves, stem, meat etc.

The four elements in Table 20 are spatially nested (distributions are larger than individuals which are larger than the product being exploited), but generally decisions at each level can be considered to some extent as being independent of other levels. For example, the decision to use simple random sampling does not have a bearing on whether the ‘plot’ should be square or a 30 minute listening period, and neither may have any relevance to the measurement of the individuals in the plot i.e. whether tree diameter or relative cover of herbs is measured.

5.3 Sampling design There are a great range of alternative sampling designs each of which has advantages and disadvantages. The problem facing most inventory designers is the selection of the most efficient and appropriate design for the particular product under investigation. If the population distribution is taken as being relevant to these choices then what is required is an indication of which designs are best for different types of distribution. Table 22 illustrates a range of population distributions common in NTFPs and suggested sampling designs.

Table 22 includes Adaptive Cluster Sampling (ACS) and Rank Set Sampling (RSS) which are new techniques which theoretically provide significant advantages over the more traditional methods for NTFPs. A brief description of the features and potential merits of ACS and RSS is given in Appendix 7. There has been some interest in the use of RSS for NTFPs (Myers & Patil 1995) and ACS for biodiversity inventory (Sheil 1998). Pilz et al.(1996b) considered using ACS for mushroom monitoring but report that there were too many problems with trampling of potential plots and locating plots in difficult terrain made it impractical in mountainous temperate forest (Pilz pers comm.). There has been substantial theoretical development of ACS (Seber & Thompson 1994, Thompson & Seber 1994, Thompson 1991, 1992, 1997) but only one on-going study that has attempted to apply it to tropical forest environments (Acworth pers comm., Underwood 2000). RSS is less well developed and would require theoretical development as well as application to NTFP problems.

79 Table 22 Sampling design and population characteristics

Characteristics Key sampling design considerations Populations within small Census or 100% enumeration (=stock survey), particularly if mapping is also required. study area Abundant Sampling needs to be efficient and cost-effective - Perform pilot study or obtain data from previous study in order to determine optimum number of plots for required precision. • Random populations – use estimate of population variance to determine optimum sample size • Non-random populations – use variance/mean relationship to determine optimum sample size (e.g. using Taylor’s power law) Rare Problem acquiring sufficient observations of target organism • ACS with initial systematic sample • Sequential sampling (set target number of observations and sample until this is met) • Double or two-phase sampling – stratified sampling using knowledge of species distribution obtained from initial survey to define strata -sampling may be proportional to estimated density in strata i.e. more plots in strata containing target species • Guided transect sampling • Gradsect sampling (efficient means of finding populations) • Sample for index of population abundance (e.g. available habitat etc.) • High sampling intensity (e.g. 25% recommended for rattans) High small scale Need to sample sufficient plots close together to characterise small scale as well as larger scale variability variability (~10 m) • RSS • Two-stage SRS or systematic sampling (sampling of subplots within plots) • Cluster sampling Intermediate scale Need to sample clumps adequately without enumerating too many empty plots clumping ACS with initial random sampling (~ 100 m) AA (if resources limited) Cluster sampling (area covered by cluster, large and approximates scale of clumping, high sampling fraction within cluster means. Within cluster errors are small so mean for cluster is treated as if derived from a single plot measurement). Distribution linked to Difficult to cover large area efficiently: landscape features Transect sampling e.g. line-intercept, strip, line-plot sampling (~1 000 m) Gradsect sampling ACS with initial strip sampling Stratified ACS with sample allocation according to observations in previous strata Systematic sampling Uniform Few problems, choice of sampling design related to ease of field operations, available resources and required sampling accuracy and precision. Nearest neighbour methods (T-square, point-centred quarter etc) Terrain difficulties Cost of locating sample plots major part of overall inventory costs Transect sampling (maximises observations for field work effort) Systematic sampling (locations easy to locate) ACS with initial strip sampling Non-normal populations Finding an unbiased sampling design / analysis as SRS and derivatives are not applicable especially for calculation of confidence limits Unbalanced RSS AA with second phase sampling designed to minimise variance Normalise data (group data into larger units, use log, square root etc. transformation to achieve normality) Use calculations appropriate to distribution (e.g. Poisson, negative binomial etc.) Use randomisation methods such as jack-knife or bootstrapping Oligarchic species Important to characterise within and between-stand variability In dense stands – considerations as for abundant species In scattered stands – considerations as for small to intermediate scale clumping. Species in complex Accounting for between-species interactions and temporal change. ecological communities Habitat and community-based sampling Multi-resource inventory (ecosystem orientated) Study with limited Insufficient funds for formal sampling resources (either funds Indigenous knowledge used to select sample sites or time) Personal judgement used to select ‘representative’ sample BUT reliability of assessments cannot be determined and results cannot be reliably extrapolated (so problematic for generalisation). Table based on: Cochran 1977, Gillison & Brewer 1985, Schreuder et al. 1993, Philip 1994, Seber & Thompson 1994, Patil et al. 1994, Myers & Patil 1995, Greenwood 1996, Sheil 1998, Brown unknown date. ACS – Adaptive cluster sampling AA – Adaptive allocation RSS – Ranked set sampling SRS – Simple random sampling

80 5.4 Plot configuration A ‘plot’ is a unit of space and time within which observations are made on the species of interest. For plants, the space element is most important and plots usually have a defined area and it matters little when and for how long enumeration takes place. Animals are generally more mobile than plants and are often counted over a fixed time period and a point or along a transect line.

It is obvious that plot form should be matched to the life-form and growth-habit of the resource being inventoried. Parren et al.(1998) discuss the use of a number of novel plot configurations for lianas including a cylindrical plot which samples to the top of the crown, a plane-intercept plot at 1.3 m above the ground and make general recommendations for different purposes e.g. circular plots for studying the spatial distribution of lianas in the canopy of a single tree. However, they note that the different types of liana growth form (e.g. scramblers, climbers, multi-rooted and stemmed individuals) may require different approaches. This suggests that it is size and growth-habit that should be the main determinants of plot dimensions. There has been some work on optimal plot shape and size for rattans (see Section 3.6.5) but little done on other types of resource or comparing different plot configurations rather than simply comparing square with rectangular fixed area plots.

The determination of the best plot types for different NTFPs especially for multi-species inventory is something that requires research. Consequently it is not possible to indicate the optimal plot for different life or growth form. However, there is some advice on choice of methods for different life-forms available in Sutherland (1996) for the purpose of ecological studies. However, since there is little of this nature for NTFPs Table 23 does not attempt to advise which design is best for specific life-forms but rather indicates the range of plot types that have been employed for NTFPs. Table 23 Use of plot configuration for NTFP resource assessment

Plot configuration Discipline Description Examples Measured fixed Forestry Square, rectangular or circular measured Commonest type of plot area plots areas, strip transects, frame quadrats Measured fixed Wildlife survey Fixed period listening stations mainly for No NTFP examples time periods bird or primate calls usually at specified times of day and perhaps also at night Unmeasured area Botanical Undefined area usually within a specific Hawthorne & Abu-Juam 1995 survey landscape unit from which samples are collected Plotless sampling Plant ecology Point-centred quarter method Schreckenberg 1996 Lescure et al. 1992 Forestry Relascope sweeps No NTFP examples Plant survey Fixed number of individuals closest to Sheil 1997 sample point or within sample area Singh & Dogra 1996 Pinard 1993 Point quadrats Plant ecology Fixed area frames with array of needles No NTFP examples used to identify points for sampling plant cover Point and line Wildlife survey One dimensional plots; generally White 1994 transects observations are made while standing on Bodmer et al. 1994, Bodmer (variable width the point or line see DISTANCE sampling 1995 transects) below Silva & Strahl 1991 Line-plot Plant surveys Plots located along a transect line Cevallos undated transects (usually distances along line are fixed in which case this is systematic sampling) Line-intercept Forestry and Observations made of intercepts (tracks, Fragoso 1991 transects animal survey signs, plant clumps) with a line or plan Ringvall & Ståhl 1999 projected above line. Sheil 1997 Strip transects Plant and Narrow, very long transects treated as a FitzGibbon et al. 1995 animal surveys fixed sample area. Lahm 1993 Stockdale & Corbett 1999 Gradsects Ecological Gradient orientated transects as basis for Gillison & Brewer 1985 survey survey

81 5.5 Enumeration protocols It is argued above that enumeration protocols for measurement and density determination for NTFPs is dependent on the life-form and growth-habit of the species. Table 24 presents a range of protocols used for NTFPs culled from the review and more general inventory texts (see Appendix 5). There has been little work on the determination of the best protocols for tropical non-tree plants. It is probably not possible to use the plant ecology methods developed for temperate non-trees without some additional research, as the size and form of non-tree plants are quite different in the tropics (e.g. point quadrats would not work in the tropics because herbaceous plants are generally larger than temperate grass swards). Kleinn et al.(1996) also point out that for non-trees some accommodation of differential detectability is required, which is seldom accommodated in temperate vegetation studies.

Enumeration protocols for animals are closely related to the type of plot used and the method of observation i.e. whether it uses sightings, calls, trapping or kills. Methods for animals are well researched (see texts in Appendix 5) and do not require major development – just their application to NTFP problems. Table 24 Example possible enumeration protocols for NTFP resource assessment

Method Life form Description Tally Any – sessile Counts of target individuals in plot Presence/absence Any Record occurrence of target in plot (e.g. biodiversity survey, 1 ha ethnobotanical plots) Size/age Larger plants and Measure size of all individuals in plot (e.g. leaf width, stem measurement animals diameter, height, life stage – juvenile/adult etc.) Cover Plants Record percentage of plot covered by target species. Relative abundance Any Score density of target in plot into subjective classes e.g. low, medium, high or Braun-Blanquet and Domin scales for plants Trapping Motile – animals and Capture individuals for counting and measurement e.g. mist fruit/seeds of trees netting, Sherman traps, seed traps Partial trapping out Small animals (where Capture individuals and remove from population, repeat over loss of individuals is a period of time and use exponential model of decreasing not critical) capture rates to extrapolate initial population Mark-recapture Animals (palm fruit Capture individuals, mark (toe clipping, tags, paint etc), see Phillips 1993) release and re-capture, use numbers re-caught to estimate total population. Many variations see Greenwood 1996. DISTANCE Animals Record distance from observation point to target and use sampling Fourier analysis to estimate target population Response to Birds Play recording of bird calls and count number of responses playback Indirect / Index Any Record hair, dung, nests or other easily observable signs methods and use regression methods to estimate size of target population.

From a foresters’ perspective the inventory of NTFPs poses a number of unfamilar problems such as the difficulties of making counts when the individuals of interest are hidden (e.g. truffles, epiphytes) or run away when approached. This class of problems termed ‘imperfect detectability’ and there are a range of methods for dealing with it (e.g. line transect or Distance sampling. These methods are at present the preserve of wildlife research but could potentially be adopted for cryptic NTFP plants.

5.6 Yield measurement Yield determination is mostly a matter of measuring (volume, length or weight) the part of the plant or animal that is harvested. This is often done using pickers or hunters to do the harvesting and weighing etc. of what they collect. Alternatively the quantity of the relevant part can be measured in the plots and the results adjusted for accessibility (e.g. Phillips 1993).

82 There are a number of protocols that have been developed for enumerating plant products (see Section 3.7.1 and Table 11). However, few of these have been sufficiently tested to form the basis of universal recommendations for different types of product e.g. fruit or bark.

However, there are a few general points that emerge from the review: - Harvesting of products should be as close as possible to the methods actually used, the easiest way to ensure this is to use local pickers or hunters and not to restrict harvesting. - Total quantities of product assessed in the field should be access-weighted to give a measure of the amounts available to harvesters. - Forecast models which include climate and site variables should be used to determine yields and sustainable harvests from seasonal products such as fruit.

5.7 Growth and productivity Growth and productivity studies are a prerequisite for the determination of sustainable yields. Studies on plants generally take the form of long-term monitoring and involve repeat measurements on tagged individuals either standing alone or in plots. Animal productivity studies generally seek to describe population demography. There are no studies which specifically develop or compare dynamic protocols for NTFPs and there are insufficient examples on which to base any specific recommendations. However, a few general observations can be made.

PLANTS – permanently marked sample plots or tagged individuals Sampling design is seldom an issue and plots are often located subjectively (Sheil 1998). Plot configuration is usually a standard 1 ha square plot as used in forestry (Alder & Synott 1992). There have been a few studies of repeat measurements for palm leaf and fruit production but generally there has been very little done on the productivity of non-tree plants. The classification of McCormack (1998) is useful when considering productivity studies, especially for enumeration intervals:

1) Seasonal / ephemeral products – one-off records every season or repeat enumerations through relevant season e.g. mushrooms and fruit recorded every week through season with mature ones either harvested or painted to preclude repeat enumeration. 2) Non-seasonal / ephemeral products – record time taken for relevant part to reach maturity at an appropriate time scale (e.g. monthly for leaves, quinquennially for woody trees, annually for bark etc). 3) Perennial products – need to record time taken to reach maturity and reproductive success at appropriate time scale usually 1-5 years.

ANIMALS Use standard techniques to record life-cycle parameters such as fecundity and mortality. Pay special attention to density dependence particularly in fecundity rates. Generally it seems that estimates of fecundity, mortality, longevity etc. are taken from in-depth ecological studies with field studies providing estimates of local carrying capacity and actual population densities.

83 6. Research issues The provision of biometrically adequate inventory methods is only one among the many identified research needs in the study and management of NTFPs (see Beer 1999, Ruiz-Perez & Arnold 1996, Kaybuye 1999, Peters 1999a, Ros-Tonen et al 1995, Ros-Tonen 1999, Sunderland et al. 1999). Evaluating the relative importance of biometric research needs against wider NTFP research interests has not been undertaken and remains to be resolved by a wide stakeholder group. However, many studies place the provision of good quality data on the status and sustainable yields of products high on their lists of priorities for further work. Even in a paper intended to stress the social science contribution to NTFP management the point is made that since there are only poor quality data (in terms of sample size, geographic coverage and reliability) available for the density of hunted animals that the provision of better quality data is a high priority (Wilkie et al. 1998).

A set of six areas which would benefit from biometrics research have been identified. These suggestions are not intended to be prescriptive as it seems appropriate for the whole programme to be process- orientated as it is not possible to know in advance whether the application of specific methods to NTFPs is either possible or desirable. The programme will only be achieved through cross-disciplinary exchange of ideas and experience drawn from forestry, conservation biology, geography, horticulture, sociology, rural development, ethnobotany, statistics etc. in collaboration with local communities and forestry staff. The ethos of the whole program should be the development and presentation of well researched, tested and documented field methodology.

6.1 Evaluation of novel sampling designs for use in NTFP inventory NTFP inventory, even more than timber inventory has to be cost-effective to an extreme. There are reports that conventional designs may be too costly to be borne by a self-sustaining NTFP management system. The Forest Management Department (1999) of the Mount Cameroon Project concluded that the cost of the 1% inventory requested by the Ministry to support quotas of Prunus africana bark would be approximately 20% of the value of the quota. This is considered to be unaffordable and a reliable design which will provide the necessary accuracy at an appropriate cost is being sought (Acworth pers comm.). Likewise, Evans (submitted) suggests that time costs of inventory for rattan in Laos would outweigh any economic benefits they may offer. He therefore concludes by questioning whether standard, plot-based, rigorous resource inventories are an affordable management tool for NTFPs. Interestingly, the reasons Evans (submitted) gives for the high cost are, large forests, difficult terrain and patchy distribution of the target species which have much in common with the situation for Prunus in Cameroon. Given that these situations are common for a wide range of NTFPs most of which have relatively low market prices there is an urgent need to develop short-cut methods for NTFP inventory which will retain an acceptable level of biometric rigour.

One of the most common inventory problems posed by NTFPs is their tendency to have patchy or clumped populations. These distribution patterns are inherently poorly served by conventional inventory designs. However there are several new designs that have been proposed as offering advantages for use with sparse and/or clumped populations. Notable among these are the various manifestations of adaptive designs (see Appendix 7). However, there are reservations concerning the use of adaptive cluster designs in particular for sampling mushrooms in mountainous temperate forest (Pilz pers comm., Pilz & Molina in press) because of terrain and scale problems. Based on these observations, Pilz (pers comm.) raises the issue of the degree of aggregation required to make adaptive sampling advantageous. Indeed, recent experience of adaptive designs in Cameroon for Prunus africana suggests that adaptive designs will need to be carefully optimised to a specific product, resource distribution pattern and terrain to maximise their benefits (Acworth pers comm., Underwood 2000). Other recently proposed sampling designs which may have relevance to NTFPs are gradient directed transects (Ståhl et al. 1999) and line intersect sampling (Sheil 1997) which could also be investigated for use with NTFPs.

It is the hope that the adoption and optimisation of some of the newer sampling designs will be able to significantly reduce the cost of inventory and therefore accessible to a wide group of NTFP managers.

84 However, the proposed sampling designs and procedures have not been extensively field tested so a programme to develop and test the most promising protocols is required. To this end field trials in a number of locations, different life-forms and terrains will be needed. The cost and time-efficiency of the methods should be determined with respect to improvements in statistical precision and accuracy, field logistics, and degree of training required for field enumerators with a range of skill levels.

Local knowledge is an important source of information on all aspects of the use, distribution and ecology of NTFPs. There are a large number of methods available in the social sciences for collecting and using local knowledge in the context of community involvement in management (see Section 3.3 of the Review). Due to time and financial constraints many researchers wishing to quantify some aspect of a specific product have appropriated some of these techniques to locate ‘representative’ sites or significant populations of rare species for study (see Section 4.5.4). However, the use of such methods often generates the possibility of bias in the sample selection. Nevertheless, this should not rule out the use of local knowledge, rather it suggests that there is a need to formalise its use in sampling design. This is essential, both as part of the growing recognition of the value of local knowledge, the need to establish two-way communication of indigenous and exogenous knowledge (Messerschmidt & Hammond 1998) and also as a means of improving the selection of a small, and therefore affordable, number of plots. Rank set sampling (RSS, see Appendix 7) is a technique which relies on the subjective ranking of small number (~3) candidate plots at each sampling location, at the first location the plot ranked 1 is chosen for sampling, at the second, rank 2 and at the third rank 3 and so on. The combination of IK to perform the ranking, the small numbers of plots required and improvements in biometric performance is attractive for a wide range of NTFPs management contexts. Unfortunately, RSS has received little attention and there is only one field protocol available which is not suitable for use in forested environments. Theoretical and methodological research is therefore required to determine if it is possible to use the principles of RSS for NTFPs in a tropical forest environment.

6.2 Development of resource measurement techniques for non-tree products Measuring NTFP resources usually involves two stages; estimating the abundance of the populations being exploited and the measurement of the quantity of product for each individual. The review revealed that there are few readily accessible methods for either in the NTFP literature. This research topic is designed to address these shortcoming.

Develop and test enumeration protocols for common product types There are a range of sophisticated techniques for assessing large tree and wildlife populations but there is very little available for non-timber products for example, leaves, seed case floss, fruit, parts of climbers and herbs and insects such as mopane worm. These resources fall into an institutional gap in most regulatory systems (e.g. as in the USA, Bailey pers comm.) and methodology for their enumeration is generally lacking.

However, within agriculture and horticulture there is a considerable body of experience of measuring yields from herbaceous plants and tree fruit. Only a few of these have been tested for use with NTFPs (e.g. randomised branch sampling, Hall pers comm.) and it is likely that there are many more that could be adapted for use with NTFPs. Horticultural yield assessment methods will focus on yields from monocultures which are very different from wild NTFPs so methodological development will be necessary. Plant ecology, especially autecology, also has methods for assessing wild plants and a few of these concern themselves with the quantification of spatial variation in yields (Kerns pers comm.). What is required is to draw together protocols from all these disciplines and to identify those with potential for application to NTFPs. The techniques used for crop forecasting may also have some relevance to NTFPs. Identified protocols would need to be tested in the field and obvious gaps addressed with the development of novel enumeration techniques.

Develop and test unified protocols for plant and animal survey There is a notable gulf between people interested in trees, plants in general and animals. This is evident amongst both academics and managers and consequently there have been few quantitative studies which

85 include both plants and animals. The resultant deconstruction of the forest ecosystem results in serious biases and omissions especially from the perspective of local people who value animal and plant products equally (Bird pers comm.) and also from an ecological perspective as it fails to treat the forest is a single functional ecosystem. Furthermore, the sharing of costly, ephemeral resources such as cut lines and demarcated plots between disciplines, say in a multi-purpose resource inventory (see Lund 1998) could greatly increase the cost-effectiveness of the undertaking as well as providing useful synergy which should enhance understanding of the forest and its dynamics. At present there are no tried and tested protocols for the simultaneous inventory of plants and animals in a tropical forest.

Develop community based animal enumeration protocols For bushmeat exploitation to become sustainable there is a need for hunters to have at their disposal a range of tools for estimating the abundance and health of populations and to make appropriate adjustments to their harvesting levels (Noss 1999). At present there are few methods that are accessible to hunters though there has been some success of the use of daily diaries (Marks 1994) and the CyberTracker system based on hand held computers (Cunningham & Leibenberg 1998). Such systems should be evaluated in the field and proposals made for suitable assessment and management systems for bushmeat species, in particular those taken from natural (including secondary and logged) forest environments.

6.3 Development of NTFP resource monitoring protocols Monitoring of the consequences of exploitation is a fundamental component of any rational management system. There is much interest in the monitoring of NTFP exploitation both on the target species and the forest in general. Unfortunately there are few protocols available which take into consideration the complexity of monitoring diverse and little studied ecosystems. This topic proposes to refine the use of commonly used indicators and to prepare advice on how to prepare biometrically sound monitoring programmes.

Test of resource condition indicators Biometrically adequate monitoring is both costly, time consuming and requires a certain level of institutional commitment to organise and run. This is often not available to NTFP managers who nevertheless still require accurate data on the effect of harvesting on species and the forest. Monitoring of indicators of forest or species health is often used as a proxy for direct enumeration of resources and is also used for determining compliance with management standards. Indirect monitoring of resource condition takes many forms and can include harvest records, indicator species and local knowledge. For example, trends in population density as perceived by local people are often used as indicating resource depletion. Although this is valid for constructing an environmental history it is not really satisfactory for resource monitoring. Likewise, harvest records are relatively easy to collect but are often not closely coupled with resource extraction (Milner-Gulland & Mace 1998) but rather with socio-economic trends (Bailey pers comm.). This does not mean that these proxies are not useful but rather that the mechanisms linking them to resource extraction need to be better known and they need to be calibrated with snap-shot and long-term ecological studies of population structure and change. However, there has been very little verification that chosen indicators do indeed measure relevant features of the resource or calibrate the indicator with a more direct measure of resource condition. Without such studies it is difficult to be confident in the conclusions drawn from indirect monitoring. Therefore it is desirable to test the assumptions behind the use of common indirect indicators such as harvest monitoring and interview techniques (Phillips pers comm.). It will be necessary to develop simple field protocols and analyses for undertaking the calibration of indirect resource indicators.

It is often the case that local communities have traditional management systems for subsistence resources. For these systems to have proved effective in maintaining the resource it is possible that they include the assessment of indicators of resource health and rules that modify harvesting practice. Elicitation and quantification of such knowledge may provide a valuable source of resource condition indicators (Schreckenberg pers comm.).

86 Develop recommendations for the monitoring of NTFP resources Monitoring the condition and sustainability of NTFP resources is something which has only recently received any serious attention (see Section 3.10 of the Review). There are a range of issues that have been raised by various people who have begun to consider the challenges involved. Sheil (1997) developed a series of recommendations for monitoring based on transects for Uganda. Evans (submitted) points out that the power of a monitoring scheme to detect change in the population is related to the precision of each enumeration and that the numbers of plots involved are likely to be unaffordable. Other suggestions are tracking the fate of tagged individuals (Cunningham 1990) and the two-stage approach advocated by Gagnon (1999a & b). Regional monitoring systems for mushrooms in the USA are in the process of being developed and tested (Pilz & Molina 1998, in press). Whereas, long-term monitoring of NTFP yields is common-place in European cold temperate forests e.g. Finland (Kujala 1988), Lithuania (Rutkauskas 1998). There are also other initiatives linked to the emergence of adaptive management that place emphasis on monitoring systems (Gibbs et al 1999, Ringold et al 1999) which may have some relevance to NTFPs. There is a need for serious consideration of these and other possible approaches for application to NTFPs in tropical forests.

6.4 Development of methods to determine optimal harvesting levels Perhaps the biggest challenge facing NTFP managers and their advisors is the problem of determining the yields which can be sustainably harvested. This is a complex problem and there is a need for theoretical development of suitable models of population demography and the effect of exploitation on the general functioning of the forests themselves. Such research is perhaps beyond the scope of development oriented research though Havens & Aumen (2000) convincingly argue that hypothesis- driven experimental research is an essential part of natural resource management. The research proposals outlined here are intended to consolidate and disseminate existing experience.

Forecasting yields of seasonal products Ephemeral or seasonal products (e.g. mushrooms, fruit) generally have highly variable annual yields. It is therefore impossible to prescribe constant levels of ‘sustainable’ harvests. In northern European forests there are considerable commercial harvests of wild berries and mushrooms which have prompted the development of yield forecasting systems to permit management and monitoring of resource use (e.g. Belonogova 1988, Saastamoinen et al 1998, Salo 1999). Such systems depend on national-level observations over long periods of time (> 10 years) by a network of volunteer observers. The results are used to generate empirical predictive relationships between product yields, site conditions (overstorey species, soil type etc.) and climate (duration of frosts, temperatures in previous autumn etc.). The methods used for making these forecasts are little known outside their respective countries and are not reported in the Anglophone literature in any depth. However, they are potentially of great interest and relevance to the management of tropical fruit and other ephemeral products. Before these methods can be tried the detailed protocols need to be made more accessible and modified for use in tropical environments and products. Alhtough, few details are reported it appears that there is work in South Africa on the forecasting of fern frond production which also depends on linking productivity to climate (Geldenhuys & Merwe 1988).

Yield forecasting of plantation crops (e.g. cocoa, coffee etc.) use wide-ranging field observations and presumably need to be accurate as they provide the basis for prices in international futures markets. It is assumed that these methods may have some relevance to NTFP forecasting. The methodology used in these predictions should be investigated for possible extension to NTFP management.

Developing methods to determine the sustainable yield of specific products Many of the reviewed NTFP studies make use of matrix models of the population dynamics of plant and animal resource species to estimate the potential sustainability of extraction levels (see Sections 3.9.3 and 3.9.4 of the Review). Most of the models developed depend either on secondary data or observations over only short time periods. Given the complexity of a tropical forest, such models are very much a first look at the problem rather than the last word. For plants, single species matrix models have been proposed by Peters (1996a) while for animals the model proposed by Robinson & Redford (1991) has

87 become popular. Recently, the use of stochastic matrix models to evaluate the risk of extinction under a range of harvesting scenarios has been proposed (Gagnon 1999a) which would seem to offer a more sensitive way of dealing with the exploitation of species with conservation interest. A more pragmatic alternative is the adoption of the iterative ‘periodic harvest adjustments’ described by Peters (1996a) though this will need to be refined for use with specific products.

The development of methods for determining the optimal and sustainable models on which to base harvesting decisions is very much something ‘science can contribute’ to NTFP management (Wieren 1999). The challenge is there, what is now required is a considered evaluation of how to extract a sustainable harvest from NTFP species. There is therefore a need to evaluate both the theory and experience of NTFP harvesting in order to derive sound proposals for the analysis of sustainability which can be applied by NTFP managers from national to local levels.

6.5 Documentation and dissemination of statistical advice for NTFP assessment There is a common mis-conception that there are few studies which attempt to quantify NTFP resources. However, the review revealed that there is in fact an increasing body of experience in the assessment of a wide range of resources. Much of this material is difficult to locate as it is scattered across a wide range of disciplines many of whom are not familiar with the term ‘NTFP’. In order to make use of all relevant experience it is first necessary to make this material more familiar to the ‘NTFP’ interest group. Ideally this would include the preparation of annotated bibliographies along the lines of that prepared by Hagan et al. (1996) of work done in the former USSR where NTFP study is well developed (see Niskanen & Demidova 1999).

There are no textbooks which outline a biometrically sound procedure for preparing NTFP resource inventry protocols. There is even less advice on the correct procedures to use to analyses and test the data generated. This topic is therefore concerned with the collation and dissemination of experience and advice to the NTFP community with particular emphasis on statistics.

Preparation of a handbook for the application of statistical methods for use in the analysis of NTFP datasets The advice on statistical analyses for inventory data once they have been collected in standard forest inventory texts are based on an assumption that the data are normally distributed. If data are non-normal then the traditional advice is to devise a suitable transformation to enable the use of statistics based on assumptions of normality (e.g. Freese 1984). These parametric statistical methods (i.e. ANOVA, t-tests, chi-square tests, regression analysis etc.) have become ‘conventional’ in natural resource inventory (Sheil 1998) and are well documented and known. Unfortunately, most NTFPs are markedly non-normal in distribution often because rarity and clumping give rise to large sample sizes with few observations and consequently a large number of empty plots. There is little or no advice readily available on how to deal with non-normal distributions such as counts or proportions and statistical analyses of such data can pose severe difficulties to inventory practitioners (Acworth pers comm., Wright pers comm.). However, there are a body of methods, sometimes termed non-parametric (e.g. Wilcoxon’s signed ranks test, Friedman’s test, G test etc.) which are more robust, though have less discriminating power. They make use of rankings and not the actual magnitude of the records, which are suitable for use in these situations (Sheil 1998). Likewise the use of generalised linear models do not depend on normality and can be used to good effect on markedly non-normal data (Leidi pers comm.).

Although methods for dealing with non-normal distributions have been familiar in statistics for a comparatively long time they are not yet widely known or used in natural resource inventory where they would seem to offer significant advantages over more ‘conventional’ statistics. If sound sampling schemes are to be followed by equally sound analyses there is a need for a simple handbook to promote the use of such techniques in resource inventory (Leidi pers comm.). The handbook envisaged would be specifically targeted at natural resource inventory problems and use NTFP case studies to illustrate the proper application of each test.

88 Develop tools for NTFP inventory design The design of appropriate and efficient sampling strategies for NTFPs is not simple. Unfortunately, it is made more difficult by the inclusion of a wide range of cross-disciplinary techniques and methods so that much will be unfamiliar to any individual researcher even if they have a biometrics background. It has therefore been proposed that a decision-tree approach be developed to facilitate inventory design (Brown pers comm.). Given the level of complexity involved it has been proposed that this be developed as a computer-based model. Such a model would provide an ideal platform for integrating and presenting the results of the other elements of this research programme in a user-friendly form but may prove to be inaccessible to many NTFP inventory practitioners. The FAO are in the process of preparing a new inventory manual and this will contain a chapter on NTFPs. The idea is to make the manual modular in construction to maintain flexibility (Preto pers comm.) and this may prove to be a useful platform on which to present advice on the design of NTFP assessments.

However, biometric concerns are only one element in the design of an inventory, other issues being the purpose, objectives, resources, political credibility etc.. Guidance on the consideration of these issues in sampling design and strategy is also required. This could be addressed through incorporation into a single decision-support system or be independent of biometric concerns. Any system for assisting the design process should not be unduly prescriptive but guide the user through alternative approaches and encourage the tailoring of designs to the specific context of each study.

Establish a network for NTFP biometrics If any programme of research is to retain a sense of identity and develop synergy between the collaborators and partners it requires some form of institutional structure. It is therefore necessary for the workshop to consider what form of structure is appropriate in this instance. The review paper and research topics all highlight the need to integrate approaches across traditional disciplinary divides. The most practical way of bringing people from disparate institutions together is to develop a network which is actively managed by a core institution which would act as ‘host’ to the network. Ideally, what would be established would be a research facilitation and knowledge exchange network which would be able to commission or facilitate focused research on prioritised areas. It would also have a key role in the dissemination of findings in the form of manuals and practical guidance on field protocols. In the early stages, it may also be desirable for the network to provide a bureau or advisory service. This would have the dual role of providing support to those struggling with the difficulties of NTFP inventory and provide case studies for the testing of emerging protocols in the spirit of ‘action’ research.

Networking people in disparate institutions is relatively easy with the advent of the internet but care should be taken to ensure that countries, individuals and institutions that do not have access to the internet are not excluded from active participation.

6.6 Linking indigenous and scientific knowledge The naming of NTFPs is fraught with difficulties which often prevent effective communication between researchers, managers and resource users. For example, local collectors will use folk names, biodiversity specialists will use Latin names while foresters may use timber trade names. Managers often need to use information from all these sources and therefore requires a means of linking the names together. There are many examples of NTFP lists of local and Latin name equivalents (e.g. Abbiw 1990, Papadopulos & Gordon 1997) but these rarely document the complexity of sets of alternative names for single entities in each naming system. Experience suggests that recognising all alternative names for a product or species is not a simple matter and lists of equivalent names are rarely complete (Hawthorne pers comm., Dijk 1999a & b).

Despite the apparent complexity, ethnotaxonomic experience suggests that there is a structure to folk taxonomy (see Section 4.2) and folk classifications are amenable to systematic interpretations. Unfortunately, ethnotaxonomic studies are time consuming and impractical for the majority of NTFP researchers. However, it may be possible to devise a simple means of describing folk taxa which will facilitate communication and provide a basis for ascribing folk names to scientific taxa. For such a

89 methodology to be effective it needs to be accessible to non-linguists working through a local interpreter and it may be that this is not possible. What is envisaged is a generic framework around which elicitation of local names for resources and products can be conducted. This could possibly draw on experience with the use of a systems approach to the representation of local knowledge such as that developed by Sinclair & Walker (1999).

90 7. Conclusions The review has revealed that there are remarkably few methods available for the objective quantification of NTFP resources. Many NTFP assessments are undertaken using methodology developed within non- quantitative disciplines and are not biometrically robust. For many purposes such as ethnobotanical inventory this poses few problems. However, the use of non-replicated and subjective plots for the quantification of resource abundance, productivity and sustainability produces data, and therefore management recommendations, of doubtful veracity. Besides being poor science this becomes an ethical problem where recommendations are made concerning the fate of exploited species or community livelihoods.

There is therefore an urgent need to develop more rigorous methods to address the particular technical and logistical challenges of NTFP resource assessment. New methods should: • be suitable for use with sparce and clumped populations of plants and animals in tropical and sub- tropical forests; • accommodate the assessment of plants, fungi and animals; • be able to accommodate motility and imperfect detectability in protocols; • be affordable by subsistence communities; • be able to incoporate local knowledge in the inventory design; • be presented as straightforward and ideally intuitive protocols.

Moving beyond the quantification of resource abundance there is a need to address the complex challenges of monitoring exploitation. Most NTFP monitoring in the tropics is done using local hunters or harvesters in the context of a participatory management system. Interestingly, developments in the temperate zone also makes use of volunteers acting under the incentive of exclusive access to the resource in the monitoring sites. All the monitoring systems reviewed would benefit from a deeper consideration of the particular statistical problems associated with achieving designs capable of discriminating change on a practical time-scale (Burn pers comm., Evans submitted).

The greatest challenge in the provision of biological data for NTFP management is the problem of determining sustainable harvesting levels for specific products. Theoretical development of models for the exploitation of wild products has taken place in forestry (e.g. Alder 1995, Vanclay 1994) and conservation biology (e.g. Bolton 1997, Milner-Gulland & Mace 1998, Caughley & Sinclair 1994). There are significant differences in these models which relate to the intrinsic differences between the response to exploitation of fast-breeding animals who can seek out food from long-lived trees, rooted to one spot. However, both are essential components of the one forest and there is a need to consider the consequences of exploitation on the whole ecosystem, otherwise we will only be promoting the creation of ‘empty’ or ‘half-empty’ forests (Redford & Feinsinger 1999) in which all looks well but ecosystem function is breaking down. Havens & Auman (2000) also argue that holistic natural resource management requires hypothesis-driven research and that contributes to increasing understanding of the functioning of environmental systems as a necessary pre-requisite for successful management. There is therefore a need for a cross-disciplinary exchange of ideas on the development of eco-system based approaches to the management and monitoring of exploited forests.

Interestingly there are parallels between the present situation regarding NTFP quantification and the development of ornithological statistics described by North (1994). Initially, the emphasis in orthnithological studies was the analysis of data that had been collected without any particular purpose, with no thought to statistical design, or objectives for the studies, or knowledge of suitable statistical tests. This resulted in huge amounts of useless data and much frustration. North (1994) reports that contact between ornithologists and statisticians helped to get orthnithological statistics onto a sounder methodological basis. Although NTFP studies are not as disorganised as orthnithological studies apparently were, the use of statistical advisors is still an important lesson to learn if NTFP quantification is to move beyond the case-specific to generic methodology.

91 7.1 Revisiting the definition of NTFPs During the course of the literature review it became apparent that the many threads of research on NTFPs gathered from the various disciplines are converging in terms of the issues being tackled, but not in methodology. Despite efforts to introduce quantification into ethnobotanical research and resource management into market studies there is still little real cross-disciplinary work, especially any that includes plant and animal perspectives. However, most perspectives are converging on the sustainable development and management of NTFPs and the resultant conservation, livelihood, macro-economic and political ramifications of such development. Is there then a case for considering NTFPs as a fully fledged natural resource management discipline in its own right? To investigate this we first must return to the question of the definition of what is meant by NTFPs.

There is general consensus that NTFPs should be useful to human society and not include timber. However, Mallet (1999) considers that the limits of what constitutes a forest environment is not sufficiently clear. Forest products are traditionally those that come from natural forests but the definition of ‘forest’ (see above) could also include other tree-dominated systems such as plantations and agroforestry systems. However, there is some opposition to the inclusion of products from plantations, in particular, because they are artificial and have limited biodiversity (see thread on definitions on www.anthrotech.com/ice/ntfp/messboard). Others are concerned that forest-based certification systems should include diverse agroforests because they are socially beneficial and biodiverse (Mallet pers comm.). The point here is that there seems to be a desire to identify NTFPs as coming from biodiverse and socially as well as biologically sustainable production systems13. This fits well with certification initiatives (Mallet 1999, pers comm.) but it must be remembered that certification is not an issue for most NTFP enterprises which, especially in Africa, are focused on subsistence or local markets.

The vast majority of plants and animals that are generally recognised as NTFPs are wild products of natural forests or species that have only recently been brought into cultivation and are still essentially genetically wild. If NTFPs are to remain distinct from agricultural products, there needs to be a line drawn between wild and cultivated products as all cultivated plants and domesticated animals were once wild and we would end up classifying cocoa, coffee, rubber and oil palm as NTFPs as they were all once extracted from wild populations in natural forests. Should the ‘wildness’ of a product only mean that the plant or animal lives in the wilderness with the only human interaction being harvesting14? Such a definition would preclude plants that had been planted whether these were transplanted wildlings in a forest garden or enrichment planting of secondary forest. On the other hand, permitting all products derived from biodiverse production systems such as agroforests would include highly modified cultivated crops which in no sense could be thought of as wild. A middle ground between these extremes would be to define as ‘wild’ species which are freely out-breeding and occur spontaneously. Thus wild NTFPs could come from a plantation monoculture if, like mushrooms they appeared of their own accord. This still leaves a grey area for recently domesticated products grown in agroforests and biodiverse agroforestry systems. Perhaps if these are wildlings or freely cross-breeding with wild populations and maintained within the system in which they naturally occur they should still be considered as ‘wild’. However, whether the production system is biodiverse is perhaps a subtly different issue that should be treated independently of the products wildness.

This is not just an academic distinction, there are intrinsic differences in the philosophy and practice of managed exploitation of wild products. Management of wild products involves harvesting controls and the promotion of suitable environments and facilitation of growth and replacement but without hands-on

13 “A more appropriate measure of which products ought to be included may be the proximity of the production system to the natural ecological state and the level and intensity of human impact. Certification of NTFPs should seek to promote systems that focus on increasing levels of biodiversity towards natural levels, thereby increasing stability and integrity within the system.” Mallet (1999). 14 This is the sense behind the term ‘extractivism’ which is the extractive use of renewable products of naturally occurring trees in Amazonian forests (Murrieta & Rueda 1995).

92 intervention. The emphasis is on maintaining the integrity and health of the species’ natural processes. Agriculture, on the other hand focuses on direct manipulation of the products through breeding and husbandry. Indeed this is also the distinction between fisheries and fish farming and natural forest management and plantations which are also production systems for groups of products (fish and timber) which cross the wild/cultivated divide. Gagnon (1999b) stresses that the distinction between ‘wild’ and ‘woods-grown’ (cultivated in the forest) is important as a failure to distinguish between them could mask the slide of wild populations into oblivion. This is a particular concern when the only trade data is available.

In many senses it is nonsense to exclude timber of natural forest origin from a classification that centres on the ‘wildness’ and ‘utility’ of a species. Initially it seems timber was excluded because it was already the focus of forest management and the intention was to draw attention to the other neglected forest products relegated to ‘minor’ status. This was perpetuated when the emphasis shifted to small-sized products for domestic use, accessible to the poor and requiring little capital input (quoted in Lund 1997, 1998c) and timber was seen as large-scale and industrial. However, there are now many instances when timber is exploited for export by local owner groups and indigenous peoples (e.g. Dunn & Otu 1996, Lawrence & Romàn 1996). Lawrence et al. (1985) also mention the need to include timber use in order to get the full picture of resource use by a community. On the other hand, some traditionally recognised NTFPs are exploited on a large scale for export. For example, chicle and Brazil nuts from extractive reserves (Murrieta & Rueda 1995) and an increasingly wide range of products for the USA eco-friendly market (Clay 1997). There is also more in common between the management of natural forest trees and NTFPs than there is between timber from natural forests and plantations. It is therefore logical to discard the exclusion of timber and instead to define wild forest products and sub-divide this into wild non- timber forest products and wild timber products if so desired. The study of such products should be understood to include the economic, social and political ramifications of use in the same way that agriculture includes consideration of all of these for cultivated products.

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109 Appendix 1 Terms of reference

Position paper on biometrics of assessment of NTFPs

Introduction

1. Domestic use and national and international trade in non-timber forest products (NTFPs) has declined substantially since the beginning of the twentieth century. Products harvested mostly from natural forests have been replaced by industrial products processed in integrated factories, sometimes using synthesised chemicals to replace natural substances. However, use and trade of some NTFPs has continued or even increased as rising incomes permit households to pay higher prices for products based on renewable natural resources; for example, green forest foliage for floral displays and fungi harvested from the wild command substantial price premia in the Pacific Northwest of the USA. In developing countries, where choices are starker, loss of markets for traditional NTFPs has removed seasonal sources of employment and income generation from relatively unskilled groups. But NTFPs remain important for the poorest of the poor, those whose crops are most likely to fail and leave them with no income, and the landless. In spite of massive urbanisation, absolute number of rural poor and forest-dependent people continue to increase.

2. Damage to residual forest from unsupervised logging was used heavily by environmental NGOs during the 1970s/1990s as a reason for promoting less environmentally damaging forms of forest use. The harvest of NTFPs was advertised, and promoted by some NGOs and the private sector, as being environmentally neutral and sustainable, at least in comparison with uncontrolled tractor logging. Subsequently, participatory assessment of NTFPs was promoted as a means of generating interest in the definition of household and community claims to resource rights (R6352). The promoters of these assessments were sometimes strong on social sciences but almost invariably weak on biometrics. The frequent assessment of multi-stemmed bamboos and rattans, as if they were single-stemmed trees, is an example of the errors.

3. The Government of the United Kingdom re-emphasised its commitment to eradicate poverty in the White Paper on International Development published in November 1997. Projects to promote increased harvesting of NTFPs, for improved household nutrition, employment and income, without knowing if increased harvesting is sustainable, would not accord with the U.K.'s commitments to the UNCED'92 agreements from the environmental summit meeting in Rio de Janeiro in 1992. It is therefore appropriate to assist development projects to make accurate and precise assessments of the NTFP resources.

4. Although NTFPs have been used and traded for thousands of years, remarkably little study has been devoted to their accurate assessment. Forest products so widely and traditionally traded have naturally been taxed, and much of the large volume of legislation on NTFPs concerns their assessment for tax purposes. The FRP study may involve association with the efforts of FAO/FOPW to determine national-levels flows of NTFPs, especially for FRA 2000, but it is not primarily directed to that end.

Purpose

5. The primary purpose of the FRP study is to develop experimentally the most biometrically- adequate procedures for assessing the standing stock, the production dynamics, the harvestable components and the actual harvests of the main types of NTFPs in the tropics and sub-tropics.

6. The study will not deal with assessment methods for products transformed or processed beyond the usual first point of sale. For example, the study might examine methods for determining losses due to cleaning, washing, drying and preliminary grading but would not deal with methods for losses during solvent extraction. The study might take note of methods in traditional or current use for NTFP assessment by households and at local community level, but it is not the purpose of this project to reconcile

110 biometrically-adequate methods with "household" methods. This latter task might be taken up in subsequent projects specific to particular products and communities.

Clients

7. The anticipated clients for this work are community-based organisations, NGOs, private sector and government forest managers who need reliable information for determination and allocation of sustainable yields of particular NTFPs in particular forests (local forest management units). It is assumed that the clients are literate and moderately numerate.

Project sequence 8. The study as currently envisaged would involve the following stages: 8a. background or position paper (see paragraph 9 below); 8b. circulation of the position paper by mail and Internet for comment; 8c. restricted call for proposals to manage a long-term project; 8d. selection of a project managing organisation; 8e. workshop to be organised by ETFRN to agree more precisely on experimental sub-projects, implementing agencies, sub-project logframes with activities and outputs (QQT), accounting and reporting procedures, communication systems between collaborators, publication and promotion methods, training; 8f. issue of sub-contracts, perhaps after bidding processes, to collaborators for sub- 8g. workshops at intervals for collaborators and for testing of biometrically-preferred methods; 8h. multi-part field manuals, videos, posters, etc., for dissemination; it is likely that the manuals will detail a variety of biometrically-adequate methods and provide decision support systems to guide users to select the most appropriate method for their own purposes; 8i. training courses for clients.

Background or position paper 9. A position paper is required to: 9a. examine functional typologies of NTFPs (including Brown & Shiel, Peters, Stork, Wyatt) and develop or adapt a typology for the purposes of this project. This typology would not necessarily correspond to the groupings used by FAO or for tax purposes. Categories might distinguish motile/sessile; clumped/dispersed; single-/multi-stemmed; fruits & nuts; gums, resins and latex; leaves; lianas, bamboos and rattans; forest cave products; hidden products such as incense wood and tropical amber. The following products should NOT be addressed: timber, fuelwood, charcoal, lac, medicinal plants harvested as whole plants. 9b. review the biometric adequacy of NTFP assessment methods reported in the formal and grey literature for each major class in the typology, with respect to the production stages mentioned in paragraph 5 above, pointing out both desirable and undesirable procedures. 9c. draw attention to particular problems with the assessment methods reported to be in use or to have been used, and suggest how they might be solved. 9d. recommend the types of comparative experiments which should be carried out for each major class of the typology to develop assessment methods congruent with the needs for the production stages mentioned in paragraph 5 above. 9e. suggest an organisational framework for the efficient implementation of a project to improve the biometric adequacy of NTFP assesment, including provision for expertise broadly disprsed in industrialised and developing countries.

111 9f. be presented in a form acceptable for immediate publication (camera-ready) as a printed document, with full bibliographic apparatus, and also in a form which can be readily loaded into and be accessible from an Internet website.

112 Appendix 2 List of people contacted All of the following people contributed in some way to the review, either by passing on references, providing complementary copies of papers or engaging in stimulating conversation on the difficulties of inventorying almost anything from a tropical forest. The report would not be half as long or comprehensive without their contributions. Their assistance is gratefully acknowledged.

Sources of personnal communications

Name Location Acworth James Mount Cameroon Project, Limbe Botanical Gardens, Cameroon. Bailey Brent University of West Virginia, USA. Bird Neil Natural Resources International, Chatham, UK. Bolwes-Lyon David Student, Oxford, UK. Brown Nick Oxford Forestry Institute, Oxford, UK. Burn Bob Statistical Advisory Centre, University of Reading., UK. Gauthier Michelle Food and Agriculture Organisation, Rome, Italy. Grossmann Carol Institute of World Forestry, Germany. Hall John School of Agriculture and Forest Sciences, University of Wales, Bangor, UK. Harris David Royal Botanic Gardens, Edinburgh, UK. Hawthorne William Private consultant, Oxford. Healey John School of Agriculture and Forest Sciences, Univeristy of Wales, Bangor, UK. Kerns Becky Pacific NW Research Station, Corvallis, Oregon, USA. Leidi Sandro Statistical Advisory Centre, University of Reading, UK. Mallet Patrick Falls Brook Centre, Canada. Molina Randy Pacific NW Research Station, Corvallis, Oregon, USA. Parren Marc PhD student, Agricultural Univeristy, Wageningen, The Netherlands. Phillips Oliver Geography Department, University of Leeds, UK. Pilz Dave Pacific NW Research Station, Corvallis, Oregon, USA. Preto Giovanni Food and Agriculture Organisation, Rome, Italy. Rock Janet US Forest Service. Schreckenberg Kate Overseas Development Institute, London, UK. Shanley Patricia PhD student Kent at Canterbury, UK. Shiel Doug CIFOR, Bogor, Indonesia. Vanclay Jerry Southern Cross University, New South Wales, Australia. Wilkie Peter Royal Botanical Gardens Edinburgh, UK Wilson Ian Statistics Advisory Centre, University of Reading, UK. Wright Howard Oxford Forestry Institute, Oxford, UK. Zea Eduardo Bogota, Colombia / Princeton University, USA.

Other people contacted

Name Location Abbott Joanne International Institute for Environment and Development, London, UK. Abell Trevor Natural Resources Institute, Chatham, UK. Aldrich Mark World Conservation Monitoring Centre, Cambridge, UK. Arnold Mike Private consultant, Oxford, UK. Bass Steve International Institute for Environment and Development, London, UK. Burnam Philip C University College London, UK. Cahalan Christine School of Agriculture and Forest Sciences, University of Wales, Bangor, UK. Campbell Bruce Institiute of Environmental Studies, UK. Carter-Lengeler Jane Intercooperation, Switerland. Coppen John W. International specialist Culverwell James Doolan Sean Birdlife International UK, Cambridge, UK. Dunn Justine Grenada. Edwards Ian Royal Botanic Gardens, Edinburgh, UK. Evans Tom Oxford Forestry Institute, Oxford, UK. Gartlan Steve World Wildlife Fund, Cameroon. Gordon Anne Natural Resources Institute, Chatham, UK.

113 Name Location Green Clinton Consultant Harrison Mike LTS, Edinburgh. Hilton Guy Institute of Ecology and Resource Management, UK. Irwin Ben School of Agriculture and Forest Sciences, University of Wales, Bangor, UK. Jonkers Wyb Tropenbos, Waageningen, The Netherlands. Klienn Christoff CATIE, Costa Rica. Laird Sarah PhD Student. Lawrence Anna Green College, Oxford, UK. Leakey Roger Institute of Terrestrial Ecology, Edinburgh, UK. Longman George Just World Trading, UK. Lowore Jimmy Zimbabwe. Lund H. Gyde Research forester, USA. Lutrell Cecilia PhD student, Sussex University. Malla Yam AERDD, University of Reading. Malleson Ruth University College London, UK. Marmillod Daniel CATIE, Costa Rica. Martin Gary People & Plants Initiative, Paris. McCormack Anne MSc student, Oxford Forestry Institute, Oxford, UK. Milliken William Royal Botanic Gardens Edinburgh, UK. Mitchell Al Canadian Forest Service, Victoria, Canada. Morakinyo Tunde Living Earth, London. Niskanen Anssi Europeean Forestry Institute, Joensuu, Finland. Omland Mari Conservation International, Washington DC. Orchard John Natural Resources International, Chatham. O'Reilly Shelagh School of Agriculture and Forest Sciences, University of Wales, Bangor, UK. Palmer John Natural Resources International, Chatham, UK. Reitbergen Simon International Union for the Conservation of Nature, Gland, Switerland. Roby Andy Department for International Development, London, UK. Schippers Rudy Natural Resources International, Chatham, UK. Shawe Keith Natural Resources International, Chatham, UK. Sowerby James Shell International Renewables Stewart Martin Natural Resources International, Chatham, UK Swaine Mike Department of Plant Sciences, Aberdeen University. Tchamou Nicodeme CARPE Central African Regional Programme, Yaounde, Cameroon. Watt Alan Institute for Terrestrial Ecology, Edinburgh, UK. Vance Nan Forest Services Laboratory Oregon State University, USA.

114 Appendix 3 NTFP typologies A. Typology for national NTFP accounting (after Chanrasekharan 1995) A. Live plants and parts of plants Live plants Parts of plants (fresh, cut, dried or crushed), collected for specific uses Specific parts of plants with multiple uses, not included under the previous group Vegetable materials not elsewhere classified Raw exudates and similar natural products B. Animal and animal products Live animals Animal products C. Prepared / manufactured products Prepared (provisionally preserved) edible products Prepared beverages Prepared animal feed/fodder Vegetable oils/fats Animal fats/oils Prepared waxes of animal or vegetable origin Dying and colouring extracts of plant or animal origin Phytopharmaceutical/medical extracts, galenicals, medicaments Essential oils and their concentrates Rosin and rosin derivatives Processed gums and latex Fuels and alcohols Other basic organic/phytochemicals Prepared bark products Plaited products Products of natural fibre Tanned leather, fur and products of taxidermy Miscellaneous products, manufactured from non-wodd forest raw materials Other non-wood plant and animal products n.e.c. D. Services Forest-based services

B. End use classification (after Wyatt 1991) Category Code Sponges, chewing sticks, tooth cleaners A Bathing sponge AA Chewing sponge & sticks AB Tooth cleaners AC Aphrodisiac AD Fibres, bast fibres, jute, cloth B Basketry (fish traps, furniture, BA ornaments) Jute fibre BB Wool BC Cloth BD Pestles BE Foodstuffs C Wild fruit CA Sweeteners CB Neutralisers CC Vegetables & mushrooms CD Edible leaves CE Water, beverages & wine D Water DA Beverages DB Wine DC Intoxicants DD Medicinal plants E Medicinals plants EA Latex, rubbers, gums and resins F Latex FA Adulterants FB Bird lime FC Coagulants FD Gum FE Resin FF Gum copal FG Gutta percha FH Decorative beads G Decorative seeds GA

115 C. Plant use classification as used by ethnobotanists Prance et al (1987) Edwards (1991) Boom (1989) Valkenberg (1997) Salick et al (1995) Edible No use Food Timber Aesthetic Construction General purpose Fuel Special purpose wood Construction material Technology Timber Construction Bark/leaves Edible Miscellaneous NTFPs not in trade Medicinal Edible fat: Firewood Remedies NTFPs in trade Posionous Fruit Hunting Religion Commercial Exudate Animal habitat Miscellaneous Medicinal Intoxicant No use (inculding Medicinal firewood) Oils Malhotra et al. (1991) Posion Raw materials for commercial sale or processing Resins etc. Subsistence food or drinks Shade Animal fodder Timber Fuel Utility Timber and fibres for tools and construction purposes Non-timber wood Medicinals Other

D. Grouping of NWFPs according to feasibility criteria for forest inventory NWFP Group description Examples Comments group 1 Non-wood tree parts Fruits,leaves, twigs Can be related to tree dimensions 2 Products from ‘tree like’ plants Bamboo, rattan Relatively easy measurable dimensions 3 Herbs and other plants Medicinal and Some specific properties to be taken into aromatic herbs consideration when incorporating into standard forest inventories (after Kleinn et al 1996)

E. NTFP classification based on life form and plant parts (McCormack 1998) Animals Plants Perennial species & Trees Wood products Bark Non-trees Climbers Lianas Rattans Non-climbers Palms Bamboo Epiphytes Shrubs Ephemeral products from E.g. Fruit, Fluff from seed cases, Nuts / seeds, Oil seeds, perennial species Apical buds, Leaves Ephemeral species E.g. Herbs, mushrooms, wild honey

F. Lifeform classification as used in multi-species resource assessments Wong (1998) Dunn et al (1994) FitzGibbon et al Lahm (1993) Gadsby & (1995) Jenkins 1992 Non-timber trees Climbers Primates Reptiles Insectivores Herbs Shrubs Duikers Pangolin Bats Climbers Palms/bamboo Elephant shrews Rodents Primates Rattans Marantacae Squirrels Primates Rodents Non-timber trees Carnivores Carnivores Rattan Ungulates

116 G. Provisional categorisation of NTFPs according to management characteristics (Wiersum 1999) Supply characteristics 1. Production characteristics - Degree of ecological sustainability of extraction - Ease of vegetative or regenerative propagation - Ease of cultivation under different environmental conditions - Ease of stimulating production by technological means 2. Organisation of production - Access to NTFP resources - Gender division of production responsibilities Demand characteristics 1. Opportunistically collected products for subsistence consumption not related to main household needs (e.g. snack foods) 2. Occassionally collected products purposively collected in times of emergency (e.g. medicinal products, emergency foods during droughts - Products for regular household consumption - Easy to subsitute with products of other species (e.g. various food products, fodder, fuelwood 3. Difficult to subsitute with products of other species (e.g. preferred forest foods) 4. Products for sale at various market types (local, regional/national, international) - High degree of competion with substitutes - Low degree of competion with substitutes 5. Products demanded in manufactured form, and which can be locally produced giving them added value (e.g. palm sugar, liquors)

117 Appendix 4 Summary of reviewed studies

AFRICA Location Target Product Life-form Objectives Type of study Scale Summary of methodology Analysis/Results Benin Savanna trees Fruit Scattered Investigations of Phenology, Local site - Phenology - Observations of 11 species over one Phenological charts for one season. Fruit Main species: trees in gallery phenology, yields fruit yield & areas season. For 2 main species 10 trees per size class (6 yields for main species. Post-stratification Schrecken- Vitellaria forest, farms, and distribution of resource around 3 classes); Oil palm = 30 trees observed; Other species of inventory results by vegetation type. List berg 1996 paradoxa, fallows and most frequently inventory. study = 5 trees. Trees selected to be accessible and to of 125 local and botanical name Parkia savanna used trees around 3 villages represent size /environment classes. Observations equivalents. biglobosa. study villages. made of leaf, flower and fruit stage every ~ 2 weeks. Fruit yield - studied for 2 main species. Count of all fruit present on 60 trees, individual tree harvest records, estimate of pods per tree. Inventory - Point centred quarter sample point every 100m along 3 km radial transects arranged systematically at 60° intervals around centre of village. Species, local name and diameter of trees > 3 cm d or stumps > 50 cm high recorded. One of 6 vegetation types recorded for sample location. Cameroon Prunus Medicinal Low density Status and extent of Resource Reserve - Mountain divided in 5 blocks. Systematic plot layout on Size distribution of debarked stems. africana. bark canopy tree population. inventory. Mount grid 2km x 250m. Plots 50x50 m. 1 % inventory. Calculation of 95% CI. Average yield by Acworth et on high Calculation of Cameroon. Identification and measurement of all trees > 10 cm d. diameter class. Annual quotas in tonnes of al. 1998, N. altitude forest sustained yield Scoring of degree of debarking and crown health. bark calculated for each block. Ndam pers margin quotas Independent cross-check of 10% of plots. Yield - comm. replicated field studies (a) yields recorded from 150 trees (b) dimensions and bark thickness for 200 trees. Cameroon Prunus Medicinal Low density Availability and Resource Reserve - Trees counted and measured in 25x500m plots at six Average bark production per tree, no. of africana. bark canopy tree distribution of sp. on inventory. Mount sites. Seedlings counted in 3 2x2m nested sub-plots. trees required to support exploitation Cunningham on high Mount Cameroon Cameroon. Visual estimate of bark removal. Plots subjectively levels & Mbenkum altitude forest located in Prunus rich forest by local informants 1993 margin Cameroon Plants Many Trees and Determination of the Ecological Local -2 Associated socio-economic surveys: a reconnaissance Post-stratification using the size class woody lianas supply of NTFPs in inventory. logging NTFP survey in 5 villages to record the types and distributions and ecological factors. Low Dijk 1999a, in primary high various forest types Impact study. concessions importance of NTFPs, a market survey in two major plant densities and numerous vegetation Dijk 1999b forest and and of human markets and a hunter survey using a daily diary of 28 types confounded the analyses which had farmlands. impact on the hunters over 3 months. to be pooled. At forest community level the availability of Plot selection from air photo interpretation with 34 species composition, richness and resources. Aspects plots of 10 m x 1 km transects. Plots located to diversity were calculated. For individual of particular concern represent west-east ecological gradient with a higher species, the data were analysed for the are: SI close to villages used in socio-economic study. influence of physiography, vegetation A. The abundance Enumeration of trees > 10 cm d, lianas > 5 cm d. structure and overall environmental and distribution of Vegetation classified according to the type and degree gradients - habitat types were determined species with regard of disturbance and physiographic position. Saplings, and used as the basis for calculating to their habitat shrubs, small lianas and vines > 1 m height and d < 10 abundance. preferences. cm d tape measured for key species and d estimated The impact of harvesting was determined

118 Location Target Product Life-form Objectives Type of study Scale Summary of methodology Analysis/Results B. The impact of for other species in 10x10 m subplots at 100m by examining population structures under NTFP extraction on intervals along transect and tallied into 3 d classes: < 1 different intensities of exploitation and the available cm, 1-5 cm, 5-10 cm. Seedlings defined as individuals post-stratification with respect to distance resources. < 1 m height, enumerated from 1 x 1 m subplots from a village or road. C. The impact of placed in the sapling plots. Small lianas, vines and agriculture on the herbaceous species only included if they are of special available resources. importance - number of clumps counted. D. The influence of All species recognised by field recorders enumerated. commercial timber Vernacular names in Bulu used with scientific names exploitation on the taken from literature, other studies, field checks and availability of NTFP some specimen collection. resources. Selected important NTFPs not encountered in the sample plots were inventoried in collection sites. Trees enumerated from transects and herbs from random sample plots in which clump counts were made. Cameroon Mammals: 1 Bushmeat. Animals in To assign Resource Reserve - Resource survey: 6 foot surveys undertaken (total 15 1. Provisional species list with relative insectivore, 12 primary forest conservation survey. Hunter proposed days walking) along existing hunters tracks. All animal abundance. 2. Account of hunting Gadsby & bats, 15 priorities for rare survey. Etinde calls, signs and hunting signs noted but not quantified. practices. 3. Management Jenkins primates, 13 animals and Forest Hunter survey using formal and informal group recommendations. 1992 rodents, 8 ecosystems. To Reserve, interview techniques. Group interviews held in 11 carnivores 7 indicate current Mount villages supplemented by informal interviews in the others. hunting levels in Cameroon field. relation to estimated prey numbers. Cameroon Mammals: Bushmeat. Mammals and Examination of the Impact study. Reserve - Interviews and observations made over 1-2 week Description of hunting & fishing activities. (mainly fish in primary impact of the Hunter survey. Korup residency in each of 9 villages - total of 96 interviews. Estimation of average earnings and levels Infield 1988 Duikers and rainforest. creation of the Park Harvest National Data collected on hunting effort and success. of off-take. Primates) &. on local records. Park Economics of hunting and sale of bushmeat examined. Fish. communities All observed carcasses (if permission given) weighed, hunting, trapping aged and sexed. Opportunistic records of all wildlife and fishing activities seen or heard, animal signs and hunting evidence and economies. observed in forest. Cameroon Tree products. Various List for selection of Ethnobotanica Reserve - Visits to markets, villages bordering forest, interviews List of products, botanical identity, end use plant parts products for further l inventory. Mount with key informants and secondary sources. Local etc. Papadopulo study according to Cameroon, names used - no vouchering. s & Gordon various criteria e.g. 1997 location of markets. Cameroon Plants. Various. Understorey Description of a Protocol. Local - Systematic sampling of parallel 10 m wide transects Data collected can be used to: plants in methodology for village spaced 100m apart to give a SI of 0.1. The transects 1) examine the effect of habitat on the Peters tropical high determining the scale. should run away from the village along compass distribution and abundance of a particular 1999b forest. distribution and bearings taking care to cross rivers rather than run species, abundance of timber alongside them. Transect distance can be varied 2) assess the impact of harvesting, and non-wood according to the results of prior inventories suggest a 3) record seedling abundance and resources in the lower SI would provide the same results. The length regeneration status, forests and of the transect is determined by topography, the 4) document the relationship between woodlands of occurrence of extensive disturbed areas. Logistics or resource abundance and village proximity. Cameroon. the judgement of the field crew. 2-5 km recommended.

119 Location Target Product Life-form Objectives Type of study Scale Summary of methodology Analysis/Results Transects marked on base map to facilitate relocation and forest type mapping. Each transect composed of a series of 10x20m plots. Slope readings taken every 20 m and slope corrections done on transect length. In each sub-plot the following are recorded: forest type, counts of all individuals of selected sp.. > 5 cm d for trees and > 1 m tall for rattans etc.. Stem d and total ht. Recorded for trees and ht for other plants. Basic observations on vigour, reproductive condition and evidence of harvesting recorded for every individual. Every 100 m on transect, a 5x5m regeneration plot should be placed in the upper left corner of the subplot. In this all seedlings and saplings <= 1 m in ht tallied into 1-50 and 51-100 cm ht classes. Evidence of herbivory or trampling also recorded. Strongly recommendation that a brief ethnobotanical survey be conducted prior to inventory to determine which sp. should be sampled. Specimens collected for identified in a herbarium. Initially two weeks should be spent on inventory at each study site/community. Villages selected should be stratified I.e. large/small, near road/far from road etc. Cameroon 15 plant taxa. Various. Understorey To quantify the Participatory Local - Species selection done from a list prepared from Data entered using Excel spreadsheet. plants and number and size inventory. Dikome & consultations with local botanists (in botanical Statistical analysis undertaken with Jandel Sunderland trees in distribution of Bonjare gardens), villagers and in the forest with village Scientific software. & Tchouto tropical high selected plant villages, inventory technicians. 15 plants chosen for inventory. Results presented for trees as mean stem 1999 forest. resources within the Mokoko Village selection based on proximity to forest and high density, basal area and density of forest. Forest levels of NTFP collection activities. harvestable stems, for rattans as the mean Reserve, Systematic 10m wide x 1 km long parallel transects density of clumps, stems and stem length. SW with 100m between transects starting in village and Data used to prepare short accounts of the Province. crossing farmlands into the forest. distribution of each selected sp. including East-west baseline laid out 1.5 km from village, line size class distributions. 800 m long=8 transects running north-south away from Errors and confidence intervals for tree village. Baseline 1.5 km from Dikome and 2 km from stem densities and stem length of rattans Bonjare. calculated. Enumeration: Trees >= 4 cm d and other plants > 0.5 m measured and recorded. Life form, phenology and evidence of harvest also recorded. Each measured individual tagged with unique identification number to facilitate monitoring. Inventory teams of 7-9 people made up of forestry staff, researchers and villagers. Central Dioscorea Staple Wild climbing Examination of Inventory. Supra- Transects 4m wide and up to 2.5km long. 4-9 Estimates of mean number of edible stems Africa spp. food tuberous potential self- national -4 transects in 4 sites in different forest types (in different per ha and mean tuber weight per ha. plants in rain sufficiency of forest countries countries). Yam density estimated by counting yam Discussion of yam density, forest type,

120 Location Target Product Life-form Objectives Type of study Scale Summary of methodology Analysis/Results Hladik & forest. people in starch stems. Sub-sample of tubers in areas of high density forest dynamics and human occupation. Dounias resources. exhumed, fresh weight of edible, fleshy part of tuber 1993 Quantification of recorded. Yam densities and weights on forest edges variety and quantity and in fallows also examined. of yams in forest. Central Hunted Bushmeat Animals in Impacts of Impact study, Reserve - Researcher accompanied 76 net hunts over 90 Abundance index = number of person- African mammals: reserved, communal net inventory Dzanga- observation days from Sept. 1993 to Dec. 1994. casts per encounter = (number of hunters Republic Cephalophus undisturbed hunting on wildlife Sangha For each hunt, the names of all participants, number of x number of net casts) / number of monticola, C. forest. populations with Special nets and the number of times the sets were set were encounters of each species. Noss 1998 dorsalis, C. respect to species Reserve recorded. Species, weight, measurement, estimated Wildlife population density, net hunts & Noss callipygus & distribution, age age and reproductive stage recorded for all captured treated as 'drive counts' with the census 1999 Atherurus structure and sex animals. Numbers and species of escaped animals area determined by the length and width of africanus. ratios of captured noted. Individual net measures several times during the hunted area I.e. net circle diameter animals study period. and length of hunting path. Diameter of net circle calculated from average number of nets used and average net length. Comparison of offtake with estimate of overexploitation using 3 theoretical methods (Robinson & Redford, Western / Caughley & Krebs and Bodmer et al). Equatorial Hunted forest Bushmeat Mammals in Impact of Market Regional - Species and numbers of fresh carcasses brought into Maximal sustainable harvest calculated Guinea mammals, primary and commercial hunting recording. Bioko & Rio markets counted for 212 days at each location over using Robinson & Redford's method and mainly secondary on forest mammals. Muni one year. Estimates made of hunting area for each compared to actual harvests. Fa et al. duikers, rainforest market (not including riverine or swamp species). 1994 primates and rodents. Gabon Game Bushmeat. Wild animals Assessment of Impact study. Regional - Paired transects at three locations: near a village, 3-4 Sex and age ratios of captured animals. animals: 2 in disturbed to impact of hunting on Complementar north- hours walk from village, 1 to 1.5 days by dugout from Species encounters per transect for day Lahm 1993 reptile, uninhabited game species. y transect & eastern village. Transects 5 km long and separated by river or and night surveys. Encounters per km Pangolin, 5 rain forest. socio- Gabon 3-4 km to avoid double-counting. Surveys- 1-1.5 km against distance along transect. Habitat rodent, 10 economic hr-1 walk - time, species, number, position and habitat selection of primates and duikers using primate, 5 surveys. type of all animals > 1 kg encountered either directly or Jacob's preference index. Post carnivore and indirectly (dung, tracks, calls or feeding signs). 6 day- stratification. 8 ungulate time and 6 night-time surveys on each transect. spp. Harvest records taken opportunistically in 3 local villages. Socio-economic survey in target village (methodology not presented). Gabon Diurnal Biomass Mammals in Aimed to assess the Inventory Reserve - 5 study sites chosen on the basis of their past logging Densities estimated using standard line- primates, lowland semi- relative species Lopé history - lines crossed 4 main forest types. At each site transect techniques (Burnham et al 1980) White 1994 ruminants, evergreen contributions to total Reserve 1 x 5 km square drawn on map and a 1m x 5 km using the effective distance and detection pigs, tropical rain mammalian transect line located randomly perpendicular to 1 km distances of Whitesides et al 1988. elephants and forest biomass, in order to: boundary. Since defecation rates not known, the squirrels. (I) determine Standard line-transect method were used to census dung counts were treated as indices of whether dominance animal sightings commencing at 6:30 -9:30 am. abundance rather than density estimates. of elephant is a Census conducted in each site at least once per Wide range of parametrics (with norm in central month at monthly intervals for 2 periods of 14 months. appropriate transformations) and non- African rain forests, Standard dung counts for elephant and duiker dungs parametric statistics used with one-way

121 Location Target Product Life-form Objectives Type of study Scale Summary of methodology Analysis/Results (ii) enable ape nest sightings were also recorded in roughly half ANOVA with Tukey HSD multiple comparison with of the census. 21-43 census undertaken on each comparisons was used to test for between other African sites transect. site differences. for which data exist, Decay of fresh gorilla (n=57) and chimpanzee (84) Biomass calculations used estimates of (iii) contribute nests and elephant dung piles (1164) monitored to group size and published body mass data. baseline data which estimate losses in one month. may enable causes of variation in tropical mammalian biomass to be evaluated. Ghana Achatina Edible Forest- To provide data to Population Reserve, In each of the two arms of the reserve, 2 50x50 m Difference in snail density between the achatina giant dwelling substantiate density Krokosua zones were demarcated and subdivided into 25 sub- reserve arms tested using chi square test Duah & African gastropod anecdotal accounts estimate. Hills Forest quadrats of 10x10 m. 10 sub-quadrats selected (results significant). Monney snail of snail population Reserve randomly from each zone. Each sub-quadrat searched Hunter survey used to generate the 1999 depletion. Study thoroughly for snails crawling or resting under leaf average number of snails collected per sought to provide litter, crevices, under rocks, stems of shrubs and day. data on population spaces between buttress roots. Collections took place density, food and on two occasions at each site. feeding activities. In addition, the number of snails collected per day over 10 days by ten randomly selected snail hunters were recorded and measured. Ghana Mammals. Bushmeat Wild animals Better Market survey Regional - Trade network - formal & informal interviews over Volumes and value of bushmeat coming in high forest understanding of the catchment several months in main urban market, villages and into market over study period by species, Falconer region value of forest for of Kumasi roadside 'chop bars'. Intensive 3 week survey over 3 per month, processing, source etc. 1992b policy making and (urban) months. Recording of species, source, ecological Estimated annual value of bushmeat forest management market zone, capture method, sex, price, weight and transport wholesale trade. Consumer demand and planning. charges for every animal entering market between preferences. Profiles of hunting practices Examination of 06:30 and 17:30. Marketed volumes - market census, and proportions entering commercial demand and trader interviews and road and lorry station records. trade. assessment of Hunting practices - hunter interviews. Consumption supply in forest patterns - consumer surveys in urban & rural areas reserves. and chop bar surveys. Long-term (> 25 years) daily records of species, weight, sex and value of animals entering principal urban market. Ghana All useful Many Mostly Overview of current Participatory Reserve - Parallel survey lines 100m apart. Land-use, plants and Transect records traced onto base maps plants and scattered land-use patterns. mapping. Adwenaase animal signs recorded for 100m portions of line=1ha to create land use map. Data summaries Gronow & animals. individuals in Information on the and Namtee grid square. Lines pre-cut and then traversed by based on occupancy of 1ha squares. Safo 1996 logged-over distribution of community enumeration teams. Teams included hunters and secondary important species in forests herbalists. Categories of land use, plants to note etc. forest. the forest. left to community discretion. Forest condition score and all trees > 10 cm d counted. Timber trees > 30 cm d measured. Presence in 1 ha square of any useful plant and animal sign recorded. Reference lists of land-use types, tree species, non-tree useful species and animal signs prepared and coded (to overcome spelling difficulties). Voucher specimens collected

122 Location Target Product Life-form Objectives Type of study Scale Summary of methodology Analysis/Results taken for species encountered not on the list. Ghana All vascular Biodiversit All plants in Determining Botanical National - all a) Plotless samples defined by parts of the landscape. FROGGIE program for mapping forest plants (> 2000 y reserved high conservation priority survey. Forest All species collected or recorded when met for about 2 condition, species and biodiversity indices Hawthorne species). forest areas - survey to Reserves in hours or until the discovery of unrecorded species was & Abu-Juam learn about high forest less than about 1 in 2 minutes. b) Measured plots of 5 1995, distribution of zone 5x25m contiguous strips either arranged as a square Hawthorne species and plant or end to end as a transect. c) Subjective condition 1995a communities. score given to whole Forest Reserve. Ghana 7 trees NTFP All species (a) to demonstrate Resource National - TSP inventory. 814 systematic 20x500m plots on 2x2 Strategic management profiles for (understorey) species uncommon significance of inventory. High forest km grid (primarily for timber inventory). Trees- selected sp.. Wong 1998, 17 herbs widely and low NTFPs (b) zone diameter, Herbs- clump count, Climbers- stem count, Falconer (understorey) traded or density except quantification of Canes- count of immature, mature and cut stems per 1992a&b, 26 climbers believed some herbs NTFP resources clump. Bird 1990 (lianas) 5 to be which are known to be widely canes (rattan). scarce. locally traded or believed to dominant. be scarce. Kenya Hunted Bushmeat Populations To assess the extent Resource Reserve - 1) Animal density: Random sampling of 28 1 km line- Post stratification according to cover within mammals: occurring in of subsistence inventory. Arabuko- transects distributed between three forest types, half 4m of ground. High & low hunting pressure FitzGibbon Primates (2 natural hunting and Sokoke on periphery and half central to represent differential transects compared using t test. Maximum et al. 1995 spp.), duikers woodland & trapping. To Forest hunting pressure. Hunters traps up to 15 m from sustainable harvest estimated using (4 spp.), forest. determine the effect transect counted. Animal signs counted as dung Robinson & Redford's method. bushpig, of harvesting on (duiker) and nests (golden-rumped elephant shrews) elephant densities of within 3 m, tracks (4-toed elephant shrews) shrews (2 mammalian prey. intercepting transect and bushpig signs within 10m. spp.), and Counts done by local tracker and researcher. Primates squirrels (2 & squirrels within 50m enumerated on 3 weekly dawn spp.). walks, distance to group and number of individuals recorded. Vegetation characteristics recorded at 10 and 40 m intervals along transect. Mark-recapture for elephant shrews and dung production & decay rates for duikers used to convert sign abundance to densities. 2) Socio-economic survey: Household hunting survey of 51 households close and 24 2 km from forest as part of more general survey. Voluntary hunting records of 16 hunters. Malawi Bees & Honey, Insects living Development of Resource Reserve - Caterpillars - sampling in 50x50 m management plots Caterpillars - Friedman 2-way ANOVA, Saturniidae beeswax in woodland case for local use of inventory. Kasungu established 15 years previously. Enumeration of; Chi-square test Questionnaire - Chi- Munthali & caterpillars. & Mopane only found Park to support National species being exploited, forage tree species, height square test Tables of margins for bee- Mughogho worm within National livelihoods - Park. class of trees, burning history and dry weight of keeping, caterpillar collection and 1992 Park Assessment of processed caterpillars. Bee-keeping - Obtained from agriculture. productivity and study in Nyika National Park. Questionnaire - gross margins of structured and open-ended questions - random bees and caterpillar selection of 40 family heads for interview. utilisation & willingness of local people to engage in

123 Location Target Product Life-form Objectives Type of study Scale Summary of methodology Analysis/Results activities. Malawi Brachystegia Bark fibre. Scattered 1) identification of Resource Reserve - 6 transect walks along footpaths; 5 5x20 plots Descriptive statistics (means, sd, spp. low(?) density site conditions for inventory. Liwonde enumerated every 50m. Insufficient sample trees normality) Influence of site and tree cover Peham 1996 saplings bark fibre sp.. 2) Forest found therefore increased plot size to 20x100, 200m on presence/absence of saplings (Chi² impression of Reserve apart. This was also unsatisfactory (5 individuals test). Influence of site on amount of bark amount of resource located) so sampling was targeted at known fibre or number of saplings. Two-way available in local collecting areas. 5 cruises were undertaken with interactions between amount and site and area. 10x50m plots located 100m apart or at changes in tree cover. vegetation type to correspond to air photos. Plots divided into 10m sections and flagged if fibre species were present for subsequent recording of site characters and sapling enumeration. Height of harvestable stem and mid-height diameter were recorded. For a subsample, bark was harvested and compared to calculated bark area. Namibia Hyphaene Fruit, palm Multi-stemmed Assess status of Impact study. Local - Systematic cluster sampling of 100x100 m quadrats Comparison between sites and with other petersiana heart, palm common populations in Onayena & placed systematically in lines of 2-3 at 100 m intervals. studies using percent occurrence. ANOVA Sullivan et (Palm). palm wine, and abundant selected areas. To Iikeke areas, Each transect was situated approx. 1 km apart on two tests on height and basal diameter al. 1995, basketry, in palm derive an north-central sites chosen to represent high and low human and between sites. Stand curves in height size Konstant et fencing savanna. understanding of the Namibia livestock densities. 10 quadrats enumerated from each classes by gender. Frequency distribution al. 1995 materials, impact of utilisation site with 2 from Forestry Dept. exclusion zone (recent of clump size. building on population regeneration). Enumeration: signs of utilisation, height, poles. structure. Make basal diameter, clump size, gender, numbers of stems predictions of per quadrat. possible population changes due to heavy exploitation. Assess impact of human and livestock density. Nigeria 4 climbers Economic All species To provide Resource State-wide - TSP inventory. 130 systematic 20x500m & 40x250m Density of resources by forest type (lianas), 5 ally uncommon quantitative data inventory. Cross River plots - 1 plot per 2 km² on grid. Shrubs- tally < 1m/ Wong 1993, shrubs, 4 valuable and low required to formulate State forest >1m tall; Climbers- tally regeneration/mature; Dunn et al. palms / sp.. density strategic areas Palms/bamboo- count; Marantaceae- tally by clump 1994 bamboo, management plan size; Trees- tally immature/mature; Canes- tally stems Marantacae, 8 per clump into immature/mature/cut. trees, 2 types of canes. South Africa Species Baskets, Trees, palms, Identify and quantify Ethnobotanica Local - Names of plant species used in craftwork identified in Evaluation of management options for providing mortars, rushes indigenous plant l. Harvest Manguzi two local languages in field - specimens collected and craftwork raw materials. Cunningham craftwork raw spoons growing in material to supply a records. Hospital identified in herbarium. Completed craftwork items 1987 materials. etc. Maputaland craftwork project as Health Ward weighed. Mean wts multiplied by production records to coastal plain. a basis for resource determine weight of plant materials used annually. management Green to dry, processed weight conversion determined proposals. for Hyphaene coriacea to estimate number of palm leaves used for comparison with available growth data. Was not possible to relate quantities to productivity for

124 Location Target Product Life-form Objectives Type of study Scale Summary of methodology Analysis/Results other plants as not enough information on size/productivity etc. relationships available. South Africa Hyphaene Palm Multi-stemmed Assessment of leaf Productivity. Local - Leaf production - Selectively chosen study sites. Site A Annual leaf production by leaf length coriacea. leaves for palm common production in order Maputaland -16 stems marked, site B -34 stems marked. Leaf (surrogate for plant size). Table of leaf Cunningham basketry and abundant to provide a basis palmveld production measured by measuring total length of availability by size for study sites. Estimate 1988 in palmveld for management of leaves on stem (partially opened leaves counted as of annual commercial leaf production per leaf harvesting for fraction of open leaf). Leaf growth measured monthly. ha. Management recommendations. rural craftwork Leaf utilisation - 4 sites at varying distances from road. industries. Plots 50x50m or 20x20m laid out at each site. All stems within plots examined for leaf damage and measurements made of leaf length. Previous(?) years leaf production examined for harvest assessments. South Africa Hyphaene Sap = Multi-stemmed Assessment of Interviews and Local - 18 tappers interviewed by local field assistant Evaluation of potential and alternative coriacea & palm wine palms economic yield Ingwavuma concerning no. of palms tapped & max. yields. Daily management scenarios for palmveld and Cunningham Phoenix occurring at importance, observations. District measurement for 10 mths of yields from different palm palm wine production. 1990 reclinata. high density in dynamics and groups and sp.. Collected by one representative full- coastal plain effects of palm wine time tapper. Damage assessment in terms of (i) palm palmveld. tapping for policy and stems dead, (ii) tapped stem dead but palm alive development. (iii) tapped stem recovering; from sample of 203 palms. South Africa Rumohra Fern Polymorphic Information required Demographic Research - Population structure - 3 parallel transects orientated Population size structure plotted as bar adiantiformis fronds terrestrial fern to advise managers & harvesting Groenkop east-west. On each transect circular plots of 0.5 m charts. Regression analysis undertaken to Geldenhuys (decorativ in semi-dense concerning impacts. Forest, radius located 5 m apart (39, 43 and 32 plots in each determine that the best predictor of lamina & Merwe e) moist forest. controlled southern transect). In each plot the number of fronds in each of size is stalk length. 1988 exploitation of Cape 5 developmental stages were counted. Six months Seasonal variation of bud density and fronds. 3 research province. later, in 10 plots per transect; counted fronds and maturation times determined using questions: measured stalk length and width, length and surface monthly averages for all plots. Results (1) understanding of area of each lamina in each developmental stage. used with local weather data to create a population Growth rates - every month for a year a new line model of harvestable frond densities demographics, transect was marked at random through the fern suitable for harvest planning. (2) determining stands. 20-30 new buds touching the line were tagged. ANOVA used to test for differences in optimal harvesting Every fortnight the following was recorded: frond frond size between treatments. strategies, stage, stalk length, length, width and area of lamina. (3) extensive Frond growth rate calculated as the average length of monitoring of time a frond remained in a particular developmental exploitation. stage. Treatment plots -8 blocks selected to represent a gradient from dense to sparse stands. Each block divided into 3 plots of 3x3 m with an inner measurement plot of 2x2 m. 3 treatments applied: (1) control, no picking, (2) 22 week picking of all utilisable fronds, (3) 4,3 weeks picking of all utilisable fronds. Treatments applied for 1 year (July 1982-August 1983). Buds, young, mature and overmature frond stages counted monthly. Total number of fronds calculated by correcting counts using bud growth rates to adjust for repeat counts of buds. Towards end of

125 Location Target Product Life-form Objectives Type of study Scale Summary of methodology Analysis/Results treatments, the lamina length and width of all mature fronds in plots measured to determine the effect of treatment on frond size. Sudan Acacia Edible Scattered Develop a Multi-purpose Pilot study Woody vegetation: Systematic 7 km grid with random Results analysed on computer and nilotica, all gum (Gum trees in forest vegetation mapping resource for regional start and post-stratification based on vegetation maps. displayed as maps, tables and databases. Lund 1998a trees. Arabic), and farmland and inventory inventory inventory - 58 plots - 20x100m. Trees & shrubs > 5 cm at root fuelwood, programme that (MRI). Gum belt collar enumerated. Tree data: species, d, diameter at constructi would provide base root collar, bole height, total height, crown diameter, % on information on cull. Plot information: land cover class, type, condition, materials woody vegetation for tree density and estimates of soil texture class. 1x10m gum production, regeneration subplot. Data collected from sample plots fuelwood etc. to generate individual tree volume tables for wood utilising the latest down to 2 cm in diameter and 0.5 m long using mapping diameter at root collar, total height and crown diameter technologies. in regression equation. Socio-economic survey: Interviews, transects established from centre of village to edge of village lands to record chronological and spatial variation in ground cover, changing land use and general soil capability. Uganda Hardwoods, Building Trees and Quantification of key Training Reserve - Trees: 20x20m (3 / 4 plots at 3 sites) assessing Histograms of recorded categories, Poles, Large poles, bamboo found plant resources for exercise. Bwindi density and suitability of trees for building poles (> 5 species and sizes. Cunningham trees, Bean in primary identification of Resource Impenetrabl cm d) and bean stakes (>1.5 cm d) and level of 1996a Bamboo. stakes, forest vulnerability to over- inventory. e National cutting. Bamboo: 4, 10x10m plots. Large trees: 1 site, Beer exploitation Park 100x100m plot, all trees > 30 cm d. 7-point scale of boats. bark damage used to compare medicinal bark collection with elephant damage in 2 100x100m plots for all trees > 10 cm d. Uganda Useful plants Many Scattered Involvement of local Participatory Reserve - Information gathered at series of village meetings and Informant-based information used to map e.g. lianas, plants in high people in park inventory. Bwindi, forest walks. Bamboo assessment [Mount Elgon] (1) resource use, determine demand and in Watts et al. bamboo, forest management Harvest Mount Elgon semi-structured interviews (10-20% of households) for rapid vulnerability assessment. Bamboo 1996, Scott medicinal Monitoring of yields records. & Rwenzori demand assessment in 14 parishes (2) 3 sites quota determined. Monitoring - not 1998 plants. Mountains selected, 170 10x20m plots surveyed by harvesters, complete as this is action research in a National besides standard quantitative information on culm process approach. Parks number etc. plots scored for popularity (access and quality) by harvesters. Monitoring- (1) Formal PSPs managed by Parks staff. (2) In forest harvest records of official quota by Parks staff - plots to be established in areas with heavy harvests. Zaire Cephalophus Bushmeat. 5 sp.. of Development of Methodology. Local -Maji Each study site was 3 km² in extent and included Line transect data -4 estimators applied: spp. ungulates in easily executed Mbili (MM) mixed primary forest and differed from each other in generalised exponential, Fourier series, Koster & moist population indices and Kapituri terms of hunting pressure. polynomial and Kelker. Computer Hart 1988 evergreen for duikers. (K) areas Pellet-group transects: 15 randomly located transects programme LINETRAN used to calculate high forest. Comparison of drive close to 400m long at each site. Field work undertaken in dry density estimates. Examined accuracy and counts, track counts Epulu village season. Transect walked at constant speed (av. 22 precision of estimators on pellet group and pellet group in Ituri mins per transect) and ground either side scanned for density from test transects and counts. forest. pellet groups. Perpendicular distances from transect to simulations. pellet group, relative size (small or large duiker), Pellet group counts- Fourier series and

126 Location Target Product Life-form Objectives Type of study Scale Summary of methodology Analysis/Results distance along transect and approximate age generalised exponential estimators yielded recorded. best results. Daily defecation rates tested Test transects: 2 140m transects established, 6 pellet using Spearman's rank correlation groups of small and large duiker droppings placed coefficient. Pellet disappearance rate randomly along transect in each of 8 0.5 m belts on estimated by plotting loss of known groups either side of transect (48 groups for each duiker size). over time as curves. Transect walked and pellet groups recorded blind on Mean duiker densities and errors one transect 6 days and the other 16 days after calculated for all methods and compared. establishment. Conclusions: line transects with Fourier Decay rate: two cohorts (5 & 12) of small pellets and series estimator works well, sample sizes one cohort (10) large pellets placed in forest and >25 with 40 recommended are needed. checked at regular intervals until they had all Difficulties with estimating pellet group disappeared. production and disappearance rates. Defecation rates: determined for 4 blue duikers and 2 bay duikers held in 10x10m pens in forest. Maintained on 4 different diets, dietary fibre levels determined and counts made of total pellet production after 3-4 weeks on each diet. Drive counts: 5 daily drive hunts covering 145 ha on two occasions at site MM site and 10 daily hunts covering 356 ha on two occasions at site K. For each drive 20-30 hunters encircled 4-12 ha of forest, circle beaten with dogs and flushed animals killed. Hunters conducted 5-6 drives per day in same general area. Results of drives for one day combined. Assumed constant effort in drive, random placement of drive with respect to animal distributions and all animals in drive area flushed. Track counts: at 2 day intervals, small seasonally dry streambeds sampled for ungulate tracks by raking natural sandbars and recording the number of tracks on 6 subsequent daily visits. 13 sites along 0.4 km of stream at MM and 32 sites along 1 km of stream at K sampled. Stream beds averaged < 2 m wide and presented no apparent barrier to animal movements and not bordered by specialised riverine vegetation. Assumed that animal movements and sampling effort similar at both sites. Zambia Mammals Meat, Motile hunted To assess the utility Monitoring. Local - Daily records of sex, ages of all wildlife referenced by Mammal densities calculated as (Impala, hides etc. animals with of employing local Luangwa habitat and location by 3 local hunters over approx. 10 counts/search time and tracked by month Marks 1994, Buffalo, Zebra, seasonally hunters to Valley sorties per month at dates, times and places chosen for each hunter. Counts of Impala, Zebra Marks 1996 Warthog, fluctuating enumerate trends in by the hunters. Hunters also kept detailed record of and Warthog (common) used as Wildebeest, numbers and wildlife populations. time spent in different activities while on hunting trips. indicators. Analysed using multiple range Elephant, etc. composition. Survey undertaken over three years (1989, 1990 & tests, ANOVA etc with SAS computer 1993). Area mapped into large blocks using locally program. recognisable topographic features and used to track hunter movements and wildlife dispersal. Other

127 Location Target Product Life-form Objectives Type of study Scale Summary of methodology Analysis/Results residents kept records of events, activities and rainfall. Zimbabwe Berchemia Dye used Deciduous Field test of Monitoring. Field test - Condition scoring for tree health, bark damage and Histograms of scores and distribution discolor. in woodland tree. appropriate Kariyangwe cutting developed with basketmakers. Size class of maps produced from data downloaded Cunningham commerci monitoring systems area, Binga tree measured using rulers. Icons used to represent onto base PC. System worked well. & al for indigenous plant district scores to facilitate recording by illiterates. Liebenberg basketry use which involve (CAMPFIRE CyberTracker software on palm-top computers used 1998 trade & local people. ) for data collection. Plots discarded due to difficulties of subsistenc plot location, unfamiliarity of techniques for plot e / establishment etc. Trees in basketmakers own fields commerci and adjacent areas monitored. al fruit.

ASIA Location Target Product Life-form Objectives Type of study Scale Summary of methodology Analysis/Results Lao Calamus Rattan Single- Determination of an Inventory Pilot study - Survey line 600 m long running perpendicular from a Alternative designs were simulated using poilanei stemmed optimal survey methodology. Ban major stream. Line divided into 100 m sections. A the data from the sub-plots. Each plot was Evans understorey design for inventory Naphong, single 20 x 100 m plot laid out perpendicular to the line divided into an appropriate number of submitted climbing palm of a commercially Bolikhamxay and centred on it at a randomly selected points in each alternative plot sizes and shapes i.e. 2 in evergreen important rattan. Province. 100 m section. Each plot sub-divided into 40 subplots 20x50 or 4 10x50 m. 12 different plot and semi- of 5 x 10 m. In all sub-plots all stems of C. poilanei configurations were tested. One of the evergreen with > 1 m between the ground and the base of the smaller plots was randomly selected for forest. petiole of the last fully expanded leaf were counted. each large plot and used to estimate the The time taken to lay out and enumerate each plot mean and SD for rattan density. The was recorded. Survey team consisted of 5 people, 2 to simulation process was repeated 11 times lay out plot and 3 to enumerate. Total area for each alternative plot size except the enumerated was 12 ha sampled at 10% SI. two largest for which only 1 calculation was possible. Data from the 11 estimates were averaged and use to calculate the coefficient of determination CV for the alternative plot size and shapes. Regression analysis was undertaken to determine an empirical relationship between plot size, shape and CV. Power analysis undertaken to determine the minimum rate of population decline that can be detected by a specific sampling design.

128 CENTRAL AMERICA Location Target Product Life-form Objectives Type of study Scale Summary of methodology Analysis/Results Belize Plants, 7 Medicines Plants in To quantify the Valuation. Research Used 2 existing plots believed to be representative of Used data in conjunction with prices to species in 2 secondary value of managed plots -Cayo the surrounding region. Plot 1: 0.28 ha, 30 year old estimate total value of medicines per ha. Balick & plots. forest forests as a source District forest. Plot 2: 0.25 ha, 50 year old forest. Marketable Used estimate of rotation at 30 and 50 Mendelsohn of traditional medicinal plant material from 5 & 4 taxa respectively years to calculate present value of 1992 medicine. was harvested, dried and weighed. Figures translated sustainable production. in total yields per ha. Belize All useful Mainly Fuelwood, To provide data for Household Reserve - Data collected on pre-designed forms: Village survey Data extrapolated from 11 study villages to plants and subsistenc wild fruits, an economic survey. Columbia (building, facilities etc.). Household survey of 10% of whole area. Computerised analysis of Campbell & animals. e use medicinal valuation of the River Forest houses for NTFPs (fuelwood, food, medicines, data. Profiles of villages, NTFP use and Mitchell plants, reserve Reserve bushmeat, cultural). House construction survey for 5% building materials. 1998 bushmeat, of houses (materials used) Women's survey (foods, household household goods and craft materials) goods, craft materials from Columbia River Forest Reserve and Maya Mountain Forest Reserve. Belize Tapirs. Bushmeat Large Impact of hunting on Population Research. 2 Study areas of 60ha, Macal River: no hunting, Rio No tapirs observed at Rio Grande so trail mammal tapirs. Description of census. study sites: - Grande: hunted. River transects: 10km section of river density used to estimate numbers using Fragoso associated tapir habitat in Macal River canoed 14 times, 8 in day, 6 at night with lights. For relationships observed at Macal River. 1991 with rivers in Belize. & Rio each observation time, number, presence of young, TWINSPAN analysis of vegetation data primary forest. Grande sex & location recorded for known individuals. used to classify 8 habitat types. Locations tagged for later vegetation sampling. Total elapsed time for transect recorded. Trail density: randomly located 3 x 530m long line transects on each side of river (6 per site). All tapir trails that intersected transect noted. First 30 m perpendicular to river, remainder parallel to river. Vegetation: 25m² quadrats located at 50m intervals along 500m long trail transect parallel to river. In each quadrat; presence of tapir cropped pants, maximum canopy height, % leaf cover, diversity and abundance of different plant life forms (herbs, vines, sapling, trees etc) in various size classes and % leaf cover at 50 cm above ground recorded. At flagged observation sites a 25m² quadrat centred on the site. Habitat use estimated from frequency of tapir encounters and browsed plants. Belize Botan palms, Thatch, Occasional Collect data on Management Compartme 10% random sample of 1 ha (100x100m) blocks laid Not reported in paper (too early). These Warre cohune, Edible plants found in potentially valuable planning - nt -Forest out for timber stock survey. [Stock survey = 100% type of epiphyte records not useful and Smith 1995 Euterpe nuts, Palm Timber NTFPs. Collect Stock survey. Reserve enumeration of all trees >40 cm d, block is mapped, discontinued. oleracea, heart, production background compartmen mean BA and slope angle recorded.] Enumeration:

129 Location Target Product Life-form Objectives Type of study Scale Summary of methodology Analysis/Results Manilkara Chicle zone of information for t Palms - count of plants > 3m tall. Sapodilla - count of sapota, Incense Chiquibul planning process. tapped and untapped trees > 20 cm d. White copal & Protium copal, resin, All Forest Development of All spice - count of trees > 20 cm d. Epiphytes - Pimenta spice, Reserve. NTFP enumeration quadrat scored from 1(absent) to 5 (abundant) for officinalis, Decorative protocols. epiphyte load. Epiphytes. plants (Orchids & Bromeliad s) Columbia Mauritia Fruit, leaf Palm in Determine Demographic. Research - Density estimates - 0.2 ha plot, all stems tagged, sex Transition matrix using Vandermeer flexuosa. fibre, stem monospecific demographic 5 ha in and height of stem measured. Number of leaves on (1979) algorithm and Lieberman & Zea pers starch etc. stands on characteristics of Oriental crown and fallen leaves recorded monthly from Mar to Lieberman (1985) growth simulation & comm. waterlogged populations in poorly Llanos Aug. Assume number of leaves remained constant so method of Caswell (1989). Statistical soils in drained savannas. Duration=6 number of fallen leaves = number of new leaves. analysis and regression modelling for: sex depressions Use a model of months Additional plot of 0.3 ha added to improve sample size. and size differences in leaf production, and riparian population dynamics Fruit production - 34 trees across size range selected annual increment in terms of height growth belts in to evaluate and inflorescences fruit harvested and counted once. and leaf production. Life table parameters lowlands. harvesting Age/size relationships - 97 trees across size range estimated using method of Cochran & scenarios. selected and leaves tagged and divisions counted Ellener (1992). (number of divisions increases in successive leaves ~ age of stem). Several trees climbed and internode lengths measured. Germination - (a) trial plantings of 216 fruit in wild and 100 in greenhouse (b) ratio of fruit to seedlings in 0.2 ha plot. Costa Rica Carludovica Hat & Perennial herb Biological-ecological Resource Research Inventory: Line-plot transects in natural patches of C. Description of best sites for C. palmata. & Panama palmata. basketry growing in patterns and impact inventory. sites? palmata. Circular 50 m² plots every 10m. Number and Recommendation for harvest timing, fibre patches in of extraction Experimental size (height & % cover) of plants recorded. intensity and plant sizes for maximum Cevallos natural forest intensity for design cutting. Topography, vegetation and light levels recorded. production. (undated) of sustainable Yield: (1) 2 treatments (0 & 100% pruning) applied to management. all 5 size classes (2) 3 treatments (1, 50 & 100% pruning) of productive plants in 1 size class. Monthly recording of growth, reproduction, and dimensions of new 'candles' for 8 months. Mexico Thrinax Leaves as Palms in Population biology Demographic. Reserve - PSPs of variable sizes depending on stem density Life table analysis using a linear radiata, thatch, dense stands of two palm species. Sian Ka'an established in 4 sites representing harvested and population projection matrix model. Olmsted & Coccothrinax stems as in dry tropical Biosphere unharvested secondary forest. 2 year study. Lefkovitch matrix models used to estimate Alvarez- readii. constructi forests and on Reserve, Survivorship: recorded every 2 months. Seedlings, in 2 finite population growth rates. Computer Buylla 1995 on coastal dunes. Quintana classes counted in subplots (2-25 m²). Saplings, 5 simulations used to explore the possible material Roo classes of juveniles and 1 m ht classes for adults. Cut sustainable harvesting regimes by varying stumps counted. Phenology: recorded monthly number of stems cut (8-400 per ha) and (number of adults flowering, inflorescences per tree, frequency (1-4 years) of cutting. Sensitivity success of infructescence production). Germination: and elasticity analysis of population growth 100-200 seeds sown into 2x2m subplots. Leaf rate. production, growth rates and age: Monthly tracking of leaves produced for 20-30 marked accessible (sub- adult) plants. Growth quantified as height increment in cm per leaf scar. For adults 3 specimens felled and

130 Location Target Product Life-form Objectives Type of study Scale Summary of methodology Analysis/Results leaf scars counted and divided by juvenile leaf production rates. Mexico Brosimum Fruit Tree in (a) Fruit quantity (b) Demographic Research Randomly located, non-nested plots used for each life Life table analysis. Change in population alicastrum. extensive Maximum Separate plots site - 3 year stage: Adults (> 1 m tall) - 25, 20 x 20 m plots, all trees structure and size over time simulated Peters 1991 monospecific sustainable fruit for each life study tagged & measured (ht & d). Seedlings - 100, 1 m² using a modified transition matrix stands yield stage and random plots. Size specific rates of growth (Ht. & d.) & (Lefkovitch 1965). variable mortality determined biweekly for 3 years for enumeration subsample of marked trees. Phenology - 10, 0.5 m² periods. circular traps under canopy of 8 trees for 2 seasons. Pollination, fruit maturation & dispersal - direct observations Nicaragua Plants. Medicines, Plants in Comparison of Biodiversity Reserve - Transects laid through forest and stratified, random Species area curves used to compare foods, managed curandero (herbalist) survey. 10 ha forest 5x2m subplots placed in strata. All plants counted, managed forest with primary and logged Salick 1992 fibres, forest (many management with at El Castillo identified from vouchers and data taken on species forest. resins, planted). timber management. (10ha), Rio richness, diversity, density and cover for plot. wood, San Juan constructi on materials etc. Nicaragua Plants Use Plants Integration of NTFPs Applied Research Forest logging- Sampling sites chosen to represent NTFP analysis focused on use (epiphytes and categories occurring in with natural forest vegetation sites, Rio relayed series of unlogged, 1 and 9 years post logging categories/10m², intensity of use/10m², Salick et al. cryptogams : primary, management. community San Juan with silvicultural treatment applied 8 yrs post logging. sp.-area curves for useful species and 1995 under- Aesthetic, logged and Investigation of an analyses. Region. [plots established in 1991]. Plots of 1 ha (with 30m plant use categories. Parametric (ANOVA represented). constructi silviculturally alternative to borders) for all trees with stratified random 100m² etc) and non-parametric (Kruskal-Wallis on, edible, treated forest. deforestation. subplots for regeneration and random 10m² sub- test) statistical analyses undertaken. firewood, Community analysis subplots for all plants. Total of 14 plots in systematic hunting, of tropical clusters on two sites. All plants enumerated and animal biodiversity and measured (details not given) species identified from habitat, regeneration. vouchers, logging damage subjectively ranked, useful intoxicant, Specifically: species identified by single 'expert' informant. medicinal, Quantification of the oils, abundance, density poison, and diversity of resins, NTFPs before and shade, after logging. timber, utility, non-timber wood, other.

131 EUROPE Location Target Product Life-form Objectives Type of study Scale Summary of methodology Analysis/Results Czech Vaccinium Berries / Indigenous Pilot figures Household National -4 Sample of national population stratified on sex, age (> Proportion of population engaged in NTFP Republic myrtillus, V. Fruit, shrubs & fungi demonstrating the survey. surveys 15 years), education, profession, household size and collection. Estimated total weight of vitis-idaea, Shrubs & in native national importance 1994-7 district/region population density. 1994 n=856 harvests. Regional variation in NTFP Sisak 1998 Rubus idaeus, Fungi. forests and of NTFPs. households, 1995 n=991, 1996 n=1451. Main collection. Estimated value of berry and R. fructicosus, Recreatio timber questions: number of forest visits per year, main mushroom harvest. Sambucus nal plantations. purpose of visits, visiting costs, (estimated) weights nigra collection (kgs) collected of berries and mushrooms, costs of Mushroom mostly for collection, market prices, willingness to pay for forest personal visit. use. Estonia Fungi Mushroom Soil fungi in Investigate the Yield Regional - Two pine heath forest types studied. 7 permanent Tables of number of and weight of all cold regional fungal investigation. Nova and sample plots were used, 3 in each of two older stand fungal fruiting bodies by species in each Kalamees & temperate productivity of pine Vihterpalu age classes and 1 in the youngest age class. forest type, age class and year. Silver 1988 forest heaths. Districts of Sample plots were quadratic or rectangular and 0.1 ha north-west in area. During the growing season all fruiting bodies Estonia harvested from plots on average every 10 days. Mushrooms sorted into inedible, edible, whole and edible wormy. Estonia Vaccinium Edible Understorey Understanding of Productivity, Regional - Measurement in 1978-84. Stepwise-linear regression used to vitis-idaea berries shrub in the production permanent North-west 24 and 5 sub-plots containing 430 and 100 permanent determine the most significant variables Männi 1988 boreal forest characteristics of sample plots and South- 1 m² quadrats respectively from north-west and south- that contribute to the variation in berry berries in relation to east Estonia east Estonia. yield. ANOVA used to determine the soil and stand Stand, soil and co-dominant characteristics recorded significance of the relationships. Two structure. and visual estimation of productivity/phenology for the factor hierarchical ANOVA used to test the V. vitis-idaea plants. degree of association between yields in a plot on successive years. Developed predictive (linear multiple-regression) equation for the productivity of the current year and for the next year in the autumn. Finland Fungi Mushroom Forest soil Contribute to an Yield. Research - 23 stands even-aged Scots Pine stands of a range of Tables and graphs illustrating the fungi in boreal understanding of the Mätäkivenm development stages and of 0.3 to 0.5 ha on sand or presence and abundance of different Hintikka forest. succession of äki in the gravel soils selected for study. Study undertaken over mushroom species in the 4 stand 1988 mycorrhizal fungi in Ruotsinkylä 2 years (1975-77). Stands placed into 9 groups in age/development classes. the roots of Scots Experimenta similar conditions: aspects, soils etc. and 4 Pine trees. l Forest development stage groups. A 20-25 m border zone around each stand was excluded from the study. All the basidocarps (mushrooms) in transects of 3 x 250 m measured by pacing were laid out. Each transect mushrooms were collected 6-11 times simultaneously in all 23 stands. 80 species identified in the study. Finland Berries and Edible Understorey Production of Harvest National Marsi inquiry. Reports are forwarded by the District mushrooms berries shrubs and estimates, forecasts forecasting & Country divided into 18 enumeration districts. Each reporter to the Marketing Research Kujala 1988 and fungi in boreal and trade statistics market survey district has a Reporter who is assisted by local Institute of the Pellervo Society where the mushroom forest. for berry and observers (200 in all). Each observer makes reports estimate of the yields is produced and

132 Location Target Product Life-form Objectives Type of study Scale Summary of methodology Analysis/Results mushroom harvests. on the quantities of berry and mushrooms in at least distributed to buyers and pickers using the 10 forests within their commune in July, August and mass media. September. Trade data used to calculate prices per At the end of the buying season another survey is kilo and total incomes. done to collect information about the quantities and prices paid at collection points to pickers by merchants. Finland Vaccinium Fruit / Understorey National yield Yield Regional - Regression equations developed for estimating berry National berry yield estimates. vitis-idaea, V. berries shrubs of cold estimation prediction. Central production from data on ecological conditions of forest Raatikainen myrtillus. temperate Finland sites. V. vitis-idaea (vegetation type, shrub cover, et al. 1984 forest. shrub height, stand age class, crown density and weather conditions), V. myrtillus (vegetation type, stand age class, tree crown density, method and degree of coppice control and weather conditions). Survey of 13-20 1000x1m sample strips in 5 counties used to estimate national yields. Finland Berries: Edible Indigenous Research into yields Monitoring. National -57 1997 - establishment of 1110 permanent study Yield forecast maps (timing of flowering Vaccinium berries dense, of economically municipalitie compartments. Berries: 5 marked 1 m² plots - counts and berry ripeness) produced to guide Saastamoin vitis-idaea, V. and fungi clumped most important s of flowers, immature and ripe fruit. Mushrooms: berry pickers. Models describing yields of en et al. myrtillus, shrubs and native berries and species identified and counted from whole most important berries. 1998 Rubus fungi in cold mushroom compartment. Other yield information: (annual chamaemorus temperate variation in yield, factors affecting yields, timing of Mushrooms: forest. flowering and ripening of berries). Other information: Boletus spp., type of growing site, proportion of tree species, Suillus spp., development class of trees. Leccinum spp., Russula spp. etc. Finland Fungi. Edible Ephemeral Eighth national Resource National 3,009 circular plots of 300 m² located systematically on Mushroom yield as fresh weight per ha. mushroom fungal fruiting forest inventory inventory. survey tracts. South & Central - survey tracts 16km Occurrence and yield of commercial Salo 1993 bodies on floor apart, aligned e-w, 1 to 4 plots 400 m apart. North - mushrooms in stands of different ages and of cold survey tracts 32 km apart, aligned n-s, 1 to 3 plots mineral soils. temperate 600m apart. 4 quadrats for sampling mushrooms(?) forest. located in each plot. Commercial mushroom presence recorded once per survey year (without regard for seasonality). Finland Shrubs: Edible fruit Understorey Development of a Forecast and National Permanent experimental plots established in easily Information sent electronically to Joensuu Vaccinium, / fungi shrubs of cold national yield inventory accessible compartments in forest and peatland on Research Station and processed using the Salo 1999 Rubus spp. temperate forecast and appropriate site types that are known to have good MASI computer-based information system. Fungi: forest inventory system berry yields. During the growing season 4-5 reports and Boletus, 1997 - 207 forests = 1035 plots - 70 researchers sets of thematic maps (timing of flowers, Suillus, 1998 - 440 forests = 2200 plots - 174+ observers berry development, levels of berry yield Leccinum, Each observer chose 2 forest and 1 peatland area etc.) and disseminated using the national Russula, close to home. 5 marked experimental plots of 1 sq. m media. Analyses also revealed the factors Cantharellus placed in each compartment or site. Each plot visited affecting the yield especially links with and at least 3 times during the berry and mushroom climate. Craterellus seasons. Future plans: Permanent network of 440

133 Location Target Product Life-form Objectives Type of study Scale Summary of methodology Analysis/Results spp. Records made on: plots (with plans for a total of 500) set up Forest observation forms: municipality, village, across the country. Inclusion of other compartment co-ordinates, forest site-type, commercial berries and herbs. development class, tree species, age of stand, area of forest and area of berry production. Yield knowledge form: dates of 3 visits, counts of number of flowers and ripe and unripe berries and factors affecting the yield. Mushroom yield form: species, calculated or counted young, adult or old fruiting bodies present in compartment and factors affecting the yield. Finland Rubus idaeus Edible Understorey Investigate effects of Yield Local -Evo, 3 round (r=10m) plots sampled in nine experimental Table of shoots/ha, biomass, flowering % berries shrub of prescribed burning Lammi, areas burned 1-9 years before the study (1983) some and berry yields in each treatment. Vasander boreal forest on berry yields. southern of which had been treated with herbicide. In each plot 1988 Finland. the numbers of shoots, buds, green fruit, berries and empty receptacles counted. All berries picked and weighted. In some of the plots, the number of flowers and buds were counted at the flowering time. Lithuania Berry and Edible Understorey Generation of Strategic National Evaluation of 20 species of berries and herbs since Yields for each taxation plot herb species. berries & shrubs and information to permit management 1976 in all forest compartments?. For every species (=compartment?) and the relative area of Budriuniene medicinal herbs in cold the delimitation of information two indicators are evaluated visually: frequency (part compact density i.e. transformed to a 1988 herbs temperate forest areas for of a forest stand with the species) and density 100% projective cover are calculated (sic). forest. specialised (projected cover of the plants). Data yields are grouped into according to production of non- reserve and productive plant areas. From ligneous products the projective cover and the forest stand (to cover 6% of density, 3 productivity grades for non- forest area). ligneous plant areas are distinguished. Results presented in the form of description and summary tables of the compact density areas of all 20 species by administrative units, forest stand density and age classes and for different soil types. Maps are prepared for each species showing productivity grades. These maps provide the basis for management and exploitation planning. Lithuania All NTFP Berries, Wild Statutory monitoring Census. National -1.1 Compartment records of land use category, Maps of berries and medicinal herbs (for plants. mushroom populations in million landowner, protected status, dominant tree species commercial purchasers). Conversion of Rutkauskas s, cold compartmen (forest type), tree species composition, age, stocking area in cover classes into equivalent area 1998 medicinal temperate ts of 2.3 ha level, growing stock, site type, vegetation type, at 100% cover. Production areas defined plants. native forest & on 10 year undergrowth, shrub and plant density, etc. NTFPs according to stand characteristics. timber cycle. included since 1962. NTFP data obtained from stand- Exploitable harvest calculated from plantations. wise inventory or indirectly using correlated productivity standards for species observations e.g. biology, exploitation yield, forage depending on site index, forest type, classes etc. Fauna dealt with by special game harvest periodicity and biological part management unit. harvested. Poland Vaccinium Fruit / Understorey Distribution and Monitoring. National Recurrent inventory every 10 years from 1956. Forest Description of changes in yield and spatial

134 Location Target Product Life-form Objectives Type of study Scale Summary of methodology Analysis/Results myrtillus, berries shrubs of cold productivity land with berry plants divided into 4 categories based dynamics of plant distribution. Glowacki Other berries temperate on % berry cover. Forestry staff record presence, Phenological observations provide basis of 1988, & Mushroom forests. phenology and yield of berry plants in fixed-point plots. models to predict berry production as a Grochowski Since 1962 emphasis on tracking the cover density, function of stand site productivity, & Ostalski spatial distribution and height of bushes nationally. flowering and number of early ripening 1981 fruits. Poland Vaccinium Edible Understorey - Obtain information Questionnaire National in Questionnaire at compartment level completed by Tables of the area in ground cover x myrtillus & berries & shrubs in about the spatial of local 1950's & local forestry staff based on personal knowledge, field production classes. Kalinowski Frangula medicinal temperate distribution of forestry staff. 60's surveys and visual observations to estimate the area 1998 alnus plants forest. existing resource of ground covered by the target species in - Quantitative and compartments (~25 ha). Occurrence scored into qualitative classes (e.g. massive, abundant, rather abundant characteristics etc.). This was followed by a more objective % cover - Develop yield assessment (e.g. < 5%, 6-30%, 31-60%, > 60% for tables which would Frangula alnus). Sites also scored into production show the availability potential classes (3 for lowland and 1 for mountains) of raw-material based on plant density and heights. From 1997 - More plants added - similar approach to previous surveys used including more field observations and questions on the state, protection activities and use of the resources. Russia Vaccinium Edible Understorey Understanding of PSP & long- Regional - Annual monitoring of permanent sample plots began in Design gives a 15-20% precision which is myrtillus & V. berries shrubs of berry productivity term Karelia 1974. deemed acceptable for industrial and Kuchko vitus idaea boreal forest. monitoring a) Sample plots of 0.3-0.4 ha located in different forest scientific purposes. 1988 types. Complete description of ground cover and Data from 1974-1983 analysed for assessment of forest canopy made for each plot. In phenology and to determine the conditions each plot berry yield assessed in 40 systematically laid required for heavy fruiting which was out quadrats of 1 m² and 3-5 replicate samples of 100 found to be meteorological conditions in berries picked an weighted to give yield per hectare. both the current and previous year, forest b) 'random' routes across different taxation portions. type and within a type on tree canopy Main phytocenosic and topographic factors influencing closure. Yield fluctuates significantly productivity recorded and berries counted in temporary between years and between plots within a quadrats of 0.5-1 m². 30-100 plots measured forest type. depending on the size and character of the stands. Russia Vaccinium Edible Understorey Understanding the Yield. Regional - -Climate study - 3 sample plots chosen from an -A thermal-phenological nomogram vitis-idaea berries shrub in links between South existing PSP network to represent certain constructed for forecasting the dates of Paal 1988 boreal forest fruiting and climate. Karelia coenopopulations. In each plot 60 bushes chosen at flowering and ripening of the berries and random and marked. Dates of phenological phases for elucidating the relationship between recorded over 4 days depending on the weather and phenology with regional climate variation. rate of berry development. 9 phenological stages were Nomogram can predict the phenological identified and recording took place for 7 seasons. phases of V. vitis-idaea to within 3-8 days. -Fruiting uniformity study - 4 sample plots recorded for -40 sub-plots selected at random from the 3 years (1976-78). Average berry yield was estimated 4 sample plots and ranked according to from 40-100 randomly located 1 m² subplots in each berry yield in each year. Each ranking plot. divided into 8 groups. Two factor -Canopy density study - 3 plots differing in density hierarchical ANVOA with groups and years measured over 2 years (1977-78). Subpots of 0.5 x 0.5 as the independent factors. Correlation

135 Location Target Product Life-form Objectives Type of study Scale Summary of methodology Analysis/Results m placed along transects between trees. Random analysis of the regression coefficients for pairs of trees selected using the nearest neighbour yield in each group was used to determine and wandering quarter methods. the degree of association between sub- plot yields over 3 years. Discovered tendency for high yields to occur in the same sub-plots from year to year. -One-factor ANOVA using the distance from the nearest tree trunk as the independent variable, later data grouped into 11 distance groups up to 5.5 m. Distance explained only a small proportion of the variation in berry yield. Sweden Vaccinium Fruit / Forest National berry Monitoring. National Recurrent survey (1974-77). Berry pickers Effects of forest practices on berry myrtillus, V. berries understorey production accompanied national forest survey crews to estimate production especially effects of clear Eriksson et vitis-idaea, shrubs in cold berry production in standard forest survey plots cutting on species composition and re- al. 1979 Rubus idaeus. temperate [unknown design]. colonisation. forest.

INDIAN SUB-CONTINENT Location Target Product Life-form Objectives Type of study Scale Summary of methodology Analysis/Results India Phyllanthus Fruit Medium sized Extraction, Resource Reserve - Transects 10x variable length up to 1000m located in 4 Stand density tables. Regression of fruit embilica. tree, productivity levels inventory. Biligiri vegetation types, d measured for all P. emblica trees > production vs. tree d. t test of mean d in Shankar et widespread in and price Rangan 10 cm d except in scrub where trees >5 <10 were also vegetation types. al. 1996 scrub and dry appreciation. Temple enumerated. Extracted fruit recorded and weighted, deciduous Wildlife visual estimate of quantities of unharvested fruit. Total vegetation. Sanctuary extraction estimated from harvest records. Market survey - interviews and calculations of total revenue from market prices for fruit. India Insect. Lac. Insect brood Development of Methodologica Local - First visit - elicit and determine extent of senior Feasibility assessment uses triangular on Butea method for l research. Kompura villagers knowledge of lac production. Ranking of host model illustrating the institutional, bio- Centre for monosperma assessing the village.. species in relation to production potential. physical and socio-economic aspects of Arid Zone trees in arid feasibility of Selection of 1 privately owned farm. Informal and successful lac production. Indigenous Studies woodland. introducing lac unstructured interviews on 2 occasions with landowner knowledge, published information and 1998 production in and his wife. Selection of 2 ha pilot site on farm. results of pilot site investigations used to villages. Sample plot of 0.14 ha (35x40m). Trees in 0.04 ha determine the limitations of the site, sub-plot tallied into 3 broad ht classes (< 1.5 m, 1.5- suggest possible amelioration and overall 3.0 m, > 3.0 m) and extrapolated to whole plot. Lac potential for lac production. production estimated for each size class. India Plant Food, Species Development of Rapid State-wide - Study sites stratified according to length of time 1) Description of Shorea robusta products. medicines, appearing in methodology to appraisal -2 Southwest protected and matched for microclimate, floristics and succession in West Bengal 2) Lists of Malhotra et mats, Shorea assess feasibility of days. Bengal soils. Single100 m² plots at each site located > 50m plant products available in different ages al. 1991 tying. robusta forest community from forest edge. Structural regeneration: frequency of of regenerating forest. 3) Relative succession. management of all plant species in plot; measure 12 upper storey availability of forest products as forest natural forest for crowns and gaps (selected either randomly or regenerates.

136 Location Target Product Life-form Objectives Type of study Scale Summary of methodology Analysis/Results policy and systematically)-crown separation ratio=mean programme gap/mean crown; measure d and ht of 12 canopy development. trees; stand profiles drawn for each plot. NTFPs: ethnobotanical survey of all products used for home consumption or sale. Information collected included; harvesting seasons, volumes and parts utilised. India 13 spp. Raw Climbing palm Development of Inventory State-wide Review of design features of appropriate inventory Recommendations for State-wide and Rattan. material - confined to appropriate design. (Kerala) & techniques for rattan resource surveys. Forest Division two stage inventory Nandakuma many isolated, inventory methods Forest protocols based on rattan distribution and r & Menon uses inaccessible, for resource survey Division field logistics. 1992 sheltered of rattans as a 'pockets' in prerequisite for evergreen, scientific semi- management. evergreen & moist deciduous forest. India Bamboo. Raw Woody grass, Production potential Resource National -21 Bamboos included in national timber surveys since Stand tables (density per ha and green material abundant, inventory. states 1965. Stratified systematic sampling based on clusters tonnage) by species, quality and clump Rai & for cottage often of 1 to 8 square 0.1 ha plots. Clumping sp.. - clumps size. Area, total number of culms and Chauhan and dominant or counted in whole plot, clump diameter measured in growing stock tables by State. 1998 industrial sub-dominant north-west quadrant (1/4 of plot). Culm number, age, uses (e.g. in most Indian soundness, size, condition, average culm height, pulp and forest types. quality etc. enumerated for every eighth clump. Non- paper). clumping sp.. - in 1/8 of plot - condition, age, average height, total number of culms etc. is recorded. Utilisable green to dry weight relationship - 1 mature culm from each culm d. class is felled from the first clump in each plot. Length is 25 cm from ground (cutting ht) to 1 cm diameter. Green wt determined for whole culm and dry weight for 30 cm sections taken from bottom, middle and top of culm. India 21 trees, 3 Edible oil- Isolated and Enumeration Compilation of State-wide - Re-analyses of Forestry Department stand table data Estimate of total state-wide quantities of shrubs, 1 seeds. widely statistics for oil- secondary Uttar (previous 'raw material resources' inventory and Indian edible oil from 25 important oil-seed Rai 1983 climbing scattered bearing sp. to data. Pradesh. Central Oil-seeds Committee). species. shrub. species both assess possible inside and contribution to edible outside oil production to reserved meet existing State- forest. wide shortfall. India Four Stems as Climbing palm Assessment of cane Resource Local - Two stage random sampling. Area divided into 123 Cane stock tables by stem density, length commercial constructi at low density potential to meet inventory. Baratang primary blocks from which 32 were randomly selected. and weight per ha with standard errors. Sharma & species of on in evergreen cane requirements Island 3 secondary blocks of 1 ha demarcated in each Graphs for each sp.. Bhatt 1982 rattans: material and deciduous of Sports Goods selected block. Count of commercial and non- Calamus forest Export Promotion commercial culms on whole plot. Culms cut into 3.65m andamanicus, Council. billets from 0.25 ha quadrant of plot. Cut canes

137 Location Target Product Life-form Objectives Type of study Scale Summary of methodology Analysis/Results C. weighed every day until the weight was constant for 4 pseudorivalis, days. C. longisetus & Korthalsia laciniosa. India Seabuckthorn Fruit Shrub forming Study of Yield. Local - Utilisation - interview of 5 people from each village in Characteristics, regeneration, biomass, (Hippophae). monospecific characteristics, Lahaul study area. 3 study stands from which 12 plants of seed nutritional content, distribution and Singh & stands on high regeneration, valley different girth were felled and sampled for biomass utilisation profile of sp.. Dogra 1996 altitude slopes biomass, nutritional and 12 plants were dug up to count root suckers. (Himalayas). values, distribution Nutritional content of seeds determined. and utilisation of sp.. India Bamboo. Many Uniformly Feasibility of using Remote Local - Land cover types mapped for 19.3 km² study area. Bamboo easily identified in B&W and TM distributed in large scale aerial sensing. Wynad Using standard visual interpretation techniques for imagery. Best images are from Jan-Mar. Varghese et moist photos and Landsat District, B&W and TM imagery a photointerpretation key based TM best for large areas, B&W best for al. 1996 deciduous and TM in determining Kerala State on tone, texture, pattern etc. was developed for detailed mapping and density strata. evergreen bamboo brakes in different forest types and relative density of bamboo. forest the natural forest of Land cover maps field checks and corrections made. the Western Ghats Area estimates made from maps using electronic planimeter. Nepal All plants. Many Natural forest Provision of Base-line Regional -4 Selection of 2 groups of up to 4 forests representing Creation of plot and block summaries to in JFM quantitative study. Koshi Hills different forest types and condition in each District. obtain figures of stocking, basal area, Branney scheme information on forest Monitoring. districts Selected forests stratified into blocks corresponding crown cover, regeneration of useful trees 1994a resource for with the management plan. 6 blocks selected for and total regeneration. comparison with assessment within each group of forests. Block similar data to be enumeration; selection of fixed reference point and collected in 5 years selection of random bearing for transect into block. 6 time. plots laid out at 50 m intervals along transect. Plot is 5x10m and laid out perpendicular and on alternate sides of the transect. Trees are > 3m tall - local name and d recorded. Shrubs are 0.5-3m tall - name and number recorded. Plants < 0.5 m tall and of tree or shrub sp.. are classed as regeneration (if abundance count on half the plot). Canopy cover %, shrub crown diameter and crown separation, litter layer, evidence of recent damage, evidence of recent management or harvesting. List of seed trees. Tally number of species per block into plant growth form categories (trees, tall shrub, lichens, ferns etc.). Nepal Daphne Lokta bast Branchy, Development of a Biomass table National Trees selected for biomass determination from across Data from 30 trees evenly distributed bholua & D. fibre for evergreen Daphne biomass generation range in Nepal. Ht & d at 30 cm above ground through the 7 diameter classes (1-7 cm) Jeanrenaud papyracae paper shrubs/small table for use as a measured for all sample trees. Single-stemmed trees were randomly selected from the dataset. & Thompson manufactu trees 1-3 m management tool. were harvested and separated into components; These were subjected to standard 1986 re tall growing utilisable bark, waste bark, stripped stem, branches regression analysis using a log-transform. from 1,600 to and leaves and weighted in the field. A sub-sample of The regression of utilisable bark dry 3,600 m. each component returned to laboratory for oven-dry weight against diameter at 30 cm was weight determination. selected as the best model. To validate Sample stem discs taken from 30 cm above ground the model the predicted bark weights were

138 Location Target Product Life-form Objectives Type of study Scale Summary of methodology Analysis/Results and analysed for age (=annual rings) and wood regressed against the actual weights for density. the remaining trees in the sample dataset. This proved that the model is robust and subsequently all the data was used to generate the final bark biomass table. Utilisable bark wt regressed against tree age (poor fit) to give a first estimate of productivity rates. Results gave a basis for determining the length of the rotation for bark. Provides management recommendations. Nepal Herbaceous Medicines Low growing, Trial of protocol for Methodologica Local - 0.1 ha (100x10m or 200x5m) strip for NWFPs laid Plot size too small, need 5-10% plants. and non-woody integrating NWFP l development. Dhading & between 18m radius tree plots. N=20 clusters. Team enumeration because of clumped nature Kleinn et al. aromatics plants in hill resources into Nuwakot of NWFP specialists (2xbotanists, field assistant and of species. 1996 forest conventional forest Districts local helper) accompanied forest inventory team. inventory. Useful parts of 5 specimens of each species weighed and mean used to estimate weight per unit area. Nepal 81 medicinal Herbal Forest plants Survey of medicinal Ethnobotanica Local - Interviews of 110 tribal people & 20 herbalists from 15 List of highly regarded herbal remedies; plants. drugs properties of plants l. Myagdi villages based around collected plant specimens. Latin & local name, voucher number and Manandhar used by people in District Medicinal property accepted as valid if identified by 5 use. 1995 area. separate informants. 5-7 adults (aged 40-65 years) and 1 healer interviewed from each village. Sri Lanka NTFP trees. Medicines Trees > 30 cm Base-line survey. Phytosociologi Reserve - Phytosociological inventory: 5 subjectively located Table of useful plants that lists habitat, and food girth at breast Determination of cal inventory Sinharaja sample sites chosen to represent range of primary habit, IUCN threat category and Gunatilleke height management forest types. At each site, 20 0.25 ha (2 contiguous) food/medicinal properties of 75 species. & options for 7 widely plots were subjectively located to maintain within-plot Results for detailed studies indicate which Gunatilleke collected species topographic heterogeneity to a minimum. Plots divided species have the potential to be 1985, 1993 representing main into 25x25m subplots. Girth measured, voucher incorporated into forest management life forms. specimen collected and tags placed for all trees > 30 (logging and in rubber & pine plantations). cm girth. Local names collected. NTFP analysis: Use of species lists of inventory + field reconnaissance surveys for NTFPs not in previous inventory = comprehensive list of plants used for medicine & food. Detailed study of 7 NTFP species: vegetative & reproductive phenology, pollination ecology, breeding systems, fruit & seed set and seed germination. Questionnaire for methods and frequency of harvesting and processing.

139 NORTH AMERICA Location Target Product Life-form Objectives Type of study Scale Summary of methodology Analysis/Results Canada Taxus Bark - for Scattered Pilot study to design Methodologica Regional - Test two alternatives for inventory stratification based Tree density, basal area, diameter brevifolia production understorey and implement an l development British on pre-existing ecosystem and forest cover distributions and bark volume (using Jong & (Pacific yew). of Taxol tree in inventory for Pacific of stratified Columbia classifications. Questionnaire (to foresters & regression of bark thickness vs. diameter Bonner (cancer temperate yew. inventory. ecologists) used to capture local knowledge about and a cone shaped bole). Stratified 1995 drug). rainforest. occurrence of Yew as a basis for stratification. Field random sampling formulae used for sampling: 100 plots distributed amongst high means, variances and totals. probability strata (min of 3 per strata and in proportion to area) remainder in low probability area. Random selection of stands and plot locations within stands. Plot 800x10m in square torus with sides 200m long. Tally of all Yew > 30cm d. Measured diameter, total height, tree class, crown class and stem form. USA Salal, Sword Floral Understorey Provide information Exploitation Reserve - 1) Selection of products for inventory based on Spreadsheet (Lotus 123) used to perform fern, Bear material. plants and on harvestable inventory Santiam following criteria: (1) Is there is a current market for the calculations of mean, percent cover, total Barnes & grass & Noble trees in quantities and State product (2) product present in inventory area in abundance of marketable product and Musselman fir temperate values. Basic Forest, marketable quantities (3) product must be within standard error of the mean. 1996 forest. questions being: Oregon. reasonable walking distance of a road (4) product Also undertook market pricing study to how much product is must be present during the inventory (5) products as a determine market value of resources. available, what whole must be representative of the range of uni measurements are measurements accepted within the marketplace. needed to determine 2) Areas to be inventoried selected using (a) and pre- the value of that existing inventory data, (b) previous sale/permit product at current records (c) topography (d) personal knowledge of market levels and departmental staff of land owner. what are the 3) Determine units of measure for each product - acceptable harvest related to sale units I.e. 'bunches', weight etc. guidelines for the 4) Perform ground inspection to lay out boundaries for particular area. the inventory 5) Lay out systematic grid over area with circular plots at a density and size optimised for each product. 6) In each plot record; number of units available, percent of ground covered by product, observed condition (number of plants, age, condition, spacing associated plant types, tree species, slope, aspect, accessibility, proximity to land features, recent activity or previous harvesting. Summary of reported inventory Salal - 11 sites - 1/10 acre plots, SI=1.5 plots per acre. Area= 571 ac. Bunch = 1.75 lbs. Sword fern - 10 sites - 1/20 acre plots, SI= 1 plot per acre. Area= 605 ac. Bunch = 50 fronds. Bear grass - 6 sites, 1/50 acre plots, SI=1.66 plots per acre. Area= 308 ac. Bunch = 0.75 lbs. Noble fir - 1 stand, 1/10 acre plot, SI=1 plot per acre. Area=83.3 ac. Trees graded into 1 and 2. 50% of live

140 Location Target Product Life-form Objectives Type of study Scale Summary of methodology Analysis/Results volume estimated up to 2/3 tree height. 100 cubic ft of volume = 1 unit of product = 4 lb product on grade 1 trees and 2 lb product on grade 2 trees. USA Tricholoma Edible Ephemeral - Describe annual Methodologica Local -2 Design adapted from that for fungal diversity survey. 3 Skewed frequency distribution normalised magnivelare. mushroom fungal fruiting patterns of biological l study. sections (sq. experimental sites in each section. Within each using a log10(count+1) transformation. Pilz et al bodies on floor and commercial miles) of systematically placed 6 permanent 2x50 m strip plots Weekly permanent plot data summed for 1999 of temperate productivity in 3 Chemult with random orientation. For 3 yrs (1993-6) all plots each year and analysed using a repeated- forest. habitats over several Ranger sampled weekly through fruiting season (Sept-Nov). measures ANOVA with elevation as factor years District, Buttons counted and marked at first emergence to and years as repeated measure. - Examine the extent Oregon. avoid repeat counting. Cap & stem diameters and Confidence limits calculated and back- and type of wildlife distance from annulus to cap measured. Caps were transformed to median counts with consumption of collected outside plot to develop regression equations confidence limits. mushrooms of wt vs. cap dimensions. Each cap commercially Regression of mushroom dimensions and - Correlate seasonal graded and % consumed by animals recorded. weight using log transformation. fruiting patterns with For methodological study also sampled 2 to 3 2x100 m ANOVA of temporary sample plot data temperature temporary plots (moved every weekly) along random very similar to permanent plots. - Evaluate sample azimuths from centre of site. Caps counted but not plot designs. measured from these plots. Harvest levels measured using selected individuals who in exchange for exclusive harvesting rights compiled data on weights, grades and prices they harvested. At centre of site, weekly max and min soil Tº recorded at 2 inch depth and max and min air Tº at 3ft above ground. USA Fungi Edible Mychorrizal Monitoring to detect Monitoring. Regional - Three-component approach: Program not yet designed in detail and mushroom fungi in trends and correlate Pacific 1) Long-term inventory plots in natural areas where many elements not yet operational. Pilz et al in s temperate productivity with Northwest of neither mushroom nor timber harvesting is allowed as press forest. habitat, forest USA. a control and to investigate influence on fruiting of management dispersed regional influences on forest health such as activities and air pollution or climate change. Propose to enlist help environmental of volunteers from mushroom societies. conditions. 2) Measurement of total harvest quantities from intensive commercially harvested sites. This will provide critical information about whether commercial harvesting directly impacts subsequent or long-term mushroom production. Envisage using commercial harvesters who will collect data in exchange for exclusive harvesting rights. 3) Statistically rigorous of numerous sites to model the relations between mushroom productivity and forest habitat (stand conditions). Data will be used to develop predictive models that should be applicable across the region allowing forest managers to anticipate the influence of their management activities on subsequent mushroom crops. USA Cantharellus Chanterell Ephemeral, i) estimate Monitoring. Reserve - Sampling decisions reflected the need to include Non-random site selection and non-

141 Location Target Product Life-form Objectives Type of study Scale Summary of methodology Analysis/Results formosys & C. e sporadic and production per unit Olympic landowners and volunteers in study. Stands selected uniform plot locations preclude statistical Pilz et al. subalbidus. mushroom spatially area in Peninsula in three forest age classes (20-25, 40-50 & 80-100 comparisons of stand ages or 1998 s clumped representative forest Biosphere years) to reflect harvesting patterns. 11 field sites province/host species. Recommend fresh- fungal habitats ii) measure Reserve. selected; 7 in moist coastal forest and 4 in drier, inland to-dry-weight ratios should be calculated sporocarps in variations in forests. Sites selected without prior knowledge of for each sampling visit. Good log-linear temperate moisture content of mushroom presence or abundance. Local groups of relationship between mean cap diameter conifer forest. sporocarps iii) volunteers enumerated sites. Large area sampled at and cap weight. Commercial quality correlate mushroom each site to ensure clumps located, 5 plots 8x100 = grades too difficult to use. Plot design size and weight iv) 4000 m² located for ease of access within study area worked well. determine ratios of without reference to mushroom locations. Plots commercial quality sampled (observations made from centre line) every 3 grades correlate v) weeks during fruiting season for 2 years. All fruiting with local chanterelle in plots picked and sorted by commercial conditions of quality grades, counted and weighted. Subsamples moisture and taken for dry weight determination. Soil temperature temperature. measured at 12 cm depth at one end of each plot and scored estimates of humidity and soil moisture made during each visit. Tree canopy density, USA Allium Stems as Perennial To determine the Impact study. Reserve - Harvesting level: 3 sites selected on ease of access, Harvest level: Analysis of covariance used tricoccum. food spring impact of harvesting, Experimental Great abundance (at least 15 m² with (20 plants m-²) and not to test for differences between harvesting Rock 1996 ephemeral at varying levels, on harvest. Smoky regularly harvested). 15 1x1m plots (3 replicates of 5 levels, changes over time and between herb in populations in the Mountains treatments) in a non-linear arrangement at each site. site differences. Leaf totals per plot used eastern North Park. To determine National Maximum leaf width of largest plant of each plant in in plot comparisons. Harvest technique: American the impact of Park plot measured (leaf width = bulb size). 5 harvesting Not analysed because of loss of replicate temperate different harvest treatments: control, 25, 50, 75 & 100% harvesting. due to windblow of tree onto plots. hardwood techniques on Plants harvested without bias using traditional forest. populations. To methods. Leaf widths and flower/fruit production of predict the number remaining plants and recruits measured for 4 years of years required for post-harvest without further harvesting. Harvest populations to technique: 3 replicates of 3 0.5x0.5m plots established regain pre-harvest at one site. Plants harvested using three methods; levels after a single control, complete removal and partial removal of harvest. plants. All plants too small to have been harvested removed from plots to avoid counting as regeneration in subsequent years. USA Truffles. Fruiting Hypogeous Investigate Productivity Reserve - Paired plots in old growth and mature plantation ANOVA, Contingency tables, Spearman body ectomycorrhiz relationship between research. Swain stands (four replicates). 6x6 grid with 10m spacing in rank correlation, Stepwise multiple Waters et al. al fungi found stand age and total Mountain each of 8 stands. Habitat recorded from 4m radius regression, Wilcoxon rank-sum test, 1997 in random truffle production. Experimenta circle centred at each grid point. Measured d for all Poisson fit to frequency distributions. clusters l Forest standing trees and length, mid-point d and decay class (Temperate of logs > 10 cm in each habitat plot. Truffles collected conifer forest). in 1.13m radius plots located systematically near each of the 36 habitat plots, a new truffle plot was collected at each sample period. 4 visits in 1993 and 3 in 1994. Decayed logs, soil organic matter (3 observations at systematic locations) and all truffles in upper 5-10 cm of soil collected from each truffle plot. Soil samples

142 Location Target Product Life-form Objectives Type of study Scale Summary of methodology Analysis/Results taken on 3 occasions from each of the 36 grid locations. USA / Hydrastis Goldense Slow-growing Develop protocol for Monitoring National Extensive, low intensity population trend monitoring Plants grouped into cohorts according to Canada canadensis al roots perennial herb a monitoring protocol programme of 10-20 populations per State. size and demographics of each group in temperate programme which Intensive, high intensive population dynamics determined as averages of all plants in the Gagnon forest will provide data of monitoring programme of 5-10 populations per State. cohort. Rates of mortality, growth, flower 1999a wild population Study population selection criteria: (1) a minimum production, seed production, vegetative dynamics and number of 100 individual plants [which is the estimated offshoots are required. Data used in size vulnerability to minimum viable population size], (2) no evidence of classified transition matrix to determine the harvests. harvesting, (3) remote location, (4) similar and typical overall growth rate of the population for habitat, (5) no evidence of recent natural disturbance. each year of the study. Not used for At each site: soil collected for analysis and % cover in projection as environmental conditions will vegetation strata e.g. tree, shrubs etc. recorded. not be stable. Advocates the use of at Patches of plants mapped in detail in 1 m² square minimum of 4 annual matrices in random micro-plots marked into 20x20 cm grid and order to perform stochastic population sequentially numbered. In subsequent years, recruits projections. Projections of a stochastic should be numbered and the parent plant identified. series of 100 years can be used to Measurement for each plant: sequential number, ht in estimate the minimum viable population cm to lowest leaf, maximum width in cm of all leaves, size (maximum size of population which % of leaf area browsed and the number of fruit gives 5% extinction of populations) and to segments which are assumed to contain seed. predict the effects on population survival of Germination: 50 seeds collected from non-study plants harvesting. and sown under wire cages at each study population. 25 seeds taken of germination at research station in standard conditions. Measurements taken in July (fruiting season) every year. USA / Panax American Long-lived, To acquire, direct, Demographic National Two level monitoring programme of large undisturbed Suggested analyses are: Canada quinquefolius ginseng slow growing empirical evidence monitoring. wild populations: (same protocols as in Gagnon 1) Determination of minimum viable root temperate of the sustainability 1999a) population size, and population growth. Gagnon forest or otherwise of wild 1) High intensity monitoring of > 100 identified These data can be used to generate 1999b understorey American ginseng individuals (tagged or micro-plot mapped) from 5-10 region-specific annual transition matrices herb. harvesting. populations per State spread over the species range. that can be used in stochastic modelling 2) Low intensity monitoring of 10-20 populations per and elasticity matrices to determine critical State across species range. These populations to be life stages and transitions for populations monitored for size class structure i.e. numbers in each growth. size class tallied as well as fruit or seed production for 2) Detect population trends the whole mapped population. 3) Indication of resource depletion I.e. are 3) Measurement of harvested roots in trade. roots in trade becoming smaller with fewer sourced from the wild.

143 SOUTH AMERICA Location Target Product Life-form Objectives Type of study Scale Summary of methodology Analysis/Results Amazonia 6 oligarchic Edible fruit Monospecific Quantification of; (a) Demographic. Research One plot for each species, ranging from 0.1 to 1.0 ha Annual fruit production per ha calculated forest spp., & palm stands, E. density of stands (b) site depending on species (E.o. 1 ha; G.p. 0.6 ha; J.b. 0.3 for each sp.. Peters, Euterpe heart. oleracea: fruit yield ha; M.f. 1 ha; M.d. 0.1 ha; O.p. 1 ha). All individuals of Balick et al. oleracea, multi-stemmed target sp.. (>=1.0 m tall, tagged and measured for ht 1989 Grias palm, G. and d. Phenology - direct observation over year. Fruits peruviana, peruviana: - harvested, counted and weighed from subsample of Jessenia understorey labelled trees bataua, tree, J. Mauritia bataua: single- flexuosa, stemmed Myrciaria palm, M. dubia, flexuosa: Orbignya dioecious phalerata. palm, M. dubia: shrub, O. phalerata: single- stemmed palm Amazonia Trees. Various Trees in terra Evaluation of tree Quantitative Supra- One subjectively located plot for each of 4 cultural Forest value compared using percentage uses, firme forest species and families ethnobotany. national - 4 groups Plot=1 ha. All trees > 10 cm tagged and of species in plot considered useful by Prance et al. food, that seem to be forest vouchered for identification Uses categorised and different cultural groups. Plant use values 1987 constructi most useful to all peoples in scored as major=1 or minor=0.5 Use scores summed compared using use scores on, four indigenous Brazil, for each species and family. technolog groups and to Venezulela y. recommend and Bolivia Remedy, measures to protect commerce these species and and other. their associated habitats. Andean All biological Many Plants and Which products Valuation. Supra- Secondary data, interviews with experts, site visits and Description and discussion of issues. countries materials animals of have significant national - extensive fieldwork in Bolivia. Data: non-market other than natural forest economic value & Colombia - values; net present value of NTFPs; export statistics. Broekhoven timber, how can they Ecuador - 1996 fuelwood and contribute to socio- Bolivia carbon which economic are extracted development? How from natural can ecological forests for sustainability be human use. measured and what information is available? Bolivia Vascular 7 classes: Premontane Collect botanical Ethnobotanica Local -area Artefact/interview - ask for names of plants used to Table of useful species by botanical family plants (trees) Food; tropical moist knowledge of tribe l survey. used by make certain artefacts with subsequent collection. by utilisation classes. Voucher specimens Boom 1989 used by Fuel, forest before it is lost Ethnoecologic people from Inventory/interview - present informant with plant of all plants listed. Chácobo Constructi through al inventory. main village specimens and enquire about possible uses. Inventory

144 Location Target Product Life-form Objectives Type of study Scale Summary of methodology Analysis/Results people. on, acculturisation. of 1 10x1000m plot for all trees > 10 cm d. Medicinal, Quantification of Poisonous forest utilisation. , Commerci al, Miscellane ous. Brazil Leopoldinia Fibre from Palm on Documentation of Resource Local - Oxisol & podsol soils - 100x50m plots. Gley soils - Distributions of height by soil type piassaba. palm leaf. caatinga soils. biological and characterisatio Interfluve of point quarter method - 31 points 20 m apart on a 600 compared using Kolmogorov-Smirnov test. Lescure et Locally economic aspects of n. Rio Preto- m line. Height measured for each individual in plots. Spatial pattern analysed in plots using al. 1992 dominant? a poorly Rio Negro Observations of collection time and fibre weight taken 10x10m subplots and Grieg-Smith documented for 4 collectors over 4 days. dispersion index. commercial species. Brazil Iriartea Stems for Single- To describe the Demographic. Reserve - Palms censused by size (height) class in streamside Life table model parameterised from deltoidea. house stemmed, stilt- stability of the palm Chico forest within a 10 min walk of residences. Sites (5) pooled stand table. Lefkovitch population Pinard 1993 constructi rooted palm populations. Mendes subjectively selected based on separation, presence of matrix model. Simulated harvesting on Evaluate impacts of Extractive palm and hospitality of residents. At each site 5 scenarios by modifying survival stem harvesting on Reserve, 10x40m plots randomly located. Count of leaf percentages. Sensitivity and elasticity palm populations. Acre State scars/assumed constant leaf production rate=estimate analyses of model coefficients. of age & number of years to reach a certain height. Used published leaf production rate. Young palms harvested for scar counts. Direct leaf scar counts made on stems < 5m. Mean scars per m used to estimate counts for stems >5m. Brazil Euterpe Edible Multi-stemmed Economic costs and Industry Regional - Extraction rates: interview of 50 extractors in 9 Descriptive statistics. Empirical equations oleracea. palm heart palm in flood returns of extraction. viability study. Amazon counties. Processing: visits to 30 factories and relating height and d of stems with weight Pollack et al. plain forest Impact of harvest estuary intensive interviews in 9 factories. and diameter of heart. Equations used to 1995 intensity on Heart yield and size: measurements of d, height, estimate palm yield per ha. Proportion of population structure. weight & diameter of hearts for 68 wild stems across population in height classes compared Economic potential size range. across harvesting intensities. of sustainable Harvest impacts: high pressure = cutting 1-2 yrs: 2 Recommended minimum sizes for palm management 10x100 m regularly spaced plots in 5 sites. Low extraction. Economic potential- costs & pressure = 4-5 yrs: 2 10x100 m plots in 2 sites. benefits of 2 types of management. Control: 2 10x50 m plots. Recorded number of clumps with stems > 2 m tall, d of all stems >= 2 m tall, number and diameter of recently cut stems. Recorded total living and dead clumps in 2 25x50m randomly located plots in each strata. Brazil Caryocar Edible Large trees in Size specific fruit Yield. Local - 3 study villages selected according to the following Regression analysis to determine the villosum, fruit. tropical high production to adjacent criteria: adequate size and occurrence of sp.., low relationship between fruit production and Shanley in Endopleura forest. compare the value communities likelihood of logging, communal and undisputed d. prep. uchi, Platonia of fruit productions on west ownership, accessibility and necessary Analysis of links between flowering and insignis as opposed to the bank of infrastructural/political support. habitat with fruit production for V. villosum. value of timber at Capim Fruit species selected from ethnobotanical inventories, Density, standard deviation and size class the individual and River. market surveys and interviews with 60 farmers. 5 distributions generated from plot data. population level. criteria used: (1) exist in significant densities within

145 Location Target Product Life-form Objectives Type of study Scale Summary of methodology Analysis/Results regional forests (2) occur across Amazonia (3) widely utilised by community for subsistence purposes (4) demonstrate a strong market (5) considered as meriting study by local farmers and botanical authorities. 2 plots of 700x400 m (28 ha) enumerated in selected areas with minimal disturbance. In each fruit trees > 0.5 cm d labelled, measured and mapped. Number of trees sampled in each size class determined from phenology and availability. 16-109 trees per species over 4000 ha of forest used for phenological observations. Trees tagged and marked with 15x15 cm colour coded and numbered wooden plaques. 20 km long trail network linking trees cut annually. C. villosum trees (only small proportion fruit per yr) censused for flower production to determine work required to sample fruit. One month prior to fruiting, vertical projection of crown determined and ground beneath cleared of vegetation and debris. Fruit fall recorded 2-3 times per week during season for 5 years (1994-98). Fruit collected, sorted into classes and counted. Flower drop also recorded for C. villosum. Villagers also counted and recorded the number of fruit they consumed from sample trees. Rainfall data taken from a met. station 130 km from study site. Brazil Desmoncus Possible Climbing Test protocol to Inventory Research Selective location of 5 sites (to sample different Grid squares classified into 3 stand types. polyacanthos. use as palm, quantify the methodology. site -Ilhas de densities of target sp.). Transect dimensions varied Means, SE etc calculated for each stand Troy et al. 'rattan' abundant in relationship between Abaetetuba according to tree size. Smaller trees: 2 or 3 parallel type for pooled data and as weighted 1997 secondary measures of canopy transects 4x32m 4m apart and divided into 2x2m grid. average of contiguous squares of each forest & scrub. structure and the Larger trees: 2 parallel transects 5x50m 5m apart type. Unbalanced ANOVA used to test for abundance and divided into 5x5m grid. variability between grid sizes. Linear distribution of sp. in Enumeration: Live crown heights (bottom & top of regression of D. polyacanthos leaves vs. disturbed forest. crown), total canopy depth, canopy thickness (depth- canopy variables. space with no foliage), canopy density (sum of individual crown heights) and D. polyacanthos leaf number and stem height measured for each square. Cardinal canopy projection for each tree > 5cm. Measurements taken with survey rods for small trees and clinometer for larger ones. Columbia, Plants Many Plants in Comparative Methodologica Local - 3 Air photo and Landsat image interpretation into land Use values calculated using informant Ecuador & tropical high assessment of l development. sites of 1- units at 1:100,000 scale to permit a stratified random derived values (Phillips & Gentry 1993a) Peru forest. NTFP availability in 2000 sq. sample of 18-24 plots per site in mature forest. and proportional use values (Prance et al different forest types km. 1 in Sampling restricted to 3 vegetation types. 1987). NOTIM standardised database Duivenvoord in 3 pilot areas. each Vegetation composition and potential use recorded in program used to facilitate data transfer en et al. Specific questions country. 0.1 ha plot subdivided into 10x1 m subplots. between the 6 research partner

146 Location Target Product Life-form Objectives Type of study Scale Summary of methodology Analysis/Results 1999 are: Ethnobotanic information provided by local informants. institutions. - how do forest Plot records of physiography, parent material, soil Final output will be maps at 1:100,000 types differ in their fertility, canopy height, and floristics > 2.5 cm d. scale illustrating geology and potential NTFP Maximum d of each species recorded in 3 classes: < geomorphology and will include resource availability 2.5 cm, 2,5-5 cm and 5-10 cm. Diameter of trees and quantitative and qualitative on soils, - how should these lianas > 10 cm d measured directly. vegetation and potential NTFP use. differences be Transect sampling - variable length 10 m transects. In evaluated in view of each transect the presence and abundance of useful the different and indicator species (ferns and Melastomataceae) appraisal methods recorded. of NTFP availability. Ecuador Phytelephas Tagua, Large, single- Impact of tagua nut Demographic. Comuna Rio Subjective plot location in three management regimes Individual growth model (POMIB) using aequatorialis. vegetable stemmed palm extraction on Santiago- stratified by inundation. 20x30 m plots - all trees size-specific growth and survivorship Runk 1998 ivory for that forms growth, reproduction Cayapas mapped and tallied into age classes (juvenile, sub- General Linear Models for leaf and seed export, all small and sustainability Research. adult & adult). Enumerated adult density, distribution, production with management, inundation, parts monotypic under three sex, stem height, light exposure, foliage cover, number age and light level. locally stands. management of living, cut and dead leaves, inflorescences, used. regimes. infructescences and health every 3 mths for 1 yr. Leaf, flower and fruit maturation monitored by painting emergent frond/fruit. Seed production estimated using mark/recapture during collection supplemented by count of those left behind. Guyana 106 potential N/A Trees in low- Quantitative Secondary Research Used secondary data; 1) Tree inventory: Moraballi 2-way ANOVA of differences between NTFP trees. diversity assessment of analysis. sites -2 Creek=5 1.2ha plots; all trees > 10 cm d; Kurupukari=4 vegetation and utilisation categories. Johnston lowland distribution and sites: 1ha plots. 2) Local and national ethnobotanical Identification of key sp. for development- 1998 tropical forest. abundance of Moraballi surveys to identify uses. i.e. sp. with many uses and occurring at NTFPs within low Creek & high densities. diversity forest. Kurupukari Peru Mammals: 3 Bushmeat Game animals Identification of a Sustainability. Local - Comparison of actual harvest with modelled Tables of per capita and annual harvest. ungulates 1 in moist sustainable harvest Catchment sustainable harvest. Harvest rates: every 1or 3 days Comparison of hunting offtake with Alvard et al. rodent 4 tropical rain for neotropical game area of 2 household interviews to determine the number and Robinson & Redford (1991) method for 1997 primates small forest species villages -2 characteristics of all mammalian game killed since the estimating sustainable harvest. Depletion: mammals. year study last visit. All Piro interviewed and 60% of (1) logistic regression for effect of distance Machiguenga. Consumer days=number of consumers on prey encounter rates (2) calculation of present x no. of days. Total hunted biomass=species catchment area needed to support specific, age & sex body wt estimates x no. of animals. demand. Catchment area=average hunting trip distance as radius of core hunted area. Harvest expressed as kg harvested per year per km² of catchment. Prey abundance: estimated from number of encounters with prey per hour during observed hunts. Peru Hunted Bushmeat Wild animals Costs of converting Research. Reserve - Two study sites: persistent (Tahuayo) vs. slight (Yavari Animal densities, age structure and mammals: 5 in hunted terra overhunted forest to Comparative Reserva Miri) hunting pressure. Numbers, species and body biomass. Chi² and F tests use for Bodmer et ungulate, 12 firme forest. sustainable use. study of two Communal weight of hunted specimens recorded. Line transects: comparisons. between sites. Population al. 1994, primate, 6 Development of sites. Tamshiyacu Tahuayo: 150 km in 7 trail systems in 200 km² Yavari analyses for individual species (procedure Bodmer rodent, 6 management model -Tahuayo Miri: 170 km in 4 trail systems in 180 km² Transects 1- not given). Hunters preferences calculated 1995 marsupial and combining 7 km in length and surveyed on average 5 times in by Ivlev's index of selectivity.

147 Location Target Product Life-form Objectives Type of study Scale Summary of methodology Analysis/Results 7 carnivore population biology, morning and evening. Species, group size, time of sp.. cost-benefit analysis day, location, habitat type and perpendicular distance and income within 1m to first sighting. Fourier series analysis used distribution. Analysis to estimate animals densities. Age structure estimated of non-tribal hunters by tooth wear on collected skulls. Economic value of game choice (1995 animals was determined by market survey and hunter paper) interviews. Peru Myrciaria Fruit Trees in Estimation of fruit Yield. Research Populations located through interviews and Spatial distribution examined using dubia, Grias seasonally yield. sites exploration, site selection based on distribution & Morisitas's Index of Dispersion (ID). Stem Peters & peruviana, flooded forest. abundance, distance to town, accessibility and maps sampled using contiguous square Hammond Spondias M. dubia: probability of logging. M. dubia - 10, 10x10 m plots of a range of sizes, ID tested for 1990 mombin. riparian contiguous plots (all trees tagged and measured for ht significance difference from 1 using F shrub/small and basal d). G. peruviana - 15, 20x20 m contiguous statistic to determine size of clumps. Size tree, G. plots - (all trees tagged and measured. ht < 1.5m tall; class distribution log transformed - linear peruviana: ht & d > 1.5m tall). S. mombin 125 contiguous 20x20 regression fitted=negative exponential size abundant m plots (=5.0 ha plot), (all trees >1cm d counted, distribution. Phenological charts. understorey measured and mapped). Fruit production: M. dubia Regression of fruit production against tree. S. fruit marked with paint & counted on 25 adult trees for diameter. Total fruit yield=mean yield x mombin: 2 fruiting seasons. G. peruviana: biweekly censuses of number in size class. Large forest 15 adult trees for 1 year. S. mombin fruit production tree. recorded using 8 randomly located litter traps of 0.5 m² emptied weekly under 8 trees across size range for 1 season. Peru Myrciaria Fruit M. dubia: (a) Determine Demographic. Research Variable enumeration periods & plots for each life Life table analysis (transition matrix dubia, Grias Riparian shrub whether sufficient Variable site - 3 year stage. M. dubia - 10, 10x10 m contiguous plots - all modified for size class data - Lefkovitch Peters 1990 peruviana. in pure stands, fruit available for enumeration ecological trees tagged and measured for height and basal d. G. 1965). G. peruviana: commercial harvest periods and study peruviana - 15, 20x20 m contiguous plots - all trees Abundant (b)Estimate annual plot size for tagged and measured (ht < 1.5m tall; ht & d > 1.5m understorey level of fruit harvest each life tall). Fruit: M. dubia fruit marked with paint & counted tree in that would not stage. on 25 adult trees for 2 fruiting seasons. G. peruviana: monospecific damage long-term biweekly censuses of 15 adult trees for 1 year. stands regeneration Phenology - direct, weekly observations of 3 050 M. dubia and 248 G. peruviana tagged adult trees. Peru 570 larger Many Plants in Development of Quantitative Reserve - 7 previously established plots = 6.1 ha. 29 Statistical hypothesis testing using vascular plant seasonal simple technique to ethnobotany. Zone representative sample of informants interviewed (in informant use values: a) Relative utility of Phillips & species + 35 tropical moist provide data to Reservada plots and walk-in-the-woods) about uses of tagged species b) Relative utility of plant families Gentry additional tree, forest. permit hypothesis Tambopata plants on several occasions. Number of uses per c) Contribution of ecological, 1993a & b, liana and testing. species reported on single day (=event) recorded. Use physiognomic & phylogenetic factors to Phillips et al. arborescent value = sum of uses in each event / number of events utility d) Relative knowledge of different 1994 palms. for each informant and species Mean use value for informants e) relationship between cultural group or family = mean of informant/species informant knowledge and age. use values. Peru 29 tree Edible fruit Species-rich Fill information Yield. Reserve - Tagged every woody stem and some smaller plants of Statistical analyses facilitated by random species and nuts Amazonian shortfalls concerning Zona species known to have edible fruits. Visual selection of data from 10 (out of 20) Phillips 1993 including forests; Sandy annual forest fruit Reservada phenological observations and counts of immature and subplots non-contiguous subplots. Annual palms. terra firma, productivity: 1) Tambopata mature fruits made every month for 1 yr. For species fruit yield by forest type taking into account Clay terra variability of with low on-plant predation, counts were made on accessibility.

148 Location Target Product Life-form Objectives Type of study Scale Summary of methodology Analysis/Results firma, Alluvial, productivity with fruits falling onto 1m² quadrats located randomly Seasonal forest type 2) beneath canopy just after peak fruit-fall. Sample of swamp. accessibility of fruits palm fruits harvested and counted as a check on to ground based visual estimates. Sub-sample of fruits from a number collector 3) of individuals was weighed to get average fruit seasonality of fruit productivity per plant. For Mauritia trees in swamp production. forest regression of fruit per raceme with tree height was generated from earlier direct observations. Modelled 'access-weighted' production based on ground collection. Utilised Smithsonian 1 ha PSP plots. Peru Plants used by Useful Five lowland a) comparison of Quantitative Palcazu a) Between 2 and 9 randomly located plots 5x5 m Tables of numbers of useful plants in the Amuesha plant forest types useful plants ethnobotany. Valley. sampled from each forest type. Useful plants on plots different forest types. Comparative lists of Salick 1991 people. products. between major Research. identified using local herbalist. b) experimental strip useful plants before and after strip cutting. forest types. b) 20x75 m aligned N-S with a boundary shelterbelt was integration of NTFPs clearcut after enumeration of useful plants. Strips re- in commercial enumerated after 1 and 3 years for useful plants. forestry. Results confirmed with dendrological inventories. Venezuela Chachalacas, Bushmeat 14 species of Quantitative data on Population Regional -5 Census: 590 km in 180 transects utilising available Population densities: birds pre km and kg Guans & Feathers large-, habitat- the preference for census. sites in trails and primitive roads. Perpendicular distance to per ha at each study site. % interviewees Silva & Curassows. & bones specific Cracidae as food. different sighting measured from edge of road for arboreal who found Cracidae palatable. Hunting Strahl 1991 frugivorous Estimation of effects areas and species and from middle of road for terrestrial species. pressure: birds per hunter per year. forest birds. of hunting pressure forest types: Density estimates calculated using variable width on Cracidae 3 National transect equation. Hunter interviews: 17 question populations. Parks, 1 questionnaire used in villages and towns within or Forest bordered study areas=147 interviews. Reserve & 1 cattle ranch.

149 SOUTH-EAST ASIA Location Target Product Life-form Objectives Type of study Scale Summary of methodology Analysis/Results Indonesia Plants: 15 Medicinal Plants in 8 Implications of Quantitative Local - Social survey: Participant observation, formal and Summary diversity and abundance by epiphytes 14 plants locally logging and ethnobotany. Nanga Juoi informal surveys of all people aged 15+ years (n=32). vegetation type. Species accumulation Caniago & ferns 65 herbs recognised acculturation on the village and Plant collection and interviews with knowledgeable curves by vegetation type. Species Siebert 1998 15 shrubs 81 vegetation availability and surrounding healers over 3 years. 63 year old woman healer acted restricted to different vegetation types. trees 45 vines types. knowledge of forest. as principal informant. Forest sampling: Random plots Impact of harvesting by life form. 2 aquatics. medicinal plants. and transects in 8 locally recognised vegetation types. Distribution of knowledge by age and Plots: 2x2m (n=23, 38), 10x10m (n=11, 10), 2x100m gender among villagers. Table of species (n=23, 32). Transects: 2x1km (n=7, 3). In each with botanical and local names, voucher plot/transect, the identity, life form and number of each number, mean densities per ha by medicinal species was recorded. If locally-important vegetation type, parts used, use, life form, species were not found then the informant was asked harvesting impact and mean knowledge by to provide information on relative abundance and site villagers. preferences. Indonesia Babyrousa bushmeat Endemic wild Development of Spatial Local - Uses secondary data on: habitat map, road network, Coupled map lattice used to model babyrussa & pigs in tropical model which could harvesting northern market structure and harvesting processes, prices, populations of pig and hunting pressure Clayton et Sus high forest. be used to predict model arm of harvesting costs (travel cost), biological parameters within a GIS. Sensitivity analysis used to al. 1997 celebensis the future of the Sulawesi. (carrying capacity, intrinsic rate of population growth, evaluate the potential effectiveness of a harvested species density and susceptibility to hunting). range of control scenarios e.g. increasing under certain level of fines, placement of checkpoints assumptions. etc. Indonesia Useful trees Utilisation Trees > 10 cm To determine the Ethnobotanica Reserve - Identification of local names and uses for trees within List of useful trees and tabular summary (92.5% out of classes 0- occurring in local uses of trees > l. Domoga an established PSP (1984), which were tagged and by utilisation class. Edwards 109 spp). no use 1- lowland 10 cm d in a 1 ha Bone scientifically named at least to family. Questionnaire 1991 general tropical plot. National used for species with more than one use. purpose 2- rainforest. Park timber 3- NTFPs not in trade 4- NTFPs in trade. Indonesia Forest plants Various Plants and Analysis of the Inventory. Concession Household survey - interviews, participatory Abundance. Response to logging of and animals. e.g. wild animals in old socio-economic role -East observation yielding qualitative and quantitative data. specific plants. Grossmann rattan, growth forest and silvicultural Kalimantan 32 households selected from different user groups 1998 medicines management from 2 ethnically distinct villages using the same area and foods potential of NTFPs of forest. in natural timber Resource inventory - for perennial forest plants. production forest. Assessment of abundance, site preferences and management potential. Also comparative inventory in logged forest. Sample of ~400 plots. Indonesia Shorea Seeds, Trees in Provision of a Inventory Local - Sampled for selected forest products in: primary forest Abundance of products estimated from net stenoptera, fruit, tropical high quantitative Kembera and older managed forest: rubber gardens, fruit area of gardens with trees > 20 cm d. Lawrence et Durio spp., rubber & forest ecological village gardens and dry rice fallows where trees were > 20 cm Tables and graphs illustrating density, al. 1995 Hevea timber framework to lands, West d. abundance and proportion of useful trees brasiliensis, compare forest Kalimantan Managed forest: 32 plots of 20x50 m. Enumeration: by land use type and distance radii. Eusideroxylon resources and identified and measured all trees > 10 cm d and noted Abundance and use values compared

150 Location Target Product Life-form Objectives Type of study Scale Summary of methodology Analysis/Results zwageri extraction in location. between land use types using Mann- different forest Fruit garden sampling scheme: opportunistic selection Whitney U-test and Kruskal-Wallis tests. types. Examine of trails to cover 6 different areas. 2-5 gardens located Data from all samples pooled to generate constraints on on each trail, from these 1-3 randomly selected for size-class distribution of trees. stabilising land use detailed study to give a total sample of 10 plots. through the Rice fallow: prepared map of rice farms based on development of memory of 40-60 year old village informants. Half of extractive resources. fallows indicated on map selected for study such that Specific questions: the age of fallow was similar and plots adequately (1) What are the distributed over the selected trails. densities of Rubber gardens: chosen by village informants (4 marketable sp. in wealthy, 7 poor) to be representative of local, primary and productive gardens. managed forest Primary forest: 8 plots of 20x200 m randomly placed (2) What are the more than 10 m from and with the long axis abundances of perpendicular to trail. Potential timber trees (> 50 cm these sp. in primary d) sampled from 10x200 m plot nested within the and managed forest larger plot. accessible to the Species identifications done by leaf comparisons with village? known individuals, experienced local assistants and (3) Do the from specimens by a recognised authority. population Area of each type of land use estimated from 6 structures of these transects of 1.5 km and from schematic maps of sp. indicate the village lands. potential for long- Area of each land use within 3 radial distances from term extraction? the village (2.5 km = distance to nearest primary (4) How do the forest, 5.5 all primary forest to next village's cultivated density and land, 8 km distance into half of nearby reserve) abundance of these estimated from schematic maps of village land to resources influence nearest 10 ha to model extraction. the actual extraction All trees > 10 cm d grouped into 'consumption', and management of 'currently marketable' and 'no particular use' classes forest products? by local informants who were judged to have an 'average knowledge of medicinal and religious uses of trees > 10 cm d. Indonesia List depends Constructi Useful plants Trial of a new Participatory Local -Long Determination of village objectives and resources for Maps of resources. Tables of totals and on villagers: on in community methodology for inventory. Tebulo & inventory. Design: systematic lines of 5 10x10m plots mean density per ha for each resource Lund 1998a, Long Tebulo: materials, forest participatory Semambu laid end to end. Lines orientated across topography. (calculations on hand held calculators). Stockdale & 8 trees, 2 incense, resource village lands Sampling proportional to area so distance between Corbett shrubs, 1 resin, assessment. lines not standardised. Random origin for survey lines. 1999 rattan, 2 herbs, 10-15% of plots check surveyed. Vouchers collected. palms weaving Semambu: 8 materials, trees, 2 palms, edible fruit 2 bamboos, 3 & seeds, rattans, 1 dye. shrub.

151 Location Target Product Life-form Objectives Type of study Scale Summary of methodology Analysis/Results Indonesia Livistona Leaves for Palm Determination of Growth study. Research One year study. Experimental harvests on 10 small- Analysis of leaf development with canopy rotundifolia. roofing growth and site - sized (0.5-1.4 m tall) palms with 20 controls. Two closure, rainfall and timing of emergence. O'Brien & replacement rate of Tangkoko- harvest intensity treatments: light (50% of mature Analysis of average daily expansion rate, Kinnaird leaves under Dua Sudara leaves cut on 5 plants) and heavy (all leaves cut on 5 time until leaf opened, maturation time and 1996 different harvesting Nature plants). Monitored growth of 2 new leaves per palm in final leaf size for harvest treatments using levels. Are current Reserve, controls and 3 leaves in treatments. Leaf expansion multiple analysis of covariance. harvesting practices Sulawesi measured weekly and time of emergence, opening of Comparison of palm density in harvest and sustainable? What blade, cessation of expansion and damage was non-harvest zones using t test. might constitute an recorded for each leaf. Canopy cover and rainfall appropriate harvest. (known to affect leaf development) also recorded. Inventory of palms in 20 0.25 ha randomly located plots within study area. All palms tagged, heights measured and cut leaves recorded. Distribution of harvested plots used to stratify area into harvest and non-harvest zones. Indonesia Shorea Illipe nut - Common, Density of Illipe in Productivity Research Site chosen because of reported occurrence of annual Stand table. Exponential model fitted to atrinervosa. edible oil widely residual forest. site - fruiting Illipe. 1 ha plot marked into 25, 20x20m fruit production against tree size. Use of Peters for local distributed Existence of Gunung quadrants. All Illipe trees > 1m tall measured for height regression and stand table to estimate 1996b consumpti forest tree varieties with Poteng and diameter, mapped and labelled. Seedlings total fruit production per ha. Potential for on and reaching high atypical or annual sampled in 200 randomly located 1m² plots. All the sp.. Illipe production from natural forest to export densities in fruiting. Productivity > 5cm d also measured and mapped. Information on improve income of rural households. favoured of natural stands local nomenclature and use of each taxa recorded. habitats within and potential for Fruit production: selection of 4 isolated trees, 15 1m² mixed sustainable plots randomly located beneath crown, number of dipterocarp hill exploitation / intact and predated immature and mature recorded forest. management of every 7-10 days. Long term PSP (established 1990 - Illipe. paper reports results for 2 years). Indonesia Rattan, 3, 9 Many Climbing Determination of Field Reserve, At each site, standing stock of rattan enumerated in 16 Summary of species and densities (ton/ha) and 10 spp. palms adequate rattan determination District -3 ha study site divided into contiguous 10x10m subplots. found on research plot. Optimal method Siswanto & Respectively. sampling techniques of optimal sites in Species, number of stools and stems, diameter, length based on minimising sampling errors Soemarna for specific Forest inventory West, South and weight of all stems recorded Two sampling determined for each site. Continuous strip 1988, Districts or Forest design. and Central methods tested using data: Continuous strip sampling sampling with strips 10m width and 20% Siswanto & Complexes. Kalimantan. with strips of 10m and 20m width and sampling sampling intensity considered most Soemarna intensities of 10, 20 & 25%. Line plot sampling with adequate. 1990, plots of 10x10m and 20x20m with sampling intensities Siswanto of 10 & 25%. 1991 Indonesia Land and Many Land and To secure tenure to Participatory Reserve - Steps in mapping traditional resource use: Preliminary GIS for map overlays and calculation of plant useful plants land and rights to mapping. Kayan site visit. PRA sketch mapping & transect walks. River area. Stockdale & resources in traditional resources. To seek Mentarang and watershed base maps prepared from radar Ambrose especially forest use compensation for Nature imagery. Mapping workshop in formal village 1996 rattan. areas expected damage to Reserve, assembly. Village feedback. Improving map accuracy land and resources. East using GPS and GIS rubber sheeting. To manage Kalimantan resources on a sustainable basis. Indonesia Calamus Rattan Climbing palm First enumeration of Monitoring. Local -Long Site selected using local information of species Linear regression to estimate commercial

152 Location Target Product Life-form Objectives Type of study Scale Summary of methodology Analysis/Results caesius. in community PSP for C. caesius Uli village abundance and distance from village (5-6 hour walk). length from total length estimates. Stockdale managed which hadn't been lands, East 3 ha (300x100m) divided into 10x10m subplots. All Densities of stems, clumps, length etc. 1994 forest studied before. Kalimantan clumps/stems counted. Each clump classified Distribution of age classes examined using according to condition and age. Condition=alive/dead overlays. Life history parameters, age, Age=juvenile, commercially immature (< 12m), stage & size class and sexual and commercially mature (>12m). Clumps take age of vegetative fecundity estimated from oldest shoot. Leaf numbers counted for juveniles. population structure. Stems < 3m, internodes and length measured. Stems > 3m, internodes estimated, ground length measured and above-ground length estimated using ruler hypsometer. Mature stems from 32 clumps harvested and measured. Indonesia Fruit & nut Commerci Trees and Inventory of Inventory and Research - 1. Inventory: Uses pre-existing PSP plot data for 3 1. Importance values used to describe/ trees and al food, oil climbing commercially yield Sites in sites: Wanariset = 6 subplots (0.08 ha) of a 1 ha PSP, compare taxa between plots & sites. Valkenberg rattans. and palms in important NTFPs. experiments. three areas ITCI concession = 7 plots (0.5 - 2 ha, 4 unlogged, 3 Species presence/absence data used in 1997 handicraft primary and Comparison of of East logged), Apo Kayan = 4 plots (0.64 ha) and 4 line-plots conjunction with use categories to material logged over distribution and Kalimantan, of 0.12 ha. Plots arranged in a toposequence from compare NTFP use values between forest. abundance of use of valley floor to ridge crest. families, sites etc. Number of harvestable NTFPs. Study existing PSP Enumeration: all trees > 10 cm d measured and trees of timber, exudate and fruit for two effects of logging on data. located to the nearest 10 cm. Species vouchered and sites. NTFPs. Contribute identified in herbarium by original enumerators. 2. Rattan growth in terms of culm basic data for 2. Rattan study: in the selected PSP plots all rattans > recruitment and movement between sustainable 0.5m tall were tagged and its growth stage recorded: growth stages in graphs showing the % of management. sucker (0-49 cm), juvenile (50-199 cm), immature (> clumps where numbers in each growth 200 cm & green) and mature (> 200 cm & brown). stage have decreased, remained stable or Changes in growth stage noted yearly for 2 years. increased. Canes harvested from one site at end of study to 3. Correlation of recruitment, initial determine the number of harvestable canes. population size of rattan and disturbance Disturbance levels estimated for each plot. level. 3. Harvesting impact on rattan - ~30 clumps of 3 species were harvested and the remaining culms tagged for growth stage and reassessed after 12 months. Malaysia Bamboo Woody Understorey Investigation of Mapping. Reserve - Used digital image process and visual interpretation of Visual interpretation of bamboo-dominated stems. clumping, usefulness of Chebar hardcopy (TM 453). Used hardcopy for ground forest was possible in colour composite Khali et al woody grass satellite imagery for Forest truthing. images. 1995 in logged over mapping bamboo Reserve, Field inventory: sample points randomly chosen in Field data used to determine bamboo forest. areas in tropical Nami, mapped units containing bamboo. Plots were densities and permitted the discrimination logged forest. Kedah. 100x100m (1 ha). Stems tallied into diameter classes. of two bamboo density classes in each of Numbers of culm and clumps in plot counted. the 2 bamboo forest types. Malaysia Medicinal Plant parts List of plants Ethnobotanica State-wide - Voucher collection and identification of plants reported List of plants by local and botanical names plants. not currently used as l inventory. Sabah. to be cures by local informants Kulip 1997 specified cures Malaysia Calamus Rattan. Climbing palm Assessment of stem Plantation Research - Experimental plots in plantations. Young plants: leaf increment expressed on manan in tropical length and yield growth and FRIM Mensuration methods used to determine stem length a monthly and annual basis. Regression Nur Supardi moist forest. potential. yield. experimenta and growth. used to relate stem length to number of 1993 l plantations. Young plants: number of leaves counted from base to leaves on plants with between 4 and 15

153 Location Target Product Life-form Objectives Type of study Scale Summary of methodology Analysis/Results the last expanded leaf. Shed leaves counted using leaves. petiole, sheath or scar. Unexpanded leaves counted. Stem length expressed as mean and total Last leaf tagged and new leaves counted above this at stem lengths per ha. Growth expressed as subsequent enumerations. mean monthly increment. Stem length measured as distance between root collar and point where petiole of last expanded leaf and unexpanded leaf meet. Young plants measured using 1.5 m pole. Climbing at mature plants- lower length measured with tape, poles used for aerial stem to 8.5 m, beyond this relascope or counts of interknees used. Counts of interknees or fronds done from several locations. Interknee distances measured on lower stem and weighted moving average of 10 nodes used to estimate length of upper stem. Internode parameters estimated as average of 2 observations. Internode length and mid-d determined starting from 1 m from root collar. Malaysia Rattan. Stems for Climbing To determine an Methodologica Research - Study in 3 phases: staff training, 100% survey of all Means, CV and sampling errors for weaving. palms in efficient rattan l study. Pasoh & rattan in demarcated plots, implementation of 3 number of clumps, number of stems and Nur Supardi tropical high inventory design Semangkok sampling designs within the plots. stem length calculated for each forest. et al 1995 forest. adaptable to the Forest Two sites used, Pasoh (PFR) = lowland dipterocarp, Sampling designs compared with 100% different forest types Reserves, site in 50ha PSP & Semangkok (SFR) = hill enumeration. Strip sampling gives closest in Malaysia. Peninsular dipterocarp, site = 28 ha. estimates in lowland forest while clusters Malaysia. 100% enumeration - size and position of all rattan were best in hill forest. stems recorded. Grosenbaugh's criterion (SE% x time) PFR - 2 x 500x100m plot divided into 125 subplots of used to compare the efficiency of the 20x20m each sub-divided into 16 sub-quadrats of sampling methods. Cluster sampling best 5x5m. for determining number of clumps and SFR - 2 x 100x100m divided into 25 20x20m subplots. stem numbers while strip sampling best for Sampling designs estimating stem length in hill forest. In (1) Strip sampling - 5 x 100x10 m systematic strips lowland forest strip sampling is most placed 100 m apart and divided into 4 25x10m accurate although grid sampling is more subplots. efficient. (2) Grid sampling - 5 cross shaped plots of perpendicular subplots of 100x5 m with 100m between the centres of the grids. (3) Cluster sampling - 3 plots with 6 subplots of 28x10 in 2 rows 20m apart and 3 columns 50m apart - 80m between clusters. Sampling intensity fixed at 10%. In each plot and subplot, all rattan stems > 30cm were tagged, identified to sp.., cluster number, stem number, stem length, stem diameter and other observations related to growth. Length estimated using tape for ground portion and upper portion estimated using numbers of nodes or leaves and the ht of host trees as a guide.

154 Location Target Product Life-form Objectives Type of study Scale Summary of methodology Analysis/Results Enumeration done in teams of 5. Malaysia Bamboos, Various Understorey Collect and generate Pre-harvesting National, Peninsular Malaysia - Pre-felling inventory - systematic Data analysed by computer and used to rattans, palms commerci plants in following information operational Peninsular line-plot of 50x20 m with 50 m between plots on lines prepare colour coded stock maps at Thang 1992 and climbers al uses. tropical forest. on forest resources level forest Malaysia, 100 m apart. The presence of rattans, bamboos, 1:5,000 scale with incidence of bamboos before timber inventory (for Sabah & Eugeissona triste (bertam), palms and ferns etc indicated using codes written above harvesting timber). Sarawak. enumerated from the whole plot. each of the principal plots. commences: Sabah - FAO/UNDP state-wide inventory - systematic (i) species line-plots of 60x20 m with 4 nested sub-plots of 20x20, distribution by main 10x10, 5x5 and 2x2 m, 120 m between plots and commercial species 200m between lines. Incidence of rattans recorded in and species groups 60x20 m plot and climbers in 10x10 m plot. (ii) frequency of occurrence of species by selected d classes (iii) gross and net commercial volume per ha for the main species and species groups by d classes (iv) frequency of occurrence of rattans and bamboos by commercial species or species groups (v) frequency of occurrence of palms and climbers. Papua New Agathis Copal Emergent tree Reconnaissance of Air survey. Regional - 2 flights in Cessna 337 Speed: 100 miles per hour. Identification of 7 habitat types for sp.. Guinea (labillardieri). gum -in distinct Kauri stands in southern Time: 3 1/4 hours, 3 1/2 hours Distance: approx. 300 Estimate of standing volume and copal stands (3-25 relation to tributaries of miles, aborted due to bad weather. Visits to 11 production for area. Zieck 1968 mature trees production of copal. Sepik river. possible locations for survey and air photographs. per ha) in river valleys from ~50-600m altitude. Philippines 10+ spp. of Poles, Climbing Not given Multi-purpose National Country divided into 12 forest regions, 2,100 clusters Summary tables showing rattan length per Rattan. baskets, palms in resource sampled to give a sampling error of 3%. Regions ha by vegetation type, region and species. Serna 1990 hats, twine natural forest. inventory 10&11 trees sampled using systematic cluster National summaries of rattan lengths by etc. (timber, sampling on 8x8 km grid. Clusters=4 20x250m strips size/use classes. Sustained yield cut rattans, palms (20x50m subplots) orientated in each cardinal direction (SYC) determined by formula: SYC = & bamboo). offset 1 km from grid intersection. Rattans sampled in (AxD/R) x f. Where A=Forest area (ha) 10x10 m subplot centred on strip midline at beginning D=average length ha-1 R=rotation of 15 and every 100m (=3 per strip). All other regions - years f=recovery factor of 85% triangular arrangement of 6-point cluster (points and half way down sides of triangle) of 6 Bitterlich point

155 Location Target Product Life-form Objectives Type of study Scale Summary of methodology Analysis/Results samples with a basal area factor of K=9 m²ha-1 each 50m apart. Rattans sampled at corner points in a 5m radius plot. Rattan stems rooted within plot with diameters below and above 2 cm enumerated separately. Regeneration by species tallied. Tallies by diameter class and average length recorded for each species. Philippines Rattan (9 spp, Raw Climbing Determination of an Inventory Research All rattans (seedlings and mature) counted and Plot efficiency determined as SE per 3 3 genera in material palms efficient sampling methodology. site -1 ha - mapped within a 1ha plot. Within large plot 5x5m grid hour cruise (best=10x10m plots). Fit of Tandug study). for occurring in technique for low- Bayugan =400 quadrats. Records made of: a) average time to binomial, poisson and negative binomial 1978 handicraft dense cost 'good' travel 10m between plots, b) average time to count to density distribution of rattan (best=-ve and thickets. estimates. rattans within a plot, c) diameter and total commercial binomial). export. Dispersion, length of rattan (of cut culms). 9 plot sizes and shapes distribution and total (assembled from 5x5m quadrats) tested. Study counts. repeated at second location for verification of conclusions. Philippines Schizostachyu Bamboo Natural To determine the Experimental Research - 54 clumps randomly assigned to treatments in a 3x3x2 Three main analyses: m lumampao stems for clumps. effects of thinning, harvests natural factorial design (thinning, cutting & felling cycle) with 3 (1) Preparation of clumps for management Virtucio weaving cutting age and stands in replicates. (thinning) - Analysis of covariance 1993 & felling cycle on the Ilocos Norte. Treatments (2) Yearly assessment of clump Virtucio & variation of clump (1) Thinning regimes: 6 clumps in each replicate sustainability - data for last 6 years of Tomboc productivity and treated with a range of thinning intensities: heavy= in study. ANOVA 1994 harvest cut. 2nd yr of experiment all culms cut except those <= 1 yr (3) Overall yields and clump sustainability old, moderate =in 3rd yr all culms cut except those - ANOVA <=2 yrs old, light =in 4th yr all culms cut. Results indicate that optimal harvesting (2) Culm cutting age: culms cut at 3, 4 or 5 yrs of age. pattern is to cut 3 yr old culms on a 2 year (3) Felling cycle: culms harvested every yr or every 2 felling cycle with moderate initial thinning years. of mature culms in the natural clumps. Treatments carried on for 10 years (1979-1989).

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165 Appendix 5 Sources for quantitative inventory methodology Adlard P.G. (1990) Procedures for monitoring tree growth and site change. Tropical Forestry Papers 23. OFI, Oxford. 188 pp. Alder D. (1995) Growth modelling for mixed tropical forests. Tropical Forestry Papers 30. Oxford Forestry Institute. 231 pp. Alder D. & Synott T.J. (1992) Permanent sample plot techniques for mixed tropical forest. Tropical Forestry Papers 25. Oxford Forestry Institute. 124 pp. Alexiades M.N. (1996) Selected guidelines for ethnobotanical research: A field manual. New York Botanical Garden. 306 pp. Atkinson R.P.D. (1997) Practical aspects of trapping small mammals in the tropics. Journal of the Zoological Society of London 242: 390-394. Barnett A. (1992) Expedition field techniques: Small mammals (excluding bats). Expedition Advisory Centre, London. 75 pp. Berlin B. (1992) Ethnobiological classification: Principles of categorization of plants and animals in traditional societies. Princeton University Press, New Jersey. 335 pp. Bolton M. (1997) Conservation and the use of wildlife resources. Chapman & Hall. 278 pp. Branney P. (1994) Handbook for baseline forest resource assessment. Nepal-UK Community Forestry Project. LTS International, Edinburgh. 19 pp. Buckland S.T., Anderson D.R., Burnham K.P. and Laake J.L. (1993) Distance sampling. Estimating abundance of biological populations. Chapman & Hall, London. 446 pp. Burnham K.P., Anderson D.R. and Laake J.L. (1980) Estimation of density from line transect sampling of biological populations. Wildlife Monographs No. 72. Wildlife Society, New York. 55 pp. Campbell D.G. and Hammond H.D. (1989) Floristic inventory of tropical countries. New York Botanical Garden. 545 pp. Carter J. (1996) Recent approaches to participatory forest resource assessment. Rural development forestry study guide 2. ODI, London. 322 pp. Index. Caughley G. and Sinclair A.R.E. (1994) Wildlife ecology and management. Blackwell Science. 334 pp. Cochran W.G. (1977) Sampling techniques. Third edition. John Wiley & Sons. 428 pp. Collinson R.F.H. (1985) Selecting wildlife census techniques. Institute of Natural Resources. Monograph 6. University of Natal, Pietermaritzburg, S.A. 83 pp. Cook F.E.M (1995) Economic botany data collection standard: prepared for the International Working Group on Taxonomic Databases for Plant Sciences. Kew Cotton C.M. (1996) Ethnobotany principles and applications. Wiley. 424 pp. Dunn A. (1993) A manual of census techniques for surveying large animals in tropical forests. Report prepared for WWF-UK, Contract reference: NG0007 (4686) Gashaka Gumpti National Park Project. WWF. 20 pp. Farina A. (1998) Principles and methods in landscape ecology. Chapman & Hall. 235 pp. Fowler J. and Cohen L. (1995) Practical statistics for field biology. John Wiley & Sons, Chichester, New York, Brisbane, Toronto, Singapore. 227 pp. Freese F. (1984) Statistics for land managers. Paeony Press. 176 pp. Gillison A.N. and Brewer K.R.W. (1985) The use of gradient directed transects or gradsects in natural resource surveys. Journal of Environmental Management 20: 103-127. Given D.R. and Harris W. (1994) Techniques and methods of ethnobotany. Commonwealth Secretariat, London. 148 pp. Goldsmith F.B. (1991) Monitoring for conservation and ecology. Chapman & Hall, London. 275 pp. Grieg-Smith P. (1983) Quantitative plant ecology. Third edition. University of California Press,

166 Berkeley, California. Gurnell J. and Flowerdew J.R. (1990) Live trapping small animals. A practical guide. Occasional publication No. 3. Mammal Society, London. 39 pp. Hagan B. von, Weigand J.F., McLain R., Fight R. and Christensen H.H. (1996) Conservation and development of nontimber forest products in the Pacific Northwest: An annotated bibliography. General Technical Report PNW-GTR-375. Pacific Northwest Research Station, Forest Service, US Dept. of Agriculture. 246 pp. Heyer W.R. et al (1994) Measuring and monitoring biological diversity: Standard methods for amphibians. Smithsonian Institution Press, Washington. 364 pp. HMSO (1996) Biodiversity assessment. A guide to good practice. Field manual 1. Data and specimen collection of plants, fungi and microorganisms. HMSO, London. 82 pp. HMSO (1996) Biodiversity assessment. A guide to good practice. Field manual 2. Data and specimen collection of animals. HMSO, London. 80 pp. Husch B., Miller C.I. and Beers T.W. (1982) Forest mensuration. Third edition. John Wiley & Sons. 402 pp. IDRC, CIDA and IIR (1998) Participatory methods in community-based coastal resource management. Volume 3 Tools and methods. IIRR, IDRC, CIDA Koppell C. (1995) Marketing information systems for non-timber forest products. Community Forestry Field Manual No. 6. FAO, Rome. 115 pp. Koster S.H. and Hart J.A. (1988) Methods of estimating ungulate populations in tropical forests. African Journal of Ecology 26: 117-126. Linde H. van der and van Adrichem (1997) Non-timber forest products from the tropical forests of Africa. A bibliography. Netherlands Committee for IUCN. Amsterdam. 60 pp. Loetsch F., Zohrer F. and Haller K.E. (1973) Forest inventory. Volume 2. BLV Verlagsgesellschaft. 469 pp. Lund H.G. (1998) IUFRO Guidelines for designing multipurpose resource inventories. IUFRO World Series vol. 8. IUFRO, Vienna, Austria. 216 pp. Martin G.J. (1994) Ethnobotany. A methods manual. Chapman & Hall. 296 pp. McCullagh P. and Nelder J.A. (1983) Generalised linear models, 2nd edition. Monographs on Statistics and Applied Probability 37. Chapman & Hall, London. Milner-Gulland E.J. and Mace R. (1998) Conservation of biological resources. Blackwell Science. 404 pp. Myers W.L. and Shelton R.L. (1980) Survey methods for ecosystem management. John Wiley & Sons. 403 pp. Nichols P. (1991) Social survey methods: A fieldguide for development workers. Development Guidelines No. 6. Oxfam Publications. 117 pp. North P.M. (1994) Ornithological statistics. pp. 463-506. In: Environmental Statistics. Handbook of Statistics vol. 12. Patil G.P. & Rao C.R. (eds). Elsevier Science. 927 pp. Norton-Griffiths M. (1975) Counting animals. Publication no. 1 in a series on techniques currently used in African wildlife ecology, Serengeti Ecological Monitoring Programme. African Wildlife Leadership Foundation, Nairobi, Kenya. 105 pp. O'Shea M. (1992) Expedition field techniques: Reptiles and amphibians. Expedition Advisory Centre, London. 27 pp. Paivinen R. (1994) IUFRO International guidelines for forest monitoring. IUFRO World Series Vol. 5. IUFRO, Vienna, Austria. 102 pp. Patil G.P. and Rao C.R. (1994) Environmental Statistics. Handbook of Statistics vol. 12. Elsevier Science. 927 pp. Peters C.M. (1994) Sustainable harvest of non-timber plant resources in tropical moist forest: An ecological primer. Biodiversity Support Programme. WWF, Washington, USA. 44 pp.

167 Peters C.M. (1996) The ecology and management of non-timber forest resources. World Bank Technical Paper number 322. World Bank, Washington. 157 pp. Philip M.S. (1994) Measuring trees and forests. Second edition. CAB International. 310 pp. Poffenberger M., McGean B., Ravindranath N.H. and Gadgil M. (1992) Field methods manual. Vol. 1 - Diagnostic tools for supporting joint forest management systems. Joint Forest Management Support Programme. Society for Promotion of Wastelands Development, New Delhi. 101 pp. Pomeroy D. (1992) Counting birds. African Wildlife Foundation, Nairobi. 48 pp. Prescott-Allen R. and Prescott-Allen C. (eds) (1996) Assessing the sustainability of uses of wild species. Case studies and intial assessment procedure. Occasional paper no. 12. Species Survival Commission. IUCN, Gland. 135 pp. Rabinowitz A. (1993) Wildlife field research and conservation training manual. Wildlife Conservation Society, New York. 281 pp. Schemnitz S.D. (1980) Wildlife management techniques manual. Wildlife Society, Washinton. 686 pp. Schreuder H.T., Gregoire T.G. and Wood G.B. (1993) Sampling methods for multiresource forest inventory. Wiley, New York. 446 pp. Shiver B.D. and Borders B.E. (1996) Sampling techniques for forest resource inventory. John Wiley & Sons. 356 pp. Spellerberg I.F. (1992) Evaluation and assessment for conservation. Chapman & Hall, London. 260 pp. Stockdale M.C. and Corbett J.M.S. (1999) Participatory inventory: A field manual written with special reference to Indonesia Tropical Forestry Papers No. 38. Oxford Forestry Insitute. 383 pp. Sutherland M.J. (1996) Ecological census techniques. A handbook. Cambridge University Press 336 pp. Tandug L.M. (1988) How to inventory rattan. Ecosystems Research and Development Bureau, DENR College, Laguna. 6 pp. Thompson S.K. (1992) Sampling. John Wiley & Sons. 343 pp. Upton C. and Bass S. (1995) The forest certification handbook. Earthscan, London. Vanclay J.K. (1994) Modelling forest growth and yield: Applications to mixed tropical forests. CAB International. 280 pp. Vries P. de (1986) Sampling theory for forest inventory. Springer, Berlin. 399 pp. Watt A. et al (1998) Evaluation and development of methods of rapid biodiversity assessment in relation to the conservation of biodiversity in tropical moist forests. ITE, Edinburgh. Unpublished. Watt, A.D., Stork, N.E. and Hunter, M.D. (1997) Forests and insects. Chapman & Hall, London. Wilson D.E., Cole F.R., Nichols J.F., Rudran R. and Foster M.S. (1996) Measuring and monitoring biological diversity. Standard methods for mammals. Smithsonian Institution Press, Washington & London. 409 pp. Zar J.H. (1984) Biostatistical analysis. Second edition. Prentice-Hall. 718 pp.

168 Appendix 6 TROPIS search for NTFP PSP plots

Results of TROPIS search for PSPs that are enumerated for NTFPs (Vanclay 09/01/99)

Plots Country Area Name Email/Fax First Last # 4 Cameroon 0.2 Robert Fimbel [email protected] 1995 1995 1 15 China Zeng Qingbo fax +86 20 7725622 1958 1995 0 9 Colombia 0.1 Conrado Tobon Marin [email protected] 1992 1992 1 1 Malaysia 50 N. Manokaran [email protected] 1985 1995 3 131 Nepal 0.05 Prayag Raj Tamrakar [email protected] 1986 1996 17 Peru 1 Oliver L Phillips [email protected] 1979 1996 4 1 Singapore 2 James LaFrankie [email protected] 1993 1996 2 58 Uganda 0.2 Colin Chapman [email protected] 1990 1996 2 9 Uganda 0.04 Willy Kakuru fax +256 41 530134 1994 1996 12

169 Appendix 7 Summary of newer sampling methods with potential for NTFP inventory

Class of method Details Features Adaptive General class of methods in which the number of plots sampled +Efficient (precise and cost-effective) and unbiased sampling strategy for sampling responds to the occurance and number of individuals encountered rare, clustered or spatially uneven populations during sampling. +Increases sampling yield (more observations for a given sampling effort than SRS15) +Locates and incorporates local hot spots -Cannot know number/cost of sampling at start of exercise -Special calculations of mean and variance required Adaptive cluster Initial simple random sample. Add plots (usually adjacent to ‘filled’ plot +Forms clusters of sample plots that grow towards local maxima and sampling in a fixed pattern, often in a cross configuration) whenever a plot completely include aggregations of individuals contains more than a threshold number of individuals (adding rule) stop adding when all new plots do not satisfy the adding rule. Initial strip samples (plot clusters grow sideways from strip once +Good for covering large areas species is discovered) Initial systematic sample (with random starting point) +Very efficient for rare, clustered populations Order statistics adding rule (adding rule uses rank order of samples +Population of unknown density for which an a priori adding rule cannot be i.e. if new plot has density > 4th highest then add new plots) determined - Computations more involved Stratified: +Permits use of prior information (1) Clusters not allowed to cross strata boundaries (1) Strata independence maintained (2) Clusters allowed to cross strata boundaries (2) More efficient but requires special calculation of mean Adjusted for imperfect detectability: +Good for motile or cryptic organisms (1) Constant detectability -Uses non standard mean and varianace calculations (2) Variable detectability Adaptive Sample sizes based on initial observations in each stratum: +Maximises the value of pilot studies allocation Stage 1: Area divided into strata and SRS (or other allocation system) +Permits collection of additional data in areas discovered to have high used in each strata population density without compromising design Stage 2: More plots added using SRS (in proportion to number of +Costs easier to control plots per strata that qualify on adding rule or to minimise estimated -Requires two passes over study area final variance) -Small negative bias in estimates for total pooled sample Sample size based on observations from previous strata +Only requires one pass (sequential SRS of strata; allocation of plots to subsequent strata +Good for sampling across large scale environmental gradients e.g. based on adding rule and observations in previous strata) mountain slopes where target species may be confined to certain altitude zones +Traditional stratified SRS calculations apply

15 SRS – simple random sampling

170 Ranked set General class of methods which use subjective ranking into m ranks +Gives unbiased estimates and better precision than SRS of same sample sampling according to the magnitude of the characteristic of interest (e.g. size species denisty) of a set of m possible sample plots from a restricted +Works best for populations with high local variability and can be tailored to sample location. The plot of rank 1 is enumerated from set 1, rank 2 match the level of local variability from set 2 to rank m from set m. The number of ranks is usually <=5. +Permits the incorporation of subjective knowledge Repeat cycles of m sets can be done to increase number of plots for -Requires visual comparison of plot sets for ranking so they must be close inference. Average of means of each rank is an unbiased estimate of together the population mean. -Cost of locating plots for ranking needs to be small compared to cost of enumeration Unbalanced ranked set sampling i.e. sampling proportional to +Optimised for skewed distributions – more effort directed to long tail of standard deviation of ranks distribution with high variability. Ranking using concomitant variable. Ranking done using a variable -Level of ranking errors related to strength of predictive relationship between that is easier to estimate and strongly correlated to the variable of ranking variable and variable of interest interest. E.g. ranking on tree height as a surrogate for fruit yield. Class of method Details Features Guided Two-stage unbiased design for transect survey utilising high +Can use high resolution prior data i.e. classified pixels from remote sensing transect resolution prior information. interpretation sampling Stage 1: Wide strips laid out as primary units and divided into grid- +Better alternative to gradsect sampling etc. as line selection is based on cells of suitable dimensions for which prior information, ie. remote probability rather than subjectivity sensng is available. +Good for sparce populations Stage 2: One survey line for sub-sampling per strip is randomly -Requires large amounts of detailed prior information selected. The grid-cells that will form the route of the survey line are selected with probabilities proportional to their covariate values. The strategy for selecting cells can be varied. Along selected lines the inventory is performed using some transect based method such as line transect sampling, strip surveying, line intersect sampling etc.. References: Adaptive sampling: Brown (unknown date), Seber & Thompson 1994, Thompson & Seber 1994, Thompson 1991, Thompson 1992, Thompson 1997. Rank set sampling: Halls & Dell 1966, McIntyre 1952, Muttlack & McDonald 1990, Patil et al 1994. Guided transect sampling: Ståhl et al 2000.

171 Appendix 8 Folk classification and local names

Over the past 30 years the study of folk classification has been a major preoccupation of linguistic anthropologists (Martin 1994). The generally held conclusion from these studies is that the ways in which human societies categorise and name biological organisms are similar in structure and substance. Furthermore, folk systems of classification often parallel the formal scientific system which is taken as demonstrating that human beings generally perceive their environment and differences in a consistent manner (Cotton 1996). Studies of the classification of plants and animals have cumulated in models describing the systematics of folk classification such as that proposed by Berlin (1992) which is increasingly accepted by other ethnobiologists (Martin 1994, Cotton 1996).

The basic structure of a folk classification is hierarchical in that each lower order rank is a sub-set of the higher order ones. The highest level is kingdom where ‘plants’ are distinguished from ‘animals’. It is unnamed or covert in that it is conceptually recognised but does not require a name for use in everyday speech. The basic division under kingdom is lifeform, which corresponds to gross morphological differences which are easily understood; thus in the plant kingdom, for example, ‘trees’ are distinguished from ‘vines’ etc.. Under lifeform an intermediate level exists, which represents little used, covert, and therefore often unnamed groupings of similar plants. The folk generic level is the one that is of most interest and corresponds roughly to the genus and/or species level in the scientific classification. Folk generics can be divided into folk specifics and further into folk varieties though the latter are relatively uncommon. Specifics and varieties often have compound names made up from the generic name plus a qualifier such as red, hairy etc.. There seems to be a natural limit of between 300 and 600 generic names for plants within any one language (Berlin 1992, Martin 1994) so it follows that there will not be enough local names to fully describe a tropical flora which can contain several thousand scientific species.

Folk generics are the most salient names and are usually affiliated to a lifeform but there are also parallel unaffiliated naming systems. These systems often refer to the use of the plant e.g. categories for medicines, firewood etc. which can contain very different lifeforms having similar uses or properties (Martin 1994). Use-based names are most common for the culturally most important plants and applications (i.e. they are most common for cultivated plants). A plant may therefore possess a generic name associated with lifeform as well as a medicinal name that refers to its use as a cure for a specific illness. These may be interchangeable, depending on context, and confound any simplistic interpretation of plant identity.

Folk classification and names are cultural in character and describes the natural world as perceived by the local people. However, this does not permit any comparison of plants or uses between cultures or with the body of scientific knowledge. The bridge between the natural science and cultural perspectives in this case is the mapping of folk names onto the scientific classification. Although about 60 % of folk generic names map onto scientific species (i.e. there is a one-to-one correspondence of folk to scientific names) there are discrepancies as illustrated in the table below. Correspondence of folk and scientific names (after Martin 1994, Cotton 1996) Correspondence Explanation Correspondence * One-to-one correspondence Folk generic = scientific species 61% Under differentiated (I) Folk generic = two or more scientific species of the 21% same genus Under-differentiated (II) Folk species = more than one scientific genus 14% Over-differentiated More than one folk generic = scientific species 4% * Correspondence of Tzeltal Maya names (n=471) taken from Berlin (1994) quoted in Martin (1994).

The study of NTFPs is often confounded by the difficulties of assigning a scientific identity to locally named products which is not surprising given the above complexities. The more important or useful a plant is, the more likely it is to have multiple, complex or opaque names. Major NTFPs are therefore likely to:

172 - be over-differentiated (interest in specific properties of more useful plants is likely to result in folk varietal differentiation within a single scientific species), - subject to parallel classifications because of familiarity and focus on uses rather than lifeform affiliations, - have polytypic names at the generic level, - use the same primary name for the folk generic and prototypic folk specific (the most desirable or ‘proper’) name with other specifics having secondary names, - have opaque names (i.e. not descriptive and untranslatable), - have cognate names (i.e. same name across languages derived from a common root name).

Market based studies suffer from a further complication as the market name for a product may be taken from a regional lingua franca and bear no relation to any of the local names used by those gathering the product. Products made from the same species are also likely to have quite different names e.g. ‘thatch’ and ‘straw’ are possible alternative product names for stems of a single species. Sometimes these product names, rather than the ‘taxonomic’ ones, are used by local people undertaking commercial collecting for the source species, which adds a further level of complexity to the problem.

A multiplicity of names and naming systems for plants is not the prerogative of indigenous communities. Given & Harris (1994) point out that there are several parallel naming systems used for well-known plants in the west and quote the example of New Zealand Flax: Names for New Zealand flax (Given & Harris 1994) Maori names: Paoa, Parakoretawa, Kauhangaroa ~ 100+ names Botanical names: Phormium tenax, P. cookianum + 2 varieties English name: Flax Commercial cultivars: SS20, SS21 etc. Horticultural varieties: ‘Tricolor’, ‘Smiling Morn’, ‘Goliath’, ‘Bronze Baby’ etc. One would not be surprised that people might use these systems interchangeably depending on context and that knowledge of some would only be held by specialists. Mabey (1996) also quotes many variants of local names and uses for the flora of the UK. We should therefore not be too taken aback to discover that other cultures use parallel naming systems and names in an apparently inconsistent manner.

Recognition and recall of the interviewees is also a constraint on the reliability of the proffered information. Wober (1966) undertook an interesting perceptual study of the recognition and naming of animal shapes hidden (upside down, out of scale etc. as in a childs’ puzzle picture) in a drawing with Nigerian factory workers. Although this is an extreme situation the results are salutary. Of the 173 men questioned only 60 % spotted the representation of a fowl which is a very common visual image in Nigeria. Furthermore only 53 % of the men who saw the shape gave it an appropriate name while the others labelled it as bird, parrot, polly, eagle, vulture, hawk, pigeon, water-bush-bird, tick bird, head of ostrich, seagull or dove – at least these are all birds. Alternative names for a monkey were given as human being, lion, animal, hyena and elephant. Similar problems may account for some of the discrepancies in naming of plant specimens which, if presented for naming as a voucher outside the forest, will likewise be viewed out of context.

Notwithstanding the possible complexities, an appreciation of the way in which folk classification is structured should assist in the discrimination of local names in the context of NTFP studies. It has also been suggested that it may be possible to identify the most culturally significant plants by the existence of opaque or folk specific/varietal names (Cotton 1996) though it appears that this has not as yet been attempted.

Sampling schemes for determining consistent local names In order to determine folk names for useful species, ethnobotanists have given some thought to methods for sampling and collecting indigenous knowledge of plant names. There are two sampling schemes that are commonly used; using key informants carefully chosen from the community and questioning a

173 sample of the general populace usually stratified according to age, gender or occupation. Key informants are usually older members of the community with particular knowledge and experience of resource use such as herbalists, midwives, hunters or craftsmen. Caniago & Siebert (1998) (see above) demonstrated that such people are the custodians of much knowledge and that other sectors of the community may be totally ignorant of many species, names and uses. However, it is increasingly accepted that questioning a number of informants is required to obtain the entire range of plants included in a folk generic.

The number of people that need to be included in the sample depends on the size of the domain or area of interest. Martin (1994) suggests that for medium sized domains (~100 categories = folk generics), the initial sample should be 10-30 people with new informants being added until no new names are given. This is analogous to a species-area curve and has also been suggested in connection with the collection of uses for a particular species and termed a multiple-use curve (Balick 1994 reported by Cotton 1996). The problem of too many names and uses can be reduced by asking larger numbers of people to list a limited number of categories. Martin (1994), for example, reports asking 150 adults to name 25 species which yielded a list of 300 folk names. An alternative approach is to stratify according to identified groupings of people possessing unique knowledge. Strata can be defined on the basis of user groups (farmers, midwives, healers, hunters etc), gender and age (old women, young men, children etc), social standing (elite, non-elite groups), craftwork associations (basket weavers, leaf plate makers, palm wine distillers, beekeepers etc). Smaller samples of people can then be interviewed from each grouping. See Phillips & Gentry (1993a & b) for an example of a study that used 29 informants stratified according to age, gender and occupation.

Although ethnobotanical researchers are increasingly using replicated informants, quantitative analysis and hypothesis testing (Phillips 1996), methodology for analysing local names is relatively undeveloped. Most quantitative ethnobotanical analyses have focused on the determination of use values, for comparison between scientific taxa (Prance et al.1987), between ethnic groups and forest types (Prance et al.1987), vegetation disturbance and change (Salick et al.1995) or to determine the names and uses of plants in a specific locality (Edwards 1991) or peoples (Salick 1991). The development of methodology for preparing and analysing use values is perhaps not directly relevant to NTFP inventory but is nevertheless of interest as a means of ranking NTFPs in terms of cultural importance. However, it seems that the determination of consistent and widely known names for NTFP species has received little attention, and there is no established methodology for undertaking such an analysis. A rare study that considered consistency of names is that of Manandhar (1995) who interviewed 110 tribal people and 20 herbalists from 15 villages concerning the medicinal usage and names of voucher specimens of plants. By way of verification he only accepted a name and use if it had been identified by a minimum of five separate informants. Although this is not really a quantitative analysis it does at least allow some judgement to be made of the consistency of a name and use and thereby enhance the credibility of the list.

Neglecting triangulation or replication altogether will give very unreliable results for local names as was discovered by Bowes-Lyon (pers comm.) in Ghana. He was collecting local names for trees and asked a second informant to point out what he understood by the transcribed name. It turned out that what had been recorded as the name of a particular tree translated as ‘the tree behind my brothers’ house’. This demonstrates that great care has to be taken in the collection of names and that some linguistic skills are a distinct advantage.

174