ASSESSING THE NECESSARY WIDTH OF BUFFER ZONES: AN ECOLOGICAL STUDY IN RUTENG STRICT NATURE RESERVE, FLORES, INDONESIA
by
Yance de Fretes
Drs., Cenderawasih University, 1985 MES., Yale University, 1991
I A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR IN PHILOSOPHY
IN
THE FACULTY OF GRADUATE STUDIES (Department Forest Resources Management)
We accept this thesis as conforming to the required standard v
THE UNIVERSITY OF BRITISH COLUMBIA
July 1996
©Yance de Fretes, 1996 In presenting this thesis in partial fulfilment of the requirements for an advanced degree at the University of British Columbia, I agree that the Library shall make it freely available for reference and study. I further agree that permission for extensive copying of this thesis for scholarly purposes may be granted by the head of my department or by his or her representatives. It is understood that copying or publication of this thesis for financial gain shall not be allowed without my written permission.
Department of ^V^^^rX
The University of British Columbia Vancouver, Canada
Date
DE-6 (2/88) ABSTRACT
The buffer zone has become an important component in all
reserve management plans or conservation.initiatives, particularly in tropical regions. Buffer zones have been proposed as both an additional protection to existing reserves
and a means to provide opportunities for people living
adjacent to the reserves to maintain their livelihood.
One fundamental problem of the buffer zone approach is
that there are no methods available to determine appropriate buffer zone width for any given reserve. Many suggestions for
a standard buffer zone width have been offered, but these are
largely based on intuition. There is a serious lack of
ecological studies to support those suggestions. In areas where land is abundant and population density is low, we may make "prudent guesses" in determining buffer zone width.
However, in areas where human population pressure has led tb
increasing levels of resource consumption and an increase in
land-use conflicts, ecologically-based studies should be used
in determining buffer zone width.
Considering the accelerated rate of habitat destruction
and loss coupled with chronic reserve management problems,
long-term and detailed ecological studies to determine buffer
zone width .for each individual reserve are infeasible and
unrealistic. What is needed is a method that can be used to
gather biophysical data for determining necessary buffer zone width. Such a method should be simple, inexpensive, and easily-
taught to and used by park planners and communities around the
reserves; yet, it should also be comprehensive enough to
provide reliable information.
The method proposed in this thesis is based on analysis
of species richness, species diversity, stem density and
species compositions. The major concept is that areas around
the reserve showing similar species richness, species
diversity, stem density and species composition to the core
habitats of the reserve, should be legalized as buffer zone.
The proposed method must be used in conjunction with
considerations about the socio-economic and cultural
conditions of the people living around the reserve.
The potential of the proposed method is demonstrated by
an application focusing on plants in the area around the
Ruteng Strict Nature Reserve on Flores Island, Indonesia. TABLE OF CONTENT
Abstract ii Table of content iv List tables and figures vi Acknowledgement viii List of abbreviations ix
CHAPTER 1: INTRODUCTION 1
CHAPTER 2: PROTECTED AREAS 6 2.1. Protected Areas and Associated Management Problems 6 2.2. Protected Area Systems in Indonesia 11 2.3. Problems in Protected Area Management in Indonesia 19 2.4. New Approaches to Protected Area Management 21
CHAPTER 3: BUFFER ZONE DEVELOPMENT 25 3.1. The Buffer Zone Concept 25 3.2. The Buffer Zone: Progress and Gaps 28 3.3. Buffer Width: Other's Suggestions 29 3.4 Need for A New Approach to Determine Buffer Zone Width 31 3.5. Criteria for An Effective Buffer Zone Width 33 3.5.1. Biophysical criteria 33 3.5.2. Socio-economic criteria 39
CHAPTER 4: STUDY AREA 49 4.1. Ruteng, Flores Island 49 4.2. Protected Areas on Flores 60 4.2.1. Proposed Ruteng Strict Nature Reserve 62 4.2.2. Threats to the reserve 66 4.3. Social and Economic Conditions 68 4.3.1. Socio-economic characteristics 68 4.3.2. Wood contribution to the household economy 69 4.3.3. Alternatives to selling wood for income 72 4.4. Governance 75 4.4.1. Traditional systems of governance 75 4.4.2. The effectiveness of traditional systems of 77 governance
CHAPTER 5: PROPOSED METHOD AND ITS APPLICATION 79 5.1. Overview of the Method 79 5.2. Sampling Design 83 5.2.1. Study sites 84 5.2.2. Biophysical data 87 5.3. Data Analysis 87 5.4. Results 89 5.4.1. Species richness 93 5.4.2. Species diversity 97 5.4.3. Stem density 99 5.4.4. Species composition between transects 102
iv 5.5. Conclusion 103 5.5.1. Ecological determination 103 5.5.2. Buffer zone determination for the RSNR 105
CHAPTER 6: DISCUSSION: THE METHOD'S POTENTIAL 109 6.1. Introduction 109 6.2. Assessing the Ruteng Application 109 6.3. Recommendation: Refining the Method 112 6.4. General Application 113
6.5. Conclusion 115
Bibliography 116
Appendix 129
v LIST OF TABLES AND FIGURES
Tables
Table 2. 1: Indonesian Forest Classification 16 Table 2. 2: Current Gazetted Protected Areas 18 Table 2. 3: Threatened of Selected Taxa in Indonesia 21 Table 3. 1: Suggested buffer zone widths 30 Table 4. 1: Population of Manggarai District 1961 to 1990 52 Table 4. 2: Population and density by sub-district 1991 53 Table 4. 3: GRDP (in Rupiah) for the East Nusa Tenggara 55 Province 1990-1992 without gas and oil
Table 4. 4: Land Use in the Manggarai District 60 Table 4. 5: Protected areas in the Flores 62 Table 5. 1: Arithmetic mean for species richness, 90 Shannon Diversity Index, and stem density
Table 5. 2: Summary of ANOVA results using sites as true 94 replicates to compare species richness, species diversity and stem density between the transects
Table 5. 3: Summary of ANOVA results using sample plots as 96 pseudoreplicates to compare species richness between the transects at each site
Table 5. 4: Summary of ANOVA results using sample plots a 99 pseudoreplicates to.compare species diversity between the transects at each site
Table 5. 5: Summary of ANOVA results using sample plots as 10 pseudoreplicates to stem density between the transects at each site
Table 5. 6: Morisita's similarity index for species io: composition between the transects on each sites
vi Figures
Figure 3. 1: Relation between plant diversity and . 37 animal diversity
Figure 4. 1: Nusa Tenggara, Timur Province 50 Figure 4". 2: Mean rainfall in Ruteng 51 Figure 4. 3: Forest types on Nusa Tenggara and 64 Proposed Ruteng Strict Nature Reserve
Figure 5. 1: Study Sites 85 Figure 5. 2: Sample Design 86 Figure 5. 3: Species Area Curve 91 Figure •5. 4: Mean Species Richness 95 Figure 5. 5: Mean Species Diversity 98 Figure 5. Mean Stem Densities 101
vii ACKNOWLEDGEMENT
During my study, I received generous help and invaluable guidance from many individuals and institutions. I cannot name them all here, but I sincerely thank all of them. Many thanks to the EMDI Phase 3 Project staff in Lombok,. Jakarta and Halifax, particularly Pauline Lawrence and Valerie Sexton; the Kantor KLH; and the WWF Indonesia Programme in Jakarta, especially Evie Adipati. Thanks are also due to Dr. E. Widjaya; Dr. J. P. Mogea and staff from Lembaga Biologi Nasional, Bogor for helping with plant identification. In Ruteng, I was helped by Father J. A. J. Verheijen and Pak Simom Jemaat. Without the help of Pak Irinus Ros and Fabi Magus, my field assistants, the field work would have been almost unmanageable. Pak Stanis and Ansi Tatul helped.with social and cultural information. I thank them all.
In addition, I would like to thank Dr. M. M. J. van Balgooy of the Rijksherbarium, Leiden, Netherlands for helping with plant identification; Dr. B. Beehler of the Smithsonian Institute; Dr. J. Holloway; and Ibu Moria Moeliono for sharing her reports on the forestry issues in Manggarai. Many friends in Canada and the United States gave generous support and help during my study and in the preparation of this thesis. Thanks are due to Karen Peachey for her editorial help and Kathy Sestrich for.comments on the earlier drafts.
This study would not be possible without generous financial support from EMDI/CIDA. I would to take this opportunity to thank Dr. Kathryn A. Monk, my field, advisor for her tremendous help and care, both during my field work and in preparation of this thesis. I am particularly indebted to my research supervisor Dr. Alan Chambers, and committee members Peter Broothroyd, Dr. Geoffrey Hainsworth, and Dr. Tom Sullivan at University of British Columbia, for their help, patience and understanding.
viii LIST OF ABBREVIATIONS
ADB Asian Development Bank BAPPENAS National Development Planning Bureau (Badan Perencanaan Pembangunan Nasional) BPS Central Bureau of Statistic (Biro Pusat Statistik) CIDA Canadian International Development Agency dbh diameter at breast high (1.33 m) EMDI Environmental Management Development in Indonesia FAO Food and Agriculture Organization GNP Gross National Products GRDP Gross Regional Domestic Products ha hectare IPAS Integrated Protected Areas Systems IUCN International Union for Conservation of Nature and Nature Resources KLH State Ministry of Population and Environment (as April 1993, renamed State Ministry for Environment) km kilo meter (= 1.8 miles) KSDA Nature Conservation Office (Konservasi Sumberdaya Alam) MF Ministry of Forestry NTT East Nusa Tenggara (Nusa Tenggara Timur) PHPA Forest Protection and Nature Conservation Office (Perlindungan Hutan dan Pelestarian Alam) RePPProT Regional Physical Planning Programme for Transmigration Rp Rupiah (the Indonesian currency) RSNR Ruteng Strict Nature Reserve UNESCO United Nations Educational, Scientific and Cultural Organization UNEP United Nations Environmental Programme UU Decree (Undang-undang) WB World Bank WCMC World Conservation Monitoring Centre WRI World Resources Institute WWF World Wide Fund for Nature (World Wildlife Fund)
ix CHAPTER 1: INTRODUCTION
During the latter half of the twentieth century, a global constituency demanding the creation of Nature Reserves or Protected
Areas has grown into an almost irresistible political force. The result has been the establishment of protected areas' by national and regional governments with the express purpose to preserve and conserve some of the planet's remaining ecosystems that are relatively unchanged by human activity. Despite a steady increase in the establishment of protected areas world wide, however, problems of habitat loss and degradation continue, even within the protected areas themselves.
The ultimate cause of this degradation and loss is the combined global increase in human population and the increase in resource use per capita. The latter is amplified by economic growth, particularly in Asian countries where political stability and infusions of capital encourage continued infrastructure and industrial development. On the African continent, where political instability has slowed the rate of economic development, population growth alone has made the creation of protected areas difficult.
There, degradation and loss of natural habitats occurs even in those areas that have been designated under protected area systems, as a growing population tries to both feed itself and participate in the cash economy.
1 Two primary sources or causes of degradation can be identified. The first is associated with industrial development, the second with its alternative, the subsistence economy. Of these, the latter is the most ubiquitous and difficult for national and local governments to deal with. Faced with the task of reducing or eliminating the exploitation of "protected areas" by local residents, policies designed to "keep them out" were introduced. Generally, these policies have proven to be ineffective.
Subsequently, a number of "new ideas" were proposed, particularly in the context of protected areas management in tropical countries. The central'premise of these new policies is that people must be allowed to participate in the planning and the management of the' reserve. Furthermore, this participation must provide tangible benefits to people, especially to those living adjacent to the protected areas. ..
Among the. new ideas, the use of buffer zones is well known.
The buffer zone concept which allows certain human activities around protected areas was advocated by UNESCO (United Nations
Educational, Scientific and Cultural Organization) two decades ago
(Shafer 1990). To date, however, practical methods have not been developed- to help planners and local communities determine necessary buffer zone widths under varying ecological conditions,
2 nor have specific guidelines been offered to guide the design of management regimes that may be successfully implemented in a wide variety of socio-economic circumstances, following the determination of buffer zone width (cf. MacKinnon et al. 1990).
The central purpose of this dissertation is to develop and illustrate the use of a method for collecting biophysical data, which can be used to determine appropriate buffer zone widths for any given tropical reserve. Such a determination must also take into consideration the social and economic conditions of the people around the protected areas.
The method is based on the analysis of tree species richness, species diversity, stem density and species composition. The underlying principal is that an area in the periphery of a reserve, despite human activity, still shows similarity in terms of species richness, species diversity, stem density, and species composition to an area near the core of the protected area. This peripheral . area should be legalized as a buffer zone. This method was developed in the context of the Ruteng Strict Nature Reserve
(RSNR), Flores Islands, Indonesia.
Throughout this thesis, the terms "protected area",
"conservation area" and "reserve" are used interchangeably, and loosely refer to an area or areas designated for preservation
3 and/or conservation purposes. While "preservation" is a management
approach that strongly leans to completely ban any human use of
resources within the protected area, "conservation" is an approach
that would allow for sustainable human use of resources within the protected area. Both approaches can be applied simultaneously (for
example, in management of a National Park) or separately (for
example, in management of a Strict Nature Reserve). However, when a
specific protected area is mentioned or discussed, the proper or
legal category (Chapter 2) will be used, especially for protected
areas in Indonesia. It must be stressed that there is a wide gap between the legal status (henceforth, management approach) given to
a protected area and the actual management reality on the ground.
For example, Ruteng protected area is under the Strict Nature
Reserve category, where no human activity is allowed, but local
people still extract fuel wood on daily basis from within the
reserve.
I have not conducted an in-depth do social and economic
analysis in this thesis, but wish to continually caution others
that in actual application of this method, social and economic
conditions of the people around the protected area must be
analysed. The description of social and economic conditions of
people around RSNR, presented in this thesis, was intended to
illustrate what kind of analysis could be done or should be
4 considered. Such an analysis must be included with the biophysical data in determination of the appropriate buffer zone width.
This thesis is presented in six chapters. Chapter 1 briefly
describes the objectives of the thesis. Chapter 2 gives background
information on protected areas, with a focus on Indonesia,
especially to outline some of the threats and problems in the management of protected areas. Chapter 3 discusses buffer zone
development, especially its progress and information needs, and
establishes biophysical criteria for the determination of buffer
zone widths. This chapter also briefly discusses and offers some
ideas on how to develop meaningful socio-economic criteria for
determining buffer zone width. Chapter 4 provides a description of
social and economic conditions of the people around Ruteng, the
Ruteng Strict Nature Reserve, and its management problems. Chapter
5 gives an overview of the method, data collection and analyses,
and offers some suggestions for buffer zone widths for RSNR.
Lastly, Chapter 6 discusses the application of the method in and
around RSNR, and provides some recommendations for refinement of
the method in its future applications.
5 CHAPTER 2: PROTECTED AREAS
2.1. Protected Areas and Associated Management Problems
The increasing human population and its consequent
increasing demand for resources has led to the reduction of
natural habitat and the decline of biological diversity world wide. Consequently, as belief in the inexhaustibility of
resources began to falter, the idea to "set aside" areas of
unspoiled land or wilderness emerged.
The modern conservation movement started shortly after it
was realized that the "go West young man" philosophy of early
European settlers, the very philosophy that was used to
rationalize conquering larger tracts of forestland and grassland
in western North America, had drastically diminished forests,
degraded grassland and increased the extent of waste lands.
American naturalists and scientists realized that their
civilization was being jeopardized by uncontrolled resource
exploitation. This inspired them to adopt "set aside" ideas for
resource management (Miller 1988).
Yellowstone National Park (established in 1872) is widely
claimed to be the first national park in the world1. However,
1 Although some American historians point out that Hot Spring Reservation in Arkansas was the first reserve, since it was established in 1832 (Allin 1990). 6 land preservation dates back many centuries. . In Europe, for
instance, in 1084 King William I of England made an inventory of
land and resources in. his kingdom to provide a basis for rational plans for resource management and development. The concept of protected areas can be traced back to the 4th century B.C. in
India, and to.about the 3rd century B.C. in Sri Lanka (MacKinnon
et al. 1990; Singh and Rodgers 1990; Collins et al. 1991). •
Indeed, many traditions and cultures around the world have practised resource conservation for centuries (McNeely and Pitt
1985; Usher 1987; Allin 1990; Collins et al. 1990; Poffenberger
1990; Western et al. 1994). Early preservation efforts through
the establishment of forest reserves and wildlife sanctuaries
were closely linked to the beliefs and ritual practices of the
people. Often, reserves were established for the exclusive
enjoyment of kings and colonial rulers, unlike modern
conservation efforts such as the establishment of Yellowstone
National Park.
Increased public understanding of the importance of habitat
conservation and preservation of biological diversity has led
governments to designate more land for protected areas. Between
1910 and 1990, a steep rise in the designation of both
terrestrial and marine ecosystems as protected areas, brought the
total number of reserves to approximately 8,163 and the total
7 area protected to approximately 170 million has (WRI et al.
1992). Many of these reserves have not always met the conservation and preservation objectives for which they were . established. This is not surprising, considering that both the human population and per capita resource use continue to increase.
In recent years, conservation efforts have focused on solving the problem of rapid .destruction of tropical rainforests.
These ecosystems account for only 7% of the total land surface, yet harbour more than 50% of known species (Myers 1988). Due to their high rate of deforestation, the number of species they contain, and the inherent economic and; medical"values they promise, many conservation efforts have been directed.at saving tropical rainforests. These efforts have expanded beyond the designation of new reserves tb include management of existing protected areas which have been degraded by hunting, poaching, and logging, even when these activities are sanctioned and or licensed by government authorities.
The problem of management of existing protected areas is hot peculiar to tropical regions or less developed countries. Many parks and protected areas in the USA, for instance, are in as great danger as the reserves in tropical regions. As the country
8 and its citizens have prospered, the demand for resource use has increased. In 1972 population and economic pressures were identified as the main threats to parks in the USA (Fisher 1972).
Only two decades later, the list of threats has grown to include air pollution, adjacent physical development (roads, dams, and housing), agricultural development, financial constraints, overcrowding, and the invasion of exotic species (Alder, and Glick
1994; Babbitt 1994; Mitchell 1994).
Threats to protected areas and parks in the USA and Canada are similar. For example, infrastructure development has engulfed and isolated many reserves and parks in Canada. Yet little is known about the long-term effects of such isolation on animals in the parks (Eidsvik and Henwood 1990). With the existence of roads into reserves, poaching is an increasing threat to large mammals inside the parks (Dearden 1991). As in the USA, the tourist industry has become a major problem for many parks in Canada. Although the causes of these problems are apparent, many of them remain unsolved. Other problems, such as agricultural and housing development and logging operations near the parks fall beyond the park's jurisdiction. Consequently, solutions are even more difficult to identify and enforce.
9 Like the problems in parks and reserves in the USA and
Canada, Africa also has very specific problems (Lusigi 1982;
Burnett 1990; Kayanja 1990). These include political instability and a lack of qualified staff, both of which make it difficult to enforce laws or to design long-term plans for protected area management. Often during political conflicts, animals within reserves become the principal food resource of warring parties
(Purvis 1995). For local people, land values and ownership are an important part of their material and cultural existence. Park establishment alienates them from both land and animals.
Furthermore, local population and economic growth, coupled with park establishment, accelerates and exacerbates land scarcity.
Hunting prohibitions within protected areas are an alien concept to many Africans, as is the allocation of land for specific purposes such as parks or wildlife sanctuaries. Although tourism is becoming an important income resource for several African countries, only a small proportion of the benefits accrue to local residents. While many people in the West enjoy the out• door recreation that parks facilitate, recreation is not part of the African culture, thus, the existence of parks does not necessarily provide social benefits for them.
Many African countries and protected areas were established across seasonal migration routes of various species, thus
10 preventing animals from migrating during these seasons. This
condition forces animals to reside and graze at particular areas
over the year, which in turn, leads to over-grazing and soil
erosion. Soil erosion and over-grazing will prevent regrowth of
new grasses. In the long-run, these problems create shortage of
grasses and force animals to feed on agricultural land. In
addition, because different countries adopt different
conservation measures, animals may well be protected in one
country but not in the others. .Thus, if animals enter a
neighbouring country, they may be hunted or killed. In the
absence of effective cooperation in the development of protected
area systems between neighbouring countries, wildlife
conservation is threatened. Such cooperation must be established
with people who live around the park or on migration routes. For
instance, neighbouring countries may implement a similar
protection status for animals, or establish sufficient migration
corridors, that will ensure the animal's migration to and from
habitats between countries.
2.2. Protected Area Systems in Indonesia
Indonesia is one of the largest island nations in the world,
with more than 13 thousand islands that lie. between two
continents and spread across two biogeographic realms, the
Australian and the Oriental. Due to its location and ecology,
11 Indonesia is identified by Myers (1988a) as a megadiversity country. With the total land area of 1,926 million km2,
Indonesia harbours about 10% of the world's plant species; 12% of mammal species; 16% of reptile and amphibian species: and 17% of the bird species (MF/FAO 1991). Despite the loss of tropical rainforest world wide, Indonesia still has the second largest tract of tropical rainforest after Brazil (Jacobs 1988; Whitmore
1990). Sayer and Whitmore (1991) estimate that about 11,880,000 km2 of rainforest remains in Indonesia, covering approximately
56% of the land area. However, the rate of deforestation is also remarkably high, amounting to 100,000 - 120,000 km2 annually
(Sayer and Whitmore 1991).
Conservation efforts have long existed in Indonesia; formal initiatives were introduced and enforced by the colonial administration. The first reserve was established in 1889 on
Mount Gede Pangrango and the first protection ordinance was issued in 1905 by the Dutch administration (Cribb 1988).
However, as in other places, conservation and protection measures are not a new concept for Indonesians. For centuries, traditional communities have employed quite sophisticated approaches to resource utilization (Polunin 1985; Mitchell et al.
1990; Zerner 1994).
12 Shortly after the U.N. ^Conference on the Human Environment'
in Stockholm in 1972, the Indonesian government engaged in a number of conservation and environmental activities. It began with the establishment of a Ministry of State Development
Supervision and the Environment in 1978, which later became the
Ministry of State for Population and the Environment (KLH) in
1983. This ministry changed again to become the Ministry of
Environment (LH) in April 1993. With both financial and
technical support from abroad, the government has issued a number
of acts and regulations to deal with environmental and
conservation issues in Indonesia. For instance, in 1982, the
government issued decree No. 4, AThe Basic Provision for the
Management of the Living Environment'. In the same period, the
government also produced a series of xNational Conservation
Plans' for the country (MacKinnon 1982).
KLH launched a number of projects designed to improve
environmental management capacity through institutional
strengthening and human resource development. For instance, with
financial support from CIDA (Canadian International Development
Agency) and Dalhousie University, KLH embarked on EMDI
(Environmental Management Development in Indonesia) projects,
starting in 1984. Through these EMDI projects a number of
activities have been carried out, both in Indonesia and Canada,
13' including the establishment of environmental impact assessment methods and environmental standards for Indonesia and the publication of a series of ecology text books.
The first comprehensive protected area system was- designed
in the early 1980s. The Directorate General of Forestry (then, within the Ministry of Agriculture), with technical and financial
assistance from FAO (Food and Agriculture Organization), WWF
(World Wildlife Fund) and IUCN (International Union for
Conservation of Nature and Nature Resources), formulated a national conservation plan for Indonesia. The plan, presented in
eight volumes and covering all the biogeographic provinces in
Indonesia, reviewed the status of natural conservation and proposed a system of protected areas (MacKinnon 1982). The plans provide a brief description of the proposed protected areas,
reasons for their protection, recommendations of protection
status, scoring (includes genetic value,' socio-economic
justification, management viability and priority), and threats.
These volumes provide very basic information that needs to be
developed into a more detailed management plan for each .'protected
area (MaKinnon 1982).
Unfortunately, however, many reserves that have been
proposed by the plans remain ungazetted. Some gazetted reserves •
14 exist with no or very minimal management. Nevertheless, the
Government of Indonesia has made better progress in the
establishment of protected areas than have other countries in the
Asia-Pacific region (Braatz 1992), especially if we consider
Indonesia's population size, challenging economic situations,
biological diversity, and the level of endemism. Other countries
in the Asia-Pacific region, which are economically more
prosperous (in term of GNP per capita) and have smaller
populations than Indonesia, only designate a small proportion of
their land as protected areas.
In current forestry policy, forest areas are classified into
the five forest types defined below and further detailed in Table
2.1 (adapted from MF/FAO 1991):
• Conservation Forest: for nature and genetic conservation in which no exploitation is permitted;
• Protection Forest: for water and soil conservation in which no forest exploitation is permitted (note: there are examples, however, where mining exploitation take place in such protection forests);
• Limited Production Forest: for erosion prevention where timber production by selective cutting is permitted;
• Permanent Production Forest: for commercial timber production, where both clear and selective cutting are permitted; and
• Conversion Forest: allocated for agriculture or other uses, clear cutting is permitted.
15 Table 2.1: Indonesian Forest Classification.
Forest types Total Area Percentage (km2) (of forest land)
Permanent forest Protection forest 303,160 16 Conservation forest2 175,213 9 Production forests Permanent 338,660 18 Limited 305,250 16
Other forest land Conversion forest 305,370 16 Conversed forest 491,010 26
Source: Collins et al. (1991).
Indonesia applies two major conservation approaches: in situ and ex situ. The in situ approach designates marine and terrestrial ecosystems to be protected under the current protected area management regimes, while the ex situ approach encourages conservation of flora and fauna species outside their natural habitats though the establishment of botanical gardens, zoos and gene banks.
Currently, protected areas have been managed through three main reserve categories (adapted from MF/FAO 1991):
• Nature Reserve: small to large-sized areas (5,000 - 130,000 ha), usually undisturbed, having high conservation values (species diversity and endemism, rareness, ecosystem representative, and naturalness). Designated to "preserve" and maintain ecological processes within the reserve (IUCN Category I3) ;
2 PHPA (1994) gives higher figure for the conservation forest. 3 See McNeely and Miller (1984) for the IUCN Reserve Category. IUCN (1994) provides the newest IUCN Reserve category. 16 • Wildlife Sanctuary: medium-sized areas (20,000 - 160,000 ha) with rather specific conservation goals, i.e.., to protect certain taxa/animal groups (IUCN Category IV); and
• National Park: medium to large-sized undisturbed areas (50,000 - 130,000 ha), with outstanding natural values, high potential for recreation, and easy access to visitors. A national park will be managed through varied zoning systems(IUCN Category II).
Another classification of forests that is often perceived as
a "protected area" system is for recreation and the protection of water catchment areas. These forest management designations are:
• Hunting Park: medium to large-sized natural or semi-natural areas managed for recreational purposes,, especially for hunting;
• Protection Forest: medium to large-sized areas, covering either natural or man-made forests. The main objectives are: to protect water-catchment areas and to prevent land slides and soil erosion;
• Recreation Forest: small-sized natural areas of high recreational value. Primarily for recreational purposes; and,
• Grand Forest Park: medium to large-sized areas "similar" to a botanical garden, but management is focused more toward recreational uses.
As of June 1994, Indonesia had designated about 16 million
has of terrestrial ecosystems as protected areas or 8.3% of the
total land surface (Table 2.2). Another 2.7 million has of
terrestrial ecosystems will be added to the existing protected
areas by 1998/99 (MF/FAO 1991; BAPPENAS 1993). Also, about 2.2
17 million has of marine ecosystems have been designated as marine
reserves (PHPA 1994), which will be expanded to 20 million has by
the year 2000 (BAPPENAS 1993).
Table 2.2: Current Gazetted Protected Areas4 (June 1994).
Protection regimes Numbers Total Area (ha)
Terrestrial Ecosystem Strict Nature Reserve 164 6,111,272 Wildlife Sanctuary 47 3,635,121 National Park 26 5,609,437 Recreation Forest 76 272,4 57 Grand Forest Park 7 213,307 Hunting Park 14 235,198
Marine Ecosystem Strict Nature Reserve 8 253,780 Wildlife Sanctuary 4 66,120 National Park 5 2,292,955 Recreation Reserve 12 151,569 TOTAL 363 18,841,218
Source: PHPA (1994).
For ex situ conservation, the Government and.some private
institutions have set up several botanical gardens, arboreta and
zoosHowever, only a few of these facilities were established
to meet conservation purposes, such as the Bogor Botanical.
4 It should be noted that several government institutions give slightly different figures for protected areas, as well as for their size, protection regime, and status for each protected area. 18 Garden. Other facilities were created to meet certain demands, mainly for recreational purposes, and to lesser degrees for
agriculture and for medical research and development. Various
attempts have been made to establish farms and propagation
facilities for certain commercially important plant and animal
species,, but their contribution to species conservation remains
unclear. The Government also has passed a number of decrees to protect plants and animals. Currently, there are about 30
reptiles, 379 birds and 95 mammals which are protected by various
acts (PHPA 1994).
2.3. Problems in Protected Area Management in Indonesia
Economic and health-care improvement, coupled with political
stability, has led to steady growth in Indonesia's population.
Consequently, both the Government and the people make more
demands on a wide range of resources. The fact that Indonesia
still depends critically' on the extraction of. natural resources
to support its economic and physical development indicates that
such demands will directly affect natural habitats and their
conservation. Despite the fact that the Government has set aside
about 9% of the total land as conservation areas (MF/FAO 1991),
habitat degradation and loss continue to accelerate even within
protected areas, due to lack of actual management and.law.
enforcement. In Indonesia, common causes of habitat loss and degradation are conversion to agricultural fields (plantations), transmigration, irrigation projects, logging, shifting cultivation, and forest-fires. Most of these activities are attributable to economic pressures to meet the needs of a growing population.
In places where proposed or existing protected areas are present, majority of the people still depend on the daily use of the natural resources. In numerous cases, people who live adjacent to protected areas still use the resources within the reserves to meet their daily subsistence needs. Many protected areas have been planned without the knowledge of local residents, or insufficient effort has been made to inform them during the planning, implementation, or management phases. Boundaries of reserves often cut through people's traditional gardens or hunting grounds. This situation, coupled with inadequate government funding for conservation, lack of skilled conservation staff, complicated land tenure systems, and complex land uses, has created a number of difficult problems.
The major problems that must be addressed include illegal logging, hunting and wildlife trade, resettlement, and cash crop plantations inside protected areas (MacKinnon et al. 1982;
20 Sumardja et al. 1982; Petocz 1991; MF/FAO 1991). Many existing
and proposed terrestrial and marine reserves remain without proper boundary demarcation, exist without a detailed management
plan, or are under-staffed. This has led to the degradation of
about 22% of the natural habitats designated as the conservation
forests (Ramli and Ahmad 1993). More specifically, these
conditions threaten the nation's rich biota (Table 2.3) and will
result in a dramatic reduction in ecological diversity and
balance.
Table 2.3: Threatened Selected Taxa in Indonesia5.
Taxa Total Threatened
Reptile 511 21 Bird 1, 534 122 Mammal 515 . 77
Sources: MF/FAO (1991), KLH (1992), and Groqmbridge (1993).
2.4. New Approaches To Protected Area Management
Faced with the above obstacles and problems in the
management of protected areas, many new approaches have been
proposed by conservationists. To some extent, these approaches
have been implemented in tropical regions. These approaches
include social forestry, integrated protected area systems
(IPAS), extractive reserves, and the use of buffer zones
5 WGMC (1994) gives detail reference about species survivorship status. 21 (Oldfield 1988; Fearnside 1989; Sayer 1991; MacKinnon et al.
1990; Wells et al. 1992; Salafsky et al. 1993).
The common philosophy behind most of these new approaches involves 1) the participation of the local residents in the planning and management of protected areas; 2) the notion that park and protected area development must be linked with the economic and social development of local people; 3) the idea that economic benefits generated from park management, such as tourism, must go to the people who live in the vicinity; and 4) the rational use of resources within protected areas. These approaches are in many ways contrary to the old conservation philosophy that leans toward complete habitat preservation and protection, excluding people, especially those living adjacent to reserves. c
Thematic criteria first outlined by the IUCN (1980) clearly assert that people must be involved in the planning subsequent the implementation of protected area management. This notion is supported by the Bali Declaration (McNeely and Miller 1984, p.xi) which seeks to: "recognize the economic, cultural, and political contexts of protected areas; increase local support for protected areas through such measures as... revenue sharing, participation
22 in decisions, complementary development schemes adjacent to the protected area..."
Both the World Conservation Strategy and the Bali
Declaration are supported by the Global Biodiversity Strategy.
Because millions of rural people in many biologically-rich countries in tropical regions are economically poor, the declaration of a protected area may mean that these people must lose their access to natural resources either partially or completely. Thus, the Global Biodiversity Strategy calls for
"creating conditions and incentives for effective conservation by local communities".
In Indonesia, the need for participation of the local people in the conservation of natural habitat is clearly established in the Conservation Act (Chap. IX art. 37). This Act .specifically grants people the right to participate in conservation. In addition, Indonesia's Sixth Five Year Development Plan (1994/95-
1998/99) argues in favour of the need for such participation in the whole spectrum of forest management, ranging from forest utilization, protection and conservation, to restoration (Anon
1994). This acknowledgement is long overdue. Traditionally, many rural communities have been involved in conservation practices and resource management (Polunin 1985; Mitchell et al.
23 1990; Zerner 1994), but this right has often been eroded by inappropriate management practices. Letting people participate in protected area management also provides them with employment alternatives to replace hunting or agricultural activities which may be limited following the establishment of a protected area.
These approaches are now well ingrained in many conservation projects world wide and are perceived as promising solutions to the problems of protected areas management. In turn, these new approaches are very appealing to many donor agencies (ADB 1992;
Wells et al. 1992; Anon 1995). Despite their popularity, however, there is very little, experience or documentation to either support or challenge the approaches. Therefore, it is necessary to examine these approaches further.
This study is focused on one of the approaches: the use of buffer zones around protected areas. More specifically, the major objective of this study is to develop, apply and evaluate a method which park managers, together with local residents, can use to obtain the necessary biophysical data to determine appropriate buffer zone width for any given reserve.
24 CHAPTER 3: BUFFER ZONE DEVELOPMENT
3.1. The Buffer Zone Concept
Buffer zones have gained much support from park planners, conservationists and governments around the world. The buffer zone concept has achieved particular prominence since 1974 when it was advocated by UNESCO through its Man and Biosphere (MAB)
Program (Shafer 1990). The concept, however, was used in reserve management as early as 1935 for U.S. National Parks (see Shafer
1990), in the 1950s around the Nsefu Game Reserve in Zambia, and in the Corbertt National Park in northern India (Sayer 1991).
Since then, buffer zones have become an important part of planning and management of protected areas, especially in tropical regions and less developed countries (Sayer 1991; Wells et al. 1992).
This noble concept, though its success or failure has rarely been tested in the field, did inspire the Indonesian government to legalize the buffer zone concept in the Ecosystems
Conservation Act (UU No.5, 1990) (Anon 1990). However, although the Act legalized the buffer zone approach in the management of protected areas, no specific guidelines are offered. In some ways, this is unfortunate for reserve management (protection) because the Act may actually "justify" and "legalize" resource exploitation in protected areas by allowing people to continue to
25 utilize resources within the buffer zones (and protected area) without any guidelines.
Buffer zones have been defined in many different ways.
MacKinnon et al. (1990) define them as "areas adjacent to protected areas, with limited land use and [that] give an
additional protection layer to the protected areas". Sayer
(1991) defines a buffer zone as "a zone, peripheral to a national park or equivalent reserve, where restrictions are placed upon
resource use or special development measures are undertaken to
enhance the conservation value of the area".
In Indonesia, two main definitions of buffer zones have been
widely used. Wind (1991), who has worked extensively in planning
and managing protected areas in the country, offers the following
definition: "[a] buffer zone area is made between the natural
areas/conservation areas and cultivated areas/settlements' to
protect the conservation area against negative influences from
outside, and also to protect cultivated areas/settlements with
their resources against negative influences originating from the
conservation area". Another definition based on the Ecosystem
Conservation Act defines the buffer zone as: "areas outside
nature reserves in the form of forest land, state lands, untitled
lands, or lands whose rights have been assigned, which are needed
26 and able to support/safeguard the integrity of the reserve"(Anon
1990).
Clearly, .the main properties of buffer zones are that they act to protect both reserves and cultivated land, they regulate resource use, and they are located outside the reserve. None of the definitions mention whether or not "a buffer can be feasibly established inside a reserve, for instance, . in cases where settlement (enclaves) occur inside the reserve.
Despite the fact that the buffer zone concept has been accepted as a tactic for protected area management world wide, and has been addressed in the.growing number of socio-economic based studies on the subject, seldom have ecologically-based studies been conducted by conservationists. A study by Salafsky
(1993) on the mammalian use of a buffer zone near Gunung Palung
National Park, West Kalimantan, indicated that a "buffer zone" failed to protect local people's crops from animals within the park. Certainly, more studies on the subject are required to determine in what ways various kinds of buffer zone' do or do not safeguard the protected areas themselves as well as gardens from animals within reserves, a claim widely made by buffer zone proponents (Oldfield 1988; Wind 1990; MacKinnon etal. 1990;
Sayer 1991). Furthermore, studies are needed to develop methods
27 or procedures for determining buffer zone widths (see for example
Dearden 1991; Prins and Wind 1993; Given 1994).
3.2. The Buffer Zone: Progress and Gaps
Many existing documents on buffer zone management offer a range of insights into the concept and report on its application in different countries. Oldfield (1988), Sayer (1991) and Wells et al. (1992) provide examples from around the world where a variety of "buffer zone" management practices occur, but there is no evaluation of the effectiveness in safeguarding protected areas. In Indonesia, buffer zones have been established around a number of reserves (Mitchell et al. 1990; WWF and Kanwil
Kehutanan 1990; Wind 1990, 1991). It is important to note that the term buffer zone has been used indiscriminately by many conservationists when they discuss reserve management.
Therefore, use of the term in government proposals does not necessarily imply the implementation of the buffer zone approach as it has been defined by MacKinnon et al. (1990), Sayer (1991), and Wind (1991).
In spite of its popularity in reserve management policy and conservation programs, the buffer zone concept still lacks practical guidelines as to how buffer zone width should.be determined, how it should be implemented, and what constitutes its success. Many existing documents pn the buffer zone, for
28 instance, fail to provide examples of the effect of the application of the buffer zone approach on their current protect area management strategy, especially to safeguard protected area.
While it may be unrealistic to ask for these results, which may require some time to become apparent, we should remember that the concept was adopted into reserve management decades ago. We must also remember that time is not on our side in habitat conservation or biodiversity preservation. Therefore, the need to be rigorous and demanding is essential. Furthermore, we.must be cautious about the potential impacts of allowable human activities in the buffer zone on the reserve and its biota, as well as the potential impact of the buffer zone on people's gardens and the resource extraction activities.
3.3. Buffer Width: A Range of Suggestions
In regard to how wide a buffer zone should be, Wind (1990) recommends that effective buffers, in the form of natural forests, should be more than 2.5 km in width, while MacKinnon et al. (1990) suggest that hunting should be banned 1 to 2 km from reserve boundaries. Craven and de Fretes (1987) propose a 1-km wide buffer between reserves and cash crop plantations in the
Arfak Mountains Nature Reserve, Irian Jaya, Indonesia. Janzen
(1983, 1986), in his study of the Santa Rosa National Park
(northwestern Costa Rica), suggests that anthropogenic successional habitats within 5 km of a park will likely influence
29 habitats in the park. Oldfield (1988) proposes a 2-km buffer for the Lake Manyara National Park in Tanzania.
Hadisepoetro (1991), Indonesia's Director of National Parks and Recreation Forests, points out that current forest policy requires that a 500-m buffer be established between a forest concession (logging) and a park boundary, or a 1 km zone if the reserve boundary has not yet been marked. In the last Buffer
Zone Symposium in Jakarta (February 1991), Wind (1991) suggests buffer zone widths ranging from 500 m to 6 km depending on adjacent land uses (Table 3.1). It is important to note that many of these suggestions are based on intuition. There is a serious lack of empirical evidence supporting these suggestions.
Intuitively, wider buffer zones would be the best strategy.
Such an approach would help filter negative impacts of human settlements around the reserves by putting additional natural or semi-natural areas into the reserve. However, wider buffer zones will require more effort to be managed, and may raise unnecessary conflicts with other land uses. A wide buffer can be declared in areas where population densities, land pressure and demands on resource utilization are low. In areas where availability of arable land for agricultural expansion is limited and demand for resource use is high efforts should be made to determine an appropriate buffer width that will meet the conservation
30 objectives of the reserve while satisfying the needs of the people living in the vicinity of the reserve.
Table 3.1: Suggested buffer zone widths.
Suggested Remarks Reference width > 5 km park within 5 km or more will Janzen 1983, 1986. be affected by antrophogenic successional habitats 1 km between reserve and cash crop Craven & de Fretes plantations 1987. 2 km buffer extension Oldfield 1988. > 2 . 5 km buffer should be in the form Wind 1990. of natural forest 1 to 2 km no hunting should be MacKinnon et al. permitted 1990. 0.5 km between logging area and Hadisepoetro 1991. reserve 1 km between logging area and Hadisepoetro 1991. unmarked reserve 0.5 to 6 km depends on the land use types Wind 1991.
3.4. Need for A New Approach to Determining Buffer Zone Width
Despite the fact that buffer zones are widely used in protected areas management, site-specific and. detailed ecological and socio-economic data are not commonly used to determine appropriate widths of buffer zones, nor are they generally used to prescribe management practices to be applied within them.
31 Considering current rates of.forest degradation and conversion, what is needed is an approach that identifies site specific data upon which to establish appropriate buffer widths.
Of particular interest to this thesis is the need for a method that can be applied quickly and inexpensively to gather the necessary biophysical data, yet one that provides reliable information. The method should also be both simple and easily taught. In addition, data gathered must be easy to analyze using either a hand-calculator or any spreadsheet .program. Such an approach would not only provide biophysical data for the determination of legalized buffer widths, but also, due to its simplicity and low cost, would provide greater opportunities for local residents to participate and to understand what are the purposes and criteria of buffer zone management.and regulation.
Given current problems in the management of protected areas, especially those related to the cost of enforcement, the prescription of buffer zones must carefully consider the social, economic and cultural circumstances of the people living in the vicinity of the protected area. It is widely recognized by many conservationists and reserve managers that the policing required to enforce a "keep them out" policy in reserve management is likely to be both expensive and ineffective. In contrast, reserve management that recognizes the needs of local residents and provides for their participation is likely to be more
32 effective and can usually be achieved at much lower operational cost (Lewis et al. 1990).
3.5. Criteria for an Effective Buffer Zone Width
3.5.1. Biophysical criteria
Studies that involve data collection in the field must deal with a number of constraints: Although empirical data are expected to meet the requirements of rigorous statistical analyses, field ecdlogists must deal with constraints of time and logistics as well as the complexity of natural ecosystems. This is particularly so in tropical regions where it is effectively impossible to measure all properties of these diverse and complex ecosystems. Whitmore (1990:32), for example, suggests that complete enumeration of just the vegetation on a one hectare plot of evergreen rainforest in Horquetas (Costa Rica) requires 10 person-years. Because many tropical species exist in very low densities, large areas must be sampled to obtain sufficient data to establish any measure of statistical confidence (Greig-Smith et al. 1967). What is required, then, is to identify a set of indicators that reflects the condition of the natural system.
Two such indicators have been suggested in the literature.
The first, the presence or absence of soil nutrients, has been used to determine whether or not ecosystems remain "intact", and whether or not habitats recover . (Harcombe 1977; Uhl and Jordan
' • 33 1983). Because nutrient cycles in tropical regions are completely dependent on vegetation (Uhl and Jordan 1983; Whitmore
1984; Jordan 1985), sampling must take place over a very long period of time to obtain sets of representative data. The second indicator suggested in the literature, biological diversity, is by far the most commonly used and widely accepted.
Biological diversity or biodiversity refers to the variety of plant and animal species that'exist within or between ecosystems, and genetic variation the variety that exists within a single species. Biodiversity is further classified as follows:
1. alpha-diversity (diversity within habitats) - often represented by a list of species present in any given habitat;
2. beta diversity (diversity between habitats or a comparison of the alpha diversity of different habitats; and
3. gamma diversity - diversity over landscapes or different geographic regions (Shmida and Wilson 1985).
Of the three, alpha diversity or species richness, which uses individual species or biomass as the measurement unit, is the easiest to measure. Further, biodiversity has two components: species richness, or simply the number of species present, and species evenness or the relative abundance of species present in the habitat. Biodiversity can be represented in three ways: diversity index, species abundance model, and a combination of species richness and abundance- (Magurran 1988).
34 Species richness or alpha diversity is the most frequently used and widely accepted (Krebs 1989).
Studies of habitat change resulting from natural and human disturbances use species richness, diversity, and composition to determine the degree of disturbance and rate of recovery of a variety of ecosystems (Johns 1985, 1992; Holloway et al. 1992;
King and Chapman 1983; Thiollay 1992, 1995). These measures are also used in studies of forest (ecosystem) dynamics (Foster 1980;
Denslow 1980, 1984; Whitmore 1984a; Primarck and Hall 1992).
However, the logistical dilemma remains: it is difficult to inventory the enormous number of species present in tropical ecosystems with any measure of statistical confidence. This difficulty, combined with the sense of urgency resulting from the current rate of habitat destruction (for example, Myers 1988;
Sayer and Whitmore 1991), has inspired ecologists to focus on certain well-known taxonomic groups. Plant taxa (together with butterflies, reptiles, birds and mammals) have been used at a broad conservation strategy (policy) level. The "Hotspots" and the "Megadiversity" country concepts, for instance, use plant taxa as an indicator to identify global hotspots and megadiversity countries (Myers 1988a; Dinerstein and
Wikramanayake 1992).
35 Because of the enormous data requirements of biodiversity studies at the species level, other ecologists have also proposed the use of higher taxa (Williams and Gaston 1994) or guild- indicators (Severinghaus 1981; Verner 1984). These suggestions have rarely been followed, probably because it is difficult to associate the diversity of all taxa with that of one or even a small group. Many studies have shown, however, that tree species diversity is well-correlated with the diversity of other taxa
(Fig. 3.1)(MacArthur and MacArthur 1961, Murdoch et al. 1972,
Currie 1991). Considering the structural, hydrological and climatological functions that single trees, let alone entire forests make to the ecosystems which they inhabit, and most importantly their function as a primary producer, this conclusion is hardly surprising. It is supported by adding to these considerations, the important role that trees play in nutrient cycling in tropical forest ecosystems.
Prominent in the literature addressing criteria that functional buffer zones should meet is the contribution of Sayer
(1991). He suggests that good buffer zones should:
1. maintain tree cover and habitats in a natural, or near natural state;
2. resemble in its vegetation that of the protected area, both in species composition and physiognomy;
3. exhibit similar biological diversity when compared with the protected area; and
4. retain, as far as possible, their capacity to recycle soil nutrients. 36 Figure 3.1: Relation between plant diversity and animal diversity (from Murdoch et al. 1972).
200
150
° ° n ° 100
50 AVES MAMMALIA
80 a DO° o 1 60 60 40 a °B ^ 40
20
AMPHIBIA REPTILIA 0 100 150 50 100 150 \ TREE-SPECIES RICHNESS
37 These criteria call for a set of data that would require years to collect (Greig-Smith et al. 1967; Whitmore 1990). They are, therefore, impractical if we are to accept, even in part, the urgency of the situation described by Myers (1980, 1988),
Wilson (1988) and many others. Is it possible, under these circumstances, to identify criteria that, although less precise, offer a degree of approximation that lies between those of the
"educated guess" approach described in above (sec. 3.3.), and
Sayer's desired, but virtually unattainable precision? If, for example, the diversity and physiognomy of tree species within buffer zones is maintained in a state that can be considered to be "similar" to the diversity and physiognomy of tree species within the protected area, it may be reasonable to conclude that the capacity of the ecosystems to recycle soil nutrients will be maintained, and that these ecosystems are likely to regain their natural or near natural biodiversity.
Many studies in tropical regions indicate that natural disturbances actually provide mechanisms by which a forest maintains its species diversity (Foster 1980; Denslow 1980, 1984;
Whitmore 1984a; Hartshorn 1989; Primarck and Hall 1992). Studies of selectively logged forests show that, given sufficient time, forests will recover their diversity and structure (King and
Chapman 1983). There is no agreement on whether or not other taxa, such as birds and mammals, regain their original diversity
38 and species composition after selective logging. Nonetheless, studies by Johns (1985, 1992) indicate that:some bird and primate species were able given sufficient time, to fully recover a viable level of diversity (see also Thiollay 1992 and Holloway et al. 1992).
Based upon all of the above, it seems clear that, in the context of forested ecosystems, the key biophysical criteria for a functional buffer zones, should be associated with the physiognomy and tree species richness of the forest. Thus, what is needed are measures of tree species richness, forest physiognomy, or stand density at a variety of diameters, and an analysis of the changes that occur from centre to the periphery of the reserve.
3.5.2. Socio-economic criteria
Since protected areas are established to protect natural habitats within them, buffer zone widths and subsequent management prescriptions should be determined'to meet this objective. However, in light of the operational,, socio-economic and political problems involved in the management of protected areas, buffer zone widths that are solely based oh biophysical criteria are unlikely to be successfully enforced. .This consideration, plus the fact that the objectives of buffer zones are not only to safeguard protected areas but also to protect the
39' livelihood and/or safety (from animals) of people living around
the park, thus means that a good buffer zone should meet not only biophysical criteria but also a set of specific administrative, political, and socio-economic criteria.
I should make it clear that my study is not designed to
examine the socio-economic criteria. My purpose is to show that
the literature acknowledges these equally as important as biophysical criteria. Therefore, the method I suggest needs to
incorporate a planning and management approach that pays
attention to, respects, and also directly involves local people.
The application of socio-economic criteria implies a different
approach to one that simply addresses biophysical criteria. It
implies that local people will have to be involved, both in
developing the appropriate criteria, and . in applying them as part
of a co-management arrangement.
Only in exceptional circumstances have, protected areas been
established in unoccupied or uninhabited areas of the world.
Most frequently, their establishment displaces both subsistence
and market activities pf local residents that otherwise would
occur within the area receiving protected status. The economic
well-being of these people, therefore, is often severely
compromised. Not surprisingly, the typical response of local
people is to ignore the new designation and continue their
40 livelihood practices as before. In such cases this reaction leads to an increasing rate of exploitation of resources within the newly designated area. In other situations, where a new protected status regulation is stringently enforced, the result of the new buffer zone designation is to impoverish local people
(Ghimire 1991; Gadgil 1992; Colchester 1994). The suggestion that direct participation of local people can be a sufficient solution or safeguard may be true if we consider only the direct and immediate benefits, or direct use values. Other benefits, however, such as options for future use and services that a protected area can provide, have been usually over-looked (see
Munasinghe 1992 and Wells 1992).
Protected areas are often characterized and defended as long-term social investments. With the increasing interest and involvement of international donors and conservation organisations in providing technical and financial assistance to encourage tropical countries to establish protected areas (and subsequently, buffer zones), many new jobs and facilities have been created (Wells et al. 1992; Anon 1995). Unfortunately, however, these direct benefits most often occur at the international, national and regional levels not at the immediate local level (Schaik et al. 1992; Wells 1992).' Creation of protected areas thus frequently deprives local residents of access to use values within the reserve without providing
41 compensatory benefits. Such a redistribution of costs and benefits appears to be inequitable and unjust. While this conclusion is often drawn by both local residents and their governments6, it is especially true for local residents who often have no alternative for either subsistence or market activities following the establishment of a protected area.
Attempting to counter such negative assessments, and to demonstrate that protected areas also benefit local people, a number of studies have been undertaken to document such impacts and longer-term effects. The evidence gathered by some of these studies suggests that, although local residents may lose their
"direct use value" when a protected area is established, over time they often actually do receive some social and indirect economic benefits, although these benefits have not generally been compared, quantitatively, with benefits lost (Munasinghe
1992; Wells 1992). Others suggest that the collection of non- timber forest products and limited timber extraction by local people — activities that can be permitted in buffer zones— can actually provide social and economic gains that are comparable to income from logging or agriculture, and that these can be more
"sustainable" (Fearnside 1989; Peters et al. 1989; Costello 1990;
Balick and Mendelsohn 1992).
6 Studies indicate that while the economic and social benefits are (see Munasinghe 1992) incurred within local, national/regional, and international communities, the costs must be borne by local and national communities (Schaik et al. 1992; Wells 1992). 42 In spite of such evidence, however, habitat destruction within protected areas continues, and is often the result of activities of local people. In their search for solutions, conservationists argue convincingly that many of these problems can be overcome by involving local residents in the planning and management of protected areas, and by providing them with direct social and economic benefits from these activities, (Lusigi 1982;
Lewis et al. 1990; Wells et al. 1992; Wells 1994).
Numerous social and economic studies of the relationships between parks and people in tropical countries suggest that the loss of access to resources within the protected areas is the principal concern of local people. In situations where this access is maintained, people show a positive attitude toward protected areas (Newmark et al. 1993; Mkanda and Munthali 1994-) , even when their crops are damaged by wildlife from protected areas (Studsrod and Wegge 1995).
Crop damage by wildlife from protected areas is also a major concern of many people living adjacent to protected areas (Sharma
1990; Salafsky 1993; Newmark et aJ. 1994). After the loss of access to values they once harvested from newly protected areas, local people surveyed consistently rate the concern for preservation of wildlife as their second most serious concern.
43 While these studies generally found that despite such
concerns, a majority of local residents do support the existence of protected areas. However, they do not always show similar
attitudes toward park employees. This may be due to the past
"policing" practices in the management of protected areas.
Nevertheless, Newmark et al. (1993) found that a visit from a well informed and "culturally sensitive" protected area employee
can actually improve local peoples' attitude toward a protected
area's employees.
It is important to note here that, despite various socio•
economic hardships, local people interviewed during the above
studies often do attach more importance to the non-use value of a protected area than to the option of converting it to
agricultural or other uses. Thus, in assessing benefits of
protected areas and buffer zones, "economic returns" should not
be overemphasized. Many social and cultural factors can also
play essential roles in the support for and safeguarding of
protected areas.
The use of socio-economic indicators to assess the social
and economic health of a given population of people is apparent
in an ever-growing literature (Khan 198 6; Unesco 1986). Many
government institutions and international organizations regularly
publish data or express concern over the level or magnitude of
44 such indicators. Economic journals and mass media report them monthly or even daily.
Among the most commonly used and widely accepted socio•
economic indicators are GNP (Gross National Product) per capita,
GRDP (Gross Regional Domestic Product) per capita, rates of
infant mortality and adult literacy, and so on (Khan 1986).
Based on these indicators, social and economic development
objectives are then established and judgments made concerning the progress a country or region is making on improving socio•
economic performance. Changes in the development policies of
national governments, and the allocation of international
assistance, are often driven by the performance of these
indicators.
Despite the fact that these indicators are so widely
accepted, Denison (1977), Khan (1989), Daly and'Cobb (1989), Smil
(1993), and many others, have criticized their use, and value
largely because they fail to account for many'key social and
environmental factors. Attempts ,to develop new .indicators that
measure the welfare (or quality of life) of a people have been
made, but such indicators are neither widely used nor universally
accepted (Daly and Cobb 1989; Nordhaus and- Tobin 1977) .
Recently, a World Bank group of experts proposed new measures of GNP which include, in addition to produced assets, both natural capital and human resources (Zagorin 1996).
Almost invariably, socio-economic indicators rely on measurements of economic productivity on a broad scale (i.e., for a country or province) yet many social scientists argue that the
"well-being" of a population depends upon much more than what is produced and distributed through the cash economy. Often, conclusions drawn from the use of such aggregate (or average) indicators seem to be based on the assumption that the economic activity measured, and the government services provided, are distributed equally among the people. Subsistence activities are seldom, if ever, accounted for. While such aggregate indicators may be appropriate for use at national and international scales, they can become meaningless when used to assess social and economic conditions at the scale of local communities especially in the tropical countries which are under discussion.here.
An assessment of the overall impacts and contribution.that protected areas can make must be conducted over a variety of temporal and spatial scales. In the context of protected area and buffer zone management, however, what appears to be lacking is some method for measuring the dependence of the local population on activities that have been conducted within the proposed protected areas. These may be "economic" activities, in
46 the sense that people are gathering items "for sale", or they may be characterized as "subsistence" activities, in the sense that they involve gathering or growing items for consumption or other use at home. When combined with an understanding of the biophysical capabilities of an area, such information can be used to determine the extent to which alternative options for local residents must be found or provided in order to "protect" the environmental and socio-economic viability of an area.
Considering the lack of economic options for local residents, and the financial and administrative limitations of national governments, the fate of many protected areas will inevitably depend to a large extent on local residents (Wells et al. 1992). Thus, it makes more sense to establish social and economic criteria for buffer zones that recognize the circumstances of local, rather than those that are based on national or regional communities. A monetary incentive mechanism should be established to compensate local and regional communities. As Wells et al. (1992:30) put it "... local people should not have to make economic sacrifices to protect an area established to provide global benefits...". From a slightly different perspective, Wind (1991) proposes that buffer zones should "... protect cultivated areas/settlements with their resources against negative influences originating from the conservation area".
47 Based on all the above considerations it can be concluded that a well-designed buffer zone can reduce the conflict between conservation objectives and those who live adjacent to the reserve if it meets the following socio-economic criteria:
1. maintain access to the existing subsistence and economic activities of local residents, or provide alternative, comparable opportunities to these people, and
2. monitor and reduce crop and livestock damage caused by animals or plants from reserve and other negative "spill over effects" such as the possible impacts of eco-tourism.
Socio-economic data, however gathered, should document people's perceptions about the net benefits they get from protected areas (buffer zone), including their perceptions of economic losses due to crop and livestock damage by wildlife from protected areas7. These data should be gathered prior to the determination of an appropriate buffer zone width and management regime to apply within it. A monitoring plan to compare original data with that gathered, say, in the third or fifth year following the establishment of a buffer zone, could be used to determine whether or not the management regime meets the socio• economic criteria.
7 In data collection, park planners must be cautious when conducting interviews with local people, especially with regard to how questions are asked, who is asked questions, and when is the best time to ask questions. In addition, the interviewer must be aware of social class distinctions in a group interview setting, as lower class residents may not be willing to voice their views in the presence of a landowner or a member from a higher class. 48 CHAPTER 4: STUDY AREA
4.1. Ruteng, Flores Island
The method for the determination of buffer zone widths was applied around RSNR, Ruteng. This reserve was chosen because this area reflects conditions similar to many other protected areas in the country (Chapter 2) . RSNR is one of. the most important reserves in the Nusa Tenggara region (sec 4.2.1), and in terms of logistic support for. field work, it is better situated than many other reserves in Indonesia.
Ruteng is the capital of the. Kabupaten (District) Manggarai.
It is located on Flores Island (8° 30'S 121° 00'). The island is about 17>150 km2 in size,' and stretches approximately 360 km from
West to East, and varies from 12 to 70 km wide. Administratively,
Flores and its small offshore islands are divided into five districts, all of which fall under the jurisdiction of the East
Nusa Tenggara Province (Fig 4.1). The five districts are: Flores
Timur, Sikka, Ende, Ngada,. and Manggarai (ca. 7136,4 km2). The
Manggarai District is split into 10 kecamatan (sub-districts):
Komodo, Lembor, Satarmese, Mborong/ Elar, Cibal, Ruteng, Kuwus, and Reoq. In order to facilitate .development, local government has created another seven area representatives.
•49
Rainfall in the Manggarai District varies from 1,000 mm annually in the lowland areas to 3,500 mm in highland areas (Fig
4.2). Average rainfall in Ruteng is more than 3,000 mm annually, with heavy rainfall between November/December and March. The dry season begins in May and continues to October. The average temperature is between 18° and 25° C.
Figure 4.2: Mean rainfall (mm) in Ruteng (constructed with data from RePPProT 1989) .
500 n
0 I —I 1 ••—I : 1 1—: 1 1 1 I 1 I JFMAMJ JASON D
The population of Manggarai District has increased very rapidly from 254,000 in 1961 to approximately 500,000 in 1990
(Table 4.1). The average annual population growth was 2.36%.
Although overall population density for the Manggarai District is about 70 people per km2, population density in some sub-districts is remarkably high (Table 4.2). For instance, the average density of 3 sub-districts (i.e., Ruteng, Kota-Ruteng and
51 Perwakilan Ruteng sub-district) around the town of Ruteng is approximately 350 people per km2 (Moeliono 1993).
Table 4.1: Population of Manggarai District 1961 to 1990 (in parenthesis are figures for Indonesia).
Year Total Density Annual growth (000) (km2) .(%) 1961 253.7 [97,085] 35 [50] 1961-1971 2.39 [2.1] 1971 320.6 [119,208] 45 [62] 1971-1980 2.39 [2.4] 1980 397.5 [147,490] 56 [77] 1980-1985 2.31 [2.2] 1985 450.7 [164,047] . 66 [85] 1985-1990 2.31 [1.8] 1990 499, 5 [179, 248] 70 [93]
Sources: RePPProT (1989), KLH (1992a), and WB (1994).
Prior to the 20th century, the Manggarai population appears to have been relatively stable. Gordon (1975) suggested that in these earlier times that time, population density was quite low, or no greater than 20 people per km2. The majority of the people were practising slash and burn agriculture. However, it can be argued that some elements of the local culture, bad health care conditions, and frequent famines during the previous centuries were the major factors that maintained a low population in
Manggarai.
52 Table 4.2: Population and density by sub-district 1991 (italicized are sub-districts located near to the RSNR).
Sub-districts Area (km2) Population Density
Komodo 1,219.8 28,152 23. Perwakilan Komodo 555.18 17,142- 30 Lembor 694.99 41,420 59 Satarmese 572.04 42,874 75 Borong 490.2 6 38,397 .78 Perwakilan Borong 491.94 32,368 66 Elar 567.59 20,152 35 Perwakilan Elar 4 00.09 17,753 44 Lambaleda 3 60.43 21,784 60 Perwakilan Lambaleda 209.24 40/467 193 Ruteng 176.61 50,178 284 Kota Ruteng 60.54 40,123 663 Perwakilan Ruteng 75.55 ' 18,601 243 Cibal 188.27 27,776 147 Reoq 595.41 21,778 36 Kuwus 208.44 29,901 143 Perwakilan Kuwus 2 69.05 18,649 69 .
Total Manggrai 7,136.43 507,515 Average 71
Source: adapted from Moeliono (1993).
With the arrival of the Dutch in 1908, and subsequently. the
Catholic church in 1917, Manggarai experienced rapid social, economic and physical changes Improvements in health-care, the introduction of new crops and new techniques of farming and pest control, all led to a simultaneous•increase in population and a decrease in forest cover. Gordon (1975) has suggested that the
Dutch were aware of the hydrological importance of forest cover around Ruteng and as a result declared forest reserves in which cutting was monitored. After Indonesian independence in 1945, the Catholic Church continued to play an important role in; enhancing health care and agriculture systems in this region '
(Webb 1990) and in remote places elsewhere in the country.
Since 1965, there has also been a significant acceleration of economic growth throughout Indonesia. This growth, however, has primarily been concentrated around major cities and in provinces in the western parts of the country. Most places in the eastern part of the country, and especially in Kabupaten
Manggarai, have been less fortunate in regard to their share of the benefits resulting from this rapid economic growth. Table
4.3 shows GRDP and GRDP per capita for Manggarai.
54 Table 4.3: Data Gross Regional Domestic Product (in Rupiah) for the East Nusa Tenggara Province 1990-1992 without gas and oil revenues (italicized districts are on Flores) .
Districts Total GRDP (million) GRDP per capita 1990 1992 1990 1992
Kupang 287,515 428,069 520,368 747,423 Timor Tengah Selatan 93, 31 124,315 60,745 336,859 Timor Tengah Utara 53,260 68,974 316,321 397,073 Belu 38,348 91,692 305,482 395,038 Alor 60,417 72,563 405,550 472,528 Flores Timur 81,783 91,692 296,744 387,043 Sikka 88,408 115,290 346, 164 440,076 Ende 85,612 119,406 378,653 517,409 Ngada 66,372 89,872 225,090 430,816 Manggarai 152,897 202,170 297,104 378,718 Sumba Timur 68,615 91,355 430,908 556,058 Sumbawa Barat 89,865 119,532 299, 108 384,106 TOTAL East Nusa Tenggara 1,196,773 1, 631, 622 352,536 466,240 INDONESIA (*= trillion) 115* 130* 934,604 1,234,724
Sources: Kantor Statistik NTT (1994) and BPS (1995).
The majority of the population in Manggarai is engaged in agriculture. Of the total 65,600 households, about 62,570 households (or 96.18%) were engaged agriculture in 1983. As the population continued to increase, the number of households working as farmers has correspondingly increased. In a 10-year
55 period, 1983-93, the number of households that engage in agriculture increased from 62,570 to 80,920 out of a total of
88,190 households in 1993 (Kantor Statistik 1994). Manggarai is not only faced with rapid population growth but also must deal with uneven population distribution. Very high population densities are found in urban areas (i.e., around the town of
Ruteng).
A direct consequence of accelerated population growth has been the decline in arable agricultural land per capita from 1.72 hectares per household in 1983 to 1.07 hectares in 1993. The percentage of households owning land less than 0.5 hectares has increased from 8,840 households (of the total 62,570 or 14.13%) in 1983 to 22,390 households (of the total 80,920 or 27.67%) in
1993 (Kantor Statistik 1994). Consequently, as more households are engaged in agriculture, less land is available to each family.
In Manggarai, as in many other places in the country, land claims are based on the principle of first cultivation. A piece of land automatically belongs to the first person to clear forested land and bring it under cultivation. In a traditional
Manggarai village two functionaires have traditionally played important roles in the land allocation and land use: tu'a teno
56 (agricultural chief) and tu'a golo (village chief). While the tu'a teno dealt with the agriculture activities in the village, the tu'a golo dealt with political affairs in the village or in neighbouring villages and in particular in the case of land disputes. The tu'a teno function is usually held by the first cultivator, his descendant (son), or a member of his clan, while the tu'a golo function may be given to the second most important clan in the village (Gordon 1975). Often, however, both positions are held by one person.
In a traditional Manggarai village, there are one or several circular-shaped gardens {lingko). In cases where forest was newly cleared for a garden, the tu'a teno would allocate land for the families in his village. After he performed a series of ritual ceremonies, the circular-shaped garden was divided into several pie-shaped pieces (lodok). Depending on family size, or on one's prestige in the village, a family will be given one or several pieces to be cultivated. Although land can be permanently owned or cultivated by a family, land can only be replanted after the tu'a teno has performed a ritual ceremony.
Only sons in the family will inherit the land when a father is old or deceased. A daughter is regarded as an "outsider" in the family (as she will move to her husband's village); therefore, she can never inherit her father's land. Although adat (custom)
57 laws remain strong in the everyday life of the Manggarai people today, land transfer to people from outside the village or the clan does sometimes occur.
Despite enormous efforts by the Dutch administration, and later by the Indonesian Government, to improve agricultural techniques and to introduce changes in land use practices systems, traditional land use still remains strong. This is particularly true where land is under dryland cultivation. A number of lingkos exist around Ruteng today. In addition, land claims that are based on the traditional tenurial system remain strong. Often this situation, coupled with increasing land scarcity, triggers fatal land disputes between villages around
Ruteng.
A majority of people in Manggarai practice slash and burn cultivation. A tract of forested land is cleared, and tree or shrub debris is left to dry and is later burned. Then, the land is cultivated, mainly with corn, dry rice, cassava and several types of vegetable. In general, after the second harvest, land productivity will be sharply diminished. People will then abandon the field and move to new forested land. Usually, after a fallow period, which ranges from 10 to 20 years for Ruteng
(Ruwiastuti 1992), the land will be forested again, and the cycle
58 repeats itself; However, due to population growth, and physical development, agricultural land has become scarce, forcing farmers to shorten the fallow period. This situation, in turn, leads to a decline in soil fertility, making it suitable only for the growth of scrubby vegetation and alang-alang (Imperata cylindrica) . In addition, many fallow plots, in the- area have been burned to generate new shoots for grazing. This practice prevents the regrowth of the original vegetation.
It is not surprising, therefore,, that land in Manggarai is currently dominated by scrub, alang-alang grassland, and secondary forests. Surrounding the villages located on hilly terrain around Ruteng, land use is dominated by wetland-rice terraces. In addition, a large proportion of the land is under small scale plantations, planted by coffee or eucalyptus and pine trees. Due to the availability of agricultural land and the current land use pattern in Ruteng, there is mounting pressure by local farmers to use resources' and land within the RSNR. Table
4.4 shows land usage in Manggarai.
59 Table 4.4: Land Use in the Manggarai District (1991).
Type of land use Area (ha) % of total
Settlements 2,921 0.41 Wetland rice (irrigated) 10,196 1.43 Wetland rice (rain-fed) 13,207 1.85 Dryland fields 76, 328 10.69 Small, scale estates 4,355 0. 61 Mixed gardens 54,325 7 . 61 "Closed" forest 95, 084 13.32 Secondary forest 158,241 22.17 Plantation forest 16, 849. 2.36 Scrub/alarig grasslands 280,401 39.29 Wetlands/ponds/lakes 1,64 6 0.23 "Badlands" 15 0.002 Other uses 102 0.01 Total 713,643
Sources: Data Pokok Pembangunan Daerah (as cited by Moeliono 1993).
4.2. Protected Areas on Flores
Flores and its off-shore islands fall under the Lesser
Sunda Islands Biogeographic Province. Based on bird distribution, the Lesser Sunda biogeographic province, can further be classified into three biogeographic units: Sumba, Timor and
Flores (MacKinnon et al. 1982). The Flores biogeographic unit consists of Flores, Lombok, and Sumbawa through the Alor Islands.
60 The flora resembles Melanesian floras with only 3% of endemism. In Flores, however, there are some Australian forms, such as Eucalyptus spp. and sandalwood, Santalum album. In general, this biogeographic province has a low species diversity and endemism, especially for non-flying terrestrial mammals, but it has rich bird species diversity and endemism. For example, about 66 of 242 birds (30%), 8 mammals (12%), and 17 reptiles
(22%) are endemic to this region (MacKinnon and MacKinnon 1986).
FAO listed eight protected areas on Flores (Table 4.5), of which only four have been gazetted and four remain without any legal protection status (MacKinnon et al. 1982). Regardless of their legal status (gazetted or ungazetted), these reserves face increasing threats from agricultural expansion, wood extraction, fire and poaching. Habitat loss is one of the major threats for all endemic birds on Flores. For instance, a short-term bird survey on the proposed Kerita Mese Wildlife Sanctuary and the proposed Ruteng Strict Nature Reserve in 1993 confirmed that three of the four birds found only on Flores are present in these reserves, yet both reserves have no legal protection status
(Butchart et al. 1993). Therefore, important conservation steps that have been proposed are: to give all remaining proposed reserves legal status (i.e., gazetted), and subsequently, to ensure effective management to prevent further habitat loss and degradation.
61 Table 4.5: Protected areas in the Flores and offshore islands (italicized are gazetted reserves).
Reserve types Size Altitude P. Threats (ha) (m)
CA Pulau 17 11,900 sea level na na CA Ruteng 30,000 900-2400 1 wood extraction, agriculture encroachment, gravel mining CA Gn. Abulombo 5, 000 1000-2149 3 agricultural encroachment
SM Wae Wuul 3, 000 0-300 2 animals poaching, fire, settlement expansion SM Kerita Mese 15,000 0-1000 2 fire and hunting SM Tg.Watupajung 5 sea level 3 poaching
NP Komodo 0-735 1 poaching, fire, 219,322 dynamite fishing NP Kalimutu 5,340 1000-1500 2 agriculture expansion, fire, wood extraction, and litter from tourists
Sources: MacKinnon et al. (1982) and Balai KSDA VII (1992). CA: strict nature reserve SM: wildlife sanctuary NP: national park P.: priority for conservation
4.2.1. Proposed Ruteng Strict Nature Reserve
The proposed RSNR lies in the Flores biogeographic unit of the Lesser Sunda Island Biogeographic Province (MacKinnon and
MacKinnon 1986). The reserve stretches over a series of seven
8 FAO lists this reserve as a proposed strict nature reserve (MacKinnon et al. 1982), while KLH (1992) lists it as a strict nature reserve meaning it has been gazetted, but failed to give clear reference as to when it was gazetted. ADB (1992) refers to it as the Ruteng Grand Forest Park. 62 volcanic mountains with altitudes ranging from 900 to 2,400 m above sea level. The area is formed on basaltic substrate and covered by tropical semi-evergreen and upper montane rainforests.
Due to its biogeographic processes, the distance from bigger islands, and its dry climate, the Lesser Sunda region is considered low in species diversity and endemism compared with the other biogeographic regions in Indonesia. A large proportion of the region has been deforested. Most of the remaining forests occur at higher altitudes and in steep hilly terrain. Flores is not exceptional in these attributes. Nevertheless, the RSNR contains one of the most continuous tropical semi-evergreen and upper montane rainforests (MacKinnon and MacKinnon 1986) in the whole Nusa Tenggara (Fig 4.3). Moreover, because of its position as transition zone between the Australian and the Oriental realms, it offers unique opportunities for future biogeographic and evolutionary studies. The protection of natural habitats in this region will ensure the completeness of habitat types, in the
Indonesian protected area system. In terms of wildlife diversity, about 100 bird species, including 20 endemic species, are likely to occur in the reserve (ADB 1992). There are about seven endemic mammals which are mainly rodents and bats (Petocz
1989) .
63
In 1936 about 39,000 hectares of forest around Ruteng were declared a forest reserve by the Dutch administration to prevent further deforestation by the rapidly growing population (Gordon
1975; ADB.1992). In 1982, FAO developed a comprehensive protected area system for Indonesia. The Ruteng protection forest was proposed as a cagar alam (strict nature reserve), with a total area of 30,000 hectares. It was designated as a reserve with Priority I9 status (MacKinnon et al. 1982).
Along with RSNR, FAO proposed about six reserves on Flores
(excluding recreational reserves). The RSNR contains the highest peak on Flores. The protection of the RSNR and other reserves at lower altitudes (i.e., Tanjung Kerita Mese) will ensure that all natural habitats and biota of Flores will be covered in the protected area system..
The main objective of the reserve is to protect the hydrological functions of the forest and to preserve rare and rich habitat types with .endemic flora and fauna (Gordon 1975;
MacKinnon et al. 1982). Unfortunately, as with many other protected areas in the region, almost 10 years have passed since it was first proposed. No further action has been taken to
9 Priority I is given to an area of major conservation importance whose omission from the reserve system would constitute major gaps in the habitat coverage (MacKinnon et al. 1982). ' 65 implement the FAQ recommendations. In 1990, the reserve was reproposed as the Ruteng Mountains Grand Forest by the Asian
Development Bank and the Forestry Department (ADB 1992).-
4.2.2. Threats to the reserve
In many ways, Manggarai's social and economic situation reflects that of other areas in Indonesia. Development.efforts have largely focused on social and physical needs (i.e., health care and agriculture productivity), resulting in continued and increased pressure on land and natural resources within reserves.
The reduction of available agricultural land and the increases in opportunities to engage in cash exchange economic activities has led people to explore other means to provide for their basic daily needs. The rising demand for firewood and building materials due to population growth and on-going physical development has also provided new incentives for people to obtain cash through the cutting and selling of wood (Moeliono'1994). In fact, for some families, .selling wood may be the only available income option, especially for those who own less than 0.5 hectares of agricultural land on which to support their families.
The main threat to the reserve is-the collection pf building materials and firewood from within the protected area. Almost all local residents use forest products to obtain cash income
66 through the sale of poles for building and firewood. Only a small proportion of the products taken from the reserve are for direct household use. On any path to the reserve, about 10 to. 15 local people can be observed daily. Each will be dragging more than three raw poles (approximately 7 m long and between 10 and
30 cm in diameter). Dragging of poles has also caused quite serious soil erosion. Firewood collection, usually conducted by secondary and high school students, occurs less intensively than the collection of building materials.
Apart from direct threats generated by local people, there are a number of other serious management problems for the reserve. Despite its location near the capital of the Manggarai
District, there are no signs of active management (i.e., protection). The only indication of the reserve boundary are a few posts, all of which are covered by vegetation. The boundary posts are too small and too short to be easily seen by local residents or visitors. No marker sign exists to indicate the presence of the reserve. Moeliono (1993) suggested that, with only about 17 forest wardens to cover approximately 269,629 hectares of forest in the Manggarai District, proper guardianship is simply not possible. It is not surprising, therefore, that during a one year period of field study around the reserve, the author never encountered any of the forest wardens, despite the
67 fact that every day villagers cut trees from the protected forests.
4.3. Social and Economic Conditions
4.3.1. Socio-economic characteristics
About 80,920 households (or 92%) in Manggarai are engaged in agriculture. If, on average, one hectare of agricultural land
(that includes wet-rice field [sawah] and dry-land [ladang]) in
Manggarai produced 2.17 tons of rice (N = 17; SE = +0.72), then each household (owning one hectare of agriculture land) will be earning about Rp. 90,416 (or approximately US$45)10 monthly.
However, since most of the agricultural land (68%) (Barlow et al.
1991; Moeliono 1993) is under shifting cultivation (i.e. dry• land), then land productivity will be lower, producing about 0.5 tons of rice per hectare (Kantor Statistik 1994a). In other words, the total earning capacity from agriculture for one average farming household is much lower than the calculation above would suggest.
Average monthly spending (to meet a basic cost of living) per person in 1991 in Manggarai was calculated at Rp. 40,000
10 The land productivity figures were calculated from Table 3, p. 3 (Kantor Statistik 1994a). Land productivity figures were less than in Java, where the average is > 4 tons rice per hectare. Due to the lack of water in Ruteng, farmers can only cultivate their land once a year, except for in some coastal areas (Gordon 1975). The total earning from agriculture is far too small given that an average family in Manggarai consists of six people (Moeliono 1993).
68 (Kantor Statistik NTT 1994). Consequently, a household
(consisting of six persons) requires about Rp. 240,000 monthly.
Thus, it can be concluded that farmers must seek other income opportunities to meet household monthly spending. Increasing the financial demands on the low income families, are many traditional ceremonies still practised by local residents. From a strictly economic point of view, some traditional customs, such as bridal price and wedding ceremonies are very expensive, leaving residents with a sizeable debt (and often permanent indebtedness).
4.3.2. Wood contribution to the household economy
It is difficult to make a "clear-cut" calculation based on residents' monthly income and cost of living (see 4.3.1), but economic conditions suggest that income from agriculture is insufficient for family support on a monthly basis. Thus, for many households, selling wood is an important supplementary activity to earn extra money. As Moeliono (1993: 18) concludes,
"nowadays, many people earn the major part of their income from cutting wood".
Selling wood has become an important income alternative for the residents because: 1) residents have easy access to the forest, 2) it requires no capital investment (except for a machete or hand-saw), 3) it involves almost no risk, 4) there are
69 no seasonal limitations (such as in agriculture or temporary
jobs), 5) it is easy to sell the wood and there is a high demand
for wood around Ruteng, and 6) there are literally no laws or
regulations for harvesting.
Demand for wood is remarkably high in Manggarai. Government
data for fuel usage in 1990 showed that, of 85,811 households in
Manggarai, about 82,102 (or 95%) used wood daily for cooking.
Only 1/332 households (less than 5%) used kerosene, and 138
households (less than 0.2%) used electricity (Kantor Statistik
NTT 1994). With a total population of about 108,902 around
Ruteng (Table 4.5), of whom 90% used firewood for cooking, it can
be estimated that they need approximately 98,000 m3 of firewood
for this purpose annually11. If on average wood volume is
estimated at about 170 m3/ha for forests12 in Nusa Tenggara, then
about 576 ha of forest are needed annually to meet the fuel wood
demand in Ruteng alone 1 Such demand requires, at the very least,
an output equivalent to the annual increment of 8,500 ha of
plantation of Pinus merkusii and Tectona grandis (see Repetto et
al. 1989).
11 Estimated figure for firewood consumption per capita outside Java is 0.9 m3 annually (see ADB 1992; Moeliono 1994).
12 See Repetto et al. (1989: 30) for this calculation. 70 In addition to fuel, people use wood to build houses. In
1990, approximately 30% of households in Manggarai used wood for house floor surfaces and another 45% for the outer walls (Kantor
Statistik NTT 1994). Unfortunately, no figures were available for house types and wood usage for houses around Ruteng.
However, Moeliono who studied wood demand for the Manggarai
District, estimated that about 10,000 m3 wood was needed for house construction annually (Moeliono 1994).
Although a direct assessment of the contribution to house hold income from selling wood cannot be made, it can be concluded based on the current wood demand in Manggarai, that selling wood, either for fuel or building material, makes a significant contribution to the incomes of local residents.
Data on either the amount of wood sold or wood prices are unavailable. This is because the selling of wood is a small- scale activity involving many people, making it difficult to trace. Despite the fact that selling wood has become a major income source for local people, it is mostly been carried out on a "non-commercial" basis. Consequently, a 5-m piece of wood is likely to be priced the same as a 4-m piece (Moeliono 1993).
Income from selling fuel wood varies, but, in and around Ruteng, a person will earn about Rp. 750 - Rp. 1,500 (approximately 50
71 cents US$) daily13 (Moeliono 1993), which, according to Moeliono
(1993), provides a significant contribution to their household income.
4.3.3. Alternatives to selling wood for income
Unfortunately, there are not many alternative ways to earn money readily available to local residents, except for working in agriculture or in temporary construction jobs. The cement factory in Kupang (on Timor Islands) was the only large-scale industrial activity14 in the East Nusa Tenggara Province, with a total of 274 workers in 1989 (Purba 1991). In 1992 there were about 10 small-scale industries with a total of 92 workers, and about 1,863 handicraft industries in Manggarai employing a total of 2,779 workers (Kantor Statistik NTT 1994).'
A lack of other natural resource industries and endowments, such as mining or forestry (timber resources for large scale industry), infrastructure, or support facilities (such as good roads, harbours, and airports), seriously limits the prospects for industrial development in Manggarai. There is also an apparent lack of entrepreneurship from the Manggarainese, as well as limited capital funds and the small size of local markets
13 Almost equal to a day wage of unskilled labor around Ruteng, which was Rp. 2,000. 14 An industry is classified as large-scale if it employs more than 100 workers, as medium if 20-99 workers are employed, and as small if it comprises 5-19 workers (Purba 1991)
72 (Purba 1991). With a lack of raw materials, and the district's long distance from Java, it is difficult to predict new industrial development in Manggarai occurring spontaneously (or even on a subsidized basis) in the foreseeable future.
In addition to the lack of job opportunities in the industrial sector, the average wage earned was not higher than wages in agriculture. In general, workers were paid between
Rp.75,000 to Rp. 150,000 monthly in 1990 for industrial work.
Therefore,, even if people can find work in industry they would still require extra money to meet monthly living expenses.
Although there is a sizeable coffee plantation near Ruteng, it was quite small and relatively unknown in Indonesian markets which are dominated by coffee from other parts of the country.
In 1993, about 15,073 hectares of coffee plantation in Manggarai produced only 7,428 tons coffee (Kantor Statistik NTT 1994).
Coffee owners often under-priced their coffee to brokers or middlemen to obtain advance money. Thus, the coffee business doe not appear to be benefiting the coffee cultivators but, rather, the coffee traders and middlemen.
Tourism development in Ruteng is constrained by poor land, sea, and air access even during the pleasant dry season. Ruteng also lacks restaurants and food that is generally appealing to
73 tourists (ADB 1992), and does not have many physical or cultural attractions that would appeal to the typical tourist. Official figures indicate that in 1993 about 46,678 foreign tourists visited the Manggarai District, but almost all of them travelled only as far as Labuan Bajo (the west tip of Flores) and to the
Komodo Islands.
Based on the current economic situation, as discussed above, it can be concluded that there are very limited alternatives to the people around the RSNR to substitute for their dependence on agriculture, and the cutting and selling of wood.
The above discussion on the socio-economic situation around the reserve reveals that, without providing income alternatives or some kind of economic assistance directly to the residents around the reserve, buffer zone management and the protection of the reserve is unlikely to be-successful.
Furthermore, a complete ban on wood extraction may simply raise wood prices, which in turn will encourage illegal cutting.
However, without any kind of management (i.e., control), wood extraction from the reserve will ultimately destroy the reserve-— the only water catchment area around Ruteng—'• within a matter of years. This, in turn, will threaten many hectares of rice fields
74 around the reserve (i.e., Ruteng, Iteng and Mborong), as well as jeopardising the water resources of many residents around Ruteng.
4.4. Governance
4.4.1. Local systems of governance
Traditionally, the Manggarai people lived in a group based on the male blood line (parti genealogic) . This system likely began when a farmer succeeded at clearing a forest tract and bringing it under cultivation. This success in cultivation, in turn, allowed people to settle around the new garden. The settlement slowly evolved to become a village (beo) . The first cultivator then became the leader of the village. Since agriculture was one of the most important aspects of Manggarai livelihood, it played an essential role in the traditional system of governance. Many customary regulations dealt exclusively with agricultural related activities (Djagon 1959; Gordon 1975; Hemo
1988; Lewis 1991; Erb 1994).
During the field study, I failed to observe any form of formal association or cultural or spiritual connection between people and the local environments or nature. Nor did I find a set of regulations on how people should manage the natural resources surrounding them as these can be found elsewhere in the country
(for example see Mitchell et al. 1990 and Zerner 1994). Some old tales suggested that traditionally the Manggarainese believed
75 that their ancestors were protected or helped by certain animals,
and therefore they were prohibited to hunt and eat those animals
(ceki or mawa) . But the tales offer no further details, such as
which clan should protect what animals, or to what extent people
still abide by these rules (Djagon 1959; Hemo 1988).
The fact that traditional systems of governance in Manggarai
society centre mainly on agricultural activity (i.e., around the
village) suggests that the traditional systems of governance
offer little help to enhance reserve protection. For instance,
unlike other places in Indonesia, forested land and mountains
were not under "stewardship" or claimed by people in Ruteng. In
addition, despite their dependence on land and agriculture,
traditional systems of governance have become weak since
Manggarai was ruled by Goa in the 16th century, Bima in the early
of the 18th century, and then later the Dutch from the early 19th
century (Hemo 1988). Current national laws do not make much
allowance for traditional systems of governance. Land scarcity
and the importance of agriculture for the household economy
around Ruteng can be capitalised on to encourage people's
participation in buffer zone management. Only by ensuring a
better land tenure system, and offering some kind of assistance
in agriculture, may a more effective management system become
possible.
76 4.4.2. The effectiveness of traditional systems of governance
When Manggarai was ruled by Goa, traditional systems of governance were replaced (Hemo 1988). To enhance tax collection, the Goa divided Manggarai territory into dalus and gelarangs.
Even after first Bima, and later when the Dutch took over
Manggarai, the new dalu systems were maintained. However, after
Indonesia gained political independence, these dalu systems of
Manggarai were replaced with the district (kabupaten) and sub- district (kecamatan) systems as were instituted elsewhere in the country.
Due to these historical changes, the traditional system of governance, where tu 'a teno played a very important role in daily life, became weaker, especially in places near Ruteng town. In addition, land transfers as a consequence of population growth, physical development, the increasing influence of outside cultures, and national regulations on government affairs and land tenure, further weakened the traditional systems of governance.
In all the study sites located relatively close to Ruteng, the traditional systems are long gone. Recent deadly disputes occuring around Ruteng (Anon 1996) over land located between neighbouring villages, were not necessarily a reflection of traditional land management problems, but triggered by land scarcity. Planning and management must take into consideration both traditional and current governance issues, and must work
77 with local governance systems to consider the implications of socio-economic data presented above.
78 CHAPTER 5: PROPOSED METHOD AND ITS RUTENG APPLICATION
5.1. Overview of the Method
Considering problems we face in management of protected areas (Chapter 2), the thesis calls for a method that is simple, inexpensive, and easily-taught, yet which provides reliable information for determining buffer zone widths for any given reserve. Such a method should also include simple though rigorous data analysis and that will allow for greater participation of park planners, conservationists, and local communities.
The method proposed in this thesis for determining functional buffer zone widths is one based on the analysis of species richness, species diversity, stem density and species composition. The method assumes that a reserve has legally been established and that there is "illegal" incursion by people living outside the reserve seeking to use resources 'within it.
The proposed method involves 1) establishing biophysical criteria for functional buffer zone widths; 2) data collection along transects; and 3) data analysis.
The biophysical criteria for the method were established in
Chapter 3. They are based on a number of suggestions (for example see Oldfield 1988; Sayer 1991; Wind 1991) as to how buffer zones should function.
79 The data collection component of the method involves first establishing a series of transects (a) parallel to the reserve periphery, (b) within the existing reserve from the periphery toward the core, and (c) from the existing human activities at various sites in the potential buffer zone (see Fig. 5.1, for example). The potential buffer zone within an existing reserve is considered to be the area where people are actively (even though illegally) harvesting resources. Secondly, for the reasons explained in Chapter 3 and elsewhere, tree species > 5 cm diameter at breast height were within each transect. The same procedure is followed in all transects at all sites.
The analysis involves comparing tree species richness, species diversity, stem density, and species composition between the transects at each site. The basic proposition underlying the analysis' is that, despite illegal human incursions, if areas just within the periphery of the reserve show "similarity" with areas closer to the core of the reserve in terms of species richness, species diversity, stem density, and species composition, then, those areas at the periphery can be, and perhaps should be, accepted and legalized as a buffer zone, in which people are legally permitted to maintain their existing activity. This is so because the analysis has shown that their activity at the existing level and with the existing productivity does not significantly alter the biological diversity of the reserve. By
80 establishing a buffer zone, do not only the new regulations better match actual practices in and around the reserve, but it also creates rules for the buffer zone to ensure that the level of human activity does not increase or extend beyond the now "de facto" buffer zone. If, on the other hand, there is less similarity between periphery and core, then we may conclude that a legal buffer zone needs to be established outside the reserve in order to protect the biological diversity of the existing reserve.
If it is found that a buffer zone can be established in the reserve's area currently used by people, then the width will be determined by where, in the measurement toward the periphery, significant changes in species richness, species diversity, stem density, and species composition (dissimilarity) begin. If it is found to be necessary to establish the buffer zone outside the reserve, then a desired width can be initially estimated (later to be tested) from the analysis of species ,richness, species diversity, stem density and species composition within the reserve. For example, if human activity has caused the biological diversity within the reserve to deteriorate up to 2 km from the periphery towards the core at a certain site, then it may be initially determined that a buffer zone outside the reserve at that site should be 2 km wide.
81 Application of the method focuses on plant taxa because studies have shown that plant diversity is well-correlated with diversity of other taxa (see Chapter 3). Through evolutionary processes, plants have developed defence (or survival) mechanisms against certain animals, especially insects and large herbivores.
In turn, animals, through evolutionary processes, have also developed mechanisms to feed on certain plant species (Gilbert
1980). These mechanisms have resulted in a specific association between certain plant and insect species. Studies have shown a consistent relationship between plant taxonomic and structural diversity with insect diversity (Murdoch et al. 1972; Southwood et al. 1979; Currie 1991). Similar relationships have also been observed in bird communities (MacArthur and MacArthur 1961;
MacArthur et al. 1966; Karr 1968; Karr and Roth 1971). There are a few studies on the relationship between plant structural diversity and diversity of other taxa, such as mammals
(Rosenzweig 1973, where only two species were studied) and lizards (Pianka 1967). The results showed a similar trend.
Holling et al. (1995) points out that in any given ecosystem, hundreds or thousands- of species interact amongst themselves and with the physical and chemical environment.
However, not all species have the same strength and direction in such interactions. Only a small number of biotic (species) and abiotic variables form templates or niches, which in turn allow
82 other species to exist.. In other words, the diversity of a whole community is dependent on only a few species that interact with abiotic factors, such as soil and water. Unfortunately, it is not clear in this context which those species are (Holling et al.
1995). However, if one considers the roles of plant species
(trees) in the forest ecosystem, their functions tend to fit this type of role. Undoubtedly, plant interactions with abiotic environments provide niches for other species, as indicated by numerous studies cited above.
If we consider the interaction between plants and abiotic variables in tropical.forest ecosystems, it shows that trees play important roles in the interaction, especially in regard to nutrient cycling where large amounts of biomass and nutrients are stored in trees (Whitmore 1984). Thus, the biophysical criteria proposed here not only reflect diversity of the community, but also the interaction between biotic and abiotic components in any given ecosystem.
5.2. Sampling Design
In order to illustrate and test,this method for determining buffer zone width, biophysical data were collected around the proposed and legally established RSNR, Flores. Two field studies were undertaken: one over three months in the summer of 1992 and one over 12 months from May 1993 to May 1994.' In 1992,
83 preliminary reconnaissance was conducted to select study sites around RSNR. A basic criteria for an area to be selected as a study site is there must be a "similar" level and intensity of human activities within the protected areas. Fieldwork was conducted from May- 1993 to May 1994 to collect data.
5.2.1. Study sites
Four sites within the reserve and adjacent to Tenda, Laci,
Poka and Nano villages were chosen for this study (Fig. 5.1). At three of the sites, people from the respective villages use the forest within the reserve daily, mainly to extract wood. Near
Nano village, the fourth site, wood extraction is much less, or, is non-existent.
At each study site, four transects 50 m wide x 100 m long running parallel to the reserve boundary.were established to. sample tree species. Transect 1 was located at the reserve's periphery, transect 2 at 500 m, and transect 3 at 1000 m.
Transect 4 was in all cases beyond the existing range of human activity (Fig. 5.2). Thus, in total, there were 16'transects established (9 transects at sites where wood extraction was occurring and 7 transects at the site where there was no or less much wood extraction).
84
Figure 5.2: Sample and Plots Designs.
SI S2 S3
T2
T3
T4 -
transect size sample plot si
100 m 20 m 25 m i 1 50 m
86 5.2.2. Biophysical data
Biophysical data were collected in the 16 transects. All live trees > 5 cm in diameter at breast height (dbh - 1.33 m) were measured and counted in 10 plots of 20 m x 25 m. The species name, number of stems, and diameter were recorded.
Three sets of tree specimens were collected and labelled for further identification. Two sets were sent to the Herbarium
Bogorience (Balai Penelitian dan Pengembangan Botani), Bogor,
Indonesia and the Rijksherbarium, Leiden, Netherlands. The specimens were identified by Dr. J. P. Mogea of the Herbarium
Bogorience, and Dr. M. M. J. van Balgooy of the Rijksherbarium.
5.3. Data Analysis
Only trees with diameter > 10 cm at dbh were used in the data analysis. The number of species was used to calculate tree species richness for each transect. The number of species was used to calculate a diversity index for each transect.
Community ecologists have developed numerous formulae to create species diversity indices (MacArthur 1965; Pielou 1966;
Berger and Parker 1970; Hurlbert 1971; Whittaker 1972). These, in turn, have led to different diversity measurements (Peet 1974;
Routledge 1979; Magurran 1988). Among indices, log series
(alpha), Shannon-Weiner diversity index, and Simpon's index are
87 widely used (Magurran 1988), but there is little agreement among ecologists as to which index should be used. Magurran (1988), using the diversity of moths from ten areas in the Banagher woodlands (UK), examined the results of these indexes in measuring species diversity and found that many indexes showed similar results. She argued that a good index should meet four criteria: 1) ability to discriminate between sites, 2) dependence on sample size, 3) the component of diversity that it was intended to measure, and 4) whether or not the index is widely used and understood.
I used the Shannon-Weiner15 Index of Diversity (H*):
H'= -E pi In pi
where pi = proportion of ith species, to calculate tree species diversity (Pielou 1966; Magurran 1988;
Krebs 1989).
Analyses of Variance (ANOVA) was used to compare tree
species diversity (H')f species richness (5), and tree density among the transects. If significantly different (P < 0.05), then the Tukey test (Fowler and Cohen 1990) was used determine the difference between transects.
5 Henceforth, referred to as Shannon Diversity Index. 88 T= q x Vvariance within/n where, n: number of sample; and q: Tukey value for the varying number of samples and degrees of freedom, obtained from Tukey tables
For the comparison of tree species composition among the transects in each site, the Morisita's index of similarity was used (Magurran 1988; Krebs 1989):
n Cx = 2 T. XijXik (XI + X2)NjN* where, Cx - Morisita's index of similarity between samples j and k XijXik = Number of individuals of species i in sample j and k Nj = ZXij = Total number of individuals in sample j Nk = "LXik .= Total number of. individuals in sample k.
The program SIMILAR by Krebs (1989) was used to calculate the Morisita's index of similarity.
5.4. Results
Based on arithmetic means, Site 4 had higher species richness, diversity, and stem density than Sites 1, 2 or 3 (Table
5.1). There was a tendency for transects located near the reserve boundary (i.e., TI and T2) to have higher tree density
(due to regrowth) than transects closer to the core of reserve
(i.e., T3 and T4). Many of these trees were smaller in diameter compared to the trees in T3 and T416. Because of this situation,
16 SI: Site 1, TI: Transect 1, S1T1: Transect 1 at Site 1, etc. 89 a preliminary analysis which included all live trees (> 5 cm at
dbh) was inconclusive. For that reason, only live trees > 10 cm
were used in the data analysis. Ecologically this approach can
be justified, since many of the smaller trees showed high mortality (Whitmore 1984; Jacobs 1988). Thus, their roles in
long-term tree species diversity and conservation remain unknown.
Certainly, this approach made data analyses more manageable.
Table 5.1: Arithmetic mean ( + S.E.) for species richness, Shannon Diversity Index, and stem density (n = 10 for each transect).
Species Richness Shannon Diversity Stem density (ha) (S) Index (if' ) S1T1 5.9 (+2.511; 1.25 (+ 0.62) 380 (+ 134) •^:•:•;•:•:•:•:•:•:•^:•:•:•:•:•:•:•;•^^^^:•:•^+«: :•; : S1T2 7.5 (+2.88) 1.74 (+ 0.56) 244 (+ 79) S1T3 14.7 (+ 2.41) 2.50 (+0.21) 436 (+ 161) S1T4 13.9 (+ 5.30) 2.34 (+0.42) 592 (+ 211) j S2T1 8.7 (+ 2.87) 1.93 (+ 0.36) 282 (+ 98) | S2T2 10.3 (+ 3.27) 2.13 (+ 0.33) 372 (+ 141) S2T3 9.8 (+ 2.74) 2.02 (+ 0.40) 386 (+ 125) S2T4 14.2 (+ 5.63) 2.42 (+ 0.46) 428 (+ 210) S3T1 6.2 (+ 1.69) 1.62 (+ 0.32) 214 (+83) ++++ 1 S3T2 9.3 (+ 4.01) it-:-::-::-:-::::-:-::-:-:-::::1 .95 ,( **+* 0.54:•: ) 324 (+ 111) 1 S3T3 13.2 (+2.82); 2.39 (+ 0.29) 4 64 (+ 92) S3T4 14.9 (+ 3.28) 2.49 (+ 0.29) 474 (+ 81) S4T1 16.9 (+ 5.15) 2.50 (+ 0.32) 710 (+ 261) S4T2 16.5 (+ 2.55) 2.47 (+ 0.20) 856 (+ 168) S4T3 19.0 (+ 3.46) 2.63 (+ 0.18) 922 (+ 298) S4T4 16.2 (+ 3.71) 2.47 (+ 0.27) 734 (+ 279)
90 About 71 tree species (> 10 cm at dbh) were sampled both at
SI (Kenda) and.S3 (Poka), and 81 tree species were sampled both at S2 (Laei) and S4 (forest near Nano village) (Appendix 1). Fdr
ANOVA, data for species richness and stem density were logarithmically (normal) transformed (Fowler and Cohen 1990).
Figure 5;3 shows the species area curve. This figure was constructed with tree richness data from S4 (T2), because this transect was the richest. The figure showed cumulative tree species sampled from 10 of 20 mx 25 m plots. The curve was relatively flat at the 0.5 hectare range.
Figure 5.3,: Species Area curve (trees with dbh > 10 cm) .
70
0.5 ha
91 In general, the similarity analyses using the Morisita index of similarity showed that tree species composition at T4 (core area) tended be "similar" to T3 as compared to TI and T2 on all sites (Table 5.6). However, one should be cautious with these results considering the high diversity in tropical forest ecosystems and that trees were sampled only in 0.5 ha plots.
Using sample plots as pseudoreplicates, ANOVA showed that there were significant differences in species richness, species diversity, and stem density between the transects at SI and S3.
Only tree species diversity was significantly different between
TI and T4 at S2. There was no significant difference in species richness, diversity, and stem density between the transects at
S4. Using pooled data from SI, S2, and S3, ANOVA showed there were significant differences in species richness, diversity and stem density between the transects.
Using sites (SI, S2, and S3) as true replicates, ANOVA revealed that there were significant differences in species richness between TI and T3, TI and T4, and T2 and T4. For species diversity, there were significant differences between TI and T3, and TI and T4; while there were significant differences in stem density, between TI and T4, and T2 and T4 (Table 5.2).
92 The significant differences between species richness, species diversity and stem density between the transects in SI,
S2 and S3 can be attributed to the current human activities within the protected area.
Biophysical data were analysed in two ways: 1) sites were treated as true replicates, and 2) sample plots were treated as
"pseudoreplicates" (Hurlbert 1984), because in many field situations, it may be impossible to obtain data from other sites that can serve as true replicates.
5.4.1. Species richness
While species diversity takes into account the relative abundance of each species (number of individuals or stems in the species), species richness measures only species present (Table
5.2 and Fig. 5.4).
93 Table 5.2: Summary of ANOVA results using sites (SI, S2 and S3) as true replicates to compare species richness, species diversity and stem density between the transects (ns = not significant, ** = P < 0.05).
Parameters F3,8 P Tukey test TI T2 T3
Species Richness 12.30 0.005 T2 ns T3 ** ns T4 ** ** ns
Species Diversity 7.40 0.01 T2 ns T3 ** ns T4 ** ns ns
Stem Density 5.58 0.025 T2 ns T3 ns ns T4 ** ** ns
94 Figure 5.4: Mean Species Richness on TI, T2, T3, and T4 at SI, S2, S3 and S4 (from 10 plots of 20 m x 25 m).
95 Where sites were treated as true replicates, ANOVA revealed that there were significant differences in species richness between TI and T3, TI and T4, and T2 and T4. When sample plots were treated as pseudoreplicates, ANOVA suggested that there was no significant difference in species richness at S2 and S4, but there was a difference at SI and S3. The differences occurred between TI and T3, TI and T4, T2 and T3, and T2 and T4 (Table
5.3). Pooled sites showed that there were significant differences between TI and T3, TI and T4, and T2 and T4.
Table 5.3: Summary of ANOVA results using sample plots as "pseudoreplicates" to compare species richness between the transects at each site.
Species Richness F3, 36 P Tukey test . TI . T2 T3
Site 1 14.32 0.001 T2 ns T3 * * * * T4 * * * * ns
Site 2 2.33 0.07
Site 3 . .15.8 6 0.001 T2 ns '. T3 * * . T4 * * '**'' ns
Site 4 1.03 0.39
Sites 1, 2, 3 pooled (F3,ii6) 23.36 • 0.001 T2 ns T3 * * ns T4 *•* ns
96 5.4.2. Species diversity
Figure 5.5 shows species diversity for SI, S2, S3 and S4.
ANOVA, using sites (1, 2, 3), revealed that there were significant differences between the transects (Table 5.2). There were significant differences in species diversity between TI and
T3, and TI and T4. Using sample.plots, ANOVA showed there were significant differences in species diversity between the transects at SI, S2 and S3 (Table 5.4). There was no significant difference in species diversity between transects at S4. At SI, the differences occurred between TI and T3, TI and T4, T2 and T3, and T2 and T4., At S2, the difference occurred between TI and T4; while at S3 between TI and T3, TI and T4, and T2 and T4.
97 Figure 5.5: Mean Species Diversity on TI, T2, T3, and T4 at SI, S2, S3, and S4 (from 10 of 20 m x 25 m plots).
Site 1 Site 2
3i
>*5 -P •H
T1 T2 T3 T4 T2 T3 T4
Site 3 Site 4
T1 T2 T3 T4 T1 T2 T3 T4
98 Table 5.4: Summary of ANOVA results using sample plots as "pseudoreplicates" to compare species diversity between the transects at each site.
Species Diversity F3(36 P Tukey test TI T2 T3
Site 1 14.26 0.001
T2 ns
T4 ** ** ns
Site 2 3.01 0.05 T2 ns T3 ns ns T4 ** ns ns Site 3 11.49 0.001 T2 ns T3 ** ns T4 ** ** ns
Site 4 0.89 0.41
Sites 1,2, 3 pooled (F3,nS) 20.48 0.001 T2 ns T3 ** ns T4 ** ** ns
5.4.3. Stem density
Using sites (1, 2, and 3) as true replicates, ANOVA showed that there were significant differences in stem density between
TI and T4, and T2 and T4 (Table 5.2). Using sample plots as pseudoreplicates, ANOVA showed that there were significant differences in stem density between the transects at SI and S3
(Table 5.5). At SI, stem densities were different between T2 and
99 T3, and T2 and T4; while at S3 the differences occurred between
TI and T2, TI and T3, TI and T4, T2 and T3, and T2 and T4.
Figure 5.6 shows mean stem density on TI, T2, T3, and T4.
Table 5.5: Summary of ANOVA results using sample plots as "pseudoreplicates" to stem density between the transects at each site.
Stem Density F3,36 P Tukey test TI T2 T3
Site 1 7.43 0.001 T2 ns T3 ns T4 ns ** ns
Site 2 1.47 0.24
Site 3 19.62 0.001 T2 T3 T4 ** ** ns
Site 4 1.73 0.18
Sites 1,2, 3 pooled (F3,116) 12 . 14 0. 001 T2 ns T3 ** ns T4 ** ** ns
100 Figure 5.6: Mean Stem Density on TI, T2, T3, and T4 at SI, S2, S and S4 (from 10 plots of 20 m X 25 m).
Site 4
950
c0
700
4-> •H CO C Q) P 450 cu 4-J in ii ill IP 200 I T1 T3 T4
101 5.4.4. Species composition between transects
One of the criteria to determine buffer zone width is the similarity of species composition in the core area and areas at the reserve's periphery. In other words, despite human activity, areas at the reserve periphery which show some similarity in species composition to the core area can be considered to be properly functioning buffer zones.
As similarity measures are descriptive, it is difficult to conduct meaningful statistical comparisons (tests.of
Significance) between the transects (Krebs 1989). The index varies from 0 (no similarity) to 1 (more similarity). Thus, transects that show a higher similarity index have a more
"similar" species composition than transects which show.a lower . index.
The main interest here is. to compare species' similarity, in core areas (T4) with that in.areas at the periphery (TI, T2, and
T3). It can be concluded that T3- closely resembles T4 in species composition,' more so than TI and T2 (Table 5.6)..
102 Table 5.6: Morisita's similarity index for species composition between the transects on each site (0 = no similarity, 1 = more similarity).
Site TI T2 T3
Site 1 T2 0.80 T3 0.14 0.38 T4 0.05 0.22 0.50
Site 2 T2 0.06 T3 0.05 ' 0.91 T4 0.29 . 0.46 0.50
Site 3 T2 0.26 :; T3 0.22 0. 65 T4 0.17 . 0.36 0.70
Site 4 T2 0.73'. T3 0.58 0.57 T4 0.42 0.50 0.74
5.5. Conclusion.
5.5.1. Ecological determination
ANOVA, using sample plots as pseudoreplicates, showed that there were significant differences in species diversity, richness and stem density between sites SI, S2 and S3. But there was no significant difference in species richness, species diversity and stem density between the transects at S4. Using pooled data from
SI, S2, and S3, 7ANOVA showed that there, were highly significant
(P < 0.001) differences in species richness between TI and T3, TI and T4; and T2 and T4. There was no significant difference in species richness between T3 and T4. There were also highly
103 significant (P < 0.001) differences in species diversity between
TI and T3, TI and T4; and T2 and T4, but there was no difference between T3 and T4. Similar results were apparent in the analyses of variation in stem densities. That is, there were highly significant (P < 0.001) differences in stem densities between TI and T3, TI and T4; and between T2 and T4, but there was no significant difference in stem densities between T3 and T4.
In general ANOVA, using sites as true replicates showed similar results. There were significant differences in species richness between TI and T3, TI and T4, and T2 and T4. There were no significant differences between TI and T2, and T3 and T4. For species diversity, differences were observed between TI and T3, and TI and T4, while there were no significant differences between TI and T2, T2 and T3, T2 and T4, or between T3 and T4.
There were significant differences in stem density between TI and
T4, and T2 and T4.
Tests of similarity indicated that species composition was
"similar" in T3 and T4 at all sites, and that all transects at S4 were more similar in species composition when compared with the transects at SI, S2, and S3 (Table 5.6). The differences between
SI, S2, S3 and S4 appeared to be directly related to wood extraction that took place at SI, S2 and S3.
104 5.5.2. Buffer zone determination for the RSNR
The field study results at RSNR suggest that there is a need to established buffer zones outside the reserve at Sites 1, 2, and 3. The analysis indicates that the width for Site 1 and Site
3 should be established at 1,000 m from the reserve, but can be less than 1,000 m at Site 2. These findings show that site specific analyses, followed by site-specific buffer zone prescription is recommended, rather than a general management for all sites. However, this may prolong the study period because data must be collected and analyzed for each site. Principle regulations and enforcement should remain as uniform as possible in the entire area around the reserve.
It is important to note that strictly enforced conservation regulations to protect the RSNR will directly affect about 50% of the local residents, whose livelihoods depend on selling wood.
Potentially, it will cost the local community about Rp. 500,000 to Rp. 750,000 (approximately 187 to 375 US$) per day. Thus, another option for the buffer zone is "adaptive management".
Instead of a complete ban on wood extraction,, park agencies can impose a partial or temporary ban. For example, in the first year, all wood extraction beyond 1.5 km of the reserve would be banned. Or, a temporary ban could be imposed on sites where forests are badly degraded. This approach can only be effective if park agencies also offer other alternatives for the local
105 people, such as participation in agroforestry or timber plantations. As management progresses, for example, to the 10th year, park agencies may impose a complete ban on cutting wood from the reserve.
The protection of the RSNR is not only challenged by the socio-economic conditions around the reserve, but indirectly by the physical limitations around it. A survey made by RePPProT
(1989) concludes that soil fertility and water availability are the main limiting factors for agricultural development around
Ruteng. Although Ruteng receives rainfall between 1,000 to 3,500 mm annually, it is distributed unevenly throughout the year.
Thus, despite large amounts of rain, many farmers can only cultivate their land once a year. Other limitations include a lack of suitable land for agriculture, and an abundance of steep slopes prone to soil erosion and land slides during the monsoon season. These conditions, coupled with rapid population growth around Ruteng, have increased dependence on wood extraction from the reserve.
The ADB (1992) recommends several small-scale development and agroforestry options for people around the reserve.
Recommendations cover a range of options including providing staple food (especially for famine prone communities around the reserve), cash and annual crops, apiculture, timber plantations,
106 and tourism. However, in light of the RePPProT's (1989) findings, the ADB's recommendations sound overly ambitious.
Cases exist, however, in which people living in similar socio-economic conditions.and physical limitations to those described above are able to improve their living conditions and physical environment with financial and technical assistance from the government and private sector. For instance, Oh (1985) describes the case of a Korean community, which, after years of timber exploitation, had to deal with severe flooding, drought, soil erosion, low agricultural productivity, shortage of fuel wood and fodder, and general poverty. However, with government financial and technical assistance, a better land tenure agreement and the involvement of local NGOs, the community was successful in meeting their fuel wood, fodder and timber needs, as well as in improving their incomes, all within a relatively short period of time. Certainly, these achievements cannot be directly duplicated in Ruteng, but there are lessons that can be learned.
The fact that nutrients in tropical soils are stored in the biomass suggests that soil nutrients in the tropics can be improved through the growth of vegetation. Thus, despite the lack of soil nutrients, agroforestry is, in this sense, possible around Ruteng. There is ample evidence around Ruteng suggesting
107 that many cash crops, such as coffee and cacao grow well under nitrogen fixing trees. What is needed is government investment and a long-term commitment. In addition, if the local residents can be offered a better land tenure system, especially one addressing the needs of the landless, they may be encouraged to participate in agroforestry activities in the buffer zones'.
Also, there is need to train the local residents in better marketing techniques and income management than they now are able to practice.
108 CHAPTER 6: DISCUSSION: THE METHOD'S POTENTIAL
6.1. Introduction
The application of the method around RSNR showed that the method can be used to determine functional buffer zone widths for any given reserve. Further applications of the method are recommended to examine its effectiveness and to improve its uses in the future. The application also showed that data collection and analysis can be done in a timely manner and relatively inexpensively. With a crew of three people, it took three to four days to sample all trees > 5 cm at dbh in a transects.
Familiarity with the plants or taxa under study and field conditions would help in data collection. Data analyses are straightforward and can be done by using a hand-calculator or spreadsheet program (Exell 5.1 was used for ANOVA). Therefore, it can be concluded that, in addition to the applicability of the method, it is also inexpensive, time efficient, easily-taught, and can be used by park planners, conservationists, and local communities. This chapter offers suggestions on how to improve and apply the method in the future.
6.2. Assessing the Ruteng Application
The application of this method around RSNR suggests that in future studies, only trees > 10 cm (at dbh) should be sampled.
109 Trees > 10 cm likely play important roles in physiognomy of the forest.
In terms of statistical analyses, sites treated as true replicates showed similar results as sample plots treated as pseudoreplicates. Therefore, a suggested study should focus on collecting data from dispersed sample plots, which are located in transects (Hurlbert 1984).
Statistical analyses adopted in this method indicated that these analyses can be used to distinguish the differences in habitat parameters (i.e., species richness, species diversity, and stem density) between the transects, especially at the sites were wood extraction occurred. Although rigorous statistical analyses could not be made for the comparison of species composition between the transects, the analysis used in this method showed that a "sufficient" comparison can be made.
When equal sample sizes are obtained, data can be easily analyzed either with a hand calculator or a spread-sheet program.
Analysis of variance is recommended for slightly more rigorous statistical analyses, but certain requirements must be met
(Fowler and Cohen 1990). For instance, observations (data) should be normally distributed. Non-parametric tests, such as
110 the Kruskal-Wallis test may also be considered. This test is simpler than ANOVA, since it requires neither normally distributed data, nor the computation of variances and means.
However, by using the Kruswall-Wallis test, one cannot determine the differences between transects. Thus analyses may be focused on comparing transects located in core areas (e.g., T4 in this study) rather than transects (TI, T2, and T3) that are located near the reserve boundary. In other words, comparisons should be made between T4 and TI, T2, and T3.
Based on the application of this method around RSNR, it is concluded that this method could be used to determine appropriate buffer zone width. If the analysis shows that there is a significant difference in terms of species richness, species diversity, stem density, and species composition in the area at the periphery of the protected area compared to the area in the core of the protected area, then buffer zone width should be as wide as where the difference begins. Thus, for instance, if the analysis found that the significant difference begins at 2 km from the protected area's periphery toward the core of the protected area, then 2-km a wide buffer (i.e., forest) is needed for that protected area. The area (i.e., forest), that will be established a as buffer zone, should be allocated outside the protected area.
• Ill 6.3. Recommendation: Refining the Method
1) This study found that disturbed areas have smaller trees
(due to regrowth) than relatively undisturbed areas, which have bigger trees. In other words, because disturbed areas were dominated by smaller size trees, they contained more trees per hectare than undisturbed areas. Because the measurements of species diversity, richness and stem density were based on areas sampled, disturbed areas tend to have a higher diversity and density than undisturbed areas. Therefore, it is recommended that future studies should sample only trees > 10 cm at dbh.
Certainly, limiting sampling to trees > 10 cm at dbh will give extra time to either sample a bigger area or other taxa.
However, for a better understanding of forest dynamics in the buffer zones, tree saplings should also be sampled, but perhaps these could be sampled in a few small areas.
2) Tree sampling should be done in a long line or rectangle rather than a square shaped area. This type of sample procedure will give a better chance to sample most of the tree species present in the area than a square shaped survey area (Whitmore et al. 1987).
3) Only plant taxonomic (species) diversity has been surveyed in this study. Future studies should also include
112 structural diversity. MacArthur and Horns (1969) provide a method to measure structural diversity of plant communities.
4) Although it is difficult to ensure an equal sample size in the field, equal sample size will make statistical analyses easier than unequal sample size. With equal sample size it is easier to conduct statistical analysis. This is very important in sampling procedures, considering that not all forestry offices have computers or can afford statisticians to analyze the data.
Simple data analysis, using hand calculators or spread-sheet programs, will also provide an opportunity for the local people to be involved in the data analysis.
It should be noted that determination of- buffer zone width is a first step of buffer zone management. In actual planning, a management prescription must follow after width determination.
6.4. General Application
The measure of species richness and diversity should focus on the resources people extract from within the reserve and the objectives of the reserve. For instance, if people hunt animals from the reserve, then the method should be adjusted to measure diversity of animals. If a reserve was established to protect certain bird populations, then the species richness, diversity
1.13 and density of these populations should also be measured. When time and logistics permit, the case study should also examine more than one taxa. Nonetheless, based on earlier studies of the relationship between plant diversity and diversity of other taxa, it can be suggested here that the primary focus should be on plant diversity.
Although some socio-economic data from governmental institutions and independent studies were presented in Chapter 5 relating to my study^area. In actual buffer zone planning cases, appropriate time would have to be allocated to planning how to gather local socio-economic data (for example, many government institutions provide only data for district or provincial levels, which do not necessarily reflect the conditions at the village or community level).
In the Ruteng study, I benefited greatly from direct participation of local people and their knowledge of tree species
(Verheijen 1982). Tree species identification in the field was made possible with their help. This suggests that, in ecologically based analysis, the direct participation of local people (either farmers or hunters) should be considered.
Certainly, information in regard to social, economic and local customs can be obtained through local people as well.
114 6.5. Conclusion
By no means will the method proposed here precisely determine an ecologically sound buffer zone width that takes into account all the relevant socio-economic and cultural circumstances of the people. But, considering the problems in the management of existing protected areas, this method offers an ecologically-sound approach for park planners. Soule' (1985,
1986:6) points out that "conservation biology is a crisis discipline. In crisis disciplines, in contrast to "conventional" science, it is sometimes imperative to make an important tactical decision before one is confident in the sufficiency of data". He adds "... the risks of non-action may be greater than the risks of inappropriate action". These remarks certainly apply to the establishment of protected areas and buffer zones, despite the fact that both tactics have been practiced for decades. Park planners, conservationists, and local people must make the "best possible" decisions or recommendations for protected areas management, based on whatever methods and data are available.
The method proposed here is very much in its infancy, but hopefully it makes a contribution toward providing a broader methodology that will be an improvement upon existing practices of forest resource and reserve management.
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128 -H & & Appendix 1: Tree specie s sampled is stu
Species Family SlTl S1T2 S1T3 S1T4 S2T1 S2T2 S2T3 S2T4 S3T1 S3T2 S3T3 S3T4 S4T1 S4T2 S4T3 S4T4 rH CM rH rH rH ro CM rH CM CJl CM Acer laurinum Aceraceae cr. rH ro rH Acronychia trifoliata Rutaceae CO rH CM rH Actinodaphne sp. Lauraceae rH LO •^r rH o LO ro rH rH rH QO CM CM Adinandra javanica Theaceae CM rH rH Archidendron sp. Fabaceae CM rH O ro Ardisia sp. Myrsinaceae CM LT> • rH rH CM cn rH rH Arytera litoralis Sapindaceae r~ rH Atalantia sp. Rutaceae cr, rH CM r- rH CM rH o rH r- rH Buchanania arborescens Anacardiaceae rH Canthium sp. Rubiaceae CO CM Celtis tetandra Ulmaceae VO rH CM rH rH ro ro in CM Chionanthus ramiflorus Oleaceae rH rH lO rH Clethra canescens Theaceae VD CM CO rH rH CM *a* rH CM rH rH Cordia sp. Borraginaceae rH rH Cryptocarya costata Lauraceae if) 0 rH CM •^r ro CM ro rH Cryptocarya densiflora Lauraceae CM rH -a* Dacrycarpus imbricatus Podocarpaceae rH ro rH ro Decaspermum fruitcosum Myrtaceae CM rH CM rH Dysoxylum nutans Meliaceae r~ lO CM VD rH rH lO CM ro r- rH ro CTl CTl r- r- TP r- CM CM o ro rH rH CM 00 CM 00 ' rH rH TP CTlC M rH rH CTi ro LO 00 VD in m rH VD rH tH TP CM rH CM rH CM VD TT rH rH CM TP O TP CM LO rH TP rH m 00 TP rH CM CM rH . m rH CO 00 rH TT ro rH tH CM ro CM CM ro ro ro lO rH. rH CM rH CM CO ro rH CM VD . ro LO CM CM CM TP CM CM rH rH TT CM CM rH rH rH ro ro rH 00 CM rH CM rH LO ro. CM ro CM CO CM CM TT rH ro rH ro. CM ro rH rH CM ro m CM CM rH CM TP rH lO CM r- ro in ro CM VD rH rH rH VD rH rH • VD CM CM rH VD LO ro rH rH TP rH rH rH o CM rH rH VD VD • CM TP rH rH rH CM rH rH m rH rH rH ro TP to m rH r— rH rH CTl rH ro O rH ro lO rH o CM CO LO ' rH rH ro . CM CM rH 10 ro TP CM CM CM rH cn rH VD CM VD rH rH rH CM rH rH rH rH rH CO rH rH ro CM rH TP ro TP ro CM ro Sapotacea e Sterculiacea e Sapindacea e Lauracea e Euphorbiacea e Euphorbiacea e Solanacea e Sabiacea e . Sabiacea e Lauracea e Proteacea e Lauracea e Lauracea e Lauracea e Euphorbiacea e Apocynacea e Icacinacea e Saxifragacea e Lauracea e Magnoliacea e Magnoliacea e . • Melastomatacea e . - Loganiacea e Euphorbiacea e Theacea e Tiliacea e Vitacea e . Urticea e . Clusiacea e Clusiacea e Myrtacea e Oleacea e Aquifoliacea e Araliacea e Pagiantha sphaerocarpa Palaquium sp . Omalanthus gigantheus Omalanthu s populneu Neolitsea sp . Neolitsea cassiaefolia• TI ex•odor a ta - Jte a macrophylla Litsea resinosa Li tsea sp . - " , ' •. Lycianthes sp . Gordonia excelsa. Grewia glabra Leptospermu m flavescens Leucosyeke capitellata Lindera polyantha Litsea diversifolia Meliosma pinnata Meliosma symplicifolia Melochia umbellata Mischocarpus sundaicus Gehiostoma rupestre Glochidion philippicum Gomphandra mappioides Leea indica • Magnolia candolHi Manglietia glauca Melastom a sylavaticum Garcinia celebica Garcinia spl . Gastonia papuana Helicia cf. seratta Macaranga tanarius' Fraxinus griffithii 130 CO rH m ro CO rH ro rH CM rH rH rH CM CM ro rH ro rH r- ro vO m rH CM ro o rH 00 rH CM rH o~» rH rH rH rH ro ro rH LO rH ro iO m -a* rH rH CM O CM rH KD rH ro rH CM CM LO CM rH CM rH CM T 00 ro rH o rH r- CO CM r- r- ro ro vD LO rH CM ro CM •rr CM ro rH vO rH CM rH ro •^r CM 00 CM 00 m cr» CM ro rH CM tr. rH ro CM ro Ot ro rH rH ro ro CM iO \D rH T . '3' CM rH CM rH CM CM rH r~ rH CM T ro o rH •*r ro o CM rH ro CM ro rH ro rH rH rH TJ- . rH rH CM rH lO rH O rH rH ro ro Ol CM rH CM CM rH rH ro ro rH r- CM CM rH iO CM" rH CM ro LO rH ro ro •CM rH rH rH rH rH m LO CM CM rH T r- CO rH CM ro r- CM CM ro ro r- ro CM rH ro rH LOZ fH ro rH LO •^r r- rH ro CO rH in t— ro rH ro rH ro l> CM- r- T m ro CM CM vO ro o rH CM rH ro r- rH tN CM rH rH CM o IT- o rH CD o CM rH rH ro CM m rH CM CM CM o\ CM ro LO ro rH ro rH LO ro ro O r- rH o rH iO rH 00 cn rH CM cn rH CSJ ,CM T CM ro rH rH ro rH ro 00 rH r- CM ro rH ro CM rH T ' m rH rH rH CM r- CM ro . T rH r- rH rH CM CM o rH CM Podocarpacea e Podocarpacea e Symplocacea e Symplocacea e Staphyleaceae - Caprifoliacea e Cunoniacea e Rubiacea e Pittosporacea e Saxifragacea e Sapotacea e Sarcospermacea e Saurauiacea e Euphrbiacea e Ulmacea e - Sapotacea e Rubiacea e Rosacea e Rosacea e Rhamnacea e Myrtacea e Myrtacea e Lauracea e Lauracea e Lauracea e Rosacea e Rosacea e Myrtacea e Asteracea e Rubiacea e Araliacea e d IQ E 'H tr. >, N Tota l stem s Tota l specie s Trem a orien taJ is Turpinia sphaerocarpa Vernonia arborea Viburnum coriaceum Syzygium lineata Syzyqium spicata iVeinmannia blumei Wendlandia cf. rufescens Saurauia verheijenii Sauropus androgynus Schefflera sp . Symplocos cochinchimensis Symplocos lucida Sarcosperma paniculata Podocarpus amarus Podocarpus neriifolius Polyosma integrifolia Po.uteri a sp . Prunus arborea Prunus wallaceana Phamnus nepalensis Photinia sp ; Pittosporum moluccanum Planchonella obovata Plectronia didyma Persea excelsa Perse a sp . Phoebe cf. tenuifolia Photinia integrifolia Pavett a sp .