A Vegetation Classification of the Nama Karoo Dwarf Shrub Savanna in South Central Namibia

A vegetation classification of The Nama Karoo Dwarf Shrub savanna in South Central Namibia

Tukaleni Nabot Mbeeli (216036275)

Thesis submitted in partial fulfillment of the requirements for the degree of Master in Natural Resources Management at the Namibia University of Science and Technology

Supervisor: Dr. Ben Strohbach (Namibia University of Science and Technology)

October 2018

Declaration

I, Tukaleni Nabot Mbeeli, hereby declare that the work contained in the thesis entitled: A vegetation classification of The Nama Karoo Dwarf Shrub savanna in South Central Namibia is my own original work and that I have not previously in its entirety or in part submitted it at any university or higher education institution for the award of a degree.

Signature:………………………………………………. Date: …………………………….

Retention and Use of Thesis

I, Tukaleni Nabot Mbeeli, being a candidate for the degree of Master in Natural Resources Management accept the requirements of the Namibia University of Science and Technology relating to the retention and use of theses deposited in the Library and Information Services.

In terms of these conditions, I agree that the original of my thesis deposited in the Library and Information Services will be accessible for purposes of study and research, in accordance with the normal conditions established by the Librarian for the care, loan or reproduction of theses.

Signature:………………………………………………. Date: …………………………….

Dedication I am dedicating this thesis to five beloved people who have meant and continue to mean so much to me. They have been my pillars of strength and continue to support, motivate and encourage me throughout the journeys I embark on.

First and foremost, to my mother Selma Mbeeli who has played an immense role to motivate and taught me the value of hard work. You single-handedly spearheaded my academic and professional career. Thank you so much for all the lessons learnt and sacrifices in making sure I get the best education.

Secondly, my father Moses Mbeeli Snr. who raised me and groomed me to be the young man that I am today. I appreciate you and your struggles did not go unnoticed.

Next, my brother Sakaria BigBoss Mbeeli who played the role of deputy parent at a young age. You were forced to provide from a young age even when you had little to nothing. You are highly appreciated.

I also want to mention my brother Moses Mbeeli Jr. who has defeated the odds by proving that hard work always pays off and the value of never giving up. You were the driving force behind never giving up.

Last but not least I am dedicating this to Taleni Thomas for all the love and affection you have shown me through this. All the encouragement and support you have served are highly appreciated.

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Acknowledgements First and foremost I would like to extend my utmost gratitude to my supervisor Dr. Ben Strohbach for his academic guidance as my supervisor and mentor throughout the course of this research. I am grateful for the opportunity to work with such an academic from the onset of proposal writing, all the way through to data collection, analysis and write up of the report. I would also like to extend my gratitude to Ms. Johanna Nghishiko for assistance during field data collection, I have learned a lot from Ms. Nghishiko by being my “walking-talking” field guide. I am thankful to Leena Naftal, Emma Shidolo, Visto Amputu, Nahas Angula Enkono, Tertu Iileka, Roxanne Godenschweig, John Mendelsohn, Elizabeth Lukas, all my friends and everyone that provided assistance while conducting my research on different stages. I am also grateful for the funding provided by the Southern African Science Service Centre for Climate Change and Adaptive Land Management (SASSCAL) covering the whole research project and tuition fees.

Table of Contents Declaration ...... i Retention and Use of Thesis ...... ii Dedication ...... iii Acknowledgements ...... iv List of Figures ...... vii List of Acronyms and Softwares ...... xii Abstract ...... 1 Chapter 1: Introduction ...... 2 1.1 Background ...... 2 1.2 Literature review ...... 3 1.3 Research Aim and Objective ...... 6 1.3.1 Specific Objectives ...... 6 1.4 Nomenclature ...... 6 Chapter 2: Study Area ...... 7 2.1 Location and Size ...... 7 2.2 Climate...... 8 2.3 Flora and Fauna ...... 9 2.4 Geology and Soils ...... 9 Chapter 3: Methods ...... 10 3.1 Introduction and Motivation ...... 10 3.2 Survey Method ...... 10 3.3 Data Analysis ...... 11 3.3.1 Multivariate Statistics (Classification) ...... 11 3.3.2 Multivariate Statistics (Environmental Gradients- Ordinations) ...... 12 3.3.3 Descriptive Statistics...... 13 3.3.4 Suitability and Sensitivity Indices ...... 13 Chapter 4: Results ...... 15 4.1 Results Overview ...... 15 4.2 Vegetation Descriptions ...... 18 4.3 Tetragonia schenkii―Tamarix usneoides Alliance ...... 28 4.3.1 Association 1.1: Neoluederitzia sericeocarpa―Lycium bosciifolium ...... 34 4.3.2 Association 1.2 Salsolo―Tetragonietum schenkii sensu Strohbach and Jankowitz (2012) .. 35 4.3.3 Association 1.3 Lycium bosciifolium ―Tamarix usneoides ...... 36 4.4 Cryptolepis decidua ―Salsola Alliance ...... 37 4.4.1 Vegetation unit 2.1 Euphorbia―Salsola ...... 43 4.4.2 Association 2.2 Cryptolepis decidua―Salsola ...... 43 4.4.3 Association 2.3 Tetragonia schenkii ―Acacia nebrownii ...... 44 4.5 Zygophyllum microcarpum―Rhigozum trichotomum Alliance ...... 45

4.5.1 Association 3.1 Stipagrostis ciliata―Rhigozum trichotomum ...... 51 4.5.2 Association 3.2 Zygophyllum microcarpum―Rhigozum trichotomum ...... 52 4.5.3 Association 3.3 Cryptolepis decidua―Rhigozum trichotomum ...... 53 4.6 Catophractes alexandrii―Lycium bosciifolium Alliance ...... 54 4.6.1 Association 4.1 Euphorbia gregaria―Rhigozum trichotomum ...... 64 4.6.2 Association 4.2 Catophractes alexandri―Lycium bosciifolium ...... 65 4.6.3 Association 4.3 Acacia mellifera―Catophractes alexandri ...... 66 4.6.4 Association 4.4 Acacia nebrownii―Lycium bosciifolium ...... 67 4.6.5 Association 4.5 Tetragonia schenkii―Rhigozum trichotomum ...... 68 4.6.6 Association 4.6 Acacia karroo―Lycium bosciifolium ...... 69 4.6.7 Association 4.7 Parkinsonia africana―Rhigozum trichotomum ...... 70 4.7 Environmental Gradients ...... 72 4.8 Utilisation Potential of the Vegetation Types ...... 79 4.8.1 Suitability index for animal husbandry ...... 80 4.8.2 Ecological Sensitivity of the Vegetation ...... 86 Chapter 5: Discussion ...... 92 5.1 Phytosociology methods ...... 92 5.2 Ordinations ...... 92 5.3 Vegetation description: patterns and relationships ...... 93 5.3.1 Comparison to other vegetation surveys ...... 94 5.3.2 Mapping of described units ...... 95 Chapter 6: Conclusion ...... 96 References ...... 97 Appendix 1 Annotated species list for The Nama Karoo Dwarf Shrub savanna in South Central Namibia 101 Appendix 2 Field Sheet for Data Collection ...... 115

List of Figures Figure 1: Location of the surveyed area in the Nama Karoo Dwarf Shrub savanna of South Central Namibia (ArcMap) ...... 7 Figure 2: Weather data for Nico weather station south of Mariental (Source: SASSCAL WeatherNet) ..... 8 Figure 3: Weather data for Gellap Ost weather station west of Keetmanshoop (Source: SASSCAL WeatherNet) ...... 8 Figure 4: Crispness scores for Classification of four Higher Alliances ...... 19 Figure 5: Dendrogram of the four higher Alliance ...... 19 Figure 6: The average total vegetation cover of the four Alliances with standard error bars ...... 23 Figure 7: The average species richness of the four Alliances with standard deviation error bars ...... 23 Figure 8: Box and Whisker plot of percentage growth form cover for Tetragonia schenkii―Tamarix usneoides Alliance ...... 24 Figure 9: Tetragonia schenkii―Tamarix usneoides Alliance ...... 24 Figure 10: Box and Whisker plot of percentage growth form cover for Cryptolepis decidua―Salsola Alliance ...... 25 Figure 11: Cryptolepis decidua―Salsola Alliance ...... 25 Figure 12: Box and Whisker plot of percentage growth form cover for Zygophyllum microcarpum―Rhigozum trichotomum Alliance ...... 26 Figure 13: Zygophyllum microcarpum―Rhigozum trichotomum Alliance ...... 26 Figure 14: Box and Whisker plot of percentage growth form cover for Catophractes alexandri―Lycium bosciifolium Alliance ...... 27 Figure 15: Catophractes alexandri―Lycium bosciifolium Alliance ...... 27 Figure 16: Crispness scores of classification for further splitting of Tetragonia schenkii―Tamarix usneoides Alliance ...... 28 Figure 17: Dendrogram of the 3 Associations from Tetragonia schenkii―Tamarix usneoides Alliance .. 29 Figure 18: The average total vegetation cover of the 3 associations of Tetragonia schenkii―Tamarix usneoides Alliance with standard error bars ...... 31 Figure 19: The average species richness of the 3 Associations of Tetragonia schenkii―Tamarix usneoides Alliance. With standard deviation error bars ...... 32 Figure 20: Box and Whisker plot of percentage growth form cover for Neoluederitzia sericeocarpa―Lycium bosciifolium Association 1.1 ...... 32 Figure 21: Box and Whisker plot of percentage growth form cover for Salsolo―Tetragonietum schenkii Association 1.2 ...... 33 Figure 22: Box and Whisker plot of percentage growth form cover for Lycium bosciifolium―Tamarix usneoides Association 1.3 ...... 33 Figure 23: Neoluederitzia sericeocarpa―Lycium bosciifolium Association ...... 34

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Figure 24: Salsolo―Tetragonietum schenkii Association ...... 35 Figure 25: Salsolo―Tetragonietum schenkii Association ...... 36 Figure 26: Tamarix usneoides―Lycium bosciifolium Association ...... 37 Figure 27: Crispness scores of Classification for further splitting of Cryptolepis decidua ―Salsola Alliance 2 ...... 38 Figure 28: Dendrogram of classification for Cryptolepis decidua ―Salsola Alliance 2 ...... 38 Figure 29: The average total vegetation cover of the 3 Associations of Cryptolepis decidua ―Salsola Alliance 2 with standard error bars ...... 41 Figure 30: The average species richness of the 3 Associations of Cryptolepis decidua ―Salsola Alliance 2 with standard deviation error bars ...... 41 Figure 31: Box and Whisker plot of percentage growth form cover for Euphorbia―Salsola vegetation unit 2.1 ...... 42 Figure 32: Box and Whisker plot of percentage growth form cover for Cryptolepis decidua―Salsola Association 2.2 ...... 42 Figure 33: Box and Whisker plot of percentage growth form cover for Tetragonia schenkii―Acacia nebrownii Association 2.3 ...... 43 Figure 34: Klein Vaalgras area picture. Association 2.2 Cryptolepis decidua―Salsola ...... 44 Figure 35: Acacia nebrownii―Tetragonia schenkii Association ...... 45 Figure 36: Crispness scores of classification for further splitting of Zygophyllum microcarpum―Rhigozum trichotomum Alliance ...... 46 Figure 37: Dendrogram for classification of Zygophyllum microcarpum―Rhigozum trichotomum Alliance ...... 46 Figure 38: The average vegetation cover of the 3 Associations of Zygophyllum microcarpum―Rhigozum trichotomum Alliance with standard error bars ...... 49 Figure 39: The average species richness of the 3 Associations of Zygophyllum microcarpum―Rhigozum trichotomum Alliance. Error bars indicate standard deviation ...... 49 Figure 40: Box and Whisker plot of percentage growth form cover for Stipagrostis ciliata―Rhigozum trichotomum Association ...... 50 Figure 41: Box and Whisker plot of percentage growth form cover for Zygophyllum microcarpum―Rhigozum trichotomum Association ...... 50 Figure 42: Box and Whisker plot of percentage growth form cover for Cryptolepis decidua―Rhigozum trichotomum Association ...... 51 Figure 43: Stipagrostis ciliata―Rhigozum trichotomum Association ...... 52 Figure 44: Zygophyllum microcarpum―Rhigozum trichotomum Association ...... 53 Figure 45: Cryptolepis decidua―Rhigozum trichotomum Association ...... 54

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Figure 46: Crispness of Classification for further splitting of Catophractes alexandri―Lycium bosciifolium Alliance ...... 55 Figure 47: Dendrogram for classification of Catophractes alexandri―Lycium bosciifolium Alliance ...... 55 Figure 48: The average total vegetation cover of the 7 Associations of Catophractes alexandrii―Lycium bosciifolium Alliance with standard error bars ...... 59 Figure 49: The average species richness of the 7 Associations of Catophractes alexandrii―Lycium bosciifolium Alliance. Error bars indicate standard deviation ...... 59 Figure 50: Box and Whisker plot of percentage growth form cover for Euphorbia gregaria―Rhigozum trichotomum Association ...... 60 Figure 51: Box and Whisker plot of percentage growth form cover for Catophractes alexandri―Lycium bosciifolium Association ...... 60 Figure 52: Box and Whisker plot of percentage growth form cover for Acacia mellifera―Catophractes alexandri Association ...... 61 Figure 53: Box and Whisker plot of percentage growth form cover for Acacia nebrownii―Lycium bosciifolium Association ...... 62 Figure 54: Box and Whisker plot of percentage growth form cover for Tetragonia schenkii―Rhigozum trichotomum Association ...... 62 Figure 55: Box and Whisker plot of percentage growth cover for Acacia karroo―Lycium bosciifolium Association ...... 63 Figure 56: Box and Whisker plot of percentage growth form cover for Parkinsonia africana―Rhigozum trichotomum Association ...... 64 Figure 57: Euphorbia gregaria―Rhigozum trichotomum Association ...... 65 Figure 58: Catophractes alexandri―Lycium bosciifolium Association ...... 66 Figure 59: Acacia mellifera―Catophractes alexandrii Association ...... 67 Figure 60: Acacia Nebrownii―Lycium bosciifolium Association ...... 68 Figure 61: Tetragonia schenkii―Rhigozum trichotomum Association ...... 69 Figure 62: Acacia karroo― Lycium bosciifolium Association ...... 70 Figure 63: Parkinsonia africana―Rhigozum trichotomum Association ...... 71 Figure 64: The Detrended Correspondence Analysis ordination diagram of 750 relevés surveyed in the Nama Karoo, south-central Namibia...... 72 Figure 65: Detrended Correspondence Analysis ordination diagram of 750 relevés showing an overlap between alliances ...... 73 Figure 66: The Detrended Correspondence Analysis ordination diagram of 57 relevés of the three associations of Tetragonia schenkii―Tamarix usneoides Alliance 1 ...... 74 Figure 67: The Detrended Correspondence Analysis ordination diagram of 112 relevés of Cryptolepis decidua―Salsola Alliance 2 associations with dominant environmental parameters ...... 75

Figure 68: The Detrended Correspondence Analysis ordination diagram of Cryptolepis decidua―Salsola alliance 2 displaying landscape type on Axis 1 and Axis 2 ...... 76 Figure 69: The Detrended Correspondence Analysis ordination diagram of 244 relevés for associations of Zygophyllum microcarpum―Rhigozum trichotomum alliance 3 ...... 77 Figure 70: The Detrended Correspondence Analysis ordination diagram of 437 relevés for associations of Catophractes alexandri―Lycium bosciifolium alliance 4 ...... 78 Figure 71: Graphical representation of how various habitat and compositional characteristics of the vegetation contribute towards the suitability rating (for livestock farming) of sixteen vegetation associations (Habitat Suitability)...... 81 Figure 72: Graphical representation of how various habitat and compositional characteristics of the vegetation contribute towards the suitability rating (for livestock farming) of sixteen vegetation associations (Structural Suitability) ...... 82 Figure 73: Graphical representation of how various habitat and compositional characteristics of the vegetation contribute towards the suitability rating (for livestock farming) of sixteen vegetation associations (Compositional Suitability) ...... 83 Figure 74: Graphical representation of how various habitat and compositional characteristics of the vegetation contribute towards the suitability rating (for livestock farming) of sixteen vegetation associations (Combined Suitability) ...... 84 Figure 75: Graphical representation of how various diversity and ecosystem functional characterisitcs of the vegetation contribute towards the ecological sensitivity of sixteen vegetation associations within the Nama Karoo of south-central Namibia (Sensitivity due to diversity) ...... 87 Figure 76: Graphical representation of how various diversity and ecosystem functional characterisitcs of the vegetation contribute towards the ecological sensitivity of sixteen vegetation associations within the Nama Karoo of south-central Namibia (Sensitivity due to ecosystem functionality) ...... 88 Figure 77: Graphical representation of how various diversity and ecosystem functional characterisitcs of the vegetation contribute towards the ecological sensitivity of sixteen vegetation associations within the Nama Karoo of south-central Namibia (total sensitivity) ...... 89 Figure 78: Estimated total number of species in each of sixteen association using the Jackknife procedure of species estimation...... 90

List of Tables Table 1: A taxonomic account of plant species recorded in the South Central Nama Karoo of Namibia, indicating the number of genera per family and number of species per genus ...... 15 Table 2: Abridged synoptic table of the vegetation alliances and number of associations under each alliance for the study area. The phi coefficient of the fidelity is presented with percentage frequency as a superscript...... 20 Table 3: Abridged Synoptic table of the vegetation associations under Tetragonia schenkii―Tamarix usneoides Alliance with percentage frequency and modified fidelity index phi coefficient...... 29 Table 4: Abridged Synoptic table of the vegetation associations under Cryptolepis decidua―Salsola alliance with percentage frequency and modified fidelity index phi coefficient...... 39 Table 5: Abridged Synoptic table of the vegetation associations under alliance Zygophyllum microcarpum―Rhigozum trichotomum with percentage frequency and modified fidelity index phi coefficient...... 47 Table 6: Abridged Synoptic table of the vegetation associations under alliance Catophractes alexandri- Lycium bosciifolium with percentage frequency and modified fidelity index phi coefficient...... 56 Table 7: Factors influencing the suitability of sixteen associations within the Nama Karoo of south- central Namibia for livestock farming ...... 80 Table 8: Factors influencing the ecological sensitivity of sixteen associations within the Nama Karoo of south-central Namibia ...... 86

List of Acronyms and Softwares CA Correspondence Analysis DCA Detrended Correspondence Analysis GIS Global Information Systems GPS Global Positioning System NMS Non-metric Multidimensional Scaling RA Reciprocal Averaging TWINSPAN Two-Way Indicator Species Analysis WIND National Herbarium of Namibia

JUICE ― A WINDOWS application for editing, classifying and analyzing large phytosociological data (Tichý 2002) PC-ORD― A WINDOWS programme for multivariate analysis of ecological data entered in spreadsheets (Peck 2010). TurboVeg― A programme designed for capture and storage of vegetation data (relevés) (Hennekens and Schaminée 2001).

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Abstract The study was conducted in the south-central part of Namibia which has a vegetation which belongs to the Nama Karoo biome. The Nama Karoo biome covers about 607 000 km² of southern Africa, located on the central plateau of South Africa and Namibia. It occupies most of the interior of the western half of South Africa and extends into the southern interior of Namibia. This study aims to contribute towards a data deficiency that exists on plot based surveys in the country, and be aligned with the Vegetation Survey of Namibia’s ultimate goal of mapping the vegetation of the entire country. The vegetation of the central Nama Karoo was classified and described by subjecting 763 relevés to multivariate analysis i.e. classification and ordination using the software JUICE (Tichý) for classifying, and PC-Ord 7 for ordinations. From a modified TWINSPAN classification, refined by Braun-Blanquet procedures, 16 plant communities, which can be grouped into four major plant communities, were identified. A combined synoptic table and crispness score graph was constructed to facilitate the recognition and definition of the plant communities represented by the data set. A classification and description of the major plant communities of higher syntaxa are presented, and these relate to landscape level alliances. Descriptions of the plant communities at associations’ level include characteristic species as well as prominent and less conspicuous species. In addition to the multivariate analysis, some basic statistical analyses were performed on the data collected in this study. The average total vegetation cover and cover per defined layer of each community was determined. The average number of species per 1000 m² of each community was also determined. Suitability and sensitivity indices were calculated for each vegetation community to assess how suitable it is for livestock farming, and its’ ecological sensitivity.

Keywords: Braun-Blanquet, floristic composition, JUICE, PC-Ord, phytosociology, plant communities, TWINSPAN, TurboVeg

Chapter 1: Introduction

1.1 Background

Biodiversity is the variety of all life, from genes to species level (Swingland 2001). This variety of all life is intimately linked to the earth`s climate and inevitably to climate change as it forms the foundations for natural processes that regulate climate. The stability and proper functioning of ecosystems and their services is generally dependent on species diversity and this stability is threatened by the global loss of biodiversity that has become a major concern and has prompted global studies into biodiversity. Namibia is the driest sub-Saharan country and is highly susceptible to climate change, as some unusual weather phenomenon have been reported across the country in the last couple of years (SASSCAL WeatherNet). There is therefore a need to study and understand the biodiversity of Namibia to address impacts of climate change and to document its mapped vegetation in addressing a vegetation data deficiency that can help us mitigate the effects of climate change. Although Namibia has long been a destination for botanists because of its diverse flora, there remains a scarcity in the classification of its vegetation. The first vegetation description of Namibia was published by Giess in 1971 which provided a macro-ecological overview of the vegetation of South-West Africa. This description is still widely used to this day, although Giess himself considered it as preliminary (see Barnard et al. 1998). Burke & Strohbach (2000) have listed numerous studies devoted to the vegetation of Namibia with a limited number dealing with classifications in their review of Vegetation studies in Namibia. Detailed vegetation classifications in various parts of Namibia, for example the Swakop River catchment (Cowlishaw and Davies 1997), and the Naukluft Mountains (Burke 2001), Classification of Nama Karoo vegetation in the Keetmanshoop area have been done but no detailed classification of the vegetation of the Old Nama Karoo has been published (Dorendorf et al. 2010a). People in the South-Central Region of Namibia largely depend on extensive livestock farming for sustainable livelihoods, and are faced with the problem of land degradation, which is common in the whole of southern Africa and particularly in Namibia as a result of over-utilization of arid rangelands (Byers 1997, Darkoh 2009). This makes sustainable use of vegetation in the area very critical for maintaining the natural resources (Mendelsohn 2006). In order to allow for preservation and farming purposes, knowledge on existing vegetation patterns and species composition of vegetation types is crucial. With this regard, vegetation classification is a useful approach and simplifies communication among and between researchers, land managers and conservation practitioners. The very first vegetation map of Southern Africa was done by Pole Evans in 1936 (Pole Evans, 1936), heralding a new era of field work and synthesis that culminated in the production of Acocks` 1956 Veld types map (Mucina and Rutherford 2006). This work laid the foundation for the existence studies related to vegetation in Southern Africa. This was published as the `Preliminary Vegetation Map of Namibia’ in 1971 (Giess 1971, 1998). A decision to further describe vegetation was taken by the then Directorate of

Nature Conservation in their natural parks and game reserves as it was felt Giess’ vegetation map was becoming outdated (Strohbach 2014). Effort has been made in making contributions to the systematic vegetation knowledge base since the 1990’s through joint research taking place between Universities and other institutions. Vegetation in Namibia has been described on a few attempts in the past (Burke and Strohbach 2000b, Strohbach and Petersen 2007, Kangombe 2010, Strohbach et al. 2010, Strohbach and Jankowitz 2012), but to date, the only concise vegetation map of Namibia was produced in the 1970’s based on field observations rather than actual surveys (Giess 1971, 1998), and depicts broad categories at biome rather than landscape level. A national vegetation map and national vegetation database are fundamentally important for environmental planning, conservation management, biodiversity assessment and research in the floristically diverse region of Southern Africa. With this, new vegetation types will need to be defined and previously defined types will need to be redefined as data is continually collected, analyzed, and correlated to close the gap between land-use planning for sustainability and lack of data there-of. This process of continuous data collection and modifying is referred to as successive refinement (or successive approximation) and constitutes a fundamental feature of vegetation classification (Westhoff and Van Der Maarel 1978, Gauch 1982, US Federal Geographic Data Committee 2008).

1.2 Literature review

Phytosociology is a division of botanical science that is concerned with methods of recognizing and defining plant communities (Barbour et al. 1987a, Kent and Coker 2004, Kangombe 2010). These communities form the basis of vegetation mapping and vegetation dynamics. Such investigations enable us to study and understand the relationships between plant species distribution patterns and environmental controls, such that the knowledge of species can be used to infer environmental or substrate conditions (Kent and Coker 2004). Vegetation classification on its own is a major research subject for botanist globally due to its use for vegetation monitoring and land management, despite much controversy regarding e.g. questions of distinct units versus continuous changes in natural vegetation (Mucina 1997). This therefore makes it an important step in understanding and describing the complex relationships between vegetation patterns and environmental parameters. Despite the obvious significance of plant communities in both the ecological sense and in terms of application to environmental management and conservation, the concept or boundaries of a plant communities remain unclear and/or subjective. Two major and contrasting views of the plant community have dominated the ecological literature where plant community ecology is concerned, and these are The Clements` view of the plant community (also known as the organismic concept), and The Gleason’s view of the plant community. The Clements` view of the plant community considers plant communities as clearly recognizable and definable entities, which repeats themselves over space (Kent and Coker 2004). The plant community is

3 viewed as a super-organism, which cannot function without all its organs i.e. species that would define it. This view stresses the dependence of species that define a given community on each other. The basic method of vegetation mapping in which a survey of species abundances should be made on pre- determined quadratic areas to allow community classification is based on this idea of Clements` view of a plant community. The conventional succession theory is supported in this view such that any climax vegetation will return to its climax state after a disturbance has occurred (Mueller-Dombois and Ellenberg 1974, Kent and Coker 2004, Kangombe 2010). Plant communities to be studied in this paper will be based on this concept. Gleason’s view of the plant community regards plant communities to be all plant species distributed as a continuum such that these species respond individually to variation in environmental factors as well as to other factors, which vary continuously in spatial and temporal scales. This concept produces a unique combination of plant species found throughout the world at any given point, meaning that the vegetation is distributed along environmental gradients as a continuum. This approach makes it rather impossible to classify vegetation into groups or distinct communities, which further makes vegetation mapping of such communities difficult. Putting this concept in terms of vegetation dynamics would mean, individual species will respond to a disturbance rather than responding as a ‘community’, hence the individualistic concept (Mueller-Dombois and Ellenberg 1974, Kent and Coker 2004, Kangombe 2010). There are various schools of Phytosociology that exist and are based on the different views of a plant community. One of the most popular is the Zurich-Montpellier School of Phytosociology, established by Professor Braun-Blanquet in 1928 and is based on Clements` view of a plant community. This school has gained considerable popularity over the years in vegetation science because it provides methods for classification of vegetation types that have become commonly used in vegetation mapping. These methods, commonly referred to as Braun-Blanquet classification methods as adapted by the Vegetation Survey of Namibia (Strohbach 2000, 2014), sort floristic data by similarities to assemble a hierarchy of plant communities in a phytosociological table. Furthermore, these methods are based on several concepts and assumptions: - relevè homogeneity, and minimal area for the concept of an association (Werger 1973, Kent and Coker 2004). It is widely accepted and an object of various studies that plot size has an influence on vegetation classifications (Petřík and Bruelheide 2006, Dengler 2009). The most appropriate plot size depends on the vegetation that is being classified and the purpose of classification. The chosen size should be a trade-off between homogeneity in vegetation and representativeness with regard to environmental parameters. Homogeneity increases with smaller plot size, while representativeness increases with larger plot size (Dierschke 1994 in Dorendorf et al. 2010, Otypková and Chytry 2006).

In community ecology, classification is defined as the assignment of entities of a vegetation data set (i.e. relevès or species) to groups based on a given similarity index. These groups are imposed on the data, regardless of the level of homogeneity (Gauch 1982, Kent and Coker 2004). Although this was a manual 4 operation in former times, the invention of computers and new algorithms has allowed for faster and more accurate classifications making the use of vegetation maps very common and much easier in conjunction with other spatial data on GIS packages (van der Maarel and Franklin 2013). To-date, there are various computer software, equipped with numerical methods based on mathematics and statistics for classification purposes that allow scientific conclusions to be derived from vegetation data that are relevant to solving ecological problems in the study of plant communities (Kent and Coker 2004). The vegetation types are then recognised most commonly by species composition or general appearance. Local plant communities can be defined by species presence, with a formal description and classification based on complete floristic composition and relative species abundance (van der Maarel and Franklin 2013). The methods for recognizing and defining plant communities are regarded as methods of classification and the best known, and universally accepted methodology for such floristic descriptions and classification is the Braun-Blanquet approach. The Braun-Blanquet classification system has designated the association as the most basic or fundamental unit of vegetation i.e. a plant community. By definition, an association is thus a plant community type obtained by grouping similar relevés together using species composition as the main criterion. There are different hierarchical levels of vegetation units used by the Braun-Blanquet classification system namely, Class; Order; Alliance; Association; sub-Association; Variant; and Facies in subsequent order (Weber et al. 2000). Higher and lower levels of classification can be recognised within the overall floristic association system depending on the amount of variation between the units. Two or more associations that have major species in common and whose differences are only explained by fine detail may be combined to form an alliance. Similarly, alliances can be pooled to give orders at a higher level; and orders into classes. At lower levels, an association can be sub-divided into sub-associations, which can further be divided into variants and so forth. The Braun-Blanquet classification system allows the entire hierarchy of the vegetation units in a region to be described, and their relationships demonstrated and understood. The allocation of names to vegetation units is based on the concept of syntaxonomy, which is a set of guidelines for naming of communities and other hierarchies under the Braun-Blanquet system, following the international Code of botanical nomenclature (Weber et al. 2000). The nomenclature system of the Zurich-Montpellier method uses names of characterising species and suffixes to denote a community type (Werger 1973, Kent and Coker 2004) and this system was not used for naming the community types identified in this study but however only used as a guideline. It must be noted that a vegetation classification system is not synonymous with a map legend (US Federal Geographic Data Committee 2008). Vegetation classification consists of grouping stands or plots into vegetation, or plant community types (Brohman et al. 2005). Each community type name represents a taxonomic concept with defined limits about which meaningful and reliable statements can be made (Jennings et al. 2006, US Federal Geographic Data Committee 2008). Vegetation mapping can therefore

5 be described as the process of delineating the geographic distribution, extent, and landscape patterns of vegetation types and/or structural characteristics (US Federal Geographic Data Committee 2008). The consistent mapping of vegetation types in the long term requires that a classification be completed first because classification defines the entities to be mapped (Brohman et al. 2005). In turn, mapping and field checking the vegetation types would help to improve the classification concepts. The revision is able to facilitate more effective mapping of vegetation at multiple scales. Due to varying scales of vegetation patterns and technological issues, map units may often include more than one vegetation type at any given level of the hierarchy. The hierarchical set of vegetation types can be used to describe the content of vegetation map units at multiple scales. There is no single methodological formula that is suitable for all possible analyses when doing classifications and interpretations (US Federal Geographic Data Committee 2008). There are a variety of numerical methods available for classification analysis, which includes direct gradient analysis, ordination, and clustering (Gauch 1982, Kent and Coker 1992, US Federal Geographic Data Committee 2008). It would therefore be vital to apply new or modified contemporary methods of vegetation classification for implementing a sound statistical approach, and to explain the rationale for the approach used (US Federal Geographic Data Committee 2008).

1.3 Research Aim and Objective

The overall aim of this study is to classify and describe the present vegetation of The Central Nama Karoo to fill a gap in vegetation data and studies in Namibia. The vegetation description and the data associated with classifying, would address implications caused by the absence of updated vegetation maps and be useful in depicting, and helping understand the causes of vegetation patterns and identify threats to habitats and species as a part of improving conservation planning, natural resource & land management and supporting environmental policy making (Scott et al, 1993; Margules and Pressey, 2000). 1.3.1 Specific Objectives a) To obtain a baseline description on the vegetation types in the south-central Nama Karoo of Namibia. b) To create an annotated plant checklist for the south-central Nama Karoo of Namibia. c) To assess the suitability of the vegetation types in the south-central Nama Karoo of Namibia to livestock farming. d) To assess the ecological sensitivity of the vegetation types in the south-central Nama Karoo.

1.4 Nomenclature

Nomenclature throughout this thesis follows Klaasen and Kwembeya (2013)

Chapter 2: Study Area

The Nama Karoo is a xeric shrubland ecoregion located on the central plateau of South Africa and Namibia. It occupies most of the interior of the western half of South Africa and extends into the southern interior of Namibia. Vegetatively, the Nama Karoo is characterised by chamaephytic- hemicryptophytic co-dominance, i.e. shrubs and grasses make up most of the perennial plant life with trees absent except along watercourses, and forbs only appear after rain (Irish 2008). Climatically, the Nama Karoo is characterised by relatively low summer rainfall of about 50-230 mm per annum, on average (Irish 2008). The year- to- year variability of rainfall is very high in the south and west of Namibia, where years without significant rainfall are normal but become less so towards the north and east of the country. The Succulent Karoo is a widely accepted eco-region and Irish (2008) further goes on to differentiate the Nama Karoo from the Succulent Karoo further south, that receives winter rainfall. He describes the Succulent Karoo as merely the Nama Karoo with winter rainfall making it a habitat with different biota.

Figure 1: Location of the surveyed area in the Nama Karoo Dwarf Shrub savanna of South Central Namibia (ArcMap) 2.1 Location and Size

The study was conducted in the south-central part of Namibia. The study area covers about 38 700 km², extending eastwards on the weissrand from Mariental to Keetmanshoop along the B1 road, and westwards towards Bethanien and Maltahöhe. Mariental is the capital of the Hardap Region, about 300km south of the State Capital Windhoek. Keetmanshoop is the capital of the Karas Region, about

200km south of Mariental and 500km south of Windhoek. Maltahöhe is about 100km west of Mariental, and Bethanien is about 100km west of Keetmanshoop.

2.2 Climate

According to (Mendelsohn et al. 2002) the climate is hot and dry. The average annual temperature is 18ᵒ C to 20 ᵒ C with the hottest month being January (average temperature at 26ᵒ C) and the coldest being July (average temperature of 15ᵒ C). Rain falls mainly between February and April with the average annual rainfall being only 100-150mm and very inconsistent over the years. The dry climate is intensified due to a high level of evaporation, which leads to an average annual water deficit of more than 2500mm (Mendelsohn et al. 2002). (See Figure 2 and Figure 3 for weather data during 2016 surveying period in the Nama Karoo)

Figure 2: Weather data for Nico weather station south of Mariental (Source: SASSCAL WeatherNet)

Figure 3: Weather data for Gellap Ost weather station west of Keetmanshoop (Source: SASSCAL WeatherNet)

2.3 Flora and Fauna

The vegetation of the study area belongs to the Nama Karoo biome, which covers about 607 000 km² of southern Africa (Palmer and Hoffman 1997). The Nama Karoo consists mainly of grasslands and dwarf shrublands, and is thus characterised by hemicryptophytes and chameophytes with the most important plant families being Asteraceae, Poaceae, Aizoaceae, Liliaceae and Scrophulariaceae (Palmer and Hoffman 1997). The Fauna in this biome is species poor but supported vast herds of springbok in the past, which were subsequently reduced by hunting and fencing (source: Namibia’s Second National Biodiversity Strategy and Action Plan 2013-2022, published by MET 2014). The area is now used as farmland mainly for (small stock) meat production in various land tenure forms (commercial, communal, resettlement farms and municipal rangelands).

2.4 Geology and Soils

The study area is mainly covered by flat-lying rock layers of the Nama Group and the Karoo Super group. The Nama Group rocks are formed on the Nama Platform, which spread out on a stable, deeply eroded land surface of the Kalahari Craton at the end of the Pre-cambrian between 650-530 million years ago. The rocks of the Nama Group are divided into three main stratigraphic units; the Kuibis Subgroup, which mainly consists of light quartzites and black limestones; the Schwarzrand Formation, which is chiefly formed of reddish-greyish sandstones and black green shales, and the Fish River Subgroup, which is dominated by red sandstones (Grünert 2000, Mendelsohn et al. 2002). The younger Karoo Supergroup has the Main Karoo Basin formed of shales and sandstones, and Volcanic rocks of Dykes and Sills as stratigraphic units formed between 300-180 million years ago. The study area falls in a zone considered to have a low relative soil fertility, as asserted by Mendelsohn et al. (2002). This excludes the areas around Mariental along the Fish river considered to be of high relative soil fertility and is used for irrigation projects (Mendelsohn et al. 2002). According to Grotehusmann (2006) as cited by Dorendorf et al. (2010), the prevailing soil types in the area are Leptosols, Regosols, Arenosols, Calcisols, Cambisols and Fluvisols. The Leptosols typically form in actively eroding landscapes, especially in the hilly or undulating areas that cover much of southern and northwestern Namibia (Mendelsohn et al. 2002a). These coarse textured soils are characterised by their limited depth caused by the presence of a continuous hard-rock, highly calcareous or cemented layer within 30cm of the surface. The Leptosols are therefore the shallowest soils to be found in Namibia and they often contain much gravel. As a result, their water-holding capacity is low, and vegetation in areas in which they occur is often subject to drought. Rates of water run-off and water erosion can be very high when heavy rains fall. At best the soils can support low densities of livestock and wildlife.

Chapter 3: Methods

3.1 Introduction and Motivation

Vegetation data was collected from February to June during the 2016 rainfall season, where a total of 72.8 mm (Figure 2) of rain was recorded at Nico weather station, and 61.4 mm (Figure 3) of rain recorded at Gellap Ost weather station in the Nama Karoo. The Braun-Blanquet approach to vegetation ecology as described by Mueller-Dombois and Ellenberg (1974); Werger (1974); Westhoff and Van Der Maarel (1978); and adapted by the Vegetation Survey of Namibia project (Strohbach 2014) was used in this study to collect data. This also corresponds to the suggested plot sizes for savanna vegetation (Brown et al. 2013). In arid environments like Namibia, vegetation data collection is best done during the peak of the growing season (Kangombe 2010), which in the study area is generally between January and March. The flowers and fruits are produced during this time while annuals and ephemerals will only grow during this time when sufficient moisture is available. Sampling during this time therefore increases the probability to encounter the true species composition than it would be during the dry season when annuals for instance, mainly only occur as seeds (Kangombe 2010). The nomenclature and arrangement used in this study follows that of Klaassen and Kwembeya (2013).

3.2 Survey Method

A satellite image of the study area was used as a base map to identify what appears to be homogenous on the landscape and guide field surveying. As one of the pre-requisites to the Braun-Blanquet sampling methodology requires homogeneity, vegetation needed to be selected at different sites and a set of relevés sampled from it. However, finding the required homogeneity within the study area proved to be difficult due to the high variation in the landscape and vegetation over small distances especially small shallow streams dissecting the plains and Weissrand vegetation. On the Weissrand, these streams drain into what Mendelsohn et al. (2002) refers to as dolines, defining them as shallow, funnel-shaped depressions into which rainwater drains often along clear drainage lines that converge and overlap with adjacent vegetation. Extensive fencing of large areas and access denial to private lands also made it challenging to sample natural vegetation in the study area. The number of sample plots is determined by the scale of the survey, the variation in the vegetation composition and the accuracy required (Werger 1974, Ellenbroek 1987, Gertenbach 1987, Filmalter 2010). A total of 763 plots were placed out on a randomly stratified basis (Barbour et al. 1987, Strohbach 2001, Filmalter 2010) within representative stands of vegetation so as to exclude as much heterogeneity in terms of floristic composition, structure and habitat as possible. Following the standardized methods for the Namibia Vegetation Survey (Strohbach, 2014; Strohbach, 2001), at each location a sample plot of 20 m X 50 m in size (1000 m²) was laid out using a measuring

10 tape and then assigned a unique number. A species composition inventory of all plant species present in the sample plot was established as the investigator walked through the plot, recording the correct scientific name of the species encountered. Additional habitat description data was also collected from the centre of the plot. These include information such as global positioning system (GPS) data collected with a Garmin e-Trex GPS, exact locality, slope, gradient, landscape type, edaphic features and disturbances for each relevé. A soil sample was also obtained from the centre of each relevé using a soil auger to obtain about 80 grams of soil to be used for soil analysis. The soil data was analysed using a simple hand method to determine the clay content by virtue of its ability to be rolled out into a sausage roll when wet. A scale of 1 to 5 was used, where 1 is very sandy (can’t be rolled into a sausage when wet) and 5 is clayed soil (makes a proper sausage roll without breaking when bent) (McDonald et al. 1998). A cover abundance value was assigned to each species expressed as a percentage of the sample plot taking note of the different height classes for woody species and herbaceous layer. The percentage cover scale used was 0.1% to 100%. A total score was calculated for each relevé by addition of the cover of each species encountered in that relevé. The method applied both physiognomic and floristic characteristics of the vegetation at each relevé during recording on a record entry sheet (Appendix 1). All unknown plant species were given a provisional name, collected and pressed following the standard pressing procedures and collector field notes to enable identification at the National Herbarium of Namibia (WIND).

3.3 Data Analysis

A floristic database was created for capturing the habitat description and vegetation data in TurboVeg (Hennekens and Schaminée 2001), which is a comprehensive data base management system for vegetation data. All vegetation and habitat description data were captured into this database for storage and for export to other programs for analysis. 3.3.1 Multivariate Statistics (Classification) The data were exported from the TurboVeg database into JUICE (Tichý 2002) via a standard XML (Extensible Markup Language) file for classification into vegetation communities (Tichý 2002). JUICE is a multivariate program for statistical analysis using different packages combined, that allows for Cluster Analysis and classification via PC-Ord (McCune et al. 2002); Cocktail (Bruelheide 2000); TWINSPAN (Chytrý 2001); modified TWINSPAN (Roleček et al. 2009); and other statistical proceedings, including routing via R-Package software. The Two-Way Indicator Species Analysis (TWINSPAN) is a method in vegetation ecology where numerical classification represents grouping a set of individual vegetation samples into groups based on their floristic composition. The original TWINSPAN was developed by Hill (1979) and refined by Roleček et al. (2009). The modified TWINSPAN is currently the most widely used technique for polythetic divisive classification (Filmalter 2010, Kangombe 2010). This technique is based on the progressive refinement of

11 a single ordination axis from reciprocal averaging or canonical analysis (Chytrý 2001, Kent and Coker 2004). The classification uses the calculation of species constancy i.e. the number of relevés that a given species occurs, to identify differential species. Differential species are species of medium to low constancy that display a tendency of occurring together in a set of relevés, thus potentially characterising that set of relevés into a group. Sequential sorting of relevés on the basis of species composition, distribution and abundance, allows similar relevés and species to be placed next to each other thus defining different community types (Chytrý 2001, Kent and Coker 2004). During analysis (classification) of the 763 relevés, four cluster groups were created with modified- TWINSPAN as described by Roleček et al. 2009) in Juice (Tichý) on the woody component data only in accordance with the method of synusial classification (Gillet and Julve 2018). This isolated 13 relevés of the 763 relevés as outliers as they had no woody component and clustering was only on 750 relevés. Each cluster group was separately classified in modified TWINSPAN yielding a total of 16 smaller cluster groups under the four major cluster groups. A combined synoptic table and crispness (Botta-Dukát et al. 2005) graph was constructed to facilitate the recognition and definition of plant communities represented in the data set. Vegetation associations could therefore be defined taking into account (a) species occurring in 40 % or more of the relevés in that association, cover not considered, (b) common species which occur with higher cover and (c) subjectively based on investigator’s field notes and knowledge to manually move some relevés between clusters to where they best fit. This was only done when movement of relevés improved the average positive fidelity and the sharpness of the cluster it is being moved to, without significantly affecting the cluster it is being moved from negatively. An increase in the fidelity and sharpness served as an indicator that such a subdivision or relevé sorting is appropriate. Characteristic species were also verified by considering their fidelity values. The concept of fidelity was developed to test a species loyalty to a given set of relevés that set a vegetation unit (Bruelheide 2000). It is important to note that a species of high constancy may not necessarily have the highest degree of fidelity. Diagnostic species have been defined as those species with fidelity value higher than the ‘lower’ frequency threshold (Kent and Coker 2004). A species can therefore be both diagnostic and constant, but the diagnostic species list is given first priority. Dominant species are defined as those species that have cover values higher than the threshold cover (Kent and Coker 2004). 3.3.2 Multivariate Statistics (Environmental Gradients- Ordinations) The soil samples taken for every relevé were analysed for sand, silt and clay content using a basic “feel test” or “home test” of soil features to determine its name according to granulometric composition. This is a method adapted from McDonald et al. (1998) to determine the soil name by wetting a soil sample on the palm of the hand. This is how they were determined:

1- Sandy soils fall to pieces in dry conditions - suppose you tried to form a small hump, sandy loams in wet condition can keep hold of ball shape. 2- Light loams can be rolled out into shape of small “sausage” with diameter of 2 cm which is easily crackled. 3- Medium textured loams easily can be distinguished from heavy ones – the “sausages” of diameter less than 1 cm cannot be rolled out from these soils. 4- For heavy loams such “sausage” can easily be bent into an arc without crackling, but are crackled when bend it into ring shape. 5- For clayed soils, the “sausage” takes shape of ring without crackling, and even it can be tied in a knot. “Sausage” of length 10 cm and of 1,0……0,5 cm diameter prepared from well wetted soil are possible. The soil data together with landscape data (slope class, landscape type, local topography, lithology etc.) combined with rainfall and frost data obtained from Atlas of Namibia (Mendelsohn et al. 2002) were used as environmental variables for a biplot on a Detrended Correspondence Analysis (DCA) (Hill and Gauch 1980), using PC-Ord 7 (McCune et al. 2002, Peck 2010) as a running software, in order to illustrate the dominating environmental gradients. A DCA was chosen because the environmental variables included a lot of null values from present, absent parameters. DCA is not affected by the number of null values between variables, and yielded desired results. 3.3.3 Descriptive Statistics In addition to the multivariate analysis, further descriptive statistical analyses were also performed on the reduced data collected in this study. The average total vegetation cover and cover per defined layer of each cluster was computed in Microsoft Excel. The average number of species per relevé (1000 m²) for each cluster was also determined. It was determined after computing that the average total vegetation cover for the clusters was very high for the Nama Karoo dwarf shrub and the allocation of vegetation cover during surveying might have been exaggerated as there is no reference scale for cover allocation. To overcome the problem, a conversion factor of 0.5 was used to calibrate the data to fall in the range of 10 – 15% cover for the Nama Karoo suggested by Strohbach in line with vegetation cover estimates done in 1996 in the paper “Erosion hazard estimates – modelling the vegetative cover” (Strohbach et al. 1996). 3.3.4 Suitability and Sensitivity Indices The multivariate and descriptive statistics results were combined to illustrate the suitability of the described vegetation types to extensive livestock farming, and the ecological sensitivity of the vegetation. The index used was adapted from Strohbach (2012, 2018) and applied by combining environmental parameters together with a range of additional data extracted from GIS-based data sources via plot positions. The calculations used are described in Strohbach (2012, 2018) as consisting of three sub-indices related to habitat, structure and composition. The habitat sub-index determines plant growth potential, but also some management options and constraints. The structure sub-index is based on the cover of perennial vs. annual grasses, shrubs and trees, as an indicator for ecosystem health. The composition

13 sub-index takes the presence of toxic plants and the palatability of grasses into account. From the sum of these sub-indices, a categorical rating is derived to describe the suitability of the vegetation for extensive livestock husbandry. The sensitivity index was adapted from Strohbach (2012b) as cited in Strohbach (2012a) deriving the conservation value from a set of criteria that includes biodiversity as a sub-index and habitat sensitivity related to landscape data.

Chapter 4: Results

4.1 Results Overview

A total of 763 relevés were sampled from which 305 species were recorded in the entire study area. These recorded species are spread across 50 families and 178 genera. Taxonomically, the area is dominated by families Poaceae which recorded 27 genera, followed by Asteraceae which recorded 22 genera and Fabaceae for which 21 genera were recorded (Table 1)

Table 1: A taxonomic account of plant species recorded in the South Central Nama Karoo of Namibia, indicating the number of genera per family and number of species per genus Family (Number of Genera) Genus (Number of Species) Barleria(4), Blepharis(4), Hypoestes(1), Justicia(2), Monechma(5), Petalidium(1), Acanthaceae (7) Ruellia(1) Aizoon(2), Aptenia(1), Brownanthus(1), Galenia(2), Gisekia(1), Plinthus(1), Sesuvium(1), Aizoaceae(9) Stoeberia(1), Tetragonia(2) Amaranthus(1), Atriplex(1), Celosia(1), Hermbstaedtia(1), Kyphocarpa(2), Leucosphaera(1), Salsola(1), Sericorema(1), Amaranthaceae(9) Suaeda(1)

Anacardiaceae(2) Ozoroa(1), Searsia(1) Gomphocarpus(2), Hoodia(1), Larryleachia(1), Apocynaceae(6) Microloma(2), Tavaresia(1), Cryptolepis(1)

Asparagaceae(3) Asparagus(4), Pseudogaltonia(1), Ledebouria(2)

Asphodelaceae(1) Aloe(2) Aspilia(1), Athanasia(1), Berkheya(1), Calostephane(1), Chrysocoma(1), Conyza(1), Dicoma(4), Emilia(1), Felicia(1), Flaveria(1), Geigeria(3), Helichrysum(1), Kleinia(1), Laggera(1), Nolletia(1), Ondetia(1), Pechuel- Loeschea(1), Pegolettia(1), Platycarphella(1), Asteraceae(22) Pteronia(1), Senecio(1), Tagetes(1)

Bignoniaceae(2) Catophractes(1), Rhigozum(2)

Boraginaceae(3) Heliotropium(4), Trichodesma(1), Wellstedia(1) 15

Family (Number of Genera) Genus (Number of Species)

Brassicaceae(2) Erucastrum(1), Lepidium(1)

Burseraceae(1) Commiphora(2)

Capparaceae(4) Boscia(2), Cadaba(1), Cleome(2), Maerua(1)

Celastraceae(1) Gymnosporia(1)

Cleomaceae(1) Cleome(3) Convolvulus(2), Evolvulus(1), Ipomoea(1), Convolvulaceae(4) Merremia(1) Citrullus(1), Coccinia(2), Corallocarpus(1), Cucurbitaceae(5) Cucumis(2), Kedrostis(1)

Ebenaceae(1) Euclea(2)

Euphorbiaceae(2) Euphorbia(9), Tragia(1) Acacia(8), Adenolobus(1), Albizia(1), Crotalaria(4), Cullen(1), Dichrostachys(1), Indigastrum(1), Indigofera(5), Leobordea(1), Lotononis(1), Melolobium(1), Neorautanenia(1), Otoptera(1), Parkinsonia(1), Prosopis(1), Ptycholobium(1), Requienia(1), Rhynchosia(1), Fabaceae(21) Senna(1), Tephrosia(2), Xerocladia(1)

Geraniaceae(2) Monsonia(1), Sarcocaulon(1)

Lamiaceae(3) Acrotome(1), Leucas(1), Ocimum(1)

Loasaceae(1) Kissenia(1)

Loranthaceae(1) Tapinanthus(1)

Malvaceae(2) Abutilon(1), Hibiscus(2)

Meliaceae(1) Nymania(1)

Molluginaceae(3) Hypertelis(1), Limeum(5), Mollugo(2)

Montiniaceae(1) Montinia(2)

Family (Number of Genera) Genus (Number of Species)

Moraceae(1) Ficus(1)

Nyctaginaceae(1) Phaeoptilum(1)

Papaveraceae(1) Argemone(1)

Pedaliaceae(1) Sesamum(3)

Phyllanthaceae(1) Phyllanthus(1)

Phytolaccaceae(1) Lophiocarpus(1)

Plumbaginaceae(1) Dyerophytum(1) Anthephora(1), Aristida(3), Brachiara(1), Cenchrus(1), Chloris(1), Cynodon(1), Dactyloctenium(1), Digitaria(1), Enneapogon(2), Entoplocamia(1), Eragrostis(7), Fingerhuthia(1), Heteropogon(1), Hyparrhenia(1), Leptochloa(1), Melinis(2), Microchloa(1), Panicum(4), Pennisetum(1), Schmidtia(2), Setaria(1), Stipagrostis(6), Themeda(1), Tragus(4), Poaceae(27) Tricholaena(1), Triraphis(2), Urochloa(1)

Portulacaceae(1) Portulaca(1)

Rhamnaceae(1) Ziziphus(1)

Rubiaceae(1) Kohautia(2)

Rutaceae(1) Thamnosma(1)

Santalaceae(1) Viscum(1)

Sapindaceae(1) Pappea(1) Anticharis(2), Aptosimum(4), Jamesbrittenia(4), Scrophulariaceae(5) Peliostomum(1), Selago(4)

Solanaceae(3) Datura(1), Lycium(4), Solanum(3)

Sterculiaceae(1) Hermannia(8)

Family (Number of Genera) Genus (Number of Species)

Tamaricaceae(1) Tamarix(1)

Tiliaceae(1) Grewia(2)

Urticaceae(1) Forsskaolea(2)

Verbenaceae(2) Chascanum(1), Lantana(1) Neoluederitzia(1), Sisyndite(1), Tribulus(2), Zygophyllaceae(4) Zygophyllum(5)

4.2 Vegetation Descriptions

A classification of floristic data yielded 4 higher order syntaxa, equivalent to Alliances sensu Weber et al. (2000) (Figure 5) which correspond to the broader landscapes of the river valleys associated with the Fish- Lewer- Konkiep River Systems (Tetragonia schenkii―Tamarix usneoides Alliance), the Central Plains (Cryptolepis decidua―Salsola Alliance), the Eastern Weissrand Plateau (Zygophyllum microcarpum―Rhigozum trichotomum Alliance), and the Western Escarpment Zone (Catophractes alexandrii―Lycium bosciifolium Alliance) see (Figure 1). Each Alliance was further classified and yielded smaller vegetation communities which were recognised as associations. There were 16 associations recognised from the 4 higher Alliances. As a distance measure for the classifications, average Sørensen dissimilarity was used together with one pseudo-species cut levels set at zero and a minimum group size of five. For each level of classification, crispness scores (Botta-Dukát et al. 2005) were graphed and used to guide and determine the optimal number of divisions (Figure 4). Although the naming and description of the vegetation units follows standards of the Vegetation Survey of Namibia (e.g. Strohbach & Jankowitz. 2012), no attempt was made to formally name the association according to the International Code of Phytosociological Nomenclature (Weber et al. 2000). The dendrogram of the four classified alliances is presented in Figure 5 below, and followed by the synoptic table of the alliances and the number of associations in each alliance, as identified within the study area, shown in Table 2.

100

30 Average Crispness Value Crispness Average

0 2 3 4 5 6 7 8 9 10 -10 Number of Clusters

Figure 4: Crispness scores for Classification of four Higher Alliances

Cryptolepisdecidua―Salsola

Catophractes alexandri―Lycium bosciifolium Catophractesalexandri―Lycium

Zygophyllum microcarpum―Rhigozum trichotomum Zygophyllum Tetragonia schenkii―Tamarix usneoides schenkii―Tamarix Tetragonia

Figure 5: Dendrogram of the four higher Alliance

Table 2: Abridged synoptic table of the vegetation alliances and number of associations under each alliance for the study area. The phi coefficient of the fidelity is presented with percentage frequency as a superscript.

____ Tetragonia schenkii― Cryptolepis decidua Zygophyllum microcarpum― Catophractes alexandri―

Tamarix usneoides ―Salsola Rhigozum trichotomum Lycium bosciifolium

Rank Alliance 1 Alliance 2 Alliance 3 Alliance 4

No. of relevés 57 112 144 437

No. Of associations 3 3 3 7

Corresponding Associations 1.1-1.3 2.1-2.3 3.1-3.3 4.1-4.7

Tamarix usneoides 63.0 47 --- . --- . --- 1 Acacia karroo 61.4 47 --- 1 --- . --- 1 Tetragonia schenckii 52.7 67 5.1 30 --- 1 --- 7 Acacia tortilis 50.1 33 --- 1 --- . --- 1 Acacia erioloba 43.0 30 --- 1 --- . --- 4 Euclea pseudebenus 37.1 21 --- . --- 1 --- 1 Neoluederitzia sericeocarpa 33.0 14 --- . --- . --- . Ziziphus mucronata 31.7 19 --- 1 --- 1 --- 4 Salsola species --- 18 68.7 87 --- 11 --- 10 Zygophyllum microcarpum --- . --- 7 52.1 48 --- 6 Rhigozum trichotomum --- 11 --- 33 46.7 89 15.1 62 Catophractes alexandri --- . --- 3 --- 8 62.2 57 Boscia foetida s. foetida --- 2 --- 3 --- 18 57.5 62 Lycium bosciifolium 25.8 53 --- 4 --- 4 42.5 66 Acacia mellifera --- 7 --- 2 4.1 17 28.4 31 Acacia senegal --- . --- . --- . 26.5 9 Euphorbia gregaria --- . --- . --- . 20.9 6 Parkinsonia africana --- 5 --- 5 --- 8 18.7 19 Otoptera burchellii --- . --- . --- . 12.5 2 Acacia hereroensis --- . --- . --- . 12.5 2

Grewia flava --- . --- . --- 1 11.8 3 Albizia anthelmintica 2.0 2 --- . --- . 11.5 4 Adenolobus species --- . --- . --- 1 11.1 3 Cadaba aphylla --- 11 --- 1 29.0 39 10.5 26 Monechma species --- . --- 2 12.3 10 9.6 9 Boscia albitrunca --- . --- . 4.2 2 8.8 3 Grewia flavescens --- . --- . --- 1 8.7 2 Dichrostachys cinerea --- . --- . --- . 5.9 1 Commiphora species --- . --- 1 11.4 6 5.6 5 Acacia nebrownii --- 19 16.0 29 --- 3 5.6 22 Acacia hebeclada 3.4 2 --- . --- 1 5.1 2 Lycium cinereum --- . --- . --- . 4.1 1 Aptosimum albomarginatum --- . --- . --- . 4.1 1 Boscia species --- . --- . --- . 4.1 1 Gomphocarpus species --- . --- . --- . 4.1 1 Tetragonia calycina --- . --- . --- . 4.1 1 Neorautanenia species --- . --- . --- . 4.1 1 Gymnosporia senegalensis --- . --- . --- . 4.1 1 Ruellia species --- . --- . --- . 4.1 1 Ipomoea adenioides --- . --- . --- . 4.1 1 Solanum capense --- . --- . --- . 4.1 1 Commiphora dinteri --- . --- . --- . 4.1 1 Lycium horridum --- . --- . --- . 4.1 1 Nymania capensis --- . --- 1 6.1 3 3.8 2 Euphorbia guerichiana --- . --- . 6.2 1 2.6 1 Montinia caryophyllacea --- . --- . 5.6 1 --- 1 Euphorbia virosa --- . --- . 5.6 1 --- 1 Kleinia longiflora --- . --- . 5.6 1 --- 1 Leucosphaera bainesii --- . --- . 7.9 1 --- 1 Aloe littoralis --- . --- . 7.9 1 --- 1 Maerua schinzii --- 2 --- . 13.1 6 --- 3 Pteronia cylindracea --- . 3.1 1 1.5 1 --- 1

Euclea undulata 9.4 2 --- . --- . --- 1 Montinia species --- . 9.5 2 --- . --- 1 Adenolobus garipensis --- . --- . 18.7 7 --- 2 Tetragonia species --- . --- . 9.0 1 --- 1 Ficus species --- . --- . 9.0 1 --- 1 Aloe dichotoma --- . --- . 16.0 5 --- 1 Lycium species 3.9 2 4.1 2 --- . --- 1 Pechuel-Loeschea leubnitziae 10.3 2 --- . --- . --- 1 Commiphora africana --- . --- . 7.2 1 --- . Solanum species --- . --- . 7.2 1 --- . Aloe species --- . --- . 7.2 1 --- . Rhigozum obovatum --- . --- . 7.2 1 --- . Aptenia geniculiflora --- . 8.2 1 --- . --- . Asparagus species --- . 8.2 1 --- . --- . Euphorbia species --- . 15.5 5 --- 1 --- 1 Zygophyllum cretaceum --- . 4.6 1 2.7 1 --- . Sisyndite spartea 12.6 4 --- . --- 1 --- 1 Searsia lancea --- . --- . 12.5 2 --- . Zygophyllum rigidum --- . 18.4 9 --- 3 --- 1 Lycium eenii 11.1 7 8.7 6 --- . --- 1 Stoeberia gigas 14.6 7 --- 3 --- 1 --- 1 Zygophyllum species --- . 26.8 11 --- 1 --- 1 Prosopis species 15.2 9 4.8 5 --- 1 --- 1 Cryptolepis decidua --- . 25.2 23 8.6 15 --- 3

vegetationcover (%) 20

0 Tetragonia Cryptolepis Zygophyllum Catophractes schenkii―Tamarix decidua―Salsola microcarpum―Rhigozum alexandri―Rhigozum usneoides trichotomum trichotomum Alliances

Figure 6: The average total vegetation cover of the four Alliances with standard error bars

(unit) 8

6 Numberofspecies 4

0 Tetragonia Cryptolepis Zygophyllum Catophractes schenkii―Tamarix decidua―Salsola microcarpum―Rhigozum alexandri―Rhigozum usneoides trichotomum trichotomum Alliances

Figure 7: The average species richness of the four Alliances with standard deviation error bars

Trees (>5m)

Tall shrubs (1-5m)

Dwarf shrubs (<1m)

Perennial grasses Growth form Growth

Annual Grasses

Herbs

0 10 20 30 40 50 60 70 80 Percentage cover (%)

Figure 8: Box and Whisker plot of percentage growth form cover for Tetragonia schenkii―Tamarix usneoides Alliance

Figure 9: Tetragonia schenkii―Tamarix usneoides Alliance

Trees (>5m)

Tall shrubs (1-5m)

Dwarf shrubs (<1m)

Perennial grasses Growth form Growth

Annual Grasses

Herbs

0 10 20 30 40 50 60 70 80 Percentage cover (%)

Figure 10: Box and Whisker plot of percentage growth form cover for Cryptolepis decidua―Salsola Alliance

Figure 11: Cryptolepis decidua―Salsola Alliance

Trees (>5m)

Tall shrubs (1-5m)

Dwarf shrubs (<1m)

Perennial grasses Growth form Growth

Annual Grasses

Herbs

0 10 20 30 40 50 60 70 80 Percentage cover (%)

Figure 12: Box and Whisker plot of percentage growth form cover for Zygophyllum microcarpum―Rhigozum trichotomum Alliance

Figure 13: Zygophyllum microcarpum―Rhigozum trichotomum Alliance

Trees (>5m)

Tall shrubs (1-5m)

Dwarf shrubs (<1m)

Perennial grasses Growth form Growth

Annual Grasses

Herbs

0 10 20 30 40 50 60 70 80 Percentage cover (%)

Figure 14: Box and Whisker plot of percentage growth form cover for Catophractes alexandri―Lycium bosciifolium Alliance

Figure 15: Catophractes alexandri―Lycium bosciifolium Alliance

4.3 Tetragonia schenkii―Tamarix usneoides Alliance

The Tetragonia schenkii―Tamarix usneoides river vegetation Alliance of the Fish―Lewer―Konkiep river valleys and landscape System, represented by 57 relevés makes up the riparian vegetation and is characterised by Tamarix usneoides, Tetragonia schenkii, Acacia karroo and Acacia tortilis. The alliance has a vegetation cover of about 54% (Figure 6) and an average species richness of 8 species per 1000 m² (Figure 7). In total 110 species have been observed in this alliance. Structurally, it is a tall open shrubland with a 19% average tall shrub cover of the vegetation cover and a 9% average tree cover of the vegetation cover (Figure 8). The alliance forms a buffer between land and a river or a stream. In the Nama Karoo these rivers or streams are often dry as the area receives little rainfall (Figure 2 and Figure 3) and the riparian vegetation survives by tapping into the underground water along the rivers and streams. The river vegetation alliance was further classified and yielded 3 associations that relate to the riparian woodland vegetation, flood bank vegetation, and lastly hummock dune vegetation.

10 Average Average CrispnessValue

0 2 3 4 5 6 7 8 9 10 Number of Clusters

Figure 16: Crispness scores of classification for further splitting of Tetragonia schenkii―Tamarix usneoides Alliance

Lycium bosciifolium Lycium

―

Tamarixusneoides

―

Neoluederitziasericeocarpa

Lyciumbosciifolium Salsolo―Tetragonietumschenkii

Figure 17: Dendrogram of the 3 Associations from Tetragonia schenkii―Tamarix usneoides Alliance

____

Table 3: Abridged Synoptic table of the vegetation associations under Tetragonia schenkii―Tamarix usneoides Alliance with percentage frequency and modified fidelity index phi coefficient.

Neoluederitzia Salsolo―Tetragonietum Lycium bosciifolium―Tamarix

Association name sericeocarpa―Lycium 1 bosciifolium 2 schenkii 3 usneoides No. of relevés 12 20 25

Neoluederitzia sericeocarpa 58 64.5 5 --- . --- Acacia nebrownii 67 64.2 5 --- 8 --- Acacia erioloba 75 55.1 25 --- 12 --- Cadaba aphylla 42 52.1 . --- 4 --- Tetragonia schenckii 25 --- 100 55.8 60 --- Salsola species . --- 40 46.3 8 --- Tamarix usneoides . --- 30 --- 84 67.0 Acacia tortilis 17 --- 10 --- 60 48.5 Acacia karroo 25 --- 30 --- 72 42.5

Acacia mellifera . --- . --- 16 33.6 Lycium bosciifolium 75 --- 15 --- 72 25.5 Ziziphus mucronata 25 --- . --- 32 23.4 Euclea pseudebenus . --- 20 --- 32 --- Albizia anthelmintica . --- . --- 4 --- Boscia foetida 8 --- . --- . --- Euclea undulata . --- 5 --- . --- Acacia hebeclada 8 --- . --- . --- Maerua schinzii 8 --- . --- . --- Prosopis species 8 --- . --- 16 --- Sisyndite spartea . --- . --- 8 --- Rhigozum trichotomum 25 --- 10 --- 4 --- Parkinsonia africana 17 --- . --- 4 --- Lycium eenii 17 --- . --- 8 --- Lycium species . --- 5 --- . --- Stoeberia gigas . --- 15 --- 4 ---

------Pechuel-Loeschea leubnitziae . 5 . ---

30 Vegetation cover (%) cover Vegetation

0 NeoluederitziaAssociationsericeocarpa 1 ― SalsoloAssociation―Tetragonietum 2 LyciumAssociation bosciifolium 3 ― Lycium bosciifolium schenkii Tamarix usneoides

Associations

Figure 18: The average total vegetation cover of the 3 associations of Tetragonia schenkii―Tamarix usneoides Alliance with standard error bars

Number of species Numberspecies of (unit) 6

0 NeoluederitziaAssociationsericeocarpa 1 ― AssociationSalsolo―Tetragonietum 2 LyciumAssociation bosciifolium ―3 Lycium bosciifolium schenkii Tamarix usneoides

Associations

Figure 19: The average species richness of the 3 Associations of Tetragonia schenkii―Tamarix usneoides Alliance. With standard deviation error bars

Trees (>5m)

Tall shrubs (1-5m)

Dwarf shrubs (<1m)

Perennial grasses Growth form Growth

Annual Grasses

Herbs

0 10 20 30 40 50 60 70 80 Percentage cover (%)

Figure 20: Box and Whisker plot of percentage growth form cover for Neoluederitzia sericeocarpa―Lycium bosciifolium Association 1.1

Trees (>5m)

Tall shrubs (1-5m)

Dwarf shrubs (<1m)

Perennial grasses Growth form Growth

Annual Grasses

Herbs

0 10 20 30 40 50 60 70 80 Percentage cover (%)

Figure 21: Box and Whisker plot of percentage growth form cover for Salsolo―Tetragonietum schenkii Association 1.2

Trees (>5m)

Tall shrubs (1-5m)

Dwarf shrubs (<1m)

Perennial grasses Growthform

Annual Grasses

Herbs

0 10 20 30 40 50 60 70 80 Percentage cover (%)

Figure 22: Box and Whisker plot of percentage growth form cover for Lycium bosciifolium―Tamarix usneoides Association 1.3

4.3.1 Association 1.1: Neoluederitzia sericeocarpa―Lycium bosciifolium

The typicum for this association is relevé 12351, sampled at 26ᵒ 27’ 37” S, 18ᵒ 16’ 06” E on 08 March 2016. The association is represented by 12 relevés and characterised by Neoluederitzia sericeocarpa, Acacia nebrownii, Acacia erioloba and Cadaba aphylla as diagnostic species. Lycium bosciifolium and Stipagrostis namaquensis occur as constant species. The association has a vegetation cover of about 51% as illustrated in Figure 18, and an average species richness of 7.5 species per 1000 m² illustrated in Figure 19. In total 42 species have been observed in this association.

Structurally, about 30% of the vegetation cover is dwarf shrub and a few tall shrub and tree cover of between 5-10% (Figure 20). The unit is essentially found along the river banks that are characteristic and associated but not restricted to Neoluederitzia sericeocarpa which is a near-endemic species found along the Fish River. This species co-occurs with Acacia nebrownii that also has a strong affinity for river banks. Neoluederitzia sericeocarpa was believed to only occur around Seeheim along the Fish River, but new populations have been found north of Seeheim at Geelwater and adjacent tributaries of the Fish River. This then shows the distribution of this restricted range endemic species and new areas where it occurs that were unknown.

Figure 23: Neoluederitzia sericeocarpa―Lycium bosciifolium Association

4.3.2 Association 1.2 Salsolo―Tetragonietum schenkii sensu Strohbach and Jankowitz (2012)

The typicum for this association is relevé 12228, sampled at 26ᵒ 14’ 24” S, 18ᵒ 09’ 27” E on 30 April 2016. The association is represented by 20 relevés and characterised by Tetragonia schenkii and Salsola species as diagnostic species and Tetragonia schenkii being constant and dominant throughout the association. The association has a vegetation cover of about 45% shown in Figure 18, and an average species richness of 6.2 species per 1000 m² shown in Figure 19. In total 33 species have been observed in this association.

Structurally, about 35% of the vegetation is dwarf shrub dominating the unit and about 15 % cover of tall shrubs and few trees (Figure 21). This unit has very little grass cover of less than 5% and more herbs (Figure 12). The unit is described in Strohbach and Jankowitz (2012) as found on hummock dunes that resembles the saline desert and dwarf shrub savanna fringe (sensu Giess 1998) described for the Etosha pan. Hummock dunes are mainly on the far flood banks of wide matured rivers forming these hummocks or on flat “pan-like” areas probably originating from a deflation process (Strohbach and Jankowitz 2012) like the flat area around Berseba that is surrounded by the hummock dune formation.

Figure 24: Salsolo―Tetragonietum schenkii Association

Figure 25: Salsolo―Tetragonietum schenkii Association

The Salsolo―Tetragonietum schenkii association and Neoluederitzia sericeocarpa―Lycium bosciifolium associations could potentially be sub-associations of each other because of their similarities. Although closely related according to species composition, these two syntaxa are recognised as separate associations due to the salt content of the soil as observed in the field. This division conforms to the criteria set by Weber et al. (2000). Neoluederitzia sericeocarpa and Acacia nebrownii can’t grow because of the salt, and they are replaced by Salsola species and Tetragonia schenkii that are salt tolerant.

4.3.3 Association 1.3 Lycium bosciifolium ―Tamarix usneoides The typicum for this association is relevé 12480, sampled at 26ᵒ 05‘ 56“ S, 18ᵒ 13‘ 57“ E on 02 June 2016. The association is represented by 25 relevés and is characterised by diagnostics of Tamarix usneoides and Chloris virgata, and dominated by Stipagrostis namaquensis. The constant species found in this association are Acacia karroo, Lycium bosciifolium, Tetragonia schenkii and Schmidtia kalahariensis. The association has a vegetation cover of about 62% (Figure 18) and a species richness of 11.2 species per 1000 m² shown in Figure 19. A total of 85 species have been observed in this unit. Structurally, the unit is diverse with the mean cover values of each structure almost equal but has a highly variable standard deviation (Figure 22). The tall shrubs dominate the structure and there is about 10% cover of trees and a good cover ratio of herbs and perennial grasses of the total vegetation cover. The trees have deep roots to reach underground water as the dry conditions and unpredictable rainfall of the

Nama Karoo does not guarantee water for these riparian vegetation. This is also to avoid competition with fast growing herbaceous plants found along these river systems.

Figure 26: Tamarix usneoides―Lycium bosciifolium Association

4.4 Cryptolepis decidua ―Salsola Alliance

This alliance of the Central Plains is represented by 112 relevés and is characterised by Salsola species that is also constant throughout the association. The alliance assumes a co-dominance between Cryptolepis decidua, Salsola species and Tetragonia schenkii that can be recognised in the 3 associations identified as they each form part of the naming of each association. The naming of the Alliance is similar to that of Association 2.2 making it the typicum association for this alliance. This Alliance occurs on the central plains of the Nama Karoo. The alliance has an average vegetation cover of 30% displayed in Figure 6, and a total of 110 species has been observed, with an average species richness of 9.7 species per 1000 m² shown in Figure 7. Structurally, the alliance is an open dwarf shrubland with a 20% average dwarf shrub cover of the vegetation cover and a 10% herb cover of the vegetation cover (Figure 12).

Average Average CrispnessValue 6

0 2 3 4 5 6 7 8 9 10 Number of Clusters

Figure 27: Crispness scores of Classification for further splitting of Cryptolepis decidua ―Salsola Alliance 2

Euphorbia―Salsola

Tetragonia schenkii―Acacia nebrownii schenkii―Acacia Tetragonia Cryptolepis decidua―Salsola Cryptolepis

Figure 28: Dendrogram of classification for Cryptolepis decidua ―Salsola Alliance 2

____

Table 4: Abridged Synoptic table of the vegetation associations under Cryptolepis decidua―Salsola alliance with percentage frequency and modified fidelity index phi coefficient.

Association name Euphorbia―Salsola 1 Cryptolepis decidua―Salsola 2 Tetragonia schenkii―Acacia 3 nebrownii No. of relevés 5 63 44

Euphorbia species 100 98.3 . --- 2 --- Cadaba aphylla 20 37.8 . --- . --- Cryptolepis decidua . --- 33 36.6 11 --- Zygophyllum species . --- 17 31.0 2 --- Salsola species 60 --- 95 30.0 77 --- Tetragonia schenckii . --- 2 --- 75 80.2 Acacia nebrownii . --- 8 --- 64 66.0 Rhigozum trichotomum 20 --- 21 --- 52 32.6 Parkinsonia africana . --- . --- 14 30.9 Zygophyllum microcarpum . --- 6 --- 9 --- Lycium eenii . --- 8 --- 5 --- Acacia karroo . --- . --- 2 --- Acacia tortilis . --- . --- 2 --- Montinia species . --- 2 --- 2 --- Acacia erioloba . --- . --- 2 --- Ziziphus mucronata . --- . --- 2 --- Acacia mellifera . --- . --- 5 --- Aptenia geniculiflora . --- . --- 2 --- Prosopis species . --- 6 --- 2 --- Stoeberia gigas 20 --- 3 --- . --- Zygophyllum cretaceum . --- 2 --- . --- Catophractes alexandri . --- 2 --- 5 --- Lycium bosciifolium . --- 3 --- 7 --- Lycium species . --- . --- 5 --- Nymania capensis . --- 2 --- . --- Zygophyllum rigidum 20 --- 11 --- 5 ---

Commiphora species . --- . --- 2 --- Asparagus species . --- . --- 2 --- Pteronia cylindracea . --- . --- 2 --- Boscia foetida . --- . --- 7 --- Monechma species . --- 3 --- . ---

30 Vegetationcover (%)

0 EuphorbiaAssociation―Salsola 4 Cryptolepis Associationdecidua―Salsola 5 Tetragonia schenkiiAssociation―Acacia 6 nebrownii Associations

Figure 29: The average total vegetation cover of the 3 Associations of Cryptolepis decidua ―Salsola Alliance 2 with standard error bars

Numberofspecies (unit) 4

0 Euphorbia―SalsolAssociation 4a CryptolepisAssociation decidua―Salsola 5 TetragoniaAssociation schenkii―Acacia 6 nebrownii Associations

Figure 30: The average species richness of the 3 Associations of Cryptolepis decidua ―Salsola Alliance 2 with standard deviation error bars

Trees (>5m)

Tall shrubs (1-5m)

Dwarf shrubs (<1m)

Perennial grasses Growthform

Annual Grasses

Herbs

0 10 20 30 40 50 60 70 80 Percentage cover (%)

Figure 31: Box and Whisker plot of percentage growth form cover for Euphorbia―Salsola vegetation unit 2.1

Trees (>5m)

Tall shrubs (1-5m)

Dwarf shrubs (<1m)

Perennial grasses Growthform

Annual Grasses

Herbs

0 10 20 30 40 50 60 70 80 Percentage cover (%)

Figure 32: Box and Whisker plot of percentage growth form cover for Cryptolepis decidua―Salsola Association 2.2

Trees (>5m)

Tall shrubs (1-5m)

Dwarf shrubs (<1m)

Perennial grasses Growthform

Annual Grasses

Herbs

0 10 20 30 40 50 60 70 80 Percentage cover (%)

Figure 33: Box and Whisker plot of percentage growth form cover for Tetragonia schenkii―Acacia nebrownii Association 2.3

4.4.1 Vegetation unit 2.1 Euphorbia―Salsola

The Euphorbia – Salsola vegetation unit is a very doubtful unit made up of five relevés and characterised by Euphorbia species and Cadaba aphylla. This unit does not make much ecological sense and following the recommendations of (Weber et al. 2000a) that the description of plant communities based on one or two relevés should be strongly discouraged and regarded as doubtful units. The association has a vegetation cover of 16% displayed in Figure 29, and a species richness of 8 species per 1000 m² shown in Figure 30 . In total, 21 species have been observed on this unit. This association has structurally no trees and tall shrubs but dominated by herbs and some dwarf shrubs in terms of vegetation cover (Figure 31). This association occurs on a dry pan-vlei like patch, east of Goageb.

4.4.2 Association 2.2 Cryptolepis decidua―Salsola

The typicum for this association is relevé 12296, sampled at 25ᵒ 49’ 43” S, 18ᵒ 10’ 46” E on 09 May 2016. The association is represented by 63 relevés and characterised by Cryptolepis decidua and Salsola species that also co-dominate the association. This is the typical association for the alliance as it makes up the naming of the alliance. The unit has a vegetation cover of 32% (Figure 29) and an average species richness of 9 species per 1000 m² (Figure 30). A total of 74 species were observed on this association. Structurally,

43 the association is dominated by herbs (15%) and dwarf shrubs (25% cover) in terms of cover shown in Figure 32. The unit occurs along drainage lines of the Central Plains creating patches and dry swamps and pans. This also includes a pan close to Klein Vaalgras that has visibly a different species of Salsola but could not be properly identified further.

Figure 34: Klein Vaalgras area picture. Association 2.2 Cryptolepis decidua―Salsola

4.4.3 Association 2.3 Tetragonia schenkii ―Acacia nebrownii

The typicum for this association is relevé 12446, sampled at 26ᵒ 04’ 20” S, 18ᵒ 32’ 41” E on 31 May 2016. The association is represented by 44 relevés and characterised by Acacia nebrownii, Tetragonia schenkii, Parkinsonia africana and Rhigozum trichotomum. This association is dominated by Tetragonia schenkii and has a vegetation cover of 31% (Figure 29) and an average species richness of 10.8 species per 1000 m² (Figure 30). A total of 87 species have been observed on this unit. This unit is structurally a tall and dwarf shrub open woodland with 20% dwarf shrub cover and 10% tall shrubs (Figure 33), that is found along shallow streams connecting the Central Plains drainage to the main river systems of the area. Along the flood drainage stands of Acacia nebrownii shrubs with Tetragonia schenkii are found. This unit is not restricted to the Central Plains but also occurs on the far banks of rivers along shallow, small dry washes that feed the rivers. Dwarf shrubs and herbs dominate the vegetation cover structure for this association as shown in Figure 33.

Figure 35: Acacia nebrownii―Tetragonia schenkii Association

4.5 Zygophyllum microcarpum―Rhigozum trichotomum Alliance

This alliance relates to the Eastern Weissrand Plateau and is characterised by Zygophyllum microcarpum and Rhigozum trichotomum that also co-dominates the alliance and are constant throughout. The alliance has a vegetation cover of 26% (Figure 6) and an average species richness of 8.9 species (Figure 7) per 1000 m². In total 114 species have been observed in this alliance. Structurally, the alliance is an open dwarf shrubland with about 20% dwarf shrub cover of the vegetation cover and about 8% cover of perennial grasses and herbs each, of the vegetation cover. Rhigozum trichotomum has displayed strong constancy in the alliance and also constant in the associations that have been distinguished under the alliance. Three associations can be recognised from this alliance.

10 Average Average CrispnessValue

0 2 3 4 5 6 7 8 9 10 Number of Clusters

Figure 36: Crispness scores of classification for further splitting of Zygophyllum microcarpum―Rhigozum trichotomum Alliance

ciliata―Rhigozum trichotomum ciliata―Rhigozum

Stipagrostis

Cryptolepis decidua―Rhigozum trichotomum decidua―Rhigozum Cryptolepis Zygophyllum microcarpum―Rhigozum trichotomum microcarpum―Rhigozum Zygophyllum

Figure 37: Dendrogram for classification of Zygophyllum microcarpum―Rhigozum trichotomum Alliance

____

Table 5: Abridged Synoptic table of the vegetation associations under alliance Zygophyllum microcarpum―Rhigozum trichotomum with percentage frequency and modified fidelity index phi coefficient.

Stipagrostis ciliata―Rhigozum Cryptolepis decidua―Rhigozum Association name 1 Zygophyllum microcarpum―Rhigozum 2 3 trichotomum trichotomum trichotomum No. of relevés 43 57 44

Cadaba aphylla 81 54.8 . --- 48 --- Zygophyllum microcarpum 2 --- 68 32.5 66 28.9 Catophractes alexandri . --- 18 31.1 2 --- Boscia foetida 5 --- 5 --- 48 51.2 Acacia mellifera 9 --- 2 --- 43 46.1 Cryptolepis decidua . --- 7 --- 39 46.1 Lycium bosciifolium . --- . --- 14 30.9 Acacia nebrownii . --- . --- 11 28.1 Monechma species 16 --- 7 --- 7 --- Searsia lancea 7 21.8 . --- . --- Rhigozum trichotomum 84 --- 95 --- 86 --- Boscia albitrunca 2 --- 2 --- 2 --- Parkinsonia africana 19 24.8 5 --- 2 --- Stoeberia gigas 5 --- . --- . --- Rhigozum obovatum . --- . --- 2 --- Adenolobus garipensis 16 22.8 . --- 7 --- Adenolobus species . --- . --- 2 --- Ziziphus mucronata . --- . --- 2 --- Sisyndite spartea . --- . --- 2 --- Grewia flavescens . --- . --- 2 --- Euphorbia guerichiana 2 --- 2 --- . --- Acacia hebeclada . --- . --- 2 --- Aloe species . --- 2 --- . --- Commiphora species 7 --- 5 --- 7 --- Salsola species 14 --- 9 --- 11 ---

Kleinia longiflora . --- 2 --- . --- Prosopis species 2 --- . --- . --- Aloe littoralis . --- . --- 5 --- Euphorbia virosa 2 --- . --- . --- Montinia caryophyllacea . --- 2 --- . --- Commiphora africana 2 --- . --- . --- Euclea pseudebenus . --- . --- 5 --- Zygophyllum cretaceum . --- . --- 2 --- Zygophyllum rigidum . --- 9 24.5 . --- Ficus species 2 --- . --- 2 --- Pteronia cylindracea . --- . --- 2 --- Euphorbia species . --- . --- 2 --- Zygophyllum species . --- 2 --- . --- Tetragonia species 5 --- . --- . --- Grewia flava 2 --- . --- . --- Leucosphaera bainesii 5 --- . --- . --- Aloe dichotoma 2 --- 4 --- 9 --- Nymania capensis . --- 5 --- 2 --- Solanum species 2 --- . --- . --- Maerua schinzii 12 --- . --- 9 --- Tetragonia schenckii . --- . --- 5 ---

30 Vegetation cover Vegetation (%) 20

0 StipagrostisAssociation ciliata 7 ZygophyllumAssociation microcarpum 8 CryptolepisAssociation decidua 9 ― ―Rhigozum trichotomum ―Rhigozum trichotomum Rhigozum trichotomum

Associations Figure 38: The average vegetation cover of the 3 Associations of Zygophyllum microcarpum―Rhigozum trichotomum Alliance with standard error bars

Numberofspecies (unit) 4

0 StipagrostisAssociation ciliata― 7 ZygophyllumAssociation microcarpum 8 CryptolepisAssociation decidua 9― Rhigozum trichotomum ―Rhigozum trichotomum Rhigozum trichotomum

Associations

Figure 39: The average species richness of the 3 Associations of Zygophyllum microcarpum―Rhigozum trichotomum Alliance. Error bars indicate standard deviation

Trees (>5m)

Tall shrubs (1-5m)

Dwarf shrubs (<1m)

Perennial grasses Growthform

Annual Grasses

Herbs

0 10 20 30 40 50 60 70 80 Percentage cover (%)

Figure 40: Box and Whisker plot of percentage growth form cover for Stipagrostis ciliata―Rhigozum trichotomum Association

Trees (>5m)

Tall shrubs (1-5m)

Dwarf shrubs (<1m)

Perennial grasses Growthform

Annual Grasses

Herbs

0 10 20 30 40 50 60 70 80 Percentage cover (%)

Figure 41: Box and Whisker plot of percentage growth form cover for Zygophyllum microcarpum―Rhigozum trichotomum Association

Trees (>5m)

Tall shrubs (1-5m)

Dwarf shrubs (<1m)

Perennial grasses Growthform

Annual Grasses

Herbs

0 10 20 30 40 50 60 70 80 Percentage cover (%)

Figure 42: Box and Whisker plot of percentage growth form cover for Cryptolepis decidua―Rhigozum trichotomum Association

4.5.1 Association 3.1 Stipagrostis ciliata―Rhigozum trichotomum

The typicum for this association is relevé 12275, sampled at 25ᵒ 57’ 06” S, 17ᵒ 52’ 27” E on 07 May 2016. The association is represented by 43 relevés and characterised by Cadaba aphylla, and dominated by Rhigozum trichotomum. These 2 species and Stipagrostis ciliata are also constant throughout the association. The association has a vegetation cover of about 22.5% (Figure 38) and an average species richness of 8.5 species per 1000 m² (Figure 39). In total 89 species were observed on this association. Structurally, dwarf shrubs (20%) dominate the cover and some herbs (10%) as shown in Figure 40. The unit is more concentrated but not restricted to the transitioning between the Weissrand Plateau and the Western Escarpment zone, moving away from the white quartz pebbles and cobbles of the Weissrand that is calcareous towards red sandstones of the Western Escarpment zone.

Figure 43: Stipagrostis ciliata―Rhigozum trichotomum Association

4.5.2 Association 3.2 Zygophyllum microcarpum―Rhigozum trichotomum

The typicum for this association is relevé 12507, sampled at 25ᵒ 44’ 38” S, 18ᵒ 08’ 09” E on 03 June 2016. The association is represented by 57 relevés, characterised and dominated by Zygophyllum microcarpum that is also constant throughout the association. Other constant species include Rhigozum trichotomum, Stipagrostis ciliata, and Enneapogon cenchroides. This association relates to the higher order ranking alliance in terms of characteristic species and dominant species hence the same name on different hierarchical levels of ranking making this the typical association of the alliance. The association has a vegetation cover of 26.8% (Figure 38) and a species richness of 8.5 species per 1000 m² (Figure 39). In total 77 species were observed on this unit. Structurally, the unit is dominated by dwarf shrubs (20%) with perennial grasses and herbs at about 10% each as shown in Figure 41. The unit is occurring mostly on the flat areas at the top of the Weissrand Escarpment stretching east of Mariental southwards towards Tses, east of the B1 road, but not restricted as it also occurs on flat areas at the top of the Western Escarpment zone, south of Bethanien and close to Groot Schwarzkuppe moving eastwards towards Keetmanshoop and north-east along the Weissrand Plateau towards Mariental. This unit is covered by unconsolidated white quartz pebbles and cobbles underlined by calcareous rocks that are cemented together.

Figure 44: Zygophyllum microcarpum―Rhigozum trichotomum Association

4.5.3 Association 3.3 Cryptolepis decidua―Rhigozum trichotomum

The typicum for this association is relevé 12514, sampled at 25ᵒ 48’ 52” S, 18ᵒ 09’ 07” E on 03 June 2016. The association is represented by 44 relevés and characterised by Cryptolepis decidua and Boscia foetida. Rhigozum trichotomum showed a strong constancy in the unit including other species such as Zygophyllum microcarpum, Cadaba aphylla, Stipagrostis ciliata and Monechma genistifolium that are constant in the association. The association has a vegetation cover of 29.6% (Figure 38) and an average species richness of 10 species per 1000 m² (Figure 39). In total 92 species were observed on this unit that is structurally dominated by dwarf shrubs (20%) and herbs (10%) shown in Figure 42. The unit is widespread on koppies that elevate from the Central Plains and the transitioning elevation between the Central Plains and the Eastern Weissrand Plateau areas.

Figure 45: Cryptolepis decidua―Rhigozum trichotomum Association

4.6 Catophractes alexandri―Lycium bosciifolium Alliance

This alliance relates to the Western Escarpment Zone and is represented by 437 relevés characterised by Catophractes alexandri, Boscia foetida, and Lycium bosciifolium. The association is dominated by Acacia mellifera, Lycium bosciifolium, Rhigozum trichotomum, and Salsola species. The alliance has a vegetation cover of 31% (Figure 6) and an average species richness of 11.9 species (Figure 7) per 1000 m². There were 236 species observed in this association. The unit is structurally a diverse open dwarf shrubland with similar growth form covers. It has about 15% dwarf shrub cover and 8% tall shrubs of the unit vegetation cover. Perennial grasses, annual grasses and herbs also have a 5- 15% (Figure 14) cover each, of the vegetation cover and a few sparse trees. This unit can support both grazing and browsing under good farming practices. The Alliance has 7 associations that can be distinguished as shown and described below. The alliance has 7 associations that were recognised but did not follow the crispness score calculations in Figure 46. This is because the crispness scores indicated a peak of 3 units but these had a high variability and the 7 units had a better ecological interpretability from field observations.

20 Average Average CrispnessValue

0 2 3 4 5 6 7 8 9 10 Number of Clusters

Figure 46: Crispness of Classification for further splitting of Catophractes alexandri―Lycium bosciifolium Alliance

―Rhigozumtrichotomum

Acacia nebrownii―Lycium bosciifolium nebrownii―Lycium Acacia

Acacia mellifera―Catophractes alexandri mellifera―Catophractes Acacia trichotomum africana―Rhigozum Parkinsonia Euphorbia gregaria Euphorbia

Catophractes alexandri―Lycium bosciifoli alexandri―Lycium Catophractes

Acacia karoo―Lycium bosciifolium karoo―Lycium Acacia Tetragonia schenkii―Rhigozum trichotomum schenkii―Rhigozum Tetragonia

Figure 47: Dendrogram for classification of Catophractes alexandri―Lycium bosciifolium Alliance

____

Table 6: Abridged Synoptic table of the vegetation associations under alliance Catophractes alexandri-Lycium bosciifolium with percentage frequency and modified fidelity index phi coefficient.

o―Lycium o―Lycium

―Rhigozum ―Rhigozum

Acacia nebrownii―Lycium nebrownii―Lycium Acacia bosciifolium

Catophractes Catophractes alexandri―Lycium alexandri―Lycium bosciifolium

Acacia Acacia mellifera―Catophractes mellifera―Catophractes alexandri

Tetragonia Tetragonia schenkii―Rhigozum trichotomum

gregaria trichotomum

Euphorbia Euphorbia

trichotomum Parkinsonia Parkinsonia africana―Rhigozum Acacia karo Acacia Association name bosciifolium No. of relevés 25 203 34 44 41 13 77

Euphorbia gregaria 100 100.0 . --- . --- . --- . --- . --- . --- Commiphora species 20 31.1 6 --- . --- 2 --- . --- . --- 3 --- Acacia mellifera 12 --- 13 --- 82 34.0 61 16.6 32 --- 46 --- 43 1.2 Acacia nebrownii 4 --- 8 --- 44 13.2 93 57.2 51 19.6 . --- 5 --- Grewia flava . --- . --- . --- 25 44.3 2 --- . --- . --- Boscia albitrunca . --- 1 --- . --- 23 41.2 . --- . --- 3 --- Tetragonia schenckii 4 --- . --- 9 --- 2 --- 51 50.8 8 --- 6 --- Salsola species 8 --- 2 --- 35 23.1 2 --- 54 44.0 . --- 4 --- Acacia hebeclada . --- . --- . --- . --- 2 --- 54 67.8 1 --- Acacia karroo . --- . --- 3 --- . --- . --- 31 49.5 . --- Acacia erioloba . --- 1 --- 6 --- 7 --- 5 --- 46 49.2 5 --- Ziziphus mucronata . --- 1 --- . --- 23 20.0 . --- 38 42.7 . --- Euclea pseudebenus . --- . --- . --- 2 --- 2 --- 23 40.0 . --- Acacia tortilis . --- . --- . --- . --- 2 --- 15 31.7 1 --- Parkinsonia africana 8 --- 4 --- 29 --- 25 --- 10 --- 8 --- 60 39.6 Cadaba aphylla 28 --- 10 --- 21 --- 16 --- 37 --- 38 --- 69 33.1 Catophractes alexandri 44 --- 84 35.7 79 32.1 48 --- 7 --- . --- 23 --- Rhigozum trichotomum 80 14.1 54 --- 6 --- 57 --- 93 24.9 69 --- 84 17.9 Boscia foetida 36 --- 66 12.4 59 --- 66 --- 49 --- 8 --- 73 17.9 Leucosphaera bainesii . --- . --- . --- . --- . --- . --- 3 14.9 Adenolobus species . --- 2 --- 3 --- . --- . --- 8 --- 6 9.4 Euphorbia species 4 --- 1 --- . --- 2 --- . --- . --- . --- Lycium eenii . --- . --- . --- . --- 7 25.2 . --- . --- 56

Tetragonia calycina . --- 1 --- . --- . --- . --- . --- . --- Boscia species . --- 1 --- . --- . --- . --- . --- . --- Montinia caryophyllacea . --- . --- . --- 2 --- . --- . --- . --- Ipomoea adenioides . --- 1 --- . --- . --- . --- . --- . --- Stoeberia gigas . --- . --- . --- . --- . --- . --- 1 --- Lycium cinereum . --- . --- . --- . --- . --- . --- 1 --- Cryptolepis decidua 8 --- 2 --- . --- . --- 2 --- . --- 4 --- Zygophyllum microcarpum 20 21.7 6 --- 6 --- 5 --- 5 --- . --- 5 --- Tetragonia species 4 --- . --- . --- . --- . --- . --- . --- Adenolobus garipensis 8 --- 1 --- 6 --- 2 --- . --- . --- 1 --- Nymania capensis . --- 2 --- 3 --- 2 --- 2 --- . --- 4 --- Solanum capense . --- . --- . --- . --- 2 --- . --- . --- Euphorbia virosa . --- . --- . --- . --- . --- . --- 1 --- Dichrostachys cinerea . --- 1 --- . --- . --- . --- 8 --- . --- Neorautanenia species . --- 1 --- . --- . --- . --- . --- . --- Aloe dichotoma 4 --- 1 --- . --- 2 --- 2 --- . --- . --- Sisyndite spartea . --- . --- 3 --- . --- . --- 8 --- . --- Montinia species . --- 1 --- . --- . --- . --- . --- 1 --- Aptosimum albomarginatum . --- . --- . --- . --- . --- . --- 1 --- Aloe littoralis 4 --- 1 --- . --- . --- . --- . --- . --- Kleinia longiflora . --- . --- . --- . --- 2 --- . --- . --- Monechma species 12 --- 11 9.2 . --- 5 --- 2 --- . --- 12 --- Grewia flavescens . --- 1 --- 3 --- 7 14.3 2 --- . --- . --- Commiphora dinteri . --- . --- 3 --- . --- . --- . --- . --- Pteronia cylindracea 4 --- 1 --- . --- . --- . --- . --- . --- Albizia anthelmintica . --- 4 --- 3 --- 7 --- 5 --- 8 --- . --- Pechuel-Loeschea leubnitziae . --- . --- . --- . --- . --- 8 25.8 . --- Gomphocarpus species . --- . --- . --- . --- . --- 8 25.8 . --- Lycium bosciifolium 48 --- 66 --- 71 --- 70 --- 71 --- 100 27.1 61 --- Euclea undulata . --- . --- . --- 5 19.8 . --- . --- . --- Acacia senegal . --- 15 17.5 9 --- 9 --- . --- . --- 4 --- Maerua schinzii 4 --- . --- 3 --- 11 14.3 . --- 8 --- 4 --- Zygophyllum rigidum 4 --- . --- . -- - . --- . --- . --- 3 --- Lycium horridum . --- . --- . --- . --- . --- . --- 1 --- Acacia hereroensis . --- 1 --- . --- 7 --- 2 --- . --- 3 --- Gymnosporia senegalensis . --- . --- . --- 2 --- . --- . --- . ---

Tamarix usneoides . --- . --- . --- . --- 2 --- 8 --- . --- Prosopis species . --- . --- . --- 2 --- . --- . --- . --- Zygophyllum species . --- . --- . --- . --- 2 --- . --- . --- Ruellia species . --- 1 --- . --- . --- . --- . --- . --- Euphorbia guerichiana . --- 1 --- . --- . --- . --- . --- 1 - -- Lycium species . --- 1 --- . --- 2 --- . --- . --- . --- Ficus species . --- . --- 3 --- . --- . --- . --- . --- Otoptera burchellii . --- 2 --- . --- . --- 2 --- . --- 4 ---

30 Vegetationcover (%)

Association 10 Association 11 Association 12 Association 13 Association 14 Association 15 Association 16

― ―

―Lycium ―Lycium

Rhigozum Rhigozum

Euphorbia Euphorbia

gregaria

trichotomum

Parkinsonia Parkinsonia

trichotomum

Acacia nebrownii nebrownii Acacia ―Lycium bosciifolium

Acacia mellifera mellifera Acacia ―Catophractes alexandrii

africana― Rhigozum Rhigozum africana―

alexandri bosciifolium schenkii― Tetragonia Rhigozum trichotomum karroo― Acacia bosciifolium Lycium Catophractes Catophractes Associations Figure 48: The average total vegetation cover of the 7 Associations of Catophractes alexandrii―Lycium bosciifolium Alliance with standard error bars

15 (unit)

10 No.of species

Association 10 Association 11 Association 12 Association 13 Association 14 Association 15 Association 16

― ―

m m

―Lyciu

― Lycium

―Rhigozu

―Lycium ―Lycium

―Rhigozu

trichotomum

Acacia mellifera Acacia Catophractes Catophractes alexandri bosciifolium Catophractes alexandri Acacia nebrownii bosciifolium m Tetragonia schenkii trichotomum m Acacia karroo bosciifolium Parkinsonia africana trichotomum m Euphorbia gregaria Euphorbia Association

Figure 49: The average species richness of the 7 Associations of Catophractes alexandrii―Lycium bosciifolium Alliance. Error bars indicate standard deviation

Trees (>5m)

Tall shrubs (1-5m)

Dwarf shrubs (<1m)

Perennial grasses Growth form Growth

Annual Grasses

Herbs

0 10 20 30 40 50 60 70 80 Percentage cover (%)

Figure 50: Box and Whisker plot of percentage growth form cover for Euphorbia gregaria―Rhigozum trichotomum Association

Trees (>5m)

Tall shrubs (1-5m)

Dwarf shrubs (<1m)

Perennial grasses Growth form Growth

Annual Grasses

Herbs

0 10 20 30 40 50 60 70 80 Percentage cover (%)

Figure 51: Box and Whisker plot of percentage growth form cover for Catophractes alexandri―Lycium bosciifolium Association

Trees (>5m)

Tall shrubs (1-5m)

Dwarf shrubs (<1m)

Perennial grasses Growth form Growth

Annual Grasses

Herbs

0 10 20 30 40 50 60 70 80 Percentage cover (%)

Figure 52: Box and Whisker plot of percentage growth form cover for Acacia mellifera―Catophractes alexandri Association

Trees (>5m)

Tall shrubs (1-5m)

Dwarf shrubs (<1m)

Growth form Growth Perennial grasses

Annual Grasses

Herbs

0 10 20 30 40 50 60 70 80 Percentage cover (%)

Figure 53: Box and Whisker plot of percentage growth form cover for Acacia nebrownii―Lycium bosciifolium Association

Trees (>5m)

Tall shrubs (1-5m)

Dwarf shrubs (<1m)

Perennial grasses Growth form Growth

Annual Grasses

Herbs

0 10 20 30 40 50 60 70 80 Percentage cover (%)

Figure 54: Box and Whisker plot of percentage growth form cover for Tetragonia schenkii―Rhigozum trichotomum Association

Trees (>5m)

Tall shrubs (1-5m)

Dwarf shrubs (<1m)

Growth form Growth Perennial grasses

Annual Grasses

Herbs

0 10 20 30 40 50 60 70 80 Percentage cover (%)

Figure 55: Box and Whisker plot of percentage growth cover for Acacia karroo―Lycium bosciifolium Association

Trees (>5m)

Tall shrubs (1-5m)

Dwarf shrubs (<1m)

Perennial grasses Growth form Growth

Annual Grasses

Herbs

0 10 20 30 40 50 60 70 80 Percentage cover (%)

Figure 56: Box and Whisker plot of percentage growth form cover for Parkinsonia africana―Rhigozum trichotomum Association

4.6.1 Association 4.1 Euphorbia gregaria―Rhigozum trichotomum The typicum for this association is relevé 12252, sampled at 26ᵒ 37’ 04” S, 17ᵒ 36’ 53” E on 04 May 2017. The association is represented by 25 relevés and characterised by Euphorbia gregaria and Gisekia africana. Rhigozum trichotomum, Stipagrostis ciliata, Tribulus terrestris, Lycium bosciifolium and Catophractes alexandri occur as constant species in this unit. The unit has a vegetation cover of 30.4% (Figure 48) and an average species richness of 12.4 species per 1000 m² (Figure 49). In total 65 species have been observed on this unit that has dwarf shrub cover of about 25% and 12% of herbs (Figure 50). The unit occurs on the Western Escarpment zone mountainous top in the area around Kosis and Goageb extending south and eastwards. Also found east of Bethanien on the escarpment at higher altitude occuring on red sandstone and shales of the Nama Karoo.

Figure 57: Euphorbia gregaria―Rhigozum trichotomum Association

4.6.2 Association 4.2 Catophractes alexandri―Lycium bosciifolium The typicum for this association is relevé 12627, sampled at 25ᵒ 11’ 58” S, 18ᵒ 19’ 06” E on 14 June 2016. The association is represented by 203 relevés and characterised by Catophractes alexandri and dominated by Lycium bosciifolium. The Stipagrostis ciliata, Aptosimum spinescens, Tribulus terrestris, Lycium bosciifolium, Boscia foetida subsp. foetida and Rhigozum trichotomum occur as constant species. This association relates to the higher order syntaxa Alliance hence the same name but different hierarchical ranking, making this the typicum association for the alliance. The unit has a vegetation cover of 30.9% (Figure 48) and an average species richness of 11.7 species per 1000 m² (Figure 49). A total of 136 species have been observed on this unit. Structurally the unit is diverse with a representation of each growth form in the unit except trees that are absent. There is a higher cover of herbs (13%) and about 10% cover of dwarf shrubs and perennial grasses each (Figure 51). The unit is widely spread throughout the whole study area, commonly occurring on the Western Escarpment zone on red sandstones of the Nama Karoo. It also occurs further east of the Weissrand Plateau close to the Kalahari on the Oskop Conservancy and surrounding areas of calcrete rocks.

Figure 58: Catophractes alexandri―Lycium bosciifolium Association

4.6.3 Association 4.3 Acacia mellifera―Catophractes alexandri The typicum for this association is relevé 12373, sampled at 25ᵒ 08’ 50” S, 18ᵒ 19’ 48” E on 13 May 2016. The association is represented by 34 relevés and characterised by diagnostic Acacia mellifera and Catophractes alexandri. The constant species are Boscia foetida subsp. foetida, Lycium bosciifolium, Acacia nebrownii and Stipagrostis ciliata. The unit has a vegetation cover of 36.7% (Figure 48) and an average species richness of 13.7 species per 1000 m² (Figure 49). In total 89 species have been observed on this unit. The unit is dwarf shrub dominated (20%) and has about 10% cover of (Figure 52). The unit is also found on the Oskop Conservancy close to the Kalahari on calcrete rocks and on the Western Escarpment zone on flat rocky areas of the Huibes Conservancy.

Figure 59: Acacia mellifera―Catophractes alexandrii Association

4.6.4 Association 4.4 Acacia nebrownii―Lycium bosciifolium The typicum for this association is relevé 12476, sampled at 26ᵒ 10’ 51” S, 18ᵒ 12’ 01” E on 01 June 2016. The association is represented by 44 relevés and characterised by Acacia nebrownii, Boscia foetida subsp. foetida, and Grewia flava. The unit is dominated by Stipagrostis ciliata and has Lycium bosciifolium, Rhigozum trichotomum, Catophractes alexandri, Acacia mellifera and Enneapogon cenchroides as constant species. The vegetation cover for the unit is 36% (Figure 48) and has an average species richness of 15 species per 1000 m² (Figure 49). In total 133 species have been observed on this unit. The unit is structurally diverse with trees, tall shrubs and dwarf shrubs present with about 10% cover each (Figure 53). The unit is widespread across the study area occurring on the flood plains along rivers in the study area.

Figure 60: Acacia Nebrownii―Lycium bosciifolium Association

4.6.5 Association 4.5 Tetragonia schenkii―Rhigozum trichotomum The typicum for this association is relevé 12487, sampled at 26ᵒ 00’ 33” S, 18ᵒ 12’ 04” E on the 02 June 2016. The association is represented by 41 relevés and is characterised by Tetragonia schenkii and Salsola species. Salsola species also dominates the unit. This unit is very similar to the Tetragonia schenkii – Salsola species (Association 2) that is dominated by Tetragonia schenkii, however the difference lies in the constant species where the Tetragonia schenkii – Rhigozum trichotomum association has Rhigozum trichotomum strongly occurring as a constant species with other species such as Stipagrostis ciliata, Lycium bosciifolium, Boscia foetida subsp. foetida, and Acacia nebrownii, while these are absent in Association 2. This unit has a vegetation cover of 31.5% (Figure 48) and an average species richness of 11.4 species per 1000 m² (Figure 49). In total 90 species have been observed on this unit. The unit is structurally dominated by dwarf shrubs and tall shrubs shown in Figure 54 with scarce trees and occurs commonly along drainage lines towards rivers on the Western Escarpment zone and Central Plains.

Figure 61: Tetragonia schenkii―Rhigozum trichotomum Association

4.6.6 Association 4.6 Acacia karroo―Lycium bosciifolium The typicum for this association is relevé 12240, sampled at 26ᵒ 37’ 58” S, 17ᵒ 30’ 58” E on the 03 May 2016. The association is represented by 13 relevés and is characterised by Acacia hebeclada subsp. hebeclada, Acacia erioloba, Euclea pseudebenus, Acacia karroo, Acacia tortilis and Ziziphus mucronata. Lycium bosciifolium, Rhigozum trichotomum, Acacia mellifera subsp. detinens and Stipagrostis ciliata are constant species. This unit is typical of River Systems and would have ideally belonged under Alliance 1, but because of the encroaching Rhigozum trichotomum that is strongly constant in this unit and the presence of Acacia hebeclada subsp. hebeclada. The river systems that occur along the Western Escarpment Zone yielded a river system unit of the Western Escarpment zone. This is because homogeneity was difficult to maintain during sampling of this unit. The unit has a vegetation cover of 30.6% (Figure 48) and an average species richness of 9 species per 1000 m² (Figure 49). A total of 54 species have been observed on this unit. There is a structural diversity in the unit with cover dominated by herbs and tall shrubs as shown in Figure 55. This unit occurs only along rivers of the Western Escarpment zone.

Figure 62: Acacia karroo― Lycium bosciifolium Association

4.6.7 Association 4.7 Parkinsonia africana―Rhigozum trichotomum The typicum for this association is relevé 12386, sampled at 25ᵒ 08’ 05” S, 17ᵒ 14’ 28” E on the 14 May 2016. The association is represented by 77 relevés that are characterised by Parkinsonia africana and Cadaba aphylla as diagnostics, and dominated by Rhigozum trichotomum and Acacia mellifera. The constant species are Boscia foetida subsp. foetida, Lycium bosciifolium, Rhigozum trichotomum and Stipagrostis ciliata. The vegetation cover for the unit is 25.8% (Figure 48) with an average species richness of 10.7 species per 1000 m² (Figure 49). In total 92 species have been observed on this unit. Structurally, the unit is cover dominated by dwarf shrubs (15%) with about 10% cover of perennial grasses and herbs each as shown in Figure 56. The unit is widespread across the study area landscapes and occurs along washes on the Western Escarpment zone and Central Plains mostly on sandy soils.

Figure 63: Parkinsonia africana―Rhigozum trichotomum Association

4.7 Environmental Gradients

The physical habitat influence on the higher syntaxa alliance level is illustrated in Figure 64 below with an ordination diagram showing soil depth and stone size to be the main environmental driver. Gravel stones are positively correlated with Axis 1, while medium stones, small stones, large stones and slope class are negatively correlated with Axis 1. The soil depth and rainfall are negatively correlated with Axis 2. Alliances Tetragonia schenkii―Tamarix usneoides Alliance Cryptolepis decidua―Salsola Alliance Zygophyllum microcarpum―Rhigozum trichotomum Alliance Catophractes alexandri―Lycium bosciifolium Alliance

Figure 64: The Detrended Correspondence Analysis ordination diagram of 750 relevés surveyed in the Nama Karoo, south-central Namibia.

Figure 65 below illustrates the overlap between all four alliances. There is only a small overlap between Tetragonia schenkii―Tamarix usneoides Alliance and Zygophyllum microcarpum―Rhigozum trichotomum Alliance. The Zygophyllum microcarpum―Rhigozum trichotomum Alliance appears to only have a positive correlation with Axis 1 on which gravel stones are a strong driver. This can be attributed by the fact that Tetragonia schenkii―Tamarix usneoides Alliance represents a river landscape where most of the material has been well sorted.

Alliances Tetragonia schenkii―Tamarix usneoides Alliance Cryptolepis decidua―Salsola Alliance Zygophyllum microcarpum―Rhigozum trichotomum Alliance Catophractes alexandri―Lycium bosciifolium Alliance

Figure 65: Detrended Correspondence Analysis ordination diagram of 750 relevés showing an overlap between alliances

The Figure 66 below illustrates the habitat features within Tetragonia schenkii―Tamarix usneoides Alliance that warrants diversity to set 3 associations apart. The strong environmental driver that comes out is soil depth positively correlating with axis 1. The Neoluederitzia sericeocarpa―Lycium bosciifolium Association 1.1 positively correlates with axis 1, while the Salsola―Tetragonia schenkii Association 1.2 negatively correlates with axis 1. The environmental factors driving this opposite correlation between Association 1.1 and 1.2 are not main environmental or strong drivers but have a combined magnitude of setting them apart. The variation that exists between the Associations appears to be more species composition related rather than strongly physical habitat related.

Associations

Tetragonia schenkii―Tamarix usneoides Association

Cryptolepis decidua―Salsola Association

Zygophyllum microcarpum―Rhigozum trichotomum Association

Figure 66: The Detrended Correspondence Analysis ordination diagram of 57 relevés of the three associations of Tetragonia schenkii―Tamarix usneoides Alliance 1

Figure 67 below illustrates the habitat features within Cryptolepis decidua―Salsola Alliance 2 that has 3 associations. The Euphorbia―Salsola Association 2.1 is a doubtful unit and also comes out as an outlier on the scatterplot. The soil depth comes out as a strong environmental driver that is negatively correlated with axis 1. Rainfall also is revealed as a main environmental driver and is positively correlated with axis 2. The Cryptolepis decidua―Salsola Association 2.2 is aligned along axis 2, while the Tetragonia schenkii―Acacia nebrownii association 2.3 is aligned negatively along axis 1.

Associations

Euphorbia―Salsola Association

Cryptolepis decidua―Salsola Association

Tetragonia schenkii―Acacia nebrownii Association

Figure 67: The Detrended Correspondence Analysis ordination diagram of 112 relevés of Cryptolepis decidua―Salsola Alliance 2 associations with dominant environmental parameters

The Cryptolepis decidua―Salsola Association 2.2 that is aligned along axis 2 is mainly made up of the landscape type relating to Plains as illustrated in Figure 68.

Figure 68: The Detrended Correspondence Analysis ordination diagram of Cryptolepis decidua―Salsola alliance 2 displaying landscape type on Axis 1 and Axis 2

Figure 69 illustrates the habitat features within the Zygophyllum microcarpum―Rhigozum trichotomum Alliance 3 that has 3 associations. The main environmental drivers are rainfall and frost that positively correlate with Axis 1. The Stipagrostis ciliata―Rhigozum trichotomum Association 3.1 and Zygophyllum microcarpum―Rhigozum trichotomum 3.2 do not overlap. Association 3.1 positively correlates with Axis 1 while Association 3.2 negatively correlates with Axis 1. The Cryptolepis decidua―Rhigozum trichotomum Association 3.3 overlaps between Association 3.1 and 3.2.

Associations

Stipagrostis ciliatai―Rhigozum trichotomum Association

Zygophyllum microcarpum―Rhigozum trichotomum Association

Cryptolepis decidua―Rhigozum trichotomum Association

Figure 69: The Detrended Correspondence Analysis ordination diagram of 244 relevés for associations of Zygophyllum microcarpum―Rhigozum trichotomum alliance 3

Figure 70 below illustrates the habitat features within Catophractes alexandri―Lycium bosciifolium Alliance 4 that has 7 associations. The main environmental drivers are stone sizes, Slope class, rainfall and frost. The rainfall and frost are negatively correlated with Axis 2, whilst the large stones, medium stones and slope class are negatively correlated with Axis 1, leaving gravel stones that are positively correlated with Axis 1. The Euphorbia gregaria―Rhigozum trichotomum Association 4.1 is positively oriented with Axis 1, and negatively oriented with Axis 2. Catophractes alexandri―Lycium bosciifolium Association 4.2 is mostly negatively oriented with Axis 1.

Euphorbia gregaria―Rhigozum trichotomum

Catophractes alexandri―Lycium bosciifolium Acacia mellifera―Catophractes alexandri Acacia nebrownii―Lycium bosciifolium Tetragonia schenkii―Rhigozum trichotomum Acacia karroo―Lycium bosciifolium

Parkinsonia africana―Rhigozum trichotomum

Figure 70: The Detrended Correspondence Analysis ordination diagram of 437 relevés for associations of Catophractes alexandri―Lycium bosciifolium alliance 4

4.8 Utilisation Potential of the Vegetation Types

The factors influencing the suitability for livestock farming and the ecological sensitivity of the described 16 associations in this thesis are presented below. These are presented as indices that have been calculated for each identified vegetation association, based on its habitat, structure and composition. It should be noted that these indices are however biased towards cattle farming because of the grazing value of dwarf shrub species that is not factored into the index (Du Toit 1997, Strohbach 2012a).

4.8.1 Suitability index for animal husbandry

Table 7: Factors influencing the suitability of sixteen associations within the Nama Karoo of south-central Namibia for livestock farming 1.1 1.2 1.3 2.1 2.2 2.3 3.1 3.2 3.3 4.1 4.2 4.3 4.4 4.5 4.6 4.7 Neoluederitzia Tetragonia Tamarix Euphorbia Cryptolepis Acacia Cadaba Zygophyllum Cryptolepis Euphorbia Catophractes Acacia Acacia Tetragonia Acacia Parkinsonia sericeocarpa- schenki - usneoides - species - decidua - nebrownii - aphylla - microcarpum - decidua - gregaria - alexandri - mellifera - nebrownii - schenkii - karroo - africana - Lycium Salsola Lycium Salsola Salsola Tetragonia Rhigozum Rhigozum Rhigozum Rhigozum Lycium Catophractes Lycium Rhigozum Lycium Rhigozum bosciifolium species bosciifolium species species schenkii trichotomum trichotomum trichotomum trichotomum bosciifolium alexandri bosciifolium trichotomum bosciifolium trichotomum actual index actual index actual index actual index actual index actual index actual index actual index actual index actual index actual index actual index actual index actual index actual index actual index GPZ 9 22.2 9 4 9 4 9 4 9 4.0 9 4 9 4 9 4 9 4 9 4 9 4 9 4 9 4 9 4 9 4 9 4 Rainfall 146.1 73.1 142.0 71.0 142.7 71.3 141.9 71.0 148.4 74.2 147.4 73.7 142.3 71.2 136.3 68.1 133.7 66.9 130.5 65.3 161.9 81 166.7 83.3 160.6 80.3 146.7 73.3 149.1 74.6 146.6 73.3 Rainfall dependability (related to CV) 77 23 77 23 79 21 73 27 77 23 76 24 75 25 77 23 78 22 76 24 73 27 71 29 74 26 75 25 75 25 76 24 Slope 2 33.3 1 37.5 1 37.5 1 37.5 1 37.5 1 37.5 3 12.5 2 20.8 3 12.5 3 12.5 2 20.8 2 20.8 2 20.8 1 37.5 2 20.8 3 12.5 Water holding capacity 1 20 1 0 1 0 2 20 2 20 1 0 1 0 1 0 2 20 1 0 1 0 1 0 1 0 1 0 1 0 1 0

Habitat subtotal 171.6 135.5 133.9 159.5 158.7 139.2 112.7 116.0 125.4 105.8 132.8 137.2 131.2 139.9 124.4 113.8 Perennial grass cover 13.1 65.4 2.1 10.3 12.6 63.2 2 10 5.8 28.8 4.0 19.8 3.7 18.4 5.6 28.2 4.2 21 4.1 20.7 6.7 33.7 6.7 33.6 6.4 31.9 3.9 19.3 6.4 31.9 3.9 19.5 annual grass cover 0.9 0.9 1.9 1.9 6.8 6.8 1.1 1.1 3.3 3.3 4.0 4 0.8 0.8 2.6 2.6 2.3 2.3 1.8 1.8 3.6 3.6 6.4 6.4 4.8 4.8 2.8 2.8 2.1 2.1 2.2 2.2 Herbaceous cover 6.7 6.7 4.9 4.9 8.6 8.6 6.1 6.1 8.7 8.7 8 8 6.1 6.1 6.5 6.5 7.1 7.1 8.6 8.6 9.1 9.1 9.6 9.6 9.3 9.3 6.8 6.8 3.096 3.1 5.9 5.9 Dwarf shrub cover 18.3 18.3 26.9 26.9 12.7 12.7 7.6 7.6 14.0 14.0 12.9 12.9 11.1 11.1 17.6 17.6 13.7 13.7 14.1 14.1 8.3 8.3 8.4 8.4 7.6 7.6 13.6 13.6 8.9 8.9 10.2 10.2 Shrub cover 7.6 7.6 8.5 8.5 15.6 15.6 0 0 0.4 0.4 1.9 1.9 0.7 0.7 0.9 0.9 2.1 2.1 1.7 1.7 3.0 3 5.4 5.4 6.9 6.9 4.3 4.3 6.7 6.7 3.3 3.3 Tree cover 4.4 4.4 1.8 1.8 6.4 6.4 0 0 0 0 0.1 0.1 0 0 0 0 0.3 0.3 0.1 0.1 0.1 0.1 0.3 0.3 1 1 0.3 0.3 3.4 3.4 0.3 0.3 Bare ground 48.9 102.2 54.1 91.9 37.2 125.7 83.3 33.5 67.9 64.2 69.1 61.8 77.5 45.0 73.2 53.5 70.4 59.2 69.6 60.9 69.1 61.8 63.3 73.4 63.9 72.1 68.4 63.1 69.37 61.3 74.2 51.7 Bush encroachment ratio 27.5 12.8 29.5 16.8 30.8 24.6 19.2 24.1 21.7 23.4 23.7 25.7 21.2 18.8 14.0 16.2

Structure subtotal 233.1 158.8 268.6 75 150.1 133.1 101.5 133.3 127.4 131.3 143.3 162.8 154.9 128.9 131.4 109.3 Total no of species 34 43 78 29 109 107 106 100 108 86 189 96 136 117 47 127 No of Toxic species 5 42.6 4 45.3 8 44.9 1 48.3 10 45.4 9 45.8 7 46.7 6 47 8 46.3 6 46.5 11 47.1 7 46.4 10 46.3 10 45.7 6 43.6 10 46.1 Abundance of Toxic species 2.2 0.2 5.7 0.1 1.7 0.3 0.4 1.4 0.3 1.6 0.7 0.7 0.1 5 0.8 0.6 0.7 0.7 0.5 1 0.1 3.8 0.2 2.2 0.2 2.8 0.4 1.3 1 0.5 0.14 3.6 High grazing value species 27.5 275 2 20 2.5 25.3 2.5 25 1.7 16.9 2.1 20.6 3.4 34.4 2.9 29.4 2.2 21.9 1.7 16.9 5.2 51.8 3.9 38.5 1.9 19.2 2.3 23.3 2.5 25 3.271 32.7 Average grazing value species 10.8 43.3 2.8 11.1 4.9 19.4 1.7 6.8 2.5 10 2.7 10.8 1.9 7.6 2.8 11.3 2.4 9.6 2.1 8.4 2.7 10.6 3 12 2 8.1 2.5 9.9 3.5 13.8 2.588 10.4 Low grazing value species 3.5 7 1.91 3.8 3.6 7.2 1.4 2.8 2 3.9 2.4 4.9 1.4 2.7 2.6 5.2 2.8 5.5 1.4 2.7 1.9 3.9 2 4.1 2.6 5.2 2.8 5.6 4.6 9.2 2.308 4.6

Composition subtotal 368.2 80.4 97.1 84.2 77.8 82.8 96.4 93.5 84 75.6 117.2 103.1 81.5 85.7 92.1 97.3 index value 772.9 374.7 499.5 318.7 386.6 355.1 310.6 342.8 336.8 312.6 393.4 403.1 367.6 354.4 347.9 320.4 suitability low suitability unsuitable low suitability unsuitable unsuitable unsuitable unsuitable unsuitable unsuitable unsuitable unsuitable low suitability unsuitable unsuitable unsuitable unsuitable

835

668

501 Water holding capacity

Slope

334 Rainfall dependability

Growing Period Zone Habitat suitability Habitat Average annual rainfall 167

0 unsuitable unsuitable low moderate high high very

Figure 71: Graphical representation of how various habitat and compositional characteristics of the vegetation contribute towards the suitability rating (for livestock farming) of sixteen vegetation associations (Habitat Suitability). 81

700

560

Bush encroachment ratio

420 Bare Ground

Tree cover

280 Shrub cover

Dwarf shrub cover Structural suitability Structural

140 Herbaceous cover

Annual grass cover

Perennial grass cover

0 unsuitable unsuitable low moderate high high very

Figure 72: Graphical representation of how various habitat and compositional characteristics of the vegetation contribute towards the suitability rating (for livestock farming) of sixteen vegetation associations (Structural Suitability)

600

480

Low grazing value species

360 Average grazing value species

High grazing value species

240 Abundance of Toxic species

No of Toxic species Compositional suitability Compositional 120

0 unsuitable unsuitable low moderate high high very

Figure 73: Graphical representation of how various habitat and compositional characteristics of the vegetation contribute towards the suitability rating (for livestock farming) of sixteen vegetation associations (Compositional Suitability)

2000

1600

1200 Composition

Structure 800

Habitat factors Combined suitability Combined 400

0 unsuitable unsuitable low moderate high very high

Figure 74: Graphical representation of how various habitat and compositional characteristics of the vegetation contribute towards the suitability rating (for livestock farming) of sixteen vegetation associations (Combined Suitability) 84

There are 3 associations of the overall 16 described associations that have a low suitability for livestock farming. These associations are namely Neoluederitzia sericeocarpa―Lycium bosciifolium; Tamarix usneoides―Lycium bosciifolium; and Acacia mellifera―Catophractes alexandri. The rest of the 13 associations are regarded to be unsuitable for livestock farming as presented in Table 7 and Figure 74 above.

In terms of Habitat Suitability, all the associations are rated to have a low suitability by the habitat suitability index. Neoluederitzia sericeocarpa―Lycium bosciifolium association has the highest habitat suitability compared to the rest (Figure 71).

There are 6 associations that have a low structural suitability, and the rest of the 10 associations are structural unsuitable for livestock farming (Figure 72). Tamarix usneoides―Lycium bosciifolium has the highest index of structural suitability. The Neoluederitzia sericeocarpa―Lycium bosciifolium has a high compositional suitability, while the rest of the 15 associations are rated to be unsuitable in terms of compositional structure (Figure 73).

4.8.2 Ecological Sensitivity of the Vegetation Table 8: Factors influencing the ecological sensitivity of sixteen associations within the Nama Karoo of south-central Namibia 1.1 1.2 1.3 2.1 2.2 2.3 3.1 3.2 3.3 4.1 4.2 4.3 4.4 4.5 4.6 4.7

Neoluederitzia Tetragonia Tamarix Euphorbia Cryptolepis Acacia Cadaba Zygophyllum Cryptolepus Euphorbia Catophractes Acacia Acacia Tetragonia Acacia Parkinsonia sericeocarpa- schenki - usneoides - species - decidua - nebrownii - aphylla - microcarpum - decidua - gregaria - alexandri - mellifera - nebrownii - schenkii - karroo - africana - Lycium Salsola Lycium Salsola Salsola Tetragonia Rhigozum Rhigozum Rhigozum Rhigozum Lycium Catophractes Lycium Rhigozum Lycium Rhigozum

maximum Weighting bosciifolium species bosciifolium species species schenkii trichotomum trichotomum trichotomum trichotomum bosciifolium alexandri bosciifolium trichotomum bosciifolium trichotomum

No of species 50 34 3.4 43 4.3 78 7.8 29 2.9 109 10.9 107 10.7 106 10.6 100 10 108 10.8 86 8.6 189 18.9 96 9.6 136 13.6 117 11.7 47 4.7 127 12.7 Estimated no of species 50 61 116 47 155 147 151 146 161 122 257 130 185 168 74 177

% Estimated no of 20 1.2 1.5 2.8 1.2 3.8 3.6 3.7 3.6 3.9 3.0 6.3 3.2 4.5 4.1 1.8 4.3 Species to National species density 50 8 8 6 6 11 11 8 8 9 9 11 11 9 9 9 9 10 10 12 12 12 12 14 14 15 15 11 11 9 9 11 11 no of endemic species 50 3 3 4 4 8 8 3 3 12 12 11 11 14 14 14 14 12 12 9 9 18 18 13 13 11 11 12 12 2 2 17 17 inverse no of exotic species 10 1 10 1 10 5 2 2 5 7 1.4 7 1.4 3 3.3 2 5 1 10 1 10 2 5 2 5 3 3.3 1 10 2 5 1 10 x 10

Species diversity no of red list species (excluding least 10 10 0 10 0 0 30 30 30 30 50 0 20 20 0 10 concerned) no of protected species 20 4 4 4 4 7 7 1 1 1 1 3 3 7 7 3 3 7 7 4 4 7 7 5 5 8 8 6 6 7 7 7 7 Subtotal: 250 39.6 39.8 38.6 31.1 38.1 40.7 77.6 74.6 83.7 76.6 117.2 49.8 75.5 74.8 29.5 72.0

Erosion Hazard (SLEMSA) 1.5 0.8 0.3 4.6 2.1 2.2 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 Slope (X) 2 20.9 1 8.7 1 8.7 1 8.7 1 8.7 1 8.7 3 0.3 2 0.3 3 0.3 3 0.3 2 0.3 2 0.3 2 0.3 1 0.3 2 0.3 3 0.3 Cover (C) 51.1 0 45.9 0.1 62.8 0 16.8 0.4 32.1 0.1 30.9 0.2 22.5 0.3 26.8 0.2 29.6 0.2 30.4 0.2 30.9 0.2 36.7 0.1 36.1 0.1 31.6 0.2 30.6 0.2 25.9 0.2 Rainfall (E) 146.1 2754.2 142.0 2676.5 142.7 2688.6 141.9 2674.6 148.4 2796.4 147.4 2777.3 142.3 2682.4 136.3 2568.1 133.7 2520.5 130.5 2459.6 161.9 3051.5 166.7 3141.4 160.6 3027.4 146.7 2764.5 149.1 2810.1 146.6 2761.9 no data, Soil erodibility (F) 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 set to 3 Final rating 70 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 influence on other ecosystems position within 60 catchment Plateau 1 0 0 0 0 0 0 0 1 10 0 0 0 0 0 0 0 0 Escarp 1 0 0 0 0 0 0 0 0 0 1 10 1 10 1 10 0 0 0 0 Upslope 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Midslope 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 footslope 4 0 0 0 0 0 0 0 0 1 40 0 0 0 0 0 0 0 pedeplain 4 0 0 0 0 0 0 1 40 0 0 0 0 0 0 1 40 0 0 floodplain 6 1 60 1 60 0 0 0 1 60 0 0 0 0 0 0 0 0 0 0

Ecosystem functionality Rivers: 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 pans & vleys 2 0 0 0 1 20 0 0 0 0 0 0 0 0 0 0 0 0 washes 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 30 1 30 omiramba 6 0 0 0 0 1 60 0 0 0 0 0 0 0 0 0 0 0 small ephemeral rivers 4 0 0 0 0 0 0 0 0 0 0 0 0 1 40 0 0 0 large ephemeral rivers (Khan, Swakop, Kuiseb 3 0 0 1 30 0 0 0 0 0 0 0 0 0 0 0 0 0 etc) productivity potential 100 34 34 16.5 16.5 22 22 14 14 17 17 15.6 15.6 13.7 13.7 15.1 15.1 14.8 14.8 13.8 13.8 17.3 17.3 17.8 17.8 16.2 16.2 15.6 15.6 15.3 15.3 14.1 14.1 Subtotal: 230 95 77.5 53 35 78 76.6 54.7 26.1 55.8 24.8 28.3 28.8 57.2 56.6 46.3 45.1 Index value 480 134.7 117.3 91.6 66.1 116.2 117.4 132.3 100.7 139.6 101.4 145.5 78.5 132.7 131.4 75.8 117.2 Sensitivity moderate Low Low Low Low Low moderate Low moderate Low moderate Low moderate moderate Low Low 86

250

Exotic species

187.5 Protected species

Red Data List Species

Endemic Species 125 Species density

Proportion of all species 62.5

Sensitivity Sensitivity due diversity to No of species (Index) low low moderate high very high 0

Figure 75: Graphical representation of how various diversity and ecosystem functional characterisitcs of the vegetation contribute towards the ecological sensitivity of sixteen vegetation associations within the Nama Karoo of south-central Namibia (Sensitivity due to diversity)

250

Utilisation potential 187.5

Waterflow patterns 125 Erosion Hazard (SLEMSA)

62.5 low low moderate high very high

0 Sensitivity Sensitivity due ecosystem to functionality

Figure 76: Graphical representation of how various diversity and ecosystem functional characterisitcs of the vegetation contribute towards the ecological sensitivity of sixteen vegetation associations within the Nama Karoo of south-central Namibia (Sensitivity due to ecosystem functionality)

500

375 Ecosystem functionality

Species 250 diversity

Total sensitivity Totalsensitivity rating 125 low low moderate high high very 0

Figure 77: Graphical representation of how various diversity and ecosystem functional characterisitcs of the vegetation contribute towards the ecological sensitivity of sixteen vegetation associations within the Nama Karoo of south-central Namibia (total sensitivity) 89

300

250 Estimated no of species 200 No of species

150

100 Number of species (unit) species of Number

Figure 78: Estimated total number of species in each of sixteen association using the Jackknife procedure of species estimation. 90

The overall sensitivity index shows 6 associations to have a moderate sensitivity, and 10 associations have a low ecological sensitivity (Figure 77) and (Table 8). There are 8 associations that have a moderate sensitivity due to diversity. Catophractes alexandri―Lycium bosciifolium has the highest sensitivity due to diversity (Figure 75). Graphical representation of the sensitivity due to ecosystem functionality (Figure 76) shows 4 associations having a moderate sensitivity. The rest of the 12 associations have a low ecosystem functionality sensitivity. Neoluederitzia sericeocarpa―Lycium bosciifolium has the highest moderate sensitivity compared to the rest of the associations. In Figure 78, Catophractes alexandri―Lycium bosciifolium has the highest number of species compared to the other associations as estimated using the Jackknife procedure for species estimation.

Chapter 5: Discussion

5.1 Phytosociology methods

The Braun-Blanquet sampling method, and multivariate analysis techniques for classification and ordination that has been applied in this study has allowed for the vegetation patterns and stratification to be studied and interpreted accordingly. This is despite the Braun-Blanquet method having been criticized for being over-simplified, too subjective, and representing a weak methodology on to a much complex real world (Werger 1974, Gauch 1982, McCune et al. 2002, Kent and Coker 2004, Kangombe 2010). However, modern Fidelity measures, Cocktail methods, objective numerical classification (Chytrý et al. 2002) as well as the use of fairly robust ordination techniques can make up for the simplified method. This simplification of a much complex real world can be viewed as an advantage by ecologists as it provides an opportunity to simplify the complexity for improved understanding of vegetation patterns, whilst modifying the method to be better suited for the much complex real world. The Braun-Blanquet method though described and criticized by many to be a weak and simplified method, still needs to undergo modification and become standardized in the sampling approach. Issues that remain unresolved such as how many plots are considered to be enough when sampling would address the problem of over-sampling one area/unit and under sampling other areas/units. The approach of using a landscape map as a base map to pre-determine units that are different creates problems later in deciding at which hierarchical level of syntaxa order a unit belongs to. There is often a lot of variation within what appears to be a uniform landscape unit from a base map. The lack of research papers that primarily looks at the methodology alone in detail, and sampling methods to guide new vegetation scientists during data collection would minimize errors during vegetation classifications. The available International Code of Phytosociological Nomenclature (Weber et al. 2000b) is a lengthy and difficult documentation to understand, that needs to be simplified for the non- expert, to avoid duplication of names and standardized practical approaches.

5.2 Ordinations

The fairly robust ordination techniques that are meant to make up for the subjectivity and other flaws of phytosociological methods have also been criticized in community ecology for one or other error, particularly those of indirect gradient analysis. One of the major criticism that came out is that of the arch effect, associated with Correspondence Analysis (CA), and even the favoured apparent superior ordination technique of Non-metric Multidimensional Scaling (NMS) (Gauch 1982, McCune et al. 2002, Kent and Coker 2004, Kangombe 2010). In CA and RA, the points at the ends of the first axis are compressed, relative to those in the middle, which produces an arch effect in the data thus interfering with appropriate interpretation of ordination diagrams. The DCA which has been used in this study, solves

92 this problem by segmentation and rescaling (by expanding segments at the ends of axis and contracting those in the middle of axis) in a process called detrending, thus removing the arch effect (Kangombe 2010). Despite its limitations, DCA remains a powerful method of indirect gradient analysis and is computationally efficient (Gauch 1982, Kent and Coker 2004, Kangombe 2010). There is a lack of information regarding ecological specificity of species and habitat preferences in the study area, which made it difficult in making confident inferences of ordination gradients. This has however been addressed by the investigator’s knowledge of the study area and field notes of species observations during the duration of the study to make suppositions of gradients on the ordinated data. The Figure 64 shows a two-dimensional samples ordination derived from DCA of floristic data collected across the whole study area, where the triangles and blocks that are color coded represent relevés surveyed. The distance between the representatives icons are approximately proportional to the dissimilarities between the relevés. Axis 1 in the ordination diagram reveals a stone size gradient with relevés (and species) of gravel sized stones that belong to the River System of Tetragonia schenkii―Tamarix usneoides Alliance 1, and the Central Plains of Cryptolepis decidua―Salsola Alliance 2, positively correlated with Axis 1. These two alliances have unconsolidated deposits from different transport mediums along which the gravel sized stones are then deposited. The gravel sized stones are deposited on the plains by the wind that blows strongly across the plains as there is little to no windbreaks. Along the River System, these gravel sized stones are transported by the flow of water through traction and saltation processes. The large to medium sized stones negatively correlate with Axis 1, and this is where the Eastern Weissrand Plateau of Zygophyllum microcarpum―Rhigozum trichotomum Alliance 3, and the Western Escarpment Zone of Catophractes alexandri―Lycium bosciifolium Alliance 4 occur. On these 2 alliances, the stone sizes are larger and you get well-formed and structured rocks in these alliances on mountainous landscape level. Axis 2 in the ordination diagram reveals a soil depth and rainfall gradient with relevés (and species) of Alliance 1 and Alliance 2. This soil depth relates to tree set-up and ability of rooting structures to penetrate through the soil. The areas that have a proper soil content structure will have deeper roots able to penetrate, and you will find larger trees growing there. This is apparent for Alliance 1 on which there are big trees growing along the river with long roots, and also with Alliance 4 of the Western Escarpment Zone that has a lot more tree structures to support the soil depth hypothesis and ability of the roots to penetrate.

5.3 Vegetation description: patterns and relationships

The Nama Karoo in southern Africa is considered to be a dwarf shrub savanna ecosystem stretching from the central plateau of South Africa to the southern interior of Namibia. The Nama Karoo vegetation of south-central Namibia can be summarized into four alliances which relate to landscape level syntaxa, and these can be further classified into 16 associations under the landscape alliances as smaller plant

93 communities. All the vegetation units were defined on the basis of their floristic composition taking into consideration the diagnostic and constant species as guided by their fidelity values. The high frequency of dwarf shrubs in the surveyed relevés illustrated by all the Box and Whisker plot diagrams confirms that the study area is situated in a dwarf shrub savanna ecosystem with naturally dynamic co-dominance in vegetation type. 5.3.1 Comparison to other vegetation surveys There are limited possibilities of comparison to other studies in the area, but the described units can be assigned into existing, broader units or vegetation types. These can then be compared to units for other parts of southern Africa with similar vegetation. The species density of the study area is comparable to other descriptions within the Nama Karoo biome in southern Namibia when it comes to biodiversity patterns. The Nico observatories (Nico North and Nico South) of the BIOTA Southern African project (Jürgens et al. 2012), the vegetation of the Farm Haribes in the Nama Karoo biome of southern Namibia (Strohbach and Jankowitz 2012) and the Hierarchical Classification of the Nama Karoo in the Keetmanshoop area, south central Namibia (Dorendorf et al. 2010b) fall within the Nama Karoo. The Nico observatories display an average of 21 and 20 species per 1000 m², respectively (Jürgens et al. 2012), compared with the 17- 19 species per 1000 m² on farm Haribes while this study displays 8- 12 species per 1000 m² which is even lower compared to that of Nico North and Nico South, and also for the Farm Haribes. (Strohbach and Jankowitz 2012) relate the slightly lower values of farm Haribes compared to Nico observatories to surveying of Haribes being conducted only during a single, comparatively dry year, whilst the Nico observatories had been surveyed over a period of seven years (but not in 2005). This can also be related to the study of the Central Nama Karoo which has only been surveyed during a single dry year attributing to the lower species density. The total number of species observed at Haribes (218) is higher than the total number of species observed at both Nico North (166) and Nico South (204), which (Strohbach and Jankowitz 2012) attribute to the fact that the area sampled at Haribes is far bigger and more diverse than the 1 km² sample areas of the BIOTA observatories. The Central Nama Karoo had more species observed (330) than farm Haribes (218), Nico North (166) and Nico South (204). This is also as Strohbach and Jankowitz (2012) attributed, the Central Nama Karoo that is sampled is far bigger and more diverse than the 1 km² sample areas of Biota observatories and also bigger than Farm Haribes. There are not a lot vegetation descriptions for the Nama Karoo that can be compared to vegetation described in this paper, but however Volk and Leippert (1971) cited in Strohbach and Jankowitz (2012) refer to the class Rhigozetea as representing the larger dwarf shrub savanna of southern Namibia. This encompasses all those syntaxa containing Rhigozum trichotomum especially in the Catophractes alexandri―Lycium bosciifolium alliance. Giess (1998) cited in Strohbach and Jankowitz (2012) superficially described the Dwarf shrub savanna to be characterized for the greatest part by Rhigozum trichotomum, Parkinsonia africana, Acacia nebrownii, Boscia foetida subsp. Foetida, Catophractes alexandri, mentioning a few to be typical for this vegetation type. This is particularly true and confirmed

94 by the associations described in this paper. The species as noted by Giess (1998) make up the naming of the associations described in this paper, particularly as co-dominating species of the landscape. The Tetragonia schenkii―Tamarix usneoides alliance does not contain your typical Karoo dwarf shrubs as expected but can be considered as riparian patches cutting through the Karoo with vegetation brought downstream along these water courses. This also attributes to the Prosopis infestation (Strohbach, Kabajani, et al. 2015, Strohbach, Ntesa, et al. 2015) taking over the Fish river system from up along the catchment. This can be observed through thick stands along the river around Mariental towards Gibeon, and even less southwards towards Keetmanshoop. Palmer and Hoffman (1997) described the vegetation to be part of Griqualand West and Bushmanland, and its’ vegetation can be divided into two units at landscape level, arid shrubland and arid grassland. The arid shrublands are synonymous with Acocks’ (1953) in (Palmer and Hoffman 1997) Orange River Broken Veld and partly the Namaqualand Broken Veld, while the arid grasslands are synonymous with Werger (1973). Although Acocks’ and Leistner (1959) described their veld types not for Namibia but for South Africa, studies by Rutherford et al. (2003), shows similarities in vegetation composition with Cadaba aphylla―Salsola spp. Due to various linking species like Aloe dichotoma, Phaeoptilum spinosum and Cadaba aphylla.

5.3.2 Mapping of described units Mapping of the described units was attempted using a Landsat 7 image of the study area whereby a satellite image was clipped to an area slightly larger than the study area and imported into ArcMap 10.1 for a supervised classification. This proved very difficult and yielded no tangible results that could be used. The signatures used for associations extracted from relevé points were very similar on the landscape and the program could not differentiate them as some of the associations occur as small patches embedded within larger associations that are difficult to differentiate. One of those that proved to be difficult was differentiating between cloud cover and the vegetation unit of the Weissrand, represented by white patched pebbles and cobbles on the map. The map used also had rough terrain showing strong geology signals that were homogenous along heterogeneous vegetation whereby the RGB bands were not strong enough to represent vegetation coding.

Chapter 6: Conclusion

The vegetation of the central Nama karoo dwarf shrubland savanna of central southern Namibia can be stratified into five alliances that relate to landscape level, and 16 plant communities at association level defined by their floristic composition. The vegetation is dynamic and mosaic with a high variation between alliances on landscape level. This vegetation is primarily not suitable for livestock even though there are a lot of people in these areas that depend on this unsuitable vegetation for their livestock farming. Efforts need to be made in establishing the exact stocking rates for these vegetation units to better advice farmers in this area in order to ensure sustainability with little to no degradation of the area. This information is also required because the grazing index is biased towards cattle farming, even though there is primarily small stock farming activities taking place in the Nama Karoo. In terms of sensitivity of the vegetation, the units have a moderate sensitivity in terms of diversity, but great care still needs to be taken in conserving the protected and threatened plant species found in these units.

References

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Appendix 1 Annotated species list for The Nama Karoo Dwarf Shrub savanna in South Central Namibia

Leaf overal abundance

"Fish-Lewer- "The Eastern "The Western Raunkiaer Konkiep" River Weissrand Escarpment local Family species status layer life form size inclination chlorotype morphotype root Systems "The Central Plains" Plateau" Zone" abundance Acanthaceae

Blepharis integrifolia LC hl th mi la is Rare Rare

Blepharis mitrata LC hl th na ve is Rare Rare

Blepharis obmitrata LC hl th mi la is Rare Rare Rare

Blepharis spinifex E hl Rare Rare Occasional Rare

Hypoestes forskaolii hl th mi la is Rare Rare

Justicia species hl Rare Occasional Rare

Justicia guerkeana NE, LC hl Rare Rare

Monechma species hl Rare Occasional Occasional Occasional

Monechma divaricatum hl th mi la is Rare Rare Rare Rare

Monechma genistifolium sub.sp genistifolium E, LC hl Occasional Common Common Occasional

Monechma mollissimum LC hl Rare Rare

Monechma spartioides hl Rare Rare

Petalidium canescens E hl Rare Rare

Ruellia species E hl th mi la is Rare Rare

Barleria damarensis E hl Rare Rare

Barleria dinteri hl Rare Rare Rare

Barleria lancifolia hl ch mi pe is/de Rare Rare

Barleria rigida LC hl Rare Rare Aizoaceae

Aptenia geniculiflora hl Rare Rare

Brownanthus kuntzei hl Rare Rare

Galenia africana LC, Poisonous hl Rare Rare Rare Rare

Galenia papulosa LC hl Rare Rare Rare

101

Leaf overal abundance

Gisekia africana hl Occasional Common Rare Occasional Occasional

Plinthus sericeus s2 Rare Rare

Sesuvium sesuvioides hl Occasional Occasional Rare Rare Occasional

Stoeberia gigas NE, P, LC hl n-ph su Occasional Rare Rare Rare Rare

Tetragonia reduplicata E s2 ph su Rare Rare Rare Rare

Tetragonia schenckii E,LC,Poisonous s2 n-ph Abundant Common Rare Occasional Common

Aizoon giessii E, LC hl Rare Rare

Aizoon schellenbergii s2 m-ch Rare Rare Rare Amaranthaceae

Atriplex lindleyi subsp. inflata hl th Rare Rare

Celosia trigyna hl Rare Rare Rare

Hermbstaedtia species hl th Rare Rare

Kyphocarpa species hl th Rare Rare

Kyphocarpa angustifolia hl th mi la is Rare Occasional Occasional Rare

Leucosphaera bainesii LC s2 ch mi la do Rare Occasional Common Occasional

Salsola species DD s2 Occasional Widespread Occasional Occasional Common

Sericorema remotiflora hl th le la is Rare Rare

Suaeda merxmuelleri DD Rare Rare

Amaranthus thunbergii Poisonous hl th mi la is Rare Rare Rare Anacardiaceae

Searsia lancea s1 Rare Rare

Ozoroa crassinervia F s1 ph no la do/de Rare Rare Apocynaceae

Cryptolepis decidua NE, Poisonous Common Occasional Occasional Occasional

Hoodia gordonii P, NT s2 m-ch Rare Rare

Larryleachia marlothii NE, LC, P hl Rare Rare

Microloma incanum LC hl n-ph Rare Rare Rare 102

Leaf overal abundance

Microloma poicilanthum R Rare Rare

Tavaresia barklyi P s2 Rare Rare

Gomphocarpus filiformis LC hl Rare Rare Rare

Gomphocarpus fruticosus subsp. fruticosus Poisonous hl n-ph Rare Rare Rare Asparagaceae

Ledebouria floribunda geo Rare Rare Rare Rare

Ledebouria undulata geo cr mi la is/de pv Rare Rare Rare Rare

Pseudogaltonia clavata Poisonous geo cr me ve is/de ro/pv Rare Rare Rare

Asparagus cooperi s2 ch Pi ve is ro Rare Rare Occasional Occasional Occasional

Asparagus exuvialis s2 m-ph Rare Rare Rare Rare

Asparagus nelsii s2 ch Pi ve is ro Rare Rare

Asparagus virgatus hl n-ph Rare Rare Asphodelaceae

Aloe dichotoma NE,P,VU,C2 t2 m-ph Rare Rare Rare

Aloe littoralis P,LC,C2 t2 mi-ph Rare Rare Rare Asteraceae

Athanasia minuta Poisonous Rare Rare Rare

Berkheya spinosissima subsp. spinosissima s2 Rare Rare Rare

Calostephane divaricata hl th mi ve is Rare Rare

Chrysocoma obtusata Rare Rare

Conyza bonariensis Inv Rare Rare

Dicoma anomala subsp. gerrardii hl Rare Rare

Dicoma capensis DD hl Rare Rare Rare Rare

Dicoma schinzii hl th mi la do Rare Rare

Dicoma tomentosa hl ch/th mi ve do Rare Rare

Emilia marlothiana hl Rare Rare

Felicia species E Rare Rare Rare 103

Leaf overal abundance

Flaveria bidentis Inv hl th mi la is Rare Rare

Geigeria species Rare Rare Rare

Geigeria ornativa Poisonous, DD hl th mi ve is Occasional Occasional Rare Occasional Occasional

Geigeria pectidea LC hl th Rare Rare

Helichrysum argyrosphaerum Poisonous hl th na la do Rare Rare Rare

Kleinia longiflora s2 ch me ve is so/su Rare Rare Rare Rare

Laggera decurrens s2 ch na co is Rare Rare

Nolletia arenosa hl ch Rare Rare Rare

Ondetia linearis E, LC, Poisonous Occasional Occasional Rare Rare Occasional

Pechuel-Loeschea leubnitziae s1 ph Rare Rare Rare

Pegolettia senegalensis LC hl th le la is Rare Rare Rare Rare

Platycarphella carlinoides Rare Rare Rare

Pteronia cylindracea s2 Rare Rare Rare Rare Rare

Senecio consanguineus hl th Rare Rare Rare

Tagetes minuta Inv hl th mi la is fi Rare Rare

Aspilia eenii E Rare Rare Rare Rare Rare Bignoniaceae

Rhigozum obovatum s2 Rare Rare

Rhigozum trichotomum t2 ph Occasional Common Widespread Abundant Common

Catophractes alexandri LC, NE s1 ph mi la do Rare Occasional Abundant Common Boraginaceae

Trichodesma africanum s2 th Rare Rare

Wellstedia dinteri s. dinteri hl ch Rare Rare Rare

Heliotropium species Rare Rare

Naturalised, semi- Heliotropium curassavicum aquatic Rare Rare

Heliotropium ovalifolium hl ph mi la is Rare Rare 104

Leaf overal abundance

Heliotropium rariflorum subsp. Hereroense Rare Rare Brassicaceae

Lepidium englerianum Naturalised Rare Rare

Erucastrum arabicum hl th Rare Rare Burseraceae

Commiphora dinteri E, LC s1 Rare Rare Rare

Commiphora pyracanthoides LC s1 ph mi la is/de ct Occasional Rare Capparaceae

Cadaba aphylla LC s1 ph Occasional Rare Common Common Occasional

Maerua schinzii F, LC t2/s1 ph mi la is Rare Occasional Rare Rare

Boscia albitrunca F, LC t2 ph mi la is sc Rare Rare Rare

Boscia foetida subsp. foetida LC s1 ph na la is sc Rare Rare Occasional Abundant Occasional

Cleome angustifolia hl th le la is Rare Occasional Rare Rare

Cleome angustifolia subsp. diandra hl Rare Rare

Cleome gynandra hl th mi la is Rare Rare

Cleome paxii NE Rare Rare

Cleome rubella hl th na la is Rare Rare Rare

Cleome suffruticosa E Rare Occasional Occasional Rare Celastraceae

Gymnosporia senegalensis s2 ch mi la is sc Rare Rare Convolvulaceae

Evolvulus species hl Rare Rare Rare Rare Rare

Ipomoea adenioides s2 ch no la is/de sc Rare Rare Rare

Merremia species Rare Rare

Convolvulus ocellatus Rare Rare Rare

Convolvulus sagittatus hl Rare Rare Cucurbitaceae 105

Leaf overal abundance

Coccinia species hl li Rare Rare Rare Rare

Coccinia rehmannii hl li Rare Rare

Corallocarpus welwitschii hl li Rare Rare

Cucumis species Rare Rare Rare Rare

Cucumis africanus Poisonous hl li/th no la is Rare Rare

Kedrostis foetidissima Rare Rare

Citrullus lanatus hl th/li me la is Rare Rare Rare Ebenaceae

Euclea pseudebenus NC t1 ph Common Rare Rare Rare

Euclea undulata NN s1 ph na ve is Rare Rare Rare Euphorbiaceae

Tragia dioica hl th/li mi la is Rare Rare

Euphorbia species Rare Occasional Rare Rare Rare

Euphorbia gariepina LC ph Rare Rare

Euphorbia glanduligera LC hl hc Occasional Occasional Occasional Occasional

Euphorbia gregaria NE, LC s2 ph Occasional Occasional

Euphorbia guerichiana LC, CII s1 ph Rare Rare Rare

Euphorbia hirta Naturalised hl th na la is Rare Rare Rare Rare

Euphorbia inaequilatera hl th mi la is Rare Occasional Rare Rare Rare

non-indigenous Euphorbia serpens (uncertain status) Rare Rare Rare Rare

Euphorbia virosa Poisonous, LC ph su Rare Rare Rare Fabaceae

Adenolobus garipensis NN s1 ph Occasional Rare Rare

Albizia anthelmintica F t2 ph mi la isde fi Rare Rare Rare

Crotalaria damarensis hl th mi ve is Rare Rare 106

Leaf overal abundance

Crotalaria dinteri Schinz Rare Rare

Crotalaria kurtii Schinz E, DD Rare Rare

Crotalaria teixeirae Rare Rare Rare

Cullen tomentosum hl Rare Rare Rare

Dichrostachys cinerea LC s2 th mi ve is pv Rare Rare

Indigastrum argyraeum hl Rare Rare Rare Rare

Indigofera species Occasional Occasional Occasional Occasional

Indigofera auricoma hl th na ve is Rare Rare

Indigofera cryptantha hl ph Rare Rare

Indigofera merxmuelleri E Rare Rare

Indigofera pechuelii LC s2 cr mi la is fi Rare Occasional Occasional

Leobordea platycarpa LC hl th no la is Rare Rare

Lotononis strigillosa NE, LC th Rare Rare

Melolobium microphyllum Rare Rare

Neorautanenia species Rare Rare

Otoptera burchellii s2 ch mi la is/de Rare Rare Rare

Parkinsonia africana F ph Occasional Occasional Occasional Occasional Occasional

Prosopis species Transformer ch mi la do Occasional Rare Rare Rare Rare

Ptycholobium biflorum NE hl ch mi la do Rare Rare Rare Rare

Requienia sphaerosperma hl th mi la is Rare Rare

Rhynchosia totta hl cr/li mi la is Rare Rare

Senna italica subsp. Arachoides cr/li no la is/de Rare Rare

Tephrosia species Rare Rare Occasional Occasional

Tephrosia dregeana var. dregeana NE th mi la is fi Rare Rare Rare

Xerocladia viridiramis s2 ch Rare Rare Rare Rare

Acacia erioloba F, Poisonous t2 ph mi la is/de fi Common Rare Rare Occasional

Acacia hebeclada subsp. hebeclada Poisonous t2 ph mi la is fi Rare Rare Rare Rare 107

Leaf overal abundance

Acacia hereroensis LC t2 ph Rare Rare

Acacia karroo LC t2 ph mi la is/de fi Common Rare Rare Occasional

Acacia mellifera subsp. Detinens LC t2 ph mi la is/de fi Occasional Rare Occasional Common Occasional

Acacia nebrownii LC t2 ph mi la is/de fi Occasional Common Rare Common Occasional

Acacia senegal s. mellifera LC t2 ph Occasional Occasional

Acacia tortilis LC t2 ph mi la is/de fi Common Rare Rare Occasional Geraniaceae

Sarcocaulon patersonii NE, LC s2 ch Rare Rare

Monsonia parvifolia hl Rare Rare Rare Lamiaceae

Leucas pechuelii NE hl ch mi la do Rare Rare

Ocimum americanum var. americanum hl th na la is Rare Rare Rare Rare

Acrotome species Rare Rare Rare Loasaceae

Kissenia capensis hl ph Rare Rare Rare Loranthaceae

Tapinanthus oleifolius LC para ch Occasional Occasional Rare Occasional Occasional Malvaceae

Hibiscus species Rare Occasional Rare

Hibiscus elliottiae s1 ch mi la is/de Rare Rare Rare

Abutilon species Rare Rare Meliaceae

Nymania capensis s1 ph Rare Rare Rare Rare Molluginaceae

Limeum species Occasional Rare Rare Rare Rare

Limeum aethiopicum s. namaense v. lanceol hl ch Rare Rare Rare Occasional Rare

Limeum argute-carinatum LC hl th le la is Occasional Occasional Rare Occasional Occasional 108

Leaf overal abundance

Limeum fenestratum LC hl th le la is Rare Rare Rare

Limeum viscosum subsp. viscosum var. viscosum hl th le la is Rare Rare

Mollugo cerviana hl th le la is Rare Rare Rare Rare Rare

Mollugo walteri E, LC hl Rare Rare Rare

Hypertelis bowkeriana LC hl Rare Rare Montiniaceae

Montinia species Rare Rare Rare

Montinia caryophyllacea s2 ph mi ve is Rare Rare Rare Moraceae

Ficus cordata subsp. cordata F t3 Rare Rare Rare Nyctaginaceae

Phaeoptilum spinosum S1 ph Rare Rare Papaveraceae

Naturalised, Argemone ochroleuca Poisonous hl Occasional Rare Rare Pedaliaceae

Sesamum species Rare Rare Rare Rare

Sesamum capense LC hl th no la is Rare Occasional Rare Occasional Rare

Sesamum triphyllum hl th no la is Rare Rare Phyllanthaceae

Phyllanthus maderaspatensis hl hc na la is Rare Rare Rare Phytolaccaceae

Lophiocarpus polystachyus LC hl ch Rare Rare Plumbaginaceae

Dyerophytum africanum hl ph Rare Rare Rare Poaceae

Aristida adscensionis ga th mi co is pv Rare Rare 109

Leaf overal abundance

Aristida congesta subsp. congesta gp hc mi co is pv Rare Common Occasional Common Occasional

Aristida meridionalis gp hc mi co is pv Rare Rare Rare Rare

Brachiaria glomerata ga is pv Rare Rare

Cenchrus ciliaris gp hc mi co is pv Occasional Rare Rare Occasional Occasional

Chloris virgata ga th mi co is pv Occasional Common Rare Rare Occasional

Cynodon dactylon Poisonous, Weed gp hc na ve is pv Rare Rare

Dactyloctenium aegyptium ga th mi co is pv Rare Rare

Digitaria eriantha gp is pv Rare Rare

Enneapogon cenchroides LC ga th mi co is pv Common Common Common Common Occasional

Enneapogon desvauxii ga th le ve is pv Common Occasional Occasional Occasional

Entoplocamia aristulata ga is pv Occasional Occasional Occasional Occasional

Eragrostis echinochloidea gp hc mi co is pv Occasional Rare Rare Rare

Eragrostis nindensis gp hc na ve is pv Rare Occasional Occasional Common Occasional

Eragrostis pallens gp hc mi co is pv Rare Rare Rare Rare Rare

Eragrostis porosa LC ga th mi co is pv Occasional Occasional Rare Occasional Occasional

Eragrostis rotifer semi-aquatic gp th mi co is pv Common Common Occasional Occasional Occasional

Eragrostis superba gp is pv Rare Rare

Eragrostis viscosa ga th mi co is pv Rare Rare Rare

Fingerhuthia africana LC gp hc/(th) na co is pv Rare Rare Rare

Heteropogon contortus gp hc mi co is pv Rare Rare

Hyparrhenia hirta gp is pv Rare Rare

Leptochloa fusca Aquatic gp is pv Occasional Occasional Rare Rare Occasional

Melinis repens gp hc mi co is pv Rare Occasional Occasional Occasional

Melinis repens subsp. grandiflora LC ga th mi co is pv Rare Rare Rare

Microchloa caffra LC gp hc na ve is pv Rare Rare

Panicum species gp is pv Rare Rare Rare Rare 110

Leaf overal abundance

Panicum coloratum LC, Poisonous gp hc mi ve is pv Rare Rare

Panicum lanipes gp hc mi ve is pv Rare Rare

Panicum maximum LC, Poisonous gp hc mi co is pv Rare Rare Rare Rare Rare

Pennisetum clandestinum Naturalised gp is pv Rare Rare

Schmidtia kalahariensis LC ga th mi la is pv Common Occasional Rare Occasional Occasional

Schmidtia pappophoroides LC gp hc mi la is pv Rare Rare Rare Rare

Setaria verticillata LC ga th mi co is pv Occasional Rare Rare Rare

Stipagrostis amabilis gp is pv Rare Rare Rare

Stipagrostis ciliata LC gp is pv Occasional Abundant Abundant Abundant Common

Stipagrostis hirtigluma subsp. hirtigluma LC ga th mi co is pv Occasional Occasional Occasional Occasional

Stipagrostis namaquensis gp is pv Common Rare Rare Rare Occasional

Stipagrostis obtusa LC gp is pv Rare Occasional Rare Occasional

Stipagrostis uniplumis LC gp hc mi co is pv Rare Rare Rare Rare

Themeda triandra LC gp is pv Rare Rare Rare

Tragus species ga is pv Rare Rare Rare

Tragus berteronianus LC ga hc mi ve is pv Rare Rare Rare

Tragus koelerioides gp is pv Rare Rare Rare Rare

Tragus racemosus LC ga th na la is pv Rare Occasional Rare Rare Rare

Tricholaena monachne LC ga th mi co is pv Rare Rare

Triraphis purpurea ga th mi co is pv Rare Rare Rare Rare

Triraphis ramosissima gp is pv Rare Rare Rare

Urochloa brachyura LC ga th mi co is pv Rare Rare

Anthephora pubescens gp hc mi ve is pv Rare Rare Rare Rare Portulacaceae

Portulaca oleracea Naturalised hl th Occasional Common Occasional Occasional Occasional Rhamnaceae

Ziziphus mucronata F t1 ph mi pe is Occasional Rare Rare Rare Rare 111

Leaf overal abundance

Kohautia angolensis Rare Rare

Kohautia cynanchica hl th na la is Rare Rare Rutaceae

Thamnosma africana hl Rare Rare Santalaceae

Viscum rotundifolium LC s2 ch Rare Rare Sapindaceae

Pappea capensis hl Rare Rare Scrophulariaceae

Aptosimum albomarginatum DD hl ch na ve is sc Rare Rare

Aptosimum lineare hl ch mi co is Rare Rare

Aptosimum lugardiae hl ch le la is Rare Rare Rare

Aptosimum spinescens s2 ch Occasional Occasional Common Common Occasional

Jamesbrittenia adpressa Rare Rare Rare

Jamesbrittenia atropurpurea hl hc le la is Rare Rare

Jamesbrittenia huillana Rare Rare

Jamesbrittenia pilgeriana E Rare Rare

Peliostomum leucorrhizum hl ch le la is Rare Rare Rare

Selago alopecuroides LC hl Rare Rare Rare

Selago dinteri LC hl hc Rare Rare

Selago divaricata LC s2 ph Rare Rare

Selago kurtdinteri LC hl ch Rare Rare

Anticharis ebracteata E, LC hl Rare Rare

Anticharis senegalensis hl Rare Rare Rare Solanaceae

Lycium bosciifolium DD s1 ch na la is sc Abundant Rare Rare Abundant Common 112

Leaf overal abundance

Lycium cinereum DD s1 ph le co is Rare Rare

Lycium eenii DD s1 ch mi la is sc Occasional Occasional Rare Rare

Lycium horridum Rare Rare

Solanum species Rare Rare Rare Rare Rare

Solanum capense hl ch Rare Rare Rare

Solanum multiglandulosum ch mi ve is Rare Rare Rare Rare

Invasive, Datura species Poisonous Occasional Rare Sterculiaceae

Hermannia species hl Rare Rare Rare Rare

Hermannia affinis hl ph Rare Rare Occasional Rare

Hermannia gariepina hl ch Rare Rare

Hermannia juttae E hl Rare Rare

Hermannia modesta hl ch na la is/do Occasional Rare Rare Rare

Hermannia paucifolia hl Rare Rare

Hermannia spinosa hl Rare Rare Rare

Hermannia tomentosa hl ch Rare Occasional Occasional Rare Tamaricaceae

Tamarix usneoides F s2 ph Common Rare Occasional Tiliaceae

Grewia flava s2 ph no la is/de Rare Rare Rare

Grewia flavescens s2 ph no la is/de Rare Rare Rare Urticaceae

Forsskaolea candida LC hl Rare Rare Rare

Forsskaolea viridis LC hl th Rare Rare Verbenaceae

Lantana species Rare Rare 113

Leaf overal abundance

Chascanum garipense hl Rare Rare Rare Rare Rare Zygophyllaceae

Sisyndite spartea NE, LC s2 ph Rare Rare Rare Rare

Tribulus terrestris Poisonous hl th mi la is fi Common Common Common Common Occasional

Tribulus zeyheri hl ch mi la is fi Rare Rare Rare Rare

Zygophyllum cretaceum s2 Rare Rare Rare

Zygophyllum microcarpum NE, Poisonous, LC S2 Occasional Common Occasional Occasional

Zygophyllum rigidum LC, NE s2 ch Occasional Rare Rare Occasional

Zygophyllum simplex LC hl th Occasional Occasional Rare Rare Occasional

Zygophyllum tenue LC s2 ch Rare Rare

Neoluederitzia sericeocarpa E, CR s1 Occasional Rare

(Klaassen and Kwembeya 2013, Strohbach 2013) ―Codes and symbols (Abbreviations) derived from these sources

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Appendix 2 Field Sheet for Data Collection

Habitat Description

Observer: Number: Computer No:

Landscape: Date: Altitude:

Locality: Region: GPS reading: ° ‘ “ S District: ° ‘ “ E Owner: Accuracy of GPS: (WGS84) Estimate from General estimate 1:50 000 map

Landscape: Local Topography: Level land LP Plain <8% <100m/km LPP Plain LPS Sand drift plain Covered by >50 % sand (unconsolidated) LPI Interdunal street LPD Low dunefield Plains with low dunes like hummock dunes LPF Flood plain Temporary water logged, especially along river systems LPO Oshana Shallow channels of the Cuvelai delta LPM Omuramba Shallow, broad drainage lines of the erosion plains LL Plateau <8% <100m/km LLP Plateau LD Depression <8% <100m/km LDP Pan Seasonally water filled LF Low gradient footslope <8% <100m/km LFF Low gradient footslope LV Valley floor <8% <100m/km LVR Dry river bed LVBD Dry river embankment LVB Perennial river embankment Sloping land SM Medium gradient 15-30 % >600m/2km SMM Medium gradient mountain mountain SMF Medium gradient footslope SML Medium gradient plateau SH Medium gradient hill 8-30 % >50 m/slope SHH Medium gradient hill unit SE Medium gradient 15-30 % <600m/2km SER River terrace Especially along the Okavango and Omurambas in escarpment zone the Kalahari sand plateau SDP Pan terrace / rim SR Ridges 8-30 % >50 m/slope SRR Rocky ridges unit SRDF Fossil dunes: foot SRDS Fossil dunes: slope SRDC Fossil dunes: crest SRAS Active dunes: slip face SRAW Active dunes: windward face SU Mountainous highland 8-30 % >600m/2km SUU Mountainous highland SP Dissected plain 8-30 % Variable SPP Dissected plain SPA Alluvial fan SWC Water courses and small rivers Steep land TM High gradient mountain >30 % >600m/2km TMM High gradient mountain TMF High gradient footslope TMB Inselbergs, bornhardts TH High gradient hill >30 % <600m/2km THH High gradient hill THR Rocky outcrops like dolerite koppies TE High gradient >30 % >600m/2km TEE Escarpment escarpment zone TET Tallus slope TV High gradient valleys >30 % Variable TVC Canyon slope TWC Steep water courses and ravines

115

Land with composite landforms CV Valley >8 % Variable Other: CL Narrow plateau >8 % Variable CD Major depression >8 % Variable

Slope: Flat Gently undulating Undulating Rolling Moderately steep Steep Very steep Extremely steep 0 – 1° 1 – 3° 3 – 6° 6 – 9° 9 – 17° 17 – 30° 30 – 50° > 50° (0-2%) (2-5%) (5-10%) (10-15%) (15-30%) (30-60%) (6-120 %) (>120%) Stoniness: Cover & Size: Aspect:

None Gravel 0.2-2 Pebbles 2-6 cm Medium 6-20 Large 20-60 cm Rock >60 cm Lithology: cm cm 0-2 % 2-5 % 5-15 % 15-40 %

40-80 % >80 % Acidic igneous rock IA1 Granite Clastic sediments SC1 Conglomerate, Breccia IA2 Grano-diorite SC2 Sandstone, greywacke, arkose IA3 Quartz-doprite SC3 Siltstone, mudstone, claystone IA4 Rhyolite SC4 Shale Intermediate igneous rock II1 Andesite, trachyte, phonolite Organic sediments SO1 Limestone and other carbonate rocks II2 Diorite-syenite SO2 Marl and other mixtures Basic igneous rock IB1 Gabbro SO3 Coals, bitumen and related rocks IB2 Basalt Evaporites SE1 Anhydrite, gypsum IB3 Dolerite SE2 Halite Ultrabasic igneous rock IU1 Peridotite Unconsolidated material UF Fluvial IU2 Pyroxenite UL Lacustrine IU3 Ilmenite, magnetite, UM Marine ironstone, serpentine UC Colluvial Acidic metamorphic rock MA1 Quartzite UE Eolian MA2 Gneiss, magmatite UG Glacial Basic metamorphic rock MB1 Slate, phylite (peltic rocks) UP Pyroclastic UO Organic MB2 Schist UCa Calcrete MB3 Gneiss rich in ferro- Other: magnesian minerals MB4 Metamorphic limestone (marble)

Erosion: none Wind erosion Wind Shifting sand Sheet Rill erosion Gully erosion Deposition by deposition erosion water slight moderate severe extreme

Surface Crusting: None Weak Moderate Strong Clay bubbles (Schaumböden) (soft or slightly hard, <0.5 (soft or slightly hard, >0.5 (hard crust >0.5 cm) present cm thick) cm thick, or hard <0.5 cm)

Rooting Depth: Very shallow Shallow Moderately deep Deep Very deep < 30 cm 30 – 50 cm 50 – 100 cm 100 – 150 cm > 150 cm

Disturbances: None Herbicides Selective Mechanical clearing clearing Fire Bush Severe Deforestatio encroachmen overgrazing n t

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Vegetation Data

Observer: Number: Computer No:

Landscape: Date: Altitude:

Locality: Region: GPS reading: ° ‘ “ S District: ° ‘ “ E Owner: Accuracy of GPS: (WGS84) Estimate from General estimate 1:50 000 map

Vegetation structure:

Total Trees Shrubs >1m Trees and Shrubs <1m Grasses Herbs shrubs Average height Total cover Vegetation structure:

Th: High tree >20m Tt: Tall tree 10 – 20m Ts: Small tree 5 –1 0m Tl: Low tree 2- 5m Sh: High shrub 2 –5 m St: Tall shrub 1 – 2m Ss: Small shrub 0.5 – 1 m Sl: Low shrub <50cm

Species composition:

Coll. Species Abundance by growth form No T1 T2 T3 S1 S2 Hl Th Tt Ts Tl Sh St Ss Sl G H

Total cover: 117

Coll. Species Abundance by growth form No T1 T2 T3 S1 S2 Hl Th Tt Ts Tl Sh St Ss Sl G H

Total cover:

118