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1 Commentary 2 3 Nature conservation at the edge 4 5 Jan Christian Habel1*, Mike Teucher2, Ronald K. Mulwa3, Wolfgang Haber4, 6 Hilde Eggermont5,6, Luc Lens7 7 8 1 9 School of Life Sciences Weihenstephan, Technische Universität München, D-85354 Freising, Terrestrial Ecology Research Group, Department of Ecology and Ecosystem Management, 10 Germany 11 2 Department of Cartography, Trier University, D-54286 Trier, Germany 12 3 Zoology Department, National Museums of Kenya, K-00100 Nairobi, Kenya 13 4 Department of Ecology and Ecosystem Management, School of Life Sciences 14 Weihenstephan, Technische Universität München, D-85354 Freising, Germany 15 5 16 1000 Brussels, Belgium 17 6 Limnology Unit, Department of Biology, Ghent University, B-9000 Ghent, Belgium 18 7 Terrestrial Ecology Unit, Department of Biology, Ghent University, B-9000 Ghent, Belgium Belgian Biodiversity Platform, OD Nature, Royal Belgian Institute of Natural Sciences, B- 19 20 *Corresponding author: 21 Jan Christian Habel, Terrestrial Ecology Research Group, Department of Ecology and 22 Ecosystem Management, School of Life Sciences Weihenstephan, Technische Universität 23 München, Hans-Carl-von-Carlowitz-Platz 2, D-85354 Freising, Germany 24 E-Mail: [email protected] 25 1 26 Key-words: Agro-ecological zone, biodiversity, cash crop, evidence-based conservation, food 27 security, food crop, human population, nature reserve, prioritization 28 2 29 ABSTRACT 30 Currently, there is an increasing need for evidence-based strategies in nature conservation, for 31 example when designing and establishing nature reserves. In this contribution, we critically 32 assess the ecological relevance of recent nature conservation practices in Kenya (East Africa), 33 a region of global biodiversity hotspots. More specifically, we overlay the distribution of 34 species richness (here based on mammals, birds, amphibians and vascular plants) with the 35 location of nature reserves, the Kenyan agro-ecological zones (areas representing diverging 36 agricultural potentials), and with the spatial distribution of human population density. Our 37 analyses indicate that the majority of protected areas are located in areas with comparatively 38 low species richness, while areas with extraordinary high levels of species richness are not 39 adequately covered by protected areas. Areas of high agricultural productivity (and with high 40 human demographic pressure) are mainly reserved for high-yield agriculture; however, these 41 regions are also characterised by high species richness. The majority of nature reserves are 42 restricted to the semi-arid regions of Kenya, marginal for agricultural usage, but also with low 43 levels of species richness. Based on this analysis, we prioritize areas for future protection. 44 This single-country case illustrates that agricultural production in high-yield areas outweighs 45 nature conservation goals, even in global biodiversity hotspot regions, and that priority setting 46 may conflict with effective nature conservation. 47 3 48 Introduction 49 Recent studies critically examined the efficiency and relevance of nature conservation, which 50 often focuses on the protection of large and charismatic species (rather than of species with 51 high ecological relevance, or species groups like arthropods providing the mass of 52 biodiversity, see Stork & Habel 2014), maintenance of specific successional stages of selected 53 ecosystems (Rodrigues et al. 2006), or the conservation of man-made landscapes, in particular 54 in Europe (Plieninger et al. 2006). In the meantime, other studies from scientists and 55 practitioners plea for a revolution in nature conservation, towards more objectivity in 56 conservation strategies with management based on ecological evidences rather than on 57 political agendas (Pullin & Knight 2003, Sutherland et al. 2004, Svancara et al. 2005). 58 59 Most of the established nature reserves in Sub-Saharan Africa are a legacy from the past 60 colonial era (MacKenzie 1997, Lindsey et al. 2007). Examples are the vast savannahs in 61 semiarid regions such as the Lowveld in Southern Africa or the Mara-Serengeti plains in East 62 Africa. These nature reserves form the main body of wildlife tourism and nature conservation, 63 and have high economic importance for many African countries (e.g. the Kenyan National 64 Parks, with >2 billion visitors per year, KNBS 2014; 12.1% of the GDP and 9.2% of total 65 employment (WTTC 2015)). However, most of these lowland protected areas are 66 characterised by marginal agricultural value and low ecological productivity, and hold a 67 comparatively small proportion of the total species richness too (Waide et al. 1999). 68 69 In this commentary, we question the ecological relevance of many of these selected areas for 70 nature conservation in Sub-Saharan African countries, and we illustrate our case with Kenya, 71 one of the leading countries in African wildlife conservation and tourism. We therefore 72 performed a country-wide assessment of (i) the distribution of species richness based on 73 mammals, birds, amphibians and vascular plants (cross-taxon consensus percentage of species 4 74 occurrence per 25x25 km grid cell), and of global biodiversity hotspots (according to 75 Conservation International; Myers et al. 2000, Mittermeier et al. 2011); (ii) the location of 76 nature conservation reserves (protected areas according to IUCN and UNEP-WCMC (2015) 77 categories, including governmental and private conservation areas); (iii) the distribution of 78 agro-ecological zones (AEZs) based on temperature, rainfall regimes and altitude; and (iv) the 79 distribution of the human population using census data of the year 2009 (KNBS 2015). In a 80 second step, we assessed potential spatial congruencies and discongruencies by creating a 81 consensus map of species richness based on the four taxa studied and spatially overlapping 82 this map with the current location of nature reserves (Fig. 1), AEZs, and human population 83 data (Fig. 2). 84 85 Centres of species richness beyond protected areas 86 At present, Kenya holds 249 governmental and non-governmental (private conservancies) 87 nature reserves that jointly cover about 8% of the country. However, the distribution of these 88 nature reserves is geographically uneven. Likewise, species richness is unevenly distributed, 89 with areas of high (endemic) species accumulation across the Eastern Afromontane region 90 (e.g. Taita Hills, Chyulu Hills, Central Kenyan highlands including the Aberdares, Mau 91 Escarpment or Mt. Kenya, as well as the mountain ranges in the north of Kenya) and the 92 Coastal Forests (both regions classified as global biodiversity hotspots, Mittermeier et al. 93 2011; see also Bennun and Njoroge 1999, Burgess et al. 2007) (Appendix S1). This spatial 94 distribution of high species richness is congruent with former studies on amphibians and 95 reptiles (Spawls et al. 2002, Lötters et al. 2007, Poynton et al. 2007, Measey et al. 2009), 96 birds (Zimmermann et al. 1999), butterflies (Larsen 1991), and vascular plants (Lovett 1998, 97 Burgess et al. 2005, Platts et al. 2010). 98 5 99 Our intersect analyses indicate that areas with high levels of species richness only cover 100 20.2% of the total area of Kenya - the highlands. But, o nly a very small proportion (14.1%) 101 of protected land is located in these highland regions (FAO 2009), and only 56 of the 249 102 nature reserves in Kenya (22.5%) overlap with the Eastern Afromontane and Coastal Forests 103 biodiversity hotspots. Only 20% (1,795,730ha) of protected areas cover regions with 104 extraordinary high species richness (>40% of the mean number of species over all taxonomic 105 groups analysed here). In reverse, 80% of all nature reserves are located beyond regions of 106 high levels of species richness. The top ten grid cells with highest levels of species richness 107 can be found in the Western and Central part of Kenya (protected by Kakamega and Nandi 108 forest, Aberdare forest reserve, Kikuyu Escarpment, Mt. Longonot, Moguga Forest, and Lake 109 Niavasha). But even these areas are only partially covered by nature reserves (Appendix S2). 110 111 Furthermore, most of nature reserves found at higher elevations are comparatively small 112 (266.2±435.1km²) compared to the mean size of nature reserves in Kenya (387.2±1125.1km²). 113 This disparity between spatial distribution of species richness and the location and extent of 114 nature reserves seems to be a worldwide phenomenon, as indicated by Burgess and colleagues 115 (2005). Criteria used to define conservation areas are therefore questionable. 116 117 Protected areas and agro-ecological zones 118 We used data from the Farm Management Handbook of Kenya (FMHB; Jaetzold et al. 2012) 119 to better understand the above-mentioned discrepancy between the distribution of species 120 richness and nature reserves. The FMHB provides a substantial long-term country-wide 121 survey of biotic and abiotic data, such as rainfall patterns, temperature, soil type, soil fertility 122 and census data on the human population density (Jaetzold et al. 2012). Based on a matrix of 123 a six-step altitudinal temperature gradient and a seven-step potential evapotranspiration (PET) 124 gradient, ranging from 0.1 PET to 1.25 PET, a total of 42 combinations of agro-ecological 6 125 zones (AEZ) are distinguished in Kenya. These AEZs range from high to low (i.e. a complete 126 lack of) agricultural productivity (Jaetzold et al. 2012). For our study, we further assigned 127 these zones into four categories according to the PET-based humidity-aridity gradient, in 128 order to establish an altitudinal independent classification of agricultural productivity with 129 high potential (AEZ 0-2), medium potential (AEZ 3 and 4), low potential (AEZ 5) and very 130 low potential (AEZ 6 and 7). We spatially overlapped these AEZs with (i) areas conserved by 131 any nature protection status, and (ii) the distribution of the human population density. 132 133 According to these FMHB data, 81.4% of the Kenyan land is semi-arid to arid, and thus of 134 marginal agricultural value (so-called `worthless land´). When overlapping these AEZs with 135 areas that are protected to some degree, we found that most protected areas are restricted to 136 land of low agricultural value (characterised by comparatively low precipitation and 137 periodically sparsely occurring rainfalls). Vice versa, only 13.2% of protected areas are found 138 within AEZs of high agricultural potential (AEZ 1 and 2), and only 8.5% within areas of 139 medium agricultural value (AEZ 3 and AEZ 4). This picture is independent of the type of 140 protection, i.e. governmental (e.g. National Park) or non-governmental (e.g. Game 141 Conservancy). The spatial configuration is displayed in Figure 2. Further details on AEZ- 142 nature reserve overlaps (distinguished between governmental and non-governmental) are 143 given in Table 1. 144 145 The spatial distribution and dominance of the AEZ with low agricultural potential underlines 146 the economic impact of agro-industries in many African and other developing countries 147 (Habel et al. 2015 with references therein). More specifically, Kenya´s economy highly 148 depends on cash-crop production representing 19.4% of the GDP and 95.2% of total 149 employment (alongside tourism, mining and manufacturing) (Kiteme et al. 2008; Worldbank 150 2015, WTTC 2015). As a consequence, areas of high productivity (in Kenya mainly found in 7 151 highland regions) are heavily exploited for food and cash-crop production (especially since 152 the colonial era), while nature protection is restricted to regions with low (or no) agricultural 153 importance. 154 155 Biodiversity, nature conservation and human population pressure 156 The semi-arid lowlands, holding many nature reserves, have been suffering from increasing 157 human pressure and (over)exploitation of natural resources, like soils (KNBS 2015). The 158 increase in human population was particularly high during the colonial period, when highly 159 productive regions (the White-Highlands, Laikipia Plateau, Uasin Gishu Plateau; Jaetzold et 160 al. 2006, 2011) were transformed into cash-crop monocultures (Habel et al. 2015) and many 161 of the former local people had to move out from these highlands, and shifted to lowland areas 162 (Kipkorir 1978, Thurston 1987). A first census on the Kenyan human population size 163 estimates about 2 million people at the beginning of the 20th century, and by the end of the 164 colonial period in 1962 the human population had increased to 8.1 million people. Thereafter 165 (i.e. past 30 years), the human population further increased with more than 250% - i.e. from 166 16.26 million people in 1980 up to 40.9 in 2010 (Republic of Kenya 1964, KNBS 2015). This 167 situation caused an increasing parcelling of land-plots, and a rising need for more land to 168 produce enough food crops, with negative effects on ecosystem functions and services. Food 169 crop yields per ha, however, stagnated (e.g. from 1980 to 2012, production increased with 170 about 160% whereas yields per hectar increased by only 140%; FAOSTAT 2014). 171 Subsequently, the land needed to produce the same amount of food increased. This resulted in 172 conflicts between the production of cash-crops (agro-economy), food crops (subsistence 173 agriculture), and nature conservation across Kenya (Habel et al. 2015). Furthermore, wildlife- 174 conflicts arised especially along the borders of protected areas with, for example, illegal 175 logging in the Taita Hills cloud forest and the Kakamega forest, illegal hunting in Arabuko 176 Sokoke forest (Wildlifedirect 2009), and illegal pastoralism in vast areas of Tsavo and Mara 8 177 National Parks (Okello & Kiringe 2004, Kiringe & Okello 2007, FAO 2009, Job & Paesler 178 2013). Today, several protected areas are fenced (e.g. Aberdares, Nairobi, Nakuru, Marsabit 179 and Mt Kenya, Arabuko Sokoke National Park), not only to reduce conflicts between wildlife 180 and humans, but also to prevent activities of local people inside these protected areas. This 181 `gated conservation´ strategy might be the only viable solution, especially in densely 182 populated areas. Yet, it prevents any participation by the local community and the long-term 183 acceptance of people. as well as migration of wildlife among protected areas. The long-term 184 efficiency of such actions therefore remains highly questionable. 185 186 Prioritizing areas for future conservation activity 187 Our overlap analyses show that nature conservation strategies in Kenya mainly focus on areas 188 with rather low species richness, while areas of high ecological relevance are mostly typified 189 by high agricultural productivity, and thus often reserved for agricultural purposes. 190 Accordingly, demographic pressure in such areas is exceptionally high. We found that some 191 regions, such as the southern and south-western parts of Kenya as well as the coastal region, 192 show extraordinary high levels of species richness, but are without any - or only under 193 marginal - nature protection. This study hence underlines that the occurrence of the “big five” 194 (African lion Panthera leo, African elephant Loxodonta africana, African buffalo Syncerus 195 caffer, African leopard Panthera pardus pardus, and the African rhinoceros Diceros bicornis 196 i.e. Ceratotherium simum) still seems to be the decisive factor when selecting nature reserves 197 due to there importance for Kenya’s tourism, while the protection of prime biodiversity 198 regions seems to be of lesser priority. 199 9 200 Acknowledgement 201 We are grateful to Ralph Jaetzold and Berthold Hornetz (Trier, Germany) for providing the 202 valuable data-sets of the FMHB. We thank one anonymous referees for critical comments on 203 a draft version of this contribution. 204 10 205 References 206 Bennun LA, Njoroge P (1999) Important bird areas of Kenya. 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Annual Review of 300 Ecology and Systematics 30: 257-300. 301 302 Wildlifedirect (2009) http://davidngala.wildlifedirect.org/2009/01/28/bush-meat-survey-inarabuko-sokoke-forest/ (accessed 20.5.2015) 13 303 Worldbank (2015) World development indicators - agriculture, value added (% of GDP), 304 http://data.worldbank.org/data-catalog/world-development-indicators (accessed 305 20.5.2015) 306 World Travel and Tourism Council (2005) Benchmarking report Kenya 2015, 307 http://www.wttc.org/- 308 /media/files/reports/benchmark%20reports/country%20reports%202015/kenya%20%20 309 benchmarking%20report%202015.pdf (accessed 20.5.2015) 310 311 Zimmerman DA, Turner DA, Pearson DJ (1999) Birds of Kenya and Northern Tanzania, Field guide edition. 312 14 1 Figure 1: Overlap of all Kenyan nature reserves (governmental and non-governmental) (white 2 lines) with species richness (consensus percentage value across four taxa in relation to the 3 total number of species known for Kenya), classified into five categories. Species richness 4 includes distribution data of the following taxonomic groups: mammals and amphibians (data 5 from the IUCN Red List of threatened species, digital distribution maps), birds (data from 6 BirdLife International and NatureServe 2015), and vascular plants (data from Kier et al. 7 2005). Data were trimmed to fit for Kenya using the clip function in ArcGis, and transformed 8 into a 25x25km grid. 9 10 15 1 Figure 2: Overlap of all 249 governmental and non-governmental protected areas (data from 2 IUCN and UNEP-WCMC 2015) (black shaded), the four categories of AEZs (according to 3 FMHB), and the distribution of the human population density (inhabitants per ha) (data from 4 KNBS 2015). 5 6 16 1 Table 1: Overlap between agro-ecological zones (divided into four categories, data obtained 2 from FMHB) and protected areas (governmental and non-governmental, distinguished). 3 Values are expressed as percentages. Type of reserve Governmental Forest Reserve Marine National Park Marine National Reserve National Park National Reserve National Sanctuary Not Reported Total (Gov.)[%] Non-governmental Community Conservancy Community Nature Reserve Community Wildlife Sanctuary Group Ranch Private Nature Reserve Private Protected Area Private Ranch Wildlife Sanctuary Total (Non-gov.) [%] Total (both) [%] AEZ very low AEZ AEZ low medium AEZ high Total [%] 0.93 38.58 17.35 59.86 1.89 2.15 3.36 0.09 7.49 5.85 0.04 0.03 1.11 3.52 0.19 0.01 10.75 15.11 2.46 0.12 17.69 23.78 0.04 0.03 44.30 24.35 0.28 0.01 64.17 5.23 75.06 0.58 0.08 0.08 0.06 0.89 0.18 82.15 67.88 2.59 8.25 0.06 0.11 0.50 1.48 0.95 0.14 14.07 10.45 0.19 3.51 0.01 0.01 0.06 3.78 8.48 13.19 8.01 86.82 0.65 0.20 0.58 1.54 1.90 0.32 35.83 100.00 4 17 1 Electronic Appendix Supplementary Material 1: Distribution of species richness of terrestrial 2 mammals, amphibians, birds and vascular plants in relation to the total number species known 3 for Kenya. Species richness grouped into 10% classes (to a maximum of 70%), and displayed 4 as 25x25km grid cells. 5 6 18 1 Electronic Appendix Supplementary Material 2: Location of the 10 grid cells with highest 2 species richness (over all four taxonomic groups assessed), displayed as grey squares, 3 intersected by existing nature reserves. 4 19