Post on 10-Mar-2018
Commentary
Nature conservation at the edge
Jan Christian Habel1*, Mike Teucher2, Ronald K. Mulwa3, Wolfgang Haber4,
Hilde Eggermont5,6, Luc Lens7
1Terrestrial Ecology Research Group, Department of Ecology and Ecosystem Management,
School of Life Sciences Weihenstephan, Technische Universität München, D-85354 Freising,
Germany
2Department of Cartography, Trier University, D-54286 Trier, Germany
3Zoology Department, National Museums of Kenya, K-00100 Nairobi, Kenya
4Department of Ecology and Ecosystem Management, School of Life Sciences
Weihenstephan, Technische Universität München, D-85354 Freising, Germany
5Belgian Biodiversity Platform, OD Nature, Royal Belgian Institute of Natural Sciences, B-
1000 Brussels, Belgium
6Limnology Unit, Department of Biology, Ghent University, B-9000 Ghent, Belgium
7Terrestrial Ecology Unit, Department of Biology, Ghent University, B-9000 Ghent, Belgium
*Corresponding author:
Jan Christian Habel, Terrestrial Ecology Research Group, Department of Ecology and
Ecosystem Management, School of Life Sciences Weihenstephan, Technische Universität
München, Hans-Carl-von-Carlowitz-Platz 2, D-85354 Freising, Germany
E-Mail: Janchristianhabel@gmx.de
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Key-words: Agro-ecological zone, biodiversity, cash crop, evidence-based conservation, food
security, food crop, human population, nature reserve, prioritization
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ABSTRACT
Currently, there is an increasing need for evidence-based strategies in nature conservation, for
example when designing and establishing nature reserves. In this contribution, we critically
assess the ecological relevance of recent nature conservation practices in Kenya (East Africa),
a region of global biodiversity hotspots. More specifically, we overlay the distribution of
species richness (here based on mammals, birds, amphibians and vascular plants) with the
location of nature reserves, the Kenyan agro-ecological zones (areas representing diverging
agricultural potentials), and with the spatial distribution of human population density. Our
analyses indicate that the majority of protected areas are located in areas with comparatively
low species richness, while areas with extraordinary high levels of species richness are not
adequately covered by protected areas. Areas of high agricultural productivity (and with high
human demographic pressure) are mainly reserved for high-yield agriculture; however, these
regions are also characterised by high species richness. The majority of nature reserves are
restricted to the semi-arid regions of Kenya, marginal for agricultural usage, but also with low
levels of species richness. Based on this analysis, we prioritize areas for future protection.
This single-country case illustrates that agricultural production in high-yield areas outweighs
nature conservation goals, even in global biodiversity hotspot regions, and that priority setting
may conflict with effective nature conservation.
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Introduction
Recent studies critically examined the efficiency and relevance of nature conservation, which
often focuses on the protection of large and charismatic species (rather than of species with
high ecological relevance, or species groups like arthropods providing the mass of
biodiversity, see Stork & Habel 2014), maintenance of specific successional stages of selected
ecosystems (Rodrigues et al. 2006), or the conservation of man-made landscapes, in particular
in Europe (Plieninger et al. 2006). In the meantime, other studies from scientists and
practitioners plea for a revolution in nature conservation, towards more objectivity in
conservation strategies with management based on ecological evidences rather than on
political agendas (Pullin & Knight 2003, Sutherland et al. 2004, Svancara et al. 2005).
Most of the established nature reserves in Sub-Saharan Africa are a legacy from the past
colonial era (MacKenzie 1997, Lindsey et al. 2007). Examples are the vast savannahs in
semiarid regions such as the Lowveld in Southern Africa or the Mara-Serengeti plains in East
Africa. These nature reserves form the main body of wildlife tourism and nature conservation,
and have high economic importance for many African countries (e.g. the Kenyan National
Parks, with >2 billion visitors per year, KNBS 2014; 12.1% of the GDP and 9.2% of total
employment (WTTC 2015)). However, most of these lowland protected areas are
characterised by marginal agricultural value and low ecological productivity, and hold a
comparatively small proportion of the total species richness too (Waide et al. 1999).
In this commentary, we question the ecological relevance of many of these selected areas for
nature conservation in Sub-Saharan African countries, and we illustrate our case with Kenya,
one of the leading countries in African wildlife conservation and tourism. We therefore
performed a country-wide assessment of (i) the distribution of species richness based on
mammals, birds, amphibians and vascular plants (cross-taxon consensus percentage of species
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occurrence per 25x25 km grid cell), and of global biodiversity hotspots (according to
Conservation International; Myers et al. 2000, Mittermeier et al. 2011); (ii) the location of
nature conservation reserves (protected areas according to IUCN and UNEP-WCMC (2015)
categories, including governmental and private conservation areas); (iii) the distribution of
agro-ecological zones (AEZs) based on temperature, rainfall regimes and altitude; and (iv) the
distribution of the human population using census data of the year 2009 (KNBS 2015). In a
second step, we assessed potential spatial congruencies and discongruencies by creating a
consensus map of species richness based on the four taxa studied and spatially overlapping
this map with the current location of nature reserves (Fig. 1), AEZs, and human population
data (Fig. 2).
Centres of species richness beyond protected areas
At present, Kenya holds 249 governmental and non-governmental (private conservancies)
nature reserves that jointly cover about 8% of the country. However, the distribution of these
nature reserves is geographically uneven. Likewise, species richness is unevenly distributed,
with areas of high (endemic) species accumulation across the Eastern Afromontane region
(e.g. Taita Hills, Chyulu Hills, Central Kenyan highlands including the Aberdares, Mau
Escarpment or Mt. Kenya, as well as the mountain ranges in the north of Kenya) and the
Coastal Forests (both regions classified as global biodiversity hotspots, Mittermeier et al.
2011; see also Bennun and Njoroge 1999, Burgess et al. 2007) (Appendix S1). This spatial
distribution of high species richness is congruent with former studies on amphibians and
reptiles (Spawls et al. 2002, Lötters et al. 2007, Poynton et al. 2007, Measey et al. 2009),
birds (Zimmermann et al. 1999), butterflies (Larsen 1991), and vascular plants (Lovett 1998,
Burgess et al. 2005, Platts et al. 2010).
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Our intersect analyses indicate that areas with high levels of species richness only cover
20.2% of the total area of Kenya - the highlands. But, o nly a very small proportion (14.1%)
of protected land is located in these highland regions (FAO 2009), and only 56 of the 249
nature reserves in Kenya (22.5%) overlap with the Eastern Afromontane and Coastal Forests
biodiversity hotspots. Only 20% (1,795,730ha) of protected areas cover regions with
extraordinary high species richness (>40% of the mean number of species over all taxonomic
groups analysed here). In reverse, 80% of all nature reserves are located beyond regions of
high levels of species richness. The top ten grid cells with highest levels of species richness
can be found in the Western and Central part of Kenya (protected by Kakamega and Nandi
forest, Aberdare forest reserve, Kikuyu Escarpment, Mt. Longonot, Moguga Forest, and Lake
Niavasha). But even these areas are only partially covered by nature reserves (Appendix S2).
Furthermore, most of nature reserves found at higher elevations are comparatively small
(266.2±435.1km²) compared to the mean size of nature reserves in Kenya (387.2±1125.1km²).
This disparity between spatial distribution of species richness and the location and extent of
nature reserves seems to be a worldwide phenomenon, as indicated by Burgess and colleagues
(2005). Criteria used to define conservation areas are therefore questionable.
Protected areas and agro-ecological zones
We used data from the Farm Management Handbook of Kenya (FMHB; Jaetzold et al. 2012)
to better understand the above-mentioned discrepancy between the distribution of species
richness and nature reserves. The FMHB provides a substantial long-term country-wide
survey of biotic and abiotic data, such as rainfall patterns, temperature, soil type, soil fertility
and census data on the human population density (Jaetzold et al. 2012). Based on a matrix of
a six-step altitudinal temperature gradient and a seven-step potential evapotranspiration (PET)
gradient, ranging from 0.1 PET to 1.25 PET, a total of 42 combinations of agro-ecological
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zones (AEZ) are distinguished in Kenya. These AEZs range from high to low (i.e. a complete
lack of) agricultural productivity (Jaetzold et al. 2012). For our study, we further assigned
these zones into four categories according to the PET-based humidity-aridity gradient, in
order to establish an altitudinal independent classification of agricultural productivity with
high potential (AEZ 0-2), medium potential (AEZ 3 and 4), low potential (AEZ 5) and very
low potential (AEZ 6 and 7). We spatially overlapped these AEZs with (i) areas conserved by
any nature protection status, and (ii) the distribution of the human population density.
According to these FMHB data, 81.4% of the Kenyan land is semi-arid to arid, and thus of
marginal agricultural value (so-called `worthless land´). When overlapping these AEZs with
areas that are protected to some degree, we found that most protected areas are restricted to
land of low agricultural value (characterised by comparatively low precipitation and
periodically sparsely occurring rainfalls). Vice versa, only 13.2% of protected areas are found
within AEZs of high agricultural potential (AEZ 1 and 2), and only 8.5% within areas of
medium agricultural value (AEZ 3 and AEZ 4). This picture is independent of the type of
protection, i.e. governmental (e.g. National Park) or non-governmental (e.g. Game
Conservancy). The spatial configuration is displayed in Figure 2. Further details on AEZ-
nature reserve overlaps (distinguished between governmental and non-governmental) are
given in Table 1.
The spatial distribution and dominance of the AEZ with low agricultural potential underlines
the economic impact of agro-industries in many African and other developing countries
(Habel et al. 2015 with references therein). More specifically, Kenya´s economy highly
depends on cash-crop production representing 19.4% of the GDP and 95.2% of total
employment (alongside tourism, mining and manufacturing) (Kiteme et al. 2008; Worldbank
2015, WTTC 2015). As a consequence, areas of high productivity (in Kenya mainly found in
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highland regions) are heavily exploited for food and cash-crop production (especially since
the colonial era), while nature protection is restricted to regions with low (or no) agricultural
importance.
Biodiversity, nature conservation and human population pressure
The semi-arid lowlands, holding many nature reserves, have been suffering from increasing
human pressure and (over)exploitation of natural resources, like soils (KNBS 2015). The
increase in human population was particularly high during the colonial period, when highly
productive regions (the White-Highlands, Laikipia Plateau, Uasin Gishu Plateau; Jaetzold et
al. 2006, 2011) were transformed into cash-crop monocultures (Habel et al. 2015) and many
of the former local people had to move out from these highlands, and shifted to lowland areas
(Kipkorir 1978, Thurston 1987). A first census on the Kenyan human population size
estimates about 2 million people at the beginning of the 20 th century, and by the end of the
colonial period in 1962 the human population had increased to 8.1 million people. Thereafter
(i.e. past 30 years), the human population further increased with more than 250% - i.e. from
16.26 million people in 1980 up to 40.9 in 2010 (Republic of Kenya 1964, KNBS 2015). This
situation caused an increasing parcelling of land-plots, and a rising need for more land to
produce enough food crops, with negative effects on ecosystem functions and services. Food
crop yields per ha, however, stagnated (e.g. from 1980 to 2012, production increased with
about 160% whereas yields per hectar increased by only 140%; FAOSTAT 2014).
Subsequently, the land needed to produce the same amount of food increased. This resulted in
conflicts between the production of cash-crops (agro-economy), food crops (subsistence
agriculture), and nature conservation across Kenya (Habel et al. 2015). Furthermore, wildlife-
conflicts arised especially along the borders of protected areas with, for example, illegal
logging in the Taita Hills cloud forest and the Kakamega forest, illegal hunting in Arabuko
Sokoke forest (Wildlifedirect 2009), and illegal pastoralism in vast areas of Tsavo and Mara
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National Parks (Okello & Kiringe 2004, Kiringe & Okello 2007, FAO 2009, Job & Paesler
2013). Today, several protected areas are fenced (e.g. Aberdares, Nairobi, Nakuru, Marsabit
and Mt Kenya, Arabuko Sokoke National Park), not only to reduce conflicts between wildlife
and humans, but also to prevent activities of local people inside these protected areas. This
`gated conservation´ strategy might be the only viable solution, especially in densely
populated areas. Yet, it prevents any participation by the local community and the long-term
acceptance of people. as well as migration of wildlife among protected areas. The long-term
efficiency of such actions therefore remains highly questionable.
Prioritizing areas for future conservation activity
Our overlap analyses show that nature conservation strategies in Kenya mainly focus on areas
with rather low species richness, while areas of high ecological relevance are mostly typified
by high agricultural productivity, and thus often reserved for agricultural purposes.
Accordingly, demographic pressure in such areas is exceptionally high. We found that some
regions, such as the southern and south-western parts of Kenya as well as the coastal region,
show extraordinary high levels of species richness, but are without any - or only under
marginal - nature protection. This study hence underlines that the occurrence of the “big five”
(African lion Panthera leo, African elephant Loxodonta africana, African buffalo Syncerus
caffer, African leopard Panthera pardus pardus, and the African rhinoceros Diceros bicornis
i.e. Ceratotherium simum) still seems to be the decisive factor when selecting nature reserves
due to there importance for Kenya’s tourism, while the protection of prime biodiversity
regions seems to be of lesser priority.
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Acknowledgement
We are grateful to Ralph Jaetzold and Berthold Hornetz (Trier, Germany) for providing the
valuable data-sets of the FMHB. We thank one anonymous referees for critical comments on
a draft version of this contribution.
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References
Bennun LA, Njoroge P (1999) Important bird areas of Kenya. Nature Kenya, Nairobi.
BirdLife International and NatureServe (2015) Bird species distribution maps of the world.
BirdLife International, Cambridge, UK and Nature Serve, Arlington, USA.
Burgess N, Küper W, Mutke J, Brown J, Westaway S, Turpie S, Meshack C, Taplin J,
McClean J, Lovett JC (2005) Major gaps in the distribution of protected areas for
threatened and narrow range afrotorpical plants. Biodiversity and Conservation 14:
1877-1894.
Burgess ND, Butynski TM, Cordeiro NJ, Doggart NH, Fjelsa J, Howell KM, Kilahama FB,
Loader SP, Lovett JC, Mbilinyi B, Menegon M, Moyer DC, Nashanda E, Perkin A,
Rovero F, Stanley WT, Stuart SN (2007) The biological importance of the Eastern Arc
Mountains of Tanzania and Kenya. Biological Conservation 134: 209-231.
Food and Agricultural Organization (2009) Human-wildlife conflict in Africa - causes,
consequences and management strategies, Rom, FAO Forest Paper 157.
Fjeldsa J, Burgess ND, Blyth S, de Klark M (2004) Where are the major gaps in the reserve
network for Africa´s mammals? Oryx 38: 17-25.
Habel JC, Teucher M, Hornetz B, Jaetzold R, Kimatu JN, Kasili S, Mairura Z, Mulwa RK,
Eggermont H, Weisser WW, Lens L (2015) Real-world complexity of food security
and biodiversity conservation. Biodiversity and Conservation 24: 1531-1539.
IUCN and UNEP-WCMC (2015) The world database on protected areas (WDPA),
Cambridge, UK, UNEP-WCMC, www.protectedplanet.net (accessed 20.5.2015)
IUCN Red List of threatened species – digital distribution maps, Cambridge, UK,
http://www.iucnredlist.org/technical-documents/spatial-data (accessed 21.12.2015)
Jaetzold R, Schmidt H, Hornetz B, Shisanya CA (2011) Farm Management Handbook of
Kenya.- Vol. II, Natural conditions and farm management information, Part B: Central
Kenya. Subpart B1b: Northern Rift Valley Province. Ministry of Agriculture and GIZ,
Nairobi.
Jaetzold R, Schmidt H, Hornetz B, Shisanya CA (2006) Farm Management Handbook of
Kenya. Volume II: Natural conditions and farm management information. Part C: East
Kenya. Subpart C1: Eastern Province. Ministry of Agriculture and GIZ, Nairobi.
Jaetzold R, Schmidt H, Hornetz B, Shisanya CA (2012) Farm Management Handbook of
Kenya. Volume II: Natural conditions and farm management information. Part C: East
Kenya. Subpart C2: Coast Province. Ministry of Agriculture and GIZ, Nairobi.
11
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
Job H, Paesler F (2013) Links between nature-based tourism, protected areas, poverty
alleviation and crises – the example of Wasini Island (Kenya). Journal of Outdoor
Recreation and Tourism 1: 18-28.
Kier G, Mutke J, Dinerstein E, Ricketts TH, Küper W, Kreft H, Barthlott W (2005) Global
patterns of plant diversity and floristic knowledge. Journal of Biogeography 32: 1107–
1116.
Kiringe JW, Okello MM (2007) Threats and their relative severity to wildlife protected areas
of Kenya. Applied Ecology and Environmental Research 5: 49-62.
Kiteme B, Liniger HP, Notter B, Wiesmann U, Kohler T (2008) Dimensions of global change
in African Mountains: The Example of Mount Kenya. In International Human
Dimensions Programme on Global Environmental Change: Mountainous Regions:
Laboratories for Adaptation; Rechkemmer A (ed), International Dimensions Programme
on Global Environmental Change: Bonn, Germany, Volume 2.
Kenya National Bureau of Statistics (2015) Population and housing census 2009,
www.knbs.or.ke/population.php (accessed 20.5.2015)
Larsen TB (1991) The butterflies of Kenya and their natural history. 490pp.
Lindsey PA, Roulet PA, Rmanach SS (2007) Economic and conservation significance of the
trophy hunting industry in sub-Saharan Africa. Biological Conservation 134: 455-469.
Lovett JC (1998) Importance of the Eastern Arc Mountains for vascular plants. Journal of
East African Natural History 87: 59-74.
Lötters S, Wagner P, Bwong BA, Schick S, Malonza PK, Muchai V, Wasonga DV, Veith M
(2007) A field guide to the amphibians and reptiles of Kakamega forest. Nairobi and
Mainz, National Museums of Kenya, Nairobi, University of Mainz, Germany, Pp 112.
MacKenzie JM (1997) The empire of nature: hunting, conservation and British imperialism.
Manchester University Press, Manchester, New York.
Okello MM, Kiringe JW (2004) Threats to biodiversity and their implications in protected and
adjacent dispersal areas of Kenya. Journal of Sustainable Tourism 12: 55-69.
Measey GJ, Malonza PK, Muchai V (2009) Amphibians of Taita Hills. SANBI Biodiversity
Series 12, South African National Biodiversity Institute, Pretoria.
Mittermeier RA, Turner WR, Larsen FW, Brooks TM, Gascon C (2011) Global biodiversity
conservation: the critical role of hotspots. In: Zachos FE, Habel JC (eds) Biodiversity
hotspots – distribution and protection of conservation priority areas. Springer,
Heidelberg, pp 2–22.
12
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
Myers N, Mittermeier RA, Mittermeier CG, da Fonseca GAB, Kent J (2000) Biodiversity
hotspots for conservation priorities. Nature 403: 853-858.
Platts PJ, Ahrends A, Gereau RE, McClean CJ, Lovett JC, Marshall AR, Pellikka PKE,
Mulligan M, Fanning E, Marchant R (2010) Delimiting tropical mountain ecoregions for
conservation. Diversity and Distributions 16: 628-642.
Plieninger T, Höchtl F, Spek T (2006) Traditional land-use and nature conservation in
European rural landscapes. Environmental Science and Policy 9: 317-321.
Poynton JC, Loader SP, Sherratt E, Clarke BT (2007) Amphibian diversity in East African
biodiversity hotspots: altitudinal and latitudinal patterns. Vertebrate Conservation and
Biodiversity 5:277-292.
Pullin AS, Knight TM (2003) Support for decision making in conservation practice: an
evidence-based approach. Journal for Nature Conservation 11: 83-90.
Republic of Kenya (1959) Kenya population census 1962. Nairobi
Rodrigues ASL, Pilgrim JD, Lamoreux JF, Hoffmann M, Brooks TM (2006) The value of the
IUCN Red List for conservation. Trends in Ecology and Evolution 21: 71-76.
Spawls S, Howell K, Drewes RC, Ashe J (2002) Field guide to the reptiles of East Africa: All
the reptiles of Kenya, Tanzania, Uganda, Rwanda and Burundi.
Stork N, Habel JC (2014) Can biodiversity hotspots protect more than tropical forest plants
and vertebrates? Journal of Biogeography 41: 421-428.
Sutherland WJ, Pullin AS, Dom PM, Knight TM (2004) The need for evidence-based
conservation. Trends in Ecology and Evolution 19: 305-308.
Svancara LK, Brannon RJ, Scott M, Groves CR, Noss RF, Pressey RL (2005) Policy-driven
versus evidence-based conservation: A review of political targets and biological needs.
BioScience 55: 989-995.
Thurston A (1987) Smallholder agriculture in colonial Kenya: the official mind and the
Swynnerton Plan. Cambridge African Monographs African Studies Centre, Cambridge
No. 8.
Waide RB, Willig MR, Steiner CF, Mittelbach G, Gough L, Dodson SI, Juday GP, Parmenter
R (1999) The relationship between productivity and species richness. Annual Review of
Ecology and Systematics 30: 257-300.
Wildlifedirect (2009) http://davidngala.wildlifedirect.org/2009/01/28/bush-meat-survey-in-
arabuko-sokoke-forest/ (accessed 20.5.2015)
13
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269
270
271
272
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274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
Worldbank (2015) World development indicators - agriculture, value added (% of GDP),
http://data.worldbank.org/data-catalog/world-development-indicators (accessed
20.5.2015)
World Travel and Tourism Council (2005) Benchmarking report Kenya 2015,
http://www.wttc.org/- /media/files/reports/benchmark%20reports/country%20reports
%202015/kenya%20%20benchmarking%20report%202015.pdf (accessed 20.5.2015)
Zimmerman DA, Turner DA, Pearson DJ (1999) Birds of Kenya and Northern Tanzania,
Field guide edition.
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Figure 1: Overlap of all Kenyan nature reserves (governmental and non-governmental) (white
lines) with species richness (consensus percentage value across four taxa in relation to the
total number of species known for Kenya), classified into five categories. Species richness
includes distribution data of the following taxonomic groups: mammals and amphibians (data
from the IUCN Red List of threatened species, digital distribution maps), birds (data from
BirdLife International and NatureServe 2015), and vascular plants (data from Kier et al.
2005). Data were trimmed to fit for Kenya using the clip function in ArcGis, and transformed
into a 25x25km grid.
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Figure 2: Overlap of all 249 governmental and non-governmental protected areas (data from
IUCN and UNEP-WCMC 2015) (black shaded), the four categories of AEZs (according to
FMHB), and the distribution of the human population density (inhabitants per ha) (data from
KNBS 2015).
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Table 1: Overlap between agro-ecological zones (divided into four categories, data obtained
from FMHB) and protected areas (governmental and non-governmental, distinguished).
Values are expressed as percentages.
Type of reserve AEZvery low
AEZ
low
AEZ medium
AEZ high
Total[%]
GovernmentalForest Reserve 0.93 1.89 5.85 15.11 23.78Marine National Park - - 0.04 - 0.04Marine National Reserve - - 0.03 - 0.03National Park 38.58 2.15 1.11 2.46 44.30National Reserve 17.35 3.36 3.52 0.12 24.35National Sanctuary - 0.09 0.19 - 0.28Not Reported - - 0.01 - 0.01Total (Gov.)[%] 59.86 7.49 10.75 17.69 64.17Non-governmentalCommunity Conservancy 5.23 2.59 0.19 - 8.01Community Nature Reserve 75.06 8.25 3.51 - 86.82Community Wildlife Sanctuary 0.58 0.06 0.01 - 0.65Group Ranch 0.08 0.11 0.01 - 0.20Private Nature Reserve 0.08 0.50 - - 0.58Private Protected Area 0.06 1.48 - - 1.54Private Ranch 0.89 0.95 0.06 - 1.90Wildlife Sanctuary 0.18 0.14 - - 0.32Total (Non-gov.) [%] 82.15 14.07 3.78 - 35.83Total (both) [%] 67.88 10.45 8.48 13.19 100.00
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Electronic Appendix Supplementary Material 1: Distribution of species richness of terrestrial
mammals, amphibians, birds and vascular plants in relation to the total number species known
for Kenya. Species richness grouped into 10% classes (to a maximum of 70%), and displayed
as 25x25km grid cells.
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