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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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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Electronic Appendix Supplementary Material 2: Location of the 10 grid cells with highest

species richness (over all four taxonomic groups assessed), displayed as grey squares,

intersected by existing nature reserves.

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