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Savanna Land Use Policy Outcomes
Serengeti-Mara Ecosystem, East Africa
Anthropology Department, University College London, United Kingdom
Geography Department, University of Louvain, Belgium
Kenya Wildlife Service, Kenya 
Institute of Resource Assessment, Dar es Salaam University, Tanzania 
-Funded by: European Union (EU) and UK's Department for International Development


Type of Study: Chain-based study

Declines in habitat and wildlife in semi-arid African savannas are widely reported and commonly attributed to agropastoral population growth, livestock impacts, and subsistence cultivation. However, directional trends and causal chains are hard to establish in these ecosystems, because of extreme annual and shorter-term variability of rainfall, primary production, vegetation, and populations of grazers. In this interdisciplinary collaborative study, two decades of changes in land cover and wildlife populations in the Serengeti-Mara region of East Africa were analyzed in terms of potential drivers (rainfall, human and livestock population growth, socio-economic trends, land tenure, agricultural policies, markets).

The 100,000 km2 Serengeti-Mara Ecosystem (SME) serves as a natural experiment, allowing analysis of the long-term outcomes of different policies for conservation on the one hand, and for community development on the other. The SME comprises contrasting land-use zones with different tenure arrangements, ranging from state-controlled "fortress" conservation areas to private and non-private tracts with multiple land uses, some with community-based conservation initiatives, superimposed on a rangeland where ecological, micro-economic, and ethnic continuities make it possible to control for many confounding variables. The SME is bisected by the Kenya/Tanzania border, allowing comparative analysis of the implications of contrasting economic, political, and land tenure contexts of Kenya and Tanzania. As well as the research design, this study's conceptual model and statistical approach integrated natural and social sciences data. Remote sensing, rainfall, and aerial census data quantified ecological dynamics and the expansion of agriculture. Using GIS techniques, interrelations between biophysical, cultural, socio-economic, and political variables, proximate and underlying causes were analyzed for land units, pooled into policy categories, linking remote sensing and survey data at the household level through spatial logistic multiple regression models.

The Kenyan part of the ecosystem shows rapid land-cover change and drastic decline for a wide range of wildlife species, but these changes are absent on the Tanzanian side. Temporal climate trends, human population density and growth rates, uptake of smallholder agriculture, and livestock population trends do not differ between the Kenyan and Tanzanian parts of the ecosystem and cannot account for observed changes. Differences in private versus State/communal land tenure, agricultural policy, and market conditions suggest, and spatial correlations confirm, that the major changes in land cover and dominant grazer species numbers are driven primarily by private landowners responding to market opportunities for mechanized agriculture, less by agropastoral population growth, cattle numbers, or smallholder land use.



Contact Information:
Professor Katherine Homewood
Head, Anthropology Department
University College London
United Kingdom
Tel: +44 20-7679-7856/3332
Fax: +44 20-7679-7728
Email: k.homewood@ucl.ac.uk


This Study is classified within these Core Themes:
This Study is classified within these Core Themes:
This Study is classified within these Core Themes:
Guidance (institutions and incentives)
Connecting the ecological, economic, and social
Integrative methods for place-based analysis
Indicators and monitoring
Sustainability processes and causation
Driving forces relevant to a sustainability transition
Methods and models
Complex adaptive systems
Observations
Case comparison
Impacts and response
Using large data sets
                                                     
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