The Maasai, the Gnu and the Metropolis (MaGnuM) Understanding the socio-ecological complexity of wildlife migration landscapes south of Nairobi National Park, Kenya — An interdisciplinary, collaborative, and operational approach

Informations

Funding country

France

Acronym

MAGNUM

URL

-

Start date

10/1/2016

End date

-

Budget

432,075 EUR

Fundings

Abstract

Habitat loss and fragmentation are major threats to biodiversity and to the sustainability and stability of human communities. A hallmark of the domination of nature by modern societies is the transformation and simplification of landscape mosaics, which can cause a disruption of ecological processes and a degradation of ecosystem services. As cornerstones of wildlife and habitat conservation, protected areas (PAs) are commonly conceived as foils to these potential problems by keeping humans out, but they often fail to consider the history of, and future potential for, the coexistence and co-evolution of humans and wildlife. Narrowly focusing on these islands of protected habitat overlooks the ecological importance of the surrounding agricultural and pastoral matrix to the wildlife present in the PA. In an increasingly crowded world, new management approaches based on novel ways of perceiving and coexisting with nature are required. The challenge set out by MaGnuM is to understand the causes, consequences and chronology of landscape change in southern Kenya by studying the magnitudes, frequencies and feedbacks of ecological and social processes. Given the complex nature of the system under investigation, the challenge lies in learning how to steer the observed socio-ecological processes under the constraints of uncertainty rather than to impose sectorial prescriptions typical of command-and-control management practices. MaGnuM is a class of project belonging to situated science, i.e. it addresses issues from a standpoint that emphasizes the importance of fieldwork, of interdisciplinary and collaborative co-production of knowledge, and the heuristic and educational value of modelling. The study area consists of (i) Nairobi National Park, which is separated from metropolitan Nairobi by an electric fence on its north side but opens out to the south onto (ii) a vast expanse of open Maasai savanna rangeland. Large populations of large ungulates migrate northward to NNP during the dry season, and return to the drier southern plains during the rainy season. Land-use change has been accelerating since the late 1990s because of suburban growth and of the division and sale of Maasai land. Accordingly, the savanna has undergone fencing and fragmentation, resulting in demographic decline among most wildlife species and accelerated socio-cultural transformations among residents. The aim of MaGnuM is to portray what has been driving landscape transformations and to encourage management approaches that are beneficial to the human and non-human occupants of the land. The quality and originality of our results hinge on the multidisciplinary nature of our approach, and on a continual co-participation of scientists and non-scientists. This should promote reciprocal learning and foster innovative landscape-, wildlife-, resource- and livelihood-management frameworks. The project is structured around three Working Packages (WP). WP1 is devoted to the characterization of the socio-ecological system from the perspective of land and land-use issues, demographic change, natural resource governance and exploitation, and environmental feedbacks between wildlife, pastoralism, and savanna landscape dynamics. WP1 calls upon skills and methods relevant to physical geography, ecology, and the social sciences. WP2 aims to build computer-generated spatial models designed to test the conceptual models of WP1 and to serve the participatory activities and scenario-building of WP3. WP2 seek to model animal dispersal patterns, land-use change and management scenarios, and combines modern technologies (e.g. GPS collars) with traditional ecological knowledge. WP3 emphasizes a strong collaborative dimension and focuses on the co-production of knowledge and on agent-based simulations of interest to stakeholders and policymakers.