CARTOGRAPHY OF HUMAN WILDLIFE CONFLICTS IN KENYA
E. Buard
IGN
elodie.buard@ign.fr
As a
consequence of human development, human beings and wildlife share natural
resources such as water. Thus they face with land competition: wildlife enters
into human lands, damaging crops and killing livestock whereas local
communities continue killing and trapping wildlife in spite of international
laws (Rerimoi 2002).
The
objective of this study is to cartography the animals’ habitats and visualises
the land conflicts as a spatial problem (Smith 2000). It provides tools to
understand the wildlife presence in the area and then to ease the co-habitation
in adopting relevant solutions. A methodology of wildlife cartography is
presented, all the more difficult as animals are always in move. My study gives
a prediction of their habitats, it means their probable location. What is more,
a link is done between land (visible by GIS), wildlife (data collected
including a census) and social data.
The first
step is to carry out the aerial photograph interpretation. This work has been
done in Kenya, next to the Maasai Mara game reserve. Different features of
analysis have been identified, underlining the most important factors: drainage
network, human settlements, density of vegetation and land cover. A land cover
classification has been created and tested on the ground in a sample survey. It
includes artificial land, arable land, bushes land and riverine forest. In
addition, two transects has been followed to assess the conflicts magnitude in
interviewing people or in seeing evidences and to evaluate the number of
animals in the area by their droppings, feet, tracks, resting sites and direct
visualisation (Kushwaha 2002). We could noticed that one transect passed
through elephant migratory corridors.
The second
part, the data analysis has been undertaken in England, at Cranfield
University. The features from photo interpretation have been digitised into
ArcGIS to become GIS layers. They have been combined together with the Raster
Calculator tool to create final maps namely human density map, habitats
suitability maps and conflicts intensity map. Each habitat suitability map has
been calculated according to the best attributes wanted: “water is vital” means
an important weight to the drainage shapefile. The final step was to analyse
the questionnaires to give statistics about population concerns or their
proposal to mitigate the conflicts. The social survey has contributed to the
GIS explanation (Muchemi 2004).
Finally my
study gives a systematic methodology to study wildlife in a particular region,
with other external data such as statistics.
Kushwaha S.P.S., 2002, Head of forestry and ecology
division, Geoinformatics for wildlife
habitat characterisation, unpublished application paper. Dehradun, India.
Muchemi J.G., Lwenga R., Nyambura A. M., 2005, Issues in Kuria and Transmara districts, Kenya: the circumstances and
outcomes of the eviction of Kuria people from their ancestral claims in
Transmara district, ERMIS Africa
Rerimoi J., 2002, Effect
of Human-Wildlife conflicts on land-use practices in Salama location, Laikipia
district, Kenya. PhD report of Environmental Studies, Egerton University,
geography department, Kenya.
Smith R.J. and Kasiki S.M., 2000, A spatial analysis of human elephant conflict in the Tsavo ecosystem,
Kenya. IUCN.