Spatial variation in the willingness to accept payment for conservation of a migratory wildlife corridor in the Athi-­‐Kaputiei Plains, Kenya.

Abstract

Payments for ecosystem services (PES) are increasingly being used as a tool to promote sustainable ecosystem services. The success of PES depends on the willingness of target landowners to accept the payments. In particular, to be effective in promoting the conservation of wide-­‐ranging migratory wildlife, the potential recipients of PES must be willing to accept the payments for ecosystem services along the entire migratory corridor to enable wildlife movements. This may be difficult and expensive to achieve where costs of providing the service vary along the corridor. This paper investigates spatial variation in willingness to accept payments (WTA) made by a Wildlife Conservation Lease Program in the Kitengela and Athi Kaputiei plains of Kenya. The program, designed as an incentive to keep land open for wildlife and livestock, currently (2012) offers land owners a flat fee of 10 US$ per ha per year, irrespective of location. We present a model relating WTA to distances to road infrastructure, towns and rivers, as well as to annual precipitation and slope. The model was implemented in GIS to display the spatial variation in the willingness of landowners to accept payments from the Wildlife Conservation Lease Program. The results reveal significant spatial variation in the willingness to accept payments for availing land for conservation, with higher willingness to accept payments concentrated away from roads and also in the south-­‐eastern section of the Kitengela plains. The results further suggest that the movements of wildlife will be blocked by lands currently not open to migration due to low WTA in the proximity of towns and tarmacked roads. An effective strategy to keep the land open for migratory wildlife should take the significant spatial variation in the willingness to 2 accept payment for land lease into account, and it is suggested to consider spatially stratifying the lease rates to reflect the underlying variation in WTA.