Game ranching in Machakos District, Kenya : an application of mathematical programming to the study of wildlife policy
This study employed a bioeconomic, mathematical programming model to analyse ranch resources allocation among cattle and game animals, and Kenya's wildlife conservation and game harvesting policies. The objective function was comprised of discounted net income flows over 30 periods of 6-months each (15 years) and was optimised subject to the population dynamics (modeled as logistic growth functions), initial animal populations and institutional constraints (Kenya Wildlife Service policies). Game animal harvests were modelled as decay functions, while carrying capacity in the logistic growth models is a function of rainfall. Cattle population is modelled as a linear difference equation. Simulation results show that abandoning the earlier preservation policy that placed the burden of wildlife conservation on private landowners was a good decision. If continued, the pre-1989 game animal preservation policy would likely not only dissipate available rent, but also extinguish non-competitive animal species, thus making this policy economically unfavorable and biologically unsustainable. After 1989, ranchers were granted (limited) user rights to wildlife, but wildlife ownership continued to reside with the Kenya Wildlife Service (KWS). In this study various ways in which KWS could exercise ownership are examined. The objectives of KWS are to conserve wildlife ungulates while providing appropriate economic incentives to ranchers. The current policy of attaining this objective is by allowing ranchers to harvest a given proportion of the game populations. Simulation results indicate that this policy is non-optimal and only marginally sustainable. When a Shannon biodiversity index is used as a constraint, game conservation was also found to be unsuitable. The biodiversity index can be attained at very low population levels, making its sustainability questionable. A better alternative is constraining the end-period populations to be equal to or greater than initial populations. This policy yields a reasonable net return and is unambiguously sustainable. The best policy, however, combines the end-period constraint with a policy that gives landowners full property rights. Ranchers can use animals in any way they wish. This approach yields a much higher net return than any other policy and is also unambiguously sustainable.
CitationKinyua, P I D (1998). Game ranching in Machakos District, Kenya : an application of mathematical programming to the study of wildlife policy
Department of Range Management, University of Nairobi