Stochastics Growth Model

The goal is to create a mathematical model that takes into account genetic defects while evaluating the development rate of roan antelopes in Kenya’s Ruma National Park.

Methodology: To estimate the population growth rate of roans, this work modified Oksendal and Lungu’s stochastic logistic model by integrating genetic defects not included by Magin and Cock. Vortex version 9.99, a computer simulation programme used to mimic the extinction process, was adjusted appropriately.

Inbreeding has a high-level impact on population expansion (survival) in tiny communities, according to the findings. Juvenile and adult roans were supplemented to promote population survival for a longer period of time.

Conclusion: To combat inbreeding, which is a serious concern to tiny populations, this paper proposes supplements rather than predator control because of the unknown implications to the environment and conflicts with wildlife management plans in protected areas. Supplementation should be done in stages so that social groupings are not disrupted. Genetic research should be conducted to determine the extent to which inbreeding influences population increase, according to this study.

Author(s) Details

Daniel Ochieng Achola
Department of Mathematics, Kabarak University, Private Bag-20157, Nakuru, Kenya.

View Book :- https://stm.bookpi.org/TPMCS-V10/article/view/1071

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