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The Maasai Mara in Kenya, renowned for its biodiversity, is witnessingecosystem degradation and species endangerment due to intensified humanactivities. Addressing this, we introduce a dynamic system harmonizingecological and human priorities. Our agent-based model replicates the MaasaiMara savanna ecosystem, incorporating 71 animal species, 10 humanclassifications, and 2 natural resource types. The model employs the metabolicrate-mass relationship for animal energy dynamics, logistic curves for animalgrowth, individual interactions for food web simulation, and human interventionimpacts. Algorithms like fitness proportional selection and particle swarmmimic organism preferences for resources. To guide preservation activities, weformulated 21 management strategies encompassing tourism, transportation,taxation, environmental conservation, research, diplomacy, and poaching,employing a game-theoretic framework. Using the TOPSIS method, we prioritizedfour key developmental indicators: environmental health, research advancement,economic growth, and security. The interplay of 16 factors determines theseindicators, each influenced by our policies to varying degrees. By evaluatingthe policies' repercussions, we aim to mitigate adverse animal-humaninteractions and equitably address human concerns. We classified the policyimpacts into three categories: Environmental Preservation, Economic Prosperity,and Holistic Development. By applying these policy groupings to our ecosystemmodel, we tracked the effects on the intricate animal-human-resource dynamics.Utilizing the entropy weight method, we assessed the efficacy of these policyclusters over a decade, identifying the optimal blend emphasizing bothenvironmental conservation and economic progression.

Revive, Restore, Revitalize: An Eco-economic Methodology for Maasai Mara