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