Integrative Spatial Modeling for Ecosystem Management: A Case Study in Maasai Mara

This study presents a generalized approach to wildlife management by introducing two adaptable models suitable for environments with varying data availability. Utilizing a Gridded Species Distribution Model and a Min-Max Model that incorporates the Simplified Floyd-Warshall Algorithm, we demonstrate a methodology capable of mapping species distributions and enhancing monitoring efficiency in habitat-rich reserves. The Gridded Model, through Optimized Hot Spot Analysis, successfully delineates critical habitats, and the Min-Max Model efficiently places monitoring stations, considering Kenya's technological landscape and data collection capabilities. Collectively, these models underpin a versatile and strategic framework, reinforcing conservation efforts in the Maasai Mara and suggesting potential for application in other contexts where similar ecological and resource challenges exist.

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Publication Details

Journal
Highlights in Science Engineering and Technology
Published
2024-08-15
DOI
https://doi.org/10.54097/dw5w9p05
Primary Topic
Wildlife Ecology and Conservation
Type
article
Field-Weighted Citation Impact
0.00
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article

Integrative Spatial Modeling for Ecosystem Management: A Case Study in Maasai Mara

Ruilang Li, Weiyi Sun, Zhuchang Gu
Highlights in Science Engineering and Technology
Wildlife Ecology and Conservation
article

Integrative Spatial Modeling for Ecosystem Management: A Case Study in Maasai Mara

Ruilang Li, Weiyi Sun, Zhuchang Gu
article en

Abstract

This study presents a generalized approach to wildlife management by introducing two adaptable models suitable for environments with varying data availability. Utilizing a Gridded Species Distribution Model and a Min-Max Model that incorporates the Simplified Floyd-Warshall Algorithm, we demonstrate a methodology capable of mapping species distributions and enhancing monitoring efficiency in habitat-rich reserves. The Gridded Model, through Optimized Hot Spot Analysis, successfully delineates critical habitats, and the Min-Max Model efficiently places monitoring stations, considering Kenya's technological landscape and data collection capabilities. Collectively, these models underpin a versatile and strategic framework, reinforcing conservation efforts in the Maasai Mara and suggesting potential for application in other contexts where similar ecological and resource challenges exist.

Highlights in Science Engineering and TechnologyVol. 107
University of Illinois Urbana-Champaign (US), Wenzhou-Kean University (CN)
Life in Land
Openalex Percentile: Top 87%
Wildlife Ecology and Conservation
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Integrative Spatial Modeling for Ecosystem Management: A Case Study in Maasai Mara — Ruilang Li, Weiyi Sun, et al. · Highlights in Science Engineering and Technology (2024) | TGRS Research Map | TGRS