Modeling the Distribution and Richness of Mammalian Species in the Nyerere National Park, Tanzania

Understanding the geographic distribution of mammal species is essential for informed conservation planning, maintaining local ecosystem stability, and addressing research gaps, particularly in data-deficient regions. This study investigated the distribution and richness of 20 mammal species within Nyerere National Park (NNP), a large and understudied protected area in Southern Tanzania. We applied species distribution models (SDMs) using presence data collected through ground surveys between 2022 and 2024, combined with environmental variables derived from remote sensing, including land surface temperature, vegetation indices, soil moisture, elevation, and proximity to water sources and human infrastructure. Models were constructed using the Maximum Entropy (MaxEnt) algorithm, and performance was evaluated using the Area Under the Curve (AUC) metric, yielding high accuracy ranging from 0.81 to 0.97. Temperature (32.3%) and vegetation indices (23.4%) emerged as the most influential predictors of species distributions, followed by elevation (21.7%) and proximity to water (14.5%). Species richness, estimated using a stacked SDM approach, was highest in the northern and riparian zones of the park, identifying potential biodiversity hotspots. This study presents the first fine-scale SDMs for mammal species in Nyerere National Park, offering a valuable ecological baseline to support conservation planning and promote sustainable ecotourism development in Tanzania’s southern protected areas.

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Publication Details

Journal
Remote Sensing
Published
2025-07-18
DOI
https://doi.org/10.3390/rs17142504
Citations
1
Primary Topic
Species Distribution and Climate Change
Type
article
Field-Weighted Citation Impact
1.84

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article

Modeling the Distribution and Richness of Mammalian Species in the Nyerere National Park, Tanzania

Enrique Casas, Richard D. Lyamuya, Tiwonge I. Mzumara, Willard Mbewe et al.
1 citations
Remote Sensing
Species Distribution and Climate Change
1.84
article

Modeling the Distribution and Richness of Mammalian Species in the Nyerere National Park, Tanzania

Enrique Casas, Richard D. Lyamuya, Tiwonge I. Mzumara, Willard Mbewe, Manuel Arbeló, Wilfred Marealle, Goodluck Massawe
article en
1 citations

Abstract

Understanding the geographic distribution of mammal species is essential for informed conservation planning, maintaining local ecosystem stability, and addressing research gaps, particularly in data-deficient regions. This study investigated the distribution and richness of 20 mammal species within Nyerere National Park (NNP), a large and understudied protected area in Southern Tanzania. We applied species distribution models (SDMs) using presence data collected through ground surveys between 2022 and 2024, combined with environmental variables derived from remote sensing, including land surface temperature, vegetation indices, soil moisture, elevation, and proximity to water sources and human infrastructure. Models were constructed using the Maximum Entropy (MaxEnt) algorithm, and performance was evaluated using the Area Under the Curve (AUC) metric, yielding high accuracy ranging from 0.81 to 0.97. Temperature (32.3%) and vegetation indices (23.4%) emerged as the most influential predictors of species distributions, followed by elevation (21.7%) and proximity to water (14.5%). Species richness, estimated using a stacked SDM approach, was highest in the northern and riparian zones of the park, identifying potential biodiversity hotspots. This study presents the first fine-scale SDMs for mammal species in Nyerere National Park, offering a valuable ecological baseline to support conservation planning and promote sustainable ecotourism development in Tanzania’s southern protected areas.

Remote SensingVol. 17(14)
Tanzania Wildlife Research Institute (TZ), Universidad de La Laguna (ES), Malawi University of Science and Technology (MW)
World Bank Group
Life in Land
Openalex Percentile: Top 13%
Species Distribution and Climate Change
1.84
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