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Maximum entropy modeling of giant pangolin Smutsia gigantea (Illiger, 1815) habitat suitability in a protected forest-savannah transition area of central Cameroon

Tijdschriftbijdrage - Tijdschriftartikel

Across the planet, biodiversity is facing ever-growing threats including habitat loss, climate change, overexploitation, and pollution. Pangolins of the order Pholidota are the only scaly mammal species worldwide and are considered the most trafficked wild mammals in the world, being widely exploited for their meat and scales. The giant pangolin (Smutsia gigantea, GP) is one of the least studied species of this order, with little being known about their response to environmental and anthropogenic variables, as well as their distribution patterns in forest-savannah transition areas. Our study aimed to increase ecological knowledge about GP by investigating the environmental factors associated with the distribution of suitable habitat for GP within a protected forest/savannah transition area of Cameroon. Using data on the locations of GP resting burrows collected using line transects and employing a maximum entropy (MaxEnt) modelling approach, we explored GP habitat suitability within a forest-savannah transition area of Cameroon. Our model revealed a good level of accuracy based on the average test area under the Receiver Operator Curve metric. The jackknife test found that Euclidian distance to the national park's boundaries, normalized difference vegetation index, elevation, and distance to river were the most important predictors determining the distribution of GP burrows. Areas predicted to be suitable for GP burrows were patchily distributed within dense forests, ecotone and savannah, with 19.24% of the study area being suitable and 1% very suitable. Overall, our study shows the possible importance of habitat suitability modeling for understanding GP distribution, as well as planning and prioritising their conservation actions. © 2023
Tijdschrift: Global Ecology and Conservation
Volume: 43
Jaar van publicatie:2023