Modeling the potential distribution of Picea chihuahuana Martínez, an endangered species at the Sierra Madre Occidental, Mexico

Abstract

Species distribution models (SDMs) help identify areas for the development of populations or communities to prevent extinctions, especially in the face of the global environmental change. This study modeled the potential distribution of the tree Picea chihuahuana Martínez, a species in danger of extinction, using the maximum entropy modeling method (MaxEnt) at three scales: local, state and national. We used a total of 38 presence data from the Sierra Madre Occidental. At the local scale, we compared MaxEnt with the reclassification and overlay method integrated in a geographic information system. MaxEnt generated maps with a high predictive capability (AUC > 0.97). The distribution of P. chihuahuana is defined by vegetation type and minimum temperature at national and state scales. At the local scale, both models calculated similar areas for the potential distribution of the species; the variables that better defined the species distribution were vegetation type, aspect and distance to water flows. Populations of P. chihuahuana have always been small, but our results show potential habitat greater than the area of the actual distribution. These results provide an insight into the availability of areas suitable for the species' regeneration, possibly through assisted colonization.