Species Distribution Modeling of the Threatened Blanding's Turtle's (Emydoidea blandingii) Range Edge as a Tool for Conservation Planning
Delineating a species range is challenging because many factors interact at multiple spatial scales to affect a species distribution. Species distribution models (SDM) can be used to identify factors most associated with a species presence and, therefore, potentially define a range edge. We evaluated the utility of two popular SDM approaches, maximum entropy models (e.g., MaxEnt) and generalized linear models (GLM), for determining the range edge for the threatened Blanding's Turtles, Emydoidea blandingii, in northeastern New York, USA. Using the mapping and analysis software ArcGIS, we constructed and validated SDMs using presence/absence records (GLM) and presence/background records (MaxEnt) with 11 environmental predictor variables. Because of the limits imposed by the low number of absences, we found that GLM was not as successful as MaxEnt at predicting habitat suitability for rare and cryptic species like E. blandingii. Our results also indicated that a distinct environmentally induced range edge is associated with factors related to elevation. Both GLM and MaxEnt models also projected the presence of suitable habitat outside of the current range, including locations with known disjunct populations. We conclude that a presence/background SDM approach such as MaxEnt is valid when accurate data on locational absences are lacking, as is typical for rare, cryptic species. Using SDM to understand factors that shape the range edge can aid in planning habitat conservation and management of threatened species such as E. blandingii.Abstract
Regional limits for SDM in New York's St. Lawrence River Valley, USA, and E. blandingii survey locations.
Mean importance of predictor variables for (A) GLM and (B) MaxEnt models at 250-m and 8,000-m scales. Error bars = SD, polarity symbols (+/−) indicate direction of effect on habitat suitability. Missing bars indicate variables not included in the models. Importance in GLM models is expressed as the regression coefficient after z-value standardization; higher coefficients are more important. Importance in MaxEnt models is expressed as percent contribution to the model.
Probability of occurrence of E. blandingii within the modeled region of northeastern New York using GLM or MaxEnt with buffer distances of 250 m or 8,000 m. Gray areas indicate high probability of occurrence. Circled area is a predicted gap between two areas of high probability of occurrence.
Projected areas of high habitat suitability for E. blandingii outside of the model building extent using MaxEnt (A) and GLM (B) with a buffer distance of 250 m. The dotted line delineates the current known distribution of E. blandingii in New York.
Projected areas of high habitat suitability for E. blandingii outside of the model building extent using MaxEnt (A) and GLM (B) with a buffer distance of 8,000 m. The dotted line delineates the current known distribution of E. blandingii in New York.
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