2016
DOI: 10.1002/ece3.2492
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Projected changes in climatic suitability for Kinosternon turtles by 2050 and 2070

Abstract: Chelonians are expected to be negatively impacted by climate change due to limited vagility and temperature‐dependent sex determination. However, few studies have examined how freshwater turtle distributions may shift under different climate change scenarios. We used a maximum entropy approach to model the distribution of five widespread North American Kinosternon species (K. baurii, K. flavescens, K. hirtipes, K. sonoriense, and K. subrubrum) under four climate change scenarios. We found that areas with suita… Show more

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Cited by 27 publications
(18 citation statements)
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References 71 publications
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“…We downloaded records of these five species from the Global Biodiversity Information Facility (https://www.gbif.org/) and combined them with undigitized herbarium records from Cornell and the New York Botanical Gardens. We followed the procedures outlined in Butler, Stanila, and Iverson (2016) for data processing and model building. We eliminated duplicates and records from outside the native range and resampled the locality data to one record per 25 km 2 .…”
Section: Methodsmentioning
confidence: 99%
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“…We downloaded records of these five species from the Global Biodiversity Information Facility (https://www.gbif.org/) and combined them with undigitized herbarium records from Cornell and the New York Botanical Gardens. We followed the procedures outlined in Butler, Stanila, and Iverson (2016) for data processing and model building. We eliminated duplicates and records from outside the native range and resampled the locality data to one record per 25 km 2 .…”
Section: Methodsmentioning
confidence: 99%
“…We followed the procedure outlined by Butler et al. (2016) and only included the variables with the most useful predictive information (i.e., the highest gain when used in isolation), as well as the variables that provided unique predictive information. As regularization multipliers ( β ) are an important component of model prediction and complexity (Moreno‐Amat et al., 2015), we used the regularization approach implemented in ENMtools (Warren, Matzke, & Cardillo, 2019) and small sample corrected variant of Akaike's information criterion (AICc) scores were used to evaluate models (Warren & Seifert, 2011) using all possible combinations of the variables that did not exhibit high multicollinearity (e.g., | r | < .8).…”
Section: Methodsmentioning
confidence: 99%
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“…We selected the best model with the highest AUC value. The remaining model settings were set to the same as those of the initial model [43][44]. The file output by the MaxEnt model is in ASCII format, and it cannot be visually displayed on the map.…”
Section: Modeling Methods and Statistical Analysismentioning
confidence: 99%
“…For example, the amount of suitable habitat for the Rio Grande Cooter (Pseudemys gorzugi) was predicted to increase by the 2050s and then decline substantially by the 2070s [108]. Similarly, models of the projected distribution of five Kinosternon species under various climate scenarios show that the distribution of two species were predicted to substantially decline, one was forecast to remain essentially unchanged, and the ranges for two species were expected to substantially increase [109]. The amount of suitable bioclimatic conditions for red-eared sliders in the Great Lakes Basin is expected to increase from 26% up to potentially 50% by 2050 [110].…”
Section: Populationsmentioning
confidence: 99%