TEMPERATURE AND PRECIPITATION AS PREDICTORS OF SPECIES RICHNESS IN NORTHERN ANDEAN AMPHIBIANS FROM COLOMBIA
<div>Our objective was to explore the spatial distribution patterns of amphibian species</div><div>richness in Antioquia, as model for the tropical Andes, and determine how annual</div><div>mean temperature, annual precipitation, and elevation range influence it. We als...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Universidad Nacional de Colombia
2013-07-01
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| Series: | Caldasia |
| Subjects: | |
| Online Access: | http://www.revistas.unal.edu.co/index.php/cal/article/view/39098 |
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| Summary: | <div>Our objective was to explore the spatial distribution patterns of amphibian species</div><div>richness in Antioquia, as model for the tropical Andes, and determine how annual</div><div>mean temperature, annual precipitation, and elevation range influence it. We also</div><div>briefly compare local and global regression models for estimating the relation</div><div>between environmental variables and species richness. Distribution maps for 223</div><div>amphibian species and environmental variables were generalized onto grid maps</div><div>of 752 blocks each covering the entire Department of Antioquia. We explored the</div><div>relationship between species richness and environment using two global regression</div><div>models (the Ordinary Least Squares “OLS” and Generalized Linear Squares</div><div>“GLS” models) and one local model (the Geographically Weighted Regression</div><div>“GWR” model). We found a significant relationship between species richness and</div><div>environmental variables (GLS r2: 0.869; GRW r2: 0.929). The GLS model efficiently</div><div>incorporated the spatial autocorrelation effect and handled spatial dependence</div><div>in the regression error terms while the GWR model showed the best fit (r2) and</div><div>balance between number of parameters and fit (AICc). GWR parameters show wide</div><div>variation within the study area, indicating that relationship between species richness</div><div>and climate is spatially complex. Temperature was the most important variable</div><div>in the GLS and GWR models, and altitude range the least significant. The strong</div><div>relationship between environment and amphibian richness is possibly due to life</div><div>history traits of amphibians, such as ectothermy and water dependency to complete</div><div>the life cycle</div> |
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| ISSN: | 0366-5232 |