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首页> 外文期刊>Caldasia >TEMPERATURE AND PRECIPITATION AS PREDICTORS OF SPECIES RICHNESS IN NORTHERN ANDEAN AMPHIBIANS FROM COLOMBIA
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TEMPERATURE AND PRECIPITATION AS PREDICTORS OF SPECIES RICHNESS IN NORTHERN ANDEAN AMPHIBIANS FROM COLOMBIA

机译：温度和降水作为哥伦比亚北非两栖类两栖动物物种丰富度的预测指标

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Our objective was to explore the spatial distribution patterns of amphibian species richness in Antioquia, as model for the tropical Andes, and determine how annual mean temperature, annual precipitation, and elevation range influence it. We also briefly compare local and global regression models for estimating the relation between environmental variables and species richness. Distribution maps for 223 amphibian species and environmental variables were generalized onto grid maps of 752 blocks each covering the entire Department of Antioquia. We explored the relationship between species richness and environment using two global regression models (the Ordinary Least Squares “OLS” and Generalized Linear Squares “GLS” models) and one local model (the Geographically Weighted Regression “GWR” model). We found a significant relationship between species richness and environmental variables (GLS r2: 0.869; GRW r2: 0.929). The GLS model efficiently incorporated the spatial autocorrelation effect and handled spatial dependence in the regression error terms while the GWR model showed the best fit (r2) and balance between number of parameters and fit (AICc). GWR parameters show wide variation within the study area, indicating that relationship between species richness and climate is spatially complex. Temperature was the most important variable in the GLS and GWR models, and altitude range the least significant. The strong relationship between environment and amphibian richness is possibly due to life history traits of amphibians, such as ectothermy and water dependency to complete the life cycle
机译：我们的目标是探索安蒂奥基亚岛两栖动物物种丰富度的空间分布格局，作为热带安第斯山脉的模型，并确定年平均温度，年降水量和海拔范围如何对其产生影响。我们还简要地比较了局部和全局回归模型，以估计环境变量与物种丰富度之间的关系。将223种两栖动物物种和环境变量的分布图概括到752个块的网格图上，每个块都覆盖了整个安蒂奥基亚省。我们使用两个全局回归模型（普通最小二乘法“ OLS”和广义线性平方“ GLS”模型）和一个局部模型（地理加权回归“ GWR”模型）探索了物种丰富度与环境之间的关系。我们发现物种丰富度与环境变量之间存在显着关系（GLS r2：0.869; GRW r2：0.929）。 GLS模型有效地合并了空间自相关效应，并在回归误差项中处理了空间依赖性，而GWR模型则显示了最佳拟合（r2）和参数数量与拟合之间的平衡（AICc）。 GWR参数显示研究区域内变化很大，表明物种丰富度与气候之间的关系在空间上很复杂。在GLS和GWR模型中，温度是最重要的变量，而海拔范围则不是最重要的变量。环境与两栖动物丰富性之间的密切关系可能归因于两栖动物的生活史特征，例如通过等温和水依赖来完成生命周期

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