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Human density and sampling time explain richness of anurans in the Brazilian biomes

机译：人的密度和取样时间解释巴西生物群体中的丰富性

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Anuran richness patterns are strongly influenced by environmental factors. However, investigations on this issue have focused on the influence of abiotic factors without considering the joint effect of many existing variables, including the data sampling methodology and human demography. In this study we investigated the relationship between 21 environmental variables and anuran richness in Brazilian biomes. Environmental variables represent a combination of human demographics, topographic, climatic and vegetation characteristics, and data sampling methodologies. We used principal component factorization and regressive and autoregressive models to select the most relevant variables for explaining anuran richness. Richness was correlated with demographic density, vegetation, accumulated rainfall, accumulated rainfall in the third and fourth quarter of the year, and accumulated rainfall in the first and second half of the year. However, the regressive and autoregressive models showed that human demographic density, sampling time, and sampling methodology were the best predictors of anuran richness. Our results highlight the importance of considering the effects of the human footprint and the methodology used for data collection on anuran species richness.
机译：Anuran Richness模式受环境因素的强烈影响。但是，对这个问题的调查侧重于非生物因素的影响，而不考虑许多现有变量的联合效应，包括数据采样方法和人口统计学。在这项研究中，我们调查了巴西生物群系的21个环境变量与Anuran丰富的关系。环境变量代表人口统计数据，地形，气候和植被特征以及数据采样方法的组合。我们使用了主成分分解和回归和自回归模型来选择最相关的变量，以解释Anuran丰富性。丰富性与年度第三和第四季度的人口密度，植被，累计降雨，累计降雨量相关，并在今年的第一个和下半年累计降雨。然而，回归和自回归模型表明，人口统计密度，取样时间和采样方法是抗麻痹性的最佳预测因子。我们的结果突出了考虑人类足迹的影响和用于对抗南草物种丰富的数据收集的方法的重要性。

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