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Hierarchical analysis of species distributions and abundance across environmental gradients

机译:跨环境梯度的物种分布和丰度的层次分析

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摘要

Abiotic and biotic processes operate at multiple spatial and temporal scales to shape many ecological processes, including species distributions and demography. Current debate about the relative roles of niche-based and stochastic processes in shaping species distributions and community composition reflects, in part, the challenge of understanding how these processes interact across scales. Traditional statistical models that ignore autocorrelation and spatial hierarchies can result in misidentification of important ecological covariates. Here, we demonstrate the utility of a hierarchical modeling framework for testing hypotheses about the importance of abiotic factors at different spatial scales and local spatial autocorrelation for shaping species distributions and abundances. For the two orchid species studied, understory light availability and soil moisture helped to explain patterns of presence and abundance at a microsite scale (< 4 m(2)), while soil organic content was important at a population scale (< 400 m(2)). The inclusion of spatial autocorrelation is shown to alter the magnitude and certainty of estimated relationships between abundance and abiotic variables, and we suggest that such analysis be used more often to explore the relationships between species life histories and distributions. The hierarchical modeling framework is shown to have great potential for elucidating ecological relationships involving abiotic and biotic processes simultaneously at multiple scales.
机译:非生物和生物过程在多个时空尺度上运作,以塑造许多生态过程,包括物种分布和人口统计。当前关于基于生态位的过程和随机过程在塑造物种分布和群落组成中的相对作用的争论,在一定程度上反映了理解这些过程如何跨规模相互作用的挑战。忽略自相关和空间层次结构的传统统计模型可能会导致对重要生态协变量的错误识别。在这里,我们演示了分层建模框架的实用性,该框架用于测试关于非生物因素在不同空间尺度上的重要性以及局部空间自相关对塑造物种分布和丰度的重要性的假设。对于所研究的两个兰花物种,地下光的可获得性和土壤湿度有助于解释微观位点规模(<4 m(2))的存在和丰度模式,而土壤有机含量在人口规模(<400 m(2) ))。包含空间自相关表明可以改变丰度和非生物变量之间估计关系的大小和确定性,我们建议这种分析应更经常地用于探索物种生活史与分布之间的关系。分层建模框架显示出巨大的潜力,可以在多个尺度上同时阐明涉及非生物和生物过程的生态关系。

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