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Analyzing spatial structure of communities using the two-dimensional Poisson lognormal species abundance model

机译:使用二维Poisson对数正态物种丰度模型分析社区的空间结构

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The joint spatial and temporal fluctuations in the community structure of tropical butterflies are analyzed by fitting the bivariate Poisson lognormal distribution to a large number of observations in space and time. By applying multivariate dependent diffusions for describing the fluctuations in the abundances, the environmental variance is estimated to be very large and so is the strength of local density regulation. The variance in the lognormal species abundance distribution is partitioned into components expressing the heterogeneity between the species, independent noise components for the different species, a demographic stochastic component, and a component due to overdispersion in the sampling. In disagreement with the neutral theory, the estimates show that the heterogeneity component is the dominating one, representing 81% of the total variance in the lognormal model. Different spatial components of diversity, the alpha, beta, and gamma diversity, are also estimated. The spatial scale of the autocorrelation function for the community is of order 1 km, while sampling of a quadrat would need to be 10 km on a side to yield the total diversity for the community. [References: 60]
机译:通过将双变量泊松对数正态分布拟合到大量的时空观测资料,分析了热带蝴蝶群落结构的联合时空波动。通过应用多元相关的扩散来描述丰度的波动,估计环境变化非常大,因此局部密度调节的强度也是如此。对数正态物种丰度分布中的方差被划分为表示物种之间异质性的成分,不同物种的独立噪声成分,人口统计随机成分以及由于采样中的过度分散所导致的成分。与中立理论不同,估计表明异质性成分是主要成分,占对数正态模型中总方差的81%。还估计了多样性的不同空间成分,即alpha,beta和gamma多样性。社区的自相关函数的空间尺度约为1 km,而一个方方的采样将需要在一侧为10 km,以产生社区的总多样性。 [参考:60]

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