Partitioning the temporal changes in abundance-based beta diversity into loss and gain components
Partitioning the temporal changes in abundance-based beta diversity into loss and gain components
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DOI：
10.1111/2041-210x.13921
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发表时间：
2021-05
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影响因子：
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通讯作者：
S. Tatsumi;Ryosuke Iritani;M. Cadotte
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文献类型：
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作者：
S. Tatsumi;Ryosuke Iritani;M. Cadotte
生态学家早就认识到，当地物种丰度的损失和增加可以减少或增加空间β多样性，这种现象通常分别被称为生物同质化和分化。然而，量化物种丰度对β多样性的这种动态影响仍然是一个方法上的挑战。在这里，我们开发了一种数值方法来添加分区的时间变化β多样性到不同的组件，反映当地物种丰度的损失和收益。我们的方法是基于Ružička和Bray-Curtis指数和归一化丰度的惠特克的β多样性。这些措施的时间变化被划分为组件，代表生物的同质化和分化的丰富的损失和收益在物种和社区水平。将该方法应用于瑞典鱼类群落数据集显示，1990年至2018年期间β多样性有所下降。鱼类群落的同质化是由各地点物种丰度的增加而不是减少来解释的。物种一级的划分进一步表明，同质化主要是由于在已经存在的地点增加了特定物种的种群规模。结果强调，我们的分区方法有效地识别当地人口和社区的过程中嵌入区域生物多样性模式。我们认为，明确的物种丰度的损失和收益的分析应该带来更深入的了解β多样性的动态。
Ecologists have long recognized that the losses and gains in local species abundances can either decrease or increase spatial beta diversity, phenomena often referred to as biotic homogenization and differentiation, respectively. However, quantifying such dynamic impacts of species abundances on beta diversity has remained a methodological challenge. Here, we develop a numerical method to additively partition the temporal changes in beta diversity into distinct components that reflect the losses and gains in local species abundances. Our method is based on Ružička and Bray–Curtis indices and the normalized abundance-based Whittaker’s beta diversity. The temporal changes in these measures are partitioned into components that represent biotic homogenization and differentiation driven by abundance losses and gains at both species and community levels. Application of the method to a Swedish fish community dataset revealed decreases in beta diversity between 1990 and 2018. The homogenization of fish communities was explained by gains, but not losses, in species abundances across sites. Species-level partitioning further showed that the homogenization was largely caused by the increased population sizes of a particular species in sites where it was already present. The results highlight that our partitioning method effectively identifies local population and community processes embedded in regional biodiversity patterns. We believe that explicit analyses of the losses and gains in species abundances should bring deeper insights into the dynamics of beta diversity.