Am Nat. 2022 Aug;200(2):181-192. doi: 10.1086/720284. Epub 2022 Jun 14.
AbstractThe relationship between biodiversity and ecosystem function (BEF) remains unclear in many natural ecosystems, partially for lack of theoretical and analytical tools that match common characteristics of observational community data. The ecological Price equation promises to meet this need by organizing many different species-level changes into a few ecologically meaningful categories that sum to total ecosystem function change. Current versions of the ecological Price equation focus on species richness and presence-absence. However, abundance and relative abundance are better estimated in samples and are likely showing a stronger response to global change. Here, we present a novel, abundance-based version of the ecological Price equation in both discrete and continuous forms and explain the similarities and differences between this method and a related, previously developed richness-based method. We also present new empirical techniques for applying the Price equation to ecological data. Our two demonstration analyses reveal how additive effects of increasing abundance on total function are modified by concurrent selection effects due to shifts in species' composition as well as intraspecific change in species' per capita function. The ecological Price equations derived here complement existing approaches and together offer BEF researchers analytical tools and a unifying framework for studying BEF in observational community data.
摘要
在许多自然生态系统中，生物多样性与生态系统功能（BEF）之间的关系仍不清楚，部分原因是缺乏与观测群落数据常见特征相匹配的理论和分析工具。生态Price 方程有望满足这一需求，它将许多不同的物种水平变化组织成几个具有生态意义的类别，这些类别加起来就是整个生态系统功能的变化。当前版本的生态 Price 方程主要关注物种丰富度和有无。然而，丰度和相对丰度在样本中更容易被估计，而且它们可能对全球变化表现出更强的响应。在这里，我们提出了一种新颖的、基于丰度的离散和连续形式的生态 Price 方程，并解释了这种方法与之前开发的基于丰富度的方法之间的相似性和差异。我们还提出了新的经验技术，用于将 Price 方程应用于生态数据。我们的两个演示分析揭示了随着物种组成的变化以及物种个体功能的种内变化而产生的物种同时的选择效应，如何改变了物种丰度增加对总功能的加性效应。这里推导的生态 Price 方程补充了现有的方法，为 BEF 研究人员提供了分析工具和统一的框架，用于研究观测群落数据中的 BEF。
