Département de biologie, chimie et géographie, Université du Québec à Rimouski, Rimouski, QC, Canada.
Ecol Lett. 2013 Jul;16(7):853-61. doi: 10.1111/ele.12118. Epub 2013 May 22.
The biodiversity-ecosystem functioning (BEF) relationship is central in community ecology. Its drivers in competitive systems (sampling effect and functional complementarity) are intuitive and elegant, but we lack an integrative understanding of these drivers in complex ecosystems. Because networks encompass two key components of the BEF relationship (species richness and biomass flow), they provide a key to identify these drivers, assuming that we have a meaningful measure of functional complementarity. In a network, diversity can be defined by species richness, the number of trophic levels, but perhaps more importantly, the diversity of interactions. In this paper, we define the concept of trophic complementarity (TC), which emerges through exploitative and apparent competition processes, and study its contribution to ecosystem functioning. Using a model of trophic community dynamics, we show that TC predicts various measures of ecosystem functioning, and generate a range of testable predictions. We find that, in addition to the number of species, the structure of their interactions needs to be accounted for to predict ecosystem productivity.
生物多样性-生态系统功能（BEF）关系是群落生态学的核心。在竞争系统中，其驱动因素（采样效应和功能互补性）直观而优雅，但我们缺乏对复杂生态系统中这些驱动因素的综合理解。由于网络包含了 BEF 关系的两个关键组成部分（物种丰富度和生物量流），因此它们提供了一个识别这些驱动因素的关键，假设我们有一个有意义的功能互补性衡量标准。在网络中，多样性可以通过物种丰富度、营养水平数来定义，但也许更重要的是，通过相互作用的多样性来定义。在本文中，我们定义了营养互补性（TC）的概念，它是通过掠夺性和明显的竞争过程出现的，并研究了它对生态系统功能的贡献。我们使用一个营养社区动态模型来表明，TC 可以预测各种生态系统功能的衡量标准，并产生一系列可测试的预测。我们发现，除了物种数量之外，还需要考虑它们相互作用的结构，以预测生态系统生产力。
