Institute of Botany, Czech Academy of Sciences, Dukelská 135 37982 Trebon, Czech Republic.
Ecology. 2012 Oct;93(10):2263-73. doi: 10.1890/11-1394.1.
Functional trait differences among species are increasingly used to infer the effects of biotic and abiotic processes on species coexistence. Commonly, the trait diversity observed within communities is compared to patterns simulated in randomly generated communities based on sampling within a region. The resulting patterns of trait convergence and divergence are assumed to reveal abiotic and biotic processes, respectively. However, biotic processes such as competition can produce both trait divergence and convergence, through either excluding similar species (niche differences, divergence) or excluding dissimilar species (weaker competitor exclusion, convergence). Hence, separating biotic and abiotic processes that can produce identical patterns of trait diversity, or even patterns that neutralize each other, is not feasible with previous methods. We propose an operational framework in which the functional trait dissimilarity within communities (FDcomm) is compared to the corresponding trait dissimilarity expected from the species pool (i.e., functional species pool diversity, FDpool). FDpool includes the set of potential species for a site delimited by the operating environmental and dispersal limitation filters. By applying these filters, the resulting pattern of trait diversity is consistent with biotic processes, i.e., trait divergence (FDcomm > FDpool) indicates niche differentiation, while trait convergence (FDcomm < FDpool) indicates weaker competitor exclusion. To illustrate this framework, with its potential application and constraints, we analyzed both simulated and field data. The functional species pool framework more consistently detected the simulated trait diversity patterns than previous approaches. In the field, using data from plant communities of typical Northern European habitats in Estonia, we found that both niche-based and weaker competitor exclusion influenced community assembly, depending on the traits and community considered. In both simulated and field data, we demonstrated that only by estimating the species pool of a site is it possible to differentiate the patterns of trait dissimilarity produced by operating biotic processes. The framework, which can be applied with both functional and phylogenetic diversity, enables a reinterpretation of community assembly processes. Solving the challenge of defining an appropriate reference species pool for a site can provide a better understanding of community assembly.
功能性状差异在物种间的差异越来越多地被用来推断生物和非生物过程对物种共存的影响。通常,将在社区内观察到的性状多样性与基于在该地区内采样的随机生成社区中的模式进行比较。假设趋同和发散的模式分别揭示了生物和非生物过程。然而,竞争等生物过程可以通过排除相似的物种(生态位差异,发散)或排除不相似的物种(较弱的竞争者排除,收敛)来产生性状的发散和收敛。因此,以前的方法无法区分可能产生相同性状多样性模式甚至相互抵消的模式的生物和非生物过程。我们提出了一个操作框架,其中社区内的功能性状差异(FDcomm)与从物种库(即功能物种库多样性,FDpool)中预期的相应性状差异进行比较。FDpool 包括由操作环境和扩散限制过滤器限定的站点的潜在物种集。通过应用这些过滤器,产生的性状多样性模式与生物过程一致,即性状发散(FDcomm > FDpool)表示生态位分化,而性状收敛(FDcomm < FDpool)表示较弱的竞争者排除。为了说明这个框架,及其潜在的应用和限制,我们分析了模拟和实地数据。与以前的方法相比,功能物种库框架更一致地检测到了模拟的性状多样性模式。在实地,我们使用了爱沙尼亚典型北欧生境的植物群落的数据,发现基于生态位和较弱的竞争者排除的两种机制都影响了群落组装,这取决于所考虑的性状和群落。在模拟和实地数据中,我们都证明,只有通过估计站点的物种库,才能区分由生物过程产生的性状差异模式。该框架可用于功能和系统发育多样性,可以重新解释群落组装过程。解决为站点定义适当的参考物种库的挑战可以更好地理解群落组装。