Am Nat. 2024 Jan;203(1):E1-E18. doi: 10.1086/727471. Epub 2023 Nov 27.
AbstractLinking species traits with the variation in species assemblages across habitats has often proved useful for developing a more mechanistic understanding of species distributions in metacommunities. However, summarizing the rich tapestry of a species in all of its nuance with a few key ecological traits can also lead to an abstraction that provides less predictability than when using taxonomy alone. As a further complication, taxonomic and functional diversities can be inequitably compared, either by integrating taxonomic-level information into the calculation of how functional aspects of communities vary or by detecting spurious trait-environment relationships. To remedy this, we here synthesize analyses of 80 datasets on different taxa, ecosystems, and spatial scales that include information on abundance or presence/absence of species across sites with variable environmental conditions and the species' traits. By developing analyses that treat functional and taxonomic diversity equitably, we ask when functional diversity helps to explain metacommunity structure. We found that patterns of functional diversity explained metacommunity structure and response to environmental variation in only 25% of the datasets using a multitrait approach but up to 59% using a single-trait approach. Nevertheless, an average of only 19% (interquartile range = 0%-29%) of the traits showed a significant signal across environmental gradients. Species-level traits, as typically collected and analyzed through functional diversity patterns, often do not bring predictive advantages over what the taxonomic information already holds. While our assessment of a limited advantage of using traits to explain variation in species assemblages was largely true across ecosystems, traits played a more useful role in explaining variation when many traits were used and when trait constructs were more related to species' status, life history, and mobility. We propose future research directions to make trait-based approaches and data more helpful for inference in metacommunity ecology.
摘要
将物种特征与栖息地中物种组合的变化联系起来，通常有助于更深入地了解物种在复合群落中的分布机制。然而，用少数几个关键生态特征来概括一个物种的丰富内涵，也可能会导致概括过于抽象，从而降低预测能力，而仅使用分类学信息则不会。更为复杂的是，分类多样性和功能多样性可能存在不公平的比较，既可以通过将分类级别信息纳入社区功能方面变化的计算中，也可以通过检测虚假的特征-环境关系来实现。为了解决这个问题，我们综合分析了 80 个关于不同分类群、生态系统和空间尺度的数据集，这些数据集包含了在具有不同环境条件的站点上的物种丰度或存在/不存在的信息，以及物种的特征。通过开发公平对待功能和分类多样性的分析方法，我们询问功能多样性何时有助于解释复合群落结构。我们发现，在使用多特征方法时，只有 25%的数据集可以通过功能多样性模式来解释复合群落结构和对环境变化的响应，而在使用单一特征方法时，最多可以解释 59%。然而，只有 19%的特征（四分位距= 0%-29%）在环境梯度上表现出显著的信号。通常通过功能多样性模式收集和分析的物种水平特征，往往不会比分类学信息更具有预测优势。虽然我们评估的使用特征来解释物种组合变化的优势在很大程度上是跨生态系统的，但当使用许多特征并且特征结构与物种地位、生活史和移动性更相关时，特征在解释变化方面发挥了更有用的作用。我们提出了未来的研究方向，以使基于特征的方法和数据更有助于复合群落生态学的推理。
