An integrative approach to quantifying the response of ecological assemblages to anthropogenic stressors

森林砍伐、气候变化、栖息地破碎化和入侵物种等生态压力源在世界各地普遍存在，部分原因可能是人类活动。检测和量化这些压力源对物种群落的影响的能力对于维持和管理生物多样性和生态系统的健康至关重要。然而，考虑到生物多样性数据的多变性和多面性，评估人类活动对这些物种群落的影响是一个具有挑战性的问题。物种的差异不仅体现在它们的分类特征上，而且体现在它们的丰度、进化史以及它们在生态系统中的作用和功能上。预测和理解物种群落如何被人为变化所改变以及新群落如何发挥功能是维持生物多样性和生态系统功能的关键。本项目旨在发展一种量化人类活动对生态系统影响的计算方法。将这些工具应用于紧迫的生态问题，将产生关于生物群落如何应对多种全球重要的人为压力的急需信息。该项目旨在开发新的计算方法，整合多种生物多样性信息来源，以描绘物种组合内的组成单位（从这里开始定义为组成群落），并量化人为压力的影响。该项目有两个具体目标。首先，将系统发育信息与物种相互作用和组成数据相结合，在异质性生物多样性数据中识别生态组合中的组分群落。二是将这些综合方法应用于不同的数据集，基于这些组成群落对人为压力源的响应来表征生态组合的组成变化。有关该项目的更多信息，请访问PI的实验室页面http://denisvalle.weebly.com/。

Ecological stressors such as deforestation, climate change, habitat fragmentation, and invasive species are pervasive throughout the world and can be driven in part by human (anthropogenic) activity. The ability to detect and quantify the impact of these stressors on species communities is critical for maintaining and managing biodiversity and the health of ecosystems. The assessment of anthropogenic impacts on these species communities, however, is a challenging problem given the multivariate nature and multiple facets of biodiversity data. Species differ not only in their taxonomic identities but also in their abundances, evolutionary history, and their role and function in ecosystems. Predicting and understanding how species communities are altered by anthropogenic change and how novel communities function is key to sustaining biodiversity and ecosystem function. This project aims to develop a computational approach for quantifying anthropogenic impacts on ecosystems. The application of these tools to pressing ecological questions will generate much needed information regarding how biological communities are responding to multiple globally important anthropogenic stressorsThis project aims to develop new computational methods that integrate multiple sources of biodiversity information to delineate constituent units within species assemblages (defined from here onwards as component communities) and quantify the impact of anthropogenic stressors. The project has two specific aims. The first is to integrate phylogenetic information with species interaction and composition data to identify component communities within ecological assemblages in heterogeneous biodiversity data. The second is to apply these integrative methods to diverse datasets to characterize the changes in composition of ecological assemblages based on responses of these component communities to anthropogenic stressors. For more information on this project visit the PI's lab page at http://denisvalle.weebly.com/.