Cantera Isabel, Giachello Simone, Münkemüller Tamara, Caccianiga Marco, Gobbi Mauro, Losapio Gianalberto, Marta Silvio, Valle Barbara, Zawierucha Krzysztof, Thuiller Wilfried, Ficetola Gentile Francesco
Department of Environmental Science and Policy, Università degli Studi di Milano, Milano, Italy.
Department of Environmental Science and Policy, Università degli Studi di Milano, Milano, Italy; Department of Sciences, Technologies and Society, University School for Advanced Studies IUSS Pavia, Pavia, Italy.
Trends Ecol Evol. 2025 Feb;40(2):170-179. doi: 10.1016/j.tree.2024.10.007. Epub 2024 Nov 21.
Comprehensive assessments of functional diversity are needed to understand ecosystem alterations under global changes. The 'Fun-eDNA' approach characterises functional diversity by assigning traits to taxonomic units obtained through environmental DNA (eDNA) sampling. By simultaneously analysing an unprecedented number of taxa over broad spatial scales, the approach provides a whole-ecosystem perspective of functional diversity. Fun-eDNA is increasingly used to tackle multiple questions, but aligning eDNA with traits poses several conceptual and technical challenges. Enhancing trait databases, improving the annotation of eDNA-based taxonomic inventories, interdisciplinary collaboration, and conceptual harmonisation of traits are key steps to achieve a comprehensive assessment of diverse taxa. Overcoming these challenges can unlock the full potential of eDNA in leveraging measures of ecosystem functions from multi-taxa assessments.
需要对功能多样性进行全面评估,以了解全球变化下的生态系统变化。“功能宏基因组学方法(Fun-eDNA)”通过将性状赋予通过环境DNA(eDNA)采样获得的分类单元来表征功能多样性。通过在广泛的空间尺度上同时分析数量空前的分类群,该方法提供了功能多样性的全生态系统视角。功能宏基因组学方法越来越多地用于解决多个问题,但将宏基因组学与性状相结合带来了一些概念和技术挑战。加强性状数据库、改进基于宏基因组学的分类清单注释、跨学科合作以及性状的概念协调是实现对多样分类群进行全面评估的关键步骤。克服这些挑战可以释放宏基因组学在利用多分类群评估中的生态系统功能测量方面的全部潜力。