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Novel Community Data in Ecology-properties and Prospects
论文题目: Novel Community Data in Ecology-properties and Prospects
作者: Florian Hartig, Nerea Abrego, Alex Bush, Jonathan M Chase, Gurutzeta Guillera-Arroita, Mathew A Leibold, Otso Ovaskainen, Loïc Pellissier, Maximilian Pichler, Giovanni Poggiato, Laura Pollock, Sara Si-Moussi, Wilfried Thuiller, Duarte S Viana, David I Warton, Damaris Zurell, Douglas W Yu
联系作者: florian.hartig@ur.de
发表年度: 2024
DOI: DOI: 10.1016/j.tree.2023.09.017
摘要:

New technologies for monitoring biodiversity such as environmental (e)DNA, passive acoustic monitoring, and optical sensors promise to generate automated spatiotemporal community observations at unprecedented scales and resolutions. Here, we introduce 'novel community data' as an umbrella term for these data. We review the emerging field around novel community data, focusing on new ecological questions that could be addressed; the analytical tools available or needed to make best use of these data; and the potential implications of these developments for policy and conservation. We conclude that novel community data offer many opportunities to advance our understanding of fundamental ecological processes, including community assembly, biotic interactions, micro- and macroevolution, and overall ecosystem functioning.

刊物名称: Trends in Ecology & Evolution
论文出处: https://www.sciencedirect.com/science/article/pii/S0169534723002653
影响因子: 16.8(2022IF)
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