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
{"title":"Novel community data in ecology-properties and prospects.","authors":"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","doi":"10.1016/j.tree.2023.09.017","DOIUrl":null,"url":null,"abstract":"<p><p>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.</p>","PeriodicalId":23274,"journal":{"name":"Trends in ecology & evolution","volume":" ","pages":"280-293"},"PeriodicalIF":16.7000,"publicationDate":"2024-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Trends in ecology & evolution","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.1016/j.tree.2023.09.017","RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2023/11/8 0:00:00","PubModel":"Epub","JCR":"Q1","JCRName":"ECOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
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.
期刊介绍:
Trends in Ecology & Evolution (TREE) is a comprehensive journal featuring polished, concise, and readable reviews, opinions, and letters in all areas of ecology and evolutionary science. Catering to researchers, lecturers, teachers, field workers, and students, it serves as a valuable source of information. The journal keeps scientists informed about new developments and ideas across the spectrum of ecology and evolutionary biology, spanning from pure to applied and molecular to global perspectives. In the face of global environmental change, Trends in Ecology & Evolution plays a crucial role in covering all significant issues concerning organisms and their environments, making it a major forum for life scientists.