Advancing our understanding of biological invasions with long-term biomonitoring data

被引:0
|
作者
Phillip J. Haubrock
Laís Carneiro
Rafael L. Macêdo
Paride Balzani
Ismael Soto
Jes Jessen Rasmussen
Peter Wiberg-Larsen
Zoltan Csabai
Gábor Várbíró
John Francis Murphy
J. Iwan Jones
Ralf C. M. Verdonschot
Piet Verdonschot
Gea van der Lee
Danish A. Ahmed
机构
[1] Senckenberg Research Institute and Natural History Museum Frankfurt,Department of River Ecology and Conservation
[2] University of South Bohemia in České Budějovice,Faculty of Fisheries and Protection of Waters, South Bohemian Research Center of Aquaculture and Biodiversity of Hydrocenoses
[3] Gulf University for Science and Technology,CAMB, Center for Applied Mathematics and Bioinformatics
[4] Federal University of Parana - UFPR,Laboratory of Ecology and Conservation, Department of Environmental Engineering
[5] Federal University of São Carlos,Graduate Program in Ecology and Natural Resources
[6] UFSCAR,Centre National de Recherche Scientifique, AgroParisTech, Ecologie Systématique Evolution
[7] Université Paris-Saclay,Department of Ecoscience
[8] Norwegian Institute for Water Research (NIVA Denmark),Department of Hydrobiology, Faculty of Sciences
[9] Aarhus University,Centre for Ecological Research
[10] University of Pécs,School of Biological and Behavioural Sciences
[11] Balaton Limnological Research Institute,Wageningen Environmental Research
[12] Institute of Aquatic Ecology,undefined
[13] Queen Mary University of London,undefined
[14] Wageningen UR,undefined
来源
Biological Invasions | 2023年 / 25卷
关键词
Biological invasion; Monitoring efforts; Ecology; Time series; Non-native species;
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中图分类号
学科分类号
摘要
The use of long-term datasets is crucial in ecology because it provides a comprehensive understanding of natural fluctuations, changes in ecosystems over extended periods of time, and robust comparisons across geographical scales. This information is critical in detecting and analysing trends and patterns in species populations, community dynamics, and ecosystem functioning, which in turn helps in predicting future changes and impacts of human activities. Additionally, long-term data sets allow for the evaluation of the effectiveness of conservation efforts and management strategies, enabling scientists and decision makers to make evidence-based decisions for biodiversity conservation. Although the use of long-term data is recognized as highly important in several scientific disciplines, its usage remains undervalued regarding questions in invasion science. Here, we used four regional subsets (i.e. England, Hungary, Denmark and the Dutch-German-Luxembourg) of a recently collated long-term time series database to investigate the abundance and dynamics of occurring non-native species over space and time in Europe. While we found differences in the numbers of non-native species across the studied regions (Dutch-German-Luxembourg region = 37; England = 17, Hungary = 34; Denmark = 3), non-native species detection rates were continuous over time. Our results further show that long-term monitoring efforts at large spatial scales can substantially increase the accuracy and rate at which non-native species are detected. This information can inform management endeavours dealing with non-native species, underlining the need for invasion scientists and authorities-stakeholders to make more effort in collecting, analysing and making available long-term datasets at broader geographic ranges.
引用
收藏
页码:3637 / 3649
页数:12
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