2023
DOI: 10.1016/j.scitotenv.2023.161486
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Alien species and climate change drive shifts in a riverine fish community and trait compositions over 35 years

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Cited by 20 publications
(13 citation statements)
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“…Furthermore, there is a pressing need for persistent spatio‐temporal sampling (Leroy et al, 2023). Regular, systematic sampling across different seasons and years would help in understanding temporal trends and the impact of environmental changes (Haubrock et al, 2023; Haubrock & Soto, 2023; Le Hen et al, 2023), such as salinization, climate change and non‐native species introductions, on fish communities (Haubrock, Balzani, et al, 2020; Leite et al, 2022; Haubrock & Soto, 2023). Additionally, incorporating environmental DNA (eDNA) sampling could offer insights into species diversity and presence with less impact on the environment and could be particularly useful for detecting rare or elusive species (Sakata et al, 2021).…”
Section: Discussionmentioning
confidence: 99%
“…Furthermore, there is a pressing need for persistent spatio‐temporal sampling (Leroy et al, 2023). Regular, systematic sampling across different seasons and years would help in understanding temporal trends and the impact of environmental changes (Haubrock et al, 2023; Haubrock & Soto, 2023; Le Hen et al, 2023), such as salinization, climate change and non‐native species introductions, on fish communities (Haubrock, Balzani, et al, 2020; Leite et al, 2022; Haubrock & Soto, 2023). Additionally, incorporating environmental DNA (eDNA) sampling could offer insights into species diversity and presence with less impact on the environment and could be particularly useful for detecting rare or elusive species (Sakata et al, 2021).…”
Section: Discussionmentioning
confidence: 99%
“…To identify periods in which the variance of costs reported within InvaCost (v4.1) changed over time, we applied a first-order autoregressive AR (1) process for the residuals [ 58 ]. This enabled the computation of derivatives of fitted splines using the method of finite differences to estimate the rate of change (slope) in the fitted smoother [ 59 ]. This produces diagnostic plots of the costs over time, where we could identify periods of non-random change(s) and superimpose them on the respective temporal trend [ 60 ].…”
Section: Methodsmentioning
confidence: 99%
“…To identify periods in which the variance of costs reported within InvaCost (v4.1) changed over time, we applied a rst-order autoregressive AR(1) process for the residuals (Nathan et al, 1999). This enabled the computation of derivatives of tted splines using the method of nite differences to estimate the rate of change (slope) in the tted smoother (Le Hen et al, 2023). This produces diagnostic plots of the costs over time, where we could identify periods of non-random change(s) and superimpose them on the respective temporal trend (Simpson, 2018).…”
Section: Temporal Projectionmentioning
confidence: 99%