Abstract
To understand biodiversity change and support conservation decision-making, estimates of species' long-term population trends at regional and national scales are essential. However, such estimates are missing for many freshwater taxa, despite the diverse range of threats that they face. For this study, we mobilised monitoring data on riverine freshwater fish abundance collected across different regions of Germany. We applied generalized mixed effect models to estimate the population trends for 55 native species and 11 non-native species between 2004 and 2020. In addition, we used boosted regression trees to identify trait-based predictors of species trends and assessed their predictive ability. We found evidence of increasing abundance trends for 14 species and decreasing trends for 15 species; while the remaining species were mostly stable (26 species). Native species were more typically decreasing than increasing (14 vs 10 species); while non-native species were more often increasing (4 vs 1 species). Important traits associated with trends were maximum length, spawning temperature, and water quality tolerance, with small species, those spawning at high temperatures, and those preferring unpolluted waters, being most likely to have positive trends. Despite these associations, overall trait-based models showed limited power to predict trends in terms of direction as well as magnitude. Our results highlight the ongoing change in riverine fish communities and the importance of on-going species-level monitoring. The trait-based associations also indicate climate change and invasive species as important drivers of change in European freshwater rivers.
Published Version
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