Invasive traits of freshwater fish database (ITOFF)

Aaron Jessop
Anna Michalopoulou
Carolyn Coonan
Lewis Mazzei
Eilidh Sutherland O'Brien
Grace Brady
Carly Davison
Wayne Gourlay
Ethan Henderson
Anna Lornie
Emily McCloskey
Hannah Ramsay
Sophie Wilson
Hideyasu Shimadzu
Miguel Barbosa
Show full list: 15 authors
Publication typePosted Content
Publication date2023-11-17
Abstract
AIM

Species invasions are a major driver of global biodiversity loss, but only a minority of invasions are successful. Evidence suggests that invasive success is linked to life-history traits. Yet, data on invasive success and species’ traits remain fragmented across multiple sources. Here we present the Invasive Traits of Freshwater Fish (ITOFF) database, an interdisciplinary framework that integrates multiple datasets to elucidate the role of life-history traits in shaping invasive success. ITOFF allows seamless access to invasive species data and fosters collaborative actions through knowledge sharing. ITOFF is supported by an innovative web-application that makes complex relationships between invasive and native species accessible to a broad audience. The scientific contribution of ITOFF is illustrated by examining the role of life-history traits and phylogeny in invasion success.

LOCATION

Global.

METHODS

Generalized linear models were used to test the contribution of generation time, trophic level, longevity, and temperature range to invasive success. Through divisive cluster analysis we investigate the role of multiple traits in determining invasive success. Finally, we construct phylogenetic trees to investigate the role of evolutionary history in the invasion process.

RESULTS

ITOFF unifies data for 1917 freshwater fish species representative of invasive species, those species they endanger, and species impacted by invasives but not considered endangered. Invasive species are generally characterized by greater temperature ranges, but are indistinguishable from impacted, endangered, and critically endangered species for the remaining life-history traits. Further, we show that invasive species are generally not distinct from impacted or endangered species when considering multiple traits or phylogeny.

MAIN CONCLUSIONS

ITOFF provides an accessible platform for the improved forecasting of species invasions. ITOFF data shows that classical predictions of life-history traits determining invasive success do not hold amongst freshwater fish species. Forecasting of invasive species must therefore shift towards a wholistic approach encompassing the species and the environment.

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