Invasive traits of freshwater fish database (ITOFF)

Aaron Jessop, Anna Michalopoulou, Carolyn Coonan, Lewis Mazzei, Eilidh O'Brien, Grace Elizabeth Brady, Carly Davison, Wayne Gourlay, Ethan Henderson, Anna Lornie, Emily McCloskey, Hannah Ramsay, Sophie Wilson, Hideyasy Shimadzu, Miguel Borges Da Costa Guint Barbosa

Research output: Working paperPreprint


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.


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.

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.
Original languageEnglish
Number of pages40
Publication statusPublished - 17 Nov 2023


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  • Invasive traits of freshwater fish database (ITOFF) (thesis dataset 2)

    Jessop, A. (Creator), Michalopoulou, A. (Creator), Coonan, C. (Creator), Mazzei, L. (Creator), Brady, G. (Creator), Gouraly, W. (Creator), Henderson, E. (Creator), Lornie, A. (Creator), McCloskey, E. (Creator), Ramsay, H. (Creator), Sutherland O'Brien, E. (Creator), Wilson, S. (Creator), Shimadzu, H. (Creator) & Barbosa, M. (Creator), Zenodo, 2023

    Dataset: Thesis dataset

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