Original Paper

Biological Invasions

, Volume 14, Issue 6, pp 1265-1278

First online:

Application of bioclimatic models coupled with network analysis for risk assessment of the killer shrimp, Dikerogammarus villosus, in Great Britain

  • Belinda GallardoAffiliated withAquatic Ecology Group, Department of Zoology, University of Cambridge Email author 
  • , M. Paz ErreaAffiliated withPyrenean Institute of Ecology (CSIC)
  • , David C. AldridgeAffiliated withAquatic Ecology Group, Department of Zoology, University of Cambridge

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In this study we use a combination of techniques to assess the general risk of invasion by the aquatic invader Dikerogammarus villosus in Great Britain at multiple scales. First, bioclimatic models (Support Vector Machine algorithm) were used to identify regions showing the highest climatic match with the European range of the species, and that might be at highest risk of initial colonization if provided with propagules. The model showed that nearly 60% of Great Britain shows the minimum bioclimatic suitability for the species, particularly southern and eastern England. Afterwards, a Network Analysis was used to model the natural spatio-temporal spread of the killer shrimp in the Great Ouse River catchment (SE England), the first region invaded by this species. This model suggested that the northern part of the catchment, including two relevant Ramsar sites (Ouse Washes and Wicken fen) are at serious risk of being invaded in the short-term (<5 years). Taking into account the rapid spread of the killer shrimp in other European countries, its broad environmental tolerance, the high climate suitability of broad areas of Great Britain to the species, the current spread of other Ponto-Caspian species, and the high natural and artificial connectivity of the hydrological network, we conclude that D. villosus is very likely to continue its spread in Great Britain, dramatically affecting the native biodiversity. The multi-scale approach proposed in this study combines large-scale bioclimatic models with local-scale dispersal models, providing managers with a powerful spatial and temporal basis for informed decision-making.


Aquatic invasive species Dispersal velocity Great Ouse River Support Vector Machine Species distribution model Zebra mussel