97th ESA Annual Meeting (August 5 -- 10, 2012)

COS 63-6 - A trait-centered approach to risk assessment of non-native fishes in trade

Tuesday, August 7, 2012: 3:20 PM
E144, Oregon Convention Center
Jennifer G. Howeth1, Crysta A. Gantz2, Paul L. Angermeier3, Emmanuel A. Frimpong4, Michael Hoff5, Reuben P. Keller6, David M. Lodge2, Nicholas E. Mandrak7, Michael P. Marchetti8, Julian D. Olden9 and Christina M. Romagosa10, (1)Department of Biological Sciences, University of Alabama, Tuscaloosa, AL, (2)Biological Sciences, University of Notre Dame, Notre Dame, IN, (3)Fisheries and Wildlife Sciences, U.S. Geological Survey, Virginia Cooperative Fish and Wildlife Research Unit, Blacksburg, VA, (4)Fisheries and Wildlife Sciences, Virginia Polytechnic Institute and State University, Blacksburg, VA, (5)Fisheries Program, United States Fish and Wildlife Service, Bloomington, MN, (6)Institute of Environmental Sustainability, Loyola University Chicago, Chicago, IL, (7)Department of Ecology and Evolutionary Biology, University of Toronto, Toronto, ON, Canada, (8)Department of Biology, St. Mary's College of California, Moraga, CA, (9)School of Aquatic and Fishery Sciences, University of Washington, Seattle, WA, (10)Department of Biological Sciences, Auburn University, Auburn, AL
Background/Question/Methods

Identifying species traits associated with the different stages of biological invasion remains a central focus of community ecology and conservation biology. The application of trait-centered models to evaluating the risk of species establishment and impact in non-native environments, however, is rare. In this study, ecological, life-history, and phylogenetic traits associated with the establishment and impact stages of invasion in non-native fish species were identified and subsequently used to detect species posing a threat to Great Lakes ecosystems. The Great Lakes are a well-documented invasion hotspot and are particularly vulnerable to non-native fish introductions due to high regional and international trade traffic. Given a diverse invader species pool from multiple trade pathways, an analysis of Great Lakes fishes provides a rigorous test of traits associated with biological invasion. Important traits were identified by comparing trait values in successfully established non-native fish species to those which failed to establish using machine learning statistical methods. Classification trees composed of several key traits were constructed for the establishment and impact stages of invasion, and were used to assess the risk of non-natives fishes in trade.

Results/Conclusions

Establishment success of non-native fish species was most strongly predicted by climate similarities between the environments of the native range and the Great Lakes region. In contrast, the ecological impact of established non-native fish species was best predicted by trophic guild, where species in the top trophic levels (piscivores, invertivore-piscivores) had the greatest impact on lake food web structure and ecosystem function. Classification tree analysis of potential invaders suggests that high risk non-native fish may be supplied via the aquarium, bait, biological supply, live food, and water garden trades. The results of this study confer insight into mechanisms underlying biological invasion by highlighting an important role of climate match in establishment success, and trophic position in ecological impact. Additionally, the results will inform state and federal policies regarding regulation of non-native species in trade. This trait-based approach to invasive species risk assessment provides an ecologically robust method of identifying species likely to become established, and have impact, in non-native environments.