Predicting the potential distribution of the non-native Red Swamp Crayfish Procambarus clarkii in the Laurentian Great Lakes

Journal of Great Lakes Research(2019)

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摘要
The ongoing threat of introduction of invasive species, including crayfish, to the Laurentian Great Lakes has motivated the development of predictive models to inform where these invaders are likely to establish. Our study is among the first to apply regional freshwater-specific GIS layers to species occurrence data to predict ecosystem suitability to invasions, specifically for the red swamp crayfish, Procambarus clarkii, in the Great Lakes. We combined a database of crayfish species occurrences with the Great Lakes Aquatic Habitat Framework (GLAHF) GIS layers to model habitats suitable to invasion by P. clarkii using boosted regression trees and physiological information for this species. We developed a model of all suitable crayfish habitat across the Great Lakes, then constrained this habitat to areas anticipated to be suitable for P. clarkii based on known physiological limitations of this species. Specifically, P. clarkii requires a minimum temperature of 15 °C for copulation and oviposition, with peak reproduction occurring at temperatures of 20–23 °C. We identified 2% of the Great Lakes as suitable for P. clarkii establishment and 0.88% as optimal for this crayfish, primarily located on the southern coastlines of lakes Michigan and Erie and shallow bays including Saginaw Bay (Lake Huron), Green Bay (Lake Michigan), and Henderson Bay (Lake Ontario). These predictions of where P. clarkii is likely to establish populations can be used to identify areas where education, outreach, compliance, and law enforcement efforts should seek to prevent new introductions of this crayfish and help prioritize locations for surveillance to detect newly established populations.
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关键词
Boosted regression trees,Ecological niche model,Exotic species,Invasive species,Risk assessment,Species distribution modeling
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