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Forecasting the Spread of Invasive Rainbow Smelt in the Laurentian Great Lakes Region of North America

Identifieur interne : 000860 ( Main/Exploration ); précédent : 000859; suivant : 000861

Forecasting the Spread of Invasive Rainbow Smelt in the Laurentian Great Lakes Region of North America

Auteurs : Norman Mercado-Silva [États-Unis] ; Julian D. Olden [États-Unis] ; Jeffrey T. Maxted [États-Unis] ; Thomas R. Hrabik [États-Unis] ; M. Jake Vander Zanden [États-Unis]

Source :

RBID : ISTEX:8DB1F46CC0042E3904165FB658C4DC685AC5E168

English descriptors

Abstract

Abstract:  Rainbow smelt (Osmerus mordax) have invaded many North American lakes, often resulting in the extirpation of native fish populations. Yet, their invasion is incipient and provides the rationale for identifying ecosystems likely to be invaded and where management and prevention efforts should be focused. To predict smelt presence and absence, we constructed a classification‐tree model based on habitat data from 354 lakes in the native range for smelt in southern Maine. Maximum lake depth, lake area, and Secchi depth (surrogate measure of lake productivity) were the most important predictors. We then used our model to identify lakes vulnerable to invasion in three regions outside the smelt's native range: northern Maine (52 of 244 lakes in the non‐native range), Ontario (4447 of 8110), and Wisconsin (553 of 5164). We further identified a subset of lakes with a strong potential for impact (potential–impact lakes) based on the presence of fish species that are affected by rainbow smelt. Ninety‐four percent of vulnerable lakes in the non‐native range in Maine are also potential–impact lakes, as are 94% and 58% of Ontario and Wisconsin's vulnerable lakes, respectively. Our modeling approach can be applied to other invaders and regions to identify invasion‐prone ecosystems, thus aiding in the management of invasive species and the efficient allocation of invasive species mitigation and prevention resources.

Url:
DOI: 10.1111/j.1523-1739.2006.00508.x


Affiliations:


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