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ICES Journal of Marine Science: Journal du Conseil Advance Access originally published online on February 28, 2008
ICES Journal of Marine Science: Journal du Conseil 2008 65(5):742-745; doi:10.1093/icesjms/fsn021
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© 2008 International Council for the Exploration of the Sea. Published by Oxford Journals. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org

Predictions for an invaded world: a strategy to predict the distribution of native and non-indigenous species at multiple scales

Deborah A. Reusser1 and Henry Lee, II2

1 US Geological Survey, Western Fisheries Research Center, Oregon State University, 2111 NE Marine Science Drive, Newport, OR 97365, USA
2 US EPA, ORD, NHEERL, Western Ecology Division, 2111 NE Marine Science Drive, Newport, OR 97365, USA

Correspondence to D. A. Reusser: tel: +1 541 8674045; fax: +1 541 8674049; e-mail: dreusser{at}usgs.gov

Reusser, D. A., and Lee II, H. 2008. Predictions for an invaded world: a strategy to predict the distribution of native and non-indigenous species at multiple scales. – ICES Journal of Marine Science, 65: 742–745.

Habitat models can be used to predict the distributions of marine and estuarine non-indigenous species (NIS) over several spatial scales. At an estuary scale, our goal is to predict the estuaries most likely to be invaded, but at a habitat scale, the goal is to predict the specific locations within an estuary that are most vulnerable to invasion. As an initial step in evaluating several habitat models, model performance for a suite of benthic species with reasonably well-known distributions on the Pacific coast of the US needs to be compared. We discuss the utility of non-parametric multiplicative regression (NPMR) for predicting habitat- and estuary-scale distributions of native and NIS. NPMR incorporates interactions among variables, allows qualitative and categorical variables, and utilizes data on absence as well as presence. Preliminary results indicate that NPMR generally performs well at both spatial scales and that distributions of NIS are predicted as well as those of native species. For most species, latitude was the single best predictor, although similar model performance could be obtained at both spatial scales with combinations of other habitat variables. Errors of commission were more frequent at a habitat scale, with omission and commission errors approximately equal at an estuary scale.

Keywords: ecological niche modelling, geographic scale, habitat modelling, non-indigenous species, non-parametric multiplicative regression, Northeast Pacific

Received 14 June 2007; accepted 21 January 2008; advance access publication 28 February 2008.


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