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Forecasting distributions of an aquatic invasive species (Nitellopsis obtusa) under future climate scenarios.
Romero-Alvarez, Daniel; Escobar, Luis E; Varela, Sara; Larkin, Daniel J; Phelps, Nicholas B D.
Affiliation
  • Romero-Alvarez D; Hospital General Enrique Garcés, Unidad de Epidemiología, Quito, Ecuador.
  • Escobar LE; Minnesota Aquatic Invasive Species Research Center, Department of Fisheries, Wildlife, and Conservation Biology, University of Minnesota, St. Paul, MN, United States of America.
  • Varela S; Museum für Naturkunde, Leibniz Institute for Evolution and Biodiversity Science, Invalidenstraße 43, Berlin, Germany.
  • Larkin DJ; Minnesota Aquatic Invasive Species Research Center, Department of Fisheries, Wildlife, and Conservation Biology, University of Minnesota, St. Paul, MN, United States of America.
  • Phelps NBD; Minnesota Aquatic Invasive Species Research Center, Department of Fisheries, Wildlife, and Conservation Biology, University of Minnesota, St. Paul, MN, United States of America.
PLoS One ; 12(7): e0180930, 2017.
Article in En | MEDLINE | ID: mdl-28704433
ABSTRACT
Starry stonewort (Nitellopsis obtusa) is an alga that has emerged as an aquatic invasive species of concern in the United States. Where established, starry stonewort can interfere with recreational uses of water bodies and potentially have ecological impacts. Incipient invasion of starry stonewort in Minnesota provides an opportunity to predict future expansion in order to target early detection and strategic management. We used ecological niche models to identify suitable areas for starry stonewort in Minnesota based on global occurrence records and present-day and future climate conditions. We assessed sensitivity of forecasts to different parameters, using four emission scenarios (i.e., RCP 2.6, RCP 4.5, RCP 6, and RCP 8.5) from five future climate models (i.e., CCSM, GISS, IPSL, MIROC, and MRI). From our niche model analyses, we found that (i) occurrences from the entire range, instead of occurrences restricted to the invaded range, provide more informed models; (ii) default settings in Maxent did not provide the best model; (iii) the model calibration area and its background samples impact model performance; (iv) model projections to future climate conditions should be restricted to analogous environments; and (v) forecasts in future climate conditions should include different future climate models and model calibration areas to better capture uncertainty in forecasts. Under present climate, the most suitable areas for starry stonewort are predicted to be found in central and southeastern Minnesota. In the future, suitable areas for starry stonewort are predicted to shift in geographic range under some future climate models and to shrink under others, with most permutations indicating a net decrease of the species' suitable range. Our suitability maps can serve to design short-term plans for surveillance and education, while future climate models suggest a plausible reduction of starry stonewort spread in the long-term if the trends in climate warming remain.
Subject(s)

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Characeae Type of study: Prognostic_studies / Screening_studies Country/Region as subject: America do norte Language: En Journal: PLoS One Journal subject: CIENCIA / MEDICINA Year: 2017 Document type: Article Affiliation country: Ecuador

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Characeae Type of study: Prognostic_studies / Screening_studies Country/Region as subject: America do norte Language: En Journal: PLoS One Journal subject: CIENCIA / MEDICINA Year: 2017 Document type: Article Affiliation country: Ecuador