Modeling of suitable habitats for starry stonewort (Nitellopsis obtusa) in inland lakes in the Midwest and northeast USA

BIOLOGICAL INVASIONS(2023)

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摘要
Nitellopsis obtusa was first documented in the St. Lawrence River in 1974 and likely spread via human-assisted activity to at-least seven states in the U.S.A. This invasive macroalga is a nuisance for native plants, animals, and recreational activities. Because eradication of invasive species is more difficult after establishment, early detection plans are an important tool in preventing and slowing their spread. Macro-scale data analyses have improved our ability to predict changes in freshwater ecosystems and are important to assess and control invasive species. We developed species distribution models (random forest, boosted regression trees, and Maxent) using presence records of N. obtusa coupled with publicly available in-lake temperature and chemistry (bicarbonate and chloride) model data and landscape scale lake watershed characteristics for over 48,000 individual lakes in the Midwest and northeast U.S.A. January and July-August-September growing degrees days, bicarbonate concentrations, and chloride concentrations correlate with high relative likelihood of occurrence. Our analyses found N. obtusa likelihood of occurrence is high in developed, lake-dense regions with similar to 2000 July-August-September growing degree days, 1-3 mMol bicarbonate, and > 10 mg L-1 chloride. Based on relative likelihood of occurrence predictions, N. obtusa has the potential to spread to new lakes within Midwest and northeast USA states that currently do not have known populations of N. obtusa, including inland lakes in Illinois, Iowa, Ohio, and Pennsylvania.
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关键词
Invasive aquatic species, Species distribution modeling, Random forest, Boosted regression trees, Maxent
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