Network connectivity of Minnesota waterbodies and implications for aquatic invasive species prevention

被引:0
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作者
Szu-Yu Zoe Kao
Eva A. Enns
Megan Tomamichel
Adam Doll
Luis E. Escobar
Huijie Qiao
Meggan E. Craft
Nicholas B. D. Phelps
机构
[1] University of Minnesota,Division of Health Policy and Management, School of Public Health
[2] University of Georgia − Athens,Odum School of Ecology
[3] University of Minnesota,Minnesota Aquatic Invasive Species Research Center
[4] Minnesota Department of Natural Resources,Department of Fish and Wildlife Conservation
[5] Virginia Polytechnic Institute and State University,Key Laboratory of Animal Ecology and Conservation Biology
[6] Chinese Academy of Sciences,Department of Veterinary Population Medicine, College of Veterinary Medicine and Department of Ecology, Evolution and Behavior, College of Biological Sciences
[7] University of Minnesota,Department of Fisheries, Wildlife and Conservation Biology, College of Food, Agriculture and Natural Resource Sciences
[8] University of Minnesota,undefined
来源
Biological Invasions | 2021年 / 23卷
关键词
Aquatic invasive species; Boater movements; Network analysis; Network features; Machine learning;
D O I
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中图分类号
学科分类号
摘要
Connectivity between waterbodies influences the risk of aquatic invasive species (AIS) invasion. Understanding and characterizing the connectivity between waterbodies through high-risk pathways, such as recreational boats, is essential to develop economical and effective prevention intervention to control the spread of AIS. Fortunately, state and local watercraft inspection programs are collecting significant data that can be used to quantify boater connectivity. We created a series of predictive models to capture the patterns of boater movements across all lakes in Minnesota, USA. Informed by more than 1.3 million watercraft inspection surveys from 2014–2017, we simulated boater movements connecting 9182 lakes with a high degree of accuracy. Our predictive model accurately predicted 97.36% of the lake pairs known to be connected and predicted 91.01% of the lake pairs known not to be connected. Lakes with high degree and betweenness centrality were more likely to be infested with an AIS than lakes with low degree (p < 0.001) and centrality (p < 0.001). On average, infested lakes were connected to 1200 more lakes than uninfested lakes. In addition, boaters that visited infested lakes were more likely to visit other lakes, increasing the risk of AIS spread to uninfested lakes. The use of the simulated boater networks can be helpful for determining the risk of AIS invasion for each lake and for developing management tools to assist decision makers to develop intervention strategies.
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页码:3231 / 3242
页数:11
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