MAISRC Research Data
Persistent link for this collectionhttps://hdl.handle.net/11299/197775
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Browsing MAISRC Research Data by Subject "aquatic invasive species"
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Item Complete data for Overwinter survival of Corbicula fluminea in a central Minnesota lake(2021-11-01) Weber, Megan M; Cibulka, Daniel; mmweber@umn.edu; Weber, Megan M; Minnesota Aquatic Invasive Species Research Center (MAISRC)Corbicula fluminea is regarded as one of the most pervasive freshwater aquatic invasive species in the world. It has been widely cited to have a lower lethal temperature threshold of 2 degrees Celcius, which suggests the species would be unable to survive in Minnesota outside of areas of thermal refuge from sources such as power plant, water treatment facility, and other raw water user effluent). In August 2020 a volunteer participating in Starry Trek, an aquatic invasive species early detection event, recovered live C. fluminea from an inland Minnesota lake with no known thermal refuge (Briggs Lake, Sherburne County). This data set documents the distribution, overwinter survival, and size class structure of the population in Briggs Lake and observational data at a nearby lake (Big Lake, Sherburne County) where additional clams were discovered by a volunteer towards the end of the Briggs Lake project timeline. The data from this study are available here for public use.Item Data in support of Quantifying the effectiveness of three aquatic invasive species prevention methods(2023-05-04) Angell, Nichole R; Campbell, Tim; Brady, Valerie; Bajcz, Alex; Kinsley, Amy; Doll, Adam; Dumke, Josh; Keller, Reuben; Phelps, Nicholas BD; nangell@glc.org; Angell, Nichole R; Minnesota Aquatic Invasive Species Research Center (MAISRC)Efforts to prevent the spread of aquatic invasive species (AIS) have been widely implemented at many scales to mitigate economic and environmental harms. Boater education, watercraft inspection, and hot water decontamination are popular strategies for prevention of AIS moving through the recreational boating pathway. However, few studies have actually quantified the effectiveness of these strategies under field conditions. We estimated their effectiveness based on the performances of boaters, watercraft inspectors, and hot water decontaminators. Participants (n=144) were recruited at 56 public water access sites in Minnesota and 1 in Wisconsin. Each participant was asked to inspect and remove AIS from a boat staged with macrophytes, dead zebra mussels, and spiny water fleas. The types and amounts of AIS removed were used to estimate the effectiveness of each prevention method. We observed that removal varied by type of AIS, with macrophytes being most commonly removed for all participants. There were also regional (metro and outstate) differences for some species perhaps due to awareness and education. Hot water decontamination was the most effective (83.7%) intervention but was not significantly better at reducing risk of spread than was watercraft inspection (79.2%). Boaters were less effective at AIS removal (56.4%). Our results suggest that watercraft inspection is an effective prevention method for most boats, and that hot water decontamination is an important tool for high-risk boats. However, robust decontamination protocols are difficult to effectively execute. Furthermore, our results provide insights into how to increase boater awareness of often-overlooked locations and help reduce risk when inspectors cannot be present at a public water access site.Item Data in Support of Widespread declines in walleye recruitment following zebra mussel invasion in Minnesota lakes(2023-04-26) Kundel, H; Hansen, Gretchen J A; kunde058@umn.edu; Kundel, H; University of Minnesota Dr. Hansen Research TeamInvasive zebra mussels (Dreissena polymorpha) alter lake ecosystems and can negatively affect first-year growth of walleye (Sander vitreus), potentially lowering walleye overwinter survival and recruitment success. Zebra mussel effects also vary among lakes, and walleye resilience to the effects of zebra mussels may vary depending on lake characteristics (e.g., depth, clarity) or fish community composition. To test these hypotheses, we used data from 1,438 surveys across 348 lakes collected between 1993 and 2019 to measure walleye recruitment, defined as relative abundance of age-0 walleye in their first fall. We fitted Bayesian hierarchical models to quantify the effects of zebra mussels on walleye recruitment while accounting for the effects of lake temperature, surface area, and water clarity. A before-after-control-impact (BACI)-like design was used to account for potential changes in recruitment due to factors other than zebra mussel invasion. Age-0 walleye recruitment to their first fall was ~41% lower (95% credible interval of 38 - 44%) in lakes containing zebra mussels compared to uninvaded lakes. Invaded lakes had higher recruitment prior to zebra mussel invasion than lakes that remain uninvaded. Conversely, walleye recruitment increased slightly (7% (95% credible interval 2 - 11%)) in lakes without zebra mussels over the same time period. Walleye recruitment was higher in larger lakes and lakes with lower water clarity. Water temperature, as indexed by degree days (base 5 °C), did not affect walleye recruitment. Our results demonstrate negative effects of zebra mussel invasion on walleye population dynamics at a landscape scale.Item Data supporting: Evaluation of a decade of management of a North American aquatic invasive species (Nitellopsis obtusa) highlights scale-dependent effectiveness and monitoring gaps(2024-11-25) Glisson, Wesley; Nault, Michelle; Jurek, Chris; Fischer, Eric; Lund, Keegan; Bloodsworth Cattoor, Kylie; Londo, April; Hauck-Jacobs, Emelia; Egdell, Rod; McComas, Steve; Fieldseth, Eric; Larkin, Daniel; djlarkin@umn.edu; Larkin, Daniel; Minnesota Aquatic Invasive Species Research Center (MAISRC); Department of Fisheries, Wildlife and Conservation BiologyNitellopsis obtusa (starry stonewort) is an invasive macroalga subject to substantial control efforts in the Midwestern United States; however, there has not been systematic evaluation of treatment effectiveness. We synthesized management approaches and outcomes using monitoring performed over a decade-long period across 38 lakes in Indiana, Wisconsin, and Minnesota. We compiled all available point-intercept (PI) survey data from lakes where N. obtusa was known to occur since the year the species was first discovered in each state (Indiana, 2008; Wisconsin, 2014; Minnesota, 2015) until 2018 (Indiana) and 2019 (Wisconsin and Minnesota). These data comprised raw survey and summary data from whole-lake PI surveys, as well as targeted sub-PI surveys within managed areas. We compiled all available information on N. obtusa management for the time periods encompassing the survey data. Management data were collected from: 1) pesticide application records (PARs; Minnesota), 2) chemical treatment and mechanical harvesting records (Wisconsin), 3) aquatic vegetation management plans (AVMPs; Indiana), and 4) direct knowledge of known management events (all states). We compiled as much information as possible for each management action on each lake. For hand pulling, we additionally compiled all available data on the biomass of N. obtusa removed during each event; we included all such data through 2022.Item Network connectivity patterns of Minnesota waterbodies and implications for aquatic invasive species prevention(2020-10-28) Kao, Szu-Yu; Enns, Eva A; Tomamichel, Megan; Doll, Adam; Escobar, Luis E; Qiao, Huijie; Craft, Meggan E; Phelps, Nicholas B. D.; phelp083@umn.edu; Phelps, Nicholas B D; Minnesota Aquatic Invasive Species Research Center (MAISRC); Division of Health Policy and Management, School of Public Health, University of Minnesota; Odum School of Ecology, University of Georgia; Department of Fish and Wildlife Conservation, Virginia Polytechnic Institute and State University; Key Laboratory of Animal Ecology and Conservation Biology, Chinese Academy of Sciences; Department of Veterinary Population Medicine, College of Veterinary Medicine, University of MinnesotaThe data contains simulated boater movements across lakes in the state of Minnesota (MN). The data were simulated based on the boater inspection program conducted by the Minnesota Department of Natural Resources in 2014-2017. Using the inspection survey, we employed machine learning technique, XGBoost, to construct three predictive boater movement models. First, we predicted the number of boater traffic on a lake for a year. Second, we predicted the boater connection between any pair of lakes in MN. Third, we predicted the number of boaters between two lakes that were predicted to have connection.Item R Code and Data Supporting: A comparison of survey method efficiency for estimating densities of Zebra Mussels (Dreissena polymorpha)(2023-05-25) Ferguson, Jake M; Jimenez, Laura; Keyes, Aislyn A; Hilding, Austen; McCartney, Michael A; St. Clair, Katie; Johnson, Douglas H; Fieberg, John R; jfieberg@umn.edu; Fieberg, John RThis repository contains data and R code supporting Ferguson et al. A comparison of survey method efficiency for estimating densities of Zebra Mussels (Dreissena polymorpha).Item R Code, Data, and Output Supporting: Facilitating effective collaboration to prevent aquatic invasive species spread(2023-09-05) Bajcz, Alex, W.; Kinsley, Amy; Haight, Robert; Phelps, Nicholas B. D.; bajcz003@umn.edu; Bajcz, Alex W.; Minnesota Aquatic Invasive Species Research Center (MAISRC); Veterinary Population Medicine, College of Veterinary Medicine; USDA Forest Service, Northern Research Station; Department of Fisheries, Wildlife, and Conservation BiologyThis repository contains R code, raw and processed data, and associated outputs supporting the results reported in: Kinsley, A, Bajcz A, Haight R, and Phelps N. 2023. Facilitating effective collaboration to prevent aquatic invasive species spread. Biological Invasions [in press]. In brief, this repository provides the inputs, code, and documentation for our process of generating optimization models, using linear integer programming (LIP) in R, that would find optimal placement patterns for watercraft inspection stations to thwart the movement of boats at risk of carrying aquatic invasive species from one lake to another within the state of Minnesota, given certain assumptions about how jurisdictional authority operates within the state.Item R Code, Data, and Output Supporting: A within-lake occupancy model for starry stonewort, Nitellopsis obtusa, to support early detection and monitoring(2022-12-19) Bajcz, Alex W; Glisson, Wesley; Larkin, Daniel J; Fieberg, John; bajcz003@umn.edu; Bajcz, Alex W; Minnesota Aquatic Invasive Species Research Center (MAISRC); Department of Fisheries, Wildlife, and Conservation BiologyThese data and files support the published paper "A within-lake occupancy model for starry stonewort, Nitellopsis obtusa, to support early detection and monitoring" | Scientific Reports (nature.com). It contains both input files and data as well as processed output files from the modeling effort described in the paper, which uses predictor variables to predict both occupancy and detection for within-lake locations by starry stonewort, an invasive aquatic macrophyte. The files being submitted include everything needed to fully replicate and further interpret our results and provide a framework for constructing similar models in similar contexts.Item Recreationist willingness to pay for aquatic invasive species management at four Minnesota lakes(2021-02-12) Levers, Lucia; Pradhananga, Amit; llevers@umn.edu; Levers, Lucia; Minnesota Aquatic Invasive Species Research Center (MAISRC)Willingness to pay data from surveys conducted with recreationists (primarily boaters) at four Minnesota Lakes (Minnewaska, Koronis, Gull, and Pokegama) in the summer of 2019.