Development and application of a risk assessment tool for aquatic invasive species in the international Rainy-Lake of the Woods Basin, United States and Canada
Bibliographic record
Abstract
First posted November 7, 2023 For additional information, contact: Director, Upper Midwest Water Science CenterU.S. Geological Survey1 Gifford Pinchot DriveMadison, WI 53726Contact Pubs Warehouse The Rainy-Lake of the Woods Basin covers 70,000 square kilometers in mid-central North America and is contained within the Provinces of Ontario and Manitoba in Canada and the State of Minnesota in the United States. This basin contains natural wilderness areas, national parks, and thousands of lakes that bring outdoor enthusiasts from around the world for hunting, fishing, backpacking, boating, and other forms of recreation. However, trade, commerce, visitors, and wildlife can inadvertently transport hitchhiking exotic invasive species that affect the functioning of natural systems by displacing native organisms, introducing diseases, and modifying predator/prey relations. In cooperation with the International Joint Commission, the U.S. Geological Survey evaluated the aquatic invasive species that pose a possible threat to North America. The outcome of this project is a set of lists of invasive species that have traits amenable or proximity to the Rainy-Lake of the Woods Basin. These lists can be referenced to further evaluate known and potential nonindigenous invasive species. The lists were derived by evaluating more than 1,500 species from several online sources including Non-Indigenous Aquatic Species, Great Lakes Aquatic Nonindigenous Species Information System, Biodiversity Information Serving Our Nation, and other State, Provincial, and Federal lists in the United States and Canada. The purpose of these lists is to be a coarse filter to determine which species pose the greatest risk to the Rainy-Lake of the Woods Basin. Using this filter, seven categories of risk assessment priorities were developed: Very High-Approaching, Very High-Present, High-Approaching, High-Present, Moderate, Low, and Native. These categories can be used by the International Rainy-Lake of the Woods Multi-Agency Arrangement Aquatic Invasive Species Subcommittee to prioritize which species will be evaluated further focusing on five risk factors: arrival risk, vulnerability assessment, ecological impact, socioeconomic impact, and beneficial impact. Based on proximity, ease of transport or introduction, and known impact to Rainy-Lake of the Woods or other impacted ecosystems, this project identified the following 10 species that could be prioritized first for risk evaluations: Bythotrephes longimanus (spiny waterflea), Faxonius rusticus (rusty crayfish), Neogobius melanostomus (round goby), Dreissena polymorpha (zebra mussel), Bithynia tentaculata (mud Bithynia or faucet snail), Potamopyrgus antipodarum (New Zealand mud snail), Butomus umbellatus (flowering rush), Nitellopsis obtusa (starry stonewort), Myriophyllum spicatum (Eurasian watermilfoil), and Phragmites australis australis (common reed).
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".