Estimating potential global sources and secondary spread of freshwater invasions under historical and future climates
Bibliographic record
Abstract
Abstract Aim We employed a climate‐matching method to evaluate potential source regions of freshwater invasive species to an introduced region and their potential secondary spread under historical and future climates. Location Global source regions, with primary introductions to the Laurentian Great Lakes and secondary introductions throughout North America. Methods We conducted a climate‐match analysis using the CLIMATE algorithm to estimate global source freshwater ecoregions under historical and future climates with an ensemble of global climate models for climate‐change scenario SSP5‐8.5. Given existing research, we use a climate match of ≥71.7% between ecoregions to indicate climatic conditions that will not inhibit the survival of introduced freshwater organisms. Further, we estimate the secondary spread of freshwater invaders to the ecoregions of North America under historical and future climates. Results We identified 54 global freshwater ecoregions with a climate match ≥71.7% to the recipient Laurentian Great Lakes under historical climatic conditions, and 11 additional ecoregions were predicted to exceed the threshold under climate change. Three of the 11 ecoregions were located in South America, a continent where no matches existed under historical climates and eight were located in the southern United States, southern Europe, Japan and New Zealand. Further, we identify 34 North American ecoregions of potential secondary spread of freshwater invasions from the Great Lakes under historical climatic conditions, and five ecoregions were predicted to exceed the threshold under climate change. Main Conclusion We provide a climate‐match method that can be employed to assess the sources and spread of freshwater invasions under historical and future climate scenarios. Our climate‐match method predicted increases in climate match between the recipient region and several potential source regions, and changes in areas of potential spread under climate change. The identified ecoregions are candidates for detailed biosecurity risk assessments and related management actions.
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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 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".