Changing community dynamics and climate alter invasion risk of freshwater fishes historically found in invasion pathways of the Laurentian Great Lakes
Bibliographic record
Abstract
Abstract Aim Here, we use an integrative, comprehensive risk assessment framework as a screening tool to evaluate how the invasion risk of previously failed introduced freshwater fish species, commonly found in the live‐trade pathway, will change under future climate‐change scenarios. Location Laurentian Great Lakes, North America. Methods The 34 species screened for invasion risk previously failed to establish populations, likely due to poor environmental suitability, low propagule pressure, and/or biotic resistance from the recipient community, and are most commonly found in the increasingly important live‐trade pathway. Using established trait‐based models, we quantified the probability of establishment success and probability of having high ecological impact in the decade of first introduction and present‐day communities (2020) based on known species extirpations, introductions and establishments between 1870 and 2020. We completed a climate match analysis under future climate‐change scenarios based on 16 bioclimatic variables. This approach identified a list of species that should be prioritized in surveillance management. Results We identified seven species that have an increased climate match with the region and an increased probability of establishment success. Five of these species have an increased probability of high ecological impacts. Twenty‐four species have a current probability of establishment success greater than 50% and 33 species have a current probability of high ecological impacts greater than 50%. Climate match was dynamic under future climate‐change scenarios with 14 species experiencing a better match between their native geographical range and the Laurentian Great Lakes region. Main conclusions Our models identify and predict the invasion risk of non‐native freshwater fish species present in pathways relevant to the Great Lakes region and provide a comprehensive framework for future management that prioritize efforts to species of highest risk. This framework could be applied to different taxa, pathways, and/or ecosystems to estimate current and predicted invasion risk under multiple scenarios.
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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 | 0.003 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.004 |
| 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".