Rating impacts in a multi‐stressor world: a quantitative assessment of 50 stressors affecting the Great Lakes
Bibliographic record
Abstract
Ecosystems often experience multiple environmental stressors simultaneously that can differ widely in their pathways and strengths of impact. Differences in the relative impact of environmental stressors can guide restoration and management prioritization, but few studies have empirically assessed a comprehensive suite of stressors acting on a given ecosystem. To fill this gap in the Laurentian Great Lakes, where considerable restoration investments are currently underway, we used expert elicitation via a detailed online survey to develop ratings of the relative impacts of 50 potential stressors. Highlighting the multiplicity of stressors in this system, experts assessed all 50 stressors as having some impact on ecosystem condition, but ratings differed greatly among stressors. Individual stressors related to invasive and nuisance species (e.g., dreissenid mussels and ballast invasion risk) and climate change were assessed as having the greatest potential impacts. These results mark a shift away from the longstanding emphasis on nonpoint phosphorus and persistent bioaccumulative toxic substances in the Great Lakes. Differences in impact ratings among lakes and ecosystem zones were weak, and experts exhibited surprisingly high levels of agreement on the relative impacts of most stressors. Our results provide a basin-wide, quantitative summary of expert opinion on the present-day influence of all major Great Lakes stressors. The resulting ratings can facilitate prioritizing stressors to achieve management objectives in a given location, as well as providing a baseline for future stressor impact assessments in the Great Lakes and elsewhere.
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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 | 0.001 | 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 | 0.000 | 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) | 0.003 | 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".