The many pathways of climate change affecting coastal ecosystems: a case study of western Vancouver Island, Canada
Bibliographic record
Abstract
Climate change threatens marine ecosystems with known effects on marine life, including changes in metabolic rates, survival, and community structure. Based on a structured literature review, we developed a conceptual “pathways of effects” model that summarizes how three stressors associated with climate change (warming, acidification, and storms) affect functional species groups on the West Coast of Vancouver Island, Canada. We identified 155 distinct pathways from the three stressors through 12 categories of biological effects ranging from changes in the biochemistry of individual organisms to effects on community composition. Most species groups were affected by several climate stressors and via many pathways, although individual studies generally considered only a small fraction of relevant pathways. These effects depended on the species of interest and geographical location, highlighting the importance of local research. Climate change stressors exert complex, sometimes contradictory effects that vary across ecological scales. For example, some stressors that adversely affected a species in laboratory studies appeared beneficial in community-scale field studies. Pathways of effects models are helpful tools to summarize scientific studies across ecological scales. Compiling them in standardized databases would allow researchers and practitioners to search across species and regions to better support ecosystem-based management and environmental impact assessment.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.007 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".