Multiple human activities in coastal benthic ecosystems: Introducing a metric of cumulative exposure
Bibliographic record
Abstract
Co-occurring anthropogenic activities influence coastal ecosystems around the world. Notions of ecological exposure are promising indicators to better understand environmental status and enhance ecosystem protection. This study characterized anthropogenic exposure in the context of multiple human activities on coastal benthic ecosystems at a scale of <100 km. Using a particle diffusion model and fishing event data, we developed an exposure index for seven human activities (aquaculture, artificial structures, dredging, fisheries, runoff, sewers and shipping) in a Canadian industrial harbour area. A generally low cumulative exposure was obtained, with the highest values observed directly in front of the city and industrial areas. Derived exposure indices explained a portion of the benthic community structure (R2 = 0.22), suggesting an ecological link between the exposure of species and their vulnerability to human activities. Such tools are relevant in data-poor environments where proxies are required to assess the state of an ecosystem, facilitating the application of ecosystem-based management.
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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 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.004 |
| 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".