The role of a dominant predator in shaping biodiversity over space and time in a marine ecosystem
Bibliographic record
Abstract
1. Exploitation of living marine resources has resulted in major changes to populations of targeted species and functional groups of large-bodied species in the ocean. However, the effects of overfishing and collapse of large top predators on the broad-scale biodiversity of oceanic ecosystems remain largely unexplored. 2. Populations of the Atlantic cod (Gadus morhua) were overfished and several collapsed in the early 1990s across Atlantic Canada, providing a unique opportunity to study potential ecosystem-level effects of the reduction of a dominant predator on fish biodiversity, and to identify how such effects might interact with other environmental factors, such as changes in climate, over time. 3. We combined causal modelling with model selection and multimodel inference to analyse 41 years of fishery-independent survey data (1970-2010) and quantify ecosystem-level effects of overfishing and climate variation on the biodiversity of fishes across a broad area (172 000 km(2) ) of the Scotian Shelf. 4. We found that alpha and beta diversity increased with decreases in cod occurrence; fish communities were less homogeneous and more variable in systems where cod no longer dominated. These effects were most pronounced in the colder north-eastern parts of the Scotian Shelf. 5. Our results provide strong evidence that intensive harvesting (and collapse) of marine apex predators can have large impacts on biodiversity, with far-reaching consequences for ecological stability across an entire ecosystem.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".