Maintenance of long-term equilibrium in a perturbed metacommunity of sub-arctic marine fishes
Bibliographic record
Abstract
The theory of island biogeography (TIB) predicts that species richness in isolated areas is determined by the processes of colonization and extinction, and, in turn, governed by island size and isolation. Metacommunity models extend the TIB, predicting that both habitat and species interactions are important drivers of community vital rates and structure, and that marine metacommunities will exhibit higher extinction/colonization rates relative to terrestrial ecosystems. Here we demonstrate that oceanic banks can be considered islands, and document how application of these theories advanced our understanding of the dynamics of these submarine islands following the fishery-induced collapse of predatory groundfish populations. We employed a 48 yr dataset of fish communities on 10 offshore banks of the Scotian Shelf, Northwest Atlantic Ocean to examine colonization and extinction rates before and after the collapse. Bank-specific colonization, extinction and turnover rates were quantified using the island R package to correct for imperfect detectability, inherent to all sampling of natural systems. Colonization and extinction events were briefly unbalanced following the predator collapse, and reflected in increases in species richness and turnover, most notably on the largest banks. However, over the longer term, a dynamic equilibrium of colonization and extinction events prevailed on 8 of the 10 banks. This resulted in a generally time-invariant species richness, and a negative relationship between species turnover and bank area, as predicted by theory. Our study provides support for the relevance of island biogeography and metacommunity theories in guiding exploration and understanding of the mechanisms governing marine community vital rates and structure.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.000 | 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 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".