MODELING FISH BIOMASS STRUCTURE AT NEAR PRISTINE CORAL REEFS AND DEGRADATION BY FISHING
Bibliographic record
Abstract
Inverted biomass pyramids (IBPs) seem to be extremely rare in natural communities. Until recently, the only examples have been in freshwater and marine planktonic communities. In 2002 and 2008, investigators documented inverted biomass pyramids for nearly pristine coral reef ecosystems within the NW Hawaiian islands and the Line Islands, where apex predator abundance comprises up to 85% of the fish biomass. Large predator:prey biomass ratio seems to be a signature of nearly pristine coral reefs. While the mechanism responsible for the IBP for homogeneously mixed planktonic communities seems to be well understood, this mechanism is not strictly applicable to nearly pristine coral reefs where much of the prey use coral as refuge and are inaccessible to the predators. We construct a mathematical model with an explicit refuge to illustrate a new biologically plausible mechanism that can explain stable IBPs in nearly pristine coral reefs. New modeling components include a refuge of explicit size, a refuge size dependent functional response, and refuge size dependent prey growth rate. Utilizing realistic life history parameters of coral reef fishes, our model exhibits a stable inverted biomass pyramid. We prove that all fishing decreases the biomass ratio and sufficiently strong fishing transforms the inverted biomass pyramid to be bottom heavy. Finally we use our model to test the conjecture that pristine coral reefs will rebound faster from environmental shocks and find that it is not always true.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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 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".