Linking fishing pressure with ecosystem thresholds and food web stability on coral reefs
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Managing fisheries for ecosystem resilience is essential, but practical guidance is limited by food‐web complexity. Processes, mechanisms, and thresholds associated with ecosystem overfishing were investigated by combining traditional concepts in fisheries biology with recent advances in food‐web modeling. Diverse coral‐reef food webs were simplified by grouping species into guilds based on the way they capture, store, and transfer energy, rather than taxonomically, as is traditionally done. Biomass fluxes between the guilds were then quantified using an allometric trophic model. The model was calibrated by linking parameters describing growth, predation, and competition with known body size and metabolic constraints, and then adjusting the base rate of parameters to match fish biomass estimates from a “pristine” coral reef system. The calibrated model was then tested by replacing equilibrium fish biomasses with observations from fished systems across the Pacific, spanning nine islands and numerous major‐reef habitats. Encouraging relationships were found between predicted algal accumulation and field observations, and between modelled and observed guild restructuring. In terms of food‐web ecology, “pristine” food webs were characterized by asynchronous population dynamics between the guilds (i.e., offsetting fluctuations), which maximized their persistence and the net accumulation of biomass within food webs. Beneficial, offsetting fluctuations were driven by the contrasting roles of density dependence, apparent competition, and predation. Fishing for predators synchronized the population fluctuations between the guilds, resulting in larger amplitudes (i.e., highs and lows), and a growing dominance of small herbivores. Continued fishing for large herbivores eventually led to an inflection point where algal biomass accumulated exponentially, revealing an ecosystem‐based fisheries benchmark. Management targets that maximized fisheries yields while controlling for algal accumulation required simultaneous exploitation across the guilds; a significant challenge because maximum yields of predators, large herbivores, and small herbivores were magnitudes of order apart. This strategy also represented a departure from modern commercial fisheries policies that place catch quotas on entire fish families taxonomically, committing systems to smaller fish, higher biomass turnover, and undesirable algal accumulation. Moving forward, the model provided a flexible and adaptable framework to consider economic and ecosystem objectives of fisheries simultaneously, ultimately balancing resilient food webs against higher fisheries productivity.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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 it