Herbivory through the lens of ecological processes across Pacific coral reefs
Bibliographic record
Abstract
Abstract Coral reefs are in global decline primarily due to climate change. Herbivory is often viewed as key to maintaining coral‐dominated reefs, and herbivore management is gaining traction as a possible strategy for promoting reef resilience. The functional impact of herbivorous fishes has typically been inferred from total biomass, but robust estimates of ecological processes are needed to better inform management targets. Here, we provide a framework to calculate rates of herbivory across Pacific reefs. We synthesized available observations of foraging metrics in relation to fish body size and found considerable variation, even among closely related species. We then applied these allometric functions to survey data and calculated rates of herbivory for acanthurids and scarines, which make up the vast majority of herbivorous fish biomass in the Pacific. Estimated rates of algal consumption, area scraped, and bioerosion varied across islands, with noticeable differences that may align with the relative influence of human population density among underlying herbivore functional groups. We found no evidence of compensatory relationships among herbivore processes whereby decreasing rates in one type of herbivory is offset by increasing rates in another. We observed nonlinear, positive relationships between fish biomass and rates of herbivory. Yet, for a given biomass, the corresponding rates of herbivory varied among regions, and we observed instances where islands with the greatest biomass did not also have the highest rates of herbivory. Islands with the largest size classes of herbivores did not consistently exhibit greater rates of herbivory, and we did not find a clear, consistent pattern between the number of fish species and corresponding rates of herbivore processes. Cropping Acanthurus spp. provided the greatest proportion of algal consumption at every island, yet no single species accounted for the majority of this process, whereas we identified parrotfish species that provided >75% of scraping or bioerosion at certain islands. Our results emphasize the importance of considering the species and size composition of herbivore assemblages when estimating processes, rather than relying on total biomass alone. Lastly, we highlight gaps in foraging observations and additional work needed to further broaden our ability to quantify the ecological processes of herbivores.
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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 | 0.000 | 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 | 0.000 | 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) | 0.004 | 0.002 |
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; both teacher heads agree on what is shown here.
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".