Aftereffects of Hurricanes Irma and Ian on queen conch Aliger gigas in the Florida Keys, USA
Bibliographic record
Abstract
Hurricanes can have substantial impacts on shallow-water marine habitats and species. Populations of slow-moving benthic species that are subject to depensation such as the queen conch Aliger gigas may be particularly vulnerable to hurricanes. The species is protected in Florida (USA), which allowed us to investigate the effects of Hurricanes Irma (2017) and Ian (2022) on the population without the confounding effects of fishing. Adult queen conch density had declined over 80% at sites resurveyed immediately after the passage of Hurricane Irma. Additionally, the sites closest to the eye of Hurricane Irma had a significant increase in the percent cover of sand. The sand mobilized by the storm likely buried numerous conch and caused mortality. Subsequent Florida Keys-wide annual monitoring did not show any substantial recovery in adult density prior to Hurricane Ian. Adult density had declined by ~45% at sites resurveyed after Hurricane Ian. Unlike after Irma, we did not detect any significant correlation in the change to the percent cover of sand with distance from Ian. This was probably because the eye of Hurricane Ian was farther away from the main portion of the Keys than that of Hurricane Irma. Nevertheless, after both hurricanes, adult density dropped below the minimum threshold for mating in the Keys, demonstrating the depensatory implications of hurricanes for conch populations. Consequently, fishery managers must consider the synergistic effects of hurricanes and harvest on exploited populations, especially since the intensity, longevity, and frequency of hurricanes are expected to increase due to climate change.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".