Characterizing and predicting essential habitat features for juvenile coastal sharks
Bibliographic record
Abstract
Abstract The successful management of shark populations requires juvenile recruitment success. Thus, conservation initiatives now strive to include the protection of areas used by pre‐adult sharks in order to promote juvenile survivorship. Many shark species use inshore areas for early life stages; however, species often segregate within sites to reduce competition. Using a fisheries‐independent gillnet survey from the Northern Gulf of Mexico (2000–2010) we describe distribution patterns and preferred habitat features of the juveniles of six shark species. Our results suggest that multiple shark species concurrently use the area for early life stages and although they overlap, they exhibit distinct habitat preferences characterized by physical variables. Habitat suitability models suggest that temperature, depth, and salinity are the important factors driving juvenile shark occurrence. Within each site, across the sampled range of physical characteristics, blacktip shark (Carcharhinus limbatus) preferred higher temperature (>30 °C) and mid‐depth (~5.5 m); bonnethead shark (Sphyrna tiburo) preferred higher temperature (>30 °C) and mid‐salinity (30–35 PSU), finetooth shark (Carcharhinus isodon) preferred low salinity (<20 PSU) with mid‐depth (~4 m), scalloped hammerhead shark (Sphyrna lewini) preferred high temperature (>30 °C) and salinity (>35 PSU), Atlantic sharpnose shark (Rhizoprionodon terraenovae) preferred high temperature (>30 °C) and deep water (>6 m), and spinner shark (Carcharhinus brevipinna) preferred deep water (>8 m) and high temperature (>30 °C). The other investigated factors, including year, month, latitude, longitude, bottom type, inlet distance, coastline and human coast were not influential for any species. Combining habitat preferences with the sampled environmental characteristics, we predicted habitat suitability throughout the four sites for which physical characteristics were sampled. Habitat suitability surfaces highlight the differences in habitat use between and within sites. This work provides important insight into the habitat ecology of juvenile shark populations, which can be used to better manage these species and protect critical habitat.
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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 | 0.000 |
| 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) | 0.001 | 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".