Seasonal and Ontogenetic Variation in Depth Use by a Critically Endangered Benthic Elasmobranch and Its Implications for Spatial Management
Bibliographic record
Abstract
Seasonal and ontogenetic variations in depth use by benthic species are often concomitant with changes in their spatial distribution. This has implications for the efficacy of spatial conservation measures such as marine protected areas (MPAs). The critically endangered flapper skate (Dipturus intermedius) is the designation feature of an MPA in Scotland. This species is generally associated with deeper waters >100 m; however, little is known about its seasonal or ontogenetic variation in habitat use. This study used archival depth data from 25 immature and mature flapper skate tagged in the MPA over multiple years. Time series ranged from 3 to 772 (mean = 246) days. Generalised additive mixed models and highest density intervals were used to identify home (95%) and core (50%) highest density depth regions (HDDRs) to quantify depth use in relation to time of year and body size. Skate used a total depth range of 1–312 m, but home HDDRs typically occurred between 20 and 225 m. Core HDDRs displayed significant seasonal and ontogenetic variations. Summer core HDDRs (100–150 m) suggest high occupancy of the deep trenches in the region by skate of most size classes. There was an inverse relationship between body size and depth use and a seasonal trend of skate moving into shallow water over winter months. These results suggest that flapper skate are not solely associated with deep water, as skate, especially large females, are frequently found in shallow waters (25–75 m). The current management, which protects the entire depth range, is appropriate for the protection of flapper skate through much of its life history. This research demonstrates why collecting data across seasonal scales and multiple ontogenetic stages is needed to assess the effectiveness of spatial management.
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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 | 0.001 |
| 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".