Dietary composition of endangered seahorses determined by stable isotope analysis
Bibliographic record
Abstract
The lack of integrated measures for assessing the feeding ecology of seahorses may restrict the effectiveness of conservation actions on wild populations of worldwide threatened seahorse species. Identifying dietary sources will allow researchers to determine their degree of vulnerability to environmental changes, redefine their conservation status and apply appropriate management strategies. The resource use of the seahorse Hippocampus guttulatus inhabiting coastal waters of Galicia (north-western Iberian Peninsula) was assessed for three populations and 2 years using stable isotope mixing models. The Bayesian mixing model (MixSIAR) estimated the relative contributions of the dietary sources to the seahorse diet and revealed that Caprellidea were the primary source, followed by Gammaridea and Caridea. Mysidae and Annelida represented the less dominant prey. This prey preference can be explained by the foraging behaviour of seahorses. Different contributions of Gammaridea and Caridea to the diet were found among sites, indicating different habitat characteristics and hence different habitat use by seahorses within each site. In addition, differences were encountered among sexes. Caprellidea was the dominant prey for females, whereas Gammaridea was the dominant prey for males. The findings of the present study will contribute to the knowledge of feeding patterns of H. guttulatus, providing relevant data for conservation of this endangered species.
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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".