Habitat suitability of two flagship species, Hippocampus hippocampus and Hippocampus guttulatus, in the Atlantic coast of the Iberian Peninsula - implications for conservation
Bibliographic record
Abstract
Anthropogenic pressures on marine ecosystems are increasing worldwide, causing loss of biodiversity and ecosystem functioning, and driving species towards risk of extinction. To protect vulnerable species and habitats, Marine Protected Areas (MPAs) are increasingly established worldwide as conservation measures. Seahorses act as flagship species for coastal ecosystem conservation due to their charismatic appearance and high vulnerability to habitat degradation. Here, the habitat suitability of the two European seahorse species, Hippocampus hippocampus and Hippocampus guttulatus, was assessed along the western Iberian Peninsula, using an ensemble species distribution modelling approach. Furthermore, the coverage of their core habitat (relative habitat suitability (HS) ≥ 0.5) with MPAs was estimated. The results show that the main drivers for habitat suitability were distance to the coast, aspect of the seafloor, tidal amplitude, and temperature. However, the importance differed between the two species. The suitable habitat of H. hippocampus extended to higher distances to the coast, while H. guttulatus were mostly restricted to areas in the vicinity of the coast and facing away from the open sea (i.e., the westerly aspect of the seafloor). Furthermore, temperature contributes more to the variation in habitat suitability in H. hippocampus than in H. guttulatus. The areas with the highest habitat suitability are estuarine or inlet waters and sheltered coasts in northwestern Spain, central and south of Portugal. Both species’ core habitats are covered by about 19-20% with implemented protected areas in Portugal. In comparison, there is less coverage for both species in Spain, with 12% for H. guttulatus and 6% for H. hippocampus. Besides, zones of full protection cover less than 0.5% of the core habitat while the rest of the protected areas provide only moderate to low restrictions and do not specifically address the protection of seahorses in their management plans. The results provide useful information on the distribution and the different habitat preferences of the two species, indications for further monitoring of populations, and recommendations for efficient spatial conservation areas that can protect the species and other associated vulnerable species and habitats.
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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 | 0.001 | 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".