Monitoring of Seahorse Populations, in the Ria Formosa Lagoon (Portugal), Reveals Steep Fluctuations: Potential Causes and Future Mitigations
Bibliographic record
Abstract
Abstract After seahorse population fluctuations were revealed in previous studies, probably due to changes in their natural habitat, this study sought to determine the current status of the populations of the two existing seahorse species in the Ria Formosa lagoon, by revisiting previously surveyed sites, while assessing the main drivers for detected changes. Hippocampus guttulatus densities decreased significantly between 2002 and 2008, followed by a significant increase between 2008 and 2012 and a significant decrease between 2012 and 2018. There were no significant differences in H. guttulatus populations between the 2002 and 2012 surveys, and between 2008 and 2018. As for Hippocampus hippocampus , there were no significant differences comparing densities from all the different dates. Among the different variables tested in this study, holdfast coverage seems to have played a crucial role in seahorse decline. It is important to further assess the impact on seahorse populations of two recently reported events, the illegal fishing of seahorses and the expansion of Caulerpa prolifera algae in the Ria Formosa lagoon, South Portugal. Considering the existent threats and the probable causes behind the recent seahorse abundance decline, seahorses’ low densities make them even more susceptible to local extirpation due to continuous threats, which emphasizes the dire urgency to put in place mitigative actions to contribute to the conservation of these iconic species.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".