Evidence of shifts in habitat use of two snappers (Lutjanidae) in a tropical estuarine bay subjected to seasonal upwelling
Bibliographic record
Abstract
Biological and environmental conditions are drivers of fish habitat use, making it essential to understand how fish move and use specific areas to inform effective fisheries management and conservation. This study quantified the residency and habitat use patterns of the juveniles and early adults of 2 commercially exploited snappers (Lutjanidae) in Santa Elena Bay, a tropical estuarine embayment influenced by a seasonal upwelling in the north Pacific coast of Costa Rica. Using an array of 28 acoustic receivers, we monitored 14 Colorado Lutjanus colorado (28.8-48.9 cm) and 16 Pacific dog L. novemfasciatus (22.5-49.3 cm) snappers over 22 mo. Both species were detected inside the bay over 60% of the monitoring days, showing higher relative abundance in mangrove and transitional estuarine habitats. Throughout the study, a shift in habitat use was observed for both species. Individuals moved from mangrove and transitional habitats to the outer reef habitat and exhibited a decreasing occurrence probability over time, suggesting they leave the bay as they mature. Season and environmental variables, e.g. temperature, had minimal or no effect on the occurrence of the tracked snappers in the bay. However, roaming varied seasonally, increasing during upwelling periods. These results suggest that habitat connectivity facilitates gradual life stage transitions, indicating that Santa Elena Bay likely supports essential fish habitat for commercially important species, particularly for L. novemfasciatus . Results also highlight the importance of integrating knowledge of the complex interplay of biological components (e.g. developmental and intra- and interspecific interactions) and seasonal habitat dynamics into conservation and management strategies.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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 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".