Upwelling Links Reproductive Success and Phenology in Tropical Brown Boobies <i>Sula leucogaster</i>
Bibliographic record
Abstract
For organisms living in seasonal environments, timing of breeding is key to ensuring reproductive success. Accordingly, temperate and polar seabird species follow seasonal pulses, matching their breeding events with peaks in ocean productivity. However, the seasonality of breeding has been much less explored in tropical seabirds. Here, we report seasonal variation in oceanography that affects reproductive success of the Brown Booby Sula leucogaster, a species widely distributed in the tropics. We monitored 61 nests during the 2019 breeding season at Bona Island, Gulf of Panama, and collected remote-sensing information for upwelling, sea-surface temperature, rainfall, chlorophyll-α concentration, wind speed, and wind direction. We used egg/chick survival probability and a sliding-window statistical approach to assess temporal changes in reproductive success. Maximum chlorophyll-α concentrations (linear and quadratic expressions) had the strongest influence over survival probability in the two to three weeks prior to the death of the egg/chick. After model averaging, we found that survival probability was positively correlated with maximum chlorophyll-α (confidence interval CI(β) = 0.19 to 2.54 mg/m3) and negatively correlated with (maximum chlorophyll-α)2 (CI(β) = −4.19 to −0.31 mg/m3). In addition, survival probability decreased with later laying dates (CI(β) = 0.43 to 1.74 days), indicating that chicks born earlier in the breeding season had higher chances of survival. Given the correlation between chlorophyll-α and upwelling, we concluded that Brown Booby reproductive success in the Gulf of Panama is influenced by upwelling and that breeding in this tropical species follows seasonal pulses like those observed in polar and temperate species.
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 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 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".