Inbound arrivals: using weather surveillance radar to quantify the diurnal timing of spring trans‐Gulf bird migration
Bibliographic record
Abstract
More than two billion birds migrate through the Gulf of Mexico each spring en route to breeding grounds in the USA and Canada. This region has a long history of complex natural and anthropogenic environments as the northern Gulf coast provides the first possible stopover habitats for migrants making nonstop trans‐Gulf crossings during spring migration. However, intense anthropogenic activity in the region, which is expanding rapidly at present, makes migrants vulnerable to a multitude of obstacles and increasingly fragments and alters these habitats. Understanding the timing of migrants' overwater arrivals has biological value for expanding our understanding of migration ecology relative to decision‐making for nonstop flights, and is imperative for advancing conservation of this critical region through the identification of key times in which to direct conservation actions (e.g. temporary halting of wind turbines, reduction of light pollution). We explored 10 years of weather surveillance radar data from five sites along the northern Gulf of Mexico coast to quantify the daily timing and intensity of arriving trans‐Gulf migrants. On a daily scale, we found that migrant intensity peaked an average of nine hours after local sunrise, occurring earliest at easternmost sites. On a seasonal level, the greatest number of arrivals occurred between late April and early May, with peak intensity occurring latest at westernmost sites. Overall intensity of migration across all 10 years of data was greatest at the westernmost sites and decreased moving farther to the east. These findings emphasize the differential spatial and temporal patterns of use of the Gulf of Mexico region by migrating birds, information that is essential for improving our understanding of the ecology of trans‐Gulf migration and for supporting data‐driven approaches to conservation actions for the migratory birds passing through this critical region.
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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 | 0.001 |
| 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".