Rapid shifts in migration routes and breeding latitude in North American bluebirds
Bibliographic record
Abstract
Abstract Spatial and temporal shifts in the migratory patterns of birds have become more frequent as climate change and habitat alteration continue to impact ecosystems and the species dependent on them. In this study, we used eBird community science data collected over ten years to examine potential changes in the migratory patterns of three North American bluebird species: eastern ( Sialia sialis ), western ( Sialia mexicana ), and mountain ( Sialia currucoides ) bluebirds. Community science datasets such as those provided through eBird are a valuable tool for examining population‐level processes, as such data are often costly and time‐consuming to collect through other approaches (e.g., directly tracking individuals). Using generalized additive models, we produced smoothed migration paths for all three species over each season from 2009 to 2018. We asked whether there were changes over this 10‐year period in the timing of spring and fall migration and migration speed, and the population centroids during breeding and migration. In contrast to many species that are experiencing poleward shifts in their distributions, the population centroids during the breeding period of all three bluebird species appear to have shifted southward over the past decade. Perhaps most surprisingly, we also detected strong longitudinal shifts in the population centroids during migration in eastern and western bluebirds, with both species shifting toward the center of the continent. Despite these changes in migratory routes and breeding distributions, we detected no change in the migratory timing or speed of any of the species. Our analysis indicates that bluebirds are rapidly altering the pattern of their migration, likely in response to changing environmental conditions, but not always in the direction predicted.
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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) | 0.004 | 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".