Data from: Changes in behavior are unable to disrupt a trophic cascade involving a specialist herbivore and its food plant
Bibliographic record
Abstract
Changes in ecological conditions can induce changes in behavior and demography of wild organisms, which in turn may influence population dynamics. Black brant (Branta bernicla nigricans) nesting in colonies on the Yukon–Kuskokwim Delta (YKD) in western Alaska have declined substantially (~50%) since the turn of the century. Black brant are herbivores that rely heavily on Carex subspathacea (Hoppner's sedge) during growth and development. The availability of C. subspathacea affects gosling growth rates, which subsequently affect pre‐ and postfledging survival, as well as size and breeding probability as an adult. We predicted that long‐term declines in C. subspathacea have affected gosling growth rates, despite the potential of behavior to buffer changes in food availability during brood rearing. We used Bayesian hierarchical mixed‐effects models to examine long‐term (1987–2015) shifts in brant behavior during brood rearing, forage availability, and gosling growth rates at the Tutakoke River colony. We showed that locomotion behaviors have increased (β = 0.05, 95% CRI: 0.032–0.068) while resting behaviors have decreased (β = −0.024, 95% CRI: −0.041 to −0.007), potentially in response to long‐term shifts in forage availability and brood density. Concurrently, gosling growth rates have decreased substantially (β = −0.100, 95% CRI: −0.191 to −0.016) despite shifts in behavior, mirroring long‐term declines in the abundance of C. subspathacea (β = −0.191, 95% CRI: −0.355 to −0.032). These results have important implications for individual fitness and population viability, where shifts in gosling behavior putatively fail to mitigate long‐term declines in forage availability.
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.399 | 0.222 |
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".