Mismatch‐induced growth reductions in a clade of Arctic‐breeding shorebirds are rarely mitigated by increasing temperatures
Bibliographic record
Abstract
Abstract In seasonal environments subject to climate change, organisms typically show phenological changes. As these changes are usually stronger in organisms at lower trophic levels than those at higher trophic levels, mismatches between consumers and their prey may occur during the consumers’ reproduction period. While in some species a trophic mismatch induces reductions in offspring growth, this is not always the case. This variation may be caused by the relative strength of the mismatch, or by mitigating factors like increased temperature‐reducing energetic costs. We investigated the response of chick growth rate to arthropod abundance and temperature for six populations of ecologically similar shorebirds breeding in the Arctic and sub‐Arctic (four subspecies of Red KnotCalidris canutus, Great KnotC.tenuirostrisand SurfbirdC.virgata). In general, chicks experienced growth benefits (measured as a condition index) when hatching before the seasonal peak in arthropod abundance, and growth reductions when hatching after the peak. The moment in the season at which growth reductions occurred varied between populations, likely depending on whether food was limiting growth before or after the peak. Higher temperatures led to faster growth on average, but could only compensate for increasing trophic mismatch for the population experiencing the coldest conditions. We did not find changes in the timing of peaks in arthropod availability across the study years, possibly because our series of observations was relatively short; timing of hatching displayed no change over the years either. Our results suggest that a trend in trophic mismatches may not yet be evident; however, we show Arctic‐breeding shorebirds to be vulnerable to this phenomenon and vulnerability to depend on seasonal prey dynamics.
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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 | 0.000 | 0.001 |
| 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) | 0.001 | 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".