A circumpolar study unveils a positive non‐linear effect of temperature on arctic arthropod availability that may reduce the risk of warming‐induced trophic mismatch for breeding shorebirds
Bibliographic record
Abstract
Seasonally abundant arthropods are a crucial food source for many migratory birds that breed in the Arctic. In cold environments, the growth and emergence of arthropods are particularly tied to temperature. Thus, the phenology of arthropods is anticipated to undergo a rapid change in response to a warming climate, potentially leading to a trophic mismatch between migratory insectivorous birds and their prey. Using data from 19 sites spanning a wide temperature gradient from the Subarctic to the High Arctic, we investigated the effects of temperature on the phenology and biomass of arthropods available to shorebirds during their short breeding season at high latitudes. We hypothesized that prolonged exposure to warmer summer temperatures would generate earlier peaks in arthropod biomass, as well as higher peak and seasonal biomass. Across the temperature gradient encompassed by our study sites (>10°C in average summer temperatures), we found a 3-day shift in average peak date for every increment of 80 cumulative thawing degree-days. Interestingly, we found a linear relationship between temperature and arthropod biomass only below temperature thresholds. Higher temperatures were associated with higher peak and seasonal biomass below 106 and 177 cumulative thawing degree-days, respectively, between June 5 and July 15. Beyond these thresholds, no relationship was observed between temperature and arthropod biomass. Our results suggest that prolonged exposure to elevated temperatures can positively influence prey availability for some arctic birds. This positive effect could, in part, stem from changes in arthropod assemblages and may reduce the risk of trophic mismatch.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".