Contingencies and compounded rare perturbations dictate sudden distributional shifts during periods of gradual climate change
Bibliographic record
Abstract
Ecological responses to climate change may occur gradually with changing conditions, or they may occur rapidly once some threshold or "tipping point" has been reached. Here, we use a high-resolution, 30-year data set on the upper vertical limit of a high intertidal alga to demonstrate that distributional shifts in this species do not keep pace with gradual trends in air temperature or sea level, but rather occur in sudden, discrete steps. These steps occur when unusually warm air temperatures are associated with unusually calm seas and are contingent in the sense that neither atmospheric nor sea conditions by themselves were sufficient to generate the underlying physiological challenge. Shifts in the upper limit did not correlate with large environmental perturbations such as El Niños; rather, they appeared to be associated with stochastic departures from otherwise gradual environmental trends. Our results exemplify the view that multiple environmental factors should be considered when attempting to understand ecological responses to climate change. Furthermore, punctuated responses such as those we have identified urge caution when attempting to infer causal mechanisms and project future distributional shifts using data of limited temporal resolution or scope.
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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 | 0.001 | 0.003 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".