Lack of evidence for the match‐mismatch hypothesis across terrestrial trophic interactions
Bibliographic record
Abstract
Climate change has led to widespread shifts in the timing of key life history events between interacting species (phenological asynchrony) with hypothesized cascading negative fitness impacts on one or more of the interacting species-often termed 'mismatch'. Yet, predicting the types of systems prone to mismatch remains a major hurdle. Recent reviews have argued that many studies do not provide strong evidence of the underlying match-mismatch hypothesis, but none have quantitatively analysed support for it. Here, we test the hypothesis by estimating the prevalence of mismatch across antagonistic trophic interactions in terrestrial systems and then examine whether studies that meet the assumptions of the hypothesis are more likely to find a mismatch. Despite a large range of synchrony to asynchrony, we did not find general support for the hypothesis. Our results thus question the general applicability of this hypothesis in terrestrial systems, but they also suggest specific types of data missing to robustly refute it. We highlight the critical need to define resource seasonality and the window of 'match' for the most rigorous tests of the hypothesis. Such efforts are necessary if we want to predict systems where mismatches are likely to occur.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".