Predator–prey interactions under climate change: the importance of habitat vs body temperature
Bibliographic record
Abstract
Habitat temperature is often assumed to serve as an effective proxy for organism body temperature when making predictions of species distributions under future climate change. However, the determinants of body temperature are complex, and organisms in identical microhabitats can occupy radically different thermal niches. This can have major implications of our understanding of how thermal stress modulates predator–prey relationships under field conditions. Using body temperature data from four different sites on Santa Cruz Island, California, we show that at two sites the body temperatures of a keystone predator (the seastar Pisaster ochraceus ) and its prey (the mussel Mytilus californianus ) followed very different trajectories, even though both animals occupied identical microhabitats. At the other two sites, body temperatures of predator and prey were closely coupled across a range of scales. The dynamical differences between predator and prey body temperatures depended on the location of pairs of sites, at the extremes of a persistent landscape‐scale weather pattern observed across the island. Thus, the well understood predator–prey interaction between Pisaster and Mytilus cannot be predicted based on habitat‐level information alone, as is now commonly attempted with landscape‐level (‘climate envelope’) models.
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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) | 0.000 | 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) | 0.008 | 0.001 |
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; both teacher heads agree on what is shown here.
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".