Effects of differential habitat warming on complex communities
Bibliographic record
Abstract
Food webs unfold across a mosaic of micro and macro habitats, with each habitat coupled by mobile consumers that behave in response to local environmental conditions. Despite this fundamental characteristic of nature, research on how climate change will affect whole ecosystems has overlooked (i) that climate warming will generally affect habitats differently and (ii) that mobile consumers may respond to this differential change in a manner that may fundamentally alter the energy pathways that sustain ecosystems. This reasoning suggests a powerful, but largely unexplored, avenue for studying the impacts of climate change on ecosystem functioning. Here, we use lake ecosystems to show that predictable behavioral adjustments to local temperature differentials govern a fundamental structural shift across 54 food webs. Data show that the trophic pathways from basal resources to a cold-adapted predator shift toward greater reliance on a cold-water refuge habitat, and food chain length increases, as air temperatures rise. Notably, cold-adapted predator behavior may substantially drive this decoupling effect across the climatic range in our study independent of warmer-adapted species responses (for example, changes in near-shore species abundance and predator absence). Such modifications reflect a flexible food web architecture that requires more attention from climate change research. The trophic pathway restructuring documented here is expected to alter biomass accumulation, through the regulation of energy fluxes to predators, and thus potentially threatens ecosystem sustainability in times of rapid environmental change.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".