Global Change Asymmetrically Rewires Ecosystems
Bibliographic record
Abstract
Global change is complex and multidimensional, making it challenging to understand how human activities affect ecosystem processes. A critical gap in this understanding is how drivers of global change broadly affect food webs. While an industry of studies documents shifts in energy pathways within food webs in response to anthropogenic pressures, a synthesis that links these shifts to structural and functional changes in food webs is lacking. To address this, we review studies across diverse ecosystems that use stable isotope analysis, energetic food web modelling, and gut content analysis to reveal the prevalence of asymmetric rewiring---a phenomenon whereby anthropogenic pressures differentially impact habitats across space, altering some energy pathways relative to others. We then highlight several examples from the literature to illustrate how this process unfolds. To explore its broader consequences, we use a simple food web model to demonstrate how asymmetric rewiring alters resilience and key ecosystem functions, such as primary and secondary production. Our synthesis uncovers a remarkably general response in food web structure to global environmental change that needs to be better understood to protect nature and the services that human societies rely on in a rapidly changing world.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".