Mutualistic coevolution and community diversity favour persistence in metacommunities under environmental changes
Bibliographic record
Abstract
Linking local to regional ecological and evolutionary processes is key to understand the response of Earth's biodiversity to environmental changes. Here we integrate evolution and mutualistic coevolution in a model of metacommunity dynamics and use numerical simulations to understand how coevolution can shape species distribution and persistence in landscapes varying in space and time. Our simulations show that coevolution and species richness can synergistically shape distribution patterns by increasing colonization and reducing extinction of populations in metacommunities. Although conflicting selective pressures emerging from mutualisms may increase mismatches with the local environment and the rate of local extinctions, coevolution increases trait matching among mutualists at the landscape scale, counteracting local maladaptation and favouring colonization and range expansions. Our results show that by facilitating colonization, coevolution can also buffer the effects of environmental changes, preventing species extinctions and the collapse of metacommunities. Our findings reveal the mechanisms whereby coevolution can favour persistence under environmental changes and highlight that these positive effects are greater in more diverse systems that retain landscape connectivity.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| 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".