Resource-use plasticity governs the causal relationship between traits and community structure in model microbial communities
Bibliographic record
Abstract
Resolving the relationship between species’ traits and their relative abundance is a central challenge in ecology. Current hypotheses assume relative abundances either result from or are independent of traits. However, despite some success, these hypotheses do not integrate the reciprocal and feedback interactions between traits and abundances to predictions of community structure such as relative abundance distributions. Here we study how plasticity in resource-use traits govern the causal relationship between traits and relative abundances. We adopt a consumer-resource model that incorporates resource-use plasticity that operates to optimize organism growth, underpinned by investment constraints in physiological machinery for acquisition of resources. We demonstrate that the rate of plasticity controls the coupling strength between trait and abundance dynamics, predicting species’ relative abundance variation. We first show how plasticity in a single species in a community allows all other non-plastic species to coexist, a case of facilitation emerging from competitive interactions where a plastic species minimizes its similarity with competitors and maximizes resource-use efficiency in its environment. We apply this environment-competition trade-off to predict trait-abundance relationships and reveal that initial traits are better predictors of equilibrium abundances than final trait values. This result highlights the importance of transient dynamics that drive species sorting. The temporal scale of transients determines the strength of species sorting due to the emergence of ‘ecological equivalence’ at equilibrium. We propose trait-abundance feedback as an eco-evolutionary mechanism linking community structure and assembly, highlighting trait plasticity’s role in community dynamics.
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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 | 0.002 | 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 | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.004 |
| 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".