How size and resource traits control species' biomass in monoculture and mixture and drive biodiversity–ecosystem functioning relationships
Bibliographic record
Abstract
Humans are driving unprecedented environmental change, causing the loss of species from local ecosystems. This local species loss is likely to result in declines in ecosystem functioning but understanding why these so‐called biodiversity–ecosystem functioning relationships vary is crucial for conservation and sustainable land management. Previous studies have shown that variation among biodiversity–ecosystem functioning (BEF) relationships can be explained by a ‘function–dominance correlation', i.e. the correlation of species' biomass in monoculture (‘functioning') versus mixtures (‘dominance'). One potential reason for the importance of the function–dominance correlation is its relationship to underlying plant traits. Here, we explore which traits control species' biomass in monoculture and mixture and thereby drive the function–dominance correlation, and hence BEF relationships. To do this, we perform a modeling experiment with six trait‐based models of plant community dynamics and classify model traits as either ‘size' or ‘resource' traits. This approach allows us to better generalize across systems that differ in terms of their key traits and/or how a given trait affects individual performance and ecosystem functioning. We found that size traits, but not resource traits, predicted species' monoculture biomass in five out of the six models. However, in mixture, resource traits became more important and – in addition to size traits – explained substantial variation in species' biomass in four models. In models where size traits were consistently important predictors of biomass variance in monoculture and mixture, the function–dominance correlation was high, and BEF relationships were strongly positive. Our analysis shows how generalizable categories of functional traits allow predicting BEF relationships across systems, and thereby the potential effects of losing species on ecosystem functioning.
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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) | 0.000 | 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".