Integrating community assembly and biodiversity to better understand ecosystem function: the Community Assembly and the Functioning of Ecosystems (<scp>CAFE</scp>) approach
Bibliographic record
Abstract
The research of a generation of ecologists was catalysed by the recognition that the number and identity of species in communities influences the functioning of ecosystems. The relationship between biodiversity and ecosystem functioning (BEF) is most often examined by controlling species richness and randomising community composition. In natural systems, biodiversity changes are often part of a bigger community assembly dynamic. Therefore, focusing on community assembly and the functioning of ecosystems (CAFE), by integrating both species richness and composition through species gains, losses and changes in abundance, will better reveal how community changes affect ecosystem function. We synthesise the BEF and CAFE perspectives using an ecological application of the Price equation, which partitions the contributions of richness and composition to function. Using empirical examples, we show how the CAFE approach reveals important contributions of composition to function. These examples show how changes in species richness and composition driven by environmental perturbations can work in concert or antagonistically to influence ecosystem function. Considering how communities change in an integrative fashion, rather than focusing on one axis of community structure at a time, will improve our ability to anticipate and predict changes in ecosystem function.
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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 | 0.003 | 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 | 0.007 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".