A general biodiversity–function relationship is mediated by trophic level
Bibliographic record
Abstract
Species diversity affects the functioning of ecosystems, including the efficiency by which communities capture limited resources, produce biomass, recycle and retain biologically essential nutrients. These ecological functions ultimately support the ecosystem services upon which humanity depends. Despite hundreds of experimental tests of the effect of biodiversity on ecosystem function (BEF), it remains unclear whether diversity effects are sufficiently general that we can use a single relationship to quantitatively predict how changes in species richness alter an ecosystem function across trophic levels, ecosystems and ecological conditions. Our objective here is to determine whether a general relationship exists between biodiversity and standing biomass. We used hierarchical mixed effects models, based on a power function between species richness and biomass production (Y = a × S b ), and a database of 374 published experiments to estimate the BEF relationship (the change in biomass with the addition of species), and its associated uncertainty, in the context of environmental factors. We found that the mean relationship ( b = 0.26, 95% CI: 0.16, 0.37) characterized the vast majority of observations, was robust to differences in experimental design, and was independent of the range of species richness levels considered. However, the richness–biomass relationship varied by trophic level and among ecosystems; in aquatic systems b was nearly twice as large for consumers (herbivores and detritivores) compared to primary producers; in terrestrial ecosystems, b for detritivores was negative but depended on few studies. We estimated changes in biomass expected for a range of changes in species richness, highlighting that species loss has greater implications than species gains, skewing a distribution of biomass change relative to observed species richness change. When biomass provides a good proxy for processes that underpin ecosystem services, this relationship could be used as a step in modeling the production of ecosystem services and their dependence on biodiversity.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".