Consequences of species loss for ecosystem functioning: meta-analyses of data from biodiversity experiments
Bibliographic record
Abstract
Abstract A large number of studies have now explicitly examined the relationship between species loss and ecosystem function. Analyzed by two independent groups, the results from such experiments show that reductions in species diversity generally result in reduced ecosystem functioning, across a wide range of ecosystems, diversity manipulations, and functions. This chapter analyzes both data sets in parallel to explain variation in the observed functional effects of biodiversity. This chapter concludes: 1) the functional effects of biodiversity differ among ecosystem types (but not between terrestrial and aquatic systems), 2) increases in species richness enhance community responses but negatively affect population responses, 3) stocks are more responsive than rates, 4) diversity reductions often reduce function at an adjacent trophic level, 5) increased biodiversity results in increased invasion resistance. This chapter also analyzes the shape of the relationship between biodiversity and function, and discuss consequences of different relationships.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.011 | 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".