Species richness along a production gradient: a multivariate approach
Bibliographic record
Abstract
The specific shape of the relationship between plant diversity and productivity and the causal mechanism(s) behind the observed pattern(s) are still highly debated. Recent advances suggest that the relationship depends on several environmental variables and may change with the observational scale. In this study, a multivariate, multiscale approach was used to identify the variables that determine the relationship between species richness and annual production along a forest/old field edge in southern Québec (Canada). Various relationships between richness and production were found at different distances to the edge. In the forest, most relationships were positive and linear, while in the old field the relationship shifted from positive linear to non-significant with increasing distance from the edge. In the forest or in the old field, the shape of the relationship (all distances from the edge combined) was unimodal. Path analyses showed that species richness was determined mostly by production, which was influenced by different limiting resources, depending on the community (forest or old field). An increasing range in production created by pooling across community types can confound the resources and/or conditions determining the diversity-productivity relationship.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".