What determines the relationship between plant diversity and habitat productivity?
Bibliographic record
Abstract
ABSTRACT The relationship between biodiversity and habitat productivity has been a fundamental topic in ecology. Although the relationship between these parameters may exhibit different shapes, the unimodal shape has been frequently encountered. The decrease in diversity at high productivity has usually been attributed to competitive exclusion. We suggest that evolutionary history and dispersal limitation may be even more important in shaping the diversity–productivity relationship. On a global scale, unimodal diversity–productivity relationships dominate in temperate regions, whereas positive relationships are more common in the tropics. This difference can be accounted for by contrasting evolutionary history. Temperate regions have smaller species pools for productive habitats since these habitats have been scarce historically for speciation, while the opposite is true for the tropics. In addition, dispersal within a region may limit diversity either due to the lack of dispersal syndromes at low productivity or the low number of diaspores at high productivity. Thereafter, biotic interactions (competition and facilitation) can shape the relationship. All these processes can act independently or concurrently. We recommend that the common approach to examining empirical diversity–environmental relationships should start with the role of large‐scale processes such as evolutionary history and dispersal limitation, followed by influences associated with ecological interactions.
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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 | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".