Relating niche and spatial overlap at the community level
Bibliographic record
Abstract
If interspecific competition is a strong structuring force of communities, ecologically similar species should tend to have spatial ranges at local scale that do not overlap. Experimental testing of this hypothesis becomes impracticable with large communities. One possibility to tackle this issue is a correlational approach, by comparing the matrix of niche overlap with that of spatial overlap. The use of the standard Mantel test is however impaired by the non‐linearity in the relationship of the two descriptors: in a competitively structured assemblage, species with high niche overlap are expected to be segregated spatially, but species with small niche overlap may or may not exhibit high spatial overlap. To overcome this problem, we devised an original randomization test, which was run for three data‐sets comprising frogs, lizards, and birds along altitudinal gradients. The test yielded intriguing results: reptiles and birds revealed an adjustment that would reduce the potential for interspecific competition, while amphibians showed the opposite trend, that is, ecologically similar species co‐occurred more than expected by chance. Frogs may be more constrained by resource requirements, possibly breeding sites, than by competition. Our test will help to assess the generality of this pattern with other data‐sets.
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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 | 0.012 |
| 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 | 0.002 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".