Using species co‐occurrence patterns to quantify relative habitat breadth in terrestrial vertebrates
Bibliographic record
Abstract
The breadth of habitats that a species uses may determine its vulnerability to environmental change, with habitat specialists at greater risk than generalists. To test that hypothesis, we need a valid index of habitat specialization. Existing indices require extensive data, or ignore the magnitude of differences among habitat categories. We suggest an index based on patterns of species co‐occurrence within each of the 101 habitat categories recognized by the International Union for Conservation of Nature. Using this metric, a species is allocated a quantitative score based on the diversity of other taxa with which it co‐occurs: a generalist species occurs in a range of habitat categories that vary considerably in species composition, whereas a specialist species is found only in habitats that contain a consistent suite of other species. We provide data on these scores for 22,230 vertebrate species and show that habitat breadth varies among Classes (amphibians > birds > mammals > reptiles). Within each Class, generalist species are less likely to be in decline or threatened with extinction. Because our index is continuous, based on biologically relevant parameters, and easily calculated for a vast number of taxa, its use will facilitate analyses of the evolution and consequences of habitat specialization.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.006 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".