Environmental drivers of arthropod communities across the endangered predator <i>Gambelia sila</i> 's current and historic range
Bibliographic record
Abstract
Abstract Describing the habitat needs of endangered species is a major focus of applied conservation research. The blunt‐nosed leopard lizard ( Gambelia sila (Stejneger, 1890)) is a flagship endangered species endemic to the San Joaquin Valley of California, USA. Arthropods are an important component of G. sila 's diet and of many other listed vertebrate species in Californian drylands. We examined the drivers of abundance, richness, and composition across the current and extirpated ranges of the blunt‐nosed leopard lizard G. sila for four arthropod communities: ground‐active, shrub‐canopy active, open area active, and aerial. We found no evidence for lower arthropod abundance or species richness at sites from which G. sila has been extirpated. In contrast, the ground‐active arthropod and beetle communities were less abundant at sites with current populations of G. sila after accounting for environmental variation. Thus, prey availability—at least at the community level and for the taxonomic groups considered—would not likely be a factor constraining future repopulation efforts for G. sila into its historical range. Beta‐diversity partitioning analyses indicated that a regional approach to conservation is necessary to conserve arthropod biodiversity across the San Joaquin Valley. Increasing aridity lowered abundance and species richness at fine scales for most communities tested and was also related to spatial composition across the region. Thus, in terms of G. sila conservation and restoration, sites with the lowest current and projected future aridity should be prioritized to maximize the abundance and richness of co‐occurring ground‐active arthropod and beetle communities.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".