Lizard community structure across a grassland – creosote bush ecotone in the Chihuahuan Desert
Bibliographic record
Abstract
I investigated the distribution and abundance of lizard species (Aspidoscelis inornatus, Aspidoscelis tesselatus, Aspidoscelis tigris, Aspidoscelis uniparens, Cophosaurus texanus, Crotaphytus collaris, Eumeces obsoletus, Gambelia wislizenii, Holbrookia maculata, Phrynosoma cornutum, Sceloporus magister, and Uta stansburiana) across a desert grassland – creosote bush (Larrea tridentata) ecotone in Dona Ana County, New Mexico. The ecotonal area in the Jornada del Muerto basin has increased dramatically in the past 150 years because of the rapid spread of creosote bush. I asked four related questions: how large and where is the ecotone based on vegetative structure, and do lizard abundance and diversity change across the ecotone? Vegetation data were analyzed using discriminate function analysis to determine the extent of the ecotone. Changes in lizard abundance across the ecotone were analyzed by analysis of variance. During two summers, 677 individual lizards of 9 genera and 12 species were captured. Lizard abundance increased with increasing distance from the ecotone and was similar in grassland and creosote bush habitat. Grasslands had higher species richness than both the creosote bush and ecotone habitats. Grassland sites had greater habitat heterogeneity than did creosote bush sites. No ecotone specialist species were detected, and all common lizard species could be found in each habitat. Three potential explanations for decreased abundance in the ecotone are presented: (1) increased risk of predation, (2) decreased prey abundance, and (3) lack of species-specific microhabitat requisites.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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 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".