Landscape- and Micro-scale Habitat Selection by Greater Short-horned Lizards
Bibliographic record
Abstract
Identification of critical habitat for species at risk is an essential component of the protection of rare species under Canada’s Species at Risk Act. In this study, I identified important microsite and landscape-level habitat characteristics for endangered greater short-horned lizards (Phrynosoma hernandesi) at their northern range limit in Grasslands National Park, Saskatchewan, Canada. A total of 650 km of transect surveys were used to analyze habitat selection based on locations where lizards were detected relative to available random locations. At the microsite level, I compared occupied locations (n = 118) to random landscape (n = 234) and random home range locations (n = 117) in 0.3 m2 ground cover plots and 0.12 m2 thermal plots using a classification and regression tree. Comparisons of occupied and random landscape microsites suggested that lizards selected microsites with higher diversity of ground cover types, especially in areas with high cover of exposed soil. At the home-range scale, lizards selected habitats with complex combinations of ground cover types and thermal characteristics. Selection was greatest for microsites with low vegetation height, low cover of lichens and mosses, and minimum temperatures that were >26.2°C, although other combinations of microsite characteristics were also supported at the home-range scale. A model of landscape-scale habitat selection (resource selection function) was also estimated for the Park using 101 lizard locations and 5000 random available locations sampled along 650 km of meander transects. Habitat selection in summer was predicted best by juniper-dune vegetation community, iii vegetation patchiness, and perhaps paradoxically areas of lower solar radiation. This model was used to define critical habitat for conservation management and to estimate an index of population size for the Park using the number of lizards detected, strip width of transects and classified habitat resulting in ~13,000 adult lizards. This population index provides a baseline for monitoring the success of conservation actions. As new information becomes available for this under-studied species, improvements in the definition of critical habitat should be considered.
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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 | 0.000 | 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) | 0.001 | 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 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".