Native shrub densities predict burrow co-occurrence patterns in Central California Drylands
Why this work is in the frame
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Bibliographic record
Abstract
Ecological resource availability is crucial for the persistence and survival of local desert animal communities. Dryland resources such as shrubs and burrows positively benefit animal species by mitigating harsh abiotic factors and providing habitat. Understanding the role of native shrubs, many of which serve as foundation species within desert regions, as well as the function of underground burrows as resources, provides insights into habitat utilization. In this study, we seek to better understand the co-occurrence of these two resources as a first step in quantifying key patterns locally and regionally in drylands. We tested whether the presence of burrows increased with the density of foundational shrubs near the burrows at two scales-within a 5 m radius of every burrow recorded and at the site level-defined as discrete ecological areas. We performed fieldwork across 31 sites within the arid and semiarid regions of Central California. We used a combination of burrow field surveys and satellite imagery to document both vertebrate animal burrow frequencies and shrub densities. Additionally, the accuracy of the shrub data was verified through ground truthing. Both fine-scale and site-level shrub densities positively predicted the relative likelihood of burrows and the frequency of burrows, respectively. The existence of two highly utilized dryland resources and the relationship between them signal that areas abundant in both resources will likely better support resident animal species. This finding underscores the significance of incorporating both shrub density and burrow frequency in studies of habitat interconnectivity and quality. The co-occurrence patterns of these resources will support novel habitat management and conservation strategies designed around both conservation and restoration efforts.
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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 it