Habitat preference of the striped legless lizard: Implications of grazing by native herbivores and livestock for conservation of grassland biota
Bibliographic record
Abstract
Abstract Across the globe, many species of reptile are threatened with extinction, with changes in grazing pressure as a significant factor in their decline. Few studies have investigated the role of native herbivores, yet studying natural grazers may provide insight into natural grazing regimes, not apparent in studies of domestic livestock. In this study, we investigate the habitat requirements of a threatened Australian grassland reptile, the striped legless lizard,Delma impar, in grasslands grazed by a native herbivore, the eastern grey kangarooMacropus giganteus.Delma imparappears sensitive to habitat change resulting from altered grazing intensity, but a lack of information hinders implementation of appropriate grazing regimes. To address this gap, we investigated habitat preferences ofD. imparat multiple spatial scales across a grazing gradient. We found that the occurrence ofD. imparwas not affected by the size of grassland remnants, but was negatively related to the density of native grazers. This result was likely a consequence of the negative effect of high grazing intensity on grass structural complexity, as the probability of encountering aD. imparwas positively related to grass structural complexity at the fine scale (1 m2). We recommend that conservation efforts should avoid high intensity grazing (equivalent to > 1.3 kangaroos/ha), yet ensure enough grazing disturbance is maintained to promote the formation of complex grass structures. We also recommend that small floristically degraded and fragmented grassland habitat should be included in conservation efforts. These recommendations will likely benefit a number of faunal species in grasslands grazed by domestic and native grazers. Importantly, our data highlight the need for managing grazing regimes, even in environments dominated by native herbivores.
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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 | 0.000 | 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 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".