Reptiles Under the Conservation Umbrella of the Greater Sage‐Grouse
Bibliographic record
Abstract
ABSTRACT In conservation paradigms, management actions for umbrella species also benefit co‐occurring species because of overlapping ranges and similar habitat associations. The greater sage‐grouse ( Centrocercus urophasianus ) is an umbrella species because it occurs across vast sagebrush ecosystems of western North America and is the recipient of extensive habitat conservation and restoration efforts that might benefit sympatric species. Biologists' understanding of how non‐target species might benefit from sage‐grouse conservation is, however, limited. Reptiles, in particular, are of interest in this regard because of their relatively high diversity in shrublands and grasslands where sage‐grouse are found. Using spatial overlap of species distributions, land cover similarity statistics, and a literature review, we quantified which reptile species may benefit from the protection of intact sage‐grouse habitat and which may be affected by recent (since about 1990) habitat restoration actions targeting sage‐grouse. Of 190 reptile species in the United States and Canadian provinces where greater sage‐grouse occur, 70 (37%) occur within the range of the bird. Of these 70 species, about a third (11 snake and 11 lizard species) have >10% of their distribution area within the sage‐grouse range. Land cover similarity indices revealed that 14 of the 22 species (8 snake and 6 lizard species) had relatively similar land cover associations to those of sage‐grouse, suggesting greater potential to be protected under the sage‐grouse conservation umbrella and greater potential to be affected, either positively or negatively, by habitat management actions intended for sage‐grouse. Conversely, the remaining 8 species are less likely to be protected because of less overlap with sage‐grouse habitat and thus uncertain effects of sage‐grouse habitat management actions. Our analyses of treatment databases indicated that from 1990 to 2014 there were at least 6,400 treatments implemented on public land that covered approximately 4 million ha within the range of the sage‐grouse and, of that, >1.5 million ha were intended to at least partially benefit sage‐grouse. Whereas our results suggest that conservation of intact sagebrush vegetation communities could benefit ≥14 reptiles, a greater number than previously estimated, additional research on each species' response to habitat restoration actions is needed to assess broader claims of multi‐taxa benefits when it comes to manipulative sage‐grouse habitat management. Published 2020. This article is a U.S. Government work and is in the public domain in the USA.
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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 | 0.001 | 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 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".