Survival, Movements, and Reproduction of Translocated Greater Sage‐Grouse in Strawberry Valley, Utah
Bibliographic record
Abstract
Abstract Translocations of greater sage‐grouse ( Centrocercus urophasianus ) have been attempted in 7 states and one Canadian province with very little success. To recover a small remnant population and test the efficacy of sage‐grouse translocations, we captured and transported 137 adult female sage‐grouse from 2 source populations to a release site in Strawberry Valley, Utah, USA, during March‐April 2003–2005. The resident population of sage‐grouse in Strawberry Valley was approximately 150 breeding birds prior to the release. We radiomarked each female and documented survival, movements, reproductive effort, flocking with resident grouse, and lek attendance. We used Program MARK to calculate annual survival of translocated females in the first year after release, which averaged 0.60 (95% CI = 0.515‐0.681). Movements of translocated females were within current and historic sage‐grouse habitat in Strawberry Valley, and we detected no grouse outside of the study area. Nesting propensity for first (newly translocated) and second (surviving) year females was 39% and 73%, respectively. Observed nest success of all translocated females during the study was 67%. By the end of their first year in Strawberry Valley, 100% of the living translocated sage‐grouse were in flocks with resident sage‐grouse. The translocated grouse attended the same lek as the birds with which they were grouped. In 2006, the peak male count for the only remaining active lek in Strawberry Valley was almost 4 times (135 M) the 6‐year pretranslocation (1998–2003) average peak attendance of 36 males (range 24–50 M). Translocations can be an effective management tool to increase small populations of greater sage‐grouse when conducted during the breeding season and before target populations have been extirpated.
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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 | 0.001 | 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".