Landscape‐scale habitat assessment for an imperiled avian species
Bibliographic record
Abstract
Abstract A comprehensive understanding of wildlife habitat suitability requires landscape‐scale assessments that provide the framework for subsequent integration with local‐scale relationships. To elucidate the functional role of habitat characteristics at large scales it is necessary to understand how abundance is related to important landscape characteristics. We estimated male greater sage‐grouse Centrocercus urophasianus abundance on leks relative to sagebrush availability, landscape connectivity and anthropogenic infrastructure densities within landscapes surrounding leks from 2006 to 2013 using binomial N‐mixture models. We focused on Wyoming, as the state will play a critical role in the long‐term persistence of greater sage‐grouse due to its relatively robust populations, widespread sagebrush habitats and innovative, large‐scale conservation approaches. Landscapes associated with higher abundance of males on leks were characterized as highly connected, sagebrush‐dominated areas with limited energy development. These modeled relationships were used to evaluate spatial and temporal changes in the landscape‐scale integrity of areas supporting the majority of the greater sage‐grouse populations in Wyoming (i.e. core areas). By assessing relative changes in abundance over time, our models indicated that most of the habitat within core areas (86%) exhibited landscape conditions conducive to supporting medium or large greater sage‐grouse populations that were stable or increasing through time. Larger populations were associated with larger, more centrally located core areas. Conversely, core areas supporting relatively small or declining populations were located along range margins in the eastern portion of the state. The landscape‐scale habitat relationships we developed can be used in combination with local‐scale assessments to generate a more complete picture of greater sage‐grouse habitat suitability.
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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".