Response of greater prairie-chickens to natural and anthropogenic disturbance on Fort Riley
Bibliographic record
Abstract
Greater Prairie-chickens (Tympanuchus cupido) historically occupied 20 states within the contiguous United States and four Canadian provinces; however, due to habitat degradation and loss, they are currently found in 11 states; only four of which have a stable population.Kansas supports a relatively large abundance of Greater Prairie-chickens, where the Flint Hills ecoregion historically supported the largest population of all ecoregions.In the past decade, however, the Flint Hills population has declined to an estimated 8,334 individuals in 2021 from 34,180 individuals in 2015 due to changes and intensification of grassland management practices.The Fort Riley Military Reservation in the northeast portion of the Flint Hills ecoregion is one of a few areas within the ecoregion that does not implement grazing or vast annual burning.The Greater Prairie-chicken population within Fort Riley has remained stable over the past 25 years despite being constrained by surrounding landscape features and development.To understand why this population is doing relatively well compared to populations in surrounding areas, I trapped, collared, and tracked 46 female Greater Prairie-chickens from March-April 2019-2020 on Fort Riley.My goals with this project were to assess female survival, nest survival, resource selection, and space use during the breeding season (Apr-Aug) on the military reservation.Despite being free from grazing and annual burning, Fort Riley experiences fairly constant military activity, which may elicit responses from Greater Prairie-chickens.I used known-fate and nest survival models in Program MARK to estimate female survival and nest success of Greater Prairie-chickens.I estimated breeding season survival as 0.275 ± 0.065 (SE) and nest survival as 0.2643 ± 0.0689 (SE), which are average and high for the Flint Hills, respectively.I used logistic regression models to assess resource selection by Greater Prairie-chicken females.I analyzed landscape features, vegetation variables, and burn mosaics to understand which features
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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 | 0.001 |
| 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".