Effects of Livestock Grazing Management on Grassland Bird Abundance in the Northern Mixed-Grass Prairie
Bibliographic record
Abstract
Grassland bird populations have been declining throughout a majority of their range in the United States and Canada over the past 40 years, and currently have the most accelerated declines of any guild of terrestrial birds in this region. Rangelands used for domestic cattle grazing are important for maintaining large tracts of native grassland that may otherwise be converted to agricultural use or other human development. In addition, grassland birds respond well to livestock grazing systems that increase habitat heterogeneity by mimicking historic grassland disturbance, such as fire and bison grazing. Montana Department of Fish, Wildlife, and Parks (FWP) implements a rest-rotation grazing system within conservation easements to increase structural heterogeneity of grassland vegetation on the landscape. However, the rest-rotation grazing system administered by Montana FWP was developed for more arid, bunchgrass-dominated rangelands and has not been evaluated as a management tool for creating structurally diverse wildlife habitat in the northern mixed-grass prairie. This study examines the effect of a rest-rotation grazing system on breeding season habitat selection and abundance of four native grassland songbird species, Baird’s sparrow (Ammodramus bairdii), grasshopper sparrow (Ammodramus savannarum), vesper sparrow (Pooecetes gramineus), and western meadowlark (Sturnella neglecta), relative to traditional season-long or rotational grazing systems on a Montana FWP conservation easement in eastern Montana. Our objectives for the study are: 1) evaluate how abundance and spaceuse of four focal grassland bird species are affected by grazing treatment; 2) estimate the importance of habitat and vegetation characteristics for focal species within pasture treatments; 3) offer management recommendations to agencies and private landowners for improving grassland bird abundance and habitat quality.
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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".