Grassland songbirds exhibit variable responses to the proximity and density of natural gas wells
Bibliographic record
Abstract
ABSTRACT Cultivation of native prairie was likely the primary cause of historical declines of grassland bird populations in North America, but the increase in natural gas development may be exacerbating those declines through habitat loss and degradation. We quantified the abundance of grassland songbirds and vegetation structure across a gradient of natural gas well densities to determine the extent to which density and proximity of gas wells influence songbird abundance. In 2008 and 2009, we conducted 1,258 point counts on 105 native grassland parcels (1.6 km 2 /parcel) at varying distances from natural gas wells and with varying gas well densities (0–25 per 1.6 km 2 ). We found that vegetation structure influenced bird abundance more strongly than natural gas well proximity or density for all but 1 species and that the response of grassland songbirds to natural gas well density and proximity varied among species and regions. Sprague's pipit ( Anthus spragueii ) and Baird's sparrow ( Ammodramus bairdii ) abundance was not influenced by natural gas well proximity or density. Grasshopper sparrow ( Ammodramus savannarum ), McCown's longspur ( Rhynchophanes mccownii ), and chestnut‐collared longspur ( Calcarius ornatus ) abundance was lower near gas wells, but both longspur species were also more abundant in areas with greater densities of gas wells. Horned lark ( Eremophilus alpestris ) abundance increased with well density in our northern study site. Savannah sparrow ( Passerculus sandwichensis ) abundance was higher near gas wells, but only in areas where well density was ≤9 wells/1.6 km 2 . We suggest that land managers and industry implement remediation activities that encourage vegetative re‐growth, thus reducing the potential interactive relationship between natural gas development and changes in vegetation structure. © 2014 The Wildlife Society.
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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 | 0.002 | 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) | 0.000 | 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".