Shallow gas development and grassland songbirds: The importance of perches
Bibliographic record
Abstract
ABSTRACT Grassland bird species have declined more than birds of any other region in North America and industrial development may exert further pressure on these species. We evaluated effects of conventional natural gas infrastructure on the relative abundances of grassland songbirds in southeastern Alberta, Canada at sites with shallow gas well pad densities ranging from 0 to 16 pads/258 ha (0–24 well heads/258 ha). Conventional gas wells have a relatively small footprint and minimal associated noise and maintenance activities, allowing us to focus on effects of the infrastructure itself and vegetation surrounding wells. We conducted fixed‐radius point counts and vegetation sampling at 34 sites in 2010 and 40 sites in 2011. We used generalized linear mixed models and information theory to evaluate effects of infrastructure on birds. Relative abundances of vesper sparrow (Pooecetes gramineus) and western meadowlark (Sturnella neglecta) increased near gas wells, whereas abundance of the threatened Sprague's pipit (Anthus spragueii) declined. Vegetation near infrastructure was shorter and sparser than locations farther from wells, but discrepancies with avian habitat preferences suggest that, in contrast to conclusions of previous studies, vegetation structure could not explain responses to infrastructure by birds. Instead, gas wells may have acted as artificial shrubs because they attracted species that use vegetation for perching but were avoided by species that avoid shrubs. Our results suggest that observed effects were a direct result of the presence of wells and associated fencing, and thus risk mitigation should focus on reducing the extent of aboveground infrastructure. © 2017 The Wildlife Society.
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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 | 0.000 | 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".