Effects of energy development on habitat use of an avian peatland specialist and generalist at multiple spatial scales
Bibliographic record
Abstract
With the persistent demand for petroleum energy products, the energy development footprint in northern Alberta continues to expand, perforating habitat in the boreal forest. Modern in situ, or below ground, bitumen extraction techniques have broadened the extent of accessible reserves and are creating a different type of footprint than conventional surface mining. Development of exploratory vegetation clearings, including 3-dimensional seismic lines (hereafter “seismic”), winter roads, and well sites, as well as permanent infrastructure, such as roads, pipelines, extraction wells, and industrial facilities, creates an expansive network of small-scale disturbances that alter biological communities, including songbirds. Additional work is needed to understand how different development features influence species-specific habitat use and selection for songbirds, especially in peatland habitats that are less-well understood. Here I examined the influence of different in situ oil sands development feature types on habitat use and selection of a conifer generalist, Dark-eyed Junco (Junco hyemalis), and peatland specialist, Palm Warbler (Setophaga palmarum), songbird at multiple spatial scales within peatland habitats. Specifically, the objectives of this study were to: (1) identify the relative effects of different in situ development and habitat features on landscape-level avian occurrence and local-scale habitat selection for songbirds with different habitat niche breadths; and (2) understand potential behavioural mechanisms affecting species-specific responses to in situ developments on individual territory placement and within-territory habitat selection. I used point counts to sample Dark-eyed Junco and Palm Warbler occurrence at 157 peatland sites located across a range of development feature types and intensities. I also examined territory-level (2nd order) and within-territory (3rd order) habitat selection by conducting behavioural observations within 11, 25-hectare sites. I modelled occurrence (presence-absence) for each species using binomial logistic regression; and modelled territory and within-territory selection using generalized linear mixed effect models to compare used to available locations for 80-82 individuals of each species. Permanent polygonal and linear features influenced occurrence for both species, whereas exploratory features did not, suggesting that permanent development features have a greater impact on avian populations. Both species avoided permanent (e.g. polygonal or linear) or larger exploratory features (e.g. well sites) at the territory scale, but relative use of development features was greater for Dark-eyed Juncos than Palm Warblers. At the within-territory scale, Dark-eyed Juncos avoided permanent features and well sites for singing but were more likely to sing by wide linear features in areas with taller vegetation, relative to locations with shorter vegetation. Juncos were more likely to forage on or near all features except seismic, but relative intensity of use for some features was greater in areas near higher productivity vegetation. Palm Warblers avoided singing by well sites but selected singing locations near wide linear features in areas with taller vegetation. Palm Warblers avoided foraging on or near well features across all habitat productivity levels but selected seismic features only in low productivity habitats. Our results show that avian responses to different development features are complex, with species-specific responses that vary for different behaviours and local habitat characteristics. Use, selection, and avoidance of different development features varies with spatial scale, and even small, 2-3 m wide seismic features can influence avian behaviours. I recommend pairing fine-scale behavioural studies with coarse-scale avian monitoring to increase understanding of the mechanisms driving species-specific responses to different development feature types and inform landscape management decisions.
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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) | 0.000 | 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".