Edge effects reduce persistence but not colonization in a declining <i>Setophaga virens</i> (Black-throated Green Warbler) population in Alberta’s boreal forest
Bibliographic record
Abstract
Abstract Setophaga virens (Black-throated Green Warbler) is listed as a species of special concern in Alberta due to perceived population declines and projected future habitat loss from resource extraction. Using dynamic occupancy models over 25 yr, we examined how different types of anthropogenic edges drive population dynamics in this interior forest specialist. We observed a 58% decline in occupancy from 1993 to 2018, driven by low colonization rates that failed to compensate for reduced persistence near edges. Sites farther from seismic lines and harvest areas showed markedly higher persistence probabilities, but edge proximity had no effect on colonization probability, suggesting that birds initially settle near edges but subsequently abandon these territories. Contrary to our predictions, regenerating harvest edges showed no mitigation of negative edge effects after 25 yr. Site-level analysis revealed dramatic variation in persistence probability across sites, ranging by nearly two orders of magnitude despite similar forest composition, enabling us to identify demographically stable sites concentrated in forest interiors. These findings demonstrate that edge impacts persist through secondary succession and may create population sinks even when suitable forest cover remains. Conservation of this species in northern Alberta will likely require maintaining large areas of older forest distant from anthropogenic edges. Our dynamic occupancy approach provides a framework for identifying priority habitats in fragmented landscapes, applicable to other species facing similar challenges from resource extraction in North America’s boreal forests.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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".