Habitat amount–fragmentation interactions drive Canada Warbler dynamics across spatial scales
Bibliographic record
Abstract
The Canada Warbler (Cardellina canadensis) is a long-distance neotropical migrant that has experienced significant population declines across its range and is listed as threatened in Canada. Understanding how landscape changes affect population dynamics is an important step in developing effective conservation strategies to prevent further declines or extinctions. We assessed the relative effects of habitat amount and fragmentation on Canada Warbler occupancy dynamics in Alberta’s industrial boreal forest using multi-scale dynamic occupancy models on 3 yrs of presence/absence data. Using species-specific habitat definitions, we tested for interactions between habitat amount (proportion habitat) and fragmentation (edge density), evaluated three increasingly refined fragmentation definitions to determine what constitutes functional barriers from this species’ perspective, and examined how these effects vary across spatial scales. Our models revealed that local extinction rates were over four times higher than colonization rates, an imbalance congruent with continued population declines. Edge density had consistent negative effects on both initial occupancy and colonization probabilities across all spatial scales. At the broader spatial scales (78 and 314 ha), we detected a counterintuitive negative interaction between habitat amount and fragmentation, where increasing edge density had stronger negative effects on occupancy in areas with higher habitat amounts. Larger polygonal disturbances like harvest cutblocks and wellpads had seemingly greater influence than narrow linear features like seismic lines at territory and local scales (7–78 ha), although all disturbance types contributed equally at landscape scales (314 ha). These findings demonstrate that preserving habitat amount alone is insufficient; landscape configuration critically influences Canada Warblers. Management should prioritize minimizing edge density and maintaining large, intact forest blocks at scales encompassing multiple territories (>78 ha), particularly in landscapes with high habitat availability where negative fragmentation effects are strongest.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".