Relative conservation value of Nova Scotia’s forests: forested wetlands as avian diversity hotspots
Bibliographic record
Abstract
Nova Scotia’s forested landscapes are degraded and under stress. As the province moves toward an ecological forestry management approach, land managers need more complete information about the relative biodiversity value of various habitats in landscapes that they manage to fully assess conservation consequences of different management options. To begin assessing the relative conservation value of different forest types, we surveyed bird communities in 18 forested wetlands (wooded bogs, tall shrub swamps, and treed swamps), mature upland forest stands, and regenerating upland forest stands in western Nova Scotia during the breeding season in 2017 and 2018. There were distinct differences among the bird communities in each forest type. Bird species diversity, overall abundance, and abundance of several guilds and species of conservation concern were higher in forested wetlands than in mature and regenerating upland forests. Bogs and shrub swamps had the highest number of species with strong habitat affinities, but treed swamps and mature sites had unique suites of strongly associated species and guilds — several of conservation concern. Regenerating sites were occupied mainly by forest-edge species and conservation value was low. Our study highlights the importance of forested wetlands to bird conservation and supports the idea that forested wetlands are avian diversity hotspots.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".