Nest-Patch Characteristics of Bicknell's Thrush in Regenerating Clearcuts, and Implications for Precommercial Thinning
Bibliographic record
Abstract
Catharus bicknelli (Bicknell's Thrush) is a rare and globally vulnerable songbird often found in regenerating clearcuts in the Canadian maritime provinces and Québec. Previous studies have shown correlations between vegetation characteristics and occurrence and abundance of this species, but no study has described vegetation associated with Bicknell's Thrush nests in managed forests. From 2007–2010, we investigated nest-habitat selection of Bicknell's Thrush in the industrial forestry landscape of north-central New Brunswick. We compared vegetation composition and structure in 5-m-radius patches around nests to vegetation in a random control-patch within the home range of each Bicknell's Thrush. Precommercial thinning (PCT) is a forest-management treatment that may reduce the suitability of habitat for Bicknell's Thrush, thus we also examined the percent of the landscape treated by this practice around Bicknell's Thrush nests. We found that Bicknell's Thrush preferentially selected nest sites with a significantly lower proportion of deciduous trees and higher overall tree density than randomly sampled habitat within their home range. We also found that an average of 44% of the area within 500 m of Bicknell's Thrush nests was treated by PCT, and most had been treated within 3–5 years of our study. We suggest that small patches of dense, Abies balsamea (Balsam Fir)-dominated forest within a thinned matrix may be sufficient to provide nesting sites for Bicknell's Thrush; however, it remains unclear if these areas support production of young or if they are population sinks. PCT could have serious negative consequences on Bicknell's Thrush breeding success and on the long-term survival of the species in Canada; thus, we encourage silviculture treatments that leave unthinned areas for nesting of Bicknell's Thrush in managed forests.
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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".