Response to clear-cut logging by northern waterthrushes
Bibliographic record
Abstract
We examined the distribution and foraging behaviour of northern waterthrushes (Seiurus noveboracensis) in recently harvested and intact landscapes of Newfoundland. Data were collected along six 1-km segments of stream and adjoining upland habitat resulting in four treatments (harvested or intact, upland or stream) with three replicates each. Although known as a riparian specialist, we found waterthrush territories equally distributed across intact upland and riparian habitats. However, few waterthrushes occupied harvested uplands, while large numbers packed into riparian buffer strips adjacent to these 5- to 10-year-old postharvest clearcuts. Arthropod abundance and biomass were highly variable between years and across the four treatments, generating significant year × treatment interaction effects. Riparian habitat (in both intact and harvested areas) had consistently greater numbers of arthropod prey and more biomass than either upland habitat type. Northern waterthrushes foraging in riparian habitat adjacent to harvested uplands had lower attack rates and more frequent long flights than waterthrushes foraging in the intact treatment types. Prolonged packing of individuals into riparian buffer strips, and apparent adverse affects on waterthrush foraging efficiency, raise concerns about the effectiveness of buffer strips for sustaining viable populations of terrestrial riparian habitat specialists.
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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 | 0.000 | 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) | 0.001 | 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".