Carry-Over Effects of Forest Fragmentation on Breeding Adult Wood Thrushes (Hylocichla mustelina)
Bibliographic record
Abstract
Full annual cycle research has become increasingly important as more evidence is found of connections between events that occur during different periods of the annual cycle, sometimes thousands of kilometers apart. For instance, long term negative carry-over effects arising from poor quality wintering habitat in the tropics have been shown to reduce future reproductive success and survival. Habitat loss and fragmentation on the breeding grounds have a negative effect on immediate breeding success of many bird species; however, short-term impacts on adult body condition and long-term impacts on migration and survival have not been studied. Individuals occupying small forest fragments are expected to experience high rates of cowbird brood parasitism, higher nest predation, and lower food availability which could directly delay fall migration due to timing constraints from late re-nesting or indirectly delay migration if adults are in poorer condition. If small fragments are lower quality habitat, breeding adults are also expected to have lower relative mass, and higher baseline levels of blood corticosterone. During the 2016-2019 breeding seasons, I fitted 117 adult Wood Thrushes with coded radio-tags in a variety of large and small forest fragments in Norfolk County, Ontario, to track their movements using Motus. For two years of the study, I also collected blood samples to measure corticosterone levels. I found that fragment size was related to many vegetation variables (e.g. density of trees, shrubs, groundcover) as expected, but it did not have a strong effect on relative mass or blood corticosterone of adults. Contrary to prediction, season-long reproductive success was also not lower in small fragments. In addition, I found that fall migration timing and annual survival were also not related to fragment size. Overall, I found no evidence that breeding habitat quality has a significant negative short-term or long-term effect on Wood Thrushes. This suggests that small forest fragments can provide good quality breeding habitat for forest songbirds and differences in quality between small and large fragments are not strong enough to trigger the kinds of negative carry-over effects that have been documented in other species on the wintering grounds.
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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) | 0.002 | 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".