Demographic Responses by Birds to Forest Fragmentation
Bibliographic record
Abstract
Abstract: Despite intensive recent research on the effects of habitat loss and fragmentation on bird populations, our understanding of underlying demographic causes of population declines is limited. We reviewed avian demography in relation to habitat fragmentation. Then, through a meta‐analysis, we compared specific demographic responses by forest birds to habitat fragmentation, providing a general perspective of factors that make some species and populations more vulnerable to fragmentation than others. We obtained data from the scientific literature on dispersal, survival, fecundity, and nesting success of birds. Birds were divided into subgroups on the basis of region, nest site, biogeographical history, and migration strategy. Species most sensitive to fragmentation were ground‐ or open‐nesters nesting in shrubs or trees. Residents were equally sensitive to fragmentation in the Nearctic and Palearctic regions, but Nearctic migrants were more sensitive than Palearctic migrants. Old World species were less sensitive than New World species, which was predicted based on the history of forest fragmentation on these two continents. Pairing success was the variable most associated with fragmentation, suggesting an important role of dispersal. Fledgling number or condition, timing of nesting, and clutch size were not associated with sensitivity to fragmentation, suggesting that negative fragmentation effects on birds do not generally result from diminished food resources with increasing level of fragmentation. Future studies on demographic responses of birds to habitat fragmentation would be more effective if based on a combination of measures that can distinguish among the demographic mechanisms underlying population changes related to habitat fragmentation.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| 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".