Landscape-Scale Disturbances Modified Bird Community Dynamics in Successional Forest Environment
Bibliographic record
Abstract
Ecosystem-based forest management strives to develop silvicultural practices that best emulate natural disturbances such as wildfire to conserve biodiversity representative of natural forest ecosystems. Yet, current logging practices alter forest structure and reduce the proportion of old-growth forest and, consequently, can exert long-term effects on the dynamics of forest biota. The stand- and landscape-scale factors driving bird community dynamics in post-disturbance environment remain poorly understood. In this study, we examined bird community dynamics along successional gradients in boreal ecosystems originating from fire and logging in landscapes dominated by old-growth forest. We tested if bird species richness and community compositions in clear-cutting stands became comparable to those in natural stands after 70 years, and identified the relative contributions of stand- and landscape-scale forest attributes in bird community dynamics. Based on records of bird occurrences at 185 field sites in natural and clearcutting stands, we demonstrate that (1) both forest structures and bird communities underwent evident changes along successional gradients in post-clearcutting environment; (2) bird species richness and community composition in 60- to 70-years-old clearcutting stands still differed from those in 50- to 79-years-old natural stands, in spite of the fact that most forest attributes of clearcutting stands became comparable to those of natural stands after 40 years; and (3) landscape disturbances contributed more than stand characteristics in explaining the lack of convergence of mature forest species, residents, and short-distance migrants in post-clearcutting environment. Our study points out that more regards should be paid to improve the landscape configuration of the managed forests, and implies that old-growth forest retention within logged areas, combined with selection cutting and prolonged logging rotations, can better emulate fire and alleviate forest harvesting effects on bird community assemblages typical of natural boreal ecosystem.
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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 | 0.000 |
| 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) | 0.001 | 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".