Natural disturbance regimes as templates for the response of bird species assemblages to contemporary forest management
Bibliographic record
Abstract
Abstract Aim In managed forest landscapes, the tolerance of species to contemporary alteration of forest cover is often assumed to reflect their resilience to natural disturbances. We tested this central tenet of ecosystem‐based management by comparing the structure of forest bird assemblages among four regions with contrasting historical natural disturbance regimes. Location Canada's boreal and northern hardwood forests. Methods Using point count data from four study regions across Canada, we first determined the relative sensitivity of individual bird species to the contemporary reduction of old forest cover at stand and ‘landscape‐context’ (1‐km radius) scales with log‐linear models. The richness of species most sensitive to loss of old forest (hereafter ‘sensitive species’) was then modelled as a function of landscape‐scale changes in old forest cover. Differences in the rate of decline in the richness of sensitive species with contemporary cover of old forest were compared among regions using ANCOVA. We then compared broken‐stick regression models with linear models to detect thresholds, if present, in this relationship in each region. Results Bird assemblages from regions with relatively infrequent natural disturbances hosted more species sensitive to contemporary reduction in old forest cover. Those species were also more abundant than in regions with frequent natural disturbances, and the rate of decline in their richness with the loss of old forest was steeper in regions with infrequent natural disturbances than in those where they were frequent. However, we did not detect thresholds in this rate of decline in any study region. Main conclusions Our findings are consistent with the contention that historical natural disturbance regimes shape the response of biota to contemporary landscape alterations through evolutionary adaptation. We argue that forest management conducted within the natural range of variability in stand and landscape structure specific to a region is likely to be ecologically sustainable.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".