A review of natural disturbances to inform implementation of ecological forestry in Nova Scotia, Canada
Bibliographic record
Abstract
Like many jurisdictions across North America, the province of Nova Scotia (NS) is faced with the challenge of restoring its forests to a more natural, presettlement state through implementation of ecological forestry. At the core of ecological forestry is the idea that natural forest structures and processes may be approximated by designing management practices that emulate natural disturbances. Successful natural disturbance emulation depends on fundamental knowledge of disturbance characteristics, including identification of specific disturbance agents, their spatial extent, severity, and return interval. To date, no comprehensive synthesis of existing data has been undertaken to document the natural disturbance regime of NS forests, limiting the application of natural disturbance emulation. Using over 300 years of documents and available data, we identified the main natural disturbance agents that affect NS forests and characterized their regimes. Overall, fire, wind (predominantly hurricanes), and outbreaks of spruce budworm (Choristoneura fumiferana (Clemens)) are the most important disturbance agents, causing substantial areas of low- (<30% mortality), moderate- (30%–60%), and high- (>60%) severity disturbance. While characterization of natural historic fire is challenging, due to past human ignitions and suppression, we estimated that the mean annual disturbance rate of moderate- to high-severity fire ranged between 0.17% and 0.4%·year−1 (return interval of 250–600 years), depending on ecosystem type. Hurricanes make landfall in NS, on average, every 7 years, resulting in wide-scale (>500 ha) forest damage. While hurricane track and damage severity vary widely among storms, the return interval of low- to high-severity damage is 700–1250 years (0.14%–0.08%·year−1). Conversely, the return interval of host-specific spruce budworm outbreaks is much shorter (<50 years) but more periodic, causing wide-scale, low- to high-severity damage to spruce–fir forests every 30–40 years. Further disturbance agents such as other insects (e.g., spruce beetle), diseases, ice storms, drought, and mammals can be locally important and (or) detrimental to individual tree species but contribute little to overall disturbance in NS. Climate change is expected to significantly alter the disturbance regime of NS, affecting current disturbances (e.g., increased fire) and driving the introduction of novel agents (e.g., hemlock wooly adelgid), and continued monitoring is needed to understand these changes.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.012 | 0.018 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".