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Record W3071938486 · doi:10.1139/er-2020-0015

A review of natural disturbances to inform implementation of ecological forestry in Nova Scotia, Canada

2020· review· en· W3071938486 on OpenAlexafffundvenueabout
Anthony R. Taylor, David A. MacLean, Peter D. Neily, Bruce Stewart, Eugene Quigley, Seán P. Basquill, Celia K. Boone, Derek Gilby, Mark D. Pulsifer

Bibliographic record

VenueEnvironmental Reviews · 2020
Typereview
Languageen
FieldEnvironmental Science
TopicFire effects on ecosystems
Canadian institutionsNova Scotia Department of AgricultureNatural Resources CanadaCanadian Forest ServiceUniversity of New Brunswick
FundersNatural Resources Canada
KeywordsDisturbance (geology)GeographyEnvironmental scienceEcologyNatural (archaeology)EcosystemFire regimeStormForestryEnvironmental resource managementMeteorologyBiology

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.942
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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.

Opus teacher head0.019
GPT teacher head0.303
Teacher spread0.284 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreReview

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".

Quick stats

Citations37
Published2020
Admission routes4
Has abstractyes

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