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Record W2017717208 · doi:10.3390/land4010083

Carbon Cycling, Climate Regulation, and Disturbances in Canadian Forests: Scientific Principles for Management

2015· article· en· W2017717208 on OpenAlexafffundabout
Jean‐Sébastien Landry, Navin Ramankutty

Bibliographic record

VenueLand · 2015
Typearticle
Languageen
FieldEnvironmental Science
TopicFire effects on ecosystems
Canadian institutionsUniversity of British ColumbiaMcGill University
FundersU.S. Forest ServiceCanadian Forest ServiceMcGill University
KeywordsCarbon cycleWildernessClimate changeGreenhouse gasEnvironmental scienceEnvironmental resource managementLoggingUncertaintyEcosystem servicesLand useForest managementNatural resource economicsEcosystemGeographyEcologyBusinessAgroforestryForestryEconomicsBiology

Abstract

fetched live from OpenAlex

Canadian forests are often perceived as pristine and among the last remaining wilderness, but the majority of them are officially managed and undergo direct land use, mostly for wood harvest. This land use has modified their functions and properties, often inadvertently (e.g., age structure) but sometimes purposefully (e.g., fire suppression). Based on a review of the literature pertaining to carbon cycling, climate regulation, and disturbances from logging, fire, and insect outbreaks, we propose five scientific principles relevant for Canadian managed forests. Among these, a principle we wish to highlight is the need to properly account for the management-related fossil fuel emissions, because they will affect the global carbon cycle and climate for millennia unless massive atmospheric carbon dioxide removal becomes a reality. We also use these five principles to address questions of current interest to research scientists, forest managers, and policy makers. Our review focusses on total ecosystem carbon storage and various mechanisms through which forests affect climate, in particular albedo and aerosols forcings—including how disturbances influence all these elements—but also touches on other ecosystem goods and services. Our review underscores the importance of conducting >100-year time horizon studies of carbon cycling, climate regulation, and disturbances in Canadian managed forests.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.769
Threshold uncertainty score0.805

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.013
GPT teacher head0.222
Teacher spread0.208 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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

Citations9
Published2015
Admission routes3
Has abstractyes

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