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Record W3089495177 · doi:10.13140/rg.2.2.30708.58249

Forest Disturbances and Climate Feedbacks in a Mixedwood Boreal Forest

2020· dissertation· en· W3089495177 on OpenAlexaboutno aff
Md. Abdul Halim

Bibliographic record

VenueTSpace · 2020
Typedissertation
Languageen
FieldEnvironmental Science
TopicForest ecology and management
Canadian institutionsnot available
Fundersnot available
KeywordsTaigaBorealEnvironmental scienceForestryAgroforestryGeographyClimatologyGeology

Abstract

fetched live from OpenAlex

Boreal forests play a critical role in global climate via important biophysical and biogeochemical feedbacks. Large-scale disturbances, particularly fire and harvesting, significantly affect these feedbacks by altering the surface and stand attributes, and can impact boreal forests’ role in the global climate system. Surface- and stand-attribute-driven feedbacks change rapidly in early successional stages, making them challenging to model. As the frequency and intensity of disturbances in boreal forests are predicted to increase, a vast landscape with proportionally more young forests is likely to result. Understanding these feedbacks during early stand development is thus more critical than ever before. Scarcity of data on key biophysical (e.g., albedo, soil temperature) and biogeochemical (e.g., soil greenhouse gas fluxes) processes during early stand development has been noted, particularly in mixedwood boreal forests. Using a series of micrometeorological towers in fire and harvesting chronosequences of a mixedwood boreal forest of northwestern Ontario, we studied combined effects of vegetation cover and climate warming on the surface soil (~2 cm depth) temperature in post-disturbance stands, and the patterns and drivers of surface albedo and soil CO2 and CH4 fluxes during early stand development stages in post-fire and post-harvest stands. A proxy-year analysis indicated that surface soil temperature in winter and spring was lower in a warm year compared to a baseline year, and the magnitude of this difference varied with vegetation cover (Chapter 2). Albedo differences between post-fire and post-harvest stands were most pronounced during winter and spring and primarily driven by stand age and species composition (Chapter 3). We also found that CO2 effluxes were lower in post-fire stands compared to post-harvest stands; post-fire stands were never a source, but some young post-harvest stands were a net source of CH4 . The magnitude in flux difference between post-fire and post-harvest stands varied with stand age and was affected by environmental variables such as soil temperature, moisture, pH, and litter depth (Chapter 4). These findings are critical for understanding dynamics in soil temperature, albedo, and soil carbon fluxes during early successional stages and useful for climate-smart boreal forest management.

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)0.000
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 score0.221
Threshold uncertainty score0.878

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.007
GPT teacher head0.257
Teacher spread0.250 · 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

Citations4
Published2020
Admission routes1
Has abstractyes

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