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Record W7002104792

Modelling the effect of fire, insect, and logging disturbances on climate and vegetation across various spatial and temporal scales

2015· dissertation· en· W7002104792 on OpenAlexaboutno aff

Bibliographic record

VenueeScholarship@McGill (McGill) · 2015
Typedissertation
Languageen
FieldMedicine
TopicMicrobial Natural Products and Biosynthesis
Canadian institutionsnot available
Fundersnot available
KeywordsAlbedo (alchemy)LoggingVegetation (pathology)Climate changeBorealTaigaClimate modelDownscalingEarth system science
DOInot available

Abstract

fetched live from OpenAlex

Fire, insect, and logging disturbances affect ecosystems worldwide and often lead to spectacular local changes in vegetation characteristics, as well as biogeochemical and biogeophysical fluxes. Despite a growing body of empirical and modelling studies, many key questions remain unanswered, and even unasked, about the effect of these disturbances on climate and vegetation. In this thesis, I explored some of these questions at different spatial and temporal scales, and mostly from a modelling perspective. In Chapter 2, I simulated various future (2015–2300) fire regimes in the University of Victoria Earth System Climate Model and estimated the resulting impacts on global carbon stocks and surface temperature, with and without the effect of the main fire-related non-CO2 emissions. This global-scale study in a fully coupled climate–carbon model allowed me to differentiate the net from the gross carbon emissions in response to changes in fire frequency, a crucial distinction that is sometimes overlooked in the literature, and to also highlight the possibly dominant effect of fire-emitted aerosols on the net climatic impact from non-deforestation fires. In Chapter 3, I investigated, with a new model developed for this purpose, how different approaches to represent fire and logging in climate models affected the simulation of albedo over boreal forests. This methodological study showed that the simplest approach, which was the one applied in Chapter 2, noticeably underestimates the long-term fire-induced albedo increase over boreal forests, but that substantial improvements can be obtained without undue additional computing requirements. Having focussed on stand-clearing disturbances in the previous two chapters, I looked at the role of insect outbreaks in Chapter 4. I assessed, with a modified version of the Integrated BIosphere Simulator dynamic vegetation–land surface model, the long-term impacts (up to >1,000 years) from recurrent mountain pine beetle (MPB) outbreaks at three different locations in British Columbia on different vegetation- and climate-related variables, namely merchantable biomass, ecosystem carbon, albedo, and net radiative forcing. This study emphasized the major role of the non-target vegetation in MPB-induced changes and illustrated various non-linearities in the responses to recurrent outbreaks. In Chapter 5, I finally performed a critical review of the literature relevant to the climate–forest–disturbances triad in Canada. More precisely, I proposed five principles relevant for the management of Canadian forests in the context of carbon cycling, climate regulation, and disturbances, and then applied these principles to address four questions of current interest. One conclusion from this study was the need to perform >100-year analyses of disturbances in Canadian forests, as I did in Chapter 4. Overall, suggesting that fire or insect disturbances seem to generally have less impact per event as they become more frequent (i.e., sub-linear scaling) is the most important scholarly contribution from this thesis. Another major outcome consists of identifying sources of uncertainty that prevent sound conclusions on the net warming or cooling impact from natural disturbances, namely the strength of cloud-mediated aerosol effects in the case of fire and the response from the non-target vegetation in the case of MPB outbreaks. Other contributions to knowledge include the possible influence of fire-emitted aerosols on land–atmosphere and ocean–atmosphere carbon exchanges, the impact of dead standing trees on the post-disturbance carbon response due to their interactions with energy and water exchanges, and the idea that the spatial distribution of trees killed by insects can modulate the resulting biogeophysical and biogeochemical consequences. Finally, this thesis illustrates that fire, insect, and logging disturbances lead to both large and small impacts, depending upon the specific scale and element considered.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.068
Threshold uncertainty score0.134

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.016
GPT teacher head0.258
Teacher spread0.242 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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

Citations0
Published2015
Admission routes1
Has abstractyes

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