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Record W1560211916

ASSESSING SEASONAL DYNAMICS OF SOIL CO2 EFFLUX USING CONTINUOUS MEASUREMENTS IN A TEMPERATE PINE FOREST

2011· dissertation· en· W1560211916 on OpenAlexaboutno aff
Emily Nicholas

Bibliographic record

VenueMacSphere (McMaster University) · 2011
Typedissertation
Languageen
FieldEnvironmental Science
TopicFire effects on ecosystems
Canadian institutionsnot available
Fundersnot available
KeywordsTemperate forestPine forestTemperate climateEnvironmental scienceTemperate rainforestAtmospheric sciencesEcologyForestryGeographyBiologyEcosystemGeology
DOInot available

Abstract

fetched live from OpenAlex

This study explores the seasonal dynamics of soil CO2 efflux (Rs) in a temperate pine plantation forest located in Southern Ontario, Canada. Rs was continuously measured from June 15, 2008 to December 31, 2010 at this site using an automated soil CO2 chamber system. Component analysis of Rs conducted by making continuous measurements in a trenched plot where live roots were excised indicated that heterotrophic respiration (Rh) contributed approximately 72 and 80% (895 and 920 g C m-2 year-1) of annual Rs in 2009 and 2010, respectively. Similarly, continuous Rs measurement in a litterless plot where the surface litter layer was removed contributed 65 and 57% (800 and 655 g C m-2 year-1) of annual Rs in 2009 and 2010, respectively. Results of this study suggested that overall soil temperature was the dominant control on Rs in this forest, except during the severe dry conditions. In order to explore the impact of soil water limitations on Rs a through-fall exclusion experiment conducted from April 1 to July 3, 2009 - the spring and early summer season. Through-fall exclusion caused a large reduction in daily Rs. This experiment further suggested that Rs became less sensitive to temperature and increasingly more sensitive to water as soil water content depleted due to the through-fall exclusion. This study helps to better understand the seasonal dynamics of Rs, and its components and controls in temperate conifer forests in Eastern North America. These forests are considered a large sink of carbon, and changes in Rs dynamics in this region may have implications for the global carbon cycle.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.270
Threshold uncertainty score0.538

Distilled classifier scores by category (both heads)

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 head0.019
GPT teacher head0.217
Teacher spread0.198 · 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 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

Citations1
Published2011
Admission routes1
Has abstractyes

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