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Record W7162035620 · doi:10.82308/31270

From forest to lake: effect of hydroelectric reservoir impoundment on the net ecosystem exchange of carbon dioxide

2011· dissertation· en· W7162035620 on OpenAlexaboutno aff
Marie-Ève Lemieux

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldEarth and Planetary Sciences
TopicMarine and coastal ecosystems
Canadian institutionsnot available
Fundersnot available
KeywordsEddy covarianceHydrology (agriculture)Carbon dioxideEcosystemTaigaHydroelectricityCarbon sinkFlux (metallurgy)

Abstract

fetched live from OpenAlex

The purpose of this research was to determine the magnitude and direction of carbon exchange resulting from a boreal forest being flooded for hydroelectric purposes and to determine the net reservoir effect. In this study, carbon dioxide fluxes were measured from March 29th 2007 to November 30th 2008 in a mature black spruce forest and a flooded forest in Eastmain-1, James Bay, Quebec, Canada using eddy covariance towers. The unburned mature boreal forest was selected to act as a pre-flooded analogue site to the newly impounded hydroelectric reservoir. Flux tower measurement of the net ecosystem exchange (NEE) showed that the forest was a carbon sink during the growing seasons (DOY 102-304 in 2007 and 104 to 305 in 2008) with a similar cumulative NEE for both years, varying from -115.6 g C m-2d-1 in 2007 to -122.5 g C m-2d-1 in 2008. When compared to the pre-flooded site, flux measurement over the reservoir revealed that this flooded environment was a constant emitter of CO2 throughout the study period. Two seasonal peaks of emissions were identified during the year defined as December 2007 to November 2008. The first occurred during the ice break up in the last week of May 2008 (DOY 143-152) with 1.78 ± 0.09 g C m-2d-1 and the second corresponded to the reservoir turnover at the end of August and September 2008 (DOY 229-274) with 1.27 ± 0.03 g C m-2d-1. Overall, the net reservoir effect was estimated to be 1.75± 0.07 g C m-2d-1 for the ice free period and of 289.2 ± 144.6 g C m-2yr-1for the entire annual period.

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 score0.060
Threshold uncertainty score0.120

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)0.0010.000

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 head0.010
GPT teacher head0.200
Teacher spread0.190 · 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

Citations0
Published2011
Admission routes1
Has abstractyes

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