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Record W2546500873 · doi:10.5194/bg-14-2799-2017

Annual greenhouse gas budget for a bog ecosystem undergoing restoration by rewetting

2017· article· en· W2546500873 on OpenAlexafffundabout
Sung‐Ching Lee, Andreas Christen, T. Andrew Black, Mark S. Johnson, Rachhpal S. Jassal, Rick Ketler, Zoran Nesic, Markus Merkens

Bibliographic record

VenueBiogeosciences · 2017
Typearticle
Languageen
FieldEnvironmental Science
TopicPeatlands and Wetlands Ecology
Canadian institutionsParks CanadaUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of CanadaCanada Foundation for Innovation
KeywordsPeatBogEnvironmental scienceSphagnumEcosystemEcosystem respirationGreenhouse gasWetlandEddy covarianceSink (geography)MireCarbon sinkHydrology (agriculture)Carbon dioxideEcologyGeographyGeologyBiology

Abstract

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Abstract. Many peatlands have been drained and harvested for peat mining, agriculture, and other purposes, which has turned them from carbon (C) sinks into C emitters. Rewetting of disturbed peatlands facilitates their ecological recovery and may help them revert to carbon dioxide (CO2) sinks. However, rewetting may also cause substantial emissions of the more potent greenhouse gas (GHG) methane (CH4). Our knowledge of the exchange of CO2 and CH4 following rewetting during restoration of disturbed peatlands is currently limited. This study quantifies annual fluxes of CO2 and CH4 in a disturbed and rewetted area located in the Burns Bog Ecological Conservancy Area in Delta, BC, Canada. Burns Bog is recognized as the largest raised bog ecosystem on North America's west coast. Burns Bog was substantially reduced in size and degraded by peat mining and agriculture. Since 2005, the bog has been declared a conservancy area, with restoration efforts focusing on rewetting disturbed ecosystems to recover Sphagnum and suppress fires. Using the eddy covariance (EC) technique, we measured year-round (16 June 2015 to 15 June 2016) turbulent fluxes of CO2 and CH4 from a tower platform in an area rewetted for the last 8 years. The study area, dominated by sedges and Sphagnum, experienced a varying water table position that ranged between 7.7 (inundation) and −26.5 cm from the surface during the study year. The annual CO2 budget of the rewetted area was −179 ± 26.2 g CO2–C m−2 yr−1 (CO2 sink) and the annual CH4 budget was 17 ± 1.0 g CH4–C m−2 yr−1 (CH4 source). Gross ecosystem productivity (GEP) exceeded ecosystem respiration (Re) during summer months (June–August), causing a net CO2 uptake. In summer, high CH4 emissions (121 mg CH4–C m−2 day−1) were measured. In winter (December–February), while roughly equal magnitudes of GEP and Re made the study area CO2 neutral, very low CH4 emissions (9 mg CH4–C m−2 day−1) were observed. The key environmental factors controlling the seasonality of these exchanges were downwelling photosynthetically active radiation and 5 cm soil temperature. It appears that the high water table caused by ditch blocking suppressed Re. With low temperatures in winter, CH4 emissions were more suppressed than Re. Annual net GHG flux from CO2 and CH4 expressed in terms of CO2 equivalents (CO2 eq.) during the study period totalled −22 ± 103.1 g CO2 eq. m−2 yr−1 (net CO2 eq. sink) and 1248 ± 147.6 g CO2 eq. m−2 yr−1 (net CO2 eq. source) by using 100- and 20-year global warming potential values, respectively. Consequently, the ecosystem was almost CO2 eq. neutral during the study period expressed on a 100-year time horizon but was a significant CO2 eq. source on a 20-year time horizon.

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 categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.334
Threshold uncertainty score1.000

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 studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.014
GPT teacher head0.249
Teacher spread0.235 · 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.

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

Citations63
Published2017
Admission routes3
Has abstractyes

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