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Record W2786991736 · doi:10.5194/bg-15-885-2018

Differential response of carbon cycling to long-term nutrient input and altered hydrological conditions in a continental Canadian peatland

2018· article· en· W2786991736 on OpenAlexaffabout
Sina Berger, Leandra Praetzel, Marie Goebel, Christian Blodau, Klaus‐Holger Knorr

Bibliographic record

VenueBiogeosciences · 2018
Typearticle
Languageen
FieldEnvironmental Science
TopicPeatlands and Wetlands Ecology
Canadian institutionsUniversity of Guelph
FundersWestfälische Wilhelms-Universität MünsterDeutsche Forschungsgemeinschaft
KeywordsPeatEnvironmental scienceCarbon cycleCyclingCarbon sinkSink (geography)Water tableNutrientShrubMossDissolved organic carbonHydrology (agriculture)EutrophicationEcologyEcosystemGeologyGroundwaterBiology

Abstract

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Peatlands play an important role in global carbon cycling, but their responses to long-term anthropogenically changed hydrologic conditions and nutrient infiltration are not well known. While experimental manipulation studies, e.g., fertilization or water table manipulations, exist on the plot scale, only few studies have addressed such factors under in situ conditions. Therefore, an ecological gradient from the center to the periphery of a continental Canadian peatland bordering a eutrophic water reservoir, as reflected by increasing nutrient input, enhanced water level fluctuations, and increasing coverage of vascular plants, was used for a case study of carbon cycling along a sequence of four differently altered sites. We monitored carbon dioxide (CO 2 ) and methane (CH 4 ) surface fluxes and dissolved inorganic carbon (DIC) and CH 4 concentrations in peat profiles from April 2014 through September 2015. Moreover, we studied bulk peat and pore-water quality and we applied δ 13 C–CH 4 and δ 13 C–CO 2 stable isotope abundance analyses to examine dominant CH 4 production and emission pathways during the growing season of 2015. We observed differential responses of carbon cycling at the four sites, presumably driven by abundances of plant functional types and vicinity to the reservoir. A shrub-dominated site in close vicinity to the reservoir was a comparably weak sink for CO 2 (in 1.5 years: −1093 ± 794, in 1 year: +135 ± 281 g CO 2 m −2 ; a net release) as compared to two graminoid-moss-dominated sites and a moss-dominated site (in 1.5 years: −1552 to −2260 g CO 2 m −2 , in 1 year: −896 to −1282 g CO 2 m −2 ). Also, the shrub-dominated site featured notably low DIC pore-water concentrations and comparably 13 C-enriched CH 4 ( δ 13 C– CH 4 : −57.81 ± 7.03 ‰) and depleted CO 2 ( δ 13 C–CO 2 : −15.85 ± 3.61 ‰) in a more decomposed peat, suggesting a higher share of CH 4 oxidation and differences in predominant methanogenic pathways. In comparison to all other sites, the graminoid-moss-dominated site in closer vicinity to the reservoir featured a ∼ 30 % higher CH 4 emission (in 1.5 years: +61.4 ± 32, in 1 year: +39.86 ± 16.81 g CH 4 m −2 ). Low δ 13 C–CH 4 signatures (−62.30 ± 5.54 ‰) indicated only low mitigation of CH 4 emissions by methanotrophic activity here. Pathways of methanogenesis and methanotrophy appeared to be related to the vicinity to the water reservoir: the importance of acetoclastic CH 4 production apparently increased toward the reservoir, whereas the importance of CH 4 oxidation increased toward the peatland center. Plant-mediated transport was the prevailing CH 4 emission pathway at all sites even where graminoids were rare. Our study thus illustrates accelerated carbon cycling in a strongly altered peatland with consequences for CO 2 and CH 4 budgets. However, our results suggest that long-term excess nutrient input does not necessarily lead to a loss of the peatland carbon sink function.

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 score0.036
Threshold uncertainty score0.077

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0010.000
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 head0.012
GPT teacher head0.248
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 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

Citations15
Published2018
Admission routes2
Has abstractyes

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