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Record W3008264376 · doi:10.1029/2019jg005473

Invasive <i>Phragmites</i> Increases Blue Carbon Stock and Soil Volume in a St. Lawrence Estuary Marsh

2020· article· en· W3008264376 on OpenAlexafffundabout
Jiali Gu, Lee B. van Ardenne, Gail L. Chmura

Bibliographic record

VenueJournal of Geophysical Research Biogeosciences · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicCoastal wetland ecosystem dynamics
Canadian institutionsMcGill University
FundersNatural Sciences and Engineering Research Council of CanadaChina Scholarship Council
KeywordsPhragmitesMarshBlue carbonBrackish marshSpartina alternifloraEnvironmental scienceEstuarySalt marshWetlandSoil carbonSpartinaEcologySoil waterCarbon sequestrationSoil scienceBiologyCarbon dioxide

Abstract

fetched live from OpenAlex

Abstract Our study of a St. Lawrence Estuary marsh reveals that, compared to native Spartina patens ‐dominated vegetation, invasive Phragmites australis makes a greater contribution to soil volume and carbon stock (referred to as blue carbon). Phragmites ' contributions to soil volume enhance marsh sustainability in face of sea level rise, and its greater contribution to soil carbon helps to reduce the atmospheric concentration of CO 2 . Phragmites australis (common reed) is a cosmopolitan species growing in fresh to brackish wetlands. An invasive genetic strain, introduced from Europe or Asia, has expanded extensively along the St. Lawrence River in the last few decades but has been little studied on the estuarine portion. We collected soil cores from three sites within an invasive Phragmites stand and one site within S. patens ‐dominated stand in a St. Lawrence Estuary salt marsh near la Pocatiere, Quebec. We measured the bulk density, carbon content, volume, and mass of belowground organic matter in 2‐cm‐thick soil layers of three cores at each Phragmites site. Bulk density and carbon content were measured in 5‐cm‐thick soil layers of three cores at S. patens site. Results showed that soil in the Phragmites stands held 37–77% more blue carbon than in the S. patens ‐dominated marsh. Based upon their diameter size, Phragmites rhizomes could be contributing 7.4–10.2 cm to the thickness in the upper 20 cm of soil. We suggest that any management of invasive Phragmites include consideration of its role in increasing blue carbon stocks and marsh resilience along with other ecosystem services.

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)0.002
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation 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 score0.041
Threshold uncertainty score0.980

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0000.001
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 head0.024
GPT teacher head0.269
Teacher spread0.245 · 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.

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

Citations23
Published2020
Admission routes3
Has abstractyes

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