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Record W3048644195 · doi:10.1098/rsfs.2019.0129

Climate change mitigation potential of wetlands and the cost-effectiveness of their restoration

2020· article· en· W3048644195 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueInterface Focus · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicCoastal wetland ecosystem dynamics
Canadian institutionsUniversité du Québec à Montréal
Fundersnot available
KeywordsWetlandEnvironmental scienceClimate changePeatCarbon sinkTemperate climateBorealCarbon sequestrationGlobal warmingEcosystemTundraGreenhouse gasMarshEcologyHydrology (agriculture)Carbon dioxide

Abstract

fetched live from OpenAlex

Abstract The cost-effective mitigation of climate change through nature-based carbon dioxide removal strategies has gained substantial policy attention. Inland and coastal wetlands (specifically boreal, temperate and tropical peatlands; tundra; floodplains; freshwater marshes; saltmarshes; and mangroves) are among the most efficient natural long-term carbon sinks. Yet, they also release methane (CH4) that can offset the carbon they sequester. Here, we conducted a meta-analysis on wetland carbon dynamics to (i) determine their impact on climate using different metrics and time horizons, (ii) investigate the cost-effectiveness of wetland restoration for climate change mitigation, and (iii) discuss their suitability for inclusion in climate policy as negative emission technologies. Depending on metrics, a wetland can simultaneously be a net carbon sink (i.e. boreal and temperate peatlands net ecosystem carbon budget = −28.1 ± 19.13 gC m−2 y−1) but have a net warming effect on climate at the 100 years time-scale (i.e. boreal and temperate peatland sustained global warming potential = 298.2 ± 100.6 gCO2 eq−1 m−2 y−1). This situation creates ambivalence regarding the effect of wetlands on global temperature. Moreover, our review reveals high heterogeneity among the (limited number of) studies that document wetland carbon budgets. We demonstrate that most coastal and inland wetlands have a net cooling effect as of today. This is explained by the limited CH4 emissions that undisturbed coastal wetlands produce, and the long-term carbon sequestration performed by older inland wetlands as opposed to the short lifetime of CH4 in the atmosphere. Analysis of wetland restoration costs relative to the amount of carbon they can sequester revealed that restoration is more cost-effective in coastal wetlands such as mangroves (US$1800 ton C−1) compared with inland wetlands (US$4200–49 200 ton C−1). We advise that for inland wetlands, priority should be given to conservation rather than restoration; while for coastal wetlands, both conservation and restoration may be effective techniques for climate change mitigation.

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.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.301
Threshold uncertainty score0.183

Codex and Gemma teacher scores by category

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 head0.015
GPT teacher head0.233
Teacher spread0.218 · 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