Evidence map›Paper›PMID 42706932›Full record

ArticleEcological applications : a publication of the Ecological Society of America2026

Strategic restoration of global inland peatlands can maximize local and global co-benefits.

Emily A Ury, Zhen Zhang, Etienne Fluet-Chouinard, Stavroula S Sartzetakis, Tianyi Sun, Brian Buma

Abstract read
In one paragraph

Article in Ecological applications : a publication of the Ecological Society of America, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Strategic restoration of global inland peatlands can maximize local and global co-benefits.Ecological applications : a publication of the Ecological Society of America · 2026
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Emily A UryEnvironmental Defense Fund, New York, New York, USA.ORCID https://orcid.org/0000-0002-1459-655X
Zhen ZhangNational Tibetan Plateau Data Center (TPDC), State Key Laboratory of Tibetan Plateau Earth System, Environment and Resource (TPESER), Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing, People's Republic of China.
Etienne Fluet-ChouinardEarth System Science Division, Pacific Northwest National Laboratory, Richland, Washington, USA.
Stavroula S SartzetakisEnvironmental Defense Fund, New York, New York, USA.ORCID https://orcid.org/0009-0002-2607-4078
Tianyi SunEnvironmental Defense Fund, New York, New York, USA.
Brian BumaEnvironmental Defense Fund, New York, New York, USA.ORCID https://orcid.org/0000-0003-2402-7737

Funding

Biological and Environmental ResearchCOMPASS-FMEEnvironmental Defense FundGrantham Foundation for the Protection of the Environment
6 · The paper itself

Abstract

Global-scale peatland restoration holds large potential for carbon sequestration; however, the peatland carbon balance is not often considered alongside co-benefits in restoration prioritization. Here, we present a spatial optimization framework for inland peatland restoration to minimize greenhouse gas (GHG) emissions and maximize peatland co-benefits, such as flood mitigation and water quality improvements. We find strategic restoration of 30% of the world's drained inland peatlands, targeting areas with the greatest potential for GHG emissions reductions, would sequester three times more GHGs (0.91 ± 0.17 Pg CO

Indexed as

Conservation of Natural ResourcesEnvironmental Restoration and RemediationGreenhouse GasesWetlandsCarbon SequestrationSoilGreenhouse GasesSoilecosystem servicesgreenhouse gasmethanepeatlandsrestorationwetlands

Identifiers

PMID42706932
PMCPMC13551036

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.