Evidence map›Paper›PMID 37439912›Full record

ReviewCarbon balance and management2023

Deriving emission factors for mangrove blue carbon ecosystem in Indonesia.

Daniel Murdiyarso, Haruni Krisnawati, Wahyu C Adinugroho, Sigit D Sasmito

Abstract readReview
In one paragraph

Review in Carbon balance and management, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Refining greenhouse gas emission factors for Indonesian peatlands and mangroves to meet ambitious climate targets.Proceedings of the National Academy of Sciences of the United States of America · 2024
    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

4 authors.

Daniel MurdiyarsoCenter for International Forestry Research - World Agroforestry, Jl. CIFOR, Situgede, Bogor, 16115, Indonesia. d.murdiyarso@cifor-icraf.org.
Haruni KrisnawatiResearch Center for Ecology and Ethnobiology, National Research and Innovation Agency, Bogor, Indonesia.
Wahyu C AdinugrohoResearch Center for Ecology and Ethnobiology, National Research and Innovation Agency, Bogor, Indonesia.
Sigit D SasmitoNUS Environmental Research Institute, National University of Singapore, 21 Lower Kent Ridge Road, Singapore, 119077, Singapore.

Funding

Norwegian International Climate and Forest Initiative (NICFI) INS 2078-19/0010United States Agency for International Development No. MTO 069018
6 · The paper itself

Abstract

backgroundUsing 'higher-tier' emission factors in National Greenhouse Gas Inventories is essential to improve quality and accuracy when reporting carbon emissions and removals. Here we systematically reviewed 736 data across 249 sites (published 2003-2020) to derive emission factors associated with land-use change in Indonesian mangroves blue carbon ecosystems.

resultsFour management regimes-aquaculture, degraded mangrove, regenerated mangrove and undisturbed mangrove-gave mean total ecosystem carbon stocks of 579, 717, 890, and 1061 Mg C ha

conclusionsUsing deep layer (e.g., 300 cm) soil carbon stocks would compensate for the underestimation of surface soil carbon removed from areas where aquaculture is widely practised. From a project perspective, deep layer data could secure permanence or buffer potential leakages. From a national GHG accounting perspective, it also provides a safeguard in the MRV system.

Indexed as

AquacultureCarbon stocksForest reference emission level (FREL)GHG fluxesMangrove restorationNational Greenhouse Gas Inventories (NGGI)Nature based climate solutions

Identifiers

PMID37439912
PMCPMC10339514

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.