ArticleNature communications2026
Learning lessons from over-crediting to ensure additionality in forest carbon credits.
Article in Nature communications, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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.
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.
Who cites it
1 citing paper in PubMed.
- Learning lessons from over-crediting to ensure additionality in forest carbon credits.Nature communications · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
16 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Independent evaluations have shown substantial over-issuance of REDD+ (Reducing Emissions from Deforestation and Degradation) credits traded on the voluntary carbon market. We synthesise these evaluations to estimate the additional forest conservation achieved by first-generation REDD+ projects and to identify mechanisms underlying over-crediting. We combine six independent ex post evaluations of avoided deforestation covering 44 REDD+ projects. These evaluations show that most projects reduced deforestation, but that they claimed an aggregate of 10.7 times more avoided deforestation than is justified by independent estimates. This discrepancy is not driven by the choice of forest cover data, but by selection bias in projects' control areas and modelling approaches. Although recent initiatives that transfer assessment to unconflicted parties and restrict methodological flexibility are critical, they are insufficient. Ex post certification against credible counterfactuals is necessary if carbon markets are to represent causal reductions in deforestation.
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Registered trials
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.