Evidence map›Paper›PMID 37803150›Full record

ArticleScientific reports2023

Estimating changes of forest carbon storage in China for 70 years (1949-2018).

WeiSheng Zeng, XinYun Chen, XueYun Yang

Abstract read
In one paragraph

Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

3 authors.

WeiSheng ZengAcademy of Inventory and Planning, National Forestry and Grassland Administration, Beijing, 100714, China. zengweisheng0928@126.com.
XinYun ChenAcademy of Inventory and Planning, National Forestry and Grassland Administration, Beijing, 100714, China.
XueYun YangAcademy of Inventory and Planning, National Forestry and Grassland Administration, Beijing, 100714, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In the realm of forest resource inventory and monitoring, stand-level biomass carbon models are especially crucial. In China, their importance is underscored as they form the bedrock for estimating national and international forest carbon storage. This study, based on the data from 52,700 permanent plots in the 9th National Forest Inventory (NFI) of China, was directed towards developing these models. After computing biomass and carbon storage per hectare using specific tree models for 34 species groups, we devised robust volume-derived biomass and carbon storage models for 20 forest types. The application of these models and historical data reveals notably a decline in China's forest carbon storage to 4.90Pg by the late 1970s due to aggressive forest exploitation. However, subsequent conservation and afforestation campaigns have affected a recovery, culminating in a storage of 8.69Pg by the 9th NFI. Over the past 40 years, China's forest carbon storage has surged by 3.79Pg, split between natural forests (2.25Pg) and planted forests (1.54Pg). In benchmarking against three pre-existing models, we discerned discernible biases, underscoring the need for larger modeling sample sizes. Overall, our models stand as a monumental stride in accurately gauging forest carbon storage fluctuations in China, both regionally and nationally.

Indexed as

CarbonForestsBiomassCarbon SequestrationChinaCarbon

Identifiers

PMID37803150
PMCPMC10558452

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Registered trials

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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.