Evidence map›Paper›PMID 39854555›Full record

ArticlePloS one2025

Multi-scenario land use change simulation and spatial-temporal evolution of carbon storage in the Yangtze River Delta region based on the PLUS-InVEST model.

Jingru Zhou, Verner Carl Johnson, Jingchao Shi, Mou Leong Tan, Fei Zhang

Abstract read
In one paragraph

Article in PloS one, 2025. 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

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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
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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

5 authors.

Jingru ZhouCollege of Geography and Environmental Sciences, Zhejiang Normal University, Jinhua, China.
Verner Carl JohnsonDepartment of Physical and Environmental Sciences, Colorado Mesa University, Grand Junction, CO, United States of America.
Jingchao ShiDepartments of Earth Sciences, the University of Memphis, Memphis, TN, United States of America.
Mou Leong TanGeo-Informatic Unit, Geography Section, School of Humanities, University Sains Malaysia, Penang, Malaysia.
Fei ZhangCollege of Geography and Environmental Sciences, Zhejiang Normal University, Jinhua, China.ORCID 0000-0003-3817-3217

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Influenced by urban expansion, population growth, and various socio-economic activities, land use in the Yangtze River Delta (YRD) area has undergone prominent changes. Modifications in land use have resulted in adjustments to ecological structures, leading to subsequent fluctuations in carbon storage. This study focuses on YRD region and analyzes the characteristics of land use changes in the area using land use data from 2000 to 2020, with a 10-year interval. Utilizing InVEST Model's Carbon Storage module in combination with PLUS model (patch-generating land use simulation), we simulated and projected future land use patterns and carbon storage across YRD region under five scenarios including natural development (ND), urban development (UD), ecological protection (EP), cropland protection (CP), and balanced development (BD). Upon comparing carbon storage levels predicted for 2030 under the five scenarios with those in 2020, carbon stocks decrease in the initial four scenarios and then increase in the fifth scenario. In the initial four declining scenarios, CP scenario had the least reduction in carbon storage, followed by EP scenario. The implementation of policies aimed at safeguarding cropland and preserving ecological integrity can efficaciously curtail the expansion of developed land into woodland and cropland, enhance the structure of land use, and mitigate the loss of carbon storage.

Indexed as

CarbonCarbon SequestrationConservation of Natural ResourcesModels, TheoreticalRiversChinaComputer SimulationEcosystemHumansSpatio-Temporal AnalysisUrbanizationCarbon

Identifiers

PMID39854555
PMCPMC11760564

What OpenQuestion holds

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LicenceCC BY
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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.