Evidence map›Paper›PMID 41174022›Full record

ArticleScientific reports2025

Scenario based assessment of carbon storage and habitat quality under land use change in Shandong Province China.

Kechen Lyu, Zhengjun Li

Abstract read
In one paragraph

Article in Scientific reports, 2025. 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

2 authors.

Kechen LyuSchool of civil engineering and geomatics, Shandong University of Technology, Zibo, 255000, Shandong, China.
Zhengjun LiSchool of civil engineering and geomatics, Shandong University of Technology, Zibo, 255000, Shandong, China. lizhengjun1017@sdut.edu.cn.

Funding

National Natural Science Foundation of China 42471239
6 · The paper itself

Abstract

Land-use change exerts a profound influence on ecosystem services (ES), and accurately assessing its spatiotemporal dynamics is essential for achieving regional sustainability. Taking Shandong Province as a case study, this research integrates the PLUS and InVEST models to simulate the impacts of land-use changes on carbon storage and habitat quality in Shandong Province between 2000 and 2020, and to project their dynamics under different scenarios for 2030. The InVEST (Integrated Valuation of Ecosystem Services and Tradeoffs) model was employed to reassess variations in carbon storage (CS) and habitat quality (HQ). The main findings are as follows: (1) Cultivated land decreased by 12.3%, while construction land expanded by 51.04%, predominantly replacing farmland and forested areas, resulting in a distinct spatial pattern characterized by an "urbanized east and agricultural west." (2) Carbon storage declined by approximately 63 million tons, primarily due to urban expansion. (3) Habitat quality experienced a 3.6% decrease, with significant ecological fragmentation identified in the central mountainous regions and the Yellow River Delta, driven by intensified urbanization and agricultural activities. (4) Future scenario simulations indicate that under the ecological conservation scenario, carbon storage could increase by 12.5% and habitat quality could reach 0.572 by 2040; in contrast, the natural development scenario suggests ongoing degradation. These findings highlight the trade-offs between land development and ecosystem services, emphasizing the necessity of reinforcing ecological zoning, compensation mechanisms, and the establishment of ecological corridors. This study provides a scientific basis for advancing sustainable land-use planning and ecosystem management.

Indexed as

Carbon storageEcosystem servicesHabitat qualityInVEST modelLand use changePLUS model

Identifiers

PMID41174022
PMCPMC12578880

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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.