Evidence map›Paper›PMID 40225892›Full record

ArticleEcology and evolution2025

Evaluation of Ecosystem Service Capacity Using the Integrated Ecosystem Services Index at Optimal Scale in Central Yunnan, China.

Lanfang Liu, Jinliang Wang, Jie Li, Suling He, Yongcui Lan, Fang Liu

Abstract read
In one paragraph

Article in Ecology and evolution, 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
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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

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

6 authors.

Lanfang LiuFaculty of Geography Yunnan Normal University Kunming China.ORCID https://orcid.org/0009-0002-2924-3594
Jinliang WangFaculty of Geography Yunnan Normal University Kunming China.ORCID https://orcid.org/0000-0001-7202-646X
Jie LiFaculty of Geography Yunnan Normal University Kunming China.
Suling HeFaculty of Geography Yunnan Normal University Kunming China.
Yongcui LanFaculty of Geography Yunnan Normal University Kunming China.
Fang LiuFaculty of Geography Yunnan Normal University Kunming China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Understanding and quantifying the dynamic features of local ecosystem services (ESs) and integrating diverse ecosystem assessment results form crucial foundations for regional ES management. However, existing methods for integrating and objectively evaluating multiple ESs remain limited. Consequently, this research evaluates four key services based on the InVEST and RUSLE models in the Central Yunnan Province (CYP)-from 2000 to 2020: water yield (WY), carbon storage (CS), habitat quality (HQ), and soil conservation (SC). It then constructs an Integrated Ecosystem Service Index (IESI) using principal component analysis (PCA). Additionally, this study explores the factors driving the spatial divergence of ESs by employing the optimal parameter-based geographical detector model (OPGD) at the optimal spatial scale. The results indicated that (1) the IESI was effectively applied in the CYP and could quantitatively and comprehensively integrate the assessment results of the four key ESs. (2) During the study period, the ESs in the CYP showed increasing trends for WY, HQ, and SC, while CS showed a decreasing trend. (3) The IESI during the study period exhibited a trend of initially decreasing and then increasing. The average IESI values for CYP were 0.7338 in 2000, 0.6981 in 2005, 0.6947 in 2010, 0.6650 in 2015, and 0.6992 in 2020. (4) A 4500 m × 4500 m grid was identified as the optimal spatial scale for detecting the spatial divergence of comprehensive ecosystem service (CES) in CYP, and relief degree of land surface (RDLS), slope, and the NDVI were the top three drivers based on q-values. This study offers a more scientific and effective method for evaluating regional CES. It also provides a comprehensive analytical tool for balancing land use competition and assessing the effectiveness of policy implementation.

Indexed as

driving force analysisIntegrated Ecosystem Service Index (IESI)InVEST modelscale effectthe Central Yunnan Province (CYP)

Identifiers

PMID40225892
PMCPMC11992009

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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.