Evidence map›Paper›PMID 41112030›Full record

ArticleEcology and evolution2025

Evaluation of the Effectiveness of Regulatory Measures for the Use of Natural Ecological Space Based on the Remote Sensing-Driven PLUS-InVEST Model: A Case Study From the Central Mountainous Area of Hainan Island.

Jiceng Xu, Xiaodong Mu, Ziwei Ma

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. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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.

Jiceng XuHainan Research Academy of Environmental Sciences Haikou China.ORCID https://orcid.org/0009-0006-0252-4264
Xiaodong MuHainan Research Academy of Environmental Sciences Haikou China.
Ziwei MaHainan Research Academy of Environmental Sciences Haikou China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Unreasonable reclamation and construction activities have led to a decline in habitat quality and loss of biodiversity in tropical rainforest areas, especially in key biodiversity regions globally. To evaluate the effectiveness of natural ecological space use regulation measures, in this study, the remote sensing data-driven PLUS-InVEST coupled model was used to evaluate and forecast the habitat quality and degree of degradation in the central mountainous region of Hainan Island, a global biodiversity hotspot. By setting natural ecological space use control measures, namely Ecological Conservation Redline, the spatiotemporal variations in land use/land cover and habitat quality were investigated under two regulatory scenarios: natural development (ND) and ecological priority (EP). The study revealed that: (1) Under the natural development (ND) regulatory scenario, from 2007 to 2021, artificial ecosystems such as farmland, water bodies, and construction land showed an increasing trend, while natural ecosystems such as forests, shrubs, and grasslands exhibited a decreasing trend in the study area. (2) Between 2007 and 2021, the habitat quality in the study area exhibited a decreasing trend, with a total reduction of 3.12%. (3) From 2021 to 2035, compared to the natural development (ND) scenario, under the ecological priority (EP) regulatory scenario, influenced by the Ecological Conservation Redline, the area of natural ecosystems in the study area showed an increasing trend, with an overall improvement in habitat quality by 0.34%, an increase in excellent quality habitat area of 57.12 km

Indexed as

central mountainous area of Hainan Islandhabitat qualityInVEST modelPLUS modeltropical rainforest area

Identifiers

PMID41112030
PMCPMC12530845

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.