Evidence map›Paper›PMID 38828330›Full record

ArticleHeliyon2024

Urban landscape sustainability in karst mountainous cities: A landscape resilience perspective.

Chao Wu, Yuan Su, Zhijie Wang

Abstract read
In one paragraph

Article in Heliyon, 2024. 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

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

2 citing papers in PubMed.

  1. Article
  2. 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.

Chao WuKey Laboratory of Plant Resource Conservation and Germplasm Innovation in Mountainous Region (Ministry of Education), College of Life Sciences/Institute of Agro-bioengineering, Guizhou University, Guiyang, 550025, Guizhou Province, China.
Yuan SuCollege of Forestry, Guizhou University, Guiyang, 550025, China.
Zhijie WangKey Laboratory of Plant Resource Conservation and Germplasm Innovation in Mountainous Region (Ministry of Education), College of Life Sciences/Institute of Agro-bioengineering, Guizhou University, Guiyang, 550025, Guizhou Province, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In the context of the rapid progress of global urbanization, the massive encroachment of social landscapes into ecological and productive landscapes has led to a series of environmental problems. Furthermore, analyzing the landscape resilience could effectively reveal the sustainable development ability of the urban landscape. This study establishes a social-ecological productive landscape resilience (SEPLR) evaluation system and reveals trade-offs and synergies between different landscape types and resilience. Finally, this study provides landscape management zonings based on the spatial and temporal dynamic characteristics of landscape resilience and subsystem resilience. The findings showed that: (1) The CUAG has significant landscape heterogeneity and change drastically, which is mainly manifested by the massive encroachment of social landscape into productive landscape. (2) The SEPLR of CUAG decreased slightly by 0.75 % over the decade, with significant changes of spatial distribution. (3) The comprehensive remediation areas and social development areas are the dominant management zones. The findings could be incorporated into the decision-making of land use trade-off development in CUAG to promote the coordinated development of social-ecological productive systems and improve the sustainability of urban landscape.

Indexed as

Landscape management zonesLandscape patternSocial-ecological productive landscape resilience

Identifiers

PMID38828330
PMCPMC11140713

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.