Wilderness beyond the natural: Mapping urban novel wilderness to support ecological conservation and recreational provision in rapidly urbanizing areas DOI Creative Commons
Lei Shen,

Duanqiang Zhai,

Chang Li

et al.

Ecological Indicators, Journal Year: 2024, Volume and Issue: 170, P. 112953 - 112953

Published: Dec. 15, 2024

Language: Английский

Identifying and rebuilding a spatial network of wildlands to promote rewilding on the Qinghai‒Tibet Plateau DOI
Pingxing Li,

Liang Xin,

Chenzhen Gao

et al.

Applied Geography, Journal Year: 2025, Volume and Issue: 179, P. 103612 - 103612

Published: April 9, 2025

Language: Английский

Citations

0

How did the diversity of woody plants in urban forests vary with the urban-rural gradient in Qingdao, China? DOI Creative Commons
Ruirui Zhu,

Danping Xiu,

Ruixin Xue

et al.

Heliyon, Journal Year: 2024, Volume and Issue: 10(18), P. e36901 - e36901

Published: Aug. 30, 2024

The distribution and diversity of woody vegetation are crucial for understanding the structure ecology urban forests. As urbanization accelerates, construction composition forests vary significantly along urban-rural gradient. Qingdao's offer an opportunity to test relationship between plants We classified gradient using imperviousness time, then investigated in under different gradients tested reasonableness their allocation. Correlation analysis found that index was highly connected (by imperviousness: r

Language: Английский

Citations

2

Characteristics of Spatial Correlation Network Structure and Carbon Balance Zoning of Land Use Carbon Emission in the Tarim River Basin DOI Creative Commons

Zhe Gao,

Jianming Ye,

Xiaoxue Zhu

et al.

Land, Journal Year: 2024, Volume and Issue: 13(11), P. 1952 - 1952

Published: Nov. 19, 2024

An accurate understanding of the structure spatial correlation networks land use carbon emissions (LUCEs) and balance zoning plays a guiding role in promoting regional emission reductions achieving high-quality coordinated development. In this study, 42 counties Tarim River Basin from 2002 to 2022 were chosen as samples (Corps cities excluded due missing statistics). The LUCE network characteristics analyzed by using Ecological Support Coefficient (ESC), Social Network Analysis (SNA), Spatial Clustering Data (SCDA), targeted optimization strategy was proposed for each zone. results study indicate following: (1) LUCEs showed an overall upward trend, but increase gradually slowed down, presenting characteristic “high mid-north low at edges”. addition, ESC decreasing with opposite that LUCEs. (2) With increasingly close Basin, presented better accessibility stability, individual differed significantly. Aksu City, Korla Bachu County, Shache Hotan Kuqa which center network, displayed remarkable ability control master correlation. (3) Based on analysis, subdivided into six functional zones synergistic reduction strategies zone promote fair efficient low-carbon transformational development among regions.

Language: Английский

Citations

1

Constructing habitat networks to protect endangered migratory birds in the Jiaozhou Bay area DOI Creative Commons
Xinyu Liu, Ye Zhao, Lin Fan

et al.

Global Ecology and Conservation, Journal Year: 2024, Volume and Issue: unknown, P. e03380 - e03380

Published: Dec. 1, 2024

Language: Английский

Citations

1

Construction and optimization of wilderness network connectivity to address landscape fragmentation in Zhejiang Province, China DOI
Xiyu Wang, Xinyuan Huang,

Jiawen Guan

et al.

Journal for Nature Conservation, Journal Year: 2024, Volume and Issue: 81, P. 126703 - 126703

Published: Aug. 23, 2024

Language: Английский

Citations

0

Wilderness beyond the natural: Mapping urban novel wilderness to support ecological conservation and recreational provision in rapidly urbanizing areas DOI Creative Commons
Lei Shen,

Duanqiang Zhai,

Chang Li

et al.

Ecological Indicators, Journal Year: 2024, Volume and Issue: 170, P. 112953 - 112953

Published: Dec. 15, 2024

Language: Английский

Citations

0