Evolution of spatial network structure for land-use carbon emissions and carbon balance zoning in Jiangxi Province: A social network analysis perspective

分区 碳汇 土地利用 空间生态学 社会网络分析 共同空间格局 地理 环境科学 自然地理学 经济地理学 生态学 气候变化 计算机科学 政治学 万维网 社会化媒体 法学 生物
作者
H. Huang,Junsong Jia,Dilan Chen,Shuting Liu
出处
期刊:Ecological Indicators [Elsevier BV]
卷期号:158: 111508-111508 被引量:12
标识
DOI:10.1016/j.ecolind.2023.111508
摘要

Exploring the spatial network structure of land-use carbon emissions (LUCE) and the carbon balance in developing regions is pivotal for climate change mitigation in these areas. Using socio-economic and land-use data from 2000 to 2020, this study focused on Jiangxi Province as a representative case to elucidate the spatial network structure of LUCE and conduct carbon balance zoning. The primary findings were as follows: (1) The LUCE distribution in Jiangxi Province demonstrated a spatial pattern with high values in the northwest and low values in the southeast. An increasing trend was observed in the total amount of LUCE. Furthermore, there were evident regional differences in the Ecological Support Coefficient (ESC), indicating a weakening regional carbon sink capacity. (2) The spatial network structure of LUCE was intricate but stable. Although the gravitational interactions of LUCE between cities have intensified, overall network connectivity remained moderately correlated, indicating a prominent regional development imbalance. (3) There was a pronounced “core-periphery” structure in the LUCE spatial correlation network. Northern Jiangxi was the “core” of the network, taking an “initiator” role, whereas most cities in southern Jiangxi played a “passive” role, and resided at the “periphery” of the network. The inter-regional LUCE network exhibited pronounced spatial spillover, with inter-block correlations surpassing those within blocks. (4) By leveraging empirical data and spatial metrics, we categorized Jiangxi Province into five distinct carbon balance zoning types and subsequently proposed land-use optimization strategies. From the perspective of social network analysis (SNA), this study offers methodological insights into low-carbon development and synergistic emission reduction in developing regions.
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