基于CiteSpace 的国内外社区保护地研究进展分析.
Published In: Journal of Anhui Agricultural Sciences, 2026, v. 54, n. 4. P. 222 1 of 3
Database: Academic Search Ultimate 2 of 3
Authored By: 苏子豪; 周 琼; 闫文强; 罗斌圣; 胡仁传2∗ 3 of 3
Abstract
A visual analysis and review of the research literature on indigenous peoples' and community conserved territories and areas (ICCAs) at home and abroad from 1996 to 2024 were conducted based on the bibliometric method of CiteSpace and the core collection of China National Knowledge Network (CNKI) and Web of Science (WOS) as data sources. The results showed that: the annual number of papers published in the study of ICCAs at home and abroad showed an increasing trend and experienced three stages of initial development, fluctuating growth and rapid growth.2 Foreign studies focused on ethnic medicinal botany, invasive alien species control, community well-being and sus-tainable livelihood strategies, soil and biome ecology, and ecosystem service evaluation. Community protection strategies, ecosystem services, and global biodiversity framework were current hot research areas. 3 Domestic research focused on community conservation behavior and cognition, resource protection and sustainable use, management and legal standardization. Community participation and protection intention of ICCAs, construction of national park system, and rural revitalization strategy were the latest research hotspots. This research provides theoretical reference and direction for further research on ICCAs in China. [ABSTRACT FROM AUTHOR]
Additional Information
- Source:Journal of Anhui Agricultural Sciences. 2026/02, Vol. 54, Issue 4, p222
- Document Type:Article
- Subject Area:Social Sciences and Humanities
- Publication Date:2026
- ISSN:0517-6611
- DOI:10.3969/j.issn.0517-6611.2026.04.042
- Accession Number:192239716
- Copyright Statement:Copyright of Journal of Anhui Agricultural Sciences is the property of Journal of Anhui Agricultural Sciences Editorial Office and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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