CPSDv0: a forest stand structure database for plantation forests in China

• Published in: Big earth data Vol. 7; no. 1; pp. 212 - 230
• Main Authors: Wu, Xiuchen, Jiang, Xiaofei, Liu, Hongyan, Allen, Craig, Li, Xiaoyan, Wang, Pei, Li, Zongshan, Yang, Yuting, Zhang, Shulei, Shi, Fangzhong, Zhu, Jiaojun, Yu, Pengtao, Zhou, Mei, Zhao, Pengwu, Wang, Yanhui, Yue, Chao, Chen, Deliang
• Format: Journal Article
• Language: English
• Published: Taylor & Francis 02.01.2023; Taylor & Francis Group
• Subjects: afforestation; canopy coverage; climate-change; Computer and Information Science; Computer Science; Data- och informationsvetenskap; density; drivers; drought; Geologi; Geology; pine; plantation; poplar plantation; productivity; regimes; Remote Sensing; stand density; Stand structure; tree age; tree height; tree mortality
• ISSN: 2096-4471; 2574-5417
• DOI: 10.1080/20964471.2021.2012911

Forest stand structure is not only a crucial factor for regulating forest functioning but also an important indicator for sustainable forest management and ecosystem services. Although there exists a few national/global structure databases for natural forests, a country-wide synthetic structure database for plantation forests over China, the world's largest player in plantation forests, has not been achieved. In this study, we built a country-wide synthetic stand structure database by surveying more than 600 peer-reviewed literature. The database covers tree species, mean stand age, mean tree height, stand density, canopy coverage, diameter at breast height, as well as the associated ancillary in-situ topographical and soil properties. A total of 594 published studies concerning diverse forest stand structure parameters were compiled for 46 tree species. This first synthesis for stand structure of plantation forests over China supports studies on the evolution/health of plantation forests in response to rapid climate change and intensified disturbances, and benefits country-wide sustainable forest management, future afforestation or reforestation planning. Potential users include those studying forest community dynamics, regional tree growth, ecosystem stability, and health, as well as those working with conservation and sustainable management. This dataset is freely accessible at http://www.doi.org/10.11922/sciencedb.j00076.00091 .