气候变化领域集成服务门户(CCPortal): Spatial mapping of key plant functional traits in terrestrial ecosystems across China

CCPortal

DOI	10.5194/essd-16-1771-2024
	Spatial mapping of key plant functional traits in terrestrial ecosystems across China
	An, Nannan; Lu, Nan; Chen, Weiliang; Chen, Yongzhe; Shi, Hao; Wu, Fuzhong; Fu, Bojie
发表日期	2024
ISSN	1866-3508
EISSN	1866-3516
起始页码	16
结束页码	4
卷号	16 期号:4
英文摘要	Trait-based approaches are of increasing concern in predicting vegetation changes and linking ecosystem structures to functions at large scales. However, a critical challenge for such approaches is acquiring spatially continuous plant functional trait maps. Here, six key plant functional traits were selected as they can reflect plant resource acquisition strategies and ecosystem functions, including specific leaf area (SLA), leaf dry matter content (LDMC), leaf N concentration (LNC), leaf P concentration (LPC), leaf area (LA) and wood density (WD). A total of 34 589 in situ trait measurements of 3447 seed plant species were collected from 1430 sampling sites in China and were used to generate spatial plant functional trait maps (similar to 1 km), together with environmental variables and vegetation indices based on two machine learning models (random forest and boosted regression trees). To obtain the optimal estimates, a weighted average algorithm was further applied to merge the predictions of the two models to derive the final spatial plant functional trait maps. The models showed good accuracy in estimating WD, LPC and SLA, with average R-2 values ranging from 0.48 to 0.68. In contrast, both the models had weak performance in estimating LDMC, with average R-2 values less than 0.30. Meanwhile, LA showed considerable differences between the two models in some regions. Climatic effects were more important than those of edaphic factors in predicting the spatial distributions of plant functional traits. Estimates of plant functional traits in northeastern China and the Qinghai-Tibetan Plateau had relatively high uncertainties due to sparse samplings, implying a need for more observations in these regions in the future. Our spatial trait maps could provide critical support for trait-based vegetation models and allow exploration of the relationships between vegetation characteristics and ecosystem functions at large scales. The six plant functional trait maps for China with 1 km spatial resolution are now available at https://doi.org/10.6084/m9.figshare.22351498 (An et al., 2023).
语种	英语
WOS研究方向	Geology ; Meteorology & Atmospheric Sciences
WOS类目	Geosciences, Multidisciplinary ; Meteorology & Atmospheric Sciences
WOS记录号	WOS:001199997000001
来源期刊	EARTH SYSTEM SCIENCE DATA
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/304461
作者单位	Fujian Normal University; Chinese Academy of Sciences; Research Center for Eco-Environmental Sciences (RCEES); Chinese Academy of Sciences; University of Chinese Academy of Sciences, CAS; University of Hong Kong
推荐引用方式 GB/T 7714	An, Nannan,Lu, Nan,Chen, Weiliang,et al. Spatial mapping of key plant functional traits in terrestrial ecosystems across China[J],2024,16(4).
APA	An, Nannan.,Lu, Nan.,Chen, Weiliang.,Chen, Yongzhe.,Shi, Hao.,...&Fu, Bojie.(2024).Spatial mapping of key plant functional traits in terrestrial ecosystems across China.EARTH SYSTEM SCIENCE DATA,16(4).
MLA	An, Nannan,et al."Spatial mapping of key plant functional traits in terrestrial ecosystems across China".EARTH SYSTEM SCIENCE DATA 16.4(2024).