萨尔萨
特质
中心性
计算机科学
环境科学
数学
统计
土壤科学
程序设计语言
格林威治
作者
Zhangbin Yu,Shen Yin,Junhong Bai,Cuizhen Wang,George Z. Chen,Weidong Wang,Yao Wang,Baoshan Cui,Xinxin Liu,X. W. Li
出处
期刊:Journal of Environmental Informatics
[International Society for Environmental Information Sciences]
日期:2024-01-01
标识
DOI:10.3808/jei.202400507
摘要
How plant traits respond to environment changes has been given more concerns worldwide. However, it is hard to reveal the integrative responses of plants only based on independent plant traits without considering the close links among plant traits. Plant trait network (PTN) is emerging as a new way to study how plant traits adapt to changing environment and to find out the key plant trait. We collected soil and plant samples from five sampling zones in Suaeda salsa wetlands of the Yellow River Delta in China to construct hydrological connectivity index (HCI) by principal component analysis of eight indicators. PTNs were estimated by network analysis of nine plant traits. The results showed that five study areas had significant different HCIs. The PTNs showed the max tightness in areas with medium HCI and the complexity of PTNs decreased with the rise of HCI. Generally, PTNs exhibited the best performance in the areas with medium HCI in which were the most appropriate for plants to grow. Plant aboveground biomass was the central trait PTNs since it had a high degree as well as betweenness centrality. The findings indicate that Suaeda salsa takes different growth strategies under different hydrological connectivity conditions. Suaeda salsa enhanced the connections of different traits in areas which were the best for plants to grow while Suaeda salsa formed different groups of function modules in areas where hydrological connectivity was weak. This study may give new sights on how plant response to the change of hydrological connectivity.
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