Z. B. Yu, S. Yin, J. H. Bai, C. Wang, G. Z. Chen, W. Wang, Y. Q. Wang, B. S. Cui, X. H. Liu, X. W. Li
{"title":"Suaeda salsa in Relation to Hydrological Connectivity: From the View of Plant Trait Networks","authors":"Z. B. Yu, S. Yin, J. H. Bai, C. Wang, G. Z. Chen, W. Wang, Y. Q. Wang, B. S. Cui, X. H. Liu, X. W. Li","doi":"10.3808/jei.41-49","DOIUrl":null,"url":null,"abstract":"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.\n","PeriodicalId":54840,"journal":{"name":"Journal of Environmental Informatics","volume":"299 1","pages":""},"PeriodicalIF":6.0000,"publicationDate":"2024-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Environmental Informatics","FirstCategoryId":"93","ListUrlMain":"https://doi.org/10.3808/jei.41-49","RegionNum":1,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENVIRONMENTAL SCIENCES","Score":null,"Total":0}
引用次数: 0
Abstract
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.
期刊介绍:
Journal of Environmental Informatics (JEI) is an international, peer-reviewed, and interdisciplinary publication designed to foster research innovation and discovery on basic science and information technology for addressing various environmental problems. The journal aims to motivate and enhance the integration of science and technology to help develop sustainable solutions that are consensus-oriented, risk-informed, scientifically-based and cost-effective. JEI serves researchers, educators and practitioners who are interested in theoretical and/or applied aspects of environmental science, regardless of disciplinary boundaries. The topics addressed by the journal include:
- Planning of energy, environmental and ecological management systems
- Simulation, optimization and Environmental decision support
- Environmental geomatics - GIS, RS and other spatial information technologies
- Informatics for environmental chemistry and biochemistry
- Environmental applications of functional materials
- Environmental phenomena at atomic, molecular and macromolecular scales
- Modeling of chemical, biological and environmental processes
- Modeling of biotechnological systems for enhanced pollution mitigation
- Computer graphics and visualization for environmental decision support
- Artificial intelligence and expert systems for environmental applications
- Environmental statistics and risk analysis
- Climate modeling, downscaling, impact assessment, and adaptation planning
- Other areas of environmental systems science and information technology.