1
|
Dong WJ, Xu MD, Yang XW, Yang XM, Long XZ, Han XY, Cui LY, Tong Q. Rice straw ash and amphibian health: A deep dive into microbiota changes and potential ecological consequences. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 926:171651. [PMID: 38490417 DOI: 10.1016/j.scitotenv.2024.171651] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/19/2023] [Revised: 03/05/2024] [Accepted: 03/09/2024] [Indexed: 03/17/2024]
Abstract
Rice straw is burned as a result of agricultural practices and technical limitations, generating significant volumes of ash that might have environmental and ecological consequences; however, the effects on organisms have not been researched. Amphibians depend on their gut and skin microbiomes. Ash exposure may cause inflammation and changes in microbial diversity and function in frogs' skin and gut microbiota due to its chemical composition and physical presence, but the implications remain unclear. Rana dybowskii were exposed to five aqueous extracts of ashes (AEA) concentrations for 30 days to study survival, metal concentrations, and microbial diversity, analyzing the microbiota of the cutaneous and gut microbiota using Illumina sequencing. Dominant elements in ash: K > Ca > Mg > Na > Al > Fe. In AEA, K > Na > Ca > Mg > As > Cu. Increased AEA concentrations significantly reduced frog survival. Skin microbiota alpha diversity varied significantly among all treatment groups, but not gut microbiota. Skin microbiota differed significantly across treatments via Bray-Curtis and weighted UniFrac; gut microbiota was only affected by Bray-Curtis. Skin microbiota varied significantly with AEA levels in Proteobacteria, Bacteroidetes, Actinobacteria, and Firmicutes, while the gut microbiota's dominant phyla, Firmicutes, Bacteroidetes, and Proteobacteria, remained consistent across all groups. Lastly, the functional prediction showed that the skin microbiota had big differences in how it worked and looked, which were linked to different health and environmental adaptation pathways. The gut microbiota, on the other hand, had smaller differences. In conclusion, AEA exposure affects R. dybowskii survival and skin microbiota diversity, indicating potential health and ecological impacts, with less effect on gut microbiota.
Collapse
Affiliation(s)
- Wen-Jing Dong
- School of Biology and Agriculture, Jiamusi University, Jiamusi 154007, China
| | - Ming-da Xu
- School of Biology and Agriculture, Jiamusi University, Jiamusi 154007, China
| | - Xue-Wen Yang
- School of Biology and Agriculture, Jiamusi University, Jiamusi 154007, China
| | - Xiu-Mei Yang
- College of Veterinary Medicine, Northeast Agricultural University, Harbin 150030, China
| | - Xin-Zhou Long
- School of Biology and Agriculture, Jiamusi University, Jiamusi 154007, China
| | - Xiao-Yun Han
- School of Biology and Agriculture, Jiamusi University, Jiamusi 154007, China
| | - Li-Yong Cui
- School of Biology and Agriculture, Jiamusi University, Jiamusi 154007, China
| | - Qing Tong
- School of Biology and Agriculture, Jiamusi University, Jiamusi 154007, China; College of Veterinary Medicine, Northeast Agricultural University, Harbin 150030, China.
| |
Collapse
|
2
|
An Z, Chen F, Zheng Y, Zhou J, Liu B, Qi L, Lin Z, Yao C, Wang B, Wang Y, Li X, Yin G, Dong H, Liang X, Liu M, Hou L. Role of n-DAMO in Mitigating Methane Emissions from Intertidal Wetlands Is Regulated by Saltmarsh Vegetations. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2024; 58:1152-1163. [PMID: 38166438 DOI: 10.1021/acs.est.3c07882] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/04/2024]
Abstract
Coastal wetlands are hotspots for methane (CH4) production, reducing their potential for global warming mitigation. Nitrite/nitrate-dependent anaerobic methane oxidation (n-DAMO) plays a crucial role in bridging carbon and nitrogen cycles, contributing significantly to CH4 consumption. However, the role of n-DAMO in reducing CH4 emissions in coastal wetlands is poorly understood. Here, the ecological functions of the n-DAMO process in different saltmarsh vegetation habitats as well as bare mudflats were quantified, and the underlying microbial mechanisms were explored. Results showed that n-DAMO rates were significantly higher in vegetated habitats (Scirpus mariqueter and Spartina alterniflora) than those in bare mudflats (P < 0.05), leading to an enhanced contribution to CH4 consumption. Compared with other habitats, the contribution of n-DAMO to the total anaerobic CH4 oxidation was significantly lower in the Phragmites australis wetland (15.0%), where the anaerobic CH4 oxidation was primarily driven by ferric iron (Fe3+). Genetic and statistical analyses suggested that the different roles of n-DAMO in various saltmarsh wetlands may be related to divergent n-DAMO microbial communities as well as environmental parameters such as sediment pH and total organic carbon. This study provides an important scientific basis for a more accurate estimation of the role of coastal wetlands in mitigating climate change.
Collapse
Affiliation(s)
- Zhirui An
- State Key Laboratory of Estuarine and Coastal Research, Yangtze Delta Estuarine Wetland Ecosystem Observation and Research Station, Ministry of Education & Shanghai, East China Normal University, Shanghai 200241, China
| | - Feiyang Chen
- Research Center for Monitoring and Environmental Sciences, Taihu Basin & East China Sea Ecological Environment Supervision and Administration Authority, Ministry of Ecology and Environment, Shanghai 200125, China
| | - Yanling Zheng
- State Key Laboratory of Estuarine and Coastal Research, Yangtze Delta Estuarine Wetland Ecosystem Observation and Research Station, Ministry of Education & Shanghai, East China Normal University, Shanghai 200241, China
- School of Geographic Sciences, East China Normal University, Shanghai 200241, China
- Key Laboratory of Geographic Information Science (Ministry of Education), East China Normal University, Shanghai 200241, China
- Key Laboratory of Spatial-temporal Big Data Analysis and Application of Natural Resources in Megacities, Ministry of Natural Resources, Shanghai 200241, China
| | - Jie Zhou
- State Key Laboratory of Estuarine and Coastal Research, Yangtze Delta Estuarine Wetland Ecosystem Observation and Research Station, Ministry of Education & Shanghai, East China Normal University, Shanghai 200241, China
| | - Bolin Liu
- State Key Laboratory of Estuarine and Coastal Research, Yangtze Delta Estuarine Wetland Ecosystem Observation and Research Station, Ministry of Education & Shanghai, East China Normal University, Shanghai 200241, China
| | - Lin Qi
- School of Geographic Sciences, East China Normal University, Shanghai 200241, China
| | - Zhuke Lin
- School of Geographic Sciences, East China Normal University, Shanghai 200241, China
| | - Cheng Yao
- School of Geographic Sciences, East China Normal University, Shanghai 200241, China
| | - Bin Wang
- State Key Laboratory of Estuarine and Coastal Research, Yangtze Delta Estuarine Wetland Ecosystem Observation and Research Station, Ministry of Education & Shanghai, East China Normal University, Shanghai 200241, China
| | - Yixuan Wang
- School of Geographic Sciences, East China Normal University, Shanghai 200241, China
| | - Xiaofei Li
- State Key Laboratory of Estuarine and Coastal Research, Yangtze Delta Estuarine Wetland Ecosystem Observation and Research Station, Ministry of Education & Shanghai, East China Normal University, Shanghai 200241, China
| | - Guoyu Yin
- School of Geographic Sciences, East China Normal University, Shanghai 200241, China
- Key Laboratory of Geographic Information Science (Ministry of Education), East China Normal University, Shanghai 200241, China
- Key Laboratory of Spatial-temporal Big Data Analysis and Application of Natural Resources in Megacities, Ministry of Natural Resources, Shanghai 200241, China
| | - Hongpo Dong
- State Key Laboratory of Estuarine and Coastal Research, Yangtze Delta Estuarine Wetland Ecosystem Observation and Research Station, Ministry of Education & Shanghai, East China Normal University, Shanghai 200241, China
| | - Xia Liang
- State Key Laboratory of Estuarine and Coastal Research, Yangtze Delta Estuarine Wetland Ecosystem Observation and Research Station, Ministry of Education & Shanghai, East China Normal University, Shanghai 200241, China
| | - Min Liu
- School of Geographic Sciences, East China Normal University, Shanghai 200241, China
- Key Laboratory of Geographic Information Science (Ministry of Education), East China Normal University, Shanghai 200241, China
- Key Laboratory of Spatial-temporal Big Data Analysis and Application of Natural Resources in Megacities, Ministry of Natural Resources, Shanghai 200241, China
| | - Lijun Hou
- State Key Laboratory of Estuarine and Coastal Research, Yangtze Delta Estuarine Wetland Ecosystem Observation and Research Station, Ministry of Education & Shanghai, East China Normal University, Shanghai 200241, China
| |
Collapse
|