Characteristics of Microbial Carbon Utilization in Peat Pore Water in the Dajiuhu Peatland, Shennongjia
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摘要: 为研究水位波动下泥炭地微生物碳代谢特征,利用Biolog-Eco微平板技术对神农架大九湖不同水位下泥炭孔隙水中微生物的碳代谢图谱进行测定.结果表明,不同水位下微生物的碳代谢活性和多样性差异显著,均表现为中水位 > 低水位 > 高水位.酯类(丙酮酸甲酯、吐温40、吐温80、D-半乳糖酸γ内酯),氨基酸(L-精氨酸、L-天冬酰胺酸、L-苯基丙氨酸、L-丝氨酸和甘氨酰-L-谷氨酸),胺类(苯乙基胺、腐胺和N-乙酰基-D-葡萄胺)是引起微生物碳代谢差异的主要贡献者.冗余度分析显示,电导率(F=3.2,P=0.018)和氧化还原电位(F=2.6,P=0.044)显著影响微生物的碳代谢,其变化与水位波动密切相关.水位波动通过改变泥炭孔隙水中微生物的碳代谢功能进而影响泥炭地碳循环.Abstract: In order to investigate the characteristics of microbial carbon metabolic activity in peatlands with water table fluctuation, microbial community-level physiological profiling of peat pore water was determined with the different water table levels using Biolog-Eco microplate technology in the Dajiuhu Peatland, Shennongjia Forestry District. The results show that the rate and diversity of microbial carbon utilization at the mediate water table were the highest, followed by the low water table, with the lowest at the high water table. Esters (pyruvic acid methyl ester, Tween 40, Tween 80 and D-Galactonic acid γ-lactone), amino acids (L-arginine, L-asparagine, L-phenylalanine, L-serine and glycyl-L-glutamic acid) and amines (phenylethylamine, putrescine and N-acetyl-D-glucosamine) were the main contributors to the variations in microbial carbon utilization of peat pore water. Redundancy analysis and fitting regression model indicate that electrical conductivity (F=3.2, P=0.018) and oxidation-reduction potential (F=2.6, P=0.044) driven by water table level affected microbial carbon utilization of peat pore water. This study reveals the effect of water table fluctuation on microbial carbon utilization in peat pore water, which enriches our understanding of carbon cycle in peatlands in the context of global climate change.
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Key words:
- peatland /
- pore water /
- water table level /
- Biolog-Eco microplate /
- carbon utilization /
- carbon cycle /
- environmental microbiology
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图 3 不同水位下泥炭孔隙水中微生物对6类碳源利用的AWCD
缩写含义同图 2
Fig. 3. AWCD of six types carbon sources from microbial communities in peat pore water at different water table levels
图 4 泥炭孔隙水中微生物的碳代谢主成分分析(a)和冗余度分析(b)
ADONIS. 置换多元方差分析;ANOSIM. 相似性分析;MRPP. 多重响应排列程序分析;F、R和δ代表差异程度.实射线表示有显著性,虚射线代表无显著性.其余缩写同图 2
Fig. 4. Principle component of analysis (a) and redundancy analysis (b) of microbial carbon utilization from peat pore water
图 5 水位与电导率(a)和氧化还原电位(b)拟合回归
蓝色实线表示拟合曲线,灰色阴影代表95%的置信区,R2和P值表示拟合效果.缩写同图 2
Fig. 5. The fitting regression models between electric conductivity (a), oxidation-reduction potential (b) and water table level
表 1 不同水位下泥炭孔隙水理化性质
Table 1. Physiochemical properties of peat pore water with different water table levels
pH 电导率(µS/cm) 溶解氧(mg/L) 氧化还原电位(mV) 水温(℃) 水位(cm) 高水位 5.55±0.07c 20.37±2.27b 0.51±0.07c 123.0±12.2c 27.7±1.4a 2.7 中水位 5.88±0.15b 41.38±6.08a 1.52±0.36b 192.4±5.4b 25.6±0.5a ‒2.6 低水位 6.66 ±0.06a 16.26±3.32b 2.61±0.16a 221.7±7.5a 22.6±0.4b ‒8.1 注:同一列不同小写字母表示各指标组间差异显著,相同小写字母表示各指标组间无显著差异(α=0.05). 表 2 不同水位下泥炭孔隙水中微生物的AWCD和碳代谢功能多样性
Table 2. AWCD and functional diversity of carbon metabolic activity from microbial communities in peat pore water with different water table levels
AWCD Shannon多样性指数(H′) McIntosh多样性指数(U) 高水位 0.682±0.021b 3.02±0.04b 4.79±0.01b 中水位 0.906±0.058a 3.28±0.07a 5.61±0.19a 低水位 0.702±0.051b 3.08±0.05b 5.08±0.24b 注:同一列不同小写字母表示各指标在组间差异显著,相同小写字母表示各指标组间无显著差异(α=0.05). 表 3 不同水位下泥炭孔隙水中微生物的碳源利用比较
Table 3. Comparison of microbial carbon utilization in peat pore water at different water table levels
糖类 氨基酸类 胺类 酯类 羧酸类 醇类 高水位 0.517±0.075Cb 0.804±0.031Bb 0.623± 0.147BCa 1.123±0.038Aa 0.566±0.084BCb 0.630±0.093BCa 中水位 0.831±0.113BCa 1.153±0.123Aa 0.931±0.179ABa 1.198±0.048Aa 0.732±0.025BCa 0.584±0.070Ca 低水位 0.293±0.131Bb 0.868±0.166Aab 0.885±0.152Aa 0.998±0.050Ab 0.666±0.070ABab 0.779±0.216Aa 注:同一行不同大写字母表示各碳源利用率差异显著(α=0.05),相同大写字母表示各碳源利用率无显著差异;同一列不同小写字母表示各碳源利用率组间差异显著,相同小写字母表示各碳源利用率组间无显著差异(α=0.05). 表 4 31种碳源的主成分载荷因子
Table 4. Loading factor of principle components from 31 carbon sources
碳源化学类别 底物 化学式 PC1 PC2 糖类 D-木糖 C5H10O5 ‒0.247 0.276 α-D-乳糖 C12H24O12 -0.716 ‒0.280 ß-甲基D-葡萄糖苷 C7H14O6 0.244 0.499 葡萄糖-1-磷酸盐 C6H13O9P -0.928 0.097 α-环状糊精 C36H60O30 ‒0.381 0.113 肝糖 C24H42O21 0.132 ‒0.182 D-纤维二糖 C12H22O11 -0.523 0.690 氨基酸类 L-精氨酸 C6H14N4O2 ‒0.057 -0.865 L-天冬酰胺酸 C4H8N2O3 0.734 0.175 L-苯基丙氨酸 C9H11NO2 0.327 -0.774 L-丝氨酸 C3H7NO3 ‒0.116 0.554 L-苏氨酸 C4H9NO3 ‒0.315 0.021 甘氨酰-L-谷氨酸 C7H12N2O5 -0.485 ‒0.114 酯类 丙酮酸甲酯 C4H6O3 0.670 0.586 吐温40 -- 0.935 0.048 吐温80 -- 0.852 ‒0.226 D-半乳糖酸γ内酯 C6H10O6 -0.747 0.132 醇类 i-赤藻糖醇 C4H10O4 ‒0.247 0.361 D-甘露醇 C6H14O6 0.828 0.199 D, L-α-甘油 C3H8O3 0.426 0.239 胺类 苯乙基胺 C8H11N 0.024 -0.938 腐胺 C4H12N2 0.025 -0.433 N-乙酰基-D-葡萄胺 C8H15NO6 0.382 0.865 羧酸类 D-半乳糖醛酸 C6H10O7 0.077 0.850 D-氨基葡萄糖酸 C6H13NO6 ‒0.159 0.081 2-羟基苯甲酸 C7H6O2 ‒0.172 -0.413 4-羟基苯甲酸 C7H6O3 0.541 ‒0.089 γ-羟基丁酸 C4H8O3 0.089 ‒0.182 衣康酸 C5H6O4 ‒0.347 ‒0.270 α-丁酮酸 C4H6O3 ‒0.333 ‒0.016 D-苹果酸 C4H6O5 0.401 ‒0.053 注:粗体代表PC上载荷因子的绝对值大于0.4. 表 5 泥炭孔隙水理化性质对微生物碳代谢差异的贡献
Table 5. Contribution of physicochemical properties of peat pore water to variances in microbial carbon metabolism
变异解释量(%) F P 电导率 31.2 3.2 0.018* 氧化还原电位 20.6 2.6 0.044* 溶解氧 9.0 1.1 0.452 水温 10.5 1.5 0.398 pH 7.0 1.0 0.485 水位 9.9 1.7 0.398 注:F值表示差异程度;P值表示差异性;*表示P < 0.05. -
Barel, J. M., Moulia, V., Hamard, S., et al., 2021. Come Rain, Come Shine: Peatland Carbon Dynamics Shift under Extreme Precipitation. Frontiers in Environmental Science, 9: 659953. https://doi.org/10.3389/fenvs.2021.659953 Benoit, J. M., Shull, D. H., Harvey, R. M., et al., 2009. Effect of Bioirrigation on Sediment-Water Exchange of Methylmercury in Boston Harbor, Massachusetts. Environmental Science & Technology, 43(10): 3669-3674. https://doi.org/10.1021/es803552q Chen, H., Wu, N., Wang, Y. F., et al., 2021. A Historical Overview about Basic Issues and Studies of Mires. Science in China (Series D), 51(1): 15-26 (in Chinese with English abstract). Chen, Z., Li, Y. Z., Peng, Y. Y., et al., 2022. Feasibility of Sewage Sludge and Food Waste Aerobic Co-Composting: Physicochemical Properties, Microbial Community Structures, and Contradiction between Microbial Metabolic Activity and Safety Risks. The Science of the Total Environment, 825: 154047. https://doi.org/10.1016/j.scitotenv.2022.154047 Corzo, A., Jiménez-Arias, J. L., Torres, E., et al., 2018. Biogeochemical Changes at the Sediment–Water Interface during Redox Transitions in an Acidic Reservoir: Exchange of Protons, Acidity and Electron Donors and Acceptors. Biogeochemistry, 139(3): 241-260. https://doi.org/10.1007/s10533-018-0465-7 Fenner, N., Freeman, C., 2011. Drought-Induced Carbon Loss in Peatlands. Nature Geoscience, 4(12): 895-900. https://doi.org/10.1038/ngeo1323 Freeman, C., Ostle, N., Kang, H., 2001. An Enzymic 'Latch' on a Global Carbon Store. Nature, 409: 149. https://doi.org/10.1038/35051650 Garland, J. L., 1996. Analytical Approaches to the Characterization of Samples of Microbial Communities Using Patterns of Potential C Source Utilization. Soil Biology and Biochemistry, 28(2): 213-221. https://doi.org/10.1016/0038-0717(95)00112-3 Haapalehto, T., Kotiaho, J. S., Matilainen, R., et al., 2014. The Effects of Long-Term Drainage and Subsequent Restoration on Water Table Level and Pore Water Chemistry in Boreal Peatlands. Journal of Hydrology, 519: 1493-1505. https://doi.org/10.1016/j.jhydrol.2014.09.013 Hribljan, J. A., Kane, E. S., Pypker, T. G., et al., 2014. The Effect of Long-Term Water Table Manipulations on Dissolved Organic Carbon Dynamics in a Poor Fen Peatland. Journal of Geophysical Research: Biogeosciences, 119(4): 577-595. https://doi.org/10.1002/2013jg002527 Huang, X. Y., Zhang, Z. Q., Wang, H. M., et al., 2017. Overview on Critical Zone Observatory at Dajiuhu Peatland, Shennongjia. Earth Science, 42(6): 1026-1038 (in Chinese with English abstract). Järveoja, J., Peichl, M., Maddison, M., et al., 2016. Impact of Water Table Level on Annual Carbon and Greenhouse Gas Balances of a Restored Peat Extraction Area. Biogeosciences, 13(9): 2637-2651. https://doi.org/10.5194/bg-13-2637-2016 Kloss, S., Zehetner, F., Buecker, J., et al., 2015. Trace Element Biogeochemistry in the Soil-Water-Plant System of a Temperate Agricultural Soil Amended with Different Biochars. Environmental Science and Pollution Research, 22(6): 4513-4526. https://doi.org/10.1007/s11356-014-3685-y Kwon, M. J., Haraguchi, A., Kang, H., 2013. Long-Term Water Regime Differentiates Changes in Decomposition and Microbial Properties in Tropical Peat Soils Exposed to the Short-Term Drought. Soil Biology and Biochemistry, 60: 33-44. https://doi.org/10.1016/j.soilbio.2013.01.023 Liao, H. H., Yu, K., Duan, Y. H., et al., 2019. Profiling Microbial Communities in a Watershed Undergoing Intensive Anthropogenic Activities. The Science of the Total Environment, 647: 1137-1147. https://doi.org/10.1016/j.scitotenv.2018.08.103 Limpens, J., Berendse, F., Blodau, C., et al., 2008. Peatlands and the Carbon Cycle: From Local Processes to Global Implications-A Synthesis. Biogeosciences, 5(5): 1475-1491. https://doi.org/10.5194/bg-5-1475-2008 Liu, H. M., An, K. R., Wang, H., et al., 2020. Effects of Fertilization Regimes on the Metabolic Diversity of Microbial Carbon Sources in a Maize Field of Fluvoaquic Soil in North China. Journal of Agro-Environment Science, 39(10): 2336-2344 (in Chinese with English abstract). Luo, T., Lun, Z. J., Gu, Y. S., et al., 2015. Plant Community Survey and Ecological Protection of Dajiuhu Wetlands in Shennongjia Area. Wetland Science, 13(2): 153-160 (in Chinese with English abstract). Palansooriya, K. N., Wong, J. T. F., Hashimoto, Y., et al., 2019. Response of Microbial Communities to Biochar-Amended Soils: a Critical Review. Biochar, 1(1): 3-22. https://doi.org/10.1007/s42773-019-00009-2 Saunois, M., Stavert, A. R., Poulter, B., et al., 2020. The Global Methane Budget 2000–2017. Earth System Science Data, 12(3): 1561-1623. https://doi.org/10.5194/essd-12-1561-2020 Si, G. H., Yuan, J. F., Xu, X. Y., et al., 2018. Effects of an Integrated Rice-Crayfish Farming System on Soil Organic Carbon, Enzyme Activity, and Microbial Diversity in Waterlogged Paddy Soil. Acta Ecologica Sinica, 38(1): 29-35. https://doi.org/10.1016/j.chnaes.2018.01.005 Song, X. C., Wang, H. L., Qin, W. D., et al., 2019. Effects of Stand Type of Artificial Forests on Soil Microbial Functional Diversity. Chinese Journal of Applied Ecology, 30(3): 841-848 (in Chinese with English abstract). Tian, W., Wang, H. M., Xiang, X., et al., 2019. Structural Variations of Bacterial Community Driven by Sphagnum Microhabitat Differentiation in a Subalpine Peatland. Frontiers in Microbiology, 10: 1661-1671. https://doi.org/10.3389/fmicb.2019.01661 Tian, W., Xiang, X., Wang, H. M., 2021. Differential Impacts of Water Table and Temperature on Bacterial Communities in Pore Water from a Subalpine Peatland, Central China. Frontiers in Microbiology, 12: 649981. https://doi.org/10.3389/fmicb.2021.649981 Treat, C. C., Kleinen, T., Broothaerts, N., et al., 2019. Widespread Global Peatland Establishment and Persistence over the last 130, 000 Y. Proceedings of the National Academy of Sciences of the United States of America, 116(11): 4822-4827. https://doi.org/10.1073/pnas.1813305116 Ulanowski, T. A., Branfireun, B. A., 2013. Small-Scale Variability in Peatland Pore-Water Biogeochemistry, Hudson Bay Lowland, Canada. The Science of the Total Environment, 454-455: 211-218. https://doi.org/10.1016/j.scitotenv.2013.02.087 Urbanová, Z., Bárta, J., 2016. Effects of Long-Term Drainage on Microbial Community Composition Vary between Peatland Types. Soil Biology and Biochemistry, 92: 16-26. https://doi.org/10.1016/j.soilbio.2015.09.017 Wang, D. X., Zhang, Y. M., Wang, R. C., et al., 2018. Characteristics of Dissolved Organic Matter in Pore Water from the Dajiuhu Peatland, Central China. Resources and Environment in the Yangtze Basin, 27(11): 2568-2577 (in Chinese with English abstract). Wang, R. C., Wang, H. M., Xi, Z. Q., et al., 2022. Hydrology Driven Vertical Distribution of Prokaryotes and Methane Functional Groups in a Subtropical Peatland. Journal of Hydrology, 608: 127592. https://doi.org/10.1016/j.jhydrol.2022.127592 Wang, R. C., Wang, H. M., Xiang, X., et al., 2018. Temporal and Spatial Variations of Microbial Carbon Utilization in Water Bodies from the Dajiuhu Peatland, Central China. Journal of Earth Science, 29(4): 969-976. https://doi.org/10.1007/s12583-017-0818-5 Wang, X., He, S. W., Pan, J. Z., et al., 2021. Effects of Aquatic Plant Restoration on Water Quality and Microbial Functional Diversity of Wanshan Lake. Journal of Ecology and Rural Environment, 37(10): 1352-1360 (in Chinese with English abstract). Xu, J. R., Morris, P. J., Liu, J. G., et al., 2018. PEATMAP: Refining Estimates of Global Peatland Distribution Based on a Meta-Analysis. CATENA, 160: 134-140. https://doi.org/10.1016/j.catena.2017.09.010 Xue, D., Chen, H., Zhan, W., et al., 2021. How do Water Table Drawdown, Duration of Drainage, and Warming Influence Greenhouse Gas Emissions from Drained Peatlands of the Zoige Plateau? Land Degradation & Development, 32(11): 3351-3364. https://doi.org/10.1002/ldr.4013 Yuan, M. M., Guo, X., Wu, L. W., et al., 2021. Climate Warming Enhances Microbial Network Complexity and Stability. Nature Climate Change, 11: 343–348. https://doi.org/10.1038/s41558-021-00989-9 Yun, Y., Cheng, X. Y., Wang, W. Q., et al., 2018. Seasonal Variation of Bacterial Community and Their Functional Diversity in Drip Water from a Karst Cave. Chinese Science Bulletin, 63(36): 3932-3944 (in Chinese). doi: 10.1360/N972018-00627 Zhang, W. X., Furtado, K., Wu, P. L., et al., 2021. Increasing Precipitation Variability on Daily-to-Multiyear Time Scales in a Warmer World. Science Advances, 7(31): eabf8021. https://doi.org/10.1126/sciadv.abf8021 Zhang, Y. M., Naafs, B. D. A., Huang, X. Y., et al., 2022. Variations in Wetland Hydrology Drive Rapid Changes in the Microbial Community, Carbon Metabolic Activity, and Greenhouse Gas Fluxes. Geochimica et Cosmochimica Acta, 317: 269-285. https://doi.org/10.1016/j.gca.2021.11.014 Zhang, Z. Q., Zhang, Y. M., Huang, X. Y., et al., 2021. Seasonal Variations and Influencing Factors of Dissolved Organic Carbon in Pore Water from the Dajiuhu Peatland in Shennongjia. Bulletin of Geological Science and Technology, 40(2): 147-155 (in Chinese with English abstract). Zhong, Q. P., Chen, H., Liu, L. F., et al., 2017. Water Table Drawdown Shapes the Depth-Dependent Variations in Prokaryotic Diversity and Structure in Zoige Peatlands. FEMS Microbiology Ecology, 93(6): fix049. https://doi.org/10.1093/femsec/fix049 Zhou, G. X., Qiu, X. W., Chen, L., et al., 2019. Succession of Organics Metabolic Function of Bacterial Community in Response to Addition of Earthworm Casts and Zeolite in Maize Straw Composting. Bioresource Technology, 280: 229-238. https://doi.org/10.1016/j.biortech.2019.02.015 陈槐, 吴宁, 王艳芬, 等, 2021. 泥炭沼泽湿地研究的若干基本问题与研究简史. 中国科学(D辑), 51(1): 15-26. 黄咸雨, 张志麒, 王红梅, 等, 2017. 神农架大九湖泥炭湿地关键带监测进展. 地球科学, 42(6): 1026-1038. doi: 10.3799/dqkx.2017.081 刘红梅, 安克锐, 王慧, 等, 2020. 不同施肥措施对华北潮土区玉米田土壤微生物碳源代谢多样性的影响. 农业环境科学学报, 39(10): 2336-2344. 罗涛, 伦子健, 顾延生, 等, 2015. 神农架大九湖湿地植物群落调查与生态保护研究. 湿地科学, 13(2): 153-160. 宋贤冲, 王会利, 秦文弟, 等, 2019. 退化人工林不同恢复类型对土壤微生物群落功能多样性的影响. 应用生态学报, 30(3): 841-848. 王东香, 张一鸣, 王锐诚, 等, 2018. 神农架大九湖泥炭地孔隙水溶解有机碳特征及其影响因素. 长江流域资源与环境, 27(11): 2568-2577. 汪欣, 何尚卫, 潘继征, 等, 2021. 水生植物恢复对宛山荡水质及水体微生物代谢功能多样性的影响. 生态与农村环境学报, 37(10): 1352-1360. 云媛, 程晓钰, 王纬琦, 等, 2018. 喀斯特洞穴滴水细菌群落组成及其代谢功能的季节性变化. 科学通报, 63(36): 3932-3944. 张志麒, 张一鸣, 黄咸雨, 等, 2021. 神农架大九湖泥炭地溶解有机碳季节性变化及其影响因素. 地质科技通报, 40(2): 147-155. -