首页|淡水养殖池塘CO2通量多时间尺度变化特征及其影响要素

淡水养殖池塘CO2通量多时间尺度变化特征及其影响要素

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为探讨淡水养殖CO2通量的多时间尺度变化特征及其影响因子,本研究以我国长江三角洲区域典型淡水养殖池塘为研究对象,基于涡度相关法(Eddy covariance,EC)测定的2016-2021年高频连续CO2通量数据,对CO2通量的多时间尺度变化特征及其环境、人为影响要素进行分析。结果表明:养殖池塘CO2通量(以C计)存在明显的日变化、季节变化和年际变化特征,其年尺度交换量的变化范围为-671~1 005 kg·hm-2·a-1,年均值为(-74±688)kg·hm-2·a-1,表现为CO2的弱汇。CO2通量在不同时间尺度的主控因子存在明显差异,其中在0。5 h尺度上,太阳辐射和气温分别是白天和夜晚CO2通量的主要影响因子;日尺度和月尺度的CO2通量则分别受太阳辐射和归一化植被指数(NDVI)调控,且CO2通量与上述要素均呈显著负相关;年际尺度上,养殖池塘CO2通量受饲料投入量与NDVI的共同作用,二者建立的回归方程可以解释64%的CO2年总通量变化,其中CO2排放量随饲料投入量的增加呈线性增加(R2=0。55,P<0。05)。根据本研究结果,建议在未来可将提高饲料利用率作为控制养殖水体温室气体排放、改善水体生态环境、实现水产养殖业可持续发展的重要途径。
Variation characteristics of CO2 flux and their impact on freshwater aquaculture pond at multi-temporal scales
In order to investigate variation characteristics of CO2 fluxes at multi-temporal scales and identify their impact factors,high-frequency CO2 flux was continuously measured by the eddy covariance method from 2016 to 2021 in typical freshwater aquaculture ponds in the Yangtze River Delta,China.By using these data,the multi-temporal variation characteristics of CO2 flux and its environmental and anthropogenic factors were analyzed.The results clearly showed daily,seasonal and interannual variations in CO2 flux.The annual amount of CO2 flux(calculated in C)ranged from-671 kg·hm-2·a-1 to 1 005 kg·hm-2·a-1 with an average value of(-74±688)kg·hm-2·a-1,indicating that the ponds were a weak CO2 sink.The main impact factors of CO2 flux at different temporal scales were not the same.At the half-hourly scale,solar radiation and air temperature controlled daytime and nighttime CO2 flux,respectively.At the daily and monthly scales,CO2 flux were regulated by solar radiation and normalized vegetation index(NDVI),respectively.Moreover,CO2 fluxes were negatively and significantly correlated with these factors.At the annual scale,the CO2 flux was influenced by both the amount of feed inputs and NDVI.The regression equation established by the two factors could explain 64%of the total annual CO2 flux variation.Furthermore,CO2 emissions increased linearly with the increase in feed inputs(R2=0.55,P<0.05).Based on this study,improving feed utilization efficiency is suggested as an important way to control greenhouse gas emissions from aquaculture ponds,improve the ecological environment of water bodies,and sustainably develop the aquaculture industry in the future.

freshwater aquaculture pondeddy covariance methodCO2 fluxmulti-temporal scaleimpact factor

葛培、赵佳玉、张弥、肖薇、邱吉丽、贾磊、包恒鑫、石婕、赵若男

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南京信息工程大学大气环境中心,南京 210044

南京信息工程大学应用气象学院,南京 210044

广东海洋大学海洋与气象学院,广东 湛江 524088

贵州省黔南州平塘县气象局,贵州 黔南 558000

河北省气象与生态环境重点实验室,石家庄 050021

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淡水养殖池塘 涡度相关法 CO2通量 多时间尺度 影响因子

国家重点研发计划项目国家重点研发计划项目国家自然科学基金项目国家自然科学基金项目

2020YFA06075012019YFA06072022020YFA06075012019YFA0607202

2024

农业环境科学学报
农业部环境保护科研监测所 中国农业生态环境保护协会

农业环境科学学报

CSTPCD北大核心
影响因子:1.52
ISSN:1672-2043
年,卷(期):2024.43(1)
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