摘要:探討生物和非生物因素對青藏高原水庫溫室氣體溶存濃度和擴散通量的影響,為高原水庫溫室氣體研究提供基礎數(shù)據(jù)。以黃河大河家水庫為研究對象,2021年暖季利用頂空平衡法和擴散模型監(jiān)測水體CO2、CH4、N2O溶存濃度和擴散通量,分析水體理化性質和沉積物微生物群落對其影響。結果顯示:(1)大河家水庫各時間段、各水域均表現(xiàn)為CO2、CH4、N2O的源,平均溶存濃度分別為(38.55±9.30)μmol/L、(0.34±0.25)μmol/L、(14.74±7.34)nmol/L;平均擴散通量分別為(751.75±249.21)μmol/(m2·h)、(6.41±4.28)μmol/(m2·h)、(282.4±154.71)nmol/(m2·h);(2)時間尺度上,CO2和N2O溶存濃度和擴散通量均為白天大于夜間,CH4無明顯晝夜變化;(3)空間尺度上,CO2和N2O溶存濃度和擴散通量表現(xiàn)為庫區(qū)和下游河段高于庫前和上游河段,CH4表現(xiàn)為上游河段高于其他區(qū)域;(4)CO2溶存濃度與水溫、總氮呈顯著正相關(P<0.05),擴散通量與風速呈顯著正相關,N2O溶存濃度和擴散通量與總氮呈顯著正相關;(5)CO2擴散通量與厚壁菌門(Firmicutes)相對豐度存在顯著負相關,CH4溶存濃度和擴散通量與放線菌門(Actinobacteria)相對豐度存在顯著正相關。
關鍵詞:溫室氣體;溶存濃度;擴散通量;高原水庫
中圖分類號:X51" " " " 文獻標志碼:A" " " " 文章編號:1674-3075(2025)02-0072-10
從Rudd等(1993)開始關注水庫溫室氣體排放,到St.Louis等(2000)將水庫視為全球溫室氣體重要排放源,水庫逐漸成為全球碳排放的一個重要研究領域。水庫不同于自然水域,其建設過程中淹沒區(qū)被淹沒分解的植被以及土壤有機質都有效地促使了溫室氣體的排放(Yang et al,2017),全球水庫每年溫室氣體排放量為1.82×1013mol CO2當量(Deemer et al,2016)。水庫溫室氣體排放受到諸多因素的影響,包括水溫、水深、溶解氧、pH等環(huán)境因素。pH較高時會促進大氣中CO2溶解到水體中,而pH較低時會促進CO2向大氣排放(趙小杰等,2008),從而增加了水庫溫室氣體排放的不確定性(程炳紅等,2012;王雪竹,2021)。生物因素也是影響水庫溫室氣體排放的重要因素,沉積物中微生物群落的多樣性會影響溫室氣體排放的溫度敏感性,群落豐度可以解釋部分溫室氣體排放的差異,例如產(chǎn)甲烷菌的群落豐度會影響CH4排放的空間差異(De Jong et al,2020;Emerson et al,2021)。水庫自身特性包括庫齡與位置同樣影響水庫溫室氣體的排放,通常在建成早期擁有最高的排放量,后期逐漸減少(Abril et al,2005;Barros et al,2011;Teodoru et al,2011;Levasseur et al,2021)。不同地區(qū)水庫溫室氣體排放量存在顯著差異,低緯度地區(qū)尤其熱帶雨林地區(qū)的水庫因其陸地生態(tài)系統(tǒng)具有更高的生物量,建成后淹沒陸地導致更高的溫室氣體排放(St. Louis et al,2000;Barros et al,2011;Song et al,2018;Colas et al,2020),使得這些地區(qū)的水庫溫室氣體排放受到了廣泛的關注。作為亞洲水塔的青藏高原,水庫數(shù)量和蓄水量巨大,卻鮮有研究關注其溫室氣體的排放。
青藏高原是受全球變暖影響的敏感地區(qū),其升溫幅度高于低海拔地區(qū)(姚檀棟等,2000;Chen et al,2013)。冰川與凍土的加速消融不僅釋放大量溫室氣體(Mu et al,2018),而且解凍的溶解性碳、氮匯入到河流、湖泊和水庫中(Spencer et al,2014),對水體溫室氣體排放產(chǎn)生重要影響。此外,青藏高原水體擁有豐富的耐寒性產(chǎn)甲烷菌,即使在寒冷季節(jié)也頻繁地進行著與產(chǎn)生溫室氣體密切相關的微生物活動(Zhang et al,2020)。青藏高原的河流和湖泊被認為是溫室氣體的重要排放源,溫室氣體排放量在全球升溫的背景下不斷增加,而區(qū)域內水庫的溫室氣體排放潛力同樣值得關注(Liu et al,2017;Zhang et al,2020;段巍巖,2022;Liu et al,2023;Lin et al,2023)。位于青藏高原東北部的黃河上游是青藏高原水庫主要分布的3大區(qū)域之一(劉云龍,2020),本文以該區(qū)域內的黃河大河家水庫為研究對象,在開展水庫表層水體溫室氣體溶存濃度監(jiān)測的基礎上,使用擴散模型估算水-氣界面溫室氣體的擴散通量,并探討生物和非生物因素對溫室氣體溶存濃度和擴散通量的影響,以期為高原水庫溫室氣體研究提供基礎數(shù)據(jù)。
1" "材料與方法
1.1" "研究區(qū)概況
黃河大河家水庫(35°50′10.44″ N,102°45′8.80″ E)位于青海省海東市民和回族土族自治縣與甘肅省臨夏回族自治州積石山保安族東鄉(xiāng)族撒拉族自治縣兩縣交界處的黃河干流上,建成于2014年。地處西北內陸地區(qū),為典型的大陸性氣候,年平均氣溫8.4 ℃,日溫差與年溫差均較大。降水較少,主要集中在夏秋兩季。植被較為稀疏,主要分布植被有針葉林、灌木叢、草原。水庫正常情況下水流較為平緩,受上游水庫開閘影響,短時間內存在流速與水位的快速變化。
1.2" "樣品采集與分析
1.2.1" "采樣方案" "以大河家水庫上游河段、庫前、庫區(qū)以及下游河段為研究區(qū)域,基于樣品采集可達性和區(qū)域均衡性,在每個區(qū)域分別布設3個采樣點,共12個采樣點(圖1),7、8采樣點之間存在居民生活污水排放口。2021年7—8月進行了水體、沉積物和溫室氣體的樣品采集。2021年7月29—31日,以6 h為間隔,連續(xù)3 d進行溫室氣體溶存濃度和擴散通量以及環(huán)境因素的日尺度監(jiān)測。
1.2.2" "環(huán)境因素" "使用YSI便攜式水質儀對各個樣點的水溫(T)、溶解氧(DO)、鹽度(SAL)、電導率(EC)等數(shù)據(jù)進行測定;使用便攜式風速儀對各個樣點的風速進行測定。水樣通過不銹鋼采水器采集并裝入水樣瓶中,用于后續(xù)水質指標的測量,檢測指標包括化學需氧量(COD)、總氮(TN)、總磷(TP)和總有機碳(TOC),檢測方法主要參考《水和廢水監(jiān)測分析方法》(國家環(huán)境保護總局,2002)。COD采用高錳酸鹽法測定,TN采用堿性過硫酸鉀消解-紫外分光光度法進行測定,TP采用堿性過硫酸鉀-鉬酸銨分光光度法進行測定,TOC采用總有機碳分析儀進行測定。
1.2.3" "沉積物微生物" "沉積物通過開口1/12 m2彼得森采泥器進行采集,過2 mm篩混勻后,使用20 mL離心管保存于4 ℃車載冰箱帶回實驗室,用于沉積物中微生物的基因提取與高通量測序分析。采用細菌DNA試劑盒從沉積物中提取微生物DNA,并利用2%瓊脂糖凝膠電泳檢測抽提基因組DNA,隨后進行PCR擴增,檢測合格的PCR產(chǎn)物委托上海美吉生物醫(yī)藥科技有限公司基于Illumina Novaseq測序平臺,利用雙末端測驗的方法,構建小片段文庫進行測序。
1.2.4" "氣體" "溫室氣體溶存濃度利用頂空平衡法進行收集測定(Johnson et al,1990),使用100 mL注射器抽取50 mL水庫表層水樣和50 mL高純氮氣(99.999%),在水下振蕩5 min后靜止20 min使其達到平衡,再將頂空氣體全部注入50 mL鋁塑復合膜采氣袋帶回實驗室使用氣相色譜儀進行測定,同時測定水面上空溫室氣體濃度背景值,基于擴散模型計算溫室氣體的擴散通量(高潔等,2014)。
1.3" "數(shù)據(jù)計算
溫室氣體溶存濃度(Cw)計算公式(Weiss et al,1980)如下:
[Cw=Cgas(βRT22.4+Vgas/Vacquatic)] ①
式中:Cw為水體中氣體溶存濃度,單位為μmol/L;Cgas為氣液兩相達到平衡時的氣相濃度,單位為μmol/L;β為Bunsen系數(shù),單位為L/(L·Pa);R為理想氣體常數(shù),8314[L·Pa/(mol·K)];T為水體溫度,單位為K;Vwater和Vaquatic分別為頂空平衡器內液相和氣相的體積,單位為L。
溫室氣體擴散通量(F)計算公式(Wang et al,2009)如下:
[F=K×(Cw?Ceq)] ②
[K=K600×(Sc600)?x] ③
[Ceq=KH×PA] ④
[Sc(CO2)=1911?118.11t+3.453t2?0.0413t3] ⑤
[Sc(CH4)=1898?114.38t+3.29t2?0.0391t3] ⑥
[Sc(N2O)=2056?137.11t+4.317t2?0.0543t3] ⑦
[K600=2.07+0.215U1.710]" ⑧
[U10=UZ1+U12d10kln (10Z)] ⑨
式中:F為水-氣界面溫室氣體擴散通量,單位為μmol/(m·d);K為氣體擴散速率(J?hne et al,1989),單位為cm/h;Ceq為實際條件下水中氣體平衡濃度,單位為μmol/L;KH為亨利常數(shù);PA為當前實際條件下大氣中溫室氣體的分壓。Sc為施密特數(shù),無量綱,CO2、CH4、N2O等的計算公式分別見公式⑤、⑥、⑦;K600為當施密特數(shù)為600時對應的氣體交換速率;x為與風速相關的系數(shù),當水面上空10 m處風速超過3.6 m/s時,x取值0.5,當風速低于3.6 m/s時,x取值0.67;t為水體溫度,單位為℃;U10為采樣當日地表高度10 m處的平均風速,單位為m/s;Uz為采樣當日Z高度風速,單位為m/s,Z取1 m;Ud10為高度10 m時的阻力系數(shù),取0.0013;k為Von Karman常數(shù),取0.41。
1.4" "數(shù)據(jù)分析
實驗數(shù)據(jù)采用Excel 2021進行整理計算,使用SPSS 25.0軟件對不同區(qū)域溫室氣體溶存濃度及擴散通量進行單因素方差分析,顯著性水平為Plt;0.05,使用Origin 2022軟件進行制圖和Pearson相關性分析。
2" "結果與分析
2.1" "CO2、CH4和N2O溶存濃度及擴散通量特征
2.1.1" "CO2" "大河家水庫各區(qū)域、各時間段均表現(xiàn)為CO2的源(圖2),溶存濃度為25.94~135.56 μmol/L,擴散通量為468.16~2 643.5 μmol/(m2·h)。在空間尺度上,單因素方差分析顯示,CO2溶存濃度在庫區(qū)(44.57±9.12)μmol/L和下游河段(45.82±8.67)μmol/L顯著大于庫前(29.85±1.26)μmol/L(Plt;0.05),CO2擴散通量在庫區(qū)(916.44±161.01)μmol/(m2·h)和下游河段(1025.85±145.88)μmol/(m2·h)顯著大于上游河段(556.09±25.46)μmol/(m2·h)和庫前(508.61±30.18)μmol/(m2·h)(Plt;0.05)。在日尺度中,大河家水庫CO2溶存濃度和擴散通量均表現(xiàn)為白天(54.82±37.53)μmol/L、(1138.51±721.66)μmol/(m2·h)大于夜間(34.33±8.73)μmol/L、(694.38±110.45)μmol/(m2·h)。
2.1.2" "CH4" "大河家水庫各區(qū)域、各時間段均表現(xiàn)為CH4的源(圖3),溶存濃度為0.11~1.12 μmol/L,擴散通量為2.1~19.59 μmol/(m2·h)。在空間尺度上,CH4溶存濃度和擴散通量均在上游河段達到峰值,單因素方差分析顯示,CH4溶存濃度在上游河段(0.64±0.33)μmol/L顯著大于庫前(0.23±0.04)μmol/L和下游河段(0.19±0.05)μmol/L(Plt;0.05),CH4擴散通量在各區(qū)域無顯著差異(Pgt;0.05)。在日尺度觀測中,大河家水庫CH4溶存濃度和擴散通均表現(xiàn)為夜間(0.32±0.05)μmol/L、(6.58±1.24)μmol/(m2·h)略大于白天(0.29±0.1)μmol/L、(6.12±2.32)μmol/(m2·h),晝夜沒有明顯的差別。
2.1.3" "N2O" "大河家水庫各區(qū)域、各時間段均表現(xiàn)為N2O的源(圖4),溶存濃度為9.31~29.31 nmol/L,擴散通量為150.05~1 388.16 nmol/(m2·h)。在空間尺度上,單因素方差分析顯示,N2O溶存濃度在各區(qū)域無顯著差異(Pgt;0.05),N2O擴散通量在下游河段(416.85±94.66)nmol/L顯著大于上游河段(171.88±24.49)nmol/L和庫前(156.09±5.9)nmol/L(Plt;0.05),庫區(qū)(384.79±171.52)nmol/L顯著大于庫前(Plt;0.05)。日尺度觀測中,大河家水庫N2O溶存濃度和擴散通量均表現(xiàn)為白天(23.16±21.82)nmol/L、(467.59±414.31)nmol/(m2·h)大于夜間(14.98±4.19)nmol/L、(301.99±91.7)nmol/(m2·h)。
2.2" "水庫水體環(huán)境的理化特性
采樣期間,水庫的主要環(huán)境指標如表1所示。水溫在庫區(qū)達到峰值(17.84±0.22)℃,上游河段與下游河段水溫均較低,分別為(13.65±0.46)℃、(13.63±0.62)℃;TP在庫前達到峰值(0.05±0.019)mg/L,其余區(qū)域數(shù)值較為接近;TN呈現(xiàn)出從上游到下游遞增的規(guī)律,下游河段達到峰值(0.76±0.14)mg/L;COD在上游河段(5.52±3.54)mg/L與下游河段(5.17±1.54)mg/L高于庫前(4.01±2.55)mg/L與庫區(qū)(4.01±0.71)mg/L;TOC在庫區(qū)達到峰值(17.79±2.85)mg/L,其余3區(qū)數(shù)值較為接近;EC在上游河段(391.33±8.06)ms/cm與下游河段(392.67±25.32)ms/cm高于庫前(362±23.72)ms/cm與庫區(qū)(368±13.37)ms/cm;DO在庫區(qū)達到峰值(6.97±0.16)mg/L,在庫前同樣較高(6.01±0.23)mg/L,上游河段與下游河段均較低(5.77±0.58)mg/L、(5.67±0.43)mg/L;風速在庫區(qū)與下游河段較快(1.56±0.3)m/s、(1.57±1.25)m/s;流速在庫區(qū)接近為0,在下游河段最快(0.33±0.06)m/s。
2.3" "水庫沉積物微生物的群落特征
沉積物微生物被認為是影響溫室氣體排放的一個重要因子。采樣期間,水庫沉積物微生物群落優(yōu)勢門類主要有變形菌門(Proteobacteria)、厚壁菌門(Firmicutes)、擬桿菌門(Bacteroidetes)、酸桿菌門(Acidobacteria)、綠灣菌門(Chloroflexi)、疣微菌門(Verrucomicrobia)、放線菌門(Actinobacteria)、ε-變形菌門(Epsilonbacteraeota),其相對豐度占總群落的91.66%~97.75%。相對豐度排名前10的還有胞菌門(Gemmatimonadetes)和硝化螺旋菌門(Nitrospirae)(圖5)。上游河段綠灣菌門相對豐度(5.88±0.17)%顯著低于其他點位(2.85±1.84)%;下游河段厚壁菌門、綠灣菌門、疣微菌門、ε-變形菌門相對豐度(11.03±2.32)%、(1.15±0.28)%、(1.08±0.68)%、(0.06±0.02)%顯著低于其他點位(23.47±7.52)%、(4.43±1.73)%、(3.7±1.81)%、(2.03±1.26)%,擬桿菌門相對豐度(31.24±9.74)%高于其他點位(9.86±0.74)%。
基于不同區(qū)域沉積物Alpha多樣性比較(表2),4個區(qū)域的Simpson指數(shù)都較為接近,下游河段的ACE指數(shù)、Chao1指數(shù)和Shannon指數(shù)均低于其他3個區(qū)域,庫前的ACE指數(shù)、Chao1指數(shù)和Shannon指數(shù)都低于上游河段與庫區(qū),上游河段與庫區(qū)的多樣性指數(shù)均值較為接近。
2.4" "溫室氣體溶存濃度及擴散通量與理化因子和微生物群落的相關性
將水庫水環(huán)境的理化數(shù)據(jù)與溫室氣體的溶存濃度和擴散通量進行Pearson相關性分析,結果見圖6。CO2溶存濃度與水溫、TN呈現(xiàn)顯著正相關(Plt;0.05),CO2擴散通量與風速呈現(xiàn)顯著正相關。CH4溶存濃度和擴散通量與各水環(huán)境因子均無顯著關系。N2O溶存濃度和擴散通量均與TN呈現(xiàn)顯著正相關。
將沉積物微生物的Alpha多樣性和門水平下相對豐度與溫室氣體的溶存濃度和擴散通量進行Pearson相關性分析,結果見圖7。CO2、CH4和N2O與沉積物Alpha多樣性之間無顯著關系。CO2擴散通量與厚壁菌門相對豐度之間存在顯著負相關(Plt;0.05)。CH4溶存濃度和擴散通量均與放線菌門相對豐度之間存在顯著正相關,N2O溶存濃度和擴散通量與各門類微生物群落特征無顯著關系。
3" "討論
3.1" "溫室氣體溶存濃度及擴散通量的影響因素
CO2產(chǎn)生與排放受溫度、TN和風速影響,溫度升高沉積物微生物的活性相應升高,從而加快沉積物有機質及生物殘體的分解速率,促進CO2等無機碳的釋放(張逸飛,2019),這解釋了CO2溶存濃度與擴散通量表現(xiàn)為白天大于夜間。氮與水體微生物代謝聯(lián)系緊密,可以影響CO2的產(chǎn)生與消耗(鄭祥旺,2022),大河家水庫CO2溶存濃度在庫區(qū)和下游河段的值較高,可能是由于附近居民點向庫區(qū)排放的生活污水中富含氮所引起的(Hu et al,2018)。風速可以影響水-氣界面氣體濃度差,促進氣體的擴散,且風力對水體的擾動作用也可促進氣體的擴散(汪國駿等,2017)。TN是硝化和反硝化細菌群落的重要影響因子,隨著TN濃度的升高,解除了微生物代謝的營養(yǎng)限制,有利于反硝化的進行,促進N2O的排放(李紅麗等,2012;Yang et al,2015;劉婷婷等,2019)。
CO2排放受厚壁菌門影響,與CO2產(chǎn)生所需要的富氧條件不同,厚壁菌門常見于厭氧環(huán)境中,其通過競爭有機氮抑制CO2的產(chǎn)生與排放(Belger et al,2011;Yang et al,2019;李欣芮,2021;張翎等,2022)。CH4產(chǎn)生與排放受放線菌門影響,放線菌門對有機質礦化以及硫、氮和碳循環(huán)具有重要意義(Mao et al,2019),但并不能直接影響CH4的排放,而是通過微生物的相互作用間接影響產(chǎn)CH4潛力(Li et al,2023)。
3.2" "不同地區(qū)水庫溫室氣體擴散通量對比
通過對比國內外不同地區(qū)水庫溫室氣體擴散通量可知(表3),各水庫均為CH4和N2O的源,大部分水庫也為CO2的源。熱帶與亞熱帶地區(qū)水庫的CH4和N2O擴散通量普遍高于溫帶與亞熱帶地區(qū)水庫,熱帶與亞熱帶地區(qū)水庫的CO2擴散通量沒有明顯高于溫帶與亞熱帶地區(qū)。在同為碳源的水庫中,大河家水庫CO2擴散通量僅高于丁解水庫以及潘家口水庫(夏季),CH4擴散通量高于溫帶F.D.Roosevelt、大黑汀、潘家口水庫以及同為青藏高寒區(qū)的藏木水庫,N2O擴散通量高于溫帶大黑汀(夏季)、潘家口水庫和寒帶的Lokka、Porttipahta水庫以及青藏高寒區(qū)的藏木水庫。在氣候變化的背景下,青藏高原升溫幅度高于其他低海拔地區(qū),近地面風速呈現(xiàn)增大趨勢(唐信英等,2022;吳佳等,2022),溫度與風速都是影響水體溫室氣體產(chǎn)生與排放的重要因子。并且降水也整體呈上升趨勢(周思儒和信忠保,2023),更多的溶解態(tài)營養(yǎng)物質匯入高原水體,帶來溫室氣體排放量的增加(張佩等,2020;蔣莉莉等,2021)。因此,應當重點關注未來氣候變化下青藏高原地區(qū)水庫的溫室氣體排放。
4" "結論
以大河家水庫為研究對象,分析其不同時間、不同區(qū)域水-氣界面溫室氣體溶存濃度和擴散通量,測定水環(huán)境與沉積物指標并分析二者響應關系,得出結論:
(1)大河家水庫各水域均表現(xiàn)為3種溫室氣體CO2、CH4和N2O的源,CO2、N2O溶存濃度和擴散通量均在下游河段達到峰值,庫區(qū)溶存濃度和擴散通量同樣較高,CH4溶存濃度和擴散通量均在上游河段達到峰值,庫前和下游河段溶存濃度與擴散通量較低;
(2)大河家水庫各時間段均表現(xiàn)為3種溫室氣體CO2、CH4和N2O的源,CO2和N2O溶存濃度和擴散通量均為白天大于夜間,CH4溶存濃度和擴散通量沒有明顯的晝夜變化;
(3)CO2溶存濃度主要受到水溫和TN影響,擴散通量受風速影響;N2O溶存濃度和擴散通量均受TN影響;CO2擴散通量與厚壁菌門相對豐度之間存在顯著負相關,CH4溶存濃度和擴散通量均與放線菌門相對豐度呈顯著正相關。
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(責任編輯" "鄭金秀" "崔莎莎)
Concentration and Flux of Greenhouse Gases and Influencing Factors in Dahejia Reservoir of the Yellow River
XIA Liang1,2, MAO Xufeng1,2, WU Yi1,2, LING Jiankang1,2, WANG Lei1,2,3,HE Daye1,2, LI Jingmei1,2.4, XU Bin1,2
(1. College of Geographic Sciences, Qinghai Normal University, Institute of Plateau Science and Sustainable Development, Xining" "810008, P.R. China;
2. Key Laboratory of Natural Geography and Environmental Processes of Qinghai Province;Qinghai-Tibet Plateau Surface Processes and Ecological Conservation Key Laboratory of the Ministry of Education, Xining" "810008, P.R. China;
3. School of Civil and Architectural Engineering, Nanchang Institute of Technology, Nanchang" "330099, P.R. China;
4. Qinghai Academy of Social Sciences, Xining" "810000, P.R. China)
Abstract:Reservoirs are important sources of greenhouse gas emissions and have gradually become an important area of research in the study of global carbon emissions. In this study, Dahejia reservoir of the Yellow River on the Qinghai-Tibet Plateau was selected for study, and we monitored the dissolved concentrations and fluxes of CO2, CH4, and N2O from the reservoir in the warm season of 2021 using the headspace equilibrium and diffusion model. We also analyzed the effects of water physicochemical properties and sediment microbial community on greenhouse gas concentrations and fluxes. The aim of the study was to provide basic data on the greenhouse gas budget for reservoirs on the Qinghai-Tibet Plateau. A total of 12 sampling points were set upstream and just above the reservoir, in the reservoir and downstream of the reservoir. In July and August 2021, water, sediment and greenhouse gases were sampled for analysis of water physicochemical parameters, sediment bacteria, and the concentrations and fluxes of CO2, CH4, and N2O. Results show: (1) Dahejia reservoir is a continuous source of CO2, CH4, and N2O in all segments with respective average concentrations of (38.55±9.3) μmol/L, (0.34±0.25) μmol/L and (14.74±7.34) nmol/L, and respective average fluxes of (751.75±249.21) μmol/(m2·h), (6.41±4.28) μmol/(m2·h) and (282.4±154.71) nmol/(m2·h). (2) Temporally, the concentrations and fluxes of CO2 and N2O were significantly higher in the day than at night, but there was no significant diurnal variation in those of CH4. (3) Spatially, the concentrations and fluxes of CO2 and N2O were significantly higher in the reservoir and downstream than just above the reservoir and upstream, while those of CH4 were significantly higher in the upstream section than in other areas. (4) The CO2 concentration was positively correlated with water temperature and total nitrogen (Plt;0.05), and the flux was positively correlated with wind speed. The N2O concentration and flux were both positively correlated with total nitrogen. The CH4 concentration and flux were not significantly correlated with any water environmental parameters. (5) The CO2 flux was negatively correlated with the relative abundance of Firmicutes and the CH4 concentration and flux increased with the relative abundance of Actinobacteria. Finally, greenhouse gas fluxes from Dahejia reservoir were compared with greenhouse gas fluxes in other reservoirs at home and abroad. Our data on the greenhouse gas budget for a reservoir on the Qinghai-Tibet Plateau allows for a more complete global greenhouse budget.
Key words: greenhouse gases; dissolved concentration; diffusion flux; plateau reservoir
基金項目:國家自然基金(52070108);青海省基礎研究項目(2022-ZJ-718);青海省創(chuàng)新平臺建設項目(2020-ZJ-Y06)。
作者簡介:夏亮,2000年生,男,研究方向為濕地生態(tài)過程。E-mail:15079266732@163.com
通信作者:毛旭鋒,1981年生,男,教授,研究方向為濕地生態(tài)過程。E-mail:maoxufeng@yeah.net