李金,任立軍,李曉宇,畢潤(rùn)學(xué),金鑫鑫,虞娜,張玉玲,鄒洪濤,張玉龍
不同秸稈還田方式對(duì)玉米農(nóng)田土壤CO2排放量和碳平衡的影響
李金,任立軍,李曉宇,畢潤(rùn)學(xué),金鑫鑫,虞娜,張玉玲,鄒洪濤,張玉龍
沈陽農(nóng)業(yè)大學(xué)土地與環(huán)境學(xué)院/農(nóng)業(yè)農(nóng)村部東北耕地保育重點(diǎn)實(shí)驗(yàn)室/土肥高效利用國(guó)家工程研究中心,沈陽 110866
【目的】探究秸稈還田方式對(duì)土壤CO2排放特征及碳平衡的影響,為東北地區(qū)農(nóng)田土壤固碳減排和秸稈還田方式的選擇提供科學(xué)依據(jù)?!痉椒ā坎捎锰镩g微區(qū)試驗(yàn),以玉米為供試作物,設(shè)置3種秸稈還田方式:秸稈淺層還田(QH)、秸稈深層還田(SH)和秸稈覆蓋還田(FG),無秸稈還田(CK)處理為對(duì)照。利用LI-8100A土壤碳通量自動(dòng)測(cè)定儀監(jiān)測(cè)玉米生長(zhǎng)季不同秸稈還田方式下土壤CO2的排放特征,探討土壤溫度、含水量、pH、微生物量碳及氮磷鉀速效養(yǎng)分和全量養(yǎng)分對(duì)土壤CO2排放的影響,并分析不同還田方式下的土壤碳平衡。【結(jié)果】在玉米生長(zhǎng)季,各處理土壤CO2排放速率均表現(xiàn)為先升高后降低的趨勢(shì)。土壤CO2累積排放量表現(xiàn)為FG>QH>SH>CK處理,相較于SH處理,F(xiàn)G和QH處理土壤CO2累積排放量分別增加了14.0%和6.4%,各處理間差異顯著(<0.05)。不同還田方式下土壤CO2排放速率與土壤溫度、土壤含水量進(jìn)行單因素模型擬合,均呈二次函數(shù)相關(guān)關(guān)系,且達(dá)到了顯著水平(<0.05),土壤溫度和土壤含水量分別解釋68.2%—73.7%和21.3%—82.8%的土壤CO2排放速率變化,但土壤溫度和土壤含水量的雙因素復(fù)合模型能更好地解釋土壤CO2排放速率的變化,解釋度達(dá)到78.5%—82.8%。相關(guān)性分析表明,土壤CO2累積排放量與速效鉀、微生物量碳呈極顯著相關(guān)關(guān)系(<0.01),與土壤有機(jī)質(zhì)、堿解氮、全氮和pH呈顯著的相關(guān)關(guān)系(<0.05)。秸稈還田處理下土壤碳平衡均為正值,為大氣CO2碳匯。SH處理下土壤碳平衡和固碳潛力顯著高于QH、FG處理,提高幅度分別為23.4%、475.7%和7.1%、30.7%(<0.05),表現(xiàn)出較強(qiáng)的碳匯功能。在兩年收獲期,秸稈還田顯著提高了玉米產(chǎn)量,其中SH處理最高,但與QH和FG處理間無顯著差異。【結(jié)論】本試驗(yàn)條件下,綜合考慮固碳減排效應(yīng)和產(chǎn)量,3種秸稈還田方式相比,秸稈深層還田(SH)是一種較好的還田方式。
秸稈還田方式;土壤CO2排放;土壤溫度;土壤含水量;玉米產(chǎn)量;碳平衡
【研究意義】溫室氣體排放導(dǎo)致的全球氣候變化和糧食安全已成為人類面臨的重大挑戰(zhàn)[1]。CO2作為一種主要溫室氣體成分,20%左右來源于土壤[2],農(nóng)田土壤是陸地生態(tài)系統(tǒng)向大氣排放CO2的重要源頭,其微小的波動(dòng)會(huì)對(duì)大氣中CO2濃度產(chǎn)生較大影響[3],并影響著全球碳循環(huán)和碳平衡過程。我國(guó)每年作物秸稈產(chǎn)量為7億—9億t[4],其中大部分秸稈被焚燒浪費(fèi),導(dǎo)致嚴(yán)重的環(huán)境污染并加速了全球溫室氣體的排放[5]。近年來,有研究學(xué)者發(fā)現(xiàn)秸稈是一種便于利用的自然資源,其還田后在提高土壤有機(jī)碳含量、改善土壤質(zhì)量和增加作物產(chǎn)量等方面有著重要的作用[6],但在秸稈還田的同時(shí)其對(duì)農(nóng)田土壤CO2排放的影響也是不容忽視的。因此,探究不同秸稈還田方式對(duì)土壤CO2排放特征及碳平衡的影響,對(duì)農(nóng)田土壤固碳減排,作物秸稈合理利用具有重大現(xiàn)實(shí)意義?!厩叭搜芯窟M(jìn)展】目前研究學(xué)者們關(guān)于秸稈還田與土壤CO2排放的關(guān)系仍存在分歧。YANG等[7]研究認(rèn)為,秸稈還田可以促進(jìn)有機(jī)物分解和養(yǎng)分循環(huán),但增加了土壤CO2排放。白銀萍等[8]研究表明,與不還田相比,秸稈覆蓋還田使土壤CO2排放增加了12.7%;而秸稈翻埋還田使土壤CO2排放降低了2.5%。WANG等[9]發(fā)現(xiàn),在冬小麥-春玉米輪作系統(tǒng)中,無論是翻耕還是免耕,秸稈覆蓋還田較不還田相比,土壤CO2排放分別降低了8.5%和14.5%。土壤碳平衡可以通過一定時(shí)間內(nèi)碳輸入和輸出的差異來計(jì)算[10],當(dāng)碳平衡值為正值時(shí),表現(xiàn)為大氣CO2的吸收“匯”,反之則為排放“源”[11]。DOSSOU-YOVO等[12]研究發(fā)現(xiàn),在貝寧北部地區(qū),秸稈覆蓋還田顯著降低了土壤碳平衡,但劉平奇等[13]研究表明,在我國(guó)東北黑土地區(qū),單獨(dú)進(jìn)行深松處理的土壤碳平衡表現(xiàn)為負(fù)值,而深松結(jié)合秸稈還田處理的土壤碳平衡卻表現(xiàn)為正值,表明秸稈還田能夠增加土壤碳平衡值。【本研究切入點(diǎn)】目前,相關(guān)學(xué)者對(duì)秸稈還田下土壤CO2排放的研究主要集中在覆蓋還田和表層淺混還田[14],而深還田下土壤CO2排放特征及其影響因素和土壤碳平衡的研究有待深入?!緮M解決的關(guān)鍵問題】本研究在田間試驗(yàn)條件下,探究秸稈還田方式對(duì)土壤CO2排放特征及碳平衡的影響,明確最佳的秸稈還田方式,以期為東北地區(qū)農(nóng)田土壤固碳減排和秸稈還田方式的選擇提供理論依據(jù)。
試驗(yàn)在沈陽農(nóng)業(yè)大學(xué)科研試驗(yàn)基地進(jìn)行(41°82′ N,123°56′ E),該區(qū)域?qū)儆跍貛О霛駶?rùn)大陸性氣候,試驗(yàn)地為雨養(yǎng)農(nóng)業(yè),年均溫度為9.00 ℃,年均降雨量為881.07 mm。供試土壤為棕壤,其基本理化性質(zhì)為有機(jī)質(zhì)含量12.21 g·kg-1、全氮0.67 g·kg-1、pH 6.70、土壤容重1.39 g·cm-3,土壤速效鉀、速效磷和堿解氮含量分別為132.52、62.19、64.45 mg·kg-1。
該試驗(yàn)始于2020年5月,已連續(xù)兩年進(jìn)行秸稈還田試驗(yàn)。采用隨機(jī)區(qū)組設(shè)計(jì),設(shè)3種秸稈還田方式,分別為秸稈淺層還田(QH)、秸稈深層還田(SH)、秸稈覆蓋還田(FG),無秸稈還田(CK)為對(duì)照,共4個(gè)處理,每個(gè)處理設(shè)3次重復(fù),各試驗(yàn)微區(qū)面積為2.08 m2(1.6 m×1.3 m),每個(gè)微區(qū)四周用混凝土澆筑并做防水處理。2020年秋季玉米收獲后將秸稈粉碎至3 cm左右還入田中,各處理秸稈還田量相同,為10 500 kg·hm-2,具體操作見表1。
表1 試驗(yàn)處理
該區(qū)域種植模式為一年一熟制度,供試作物為玉米,品種為鄭單958。于2020年和2021年5月下旬播種,9月中旬收獲。每個(gè)小區(qū)種植2行玉米,每行4株,行距為0.4 m,株距為0.3 m。各處理施肥量相同,施用過磷酸鈣(P2O5含量為12%)75 kg·hm-2,硫酸鉀(K2O含量為50%)105 kg·hm-2,尿素(N含量為46.4%)240 kg·hm-2,作為基肥在播種前一次性施入,田間管理與當(dāng)?shù)爻R?guī)玉米栽培一致。
1.3.1 樣品采集與測(cè)定 采用LI-8100A土壤碳通量自動(dòng)測(cè)定儀(Li-Cor,Lincon,NE,USA)及其自帶呼吸室測(cè)定2021年玉米季土壤CO2排放速率。為平衡土壤中氣體,降低土壤結(jié)構(gòu)擾動(dòng)帶來的影響,在測(cè)定前2—3 d,先將PVC基座(直徑20 cm,高10 cm)均勻插入土壤中[15],露出土面2 cm左右。同時(shí)為減小試驗(yàn)測(cè)量誤差,盡量將PVC基座安放在各試驗(yàn)區(qū)同一位置。測(cè)定時(shí),將呼吸室放在PVC基座上,收集從土壤釋放的CO2,每個(gè)處理布置3次重復(fù),每個(gè)試驗(yàn)區(qū)重復(fù)測(cè)定3次,若3次測(cè)定值偏差大于15%,則需繼續(xù)進(jìn)行測(cè)定直至偏差小于15%。自施肥日起,開始測(cè)定土壤CO2排放速率,第一周每2 d測(cè)定一次,第二周每2—3 d測(cè)定一次,之后平均每7 d測(cè)定一次(具體根據(jù)天氣降雨等條件變化,測(cè)定時(shí)間會(huì)有微小調(diào)整),測(cè)定時(shí)間為上午8:00—12:00,在測(cè)定氣體的同時(shí),監(jiān)測(cè)土壤溫度和土壤含水量。試驗(yàn)期間,土壤CO2累積排放量()計(jì)算公式[16]為:
式中,為土壤CO2累積排放量(kg·hm-2);為第次測(cè)定土壤CO2排放速率(μmol·m-2·s-1);(t-t)為連續(xù)兩次測(cè)定間隔時(shí)間(d);為測(cè)定的總次數(shù)。
土壤呼吸碳累積排放量():
=×0.27 (2)
式中,為土壤呼吸碳累積排放量(kg·hm-2);為土壤CO2累積排放量(kg·hm-2);0.27為C占CO2分子量的比例。
碳平衡()[10-11]:
=-(3)
=(+)×0.45 (4)
=/2.1 (5)
×0.865 (6)
=/(7)
式中,為生態(tài)系統(tǒng)碳平衡(kg·hm-2);為凈初級(jí)生產(chǎn)力固碳量(kg·hm-2);為土壤微生物異養(yǎng)呼吸的碳釋放量(kg·hm-2);為地上生物量(kg·hm-2);為根生物量(kg·hm-2);0.45為作物地上部與根部含碳量;2.1為作物地上生物量與根生物量的比例;0.865為土壤微生物異養(yǎng)呼吸轉(zhuǎn)化系數(shù);為生態(tài)系統(tǒng)土壤固碳潛力。
玉米收獲后,于2021年用五點(diǎn)法采集0—20 cm土層土樣,剔除根系和秸稈等雜物,混勻后風(fēng)干、過篩測(cè)定土壤理化性質(zhì)。土壤容重采用環(huán)刀法測(cè)定;土壤pH采用pH計(jì)測(cè)定(土水比=1﹕2.5);土壤有機(jī)質(zhì)和全氮采用元素分析儀(Vario EL Ⅲ,Elementar,Germany)測(cè)定。土壤微生物碳采用氯仿熏蒸法測(cè)定。土壤速效和全量氮磷鉀養(yǎng)分采用《土壤農(nóng)化分析》中方法測(cè)定[17]。土壤溫度采用長(zhǎng)度為10 cm的地溫計(jì)測(cè)定;10 cm土層體積含水量(全文簡(jiǎn)稱“含水量”)采用土壤水分測(cè)定儀(EC-5)測(cè)定;在2020年和2021年玉米收獲期,測(cè)量其穗行數(shù)、穗粒數(shù)、百粒重和籽粒產(chǎn)量,同時(shí)采集玉米植株地上部分,105 ℃殺青0.5 h后,在60 ℃下烘干至恒重,稱重。
1.3.2 數(shù)據(jù)處理 采用Microsoft Excel 2019和SPSS 25.0進(jìn)行數(shù)據(jù)統(tǒng)計(jì)分析;采用單因素(one-way ANOVA)和Duncan法進(jìn)行方差分析和多重比較(α=0.05)。利用Origin 2017軟件繪圖并進(jìn)行單因素非線性曲線擬合和雙因素非線性曲面模型擬合。
由圖1可知,玉米生育期內(nèi)各處理土壤CO2排放速率變化趨勢(shì)基本一致,呈先升高后降低的波動(dòng)趨勢(shì)。各處理土壤CO2排放速率均在6月9日達(dá)到峰值,QH、FG、SH和CK處理土壤CO2排放速率分別為7.65、7.40、6.31、5.64 μmol·m-2·s-1。隨后土壤CO2排放速率逐漸下降,在8月2日出現(xiàn)降雨后,土壤CO2排放速率呈上升趨勢(shì),并在8月4日再次達(dá)到峰值,此時(shí)FG處理下土壤CO2排放速率最高,為6.70 μmol·m-2·s-1,其次是SH和QH處理,分別為5.84和5.54 μmol·m-2·s-1,CK處理最低,為4.50 μmol·m-2·s-1。
圖1 不同秸稈還田方式下土壤CO2排放速率的動(dòng)態(tài)變化
由圖2可知,在玉米生長(zhǎng)季,不同處理間土壤CO2累積排放量均達(dá)到顯著差異。FG處理土壤CO2累積排放量最高,為23 897.17 kg·hm-2;其次是QH、SH處理,分別為22 298.22和20 962.72 kg·hm-2;CK處理土壤CO2累積排放量最少,為16 602.24 kg·hm-2。
不同字母表示差異顯著(P<0.05)
3種還田處理中,相較于SH處理,F(xiàn)G和QH處理土壤CO2累積排放量分別增加了14.0%和6.4%。由此可知,秸稈還田增加了土壤CO2排放,但秸稈深還相較于其他還田方式能夠減少土壤CO2排放。
2.3.1 土壤溫度 由圖3可知,不同還田方式下土壤溫度的變化趨勢(shì)基本一致,呈先升高后降低的趨勢(shì)。在玉米生育期內(nèi),CK處理土壤溫度變化范圍最大,為17.3—33.3 ℃;其次為QH和FG處理,分別為16.0—31.0和15.0—30.0 ℃;SH處理的變化范圍最小,為15.8—30.5 ℃。各處理土壤溫度均在7月28日達(dá)到最大值,CK處理土壤溫度最高,為32 ℃,其次是QH、SH和FG處理,分別為30.6、30.2和29.9 ℃。
圖3 不同秸稈還田方式下土壤溫度的動(dòng)態(tài)變化
土壤溫度與土壤CO2排放速率關(guān)系采用非線性擬合的方法進(jìn)行擬合,結(jié)果如圖4所示,不同處理下土壤溫度與土壤CO2排放速率的擬合方程均達(dá)到了顯著水平。不同秸稈還田方式下,土壤溫度可以解釋68.2%—73.7%的土壤CO2排放速率變化,其中SH處理2最大,可以解釋73.7%土壤CO2排放速率變化。此外,CK處理下,當(dāng)土壤溫度<27.2 ℃時(shí),土壤CO2排放速率隨著土壤溫度的升高而增加,當(dāng)土壤溫度>27.2 ℃時(shí),表現(xiàn)出相反的變化趨勢(shì);其他3個(gè)秸稈還田處理表現(xiàn)出相似的變化規(guī)律,但土壤CO2排放速率出現(xiàn)的最高點(diǎn)不同,QH、FG和SH處理分別為24.7、23.9和24.8 ℃。
2.3.2 土壤含水量 不同還田方式土壤含水量的動(dòng)態(tài)變化趨勢(shì)基本一致,呈現(xiàn)先升高后降低,隨后再升高達(dá)到峰值,之后下降的趨勢(shì)(圖5)。土壤含水量的變化受到了自然降雨的影響,整體隨著降雨的增加,土壤含水量增加,變化范圍在13.9%—39.6%。在大多數(shù)情況下,秸稈還田處理的土壤含水量相較于CK處理而言,均有所提高,說明秸稈還田后土壤的保水能力有所增加。土壤含水量平均值表現(xiàn)為FG>SH>QH>CK處理。
*表示在0.05水平上差異顯著(n=60)。下同
圖5 不同秸稈還田方式下土壤含水量的動(dòng)態(tài)變化
對(duì)不同秸稈還田方式下土壤含水量與土壤CO2排放速率進(jìn)行非線性擬合發(fā)現(xiàn),土壤含水量解釋了21.3%—37.5%土壤CO2排放速率變化,低于土壤溫度對(duì)土壤CO2排放速率的解釋能力(圖6)。在土壤含水量較低時(shí),土壤CO2排放速率隨著土壤含水量的增加而增加,當(dāng)土壤含水量高于一定的數(shù)值時(shí),土壤CO2排放速率呈下降的趨勢(shì),但FG處理的轉(zhuǎn)折點(diǎn)要晚于其他處理。
圖6 不同秸稈還田方式下土壤含水量與土壤CO2排放速率的模型擬合分析
2.3.3 水熱因子的綜合作用 由圖7可知,在不同秸稈還田方式下,以土壤含水量()和土壤溫度()為自變量,土壤CO2排放速率()為因變量,建立雙因素復(fù)合模型(Y=z+aW+bT+cW+dT,<0.05),CK、QH、FG、SH處理的擬合方程見表2。各處理雙因素復(fù)合模型的2在0.785—0.828之間,相較于單因素(2為0.213—0.737)模型擬合較好,說明土壤含水量和土壤溫度的雙因素復(fù)合模型可以更好地解釋土壤CO2排放速率的變化。
2.3.4 土壤理化性狀 將玉米收獲期0—20 cm土層理化性狀指標(biāo)與土壤CO2累積排放量進(jìn)行相關(guān)性分析,結(jié)果如圖8所示。土壤CO2累積排放量與速效鉀、微生物量碳呈極顯著正相關(guān)關(guān)系(<0.01),相關(guān)系數(shù)為0.83、0.74;與土壤有機(jī)質(zhì)、堿解氮和全氮呈顯著的正相關(guān)關(guān)系(<0.05),而與pH呈顯著的負(fù)相關(guān)關(guān)系,表明土壤CO2排放與土壤養(yǎng)分間有密切的聯(lián)系。
由表3可知,SH處理的凈初級(jí)生產(chǎn)力固碳量最高,為6 775.72 kg·hm-2,比QH、FG和CK處理分別提高了0.7%、14.7%和24.0%。不同還田方式對(duì)土壤微生物異養(yǎng)呼吸的碳釋放量有顯著影響,整體表現(xiàn)為FG>QH>SH>CK處理。不同還田方式各處理的碳平衡值均為正值,說明該小區(qū)生態(tài)系統(tǒng)是大氣CO2的吸收“匯”,整體表現(xiàn)為SH>CK>QH>FG處理,SH與QH、FG處理相比,土壤碳平衡值分別提高了23.37%和475.71%,且均達(dá)到了顯著性差異。土壤的固碳潛力表現(xiàn)為CK處理最高,其次是SH處理,兩個(gè)處理間,差異沒有達(dá)到顯著水平。而SH處理土壤固碳潛力顯著高于QH和FG處理,分別提高了7.1%和30.7%,表明不同秸稈還田方式中SH處理具有較強(qiáng)的固碳潛力。
表2 不同秸稈還田方式下水熱雙因素復(fù)合模型的擬合參數(shù)
擬合方程為2+2;:土壤CO2排放速率;:土壤含水量;:土壤溫度
The fitting equation is2+2;: Soil CO2emission rate;: Soil moisture content;: Soil temperature
圖7 不同秸稈還田方式下土壤溫度和含水量對(duì)土壤CO2排放速率的影響
表3 不同還田方式下玉米生長(zhǎng)季的碳平衡
:地上生物量;:凈初級(jí)生產(chǎn)力固碳量;:土壤微生物異養(yǎng)呼吸的碳釋放量;:生態(tài)系統(tǒng)碳平衡;當(dāng)是正值時(shí),表明該小區(qū)能夠作為大氣CO2的吸收“匯”,反之則是排放“源”;:土壤固碳潛力。同列不同字母表示差異顯著(<0.05)。下同
: Aboveground biomass;: Net primary productivity carbon sequestration;: Carbon emission by soil microbial heterotrophic respiration;: Ecosystem carbon balance; Whenwas positive, it indicated that the plot could be used as a "sink" of atmospheric CO2absorption; otherwise, it was the “source” of emissions;: Soil carbon sequestration potential. Different letters in the same column represent significant difference (<0.05). The same as below
圖8 土壤CO2累積排放量與土壤理化性狀相關(guān)分析
由表4可知,不同秸稈還田方式下玉米的穗粒數(shù)、百粒重和產(chǎn)量存在一定差異,但穗行數(shù)沒有達(dá)到差異顯著水平。2020年,各處理間玉米產(chǎn)量表現(xiàn)為SH>FG>QH>CK處理,在8 201.12—10 117.79 kg·hm-2間變化;2021年則表現(xiàn)為SH>QH>FG>CK處理,變化范圍為11 466.67—13 533.33 kg·hm-2。各處理玉米穗粒數(shù)與產(chǎn)量的變化趨勢(shì)相似。不同還田處理中SH處理顯著提高了玉米百粒重,與QH和FG處理相比,2年分別增加了4.63%、9.61%和4.11%、6.55%。
表4 不同秸稈還田方式下的玉米產(chǎn)量及其構(gòu)成因素
本研究中,在玉米生長(zhǎng)季前期QH處理與FG處理土壤CO2排放速率差異不大,但從6月中旬開始,F(xiàn)G處理土壤CO2排放速率明顯高于QH處理,可能是因?yàn)榍捌诮斩捙c土壤充分混合,使秸稈與土壤微生物直接接觸,刺激了微生物活性[18],到6月中旬,隨著易降解有機(jī)物質(zhì)的不斷消耗[19],QH處理下土壤CO2排放速率變小。在整個(gè)玉米生長(zhǎng)季,秸稈還田均增加了土壤CO2排放,可能有以下原因:(1)秸稈添加到土壤中,豐富了活性有機(jī)碳含量[20],進(jìn)而促進(jìn)土壤微生物代謝活動(dòng),增加了CO2排放,本研究中微生物量碳含量與CO2排放顯著的正相關(guān)關(guān)系也證實(shí)了這一點(diǎn)。(2)秸稈還田可以改善土壤肥力,促進(jìn)作物根系生長(zhǎng)和代謝[21],從而使來自根系的CO2排放量增加。(3)秸稈進(jìn)入土壤中加速了原有土壤有機(jī)質(zhì)的分解并引起正激發(fā)效應(yīng)[22],這都會(huì)導(dǎo)致土壤CO2排放增加。本研究結(jié)果表明,QH處理和SH處理下土壤CO2累積排放量顯著低于FG處理,這與閆翠萍等[23]研究發(fā)現(xiàn),秸稈還田至20 cm左右時(shí),土壤CO2累積排放量顯著高于覆蓋還田的結(jié)果存在差異。這可能與進(jìn)行秸稈還田前對(duì)土壤擾動(dòng)不同有關(guān),本文覆蓋還田和其他兩個(gè)還田方式均對(duì)不同土層土壤進(jìn)行翻動(dòng),對(duì)土壤擾動(dòng)一致,但其研究中只有秸稈還田至20 cm時(shí)對(duì)土壤進(jìn)行了擾動(dòng),而覆蓋還田為免耕播種,沒有擾動(dòng)土壤,導(dǎo)致郁閉在土壤中的氣體難以排放,故土壤CO2排放較低。同時(shí),本研究結(jié)果表明,不同秸稈還田方式中SH處理下土壤CO2累積排放量最低,一方面是因?yàn)楸韺油寥琅c底層土壤相比更易接觸氧氣,含有較高的C、N基質(zhì)供微生物活動(dòng),促進(jìn)了有機(jī)物的分解[24],另一方面,SH處理下土壤含水量明顯高于其余兩個(gè)處理,導(dǎo)致CO2在水中的溶解度變大,向地面擴(kuò)散的CO2減少[25]。此外,不同秸稈還田方式對(duì)土壤有機(jī)碳固定不同,有研究表明[26]秸稈深翻還田可以通過增加土壤有機(jī)碳固存來減少土壤CO2排放,于建光等[27]研究也發(fā)現(xiàn)土壤有機(jī)碳的穩(wěn)定性隨著土層深度的增加而增強(qiáng),深層土壤有機(jī)碳不易被微生物分解利用,所引起的激發(fā)效應(yīng)要小于表層土壤[28],因此,SH處理還田至20—40 cm土層的土壤呼吸較弱,CO2排放較低。
土壤溫度和土壤含水量是影響土壤CO2排放的重要環(huán)境因子。有研究指出[29],土壤溫度與土壤CO2排放速率呈指數(shù)關(guān)系,這與本文研究結(jié)果不一致。本研究中,土壤溫度與土壤CO2排放速率呈現(xiàn)較好的二次函數(shù)相關(guān)關(guān)系,當(dāng)土壤溫度達(dá)到一定值的時(shí)候,土壤CO2排放速率下降,并沒有隨著溫度的升高而增大,該結(jié)果與陳全勝等[30]研究發(fā)現(xiàn)土壤呼吸對(duì)土壤溫度的響應(yīng)存在一個(gè)適宜的范圍結(jié)論相一致,當(dāng)土壤溫度較高時(shí),一方面,土壤呼吸基質(zhì)數(shù)量和質(zhì)量發(fā)生變化,一些與呼吸作用相關(guān)的酶活性降低;另一方面,土壤中氮素的礦化速率增加,提高了可利用氮素含量,植物獲取氮素相對(duì)容易,使光合產(chǎn)物向地下根系分配的比例降低,影響了植物根系的代謝活動(dòng),進(jìn)而抑制了土壤呼吸。土壤含水量對(duì)土壤CO2排放的影響較為復(fù)雜,XU等[31]報(bào)道稱土壤含水量在20%左右有一個(gè)臨界值,超過這個(gè)臨界值,土壤含水量對(duì)土壤CO2排放的影響由正相關(guān)關(guān)系變?yōu)樨?fù)相關(guān)關(guān)系,與本文的研究結(jié)果一致,但也有研究表明[32]土壤CO2排放和土壤含水量之間沒有顯著的相關(guān)關(guān)系,原因可能是其研究區(qū)域土壤含水量變化范圍較窄,觀察到的值對(duì)土壤CO2排放的影響較弱[33];此外,土壤溫度是調(diào)節(jié)土壤含水量對(duì)CO2排放影響的重要因素,DING等[34]發(fā)現(xiàn)當(dāng)排除土壤溫度的混雜影響時(shí),極大地改善了土壤含水量與土壤CO2排放的關(guān)系,這是因?yàn)閮蓚€(gè)環(huán)境因素是同時(shí)變化的,土壤含水量對(duì)土壤CO2排放的影響被土壤溫度所掩蓋。有研究表明[35],當(dāng)土壤溫度或土壤含水量中的某一個(gè)因素處于較高或較低的范圍時(shí),另一個(gè)因素可能成為影響土壤CO2排放的主要因素。當(dāng)土壤含水量高于萎蔫系數(shù)時(shí),土壤CO2排放與土壤溫度密切相關(guān)[36];而當(dāng)土壤溫度較高時(shí),土壤CO2排放則隨著土壤含水量的變化而改變[37]。因此,單因素模型忽略了各因素間相互作用的影響,不能很好地描述土壤CO2排放。GOU等[38]認(rèn)為土壤溫度和土壤含水量的相互作用與土壤CO2排放之間具有更明顯的相關(guān)性,這一結(jié)果在本研究中也得到了證實(shí)。本研究發(fā)現(xiàn),土壤含水量和土壤溫度雙因素復(fù)合模型(2為0.785— 0.828)較單因素模型(2為0.213—0.737)相比,更好地解釋了土壤CO2排放速率變化。
除了受土壤溫度和含水量的影響外,土壤CO2排放還受到土壤理化性狀的影響。葛高飛等[39]研究表明,微生物量碳與土壤CO2排放有顯著的正相關(guān)關(guān)系,相關(guān)系數(shù)為0.80,本文也得到了相似的研究結(jié)果,這是因?yàn)橥寥牢⑸锖粑菢?gòu)成土壤CO2排放的重要部分,秸稈還田為微生物提供了豐富的碳源和能源,增加土壤微生物數(shù)量的同時(shí)也增加了土壤微生物量碳,提高微生物新陳代謝強(qiáng)度,加速土壤養(yǎng)分礦化進(jìn)而釋放更多的CO2[40]。有研究通過主成分分析表明[41],土壤理化性質(zhì)中土壤有機(jī)質(zhì)和碳氮鉀含量是土壤CO2排放的主要影響因子,與本文研究結(jié)果一致,而土壤磷含量對(duì)土壤CO2排放沒有影響,可能是因?yàn)榱撞⒉皇窃搮^(qū)域農(nóng)田的限制營(yíng)養(yǎng)元素。本研究中,pH與土壤CO2排放呈顯著的負(fù)相關(guān)關(guān)系,與WANG等[42]研究結(jié)果不一致,主要?dú)w因于土壤本身pH不同,本試驗(yàn)土壤呈弱酸性,而WANG等試驗(yàn)土壤環(huán)境是堿性的,堿性環(huán)境能夠更好的溶解和分散土壤有機(jī)物質(zhì),使微生物充分接觸有機(jī)質(zhì)并進(jìn)行分解,增加了微生物呼吸[43],進(jìn)而增加土壤CO2排放。
本研究中,各還田處理的碳平衡值為326.53— 1 879.87 kg·hm-2,說明進(jìn)行秸稈還田的各小區(qū)均是大氣CO2的吸收“匯”,這與在黃土高原地區(qū),秸稈還田后旱作春玉米田可作為一個(gè)碳匯的研究結(jié)果相符[44]。FG和QH較SH處理顯著降低了農(nóng)田碳匯效應(yīng),主要是因?yàn)镕G處理和QH處理兩種還田方式具有較高的土壤碳排放量,抵消了部分系統(tǒng)凈初級(jí)生產(chǎn)力固碳量,從而導(dǎo)致生態(tài)系統(tǒng)碳平衡值減小,弱化了農(nóng)田的碳匯作用。然而,也有一些研究表明[45],秸稈還田對(duì)農(nóng)田碳匯的影響微乎其微,甚至是負(fù)面的,可能是因?yàn)檫@些研究都是長(zhǎng)期試驗(yàn),長(zhǎng)期的秸稈還田使其土壤有機(jī)碳含量已經(jīng)達(dá)到了非常高的水平,進(jìn)而無法達(dá)到更高的碳平衡[46]。此外,LIU等[47]對(duì)已發(fā)表的176項(xiàng)研究進(jìn)行了meta分析,結(jié)果表明當(dāng)秸稈還田12年后,土壤碳接近飽和狀態(tài),農(nóng)田將達(dá)到新的碳平衡。由于本試驗(yàn)土壤有機(jī)質(zhì)相對(duì)較低,且秸稈還田只進(jìn)行了兩年,因此,我們認(rèn)為較低的土壤有機(jī)碳含量可能是該區(qū)域農(nóng)田表現(xiàn)為碳匯的主要原因,并且在有機(jī)碳含量未達(dá)到飽和之前,進(jìn)行秸稈還田作為農(nóng)田碳匯的效應(yīng)還將持續(xù)。WANG等[48]對(duì)中國(guó)農(nóng)田不同管理措施下土壤固碳潛力進(jìn)行預(yù)測(cè),發(fā)現(xiàn)秸稈還田措施具有最大的固碳潛力,可達(dá)34.4 Tg C·a-1。本研究發(fā)現(xiàn),SH處理土壤固碳潛力略低于CK處理,主要是因?yàn)榻斩掃€田向土壤中帶入了大量的有機(jī)質(zhì)[49],導(dǎo)致玉米生長(zhǎng)季內(nèi)有較高的土壤呼吸,增大了碳輸出量,進(jìn)而降低了土壤的固碳潛力。但劉平齊等[13]認(rèn)為,秸稈還田后,由于秸稈碳輸入導(dǎo)致的土壤呼吸增加,這并不能簡(jiǎn)單看作是土壤有機(jī)碳的損失或增加CO2排放的過程,此時(shí)土壤呼吸更多表示的是土壤動(dòng)物和微生物的活性強(qiáng)弱。若將本研究中不還田處理的秸稈全部進(jìn)行燃燒,根據(jù)玉米秸稈燃燒排放因子進(jìn)行計(jì)算[50],可產(chǎn)生19 833.33—21 262.50 kg·hm-2的CO2,加上不還田處理排放的CO2,其土壤CO2釋放總量達(dá)到36 435.57— 36 786.74 kg·hm-2,接近秸稈還田的2倍,因此綜合來看,SH處理的固碳潛力較優(yōu)。
在玉米生長(zhǎng)季,秸稈還田處理顯著增加了土壤CO2排放,不同秸稈還田方式下土壤CO2累積排放量表現(xiàn)為秸稈覆蓋>秸稈淺層還田>秸稈深層還田>無秸稈還田處理。土壤溫度和土壤含水量雙因素復(fù)合模型可以解釋78.5%—82.8%的土壤CO2排放速率變化,土壤pH和土壤養(yǎng)分(碳氮鉀)含量對(duì)土壤CO2排放也存在顯著影響。不同秸稈還田方式下土壤碳平衡均為正值,其中秸稈深還處理有較高的土壤碳平衡值,達(dá)到1 879.87 kg·hm-2,表現(xiàn)出較強(qiáng)的碳“匯”功能,同時(shí)能夠增加土壤固碳潛力和提高作物產(chǎn)量。因此,本試驗(yàn)條件下,綜合考慮固碳減排效應(yīng)和產(chǎn)量,3種秸稈還田方式相比,秸稈深層還田(SH)是一種較好的還田方式。
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Effects of Different Straw Returning Patterns on Soil CO2Emission and Carbon Balance in Maize Field
LI Jin, REN LiJun, LI XiaoYu, BI RunXue, JIN XinXin, YU Na, ZHANG YuLing, ZOU HongTao, ZHANG YuLong
College of Land and Environment, Shenyang Agricultural University/Key Laboratory of Arable Land Conservation (Northeast China), Ministry of Agriculture and Rural Affairs/National Engineering Research Center for Efficient Utilization of Soil and Fertilizer Resources, Shenyang 110866
【Objective】The effects of different straw returning patterns on soil carbon dioxide (CO2) emission characteristics and carbon balance were discussed, which provided a scientific basis for carbon (C) sequestration and emission reduction as well as the selection of straw returning patterns in Northeast China. 【Method】A field micro-plot experiment were conducted with maize as the experimental crop, and three straw returning patterns were set up, including straw shallow returning (QH), straw deep returning (SH), and straw mulching (FG). No straw returning (CK) was used as the control treatment. The LI-8100A automatic soil C flux tester was used to monitor soil CO2emission characteristics under different straw returning patterns during the maize growth period. Effects of soil temperature, soil moisture content, pH, MBC, available nutrients and total nutrients of nitrogen, phosphorus and potassium on soil CO2emissions were analyzed, and soil carbon balance was investigated too. 【Result】During the maize season, soil CO2emission rates showed a trend of first increasing and then decreasing under different straw returning patterns. The cumulative soil CO2emissions were as follows: FG>QH>SH>CK treatment. Compared with SH treatment, the cumulative soil CO2emissions under FG and QH treatments increased by 14.0% and 6.4%, respectively. There was a significant difference between the treatments (<0.05). The single factor model fitting of soil CO2emission rates, soil temperature and soil moisture content under different straw returning patterns showed a quadratic function correlation, and reached a significant level (<0.05), soil temperature could explain the variation of soil CO2emission rate of 68.2%-73.7%, and soil moisture content could explain 21.3%-37.5%. However, the two-factor composite model of soil temperature and soil moisture content could better explain the variation of soil CO2emission rate, with an explanation of 78.5%-82.8%. Correlation analysis showed that cumulative CO2emissions were significantly correlated with available potassium and MBC (<0.01), and significantly correlated with soil organic matter, available nitrogen, total nitrogen, and pH (<0.05). The soil carbon balance was positive under different straw returning patterns, which were the "sink" of atmospheric carbon dioxide. The soil carbon balance and carbon sequestration potential under the SH treatment were significantly higher than the QH and FG treatments by increased of 23.4%, 475.7% and 7.1%, 30.7% (<0.05), respectively. Compared with other treatments, the SH treatment showed a strong carbon "sink" function. In the two-year harvest period, straw returning treatments significantly increased maize yield, SH treatment had the highest maize yield, but there was no significant difference with QH and FG treatments. 【Conclusion】Therefore, under the conditions of this experiment, taking into account the carbon sequestration and emission reduction effect and yield, SH was a better straw returning pattern compared with the three patterns.
straw returning patterns; soil CO2emission; soil temperature; soil moisture content; maize yield; carbon balance
10.3864/j.issn.0578-1752.2023.14.009
2022-07-08;
2022-11-14
遼寧省教育廳重點(diǎn)項(xiàng)目(LSNZD202001)、遼寧省“興遼英才計(jì)劃”領(lǐng)軍人才項(xiàng)目(XLYC1905010)
李金,Tel:15524365461;E-mail:lijin149917@163.com。通信作者鄒洪濤,E-mail:zht@syau.edu.cn
(責(zé)任編輯 李云霞)