王 淼，曲來葉，馬克明，李桂林，楊小丹

(1. 中國科學(xué)院生態(tài)環(huán)境研究中心城市與區(qū)域生態(tài)國家重點實驗室，北京 100085;2. 中國科學(xué)院大學(xué)，北京 100049; 3. 內(nèi)蒙古賽罕烏拉國家自然保護區(qū)管理局，赤峰 025150;4. 內(nèi)蒙古赤峰市巴林右旗環(huán)境保護局， 赤峰 025150)

罕山土壤微生物群落組成對植被類型的響應(yīng)

王 淼1,2，曲來葉1,*，馬克明1，李桂林3，楊小丹4

(1. 中國科學(xué)院生態(tài)環(huán)境研究中心城市與區(qū)域生態(tài)國家重點實驗室，北京 100085;2. 中國科學(xué)院大學(xué)，北京 100049; 3. 內(nèi)蒙古賽罕烏拉國家自然保護區(qū)管理局，赤峰 025150;4. 內(nèi)蒙古赤峰市巴林右旗環(huán)境保護局， 赤峰 025150)

選取分布在中國東北部地區(qū)的闊葉林-針葉林-亞高山草甸這一明顯的植被垂直帶譜來研究植被類型對土壤微生物群落組成的影響。選取5種植被類型-山楊(Populusdavidiana)(1250—1300 m)，山楊(P.davidiana)與白樺(Betulaplatyphylla)的混交林(1370—1550 m)，白樺(B.platyphylla)(1550—1720 m)，落葉松(Larixprincipis-rupprechtii)(1840—1890 m)，亞高山草甸(1900—1951 m)，采用磷脂脂肪酸(Phopholipid Fatty Acids, PLFAs)分析方法測定不同植被類型下的土壤微生物群落組成。分別采用主成分分析(Principal Components Analysis, PCA)以及冗余分析(Redundancy Analysis, RDA)來解釋單種特征PLFAs的分異以及土壤理化指標(biāo)與微生物PLFAs指標(biāo)間的相關(guān)性。結(jié)果表明不同植被類型下土壤有機碳(SOC)對土壤微生物PLFAs總量，各類群(真菌(f)、細菌(b)、革蘭氏陽性菌(G+)、革蘭氏陰性菌(G-))生物量以及群落結(jié)構(gòu)影響顯著；土壤微生物PLFAs總量及各類群的生物量隨土層加深總體上表現(xiàn)降低趨勢，G+/G-和f/b分別隨土層加深總體上表現(xiàn)升高趨勢。不同植被類型下，闊葉混交林土壤PLFAs總量及各類群生物量總體上最高；針葉林比闊葉林下的f/b和G+/G-高；亞高山草甸下低的pH值對有機碳的可利用性有一定的抑制作用，導(dǎo)致f/b和G+/G-的值相對較高?？傊煌脖活愋拖耂OC對土壤微生物群落組成的影響最為顯著，而較低的pH對有機碳的可利用性有一定的抑制作用；真菌對植被類型的變化比細菌更敏感，而細菌更易受可利用性養(yǎng)分和pH變異的影響，這對預(yù)測不同林型下的土壤微生物群落組成有重要的啟示作用。

磷脂脂肪酸(PLFAs); 土壤微生物群落; 植被; 土壤有機碳(SOC)

土壤微生物在養(yǎng)分循環(huán)中扮演著重要角色[1- 3]。了解不同驅(qū)動因子對土壤微生物群落變化的相對影響力具有重要的生態(tài)學(xué)意義[4- 5]；為更好地解釋植被演替過程[6- 7]、人為干擾(放牧、火燒)[8- 9]后及不同土地利用類型下[10]土壤微生物群落組成、植被組成及土壤性質(zhì)之間的相互作用機制提供重要啟示。土壤微生物群落的組成和功能隨氣候[11- 12]，土壤理化性質(zhì)[13- 14]和植被組成[15- 16]而變化。

土壤是植被與土壤微生物相互作用的載體，因此，土壤理化性質(zhì)會影響微生物群落組成[17- 18]。由于植被與土壤相互影響的復(fù)雜性，目前對于各種因素對微生物不同類群的影響機制和效應(yīng)還沒有一致性的結(jié)論?？偟膩碚f，在同一氣候區(qū)內(nèi)，影響土壤微生物組成的眾多理化性質(zhì)中，土壤有機質(zhì)、土壤含水量、pH值、可利用性的C和N通常比較主要[15,19- 21]。植物凋落物分解是陸地生態(tài)系統(tǒng)中養(yǎng)分和能量流動中的重要環(huán)節(jié)[22]，通過向土壤中輸入凋落物[23]，枯死根[24]以及根系分泌物[25]，為微生物生長提供養(yǎng)分，因此對土壤微生物的組成和活性有關(guān)鍵性影響。不同植物種的凋落物和根系分泌物中碳的質(zhì)量有差異[26- 27]，可以顯著影響土壤微生物組成[28]。Merila 等[6]通過研究闊葉林與針葉林下土壤微生物群落組成和功能的差異，發(fā)現(xiàn)碳源的可利用性與微生物群落密切相關(guān)，來源于凋落物和根系分泌物的有機質(zhì)組分的差異對土壤微生物群落組成和植被演替過程影響很大。Brockett 等[12]通過研究區(qū)域性的氣候梯度下七種林型的土壤微生物群落組成，表明土壤含水量對微生物的影響很大。土壤pH升高可以使土壤微生物群落由真菌主導(dǎo)型發(fā)展為細菌主導(dǎo)型[13- 14]。真菌更適宜在高C∶N土壤中生長，而細菌則相反[14,29]，因此土壤C∶N可以很好地預(yù)測土壤微生物群落[30]；而土壤有機層中的可利用性C和N絕大部分來自植物凋落物分解過程釋放的有機質(zhì)[31]。

磷脂脂肪酸(PLFAs)分析方法最早由Bligh and Dyer[32]提出，經(jīng)過不斷完善[33- 34]，已經(jīng)被廣泛用于微生物群落組成的測定。土壤中，PLFAs的總量提供了微生物生物量的信息[33,35]，而特征脂肪酸的組成則可反映微生物群落結(jié)構(gòu)[34,36]。

本文以罕山陰坡連續(xù)分布的闊葉林—針葉林—亞高山草甸這一明顯的植被垂直帶譜為對象，研究植被類型變化對土壤微生物群落組成的影響，其中山楊(Populusdavidiana)、白樺(Betulaplatyphylla)和落葉松(Larixprincipis-rupprechtii)，均為中國東北部森林常見的優(yōu)勢樹種。通過對闊葉林與針葉林、純林與混交林、喬木與草本下主要土壤微生物類群-真菌(f)、細菌(b)、革蘭氏陽性菌(G+)及革蘭氏陰性菌(G-)的PLFAs在不同土層中分布與含量規(guī)律的研究，探討土壤微生物群落結(jié)構(gòu)對植被類型的響應(yīng)以及影響土壤微生物群落結(jié)構(gòu)的因素。

1 材料和方法

1.1 樣地描述

研究區(qū)域位于內(nèi)蒙古賽罕烏拉自然保護區(qū)(43°59′—44°27′N, 118°18′—118°55′E)東南部的第2高峰——罕山(海拔1951 m)。該區(qū)年平均氣溫2 ℃，7月份最熱，最高氣溫29 ℃，年平均降水量達400 mm，多集中在6—8月份，夏季降水歷年平均在300 m左右，占全年降水量70%—80%。植被類型在陰坡呈現(xiàn)明顯的垂直分布，沿海拔由低到高優(yōu)勢種依次為山楊(Populusdavidiana)(P)(海拔1250—1300 m)，白樺(Betulaplatyphylla)和山楊混交林(BP)(1370—1550 m)，白樺(B.platyphylla)(B)(1550—1720 m)，落葉松(Larixprincipis-rupprechtii)(L)(1840—1890 m)，亞高山草甸(SM)(1900—1951 m)。在林下灌叢植被中，虎榛子(Ostryopsisdavidiana)灌叢分布最為廣泛，多生于白樺林下緣與采伐跡地；在虎榛子灌叢上緣，小面積的興安杜鵑(Rhododendrondahuricum)灌叢多分布在森林破壞后的地塊中。落葉闊葉林下的土壤為典型的棕壤，針闊混交林下為灰色森林土，隨海拔升高，山頂亞高山草甸植被下分布著山地黑土。樣地的土壤理化性質(zhì)如表1所示。

表1 5種植被類型下土壤理化性質(zhì) (平均值±標(biāo)準差，n=3)

P:山楊林；BP:白樺與山楊混交林；B:白樺林；L:落葉松林；SM:亞高山草甸; TC:總碳；TN:總氮；AN:有效氮；SOC:土壤有機碳；C/N=SOC/TN；SWC:土壤質(zhì)量含水率；同一行中不同小寫字母代表不同植被間差異顯著

1.2 樣品采集

2010年8月，在上述五種植被類型下，分別隨機選取3塊20 m×20 m的樣地；用直徑為5 cm的土鉆在每塊樣地的優(yōu)勢物種下分別隨機采集3份0—5 cm，5—10 cm，10—20 cm土樣，將每個土層的3份土樣混合后作為一個樣；每份土樣分成兩部分，一部分過2 mm篩后用于微生物磷脂脂肪酸(PLFAs)測定的土樣保存于-80 ℃；另一部分土樣用于土壤理化性質(zhì)測定，樣品過2 mm篩后自然風(fēng)干。

1.3 研究方法

1.3.1 土壤微生物群落PLFAs測定

土壤微生物群落PLFAs采用Bligh and Dyer[32]和Frosteg?rd 等[33]介紹的方法提取，將樣品進到GC-MS中測定。脂肪酸的命名規(guī)則如下：一般用總碳原子數(shù)：雙鍵數(shù)ω烯鍵距甲基端的位置表示。后綴c，t分別表示雙鍵兩側(cè)-H鍵的順式與反式，前綴a，i分別表示支鏈的異型和同型，環(huán)丙烷脂肪酸用cy表示[36- 37]。特征磷脂脂肪酸的分類如表2所示。飽和脂肪酸/單不飽和脂肪酸(SATFA/MUFA)通常作為細菌群落中養(yǎng)分脅迫的指示者[19]。

表2 特征磷脂脂肪酸(PLFAs)分類

SATFA: 飽和脂肪酸saturated fatty acids；MUFA:單不飽和脂肪酸mono-unsaturated fatty acids；G+，革蘭氏陽性菌；G-，革蘭氏陰性菌；f，真菌；b，細菌

1.3.2 土壤理化性質(zhì)測定

過2 mm篩后自然風(fēng)干后的土壤參考《土壤農(nóng)化分析》[44]測定理化性質(zhì)。土壤含水量(SWC)經(jīng)105 ℃連續(xù)烘干恒重后計算得出；pH值用酸度計(土∶水=1∶2.5)測定；土壤有機碳(SOC)采用重鉻酸鉀氧化外加熱法；土壤有效氮(AN)采用堿解擴散法；土壤總碳、總氮采用元素分析儀(Vario EL, Elementar, Ger)測定。不同植被類型下的土壤理化性質(zhì)如附表所示。

1.4 數(shù)據(jù)分析

采用SPSS13.0 (SPSS Institute Inc., 2002)進行簡單統(tǒng)計分析。采用單因素方差分析(One-way ANOVA)檢驗不同植被，不同土層下土壤理化性質(zhì)、土壤微生物量及土壤微生物群落PLFAs差異的顯著性。

采用CANOCO軟件(Canoco for Windows 4.5)對不同植被類型，不同土層中微生物群落的特征PLFAs (mol%)進行主成分分析(Principal Components Analysis, PCA)。對土壤理化性質(zhì)、土壤微生物各類群PLFAs比例及土壤微生物量之間的關(guān)系進行冗余分析(Redundancy Analysis, RDA)。數(shù)據(jù)分析前進行l(wèi)og轉(zhuǎn)換，通過蒙特卡羅顯著性檢驗(Monte Carlo permutation test)篩選出對土壤微生物參數(shù)解釋度呈現(xiàn)顯著性(P<0.05)的環(huán)境變量。

2 結(jié)果分析

2.1 土壤微生物群落PLFAs分析

利用PCA分析不同植被類型，不同土層中的土壤微生物群落PLFAs圖譜(圖1—圖3)。如圖1a、圖2a、圖3a所示，3個土層中，PC1和PC2對不同植被類型下PLFAs(mol%)變異的總解釋度均大于80%，可以較全面地反映出PLFAs(mol%)的變異信息，且PC1的解釋度均遠遠高于PC2；代表不同植被類型的點聚集程度不一致，表明不同植被類型下土壤微生物群落組成具有很大差異。特征PLFAs(mol%)在5種植被類型下的分布如圖1b、圖2b、圖3b所示，可以將單個特征PLFAs的坐標(biāo)與植被類型對應(yīng)起來。通過特征PLFAs(mol%)與PC1、PC2的相關(guān)性分析(表3)可以得出兩個主成分軸上所包含的PLFAs信息。

圖1中0—5cm土層中，BP在PC1上的得分最高，其下土壤特征PLFAs中，i17:1、i15:0、i16:0、16:1ω7c與16:1ω5c占的比重較高；L與PC1、PC2均具有很高的相關(guān)性，15:0 3OH，a15:0，16:1 2OH，18:1ω5c和cy17:0為主要特征PLFAs；P、SM、B 3種植被聚集分布，在PC2上的得分較高，其下土壤特征PLFAs主要包括20:4ω6c，17:1ω8c，17:0，16:0，i17:0，15:0，14:0，a17:0，16:1ω7c。

圖1 5種植被類型下0—5 cm土層中土壤微生物PLFAs (mol%) 分布的PCA分析 Fig.1 PCA of soil microbial PLFAs(mol%) collected within 0—5 cm soil depth under five vegetation types 圖a中誤差線分別為PC1、PC2得分的標(biāo)準差，n=3;a: 不同土壤中的土壤微生物群落PLFAs圖譜; b: 特征PLFAs在5種植被類型下的分布

5—10 cm土層中，5種植被分布較分散，其下特征PLFAs分布差異大(圖2)。B在PC1上的得分最高，其下PLFAs主要為16:1 2OH，a15:0，17:0，20:4ω6c，20:0；SM下PLFAs主要包括i17:1，16:1ω7c，18:1ω9t，18:0，16:1ω5c，16:0，14:0，15:0；18:2ω6c，18:1ω9c，i15:0及cy17:0在L下占比重很大；BP下特征PLFAs主要包括18:1ω5c與15:0 3OH；P下主要為16:0，18:0，15:0，i16:1，14:0，16:1ω5c。

10—20 cm土層中，PC1與PC2對PLFAs(mol%)總變異的解釋度在3個土層中最高(98.2%)(圖3)。BP和SM在PC1下得分較高，但其下PLFAs種類較少，主要為 i17:1和a15:0；B與L聚集分布，特征PLFAs主要為16:1ω7c，16:1ω5c，16:0，15:0 3OH，cy17:0，18:2ω6c，18:1ω9c，18:1ω5c，18:0；P下主要為i14:0，i17:0，i16:0，i16:1，i15:1，a17:0，i15:0。

圖2 5種植被類型下5—10 cm土層中土壤微生物PLFAs (mol%) 分布的PCA分析 Fig.2 PCA of soil microbial PLFAs(mol%) collected within 5—10 cm soil depth under five vegetation types圖a中誤差線分別為PC1、PC2得分的標(biāo)準差，n=3

圖3 5種植被類型下10—20 cm土層中土壤微生物PLFAs (mol%) 分布的PCA分析Fig.3 PCA of soil microbial PLFAs (mol%) collected within 10—20 cm soil depth under five vegetation types圖a中誤差線分別為PC1、PC2得分的標(biāo)準差，n=3

對五種植被下3個土層中的微生物總量(PLFAs(T))及各類群PLFAs(真菌(f)、細菌(b)、革蘭氏陽性菌(G+)、革蘭氏陰性菌(G-))濃度進行比較分析，結(jié)果如表4所示。PLFAs(T)和微生物各類群PLFAs濃度在0—20cm土層梯度上總體表現(xiàn)出降低趨勢；但是，5—10 cm和10—20 cm土層，PLFAs(T)、G-和f分別在B、L和SM下表現(xiàn)出相反趨勢。0—5 cm和5—10 cm土層，PLFAs(T)和微生物各類群PLFAs濃度隨植被類型的變化規(guī)律總體上一致。0—10 cm土層，PLFAs(T)和各類群PLFAs濃度(除f外)在BP下均為最高，在其余4種植被下，PLFAs(T)和b隨海拔升高而降低。10—20 cm土層，PLFAs(T)和微生物各類群PLFAs濃度(除b外)在P下均最高；PLFAs(T)和b在B下均最低；G-和f分別在L和BP下最低。

表3 5種植被類型下3個土層中特征PLFAs (mol%)與主成分PC1和PC2的相關(guān)性分析

*P<0.05; **P<0.01

根據(jù)特征PLFAs的分類(表1)，對各類PLFAs的比值在不同植被類型、不同土層間的差異進行分析(圖4)?？梢钥闯?，在0—20 cm土層梯度上，G+/G-在各植被類型(除SM)下總體上表現(xiàn)出增大趨勢。0—5 cm土層中，G+/G-在L下最低，在其余四種植被下無顯著性差異(P>0.05)；5—10 cm土層中，G+/G-在L下最高，其次是SM、P，在BP和B下無顯著性差異；10—20 cm土層中，G+/G-在BP和L下最高，其次是P，在B和SM下無顯著性差異。

表4 五種植被類型下3個土層中各種微生物類群的PLFAs濃度 (平均值(標(biāo)準差，n=3))/(nmol/g干土)

PLFAs(T): 磷脂脂肪酸總量；同一行中不同小寫字母代表不同植被間差異顯著

圖4 5種植被類型下3個土層中G+/G-與f/b比較 (標(biāo)準差，n=3)Fig.4 Comparison of G+/G- and f/b within three soil layers under five vegetation types (SD，n=3)G+/G-: 革蘭氏陽性菌/革蘭氏陰性菌；f/b: 真菌/細菌

0—20 cm土層梯度上，f/b在各植被類型(除SM外)下總體上表現(xiàn)出升高趨勢。0—5 cm土層中，f/b在前4種植被下無顯著差異，在SM下最高；5—10 cm土層中，f/b在L和SM下最高，P與B下最低；10—20 cm土層中，f/b在B和L下最高，BP與SM下最低。

0—10 cm土層梯度上，SATFA/MUFA在各植被類型下(除P外)表現(xiàn)出升高趨勢(圖5)；0—20 cm土層梯度上，SATFA/MUFA在B和L下表現(xiàn)出升高趨勢，而在SM下表現(xiàn)出降低趨勢。3個土層中，SATFA/MUFA均在L下最高，其次是B和P；0—5cm土層，SATFA/MUFA在BP下最低；5—10 cm和10—20 cm土層，SATFA/MUFA在SM下最低。

圖5 5種植被類型下3個土層中SATFA/MUFA的比較 (標(biāo)準差，n=3)Fig.5 Comparison of SATFA/MUFA within three soil layers under five vegetation types (SD, n=3)SATFA/MUFA： 飽和脂肪酸/單不飽和脂肪酸saturated fatty acids/mono-unsaturated fatty acids

2.2 土壤理化性質(zhì)與土壤微生物群落組成的相關(guān)性分析

如圖6所示，PC1和PC2分別解釋微生物群落組成變異的39.3%和2.2%。土壤微生物各類群PLFAs濃度在PC1上的得分中，b(0.74)、G+(0.74)和SATFA(0.74)最高，f(-0.44)最低；各類群PLFAs的比例在PC1上的得分由大到小依次為f/b(-0.6)、G+/G-(-0.29)和SATFA/MUFA(-1.1)。通過Monte Carlo置換檢驗，得出對微生物群落組成各參數(shù)變異的解釋度具有顯著性的土壤理化指標(biāo)為土壤有機碳(SOC)(P=0.001；F=24.08)；由各環(huán)境因子的箭頭長度和與PC軸的夾角可以看出，對微生物指標(biāo)影響最高的是SOC，其次是總碳(TC)，影響最低的是C/N。土壤微生物各類群PLFAs(除f外)濃度均與各理化指標(biāo)呈現(xiàn)正相關(guān)關(guān)系，其中，b、G+和SATFA與SOC的正相關(guān)關(guān)系最顯著；f與各理化指標(biāo)(除有效氮(AN)外)均呈現(xiàn)負相關(guān)關(guān)系，其中，與pH的負相關(guān)關(guān)系最顯著。土壤微生物各類群PLFAs的比例均與土壤理化指標(biāo)呈現(xiàn)負相關(guān)關(guān)系；其中，f/b受SOC和pH的影響最大；G+/G-和SATFA/MUFA受SOC和TC的影響最大。

表5 土壤理化性質(zhì)，植被類型與土層深度之間的相關(guān)性分析

PLFAs(T): PLFAs總量；TC: 總碳；TN: 總氮；SWC: 土壤含水量；SOC: 土壤有機碳；AN: 有效氮；C/N=SOC/AN; *P<0.05；**P<0.01

圖6 五種植被類型下土壤微生物群落組成與土壤理化性質(zhì)的RDA分析Fig.6 RDA analyses for soil microbial community composition and soil propertiesPLFAs(T): PLFAs總量；TC: 總碳；TN: 總氮；SWC: 土壤含水量；SOC: 土壤有機碳；AN: 有效氮；C/N=SOC/AN

3 討論

PLFAs(T)和各類群(G+, G-, f, b)的PLFAs含量隨土層加深總體上表現(xiàn)降低趨勢(表4)，這與可利用性養(yǎng)分的含量隨凋落物分解進程在土層梯度上不斷降低[45- 46]密切相關(guān)。微生物的特征PLFAs含量與養(yǎng)分的可利用性呈現(xiàn)正相關(guān)關(guān)系[6, 10,29,47]，所以不同植被下土壤養(yǎng)分的可利用C和N的差異導(dǎo)致了微生物群落組成的變異[48- 49]。Fierer 等[50]在平原和谷地的不同土層剖面上對土壤微生物群落組成變異的研究結(jié)果一致，隨土層深度而降低的可利用性C含量與土層間的微生物組成差異有關(guān)[18,51]。

RDA分析表明，SOC對土壤微生物群落組成的影響最大(圖6)，這與Saetre和Baath[52]的觀點一致，雖然不同樹種對土壤濕度及下層植被的影響有差異，但植被對土壤微生物群落組成的影響主要來自植被向土壤中輸入的不同質(zhì)量的有機質(zhì)[53]。對不同土層、不同植被類型下單種特征PLFAs(mol%)的PCA分析(圖1—圖3)表明不同植被下PLFAs的種類及含量有顯著差異[7, 15- 16]；源于不同植物的凋落物[54]或根系分泌物[55]釋放的不同質(zhì)量的碳[27]。3個土層中，BP在PC1的得分最高，表明其下土壤特征PLFAs(mol%)對總變異的貢獻最大。BP由落葉闊葉林B和P組成，凋落物的多樣性對基質(zhì)的可利用性存在正效應(yīng)[56]，導(dǎo)致其下PLFAs(T)在0—10 cm土層最高(表4)。而SM下0—10 cm土層PLFAs(T)表現(xiàn)出最低值，可能是pH較低降低了C的可利用性[57- 58]。王欣[59]對燕山華北落葉松人工林葉凋落物分解特性的研究中表明，凋落葉中的C/N由大到小依次為落葉松、白樺、山楊，落葉松凋落物高濃度酚類物質(zhì)和高C∶N[31,60]導(dǎo)致其向土壤中輸入的可利用性養(yǎng)分較少[6,61](表1)。

細菌和真菌共同組成了超過90%的土壤微生物生物量[13,62]，且細菌主要利用易分解有機質(zhì)[63]，所以細菌PLFAs含量與PLFAs(T)的變化具有一致性，與Pennanen 等[29]在芬蘭Hailuoto島的西海岸沿植被原生演替梯度的研究結(jié)果一致(圖6，表4)。由于隨土層加深C的可利用性降低[64]，不利于細菌生長[65- 66]；另外，逐漸降低的pH值環(huán)境也不利于細菌生長[21,67]。f/b在4種喬木林下(除SM外)均表現(xiàn)出隨土層加深而升高的趨勢(圖1—圖4)，與養(yǎng)分梯度和pH值的變化一致(表5)。落葉松下f/b的值高于3種闊葉林，這是由于針葉中的酚類物質(zhì)含量顯著高于闊葉，限制了細菌的生長[65- 66]，而同時，落葉松根系中共生的菌根真菌也對f/b貢獻很大[68]；草本植物的根系大多在0—10 cm土層[50]；而pH值在這層也最低，不利于細菌群落生長[13- 14]，所以草甸f/b在0—10 cm土層內(nèi)的值最高。該區(qū)域的研究表明，植物通過根際沉積物的形式釋放的C為根際微生物提供能量和結(jié)構(gòu)物質(zhì)的來源[69]，pH值對f和b均有較大影響。一些菌根真菌會與特定植物的根形成共生結(jié)構(gòu)[70]；因此真菌對植被類型的變化比細菌更敏感；而細菌對可利用性養(yǎng)分和pH值的變異更敏感。

G+和G-是細菌的兩大類群，G-比G+在富營養(yǎng)環(huán)境中生長地更迅速[46]，而G+則對分解木質(zhì)素和纖維素的貢獻相對較大[71]。隨土層加深凋落物中難分解的有機質(zhì)比重增加，導(dǎo)致G+的比重增加；可利用性養(yǎng)分隨土層加深而繼續(xù)降低，因此導(dǎo)致G+/G-隨土層梯度表現(xiàn)出升高趨勢(除白樺林外)(圖4)。細根對水分和養(yǎng)分有很強的吸收作用[72- 73]，細根對養(yǎng)分的吸收促進了深層土壤中G-的生長[74]。先鋒樹種的根系分布較淺，北方森林表層30 cm的土壤內(nèi)細根約占80%—90%，針葉林的細根總量小于闊葉林[75]。落葉松林0—5 cm土層中G+/G-低于其他闊葉林，與總的有機質(zhì)含量在落葉松最低有關(guān)(表1)，隨土層加深針葉中高濃度酚類物質(zhì)釋放抑制G-生長[71]，導(dǎo)致G+/G-在落葉松林下最高。而草甸下G+/G-隨土層梯度表現(xiàn)的先升高后降低趨勢可能由于5—10 cm土層中易分解有機質(zhì)降低及較低的pH值抑制了G-[29, 36]，而在10—20 cm土層pH及SOC同時升高促進了G-的生長[57- 58]。

MUFA中大部分是G-的特征PLFAs[19]，而G+的特征PLFAs全部為SATFA，因此0—10 cm土層梯度上，SATFA/MUFA與G+/G-的變化一致，隨養(yǎng)分降低而升高[19,50,76]。由于混交林有機質(zhì)種類豐富且含量高導(dǎo)致向土壤輸入的可利用性養(yǎng)分多[77]，而SATFA/MUFA通常在養(yǎng)分高的環(huán)境下較低[76]，所以導(dǎo)致0—5 cm土層SATFA/MUFA在混交林下最低。而由于針葉中的可利用性養(yǎng)分含量相對較低及高濃度的酚類物質(zhì)限制了G-的生長[71, 78]，因而3個土層中，SATFA/MUFA在落葉松下均最高。0—20 cm土層中，草甸下SATFA/MUFA與G+/G-隨土層梯度的變化一致，受pH值影響較大。

4 結(jié)論

本文在不同海拔五種植被類型下的研究發(fā)現(xiàn)土壤有機碳(SOC)對土壤微生物群落組成的影響最為顯著。土壤微生物PLFAs總量及各類群(f, b, G+, G-)的生物量隨土層加深總體上表現(xiàn)降低趨勢，與土壤可利用性養(yǎng)分的降低有關(guān)。G+/G-和f/b分別隨土層加深總體上表現(xiàn)升高趨勢，均與可利用性養(yǎng)分的降低和pH值的升高有關(guān)?；旖涣諦P凋落物種類豐富，向土壤輸入的可利用性碳含量最高，因此其下土壤PLFAs總量及各類群生物量總體上最高；落葉松與闊葉林相比，由于針葉中含高濃度酚類物質(zhì)，向土壤輸入的可利用性碳含量低，因此f/b和G+/G-值高；亞高山草甸下低的pH值影響了有機碳的可利用性，對f/b和G+/G-影響顯著。綜上，不同植被類型下土壤微生物群落組成的差異顯著，而較低的pH值對有機碳的可利用性有一定的抑制作用，這對預(yù)測不同林型下的土壤微生物群落組成有重要的啟示作用。

[1] Schimel J P, Bennett J. Nitrogen mineralization: Challenges of a changing paradigm. Ecology, 2004, 85(3): 591- 602.

[2] Carney K M, Matson P A. Plant communities, soil microorganisms, and soil carbon cycling: Does altering the world belowground matter to ecosystem functioning? Ecosystems, 2005, 8(8): 928- 940.

[3] Mitchell R J, Keith A M, Potts J M, Ross J, Reid E, Dawson L A. Overstory and understory vegetation interact to alter soil community composition and activity. Plant and Soil, 2012, 352(1- 2): 65- 84.

[4] Reynolds H L, Packer A, Bever J D, Clay K. Grassroots ecology: Plant-microbe-soil interactions as drivers of plant community structure and dynamics. Ecology, 2003, 84(9): 2281- 2291.

[5] van der Heijden M G A, Bardgett R D, van Straalen N M. The unseen majority: soil microbes as drivers of plant diversity and productivity in terrestrial ecosystems. Ecology Letters, 2008, 11(3): 296- 310.

[6] Merila P, Malmivaara-Lamsa M, Spetz P, Stark S, Vierikko K, Derome J, Fritze H. Soil organic matter quality as a link between microbial community structure and vegetation composition along a successional gradient in a boreal forest. Applied Soil Ecology, 2010, 46(2): 259- 267.

[7] Mitchell R J, Hester A J, Campbell C D, Chapman S J, Cameron C M, Hewison R L, Potts J M. Is vegetation composition or soil chemistry the best predictor of the soil microbial community? Plant and Soil, 2010, 333(1- 2): 417- 430.

[8] Hiltbrunner D, Schulze S, Hagedorn F, Schmidt M W I, Zimmmermann S. Cattle trampling alters soil properties and changes soil microbial communities in a Swiss sub-alpine pasture. Geoderma, 2012, 170(1- 2): 369- 377.

[9] White C, Tardif J C, Adkins A, Staniforth R. Functional diversity of microbial communities in the mixed boreal plain forest of central Canada. Soil Biology and Biochemistry, 2005, 37(7): 1359- 1372.

[10] Lauber C L, Strickland M S, Bradford M A, Fierer N. The influence of soil properties on the structure of bacterial and fungal communities across land-use types. Soil Biology and Biochemistry, 2008, 40(9): 2407- 2415.

[11] Morris S J, Boerner R E J. Spatial distribution of fungal and bacterial biomass in southern Ohio hardwood forest soils: scale dependency and landscape patterns. Soil Biology and Biochemistry, 1999, 31(6): 887- 902.

[12] Brockett B F T, Prescott C E, Grayston S J. Soil moisture is the major factor influencing microbial community structure and enzyme activities across seven biogeoclimatic zones in western Canada. Soil Biology and Biochemistry, 2012, 44(1): 9- 20.

[13] B??th E, Anderson T H. Comparison of soil fungal/bacterial ratios in a pH gradient using physiological and PLFA-based techniques. Soil Biology and Biochemistry, 2003, 35(7): 955- 963.

[14] H?gberg M N, H?gberg P, Myrold D D. Is microbial community composition in boreal forest soils determined by pH, C-to-N ratio, the trees, or all three? Oecologia, 2007, 150(4): 590- 601.

[15] Grayston S J, Prescott C E. Microbial communities in forest floors under four tree species in coastal British Columbia. Soil Biology and Biochemistry, 2005, 37(6): 1157- 1167.

[16] Ushio M, Wagai R, Balser T C, Kitayama K. Variations in the soil microbial community composition of a tropical montane forest ecosystem: Does tree species matter? Soil Biology and Biochemistry, 2008, 40(10): 2699- 2702.

[17] Williamson W M, Wardle D A, Yeates G W. Changes in soil microbial and nematode communities during ecosystem decline across a long-term chronosequence. Soil Biology and Biochemistry, 2005, 37(7): 1289- 1301.

[18] Boyle S A, Yarwood R R, Bottomley P J, Myrold D D. Bacterial and fungal contributions to soil nitrogen cycling under Douglas fir and red alder at two sites in Oregon. Soil Biology and Biochemistry, 2008, 40(2): 443- 451.

[19] Bossio D A, Scow K M. Impacts of carbon and flooding on soil microbial communities: Phospholipid fatty acid profiles and substrate utilization patterns. Microbial Ecology, 1998, 35(3): 265- 278.

[20] Drenovsky R E, Vo D, Graham K J, Scow K M. Soil water content and organic carbon availability are major determinants of soil microbial community composition. Microbial Ecology, 2004, 48(3): 424- 430.

[21] Fierer N, Jackson R B. The diversity and biogeography of soil bacterial communities. Proceedings of the National Academy of Sciences of the United States of America, 2006, 103(3): 626- 631.

[22] Bardgett R D. The Biology of Soil: A Community and Ecosystem Approach. USA: Oxford University Press, 2005.

[23] Attiwill P M, Adams M A. Nutrient cycling in forests. New Phytologist, 1993, 124(4): 561- 582.

[24] Silver W L, Miya R K. Global patterns in root decomposition: comparisons of climate and litter quality effects. Oecologia, 2001, 129(3): 407- 419.

[25] Grayston S J, Vaughan D, Jones D. Rhizosphere carbon flow in trees, in comparison with annual plants: The importance of root exudation and its impact on microbial activity and nutrient availability. Applied Soil Ecology, 1997, 5(1): 29- 56.

[26] Tilman D, Reich P B, Knops J, Wedin D, Mielke T, Lehman C. Diversity and productivity in a long-term grassland experiment. Science, 2001, 294(5543): 843- 845.

[27] Langley J A, Hungate B A. Mycorrhizal controls on belowground litter quality. Ecology, 2003, 84(9): 2302- 2312.

[28] Breulmann M, Schulz E, Weisshuhn K, Buscot F. Impact of the plant community composition on labile soil organic carbon, soil microbial activity and community structure in semi-natural grassland ecosystems of different productivity. Plant and Soil, 2012, 352(1- 2): 253- 265.

[29] Pennanen T, Strommer R, Markkola A, Fritze H. Microbial and plant community structure across a primary succession gradient. Scandinavian Journal of Forest Research, 2001, 16(1): 37- 43.

[30] Fierer N, Strickland M S, Liptzin D, Bradford M A, Cleveland C C. Global patterns in belowground communities. Ecology Letters, 2009, 12(11): 1238- 1249.

[31] Quideau S A, Chadwick O A, Benesi A, Graham R C, Anderson M A. A direct link between forest vegetation type and soil organic matter composition. Geoderma, 2001, 104(1- 2): 41- 60.

[32] Bligh E G, Dyer W J. Orange-red flesh in god and haddock. Journal of the Fisheries Research Board of Canada, 1959, 16(4): 449- 452.

[33] Frosteg?rd A, Tunlid A, B??th E. Microbial biomass measured as total lipid phosphate in soils of different organic content. Journal of Microbiological Methods, 1991, 14(3): 151- 163.

[34] Tunlid A, White D C. Biochemical analysis of biomass, community structure, nutritional status, and metabolic activity of microbial communities in soil // Bollag J M, Stotzky G, eds. Soil Biochemistry. New York: Marcel Dekker, Inc, 1992, 7: 229- 262.

[35] Joergensen R G, Emmerling C. Methods for evaluating human impact on soil microorganisms based on their activity, biomass, and diversity in agricultural soils. Journal of Plant Nutrition and Soil Science, 2006, 169(3): 295- 309.

[36] Frosteg?rd ?, B??th E, Tunlid A. Shifts in the structure of soil microbial communities in limed forests as revealed by phospholipid fatty-acid analysis. Soil Biology and Biochemistry, 1993, 25(6): 723- 730.

[37] Zelles L. Fatty acid patterns of phospholipids and lipopolysaccharides in the characterisation of microbial communities in soil: a review. Biology and Fertility of Soils, 1999, 29(2): 111- 129.

[38] Zelles L. Phospholipid fatty acid profiles in selected members of soil microbial communities. Chemosphere, 1997, 35(1- 2): 275- 294.

[39] Zak D R, Ringelberg D B, Pregitzer K S, Randlett D L, White D C, Curtis P S. Soil microbial communities beneath Populus grandidentata crown under elevated atmospheric CO2. Ecological Applications, 1996, 6(1): 257- 262.

[40] Joergensen R G, Potthoff M. Microbial reaction in activity, biomass, and community structure after long-term continuous mixing of a grassland soil. Soil Biology and Biochemistry, 2005, 37(7): 1249- 1258.

[41] Harwood J L, Russell N J. Lipids in Plants and Microbes. London: George Allen and Unwin, 1984.

[42] Frosteg?rd A, B??th E. The use of phospholipid fatty acid analysis to estimate bacterial and fungal biomass in soil. Biology and Fertility of Soils, 1996, 22(1- 2): 59- 65.

[43] Liu B, Hu G P, Zheng X F, Zhang J F, Xie H A. Analysis on microbial diversity in the rhizosphere of rice by phospholipid fatty acid biomarkers. Chinese Journal of Rice Science, 2010, 24(3): 278- 288.

[44] Lu R K. Soil Agricultural Chemistry Analysis. Beijing: China Agricultural Science and Technology Press, 2000.

[45] Steinweg J M, Plante A F, Conant R T, Paul E A, Tanaka D L. Patterns of substrate utilization during long-term incubations at different temperatures. Soil Biology and Biochemistry, 2008, 40(11): 2722- 2728.

[46] Djukic I, Zehetner F, Watzinger A, Horacek M, Gerzabek M H.Insitucarbon turnover dynamics and the role of soil microorganisms therein: a climate warming study in an Alpine ecosystem. Fems Microbiology Ecology, 2013, 83(1): 112- 124.

[47] Zhang S X C F L, Zheng H. Response of soil microbial community structure to the leaf litter decomposition of three typical broadleaf species in mid-subtropical area, southern China. Acta Ecologica Sinica, 2011, 31(11): 3020- 3026.

[48] Harrison K A, Bardgett R D. Influence of plant species and soil conditions on plant-soil feedback in mixed grassland communities. Journal of Ecology, 2010, 98(2): 384- 395.

[49] Joergensen R, Wichern F. Quantitative assessment of the fungal contribution to microbial tissue in soil. Soil Biology and Biochemistry, 2008, 40(12): 2977- 2991.

[50] Fierer N, Schimel J P, Holden P A. Variations in microbial community composition through two soil depth profiles. Soil Biology and Biochemistry, 2003, 35(1): 167- 176.

[51] Ekelund F, Ronn R, Christensen S. Distribution with depth of protozoa, bacteria and fungi in soil profiles from three Danish forest sites. Soil Biology and Biochemistry, 2001, 33(4- 5): 475- 481.

[52] Saetre P, Baath E. Spatial variation and patterns of soil microbial community structure in a mixed spruce-birch stand. Soil Biology and Biochemistry, 2000, 32(7): 909- 917.

[53] Tscherko D, Hammesfahr U, Zeltner G, Kandeler E, Bocker R. Plant succession and rhizosphere microbial communities in a recently deglaciated alpine terrain. Basic and Applied Ecology, 2005, 6(4): 367- 383.

[54] Paterson E. Importance of rhizodeposition in the coupling of plant and microbial productivity. European Journal of Soil Science, 2003, 54(4): 741- 750.

[55] Keith A M, Brooker R W, Osler G H R, Chapman S J, Burslem D F R P, van der Wal R. Strong impacts of belowground tree inputs on soil nematode trophic composition. Soil Biology and Biochemistry, 2009, 41(6): 1060- 1065.

[56] Stephan A, Meyer A H, Schmid B. Plant diversity affects culturable soil bacteria in experimental grassland communities. Journal of Ecology, 2000, 88(6): 988- 998.

[57] Anderson T H, Domsch K H. The metabolic quotient for CO2(qCO2) as a specific activity parameter to assess the effects of environmental conditions, such as pH, on the microbial biomass of forest soils. Soil Biology and Biochemistry, 1993, 25(3): 393- 395.

[58] B??th E, Frosteg?rd A, Pennanen T, Fritze H. Microbial Community structure and Ph response in relation to soil organic-matter quality in wood-ash fertilized, clear-cut or burned coniferous forest soils. Soil Biology and Biochemistry, 1995, 27(2): 229- 240.

[59] Wang X. Studies on the Litter Decomposition Characteristie of Larix-Princicpis-Rupprechtii Mayr. Plantation in Yanshan Mountainous Regions [D]. Baoding: Hebei Agricultural University, 2012.

[60] Kanerva S, Kitunen V, Loponen J, Smolander A. Phenolic compounds and terpenes in soil organic horizon layers under silver birch, Norway spruce and Scots pine. Biology and Fertility of Soils, 2008, 44(4): 547- 556.

[61] Kubartova A, Ranger J, Berthelin J, Beguiristain T. Diversity and decomposing ability of saprophytic fungi from temperate forest litter. Microbial Ecology, 2009, 58(1): 98- 107.

[62] Rinnan R, Stark S, Tolvanen A. Responses of vegetation and soil microbial communities to warming and simulated herbivory in a subarctic heath. Journal of Ecology, 2009, 97(4): 788- 800.

[63] Holtkamp R, Kardol P, van der Wal A, Dekker S C, van der Putten W H, de Ruiter P C. Soil food web structure during ecosystem development after land abandonment. Applied Soil Ecology, 2008, 39(1): 23- 34.

[64] Trumbore S. Age of soil organic matter and soil respiration: Radiocarbon constraints on belowground C dynamics. Ecological Applications, 2000, 10(2): 399- 411.

[65] Vauramo S, Setala H. Urban belowground food-web responses to plant community manipulation-Impacts on nutrient dynamics. Landscape and Urban Planning, 2010, 97(1): 1- 10.

[66] Mitchell R J, Hester A J, Campbell C D, Chapman S J, Cameron C M, Hewison R L, Potts J M. Explaining the variation in the soil microbial community: do vegetation composition and soil chemistry explain the same or different parts of the microbial variation? Plant and Soil, 2012, 351(1- 2): 355- 362.

[67] Rousk J, B??th E, Brookes P C, Lauber C L, Lozupone C, Caporaso J G, Knight R, Fierer N. Soil bacterial and fungal communities across a pH gradient in an arable soil. The Isme Journal, 2010, 4(10): 1340- 1351.

[68] Yang X L, Yan W, Bao Y Y, Fan Y J, Jiang H Y. Diversity of arbuscular mycorrhizal fungi in Dahurian larch forests in Da Hinggan Ling Mountains. Chinese Journal of Ecology, 2010, 29(3): 504- 510.

[69] Yarwood S A, Myrold D D, Hogberg M N. Termination of belowground C allocation by trees alters soil fungal and bacterial communities in a boreal forest. Fems Microbiology Ecology, 2009, 70(1): 151- 162.

[70] Heinemeyer A, Ridgway K P, Edwards E J, Benham D G, Young J P W, Fitter A H. Impact of soil warming and shading on colonization and community structure of arbuscular mycorrhizal fungi in roots of a native grassland community. Global Change Biology, 2004, 10(1): 52- 64.

[71] Kelly J J, Favila E, Hundal L S, Marlin J C. Assessment of soil microbial communities in surface applied mixtures of Illinois River sediments and biosolids. Applied Soil Ecology, 2007, 36(2- 3): 176- 183.

[72] Rosenvald K, Kuznetsova T, Ostonen I, Truu M, Truu J, Uri V, Lohmus K. Rhizosphere effect and fine-root morphological adaptations in a chronosequence of silver birch stands on reclaimed oil shale post-mining areas. Ecological Engineering, 2011, 37(7): 1027- 1034.

[73] Cui L J, Liang Z S, Han R L, Yang J W. Biomass, soil and root system distribution characteristics of seabuckthorn × poplar mixed forest. Scientia Silvae Sinicae, 2003, 39(6): 1- 7.

[74] Treonis A M, Ostle N J, Stott A W, Primrose R, Grayston S J, Ineson P. Identification of groups of metabolically-active rhizosphere microorganisms by stable isotope probing of PLFAs. Soil Biology and Biochemistry, 2004, 36(3): 533- 537.

[75] Peng S L, Hao Y R. The dynamics of forest root and its distribution during succession. Acta Scientiarum Naturalium Universitatis Sunyatseni, 2005, 44(5): 65- 69.

[76] Lundquist E J, Scow K M, Jackson L E, Uesugi S L, Johnson C R. Rapid response of soil microbial communities from conventional, low input, and organic farming systems to a wet/dry cycle. Soil Biology and Biochemistry, 1999, 31(12): 1661- 1675.

[77] Fontaine S, Mariotti A, Abbadie L. The priming effect of organic matter: a question of microbial competition? Soil Biology and Biochemistry, 2003, 35(6): 837- 843.

[78] Han Q C, Ren H G, Liu J J. Contents and ratios of the decomposable and resistant plant material in the litters of main trees in Qingling Mountains. Journal of Northwest Forestry University, 2012, 27(5): 6- 10.

參考文獻:

[43] 劉波, 胡桂萍, 鄭雪芳, 張建福, 謝華安. 利用磷脂脂肪酸(PLFAs)生物標(biāo)記法分析水稻根際土壤微生物多樣性. 中國水稻科學(xué), 2010, 24(3): 278- 288.

[44] 魯如坤. 土壤農(nóng)化分析. 北京: 中國農(nóng)業(yè)科技出版社, 2000.

[47] 張圣喜, 陳法霖, 鄭華. 土壤微生物群落結(jié)構(gòu)對中亞熱帶三種典型闊葉樹種凋落物分解過程的響應(yīng). 生態(tài)學(xué)報, 2011, 31(11): 3020- 3026.

[59] 王欣. 燕山山地華北落葉松人工林葉凋落物分解特性研究 [D]. 保定: 河北農(nóng)業(yè)大學(xué), 2012.

[68] 楊秀麗, 閆偉, 包玉英, 樊永軍, 姜海燕. 大興安嶺落葉松林叢枝菌根真菌多樣性. 生態(tài)學(xué)雜志, 2010, 29(3): 504- 510.

[73] 崔浪軍, 梁宗鎖, 韓蕊蓮, 楊建偉. 沙棘、楊樹混交林生物量、林地土壤特性及其根系分布特征研究. 林業(yè)科學(xué), 2003, 39(6): 1- 7.

[75] 彭少麟, 郝艷茹. 森林演替過程中根系分布的動態(tài)變化. 中山大學(xué)學(xué)報: 自然科學(xué)版, 2005, 44(5): 65- 69.

[78] 韓其晟, 任宏剛, 劉建軍. 秦嶺主要森林凋落物中易分解和難分解植物殘體含量及比值研究. 西北林學(xué)院學(xué)報, 2012, 27(5): 6- 10.

Response of soil microbial community composition to vegetation types

WANG Miao1,2, QU Laiye1,*, MA Keming1, LI Guilin3, YANG Xiaodan4

1StateKeyLaboratoryofUrbanandRegionalEcology,ResearchCenterforEco-environmentalScience,ChineseAcademyofSciences,Beijing100085,China2UniversityofChineseAcademyofSciences,Beijing100049,China3SaihanWuLaNationalNatureReserveAdministration,Chifeng025150,China4BarinYouqiEnvironmentalProtectionAgency,Chifeng025150,China

There is no unifying conclusion among the considerable studies of soil microbial community composition under different vegetation types. We selected a distinct vertical vegetation distribution belt consisting of broad-leaved forests, coniferous forests, and subalpine meadows to study the effect of vegetation types on soil microbial community composition. Soil samples were collected at three different depths (0—5cm, 5—10cm, 10—20cm) from sites of five vegetation types. These sites were distinguished by their dominating vegetation: poplar (Populusdavidiana) (1250—1300m), poplar (P.davidiana) mixed with birth (Betulaplatyphylla) (1370—1550m), birth (B.platyphylla) (1550—1720m), larch (Larixprincipis-rupprechtii) (1840—1890m) and subalpine meadow (1890—1951m). Soil microbial community compositions under the various vegetation types were determined by phospholipid fatty acid (PLFA) analysis. Ordination of individual PLFA signatures and correlations among soil properties and soil microbial PLFA indicators were analyzed by principal components analysis (PCA) and redundancy analysis (RDA), respectively. The results indicated that total PLFA contents of soil microbial community, biomasses of four main microbial taxa (fungi (f), bacteria (b), gram-positive bacteria (G+), gram-negative bacteria (G-)), and microbial community structure were significantly affected (P<0.05) by soil organic carbon (SOC) under all vegetations; PLFA contents of total microbial community and main taxa generally decreased as soil depth increased, while G+/G-and f/b increased with soil depth. Among different vegetations, total PLFA contents and main taxa biomass under mixed broad-leaved forests were the highest; f/b and G+/G-under coniferous forests were higher than those under broad-leaved forests; the availability of SOC under subalpine meadows was constrained on some level by the low pH value, which led to a relatively high f/b and G+/G-. In conclusion, the effect of SOC on soil microbial community composition was the most significant of all soil parameters under all vegetation types, though the availability of SOC could be constrained by relatively low pH values on some level; fungi was more sensitive to the changes of vegetation types while bacteria was more sensitive to the variability of nutrient availability and pH. This conclusion could have a significant impact on forecasting soil microbial community composition under different vegetations.

PLFAs, soil microbial community, vegetation, soil organic carbon

國家自然科學(xué)基金(31170581, 30700639)

2013- 02- 20; 網(wǎng)絡(luò)出版日期:2014- 03- 17

10.5846/stxb201302200278

*通訊作者Corresponding author.E-mail: lyqu@rcees.ac.cn

王淼，曲來葉，馬克明，李桂林，楊小丹.罕山土壤微生物群落組成對植被類型的響應(yīng).生態(tài)學(xué)報,2014,34(22):6640- 6654.

Wang M, Qu L Y, Ma K M, Li G L, Yang X D.Response of soil microbial community composition to vegetation types.Acta Ecologica Sinica,2014,34(22):6640- 6654.