林业科学  2016, Vol. 52 Issue (2): 106-113   PDF    
DOI: 10.11707/j.1001-7488.20160213
0

文章信息

万菁娟, 郭剑芬, 纪淑蓉, 任卫岭, 杨玉盛
Wan Jingjuan, Guo Jianfen, Ji Shurong, Ren Weiling, Yang Yusheng
可溶性有机物输入对亚热带森林土壤CO2排放及微生物群落的影响
Effects of Dissolved Organic Matter Input on Soil CO2 Emission and Microbial Community Composition in a Subtropical Forest
林业科学, 2016, 52(2): 106-113
Scientia Silvae Sinicae, 2016, 52(2): 106-113.
DOI: 10.11707/j.1001-7488.20160213

文章历史

收稿日期：2015-01-31
修回日期：2015-12-29

作者相关文章

万菁娟
郭剑芬
纪淑蓉
任卫岭
杨玉盛

引用本文
万菁娟, 郭剑芬, 纪淑蓉, 任卫岭, 杨玉盛. 2016. 可溶性有机物输入对亚热带森林土壤CO2排放及微生物群落的影响[J]. 林业科学, 52(2): 106-113.
Wan Jingjuan, Guo Jianfen, Ji Shurong, Ren Weiling, Yang Yusheng. 2016. Effects of Dissolved Organic Matter Input on Soil CO2 Emission and Microbial Community Composition in a Subtropical Forest. Scientia Silvae Sinicae, 52(2): 106-113.  DOI: 10.11707/j.1001-7488.20160213
可溶性有机物输入对亚热带森林土壤CO2排放及微生物群落的影响
万菁娟, 郭剑芬, 纪淑蓉, 任卫岭, 杨玉盛    
湿润亚热带山地生态国家重点实验室培育基地 福建师范大学地理科学学院 福州 350007
收稿日期：2015-01-31；修回日期：2015-12-29
基金项目：国家自然科学基金项目(31370615,31130013,31470501);福建省自然科学基金项目(2015J01121)。
通讯作者：郭剑芬
摘要：[目的] 研究可溶性有机物(DOM)输入对森林土壤CO2排放及微生物群落的影响,为探讨DOM在森林生态系统碳循环中的作用提供依据。[方法] 设置添加米槠凋落叶DOM、杉木凋落叶DOM、米槠枯死根DOM、杉木枯死根DOM及添加去离子水(对照)处理,通过36 h短期室内培养,研究添加米槠及杉木凋落叶和枯死根DOM后土壤CO2排放速率最大值出现的时间及对土壤微生物群落的影响。[结果] 无论米槠还是杉木,其凋落叶DOC含量均显著高于枯死根DOC含量,而凋落叶DOM的腐殖化指数(HIX)则显著低于枯死根DOM的HIX,添加米槠枯死根DOM和杉木枯死根DOM的土壤CO2排放速率在第2 h达到最大值,分别是对照的7.3和8.3倍,在24 h时则降低至最大值的78.9%和66.3%;而添加米槠凋落叶DOM和杉木凋落叶DOM的土壤CO2排放速率在12 h时达到最大值,分别是对照的20.6和13.2倍,在24 h时则分别降低至最大值的84.0%和53.1%;磷脂脂肪酸(PLFA)分析结果显示,土壤添加米槠凋落叶DOM后革兰氏阳性细菌、革兰氏阴性细菌、放线菌和真菌的PLFAs含量显著低于土壤添加杉木凋落叶DOM的27%,38%,46%和41% (P<0.05);土壤添加米槠枯死根DOM后革兰氏阳性细菌、革兰氏阴性细菌和真菌PLFAs含量显著低于添加杉木枯死根DOM的21%,21%和22% (P<0.05);培养36 h时,添加米槠凋落叶DOM的土壤和对照土壤中G+:G-(革兰氏阳性细菌:革兰氏阴性细菌)高于培养前,但添加米槠凋落叶DOM的土壤中真菌:细菌低于培养前,这与其他处理的结果相反,表明添加不同来源DOM对土壤微生物群落的影响不一致。[结论] 外源添加DOM后土壤CO2排放速率最大值的出现时间由外源添加DOM的组成和化学性质决定,而且外源添加DOM显著影响土壤微生物的群落组成。
关键词： 米槠    杉木    CO2排放    可溶性有机物    微生物群落    
Effects of Dissolved Organic Matter Input on Soil CO2 Emission and Microbial Community Composition in a Subtropical Forest
Wan Jingjuan, Guo Jianfen , Ji Shurong, Ren Weiling, Yang Yusheng    
State Key Laboratory Breeding Base of Humid Subtropical Mountain Ecology College of Geographical Sciences, Fujian Normal University Fuzhou 350007
Abstract: [Objective] DOM (dissolved organic matter) is an important labile carbon source in soil, and can be an important factor regulating CO2 emission of forest soil. This study will improve understanding of the role of DOM on forest C cycle.[Method] We added DOM from leaf litter and dead roots of Cunninghamia lanceolata and Castanopsis carlesii to soil to examine the effects of carbon inputs on soil CO2 efflux and microbial community composition by phospholipid fatty acid (PLFA) analysis through laboratory incubations for 36 hours. The treatments were as follows:soil with DOM from C. carlesii leaf litter, soil with DOM from C. lanceolata leaf litter, soil with DOM from C. carlesii dead root, soil with DOM from C. lanceolata dead root, and a control (soil with deionized water). Mineral soil (0-10 cm) was from an 11-year-old C. lanceolata plantation in Sanming of Fujian Province, China. Carbon mineralization was determined using CO2 respiration method.[Result] The contents of dissolved organic carbon (DOC) from leaf litter were much higher than those from dead roots, and the humification index (HIX) values of the DOM were opposite. The maximum rates of C mineralization occurred in 2 hours following addition of DOM from dead roots of C. lanceolata and C. carlesii, and were 7.3 and 8.3 times higher than that of control respectively, then decreased to 78.9% and 66.3% of the maximum values by 24 hours. In contrast, the maximum rates of C mineralization were in 12 hours following addition of DOM from leaf litter of C. lanceolata and C. carlesii, and the magnitudes were 20.6 and 13.2 times that of control respectively, then decreased to 84.0% and 53.1% of the maximum by 24 hours. PLFA analysis showed that the contents of gram-positive bacteria, gram-negative bacteria, actinomycetes and fungi in soils added with DOM from C. carlesii leaf litter were 27%, 38%, 46% and 41% lower than those of soils added with DOM from C. lanceolata leaf litter, respectively (P<0.05). Compared to soils added with DOM from dead roots of C. lanceolata, the contents of gram-positive bacteria, gram-negative bacteria and fungi were 21%, 21% and 22% lower in soils added with DOM from dead roots of C. carlesii, respectively (P<0.05). After 36 h incubation, the ratios of gram-positive bacteria to gram-negative bacteria in soils added with DOM from C. carlesii leaf litter and the control were higher than those in untreated soil, while compared to untreated soil, the ratio of fungi to bacteria was lower following additions of DOM from leaf litter of C. carlesii.[Conclusion] There was significant difference in the microbial community composition following additions of DOM from various sources, and the maximum rates of C mineralization following addition of DOM depended on the quantity and quality of DOM.
Key words: Castanopsis carlesii    Cunninghamia lanceolata    CO2 emission    dissolved organic matter    microbial community composition    

可溶性有机物(dissolved organic matter，DOM)是最活跃、最易变的土壤有机质(soil organic matter，SOM)形态，同时也是目前最有争议的土壤碳库之一(Von Lützow et al., 2007)。研究指出，尽管DOM的量很少，但其具有周转速率快、移动能力强等特点，是土壤易变碳库和稳定SOM间的重要中介(Neff et al., 2001; Boddy et al., 2007)，在陆地C循环中发挥了重要作用。不同外源DOM的浓度与化学性质均会影响土壤CO2的排放，如Clevel and 等(2010)和Leff等(2012)研究表明，土壤CO2通量随着添加的DOM浓度增加而增加；Wieder等(2008)指出，添加等浓度的不同树种凋落叶DOM到土壤中，土壤CO2累积排放量的差异性很大。但目前关于添加不同外源DOM对土壤微生物群落的影响研究鲜见报道。

已有研究表明，添加外源有机物改变土壤微生物群落结构(Denef et al., 2009; Dungait et al., 2011)，主要是通过影响土壤可利用性碳源和营养物质而引起的(Crow et al., 2009; Nemergut et al., 2010; Chen et al., 2012)。Clevel and 等(2007)研究发现，热带雨林土壤中添加凋落物淋溶的DOM后短期内会产生较大的CO2通量，主要是由土壤微生物群落变化引起的(Neff et al., 2001; Clevel and et al., 2004)。土壤中的细菌群落会优先利用外源有机物中易分解的部分(Paterson et al., 2007; Moore-Kucera et al., 2008)，尤其是r型细菌会引起假激发效应(Blagodatskaya et al., 2008; Nottingham et al., 2009)，而真菌被认为与土壤有机碳矿化速率变化有关(Kuzyakov，2010)。Garcia-Pausas等(2011)添加葡萄糖到土壤中后，增加了土壤真菌和放线菌生物量而增加了土壤有机碳矿化。

前期研究发现，添加外源DOM到土壤中后，培养当天CO2排放速率就达到最大值，但是否添加不同DOM后土壤CO2排放速率均在同一时间达到最大值？CO2排放达到最大值时，土壤微生物群落与CO2排放速率是否具有相关性？这些问题仍不清楚(万菁娟等，2015)。本研究通过室内培养试验探讨添加米槠(Castanopsis carlesii)及杉木(Cunninghamia lanceolata)凋落叶和枯死根DOM对土壤CO2排放(速率和通量)及土壤微生物群落结构的影响，为探讨DOM在森林生态系统碳循环中的作用提供依据。

1 研究区概况

研究区位于福建省三明市格氏栲自然保护区(117°28′E，26°11′N)，该区东南面和西北面分别与戴云山脉和武夷山脉相连，以低山丘陵为主，平均海拔300 m，平均坡度25°~35°。属中亚热带海洋季风气候，具有冬冷夏热、水热同季、湿润多雨的特点，试验地附近的三明市年均气温20.1 ℃，年降水量1 670 mm，且多集中于3—8月。杉木人工林为在2003年米槠次生林皆伐迹地上营造的纯林，林龄11年。林分表层(0~10 cm)土壤有机碳、全氮和微生物量碳含量分别为17.55 g·kg-1、1.31 g·kg-1和423.5 mg·kg-1；土壤饱和含水量为46.35%，pH为4.56。

2 研究方法 2.1 土壤样品和外源DOM样品取样

2014年3月，于杉木人工林的上、中、下坡布设3块20 m × 20 m标准样地，在每块标准样地内用土钻按“S”形取5个点的0～10 cm土层土壤，迅速冷藏并带回实验室用于培养试验。同时选取长势、大小一致的杉木和米槠1年生幼苗进行盆栽种植，2013年5月开始13C标记，7月结束，在人为干旱情况下致死，收获整株树木，分别取叶片、枝干和根，带回实验室烘干保存。

2.2 试验设计与样品测定

2014年10月进行样品DOM的浸提。浸提时样品与水的比例为1∶10，即米槠凋落叶、杉木凋落叶、米槠枯死根和杉木枯死根各取30 g，各加入300 mL去离子水，浸泡24 h后，上清液用0.45 μm玻璃纤维过滤器减压过滤，得到DOM浸提液并于4 ℃下保存(表 1)。

表1 不同来源DOM的性质① Tab.1 Initial DOM characterization from different sources

取相当于50 g干土质量的鲜土到500 mL特质瓶中，调节土壤含水量为饱和持水量的40%，放置在25 ℃生化培养箱中先进行15天的预培养，使土壤内部环境趋于稳定。预培养结束后，分别加入米槠及杉木的凋落叶和死根DOM浸提液各4 mL和等量去离子水(4 mL)(对照)，调节土壤含水量达到饱和持水量的60%，每处理及对照均3次重复。加入DOM后的第2，5，8，12，24和36 h抽气取样，取样前1 h将瓶盖拧紧，然后将气体注入气相色谱仪(Shimadzu GC-2010，日本)测定土壤CO2排放速率，计算CO2累积排放量。

培养结束后，土壤微生物群落组成采用磷脂脂肪酸 PLFA法测定。即称取8 g干土(冷冻干燥土壤)，加入23 mL由磷酸缓冲液、甲醇、氯仿配置而成的提取液，振荡离心，将上层清液转移至分液漏斗中，反复2次，然后将分液漏斗在黑暗环境下静置一夜；收集下层有机相，在氮气下吹干，通过硅胶柱分离出磷脂，加甲醇∶ 甲苯(1∶1，V/V)和0.2 mol·L-1氢氧化钾溶液进行皂化和甲基化形成脂肪酸甲酯。上机测定前，用正十九烷酸甲酯作为内标溶液，将得到的脂肪酸甲酯转移到GC小瓶，通过气相色谱仪(Agilent 6890 N，美国)和MIDI微生物识别系统(MIDI Inc.，Newark，DE)进行鉴定。本研究中，将不同种类PLFA进行归类，i15:0，a15:0，i16:0，i17:0，a17:0表征革兰氏阳性细菌(Denef et al., 2009; Landesman et al., 2010)；cy17:0，18:1ω7c，18:1ω5c，cy19:0表征革兰氏阴性细菌(Swallow et al., 2009; Frostegård et al., 2010)；18:1ω9c和18:2ω6，9c表征真菌(Swallow et al., 2009)；10Me16:0、10Me17:0和10Me18:0表征放线菌；真菌∶细菌为真菌与细菌(包括革兰氏阳性细菌和革兰氏阴性细菌)的磷脂脂肪酸含量之比。

浸提液可溶性有机碳(dissolved organic carbon，DOC)含量采用总有机碳分析仪(SHIMADZU TOC-VCPH/CPN Analyzer)测定; 浸提液可溶性有机氮(dissolved organic nitrogen，DON)含量采用流动注射分析仪(Lachat Qyickchem Automatedion Analyzer)测定。使用紫外可见分光光度计(UV-2450，Shimadzu，Kyoto，Japan)测定浸提液DOM在波长254 nm处的紫外吸收值(UV)，在波长250和365 nm处的紫外吸光度比值表示DOM平均分子质量大小。荧光发射光谱用日立-4600 荧光分光光度计测定，激发波长λex为254 nm，狭缝宽10 nm，发射波长λem为300~480 nm，狭缝宽10 nm，扫描速度为2 400 nm·min-1；腐殖化指数(humi fication index，HIX)通过计算发射光谱中Σ435~480与Σ300~345 nm的峰面积比获得(熊丽等，2014)。

2.3 计算方法及数据处理

CO2排放速率计算公式为：

F=k×v/m×Δc/Δt×273/(273+T)。 (1)
式中：F为气体排放速率(mg·kg-1h-1)；k为常数1.964(kg·m-3)；Δc/Δt为在观测时间内气体浓度随时间变化的直线斜率(mg·h-1)；v为培养容器的体积(m-3)；m为土壤干质量(kg)；T为培养温度(℃)。加入DOM后第2，5，8，12，24和36 h 时CO2累积排放量采用相邻2次产生CO2速率的平均值乘以间隔的时间而得。

数据处理在Excel和SPSS 17.0软件中完成，图表采用Origin 8.0 软件制作。采用单因素方差分析(one-way ANOVA)检验添加不同来源DOM对土壤CO2排放的影响，多因素方差分析(multiple comparisons ANOVA)检验树种和凋落物种类对DOM组成和化学性质的影响(P< 0.05)，并采用Pearson相关法分析添加外源DOM培养36 h后土壤CO2累积排放量与土壤微生物群落磷脂脂肪酸含量之间的相关性。

3 结果与分析 3.1 不同来源DOM差异

多因素方差分析发现，树种和凋落物种类均对DOC浓度具有显著影响(P< 0.01)。如米槠凋落叶浸提得到的DOC浓度最大(3 299 mg·L-1)，而杉木枯死根浸提得到的DOC浓度最小(227 mg·L-1)，其差异超过了14倍(表 1)。米槠凋落叶DON浓度显著低于米槠枯死根DON浓度(P< 0.05)，说明米槠枯死根DOM中含有更多的氮营养物质。杉木凋落叶DOM的HIX，UV均显著低于米槠凋落叶DOM的HIX，UV(P< 0.05)，DOM分子质量大小则相反，即阔叶树种凋落叶DOM比针叶树种凋落叶DOM含有更多高分子质量、芳香类的腐殖酸难分解物质。这与相对荧光光谱图的趋势一致(图 1)，由针叶树种到阔叶树种最大荧光强度所对应波长向更长的波长转移，表明DOM中共轭体系在增大，分子结构更复杂。另外，凋落叶DOM的疏水性碳(hydrophobic dissolved organic carbon，HDOC)含量显著高于枯死根，而凋落叶DOM的HIX值显著低于枯死根(P< 0.05)，不同来源DOM分子质量大小表现为凋落叶高于枯死根，表明凋落叶DOM中含有更多低分子质量、易分解的有机质，而枯死根DOM则以高分子质量的腐殖质为主。

图1 不同来源DOM的荧光发射光谱 Fig.1 Fluorescence emission spectra of DOM from different sources
3.2 添加不同来源DOM对土壤CO2排放的影响

添加米槠凋落叶DOM、杉木凋落叶DOM、米槠枯死根DOM和杉木枯死根DOM到土壤中后，土壤CO2排放速率均显著高于对照(P< 0.05)(图 2)，其中添加米槠和杉木枯死根DOM的土壤CO2排放速率在第2 h达到最大值，分别是对照的7.3和8.3倍；添加米槠和杉木凋落叶DOM的土壤CO2排放速率在第12 h达到最大值，分别是对照的20.6和13.2倍。添加凋落叶DOM的土壤CO2排放速率一直高于添加枯死根DOM的土壤CO2排放速率。

图2 添加不同来源DOM土壤的CO2排放速率 Fig.2 CO2 emission rate after DOM addition from different sources

在培养36 h时，添加不同树种和不同种类凋落物DOM均对土壤CO2累积排放量有显著影响(P< 0.05)(图 3)。添加米槠凋落叶DOM、杉木凋落叶DOM、米槠枯死根DOM和杉木枯死根DOM的土壤CO2累积排放量均明显大于对照。添加凋落叶DOM的土壤CO2累积排放量显著高于添加相同树种枯死根DOM的土壤CO2累积排放量，如添加米槠凋落叶DOM的土壤CO2累积排放量是添加米槠枯死根的4倍，添加杉木凋落叶DOM的土壤CO2累积排放量是添加杉木枯死根的3.7倍。添加米槠凋落叶DOM的土壤CO2累积排放量显著高于添加杉木凋落叶的53.9%，添加米槠枯死根DOM土壤CO2累积排放量显著高于添加杉木枯死根的43.5%。在培养36 h时，添加不同来源DOM的土壤CO2累积排放量的大小表现为： 添加米槠凋落叶DOM >添加杉木凋落叶DOM >添加米槠枯死根DOM >添加杉木枯死根DOM。

图3 添加不同来源DOM的土壤CO2累积排放量 Fig.3 Cumulative CO2 emission after DOM addition from different sources
3.3 添加不同来源DOM对土壤微生物群落的影响

添加米槠凋落叶DOM、杉木凋落叶DOM、米槠枯死根DOM和杉木枯死根DOM的土壤微生物磷脂脂肪酸(phospholipid fatty acid，PLFA)种类没有显著差异，但对照(添加去离子水)土壤的PLFA种类少了10Me 18:0。添加不同来源DOM到土壤中，含量较高的3种PLFA种类依次是16:0、cy19:0 w8c和i15:0。归类结果分析(表 2)表明，添加杉木凋落叶和枯死根DOM的土壤中G+、G-、放线菌和真菌的PLFAs含量显著大于对照(P< 0.05)。类似地，添加米槠凋落叶和枯死根DOM的土壤中G+、G-、放线菌和真菌的PLFAs含量亦大于对照，但差异不显著(P>0.05)。从添加不同树种凋落叶DOM来看，添加杉木凋落叶DOM的土壤中G+、G-、放线菌和真菌PLFAs含量及真菌∶细菌均显著大于添加米槠凋落叶DOM(P< 0.05)，但添加杉木凋落叶DOM的土壤G+∶G-显著低于添加米槠凋落叶DOM(P< 0.05)。比较添加杉木和米槠枯死根DOM的土壤微生物PLFAs含量可知，添加杉木枯死根DOM的土壤中G+、G-和真菌PLFAs含量显著高于添加米槠枯死根DOM(P< 0.05)，而放线菌PLFAs含量、G+∶G-、真菌∶细菌均没有显著差异。此外，添加杉木凋落叶DOM、米槠枯死根DOM和杉木枯死根DOM的土壤中G+∶G-低于培养前，而添加米槠凋落叶DOM和对照(添加去离子水)高于培养前；添加米槠凋落叶DOM的真菌∶细菌低于培养前，而其他3种处理均高于培养前，可见添加不同来源DOM对土壤微生物群落生物量的影响亦不一致。通过Pearson相关分析发现，培养36 h时添加不同来源DOM的土壤G+、G-、放线菌和真菌PLFAs含量与土壤CO2排放量之间没有显著的相关性(r=0.089，P=0.752)。

表2 添加不同来源DOM后土壤微生物磷脂脂肪酸(PLFAs)含量 Tab.2 Content of soil microbial phospholipid fatty acids(PLFAs)after addition of dissolved organic matter from different sources nmol·g-1
4 讨论 4.1 添加不同来源DOM的土壤CO2排放差异

本研究中，添加不同凋落物DOM的土壤CO2最大排放速率出现的时间不一致，这可能与外源添加DOM中DOC量的大小有关(表 1)，因为DOC是土壤微生物生长和代谢过程的重要能量来源(Leff et al., 2012)。外源添加米槠和杉木枯死根DOC量分别是1.5和0.9 mg，而外源添加米槠和杉木凋落叶DOC量分别是13.2和5.8 mg。在培养过程中，添加米槠和杉木凋落叶DOM的土壤CO2排放速率一直大于添加米槠和杉木枯死根DOM的土壤CO2排放速率，因为外源添加的凋落叶DOM相比枯死根DOM中含有更多可利用有机碳且分子结构更简单，因而更容易被微生物所利用(万菁娟等，2015)。此外，培养期间对照土壤CO2排放速率一直高于培养前，这可能是由于土壤水分从饱和含水量的40%调整到60%，促进了土壤有机碳的矿化(Housman et al.， 2006;Potts et al.， 2006)。

4.2 添加不同来源DOM的土壤微生物群落差异

许多研究表明，树种会影响土壤微生物群落组成，在不同树种下会形成独特的微生物群落(Lejon et al., 2005)。本研究供试土壤来自于杉木人工林，由于针叶凋落物中总酚、木质素、脂溶性物质多等因素(程东升，1993)，使得土壤中K策略者真菌含量较大，而r策略者细菌含量较少(Fontaine et al., 2003)。添加不同来源DOM的土壤微生物群落

PLFAs含量均高于对照，其原因是添加可溶性有机C源后，土壤中r策略者的能量限制得到缓解，能迅速增殖而促进胞外酶增加，因而也有利于增加K策略者(Kuzyakov et al., 2000; Paterson，2009)。外源碳添加会改变土壤微生物群落组成(Feng et al., 2009; Dungait et al., 2011; Wang et al., 2013)。Garcia-Pausas等(2011)研究发现，添加葡萄糖到土壤中后增加了土壤真菌与放线菌PLFAs含量。Wang等(2013)直接添加凋落物到土壤中后，增加了土壤微生物活性，降低了细菌∶真菌的值。本研究发现，添加杉木凋落叶DOM、米槠枯死根DOM和杉木枯死根DOM的土壤真菌∶细菌高于培养前，但添加米槠凋落叶DOM的土壤真菌∶细菌低于培养前，表明添加米槠凋落叶DOM的土壤细菌生物量增加得更多。添加杉木凋落叶DOM、米槠枯死根DOM和杉木枯死根DOM后土壤的G+∶G-均低于培养前，表明3种来源DOM添加促进了革兰氏阴性细菌群落的繁殖(Kuzyakov et al., 2000; Garcia-Pausas et al., 2011)，而添加米槠凋落叶DOM后土壤G+∶G-高于培养前，这可能是因为不同微生物群落对碳源的利用具有选择性，其中革兰氏阴性细菌会优先利用外源添加有机物，而革兰氏阳性细菌会优先利用原有土壤有机物(Kramer et al., 2006; Tavi et al., 2013)。

4.3 土壤CO2排放与微生物群落相关性分析

在培养36 h时，添加不同来源DOM的土壤中G+、G-、放线菌和真菌PLFAs含量与土壤CO2累积排放量的相关性很低，这可能与供试土壤有关，因为外源添加杉木凋落叶和枯死根DOM在杉木人工林土壤中会有一定的主场优势(Ayres et al., 2009)，也可能由于土壤CO2排放是一个渐进的过程，培养过程中存在微生物的更替，不同生存策略的微生物对CO2排放的贡献不一致(Gärdenäs et al., 2011)。另外，本研究培养时间短暂，需较长时间培养以进行验证。

5 结论

36 h的短期培养试验发现，添加米槠和杉木枯死根DOM的土壤CO2排放速率在第2 h达到最大值，而添加米槠和杉木凋落叶DOM的土壤CO2排放速率最大值出现在第12 h，土壤CO2排放速率最大值出现时间不同可能与外源添加DOM的性质差异有关。培养36 h时，添加不同来源DOM的土壤G+、G-、放线菌和真菌PLFAs含量均高于培养前，添加杉木凋落叶和枯死根DOM的土壤G+、G-和真菌PLFAs含量均显著高于添加米槠凋落叶和枯死根DOM，可见外源添加DOM影响了土壤微生物群落，但DOM对土壤微生物的影响机制还有待进一步研究。

参考文献(References)
[1] 程东升. 1993.森林微生物生态学. 哈尔滨:东北林业大学出版社, 81-84.
(Cheng D S.1993.Forest microbial Ecology. Harbin:Northeast Forestry University Press, 81-84.[in Chinese])
[2] 万菁娟,郭剑芬,纪淑蓉,等. 2015.杉木和米槠凋落叶DOM对土壤碳矿化的影响. 生态学报, 35(24):8148-8154.
(Wan J J, Guo J F, Ji S R, et al. 2015.Effects of dissolved organic matter from Cunninghamia lanceolata and Castanopsis carlesii leaf litter on soil C mineralization. Acta Ecologica Sinica, 35(24):8148-8154.[in Chinese])(2)
[3] 熊丽, 杨玉盛, 王巧珍. 等. 2014.可溶性有机碳在米槠天然林土壤中的淋溶特征. 亚热带资源与环境学报, 9(1):46-52.
(Xiong L, Yang Y S, Wang Q Z, et al. 2014.Movement of dissolved organic carbon in natural forest soil of Castanopsis carlesii. Journal of Subtropical Resources and Environment, 9(1):46-52.[in Chinese])(1)
[4] Ayres E, Steltzer H, Simmons B L, et al. 2009.Soil biota accelerate decomposition in high-elevation forests by specializing in the breakdown of litter produced by the plant species above them. Journal of Ecology, 97(5):901-912.(1)
[5] Blagodatskaya E, Kuzyakov Y. 2008.Mechanisms of real and apparent priming effects and their dependence on soil microbial biomass and community structure:critical review. Biology and Fertility of Soils, 45(2):115-131.(1)
[6] Boddy E, Hill P W. 2007.Fast turnover of low molecular weight components of the dissolved organic carbon pool of temperate grassland field soils. Soil Biology and Biochemistry, 39(4):827-835.(1)
[7] Chen Q H, Feng Y, Zhang Y P, et al. 2012.Short-term responses of nitrogen mineralization and microbial community to moisture regimes in greehouse vegetable soils. Pedosphere, 22 (2):263-272.(1)
[8] Cleveland C C, Neff J C, Townsend A R, et al. 2004.Composition, dynamics, and fate of leached dissolved organic matter in terrestrial ecosystems:results from a decomposition experiment. Ecosystems, 7(3):175-285.(1)
[9] Cleveland C C, Nemergut D R, Schmidt S K, et al. 2007.Increases in soil respiration following labile carbon additions linked to rapid shifts in soil microbial community composition. Biogeochemistry, 82(3):229-240.(1)
[10] Cleveland C C, Wieder W R, Reed S C, et al. 2010.Experimental drought in a tropical rain forest increases soil carbon dioxide losses to the atmosphere. Ecology, 91(8):2313-2323.(1)
[11] Crow S E, Lajtha K, Filley T R, et al. 2009.Sources of plant-derived carbon and stability of organic matter in soil:implications for global change. Global Change Biology, 15(8):2003-2019.(1)
[12] Denef K, Roobroeck D, Manimel Wadu M C, et al. 2009.Microbial community composition and rhizodeposit-carbon assimilation in differently managed temperate grassland soils. Soil Biology and Biochemistry, 41(1):144-153.(2)
[13] Dungait J A J, Kemmitt S J, Michallon L, et al. 2011.Variable responses of the soil microbial biomass to trace concentrations of 13C-labelled glucose, using 13C-PLFA analysis. European Journal of Soil Science, 62(1):117-126.(2)
[14] Feng W T, Zou X M, Schaefer D. 2009.Above- and belowground carbon inputs affect seasonal variations of soil microbial biomass in a subtropical monsoon forest of southwest China. Soil Biology and Biochemistry, 41(5):978-983.(1)
[15] Fontaine S, Mariotti A, Abbadie L. 2003.The priming effect of organic matter:a question of microbial competition? Soil Biology and Biochemistry, 35(6):837-843.(1)
[16] Frostegård Å, Tunlid A, Bååth E. 2011.Use and misuse of PLFA measurements in soils. Soil Biology and Biochemistry, 43(8):1621-1625.(1)
[17] Garcia-Pausas J, Paterson E. 2011.Microbial community abundance and structure are determinants of soil organic matter mineralisation in the presence of labile carbon. Soil Biology and Biochemistry, 43(8):1705-1713.(3)
[18] Gärdenäs A I, Ågren G I, Bird J A, et al. 2011.Knowledge gaps in soil carbon and nitrogen interactions -from molecular to global scale. Soil Biology and Biochemistry, 43 (4):702-717.(1)
[19] Housman D C, Powers H H, Collins A D, et al. 2006.Carbon and nitrogen fixation differ between successional stages of biological soil crusts in the Colorado Plateau and Chihuahuan Desert. Journal of Arid Environments, 66(4):620-634.(1)
[20] Kramer C, Gleixner G. 2006.Variable use of plant- and soil-derived carbon by microorganisms in agricultural soils. Soil Biology and Biochemistry, 38(11):3267-3278.(1)
[21] Kuzyakov Y. 2010. Priming effects:interactions between living and dead organic matter. Soil Biology and Biochemistry, 42(9):1363-1371.(1)
[22] Kuzyakov Y, Friedel J K, Stahr K. 2000.Review of mechanisms and quantification of priming effects. Soil Biology and Biochemistry, 32(11):1485-1498.(2)
[23] Landesman W J, Dighton J. 2010.Response of soil microbial communities and the production of plant-available nitrogen to a two-year rainfall manipulation in the New Jersey Pinelands. Soil Biology and Biochemistry, 42(10):1751-1758.(1)
[24] Leff J W, Nemergut D R, Grandy A S, et al. 2012.The effects of soil bacterial community structure on decomposition in a tropical rain forest. Ecosystems, 15(2):284-298.(2)
[25] Lejon D P, Chaussod R, Ranger J, et al. 2005.Microbial community structure and density under different tree species in an acid forest soil (Morvan, France). Microbial Ecology, 50(4):614-625.(1)
[26] Moore-Kucera J, Dick R P. 2008.Application of 13C-labeled litter and root materials for in situ decomposition studies using phospholipid fatty acids. Soil Biology and Biochemistry, 40(10):2485-2493.(1)
[27] Neff J C, Asner G P. 2001.Dissolved organic carbon in terrestrial ecosystems:synthesis and a model. Ecosystems, 4(1):29-48.(2)
[28] Nemergut D R, Cleveland C C, Wieder W R, et al. 2010.Plot-scale manipulations of organic matter inputs to soils correlate with shifts in microbial community composition in a lowland tropical rain forest. Soil Biology and Biochemistry, 42(12):2153-2160.(1)
[29] Nottingham A T, Griffiths H, Chamberlain P M, et al. 2009.Soil priming by sugar and leaf-litter substrates:a link to microbial groups. Applied Soil Ecology, 42(3):183-190.(1)
[30] Paterson E. 2009.Comments on the regulatory gate hypothesis and implications for C-cycling in soil. Soil Biology and Biochemistry, 41(6):1352-1354.(1)
[31] Paterson E, Gebbing T, Abel C, et al. 2007.Rhizodeposition shapes rhizosphere microbial community structure in organic soil. New Phytologist, 173(3):600-610.(1)
[32] Potts D L, Huxman T E, Cable J M, et al. 2006.Antecedent moisture and seasonal precipitation influence the response of canopy-scale carbon and water exchange to rainfall pulses in a semi-arid grassland. New Phytologist, 170(4):849-860.(1)
[33] Swallow M, Quideau S, MacKenzie M, et al. 2009.Microbial community structure and function:the effect of silvicultural burning and topographic variability in northern Alberta. Soil Biology and Biochemistry, 41(4):770-777.(1)
[34] Tavi N M, Martikainen P J, Lokko K, et al. 2013.Linking microbial community structure and allocation of plant-derived carbon in an organic agricultural soil using 13CO2 pulse-chase labelling combined with 13C-PLFA profiling. Soil Biology and Biochemistry, 58(3):207-215.(1)
[35] Von Lützow M, K gel-Knabner I, Ekschmitt K, et al. 2007.SOM fractionation methods:relevance to functional pools and to stabilization mechanisms. Soil Biology and Biochemistry, 39(9):2183-2207.(1)
[36] Wang Q, He T, Wang S, et al. 2013.Carbon input manipulation affects soil respiration and microbial community composition in a subtropical coniferous forest. Agricultural and Forest Meteorology, 178-179:152-160.(1)
[37] Wieder WR, Cleveland C, Townsend A R. 2008.Tropical tree species composition affects the oxidation of dissolved organic matter from litter. Biogeochemistry, 88(2):127-138.(1)