生态学报  2014, Vol. 34 Issue (2): 451-459

文章信息

刘纯, 刘延坤, 金光泽
LIU Chun, LIU Yankun, JIN Guangze
小兴安岭6种森林类型土壤微生物量的季节变化特征
Seasonal dynamics of soil microbial biomass in six forest types in Xiaoxing’an Mountains, China
生态学报, 2014, 34(2): 451-459
Acta Ecologica Sinica, 2014, 34(2): 451-459
http://dx.doi.org/10.5846/stxb201304050608

文章历史

收稿日期:2013-4-5
修订日期:2013-9-10
小兴安岭6种森林类型土壤微生物量的季节变化特征
刘纯1, 刘延坤1, 2, 金光泽1     
1. 东北林业大学生态研究中心, 哈尔滨 150040;
2. 黑龙江省森林工程与环境研究所, 哈尔滨 150081
摘要:土壤微生物是森林生态系统的重要调节者和分解者,其微生物量是陆地生态系统碳氮循环的重要组成部分。采用氯仿熏蒸浸提法测定了小兴安岭6种森林类型不同季节的土壤微生物量碳(MBC)和氮(MBN),并分析了其与土壤环境因子的关系,探讨根系去除对土壤微生物量的影响。结果表明:MBC和MBN的季节变化因森林类型的差异而有所不同,但最高值多发生在8月中旬;MBC和MBN在根系去除后均有不同程度的减少;MBC和MBN分别与土壤有机碳、全氮及含水量呈显著正相关(P <0.05);MBN与土壤温度呈极显著正相关(P <0.01)。显然,研究区的土壤微生物量受土壤温度、湿度及土壤有效养分综合作用的影响。
关键词小兴安岭    土壤微生物量碳氮    季节变化    根系去除    
Seasonal dynamics of soil microbial biomass in six forest types in Xiaoxing’an Mountains, China
LIU Chun1, LIU Yankun1, 2, JIN Guangze1     
1. Center for Ecological Research, Northeast Forestry University, Harbin 150040, China;
2. Forest Engineering and Environmental Research Institute of Heilongjiang Province, Harbin 150081, China
Abstract:Soil microbes are the most important regulator and decomposer in the forest ecosystem. Soil microbial biomass is an important component of the carbon and nitrogen cycles in the terrestrial ecosystem. The Heilongjiang Liangshui Nature Reserve has full gradient interference, which includes virgin forests, secondary forests, and plantation forests. The reserve provides a good platform to explore soil microbial biomass and to determine the factors influencing soil microbial biomass in the Xiaoxing'an Mountains. We used the chloroform fumigation extraction method to measure and compare the microbial biomass carbon (MBC), the microbial biomass nitrogen (MBN), and the influencing factors (i.e., soil organic carbon, soil total nitrogen, soil water content and soil temperature) throughout the growing season. We also explored the effect of root removal on soil microbial biomass. The experiment included six typical forest types, namely, virgin mixed broadleaved-Korean pine (Pinus koraiensis) forest, selectively cut mixed broadleaved-Korean pine forest, secondary birch (Betula platyphylla) forest, artificial larch (Larix gmelinii) plantation, artificial Korean pine forest, and valley spruce-fir (Picea-Abies) forest. Each forest type consists of three 20 m × 30 m plots, and four 2 m × 2 m root trenching subplots and four 2 m × 2 m control subplots were randomly chosen in each plot. Soil samples from 0 cm to 10 cm soil layers were randomly selected monthly from the six forest types from June 2010 to October 2010. The samples in each plot were mixed as one sample to determine MBC and MBN. Results show that the seasonal changes in the soil microbial biomass of the six forest types were different during the study period. The maximum soil microbial biomass was mostly obtained in mid-August. The MBC and MBN generally showed similar seasonal dynamics in the control and root removal plots. The average values of MBC and MBN for the six forest types varied from 383.5 mg/kg to 1633.6 mg/kg and 47.6 mg/kg to 231.0 mg/kg, respectively, accounting for 1% to 2% and 2% to 4% of the soil organic carbon and nitrogen content. The average soil microbial biomass (MBC and MBN, respectively) of each forest type was recorded as follows: secondary birch forest (1318.8 and 215.5 mg/kg) > artificial Korean pine forest (1137.3 and 169.1 mg/kg) > selectively cut mixed broadleaved-Korean pine forest (980.3 and 153.4 mg/kg) > virgin mixed broadleaved-Korean pine forest (948.9 and 143.6 mg/kg) > artificial larch forest (927.2 and 131.0 mg/kg) > valley spruce-fir forest (606.2 and 95.0 mg/kg). Root removal significantly decreased soil microbial biomass (P <0.01). The maximum MBC (44%) and MBN (34%) reductions were found in the valley spruce-fir forest and the artificial larch forest, respectively. The minimum MBC (12%) and MBN (11%) reductions were found in the selectively cut mixed broadleaved-Korean pine forest. MBC and MBN were significantly positively correlated with soil organic carbon, soil total nitrogen, and soil water content (P <0.05), and MBN was significantly positively correlated with soil temperature (P <0.01). We concluded that the combined effects of soil temperature, soil water content, and soil nutrients contributed to the differences in the soil microbial biomass found across the six forest types.
Key words: Xiaoxing’an Mountains    soil microbial biomass carbon and nitrogen    seasonal variation    root removal    

土壤微生物是陆地生态系统的调节者和分解者,参与生态系统的物质循环和能量流动,是维护森林生态系统可持续发展的重要组成部分[1, 2]。土壤微生物量是土壤有机质的活性部分,对土壤环境因子的变化极为敏感[3],不仅在养分转化中起重要作用,其本身也是土壤养分的供应源和贮存库[4]。土壤微生物量碳尽管只占土壤总有机碳的1%—5%,但却参与土壤有机质分解、养分循环、污染物的降解和土壤结构形成等诸多土壤生态过程,是控制土壤养分周转的主要因素,对全球碳循环有重要贡献[5, 6, 7]

森林生态系统中土壤微生物量具有明显的季节性波动,其波动模式复杂,受多种生态因子综合作用的影响[8]。不同生态系统,即使处于同一气候区域,土壤微生物量对季节变化的响应也不同,在同一季节或升高,或下降[9, 10]。就某一特定森林生态系统而言,土壤温湿度、降雨量、土壤理化性质和树种特性等因素是调控土壤微生物量季节变化的主要因子[11]。作为环境因子,土壤有效碳也是调节土壤微生物量增长变化的驱动因子[5]。Hütsch发现植物根系分泌物是土壤有效碳的重要来源,土壤微生物活性随着根系分泌物的增加而增加[12];土壤微生物量的季节变化与土壤中植物根系分泌物的多少有关[13, 14]

以往对土壤微生物量的研究多集中在典型生态系统[15]、土地利用方式[16]及退化土壤植被恢复[17]对土壤微生物量的影响等方面,对同一气候区不同森林类型的土壤生物量研究还很匮乏。小兴安岭是我国主要林区之一,且地处气候变化敏感地区。本文选择黑龙江凉水国家级自然保护区内具有代表性的6种森林类型为研究对象,探讨土壤微生物量季节动态变及其影响因子,分析根系去除对土壤微生物量的影响,为揭示该区森林碳氮循环过程与机制提供基础数据与科学依据。

1 材料与方法 1.1 研究区自然条件

研究样地设在黑龙江凉水国家级自然保护区(128°53′20″ E、47°10′50″ N)内。保护区海拔高度在280—707.3 m之间,山地坡度一般在10—15°之间,是典型的低山丘陵地貌。该区属温带大陆性夏雨季风气候,春季迟缓,降水少;夏季短促,温凉多雨;秋季降温快,多出现早霜;冬季漫长且寒冷干燥。年平均气温-0.3 ℃,年均最高气温7.5 ℃,年均最低气温-6.6 ℃,正值积温在2200—2600 ℃之间。年平均降水量676 mm,年平均蒸发量805 mm,无霜期100—120 d,积雪期130—150 d,地带性土壤为暗棕壤,非地带性土壤为草甸土、沼泽土和泥炭土。

1.2 实验设计与方法

本研究以小兴安岭6种典型森林类型为研究对象,分别为:原始阔叶红松(Pinus koraiensis)林 、原始阔叶红松林经过择伐后形成的阔叶红松择伐林(以下简称择伐林)、阔叶红松林皆伐后天然更新形成的次生白桦(Betula platyphylla)林和阔叶红松林皆伐后人工造林的落叶松(Larix gmelinii)林和红松林,以及非地带性顶极植被-谷地云冷杉(Picea-Abies)林,其植被概况详见史宝库[18]

2 009年10月,在每个森林类型内随机设置3个20 m×30 m的固定样地。在每个固定样地内随机选取4个2 m×2 m的对照样方和4个2 m×2 m的去除根系样方。采用挖壕法:即在样方四周挖0.2 m的壕,深至基岩或无根系位置(≥60 cm),壕内用双层细孔井底布隔离样方周围的根系,既可以阻止周围植物根系的侵入,又保证透气、透水,而后按原土层回填壕内的土壤。贴地面剪除小样方内的地面植被,尽量减少对地表土壤的扰动,在随后的测定中始终保持样方内没有活体植物。

于2010年6—10月期间,每月(其中8月和9月每半个月1次)在每块样地采用混合取样法进行土壤样品采集。取样前移去土壤表面的凋落物层后用土钻采集表层(0—10 cm)土壤。每块样地2份混合土壤样品(对照1份,去根处理1份),6种林型共计36份土壤样品。样品立即装入保温箱内带回实验室置于4 °C下贮存,并于1周内完成土壤微生物量碳、氮的测定。同时将一部分土壤样品风干,用于土壤理化性质测定。

土壤含水率(Ws)采用烘干法((105±2)℃,12 h);土壤温度(Ts)采用LI-6400便携式CO2 /H2O分析系统(LI-COR Inc.,Lincoln,NE,USA)附带的温度探针测定;土壤总有机碳(SOC)采用multi N/C 3000 TOC分析仪(Analytik Jena AG,Germany)测定;土壤全氮(TN)采用KjeltecTM2300凯氏定氮仪(Foss Teactor AB,Sweden)进行测定;土壤微生物量采用氯仿熏蒸浸提法测定[19],浸提液中有机碳及全氮含量由Multi N/C 3000分析仪测定。土壤微生物量碳(MBC)和土壤微生物量氮(MBN)分别用下式求得[20, 21]

式中,ECEN分别为熏蒸和未熏蒸土样浸提液有机碳、全氮的差值;0.45为校正系数。

1.3 数据分析

利用t检验法检验同一林型对照与处理间的MBC、MBN及环境因子的差异;Duncan多重检验比较林型间MBC和MBN显著性差异;利用Pearson相关系数评价MBC和MBN 与SOC、TN、WsTs之间的关系。以上统计分析均使用了SPSS16.0。

2 结果与分析 2.1 土壤理化性质

在6种森林类型中,人工红松林的土壤有机碳显著高于阔叶红松林、人工落叶松林、谷地云冷杉林和择伐林(P < 0.05);土壤全氮在次生白桦林和人工落叶松林间差异显著(P < 0.05),在阔叶红松林、人工红松林、谷地云冷杉林和择伐林之间差异不显著(P > 0.05);次生白桦林的土壤湿度显著高于阔叶红松林、人工红松林、人工落叶松林、谷地云冷杉林和择伐林(P < 0.05);土壤温度在所有林型差异不显著(P > 0.05)(表 1)。

表 1 6种森林类型的土壤理化性质 Table 1 Soil physical and chemical properties of the six forest types
森林类型
Forest type
对照Control 去根Roots removal
总有机碳
Total organic
carbon
/(g/kg)
全氮
Total
nitrogen
/(g/kg)
含水率
Soil water
content
/%
温度
Soil
temperature
/℃
总有机碳
Total organic
carbon
/(g/kg)
全氮
Total
nitrogen
/(g/kg)
含水率
Soil water
content
/%
温度
Soil
temperature
/℃
不同大、小写字母分别表示同一处理不同林型间和同一林型不同处理间差异显著(α=0.05)
次生白桦林
Secondary birch forest
84.20ABa6.74Aa93.29Aa15.68Aa73.46Aa8.36Ab95.30Aa15.66Aa
阔叶红松林
Mixed broadleaved-Korean pine forest
61.53Ba6.35ABa63.34Ba14.18Aa53.89Ba8.24ABb69.79Ca14.32Aa
人工红松林
Artificial Korean pine
forest
96.93Aa5.93ABa63.86Ba13.36Aa77.06Aa7.96ABCb89.69ABb13.51Aa
人工落叶松林
Artificial larch forest
60.04Ba5.79Ba56.32Ba13.86Aa53.18Ba6.79Cb68.84Ca14.04Aa
谷地云冷杉林
Valley spruce-fir forest
59.45Ba6.02ABa68.42Ba13.01Aa45.34Bb7.73ABCb65.55Ca13.51Aa
择伐林
Selection cutting forest
63.75Ba5.85ABa69.63Ba15.01Aa56.08Bb6.99BCb78.29BCa15.26Aa

与对照样地相比,去根处理后6种林型的总有机碳均有不同程度的减少,其中在谷地云冷杉林和择伐林显著减少(P < 0.05);全氮含量均显著增加(P < 0.05);湿度在大部分林型表现为增加,其中在人工红松林表现为显著增加(P < 0.05);温度在大部分林型表现为增加,但均没有显著差异(P > 0.05)(表 1)。

2.2 土壤微生物量碳和氮含量及其季节变化

6种林型土壤微生物量碳、氮大小均依次为:次生白桦林>人工红松林>择伐林>阔叶红松林>人工落叶松林>谷地云冷杉林。其中次生白桦林和人工红松林2种林型的MBC与谷地云冷杉林的差异显著(P < 0.05),阔叶红松林、人工落叶松林和择伐林3种林型间的MBC差异不显著(P >0.05);MBN在次生白桦林、谷地云冷杉林和择伐林之间差异显著(P < 0.05),在阔叶红松林、人工红松林和人工落叶松林之间差异不显著(P >0.05)。阔叶林或阔叶树比率较高的森林类型(次生白桦林、阔叶红松林和择伐林)的土壤微生物量(MBC和MBN:1082.70 mg/kg和170.85 mg/kg)总体上高于针叶林或针叶树比率较高的森林类型(谷地云冷杉林、人工红松林和人工落叶松林)(MBC和MBN:890.23 mg/kg和131.70 mg/kg)(表 2)。

表 2 6种森林类型土壤微生物量碳(MBC)、氮(MBN)的多重比较 Table 2 Multiple-range test for the means of soil microbial biomass carbon (MBC) and nitrogen (MBN) of the six forest types
森林类型
Forest type
对照Control 去根Roots removal
土壤微生物量碳
Soil microbial
biomass carbon
/(mg/kg)
土壤微生物量氮
Soil microbial
biomass nitrogen
/(mg/kg)
土壤微生物量碳
Soil microbial
biomass carbon
/(mg/kg)
土壤微生物量氮
Soil microbial
biomass nitrogen
/(mg/kg)
次生白桦林
Secondary birch forest
1318.85Aa215.52Aa1118.58Aa173.41Aa
阔叶红松林
Mixed broadleaved-Korean pine forest
948.95ABa143.62BCa783.58Ba95.89BCb
人工红松林
Artificial Korean pine forest
1137.34Aa169.09ABa933.48ABa150.06Aa
人工落叶松林
Artificial larch forest
927.16ABa130.98BCa652.86Bb86.43Cb
谷地云冷杉林
Valley spruce-fir forest
606.19Ba95.03Ca339.57Cb68.60Ca
择伐林
Selection cutting forest
980.29ABa153.42Ba866.29ABa135.88ABa

与对照样地相比,去根处理后所有林型的土壤 微生物量均有不同程度的减少,其中谷地云冷杉林的MBC(44%)和人工落叶松林MBN(34%)的减少量最大,择伐林的MBC(12%)和MBN(11%)减少量最小,MBC和MBN的波动在275.77—1252.00 mg/kg和43.20—175.89 mg/kg之间,均占有机碳和全氮含量的1%—2%(表 2)。

研究期间,6种森林类型MBC的季节变化趋势有所不同(图 1)。次生白桦林、阔叶红松林和择伐林的MBC 在6月末—8月中旬呈上升趋势,8月12日达到峰值,随后呈下降趋势;而3种森林类型的MBC没有明显的最低值,其中择伐林的季节波动较小。人工红松林和人工落叶松林的MBC呈先降低再升高的趋势,8月12日达到峰值,随后逐渐降低,在9月18日出现第2峰值。因森林类型的差异MBC发生最低值的时间不同,人工红松林在8月下旬,人工落叶松林在9月初;而谷地云冷杉林的MBC基本呈“W”型变化趋势,最低值发生在8月下旬,最高值发生在10月初,且季节波动较小。

图 1 6种森林类型土壤微生物量碳 (MBC) 的季节变化 Fig.1 Seasonal dynamics of soil microbial biomass carbon (MBC) of the six forest types (mean±SE)

MBN的季节变化与MBC基本一致(图 2),即:在研究期间呈先升高后降低再升高的变化趋势,人工落叶松林最高值发生在10月初,其他5种森林类型均发生在8月12日。根系去除并没有改变土壤微生物量的季节变化趋势(除谷地云冷杉林外)(图 1图 2)。

图 2 6种森林类型土壤微生物量氮 (MBN) 的季节变化 Fig.2 Seasonal dynamics of soil microbial biomass nitrogen (MBN) of the six forest types (mean±SE)
2.3 土壤微生物量与土壤理化性质的关系

Pearson相关分析表明,MBC、MBN分别与SOC、TN及Ws呈极显著正相关(P < 0.01),MBC与Ts相关关系不显著(P > 0.05),MBN与Ts呈极显著正相关(P < 0.01);MBC/MBN与SOC、TN、WsTs相关关系均不显著(P > 0.05)(表 3)。

表 3 土壤微生物量碳、氮和微生物量碳氮比与土壤理化性质的相关分析 Table 3 Correlation between soil microbial biomass carbon (MBC) ,nitrogen (MBN) ,soil microbial biomass carbon / nitrogen (MBC/MBN) and soil physical and chemical properties
总有机碳
Total organic carbon
全氮
Total nitrogen
含水率
Soil water content
温度
Soil temperature
*P < 0.05,**P < 0.01
土壤微生物量碳
Soil microbial biomass carbon
0.628* *0.281* *0.306* *0.068
土壤微生物量氮
Soil microbial biomass nitrogen
0.570* *0.285* *0.321* *0.242* *
土壤微生物量碳氮比
Soil microbial biomass carbon/ nitrogen
-0.019-0.067-0.066-0.093
3 讨论 3.1 不同森林类型土壤微生物量的差异

土地利用方式、植被类型以及林分结构的差异影响着凋落物组成、土壤微生物代谢底物和林内小气候,导致即使处于同一气候带,土壤微生物量也有所差异[16, 22, 23, 24]。本研究中MBC和MBN的波动分别在383.54—1633.65 mg/kg和47.56—231.97 mg/kg之间(图 1图 2),高于温带其他地区[25, 26],其差异可能是由于森林类型和采样周期不同而造成的。6种森林类型MBC和MBN的大小顺序依次为:次生白桦林>人工红松林>择伐林>阔叶红松林>人工落叶松林>谷地云冷杉林。杨刚等[23]研究发现次生林的土壤微生物量(MBC和MBN:2931 mg/kg和338 mg/kg)显著高于成熟林(MBC和MBN:2243 mg/kg和236 mg/kg),王国兵等[8]发现次生栎林的MBC(278.6—467.8 mg/kg)高于火炬松(Pinus teada)人工林(267.8—459.8 mg/kg),这些研究结果与本研究一致。本研究中次生白桦林是原始阔叶红松林经过皆伐后自然更新形成的,处于演替的早期阶段,生态系统代谢旺盛,不同植物根系相互作用,刺激了土壤微生物的生长和繁殖。谷地云冷杉林是本地区的非地带性顶极群落,其土壤微生物所转化的养分不能满足植被生长所需[23],较低的土壤温、湿度又限制了土壤微生物的活动,使其生物量相对较低,这种差异是森林类型和环境因子共同作用的结果。Thoms等[22]指出不同植被组成凋落物的质量和数量存在差异,使输入到土壤中的有机养分不同,进而影响土壤微生物的活动。本研究发现阔叶林或阔叶树比率较高的森林类型(次生白桦林、阔叶红松林和择伐林)的土壤微生物量总体上高于针叶林或针叶树比率较高的森林类型(谷地云冷杉林、人工红松林和人工落叶松林)(表 2),与Chodak等[27]和Bohlen等[28]的研究结果一致,进一步表明了森林类型是影响土壤微生物量的重要因素。

3.2 不同森林类型土壤微生物量的季节变化特征

众多研究表明土壤微生物量受季节变化影响显著[9, 10, 29],然而其研究结果并没有统一的规律。本研究中6种森林类型土壤微生物量的季节变化有所差异(图 1图 2),最高值多发生在8月中旬,与以往研究结果一致[25, 30, 31],可能此时适宜的土壤温、湿度为微生物提供了良好的代谢环境,有助于其生长和繁殖;生长末期,较低的土壤温、湿度抑制了土壤微生物的生长,使其代谢减弱,从而减少土壤微生物量。Wardle[5]总结发现,在生长季节植物和土壤微生物对养分的利用存在互相促进和竞争的关系,也可导致土壤微生物量发生季节变化。

本研究相关分析表明,MBC和MBN分别与SOC、TN及Ts呈极显著正相关(P < 0.01),MBN还与Ts呈极显著正相关(P < 0.01)(表 3),与大多数研究结论相同[32, 33, 34, 35],表明土壤有机碳、全氮及温度与湿度是影响本研究区土壤微生物量变化的主要因子。然而,土壤微生物量通常受多种因子的交互影响,由于不同森林生态系统的主要影响因子不同,土壤微生物量的季节变化存在差异[8]。例如,在温带气候条件下,土壤微生物量表现出夏低冬高或夏高冬低的变化趋势,这可能与土壤温湿度的综合作用有关[26, 31];在热带和亚热带气候区,土壤微生物量不规则的季节波动主要是由于植物和微生物对养分吸收的不同步造成的[36, 37];在干热带森林和农业生态系统中,水分是最主要的限制因子,在水分的干-湿交替下会造成土壤微生物量发生相应的干-湿循环变化[9, 38],这些研究表明土壤微生物量季节变化及其复杂,不仅受土壤环境因子和植物生长节律的影响,还受生态系统和气候类型的影响。

本研究中谷地云冷杉林的季节变化比较稳定,且峰值发生推迟到10月初,原因之一可能是云冷杉林中多为常绿树种,其凋落物的全年输入使土壤微生物量相对稳定。Ruan等[36]和吴艺雪等[39]的研究也证实了这一点,即土壤微生物量和地上凋落物的季节变化异步发生,可能提前或滞后凋落物1个月。Myers等[11]研究发现不同生态系统土壤微生物量的季节变化与水热条件和植物的物候变化有很大关系。综上,土壤微生物量的季节变化可能受不同机制的驱动,本研究中6种林型土壤微生物量季节变化的差异,也可能与不同林型组成树种物候及其生理过程的差异有关。

3.3 土壤微生物量与土壤理化性质之间的关系

植被通过根系分泌物和死亡残体向土壤提供碳氮,影响土壤有机碳的输入,从而影响土壤微生物量[40]。土壤微生物对于环境的变化十分敏感,本研究测定了对照和去除根系样地的土壤有机碳、全氮及温度与湿度等土壤因子,结果发现根系去除改变了土壤微生物的理化性质(表 1),使6种森林类型的土壤微生物量有不同程度的减少,具体表现为谷地云冷杉林、人工落叶松林、人工红松林、阔叶红松林、次生白桦林和择伐林的MBC和MBN分别减少了44%、30%、18%、17%、15%、12%和28%、34%、11%、33%、20%和12%(表 2),表明土壤微生物的生长受到土壤中有效碳和养分的限制。Feng等[41]研究地上、地下碳输入对MBC的影响时,也发现根系的去除使其含量降低。张伟东等[42]研究发现与凋落物相比,增加杉木根系对土壤微生物量的促进作用更为显著。相反,在美国和匈牙利的3个DIRT(detritus input and removal treatments,DIRT)实验中,去除根系没有影响土壤微生物量和细菌生物量的变化[43]。这些研究表明根系的去除对土壤微生物量的影响因所处区域和植被类型而存在差异。此外,本研究发现人工林MBC的减少量大于次生林,这与Li等[44]的研究结果相反。可能与本研究未对凋落物进行处理有关,即大量凋落物的输入,能弥补根去除导致的养分损失。也有研究[45]报道针叶凋落物中存在大量顽抗的化合物,使其分解速率降低,随之向土壤中转移养分的速率也下降,使土壤微生物活性减弱。因此,不同森林类型的土壤微生物量不仅受地下碳的影响,可能还受地上凋落物的影响,今后还需对地下根系和地上凋落物进行有效的分离,以区分其对土壤微生物量的影响。

参考文献
[1] Wardle D A, Bardgett R D, Klironomos J N, Setälä H, Van der Putten W H, Wall D H. Ecological linkages between aboveground and belowground biota. Science, 2004, 304(5677): 1629-1633.
[2] Lou Y L, Liang W J, Xu M G, He X H, Wang Y D, Zhao K. Straw coverage alleviates seasonal variability of the topsoil microbial biomass and activity. Catena, 2011, 86(2): 117-120.
[3] Zhao X, Wang Q, Kakubari Y. Stand-scale spatial patterns of soil microbial biomass in natural cold-temperate beech forests along an elevation gradient. Soil Biology and Biochemistry, 2009, 41(7): 1466-1474.
[4] Yang K, Zhu J J, Zhang J X, Yan Q L. Seasonal dynamics of soil microbial biomass C and N in two larch plantation forests with different ages in Northeastern China. Acta Ecologica Sinica, 2009, 29(10): 5500-5507.
[5] Wardle D A. A comparative assessment of factors which influence microbial biomass carbon and nitrogen levels in soil. Biological Reviews, 1992, 67(3): 321-358.
[6] Piotrowska A, Długosz J. Spatio-temporal variability of microbial biomass content and activities related to some physicochemical properties of Luvisols. Geoderma, 2012, 173-174: 199-208.
[7] Kaschuk G, Alberton O, Hungria M. Three decades of soil microbial biomass studies in Brazilian ecosystems: Lessons learned about soil quality and indications for improving sustainability. Soil Biology and Biochemistry, 2010, 42(1): 1-13.
[8] Wang G B, Ruan H H, Tang Y F, Luan Y L, Chen Y Q, Tao Z F. Seasonal fluctuation of soil microbial biomass carbon in secondary oak forest and Pinus taeda plantation in north subtropical area of China. Chinese Journal of Applied Ecology, 2008, 19(1): 37-42.
[9] Patel K, Nirmal Kumar J I, N Kumar R, Kumar Bhoi R. Seasonal and temporal variation in soil microbial biomass C, N and P in different types land uses of dry deciduous forest ecosystem of Udaipur, Rajasthan, Western India. Applied Ecology and Environmental Research, 2010, 8(4): 377-390.
[10] Singh J S, Singh D P, Kashyap A K. Microbial biomass C, N and P in disturbed dry tropical forest soils, India. Pedosphere, 2010, 20(6): 780-788.
[11] Myers R T, Zak D R, White D C, Peacock A. Landscape-level patterns of microbial community composition and substrate use in upland forest ecosystems. Soil Science Society of America Journal, 2001, 65(2): 359-367.
[12] HÜtsch B W, Augustin J, Merbach W. Plant rhizodeposition-an important source for carbon turnover in soils. Journal of Plant Nutrition and Soil Science, 2002, 165(4): 397-407.
[13] Boone R D, Nadelhoffer K J, Canary J D, Kaye J P. Roots exert a strong influence on the temperature sensitivity of soil respiration. Nature, 1998, 396(6711): 570-572.
[14] Högberg P, Nordgren A, Buchmann N, Taylor A F S, Ekblad A, Högberg M N, Nyberg G, Ottosson-Löfvenius M, Read D J. Large-scale forest girdling shows that current photosynthesis drives soil respiration. Nature, 2001, 411(6839): 789-792.
[15] Jiang Y M, Pang X Y, Bao W K. Soil microbial biomass and the influencing factors under Pinus tabulaeformis and Picea asperata plantations in the upper Minjiang River. Acta Ecologica Sinica, 2011, 31(3): 801-811.
[16] Pang X, He W Q, Yan C R, Liu E K, Liu S, Yin T. Effect of tillage and residue management on dynamic of soil microbial biomass carbon. Acta Ecologica Sinica, 2013, 33(4): 1308-1316.
[17] Huang Y M, An S S, Xue H. Responses of soil microbial biomass C and N and respiratory quotient (qCO2) revegetation on the Loess Hilly-Gully region. Acta Ecologica Sinica, 2009, 29(6): 2811-2818.
[18] Shi B K. Soil Respiration Characteristics of Six Forest Types in Xiaoxing'an Mountains, China[D]. Harbin: Northeast Forestry University, 2012.
[19] Lin Q M, Wu Y G, Liu H L. Modification of fumigation extraction method for measuring soil microbial biomass carbon. Chinese Journal of Ecology, 1999, 18(2): 63-66.
[20] Wu J, Joergensen R G, Pommerening B, Chaussod R, Brookes P C. Measurement of soil microbial biomass C by fumigation-extraction: an automated procedure. Soil Biology and Biochemistry, 1990, 22(8): 1167-1169.
[21] Joergensen R G, Brookes P C. Ninhydrin-reactive nitrogen measurements of microbial biomass in 0.5 mol K2SO4 soil extracts. Soil Biology and Biochemistry, 1990, 22(8): 1023-1027.
[22] Thoms C, Gattinger A, Jacob M, Thomas F M, Gleixner G. Direct and indirect effects of tree diversity drive soil microbial diversity in temperate deciduous forest. Soil Biology and Biochemistry, 2010, 42(9): 1558-1565.
[23] Yang G, He X Y, Wang K L, Huang J S, Chen Z H, Li Y Z, Ai M H. Effects of vegetation types on soil micro-biomass carbon, nitrogen and soil respiration. Chinese Journal of Soil Science, 2008, 39(1): 189-191.
[24] Malchair S, Carnol M. Microbial biomass and C and N transformations in forest floors under European beech, sessile oak, Norway spruce and Douglas-fir at four temperate forest sites. Soil Biology and Biochemistry, 2009, 41(4): 831-839.
[25] Yang K, Zhu J J, Zhang M, Yan Q L, Sun O J X. Soil microbial biomass carbon and nitrogen in forest ecosystems of Northeast China: a comparison between natural secondary forest and larch plantation. Journal of Plant Ecology, 2010, 3(3): 175-182.
[26] Liu S, Wang C K. Spatio-temporal patterns of soil microbial biomass carbon and nitrogen in five temperate forest ecosystems. Acta Ecologica Sinica, 2010, 30(12): 3135-3143.
[27] Chodak M, Niklińska M. Effect of texture and tree species on microbial properties of mine soils. Applied Soil Ecology, 2010, 46(2): 268-275.
[28] Bohlen P J, Groffman P M, Driscoll C T, Fahey T J, Siccama T G. Plant-soil-microbial interactions in a northern hardwood forest. Ecology, 2001, 82(4): 965-978.
[29] Edwards K A, Jefferies R L. Inter-annual and seasonal dynamics of soil microbial biomass and nutrients in wet and dry low-Arctic sedge meadows. Soil Biology and Biochemistry, 2013, 57: 83-90.
[30] Chen C R, Xu Z H, Blumfield T J, Hughes J M. Soil microbial biomass during the early establishment of hoop pine plantation: seasonal variation and impacts of site preparation. Forest Ecology and Management, 2003, 186(1/3): 213-225.
[31] Liu Y, Han S J. Factors controlling soil respiration in four types of forest of Changbai Mountains, China. Ecology and Environmental Sciences, 2009, 18(3): 1061-1065.
[32] Zhang D, Zhang Y X, Qu L Y, Ma K M, Dai S D. Effects of slope position on soil microbial biomass of Quercus liaotungensis forest in Dongling Mountain. Acta Ecologica Sinica, 2012, 32(20): 6412-6421.
[33] Abbasi M K, Khizar A. Microbial biomass carbon and nitrogen transformations in a loam soil amended with organic-inorganic N sources and their effect on growth and N-uptake in maize. Ecological Engineering, 2012, 39: 123-132.
[34] Santos V B, Araújo A S F, Leite L F C, Nunes L A P L, Melo W J. Soil microbial biomass and organic matter fractions during transition from conventional to organic farming systems. Geoderma, 2012, 170: 227-231.
[35] He R, Wang G B, Wang J S, Xu B F, Wang K J, Fang Y H, Shi Z, Ruan H H. Seasonal variation and its main affecting factors of soil microbial biomass under different vegetations along an elevation gradient in Wuyi Mountains of China. Chinese Journal of Ecology, 2009, 28(3): 394-399.
[36] Ruan H H, Zou X M, Scatena F N, Zimmerman J K. Asynchronous fluctuation of soil microbial biomass and plant litterfall in a tropical wet forest. Plant and Soil, 2004, 260(1/2): 147-154.
[37] Barbhuiya A R, Arunachalam A, Pandey H N, Arunachalam K, Khan M L, Nath P C. Dynamics of soil microbial biomass C, N and P in disturbed and undisturbed stands of a tropical wet-evergreen forest. European Journal of Soil Biology, 2004, 40(3/4): 113-121.
[38] Sugihara S, Funakawa S, Kilasara M, Kosaki T. Effect of land management and soil texture on seasonal variations in soil microbial biomass in dry tropical agroecosystems in Tanzania. Applied Soil Ecology, 2010, 44(1): 80-88.
[39] Wu Y X, Yang X D, Yu G B. Seasonal fluctuation of soil microbial biomass carbon and its influence factors in two types of tropical rainforests. Ecology and Environmental Sciences, 2009, 18(2): 658-663.
[40] Rutigliano F A, D'Ascoli R, Virzo De Santo A. Soil microbial metabolism and nutrient status in a Mediterranean area as affected by plant cover. Soil Biology and Biochemistry, 2004, 36(11): 1719-1729.
[41] Feng W T, Zou X M, Schaefer D. Above- and belowground carbon inputs affect seasonal variations of soil microbial biomass in a subtropical monsoon forest of southwest China. Soil Biology and Biochemistry, 2009, 41(5): 978-983.
[42] Zhang W D, Wang S L, Yan S K, Yang H X, Xu G B. Effects of root system and litter of Chinese fir on soil microbial properties. Chinese Journal of Applied Ecology, 2009, 20(10): 2345-2350.
[43] Brant J B, Myrold D D, Sulzman E W. Root controls on soil microbial community structure in forest soils. Oecologia, 2006, 148(4): 650-659.
[44] Li Y Q, Xu M, Sun O J, Cui W C. Effects of root and litter exclusion on soil CO2 efflux and microbial biomass in wet tropical forests. Soil Biology and Biochemistry, 2004, 36(12): 2111-2114.
[45] Leckie S E, Prescott C E, Grayston S J. Forest floor microbial community response to tree species and fertilization of regenerating coniferous forests. Canadian Journal of Forest Research, 2004, 34(7): 1426-1435.
[4] 杨凯, 朱教君, 张金鑫, 闫巧玲. 不同林龄落叶松人工林土壤微生物生物量碳氮的季节变化. 生态学报, 2009, 29(10): 5500-5507.
[8] 王国兵, 阮宏华, 唐燕飞, 栾以玲, 陈月琴, 陶忠芳. 北亚热带次生栎林与火炬松人工林土壤微生物生物量碳的季节动态. 应用生态学报, 2008, 19(1): 37-42.
[15] 江元明, 庞学勇, 包维楷. 岷江上游油松与云杉人工林土壤微生物生物量及其影响因素. 生态学报, 2011, 31(3): 801-811.
[16] 庞绪, 何文清, 严昌荣, 刘恩科, 刘爽, 殷涛. 耕作措施对土壤水热特性和微生物生物量碳的影响. 生态学报, 2013, 33(4): 1308-1316.
[17] 黄懿梅, 安韶山, 薛虹. 黄土丘陵区草地土壤微生物C、N及呼吸熵对植被恢复的响应. 生态学报, 2009, 29(6): 2811-2818.
[18] 史宝库. 小兴安岭6种林型土壤呼吸特征 [D]. 哈尔滨: 东北林业大学, 2012.
[19] 林启美, 吴玉光, 刘焕龙. 熏蒸法测定土壤微生物量碳的改进. 生态学杂志, 1999, 18(2): 63-66.
[23] 杨刚, 何寻阳, 王克林, 黄继山, 陈志辉, 李有志, 艾美荣. 不同植被类型对土壤微生物量碳氮及土壤呼吸的影响. 土壤通报, 2008, 39(1): 189-191.
[26] 刘爽, 王传宽. 五种温带森林土壤微生物生物量碳氮的时空格局. 生态学报, 2010, 30(12): 3135-3143.
[31] 刘颖, 韩士杰. 长白山四种森林土壤呼吸的影响因素. 生态环境学报, 2009, 18(3): 1061-1065.
[32] 张地, 张育新, 曲来叶, 马克明, 戴斯迪. 坡位对东灵山辽东栎林土壤微生物量的影响. 生态学报, 2012, 32(20): 6412-6421.
[35] 何容, 王国兵, 汪家社, 许波峰, 汪科继, 方燕鸿, 施政, 阮宏华. 武夷山不同海拔植被土壤微生物量的季节动态及主要影响因子. 生态学杂志, 2009, 28(3): 394-399.
[39] 吴艺雪, 杨效东, 余广彬. 两种热带雨林土壤微生物生物量碳季节动态及其影响因素. 生态环境学报, 2009, 18(2): 658-663.
[42] 张伟东, 汪思龙, 颜绍馗, 杨会侠, 徐广标. 杉木根系和凋落物对土壤微生物学性质的影响. 应用生态学报, 2009, 20(10): 2345-2350.