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土壤有机碳矿化是土壤碳库向大气碳库输入CO2的主要途径，对全球气候变化具有重要作用[1]。土壤有机碳矿化是个复杂的生态学过程，其影响因素众多，包括温度[2]、湿度[3]、森林类型[4]、土壤质地[5]、土壤深度[6]、林火干扰[7]、物理扰动[8]等。全面掌握土壤有机碳矿化作用机制，对研究土壤有机质对大气CO2的源/汇作用十分重要。
近年来土壤有机碳矿化越来越受学者关注。许多研究采用一级动力学方程拟合土壤有机碳矿化动态，研究土壤有机碳各库大小和周转时间及其对土地利用变化、温度升高等的响应[9-11]。其他研究则集中在添加外源有机物对土壤有机碳矿化的影响，如凋落物[12]、养分[13]、火成碳[14]等。还有很多研究关于物理扰动对土壤有机碳矿化的影响。物理扰动对土壤有机碳矿化的影响因土壤类型、物理扰动程度、土壤有机碳稳定机制等不同，结果主要有增加[15-16]，减少[17]和基本无影响[18-20]3种。当前土壤有机碳矿化研究存在的一个科学问题是过筛处理影响土壤有机碳矿化结果。野外采集的土壤样品先过筛再进行室内培养，目前相关研究采用的土壤筛有1 mm[17-18]、2 mm[16, 21]、4 mm[18]等不同孔径，这将导致不同研究间土壤有机碳矿化结果的比较变得困难。因此，系统研究过筛处理对土壤有机碳矿化的影响并揭示其作用机制，可为室内培养过程中土壤样品的处理，土壤有机碳分解格局的比较提供理论参考。
碳水化合物虽然仅占土壤有机质的很小一部分(10%~20%)，却是微生物赖以生存的主要碳源和C、N矿化的重要基质[22]，同时还是土壤团聚体结构形成的重要胶结物质，对土壤结构的形成和稳定具有重要作用[23-24]。目前土壤碳水化合物测定多采用水解的方法进行提取，常用的提取试剂有硫酸、三氟乙酸和盐酸[25]，但有学者指出有机组分在土壤水溶液中的移动性影响微生物对其分解和利用[26-27]，因此本研究采用水溶液提取土壤中现存的而非水解提取的碳水化合物。本研究以小兴安岭阔叶次生林和原始红松(Pinus koraiensis)林为对象，将不同孔径土壤筛处理的和未过筛处理的土壤样品分别在室内培养35 d，测定不同过筛处理后土壤有机碳的矿化特征以及培养前后土壤水提取碳水化合物的变化，并用一级动力学模型拟合土壤有机碳矿化参数，定量研究过筛处理对土壤有机碳矿化的影响，以期为全面理解土壤有机碳动态及其矿化作用机制提供依据。
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研究区位于小兴安岭凉水国家级自然保护区(47°14′22″ N，128°48′30″ E)。该区具明显的温带大陆性季风气候特征，年均气温-0.3 ℃，年均最低温度-6.6 ℃，年均最高温度7.5 ℃，年降水量680~650 mm，无霜期约120 d。地带性植被为以红松为主的针阔叶混交林，即原始红松林。原始阔叶红松林采伐后形成以杨(Populus spp.)、桦(Betula spp.)为主的阔叶次生林。原始阔叶红松林样地位于保护区内，未受择伐干扰且林相整齐，林龄在250年以上；阔叶次生林样地位于保护区或毗邻区，主要树种为白桦(Betula platyphylla)、枫桦(B. costata)、山杨(Populus davidiana)、色木槭(Acer mono)等，林木生长良好且林相整齐，林龄40年以上。该地区为典型的低山丘陵地貌，海拔为300~500 m，地形起伏较平缓，坡度多为10°~25°。地带性土壤类型为温带湿润针阔混交林下发育的暗棕壤(暗沃冷凉淋溶土/冷凉湿润雏形土，CST)，其母质以花岗岩风化坡积物为主。
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于2013年4月，在自然保护区原始阔叶红松林和阔叶次生林设置固定样地10 m×10 m，各3块，在每块样地内采用3点混合随机取样法，分别采集0~5 cm、5~10 cm土层土壤样品，每层采集约1 kg。将新鲜土样去除根系、凋落物等后分成两部分，一部分用于室内培养试验和水提取碳水化合物的测定，另一部分用于测定土壤含水量、pH值、总有机碳和全氮，3次重复。
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新鲜土壤样品挑去可见根系、凋落物等后，分别采用不同样品处理方法进行处理：即将土壤样品分别过2和1 mm孔径筛，留在土壤筛上部的组分用手轻轻压碎直至全部通过，并将不经过筛处理的土壤作为对照。将3种状态的土壤样品分别进行室内培养实验和培养前后土壤水浸提碳水化合物的测定。
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采用室内恒温培养、碱液吸收法[28]测定土壤有机碳矿化速率和累积矿化量。分别称取25.00 g上述3种状态的新鲜土壤，放入装有20 mL 0.1 mol/L NaOH的500 mL三角瓶中，密封后18 ℃(模拟夏季土温)下黑暗培养35 d，在1、2、3、5、7、9、13、17、21、28、35 d测定CO2的释放量，根据CO2释放量计算培养期内土壤有机碳矿化量。
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称取10.00 g新鲜土样，加入100 mL蒸馏水，室温(25 ℃)下往复震荡30 min(250 r/min)[29]，在6 000 r/min下离心10 min，上清液过0.45 μm滤膜，滤液在-20 ℃下贮存，用于测定冷水提取碳水化合物。称取10.00 g新鲜土样，加入100 mL蒸馏水，在100 ℃水浴锅中水浴加热60 min[30]；冷却至室温后，在6 000 r/min下离心10 min，上清液过0.45 μm滤膜，滤液在-20 ℃下贮存，用于测定热水提取碳水化合物。土壤冷水提取碳水化合物和热水提取碳水化合物均采用硫酸-蒽酮法测定，即提取液加蒸馏水稀释后，加入10 mL蒽酮-硫酸溶液，在625 nm下测定溶液的吸光值[31]，所用仪器为7221型可见分光光度计(上海仪器公司)。
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土壤有机碳和全氮含量采用元素分析仪(Heraeus Elementar Vario EL, Hanau, Germany)直接测定；土壤pH值用HANNA pH 211型pH计测定；土壤含水量采用烘干法测定。样地土壤基本性质见表 1。
表 1 土壤基本性质
Table 1. Basic properties of sampled soil
森林类型
Forest type土层Soil
depth/cm含水量
Soil moisture/%pH 土壤有机碳
Soil organic carbon (SOC)/(g·kg-1)土壤全氮
Soil total nitrogen/(g·kg-1)C/N 阔叶次生林
Broadleaved secondary forest0~5 50.55 5.71 142.49 9.21 15.47 5~10 39.33 5.82 47.44 3.84 12.35 原始红松林
Virgin Korean pine forest0~5 47.00 5.45 117.49 5.99 19.62 5~10 34.67 5.68 37.56 2.33 16.09 -
采用单库一级动力学模型拟合土壤有机碳分解动态：
$$ {C_m} = {C_0}\left( {1 - {e^{ - kt}}} \right) + {C_1} $$ 式中：Cm为t时刻的有机碳累计矿化量；C0为潜在可矿化有机碳含量；C1为易矿化有机碳含量；k为有机碳矿化速率常数[18]。
利用SPSS18.0软件和Duncan多重比较法检验差异显著性(α=0.05)；利用Pearson相关系数评价各因素间的关系；利用Sigma Plot 10.0软件作图及进行有机碳矿化方程的拟合。图表中数据为平均值±标准差。
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由图 1可知，在培养初期阔叶次生林0~5 cm、5~10 cm土层有机碳矿化速率分别为140.17~236.48 mg/(kg·d)、37.81~58.46 mg/(kg·d)；原始红松林0~5 cm、5~10 cm土层有机碳矿化速率分别为88.84~154.69 mg/(kg·d)、32.78~54.40 mg/(kg·d)。至培养末期，阔叶次生林0~5 cm、5~10 cm土层有机碳矿化速率分别降为40.01~51.65 mg/(kg·d)、13.32~16.17 mg/(kg·d)；原始红松林0~5 cm、5~10 cm土层有机碳矿化速率分别降为29.90~39.35 mg/(kg·d)、11.05~13.59 mg/(kg·d)。2种森林类型土壤有机碳矿化速率变化趋势基本一致，随培养时间延长先急剧减小后缓慢下降。
图 1 过筛处理下2种森林类型土壤有机碳矿化速率
Figure 1. Mineralization rates of SOC in two forest types under different sample sieving methods
2种森林类型土壤有机碳矿化速率对过筛处理的响应一致，即土壤有机碳矿化速率表现为1 mm过筛土>2 mm过筛土>对照。3种处理方法间土壤有机碳矿化速率的差异随培养时间延长而减小。
在相同土层，阔叶次生林土壤有机碳矿化速率大于原始红松林。同一森林类型，0~5 cm土层土壤有机碳矿化速率大于5~10 cm土层。
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由图 2知，2种森林类型土壤有机碳矿化量均表现为1 mm过筛土>2 mm过筛土>对照。与对照相比，阔叶次生林2 mm过筛土有机碳累积矿化量增加17.57%~18.07%，1 mm过筛土增加33.18%~37.88%；原始红松林2 mm过筛土有机碳累积矿化量增加16.74%~17.05%，1 mm过筛土增加38.25%~39.16%。过筛处理能使2种森林类型土壤有机碳累积矿化量增加。
图 2 不同过筛处理下2种森林类型土壤有机碳累积矿化量
Figure 2. Cumulative SOC mineralization amount in two forest types under different sample sieving methods
在0~5 cm土层，2个过筛处理均使土壤有机碳累积矿化量显著增加；在5~10 cm土层，仅过1 mm筛使土壤有机碳累积矿化量显著增加，过2 mm筛土壤有机碳累积矿化量增加不明显。
阔叶次生林土壤有机碳累积矿化量大于原始红松林。0~5 cm土层土壤有机碳累积矿化量显著大于5~10 cm土层。
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由表 2知，过筛处理使2种森林类型土壤潜在可矿化碳C0和易矿化碳C1均增加，具体表现为1 mm过筛土>2 mm过筛土>对照。过筛处理对土壤C0影响不显著，但显著增加土壤C1的含量。与对照相比，阔叶次生林2 mm过筛土C1增加49.09%~59.58%，1 mm过筛土C1增加109.43%~132.40%；原始红松林2 mm过筛土C1增加55.76%~68.06%，1 mm过筛土C1增加91.03%~133.83%。
表 2 2种森林类型土壤有机碳矿化参数
Table 2. Estimated parameters according to the first order knitics model for soil C mineralization
森林类型
Forest type土层深度
Soil depth/cm处理方式
Processing methods潜在可矿化碳
C0/(mg·kg-1)易矿化碳含量
Easily mineralizable C (C1)/(mg·kg-1)矿化速率常数
Constant of mineralization rate K/d-1C0/SOC/
%R2 阔叶次生林
Broadleaved secondaryforest0~5 对照Control 3 405.81±200.23a 62.62±11.38a 0.026 9a 3.39 0.999 9 2 mm筛2 mm Sieve 3 885.66±99.23a 93.36±15.33b 0.028 2a 2.86 0.999 9 1 mm筛1 mm Sieve 4 040.65±211.80a 145.53±9.81c 0.032 1a 2.85 0.999 6 5~10 对照Control 1 167.04±139.39a 16.97±5.00a 0.021 5a 3.24 0.999 9 2 mm筛2 mm Sieve 1 266.58±98.53a 27.08±7.06b 0.023 9a 2.64 0.999 7 1 mm筛1 mm Sieve 1 305.20±151.45a 35.54±8.18c 0.027 5a 2.35 0.999 4 原始红松林Virgin
Korean pine forest0~5 对照Control 2 646.98±181.30a 47.94±7.70a 0.021 9a 2.10 0.999 7 2 mm筛2 mm Sieve 2 694.56±100.25a 80.57±9.99b 0.026 5a 2.08 0.999 1 1 mm筛1 mm Sieve 2 951.80±99.69a 112.10±15.58c 0.029 8a 1.92 0.998 6 5~10 对照Control 968.24±20.25a 16.50±3.21a 0.022 0a 2.59 0.999 9 2 mm筛2 mm Sieve 944.03±31.52a 25.70±4.03b 0.028 6a 2.09 0.999 5 1 mm筛1 mm Sieve 953.64±29.63a 31.52±6.13c 0.031 7a 1.54 0.999 5 注:不同小写字母表示相同土层不同过筛处理间差异显著(p＜0.05)。Note: different lowercase letters indicate significant differences (P＜0.05) among different sieving methods at the same soil layer. 阔叶次生林C0和C1均大于原始红松林。0~5 cm土层C0和C1均大于5~10 cm土层。2种森林类型、2个土层土壤有机碳矿化速率常数K差异不显著。
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由图 3知，过筛处理显著增加土壤冷水提取碳水化合物(Cool water extractable carbohydrate, CWEC)含量，而1 mm过筛土和2 mm过筛土CWEC差异不显著。在培养前，阔叶次生林2 mm过筛土CWEC增加37.87%~38.66%，1 mm过筛土增加40.37%~42.53%；原始红松林2 mm过筛土CWEC增加31.11%~34.20%，1 mm过筛土增加37.71%~38.42%。经过35 d培养后，阔叶次生林对照土壤CWEC减少42.13~79.58 mg/kg，2 mm过筛土减少60.66~93.96 mg/kg，1 mm过筛土减少62.17~104.72 mg/kg；原始红松林对照减少41.66~59.07 mg/kg，2 mm过筛土减少58.65~69.15 mg/kg，1 mm过筛土减少60.24~97.21 mg/kg。可见，过筛处理不仅影响培养前土壤CWEC的含量，还影响其在培养过程中的消耗。
图 3 样品处理方法对土壤冷水提取碳水化合物的影响
Figure 3. Effects of sample processing methods on soil extractable carbohydrate by cool water
阔叶次生林土壤CWEC含量显著大于原始红松林。0~5 cm土层CWEC含量显著大于5~10 cm土层。
由图 4知，不同样品处理方法对土壤热水提取碳水化合物(Hot water extractable carbohydrate, HWEC)基本无影响。与培养前相比，阔叶次生林对照土壤HWEC减少797.43~1 715.91 mg/kg，2 mm过筛土减少854.72~1 872.31 mg/kg，1 mm过筛土减少865.70~1 907.67 mg/kg；原始红松林对照减少533.71~1 143.44 mg/kg，2 mm过筛土减少563.32~1 212.48 mg/kg，1 mm过筛土减少560.47~1 340.01 mg/kg。
图 4 过筛处理对土壤热水提取碳水化合物的影响
Figure 4. Effects of sieving methods on soil extractable carbohydrate by hot water
阔叶次生林土壤HWEC含量大于原始红松林。0~5 cm土壤HWEC显著大于5~10 cm土层。
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从表 3可以看出，土壤有机碳累积矿化量与CWEC的初始含量和变化量均呈极显著正相关关系，与结束含量相关性较差。土壤有机碳矿化量与HWEC的初始含量、结束含量及其变化量均呈显著正相关关系。可见，土壤水提取碳水化合物显著影响土壤有机碳矿化。与对照相比，过筛土有机碳累积矿化量与水提取碳水化合物初始含量和变化量的相关系数更大，即过筛处理使土壤有机碳矿化与水提取碳水化合物的关系更紧密。在培养结束时土壤有机碳累积矿化量与冷水提取碳水化合物的相关性不显著。
表 3 土壤有机碳累积矿化量与水浸提碳水化合物的Pearson相关系数
Table 3. Pearson correlation coefficients between SOC cumulative mineralization amount and water extractable carbohydrate
冷水提取碳水化合物
Cool water extractable carbohydrate(CWEC)热水提取碳水化合物
Hot water extractable carbohydrate(HWEC)初始含量
Initial content结束含量
Final content变化量
Change of content初始含量
Initial content结束含量
Final content变化量
Change of content对照CK 0.883** 0.300 0.775** 0.938** 0.906** 0.889** 2 mm过筛土Soil sieved to 2 mm 0.906** 0.837 0.624** 0.954** 0.933** 0.889* 1 mm过筛土Soil sieved to 1 mm 0.877** 0.490 0.854** 0.922** 0.860** 0.894** 注Notes:*P＜0.05, **P＜0.01. -
室内培养过程中，2种林型土壤有机碳矿化速率随着培养时间延长表现出先快速下降后缓慢降低的趋势，主要与土壤有机碳的异质性有关。土壤有机碳由一系列易分解和难分解的有机碳组成，在其分解过程中微生物优先利用易分解的活性组分，矿化速率快，当活性组分不足时微生物开始利用相对难分解的复杂组分，矿化速率逐渐下降[9, 32-33]。2种森林类型0~5 cm土层有机碳矿化速率和累积矿化量均高于5~10 cm土层，与其他研究结果一致[34-35]。研究表明上层土壤含有更多活性组分，更易被微生物所利用[2, 36]。Fontaine等[37]则认为上层土壤含有更多新鲜的枯落物，会刺激微生物活动，促进其对有机质的分解。
阔叶次生林土壤有机碳矿化速率和累积矿化量大于原始红松林，与其他研究结果相似[38-39]。森林类型主要通过改变向土壤输入凋落物的数量和种类、根系-土壤相互作用、微生物群落组成等影响土壤有机碳矿化过程[40-41]。通常阔叶林土壤具有大量凋落物和较高的溶解性有机碳含量[41-43]，针叶林土壤有较多的木质素和较高的C/N比[38]，因而阔叶林土壤有机碳矿化速率高于针叶林。但也有不少研究得出针叶林土壤有机碳矿化速率高于阔叶林的结果[44-45]。
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阔叶次生林土壤热水提取碳水化合物和冷水提取碳水化合物显著高于原始红松林，与其他研究一致[27, 46]。阔叶次生林土壤热水提取碳水化合物含量是冷水提取碳水化合物的5~21倍，原始红松林土壤热水提取碳水化合物含量是冷水提取碳水化合物的3~16倍，与其他研究结果[27, 46]相符。因为高温能够水解土壤有机结构，裂解细胞，并把有机质从无机胶体上分离出来[47]，且高温加速了微生物的死亡从而使更多的有机质溶解到提取液中[48-49]。过筛处理显著增加培养前土壤冷水提取碳水化合物，但对热水提取碳水化合物影响不显著，可能是因为土壤热水提取碳水化合物除了包含冷水提取碳水化合物外，大部分来自微生物细胞的裂解和有机结构的水解，其含量远高于冷水提取碳水化合物，冷水提取碳水化合物数量的变化并不能引起土壤热水提取碳水化合物的显著改变。
分析发现土壤有机碳累积矿化量与冷水、热水提取碳水化合物初始含量和变化量均呈极显著正相关，且2种林型土壤有机碳累积矿化量和冷水提取碳水化合物分布格局一致。表明冷水提取碳水化合物是土壤有机碳矿化的关键组成部分，土壤冷水提取碳水化合物的损耗很大程度上能解释土壤有机碳矿化释放的CO2。土壤有机碳累积矿化量与培养结束时的冷水提取碳水化合物相关性不显著，可能因为培养结束时土壤中有新碳水化合物生成。土壤碳水化合物含量是其生成和消耗相平衡的结果，微生物除了能将碳水化合物矿化分解为CO2外，还可将其转化为其他不同结构的碳水化合物。Kalbitz等[50]指出，在培养过程中土壤多糖含量增加主要是因为微生物的合成作用，而且细菌和真菌能够释放出多种不同结构的多糖组分。
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过筛处理影响土壤有机碳矿化过程。Hassink等[17]将新西兰草地土壤分别过8和1 mm筛，发现与过8 mm筛相比，过1 mm筛使壤土和黏土有机碳矿化增加，使沙土有机碳矿化减少20%。Curtin等[18]研究表明，过4 mm筛土壤有机碳矿化与原状土相比没有差异，过1 mm筛使土壤有机碳矿化增加25%以上，并认为可能是过筛使包裹有机质暴露出来导致的；Stenger等[19]则发现过2 mm筛的新鲜土壤有机碳矿化与原状土没有差异。而陆志敏等[21]发现研磨过2 mm筛的黄泥土有机碳矿化速率和矿化量高于原状土。出现相异的研究结果可能与土壤样品过筛处理方法、土壤质地、有机碳保护机制等不同有关。
本研究发现过筛处理对小兴安岭2种森林类型土壤有机碳矿化速率的影响随着培养时间延长而减小。过筛处理使土壤有机碳矿化速率和累积矿化量增加，其中1 mm过筛土壤有机碳矿化增加量大于2 mm过筛土。采用一级动力学模型拟合土壤有机碳矿化过程，发现过筛处理对土壤潜在可矿化碳基本无影响，这与其他研究一致[18, 20]，但显著增加土壤易矿化有机碳，表明过筛处理可能破坏了土壤团聚体结构，释放出被保护的活性有机碳。以上结果很大程度上可由土壤冷水提取碳水化合物的变化进行解释。碳水化合物是土壤团聚结构形成的重要胶结物质[23-24]，同时冷水提取碳水化合物是土壤易矿化有机碳的关键组成部分，过筛处理破坏部分团聚体结构释放出团聚体胶结物质，显著增加土壤冷水提取碳水化合物，从而导致土壤有机碳矿化增加。因此，就小兴安岭森林土壤而言，室内培养模拟野外土壤有机碳矿化时与过1 mm筛和2 mm筛相比，不进行过筛处理或许更接近野外结果，但本研究结果仅限于过1 mm筛和过2 mm筛2个处理，更细的过筛处理后土壤有机碳矿化动态尚属未知，下一步将从团聚体分级方面深入研究土壤各组分有机碳的分解及稳定格局。虽然过筛处理使土壤有机碳矿化增加很大程度上与水提取碳水化合物的增加有关，但由于土壤有机碳矿化过程的复杂性，过筛处理使土壤有机碳矿化增加的更详尽原因还有待进一步探讨。
Effects of sieving process on soil organic carbon mineralization for two forest types in Xiaoxing'an Mountains, Northeast China
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摘要: 采用室内培养法研究了过筛处理对小兴安岭阔叶次生林和原始红松林土壤有机碳(SOC)矿化的影响，测定了土壤有机碳矿化速率和累积矿化量(Cm)，以及培养前后土壤冷水提取碳水化合物(CWEC)和热水提取碳水化合物(HWEC)，利用一级动力学模型拟合土壤有机碳矿化参数：潜在可矿化碳(C0)、易矿化有机碳(C1)等，并分析了土壤Cm与冷水提取碳水化合物和热水提取碳水化合物的关系。结果表明：阔叶次生林土壤有机碳矿化速率和Cm均大于原始红松林。过筛处理使2种森林类型土壤有机碳矿化速率和累积矿化量增加，其中1 mm过筛土壤有机碳矿化增加量大于2 mm过筛土。过筛处理对2种森林类型土壤有机碳矿化速率的影响随着培养时间延长而减小。过筛处理对土壤C0无影响，却使土壤C1增加，其中2 mm过筛土C1增加49.09%~68.06%，1 mm过筛土C1增加91.03%~133.83%。过筛处理使土壤CWEC增加，但对HWEC无影响。土壤Cm与CWEC和HWEC的初始含量及变化量均呈极显著正相关，表明水提取碳水化合物是土壤有机碳矿化的关键组成部分，碳水化合物的损耗可以在很大程度上解释土壤矿化释放的CO2。综上，过筛处理破坏土壤结构，释放出部分胶结团聚体的碳水化合物，增加土壤有机碳矿化。Abstract: We explored the effects of sieving process on soil organic carbon (SOC) mineralization in broad-leaved secondary forest and virgin Korean pine forest in the Xiaoxing'an Mountains by using incubation method. The SOC mineralization rate, cumulative SOC mineralization (Cm), and the content of cool water extractable carbohydrate (CWEC) and hot water extractable carbohydrate (HWEC) before and after incubation were measured; the simultaneous reaction model was employed to estimate SOC mineralization parameters including soil easily mineralizable C (C1) and potentially mineralizable C (C0); the correlations between Cm, CWEC and HWEC were also analyzed. Results showed that both the mineralization rate and Cm of SOC in the broadleaved secondary forest were greater than the ones in the virgin Korean pine forest. Both the mineralization rate and Cm of SOC in two forests were increased by sieving process, and Cm in the soil sieved to 1 mm was increased more than that in the soil sieved to 2 mm. The sieving process had a decreasing impact on the mineralization rate of SOC in the two forest types as the incubation time increased, while it had little impact on C0 but did increase C1 by 49.09%-68.06% in 2 mm sieved soil and 91.03%-133.83% in 1 mm sieved soil. The sieving process increased the CWEC, but had no effect on the HWEC. Significantly positive correlations had been observed between the Cm and both the initial and changed contents of CWEC and HWEC, indicating that water extractable carbohydrate was the key factor for the mineralization of the organic carbon in soil, and that the loss of carbohydrates could largely explain the CO2 released during the soil organic carbon mineralization. In conclusion, the sieving process could destroy the soil structure, release some carbohydrates from soil aggregates, and increase the mineralization level of the organic carbon in soil.
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Key words:
- forest soil /
- organic carbon /
- mineralization /
- carbohydrate /
- sieving
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图 1 过筛处理下2种森林类型土壤有机碳矿化速率
A.阔叶次生林0 ~ 5 cm土层; B.阔叶次生林5 ~ 10 cm土层; C.原始红松林0 ~ 5 cm土层; D.原始红松林5 ~ 10 cm土层。
Figure 1. Mineralization rates of SOC in two forest types under different sample sieving methods
A, 0-5 cm soil depth for broadleaved secondary forest; B, 5-10 cm soil depth for broadleaved secondary forest; C, 0-5 cm soil depth for virgin Korean pine forest; D. 5-10 cm soil depth for virgin Korean pine forest.
图 2 不同过筛处理下2种森林类型土壤有机碳累积矿化量
A.阔叶次生林; B.原始红松林。不同小写字母表示相同土层不同过筛处理间差异显著, 不同大写字母表示相同处理不同土层间差异显著(P<0.05)。下同。
Figure 2. Cumulative SOC mineralization amount in two forest types under different sample sieving methods
A, broadleaved secondary forest; B. virgin Korean pine forest. Different lower-case letters indicate significant differences (P<0.05) among different sieving methods at the same soil layer, different upper-case letters indicate significant differences (P<0.05) among different soil layers with the same sieving method. The same below.
图 3 样品处理方法对土壤冷水提取碳水化合物的影响
A.阔叶次生林培养前; B.阔叶次生林培养后; C.原始红松林培养前; D.原始红松林培养后。
Figure 3. Effects of sample processing methods on soil extractable carbohydrate by cool water
A, broadleaved secondary forest before incubation; B, broadleaved secondary forest after incubation; C, virgin Korean pine forest before incubation; D, virgin Korean pine forest after incubation.
图 4 过筛处理对土壤热水提取碳水化合物的影响
A.阔叶次生林培养前; B.阔叶次生林培养后; C.原始红松林培养前; D.原始红松林培养后。
Figure 4. Effects of sieving methods on soil extractable carbohydrate by hot water
A, broadleaved secondary forest before incubation; B, broadleaved secondary forest after incubation; C, virgin Korean pine forest before incubation; D, virgin Korean pine forest after incubation.
表 1 土壤基本性质
Table 1. Basic properties of sampled soil
森林类型
Forest type土层Soil
depth/cm含水量
Soil moisture/%pH 土壤有机碳
Soil organic carbon (SOC)/(g·kg-1)土壤全氮
Soil total nitrogen/(g·kg-1)C/N 阔叶次生林
Broadleaved secondary forest0~5 50.55 5.71 142.49 9.21 15.47 5~10 39.33 5.82 47.44 3.84 12.35 原始红松林
Virgin Korean pine forest0~5 47.00 5.45 117.49 5.99 19.62 5~10 34.67 5.68 37.56 2.33 16.09 
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表 2 2种森林类型土壤有机碳矿化参数
Table 2. Estimated parameters according to the first order knitics model for soil C mineralization
森林类型
Forest type土层深度
Soil depth/cm处理方式
Processing methods潜在可矿化碳
C0/(mg·kg-1)易矿化碳含量
Easily mineralizable C (C1)/(mg·kg-1)矿化速率常数
Constant of mineralization rate K/d-1C0/SOC/
%R2 阔叶次生林
Broadleaved secondaryforest0~5 对照Control 3 405.81±200.23a 62.62±11.38a 0.026 9a 3.39 0.999 9 2 mm筛2 mm Sieve 3 885.66±99.23a 93.36±15.33b 0.028 2a 2.86 0.999 9 1 mm筛1 mm Sieve 4 040.65±211.80a 145.53±9.81c 0.032 1a 2.85 0.999 6 5~10 对照Control 1 167.04±139.39a 16.97±5.00a 0.021 5a 3.24 0.999 9 2 mm筛2 mm Sieve 1 266.58±98.53a 27.08±7.06b 0.023 9a 2.64 0.999 7 1 mm筛1 mm Sieve 1 305.20±151.45a 35.54±8.18c 0.027 5a 2.35 0.999 4 原始红松林Virgin
Korean pine forest0~5 对照Control 2 646.98±181.30a 47.94±7.70a 0.021 9a 2.10 0.999 7 2 mm筛2 mm Sieve 2 694.56±100.25a 80.57±9.99b 0.026 5a 2.08 0.999 1 1 mm筛1 mm Sieve 2 951.80±99.69a 112.10±15.58c 0.029 8a 1.92 0.998 6 5~10 对照Control 968.24±20.25a 16.50±3.21a 0.022 0a 2.59 0.999 9 2 mm筛2 mm Sieve 944.03±31.52a 25.70±4.03b 0.028 6a 2.09 0.999 5 1 mm筛1 mm Sieve 953.64±29.63a 31.52±6.13c 0.031 7a 1.54 0.999 5 注:不同小写字母表示相同土层不同过筛处理间差异显著(p＜0.05)。Note: different lowercase letters indicate significant differences (P＜0.05) among different sieving methods at the same soil layer.
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表 3 土壤有机碳累积矿化量与水浸提碳水化合物的Pearson相关系数
Table 3. Pearson correlation coefficients between SOC cumulative mineralization amount and water extractable carbohydrate
冷水提取碳水化合物
Cool water extractable carbohydrate(CWEC)热水提取碳水化合物
Hot water extractable carbohydrate(HWEC)初始含量
Initial content结束含量
Final content变化量
Change of content初始含量
Initial content结束含量
Final content变化量
Change of content对照CK 0.883** 0.300 0.775** 0.938** 0.906** 0.889** 2 mm过筛土Soil sieved to 2 mm 0.906** 0.837 0.624** 0.954** 0.933** 0.889* 1 mm过筛土Soil sieved to 1 mm 0.877** 0.490 0.854** 0.922** 0.860** 0.894** 注Notes:*P＜0.05, **P＜0.01.
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