Effect of Rice Straw Addition on CH4 Emission in Black Soil with Different Rice Planting Years
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摘要:目的 评估水稻秸秆添加对东北地区不同种稻年限黑土CH4的排放的影响,以期为黑土水稻田秸秆还田提供理论依据。方法 不同种稻年限(0、12、35、62和85 a)黑土,分别设不添加(CK)和添加1%水稻秸秆(S)处理,进行淹水培养试验(培养温度为20 ℃,淹水层为1 cm),测定土壤CH4排放通量及累积排放量,比较不同种稻年限土壤对水稻秸秆添加响应的差异。结果 在淹水培养期间(150 d),添加水稻秸秆处理各种稻年限土壤CH4排放通量(0.00 ~ 3.33 mg kg−1 d−1)显著(P > 0.05)高于未添加秸秆处理(0.00 ~ 0.13 mg kg−1 d−1),未添加和添加水稻秸秆处理土壤CH4排放主要集中于淹水培养的前80 d和60 d。未添加水稻秸秆处理土壤CH4累积排放量为0.04 ~ 4.45 mg kg−1,不同年限稻田土壤CH4累积排放量差异不显著(P > 0.05)。添加水稻秸秆处理土壤CH4累积排放量为29.64 ~ 91.08 mg kg−1,显著高于未添加水稻秸秆处理(P < 0.05),且12 a和35 a土壤CH4累积排放量显著高于0 a、62 a和85 a(P < 0.05)。未添加和添加水稻秸秆处理土壤CH4累积排放量与土壤有机碳、可溶性有机碳氮和铵态氮含量呈显著正相关(P < 0.01)。添加水稻秸秆处理土壤CH4累积排放量还与土壤β-葡萄糖苷酶活性呈显著负相关(P < 0.05),土壤CH4累积排放量增量也与土壤有机碳含量也呈显著线性正相关(P < 0.01)。水稻秸秆添加后土壤可溶性有机氮含量是影响土壤CH4排放的直接因素,土壤可溶性有机碳和铵态氮含量及β-葡萄糖苷酶活性是影响土壤CH4排放的间接因素。结论 水稻秸秆添加显著促进了黑土不同种稻年限土壤CH4排放,种稻年限越长,水稻秸秆添加后土壤CH4排放量越少。本试验条件下,黑土种稻年限大于35年时,水稻秸秆还田带来的土壤CH4排放量相对较小。Abstract:Objective The effect of rice straw addition on soil CH4 emission in Black soil with different rice planting years in Northeast China needed to be evaluated, which will provide to provide a theoretical basis for the return of rice straw in paddy field of Black soil.Method Flooding incubation experiment in a laboratory for 150 days (at 20 ℃, with 1 cm water-flooded layer) was carried out, and 1% rice straw was added to black soils with different rice planting years (0, 12, 35, 62 and 85 years), and the soil without rice straw addition was used as the control. The CH4 emission flux and cumulative emissions from soil were determined.Result During flooding incubation period (150 days), the soil CH4 emission flux (0.00 - 3.33 mg kg−1 d−1) from the treatments with rice straw was significantly higher than that from the treatments without rice straw (0.00 - 0.13 mg kg−1 d−1). The CH4 emission from the treatments without and with rice straw mainly occurred in the first 80 days and the first 60 days, respectively. The cumulative emissions of soil CH4 from the treatments without rice straw were 0.04 - 4.45 mg kg−1, there was no significant difference in soil CH4 cumulative emissions in different rice planting years (P > 0.05). The cumulative emissions of soil CH4 from the treatments with rice straw were 29.64 - 91.08 mg kg−1, which was significantly higher than that of without rice straw treatments (P < 0.05), and the cumulative emissions of soil CH4 from 12 years and 35 years were significantly higher than that of 0 year, 62 years and 85 years (P < 0.05). The cumulative emissions of CH4 from the treatments without and with rice straw positive correlated significant (P < 0.01) with soil organic carbon (SOC), dissolve organic carbon (DOC), dissolve organic nitrogen(DON)and NH4 + −N. The cumulative emissions of CH4 from the treatments with rice straw negatively correlated significantly (P < 0.05) with β- Glucosidase activity, the cumulative emission increment of CH4 positive correlated significant (P < 0.01) with SOC and DON in the treatments with rice straw addition, which means that the SOC and DON are the main affecting factors for CH4 emission. While the DOC, NH4 + −N and β -glucosidase activities were the indirect factors affecting soil CH4 emission.Conclusion These results suggest that the addition of rice straw significantly promots the CH4 emission in Black Soil with different rice planting years, the longer the years of rice planting, the soil CH4 emission is relatively lower. Therefore, the soil CH4 emission increases from the treatments with rice straw addition is relatively small in more than 35-year rice planting Black soils
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Keywords:
- Rice straw returning /
- Black soil /
- CH4 emission /
- Soil organic carbon /
- Paddy soil
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【研究意义】我国稻田面积约为0.3 × 108 hm2,约占世界稻田土壤面积(1.67 × 108 hm2)的五分之一[1]。CH4是全球变暖的主要温室气体之一,稻田土壤是CH4排放的重要来源[2]。水稻秸秆还田是保持土壤肥力,改善土壤结构,增加土壤有机碳含量的常见农业措施[3]。东北地区黑土开垦种稻是土地利用的重要方式,水稻秸秆还田已成为我国东北黑土地保护的重要措施。因此,开展水稻秸秆还田对黑土稻田土壤CH4排放影响的研究,对于评估东北黑土水稻田秸秆还田的温室效应及水稻秸秆的合理利用具有重要意义。【前人研究进展】大量研究表明,水稻秸秆还田能够促进稻田土壤CH4排放[4-7],CH4排放量受施肥[5]、土壤温度和水分影响[3-4]。Zhu等[5-6]研究发现淹水条件下水稻秸秆添加土壤CH4排放量明显增加,但水稻秸秆还田配施无机肥后可显著降低土壤CH4排放量[5]。Zhang等[4]研究表明水稻秸秆添加土壤在好氧培养期间无CH4产生,但在随后淹水培养2周内,土壤CH4排放速率较快,土壤CH4排放量随前期好氧培养时土壤温度的增加而显著下降。一些研究也证实有氧条件下外源碳的添加和高温对土壤CH4的排放没有显著影响[8-10],但也有研究发现好氧条件下水稻秸秆添加可显著增加土壤CH4排放通量和累积排放量[11]。淹水条件下稻田土壤有机质厌氧分解产生大量的CH4,土壤CH4排放明显增加[12],但在水稻种植过程中,控制灌溉能够有效的减少稻田土壤CH4排放[13-16]。Wu等[17]研究发现水分、秸秆及其交互作用对土壤CH4累积排放量均有显著影响,但秸秆覆盖对土壤CH4排放的影响小于比秸秆混入还田。Wang等[18]研究显示土壤CH4排放量与秸秆施用量呈正相关,秸秆添加后的有效基质增加对CH4排放有促进作用。肖小平等[19]研究发现免耕还田土壤CH4平均排放速率低于较旋耕还田和翻耕还田。土地利用方式对土壤CH4排放有较大影响[20-21],沼泽地改成旱地导致了土壤CH4排放从强源到弱汇的转变[20]。由此可见,秸秆还田后土壤CH4排放量因土壤环境条件、还田用量、还田方式及土地利用方式的不同而异。【本研究切入点】东北黑土有机质含量高,开垦种植水稻不同年限土壤的养分状况及性质产生很大变化[22-23],水稻秸秆添加对黑土不同种稻年限土壤CH4的排放速率及其排放量的影响如何?目前尚不清楚。因此,开展水稻秸秆添加对东北黑土不同种稻年限土壤CH4排放的影响,对于评估水稻秸秆还田对黑土稻田土壤CH4排放和水稻秸秆的合理利用具有重要意义。【拟解决的问题】以东北典型黑土不同种稻年限土壤为研究对象,研究淹水条件下水稻秸秆添加对黑土不同种稻年限土壤CH4排放通量和累积排放量的影响,探讨土壤CH4排放的影响因素,为明确黑土稻田土壤CH4排放效应及水稻秸秆合理利用提供理论依据。
1. 材料与方法
1.1 供试材料
本试验黑土采自黑龙江省绥化市庆安县。庆安县位于黑龙江省中部,小兴安岭南麓向松嫩平原的过渡地带,地理位置为137°30′ ~ 128°35′ E,46°30′ ~ 47°35′ N,气候属寒温带大陆性季风气候,温热湿润,年平均日照时数为2599 h,年平均气温1.69 ℃,无霜期128 d,年平均降水量577 mm,是黑土的典型区域,自然植被以草甸植被为主,土壤由黄土性沉积物发育而成[23]。经过项目组调查,在研究区域选取了以自然草甸植被为主的未开垦黑土(0 a,作为对照土壤)及开垦种稻12、35、62和85 a稻田土壤为研究对象。各年限稻田土壤田块的气候和地形条件几乎一致,均不施有机肥,每年施用化肥量大致相同,但年限之间的化肥种类和使用量存在一定差异,水分管理等措施也大致相同。采样时,分别将对照土壤和各年限稻田土壤作为一个采样单元,每个采样单元选取面积约2 ~ 3亩大致相同的3个子单元,即3次重复。每个子单元“S”型布点、采集5 ~ 8点土样混匀后作为1个土壤样本,采样深度为0 ~ 20 cm。挑出土壤样本可见水稻根系和杂物,自然风干备用。供试土壤的地理坐标及基本性质见表1。供试水稻秸秆的有机碳含量为419.33 g kg–1,全氮含量为9.15 g kg–1,C/N为45.83。
表 1 供试土壤的地理坐标及基本性质Table 1. Geographical information and basic properties of the soil samples年限
Year
(a)地理坐标
Geographic coordinatespH 有机碳
Organic C
(g kg–1)全氮
Total N
(g kg–1)C/N 碱解氮
Alkaline N
(mg kg–1)速效磷
Available P
(mg kg–1)速效钾
Available K
(mg kg–1)0 127.466° E, 47.031° N 5.0 c 38.8 bc 3.8 a 10.2 d 324.2 a 19.3 b 144.7 b 12 127.470° E, 47.026° N 5.6 a 45.7 a 3.7 a 12.5 bc 267.3 b 34.7 ab 150.9 b 35 127.476° E, 47.028° N 5.4 ab 42.5 ab 3.3 a 12.8 a 238.4 c 35.5 ab 144.3 b 62 127.479° E, 47.027° N 5.5 ab 34.7 cd 2.7 b 12.7 ab 218.0 d 34.6 ab 125.6 a 85 127.476° E, 47.033° N 5.4 b 31.1 d 2.5 b 12.4 c 163.6 e 37.3 a 124.4 a 注:不同小写字母表示5个年限间差异显著(P < 0.05)。 1.2 室内培养试验
不同种稻年限土壤(0、12、35、62和85 a)分别设不添加水稻秸秆处理(CK)和添加1%水稻秸秆处理(S),总计10个处理,分别记为CK0、CK12、CK35、CK62、CK85、S0、S12、S35、S62、S85,每处理3个重复。培养试验温度为20 ℃,依据黑龙江绥化市庆安县地区水稻生长季(5 ~ 9月)月平均气温(14.3 ~ 23.9 ℃)设置;水分依据水稻生长季的淹水条件设置约1 cm淹水层。
为了恢复和稳定土壤微生物群落,将事先过5 mm筛的风干土样,加入蒸馏水调至40%土壤充水孔隙含水量(WFPS)[4-5,24],置于25 ℃黑暗培养箱预培养2周。将预培养的供试土壤80 g(以干土计)分别放在专用培养瓶(420 ml)中,再将事先剪成小于6 mm的小段、60 ℃烘干的水稻秸秆按设计的用量添加至培养瓶中(为防止秸秆漂浮,平铺于土层中间),之后向所有密闭培养瓶中加入蒸馏水至约1 cm 淹水层(相同培养瓶中的水量相等)。每一处理共计18个培养瓶,其中3个培养瓶进行密闭,其余15个培养瓶用保鲜膜封口,扎若干数量小孔通气;并将所有培养瓶置于20 ℃恒温培养箱中培养150 d。所有培养瓶中水土比相同,培养条件基本一致。每3 ~ 5 d重量法补充水分,以维持水分平衡。
在培养过程中,密闭培养瓶分别在第7、15、30、45、60、80、100、130和150 d,用60 ml注射器抽取50 ml气体样本放入100 ml 真空袋中,以测定CH4浓度;每次气体采集后分别将未添加和添加处理培养瓶置于试验室无干扰处通气10 min以维持瓶内气体状态,培养过程中水分几乎不损失,不进行补水。其余培养瓶分别在第5、15、30、60和150 d时进行破坏性土壤样本采集,每次采集后土壤含水量自然降到40%WFPS时,鲜土样密封置于4 ℃冰箱保存,用于测定土壤可溶性有机碳氮、铵态氮含量和β-葡萄糖苷酶。
1.3 测定方法
气体样品中CH4浓度用 Agilent 7890B 气相色谱仪进行分析,分析柱为 Porpak. Q 填充柱,柱箱温度为 60 ℃,所用载气为高纯度N2,CH4的测定采用氢气检测器(FID),工作温度为250 ℃,使用气相色谱仪时均用国家标准计量中心的标准气体进行标定。
土壤有机碳(SOC)、全氮(N)采用元素分析仪(Elementar Vario EL Ⅲ,德国)测定;可溶性有机碳(DOC)、可溶性有机氮(DON)采用0.5 mol L–1K2SO4溶液浸提(液土比5∶1),浸提液中有机碳含量采用重铬酸钾容量法测定,浸提液中总氮含量采用3%碱性过硫钾氧化—AA3流动分析仪(Bran + Luebbe,德国)测定,浸提液中铵态氮(NH4 + -N)采用AA3流动分析仪测定,总氮与铵态氮的差值即为DON;β-葡萄糖苷酶采用酶联免疫分析(ELISA)试剂盒测定;其它指标均采用常规方法测定。
1.4 数据计算
土壤CH4排放通量(
$ {F}_{i} $ ,mg kg–1 d–1)和累积排放量(F,mg kg–1)[5,25]:$$ {F}_{i}=\frac{{C}_{i}\times ({V}_{1} + \alpha \times {V}_{2})\times M\times \dfrac{273}{273 + t}}{22.4\times m\times d} $$ (1) $$ F={\sum} _{i=1}^{n}{F}_{i}\times d $$ (2) 式中,Ci为第 i 次取样时各处理排放的CH4-C浓度(ppm);t 为 CH4测定时的温度(25 ℃),V1 为培养瓶实际填充气体的体积(m3);V2 为培养瓶中水分的体积(m3);α 为根据亨利定律所计算的CH4在水中的溶解度,为0.0329[25];M 为C的摩尔质量,为12 g mol–1,m 为供试土壤干土质量(kg),di 为第i次取样时段的培养天数(d),n 为取样次数。
1.5 统计分析
采用 WPS Office 11.1.0.10495-release进行数据整理,采用 Origin 2017软件进行绘图,运用SPSS Statistics 22 软件进行统计分析。试验数据处理间差异显著性采用双因素方差分析进行检验,用邓肯法进行多重比较(P < 0.05)。
2. 结果与分析
2.1 土壤CH4排放通量和累积排放量
未添加和添加水稻秸秆处理土壤CH4排放主要集中在淹水培养80 d内,而后变化较为平缓;在培养期间,添加水稻秸秆处理土壤CH4-C排放通量(0.00 ~ 3.331 mg kg–1 d–1)高于未添加秸秆处理土壤(0.00 ~ 0.13 mg kg–1 d–1)(图1a和图1b)。在整个培养期,未添加水稻秸秆处理,土壤CH4累积排放量约在80 d时趋于稳定,而添加水稻秸秆处理土壤CH4累积排放量约在60 d时趋于稳定(图1c和图1d),表明水稻秸秆添加土壤CH4排放的时间相对缩短;添加水稻秸秆处理,在培养45 d 时,各年限稻田土壤CH4累积排放量均高于对照土壤,而在培养60 d 后,种稻62 和85 a土壤CH4累积排放量要低于对照土壤,但种稻12和35 a土壤CH4累积排放量仍高于对照土壤(图1d)。总体上,添加水稻秸秆和种稻年限以及二者的交互作用对土壤CH4累积排放量均有显著影响(表2)。
表 2 土壤CH4累积排放量的双因素方差分析结果(P值)Table 2. Results of two factor analysis of variance of soil CH4 cumulative emissions (P value)因素
Factor培养时间 (d)
Incubation time7 15 30 45 60 80 100 130 150 秸秆 < 0.01 < 0.01 < 0.01 < 0.01 < 0.01 < 0.01 < 0.01 < 0.01 < 0.01 年限 < 0.01 < 0.01 > 0.05 < 0.01 < 0.01 < 0.01 < 0.01 < 0.01 < 0.01 秸秆 × 年限 < 0.01 > 0.05 > 0.05 < 0.01 < 0.01 < 0.01 < 0.01 < 0.01 < 0.01 在淹水培养结束(150 d)时,未添加水稻秸秆处理土壤CH4-C累积排放量为0.04 ~ 4.54 mg kg–1,各年限之间土壤CH4累积排放量无显著差异(P > 0.05);添加水稻秸秆处理土壤CH4-C累积排放量为29.64 ~ 1.08 mg kg–1,均显著高于未添加秸秆处理(P < 0.05)(图2),各年限土壤CH4-C排放量增加29.18 ~ 86.87 mg kg–1,12 a(S12)、35 a(S35)土壤CH4排放量及其增量均显著高于对照土壤(S0)、62 (S62)和85 a(S85)(P < 0.05)。进一步分析发现,在淹水培养150 d,未添加和添加水稻秸秆处理土壤CH4累积排放量、添加水稻秸秆处理土壤CH4累积排放量增量与培养前土壤有机碳含量均呈显著线性正相关(图3)。
2.2 土壤可溶有机碳氮和铵态氮含量及β-葡萄糖苷酶活性
淹水培养过程中,未添加和添加水稻秸秆处理土壤DOC和NH4 + -N含量均随着培养时间延长呈先上升后下降的趋势,土壤DON含量随着培养时间的延长呈下降趋势,但三者含量均在30 ~ 60 d期间较高(图4)。未添加和添加水稻秸秆处理土壤DOC、DON和NH4 + -N的平均含量均随种稻年限增加呈先增加后降低趋势。与未添加水稻秸秆处理相比,添加水稻秸秆后S0、S12、S35、S62和S85处理土壤DOC平均含量分别增加了610.99、168.15、158.28、−27.74和12.62 mg kg–1,DON平均含量分别增加了71.73、−84.73、82.6、2.24和32.69 mg kg–1,NH4 + -N平均含量分别增加了72.98 、23.45、90.93、19.84和8.36 mg kg–1。秸秆添加和种稻年限及二者的交互作用对土壤DOC、DON和NH4 + -N含量均有显著影响(表3)。相关分析发现,未添加水稻秸秆土壤DOC、DON和NH4 + -N含量与土壤有机碳含量均呈显著正相关(P < 0.01),相关系数分别为0.696、0.771和0.805;添加水稻秸秆后土壤DOC、DON和NH4 + -N含量与土壤有机碳含量也均呈显著正相关(P < 0.01),相关系数分别为0.822、0.847和0.798。
表 3 土壤可溶有机碳氮和铵态氮含量及β-葡萄糖苷酶活性的双因素方差分析的结果(P值)Table 3. Results of two-way ANOVA of DOC, DON, NH4 + -N and β-glucosidase activity (P value)因素
FactorDOC DON NH4 + -N β-glucosidase 秸秆 < 0.01 < 0.01 < 0.01 > 0.05 年限 < 0.01 < 0.01 < 0.01 < 0.05 秸秆 × 年限 < 0.01 < 0.01 < 0.05 < 0.01 注:DOC:可溶性有机碳,DON:可溶性有机氮,NH4 + -N:铵态氮,β-glucosidase:β-葡萄糖甘酶。 淹水培养过程中,未添加和添加水稻秸秆处理土壤β-葡萄糖苷酶活性均随着培养时间延长呈先上升后下降的趋势,在15 ~ 60 d期间含量较高,60 d之后处于稳定的趋势;添加水稻秸秆处理土壤β-葡萄糖甘酶活性在培养前期略有所下降,但各年限土壤之间的数值相接近(图5)。种稻年限及添加秸秆与种稻年限的交互作用对β-葡萄糖甘酶活性均影响显著(表3)。
2.3 土壤CH4排放的影响因素分析
培养结束时,未添加和添加水稻秸秆处理土壤DOC、DON和NH4 + -N含量与土壤CH4排放量之间具有显著正相关;添加水稻秸秆处理土壤β-葡萄糖苷酶活性与土壤CH4排放量之间则具有显著负相关(表4)。
表 4 土壤可溶性有机碳氮和铵态氮含量、β-葡萄糖苷酶活性与土壤CH4累积排放量相关性分析Table 4. Correlation analysis between the soil CH4 cumulative emissions and DOC, DON, NH4 + -N and β-glucosidase activity处理
Treatment指标
IndexDOC DON NH4 + −N β-glucosidase CH4累积排放量
CH4 cumulative emissionsCK DOC 1 0.903** 0.924** 0.400 0.719** DON 1 0.927** 0.237 0.896** NH4 + -N 1 0.184 0.710** β-glucosidase 1 0.271 S DOC 1 0.772** 0.769** −0.206 0.677** DON 1 0.976** −0.453 0.884** NH4 + -N 1 −0.532* 0.868** β-glucosidase 1 −0.517* 注: DOC:可溶性有机碳,DON:可溶性有机氮,NH4 + −N:铵态氮,β-glucosidase:β-葡萄糖甘酶。*,**分别表示0.05,0.01显著水平。 由于未添加秸秆处理土壤DOC、DON和NH4 + -N含量之间具有自相关,添加秸秆处理土壤DOC、DON、NH4 + -N含量和β-葡萄糖苷酶活性之间也具有自相关,进一步通过多元回归分析和通径分析发现,未添加秸秆土壤DON对土壤CH4排放的直接通径系数最大且为正值(1.724),DOC对土壤CH4排放直接通径系数次之,为负值(−0.769),DOC和NH4 + -N通过DON对土壤CH4排放的间接通径系数均很大,分别为1.557和1.598;添加秸秆土壤DON对土壤CH4排放的直接通径系数也最大且为正值(0.996),DOC和NH4 + -N通过DON对土壤CH4排放的间接通径系数均很大,分别为0.769和0.972;但β-葡萄糖苷酶活性通过DON对土壤CH4排放的间接通径系数却为负值(−0.451)。由此可见,添加秸秆土壤DON含量是影响土壤CH4排放的直接因素,DOC、NH4 + -N和β-葡萄糖苷酶活性是影响土壤CH4排放的间接因素。
3. 讨论
稻田土壤CH4排放受生物因素和非生物因素的综合影响[26]。水稻秸秆添加对土壤环境的影响很大,不仅提高了土壤有机质含量,而且也向土壤中提供了氮和钾等矿质元素[27],同时也能够增加土壤微生物数量和土壤酶活性[28-29]。土壤可溶性有机碳和可溶性氮是微生物生长和代谢所需的重要碳、氮源[30],也是产甲烷菌生长的重要底物[31]。本研究中,无论是否添加水稻秸秆,土壤DOC、DON和NH4 + -N含量均与土壤有机碳含量呈显著正相关(P < 0.01),这表明不同种稻年限土壤有机碳含量显著差异(表1),是影响土壤可溶性有机碳和可溶性氮含量的重要因素。秸秆添加和种稻年限及二者的交互作用对土壤DOC、DON和NH4 + -N含量(表3),进而显著影响CH4排放量(表4)。水稻秸秆添加显著促进了土壤CH4排放(图2),CH4排放量增量则与土壤有机碳含量呈显著正相关(图3)。本研究中添加水稻秸秆土壤中可溶性有机碳与有机氮的比值有所下降,可溶性有机氮含量是影响土壤CH4排放的直接因素(表5)。这说明秸秆分解会产生不稳定化合物且易于矿化分解,这会为土壤微生物提供充足的碳源和氮源,也会为产甲烷菌提供了充足的底物,促进产甲烷菌的生长[32],进而促进了含碳有机物质向CH4转化[33]。
表 5 土壤CH4累积排放量的影响因素的通径分析Table 5. Path analysis of influencing factors for CH4 cumulative emissions处理
Treatment指标
Index直接通径系数
Direct path coefficient间接通径系数
Indirect path coefficientDOC DON NH4 + −N β-glucosidase CK DOC −0.128 1.557 −0.710 DON 1.724 −0.116 −0.713 NH4 + -N −0.769 −0.118 1.598 S DOC 0.065 0.769 −0.195 0.039 DON 0.996 0.050 −0.247 0.085 NH4 + -N −0.254 0.050 0.972 0.100 β-glucosidase −0.188 −0.013 −0.451 0.135 注: DOC:可溶性有机碳,DON:可溶性有机氮,NH4 + -N:铵态氮,β-glucosidase:β-葡萄糖甘酶。 土壤β-葡萄糖苷酶能够催化水解芳基或烃基与糖基原子团之间的糖苷键生成葡萄糖,因此β-葡萄糖苷酶可以作为土壤微生物能量碳需求的指示物[34]。本研究中,添加水稻秸秆土壤β-葡萄糖苷酶活性受种植年限及添加秸秆和种稻年限交互作用的影响显著(图5),添加水稻秸秆土壤CH4排放量与β-葡萄糖苷酶活性呈显著负相关(表4),说明添加水稻秸秆和不同种稻年限土壤的理化性质共同影响着土壤β-葡萄糖苷酶活性。土壤β-葡萄糖苷酶活性高低会影响有机质分解,进而影响土壤CH4排放,这一结果与袁武等[35]的研究结果相一致。稻田土壤中不同机制控制着碳循环相关的胞外酶活性和CH4排放[35],外源水稻秸秆输入在为微生物提供新鲜底物的同时,也促进了土壤中老化腐殖质对胞外酶的吸附,这种被老化腐殖质吸附结合的胞外酶仍具有一定的活性,并且具有较强的纤维素抗分解能力[36]。此外,较高的碳循环相关的胞外酶活性能够提高土壤微生物碳利用率,促进土壤有机碳积累或固定[37-38],进而减少CH4排放。
淹水条件下在培养初期好氧微生物的活性较强,易矿化有机质分解会消耗大量的O2,从而增加土壤中的厌氧条件[39],而兼性厌氧细菌和厌氧菌更适应在培养后期生长,为产甲烷菌提供了适宜的环境[40]。土壤CH4产生是厌氧微生物分解有机质的最后步骤,土壤淹水后电子受体如NO3−、Mn4 + 、Fe3 + 和SO42−依次还原,无机电子受体耗尽,随后CH4大量产生,进而使CH4排放产生了滞后[41]。本研究显示,未添加水稻秸秆土壤在淹水条件下培养15 d 时才表现出较高CH4排放通量,而添加水稻秸秆后土壤CH4排放通量峰值出现的时间早,种稻年限越长其峰值出现的时间越早,土壤CH4排放趋于稳定的时间也相对短(图1)。这说明水稻秸秆添加后土壤中新鲜的碳基质增加,微生物更喜欢新鲜的碳基质[5],进而减弱了CH4排放的滞后性,当微生物将新鲜的碳基质耗尽后,CH4排放量降低,这一研究结果与大多数研究结果相同[4-6]。
4. 结论
淹水培养条件下水稻秸秆添加可显著促进不同种稻年限黑土CH4排放通量和累积排放量。添加水稻秸秆后土壤可溶性有机氮含量是影响CH4排放的直接因素,而土壤可溶有机碳、铵态氮含量及其β-葡萄糖苷酶活性是影响土壤CH4排放量的间接因素。添加水稻秸秆后不同种稻年限CH4累积排放量与其有机碳含量密切关系,黑土种稻年限大于35年时,土壤有机碳含量下降,水稻秸秆添加后土壤CH4累积排放量相对较少。
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表 1 供试土壤的地理坐标及基本性质
Table 1 Geographical information and basic properties of the soil samples
年限
Year
(a)地理坐标
Geographic coordinatespH 有机碳
Organic C
(g kg–1)全氮
Total N
(g kg–1)C/N 碱解氮
Alkaline N
(mg kg–1)速效磷
Available P
(mg kg–1)速效钾
Available K
(mg kg–1)0 127.466° E, 47.031° N 5.0 c 38.8 bc 3.8 a 10.2 d 324.2 a 19.3 b 144.7 b 12 127.470° E, 47.026° N 5.6 a 45.7 a 3.7 a 12.5 bc 267.3 b 34.7 ab 150.9 b 35 127.476° E, 47.028° N 5.4 ab 42.5 ab 3.3 a 12.8 a 238.4 c 35.5 ab 144.3 b 62 127.479° E, 47.027° N 5.5 ab 34.7 cd 2.7 b 12.7 ab 218.0 d 34.6 ab 125.6 a 85 127.476° E, 47.033° N 5.4 b 31.1 d 2.5 b 12.4 c 163.6 e 37.3 a 124.4 a 注:不同小写字母表示5个年限间差异显著(P < 0.05)。 表 2 土壤CH4累积排放量的双因素方差分析结果(P值)
Table 2 Results of two factor analysis of variance of soil CH4 cumulative emissions (P value)
因素
Factor培养时间 (d)
Incubation time7 15 30 45 60 80 100 130 150 秸秆 < 0.01 < 0.01 < 0.01 < 0.01 < 0.01 < 0.01 < 0.01 < 0.01 < 0.01 年限 < 0.01 < 0.01 > 0.05 < 0.01 < 0.01 < 0.01 < 0.01 < 0.01 < 0.01 秸秆 × 年限 < 0.01 > 0.05 > 0.05 < 0.01 < 0.01 < 0.01 < 0.01 < 0.01 < 0.01 表 3 土壤可溶有机碳氮和铵态氮含量及β-葡萄糖苷酶活性的双因素方差分析的结果(P值)
Table 3 Results of two-way ANOVA of DOC, DON, NH4 + -N and β-glucosidase activity (P value)
因素
FactorDOC DON NH4 + -N β-glucosidase 秸秆 < 0.01 < 0.01 < 0.01 > 0.05 年限 < 0.01 < 0.01 < 0.01 < 0.05 秸秆 × 年限 < 0.01 < 0.01 < 0.05 < 0.01 注:DOC:可溶性有机碳,DON:可溶性有机氮,NH4 + -N:铵态氮,β-glucosidase:β-葡萄糖甘酶。 表 4 土壤可溶性有机碳氮和铵态氮含量、β-葡萄糖苷酶活性与土壤CH4累积排放量相关性分析
Table 4 Correlation analysis between the soil CH4 cumulative emissions and DOC, DON, NH4 + -N and β-glucosidase activity
处理
Treatment指标
IndexDOC DON NH4 + −N β-glucosidase CH4累积排放量
CH4 cumulative emissionsCK DOC 1 0.903** 0.924** 0.400 0.719** DON 1 0.927** 0.237 0.896** NH4 + -N 1 0.184 0.710** β-glucosidase 1 0.271 S DOC 1 0.772** 0.769** −0.206 0.677** DON 1 0.976** −0.453 0.884** NH4 + -N 1 −0.532* 0.868** β-glucosidase 1 −0.517* 注: DOC:可溶性有机碳,DON:可溶性有机氮,NH4 + −N:铵态氮,β-glucosidase:β-葡萄糖甘酶。*,**分别表示0.05,0.01显著水平。 表 5 土壤CH4累积排放量的影响因素的通径分析
Table 5 Path analysis of influencing factors for CH4 cumulative emissions
处理
Treatment指标
Index直接通径系数
Direct path coefficient间接通径系数
Indirect path coefficientDOC DON NH4 + −N β-glucosidase CK DOC −0.128 1.557 −0.710 DON 1.724 −0.116 −0.713 NH4 + -N −0.769 −0.118 1.598 S DOC 0.065 0.769 −0.195 0.039 DON 0.996 0.050 −0.247 0.085 NH4 + -N −0.254 0.050 0.972 0.100 β-glucosidase −0.188 −0.013 −0.451 0.135 注: DOC:可溶性有机碳,DON:可溶性有机氮,NH4 + -N:铵态氮,β-glucosidase:β-葡萄糖甘酶。 -
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