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林业科学 ›› 2020, Vol. 56 ›› Issue (10): 11-25.doi: 10.11707/j.1001-7488.20201002

• 论文与研究报告 • 上一篇    下一篇

黑龙江帽儿山温带森林类型土壤非生长季温室气体排放特征

刘辉1,2,牟长城1,*,吴彬1,张悦1,井立杰1   

  1. 1. 东北林业大学生态研究中心 哈尔滨 150040
    2. 国家林业和草原局大兴安岭调查规划设计院 加格达奇 165100
  • 收稿日期:2019-02-06 出版日期:2020-10-25 发布日期:2020-10-20
  • 通讯作者: 牟长城
  • 基金资助:
    国家重点研发计划项目(2017YFC0504102)

Characterization of Greenhouse Gas Emissions from the Soil of Temperate Forest Types During Non-Growing Season in Maoer Mountain, Heilongjiang

Hui Liu1,2,Changcheng Mu1,*,Bin Wu1,Yue Zhang1,Lijie Jing1   

  1. 1. Center for Ecological Research, Northeast Forestry University Harbin 150040
    2. Daxinganling Survey, Planning and Design Institute of National Forestry and Grassland Administration Jiagedaqi 165100
  • Received:2019-02-06 Online:2020-10-25 Published:2020-10-20
  • Contact: Changcheng Mu

摘要:

目的: 探讨东北温带8种森林类型非生长季土壤温室气体通量、非生长季土壤温室气体排放的年贡献率及增温潜势的规律,以期揭示森林类型变化对土壤非生长季温室气体排放的影响。方法: 采用静态暗箱-气相色谱方法,测定温带帽儿山2种人工林(红松人工林与兴安落叶松人工林,林龄均51年)、5种天然次生林(硬阔林、白桦林、山杨林、杂木林和蒙古栎林,林龄均为61~67年)和原始针阔混交林(林龄150年)非生长季土壤CO2、CH4和N2O通量及相关环境因子(0~40 cm土层土壤含水率、pH值、有机碳含量和有效氮含量,5 cm深处土壤温度T5及积雪厚度),采用单因素和Duncan法进行方差分析和多重比较(α=0.05),利用多元逐步回归从各月平均气体通量的可能影响因子(0~40 cm土层土壤含水率、pH值、有机碳含量和有效氮含量,5 cm深处土壤温度T5及积雪厚度)中筛选主要影响因子。结果: 帽儿山8种温带林型的非生长季土壤CO2通量(15.97~57.86 mg·m-2h-1)表现为2种人工林和4种次生林(蒙古栎林除外)显著高于原始林107.5%~147.1%和135.3%~262.3%(P < 0.05);非生长季CH4通量(-69.74~-9.13 μg·m-2h-1)表现为3种次生林(硬阔林、山杨林和杂木林)显著高于原始林152.8%~174.6%(P < 0.05),2种人工林却低于原始林52.0%~64.1%(P > 0.05);非生长季N2O通量(7.68~40.55 μg·m-2h-1)表现为2种人工林和3种次生林(硬阔林、山杨林和杂木林)显著高于原始林114.2%~286.6%和116.3%~192.0%(P < 0.05);非生长季土壤CO2排放通量表现为原始林主要受T5及0~40 cm土层土壤pH值、含水率及硝态氮含量影响,人工林主要受T5和积雪厚度影响,次生林主要受T5和0~40 cm土层土壤铵态氮含量影响;CH4吸收表现为原始林仅受T5影响,人工林受积雪厚度影响,次生林受T5和0~40 cm土层土壤铵态氮含量影响;N2O排放表现为原始林仅受积雪厚度影响,人工林与次生林主要受积雪厚度及0~40 cm土层土壤铵态氮含量和含水率影响;与原始林相比,人工林和次生林使非生长季土壤CH4吸收的年贡献率(12.3%~30.2%)减少2.8%~10.0%(山杨林除外),而使CO2和N2O排放的年贡献率(4.8%~12.5%和7.0%~63.6%)增加了3.1%~7.7%或3.0%~56.6%;与原始林相比,人工林和次生林使非生长季土壤温室气体增温潜势(71.16~250.64 g CO2·m-2)显著提高130%~190%和120%~250%(P < 0.05)。结论: 温带原始红松林被皆伐后形成的人工林和次生林恢复至51~67年时,早期的人为干扰对其非生长季温室气体排放的影响尚未得到彻底消除;人工林和次生林CO2、N2O通量较原始林均显著提高,次生林CH4通量显著提高,人工林却显著降低。

关键词: 温带森林, 人工林和次生林, 非生长季温室气体排放, 主控因素, 增温潜势与年贡献率

Abstract:

Objective: In order to reveal the influence of changes of forest types on greenhouse gases emission from soils, the fluxes of greenhouse gases, the annual contribution rate and the patterns of warming potential were investigated for 8 temperate forest types in the northeast during the non-growing season. Method: With the static chamber-gas chromatography method, CH4, CO2, and N2O fluxes were measured along with the environmental factors (snow cover thickness, 5 cm deep soil temperature T5, 0-40 cm soil water content, organic carbon, available nitrogen, pH) from two 51-year-old plantation (Korean pine plantation HR and larch plantation LR), 5 natural secondary forests with 61 to 67 years old hardwood forest YK, Betula platyphylla forest BH, Populous davidiana forest SY, mixed deciduous forest ZM, Mongolian oak forest MGL, and 150-year-old primary Korean pine and broad-leaved mixed forest YS, One-way variance and Duncan method were used for variance analysis and multiple comparison (α=0.05). Multiple stepwise regression was used to find the main factors affecting the greenhouse gas flux from all environmental factors. Result: The CO2 fluxes were 15.97-57.86 mg·m-2h-1among the 8 temperate forest types during the non-growing season, and those of the 2 plantations and the 4 secondary forests (except for MGL) were significantly higher than those of YS respectively by 107.5%-147.1% and 135.3%-262.3% (P < 0.05); The CH4 absorption values were -69.74--9.13 μg·m-2h-1 among the 8 temperate forest types during the non-growing season, and the values of the 3 secondary forests (YK, SY, ZM) were significantly higher than that of YS by 152.8%-174.6% (P < 0.05), while those of the 2 plantations were significantly lower than that of the YS by 52.0%-64.1% (P > 0.05); The N2O fluxes were 7.68-40.55 μg·m-2h-1 among the 8 temperate forest types during the non-growing season, and the 2 plantations and 3 secondary forests (YK, SY, ZM) were significantly higher than YS by 114.2%-286.6% and 116.3%-192.0% (P < 0.05) respectively; During the non-growing season, soil CO2 emissions from YS were mainly controlled by T5, 0-40 cm soil water content, pH and nitrate nitrogen, while that from the plantations were mainly influenced by T5, and snow cover thickness, and the CO2 emissions from the secondary forests were mainly controlled by T5 and 0-40 cm soil ammonium nitrogen (YK and MGL). CH4 fluxes from YS were impacted only by T5, from the 2 plantations by snow cover thickness, and from the secondary forests by T5 and 0-40 cm soil ammonium nitrogen. N2O fluxes from YS was mainly controlled only by snow cover thickness, while those from the plantations and the secondary forests were generally controlled by 0-40 cm soil ammonium nitrogen, moisture content and snow cover thickness. Compared with YS, the plantations and the natural secondary forests reduced the annual contribution rate of soil CH4 uptake (12.3%-30.2%) by 2.8%-10.0% (except SY) during the non-growing season, and made the annual contribution rates of CO2 and N2O emissions (4.8%-12.5% and 7.0%-63.6%) with an increase by 3.1%-7.7% or 3.0%-56.6%, respectively. The greenhouse gas warming potential (71.16-250.64 g CO2·m-2) of the 2 plantations and the 5 natural secondary forests showed a significant increase of 130%-190% and 120%-250% (P < 0.05) during the non-growing season, compared with YS. Conclusion: Therefore, the effects of early human disturbance on greenhouse gases fluxes during the non-growing season have not been completely eliminated even after 51-67 years of restoration of the plantations and natural secondary forests since the clear-cut of the primary temperate forests of Korean Pine. The CO2 and N2O fluxes of plantations and secondary forests were significantly higher than that of YS. The CH4 flux of secondary forests was significantly increased, while that of plantations was significantly decreased.

Key words: temperate forests, plantation and secondary forests, non-growth greenhouse gas emissions, control factors, global warming potential and annual contribution rate

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