油松人工林土壤N2O排放通量的昼夜变化规律及其影响因子

doi:10.13466/j.cnki.lyzygl.2023.02.012

摘要/Abstract

摘要：

在全球气候变暖的背景下,揭示大青山油松人工林全年土壤N₂O排放通量的昼夜变化规律,基于土壤N₂O排放通量观测的日动态数据,确定最佳的日采样时段,为精确评估区域土壤N₂O排放通量提供基础数据。采用静态箱-气相色谱(GC)法,对大青山油松人工林2020—2021年生长季和冻融期土壤的N₂O排放通量进行野外原位观测。结果表明:1)生长季(2020年6—9月),观测日土壤N₂O排放通量平均值都出现在当日的15:00—17:00时段内;冻融期(2020年11月至翌年3月),观测日8:00—12:00时段的观测值接近土壤N₂O排放通量的日平均值。2)2021年,观测日土壤N₂O排放通量平均值出现在7月当日的7:00—9:00时段内及6—9月当日的15:00—17:00时段内。根据研究结果确定了大青山地区油松人工林土壤N₂O排放通量的最佳取样时间为生长季的上午9:00或下午15:00,冻融期的上午8:00,获得的通量值经过矫正后可代表当日土壤N₂O平均排放通量;根据生长季和冻融期温度与土壤N₂O排放通量效应值的分析结果,确定温度为影响大青山地区油松人工林土壤N₂O排放通量的重要因素。

关键词: 油松人工林, N₂O排放通量, 温度, 昼夜变化, 月变化

Abstract:

In the context of global warming,the diurnal variation of annual soil N₂O emission flux in Pinus tabulaeformis plantation was revealed,and the optimal daily sampling period was determined based on the daily dynamic data of N₂O emission flux observation,which provided basic data for accurate assessment of regional soil N₂O flux.The N₂O emission fluxes in the growing season and freezing-thawing period of Pinus tabulaeformis plantation in 2020—2021 were measured by static box gas chromatography (GC).The results showed as follows:1) During the growing season (June-September 2020),the average N₂O emission flux of the observation days all appeared during 15:00—17:00 of the same day;During freeze-thaw period (November 2020 to March next year),the observed values from 8:00 to 12:00 on the observation day were close to the daily mean value of N₂O flux.2) In 2021,the average N₂O emission flux of observation days appeared in the period of 7:00—9:00 on July days and 15:00—17:00from June days to September days.According to the results,the best sampling time of N₂O in Pinus tabulaeformis plantation in Daqing Mountain was 9:00 AM or 15:00 PM in the growing season and 8:00 am in the freezing-thawing period.The obtained flux value could represent the average N₂O flux of the day after correction.According to the analysis results,temperature in the growing season and the freeze-thaw period and the N₂O emission flux effect value,it can be determined that temperature is an important factor for the N₂O emission of Pinus tabulaeformis plantation in Daqing Mountain.

Key words: Pinus tabulaeformis plantation, N₂O emission flux, soil temperature, diurnal variation, monthly variation

中图分类号:

李枭阳, 马秀枝, 杨玉培, 李长生. 油松人工林土壤N₂O排放通量的昼夜变化规律及其影响因子[J]. 林业资源管理, 2023,(2): 88-95.

LI Xiaoyang, MA Xiuzhi, YANG Yupei, LI Changsheng. Diurnal Variation of Soil N₂O Emission Fluxes and Its Influencing Factors in Pinus tabulaeformis Plantation[J]. FOREST RESOURCES WANAGEMENT, 2023,(2): 88-95.

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参考文献 29

[1]	Houghton J T, Callander B A, Varney S K. The Supplementary Report to the IPCC Scientific Assessment[J]. Climate Change, 1992, 58(10):1189-1194.
[2]	周波涛. 全球气候变暖:浅谈从AR5到AR6的认知进展[J]. 大气科学学报, 2021, 44(5):667-671.
[3]	樊星, 秦圆圆, 高翔. IPCC第六次评估报告第一工作组报告主要结论解读及建议[J]. 环境保护, 2021, 49(Z 2):44-48.
[4]	Yong S K, Makoto K, Takakai F, et al. Greenhouse gas emissions after a prescribed fire in white birch-dwarf bamboo stands in northern Japan,focusing on the role of charcoal[J]. European Journal of Forest Research, 2011, 130(6):1031-1044. doi: 10.1007/s10342-011-0490-8
[5]	Ravishankara A R, Daniel J S, Portmann R W. Nitrous oxide(N₂O):The dominant ozone-depleting substance emitted in the 21st century[J]. Science, 2009, 326(5949):123-125. doi: 10.1126/science.1176985 pmid: 19713491
[6]	Abalos D, Groenigen J W V, Deyn G B D. What plant functional traits can reduce nitrous oxide emissions from intensively managed grasslands?[J]. Global Change Biology, 2018, 24(1):248-258. doi: 10.1111/gcb.13827 pmid: 28727214
[7]	Khalil M A K, Easmussen R A. Nitrous oxide:Trends and global mass balance over the last 3000 years[J]. Annal Glaciology, 1988, 10:73-79.
[8]	Shcherbak I, Millar N, Robertson G P. Global metaanalysis of the nonlinear response of soil nitrous oxide(N₂O)emissions to fertilizer nitrogen[J]. Proceedings of the National Academy of Sciences, 2014, 111(25):9199-9204. doi: 10.1073/pnas.1322434111
[9]	国家林业和草原局. 中国森林资源报告[M].中国林业出版社. 2019.
[10]	傅民杰, 王传宽, 王颖, 等. 气候暖化对解冻期不同纬度兴安落叶松林土壤氧化亚氮释放的影响[J]. 应用生态学报, 2009, 20(7):1635-1642.
[11]	肖冬梅, 王淼, 姬兰柱, 等. 长白山阔叶红松林土壤N₂O排放通量的变化特征[J]. 生态学杂志, 2004(5):46-52.
[12]	孙向阳, 徐化成. 北京低山区两种人工林土壤中N₂O排放通量的研究[J]. 林业科学, 2001(5):57-63.
[13]	莎仁图雅, 段玉玺, 武佳琪. 内蒙古大青山不同林分密度油松人工林碳密度研究[J]. 内蒙古林业科技, 2013, 39(3):13-16.
[14]	陈丽霞. 内蒙古大青山森林土壤微生物量碳氮及微生物特征研究[D]. 呼和浩特: 内蒙古农业大学, 2015.
[15]	Ma Xiuzhi, Wang Shiping, Jiang Gaoming, et al. Short-term effect of targeted placements of sheep excrement on grassland in inner mongolia on soil and plant parameters[J]. Communications in Soil Science & Plant Analysis, 2007, 38(11/12):1589-1604.
[16]	Oertel C, Matschullat J, Zurba K, et al. Greenhouse gas emissions from soils-A review[J]. Chemie der Erde-Geochemistry, 2016, 76(3):327-352. doi: 10.1016/j.chemer.2016.04.002
[17]	Fisher D A, Lacelle D, Pollard W. A model of unfrozen water content and its transport in icy permafrost soils:Effects on ground ice content and permafrost stability[J]. Permafrost and Periglacial Processes, 2019, 31(1):184-199. doi: 10.1002/ppp.v31.1
[18]	Li Zhaolei, Zeng Zhaoqi, Tian Dashuan, et al. Global patterns and controlling factors of soil nitrification rate[J]. Global Change Biology, 2020, 26(7):4147-4157. doi: 10.1111/gcb.15119 pmid: 32301539
[19]	梁东丽, 同延安, Emteryd O, 等. 干湿交替对旱地土壤N₂O气态损失的影响[J]. 干旱地区农业研究, 2002(2):28-31.
[20]	齐玉春, 董云社. 土壤氧化亚氮产生、排放及其影响因素[J]. 地理学报, 1999(6):534-542. doi: 10.11821/xb199906007
[21]	谢军飞, 李玉娥. 土壤温度对北京旱地农田N₂O排放的影响[J]. 中国农业气象, 2005(1):8-11.
[22]	胡承彪, 韦源连, 梁宏温, 等. 两种森林凋落物分解及其土壤效应的研究[J]. 广西农业大学学报, 1992(4):47-52.
[23]	王鹤松, 张劲松, 孟平, 等. 侧柏人工林地土壤呼吸及其影响因子的研究[J]. 土壤通报, 2009, 40(5):1031-1035.
[24]	黄国宏, 陈冠雄, 吴杰, 等. 东北典型旱作农田N₂O和CH₄排放通量研究[J]. 应用生态学报, 1995(4):383-386.
[25]	高德才, 白娥. 冻融循环期间土壤氧化亚氮排放影响因素[J]. 植物生态学报, 2021, 45(9):1006-1023. doi: 10.17521/cjpe.2021.0040
[26]	Yanai Y, Toyota K, Okazaki M. Effects of successive soil freeze-thaw cycles on soil microbial biomass and organic matter decomposition potential of soils[J]. Soil Science and Plant Nutrition, 2004, 50:821-829. doi: 10.1080/00380768.2004.10408542
[27]	Freppaz M, Williams B L, Edwards A C, et al. Simulating soil freeze/thaw cycles typical of winter alpine conditions:implications for N and P availability[J]. Applied Soil Ecology, 2007, 35:247-255. doi: 10.1016/j.apsoil.2006.03.012
[28]	Pelster D E, Chantigny M H, Rochette P, et al. Crop residue incorporation alters soil nitrous oxide emissions during freeze-thaw cycles[J]. Canadian Journal of Soil Science, 2013, 93:415-425. doi: 10.4141/cjss2012-043
[29]	Nottingham A T, Bååth E, Reischke S, et al. Adaptation of soil microbial growth to tempera ture:Using a tropical elevation gradient to predict future changes[J]. Global Change Biology, 2019, 25:827-838. doi: 10.1111/gcb.14502 pmid: 30372571

时间段	N₂O通量	6月	7月	8月	9月
日均	2020年N₂O通量/	8.63±4.08	8.71±4.14	14.65±4.30	10.89±2.57
9:00	[μg/(m²·h)]	19.28(+10.65)	4.80(-3.91)	18.11(+3.46)	15.72(+4.83)
15:00		6.98(-1.65)	7.55(-1.16)	14.92(+0.67)	11.71(+0.82)
日均	2021年N₂O通量/	4.02±1.44	8.64±4.61	7.84±3.75	6.15±4.19
9:00	[μg/(m²·h)]	2.61(-1.41)	7.09(-1.55)	7.09(-0.75)	18.45(+12.3)
15:00		2.41(-1.61)	7.08(-1.56)	5.61(-2.23)	7.06(+0.91)

油松人工林土壤N₂O排放通量的昼夜变化规律及其影响因子

Diurnal Variation of Soil N₂O Emission Fluxes and Its Influencing Factors in Pinus tabulaeformis Plantation

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