不同经营模式对华北油松人工林碳储量的影响

doi:10.16258/j.cnki.1674-5906.2022.11.004

生态环境学报 ›› 2022, Vol. 31 ›› Issue (11): 2134-2142.DOI: 10.16258/j.cnki.1674-5906.2022.11.004

不同经营模式对华北油松人工林碳储量的影响

肖军¹^,²(), 雷蕾¹, 曾立雄¹, 李肇晨², 马成功³, 肖文发¹^,^*()

1.中国林业科学研究院森林生态环境与自然保护研究所/国家林业和草原局森林生态环境重点实验室，北京 100091
2.亚太森林恢复与可持续管理组织，北京 100102
3.旺业甸实验林场，内蒙古赤峰 024023

收稿日期:2022-06-05 出版日期:2022-11-18 发布日期:2022-12-22
通讯作者: *肖文发（1964年生），男，研究员，博士研究生导师，研究方向为森林生态学、全球气候变化与森林保护和可持续经营等。E-mail: xiaowenf@caf.ac.cn
作者简介:肖军（1982年生），男，博士研究生，研究方向为森林生态学。E-mail: xiaojun@apfnet.cn
基金资助:
“十三五”重点研发计划项目(2016YFD0600200);APFNet多功能森林经营试点示范项目(2011P3-INM);APFNet多功能森林经营试点示范项目(2015P8-INM-II)

Effects of Different Management Regimes on Carbon Stock of Pinus tabulaeformis Plantations in Northern China

XIAO Jun¹^,²(), LEI Lei¹, ZENG Lixiong¹, LI Zhaochen², MA Chenggong³, XIAO Wenfa¹^,^*()

1. Ecology and Nature Conservation Institute, Chinese Academy of Forestry/Key Laboratory of Forest Ecology and Environment, National Forestry and Grassland Administration, Beijing 100091, P. R. China
2. Asia-Pacific Network for Sustainable Forest Management and Rehabilitation, Beijing 100102, P. R. China
3. Wangyedian Experimental Forest Farm, Chifeng 024423, P. R. China

Received:2022-06-05 Online:2022-11-18 Published:2022-12-22

摘要/Abstract

摘要：

科学认识不同经营模式下人工林碳储量变化规律对于采取合理的经营措施以提高森林碳汇潜力和木材生产具有重要意义。以赤峰旺业甸实验林场3个龄级（10年林、47年林、56年林）油松（Pinus tabuliformis）人工林为研究对象，调查分析近自然经营、常规经营、未经营等3种经营模式对其生态系统碳储量及6年年均增量的影响。结果表明：3种经营模式的油松人工林生态系统碳储量组成均呈土壤层>乔木层>枯落物层>草本层>灌木层，且乔木层、植被层和生态系统的碳储量均随林龄增加而显著增加（P<0.05）；3种经营模式在3个龄级的油松人工林生态系统碳储量年均增量均为正值，未经营林分的随林龄增加而降低，近自然经营林分和常规经营林分通过不同的经营措施均改变了这一下降趋势（P<0.05）；近自然经营显著提高了56年林生态系统、47年林和56年林乔木层及3个龄级枯落物层的碳储量年均增量（P<0.05），常规经营显著降低了3个龄级生态系统（P<0.05）、10年林和47年林土壤层碳储量的年均增量（P<0.01）；就龄级而言，近自然经营和常规经营56年林生态系统碳储量的年均增量（7.49 Mg·hm^-2·a^-1，3.49 Mg·hm^-2·a^-1）均大于47年林（5.82 Mg·hm^-2·a^-1，1.27 Mg·hm^-2·a^-1）。为提高油松人工林生态系统碳储量，对尚未郁闭的低龄林分应尽量减少抚育间伐等人为干扰，但综合考虑碳储量增长和大径级用材林培育，近自然经营最理想。该研究区60年左右的油松人工林乔木层和生态系统碳储量仍在持续增长，建议提高其成熟林林龄区间的划分，以提高森林生态系统碳汇功能并培育更多的大径材。

关键词: 油松人工林, 近自然经营, 碳储量, 年均增量, 旺业甸实验林场

Abstract:

It is of great significance to scientifically understand the change law of carbon storage of plantations under different management modes for taking reasonable silvicultural measures to improve the carbon storage potential of forests and wood production. In this study, Pinus Tabuliformis plantations of three age classes (10 year old, 47 year old, 56 year old) in Wangyedian Experimental Forest Farm in Chifeng were taken as research objects. At the same time, the impacts of close-to-nature management (CTNM), conventional management (CM) and no human intervention (NHI) on the carbon storage of the ecosystem and the 6-year average annual increment were investigated and analyzed. The results show the order of the amounts of carbon storage of Pinus Tabuliformis plantation ecosystem under the three management modes as soil>trees>litter>grass>shrubs. Carbon storage in trees, vegetation and ecosystem of Pinus Tabuliformis plantation increased significantly with the increase of stand age (P<0.05). Moreover, CTNM boosts the annual increment of ecosystem carbon stock in the 56-year-old stand, that of tree carbon stock in 47- and 56-year old stands, and that of litter carbon stock in stands of all three ages (P<0.05). But CM significantly reduced the average annual increment of carbon storage in soil of 3 age class ecosystems (P<0.05), 10-year-old forests and 47-year-old forests (P<0.01). The annual increments of ecosystem carbon stock of 56-year-old stands under CTNM and CM (7.49 Mg·hm^-2·a^-1, 3.48 Mg·hm^-2·a^-1) were greater than those in 47-year-old stands (5.82 Mg·hm^-2·a^-1, 1.28 Mg·hm^-2·a^-1). Considering the growth of carbon storage of Chinese pine plantations and the cultivation of large diameter timber forests, CTNM is the most ideal management mode. Additionally, the carbon storage of tree layers and ecosystems of Pinus Tabuliformis plantations about 60 years old in the study area is still growing. It is suggested that the division of mature forest age interval should be improved to improve the carbon sink function of forest ecosystem and cultivate more large diameter timber.

Key words: Pinus tabulaeformis plantation, close-to-nature management, carbon stock, annual increment, Wangyedian Experimental Forest Farm

中图分类号:

肖军, 雷蕾, 曾立雄, 李肇晨, 马成功, 肖文发. 不同经营模式对华北油松人工林碳储量的影响[J]. 生态环境学报, 2022, 31(11): 2134-2142.

XIAO Jun, LEI Lei, ZENG Lixiong, LI Zhaochen, MA Chenggong, XIAO Wenfa. Effects of Different Management Regimes on Carbon Stock of Pinus tabulaeformis Plantations in Northern China[J]. Ecology and Environment, 2022, 31(11): 2134-2142.

图/表 4

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林龄 Stand age	经营类型 Management regime	平均胸径 Mean diameter/cm		乔木株数 Tree density/(plant·hm^-2)		土壤容重 Soil bulk density/(g·cm^-3)		抚育强度 Thinning intensity	海拔 Altitude/ m	坡度 Slope/ (º)
林龄 Stand age	经营类型 Management regime	2013	2019	2013	2019	2013	2019	抚育强度 Thinning intensity	海拔 Altitude/ m	坡度 Slope/ (º)
10	近自然经营 CTNM	2.28±0.06a	5.10±0.09a	3261±106b	3211±96b	1.25±0.10a	1.23±0.04a	16%±1%b	1142-1202	≤20
47		17.84±0.30a	19.70±0.16a	789±48a	783±44a	1.18±0.03b	1.35±0.07a	18%±1%b	1165-1201	≤20
56		24.69±0.85a	27.56±0.76a	578±20a	578±20a	1.10±0.03b	1.13±0.05a	16%±2%b	1322-1359	≤16
10	常规经营 CM	2.42±0.04a	5.08±0.09a	2917±44c	2861±39c	1.21±0.02a	1.34±0.04a	26%±2%a	1193-1230	≤22
47		18.90±0.60a	20.90±0.66a	717±104a	711±98a	1.39±0.04a	1.36±0.04a	25%±2%a	1129-1157	≤20
56		24.13±0.79a	26.70±0.65a	517±38a	511±34a	1.31±0.04a	1.18±0.04a	24%±4%a	1349-1373	≤15
10	未经营 NHI	2.30±0.04a	5.01±0.06a	3700±88a	3578±74a	1.23±0.05a	1.29±0.09a	0%±0%c	1205-1259	≤23
47		17.42±1.06a	19.01±1.08a	1056±174a	1022±164a	1.27±0.05b	1.29±0.06a	0%±0%c	1148-1171	≤22
56		24.40±0.71a	26.84±0.75a	645±40a	622±349a	1.16±0.04b	1.14±0.02a	0%±0%c	1342-1367	≤15

林龄 Stand age	经营类型 Management regime	平均胸径 Mean diameter/cm		乔木株数 Tree density/(plant·hm^-2)		土壤容重 Soil bulk density/(g·cm^-3)		抚育强度 Thinning intensity	海拔 Altitude/ m	坡度 Slope/ (º)
林龄 Stand age	经营类型 Management regime	2013	2019	2013	2019	2013	2019	抚育强度 Thinning intensity	海拔 Altitude/ m	坡度 Slope/ (º)
10	近自然经营 CTNM	2.28±0.06a	5.10±0.09a	3261±106b	3211±96b	1.25±0.10a	1.23±0.04a	16%±1%b	1142-1202	≤20
47		17.84±0.30a	19.70±0.16a	789±48a	783±44a	1.18±0.03b	1.35±0.07a	18%±1%b	1165-1201	≤20
56		24.69±0.85a	27.56±0.76a	578±20a	578±20a	1.10±0.03b	1.13±0.05a	16%±2%b	1322-1359	≤16
10	常规经营 CM	2.42±0.04a	5.08±0.09a	2917±44c	2861±39c	1.21±0.02a	1.34±0.04a	26%±2%a	1193-1230	≤22
47		18.90±0.60a	20.90±0.66a	717±104a	711±98a	1.39±0.04a	1.36±0.04a	25%±2%a	1129-1157	≤20
56		24.13±0.79a	26.70±0.65a	517±38a	511±34a	1.31±0.04a	1.18±0.04a	24%±4%a	1349-1373	≤15
10	未经营 NHI	2.30±0.04a	5.01±0.06a	3700±88a	3578±74a	1.23±0.05a	1.29±0.09a	0%±0%c	1205-1259	≤23
47		17.42±1.06a	19.01±1.08a	1056±174a	1022±164a	1.27±0.05b	1.29±0.06a	0%±0%c	1148-1171	≤22
56		24.40±0.71a	26.84±0.75a	645±40a	622±349a	1.16±0.04b	1.14±0.02a	0%±0%c	1342-1367	≤15

树种 Tree species	含碳率 Carbon factor	根茎比 Root-to-shoot ratio	木材密度 Wood density	生物量扩展因子 Biomass conservation factor
落叶松 Larix principis-rupprechtii	0.521	0.212	0.490	1.40
油松 Pinus tabuliformis	0.521	0.251	0.360	1.59
白桦 Betula platyphylla	0.491	0.248	0.541	1.37
山杨 Betula dahurica	0.496	0.227	0.378	1.59
黑桦 Populus davidiana	0.491	0.248	0.541	1.37
灌木Shrubs	0.47	0.40
草本Grass	0.47	2.80

树种 Tree species	含碳率 Carbon factor	根茎比 Root-to-shoot ratio	木材密度 Wood density	生物量扩展因子 Biomass conservation factor
落叶松 Larix principis-rupprechtii	0.521	0.212	0.490	1.40
油松 Pinus tabuliformis	0.521	0.251	0.360	1.59
白桦 Betula platyphylla	0.491	0.248	0.541	1.37
山杨 Betula dahurica	0.496	0.227	0.378	1.59
黑桦 Populus davidiana	0.491	0.248	0.541	1.37
灌木Shrubs	0.47	0.40
草本Grass	0.47	2.80

林龄 Stand age		10年林 10-year-old stand			47年林 47-year-old stand			56年林 56-year-old stand
经营类型 Management regime	调查年 Year	近自然经营 CTNM	常规经营 CM	未经营 NHI	近自然经营 CTNM	常规经营 CM	未经营 NHI	近自然经营 CTNM	常规经营 CM	未经营 NHI
乔木层碳储量 Tree carbon stock	2013	1.75±0.09Ca	1.70±0.03Ca	1.85±0.21Ca	42.02±0.99Ba	39.76±3.39Ba	46.44±1.48Ba	69.16±3.44Aa	65.68±4.52Aa	75.50±1.26Aa
乔木层碳储量 Tree carbon stock	2019	8.47±0.25Ca	7.66±0.62Ca	8.61±0.19Ca	56.11±1.28Ba	51.97±3.79Ba	56.56±1.24Ba	90.35±3.69Aa	81.95±4.68Aa	95.38±1.32Aa
灌木层碳储量 Shrubs carbon stock	2013	0.03±0.00Ab	0.04±0.02Ab	0.24±0.06Aa	0.20±0.10Aa	0.08±0.08Aa	0.01±0.00Ba	0.09±0.04Aa	0.07±0.04Aa	0.11±0.03Ba
灌木层碳储量 Shrubs carbon stock	2019	0.07±0.04Aa	0.03±0.03Aa	0.07±0.02Aa	0.13±0.13Aa	0.02±0.02Aa	0.00±0.00Ba	0.08±0.04Aa	0.02±0.02Aa	0.02±0.00Ba
草本层碳储量 Grass carbon stock	2013	1.70±0.53Aa	1.32±0.30Aa	0.68±0.09Aa	0.94±0.32Aa	0.92±0.10ABa	0.90±0.05Aa	0.26±0.12Aa	0.38±0.08Ba	0.25±0.06Ba
草本层碳储量 Grass carbon stock	2019	0.22±0.13Aa	0.41±0.04Aa	0.09±0.04Aa	0.97±0.35Aa	0.81±0.09Aa	0.47±0.02Aa	0.24±0.13Ba	0.44±0.25Aa	0.12±0.04Ba
枯落物层碳储量 Litter carbon stock	2013	2.05±0.69Ba	2.18±0.61Ba	1.64±0.10Ba	2.61±0.20Ba	2.01±0.20Bab	1.21±0.40Bb	4.33±0.30Aa	5.58±1.17Aa	3.80±0.39Aa
枯落物层碳储量 Litter carbon stock	2019	8.03±1.76Aa	4.63±1.21Aa	6.93±0.34Aa	11.88±0.79Aa	4.18±0.43Ac	8.51±1.10Ab	10.20±0.43Aa	6.93±2.07Aa	6.73±0.81Aa
土壤层碳储量 Soil carbon stock	2013	18.59±7.50Bb	61.40±11.56Aa	41.47±3.81Bab	50.34±12.23Ba	55.19±13.69Aa	31.26±4.68Ba	86.91±9.33Aa	119.28±27.55Aa	95.70±13.29Aa
土壤层碳储量 Soil carbon stock	2019	33.67±8.82Ba	60.69±11.31Aa	72.16±7.60Aa	61.94±17.68ABa	48.60±12.89Aa	54.98±8.17Aa	104.83±9.89Aa	122.56±27.22Aa	96.97±13.88Aa
植被碳储量 Vegetation carbon stock	2013	3.48±0.47Ca	3.06±0.34Ca	2.77±0.29Ca	43.16±0.78Ba	40.76±3.47Ba	47.35±1.43Ba	69.52±3.32Aa	66.13±4.40Aa	75.85±1.31Aa
植被碳储量 Vegetation carbon stock	2019	8.75±0.28Ca	8.09±0.61Ca	8.77±0.13Ca	57.21±0.95Ba	52.80±3.88Ba	57.03±1.23Ba	90.67±3.55Aa	82.41±4.46Aa	95.51±1.37Aa
生态系统碳储量 Ecosystem carbon stock	2013	24.12±6.42Cb	66.64±11.87Ca	45.88±3.47Cab	96.11±12.37Ba	97.96±11.78Ba	79.83±5.16Ba	160.75±10.55Aa	190.99±23.47Aa	175.36±13.39Aa
生态系统碳储量 Ecosystem carbon stock	2019	50.45±7.13Ca	73.41±11.15Ba	87.86±7.67Ba	131.03±17.78Ba	105.58±10.13Ba	120.52±7.09Ba	205.70±10.38Aa	211.90±24.51Aa	199.22±13.33Aa

不同经营模式对华北油松人工林碳储量的影响

Effects of Different Management Regimes on Carbon Stock of Pinus tabulaeformis Plantations in Northern China

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