Scientia Agricultura Sinica ›› 2020, Vol. 53 ›› Issue (13): 2757-2768.doi: 10.3864/j.issn.0578-1752.2020.13.022

• ECOLOGICAL INDUSTRY PRACTICE AND REGIONAL SCALE PROCESSES • Previous Articles    

Biomass Carbon Storage and Its Effect Factors in Steppe and Agro-Pastoral Ecotones in Northern China

XIN XiaoPing1(),DING Lei1,CHENG Wei1,ZHU XiaoYu1,CHEN BaoRui1,LIU ZhongLing2,HE GuangLi3,QING GeLe1,YANG GuiXia1,TANG HuaJun1   

  1. 1Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences/National Hulunber Grassland Ecosystem Observation and Research Station, Beijing 100081
    2Department of Environmental Sciences, Inner Mongolia University, Huhhot 010021
    3Department of Grassland Ecology and Animal Husbandry, Xilingol Vocational College, Xilinhot 026000, Inner Mongolia
  • Received:2019-09-23 Accepted:2020-02-19 Online:2020-07-01 Published:2020-07-16
  • Contact: XiaoPing XIN E-mail:xinxp@sina.com

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Abstract:

【Objective】 The grassland ecosystem plays an important role in the global carbon balance. The study of grassland carbon pool and its driving force is a hot point of vegetation ecology. This study investigated the vegetation carbon density and its spatial pattern in the steppe and agro-pastoral ecotones of northern China. The major factors driving the spatial variation of grassland vegetation carbon density were identified, as well as the relative contribution of climate, soil texture, grazing intensity and other factors to the grassland vegetation carbon pool. 【Method】 Using the survey data of the grassland vegetation in northern grassland during 2002 and 2009, combined with the MODIS/NDVI remote sensing data and 1:1 million grassland type map, the estimation model of above- and below-ground biomass in the main grassland types of northern China was established. Based on 255 county-level administrative units in the study area, the relationship between grassland vegetation carbon density and climate factors, soil texture and livestock carrying capacity were explored, and derived the relative contribution of different driving factors to grassland carbon density using the general linear model (GLM). 【Result】 (1) The average above-ground biomass (AGB) of the steppe and agro-pastoral ecotones of northern China was 36.9 g C·m-2, and the below-ground biomass (BGB) was 362.9 g C·m-2, nearly 10 times the AGB. Both the above- and below-ground biomass decreased from east to west, and followed logarithmic normal distribution. The biomass carbon density of grassland types was significantly different. (2) In the whole study region and steppe sub-region, desert sub-region, agro-pastoral sub-region, the AGB showed a significantly positive correlation with mean annual precipitation (MAP) and soil clay content (Clay%), a significantly negative relationship with the mean annual temperature (MAT) and soil sand content (Sand%). The AGB increased with livestock carrying capacity except in the steppe sub-region where were very heavily grazed. (3) General Linear Model (GLM) analysis indicated that the MAP, MAT, Clay% and grazing intensity explained 29.6% (P<0.001), 5.8% (P<0.001), 0.8% (P<0.05) and 1.3% (P<0.001) of AGB variation, respectively, and the MAP, MAT and Sand% contributed to 12.1% (P<0.001), 6.8% (P<0.001) and 1.9% (P<0.005) to BGB variation, respectively, and the grazing intensity had minor contribution to BGB. 【Conclusion】 Climate factors especially MAP was the dominate driving factor of grassland vegetation carbon density, and its impact on AGB was more obvious than on BGB. Soil texture also had a significant contribution to the grassland vegetation carbon density, especially on the BGB. Grazing intensity explained only 1.3% of the AGB and had no impact on BGB. This finding indicated that the climate factors were major contributor grassland vegetation carbon density comparing with grazing intensity.

Key words: steppe and agro-pastoral ecotones in northern China, biomass carbon storage, climate, livestock capacity, soil texture

Fig. 1

Research region and distribution of sampling sites 审图号:GS（2020）2229号"

Fig. 2

The relationship between NDVI and Log (AGB) (A) and validation of AGB estimation (B) LM, MM, TMS, TS, TD, AM and AS represent respectively lowland meadow, mountain meadow, temperate meadow steppe, typical steppe, temperate desert, alpine meadow and alpine steppe"

Fig. 3

Spatial pattern (A, C) and frequency distribution(B, D) of above-ground biomass (AGB) and below-ground biomass (BGB) 审图号:GS（2020）2229号"

Table 1

Carbon density and carbon storage of different grassland types"

草地类型
Grassland Type		 面积
Area (×104km2)		 碳密度 Carbon density (g C·m-2) 碳储量 Carbon storage (Tg)
地上AGB 地下BGB 总量Total 地上AGB 地下BGB 总量Total
TMS 14.13 65.46 582.44 647.90 9.25 82.30 91.54
TS 36.04 38.65 341.04 379.69 13.93 122.92 136.85
TDS 13.59 29.27 255.00 284.27 3.98 34.66 38.64
TD 32.36 19.02 151.01 170.03 6.16 48.87 55.03
LM 11.80 47.50 662.64 710.14 5.60 78.17 83.77
MM 2.11 67.92 365.99 433.91 1.43 7.71 9.15
AM 1.96 38.43 1456.2 1494.62 0.75 28.60 29.36
AS 1.58 17.31 482.71 500.02 0.27 7.63 7.90
Other 1.70 67.31 443.07 510.38 1.15 7.55 8.70
Total 115.28 36.89 362.95 399.84 42.52 418.42 460.94

Table 2

Correlation coefficient between above-ground biomass (AGB) and environment factors"

相关系数
Correlation Coefficient		 草原区
Steppe area		 荒漠区
Desert area		 农牧交错区
Agro-pasture area		 研究区
Research region
年均气温MAT -0.65*** -0.69*** -0.53*** -0.46***
年降水量MAP 0.50*** 0.81*** 0.53*** 0.72***
家畜承载量Livestock capacity 0.09 0.45* 0.34*** 0.25***
砂砾含量Sand% -0.65*** -0.63** -0.23** -0.42***
黏粒含量Clay% 0.54*** 0.73*** 0.46*** 0.59***

Fig. 4

Relationship between above-ground biomass (AGB) and climate, soil texture and livestock capacity A-D: Relationship between above-ground biomass and mean annual temperature; E-H: Relationship between above-ground biomass and mean annual precipitation; I-L: Relationship between above-ground biomass and livestock capacity; M-P: Relationship between above-ground biomass and soil texture. DSE: Dry sheep equivalent"

Table 3

Root/shoot ratio (R/S) used in different studies"

草地类型
Grassland type		 朴世龙[27] YANG[32] MA[14] FAN[9] R/S used in this study[28]
本研究使用王道龙[28]
Sample No. R/S
温性草甸草原Temperate meadow steppe 5.26 5.20 7.00 11.85 108 7.48(±4.74)
温性草原类Typical steppe 4.25 5.60 5.54 10.80 86 9.36(±6.35)
温性荒漠草原类Temperate desert steppe 7.89 6.40 5.19 6.71 100 6.73(±5.87)
高寒草甸草原类Alpine meadow steppe 7.91 42.67
高寒草原类Alpine steppe 4.25 5.20 39.51 139 27.89(±13.23)
高寒荒漠草原类Alpine desert steppe 7.89 24.38
温性草原化荒漠 Temperate desert steppe 7.89 5.31 87 5.92(±4.95)
温性荒漠类Temperate desert 7.89 1.09
高寒荒漠类Alpine desert 7.89 15.67
暖性草丛类Warm temperate herbosa 4.42 3.67
暖性灌草丛类Warm temperate shrub herbosa 4.42 1.52
热性草丛类Tropical herbosa 4.42
热性灌草丛类Tropical shrub herbosa 4.42
低地草甸类Lowland meadow 6.31 2.04 37 6.84(±3.12)
山地草甸类Mountain meadow 6.23 3.50 5.71 9.67 20 5.39(±2.48)
高寒草甸类Alpine meadow 7.92 6.80 20.06 129 37.8(±22.10)
沼泽类Marsh 15.68 12.57

Table 4

General linear model (GLM) analysis between above-ground biomass (AGB), below-ground biomass (BGB), and environment factors"

源
Source		 df 地上生物量Above-ground biomass 地下生物量Below-ground biomass
SS% F Sig. SS% F Sig.
校正模型Adjusted model 5 68.81 107.242 0.000 48.20 45.223 0.000
年均气温MAT 1 5.8 45.190 0.000 6.79 31.850 0.000
年降水量MAP 1 29.56 230.312 0.000 12.12 56.875 0.000
放牧强度Livestock capacity 1 1.34 10.465 0.001 0.49 2.307 0.130
黏粒含量Clay% 1 0.78 6.044 0.015 0.02 0.076 0.783
砂粒含量Sand% 1 0.05 0.371 0.543 1.91 8.978 0.003
误差Residuals 243 31.19 51.80
总计R2 248
校正的总计Adjusted R2 248 R2 = 0.688（调整Adjusted R2 = 0.682） R2 = 0.482（调整Adjusted R2 = 0.471）
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