Biomass Carbon Storage and Its Effect Factors in Steppe and Agro-Pastoral Ecotones in Northern China
XIN XiaoPing,1, DING Lei1, CHENG Wei1, ZHU XiaoYu1, CHEN BaoRui1, LIU ZhongLing2, HE GuangLi3, QING GeLe1, YANG GuiXia1, TANG HuaJun11Institute 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
摘要 【目的】 草地生态系统在全球碳平衡中有重要的意义,草地植被碳库及其变化机制研究是植被生态学的重要命题。本文研究北方草地和农牧交错区草地植被碳密度及其空间格局,解析不同区域草地植被碳密度的关键影响因素,分析了气候、土壤、放牧等因素对地上地下植被碳库的相对贡献。【方法】 基于2002—2009年北方草地及农牧交错带草地植被调查数据,结合同期MODIS/NDVI遥感影像和1﹕100万草地类型图,建立了我国主要草地类型的生物量估算模型;整合野外考察数据和前人研究结果,探讨了研究区地上地下生物碳库及其空间格局;基于研究区255个县级行政单元,分析了不同类型草地植被碳库与气候要素、土壤要素及家畜承载量的关系,应用一般线性模型(GLM)解析了不同影响因素对草地碳密度的相对贡献。【结果】 (1)北方草地与农牧交错区草地地上平均生物碳密度为36.9 g C·m-2,地下生物碳密度为362.9 g C·m-2,地下生物碳密度高于地上10倍,均呈从东到西递减的趋势,频率分布图基本服从对数正态分布,不同草地类型的生物碳密度存在明显差异;(2)整个研究区及草原亚区、荒漠亚区、农牧交错亚区内,地上生物量与年降水量(MAP)呈极显著正相关、与年均气温(MAT)均呈极显著负相关,与土壤黏粒含量(Clay%)呈显著正相关、与土壤砂粒含量(Sand%)呈显著负相关,整个研究区家畜承载量与草地地上生物量之间呈极显著正相关;(3)一般线性模型(GLM)分析结果表明,年平均降水量(MAP)、年均气温(MAT)、土壤黏粒含量(Clay%)、放牧强度对地上生物量空间变异的解释率分别达到29.6%(P<0.001)、5.8%(P<0.001)、0.8%(P<0.05)、1.3%(P<0.001);地下生物量的空间变异主要来自于年降水量(MAP)、年均气温(MAT)、土壤砂粒含量(Sand%),对方差的解释率分别达到12.1%(P<0.001)、6.8%(P<0.001)、1.9%(P<0.005),放牧强度没有明显贡献。【结论】 气候条件尤其是年降水量是草地生物量碳库的主要影响因素,但对地上生物量影响更为明显;土壤质地对植被生物碳库也有显著贡献,尤其对地下生物量的影响更加显著;放牧强度只能解释地上生物量变化的1.3%、对地下生物量没有显著贡献,这一发现意味着气候对生物量碳库的贡献远大于放牧影响。 关键词:北方草地及农牧交错区;植被碳储量;气候因素;家畜承载量;土壤质地
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. Keywords:steppe and agro-pastoral ecotones in northern China;biomass carbon storage;climate;livestock capacity;soil texture
PDF (4493KB)元数据多维度评价相关文章导出EndNote|Ris|Bibtex收藏本文 本文引用格式 辛晓平, 丁蕾, 程伟, 朱晓昱, 陈宝瑞, 刘钟龄, 何广礼, 青格勒, 杨桂霞, 唐华俊. 北方草地及农牧交错区草地植被碳储量及其影响因素[J]. 中国农业科学, 2020, 53(13): 2757-2768 doi:10.3864/j.issn.0578-1752.2020.13.022 XIN XiaoPing, DING Lei, CHENG Wei, ZHU XiaoYu, CHEN BaoRui, LIU ZhongLing, HE GuangLi, QING GeLe, YANG GuiXia, TANG HuaJun. Biomass Carbon Storage and Its Effect Factors in Steppe and Agro-Pastoral Ecotones in Northern China[J]. Scientia Acricultura Sinica, 2020, 53(13): 2757-2768 doi:10.3864/j.issn.0578-1752.2020.13.022
北方草地与农牧交错区草地地上平均生物碳密度为36.9 g C·m-2,地下生物碳密度将近地上生物碳密度的10倍(362.9 g C·m-2)。从分布格局看,地上、地下生物碳密度均呈从东到西递减的趋势,频率分布图基本服从对数正态分布(图3)。不同草地类型生物碳密度存在明显差异。温性草地地上生物碳密度从大到小依次是山地草甸、温性草甸草原、低地草甸、典型草原、荒漠草原及荒漠,分别是67.92、65.46、47.50、38.65、29.27、19.02 g C·m-2,不同类型间地下生物碳密度基本与地上生物量一致。高寒草地地上生物碳密度比温性草地偏低(高寒草甸38.43 g C·m-2,高寒草原17.31 g C·m-2),但由于高寒草地根冠比明显高于温性草地根冠比[28],其地下生物碳密度明显高于温性草地(高寒草甸1 456.2 g C·m-2,高寒草原482.71 g C·m-2)。但研究区域高寒草地只在荒漠区山地小面积分布,因此对区域碳储量贡献不大(表1)。
A—D:地上生物量碳密度与平均年均气温的关系,E—H:地上生物量碳密度与平均年降水的关系,I—L:地上生物量碳密度与家畜承载量的关系,M—P:地上生物量碳密度与土壤质地的关系。DSE:羊单位 Fig. 4Relationship 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 4 表4 表4地上地下生物量与环境因子的一般线性模型分析结果 Table 4General 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)
SS%变量所解释的方差比例 Proportion of variances explained by the variable
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