2000~2007年不同管理措施下内蒙古锡林郭勒盟草地土壤有机碳贮量的估算
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摘要
草地作为陆地生态系统的重要组成部分,是世界上分布最广的植被类型之一,全球草地面积约占陆地面积的25%,土壤碳储量约占陆地总碳储量的20%,在气候变化及全球碳循环中扮演着重要的角色。我国草地面积约400×106hm2,占世界草地面积的12.5%,主要分布在西部和北部地区,其中北方温带草原约占全部草地面积的78%,是我国草地的主体。由于过度放牧、不合理开垦和乱采滥挖等,我国北方重点牧区退化草地面积由1980s的39.7%增加到1990s的50.2%,其中轻度、中度和重度退化草地面积分别占退化草地总面积的57.3%,30.5%和12.2%,草地退化导致土壤有机碳不同程度下降。
     近十余年来,为遏制草地退化、改善草地生态环境和提高草地生产力,中国政府实施了一系列草原保护和建设工程。锡林郭勒盟是我国北方重点牧区之一。自20世纪末以来,该盟采取了围栏、改良等措施以保护草原生态环境,良好的管理措施不仅使退化草地的植被生产力得以恢复,而且使土壤有机碳逐步增加。以内蒙古锡林郭勒盟历年草地管理面积和不同草地管理下土壤有机碳变化的文献数据为基础,分别采用《2006年IPCC国家温室气体清单指南》方法2和基于文献数据的转移矩阵方法,估算2000-2007年锡林郭勒盟草地土壤有机碳库变化,以期初步阐明草地管理在区域土壤碳贮量变化中的作用,为有效制定草地碳增汇策略提供科学依据。
     1)不同管理措施对锡盟草地土壤有机碳影响不同。改良、打草、围栏措施下土壤有机碳贮量增加,年增加量分别为0.83tC·hm-2·a-1、0.49tC·hm-2·a-1和0.63tC·hm-2·a-1,年变化率分别为2.0%、1.4%和2.4%;放牧造成草地土壤有机碳贮量减少,随着放牧强度的增加,土壤有机碳贮量逐渐减少,轻牧、中牧、重牧下土壤有机碳年变化量分别为-0.15tC·hm-2·a-1、-0.45tC·hm-2·a-1和-0.89tC·hm2·a-1,年变化率分别为-0.4%、-1.1%和-2.3%。
     2)IPCC Tier 2和转移矩阵方法估计结果表明,2000-2007年间,锡林郭勒盟草地土壤有机碳增加量为20.85-29.76Tg,年均2.61-3.72Tg,这得益于草地围栏面积大幅度增加。其中,东乌珠穆沁旗、西乌珠穆沁旗、苏尼特左旗、苏尼特右旗、阿巴嘎旗和锡林浩特市有机碳增加明显,占全盟总量的80%以上。相关性分析表明,采用IPCC方法2与转移矩阵法估算的土壤有机碳变化量在空间上具有很好的一致性,但前者的估计值比后者约低1/3。用两种方法估算的逐年有机碳变化量在时间序列上不具可比性,IPCC方法2估算的土壤碳贮量前3年增加迅速,其后增速减缓,且不同管理措施下的碳库变化因子对估计结果极其敏感;转移矩阵法估算的土壤碳贮量后5年增加迅速,是前3年的2.4倍,且有机碳变化因子对估计结果的敏感性低于IPCC方法2。
     3) IPCC Tier 2和转移矩阵估计结果表明,围栏措施对土壤有机碳增加最多,其次为改良和打草,轻牧面积的减少导致IPCC Tier 2估算其碳储量下降。东乌珠穆沁旗草地近8年土壤碳增量最多,太仆寺旗最少。IPCC Tier 2和转移矩阵方法估算的各旗(县、市)管理措施下有机碳变化量具有很好的可比性,两种方法估算的改良、打草和围栏措施下有机碳均表现为增加,前者估算结果是后者的12倍;两种方法估算的轻牧、中牧和重牧下土壤碳均减少,但前者比后者低估了76倍。获得精确的土壤碳库变化因子有助于减小估算结果的误差。
As an important component of terrestrial ecosystem, grasslands are one of the most widespread vegetation types worldwide, covering nearly one-forth of the world's land surface, and the soil carbon stocks amount to 20% of the global total, sograssland plays a significant role in climate change and global carbon cycle. The area of grassland in China is approximately 4×108ha, accounting for 12.5% of the total in world, distributed mainly in the western and northern areas, and the northern temperate steppe which almost covers 78% of the national grassland is the main grassland in China. As a result of overgrazing, unreasonable reclamation, over gathering and colleting, etc, the degenerate grassland area of the important pasture in northern China has increased from 39.7% in 1980s to 50.2% in 1990s, of which, areas of light, middle and heavy degenerate account for 57.3%,30.5% and 12.2% of the degenerate grassland respectively. Grassland degeneration leads to a different decreases in SOC storage.
     In the past ten years or more. China's government has taken a set of grassland protection and construction projects to hold back degeneration, improve grassland ecosystem and enhance grassland productivity. Xilinguole League is one of important pastoral zones in the northern, measures such as fencing, improving and so on have been taken to protect the grassland eco-environment since the end of 20th century, good management practices not only restore the vegetation productivity of degraded grassland but also increase the SOC storage gradually. On the basis of grassland area with different managements and data sets of soil organic carbon (SOC) extracted from the literature, we estimated the changes in SOC of grassland in Xilinguole, Inner Mongolia Municipality from 2000 to 2007 by two approaches. One is the IPCC Tier 2, and the second is based on a transfer matrix of soil organic carbon under various managements. The objective is to elucidate the effects of grassland managements and provide support for making effective measures to increase carbon sink in grassland.
     The different managements have different influence to the SOC storage in grassland. The yearly increase amount of SOC for improving, mowing, enclosure were 0.83tC·hm-2·a-1 0.49tC·hm-2·a-1,0.63tC·hm·2·a-1. and the change rates of SOC were 2.0%,1.4%,2.4%. the SOC storage decreased with the grazing intensity increased, the annual SOC change for light grazing, medium grazing, heavy grazing were -0.15tC·hm-2·a-1,-0.45tC·hm-2·a-1-0.89tC·hm-2·a-1. and the change rates of SOC were -0.4%,-1.1%,-2.3%.
     The estimated results by the two approaches showed that SOC of grassland in the Xilinguole has increased by 20.85-29.80Tg, with an average rate of 2.61-3.72Tg a-1 over the period of 2000-2007. This increase is attributed to a substantial expansion of grassland enclosure. More than 80% of the increase was located in the counties of Dongwuzhumuqin, Xiwuzhumuqin, Sunitezuo, Suniteyou and Abaga, and Xilinhaote city. Correlation analysis indicated a good agreement of the estimated spatial changes in SOC using the two approaches, while it was approximately one third lower using the IPCC Tier 2 than that using the transfer matrix approach as the total amount was concerned. Nevertheless, the estimated annual SOC changes were not consistent between these two approaches. The annual increment of SOC in the first three years was greater than the last several years using the IPCC Tier 2, while the increment in the last five years was 1.4 times higher than the average of first three years using the transfer matrix approach. Moreover, the relative SOC stock change factors in the IPCC Tier 2 approach were much sensitive than the SOC density change factors in the transfer matrix approach to the estimates of SOC
     The estimated results by IPCC Tier 2 and transfer matrix approach showed that the increasing amount of SOC for enclosure was the highest, followed by improving and mowing, the reduced area for light grazing led to the decrease of SOC by IPCC Tier 2 during 2000 to 2007. The total SOC increase in Dongwuzhumuqin county was the largest. while that was the smallest in Taipusi county. the total SOC change under different managements showed good comparability between IPCC Tier 2 and transfer matrix approach, the estimated results by the two methods indicated that the SOC storage increased for improving, mowing and enclosure(R2=0.97, p<0.001), but the results estimated by the former was 12 times more than that by the latter, while the SOC decreased for grazing(R2=0.90,p<0.001), and it underestimated 76 times as compared to the transfer matrix approach.
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