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基于干旱区生态系统模型的亚洲中部生态系统有机碳储量估算及其对气候变化响应的研究
李超凡
学位类型博士
导师罗格平
2015
学位授予单位中国科学院大学
学位授予地点北京
学位专业地图学与地理信息系统
关键词干旱区生态系统模型(arid Ecosystem Model) 碳储量 亚洲中部干旱区 气候变化 温带荒漠
摘要作为新丝绸之路核心区,亚洲中部干旱区分布着世界80%以上的温带荒漠,近半个世纪以来,其经历了剧烈的气候变化,并显著改变了区域碳水和能量传输等生物地球化学过程。生态系统模型是国际上深入分析这一过程的主流手段,并在全球尺度上对温带荒漠的生物地球化学过程有过表征和研究,但由于缺乏系统完整的、较为客观的反映中亚气候、植被、土壤等的生态-地理数据库,和反映温带荒漠适应气候变化的特殊生理生态机制的生态系统过程模型,关于亚洲中部干旱区生态系统碳水循环的研究,存在很大的不确定性,尤其是作为生态系统稳定性重要表征的有机碳库及其对气候变化的响应过程仍不清楚,使该地区成为全球碳平衡评估中最不确定的地区之一。 鉴于此,在国家973项目“亚欧内陆干旱区碳循环过程及其在全球碳循环中的作用”支持下,本项研究首先参与自主研发了针对亚洲中部的干旱区生态系统过程模型(Arid Ecosystem Model, AEM)。AEM可模拟温带荒漠生态系统的地上、地下特殊结构特征,土壤水移动/根系吸收的详细过程,以及植物高效节水光合过程等干旱区重要生态机制。在本地参数化的基础上,通过模型精度验证、参数敏感性分析以及多情景数值模拟实验,全面评估AEM的适用性与可靠性。同时,在科技部重大国际合作项目“中亚地区应对气候变化条件下的生态环境保护与资源管理联合调查与研究”支持下,参与构建高时空分辨率的中亚气候、植被、土壤、地形、土地利用等生态-地理综合数据库。在此基础上,结合基于文献调查与野外采样(353条植被碳和284条土壤有机碳数据)的碳密度清单经验统计方法和校准的AEM过程机理模型,全面评估亚洲中部干旱区有机碳库格局。最后,利用高精度的中亚生态与地理综合数据集驱动AEM模型,模拟和分析近30年亚洲中部干旱区有机碳库对气候变化的时空响应。获得的主要结论如下: (1)AEM模型能够准确模拟亚洲中部干旱区植被地上、地下形态特征,植被碳密度,土壤有机碳密度,植被生产力以及蒸腾作用;也能精确捕捉干旱区碳、水通量对降水事件的瞬时脉冲响应。数值模拟实验表明,亚洲中部干旱生态系统对气候因子以及地下水位波动能做出有效响应,但由于植被形态和生理特征的差异,不同的植被功能类型响应的敏感度不同。实践证明AEM模型是研究亚洲中部干旱区生态系统对气候变化响应的有效工具,可以高精度模拟和分析干旱区生态系统结构与功能对区域气候变化的响应。 (2)亚洲中部干旱区有机碳总储量为31.34-34.16 Pg (其中荒漠土壤有机碳库参考深度dsoil为0-1 m;1 P = 1015)和44.00-44.58 Pg(dsoil = 0-3 m),占世界荒漠与干旱灌丛碳库的18-24%,与中东碳库相当、同澳洲碳库可比。其中,植被碳储量为3.04-4.12 Pg;区域总有机碳库的90%以上储存在土壤中,明显高于澳洲等其他干旱区60-70%的比例。本研究还发现荒漠灌木生态系统有65-68%的土壤有机碳分布在1-3 m的深层土壤中,指出前人研究仅考虑0-1 m深度土壤会导致其低估温带荒漠碳储量。此外,该地区温带荒漠的土壤有机碳密度显著高于热带和亚热带荒漠。 (3)亚洲中部干旱区有机碳库受到气候变化的显著影响,在1979-2011年期间共失碳0.46 Pg。区域碳库流失主要受1998-2008年间哈萨克斯坦北部地区长期干旱的影响。本研究发现该干旱与La Nina现象密切相关,导致植被碳库减少8%。哈萨克斯坦北部为主要有机碳库流失区,我国新疆北部的有机碳储量则由于气候的暖湿化显著增加。植被碳库波动是区域总有机碳库动态的主要组成因子;土壤有机碳库由于凋落物输入的减少与土壤呼吸减弱之间的平衡而保持稳定。
其他摘要As the heart of New Silk Road, Central Asia contains 80% of the world’s temperate deserts. Significant climate changes in recent decades have profoundly affected the ecosystem carbon (C) and water processes of this area. Process-based models are effective tools in addressing complex interactions among ecological processes and multiple environmental factors. However, general models usually could not embody substantial mechanisms of dryland ecosystem, which may introduce a set of uncertainties in the application for Central Asia. The lack of observational data (partially due to insufficient translation of Russian literatures) made it difficult to gain a comprehensive view of the C balance in this area, making Central Asia one of the most uncertain areas in the estimation of the global C stock/balance. Therefore, under the support of the National Basic Research Program of China (2009CB825105), this study first engaged in developing a process-based and spatial-explicit Arid Ecosystem Model (AEM). AEM addresses the structure of desert plants and their related C and water processes by including an improved vertical root distribution sub-model, a mechanistic sub-model for water movement along the groundwater-soil-root-canopy continuum, and a plant form sub-model that dynamically updates a plant’s aboveground structure and crown size on a daily basis. It can also model the strong photo-degradation effects on dryland detritus pools. Performance of AEM was evaluated by conducting sensitivity analysis as well as model validation against field observations including daily water flux, annual productivities and C storage in Central Asia. Meanwhile, under the support of International Science & Technology Cooperation Program of China (2010DFA92720), this study constructed an eco-geographical database that contains high resolution of climate, vegetation, soil properties, and topography data of Central Asia. Driving by the eco-geographical database, this study used both inventory and modeling approaches to assess the size and distribution of the ecosystem C stock in Central Asia and characterizing the spatiotemporal responses of the C pools to changing climate at the regional scale. The inventory approach linked the C densities of different vegetation types to the vegetation map of Central Asia. Vegetation C densities were estimated from 353 field observations based on literature review and field surveys. Soil organic C densities were estimated based on measurements of 284 soil profiles. Estimations based on the inventory method were compared to the model simulation results. The main findings are as follows: (1) The model accurately predicted the water and C pulses in response to abrupt precipitation events. The numerical experiments indicated that Central Asian dryland ecosystems could respond promptly to changes in climate and groundwater fluctuation, and PFTs differed in their sensitivities to environmental changes because of plant structure and physiology differences. This study showed that a process-based model, such as the AEM, could be useful in studying the complex interactions between plants and their water-stressed environment in the context of the dramatic climate change in Central Asia. (2) C stock in Central Asia was 31.34-34.16 Pg with the soil depth of 0-1 m and another 10.42-11.43 Pg in deep soil (1-3 m) of the temperate deserts. They amounted to 18 to 24% of the global C stock in deserts and dry shrublands. The C stock was comparable to that of the neighboring regions in Eurasia or major drylands around the world (e.g., Australia). However, 90% of Central Asia C pool was stored in soil, and the fraction was much higher than in other regions. Compared to hot deserts of the world, the temperate deserts in Central Asia had relatively high soil organic C density. (3) The C stock in Central Asia is under threat from dramatic climate change. During a decadal drought between 1998 and 2008, which was possibly related to protracted La Niña episodes, the dryland lost approximately 0.46 Pg C from 1979 to 2011. The largest C losses were found in northern Kazakhstan. The regional C dynamics were mainly determined by changes in the vegetation C pool, and the SOC pool was stable due to the balance between reduced plant-derived C influx and inhibited respiration.
学科领域地图学与地理信息系统
语种中文
文献类型学位论文
条目标识符http://ir.xjlas.org/handle/365004/14608
专题研究系统_荒漠环境研究室
作者单位中科院新疆生态与地理研究所
推荐引用方式
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李超凡. 基于干旱区生态系统模型的亚洲中部生态系统有机碳储量估算及其对气候变化响应的研究[D]. 北京. 中国科学院大学,2015.
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