Knowledge Resource Center for Ecological Environment in Arid Area
| 1982-2013年欧亚大陆草原地上净初级生产力的空间格局和动态变化研究 | |
| 其他题名 | Analysis of spatial and temporal patterns of aboveground net primary productivity in the Eurasian steppe region from 1982 to 2013 |
| 焦翠翠 | |
| 出版年 | 2017 |
| 学位类型 | 博士 |
| 导师 | 于贵瑞 |
| 学位授予单位 | 中国科学院大学 |
| 中文摘要 | 草地是地球上广泛分布的生态系统之一，约占陆地表面的20%，年均碳汇值约为0.5 Pg C，约占全球陆地生态系统当前碳汇量的18%，在调节温室气体浓度变化的过程中具有重要的作用。地上净初级生产力（Aboveground net primary productivity, ANPP）是表征生态系统碳/源汇功能的重要基础通量之一，其动态变化代表了生态系统对气候变化的响应。欧亚大陆草原（The Eurasian steppe region, EASR）是世界上面积最大、连续分布的草原，且同时受到季风气候、温带大陆性气候和地中海气候的共同影响，是全球变化的敏感区域。但是，目前的研究尚未以EASR整个区域为分析对象，关于EASR的ANPP空间分布规律，整个区域的ANPP总量（Total aboveground net primary productivity, TANPP）在全球草地生态系统中所占的比例，及其对气候变化的响应还属于一个知识空白领域。本研究将ANPP的地面调查数据和美国国家航空航天局（National Aeronautics and Space Administration, NASA）全球监测与模型研究组（Global inventory monitoring and modeling studies, GIMMS）发布的长时间序列的归一化植被指数（Normalized Difference Vegetation Index, NDVI ）数据相结合，综合考虑研究区域的空间异质性、NDVI的合成时相等因素，分别在总体统一模式下和分区综合模式下构建了ANPP的估算模型。通过模型精度的比较，运用EASR的区域ANPP最优估算模型（Integrated ANPPNDVI Model）估算了EASR及其3个亚区：黑海—哈萨克斯坦草原亚区（The Black Sea-Kazakhstan steppe subregion, BKSSR）、蒙古高原草原亚区（The Mongolian Plateau steppe subregion, MPSSR）和青藏高原高寒草原亚区（The Tibetan Plateau alpine steppe subregion, TPSSR）的ANPP和TANPP（ANPP区域总量）在1982-2013年期间的大小，分析了其空间格局、动态变化规律和对气候变化的响应。主要的结果如下：（1）NDVI能够较好地表征EASR的ANPP时空变异特征，且在分区综合模式下构建的ANPP估算模型较在总体统一模式下构建的模型精度高。表征ANPP变化的最优NDVI合成时相会因区域的环境差异而有所不同，因此，在运用NDVI数据反演ANPP时，应该根据区域的气候和植被等条件选择相应的NDVI合成时相。根据本研究的结论，对于半湿润区域、半干旱区域和荒漠植被，我们建议分别选用生长季早—中期的平均NDVI、生长季中—后期的平均NDVI和年NDVI最大值。（2）EASR的区域平均ANPP为43.78±22.77g C m-2 yr-1，低于全球草地生态系统的平均值，也低于北美洲和南美洲等世界上主要草地生态系统的平均水平。从EASR的3个亚区之间ANPP的差异特征来看，BKSSR的区域平均ANPP最小，值为37.70±16.60 g C m-2 yr-1；MPSSR的区域平均ANPP最大，值为52.86±24.78 g C m-2 yr-1；TPSSR区域平均ANPP的大小介于BKSSR和MPSSR两个亚区之间，值为46.98±28.94 g C m-2 yr-1。（3）EASR的ANPP呈现出明显的空间分布规律。BKSSR和MPSSR的ANPP都是自亚区中心向边缘区域逐渐升高，TPSSR的ANPP则表现为自西北——东南方向逐渐增大的空间分异规律。从EASR整体来看，ANPP的空间变异主要受到年总降水（MAP）的影响，ANPP与MAP的空间变异呈线性正相关关系。BKSSR和MPSSR的ANPP空间变异影响因素与整个EASR相一致。TPSSR的ANPP空间变异影响因素则与整个EASR不同，主要受到年总辐射（MAR）的影响，与MAR呈负相关关系。（4） EASR的TANPP为378.97 Tg C yr-1，占到全球草地生态系统TANPP的8.18% - 36.03%。EASR的TANPP高于北美洲、南美洲、非洲、澳洲和新西兰等世界上其他主要草地生态系统的TANPP。对于BKSSR、MPSSR和TPSSR 3个亚区，BKSSR的TANPP最大，值为173.08Tg C yr-1。MPSSR和TPSSR的TANPP分别为133.31 Tg C yr-1和72.58 Tg C yr-1。（5）EASR的TANPP在1982-2013年期间内呈波动式增加趋势，增加速率低于全球草地生态系统的平均水平。与世界其他主要草地生态系统相比，EASR的TANPP增加速率高于同期北美洲和南美洲草地生态系统，而低于非洲草地生态系统。1995年和2007年是TANPP随时间动态变化趋势发生显著变化的两个拐点年份。 EASR的TANPP在1982-1995年和2008-2013年期间呈增加的变化趋势，在1996-2007年期间则显著减小。这主要是因为在1996-2007年期间MPSSR和TPSSR的TANPP显著减小，显著不同于前后两个时期显著增加的变化趋势造成的。（6）从EASR整体来看，ANPP的年际变异主要受到降水的影响，重要降水时期（Critical Precipitation Period, CPP）为1-8月份。对于3个亚区来说，BKSSR和MPSSR的ANPP年际变异的气候影响因素与EASR整体类似，都是受到降水的影响，但是CPP有差异：分别为1-9月和5-7月。在TPSSR，ANPP年际变异则是主要受到温度的影响，重要温度时期（Critical Temperature Period, CTP）为6-7月。EASR的TANPP在1995-2007年期间显著降低，主要是因为在该时期MPSSR 的5-7月累积降水量明显减少和TPSSR的 6-7 月平均温度显著降低引起的。 （7）EASR的ANPP对气候变化的响应机制为：夏季北极涛动、春末夏初的北大西洋涛动和中国南海夏季风分别通过调控BKSSR的 1-9月的降水、MPSSR的 5-7月的降水和TPSSR 的6-7月的温度来影响各个亚区ANPP的年际变异。另外，强的ENSO事件通过直接影响降水或者通过调控中国南海夏季风的强度进一步影响温度，进而影响各个亚区ANPP的年际变异。 |
| 英文摘要 | Grasslands are one of the most widespread biomes, accounting for approximately 20% of the world’s land surface. Grasslands likely contribute an annual carbon sink of up to ~0.5 Pg C, and amount to about 18% of the total current global terrestrial carbon sink, playing a key role in balancing the concentration of global atmospheric greenhouses gases through carbon sequestrating. Aboveground net primary productivity (ANPP)(李文华, 1998 #252;蒙古国科学院地理研究所, 2009 #254) is one of important and fundamental fluxes indicating carbon sinks/sources of ecosystems, of which variations over time reflect the response of ecosystems to climate change. The Eurasian steppe region (EASR), the largest continuous grassland biome worldwide, is influenced by monsoon, continental and Mediterranean climates together and is sensitive to global climate change. However, studies on the spatiotemporal dynamics of ANPP have not yet been specifically reported for the entire EASR. There is thus a knowledge gap on spatiotemporal dynamics in ANPP for the entire EASR and on roles that the EASR plays in the global carbon budget.In this study, based on field-observed ANPP and long-term NDVI time-series data, by considering spatial heterogeneities across the study area, we developed ANPP estimation models for the entire EASR through two different schemes, respectively: the Entirety Overall Scheme and the Subregions Integrated Scheme. The best ANPP estimation model (Integrated ANPPNDVI Model) specific to the entire EASR was obtained by selecting the model with higher validation accuracy. ANPP and total ANPP (TANPP) during 1982 to 2013 in the EASR and its 3 subregions (The Black Sea-Kazakhstan steppe subregion, BKSSR; The Mongolian Plateau steppe subregion, MPSSR; and The Tibetan Plateau alpine steppe subregion, TPSSR) were estimated from the Integrated ANPPNDVI model, of which spatial and temporal variations were also analyzed. Main results were as follows: (1) NDVI can be used to model spatiotemporal dynamics of ANPP for the entire EASR. In addition, the Integrated ANPPNDVI model developed within the Subregions Integrated Scheme performed better than the Overall ANPPNDVI model developed from the Entirety Overall Scheme. Composite periods of NDVI data should be selected according to climatic conditions and vegetation types found in a given study area when NDVI data are applied in empirical annual ANPP estimation models. Our analysis results show that early–middle growing season averaged NDVI, middle–late growing season averaged NDVI and annual maximum NDVI should, respectively be applied for semi-humid regions, semi-arid regions and desert vegetation in semi-arid regions.(2) The mean value of annual ANPP for the entire EASR was recorded as 43.78±22.77 g C m-2 yr-1, which is lower than that for global grasslands average, North and South American grasslands. For difference characteristics of ANPP among 3 subregions of EASR, the BKSSR had the lowest mean annual ANPP with a value of 37.70±16.60 g C m-2 yr-1. The MPSSR had the highest mean annual ANPP with a value of 52.86±24.78 g C m-2 yr-1. The TPSSR fell between that of the BKSSR and MPSSR, at a value of 46.98±28.94 g C m-2 yr-1.(3) ANPP revealed pronounced spatial variations in the EASR. More specifically, an increase in ANPP traveled from the center to the boundaries of the BKSSR and the MPSSR, and from the northwest to the southeast of the TPSSR. For the entire EASR, the spatial variations of mean annual precipitation (MAP) mainly controlled the spatial patterns of ANPP. ANPP was positively related to MAP for the entire EASR. For the BKSSR and the MPSSR, that was similar to the entire EASR. However, spatial variations in TPSSR’s ANPP were mainly influenced by mean annual solar radiation (MAR), which were negatively related to MAR.(4) TANPP for the entire EASR was recorded as 378.97 Tg C yr-1, accounting for 8.18% - 36.03% of that of all grasslands. EASR’s TANPP is higher than that for grasslands in North America, South America, Africa, Australia and New Zealand. For the three subregions studied, TANPP values were found to be the highest in the BKSSR at 173.08 Tg C yr-1, and the lowest in the TPSSR at 72.58 Tg C yr-1. Moreover, the TANPP of the MPSSR was recorded as 133.31 Tg C yr-1.(5) The EASR’s TANPP increased in a fluctuating manner during the entire period of 1982-2013. Compared to other grasslands, the TANPP increasing rate estimated here was lower than that of the global grasslands average and African grasslands, while higher than that of North and South American grasslands. 1995 and 2007 constituted two turning points at which trends in EASR’s TANPP significantly changed. It showed that trend in EASR’s TANPP obviously decreased during 1996 – 2007, and was significantly different from the apparent uptrends during 1982 -1995 and 2008-2013. That was mainly driven by decreasing TANPP in the MPSSR and the TPSSR.(6) For the entire EASR, the interannual variabilities of TANPP were affected by precipitation. The period during January to August was the critical precipitation period (CPP) for the interannual variations of EASR’TANPP. For the 3 subregions, temporal dynamics in TANPP both of the BKSSR and the MPSSR were influenced by precipitation, which was similar to that for the entire EASR. However, CPP were different between the BKSSR and the MPSSR. In the BKSSR, the CPP was the period of from January to September. In the MPSSR, the CPP was the period during May to July. For the TPSSR, the interannual variabilities of TANPP was influenced by temperature. The critical temperature period was the period from June to July. The decreasing of EASR’s TANPP from 1995 to 2007 was generated by decreasing precipitation during May to July in the MPSSR and decreasing temperature during June to July in the TPSSR.(7) The response mechanism of interannual variations of ANPP to climate change in the EASR could be summarized: The cumulative precipitation during the period from January to September (MAP01-09), the cumulative precipitation during the period from May to July (MAP05-07), and the mean temperature during the period from June to July (MAT06-07) were respectively the controlling factors of interannual variations in ANPP for the BKSSR, the MPSSR and the TPSSR. MAP01-09 in the BKSSR could be influenced by Arctic Oscillation in summer (July), MAP05-07 in the MPSSR could be affected by North Atlantic Oscillation during the period from the end of spring to the beginning of summer (May), and MAT06-07 in the TPSSR could be influenced by South China Sea Summer Monsoon (June). In addition, strong ENSO could impact MAP01-09 in the BKSSR, and the South China Sea Summer Monsoon which could affected MAT06-07 in the TPSSR. |
| 中文关键词 | 欧亚大陆草原 ; 地上净初级生产力 ; 时空变异 ; 重要降水（温度）时期 ; 气候变化 |
| 英文关键词 | The Eurasian steppe region (EASR) aboveground net primary productivity (ANPP) spatiotemporal dynamics critical precipitation/temperature period (CPP/CTP) climate change |
| 语种 | 中文 |
| 国家 | 中国 |
| 来源学科分类 | 生态学 |
| 来源机构 | 中国科学院地理科学与资源研究所 |
| 资源类型 | 学位论文 |
| 条目标识符 | http://119.78.100.177/qdio/handle/2XILL650/287863 |
| 推荐引用方式 GB/T 7714 | 焦翠翠. 1982-2013年欧亚大陆草原地上净初级生产力的空间格局和动态变化研究[D]. 中国科学院大学,2017. |
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