区域气候要素的空间模拟精度直接关系到区域气候-植被生态系统的模拟精度。针对这一问题,运用HASM方法对江西省气候要素进行空间模拟,而且与IDW、Kriging、Spline等传统经典方法模拟结果的对比分析表明,HASM方法的模拟精度最高。因此,在10年和30年时间尺度上,运用HASM方法分别完成江西过去60年的平均气温、平均降水和潜在蒸散的空间模拟,并采用Holdridge生命地带(HLZ)模型分别实现了江西不同时间尺度的HLZ生态系统时空变化模拟。模拟结果显示,在1961-2010年期间,20%左右的HLZ生态系统发生了变化,平均气温上升是HLZ生态系统发生变化的主要驱动因子。另外,在江西省出现的7种HLZ生态系统类型中,暖温带湿润森林类型受平均气温上升的影响最大。
The spatial simulation quality of climate change directly affects simulation accuracy of climate-vegetation system at regional level. In this paper, mean annual temperature (MAT) and mean annual precipitation (MAP) of Jiangxi province are simulated by methods of HASM, IDW, Kriging and Spline. The cross-validation results show that HASM has the highest accuracy. The MAT, MAP and mean annual potential evapotranspiration ratio (MAPER) of Jiangxi in the last 60 years are respectively simulated at time resolutions of 10 years and 30 years. The climate-vegetation system of Jiangxi is simulated by running Holdridge life zone (HLZ) model on the simulated climatic surfaces of MAT, MAP and MAPER at the time resolutions of 10 years and 30 years. From 1961 to 2010, both MAT and MAP in Jiangxi went up. The changed lattices of HLZ ecosystems was about 20% in Jiangxi province. The change of HLZ ecosystems was mainly driven by the climate warming. The warm temperate moist forest had the most significant change compared with the other six HLZ ecosystems.
[1] 陈育峰. GIS支持下的全球气候变化对中国生命地带的可能影响研究. 遥感学报, 1997, 1(1): 74-79.
[2] 范泽孟, 岳天祥, 田永中. 中国Holdridge 生命地带平均中心的时空分布及其偏移趋势. 生态学报, 2004, 24(7): 1380-1387.
[3] 范泽孟, 岳天祥. 中国Holdridge生命地带及其多样性的时空变化分析. 地理研究, 2005, 24(1): 121-129.
[4] 杨正宇, 周广胜, 杨奠安. 4 个常用的气候-植被分类模型对中国植被分布模拟的比较研究. 植物生态学报, 2003, 27 (5): 587-593.
[5] 张新时, 杨奠安, 倪文革.植被的PE(可能蒸散)指标与植被-气候分类(三): 几种主要方法与PEP 程序介绍. 植物生态 学与地植物学学报, 1993, 17(2): 97-109.
[6] 林忠辉, 莫兴国, 李宏轩, 等. 中国陆地区域气象要素的空间插值. 地理学报, 2002, 57(1): 47-56.
[7] 李军, 游松财, 黄敬峰. 中国1961-2000 年月平均气温空间插值方法与空间分布. 生态环境, 2006,15(1): 109-114.
[8] Ashraf M, Loftis J C, Hubhard K G. Application of geostatistics to evaluate partial weather station networks. Agricultural and Forest Meteorology. 1997, 84(3-4): 255-271.
[9] Holdridge L R. Determination of world plant fornations from simple climate data. Science, 1947, 105(2727): 367-368.
[10] Nalder I A, Wein R W. Spatial interpolation of climate Normals: test of a new method in the Canadian boreal forest. Agricultural and Forest Meteorology, 1998, 92(4): 211-225.
[11] Price D T, Mckenney D W, Nalder I A, et al. A comparison of two statistical methods for spatial interpolation of Canadian monthly mean climate data. Agricultural and Forest Meteorology, 2000, 101(2-3): 81-94.
[12] Patrick M B, Keller C P. Multivariate interpolation to incorporate thematic surface data using inverse distance weighting(IDW). Computers & Geosciences, 1996, 22(7): 795-799.
[13] Yue T X, Liu J Y, Jrgensen S E, et al. Changes of Holdridge life zone diversity in all of china over half a century. Ecological Modelling. 2001, 144(2-3): 153-162.
[14] Yue T X, Du Z P, Song D J, et al. A new method of surface modeling and its application to DEM construction. Geomorphology, 2007, 91(1-2): 161-172.
[15] Yue T X. Surface Modeling: High Accuracy and High Speed Methods. New York: CRC Press, 2011, 28-38.
