干旱、半干旱区约占全球陆地表面的41%（Reynolds et al.,2007）,是陆地生态系统的重要组成部分。但是,由于干旱荒漠地区土壤水分含量低,而且降水稀少,因此不能支撑大面积、连续分布的植被（Schulze et al.,2005）,植物群落通常较为单一...干旱、半干旱区约占全球陆地表面的41%（Reynolds et al.,2007）,是陆地生态系统的重要组成部分。但是,由于干旱荒漠地区土壤水分含量低,而且降水稀少,因此不能支撑大面积、连续分布的植被（Schulze et al.,2005）,植物群落通常较为单一,不同类型灌木的斑块状分布格局是荒漠区植被的显著特征（Whitford,2002）。昆虫多样性是全球生物多样性的重要组成部分（Lewinsohn et al.,2008）,而其中的荒漠昆虫是随着荒漠的出现,适应环境改变演化而来的一支特殊旱生昆虫类群（黄人鑫等,2005）,是荒漠生态系统的重要组成部分。展开更多
In order to get the spatial grid data of monthly precipitation and monthly average temperature of Sanjiangyuan area, the Co-Kriging (COK) and thin plate smoothing splines(TPS) interpolation methods were applied by usi...In order to get the spatial grid data of monthly precipitation and monthly average temperature of Sanjiangyuan area, the Co-Kriging (COK) and thin plate smoothing splines(TPS) interpolation methods were applied by using the climate data during 1971-2000 of 58 meteorological stations around Qinghai Province and the 3 arc-second digital elevation model (DEM) data. The performance was evaluated by the smallest statistical errors by general cross validation (GCV). Root-mean-squared predicted errors (RMSE) and mean absolute errors (MAE) were used to compare the performance of the two methods. The results showed that: 1) After combing covariates into the models, both methods performed better; 2) The performance of TPS was significantly better than COK: for monthly average temperature, the RMSE derived from TPS was 69.48% higher than COK, as MAE increased by 70.56%. And for monthly precipitation, the RMSE derived from TPS was 28.07% higher than COK, as MAE increased by 29.06%.展开更多
文摘干旱、半干旱区约占全球陆地表面的41%（Reynolds et al.,2007）,是陆地生态系统的重要组成部分。但是,由于干旱荒漠地区土壤水分含量低,而且降水稀少,因此不能支撑大面积、连续分布的植被（Schulze et al.,2005）,植物群落通常较为单一,不同类型灌木的斑块状分布格局是荒漠区植被的显著特征（Whitford,2002）。昆虫多样性是全球生物多样性的重要组成部分（Lewinsohn et al.,2008）,而其中的荒漠昆虫是随着荒漠的出现,适应环境改变演化而来的一支特殊旱生昆虫类群（黄人鑫等,2005）,是荒漠生态系统的重要组成部分。
基金Supported by Forestry Science and Technology Support Project (2008BADB0B0203)National Technology Support Project (2007BAC03A08-5)
文摘In order to get the spatial grid data of monthly precipitation and monthly average temperature of Sanjiangyuan area, the Co-Kriging (COK) and thin plate smoothing splines(TPS) interpolation methods were applied by using the climate data during 1971-2000 of 58 meteorological stations around Qinghai Province and the 3 arc-second digital elevation model (DEM) data. The performance was evaluated by the smallest statistical errors by general cross validation (GCV). Root-mean-squared predicted errors (RMSE) and mean absolute errors (MAE) were used to compare the performance of the two methods. The results showed that: 1) After combing covariates into the models, both methods performed better; 2) The performance of TPS was significantly better than COK: for monthly average temperature, the RMSE derived from TPS was 69.48% higher than COK, as MAE increased by 70.56%. And for monthly precipitation, the RMSE derived from TPS was 28.07% higher than COK, as MAE increased by 29.06%.
