Grassland is the important component of the terrestrial ecosystems. Estimating net primary productivity （NPP） of grassland ecosystem has been a central focus in global climate change researches. To simulate the gras...Grassland is the important component of the terrestrial ecosystems. Estimating net primary productivity （NPP） of grassland ecosystem has been a central focus in global climate change researches. To simulate the grassland NPP in southern China, we built a new climate productivity model, and validated the model with the measured data from different years in the past. The results showed that there was a logarithmic correlation between the grassland NPP and the mean annual temperature, and there was a linear positive correlation between the grassland NPP and the annual precipitation in southern China. Al these results reached a very signiifcant level （P〈0.01）. There was a good correlation between the simulated and the measured NPP, withR2 of 0.8027, reaching the very signiifcant level. Meanwhile, both root mean square errors （RMSE） and relative root-mean-square errors （RRMSE） stayed at a relatively low level, showing that the simulation results of the model were reliable. The NPP values in the study area had a decreasing trend from east to west and from south to north, and the mean NPP was 471.62 g C m？2 from 2000 to 2011. Additionaly, there was a rising trend year by year for the mean annual NPP of southern grassland and the tilt rate of the mean annual NPP was 3.49 g C m？2 yr？1 in recent 12 years. The above results provided a new method for grassland NPP estimation in southern China.展开更多
利用国产卫星高分一号卫星数据评估其植被第一生产力(NPP)的潜力,对植被指数取值范围、光能利用率、水分指数等参数进行修订,建立适合高分卫星数据的光能利用率模型,反演小尺度草地生态系统的生产力,利用野外观测数据对反演结果进行验证...利用国产卫星高分一号卫星数据评估其植被第一生产力(NPP)的潜力,对植被指数取值范围、光能利用率、水分指数等参数进行修订,建立适合高分卫星数据的光能利用率模型,反演小尺度草地生态系统的生产力,利用野外观测数据对反演结果进行验证.模型模拟的数值与实测值的拟合度达到0.94,均方差为20.59 g C/(m2·a),并进一步将该结果与该区域同类型研究进行类比分析.结果表明,该模型对小尺度草地NPP估算可行,减少了工作量,为国产高分数据进行草地NPP、尤其煤矿区草地环境的监测提供了可行的技术方法,从而推动国产卫星在该地区的应用.展开更多
植被净初级生产力(net primary productivity, NPP)在全球气候变化及碳循环研究中扮演着重要的角色,精准快速的估算NPP对评估区域生态系统承载力以及合理利用自然资源具有重要的意义。利用2011-2014年甘南地面实测草地地上生物量(aboveg...植被净初级生产力(net primary productivity, NPP)在全球气候变化及碳循环研究中扮演着重要的角色,精准快速的估算NPP对评估区域生态系统承载力以及合理利用自然资源具有重要的意义。利用2011-2014年甘南地面实测草地地上生物量(aboveground biomass, AGB)数据和根冠比系数计算的草地NPP数据,分别验证了MOD17A3 NPP产品和基于CASA(Carnegie-Ames-Stanford approach)模型估算的草地NPP的精度,分析了2000-2016年甘南地区草地NPP的时空动态变化。结果表明:基于CASA模型模拟的草地NPP精度整体上高于MOD17A3 NPP产品的精度,其均方根误差(root mean square error, RMSE)较MOD17A3 NPP小9.94 g C·m^-2;CASA模型分析的甘南地区草地NPP总体上呈现由西南向东北逐渐减少的趋势;对不同草地类型而言,沼泽类的平均NPP最高(469.07 g C·m^-2),温性草原类最低(324.18 g C·m^-2),而占研究区草地总面积比例较大的高寒草甸类和高寒灌丛草甸类草地的平均NPP分别为449.22和465.27 g C·m^-2;2000-2016年间,甘南地区大部分草地NPP稳定不变,其面积占研究区草地总面积的75.31%,NPP呈增加趋势的区域占草地面积的22.63%,而NPP呈减少趋势的区域占比最小,仅为2.06%。以上研究结果表明CASA模型在高寒地区草地NPP评估、草地资源合理利用与管理方面具有重要的应用价值。展开更多
文摘植被净初级生产力(net primary productivity,NPP)及其对气候变化的响应研究是全球变化的核心内容之一。通过改进的光能利用率模型(CASA模型),利用MODIS NDVI数据、土地覆盖分类数据、气象数据等,逐像元模拟2001-2010年内蒙古草地生态系统NPP的时空变化,分析其对气候因子变化的响应关系。结果表明,1)2001-2010年内蒙古草地多年平均NPP为281.3 g C/(m2.a),空间分布呈由西南向东北递增的趋势,草甸草原、典型草原和荒漠草原平均NPP分别为431.8,288.7和123.5 g C/(m2.a);2)2001-2010年间内蒙古草地NPP总体上呈上升趋势。NPP上升趋势最明显的草地主要分布在毛乌素沙地、浑善达克沙地、科尔沁沙地、呼伦贝尔盟和大兴安岭南麓地区,而下降趋势最明显的草地主要分布在阴山山脉和锡林郭勒盟中部的典型草原区;3)总体而言,降水量是内蒙古草地净初级生产力的主要影响因素。草甸草原NPP与降水量、温度的关系均很密切,而且与温度的相关性更强;典型草原和荒漠草原NPP则主要受降水量控制,其中荒漠草原NPP与降水量的关系更密切。
基金funded by the Priority Academic Program Development of Jiangsu Higher Education Institutions, China (PAPD)the Science and Technology Innovation Project Fund of Chinese Academy of Agricultural Sciences (2015)
文摘Grassland is the important component of the terrestrial ecosystems. Estimating net primary productivity （NPP） of grassland ecosystem has been a central focus in global climate change researches. To simulate the grassland NPP in southern China, we built a new climate productivity model, and validated the model with the measured data from different years in the past. The results showed that there was a logarithmic correlation between the grassland NPP and the mean annual temperature, and there was a linear positive correlation between the grassland NPP and the annual precipitation in southern China. Al these results reached a very signiifcant level （P〈0.01）. There was a good correlation between the simulated and the measured NPP, withR2 of 0.8027, reaching the very signiifcant level. Meanwhile, both root mean square errors （RMSE） and relative root-mean-square errors （RRMSE） stayed at a relatively low level, showing that the simulation results of the model were reliable. The NPP values in the study area had a decreasing trend from east to west and from south to north, and the mean NPP was 471.62 g C m？2 from 2000 to 2011. Additionaly, there was a rising trend year by year for the mean annual NPP of southern grassland and the tilt rate of the mean annual NPP was 3.49 g C m？2 yr？1 in recent 12 years. The above results provided a new method for grassland NPP estimation in southern China.
文摘利用国产卫星高分一号卫星数据评估其植被第一生产力(NPP)的潜力,对植被指数取值范围、光能利用率、水分指数等参数进行修订,建立适合高分卫星数据的光能利用率模型,反演小尺度草地生态系统的生产力,利用野外观测数据对反演结果进行验证.模型模拟的数值与实测值的拟合度达到0.94,均方差为20.59 g C/(m2·a),并进一步将该结果与该区域同类型研究进行类比分析.结果表明,该模型对小尺度草地NPP估算可行,减少了工作量,为国产高分数据进行草地NPP、尤其煤矿区草地环境的监测提供了可行的技术方法,从而推动国产卫星在该地区的应用.
文摘植被净初级生产力(net primary productivity, NPP)在全球气候变化及碳循环研究中扮演着重要的角色,精准快速的估算NPP对评估区域生态系统承载力以及合理利用自然资源具有重要的意义。利用2011-2014年甘南地面实测草地地上生物量(aboveground biomass, AGB)数据和根冠比系数计算的草地NPP数据,分别验证了MOD17A3 NPP产品和基于CASA(Carnegie-Ames-Stanford approach)模型估算的草地NPP的精度,分析了2000-2016年甘南地区草地NPP的时空动态变化。结果表明:基于CASA模型模拟的草地NPP精度整体上高于MOD17A3 NPP产品的精度,其均方根误差(root mean square error, RMSE)较MOD17A3 NPP小9.94 g C·m^-2;CASA模型分析的甘南地区草地NPP总体上呈现由西南向东北逐渐减少的趋势;对不同草地类型而言,沼泽类的平均NPP最高(469.07 g C·m^-2),温性草原类最低(324.18 g C·m^-2),而占研究区草地总面积比例较大的高寒草甸类和高寒灌丛草甸类草地的平均NPP分别为449.22和465.27 g C·m^-2;2000-2016年间,甘南地区大部分草地NPP稳定不变,其面积占研究区草地总面积的75.31%,NPP呈增加趋势的区域占草地面积的22.63%,而NPP呈减少趋势的区域占比最小,仅为2.06%。以上研究结果表明CASA模型在高寒地区草地NPP评估、草地资源合理利用与管理方面具有重要的应用价值。
