黄淮海平原耕地转移对植被碳储量的影响

应用GLO-PEM模型和1988年NOAA/AVHRR遥感数据,估算了黄淮海平原植被净初级生产力(NPP),并根据NPP和植被凋落物产生量计算了不同土地利用类型的植被碳密度。通过对1988年与2000年土地利用图的叠置分析,统计了耕地与其他土地利用类型之间的转移量,并估算了耕地转移对植被碳储量的影响。研究发现,耕地转移对植被碳储量变化的影响在不同区域与不同土地利用类型上存在显著差异。1988~2000年间,耕地转移导致全区植被碳储量下降了0.24%,其中耕地转为建设用地是植被碳储量减少的主要原因。这一研究结论为正确把握耕地转移对区域植被碳储量的影响,并据此制订碳汇管理措施具有重要的参考价值。     

中国陆地净初级生产力的季节变化研究

了解不同季节陆地净初级生产力(NPP)的变化及与气候的相互关系以及在不同地类的差异对深刻理解我国陆地生态系统对全球气候变化的响应和陆地碳循环研究具有重要意义。本文使用1981～2000年间GLO-PEM模型模拟的我国陆地NPP数据和同期气温、降水以及土地利用数据, 研究不同季节我国陆地植被NPP的变化。结果表明,在1981～2000年期间,四个季节的NPP都呈显著增加趋势,春季是NPP增加速率最快的季节,夏季是NPP增加量最大的季节。耕地在春、夏和秋季NPP增长和增长率最高,林地冬季NPP增长最多而水域冬季NPP增长率最高。夏季NPP增长最高的区域分布于我国东部的多数地区、内蒙古东部、四川盆地、贵州东部、藏南和新疆西部;夏季NPP降低最多的区域分布于在呼伦贝尔高原、鄂尔多斯高原、黄土高原、青藏高原东部和新疆西北部。     

土地利用和气候变化对区域净初级生产力的影响

应用以遥感观测数据驱动的GLO-PEM模式模拟估计的中国北方20年的NPP数据同其20年气候数据结合,同时利用通过遥感宏观调查所得的两期土地利用数据,分析20年气候和土地利用变化对区域净初级生产力 (Net Primary Productivity,NPP) 的影响的时空特征。分析结果表明,20年来研究区域年均温度显著增加 (年均增温0.064 ^oC),年降水量明显减少 (年降水减少率为1.49 mm/年),NPP以减少趋势为主 (年减少率6.9 TgC)。研究区域NPP的变化受旬 (月) 均温和旬 (月) 降水量和季节温度和季节降水的变化影响显著。季节NPP同季节降水和温度的相关性在空间上同植被覆盖表现出高度的一致性,其相关系数大小随着不同植被覆盖类型变化而变化。通过分析可见,就整个研究区来说,发生土地利用变化的区域仅占整个研究区域的5.45%, 气候对整个研究区域NPP的影响占主导地位 (占了总影响量的90%);土地利用发生区域土地利用的作用占了绝对地位,土地利用的影响占了约97%。整个研究区域近20年来因为降水明显减少,温度显著升高,导致NPP明显下降,在两期土地利用间隔时间段内 (约10年) 因气候影响NPP减少了78 (±0.6) TgC。因为土地利用的变化导致NPP减少9 (±0.2) TgC。气候和土地利用共同作用是研究区域的NPP减少87 (±0.8) TgC。     

土地利用和气候变化对区域净初级生产力影响

1IntroductionThe global change caused by the continuous increasing concentration of atmospheric greenhouse gases has threatened the existence of human beings, and the importance of carbon dioxide emissions as a major environmental issue of international concern has grown substantially in the world (IPCC, 2000). At the same time, the Kyoto Protocol, the first and only realistic plan for achieving a worldwide reduction in greenhouse gas emissions, has been passed. Since there are many uncertai…     

Impacts of land use and climate change on regional net primary productivity

Combined with recent historical climate data and two periods of land use data sets from remote sensing data, we test the net primary productivity (NPP) data sets in North China modelled by the satellite data-driven Global Production Efficiency Model (GLO-PEM) for detecting the widespread spatial and temporal characteristics of the impacts of climate and land use change on the regional NPP. Our results show that over the past 20 years, the mean annual temperature in the study region has remarkably increased by more than 0.064 oC, but over the same period, there has been a 1.49 mm decrease in annual precipitation and decrease in NPP by an annual rate of 6.9 TgC. The NPP changes in the study region were greatly affected by the average temperature and precipitation by ten-day periods as well as the seasonal temperature and precipitation in the study region. The correlation between seasonal NPP and seasonal precipitation and temperature is highly consistent with land cover spatially, and the correlation coefficient changes with the changes of vegetation types. The analysis reveals that the related areas in land use change only take up 5.45% of the whole studied region, so the climate changes dominate the impacts on the NPP in the whole study region (90% of the total). However, land use plays an absolute dominative role in areas with land cover changes, accounting for 97% of the total. From 1981 to 2000, the NPP in the whole study region remarkably reduced due to obvious precipitation decrease and temperature rise. Between two periods of land use (about 10 years), the changes in climate are predicted to promote a decrease in NPP by 78 (±0.6) TgC, and integrated impacts of climate changes and land use to promote a decrease in NPP by 87(±0.8) TgC.