草地对全球气候变化的响应及其碳汇潜势研究

 本研究用综合顺序分类法（ＣＳＣＳ）分析了１９５０－２０００年和２００１－２０５０年期间的草原类型演替及碳汇动态。证明中国草地的碳汇主体依次是冻原和高山草地、温带湿润草地、斯泰普草地和半荒漠草地大类,占中国潜在草地总面积的８５．５２％,年碳汇潜力占中国潜在草地年碳汇潜力的９３．２９％。全球草地的碳汇主体是萨王纳、冻原和高山草地大类,两者的面积和占全球潜在草地总面积的４８．５０％,年碳汇潜力占全球潜在草地年碳汇潜力的７２．２２％。在全球气候暖干化的强（Ａ２ａ）、弱（Ｂ２ａ）情景下,与当前（１９５０－２０００年）情景相比,中国将呈现草地面积减少,林地面积增加的态势;与中国的趋势相反,全球将呈现草地面积增加,林地面积减少的态势。在全球暖干化的Ａ２ａ和Ｂ２ａ模式下,草地年碳汇潜力,中国将分别提升１４．６％和１８．５％,全球将分别提升１７．３％ 和１６．８％。但两者的增长方式不同,全球是以温带湿润草地大类年碳汇潜力大幅增加为特征,而中国是以负增长为特征。我国的暖干化趋势在草地年碳汇潜力上的反映较之全球更强烈。尽管造成全球气候暖干化的自然因素远非人力所能控制,但系统问题只能靠系统综合的办法治理。这是草地工作者当前的使命。     

北京房山区8月份净第一性生产力变化分析

净第一性生产力是评价地表植被状况的重要指标之一,对分析和评价全球和区域生态环境、碳循环等变化具有重要作用.该文借助在CASA模型机理以及区域太阳辐射估算模型基础上建立的区域净第一性生产力估算模型,以房山区为例,分析了北京市郊区19922、001、2004年3年间8月份净第一性生产力的变化.分析结果表明,研究区3年间8月份的NPP分别为152.01、142.83、96.32 g/(m2.月);由于受到各种因素的影响,3年间8月份NPP结构构成不同,1992和2001年均以较高产区的NPP产量最高,其次是高产区和中产区,而2004年则以中产区的NPP产量最高,其次是高产区和低产区,而较高产区的NPP产量最低;1992和2001年各产量水平区的NPP总量在全区NPP总量中的比重,随NPP分区产量水平的提高而逐步提高,较高产区的NPP产量比重分别为:1992年42.26%,2001年37.54%;2004年各产量水平区所占比重变化较大,以中产区最高,占全区NPP总量的42.39%,其次是高产区和低产区,而以较高产区的NPP产量比重最低;通过逐步回归分析可知,在影响研究区NPP变化的各气候因素中,以平均风速、降雨量和实际日照时数影响最为显著,其中尤以降雨量的影响最大.     

草地净第一性生产力估算的研究进展

草地净第一性生产力(NPP)是全球变化与陆地生态系统研究的核心内容之一。草地NPP的模拟方法从站点实测法、统计模型发展到了机理性的过程模型,NPP的站点实测数据为统计模型和过程模型模拟结果提供参考。统计模型通过NPP和温度、降雨等气候因子或者直接与遥感获得的植被指数建立统计关系计算NPP;过程模型从机理上对植物的生物生理过程进行模拟并能够对NPP的影响因子进行分析,主要过程包括了光合作用、生长和维持呼吸、蒸散、氮吸收和释放、光合物质分配与分解,和季相变化等。遥感过程模型通过遥感手段获得地表覆盖状况、植被冠层结构变量值(如LAI)、地表反射率、地表辐射温度及土壤水分状况等作为重要参数应用到模型中,改善了模拟结果的时空精度,成为当前草地生产力模型的主要研究方向。最后对遥感监测草地NPP研究中存在的问题进行了分析并提出了展望。     

Estimation of biomass,net primary production and net ecosystem production of China's forests based on the 1999–2003 National Forest Inventory

Abstract

The National Forest Inventory (NFI) is an important resource for estimating the national carbon (C) balance. Based on the volume, biomass, annual biomass increment and litterfall of different forest types and the 6th NFI in China, the hyperbolic relationships between them were established and net primary production (NPP) and net ecosystem production (NEP) were estimated accordingly. The results showed that the total biomass, NPP and NEP of China's forests were 5.06 Pg C, 0.68 Pg C year^?1 and 0.21 Pg C year^?1, respectively. The area-weighted mean biomass, NPP and NEP were 35.43 Mg C ha^?1, 4.76 Mg C ha^?1 year^?1 and 1.47 Mg C ha^?1 year^?1 and varied from 13.36 to 79.89 Mg C ha^?1, from 2.13 to 9.15 Mg C ha^?1 year^?1 and from ?0.16 to 5.80 Mg C ha^?1 year^?1, respectively. The carbon sequestration was composed mainly of Betula and Populus forest, subtropical evergreen broadleaved forest and subtropical mixed evergreen–deciduous broadleaved forest, whereas Pinus massoniana forest and P. tabulaeformis forest were carbon sources. This study provides a method to calculate the biomass, NPP and NEP of forest ecosystems using the NFI, and may be useful for evaluating terrestrial carbon balance at regional and global levels.     

应用三种模型对浙江省植被净第一性生产力(NPP)的模拟与比较

运用Miami模型、Thornthwaite模型以及综合模型,计算浙江省植被NPP,并与国际生物学计划(IBP)推荐值进行比较,旨在找出最适用于浙江省的一种植被NPP计算模型;分别分析三种模型模拟的植被NPP的年际及年代际变化特征;利用站点的经纬度、DEM及其衍生数据建立多元回归方程对浙江省植被NPP进行空间插值,并分析其空间分布特点。结果显示:(1)综合模型模拟的浙江省植被NPP与国际生物学计划(IBP)推荐值最接近,为952.722～1376.971g.m-2.a-1,并且NPP随时间呈波动上升趋势;20世纪60-70年代植被NPP增幅最大,为33.31g.m-2.a-1;(2)对于三种模型,北部嘉兴市的植被NPP最小,南部温州市的植被NPP最大;植被NPP的空间分布形态一致,全省范围内均表现为西北低、东南高;(3)比较得出,综合模型在模拟计算浙江省NPP时更具有实用性。     

Comparative Assessment of Grassland NPP Dynamics in Response to Climate Change in China,North America,Europe and Australia from 1981 to 2010

Although climate change has been modifying grassland ecosystems for a long time, few studies on grassland ecosystems have focused on large‐scale responses to climate change. Hence, grassland net primary productivity (NPP) from 1981 to 2010, as well as its variations in China, North America, Europe and Australia, was assessed and compared using a synthetic model in this study. Subsequently, the correlations between the NPP of each grassland type and climate factors were evaluated to reveal the responses of grassland eco‐systems to climate change. The results showed that North America, which has the largest area of grassland ecosystems, exhibits maximum grassland NPP of 4225.30 ± 215.43 Tg DW year^?1, whereas Europe, which has the least area of grassland ecosystems among the four regions, exhibits minimum grassland NPP of 928.95 ± 24.68 Tg DW year^?1. Grassland NPP presented an increasing trend in China and Australia, but decreasing in Europe and North America from 1981 to 2010. In addition, grassland NPP is positively correlated with mean annual precipitation, but demonstrates notable differences with mean annual temperature. In conclusion, climate change has a significant role in explaining the spatiotemporal patterns of and the variations in grassland NPP in the four regions.     

Estimating regional forest productivity and water yield using an ecosystem model linked to a GIS

We used the PnET-II model of forest carbon and water balances to estimate regional forest productivity and runoff for the northeastern United States. The model was run at 30 arc sec resolution (approximately 1 km) in conjunction with a Geographic Information System that contained monthly climate data and a satellite-derived land cover map. Predicted net primary production (NPP) ranged from 700 to 1450 g m² yr¹ with a regional mean of 1084 g m² yr¹. Validation at a number of locations within the region showed close agreement between predicted and observed values. Disagreement at two sites was proportional to differences between measured foliar N concentrations and values used in the model. Predicted runoff ranged from 24 to 150 cm yr¹with a regional mean of 63 cm yr¹. Predictions agreed well with observed values from U.S. Geologic Survey watersheds across the region although there was a slight bias towards overprediction at high elevations and underprediction at lower elevations.Spatial patterns in NPP followed patterns of precipitation and growing degree days, depending on the degree of predicted water versus energy limitation within each forest type. Randomized sensitivity analyses indicated that NPP within hardwood and pine forests was limited by variables controlling water availability (precipitation and soil water holding capacity) to a greater extent than foliar nitrogen, suggesting greater limitations by water than nitrogen for these forest types. In contrast, spruce-fir NPP was not sensitive to water availability and was highly sensitivity to foliar N, indicating greater limitation by available nitrogen. Although more work is needed to fully understand the relative importance of water versus nitrogen limitation in northeastern forests, these results suggests that spatial patterns of NPP for hardwoods and pines can be largely captured using currently available data sets, while substantial uncertainties exist for spruce-fir.     

Estimation of spatial and temporal changes in net primary production based on Carnegie Ames Stanford Approach (CASA) model in semi-arid rangelands of SemiromCounty,Iran

Net primary production (NPP) is an indicator of rangeland ecosystem function. This research assessed the potential of the Carnegie Ames Stanford Approach (CASA) model for estimating NPP and its spatial and temporal changes in semi-arid rangelands of Semirom County, Iran. Using CASA model, we estimated the NPP values based on monthly climate data and the normalized difference vegetation index (NDVI) obtained from the MODIS sensor. Regression analysis was then applied to compare the estimated production data with observed production data. The spatial and temporal changes in NPP and light utilization efficiency (LUE) were investigated in different rangeland vegetation types. The standardized precipitation index (SPI) was also calculated at different time scales and the correlation of SPI with NPP changes was determined. The results indicated that the estimated NPP values varied from 0.00 to 74.48 g C/(m²?a). The observed and estimated NPP values had different correlations, depending on rangeland conditions and vegetation types. The highest and lowest correlations were respectively observed in Astragalus spp.-Agropyronspp. rangeland (R²=0.75) with good condition and Gundeliaspp.-Cousiniaspp. rangeland (R²=0.36) with poor and very poor conditions. The maximum and minimum LUE values were found in Astragalus spp.-Agropyronspp. rangeland (0.117 g C/MJ) with good condition and annual grasses-annual forbs rangeland (0.010 g C/MJ), respectively. According to the correlations between SPI and NPP changes, the effects of drought periods on NPP depended on vegetation types and rangeland conditions. Annual plants had the highest drought sensitivity while shrubs exhibited the lowest drought sensitivity. The positive effects of wet periods on NPP were less evident in degraded areas where the destructive effects of drought were more prominent. Therefore, determining vegetation types and rangeland conditions is essential in NPP estimation. The findings of this study confirmed the potential of the CASA for estimating rangeland production. Therefore, the model output maps can be used to evaluate, monitor and optimize rangeland management in semi-arid rangelands of Iran where MODIS NPP products are not available.     

伊犁地区土地覆被变化及其对植被碳储量的影响

以伊犁地区为研究对象,以2005、2010年和2015年的土地覆被类型数据和植被功能型分类方案为依据,并利用植被固碳模型,分析了近10 a伊犁地区土地覆被变化特征及其对植被碳储量的影响。结果表明:1）伊犁地区土地覆被变化主要表现为农业用地、林地和建筑用地呈增加趋势,年变化率分别为0.007%、0.031%和0.001%,草地和灌木呈减少趋势,年变化率分别为0.003%和0.1%。2）10 a增加农业用地的面积为923.9 km²,主要的转化来源为草地,占转化总量的83.9%,同时也有78.8%的农业用地转化为草地。3）由于土地覆被的变化、植被净初级生产力以及不同土地覆被类型之间碳转化系数的影响,导致植被的碳储量总体上减少了2.48×10⁵ t。从整体上来看,伊犁地区的农业用地和草地的变化最为显著,土地覆被的变化导致的植被碳储量整体呈减少的趋势。由此可以得出,近10 a伊犁地区草地和农业用地的变化是影响植被碳储量的重要因素。     

太行山区植被NPP时空变化特征及其驱动力分析

本文基于2000—2014年MODIS NPP数据,结合同期土地利用变化、气温、降水和DEM数据,运用趋势分析法、相关系数法及分区统计法等方法,研究了太行山区2000—2014年植被NPP时空变化特征,分析了气温、降水等气候因素和人为因素对植被NPP变化的影响,为太行山区植被资源管理及生态环境调控提供参考。研究结果表明:(1)太行山区植被NPP多年平均值为284.0 g(C)·m~(-2)·a~(-1),耕地、林地和草地的NPP均值分别为302.5 g(C)·m~(-2)·a~(-1)、258.1 g(C)·m~(-2)·a~(-1)、286.5 g(C)·m~(-2)·a~(-1)。(2)2000—2014年太行山区植被NPP整体呈上升趋势,但大部分植被NPP变化未达到显著水平;16.17%的植被NPP显著或极显著升高,主要分布在太行山区西侧;0.88%的植被NPP显著或极显著降低,零散分布在研究区内。(3)不同植被类型NPP变化速率为草地耕地林地。(4)基于区域平均计算,太行山区植被NPP与降水显著正相关(P0.05),与气温负相关(P0.05)。基于像元计算,植被NPP与降水显著或极显著正相关区面积比例为23.82%,主要分布在太行山区北段,几乎没有显著负相关区;植被NPP与气温显著或极显著负相关区面积比例为8.42%,主要分布在太行山区西侧,显著或极显著正相关区面积比例为0.81%,主要分布在太行山区最北端。(5)研究期内气候因子对植被NPP的升高整体上表现为促进作用,而人为因素主要表现为抑制作用。太行山区生态环境保护仍应以减少人为干扰为主。