基于CSCS改进CASA模型的中国草地净初级生产力模拟

将草原综合顺序分类系统（CSCS）中的热量指标（∑θ）和湿润度指标（K）引入CASA模型。利用该模型模拟了2004-2008年中国41个草地类的净初级生产力（NPP）,并分析了其时空变化和不同草地类NPP变化。结果表明：2004-2008年中国草地NPP模拟平均值与实测平均值分别为503.8 g·m^-2·a^-1和567.3 g·m^-2·a^-1,两者较为接近。各类草地的平均误差和平均相对误差均值分别为4.85 g·m^-2·a^-1和7.6%。草地NPP的实测值和模拟值相关性较好。改进CASA模型模拟值比Miami和Thornthwaite Memorial模型模拟值更接近实测值。NPP空间分布呈东高西低,南高北低,从西北向东南逐渐增加的趋势,体现了K和∑θ的水平和垂直地带性分布规律。2004-2008年中国草地NPP总体呈现增加趋势,其总量增加了23.0%。草地NPP年均值在不同植被类型中差异显著,分布规律与CSCS划分草地类的K和∑θ密切相关。总之,改进后的CASA模型模拟精度较高,实现了草地NPP模拟与草地分类的相互关联。     

青藏高原高寒草地净初级生产力(NPP)时空分异

基于1982-2009 年间的遥感数据和野外台站生态实测数据,利用遥感生产力模型(CASA模型) 估算青藏高原高寒草地植被净初级生产力(NPP),分别从地带属性(自然地带、海拔高程、经纬度)、流域、行政区域(县级) 等方面对其时空变化过程进行分析,阐述了1982 年以来青藏高原高寒草地植被NPP的时空格局与变化特征。结果表明:① 青藏高原高寒草地NPP多年均值的空间分布表现为由东南向西北逐渐递减;1982-2009 年间,青藏高原高寒草地的年均总NPP为177.2×10¹² gC·yr^-1,单位面积年均植被NPP为120.8 gC·m^-2yr^-1;② 研究时段内,青藏高原高寒草地年均NPP 在112.6~129.9 gC·m^-2yr^-1 间,呈波动上升的趋势,增幅为13.3%;NPP 增加的草地占草地总面积的32.56%、减少的占5.55%;③ 青藏高原多数自然地带内的NPP呈增加趋势,仅阿里山地半荒漠、荒漠地带NPP呈轻微减低趋势,其中高寒灌丛草甸地带和草原地带的NPP增长幅度明显大于高寒荒漠地带;年均NPP增加面积比随着海拔升高呈现"升高—稳定—降低"的特点,而降低面积比则呈现"降低—稳定—升高"的特征;④ 各主要流域草地年均植被NPP均呈现增长趋势,其中黄河流域增长趋势显著且增幅最大。植被NPP和盖度及生长季时空变化显示,青藏高原高寒草地生态系统健康状况总体改善局部恶化。     

基于改进土壤冻融水循环的Biome-BGC模型估算青藏高原草地NPP

Biome-BGC模型被广泛用于估算植被净初级生产力（Net Primary Productivity, NPP）,但是该模型未考虑冻土区土壤冻融水循环过程对植被生长的影响。本文基于Biome-BGC模型,改进冻土区活动层土壤冻融水循环,估算了2000—2018年青藏高原高寒草地NPP。通过比较原模型和改进后的模型,并对NPP模拟结果的时空特征进行了分析,结果表明：① 增加冻融循环提高了NPP估算精度,青藏高原草地NPP均值由114.68 gC/(m²·a)提高到128.02 gC/(m²·a)。② 原模型和改进后NPP的空间分布差异较大,时间变化趋势差异不明显。③ 青藏高原草地NPP总量为253.83 TgC/a,呈东南向西北递减的空间格局,年均增速为0.21gC/(m²·a)（P=0.023）,显著增加的占17.85%,主要分布在羌塘高寒草原地带的大部分地区和藏南山地灌木草原地带的西部。④ 该冻融水循环改进方法简单可靠,具有在其他多年冻土区推广的价值。     

基于植被盖度和高度的不同退化程度高寒草地地上生物量估算

由于气候变化和不合理的人类活动，20世纪80年代以来青藏高原高寒草地发生严重退化。地上生物量是评价草地退化的直观指标。通常采用植被盖度和高度来估算草地地上生物量，但草地退化后，植被盖度和高度与地上生物量之间的关系是否会发生变化目前还不清楚，这影响着退化草地生物量估算的精度。通过多元回归分析研究了青藏高原中部和东北部高寒草甸、高寒草原在不同退化程度下植被盖度和高度与地上生物量的关系。结果表明：（1）高寒草甸与高寒草原地上生物量整体上及不同退化阶段都没有显著差异（P>0.05）。（2）随着退化程度的加剧植被盖度和高度对地上生物量的影响也发生改变，体现在未退化阶段地上生物量主要受植被高度影响，退化后主要受植被盖度影响。（3）无论是高寒草甸还是高寒草原分退化程度的回归模型估算结果都较不分退化程度模型估算的生物量更接近实测值。我们建议在退化高寒草地研究中采用盖度和高度估算生物量时，根据退化阶段采用不同的估算模型。     

俄罗斯布里亚特共和国植被NPP时空分布格局及其对气候变化的响应

研究利用遥感和气象数据以及改进后的CASA模型（生物温度代替月均温）,估算俄罗斯布里亚特共和国2000-2008年的植被NPP,并验证模型的精度,分析该地区植被NPP的时空分布格局及其对气候变化的响应规律。研究结果表明：改进后的CASA模型具较高精度,可运用于布里亚特共和国植被NPP的估算。时间上,植被NPP年际上呈现为在波动中上升的趋势,月份上表现为先升后降的单峰变化趋势;空间上,植被NPP呈现出随经度的增加而增大,随纬度的增加而减小,由西南到东北逐渐递增的分布格局;不同植被类型的NPP从大到小依此为：草地、沼泽林〉森林〉森林、草原〉稀树草原〉高山植被。该地区植被NPP的变化主要受气温和降水量变化的作用。     

基于MODIS的青海草地产草量变化遥感分析

青海省属于全国四大牧区之一，及时监测草地植被长势、准确估算牧草产量对青海牧区可持续发展与生态保护具有重要意义。草地产草量遥感估算主要基于植被指数与地面实测数据的统计关系，但是估算涉及植被指数、统计模型和建模指标等因素，不同组合建立的估算模型的精度不同。本文基于青海省MODIS数据与地面实测产草量数据，选择了6种植被指数（NDVI、EVI、RVI、DVI、RDVI、MSAVI）、5种统计模型（简单线性模型、二次多项式模型、幂函数模型、指数函数模型、对数函数模型）以及3种建模指标（植被指数年度最大值VI_max、植被指数生长季累积值VI_season-cum、植被指数年度累积值VI_annual-cum），研究不同组合下估算模型的精度差异，并从中选出最优产草量估算模型，用于估算青海省2015年和2016年的产草量。结果表明：（1）6种植被指数中，基于NDVI的产草量估算精度最高；非线性模型的估算精度高于线性模型，尤其是指数模型，适用于大多数草地类型产草量的估算；基于NDVI年度最大值的估算模型对大多数草地类型都具有最高的决定系数（R²）。（2）从干重来看，高产草量区（>1 200 kg·hm^-2）主要位于青海东部的高寒草原，中等产草量区（600~1 200 kg·hm^-2）位于青海南部和东部的高寒草原和禾草草原，低产草量区（<600 kg·hm^-2）位于青海西部和北部的高寒草甸、高寒草原、高寒荒漠和盐生草甸。（3）与2015年相比，2016年青海省干草总产量减少31.60×10⁴ t，减幅为1.36%。其中，禾草草原和高寒草甸的减产幅度最大，而荒漠草原和盐生草甸的产量则有所增加。本文可为草地产草量遥感估算的研究和实践提供参考。     

不同草地类型净初级生产力(NPP)模拟及其敏感性分析

气候变化问题作为人类社会可持续发展面临的重大挑战,受到国际社会越来越强烈的关注。全球气候变化深刻影响着草地生态系统,定量评估区域和不同类型草地生态系统的生产力,研究其对气候变化的敏感性可以为草地生态系统适应未来气候变化提供基础数据和理论依据。草原综合顺序分类系统(CSCS)将天然草原分为42类(其中中国包含41类),并将其聚合为10个类组。研究利用改进Carnegie-Ames-Stanford Approach(CASA)模型模拟分析中国天然草地2004—2008年的净初级生产力(NPP)并进行系统聚类,分析了草地NPP与影响因子的相关性和敏感程度。结果表明:2004—2008年中国10个草地类组年均NPP均呈现增长趋势,其中亚热带森林草地增长最快,增长率达38.2%。温带湿润草地增长最慢,增长率为14.3%。通过聚类分析将中国41类草原的年均NPP分为3类:第1类NPP值较小,其湿润度级较低,而热量级较高;第2类NPP值较大,其热量级和湿润度级均较高,水热比适宜植被的生长;其余为第3类,其NPP值介于上述两者之间。可见,不同草地类型NPP分布规律与CSCS划分草地类型的湿润度级和热量级密切相关。草地年均NPP与>0℃年积温(Σθ)、降水量、湿润度(K)和NDVI的相关性强,与太阳辐射的相关性弱。草地类组NPP平均值对NDVI最敏感,其次为Σθ、K和降水量,敏感性最弱的为太阳辐射。草地NPP对CSCS量化分类的标准Σθ和K较为敏感,改进CASA模型在一定程度上实现了CSCS与草地生产力的耦合。     

青海省草地资源净初级生产力遥感监测

在研究特定区域的草地光能利用率和环境影响因素典型特点的基础上,建立基于光能利用率的草地NPP遥感估算模型,模拟并分析2006年青海省草地FPAR、光能利用率、NPP的空间分布和季相变化特征。研究结果表明,2006年青海省草地净初级生产力平均值为173.28 gC/(m2.a)。青海省东南部、南部和青海湖周围三个地区,是青海省草地NPP较高的区域。不同草地类型的NPP存在差异,高覆盖度草地的单位面积平均NPP为193.82 gC/(m2.a),中覆盖度草地NPP为157.14 gC/(m2.a),低覆盖度草地NPP为121.08 gC/(m2.a)。     

利用MODIS影像和气候数据模拟青藏高原草地地上生物量（英文）

精确量化高寒区域的草地地上生物量在精确量化全球碳循环方面起着非常重要的作用。本研究利用月尺度的归一化植被指数、增强型植被指数、平均空气温度、≥5℃积温、总降水、降水积温比模拟了青藏高原高寒草地地上生物量。本研究对比分析了三种多重逐步回归模型,即地上生物量与归一化植被指数和增强型植被指数的逐步回归模型,地上生物量与空气温度、积温、降水和降水积温比的逐步回归模型,地上生物量与归一化植被指数、增强型植被指数、空气温度、积温、降水和降水积温比的逐步回归模型。结果表明,在高寒草甸,归一化植被指数模拟的地上生物量与观测的地上生物量间的平均绝对误差和均方根误差分别为31.05 g m~(-2)和44.12 g m~(-2);在高寒草原,归一化植被指数模拟的地上生物量与观测的地上生物量间的平均绝对误差和均方根误差分别为95.43 g m~(-2)和131.58 g m~(-2)。在高寒草原,积温模拟的地上生物量与观测的地上生物量间的平均绝对误差和均方根误差分别为33.61g m~(-2)和48.04 g m~(-2)。在高寒草甸,植被指数和气象数据模拟的地上生物量与观测的地上生物量间的平均绝对误差和均方根误差分别为28.09 g m~(-2)和42.71 g m~(-2);在高寒草原,植被指数和气象数据模拟的地上生物量与观测的地上生物量间的平均绝对误差和均方根误差分别为35.86 g m~(-2)和47.94 g m~(-2)。因此,植被指数和气候数据同时参与的逐步回归模型比植被指数或气候数据单独参与的逐步回归模型的精度高;不同高寒草地类型的回归模型精度不同。     

气候变化对中亚草地生态系统碳循环的影响研究

准确评估草地生产力、碳源/碳汇功能,分析气候变化对草地生态系统碳循环的影响,对于草地资源的合理开发和有效保护至关重要。选取对气候变化以及人类干扰高度敏感的中亚干旱区草地生态系统为研究对象,利用Biome-BGC模型,模拟分析其NPP、NEP的年际变化趋势及其空间分布格局。结果显示：（1）1979-2011年中亚地区草地生态系统NPP年平均值为135.6 gC·m^-2·a^-1,且随着时间的推移呈现出波动下降的趋势,下降速率为0.34 gC·m^-2·a^-1。（2）NEP的年平均值为-8.3 gC·m^-2·a^-1,表现为碳源,且该值随着时间的推移呈现出波动上升的趋势,上升速率为0.58 gC·m^-2·a^-1。（3）NPP高值区域在降水较为丰富的天山山脉附近以及哈萨克斯坦北部。（4）NPP的年际变化与降水量的年际变化趋势基本一致,相关系数为0.52;NPP与温度的相关系数为-0.28,未达到显著相关水平。本研究实现了Biome-BGC模型在中亚干旱区草地生态系统的应用,对评价干旱区草地生态系统碳源/碳汇功能及其在全球碳循环和全球变化中的作用、实现中亚草地生态系统的可持续利用、完善区域和全球碳循环理论体系具有重要意义。     

Simulating net primary production of grasslands in northeastern Asia using MODIS data from 2000 to 2005

The net primary production (NPP) of grasslands in northeastern Asia was estimated using improved CASA model with MODIS data distributed from 2000 and ground data as driving variables from 2000 to 2005. Average annual NPP was 146.05 g C m?2 yr?1 and average annual total NPP was 0.32 Pg C yr?1 in all grasslands during the period. It was shown that average annual grassland NPP in the whole northeastern Asia changed dramatically from 2000 to 2005, with the highest value of 174.80 g C m?2 yr?1 in 2005 and the lowest value of 125.65 g C m?2 yr?1 in 2001. On regional scale, average annual grassland NPP of 179.71 g C m?2 yr?1 in southeastern Russia was the highest among the three main grassland regions in the six years. Grasslands in northern China exhibited the highest average annual total NPP of 0.16 Pg C yr?1 and contributed 51.42% of the average annual total grassland NPP in northeastern Asia. Grassland NPP in northeastern Asia also showed a clear seasonal pattern with the highest NPP occurred in July every year. Average monthly grassland NPP in southeastern Russia was the highest from May to August while average monthly grassland NPP in northern China showed the highest NPP before May and after August. The change rate distribution of grassland NPP between the former three years and the latter three years showed grassland NPP changed slightly between the two stages in most regions, and that NPP change rate in 80.98% of northeastern Asia grasslands was between –0.2 and 0.2. Grassland NPP had close correlation with precipitation and temperature, that indicates climate change will influence the grassland NPP and thus have a great impact on domestic livestock in this region in future.     

基于MODIS数据的2000-2005年东北亚草地NPP模拟(英文)

The net primary production(NPP)of grasslands in northeastern Asia was estimated using improved CASA model with MODIS data distributed from 2000 and ground data as driving variables from 2000 to 2005.Average annual NPP was 146.05 g C m-2yr -1and average annual total NPP was 0.32 Pg C yr-1in all grasslands during the period.It was shown that average annual grassland NPP in the whole northeastern Asia changed dramatically from 2000 to 2005,with the highest value of 174.80 g C m-2yr-1in 2005 and the lowest valu...     

Assessment of effectiveness of nature reserves on the Tibetan Plateau based on net primary production and the large sample comparison method

Twenty-one typical coupled large samples were chosen from areas within and surrounding nature reserves on the Tibetan Plateau using the large sample comparison method (LSCM). To evaluate the effectiveness of the nature reserves in protecting the ecological environment, the alpine grassland net primary production (NPP) of these coupled samples were compared and the differences between them before and after their establishment as protected areas were analyzed. The results showed that: (1) With respect to the alpine grassland NPP, the ecological and environmental conditions of most nature reserves were more fragile than those of the surrounding areas and also lower than the average values for the Tibetan Plateau. (2) Of the 11 typical nature reserves selected, the positive trend in the NPP for Manzetang was the most significant, whereas there was no obvious trend in Taxkorgan. With the exception of Selincuo, the annual NPP growth rate in the nature reserves covered by alpine meadow and wetland was higher than that in nature reserves consisting of alpine steppe and alpine desert. (3) There were notable findings in 21 typical coupled samples: (a) After the establishment of the nature reserves, the annual rate of increase in the NPP in 76% of samples inside nature reserves and 82% of samples inside national nature reserves was higher than that of the corresponding samples outside nature reserves. (b) The effectiveness of ecological protection of the Mid-Kunlun, Changshagongma, Zoige and Selincuo (Selin Co) nature reserves was significant; the effectiveness of protection was relatively significant in most parts of the Sanjiangyuan and Qiangtang nature reserves, whereas in south-east Manzetang and north Taxkorgan the protection effectiveness was not obvious. (c) The ecological protection effectiveness was significant in nature reserves consisting of alpine meadow, but was weak in nature reserves covered by alpine steppe. This study also shows that the advantage of large sample comparison method in evaluating regional ecology change. Careful design of the samples used, to ensure comparability between the samples, is crucial to the success of this LSCM.     

基于Biome-BGC模型的青藏高原五道梁地区NPP变化及情景模拟

以“气候变暖”为标志的全球气候变化对青藏高原生态系统产生强烈影响,利用参数本地化的生物地球化学模型（Biome-BGC）对五道梁地区草地生态系统进行模拟,研究了该区域1961~2015年净初级生产力（net primary productivity,NPP）的变化,并进行了情景模拟。结果表明:五道梁地区近55 a草地年均NPP为67.94 g/(m ²·a),呈显著上升趋势,主要是由生长季延长以及9月份生物量快速增长造成。在该地区,温度是草地NPP的主导因子,降水变化在40%以内对生产力影响不显著;温度和降水交互影响NPP,对单一影响有放大作用,暖湿条件下NPP对气候变化响应更加明显。     

Responses of Grassland Net Primary Productivity to Environmental Variables in Northern China

Various environmental factors affect net primary productivity (NPP) of grassland ecosystem. Extensive reports on the effects of environmental variables on NPP can be found in literature. However, the agreement on the relative importance of various factors in shaping the spatial pattern of grassland NPP has not yet been reached. Here a grassland in situ NPP database comprising 602 samples in northern China for 1980-1999 was developed based on a literature review of published biomass and forage yield field measurements. Correlation analyses and dominance analysis were used to quantify the separate and combined effects of environmental variables (climate, topography and soil) on spatial variation in NPP separately. Grassland NPP ranged from 4.76 g C m^-2a^-1 to 975.94 g C m^-2a^-1, showing significant variations in space. NPP increased with annual precipitation and declined with annual mean temperature significantly. Specifically, precipitation had the greatest impact on deserts, followed by steppes and meadows. Grassland NPP decreased with increasing altitude because of water limitation, and positively correlated with slope, but weakly correlated with aspect. Soil quality showed positive effects on NPP. Annual precipitation was the dominant factor affecting the spatial variability of net primary productivity, followed by elevation.     

基于NPP数据和样区对比法的青藏高原自然保护区保护成效分析（英文）

Twenty-one typical coupled large samples were chosen from areas within and surrounding nature reserves on the Tibetan Plateau using the large sample comparison method(LSCM).To evaluate the effectiveness of the nature reserves in protecting the ecological environment,the alpine grassland net primary production(NPP) of these coupled samples were compared and the differences between them before and after their establishment as protected areas were analyzed.The results showed that:(1) With respect to the alpine grassland NPP,the ecological and environmental conditions of most nature reserves were more fragile than those of the surrounding areas and also lower than the average values for the Tibetan Plateau.(2) Of the 11 typical nature reserves selected,the positive trend in the NPP for Manzetang was the most significant,whereas there was no obvious trend in Taxkorgan.With the exception of Selincuo,the annual NPP growth rate in the nature reserves covered by alpine meadow and wetland was higher than that in nature reserves consisting of alpine steppe and alpine desert.(3) There were notable findings in 21 typical coupled samples:(a) After the establishment of the nature reserves,the annual rate of increase in the NPP in 76% of samples inside nature reserves and 82% of samples inside national nature reserves was higher than that of the corresponding samples outside nature reserves.(b) The effectiveness of ecological protection of the Mid-Kunlun,Changshagongma,Zoige and Selincuo(Selin Co) nature reserves was significant; the effectiveness of protection was relatively sig-nificant in most parts of the Sanjiangyuan and Qiangtang nature reserves,whereas in south-east Manzetang and north Taxkorgan the protection effectiveness was not obvious.(c) The ecological protection effectiveness was significant in nature reserves consisting of alpine meadow,but was weak in nature reserves covered by alpine steppe.This study also shows that the advantage of large sample comparison method in evaluating regional ecology change.Careful design of the samples used,to ensure comparability between the samples,is crucial to the success of this LSCM.