宁夏典型温性天然草地固碳特征

本文研究了宁夏草甸草原、温性草原、草原化荒漠和荒漠草原4种温性典型天然草地生态系统碳储量及其构成特征。结果表明: 草甸草原、温性草原、草原化荒漠和荒漠草原植被总生物量分别为1178.91、481.22、292.80和209.09 g·m^-2。其中,地下根系生物量是构成草甸草原和温性草原植被总生物量的主体,分别占总生物量的73.1%和56.6%;地上植被生物量是构成草原化荒漠和荒漠草原植被总生物量的主体,分别占总生物量的50.3%和47.6%;枯落物生物量占比较低,分别仅为8.5%、8.0%、6.4%和16.2%。草甸草原、温性草原、草原化荒漠和荒漠草原4种天然草地生态系统碳储量分别为13.90、5.94、2.69和2.37 kg·m^-2,其中植被碳储量分别为470.26、192.23、117.17、83.36 g·m^-2,0～40 cm土层土壤有机碳储量分别为13.43、5.75、2.58和2.29 kg·m^-2,土壤有机碳储量是构成宁夏典型天然草地碳储量的主体,分别占到了生态系统碳储量的96.6%、96.8%、95.6%和96.5%。4种草地类型植被总生物量、植被碳储量、土壤有机碳储量和生态系统碳储量均表现为:草甸草原＞温性草原＞草原化荒漠＞荒漠草原。     

黄土高原典型草原地上生物量估测模型

为了寻求有效的草地地上生物量估测方法和精确估测黄土高原典型草原草原地上生物量。于2014年8月中旬,在黄土高原典型草原草原地上生物量达到最大值,分别从单株水平和种群水平进行野外调查。以株高(H)和盖度(C)的复合因子(C×H)为自变量,通过回归分析,建立地上生物量估测模型,采用留一法对其精确性进行评估;并通过校正系数以及群落总生物量估测值和实测值比较单株水平和种群水平所建模型的精确性。结果表明:黄土高原典型草原草地,无论在单株水平还是种群水平,线性和幂函数对该区域生物量的拟合效果更好。估测模型检验结果表明,在单株水平各个物种的生物量估测值与实测值相关性较好,均达到了显著水平(P0.05),其r值均大于0.6,总相对误差RS均小于10%,平均相对误差绝对值RMA(average absolute value of relative error)均小于30%,总生物量的实测值与估测值比较接近,校正系数均接近1;而在种群水平上,虽然各物种的生物量估测值与实测值相关性均达到了显著水平(P0.05),但多数物种平均相对误差绝对值RMA大于30%,总相对误差RS(total relative error)均大于10%,总生物量的估测值均大于实测值,校正系数均偏离了1,说明在黄土高原典型草原通过单株水平建立的物种生物量估测模型的精度优于种群水平建立的物种生物量估测模型的精度。     

利用多时相近地面反射波谱特征对不同退化等级草地的鉴别研究

 草地各退化等级群落反射波谱特征之间的差异性大小与草地类型和生长季节有关,羊草(Leymus chinensis)草原不同退化等级群落反射波谱特征之间的差异在6月底最为显著,在5月底的差异最不明显, 大针茅(Stipa grandis)草原不同退化等级群落反射波谱特征之间在7月底、8月底的差异最为显著,在5月底和6月底的差异最不明显。植被指数(NDVI)在5月底、6月底和9月底在各草地类型的不同退化等级群落中都无显著差异,而在7月底、8月底差异显著程度也小于各波段反射率。主分量分析(PCA)和模式识别分析结果表明：对于羊草草原退化生态系列的不同退化等级群落分类效果最佳的鉴别函数是蓝光、红光和近红外波段反射率的线性组合,最佳分类时间在6月底,平均错误概率仅为0.7%,5月底进行分类效果最差,平均错误概率为12%左右,7月底、8月底、9月底的分类效果居中;对大针茅草原退化生态系列的不同退化等级群落分类效果最佳的鉴别函数是蓝光、绿光和近红外波段3个反射率的线性组合,在7月底和8月底进行分类效果最好,分类的平均错误概率为4％左右,9月底的分类效果最差,平均错误概率达10%左右。     

基于草地综合顺序分类系统(IOCSG)的中国北方草地地上生物量高精度模拟

草地生态系统是陆地生态系统中分布最广泛的生态系统类型之一,草地生物量的精确估算一直是陆地生态学研究的重点问题。针对目前草地生物量估算方法的不确定性问题,提出了不依赖于遥感植被指数,而是通过分析草地生物量影响因素的方法去构建草地生物量估算模型。根据年积温(0℃)和湿润度指标将研究区域划分为4种潜在植被类型,即微温干旱温带半荒漠类、微温微干温带典型草原类、微温微润草甸草原类和微温湿润森林草原类,然后对每一种潜在植被类型的草地生物量分析其内在影响因素,研究结果发现,微温干旱温带半荒漠类的草地生物量与年积温存在较好的线性关系,微温微干温带典型草原类的草地生物量可以用表层土壤粘粒含量的二次多项式来模拟,后两种潜在植被类型的草地生物量则随着潜在NPP的变化呈现先减小后增大的变化趋势。对4种潜在植被类型区域分别建立草地生物量与其影响因素之间的回归关系确定研究区域草地生物量的趋势面,结合HASM模型实现研究区域草地生物量的高精度模拟,结果显示上述4种潜在植被类型区的草地平均生物量分别为76.62、110.94、142.69、184.40 g/m2。     

围封与放牧对青藏高原草地生物量与功能群结构的影响

以青藏高原高寒草甸、高寒草原、温性荒漠草原的退化草地为基础,比较了5年围封样地与放牧样地的生物量和群落结构。结果表明:(1)围封后3类草地地上总生物量较放牧样地分别显著增加了48.1%、10.8%、34.5%;地下生物量对围封的响应与地上总生物量一致,且围封后高寒草原0~10cm土层根系生物量比例较放牧地显著下降。(2)围封显著降低了高寒草甸的根冠比,高寒草原和温性荒漠草原无显著变化。(3)与放牧地相比,围封显著增加了高寒草甸和高寒草原禾本科植物的生物量比例,高寒草甸杂类草显著降低,温性荒漠草原功能群生物量比例无显著差异。     

新疆阿勒泰地区草地类型及植物多样性的研究

基于33个样地、99个样方的野外调查资料,分析了新疆阿勒泰地区草地群落的植物物种多样性特征。结果表明：草地群落间的植物物种丰富度指数、均匀度指数和多样性指数差异显著,丰富度由山地草原、经山地草甸、荒漠草原、草甸化草原、平原荒漠、高寒草甸到山地荒漠依次下降,均匀度指数由山地草原,经草甸化草原、荒漠草原、平原荒漠、山地草甸、高寒草甸,到山地荒漠依次下降,多样性指数从山地草原,经草甸化草原、荒漠草原、山地草甸、平原荒漠、高寒草甸,到山地荒漠呈下降趋势。在群落多样性梯度上,物种丰富度对多样性的贡献率要比均匀度的贡献率小。草地群落的物种丰富度、均匀度和多样性指数随海拔升高均表现为先上升,后下降,峰值出现在1800～2000m的山地草原,且变化趋势一致。     

中国北方典型草地物种丰富度与生产力的关系

利用2002–2004年内蒙古和甘肃南部几种典型草地的实测资料,研究了不同尺度物种丰富度与生产力的关系,并初步探讨了其形成机制。结果显示,温带草地的物种丰富度随生产力的增加而增加,但受空间尺度影响。在群落尺度(同一群落),在7种样方数大于15的群落中,仅沙生针茅(Stipaglareosa)群落物种丰富度与生产力呈现单峰型关系,其余均呈现线性正相关关系;在植被类型尺度,物种丰富度–生产力之间表现为显著的正相关关系;在研究区尺度,物种丰富度随生产力的增加而显著增加。研究还表明,研究区群落生产力的变化范围为13–368g·m–2·yr–1,物种丰富度为4–35种;生产力从高到低的顺序为:高寒草甸>草甸草原>典型草原>荒漠草原。     

中国北方草地植物群落季节生长格局模拟

中国北方草地横跨干旱、半干旱及亚湿润干旱气候区,水分是限制中国北方草地植物群落生产力的主要气候因子.采用基于水分平衡过程的、简单的植物群落模型,利用460个气象站40年气象数据的月平均值,模拟中国北方7种草地类型的季节及年生长、叶片投影盖度(FPC)、蒸发系数(k)及净第一性生产力(NPP).野外观测数据对模型的验证显示模拟结果与观测值相符较好.温性草地自东向西,青藏高原自东南向西北,植物群落的k、NPP与FPC呈递减趋势,显示了中国温性草地自东向西,青藏高原自东南向西北逐渐干旱的水分梯度;其中高寒草甸的3个模拟参数值均最高,高寒草原FPC次于高寒草甸,而NPP却与温性典型草原相近,温性典型荒漠的3个参数最低.高寒草甸、高寒草原、温性草甸草原、温性典型草原、温性荒漠草原、温性草原化荒漠和温性典型荒漠等7种类型草地的畜群承载力约为每公顷5.2、2.3、3.6、2.1、1.0、0.6和0.2只羊单位,区域最适恢复植被盖度分别以93%、79% 、56%、50%、44%、38%和37%为宜.     

西藏高原高寒草地群落植物多样性和地上生物量监测方法的比较研究

以西藏高原高寒草地3种植被类型(高寒草甸、高寒草原和高寒荒漠草原)为研究对象,分别采用样线法、样方法和巢式样方法进行实地调查,记录每条样线上或每个样方内出现的所有物种,并分物种刈割样方内地上部分,通过统计分析比较不同高寒草地群落植物多样性和地上生物量监测方法,以阐明西藏高原高寒草地不同植被类型的最小取样面积和最少样方数或样线长度。结果显示:(1)就物种丰富度而言,400m样线法观测到的高寒草甸、高寒草原和高寒荒漠草原的所有物种数分别占3种方法调查到的总物种数的55%、71%和50%;8m2巢式样方法调查到高寒草甸、高寒草原的总物种数占所有3种方法观测的物种总数的57.5%和57%,而8m2的巢式样方对高寒荒漠草原的调查监测到的物种数最多,其中2m2观测到的物种数就达到所有可能出现物种的83%;20个样方法监测到高寒草甸和高寒草原的物种数最多,占3种方法观测到总物种数的78%和86%,所以对物种丰富度的调查高寒草甸和高寒典型草原至少需要20个样方,高寒荒漠草原需要最小面积不少于2m2的2个样方。(2)就地上生物量而言,由地上生物量与物种数之间的变异关系得出最小样方数为7~11个,而由地上生物量的变异系数可知,在变异系数小于等于5%的前提下,高寒草甸的最小取样面积不小于0.25m2,高寒典型草原和高寒荒漠草原的最小取样面积不少于1m2。研究表明,对于生产力的监测方法而言,高寒草甸采用10个0.5m×0.5m的样方,而高寒草原和高寒荒漠草原采用10个1m×1m的样方为宜;而对于物种丰富度的监测方法而言,高寒草甸以20个0.5m×0.5m的样方和高寒草原20个1m×1m的样方为宜,高寒荒漠草原采用2个不小于2m2样方面积为宜。     

陇东黄土高原丘陵沟壑区天然草地群落学特征研究

采用路线调查法和样方法研究了陇东黄土高原丘陵沟壑区天然草地植物群落组成的特征.结果表明,该研究区地带性植被的主要类型为草甸草原和典型草原,草甸草原以蒿类、白羊草和白草为代表群落;典型草原以长芒草、蒿类、百里香和毛沙芦草等为代表群落.草地群落物种组成较为简单,优势种的优势度显著,其中长芒草、山蒿、冷蒿、牛枝子、糙隐子草、铁杆蒿、阿尔泰狗娃花、赖草、猪毛蒿、百里香等是群落物种组成中相对重要的物种;天然草地群落数量特征的平均值为:种数17.1、多度163.5、高度49.2 cm、盖度52.8%、鲜重284.9 g?m-2、干重151.8g?m-2;草甸草原群落的高度、盖度、生物量和物种丰富度值均大于典型草原.     

Characterization of diverse plant communities in Aspen Parkland rangeland using LiDAR data

Question: How effective is high-resolution airborne LiDAR technology for quantifying biophysical characteristics of multiple community types within diverse rangeland environments? Location: Native Aspen Parkland vegetation in central Alberta, Canada. Methods: Vegetation within 117 reference plots stratified across eight types, including forest, shrubland, upland grassland and lowland meadow communities, were assessed in 2001 for the height, cover and density of vegetation within various strata (herb, shrub and tree layers). Actual ground data were subsequently compared against modelled values for each community type and strata derived from the analysis of airborne LiDAR data obtained in 2000. Results: LiDAR data were effective for quantifying vegetation height, cover and density of the overstory within closed- and open Populus forest communities. However, LiDAR measurements typically underestimated the height and cover of shrublands, as well as most of the herbaceous communities. Analysis of LiDAR intensity data indicated reflectance generally decreased as LiDAR sampling points moved upwards from the ground to the vegetation canopy. Conclusions: While LiDAR technology is useful for characterizing deciduous forest properties, the quantification of understory vegetation characteristics, as well as those of individual shrublands and grasslands, was more limiting. Further refinements in analysis methods are necessary to increase the reliability of characterizing these communities.     

Spectral feature differences between shrub and grass communities and shrub coverage retrieval in shrub-encroached grassland in Xianghuang Banner,Nei Mongol,China北大核心CSCD

Aims: Shrub-encroached grassland has become an important vegetation type in China's arid and semi-arid region. Our study objective is to explore the spectral features of shrub and grass communities, as well as their empirical relationships with shrub coverage. The quantitative estimation of shrub cover based on medium-resolution Landsat satellite imagery provides the practical basis for long term retrieval of large areas of shrub expansion in the grassland region. Methods: Linear models and Multiple Endmember Spectral Analysis Model (MESMA) based on medium resolution Landsat satellite imagery were developed to quantify the shrub coverage in a shrub-encroached grassland region in Xianghuang Banner, Nei Mongol using the spectral features and their seasonal differences between the shrub and grass communities. Important findings: Compared to Leymus chinensis and Stipa krylovii dominated grass communities, Caragana microphylla community had a higher normalized difference vegetation index (NDVI), modified red edge normalized difference vegetation index (mNDVI705), and red edge slope. The red edge position of C. microphylla community shifted to longer wavelengths. The average and the maximum shrub coverage was 13% and 25%, respectively, in the shrub-encroached grassland based on both models. The correlation coefficient of determination (R2) and root mean square error (RMSE) of the linear model was 0.31 and 0.05, respectively. We found that the linear model based on seasonal differences of shrub and grass community was more suitable for retrieving shrub coverage in the study area from medium resolution imagery than the MESMA model that is based on mid-summer images.     

草地植物群落地上生物量非破坏性估测方法的探讨

 羊草群落的高度和盖度与地上生物量存在良好的复相关关系(R=0.9316),所获多元回归方程可用于该群落地上生物量的估测。通过对羊草群落、羊草+杂类草群落和贝加尔针茅群落植冠红光(0.63—0.69μm)和近红外辐射(0.76—0.90μm)反射率实测数据的分析,表明这些群落的光谱反射率比IR、IR/R和VI与地上生物量呈高度的指数相关关系,其中由VI和IR/R所获各群落不同生长时期地上生物量回归模型的估测效果较好。     

阿尔泰山两河源牧区草地群落生物量及物种多样性

群落生物量和物种多样性是表征草地生态系统数量特征的重要指标。该研究以新疆阿尔泰山南麓两河源放牧区草地为研究对象,利用样方法对两河源不同放牧区的草地植被进行调查,分析研究区生物量和物种多样性变化,探讨二者与环境因子之间的关联性,为草地群落物种保护以及草地可持续利用提供理论依据。结果表明：(1) 两河源不同牧区间群落盖度、高度、植株密度、地上生物量和单位盖度生物量存在差异。(2) 两河源牧区草地群落地上生物量与群落盖度、植株密度呈显著正相关关系(P<0.05),且地上生物量主要受草地群落盖度的影响;不同牧区的物种多样性指数有一定差异,但物种分布相对均匀。(3)两河源牧区草地群落生物量及物种多样性主要受气温和降水的影响。     

Spectral feature differences between shrub and grass communities and shrub coverage retri- eval in shrub-encroached grassland in Xianghuang Banner,Nei Mongol,China

Aims Shrub-encroached grassland has become an important vegetation type in China’s arid and semi-arid region. Our study objective is to explore the spectral features of shrub and grass communities, as well as their empirical relationships with shrub coverage. The quantitative estimation of shrub cover based on medium-resolution Landsat satellite imagery provides the practical basis for long term retrieval of large areas of shrub expansion in the grassland region. Methods Linear models and Multiple Endmember Spectral Analysis Model (MESMA) based on medium resolution Landsat satellite imagery were developed to quantify the shrub coverage in a shrub-encroached grassland region in Xianghuang Banner, Nei Mongol using the spectral features and their seasonal differences between the shrub and grass communities. Important findings Compared to Leymus chinensis and Stipa krylovii dominated grass communities, Caragana microphylla community had a higher normalized difference vegetation index (NDVI), modified red edge normalized difference vegetation index (mNDVI₇₀₅), and red edge slope. The red edge position of C. microphylla community shifted to longer wavelengths. The average and the maximum shrub coverage was 13% and 25%, respectively, in the shrub-encroached grassland based on both models. The correlation coefficient of determination (R²) and root mean square error (RMSE) of the linear model was 0.31 and 0.05, respectively. We found that the linear model based on seasonal differences of shrub and grass community was more suitable for retrieving shrub coverage in the study area from medium resolution imagery than the MESMA model that is based on mid-summer images.     

应用间接排序识别盐沼植被的光谱特征:以崇明东滩为例

遥感技术已成为大尺度植被分类的重要手段,而地面植物群落特征与其光谱特征之间的关系是解译遥感影像的关键。该研究选择上海崇明东滩自然保护区的盐沼植物群落为对象,应用ASD地物光谱仪测定其植物群落的光谱反射率,并采用10个小型机载成像光谱仪(CASI)默认植被波段组,应用主分量分析法和相关分析分析了不同群落光谱特征与生态环境因子之间的关系。分析结果表明,间接排序法PCA能够识别盐沼植被中光滩、海三棱 草(Scirpus mariqueter)群落、芦苇(Phragmites australis)群落和互花米草(Spartina alterniflora)等群落的光谱特征,绝大多数盐沼湿地植物群落组成与光谱特征之间有显著的相关,识别效果最好的波段组是736~744 nm、746~753 nm、775~784 nm、815~824 nm和860~870 nm;对光谱反射率影响最大的生态环境因子分别是植物群落的高度和盖度,高程和其它环境因子的影响次之。研究成果可为遥感监测崇明东滩自然保护区内入侵种互花米草的空间分布和扩散规律提供技术支撑,为高光谱遥感影像的影像判读和解译分类以及盐沼湿地植被制图提供科学依据。     

上海盐沼植被的多季相地面光谱测量与分析

遥感是大尺度生态研究的重要工具之一,而地面植物群落特征与其光谱特征之间的关系是解译遥感影像的关键.研究选择上海崇明东滩候鸟自然保护区的盐沼植被为研究对象,使用ASD便携式地物光谱仪测定芦苇、互花米草、海三棱藨草和糙叶苔草4类主要群落的春、夏、秋各季冠层反射光谱,并计算生成350～1000nm的反射率曲线的一阶导数曲线,在此基础上分析反射率与一阶导数曲线在可见光与近红外波段以及物候特征的“绿峰”和“红边”等波段的差异.分析显示,不同盐沼群落在各生长季都有较独特的光谱特征,四类盐沼群落的光谱特征在季相上表现各异.上海地区盐沼植被各类群落的遥感识别和分类的适宜季相不尽相同,应用多季相影像进行综合分类可取得较好的效果.研究结果可为遥感监测外来种互花米草的空间分布与动态提供技术支撑,为高光谱遥感的影像判读和解译分类以及盐沼植被制图提供科学依据.     

Bird Communities and Biomass Yields in Potential Bioenergy Grasslands

Demand for bioenergy is increasing, but the ecological consequences of bioenergy crop production on working lands remain unresolved. Corn is currently a dominant bioenergy crop, but perennial grasslands could produce renewable bioenergy resources and enhance biodiversity. Grassland bird populations have declined in recent decades and may particularly benefit from perennial grasslands grown for bioenergy. We asked how breeding bird community assemblages, vegetation characteristics, and biomass yields varied among three types of potential bioenergy grassland fields (grass monocultures, grass-dominated fields, and forb-dominated fields), and assessed tradeoffs between grassland biomass production and bird habitat. We also compared the bird communities in grassland fields to nearby cornfields. Cornfields had few birds compared to perennial grassland fields. Ten bird Species of Greatest Conservation Need (SGCN) were observed in perennial grassland fields. Bird species richness and total bird density increased with forb cover and were greater in forb-dominated fields than grass monocultures. SGCN density declined with increasing vertical vegetation density, indicating that tall, dense grassland fields managed for maximum biomass yield would be of lesser value to imperiled grassland bird species. The proportion of grassland habitat within 1 km of study sites was positively associated with bird species richness and the density of total birds and SGCNs, suggesting that grassland bioenergy fields may be more beneficial for grassland birds if they are established near other grassland parcels. Predicted total bird density peaked below maximum biomass yields and predicted SGCN density was negatively related to biomass yields. Our results indicate that perennial grassland fields could produce bioenergy feedstocks while providing bird habitat. Bioenergy grasslands promote agricultural multifunctionality and conservation of biodiversity in working landscapes.     

Estimation of aboveground biomass using in situ hyperspectral measurements in five major grassland ecosystems on the Tibetan Plateau

Aims There are numerous grassland ecosystem types on the Tibetan Plateau. These include the alpine meadow and steppe and degraded alpine meadow and steppe. This study aimed at developing a method to estimate aboveground biomass (AGB) for these grasslands from hyperspectral data and to explore the feasibility of applying air/satellite-borne remote sensing techniques to AGB estimation at larger scales.Methods We carried out a field survey to collect hyperspectral reflectance and AGB for five major grassland ecosystems on the Tibetan Plateau and calculated seven narrow-band vegetation indices and the vegetation index based on universal pattern decomposition (VIUPD) from the spectra to estimate AGB. First, we investigated correlations between AGB and each of these vegetation indices to identify the best estimator of AGB for each ecosystem type. Next, we estimated AGB for the five pooled ecosystem types by developing models containing dummy variables. At last, we compared the predictions of simple regression models and the models containing dummy variables to seek an ecosystem type-independent model to improve prediction of AGB for these various grassland ecosystems from hyperspectral measurements.Important findings When we considered each ecosystem type separately, all eight vegetation indices provided good estimates of AGB, with the best predictor of AGB varying among different ecosystems. When AGB of all the five ecosystems was estimated together using a simple linear model, VIUPD showed the lowest prediction error among the eight vegetation indices. The regression models containing dummy variables predicted AGB with higher accuracy than the simple models, which could be attributed to the dummy variables accounting for the effects of ecosystem type on the relationship between AGB and vegetation index (VI). These results suggest that VIUPD is the best predictor of AGB among simple regression models. Moreover, both VIUPD and the soil-adjusted VI could provide accurate estimates of AGB with dummy variables integrated in regression models. Therefore, ground-based hyperspectral measurements are useful for estimating AGB, which indicates the potential of applying satellite/airborne remote sensing techniques to AGB estimation of these grasslands on the Tibetan Plateau.