山西高原植被与气候的关系分析及植被数量区划的研究

本文利用去势典范对应分析和数量区划的方法,研究了山西高原植被与气候之间的关系,并进行了数量区划。排序的结果表明：DCCA的第—轴代表山西高原植被和气候梯度的纬向性,热量梯度是决定植被分布最主要的气候因子,水分梯度中的年降水量也对第—轴有较大的影响,由于山西高原南北跨度大,植被与气候因子表现出明显的纬向性;DCCA第二轴代表山西高原植被和气候梯度的经向性,与DCCA第二轴相关性较大的是水分因子中的年降水量、年蒸发量,由于山西高原东西跨度不大,而且大部分地区处在吕梁山脉和太行山脉之间,东西向的气候变化幅度不大,所以植被与气候梯度的经向性不明显。植被数量区划的结果表明：山西高原可划分为17个植被区,用图示的方法确定山西高原大致有三个极点和—个中心。     

Linking riparian vegetation types and fluvial geomorphology along the Sabie River within the Kruger National Park, South Africa

Vegetation types were studied in relation to the fluvial geomorphology along the mixed bedrock‐alluvial Sabie River within the Kruger National Park, Mpumalanga, South Africa. Six vegetation types were identified using TWINSPAN analysis, namely: Phragmites mauritianus , Phyllanthus reticulatus , Breonadia salicina , Combretum erythrophyllum , Diospyros mespiliformis and Spirostachys africana vegetation types. Spirostachys africana and Diospyros mespiliformis vegetation types were found to occur predominantly on the stable, infrequently flooded macro‐channel banks, while the remaining four vegetation types were found almost exclusively along the more geomorphically and hydrologically dynamic macro‐channel floor. The degree of bedrock or alluvial influence was identified as being an integral factor in the distribution of the four macro‐channel floor vegetation types at both the morphological unit and the channel type scale. The geomorphological continuum from the bedrock influenced bedrock anastomosing channel types, to mixed anastomosing and pool‐rapid channel types, to the fully alluvial braided channel types, is reflected in the change in species composition from Breonadia salicina vegetation type, to Phyllanthus reticulatus and Phragmites mauritianus vegetation types, to Combretum erythrophyllum vegetation types, respectively. Given the vegetation/fluvial geomorphology links established, changes in vegetation composition are proposed in response to scenarios of geomorphological change as a result of progressive sedimentation.     

Applying ecological site concepts and state‐and‐transition models to a grazed riparian rangeland

Ecological sites and state‐and‐transition models are useful tools for generating and testing hypotheses about drivers of vegetation composition in rangeland systems. These models have been widely implemented in upland rangelands, but comparatively, little attention has been given to developing ecological site concepts for rangeland riparian areas, and additional environmental criteria may be necessary to classify riparian ecological sites. Between 2013 and 2016, fifteen study reaches on five creeks were studied at Tejon Ranch in southern California. Data were collected to describe the relationship between riparian vegetation composition, environmental variables, and livestock management; and to explore the utility of ecological sites and state‐and‐transition models for describing riparian vegetation communities and for creating hypotheses about drivers of vegetation change. Hierarchical cluster analysis was used to classify the environmental and vegetation data (15 stream reaches × 4 years) into two ecological sites and eight community phases that comprised three vegetation states. Classification and regression tree (CART) analysis was used to determine the influence of abiotic site variables, annual precipitation, and cattle activity on vegetation clusters. Channel slope explained the greatest amount of variation in vegetation clusters; however, soil texture, geology, watershed size, and elevation were also selected as important predictors of vegetation composition. The classification tree built with this limited set of abiotic predictor variables explained 90% of the observed vegetation clusters. Cattle grazing and annual precipitation were not linked to qualitative differences in vegetation. Abiotic variables explained almost all of the observed riparian vegetation dynamics—and the divisions in the CART analysis corresponded roughly to the ecological sites—suggesting that ecological sites are well‐suited for understanding and predicting change in this highly variable system. These findings support continued development of riparian ecological site concepts and state‐and‐transition models to aid decision making for conservation and management of rangeland riparian areas.     

Trend analysis of vegetation dynamics in Qinghai-Tibet Plateau using Hurst Exponent

As one of the most sensitive areas responding to global environmental change, especially global climate change, Qinghai-Tibet Plateau has been recognized as a hotspot for coupled studies on global terrestrial ecosystem change and global climate change. As an important component of terrestrial ecosystems, vegetation dynamic has become one of the key issues in global environmental change, and numerous case studies have been conducted on vegetation dynamic trend in different study periods. However, few are focused on the quantitative analysis of the consistency of vegetation dynamic trends after the study periods. In the study, taking Qinghai-Tibet Plateau as a case, vegetation dynamic trend during 1982-2003 were analyzed, with the application of the method of linear regression analysis. The results showed that, vegetation dynamics in Qinghai-Tibet Plateau experienced a significant increasing as a whole, with nearly 50% forest degradation in the study period. And among the 7 kinds of vegetation types, the change of forest was the most fluctuant with desert the least one. Furthermore, the consistency of vegetation dynamic trends after the study period, was quantified using Hurst Exponent and the method of R/S analysis. The results showed high consistency of future vegetation dynamic trends for the whole plateau, and inconsistent areas were mainly meadow and steppe distributed in the middle or east of the plateau. It was also convinced that, vegetation dynamic trends in the study area were significantly influenced by topography, especially the elevation.     

基于植物多样性特征的武汉市城市湖泊湿地植被分类保护和恢复

湿地植被多样性特征及其影响因素的调查分析是湿地植被保护与恢复策略制定的基础。借鉴生物多样性热点分析原理,在武汉市城市湖泊湿地植物多样性调查的基础上,研究了湖泊湿地的植被多样性特征,探讨了城市湖泊湿地植被分类保护与恢复对策。结果表明,武汉市湿地维管束植物的物种丰富度、植物多样性、优势度和均匀度指数在各湖泊间的变化趋势较为一致,但在空间变化幅度上存在一定差异。按照物种丰富度、多样性、优势度、均匀度、湿地植被群丛数目,以及典型湿地植物的物种所占比例、丰富度和优势度的差异,可将调查涉及的26个典型湖泊湿地分为原生植被湖泊、次生植被湖泊、人工植被湖泊和退化植被湖泊4类。原生植被湖泊应建立相对严格的湿地保护区,优先保护原有湿地植被。次生植被湖泊最多,城市发展区内的次生植被湖泊应建立30-100m的植被缓冲带,促进植被自然恢复和发育;而农业区的次生植被湖泊应引导和规范湖泊周围的农业生产模式,以减少人类活动干扰。人工植被湖泊应通过建立城市湿地公园,人工促进植被的近自然恢复。而退化植被湖泊则应尽快采用生态工程法促进湿地植被生境改善,并积极开展近自然湿地植被重建与恢复。     

黄土高原植被覆盖与水热时空通径分析

探究黄土高原地区气象因子对植被覆盖的影响作用以丰富生态修复理论。基于黄土高原2001—2017年归一化植被指数(Normalized Difference Vegetation Index, NDVI)与气象数据,采用通径分析方法分别从时间和空间尺度上,分析黄土高原气温和降水对植被覆盖变化的直接及间接影响作用,为该地区生态建设提供科学依据。结果如下：黄土高原地区年际间植被明显波动增长,降水变化大体上与植被变化相似;降水整体较气温对植被覆盖变化的作用大。黄土高原植被与水热空间关系的最优分析尺度为80km,在80km空间尺度上,植被与气温有最大相关性,植被、降水由东南到西北递减,而气温分布规律不显著;降水整体呈现促进作用,气温的抑制作用较强,且空间差异明显。在时间与空间尺度上,植被主要受水热促进尤其是降水促进影响,且降水对植被生长的直接作用远大于通过气温的间接作用;不论生态区还是植被类型,气候因子作用均以促进类型为主,但存在明显差异。水热作用在时空尺度上具有明显空间差异性,不同地区影响植被变化的主控因子不同。     

神农架龙门河地区的植被制图及植被现状分析

依据龙门河地区所处位置的植被地理分布规律性 ,绘制了该地区 1∶50 0 0 0的植被复原图。并在野外调查、资料搜集的基础上 ,辅以全球定位系统 (GPS)、GIS软件及TM影像数据 ,绘制了该地区 1∶50 0 0 0的植被类型图。结果表明 :1 )植被海拔分布由低至高依次为常绿阔叶林 (海拔 90 0m以下 ) ,硬叶常绿阔叶林 (海拔 90 0～ 1 30 0m)、常绿落叶阔叶混交林 (海拔 1 30 0～ 1 60 0m)以及落叶阔叶林 (海拔 1 60 0～ 2 2 0 0m)。 2 )龙门河地区林地面积 441 9.2hm2 ,占该地区总面积的 93 .71 % ,共计 8个植被型 65个群系。其中常绿落叶阔叶混交林面积最大 ,为 1 674.0 9hm2 ,占林地面积的 37.88%。另外 ,果园 (3种类型 )和农田两种农业用地面积 2 2 8.1 2hm2 ,占总面积的 4 .84%。 3)由植被复原图与现状植被类型图叠加分析可知 ,干扰后增加了针叶林、针阔混交林、灌丛、草地 4种植被类型 ,占龙门河地区总面积的 34 .6 %。其中针阔混交林所占面积最大 ,996 .79hm2 。     

Automating analysis of vegetation with computer vision: Cover estimates and classification

This study develops an approach to automating the process of vegetation cover estimates using computer vision and pattern recognition algorithms. Visual cover estimation is a key tool for many ecological studies, yet quadrat‐based analyses are known to suffer from issues of consistency between people as well as across sites (spatially) and time (temporally). Previous efforts to estimate cover from photograps require considerable manual work. We demonstrate that an automated system can be used to estimate vegetation cover and the type of vegetation cover present using top–down photographs of 1 m by 1 m quadrats. Vegetation cover is estimated by modelling the distribution of color using a multivariate Gaussian. The type of vegetation cover is then classified, using illumination robust local binary pattern features, into two broad groups: graminoids (grasses) and forbs. This system is evaluated on two datasets from the globally distributed experiment, the Nutrient Network (NutNet). These NutNet sites were selected for analyses because repeat photographs were taken over time and these sites are representative of very different grassland ecosystems—a low stature subalpine grassland in an alpine region of Australia and a higher stature and more productive lowland grassland in the Pacific Northwest of the USA. We find that estimates of treatment effects on grass and forb cover did not differ between field and automated estimates for eight of nine experimental treatments. Conclusions about total vegetation cover did not correspond quite as strongly, particularly at the more productive site. A limitation with this automated system is that the total vegetation cover is given as a percentage of pixels considered to contain vegetation, but ecologists can distinguish species with overlapping coverage and thus can estimate total coverage to exceed 100%. Automated approaches such as this offer techniques for estimating vegetation cover that are repeatable, cheaper to use, and likely more reliable for quantifying changes in vegetation over the long‐term. These approaches would also enable ecologists to increase the spatial and temporal depth of their coverage estimates with methods that allow for vegetation sampling over large spatial scales quickly.     

基于环境卫星数据的黄河湿地植被生物量反演研究

回归模型拟合植被指数与生物量的定量关系是植被生物量反演的重要研究方法之一.研究在此基础上,基于环境卫星遥感数据和同步野外实地采样数据,以郑州黄河湿地自然保护区为试验区,比较MLRM(多元线性回归模型)与SCRM(一元曲线回归模型)反演植被生物量的能力,并估算研究区植被生物量,生成研究区生物量分布图.结果表明,文中所建立的MLRM在研究区具有较好的反演精度和预测能力.其模型显著性检验为极显著,相关系数为0.9791,模型拟合精度达到29.8 g/m2,其模型预测结果系统误差为49.9g/m2,均方根误差为67.2 g/m2,预测决定系数为0.8742,比传统的一元回归模型具有更高的精度和可靠性.估算研究区域2010年8月湿生植被生物量约为6.849199 t/hm2,相对误差为4.73％.     

生物土壤结皮对照相法测量植被覆盖度结果的影响

植被覆盖度测度的准确性很大程度上影响着研究结论是否科学合理。在干旱半干旱退化草原区,尤其是受采矿剧烈扰动的矿区,发育的生物土壤结皮(Biological soil crust,BSC)由于其颜色和光谱同绿色植被具有相似性,导致对植被覆盖度的测量存在一定的影响。以伊敏露天矿区为研究区,在西排土场和内排土场采集了含苔藓结皮、地衣结皮和藻结皮的样方相片各四组(每组中包含样方喷水前和喷水后的相片各一张),并采集了一组不含结皮的样方相片作为对照组,运用数码照相法提取植被覆盖度,通过不同的数据处理方法(最大似然分类法及RGB阈值法)进行植被覆盖度提取,设立对比试验,分析BSC对于植被覆盖度测度是否有影响,其影响大小如何,影响程度是否受BSC含水量大小的影响,并对比各常规处理方法的优劣,研究能否通过结合纹理特征与色彩信息剔除BSC对植被覆盖度提取值的影响。研究结论:1)基于照相法的常规数据处理方法提取植被覆盖度时,BSC的存在导致测得的植被覆盖度值偏高,且苔藓结皮、地衣结皮吸水后比吸水前影响更显著,藻结皮相反;2)3个演替阶段的BSC中,尤以含苔藓结皮的样方植被覆盖度高估最为明显,其次为地衣,而含藻结皮样方规律不明显;3)样方内BSC覆盖度越高,植被覆盖度越低,其植被覆盖度测度越不准确,因此在研究草原矿区这类草本植物覆盖度较低、结皮发育的区域时,应当注意BSC的影响;4)试通过应用纹理信息提出改进的提取方法,发现单纯的纹理分类精度极低,而结合了纹理信息与RGB色彩信息的分类精度较高;5)对两种常规分类方法的精度进行比较,RGB阈值法较最大似然分类法更为不准确,对植被覆盖度的高估接近最大似然分类法的2倍。对两种改进的提取方法的精度进行比较,二者都可以有效提高测量精度,基于波段合成的纹理分类方法最佳。四种方法精度由高到低的顺序为:纹理结合RGB法考虑生物土壤结皮的最大似然分类法普通最大似然分类法RGB阈值法。