Quantitative phytogeography of the Yukon Territory (NW Canada) on a chorological-phytosociological basis

This study is based on the analysis of the chorological spectra from 19 vegetation types obtained from a numerical classification of ca. 400 phytosociological relevés taken during a vegetation survey in the Yukon Territory (NW Canada).All vegetation types are well characterized in terms of their chorological features. This allowed an ecological-historical interpretation of the vegetation in the study area. The distribution of the various chorological categories within the vegetation types is strongly correlated with the main environmental influences, whose action led to the present floristical and vegetational characteristics of the area, such as glaciation, fire, permafrost and water availability.The results show how the phytosociological approach constitutes an effective methodological tool for clarifying the phytogeographical aspects in the historical-ecological interpretation of a large area.Nomenclature follows Hultén (1968), otherwise author names are specified.The field work was completed in the summer of 1978. We are grateful to Dr W. Stanek, Canadian Forestry Service, for coordination of the survey and for soil data, and to Prof. L. Orlóci for organization. Partial financial support was received from the Italian C.N.R.     

The power of potential natural vegetation (and of spatial‐temporal scale): a response to Carrión & Fernández (2009)

A commentary by Carrión & Fernández (Journal of Biogeography, 2009, 36 , 2202–2203) compared Holocene pollen records with models of potential natural vegetation (PNV) proposed in the phytosociological literature and concluded that the predicted PNV resulted from anthropogenic disturbance. However, the authors misinterpreted PNV, leading to two serious flaws in their assumptions: (1) PNV is not defined as a pre‐anthropic or climax plant community; and (2) PNV is not a concept restricted to the phytosociological method. Therefore we criticize the conclusions expressed in the commentary, and we stress the need for an interdisciplinary approach based on multi‐temporal and multi‐spatial scales to achieve a modern framework for the study of plant communities.     

基于植被指数的海南岛霸王岭热带森林地上生物量空间分布模拟

热带森林在全球碳循环方面扮演着重要的角色, 预测其生物量分布可以加深对碳循环过程的理解。然而目前基于植被指数模拟技术进行热带森林生物量分布的研究报道较少。该文以海南岛霸王岭林区热带森林为研究对象, 在基于遥感影像和135个公里网格样地调查的基础上, 分别选取归一化差异植被指数(NDVI)、短红外湿度植被指数(MVI5)、中红外湿度植被指数(MVI7)和比值植被指数(RVI)与总物种生物量、顶极种生物量和先锋种生物量做相关分析, 并利用逐步线性回归分析分别构建了基于植被指数的生物量回归模型; 利用残差图对模型的有效性进行检验。结果表明, MVI7和MVI5与总物种和顶极种生物量关系显著, 而NDVI和RVI对先锋种生物量具有较好的指示作用; 总物种、顶极种和先锋种生物量预测精度较高的区域分别占总面积的69.24%、73.98%和88.08%, 表明3个生物量模型均具有较好的拟合精度; 模拟结果表明总物种和顶极种生物量主要集中于研究区中部、北部和西南部区域, 而先锋种生物量无明显的分布规律, 是不均衡地散布于整个研究区域, 反映了群落组成结构、干扰历史、地形及气候因素等的影响。     

Assessing the impacts of fire on the vegetation resources that are available to the local communities of the seasonal wetlands of the Okavango, Botswana, in the context of different land uses and key government policies

The Okavango wetlands in north western Botswana are the most fire-prone environment in Botswana. Most of these fires are anthropogenic. The fires in this environment are thought to impact the environment negatively and therefore practices that are associated with extensive use of fire have been strongly criticized. Despite this, there has been little work done to understand how these fires impact the wetlands environment and its dynamics, especially the vegetation resources that are used by the local communities in the wetlands. The objective of the study was to identify fire spatial and temporal trends in relation to settlement distribution, through the use of remote sensing, socio-economic and phytosociological surveys. The fire history results show that geographically there has not been any significant change in vegetation structure and that in fact fires may have promoted biodiversity. The results of analysis show an overall variance on vegetation structure of 23% whereas the rest are unaccounted for. There is a strong association between settlements, ethnicities, literacy and fire occurrences. The most fire-prone areas are inhabited by communities that have used fire in the past for various resource use practices.     

Bioclimatic classification of US vegetation along a coast-to-coast macrotransect crossing central United States. I: Mediterranean vegetation

This report presents the first of two parts of a bioclimatic classification of the vegetation of the United States. Using a geographical information system, 987 weather stations were located along a longitudinal macrotransect from the shores of the Atlantic to Pacific on four maps: Map of the Physiographic Divisions of the Conterminous US, US Potential Natural Vegetation Map, US Ecoregion Map, and Terrestrial Ecosystems-Isobioclimates Map of the Conterminous United States. Based on these maps, bibliographic resources and field data, we deduced the potential natural vegetation (PNV) of each weather station; then, we assigned the different PNV types to alliance or association levels using the US National Vegetation Classification (USNVC). In a next step, USNVC groups were related with similar level phytosociological syntaxa described in the study area. The bioclimatic distribution of the USNVC units defined was then interpreted using the bioclimatic classification proposed in successive approximations by S. Rivas-Martínez. The distribution of USNVC alliances was mainly linked to the macrobioclimates (Mediterranean, Temperate, and Tropical) of the longitudinal gradient examined, though some edaphic factors induced the appearance of specialized plant groups. Herein, we present our data for the Mediterranean macrobioclimate, in which 53 alliances and 28 isobioclimates were identified.     

黄土高原典型区植被冗亏

选择了黄土高原中部典型区——泾河流域为研究区域。采用Holdridge潜在蒸发方法计算出了泾河流域的气候干燥度指数,构建了遥感植被指数与气候干燥度指数之间的回归模型。通过该模型反衍出了泾河流域潜在植被指数,提出以该指数为基础的植被冗亏格局的评价新方法。通过该评价方法发现,在泾河流域西北部的大部分子流域的植被冗亏指数小于-0.2,植被亏缺较为严重;在自然环境较差的流域北部,植被冗亏指数介于-0.20到-0.10之间,植被亏缺较轻;而流域东南部山区的大部分子流域的植被冗亏指数介于-0.10到0.10之间,植被亏缺最轻。从植被冗亏的时间尺度上分析,植被亏缺主要发生在植被生长旺盛的6~9月份,其中农田植被亏缺最大,冗亏指数在7月份可达到-0.51;稀疏草原植被亏缺较小,其冗亏指数最小值在-0.18左右;森林植被的冗亏指数接近于0。     

A vegetation-ecological approach to the classification and evaluation of potential natural vegetation of the Fagetea crenatae region in Tohoku (northern Honshu), Japan

A new vegetation-ecological approach is proposed for classification and evaluation of vegetation zones by means of phytosociological landscape analysis, based on the potential natural vegetation. The study area is the “Fagetea crenatae region” of the cool-temperate zone of Tohoku (northern Honshu) and the northern parts of Kanto. The area was divided into 953 geographic quadrats on a base map at a scale of 1 ∶ 500000. Based on climax complexes of vegetation in each quadrat, 55 community sub-groups were distinguished as basic units of community complex and vegetation landscapes. The community sub-groups were then grouped into 17 larger community groups by the phytosociological table method. As a result, three phytogeographic vegetation zones (Japan Sea side, inland areas and Pacific side) were classified. For each of these community sub-groups, five geographical and climatic variables (average altitude, mean annual temperature, Kira's warmth index, annual precipitation and mean annual maximum snow depth) were averaged, and the community sub-groups in the same community group, which resembled each other ecologically, were assembled into 28 clusters. The clusters were combined into 11 ecological groups by means of Pearson's similarity ratio of geographical and climatic characteristics. By comparing these ecological groups as a vegetation complex, four phytogeographic vegetation zones (Japan Sea side, inland areas, Pacific side and northern Honshu) corresponding to each potential natural vegetation region with distinct environmental characteristics, were newly classified.     

The global distribution of ecosystems in a world without fire

This paper is the first global study of the extent to which fire determines global vegetation patterns by preventing ecosystems from achieving the potential height, biomass and dominant functional types expected under the ambient climate (climate potential). To determine climate potential, we simulated vegetation without fire using a dynamic global-vegetation model. Model results were tested against fire exclusion studies from different parts of the world. Simulated dominant growth forms and tree cover were compared with satellite-derived land- and tree-cover maps. Simulations were generally consistent with results of fire exclusion studies in southern Africa and elsewhere. Comparison of global 'fire off' simulations with landcover and treecover maps show that vast areas of humid C(4) grasslands and savannas, especially in South America and Africa, have the climate potential to form forests. These are the most frequently burnt ecosystems in the world. Without fire, closed forests would double from 27% to 56% of vegetated grid cells, mostly at the expense of C(4) plants but also of C(3) shrubs and grasses in cooler climates. C(4) grasses began spreading 6-8 Ma, long before human influence on fire regimes. Our results suggest that fire was a major factor in their spread into forested regions, splitting biotas into fire tolerant and intolerant taxa.     

中国东北主要植被类型的分布与气候的关系

本文根据吉良的热量指标和作者提出的湿度指数,研究了我国东北主要植被类型的分布与气候之间的关系：1．确定了东北地区10个水平地带性植被类型的热量分布范围和水热指标的平均值。2．研究了东北山地垂直地带性植被类型的水热指标分布特点,并用定量指标讨论了东北东部山地岳桦林带的分布、大兴安岭存在山地冻原和东北植被区域的分界线问题。     

Impacts of climate change on the vegetation of Africa: an adaptive dynamic vegetation modelling approach

Recent IPCC projections suggest that Africa will be subject to particularly severe changes in atmospheric conditions. How the vegetation of Africa and particularly the grassland–savanna–forest complex will respond to these changes has rarely been investigated. Most studies on global carbon cycles use vegetation models that do not adequately account for the complexity of the interactions that shape the distribution of tropical grasslands, savannas and forests. This casts doubt on their ability to reliably simulate the future vegetation of Africa. We present a new vegetation model, the adaptive dynamic global vegetation model (aDGVM) that was specifically developed for tropical vegetation. The aDGVM combines established components from existing DGVMs with novel process‐based and adaptive modules for phenology, carbon allocation and fire within an individual‐based framework. Thus, the model allows vegetation to adapt phenology, allocation and physiology to changing environmental conditions and disturbances in a way not possible in models based on fixed functional types. We used the model to simulate the current vegetation patterns of Africa and found good agreement between model projections and vegetation maps. We simulated vegetation in absence of fire and found that fire suppression strongly influences tree dominance at the regional scale while at a continental scale fire suppression increases biomass in vegetation by a more modest 13%. Simulations under elevated temperature and atmospheric CO₂ concentrations predicted longer growing periods, higher allocation to roots, higher fecundity, more biomass and a dramatic shift toward tree dominated biomes. Our analyses suggest that the CO₂ fertilization effect is not saturated at ambient CO₂ levels and will strongly increase in response to further increases in CO₂ levels. The model provides a general and flexible framework for describing vegetation response to the interactive effects of climate and disturbances.     

基于地理探测的黄土高原植被生长对气候的响应

为探讨黄土高原不同植被类型对气候变化的响应机制,以2002-2019年黄土高原归一化植被指数(NDVI)数据为基础,利用趋势分析、Hurst指数、地理探测器等方法分析不同植被类型NDVI变化趋势及其与气象因子的关系.结果 表明:2002-2019年,黄土高原不同植被类型NDVI以增长趋势和同向中持续性为主,仅栽培植被在...     

Vegetation maps based on remote sensing are informative predictors of habitat selection of grassland birds across a wetness gradient

Vegetation is a major environmental factor influencing habitat selection in bird species. High resolution mapping of vegetation cover is essential to model the distribution of populations and improve the management of breeding habitats. However, the task is challenging for grassland birds because microhabitat variations relevant at the territory scale cannot be measured continuously over large areas to delineate areas of higher suitability. Remote sensing may help to circumvent this problem. We addressed this issue by using SPOT 5 imagery and phytosociological data. We mapped grassland vegetation in a floodplain using two methods. We (i) mapped the continuous Ellenberg index of moisture and (ii) identified 5 vegetation classes distributed across the wetness gradient. These two methods produced consistent output maps, but they also provided complementary results. Ellenberg index is a valuable proxy for soil moisture while the class approach provided more information about vegetation structure, and possibly trophic resources. In spite of the apparent uniformity of meadows, our data show that birds do not settle randomly along the moisture and vegetation gradients. Overall birds tend to avoid the driest vegetation classes, i.e. the highest grounds. Thus, vegetation maps based on remote sensing could be valuable tools to study habitat selection and niche partition in grassland bird communities. It is also a valuable tool for conservation and habitat management.     

基于无人机高清数码影像和高光谱遥感数据反演大豆典型生育期氮平衡指数

氮平衡指数(NBI)是反映作物长势的重要指标之一.通过测量NBI可以快速监测作物氮肥盈亏状况,为农业生产和管理提供精准信息.本文以无人机高清数码影像和高光谱遥感数据,以及地面实测大豆NBI数据为基础,分析大豆从开花期到成熟期,原始光谱和红外、近红外波段的导数光谱与NBI的相关性,筛选敏感波段并计算植被指数.采用经验模型法构建NBI反演模型,通过分析验证模型的决定系数(R^2)和均方根误差(RMSE),得出最佳反演模型.结果表明:大豆NBI与导数光谱反射率的相关性好于与原始光谱反射率的相关性;本文筛选的14个植被指数中,除了导数光谱光化学植被指数与大豆NBI呈不显著相关外,其余13个植被指数与大豆NBI呈极显著相关;利用13个植被指数构建NBI反演模型,并分析模型反演精度,结果显示,利用导数光谱差值植被指数构建NBI反演模型的精度最高,R^2和RMSE分别为0.771和3.077,利用该模型生成大豆典型生育期NBI分布图,能够反映大豆的长势状况.通过多载荷无人机获取的高清数码影像和高光谱遥感数据进行NBI估算,能够实时、动态、非破坏性、快速有效地监测大豆氮素营养状况,可为大豆氮肥精确管理提供简便实用的方法.     

2000—2018年黄河流域生长季植被指数变化及其对气候因子的响应

黄河流域位于我国干旱、半干旱地区,生态环境脆弱,探究其植被指数变化和对气候因子的响应对该地区生态建设具有重要意义。基于黄河流域2000—2018年MODIS归一化植被指数、增加型植被指数和气象数据,利用最大值合成法、趋势分析和相关分析等方法,分析了两种植被指数的时空变化特征及受气候因子的影响机制,探讨了NDVI与EVI在反映植被变化和对气候因子响应的差异。结果表明：2000—2018年,黄河流域地区植被NDVI、EVI分别以0.059/10a、0.038/10a的变化率增加,空间上以显著改善为主,面积占比分别为77.13%和75.27%,大多分布在1000—1500 m海拔处,中游地区改善较为良好,林地改善率最高。显著退化区域较小,主要分布在巴颜喀拉山西北部、西宁市、银川市、包头市、呼和浩特市、太原市、西安市及关中盆地和洛阳市周边,建设用地退化率最高。在生长季期间,植被指数变化与气温和降水以正相关为主,气温滞后时间为1个月,降水滞后时间为3个月,都为草地最为相关;与辐射之间为负相关,滞后时间为3个月,其中林地最为相关。在0.05显著性检验水平下,驱动黄河流域生长季植被变化的主要气候因子...     

Formalized reproduction of an expert‐based phytosociological classification: A case study of subalpine tall‐forb vegetation

Abstract. Delimitation of vegetation units in phytosociology is traditionally based on expert knowledge. Applications of expert‐based classifications are often inconsistent because criteria for assigning relevés to vegetation units are seldom given explicitly. Still, there is, e.g. in nature conservation, an increasing need for a consistent application of vegetation classification using computer expert systems for unit identification. We propose a procedure for formalized reproduction of an expert‐based vegetation classification, which is applicable to large phytosociological data sets. This procedure combines Bruelheide's Cocktail method with a similarity‐based assignment of relevés to constancy columns of a vegetation table. As a test of this method we attempt to reproduce the expert‐based phytosociological classification of subalpine tall‐forb vegetation of the Czech Republic which has been made by combination of expert judgement and stepwise numerical classification of 718 relevés by TWINSPAN. Applying the Cocktail method to a geographically stratified data set of 21794 relevés of all Czech vegetation types, we defined groups of species with the statistical tendency of joint occurrences in vegetation. Combinations of 12 of these species groups by logical operators AND, OR and AND NOT yielded formal definitions of 14 of 16 associations which had been accepted in the expert‐based classification. Application of these formal definitions to the original data set of 718 relevés resulted in an assignment of 376 relevés to the associations. This assignment agreed well with the original expert‐based classification. Relevés that remained un‐assigned because they had not met the requirements of any of the formal definitions, were subsequently assigned to the associations by calculating similarity to relevé groups that had already been assigned to the associations. A new index, based on frequency and fidelity, was proposed for calculating similarity. The agreement with the expert‐based classification achieved by the formal definitions was still improved after applying the similarity‐based assignment. Results indicate that the expert‐based classification can be successfully formalized and converted into a computer expert system.     

林地叶面积指数遥感估算方法适用分析

叶面积指数是与森林冠层能量和CO2交换密切相关的一个重要植被结构参数,为了探讨估算林地叶面积指数LAI的遥感适用方法和提高精度的途径,利用TRAC仪器测定北京城区森林样地的LAI,从Landsat TM遥感图像计算NDVI、SR、RSR、SAVI植被指数,分别建立估算LAI的单植被指数统计模型、多植被指数组合的改进BP神经网络,获取最有效描述LAI与植被指数非线性关系的方法并应用到TM图像估算北京城区LAI。结果表明,单植被指数非线性统计模型估算LAI的精度高于线性统计模型;多植被指数组合神经网络中,以NDVI、RSR、SAVI组合估算LAI的精度最高,估算值与观测值线性回归方程的R2最高,为0.827,而RMSE最低,为0.189,神经网络解决了多植被指数组合统计模型非线性回归方程的系数较多、较难确定的问题,可较为有效的应用于遥感图像林地LAI的估算。     

遥感植被指数与植物多样性的相关性及空间分布特征研究——以海口市主城区为例

植物多样性监测是开展物种保护与植被景观规划的重要基础,对实施生物多样性的优先区域保护具有重要意义.该文以海口市主城区为例,利用Landsat 8遥感数据与样方实测数据分析了植被指数与植物多样性指数之间的相关性,根据相关性分析结果构建植物多样性遥感监测数学模型,并筛选出最优模型用于监测研究区植物多样性的空间分布状况.结果...     

基于植被指数的典型草原区生物量模型——以内蒙古锡林浩特市为例

利用遥感估测地上生物量是国内外生态学与地理学的研究热点。但基于植被指数的生物量回归模型结果差异较大,究竟哪种植被指数与哪种模型更适合典型草原的生物量反演,是现代草地遥感急需解决的问题之一。该文基于TM影像数据的不同植被指数(VI)差异性,分别选取了RVI(比值植被指数)、NDVI(归一化差异植被指数)、SAVI(土壤调节植被指数)、MASVI(修改型土壤调整植被指数)和RSR(简化比率植被指数)5种植被指数,与同期的内蒙古典型草原区地面实测地上生物量做相关分析,分别建立了5种植被指数与地上生物量的线性及3种非线性(对数、二次多项式、三次多项式)回归模型。研究结果表明:对于中国北方典型草原区而言,地上生物量与5种植被指数(RVI、NDVI、SAVI、MSAVI和RSR)均呈现出显著相关,但地上生物量与后4种植被指数是正相关,与RVI为负相关;利用5种植被指数(RVI、NDVI、SAVI、MSAVI和RSR)监测草地植被生物量的复相关系数均大于0.6,充分说明利用植被指数检测典型草原生物量是一种简单可行的方法;NDVI建立的生物量回归模型,其复相关系数大于其它4类植被指数(RVI、SAVI、MSAVI和RSR),说明NDVI-生物量模型优于植被指数RVI、SAVI、MSAVI和RSR 模型,其模拟地表生物量的效果好;对于TM影像来说,植被生物量的线性模型与3种非线性模型(三次多项式生物量模型、二次多项式生物量模型、对数模型)都表现出较好的模拟效果,都通过了0.01的显著性检验,而且该研究的结果显示出三次多项式生物量回归模型最优,其次是二次多项式生物量模型,再次是线性模型,相对较差的是对数模型。通过NDVI-生物量三次多项式回归模型模拟锡林浩特草原的生物量,可以看出整个研究区的地上生物量基本上是东高西低、东南高西北低的趋势,这与研究区的地形、气候及土地利用等多种因素有关。     

基于地面调查的植被生态质量综合评估指标体系构建

植被是陆地生态系统的主体,是保障生态质量的基础,也是基于自然的生态系统增汇、实现“碳中和”的重要利器。植被是生态质量评价的核心要素,但目前的生态质量评价研究中所用到的植被指标多是通过遥感反演或者气象指数模型计算得到的,而基于典型生态系统尺度地面调查的植被观测数据更直接、更准确,数据也很丰富,却很少用于生态质量评价,也缺乏系统的评价指标体系。通过文献研究、专家研讨和问卷调查,并借鉴群落退化演替和生态系统长期监测研究的理论基础,构建基于地面调查的植被生态质量综合评估指标体系。该指标体系整体分为三级,一级综合指数由群落结构指数、物质生产指数、生物多样性指数、群落发展或者演替趋势4个二级分项指标构成,二级分项指标由12—14个三级指标组成,不同植被类型各有其特征指标。该体系将完善我国多尺度陆地生态系统的生态质量评价指标体系,为新时期国家生态质量评价提供科学建议,为我国生态文明建设提供技术支撑。     

Wide Dynamic Range Vegetation Index for remote quantification of biophysical characteristics of vegetation

The Normalized Difference Vegetation Index (NDVI) is widely used for monitoring, analyzing, and mapping temporal and spatial distributions of physiological and biophysical characteristics of vegetation. It is well documented that the NDVI approaches saturation asymptotically under conditions of moderate-to-high aboveground biomass. While reflectance in the red region (rho(red)) exhibits a nearly flat response once the leaf area index (LAI) exceeds 2, the near infrared (NIR) reflectance (PNIR) continue to respond significantly to changes in moderate-to-high vegetation density (LAI from 2 to 6) in crops. However, this higher sensitivity of the rho(NIR) has little effect on NDVI values once the rho(NIR) exceeds 30%. In this paper a simple modification of the NDVI was proposed. The Wide Dynamic Range Vegetation Index, WDRVI = (a * rho(NIR-rho(red))/(a * rho(NIR) + rho(red)), where the weighting coefficient a has a value of 0.1-0.2, increases correlation with vegetation fraction by linearizing the relationship for typical wheat, soybean, and maize canopies. The sensitivity of the WDRVI to moderate-to-high LAI (between 2 and 6) was at least three times greater than that of the NDVI. By enhancing the dynamic range while using the same bands as the NDVI, the WDRVI enables a more robust characterization of crop physiological and phenological characteristics. Although this index needs further evaluation, the linear relationship with vegetation fraction and much higher sensitivity to change in LAI will be especially valuable for precision agriculture and monitoring vegetation status under conditions of moderate-to-high density. It is anticipated that the new index will complement the NDVI and other vegetation indices that are based on the red and NIR spectral bands.