Predicting vegetation types at treeline using topography and biophysical disturbance variables

Abstract. The relationships between four vegetation types and variables representing topography and biophysical disturbance gradients were modeled for a study area in east-central Glacier National Park, Montana. Four treeline transition vegetation types including closed-canopy forest, open-canopy forest, meadow, and unvegetated surfaces (e.g. rock, snow, and ice) were identified and mapped through classification of satellite data and subsequent field verification. Topographic characteristics were represented using a digital elevation model and three variables derived from topoclimatic potential models (solar radiation potential, snow accumulation potential, and soil saturation potential). A combination of generalized additive and generalized linear modeling (GAM and GLM, respectively) techniques was used to construct logistic regression models representing the distributions of the four vegetation types. The variables explained significant amounts of variation in the vegetation types, but high levels of variation remained unexplained. A comparison of ‘expected’ and ‘observed’ vegetation patterns suggested that some unexplained variation may have occurred at the basin scale. A suite of tools and techniques is presented that facilitates predicting landscape-scale vegetation patterns and testing hypotheses about the spatial controls on those patterns.     

Ecotope mapping for landscape ecological assessment of habitat and ecosystem

An ecotope (spatial eco-space) map that considers topography and bio-organism-relevant variables emerges as an important basic framework when landscape-scale characteristics for ecosystem management and wildlife conservation are needed. A spatio-geoecological framework based on geographic information systems (GIS) and a vegetation survey were developed for wildlife habitat evaluation of national parks and applied to a representative rugged valley area of Mt. Sorak National Park in Korea. An ecotope map was classified into hundreds of types and dozens of groups by combining biological and geophysical variables. Variables included: forest vegetation type, topographic solar radiation, normalized difference vegetation index (NDVI), elevation, and anthropogenic factors, such as, streams and roads. Layers of GIS variables were produced by field surveys, modeling, satellite images, or digitalization. Vegetation surveys were carried out to identify finer-scale distribution of vegetation types in the rugged valley area. Digital forest vegetation maps from the Forestry Administrator were then modified using the field-surveyed vegetation maps. Topographic solar radiation was predicted with a daily topographic radiation model. The NDVI was calculated from the satellite imagery of a Landsat Thematic Mapper. A digital elevation model (DEM) was used and the other layers were digitized using topographical maps with a scale of 1:25000. The aim of this study is to determine the geoecological factors relating to the spatial pattern of plant community. It was cleared by the spatial pattern of environmental variables and vegetation characteristics by detrended correspondence analysis using plant species and the environmental variables of each plot. The ordination component value of the first axis shows significant regression to some environmental variables. A case study of habitat evaluation was carried out using the resultant ecotope map. The spatial distribution of potential goral habitat and vegetation characteristics were predicted and the impact of human trails on the neighboring vegetation was also examined for restoration planning. The GIS-based framework developed for wildlife habitat evaluation is useful for natural resource management and human activity control in national parks in Korea.     

Influence of vegetation cover on evapotranspiration patterns in mountainous areas

The study presents results of calculation of potential evapotranspiration based on vegetation cover and actual solar energy income modeling obtained in the Jalovecky creek experimental hydrological basin in the Western Tatra mountains. Vegetation cover in the basin is represented by Bare rock, Grass, Natural grassland, Coniferous forest and Dwarf pine. Spatial evapotranspiration patterns for vegetation cover were calculated with three different methods build in the SOLEI model. They are Simple regression model, Radiation model by FAO and Penman-Monteith model. Vegetation cover is represented in all mentioned methods by albedo maps derived from the land use grid map. Together with Digital elevation model (DEM) it is the main input value to the SOLEI model. Albedo coefficients influence mainly solar energy income to the slopes. Because the Simple regression model and Radiation model by FAO are mainly based on solar energy income, the shapes of calculated spatial evapotranspiration patterns are similar to solar energy spatial maps. Results obtained from PenmanMonteith model are more closed to vegetation maps.     

Net radiation balance for two forested slopes on opposite sides of a valley

Measurements of the net radiation balance of two forested sites on the opposite slopes of a valley in south-western Germany, made over 3 years, are presented in this study. Radiation sensors were mounted horizontally on two measurement towers above two beech stands. The direct part of the measured short-wave incoming radiation was adjusted according to the slopes angle to convert horizontally measured radiation data into surface-parallel radiation fluxes. During periods when contemporaneous measurements of slope-parallel and horizontal radiation fluxes were available, the calculation of surface-parallel radiation fluxes from the horizontally recorded net radiation components were compared with measured values. The net radiative fluxes parallel to the slopes were calculated for a period of 36 months and analysed. Results show that the different aspects of both sites cause significant differences of the net radiation balance. In June, when the elevation of the sun is highest, incoming solar radiation K received on the NE-slope was 9% lower than K received on the SW-slope. During the winter months, the differences were much greater and incoming solar radiation to the NE-slope was 50% of that to the SW-slope. Due to the differing solar irradiance, net radiation fluxes were significantly higher on the SW-slope than on the NE-slope. For long-wave radiation only small differences between both slopes could be found. Since radiative fluxes determine the energy balance and hence the microclimate and water balance of a forest stand, these differences in the net radiation balance between the slopes are important for the vegetation.     

小五台亚高山草甸与生境关系分析

该文结合野外植被调查,在获取更为详细的景观尺度生境数据基础上,探讨了小五台亚高山草甸植物群落与直接环境因子之间的定量关系。典范对应分析(CCA)的结果表明:1) 在小五台的亚高山草甸分布地段,热量、养分和水分条件构成了其生境特征差异的基本格局;2) 用效应温度和太阳直接辐射量所表征的热量因子,指示出研究区植物群落最基本的分化,说明热量条件是制约研究区草甸群落分布的最重要的因子;3) 养分状况的差异,除了说明生境条件本身的差异外,也在一定程度上指示了放牧干扰对群落分布的影响;4) 由地形等因素控制的土壤表层水分状况,则反映了草甸植物群落分布所受到的水分条件影响。     

毛乌素沙地海流兔河流域植被净初级生产力估算

采用CASA(Carnegie-Ames-Stanford Approach)模型,结合TERRA MODIS卫星数据和气象数据,对毛乌素沙地海流兔河流域2015年各月的植被净初级生产力(NPP)进行估算,并对植被NPP月平均值的时空分布规律及其与气象因子和地下水位埋深的关系进行了分析.结果表明:毛乌素沙地海流兔河流域2015年植被NPP总量为2.88×1011 g,生长季(4月份至10月份)的植被NPP总量达2.81×1011 g,占全年植被NPP总量的97.57%.随着时间推移,植被NPP月平均值和归一化差分植被指数(NDVI)月平均值呈"缓慢增加—急剧增加—急剧下降"的变化趋势.植被NPP月平均值季节变化明显,春季、夏季、秋季和冬季植被NPP月平均值之和分别为20.55、69.39、20.46和0.48 g·m-2.从空间分布上看,中部河谷和滩地的植被NPP月平均值总体上高于东南部、西部和西北部等沙丘荒漠区.月平均气温对植被NPP月平均值变化的影响最大,其次为平均实际日蒸散发量和地表月太阳辐射.植被NPP月平均值随着地下水位埋深的增加而减小,最大值出现在地下水位埋深1~2 m之间.上述研究结果显示:采用CASA模型可以较好地估算毛乌素沙地海流兔河流域植被NPP值,月平均气温和地下水位埋深对该流域植被NPP值的影响较大.     

Estimating mean monthly incident solar radiation on horizontal and inclined slopes from mean monthly temperatures extremes

Although satellite-borne sensors are now available to estimate cloud cover and incoming short-wave radiation across the Earth’s surface, the study of climatic variation and its impact on terrestrial and marine ecosystems involves historical analyses of data from networks of weather stations that only record extremes in temperatures and precipitation on a daily basis. Similarly, when projections are made with global atmospheric circulation models, the spatial resolution of predicted radiation is too coarse to incorporate the effects of heterogeneous topography. In this paper, we review the development and set forth a set of general equations that allow both diffuse and direct solar radiation to be estimated for each month on the basis of mean daily maximum and minimum temperatures, latitude, elevation, slope, and aspect. Adjustments for differences in slope, aspect, and elevation are made by varying the fraction of diffuse and direct solar beam radiation. To test the equations on various slopes and under different climatic conditions, we drew on high-quality radiation data recorded at a number of sites on three continents. On horizontal surfaces the set of equations predicted both direct and diffuse components of solar radiation within 1%–7% of recorded values. On slopes, estimates of monthly mean solar radiation were with 13% of observed values with a mean error of less than 2 MJ m^–2day^–1 over any given month. Received: 22 October 1999 / Revised: 14 May 2000 / Accepted: 5 June 2000     

Analysis of topography and vegetation distribution using a digital elevation model: case study of a snowy mountain basin in northeastern Japan

This study examines the relations between the local variations in vegetation and topography using logistic regression (LR) and GIS in a snowy basin in the Ohu Mountains of northeastern Japan. The spatial distribution of seven vegetation classes interpreted from aerial photographs—(a) large-sparse crown beech forest, (b) middle-dense crown beech forest, (c) dwarf beech scrub, (d) dwarf bamboo thicket, (e) Japanese white pine forest, (f) snow-avalanche scrub or meadow, and (g) riparian forest—was analyzed with terrain parameters derived from a 10 m digital elevation model (10 m DEM) and parameters of landslide distribution and surface geology. While large-sparse crown beech forests dominate the slopes, smaller crown beech forests or scrubs are often found on the west-facing (i.e., windward side) upper parts of slopes and crests. On the contrary, snow-avalanche scrubs or meadows are found on the leeward side of steep slopes and concave plan curvatures. Dwarf bamboo thickets are often found on east-facing (i.e., leeward side) gently sloping crests, where the snow remains until summer. Japanese white pine forests respond positively to sharp ridges, whereas riparian forests show a positive response to the gently sloping lower parts of slopes and bottomlands at low elevation. The heterogeneous vegetation distribution in the basin indicates differences in site conditions (e.g., soil–water conditions), and the existence of various disturbance regimes induced by the strong winter monsoon with heavy snowfall, snow movements (e.g., avalanches), and temporal differences in snowmelt on different topographies. The estimated vegetation maps could be used for forest management and restoration.

     

Incoming solar radiation patterns and vegetation response: Examples from the natal drakensberg

Summary A method of accurately estimating and mapping patterns of incoming solar radiation fluxes on sloping terrain, using data from standard meteorological instruments, is described. The results of the radiation maps produced are then related to a specific example of vegetation successional changes in the Cathedral Peak area of the Natal Drakensberg mountain range, indicating that these changes occur most readily on cooler aspects. For the same region, the differences in the major plant communities at two other sites, attributable largely to variations in incoming solar radiation loads, are discussed.The authors wish to thank the Department of Forestry of the Republic of South Africa for providing data and for facilitating fieldwork to be undertaken at Cathedral Peak. This Research was funded in part by the South African Council for Scientific and Industrial Research, whose support is hereby gratefully acknowledged (by R.E.S.). The maps illustrating this paper were prepared by Mrs. C. Coetzee and Mr B. Martin of the University of Natal, Pietermaritzburg.     

Regional application of an ecosystem production model for studies of biogeochemistry in Brazilian Amazonia

The degree to which primary production, soil carbon, and trace gas fluxes in tropical forests of the Amazon are limited by moisture availability and other environmental factors was examined using an ecosystem modelling application for the country of Brazil. A regional geographical information system (GIS) serves as the data source of climate drivers, satellite images, land cover, and soil properties for input to the NASA Ames-CASA (Carnegie-Ames-Stanford Approach) model over a 8-km grid resolution. Simulation results lead us to hypothesize that net primary production (NPP) is limited by cloud interception of solar radiation over the humid north-western portion of the region. Peak annual rates for NPP of nearly 1.4 kg C m^–2 year^–1 are localized in the seasonally dry eastern Amazon in areas that we assume are primarily deep-rooted evergreen forest cover. Regional effects of forest conversion on NPP and soil carbon content are indicated in the model results, especially in seasonally dry areas. Comparison of model flux predictions along selected eco-climatic transects reveal moisture, soil, and land use controls on gradients of ecosystem production and soil trace gas emissions (CO₂, N₂O, and NO). These results are used to formulate a series of research hypotheses for testing in the next phase of regional modelling, which includes recalibration of the light-use efficiency term in NASA-CASA using field measurements of NPP, and refinements of vegetation index and soil property (texture and potential rooting depth) maps for the region.     

长白山阔叶红松林生长季热量平衡变化特征

根据长白山阔叶红松林2001年5月下旬至10月上旬微气象梯度观测资料和辐射、土壤热通量资料,用波文比-能量平衡方法(BREB方法)计算了森林的显热通量和感热通量,并计算了森林大气和植被体的储热量,分析了阔叶红松林热量平衡各项的日变化和季节变化,结果发现,热量平衡(净辐射)与太阳总辐射呈线性关系;热量平衡各项都与净辐射有相同的日变化特征,为昼正夜负的曲线．各项的绝对值一般表现为净辐射>潜热通量>感热通量>储热变化．受日照时间的影响,6～10月各分量正值的日持续时间逐渐缩短．月平均结果,白天净辐射6月份最大,10月上旬最小,变化于0～527W·m^-2,夜间的净辐射在0～-121W·m^-2．潜热通量白天和夜间分别在0～441、0～-81W·m^-2,感热通量昼夜分别在0～80、0～-26W·m^-2．储热变化则为0～44、0～-26W·m^-2．白天潜热通量占净辐射的比例8～10月逐渐下降,而感热通量和储热变化的比例9～10月明显上升,特别在严霜后2～3d,出现潜热通量比例突减、感热通量比例突增的现象．文中还对通量观测仪器、方法进行了简要分析．     

石羊河流域土地利用类型景观异质性

在GIS支持下,以TM/ETM遥感影像为数据源,利用人工解译方法得到石羊河流域14类景观,并结合数字高程模型(DEM),参考相关的地理基础图件,应用景观生态学理论和方法,采用景观空间格局指标对石羊河流域荒漠、绿洲为主的生态系统景观异质性做了分析。结果表明:耕地、林地、草地和沙地是主要的景观类型和结构成分,其相对频率平均值都在42%以上;在荒漠景观生态系统中,基质沙地的异质性是均质化方向上的异质性,而在绿洲景观生态系统中,基质林地、草地和耕地的异质性是异质化方向上的异质性;作为廊道的水系景观,其相对频率在荒漠和绿洲生态系统中都是较小的,且斑块和廊道异质性均表现为异质化方向上的异质性。研究结果对干旱内陆河流域土地有效利用及生态环境变化监测研究具有重要意义。     

荒漠人工固沙植被区土壤水分的时空变异性

表层土壤水分具有高度的时间和空间变异性.研究的目的:(1)揭示沙坡头人工固沙植被区浅层土壤水分的时空变异性特征;(2)确定驱动土壤水分变异的主要环境因子.在人工固沙植被区内一个4500m2的网格样地上每隔10m设置取样点,在连续7个月的时间内 (2005年4～10月),每隔15d用时域反射仪测量各样点表层以下15cm和30cm深度的土壤容积含水量.结果表明,该区网格尺度上浅层土壤水分的分布具有明显的空间变异性,其变异性随着土壤水分含量的降低而减小;相对海拔是驱动土壤水分空间变异的主要环境因子,其作用在降雨后尤为显著,且其对土壤下层的影响比上层更明显;植被和土壤水分含量的相关性时间序列与相对海拔一致--降雨使其相关性增加;土壤质地(土壤粒径分布)和土壤水分含量的相关性时间序列特征与植被和相对海拔相反,且其对土壤上层的影响比下层更明显.因此,在沙坡头荒漠人工固沙植被区,降雨后的短暂湿润期,地形和植被是驱动浅层土壤水分变异的主要影响因子,而随着降雨之后土壤逐渐变干,土壤质地的影响变得更加明显.     

Predictive mapping of alpine grasslands in Switzerland: Species versus community approach

Abstract. Separate logistic regression models were developed to predict the distribution and large-scale spatial patterns of dominant graminoid species and communities in alpine grasslands. The models are driven by four bioclimatic parameters: degree-days of growing season (basis 0 °C), a moisture index for July, potential direct solar radiation for March, and a continentality index. Geology and slope angle were used as a surrogate for nutrient availability and soil water capacity. The bioclimatic parameters were derived from monthly mean temperature, precipitation, cloudiness and potential direct solar radiation. The environmental parameters were interpolated using a digital elevation model with a resolution of 50 m. The vegetation data for model calibration originate from field surveys and literature. An independent test data set with samples from three different climatic zones was used to test the model. The degree of coincidence between simulated and observed patterns was similar for species and communities, but the κ-values for communities were generally higher (κ= 0.539) than for species (mean individual κ= 0.201). Information on land use was detected as a major factor that could significantly improve both the species and the community model. Nevertheless, the climatic factors used to drive the model explained a major part of the observed patterns.     

Understanding global teleconnections of climate to regional model estimates of Amazon ecosystem carbon fluxes

We have investigated global teleconnections of climate to regional satellite‐driven observations for prediction of Amazon ecosystem production, in the form of monthly estimates of net carbon exchange over the period 1982–1998 from the NASA–CASA (Carnegie–Ames–Stanford) biosphere model. This model is driven by observed surface climate and monthly estimates of vegetation leaf area index (LAI) and fraction of absorbed PAR (fraction of photosynthetically active radiation, FPAR) generated from the NOAA satellite advanced very high‐resolution radiometer (AVHRR) and similar sensors. Land surface AVHRR data processing using modified moderate‐resolution imaging spectroradiometer radiative transfer algorithms includes improved calibration for intra‐ and intersensor variations, partial atmospheric correction for gaseous absorption and scattering, and correction for stratospheric aerosol effects associated with volcanic eruptions. Results from our analysis suggest that anomalies of net primary production and net ecosystem production predicted from the NASA–CASA model over large areas of the Amazon region east of 60°W longitude are strongly correlated with the Southern Oscillation index. Extensive areas of the south‐central Amazon show strong linkages of the FPAR and the NASA–CASA anomaly record to the Arctic Oscillation index, which help confirm a strong relation to southern Atlantic climate anomalies, with associated impacts on Amazon rainfall patterns. Processes are investigated for these teleconnections of global climate to Amazon ecosystem carbon fluxes and regional land surface climate.     

Vascular plant species richness along environmental gradients in a cool temperate to sub-alpine mountainous zone in central Japan

In order to clarify how vegetation types change along the environmental gradients in a cool temperate to sub-alpine mountainous zone and the determinant factors that define plant species richness, we established 360 plots (each 4 × 10 m) within which the vegetation type, species richness, elevation, topographic position index (TPI), slope inclination, and ground light index (GLI) of the natural vegetation were surveyed. Mean elevation, TPI, slope inclination, and GLI differed across vegetation types. Tree species richness was negatively correlated with elevation, whereas fern and herb species richness were positively correlated. Tree species richness was greater in the upper slope area than the lower slope area, whereas fern and herb species richness were greater in the lower slope area. Ferns and trees species richness were smaller in the open canopy, whereas herb species richness was greater in the open canopy. Vegetation types were determined firstly by elevation and secondary by topographic configurations, such as topographic position, and slope inclination. Elevation and topography were the most important factors affecting plant richness, but the most influential variables differed among plant life-form groups. Moreover, the species richness responses to these environmental gradients greatly differed among ferns, herbs, and trees.     

Linking a spatially-explicit model of acacias to GIS and remotely-sensed data

Spatially-explicit and landscape-related simulation models are increasingly used in ecology, but are often criticized because their parameterization has high data requirements. A frequently suggested approach to overcome this difficulty is the linkage of spatially-explicit or landscape-related models with GIS (geographic information system) and remote-sensing technology. GIS can provide data on relevant landscape features, such as topography, and satellite images can be used to identify spatial vegetation distribution. In this paper, we use these techniques for simple, cost-inexpensive (in both time and money) parameterization based on readily-available GIS and remotely-sensed data. We use a previously developed, spatially-explicit model of the population dynamics of anAcacia species in the Negev desert of Israel (SAM, spatialAcacia model) to investigate if model initialization (measurement of current tree distribution) can be obtained from readily-available satellite images using a radiometric vegetation index (NDVI, normalized difference vegetation index). Furthermore, we investigate the applicability and the advantages of using an explicit consideration of landscape features in the model based on topographic data from a GIS. Using a DEM (digital elevation model), we compare the wadi topography to the current tree distribution observed in the field.     

A coupled carbon and water flux model to predict vegetation structure

Abstract. A coupled carbon and water flux model (BIOME2) captures the broad-scale environmental controls on the natural distribution of vegetation structural and phenological types in Australia. Model input consists of latitude, soil type, and mean monthly climate (temperature, precipitation, and sunshine hours) data on a 1/10° grid. Model output consists of foliage projective cover (FPC) for the quantitative combination of plant types that maximizes net primary production (NPP). The model realistically simulates changes in FPC along moisture gradients as a consequence of the trade-off between light capture and water stress. A two-layer soil hydrology model also allows simulation of the competitive balance between grass and woody vegetation including the strong effects of soil texture.     

Validation of the Integrated Biosphere Simulator in simulating the potential natural vegetation map of China

The Integrated Biosphere Simulator (IBIS)—a Dynamic Global Vegetation Model—was validated by simulating the potential natural vegetation map of China using data on monthly mean climate from 1961 to 1990, soil texture, and topography. Although the vegetation map simulated by IBIS was able to describe the sketch of vegetation patterns in China, the distributions of several plant functional types (PFTs) and vegetation types were still simulated incorrectly, especially in eastern temperate areas, southern subtropics, the southern Sichuan basin, and the Hengduan mountains area. By adjusting some of the climatic constraints and physiological parameters of PFTs defined in IBIS, the simulated distributions of PFTs became reasonable, and the simulated vegetation map fitted the natural vegetation map better. The kappa statistic between the simulated and the natural vegetation maps was 0.76, an increase of 16.9% from the previous parameter adjustment of 0.65. Correspondingly, the degree of agreement between these two maps rose from “good” to “very good”. After the parameter adjustments, IBIS became more suitable for the large-scale simulation of Chinese natural vegetation distributions and could provide a powerful support to reveal the dynamic responses of terrestrial ecosystems to climate change in China.