Scaling patterns of biomass and soil properties: an empirical analysis

We argue that studies at multiple scales must necessarilychange the extent of measurements, not just the spacing, in order toeffectivelycapture information regarding processes at multiple scales. We have implementeda multi-scale sampling scheme using transects of 10 cm, 1m, 10 m, 100 m, and 1 km ateach of four sites along an elevational gradient from dry foothills forest toalpine tundra in the Front Range of Colorado; these four sites form anadditional transect of 22 km. Along each of these transects wetookten equally spaced soil cores and measured variables important in determiningboth microbial and plant community structure: soil water content, organicmattercontent, pH, and total soil biomass. With this sampling scheme we are able totreat scale as an independent variable in our analyses, and our data show thatboth particular sites and particular variables can determine whether estimatesof mean values are scale-dependent or not. A geostatistical analysis using allof our data shows common relationships between scales across ecologicallydiverse sites; biomass shows the most complex pattern of distribution acrossscales, as measured by fractal dimension. Our analyses also reveal theinadequacy of several standard geostatistical models when applied to data frommultiple scales of measurement – we recommend the use of the boundedpowerlaw model in such cases. We hypothesize that because biological communitiesmustrespond simultaneously to multiple variables with differing patterns of spatialvariation, the spatial variation of biological communities will be at least ascomplex as the most complex environmental variable at any given site.This revised version was published online in May 2005 with corrections to the Cover Date.     

Agricultural land-use patterns and soil erosion vulnerability of watershed units in Vietnam’s northern highlands

Since the mid eighties, agricultural development and increased population growth in Vietnam’s northern highlands have modified land use patterns and thus, increased the runoff process and soil degradation induced by water erosion. In the last decade, Vietnamese literature has focused on the computation of soil losses over large areas. Most of these spatial and quantitative soil erosion studies do not consider the impact of agricultural land use diversity (spatial heterogeneity), particularly at the watershed scale, and the annual variability of seasonal landscape factors on soil erosion vulnerability and hence, landscape dynamics. We present an integrated approach combining field measurements and observations, GIS and modeling to determine the spatial and temporal dynamics of soil erosion vulnerability according to watershed units and hence, the impact of physical environment components and agricultural land use patterns on landscape evolution. Tables and graphics showing the cropping systems, the periods within a year, and the watershed units that are most vulnerable are presented. The double cultivation cycles for paddy rice fields not only imply two periods of land preparation and establishment that expose the soil surface to raindrop impacts, but also increased soil management practices that decrease the soil’s resistance to detachment. Despite the low levels of soil management practices for the shifting cultivation system, the near absence of soil conservation practices clearly increases their vulnerability. Hence, rainfed cropping systems, mainly soya and cassava, cultivated on sloping lands (hills and mountains) where soil erosion vulnerability is the highest represent the watershed units which are the most prone to soil loss.     

Variation of soil respiration at three spatial scales: Components within measurements, intra-site variation and patterns on the landscape

Soil respiration is an important component of terrestrial carbon cycling and can be influenced by many factors that vary spatially. This research aims to determine the extent and causes of spatial variation of soil respiration, and to quantify the importance of scale on measuring and modeling soil respiration within and among common forests of Northern Wisconsin. The potential sources of variation were examined at three scales: [1] variation among the litter, root, and bulk soil respiration components within individual 0.1 m measurement collars, [2] variation between individual soil respiration measurements within a site (<1 m to 10 m), and [3] variation on the landscape caused by topographic influence (100 m to 1000 m). Soil respiration was measured over a two-year period at 12 plots that included four forest types. Root exclusion collars were installed at a subset of the sites, and periodic removal of the litter layer allowed litter and bulk soil contributions to be estimated by subtraction. Soil respiration was also measured at fixed locations in six northern hardwood sites and two aspen sites to examine the stability of variation between individual measurements. These study sites were added to an existing data set where soil respiration was measured in a random, rotating, systematic clustering which allowed the examination of spatial variability from scales of <1 m to 100+ m. The combined data set for this area was also used to examine the influence of topography on soil respiration at scales of over 1000 m by using a temperature and moisture driven soil respiration model and a 4 km² digital elevation model (DEM) to model soil moisture. Results indicate that, although variation of soil respiration and soil moisture is greatest at scales of 100 m or more, variation from locations 1 m or less can be large (standard deviation during summer period of 1.58 and 1.28 μmol CO₂ m⁻² s⁻¹, respectively). At the smallest of scales, the individual contributions of the bulk soil, the roots, and the litter mat changed greatly throughout the season and between forest types, although the data were highly variable within any given site. For scales of 1-10 m, variation between individual measurements could be explained by positive relationships between forest floor mass, root mass, carbon and nitrogen pools, or root nitrogen concentration. Lastly, topography strongly influenced soil moisture and soil properties, and created spatial patterns of soil respiration which changed greatly during a drought event. Integrating soil fluxes over a 4 km² region using an elevation dependent soil respiration model resulted in a drought induced reduction of peak summer flux rates by 37.5%, versus a 31.3% when only plot level data was used. The trends at these important scales may help explain some inter-annual and spatial variability of the net ecosystem exchange of carbon.     

中国辽宁典型风成黄土分维区间选取研究

应用分形理论中的幂指函数关系法,选取粒径R区间为无标度区,使用线性回归(linear regression)和分段线性回归(piecewise linear regression)来确定辽宁典型风成黄土837个样品粒度分维的无标度区。统计分析结果表明:一元分维的粒度分维值介于1.446~2.027,决定系数均大于0.900,确定无标度区为0.1~54.4μm;二元分维得到节点平均值为7.64μm±1.21μm(CV=15.87%),决定系数在0.978~0.999之间变化,变异系数为0.438%,确定无标度区为0.1~7.64μm(F_2)和7.64~54.4μm(F_1),且分维值D_(F1)D_(F2)。二元分维值与一元分维值差异较大,从另一个侧面表明即使是同一个研究对象,选取不同标度区范围,得到的分维值及其决定系数也不同,因此,使用分维模型前要注意无标度区的选取。分维值包含着土壤发生与沉积环境信息,深入解译分维值信息有助于理解黄土-古土壤的土壤发生过程。     

Mapping and spatial uncertainty analysis of forest vegetation carbon by combining national forest inventory data and satellite images

Forests play an important role in carbon sinks and mitigation of atmospheric concentrations of carbon dioxide and greenhouse effect. Given that sample plots used for collection of forest carbon observations are often much smaller than the map units of forest carbon at regional, national, and global scales, scientists are currently experiencing two challenges. The first challenge is to produce reliable maps of forest carbon using the data from inconsistent sizes of plots and image pixels. Also, because estimates of forest carbon normally contain uncertainties, the second challenge is to accurately model propagation of uncertainties from input data to output results. In this study, a methodology for mapping and analyzing spatial uncertainty of forest carbon estimates was developed to address these challenges. The methodological framework consisted of two methods. The first one was up-scaling method that combined and scaled up existing national forest inventory plot data and satellite images from smaller sample plots and image pixels to larger map units. The second one was spatial uncertainty analysis and error budget method that entailed modeling propagated uncertainties through a geostatistical mapping system. A case study using 46 permanent national forest inventory plots from Wu-Yuan County, Jiangxi, China, was undertaken to test this methodology. The results showed that this method reproduced not only the spatial distribution of forest carbon but also the spatial pattern of variances of its estimates and was able to quantify the contributions of uncertainties from the field plot data and satellite images to the uncertainties of forest carbon estimates. Thus, this study, to some extent, overcame the gaps that currently exist in the generation and assessment of forest carbon estimation maps. Moreover, the results showed that in this case study, the variation of the band ratio defined as (TM2 + TM3 + TM5)/TM7 contributed more uncertainties to the estimates of forest carbon than the variation of the plot data. In addition, we also found out that the product of the input plot forest carbon variance and the band ratio variance, implying the interaction between these two variables, reduced the uncertainties of the forest carbon estimates.     

二元小波紧框架的显式构造

研究了二元小波紧框架的结构,这个小波紧框架是由V1中的n个函数构成．首先给出由这n个函数生成二元小波紧框架的充分条件,并借助尺度函数给出了构造二元小波紧框架的显式公式,其次给出二元小波紧框架的分解与重构算法,并构造了小波紧框架的数值算例．     

浅论图书馆信息检索可视化技术

信息可视化是将抽象数据用可视的形式表示出来,以利于分析数据、发现规律和决策制定。信息检索可视化不仅用图形、图像来显示多维的非空间数据,使用户加深对数据含义及数据间关系的理解,而且用形象直观的图形、图像来指引检索过程,加快检索速度。在介绍信息检索可视化相关技术基础上,围绕信息检索和检索结果可视化在图书馆应用进行了探讨。     

Resource use dynamics and interactions in the tropics: Scaling up in space and time

We discuss the temporal and spatial dynamics of nutrient resources and water within cropping and livestock systems, their interactions and those with other resources such as labour. Short-term dynamics (within season) revolve around nutrient availability and losses as a function of soil moisture dynamics. Longer-term effects (multiple seasons and years) are related to residual effects of crop management in successive seasons and to changes in soil organic matter contents.     

Landscape phenology: an integrative approach to seasonal vegetation dynamics

This brief report addresses the theory and methodology of landscape phenology (LP), along with synopsis of a case study conducted in the northern Wisconsin temperate mixed forest. LP engages questions related to ecosystem phenology, landscape genetics, and vegetation change science across multiple scales, which have rarely been addressed by existing studies. Intensive in situ observations, remote sensing data, and spatiotemporal analysis are employed for understanding patterns and processes within the complexity of seasonal landscape dynamics. A hierarchical upscaling approach is also introduced. Results from the case study suggest that plot-scale phenology lacks spatial autocorrelation and varies individualistically, with genetic heterogeneity overriding small microenvironmental gradients. However, at the landscape level, forest phenology responds coherently to weather fluctuations. The resultant LP index confirms the relative reliability of moderate resolution imaging spectroradiometer (MODIS)-based land surface phenology (LSP). Due to technological advancement in spatial data acquisition and analysis, LP has the ability to connect conventional plant phenology studies back to their intricate ecological context, and provides a new approach to validating coarse-scale monitoring and modeling of LSP and other seasonal ecosystem processes.     

杨凌区土壤入渗特性的空间变异特征研究

为揭示杨凌区黏壤土区域土壤入渗特性的空间变异特征,通过在该研究区内进行的44组大田土壤入渗试验为基础,采用标定理论与地统计学相结合的方法,对Philip入渗公式进行了标定,并分析了标定因子和土壤累计人渗量的空间变异特征.结果表明:在研究区内基于土壤稳渗率A计算的标定因子aA标定效果最优;aA的变异系数为0.257 5,属于中等变异强度,且服从对数正态分布;aA的空间变化呈现二阶趋势,块金值与基台值的比值为0.228 0,表明其具有强烈的空间相关性.普通Kriging插值结果显示所有测点的aA和90 min累计入渗量空间分布特征具有高的一致性,并在此基础上,将aA和30 min、60 min、90 min累计入渗量预测值与实测值进行了比较,其两者的误差绝对值均值分别为12.25％、28.15％、25.56％和24.57％,结合实际情况,可认为该方法的预测结果是完全可以接受的.