Analysis of a Long-term Experiment with Repeated-measurement Models

Long‐term experiments are a classical case of repeated measurements. Traits are measured on the same experimental unit over many years so that correlations arise between the observations made on the same plot in consecutive years. This paper describes the analysis of a three‐crop‐rotation long‐term experiment. We analysed the yields of the crops and the organic carbon content in the topsoil over 30 consecutive years. Several variance–covariance approaches are discussed and the trait‐specific best fit is interpreted. Mixed models are used to describe the structure of the experiment. Both yields and soil organic carbon show a more or less pronounced variance heterogeneity. Especially for yields, the heterogeneity of cycles and years is dominant. The consideration of correlations results in a better model fit in all cases.     

Spatial epidemiology of the Asian honey bee mite (Varroa destructor) in the North Island of New Zealand

We describe the spatial epidemiology of Varroa destructor infestation among honey bee apiaries in the greater Auckland area of the North Island of New Zealand. The study population was comprised of 641 apiaries located within the boundaries of the study area on 11 April 2000. Cases were those members of the study population declared Varroa-infested on the basis of testing conducted between April and June 2000. The odds of Varroa was highest in apiaries in the area surrounding transport and storage facilities in the vicinity of Auckland International Airport. A mixed-effects geostatistical model, accounting for spatial extra-binomial variation in Varroa prevalence, showed a 17% reduction in the odds of an apiary being Varroa infested for each kilometre increase in the squared distance from the likely site of incursion (95% Bayesian credible interval 7–28%). The pattern of spatially autocorrelated risk that remained after controlling for the effect of distance from the likely incursion site identified areas thought to be ‘secondary’ foci of Varroa infestation initiated by beekeeper-assisted movement of infested bees. Targeted investigations within these identified areas indicated that the maximum rate of local spread of Varroa was in the order of 12 km/year (interquartile range 10–15 km/year).     

Spatial dependence and the relationship of soil organic carbon and soil moisture in the Luquillo Experimental Forest,Puerto Rico

We used geo-spatial statistical techniques to examine the spatial variation and relationship of soil organic carbon (SOC) and soil moisture (SM) in the Luquillo Experimental Forest (LEF), Puerto Rico, in order to test the hypothesis that mountainous terrain introduces spatial autocorrelation and crosscorrelation in ecosystem and soil properties. Soil samples (n = 100) were collected from the LEF in the summer of 1998 and analyzed for SOC, SM, and bulk density (BD). A global positioning system was used to georeference the location of each sampling site. At each site, elevation, slope and aspect were recorded. We calculated the isotropic and anisotropic semivariograms of soil and topographic properties, as well as the cross-variograms between SOC and SM, and between SOC and elevation. Then we used four models (random, linear, spherical and wave/hole) to test the semi-variances of SOC, SM, BD, elevation, slope and aspect for spatial dependence. Our results indicate that all the studied properties except slope angle exhibit spatial dependence within the scale of sampling (200 – 1000 m sampling interval). The spatially structured variance (the variance due to the location of sampling sites) accounted for a large proportion of the sample variance for elevation (99%), BD (90%), SOC (68%), aspect (56%) and SM (44%). The ranges of spatial dependence (the distances within which parameters are spatially dependent) for aspect, SOC, elevation, SM, and BD were 9810 m, 3070 m, 1120 m, 930 m and 430 m, respectively. Cross correlograms indicate that SOC varies closely with elevation and SM depending on the distances between samples. The correlation can shift from positive to negative as the separation distance increases. Larger ranges of spatial dependence of SOC, aspect and elevation indicate that the distribution of SOC in the LEF is determined by a combination of biotic (e.g., litterfall) and abiotic factors (e.g., microclimate and topographic features) related to elevation and aspect. This demonstrates the importance of both elevation and topographic gradients in controlling climate, vegetation distribution and soil properties as well as the associated biogeochemical processes in the LEF.This revised version was published online in May 2005 with corrections to the Cover Date.     

Ecotonal changes and altered tree spatial patterns in lower mixed-conifer forests, Grand Canyon National Park, Arizona, U.S.A.

This research analyzes patch development and determines tree spatial patterns along the lower mixed-conifer ecotone on the North Rim of Grand Canyon National Park in Arizona (U.S.A.). Patterns of patch development were interpreted from spatial analyses, based on tree age and size, and past records of disturbance and climate. Five plots in the ecotone between mixed conifer forests and monospecific stands of ponderosa pine (Pinus ponderosa) were studied for patterns of patch development. The methods used include: (1) size-structure analyses, to compare species patch development; (2) dendrochronological dating of tree establishment; (3) tree ring master chronology, to determine periods of suppressed growth, compared to a Palmer Drought Severity Index; and (4) spatial analyses by species composition, size and age, with univariate and bivariate analyses of spatial association and spatial autocorrelation. We found an increased density of shade-tolerant and fire-intolerant species namely clusters of pole-sized white fir, and fewer large ponderosa pine. This revised version was published online in May 2005 with corrections to the Cover Date. This revised version was published online in July 2006 with corrections to the Cover Date.     

Modelling land cover transitions: A solution to the problem of spatial dependence in data

Raster-based spatial land cover transition models (LCTMs) are widely used in landscape ecology. However, many LCTMs do not account for spatial dependence of the input data, which may artificially fragment the output spatial configuration. We demonstrate the consequences of ignoring spatial dependence, thus assigning probabilities randomly in space, using a simple LCTM. We ran the model from four different initial conditions with distinct spatial configurations and results indicated that, after 20 simulation steps, all of them converged towards the spatial configuration of the random data set. From an ecological perspective this is a serious problem because ecological data often exhibit distinct spatial configuration related to ecological processes. As a solution, we propose an approach (region approach) that accounts for spatial dependence of LCTM input data. Underlying spatial dependence was used to apply spatial bias to probability assignment within the model. As a case study we applied a region approach to a Vegetation Transition Model (VTM); a semi-Markovian model that simulates forest succession. The VTM was applied to approximately 500,000 ha of boreal forest in Ontario, at 1 ha pixel resolution. When the stochastic transition algorithms were applied without accounting for spatial dependence, spatial configuration of the output data became progressively more fragmented. When the VTM was applied using the region approach to account for spatial dependence output fragmentation was reduced. Accounting for spatial dependence in transition models will create more reliable output for analyzing spatial patterns and relating those patterns to ecological processes.This revised version was published online in May 2005 with corrections to the Cover Date.     

多年生人工草地矮生嵩草(Kobresia humilis)种群空间格局与种内关联性

植物种群空间分布格局不仅反映植物的空间分布特点,还有助于研究者了解植物利用资源的现状和生存能力。本研究以矮生嵩草(Kobresia humilis)为研究对象,按株丛斑块面积将矮生嵩草分为小斑块级株丛(0～30 cm²)、中斑块级株丛(30～80 cm²)和大斑块级株丛(>80 cm²)3个株丛级,采用点格局分析的g函数统计方法,分析了矮生嵩草各级株丛的空间格局及关联性。结果表明：矮生嵩草种群中小斑块级株丛占比高于中斑块、大斑块级株丛占比,种群中幼苗充足,正处于稳定的增长阶段;矮生嵩草小斑块、中斑块、大斑块级株丛在小尺度范围内表现为聚集分布,随着尺度的增大,所有株丛斑块的聚集程度减弱,逐渐趋向于随机分布;小斑块与中斑块、大斑块的矮生嵩草株丛在小尺度内表现为正关联。斑块聚集分布和相互共存是矮生嵩草的一种生存策略。     

卵形异绒螨空间分布型及二阶抽样技术研究

卵形异绒螨是我国北方地区梨树蚜虫的一种外寄生性天敌。通过2005年5月调查,得出卵形异绒螨在梨树间和梨树内都属于聚集分布。计算了卵形异绒螨二阶抽样的理论抽样数,进行了卵形异绒螨二阶抽样的序贯分析。     

基于ArcSDE的空间数据组织和管理

重点讨论了ArcsDE的数据组织模型,以及如何组织和管理空间数据;利用AreSDE结合Oraclegi技术,实现了中国--东盟自由贸易区电子政务系统中数据库的建立.     

不同放牧制度对荒漠草原表层土壤氮素空间异质性的影响

以荒漠草原不同放牧制度下表层土壤氮素含量为研究对象,采用GS+软件和地统计学分析方法对其空间异质性分布进行了研究.结果显示,划区轮牧区表层士壤碱解氮含量显著低于对照区和自由放牧区,土壤全氮含量没有发生显著性变化.样点间土壤氮素含量差异表明,表层土壤氮素含量存在空间异质性.划区轮牧使得土壤碱解氮含量和土壤全氮含量空间分布受随机因素影响大,自由放牧使土壤全氮含量空间分布受随机因素影响大,围封状态的对照区土壤碱解氮含量和土壤全氮含量空间分布几乎不受随机因素影响.划区轮牧能够减小土壤氮素空间分布的异质性,自由放牧导致表层土壤碱解氮含量空间差异较大.在划区轮牧区,土壤碱解氮含量和土壤全氮含量空间分布都比较均匀,呈片状分布,自由轮牧区土壤碱解氮整体呈破碎斑块分布.     

基于时空变异的旱地土壤有机碳高效采样策略研究

土壤有机碳(SOC)空间分布具有时序差异性,明确样点数量对不同时期SOC预测精度影响是制定高效采样策略的基础.选取3.93×104 km2江苏北部旱地作为案例区,运用普通克里金插值方法,分析样点数量对不同时期SOC空间预测精度的影响.结果表明:不同数量样点数据集下1980年苏北旱地SOC预测值与实测值的相关系数r和均方...