A citywide survey of the pine processionary moth Thaumetopoea pityocampa spatial distribution in Orléans (France)

There is a growing recognition that urban trees provide various valuable benefits and services such as enhanced human wellbeing. However, they also have a cost in terms of public health either directly (allergies) or by harboring species representing health risk for humans. This paper focuses on such a forest insect species, the pine processionary moth Thaumetopoea pityocampa. Its caterpillars develop gregariously during winter in a conspicuous silk nest in coniferous hosts. When disturbed, the larvae release urticating hairs that cause human or animal serious health problems. The purpose of our survey was to (1) inventory all individual trees belonging to potential host species and estimate the density of T. pityocampa (2) assess the spatial pattern of the insect population at the city scale. We conducted an exhaustive inventory of potential coniferous host trees in five municipalities (ca. 5000 ha) in the north of Orléans, France. Each tree was identified, geo-referenced and the number of moth nests it hosted was counted. A total of 9321 urban trees representing 11 coniferous taxonomic units were investigated. The distribution of T. pityocampa exhibited a marked spatial structure citywide. Geostatistics allowed to draw risk maps revealing strong patchiness. We provide the first estimate of T. pityocampa host tree preference in an urban context and found that Pinus nigra, P. pinaster and P. sylvestris were the most attacked trees. We also report numerous cases of T. pityocampa occurrence on the exotic ornamental Himalayan cedar Cedrus deodara. The management implications of our findings are two-fold: (1) risk maps constitute a useful framework for communication and public information, and can help developing control strategies; (2) some species frequently used for ornamental purposes are poor quality hosts regarding T. pityocampa and should therefore be preferred in public place usually frequented by vulnerable people (schools, nurseries, hospitals).     

Geostatistical interpolation and aggregation of crop growth model outputs

Many crop growth models require daily meteorological data. Consequently, model simulations can be obtained only at a limited number of locations, i.e. at weather stations with long-term records of daily data. To estimate the potential crop production at country level, we present in this study a geostatistical approach for spatial interpolation and aggregation of crop growth model outputs. As case study, we interpolated, simulated and aggregated crop growth model outputs of sorghum and millet in West-Africa. We used crop growth model outputs to calibrate a linear regression model using environmental covariates as predictors. The spatial regression residuals were investigated for spatial correlation. The linear regression model and the spatial correlation of residuals together were used to predict theoretical crop yield at all locations using kriging with external drift. A spatial standard deviation comes along with this prediction, indicating the uncertainty of the prediction. In combination with land use data and country borders, we summed the crop yield predictions to determine an area total. With spatial stochastic simulation, we estimated the uncertainty of that total production potential as well as the spatial cumulative distribution function. We compared our results with the prevailing agro-ecological Climate Zones approach used for spatial aggregation. Linear regression could explain up to 70% of the spatial variation of the yield. In three out of four cases the regression residuals showed spatial correlation. The potential crop production per country according to the Climate Zones approach was in all countries and cases except one within the 95% prediction interval as obtained after yield aggregation. We concluded that the geostatistical approach can estimate a country’s crop production, including a quantification of uncertainty. In addition, we stress the importance of the use of geostatistics to create tools for crop modelling scientists to explore relationships between yields and spatial environmental variables and to assist policy makers with tangible results on yield gaps at multiple levels of spatial aggregation.     

邛海盆地土壤氮素空间变异特征与影响因素研究

以西昌市邛海盆地为研究区域,随机均匀布点采集386个耕作层土壤样点,分析化验土壤理化性质,运用地统计学方法和GIS技术研究邛海盆地表层土壤氮素含量的空间变异特征,利用方差分析、缓冲区分析和回归分析定量分析区域内土壤氮素空间变异的影响因素。研究结果表明,研究区表层土壤全氮和速效氮含量分别为(1.85±0.51)g/kg和(138.5±47.7)mg/kg,属较丰富水平,变异系数分别为27.52%和32.24%,属中等差异强度;土壤全氮和速效氮具有中等程度的空间相关性,空间变异均以随机变异为主,具有各向异性特征,在西北-东南方向上空间变异相对剧烈;研究区土壤全氮和速效氮含量总体上呈条带状或斑块状分布特征,高值区主要位于西昌市的东南郊区,并以此高值中心向南、向东和向北3个方向逐步递减,低值区主要出现在邛海北面近湖岸地带。影响因素分析结果表明,土地利用方式、土壤母质、土壤质地、土壤p H值、城镇、河流、邛海湖对土壤全氮和速效氮空间变异具有显著影响,而道路对土壤氮素空间变异影响不显著。     

基于GIS的精确农业合理采样与施肥间距研究

在GIS软件平台下对采样点进行行列删减,人为减小采样密度,运用地统计学方法制作养分分布图,并与原始采样方案进行形状和面积对比,选取合理的删减方案作为土壤养分的合理采样方案.碱解氮、速效磷和速效钾的合理采样间距分别为64 m×51 m、32 m×76 m和32 m×25 m.为综合考虑多种养分,提出3条综合采样测土原则.提出了调整施肥间距的实现方法,自动变量施肥宜采用"大网格采样、小网格施肥",手动变量施肥则宜采用"小网格采样、大网格施肥".试验表明提出的方法实现了定性与定量相结合来研究土壤采样间距.     

Changes in the spatial structure of oak carbon-based secondary compounds after pine harvesting

In natural plant populations, leaf polyphenols show high intraspecific variation that occurs both temporally and spatially. Leaf phenolics may be induced by diverse ecological factors such as light, nitrogen availability or herbivory attack. Both light and nitrogen availability can show spatial structure in forested stands, meaning that they each have a high degree of autocorrelation, which can determine the appearance of spatial structure in leaf polyphenols. However, the availability of these resources may be drastically changed by forest disturbance, and little is known about the effect of forest disturbance on the spatial pattern and scale of leaf secondary compounds. We hypothesise that the spatial structure of leaf polyphenols in understory vegetation will disappear due to forest harvesting, because these compounds depend on light availability, yet it will remain unaltered for those compounds that either depend on the availability of other resources or are under major genetic control. The study was performed in young pedunculate oak (Quercus robur) populations growing either under a pine canopy (Pinus pinaster) stand or in a pine harvested stand in NW Spain. The spatial structures of green and senescent leaf polyphenols, tannins, non-tannin polyphenols and nitrogen were analysed in both stands using geostatistical analysis. The spatial structures observed for green and senescent leaf polyphenols and tannins in the forested stand disappeared in the harvested stand. However, non-tannin polyphenols, as well as nitrogen, showed spatial structure in both stands. Understanding these changes may be important for the successful recovery of native oak populations growing under pine forests in NW Spain, one of the priorities of the local government. Our results showed that changes in the concentration of leaf secondary compounds after disturbance may be accompanied by differences in their spatial properties, which may have important consequences for ecosystem function.     

Spatial structure of deciduous forest stands with contrasting human influence in northwest Spain

Five contrasting deciduous forest stands were studied to characterize the spatial structural variability in human-influenced forests. These stands are representative of cultural forest types widely represented in western Europe: one plantation, two coppices, one wood-pasture forest and one high forest stand. All stems with DBH > 5 cm were measured and mapped, and stem DBH distributions, spatial structure of DBH, spatial point patterns and spatial associations were analysed. Spatial autocorrelation for DBH was calculated with Moran’s I correlograms and semivariograms. Complete spatial randomness hypothesis for spatial point patterns, and both independence and random labelling hypotheses for spatial associations were analysed using Ripley’s K function. The results showed that tree sizes were conditioned by particular former management systems, which determined unimodal symmetric, positively skewed or compound DBH distributions. Spatial structure was more complex when human influence became reduced. Coppice stands showed clumped spatial patterns and independence among size classes, as a consequence of sexual and vegetative establishment of new stems in open areas. The largest clumping intensity was observed in the wood-pasture with an intermediate disturbance frequency and low inter-tree competition. The high forest stand displayed spatial traits consistent with the gap-dynamics paradigm, such as clumping of smaller trees, random arrangement of larger trees, negative association between juveniles and adults, and high structural heterogeneity. It can be expected that after cessation of human interference, coppices and wood-pastures would evolve to a more heterogeneous structure, probably with a higher habitat and species diversity.     

Spatial variability in the growth of direct-seeded rainfed lowland rice (Oryza sativa L.) in northeast Thailand

Large within-field variation in rice growth often causes production loss in broadcast-seeded (BC) rainfed lowland rice. The spatial variability of direct-seeded rainfed lowland rice was evaluated in 2004, 2005, and 2007 in on-station experiments at Ubon Ratchathani, northeast Thailand, in relation to soil water content and weed infestation, by adopting semivariogram and block kriging, including comparisons among BC with harrowing (BCH; no weeding), BC with no harrowing (BCNH; no weeding), and row-seeded (RS; interrow weeding once) fields. BCH and BCNH were also compared in 11 farmers’ fields in 2006 and 2007, to assess the effect of harrowing on rice growth and weed infestation. During most of the rice growing periods, flooded and non-flooded portions existed simultaneously in the fields, with different proportions among years and among seeding methods in the on-station experiment. BCH and BCNH rice had large within-field variation in seedling density, heading date, shoot dry matter, grain yield, harvest index, panicle density, and filled spikelet per panicle, as well as in weed infestation, measured by a quick visual estimation. Many of the measured variables (except mean soil water content in RS in 2007, seedling density in BCH in 2005 and 2007, shoot dry matter in BCH and BCNH in 2007, and panicle density in BCH in 2007) were spatially dependent (i.e., data from nearby locations were most similar) by geostatistical analysis. Analysis of correlations using the 420 data sets of BCH plots in 2005 and BCH, BCNH, and RS plots in 2007 revealed a positive correlation between soil water content and grain yield and negative correlations between weed infestation and soil water content and grain yield. Compared with BCH, in 2007 BCNH had much lower grain yield because of lower soil water content after establishment and more weed infestation. BCH had higher grain yield than BCNH in weedy fields in the farmers’ fields experiment. RS with interrow weeding resulted in a smaller coefficient of variation, smaller sill value, and higher grain yield than BCH, due to less weed infestation and a higher proportion of flooded water. These results indicated that reducing the spatial variability in rice growth requires careful field preparation, such as harrowing to level the soil surface and to reduce the uneven distribution of standing water and the variability in soil water content, combined with effective crop and weed management (i.e., harrowing and row-seeding). This is the first study that examined spatial variability in the growth of direct-seeded rice as a function of soil water content and weed infestation in a rainfed lowland environment.     

蔬菜地土壤重金属含量空间插值精度分析

蔬菜地土壤重金属含量影响环境安全和人类健康。采用地统计分析和GIS相结合的方法,对研究区土壤重金属镉、汞、铬、砷、铅进行空间插值和精度分析,根据交叉检验参数和相对误差指标比较普通克里格法和协同克里格法的空间预测效果。结果表明：研究区土壤重金属存在中强等变异性,在重金属间显著相关性条件下,普通克里格法对汞、镉、砷含量预测精度较高;协同克里格法对铬和铅含量预测精度较高。建议根据土壤重金属空间变异程度选择合适的空间插值方法。     

基于地统计学与GIS技术的森林土壤养分空间变异性研究

以云浮市云城区和云安区森林土壤为研究对象,应用传统统计学和地统计学方法结合 GIS 技术分析其土壤养分的空间变异性,预测土壤养分空间分布。地统计学主要从空间插值模型和人工神经网络模型的角度对土壤养分的空间变异性进行诠释,并利用平均绝对误差(MAE)和均方根误差(RMSE)两个指标以及模型预测点与实测点间的相关系数作为判断模型好坏的标准。研究结果认为插值模型中泛克里格插值法在样点密度较小时显示出明显优势,而 BP-ANN 在模型的稳定性和推广性表现尤为突出,最后对泛克里格插值模型和 BP-ANN 下的有机碳、全氮、全磷、全钾4种养分空间预测分布特征进行描述。     

Spatial variability of water retention parameters and saturated hydraulic conductivity in a calcareous Inceptisols (Khuzestan province of Iran) under sugarcane cropping

The objective of this study was to quantify inherent spatial variability and spatial cross-correlation of the van Genuchten retention parameters and saturated hydraulic conductivity (K_s) of surface and subsurface layers in a calcareous Inceptisols (Khuzestan province, Iran) under sugarcane cropping. Measurements were performed on 100-cm³ undisturbed soil cores collected at 94 locations along a 30-m-long transect with horizontal sampling distance intervals of 0.3 and 1 m at soil depths of 0–40 and 40–80 cm, respectively. Spatial variability was investigated using conventional statistics and geostatistical techniques. Coefficient of variation (CV) varied from 8.2% (for shape parameter, n at 40–80 cm depth) to 256.7% (for K_s at 0–40 cm depth). The n parameter and saturated water content, θ_s, showed a small-scale spatial heterogeneity with a maximum CV of 11.3% for the first depth and 9.2% for the second depth. Most of the hydraulic parameters at both depths showed a spatial structure and convex experimental semivariograms with dominant spherical models with the influence range of 3.2–41 m. In most cases, the extent of spatial correlation scales of cross-semivariograms for pairs of cross-correlated hydraulic variables was found to be different with reference to those relating to the direct semivariograms of correlated variables.