Spatial Variability of Soil Organic Carbon in Relation to Environmental Factors of a Typical Small Watershed in the Black Soil Region, Northeast China

A total of 292 soil samples were taken from surface soil (0–20 cm) of a typical small watershed–Tongshuang in the black soil region of Heilongjiang province, northeast China in June 2005 for examining the concentration of soil organic carbon (SOC). Spatial variability of SOC in relation to topography and land use was evaluated using classical statistics, geostatistics and geographic information system (GIS) analyses. The objective of this study was to provide a scientific basis for land management targeting at improving soil quality in this region. Classical statistical analysis results indicated that the variability of SOC was moderate (C _V = 0.30). Slope position and land use types were discriminating factors for its spatial variability. Geostatistics analyses showed that SOC had a strong spatial autocorrelation, which was mainly induced by structural factors. Mean concentration of SOC in surface soil was 2.27% in this watershed, which was a very low level in the northern black soil region of northeast China. In this small watershed, present soil and water conservation measures played an important role in controlling soil loss. But SOC's restoration was unsatisfactory. Nearly three-quarters of the area had worrisome productivity. How to improve SOC concentration targeting at soil fertility is a pressing need in the future.     

Soil seed bank and seedling populations of Hordeum murinum and Cardaria draba in saffron fields

Geostatistical techniques were used to characterize the spatial relationship between Hordeum murinum and Cardaria draba seedling and soil seed bank over the entire growing season of 2004–2005 in three saffron (Crocus sativus) fields, located in Southern Khorasan (33°N latitude, 57°E longitude), Iran. The maps of H. murinum seed bank density corresponded moderately to those seedling density in a and strongly to those in b and c fields. The emergence percentage of C. draba was higher than for H. murinum in all fields. Semivariograms showed spatial autocorrelation in seed bank and seedling populations of H. murinum and C. draba in all fields. Grey-scale field maps of C. draba seed banks corresponded visually to maps of seedling populations and could have been used to target control efforts, but visual correspondence between H. murinum seed bank and seedling maps was poor.     

城市河流水质参数空间变异性研究——以苏南某市为例

基于现场的采样数据,结合河流自身特点,应用地质统计学的理论和方法分析了苏南某城市河流水质参数的空间变异规律及其原因。研究结果表明,根据变差函数模型分析,发现研究区河流3个水质参数在一定范围内存在空间相关性;研究区河流的CODMn呈现中南部较高,其他部位相对均匀的趋势,CODMn的空间变异性主要是由居民的日常活动及河道的自身特点引起;研究区河流的TP和NH3-N含量严重超标,水体富营养化程度严重。TP和NH3-N的空间变异性相似,含量较高区域集中在研究区的西南部、东南部和东北部,其空间变异性主要由工业活动和居民日常生活共同作用引起,其中工业活动占主导作用。     

Effects of Land Management Change on Spatial Variability of Organic Matter and Nutrients in Paddy Field: A Case Study of Pinghu,China

The Household Responsibility System initiated in the late 1970s in China has brought a profound change to its rural economy. The shift from the collective farming system to individual family farms has changed land management. The change, including fertilization and crop systems, may have significant effects on soil quality and agro-environmental sustainability. However, very little research is being carried out on the impact of reformed land tenure systems on the spatial variability of soil nutrients. In this study, geostatistics was applied to analyze changes in the spatial variability of soil organic matter and nutrients in paddy fields in Pinghu County, China after 20 years of land management change. In 1984 and 2002, 617 and 131 locations were selected, respectively, for collecting surface soil samples to analyze soil organic matter (SOM), total nitrogen (TN), available phosphorus (AP), and available potassium (AK). From 1984 to 2002, variability of the SOM and TN changed from strongly to moderately spatial-dependent, and the variability of AP remained weakly dependent on space, but that of the AK changed from moderately to weakly spatial-dependent. That the trend of the variability of four soil properties in 2002 became weaker than that in 1984 showed that the extrinsic factors (soil management practices, such as fertilization) weakened the effect by intrinsic factors (soil formation factors, such as soil parent materials) owing to a long period of land management change. The temporal geographic maps of the SOM and nutrients spatial distributions suggested that the concentrations of the SOM and nutrients had been changed to different extents during the period. Significant increase in AP and decrease in AK were noted. The changes were likely due to the imbalance between N, P, and K fertilizers and increased grain yield.     

Assessment of spatial variability in some soil properties as related to soil salinity and alkalinity in Bafra plain in northern Turkey

The objectives of this study were to assess the variability in soil properties affecting salinity and alkalinity, and to analyze spatial distribution patterns of salinity (EC) and alkalinity (ESP) in the plain, which was used irrigation agriculture with low quality waters. Soil samples were collected from 0–30cm, 30–60cm, 60–90cm and 90–120cm soil depths at 60 sampling sites. Soil pH had the minimum variability, and hydraulic conductivity (Ks) had the maximum variability at all depths. The mean values of pH, EC, ESP and Ks increased while the mean values of CEC decreased with soil depth. Values pH, EC and ESP were generally high in the east and northeastern sides. Soil properties indicated moderate to strong spatial dependence. ESP and pH were moderately spatially dependent for three of the four depths, EC exhibited moderate spatial dependence for one of the four depths, CEC had a moderate spatial dependence at all depths, and Ks exhibited a strong spatial dependence. EC, CEC, and ESP were considerably variable in small distances. The spatial variability in small distances of EC, CEC, pH and ESP generally increased with depth. All geostatistical range values were greater than 1230m. It was inferred that the strong spatial dependency of soil properties would be resulted in extrinsic factors such as ground water level, drainage, irrigation systems and microtopography.     

Pilot-study on GIS-based risk modelling of a climate warming induced tertian malaria outbreak in Lower Saxony (Germany)

This project was designed to establish baseline aquatic biological community structure and physical habitat conditions in select wadeable streams within the California Central Valley. A secondary objective was to evaluate possible water quality differences between site types and seasons. Two agricultural and two urban streams were monitored in spring and fall for two consecutive years beginning in the fall of 2002. Bioassessment sampling was conducted according to modified US EPA methods. The study included physical habitat assessment, water and sediment chemical analysis and characterization of the benthic macroinvertebrate community at each site. Water samples were analyzed for selected organophosphate insecticides, pyrethroid insecticides and herbicides, while sediment samples were analyzed for pyrethroids only. All sites had substantial physical habitat and water quality impairments, and the absence of pollution intolerant macroinvertebrates and dominance of pollution tolerant macroinvertebrates were indications of biological impairment. Due to the limited amount of water quality and pesticide data collected, it was not possible to definitively demonstrate any cause and effect relationships between BMI community structure and water quality or pesticide concentrations. Though most physical habitat parameters were similar and EPA physical habitat scores revealed on no significant differences between urban and agricultural sites (P? = ?0.290), a significant difference was seen in substrate embeddedness (P? = ?0.020). Dominant taxon found at all sites were chironomids, amphipods, and oligochaetes. Benthic macroinvertebrate metrics were significantly different between both types of sites (P? = ?0.001) and seasons (P? = ?0.014). Chironomidae taxon and those of the functional feeding group scrapers were greater at urban sites, while those of the functional feeding group filterers were greater at agricultural sites. In addition, the metric groups Chironomidae, filterers, and predators were found in greater numbers in the spring than the fall.     

Impact of neighbourhood land-cover in epiphytic lichen diversity: analysis of multiple factors working at different spatial scales

The objective of this work was to determine the impact of neighbourhood land-cover in epiphytic lichen diversity. We used geostatistics to analyse the spatial structure of lichen-indicators (number of lichen species and Lichen Diversity Value) and correlate them to land-cover considering different distances from the observed data. The results showed that lichen diversity was influenced by different environmental factors that act in the same territory but impact lichens at different distances from the source. The differences in the distance of influence of the several land-cover types seem to be related to the size of pollutants/particles that predominantly are dispersed by each land-cover type. We also showed that a local scale of analysis gives a deeper insight into the understanding of lichen richness and abundance in the region. This work highlighted the importance of a multiple spatial scale of analysis to deeply interpret the relation between lichen diversity and the underling environmental factors.     

A multi-stage sampling strategy for the delineation of soil pollution in a contaminated brownfield

A multi-stage sampling strategy, based on sequential Gaussian simulation, was presented to optimize the step-wise selection of a small numbers of additional samples to delineate soil pollution. This strategy was applied to a Belgian brownfield of 5.2 ha polluted with lead (Pb). Starting from an initial number of 240 samples in stage 1, additional samples were added, 25 per stage, and the reduction of the uncertainty in the Pb delineation was monitored. Twenty stages were used. Already in stage 6 a local optimum was found based on the median conditional coefficient of variation. An independent validation confirmed that this index was to be preferred over the median conditional variance. So for the brownfield considered our procedure indicated that 365 selected samples would have been sufficient, representing a gain of 70.7% in sampling effort compared to current practice which resulted in a sampling effort of 1245 samples.     

Heavy metal sources identification and sampling uncertainty analysis in a field-scale vegetable soil of Hangzhou, China

At a field-scale (6.7 ha), 100 surface soil samples were collected from a vegetable field to determine total concentrations of Cd, Co, Cu, Hg, Mn, Ni and Zn. To identify possible sources of these metals and characterize their spatial variation, classic statistic and geostatistic techniques were applied. Through correlation and geostatistical analysis, it was found that the primary inputs of Co, Mn and Ni were due to pedogenic sources, whereas the sources of Hg and Cd were mainly due to human activities. Because of their different sources, their variations followed: Hg > Cd ≈ Cu > Zn ≈ Co ≈ Mn ≈ Ni. Based on their relationships with other soil properties, co-kriging was used to minimize sampling density. Sampling numbers for Cd, Cu, Zn, Mn, Co and Ni can be reduced from 100 to 90, 80, 70, 60, 60 and 60, respectively, without losing accuracy relative to ordinary kriging.     

Spatial statistical models that use flow and stream distance

We develop spatial statistical models for stream networks that can estimate relationships between a response variable and other covariates, make predictions at unsampled locations, and predict an average or total for a stream or a stream segment. There have been very few attempts to develop valid spatial covariance models that incorporate flow, stream distance, or both. The application of typical spatial autocovariance functions based on Euclidean distance, such as the spherical covariance model, are not valid when using stream distance. In this paper we develop a large class of valid models that incorporate flow and stream distance by using spatial moving averages. These methods integrate a moving average function, or kernel, against a white noise process. By running the moving average function upstream from a location, we develop models that use flow, and by construction they are valid models based on stream distance. We show that with proper weighting, many of the usual spatial models based on Euclidean distance have a counterpart for stream networks. Using sulfate concentrations from an example data set, the Maryland Biological Stream Survey (MBSS), we show that models using flow may be more appropriate than models that only use stream distance. For the MBSS data set, we use restricted maximum likelihood to fit a valid covariance matrix that uses flow and stream distance, and then we use this covariance matrix to estimate fixed effects and make kriging and block kriging predictions. Received: July 2005 / Revised: March 2006