Strong Spatial Structure Research Articles

Spatial variability of soil acidity attributes and liming requirement for conilon coffee

The soils of Espirito Santo State are low natural fertility level, which frequently limit crop yields due to deficiencies of some soil elements, however, it presents high production potential. The purpose of this work was to describe the spatial variability of attributes related to soil acidity (pH, potential acidity, aluminum, calcium, magnesium), organic matter and liming requirement in a conilon coffee plantation (Coffea canephora Pierre) in a typical dystrophic Yellow Latosol (LAd). The study was carried out in a farm area, in the Northern part of the state of Espirito Santo, Brazil. The experimental area was 20 x 61.6 m (1.232 m2) in a regular grid where 60 samples were equally spaced in grids of 5.6 x 5 m, at a soil depth of 0-20 cm. All property semivariograms disclosure were satisfactorily described by spherical model with a moderate and strong spatial structure with ranges of spatial structure varying from 8.0 m to 33.58 m.

Spatial Variability of Potato Tuber Yield and Plant Nitrogen Uptake Related to Soil Properties

Inferring correlations between yield and soil properties is difficult, because the variables involved vary at different scales. The study goal was to describe the spatial distribution of tuber yield (total yield), plant N accumulation (Nuptake) and soil properties at small and large field scales with a multivariate geostatistical method (Co‐Regionalization Analysis with a Drift), allowing for a correlation analysis of crop and soil properties at the same scale of variability. Two sites with similar growing practices but different pedodiversity were instrumented at 108 sampling points. Total yield was represented mostly by a small‐scale spatial component (<12.4 m) at Site 1, whereas the importance of the small‐scale variability was minor at Site 2. The Nuptake showed a strong spatial structure at small scale at both sites. Large‐scale component of Nuptake was also present at both sites, and correlations with total yield and Nuptake were stronger at this scale. Correlations with soil properties at large scale only indicate a low temperature early in the season and a lack of water later during the season decreased yield whereas lower soil density and higher electrical conductivity increased plant productivity. For high productivity, some irrigation may be needed, even only once during the season. Property measurements should be taken at large scale for precision agriculture by respecting the scale of variability of each property. Small‐scale variability should be used when treatments are of interest, for example, plots no longer than 11 m should be used to compare fertilizer rates at the sites of this study.

Landscape and oceanic barriers shape dispersal and population structure in the island nematodePristionchus pacificus

Despite the biological importance and diversity of nematodes, little is known of the factors influencing their dispersal and shaping their evolutionary history. Populations of the cosmopolitan species Pristionchus pacificus are characterized by high genetic diversity and strong spatial structure, which contrasts with patterns detected in nematode species such as Caenorhabditis elegans. The environmentally heterogeneous volcanic Mascarene Islands provide an ideal setting for investigating fine-scale patterns of nematode migration and gene flow. Based on the analysis of data from 19 nuclear microsatellites and one mitochondrial marker, we infer support for the colonization of both La Reunion Island and Mauritius from similar multiple geographical sources. Although the long-term persistence of populations on both islands is well supported, the historical colonization of one island from the other cannot be discounted. In fact, periodic, bi-directional migration between the islands following their initial colonization is strongly supported in isolation with migration analyses, supporting the occurrence of rare trans-oceanic dispersal events in P. pacificus. Through a combination of population and landscape genetic analyses we also infer non-uniform dispersal across the landscape on the island of La Reunion, probably mediated by the movements of beetle hosts. Collectively, we show that gene flow in P. pacificus is limited by environmental and oceanic barriers, and shaped by the intricacies of the nematode–beetle host interaction. © 2014 The Linnean Society of London, Biological Journal of the Linnean Society, 2014, 112, 1–15.

Post-Glacial Expansion and Population Genetic Divergence of Mangrove Species Avicennia germinans (L.) Stearn and Rhizophora mangle L. along the Mexican Coast

Mangrove forests in the Gulf of California, Mexico represent the northernmost populations along the Pacific coast and thus they are likely to be source populations for colonization at higher latitudes as climate becomes more favorable. Today, these populations are relatively small and fragmented and prior research has indicated that they are poor in genetic diversity. Here we set out to investigate whether the low diversity in this region was a result of recent colonization, or fragmentation and genetic drift of once more extensive mangroves due to climatic changes in the recent past. By sampling the two major mangrove species, Rhizophora mangle and Avicennia germinans, along the Pacific and Atlantic coasts of Mexico, we set out to test whether concordant genetic signals could elucidate recent evolution of the ecosystem. Genetic diversity of both mangrove species showed a decreasing trend toward northern latitudes along the Pacific coast. The lowest levels of genetic diversity were found at the range limits around the Gulf of California and the outer Baja California peninsula. Lack of a strong spatial genetic structure in this area and recent northern gene flow in A. germinans suggest recent colonization by this species. On the other hand, lack of a signal of recent northern dispersal in R. mangle, despite the higher dispersal capability of this species, indicates a longer presence of populations, at least in the southern Gulf of California. We suggest that the longer history, together with higher genetic diversity of R. mangle at the range limits, likely provides a gene pool better able to colonize northwards under climate change than A. germinans.

Measuring local genetic variability in populations of codling moth (Lepidoptera: Tortricidae) across an unmanaged and commercial orchard interface.

The genetic structure of adult codling moth, Cydia pomonella (L.), populations was characterized both inside a managed apple, Malus domestica Borkdhausen, orchard and in surrounding unmanaged hosts and nonhost trees in central Chile during 2006-2007. Adult males were collected using an array of sex pheromone-baited traps. Five microsatellite genetic markers were used to study the population genetic structure across both spatial (1-100 ha) and temporal (generations within a season) gradients. Analysis of molecular variance (AMOVA) found a significant, but weak, association in both the spatial and temporal genetic structures. Discriminant analysis also found significant differentiation between the first and second generation for traps located either inside or outside the managed orchard. The Bayesian assignment test detected three genetic clusters during each of the two generations, which corresponded to different areas within the unmanaged and managed apple orchard interface. The lack of a strong spatial structure at a local scale was hypothesized to be because of active adult movement between the managed and unmanaged hosts and the asymmetry in the insecticide selection pressure inside and outside the managed habitats. These data highlight the importance of developing area-wide management programs that incorporate management tactics effective at the landscape level for successful codling moth control.

Can coarse‐grain patterns in insect atlas data predict local occupancy?

AbstractAimSpecies atlases provide an economical way to collect data with national coverage, but are typically too coarse‐grained to monitor fine‐grain patterns in rarity, distribution and abundance. We test the performance of ten downscaling models in extrapolating occupancy across two orders of magnitude. To provide a greater challenge to downscaling models, we extend previous downscaling tests with plants to highly mobile insect taxa (Odonata) with a life history that is tied to freshwater bodies for reproduction. We investigate the species‐level correlates of predictive accuracy for the best performing model to understand whether traits driving spatial structure can cause interspecific variation in downscaling success.LocationMainland Britain.MethodsOccupancy data for 38 British Odonata species were extracted from the Dragonfly Recording Network (DRN). Occupancy at grains ≥ 100 km2 was used as training data to parameterize ten downscaling models. Predicted occupancy at the 25, 4 and 1 km2 grains was compared to observed data at corresponding grains. Model predictive error was evaluated across species and grains.Main conclusionsThe Hui model gave the most accurate downscaling predictions across 114 species:grain combinations and the best predictions for 14 of the 38 species, despite being the only model using information at a single spatial grain. The occupancy–area relationship was sigmoidal in shape for most species. Species' distribution type and dispersal ability explained over half of the variation in downscaling predictive error at the species level. Species with a climatic range limit in Britain were poorly predicted compared with other distribution types, and high dispersal ability was associated with relatively poor downscaling predictions. Our results suggest that downscaling models, using widely available coarse‐grain atlas data, provide reasonable estimates of fine‐grain occupancy, even for insect taxa with strong spatial structure. Linking species‐level traits with predictive accuracy reveals general principles about when downscaling will be successful.

Phylogeographic analysis of rabies viruses in the Philippines

Rabies still remains a public health threat in the Philippines. A significant number of human rabies cases, about 200–300 cases annually, have been reported, and the country needs an effective strategy for rabies control. To develop an effective control strategy, it is important to understand the transmission patterns of the rabies viruses. We conducted phylogenetic analyses by considering the temporal and spatial evolution of rabies viruses to reveal the transmission dynamics in the Philippines.After evaluating the molecular clock and phylogeographic analysis, we estimated that the Philippine strains were introduced from China around the beginning of 20th century. Upon this introduction, the rabies viruses evolved within the Philippines to form three major clades, and there was no indication of introduction of other rabies viruses from any other country. However, within the Philippines, island-to-island migrations were observed. Since then, the rabies viruses have diffused and only evolved within each island group.The evolutionary pattern of these viruses was strongly shaped by geographical boundaries. The association index statistics demonstrated a strong spatial structure within the island group, indicating that the seas were a significant geographical barrier for viral dispersal. Strong spatial structure was also observed even at a regional level, and most of the viral migrations (79.7% of the total median number) in Luzon were observed between neighboring regions.Rabies viruses were genetically clustered at a regional level, and this strong spatial structure suggests a geographical clustering of transmission chains and the potential effectiveness of rabies control that targets geographical clustering. Dog vaccination campaigns have been conducted independently by local governments in the Philippines, but it could be more effective to implement a coordinated vaccination campaign among neighboring areas to eliminate geographically-clustered rabies transmission chains.

Communities of fungal endophytes in tropical forest grasses: highly diverse host- and habitat generalists characterized by strong spatial structure

Abstract Plant-symbiotic fungi influence the structure and function of all terrestrial ecosystems, but factors shaping their distributions in time and space are rarely well understood. Grasses (Poaceae), which first arose and diversified in tropical forests, harbor diverse but little-studied endophytes in the lowland forests of Panama. We used sequence data for 402 isolates from two sampling years, 11 host species, and 55 microsites at Barro Colorado Island, Panama to investigate the influence of host and habitat (soil type, forest age) in shaping endophyte diversity and composition. In contrast to previous studies, we found no evidence for host- or habitat specificity. Instead, endophytes demonstrated strong spatial structure consistent with dispersal limitation, with community similarity decaying markedly over a scale of hundreds of meters. Spatial structure that is independent of host species and habitat reveals remarkable heterogeneity of endophyte–host associations at small geographic scales and adds an important spatial component to extrapolative estimates of fungal diversity.

Mapping of Variability in Major and Micro Nutrients for Site-Specific Nutrient Management

Background: Spatial variation of soil physical and chemical properties influences soil and crop management efficiency causes uneven crop growth and decreases the effectiveness of uniformly applied fertilizers. Purpose: Therefore, a comprehensive survey was made to determine the spatial variability of soil properties and their mapping in Charsadda district of Khyber Pakhtunkhwa Province (KP) of Pakistan to delineated area into low, medium and high level of plant nutrients for site-specific nutrient management using variable rate fertilizer technology. Method: Soil sampling was done on a grid system using Global Position System (GPS) from two depths (0-15, and 15-45 cm) during 2004; and the samples were analyzed for soil physical (soil texture and saturation percentage), soil chemical (pH, ECe, SAR, lime, Original Research Article Khan et al.; IJPSS, Article no. IJPSS.2014.008 304 and organic matter) and soil fertility status (mineral N, AB-DTPA extractable P, K, Zn, Cu, Fe, Mn and HCl extractable B). Geostatistical techniques of semivariogram analysis and kriging were used to model the spatial variability and interpolation of data values at unsampled locations and mapping of the district. Semivariogram analyses of data showed some spatial patterns for soil properties. Silt (r2=0.48), clay (r2=0.71) contents and saturation percentage (r2=0.71) were described by linear model in both the depths (0-15, and 15-45 cm). Electrical conductivity was described by a linear model in both the depths with strong spatial structure in surface soil (r2=0.81). Calcium carbonate (CaCO3) in the surface soil had strong spatial structure (r2=0.59), organic matter content in the surface soil was described by a spherical model with a range of influence 6.65 km, while in the subsoil (15-45 cm) it was described by a linear model with moderate spatial structure (r2=0.41). Mineral N and P were described by linear models with strong spatial structure for P in both the depths (r2=0.77, 0.73) and moderate spatial structure (r2=0.36) for surface soil N. Potash content was described by a linear model in surface soil with moderate structure (r2=0.24), while in subsoil it was explained by a spherical model with strong spatial structure (r2=0.64) and a range of about 9 km. Zinc and Cu in the surface soil were randomly distributed, while they have strong spatial structure (r2=0.63 and 0.54, respectively) with a linear model in subsoil. Boron content in both the depths was described by a linear model with strong spatial structure in surface (r2=0.61) and moderate structure (r2=0.31) in subsoil. Results: The maps of various measured soil properties showed that soil mineral N and boron (B) increases from north-east toward west-south, available P form south-east towards north-west and lime form northern towards southern parts of the district. Soil organic matter, sand and silt contents showed little spatial variation within sampled areas. Conclusion: Texture of Charsadda district ranged from silt to sandy loam. Sand content in the east and silt in the whole area was higher, while clay was found low throughout the soil surveyed. All the soils were alkaline in reaction and calcareous in nature to different degrees as indicated in maps of surface soil pH and CaCO3. Organic matter content of both the depths was low. surface soils was deficient in N in all soils of district Charsadda while deficiencies of P, Zn and B were observed to a greater extent, while K, Cu and Mn are also appearing deficient in soil.

The impact of Border policy effect on cross-border ethnic areas

Abstract. Boundary effect analysis is related to border policy making in the cross-border ethnic area. The border effect literatures show that geographic boundaries have obvious impacts on economic, social and cultural relations in both sides of a nation border. Particularly in cross-border ethnic areas, each ethnic group has strong internal spatial structure relevance, and the boundary effect is more obvious. However, most of China's border areas are cross-border ethnic areas, each of border issues is unique. Under this perspective, we analyze the border effects of various boundaries can provide basis for formulating border management policies. For small scale of cross-border ethnic minority areas, how to formulate the boundary management policy is a good question to explore. This paper is demonstrated by a study of the impact of border management policies in Dehong Dai and Jingpo Autonomous Prefecture in Yunnan Province at the border area to Burma. The comparative method is used to analysis the border management policies in past 50 decades for the border area of Yunnan Province .This research aims to define trends within border policy and its influences to national security. This paper also examines Wendy Brown's liberal theory of border management policy. We found that it is not suitable for Sino-Burma border area. The conclusion is that the changes or instability of international economic and political situation has more influence to this cross-border ethnic area, and only innovative policy will be effective in cross-border ethnic area. So the border management policies should reflect the change of international context.

Small area estimation for semicontinuous skewed spatial data: An application to the grape wine production in Tuscany

Linear-mixed models are frequently used to obtain model-based estimators in small area estimation (SAE) problems. Such models, however, are not suitable when the target variable exhibits a point mass at zero, a highly skewed distribution of the nonzero values and a strong spatial structure. In this paper, a SAE approach for dealing with such variables is suggested. We propose a two-part random effects SAE model that includes a correlation structure on the area random effects that appears in the two parts and incorporates a bivariate smooth function of the geographical coordinates of units. To account for the skewness of the distribution of the positive values of the response variable, a Gamma model is adopted. To fit the model, to get small area estimates and to evaluate their precision, a hierarchical Bayesian approach is used. The study is motivated by a real SAE problem. We focus on estimation of the per-farm average grape wine production in Tuscany, at subregional level, using the Farm Structure Survey data. Results from this real data application and those obtained by a model-based simulation experiment show a satisfactory performance of the suggested SAE approach.

Spatial Variability of Nutrients in Wheat Plants in Semi-arid Regions of Northwestern Pakistan

This study was undertaken to assess spatial variability of nutrients in wheat plants for variable-rate site-specific fertilizer-management strategy. Wheat plants were collected from two semi-arid regions in northwestern Pakistan during 2004 and analyzed for nutrient contents and spatial variability. Wheat samples from both regions showed widespread deficiency of phosphorus (P), potassium (K), and zinc (Zn). In Kohat, Zn and manganese (Mn) were spatially distributed, described by linear models with moderate spatial patterns, but K, copper (Cu), and iron (Fe) showed weak spatial structures. In Bannu, K was described by a linear model with strong spatial structure and Fe had moderate spatial structure, but P, Cu, Mn, and Zn had random spatial distributions. The maps developed in this study showed variation in plant nutrients and spatial trends in the cases of spatially distributed nutrients and can be used to delineate plant nutrients into low, medium, and high categories to develop variable-rate fertilizer-management strategy.

Landform and landscape mapping, French Guiana (South America)

In this paper two geomorphologic maps (landform level and landscape level) are presented covering the French Guianan rainforest (84,000 km2) using full-resolution Shuttle Radar Topography Mission (SRTM) data. The entire country was segmented into 224,000 landform units on the basis of an original object-oriented approach using a modified counting box algorithm. A Principal Components Analysis (PCA) followed by k-means clustering (Ward's method) identified 12 different landform types corresponding to theoretical elementary landforms. The landscape map was generated by analyzing the spatial distribution of the different landform types. The different maps and models were compared with topographic field data collected on 92 transects totaling 260 km in length. The object-focused approach is a very efficient method that preserves geomorphologic consistency and discriminates between landforms using simple descriptors that are easily understood by non-geomorphologists. Despite major noise in the data, the landform map proved to be reliable and provided a strong spatial structure for the definition of landscape units. We recommend using the landform map at scales 1: 100,000–1: 250,000. Landscape map, used on a 1:1,000,000–1:2,000,000 scale, enabled us to draw bio-geographical limits in this region and provides exhaustive relief information that usefully supplements the geological map.

Surfing in tortoises? Empirical signs of genetic structuring owing to range expansion

Much of our current knowledge about the genetic dynamics in range expansions originates from models, simulations and microcosm experiments that need to be corroborated by field data. Here, we report a neutral genetic pattern that matches the predictions of the genetic surfing theory. Genetic surfing occurs when repeated founding events and genetic drift act on the wave of advance of an expanding population, promoting strong spatial structure. In the range expansion of the tortoise Testudo graeca from North Africa to southeastern Spain, we found several genetic signatures consistent with surfing: a decrease of genetic diversity with distance from the initial founder area, clinal patterns in allele frequencies, rare African alleles which have become common at distal sites in the Spanish range, and stronger spatial differentiation in the expanded range than in the original one. Our results provide support for the theory that genetic drift can be an important force in shaping the genetic structure of expanding populations.

Cooperation and the evolutionary ecology of bacterial virulence: TheBacillus cereusgroup as a novel study system

How significant is social evolution theory for the maintenance of virulence in natural populations? We assume that secreted, distantly acting virulence factors are highly likely to be cooperative public goods. Using this assumption, we discuss and critically assess the potential importance of social interactions for understanding the evolution, diversity and distribution of virulence in the Bacillus cereus group, a novel study system for microbial social biology. We conclude that dynamic equilibria in Cry toxin production, as well as strong spatial structure and population bottlenecks in hosts are the main ecological factors maintaining the cooperative secretion of virulence factors and argue that collective action has contributed to the evolution of narrow host range. Non-linearities in the benefits associated with public goods, as well as the lack of private secretion systems in the Firmicutes may also explain the prevalence and importance of distantly acting virulence factors in B. cereus and its relatives.

Using GIS and Geostatistics to Optimize Soil Phosphorus and Magnesium Sampling in Temperate Grassland

Soil sampling design is an important issue for agricultural management and environmental monitoring. In this study, a total of 537 soil samples were collected based on a 30 × 30–m grid from a permanent dairy farm in southeastern Ireland. Five different subsample experiments at lower densities based on the original data set were performed to study the optimal soil sampling design for soil P and Mg using geostatistics and a GIS (geographical information system). Soil P ranged from 1.3 to 35.7 mg L, with a CV value of 0.68. Soil Mg ranged from 134.7 to 685.2 mg L, with a small CV value of 0.28. Soil P followed neither a normal nor a lognormal distribution. Box-Cox transformation was applied to achieve normality. On the other hand, soil Mg followed a normal distribution, as did its subdata. For soil P, an omnidirectional spherical model was used to describe the spatial autocorrelation. For soil Mg, a nested model (an exponential model combined with a Gaussian model) was used to fit the variograms. Further soil P interpolated maps revealed that soil grid sampling interval could increase to 90 m without a significant loss of spatial information, whereas soil Mg sampling interval could increase to 120 m, confirming that soil Mg had much stronger spatial structure than soil P. According to this study, a grid of 90 × 90 m was recommended for soil sampling, which was confirmed in other practical grassland farms. The spatial structure information was very useful to optimize soil sampling design for practical grassland management.

Patterns of weed invasion: evidence from the spatial genetic structure of Raphanus raphanistrum

Knowledge of the pathways of colonization is critical for risk assessment and management of weeds. In this study we adopted a landscape genetics approach to assess the impact of human disturbances and large-scale environmental features on the colonization of a global agricultural weed, Raphanus raphanistrum. We used nuclear microsatellite and chloroplast DNA sequence data to quantify the pattern of genetic diversity in 336 plants collected from 13 sites throughout the Cape Floristic Region, South Africa, one of the world’s recognized global biodiversity hotspots. The lack of strong spatial genetic structure suggests that R. raphanistrum colonized throughout the Cape Floristic Region via both local diffusive spread and long-distance jump dispersal. Furthermore, 47 % of analyzed plants contained Raphanus sativus (cultivated radish) chloroplast genomes, indicating historical and/or contemporary gene flow between wild and cultivated radish populations. The prevalence of high genetic diversity and long-distance gene flow are discussed in the context of ecological risk assessment.

Strong Spatial Genetic Structure Reduces Reproductive Success in the Critically Endangered Plant Genus Pseudomisopates

Clonal growth can be a double-edged sword for endangered species, because the short-term insurance against extinction may incur a longer-term hazard of creating small inbred populations with low fecundity. In the present study, we quantify the advantages and disadvantages of clonal growth regarding the fitness of the central Iberian monotypic endangered genus Pseudomisopates. Preliminary studies showed that the species is self-incompatible and exhibits extensive clonal growth with plants flowering profusely. However, seeds at many sites seemed to be unviable, and no seedlings have been observed in the field. A fully replicated nested sampling design (n = 100) was conducted to explore genetic (using seven SSR loci) and environmental factors potentially affecting seed viability, such as: 1) clonal and genetic diversity, 2) spatial genetic structure, and 3) environmental factors (shrub cover and grazing). Generalized Linear Mixed Models were fitted relating genetic and environmental variables to reproductive variables (seed viability and flower display). Our results indicate that the relatively low genotypic diversity of the population (PD = 0.23), as quantified by SSRs, and the strong spatial genetic structure observed are congruent with intense clonal growth. This clonal growth is enhanced by unfavorable environmental conditions, such as canopy closure and grazing. Under these circumstances, both flower display and mate availability decrease, thus hindering sexual reproduction. Indeed, a mixed reproductive system (clonal and sexual) to escape environmental stochasticity is crucial for the survival of Pseudomisopates, a species inhabiting a disturbance-prone ecosystem.

Distribuição espacial da precipitação e da erosividade da chuva mensal e anual no Estado do Espírito Santo

O mapeamento da erosividade da chuva e da precipitação pluvial consiste de um instrumento prático e indispensável para o planejamento do uso do solo em escalas regionalizadas, como países, Estados ou grandes bacias hidrográficas. Nesse contexto, objetivou-se neste estudo analisar a continuidade espacial do potencial erosivo da chuva e da precipitação pluviométrica, nas escalas de tempo mensal e anual, e posterior mapeamento destas, para o Estado do Espírito Santo, visando fornecer informações básicas ao planejamento de uso e manejo sustentável do solo. Para isso, 129 estações pluviométricas foram empregadas no estudo; a erosividade da chuva foi calculada tendo-se como base equações de Fournier ajustadas para os Estados vizinhos, porém com características climáticas semelhantes. Observou-se forte estrutura de dependência espacial das variáveis regionalizadas, especialmente da erosividade da chuva, com predomínio do modelo de semivariograma exponencial. Quanto à precipitação pluvial, os valores do grau de dependência espacial foram inferiores aos obtidos para a erosividade; contudo, foi possível classificar a estrutura de dependência como moderada a forte. A região do Rio Doce foi classificada como de "alto" a "muito alto" potencial erosivo, cuja erosividade média anual variou de 7.000 a 11.460 MJ mm ha-1 h-1 ano-1. Nessa região, os solos, além de ocorrerem em relevo dissecado e serem pobres em nutrientes, apresentam déficit hídrico pronunciado, dificultando o estabelecimento da vegetação, e são aqueles de maior vulnerabilidade natural à erosão hídrica.

Soil organic matter and cation-exchange capacity sensing with on-the-go electrical conductivity and optical sensors

An on-the-go optical soil sensor with 660nm red and 940nm near-infrared wavelengths with an electrical conductivity (EC) sensing unit were tested to estimate soil organic matter (SOM) and cation-exchange capacity (CEC) on 551ha on 15 fields in 6 U.S. states. For calibration between sensed data and lab-analyzed values, a multivariate linear regression (MLR) with leave-one-out cross validation was performed on fields with more than 10 lab samples and a single variable linear regression was performed on fields with less than 10 samples. From the SOM calibration results, 12 of 15 fields had good results with R2 of 0.80 or higher and RPD (Ratio of Prediction to Deviation=standard deviation / root mean square error of prediction) of 2.33 or greater. For CEC calibrations, six of nine fields had good results with R2 of 0.86 or higher and RPD of 2.78 or greater. The best calibration model was applied to each field and the estimated SOM and CEC maps exhibited strong spatial structure and high correlation to lab-analyzed SOM in all fields. EC and optical data in each field was normalized and combined together by state and tested with MLR. Combining fields in this manner showed good results with R2 of 0.80 or higher and RPD of 2.30 or greater for SOM in four of five states, and combined fields in two of three states showed good correlations to lab data with R2 of 0.86 or higher and RPD of 2.69 or greater for CEC. From these results, SOM and CEC mapping with soil EC and optical sensors seems to be a promising approach. Future research will be implemented to estimate SOM and CEC more precisely by developing a reliable universal calibration model using soil EC, optical data, soil moisture contents and topographic attributes for global areas.