Plant species richness and environmental heterogeneity in a mountain landscape: effects of variability and spatial configuration

The loss of biodiversity has become a matter of urgent concern and a better understanding of local drivers is crucial for conservation. Although environmental heterogeneity is recognized as an important determinant of biodiversity, this has rarely been tested using field data at management scale. We propose and provide evidence for the simple hypothesis that local species diversity is related to spatial environmental heterogeneity. Species partition the environment into habitats. Biodiversity is therefore expected to be influenced by two aspects of spatial heterogeneity: 1) the variability of environmental conditions, which will affect the number of types of habitat, and 2) the spatial configuration of habitats, which will affect the rates of ecological processes, such as dispersal or competition. Earlier, simulation experiments predicted that both aspects of heterogeneity will influence plant species richness at a particular site. For the first time, these predictions were tested for plant communities using field data, which we collected in a wooded pasture in the Swiss Jura mountains using a four-level hierarchical sampling design. Richness generally increased with increasing environmental variability and "roughness" (i.e. decreasing spatial aggregation). Effects occurred at all scales, but the nature of the effect changed with scale, suggesting a change in the underlying mechanisms, which will need to be taken into account if scaling up to larger landscapes. Although we found significant effects of environmental heterogeneity, other factors such as history could also be important determinants. If a relationship between environmental heterogeneity and species richness can be shown to be general, recently available high-resolution environmental data can be used to complement the assessment of patterns of local richness and improve the prediction of the effects of land use change based on mean site conditions or land use history.

Personality and Culture Cross-Cultural Psychology at the Next Crossroads

A review of nearly three decades of cross-cultural research shows that this domain still has to address several issues regarding the biases of data collection and sampling methods, the lack of clear and consensual definitions of constructs and variables, and measurement invariance issues that seriously limit the comparability of results across cultures. Indeed, a large majority of the existing studies are still based on the anthropological model, which compares two cultures and mainly uses convenience samples of university students. This paper stresses the need to incorporate a larger variety of regions and cultures in the research designs, the necessity to theorize and identify a larger set of variables in order to describe a human environment, and the importance of overcoming methodological weaknesses to improve the comparability of measurement results. Cross-cultural psychology is at the next crossroads in it's development, and researchers can certainly make major contributions to this domain if they can address these weaknesses and challenges.

Spatial and temporal variability of crop yield and some Rhodic Hapludox properties under no-tillage

Soil properties are closely related with crop production and spite of the measures implemented, spatial variation has been repeatedly observed and described. Identifying and describing spatial variations of soil properties and their effects on crop yield can be a powerful decision-making tool in specific land management systems. The objective of this research was to characterize the spatial and temporal variations in crop yield and chemical and physical properties of a Rhodic Hapludox soil under no-tillage. The studied area of 3.42 ha had been cultivated since 1985 under no-tillage crop rotation in summer and winter. Yield and soil property were sampled in a regular 10 x 10 m grid, with 302 sample points. Yields of several crops were analyzed (soybean, maize, triticale, hyacinth bean and castor bean) as well as soil chemical (pH, Soil Organic Matter (SOM), P, Ca2+, Mg2+, H + Al, B, Fe, Mn, Zn, CEC, sum of bases (SB), and base saturation (V %)) and soil physical properties (saturated hydraulic conductivity, texture, density, total porosity, and mechanical penetration resistance). Data were analyzed using geostatistical analysis procedures and maps based on interpolation by kriging. Great variation in crop yields was observed in the years evaluated. The yield values in the Northern region of the study area were high in some years. Crop yields and some physical and soil chemical properties were spatially correlated.

Spatial variability of physical attributes of an alfisol under different hillslope curvatures

The influence of relief forms has been studied by several authors and explains the variability in the soil attributes of a landscape. Soil physical attributes depend on relief forms, and their assessment is important in mechanized agricultural systems, such as of sugarcane. This study aimed to characterize the spatial variability in the physical soil attributes and their relationship to the hillslope curvatures in an Alfisol developed from sandstone and growing sugarcane. Grids of 100 x 100 m were delimited in a convex and a concave area. The grids had a regular spacing of 10 x 10 m, and the crossing points of this spacing determined a total of 121 georeferenced sampling points. Samples were collected to determine the physical attributes related to soil aggregates, porosity, bulk density, resistance to penetration and moisture within the 0-0.2 and 0.2-0.4 m depth. Statistical analyses, geostatistics and Student's t-tests were performed with the means of the areas. All attributes, except aggregates > 2 mm in the 0-0.2 m depth and macroporosity at both depths, showed significant differences between the hillslope curvatures. The convex area showed the highest values of the mean weighted diameter, mean geometric diameter, aggregates > 2 mm, 1-2 mm aggregates, total porosity and moisture and lower values of bulk density and resistance to penetration in both depth compared to the concave area. The number of soil attributes with greater spatial variability was higher in the concave area.

Pedotransfer functions related to spatial variability of water retention attributes for lowland soils

The estimation of non available soil variables through the knowledge of other related measured variables can be achieved through pedotransfer functions (PTF) mainly saving time and reducing cost. Great differences among soils, however, can yield non desirable results when applying this method. This study discusses the application of developed PTFs by several authors using a variety of soils of different characteristics, to evaluate soil water contents of two Brazilian lowland soils. Comparisons are made between PTF evaluated data and field measured data, using statistical and geostatistical tools, like mean error, root mean square error, semivariogram, cross-validation, and regression coefficient. The eight tested PTFs to evaluate gravimetric soil water contents (Ug) at the tensions of 33 kPa and 1,500 kPa presented a tendency to overestimate Ug 33 kPa and underestimate Ug1,500 kPa. The PTFs were ranked according to their performance and also with respect to their potential in describing the structure of the spatial variability of the set of measured values. Although none of the PTFs have changed the distribution pattern of the data, all resulted in mean and variance statistically different from those observed for all measured values. The PTFs that presented the best predictive values of Ug33 kPa and Ug1,500 kPa were not the same that had the best performance to reproduce the structure of spatial variability of these variables.

The cross-cultural generalizability of Zuckerman's alternative Five-Factor Model of personality

The aim of this study was to analyze the cross-cultural generalizability of the alternative Five-Factor Model (AFFM). The total sample was made up of 9,152 subjects from six countries: China, Germany, Italy, Spain, Switzerland, and the United States. The internal consistencies for all countries were generally similar to those found for the normative American sample. Factor analyses within cultures showed that the normative American structure was replicated in all cultures, however the congruence coefficients were slightly lower in China and Italy. A similar analysis at the facet level confirmed the high cross-cultural replicability of the AFFM. Mean-level comparisons did not always show the hypothesized effects. The mean score differences across countries were very small.

Report on the Iowa Department of Cultural Affairs for the year ended June 30, 2010

Report on the Iowa Department of Cultural Affairs for the year ended June 30, 2010

Temporal variability of soil water content under different surface conditions in the semiarid region of the Pernambuco state

Rainfall in the semiarid region of Pernambuco is characterized by irregular distribution in time and space, which significantly hinders the rainfed agriculture in the region. This work aims to evaluate the temporal profile of soil moisture in the semiarid region of the Pernambuco State (Brazil) and the effect of different soil surface conditions on soil water content variation and the yield of rainfed beans. To monitor soil water content, five plots 4.5 m wide by 11 m long were installed in a Yellow Argisol (Ultisol). The following treatments were adopted in the experimental plots: natural vegetation, bean intercropped with cactus, beans planted down the slope, beans planted along contour lines with mulch and rock barriers, and bare soil. In each plot, eight PVC access tubes were installed for monitoring the soil water content profile at depths of 0.20 and 0.40 m using a neutron probe device. The surface condition significantly influenced the soil water content variation, both in the dry and rainy seasons. The use of mulch, associated with rock barriers, provided higher soil water content levels than the other treatments and increased the rainfed beans production.

Implications of the variability in soil penetration resistance for statistical analysis

Soil penetration resistance (PR) is a measure of soil compaction closely related to soil structure and plant growth. However, the variability in PR hampers the statistical analyses. This study aimed to evaluate the variability of soil PR on the efficiency of parametric and nonparametric analyses in indentifying significant effects of soil compaction and to classify the coefficient of variation of PR into low, medium, high and very high. On six dates, the PR of a typical dystrophic Red Ultisol under continuous no-tillage for 16 years was measured. Three tillage and/or traffic conditions were established with the application of: (i) no chiseling or additional traffic, (ii) additional compaction, and (iii) chiseling. On each date, the nineteen PR data (measured at every 1.5 cm to a depth of 28.5 cm) were grouped in layers with different thickness. In each layer, the treatment effects were evaluated by variance (ANOVA) and Kruskal-Wallis analyses in a completely randomized design, and the coefficients of variation of all analyses were classified (low, intermediate, high and very high). The ANOVA performed better in discriminating the compaction effects, but the rejection rate of null hypothesis decreased from 100 to 80 % when the coefficient of variation increased from 15 to 26 %. The values of 15 and 26 % were the thresholds separating the low/intermediate and the high/very high coefficient variation classes of PR in this Ultisol.

Uncertainties in the prediction of spatial variability of soil CO2 emissions and related properties

The soil CO2 emission has high spatial variability because it depends strongly on soil properties. The purpose of this study was to (i) characterize the spatial variability of soil respiration and related properties, (ii) evaluate the accuracy of results of the ordinary kriging method and sequential Gaussian simulation, and (iii) evaluate the uncertainty in predicting the spatial variability of soil CO2 emission and other properties using sequential Gaussian simulations. The study was conducted in a sugarcane area, using a regular sampling grid with 141 points, where soil CO2 emission, soil temperature, air-filled pore space, soil organic matter and soil bulk density were evaluated. All variables showed spatial dependence structure. The soil CO2 emission was positively correlated with organic matter (r = 0.25, p < 0.05) and air-filled pore space (r = 0.27, p < 0.01) and negatively with soil bulk density (r = -0.41, p < 0.01). However, when the estimated spatial values were considered, the air-filled pore space was the variable mainly responsible for the spatial characteristics of soil respiration, with a correlation of 0.26 (p < 0.01). For all variables, individual simulations represented the cumulative distribution functions and variograms better than ordinary kriging and E-type estimates. The greatest uncertainties in predicting soil CO2 emission were associated with areas with the highest estimated values, which produced estimates from 0.18 to 1.85 t CO2 ha-1, according to the different scenarios considered. The knowledge of the uncertainties generated by the different scenarios can be used in inventories of greenhouse gases, to provide conservative estimates of the potential emission of these gases.

Agency Fact Sheet, Department of Cultural Affairs, FY2007

This document produced by the Iowa Department of Administrative Services has been developed to provide a multitude of information about executive branch agencies/department on a single sheet of paper. The facts provides general information, contact information, workforce data, leave and benefits information and affirmative action data.

Agency Fact Sheet, Department of Cultural Affairs, FY2008

This document produced by the Iowa Department of Administrative Services has been developed to provide a multitude of information about executive branch agencies/department on a single sheet of paper. The facts provides general information, contact information, workforce data, leave and benefits information and affirmative action data.