Highlands of the upper Jequitinhonha valley, Brazil: II - mineralogy, micromorphology, and landscape evolution¹

Palm swanp formations, the so-called veredas, typically occur in the Brazilian biome known as "Cerrado" (savanna-like vegetation), especially on flattened areas or tablelands (chapadas). The aim of this study was to characterize the mineralogy and micromorphology of soil materials from a representative toposequence of the watershed of the vereda Lagoa do Leandro, located in Minas Novas, state of Minas Gerais, Brazil, on plains in the region of the upper Jequitinhonha valley, emphasizing essential aspects of their genesis and landscape evolution. The toposequence is underlain by rocks of the Macaúbas group and covered with detrital and metamorphic rocks (schists of Proterozoic diamictites). The soil profiles were first pedologically described; samples of the disturbed and undisturbed soils were collected from all horizons for further micromorphological and mineralogical analyses. The mineralogical analysis was mainly based on powder X ray diffractometry (XRD) and micromorphological descriptions of thin sections under a petrographic microscope. The soils from the bottom to the top of this toposequence were classified as: Typic Albaquult (GXbd), Xanthic Haplustox, gray color, here called "Gray Haplustox" ("LAC"), Xanthic Haplustox (LA) and Typic Haplustox (LVA). The clay mineralogy of all soils was found to be dominated by kaolinite. In soil of LA and LVA, the occurrence of goethite, gibbsite, and anatase was evidenced; "LAC" also contained anatase and the GXbd, illite, anatase, and traces of vermiculite. The micromorphological analyses of the LVA, LA and "LAC" soils showed the prevalence of a microaggregate-like or granular microstructure, and aggregate porosity has a stacked/packed structure, which is typical of Oxisols. A massive structure was observed in GXbd material, with the presence of illuviation cutans of clay minerals and iron compounds. Paleogleissolos, which are strongly weathered, due to the action of the excavating fauna , and resulted in the present "LAC". The GXbd at the base of the vereda preserved the physical, mineralogical and micromorphological properties that are typical of a pedogenesis with a strong influence of long dry periods.

Landscape structure affects dispersal in the greater white-toothed shrew: inference between genetic and simulated ecological distances

Animal dispersal in a fragmented landscape depends on the complex interaction between landscape structure and animal behavior. To better understand how individuals disperse, it is important to explicitly represent the properties of organisms and the landscape in which they move. A common approach to modelling dispersal includes representing the landscape as a grid of equal sized cells and then simulating individual movement as a correlated random walk. This approach uses a priori scale of resolution, which limits the representation of all landscape features and how different dispersal abilities are modelled. We develop a vector-based landscape model coupled with an object-oriented model for animal dispersal. In this spatially explicit dispersal model, landscape features are defined based on their geographic and thematic properties and dispersal is modelled through consideration of an organism's behavior, movement rules and searching strategies (such as visual cues). We present the model's underlying concepts, its ability to adequately represent landscape features and provide simulation of dispersal according to different dispersal abilities. We demonstrate the potential of the model by simulating two virtual species in a real Swiss landscape. This illustrates the model's ability to simulate complex dispersal processes and provides information about dispersal such as colonization probability and spatial distribution of the organism's path

Convergent genetic architecture underlies social organization in ants.

Complex adaptive polymorphisms are common in nature, but what mechanisms maintain the underlying favorable allelic combinations [1-4]? The convergent evolution of polymorphic social organization in two independent ant species provides a great opportunity to investigate how genomes evolved under parallel selection. Here, we demonstrate that a large, nonrecombining "social chromosome" is associated with social organization in the Alpine silver ant, Formica selysi. This social chromosome shares architectural characteristics with that of the fire ant Solenopsis invicta [2], but the two show no detectable similarity in gene content. The discovery of convergence at two levels-the phenotype and the genetic architecture associated with alternative social forms-points at general genetic mechanisms underlying transitions in social organization. More broadly, our findings are consistent with recent theoretical studies suggesting that suppression of recombination plays a key role in facilitating coordinated shifts in coadapted traits [5, 6].

Magnetic susceptibility to identify landscape segments on a detailed scale in the region of Jaboticabal, São Paulo, Brazil

The agricultural potential is generally assessed and managed based on a one-dimensional vision of the soil profile, however, the increased appreciation of sustainable production has stimulated studies on faster and more accurate evaluation techniques and methods of the agricultural potential on detailed scales. The objective of this study was to investigate the possibility of using soil magnetic susceptibility for the identification of landscape segments on a detailed scale in the region of Jaboticabal, São Paulo State. The studied area has two slope curvatures: linear and concave, subdivided into three landscape segments: upper slope (US, concave), middle slope (MS, linear) and lower slope (LS, linear). In each of these segments, 20 points were randomly sampled from a database with 207 samples forming a regular grid installed in each landscape segment. The soil physical and chemical properties, CO2 emissions (FCO2) and magnetic susceptibility (MS) of the samples were evaluated represented by: magnetic susceptibility of air-dried fine earth (MS ADFE), magnetic susceptibility of the total sand fraction (MS TS) and magnetic susceptibility of the clay fraction (MS Cl) in the 0.00 - 0.15 m layer. The principal component analysis showed that MS is an important property that can be used to identify landscape segments, because the correlation of this property within the first principal component was high. The hierarchical cluster analysis method identified two groups based on the variables selected by principal component analysis; of the six selected variables, three were related to magnetic susceptibility. The landscape segments were differentiated similarly by the principal component analysis and by the cluster analysis using only the properties with higher discriminatory power. The cluster analysis of MS ADFE, MS TS and MS Cl allowed the formation of three groups that agree with the segment division established in the field. The grouping by cluster analysis indicated MS as a tool that could facilitate the identification of landscape segments and enable the mapping of more homogeneous areas at similar locations.

Artificial neural networks applied for soil class prediction in mountainous landscape of the Serra do Mar¹

Soil information is needed for managing the agricultural environment. The aim of this study was to apply artificial neural networks (ANNs) for the prediction of soil classes using orbital remote sensing products, terrain attributes derived from a digital elevation model and local geology information as data sources. This approach to digital soil mapping was evaluated in an area with a high degree of lithologic diversity in the Serra do Mar. The neural network simulator used in this study was JavaNNS and the backpropagation learning algorithm. For soil class prediction, different combinations of the selected discriminant variables were tested: elevation, declivity, aspect, curvature, curvature plan, curvature profile, topographic index, solar radiation, LS topographic factor, local geology information, and clay mineral indices, iron oxides and the normalized difference vegetation index (NDVI) derived from an image of a Landsat-7 Enhanced Thematic Mapper Plus (ETM+) sensor. With the tested sets, best results were obtained when all discriminant variables were associated with geological information (overall accuracy 93.2 - 95.6 %, Kappa index 0.924 - 0.951, for set 13). Excluding the variable profile curvature (set 12), overall accuracy ranged from 93.9 to 95.4 % and the Kappa index from 0.932 to 0.948. The maps based on the neural network classifier were consistent and similar to conventional soil maps drawn for the study area, although with more spatial details. The results show the potential of ANNs for soil class prediction in mountainous areas with lithological diversity.

The Moroccan political partisan landscape : a polarized microcosm?

Using an original investigative protocol and a data base of 4,127 national delegates from ten Moroccan political organizations, surveyed between 2008 and 2012, this article examines the characteristics of party members in Morocco. Initial results indicate that the field of Moroccan political parties is a small world dominated by city dwellers, mature men, and the most highly educated, wealthiest individuals. However, far from being isolated from ordinary citizens, there are social dynamics at work. While it cannot be reduced to a segmented clientele, it is, nonetheless, shaped by an ideal-typical opposition between parties of notables and parties of activists.