Classical parameters of Shadowlands by Richard Attenborough (On C. S. Lewis's Life and Work)

The aim of this article is to show the classical parameters of Shadowlands by R. Attenborough, with a screenplay by W. Nicholson, on C. S. Lewis's life and work. Based upon an accurate reading of Lewis's works, the author of this article proposes to interpret the opposition Lewis / Gresham as the translation into the real life of the opposition between the Platonic or idealistic and the Aristotelian or materialistic temperaments which was already maintained by Coleridge. In any case, there are many classical references which must be taken into account in order to understand to what extent C. S. Lewis's Christianity is also a classic Christianity, that is, a Greek and Latin one.

Surface mapping, organic matter and water stocks in peatlands of the Serra do Espinhaço meridional - Brazil

Peatlands are soil environments that store carbon and large amounts of water, due to their composition (90 % water), low hydraulic conductivity and a sponge-like behavior. It is estimated that peat bogs cover approximately 4.2 % of the Earth's surface and stock 28.4 % of the soil carbon of the planet. Approximately 612 000 ha of peatlands have been mapped in Brazil, but the peat bogs in the Serra do Espinhaço Meridional (SdEM) were not included. The objective of this study was to map the peat bogs of the northern part of the SdEM and estimate the organic matter pools and water volume they stock. The peat bogs were pre-identified and mapped by GIS and remote sensing techniques, using ArcGIS 9.3, ENVI 4.5 and GPS Track Maker Pro software and the maps validated in the field. Six peat bogs were mapped in detail (1:20,000 and 1:5,000) by transects spaced 100 m and each transect were determined every 20 m, the UTM (Universal Transverse Mercator) coordinates, depth and samples collected for characterization and determination of organic matter, according to the Brazilian System of Soil Classification. In the northern part of SdEM, 14,287.55 ha of peatlands were mapped, distributed over 1,180,109 ha, representing 1.2 % of the total area. These peatlands have an average volume of 170,021,845.00 m³ and stock 6,120,167 t (428.36 t ha-1) of organic matter and 142,138,262 m³ (9,948 m³ ha-1) of water. In the peat bogs of the Serra do Espinhaço Meridional, advanced stages of decomposing (sapric) organic matter predominate, followed by the intermediate stage (hemic). The vertical growth rate of the peatlands ranged between 0.04 and 0.43 mm year-1, while the carbon accumulation rate varied between 6.59 and 37.66 g m-2 year-1. The peat bogs of the SdEM contain the headwaters of important water bodies in the basins of the Jequitinhonha and San Francisco Rivers and store large amounts of organic carbon and water, which is the reason why the protection and preservation of these soil environments is such an urgent and increasing need.

Gênese e classificação dos solos de uma topossequência em área de carste na Serra da Bodoquena , MS

Pouco se conhece sobre os solos dos sistemas cársticos carbonáticos no Brasil, apesar da sua importância e reconhecida fragilidade. Os objetivos deste estudo foram avaliar a gênese de solos desenvolvidos de rochas calcárias e materiais derivados e caracterizar os atributos desses, contribuindo para o Sistema Brasileiro de Classificação de Solos (SiBCS). Foram estudados três perfis de solos em uma topossequência na Serra da Bodoquena, MS, dispostos nas posições de sopé (P1), terço médio (P2) e topo (P3) de encosta suave-ondulada com pendente longa e perfil longitudinal plano-convexo-plano. Todos os perfis são profundos, com cores bruno-escura nos horizontes superficiais e avermelhada em subsuperfície, além de textura argilosa com incremento de argila em profundidade. O íon cálcio predomina no complexo sortivo, bem como a fração humina entre as frações húmicas. A micromorfologia dos solos revela feições de iluviação de argila em associação com feições de acumulações de CaCO3. Porém, em nenhum dos perfis, os teores de CaCO3 equivalente foram suficientes para o reconhecimento do horizonte cálcico e, ou, petrocálcico, ou de caráter carbonático ou hipocarbonático. Com sequência de horizontes A-Bt (P1); A-E-Bt (P2); e A-Bi (P3), os solos apresentam a seguinte ordem de evolução pedogenética: P1 > P2 > P3. De acordo com o SiBCS, os solos são classificados como Argissolo Vermelho eutrófico nitossólico (P1); Argissolo Vermelho distrófico típico (P2); e Cambissolo Háplico Tb eutrófico típico (P3). Para todos os perfis, no quinto nível aplica-se a classe de atividade de argila - Tm (atividade média), validando proposta recente do SiBCS.

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.