Combining climatic and soil properties better predicts covers of Brazilian biomes

Several techniques have been used to model the area covered by biomes or species. However, most models allow little freedom of choice of response variables and are conditioned to the use of climate predictors. This major restriction of the models has generated distributions of low accuracy or inconsistent with the actual cover. Our objective was to characterize the environmental space of the most representative biomes of Brazil and predict their cover, using climate and soil-related predictors. As sample units, we used 500 cells of 100 km² for ten biomes, derived from the official vegetation map of Brazil (IBGE 2004). With a total of 38 (climatic and soil-related) predictors, an a priori model was run with the random forest classifier. Each biome was calibrated with 75% of the samples. The final model was based on four climate and six soil-related predictors, the most important variables for the a priori model, without collinearity. The model reached a kappa value of 0.82, generating a highly consistent prediction with the actual cover of the country. We showed here that the richness of biomes should not be underestimated, and that in spite of the complex relationship, highly accurate modeling based on climatic and soil-related predictors is possible. These predictors are complementary, for covering different parts of the multidimensional niche. Thus, a single biome can cover a wide range of climatic space, versus a narrow range of soil types, so that its prediction is best adjusted by soil-related variables, or vice versa.     

Absorption and translocation of sulfometuron-methyl in sugarcane (Saccharum officinarum L.) at different growth stages

ABSTRACT

In Brazil, weed management in sugarcane fields is mainly done with the use of selective herbicide formulations. For many years, diuron+hexazinone was one of the main herbicide mixture formulations used in sugarcane. Later, sulfometuron-methyl was included in the same mixture, which was marketed as a new herbicide formulation for residual in-season weed control in sugarcane. The mixture diuron+hexazinone+sulfometuron-methyl has been widely used in commercial sugarcane fields in Brazil. However, recent field observations have shown that sugarcane plants at different growth stages varied in their phytotoxicity levels after treatment with diuron+hexazinone+sulfometuron-methyl. Greenhouse and laboratory studies were conducted to determine ¹⁴Csulfometuron-methyl absorption and translocation, as well as ¹⁴C distribution in sugarcane at two growth stages, 2 to 3 leaves and 5 to 6 leaves. ¹⁴Csulfometuron-methyl absorption by sugarcane did not differ between the two growth stages. Different patterns of ¹⁴C accumulation were observed, which may explain variations in sulfometuron-methyl phytotoxic responses observed in the field.     

New objective function for data reconciliation in water balance from industrial processes

The promotion of a better rational use of water in industry requires an adequate knowledge of aqueous streams inside industrial plants. The main difficulty found in this respect is a lack of accurate measurement of such streams. In order to overcome this difficulty, a water balance tool with data reconciliation is used. This paper presents a method based on the idea that an estimated assumption can be made for any flow rate based on the best available information (quality of information). The quality of information is inversely proportional to the uncertainty of the estimated or measured flow rate and therefore there is a proportionality constant that relates these two. This paper demonstrates that the values of the proportionality constants in the real system are proximally the same for any stream. Furthermore, the proposed method has been applied to real systems with very poor measurement. This method enables the data reconciliation from water balances without data redundancy and without having to ignore flow rates with high levels of uncertainty.     

An integrated methodology for environmental impacts and costs evaluation in industrial processes

The development of methods for process analysis has contributed to the improvement of production systems. In this context, many models and methodologies have been established in the literature in order to evaluate environmental performance of industrial processes, since it has become an important issue for society. However, few of them analyze environmental impacts and related costs simultaneously. So, this work presents an integrated methodology to perform this evaluation, based on Life Cycle Assessment (LCA) and Activity-Based Costing (ABC) principles. The proposed methodology was applied in a metallurgical industry in Brazil. As result, it allowed to identify the production process stages which have critical environmental impacts and greatest contribution to increase environmental costs of the company.     

Genetic differentiation between morphotypes in the Antarctic limpet <Emphasis Type="Italic">Nacella concinna</Emphasis> as revealed by inter-simple sequence repeat markers

The limpet Nacella concinna (Strebel 1908) was the focus of numerous studies dealing with Antarctic benthos. One of the main characteristics of the species is the presence of two distinguishable morphotypes, one inhabiting the intertidal (during summer) and the other inhabiting the subtidal. For a long time these forms were considered as an expression of phenotypic plasticity, since previous studies did not found genetic differences between them. In the present work, we performed both a morphometric and a genetic differentiation analysis (using ISSR-PCR markers) of these two forms in three stations sampled at Potter Cove, South Shetland Islands. The results confirmed the morphological differences between intertidal and subtidal forms reported in other Antarctic localities. The genetic differences detected indicate that the two forms can be considered as genetically distinct populations maintaining low levels of gene flow. The degree of reproductive isolation of the ecotypes is discussed, as well as the possible origin of the divergence. The genetic differentiation observed can also have behavioral and physiological correlates, pointing out the importance of taking into account the potential differences in the response of both populations to different conditions in future studies in this species. M. C. de Aranzamendi and R. Sahade contributed equally to this paper.     

Analysis of PCB levels in snow from the Aconcagua Mountain (Southern Andes) using the stir bar sorptive extraction

This paper presents a first result of an investigation of the presence of anthropogenic pollutants named polychlorinated biphenyls (PCBs, sum of 25 congeners) in snow samples in the Aconcagua Mountains in the Andean Range, along an altitudinal gradient. Samples were taken during an expedition in 2003 and analysed by using a specific technique of thermodesorption and GC-MS adapted to small amount of sample. Mountain ecosystems could be efficient natural trap of persistent organic pollutants (POPs) transported by the atmosphere, and it is shown in this note that PCBs are also present in snow samples but at low concentrations, levels ranged from 0.02 to 0.190 ng/L. The detected congeners were those more persistent (PCB 138, PCB180) and compared to other mountain and cold areas around the world, detected levels are in the low range indicating that pollution levels are lower in the southern hemisphere. This results points out the need of investigating with some more detail the role of mountains in the trapping of POPs and the associated risks including the climate change.     

Calibration and predictive ability analysis of longitudinal solute transport models in mountain streams

The first step in developing travel time and water quality models in streams is to correctly model solute transport mechanisms. In this paper a comparison between two solute transport models is performed. The parameters of the Transient Storage model (TS) and the Aggregated Dead Zone model (ADZ) are estimated using data of thirty seven tracer experiments carried out under different discharges in five mountain streams of Colombian Los Andes. Calibration is performed with the generalized uncertainty estimation method (GLUE) based on Monte-Carlo simulations. Aspects of model parameters identifiability and model parsimony are analyzed and discussed. The TS model with four parameters shows excellent results during calibration but the model parameters present high interaction and poor identifiability. The ADZ model with two independent and clearly identifiable parameters gives sufficiently precise calibration results. As a conclusion, it is stated that the ADZ model with only two parameters is a parsimonious model that is able to represent solute transport mechanisms of advection and longitudinal dispersion in the studied mountain streams. A simple model parameter estimation methodology as a function of discharge is proposed in this work to be used in prediction mode of travel time and solute transport applications along mountain streams.