Macroinvertebrates under stochastic hydrological disturbance in Cerrado streams of Central Brazil

In the Cerrado vegetation, where the seasonal is well defined, rainfall has an important role in controlling the flow of streams and consequently on the structure of macroinvertebrates community. Despite the effects of rainfall associated with seasonality are well studied, little is known about the effects of stochastic rains on the community. In the present study we evaluated the structure and faunal composition of four first-order streams in Central Brazil during the dry season in two years, with and without stochastic rains. Community sampling was done by colonization of boards of high density polyethylene (HDPE), removed after one month submerged in streams. Analysis of Variance (ANOVA) performed indicated no difference in rarefied richness between the two periods, different from numeric density of organisms that was higher in the period without disturbance; moreover, the Detrended Correspondence Analysis (DCA) revealed differences in faunal composition between the two periods. Our results indicate that stochastic rainfall is an important factor in structuring the macroinvertebrates community in studied region.

INCLUDING RISK IN ECONOMIC FEASIBILITY ANALYSIS:A STOCHASTIC SIMULATION MODEL FOR BLUEBERRY INVESTMENT DECISIONS IN CHILE

ABSTRACT The traditional method of net present value (NPV) to analyze the economic profitability of an investment (based on a deterministic approach) does not adequately represent the implicit risk associated with different but correlated input variables. Using a stochastic simulation approach for evaluating the profitability of blueberry (Vaccinium corymbosum L.) production in Chile, the objective of this study is to illustrate the complexity of including risk in economic feasibility analysis when the project is subject to several but correlated risks. The results of the simulation analysis suggest that the non-inclusion of the intratemporal correlation between input variables underestimate the risk associated with investment decisions. The methodological contribution of this study illustrates the complexity of the interrelationships between uncertain variables and their impact on the convenience of carrying out this type of business in Chile. The steps for the analysis of economic viability were: First, adjusted probability distributions for stochastic input variables (SIV) were simulated and validated. Second, the random values of SIV were used to calculate random values of variables such as production, revenues, costs, depreciation, taxes and net cash flows. Third, the complete stochastic model was simulated with 10,000 iterations using random values for SIV. This result gave information to estimate the probability distributions of the stochastic output variables (SOV) such as the net present value, internal rate of return, value at risk, average cost of production, contribution margin and return on capital. Fourth, the complete stochastic model simulation results were used to analyze alternative scenarios and provide the results to decision makers in the form of probabilities, probability distributions, and for the SOV probabilistic forecasts. The main conclusion shown that this project is a profitable alternative investment in fruit trees in Chile.

PRACTICAL STOCHASTIC MODEL FOR CHEMICAL KINETICS

The Practical Stochastic Model is a simple and robust method to describe coupled chemical reactions. The connection between this stochastic method and a deterministic method was initially established to understand how the parameters and variables that describe the concentration in both methods were related. It was necessary to define two main concepts to make this connection: the filling of compartments or dilutions and the rate of reaction enhancement. The parameters, variables, and the time of the stochastic methods were scaled with the size of the compartment and were compared with a deterministic method. The deterministic approach was employed as an initial reference to achieve a consistent stochastic result. Finally, an independent robust stochastic method was obtained. This method could be compared with the Stochastic Simulation Algorithm developed by Gillespie, 1977. The Practical Stochastic Model produced absolute values that were essential to describe non-linear chemical reactions with a simple structure, and allowed for a correct description of the chemical kinetics.

Early detection of metabolic and energy disorders by thermal time series stochastic complexity analysis

Maintenance of thermal homeostasis in rats fed a high-fat diet (HFD) is associated with changes in their thermal balance. The thermodynamic relationship between heat dissipation and energy storage is altered by the ingestion of high-energy diet content. Observation of thermal registers of core temperature behavior, in humans and rodents, permits identification of some characteristics of time series, such as autoreference and stationarity that fit adequately to a stochastic analysis. To identify this change, we used, for the first time, a stochastic autoregressive model, the concepts of which match those associated with physiological systems involved and applied in male HFD rats compared with their appropriate standard food intake age-matched male controls (n=7 per group). By analyzing a recorded temperature time series, we were able to identify when thermal homeostasis would be affected by a new diet. The autoregressive time series model (AR model) was used to predict the occurrence of thermal homeostasis, and this model proved to be very effective in distinguishing such a physiological disorder. Thus, we infer from the results of our study that maximum entropy distribution as a means for stochastic characterization of temperature time series registers may be established as an important and early tool to aid in the diagnosis and prevention of metabolic diseases due to their ability to detect small variations in thermal profile.

Can future systemic financial risks be quantified?: ergodic vs nonergodic stochastic processes

Different axioms underlie efficient market theory and Keynes's liquidity preference theory. Efficient market theory assumes the ergodic axiom. Consequently, today's decision makers can calculate with actuarial precision the future value of all possible outcomes resulting from today's decisions. Since in an efficient market world decision makers "know" their intertemporal budget constraints, decision makers never default on a loan, i.e., systemic defaults, insolvencies, and bankruptcies are impossible. Keynes liquidity preference theory rejects the ergodic axiom. The future is ontologically uncertain. Accordingly systemic defaults and insolvencies can occur but can never be predicted in advance.

Options listing and the volatility of the underling asset: a study on the derivative market function

There are basic misunderstandings on derivative markets. Some professionals believe that they are a kind of casinos and have no utility for the investors. This work looks at the effects of options introduction in the Brazilian market, seeking for another benefit for this introduction: changes in the stocks risk leveI. Our results are the same found in the US and other markets: the options introduction reduces the stocks volatility. We also found that there is a slight indication that the volatility becames more stochastic with this alternative.

Arthropods obtained from the Amazonian tree species "Cupiuba" (Goupia glabra) by repeated canopy fogging with natural Pyrethrum

Two canopies of a widely distributed Amazonian tree species, Goupia glabra Aubl. (Celastraceae, height 38 and 45m) were fogged several times with 1% natural pyrethrum during the rainy and dry seasons (1991-1994) in the Adolpho Ducke Forest Reserve near Manaus/Brazil. Between 50 and 158 ind./m2 of arthropods were obtained per tree and fogging event. Hymenoptera, mostly Formicidae, and Diptcra dominated. A total of 95 ant species occurred on a single tree. Most ants were permanently foraging in the canopy and their recolonization after fogging seems to follow stochastic pathways. Data indicated an interaction between - 1) predating Formicidae and gall building Cecidomyiidae and - 2) Cecidomyiidae and the parasitic Hymenoptera.

Tolerance to salinities shocks of the invasive mussel Limnoperma fortunei under experimental conditions

The golden mussel, Limnoperna fortunei (Dunker, 1857), has been found in the estuarine regions of South America, including the Patos Lagoon (Brazil), a huge choked lagoon with an estuarine region that is highly unstable chemically. Limnoperna fortunei space-temporal variability in the lagoon's estuarine region demonstrated the need to evaluate this species' ability to survive under salinity shocks. A set of experiments was conducted under controlled laboratory conditions. Specimens were tested under salinities of 2, 4, 6, 8 and 12 ppt, and were exposed for periods of 24, 48, 72, 96 and 240 hours. The mussel can survive (90%) up to a salinity shock of 2 ppt for periods of at least 10 days. Considering the influence of climatic and stochastic events and the chemical instability of the Patos Lagoon estuarine region, it's unlikely that populations could survive for longer periods (more than a year) in this area.

Daily variation of zooplankton abundance and evenness in the Rosana reservoir, Brazil: biotic and abiotic inferences

The zooplankton community presents stochastic temporal fluctuation and heterogeneous spatial variation determined by the relationships among the organisms and environmental conditions. We predicted that the temporal and spatial zooplankton distribution is heterogeneous and discrete, respectively, and that the daily variation of most abundant species is related to environmental conditions, specifically the availability of resources. Zooplankton samples were collected daily at three sampling stations in a lateral arm of the Rosana Reservoir (SP/PR). The zooplankton did not present significant differences in abundance and evenness among sampling stations, but the temporal variation of these attributes was significant. Abiotic variables and algal resource availability have significantly explained the daily variation of the most abundant species (p<0.001), however, the species distribution makes inferences on biotic relationships between them. Thus, not only the food resource availability is influential on the abundance of principal zooplankton species, but rather a set of factors (abiotic variables and biotic relationships).