Utilização de modelo matemático na busca do manejo sustentável das pastagens naturais

Abstract

The objective was to model on a scale spatiotemporal dynamics of rangeland vegetation types characterized by functional when subjected to different disorders, aiming to predict patterns in the vegetation inventory for future analysis of the fractal dimension associated with the model of cellular automata. So, initially evaluated the use of fractal analysis as a tool to determine patterns in a reduced scale of grazing on natural pastures under different managements. The experiment evaluated the effect of grazing and burning disturbances applied in two relief positions in a natural grassland located in Santa Maria-RS. Another area located in Bagé-RS assesses the improvement of natural grassland with the introduction of ryegrass, white clover and birdsfoot trefoil. The diversity of the pasture was derived by Shannon and Equitabilidade indices. The information fractal dimension was calculated by regression between the Shannon index(ε) and ε natural algorithm, and the slope of the fractal dimension information. The results showed that the fractal dimension can be a tool for determining patterns in plant community in small-scale grazing. The limitation of this technique to small scales is the need for a greater number of repetitions. Secondly, we validated a model is spatially explicit empirical predictive vegetation dynamics of a natural grassland subjected to different disorders based on cellular automata using the approach of plant functional types by comparing the model predictions with actual observations of experiments. The simulations were performed in two temporal and spatial scales, small and large. The temporal resolution of monthly simulation was considered when the spatial dimension was 0.0625 square meters, featuring a reduced scale. A wide range was considered when the temporal resolution was annual and the spatial dimension was 306.25 m². The factors were: grazing, absence and presence, he burns the absence and presence and position of relief, slope and lowland. The model consists of a three-dimensional array, the first being characterized by the temporal dimension and the second and third, representing flat two-dimensional space, each cell being a PFT, which changes with each step in time as the composition of cell itself and the eight neighboring cells. The model evaluated proved to be efficient in predicting the dynamics of natural grassland vegetation can be used to simulate different scenarios. However, the limitation of the model is correct in determining the level of disturbance. Finally, we introduced the fractal dimension to the previously mentioned model and simulated the effect of grazing management of the biennial burns or every three years, with each simulation corresponded to 100 iterations with a spatial resolution of 306.25 m² and temporal equal to one year. The level of disturbance adopted to characterize both the grazing and burning was 0.18. In the treatments with burns, the years when it was used the level of disorder was 0.36, corresponding to the sum of grazing disturbance and burning. The treatments were evaluated in relation to two situations of environmental resources (and with great restraint). The evaluation of fractal dimension in spatially explicit model based on cellular automata has proven to be a viable tool to determine patterns and dynamics of plant communities regardless of scale. The model does not adequately simulated the colonization of species, this being a key topic for future studies that use this approach. The use of only two functional types allowed better visualization of results. The determination of the amount of functional types to be used in the simulation will depend on further investigations.