Population growth and migration represent an important underlying cause of deforestation in the Brazilian Amazon. Models designed to simulate deforestation should therefore incorporate a demographic ...dynamics system to help project the influence of these variables on the location and rates of deforestation across the basin. We present a demographic model that projects population at municipality level by computing migration fluxes among the Amazonian municipalities and in and outward the region, as well as their crude birth and death rates. The annual projections from 1995 to 2035 are based mainly on mortality, fertility and migration data from 1991’s and 2000’s IBGE census. The model assumes a logistic curve to project the municipalities’ crude birth and death rates, which are derived using specific functions of fertility and mortality by age. The migratory fluxes were determined by establishing a origin-destiny matrix for all the Amazonian municipalities and Brazilian states for the 1995-2000 time period. VESIM, a system-thinking software which allows the solution of simultaneous equation for the 810 defined spatial units by employing integration techniques - such as the Runge-Kutta method, is used to implement the simulation model. Validation was performed comparing 2000’s IBGE municipality data. The model is designed to handle various scenarios of regional migration in face of the current projects to expand infrastructure across the Amazon region.
Population growth and migration represent an important underlying cause of deforestation in the Brazilian Amazon. Models designed to simulate deforestation should therefore incorporate a demographic ...dynamics system to help project the influence of these variables on the location and rates of deforestation across the basin. We present a demographic model that projects population at municipality level by computing migration fluxes among the Amazonian municipalities and in and outward the region, as well as their crude birth and death rates. The annual projections from 1995 to 2035 are based mainly on mortality, fertility and migration data from 1991's and 2000's IBGE census. The model assumes a logistic curve to project the municipalities' crude birth and death rates, which are derived using specific functions of fertility and mortality by age. The migratory fluxes were determined by establishing a origin-destiny matrix for all the Amazonian municipalities and Brazilian states for the 1995-2000 time period. VESIM, a system-thinking software which allows the solution of simultaneous equation for the 810 defined spatial units by employing integration techniques - such as the Runge-Kutta method, is used to implement the simulation model. Validation was performed comparing 2000's IBGE municipality data. The model is designed to handle various scenarios of regional migration in face of the current projects to expand infrastructure across the Amazon region.
Britain's peat ecosystems have long been regarded as little more than wastelands: not much good for agriculture, until recently a source of poor quality fuel for crofters in Scotland and often simply ...set aside for hunting. It is no coincidence that Britain's first national park, the Peak District, is made up largely of unwanted peat; an ecosystem further battered by soot and acid-rain pollution from surrounding industrial cities, which has eliminated many native plant species (Dudley, 1987). Solitary walks across Kinder Scout and the aptly named Bleaklow and Black Hill gave me both my first taste of the concept of wilderness and my first real understanding of how badly we have undermined our ecology. Yet all this could change. Peat is recognized as the ecosystem that stores more carbon than any other and is thus a potentially critical tool in mitigating climate change. It also plays a fundamental role in storing and releasing water, and therefore mediating seasonal groundwater and surface flows, but only if it is managed properly: the balance of greenhouse gas emissions and sequestration in peat is delicate and easily upset so that inappropriately managed peat can quickly become a net carbon emitter, which is probably the case in the Peak District. New projects are springing up around the country to improve management of peat, which invariably means introducing a form of management involving a great deal of protection. The economic value of the Peak District's uplands may be on the rise again.
This paper concerns the methodology applied to the erosive potential analysis in the Rio da Velhashydrographic basin (Minas Gerais State, Brasil) along with the results obtained. This project aimed ...at theproduction of a digital map at a 1: 200 000 scale of the fragility of both natural and human-interferedenvironments in Rio das Velhas Basin. The adopted approach seeks to integrate the combined effects of aset of variables – relief, soil, climate and land use/land cover – to identify the environmental instability andto map the ecodynamic units. First, the cartographic variables were classified according to their degree ofenvironmental instability, these were later combined pair-wise and a set of decision rules was applied toproduce the final map. The results depicted well the major fragile areas in the basin, which should receivespecial care for their preservation. The developed methodology is easily implemented and flexible enoughto permit changing the decision rules to fit different criteria.
A total of 256 sites in 11 habitats were surveyed for Biomphalaria in Melquiades rural area (State of Minas Gerais) in August and November 1999 and in March 2000. Of the 1,780 Biomphalaria collected, ...1,721 (96.7%) were B. glabrata and 59 (3.3%) B. straminea. Snails were found in all habitats except in wells, with the largest mean numbers in tanks, seepage ponds and canals, and the smallest numbers in springs, rice fields and fishponds. People's knowledge of the occurrence of Biomphalaria at the collection sites and the presence of Biomphalaria ova were strongly correlated with the occurrence of snails, and distance between houses and collection sites, as well as water velocity were inversely correlated with Biomphalaria occurrence (p < 0.001). The strongest predictor o f Biomphalaria occurrence was the presence of tilapia fish in fishponds. Fourteen Biomphalaria (0.8% of all snails) found at 6 sites were infected with Schistosoma mansoni. Suggestions are made for the utilization of local people's knowledge in snail surveys and further studies are recommended on the possible use of tilapia for biological control of Biomphalaria in fishponds, as well as modeling of S. mansoni transmission and reinfection.
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