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Modelagem do desmatamento no noroeste mato-grossense

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dc.contributor.advisor Filho, Arnaldo Carneiro Ferreira, Daniel Assumpção Costa 2013-10-21T18:28:05Z 2013-10-21T18:28:05Z 2006-06
dc.identifier.citation FERREIRA, D. A. C. Modelagem do desmatamento no noroeste mato-grossense. 2006. 109 f. Dissertação (Mestrado em Ciência de Florestas Tropicais) - Instituto Nacional de pesquisas da Amazônia, Manaus. 2006. pt_BR
dc.description Dissertação de mestrado defendida no INPA - INSTITUTO NACIONAL DE PESQUISAS DA AMAZÔNIA pt_BR
dc.description.abstract pt_BR
dc.description.abstract The Amazon has the largest tropical rain forest in the world, containing the largest proportion of natural forest and one fifth of the world ́s fresh water sources. Approximately 700.000 km2, or 17% of the Brazilian part of the Amazon, had been already deforested by 2005. Most of this deforestation is concentrated at the “deforestation arc “, region that comprised the southern and southwestern parties of the state of Pará, the northern part of the state of Mato-Grosso and the central part of the state of Rondônia. Among these states, Mato Grosso deserves special attention, because over the last 10 years, this state was responsible for at least 35% of the deforestation reported annually by the Brazilian National Institute of Spatial Research (INPE - PRODES). In 2004 this level rose to 48%. Although, historically, livestock was considered to be the main vector of deforestation, occupying approximately 75% of the total deforested area in the Amazon today, in the state of Mato-Gosso the expansion of soybean cultivation has recently gained importance. The considerable rise of the deforestation rates in this state, between 2000 and 2004, coincide with the entrance of the soybean crop in the Amazon biome. Although this crop is mainly grown in former pasture areas, it forces the livestock production to shift to new frontier areas and clear pristine forest. Considering the facts above, the aim of this study was to analyze the present spatio- temporal dynamics of the deforestation in Mato-Grosso state and to predict the spatial configuration of the residual forest up to the year 2020. For the simulation of scenarios we used a spatial explicit model, called DINAMICA, based on cellular automata. We simulated 3 distinct scenarios at two different spatial scales: (1) the central north and northwest region of Mato Grosso state, (2) Colniza -MT county. At both scales the simulated scenarios were: (1) Business as usual – based on the annual deforestation rate reported for the period 2000 - 2004, (2) intermediary – based on the deforestation rate registered between 2004-2005, when the deforestation rate decreased by approximately 50%, and (3) optimistic – based on the Brazilian Forest Code that requires maintenanced the legal reserve status in 80% of private properties under forest. However, on a regional scale this percentage was reduced to a more realistic level of 50%, because 32% of the forest over these areas had been already deforested by 2004. On a regional scale, among the 3 simulated scenarios up to 2020, only the optimistic scenario would maintain a forest matrix with reasonable connectivity among the forest fragments. If we maintain the deforestation rates observed in the usual and intermediary scenarios, in 2020 we will have respectively 69.3% and 55% of the total area deforested with the residual forest being limited to the protected areas and some portions on the extreme northwest of the region. With the projections made for Colniza- MT county, of the 90% forest cover in 2004, deforestation at the present rate will reduce this amount to approximately 70% in 2020. If actually implemented, the 80% legal reserve policy imposed by the Brazillian Forest Code will be of great value for maintain future quality of life, including ecological, social and economic values in this county. pt_BR
dc.format 109 folhas pt_BR
dc.language.iso pt_BR pt_BR
dc.subject.classification Ciências Florestais::Meio ambiente pt_BR
dc.subject.classification Ciências Florestais::Meio ambiente::Gestão ambiental pt_BR
dc.subject.classification Ciências Florestais::Manejo florestal::Geoprocessamento e sensoriamento remoto pt_BR
dc.title Modelagem do desmatamento no noroeste mato-grossense pt_BR
dc.type Dissertação pt_BR

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