Diagnóstico e proposta para estratégias de mitigação e políticas públicas para a conservação da Amazônia Legal

• Autor(a) principal: Miranda, Yara Campos
• Data de Publicação: 2022
• Tipo de documento: Tese
• Idioma: por
• Título da fonte: Repositório Institucional da UFSCAR
• Texto Completo: https://repositorio.ufscar.br/handle/ufscar/17366
• topic: Impactos ambientais na Amazônia; Modelos de previsão; Pagamento por serviços ambientais; Valor presente líquido; Disposição a pagar; Environmental impacts in the Amazon; Prediction models; Payment for environmental services; Willingness to pay; CIENCIAS AGRARIAS::RECURSOS FLORESTAIS E ENGENHARIA FLORESTAL::CONSERVACAO DA NATUREZA::CONSERVACAO DE BACIAS HIDROGRAFICAS; CIENCIAS AGRARIAS::RECURSOS FLORESTAIS E ENGENHARIA FLORESTAL::CONSERVACAO DA NATUREZA::RECUPERACAO DE AREAS DEGRADADAS; ENGENHARIAS::ENGENHARIA SANITARIA::RECURSOS HIDRICOS

The fragmentation of habitats from deforestation is one of the main agents of anthropogenic degradation in the Legal Amazon region. As a result, diagnoses that seek to identify priority areas and propose mitigation strategies are essential to guarantee the preservation of the largest tropical forest in the world. In this scenario, programs based on Payment for Environmental Services (PSA) stand out. The objective of this work is to understand the dynamics of deforestation in the Legal Amazon region in order to propose environmental valuation strategies that reconcile economic activities with environmental variables. To this end, initially, a historical analysis of the behavior of hot spots in the Brazilian Amazon was carried out in the period from 2000 to 2020, which resulted in the fact that 76% of the records affect the states of Pará, Mato Grosso and Rondônia, occurred mainly between 2000 and 2010. Also, the data reflect seasonality, in which the foci are concentrated in the dry period, that is, between August and November. With this, it is possible to verify that the region with the highest incidence of fires corresponds to the arc of deforestation, an environment in which public policies and monitoring strategies must be more effective, in order to control the anthropic process of expansion of the agricultural frontier, since most of the recorded fires are of anthropic origin. Faced with such findings, a comparative analysis was carried out between the burned area of the Legal Amazon and the Province of Alberta in Canada, both regions that record the highest numbers of fires in the world. For this purpose, a linear polynomial regression statistical model was used combined with a stochastic volativity model based on burned area data, with both data provided by the relevant environmental agencies. The results demonstrated the influence of meteorological variables on the size of the burned areas, since the largest records correspond to the dry periods in both regions. Also, that public policies for monitoring and regulating activities are fundamental, as they condition a quick response from the registration of hot spots, which favors effective control combined with less severe environmental impacts. From the understanding of the influence of natural and anthropic variables, a comparison was made between two multicriteria methods OWA and WLC in five different scenarios for the identification of priority areas of the legal Amazon, verifying that the state of Mato Grosso is the one that covers the greater territorial extension of priority areas. In addition, it was concluded that both are accessible tools for environmental planning, and the choice between them will depend on the planner's experience and the objective of the work. Based on this identification, an environmental valuation model was proposed for the Nascentes do Rio Xingu Watershed based on calculations of the opportunity cost of Net Present Value (NPV). As a result, it was found that in order to preserve and recover areas classified as a priority by the proposed method, R$ 12,495 billion are needed, of which R$ 4.67 billion are destined for the application of PSA in areas with high priority and very tall. In this way, the data demonstrate that the identification of priority areas favors the planning process, providing valuable data for the allocation of resources and environmental preservation.