Carbon sequestration: mathematical model of the Brazilian Atlantic Forest.

• Ano de defesa: 2016
• Autor(a) principal: Villacampa, Marion
• Tipo de documento: Tese
• Tipo de acesso: Acesso aberto
• Idioma: eng
• Instituição de defesa: Biblioteca Digitais de Teses e Dissertações da USP
• Palavras-chave em Português: Biomass; Biomassa; Mathematical models; Modelos matemáticos
• Link de acesso: http://www.teses.usp.br/teses/disponiveis/3/3137/tde-12122016-113919/

The Brazilian Atlantic Forest is one of the world\'s biodiversity hotspots and probably one of the most highly threatened tropical forests. Understanding the forest, the carbon sequestration and develop a valid representation of the longterm dynamics of natural tropical forest are essential. Building a local forest growth model including anthropogenic activities will lead us to a better understanding in order to take sustainable actions. In the first part of the thesis a model of the floristic and ecological interaction in plant communities in the Parque Estadual da Serra do Mar, state of São Paulo, Brazil is built. The model is a multi-species model which contains nine functionally different species, each depicting a component of the canopy layer that it can reach and a shade tolerance. In a second part, the thesis explores the impact of different patterns of non forest areas due to human colonization on the Brazilian Atlantic Forest. The long-term structure, the dynamics and the carbon sequestration of the forest is then analyzed. The results suggest that an offshore inland colonization minimizes ecological impact on the forest composition and on the quantity of carbon stored in the forest biomass. Finally this project aims to understand the forest regeneration under different scenarios. The thesis determines how long it takes for the forest to recover after a clear out, and what are the impacts of external seed input playing during the regeneration of the forest. The proposed model gives satisfactory results and can be use as a decision support tool in order to take sustainable actions.