Tendências ecológicas de longo prazo das Florestas Tropicais Sazonais em Minas Gerais

Detalhes bibliográficos
Ano de defesa: 2021
Autor(a) principal: Paula, Gabriela Gomes Pires de
Orientador(a): Não Informado pela instituição
Banca de defesa: Não Informado pela instituição
Tipo de documento: Tese
Tipo de acesso: Acesso aberto
Idioma: por
Instituição de defesa: Universidade Federal de Lavras
Programa de Pós-Graduação em Engenharia Florestal
UFLA
brasil
Departamento de Ciências Florestais
Programa de Pós-Graduação: Não Informado pela instituição
Departamento: Não Informado pela instituição
País: Não Informado pela instituição
Palavras-chave em Português:
Link de acesso: http://repositorio.ufla.br/jspui/handle/1/48031
Resumo: The rapid and accelerating loss of biodiversity is the most significant ecological challenge we face today, and while the tropical rainforests of South America are known to be heavily affected by climate change, long-term ecological trends in seasonal forests are still low. Through monitoring 32 areas of cerrado forests, Atlantic forest and caatinga in Minas Gerais, we approached the behavior of forest species over time, with some areas having been monitored for more than 20 years. In the first article, we assess the ecological trends of seasonal forests under the influence of environmental and climatic variables and how these variables are reflecting on forest demography and productivity. The second article addresses how the forest species monitored are framed by the IUCN conservation criteria. From this, together with the study of the characteristics of the species (example: biomass, frequency, probability of exclusion) we propose a more refined way of classifying the species, with the objective of subsidizing projects of restoration, recomposition and conservation of the species in our region of study. It is expected that this thesis summarizes the behavior of forest species in seasonal forests over the past few years and that, based on that, it will foster new discussions on how to use forest monitoring data for species conservation.