Combining species distribution modelling and environmental perceptions to support sustainable strategies for Amazon-nut (Bertholletia excelsa Bonpl.) planting and conservation

• Ano de defesa: 2018
• Autor(a) principal: Tourne, Daiana Carolina Monteiro
• 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: Amazônia; Conservação; Conservation; Environmental perception; Espécie ameaçada; Habitat suitability; Modelagem de habitat; Percepção ambiental; Threatened species
• Link de acesso: http://www.teses.usp.br/teses/disponiveis/91/91131/tde-14032019-160707/

The amazon ecosystems have been compromised by historical forms of occupation and land-use causing habitat loss and forest fragmentation. These anthropogenic disturbances associated to climate changes have direct consequences on the distribution of species and their in situ persistence. Currently, 76 of 14.003 plants taxonomically identified in the Amazon have been listed by the Brasilian Ministry of the Environment as threatened species, though we believe this number to be much bigger in the reality. Among them, Amazon-nut (Bertholletia excelsa), a native tree species, national and internationally known for its cultural, social-economic and nutritional value has been classified as vulnerable. For developping of public policy turned to its management and conservation is fundamental to know the percentage of habitat available, as well as the nature and scale of threats to this environments. Species distribution modelling is an increasingly important tool for predicting habitat suitability and for understanding species environmental tolerances, but has been rarely used in Brazil, especially for Amazonian species. This study aimed to model the potential distribution of B. excelsa in the Amazon biome and to know the factors that control its distribution. To enhance our analysis, case studies were carried out with stakeholders aiming to know their perceptions about the main threats to the species and potential solutions.This research project was based on two hypotheses: (i) There is a suitable habitat to Amazon-nut which require different objectives for conservation and planting; (ii) If the local people are aware of the species vulnerability, they are able to point out the factors that cause this condition. In the chapter 1, habitat was investigated using MAXENT algoritm. We collected 3,325 Amazon-nut records and organized one hundred-and-two environmental variables into climatic, edaphic and geophysical categories at a spatial resolution of 30 arcs-second (~1km). Multi-colinearity between variables was dealt with multivariate statistics associated to expert\'s knowledge, and presence data biased with the spatial filtering. The best model was selected adopting quantitative metrics and visual examination. The most importante biophysic variables we identified were: altitude (m), coarse soil fragments (<2mm) and clay (%). Finaly, the best model indicated 2.3 million km2 i.e., 32% of the Amazon basin has potential for B. excelsa to grow. In the chapter 2, the factors that affect Amazon-nut conservation and planting were discussed with local communities, public managers and researchers, totalyzing 203 participants. Focus groups, individual interviews and questionaire techniques were used to gather information. Data were categorized and the perceptions among stakeholders compared using quali-quantitative analyses. We found that there are currently 36 problems responsible for the species vulnerability and 72% of them belong to environmental and political contexts. Deforestation was the main problem mentioned, followed by fruit depreciation, control failures and lack of organization in the communities. For three groups of stakeholders, the main solutions were related to political context. The results obtained in this study contribute to increase ecological knowledge on the species, to demonstrate the complexity of sustainable use in the Amazon and to guide decisions makers in the selection of priority areas for conservation and potential planting.