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Modelling Amazon nut (Bertholletia excelsa Bonpl.) current and future distribution to subsidize plantations and conservation sustainable strategies

Grant number: 16/16718-6
Support Opportunities:Scholarships abroad - Research Internship - Doctorate
Start date: March 13, 2017
End date: March 12, 2018
Field of knowledge:Biological Sciences - Ecology - Applied Ecology
Principal Investigator:Maria Victoria Ramos Ballester
Grantee:Daiana Carolina Monteiro Tourne
Supervisor: Patrick M. A. James
Host Institution: Centro de Energia Nuclear na Agricultura (CENA). Universidade de São Paulo (USP). Piracicaba , SP, Brazil
Institution abroad: Université de Montréal, Canada  
Associated to the scholarship:15/04749-1 - Modelling Amazon nut (Bertholletia excelsa Bonpl.) current and future distribution to subsidize plantations and conservation sustainable strategies, BP.DR

Abstract

The amazon rainforest has been impaired by historical forms of occupation and land-use that cause habitat loss and forest fragmentation. These anthropogenic disturbances associated with climate change have direct consequences on the distribution of species. Amazon nut (Bertholetia excelsa Bonpl.) is an endangered amazon native species and protected by Ministry of Environment of Brazil (MMA) and it was classified as vulnerability level according to the International Union for Conservation of Nature (IUCN). However, the Amazon nut trees have sustained ecological and social relevance for wildlife, flora and human communities in the Amazon, even outside the Brazilian limits. Thus, the objective of this project are identify the main factors that influence amazon nut distribution using modeling capabilities in other to obtain their current and future distribution adding information of landscape ecology and environmental perception. The project will be made in two scale of analysis: 1) Current and future modeling distribution at Panamazon; 2) identification of the factors that influence the current distribution of specie in State of Para through semi-structured interviews and mappings based on local social agents and landscapes metrics. Biotic and abiotic variables will be integrated by complex models recommended in the scientific community, as maximum entropy (MAXENT) with support by classification and regression analysis trees (CART). This project is based on three hypothesis (i) There are zones with the highest suitability for amazon nut that support different goals for conservation and planting in the Amazon; (ii) local population has perception this species is endangered; (iii) the area of species distribution is reduced with climate changes. Therefore, to add more scientific knowledge to this Thesis research in progress, we propose a stage with research groups abroad in order to analyze the models built in Brazil (discuss our methodologies applied, the data, as well as the results in ecological modelling), then we will analyze forest fragments in four municipalities in the State of Pará by landscape ecology techniques. Next, we will build models using the classification and regression tree, finally we hope that the two institutions together may prepare robust predictions of species distribution and develop strategies for the conservation and planting of Amazon nut.

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