Predicting species compositional turnover across the Amazon wetlands from evolutionary and ecological characteristics

• Grant number: 18/23532-1
• Support Opportunities: Scholarships abroad - Research Internship - Doctorate
• Start date: April 15, 2019
• End date: July 14, 2019
• Field of knowledge: Biological Sciences - Ecology - Applied Ecology
• Principal Investigator: Clarisse Palma da Silva
• Grantee: Bruno Garcia Luize
• Supervisor: Simon Ferrier
• Host Institution: Instituto de Biociências (IB). Universidade Estadual Paulista (UNESP). Campus de Rio Claro. Rio Claro , SP, Brazil
• Institution abroad: Commonwealth Scientific and Industrial Research Organisation (CSIRO), Australia
• Associated to the scholarship: 15/24554-0 - The role of floodplains in the origin and maintenance of tree species diversity in the Amazon, BP.DR

Abstract

Biodiversity is a common good of global concern. Nonetheless, much of the life on Earth is threatened by both local and global human actions. The steep increase of biodiversity loss is not accompanied by the same pace of our understanding of biodiversity distribution and evolution. Australian researchers and institutions are at the frontier of biodiversity assessment, producing much valuable information and developing new methods to improve our understanding of biodiversity. Variations in species distribution might cause dissimilarity in community composition. Therefore, we need to know exactly the area of distribution for each species to shed light on the pattern of biodiversity distribution across landscapes and regions. Generalized Dissimilarity Modelling (GDM) is advocated as a "statistical technique for analyzing and predicting spatial patterns of turnover in community composition" and close to 400 studies have applied the approach since 2007, when the authors proposed it. GDM relates biotic and abiotic data (i.e. compositional dissimilarity and environmental variables). The proposed research to be conducted during my internship in Australia aims to apply GDM models to understand the pattern of compositional dissimilarity in floodplain forests of the Central Amazon region and the role of environmental gradients in this generating this pattern. During 2008-2013, I performed forest inventories in 43 localities along the Amazon river mainstream, encompassing an area of approximately 52,000km2. From these inventories, close to 400 tree species were registered and flooding regime information for each plot was assessed. For implementation of the analyses I will calculate a compositional dissimilarity matrix between pairs of plots, I-spline basis functions for three different environmental gradients that define the plots surveyed and the absolute differences between these I-spline values for each pair of plots. I expect to generate a map predicting the compositional variation in floodplain forests of Central Amazon, which could be readily applied by policy makers and conservation planners. I also expect to generate a scientific paper discussing the role of environmental gradients driving the compositional dissimilarity found in these forests. The internship opportunity will advance my research in biodiversity since I will learn how to apply these analyses directly from the researchers who developed the methodology and I will have the chance to generate one outcome proposed in my PhD project.