Amazonia has an incredible biodiversity, shaped over millions of years. In recent millennia the climate in the region has become more humid, increasing the availability of suitable habitat for forest species and influencing its distributions and the expansion of the forest in this period. However, human influences on climate and land use have led to a reduction in the habitat of many species in the region, and projections show an intensification in the future with impacts potentially negative on the richness and distribution of Amazonian biodiversity. In addition, there are several knowledge gaps on how climate and land use has shaped and will shape the Amazonian rainforest, and the wide variety of methods available for such analysis also raises questions on the best methodological practices for studying an area as large and diverse as Amazonia. Understanding the origin, maintenance and loss of biodiversity has a profound importance for future human life. This thesis addresses some of the knowledge gaps on these topics, comparing methods of estimating richness and distribution of species of the Amazonian rainforest at different time scales. This study is an interdisciplinary research that relates aspects of different scientific areas to understanding the consequences of the two main threats to Amazonian biodiversity attributed to climate change and deforestation. The study was supported by a cooperation between the Naturalis Biodiversity Center – The Netherlands and Museu Paraense Emílio Goeldi – MPEG on a Sandwich Doctorate Scholarship – SWE (CNPq Prossess 203102/2015-0). Furthermore, the study is part of the INCT project Biodiversidade e Uso da Terra na Amazônia (Biodiversity and Land Use in Amazonia) (CNPq Prossess 574008/2008-0), coordinated by MPEG, which is dedicated to the study of biodiversity and Amazonian landscape, aiming to understand environmental and social consequences of different land uses, providing scientific bases for sustainable economic practices and support for public policies for Amazonia.
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