Processos ecológicos e evolutivos no surgimento e manutenção da diversidade biocultural

• Autor(a) principal: Coelho, Marco Túlio Pacheco
• Data de Publicação: 2020
• Tipo de documento: Tese
• Idioma: por
• Título da fonte: Repositório Institucional da UFG
• Texto Completo: http://repositorio.bc.ufg.br/tede/handle/tede/10446
• topic: Parcimônia; Teoria neutra; Gradientes de diversidade; Conservação de nicho; Macroecologia humana; Parsimony; Neutral theory; Diversity gradients; Niche conservatism; Human macroecology; CIENCIAS BIOLOGICAS::ECOLOGIA

current challenge in ecology and evolution is to understand the direct and indirect effects of ecological and evolutionary processes on the spatial structure of biodiversity. To overcome this challenge, ecologists and evolutionary biologists use two types of models: models that describe nature (i.e. correlative models) and models that explain nature (i.e. mechanistic models). Three knowledge gaps, involving the use of correlative and mechanistic models to investigate spatial patterns of biodiversity, are explored in my thesis: (i) heuristic criteria (i.e., a method lacking rational justification or theoretical basis, but accepted as good enough for a given purpose), inherited from the beginning of science, are used to judge the credibility of correlative and mechanistic models that are widely used to understand complex patterns of biodiversity. However, critical discussions about the validity of these criteria are rare in ecology and evolution; (ii) few mechanistic models assume the interaction of ecological and evolutionary processes at individuals’ level in broad spatial and temporal scales, when studying spatial patterns of species diversity; (iii) few studies explore the effect of ecological and evolutionary factors, using the methodological advances on the use of correlative and mechanistic models, to better understand human diversity patterns. All the three points presented earlier are explored in my thesis that is divided into three parts and six chapters. In the first chapter, I discussed the philosophical and statistical bases used to justify the use of simplicity when judging the credibility of theories, hypothesis and models in ecology and evolutionary biology. I showed that invoking the parsimony principle in ecology and evolution is particularly important in models that are used as operational tools to make predictions. In the second and third chapter, I built a mechanistic simulation model that assumes the absence of ecological niche but assumes the effect of energy on processes structuring biodiversity, such as speciation, extinction and dispersion. This model reproduced the richness pattern of terrestrial mammals in Australia (chapter 2) and latitudinal patterns of bird richness in different continents (chapter 3). By also using a mechanistic model, in the fourth chapter I tested the effect of biogeographical processes on climatic niche diversification though a model that purposely disregards the effect of any adaptive process on climactic niche evolution. This study showed the strong role of biogeographical processes on climatic niche evolution, even when no adaptative force is acting on climatic niche diversification. Finally, in the last two chapters, I explored aspects of human diversity drawing the attention of ecologists and evolutionary biologists to aspects of biodiversity that are seldom explored in ecology. In the fifth chapter, I revised aspects of human diversity that are similar to several patterns described in biogeography and macroecology, showing that ecologists and evolutionary biologists can contribute to long-standing debates in many fields of science, using their theoretical and methodological tools to study patterns of human diversity. Lastly, in the sixth chapter I used a combination of path analysis, mechanistic model and geographically weighted regression (GWR) to investigate the broadly described pattern of language diversity in North America. This study showed that the ecological predictors of language diversity are not perfectly universal nor entirely direct and that the predictive power of the model vary through space with regions where almost 86% of the variation in language diversity is explained, to regions where around 40% of variation is explained.