Mathematical models for ecological and evolutionary processes in biological invasion

Detalhes bibliográficos
Ano de defesa: 2023
Autor(a) principal: Lyra, Silas Poloni
Orientador(a): Não Informado pela instituição
Banca de defesa: Não Informado pela instituição
Tipo de documento: Tese
Tipo de acesso: Acesso aberto
Idioma: eng
Instituição de defesa: Universidade Estadual Paulista (Unesp)
Programa de Pós-Graduação: Não Informado pela instituição
Departamento: Não Informado pela instituição
País: Não Informado pela instituição
Palavras-chave em Português:
Link de acesso: https://hdl.handle.net/11449/251973
Resumo: Biological invasions are ubiquitous in the Anthropocene. With many factors in- fluencing how alien species spread into novel territory and large spatio-temporal scales often make experiments much more complicated. This way, theoretical quantitative approaches become a useful tool into understanding such factors and estimating spreading speeds and regime shifts caused by invading populations. In this thesis we review classical mathematical models for biological invasions in the form of reaction diffusion equations and integro-difference equations. Then, build- ing upon reaction diffusion equations theory, we formulate models for consumer population invasions leading to intraguild predation interaction networks with resident species in both homogeneous and heterogeneous landscapes. We show speeds are linearly determinate, and that competitive reversals among intraguild prey and predator might occur in heterogenous landscapes, leading to unnex- pected coexistence and exclusion regimes. Moving on, we also develop models for evolutionary processes in biological invasions, that have been show to take place in ecological timescale and significantly change spread phenomena. We show that discrete time recursions for trait structured populations can also exhibit traveling wave solutions and linearly determinate speeds, and determine the leading edge trait distributions for different growth-dispersal trade-offs and mutation rates. Finally, we outline some perspectives and conclusions of our work.