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Simulation of allopatric speciation processes associated with island ecosystems through Agent-based Modeling (ABM)

Grant number: 23/16496-7
Support Opportunities:Scholarships in Brazil - Scientific Initiation
Effective date (Start): April 01, 2024
Effective date (End): March 31, 2025
Field of knowledge:Biological Sciences - Ecology - Theoretical Ecology
Principal Investigator:Sérgio Henrique Vannucchi Leme de Mattos
Grantee:Rafael Roefero Marques da Silva
Host Institution: Centro de Ciências Biológicas e da Saúde (CCBS). Universidade Federal de São Carlos (UFSCAR). São Carlos , SP, Brazil

Abstract

Island ecosystems play an essential role in the dynamics of biodiversity given their isolation from the matrix in which they are found, which usually acts as a geographical barrier for many of the beings that inhabit them. This often causes genetic isolation of these populations in relation to other populations of the same species in the surroundings, which may cause a process of allopatric speciation by vicariance. Currently, phenomena such as global warming, rising sea levels and deforestation are responsible for generating landscape patches isolated from their matrix. The emergence of these "islands" in landscape reduces or even eliminates gene flow, affecting biodiversity conservation in various ecosystems around the globe. Facing that reality, this project proposes to develop an Agent Based Model (ABM) whose objective is to simulate processes of allopatric speciation in varying degrees of reduction or even loss of gene flow in order to understand the dynamics of a natural system in which the fragmentation of the environment is present. Parameters established for analysis and evaluation of results will be mainly applied to ecological dynamics of simulated landscapes and to genetic evolution of their populations, as well as for the way they occupy the fragmented space. For this, R statistical packages and CompPlex toolbox will be used, which allows the evaluation of the spatial and temporal complexity of the systems from measures based on informational entropy. Thus, it is expected to contribute both to the study of the future of biodiversity conservation, better understanding the consequences of habitat fragmentation, and to the study of evolutionary biology in island ecosystems.

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