Phylogenetic and phylogeographic approaches have become widespread in evolutionary biology, ecology, and biogeography. However, analyses that incorporate inferences from historical biogeography (e.g. timing of colonization of a region) may be essential to answer the most important large-scale questions in these fields, but they remain infrequently used. I focus on two examples here. First, I ar...

Biogeography-based optimization (BBO) is an evolutionary algorithm (EA) based upon the models of biogeography, which describe the relationship between habitat suitability and the migration of species across habitats. In this work, we apply BBO to the problem of tuning the fuzzy tracking controller of mobile robots. This is an extension of previous work, in which we used BBO to tune a proportion...

Biogeography-based optimization (BBO) is a relatively new bioinspired heuristic for global optimization based on the mathematical models of biogeography. By investigating the applicability and performance of BBO for integer programming, we find that the original BBO algorithm does not perform well on a set of benchmark integer programming problems. Thus we modify the mutation operator and/or th...

Conservation Biogeography and Macroecology Programme, School of Geography and the Environment, University of Oxford, Oxford OX1 3QY, UK, Departamento de Cîencias Agr arias – CITAA, Azorean Biodiversity Group, Universidade dos Ac ores, Angra do Hero ısmo, Pico da Urze, 9700-042 Terceira, Ac ores, Portugal, Department of Biogeography, BayCEER, University of Bayreuth, Bayreuth D-95447, Germany, De...

Biogeography based optimization (BBO) is a type of evolutionary algorithm. It is a population based optimization algorithm and provides clarification about the changing distribution of all species in different environment with time. Color quantization is the process of reducing the number of colors in the image and preserving the most important color information and compromise with other. A col...

Island Ecology and Biogeography Research Group. Instituto Universitario de Enfermedades Tropicales y Salud Pública de Canarias (IUETSPC), Universidad de La Laguna, Tenerife, Canary Islands 38206, Spain, Conservation Biogeography and Macroecology Group, School of Geography and the Environment, South Parks Road, Oxford OX1 3QY, UK, Computation GeoEcology Group, Institute for Biodiversity and Ecos...

The interest of hybridizing different nature inspired algorithms has been growing in recent years. As a relatively new algorithm in this field, Biogeography Based Optimization(BBO) shows great potential in solving numerical optimization problems and some practical problems like TSP. In this paper, we proposed an algorithm which combines Biogeography Based Optimization (BBO) and Clonal Selection...

Modern biogeography now encompasses an impressive diversity of patterns and phenomena of the geography of nature, providing insights fundamental to understanding the forces influencing the spatial and temporal dynamics of biological diversity. However, rather than praise our discipline for its great breadth of visions, our purpose here is to point out our glaring oversight of a potentially tran...

EDITORIAL article Front. Ecol. Evol., 31 March 2021Sec. Biogeography and Macroecology https://doi.org/10.3389/fevo.2021.670212

One of the central aims of modern historical biogeography is to reconstruct the history of a particular taxon or a group of taxa based on phylogenetic hypotheses (Cox & Moore, 2005; Lomolino et al., 2006). The advent of molecular datasets and improved analytical methods in phylogenetics has led to a proliferation of phylogenetic studies in the last two decades. Historical biogeography has been ...