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• W2950120599 abstract "Abstract In recent years sympatry networks have been proposed as a mean to perform biogeographic analysis, but their computation posed practical difficulties that limited their use. We propose a novel approach, bringing closer the application of well-established network analysis tools to the study of sympatry patterns using both geographic and environmental data associated with the occurrence of species. Our proposed algorithm, SG ra F u L o , combines the use of fuzzy logic and numerical methods to directly compute the network of interest from point locality records, without the need of specialized tools, such as geographic information systems, thereby simplifying the process for end users. By posing the problem in matrix terms, SG ra F u L o is able to achieve remarkable efficiency even for large datasets, taking advantage of well established scientific computing algorithms. We present sympatry networks constructed using real-world data collected in Mexico and Central America and highlight the potential of our approach in the analysis of overlapping niches of species that could have important applications even in evolutionary studies. We also present details on the design and implementation of the algorithm, as well as experiments that show its efficiency. The source code is freely released and datasets are also available to support the reproducibility of our results." @default.
• W2950120599 created "2019-06-27" @default.
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• W2950120599 date "2019-09-01" @default.
• W2950120599 modified "2023-10-02" @default.
• W2950120599 title "An application of fuzzy logic to build ecological sympatry networks" @default.
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• W2950120599 doi "https://doi.org/10.1016/j.ecoinf.2019.100978" @default.
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