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Using codispersion analysis to characterize spatial patterns in species co-occurrences.

Hannah L Buckley, Bradley S Case, Aaron M Ellison

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    Codispersion analysis reveals spatial patterns in species co-occurrence, detecting aggregation and segregation. This method helps ecologists understand complex ecological processes and spatial scales.

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    Area of Science:

    • Ecology
    • Spatial Statistics

    Background:

    • Species co-occurrence patterns provide insights into ecological processes and spatial scales.
    • Traditional statistical models often assume isotropic and stationary spatial processes, which may not reflect ecological reality.
    • Anisotropic and non-stationary spatial processes are common in ecological systems.

    Purpose of the Study:

    • Introduce codispersion analysis as a novel tool for ecologists.
    • Detect and quantify anisotropic and non-stationary spatial patterns in bivariate co-occurrence data.
    • Determine the relevant spatial scales of these co-occurrence patterns.

    Main Methods:

    • Developed and applied codispersion analysis to ecological data.
    • Utilized simulated data to validate the accuracy of codispersion analysis in characterizing complex spatial patterns.
    • Analyzed co-occurrence patterns of common tree species in a 35-hectare plot.
    • Compared observed co-occurrence patterns with those generated by two different null models.

    Main Results:

    • Codispersion analysis accurately characterized complex spatial patterns in simulated data.
    • Identified both positive (aggregation) and negative (segregation) codispersion between different tree species.
    • Demonstrated that the codispersion of most species pairs significantly deviated from random expectations.
    • Revealed the presence of anisotropic and non-stationary spatial patterns in tree species co-occurrence.

    Conclusions:

    • Codispersion analysis is a valuable exploratory tool for ecologists.
    • The method effectively detects and quantifies anisotropic and non-stationary spatial patterns.
    • Findings guide ecologists in modeling complex spatial processes structuring species assemblages.
    • Highlights the importance of considering non-stationary and anisotropic processes in ecological studies.