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Monitoring Spatial Segregation in Surface Colonizing Microbial Populations
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    Area of Science:

    • Ecology
    • Spatial Modeling
    • Population Dynamics

    Background:

    • Dynamic occupancy models are vital for understanding open populations with changing site occupancy over time due to colonization and extinction.
    • Existing models often overlook the influence of neighboring site occupancies on these dynamic processes.
    • Incorporating spatial dependencies is crucial for accurately modeling species distribution and spread.

    Purpose of the Study:

    • To develop a novel dynamic occupancy modeling framework that integrates spatial dependencies, specifically the influence of neighboring sites on colonization and extinction probabilities.
    • To create a flexible model capable of describing diverse spatiotemporal colonization and extinction processes based on simple, local rules.
    • To formally account for detectability within the occupancy modeling framework, enhancing its applicability.

    Main Methods:

    • Developed a dynamic, multi-season occupancy model framework that explicitly incorporates the occupancy status of neighboring sites.
    • Integrated environmental characteristics of sites and their neighbors to predict colonization likelihood.
    • Included a long-distance dispersal process to account for colonization of isolated sites.
    • Formally incorporated detectability, distinguishing it from similar epidemiological models.

    Main Results:

    • The new model successfully simulates complex large-scale occupancy patterns from simple small-scale rules.
    • Demonstrated the model's viability and potential through a simulation study.
    • Applied the model to the Common Myna invasion in South Africa, revealing its spread is primarily driven by short-distance movements.
    • Inference suggests the Common Myna is enlarging its distribution through localized spread rather than long-distance dispersal.

    Conclusions:

    • The developed dynamic occupancy model offers a powerful tool for analyzing colonization drivers, including dispersal modes, habitat quality, and proximity to source populations.
    • The framework provides valuable insights for wildlife management and conservation strategies, particularly for invasive species.
    • Understanding the interplay between local colonization rules and spatial factors is key to predicting and managing species distributions.