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  • Modelling Multiscale Relationships in Riverine Landscapes: Putting the "Riverscape" into Statistical Models for River Ecology and Management

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    Stewart-Koster_2011_02Thesis.pdf (2.317Mb)
    Author(s)
    Stewart-Koster, Ben D.
    Primary Supervisor
    Sheldon, Fran
    Kennard, Mark
    Other Supervisors
    Bunn, Stuart
    Year published
    2011
    Metadata
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    Abstract
    Many questions in ecology involve exploring the environmental processes that influence species’ distributions and abundances in both space and time. Such environmental processes are rarely independent, and generally operate across many scales. This is particularly relevant to riverine systems, where the nested hierarchical structure of the riverscape means fine-scale processes are strongly influenced by processes operating across larger scales. Recent research has identified some key advantages in applying Bayesian hierarchical models to hierarchical ecological problems such as identifying relationships between species’ ...
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    Many questions in ecology involve exploring the environmental processes that influence species’ distributions and abundances in both space and time. Such environmental processes are rarely independent, and generally operate across many scales. This is particularly relevant to riverine systems, where the nested hierarchical structure of the riverscape means fine-scale processes are strongly influenced by processes operating across larger scales. Recent research has identified some key advantages in applying Bayesian hierarchical models to hierarchical ecological problems such as identifying relationships between species’ abundances and environmental predictor variables across multiple scales. This thesis focuses on applying Bayesian hierarchical models to multiscale datasets for freshwater fishes and aquatic macrophyte cover in South-East Queensland, Australia, to address two key aspects of applied river ecology and management. Firstly, it examines multiscale species-environment relationships for freshwater fishes. This involves developing Bayesian hierarchical models that reflect the structure of a conceptual model of fish species’ distribution and abundance. Secondly, this thesis examines methods to integrate such multiscale relationships into models for river management and restoration using Bayesian networks with an emphasis on the management of aquatic macrophytes (BNs). Novel statistical methods such as Bayesian hierarchical models and BNs have the potential to advance our understanding of multiscale abiotic drivers of ecosystem structure and function across the riverscape.
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    Thesis Type
    Thesis (PhD Doctorate)
    Degree Program
    Doctor of Philosophy (PhD)
    School
    Griffith School of Environment
    DOI
    https://doi.org/10.25904/1912/2951
    Copyright Statement
    The author owns the copyright in this thesis, unless stated otherwise.
    Item Access Status
    Public
    Note
    The 2 papers included in the Appendix are not published here.
    Subject
    Riverine systems
    Mary River, South east Queensland
    Freshwater fishes
    Publication URI
    http://hdl.handle.net/10072/367114
    Collection
    • Theses - Higher Degree by Research

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