Modelling Multiscale Relationships in Riverine Landscapes: Putting the "Riverscape" into Statistical Models for River Ecology and Management
Author(s)
Primary Supervisor
Sheldon, Fran
Kennard, Mark
Other Supervisors
Bunn, Stuart
Year published
2011
Metadata
Show full item recordAbstract
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’ ...
View more >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.
View less >
View more >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.
View less >
Thesis Type
Thesis (PhD Doctorate)
Degree Program
Doctor of Philosophy (PhD)
School
Griffith School of Environment
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