Investigation and integration of spatial analyses in benthic habitat mapping with application to nearshore Arctic environments

Misiuk, Benjamin (2019) Investigation and integration of spatial analyses in benthic habitat mapping with application to nearshore Arctic environments. Doctoral (PhD) thesis, Memorial University of Newfoundland.

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The field of benthic habitat mapping has entered an era of automated statistical methods that have increased the capacity to produce maps as marine management tools. Spurred by a confluence of advances in acoustic remote sensing, open-source statistical tools, GIS, and computing power, these methods facilitate quick and objective mapping of habitats and physical seabed characteristics. Their performance and accessibility have led to widespread uptake, yet key spatial issues associated with these methods have not fully translated into the benthic habitat mapping workflow. Towards establishing “best practices”, this thesis explores the application of several spatial concepts to benthic habitat mapping using three Canadian Arctic case studies. Relationships between seabed morphology and benthic habitats are well-established. Though recognized as a critical element in the field of geomorphometry, the scale dependence of these relationships is commonly neglected in habitat mapping. Chapter 2 provides evidence of the scale dependence of benthic terrain variables and demonstrates methods for testing and selecting from among many variables and scales for modelling the distribution of sediment grain size near Qikiqtarjuaq, Nunavut. Given challenges associated with marine data collection that are pronounced in the Arctic, benthic habitat maps commonly utilize multi-year and multisource datasets. Despite apparent advantages, there can be substantial challenges associated with the compatibility and spatial properties of such data. Chapter 3 demonstrates that spatially autocorrelated samples are likely to inflate estimates of predictive performance and uses a spatial resampling strategy to estimate and correct for inflation in a multi-model Arctic clam habitat map near Qikiqtarjuaq, Nunavut. Classified seabed maps are a common requirement for marine management and one of two broad approaches are often selected to produce them. Chapter 4 examines differences between classification and continuous modelling approaches in a spatial context to produce classified seabed sediment maps for inner Frobisher Bay, Nunavut. Non-spatial methods failed to indicate whether models could extrapolate to unsampled areas, which was a requirement for this study. When evaluated in a spatial context, the qualities of the classification approach made it more suitable, which was a function of ground-truth dataset characteristics and the predictive goals of the model. Non-spatial techniques may be appropriate for interpolation, but the ability to extrapolate needs to be examined in a spatial context.

Item Type: Thesis (Doctoral (PhD))
Item ID: 13944
Additional Information: Includes bibliographical references.
Keywords: Benthic habitat mapping, Species distribution modelling, Spatial autocorrelation, Multiscale, Boosted Regression Trees, Random Forest, Arctic
Department(s): Humanities and Social Sciences, Faculty of > Geography
Date: October 2019
Date Type: Submission
Library of Congress Subject Heading: Submarine topography; Benthos--Habitat--Remote sensing

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