Integration of High-Resolution Multibeam Sonar Imagery with Observational Data from Submersibles to Classify and Map Benthic Habitats at Heceta Bank, Oregon

Master of Science, Marine Resource Management, Oregon State University, Winter 2003
Double-Minor in Earth Science Information & Technology and Fisheries and Wildlife

Graduate committee: D. Wright, R.W. Embley (co-adviser, NOAA PMEL), A.J. Kimerling, Selina Heppell, W. Wakefield (NOAA NMFS), P. Bottomley

Curt Whitmire
College of Oceanic & Atmospheric Sciences, Oregon State Univ
Corvallis, OR 97331
curt.whitmire-at-noaa.gov

Abstract.
With the evolution of fishery science, methods for assessing fish stocks have greatly improved through the development of enhanced sampling equipment and techniques. Despite these improvements, the fishing industry and related management entities often criticize current methods for not yielding accurate and precise estimates of biomass. Earlier studies at Heceta Bank, Oregon using the Delta submersible have provided statistical evidence that certain species of demersal fishes (groundfish) associate with varying seafloor substratum classes (Pearcy et al. 1989, Hixon et al. 1991, Stein et al. 1992). One possible alternative to traditional trawl survey methods involves using the knowledge of important fish-habitat associations to inform a model design for habitat-based community assessments.

One important preliminary step in performing such habitat-based assessments is to classify seafloor substrata. The integration of high-resolution multibeam sonar imagery and habitat characteristics observed from submersibles enabled the classification of benthic habitats at Heceta Bank - a shallow, rocky shoal off the central Oregon coast. This habitat classification is based on the premise that distinct habitat characteristics can be described by a series of quantitative map parameters derived from bathymetric and textural imagery of the seafloor. Using a combination of previously developed (Nasby et al. 2002) and new GIS methods, imagery that predicts the locations of meaningful groundfish habitats on Heceta Bank was created.

This classification will provide a context to support improved abundance estimates of various stocks of groundfish on a scale applicable to regional stock assessments. Furthermore, future integration of other parameters of ecological importance will produce a more comprehensive classification of habitats to facilitate spatial analyses of a variety of pertinent data and more specifically map essential fish habitat.

This thesis builds on the 2000 thesis of Nicole Nasby Lucas

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