Date of Award

8-2021

Document Type

Open Access Thesis

Degree Name

Master of Science (MS)

Department

Marine Sciences and Technology

First Advisor

Mark Borrelli

Second Advisor

Eugene Gallagher

Third Advisor

Agnes Mittermayr

Abstract

One of the first steps of ecosystem-based management should be to classify and map habitats. The Coastal and Marine Ecological Classification Standard (CMECS) was adopted by the federal government to standardize habitat classification in coastal U.S. waters. CMECS provides a hierarchal framework to define and interpret benthic habitats and biotopes but does not prescribe specific sampling methods to adopt. Imagery techniques have been utilized for many decades in benthic ecology but have rarely been employed in habitat classification using CMECS. Furthermore, no study to date has quantitatively examined the benefit of incorporating benthic imagery into the classification of biotopes using CMECS. The objective of this study is to describe the study site, a roughly 1 km2 near-shore, subtidal area at Herring Cove in Provincetown, MA, with CMECS, and to quantify the benefit of augmenting benthic habitat classification with low-cost imagery. A benthic habitat survey of the study area in October 2017 included grab sampling for grain-size analysis and invertebrate taxonomy, benthic imagery, and water quality sampling at 24 sampling stations, as well as acoustic mapping of the study area. Multivariate statistical analyses were conducted to classify biotic communities and link environmental and biological data to classify biotopes. Results showed that benthic imagery improved the accuracy of the Substrate Component classification by providing information on coarse gravel substrates that is lost using traditional grain-size analysis. Benthic imagery improved the resolution of the Biotic Component classification by providing information on benthic macroalgal communities and ecological context for the classification of epifaunal communities. Percent cover of submerged aquatic vegetation (collected using benthic imagery) explained the most variation in benthic invertebrate community structure and improved the accuracy and ecological relevance of the classification of biotopes. Furthermore, benthic imagery provided insights to environmental gradients, associated with biotope structure, that would have not been evident otherwise. These findings imply that the incorporation of low-cost benthic imagery is warranted in coastal benthic biotope classification and mapping studies and should be regularly adopted. This study has implications for coastal benthic ecologists classifying benthic habitats within the CMECS framework.

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