Date of Award

5-2006

Level of Access

Campus-Only Thesis

Degree Name

Master of Science (MS)

Department

Marine Biology

Advisor

Yong Chen

Second Committee Member

James A. Wilson

Third Committee Member

James McCleave

Abstract

The green sea urchin (Strongylocentrotus droebachiensis) fishery has been an important commercial fishery in Maine since its inception in the late-1980s. Sea urchin landings peaked in 1993 and have been declining for the past 12 years. Management of the sea urchin fishery has been largely unsuccessful at conserving the stock and ensuring a sustainable fishery. Landings are at an all-time low, fishermen have been forced to quit fishing because the industry is no longer profitable, and market infrastructure is disappearing.

This document discusses the spatial dynamics of the urchin population and ecological drivers. Biomass- and abundance-based indices were developed to examine the spatial dynamics of the urchin population. Sea urchin size structure and abundance vary regionally and with depth. Ecological interactions among sea urchins, algae, and crabs help to describe the pattern of distribution and abundance.

Sea urchins aggregate to facilitate certain critical life history processes. For example, fertilization success depends on the proximity of other urchins. As a result, sea urchin density must be maintained at a local scale in order to protect the sea urchin population as a whole. Current management does not protect the small-scale dynamics in the urchin population. Acknowledging small-scale variation in urchin abundance and recognizing the importance of maintaining localized aggregations would improve sea urchin assessment and management.

Recognizing the importance of spatial scale in life history processes and fishery practices, I propose using two different approaches to assess the sea urchin stock: (1) a length-based population dynamics model developed in by Chen and Hunter (2003) and later modified by Kanaiwa et al. (2005) for assessing sea urchin on a large scale (coast wide); and (2) a spatial statistics model developed by Grabowski et al. (2003) for assessing the sea urchin stock on a fine spatial scale. I compared the two approaches based on input data, methodologies, output data, and assumptions. I evaluated output generated by each model while considering the relevance of each to different spatial scales. Both models can play a distinct role in the assessment and management of the fishery.

In this document I provide evidence to show that the scale of biological processes important to sea urchin life history and the scale of management are mis-aligned. In addition, resource users' and managers' perceptions of the urchin fishery are at odds as well. Each of these mis-matches may be substantially mitigated through recognition of the importance of small-scale dynamics in the sea urchin population. The current management regime has enacted laws and regulations that successfully address largescale processes. In addition to coast-wide regulations, smaller management zones or governance units could be created to match spatial scales of biological process and management more easily. Whether it be smaller management zones some other strategy, a successful urchin management regime will create an arena that will facilitate changes in fishermen's incentives as well as address the preservation of small-scale urchin density.

Comments

Master of Science (in Marine Policy)

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