Date of Award

Summer 8-2017

Degree Type

Masters Thesis

Degree Name

Master of Science (MS)


Ocean Science and Technology

Committee Chair

Eric N. Powell

Committee Chair Department

Ocean Science and Technology

Committee Member 2

Roger Mann

Committee Member 3

Chet F. Rakocinski

Committee Member 3 Department

Ocean Science and Technology

Committee Member 4

James S. Franks

Committee Member 4 Department

Ocean Science and Technology


Ocean quahogs (Arctica islandica) are the longest-lived, non-colonial animals known today, with a maximum life span exceeding 500 years. Limited information is available regarding recruitment, making the sustainable management of this valuable fishery a challenge. The objective of this research was to describe the age structure and growth rates for four populations of ocean quahogs from the mid-Atlantic stock to evaluate long-term recruitment trends. Clams were sectioned for age estimation to develop population age frequencies. Initial colonization began approximately 175-250 years ago depending upon site. All sites experienced an increase in recruitment beginning in the late 1800’s to early 1900’s, after which the populations reached and remained at carrying capacity, characterized by more or less continuous low-level recruitment. Growth rates for select individuals from the Georges Bank site were evaluated using three growth models. The ALOG model was more suitable because it allows for early, rapid growth and for persistent indeterminate growth into old age. Growth rates for clams from all sites were analyzed to investigate both geographical and temporal differences. A substantive increase in the age at which animals reach 60, 80, and 90 mm has occurred, as well as an increase in average growth rates to 60, 80, 90, and post-90 mm, at the two sites in the southern portion of the stock since initial colonization, likely in response to increasing bottom water temperatures since the end of the Little Ice Age. These results have important implications for fishery management and will be used to inform management decisions.