Date of Award
2021
Degree Type
Thesis
Degree Name
Master of Science in Oceanography
Specialization
Biological Oceanography
Department
Oceanography
First Advisor
Jeremy Collie
Abstract
Food web models capture shifting species interactions, making them useful tools for exploring community responses to perturbations. The inclusion of environmental drivers, such as temperature, can improve model predictions as energy demands of an organism can be temperature-specific. While Ecopath with Ecosim (EwE) and the recent R implementation of this software, Rpath, have included some thermal responses in past work, models have yet to include temperature-dependent energetic demands and metabolic costs. Our work demonstrates the inclusion of temperature-dependent bioenergetics into an Rpath food web model using the case study of a warming estuary: Narragansett Bay (RI, U.S.). Thermal response parameters from literature were used to construct Kitchell curves describing temperature-dependent consumption and modified Arrhenius curves describing temperature-dependent respiration. Surface water temperature time series from 1994 to 2054 for high and low warming scenarios were created from observed temperatures and projections from the Coupled Model Intercomparison Project (CMIP6) multi-model ensemble. The integration of temperature-dependent fish bioenergetics resulted in lower projected biomasses compared to the base version of the model without environmental forcing, reflecting the impact of increased energetic demands. The differences in the model-predicted biomasses highlight the importance of accounting for thermal effects on marine species in ecosystem models, which will become increasingly important as ocean temperatures continue to rise in Narragansett Bay and worldwide.
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.
Recommended Citation
Heinichen, Margaret A., "INCORPORATING TEMPERATURE-DEPENDENT FISH BIOENERGETICS INTO A NARRAGANSETT BAY FOOD WEB MODEL" (2021). Open Access Master's Theses. Paper 1934.
https://digitalcommons.uri.edu/theses/1934