Modeling Life History and Population Dynamics of American Lobster and Atlantic Sea Scallops in a Warming Gulf of Maine

Climate change is impacting many marine species distributions, life histories, and behaviors, as well as their associated fisheries and overall production. This is perhaps especially true for the Gulf of Maine (GOM). Here, warming rates are exceeding a vast majority of the world’s oceans. This highly dynamic system supports myriad species, but is both economically recognized and culturally known for its Atlantic sea scallop (Placopecten magellanicus) and American lobster (Homarus americanus) fisheries. This dissertation examines the influence of regional climate change on these species in an effort to predict how these stocks and their fisheries may change in the future. For scallops, this was accomplished by examining and aging shells collected throughout the GOM to determine if spatial and temporal differences in growth patterns could be explained by regional thermal habitats and salinities. For lobster, a five-step process was developed. Firstly, I conducted a simulation study to evaluate the stock assessment model performance under possible changes in lobster molting probability, lobster molt increment size, and size-at-maturity as a result of changes in thermal habitat. Secondly, using two temperature covariates important for early survival and development, a stock-wide, thermally-explicit Beverton-Holt stock-recruit relationship was estimated for the GOM. This relationship served as the basis of a framework to be used by management to test what levels of spawning biomass are necessary in the current year to achieve the desired levels of recruitment in the near future. Thirdly, a delta-generalized linear mixed model was used to predict lobster spatial density throughout the GOM. This spatial density informed a stock-wide abundance index which was used to replace the traditionally used design-based indices in the stock assessment model. Fourthly, a stock forecasting model was developed that could utilize the aforementioned stock-recruit relationship and consequences of ignoring this thermal influence on recruitment estimations were explored. Lastly, a bioclimate envelope model was used to determine relationships of multiple habitat covariates to lobster abundance from trawl survey data before using these relationships to map and forecast lobster habitat in the GOM

A framework to incorporate environmental effects into stock assessments informed by fishery-independent surveys: a case study with American lobster (Homarus americanus)

Stock assessments for a majority of the world’s fisheries often do not explicitly consider the effects of environmental conditions on target species, which can raise model uncertainty and potentially reduce forecasting quality. Model-based abundance indices were developed using a delta generalized linear mixed model that incorporates environmental variability for use in stock assessment to understand how the incorporation of environmental variability impacts our understanding of population dynamics. For this study, multiple model-based abundance indices were developed to test the incorporation of environmental covariates in a length-structured assessment of the American lobster (Homarus americanus) stock in the Gulf of Maine – Georges Bank on the possible improvement of stock assessment quality. Comparisons reveal that modelled indices with environmental covariates appear to be more precise than traditional indices, but model performance metrics and hindcasted fishery statuses revealed that these improvements to indices may not necessarily mean an improved assessment. Model-based abundance indices are not intrinsically better than design-based indices and should be tested for each species individually.The accepted manuscript in pdf format is listed with the files at the bottom of this page. The presentation of the authors' names and (or) special characters in the title of the manuscript may differ slightly between what is listed on this page and what is listed in the pdf file of the accepted manuscript; that in the pdf file of the accepted manuscript is what was submitted by the author