Department of Fisheries Oceanography

“The Spawning Dynamics and Biology of Cod in Southern New England Offshore Wind Energy Areas”

By:

Alison Frey

Advisor

Steven X. Cadrin (UMass Dartmouth)

Committee Members

Kevin Stokesbury (UMass Dartmouth), Lauran Brewster (UMass Dartmouth), and Greg DeCelles (Ørsted)

Thursday June 5, 2025

1:00 PM

SMAST East 101-103

836 S. Rodney French Blvd, New Bedford

and via Zoom

Abstract:

Atlantic cod (Gadus morhua) supported a robust fishery through most of the 20th century, but due to overfishing and environmental change, stocks collapsed in the 1990s, and populations remain below target biomass levels. Successful spawning and recruitment are critical for stock rebuilding, but spawning is a sensitive period within the lifecycle of cod and is vulnerable to anthropogenic activities. The most southern cod stock off Southern New England is currently assessed to be overfished with overfishing occurring. Offshore wind energy development is occurring on a known spawning ground, Cox Ledge, which is designated as Essential Fish Habitat and a Habitat Area of Particular Concern, and may have impacts on cod reproduction. To characterize impacts of offshore wind development on spawning of Southern New England cod, data on habitat use and spawning dynamics were collected via acoustic telemetry to compare pre-construction and post-construction residency to the spawning ground (chapter 1). Environmental drivers of cod presence on Cox Ledge will be assessed with generalized linear models (chapter 2), and biological sampling will be used to estimate size at maturity to inform the data-moderate Southern New England stock assessment (chapter 3). This proposed work will aid in effective assessment and management of fisheries and offshore wind interactions with vulnerable living marine resources.

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Join Zoom Meeting

Topic: Ali Frey Thesis Defense

Time: Jun 5, 2025 12:00 Eastern Time (US and Canada)

Join Zoom Meeting

https://umassd.zoom.us/j/94363529761

Meeting ID: 943 6352 9761

Passcode: 595695

Department of Fisheries Oceanography

“Impacts to stock abundance indices due to offshore wind development-driven changes to fishery-independent survey effort”

By:

Angelia Miller

Advisor

Dr. Gavin Fay (University of Massachusetts Dartmouth)

Committee Members

Dr. Steven X. Cadrin (University of Massachusetts Dartmouth), and Dr. Catherine Foley (NOAA NEFSC)

Tuesday May 20th, 2025

1:30 PM

SMAST East 101-103

836 S. Rodney French Blvd, New Bedford

and via Zoom

Abstract:

Offshore wind energy development is occurring throughout the Northeast Large Marine Ecosystem and will interact with many marine use sectors, including fisheries. Wind areas overlap spatially with the footprint of the National Marine Fisheries Service (NMFS) Northeast Fisheries Science Center (NEFSC) multispecies bottom trawl survey, which has been conducted since the 1960s, and whose data are relied upon for the assessment and management of many fisheries stocks in the Northeast U.S. This fishery-independent survey is confronted by potential preclusion of trawl sampling efforts due to the spatial conflict arising from offshore wind energy development. My thesis aims to quantify the impacts of preclusion to monitoring and operations and understand changes to species distributions and abundances within wind areas, which could jointly affect downstream data products, such as stock abundance indices, and fisheries management advice. The first phase of my study serves as a proxy for expected losses for comparison to my species distribution modeling and suggests that, when accounting for reduced trawl samples, annual estimates of relative abundance are lower than those calculated when including all samples. Additionally, when compared to a random, null model of effort reduction, preclusion of wind areas resulted in lower abundance estimates. Applying summer flounder (Paralichthys dentatus) and Atlantic mackerel (Scomber scombrus) as two case study species, I fit a spatiotemporal generalized linear mixed effects model (GLMM), generate simulated survey data, and calculate indices of abundance and population trends to compare survey outcomes with and without trawl samples inside proposed wind development areas in the second phase of my study. I employed the species distribution operating model to examine changes in fish density under assumed changes in species productivity, and to survey catch rates, as a function of offshore wind development. I found that the loss of samples inside wind areas has a substantial impact on estimates of abundance indices and population trends. This study contributes directly to implementation of the Federal Survey Mitigation Strategy for the Northeast U.S. Region (Action 3.2.2) as a part of the Survey Simulation Evaluation and Experimentation Project, which aims to assess potential impacts to the bottom trawl survey operations and data products and identify mitigation strategies to maintain data integrity. Furthermore, this study contributes to the current knowledge surrounding the impacts that offshore wind energy development can have on fishery-independent surveys, which globally is scarce.

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https://umassd.zoom.us/j/92249874120

Meeting ID: 922 4987 4120

Passcode: 747985

Department of Fisheries Oceanography

“LOOK BUT DON’T TOUCH: MINIMALLY INVASIVE TRAWL SURVEY TECHNOLOGY”

By:

Nicholas M. Calabrese

Advisor

Kevin Stokesbury (UMass Dartmouth)

Committee Members

Steven X. Cadrin (UMass Dartmouth), Pingguo He (UMass Dartmouth), Michael J.W. Stokesbury (Acadia University), and Anna Mercer (NOAA Federal)

Wednesday May 28th, 2025

1:00 PM

SMAST East 101-103

836 S. Rodney French Blvd, New Bedford

and via Zoom

Abstract:

The School for Marine Science and Technology (SMAST) video trawl survey employs cameras mounted in the open codend of a trawl to identify and numerate groundfish. This minimally invasive survey technology has been used for semi-annual surveys of Atlantic Cod (Gadus morhua) in the Western Gulf of Maine since 2020. Accurate estimates of absolute abundance from the video trawl survey required estimates of catchability, efficiency, and fish length. This project aimed to address these requirements through three experiments and evaluate sampling methodology in a fourth experiment. First, a passive integrated transponder (PIT) tag detection system was developed, tested, and installed in the codend of the net. The custom-designed PIT tag detection system achieved an efficiency of 79%, with detection rates influenced by tag orientation and group size. Then, a mark-recapture experiment to estimate the efficiency and catchability of Atlantic cod was conducted using this system. A Petersen mark-recapture model, based on 1,094 tagged fish and six recaptures, accounting for both discard mortality and reader efficiency, yielded a doorspread efficiency of 12% and a catchability coefficient of 0.0024 per hour of towing. Next, the accuracy of length measurements derived from an off-the-shelf stereoscopic camera mounted within the trawl was assessed. This camera produced inaccurate length measurements, however, these findings helped inform the design of a custom imaging system. Finally, optical data from the survey were used to evaluate the effects of sampling design, tow duration, and sampling intensity on the variance of population estimates through a novel analytical approach. Stratified random sampling produced more precise biomass estimates than simple random sampling. In addition, CPUE mean, and variance increased with shorter tow durations. A 30-minute tow duration minimized within-tow variability and yielded the most precise abundance estimates, although this analysis lacked factors such as fish size and logistical constraints. Collectively, this research advances fisheries-independent survey methodology by addressing key limitations of new approaches.

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https://umassd.zoom.us/j/92695694559

Meeting ID: 926 9569 4559

Passcode: 106409

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For additional information, please contact Callie Rumbut at c.rumbut@umassd.edu

DFO Doctoral Dissertation Defense by Benjamin Galuardi

Date:                 Monday, April 28, 2025

Time:                 1:00 p.m.

Topic:                Estimating Population-Level Movement Rates of Large Pelagic Species from Electronic Tag Information

Location:          SMAST East, Rooms 101-103

Zoom Link:     https://umassd.zoom.us/j/93461632396

Meeting ID: 934 6163 2396

Passcode: 351775

Abstract:

Spatial structure and movement have important implications for stock assessment of highly migratory species and management of fisheries that target them. Telemetry data from electronic tags (E-tags) are valuable for determining habitat utilization and behavior and offer a unique path to providing fishery-independent information on movement rates. The bridge between individual E-tag deployments and population level inference can be summarized through Markovian movement matrices, stratified in space and time (e.g., seasons). To properly apply E-tag information to populations, a thorough understanding of the limitations of the technologies and the methods by which information is derived is necessary. Chapter 1 provides a review of E-tag types and geolocation techniques for estimated location and location error. A practical integration of geolocation models and population level inference is presented in Chapter 2 as a package for the R statistical software, SatTagSim. The methods draw from an advection-diffusion framework to produce simulations based on E-tag geolocation estimates and error structures. The products and methods in Chapter 2 are applied to a large E-tag dataset for Atlantic bluefin tuna (Thunnus thynnus) in Chapter 3. Tagging data from both the eastern and western Atlantic are used to generate seasonal movement matrices. These matrices are designed to be used in a variety of spatially explicit operational and stock assessment models and management strategy evaluations. Results suggest that estimates of movement rates were more reliable for simpler movement patterns (e.g., movement among fewer areas). Deriving movement estimates from E-tag data can benefit spatially explicit stock assessments and operating models for simulation testing by providing movement estimates that are independent of fishing patterns and can be beneficial in the estimation process of spatially explicit stock assessments and management strategy evaluations. This dissertation provides tools, readily available results for future assessments, and general guidelines on the trade-off between data availability and spatial inference.

ADVISOR(S):                                Dr. Steven X. Cadrin, UMass Dartmouth

                                           (scadrin@umassd.edu )

COMMITTEE MEMBERS:          Geoffrey Cowles, UMass Dartmouth

                                                          Gavin Fay, UMass Dartmouth
Molly Lutcavage, UMass Boston

                                                          Timothy Miller (NEFSC)

NOTE:                All SMAST Students are ENCOURAGED to attend.

Department of Fisheries Oceanography

“Environmental Effects on Population Dynamics of New England Yellowtail Flounder”

By: Jessica Kittel

Advisor: Steven X. Cadrin

Committee Members: Kevin Stokesbury (UMass Dartmouth), Gavin Fay (UMass Dartmouth), Lisa Kerr (U Maine), Alex Hansell (NEFSC)

Monday April 7th, 2025

2:00 PM

SMAST East 101-103

836 S. Rodney French Blvd, New Bedford

and via Zoom

Abstract:

Yellowtail flounder, Limanda ferruginea (a.k.a., Pleuronectes ferruginea, Myzopsetta ferruginea), inhabit the continental shelf of the northwest Atlantic and historically supported target fisheries off New England. However, the Georges Bank and Southern New England/ Mid-Atlantic stocks have declined in recent decades and have not recovered despite severely restricted fisheries, suggesting that productivity may be negatively affected by climate change. Ocean waters off New England are warming four times faster than the global average, and decreased yellowtail flounder productivity has been associated with ocean warming in the region. US stock assessments of yellowtail flounder have exhibited retrospective patterns, in which contemporary estimates of abundance decrease when a new year of data is added, presenting a major source of uncertainty for determining stock status and informing rebuilding plans. Retrospective patterns may result from model assumptions that do not account for environmental effects on population or fishery dynamics. In the face of climate change, there is increasing exploration of climate impacts on stock dynamics in the context of stock assessments. However, incorrectly integrating climate information can contribute to model misspecification. Thus, it is important to identify significant relationships and understand mechanisms before including them in assessments. Process error refers to the variability in population dynamics due to natural fluctuations (such as environmental effects) not captured by the model. State space models explicitly model this uncertainty, potentially improving the accuracy of assessments and supporting more adaptive, sustainable fisheries management. I led a review of the available information on environmental drivers that may be impacting US stocks of yellowtail flounder from literature and harvesters’ ecological knowledge, tested relationships between environmental indices and components of productivity (i.e., recruitment, growth, maturity, survival), and helped developed stock assessment models that account for environmental effects. Chapter One reviews the available information on environmental drivers impacting stocks of yellowtail flounder off New England from literature and harvesters’ ecological knowledge. Results suggest that several aspects of yellowtail flounder population dynamics have been sensitive to the environment, including geographic distribution, recruitment, and potentially other components of production such as natural mortality and growth. Chapter Two tested relationships between environmental indices and components of population dynamics. Generalized Additive Models (GAMs) were applied to explore relationships between the identified environmental variables and stock dynamics to determine what data should be explored in the yellowtail flounder stock assessment models. Several potential climate impacts were identified. Recruitment of yellowtail flounder off southern New England was correlated to the Mid-Atlantic Bight Cold Pool. Recruitment of yellowtail flounder on Georges Bank was correlated with bottom temperature and the Atlantic Multidecadal Oscillation. Chapter Three developed an assessment model for the Georges Bank yellowtail flounder stock that accounts for environmental effects. Results show that incorporating environmental covariates into the stock assessment improves model diagnostics and reduces uncertainty in short-term projections. This research has implications for improving assessment and management of New England yellowtail flounder fisheries and serves as a model for how appropriate ecosystem drivers can be identified for use in integrated state-space stock assessments for other assessments.

DFO’s own Jessica Kittel will be defending her PhD Dissertation “Environmental Effects on Population Dynamics of New England Yellowtail Flounder” on April 7! Join us at SMAST East, Rooms 101-103 or on Zoom. Check out Jessie’s abstract below!

Abstract:

Yellowtail flounder, Limanda ferruginea (a.k.a., Pleuronectes ferruginea, Myzopsetta ferruginea), inhabit the continental shelf of the northwest Atlantic and historically supported target fisheries off New England. However, the Georges Bank and Southern New England/ Mid-Atlantic stocks have declined in recent decades and have not recovered despite severely restricted fisheries, suggesting that productivity may be negatively affected by climate change. Ocean waters off New England are warming four times faster than the global average, and decreased yellowtail flounder productivity has been associated with ocean warming in the region. US stock assessments of yellowtail flounder have exhibited retrospective patterns, in which contemporary estimates of abundance decrease when a new year of data is added, presenting a major source of uncertainty for determining stock status and informing rebuilding plans. Retrospective patterns may result from model assumptions that do not account for environmental effects on population or fishery dynamics. In the face of climate change, there is increasing exploration of climate impacts on stock dynamics in the context of stock assessments. However, incorrectly integrating climate information can contribute to model misspecification. Thus, it is important to identify significant relationships and understand mechanisms before including them in assessments. Process error refers to the variability in population dynamics due to natural fluctuations (such as environmental effects) not captured by the model. State space models explicitly model this uncertainty, potentially improving the accuracy of assessments and supporting more adaptive, sustainable fisheries management. I led a review of the available information on environmental drivers that may be impacting US stocks of yellowtail flounder from literature and harvesters’ ecological knowledge, tested relationships between environmental indices and components of productivity (i.e., recruitment, growth, maturity, survival), and helped developed stock assessment models that account for environmental effects. Chapter One reviews the available information on environmental drivers impacting stocks of yellowtail flounder off New England from literature and harvesters’ ecological knowledge. Results suggest that several aspects of yellowtail flounder population dynamics have been sensitive to the environment, including geographic distribution, recruitment, and potentially other components of production such as natural mortality and growth. Chapter Two tested relationships between environmental indices and components of population dynamics. Generalized Additive Models (GAMs) were applied to explore relationships between the identified environmental variables and stock dynamics to determine what data should be explored in the yellowtail flounder stock assessment models. Several potential climate impacts were identified. Recruitment of yellowtail flounder off southern New England was correlated to the Mid-Atlantic Bight Cold Pool. Recruitment of yellowtail flounder on Georges Bank was correlated with bottom temperature and the Atlantic Multidecadal Oscillation. Chapter Three developed an assessment model for the Georges Bank yellowtail flounder stock that accounts for environmental effects. Results show that incorporating environmental covariates into the stock assessment improves model diagnostics and reduces uncertainty in short-term projections. This research has implications for improving assessment and management of New England yellowtail flounder fisheries and serves as a model for how appropriate ecosystem drivers can be identified for use in integrated state-space stock assessments for other assessments.