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.