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welcomeI'm Christine, a quantitative ecologist interested in statistical methods to improve population assessment, researching how populations respond to environmental variability and change, and developing and improving software tools. Currently, I develop and improve usability of statistical fisheries stock assessment models and tools as an employee of NOAA Fisheries' Office of Science and Technology. I completed my PhD at the University of Washington in the Quantitative Ecology and Resource Management (QERM) program in 2017. I worked with Dr. Tim Essington in the School of Aquatic and Fishery Sciences to develop statistical models to estimate growth change in marine fish from messy data and run simulation analyses to how this variation affects population productivity and fisheries management. I'd be happy to talk to you about my research; email is the best way to contact me. |
about meI was born and raised in Staten Island, New York, after which I attended the University of Virginia (UVa). At UVa I majored in Systems Engineering, with a focus on computer systems, and spent my summers working as a developer and database administrator. After college, I moved to Seattle and worked at Microsoft for three years as a Program Manager on the Windows team. I fell in love with the Pacific Northwest while here, and sought a career that allowed me to dig deeper into mathematical modeling and programming and apply these technical and mathematical skills to studying the marine ecosystem. So, it was an easy choice to attend graduate school in the QERM program, which gives mathematically-minded students a rigorous statistical background that can then be used to solve ecological questions. Throughout my PhD, I developed and applied statistical models to marine fish populations, conducted a meta-analysis on seafood mislabeling, and learned and taught statistical models and the R programming language. Throughout my PhD work I was supported by funding via the NMFS/Sea Grant Population Dynamics Fellowship program and the NSF IGERT Program on Ocean Change. I moved over to the Alaska Fisheries Science Center for a postdoctoral position after completing my PhD. I was hired by NOAA's National Stock Assessment Program within the Office of Science and Technology as a contractor in 2018 and became a federal employee in 2021. In this work, I develop and improve next-generation fisheries stock assessment models. I've volunteered at the Seattle Aquarium, as a judge with the National Ocean Sciences Bowl, and with the Ocean Inquiry Project. In my free time, I enjoy hiking, reading, knitting, snowboarding, and traveling. |
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 Note: I don't work on tubeworms, but I do like them. |
The most recent version of my CV (8/2021) is here. Google scholar will have the most up-to-date list of publications.next-generation assessment modelsI am currently researching and developing the Fisheries Integrated Modeling System (FIMS), a new framework for next-generation fisheries stock assessment models. FIMS will be built according to software design best practices while incorporating state-of-the-art research in assessment modeling. This team spans a large group of domestic collaborators and individual comment from international experts. For more information about FIMS, please see the official NOAA website. I also support the NOAA Fisheries Integrated Toolbox which you can visit here |
postdoctoral research on snow crabI worked on an individual-based model (using the DisMELS framework) that simulates a range of probabilistic trajectories for larval dispersion (and integrates metabolic effects on growth) to predict how anticipated changes in ocean pH and temperatures will affect Alaska snow crab (Chinoecetes opilio) in the Bering Sea. The model incorporates stage-structure and integrates impacts of climate on larval through juvenile stages of crab from experimental results with output forecasts from a regional ocean model of the Bering Sea under alternative climate scenarios. |
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detecting variation in growth in marine groundfishAs part of my dissertation research at the University of Washington, I developed a method to quantify somatic growth variation in Northeastern Pacific groundfish. We developed a Bayesian state-space approach to isolate biological changes in growth from measurement error across thirty populations. To determine at which scale growth varied, we evaluated four alternative models: one in which growth varied annually across the population, one where size of recruited fish varied, one where cohorts had either increased or decreased growth rates, and a null model (no growth variation). We found evidence for growth variation across a large number of examined groundfish species, and variation at annual scales was most common. You can read this work here. |
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quantifying the impact of growth changes on populationsOnce we quantified growth varied substantially across a number of fish populations, the question remained: "how much does it matter?" We used a simulation approach to determine if changes in somatic growth could 1. induce fluctuations into populations of marine fish as much as changes in recruitment success and 2. affect recommendations for harvest of marine fisheries. For the first component, we used the measured growth changes from the above project and recruitment variation patterns derived from population assessment output combined with a simple population model. In a large minority of species (40%), we found growth variation could induce changes in population biomass on par with that caused by changes in recruitment. This appeared to be tied to what type of growth variation was present rather than predictable life history invariants. You can read this work here. Next, we used a simulation approach in conjunction with the model used for management of California Current petrale sole to test if growth variation affected estimates of population biomass and harvest targets. We found changes in growth that corresponded to regime-like step changes in growth patterns could affect estimates of population status, such that the population size could be overestimated if growth variation was not accounted for. You can read this work here |
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climate adaptation planning in coastal citiesI'm working with an interdisciplinary group of IGERT Program on Ocean Change students, including economic, atmospheric, and natural scientists, to qualitatively evaluate the level of adaptation to sea level rise being undertaken in a small number of US coastal cities. We are particularly interested in the role of science in informing plans to adapt to sea level rise and creating recommendations for how physical scientists can make their products more applicable to planning. We conducted a survey of a large number of coastal communities and you can read our paper here |
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publications
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