This is an informal place for me to list my research projects. It is not meant to be complete nor up to date. Please see links below for Google Scholar for the most recent updates. Broadly speaking I'm interested in developing and applying quantitative techniques to manage marine resources efficiently and sustainably. Below is a collection of research projects I’ve been involved in, with newer projects at the top.

I am currently a research scientist with a joint position between the University of Washington and Alaska Fisheries Science Center (NOAA) in Seattle. I am working on a spatiotemporal index standardization that combines information from bottom and acoustic trawl data. The method is a spatial factor analysis as implemented in the software VAST, and the end goal is to improve the stock assessment for walleye pollock in the Eastern Bering Sea.

Advancing Bayesian methods in integrated fisheries stock assessment

For my PhD I studied the advantages of a Bayesian algorithm called Hamiltonian Monte Carlo for statistical inference in fisheries stock assessment. I added capabilities similar to the statistical modeling software Stan into AD Model Builder so that these new powerful tools were readily available to most existing stock assessments. The overarching goal was to provide a software toolset and guidance such that interested analysts could perform Bayesian inference if desired.

Population trends of the eastern North Pacific blue whale

The topic of my Master's degree was the population trends of blue whales off the coast of California. I combined multiple existings data sets to infer the spatial pattern of whaling and then combined that with recent abundance estimates to gauge the risk of lethal ship strikes to the recovery of this population.

Simulation testing of fisheries stock assessments

Fisheries stock assessment models (used to management fisheries in the US and around the world) are complex and often unpredictable. One approach to help understand their statistical behavior is to use simulation testing. With this in mind a group of students and postdocs, based mainly at the UW, developed a software platform called ss3sim (code and paper) which facilitates this type of simulation testing. So far we have used our package in several studies:

  • Implications of process error in selectivity. Read more
  • The effect of length bin width. Read more
  • Using empirical weights instead of somatic growth functions. Read more
  • Retrospective patterns. Read more
  • Time-varying natural mortality. Read more
  • The importance of length and age composition data. Read more