Dissertation

My dissertation focused on understanding how commercial fishermen affect (and are influenced by) the marine ecosystems from which they harvest. Using a large datasets describing commercial fishing, fish abundance and environmental data, I examine the implications of human coupling of disparate marine food webs.

Range shifts and harvesting: a simple model

This study extends a theoretical model to examine how a population of fish would be affected by the joint pressures of two stressors: climate-change-driven range shifts and harvest. In this model we explore not only the possible synergy of the two stressors, but also examine the outcomes of two common forms of management. We find that, while these stressors are approximately additive, the management recommended is sensitive to the assumptions made on how effort is reallocated. This theoretical model, built with the aim of determining the sensitivity of marine fish to joint biophysical stressors, instead emphasizes the importance of understanding human behavior. This result dovetails with existing theoretical work suggesting that the dynamics of harvesters, i.e. how they respond to changes in the ecological conditions, can determine the stability of a system and ability to be managed sustainably

Status: Published in Ecosphere, see here for the paper, and our github repo here

Quantifying Human Connectivity of Commercial Fisheries on the US West Coast

I use landings data on the US west coast to develop an approach to quantitatively link fishing communities (the social system) to individual fisheries (the ecological system). This approach is a novel conceptual framework and advances our understanding of the system-level human connectivity amongst fisheries. This analysis reveals the existence of system-level properties that may be useful heuristics for managers to use in evaluating adaptive capacity of these fishing communities. In particular, I provide a way to quantitatively measure the ‘management importance’ of fisheries based on their centrality in these networks. Perturbations in fisheries of high management importance, either due to management or environmental change, are likely to be have large indirect effects via changes in participation that ripple across these participation networks.

Status: Submitted to Science Policy Forum, email me for more information!

Can catch shares improve livelihoods of fishermen and fishing communities?

Because the appreciation of the interconnectivity of marine systems is still relatively recent and the inclusion of people in these networks nascent, there are to my knowledge no published studies empirically examining how these system-level properties change as a function of management. Yet to effectively manage social ecological systems such studies are necessary to choose among policy options. In my third chapter I contribute to filling this gap by making use of the systems-level analysis described above to analyze how a major change in the management of a single fishery affects the human connectivity of the US west coast commercial fisheries system. Thanks to the rich data, I am able to conduct this analysis at two scales: that of the individual fishing vessel and the fishing community, contributing additional nuance to the results. I find that fishermen have changed their patterns of participation across fisheries as a function of how they were affected by the management change, but the system-level properties remained unchanged. While the goal of the studied management change had nothing to do with the larger fishery system, this work demonstrates how such systems-level policy evaluations could proceed.

Status: In prep, email me for more information!

Side Projects

Collaboration is the best, and I’m pleased to be involved in the following projects.

Shifting fish and fishers

As a co-leader of a SESYNC funded graduate student working group, I’m collaborating with social science and fellow ecology grad students to examine how fishermen are responding to climate change in the Northeast US.

Collaborators: Talia Young, Brad Dubik, Josh Stoll, Kaycee Colman, Mikaela Provost, Sara Bess Jones, Elizabeth Clark, Kevin St. Martin, Malin Pinsky

Predictin Parturition from GPS data in Large Ungulates

Working with Matt Hayes at the University of Wyoming, we’re using machine learning approaches to build a flexible classification algorithm to infer parturition events in North American large ungulates from GPS data.

Collaborators: Matt Hayes