Salmon on the run: Practicing scale in the study of wild Alaska salmon

Abstract

Modern scientific research infrastructure has eclipsed the importance of scaling when understanding ecosystem change. Scale is the lens through which scientists parse complexity. Although scale is central to scientific practice, modern research infrastructure has replaced the importance of scale with a focus on scalability in data. This dissertation engages the topic of scale in an ethnographic study of the State of Alaska’s Salmon and People (SASAP) project, a 3-year initiative designed to investigate how data science can aid natural sciences. Through the synthesis of three empirical studies, this thesis proposes a conceptual framework that brings the extant theorizations of scale into conversation with the theorizations of scale in ecology. This study explores scale in three different cases: 1- a data science application for ecological data synthesis; 2- a field program focused on collecting and storing data in the long-term; and 3- a participatory modeling initiative instrumenting the local. As such, this thesis articulates how research practitioners reconcile issues of scale in wild Alaska salmon research and offers general insights about how to define scale. Building on prior work in infrastructure studies, this dissertation also provides methodological contributions for the ethnographic study of contemporary data initiatives. In conclusion, this research offers insights into how scientists define and instrument scale, methodological contributions for conducting studies of large-scale data initiatives, and a general language for working with scale.