NOAA Fisheries is responsible for administering the Endangered Species Act (ESA) to insure actions by any government agency are not likely to jeopardize the continued existence of any threatened or endangered species we manage. In the West Coast Region this includes many species of whales, sea turtles, sea lions, salmon, steelhead trout, and marine fishes. Our region’s biologists implement ESA policy across Washington, Oregon, Idaho, and California and are responsible for analyzing how proposed projects may impact protected species. The regulated community we serve (i.e. federal agencies, and any organization that receives funding or requires a permit from any federal agency) counts on NOAA Fisheries to provide authorization under the ESA to be able to carry out their projects. Our agency is also obligated to make sure our analyses are transparent to the public and based on the best available science.
Over time, our offices have had to find ways to complete more of these analyses within regulatory deadlines with fewer staff, all while maintaining the consistency of our methods and decisions. Adding to this challenge is a legacy of organizational culture (common to many federal agencies) where analysts tend to work in separate ‘silos’ specific to species, geographies, or project types, and communication across offices is limited. This situation presents our teams with a common problem: how do we perform rigorous analyses consistently, transparently, and on time with growing demand and limited resources?
Our team of regulatory biologists took a new approach to what were previously separate state-level evaluations, and used R to automate analyses of the impacts of research projects across the West Coast Region. In describing our process, this example will show how the new approach has transformed the workflow we use to analyze our data and generate authorizing documents. We now tackle the analysis as a collaborative team of code builders, code users, and output consumers, and this strategy has saved hundreds of collective staff hours and improved the consistency of our results. The approach also allows our team to provide ESA coverage to applicants faster, providing researchers greater confidence their projects can start when planned. Seeing how using R has improved our group’s efficiency and ability to balance workloads has already inspired other teams in our region to start adopting similar approaches. Government resource managers and policy analysts may not think of themselves as prime candidates for using code, but we are quickly learning R can set regulatory teams on a path to more efficient and flexible collaboration.
Bio: Diana Dishman is a Natural Resource Management Specialist in the Protected Resources Division of NOAA Fisheries’ West Coast Region. She has a Master’s in Biology from Portland State University, where her research focused on marine mammal population genetics, and a Bachelor’s in Biology from Scripps College. Prior to joining NOAA Diana worked in an aquatic toxicology laboratory looking at the impacts of contaminated waters on fish and invertebrates. She later fell in love with data management, analysis, and visualization as an environmental consultant, investigating contaminant and biodiversity data associated with Superfund sites, the Deepwater Horizon oil spill, and litigated water disputes, and working to distill complex data into clear and compelling products used to guide clean-up and recovery of impacted habitats. In her current role with NOAA Fisheries Diana is helping her branch streamline Endangered Species Act consultations and permitting by building products in R, and working to expand internal R training for others in the Region. Diana lives in Clackamas, Oregon, and when she's not coding is usually trying to keep up with her two daughters, two dogs, and too many farm animals.