The Devils Hole pupfish (Cyprinodon diabolis) is one of the world’s most endangered animals. There is only one wild population living in a single aquifer-fed thermal pool in Nye County, Nevada, and has been perched on the brink of extinction at 35–68 fish in 2013. A major strategy for conserving the pupfish has been to create additional captive populations, but scientists needed to know how to best extract wild pupfish for breeding purposes without unduly accelerating the extinction risk for the population in Devil’s Hole. Dr. Steven Beissinger, Professor of Conservation Biology at the University of California, Berkeley, constructed a population variability analysis (PVA) using @RISK to better inform this dilemma.
Dr. Beissinger first created models for extinction risk in the wild for the pupfish, which showed that most simulated populations of the pupfish became extinct within 50 years. Median and mean time to extinction were 26 and 27 years, and 17 and 22 years, respectively. Next, to evaluate the effects of different strategies for removing individuals to initiate a captive breeding program on the wild population, Dr. Beissinger modeled the effects of removing different numbers of individuals (0–14) at the start of each simulated year.
Dr. Beissinger then wanted to answer the question of which life-stage should pupfish be harvested. The model showed that removing pupfish eggs had the least effect on the wild population. Indeed, Dr. Beissinger calculated that removing 25 eggs for captive breeding is equivalent to removing a single adult in terms of its influence on population dynamics.
This modeling work has helped to inform decisions made by the U.S. Fish and Wildlife Service to conserve the Devil’s Hole pupfish, which has now begun to remove pupfish eggs from Devil’s Hole to start a captive population in its state-of-the-art breeding facility. “The modeling helped everyone to see what some of the trade-offs would be and made the various outcomes more explicit,” says Dr. Beissinger.
Dr. Beissinger uses @RISK for both research and teaching, and finds it to be a valuable tool: “@RISK makes Monte Carlo processes easy for professionals and students to understand,” he says. “The nice thing about it, from my perspective, is that it functions within Excel, which makes visualizing the information a lot easier and more intuitive for people. It makes what would otherwise be a lot of tedious steps a lot easier to do.”
