Using Predictive Modeling to Explore Escapes From Aquaculture
This webinar will explore how predictive modeling can be used to explore genetic risks posed to natural populations by aquaculture escapes.
Using Predictive Modeling to Explore the Genetic Risks Posed to Natural Populations by Escapes from Aquaculture
Join us for a webinar on Nov 15, 2017 at 3:00 PM EST.
To fulfill its stewardship mission, NOAA Fisheries (and others) produced models to examine risk and develop management approaches and regulations that balance marine aquaculture industry needs with protecting wild stocks. The potential for negative genetic impacts should farmed fish escape and encounter wild conspecifics has been a commonly held concern, however up until now, our ability to determine the degree of risk from a given escape pattern for a given species has been limited. Genetic impacts due to interbreeding between wild and escaped fish may result in reduced genetic diversity within and among populations and loss of fitness, compromising adaptive potential, which can make a population less responsive to changing environmental conditions. There is little scientific data, however, that reliably evaluates the magnitude and duration of any negative effects due to aquaculture escapees, particularly in marine species. Thus, existing regulatory standards are largely preventative, theoretical, or qualitative rather than quantitative. More data and fitness impact models have been developed for stock enhancement which is conceptually similar to escapes. Adapting these predictive modeling approaches promises to provide a more robust way to evaluate trade-offs resulting from different management options.
The Office of Aquaculture addressed this knowledge gap by developing the Offshore Mariculture Escapes Genetics Assessment (OMEGA) simulation model in collaboration with ICF International. OMEGA is intended to provide insight into variables affecting risk, help identify research priorities, explore options for operational design or modification, and inform policy and management decisions. Current work is focused on 1) a sensitivity analysis to identify input variables with significant or non-significant effects on model output toward making OMEGA operational and user-friendly and 2) fostering external collaborations to develop model scenarios with data from aquaculture operations worldwide.