In order to support more robust and informed effects analyses, the U.S. Fish and wildlife service (hereafter, USFWS) sees the need to develop a population viability analysis for roseate terns

This Cooperative Agreement award from the U.S. Fish and Wildlife Service (USFWS) under the Endangered Species Recovery Implementation program (CFDA 15.657) provides $287,596.98 to the University of Massachusetts to develop a population viability analysis for the Northwest Atlantic roseate tern population. The objectives are to assess the risk faced by this species from offshore wind energy development, estimate apparent survival rates, create an integrated population model, and conduct a Bayesian population viability analysis. This work will help inform effects analyses and mitigation strategies related to the potential impacts of offshore wind projects on the roseate tern population. The award period runs from May 1, 2025 to November 1, 2027.

The purpose of the population viability analysis would utilize movement and demographic data to estimate risk faced by the northwest atlantic population (hereafter, northeast) of the species from offshore wind energy development and to better understand relative trends in abundance and probability of persistence quasi-extinction over a variety of time frames. Risk estimates would include, but are not limited to, impacts from collision mortality and displacement from key foraging areas. Scenarios may include changes in apparent survival and impacts to the population trajectory of the northeast population and associated life stages (e.g., breeding, migration, wintering) and age classes. Specific scenarios will be developed in partnership with USFWS biologists. Mitigation is being pursued related to offshore wind development and gaining a better understanding of the impact of potential mitigation projects on the population trajectory would be valuable. Objectives will include an offshore wind energy development risk assessment, estimates of apparent survival rate, an integrated population model, and a bayesian population viability analysis.