Monitoring studies indicate that a wide variety of avian species are exposed to per- and polyfluoroalkyl substances (PFAS), including gulls, wading birds, piscivorous and insectivorous birds, and terrestrial raptors. Some PFAS are known to bioaccumulate and biomagnify, though the distribution and movement of PFAS in avian food webs are poorly understood. As with exposure, the effects of PFAS on birds are also poorly understood. The technical objectives of this project are as follows:
At the broadest scale, the approach is to develop experimental populations of three breeding songbird species at six sites with variable levels of PFAS, including a subset who will be dosed with perfluorooctane sulfonate (PFOS) under semi-controlled conditions. These sites and species will provide the environmental, biological, and ecological data used to address the objectives.
Food web modeling will be done using both static and dynamic models with field-collected data on PFAS concentrations in environmental media (soil, sediment, and water) and invertebrate prey. These data will be augmented with prey identification using DNA metabarcoding, isotope analysis of trophic status (change in radiolabeled nitrogen (δ15N)), and terrestrial versus aquatic source (δ13C) of invertebrate prey. Static food web models will employ bioconcentration factors, bioaccumulation factors, and biota sediment accumulation factors (BCFs, BAFs, and BSAFs). Dynamic bioenergetic models will compare whole nestling concentrations to predictions based on consumption rates of impacted prey. Nestling biochemical measurements in blood and tissues will inform predictive linkages along AOPs to apical outcomes relevant to population modeling and to support toxicodynamic modeling of PFAS-impacted physiology. Reproductive success will be modeled as a multistate Markov process. Fitness will be estimated and modeled using endogenous lifecycle models.
This research will generate definitive reference datasets to study the distribution of PFAS in mixed aquatic-terrestrial food webs. It will greatly advance the understanding of bioaccumulation and biomagnification potential of different PFAS. It will also advance the understanding of adverse outcomes triggered by PFAS exposure. Finally, it will provide a foundational system for predicting PFAS effects in birds from environmental data that can be applied at varied sites with different PFAS impact profiles. (Anticipated Project Completion - 2026)