Oceanographic regime and foraging behaviour structure compound-specific PFAS variability in arctic-atlantic...

Area of Science:

• Environmental toxicology
• Marine ecology
• Ecotoxicology

Background:

• Current chemical exposure studies often overlook individual variability, treating it as statistical noise.
• Individual exposure variability may contain structured ecological information related to habitat use and foraging behavior.
• Per- and polyfluoroalkyl substances (PFAS) are persistent environmental contaminants with complex exposure pathways.

Purpose of the Study:

• To test the hypothesis that individual PFAS exposure variability acts as a structured ecological signal.
• To investigate the relationship between PFAS exposure variability and individual foraging stability in seabirds.
• To understand how oceanographic gradients and trophic sources influence contaminant acquisition patterns.

Main Methods:

• Integrated PFAS variability data with isotopic consistency scores (δ13C and δ15N) from dual-tissue samples (plasma and red blood cells) of guillemots (Uria aalge and Uria lomvia).
• Analyzed PFAS concentrations and stable isotope ratios from 112 individuals across five Icelandic colonies during the 2018 breeding season.
• Employed cluster analysis and bivariate segmented regression to identify exposure states and hierarchical drivers of contaminant acquisition.

Main Results:

• PFAS variability was strongly structured by compound class, primarily long-chain perfluoroalkyl carboxylic acids (PFCAs) and perfluorooctane sulfonate (PFOS).
• Two distinct exposure states were identified: constrained PFOS variability and constrained PFCA variability.
• Oceanographic regime (δ13C) was the primary driver of PFOS variability, while trophic sources (δ15N) conditionally modulated PFCA variability, especially in higher trophic levels.

Conclusions:

• Individual PFAS exposure variability provides a valuable ecological signal, reflecting habitat use and foraging behavior.
• Contaminant acquisition follows a hierarchical structure influenced by both broad oceanographic conditions and fine-scale niche partitioning.
• Understanding contaminant variability is crucial for predicting exposure shifts in marine ecosystems under climate change.