The Pelagic Species Trait Database, an open data resource to support trait-based ocean research.

Trait-based frameworks are increasingly used for predicting how ecological communities respond to ongoing global change. As species range shifts result in novel encounters between predators and prey, identifying prey 'guilds', based on a suite of shared traits, can distill complex species interactions, and aid in predicting food web dynamics. To support advances in trait-based research in open-ocean systems, we present the Pelagic Species Trait Database, an extensive resource documenting functional traits of 529 pelagic fish and invertebrate species in a single, open-source repository. We synthesized literature sources and online resources, conducted morphometric analysis of species images, as well as laboratory analyses of trawl-captured specimens to collate traits describing 1) habitat use and behavior, 2) morphology, 3) nutritional quality, and 4) population status information. Species in the dataset primarily inhabit the California Current system and broader NE Pacific Ocean, but also includes pelagic species known to be consumed by top ocean predators from other ocean basins. The aim of this dataset is to enhance the use of trait-based approaches in marine ecosystems and for predator populations worldwide.

The influence of complex matrices on method performance in extracting and monitoring for microplastics.

Previous studies have evaluated method performance for quantifying and characterizing microplastics in clean water, but little is known about the efficacy of procedures used to extract microplastics from complex matrices. Here we provided 15 laboratories with samples representing four matrices (i.e., drinking water, fish tissue, sediment, and surface water) each spiked with a known number of microplastic particles spanning a variety of polymers, morphologies, colors, and sizes. Percent recovery (i.e., accuracy) in complex matrices was particle size dependent, with ∼60-70% recovery for particles >212 µm, but as little as 2% recovery for particles <20 µm. Extraction from sediment was most problematic, with recoveries reduced by at least one-third relative to drinking water. Though accuracy was low, the extraction procedures had no observed effect on precision or chemical identification using spectroscopy. Extraction procedures greatly increased sample processing times for all matrices with the extraction of sediment, tissue, and surface water taking approximately 16, 9, and 4 times longer than drinking water, respectively. Overall, our findings indicate that increasing accuracy and reducing sample processing times present the greatest opportunities for method improvement rather than particle identification and characterization.

Monitoring microplastics in drinking water: An interlaboratory study to inform effective methods for quantifying and characterizing microplastics.

California Senate Bill 1422 requires the development of State-approved standardized methods for quantifying and characterizing microplastics in drinking water. Accordingly, we led an interlaboratory microplastic method evaluation study, with 22 participating laboratories from six countries, to evaluate the performance of widely used methods: sample extraction via filtering/sieving, optical microscopy, FTIR spectroscopy, and Raman spectroscopy. Three spiked samples of simulated clean water and a laboratory blank were sent to each laboratory with a prescribed standard operating procedure for particle extraction, quantification, and characterization. The samples contained known amounts of microparticles within four size fractions (1-20 µm, 20-212 µm, 212-500 µm, >500 µm), four polymer types (PE, PS, PVC, and PET), and six colors (clear, white, green, blue, red, and orange). They also included false positives (natural hair, fibers, and shells) that may be mistaken for microplastics. Among laboratories, mean particle recovery using stereomicroscopy was 76% ± 10% (SE). For particles in the three largest size fractions, mean recovery was 92% ± 12% SD. On average, laboratory contamination from blank samples was 91 particles (± 141 SD). FTIR and Raman spectroscopy accurately identified microplastics by polymer type for 95% and 91% of particles analyzed, respectively. Per particle, FTIR spectroscopy required the longest time for analysis (12 min ± 9 SD). Participants demonstrated excellent recovery and chemical identification for particles greater than 50 µm in size, with opportunity for increased accuracy and precision through training and further method refinement. This work has informed methods and QA/QC for microplastics monitoring in drinking water in the State of California.