Integrating pigment and fatty acid profiles for enhanced estimation of seston community composition

Climate change, nutrition pollution, and land use alterations influence the primary production of lakes. While light-microscopy counting remains the standard for estimating phytoplankton community composition, its expense and time-consuming nature necessitate cost-effective alternatives for seston analysis. Furthermore, estimating the contribution of seston constituents other than primary producers, or non-algal particles, is not possible with light-microscopy counting. Biotracer approach using computational methods and chemotaxonomic biomarkers such as carotenoid pigments and fatty acids have been used as an alternative in seston analysis when species-level taxonomy is not required. However, a comprehensive testing of how well carotenoid and fatty acids can be used in estimating a wide range of seston phytoplankton communities using different estimation methods is lacking. To assess the accuracy of a suite of state-of-the-art biotracer-based computational methods, namely CHEMTAX, FASTAR (Fatty Acid Source-Tracking Algorithm in R), MixSIAR, and QFASA (Quantitative Fatty Acid Signature Analysis), lake water samples were collected in 2016, 2018, 2019, 2020, and 2021 for seston composition analysis in a boreal eutrophic lake with light-microscopy counting serving as the reference for seston composition. Absolute errors between the biotracer-based estimates were calculated to evaluate method performance. A small laboratory experiment to assess the reliability of estimating the contribution of non-algal particles using the computational methods with fatty acids was also conducted. The closest alignment to light-microscopy counting in terms of absolute error was achieved when both carotenoids and fatty acids were used together in the QFASA method. For CHEMTAX, FASTAR, and MixSIAR, using carotenoids alone produced the closest results. Additionally, the estimation methods accurately assessed the proportion of non-algal particles in the seston when using fatty acid profiles, a capability not possible with light-microscopy counting. Our findings demonstrate that the biotracer approach provides a viable and cost-effective alternative to light-microscopy counting when group-level information of phytoplankton community composition suffices. Furthermore, we show that non-algal particles can be effectively estimated together with phytoplankton when using fatty acids.