Assessing the potential of remote sensing-derived water quality data to explain variations in fish assemblages and to support fish status assessments in large lakes

Remote sensing techniques may provide a higher temporal and spatial resolution than traditional water monitoringmethods. We tested if this auxiliary information can be used to (i) explain patterns in fish assemblage composition and (ii) test candidate metrics to assess ecological status in large lake water bodies. We used MERIS-derived layers describing chlorophyll a, total suspended matter, and colored dissolved organic matter(CDOM) overlaid on all available fish monitoring data from the four largest Swedish lakes (Vanern, Vattern, Malaren, and Hjalmaren). We assessed the influence of remote sensing-derived parameters in the pelagic, offshore benthic, and the inshore benthic habitats. Our results demonstrated that chlorophyll a and CDOM together with depth at the sampling site explained a significant part of the variation in the distribution of fish assemblages. These predictors were particularly important not only in pelagic, but also in inshore benthic areas. Furthermore, we identified three potential candidate metrics to assess pressure from eutrophication in large lakes: density of pelagic fishes, biomass of planktivorousspecies, and the proportion of cyprinids when roach was excluded. Remote sensing was considered a useful tool to support analyses of fish community composition and dynamics.