Microbial and small zooplankton communities predict density of baleen whales in the southern California Current Ecosystem
Satterthwaite, E. V.; Ruiz, T.; Patin, N. V.; Alksne, M. N.; Thomas, L.; Dinasquet, J.; Lampe, R. H.; Chan, K. G.; Patrick, N. A.; Allen, A. E.; Baumann-Pickering, S.; Semmens, B. X.
Show abstract
Understanding the density of marine mammals is important for assessing population dynamics and evaluating the impacts of human activities on these species. In this work, we examine microorganisms that may be ecologically associated, whether directly or indirectly, with baleen whales - the potential "ecological habitat" - to predict baleen whale densities via statistical relationships adjusted for seasonal patterns of occurrence. We assessed the capability of microbial and small plankton communities to predict the density of Balaenopteridae whales in the Southern California Current Ecosystem in each quarterly season from 2014 to 2020 using data from the California Cooperative Oceanic Fisheries Investigations (CalCOFI). Densities were estimated from visual sightings for three target species - blue, fin, and humpback whales - and microbial and small plankton communities were examined using concurrent water samples via metabarcoding of the 16S and 18S rRNA genes. We identified microbial and small plankton communities specific to each target species that were strong predictors of estimated density. Groups of 23-60 distinct Amplicon Sequence Variants (ASVs) per baleen whale species explained 81-99% of variability in estimated whale density and predicted density estimates to within [~]1 individual per 1000 km2. The predictive accuracy achieved by our approach, compared with naive seasonal carry-forward and seasonal averaging approaches to prediction, improves out-of-sample RMSE by up to an estimated 65%. Microbial and small plankton communities were characterized by 148 unique taxonomic annotations enumerated across marker genes. Of these, 20% were shared across all three species, 21% were shared by two species, and the remaining (59%) were unique to a single whale species, which suggests that there is some overlap in the ecological habitat among blue, humpback, and fin whales, but each species is also related to a distinct community of microbes and small plankton. We also conducted a narrative review to examine existing known relationships of baleen whales with microbes or small plankton. Of the 148 unique taxonomic annotations we found to be predictive of baleen whale densities, 23% have been referenced within the existing literature exploring microbial prey, parasites, commensals, or respiratory-associated organisms of baleen whales, with matches at the genus or family level. The rest matched at higher taxonomic levels (41%) or had no documented matches in our literature search (36%). These findings suggest that some of the microbial and small plankton community predictors may be ecologically relevant, yet further studies are needed to understand how these organisms function collectively as a community and interact with whale ecology, prey, and the surrounding environment. Our results suggest that using microbial and small plankton communities to quantify the potential ecological habitat of larger organisms, like baleen whales, can enhance predictive models and may inform hypotheses about the ecological relationships between whales and the biological communities with which they co-occur.
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