Microbial eukaryotes fulfill key ecological positions in marine food webs. Molecular approaches that connect protistan diversity and biogeography to their diverse metabolisms will greatly improve our understanding of marine ecosystem function. The majority of molecular-based studies to date use 18S rRNA gene sequencing to characterize natural microbial assemblages, but this approach does not necessarily discriminate between active and non-active cells. We incorporated RNA sequencing into standard 18S rRNA gene sequence surveys with the purpose of assessing those members of the protistan community contributing to biogeochemical cycling (active organisms), using the ratio of cDNA (reverse transcribed from total RNA) to 18S rRNA gene sequences within major protistan taxonomic groups. Trophically important phytoplankton, such as diatoms and chlorophytes exhibited seasonal trends in relative activity. Additionally, both radiolaria and ciliates displayed previously unreported high relative activities below the euphotic zone. This study sheds new light on the relative metabolic activity of specific protistan groups and how microbial communities respond to changing environmental conditions.

CitationBiogeochemical interactions control a temporal succession in the elemental composition of marine communities 2016, 61 (2):531 Limnology and Oceanography

Robotic sampling is attractive in many field robotics applications that require persistent collection of physical samples for ex-situ analysis. Examples abound in the earth sciences in studies involving the collection of rock, soil, and water samples for laboratory analysis. In our test domain, marine ecosystem monitoring, detailed understanding of plankton ecology requires laboratory analysis of water samples, but predictions using physical and chemical properties measured in real-time by sensors aboard an autonomous underwater vehicle (AUV) can guide sample collection decisions. In this paper, we present a data-driven and opportunistic sampling strategy to minimize cumulative regret for batches of plankton samples acquired by an AUV over multiple surveys. Samples are labeled at the end of each survey, and used to update a probabilistic model that guides sampling during subsequent surveys. During a survey, the AUV makes irrevocable sample collection decisions online for a sequential stream of candidates, with no knowledge of the quality of future samples. In addition to extensive simulations using historical field data, we present results from a one-day field trial where beginning with a prior model learned from data collected and labeled in an earlier campaign, the AUV collected water samples with a high abundance of a pre-specified planktonic target. This is the first time such a field experiment has been carried out in its entirety in a data-driven fashion, in effect ''closing the loop'' on a significant and relevant ecosystem monitoring problem while allowing domain experts (marine ecologists) to specify the mission at a relatively high level.

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Reports of toxic harmful algal blooms (HABs) attributed to the diatom Pseudo-nitzschia spp. have been increasing in California during the last several decades. Whether this increase can be attributed to enhanced awareness and monitoring or to a dramatic upswing in the development of HAB events remains unresolved. Given these uncertainties, the ability to accurately and rapidly identify an emerging HAB event is of high importance. Monitoring of HAB species and other pertinent chemical/physical parameters at two piers in southern California, Newport and Redondo Beach, was used to investigate the development of a site-specific bloom definition for identifying emerging domoic acid (DA) events. Emphasis was given to abundances of the Pseudo-nitzschia seriata size category of Pseudo-nitzschia due to the prevalence of this size class in the region. P. seriata bloom thresholds were established for each location based on deviations from their respective long-term mean abundances, allowing the identification of major and minor blooms. Sixty-five percent of blooms identified at Newport Beach coincided with measurable DA concentrations, while 36 % of blooms at Redondo Beach coincided with measurable DA. Bloom definitions allowed for increased specificity in multiple regression analysis of environmental forcing factors significant to the presence of DA and P. seriata. The strongest relationship identified was between P. seriata abundances 2 weeks following upwelling events at Newport Beach.