Harmful algal blooms and climate change: Learning from the past and present to forecast the future.

https://ir.library.oregonstate.edu/downloads/bn999842j

Global solutions to regional problems: Collecting global expertise to address the problem of harmful cyanobacterial blooms. A Lake Erie case study.

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.

Data-driven robotic sampling for marine ecosystem monitoring

An ecologically and economically disruptive harmful algal bloom (HAB) affected much of the northeast Pacific margin in 2015, during a prolonged oceanic warm anomaly Caused by diatoms of the genus Pseudo-nitzschia, this HAB produced the highest particulate concentrations of the biotoxin domoic acid (DA) ever recorded in Monterey Bay, California Bloom inception followed strong upwelling during the spring transition, which introduced nutrients and eliminated the warm anomaly locally Subsequently, moderate and intermittent upwelling created favorable conditions for growth and accumulation of HAB biomass, which was dominated by a highly toxigenic species, P australis High cellular DA concentrations were associated with available nitrogen for DA synthesis coincident with silicate exhaustion This nutrient influence resulted from two factors: (1) disproportionate depletion of silicate in upwelling source waters during the warm anomaly, the most severe depletion observed in 24 years, and (2) silicate uptake by the dense diatom bloom

https://agupubs.onlinelibrary.wiley.com/doi/pdf/10.1002/2017GL072637

Causality of an extreme harmful algal bloom in Monterey Bay, California, during the 2014-2016 northeast Pacific warm anomaly

As a demonstrator for technologies for the next generation of ocean color sensors, the Hyperspectral Imager for the Coastal Ocean (HICO) provides enhanced spatial and spectral resolution that is required to understand optically complex aquatic environments. In this study we apply HICO, along with satellite remote sensing and in situ observations, to studies of phytoplankton ecology in a dynamic coastal upwelling environment—Monterey Bay, CA, USA. From a spring 2011 study, we examine HICO-detected spatial patterns in phytoplankton optical properties along an environmental gradient defined by upwelling flow patterns and along a temporal gradient of upwelling intensification. From a fall 2011 study, we use HICO's enhanced spatial and spectral resolution to distinguish a small-scale ―red tide‖ bloom, and we examine bloom expansion and its supporting processes using other remote sensing and in situ data. From a spectacular HICO image of the Monterey Bay region acquired during fall of 2012, we present a suite of algorithm results for characterization of phytoplankton, and we examine the strengths, limitations, and distinctions of each algorithm in the context of the enhanced spatial and spectral resolution.

/pdf/application-of-the-hyperspectral-imager-for-the-coastal-354lh0jrth.pdf

Application of the hyperspectral imager for the coastal ocean to phytoplankton ecology studies in Monterey Bay, CA, USA

Coastal marine ecosystems are profoundly influenced by processes that originate from their boundaries. These include fluid boundaries—with the atmosphere, oceanic boundary currents and terrestrial aquatic systems, as well as solid boundaries—with the seafloor and coast. Phytoplankton populations transfer complexly interacting boundary influences into the biosphere. In this contribution, we apply data from an ocean observing and modeling system to examine boundary influences driving phytoplankton ecology in Monterey Bay, CA, USA. The study was focused on species that may cause harmful algal blooms (HABs). During September–October 2010, autonomous molecular analytical devices were moored at two locations characterized by different degrees of stratification and exposure to upwelling dynamics. The time-series revealed multiple transitions in local HAB phytoplankton communities, involving diatoms (Pseudo-nitzschia spp.), dinoflagellates (Alexandrium catenella), and raphidophytes (Heterosigma akashiwo). Observational and model results showed that the biological transitions were closely related to environmental changes that resulted from a variety of boundary processes—responses of oceanic circulation to wind forcing, influxes of different water types that originated outside the bay, and emergence of strongly stratified nearshore water into the greater bay. Boundary processes were further implicated at patch scales. High-resolution mapping and sampling of a phytoplankton-enriched patch were conducted in a Lagrangian framework using autonomous underwater vehicles. These highly resolved measurements showed that small-scale spatial patterns in the toxicity of Pseudo-nitzschia populations were related to the coupling of resuspended sediments from the bottom boundary layer to the surface mixed layer.

T. Pennington

Papers

Boundary influences on HAB phytoplankton ecology in a stratification-enhanced upwelling shadow