Radiometric approach for the detection of picophytoplankton assemblages across oceanic fronts.

Cell abundances of Prochlorococcus, Synechococcus, and autotrophic picoeukaryotes were estimated in surface waters using principal component analysis (PCA) of hyperspectral and multispectral remote-sensing reflectance data. This involved the development of models that employed multilinear correlations between cell abundances across the Atlantic Ocean and a combination of PCA scores and sea surface temperatures. The models retrieve high Prochlorococcus abundances in the Equatorial Convergence Zone and show their numerical dominance in oceanic gyres, with decreases in Prochlorococcus abundances towards temperate waters where Synechococcus flourishes, and an emergence of picoeukaryotes in temperate waters. Fine-scale in-situ sampling across ocean fronts provided a large dynamic range of measurements for the training dataset, which resulted in the successful detection of fine-scale Synechococcus patches. Satellite implementation of the models showed good performance (R2 > 0.50) when validated against in-situ data from six Atlantic Meridional Transect cruises. The improved relative performance of the hyperspectral models highlights the importance of future high spectral resolution satellite instruments, such as the NASA PACE mission's Ocean Color Instrument, to extend our spatiotemporal knowledge about ecologically relevant phytoplankton assemblages.

A global compilation of in situ aquatic high spectral resolution inherent and apparent optical property data for remote sensing applications.

Light emerging from natural water bodies and measured by radiometers contains information about the local type and concentrations of phytoplankton, non-algal particles and colored dissolved organic matter in the underlying waters. An increase in spectral resolution in forthcoming satellite and airborne remote sensing missions is expected to lead to new or improved capabilities for characterizing aquatic ecosystems. Such upcoming missions include NASA's Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) mission; the NASA Surface Biology and Geology designated observable mission; and NASA Airborne Visible/Infrared Imaging Spectrometer - Next Generation (AVIRIS-NG) airborne missions. In anticipation of these missions, we present an organized dataset of geographically diverse, quality-controlled, high spectral resolution inherent and apparent optical property (IOP-AOP) aquatic data. The data are intended to be of use to increase our understanding of aquatic optical properties, to develop aquatic remote sensing data product algorithms, and to perform calibration and validation activities for forthcoming aquatic-focused imaging spectrometry missions. The dataset is comprised of contributions from several investigators and investigating teams collected over a range of geographic areas and water types, including inland waters, estuaries, and oceans. Specific in situ measurements include remote-sensing reflectance, irradiance reflectance, and coefficients describing particulate absorption, particulate attenuation, non-algal particulate absorption, colored dissolved organic matter absorption, phytoplankton absorption, total absorption, total attenuation, particulate backscattering, and total backscattering. The dataset can be downloaded from https://doi.org/10.1594/PANGAEA.902230 (Casey et al., 2019).

An overview of approaches and challenges for retrieving marine inherent optical properties from ocean color remote sensing.

Ocean color measured from satellites provides daily global, synoptic views of spectral waterleaving reflectances that can be used to generate estimates of marine inherent optical properties (IOPs). These reflectances, namely the ratio of spectral upwelled radiances to spectral downwelled irradiances, describe the light exiting a water mass that defines its color. IOPs are the spectral absorption and scattering characteristics of ocean water and its dissolved and particulate constituents. Because of their dependence on the concentration and composition of marine constituents, IOPs can be used to describe the contents of the upper ocean mixed layer. This information is critical to further our scientific understanding of biogeochemical oceanic processes, such as organic carbon production and export, phytoplankton dynamics, and responses to climatic disturbances. Given their importance, the international ocean color community has invested significant effort in improving the quality of satellite-derived IOP products, both regionally and globally. Recognizing the current influx of data products into the community and the need to improve current algorithms in anticipation of new satellite instruments (e.g., the global, hyperspectral spectroradiometer of the NASA Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) mission), we present a synopsis of the current state of the art in the retrieval of these core optical properties. Contemporary approaches for obtaining IOPs from satellite ocean color are reviewed and, for clarity, separated based their inversion methodology or the type of IOPs sought. Summaries of known uncertainties associated with each approach are provided, as well as common performance metrics used to evaluate them. We discuss current knowledge gaps and make recommendations for future investment for upcoming missions whose instrument characteristics diverge sufficiently from heritage and existing sensors to warrant reassessing current approaches.

Metaproteomic analysis of a winter to spring succession in coastal northwest Atlantic Ocean microbial plankton.

In this study, we used comparative metaproteomics to investigate the metabolic activity of microbial plankton inhabiting a seasonally hypoxic basin in the Northwest Atlantic Ocean (Bedford Basin). From winter to spring, we observed a seasonal increase in high-affinity membrane transport proteins involved in scavenging of organic substrates; Rhodobacterales transporters were strongly associated with the spring phytoplankton bloom, whereas SAR11 transporters were abundant in the underlying waters. A diverse array of transporters for organic compounds were similar to the SAR324 clade, revealing an active heterotrophic lifestyle in coastal waters. Proteins involved in methanol oxidation (from the OM43 clade) and carbon monoxide (from a wide variety of bacteria) were identified throughout Bedford Basin. Metabolic niche partitioning between the SUP05 and ARCTIC96BD-19 clades, which together comprise the Gamma-proteobacterial sulfur oxidizers group was apparent. ARCTIC96BD-19 proteins involved in the transport of organic compounds indicated that in productive coastal waters this lineage tends toward a heterotrophic metabolism. In contrast, the identification of sulfur oxidation proteins from SUP05 indicated the use of reduced sulfur as an energy source in hypoxic bottom water. We identified an abundance of Marine Group I Thaumarchaeota proteins in the hypoxic deep layer, including proteins for nitrification and carbon fixation. No transporters for organic compounds were detected among the thaumarchaeal proteins, suggesting a reliance on autotrophic carbon assimilation. In summary, our analyses revealed the spatiotemporal structure of numerous metabolic activities in the coastal ocean that are central to carbon, nitrogen and sulfur cycling in the sea.

Curvature in models of the photosynthesis-irradiance response.

An equation for the rate of photosynthesis as a function of irradiance introduced by T. T. Bannister included an empirical parameter b to account for observed variations in curvature between the initial slope and the maximum rate of photosynthesis. Yet researchers have generally favored equations with fixed curvature, possibly because b was viewed as having no physiological meaning. We developed an analytic photosynthesis-irradiance equation relating variations in curvature to changes in the degree of connectivity between photosystems, and also considered a recently published alternative, based on changes in the size of the plastoquinone pool. When fitted to a set of 185 observed photosynthesis-irradiance curves, it was found that the Bannister equation provided the best fit more frequently compared to either of the analytic equations. While Bannister's curvature parameter engendered negligible improvement in the statistical fit to the study data, we argued that the parameter is nevertheless quite useful because it allows for consistent estimates of initial slope and saturation irradiance for observations exhibiting a range of curvatures, which would otherwise have to be fitted to different fixed-curvature equations. Using theoretical models, we also found that intra- and intercellular self-shading can result in biased estimates of both curvature and the saturation irradiance parameter. We concluded that Bannister's is the best currently available equation accounting for variations in curvature precisely because it does not assign inappropriate physiological meaning to its curvature parameter, and we proposed that b should be thought of as the expression of the integration of all factors impacting curvature.

Using mass reconstruction along a four-site transect as a method to interpret PM10 in west-central Scotland, United Kingdom.

Concurrent 24-hr samples of particulate matter of median aerodynamic diameter less than 10 microm (PM10) were collected over a 10-day period in August 2000 at four sites along a transect in west-central Scotland, UK (passing from the coast through the city of Glasgow) in line with the prevailing southwesterly wind. Each sample was analyzed for chloride (Cl(-)), nitrate (NO3(-)), sulfate (SO4(2-)), ammonium (NH4(+)), calcium (Ca(2+)), iron (Fe), and organic hydrocarbon material (OHM). The contribution from elemental carbon (EC) was estimated. Sampling days were categorized according to local wind direction, synoptic flow, and air mass back trajectories. Chemical mass balance (CMB) reconstruction of the following PM10 components was derived for each wind direction group and at each transect location: ammonium sulfate ((NH4)2SO4), ammonium nitrate (NH4NO3), sodium chloride (NaCl), gypsum (CaSO4), OHM, EC, soil/surface dusts, and particle-bound water. The results showed that PM10 at the coastal site was dominated by the marine background (NaCl) compared with the urban sites, which were dominated by local primary (EC and soil/resuspension) and secondary sources (NH4NO3, (NH4)2SO4, and OHM). There was evidence of Cl(-) depletion as NaCl aerosol passes over urban areas. There was also evidence of long-range transport of primary PM10 (EC and OHM); for example, at the coastal site from transport from Ireland. The work demonstrates how the general approach of combining mass reconstruction along a transect with other information such as wind/air-mass direction generates insight into the sources contributing to PM10 over a more extended spatial scale than at a single receptor.

Use of hyperspectral remote sensing reflectance for detection and assessment of the harmful alga, Karenia brevis.

We applied two numerical methods to in situ hyperspectral measurements of remote sensing reflectance Rrs to assess the feasibility of remote detection and monitoring of the toxic dinoflagellate, Karenia brevis, which has been shown to exhibit unique absorption properties. First, an existing quasi-analytical algorithm was used to invert remote sensing reflectance spectra, Rrs(lambda), to derive phytoplankton absorption spectra, a(phi)Rrs(lambda). Second, the fourth derivatives of the a(phi)Rrs(lambda) spectra were compared to the fourth derivative of a reference K. brevis absorption spectrum by means of a similarity index (SI) analysis. Comparison of reflectance-derived a(phi) with filter pad measured a(phi) found them to agree well (R2=0.891; average percentage difference, 22.8%). A strong correlation (R2=0.743) between surface cell concentration and the SI was observed, showing the potential utility of SI magnitude as an indicator of bloom strength. A sensitivity analysis conducted to investigate the effects of varying levels of cell concentrations and colored dissolved organic matter (CDOM) on the efficacy of the quasi-analytical algorithm and SI found that a(phi)Rrs(lambda) could not be derived for very low cell concentrations and that, although it is possible to derive a(phi)Rrs(lambda) in the presence of high CDOM concentrations, CDOM levels influence the a(phi)Rrs(lambda) amplitude and shape. Results suggest that detection and mapping of K. brevis blooms based on hyperspectral measurements of Rrs are feasible.