Susanne E. Craig

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 Bannisters 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 Bannisters 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.

Abstract Concurrent 24-hr samples of particulate matter of median aerodynamic diameter less than 10 µm (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 (Ca2+), 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 com ponents 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.

A novel statistical approach for ocean colour estimation of inherent optical properties and cyanobacteria abundance in optically complex waters

Eutrophication is an increasing problem in coastal waters of the Baltic Sea. Moreover, algal blooms, which occur every summer in the Gulf of Gdansk can deleteriously impact human health, the aquatic environment, and economically important fisheries, tourism, and recreation industries. Traditional laboratory-based techniques for water monitoring are expensive and time consuming, which usually results in limited numbers of observations and discontinuity in space and time. The use of hyperspectral radiometers for coastal water observation provides the potential for more detailed remote optical monitoring. A statistical approach to develop local models for the estimation of optically significant components from in situ measured hyperspectral remote sensing reflectance in case 2 waters is presented in this study. The models, which are based on empirical orthogonal function (EOF) analysis and stepwise multilinear regression, allow for the estimation of parameters strongly correlated with phytoplankton (pigment concentration, absorption coefficient) and coloured detrital matter abundance (absorption coefficient) directly from reflectance spectra measured in situ. Chlorophyll a concentration, which is commonly used as a proxy for phytoplankton biomass, was retrieved with low error (median percent difference, MPD = 17%, root mean square error RMSE = 0.14 in log10 space) and showed a high correlation with chlorophyll a measured in situ (R = 0.84). Furthermore, phycocyanin and phycoerythrin, both characteristic pigments for cyanobacteria species, were also retrieved reliably from reflectance with MPD = 23%, RMSE = 0.23, R2 = 0.77 and MPD = 24%, RMSE = 0.15, R2 = 0.74, respectively. The EOF technique proved to be accurate in the derivation of the absorption spectra of phytoplankton and coloured detrital matter (CDM), with R2 (?) above 0.83 and RMSE around 0.10. The approach was also applied to satellite multispectral remote sensing reflectance data, thus allowing for improved temporal and spatial resolution compared with the in situ measurements. The EOF method tested on simulated Medium Resolution Imaging Spectrometer (MERIS) or Ocean and Land Colour Instrument (OLCI) data resulted in RMSE = 0.16 for chl-a and RMSE = 0.29 for phycocyanin. The presented methods, applied to both in situ and satellite data, provide a powerful tool for coastal monitoring and management.

Chlorophyll-a Concentration Retrieval in the Optically Complex Waters of the St. Lawrence Estuary and Gulf Using Principal Component Analysis

Empirical methods based on band ratios to infer chlorophyll-a concentration by satellite do not perform well over the optically complex waters of the St. Lawrence Estuary and Gulf. Using a dataset of 93 match-ups, we explore an alternative method relying on empirical orthogonal functions (EOF) to develop an algorithm that relates the satellite-derived remote sensing reflectances to in situ chlorophyll-a concentration for the Sea-viewing Wide Field-of-view Sensor (SeaWiFS). Results show that an accuracy of 41% at retrieving chlorophyll-a concentration can be reached using the EOF method compared to 140% for the widely-used Ocean Chlorophyll 4 (OC4v4) empirical algorithm, 53% for the Garver-Siegel-Maritorena (GSM01) and 54% for the Generalized Inherent Optical Property (GIOP) semi-analytical algorithms. This result is possible because the EOF approach is able to extract region-specific radiometric features from the satellite remote sensing reflectances that are related to absorption properties of optical components (water, coloured dissolved organic matter and chlorophyll-a) using the visible SeaWiFS channels. The method could easily be used with other ocean-colour satellite sensors (e.g., MODIS, MERIS, VIIRS, OLCI) to extend the time series for the St. Lawrence Estuary and Gulf waters.