• Energy Research

Quantitative assessment of the UV effects on aquatic ecosystems requires an estimate of the in-water radiation field. Actual ocean UV reflectances are needed for improving the total ozone retrievals from the total ozone mapping spectrometer (TOMS) and the ozone monitoring instrument (OMI) flown on NASA's Aura satellite. The estimate of underwater UV radiation can be done on the basis of measurements from the TOMS/OMI and full models of radiative transfer (RT) in the atmosphere-ocean system. The Hydrolight code, modified for extension to the UV, is used for the generation of look-up tables for in-water irradiances. A look-up table for surface radiances generated with a full RT code is input for the Hydrolight simulations. A model of seawater inherent optical properties (IOPs) is an extension of the Case 1 water model to the UV. A new element of the IOP model is parameterization of particulate matter absorption based on recent in situ data. A chlorophyll product from ocean color sensors is input for the IOP model. Verification of the in-water computational scheme shows that the calculated diffuse attenuation coefficient Kd is in good agreement with the measured Kd.

Quantitative assessment of the UV effects on aquatic ecosystems requires an estimate of the in-water radiation field. Actual ocean UV reflectances are needed for improving the total ozone retrievals from the total ozone mapping spectrometer (TOMS) and the ozone monitoring instrument (OMI) flown on NASA's Aura satellite. The estimate of underwater UV radiation can be done on the basis of measurements from the TOMS/OMI and full models of radiative transfer (RT) in the atmosphere-ocean system. The Hydrolight code, modified for extension to the UV, is used for the generation of look-up tables for in-water irradiances. A look-up table for surface radiances generated with a full RT code is input for the Hydrolight simulations. A model of seawater inherent optical properties (IOPs) is an extension of the Case 1 water model to the UV. A new element of the IOP model is parameterization of particulate matter absorption based on recent in situ data. A chlorophyll product from ocean color sensors is input for the IOP model. Verification of the in-water computational scheme shows that the calculated diffuse attenuation coefficient Kd is in good agreement with the measured Kd.

SummaryPhotoacclimation consists of short‐ and long‐term strategies used by photosynthetic organisms to adapt to dynamic light environments. Observable photophysiology changes resulting from these strategies have been used in coarse‐grained models to predict light‐dependent growth and photosynthetic rates. However, the contribution of the broader metabolic network, relevant to species‐specific strategies and fitness, is not accounted for in these simple models.We incorporated photophysiology experimental data with genome‐scale modeling to characterize organism‐level, light‐dependent metabolic changes in the model diatomPhaeodactylum tricornutum. Oxygen evolution and photon absorption rates were combined with condition‐specific biomass compositions to predict metabolic pathway usage for cells acclimated to four different light intensities.Photorespiration, an ornithine‐glutamine shunt, and branched‐chain amino acid metabolism were hypothesized as the primary intercompartment reductant shuttles for mediating excess light energy dissipation. Additionally, simulations suggested that carbon shunted through photorespiration is recycled back to the chloroplast as pyruvate, a mechanism distinct from known strategies in photosynthetic organisms.Our results suggest a flexible metabolic network inP. tricornutumthat tunes intercompartment metabolism to optimize energy transport between the organelles, consuming excess energy as needed. Characterization of these intercompartment reductant shuttles broadens our understanding of energy partitioning strategies in this clade of ecologically important primary producers.

SummaryPhotoacclimation consists of short‐ and long‐term strategies used by photosynthetic organisms to adapt to dynamic light environments. Observable photophysiology changes resulting from these strategies have been used in coarse‐grained models to predict light‐dependent growth and photosynthetic rates. However, the contribution of the broader metabolic network, relevant to species‐specific strategies and fitness, is not accounted for in these simple models.We incorporated photophysiology experimental data with genome‐scale modeling to characterize organism‐level, light‐dependent metabolic changes in the model diatomPhaeodactylum tricornutum. Oxygen evolution and photon absorption rates were combined with condition‐specific biomass compositions to predict metabolic pathway usage for cells acclimated to four different light intensities.Photorespiration, an ornithine‐glutamine shunt, and branched‐chain amino acid metabolism were hypothesized as the primary intercompartment reductant shuttles for mediating excess light energy dissipation. Additionally, simulations suggested that carbon shunted through photorespiration is recycled back to the chloroplast as pyruvate, a mechanism distinct from known strategies in photosynthetic organisms.Our results suggest a flexible metabolic network inP. tricornutumthat tunes intercompartment metabolism to optimize energy transport between the organelles, consuming excess energy as needed. Characterization of these intercompartment reductant shuttles broadens our understanding of energy partitioning strategies in this clade of ecologically important primary producers.

Microalgae biorefinery systems have been extensively studied from the perspective of resources, energy expenditure, biofuel production potential, and high-added value products. The genus Spirulina (Arthrospira) stands out among the microalgae of commercial importance. It accounts for over 30% of biomass produced globally because of high protein concentration and, carotenoid and phycocyanin content. Spirulina cultivation can be used to reduce greenhouse gases and for effluent treatment. Furthermore, its cellular morphology facilitates biomass recovery, which contributes to the process cost reduction. Spirulina biomass is widely applicable in food, feed, cosmetics, biofertilizers, biofuels, and biomaterials. A feasibility analysis of Spirulina biorefinery would provide specific information for the decision-making for the improvement of the Spirulina production process. In that context, this review aimed to present a parameter assessment to contribute to the economic viability of Spirulina production in a biorefinery system.

Microalgae biorefinery systems have been extensively studied from the perspective of resources, energy expenditure, biofuel production potential, and high-added value products. The genus Spirulina (Arthrospira) stands out among the microalgae of commercial importance. It accounts for over 30% of biomass produced globally because of high protein concentration and, carotenoid and phycocyanin content. Spirulina cultivation can be used to reduce greenhouse gases and for effluent treatment. Furthermore, its cellular morphology facilitates biomass recovery, which contributes to the process cost reduction. Spirulina biomass is widely applicable in food, feed, cosmetics, biofertilizers, biofuels, and biomaterials. A feasibility analysis of Spirulina biorefinery would provide specific information for the decision-making for the improvement of the Spirulina production process. In that context, this review aimed to present a parameter assessment to contribute to the economic viability of Spirulina production in a biorefinery system.

Global climate change and other anthropogenic stressors have heightened the need to rapidly characterize ecological changes in marine benthic communities across large scales. Digital photography enables rapid collection of survey images to meet this need, but the subsequent image annotation is typically a time consuming, manual task. We investigated the feasibility of using automated point-annotation to expedite cover estimation of the 17 dominant benthic categories from survey-images captured at four Pacific coral reefs. Inter- and intra- annotator variability among six human experts was quantified and compared to semi- and fully- automated annotation methods, which are made available at coralnet.ucsd.edu. Our results indicate high expert agreement for identification of coral genera, but lower agreement for algal functional groups, in particular between turf algae and crustose coralline algae. This indicates the need for unequivocal definitions of algal groups, careful training of multiple annotators, and enhanced imaging technology. Semi-automated annotation, where 50% of the annotation decisions were performed automatically, yielded cover estimate errors comparable to those of the human experts. Furthermore, fully-automated annotation yielded rapid, unbiased cover estimates but with increased variance. These results show that automated annotation can increase spatial coverage and decrease time and financial outlay for image-based reef surveys.