Uncertainty in ocean-color estimates of chlorophyll for phytoplankton groups

This is the final version. Available from Frontiers Media via the DOI in this record.Over the past decade, techniques have been presented to derive the community structure of phytoplankton at synoptic scales using satellite ocean-color data. There is a growing demand from the ecosystem modeling community to use these products for model evaluation and data assimilation. Yet, from the perspective of an ecosystem modeler these products are of limited use unless: (i) the phytoplankton products provided by the remote-sensing community match those required by the ecosystem modelers; and (ii) information on per-pixel uncertainty is provided to evaluate data quality. Using a large dataset collected in the North Atlantic, we re-tune a method to estimate the chlorophyll concentration of three phytoplankton groups, partitioned according to size [pico- (20 μm)]. The method is modified to account for the influence of sea surface temperature, also available from satellite data, on model parameters and on the partitioning of microphytoplankton into diatoms and dinoflagellates, such that the phytoplankton groups provided match those simulated in a state of the art marine ecosystem model (the European Regional Seas Ecosystem Model, ERSEM). The method is validated using another dataset, independent of the data used to parameterize the method, of more than 800 satellite and in situ match-ups. Using fuzzy-logic techniques for deriving per-pixel uncertainty, developed within the ESA Ocean Colour Climate Change Initiative (OC-CCI), the match-up dataset is used to derive the root mean square error and the bias between in situ and satellite estimates of the chlorophyll for each phytoplankton group, for 14 different optical water types (OWT). These values are then used with satellite estimates of OWTs to map uncertainty in chlorophyll on a per pixel basis for each phytoplankton group. It is envisaged these satellite products will be useful for those working on the validation of, and assimilation of data into, marine ecosystem models that simulate different phytoplankton groups.National Centre for Earth Observation (NCEO)European Space Agency (ESA)NERC-UK ECOMA

Uncertainty in ocean-colour estimates of chlorophyll for phytoplankton groups

Over the past decade, techniques have been presented to derive the community structure of phytoplankton at synoptic scales using satellite ocean-color data. There is a growing demand from the ecosystem modeling community to use these products for model evaluation and data assimilation. Yet, from the perspective of an ecosystem modeler these products are of limited use unless: (i) the phytoplankton products provided by the remote-sensing community match those required by the ecosystem modelers; and (ii) information on per-pixel uncertainty is provided to evaluate data quality. Using a large dataset collected in the North Atlantic, we re-tune a method to estimate the chlorophyll concentration of three phytoplankton groups, partitioned according to size [pico- (20 μm)]. The method is modified to account for the influence of sea surface temperature, also available from satellite data, on model parameters and on the partitioning of microphytoplankton into diatoms and dinoflagellates, such that the phytoplankton groups provided match those simulated in a state of the art marine ecosystem model (the European Regional Seas Ecosystem Model, ERSEM). The method is validated using another dataset, independent of the data used to parameterize the method, of more than 800 satellite and in situ match-ups. Using fuzzy-logic techniques for deriving per-pixel uncertainty, developed within the ESA Ocean Colour Climate Change Initiative (OC-CCI), the match-up dataset is used to derive the root mean square error and the bias between in situ and satellite estimates of the chlorophyll for each phytoplankton group, for 14 different optical water types (OWT). These values are then used with satellite estimates of OWTs to map uncertainty in chlorophyll on a per pixel basis for each phytoplankton group. It is envisaged these satellite products will be useful for those working on the validation of, and assimilation of data into, marine ecosystem models that simulate different phytoplankton groups

Agronomic and environmental implications of using a By-Product of the Intermediate Tanning Processes as Nitrogen Fertilizer

ABSTRACT Nitrogen (N) is an important nutrient for agriculture, and Brazil is heavily dependent on N imports. A by-product of the intermediate processes of tanning (BPIPT) may be used as an N fertilizer which will reduce this dependency, but its chromium (Cr) content is a matter of concern. This work assessed Cr (III, VI) and N (total, inorganic) contents in four soil samples with contrasting characteristics (especially with respect to their content of manganese (Mn), a potential Cr(III) oxidant), following the addition of the BPIPT. Chemical and microbiological indicators of soil quality were measured to assess the agronomic and environmental implications of the BPIPT addition in Brazilian soils. Our results indicate that the BPIPT is a promising source of N. The originally available Mn content in the soil did not influence the effect of the BPIPT on soil Cr(VI) content. Finally, microbial activity was generally stimulated after BPIPT addition to the soil. This information is relevant because: 1) it shows that the beneficial use of the BPIPT as an N fertilizer is important for adding value to a by-product with agronomic potential; and 2) it indicates that, at the dosage of the BPIPT used in this study (2.5 g kgsoil−1), the typical increases in the soil concentration of labile Cr (0–25 mg kgsoil−1) and Cr(VI) (0–0.8 mg kgsoil−1) due to the application of the BPIPT are not detrimental to biological activity in the soil. However, further investigations are still necessary to evaluate the mobility of these Cr species in the soil and possible risks of groundwater contamination, which were not addressed in this study

Sensing the ocean biological carbon pump from space: A review of capabilities, concepts, research gaps and future developments

The element carbon plays a central role in climate and life on Earth. It is capable of moving among the geosphere, cryosphere, atmosphere, biosphere and hydrosphere. This flow of carbon is referred to as the Earth’s carbon cycle. It is also intimately linked to the cycling of other elements and compounds. The ocean plays a fundamental role in Earth’s carbon cycle, helping to regulate atmospheric CO2 concentration. The ocean biological carbon pump (OBCP), defined as a set of processes that transfer organic carbon from the surface to the deep ocean, is at the heart of the ocean carbon cycle. Monitoring the OBCP is critical to understanding how the Earth’s carbon cycle is changing. At present, satellite remote sensing is the only tool available for viewing the entire surface ocean at high temporal and spatial scales. In this paper, we review methods for monitoring the OBCP with a focus on satellites. We begin by providing an overview of the OBCP, defining and describing the pools of carbon in the ocean, and the processes controlling fluxes of carbon between the pools, from the surface to the deep ocean, and among ocean, land and atmosphere. We then examine how field measurements, from ship and autonomous platforms, complement satellite observations, provide validation points for satellite products and lead to a more complete view of the OBCP than would be possible from satellite observations alone. A thorough analysis is then provided on methods used for monitoring the OBCP from satellite platforms, covering current capabilities, concepts and gaps, and the requirement for uncertainties in satellite products. We finish by discussing the potential for producing a satellite-based carbon budget for the oceans, the advantages of integrating satellite-based observations with ecosystem models and field measurements, and future opportunities in space, all with a view towards bringing satellite observations into the limelight of ocean carbon research

Fungal endophytes from arid areas of Andalusia: high potential sources for antifungal and antitumoral agents

Native plant communities from arid areas present distinctive characteristics to survive in extreme conditions. The large number of poorly studied endemic plants represents a unique potential source for the discovery of novel fungal symbionts as well as host-specific endophytes not yet described. The addition of adsorptive polymeric resins in fungal fermentations has been seen to promote the production of new secondary metabolites and is a tool used consistently to generate new compounds with potential biological activities. A total of 349 fungal strains isolated from 63 selected plant species from arid ecosystems located in the southeast of the Iberian Peninsula, were characterized morphologically as well as based on their ITS/28S ribosomal gene sequences. The fungal community isolated was distributed among 19 orders including Basidiomycetes and Ascomycetes, being Pleosporales the most abundant order. In total, 107 different genera were identified being Neocamarosporium the genus most frequently isolated from these plants, followed by Preussia and Alternaria. Strains were grown in four different media in presence and absence of selected resins to promote chemical diversity generation of new secondary metabolites. Fermentation extracts were evaluated, looking for new antifungal activities against plant and human fungal pathogens, as well as, cytotoxic activities against the human liver cancer cell line HepG2. From the 349 isolates tested, 126 (36%) exhibited significant bioactivities including 58 strains with exclusive antifungal properties and 33 strains with exclusive activity against the HepG2 hepatocellular carcinoma cell line. After LCMS analysis, 68 known bioactive secondary metabolites could be identified as produced by 96 strains, and 12 likely unknown compounds were found in a subset of 14 fungal endophytes. The chemical profiles of the differential expression of induced activities were compared. As proof of concept, ten active secondary metabolites only produced in the presence of resins were purified and identified. The structures of three of these compounds were new and herein are elucidated.This work was supported by Fundación MEDINA and the Andalusian Government grant RNM-7987 ‘Sustainable use of plants and their fungal parasites from arid regions of Andalucía for new molecules useful for antifungals and neuroprotectors’

Satellite Ocean Colour: Current Status and Future Perspective

Spectrally resolved water-leaving radiances (ocean colour) and inferred chlorophyll concentration are key to studying phytoplankton dynamics at seasonal and interannual scales, for a better understanding of the role of phytoplankton in marine biogeochemistry; the global carbon cycle; and the response of marine ecosystems to climate variability, change and feedback processes. Ocean colour data also have a critical role in operational observation systems monitoring coastal eutrophication, harmful algal blooms, and sediment plumes. The contiguous ocean-colour record reached 21 years in 2018; however, it is comprised of a number of one-off missions such that creating a consistent time-series of ocean-colour data requires merging of the individual sensors (including MERIS, Aqua-MODIS, SeaWiFS, VIIRS, and OLCI) with differing sensor characteristics, without introducing artefacts. By contrast, the next decade will see consistent observations from operational ocean colour series with sensors of similar design and with a replacement strategy. Also, by 2029 the record will start to be of sufficient duration to discriminate climate change impacts from natural variability, at least in some regions. This paper describes the current status and future prospects in the field of ocean colour focusing on large to medium resolution observations of oceans and coastal seas. It reviews the user requirements in terms of products and uncertainty characteristics and then describes features of current and future satellite ocean-colour sensors, both operational and innovative. The key role of in situ validation and calibration is highlighted as are ground segments that process the data received from the ocean-colour sensors and deliver analysis-ready products to end-users. Example applications of the ocean-colour data are presented, focusing on the climate data record and operational applications including water quality and assimilation into numerical models. Current capacity building and training activities pertinent to ocean colour are described and finally a summary of future perspectives is provided

ANCA-associated vasculitis.

The anti-neutrophil cytoplasmic antibody (ANCA)-associated vasculitides (AAVs) are a group of disorders involving severe, systemic, small-vessel vasculitis and are characterized by the development of autoantibodies to the neutrophil proteins leukocyte proteinase 3 (PR3-ANCA) or myeloperoxidase (MPO-ANCA). The three AAV subgroups, namely granulomatosis with polyangiitis (GPA), microscopic polyangiitis and eosinophilic GPA (EGPA), are defined according to clinical features. However, genetic and other clinical findings suggest that these clinical syndromes may be better classified as PR3-positive AAV (PR3-AAV), MPO-positive AAV (MPO-AAV) and, for EGPA, by the presence or absence of ANCA (ANCA+ or ANCA-, respectively). Although any tissue can be involved in AAV, the upper and lower respiratory tract and kidneys are most commonly and severely affected. AAVs have a complex and unique pathogenesis, with evidence for a loss of tolerance to neutrophil proteins, which leads to ANCA-mediated neutrophil activation, recruitment and injury, with effector T cells also involved. Without therapy, prognosis is poor but treatments, typically immunosuppressants, have improved survival, albeit with considerable morbidity from glucocorticoids and other immunosuppressive medications. Current challenges include improving the measures of disease activity and risk of relapse, uncertainty about optimal therapy duration and a need for targeted therapies with fewer adverse effects. Meeting these challenges requires a more detailed knowledge of the fundamental biology of AAV as well as cooperative international research and clinical trials with meaningful input from patients

Content and performance of the MiniMUGA genotyping array: A new tool to improve rigor and reproducibility in mouse research

The laboratory mouse is the most widely used animal model for biomedical research, due in part to its well-annotated genome, wealth of genetic resources, and the ability to precisely manipulate its genome. Despite the importance of genetics for mouse research, genetic quality control (QC) is not standardized, in part due to the lack of cost-effective, informative, and robust platforms. Genotyping arrays are standard tools for mouse research and remain an attractive alternative even in the era of high-throughput whole-genome sequencing. Here, we describe the content and performance of a new iteration of the Mouse Universal Genotyping Array (MUGA), MiniMUGA, an array-based genetic QC platform with over 11,000 probes. In addition to robust discrimination between most classical and wild-derived laboratory strains, MiniMUGA was designed to contain features not available in other platforms: (1) chromosomal sex determination, (2) discrimination between substrains from multiple commercial vendors, (3) diagnostic SNPs for popular laboratory strains, (4) detection of constructs used in genetically engineered mice, and (5) an easy-to-interpret report summarizing these results. In-depth annotation of all probes should facilitate custom analyses by individual researchers. To determine the performance of MiniMUGA, we genotyped 6899 samples from a wide variety of genetic backgrounds. The performance of MiniMUGA compares favorably with three previous iterations of the MUGA family of arrays, both in discrimination capabilities and robustness. We have generated publicly available consensus genotypes for 241 inbred strains including classical, wild-derived, and recombinant inbred lines. Here, we also report the detection of a substantial number of XO and XXY individuals across a variety of sample types, new markers that expand the utility of reduced complexity crosses to genetic backgrounds other than C57BL/6, and the robust detection of 17 genetic constructs. We provide preliminary evidence that the array can be used to identify both partial sex chromosome duplication and mosaicism, and that diagnostic SNPs can be used to determine how long inbred mice have been bred independently from the relevant main stock. We conclude that MiniMUGA is a valuable platform for genetic QC, and an important new tool to increase the rigor and reproducibility of mouse research

Copernicus Marine Service ocean state report, issue 4

This is the final version. Available from Taylor & Francis via the DOI in this record. FCT/MCTE