Mixotrophic uptake of organic compounds by coccolithophores

Osmotrophy is one of the main modes of mixotrophic acquisition of carbon by phytoplankton, but historically it has been under‐investigated and its physiological and ecological relevance remains poorly understood. Here, we investigate osmotrophy in coccolithophores. Coccolithophores are one of the major contributors to the ocean biomass inhabiting both euphotic and subeuphotic depths in the marine environment. Coccolithophores demonstrate the potential to utilize a wide array of organic compounds in darkness. In experiments with BioLog Ecoplates, we screened a wide array of organic compounds as potential carbon sources, and observed that the major types of organic compounds taken up by coccolithophores were primarily carbohydrates along with a few amino acids and polymers. Furthermore, in subsequent radiotracer experiments, the uptake rates of 14C‐labeled dissolved organic carbon compounds in the dark were low relative to the maximal rates of photosynthetic carbon fixation in the light. The time course of uptake for some compounds suggests constitutive capacity for their transport, while for others the transport appears to be activated. Nonetheless, the collective slow uptake rate of a large array of organic compounds found in seawater, might be the only way that osmotrophy could fuel significant coccolithophore growth in the deep euphotic and subeuphotic zones in the sea

A new methodology to assess the performance and uncertainty of source apportionment models II: The results of two European intercomparison exercises

The performance and the uncertainty of receptor models (RMs) were assessed in intercomparison exercises employing real-world and synthetic input datasets. To that end, the results obtained by different practitioners using ten different RMs were compared with a reference. In order to explain the differences in the performances and uncertainties of the different approaches, the apportioned mass, the number of sources, the chemical profiles, the contribution-to-species and the time trends of the sources were all evaluated using the methodology described in Belis et al. (2015). In this study, 87% of the 344 source contribution estimates (SCEs) reported by participants in 47 different source apportionment model results met the 50% standard uncertainty quality objective established for the performance test. In addition, 68% of the SCE uncertainties reported in the results were coherent with the analytical uncertainties in the input data. The most used models, EPA-PMF v.3, PMF2 and EPA-CMB 8.2, presented quite satisfactory performances in the estimation of SCEs while unconstrained models, that do not account for the uncertainty in the input data (e.g. APCS and FA-MLRA), showed below average performance. Sources with well-defined chemical profiles and seasonal time trends, that make appreciable contributions (>10%), were those better quantified by the models while those with contributions to the PM mass close to 1% represented a challenge. The results of the assessment indicate that RMs are capable of estimating the contribution of the major pollution source categories over a given time window with a level of accuracy that is in line with the needs of air quality management

Evaluation of receptor and chemical transport models for PM10 source apportionment

In this study, the performance of two types of source apportionment models was evaluated by assessing the results provided by 40 different groups in the framework of an intercomparison organised by FAIRMODE WG3 (Forum for air quality modelling in Europe, Working Group 3). The evaluation was based on two performance indicators: z-scores and the root mean square error weighted by the reference uncertainty (RMSEu), with pre-established acceptability criteria. By involving models based on completely different and independent input data, such as receptor models (RMs) and chemical transport models (CTMs), the intercomparison provided a unique opportunity for their cross-validation. In addition, comparing the CTM chemical profiles with those measured directly at the source contributed to corroborate the consistency of the tested model results. The most commonly used RM was the US EPA- PMF version 5. RMs showed very good performance for the overall dataset (91% of z-scores accepted) while more difficulties were observed with the source contribution time series (72% of RMSEu accepted). Industrial activities proved to be the most difficult sources to be quantified by RMs, with high variability in the estimated contributions. In the CTMs, the sum of computed source contributions was lower than the measured gravimetric PM10 mass concentrations. The performance tests pointed out the differences between the two CTM approaches used for source apportionment in this study: brute force (or emission reduction impact) and tagged species methods. The sources meeting the z-score and RMSEu acceptability criteria tests were 50% and 86%, respectively. The CTM source contributions to PM10 were in the majority of cases lower than the RM averages for the corresponding source. The CTMs and RMs source contributions for the overall dataset were more comparable (83% of the z-scores accepted) than their time series (successful RMSEu in the range 25% - 34%). The comparability between CTMs and RMs varied depending on the source: traffic/exhaust and industry were the source categories with the best results in the RMSEu tests while the most critical ones were soil dust and road dust. The differences between RMs and CTMs source reconstructions confirmed the importance of cross validating the results of these two families of models

Results of the first European Source Apportionment intercomparison for Receptor and Chemical Transport Models

In this study, the performance of the source apportionment model applications were evaluated by comparing the model results provided by 44 participants adopting a methodology based on performance indicators: z-scores and RMSEu, with pre-established acceptability criteria. Involving models based on completely different and independent input data, such as receptor models (RMs) and chemical transport models (CTMs), provided a unique opportunity to cross-validate them. In addition, comparing the modelled source chemical profiles, with those measured directly at the source contributed to corroborate the chemical profile of the tested model results. The most used RM was EPA- PMF5. RMs showed very good performance for the overall dataset (91% of z-scores accepted) and more difficulties are observed with SCE time series (72% of RMSEu accepted). Industry resulted the most problematic source for RMs due to the high variability among participants. Also the results obtained with CTMs were quite comparable to their ensemble reference using all models for the overall average (>92% of successful z-scores) while the comparability of the time series is more problematic (between 58% and 77% of the candidates’ RMSEu are accepted). In the CTM models a gap was observed between the sum of source contributions and the gravimetric PM10 mass likely due to PM underestimation in the base case. Interestingly, when only the tagged species CTM results were used in the reference, the differences between the two CTM approaches (brute force and tagged species) were evident. In this case the percentage of candidates passing the z-score and RMSEu tests were only 50% and 86%, respectively. CTMs showed good comparability with RMs for the overall dataset (83% of the z-scores accepted), more differences were observed when dealing with the time series of the single source categories. In this case the share of successful RMSEu was in the range 25% - 34%.JRC.C.5-Air and Climat

Living on Cold Substrata: New Insights and Approaches in the Study of Microphytobenthos Ecophysiology and Ecology in Kongsfjorden

Organisms in shallow waters at high latitudes are under pressure due to climate change. These areas are typically inhabited by microphytobenthos (MPB) communities, composed mainly of diatoms. Only sparse information is available on the ecophysiology and acclimation processes within MPBs from Arctic regions. The physico-chemical environment and the ecology and ecophysiology of benthic diatoms in Kongsfjorden (Svalbard, Norway) are addressed in this review. MPB biofilms cover extensive areas of sediment. They show high rates of primary production, stabilise sediment surfaces against erosion under hydrodynamic forces,and affect the exchange of oxygen and nutrients across the sediment-water interface. Additionally, this phototrophic community represents a key component in the functioning of the Kongsfjorden trophic web, particularly as a major food source for benthic suspension- or deposit-feeders. MPB in Kongsfjorden is confronted with pronounced seasonal variations in solar radiation, low temperatures, and hyposaline (meltwater) conditions in summer, as well as long periods of ice and snow cover in winter. From the few data available, it seems that these organisms can easily cope with these environmental extremes. The underlying physiological mechanisms that allow growth and photosynthesis to continue under widely varying abiotic parameters, along with vertical migration and heterotrophy, and biochemical features such as a pronounced fatty-acid metabolism and silicate incorporation are discussed. Existing gaps in our knowledge of benthic diatoms in Kongsfjorden, such as the chemical ecology of biotic interactions, need to be filled. In addition, since many of the underlying molecular acclimation mechanisms are poorly understood, modern approaches based on transcriptomics, proteomics, and/or metabolomics, in conjunction with cell biological and biochemical techniques, are urgently needed. Climate change models for the Arctic predict other multifactorial stressors, such as an increase in precipitation and permafrost thawing, with consequences for the shallow-water regions. Both precipitation and permafrost thawing are likely to increase nutrient-enriched, turbid freshwater runoff and may locally counteract the expected increase in coastal radiation availability. So far, complex interactions among factors, as well as the full genetic diversity and physiological plasticity of Arctic benthic diatoms, have only rarely been considered. The limited existing information is described and discussed in this review