Diatoms Si uptake capacity drives carbon export in coastal upwelling systems

Coastal upwelling systems account for approximately half of global ocean primary production and contribute disproportionately to biologically driven carbon sequestration. Diatoms, silica-precipitating microalgae, constitute the dominant phytoplankton in these productive regions, and their abundance and assemblage composition in the sedimentary record is considered one of the best proxies for primary production. The study of the sedimentary diatom abundance (SDA) and total organic carbon content (TOC) in the five most important coastal upwelling systems of the modern ocean (Iberia-Canary, Benguela, Peru-Humboldt, California, and Somalia-Oman) reveals a global-scale positive relationship between diatom production and organic carbon burial. The analysis of SDA in conjunction with environmental variables of coastal upwelling systems such as upwelling strength, satellite-derived net primary production, and surface water nutrient concentrations shows different relations between SDA and primary production on the regional scale. On the global scale, SDA appears modulated by the capacity of diatoms to take up silicic acid, which ultimately sets an upper limit to global export production in these ocean regions

Factors controlling the community structure of picoplankton in contrasting marine environments

The effect of inorganic nutrients on planktonic assemblages has traditionally relied on concentrations rather than estimates of nutrient supply. We combined a novel dataset of hydrographic properties, turbulent mixing, nutrient concentration, and picoplankton community composition with the aims of (i) quantifying the role of temperature, light, and nitrate fluxes as factors controlling the distribution of autotrophic and heterotrophic picoplankton subgroups, as determined by flow cytometry, and (ii) describing the ecological niches of the various components of the picoplankton community. Data were collected at 97 stations in the Atlantic Ocean, including tropical and subtropical open-ocean waters, the northwestern Mediterranean Sea, and the Galician coastal upwelling system of the northwest Iberian Peninsula. A generalized additive model (GAM) approach was used to predict depth-integrated biomass of each picoplankton subgroup based on three niche predictors: sea surface temperature, averaged daily surface irradiance, and the transport of nitrate into the euphotic zone, through both diffusion and advection. In addition, niche overlap among different picoplankton subgroups was computed using nonparametric kernel density functions. Temperature and nitrate supply were more relevant than light in predicting the biomass of most picoplankton subgroups, except for Prochlorococcus and low-nucleic-acid (LNA) prokaryotes, for which irradiance also played a significant role. Nitrate supply was the only factor that allowed the distinction among the ecological niches of all autotrophic and heterotrophic picoplankton subgroups. Prochlorococcus and LNA prokaryotes were more abundant in warmer waters ( \u3e 20°C) where the nitrate fluxes were low, whereas Synechococcus and high-nucleic-acid (HNA) prokaryotes prevailed mainly in cooler environments characterized by intermediate or high levels of nitrate supply. Finally, the niche of picoeukaryotes was defined by low temperatures and high nitrate supply. These results support the key role of nitrate supply, as it not only promotes the growth of large phytoplankton, but it also controls the structure of marine picoplankton communities

Ocean kinetic energy and photosynthetic biomass are important drivers of planktonic foraminigera diversity in the Atlantic Ocean

It is hypothesized and tested for the first time, that the large-scale diversity patterns of foraminifera communities are determined by sea surface temperature (ISST, representing energy), Chl-a (a surrogate for photosynthetic biomass) and ocean kinetic energy (as EKE). Alpha diversity was estimated using species richness (S), Shannon Wiener index (H), and Simpson evenness (E), and mapped using geostatistical approaches. Beta diversity was studied through species turnover using gradient forest analysis (59% of the variation). The geographic location of the transition between the four main biogeographic zones was redefined based on the results of beta diversity analysis and incorporating the new datasets, identifying the major marine latitudinal gradients, the most important upwelling areas (Benguela Current, Canary Current), the Equatorial divergence, and the subtropical fronts (Gulf Stream-North Atlantic Drift path in the north and the South Atlantic current in the south). We provide statistical proof that energy (SST), food supply (Chl-a), and currents (EKE) are the main environmental drivers shaping planktonic foraminifera diversity in the Atlantic ocean and define the associated thresholds for species change on those variables.info:eu-repo/semantics/publishedVersio

Dimensions of marine phytoplankton diversity

Biodiversity of phytoplankton is important for ecosystem stability and marine biogeochemistry. However, the large-scale patterns of diversity are not well understood and are often poorly characterized in terms of statistical relationships with factors such as latitude, temperature and productivity. Here we use ecological theory and a global trait-based ecosystem model to provide mechanistic understanding of patterns of phytoplankton diversity. Our study suggests that phytoplankton diversity across three dimensions of trait space (size, biogeochemical function and thermal tolerance) is controlled by disparate combinations of drivers: the supply rate of the limiting resource, the imbalance in different resource supplies relative to competing phytoplankton demands, size-selective grazing and transport by the moving ocean. Using sensitivity studies we show that each dimension of diversity is controlled by different drivers. Models including only one (or two) of the trait dimensions will have different patterns of diversity than one which incorporates another trait dimension. We use the results of our model exploration to infer the controls on the diversity patterns derived from field observations along meridional transects in the Atlantic and to explain why different taxa and size classes have differing patterns.NASA (Grant NNX16AR47G

Dimensions of marine phytoplankton diversity

Biodiversity of phytoplankton is important for ecosystem stability and marine biogeochemistry. However, the large-scale patterns of diversity are not well understood and are often poorly characterized in terms of statistical relationships with factors such as latitude, temperature and productivity. Here we use ecological theory and a global trait-based ecosystem model to provide mechanistic understanding of patterns of phytoplankton diversity. Our study suggests that phytoplankton diversity across three dimensions of trait space (size, biogeochemical function and thermal tolerance) is controlled by disparate combinations of drivers: the supply rate of the limiting resource, the imbalance in different resource supplies relative to competing phytoplankton demands, size-selective grazing and transport by the moving ocean. Using sensitivity studies we show that each dimension of diversity is controlled by different drivers. Models including only one (or two) of the trait dimensions will have different patterns of diversity than one which incorporates another trait dimension. We use the results of our model exploration to infer the controls on the diversity patterns derived from field observations along meridional transects in the Atlantic and to explain why different taxa and size classes have differing patterns

SYN-MAD 2022: Competition on Face Morphing Attack Detection Based on Privacy-aware Synthetic Training Data

This paper presents a summary of the Competition on Face Morphing Attack Detection Based on Privacy-aware Synthetic Training Data (SYN-MAD) held at the 2022 International Joint Conference on Biometrics (IJCB 2022). The competition attracted a total of 12 participating teams, both from academia and industry and present in 11 different countries. In the end, seven valid submissions were submitted by the participating teams and evaluated by the organizers. The competition was held to present and attract solutions that deal with detecting face morphing attacks while protecting people’s privacy for ethical and legal reasons. To ensure this, the training data was limited to synthetic data provided by the organizers. The submitted solutions presented innovations that led to outperforming the considered baseline in many experimental settings. The evaluation benchmark is now available at: https://github.com/marcohuber/SYN-MAD-2022