Substantial energy input to the mesopelagic ecosystem from the seasonal mixed-layer pump

This is the author accepted manuscript. The final version is available from Nature Research via the DOI in this record.The ocean region known as the mesopelagic zone, which is at depths of about 100-1,000 m, harbours one of the largest ecosystems and fish stocks on the planet. Life in this region is believed to rely on particulate organic carbon supplied by the biological carbon pump. Yet this supply appears insufficient to meet mesopelagic metabolic demands. An additional organic carbon source to the mesopelagic zone could be provided by the seasonal entrainment of surface waters in deeper layers, a process known as the mixed-layer pump. Little is known about the magnitude and spatial distribution of this process globally or its potential to transport carbon to the mesopelagic zone. Here we combine mixed-layer depth data from Argo floats with satellite estimates of particulate organic carbon concentrations to show that the mixed-layer pump supplies an important seasonal flux of organic carbon to the mesopelagic zone. We estimate that this process is responsible for a global flux of 0.1-0.5 Pg C yr-1. In high-latitude regions where the mixed layer is usually deep, this flux amounts on average to 23% of the carbon supplied by fast sinking particles, but it can be greater than 100%. We conclude that the seasonal mixed-layer pump is an important source of organic carbon for the mesopelagic zone.UK National Centre for Earth Observation, UK NERCMarie Curie(UK) NERC National Capability in Sustained Observations and Marine ModellingEuropean Research CouncilH2020 ATLANTOS EU projec

Transcribed ultraconserved noncoding RNAs (T-UCR) are involved in Barrett's esophagus carcinogenesis.

Barretts esophagus (BE) involves a metaplastic replacement of native esophageal squamous epithelium (Sq) by columnar-intestinalized mucosa, and it is the main risk factor for Barrett-related adenocarcinoma (BAc). Ultra-conserved regions (UCRs) are a class non-coding sequences that are conserved in humans, mice and rats. More than 90% of UCRs are transcribed (T-UCRs) in normal tissues, and are altered at transcriptional level in tumorigenesis. To identify the T-UCR profiles that are dysregulated in Barretts mucosa transformation, microarray analysis was performed on a discovery set of 51 macro-dissected samples obtained from 14 long-segment BE patients. Results were validated in an independent series of esophageal biopsy/surgery specimens and in two murine models of Barretts esophagus (i.e. esophagogastric-duodenal anastomosis). Progression from normal to BE to adenocarcinoma was each associated with specific and mutually exclusive T-UCR signatures that included up-regulation of uc.58-, uc.202-, uc.207-, and uc.223- and down-regulation of uc.214+. A 9 T-UCR signature characterized BE versus Sq (with the down-regulation of uc.161-, uc.165-, and uc.327-, and the up-regulation of uc.153-, uc.158-, uc.206-, uc.274-, uc.472-, and uc.473-). Analogous BE-specific T-UCR profiles were shared by human and murine lesions. This study is the first demonstration of a role for T-UCRs in the transformation of Barretts mucosa

Inferring phytoplankton carbon and eco-physiological rates from diel cycles of spectral particulate beam-attenuation coefficient

The diurnal fluctuations in solar irradiance impose a fundamental frequency on ocean biogeochemistry. Observations of the ocean carbon cycle at these frequencies are rare, but could be considerably expanded by measuring and interpreting the inherent optical properties. A method is presented to analyze diel cycles in particulate beam-attenuation coefficient (<i>c</i><sub>p</sub>) measured at multiple wavelengths. The method is based on fitting observations with a size-structured population model coupled to an optical model to infer the particle size distribution and physiologically relevant parameters of the cells responsible for the measured diel cycle in <i>c</i><sub>p</sub>. Results show that the information related to size and contained in the spectral data can be exploited to independently estimate growth and loss rates during the day and night. In addition, the model can characterize the population of particles affecting the diel variability in <i>c</i><sub>p</sub>. Application of this method to spectral <i>c</i><sub>p</sub> measured at a station in the oligotrophic Mediterranean Sea suggests that most of the observed variations in <i>c</i><sub>p</sub> can be ascribed to a synchronized population of cells with an equivalent spherical diameter around 4.6±1.5 μm. The inferred carbon biomass of these cells was about 5.2–6.0 mg m<sup>−3</sup> and accounted for approximately 10% of the total particulate organic carbon. If successfully validated, this method may improve our in situ estimates of primary productivity

Two databases derived from BGC-Argo float measurements for marine biogeochemical and bio-optical applications

Since 2012, an array of 105 Biogeochemical-Argo (BGC-Argo) floats has been deployed across the world’s oceans to assist in filling observational gaps that are required for characterizing open-ocean environments. Profiles of biogeochemical (chlorophyll and dissolved organic matter) and optical (single-wavelength particulate optical backscattering, downward irradiance at three wavelengths, and photosynthetically available radiation) variables are collected in the upper 1000m every 1 to 10 days. The database of 9837 vertical profiles collected up to January 2016 is presented and its spatial and temporal coverage is discussed. Each variable is quality controlled with specifically developed procedures and its time series is quality-assessed to identify issues related to biofouling and/or instrument drift. A second database of 5748 profile-derived products within the first optical depth (i.e., the layer of interest for satellite remote sensing) is also presented and its spatiotemporal distribution discussed. This database, devoted to field and remote ocean color applications, includes diffuse attenuation coefficients for downward irradiance at three narrow wavebands and one broad waveband (photosynthetically available radiation), calibrated chlorophyll and fluorescent dissolved organic matter concentrations, and single wavelength particulate optical backscattering. To demonstrate the applicability of these databases, data within the first optical depth are compared with previously established bio-optical models and used to validate remotely derived bio-optical products. The quality-controlled databases are publicly available from the SEANOE (SEA scieNtific Open data Edition) publisher at https://doi.org/10.17882/49388 and https://doi.org/10.17882/47142 for vertical profiles and products within the first optical depth, respectively

A synthesis of the environmental response of the North and South Atlantic Sub-Tropical Gyres during two decades of AMT

This is the author accepted manuscript. The final version is available from Elsevier via the DOI in this record.Anthropogenically-induced global warming is expected to decrease primary productivity in the subtropical oceans by strengthening stratification of the water column and reducing the flux of nutrients from deep-waters to the sunlit surface layers. Identification of such changes is hindered by a paucity of long-term, spatially-resolved, biological time-series data at the basin scale. This paper exploits Atlantic Meridional Transect (AMT) data on physical and biogeochemical properties (1995–2014) in synergy with a wide range of remote-sensing (RS) observations from ocean colour, Sea Surface Temperature (SST), Sea Surface Salinity (SSS) and altimetry (surface currents), combined with different modelling approaches (both empirical and a coupled 1-D Ecosystem model), to produce a synthesis of the seasonal functioning of the North and South Atlantic Sub-Tropical Gyres (STGs), and assess their response to longer-term changes in climate. We explore definitive characteristics of the STGs using data of physical (SST, SSS and peripheral current systems) and biogeochemical variables (chlorophyll and nitrate), with inherent criteria (permanent thermal stratification and oligotrophy), and define the gyre boundary from a sharp gradient in these physical and biogeochemical properties. From RS data, the seasonal cycles for the period 1998–2012 show significant relationships between physical properties (SST and PAR) and gyre area. In contrast to expectations, the surface layer chlorophyll concentration from RS data (CHL) shows an upward trend for the mean values in both subtropical gyres. Furthermore, trends in physical properties (SST, PAR, gyre area) differ between the North and South STGs, suggesting the processes responsible for an upward trend in CHL may vary between gyres. There are significant anomalies in CHL and SST that are associated with El Niño events. These conclusions are drawn cautiously considering the short length of the time-series (1998–2012), emphasising the need to sustain spatially-extensive surveys such as AMT and integrate such observations with models, autonomous observations and RS data, to help address fundamental questions about how our planet is responding to climate change. A small number of dedicated AMT cruises in the keystone months of January and July would complement our understanding of seasonal cycles in the STGs.Natural Environment Research Council National CapabilityUK National Centre for Earth Observatio

Uncertainty in Ocean-Color 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.info:eu-repo/semantics/publishedVersio

Inferring phytoplankton carbon and eco-physiological rates from diel cycles of spectral particulate beam-attenuation coefficient

The diurnal fluctuations in solar irradiance impose a fundamental frequency on ocean biogeochemistry. Observations of the ocean carbon cycle at these frequencies are rare, but could be considerably expanded by measuring and interpreting the inherent optical properties. A method is presented to analyze diel cycles in particulate beam-attenuation coefficient (c[subscript p]) measured at multiple wavelengths. The method is based on fitting observations with a size-structured population model coupled to an optical model to infer the particle size distribution and physiologically relevant parameters of the cells responsible for the measured diel cycle in c[subscript p]. Results show that the information related to size and contained in the spectral data can be exploited to independently estimate growth and loss rates during the day and night. In addition, the model can characterize the population of particles affecting the diel variability in c[subscript p]. Application of this method to spectral c[subscript p] measured at a station in the oligotrophic Mediterranean Sea suggests that most of the observed variations in c[subscript p] can be ascribed to a synchronized population of cells with an equivalent spherical diameter around 4.6±1.5 μm. The inferred carbon biomass of these cells was about 5.2–6.0 mg m⁻³ and accounted for approximately 10% of the total particulate organic carbon. If successfully validated, this method may improve our in situ estimates of primary productivity

Potential controls of isoprene in the surface ocean

Isoprene surface ocean concentrations and vertical distribution, atmospheric mixing ratios, and calculated sea-to-air fluxes spanning approximately 125° of latitude (80°N–45°S) over the Arctic and Atlantic Oceans are reported. Oceanic isoprene concentrations were associated with a number of concurrently monitored biological variables including chlorophyll a (Chl a), photoprotective pigments, integrated primary production (intPP), and cyanobacterial cell counts, with higher isoprene concentrations relative to all respective variables found at sea surface temperatures greater than 20°C. The correlation between isoprene and the sum of photoprotective carotenoids, which is reported here for the first time, was the most consistent across all cruises. Parameterizations based on linear regression analyses of these relationships perform well for Arctic and Atlantic data, producing a better fit to observations than an existing Chl a-based parameterization. Global extrapolation of isoprene surface water concentrations using satellite-derived Chl a and intPP reproduced general trends in the in situ data and absolute values within a factor of 2 between 60% and 85%, depending on the data set and algorithm used

DELINEAMENTO AMOSTRAL EM RESERVATÓRIOS UTILIZANDO IMAGENS LANDSAT-8/OLI: UM ESTUDO DE CASO NO RESERVATÓRIO DE NOVA AVANHANDAVA (ESTADO DE SÃO PAULO, BRASIL)

O uso do sensoriamento remoto voltado para a determinação de amostras de campo é de grande valia para estudos ambientais, uma vez que as imagens de satélite apresentam atributos capazes de avaliar a variabilidade espectral da superfície da água considerando uma área extensa. Desse modo, a abordagem deste trabalho objetiva definir um método de seleção estratificada de amostras baseada na variabilidade de imagens no espectro do visível e infravermelho oriundos do sensor Landsat-8/OLI. O método conta com a utilização de dados raster que representam o desvio padrão de uma série temporal de imagens Landsat-8/OLI e em seguida a definição automática de pontos de campo apoiada na técnica de amostragem estratificada aleatória. A escolha da imagem que deu origem a seleção dos pontos foi baseada na componente de maior variabilidade espectral por meio da técnica de Principal Componente. Como resultado foram obtidos vinte pontos representativos de um total de seis classes espectralmente semelhantes