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We conducted samplings of total and particulate 234Th, along with particulate organic carbon (POC), in the summer of 2017 to examine nutrient-dependent structures of export productivity within the euphotic zone (Ez) of the oligotrophic basin of the South China Sea (SCS). Nitrate concentrations throughout the study area were below detection limits in the nutrient-depleted layer (NDL) above the nutricline, while they sharply increased with depth in the nutrient-replete layer (NRL) across the nutricline until the base of the Ez. Based on our vertical profilings of 234Th–238U disequilibria, this study estimated for the first time POC export fluxes both out of the NDL and at the horizon of the Ez base. The total 234Th deficit relative to 238U was determined in the NDL at all study sites. By contrast, 234Th was mostly in equilibrium with 238U in the NRL, except at the northernmost station, SEATS (SouthEast Asian Time-series Study; 18∘ N, 116∘ E), where the 234Th deficit was also observed in the NRL. By combining 1D steady-state 234Th fluxes and POC/234Th ratios, we derived vertical patterns of POC export fluxes. The POC export fluxes at station SEATS were 1.6 ± 0.6 mmol C m−2 d−1 at the NDL base, accounting for approximately half of that at the base of the Ez. For the rest of the sampling sites, the POC export fluxes at the NDL base (averaged at 2.3 ± 1.1 mmol C m−2 d−1) were comparable with those at the base of the Ez (1.9 ± 0.5 mmol C m−2 d−1), suggesting rapid export of POC out of the NDL. This finding fundamentally changes our traditional view that the NDL, being depleted in nutrients, would not be a net exporter of POC. Furthermore, our results revealed a significant positive correlation between POC export fluxes at the NDL base and the potential of subsurface nutrient supplies, indicated by nutricline depth and nutrient concentrations obtained from both in situ measurements and numerical modeling. POC export fluxes (averaged at 3.4 ± 1.2 mmol C m−2 d−1) at the NDL base at stations with shallow nutriclines and high levels of subsurface nutrients approximately doubled those (averaged at 1.6 ± 0.5 mmol C m−2 d−1) at other stations. We subsequently used a two-endmember mixing model based on the mass and 15N isotopic balances to evaluate the relative contribution of different sources of new nitrogen that support the observed particle export at stations SEATS and SS1, located respectively in the northern and southern basin of the SCS with different hydrological features. We showed that more than 50 % of the particle flux out of the NDL was supported by nitrate sources likely supplied from depth and associated with episodic intrusions other than atmospheric deposition and nitrogen fixation. However, the exact mechanisms and pathways for subsurface nutrients to support the export production from the NDL merit additional careful and dedicated studies.

Purpose The stressful global situation due to the COVID-19 pandemic has had a tremendous impact on mental health in hospitalized patients with schizophrenia. The mediating roles of psychological impacts related to COVID-19 sleep quality and emotional distress were investigated in the association between childhood trauma and suicide risk in inpatients with schizophrenia. Methods A total of 270 participants, including 125 in-patients with schizophrenia and 145 healthy controls (HCs) were enrolled. Childhood trauma, psychological impact related to COVID-19, global sleep quality, and psychological distress were measured using the Childhood Trauma Questionnaires (CTQ), Impact of Event Scale-Revised (IES-R), Pittsburgh Sleep Quality Index (PSQI), and Depression, Anxiety and Stress Scale (DASS-21), respectively. Results The total score and subtype scores of CTQ and the mean scores of the IES-R, PSQI, and DASS-21 in patients with schizophrenia were higher than those in HCs (all p < 0.001). Hierarchical linear regression analyses showed that a history of childhood trauma or schizophrenia was a good predictor of psychological impact, global sleep quality, and emotional distress (all p < 0.01). Moreover, the chain mediation model showed that the effect of childhood trauma on suicide risk in hospitalized patients with schizophrenia was totally sequentially mediated by thepsychological impact of COVID-19, sleep quality, and emotional distress. Conclusions It is important for clinicians to recognize the increased suicide risk associated with COVID-19-related psychological distress in patients with schizophrenia with a history of childhood trauma.

In this paper, we outline the need for a coordinated international effort toward the building of an open-access Global Ocean Oxygen Database and ATlas (GO 2DAT) complying with the FAIR principles (Findable, Accessible, Interoperable, and Reusable). GO 2DAT will combine data from the coastal and open ocean, as measured by the chemical Winkler titration method or by sensors (e.g., optodes, electrodes) from Eulerian and Lagrangian platforms (e.g., ships, moorings, profiling floats, gliders, ships of opportunities, marine mammals, cabled observatories). GO 2DAT will further adopt a community-agreed, fully documented metadata format and a consistent quality control (QC) procedure and quality flagging (QF) system. GO 2DAT will serve to support the development of advanced data analysis and biogeochemical models for improving our mapping, understanding and forecasting capabilities for ocean O 2 changes and deoxygenation trends. It will offer the opportunity to develop quality-controlled data synthesis products with unprecedented spatial (vertical and horizontal) and temporal (sub-seasonal to multi-decadal) resolution. These products will support model assessment, improvement and evaluation as well as the development of climate and ocean health indicators. They will further support the decision-making processes associated with the emerging blue economy, the conservation of marine resources and their associated ecosystem services and the development of management tools required by a diverse community of users (e.g., environmental agencies, aquaculture, and fishing sectors). A better knowledge base of the spatial and temporal variations of marine O 2 will improve our understanding of the ocean O 2 budget, and allow better quantification of the Earth’s carbon and heat budgets. With the ever-increasing need to protect and sustainably manage ocean services, GO 2DAT will allow scientists to fully harness the increasing volumes of O 2 data already delivered by the expanding global ocean observing system and enable smooth incorporation of much higher quantities of data from autonomous platforms in the open ocean and coastal areas into comprehensive data products in the years to come. This paper aims at engaging the community (e.g., scientists, data managers, policy makers, service users) toward the development of GO 2DAT within the framework of the UN Global Ocean Oxygen Decade (GOOD) program recently endorsed by IOC-UNESCO. A roadmap toward GO 2DAT is proposed highlighting the efforts needed (e.g., in terms of human resources).

In this paper, we outline the need for a coordinated international effort toward the building of an open-access Global Ocean Oxygen Database and ATlas (GO2DAT) complying with the FAIR principles (Findable, Accessible, Interoperable, and Reusable). GO2DAT will combine data from the coastal and open ocean, as measured by the chemical Winkler titration method or by sensors (e.g., optodes, electrodes) from Eulerian and Lagrangian platforms (e.g., ships, moorings, profiling floats, gliders, ships of opportunities, marine mammals, cabled observatories). GO2DAT will further adopt a community-agreed, fully documented metadata format and a consistent quality control (QC) procedure and quality flagging (QF) system. GO2DAT will serve to support the development of advanced data analysis and biogeochemical models for improving our mapping, understanding and forecasting capabilities for ocean O2 changes and deoxygenation trends. It will offer the opportunity to develop quality-controlled data synthesis products with unprecedented spatial (vertical and horizontal) and temporal (sub-seasonal to multi-decadal) resolution. These products will support model assessment, improvement and evaluation as well as the development of climate and ocean health indicators. They will further support the decision-making processes associated with the emerging blue economy, the conservation of marine resources and their associated ecosystem services and the development of management tools required by a diverse community of users (e.g., environmental agencies, aquaculture, and fishing sectors). A better knowledge base of the spatial and temporal variations of marine O2 will improve our understanding of the ocean O2 budget, and allow better quantification of the Earth’s carbon and heat budgets. With the ever-increasing need to protect and sustainably manage ocean services, GO2DAT will allow scientists to fully harness the increasing volumes of O2 data already delivered by the expanding global ocean observing system and enable smooth incorporation of much higher quantities of data from autonomous platforms in the open ocean and coastal areas into comprehensive data products in the years to come. This paper aims at engaging the community (e.g., scientists, data managers, policy makers, service users) toward the development of GO2DAT within the framework of the UN Global Ocean Oxygen Decade (GOOD) program recently endorsed by IOC-UNESCO. A roadmap toward GO2DAT is proposed highlighting the efforts needed (e.g., in terms of human resources).

IOC Technical Series, 158 Rev.

The Integrated Ocean Carbon Research (IOC-R) programme is a formal working group of the Intergovernmental Oceanographic Commission (IOC) that was formed in 2018 in response to the United Nations (UN) Decade of Ocean Science for Sustainable Development (2021-2030), “the Decade.” The IOC-R will contribute to the science elements of the overarching Implementation Plan for the Decade1. The Implementation Plan is a high-level framework to guide actions by which ocean science can more effectively deliver its contribution and co-development with other entities to achieve the societal outcomes outlined in the Decade plan and the sustainable development goals (SDGs) of the UN., PERSISTENCIA DE SUSTRATOS ORGANICOS EN AMBIENTES OCEANICOS DILUIDOS, UNESCO, POSEIDON

Nitrous oxide (N2O) has significant global warming potential as a greenhouse gas. Estuarine and coastal regimes are the major zones of N2O production in the marine system. However, knowledge on biological sources of N2O in estuarine ecosystems remains controversial but is of great importance for understanding global N2O emission patterns. Here, we measured concentrations and isotopic compositions of N2O as well as distributions of ammonia-oxidizing bacterial and archaeal amoA and denitrifier nirS genes by quantitative polymerase chain reaction along a salinity gradient in the Pearl River estuary, and we performed in situ incubation experiments to estimate N2O yields. Our results indicated that nitrification predominantly occurred, with significant N2O production during ammonia oxidation. In the hypoxic waters of the upper estuary, strong nitrification resulted in the observed maximum N2O and ΔN2Oexcess concentrations, although minor denitrification might be concurrent at the site with the lowest dissolved oxygen. Ammonia-oxidizing β-proteobacteria (AOB) were significantly positively correlated with all N2O-related parameters, although their amoA gene abundances were distinctly lower than ammonia-oxidizing archaea (AOA) throughout the estuary. Furthermore, the N2O production rate and the N2O yield normalized to amoA gene copies or transcripts estimated a higher relative contribution of AOB to the N2O production in the upper estuary. Taken together, the in situ incubation experiments, N2O isotopic composition and concentrations, and gene datasets suggested that the high concentration of N2O (oversaturated) is mainly produced from strong nitrification by the relatively high abundance of AOB in the upper reaches and is the major source of N2O emitted to the atmosphere in the Pearl River estuary.

There is increasing concern about the effects of ocean acidification on marine biogeochemical and ecological processes and the organisms that drive them, including marine bacteria. Here, we examine the effects of elevated CO2 on the bacterioplankton community during a mesocosm experiment using an artificial phytoplankton community in subtropical, eutrophic coastal waters of Xiamen, southern China. Through sequencing the bacterial 16S rRNA gene V3-V4 region, we found that the bacterioplankton community in this high-nutrient coastal environment was relatively resilient to changes in seawater carbonate chemistry. Based on comparative ecological network analysis, we found that elevated CO2 hardly altered the network structure of high-abundance bacterioplankton taxa but appeared to reassemble the community network of low abundance taxa. This led to relatively high resilience of the whole bacterioplankton community to the elevated CO2 level and associated chemical changes. We also observed that the Flavobacteria group, which plays an important role in the microbial carbon pump, showed higher relative abundance under the elevated CO2 condition during the early stage of the phytoplankton bloom in the mesocosms. Our results provide new insights into how elevated CO2 may influence bacterioplankton community structure.

In 2017, the International Ocean Carbon Coordination Project (IOCCP) and the Japan Agency for Marine-Earth Science and Technology (JAMSTEC) decided to conduct the 6th International Inter-Calibration Exercise, the “2017/18 inter-laboratory comparison exercise of Certified Reference Materials of Nutrients in Seawater, CRM”. As was the case with the previous four inter-comparison (IC) studies organized by MRI-JMA and the previous IOCCCP-JAMSTEC IC exercise in 2015, the aim of this IC exercise was to improve the level of comparability by exchanging knowledge among participating laboratories. The scale of the study was expanded. One hundred seven laboratories in 33 countries across five continents received a letter of invitation to the IC exercise, and 71 laboratories in 30 counties agreed to participate in this IC exercise. Results were returned from 69 laboratories in 30 countries. The data were statistically analyzed, and the results are described in this report. The agreement between consensus median/mean and certified values was within uncertainty for all five samples used in this IC exercise. Only small discrepancies existed among core laboratories that reported close-to-consensus values and certified values. Normalized cumulative distributions for nitrate and phosphate obtained in 2018 were better (i.e., flatter) than the normalized cumulative distributions obtained from previous IC exercises conducted in 2008, 2012, and 2015. The indication is that comparability of nitrate and phosphate analysis among the laboratories has gradually improved from 2008 to 2018. In contrast with the nitrate and phosphate results, the normalized cumulative distribution for silicate obtained in 2018 was similar to the distributions in previous years. The indication is that comparability of silicate analysis among the laboratories has not changed during these years. The results of this IC exercise also showed that nonlinearity of the calibration curves for the nutrient analyses in each laboratory is still a significant source of reduced comparability of nutrient data. Analysis of ranked scatter plots led to this conclusion. The implication is that we need to use a set of nutrient CRMs, the concentrations of which cover the whole range of nutrient concentrations in the world’s oceans to maintain comparability of results. Thirty-eight laboratories among 69 laboratories used a CRM/RM. The remaining 31 laboratories did not use a CRM/RM or did not reply to the questionnaire. It is obvious that the number of the laboratories that use CRMs has been increasing since 2008. In general, the reported results from laboratories that used CRMs were located in the central part of the ranked plots and showed good Z-scores, as expected. The results of this IC exercise imply that the majority of the participating laboratories are very capable of measuring nutrient concentrations in seawater, and using CRMs will further increase the comparability of results. The results may be SI traceable in the near future. Fil: Aoyama, Michio. Fukushima University; Japón Fil: Abad, Mara. Consejo Superior de Investigaciones Científicas. Instituto de Ciencias del Mar; España Fil: Aguilar-Islas, Ana. University of Alaska; Estados Unidos Fil: Ashraf P, Muhamed. Central Institute of Fisheries Education. Fishing Technology Division; India Fil: Azetsu-Scott, Kumiko. Bedford Institute of Oceanography; Canadá Fil: Bakir, Adil. University of Portsmouth; Reino Unido Fil: Becker, Susan. University of California at San Diego. Scripps Institution of Oceanography; Estados Unidos Fil: Benoit-Cattin-Breton, Alice. Marine Research Institute; Islandia Fil: Berdalet, Elisa. Consejo Superior de Investigaciones Científicas. Instituto de Ciencias del Mar; España Fil: Björkman, Karin. University of Hawaii at Manoa; Estados Unidos Fil: Blum, Marguerite. Monterey Bay Aquarium Research Institute; Estados Unidos Fil: de Santis Braga, Elisabete. Universidade de Sao Paulo; Brasil Fil: Caradec, Florian. French Research Institute for Exploitation of the Sea; Francia Fil: Cariou, Thierry. Université Pierre et Marie Curie; Francia. Centre National de la Recherche Scientifique; Francia Fil: Gonsalez Chiozzini, Vitor. Universidade de Sao Paulo; Brasil Fil: Collin, Karine. French Research Institute for Exploitation of the Sea; Francia Fil: Coppola, Laurent. Centre National de la Recherche Scientifique; Francia Fil: Crump, Mike. National Institute of Water and Atmospheric Research; Nueva Zelanda Fil: Dai, Minhan. Xiamen University. Laboratory of Marine Environmental Science; China Fil: Daniel, Anne. French Research Institute for Exploitation of the Sea; Francia Fil: Davis, Clare. University of Liverpool; Reino Unido Fil: Solis, Miriam Edith. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Centro Nacional Patagónico. Centro para el Estudio de Sistemas Marinos; Argentina Fil: Edelvang, Karen. Technical University of Denmark; Dinamarca Fil: Faber, David. University of California at San Diego. Scripps Institution of Oceanography; Estados Unidos Fil: Fidel, Robinson. Centro de Investigaciones Oceanográficas e Hidrográficas del Pacífico; Colombia Fil: Lunde Fonnes, Linda. Institute of Marine Research; Noruega Fil: Frank, Jerry. University of Maryland; Estados Unidos Fil: Frew, Pauline. Scottish Environment Protection Agency; Reino Unido Fil: Funkey, Carolina. University of Hawaii at Manoa; Estados Unidos Fil: Gallia, Roberto. Stazione Zoologica Anton Dohrn; Italia

In order to better comprehend the global carbon cycle and predict the prognosis for the response to climate change, accurate assessment of sea-air CO2 flux is necessary. Comparing to the relative homogeneously distribution of atmospheric CO2 , the pCO2 in the sea surface water is exposed to huge spatio-temporal variability, which leaves a prominent uncertainty resource. Many regional studies typically divided the observational pCO2 data into grid boxes so as to obtain enough data points statistically for their calculatio. However, using the data inside the grid box areas to represent its holistic property (such as standard deviation to represent spatial variance) will mix up three different uncertainty sources. First, the analytical error in the pCO2 determination and the associated environmental parameters used in deriving pCO2 . Second, the spatial variance because of inhomogenous spatial pattern of sea surface pCO2 , especially the region with a dramatically dynamic circumstance like: coastal areas, boundaries or fronts and etc. Third, the estimation process in undersampling condition, specifically, this kind of uncertainty origins from the process that using a sparse data to represent its holistic property of the box area. Common uncertainty quantification by Standard Deviation will mix up the different sources of uncertainty. In this paper, it introduces an optimized procedure to determine three sources of uncertainty (1st analytical error, 2nd spatial variance, 3rd bias from undersampling.) using the combined remote sensing-derived and field-measured pCO2 data. In order to provide a comprehensive error assessment report.

The objective of this inter-laboratory calibration exercise is to evaluate and improve comparability of global nutrients data in the world ocean. IOCCP and JAMSTEC co-organized an inter-laboratory calibration exercise of nutrients in seawater using four lots of recently certified RM produced by KANSO and three CRMs provided by National Metrology Institute of Japan which are certified in Marine 2014. 71 laboratories in 28 countries had replied to the call for participants. Results were returned from 59 laboratories. Korean Institute of Ocean Science and Technology, KIOST, also offered to provide their recently developed RMs to this I/C exercise. The Royal Netherlands Institute for Sea Research, NIOZ, also offers to provide silicate stock solution to contribute to the overall assessment of results regarding with this I/C exercise. Mean, median and standard deviation were calculated, robust mean and standard deviation were also calculated. Successive t-tests at the 95% confidence level were applied to the results before estimating the consensus mean, consensus median, and consensus standard deviation. Z-scores were also calculated to evaluate the performance of laboratories as in the previous inter-comparison studies. The ranked concentration plots for a particular nutrient would be proportional and roughly parallel to each other for samples with different nutrient concentrations if each laboratory appropriately compensated for the non-linearity of the calibration curves. However there are non-proportional results from some laboratories for all of the determinants as well as observed in the previous I/C studies. These results indicate that non-linearity of the calibration curves for nutrient analysis is one of significant sources of less comparability of nutrients data. This implies that we need to use a set of CRM of which nutrients concentrations can cover whole range of measurements of nutrients concentration to keep comparability of whole range of nutrients concentration in the world ocean. It is clear that present comparability among the participants in 2015 I/C exercise is quite similar with previously obtained comparability in 2012 I/C study and previous I/C studies. Consensus standard deviations of all determinands are one order of magnitude large rather than homogeneity of the CRMs distributed and consensus standard deviations are about double of reported precision of measurements of the laboratories. Therefore these I/C results show that use of CRM will be able to greatly improve comparability of nutrient data among the laboratories of the world. There are good signal in the results that although consensus standard deviations are relatively large, consensus median/mean of each samples showed good agreement with certified values of the samples within consensus SDs. This implies that majority of the participating laboratories have good capability to measure nutrients concentration in seawater and using CRM will increase more on the comparability and could be their results to be SI traceable quickly. Fil: Aoyama Michio. Fukushima University; Japón Fil: Abad, Mara. Consejo Superior de Investigaciones Científicas. Instituto de Ciencias del Mar; España Fil: Anstey, Carol. CSIRO Marine and Atmospheric Research; Australia Fil: Ashraf, Muhamed. Central Institute of Fisheries Technology; India Fil: Bakir, Adil. University of Portsmouth; Reino Unido Fil: Solis, Miriam Edith. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Nacional Patagónico; Argentina Fil: Becker, Susan. University of California at San Diego. Scripps Institution of Oceanography; Estados Unidos Fil: Bell, Steven. Bermuda Institute of Ocean Science; Bermudas Fil: Berdalet, Elisa. Consejo Superior de Investigaciones Científicas. Instituto de Ciencias del Mar; España Fil: Blum, Marguerite. Monterey Bay Aquarium Research Institute; Estados Unidos Fil: Briggs, Rebecca. SOEST Laboratory for Analytical Biogeochemistry. University of Hawaii; Estados Unidos Fil: Caradec, Florian. Ifremer; Francia Fil: Cariou, Thierry. Université Pierre et Marie Curie; Francia. Centre National de la Recherche Scientifique; Francia Fil: Church, Matt. Hawaii Ocean Time-series; Estados Unidos Fil: Coppola, Laurent. Centre National de la Recherche Scientifique; Francia Fil: Crump, Mike. National Institute of Water and Atmospheric Research; Nueva Zelanda Fil: Curless, Susan. Hawaii Ocean Time-series; Estados Unidos Fil: Dai, Minhan. Xiamen University. State Key laboratory of Marine Environmental Science; China Fil: Daniel, Anne. Ifremer; Francia Fil: Davis, Clare. University of Liverpool; Reino Unido Fil: de Santis Braga, Elisabete. Universidade de Sao Paulo; Brasil Fil: Ekern, Lindsey. University of California at San Diego. Scripps Institution of Oceanography; Estados Unidos Fil: Faber, David. University of California at San Diego. Scripps Institution of Oceanography; Estados Unidos Fil: Fraser, Tamara. Fisheries And Ocean Canada; Canadá Fil: Gundersen, Kjell. Institute of Marine Research; Noruega Fil: Jacobsen, Sólvá. Faroe Marine Research Institute; Dinamarca Fil: Knockaert, Marc. Directorate Natural Environment. Ecosystems Physico-Chemistry; Bélgica Fil: Komada, Taketoshi. University Of Tartu.; Estonia Fil: Kralj, Martina. Istituto Nazionale di Oceanografía e Geofísica Sperimentale; Italia Fil: Kramer, Rita. Bundesamt für Seeschifffahrt und Hydrographie. Laboratorium Sülldorf; Alemania

Totally 284 phytoplankton water samples were collected in a multidisciplinary investigation in East China Sea(24°00′—32°00′N,120°00′—128°00′E) from December 23th 2009 to January 5th 2010.Phytoplankton species composition and assemblage structure were studied by Utermhl method.A total of 171 taxa which belong to 67 genera of 4 phyla were identified.The phytoplankton community was mainly composed of Bacillariophyta and Dinophyta,and there were also a few species belonging to Cyanophyta and Chrysophyta.Most of the ecotypes of phytoplankton were temperate coastal species,and dominant species were Paralia sulcata,Thalassionema nitzschioides,Pseudo-nitzschia delicatissima,Thalassiosira angulata and Thalassiosira subtilis etc.Cell abundance ranged from 0.356×103 to 142.578×103cells/L with an average of 14.137×103cells/L,of which Bacillariophyta was the major group ranging from 0.356×103 to 142.578×103cells/L with an average of 13.023×103cells/L,followed by Dinophyta,ranging from 0.356×103 to 11.378×103cells/L with an average of 1.177×103cells/L.Horizontally,the surface distribution of cell abundance in survey area was mainly dominated by Bacillariophyta and the high value appeared in the sea northeast of Changjiang estuary.Dinophyta mostly concentrated in the southern and southeast part of the survey area where Kuroshio water flowed by.Vertically,the maximum of cell abundance was found in subsurface water,and along with the increase of the depth cell abundance firstly increased then decreased.According to the Pearson correlation analysis,the distribution of phytoplankton cell abundance was positively correlated with phosphate and silicata,negatively correlated with temperature,and nitrate′s effect on cell abundance wasn′t obvious.

We present the first set of dissolved silicon isotope data in seawater (delta Si-30(Si(OH)4)) from the East China Sea, a large and productive marginal sea significantly influenced by the Kuroshio Current and freshwater inputs from the Changjiang (Yangtze River). In summer (August 2009), the lowest surface delta Si-30(Si(OH)4) signatures of +2.1 parts per thousand corresponding to the highest Si(OH)(4) concentrations (similar to 30.0 mu mol L-1) were observed nearshore in Changjiang Diluted Water. During advection on the East China Sea inner shelf, surface delta Si-30(Si(OH)4) increased rapidly to +3.2 parts per thousand while Si(OH)(4) became depleted, indicating increasing biological utilization of the Si(OH)(4) originating from the Changjiang Diluted Water. This is also reflected in the water column profiles characterized by a general decrease of delta Si-30(Si(OH)4) and an increase of Si(OH)(4) with depth on the East China Sea mid-shelf and slope. In winter (December 2009-January 2010), however, the delta Si-30(Si(OH)4) was nearly constant at +1.9 parts per thousand throughout the water column on the East China Sea shelf beyond the nearshore, which was a consequence of enhanced vertical mixing of the Kuroshio subsurface water. Horizontal admixture of Kuroshio surface water, which is highly fractionated in Si isotopes, was observed only beyond the shelf break. Significant seasonal differences in delta Si-30(Si(OH)4) were detected in the surface waters beyond the Changjiang Diluted Water-influenced region on the East China Sea shelf, where the winter values were similar to 1.0 parts per thousand lower than those in summer, despite the same primary Si(OH)(4) supply from the Kuroshio subsurface water during both seasons. This demonstrates significantly higher biological consumption and utilization of Si(OH)(4) in summer than in winter.

Autoclaved natural seawater collected in the North Pacific Ocean was used as a reference material for nutrients in seawater (RMNS) during an inter-laboratory comparison (I/C) study conducted in 2008. This study was a follow-up to previous studies conducted in 2003 and 2006. A set of six samples was distributed to each of 58 laboratories in 15 countries around the globe, and results were returned by 54 of those laboratories (15 countries). The homogeneities of samples used in the 2008 I/C study, based on analyses for three determinants, were improved compared to those of samples used in the 2003 and 2006 I/C studies. Results of these I/C studies indicate that most of the participating laboratories have an analytical technique for nutrients that is sufficient to provide data of high comparability. The differences between reported concentrations from the same laboratories in the 2006 and 2008 I/C studies for the same batch of RMNS indicate that most of the laboratories have been maintaining internal comparability for two years. Thus, with the current high level of performance in the participating laboratories, the use of a common reference material and the adaptation of an internationally accepted nutrient scale system would increase comparability among laboratories worldwide, and the use of a certified reference material would establish traceability. In the 2008 I/C study we observed a problem of non-linearity of the instruments of the participating laboratories similar to that observed among the laboratories in the 2006 I/C study. This problem of non-linearity should be investigated and discussed to improve comparability for the full range of nutrient concentrations. For silicate comparability in particular, we see relatively larger consensus standard deviations than those for nitrate and phosphate.

International audience

Nutrients limiting phytoplankton growth in the ocean are a critical control on ocean productivity and can underpin predicted responses to climate change. The extensive western subtropical North Pacific is assumed to be under strong nitrogen limitation, but this is not well supported by experimental evidence. Here, we report the results of 14 factorial nitrogen–phosphorus–iron addition experiments through the Philippine Sea, which demonstrate a gradient from nitrogen limitation in the north to nitrogen–iron co‐limitation in the south. While nitrogen limited sites responded weakly to nutrient supply, co‐limited sites bloomed with up to ~60‐fold increases in chlorophyll a biomass that was dominated by initially undetectable diatoms. The transition in limiting nutrients and phytoplankton growth capacity was driven by a gradient in deep water nutrient supply, which was undetectable in surface concentration fields. We hypothesize that this large‐scale phytoplankton response gradient is both climate sensitive and potentially important for regulating the distribution of predatory fish., National Natural Science Foundation of China http://dx.doi.org/10.13039/501100001809