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A rare intercomparison of nutrient analysis at sea: lessons learned and recommendations to enhance comparability of open-ocean nutrient data

Dissolved nutrients such as nitrate, nitrite, silicate and phosphate can be a critical limiting factor constraining the growth of phytoplankton, which in turn form the base of the marine food web. They also provide useful chemical signatures (e.g. ratios of preformed nutrients) that can distinguish water masses and their origins (Broecker and Peng, 1982) as well as act as tracers for biogeochemical processes such as nitrogen fixation and denitrification (Deutsch and Weber, 2012). There is growing evidence for significant variability, including long-term trends in nutrient levels in both coastal (Kim et al., 2011) and open-ocean surface (Yasunaka et al., 2014), and deepwater (Kim et al., 2014). These changes reflect direct human intervention in the global environment, especially the effects of the massive ongoing perturbation of the nitrogen cycle (Yang and Gruber, 2016), as well as changes in ocean circulation and biogeochemical cycling that may or may not be anthropogenically influenced (e.g. Di Lorenzo et al., 2008).

Identification and attribution of the variability of nutrient concentrations has been complicated by the existence of systematic analytical errors in data sets collected by different groups at different times. This can lead to controversy over the significance of observed long-term changes (e.g. Zhang et al., 2001) and generally requires empirical correction of historical data, using a variety of ad hoc approaches and principles (Keller et al., 2002; Moon et al., 2016; Pahlow and Riebesell, 2000; Tanhua et al., 2010). Recognition of such systematic errors within and between data sets led to a series of international comparison studies and the introduction of certified reference materials (CRMs) for dissolved nutrients (Aoyama et al., 2016, 2007), as well as recommendations concerning standard protocols for sampling, sample preservation and analysis (Hydes et al., 2010). These steps have undoubtedly contributed to a general improvement in interlaboratory comparability of field-collected data. However, it is notable that most intercomparison studies rely on either (a) shore-based laboratory-based analysis of replicate samples in the context of specially organised intercomparison studies or (b) crossover analysis of measurements made at nearby locations in the ocean where temporal and spatial variability is expected to be small.

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