Abstract. Marine diazotrophs convert dinitrogen (N2) gas into bioavailable nitrogen (N), supporting life in the global ocean. In 2012, the first version of the global oceanic diazotroph database (version 1) was published. Here, we present an updated version of the database (version 2), significantly increasing the number of in situ diazotrophic measurements from 13 565 to 55 286. Data points for N2 fixation rates, diazotrophic cell abundance, and nifH gene copy abundance have increased by 184 %, 86 %, and 809 %, respectively. Version 2 includes two new data sheets for the nifH gene copy abundance of non-cyanobacterial diazotrophs and cell-specific N2 fixation rates. The measurements of N2 fixation rates approximately follow a log-normal distribution in both version 1 and version 2. However, version 2 considerably extends both the left and right tails of the distribution. Consequently, when estimating global oceanic N2 fixation rates using the geometric means of different ocean basins, version 1 and version 2 yield similar rates (43–57 versus 45–63 Tg N yr−1; ranges based on one geometric standard error). In contrast, when using arithmetic means, version 2 suggests a significantly higher rate of 223±30 Tg N yr−1 (mean ± standard error; same hereafter) compared to version 1 (74±7 Tg N yr−1). Specifically, substantial rate increases are estimated for the South Pacific Ocean (88±23 versus 20±2 Tg N yr−1), primarily driven by measurements in the southwestern subtropics, and for the North Atlantic Ocean (40±9 versus 10±2 Tg N yr−1). Moreover, version 2 estimates the N2 fixation rate in the Indian Ocean to be 35±14 Tg N yr−1, which could not be estimated using version 1 due to limited data availability. Furthermore, a comparison of N2 fixation rates obtained through different measurement methods at the same months, locations, and depths reveals that the conventional 15N2 bubble method yields lower rates in 69 % cases compared to the new 15N2 dissolution method. This updated version of the database can facilitate future studies in marine ecology and biogeochemistry. The database is stored at the Figshare repository (https://doi.org/10.6084/m9.figshare.21677687; Shao et al., 2022).

Critical latitudes are a significant area of tidal dissipation. Generally, critical latitudes are taken to be the exact latitude where the tidal frequency equals the inertial frequency. However, the key is really where the tidal frequency equals the combination of planetary vorticity and relative vorticity from background currents. Although the influence of background currents on critical latitude effects and nonlinear interactions have been noted for many years, their exact impacts are not well known. The latitude dependence of critical latitude impacts on the tides, internal tides, and internal waves in the presence of background currents was investigated using the Regional Ocean Modeling System by shifting a small domain including a seamount from 20.6° to 38.6°S and comparing simulations with and without background currents. The diurnal kinetic energy with mesoscale currents was relatively unchanged for most latitudes, except for a slight decrease 1–4° poleward of the critical latitude. However, the semidiurnal and high‐frequency (≥3 cycles per day) kinetic energy increased with the presence of mesoscale currents, especially within the diurnal critical latitude range. Spectral and nonlinear analyses indicated mesoscale currents broadened the range of critical latitude effects and enhanced energy transferring from diurnal frequencies to semidiurnal and high frequencies and from low to high mode waves. Local diffusivities increased, roughly an order of magnitude, when mesoscale currents were present. The impacts of mesoscale currents on the broadening of the critical latitude range and enhancement of nonlinear interactions were attributed to the additional relative vorticity and near‐inertial internal waves generated by mesoscale currents.

Abstract. Non-cyanobacterial diazotrophs may be contributors to global marine N2 fixation, although the factors controlling their distribution are unclear. Here, we explored what controls the distribution of the most sampled non-cyanobacterial diazotroph phylotype, Gamma A, in the global ocean. First, we represented Gamma A abundance by its nifH quantitative polymerase chain reaction (qPCR) copies reported in the literature and analyzed its relationship to climatological biological and environmental conditions. There was a positive correlation between the Gamma A abundance and local net primary production (NPP), and the maximal observed Gamma A abundance increased with NPP and became saturated when NPP reached ∼ 400 mg C m−2 d−1. Additionally, an analysis using a multivariate generalized additive model (GAM) revealed that the Gamma A abundance increased with light intensity but decreased with increasing iron concentration. The GAM also showed a weak but significant positive relationship between Gamma A abundance and silicate concentration, as well as a substantial elevation of Gamma A abundance when the nitrate concentration was very high (≳ 10 µM). Using the GAM, these climatological factors together explained 43 % of the variance in the Gamma A abundance. Second, in addition to the climatological background, we found that Gamma A abundance was elevated in mesoscale cyclonic eddies in high-productivity (climatological NPP > 400 mg m−2 d−1) regions, implying that Gamma A can respond to mesoscale features and benefit from nutrient inputs. Overall, our results suggest that Gamma A tends to inhabit ocean environments with high productivity and low iron concentrations and therefore provide insight into the niche differentiation of Gamma A from cyanobacterial diazotrophs, which are generally most active in oligotrophic ocean regions and need a sufficient iron supply, although both groups prefer well-lit surface waters. More sampling on Gamma A and other non-cyanobacterial diazotroph phylotypes is needed to reveal the controlling mechanisms of heterotrophic N2 fixation in the ocean.

The main objective of the present study is to present the concept of process capability and to focus its significance in pharmaceutical industries. From a practical view point, the control charts (such as X and R hart) sometimes are not convenient summary statistics when hundreds of characteristics in a plant or supply base are considered. In many situations, capability indices can be used to relate the process parameters. The resulting indices are unit less and provide a common, easily understood language for quantifying the performance of a process. Process capability indices (PCIs) are powerful means of studying the process ability for manufacturing a product that meets specifications. Several capability indices including Cp, Cpu, Cpl and Cpk have been widely used in manufacturing industry to provide common quantitative measures on process potential and performance. The formulas for these indices are easily understood and can be directly implemented. A process capability analysis compares the distribution of output from an in-control process to its specifications limits to determine the consistency with which the specifications can be met. The process capability is also having a significant role in pharmaceutical industry. Process capability indices can be a powerful tool by which to ensure drug product quality and process robustness. Determining process capability provides far more insight into any pharmaceutical process performance than simply computing the percentage of batches that pass or fail each year. Keywords: Process capability; Cp/Cpk; Pp/Ppk; Pharmaceutical quality, process robustness, specification

Abstract. Marine diazotrophs convert dinitrogen (N2) in seawater into bioavailable nitrogen (N), contributing approximately half of the external input of bioavailable N to the global ocean. A global oceanic diazotroph database was previously published in 2012. Here, we compiled version 2 of the database by adding 23,095 in situ measurements of marine diazotrophic abundance and N2 fixation rates published in the past decade, increasing the number of N2 fixation rates and microscopic and qPCR-based diazotrophic abundance data by 140 %, 26 % and 443 %, respectively. Although the updated database expanded spatial coverage considerably, particularly in the Indian Ocean, the data distribution was still not uniform and most data were sampled in the surface Pacific and Atlantic Oceans. By summing the arithmetic means of the N2 fixation rates in each ocean basin, the updated database substantially increased the estimate of global oceanic N2 fixation from 137 ± 9 Tg N yr-1 using the old database to 260 ± 20 Tg N yr-1 (mean ± standard error). However, using geometric means instead, the updated database gave an estimate of global oceanic N2 fixation (60 Tg N yr-1) similar to that estimated from the old database (62 Tg N yr-1), while the new estimate had a larger uncertainty (confidence intervals based on one standard error: 47 – 107 Tg N yr-1 versus 52 – 73 Tg N yr-1), mostly attributable to elevated uncertainties in the Pacific Ocean. An analysis comparing N2 fixation rates measured at the same months and location (1° × 1° grids) showed that the new 15N2 dissolution method obtained N2 fixation rates higher than the conventional 15N2 bubble method in 65 % of cases, with this percentage increasing when the N2 fixation rates were high (> approximately 3 μmol N m-3 d-1 using the 15N2 dissolution method). With greatly increased data points, this version 2 of the global oceanic diazotrophic database can support future studies in marine ecology and biogeochemistry. The database is stored at the Figshare repository (https://doi.org/10.6084/m9.figshare.21677687) (Shao et al., 2022).