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Measuring plankton and associated variables as part of ocean time-series stations has the potential to revolutionize our understanding of ocean biology and ecology and their ties to ocean biogeochemistry. It will open temporal scales (e.g., resolving diel cycles) not typically sampled as a function of depth. In this review we motivate the addition of biological measurements to time-series sites by detailing science questions they could help address, reviewing existing technology that could be deployed, and providing examples of time-series sites already deploying some of those technologies. We consider here the opportunities that exist through global coordination within the OceanSITES network for long-term (climate) time series station in the open ocean. Especially with respect to data management, global solutions are needed as these are critical to maximize the utility of such data. We conclude by providing recommendations for an implementation plan. 

Abstract The photosynthetic cyanobacterium Trichodesmium is widely distributed in the surface low latitude ocean where it contributes significantly to N2 fixation and primary productivity. Previous studies found nifH genes and intact Trichodesmium colonies in the sunlight-deprived meso- and bathypelagic layers of the ocean (200–4000 m depth). Yet, the ability of Trichodesmium to fix N2 in the dark ocean has not been explored. We performed 15N2 incubations in sediment traps at 170, 270 and 1000 m at two locations in the South Pacific. Sinking Trichodesmium colonies fixed N2 at similar rates than previously observed in the surface ocean (36–214 fmol N cell−1 d−1). This activity accounted for 40 ± 28% of the bulk N2 fixation rates measured in the traps, indicating that other diazotrophs were also active in the mesopelagic zone. Accordingly, cDNA nifH amplicon sequencing revealed that while Trichodesmium accounted for most of the expressed nifH genes in the traps, other diazotrophs such as Chlorobium and Deltaproteobacteria were also active. Laboratory experiments simulating mesopelagic conditions confirmed that increasing hydrostatic pressure and decreasing temperature reduced but did not completely inhibit N2 fixation in Trichodesmium. Finally, using a cell metabolism model we predict that Trichodesmium uses photosynthesis-derived stored carbon to sustain N2 fixation while sinking into the mesopelagic. We conclude that sinking Trichodesmium provides ammonium, dissolved organic matter and biomass to mesopelagic prokaryotes. 

Phytoplankton photosynthetic physiology can be investigated through single-turnover variable chlorophyll fluorescence (ST-ChlF) approaches, which carry unique potential to autonomously collect data at high spatial and temporal resolution. Over the past decades, significant progress has been made in the development and application of ST-ChlF methods in aquatic ecosystems, and in the interpretation of the resulting observations. At the same time, however, an increasing number of sensor types, sampling protocols, and data processing algorithms have created confusion and uncertainty among potential users, with a growing divergence of practice among different research groups. In this review, we assist the existing and upcoming user community by providing an overview of current approaches and consensus recommendations for the use of ST-ChlF measurements to examine in-situ phytoplankton productivity and photo-physiology. We argue that a consistency of practice and adherence to basic operational and quality control standards is critical to ensuring data inter-comparability. Large datasets of inter-comparable and globally coherent ST-ChlF observations hold the potential to reveal large-scale patterns and trends in phytoplankton photo-physiology, photosynthetic rates and bottom-up controls on primary productivity. As such, they hold great potential to provide invaluable physiological observations on the scales relevant for the development and validation of ecosystem models and remote sensing algorithms. 

Abstract. Marine diazotrophs convert dinitrogen (N2) gas intobioavailable nitrogen (N), supporting life in the global ocean. In 2012, thefirst version of the global oceanic diazotroph database (version 1) waspublished. Here, we present an updated version of the database (version 2),significantly increasing the number of in situ diazotrophic measurements from13 565 to 55 286. Data points for N2 fixation rates, diazotrophic cellabundance, and nifH gene copy abundance have increased by 184 %, 86 %, and809 %, respectively. Version 2 includes two new data sheets for the nifH genecopy abundance of non-cyanobacterial diazotrophs and cell-specific N2fixation rates. The measurements of N2 fixation rates approximatelyfollow a log-normal distribution in both version 1 and version 2. However,version 2 considerably extends both the left and right tails of thedistribution. Consequently, when estimating global oceanic N2 fixationrates using the geometric means of different ocean basins, version 1 andversion 2 yield similar rates (43–57 versus 45–63 Tg N yr−1; rangesbased on one geometric standard error). In contrast, when using arithmeticmeans, 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 areestimated 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 theIndian Ocean to be 35±14 Tg N yr−1, which could not be estimatedusing version 1 due to limited data availability. Furthermore, a comparisonof N2 fixation rates obtained through different measurement methods atthe same months, locations, and depths reveals that the conventional15N2 bubble method yields lower rates in 69 % cases compared tothe new 15N2 dissolution method. This updated version of thedatabase can facilitate future studies in marine ecology andbiogeochemistry. The database is stored at the Figshare repository(https://doi.org/10.6084/m9.figshare.21677687; Shao etal., 2022).