Hawaii Ocean Time-series Research Articles

Editorial

Editorial

ALOHA From the Edge: Reconciling Three Decades of in Situ Eulerian Observations and Geographic Variability in the North Pacific Subtropical Gyre

Global analyses of satellite-and modeled data suggest decreased phytoplankton abundance and primary productivity in oligotrophic gyres as they expand in response to increased surface temperatures, shoaling of surface mixed layers, and decreased supply of subsurface macronutrients. However, concomitant changes have not been evident in situ at Hawaii Ocean Time-series (HOT) Station ALOHA, suggesting physiological or structural reorganization not observed from space, uncharacterized spatiotemporal variability, or uncorrected sensor drift. To address the spatiotemporal variability hypothesis, we compared interannual patterns of in situ data to gyre geography based on multiple metrics including dynamic topography, satellite surface chlorophyll (chl a), and multivariate seascapes using modelled or satellite data. There was only weak evidence of secular increases in the extent of the subtropical gyre; rather, interannual oscillations were evident in physical, biological, and multivariate biophysical definitions of the gyre. Modelled and satellite-based multivariate seascapes agreed well in terms of expansion (surface area of seascapes) and isolation of Station ALOHA (distance to seascape boundary) resulting in combined data record of nearly three decades. Isolation was associated positively with the North Pacific Gyre Oscillation (NPGO), and negatively with Multivariate ENSO Index (MEI) and Pacific Decadal Oscillation (PDO); the converse was true for the gyre’s expansion. This expansion followed a shoaling and freshening of the surface mixed layer and declines in in situ 14C assimilation rates measured over 12 hours in ambient light suggesting that Station ALOHA may serve as an leading indicator of gyre biogeographic patterns. Lags between geographic indicators and in situ conditions appear to partially explain past observed discrepancies between patterns from satellite remote sensing and those from in situ conditions at Station ALOHA appear to be partially explained by lags between geographic indicators and in situ conditions as well as satellite sensor drift and data record length.

Models for estimating photosynthesis parameters from in situ production profiles

The rate of carbon assimilation in phytoplankton primary production models is mathematically prescribed with photosynthesis irradiance functions, which convert a light flux (energy) into a material flux (carbon). Information on this rate is contained in photosynthesis parameters: the initial slope and the assimilation number. The exactness of parameter values is crucial for precise calculation of primary production. Here we use a model of the daily production profile based on a suite of photosynthesis irradiance functions and extract photosynthesis parameters from in situ measured daily production profiles at the Hawaii Ocean Time-series station Aloha. For each function we recover parameter values, establish parameter distributions and quantify model skill. We observe that the choice of the photosynthesis irradiance function to estimate the photosynthesis parameters affects the magnitudes of parameter values as recovered from in situ profiles. We also tackle the problem of parameter exchange amongst the models and the effect it has on model performance. All models displayed little or no bias prior to parameter exchange, but significant bias following parameter exchange. The best model performance resulted from using optimal parameter values. Model formulation was extended further by accounting for spectral effects and deriving a spectral analytical solution for the daily production profile. The daily production profile was also formulated with time dependent growing biomass governed by a growth equation. The work on parameter recovery was further extended by exploring how to extract photosynthesis parameters from information on watercolumn production. It was demonstrated how to estimate parameter values based on a linearization of the full analytical solution for normalized watercolumn production and from the solution itself, without linearization. The paper complements previous works on photosynthesis irradiance models by analysing the skill and consistency of photosynthesis irradiance functions and parameters for modeling in situ production profiles. In light of the results obtained in this work we argue that the choice of the primary production model should reflect the available data and these models should be data driven regarding parameter estimation.

Extended Formulations and Analytic Solutions for Watercolumn Production Integrals

The effect of biomass dynamics on the estimation of watercolumn primary production is analysed, by coupling a primary production model to a simple growth equation for phytoplankton. The production model is formulated with depth- and time-resolved biomass, and placed in the context of earlier models, with emphasis on the canonical solution for watercolumn production. A relation between the canonical solution and the general solution for the case of an arbitrary depth-dependent biomass profile was derived, together with an analytical solution for watercolumn production in case of a depth dependent biomass profile described with the shifted Gaussian function. The analysis was further extended to the case of a time-dependent, mixed-layer biomass and two additional analytical solutions to this problem were derived, the first in case of increasing mixed-layer biomass and the second in case of declining biomass. The solutions were tested with Hawaii Ocean Time-series data. The canonical solution for mixed-layer production has proven to be a good model for this data set. The shifted Gaussian function was demonstrated to be an accurate model for the measured biomass profiles and the shifted Gaussian parameters extracted from the measured profiles were further used in the analytical solution for watercolumn production and results compared with data. The influence of time-dependent biomass on mixed-layer production was studied through analytical solutions. Re-examining the Critical Depth Hypothesis we derived an expression for the daily increase in mixed-layer biomass. Finally, the work was placed in a remote sensing context and the time-dependent model for biomass related to the remotely sensed-biomass.

Hawaiian imprint on dissolved Nd and Ra isotopes and rare earth elements in the central North Pacific: Local survey and seasonal variability

Dissolved neodymium isotopes (143Nd/144Nd, expressed as εNd) and rare earth elements (REEs) have the potential to trace the provenance of lithogenic material as well as water masses. The central North Pacific is poorly investigated with respect to its Nd isotope signature and REE cycling, and little is known about the contributions of volcanic islands, such as Hawaii, relative to dust input from Asian deserts to the surface water REE budgets. Here we present dissolved Nd isotope and REE data along with long-lived radium isotope activities from Hawaii Ocean Time-Series Station ALOHA and coastal waters from Oahu, sampled for a GEOTRACES process study in February 2011. The data are supplemented with seasonal samples from ALOHA. Our results show a clear influence of the Hawaiian Islands on the coastal ocean and surface waters at ALOHA during February, expressed by higher surface water Ra activities, radiogenic surface εNd (εNd=+1.4 to −1.0), and elevated Eu anomalies (Eu/Eu∗⩾1.3). Seasonal cycles of Asian dust deposition most likely contribute to the seasonal εNd variability of surface waters at ALOHA, as suggested by more negative εNd and the lack of Eu anomalies in summer. Neodymium isotopes in the intermediate and deep water column at ALOHA trace typical North Pacific water masses, such as North Pacific Intermediate Water and North Pacific Deep Water. We suggest that a radiogenic εNd excursion in 1000–2000m water depth, observed in various North Pacific profiles, is controlled by advection of a modified Upper Circumpolar Deep Water or North Equatorial Pacific Intermediate Water. We further present an updated average εNd signature of −3.5±0.5 for North Pacific Deep Water and show that REE patterns of deep waters at ALOHA are dominantly controlled by vertical processes.

A new statistical approach for interpreting oceanic fCO2 data

Surface ocean CO2 fugacity (fCO2) often exhibits large fluctuations and heterogeneity because of multiple controlling factors that pose a challenge for trend analysis, especially in the ocean margins. We propose a new statistical approach, Generalized Additive Mixed Modeling (GAMM), to interpret oceanic fCO2 data in two ocean margins (Japan and Europe) and two open ocean areas. The latter included areas near the Hawaii Ocean Time-series (HOT) and the Bermuda Atlantic Time-series (BATS). This method utilizes day of year, sea surface salinity (SSS), sea surface temperature (SST), and sampling date as predictors. Using this method, we were able to derive multidecadal fCO2 trends with both improved precision and greater robustness to data gaps compared to an existing deseasonalization method used in the open ocean. The fCO2 trend derived by our method for the Japanese margin (1992–2013), the European margin (1989–2014), and the open ocean near HOT (1983–2013) were 2.1±0.6, 1.9±0.7, and 2.0±0.5μatmyear−1 (mean±standard deviation of multiple 1°×1° grids in margins and 5°×5° grids in open ocean), respectively, and the fCO2 trends were all close to the atmosphere CO2 trend (1.7–1.9μatmyear−1). Our analysis produced generally smaller standard errors (paired t-test, p≪0.001) than those obtained using the existing method based on the same dataset. In addition, our method was less sensitive to data gaps compared to this existing method. However, for regularly spaced fCO2 times-series data, for example, discrete bottle data collected in the BATS station in 1991–2011, this method was not advantageous over the existing method (1.9±0.2 vs. 2.0±0.2μatmyear−1). To test the broader applicability of this method, we compared fCO2 trends in the Southern Ocean derived using our method with those from a recently reported Markov Chain Monte Carlo method and found no significant difference between the two sets of values. Therefore, we recommend the application of our method in interpreting fCO2 data in different oceanic environments.

Wind and sunlight shape microbial diversity in surface waters of the North Pacific Subtropical Gyre.

Few microbial time-series studies have been conducted in open ocean habitats having low seasonal variability such as the North Pacific Subtropical Gyre (NPSG), where surface waters experience comparatively mild seasonal variation. To better describe microbial seasonal variability in this habitat, we analyzed rRNA amplicon and shotgun metagenomic data over two years at the Hawaii Ocean Time-series Station ALOHA. We postulated that this relatively stable habitat might reveal different environmental factors that influence planktonic microbial community diversity than those previously observed in more seasonally dynamic habitats. Unexpectedly, the data showed that microbial diversity at 25 m was positively correlated with average wind speed 3 to 10 days prior to sampling. In addition, microbial community composition at 25 m exhibited significant correlations with solar irradiance. Many bacterial groups whose relative abundances varied with solar radiation corresponded to taxa known to exhibit strong seasonality in other oceanic regions. Network co-correlation analysis of 25 m communities showed seasonal transitions in composition, and distinct successional cohorts of co-occurring phylogenetic groups. Similar network analyses of metagenomic data also indicated distinct seasonality in genes originating from cyanophage, and several bacterial clades including SAR116 and SAR324. At 500 m, microbial community diversity and composition did not vary significantly with any measured environmental parameters. The minimal seasonal variability in the NPSG facilitated detection of more subtle environmental influences, such as episodic wind variation, on surface water microbial diversity. Community composition in NPSG surface waters varied in response to solar irradiance, but less dramatically than reported in other ocean provinces.

Recovery of photosynthesis parameters fromin situprofiles of phytoplankton production

We examine a model of the rate of phytoplankton production in the ocean and its dependence on depth. The model is analysed as a function of photosynthesis parameters and it is shown that: (i) production profiles with depth are determined uniquely by the parameter values ; (ii) daily water column production is not uniquely determined by the parameter values ; (iii) a unique combination of parameters exists for which the model best fits a measured production profile. An inverse procedure is developed to recover photosynthesis parameters from measured profiles of primary production, and its performance tested by application to profiles of primary production collected at the Hawaii Ocean Time Series. For each profile tested, the method is successful in recovery of the photosynthesis parameters. The method can be applied to the estimation of photosynthesis parameters from data on in situ production profiles, which have been collected globally for more than half a century, thereby augmenting the world archive of these parameters for application in ecosystem modelling and estimation of primary production from remotely sensed data.

Daily to decadal variability of size-fractionated iron and iron-binding ligands at the Hawaii Ocean Time-series Station ALOHA

Time-series studies of trace metals in the ocean are rare, but they are critical for evaluating both the residence times of the metals themselves and also the timescales over which the marine ecosystems that depend on micronutrient metals can change. In this paper we present two new time-series of the essential micronutrient iron (Fe) taken from the Hawaii Ocean Time-series (HOT) site, Station ALOHA (22.75°N, 158°W): a set of intermittent monthly surface samples taken from ∼50 dates between 1999 and 2011 by the HOT program, and a daily-resolved sample set from summer 2012 and 2013 containing ∼80 surface samples and 7 profiles to 1500m depth. The long-term monthly climatology of surface total dissolvable Fe (TDFe) concentrations covaried with the seasonal cycle of continental Asian dust deposition at Hawaii, indicating dust as the major source of TDFe to ALOHA surface waters and a short residence time for TDFe (order∼months). During the daily summer time-series, surface Fe was most variable in the larger size fractions (>0.4μm particulate and 0.02–0.4μm colloidal) and nearly constant in the smallest (<0.02μm) soluble size fractions, confirming that the larger size fractions have shorter residence times with respect to scavenging/settling. The most significant Fe event lasted three days in early August and “cascaded” through the Fe size fractions from largest to smallest; lacking evidence that dust triggered this event, we correlated it with the arrival of the edge of an anticyclonic eddy and an increase in diatom abundance at ALOHA. The surface Fe-binding ligand daily time-series showed that excess ligand concentrations lagged dFe by 1–2days, revealing a short residence time of ligands in the central North Pacific likely due to photochemical degradation. In the ferricline, the dissolved Fe (dFe) linear relationship with apparent oxygen utilization was used to establish a water column dFe:C ratio of 3.12±0.11μmol/mol and a pre-formed dFe concentration of 0.067±0.009nmol/kg that defines the central/mode waters of Station ALOHA. Finally, in deep waters near 1200m, where minimal temporal variation in dFe might be expected, dFe instead ranged over a factor of two in concentration (0.72–1.44nmol/kg), driven by the intermittent passing of the Loihi hydrothermal plume through Station ALOHA. This study not only provides the largest number of Fe measurements made at a single location anywhere in the global ocean to date but also reveals the strength of time-series measurements for exploring mechanisms and timescales of biogeochemical events.

Thorium isotopes tracing the iron cycle at the Hawaii Ocean Time-series Station ALOHA

The role of iron as a limiting micronutrient motivates an effort to understand the supply and removal of lithogenic trace metals in the ocean. The long-lived thorium isotopes (232Th and 230Th) in seawater can be used to quantify the input of lithogenic metals attributable to the partial dissolution of aerosol dust. Thus, Th can help in disentangling the Fe cycle by providing an estimate of its ultimate supply and turnover rate. Here we present time-series (1994–2014) data on thorium isotopes and iron concentrations in seawater from the Hawaii Ocean Time-series Station ALOHA. By comparing Th-based dissolved Fe fluxes with measured dissolved Fe inventories, we derive Fe residence times of 6–12months for the surface ocean. Therefore, Fe inventories in the surface ocean are sensitive to seasonal changes in dust input. Ultrafiltration results further reveal that Th has a much lower colloidal content than Fe does, despite a common source. On this basis, we suggest Fe colloids may be predominantly organic in composition, at least at Station ALOHA. In the deep ocean (>2km), Fe approaches a solubility limit while Th, surprisingly, is continually leached from lithogenic particles. This distinction has implications for the relevance of Fe ligand availability in the deep ocean, but also suggests Th is not a good tracer for Fe in deep waters. While uncovering divergent behavior of these elements in the water column, this study finds that dissolved Th flux is a suitable proxy for the supply of Fe from dust in the remote surface ocean.

The shape of the oceanic nitracline

Abstract. In most regions of the ocean, nitrate is depleted near the surface by phytoplankton consumption and increases with depth, exhibiting a strong vertical gradient in the pycnocline (here referred to as the nitracline). The vertical supply of nutrients to the surface euphotic zone is influenced by the vertical gradient (slope) of the nitracline and by the vertical separation (depth) of the nitracline from the sunlit surface layer. Hence it is important to understand the shape (slope and curvature) and depth of the oceanic nitracline. By using density coordinates to analyze nitrate profiles from autonomous Autonomous Profiling EXplorer floats with In-Situ Ultraviolet Spectrophotometers (APEX-ISUS) and ship-based platforms (World Ocean Atlas – WOA09; Hawaii Ocean Time-series – HOT; Bermuda Atlantic Time-series Study – BATS; and California Cooperative Oceanic Fisheries Investigations – CalCOFI), we are able to eliminate much of the spatial and temporal variability in the profiles and derive robust relationships between nitrate and density. This allows us to characterize the depth, slope and curvature of the nitracline in different regions of the world's oceans. The analysis reveals distinguishing patterns in the nitracline between subtropical gyres, upwelling regions and subpolar gyres. We propose a one-dimensional, mechanistic model that relates the shape of the nitracline to the relative depths of the surface mixed layer and euphotic layer. Though heuristic, the model accounts for some of the seasonal patterns and regional differences in the nitrate–density relationships seen in the data.

Quantifying subtropical North Pacific gyre mixed layer primary productivity from Seaglider observations of diel oxygen cycles

AbstractUsing autonomous underwater gliders, we quantified diurnal periodicity in dissolved oxygen, chlorophyll, and temperature in the subtropical North Pacific near the Hawaii Ocean Time‐series (HOT) Station ALOHA during summer 2012. Oxygen optodes provided sufficient stability and precision to quantify diel cycles of average amplitude of 0.6 µmol kg−1. A theoretical diel curve was fit to daily observations to infer an average mixed layer gross primary productivity (GPP) of 1.8 mmol O2 m−3 d−1. Cumulative net community production (NCP) over 110 days was 500 mmol O2 m−2 for the mixed layer, which averaged 57 m in depth. Both GPP and NCP estimates indicated a significant period of below‐average productivity at Station ALOHA in 2012, an observation confirmed by 14C productivity incubations and O2/Ar ratios. Given our success in an oligotrophic gyre where biological signals are small, our diel GPP approach holds promise for remote characterization of productivity across the spectrum of marine environments.

Global monthly sea surface nitrate fields estimated from remotely sensed sea surface temperature, chlorophyll, and modeled mixed layer depth

AbstractInformation about oceanic nitrate is crucial for making inferences about marine biological production and the efficiency of the biological carbon pump. While there are no optical properties that allow direct estimation of inorganic nitrogen, its correlation with other biogeochemical variables may permit its inference from satellite data. Here we report a new method for estimating monthly mean surface nitrate concentrations employing local multiple linear regressions on a global 1° by 1° resolution grid, using satellite‐derived sea surface temperature, chlorophyll, and modeled mixed layer depth. Our method is able to reproduce the interannual variability of independent in situ nitrate observations at the Bermuda Atlantic Time Series, the Hawaii Ocean Time series, the California coast, and the southern New Zealand region. Our new method is shown to be more accurate than previous algorithms and thus can provide improved information on temporal and spatial nutrient variations beyond the climatological mean at regional and global scales.

Paired windward and leeward biogeochemical time series reveal consistent surface ocean CO2 trends across the Hawaiian Ridge

Sustained time series have provided compelling evidence for progressive acidification of the surface oceans through exchange with the growing atmospheric reservoir of carbon dioxide. However, few long-term programs exist, and extrapolation of results from one site to larger oceanic expanses is hampered by the lack of spatial coverage inherent to Eulerian sampling. Since 1988, the Hawaii Ocean Time-series program has sampled CO2 system variables nearly monthly at Station ALOHA, a deep ocean site windward and 115 km north of the island of Oahu. Surface measurements have also been made at Station Kahe, a leeward site 12 km from the island and on the opposite side of the Hawaiian Ridge. Despite having different physical settings, the sites exhibit identical rates of surface pCO2 increase and hydrogen ion accumulation, suggesting that atmospheric forcing dominates over local dynamics in determining the CO2 trend in the surface waters of the North Pacific subtropical gyre.

Microbial oceanography and the Hawaii Ocean Time-series programme.

The Hawaii Ocean Time-series (HOT) programme has been tracking microbial and biogeochemical processes in the North Pacific Subtropical Gyre since October 1988. The near-monthly time series observations have revealed previously undocumented phenomena within a temporally dynamic ecosystem that is vulnerable to climate change. Novel microorganisms, genes and unexpected metabolic pathways have been discovered and are being integrated into our evolving ecological paradigms. Continued research, including higher-frequency observations and at-sea experimentation, will help to provide a comprehensive scientific understanding of microbial processes in the largest biome on Earth.

Metabolic pathways for the whole community.

BackgroundA convergence of high-throughput sequencing and computational power is transforming biology into information science. Despite these technological advances, converting bits and bytes of sequence information into meaningful insights remains a challenging enterprise. Biological systems operate on multiple hierarchical levels from genomes to biomes. Holistic understanding of biological systems requires agile software tools that permit comparative analyses across multiple information levels (DNA, RNA, protein, and metabolites) to identify emergent properties, diagnose system states, or predict responses to environmental change.ResultsHere we adopt the MetaPathways annotation and analysis pipeline and Pathway Tools to construct environmental pathway/genome databases (ePGDBs) that describe microbial community metabolism using MetaCyc, a highly curated database of metabolic pathways and components covering all domains of life. We evaluate Pathway Tools’ performance on three datasets with different complexity and coding potential, including simulated metagenomes, a symbiotic system, and the Hawaii Ocean Time-series. We define accuracy and sensitivity relationships between read length, coverage and pathway recovery and evaluate the impact of taxonomic pruning on ePGDB construction and interpretation. Resulting ePGDBs provide interactive metabolic maps, predict emergent metabolic pathways associated with biosynthesis and energy production and differentiate between genomic potential and phenotypic expression across defined environmental gradients.ConclusionsThis multi-tiered analysis provides the user community with specific operating guidelines, performance metrics and prediction hazards for more reliable ePGDB construction and interpretation. Moreover, it demonstrates the power of Pathway Tools in predicting metabolic interactions in natural and engineered ecosystems.Electronic supplementary materialThe online version of this article (doi:10.1186/1471-2164-15-619) contains supplementary material, which is available to authorized users.

Remineralization of phytoplankton-derived organic matter by natural populations of heterotrophic bacteria

The relative lability, elemental stoichiometry, and remineralization rates of various particulate organic matter (POM) substrates by natural heterotrophic marine microorganisms were investigated. POM was harvested from laboratory cultures of a marine diazotroph (Trichodesmium IMS101), a cosmopolitan diatom (Thalassiosira weissflogii), a common marine cyanobacteria (Prochlorococcus MED4), and from surface waters off the Oregon coast. These POM resources were used as inoculants in a field experiment conducted at the Hawaii Ocean Time-series Station ALOHA in the North Pacific Subtropical Gyre. POM from these various sources was added to seawater collected from below the surface mixed layer, incubated in the dark, and remineralization rates were quantified via high-frequency measurement of soluble phosphorus (P) and nitrogen (N) concentrations over a 6-d period. Rapid solubilization and near complete remineralization of particulate P (PP) occurred in all treatments where cultured POM was used, with lesser relative mobilization of P from a ‘natural’ POM sample isolated from surface seawater off the Oregon coast. Soluble P pools, likely consisting of surface-adsorbed inorganic P and inorganic P liberated from cells during harvesting of biomass accounted for 28% of natural PP pools and 80±32% of cultured PP. 31P nuclear magnetic resonance (NMR) confirmed that PP was predominately present as orthophosphate in all POM types. By the end of the incubation period, all added P from cultured material had been converted to dissolved inorganic P. This finding may be a caveat of our utilization of laboratory cultures and natural POM which has been exposed to high inorganic P concentrations (0.8–5.0μmolL−1), albeit it is consistent with previous reports of significant contributions of surface-adsorbed P to total particulate P. In contrast, over the course of these experiments, only 37–40% of added N had been remineralized to ammonium (NH4+). In general, N remineralization rates of cultured material increased with the amount of N added (per gram of dry material). The net yield of bacterial cells was also positively correlated to the initial amount of C and N added. Most notably, when corrected for non-biological turnover (i.e. removal of soluble pools), the N:P remineralization ratio of cultured material (8.5±1.3) was independent of the N:P of added organic material (5–23).

Nearshore Carbonate Dissolution in the Hawaiian Archipelago?

Inorganic carbon measurements made in the late 1980s suggest that alkalinity in the waters surrounding the Hawaiian Archipelago is elevated relative to the oligotrophic waters of the North Pacific. These observations have been interpreted as evidence for a “halo” of elevated carbonate saturation state produced by the dissolution of highly soluble magnesium calcites and aragonite on the island platform or in the water column surrounding the islands. If present, this “halo” has implications for air–sea carbon dioxide exchange in Hawaiian waters and may impact the response of coral reef communities to the acidification of the surface waters of the global ocean. The purpose of this study was to assess the magnitude and extent of the elevated calcium carbonate saturation state observed on previous expeditions to this region. Transects were conducted near several atolls in the Northwestern Hawaiian Islands from shallow water adjacent to the forereef to the open ocean 15 km from the island. Hydrographic profiles were collected at each station, and discrete water samples were collected for the measurement of carbon system parameters necessary to compute calcium carbonate saturation state. Our data were compared with observations made at the Hawaii Ocean Time-series site at Station ALOHA and with hydrographic data collected on the WOCE lines in the North Pacific around the archipelago. We did not detect a carbonate dissolution halo around the islands. We conclude that the previously observed halo was probably an analytical artifact, or possibly a result of extreme variability in carbon chemistry surrounding the islands.

A Time-Series View of Changing Ocean Chemistry Due to Ocean Uptake of Anthropogenic CO2 and Ocean Acidification

Sustained observations provide critically needed data and understanding not only about ocean warming and water cycle reorganization (e.g., salinity changes), ocean eutrophication, and ocean deoxygenation, but also about changes in ocean chemistry. As an example of changes in the global ocean carbon cycle, consistent changes in surface seawater CO2-carbonate chemistry are documented by seven independent CO2 time series that provide sustained ocean observations collected for periods from 15 to 30 years: (1) Iceland Sea, (2) Irminger Sea, (3) Bermuda Atlantic Time-series Study (BATS), (4) European Station for Time series in the Ocean at the Canary Islands (ESTOC), (5) CArbon Retention In A Colored Ocean sites in the North Atlantic (CARIACO), (6) Hawaii Ocean Time-series (HOT), and (7) Munida in the Pacific Ocean. These ocean time-series sites exhibit very consistent changes in surface ocean chemistry that reflect the impact of uptake of anthropogenic CO2 and ocean acidification. The article discusses the long-term changes in dissolved inorganic carbon (DIC), salinity-normalized DIC, and surface seawater pCO2 (partial pressure of CO2) due to the uptake of anthropogenic CO2 and its impact on the ocean's buffering capacity. In addition, we evaluate changes in seawater chemistry that are due to ocean acidification and its impact on pH and saturation states for biogenic calcium carbonate minerals.

Annual net community production and the biological carbon flux in the ocean

AbstractThe flux of biologically produced organic matter from the surface ocean (the biological pump), over an annual cycle, is equal to the annual net community production (ANCP). Experimental determinations of ANCP at ocean time series sites using a variety of different metabolite mass balances have made it possible to evaluate the accuracy of sediment trap fluxes and satellite‐determined ocean carbon export. ANCP values at the Hawaii Ocean Time‐series (HOT), the Bermuda Atlantic Time‐series Study (BATS), Ocean Station Papa (OSP) are 3 ± 1 mol C m−2 yr−1—much less variable than presently suggested by satellite remote sensing measurements and global circulation models. ANCP determined from mass balances at these locations are 3–4 times particulate organic carbon fluxes measured in sediment traps. When the roles of dissolved organic carbon (DOC) flux, zooplankton migration, and depth‐dependent respiration are considered these differences are reconciled at HOT and OSP but not at BATS, where measured particulate fluxes are about 3 times lower than expected. Even in the cases where sediment trap fluxes are accurate, it is not possible to “scale up” these measurements to determine ANCP without independent determinations of geographically variable DOC flux and zooplankton migration. Estimates of ANCP from satellite remote sensing using net primary production determined by the carbon‐based productivity model suggests less geographic variability than its predecessor (the vertically generalized productivity model) and brings predictions at HOT and OSP closer to measurements; however, satellite‐predicted ANCP at BATS is still 3 times too low.