Posts Tagged 'methods'

Variability of total alkalinity in coastal surface waters determined using an in-situ analyzer in conjunction with the application of a neural network-based prediction model

Highlights

  • Total Alkalinity (TA) variation in Tong’an Bay observed with in-situ analyzer.
  • The TA variations in late summer and early winter controlled by mixing of water bodies.
  • The diel TA variations mainly influenced by tide.
  • Artificial neural network-based TA prediction model developed for Tong’an Bay.

Abstract

Total alkalinity (TA) is an important variable of the ocean carbonate system. In coastal oceans, carbonate system dynamics are controlled by a range of processes including photosynthesis and respiration, calcification, mixing of water masses, continental inputs, temperature changes, and seasonal upwelling. Assessments of diel, seasonal and interannual variations in TA are required to understand the carbon cycle in coastal oceans. However, our understanding of these variations remains underdeveloped due to limitations in observational techniques. Autonomous TA measurements are therefore required. In this study, an in situ TA analyzer (ISA-TA) based on a single-point titration with spectrophotometric pH detection was deployed in Tong’an Bay, Xiamen, China, over a five-month period in 2021 to determine diel and seasonal TA variations. The TA observations were combined with an artificial neural network (ANN) model to construct TA prediction models for this area. This provided a simple method to investigate TA variations in this region and was applied to predict surface water TA between March and April 2021. The in situ TA observations showed that TA values in Tong’an Bay varied within a range from 1931 to 2294 μmol kg−1 over the study period, with low TA in late winter, early summer and late summer, and high TA in early winter. The TA variations in late summer and early winter were mainly controlled by mixing of water bodies. The diel variations of TA were greatly determined by tides, with a diel amplitude of 9 to 247 μmol kg−1. The ANN model used temperature, salinity, chlorophyll, and dissolved oxygen to estimate TA, with a root-mean-square error (RMSE) of ∼14 μmol kg−1, with salinity as the input variable with the greatest weight. The approach of combining ISA-TA observations with an ANN model can be extended to study the carbonate system in other coastal regions.

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Insights into the response of coral biomineralisation to environmental change from aragonite precipitations in vitro

Precipitation of marine biogenic CaCO3 minerals occurs at specialist sites, typically with elevated pH and dissolved inorganic carbon, and in the presence of biomolecules which control the nucleation, growth, and morphology of the calcium carbonate structure. Here we explore aragonite precipitation in vitro under conditions inferred to occur in tropical coral calcification media under present and future atmospheric CO2 scenarios. We vary pH, ΩAr and pCO2 between experiments to explore how both HCO3 and CO32- influence precipitation rate and we identify the effects of the three most common amino acids in coral skeletons (aspartic acid, glutamic acid and glycine) on precipitation rate and aragonite morphology. We find that fluid ΩAr or [CO32-] is the main control on precipitation rate at 25°C, with no significant contribution from HCO3 or pH. All amino acids inhibit aragonite precipitation at 0.2-5 mM and the degree of inhibition is inversely correlated with ΩAr and, in the case of aspartic acid, also inversely correlated with seawater temperature. Aspartic acid inhibits precipitation the most, of the tested amino acids (and generates changes in aragonite morphology) and glycine inhibits precipitation the least. Previous work shows that ocean acidification increases the amino acid content of coral skeletons and probably reduces calcification media ΩAr, both of which can inhibit aragonite precipitation. This study and previous work shows aragonite precipitation rate is exponentially related to temperature from 10-30°C and small anthropogenic increases in seawater temperature will likely offset the inhibition in precipitation rate predicted to occur due to increased skeletal aspartic acid and reduced calcification media ΩAr under ocean acidification.

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Preliminary assessment of carbonic acid dissociation constants: Insights from observations in China’s east coastal oceans

Based on observations in China’s east coastal oceans, we conducted a preliminary assessment of 16 sets of carbonic acid dissociation constants (K1* and K2*) by comparing spectrophotometrically measured pH values at 25 °C with those calculated from total alkalinity and dissolved inorganic carbon. We obtained that K1* and K2* often performed differently within different salinity ranges, and that the constants of Millero et al. (2002) (M02) demonstrated the best performance for the salinity range of 24–35. In contrast, the often recommended constants of Mehrbach et al. (1973) refit by Dickson and Millero (1987) (DM87-M) and Lucker et al. (2000) (L00) would underestimate pH at salinities of 24–30. This was mainly associated with the higher product of K1* and K2* by DM87-M and L00 than by M02 at this salinity range. Also, we found almost no differences between pH values calculated with DM87-M and L00.

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Hermit crabs as model species for investigating the behavioural responses to pollution

Highlights

  • Pollution can impact behaviour directly and by disrupting cognition.
  • Individual responses can cascade to populations, communities and ecosystems.
  • Hermit crabs provide a globally distributed model for investigating info-disruption
  • Hermit crab behaviour is affected by climate change, chemicals, noise and light.
  • These effects can be readily studied across a wide range of behavioural contexts.

Abstract

Human impacts on the environment affect organisms at all levels of biological organisation and ultimately can change their phenotype. Over time, phenotypic change may arise due to selection but individual phenotypes are also subject to change via genotype × environment interactions. In animals, behaviour is the most flexible aspect of phenotype, and hence the most liable to change across environmental gradients including exposure to pollution. Here we review current knowledge on the impacts of pollution, broadly defined to include the release of substances, energy, and the effects of carbon emissions, on the behaviour of a highly studied group, the globally distributed hermit crabs. We first show how their obligate association with empty gastropod shells underpins their use as model organisms for the study of resource-assessment, contest, and risk-coping behaviours. Intense study of hermit crabs has advanced our understanding of how animals use information, and we discuss the ways in which pollutants can disrupt the cognitive processes involved. We then highlight current studies of hermit crabs, which paint a clear picture of behavioural changes due to multiple pollutants. Impacts on behaviour vary across pollutants and entire suites of behaviours can be influenced by a single pollutant, with the potential for interactive and cascade effects. Hermit crabs offer the opportunity for detailed behavioural analysis, including application of the repeated measures animal-personality framework, and they are highly amenable to experimental manipulations. As such, we show how they now provide a model system for studying the impacts of pollution on behaviour, yielding insights broadly applicable across animal diversity.

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Satellite-based assessments of ocean acidification for the Hawaiian islands region

Ocean acidification (OA) is a growing global environmental concern with impacts affecting regions all over the world, including remote areas such as Hawai‘i. OA is gaining worldwide attention due to environmental impacts including the detrimental effects of OA on coral reefs. Increased anthropogenic release of CO2 into the atmosphere will result in increased absorption by the world oceans. There is a general lack of information regarding small-scale spatiotemporal variations in surface ocean carbon parameters, however satellites and other remote sensing platforms are becoming increasingly utilized for Earth system observations and can be used to help evaluate OA patterns around Hawai‘i. With the use of empirical algorithms, remote measurements of sea surface temperature (SST) and sea surface salinity (SSS) can be used to assess OA patterns in coastal and open-ocean waters around the state. For the purposes of this study, in situ data collected from mooring buoys and ship studies are used to develop empirical algorithms that relate satellite observations to OA conditions for the Hawaiian Islands region (HIR).

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Vulnerability to climate change of United States marine mammal stocks in the western North Atlantic, Gulf of Mexico, and Caribbean

Climate change and climate variability are affecting marine mammal species and these impacts are projected to continue in the coming decades. Vulnerability assessments provide a framework for evaluating climate impacts over a broad range of species using currently available information. We conducted a trait-based climate vulnerability assessment using expert elicitation for 108 marine mammal stocks and stock groups in the western North Atlantic, Gulf of Mexico, and Caribbean Sea. Our approach combined the exposure (projected change in environmental conditions) and sensitivity (ability to tolerate and adapt to changing conditions) of marine mammal stocks to estimate vulnerability to climate change, and categorize stocks with a vulnerability index. The climate vulnerability score was very high for 44% (n = 47) of these stocks, high for 29% (n = 31), moderate for 20% (n = 22), and low for 7% (n = 8). The majority of stocks (n = 78; 72%) scored very high exposure, whereas 24% (n = 26) scored high, and 4% (n = 4) scored moderate. The sensitivity score was very high for 33% (n = 36) of these stocks, high for 18% (n = 19), moderate for 34% (n = 37), and low for 15% (n = 16). Vulnerability results were summarized for stocks in five taxonomic groups: pinnipeds (n = 4; 25% high, 75% moderate), mysticetes (n = 7; 29% very high, 57% high, 14% moderate), ziphiids (n = 8; 13% very high, 50% high, 38% moderate), delphinids (n = 84; 52% very high, 23% high, 15% moderate, 10% low), and other odontocetes (n = 5; 60% high, 40% moderate). Factors including temperature, ocean pH, and dissolved oxygen were the primary drivers of high climate exposure, with effects mediated through prey and habitat parameters. We quantified sources of uncertainty by bootstrapping vulnerability scores, conducting leave-one-out analyses of individual attributes and individual scorers, and through scoring data quality for each attribute. These results provide information for researchers, managers, and the public on marine mammal responses to climate change to enhance the development of more effective marine mammal management, restoration, and conservation activities that address current and future environmental variation and biological responses due to climate change.

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Reproducibility crisis and gravitation towards a consensus in ocean acidification research

Reproducibility is a persistent concern in science and recently attracts considerable attention in assessing biological responses to ocean acidification. Here we track the reproducibility of the harmful effects of ocean acidification on calcification of shell-building organisms by conducting a meta-analysis of 373 studies across 24 years. The pioneering studies tended to report large negative effects, but as other researchers assimilated this research into understanding their biological systems, the size of negative effects declined. Such declines represent a scientific process by which discoveries are initially assimilated and their limitations are subsequently explored. We suggest that scientific novelties can polarize a discipline where researchers fail to distinguish between different motivations for testing a phenomenon, that is, its existence (theory proposal) versus its influence within ever-widening contexts (theory development). Where context dependency is high, the lack of reproducibility may not represent a crisis but a part of theory development and eventual gravitation towards a consensus position.

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Toward citizen science-based ocean acidification observations using smartphone devices

pH is a key parameter in many chemical, biological, and biogeochemical processes, making it a fundamental aspect of environmental monitoring. Rapid and accurate seawater pH measurements are essential for effective ocean observation and acidification investigations, resulting in the need for novel solutions that allow robust, precise, and affordable pH monitoring. In this study, a versatile smartphone-based environmental analyzer (vSEA) was used for the rapid measurement of seawater pH in a field study. The feasibility of the use of the vSEA algorithm for pH quantification was explored and verified. When used in conjunction with a three-dimensional (3D)-printed light-proof shell, the quality of captured images is guaranteed. The quantitative accuracy of vSEA pH measurements reached 0.018 units with an uncertainty of <0.01, meeting the requirements of the Global Ocean Acidification Observing Network (GOA-ON) for “weather” goals (permitting a maximum pH uncertainty of 0.02). The vSEA–pH system was successfully applied for on-site pH measurements in coastal seawater and coral systems. The performance of the vSEA–pH system was validated using different real-world samples, and t-test results showed that the vSEA–pH system was consistent with pH measurements obtained using a state-of-the-art benchtop spectrophotometer (t = 1.986, p = 0.7949). The vSEA–pH system is applicable to different types of smartphone devices, making it possible for vSEA–pH to be widely promoted for public citizen use. The vSEA–pH system offers a simple, accurate, and applicable method for the on-site measurement of seawater pH, assisting the large-scale monitoring of ocean acidification by allowing the contribution of citizen science-based data collection.

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More than marine heatwaves: a new regime of heat, acidity, and low oxygen compound extreme events in the Gulf of Alaska

Recent marine heatwaves in the Gulf of Alaska have had devastating and lasting impacts on species from various trophic levels. As a result of climate change, total heat exposure in the upper ocean has become longer, more intense, more frequent, and more likely to happen at the same time as other environmental extremes. The combination of multiple environmental extremes can exacerbate the response of sensitive marine organisms. Our hindcast simulation provides the first indication that more than 20 % of the bottom water of the Gulf of Alaska continental shelf was exposed to quadruple heat, positive [H+], negative Ωarag, and negative [O2] compound extreme events during the 2018-2020 marine heat wave. Natural intrusion of deep and acidified water combined with the marine heat wave triggered the first occurrence of these events in 2019. During the 2013-2016 marine heat wave, surface waters were already exposed to widespread marine heat and positive [H+] compound extreme events due to the temperature effect on the [H+]. We introduce a new Gulf of Alaska Downwelling Index (GOADI) with short-term predictive skill, which can serve as indicator of past and near-future positive [H+], negative Ωarag, and negative [O2] compound extreme events on the shelf. Our results suggest that the marine heat waves may have not been the sole environmental stressor that led to the observed ecosystem impacts and warrant a closer look at existing in situ inorganic carbon and other environmental data in combination with biological observations and model output.

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Anthropogenic carbon estimation in the surface ocean from atmospheric CO2 fugacity at the BATS (Bermuda Atlantic time-series study) station

In surface seawater, it is usually very difficult to quantify anthropogenic carbon concentrations. Many processes (such as air-sea exchanges of gases and heat, biological activity, and mixing of water masses), are at play and often on different timescales. Thus, various hypotheses are used to estimate the anthropogenic concentrations in surface waters. Here, using the relatively long (1980s to present) time series data sets from the Bermuda Atlantic Time-series Study site (BATS; 31°40′N, 64°10′W) in the North Atlantic Ocean, we evaluate results based upon two different hypotheses. The results clearly confirm that it is very difficult to assess anthropogenic carbon concentrations in surface waters from sole oceanic properties. However, this study further indicates that at this ocean site, they can be appropriately determined from low-frequency variations of atmospheric CO2 concentrations. Consequently, the impact of anthropogenic carbon penetration in surface waters on their acidification could be predicted.

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Development of optical fibre pH sensors for marine microenvironments

The oceans absorb approximately one-third of the CO2 emission into the atmosphere causing a decline in seawater pH, a process known as ocean acidification (OA). This decline in pH reflects changes to the seawater carbonate system and is expected to have an impact on the marine environment and ecosystems. pH changes along coastal ecosystems are highly variable and knowledge of these marine environments can be used to enhance our understanding of OA impacts on marine organisms.

The micro-to-centimetre thick layer directly surrounding many aquatic organisms is known as the diffusion boundary layer (DBL). The DBL creates a region which reduces the exposure of calcifying species to OA conditions. The pH within the DBL is dependent on light-controlled metabolic activities and exhibits different pH behaviour to bulk seawater. The challenge of detecting in situ pH variations and attributing OA effects highlights a need for a fresh research approach and innovative analyses.

The objective of this research is to develop optical fibre pH sensors capable of continuous pH measurement, and suitable for measuring pH variation in marine microenvironments. The development, characterisation, and applications of optical fibre pH sensors are described. The pH sensing components consist of pH-sensitive indicators immobilised in an optimised sol-gel matrix, minimising indicator leaching without the need for a covalent bond. This research explores two approaches, absorbance-based and fluorescence-based pH sensors.

The absorbance-based sensor applied meta-cresol purple (mCP) as the pH-sensitive indicator. The pH sensor has a usable lifetime of 7 days and a dynamic range of pH 7.4 to 9.7. This self-referencing pH sensor was utilised for real-time pH measurements within the DBL of the seaweed Ulva sp., and successfully used to monitor metabolic activity for 100 hours, achieving a precision of 0.02 pH units. This sensor conformed to the GOA-ON Weather quality guideline and demonstrated its capability to identify short-term variation in biological and environmental studies.

The fluorescence pH sensor utilises a time-domain dual-lifetime referencing scheme (t-DLR). The fluorescence pH sensing materials required the synthesis of pH-sensitive iminocoumarin and the encapsulation of pH-inert reference Ru(dpp)3 in polyacrylonitrile (PAN). The pH is determined from the ratio of the combined excitation intensity to the emission intensity of the reference indicator. This approach allows the signal to be referenced internally, independent of fluorescence dye concentration and variations in excitation light intensity. The t-DLR instrumentation used commercial electronic and optical components, integrated with custom-made electronic circuits. The pH sensor has a dynamic range of pH 7.8 to 9.3 and a precision of 0.02 pH units. The pH sensor was insensitive to changes in salinity and had negligible dye leaching and minimal photobleaching.

This work accomplished the development of mCP-based and dual-layer t-DLR fluorescent-based optical fibre pH sensors. This highlights the versatility of optical fibre pH sensors and the potential for a wider range of applications.

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Implementing a coral reef CaCO3 production module in the iLOVECLIM climate model

Coral reef development is intricately linked to both climate and the concentration of atmospheric CO2, specifically through temperature and carbonate chemistry in the upper ocean. In turn, the calcification of corals modifies the concentration of dissolved inorganic carbon and total alkalinity in the ocean, impacting air-sea gas exchange, atmospheric CO2 concentration, and ultimately the climate. This retroaction between atmospheric conditions and coral biogeochemistry can only be accounted for with a coupled coral-carbon-climate model. Here we present the implementation of a coral reef calcification module into an Earth System model. Simulated coral reef production of the calcium carbonate mineral aragonite depends on photosynthetically active radiation, nutrient concentrations, salinity, temperature and the aragonite saturation state. An ensemble of 210 parameter perturbation simulations was performed to identify carbonate production parameter values that optimise the simulated distribution of coral reefs and associated carbonate production. The tuned model simulates the presence of coral reefs and regional-to-global carbonate production values in good agreement with data-based estimates. The model enables assessment of past and future coral-climate coupling on seasonal to millennial timescales, highlighting how climatic trends and variability may affect reef development and the resulting climate-carbon feedback.

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Laboratory experiments in ocean alkalinity enhancement research

Recent concern about the consequences of continuing increases in atmospheric CO2 as a key heat-trapping agent (USGCRP, 2017; IPCC, 2021) have prompted ocean experts to come together to discuss how to provide science-based solutions. Ocean alkalinity enhancement (OAE) is being considered not only as a ocean carbon dioxide removal (CDR) approach, but also as a potential way to mitigate ocean acidification. Over the last two decades, inter-laboratory comparisons have proven valuable in evaluating the reliability of methodologies associated with sampling and analysis of carbonate chemistry parameters, which have been routinely used in ocean acidification research (Bockmon and Dickson, 2015). Given the complexity of processes and mechanisms related to ecosystem responses to OAE, consolidating protocols to ensure compatibility across studies is fundamental for synthesis and upscaling analysis. This chapter provides an overview of best practice in OAE laboratory experimentation and facilitates awareness of the importance of applying standardized methods to promote data re- use, inter-lab comparisons, and transparency. This chapter provides the reader with the tools to (1) identify the criteria to achieve the best laboratory practice and experimental design; (2) provide guidance on the selection of response variables for various purposes (physiological, biogeochemical, ecological, evolutionary) for inter-lab comparisons; (3) offer recommendation for a minimum set of variables that should be sampled and propose additional variables critical for different types of synthesis and upscaling; and (4) identify protocols for standardized measurements of response variables.

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Mesocosm experiments in ocean alkalinity enhancement research

An essential prerequisite for the implementation of ocean alkalinity enhancement (OAE) applications is their environmental safety. Only if it can be ensured that ecosystem health and ecosystem services are not at risk will the implementation of OAE move forward. Public opinion on OAEs will depend first and foremost on reliable evidence that no harm will be done to marine ecosystems and licensing authorities will demand measurable criteria against which environmental sustainability can be determined. In this context mesocosm experiments represent a highly valuable tool in determining the safe operating space of OAE applications. By combining realism and biological complexity with controllability and replication they provide an ideal OAE test bed and a critical stepping stone towards field applications. Mesocosm approaches can also be helpful in testing the efficacy, efficiency and permanence of OAE applications. This chapter outlines strengths and weaknesses of mesocosm approaches, illustrates mesocosm facilities and suitable experimental designs presently employed in OAE research, describes critical steps in mesocosm operation, and discusses possible approaches for alkalinity manipulation and monitoring. Building on a general treatise on each of these aspects, the chapter describes pelagic and benthic mesocosm approaches separately, given their inherent differences. The chapter concludes with recommendations for best practices in OAE-related mesocosm research.

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Seawater carbonate system considerations for ocean alkalinity enhancement research

Ocean alkalinity enhancement (OAE) is a proposed marine carbon dioxide removal (mCDR) approach that has the potential for large-scale uptake of significant amounts of atmospheric carbon dioxide (CO2). Removing anthropogenic legacy CO2 will be required to stabalise global surface temperatures below the 1.5–2 °C Paris Agreement target of 2015. In this chapter we describe the impacts of various OAE feedstocks on seawater carbonate chemistry, as well as pitfalls that need to be avoided during sampling, storage and measurement of the four main carbonate chemistry parameters, i.e. dissolved inorganic carbon (DIC), total alkalinity (TA), pH and CO2 fugacity (fCO2). Finally, we also discuss considerations in regard to calculating carbonate chemistry speciation from two measured parameters.

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Forecasting seasonal changes in ocean acidification using a novel Grey Seasonal Model with Grey Wolf Optimization

Ocean acidification forecasting has important implications for studying global carbon dioxide emissions reductions. However, due to seasonal and cyclical features, ocean acidification forecasting remains an extremely challenging task. Therefore, this paper proposes a grey wolf optimized fractional-order-accumulation discrete grey seasonal model (GFSM(1,1)). The GFSM(1,1) model improves the prediction of ocean acidification in two ways: The new information priority of seasonal data is improved by the fractional accumulation operator, and the adaptability of the grey model to seasonal data is increased by seasonal item parameters. The above two works have significantly improved the prediction accuracy of the grey prediction model for ocean acidification. The prediction results in practical cases prove that the prediction effect of the GFSM(1,1) model is not only better than the existing grey models (FMGM(1,N). NSGM(1,N), and GM(1,1)) but also better than statistical models (Nonlinear regression and ARIMA), traditional neural network model (LSTM) and deep learning model (SVM). Finally, the GFSM(1,1) model is applied to the prediction of seawater acidification. The forecast results show that the ocean will be acidified at a rate of 0.001863 per year, and the pH of the ocean will decrease by about 0.03% per year compared to the same period in previous years.

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Succession of ocean acidification and its effects on reef-building corals

Since 2008, we have been conducting a series of coral-rearing experiments, mainly at the Sesoko Station of the Tropical Biosphere Research Center at the University of the Ryukyus, under an overarching project, called the Acidification Impact on Calcifiers project (AICAL project). The AICAL project integrates the efforts of several individual research programs, and project members employ a custom-made, high-precision pCO2-adjusted seawater generator (the AICAL apparatus) to study the effects of ocean acidification on marine calcifying organisms. With this system, rearing experiments can be conducted under conditions mimicking those in the preindustrial era, and the future. In this review, we summarize the results of ocean acidification experiments on corals and other organisms, with a focus on studies conducted by the AICAL project members. We examine the response of organisms to ocean acidification in a hierarchical fashion: differences among various groups of calcifying organisms, and interspecific and intraspecific variation in corals. In the case of corals, we consider not only the effects of ocean acidification, but also those caused by rising seawater temperatures and eutrophication. Our major findings are that coral calcification may have already decreased from a preindustrial level and that there are evident interspecific and intraspecific differences in tolerance against ocean acidification. These findings suggest future decrease of coral cover, accompanied by species compositional changes under climate change scenarios.

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Methane-derived authigenic carbonates – a case for a globally relevant marine carbonate factory

Precipitation of methane-derived authigenic carbonates (MDAC) is an integral part of marine methane production and consumption, but MDAC’s relative significance to the global marine carbon cycle is not well understood. Here we provide a synthesis and perspective to highlight MDAC from a global marine carbon biogeochemistry viewpoint. MDAC formation is a result and archive of carbon‑sulfur (C – S) coupling in the shallow sulfatic zone and carbon‑silicon (C – Si) coupling in deeper methanic sediments. MDAC constitute a carbon sequestration of 3.93 Tmol C yr−1 (range 2.34–5.8 Tmol C yr−1) in the modern ocean and are the third-largest carbon burial mechanism in marine sediments. This burial compares to 29% (11–57%) organic carbon and 10% (6–23%) skeletal carbonate carbon burial along continental margins. MDAC formation is also an important sink for benthic alkalinity and, thereby, a potential contributor to bottom water acidification. Our understanding of the impact of MDAC on global biogeochemical cycles has evolved over the past five decades from what was traditionally considered a passive carbon sequestration mechanism in a seep-oasis setting to what is now considered a dynamic carbonate factory expanding from deep sediments to bottom waters—a factory that has been operational since the Precambrian. We present a strong case for the need to improve regional scale quantification of MDAC accumulation rates and associated carbonate biogeochemical parameters, leading to their incorporation in present and paleo‑carbon budgets in the next phase of MDAC exploration.

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Organic alkalinity dynamics in Irish coastal waters: case study Rogerstown Estuary

Highlights

  • OrgAlk can be an important fraction of TA in coastal waters.
  • OrgAlk acid-base properties are suggestive of carboxyl and phenolic-like signals.
  • Complementary fluorescence analysis of DOM can elucidate origins and transformations of OrgAlk.
  • OrgAlk can lead to the propagation of uncertainty on calculated carbonate parameters.

Abstract

Total alkalinity (TA) is a popularly measured carbonate system parameter and is widely used in calculations of key carbonate system descriptors such as the calcium carbonate saturation state, an important indicator of ocean acidification. Organic alkalinity (OrgAlk) is recognised as a contributor to TA in coastal waters, with this having implications on the use of TA to calculate key carbonate chemistry descriptors. As titratable charge groups of OrgAlk can act as unknown acid-base species, the inclusion of the total concentration and apparent dissociation constants of OrgAlk in carbonate calculations involving TA is required to minimise uncertainty in computed speciation. Here we present an investigation of the prevalence and properties of OrgAlk as well as the impact of OrgAlk on carbonate chemistry calculations in a transitional waterbody. Water samples were collected during low and high tide over a 5-week period in Rogerstown Estuary, Dublin Ireland. TA and OrgAlk were measured using modified Global Ocean Acidification Observing Network (GOA-ON) titration apparatus in conjunction with OrgAlkCalc, an open-source Python based computational programme. pH was measured on the total scale using meta-cresol purple (mCP) as the indicator dye. Dissolved inorganic carbon (DIC), the partial pressure of CO2 (pCO2), in situ pH on the total scale (pHT) and the saturation state of aragonite (∆ΩA) were calculated using pH and both OrgAlk adjusted TA and measured TA as the input parameters. Optical analysis of DOM was conducted to compliment OrgAlk characterisations and to further elucidate OrgAlk sources and dynamics. OrgAlk charge groups concentrations ranged from 35,198 μmol·kg−1, with the highest concentrations observed in more marine waters. Two apparent charge groups were associated with OrgAlk, with pK values of 4.38 ± 0.27 and 6.95 ± 0.43. Differences between calculated carbonate system parameters when using OrgAlk adjusted TA and non-OrgAlk adjusted TA ranged from 88 to 254 μmol·kg−1 DIC, −98–67 μatm pCO2, −0.02–0.12 pHT and 0.02–0.64 ∆ΩA. Variability in the differences in calculated carbonate systems was largely a factor of OrgAlk charge group concentration and pK. This work highlights the importance of considering OrgAlk if using TA as an input parameter in carbonate system investigations of coastal waters.

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Predicting carbonate chemistry on the Northwest Atlantic shelf using neural networks

The Northwest Atlantic Shelf (NAS) region has experienced accelerated warming, heatwaves, and is susceptible to ocean acidification, yet also suffers from a paucity of carbonate chemistry observations, particularly at depth. We address this critical data gap by developing three different neural network models to predict dissolved inorganic carbon (DIC) and total alkalinity (TA) in the NAS region from more readily available hydrographic and satellite data. The models predicted DIC with r2 between 0.913 – 0.963 and root mean square errors (RMSE) between 15.4 – 23.7 (µmol kg-1) and TA with r2 between 0.986 – 0.983 and RMSE between 9.0 – 10.4 (µmol kg-1) on an unseen test data set that was not used in training the models. Cross-validation analysis revealed that all models were insensitive to the choice of training data and had good generalization performance on unseen data. Uncertainty in DIC and TA were low (coefficients of variation 0.1-1%). Compared with other predictive models of carbonate system variables in this region, a larger and more diverse dataset with full seasonal coverage and a more sophisticated model architecture resulted in a robust predictive model with higher accuracy and precision across all seasons. We used one of the models to generate a reconstructed seasonal distribution of carbonate chemistry fields based on DIC and TA predictions that shows a clear seasonal progression and large spatial gradients consistent with observations. The distinct models will allow for a range of applications based on the predictor variables available and will be useful to understand and address ocean sustainability challenges.

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