the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
A global database of dissolved organic matter (DOM) concentration measurements in coastal waters (CoastDOM v1)
Cátia Carreira
Gwenaël Abril
Susana Agustí
Valentina Amaral
Agneta Andersson
Javier Arístegui
Punyasloke Bhadury
Mariana B. Bif
Alberto V. Borges
Steven Bouillon
Maria Ll. Calleja
Luiz C. Cotovicz Jr.
Stefano Cozzi
Maryló Doval
Carlos M. Duarte
Bradley Eyre
Cédric G. Fichot
E. Elena García-Martín
Alexandra Garzon-Garcia
Michele Giani
Rafael Gonçalves-Araujo
Renee Gruber
Dennis A. Hansell
Fuminori Hashihama
Johnna M. Holding
William R. Hunter
J. Severino P. Ibánhez
Valeria Ibello
Shan Jiang
Guebuem Kim
Katja Klun
Piotr Kowalczuk
Atsushi Kubo
Choon-Weng Lee
Cláudia B. Lopes
Federica Maggioni
Paolo Magni
Celia Marrase
Patrick Martin
S. Leigh McCallister
Roisin McCallum
Patricia M. Medeiros
Xosé Anxelu G. Morán
Frank E. Muller-Karger
Allison Myers-Pigg
Marit Norli
Joanne M. Oakes
Helena Osterholz
Hyekyung Park
Maria Lund Paulsen
Judith A. Rosentreter
Jeff D. Ross
Digna Rueda-Roa
Chiara Santinelli
Yuan Shen
Eva Teira
Tinkara Tinta
Guenther Uher
Masahide Wakita
Nicholas Ward
Kenta Watanabe
Yu Xin
Youhei Yamashita
Liyang Yang
Jacob Yeo
Huamao Yuan
Qiang Zheng
Xosé Antón Álvarez-Salgado
Measurements of dissolved organic carbon (DOC), nitrogen (DON), and phosphorus (DOP) concentrations are used to characterize the dissolved organic matter (DOM) pool and are important components of biogeochemical cycling in the coastal ocean. Here, we present the first edition of a global database (CoastDOM v1; available at https://doi.org/10.1594/PANGAEA.964012, Lønborg et al., 2023) compiling previously published and unpublished measurements of DOC, DON, and DOP in coastal waters. These data are complemented by hydrographic data such as temperature and salinity and, to the extent possible, other biogeochemical variables (e.g. chlorophyll a, inorganic nutrients) and the inorganic carbon system (e.g. dissolved inorganic carbon and total alkalinity). Overall, CoastDOM v1 includes observations of concentrations from all continents. However, most data were collected in the Northern Hemisphere, with a clear gap in DOM measurements from the Southern Hemisphere. The data included were collected from 1978 to 2022 and consist of 62 338 data points for DOC, 20 356 for DON, and 13 533 for DOP. The number of measurements decreases progressively in the sequence DOC > DON > DOP, reflecting both differences in the maturity of the analytical methods and the greater focus on carbon cycling by the aquatic science community. The global database shows that the average DOC concentration in coastal waters (average ± standard deviation (SD): 182±314 µmol C L−1; median: 103 µmol C L−1) is 13-fold higher than the average coastal DON concentration (13.6±30.4 µmol N L−1; median: 8.0 µmol N L−1), which is itself 39-fold higher than the average coastal DOP concentration (0.34±1.11 µmol P L−1; median: 0.18 µmol P L−1). This dataset will be useful for identifying global spatial and temporal patterns in DOM and will help facilitate the reuse of DOC, DON, and DOP data in studies aimed at better characterizing local biogeochemical processes; closing nutrient budgets; estimating carbon, nitrogen, and phosphorous pools; and establishing a baseline for modelling future changes in coastal waters.
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Coastal waters are the most biogeochemically dynamic areas of the ocean, exhibiting the highest standing stocks, process rates, and transport fluxes of carbon (C), nitrogen (N), and phosphorus (P) per unit area (Bauer et al., 2013; Mackenzie et al., 2011). In these areas, organic matter plays a critical role in numerous biogeochemical processes, serving as both a C, N, and P reservoir and substrate (Carreira et al., 2021).
Organic material found in the marine environment is commonly distinguished by its size; material retained on a filter with a pore size typically between 0.2 and 0.7 µm is classified as particulate organic matter (POM), whereas organic matter that passes through the filter is referred to as dissolved organic matter (DOM). This partitioning is operational but has implications for biogeochemical cycling: POM can be suspended in the water column or sink to the sediments controlled by its size, shape, and density (Laurenceau-Cornec et al., 2015), whereas DOM is a solute that mostly remains in the water column. In most coastal waters, DOM concentrations are higher than POM, with POM having a larger proportion of known biochemical classes (e.g. carbohydrates, proteins) than the dissolved fraction, suggesting that, generally, DOM is more reworked and recalcitrant (Boudreau and Ruddick, 1991; Lønborg et al., 2018; Benner and Amon, 2015).
The DOM pool consists mainly of C (DOC), N (DON), and P (DOP), but it also includes other elements such as oxygen, sulfur, and trace elements (Lønborg et al., 2020). In coastal waters, DOM originates from multiple sources. Internal, or autochthonous, sources include planktonic organisms (Lønborg et al., 2009; Carlson and Hansell, 2015), benthic microalgae, macrophytes, and sediment porewater (Burdige and Komada, 2014; Wada et al., 2008). On the other hand, DOM from external, or allochthonous, sources, has mainly terrestrial origins, including wetlands, river and surface runoff, groundwater discharges, and atmospheric deposition (Iavorivska et al., 2016; Raymond and Spencer, 2015; Taniguchi et al., 2019; Santos et al., 2021). The main sinks for DOM from the water column in coastal waters are the following: (1) bubble coagulation and abiotic flocculation (Kerner et al., 2003) or sorption to particles (Chin et al., 1998), (2) sunlight-mediated photodegradation (Mopper et al., 2015), and (3) microbial degradation by mainly heterotrophic prokaryotes (Lønborg and Álvarez-Salgado, 2012).
Given the importance of DOM as a source of nutrients and for coastal biogeochemical cycling in general, numerous studies have measured the C, N, and P contents of the DOM pool over the last few decades (e.g. García-Martín et al., 2021; Cauwet, 2002; Osterholz et al., 2021). Most data, however, are often unavailable or stored in an inaccessible manner, making it difficult to, for example, analyse global spatial and temporal patterns effectively. Global open ocean DOM data compilation for DOC, total dissolved nitrogen (TDN) (Hansell et al., 2021), and DOP (Liang et al., 2022; Karl and Björkman, 2015) already exists and contains a few coastal samples (<200 m) (Hansell et al., 2021), but there are no compilations specifically focused on coastal waters. Hence, there is a clear need for a comprehensive global and integrated database of DOC, DON, and DOP measurements for coastal waters. To address this need, we have prepared the first edition of a coastal DOM database (named CoastDOM v1), by compiling both previously reported as well as unpublished data. These data have been obtained from authors of the original studies or extracted directly from the original studies. In order to allow the DOM measurements to be interpreted across larger scales, and to better understand their relationship with local environmental conditions, we have included concurrently collected ancillary data (such as physical and/or chemical seawater properties) whenever available. The objective of this database is multifaceted. Firstly, we aimed to compile all available coastal DOM data into a single repository. Secondly, our intention was to make these data easily accessible to the research community. And thirdly, we sought to achieve long-term consistency of the measurements to enable data intercomparison and establish a robust baseline for assessing, for example, the impacts of climate change and land use changes.
2.1 Data compilation
The measurements included in CoastDOM v1 were obtained directly from authors of previously published studies, from online databases, or from scientific papers. An extensive search of published reports, PhD theses, and peer-reviewed literature was performed to identify studies dealing with DOM in coastal waters. First, a formal search was performed using Google Scholar in January 2022 using the search terms “dissolved organic carbon”, “dissolved organic nitrogen”, and “dissolved organic phosphorus” in connection with “marine” or “ocean”, which yielded a total of 897 articles (after filtering the query by searching content in the title and abstract and excluding non-coastal articles). When data could not be obtained directly from the corresponding authors, relevant data were extracted. Further searches for relevant datasets were conducted using the reference lists of the identified scientific papers as well as databases and repositories to capture as many datasets as possible. Additionally, research groups that were invited to participate in this effort were also encouraged to submit unpublished data to CoastDOM v1.
2.2 Dissolved organic matter analysis
The DOC concentrations included in CoastDOM v1 were commonly measured using a total organic carbon (TOC) high-temperature catalytic oxidation (HTCO) analyser (81 % of samples; Sharp et al., 1993). Some were measured by a combined wet chemical oxidation (WCO) step and/or UV digestion, after which the carbon dioxide generated was quantified (19 % of samples). Similarly, concentrations of total dissolved nitrogen (TDN; Sipler and Bronk, 2015) were determined using either a nitric oxide chemiluminescence detector connected in series with the HTCO analyser used for DOC analyses (31 % of the samples) or by employing a UV and/or chemical oxidation step (69 %). In the latter approach, both organic and inorganic N compounds were oxidized to nitrate, which was subsequently quantified through a colorimetric method to determine the concentration of inorganic N (Valderrama, 1981; Álvarez-Salgado et al., 2023; Halewood et al., 2022; Foreman et al., 2019). Another method used for DON determination is oxidizing the sample and measuring the resulting total nitrate by the nitric oxide chemiluminescence method (Knapp et al., 2005). However, none of the concentration measurements included in CoastDOM v1 applied this method. The reported DON concentrations were calculated as the difference between TDN and dissolved inorganic nitrogen (DIN: sum of ammonium (NH) and nitrate/nitrite (NO + NO); DON = TDN − DIN) (Álvarez-Salgado et al., 2023). Analyses of total dissolved phosphorus (TDP) were determined by UV (4 %), wet chemical oxidation (66 %), or a combination of these (30 %), and they were subsequently analysed for inorganic phosphorus by a colorimetric method (Álvarez-Salgado et al., 2023). Another method also previously used for TDP analysis is the ash/hydrolysis method (Solorzano and Sharp, 1980), even though none of the data included in CoastDOM v1 used this method. The DOP concentrations were calculated as the difference between TDP and soluble reactive phosphorus (SRP: HPO) (DOP = TDP − SRP) (Álvarez-Salgado et al., 2023).
The data compiled in CoastDOM v1 were collected, analysed and processed by different laboratories; however, all data included have undergone quality control measures, either by using reference samples or internal quality assurance procedures. While many of the included DOC and TDN data have been systematically compared against consensus reference material (CRM), mainly provided by the University of Miami's CRM programme (Hansell, 2005), there is a limitation in CoastDOM v1 regarding the inter-calibration across different measurement systems used for both DOP and DON determination. While the CRM could be used for DOC, DON, and DOP measurements, this has not yet been attempted for DOP, and measurement uncertainties increase in the sequence DOC > DON > DOP. Although some of the reported measurements have quantified the DOP recovery based on commercially available DOP compounds such as adenosine triphosphate (ATP), it is not known if these were conducted systematically in all cases. Therefore, we strongly recommend undertaking further inter-calibration across laboratories for future measurements of TDP, as has been done for DOC and TDN measurements (e.g. Sharp et al., 2002). Since additional quality control is not possible in retrospect, we assessed the quality of CoastDOM v1 based on its internal consistency.
In CoastDOM v1, we defined “coastal water” as encompassing estuaries (salinity >0.1) to the continental shelf break (water depth <200 m). However, some locations, such as deep fjords which are close to the coast, cannot be classed as coastal due to bathymetry (deeper than >200 m). Therefore, we evaluated the inclusion of some datasets on a case-by-case basis. For inclusion in the database, each DOM measurement needed, at a minimum, to contain the following information (if reported in the original publication or otherwise available):
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country where samples were collected,
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latitude of measurement (in decimal degree),
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longitude of measurement (in decimal degree),
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year of sampling,
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month of sampling,
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sampling day (when available),
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depth (m) at which the discrete samples were collected,
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temperature (°C) of the sample,
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salinity of the sample,
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dissolved organic carbon (DOC) concentration (µmol L−1),
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method used to measure DOC concentration,
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DOC − QA flag: quality flag for DOC measurement,
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dissolved organic nitrogen (DON) concentration (µmol L−1),
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total dissolved nitrogen (TDN) concentration (µmol L−1),
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method used to measure TDN concentration,
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TDN − QA flag: quality flag for TDN measurement,
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dissolved organic phosphorus (DOP) concentration (µmol L−1),
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total dissolved phosphorus (TDP) concentration (µmol L−1),
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method used to measure TDP concentration,
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TDP − QA flag: quality flag for TDP measurement,
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responsible person,
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originator institution,
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contact info of data originator.
It should be noted that in all entries at least DOC, DON, or DOP should have been measured. In addition, we also included other relevant data, when available, in the CoastDOM v1 dataset:
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depth at the station where the sample was collected (Bottom depth, metres),
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total suspended solid (TSS) concentration (mg L−1),
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chlorophyll a (Chl a) concentration (µg L−1),
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chl a − QA flag: quality flag for chlorophyll a measurement,
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sum of nitrate and nitrite (NO NO) concentration (µmol L−1),
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NO NO − QA flag: quality flag for NO NO measurement,
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ammonium (NH) concentration (µmol L−1),
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NH − QA flag: quality flag for NH measurement,
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soluble reactive phosphorus (HPO) concentration (µmol L−1),
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HPO − QA flag: quality flag for HPO measurement,
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particulate organic carbon (POC) concentration (µmol L−1),
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method used to measure POC concentration,
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POC − QA flag: quality flag for POC measurement,
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particulate nitrogen (PN) concentration (µmol L−1),
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method used to measure PN concentration,
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PN − QA flag: quality flag for PN measurement,
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particulate phosphorus (PP) concentration (µmol L−1),
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method used to measure PP concentration,
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PP − QA flag: quality flag for PP measurement,
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dissolved inorganic carbon (DIC) concentration (µmol kg−1),
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DIC − QA flag: quality flag for DIC measurement,
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total alkalinity (TA) concentration (µmol kg−1),
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TA − QA flag: quality flag for TA measurement.
Quality control of large datasets is crucial to ensure their reliability and usefulness. Thus, we have not included data that were deemed compromised, such as records that had not gone through quality control by the data originators. We also accepted a certain degree of measurement error since multiple groups have been involved in the collection, analysis, and/or compilation of the information. Some of these errors were corrected (e.g. when a value was placed in a wrong column or when clearly inaccurate locations were reallocated for consistency with the place of study), while others could not be rectified (e.g. values showing clear signs of contamination) and were consequently excluded from CoastDOM v1 (Fig. 1). It should also be noted that differences in analytical capabilities between laboratories and individual measurement campaigns likely caused additional uncertainty. Outliers, arising, for example, from contamination, were removed from the dataset. The data were moreover screened for zero values (i.e. concentrations below the detection limit or absence of data). In cases where concentrations were below the detection limit, the zero values were replaced with half the value of the limit of detection. Commonly reported detection limits are 4 µmol L−1 for DOC, 0.3 µmol L−1 for DON, and are 0.03 µmol L−1 for DOP.
To ensure the inclusion of only high-quality data, we only accepted entries with specific World Ocean Circulation Experiment (WOCE) quality codes: “2: Acceptable measurement” and “6: Mean of replicate measurements”. In our quality control assessments, we carefully avoided overly strict criteria, known as “data grooming”, which could potentially overlook genuine patterns and changes in the dataset that may be significant over longer temporal and/or wider spatial scales. Coastal waters are known to exhibit a wide range of environmental concentrations, influenced by factors such as seasonality and local anthropogenic activities. Consequently, these data points may encompass a wide concentration range. However, obtaining consistent long-term datasets is important to enable data intercomparison and establish a robust baseline. Such long-term consistency can be achieved by using the CRM standards provided by the Hansell laboratory for DOC and TDN. Another helpful approach is comparing the DOM concentrations obtained by different laboratories in the same study area and time of year.
3.1 Summary of dissolved organic carbon (DOC) concentration observations
Measurements of DOC concentrations were conducted between 1978 to 2022, with a total of 62 338 individual data points (Table 1). The DOC concentrations ranged from 17 to 30 327 µmol C L−1 (average ± standard deviation (SD): 182±314 µmol C L−1; median: 103 µmol C L−1; Table 1). The majority (53 %) of the concentrations fell within the range of 60 to 120 µmol C L−1 (Fig. 2). A large number of DOC concentration observations (17 %) ranged between 300 and 600 µmol C L−1, which were predominantly collected in eutrophic and river-influenced coastal waters of the Northern Hemisphere, such as the Baltic Sea (Fig. 2). It was observed that 75 % of the DOC concentrations were higher than 77 µmol C L−1, while 25 % of the measurements surpassed 228 µmol C L−1 (Table 1).
Coastal environments that experience minimal continental runoff, such as Palmer Station in Antarctica, typically exhibit low DOC concentrations. On the other hand, coastal waters heavily influenced by humic-rich terrigenous inputs, such as the Sarawak region in Malaysia, tended to have high DOC concentrations. In addition, some extremely high DOC concentrations were measured in the River Derwent in Australia, which is impacted by paper mill effluents. There has been a large increase in the number of DOC concentration observations after 1992 (Fig. 3), and those measurements were from a wide range of locations. However, these concentration observations were not evenly distributed around the globe, with the Southern Hemisphere being under-sampled (10 % of observations), especially in the African, South American, and Antarctic continents (Figs. 3, 4).
3.2 Summary of dissolved organic nitrogen (DON) concentration observations
The DON concentration measurements were collected between 1990 and 2021, with a total of 20 356 data points (Table 1). Concentrations of DON ranged from <0.1 to 2095.3 µmol N L−1 (average ± SD: 13.6±30.4 µmol N L−1; median: 8.0 µmol N L−1; Table 1), with the most common range (42 %) for DON concentrations between 4 to 8 µmol N L−1 (Fig. 2). Overall, 75 % of DON concentrations were above 5.5 µmol N L−1, while 25 % were above 15.8 µmol N L−1 (Table 1).
The lowest DON concentrations were recorded in Young Sound, Greenland, which receives direct runoff from the Greenland Ice Sheet, whereas the highest concentrations were detected during a flood event in the Richmond River estuary, Australia. Since 1995, there has been a large increase in the number of DON measurements conducted in coastal waters globally (Fig. 3); however, the majority of those measurements have been in the Northern Hemisphere (79 % of observations), mostly in Europe and the United States (Figs. 3, 4).
3.3 Summary of dissolved organic phosphorus (DOP) concentration observations
CoastDOM v1 includes a total of 13 533 DOP measurements, collected between 1990 and 2021 (Table 1). Overall, DOP concentrations ranged from <0.10 to 84.27 µmol P L−1 (average ± SD: 0.34±1.11 µmol P L−1; median: 0.18 µmol P L−1; Table 2). The majority (74 %) of DOP concentrations were below 0.30 µmol P L−1 (Fig. 2). Analysis of the DOP dataset revealed that 75 % of the concentrations were above 0.11 µmol P L−1, while 25 % were above 0.30 µmol P L−1 (Table 1).
The lowest DOP concentrations were measured off the Kimberley Coast in Australia, while the highest concentrations were found in the Vasse-Wonnerup Estuary in the southwest region of Australia. Similar to DOC and DON, most of the DOP measurements have been conducted from the 1990s onwards, with a predominant focus in the Northern Hemisphere (70 % of observations), particularly in Europe and the United States (Figs. 3, 4).
3.4 Summary of dissolved organic matter (DOM) concentration observations
In CoastDOM v1, the number of measurements decreases progressively in the sequence DOC > DON > DOP (62 338, 20 356, and 13 533, respectively), reflecting both differences in the maturity of the analytical methods and the greater focus on carbon cycling by the aquatic science community. In addition, the average DOC concentration in coastal waters ((182±314) µmol C L−1) was 13-fold higher than the average coastal DON concentrations ((13.6±30.4) µmol N L−1), which was itself 39-fold higher than the average coastal DOP concentrations (0.34±1.11 µmol P L−1) (Table 1). Interestingly, the coefficient of variation (CV – dispersion of the data around the mean) increased from DOC (173 %) to DON (224 %) and DOP (326 %), which is related to the fact that the percent contribution of refractory organic material decreases in the same sequence (Table 1). It should be noted that CoastDOM v1 only contains 7058 paired measurements of DOC, DON, and DOP; therefore, only a subset of observations reported all three element pools. The average stoichiometry for these paired DOM measurements was (Table 1), which was very N and P depleted compared to the Redfield ratio (Redfield et al., 1963). However, the large variations in C:N, C:P, and N:P ratios reveals large variations in the composition of the DOM pool in coastal waters.
3.5 Potential use of the dataset
The use of the CoastDOM v1 dataset should be accompanied by the citation of this paper and the inclusion of the correct DOI reference. CoastDOM v1 is available in full open access on the PANGEA web page as a *.csv file. The dataset includes a brief description of the metadata and methods employed, with emphasis on measurement techniques and data units. We chose the terminology most familiar to the ocean science community. It is important to note that all data included in CoastDOM v1, as well as this paper, are considered public domain; as such, a subset of this global dataset is also available in previous data compilations (e.g. Hansell et al., 2021). The list of citations and links referenced in CoastDOM v1 also provides users with information on how these data have been previously used in publications or databases.
The dataset is available at the PANGEA database (https://doi.org/10.1594/PANGAEA.964012; Lønborg et al., 2023). The file can be downloaded as a *.csv merged file and is available in full open access.
In CoastDOM v1, we have compiled available coastal DOM data in a single repository, making it openly and freely available to the research community. This compilation has established a consistent global dataset, serving as a valuable information source to investigate a variety of environmental questions and to explore spatial and temporal trends. We suggest a set of recommendations for the future expansion of this global dataset. First, our analysis highlights a spatial bias, with a concentration of sampling efforts and/or data availability predominantly concentrated in the Northern Hemisphere. The data gap in coastal DOM measurements in the Southern Hemisphere needs to be addressed to provide a more representative global understanding of the role of DOM in coastal water biogeochemistry. Additionally, increased sampling efforts especially around Africa and South America as well as island nations are warranted due to the vulnerability of many coastal areas to climate change and intensifying human activities, which will undoubtedly impact DOM biogeochemistry. Furthermore, there are comparatively few data from coastal waters affected by river discharge into the tropics, e.g. the Amazon or Indian and Indonesian rivers that together dominate freshwater inputs to the coastal ocean. Second, there is a need for more comprehensive temporal and spatial datasets to capture the variability of DOM concentrations in highly dynamic and productive coastal systems. Focused efforts should be made to resolve these temporal and spatial changes. Third, only a fraction of data entries report paired DOC, DON, and DOP measurements; we encourage that these be measured and reported together in order to better determine changes in stoichiometry and composition. Fourth, collecting and reporting ancillary data, such as temperature, salinity, nutrient measurements, and particulate components, are important to provide context and to better understand the underlying processes driving the observed DOM concentrations. Fifth, studies need to collect a minimum of metadata and report them in a standardized manner. Lastly, we recommend regular inter-calibration exercises to establish standardized and interoperable methods and data, particularly for DON and DOP measurements. This will ensure the comparability and reliability of data across different studies and enhance our understanding of DON and DOP dynamics in coastal waters.
In light of ongoing global environmental changes, the mobilization and open sharing of existing data for important biogeochemical variables, such as the DOM pool, are crucial for establishing baselines and determining global trends and changes in coastal waters. The aim is to publish an updated version of the database periodically to determine global trends of DOM levels in coastal waters, and we therefore encourage researchers to submit new data to the corresponding author. The CoastDOM v1 dataset was developed according to the FAIR principles regarding findability, accessibility, interoperability, and reusability of data. Thus, CoastDOM v1 will serve as a reliable open-source information resource, enabling in-depth analyses and providing quality-controlled input data for large-scale ecosystem models.
CL, CC, and XAÁS started the initiative and finalized the data compilation. All other co-authors contributed data. CL wrote the manuscript with input from all co-authors.
The contact author has declared that none of the authors has any competing interests.
Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims made in the text, published maps, institutional affiliations, or any other geographical representation in this paper. While Copernicus Publications makes every effort to include appropriate place names, the final responsibility lies with the authors.
Qi Chen is acknowledged for his very skilful help with Fig. 4. Cláudia B. Lopes thanks FCT for her researcher contract, 2021.03739.CEECIND/CP1659/CT0025 (https://doi.org/10.54499/2021.03739.CEECIND/CP1659/CT0025, PTCRIS, 2022–2024a), and project CICECO-Aveiro Institute of Materials, UIDB/50011/2020 (https://doi.org/10.54499/UIDB/50011/2020, PTCRIS, 2020–2023) & LA/P/0006/2020 (https://doi.org/10.54499/LA/P/0006/2020, PTCRIS, 2022–2024b), financed by national funds through the FCT/MCTES (PIDDAC).
During the drafting of the manuscript, Christian Lønborg received funding from the Independent Research Fund Denmark (grant no. 1127-00033B). The monitoring data obtained from Bermuda received funding from the Bermuda Government Department of Environment and Natural Resources. A subset of the data obtained from UK coastal estuaries received funding from the Natural Environment Research Council (grant no. NE/N018087/1). Data retrieved from the Palmer LTER data were collected with support from the Office of Polar Programs, US National Science Foundation. Data obtained from the Great Barrier Reef Marine Monitoring Program for Inshore Water Quality, which is a partnership between the Great Barrier Reef Marine Park Authority, the Australian Institute of Marine Science, James Cook University, and the Cape York Water Partnership. The contribution by Piotr Kowalczuk was supported by DiSeDOM (project contract no. UMO-2019/33/B/ST10/01232) funded by the NCN – National Science Centre, Poland. Nicholas Ward and Allison Myers-Pigg participated in this synthesis effort with funding provided by the U.S. Department of Energy funded COMPASS-FME project; the provided data was collected with funding from the PREMIS Initiative, conducted under the Laboratory Directed Research and Development Program at Pacific Northwest National Laboratory. The data obtained from the Levantine Sea (Med Sea) received funding from the Scientific and Technological Research Council of Türkiye (TÜBİTAK, 1001 programme, grant no. 115Y629). The data obtained from Gulf of Trieste (Slovenian waters) were financed by Research Program No. P1-0237 (Slovenian Research and Innovation Agency). Data obtained from the northern Baltic Sea were financed by the research programme EcoChange (Swedish research council FORMAS). The contribution by Ding He was supported by the National Natural Science Foundation of China (grant no. 42222061) and funding support from the Center for Ocean Research in Hong Kong and Macau (CORE). CORE is a joint research centre for ocean research between Laoshan Laboratory and HKUST. The contribution by Yuan Shen was supported by National Natural Science Foundation of China (grant no. 42106040), the Fundamental Research Funds for the Central Universities of China (grant no. 20720210076), and Fujian Provincial Central Guided Local Science and Technology Development Special Project (grant no. 2022L3078). The data provided by Luiz C. Cotovicz Jr. were supported by the Brazilian National Council of Research and Development (CNPq-Pve No. 401.726/2012-6) and by the Carlos Chagas Foundation for Research Support of the State of Rio de Janeiro (FAPERJ; No. E-26202.785/2016). Data provided by Stefano Cozzi were collected in the framework of Italian (PRISMA 1 and 2, ANOCSIA and VECTOR) and European (OCEANCERTAIN) research projects. Data provided by MG were collected within the Project “Mucilages in the Adriatic and Tyrrhenian Seas (MAT)”, coordinated by the Istituto Centrale per la Ricerca Scientifica e Tecnologica Applicata al Mare and financially supported by the Italian Ministry of the Environment. Data obtained from the Georgia coast (USA) were supported by the National Science Foundation through grants OCE-1832178 (GCE-LTER Program) and OCE-1902131. Observations in the southern Caribbean Sea including the Cariaco Basin were collected as part of the CARIACO Ocean Time Series programme (supported by the Consejo Nacional de Ciencia y Tecnología of Venezuela, the Ley de Ciencia, Tecnología e Innovación de Venezuela, the Estación de Investigaciones Marinas de Venezuela; the National Science Foundation (grant nos. OCE-0752139, OCE-9216626, OCE-9729284, OCE-491 9401537, OCE-9729697, OCE-9415790, OCE-9711318, OCE-0326268, OCE-0963028, OCE-0326313, and OCE-0326268, NASA grants NAG5-6448, NAS5-97128, and NNX14AP62A); the Inter-American Institute for Global Change Research grant IAI-CRN3094), and the Marine Biodiversity Observation Network/MBON of the Group on Earth Observations Biodiversity Observation Network). Data provided by Digna Rueda-Roa and Bradley Eyre was supported by ARC Linkage (LP0770222), with Norske-Skog Boyer and the Derwent Estuary Program providing financial and in-kind assistance.
This paper was edited by Xingchen Wang and reviewed by two anonymous referees.
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