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. 2014 Dec 9;1:140048. doi: 10.1038/sdata.2014.48

Concentrations and ratios of particulate organic carbon, nitrogen, and phosphorus in the global ocean

Adam C Martiny 1,2,a, Jasper A Vrugt 1,3, Michael W Lomas 4
PMCID: PMC4421931  PMID: 25977799

Abstract

Knowledge of concentrations and elemental ratios of suspended particles are important for understanding many biogeochemical processes in the ocean. These include patterns of phytoplankton nutrient limitation as well as linkages between the cycles of carbon and nitrogen or phosphorus. To further enable studies of ocean biogeochemistry, we here present a global dataset consisting of 100,605 total measurements of particulate organic carbon, nitrogen, or phosphorus analyzed as part of 70 cruises or time-series. The data are globally distributed and represent all major ocean regions as well as different depths in the water column. The global median C:P, N:P, and C:N ratios are 163, 22, and 6.6, respectively, but the data also includes extensive variation between samples from different regions. Thus, this compilation will hopefully assist in a wide range of future studies of ocean elemental ratios.

Background & Summary

One of the fundamental tenets of ocean biogeochemistry is the Redfield ratio. Redfield identified a similarity between the N:P ratio of plankton living in the surface ocean and that of dissolved nitrate and phosphate in the deep ocean1,2. He hypothesized that the deep ocean nutrient concentrations were controlled by the elemental requirements of the surface plankton. This concept has been extended to include other elements like carbon and remains a cornerstone for our understanding of ocean biogeochemistry. Despite the importance of this ratio, there is no obvious mechanism for a globally consistent C:N:P ratio of 106:16:1 (i.e., Redfield ratio), and there is substantial elemental variation among ocean taxa3–6. Furthermore, many small plankton are not homeostatic but instead, the cellular elemental content varies depending on growth conditions7. Thus, it has become apparent that changes in biodiversity or cell physiology can lead to variations in marine plankton elemental stoichiometry.

Variations in elemental content and ratios of marine microbial communities have multiple important implications. Broecker and Henderson have proposed that increased plankton C:N:P ratios and thus increased CO2 uptake in the ocean could explain the glacial to inter-glacial variation in atmospheric CO2 concentration8. Rates of N2 fixation as well as competition between phytoplankton and N2-fixers are also dependent upon an assumed N:P ratio (specifically the Redfield ratio). Recently, multiple researchers have argued that our understanding (or lack thereof) of cellular elemental stoichiometry has a large influence on our ability to estimate the global ocean N budget9,10.

It has been observed that specific phytoplankton groups as well as particulate organic matter display regional differences in elemental stoichiometry11–14. For example, the C:P, N:P, and C:N ratios all appear to be above Redfield proportions in the oligotrophic gyres, near Redfield proportions in upwelling regions like the Eastern Equatorial Pacific Ocean, and below Redfield proportions in colder, nutrient rich high latitude environments11,12. The ratios may also vary between the gyres depending on the nutrient supply ratio and the resulting degree of nitrogen versus phosphorus limitation. Thus, rather than globally static C:N:P ratios, differences in environmental conditions and plankton community composition can lead to variations in the elemental composition of plankton and particulate organic material4,11–13,15. In addition, we also observe extensive variations in the ratios of particulate nutrients which cannot be explained with common physio-chemical parameters11,12. Thus, future studies are needed to identify factors causing this variation.

The elemental stoichiometry of ocean plankton communities has also been the focus in many model studies10,15–17. This includes models describing cellular elemental composition in response to changes in light intensity, nutrients, or other environment conditions16,17. Other models focus on identifying regional differences in the elemental stoichiometry15. Thus, models have indicated that the elemental stoichiometry of cells, communities, and ocean regions are not constant but vary depending on biodiversity and environmental conditions. However, we currently do not have global datasets to evaluate the output of such models.

To address this issue, we here present a compilation of measurements of marine particulate organic carbon (POC), nitrogen (PON), and phosphorus (POP) from 70 cruises or time-series during the last 40 years (Table 1 (available online only))12,18–67. The dataset includes a total of 100,605 discrete measurements of particulate organic nutrients including 6940 POP, 46728 PON, and 46937 POC measurements. This leads to 5948 N:P, 5573 C:P, and 45476 C:N observations. Due to the common concurrent and largely automated measurements of PON and POC, these two particulate nutrients are over-represented in comparison to the sparse measurements of POP.

Table 1. Summary of cruises and time-series in this dataset including number of stations and POM samples as well as the mean elemental ratios.

Cruise #Sta Year Latitude
  Longitude
POC PON POP C:P * N:P C:N Ref.
min max min max (#samples)    
AMT1 23 1995 −51 49 −57 −9 23 23 — — — 8.0 18
AMT10 42 2000 −35 49 −49 −6 57 57 — — — 9.5 19
AMT12 14 2003 −38 45 −38 −19 72 72 — — — 8.3 18
AMT13 10 2003 −36 40 −34 −18 50 50 — — — 7.7 18
AMT14 15 2004 −47 49 −50 −16 71 78 — — — 7.0 18
AMT15 21 2004 −40 39 −25 10 100 100 — — — 8.7 18
AMT16 32 2005 −32 47 −46 17 191 191 — — — 12 18
AMT17 33 2005 −35 49 −39 14 178 178 — — — 9.0 18
Antares3 20 1995 −59 −48 62 74 146 146 — — — 8.8 20
Antares4 25 1999 −46 −43 62 65 364 356 — — — 8.0 21
ANTVI 61 1992 −60 −47 −50 −6 582 582 — — — 6.7 22
ANTXXIII 26 2005 −26 50 −21 9 120 120 — — — 7.6 23
Arabesque 14 1994 8 19 58 67 70 52 — — — 7.0 24
Atlantic 4 1973 31 31 −10 −10 19 19 19 110 17 6.6 25
Atlantic Ocean 160 1990–95 24 61 −65 −10 1174 1174 — — — 10 24
ATP3 13 2006 21 32 −66 −64 129 129 130 297 56 5.3 12
BATS 73 2003–10 31 32 −64 −64 722 722 661 188 36 5.2 26
Bering Sea 75 2009–10 54 63 −179 −161 291 272 296 84 9.8 8.1 12
BIOSOPE 21 2004 −35 −8 −141 −73 162 156 164 171 21 7.9 27
BloomER 2 2007 23 24 −159 −159 16 16 — — — 9.7 28
Blue Water Zone 49 2004–06 −64 −60 −63 −53 260 259 — — — 7.1 29
BULA/CMORE 9 2007 −16 17 −170 −159 45 45 48 278 50 5.5 30
BV37+39 12 2007 20 34 −66 −64 46 46 181 448 60 7.1 12
CARIACO 156 1995–2010 11 11 −65 −65 2893 2885 — — — 7.4 31
CCU LTER process 68 2006–08 32 35 −124 −120 798 798 — — — 6.1 32
CCU LTER survey 818 2004–09 30 74 −124 −117 4406 4406 — — — 6.4 32
Copin-Montegut 10 1974 −56 −26 61 75 9 10 10 80 13 6.2 33
Copin-Montegut 1 1975 42 42 5 5 6 6 6 121 19 6.3 25
CYCLOPS 66 1971–72 −35 56 −18 142 66 66 — — — 9.4 34
DCM 17 1996 7 34 −54 −23 119 113 — — — 14 35
DIAPAZON 62 2002–03 −24 −20 166 168 202 203 305 238 27 8.8 36
EDT1 2004 17 2004 30 31 −66 −64 259 259 — — — 6.8 37
EDT2 2004 8 2004 30 32 −66 −64 244 244 — — — 6.8 37
EDT3 2005 12 2005 30 32 −67 −64 231 231 — — — 5.4 37
EDT4 2005 15 2005 30 30 −69 −68 224 224 — — — 5.5 37
EUMELI 18 1991–92 18 21 −31 −21 — 318 327 — 18 — 38
FLUPAC 42 1994 −14 6 −179 −149 374 375 400 132 16 8.2 39
FRUELA 95 35 1995–96 −65 −63 −66 −59 306 306 — — — 6.1 40
Gulf of St Lawrence 36 1992–94 43 50 −66 −60 397 398 — — — 6.1 24
HOT 195 1989–2009 23 23 −158 −158 1632 1632 1581 161 25 6.5 41
IronEx II 11 1995 −7 −4 −111 −105 114 114 — — — 5.9 42
JGOFS Arabian Sea 120 1995 10 24 57 69 1229 1217 — — — 4.9 43
JGOFS EqPac 99 1992 −12 12 −141 −135 803 1468 — — — 7.3 44
JGOFS S. Ocean 175 1996–98 −78 −53 −178 180 2150 2135 — — — 8.8 45
Kahler 10 2002 18 32 −30 −30 59 59 60 152 22 7.0 46
Keycop 12 1999–2000 39 40 25 26 70 59 — — — 1.1 47
Latitud-II 11 1995 −33 25 −45 −18 16 16 — — — 12.3 48
Line P 100 1992–97 49 50 −145 −127 997 970 — — — 6.8 49
Loh and Bauer 4 1996 −54 36 −176 −122 31 31 31 255 34 7.5 50
MD03/ICHTYO 123 1974 −56 −24 26 78 159 159 159 93 15 6.4 33
MEDAR 97 1991 −2001 41 45 5 14 1256 1160 190 165 21 8.1 51
Meteor 36–2 32 1996 33 60 −22 −20 96 96 — — — 5.9 52
Meteor 36–6 8 1996 46 48 −20 −18 73 73 — — — 6.9 53
MOOGLI 10 1997–99 43 43 5 5 114 121 123 182 22 8.1 54
NABE 20 1989 18 34 −31 −21 237 236 239 72 11 6.6 55
NOPACCS 110 1992–95 −36 48 143 175 1405 1405 — — — 7.0 56
OLIPAC 13 1994 −16 1 −150 −150 — 152 152 — 20 — 57
OMEX 228 1993–95 47 50 −16 −7 2216 1261 735 294 25 9.7 58
OPEREX 8 2008 22 26 −160 −157 58 58 — — — 6.1 59
PALLTER Seasonal 650 1991–2010 −65 −64 −65 −64 5775 5743 — — — 7.2 60
PALLTER Survey 679 1991–2010 −70 −79 7278 7232 — — — 6.6 60
PROSOPE 22 1999 31 43 −10 22 217 221 223 115 16 7.1 61
SBC LTER 307 2000–10 34 35 −121 −119 4594 4593 — — — 6.3 62
SEED 12 2001 49 49 164 165 129 129 57 140 17 8.4 63
SOIREE 13 1999 −61 −61 140 141 102 102 — — — 5.9 64
SUPER-HI-CAT 13 2008 28 35 −155 −138 83 83 81 250 35 7.2 65
Tuamotu 15 1985–96 −18 −15 −148 −141 16 16 14 158 21 7.6 66
WCSI 18 2007–08 16 74 68 68 — — — 5.9 67
X0705 29 2007 27 38 −66 −56 215 213 238 161 29 5.6 12
X0804 34 2008 20 32 −66 −45 1256 1160 190 107 24 4.5 12
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*Geometric means of elemental molar ratios.

It is worth noting that this represents an aggregated dataset collected by many independent researchers (Table 1 (availale online only)). Even though most studies utilize the same techniques and sample volumes, there are likely many small deviations in the technical approach. As a result, some care should be taken when comparing values.

The data covers 5336 unique stations from all major ocean regions (Figure 1). 89% of the samples originate from the top 200 m of the water and thus the dataset is skewed towards processes occurring in or near the euphotic zone (Figure 2a). The data is also biased towards regions of oceanographic research. This includes samples near the Palmer Station in the Southern Ocean, North Atlantic Ocean and Eastern North Pacific Ocean (including the HOT site and California Current) (Figure 2b and Figure 2c). Thus, this compilation of data identifies regions where we currently have very sparse data (e.g., the South Pacific, South Atlantic, and Eastern Indian Ocean). Overall, the median C:P, N:P, and C:N ratios are 163, 22, and 6.6, respectively, in this dataset but the data span a wide range for all three ratios (Figure 2d–f). Combined with the wide geographic extent of the data, this compilation will enable a range of analyses of elemental concentrations or ratios in particulate organic matter.

Figure 1. Global distribution of POM measurements in the dataset.

Figure 1

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A depth profile was defined as at least two unique depths from the same station.

Figure 2. Summary of POM measurements and ratios in the aggregated dataset.

Figure 2

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Histogram of the number of observations across depths (a), latitude (b), and longitude (c) as well as the range of C:P (d), N:P (e), and C:N (f) elemental ratios. M represents the median value. Please note a difference in the total number of observations for each elemental ratio.

Methods

Nearly all POC and PON measurements were done by collecting seawater particles onto glass-fibers filters (i.e., GF/F) and quantified using an combustion GC-IR based elemental analyzer68. The only exceptions were ‘EUMELI’ and ‘OLIPAC’, where PON was measured using a chemical oxidation technique38. Particulate phosphorus was quantified using the ash-hydrolysis method26,69. We operationally defined station IDs as samples taken within a 1°×1° area on the same day11.

The data was gathered by searching available databases (i.e., PANGAEA, BCO-DMO, JGOFS, and IFREMER) as well as published literature. We aggregated all available datasets in order to create the most exhaustive global description of particulate organic nutrients and thus did not exclude any specific cruises or time-series. The only data excluded were samples subjected to a prior manipulation or incubation.

Data Records

The dataset includes the following fields for each record:

  • Cruise

  • Year

  • Month

  • Day

  • Latitude (−90 to 90)

  • Longitude (−180 to 180)

  • Sampling depth (m)

  • Particulate organic Carbon (μM)

  • Particulate organic Nitrogen (μM)

  • Particulate organic Phosphorus (μM)

Data Record 1

The database files (June 20, 2014 version) in csv format were uploaded to Dryad (Data Citation 1). A file containing all the fields listed above is available. ‘−9999’ denotes missing data.

Data Record 2

The particulate nutrient data were also uploaded to the Biological and Chemical Oceanography Data Management Office system (BCO-DMO) (Data Citation 2) with all the fields listed above. The database is organized at level 0 by cruise dataset (Table 1 (availale online only)), level 1 by stations, and level 2 with the POM data. ‘−9999’ describes missing data. This dataset will be updated if new data becomes available.

Technical Validation

In our experience, when all precautions are taken, variance between replicate samples for elemental analysis can be <5%, assuming the actual sample is above the analytical blank. However, not all precautions are always taken, for example it is rare that when sampling for POC that the entire Niskin bottle is drained, well mixed and then subsampled. It is known that as the sample sits in the bottle, large particles sink to the bottom and often below the spigot resulting in an underestimation of particulate matter concentrations in the seawater sample70. There is also the question of limit of detection. For particulate analyses, this depends in part upon the volume you are filtering, the concentration of your analyte of interest and overall cleanliness of your procedures71. For example, in the Sargasso Sea, where particulate nutrients are very low, we filter 4 liters of seawater for particulate organic phosphorus26 to ensure that the sample well exceeds the blank. In our experience making these measurements using the methods reported here, reasonable blank measurements for POC, PON and POP are ~0.5 μM, ~0.04 μM and ~3 nM, respectively. It is common practice to subtract blanks from analyzed samples, and we assume that has been done for all reported data however, we cannot be fully confident in how that blank correction was conducted. Whether blank-corrected samples are significantly different than zero is a different question and depends upon the actual value and variability of the blank which is not commonly reported in published works or available datasets. However, we are confident that blank-corrected particulate organic matter concentrations greater than ~0.5 μM POC, ~0.05 μM PON and 5 nM POP are valid numbers to report. This benchmark may change between ocean regimes and with specific protocols. We should also note that some samples give either very high or low elemental ratios. These could arise from analytical artifacts, for example, one or both values in the ratio being close to the analytical detection limit, as well as other sampling artifacts. However, we currently do not have a good handle on the spatio-temporal variation in particulate nutrient concentrations and ratios and thus, it is difficult to give precise guidelines for flagging possible artifacts and thus really high/low values should be examined more closely and used with caution.

Usage Notes

The dataset can be used to identify novel regional or environmentally driven patterns in both the concentration of particulate organic matter as well as the ratios of different elements. Within this dataset are observations from time-series stations and thus temporal analysis of particulate organic matter concentrations and ratios can also be evaluated. Further, the data can be utilized to evaluate outputs from ocean biogeochemical models.

Additional information

Table 1 is only available in online version of this paper.

How to cite this article: Martiny, A. C. et al. Concentrations and ratios of particulate organic carbon, nitrogen, and phosphorus in the global ocean. Sci. Data 1:140048 doi: 10.1038/sdata.2014.48 (2014).

Supplementary Material

sdata201448-isa1.zip (164.6KB, zip)

Acknowledgments

We would like to thank all the researchers for sharing their data with us and making this compilation possible as well as Cyndy Chandler and Steve Gegg for enabling the posting of the data at The Biological and Chemical Oceanography Data Management Office (BCO-DMO). We would like to acknowledge the NSF Dimensions of Biodiversity and Biological Oceanography programs (A.C.M. and M.W.L.) and the UCI Environment Institute (A.C.M. and J.A.V.) for supporting our research.

Footnotes

The authors declare no competing financial interests.

Data Citations

  1. Martiny A. C., Vrugt J. A., Lomas M. W. 2014. Dryad. http://dx.doi.org/10.5061/dryad.d702p [DOI] [PMC free article] [PubMed]
  2. Martiny A. C., Vrugt J. A., Lomas M. W. 2014. The Biological and Chemical Oceanography Data Management Office. http://www.bco-dmo.org/dataset/526747

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Data Citations

  1. Martiny A. C., Vrugt J. A., Lomas M. W. 2014. Dryad. http://dx.doi.org/10.5061/dryad.d702p [DOI] [PMC free article] [PubMed]
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Supplementary Materials

sdata201448-isa1.zip (164.6KB, zip)

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