NASA/IOCCG Aquatic Primary Productivity Workshop

Agenda (PDF, 233 KB)

The measurement of aquatic primary production (PP) is central to the quantitative understanding of the global carbon cycle and ecosystem function. The accumulation of theoretical, methodological, and technological advances over the past few decades has resulted in the development of numerous approaches to measure oceanic PP. These advances have enabled the synoptic understanding of carbon dynamics from intracellular to global scales. However, this methodological diversity has also hindered interoperability and scalability of existing measurements into synthesis efforts aimed at carbon cycle modeling and satellite algorithm development. Therefore, there is a critical need for an assessment of current methods for measuring productivity rates in aquatic ecosystems in the context of a community consensus-building exercise. The establishment of uniform protocols is imperative to ensure that existing and future measurements can be compared, assimilated, and their uncertainties determined.

PP is a biological process whose magnitude cannot be quantified as accurately as other oceanic variables, such as temperature or the concentration of nitrate (Cullen 2001). Every methodology carries substantial artifacts and assumptions, and there is no unanimous agreement as to how different measurements relate to specific ecosystem processes (i.e., gross and net production, respiration). Nevertheless, systematic and random biases can be minimized through better understanding of assumptions and limitations of the various available measurement approaches and by promoting best practices.

We are proposing a working group, in collaboration with NASA and the International Ocean-Colour Coordinating Group (IOCCG), to establish standard, community-consensus field protocols for measuring aquatic PP in coastal and ocean waters across diverse methodologies. The objectives of the proposed scientific working group are:

• Establish community consensus, best practice protocols for various PP measurement approaches.
• Define what each technique/approach measures (e.g., net vs. gross, primary vs. community, productivity/respiration).
• Define the uncertainty associated with each measurement.
• Define the relevant spatial and temporal scales for each measurement.

This effort will draw from a broadly international workshop that will bring together active investigators with experience in conducting field and laboratory measurements, using different methods of PP and related parameters. The core, US-based organizing committee will be complemented by a broad contingent of invited participants that will include a significant fraction of international contributors.

The proposed activity will move the community forward towards the establishment of climate-quality measurement capabilities necessary for the success of future modeling synthesis efforts, and the development of space-borne observations. The specific deliverable from of this activity will be in the form of a synthesis document published in coordination with the IOCCG, summarizing the above objectives.

The contribution of land and ocean to the global carbon flux through net PP is about equal (Field et al. 1998). Assessment of oceanic carbon flux has been attained by the power of the discrete measurements of PP accumulated over the years, and the capacity afforded by satellite observations of ocean biomass and its physical environment, to scale up those data into a comprehensive, global picture (National Research Council 2008). The combination of modeling efforts with satellite observations, even if not explicit, is the only viable path to gauge the rate of marine carbon fixation at a global scale, and thus is critical to evaluate model outputs against accurate in situ measurements from diverse regions (Saba et al. 2011).

However, in spite of the ubiquitous nature of PP measurements in oceanographic research, it is notable that perhaps no single measurement in the suite of significant oceanographic observations exhibits as much methodological diversity as well as interpretive ambiguity (del Giorgio and Williams 2005; Marra 2002). Methods used to derive estimates of PP include in vitro incubations to measure oxygen gas accumulation (Riley 1939), uptake of radioactive C isotopes (Steeman Nielsen 1952), stable ¹³C (Hama et al. 1993; Slawyk 1979; Slawyk et al. 1977), ¹⁸O (Grande et al. 1989), the isotopic composition of atmospheric and dissolved oxygen (¹⁶O, ¹⁷O, and ¹⁸O; Luz and Barkan 2009), dilution growth/grazing incubation experiments (Calbet and Landry 2004; Landry et al. 2000), underway measurements of O₂/Ar ratios (Cassar et al. 2009), the use of temporally and spatially integrated oxygen time-series from gliders and/or buoys (Alkire et al. 2014; Nicholson et al. 2008), bio-optical beam attenuation used as a proxy for changes in particulate organic carbon (ΔPOC) over time (Claustre et al. 1999), and novel in situ methods that utilize fast repetition rate fluorometry (FRRF; Kolber et al. 1998).

The techniques and approaches used for measuring PP are dependent on multiple assumptions, and are prone to artifacts that can introduce significant biases between measurements (Marra 2002; Peterson 1980; Regaudie-de-Gioux et al. 2014). Moreover, variations in results extend beyond the specific parameter used to estimate the rates of carbon fixation, and can often arise from environmental or experimental variability due to temperature (Eppley 1972), light source/quality (Kirk 2011), filtration (Sharp 1977), bottle effects (Worrest et al. 1980), length and type of incubations (Lohrenz et al. 1992), and inherent assumptions made about respiration and dissolved losses, and the depth of the photic zone (Geider and Osborne 1992; Marra 2015), grazing (Laws et al. 2000), regenerated production (Harrison 1980), quantum yield (Morel et al. 1996), as well as mixing and air-sea exchange (Duarte et al. 2013), among others. Results from identical samples analyzed at different laboratories have shown an average coefficient of variation on the order of 25-40% (Richardson 1991). These uncertainties are not always quantified in a manner that is standard for other biogeochemical measurements, leading to ambiguity in the interpretation and applicability of data for subsequent global PP model validation.

Despite recent advances as applied to the estimation of PP from satellite data (Behrenfeld et al. 2005; Silsbe et al. 2016), this parameter is not yet a standard NASA ocean color data product, such as chlorophyll-a or particulate organic carbon. The necessary preamble for the development of new algorithms for ocean parameters is the establishment of in situ data records, such as those in NASA's SeaWiFS Bio-optical Archive and Storage System (SeaBASS; Werdell and Bailey 2002) or NSF's Biological and Chemical Oceanography Data Management Office (BCO-DMO). NASA's mandate to collect and distribute in situ data of the highest possible quality to support their satellite algorithm development and data product validation activities requires that those field measurements be generated with a documented uncertainty in keeping with established performance metrics for producing climate-quality data records (CDR; Hooker et al. 2007). Lack of uniformed consensus protocols precludes a complete assessment of algorithm uncertainty and the accuracy of satellite data products.

The reasons above point to an urgent need to develop community consensus on best practices protocols for various PP measurement approaches, and define the uncertainty associated with each type of measurement. Accurate determination of carbon cycle parameters is central to NASA priorities and is required for the success of current and future programs in producing CDR-quality data from sea-going platforms and space borne sensors.

The proposed working group will work jointly in the development of a set of community consensus protocols for carrying out in situ measurements of PP and related parameters. The objective is to generate recommendations for best practices to homogenize methodologies, and to account for known artifacts and sources of error across the various measurement approaches. The organizing committee will nominate and invite a participant roster of approximately two dozen active investigators with experience in conducting field and laboratory measurements of PP. Invited contributors will represent a broad set of international institutions.

A 2.5-day workshop to be held at USRA headquarters in Columbia, MD, scheduled for December 5-7, 2018, will combine short presentations and discussions during the first day. The rest of the meeting will be devoted to break-out groups split by broad methodological approach to establish priorities for protocol consensus building. On the last half-day of the meeting, groups will be expected to develop a template document containing the sub-headings, with writing assignments, of what will constitute a protocol document detailing best practices for each PP methodology.

The synthesis document published and distributed in coordination with IOCCG as a report, will detail the consensus protocols devised by the sub-groups for each of the PP methodologies. Each protocol chapter will review the development and application for each technique, identify known biases and artifacts, and provide an assessment of method uncertainty. Each contribution will propose a set of state-of-the-art protocol guidelines. The synthesis document will be posted for public comment peer review for no less than 60 days. Thereafter, the editors and authors will resolve those comments and finalize the report. Our intention is for this report to be a living document that is updated as advances in techniques and technology allow for improved measurement capabilities.

Alkire, M.B., C. Lee, E. D'Asaro, M.J. Perry, N. Briggs, I. Cetinić & A. Gray, 2014. Net community production and export from Seaglider measurements in the North Atlantic after the spring bloom. Journal of Geophysical Research: Oceans, 119(9):6121-6139 doi:10.1002/2014JC010105.

Behrenfeld, M.J., E. Boss, D.A. Siegel, and D.M. Shea, 2005. Carbon-based ocean productivity and phytoplankton physiology from space. Global Biogeochem Cycles, 19 doi:10.1029/2004gb002299.

Calbet, A. and M.R. Landry, 2004. Phytoplankton growth, microzooplankton grazing, and carbon cycling in marine systems. Limnology and Oceanography, 49(1):51-57 doi:10.4319/lo.2004.49.1.0051.

Cassar, N., B.A. Barnett, M.L. Bender, J. Kaiser, R.C. Hamme, and B. Tilbrook, 2009. Continuous high-frequency dissolved O₂/Ar measurements by equilibrator inlet mass spectrometry. Analytical Chemistry, 81(5):1855-1864 doi:10.1021/ac802300u.

Claustre, H., A. Morel, M. Babin, C. Cailliau, D. Marie, J.-C. Marty, D. Tailliez, and D. Vaulot, 1999. Variability in particle attenuation and chlorophyll fluorescence in the tropical Pacific: Scales, patterns, and biogeochemical implications. Journal of Geophysical Research: Oceans, 104(C2):3401-3422 doi:10.1029/98JC01334.

Cullen, J.J., 2001. Primary Production Methods Encyclopedia of Ocean Sciences. Academic Press, Oxford, 2277-2284.

del Giorgio, P. and P. Williams, 2005. Respiration in Aquatic Ecosystems. Oxford University Press.

Duarte, C.M., A. Regaudie-de-Gioux, J.M. Arrieta, A. Delgado-Huertas, and S. Agustí, 2013. The Oligotrophic ocean is heterotrophic. Annual Review of Marine Science, 5(1):551-569 doi:10.1146/annurev-marine-121211-172337.

Eppley, R.W., 1972. Temperature and phytoplankton growth in the sea. Fishery Bulletin, 70(4):1063-1085.

Field, C.B., M. J. Behrenfeld, J.T. Randerson, and P. Falkowski, 1998. Primary production of the biosphere: Integrating terrestrial and oceanic components. Science, 281(5374):237-240 doi:10.1126/science.281.5374.237.

Geider, R.J. and B.A. Osborne, 1992. Algal Photosynthesis: The Measurement of Algal Gas Exchange. Chapman and Hall.

Grande, K.D., P.J.L. Williams, J. Marra, D.A. Purdie, K. Heinemann, R.W. Eppley, and M.L. Bender, 1989. Primary production in the North Pacific gyre: A comparison of rates determined by the C, O₂ concentration and 18O methods. Deep Sea Research Part A Oceanographic Research Papers, 36(11):1621-1634 doi:https://doi.org/10.1016/0198-0149(89)90063-0.

Hama, T., J. Hama, and N. Handa, 1993. ¹³C Tracer Methodology in Microbial Ecology with Special Reference to Primary Production Processes in Aquatic Environments. In Jones, J. G. (ed) Advances in Microbial Ecology. Springer US, Boston, MA, 39-83.

Harrison, W.G., 1980. Nutrient Regeneration and Primary Production in the Sea. In Falkowski, P.G. (ed) Primary Productivity in the Sea. Springer US, Boston, MA, 433-460.

Hooker, S.B., C.R. McClain, and A. Mannino, 2007. NASA Strategic Planning Document: A Comprehensive Plan for the Long-Term Calibration and Validation of Oceanic Biogeochemical Satellite Data. National Aeronautics and Space Administration, Greenbelt, MD, 31.

Kirk, J.T.O., 2011. Light and Photosynthesis in Aquatic Ecosystems, Third edn. Cambridge.

Kolber, Z.S., O. Prášil, and P.G. Falkowski, 1998. Measurements of variable chlorophyll fluorescence using fast repetition rate techniques: Defining methodology and experimental protocols. Biochimica et Biophysica Acta (BBA) - Bioenergetics, 1367(1–3):88-106 doi:http://dx.doi.org/10.1016/S0005-2728(98)00135-2.

Landry, M.R., J. Constantinou, M. Latasa, S.L. Brown, R.R. Bidigare, and M.E. Ondrusek, 2000. Biological response to iron fertilization in the eastern equatorial Pacific (IronEx II) III. Dynamics of phytoplankton growth and microzooplankton grazing. Marine Ecology Progress Series, 201:57-72.

Laws, E.A., M.R. Landry, R.T. Barber, L. Campbell, M.-L. Dickson, and J. Marra, 2000. Carbon cycling in primary production bottle incubations: Inferences from grazing experiments and photosynthetic studies using C and 18O in the Arabian Sea. Deep Sea Research Part II: Topical Studies in Oceanography, 47(7-8):1339-1352.

Lohrenz, S.E., D.A. Wiesenburg, C.R. Rein, R.A. Arnone, C.D. Taylor, G.A. Knauer, and A.H. Knap, 1992. A comparison of in situ and simulated in situ methods for estimating oceanic primary production. Journal of Plankton Research, 14(2):201-221 doi:10.1093/plankt/14.2.201.

Luz, B. and E. Barkan, 2009. Net and gross oxygen production from O₂/Ar, ¹⁷O/¹⁶O and ¹⁸O/¹⁶O ratios. Aquatic Microbial Ecology, 56(2-3):133-145.

Marra, J., 2002. Approaches to the Measurement of Plankton Production Phytoplankton Productivity. Blackwell Science Ltd, 78-108.

Marra, J.F., 2015. Ocean productivity: A personal perspective since the first Liege Colloquium. Journal of Marine Systems, 147:3-8 doi:https://doi.org/10.1016/j.jmarsys.2014.01.012.

Morel, A., D. Antoine, M. Babin, and Y. Dandonneau, 1996. Measured and modeled primary production in the northeast Atlantic (EUMELI JGOFS program): The impact of natural variations in photosynthetic parameters on model predictive skill. Deep Sea Research Part I: Oceanographic Research Papers, 43(8):1273-1304 doi:https://doi.org/10.1016/0967-0637(96)00059-3.

National Research Council, 2008. Earth Observations from Space: The First 50 Years of Scientific Achievements. The National Academies Press, Washington, DC.

Nicholson, D., S. Emerson, and C.C. Eriksen, 2008. Net community production in the deep euphotic zone of the subtropical North Pacific gyre from glider surveys. Limnology and Oceanography, 53(5part2):2226-2236 doi:10.4319/lo.2008.53.5_part_2.2226.

Peterson, B.J., 1980. Aquatic primary productivity and the ¹⁴C-CO₂ method: A history of the productivity problem. Annual Review of Ecology and Systematics, 11:359-385.

Regaudie-de-Gioux, A., S. Lasternas, S. Agustí, and C.M. Duarte, 2014. Comparing marine primary production estimates through different methods and development of conversion equations. Frontiers in Marine Science, 1:19.

Richardson, K., 1991. Comparison of ¹⁴C primary production determinations made by different laboratories. Marine Ecology Progress Series, 72(1/2):189-201.

Riley, G.A., 1939. Plankton studies II. The western North Atlantic, May-June, 1932. Journal Marine Research, 2(1):145-162.

Saba, V.S., M.A.M. Friedrichs, D. Antoine, R.A. Armstrong, I. Asanuma, M.J. Behrenfeld, A.M. Ciotti, M. Dowell, N. Hoepffner, K.J.W. Hyde, J. Ishizaka, T. Kameda, J. Marra, F. Mélin, A. Morel, J. O'Reilly, M. Scardi, W.O. Smith Jr, T.J. Smyth, S. Tang, J. Uitz, K. Waters, and T.K. Westberry, 2011. An evaluation of ocean color model estimates of marine primary productivity in coastal and pelagic regions across the globe. Biogeosciences, 8(2):489-503 doi:10.5194/bg-8-489-2011.

Sharp, J.H., 1977. Excretion of organic matter by marine phytoplankton: Do healthy cells do it?. Limnology and Oceanography, 22(3):381-399 doi:10.4319/lo.1977.22.3.0381.

Silsbe, G.M., M.J. Behrenfeld, K.H. Halsey, A.J. Milligan, and T.K. Westberry, 2016. The CAFE model: A net production model for global ocean phytoplankton. Global Biogeochemical Cycles, 30(12):1756-1777 doi:10.1002/2016gb005521.

Slawyk, G., 1979. ¹³C and ¹⁵N Uptake by phytoplankton in the Antarctic upwelling area: Results from the Antiprod I Cruise in the Indian Ocean sector. Marine and Freshwater Research, 30(4):431-448.

Slawyk, G., Y. Collos, and J.-C. Auclair, 1977. The use of the ¹³C and ¹⁵N isotopes for the simultaneous measurement of carbon and nitrogen turnover rates in marine phytoplankton. Limnology and Oceanography, 22(5):925-932 doi:10.4319/lo.1977.22.5.0925.

Steeman Nielsen, E., 1952. The use of radio-active carbon (C^14) for measuring organic production in the sea. Journal du Conseil/Conseil Permanent International pour l'Exploration de la Mer, 18:117-140.

Werdell, P.J. and S.W. Bailey, 2002. The SeaWiFS Bio-Optical Archive and Storage System (SeaBASS): Current Architecture and Implementation. In: Fargion, G.S. and C.R. McClain (eds) NASA Tech Memo. National Aeronautics and Space Administration, Greenbelt, MD, 45.

Worrest, R.C., D.L. Brooker, and H.V. Dyke, 1980. Results of a primary productivity study as affected by the type of glass in the culture bottles. Limnology and Oceanography, 25(2):360-364.