Carbon-Based Ocean Productivity and Phytoplankton Physiology from Space

Ocean biogeochemical and ecosystem processes are linked by net primary production (NPP) in the ocean\u27s surface layer, where inorganic carbon is fixed by photosynthetic processes. Determinations of NPP are necessarily a function of phytoplankton biomass and its physiological status, but the estimation of these two terms from space has remained an elusive target. Here we present new satellite ocean color observations of phytoplankton carbon (C) and chlorophyll (Chl) biomass and show that derived Chl:C ratios closely follow anticipated physiological dependencies on light, nutrients, and temperature. With this new information, global estimates of phytoplankton growth rates (mu) and carbon-based NPP are made for the first time. Compared to an earlier chlorophyll-based approach, our carbon-based values are considerably higher in tropical oceans, show greater seasonality at middle and high latitudes, and illustrate important differences in the formation and demise of regional algal blooms. This fusion of emerging concepts from the phycological and remote sensing disciplines has the potential to fundamentally change how we model and observe carbon cycling in the global oceans

Evaluating satellite estimates of particulate backscatter in the global open ocean using autonomous profiling floats

Satellite retrievals of particulate backscattering (bbp) are widely used in studies of ocean ecology and biogeochemistry, but have been historically difficult to validate due to the paucity of available ship-based comparative field measurements. Here we present a comparison of satellite and in situ bbp using observations from autonomous floats (n = 2,486 total matchups across three satellites), which provide bbp at 700 nm. With these data, we quantify how well the three inversion products currently distributed by NASA ocean color retrieve bbp. We find that the median ratio of satellite derived bbp to float bbp ranges from 0.77 to 1.60 and Spearman’s rank correlations vary from r = 0.06 to r = 0.79, depending on which algorithm and sensor is used. Model skill degrades with increased spatial variability in remote sensing reflectance, which suggests that more rigorous matchup criteria and factors contributing to sensor noisiness may be useful to address in future work, and/or that we have built in biases in the current widely distributed inversion algorithms

Carbon-Based Primary Productivity Modeling With Vertically Resolved Photoacclimation

Net primary production (NPP) is commonly modeled as a function of chlorophyll concentration (Chl), even though it has been long recognized that variability in intracellular chlorophyll content from light acclimation and nutrient stress confounds the relationship between Chl and phytoplankton biomass. It was suggested previously that satellite estimates of backscattering can be related to phytoplankton carbon biomass (C) under conditions of a conserved particle size distribution or a relatively stable relationship between C and total particulate organic carbon. Together, C and Chl can be used to describe physiological state (through variations in Chl:C ratios) and NPP. Here, we fully develop the carbon-based productivity model (CbPM) to include information on the subsurface light field and nitracline depths to parameterize photoacclimation and nutrient stress throughout the water column. This depth-resolved approach produces profiles of biological properties (Chl, C, NPP) that are broadly consistent with observations. The CbPM is validated using regional in situ data sets of irradiance-derived products, phytoplankton chlorophyll: carbon ratios, and measured NPP rates. CbPM-based distributions of global NPP are significantly different in both space and time from previous Chl-based estimates because of the distinction between biomass and physiological influences on global Chl fields. The new model yields annual, areally integrated water column production of similar to 52 Pg C a(-1) for the global oceans

Spatial and temporal variations in dissolved and particulate organic nitrogen in the equatorial Pacific: biological and physical influences

To quote Libby and Wheeler (1997), "we have only a cursory knowledge of the distributions of dissolved and particulate organic nitrogen" in the equatorial Pacific. A decade later, we are still in need of spatial and temporal analyses of these organic nitrogen pools. To address this issue, we employ a basin scale physical-biogeochemical model to study the spatial and temporal variations of dissolved organic nitrogen (DON) and particulate organic nitrogen (PON). The model is able to reproduce many observed features of nitrate, ammonium, DON and PON in the central and eastern equatorial Pacific, including the asymmetries of nitrate and ammonium, and the meridional distributions of DON and PON. Modeled DON (5–8 mmol m<sup>−3</sup>) shows small zonal and meridional variations in the mixed layer whereas modeled PON (0.4–1.5 mmol m<sup>−3</sup>) shows considerable spatial variability. While there is a moderate seasonality in both DON and PON in the mixed layer, there is a much weaker interannual variability in DON than in PON. The interannual variability in PON is largely associated with the El Niño/Southern Oscillation (ENSO) phenomenon, showing high values during cold ENSO phase but low values during warm ENSO phase. Overall, DON and PON have significant positive correlations with phytoplankton and zooplankton in the mixed layer, indicting the biological regulation on distribution of organic nitrogen. However, the relationships with phytoplankton and zooplankton are much weaker for DON (r=0.18–0.71) than for PON (r=0.25–0.97). Such a difference is ascribed to a relatively larger degree of physical control (e.g., upwelling of low-organic-N deep waters into the surface) on DON than PON

Global assessment of ocean carbon export by combining satellite observations and food-web models

The export of organic carbon from the surface ocean by sinking particles is an important, yet highly uncertain, component of the global carbon cycle. Here we introduce a mechanistic assessment of the global ocean carbon export using satellite observations, including determinations of net primary production and the slope of the particle size spectrum, to drive a food-web model that estimates the production of sinking zooplankton feces and algal aggregates comprising the sinking particle flux at the base of the euphotic zone. The synthesis of observations and models reveals fundamentally different and ecologically consistent regional-scale patterns in export and export efficiency not found in previous global carbon export assessments. The model reproduces regional-scale particle export field observations and predicts a climatological mean global carbon export from the euphotic zone of ~6 Pg C yr−1. Global export estimates show small variation (typically < 10%) to factor of 2 changes in model parameter values. The model is also robust to the choices of the satellite data products used and enables interannual changes to be quantified. The present synthesis of observations and models provides a path for quantifying the ocean's biological pump

Significant Contribution of Large Particles to Optical Backscattering in the Open Ocean

The light scattering properties of oceanic particles have been suggested as an alternative index of phytoplankton biomass than chlorophyll-a concentration (chl-a), with the benefit of being less sensitive to physiological forcings (e.g., light and nutrients) that alter the intracellular pigment concentrations. The drawback of particulate scattering is that it is not unique to phytoplankton. Nevertheless, field studies have demonstrated that, to first order, the particulate beam-attenuation coefficient (c(p)) can track phytoplankton biomass. The relationship between c(p) and the particulate backscattering coefficient (b(bp)), a property retrievable from space, has not been fully evaluated, largely due to a lack of open-ocean field observations. Here, we present extensive data on inherent optical properties from the Equatorial Pacific surface waters and demonstrate a remarkable coherence in b(bp) and c(p). Coincident measurements of particle size distributions (PSDs) and optical properties of size-fractionated samples indicate that this covariance is due to both the conserved nature of the PSD and a greater contribution of phytoplankton-sized particles to b(bp) than theoretically predicted. These findings suggest that satellite-derived b(bp)could provide similar information on phytoplankton biomass in the open ocean as c(p)

State of the Climate in 2016: Global Ocean Phytoplankton

Marine phytoplankton contribute roughly half the net primary production (NPP) on Earth, fixing atmospheric CO2 into food that fuels global ocean ecosystems and drives biogeochemical cycles. Satellite ocean color sensors, such as SeaWiFS, MODIS, and VIIRS, provide observations of sufficient frequency and geographic coverage to globally monitor changes in the near-surface concentrations of the phytoplankton pigment chlorophyll-a (Chla; mg -cu m) that serve as a proxy for phytoplankton abundance. Here, global Chla distributions for 2016 are evaluated within the context of the 19-year continuous record provided through the combined observations of SeaWiFS (19972010), MODIS on Aqua (MODISA, 2002present), and VIIRS on Suomi-NPP (2011present). All Chla data used in this analysis correspond to version R2014.0, which utilized common algorithms and calibration methods to maximize consistency in the multi-mission satellite record

Global Ocean Phytoplankton

Phytoplankton are free-floating algae that grow in the euphotic zone of the upper ocean, converting carbon dioxide, sunlight, and available nutrients into organic carbon through photosynthesis. Despite their microscopic size, these photoautotrophs are responsible for roughly half the net primary production on Earth (NPP; gross primary production minus respiration), fixing atmospheric CO2 into food that fuels our global ocean ecosystems. Phytoplankton thus play a critical role in the global carbon cycle, and their growth patterns are highly sensitive to environmental changes such as increased ocean temperatures that stratify the water column and prohibit the transfer of cold, nutrient richwaters to the upper ocean euphotic zone

Inferring phytoplankton carbon and eco-physiological rates from diel cycles of spectral particulate beam-attenuation coefficient

The diurnal fluctuations in solar irradiance impose a fundamental frequency on ocean biogeochemistry. Observations of the ocean carbon cycle at these frequencies are rare, but could be considerably expanded by measuring and interpreting the inherent optical properties. A method is presented to analyze diel cycles in particulate beam-attenuation coefficient (&lt;i&gt;c&lt;/i&gt;&lt;sub&gt;p&lt;/sub&gt;) measured at multiple wavelengths. The method is based on fitting observations with a size-structured population model coupled to an optical model to infer the particle size distribution and physiologically relevant parameters of the cells responsible for the measured diel cycle in &lt;i&gt;c&lt;/i&gt;&lt;sub&gt;p&lt;/sub&gt;. Results show that the information related to size and contained in the spectral data can be exploited to independently estimate growth and loss rates during the day and night. In addition, the model can characterize the population of particles affecting the diel variability in &lt;i&gt;c&lt;/i&gt;&lt;sub&gt;p&lt;/sub&gt;. Application of this method to spectral &lt;i&gt;c&lt;/i&gt;&lt;sub&gt;p&lt;/sub&gt; measured at a station in the oligotrophic Mediterranean Sea suggests that most of the observed variations in &lt;i&gt;c&lt;/i&gt;&lt;sub&gt;p&lt;/sub&gt; can be ascribed to a synchronized population of cells with an equivalent spherical diameter around 4.6±1.5 μm. The inferred carbon biomass of these cells was about 5.2–6.0 mg m&lt;sup&gt;−3&lt;/sup&gt; and accounted for approximately 10% of the total particulate organic carbon. If successfully validated, this method may improve our in situ estimates of primary productivity