Obtaining Phytoplankton Diversity from Ocean Color: A Scientific Roadmap for Future Development

Abstract

To improve our understanding of the role of phytoplankton for marine ecosystems and global biogeochemical cycles, information on the global distribution of major phytoplankton groups is essential. Although algorithms have been developed to assess phytoplankton diversity from space for over two decades, so far the application of these data sets has been limited. This scientific roadmap identifies user needs, summarizes the current state of the art, and pinpoints major gaps in long-term objectives to deliver space-derived phytoplankton diversity data that meets the user requirements. These major gaps in using ocean color to estimate phytoplankton community structure were identified as: (a) the mismatch between satellite, in situ and model data on phytoplankton composition, (b) the lack of quantitative uncertainty estimates provided with satellite data, (c) the spectral limitation of current sensors to enable the full exploitation of backscattered sunlight, and (d) the very limited applicability of satellite algorithms determining phytoplankton composition for regional, especially coastal or inland, waters. Recommendation for actions include but are not limited to: (i) an increased communication and round-robin exercises among and within the related expert groups, (ii) the launching of higher spectrally and spatially resolved sensors, (iii) the development of algorithms that exploit

Photosynthesis–irradiance parameters of marine phytoplankton: synthesis of a global data set

“…As new remote-sensing algorithms are now starting to yield information on the size and taxonomic structure of phytoplankton, it would be useful to derive additional information on the P-E response of key phytoplankton taxa and size classes, especially those implicated as playing key roles in ocean biogeochemical cycles (LeQuéré et al, 2005;Nair et al, 2008;Bracher et al, 2017). Although detailed information on the taxonomic and size structure of ship-based experiments was lacking for several of the samples included in this data set, more recent studies include some measure of phytoplankton community structure, whether it be from use of pigment markers, size fraction of pigment and/or productivity, or cell counts.…”

“…As information on the global distribution of key phytoplankton groups is becoming available from global studies of phytoplankton pigment markers and flow cytometric counts (Buitenhuis et al, 2012;Peloquin et al, 2013;Swan et al, 2015), links between phytoplankton biogeography and large-scale pattern in photophysiology as revealed through the P-E parameters may be explored. Although there is a question as to what the standard indices of community structure should be that can help account for community-based variation in the photophysiological parameters across oceanographic data sets (Bracher et al, 2017), it is likely that information on gross community structure alone will not account for a large fraction of the variability in P-E parameters, especially across regions or seasons with different environmental forcing (Bouman et al, 2005;Smith Jr. and Donaldson, 2015) or resident ecotypes (Geider and Osborne, 1991). Establishing relationships between taxonomic composition and phytoplankton photophysiology will require simultaneous measurements of community structure alongside photosynthesis-irradiance experiments.…”

Regional Empirical Algorithms for an Improved Identification of Phytoplankton Functional Types and Size Classes in the Mediterranean Sea Using Satellite Data

“…Nowadays, in the context of international Climate Change Initiatives and cooperation, a synergic effort of the Space Agencies in collaboration with remote sensing scientist is conducted to identify the major gaps (both instrumental and scientific) that should be filled to improve the accuracy of satellite estimates of the phytoplankton groups and their variability (Bracher et al, 2017). In this framework, the following actions summarize our future perspectives to improve remote observations on the Mediterranean Sea: (a) to extend the validation and calibration of the PFT new regional algorithms including new in-situ dataset of HPLC Total Chlorophyll a and diagnostic pigments acquired, in recent years, by the Mediterranean scientific community; (b) to improve the accuracy of the PSC algorithms with a new calibration and validation only based on TChla size-fractions; (c) to carry on the insitu bio-optical measurements to cover all the un-sampled Mediterranean regions, also with the intent to exploit different approaches (e.g., spectral response-based); (d) to extend this regionalization activity to new generation sensors (e.g., OLCI for Sentinel-3) to obtain higher resolution information also for phytoplankton dynamical studies at mesoscale; (e) to analyse the Mediterranean PFT and PSC trends, thanks to the availability of consistent long term satellite observation time series.…”

Reproduction of Spatio-Temporal Patterns of Major Mediterranean Phytoplankton Groups from Remote Sensing OC-CCI Data

“…Finally, observed increases in Chla correlate with decreases in the contribution of picoplankton and nanoplankton, and increases in diatom concentration during February and March (Siokou-Frangou et al, 2010). Bracher et al (2017) recently highlighted the limited applicability of global satellite algorithms to determine the composition of phytoplankton at a regional scale as one of the major gaps in satellite research. Accordingly, these authors suggest a roadmap for future developments in regionally adapted algorithms.…”