Action #5: Intercomparison of phytoplankton distribution using data integration

Objectives: Create and integrate representation of phytoplankton combining different data sources: in-situ observations from various platforms and sensors, satellite data, and model data. This activity involves a range of drivers of phytoplankton dynamics, including hydrodynamic transport, river loads (through models), underwater light climate and associated turbidity, and suspended particulate matter (SPM) dynamics. It aims at quantifying the impacts of phytoplankton dynamics in terms of eutrophication and carbon fluxes. This action will also evaluate the potential of merging multi-source knowledge to estimate the spatial and temporal variability of phytoplankton and SPM concentration in response to intense/extreme events and long-term trends. 

Action Lead and other Partners (with contact persons): DELTARES (Blauw, Van Kessel), IFREMER (Lefebvre, Verney), CNRS (Artigas), CEFAS (Collingridge, Greenwood), VLIZ (Debusschere), HEREON (Voynova) RBINS (Fettweis).

JS3 Platforms included: FerryBox: Lysbris (HEREON), Magnolia Seaways (HEREON), FunnyGirl (HEREON), Thalassa (IFREMER), Côtes de la Manche (CNRS), Sepîa II (CNRS), Antéa (IRD), Norrona (NIVA), Connector (NIVA/RWS), Simon Stevin (VLIZ); Buoys: ASTAN (CNRS), SMILE (IFREMER, CNRS), SCENES (IFREMER), WARP TH1 and WEST GABBARD (CEFAS), Thornton (VLIZ); Benthic lander MOW1 (RBINS); Cabled observatory COSYNA Helgoland (AWI, HEREON); Fixed Station MAREL-Carnot (IFREMER); Additional infrastructure: monitoring by R/V. 

Other data sources and external partners for implementation: Available satellite data on chlorophyll-a, suspended particulate matter, primary productivity and sea surface temperature could provide useful additional data with good spatial and temporal coverage. 

Overall timetable of action: Dec 2020 – Aug 2022.

Description of action: Despite the presence of observational platforms in both the Channel and the North Sea, observational infrastructures are operated by regional and national entities and have been hardly connected so far. Usually, the field data are obtained from different locations and times and cannot be directly compared. Satellite and model data are available for the whole area (both Channel and the North Sea) for long periods. For this action, the models of DELTARES and IFREMER (ECOMARS-3D) will be used as ‘smart interpolation’ tools of observation data. These will provide coherent baselines in space and time to cross-validate the different available data sources and gain a better understanding of the drivers of spatial and temporal variability of phytoplankton and carbon fluxes and underlying nutrient and SPM concentration fields. Therefore, we will first start with creating the overview of available in situ and remote sensing observation data and making (part of) these data available for model validation. Processing of existing data files into coherent datasets that have comparable variable definitions with model variables will be done as far as feasible. Some data files may require too much work to be processed in this context or lack knowledge on how to convert them. 

The Action will investigate how the aggregation of coastal observatory databases, satellite ocean colour databases, and model results can resolve the spatio-temporal variability of phytoplankton, carbon, and SPM dynamics. This question will be examined from regional to inter-regional and PSS spatial scales and will look for innovative methods to decipher the contribution of « expected seasonal dynamics », unexpected, rare or extreme events, and long-term trends. 

This action will not involve additional monitoring activities. However, the results of the comparison will provide information on the comparability of data from different platforms and equipment. This supports the planning of the next steps towards more coherent monitoring, which will possibly involve the sharing of platforms and equipment. 

Best practices used or developed: N/A as no specific sampling planned.

Data flows: Partners collecting in situ marine data will share these data with other partners working on the comparison with satellite and model data.

Data QC routines: Each institute is responsible for the QC on its own data. When sharing the data with other partners involved, the metadata on applied QC procedures will be shared as well.

Data management issues: Data will be shared preferably from existing portals, so other partners can download and process the data with automated scripts that can be easily updated in the future. Where this is not feasible, the data files can be shared with other ad-hoc approaches, such as mails or cloud servers. 

Expected results: The comparison of the various sources of in-situ data with coherent satellite and model data is expected to provide information on 1) the comparability and quality of the sensor-based in-situ data and 2) the reliability of the satellite and model data and 3) possible next steps to reduce differences between information from different data sources. 

Users of results: An integrated representation of eutrophication indicators (nutrients, chlorophyll-a) and biodiversity indicators (primary production and phytoplankton species composition) would enable more complete and coherent ecosystem assessments for OSPAR and MSFD. Furthermore, JERICO partners and OSPAR member states can improve their monitoring and QC strategies based on our experiences with combining data from different monitoring methods. 

Dissemination of results: Results will be presented in relevant meetings of the project, conferences, and OSPAR/MSFD meetings.

Links: This action will contribute to Action #6 (Identification of Observational Gaps) by identifying gaps in data availability and measurement efforts and is linked to tasks 2.3 (satellite data), 2.4 (linking across different scales and regions; coupling of observations and modelling communities) and task 2.5 (linking to the political realm).