|Task 5.1: Coordination and Dissemination|
|Task 5.2: Functional homogenisation support and tools for mature coastal observing platforms|
|Task 5.3:Procedures and best practices for observing biological and biogeochemical variables from JERICO-RI platforms|
|Task 5.4: Performance Monitoring for the operation and integration of JERICO-RI platforms|
Procedures and best practices for observing biological and biogeochemical variables from JERICO-RI platforms
M1-M38 (Lead: SMHI; Partners: SOCIB, NIVA, CNRS, HCMR, CNR, AZTI, NORCE, IFREMER, CEFAS, IRB, VLIZ, Hereon, SYKE)
The actions will be performed within the following Steering Teams: ST5 Biogeochemical variable from various platforms (NIVA, SOCIB, CNRS-LOV, HCMR, CNR), ST6 Automatic sampling for DNA analysis (AZTI, NORCE, CEFAS, IRB), ST7 Biological automated platforms (CNRS, CEFAS, SMHI, IFREMER, VLIZ, Hereon, SYKE, NIVA).
Subtask 5.3.1 Observing biogeochemical variables from multiple JERICO-RI platforms (Lead: NIVA; ST5). While progress has been made in recent years, there still exists a significant gap in coverage, as well as harmonisation in implementation, of biogeochemical sensors on coastal observing platforms (e.g., carbonate system variables, oxygen, nutrients). Various reviews, intercomparisons, and best practices have been produced for biogeochemical sensors, but recommendations related to implementation of near real-time (NRT) biogeochemical observations on different JERICO-RI platforms (FerryBox, gliders, coastal profiling systems, fixed platforms) are still needed. This subtask will use inputs of operational experiences from ST5, IRSs (WP3), PSSs (WP4), and related innovation activities in WP7 for implementation recommendations (D5.4). This will in turn contribute to the JERICO-RI science strategy (WP1) and subsequent integration of biogeochemical observations in IRS/PSSs.
Subtask 5.3.2 Protocols for automatic sampling for DNA analysis (Lead: AZTI; ST6). Community DNA can provide information on the organisms sampled by a particular method (filtration, plankton net, sediment grab, …). Within this subtask, we aim at producing Standard Operating Protocols (SOP) for automated coastal water sampling and preservation of target molecules (barcodes) for DNA based biodiversity lab measurements. The produced SOP (MS5.2) will be used as guideline and specifications for the development of the DNA module of the WASP (WP7.2.3). SOP will be possibly revised and adjusted following the results of the testing of the WASP (MS5.6).
Subtask 5.3.3 Biological automated sensors (Lead: CNRS; ST7). The task will progress toward the definition of best practices on the implementation/deployment of biological automated sensors following the JRAPs activities performed in JERICO-NEXT (MS5.1). The focus will be mainly on phytoplankton functional diversity using flow cytometry and multispectral fluorometer. Phytoplankton and zooplankton diversity will be addressed by in flow and in situ imaging. This task will define operational and calibration procedures, determine flags to be implemented in the metadata base (WP6), develop specific recommendations according to the IRS and PSS specificities and platform types for sampling strategy (D5.6). The latter will be exploited for further technological development of flow cytometry sensors in WP7.2.2. In collaboration with the sensor providers, a checklist on sensor performance will be established (e.g catalogue of the specificities for each sensor, diagnostic after maintenance, troubleshooting guide) and annually reviewed by the ST7. To move towards physiological measurements as well at the interface with biogeochemistry (primary productivity), the fast repetition rate fluorometry (FRRF) will be discussed as an emerging technology for measuring primary production.
Task 5.3: D5.4 Recommendation for Multiplatform implementation of a biogeochemical NRT observatory.
Task 5.3: D5.1 Catalogue and checklists for existing biological sensors that will be implemented in J-S3.
Task 5.3: D5.6 Best practices document for sampling procedures of biological automatic sensors (imaging-in-flow, automated flow cytometry and multispectral fluorometry)