The Marine Organic Carbon Atlas Living Lab will contribute to the following project objectives:

• help better understand links between biodiversity, biogeochemistry and climate;
• enable development, initialization and validation of ecosystem forecasts and biogeochemical models.
   

In the MOCA Living Lab we will undertake significant local and regional data rescue efforts related to several EOVs, initiate a new organic carbon data product based on decades-long pelagic and benthic ecosystem monitoring in the Arctic..

The MOCA Living Lab will conduct data rescue efforts to unlock unprecedented amounts of historical data collected in the Arctic using standardised (Darwin Core) metadata and data records. The demo product for the Arctic will be co-created with international modelling communities to ensure direct applicability for biogeochemical and ecosystem models. MOCA will deliver a roadmap towards a novel data product building on the state-of-the-art biological and biogeochemical data, and publish pilot datasets from the Arctic region. Development of the Arctic pilot of MOCA, including its visual formats, will be consulted with specific needs of local (Svalbard, Greenland) authorities and other stakeholders with specific interest in blue carbon and biodiversity monitoring and resource management.

Main EOVs studied in the Living Lab:
(Click on the EOV name to access the corresponding GOOS EOV Specification Sheet if available)

Phytoplankton biomass and diversity

Zooplankton biomass and diversity

Benthic invertebrate abundance and distribution (EOV Specification Sheet under development)

Seagrass cover and composition

Macroalgae canopy cover and composition
 

Task on “Validation of emerging technologies” 

Lead partner: UNIPI

Contributing partners: DTU, UU, CIIMAR, MOi

In this task we perform calibration and validation of emerging biodiversity observation technologies to sense EOVs through direct comparisons with traditional sampling methods, with the aim of increasing their spatial coverage and sampling frequency. The task focuses on cabled camera networks, eDNA sampling, Argo floats and acoustics, and how modelling analyses can add value to these observations. Recommendations for improved sampling protocols will also be provided. 

Task on “Predicting key ecosystem services: carbon sequestration in the open ocean”

Lead partner: DTU

Contributing partners: MOi, IOPAN

This task will use historical and newly connected in situ data in combination with state-of-the-art models to better quantify the processes that contribute to export flux and carbon sequestration; and recommend how these processes could be best measured within the EOV framework. Main focus of the task will be on 1) phyto- and zooplankton functional diversity and biomass, 2) vertical migration of zooplankton, mesopelagic fish and invertebrates, 3) feeding and respiration rates of epi- and mesopelagic copepods and 4) effect of multiple stressors on the behaviour and metabolic rates of functional groups of zooplankton and mesopelagic organisms. 

Task on “Coordination of the living labs to demonstrate an operational workflow in different settings” 

Lead partners: IOPAN, UU

Contributing partners: All partners

This task coordinates across all the focal living labs to iteratively test the ability to

connect all the components of the workflow by responding to the Blueprint’s guiding questions in particular settings. Feedback from the living labs will be collected at various stages and used to improve the final Blueprint. 

Task on “Improved capacity for sustained observations and reporting of EVs and related indicators” 

Lead partner: UNESCO

Contributing partners: IOPAN, AIR CENTRE, UNIPI, UU, CIIMAR

This task will demonstrate the improved ability to observe and report on various biology and ecosystems Essential Variables (EV) and indicator frameworks. Knowledge of the status of biological observations will be improved by collecting metadata from previously unreported long-term monitoring activities to the GOOS BioEco Portal, thus enabling better identification of outstanding gaps in coordinated observations and data reporting. We will also review positive examples of adopting common sampling protocols for the benefit of integrating collocated biological, biogeochemical and physical EOV observations to develop novel data

products and applications.

Task on “Development of new EOV data products and associated roadmaps”

Lead partner: IOPAN

Contributing partners: All partners

This task develops roadmaps and implementation plans towards establishing new biological data products critical for advancing ecosystem, biodiversity and climate projections and global assessments. Roadmaps will be co-created with relevant stakeholders, in particular the modelling communitie and key data integrators. In the process we will test the applicability of the Blueprint workflow specifically for data product development. Substantial data rescue effort targeting publication of long-term biological observations from the Arctic region will be undertaken to deliver a pilot demonstration of the Marine Organic Carbon Atlas. Incorporating remote sensing and model estimates of marine organic carbon stocks and fluxes will help better understand and model the links between biology, biodiversity, biogeochemistry and climate.

Task on “Demonstrated advancement in BioEco forecasting” 

Lead partner: MOi

Contributing partners: IOPAN, DTU

This task will contribute to decreased uncertainty in biology and ecosystem model projections to facilitate regional and global assessments. Particular examples of this are the leatherback turtle model and the trait-based approach to modelling unicellular and multicellular life in the ocean. In parallel, we will collaborate with international expert working groups to further the development of a protocol for scientific validation of BioEco model forecasts.

Task on “Establishing early-warning indicators, detecting and assessing impacts of compound events and tipping points”

Lead partner: UNIPI

Contributing partners: MOi, DTU, CIIMAR, UU, IO PAN

Some of the main challenges addressed in the different focal living labs are identifying and predicting nonlinear changes (such as tipping points), potentially caused by combined effects of different forcing factors. In addition to classical indicators of loss of resilience based on time series, this task considers spatial early warning signals that rely on short-term observations that can be easily obtained and updated. We will recommend and test the performance of a set of potential early-warning indicators. The focus will be on exploring indicators from cable camera observations relevant to detecting changes in macroalgae and seagrass; and new functional plankton diversity indicators derived from a combination of

trait-based models and historical observations.