Our key objectives in the Tuscan Archipelago Living Lab are to: 

• validate emerging sampling technologies for macroalgae, including eDNA and imaging
• evaluate the statistical power of EOVs (macroalgae, seagrasses and fish) under scenarios of biodiversity change
• identify thresholds and tipping points* in the macroalgae and seagrass habitats, 
• develop early warning indicators,  
• quantify the cumulative effects of multiple stressors in these ecosystems.  

The Tuscan Archipelago includes seven islands that are managed differently with respect to human activities, with restrictions ranging from fully protected islands with limited human access and no extractive activities to fully open islands. This Living Lab thus provides a unique natural laboratory to test and validate innovative observing platforms and EOV indicators, especially regarding seagrass and habitat-forming macroalgae, along gradients of anthropogenic pressure.   

The Tuscan Archipelago Living Lab is closely collaborating with the Atlantic Living Lab and the Baltic Sea Living Lab. 

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

Macroalgae canopy cover and composition

Seagrass 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 “Evaluating the power of EOVs under scenarios of biodiversity change” 

Lead partner: UNIPI

Contributing partners: DTU, UU

In this task we assess the power of statistical models involving EOVs and their supporting, complementary and sub-variables under different scenarios of biodiversity change. This is because different EOVs may have different ability to capture changes such as steep vs. gradual decline or loss of resilience, depending on their inherent level of variability against which the signal must be identified. The task will generate power curves for different combinations of effect sizes and sampling designs that will ultimately guide the operational use of EOVs.

Task on “Variables to detect change” 

Lead partner: UU 

Contributing partners: CIIMAR, AD AIR CENTRE, UNIPI

This task explores the environmental, social and economic factors and associated variables that would be advantageous to measure to detect change in coastal systems. This will be done by reviewing the literature to identify potential drivers of change, which will then be translated to measurable variables (e.g., agricultural land-runoff could be estimated by area

of agricultural land). Future monitoring needs a much more holistic approach, and  environmental, social and economic factors need to be considered, and appropriate variables need to be measured, to understand the reasons for change, both positive and negative. 

Task on “Advancing remote sensing observations of marine biodiversity” 

Lead partner: AIR CENTRE

Contributing partners: UU, UNIPI, CIIMAR 

This task utilises the potential of emerging high-resolution remote sensing technologies to

improve the capacity to generate macroalgae and seagrass distribution maps from space, using Copernicus data. The development of models and tools to increase the certainty about the status and trends of macroalgae and seagrass will be validated with existing test sites, where the area covered with macroalgae and seagrass is well known, allowing to fine-tune the results. The developed frameworks will serve as a guidance tool to produce high-

resolution products of macroalgae and seagrass cover extent, and allow for enhanced mapping and improved monitoring of the EOVs.

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 “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.