The Pelagic Ocean Living Lab 1 focuses on studying the importance of low trophic levels of the ocean food web for the epipelagic and mesopelagic (0 to 1000 m depth) ocean ecosystems. Changes within the zooplankton community, such as species abundance, stock and functional diversity, are vital for the distribution of higher predators like fish, seabirds, sea turtles and mammals. For example, salps, a gelatinous zooplankton group, are targeted prey of some marine turtle species, but can also compete with other zooplankton groups like copepods and krill for resources, and impact fish recruitment success.
Objectives
Our key objectives in the Pelagic Ocean Living Lab 1 are to:
- Advance the knowledge of the interplay between ocean biodiversity, biogeochemistry and climate by identifying the importance of functional zooplankton diversity in energy transfer, food web dynamics and carbon fluxes for different climate conditions;
- Develop forecasting tools for trustworthy projections on marine species habitat suitability that can be used for policy advice and operational forecasting (e.g., monitor and project the status of Marine Protected Areas, advice for sustainable fisheries strategies).
Through its work, the Pelagic Ocean Living Lab will demonstrate an increased capacity to understand and project changes in several Essential Ocean Variables as well as Essential Biodiversity Variables, contributing towards more operational workflows, from observing system design to policy applications, with respect to biological and ecosystem ocean observations.
The Pelagic Ocean Living Lab 1 is collaborating closely with the Pelagic Ocean Living Lab 2 and the Marine Organic Carbon Atlas Living Lab.
Essential Ocean Variables under study
Main EOVs studied in the Living Lab:
(Click on the EOV name to access the corresponding GOOS EOV Specification Sheet if available)
Zooplankton biomass and diversity
Marine turtles abundance and distribution
Fish abundance and distribution
Related project tasks
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Task on “Establishing early-warning indicators, detecting and assessing impacts of compound events and tipping points”
Lead partner: UNIPI
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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.
