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Indicators to assess temporal variability in marine connectivity processes: A semi-theoretical approach
Morane Clavel-Henry1, Nixon Bahamon1, Jacopo Aguzzi1
1Institut de Ciències del Mar, Consejo Superior de Investigaciones Científicas, Barcelona, Spain.
Plos One
|July 1, 2024
Summary
Temporal variability in oceanographic connectivity is key for marine conservation. New indicators can assess connectivity changes, aiding Marine Protected Area (MPA) network design and effectiveness. This helps prioritize marine resource protection.
Area of Science:
- Marine ecology
- Oceanography
- Conservation science
Background:
- Effective marine conservation relies on understanding oceanographic connectivity.
- Temporal variability in connectivity is often overlooked in Marine Protected Area (MPA) network design.
- Assessing connectivity dynamics is crucial for stable marine populations.
Purpose of the Study:
- To define and test indicators for temporal variability in marine connectivity.
- To evaluate connectivity patterns in the northwestern Mediterranean Sea.
- To assess the influence of hydrodynamics and transport duration/depth on connectivity.
Main Methods:
- Developed indicators for connectivity occurrence, flux, and frequency.
- Utilized a passive particle transport model for semi-theoretical connection estimation.
- Compared connectivity over a climatological year and specific years (2006-2020).
Main Results:
- Significant deviations in connectivity were observed between the climatological year and actual years.
- Indicators revealed spatial differences in connectivity influenced by location and mesoscale hydrodynamics.
- Temporal connectivity variability was affected by particle transport duration and depth, though patterns varied across zones.
Conclusions:
- Indicators of temporal connectivity variability can support spatial conservation planning and MPA effectiveness evaluation.
- These indicators can help prioritize marine resource protection with specific objectives.
- A long-term vision for ocean management can benefit from incorporating temporal connectivity dynamics.

