Using predictive models to identify kelp refuges in marine protected areas for management prioritization

Area of Science:

• Marine ecology
• Climate change impacts
• Conservation science

Background:

• Kelp forests are vital foundation species in temperate marine ecosystems.
• Climate change poses significant threats to kelp forest persistence.
• Identifying climate refugia is crucial for effective marine ecosystem management.

Purpose of the Study:

• To model current and future kelp (Ecklonia radiata, Phyllospora comosa) distribution in Victoria, Australia.
• To identify potential climate refugia for kelp forests within Marine Protected Areas (MPAs).
• To develop a management framework for prioritizing conservation and restoration actions.

Main Methods:

• Utilized a long-term dataset (1998-2019) of kelp percentage cover.
• Employed generalized additive mixed-effects models incorporating environmental variables (depth, wave climate, temperature, etc.).
• Developed predictive maps of current and future kelp cover (2090, RCP 4.5 & 8.5) and classified refugia.

Main Results:

• Generated spatial predictions of kelp cover and change over time.
• Identified areas of current stability and future predicted change for both species.
• Classified MPAs into refugia categories (unlikely, neutral, potential, likely).

Conclusions:

• Species distribution models effectively identify potential kelp forest refugia.
• The developed management framework aids in prioritizing conservation actions.
• Future-proofed management strategies are essential for kelp forest resilience.