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Dryad

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

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Dec 04, 2024 version files 2.19 MB

Abstract

Kelp forests serve as the foundation for shallow marine ecosystems in many temperate areas of the world but are under threat from various stressors, including climate change. To better manage these ecosystems now and into the future, understanding the impacts of climate change and identifying potential refuges will help to prioritise management actions. In this study, we use a long-term dataset of observations of kelp percentage cover for two dominant canopy-forming species off the coast of Victoria, Australia: Ecklonia radiata and Phyllospora comosa. These observations were collected across three scuba sampling programs that extend from 1998 to 2019. We then associated those observations with habitat and environmental variables including depth, seafloor structure, wave climate, currents, temperature, and population connectivity in generalised additive mixed effects models and used these models to develop predictive maps of kelp cover across the Victorian MPAs. These models were also used to project kelp coverage into the future by replacing wave climate and temperature with future projections (2090, RCP4.5 and RCP8.5). Once all the past, current, and future predictions were compiled, we calculated percent cover change from 1998-2019, stability over the same period, and future predicted change in percent cover (2019-2090) to understand the dynamics for each species across the MPAs. We also used the current percentage cover, stability, and future percentage cover to develop a ranking system for classifying the maps into high climate vulnerability, climate vulnerability, neutral, potential refugia, and likely refugia. A management framework was then developed to use those refugia ranking values to inform management actions and we applied this framework across three case studies: one at the scale of the MPA network and two at the scale of individual MPAs, one where management decisions were the same for both species and one where the actions were species-specific. This study shows how species distribution models, both contemporary and with future projections, can help to identify potential refugia areas that can be used prioritise management decisions and future-proof restoration actions.