An Integrated Coral Reef Ecosystem Model to Support Resource Management under a Changing Climate

Ecosystem-based management is a useful management tool that considers both indirect and cumulative effects of added stressors to a system. Ecosystem models, especially those that consider physical and biological disturbances and human uses, can help to inform ecosystem-based management during planning and implementation stages. This study modified the Atlantis Ecosystem Model to quantify and predict the effect of added stressors on the Guam coral reef ecosystem. Specifically, the study focused on three main stressors: climate change, land-based sources of pollution (LBSP), and fishing. The study used the IPCC Fifth Assessment Report highest emission scenario to predict atmospheric COconcentrations and the RCP8.5 projection to predict sea surface temperatures. LBSP was predicted using previous data collected on Guam’s sediment and nutrient loads and river flow. Fishing predictions were based on historical catches. Short term (i.e. 30 years) and long term (i.e. 65 years) simulation tests were run for each stressor.

The short term tests revealed that fishing resulted in the greatest negative impacts with LBSP following close behind. Climate change became the dominant stressor in longer time scales with the bleaching threshold exceeded every year after year 48. It becomes clear that long-term high intensity disturbances from multiple stressors limits and sometimes even prevents ecosystem recovery. Limiting frequency, intensity, and number of stressors can significantly increase reef resilience. This study revealed that reducing LBSP and increasing water quality can delay climate-related impacts for up to 8 years while buying time for the corals to adapt to higher temperatures. The Atlantis Ecosystem Model and others like it can be used to provide a wealth of knowledge to inform ecosystem-based management decisions on both regional and global levels.

Author: Weijerman M., E.A. Fulton, I.C. Kaplan, R. Gorton, R. Leemans, W.M. Mooij, and R.E. Brainard
Year: 2015
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PLoS ONE 10(12). doi: 10.1371/journal.pone.0144165

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