Determining the Influence of Seascape Structure on Coral Reef Fishes in Hawaii Using a Geospatial Approach

Abstract

We assessed the utility of several LIDAR-derived seascape metrics (e.g. depth, rugosity, slope, variance in depth) to determine which measures of the seascape demonstrated important relationships with fish assemblage structure and would ultimately serve as the best ecological criteria to advance predictive modeling of fish assemblages using remote sensing and GIS analysis. Variance in depth (within a 75 m radius) was the seascape metric that had the strongest relationships with most fish assemblage metrics, followed by depth and slope. Our results demonstrate the potential for using remotely sensed measures of the seascape to support predictive mapping and modeling of fish assemblages.

Keywords:

• Seascape metrics
• remote sensing
• LIDAR
• GIS
• marine protected area
• Hawaii

Acknowledgements

We would like to thank Athline Clark, Paul Jokiel, Eric Brown, and Alan Hong for their support during this project. Mark Monaco, Simon Pittman, and two anonymous reviewers provided valuable comments on this manuscript. The U.S. Army Corps of Engineers contributed the SHOALS LIDAR data used for this study. This research was funded by NOAA's Coral Reef Conservation Program and National Centers for Coastal Ocean Science-Center for Coastal Monitoring and Assessment.

Notes

∗Pupukea MLCD boundary was expanded and rules were modified in 2003.

∗∗Selar crumenophthalmus (November-December) and Decapterus spp. (August-September).

∗measurement taken in a 75 m radius buffer around the transect location.