High-resolution mapping of artificial reefs in southern California: Linking sonar-derived habitat metrics to reef construction material and design

Artificial reefs can be designed to support ecosystem functioning by optimizing habitat variables. Unfortunately, fine-scale quantitative descriptions of their habitat structure remain limited, especially in California. We collected high-resolution sonar bathymetry and backscatter (0.3 m cells) across 13 artificial reef complexes and shipwrecks along the southern California coast. There were 154 delineated reef modules using an unsupervised habitat-classification workflow that integrated bathymetry-derived slope and vector ruggedness with backscatter. Most modules were primarily composed of quarry rock (n = 84) or concrete pilings/light poles (n = 45), with additional concrete rubble modules (n = 14), barges (n = 4), shipwrecks (n = 3), and a missile tower (n = 1). This approach generally resolved boundaries, but irregular and discontinuous modules built from primarily scattered concrete materials (e.g., pier pilings, light poles, dock floats) lacked clear edges and often included interspersed soft bottom, rendering their mapped footprints more subjective as opposed to contiguous materials (e.g., quarry-rock piles, barges, shipwrecks). For each module we calculated footprint area, volume, mean and maximum vertical relief, mean slope, mean rugosity, and standard deviation heterogeneity metrics for relief, slope, and rugosity. In multivariate analyses modules generally grouped by construction material and design (artificial reef complex), indicating that these metrics capture ecologically relevant structural differences. Quarry rock modules generally exhibited higher mean relief, slope, and rugosity over more compact footprints, whereas scattered concrete modules typically had lower mean complexity but greater rugosity heterogeneity, driven in part by extreme low and high values created by interspersed patches of flat soft bottom amongst concrete materials. The resulting maps improve positional accuracy relative to historical maps and our approach provides a workflow for quantifying reef habitat structure, enabling analyses informing the design of artificial reef projects.