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Assessing drivers of rocky reef fish biomass density from the Southern California Bight

Biomass is often used as a metric for valuing and comparing ecosystems. However, many variables contribute to the amount of biomass an ecosystem can maintain; thus, it is necessary to evaluate the driving forces of patterns in biomass variation across sites. Here we utilized datasets associated with nearshore rocky reef fish biomass that span the Southern California Bight, using generalized least-squares modelling within the information-theoretic approach. Fish density, length, invertebrate density, algal density, and reef characteristics (relief and substrate type) were visually sampled at 89 sites, via SCUBA, with a random stratified sampling design using belt transects across depth strata in <20 m depth. Fish data were converted to biomass using published length–weight relationships. In addition to our visual surveys, spatially resolved ex planatory variables included sea surface temperature, sea surface chlorophyll a, maximum wave height, kelp biomass, fishery harvest intensity index, a new remote sensing method for calculating reef slope, and distance to the 200 m isobath, a novel characteristic. All models in the confidence model set (ΔAICc <2) for total fish biomass included the variables sea surface temperature, distance to the 200 m isobath, sea surface chl a, slope, and the standard deviation of substrate and relief. Not all rocky reefs in the SCB equally support high densities of fish biomass, and our results suggest that an optimal combination of physical characteristics and forcing drive this variation. The novel variable, distance to the 200 m isobath, may be applicable for understanding fish biomass variation in marine ecosystems.