Recovery rates of benthic communities following physical disturbance

Abstract

Summary Despite numerous studies that have investigated the effects of physical disturbance on marine benthic communities, deducing the ecological significance of such events has been hampered by the specificity of individual studies. Less stable habitats (coarse, clean sands) are thought to recover more quickly than stable (muddy sands and mud) habitats but so far an empirical test of this paradigm has been lacking. We describe a large‐scale field experiment that investigated the response of marine benthic communities within a variety of sediment types (clean sand, silty sand, muddy sand and mud) to physical disturbance. Sites were sampled for macrofauna and habitat characteristics (sediment organic content and water content, depth of water within disturbed pits) following disturbance, in order to examine any relationship between the rate of physical and biological recovery. There were no detectable changes to the measured physical parameters following the disturbance with the exception of the water depth within disturbed areas. It was not possible to derive a linear relationship between the measured habitat characteristics (percentage silt and clay content) and the recovery trajectory of the associated community. However, the rate of sediment infilling of disturbed plots was strongly correlated to the recovery rate of the numbers of individuals within disturbed areas. Clean sand communities had the most rapid recovery rate following disturbance, whereas communities from muddy sand habitats had the slowest physical and biological recovery rates. These findings concur with the predictions of a meta analysis of fishing disturbances for similar habitats. We suggest that physical and biological recovery rates are mediated by a combination of physical, chemical and biological factors that differ in their relative importance in different habitats. Monitoring the infilling rate of physically disturbed patches of sediment has the potential to become a useful tool to predict the recovery rate of associated communities.