Influences of Herbivores, Temperature, and Nutrient Availability on Marine Microbial Assemblages: Results of an in-situ Field Experiment

While the importance of nutrient cycling between macrofauna and microbes in pelagic systems is well recognized, researchers in intertidal marine systems frequently ignore the nutrient feedbacks between herbivores and co-occurring benthic biofilms. Although herbivores have well-documented consumptive effects on benthic microbial growth, they also alter local nutrient availability and algal recruitment on rocky shores. Herbivore mediation of local-scale processes can impact microbial diversity and function from both the top-down (via consumption) and the bottom-up (via nutrient regeneration and enhancement of recruitment). The net effect of herbivory on benthic microbial communities and their productivity remains understudied. Water temperatures, herbivore abundances, and nutrient availability are being altered by humans, and we predict that these changes are likely to affect the interactions between herbivores and microbial biofilms. We conducted a manipulative experiment to quantify the main and interactive effects of herbivore density (removal, addition), temperature (ambient, elevated), and nutrient concentrations (ambient, elevated) on benthic biofilms in tide pools at two locations on the California coast characterized by different nutrient levels and seawater temperatures. In each tide pool, we installed stone tiles as substrates for microbial recruitment. Half of the tiles in each pool were fenced to limit consumption of the biofilm by molluscan grazers, but fences allowed nutrients to pass freely. At the completion of the experiment, tiles were collected and a total of 160 samples per site were collected for microbial analysis using 16S rRNA and 18S rRNA to assess effects of herbivores, temperature, and nutrients on microbial diversity. By identifying and characterizing these benthic microbial communities, we can begin to understand the effects of consumers on marine ecosystem functioning and to predict how ecosystems are likely to be disrupted in the future.