Mechanisms driving Antarctic microbial community responses to ocean acidification: a network modelling approach
Subramaniam, RC and Melbourne-Thomas, J and Davidson, AT and Corney, SP, Mechanisms driving Antarctic microbial community responses to ocean acidification: a network modelling approach, Polar Biology, 40, (3) pp. 727-734. ISSN 0722-4060 (2017) [Refereed Article]
Rising atmospheric CO2 concentrations and the subsequent changes to ocean chemistry may have pronounced effects on marine microbial communities, particularly for the cold Southern Ocean. Changes to the microbial community in this region could affect the way nutrients are cycled, impact the efficiency of carbon drawdown, and cause shifts in food supply to higher trophic levels. Increased CO2 could affect the bioavailability of iron to phytoplankton. Fertilisation experiments show that iron can influence phytoplankton community composition, favouring large phytoplankton species in iron-replete conditions. The potential interactive effects of CO2 and iron bioavailability are currently poorly understood but are likely to be important in determining CO2-induced changes to the microbial community. We employ a qualitative network modelling approach to evaluate alternative hypotheses regarding the effects of elevated CO2 on Antarctic microbial communities in incubation experiments. We used a sequential approach to model development and testing, where we first formulated a base model for microbial community interactions, and then sequentially added direct and indirect effects of elevated CO2 on particular groups. We found that model simulations were most consistent with observations from incubation experiments when we assumed an indirect effect of CO2 on phytoplankton. In particular, when we assumed a negative effect of elevated CO2 on the uptake of iron by large phytoplankton, as a result of a decrease in iron bioavailability. Our findings show that qualitative network models can be used to test hypotheses relating to results from experimental studies, and help identify key processes to target in future studies.