Incorporating molecular-based functional and co-occurrence network properties into benthic marine impact assessments

Taxonomic and functional community structures may respond differently to anthropogenic stressors. Used in combination they can provide an estimate of functional redundancy, a key component of ecosystem resilience. In this study, the utility of incorporating functional community structure and co-occurrence network properties into impact assessments of offshore oil and gas (O&G) operations on benthic bacterial communities was investigated. Sediment samples and physico-chemical data were collected along a transect at increasing distances from one exploratory drilling (ED), and one gas production and drilling (GPD) field. Bacterial community composition was determined by 16S rRNA metabarcoding. A hidden-state prediction method (PAPRICA) was used to characterize bacterial metabolic community functions. At both sites, diversity differed significantly between near-field (impacted) and far-field (non-impacted) stations, with both taxonomic and functional alpha-diversity positively affected in near-field stations at the GPD site. The opposite pattern was observed in the near-field samples of ED with lower and higher values respectively. Overall, impacted stations displayed a distinct network signature, with a lower ratio of positive interactions and signs of higher community cohesion. Community profiles from metabolic inference and co-occurrence network topology provided complementary information to taxonomic indices, which may assist with assessing the effects of O&G activities on benthic communities.