Aquifers are oligotrophic environments that harbour diverse and novel microorganisms. These microorganisms form networks of microbial food webs which govern biogeochemical processes and cycle nutrients. Currently, little is known about the functional capacities of these subsurface ecosystems and how globally problematic anthropogenic pollutants, such as nitrate, can effect ecosystem health. This project aims to study how these communities respond to and mitigate inputs of pollution. We hypothesize that aquifer metabolism will strongly reflect non-agricultural and agricultural influences on groundwater chemistry, and that groundwater microorganisms play an important role in mitigating nutrient pollution. A series of wells in a globally common aquifer type – alluvial sandy gravel - were selected along a nutrient gradient in Canterbury, New Zealand. Biological groundwater samples were recovered using filtration. Microbial cells were captured using a 0.22 μm pore size filter. In order to sample both groundwater communities and communities attached to the aquifer substrate, we used a low-frequency in situ sonication to induce biofilm detachment. Chemical parameters of the groundwater such as nitrogen species, sulfur species, organic carbon and metals were measured. The nitrate gradient across the well series ranges from 0.45 to 12.6 g/m3. Results from 16S amplicon data shows changes in community composition across the gradient. In particular, higher abundances of N2-producing anaerobic ammonium-oxidizing Planctomycetes (Brocadiales) were found at anoxic sites. Consistent with this observation, excess N2 was detected in groundwater at these anaerobic sites, indicating removal of N from the system. Whole genome and transcriptome sequencing is in process in order to gain insights into active gene pathways across the nitrate gradient. To expand the scope of these findings a survey of aquifers of similar lithology across New Zealand is also underway. This will allow key steps in the nitrogen cycle to be quantified across different nutrient conditions using Droplet Digital PCR. Information from this survey will determine the dominant N-cycling mechanisms in nutrient polluted and pristine aquifers.