5. CONCLUSIONS
In this study, we assessed the feasibility of utilizing estuarine monitoring data from a representative regulatory program (i.e., shellfish sanitation) to infer long term water quality trends. We used these data to look specifically at the spatial and temporal trends in FC concentrations and identified possible management and environmental drivers of these trends. Our study system, coastal North Carolina, exhibited a variety of trends in both the 20-year FC concentrations and the considered environmental drivers. While the resulting water quality trends and their relationships with environmental factors were complex, there were emergent patterns that we found to offer key insights. In particular, we concluded that shellfish sanitation data collected routinely through a systematic random sampling strategy as defined by the National Shellfish Sanitation Program (NSSP) could be used for long-term water quality trend analysis, and to fill extensive gaps in existing coastal water quality monitoring programs.
Although our results demonstrated opportunities of using shellfish sanitation data for inferring long-term water quality trends, our study was limited by several factors. Firstly, we did not account for tidal circulation due to the major modeling effort that would be required to include tidal circulation and flow patterns at this spatial and temporal scale. Future research should improve upon the methods presented here by including factors that capture the marine flushing of an area such as inlet maintenance or distance to the nearest intracoastal waterway. Secondly, there was a lack of unbiased FC concentration datasets for trend validation, and we relied on findings from prior published studies to “ground truth” FC trends calculated from monitoring data. Regions outside of our study area may not have access to the type of information used to help diagnose the reliability of shellfish sanitation monitoring data for water quality inference. As new monitoring programs are introduced to track changes in marine systems, opportunities to pair sites with existing shellfish sanitation program monitoring locations could help to create data needed to characterize potential sampling bias effects and increase the ability for long-term shellfish sanitation data to be used for water quality analyses. Finally, because of variation in sampling protocols across state programs, shellfish sanitation data are nuanced and challenging to interpret. This study offers context and an approach for confronting nuance in the data. However, directly engaging with shellfish sanitation program managers is essential to accurately interpreting trend results like those presented here, as local expertise provides invaluable insight into the state and function of these estuarine systems and their management.