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.