1. INTRODUCTION
Healthy estuarine environments are critical for maintaining ecological
stability, coastal economies, and human health standards. In order to
maintain and even improve these habitats, metrics of current and past
conditions must be evaluated to inform proper management. Water quality
measurements can be used to indicate overall estuarine health and can
aid in understanding increasing coastal threats such as rising sea
levels, increased salinities, and urbanization. Long-term water quality
analysis is key for developing target thresholds for future management
action as well as assessing the efficacy of past management measures
(Cloern et al., 2016). The value of historical observations in advancing
understanding of estuarine water quality has been demonstrated by
multi-decadal studies of several systems, including the San Francisco
Bay area (Beck et al., 2018; Cloern et al., 2016), May River, South
Carolina (Souedan et al., 2021), Texas’s coastline (Bugica et al.,
2020), and the Chesapeake Bay area (Zhang et al., 2018; Harding et al.,
2019). Most notably, long-term water quality monitoring in the
Chesapeake Bay has led to the identification of climatic and
anthropogenic drivers for certain water quality parameters and
subsequent evaluation of the effectiveness of past management and
restoration efforts (Kemp et al., 2005; Leight et al., 2011; Zhang et
al., 2018; Harding et al., 2019).
Datasets used for prior longitudinal water quality studies are commonly
a product of governmental agencies developing localized programs, like
the Chesapeake Bay Program (Chesapeake Bay Monitoring Program, 2022), in
response to increasing population and significant degradation of vital
estuarine ecosystems. While national and regional efforts have attempted
to provide unbiased, sustained monitoring, these programs currently lack
the spatial extent needed to capture coastwide water quality trends. The
National Estuarine Research Reserve System (NERRS) is one of the few
organizations with dedicated coastal water quality monitoring stations,
which are included as part of the NERRS System Wide Monitoring Program
(SWMP) that maintains 355 coastal water quality monitoring stations
across 29 designated coastal reserves along the USA coastline (National
Estuarine Research Reserve System, 2022). Compared to the over 13,500
freshwater monitoring stations maintained by the United States
Geological Survey (USGS, 2022), the relatively small number of water
quality monitoring stations across coastal and estuarine waters (NOAA
Tides & Currents, 2022; US EPA, 2022) are likely not representative of
the variations in environmental conditions that we observe across the
tens of thousands of miles of shoreline along the United States.
Because of the limited number of unbiased monitoring programs, the
ability to use water quality data from regulatory operations presents a
potentially valuable resource for assessing long-term estuarine
conditions. Regulatory programs differ from monitoring programs by
collecting water quality samples to meet regulatory requirements and
inform short-term decision-making. For example, in North Carolina (NC),
there are four NERRS SWMP monitoring stations and eight coastal stations
with water quality data available through the USGS (South Atlantic Water
Science Center, North Carolina Office, 2022) and fifty stations from the
NC Ambient Monitoring System (Water Quality Portal, 2021), but the NC
Division of Marine Fisheries (NCDMF) shellfish sanitation program
maintains 1,924 water quality monitoring stations. In fact, state
shellfish sanitation programs across the USA collect an abundance of
water quality observations, and often have for decades. Shellfish
mariculture is highly dependent on water quality monitoring due to the
direct influence that ambient conditions have on the safety of shellfish
meat consumption. The U.S. Food and Drug Administration’s National
Shellfish Sanitation Program (NSSP) was developed in 1925 to maintain
public safety and human health standards in relation to the consumption
of shellfish grown in potentially polluted waters (NSSP, 2019). The
implementation of the NSSP has resulted in systematic sampling of water
quality for day-to-day fisheries regulation, specifically for Fecal
Indicator Bacteria (FIB), a group of bacteria that are commonly used as
a proxy measure for harmful pathogen loads in the waterway that could
potentially be incorporated into shellfish meat through filter feeding.
Thus, fecal coliforms (FC), a type of FIB, and other environmental
factors that contribute to FC load and water quality, are regularly
measured in shellfish growing waters due to the food safety
implications. As a product of this regular testing, fisheries operations
have accumulated decades of data with the potential to provide insights
on historical trends with wide spatial extents, potentially filling gaps
in long-term water quality monitoring capacity.
However, because of the limited resources and industry specific
priorities, regulatory data can maintain underlying biases as a result
of the sampling methodology used to collect the water quality sample.
Often, the collection of a sample can be motivated by day-to-day
operational decisions, such as weather, the availability of field
technicians, and ease of collection. These operational decisions lead to
non-random sampling that provides observations that are not always
representative of the system’s true dynamics. Engaging regulatory
personnel to understand their fisheries management and sampling
decisions is necessary to properly analyze the observations collected by
shellfish sanitation programs.
For example, the NSSP permits states to employ one of two sampling
strategies when collecting regulatory water quality data in shellfish
growing waters: adverse pollution condition sampling and systematic
random sampling. The adverse pollution condition sampling strategy
describes sampling in periods when known contamination events (commonly
due to point-source pollution events or rainfall events) have degraded
the water quality, and data collected under these conditions capture
peak contamination. States must collect “a minimum of five
samples… annually under adverse pollution conditions from each
sample station in the growing area” (NSSP, 2019) to meet NSSP sampling
requirements. In contrast, the systematic random sampling strategy
describes the collection of data across “a statistically representative
cross section of all meteorological, hydrographic, and/or other
pollution events” (NSSP, 2019), resulting in the data collection under
varied environment and climactic conditions. For state programs that use
systematic random sampling, the NSSP requires samples be collected at
least 6 times throughout the year (NSSP, 2019). As a result of the
requirements for the conditions under which the two systems of sampling
can take place, the resulting data may be biased and impact their
utility for use in long-term water quality assessments. With our growing
reliance on aquaculture and the expanding value of shellfish production
driving the development of fisheries management infrastructure (Azra et
al., 2021), long-term datasets available through shellfish sanitation
programs will become increasingly valuable. Realizing the potential of
regulatory datasets to inform long-term water quality trends is a vital
next step for assessing the health of our coastal ecosystems, but
research is needed to determine the utility of these data for water
quality analyses.
The goal of this study was to utilize shellfish management data to infer
long-term spatiotemporal trends in water quality parameters, including
FC and salinity, while accounting for variation in routine sampling
conditions and environmental landscapes. Study objectives included (1)
analyzing spatiotemporal trends from multidecadal fecal coliform
concentration observations collected by a shellfish sanitation program,
(2) identifying possible management and environmental drivers of fecal
coliform trends, and (3) assessing the feasibility of using these
monitoring data to infer long-term water quality dynamics. We focused on
North Carolina’s shellfish waters as a representative study system due
to the availability of public, digitized multidecadal data, and the
region’s rapidly growing population, wide variety of land use
characteristics along the coast, presence of the second largest
estuarine system in the contiguous USA, and growing shellfish industry.
Ultimately, this study demonstrates the application of shellfish
management data for long-term water quality trend analysis in estuaries,
informs future resource management strategies, and reveals new insights
into the functioning of coastal systems.