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Figure 1.1: Location of FIU sampling sites in Biscayne Bay.
Figure 1.2: DERM sampling sites in Biscayne Bay and its watershed
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National Park Service data includes daily and monthly averages based on 15 min
samplings of temperature, conductivity, salinity and depth, from 47 sampling sites (Fig
1.3). Monitoring began in 2004 and it is still active.
Figure 1.3: Location of BNP sampling stations in Biscayne Bay.
The USGS data set contains groundwater, rain and well data. NOAA data sets
include rain and salinity measured along about-monthly cruises of BB. NADP data set
contain chemical Ca, Mg, K, Ca, NH4, NO3, Cl, SO4, pH, conductivity and precipitation.
Besides nutrients and physical chemical properties of surface waters in the bay
and its immediate watershed, we collected data for metals, pesticides, herbicides, and
organic and inorganic pollutants in waters and sediments to identify areas most
impacted by these contaminants. Among the studies, usually short-term and lasting
less than 4 years and/or covering restricted areas, we could mention those of Brand
(1986), Cantillo and Lauenstein (2004), Corcoran (1984, 1984b), McKinley (1995) and
Carnahan (2005, 2008).
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QUALITY ASSESSMENT / QUALITY CONTROL
Water quality data was subjected to detailed QA/QC procedures. The initial steps
are summarized in Figure 1.4. In general it involved corrections for negative values,
flagging values below detection limit (BDL), detection of data gaps and potential
outliers, and correction of miscellaneous typographical errors and formatting. Detection
limits (DL) posed a special complication because of their variability along the period of
record (POR) and/or lack of reporting levels. When DLs were available, values below
detection limit (BDL) were flagged for further statistical analysis with applicable methods
(Helsel 2005). Special care was taken on suspected statistical outliers, because
ecological data may contain extremely high (i.e. CHLa data) or extremely low (i.e.
salinity) values which are in fact valid system responses, so their deletion or substitution
would impair a correct analysis. Outlier identification in data sets was part of the data
screening process done routinely before further statistical analysis. The simplest case
was the identification of univariate outliers in symmetric distributions where extreme
data values to the right or left are the obvious outlier candidates. Generally in our case,
most potential outliers to the left are bundled together in the non-detects and are
incorporated as such in the statistical treatment. In skewed distribution, as in most
ecological data sets, the suspect outliers are likely to be the extremes of the longer tail
(extreme high).
Figure 1.4: Summary of QA/QC procedures and summary statistics calculation for WQ data
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Criteria for assessing if a value is an outlier are complicated (Burke 2009;
Montgomery 2001) because ecological data do not necessarily follow a specific type of
statistical distribution. We applied the golden rule of ―no value should be removed from
a data set on statistical grounds alone‖. First, we used box-plots as non-parametric tool
to display data without making any assumptions of the underlying statistical distribution
to isolated potential outliers. The box and- whisker plot is a powerful statistic as it shows
the median, range, the data distribution as well as serving as a graphical, nonparametric
ANOVA. The center horizontal line of the box is the median of the data, the top and
bottom of the box are the 25th and 75th percentiles (quartiles), and the ends of the
whiskers are the 5th and 95th percentiles. The notch in the box is the 95% confidence
interval of the median. When notches between boxes do not overlap, the medians are
considered significantly different.
Each suspected outlier was analyzed individually to assess its validity when the
overall time-series was displayed together with its corresponding z-scored running-sum
(Zcusum) plots. If the value belonged to a dataset where extreme values are expected,
like in CHLa or salinity, we verified if the occurrence(s) responded to seasonality or to
extreme events of canal flows or storm events. If so, the value was not considered an
outlier favoring knowledge-based criteria over purely statistical considerations. If the
value was a unique (way above/below any other value) and isolated occurrence, not
appearing periodically and/or was not accompanied by high values before and/or after
its occurrence, it was flagged as outlier and was discarded before calculation of
summary statistics. This approach, although time-consuming and perhaps tedious,
renders the best results. Major complications arise when analyzing metal and pollutant
concentrations. These data are usually the result of eventual sampling responding to
specific needs, hence, data is scattered in space and time, values show extreme
spread, and a direct connection with other data sets is rarely possible. Finally, after
QA/QC procedures were completed, data were consolidated in a Master Database as
described in Appendix 3.
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SECTION 2:
PARK DESCRIPTION
Most of Biscayne National Park is within BB, a shallow subtropical estuary
located along the southeast coast of the Florida Peninsula (Fig 2.1). This coastal lagoon
extends 56 km from north to south and up to 13 km wide, for a total marine ecosystem
of about 701 square km, and a watershed spanning 2,434 square kilometer, most of it
draining urban and agricultural lands. The bay is bordered on the east by barrier islands
separating it from the Atlantic Ocean, and is rimmed on the west by the City of Miami.
Most of BB is shallower than three meters (Wang et al. 2003; Harlem et al. 2009) and
deeper waters are only found in the North Central portion of the bay and in eastern Card
Sound.
Biscayne Bay has been traditionally divided for purposes of discussion and
analysis intro three general areas differing in geographical and hydrodynamic
characteristics: north (from Dumfoundling Bay south to the Rickenbacker Causeway),
central (extending from the Rickenbacker Causeway south to Black Point), and south
BB (from Black Point south to Barnes Sound) (Wang and van de Kreeke, 1994;
Corcoran et al., 1984; SFWMD 1995; Bellmund et al. 2009). Our modeling work focus
on Central and South BB and the inland watershed to the west, including urban,
industrial and agricultural areas as integral part of the analysis. The southern limit of
North-central BB is marked by the shallow waters on the Featherbed Banks. This
portion of the bay is significantly affected by urban development in the communities of
Coral Gables and Coconut Grove and canal inputs on the west and Virginia Key and
Key Biscayne on the east, and experiences the most active ocean exchange of the
overall bay through the ―Safety Valve‖ (Fig 2.1). On the west margin of South-central BB
urban development is less dense and a fringe of wetlands rims the shoreline. While
direct ocean exchange is limited in South-Central BB, large volumes of freshwater are
contributed from canals, especially from Black, Princeton, Military and Mowry canals
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(Fig 2.1). Finally, Card Sound, Barnes Sound and Manatee Bay make South BB. These
water bodies are somewhat separated from the rest of the bay by extensive shallow
banks and have restricted oceanic exchange. Their watersheds are mostly located
within Everglades wetlands with little urban development.