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experiments of seagrass meadows suggest that upon enrichment, Halodule wrightii
replaces Thalassia testudinum (Fourqurean et al 1995), and total epiphyte and epiphyte
chlorophyll loads were significantly, but weakly, correlated with phosphorus availability
(Frankovich and Fourqurean 1997). Likewise, the responses of benthic communities to
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N and P enrichment in the coral reefs of the Florida Keys vary appreciably between
nearshore and offshore habitats, and responses were species-specific. Nutrient addition
at nearshore sites increased the relative abundance of macroalgae, epiphytes, and
sediment microalgae.
Ferdie and Fourqurean (2004) and Fourqurean (2008) used in situ nutrient
enrichment experiments in seagrass beds in the Florida Keys and Florida Bay. Results
from their analysis of N and P concentration in T. testudinum leaves lead them to
suggest a preliminary relationship between nutrient enrichment and a drift of the N:P
ratio towards a value of 30 (similar to a Redfield Ratio). Meeder and Boyer (2001)
studied areas within and adjacent to Biscayne National Park and documented a strong
correlation between elevated NH4
+
concentrations with a decrease in Thalassia, an
increase in Halodule and fast growing algae, and an increase in filamentous algae cover
near Black Creek.
Given the uncertainties and lack of conclusive dose experiments, we focused our
approach on water quality monitoring datasets for two causative (phosphorus and
nitrogen) and one response (chlorophyll a) variables. This selection finds support on
abundant literature worldwide documenting nutrient influx as the primary cause of algal
blooms (Sparrow et al. 2007), by either natural events such as river plumes, storms and
upwelling (Fujita et al. 1989, Longhurst 1993, Grimes and Kingsford 1996, Oke and
Middleton 2001, Fitzwater et al. 2003, Moisander et al. 2003, Wieters et al. 2003, Yin
2003, Carstensen et al. 2004, Hodgkiss and Lu 2004, Yin et al. 2004, Beman et al.
2005, Furnas et al. 2005), or urban runoff and sewage (Smith et al. 1981, Hodgkiss and
Lu 2004, Lapointe et al. 2004, Carruthers et al. 2005; Sparrow et al. 2007)
The relationship between nutrients and phytoplankton biomass (i.e. CHLa) in
South Florida waters has been widely reported (Brand 1986; Fourqurean et al 1993;
Rudnick et al. 1999, 2006, 2007; Boyer and Briceño 2007; Briceño and Boyer 2008,
2010; Boyer et al. 2009), so CHLa seems to be a reasonable proxy to assess nutrient
enrichment. The selection of these parameters finds support on a preliminary
assessment of FIU’s dataset indicating a positive correlation between both nutrients and
CHLa, especially TP, the recognized main limiting nutrient region-wide (Brand 1988;
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Brand et al 1991; Boyer et al 1999; Fourqurean et al 1993; Szmant and Forrester 1996;
Fourqurean and Robblee 1999; Hoyer et al 2002; Boyer 2006; Boyer et al. 2009).
Threshold Analysis
In this report, we adopt the definition of ecological threshold of Andersen et al.
(2008) who stated …―an ecological threshold is the critical value of an environmental
driver for which small changes can produce an abrupt shift in ecosystem conditions,
where core ecosystem functions, structures and processes are essentially changed
between alternative states‖. Nutrient (TN, TP) concentration thresholds for each
segment were derived by identifying concentrations that were associated with sudden
and sustained increases (shifts) between CHLa alternative states. CHLa z-scored
cumulative sums were plotted along either TP or TN gradients, mimicking nutrient doseexperiment results. These graphs, constructed as described in Appendix 4, illustrate the
cumulative reaction of phytoplankton biomass to nutrient enrichment, highlight the main
threshold(s), and provide information to assess the potential health status of
phytoplankton communities in the water column.
Andersen et al. (2008) give an excellent description of driver:response scenarios
and the resulting regime shifts as shown in Fig 6.4. Panel (a) illustrates a regime shift
when the driver is linearly mediated to the ecosystem state response, and steps appear
only in the time series. Panel (b) shows a regime shift in ecosystem state after the driver
exceeds a threshold. The jump appears in the time series of the response. Panel (c)
shows a hysteresis loop linking the response to the environmental driver causing shifts
between two alternative states. The Zcusum charts along the lower row precisely
display the location of the threshold in every case.
There is a wide variety of patterns in Zcusum charts for South Florida waters
reflecting the complexity of these ecosystems as shown in a transect from SCI to ocean
(OFF) waters (Fig 6.5). In SCI CHLa seems to respond positively to nutrient
enrichment, although the pattern for TN is rather complex and the first important CHLa
reaction (shift) to increasing TN values occurs well below the median TN concentration.
This complexity reflects the dynamics of SCI, strongly affected by canal inputs, sudden
changes in salinity and nutrient concentrations, and perhaps different assemblages of
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CHLa producers. For TP at SCI there is a CHLa increasing pattern (―V-shaped‖
Zcusum) and a threshold location way below the median TP concentration. Further
east, in SCM, both TN and TP seem to share the control on phytoplankton biomass
production, although the CHLa pattern is better developed for TN than for TP. Also
notice that for values just above the median TP concentration the relationship reverses
and CHLa declines. In SCO, more affected by oceanic exchange, TN and TP play
inverse roles on CHLa production with TN positively correlated and TP negatively
correlated to CHLa, and a potential threshold at relatively low TP concentration. The TP
threshold for SCI, SCM and SCO is the same, 0,004 mg/l TP. Finally, in oceanic waters
to the east and above the reef track (OFF) CHLa is positively correlated to TN and TP.
These relationships underscore both, the compartmentalization of Biscayne Bay waters
and the complexity of the exchange between relatively nutrient-rich freshwaters and
nutrient-poor oceanic waters.
Figure 6.4: Selected relations driver:response and their resulting regime shifts: (a)
smooth pressure–status relationships, (b) threshold-like state responses and (c)
bistable systems with hysteresis. Modified after Andersen et al. 2008.
Response Z-Cusum
Driver
Driver
Time
Response
Time
Response
Driver
Driver
Time
Response
Time
Response Z-Cusum
Driver
Response
Driver