The Influence of Salinity on Seagrass Growth ... - Semantic Scholar

Estuaries

Vol. 26, No. 1, p. 131–141

February 2003

The Influence of Salinity on Seagrass Growth, Survivorship, and Distribution within Biscayne Bay, Florida: Field, Experimental, and Modeling Studies DIEGO LIRMAN* and WENDELL P. CROPPER, JR. Rosenstiel School of Marine and Atmospheric Science, University of Miami, 4600 Rickenbacker Causeway, Miami, Florida 33149 ABSTRACT: We evaluate if the distribution and abundance of Thalassia testudinum, Syringodium filiforme, and Halodule wrightii within Biscayne Bay, Florida, are influenced by salinity regimes using a combination of field surveys, salinity exposure experiments, and a seagrass simulation model. Surveys conducted in June 2001 revealed that while T. testudinum is found throughout Biscayne Bay (84% of sites surveyed), S. filiforme and H. wrightii have distributions limited mainly to the Key Biscayne area. H. wrightii can also be found in areas influenced by canal discharge. The exposure of seagrasses to short-term salinity pulses (14 d, 5–45‰) within microcosms showed species-specific susceptibility to the salinity treatments. Maximum growth rates for T. testudinum were observed near oceanic salinity values (30–40‰) and lowest growth rates at extreme values (5‰ and 45‰). S. filiforme was the most susceptible seagrass species; maximum growth rates for this species were observed at 25‰ and dropped dramatically at higher and lower salinity. H. wrightii was the most tolerant, growing well at all salinity levels. Establishing the relationship between seagrass abundance and distribution and salinity is especially relevant in South Florida where freshwater deliveries into coastal bays are influenced by water management practices. The seagrass model developed by Fong and Harwell (1994) and modified here to include a shortterm salinity response function suggests that freshwater inputs and associated decreases in salinity in nearshore areas influence the distribution and growth of single species as well as modify competitive interactions so that species replacements may occur. Our simulations indicate that although growth rates of T. testudinum decrease when salinity is lowered, this species can still be a dominant component of nearshore communities as confirmed by our surveys. Only when mean salinity values are drastically lowered in a hypothetical restoration scenario is H. wrightii able to outcompete T. testudinum.

seagrass die-off have been linked to the reduction in freshwater inputs and modification of salinity fields within the coastal lagoons of South Florida as a consequence of the water management system now in place (Smith et al. 1989; Fourqurean and Robblee 1999). The present hydrology of the region is managed by over 1,500 km of canals and other structures that control freshwater deliveries into coastal habitats (Davis and Ogden 1994; Light and Dineen 1994; Harwell 1997; Browder and Ogden 1999). In response to patterns of environmental degradation, the Comprehensive Everglades Restoration Project (CERP) was proposed to restore the lost natural hydrology (CERP 2001). One of the management goals of this project is to increase freshwater inputs from upland sources to reestablish estuarine conditions along nearshore environments (Davis and Ogden 1994; Browder and Wanless 2001). Considering the potential impacts of these activities on the salinity fields of these coastal lagoons, we investigate how the abundance and distribution of seagrass species may be influenced by salinity using a combination of field surveys, salinity exposure experiments, and a seagrass simulation model.

Introduction Seagrasses are keystone components of coastal ecosystems throughout the world, where they contribute to productivity, carbon budget, and sediment stability, as well as provide essential habitat to a large number of associated organisms (e.g., Zieman 1972; Davis and Dodrill 1989; Holmquist et al. 1989; Walker et al. 2001). The importance of seagrass beds to the health of coastal ecosystems was evidenced by the recent seagrass mass mortality within Florida Bay, U.S., where both water quality and abundance of commercial fishery stocks were greatly diminished after over 4000 ha of Thalassia testudinum were lost starting in 1987 (Robblee et al. 1991; Durako 1994; Zieman et al. 1999). Although the exact causes of this demise are still being debated, several interacting factors including elevated temperature, changes in salinity, reduced dissolved oxygen, sulfide toxicity, and disease have all been proposed as causative agents (Hall et al. 1999). Many of the potential factors influencing this * Corresponding author; tele: 305/361-4168; fax: 305/3614600; e-mail: [email protected]. Q 2003 Estuarine Research Federation

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D. Lirman and W. P. Cropper, Jr.

Previous studies that documented spatial correlations between seagrass distribution and salinity have yielded the commonly accepted conclusion that Halodule wrightii has a high tolerance for low salinities and can be dominant in nearshore areas influenced by canal discharge (Montague and Ley 1993; Fong et al. 1997). T. testudinum and Syringodium filiforme can also be found near canals, but growth and productivity of these species may be reduced at sites influenced by freshwater discharge (Conover 1964; Lewis et al. 1985; Montague 1989). A limited number of experimental studies have examined the effects of salinity stress on T. testudinum, H. wrightii, and S. filiforme. McMillan and Moseley (1967) showed that while salinities of 45–60‰ can cause S. filiforme and T. testudinum to stop growing, H. wrightii can continue to grow even at 72‰. High tolerance of H. wrightii to a wide range of salinities (5–80‰) was also reported by McMahan (1968) and McMillan (1974). Within Biscayne Bay, Florida, seagrass beds composed of T. testudinum, H. wrightii, and S. filiforme cover over 70% of the bottom, providing essential habitat for numerous commercial species including tarpon, snook, bonefish, snappers, groupers, shrimp, and crabs (de Sylva 1969; Thorhaug 1976; Ault et al. 1999a,b). Past changes in seagrass abundance and distribution in Florida Bay raise concerns that future changes in salinity within Biscayne Bay may result in similar patterns of loss. We conducted field surveys within Biscayne Bay to determine whether seagrass distribution and abundance were correlated with measured gradients in salinity. A microcosm experiment was also conducted to determine the growth response of T. testudinum, H. wrightii, and S. filiforme to prolonged exposure to different salinities (14 d, 5–45‰). The results from this experiment were incorporated into the seagrass growth model developed by Fong and Harwell (1994) and Fong et al. (1997) to evaluate the sensitivity of the model to the newly obtained salinity-growth functions under different simulation scenarios. These scenarios simulate the environmental conditions commonly found within different areas of Biscayne Bay, as well as potential salinity changes resulting from the Everglades Restoration activities. Materials and Methods SALINITY FIELDS

WITHIN

BISCAYNE BAY

Salinity fields within Biscayne Bay are influenced by precipitation, freshwater inputs from land, canal, and groundwater sources, and tidal influx of oceanic water (Alleman 1995; Wang et al. In press). The spatial and temporal distribution of these influences results in marked salinity fields

Fig. 1. Map of the study area with the location of seagrass survey sites (n 5 106), salinity instruments (*NS 5 Nearshore, *EB 5 Eastern Bay), and canals draining into Biscayne Bay. The dashed lines and numbered diamonds (1–6) show the six survey strata that divided the area into three regions (Key Biscayne, Safety Valve, Central Bay) and two salinity regimes (Nearshore and Eastern Bay).

with distinct characteristics. A clear salinity gradient can be found, with lower, variable salinity occurring in the western margin of the bay due to freshwater inflow from canal discharge and runoff, and higher, more stable salinities in the eastern margin, where oceanic influences prevail (Wang et al. 1978, In press; Brook 1982; Chin Fatt and Wang 1987). SEAGRASS DISTRIBUTION The blade density of the three main seagrass species within Biscayne Bay was documented in June 2001. Sampling locations (106 random points) were determined based on a stratified random sampling design modified from methods described by Ault et al. (1999b). The sampling area was divided into six strata (3 geographical regions 3 2 salinity regions; Fig. 1). The three geographical regions, Key Biscayne, Safety Valve, and Central Bay, were sub-divided into the following two salinity regions identified based on data collected by field instruments: a Nearshore region with highly vari-

Salinity Effects on Seagrass Distribution

Fig. 2. Mean daily salinity values for 1998 (see Fig. 1 for location of instruments). Nearshore areas are influenced mainly by freshwater inputs from canal, groundwater, and overland sources, whereas oceanic influences prevail along the Eastern margin of Biscayne Bay. Data provided by Biscayne National Park. Missing salinity values were estimated by linear interpolation.

able and lower mean salinity (mean salinity in 1998 5 23.9‰, SD 5 4.8, range 5 12–34‰) and an Eastern Bay region with more constant, oceanic salinity conditions (mean salinity 5 33.1‰, SD 5 2.4, range 5 29–39‰; Fig. 2). Locations within each stratum were determined by selecting cells at random from the SEASCAPE model of Biscayne Bay that divides the bay into 170,848 square grid elements (100 3 100 m; Cropper et al. 2001). The center coordinates for the cells chosen for each stratum were determined and a differential Global Positioning System unit was used to locate the survey point. At each location, divers surveyed four haphazardly located plots (0.25 m2). Within each plot, all the aboveground seagrass biomass was collected by clipping; the number of seagrass blades was determined by species and averaged by location (n 5 4). Depth at each station was obtained with a weighted line marked with 5-cm intervals. Data collected in these surveys were interpolated with ArcView’s Spatial Analyst Extension using an Inverse Distance Weighted interpolation procedure with a cell size of 100 3 100 m. SALINITY EXPOSURE EXPERIMENTS T. testudinum, S. filiforme, and H. wrightii were collected from Key Biscayne, Florida (depth 5 1 m). Rhizome sections with at least 3 intact short shoots were used as rhizomes with 1–2 short shoots were found to experience high mortality in previous transplant studies (Tomasko et al. 1991; Lirman unpublished data). Salinity exposure experiments were conducted

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at the microcosm facility at the University of Miami’s Rosenstiel School of Marine and Atmospheric Science in April 2000. The experimental units were 120-L aquaria filled with 10 cm of sediments obtained from the seagrass collection site and housed in an outdoor greenhouse. Salinity for each treatment (n 5 2 tanks per salinity treatment) was adjusted prior to the onset of the experiment and adjusted daily as needed. The salinity treatments used were 5‰, 10‰, 15‰, 20‰, 25‰, 30‰, 35‰ (ambient), 40‰, and 45‰. A 14-d exposure period was selected to represent the longest low-salinity peaks observed adjacent to canal outflow areas (Fig. 2). The seagrass rhizomes were placed directly (i.e., without an acclimation period) into the salinity treatments to simulate the sudden drops in salinity associated with storm events or the opening of water control structures along the coast. Three rhizome sections from each species were anchored to the sediments with plastic anchors inside each aquarium. Short shoots of T. testudinum were marked for growth using the needle-punching method described by Zieman (1974) and Zieman et al. (1999). Production in H. wrightii and S. filiforme was estimated using the clipping method described by Dunton (1990, 1994). After 14 d, leaf extension rates were determined for each shoot. Linear blade growth values were averaged by shoot and rhizome for each tank. These values were averaged by treatment if no significant differences in mean growth were detected between tanks (t-tests, p . 0.05). SEAGRASS MODEL We modified an existing seagrass growth model (Fong and Harwell 1994; Fong et al. 1997) by implementing our measured short-term salinity responses while all other model structures and parameters are held constant. The salinity-response function in the original seagrass model was derived from observational studies that correlated seagrass distribution and productivity with measured field salinity patterns. To assess the effects of replacing the original, distribution-based salinity function, our new model was run under the four environmental scenarios chosen by Fong and Harwell (1994) to describe representative areas with contrasting nutrient, temperature, and light regimes (Table 1). While the original model was run using a periodic function to simulate salinity patterns, the new model was run under two contrasting salinity regimes, Nearshore and Eastern Bay, using salinity values measured in the field (Fig. 2). We ran a version that incorporates competition among the three seagrass species (interactive model) as well as a version restricted to a single seagrass spe-

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TABLE 1. Parameters from original model used in the simulation scenarios described by Fong and Harwell (1994). Salinity values used in the new model were obtained from field data collected from Nearshore and Eastern regions of Biscayne Bay (Fig. 2). Temperature (8C) Scenario

Mean

Range

1 2 3 4

26 26 26 26

19–33 17–35 24–28 19–33

PO4 Concentration (mM) Water Column

2 2 2 10

Sediment

5 11 1 5

Light (mE m22 s21) Mean

Range

Comments

650 650 650 650

300–1000 300–1000 300–1000 300–1000

Average bay conditions High input of freshwater and organic matter Oligotrophic conditions Enriched water column

cies (single-species model) to evaluate the effects of competitive interactions. Competition effects are based on a reduction of the maximum growth rate of each species as a function of total seagrass biomass of all three species. Thalassia biomass was reduced by total seagrass biomass less than the other species (Fong and Harwell 1994) leading to rapid Thalassia dominance under many conditions. The single-species model retained the biomass-dependent maximum growth reduction, but replaced the total biomass of the three seagrass species with that of only the species being simulated. Although the precise scenarios that describe future changes in freshwater delivery into Biscayne Bay have not been formulated, one such restoration scenario was simulated by decreasing salinity by 20‰ from measured Nearshore salinities. This extreme salinity-reduction scenario was chosen to represent the potential impacts of increased freshwater flows in the vicinity of canal outflow areas where the effects of the salinity changes would be most likely detected. The seagrass model was developed as a system of differential equations of the following form: dB/dt 5 maxG (f(S) 3 f(T) 3 f(L) 3 f(N)) 2 loss rate (1) where maxG is the species specific maximum daily aboveground productivity (g dry wt m22 d21), f(S) is a zero to one salinity scalar, f(T) is the temperature scalar, f(L) is the light scalar, and f(N) is the sediment nutrient scalar. We simulated the model using fourth order Runge-Kutta integration with a time step of 0.02 d. The salinity response function (f(S)) was implemented as a look-up table with linear interpolation that mapped daily salinity values to the daily salinity scalar value (0–1). Loss rate was simulated as a function of seagrass senescence and turnover. Driving functions for light and temperature were simulated in the model as periodic functions: Daily value 5 Mean 1 (R2 3 sin(3p/2 1 (2p) 3 DayNo/360)) (2) where Mean is the average annual value for the environmental variable (8C for temperature, and

mol m22 s21 of PAR for light), R2 is half of the annual range of the variable, and DayNo is the number of days from the start of the simulation. Results SEAGRASS SPATIAL DISTRIBUTION T. testudinum, the most abundant seagrass within Biscayne Bay, was present at 84% of the points surveyed (present in 89 of 106 points surveyed), while S. filiforme was present at 21% (n 5 22 points) and H. wrightii at 16%. Beds containing all three seagrass species were found at 7% of sites, beds with T. testudinum and H. wrightii at 7%, and beds with T. testudinum and S. filiforme at 12%. Beds containing S. filiforme and H. wrightii together were not found. Monospecific beds of T. testudinum were found at 57% of sites (mean depth [6 SE] 5 210 [21] cm), S. filiforme at 1% (depth 5 250 cm), and H. wrightii at 2% (mean depth 5 145 [13] cm). Only 13% of the sites surveyed had no seagrass biomass, and these sites were mainly within deeper dredged areas of the bay (mean depth 5 280 cm [SE 5 6 32]) where boat traffic is high and light penetration limited due to suspended sediments. The contours constructed based on blade density indicate that T. testudinum is found throughout Biscayne Bay, while S. filiforme and H. wrightii have more restricted distributions, being limited mainly to the Key Biscayne area (Figs. 1 and 3). H. wrightii can be found in areas heavily influenced by canal discharge such as the Black Point and Chicken Key areas, as well as a shallow bank in the middle of the Bay (Figs. 1 and 3). Maximum blade densities were 4,130 blades m22 for T. testudinum, 1,257 blades m22 for H. wrightii, and 2,539 blades m22 for S. filiforme. SALINITY EXPOSURE EXPERIMENTS Exposure of seagrasses to different salinity treatments revealed species-specific growth responses. T. testudinum exhibited peak leaf elongation rates at 40‰, decreasing gradually as salinity decreased, and having its lowest growth rates at the highest salinity, 45‰ (Fig. 4a). Maximum extension rate for a single blade was 0.31 cm d21. The highest mean blade extension rates were recorded at 40‰


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Fig. 3. Contour maps of seagrass blade densities within Biscayne Bay based on point surveys performed in June 2001 (n 5 106 sites).

(0.08 cm d21). Mean extension rates at the salinity extremes were 0.03 cm d21 at 45‰ (35% of the mean rate recorded) and 0.05 cm d21 at 5‰ (63% of the mean). S. filiforme was the species most susceptible to changes in salinity (Fig. 4b). Maximum extension rate for a single blade was 0.75 cm d21. The highest mean blade extension rates were recorded at 25‰ (0.34 cm d21) and dropped dramatically at both higher and lower salinity. Mean leaf extension rates were 0.12 cm d21 at 45‰ (35% of the mean rate recorded) and 0.08 cm d21 at 5‰ (23% of the mean). Of the three species tested, H. wrightii showed the widest tolerance to changes in salinity as growth rates did not vary widely among salinity treatments (Fig. 4c). Maximum extension rate for a single blade was 0.64 cm d21. The highest mean blade extension rates were recorded at 35‰ (0.22 cm d21) and lowest at 45‰ (0.17 cm d21) and 5‰ (0.17 cm d21). Blade extension rates did not fall bellow 76% of the maximum mean extension rates for any salinity treatment. SIMULATION RESULTS When the measured Eastern Bay salinity was used in the simulation models, highest biomass values were obtained for T. testudinum under Scenario 1, used to represent intermediate sediment nutrient concentrations, S. filiforme under Scenario 3, used to represent low-nutrient conditions, and H. wrightii under Scenario 2, used to represent high sediment nutrient conditions commonly found areas influenced by canal inputs (Table 2). Biomass differences between the models were generally low when Eastern Bay salinity values were used (rarely exceeding 10%), but the simulated biomass of T. testudinum was always lower with the

Fig. 4. Mean daily leaf extension rates (cm, 6 1 SE) of A) Thalassia testudinum, B) Syringodium filiforme, and C) Halodule wrightii exposed to different salinity treatments for 14 days.

new model, biomass of H. wrightii was higher with the new model, especially under the interactive version, and biomass of S. filiforme was unchanged except under Scenario 3 where the new model predicted lower mean annual biomass. The largest differences in the species-specific responses were simulated when Nearshore salinity values were used (Table 2). As was the case for the simulations with Eastern Bay salinity, when using Nearshore salinity, highest mean biomass values were obtained for T. testudinum under Scenario 1 (Fig. 5), S. filiforme under Scenario 3 (Fig. 6), and H. wrightii under Scenario 2 (Fig. 7). The mean annual biomass of T. testudinum simulated with the new model was consistently higher than in the original model under all the scenarios simulated for both the interactive (Fig. 5a) and single-species versions (Fig. 5b). The new model also

Max

138 138 148 147 43 40 136 138 134 138 147 147 43 41 125 137 104 107 127 130 32 32 85 89 88 106 130 130 32 32 65 89 10 10 101 104 10 16 33 37 89 10 132 106 38 11 93 42 1.2 1.3 50 56 1.6 3.2 15 17 39 1.5 99 63 14 2 51 20 10 10 10 10 262 258 10 10 10 10 10 10 251 262 10 10 4.6 4.6 4.6 4.6 214 199 4.6 4.6 4.6 4.6 4.6 4.6 143 211 4.6 4.6 10 10 10 10 242 240 10 10 10 10 10 10 228 245 10 10 4.6 4.6 4.6 4.6 218 207 4.6 4.6 4.6 4.6 4.6 4.6 138 219 4.6 4.6 362 356 150 150 150 150 336 322 339 335 150 150 150 150 201 289 310 298 96 89 26 25 157 147 141 283 42 82 15 23 56 133 357 351 150 150 150 150 330 317 320 333 150 150 150 150 150 286 308 296 97 90 27 25 157 147 139 281 43 83 15 24 52 134 EB EB EB EB EB EB EB EB NS NS NS NS NS NS NS NS 1 1 2 2 3 3 4 4 1 1 2 2 3 3 4 4

Original New Original New Original New Original New Original New Original New Original New Original New

Max Scenario

Single-Species Model

Mean Biomass Max Max

Max

Max

Mean Biomass Mean Biomass Mean Biomass Mean Biomass Mean Biomass Seagrass Model Field Salinity

Interactive Model Single-Species Model Interactive Model

Syringodium filiforme Thalassia testudinum

Single-Species Model

Halodule wrightii


Interactive Model

TABLE 2. Mean annual aboveground biomass of seagrass species found in Biscayne Bay, Florida, simulated under different scenarios. Field salinity data are from Nearshore (NS) and Eastern Bay (EB) locations. Results from both the interactive model and the single-species model are presented here. The two different salinity functions are those used in the original seagrass model (Fong and Harwell 1994) and the new function obtained from a microcosm experiment.

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Fig. 5. Aboveground biomass of Thalassia testudinum for Scenario 1 (average bay conditions) using measured Nearshore salinity values for A) new and original models, single-species version, and B) new and original models, interactive version.

led to less seasonal variability in the simulated T. testudinum biomass. S. filiforme reached high biomass only under the scenario representing oligotrophic conditions (Scenario 3; Table 2). Increases in biomass as well as a reduction in seasonal variability were seen for S. filiforme with the new model compared with the original model for both the interactive (Fig. 6a) and single-species versions (Fig. 6b). Biomass patterns differed in magnitude and variability between the original and new models for H. wrightii. In the interactive version, mean annual biomass of H. wrightii almost disappeared in Scenarios 1 and 3, and was lowered by 61% in Scenario 4 (Table 2). In the single-species version, the new model resulted in either no change (Scenario 3) or increases in biomass (20% in Scenario 1 and 37% in Scenario 4). Under Scenario 2, which represents the best growing conditions for this species under canal-influenced areas with high sediment nutrient concentrations, no differences between the models were found using the single-species version (Fig. 7a). A reduction in both the mean biomass (36% lower with the new model compared to the original) and the seasonal variability were seen when the new model was run using the interactive version (Fig. 7b). Effects of interspecific competition were ob-


Fig. 6. Aboveground biomass of Syringodium filiforme for Scenario 3 (oligotrophic conditions) using measured Nearshore salinity values for: A) new and original models, single-species version, and B) new and original models, interactive version.

served only for H. wrightii. The biomass of H. wrightii was higher in all scenarios in the singlespecies compared to the interactive version of both models (Table 2). Using the new model, mean annual biomass from the H. wrightii-only model was twice as high and less variable than H. wrightii biomass from the interactive version (Fig. 7). The simulations also indicated that H. wrightii was being suppressed by T. testudinum. With the new model, T. testudinum biomass was higher than H. wrightii biomass, as opposed to H. wrightii dominance in the original model under Scenario 2 (Table 2). When Nearshore salinity values were lowered by 20‰ year-round to simulate the potential impacts of the Everglades restoration project on freshwater deliveries to coastal bays of South Florida, biomass patterns of H. wrightii and T. testudinum were altered. When the interactive version of the new model was run under Scenario 2 to simulate Nearshore conditions, mean annual biomass of T. testudinum (83 g m22) exceeded that of H. wrightii (63 g m22; Fig. 8a). This pattern was reversed when salinity values were lowered by 20‰. In this simulated restoration scenario, the biomass of H. wrightii (95 g m22) was more than double that of T. testudinum (45 g m22; Fig. 8b).

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Fig. 7. Aboveground biomass of Halodule wrightii for Scenario 2 (high input of freshwater and organic matter) using measured Nearshore salinity values for: A) new and original models, single-species version, and B) new and original models, interactive version.

Discussion The commonly accepted paradigm of seagrass succession and resource competition indicates that T. testudinum, the recognized competitive-dominant species, will monopolize available space and persist under low nutrient conditions when temperature and salinity exhibit restricted variability (Zieman 1976, 1982; Williams 1987, 1990; Gallegos et al. 1994). S. filiforme is a dominant component of seagrass beds only in deeper areas with direct oceanic influences (Zieman et al. 1989; Hall et al. 1999) and possibly higher phosphorus availability (Fourqurean et al. 2002). H. wrightii is often considered an early successional, pioneer species able to monopolize space only after other species have been removed by disturbance and remain dominant under high-nutrient conditions or fluctuating environments (Montague and Ley 1993; Fourqurean et al. 1995). The spatial distribution of seagrasses documented within Biscayne Bay was generally consistent with this paradigm and agreed with the distribution patterns documented within the neighboring Florida Bay, where T. testudinum has a wide distribution, S. filiforme dominates in deeper areas, and H. wrightii is abundant only in

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Fig. 8. Aboveground biomass of Halodule wrightii and Thalassia testudinum for Scenario 2 (high input of freshwater and organic matter) using A) Nearshore salinity values and B) salinity values from a Restoration Scenario (Nearshore salinity reduced by 20‰) simulated with the new model and the interactive version.

areas with high nutrients and fluctuating salinity (Zieman et al. 1999; Fourqurean et al. 2002). Both nutrient availability and salinity may play a role in explaining the distribution of S. filiforme and H. wrightii in the Key Biscayne and canal discharge areas. Although nutrient concentrations were not recorded in this study, historical data (1979–1992) show elevated phosphorus and nitrogen levels in water samples from northern Biscayne Bay and adjacent to canal discharge sites (Alleman 1995). The spatial correlation of this nutrient pattern and seagrass distribution agree with studies that have shown that S. filiforme and H. wrightii can coexist or even outcompete T. testudinum under elevated nutrient conditions (Williams 1987; Fourqurean et al. 1995). The distribution of S. filiforme highlights a limitation of the model which, in its present form, simulates high biomass of this species only under oligotrophic conditions. Low and variable salinity can delineate localized nearshore habitats where dense H. wrightii populations can persist over time even when surrounding areas are dominated by T. testudinum. These

salinity patterns would preclude the establishment of S. filiforme based on its documented low tolerance of this species to extreme low salinity, even when the new model predicted a high biomass for S. filiforme for these areas (Scenario 3, Nearshore salinity). In this case, although salinity was lower at the Nearshore location, it never reached the extreme levels required to remove S. filiforme based on its salinity tolerance. Data from other locations as well as a hydrodynamics model of Biscayne Bay have shown that salinity can indeed reach values below 10‰ near canal outflow areas (Brand 2002; Wang et al. In press). The documented salinity responses of T. testudinum, S. filiforme, and H. wrightii were consistent with those reported in previous studies (McMillan and Moseley 1967; McMahan 1968; McMillan 1974). Just as in these studies, H. wrightii showed the widest salinity tolerance while S. filiforme was the most susceptible to sudden changes in salinity, and T. testudinum showed decreased growth only at extreme values. While microcosm studies may not be fully representative of natural conditions, the leaf extension rates calculated for H. wrightii and S. filiforme during the salinity exposure experiment were within the lower range of values obtained by previous studies in the field (0.1–0.9 cm d21; Short et al. 1985; Williams 1987; Dunton 1990). And while mean leaf elongation rates of T. testudinum were lower within the experimental units compared to field measurements (0.2–0.4 cm d21; Zieman 1975), maximum elongation rates (0.3 cm d21) were within the observed range. The lower levels recorded may be a response of the timing of this study (April) before the reported summer peak in growth and standing stock in Biscayne Bay (Zieman 1975) as well as the use of rhizome fragments. The use of short rhizome segments, the lack of an acclimation period prior to exposure, and the prolonged exposure period used (14 d), simulate rather extreme conditions that may also over-emphasize the effects of salinity changes on seagrass growth. Sudden and prolonged drops in salinity are common features of the salinity regime near canal outflow areas in coastal bays, and the response of seagrasses to these fluctuating conditions does need to be characterized. When the outcome of the original model (Fong and Harwell 1994; Fong et al. 1997) and that of the new version of the model were compared, only minor differences in annual biomass were obtained for the three seagrass species under the stable salinity regime found along the Eastern Bay. This indicates that when mean salinity is high and seasonal variability is limited, a salinity function derived from correlational studies of seagrass distribution is adequate to simulate seagrass biomass.


Caution should be exercised when using functions based on geographical distributions to model growth and competition under rapidly fluctuating environments. As is the case along the canal-influenced environment of Biscayne Bay, a salinity response determined experimentally provides a better representation of short-term seagrass growth and competition dynamics. Using a similar modeling approach, short-term salinity response functions were used by Wortmann et al. (1997) to determine the potential effects of floods and dry conditions on the growth and survivorship of Zostera capensis in South Africa. An example where the new model provides a better description of the documented seagrass distribution patterns is that of T. testudinum in nearshore environments. In this case, the simulated mean annual biomass is 60% to 100% higher with the new model, which agrees with the density and biomass observed for T. testudinum in the nearshore environments of Biscayne Bay (Zieman 1975; Irlandi et al. 2001). The higher simulated output is due to the reduced susceptibility of T. testudinum observed in the exposure experiment compared to the previously used salinity function based on geographical distributions (Fong and Harwell 1994). This shows that although growth rates of T. testudinum decrease when salinity is lowered, this species can still be a dominant component of nearshore communities. Our simulations also highlight how competitive interactions can determine seagrass community composition in variable environments. Whereas the biomass of the competitive dominant T. testudinum shows little difference between the interactive and single-species versions of the model, the growth dynamics of H. wrightii are greatly affected by competitive interactions. Although the competitive dominance of T. testudinum has been documented in studies of seagrass succession (Williams 1987, 1990), a change in environmental conditions can shift this dominance and allow other species to thrive. When salinity values were drastically lowered in our hypothetical restoration scenario, H. wrightii was able to outcompete T. testudinum, which is adversely affected by the lower salinities to a greater extent. Replacement of T. testudinum by H. wrightii was also observed under nutrient enriched conditions (Fourqurean et al. 1995). Mean salinity values as well as salinity fluctuations can play a role in the abundance and distribution of seagrass species in Biscayne Bay. Even if localized distribution patterns such as the high abundance of H. wrightii in canal-influenced areas may be explained on the basis of salinity regimes, salinity tolerances alone can not account for all of the observed large-scale patterns in seagrass distri-

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bution. The restricted distribution of S. filiforme and the lack of additional dense H. wrightii populations along the coastal fringe still remain unexplained by the documented or simulated environmental gradients. Data on other important factors such as sediment nutrient dynamics, light availability, seagrass recruitment and rhizome expansion, competition from seagrasses, epiphytes, and drift and rhizophytic macroalgae, are needed to fully understand and predict the large-scale distribution dynamics of SAV within Biscayne Bay. Establishing the relationship between seagrass growth, abundance, and distribution and salinity patterns is especially relevant in South Florida where freshwater deliveries into coastal bays are influenced to a large extent by water management practices. The seagrass model developed by Fong and Harwell (1994) and modified here to include an experimental salinity-response function can provide an important tool within the restoration framework proposed for the Everglades landscape by providing testable hypotheses where different restoration scenarios can be tested prior to their implementation. Within this context, the simulations presented here indicate that increased freshwater inputs and associated decreases in salinity in nearshore areas can influence growth dynamics of single species as well as modify competitive interactions so that species replacements may occur. ACKNOWLEDGMENTS We would like to thank those people whose help in the field made this research possible: B. Orlando, P. Biber, L. Kaufman, T. Jones, S. Macia´, and D. Manzello. Financial support was provided by National Oceanic and Atmospheric Administration Coastal Ocean Program (#NA67RJ0149) and Environmental Protection Agency STAR Program (#R-827453-01-0). Richard Curry, Science Director of Biscayne National Park, provided field support for this project. This manuscript was improved by the helpful suggestions provided by P. Fong, T. Chesnes, and an anonymous reviewer.

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