Wetland ecology.

In tropical wetlands, breeding wading birds rely on concentrations of aquatic
fauna during the dry season to meet increased energetic demands. Wetland
microtopography increases aquatic fauna concentration levels. Crocodilians modify the
landscape creating deep-water refugia but their role as a mechanism for aquatic fauna
concentration is unknown. I sampled alligator (Alligator mississippiensis) abundance and
slough microtopography to examine correlation between the two measures. Despite
increased microtopography in high alligator use sloughs, the differences were not
significant. Using an in situ experimental approach, I quantified the magnitude, timing,
and spatial extent of aquatic fauna concentrations within simulated alligator depressions
and the surrounding marsh. Aquatic fauna density and biomass were greater within
simulated depressions, thus enhancing wading bird foraging habitat. Further
understanding the mechanisms creating microtopography, thus enhancing wading bird habitat, is critical to facilitate restoration and prevent declines of wading bird populations
in seasonally pulsed wetlands worldwide.

Wetlands are some of the most diverse and productive ecosystems on earth. Water-level fluctuations determine the ecological function of shallow lakes and wetlands. Currently, anthropogenic modification to water-level fluctuations is the leading source of ecological degradation in lake and wetland ecosystems worldwide. I used wading birds nesting in Lake Okeechobee, as a model system to address the challenges of environmental restoration within an ecosystem greatly impacted by anthropogenic activities. Specifically, I 1) identified environmental factors most important for predicting the number of wading bird nests, 2) tested the assumptions of both the match-mismatch and the threshold hypothesis by modeling the relationship between nesting success and prey density with foraging habitat availability, and 3) measured the stress response of Great (Ardea alba) and Snowy Egrets (Egretta thula) to hydrologically-mediated changes in food availability. Collectively, the results suggest that the number of nests was greatest when area of nesting substrate was high and water-levels were moderate (3.9 - 4.4 m). Nest numbers dropped when either nesting substrate or foraging habitat was limited. My investigation into the predictions of the match-mismatch and threshold hypotheses found that indeed, prey density can reduce or intensify the effects of a mismatch event. The interaction of prey density and foraging habitat availability was significant and positive in both models. Saturation thresholds existed for both fledging success (147 prey (m^2)^-1) and total productivity (189 prey (m^2)^-1), above which high concentrations of prey could sustain nesting when foraging habitat availability was low. Finally, my studies of the stress response support the hypothesis that hydrologic factors associated with prey availability play an important role in regulating nesting patterns, although the level of food limitation the birds experience at the lake was not as severe as expected. Model selection identified foraging habitat availability as most influential to the nestling Great Egret stress response, whereas foraging habitat availability and prey density both influenced nestling Snowy Egret stress response. Moreover, the Snowy Egret stress response was more sensitive to changes in prey availability than was the Great Egret stress response. Temperature and foraging conditions influenced yolk corticosterone concentrations for both egret species.

Seagrass is a key stone component for the Indian River Lagoon (IRL) ecosystem,
and therefore it is an important topic for many studies in the lagoon. This study focuses
on the effects of seagrass beds on the hydrodynamics in the IRL. A hydrodynamic model
based on the Delft3D modeling system has been developed for the southern IRL
including the St. Lucie estuary, Ft. Pierce and St. Lucie Inlets, and adjacent coastal
waters. The model is driven by freshwater inputs from the watershed, tides,
meteorological forcing, and oceanic boundary forcing. The model has been systematically calibrated through a series of numerical
experiments for key parameters, particularly the bottom roughness, and configuration
including heat flux formulation and bottom bathymetry. The model skills were evaluated
with quantitative metrics (point-to-point correlation, root-mean-square difference, and
mean bias) to gauge the agreements between model and data for key variables including temperature, salinity, and currents. A three-year (2013-2015) simulation has been
performed, and the results have been validated with available data including observations
at HBOI Land-Ocean Biogeochemistry Observatory (LOBO) stations and in situ
measurements from various sources. The validated model is then used to investigate the
effects of 1) model vertical resolution (total number of model vertical layers), 2) spatial
variability of surface winds, and 3) seagrass beds on the simulated hydrodynamics. The
study focuses on the vicinity of Ft. Pierce Inlet, where significant seagrass coverage can
be found. A series of numerical experiments were performed with a combination of
different configurations. Overall, the experiment with 2-dimensional (2-D) winds, ten
vertical layers and incorporating seagrass provided the most satisfactory outcomes.
Overall, both vertical resolution and spatial variability of surface winds affect
significantly the model results. In particular, increasing vertical resolution improves
model prediction of temperature, salinity and currents. Similarly, the model with 2-D
winds yields more realistic results than the model forced by 0-D winds.
The seagrass beds have significant effects on the model results, particularly the
tidal and sub-tidal currents. In general, model results show that both tidal and sub-tidal
currents are much weaker due to increase bottom friction from seagrass. For tidal
currents, the strongest impacts lie in the main channel (inter-coastal waterway) and
western part of the lagoon, where strong tidal currents can be found. Inclusion of seagrass
in the model also improves the simulation of sub-tidal currents. Seagrass beds also affect
model temperature and salinity including strengthening vertical stratification. In general,
seagrass effects vary over time, particularly tidal cycle with stronger effects seen in flood
and ebb tides, and seasonal cycle with stronger effects in the summer than in winter.