Lacustrine ecology

Wetlandscape topography creates spatial variation in hydroperiod, which in turn creates spatial variation in biotic communities. Such spatiotemporal variation occurs on a large scale in some of the most productive wetlands in the world, including those of south Florida, U.S.A. Wading birds (Pelicaniformes and Ciconiiformes) are iconic, top-level consumers of such ecosystems. Infrequent drying is necessary to maintain the primary nest substrate (Salix caroliniana), and prey availability is regulated by production of prey biomass in the wet season and the subsequent concentration of prey biomass into shallow pools during the dry season. The goal of this dissertation was to explicitly model wading bird nest abundance and survival as functions of water-level fluctuations, which were spatially nested (i.e., the effects of water-level fluctuations that occurred over a large scale were measured separately from the effects of water-level fluctuations that occurred over a small scale). In Chapter 2, I modeled colony-specific effects of wetlandscape water level fluctuations on wading bird nest abundance. Modeling the response at the colony level allowed the inclusion of important parameters that cannot be measured at the wetlandscape scale. For instance, each colony had its own optimal range of lake stage, which depended on local topography. I used the models to predict cumulative nest abundance under six hydrologic scenarios that were based on potential water management actions at Lake Okeechobee. I found that increasing water levels at the lake would marginally benefit the Great Egret but would substantially reduce long-term Snowy Egret and White Ibis populations. In Chapter 3, I modelled spatiotemporal distributions of fish biomass density in Lake Okeechobee’s littoral zone as a function of hierarchically nested hydrological variables. These models were consistent with the dynamic landscape connectivity model previously described in the literature. I modified the models to predict a binomial response which could then be linked to wading bird foraging threshold. The model predictions were used to estimate the number of available patch days during the breeding season, which was highly correlated with the number of nests for the great egret (Ardea alba), the snowy egret (Egretta thula), and the white ibis (Eudocimus albus). In Chapter 4, I used spatial statistics to better understand how interannual variability in resource wave patterns in the littoral zone influenced wading bird nest abundance. I found that more birds nested in years when the drying edge of the marsh moved further across the landscape. Great egret nest survival increased also, but small heron nest survival decreased. This decrease was likely because small herons continued to nest late into the season in years with longer waves, and, as with most bird species, nests that are initiated later in the season. In Chapter 5, I compiled conventional nestling diet data from 5 wading bird species sampled in 4 wetland types from 2010 to 2020 (not every wetland type was sampled in every year). This chapter provides a comprehensive, broad description of wading bird diets in south Florida, and quantifies interspecies, spatial, and interannual variation in nestling diets. By using a model-based approach to quantify the relative biomass of prey species and prey traits in nestling diets, I provide the first diet analysis that is fully reproducible across the large sympatric range of the wading bird species in the study (great egret, snowy egret, tricolored heron [Egretta tricolor], little blue heron [Egretta caerulea], and wood stork [Mycteria americana]).