Anthropogenic impacts, such as habitat destruction and spread of exotic species,
are contributing to the sixth major extinction event in Earth’s history. To develop
effective management and conservation plans, it is important to understand the ecological
drivers of at-risk populations, assess the ability of a population to adapt to environmental
change, and develop research methods for long-term ecosystem monitoring. I used
wading birds nesting in the Florida Everglades, USA as a model system to address the
challenges of managing and monitoring populations within an ecosystem greatly
impacted by anthropogenic activities. Specifically, my project investigated 1) the prey
selection of wading bird species, and the role of prey and foraging habitat availability on
annual nesting numbers, 2) the ability of using diet change to predict species adaptability
to a rapidly changing environment, and 3) the use of sensory data to provide low-cost,
long-term monitoring of dynamic wetlands. I found that tricolored herons, snowy egrets, and little blue herons consumed marsh fish larger than those generally available across
the landscape. Additionally, number of nests initiated by tricolored herons, snowy egrets,
and little blue herons was strongly correlated with the annual densities of large fish
available within the Everglades landscape. Conversely, number of nests initiated by
wood storks, great egrets, and white ibises was more correlated with the amount of
foraging habitat availability across the nesting season. Wood stork diets changed
considerably since the 1960’s, consisting of mainly sunfish and exotic fish as opposed to
marsh fishes dominant in historical diet studies. Storks also consumed more exotic fish
species than they did historically. This diet plasticity and the species’ ability to exploit
anthropogenic habitats may be conducive to maintaining population viability as storks
experience widespread human-induced changes to their habitat. Sensory-only data
models generated complementary results to models that used site-specific field data.
Additionally, sensory-only models were able to detect different responses between size
classes of fish to the processes that increase their concentrations in drying pools.
However, the degree to which sensory variables were able to fit species data was
dependent upon the ability of sensors to measure species-specific population drivers and
the scale at which sensors can measure environmental change. / Includes bibliography. / Dissertation (Ph.D.)--Florida Atlantic University, 2016. / FAU Electronic Theses and Dissertations Collection
| Identifer | oai:union.ndltd.org:fau.edu/oai:fau.digital.flvc.org:fau_33692 |
| Contributors | Klassen, Jessica A. (author), Gawlik, Dale E. (Thesis advisor), Florida Atlantic University (Degree grantor), Charles E. Schmidt College of Science, Department of Biological Sciences |
| Publisher | Florida Atlantic University |
| Source Sets | Florida Atlantic University |
| Language | English |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation, Text |
| Format | 133 p., application/pdf |
| Rights | Copyright © is held by the author, with permission granted to Florida Atlantic University to digitize, archive and distribute this item for non-profit research and educational purposes. Any reuse of this item in excess of fair use or other copyright exemptions requires permission of the copyright holder., http://rightsstatements.org/vocab/InC/1.0/ |
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