Species

Salt marshes are highly dynamic ecosystems that rely on multiple environmental and physical drivers that determine species distribution and soil property distribution. However, climate change and human interference are threatening the delicate ecosystem. One of the easiest ways to monitor marsh dynamics is through remote sensing. Traditional methods may not handle the large, non-parametric datasets well and often do not spatially determine areas of uncertainty. This dissertation research developed a framework to map marsh species and predict ground soil properties using multiple remote sensing data sources by integrating modern Object-based Image Analysis (OBIA), machine learning, data fusion, and band indices techniques. It also sought to determine areas of uncertainty in the final outputs and differences between different spectral resolutions. Five machine learning classifiers were examined including Support Vector Machine (SVM) and Random Forest (RF) to map marsh species. Overall results illustrated that RF and SVM typically performed best, especially when using hyperspectral data combined with DEM information. Seven regressors were assessed to map three different soil properties. Again, RF and SVM performed the best no matter the dataset used, or soil property mapped. Soil salinity had r as high as 0.93, soil moisture had r as high as 0.91, and soil organic an r as high as 0.74 when using hyperspectral data.

The relationship between water-level fluctuations and wading bird nest numbers and nesting location is well documented, yet species-specific reproductive responses of wading birds to environmental drivers and nesting habitat type is poorly understood. Here, I compared the reproductive responses of two ecologically similar species, Snowy Egret and Tricolored Heron, to foraging conditions influenced by water management and examined the effect of nestling island type on the reproductive success of three wading bird species. Reproductive responses to foraging conditions were broadly similar between Snowy Egrets and Tricolored Herons, however this study revealed specific-specific differences that could lead to different population dynamics in response to management over the long-term. I also found that these two species had lower productivity at spoil islands than marsh colonies, whereas Great Egret productivity did not vary by colony type. This study demonstrates the importance of establishing species-species relationships between productivity and environmental conditions