Present Research
My dissertation research is based in the overlap of applied community ecology and geographic information science, specifically examining the spatial and temporal patterns of forest rank abundance diagrams (RADs). From this research, I anticipate three publications:
1. An examination of the effect of sample size and reporting abundance on the identification of the community RAD model and the calculation of RAD parameter values. This manuscript, entititled The influence of sample size and reporting abundance on rank abundance distributions of eastern USA forests is currently being revised after peer review.
2. A comparison of forests prior to European settlement to present day in four regions in western New York and Pennsylvania using presettlement land survey records and Forest Inventory and Analysis (FIA) databases, respectively. Of particular importance with this study is the effect of taxonomic aggregation in the comparison of forest compositional change between the four regions. The tentative title of this paper is The effects of geographic and taxonomic aggregation in the determination of forest compositional change, circa. 1800 to present which will be submitted to Plant Ecology.
3. A model driven analysis of the spatial pattern of the forest RADs across the eastern United States using the FIA database. Environmental and community variables are used to explain the identification of the most appropriate RAD distribution as well as the values for several RAD parameters. This paper is tentively titled Unveiling the spatial pattern of forest rank abundance distributions through comparisons of environmental variables.
Future Research
Within the next several years, I see my research expanding into these areas:
Applied Use of RADs in Forest Communities of the Eastern United States
The pattern of species abundance seems to follow a near universal law; ecological communities contain few common species and many rare ones. By examining species rank abundance distributions (RADs), information about how communities order themselves and allocate resources may be obtained. Investigations into RADs either focus on the fitting of observed abundance data to theoretically proposed distributions or the comparison of RAD model parameters to environmental conditions. I anticipate further expanding on the spatial component of my dissertation by investigating how RAD models and parameters are affected by community change and forest succession as well as examining how different abundance currencies (e.g. biomass, basal area, importance values) may reveal further information about how forest communities are structured.
Ecological Analysis using Presettlement Land Survey Records
Pre-European settlement land records provide a detailed survey of North American forests circa 1800. Records contain information regarding the vegetation and features of the 19th century landscape including the location, species and diameter of witness trees used to mark the bearing posting for the survey. With an increase of these records being used for environmental and climate change modeling, the error, both statistical and taxonomic, associated with using these records needs to be investigated. I will be quantifying such error through a series of systematic analyses, the results of which will allow for a more informed use of the data particularly when combining studies from different researchers. I will also continue to investigate the pattern of RAD models in presettlement forests, particularly with regards to taxonomic aggregation and physiographic differentiation.
Spatial Pattern and Clustering of Health Data
Public health data has an inherently spatial component and, by analyzing it, it is possible to detect and quantify patterns of occurrence as well as associated risk. Linked to this are the spatial patterns of a region's sociodemographic structure, occupational and lifestyle patterns and environmental exposure that can contribute to the geography of a particular disease. My colleagues and I have begun to investigate two important health concerns, suicide and HIV/AIDS, within such a framework. Through our research, we hope to better inform public health professionals in how to direct and target potential prevention programs as well as provide them with refined tools and methodologies for identifying disease hot spots.
