Document Type
Dissertation
Degree
Doctor of Philosophy (PhD)
Major/Program
Biology
First Advisor's Name
DeEtta Mills
First Advisor's Committee Title
Committee Chair
Second Advisor's Name
Eric Von Wettberg
Second Advisor's Committee Title
Committee Member
Third Advisor's Name
Jeffrey Wells
Third Advisor's Committee Title
Committee Member
Fourth Advisor's Name
Jennifer Gebelein
Fourth Advisor's Committee Title
Committee Member
Fifth Advisor's Name
John Kominoski
Fifth Advisor's Committee Title
Committee Member
Keywords
soil provenance, microbial profiling, forensics, spatial scale, temporal variability, machine learning, functional diversity
Date of Defense
10-28-2016
Abstract
The current ecological hypothesis states that the soil type (e.g., chemical and physical properties) determines which microbes occupy a particular soil and provides the foundation for soil provenance studies. As human profiles are used to determine a match between evidence from a crime scene and a suspect, a soil microbial profile can be used to determine a match between soil found on the suspect’s shoes or clothing to the soil at a crime scene. However, for a robust tool to be applied in forensic application, an understanding of the uncertainty associated with any comparisons and the parameters that can significantly influence variability in profiles needs to be determined. This study attempted to address some of the most obvious uncertainties of soil provenance applications such as spatial variability, temporal variability, and marker selection (i.e., taxa discrimination). Pattern analysis was used to validate the ecological theories driving the soil microbial biogeography. Elucidating soil microbial communities’ spatial and temporal variability is critical to improve our understanding of the factors regulating their structure and function. Microbial profiling and bioinformatics analyses of the soil community provided a rapid method for soil provenance that can be informative, easier to perform, and more cost effective than approaches using traditional physico-chemical data. This study also showed that stable profiles may allow comparison between evidence and a possible crime scene despite the time lapse (4 years) between sample collections, however, this is dependent on the analysis method, site, vegetation, and level of disturbance. Marker selection was also an important consideration for profiling. Even though Fungi look promising for single taxon soil discrimination, the additional markers can help discriminate between a wide variety of soil types. As in human identification, the more DNA markers queried the greater the discrimination power. Lastly, this study illustrated a novel method to query the iron relating genes and ability to design a novel marker that can easily be used to profile the functional diversity of a soil community to enhance soil classification. Overall this research demonstrated the potential and effectiveness of using microbial DNA from soil, not just for comparison, but also for intelligence gathering to pinpoint the geographic origin of the soil.
Identifier
FIDC001216
Recommended Citation
Damaso, Natalie, "Biogeographical Patterns of Soil Microbial Communities: Ecological, Structural, and Functional Diversity and their Application to Soil Provenance" (2016). FIU Electronic Theses and Dissertations. 3006.
https://digitalcommons.fiu.edu/etd/3006
Included in
Biodiversity Commons, Bioinformatics Commons, Biology Commons, Environmental Microbiology and Microbial Ecology Commons, Multivariate Analysis Commons, Soil Science Commons
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