Date of Graduation

7-2020

Document Type

Dissertation

Degree Name

Doctor of Philosophy in Crop, Soil & Environmental Sciences (PhD)

Degree Level

Graduate

Department

Crop, Soil & Environmental Sciences

Advisor/Mentor

Miller, David M.

Committee Member

Savin, Mary C.

Second Committee Member

Spiegel, Frederick W.

Third Committee Member

Naithani, Kusum J.

Keywords

Soil function; Microbial Community Composition; Wet-prairie sanctuary; Soil texture; Wetland health; Wetland function; Soil C models

Abstract

Soil microorganisms help maintain nutrient cycling, control carbon sequestration, impact plant productivity, and influence several soil chemical and physical properties; yet, the processes that control the microbial composition of soil and how environmental changes may affect the composition and activity of these organisms at different scales remains a difficult and intriguing puzzle for soil scientists, ecologists, and modelers. Wetlands are endangered and important ecosystems that provide several services, which are directly linked to soil function. However, few wetland assessments consider the soil environment and microbial ecology. Linking soil microbial community composition and distribution patterns to soil physio-chemical properties would provide fundamental information for the further exploration of how biogeochemical properties relate to ecosystem function, and pave the way towards developing new wetland success indicators. By using spatial ecology concepts along with soil metabarcoding, this research provides insight into the fungal and bacterial community composition and their relationship to the soil environment within a mounded wet prairie in southern United States. Generalized dissimilarity modeling (GDM), a form of nonlinear matrix regression, and amplicon metabarcoding was applied to simultaneously quantify the relative effects of geographic distance, elevation, and soil properties driving microbial community composition. The wet prairie surveyed in this research contained high spatial heterogeneity of soil chemical and physical properties, as well as distinct microtopography, which influenced the composition and diversity of soil microbial communities. The GDMs explained 28.3 and 41.5% of the total variation in bacterial and fungal beta diversity, respectively. Soil texture was an important and unexpected driver of both fungal and bacterial composition and diversity within the study site. Bacterial alpha diversity increased and fungal alpha diversity decreased with increasing sand content within the site. Sand content was also greatest on mounds in the site. Future wetland restoration studies should consider the influence of spatial heterogeneity of soil texture and micro-topography on microbial diversity, as it may affect the success of future restoration efforts. Understanding how soil microbial ecology connects to the soil environment at an ecosystem level can help inform future restoration practices, and can also be used to improve our predictive capabilities on a global scale for ecosystem services like carbon sequestration. The future applications of soil metagenomic data to infer ecosystem function and predict responses to a changing world are promising, but there are still many hurtles to overcome. While sequence databases are continuously growing, many metagenomic sequences still can’t be aligned or assigned to a functional pathway. Thus, our ability to use metagenomic data for ecological models or to predict soil microbial response to climate change is dependent on continued efforts to characterize microbes and their associated environments.

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