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Soil Resource Data Bank (SoilDB) Florida
Research Team
PI:
Sabine Grunwald, Soil and Water Science Department, University of Florida
Co-PIs:
Faculty members in the Soil and Water Science Department: Mark Clark, George O’Connor, Samira Daroub, Carl Fitz, Willie Harris, Zhenli He, George Hochmuth, Jim Jawitz, Yungcong Li, Lena Ma, Cheryl Mackowiak, Kelly Morgan, Brent Myers, Peter Nkedi-Kizza, Andy Ogram, Arnold Schumann, Amy Shober, Maria Silveira, Craig Stanley, Max Teplitski, Gurpal Toor, Chris Wilson, and Alan Wright
Programmer:
Brandon Hoover
Time: 09/2009 to current
Funding Source: Seed funding provided by the Soil and Water Science Department, University of Florida
Summary
What is Soil DB? SoilDB allows online sharing of soil resource data collected across micro-, meso- and macro spatial scales and different time periods. The data bank includes physical, chemical, biological, and taxonomic soil data from historic and current projects generated by the Soil and Water Science Department, University of Florida, which will be complemented by other soil datasets in the next phase. The geographic focus is Florida, but includes other regions in and outside U.S. Soil resource data collected in different ecosystem types including agricultural, forest, rangeland, wetlands, urban, and natural conservation areas, are included. SoilDB will be linked to a Google Earth application allowing displaying and exploring soil datasets.
Aim: The aim of SoilDB is to facilitate synthesis of various soil properties to analyze spatial or temporal trends, compare site conditions, or conduct other types of meta-analysis by fusing soil data from the data bank. Soil data can be complemented by environmental datasets to perform more complex analysis and populate mechanistic, deterministic, or stochastic models. Synthesis of data will allow to gain new insights and enhance knowledge on various topical areas including soil and water contamination and public health, carbon management and ecosystem services, wetlands and aquatic ecosystems, landscape analysis and modeling, and nutrient, pesticide & water management.
Benefits: Soil data are costly to collect and require investment in labor and time and analytical expertise to derive biogeochemical properties. Since the data bank archives soil data it protects this investment. By reusing soil data for multiple projects value is added to ongoing and future research. Sharing of data facilitates to build on previous work and synthesize knowledge. Assembling soil data in a data bank allows generating knowledge by fusion of data into larger sets that encompass more observations, more biogeochemical properties, and/or extend the geographic region of an analysis. New insight can be gained by reanalyzing data in various combinations and fusing with ancillary environmental datasets. Sharing of data in form of a data bank stimulates collaboration among researchers, reduces investment to launch new projects, and stimulates new research ideas and projects through pooling of data.
Fig. 1. Architecture of Soil Resource Data Bank and geospatial outreach.
Results (in progress)
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