Location: Agroecosystems Management Research
Title: Soil health assessment of organic production systems: A Cynthia Cambardella legacyAuthor
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NUNES, MARCIO - Orise Fellow |
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KARLEN, DOUGLASS - Retired ARS Employee |
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DELATE, KATHLEEN - Iowa State University |
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Logsdon, Sally |
Submitted to: ASA-CSSA-SSSA Annual Meeting Abstracts
Publication Type: Abstract Only Publication Acceptance Date: 11/10/2021 Publication Date: 11/10/2021 Citation: Nunes, M.R., Karlen, D.L., Delate, K., Logsdon, S.D. 2021. Soil health assessment of organic production systems: A Cynthia Cambardella legacy [abstract]. ASA-CSSA-SSSA Annual Meeting. Paper no. 137271. Interpretive Summary: Technical Abstract: Conversion of conventional farming practices to organic cropping systems (OCS) has been suggested as one way to improve soil health but quantifying those effects has always been difficult due to interactions between inherent and dynamic soil properties and processes. Inherent indicators reflect basic soil forming factors – climate, topography, parent material, vegetation, and time, while dynamic indicators reflect current and past soil management effects. Dr. Cambardella (Cindy) was an internationally recognized leader for soil health assessment, especially for organic farming systems. In recognition of Cindy’s contributions, we will briefly review a landscape scale study she conducted using the Soil Management Assessment Framework (SMAF) on deep loess soils in western Iowa, and one of the nation’s first organic production studies where crop productivity and water quality were quantified. We conclude by briefly reviewing Cindy’s soil health legacy project which is providing the foundation for a second-generation assessment tool defined as SHAPE (Soil Health Assessment Protocol and Evaluation). SHAPE was developed using 14,680 soil organic C (SOC) observations from across the United States that were then coupled with edaphic and climate factors at the continental scale. SOC interpretation data were compiled from multiple sources and used to improve scoring curves compared to those in the SMAF. The new interpretation curves use Bayesian model estimates in a conditional cumulative distribution function (CDF) to create soil peer groups based on soil texture, suborder class (morphology), mean annual temperature (MAT) and mean annual precipitation (MAP). In tribute to Cindy, who was always striving for better and more precise methods to evaluate soil health, we have used SHAPE to quantify long-term effects of selected OCS in Iowa. |