Continuum of Risk Analysis Methods to Assess Tillage System Sustainability at the Experimental Plot Level

Eihab M Fathelrahman,Lori J Wiles,Philip Heilman,Ramesh S Kanwar,Dana L Hoag,Robert W Malone,James C Ascough Ii

doi:10.3390/su3071035

Abstract

This study applied a broad continuum of risk analysis methods including mean-variance and coefficient of variation (CV) statistical criteria, second-degree stochastic dominance (SSD), stochastic dominance with respect to a function (SDRF), and stochastic efficiency with respect to a function (SERF) for comparing income-risk efficiency sustainability of conventional and reduced tillage systems. Fourteen years (1990–2003) of economic budget data derived from 35 treatments on 36 experimental plots under corn (Zea mays L.) and soybean (Glycine max L.) at the Iowa State University Northeast Research Station near Nashua, IA, USA were used. In addition to the other analyses, a visually-based Stoplight or “probability of target value” procedure was employed for displaying gross margin and net return probability distribution information. Mean-variance and CV analysis of the economic measures alone provided somewhat contradictive and inconclusive sustainability rankings, i.e., corn/soybean gross margin and net return showed that different tillage system alternatives were the highest ranked depending on the criterion and type of crop. Stochastic dominance analysis results were similar for SSD and SDRF in that both the conventional and reduced tillage system alternatives were highly ranked depending on the type of crop and tillage system. For the SERF analysis, results were dependent on the type of crop and level of risk aversion. The conventional tillage system was preferred for both corn and soybean for the Stoplight analysis. The results of this study are unique in that they highlight the potential of both traditional stochastic dominance and SERF methods for distinguishing economically sustainable choices between different tillage systems across a range of risk aversion. This study also indicates that the SERF risk analysis method appears to be a useful and easily understood tool to assist farm managers, experimental researchers, and potentially policy makers and advisers on problems involving agricultural risk and sustainability.

Highlights

Interest in tillage systems that reduce the number of cultivation steps has increased steadily worldwide over the past two decades
The no-till system had the largest mean and had a much higher variance than the moldboard plow tillage system, indicating a larger degree of risk relative to the expected return
It is worth noting that the ridge-till tillage system had lower variances than the no-till system for all the corn and soybean gross margin and net return combinations

Summary

Introduction

Interest in tillage systems that reduce the number of cultivation steps has increased steadily worldwide over the past two decades. These reduced tillage systems—commonly called reduced till, no-till, low till, limited till, or conservation till—potentially have the ability to reduce wind and water erosion, conserve soil moisture, and improve soil structure. Many studies have found that using reduced tillage systems reduces input costs such as fuel, labor, and machinery repair/depreciation costs [1,2]. Lower production costs found in reduced tillage systems may be offset by increased chemical costs for many crops [3,4,5]. Generally better economic performance for reduced tillage systems has been noted for well-drained soils and warmer climates [6,7] and poorer performance noted for poorly drained soils and cooler climates [8,9,10]

Objectives

Methods

Results

Discussion

Conclusion