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. 2014 Feb 17;369(1639):20120280.
doi: 10.1098/rstb.2012.0280. Print 2014 Apr 5.

New parsimonious simulation methods and tools to assess future food and environmental security of farm populations

John M Antle  1 , Jetse J Stoorvogel, Roberto O Valdivia
Affiliations

New parsimonious simulation methods and tools to assess future food and environmental security of farm populations

John M Antle et al. Philos Trans R Soc Lond B Biol Sci. .

Abstract

This article presents conceptual and empirical foundations for new parsimonious simulation models that are being used to assess future food and environmental security of farm populations. The conceptual framework integrates key features of the biophysical and economic processes on which the farming systems are based. The approach represents a methodological advance by coupling important behavioural processes, for example, self-selection in adaptive responses to technological and environmental change, with aggregate processes, such as changes in market supply and demand conditions or environmental conditions as climate. Suitable biophysical and economic data are a critical limiting factor in modelling these complex systems, particularly for the characterization of out-of-sample counterfactuals in ex ante analyses. Parsimonious, population-based simulation methods are described that exploit available observational, experimental, modelled and expert data. The analysis makes use of a new scenario design concept called representative agricultural pathways. A case study illustrates how these methods can be used to assess food and environmental security. The concluding section addresses generalizations of parametric forms and linkages of regional models to global models.

Keywords: economics; environment; food; parsimony; simulation.

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Figures

Figure 1.
Figure 1.
Adoption curves for improved fertilizer use at base and ME prices. Predicted adoption rate is where curves cross the horizontal axis.
Figure 2.
Figure 2.
Per cent of farms above poverty in Machakos, Kenya: all farms, non-adopters and adopters of improved fertilizer use at ME prices (predicted adoption rate is 55%).
Figure 3.
Figure 3.
Price-based and adoption-based trade-off curves for improved fertilizer use at base and ME prices. Predicted adoption rates are at maximum point on the adoption-based trade-off curves (points 1′ and 2′).
Figure 4.
Figure 4.
The conceptual model of technology adoption and impact assessment.
Figure 5.
Figure 5.
Linkage of impact assessment to ME using adoption-based and price-based trade-off curves (Iz and Iv are environmental and economic indicators).
See this image and copyright information in PMC

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