Hostname: page-component-8448b6f56d-t5pn6 Total loading time: 0 Render date: 2024-04-18T23:37:50.101Z Has data issue: false hasContentIssue false

Incorporating systems dynamics and spatial heterogeneity in integrated assessment of agricultural production systems

Published online by Cambridge University Press:  30 January 2006

JOHN M. ANTLE
Affiliation:
Department of Agricultural Economics and Economics, Montana State University, PO Box 172920, Bozeman, MT 59717-2920, USA. E-mail: jantle@montana.edu
JETSE J. STOORVOGEL
Affiliation:
Department of Environmental Sciences, Wageningen University, P.O. Box 37, 6700 AA Wageningen, The Netherlands. E-mail: jetse.stoorvogel@wur.nl

Abstract

Agricultural systems are complex and dynamic, being made up of inter-acting bio-physical and human sub-systems. Moreover, agricultural systems are re-markably diverse, both within geographic regions and across regions. Accordingly, this paper focuses on dynamics and heterogeneity in coupled, multi-disciplinary simulation models of agricultural systems. We begin with a discussion of the principal features of agricultural production systems. We then present an example of a ‘loosely coupled’ model, the type of model most researchers have used to represent agricultural systems. We discuss the loosely coupled model's features and limitations, and show how it can be modified to incorporate feedbacks among sub-models. Finally, we use a case study of a hillside production system in Ecuador to illustrate the importance of model coupling, dynamics and heterogeneity in the analysis of production systems. This example shows that feedbacks and threshold effects are most important at sites most vulnerable to tillage erosion.

Type
Research Article
Copyright
© 2006 Cambridge University Press

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

Footnotes

This research was supported by grants from the USAID Soil Management Collaborative Research Support Program and the USEPA STAR Program Grant GR828745-01-0.