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Modelling approaches for mixed-species agroforestry systems
Book chapter

Modelling approaches for mixed-species agroforestry systems

Steve R Harrison and Robert Harrison
Promoting sustainable agriculture and agroforestry to replace unproductive land use in Fiji and Vanuatu, pp.19-37
ACIAR Monograph, MN191, Australian Centre for International Agricultural Research
2016
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https://aciar.gov.au/View
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Abstract

Forestry Sciences
Given their complexity, the design and evaluation of agroforestry systems has been a challenging task for researchers. A 'triple bottom line' evaluation in terms of financial, social and environmental impacts is called for. This working paper was developed to select a logical and consistent modelling approach for multispecies agroforestry (MSA) systems, with particular emphasis on predicting financial performance. A number of potentially suitable modelling approaches and software packages are reported in the literature. These have typically used third and fourth generation computer programming languages and modern software packages (notably spreadsheet packages). The Australian Cabinet Timber Financial Model (ACTFM) was developed to predict potential returns from small-scale plantations of north Queensland high-value mixed-species rainforest cabinet timbers, for which there was little experience of plantation commercial production. The New Zealand Agroforestry Estate Model (AEM) was designed to evaluate agroforestry in combination with other farm activities. The Agroforestry Modelling Environment (AME) was designed as an object-oriented modelling tool to graphically visualise, construct, integrate and exchange agroforestry models. The AME was subsequently developed into the SIMILE simulation package, designed for building general ecology models. Nowadays, with the continued development of spreadsheet packages (notably Excel), increasing use is being made of this software for forestry modelling. While spreadsheets are widely used in the timber industry, and in forestry research projects, their use for design and evaluation of complex MSA systems is less well exploited. An intuitively powerful approach is to develop MSA financial models in an Excel workbook, with separate spreadsheets within the workbook for individual species. In support of this approach, a suite of financial models for individual species could be developed as modules, which can be combined relatively quickly to evaluate various MSA designs.

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