An expert system to support site preparation decisions related to reforestation

An expert system to support site preparation decisions related to reforestation

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Article ID: iaor1994147
Country: Canada
Volume: 31
Issue: 3
Start Page Number: 220
End Page Number: 243
Publication Date: Aug 1993
Journal: INFOR
Authors: , ,
Keywords: geography & environment, ecology, artificial intelligence: expert systems, decision: applications
Abstract:

Site preparation is commonly employed in forestry in order to improve reforestation success. Application of the proper treatment can affect the future ecology of the site significantly. Site preparation decisions are naturally complex as they relate to processes that involve interaction of a multitude of ecological factors. There are three major types of treatment-prescribed burning, mechanical, and chemical. The preferred treatment depends on the site, and for a given treatment, details of application have to be carefully chosen. A treatment may have several ecological outcomes. Of these, a crucial one is the effect of the treatment on the seedling productivity. It is important to be able to predict this effect in order to choose the most appropriate treatment. However, no analytic models to predict the effects of a treatment on a given situation exist. Moreover, the outcomes are measured in terms of multiple variables which interact in a complex and not fully known way to affect seedling growth on the site. In practice, treatment decisions are usually based on experience, expertise, manuals, and guides that are frequently heuristic in nature. The knowledge required to predict the outcomes of a site preparation treatment spans diverse domains such as the science of soils, plant ecology and forestry. This situation motivated the development of an expert system to predict the ecological effects of site preparation treatments. Presently, the prescribed burning and mechanical components have been deployed in one of the forest regions of British Columbia. The chemical treatment component is being prototyped. This paper describes the nature of the problem and the process of developing and deploying the expert system. Issues discussed include development of the conceptual knowledge model, reconciliation of knowledge obtained from multiple sources of expertise, knowledge base validation, user interface principles, system evaluation, and the introduction of the system into the field. Conclusions are drawn as to the process of expert systems developed for problems of this nature.

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