A Critique on
Forest management optimization models and habitat diversity: a goal programming approach
Author : M Bertomeu and C Romero Journal of the Operational Research Society 2002 53, 1175–1184 2002 Operational Research Society Ltd.
I. Title of the Study
• As a researcher, the title provided by the authors has the element of simplicity, brevity, specificity and location and subject matter focused. The reader can easily determine
what the study is all about and what it tries to investigate Forest management optimization models and habitat diversity and what mathematical model? a goal
programming approach. Brief title but very informative. It would be better if the author mention the research location on the title to make more informative.
• Just going through the title, one can easily understand that the concern of the research study is related to optimization model in forestry. The keywords used such as “Forest
management optimization models and habitat diversity: a goal programming approach” clearly indicate that the subject matter is in the field of forestry.
II. Rationale, Background and Objectives of the Study A. Rationale of the Study:
• The authors looked into the forest management optimization models and habitat diversity: a goal programming approach. Goal Programming is concerned where a
decision maker needs to consider multiple criteria in arriving at the overall best decision.
B. Background of the Study:
• According the authors, the modern societies demand from forests not only private goods sold in well-established markets but also public goods and services for which
there are no defined markets. Among the set of public goods and services demanded by society, the protection of biodiversity has become of paramount importance in the
past few years.
• Basically, biodiversity can be considered at three different levels of organization: genes, species and habitats Westman, 1990. Most managers who aim at the protection of
biological diversity of forest ecosystems specifically focus on species and habitat diversity. In the last years, many efforts have been undertaken in order to incorporate
biodiversity into forest management planning processes.
• The structural diversity is measured by the Shannon index or the so called normalized absolute deviation index for different characteristics e.g. the species diversity, the
basal area andor diameter distribution diversity, the foliage height diversity. • Finally, many other papers Mealey et al., 1982; Carter et al., 1997; Bettinger et al.,
1997; and Bevers and Hof, 1999 focus on the optimization of the spatial arrangement of forest stands age classes, provided that the habitat requirements of species with
respect to the amount of edges, the juxtaposition of different habitats, and other aspects related to the spatial distribution of habitats are previously known.
C. Objectives of the Study:
• The aim of this paper, as cited by the author is to propose a different analytical formulation for the incorporation of edge contrast as an operational measure of habitat
diversity proposed in the forest ecology field Harris, 1984 and Hunter, 1990. The starting point is a mathematical programming model recently formulated Bertomeu and
Universitas Sumatera Utara
Romero 2001 in which a harvest schedule holding some desirable properties from the habitat diversity viewpoint was determined.
• In this paper, the trade-off curve between the proposed measure of habitat diversity and financial returns from harvested timber is determined. Then, a zero-one goal
programming model that integrates the mentioned habitat diversity index and the economic criterion in conjunction with other relevant forest management criteria such
as volume control over the planning horizon and ending forest volume inventory is formulated. From this model, several best compromise or satisfying harvest schedules
are obtained and interpreted in utility terms.
III. Research Procedure
A. Goal Programming 1. Definition
