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Growth and Management of Mixed-Species, Uneven-Aged Forests in the French Jura: Implications for Economic Returns and Tree Diversity

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Abstract:

The forests of the Jura mountains are among the most productive in France. This study developed quantitative models to improve the management of these mixed forests of fir, spruce, and beech. A nonlinear matrix model of stand growth was estimated and validated with medium-term projections and simulations of long-term stand dynamics. The ecological criteria were Shannon's index of tree diversity by species and size, the minimum number of trees in any species-size class, and basal area. The economic criteria were the present value of harvests, gross or net of the value of the growing stock, and the rate of return on the capital invested in the growing stock. Linear and goal programming were used to determine the effects, on all criteria, of managements that would maintain the stand in a steady state, and either (i) remove only the dead trees, (ii) maintain the forest close to its current state, (iii) achieve economic efficiency, subject to a desired level of diversity, (iv) maximize diversity, with or without constraints on economic returns. The results suggested that a light management could improve tree diversity, relative to natural stand growth. Maximum economic efficiency would require a substantial reduction in basal area and average size of trees, and it would lead to low tree diversity. Maximizing unconstrained tree diversity would be costly. Managements that conciliated diversity and economic efficiency all required a decrease in the basal area of stands, relative to their current state. A simple approach to convert a stand from its current condition to a desired steady state was investigated. For. Sci. 41(3):397-429.

Keywords: Biological diversity; goal programming; investment analysis; linear programming; operations research

Document Type: Journal Article

Affiliations: ENGREF, Nancy, France

Publication date: 1995-08-01

More about this publication?
  • Forest Science is a peer-reviewed journal publishing fundamental and applied research that explores all aspects of natural and social sciences as they apply to the function and management of the forested ecosystems of the world. Topics include silviculture, forest management, biometrics, economics, entomology & pathology, fire & fuels management, forest ecology, genetics & tree improvement, geospatial technologies, harvesting & utilization, landscape ecology, operations research, forest policy, physiology, recreation, social sciences, soils & hydrology, and wildlife management.
    Forest Science is published bimonthly in February, April, June, August, October, and December.

    2015 Impact Factor: 1.702
    Ranking: 16 of 66 in forestry

    Average time from submission to first decision: 62.5 days*
    June 1, 2016 to Feb. 28, 2017

    Also published by SAF:
    Journal of Forestry
    Other SAF Publications
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