Skip to main content

Management of Mixed-Species, Uneven-Aged Forests in the French Jura: From Stochastic Growth and Price Models to Decision Tables

Buy Article:

$29.50 plus tax (Refund Policy)

Abstract:

A deterministic matrix growth model of uneven-aged stands of fir, spruce, and hardwood trees was extended to recognize random shocks. The results showed that the expected basal area of hardwoods, mainly beech, was substantially higher in the long run than that predicted by the deterministic model. A parallel stochastic model of prices was also developed from past data. It showed that real prices had no trend but that they were autocorrelated over time. The stochastic stand and price models were simulated simultaneously to obtain the probabilities of transition between stand and market states. This transition probability matrix was used in Markov decision-process models to calculate the best decision in each possible stand and market state. The policies examined included maximizing net present value, or expected tree diversity, production, or annual returns, subject to constraints on net present value, expected tree diversity, and basal area. A general mathematical programming method is presented to optimize economic or ecological objective functions subject to multiple constraints with or without time discounting. In the French Jura context, the solutions suggested that high net present value could be obtained while maintaining the average basal area near its current level, and keeping a high level of tree diversity. Accounting for risk called for more intense harvesting to raise revenues, and it led to stands that were much more diverse than suggested by deterministic solutions. FOR. SCI. 51(1):64–75.

Keywords: Markov chain; diversity; ecology; economics; environmental management; forest; forest management; forest resources; forestry; forestry research; forestry science; natural resource management; natural resources; risk

Document Type: Regular Article

Affiliations: 1: Ingénieur du Génie Rural, des Eaux et des Forêts Office National des Forêts Verdun France francois, Email: rollin@hotmail.com 2: Class of 1933 Bascom Professor and the John McGovern WARF Professor Department of Forest Ecology and Management University of Wisconsin Madison WI, Fax: (608) 262-9922, Email: jbuongio@wisc.edu 3: Graduate Student and Research Assistant Department of Forest Ecology and Management University of Wisconsin Madison WI, Email: mozhou@students.wisc.edu 4: Ingénieur en Génie Rural, des Eaux et des Forêts Former Head The Forest Economics Laboratory Nancy France F-54042, Email: Peyron@gip-ecofor.org

Publication date: 2005-02-01

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
  • Submit a Paper
  • Membership Information
  • Author Guidelines
  • Podcasts
  • Ingenta Connect is not responsible for the content or availability of external websites
  • Access Key
  • Free content
  • Partial Free content
  • New content
  • Open access content
  • Partial Open access content
  • Subscribed content
  • Partial Subscribed content
  • Free trial content
Cookie Policy
X
Cookie Policy
Ingenta Connect website makes use of cookies so as to keep track of data that you have filled in. I am Happy with this Find out more