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Determining the appropriate timing of the next forest inventory: incorporating forest owner risk preferences and the uncertainty of forest data quality / Kyle J. Eyvindson in Annals of Forest Science, vol 74 n° 1 (March 2017)  

Public [article]  inAnnals of Forest Science > vol 74 n° 1 (March 2017) Titre : Determining the appropriate timing of the next forest inventory: incorporating forest owner risk preferences and the uncertainty of forest data quality Type de document : Article/Communication Auteurs : Kyle J. Eyvindson, Auteur ; Aaron D. Petty, Auteur ; Annika S. Kangas, Auteur Année de publication : 2017 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] aide à la décision [Termes IGN] incertitude des données [Termes IGN] méthode de Monte-Carlo [Termes IGN] programmation stochastique [Termes IGN] risque naturel [Termes IGN] simulation numérique [Vedettes matières IGN] Inventaire forestier Résumé : (Auteur) The timing to conduct new forest inventories should be based on the requirements of the decision maker. Importance should be placed on the objectives of the decision maker and his/her risk preferences related to those objectives. Context : The appropriate use of pertinent and available information is paramount in any decision-making process. Within forestry, a new forest inventory is typically conducted prior to creating a forest management plan. The acquisition of new forest inventory data is justified by the simple statement of “good decisions require good data.” Aims : By integrating potential risk preferences, we examine the specific needs to collect new forest information. Methods : Through a two-stage stochastic programming with recourse model, we evaluate the specific timing to conduct a holding level forest inventory. A Monte Carlo simulation was used to integrate both inventory and growth model errors, resulting in a large number of potential scenarios process to be used as data for the stochastic program. To allow for recourse, an algorithm to sort the simulations to represent possible updated forest inventories, using the same data was developed. Results : Risk neutral decision makers should delay obtaining new forest information when compared to risk averse decision makers. Conclusion : New inventory data may only need to be collected rather infrequently; however, the exact timing depends on the forest owner’s objectives and risk preferences. Numéro de notice : A2017-042 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article DOI : 10.1007/s13595-016-0607-9 Date de publication en ligne : 08/02/2017 En ligne : https://doi.org/10.1007/s13595-016-0607-9 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=84200 [article]

Integrating risk preferences in forest harvest scheduling / Kyle J. Eyvindson in Annals of Forest Science, vol 73 n° 2 (June 2016)  

Public [article]  inAnnals of Forest Science > vol 73 n° 2 (June 2016) . - pp 321 - 330 Titre : Integrating risk preferences in forest harvest scheduling Type de document : Article/Communication Auteurs : Kyle J. Eyvindson, Auteur ; Annika S. Kangas, Auteur Année de publication : 2016 Article en page(s) : pp 321 - 330 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Végétation [Termes IGN] gestion [Termes IGN] gestion prévisionnelle [Termes IGN] planification [Termes IGN] production agricole végétale [Termes IGN] programmation stochastique [Termes IGN] risque environnemental [Termes IGN] sylviculture Résumé : (auteur) Key message: Through a stochastic programming framework, risk preferences can be included in forest planning. The value of utilizing stochastic programming is always positive; however, the value depends on the information quality and risk preferences of the decision maker. Context: Harvest scheduling requires decisions be taken based on imperfect information and assumptions regarding the future state of the forest and markets. Aims: The aim of this study is to incorporate elements of risk management into forest management, so that the decision maker can understand the risks associated with utilizing the imperfect data. Methods: Incorporation of uncertainty is done through stochastic programming. This allows for the decision maker’s attitude towards risk to be incorporated into the development of a solution. By means of a simple even-flow problem formulation, a method of using stochastic programming to incorporate explicit trade-off between objective function value and risk of not meeting the constraints has been developed. Results: The different models highlight the importance of including uncertainty in management of forest resources. In general, as the decision maker becomes more risk averse, the incorporation of uncertainty into the model becomes more important. Conclusions: The use of stochastic programming allows for additional information to be included in the formulation, and this allows for the decision maker to account for downside risk. Numéro de notice : A2016-351 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article DOI : 10.1007/s13595-015-0517-2 Date de publication en ligne : 11/09/2015 En ligne : https://doi.org/10.1007/s13595-015-0517-2 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=81061 [article]