Category: Research article
article id 387, category Research article
Evaluation of the multicriteria approval method for timber-harvesting group decision support. Silva Fennica vol. 39 no. 2 article id 387. https://doi.org/10.14214/sf.387
The decision support methods most often used in timber-harvesting planning are based on a single criterion. In this study, a voting-theory-based method called multicriteria approval (MA) is introduced to the group decision support of timber-harvesting. The use of voting methods alleviates the problems caused by the multitude of decision objectives involved in forestry decision-making and by the poor quality of information concerning both the preferences of decision-makers and the evaluation of decision alternatives with respect to the objectives often faced in practical timber-harvesting planning. In the case study, the tactical forest management plan of a forest holding jointly owned by three people was specified at the operative timber-harvesting level. The task was to find the best actual operative alternatives for the harvesting that had been proposed in the tactical plan. These timber-harvesting alternatives were combinations of treatment, timber-harvesting system and the timing of logging. Forest owners established multiple criteria under which the alternatives were evaluated. Two versions of MA were tested, one of them based on individual decision analyses and other one based on a composite analysis. The first was markedly modified from the original MA, combining properties of MA and Borda count voting. The other was an original MA with the order of importance for criteria estimated either using Borda count or cumulative voting. The results of the tested MA versions produced were very similar to each other. MA was found to be a useful tool for the group decision support of timber-harvesting.
article id 580, category Research article
Estimating individual tree growth with the k-nearest neighbour and k-Most Similar Neighbour methods. Silva Fennica vol. 35 no. 4 article id 580. https://doi.org/10.14214/sf.580
The purpose of this study was to examine the use of non-parametric methods in estimating tree level growth models. In non-parametric methods the growth of a tree is predicted as a weighted average of the values of neighbouring observations. The selection of the nearest neighbours is based on the differences between tree and stand level characteristics of the target tree and the neighbours. The data for the models were collected from the areas owned by Kuusamo Common Forest in Northeast Finland. The whole data consisted of 4051 tally trees and 1308 Scots pines (Pinus sylvestris L.) and 367 Norway spruces (Picea abies Karst.). Models for 5-year diameter growth and bark thickness at the end of the growing period were constructed with two different non-parametric methods: the k-nearest neighbour regression and k-Most Similar Neighbour method. Diameter at breast height, tree height, mean age of the stand and basal area of the trees larger than the subject tree were found to predict the diameter growth most accurately. The non-parametric methods were compared to traditional regression growth models and were found to be quite competitive and reliable growth estimators.
article id 597, category Research article
Outranking methods as tools in strategic natural resources planning. Silva Fennica vol. 35 no. 2 article id 597. https://doi.org/10.14214/sf.597
Two outranking methods, ELECTRE III and PROMETHEE II, commonly used as decision-aid in various environmental problems, and their applications to decision support for natural resources management are presented. These methods represent ‘the European school’ of multi-criteria decision making (MCDM), as opposed to ‘the American school’, represented by, for instance, the AHP method. On the basis of a case study, outranking methods are compared to so far more usually applied techniques based on the ideas of multi attribute utility theory (MAUT). The outranking methods have been recommended for situations where there is a finite number of discrete alternatives to be chosen among. The number of decision criteria and decision makers may be large. An important advantage of outranking methods, when compared to decision support techniques most often applied in today’s natural resources management, is the ability to deal with ordinal and more or less descriptive information on the alternative plans to be evaluated. Furthermore, the uncertainty concerning the values of the criterion variables can be taken into account using fuzzy relations, determined by indifference and preference thresholds. The difficult interpretation of the results, on the other hand, is the main drawback of the outranking methods.
article id 606, category Research article
Modelling future timber price development by using expert judgments and time series analysis. Silva Fennica vol. 35 no. 1 article id 606. https://doi.org/10.14214/sf.606
Timber prices belong to the most important variables affecting the optimality of forest management. On the other hand, forecasting of timber prices is very uncertain. One difficulty when using past time series data in forecasting future timber price development is the possibility of changes in the markets and in the society at large. Expert knowledge can be applied in forecasting of timber prices as information additional to that provided by time series modelling. This paper presents an approach utilising both time series data and expert judgments in modelling future timber prices. A time series model is used as the basis for the approach. Parameters describing future timber price trends, variation in future timber prices, and the probabilities of price peaks taking place in the future are estimated with expert judgments as the basis. A case study involving 12 experts was carried out in Finland, and models were estimated for all the six major timber assortments in the country. The model produced can be utilised in the optimisation calculations of forest planning.
article id 621, category Research article
Integrating timber price scenario modeling with tactical management planning of private forestry at forest holding level. Silva Fennica vol. 34 no. 4 article id 621. https://doi.org/10.14214/sf.621
In forest management planning, deterministic timber prices are typically assumed. However, real-life timber prices vary in the course of time, and also price peaks, i.e. exceptionally high timber prices, might occur. If land-owners can utilise the price variation by selling timber with the high prices, they are able to increase their net revenues correspondingly. In this study, an approach is presented to study the timber price variation and its significance in the optimization of forest management. The approach utilizes stochastic timber price scenario modelling, simulation of forest development, and optimization of forest management. The approach is presented and illustrated by means of a case study. It is shown how the degree of uncertainty due to variation in timber prices can be analyzed in tactical forest planning of private forestry, and how the potential benefits of adaptive timber-selling behaviour for a forest landowner can be computed by using the approach. The effects of stochastic timber prices on the choice of forest plan are studied at the forest holding level considering also the spacing and type of cuttings and the optimal cutting order. A forest plan prepared under the assumption of constant timber price very seldom results in optimal forest management. Through studying the effects of stochastic timber prices, forest landowners and other decision makers obtain valuable information about the significance of adaptive timber selling behaviour. The presented methodology can also be used in analysing the land-owners’ economic risks as a function of time-price structure.
article id 651, category Research article
Optimization bias in forest management planning solutions due to errors in forest variables. Silva Fennica vol. 33 no. 4 article id 651. https://doi.org/10.14214/sf.651
The yield of various forest variables is predicted by means of a simulation system to provide information for forest management planning. These predictions contain many kinds of uncertainty, for example, prediction and measurement errors. Inevitably, this has an effect on forest management planning. It is well known that uncertainty in the forest yields causes optimistic bias in the observed values of the objective function. This bias increases with the error variances. The amount of bias, however, also depends on the error structure and the relations between the objective variables. In this paper, the effect of uncertainty in forest yields on optimization is studied by simulation. The effect of two different sources of error, the correlation structure of these errors and relations among the objective variables are considered, as well as the effect of two different optimization approaches. The relations between the objective variables and the error structure had a notable effect on the optimization results.
article id 677, category Research article
Analysing uncertainties of interval judgment data in multiple-criteria evaluation of forest plans. Silva Fennica vol. 32 no. 4 article id 677. https://doi.org/10.14214/sf.677
The use of interval judgments instead of accurate pairwise comparisons has been proposed as a solution to facilitate the analysis of uncertainties in the widely applied pairwise comparisons technique. A method is presented for deriving probability distributions for the pairwise comparisons and for utilizing the distributions in the analysis of uncertainties in the evaluation process. The first step is that the expert or the decision-maker is queried as to the best guess of the priority ratio of the attributes compared. This is followed by an adjusting query concerning the uncertainty in the comparison: what is the probability of the priority ratio being between the best guess ± 1 unit of the pairwise comparison scale? An application of the method is presented in the form of multiple-criteria evaluation of alternative management plans for a forest area.
Category: Discussion article
article id 527, category Discussion article
Socioecological landscape planning: an approach to multi-functional forest management. Silva Fennica vol. 36 no. 4 article id 527. https://doi.org/10.14214/sf.527
article id 5636, category Article
Integrating forest-level and compartment-level indices of species diversity with numerical forest planning. Silva Fennica vol. 31 no. 4 article id 5636. https://doi.org/10.14214/sf.a8538
The study proposes a technique which enables the computation of user-defined indices for species diversity. These indices are derived from characteristics, called diversity indicators, of inventory plots, stand compartments, and the whole forest holding. The study discusses the modifications required to be made to typical forest planning systems due to this kind of biodiversity computation. A case study illustrating the use of the indices and a modified forest planning system is provided. In the case study, forest-level species diversity index was computed from the volume of dead wood, volume of broadleaved trees, area of old forest, and between-stand variety.
At the stand level, the area of old forest was replaced by stand age, and variety was described by within-stand variety. All but one of the indicators were further partitioned into two to four sub-indicators. For example, the volume of broadleaved trees was divided into volumes of birch, aspen, willow, and other tree species. The partial contribution of an indicator to the diversity index was obtained from a sub-priority function, determined separately for each indicator. The diversity index was obtained when the partial contributions were multiplied by the weights of the corresponding indicators and then were summed. The production frontiers computed for the harvested volume and diversity indices were concave, especially for the forest-level diversity index, indicating that diversity can be maintained at satisfactory level with medium harvest levels.
article id 5519, category Article
A method for estimating the suitability function of wildlife habitat for forest planning on the basis of expertise. Silva Fennica vol. 27 no. 4 article id 5519. https://doi.org/10.14214/sf.a15680
In the method presented in this study, a group of experts evaluate, in a pairwise manner, a set of forest areas with respect to the game species considered. On the basis of these comparisons, relative priorities of forest areas are estimated using the eigenvalue technique. Using regression analysis, a habitat suitability function is estimated in which the priority is predicted by measures already familiar in forest planning. As a case study, a habitat suitability function was estimated for black grouse (Tetrao tetrix, Lururus tetrix L.). The function is applicable in forestry planning carried out using modern planning techniques.
The PDF includes an abstract in Finnish.
article id 5484, category Article
A decision theoretic approach applied to goal programming of forest management. Silva Fennica vol. 26 no. 3 article id 5484. https://doi.org/10.14214/sf.a15645
An alternative approach to formulating a forestry goal programming problem is presented. First, single objective optima levels are solved. The Analytical Hierarchy Process is applied in the estimation of a priori weights of deviations from the goal target levels. The ratios of the weights can be interpreted as relative importance of the goals, respectively. The sum of the weighted deviations from all single optima levels associated with the management goals is minimized. Instead of absolute deviations, relative ones are used. A case study problem of forest management planning with several objectives, measured in different units, is analysed.
The PDF includes an abstract in Finnish.
article id 7513, category Article
A participatory approach to tactical forest planning. Acta Forestalia Fennica no. 251 article id 7513. https://doi.org/10.14214/aff.7513
The paper examines the needs, premises and criteria for effective public participation in tactical forest planning. A method for participatory forest planning utilizing the techniques of preference analysis, professional expertise and heuristic optimization is introduced. The techniques do not cover the whole process of participatory planning, but are applied as a tool constituting the numerical core for decision support. The complexity of multi-resource management is addressed by hierarchical decision analysis which assesses the public values, preferences and decision criteria toward the planning situation. An optimal management plan is sought using heuristic optimization. The plan can further be improved through mutual negotiations, if necessary. The use of the approach is demonstrated with an illustrative example. Its merits and challenges for participatory forest planning and decision making are discussed and a model for applying it in general forest planning context is depicted. By using the approach, valuable information can be obtained about public preferences and the effects of taking them into consideration on the choice of the combination of standwise treatment proposals for a forest area. Participatory forest planning calculations, carried out by the approach presented in the paper, can be utilized in conflict management and in developing compromises between competing interests.