Jari Miina

Comparison of a physiological model and a statistical model for prediction of growth and yield in boreal forests

The structural and functional properties of a physiological model (FinnFor) and a statistical model (Motti), developed independently, were analysed in order to assess whether the former would provide the same prediction capacity as the latter, which is based on a huge body of long-term inventory data. The predictions were compared in terms of (i) stand-level variables, (ii) analysis of volume growth graphs, and (iii) stand structure variables (diameter and height distributions). Both unmanaged and managed (thinned) stands of Scots pine (Pinus sylvestris), Norway spruce (Picea abies) and silver birch (Betula pendula) growing on medium-fertility sites in central Finland were used for the comparison. In general, the outputs of the models agreed well in terms of relative growth rates regardless of tree species, with the implication that both predict competition within a stand and the effect of position on tree growth in a similar way. The statistical model was stable in its predictions, but not as sensitive to initial stand conditions and management as that based on physiological processes, but the two models agreed well in their dynamics and predictions. The process-based model may therefore be applied to practical management situations, in order to achieve more precise predictions under changing environmental conditions, as in the case of climate warming. On the other hand, some elements of process-model thinking could be incorporated into statistical models in order to make these responsive to changing conditions.

A method for stochastic multiobjective optimization of stand management

Abstract The paper describes a way of simultaneously optimizing several stand management objectives differing in measurement units and character. The simulation-optimization system accommodates, besides multiple objectives, the time and risk preferences of the decision maker. Multiple objectives are integrated in optimization through an additive utility function. Time preferences are dealt with by discounting, and the discounting rate is specified separately for each objective. Objectives related to products are described by the sum of the discounted values while objectives related to the status of the forest are described by the integral of the discounted value of a state variable. Different units are made commensurable via subutility functions that scale all objective variables between zero and one. Risks associated with the future growth level and timber prices, and with the preferences of the decision maker, are taken into account by stochastic optimization based on the scenario technique. With this technique, each management alternative produces a distribution of utility indices. This distribution is used to compute a utility index corrected by risk preferences; different parts of the distribution are weighted in a manner that reflects the decision makers attitude toward risk. A case simulation-optimization system is described, based on the above techniques, to deal with multiple objectives, time preferences, risks and risk preferences. Calculations using this system indicated that security and recreational amenities lengthen the optimal rotation of mixtures of Scots pine and Norway spruce, compared to a situation in which the maximal soil expectation value is the only objective. In a multiobjective case, stochastic growth, timber price and preferences increased the rotation length by 15 years (17%) from the deterministic optimum. Attitude toward risk also affected the optimal stand management.

Dependence of tree-ring, earlywood and latewood indices of Scots pine and Norway spruce on climatic factors in eastern Finland

Abstract First, mixed linear models were utilised to predict growth index series related to climate. The indexed series were predicted for the whole tree-ring, earlywood and latewood of Scots pine ( Pinus sylvestris L.) and Norway spruce ( Picea abies (L.) Karst.) in eastern Finland. The ratio of latewood and earlywood indices was also calculated. Second, autoregressive moving average and transfer function modelling were used to evaluate the influence of monthly climatic data (input series) on the index series (output series) during 1910–1989. The index series were filtered with a first-order autoregressive or moving average model because only the latewood/earlywood ratio for Scots pine was a white noise series. The summer temperature of the current year was positively correlated with the indices of Scots pine, except with the earlywood indices, which correlated positively with precipitation in May. Precipitation in the previous summer had a positive influence on all Scots pine index series. All growth indices of Norway spruce were related positively to temperature of the current growing season and negatively to temperatures of the previous July and August. In Scots pine the latewood/earlywood ratio increased with high temperatures in the spring and late summer. In Norway spruce mild winters and high spring and low June temperatures increased the latewood/earlywood ratio.

A spatial yield model for optimizing the thinning regime of mixed stands of Pinus sylvestris and Picea abies

This paper presents a distance‐dependent yield model for a mixed stand of Scots pine (Pinus sylvestris L.) and Norway spruce (Picea abies (L.) Karst.) that accounts for the possible mixture effects...

Modelling the production and species richness of wild mushrooms in pine forests of the Central Pyrenees in Northeastern Spain.

Multiple-use forestry requires comprehensive planning to maximize the utilization and sustainability of many forest resources whose growth and productivity are interconnected. Forest fungi represent an economically important nonwood forest resource that provides food, medicine, and recreation worldwide. A vast majority of edible and marketed forest mushrooms belong to fungi that grow symbiotically with forest trees. To respond to the need for planning tools for multiple-use forestry, we developed empirical models for predicting the production of wild mushrooms in pine forests in the South-Central Pyrenees using forest stand and site characteristics as predictors. Mushroom production and species richness data from 45 plots were used. A mixed modelling technique was used to account for between-plot and between-year variation in the mushroom production data. The most significant stand structure variable for predicting mushroom yield was stand basal area. The stand basal area associated with maximum mushroom ...

Predicting regeneration establishment in Norway spruce plantations using a multivariate multilevel model

This study predicts the regeneration establishment on 3-year-old Norway spruce (Picea abies (L.) Karst.) plantations in southern Finland using regeneration survey data. Regeneration establishment was described by seven response variables: number of planted spruces, natural Scots pines (Pinus sylvestris L.), natural spruces, natural seed-origin birches (Betula pubescens Ehrh. and B. pendula Roth.) and other broadleaves (i.e. sprout-origin birches and other broadleaves than birch), as well as height of crop-tree spruce and dominant height of broadleaves. Due to the multivariate (several responses for each plot) and multilevel (plot, stand, municipality, forest centre) structure, regeneration establishment was modelled by fitting a multivariate multilevel model with explanatory variables such as temperature sum, site fertility, soil quality and method of site preparation. In the model, the numbers of tree seedlings were modelled using over-dispersed Poisson distributed equations, and the tree heights were modelled using normally distributed linear equations. The estimated fixed and random parameters of the equations were logical, and there was no serious bias in predicting the regeneration establishment in the independent test data set. This modelling approach can be used to predict the regeneration establishment stochastically by taking into account the large unexplained variation in regeneration models.

Response to different thinning intensities in young Pinus sylvestris

The study reports on the growth of Scots pine (Pinus sylvestris L.) following the first commercial thinning. The study material consisted of 10 plots, each 1200 m2 in area, which were subjected to low‐thinning resulting in varying retention‐stand densities. The post‐thinning diameter growth of the trees correlated positively with the harvested competition and negatively with the retained competition. However, the variables describing removal were not useful model predictors in distance‐dependent single‐tree growth models; the models based on the retained competition only were equally good as models including removal as an additional predictor. In the study thinning response is defined as the change in growth rate as a result of the thinning. The 5‐yr thinning response correlated positively with the harvested competition and negatively with the retained competition, but the correlations were weak. The 5‐yr thinning response did not depend on relative or absolute tree size. Analysis of the temporal distribu...

Productivity of mixed stands of Pinus sylvestris and Picea abies

Growth comparisons of different mixtures of Scots pine (Pinus sylvestris) and Norway spruce (Picea abies) were based on spatial individual‐tree growth models in which the competition by pines and spruces was accounted for by separate competition indices. The study material represented growing sites of medium fertility. The models indicated that a spruce competitor decreases the growth rate of another spruce clearly more than a pine competitor. The diameter growth of a pine was affected slightly more by another pine than by a spruce of the same size and at the same proximity. According to growth and thinning simulations conducted, a conifer mixture may have a volume increment 10–15% higher than a pure pine or spruce stand with the same stand age and basal area.

Residual variation in diameter growth in a stand of Scots pine and Norway spruce

The study of the residual variation associated with tree diameter growth predictions in one Scots pine (Pinus sylvestris L.) stand and one Norway spruce (Picea abies( L.) Karst.) stand is evaluated. Annual diameter growth of trees was smoothed with equations that accounted for the variation caused by predictors commonly used in growth models. A time series of the deviations from the annual smoothing equations was calculated for each tree. The variation in residuals was modelled by four random parameters, which describe the level, trend, autocorrelation and error variance of the time series of the residuals. In growth simulations, the modelled residual variation can be added as a stochastic component to the growth estimate to take into account the total variation in diameter growth, and to obtain a close similarity between real and simulated stand development. In simulations that added the modelled stochastic variation to the diameter growth, the differentiation of trees into diameter classes was more rapid than in deterministic growth simulations. In the stochastic simulations the sawtimber production was greater than in the deterministic ones. The addition of the stochastic residual variation to the growth estimate did not notably affect the volume growth of the stand.

Application of ecological field theory in distance-dependent growth modelling

In this study, we compared the performance of an additive competition index and two new index types derived from ecological field theory. One type of competition index at a time was used as a distance-dependent predictor in a diameter growth model, together with a permanent set of distance-independent predictors. One of the new index types was computed multiplicatively from the relative influences of competitors at the location of the subject tree. This may be called the ecological interference potential of competitors. The other new index was a simple spatial integral of the ecological interference potential around the subject tree. Its value depends on the directional distribution of competitors. The results indicated that, for both Scots pine (Pinus sylvestris L.) and Norway spruce (Picea abies (L.) Karst.), the indices based on ecological field theory are better predictors of a growth model than a traditional additive index is. The spatial integral of the interference potential was better than the point value.