Browsing by Subject "epäoptimaalisuustappio"

There is need for information about stands and their future development in forest planning decision making. This information is collected by inventories. In general inventory is repeated with some before-hand set intervals, irrespective of the method. Between inventories information is updated with growth models. Both inventory and using of growth models causes errors in forest planning results, for example in management options. Erroneous predictions can lead to wrong conclusions and inoptimal decisions. If the optimal result is known, economical losses caused by wrong conclusions can be described with so called inoptimality losses. The aim of this study was to answer the question how long forest inventory information, updated with growth models, can be used in forest planning purposes. Study approach was economical, so evaluation of information`s usefulness was based on inoptimality losses which arise when development of the stand is predicted incorrectly with growth models. The study material included 99 stands. Their development was simulated with the SIMO software for 60 years from present. In the 60 years period influencies of growth prediction errors were studied with inventory periods which lengths were 5, 10, 15, 20, 30 and 60 years. It was assumed that new error-free forest inventory information was received in the beginning of each of the inventory periods. In order to study effects of different inventory periods, it was assumed that the growth models were able to predict the true development of stands. Erroneous developments were yielded with error model which was developed for this study and added to the growth models. Inoptimality losses were calculated with the information derived from the optimization of stands` true and erroneous developments. Inoptimality losses increased when the inventory period became longer. Absolute inoptimality loss was approximately 230 eur/ha when the inventory period was 5 years and approximately 860 eur/ha when the inventory period was 60 years. Relative inoptimality loss was 3,3 % when the inventory period was 5 years and 11,6 % when the inventory period was 60 years. The average inoptimality losses were different between different development classes, site classes and main tree species. Study results show that the length of the updating period has an effect on the developing economical losses. It seems also that the inventory period should be different for example in different development classes. However, it is difficult to specify the optimal updating period because total losses are a sum of losses of inventory errors, losses of growth prediction errors and losses caused by other uncertainty sources. The effects of both inventory errors and growth prediction errors are different in different kinds of stands. So estimation of total losses and estimation of inoptimality losses caused by different error sources requires more research.