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We used national scenario analyses to examine the effects of harvesting intensity on the development of forest resources, timber supply, carbon balance, and biodiversity indicators of Finnish forestry in nine 10-year simulation periods (90-year simulation period) under the current climate. Data from the 11 th National Forest Inventory of Finland were used to develop five even-flow harvesting scenarios for non-protected forests with the annual harvest ranging from 40 to 100 million m 3. The results show that the highest annual even-flow harvest level, which did not decrease the growing stock volume over the 90-year simulation period, was 73 million m 3. The total 90-year timber production, consisting of harvested volume and change in growing stock volume, was maximized when the annual harvest was 60 mill. m3. Volume increment increased for several decades when harvested volume was less than the current volume increment. The total carbon balance of forestry was the highest with low volume of harvested wood. Low harvested volume increased the values of biodiversity indicators, namely volume of deciduous trees, amount of deadwood and area of old forest.

Abstract:We investigated how climate change affects the diameter growth of boreal Scots pine (Pinus sylvestris L.), Norway spruce (Picea abies (L.) H. Karst.), and silver birch (Betula pendula Roth) at varying temporal and spatial scales. We generated data with a gap-type ecosystem model for selected locations and sites throughout Finland. In simulations, we used the current climate and recent-generation (CMIP5) global climate model projections under three representative concentration pathways (RCPs) forcing scenarios for the period 2010-2099. Based on this data, we developed diameter growth response functions to identify the growth responses of forests under mild (RCP2.6), moderate (RCP4.5), and severe (RCP8.5) climate change at varying temporal and spatial scales. Climate change may increase growth primarily in the north, with a clearly larger effect on birch and Scots pine than Norway spruce. In the south, the growth of Norway spruce may decrease largely under moderate and severe climate change, in contrast to that of birch. The growth of Scots pine may also decrease slightly under severe climate change. The degree of differences between tree species and regions may increase along with the severity of climate change. Appropriate site-specific use of tree species may sustain forest productivity under climate change. Growth response functions, like we developed, provide novel means to take account of climate change in empirical growth and yield models, which as such include no climate change for forest calculations.

This study presents a comparison of the performance of four heuristic techniques with one-and two-compartment neighbourhoods in harvest scheduling problems including a spatial objective variable. The tested heuristics were random ascent, Hero, simulated annealing and tabu search. All methods seek better solutions by inspecting the neighbourhood solutions, which are combinations that can be obtained by changing the treatment schedule in one (one-compartment neighbourhood) or two (two-compartment neighbourhood) compartments. The methods and neighbourhoods were examined in one artificial and four real landscapes ranging from 700 to 981 ha in size. The landscapes had 608 to 900 stand compartments, and the examined planning problems had 2986 to 4773 binary decision variables. The objective function was a multi-objective utility function. The spatial objective variable was the percentage of compartment boundary that joins two compartments, both of which are to be cut during the same 20-year period. The non-spatial objectives were net incomes of three consecutive 20-year management periods and the remaining growing stock volume at the end of the third 20-year period. In another problem formulation, the total harvest of the first 20-year period was used as an objective variable together with the spatial objective. The results showed that a two-compartment neighbourhood was systematically and often clearly better than a one-compartment neighbourhood. The improvements were greatest with the simplest heuristics, random ascent and Hero. Of the four heuristics, tabu search and simulated annealing proved to be the best methods, but with a two-compartment neighbourhood the differences between methods were negligible.