Fill-in seedlings in constituting the stocking of Scots pine stands in northern Finland

Summary

Decay of unstable states in the presence of colored noise and random initial conditions. II. Analog experiments and digital simulations

The decay of an unstable state under the influence of external colored noise has been studied by means of analog experiments and digital simulations. For both fixed and random initial conditions, the time evolution of the second moment ¿x2(t)¿ of the system variable was determined and then used to evaluate the nonlinear relaxation time. The results obtained are found to be in excellent agreement with the theoretical predictions of the immediately preceding paper [Casademunt, Jiménez-Aquino, and Sancho, Phys. Rev. A 40, 5905 (1989)].

Professor Sergei A. Kitaigorodskii in Finland

Liite: S. A. Kitaigorodskiin kirjallisuusluettelo

Assessing the risks and uncertainties of regional crop potential under changing climate in Finland

Selostus: Arviointi Suomen kasvintuotantopotentiaalin alueellisista riskeistä ja epävarmuuksista ilmaston muuttuessa

Carbon Reservoirs in Peatlands and Forests in the Boreal Regions of Finland

Summary

Pest status and incidence of the honey bee tracheal mite in Finland

Selostus: Mehiläisen sisuspunkin aiheuttamat tuhot ja esiintyminen Suomessa

Digital soil mapping: strategy for data pre-processing

The region of greatest variability on soil maps is along the edge of their polygons, causing disagreement among pedologists about the appropriate description of soil classes at these locations. The objective of this work was to propose a strategy for data pre-processing applied to digital soil mapping (DSM). Soil polygons on a training map were shrunk by 100 and 160 m. This strategy prevented the use of covariates located near the edge of the soil classes for the Decision Tree (DT) models. Three DT models derived from eight predictive covariates, related to relief and organism factors sampled on the original polygons of a soil map and on polygons shrunk by 100 and 160 m were used to predict soil classes. The DT model derived from observations 160 m away from the edge of the polygons on the original map is less complex and has a better predictive performance.

Soil temperature regimes in Finland

Selostus: Maan lämpötila Suomessa