Current issue: 55(5)
Under compilation: 56(1)
Dalbergia latifolia Roxb., commonly known as rosewood, is one of the highly valuable tropical timber species of Nepal. The tree species was widely distributed in the past, however, over-exploitation of natural habitat, deforestation, forest conversion for agriculture, illegal logging and the invasion of alien species resulted in the classification of this species as vulnerable by the IUCN (International Union for Conservation of Nature) category. So, the prediction of habitat suitability and potential distribution of the species is required to develop restoration mechanisms and conservation interventions. In this study, we modelled the suitable habitat of D. latifolia over the entire possible range of Nepal using a Maxent model. We compiled 23 environmental variables (19 bioclimatic, 3 topographic and a vegetative layer), however, only 12 least correlated variables along with 43 spatially representative presence locations were retained for model prediction. We used a receiver operating characteristic (ROC) curve to assess the model’s performance and a Jackknife procedure to evaluate the relative importance of predictor variables. The model was statistically significant with an area under the curve (AUC) value of 0.969. The internal Jackknife test indicated that elevation was the most important variable for the model prediction with 71.3% contribution followed by mean temperature of driest quarter (9.8%). The most (>0.6) suitable habitat for the D. latifolia was 235 484 hectares with large sections of area in two provinces whereas, the western most provinces were not suitable for D. latifolia as per Maxent model. The information presented here can provide a framework for nature conservation planning, monitoring and habitat management of this rare and endangered species.
We modelled the effect of habitat composition and roads on the number and occurrence of moose (Alces alces L.) damage in Ostrobothnia and Lapland using a zero-inflated count model. Models were developed for 1 km2, 25 km2 and 100 km2 landscapes consisting of equilateral rectangular grid cells. Count models predict the number of damage, i.e. the number of plantations and zero models the probability of a landscape being without damage for a given habitat composition. The number of moose damage in neighboring grid cells was a significant predictor in all models. The proportion of mature forest was the most frequent significant variable, and an increasing admixture of mature forests among plantations increased the number and occurrence of damage. The amount of all types of plantations was the second most common significant variable predicting increasing damage along with increasing amount of plantations. An increase in thinning forests as an admixture also increased damage in 1 km2 landscapes in both areas, whereas an increase in pine-dominated thinning forests in Lapland reduced the number of damage in 25 km2 landscapes. An increasing amount of inhabited areas in Ostrobothnia and the length of connecting roads in Lapland reduced the number of damage in 1 and 25 km2 landscapes. Differences in model variables between areas suggest that models of moose damage risk should be adjusted according to characteristics that are specific to the study area.
The genus Betula L. is composed of several species, which are difficult to distinguish in the field on the basis of morphological traits. The aim of this study was to evaluate the taxonomic importance of using visible + near infrared (Vis + NIR) spectra of single seeds for differentiating Betula pendula Roth and Betula pubescens Ehrh. Seeds from several families (controlled crossings of known parent trees) of each species were used and Vis + NIR reflectance spectra were obtained from single seeds. Multivariate discriminant models were developed by Orthogonal Projections to Latent Structures – Discriminant Analysis (OPLS-DA). The OPLS-DA model fitted on Vis + NIR spectra recognized B. pubescens with 100% classification accuracy while the prediction accuracy of class membership for B. pendula was 99%. However, the discriminant models fitted on NIR spectra alone resulted in 100% classification accuracies for both species. Absorption bands accounted for distinguishing between birch species were attributed to differences in color and chemical composition, presumably polysaccharides, proteins and fatty acids, of the seeds. In conclusion, the results demonstrate the feasibility of NIR spectroscopy as taxonomic tool for classification of species that have morphological resemblance.
This explorative study examined practices of competence modelling in the forest sector organisations and how organisations anticipate changes in competence needs in the future. Semi-structured in-depth interviews (n=10) were conducted amongst forest sector experts in Finland and data was analysed by thematic analysis. The findings showed that the practices of modelling competences were diverse, most frequently used ones being superior-subordinate review discussions and quantitative competence surveys. In addition to these formal systems, informal modelling, especially on the team level and in smaller companies was also frequent. Organisations used competence modelling for several human resources functions, such as appraisal, motivation and promotion of employees. Surprisingly hiring and compensation functions were not mentioned. Perceptions related to competence modelling were generally speaking positive. The most important challenges were the lack of further actions and sometimes the extraordinary burden to the employees. When anticipating the future, the experts interviewed mentioned several commonly recognised trends, e.g., development of information technology, fragmentation of working life and structural changes in labour markets. All these require more generic competences related to information processing and personal self-management, especially respondents highlighted the importance of self-awareness skills. It is concluded that several useful practices for competence modelling already exist and that present study provides a basis for further quantitative further study.
Operating conditions affecting the quality of spot mounding by Bracke continuously advancing mounders were investigated on 66 regeneration areas (124 ha) in eastern Finland. The quality of mounds was classified as suitable (good or acceptable after additional compression) or unsuitable for planting. Models were constructed for the number of suitable planting spots obtained per hectare (good and acceptable mounds), the probability of successful mounding (≥1600 planting spots ha–1) and the probability of creating a suitable mound as a function of terrain, site and soil characteristics, as well as slash conditions (removed, fresh or dry logging residues). The average number of mounds created was 1892 ± 290 mounds ha–1, of which 1398 ± 325 mounds ha–1 (74%) were classified as suitable for planting. The quality of spot mounding was reduced by steep terrain, a thick humus layer and fresh logging residues. Stoniness and soil texture also affected the number of planting spots created. Mounding after logging residues had dried increased the number of planting spots by 191 spots ha–1 compared with mounding in the presence of fresh residues. Removing residues did not significantly increase the number of planting spots compared with mounding amongst dry residues. A thick humus layer, very stony soil, steep slopes and valley terrain decreased the number of planting spots by 150–450 spots ha–1. The number and quality of mounds varied considerably according to the operating conditions, but with careful selection of timing and sites the quality obtained by a continuously advancing mounder can be improved.
Remote sensing using unmanned aerial vehicle (UAV) -borne sensors is currently a highly interesting approach for the estimation of forest characteristics. 3D remote sensing data from airborne laser scanning or digital stereo photogrammetry enable highly accurate estimation of forest variables related to the volume of growing stock and dimension of the trees, whereas recognition of tree species dominance and proportion of different tree species has been a major complication in remote sensing-based estimation of stand variables. In this study the use of UAV-borne hyperspectral imagery was examined in combination with a high-resolution photogrammetric canopy height model in estimating forest variables of 298 sample plots. Data were captured from eleven separate test sites under weather conditions varying from sunny to cloudy and partially cloudy. Both calibrated hyperspectral reflectance images and uncalibrated imagery were tested in combination with a canopy height model based on RGB camera imagery using the k-nearest neighbour estimation method. The results indicate that this data combination allows accurate estimation of stand volume, mean height and diameter: the best relative RMSE values for those variables were 22.7%, 7.4% and 14.7%, respectively. In estimating volume and dimension-related variables, the use of a calibrated image mosaic did not bring significant improvement in the results. In estimating the volumes of individual tree species, the use of calibrated hyperspectral imagery generally brought marked improvement in the estimation accuracy; the best relative RMSE values for the volumes for pine, spruce, larch and broadleaved trees were 34.5%, 57.2%, 45.7% and 42.0%, respectively.
Models attempting to predict treeline shifts in changing climates must include the relevant ecological processes in sufficient detail. A previous correlative model study has pointed to nutrients, competition, and temperature as the most important factors shaping the treelines of Pinus sylvestris L., Picea abies (L.) H. Karst. and Betula pubescens Ehrh. in Finnish Lapland. Here, we applied a widely used process-based dynamic vegetation model (LPJ-GUESS) to (i) test its capability to simulate observed spatial and temporal patterns of the main tree species in Finnish Lapland, and (ii) to explore the model representation of important processes in order to guide further model development. A European parameterization of LPJ-GUESS overestimated especially P. abies biomass and the species’ northern range limit. We identified implemented processes to adjust (competition, disturbance) and crucial processes in boreal forests to include (nutrient limitation, forest management) which account for the model’s failure to (edaphically) restrict P. abies in Finnish Lapland and the resulting species imbalance. Key competitive mechanisms are shade and drought tolerance, nutrient limitation, fire resistance, and susceptibility to disturbances (storm, herbivory) which we discussed with respect to boreal ecology and promising model developments to provide a starting point for future model development.
Ungulate browsing results in important damages on the forests, affecting their structure, composition and development. In the present paper, we examine the occurrence of browsing damage in Norwegian forests, using data provided by the National Forest Inventory along several consecutive measurements (entailing the period 1995–2014). A portfolio of variables describing the stand, site and silvicultural treatments are analyzed using classification trees to retrieve combinations related to browsing damage. Our results indicate that the most vulnerable forest stands are young with densities below 1400 trees ha–1 and dominated by birch, pine or mixed species. In addition, stand diversity and previous treatments (e.g. thinnings) increase the damage occurrence and other variables, like stand size, could play a role on forest susceptibility to browsing occurrence although the latter is based on weaker evidence. The methods and results of our study can be applied to implement management measures aiming at reducing the browsing damages of forests.
Despite the numerous studies on year-to-year variation of tree growth, the physiological mechanisms controlling annual variation in growth are still not understood in detail. We studied the applicability of data-driven approach i.e. different regression models in analysing high-dimensional data set including continuous and comprehensive measurements over meteorology, ecosystem-scale water and carbon fluxes and the annual variation in the growth of app. 50-year-old Scots pine stand in southern Finland. Even though our dataset covered only 16 years, it is the most extensive collection of interactions between a Scots pine ecosystem and atmosphere. The analysis revealed that height growth was favoured by high water potential of the tree and carbon gain during the bud forming period and high water potential during the elongation period. Diameter growth seemed to be favoured by a winter with high precipitation and deep snow cover and a spring with high carbon gain. The obtained models had low generalization performance and they would require more evaluation and iterative validation to achieve credibility perhaps as a mixture of data-driven and first principle modeling approaches.
We designed a streamlined timber growth and quality model that aims at the effect of stand management on the efficiency of wood resource use. Applying the R based module toolbox to experimental plots of Douglas fir (Pseudotsuga menziesii [Mirb.] Franco) we analysed essential model features for reflecting the influence of planting density on board strength. The current version realistically predicted a significant increase of centre board bending strength at tree age 40 with initial stand density. Model performance gained clear advantage from a) parameterisation of height to diameter allometry as dependent on planting density b) consideration of cambial age and cross‑sectional knot area in board strength computation. Crown shape was less decisive. The model produced a significant effect of planting density even after a whole rotation period of 70 years as well as a realistic spectrum of board bending strength.
A shoot-root carbon:nitrogen allocation model, based on the two processes of transport and chemical conversion, is described and explored. The view is proposed that all allocation models, whether built for the purposes of theoretical investigation or practical application, should start with this irreducible framework. In the present implementation, the processes operate according to: for substrate sources, dependence on shoot and root sizes, with possible product inhibition; for transport, movement down a substrate concentration gradient; for substrate sinks or utilization, linear bisubstrate kinetics. The dynamic and equilibrium properties of the model are explored. Failure of this approach to allocation will indicate to the modeller that additional mechanisms to control the processes are needed, and the mode of failure will indicate the type of mechanisms required. Additional mechanisms are discussed which may involve hormones or teleonomic (goal-seeking) controls, and may be added to the irreducible framework. However, these additions should not replace the irreducible framework of transport and chemical conversion, because they do not in reality. Modifications to the basic model to reflect some possibilities such as ontogenesis with the transition from exponential growth towards a steady state or with the scaling of within-plant transport resistances, the influence of hormones, and active transport, are described.
The model HYDRA, which simulates water flow in the branched tree architecture, is characterized. Empirical studies of the last decades give strong evidence for a close structure-function linkage in the case of tree water flow. Like stomatal regulation, spatial patterns of leaf specific conductivity can be regarded as a strategy counteracting conductivity losses, which may arise under drought. Branching-oriented water flow simulation may help to understand how damaging and compensating mechanisms interact within the hydraulic network of trees. Furthermore, a coupling of hydraulic to morphological modelling is a prerequisite if water flow shall be linked to other processes. Basic assumptions of the tree water flow model HYDRA are mass conservation, Darcy's law and the spatial homogeneity of capacitance and axial conductivity. Soil water potential is given as a one-sided border condition. Water flow is driven by transpiration. For unbranched regions these principles are condensed to a nonlinear diffusion equation, which serves as a continuous reference for the discrete method tailored to the specific features of the hydraulic network. The mathematical derivation and model tests indicate that the realization of the basic assumptions is reproducible and sufficiently exact. Moreover, structure and function are coupled in a flexible and computationally efficient manner. Thus, HYDRA may serve as a tool for the comparative study of different tree architectures in terms of hydraulic function.
A system of zonality in Siberia has been formed under the control of continentality, which provides the heat and humidity regimes of the forest provinces. Three sectors of continentality and four to six boreal sub-zone form a framework for the systematization of the different features of land cover in Siberia. Their climatic ordination provides the fundamental basis for the principal potential forest types (composition, productivity) forecasting the current climate. These are useful in predicting the future transformations and succession under global change.
An equilibrium model driven by climatic parameters, the Siberian Vegetation Model, was used to estimate changes in the phytomass of Siberian vegetation under climate change scenarios (CO2 doubling) from four general circulation models (GCM's) of the atmosphere. Ecosystems were classified using a three-dimensional climatic ordination of growing degree days (above a 5 °C threshold), Budyko's dryness index (based on radiation balance and annual precipitation), and Conrad's continentality index. Phytomass density was estimated using published data of Bazilevich covering all vegetation zones in Siberia. Under current climate, total phytomass of Siberia is estimated to be 74.1 ± 2.0 Pg (petagram = 1,015 g). Note that this estimate is based on the current forested percentage in each vegetation class compiled from forest inventory data.
Moderate warming associated with the GISS (Goddard Institute for Space Studies) and OSU (Oregon State Univ.) projections resulted in a 23–26 % increase in phytomass (to 91.3 ± 2.1 Pg and 93.6 ± 2.4 Pg, respectively), primarily due to an increase in the productive Southern Taiga and Sub-taiga classes. Greater warming associated with the GFDL (General Fluid Dynamics Laboratory) and UKMO (United Kingdom Meteorological Office) projections resulted in a small 3–7 % increase in phytomass (to 76.6 ± 1.3 Pg and 79.6 ± 1.2 Pg, respectively). A major component of predicted change using GFDL and UKMO is the introduction of a vast Temperate Forest-Steppe class covering nearly 40% of the area of Siberia, at the expense of Taiga; with current climate, this vegetation class is nearly non-existent in Siberia. In addition, Sub-boreal Forest-Steppe phytomass double with all GCM predictions. In all four climate change scenarios, the predicted phytomass stock of all colder, northern classes is reduced considerably (viz., Tundra, Fore Tundra, northern Taiga, and Middle Taiga). Phytomass in Sub-taiga increases greatly with all scenarios, from a doubling with GFDL to quadrupling with OSU and GISS. Overall, phytomass of the Taiga biome (Northern, Middle, Southern and Sub-taiga) increased 15% in the moderate OSU and GISS scenarios and decreased by a third in the warmer UKMO and GFDL projections. In addition, a sensitivity analysis found that the percentage of a vegetation class that is forested is a major factor determining phytomass distribution. From 25 to 50% more phytomass is predicted under climate change if the forested proportion corresponding to potential rather than current vegetation is assumed.
Much of forestry data is characterized by a longitudinal or repeated measures structure where multiple observations taken on some units of interest are correlated. Such dependencies are often ignored in favour of an apparently simpler analysis at the cost of invalid inferences. The last decade has brought to light many new statistical techniques that enable one to successfully deal with dependent observations. Although apparently distinct at first, the theory of Estimating Functions provides a natural extension of classical estimation that encompasses many of these new approaches. This contribution introduces Estimating Function Theory as a principle with potential for unification and presents examples covering a variety of modelling issues to demonstrate its applicability.
The seed crop of Norway spruce (Picea abies (L.) H. Karst.) and Scots pine (Pinus sylvestris L.) is predicted with the help of mean monthly temperatures during May–August one and two years before the flowering year. The prediction models were made separately for Lapland and for the rest of Finland. The models are based on 10-year periods of seed crop measurements and climatic data. The total number of time series was 59.
In Lapland, Norway spruce flowered abundantly and produced an abundant seed crop after warm July–August and two years after cool July–August. In other parts of Finland, warm June and July produced a good flowering year, especially if these months were cool two years before the flowering year.
In Lapland, Scots pine flowered abundantly if the whole previous growing season was warm. Elsewhere in Finland, a cool June preceded prolific flowering in the coming year if the rest of the growing season was considerably warmer than the average.
The prediction models explained 37–49 % of the variation in the size of the seed crop. The occurrence of good and poor seed years was usually predicted correctly. Using the presented models, the prediction of the seed crop is obtainable 1.5 year for Norway spruce and 2.5 year for Scots pine before the year of seed fall.
The PDF includes an abstract in English.
The effect of the size of seed crop, dispersal of seeds and the early development of seedlings on the density and spatial distribution of young Scots pine (Pinus sylvestris L.) stands are evaluated on the basis of theoretical models. The models include (i) number and spatial distribution of parent trees on the regeneration area, (ii) size of annual seed crop, (iii) seed dispersal from a particular parent tree, (iv) germination of the seeds (germination percentage), (v) death of ageing seedlings after the establishment process, and (vi) height growth of the seedlings.
As expected, stand density and spatial distribution varied within a large range in relation to the density of the parent trees and the distance from them. The simulations also showed that natural seedling stands can be expected to be heterogenous due to the geometry of seed dispersal, emphasizing the frequency of young and small trees. The properties of the seedling stands were, however, greatly dependent on the density of the parent trees and the length of the regeneration period.
The PDF includes an abstract in Finnish.
Two Japanese models regarding the within-stand competition have been reviewed on the basis of relevant literature. Competition-density and 3/2 th power models seem to be applicable also into tree stands. The latter model has been applied into the material obtained from literature. Computations showed consistancy with the results obtained elsewhere in the world. It is concluded that also in Finnish conditions the 3/2 th power law may have great potentials in describing the effects of stand density on tree size.
The PDF includes a summary in English.
A dynamic programming approach toward stem value estimation for standing Scots pine (Pinus sylvestris L.) trees was developed. The determination of the saw log value was based on the sawing pattern and on the final products composition. The combination of taper curve models and bark models providing taper curves both over bark and under bark, which constituted the basis of the optimum stem scaling. A computer program was developed to determine the optimum log sequence of the stem aiming at maximizing the value of the final products. To examine the reliability of the computation system, 445 Scots pine sample trees from 29 stands were used as a test material. The stem values of sample trees were calculated in two ways: 1) with 12 measured diameters, and 2) with 12 estimated diameters derived from measured tree characteristics. In both cases the values of the intermediate diameters were calculated via cubic spline interpolation.
The PDF includes a summary in Finnish.
Methods involving the use of moving averages, trend surfaces and their combination are compared in deriving local values of monthly mean temperatures and precipitation sums from the observations made by the Finnish Meteorological Office. Correlation between meteorological variables and sea index, lake index and height above sea level were used in the trend surface method and in the combined method. Combined method, with a trend surface calculated from means of a long time period, was the most reliable method to estimate long local time series.
A method to calculate unbiased estimates of effective temperature sums from monthly mean temperatures is presented.
The PDF includes a summary in English.
A model was constructed, the aim of which was to predict growth under conditions where air pollutants are present. The model is based on photosynthesis and on the allocation of photosynthetic products for growth. It is assumed that air pollutants released during energy production mainly affect photosynthesis in two ways: 1) directly by injuring the photosynthetic mechanism, and 2) indirectly by leaching nutrients. The two ways were studied empirically in order to identify a sub-model for the photosynthesis of a plant exposed to air pollutants.
The stand model will be applied to two purposes. The present stage of forests in Finland is compared with the simulated state based on the assumption that no pollutants are present. In addition, the decrease in forest yield under different conditions derived from predictions about long-range pollutant transport in Europe is analysed.
A semi-statistical model is suggested for monitoring injuries of plants for long-time field exposures (months). The model is based on the following assumptions:
1. The concentrations of air pollutants in the atmosphere follow the Johnson SB distribution.
2. The degree of plant injury is proportional to the logarithm of air pollutant dose.
3. No injuries occur below a certain dose level.
4. A dose is defined as the air pollutant concentration multiplied by the duration of exposure raised to an exponent.
Based on the air pollutant frequency distribution a total dose for the exposure period is calculated by integration, and the total dose is related to the observed plant injury by non-linear regression. The model is tested for long-time exposures of sulphur dioxide to transplant lichen in natural environment.
In this study we analyse how the ion concentrations in forest soil solution are determined by hydrological and biogeochemical processes. A dynamic mode ACIDIC was developed, including processes common to dynamic soil acidification models. The model treats one to eight interacting layers and simulates soil hydrology, transpiration, root water and nutrient uptake, cation exchange, dissolutions and reaction of Al hydroxides in solution, and the formation of carbonic acid and its dissociation products. It includes also a possibility to a simultaneous use of preferential and matrix flow paths, enabling the throughfall water to enter the deeper soil layers in macropores without first reacting with the upper layers. Three different combinations of routing the throughfall water via macro- and micropores through the soil profile is presented. The large vertical gradient in the observed total charge was simulated successfully. According to the simulations, gradient is mostly caused by differences in the intensity of water uptake, sulphate adsorption and organic anion retention at the various depths. The temporal variations in Ca and Mg concentrations were simulated fairly well in all soil layers. For H+, Al and K there were much more variation in the observed than in the simulated concentrations. Flow in macropores is a possible explanation for the apparent disequilibrium of the cation exchange for H+ ad K, as the solution H+ and K concentrations have great vertical gradients in soil. The amount of exchangeable H+ increased in O and E horizons and decreased in the Bs1 and Bs2 horizons, the net change in whole soil profile being a decrease. A large part of the decrease of the exchangeable H+ in the illuvial B horizon was caused by sulphate adsorption. The model produces soil water amounts and solution ion concentrations which are comparable to the measured values, and it can be used in both hydrological and chemical studies of soils.
A sensitive framework has been developed for modelling young radiata pine (Pinus radiata D. Don) survival, its growth and size class distribution, from time of planting to age 5 or 6 years. The data and analysis refer to the Central North Island region of New Zealand. The survival function is derived from a Weibull probability density function, to reflect diminishing mortality with the passage of time in young stands. An anamorphic family of trends was used, as very little between-tree competition can be expected in young stands. An exponential height function was found to fit best the lower portion of its sigmoid form. The most appropriate basal area/ha exponential function included an allometric adjustment which resulted in compatible mean height and basal area/ha models. Each of these equations successfully represented the effects of several establishment practices by making coefficients linear functions of site factors, management activities and their interactions. Height and diameter distribution modelling techniques that ensured compatibility with stand values were employed to represent the effects of management practices on crop variation. Model parameters for this research were estimated using data from site preparation experiments in the region and were tested with some independent data sets.
Factors determining newsprint consumption in Finland in 1960–1986 were analysed. An econometric recursive multi-equation model describing the structure of the newspaper industry was formulated and estimated to obtain information on direct factors influencing newsprint demand. Short-term and long-term demand elasticities for newspapers and newspaper advertising were estimated.
The results indicate that the main factors affecting newsprint consumption are total circulation of newspapers, volume of newspaper advertising and the change in newsprint substance weight. Total newspaper circulation was found to depend on the rate of household formation and real household income changes. Demand for newspapers was shown to be price-inelastic. Structural analysis indicates that income elasticity of newspaper demand has increased slightly over time.
The volume of newspaper advertising was shown to affect newsprint consumption via the effects on pagination. Newspaper and television advertising were found to be independent of each other. The impact of the reduction in the basis weight was found to be substantial. The estimation of long-term elasticities of demand for newspapers and newspaper advertising using dynamic models revealed that demand rigidities exist.
The case study of Finland proposes three reasons why newsprint demand has not shown clear signs of reaching a saturation level. First, although population growth has stagnated in major consuming countries, the number of households has been increasing continuously. Second, income elasticity of newspaper demand does not show a declining trend. Third, the main driving force behind the buoyant demand is the resurgence of demand for newspaper as an advertising medium. In forecasting newsprint consumption, in addition to projections of economic growth, attention must be paid to the rate of household formation, the development of the advertising sector, the factors affecting competition between alternative media and the resulting media-mix in advertising, and changes in the substantial weight.
The PDF includes a summary in Finnish
At the beginning of the investigation period the total biomass of the Scots pine (Pinus sylvestris L.) stands on the ordinary sedge pine mire was 48 t/ha. The biomass of the mixed stands of Scots pine and birch (Betula pubescens Erhr.) on the herbrich sedge pine mire was 91 t/ha, out of which 60% was from pine. The biomass of the Norway spruce (Picea abies (L.) H. Karst.) on the Vaccinium-Myrtillus spruce mire was 148 t/ha. The average annual net increment of the stand biomass was 5.8 t/ha in the unfertilized pine stand and 6.7 t/ha in the NPK and micronutrient fertilized one during the six-year investigation period. The corresponding figures in the mixed stand were 7.2 t/ha and 7.6 t/ha. The net increment of the biomass in the unfertilized spruce stand was 6.9 t/ha and in the fertilized 8.4 t/ha. A considerable proportion of the net increment was lost to the ground as litter in all stands.
The nitrogen, phosphorus, potassium, magnesium, iron, manganese, zinc, copper and boron cycles were investigated. The annual nitrogen uptake from the soil was 26–42 kg/ha, that of phosphorus 2.5–3.4 kg/ha, potassium 4.5–12 kg/ha, calcium 12–29 kg/ha, magnesium 2–4 kg/ha, iron 1.4–6.6 kg/ha, manganese less than 2 kg/ha and the other nutrients only some grams. Only part of the fertilized nutrients was fixed in the stand.
The PDF includes a summary in Finnish.