Kenneth Nyström

Yield capacity of planted Picea abies in northern Sweden

Norway spruce (Picea abies (L.) Karst.) is the dominant species in the older forests of central northern Sweden. However, spruce has seldom been planted in the area, partly because existing tools for site classification have indicated a low yield capacity for the species. The aim of this study was to examine the yield capacity of spruce on the basis of existing plantations. In total, 91 operational and experimental plantations in the age interval 27–46 yrs were sampled. Stands were located between 62° and 65° N at altitudes 130–620 m a.s.l. Site index was estimated by height growth and site‐factor equations previously developed from old‐growth stand data. Height developments in the plantations indicate that site index for these stands is on average 4.6 m higher than predicted by site‐factor equations. The differences between the two methods are larger on poor sites than on rich sites. No systematic deviations of top height development from the site index curves could be detected on remeasured sample plots...

Models for predicting height and diameter of individual trees in young Picea abies (L) karst. stands

Models for predicting height and diameter of individual trees in young Picea abies (L.) Karst. stands were developed. Data collected in a large survey of young forest stands in Sweden (the HUGIN young stand survey) were used in the construction of the models. Models were developed both with and without competition indices included. When constructing the competition indices trees within three metres from the subject tree were regarded as competitors. Functions with competition indices included (distance dependent) will be useful in analyses of the development of stands with different stand structure, whereas functions without competition indices (distance independent) will be useful in systems for long‐term forecasts of yield.

Stability of Site Index in Scots Pine (Pinus sylvestris, L.) Plantations over Year of Plantingin the Period 1900-1977 in Sweden

The hypothesis that environmental changes have affected site productivity was tested through examination of site index over year of planting. Data included 197 experimental plots established 1886–1977 and 617 survey plots established 1952–1968, all with Scots pine (Pinus sylvestris L.). Effects of site differences were balanced in a multiple regression analysis. Evaluation with the current site index equation did not reveal any certain trend, but with a new site index equation based on data from repeated measurements of the experimental plots, a significant annual increase of site index of 2.4 cm was estimated for the period 1900–1977. However, the main difference was between stands established before and after 1940. Segmentation indicated a significant difference between these groups but no significant, continuous trend. The difference between the two groups could be related to differences in establishment and tending of the stands.

Assessment of bias due to random measurement errors in stem volume growth estimation by the Swedish National Forest Inventory

Abstract We evaluated the performance of two methods for estimating stem volume increment at individual tree level with respect to bias due to random measurement errors. Here, growth is either predicted as the difference between two consecutive volume estimates where single-tree volume functions are applied to data from repeated measurements or by a regression model that is applied to data from a single survey and includes radial increment. In national forest inventories (NFIs), the first method is typically used for permanent plots, the second for temporary plots. The Swedish NFI combines estimates from both plot types to assess growth at national and regional scales and it is, therefore, important that the two methods provide similar results. The accuracy of these estimates is affected by random measurement errors in the independent variables, which may lead to systematic errors in predicted variables due to model non-linearity. Using Taylor series expansion and empirical data from the Swedish NFI we compared the expected bias in stem volume growth estimates for different diameter classes of Scots pine (Pinus sylvestris L.) and Norway spruce (Picea abies (L.) Karst.). Our results indicate that both methods are fairly insensitive to random measurement errors of the size that occur in the Swedish NFI. The empirical comparison between the two methods showed greater differences for large diameter trees of both pine and spruce. A likely explanation is that the regressions are uncertain because few large trees were available for developing the models.

Improved Prediction of Forest Variables Using Data Assimilation of Interferometric Synthetic Aperture Radar Data

ABSTRACT The statistical framework of data assimilation provides methods for utilizing new data for obtaining up-to-date forest data: existing forest data are forecasted and combined with each new remote sensing data set. This new paradigm for updating forest database, well known from other fields of study, will provide a framework for utilizing all available remote sensing data in proportion to their quality to improve prediction. It also solves the problem that not all remote sensing data sets provide information for the entire area of interest, since areas with no remote sensing data can be forecasted until new remote sensing data become available. In this study, extended Kalman filtering was used for assimilating data from 19 TanDEM-X InSAR images on 137 sample plots, each of 10-meter radius at a test site in southern Sweden over a period of 4 years. At almost all time points data assimilation resulted in predictions closer to the reference value than predictions based on data from that single time point. For the study variables Loreys mean height, basal area, and stem volume, the median reduction in root mean square error was 0.4 m, 0.9 m2/ha, and 15.3 m3/ha (2, 3, and 6 percentage points), respectively.

Estimating forest age and site productivity using time series of 3D remote sensing data

Three-dimensional (3D) data about forest captured by airborne laser scanning (ALS) have revolutionized forest management planning. Accurate, updated large-scale maps of forest variables produced with low costs today support greatly improved decisions about silvicultural treatments compared to the past practice based on field surveyed data only. These maps usually lack important information about forest age and site productivity, as this cannot be accurately assessed from the available ALS data. In Sweden, ALS has recently been performed nation-wide, except the mountainous area, to produce a new and accurate digital terrain model (DTM). This DTM enables extremely cost-efficient extraction of 3D data about the forest from other sources than ALS, such as automatic stereo-matching of aerial images as well as from single-pass spaceborne interferometric synthetic aperture radar (InSAR). In contrast to ALS, these data sources can provide low-cost time-series of 3D data. Aerial images of Sweden are often available in archives back to approximately 1960, and the TanDEM-X SAR system has the potential to provide new data every second week over large areas. These data have a potentially high value for forest management planning, since they may provide missing and highly important information - forest site productivity, Site Index (SI) and forest age. This pilot study explores a least-squares minimization approach to estimate forest age and SI from time series of 3D data produced by 1) image matching of DMC aerial images, and 2) TanDEM-X SAR data.

Development of Scots pine stands after first biomass thinning with implications on management profitability over rotation

The aim of this study was to investigate the profitability of management regimes including both early biomass thinning (leaving 4000 stems/ha and using systematic boom-corridor thinning) and conventional production of pulp and timber. Empirical data obtained from five dense (11,000–20,000 stems/ha) naturally regenerated Scots pine experimental plots in which pre-commercial thinning (PCT) to 2500 stems/ha and control treatments (no PCT) were originally applied were used to initiate simulations. Biomass thinning was simulated at mean heights 6–7 m (BIO1) and 8–9 m (BIO2) in control plots. Land expectation values (LEVs) were calculated (3% interest rate), after simulating stands development to final harvest. Given the targeted stand stem density, 36–67 oven dry tons/ha were harvested in the simulations. Compared with PCT, both BIO regimes resulted in a somewhat lower average tree size in all subsequent harvest operations but a higher LEV in four of the five stands, if thinning was integrated with bundling. Higher LEVs (on average 27%) were achieved when BIO2 was applied compared to BIO1. Consequently, high biomass removal from dense Scots pine stands early in rotation periods might provide substantial economic benefits for forest owners, but appropriate general decision tools are needed to maximize profit.