Accuracy of forest inventory using airborne laser scanning: evaluating the first nordic full-scale operational project

This research reports the major results from an evaluation of the first Nordic operational stand-based forest inventory using airborne laser scanner data. Laser data from a forest area of 250 km² were used to predict six biophysical stand variables used in forest planning. The predictions were based on regression equations estimated from 250 m² field training plots distributed systematically throughout the forest area. Test plots with an approximate size of 0.1–0.4 ha were used for validation. The testing revealed standard deviations between ground-truth values and predicted values of 0.36–1.37 m (1.9–7.6%) for mean height, 0.70–1.55 m (3.0–7.6%) for dominant height, 2.38–4.88 m² ha^?1 (7.8–14.2%) for basal area and 13.9–45.9 m³ ha^?1 (6.5–13.4%) for stand volume. No serious bias was detected.     

Forest variable estimation using photogrammetric matching of digital aerial images in combination with a high-resolution DEM

Abstract

The rapid development in aerial digital cameras in combination with the increased availability of high-resolution Digital Elevation Models (DEMs) provides a renaissance for photogrammetry in forest management planning. Tree height, stem volume, and basal area were estimated for forest stands using canopy height, density, and texture metrics derived from photogrammetric matching of digital aerial images and a high-resolution DEM. The study was conducted at a coniferous hemi-boreal site in southern Sweden. Three different data-sets of digital aerial images were used to test the effects of flight altitude and stereo overlap on an area-based estimation of forest variables. Metrics were calculated for 344 field plots (10 m radius) from point cloud data and used in regression analysis. Stand level accuracy was evaluated using leave-one-out cross validation of 24 stands. For these stands the tree height ranged from 4.8 to 26.9 m (17.8 m mean), stem volume 13.3 to 455 m³ ha^?1 (250 m³ ha^?1 mean), and basal area from 4.1 to 42.9 m² ha^?1 (27.1 m² ha^?1 mean) with mean stand size of 2.8 ha. The results showed small differences in estimation accuracy of forest variables between the data-sets. The data-set of digital aerial images corresponding to the standard acquisition of the Swedish National Land Survey (Lantmäteriet), showed Root Mean Square Errors (in percent of the surveyed stand mean) of 8.8% for tree height, 13.1% for stem volume and 14.9% for basal area. The results imply that photogrammetric matching of digital aerial images has significant potential for operational use in forestry.     

Practical large-scale forest stand inventory using a small-footprint airborne scanning laser

Mean tree height, dominant height, mean diameter, stem number, basal area and timber volume of 116 georeferenced field sample plots were estimated from various canopy height and canopy density metrics derived by means of a small-footprint laser scanner over young and mature forest stands using regression analysis. The sample plots were distributed systematically throughout a 6500 ha study area, and the size of each plot was 232.9 m². Regressions for coniferous forest explained 60–97% of the variability in ground reference values of the six studied characteristics. A proposed practical two-phase procedure for prediction of corresponding characteristics of entire forest stands was tested. Fifty-seven test plots within the study area with a size of approximately 3740 m² each were divided into 232.9 m² regular grid cells. The six examined characteristics were predicted for each grid cell from the corresponding laser data using the estimated regression equations. Average values for each test plot were computed and compared with ground-based estimates measured over the entire plot. The bias and standard deviations of the differences between predicted and ground reference values (in parentheses) of mean height, dominant height, mean diameter, stem number, basal area and volume were ?0.58 to ?0.85 m (0.64–1.01 m), ?0.60 to ?0.99 m (0.67–0.84 m), 0.15–0.74 cm (1.33–2.42 cm), 34–108 ha^?1 (97–466 ha^?1), 0.43–2.51 m² ha^?1 (1.83–3.94 m² ha^?1) and 5.9–16.1 m³ ha^?1 (15.1–35.1 m³ ha^?1), respectively.     

Developing an airborne laser scanning dominant height model from a countrywide scanning survey and national forest inventory data

Abstract

An airborne laser scanning (ALS) dominant height model was developed based on data from a national scanning survey with the aim of developing a digital terrain model (DTM) for Denmark. Data obtained in the ongoing Danish national forest inventory (NFI) were used as reference data. The data comprised a total of 2072 measurements of dominant height on NFI sample plots inventoried in 2006–2007 and their corresponding ALS data. The dominant height model included four variables derived from the ALS point cloud distribution. The variables were related to canopy height, canopy density and species composition on individual plots. The RMSE of the final model was 2.25 m and the model explained 93.9% of the variation (R ²). The model was successful in predicting dominant height across a wide range of forest tree species, stand heights, stand densities, canopy cover and growing conditions. The study demonstrated how low-density ALS data obtained in a survey not specifically aimed at forest applications may be used for obtaining biophysical forest properties such as dominant height, thereby reducing the overall forest inventory costs.     

Mapping tree aboveground biomass and carbon in Omo Forest Reserve Nigeria using Landsat 8 OLI data

Protected areas in Nigeria are important ecosystems for carbon storage. The aim of this study was to estimate and map tree aboveground biomass (TAGB) and carbon (TAGC) within a tropical forest in Nigeria. Stepwise regression analysis was implemented to develop models for predicting TAGB in the forest stand, by integrating field TAGB data with Landsat 8 OLI data. Spectral variables used in the analysis include spectral bands, vegetation indices, tasseled cap indices and principal components. Model validation was performed using independent sample plots. The results showed that incorporating more than one category of spectral variables improved the prediction of TAGB. The best-fit model was applied to map the spatial distribution of TAGB and TAGC. The TAGC was estimated as 52.3% of TAGB, based on the average carbon content of tree species derived in this study. Average TAGB and TAGC estimates for the forest stand were 373.1 ± 165.4 t ha^?1 and 194 ± 82.7 t ha^?1, respectively. Reliable estimates of TAGB and TAGC for the forest reserve were obtained. This study provides important information required to manage the forest stand for optimal carbon sequestration.     

The choice of definition has a large effect on reported quantities of dead wood in boreal forest

A survey was conducted to assess the impact of the choice of definition on reported quantities of dead wood in Swedish forests, which to more than 90% are located in the boreal zone. The data collection was made on a subsample of the permanent plots of the Swedish national forest inventory. The objects included were standing dead trees and snags down to 5-cm diameter at breast height, dead lying stems and branches down to a threshold diameter of 1 cm and stumps down to a threshold diameter of 5-cm at normal stump height. Standing trees, snags and stumps were inventoried on 10-m radius circular plots while the downed objects were inventoried using both circular plots and line intersect sampling; thin objects (diameter 1–5 cm) were assessed only through line intersect sampling. The results showed that the estimated volume of dead wood was as high as 25 m³ ha^?1 when all components were included. With the standard Swedish definition, the corresponding estimate was only 10.9 m³ ha^?1, or 43% of the total value. Since definitions of dead wood vary greatly between countries we conclude that great caution must be exercised when figures are compared in connection with international reporting. For example, adding stumps to the Swedish definition would increase the amounts of dead wood from 10.9 to 15.7 m³ ha^?1, i.e. with 44%.     

Litterfall in relation to stand parameters and climatic factors in Pinus brutia forests in Turkey

With this study we investigated the effective factors on annual amount of total litterfall and needle litterfall in Pinus brutia forests and estimated them with a regression model based on certain stand parameters. We studied 27 permanent plots representing different stand structure and environmental conditions in South-Western Turkey. Litterfall was collected in three month intervals corresponding to each of four seasons for a three-year period. We found a significant relationship between litterfall and stand properties such as crown closure (%), basal area (m²?ha^?1), stand stem volume (m³?ha^?1), above-ground biomass (t?ha^?1), mean annual volume increment (m³?ha^?1?yr^?1) and site index (T?=?75). Similar relationships also hold true between litterfall and each of such climatic factors as seasonal mean temperature (°C), relative humidity (%) and temperature/precipitation ratio (dimensionless). The mean annual litterfall considerably varied depending on stand characteristics and certain environmental factors. Both needle litterfall and total litterfall may be predicted for long term by regression models using certain stand parameters. Models developed for litterfall of P. brutia forests in this study may be used for national C inventory in Turkey.     

Retrieval of forest attributes in complex successional forests of Central Indonesia: Modeling and estimation of bitemporal data

Quantification of forest parameters in different successional stages is required because of its importance as a source of global emissions and ecosystem changes. This study focuses on a successional tropical forest under logging practices in East Kalimantan province, Indonesia. We modeled the forest attributes using both a parametric multiple linear regression analysis and neural networks approach, with Landsat ETM data acquired in 2000 (ETM00). We compiled sample plot data using forest inventory data collected from 1997 to 1998. A total of 226 plots were used to train the models and 112 plots were used for the validation. The remote sensing data (spectral values, vegetation indices, texture, etc.) coupled with digital elevation model (DEM) were experimented with and selectively used to model basal area, stem volume and above ground biomass (AGB). We investigated the possibility to estimate the forest attributes from bitemporal ETM data by calibrating radiometric properties of the ETM image from 2003 (ETM03) using the multivariate alteration detection method. The Pearson correlations showed that the mean texture index is strongly correlated with the forest attributes. We show that neural networks resulted in a higher coefficient of determination (r²) and lower RMSE than multiple regressions for predicting the forest attributes. The estimated forest properties increased with the forest succession advancement (i.e. from the open forest to advanced secondary forest classes). The modeled basal area, stem volume and AGB varied from 10.7–15.1 m² ha⁻¹, 123.2–181.9 m³ ha⁻¹, and 132.7–185.3 Mg ha⁻¹, respectively. The RMSE_r values of model fitting ranged from 11.2% to 13.3%, and the test dataset estimated slightly higher RMSE_r which varied from 12% to 14.1%. The ETM03 forest attributes revealed favorable estimates, showing considerably higher estimates than the ETM00. The estimation of forest properties using neural networks makes Landsat data a valuable source of information for forest management, mainly with the recent free access to its historical dataset.     

Estimation of forest stem volume using multispectral optical satellite and tree height data in combination

Abstract

The accuracy of forest stem volume estimation at stand level was investigated using multispectral optical satellite and tree height data in combination. The stem volumes for the investigated coniferous stands, located in southern Sweden, were in the range of 15–585 m³ ha^?1 with an average stem volume of 266 m³ ha^?1. The results from regression analysis showed a substantial improvement for the combined stem volume estimates compared with using satellite data only. The accuracy in terms of root mean square error (RMSE) was calculated to 11.2% of the average stem volume using SPOT-4 data and tree height data in combination compared with 23.9% using SPOT-4 data only. By replacing SPOT-4 data with Landsat TM data the RMSE was improved from 25.2% to 12.2%. In addition, a sensitivity analysis was performed on the combined stem volume estimates by adding random errors, normally distributed with zero expectations, with standard deviations of 1, 1.5 and 2 m to tree height data. The results showed that the RMSE increased with increasing random tree height error to 15.4%, 18.0% and 19.9% using SPOT-4 data and 16.3%, 19.2% and 21.2% using Landsat TM data. The results imply that multispectral optical satellite data in combination with accurate tree height data could be used for standwise stem volume estimation in forestry applications.     

Growth and productivity of black spruce in even- and uneven-aged stands at the limit of the closed boreal forest

The increasing commercial interest and advancing exploitation of new remote territories of the boreal forest require deeper knowledge of the productivity of these ecosystems. Canadian boreal forests are commonly assumed to be evenly aged, but recent studies show that frequent small-scale disturbances can lead to uneven-aged class distributions. However, how age distribution affects tree growth and stand productivity at high latitudes remains an unanswered question. Dynamics of tree growth in even- and uneven-aged stands at the limit of the closed black spruce (Picea mariana) forest in Quebec (Canada) were assessed on 18 plots with ages ranging from 77 to 340 years. Height, diameter and age of all trees were measured. Stem analysis was performed on the 10 dominant trees of each plot by measuring tree-ring widths on discs collected each meter from the stem, and the growth dynamics in height, diameter and volume were estimated according to tree age. Although growth followed a sigmoid pattern with similar shapes and asymptotes in even- and uneven-aged stands, trees in the latter showed curves more flattened and with increases delayed in time. Growth rates in even-aged plots were at least twice those of uneven-aged plots. The vigorous growth rates occurred earlier in trees of even-aged plots with a culmination of the mean annual increment in height, diameter and volume estimated at 40–80 years, 90–110 years earlier than in uneven-aged plots. Stand volume ranged between 30 and 238 m³ ha⁻¹ with 75% of stands showing values lower than 120 m³ ha⁻¹ and higher volumes occurring at greater dominant heights and stand densities. Results demonstrated the different growth dynamics of black spruce in single- and multi-cohort stands and suggested the need for information on the stand structure when estimating the effective or potential growth performance for forest management of this species.     

Tree mortality after low-intensity prescribed fires in managed Pinus sylvestris stands in southern Finland

Abstract

Tree mortality, its causes, and the input of dead charred wood were studied in 11 managed 30–45-year-old Scots pine (Pinus sylvestris L.) stands 1 year after experimental low-intensity prescribed burnings in southern Finland. First, the relationship between fire-induced tree damage and several external variables, e.g. stand density, within-stand wind speed, open-air wind speed, the Finnish Forest Fire Index (FFI) and flame height, was studied. Secondly, the study examined which damage and morphological characteristics best predicted tree mortality. Tree mortality was very variable in the experimental plots, ranging from 0% to 48% on the basis of stem number and from 0% to 41% in terms of wood volume. The input of dead and charred wood decreased with stand age, being 19.4 m³ ha^?1 in 30–35-year-old stands, but only 1.7 m³ ha^?1 in 45-year-old stands. The input of dead wood was on average 10 m³ ha^?1, representing less than 5% of the mean volume before the prescribed fire. The external variables that best explained fire-induced damage were within-stand wind speed, flame height and FFI. Tree mortality was best predicted by charred stem ratio with bark thickness, and by charred stem ratio with tree diameter. The results indicate that prescribed burning that is conducted downwind increases tree mortality and changes subsequent stand structure with increasing within-stand wind speed.     

Annual allowable cut for merchantable woody species in a community managed forest in western Kenya

Changes in stand density, basal area, off-take and annual increment were determined from 18 permanent sample plots established in 1997 in Got Ramogi Forest in western Kenya. The plots were assessed in 2003 and 2008. A total of 824 stems ?1.5 m in height were recorded from 43 woody species. Key merchantable woody species comprised 20% of the woody species and 67% of the overall stem density. There was a significant reduction in the overall stand density and in the stem density of key merchantable woody species, but not among other woody species between 1997 and 2008. The basal area decreased significantly among key merchantable woody species, but not for the overall forest. The basal area decreased from 22.6 to 9.7 m² ha⁻¹ for key merchantable woody species. The stand volume of key merchantable woody species decreased from 156 m³ ha⁻¹ in 1997 to 61.7 m³ ha⁻¹ in 2008. The mean annual off-take declined from 10.3 m³ ha⁻¹ year⁻¹ between 1997 and 2003 to 9.1 m³ ha⁻¹ year⁻¹ between 2003 and 2008, while the mean annual increment increased from 2.9 to 3.3 m³ ha⁻¹ year⁻¹. It was predicted that forest recovery would surpass the 1997 stand volume of 156 m³ ha⁻¹ if off-take levels between 10% and 90% of the mean annual increment were adopted. We settled on an annual allowable cut of 80% of the mean annual increment as a compromise between consumptive and conservation interests. We identified over-harvesting as the main cause of the reduction in stem density among key merchantable woody species. A management plan with compartment registers indicating the diversity, abundance and distribution of each woody species was recommended to guide their utilization and monitor their population dynamics.     

Estimating forest data for analyses of forest production and utilization possibilities at local level by means of multi-source National Forest Inventory

The sample plot data of National Forest Inventories (NFI) are widely used in the analysis of forest production and utilization possibilities to support national and regional forest policy. However, there is an increasing interest for similar impact and scenario analyses for strategic planning at the local level. As the fairly sparse network of field plots only provides calculations for large areas, satellite image data have been applied to produce forest information for smaller areas. The aim of this study was to test the feasibility of generating forest data for a Finnish forest analysis tool, the MELA system, by means of the Landsat satellite imagery and the NFI sample plot data. The study was part of the preparation of a local forestry programme, where a strategic scenario analysis for the forest area of two villages (ca 8000 ha) was carried out. Management units that approximate forest stands were delineated by image segmentation. Stand volume and other parameters for each forest segment were estimated from weighted means of the NFI sample plots, where the individual sample plot weights were estimated by the k nearest neighbour (kNN) method. Two different spectral features were tested: single pixel values and average pixel values within a segment. The estimated forest data were compared with the forest data based on independent stand-level field assessments in two subareas, a national park and an area of forest managed for timber production.In the national park, the estimated mean volume of the growing stock from both spectral feature sets (about 160 m³ ha⁻¹) was clearly lower than that obtained from stand-level field assessment (186 m³ ha⁻¹). Using average pixel values within a segment resulted in a higher proportion of pine and a lower proportion of spruce volume than using single pixel values. It also resulted in an estimated felling potential nearly 10% higher over the first 10-year period in the scenario analysis of the area dedicated to timber production. However, the maximum long-term sustainable removal was at the same level (about 30,000 m³ year⁻¹) for both feature sets over the simulated 30-year period. The resulting annual felling area in the first 10-year period was 12% lower when the segment averages were applied, but the difference subsequently levelled off. The kNN approach in estimating initial forest data for scenario analyses at the local level was found promising.     

News and Views

New forest inventory methods must be developed in order to create good conditions for decision‐making regarding ecological and economical issues in forestry. There are good field measurement methods to use, but they are often very expensive. Coherent all radio band sensing (CARABAS) is a newly developed synthetic aperture radar (SAR) sensor. It differs significantly from the earlier SARs by using longer wavelengths. The CARABAS sensor is more adapted to the scatterers of interest in the forest, due to its longer wavelengths. In this study, CARABAS imagery is compared with forest tree volume. Regression analysis was used to relate radar backscattering to forest tree volume. Due to the large range of incidence angle (45°‐68°), the CARABAS image had to be radiometrically relative‐calibrated. Radar backscattering from five forest stands with similar volume contents were plotted against the distance from the sensor. The plot revealed a linear relationship between these variables. By linear regression on that material the other pixels were relative‐calibrated in the image. Finally, radar backscattering was related to forest stand volumes by using linear regression. The results showed that the backscattering component of the CARABAS imagery is highly correlated to forest tree volume (R² = 74.9%). In this material, there seemed to be no saturation level of the backscattering component up to 300 m³ ha^?1.     

Prediction of tree height,basal area and stem volume in forest stands using airborne laser scanning

The aim of this study was to develop prediction models using laser scanning for estimation of forest variables at plot level, validate the estimations at stand level (area 0.64 ha) and test the effect of different laser measurement densities on the estimation errors. The predictions were validated using 29 forest stands (80×80 m²), each containing 16 field plots with a 10 m radius. For the best tested case, mean tree height, basal area and stem volume were predicted with a root mean square error of 0.59 m (3% of average value), 2.7 m² ha^?1 (10% of average value) and 31 m³ ha^?1 (11% of average value), respectively, at stand level. There were small differences in terms of prediction errors for different measuring densities. The results indicate that mean tree height, basal area and stem volume can be estimated in small stands with low laser measurement densities producing accuracies similar to traditional field inventories.     

Validation of an efficient visual method for estimating leaf area index in clonal Eucalyptus plantations

Leaf area index (LAI) is a key ecophysiological parameter in forest stands because it characterises the interface between atmospheric processes and plant physiology. Several indirect methods for estimating LAI have been developed. However, these methods have limitations that can affect the estimates. This study aimed to evaluate the accuracy and applicability of a visual method for estimating LAI in clonal Eucalyptus grandis × E. urophylla plantations and to compare it with hemispherical photography, ceptometer and LAI-2000^® estimates. Destructive sampling for direct determination of the actual LAI was performed in 22 plots at two geographical locations in Brazil. Actual LAI values were then used to develop a field guide with photographic images representing an LAI range of 1.0–5.0 m² m^?2 (leaf area/ground area). The visual LAI estimation guide was evaluated with 17 observers in the field. The average difference between actual LAI and visual LAI estimation was 12% and the absolute difference between the two methods was less than or equal to 0.5 m² m^?2 in 77% of plots. Pearson’s correlation coefficients were high between actual LAI and hemispherical photographs (0.8), visual estimation (0.93) and LAI-2000^® (0.99) and low for the ceptometer (0.18). However, absolute values differed among methods, with the average difference between the actual and estimated LAI of [12]% for visual estimation, 28% for the LAI-2000^®, 37% for the ceptometer and ?43% for hemispherical photographs. The LAI-2000^® and ceptometer overestimated LAI in all plots, whereas hemispherical photographs underestimated the values in all measurements, showing that these methods need calibration to be used. No differences were observed between actual LAI and visual estimates across stand ages of 2–8 years and LAI of 1.5–5.3 m² m^?2 (P > 0.05). The results show that visual estimation of LAI in Eucalyptus stands is a practical method that is unaffected by atmospheric characteristics and can be used on an operational scale.     

Weibull and percentile models for lidar-based estimation of basal area distribution

Abstract

The aim of this study was to assess the accuracy of basal area distributions of sample plots in coniferous forest derived from small-footprint airborne laser scanner data, and to compare the accuracy of two methods for derivation of such distributions based on: (1) two percentiles of a two-parameter Weibull and parameter recovery, and (2) a system of 10 percentiles defined across the range of observed diameters. The 12 percentiles were derived from the empirical basal area distributions of 141 plots with size 300–400 m². Regression analysis was used to relate the percentiles to various canopy height and canopy density metrics derived from the laser data. On average, the distance between transmitted laser pulses was 0.9 m on the ground. The plots were divided into three strata according to age class and site quality. The stratum-specific regressions explained 7–91% of the variability. Total plot volume predicted from the estimated distributions was used to assess the accuracy of the regressions. Cross-validation of the regressions revealed a bias of ?1.2 to 2.1% between predicted and ground-truth values of plot volume. The standard deviations of the differences between predicted and ground-truth values of plot volume were 15.1–16.4%. Neither bias nor standard deviation differed significantly between the two validated methods.     

Medicinal plants in old-growth, degraded and re-growth forests of NW Pakistan

Many old-growth forest stands in northwest Pakistan have been structurally transformed as a consequence of logging and livestock grazing, some of which are thereafter left to secondary succession. These forests represent an important resource for local inhabitants who gather and sell medicinal plants as part of their livelihood. With this in mind, the main objectives of our study were: (1) to assess differences in the structure of the tree layer and the abundance of medicinal plants among differently transformed forests, (2) to evaluate the recovery potential of medicinal plants under re-growth forests, and (3) to assess relationships between tree stand structural characteristics and the occurrence of medicinal plants.The first step of the study involved creating an approximate map covering an area of 90 km² for five forest-use types (old-growth forest, forest degraded by logging, derived woodland, agroforest and re-growth forest). Fifteen plots per forest-use type were randomly allocated at altitudes ranging from 2200 m to 2400 m asl, within which the abundance of 10 locally important medicinal herb species was assessed.The study stands differed greatly in tree basal area, which was highest in old-growth forest (48 m² ha⁻¹), lowest in agroforest areas (6 m² ha⁻¹) and intermediate in re-growth forest (20 m² ha⁻¹). All ten medicinal plant species were encountered in old-growth and in re-growth forests, but only five of these species also occurred on agroforest plots. The mean coverage of study medicinal plants was highest in old-growth forest (7%), low in forest degraded by logging, derived woodland and agroforest (0.3-2%), and intermediate in re-growth forest (4%). The Jaccard abundance based similarity index indicates a considerable similarity (0.6) between re-growth and old growth forest for both trees and medicinal plants. The overall abundance of medicinal plants increased with increasing tree basal area and canopy cover. The abundance of some particular species decreased; however, the most sought-after medicinal species Bergenia ciliata, Valeriana jatamansi and Viola cancescens increased with tree basal area within specific forest-use type and also across forest-use types. In conclusion, our data suggest that anthropogenic forest degradation leads to a reduction in the abundance of economically viable medicinal plants for the study region. It is further indicated that this can be reversed if degraded forests are allowed to regenerate.     

Canopy density in stands of Picea abies and Pinus sylvestris after different thinning methods

Altogether 82 plots (261 estimations) of Picea abies (L.) Karst, and 193 plots (360 estimations) of Pinus sylvestris (L.) stands were estimated by a vertical tube. The “crown free projection”, CFP, of stands thinned in three methods with different thinning grades was measured: unthinned, heavily and very heavily thinned, heavily thinned delayed first thinning, extra heavily thinned and thinned from the top. Basal area (m²ha^?1) density (stems ha^?1) and diameter sum (m ha^?1) were plotted against CFP. Basal area was the best practical measure of stand in this study. Generally Scots pine stands have higher CFP and the curves are steeper than in Norway spruce stands. Depending on the grade of thinning, heavily and very heavily thinned spruce stands, delayed first thinning included, have CFP values of 10–15% and stands thinned from the top, 20–40%, compared with 30–80% and 30–60% respectively in pine stands. Extra heavily thinned stands have the highest CFP, 20–80% in spruce and 50–90% in pine stands. The CFP levels after thinning are too high in pine stands for avoidance of sucker and sprout production of aspen and birch. In dense Norway spruce stands thinned from the top or heavily and very heavily thinned, the CFP values are low enough (≤30%) to diminish the production of suckers.     

Influence of nitrogen and phosphorus fertilizers on amount and nutrient content of litterfall in a regrowth eucalypt forest

The effects of fertilizer treatment on nutrient transfers to the forest floor were examined in regrowth Eucalyptus diversicolor F. Muell. forest. Dry weight and nutrient content of leaf litterfall and total litterfall were measured for 3 years in a stand to which two levels of N (0, 200 kg ha^-1 year^-1) were applied each year at each of three levels of a single initial application of P (0, 30, 200 kg ha^-1). Annual accessions of litter to the forest floor were significantly increased by additions of both N (by 17%, 18% and 21% in the 3 years) and 200 kg P ha^-1 (by 8%, 8% and 4% in the 3 years) but there was no interaction between effects of N and P treatments. Fertilizer application also had a significant effect on the nutrient content of leaf litterfall and total litterfall. Concentration of N in leaf litterfall was 9% to 23% greater on plots treated with N fertilizer compared to untreated plots. The amounts of N in litterfall were about 30% greater on N-treated compared to untreated plots. On plots treated with 200 kg P ha^-1, P concentrations in leaf litter were 50% to 100% greater than in litter from plots receiving no P. Application of 200 kg P ha^-1 increased the amounts of P in annual litterfall by 32% to 87%. The greatest increase in P accessions occurred soon after fertilizer treatment. The amounts of Ca, K, and Na in litterfall were also significantly increased by fertilizer application. For Ca and K this was due partly to increases in element concentrations in litterfall following application of treatments. The effect of fertilizers on internal recycling of plant nutrients and on litter accumulation and nutrient dynamics in forest floor litter is discussed.