Estimating foliage biomass in Scots pine (Pinus sylvestris) and Norway spruce (Picea abies) plots

Dynamic decomposition models are needed to estimate changes in the carbon stock of boreal soil because these changes are difficult to measure directly. An important aboveground carbon flux to the soil is foliage litterfall. To estimate this flux, both the amount and the turnover rate of the foliage biomass component must be known. Several methods for estimating foliage biomass of Scots pine (Pinus sylvestris L.) and Norway spruce (Picea abies (L.) Karst.), including biomass equations and biomass expansion factors (BEFs), were compared with predicted foliage biomass based on forest inventory plot-level measurements. Measured foliage biomass was up-scaled from the branch-level to the plot-level by combining forest inventory variables (diameter, height, height at the crown base and crown base diameter) based on the assumptions of pipe model theory. Combining the foliage biomass: cross-sectional area ratio with the forest inventory variables provided accurate estimates of foliage biomass at the plot-level for plots in southern Finland. The results emphasize the need to test biomass equations with independent data, especially when the equations applied are based on neighboring regions.     

Effects of competition and climate variables on modelling height to live crown for three boreal tree species in Alberta,Canada

Using tree data from permanent sample plots and climate data from the ClimateWNA model, mixed-effects height to live crown (HTC) models were developed for three boreal tree species in Alberta, Canada: trembling aspen (Populus tremuloides Michx.), lodgepole pine (Pinus contorta var. latifolia Engelm.) and white spruce (Picea glauca (Moench) Voss). Three model forms, the Wykoff model, a logistic model and an exponential model, were evaluated for each species. Tree height was the most significant predictor of HTC and was used in all models. In addition, we investigated the effects of competition and climatic variables on HTC modelling. Height–diameter ratio and either total stand basal area or basal area of coniferous trees were used as competition measures in the models. Different climate variables were evaluated, and spring degree-days below 0 °C, mean annual precipitation and summer heat–moisture index were incorporated into the aspen, lodgepole pine and white spruce models, respectively. Site index was only significant in lodgepole pine models. Residual variances were modelled as functions of tree height to account for heteroscedasticity still present in the mixed-effects models after the inclusion of random parameters. Based on model fitting and validation results as well as biological realism, the mixed-effects Wykoff models were the best for aspen and white spruce, and the mixed-effects logistic model was the best for lodgepole pine.     

Species Interactions in the Dynamics of Even- and Uneven-Aged Boreal Forests

Many boreal tree stands are neither clearly even-aged nor clearly uneven-aged. The stands may undergo a series of stages, during which an even-aged stand is transformed into two-storied mixed stand, and finally to multistoried or uneven-aged stand structure. The species composition often changes during the succession of stand stages. This study developed models for stand dynamics that can be used in different stand structures and species compositions. The model set consists of species-specific individual-tree diameter increment and survival models, and models for ingrowth. Separate models were developed for Scots pine, Norway spruce, and hardwood species. The models were used in a growth simulator, to give illustrative examples on species influences and stand dynamics. Methods to simulate residual variation around diameter increment and ingrowth models are also presented. The results suggest that mixed stands are more productive than one-species stands. Spruce in particular benefits from an admixture of other species. Mixed species improve diameter increment, decrease mortality, and increase ingrowth. Pine is a more beneficial admixture than birch. Simulations showed that uneven-aged management of spruce forests is sustainable and productive, and even-aged conifer stands growing on medium sites can be converted into uneven-aged mixed stands by a series of strong high thinnings.     

Determination of mean diameter by basal area in stands of picea abies and pinus sylvestris in southeastern Norway by means of aerial photographs

Mean diameter by basal area (d_g) is an important stand variable for long‐term economic forecasts of forest holdings. In order to use stand‐by‐stand surveys based on aerial photo interpretation as the data basis for forecasts, d_g has to be determined. The objective was to develop and test a regression function for d_g in mature stands of Norway spruce (Picea abies (L.) Karst.) and Scots pine (Pinus sylvestris L.) applicable in southeastern Norway. A study of 700 plots was used to estimate a function for d_g . An additive model was found to be most suitable. The independent variables were potential yield capacity, Lorey's mean tree height, crown closure determined by ocular estimation by means of aerial photographs, and the product of potential yield capacity and crown closure. The R² value was 0.604 and the coefficient of variation was 10.8%. The regression fitted most parts of the calibration data quite well, but it may overestimate the mean diameter in pure spruce stands by 1–2%, and underestimate the diameter in pure pine stands by 3%. For mixed coniferous stands the regression seems satisfactory. Testing by means of an independent data set showed systematic errors of 3–23%. The systematic errors were due partly to calibration problems in connection with the ocular crown closure estimation.     

Integrating the risk of wind damage into forest planning

Wind is the major abiotic risk factor in Finnish forests. Therefore, tools that help managers to assess the risk of wind damage are required. This study developed simple regression models for predicting the critical wind speed needed to uproot Scots pine, Norway spruce and birch trees at the stand edges in Finnish conditions, using the characteristics of the retained forest both downwind and upwind stands as predictors. Using information on the prevailing wind conditions in the region, the critical wind speeds were converted into probabilities of wind damage, from which a mean risk index was calculated. The mean risk index was used as an objective variable in heuristic optimisation. The results of minimizing the mean risk index were compared to other objective variables such as minimal height differences between adjacent stands. The residuals of the regression models of critical wind speeds were small, especially in Scots pine and birch. Increasing tree height of the downwind stand or area of the upwind stand (gap size) decreased the critical wind speed regardless of tree species, whereas increases in the dbh/height ratio of the downwind stand increased the critical wind speed. The shelter effect of upwind stand height was stronger in Norway spruce than in other tree species, whereas the effect of tree height of the downwind stand was larger in Scots pine and birch. Minimization of the mean risk of wind damage within forest landscapes led to smooth and non-fragmented landscape structures in terms of tree height. Incorporating even-flow constraints into the planning model led to a slight increase in the mean risk of wind damage. Of the surrogate methods for risk assessment minimization of height differences between adjacent stands performed well but not equally well as minimization of the mean risk index.     

Comparison between TanDEM-X- and ALS-based estimation of aboveground biomass and tree height in boreal forests

Interferometric Synthetic Aperture Radar (InSAR) data from TerraSAR-X add-on for Digital Elevation Measurement (TanDEM-X) were used to estimate aboveground biomass (AGB) and tree height with linear regression models. These were compared to models based on airborne laser scanning (ALS) data at two Swedish boreal forest test sites, Krycklan (64°N19°E) and Remningstorp (58°N13°E). The predictions were validated using field data at the stand-level (0.5–26.1 ha) and at the plot-level (10 m radius). Additionally, the ALS metrics percentile 99 (p99) and vegetation ratio, commonly used to estimate AGB and tree height, were estimated in order to investigate the feasibility of replacing ALS data with TanDEM-X InSAR data. Both AGB and tree height could be estimated with about the same accuracy at the stand-level from both TanDEM-X- and ALS-based data. The AGB was estimated with 17.2% and 14.6% root mean square error (RMSE) and the tree height with 7.6% and 4.1% RMSE from TanDEM-X data at the stand-level at the two test sites Krycklan and Remningstorp. The Pearson correlation coefficients between the TanDEM-X height and the ALS height p99 were r?=?.98 and r?=?.95 at the two test sites. The TanDEM-X height contains information related to both tree height and forest density, which was validated from several estimation models.     

林木高径比研究综述

林木高径比是基本测树因子之一。由于精确树高测定困难（特别是在结构复杂的森林中）,对林木高径比的直接相关研究相对较少。文中从林木高径比的研究对象、影响因素、林木高径比与单一测树因子的关系、林木高径比模型模拟、林木高径比与林木遭受风雪灾害的关系5个方面进行综述,以期为进一步研究林木高径比奠定基础。目前大部分研究是针对结构简单、单层同龄的人工针叶纯林,针对分树种和分林层的研究极少且只有国外报道。林木高径比可能受到树龄、树种、竞争、立地和气候等多种因素的影响。胸径、断面积、材积和地径等单一测树因子与林木高径比关系较为紧密,且呈负相关,而树高、冠长、冠幅、树冠面积、冠径、树冠比和树冠闭合百分比等单一测树因子与林木高径比关系较不紧密。目前的林木高径比模型多以胸径为自变量,然后进行多模型优选,所选的最佳模型多为非线性模型;部分研究则在最佳模型中加入其他的自变量,如竞争、立地、林层和树种等因子。多数研究认为,林木高径比越大,林木越容易遭受风雪灾害。     

Fine root biomass in relation to site and stand characteristics in Norway spruce and Scots pine stands

Variations in fine root biomass of trees and understory in 16 stands throughout Finland were examined and relationships to site and stand characteristics determined. Norway spruce fine root biomass varied between 184 and 370 g m(-2), and that of Scots pine ranged between 149 and 386 g m(-2). In northern Finland, understory roots and rhizomes (< 2 mm diameter) accounted for up to 50% of the stand total fine root biomass. Therefore, the fine root biomass of trees plus understory was larger in northern Finland in stands of both tree species, resulting in a negative relationship between fine root biomass and the temperature sum and a positive relationship between fine root biomass and the carbon:nitrogen ratio of the soil organic layer. The foliage:fine root ratio varied between 2.1 and 6.4 for Norway spruce and between 0.8 and 2.2 for Scots pine. The ratio decreased for both Norway spruce and Scots pine from south to north, as well as from fertile to more infertile site types. The foliage:fine root ratio of Norway spruce was related to basal area and stem surface area. The strong positive correlations of these three parameters with fine root nitrogen concentration implies that more fine roots are needed to maintain a certain amount of foliage when nutrient availability is low. No significant relationships were found between stand parameters and fine root biomass at the stand level, but the relationships considerably improved when both fine root biomass and stand parameters were calculated for the mean tree in the stand. When the northern and southern sites were analyzed separately, fine root biomass per tree of both species was significantly correlated with basal area and stem surface area per tree. Basal area, stem surface area and stand density can be estimated accurately and easily. Thus, our results may have value in predicting fine root biomass at the tree and stand level in boreal Norway spruce and Scots pine forests.     

The contribution of structural indices to the modelling of Sitka spruce (Picea sitchensis) and birch (Betula spp.) crowns

Crown dimensions are important for the quantification of tree interactions in some growth models. This study investigates the potential for structural indices and other spatial measures to improve the prediction of crown radius and crown length for birch (Betula spp.) and Sitka spruce (Picea sitchensis (Bong.) Carr.) in forests in Wales. Crown dimensions were measured for 125 birch and 154 spruce in six fully stem-mapped research plots. These data were used to test the performance of a crown radius model and a crown length model which estimated crown dimensions on the basis of allometric relationships with stem dimensions. Spatial data from the six plots were used to calculate the structural indices mean directional index, diameter correlation index, species mingling, dbh and height dominance, and dbh differentiation, as well as the Hegyi competition index, and basal area of neighbours and larger neighbours, for each crown measurement sample tree, using various numbers of nearest neighbours. Two non-spatial indices, BAL and BALMOD, were also calculated for all sample trees for comparison. These spatial and non-spatial variables were then incorporated into modified crown dimension models. Model performances, in terms of efficiency and relative bias, were compared to determine whether the inclusion of spatial or non-spatial variables resulted in any improvements over models using tree dimensions alone. Crown length and radius were found to be correlated with most of the spatial measures studied. Models incorporating spatial variables gave improvements in performance over allometric models for every data set, and performed more consistently than models containing non-spatial variables. The greatest improvements were achieved for suppressed birch in unthinned forests which had irregularly shaped and strongly displaced crowns. The spatial variable contributing to the most efficient model for each data set varied widely. This points to the complexity of tree spatial interactions and indicates that there is a great deal of scope for investigating other structural indices and crown dimension model forms.     

Height-diameter curves with random intercepts and slopes for trees growing on drained peatlands

Models for predicting tree height were constructed for Scots pine (Pinus sylvestris), Norway spruce (Picea abies) and pubescent birch (Betula pubescens). The data consisted of two separate sets of permanent sample plots forming a representative sample of drained peatland stands in the whole country. A logarithmic height-diameter curve with one nonlinear parameter specific to each tree species was applied. It was assumed that the intercept and slope of the curve would vary randomly from stand to stand. Stand characteristics were used to predict the mean intercept and slope. A nonhomogeneous variance of the residual error was modelled as a function of tree diameter. A mixed linear model technique was applied to fit the models. The diameter of the tree of the median basal area, stand basal area, geographical location of the stand, and site quality were used as fixed independent variables in explaining the variation in the intercept. The diameter of the tree of the median basal area and the stand basal area were used in explaining the variation in the slope.     

Characterization of radiation regimes in nonrandom forest canopies: theory,measurements, and a simplified modeling approach

We used field measurements and Monte Carlo simulations of canopy gap-size distribution and gap fraction to examine how beam radiation interacts with clumped boreal forest canopies of aspen (Populus tremuloides Michx.), black spruce (Picea mariana (Mill.) B.S.P.) and jack pine (Pinus banksiana Lamb.). We demonstrate that the Beer-Lambert law can be modified to accommodate transmission of radiation through a clumped forest canopy as a function of path length or sun zenith angle. Multiband Vegetation Imager (MVI) measurements and Monte Carlo simulations showed that values of the zenith element clumping index (Omega(e)(0)) are typically between 0.4 and 0.5 in jack pine and black spruce and 0.65 in aspen. Estimates of LAI obtained from MVI measurements of the canopy gap fraction and adjusted for canopy clumping and branch architecture yielded LAI values of 3.0 in jack pine, 3.3 in aspen, and about 6.0 in black spruce. These LAI estimates were within 10-25% of direct measurements made at the same sites. Data obtained with the MVI, along with numerical simulations, demonstrated that assumptions of random foliage distributions in boreal forests are invalid and could yield erroneous values of LAI measured by indirect techniques and false characterizations of atmosphere-biosphere interactions. Monte Carlo simulations were used to develop a general equation for beam radiation penetration as a function of zenith angle in clumped canopies. The essential measurements included stem spacing, crown diameter, crown depth, and within-crown gap fraction.     

Airborne laser scanning-based decision support for wood procurement planning

We present a decision support tool for guiding the selection of marked stands based on airborne laser scanning (ALS) data. We describe three stages, namely (1) wall-to-wall mapping of the stands matured for cutting using low-density ALS data; (2) tree-level inventory of these stands using high-density ALS data and (3) theoretical bucking of the imputed tree stems to produce detailed information on their characteristics. We tested them in a Scots pine dominated boreal forest area in Eastern Finland, where 79 sample plots were measured in the field. The detection of the stands matured for cutting had a success rate of 95% and our results demonstrated a further potential to limit the result towards stands dominated by certain species by means of intensity values derived from the low-density ALS data. The applied single-tree detection and estimation chain produced detailed tree-level information and realistic diameter distributions, yet the detection was highly emphasised on the dominant tree layer. The error levels in the estimates were generally less than standard deviations of the field attributes. Finally, plot-level accumulations of saw-log volumes were found rather similar, whether the input was based on the imputed tree data or trees measured in the field. The results are considered useful for ranking the stands based on their properties, whether the aim in the wood procurement is to focus on certain species or to select stands suitable for production needs.     

Predicting dynamic modulus of elasticity of Norway spruce structural timber by forest inventory,airborne laser scanning and harvester-derived data

Norway spruce structural timber is one of the most important products of the Norwegian sawmilling industry, and a high grade-yield of structural timber is therefore important for the economic yield. Presorting of logs suited for production of structural timber might be one option to increase the grade yield. In this study, dynamic modulus of elasticity (E_dyn) of structural timber was predicted based on forest inventory data at site level and single-tree data from airborne laser scanning (ALS) and harvester. The models were based on 611 boards from 4 sites in southeastern Norway. Important variables at site level were elevation, site index (SI), and mean stand age. However, when combining data from all information sources, mean stand age and site index were the only significant variables at site level. Tree height and variables describing the crown, like crown length and crown volume, were important vaiables extracted from ALS data. Stem diameter measures and tapering were important variables measured by the harvester. The combined model with variables from all three information sources reduced the variance the most, especially when using individual tree age instead of average stand age. However, combining all these data requires accurate positioning of the trees by the harvester.     

Individual-tree diameter growth models for black spruce and jack pine plantations in northern Ontario

Individual-tree distance independent diameter growth models were developed for black spruce and jack pine plantations. Data used in this study came via stem analysis on 1170 black spruce (Picea mariana [Mill.] B.S.P.) and 800 jack pine (Pinus banksiana Lamb.) trees sampled from 75 stands of 25 even-aged monospecific plantations for each species in the Canadian boreal forest region of northern Ontario. Of the 75 stands, 50 were randomly selected for each species and all trees from these stands were used for model development. Trees from the remaining stands were used for model evaluation.A nonlinear mixed-effects approach was applied in fitting the diameter growth models. The predictive accuracy of the models was improved by including random effects coefficients. Four selection criteria - random, dominant or codominant, tree size close to quadratic mean diameter, and small sized - were evaluated for accuracy in predicting random effects for a new stand using the developed models. Random effects predicted based on trees selected using the random selection criterion provided more accurate diameter predictions than those using trees obtained via other selection criteria for both species. The models developed here are very important to forest managers as the diameters predicted by these models or, their stand-level summaries (i.e., basal area, average diameter), are used as inputs in any forest growth and yield models. In addition, individual-tree diameter growth models can be used to directly forecast changes in diameter distribution of stands.     

A density management diagram for Norway spruce in the temperate European montane region

Norway spruce is one of the most important conifer tree species in Europe, paramount for timber provision, habitat, recreation, and protection of mountain roads and settlements from natural hazards. Although natural Norway spruce forests exhibit diverse structures, even-aged stands can arise after disturbance or as the result of common silvicultural practice, including off-site afforestation. Many even-aged Norway spruce forests face issues such as senescence, insufficient regeneration, mechanical stability, sensitivity to biotic disturbances, and restoration. We propose the use of Density Management Diagrams (DMD), stand-scale graphical models designed to project growth and yield of even-aged forests, as a heuristic tool for assessing the structure and development of even-aged Norway spruce stands. DMDs are predicated on basic tree allometry and the assumption that self-thinning occurs predictably in forest stands. We designed a DMD for Norway spruce in temperate Europe based on wide-ranging forest inventory data. Quantitative relationships between tree- and stand-level variables that describe resistance to selected natural disturbances were superimposed on the DMD. These susceptibility zones were used to demonstrate assessment and possible management actions related to, for example, windfirmness and effectiveness of the protective function against rockfall or avalanches. The Norway spruce DMD provides forest managers and silviculturists a simple, easy-to-use, tool for evaluating stand dynamics and scheduling needed density management actions.     

Assessing the impacts of species composition, top height and density on individual tree height prediction of quaking aspen in boreal mixedwoods

In this study we developed an individual tree height prediction model for quaking aspen (Populus tremuloides Michx.) grown in boreal mixedwood forests in Alberta using the nonlinear mixed model (NLMM) approach. We examined the impacts of density, species composition, and top height on aspen height predictions. Statistically significant stand level variables were incorporated into the base height–diameter model to increase the predictive ability and accuracy of the model at both the population and subject-specific levels. Our analyses showed that top height and density impacted height growth, but species composition did not. More importantly, we found that the inclusion of additional variables into the base model, despite improving model fitting statistics on the modelling data, did not improve the model's predictive ability and accuracy when cross-validated and when tested on an independent testing data set. Under the NLMM framework the base model performed as well as or better than the expanded models that contained other stand level variables. This has important theoretical and practical implications because, other than for biological reasons, more accurate local tree height predictions for aspen can be achieved simply by using the base height–diameter model fitted with the NLMM approach without the inclusion of other variables.     

Models for Predicting Wood Properties in Stems of Picea abies and Pinus sylvestris in Sweden

To study and model the variation of wood properties, sample trees were selected from 42 Norway spruce and 20 Scots pine stands covering a wide variation in climatic and site conditions, stand maturation and tree sizes. Plot and tree measurements were followed by sampling wood from different heights in each sample tree and laboratory measurements of wood properties. Mixed linear and non-linear prediction models were developed using diameters, number of annual rings and climatic indices as explanatory variables. The variation in spruce properties explained by these variables was: basic density 50%, latewood content 52%, juvenile wood diameter 85%, heartwood diameter 94% and bark thickness 76%. The corresponding values for pine were 59, 54, 79, 92 and 85%. Random among-tree variance was an important contributor to the remaining variation for density and latewood. In general, only a minor part of the random variation was related to variance between stands. Predictions derived from the models for density and juvenile wood in both species, and heartwood in pine showed good agreement when validated with data sets from two other studies. The resulting models may be used for predicting wood properties in forest planning and in bucking computers in harvesters, provided that the essential information is available.     

A model describing natural regeneration recruitment of Norway spruce (Picea abies (L.) Karst.) in Austria

In the absence of reliable and representative data on the frequency of seed years, seed amounts, germination and survival of seeds, the data of the observation period 1992–1996 of the permanent national forest inventory of Austria are used to develop a model describing the probability for the occurrence, density and height of Norway spruce (Picea abies (L.) Karst) natural regeneration in the forests of Austria. The forest inventory provided data on natural regeneration (saplings between 10 and 130 cm height) on clusters within a 3.89 km square sampling grid. A logistic equation is used to predict the probability for natural regeneration occurrence. Input parameters for this equation are the variables that describe the site, with slope and azimuth as continuous variables, and growth districts and vegetation types as discrete variables; the crown competition factor describes density and the quadratic mean diameter describes the stage of development of the stand. The same equation type is used to predict the probability for the occurrence of Norway spruce, conditional on the occurrence of some regeneration. An additional variable in this species specific model is a dummy variable which is set to 1 if Norway spruce occurs in the overstory and otherwise zero. Additional site variables entering this model are elevation and vegetation types characterizing soil fertility and moisture. Because the density and height of spruce regeneration depends on the stand's susceptibility to browsing, the probability for browsing is also modelled as a logistic equation depending on elevation, vegetation type, and stand density. Finally the probability distribution for height and density of the regeneration is described by two bivariate Weibull-distributions, each one describing browsed and unbrowsed Norway spruce regeneration respectively.     

Effects of using certain tree species in forest regeneration on volume growth,timber yield,and carbon stock of boreal forests in Finland under different CMIP5 projections

We studied how the use of certain tree species in forest regeneration affected the volume growth, timber yield, and carbon stock of boreal forests in Finland under the current climate (1981–2010) and recent-generation global climate model (GCM) predictions (i.e., multi-model means and individual GCMs of CMIP5), using the representative concentration pathways RCP4.5 and RCP8.5 over the period 2010–2099. Forest ecosystem model simulations were conducted on upland national forest inventory plots throughout Finland. In a baseline management regime, forest regeneration was performed by planting the same tree species that was dominant before the final cut. In alternative management regimes, either Scots pine, Norway spruce, or silver birch were planted on medium-fertility sites. Other management actions over rotation were done as in a baseline management. Compared to baseline management, an increased planting of birch resulted in relative sense highest increase in the volume growth, timber yield, and carbon stock in forests in the south, especially under severe climate projections (e.g., multi-model mean RCP8.5, and GCMs such as HadGEM2-ES RCP8.5 and GFDL-CM3 RCP8.5). This situation was opposite for Norway spruce. In the north, the volume growth, timber yield, and carbon stock of forests increased the most under severe climate projections (e.g., multi-model mean RCP8.5 and CNRM-CM5 RCP8.5), regardless of tree species preference. The magnitude of the climate change impacts depended largely on the geographical region and the severity of the climate projection. Increasing the cultivation of birch and Scots pine, as opposed to Norway spruce, could be recommended for the south. In the north, all three species could be cultivated, regardless of the severity of climate change.     

Species differences in total and vertical distribution of branch- and tree-level leaf area for the five primary conifer species in Maine, USA

Vertical distribution of leaf area largely governs both tree structure and function. Models of this important tree attribute have been constructed for several commercially important conifers. However, a limited number of studies have compared alternative modeling techniques and inherent species differences. This study used several existing datasets for the five primary conifer species in Maine, namely balsam fir [Abies balsamea (L.) Mill.], northern white-cedar [Thuja occidentalis (L.)], eastern hemlock [Tsuga canadensis (L.) Carr.], eastern white pine [Pinus strobus (L.)], and red spruce [Picea rubens (Sarg.)] to examine species variation in total and vertical distribution of projected leaf area at the individual branch- and tree-levels. In addition, multiple methods for modeling the vertical distribution of leaf area were examined across the species. For a given branch diameter and location within the crown, eastern hemlock branches held the greatest amount of leaf area, followed by balsam fir, northern white-cedar, white pine, and red spruce. At the tree-level, eastern white pine held the greatest amount of leaf area followed by eastern hemlock, balsam fir, red spruce, and northern white-cedar for a given tree size. Across species, the two-parameter, right-truncated Weibull distribution performed the best for predicting vertical distribution of leaf area when compared to the four-parameter beta and Johnson's S_B distributions (reduction of root mean square error of 1.7–21.1%). Northern white-cedar had a relative distribution of leaf area distinctly different than other species in this study with a mode shifted towards the upper crown. In contrast to red spruce and white pine, the mode of the relative distribution of leaf area for balsam fir and eastern hemlock occurred lower in the crown. Results of this study suggest that differences in total and vertical distribution of leaf area exist between species, but significant amounts of their variation are largely accounted for by bole and crown size.