Meta-analysis of understory white spruce response to release from overstory aspen

2004 ◽  
Vol 80 (6) ◽  
pp. 694-704 ◽  
Author(s):  
Rongzhou Man ◽  
Ken J Greenway

Meta-analysis was used to summarize the research results on the growth response of understory white spruce to release from overstory aspen from different studies available from published and unpublished sources. The data were screened for the suitability for meta-analysis. Treatment effect sizes were calculated using response ratio from mean cumulative increments of released and control trees since release in height, diameter, and volume and modeled using a polynomial mixed effect regression procedure. Predictor variables include linear, quadratic, and cubic components of three independent variables — initial tree height, number of years after release, and residual basal area at release — and their linear interactions. Models with a reasonable predictive power were developed for height, diameter, and volume response, but no significant model was identified for survival. The models developed in this study can be applied to predict the growth response of understory white spruce to release, based on the growth of unreleased control trees, initial tree height, residual basal area at release, and time since release. The individual tree prediction can be easily scaled up to stand level if residual tree density and distribution is known. Key words: meta-analysis, boreal mixedwood, mixed model, polynomial regression, response ratio, growth, survival

2021 ◽  
Vol 13 (12) ◽  
pp. 2297
Author(s):  
Jonathon J. Donager ◽  
Andrew J. Sánchez Meador ◽  
Ryan C. Blackburn

Applications of lidar in ecosystem conservation and management continue to expand as technology has rapidly evolved. An accounting of relative accuracy and errors among lidar platforms within a range of forest types and structural configurations was needed. Within a ponderosa pine forest in northern Arizona, we compare vegetation attributes at the tree-, plot-, and stand-scales derived from three lidar platforms: fixed-wing airborne (ALS), fixed-location terrestrial (TLS), and hand-held mobile laser scanning (MLS). We present a methodology to segment individual trees from TLS and MLS datasets, incorporating eigen-value and density metrics to locate trees, then assigning point returns to trees using a graph-theory shortest-path approach. Overall, we found MLS consistently provided more accurate structural metrics at the tree- (e.g., mean absolute error for DBH in cm was 4.8, 5.0, and 9.1 for MLS, TLS and ALS, respectively) and plot-scale (e.g., R2 for field observed and lidar-derived basal area, m2 ha−1, was 0.986, 0.974, and 0.851 for MLS, TLS, and ALS, respectively) as compared to ALS and TLS. While TLS data produced estimates similar to MLS, attributes derived from TLS often underpredicted structural values due to occlusion. Additionally, ALS data provided accurate estimates of tree height for larger trees, yet consistently missed and underpredicted small trees (≤35 cm). MLS produced accurate estimates of canopy cover and landscape metrics up to 50 m from plot center. TLS tended to underpredict both canopy cover and patch metrics with constant bias due to occlusion. Taking full advantage of minimal occlusion effects, MLS data consistently provided the best individual tree and plot-based metrics, with ALS providing the best estimates for volume, biomass, and canopy cover. Overall, we found MLS data logistically simple, quickly acquirable, and accurate for small area inventories, assessments, and monitoring activities. We suggest further work exploring the active use of MLS for forest monitoring and inventory.


2021 ◽  
Author(s):  
Timo Pampuch ◽  
Mario Trouillier ◽  
Alba Anadon-Rosell ◽  
Jelena Lange ◽  
Martin Wilmking

<p>Treeline ecosystems are of great scientific interest to study the direct and indirect influence of limiting environmental conditions on tree growth. However, tree growth is complex and multidimensional, and its responses to the environment depend on a large number of abiotic and biotic factors and their interactions.</p><p>In this study, we analyze the growth and xylem anatomy of white spruce trees (<em>Picea glauca</em> [Moench] Voss) from three treelines in Alaska (one warm and drought-limited, and two cold and temperature-limited treelines). We hypothesized (1) no difference between the treelines regarding the relationship between tree DBH and height, yet in general (2) faster growing trees at the warmer site. Additionally, we expected to find differences in xylem anatomical traits with trees from the drought-limited site having adapted to drought conditions by (3) forming smaller lumen diameter due to water deficit but (4) a higher xylem anatomical density due to higher temperatures and a longer vegetation period.</p><p>Regarding growth in height and diameter, trees at the drought-limited treeline grew relatively (1) taller and (2) faster compared to trees at the temperature-limited treelines. Raw xylem anatomical measurements showed (3) smaller lumen diameters and (4) higher density in trees at the drought-limited treeline. However, using linear mixed-effect models, we found that (i) traits related to water transport like lumen diameter were not significantly correlated with the actual amount of precipitation during the vegetation period but with tree height. We also found that (ii) traits related to mechanical support like density were mainly positively influenced by the mean temperature during the vegetation period.</p><p>The differences in lumen diameter found in the raw data can be explained by differences in the growth rates of the trees, since lumen diameter at the lower part of the tree stem needs to increase over time with increasing tree height. The greater wood density at the drought-limited treeline is probably caused by the higher temperature that leads to more biomass production, and potentially longer vegetation periods.</p><p>Our study shows that xylem anatomical traits in white spruce can be directly and indirectly controlled by environmental conditions. While lumen diameter is not directly influenced by environmental conditions but indirectly through tree height, other traits like anatomical density show a direct correlation with environmental conditions. Our results highlight the importance of approaching tree growth in a multidimensional way and considering direct and indirect effects of environmental forcing.</p>


Forests ◽  
2019 ◽  
Vol 10 (10) ◽  
pp. 905 ◽  
Author(s):  
Guerra-Hernández ◽  
Cosenza ◽  
Cardil ◽  
Silva ◽  
Botequim ◽  
...  

Estimating forest inventory variables is important in monitoring forest resources and mitigating climate change. In this respect, forest managers require flexible, non-destructive methods for estimating volume and biomass. High-resolution and low-cost remote sensing data are increasingly available to measure three-dimensional (3D) canopy structure and to model forest structural attributes. The main objective of this study was to evaluate and compare the individual tree volume estimates derived from high-density point clouds obtained from airborne laser scanning (ALS) and digital aerial photogrammetry (DAP) in Eucalyptus spp. plantations. Object-based image analysis (OBIA) techniques were applied for individual tree crown (ITC) delineation. The ITC algorithm applied correctly detected and delineated 199 trees from ALS-derived data, while 192 trees were correctly identified using DAP-based point clouds acquired from Unmanned Aerial Vehicles (UAV), representing accuracy levels of respectively 62% and 60%. Addressing volume modelling, non-linear regression fit based on individual tree height and individual crown area derived from the ITC provided the following results: Model Efficiency (Mef) = 0.43 and 0.46, Root Mean Square Error (RMSE) = 0.030 m3 and 0.026 m3, rRMSE = 20.31% and 19.97%, and an approximately unbiased results (0.025 m3 and 0.0004 m3) using DAP and ALS-based estimations, respectively. No significant difference was found between the observed value (field data) and volume estimation from ALS and DAP (p-value from t-test statistic = 0.99 and 0.98, respectively). The proposed approaches could also be used to estimate basal area or biomass stocks in Eucalyptus spp. plantations.


2014 ◽  
Vol 44 (2) ◽  
pp. 162-171 ◽  
Author(s):  
Derek F. Sattler ◽  
Philip G. Comeau ◽  
Alexis Achim

Radial patterns of modulus of elasticity (MOE) were examined for white spruce (Picea glauca (Moench) Voss) and trembling aspen (Populus tremuoides Michx.) from 19 mature, uneven-aged stands in the boreal mixedwood region of northern Alberta, Canada. The main objectives were to (1) evaluate the relationship between pith-to-bark changes in MOE and cambial age or distance from pith; (2) develop species-specific models to predict pith-to-bark changes in MOE; and (3) to test the influences of radial growth, relative vertical height, and tree slenderness (tree height/DBH) on MOE. For both species, cambial age was selected as the best explanatory variable with which to build pith-to-bark models of MOE. For white spruce and trembling aspen, the final nonlinear mixed-effect models indicated that an augmented rate of increase in MOE occurred with increasing vertical position within the tree. For white spruce trees, radial growth and slenderness were found to positively influence maximum estimated MOE. For trembling aspen, there was no apparent effect of vertical position or radial growth on maximum MOE. The results shed light on potential drivers of radial patterns of MOE and will be useful in guiding silvicultural prescriptions.


2007 ◽  
Vol 22 (3) ◽  
pp. 213-219 ◽  
Author(s):  
Hailemariam Temesgen ◽  
David W. Hann ◽  
Vincente J. Monleon

Abstract Selected tree height and diameter functions were evaluated for their predictive abilities for major tree species of southwest Oregon. Two sets of equations were evaluated. The first set included four base equations for estimating height as a function of individual tree diameter, and the remaining 16 equations enhanced the four base equations with alternative measures of stand density and relative position. The inclusion of the crown competition factor in larger trees (CCFL) and basal area (BA), which simultaneously indicates the relative position of a tree and stand density, into the base height–diameter equations increased the accuracy of prediction for all species. On the average, root mean square error values were reduced by 45 cm (15% improvement). On the basis of the residual plots and fit statistics, two equations are recommended for estimating tree heights for major tree species in southwest Oregon. The equation coefficients are documented for future use.


2004 ◽  
Vol 34 (1) ◽  
pp. 131-140 ◽  
Author(s):  
Lauri Mehtätalo

A height–diameter (H–D) model for Norway spruce (Picea abies (L.) Karst.) was estimated from longitudinal data. The Korf growth curve was used as the H–D curve. Firstly, H–D curves for each stand at each measurement time were fitted, and the trends in the parameters of the H–D curve were modeled. Secondly, the trends were included in the H–D model to estimate the whole model at once. To take the hierarchy of the data into account, a mixed-model approach was used. This makes it possible to calibrate the model for a new stand at a given point in time using sample tree height(s). The heights may be from different points in time and need not be from the point in time being predicted. The trends in the parameters of the H–D curve were not estimated as a function of stand age but as a function of the median diameter of basal area weighted diameter distribution (dGm). This approach was chosen because the stand ages may differ substantially among stands with similar current growth patterns. This is true especially with shade-tolerant tree species, which can regenerate and survive for several years beneath the dominant canopy layer and start rapid growth later. The growth patterns in stands with a given dGm, on the other hand, seem not to vary much. This finding indicates that the growth pattern of a stand does not depend on stand age but on mean tree size in the stand.


1998 ◽  
Vol 28 (9) ◽  
pp. 1344-1351 ◽  
Author(s):  
Hubert Sterba ◽  
Ralph L Amateis

Crown efficiency was first defined by Assmann (1961. Waldertragskunde. BLV, München) as individual tree volume increment per unit of crown projection area. He hypothesized that within a given crown class, smaller crowns are more efficient because their ratio between crown surface and horizontal crown projection is higher. Data from a loblolly pine (Pinus taeda L.) spacing experiment were used to test if this hypothesis also holds in young loblolly pine stands and, if so, to determine if it explains the increment differences between spacings in the spacing experiment. Using individual tree height relative to plot dominant height to describe crown class, within-plot regression showed that crown efficiency decreased with crown size for trees below dominant height. This relationship was much less pronounced than indicated from Assmann's examples, although the crown surface to crown projection ratio behaved in the same way as Assmann had hypothesized. Crown efficiency as well as the crown surface to crown projection area ratio decreased with increasing density. Basal area increment per hectare increased until total crown closure approached 130% and then stayed constant. This major impact of total crown coverage brings into question the usefullness of crown efficiency as an indicator for unit area growth.


2021 ◽  
Vol 126 ◽  
pp. 61-76
Author(s):  
Andrej Ficko ◽  
Vasilije Trifković

We present seven alternative statistical models for modelling tree diameter increment with data from permanent sampling plots. In addition to the polynomial regression model, we present a regression model with added random noise, a mixed linear model, regression with natural splines, and three models with limited dependent variables: truncated regression, tobit regression and grouped data regression. The models may be used when dealing with truncated or censored variables, biased estimation of the increment due to censoring and rounding down, or when having multilevel data. The parametrization of the models was done using 21,013 fir trees on 4,405 plots in the period 1990–2014 in uneven-aged Dinaric fir-beech forests. All models showed a similar effect of tree diameter, stand basal area, basal area of larger trees, diameter structure diversity, altitude and slope. There were only minor differences in the regression coefficients and fit measures. The highest increment predictions were given by the tobit model. The mixed model fit the data best and, compared to the other models, predicted a slower decrease in the growth of large-diameter trees after growth culmination.


2020 ◽  
Vol 50 (8) ◽  
pp. 726-735
Author(s):  
Sandra Carr ◽  
Guy R. Larocque ◽  
Nancy Luckai ◽  
F. Wayne Bell

Increasing the production of wood fibre from conifer species such as white spruce (Picea glauca (Moench) Voss) is one of many challenges in the management of boreal mixedwood forests. The effects of various competition measures on relative growth and relative growth rate variables were calculated for individual white spruce subject trees. Correlation analysis was used to explore relationships with competitor structural features, including the ratio of competitor basal area to subject tree basal area (CBAS), the ratio of competitor height to subject tree height (AHCS), and the proportion of softwood (FSW). Regression analysis was used to explore relationships with three distance-dependent competition indices. The ratio of subject tree height to diameter at breast height (DBH) (HDR), crown ratio (CR), and crown relative increment rate (CRIR) were significantly correlated with CBAS and AHCS. HDR, CR, CRIR, and DBH relative growth rate were all statistically significantly related to the competition indices. Results indicated that (i) relative growth and relative growth rate measures successfully captured a range of competition, (ii) crowns of trees with larger diameters used their horizontal growing space more efficiently to produce stemwood, and (iii) the proportion of softwood contributing to competition did not appear to influence subject tree production efficiency. Growth efficiency variables have the potential to improve our understanding of boreal mixedwood dynamics.


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