An individual tree height increment model for mixed white spruce–aspen stands in Alberta, Canada

1999 ◽  
Vol 123 (1) ◽  
pp. 41-53 ◽  
Author(s):  
Shongming Huang ◽  
Stephen J. Titus
Keyword(s):  
Tree Height ◽  
White Spruce ◽  
Height Increment ◽  
Individual Tree

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
Keyword(s):  
Growth Response ◽  
Mixed Model ◽  
Polynomial Regression ◽  
Meta Analysis ◽  
Basal Area ◽  
Tree Height ◽  
White Spruce ◽  
Response Ratio ◽  
Mixed Effect ◽  
Individual Tree

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response of understory white spruce to release from overstory aspen from different studies available from published and unpublished sources.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

An age-independent individual tree height prediction model for boreal spruce–aspen stands in Alberta

1994 ◽  
Vol 24 (7) ◽  
pp. 1295-1301 ◽  
Author(s):  
Shongming Huang ◽  
Stephen J. Titus
Keyword(s):  
Prediction Model ◽  
Nonlinear Regression ◽  
Prediction Method ◽  
Tree Height ◽  
White Spruce ◽  
Data Set ◽  
Individual Tree ◽  
Permanent Sample Plots ◽  
Height Prediction ◽  
Age Independent

This study presents an individual tree height prediction model for white spruce (Piceaglauca (Moench) Voss) and trembling aspen (Populustremuloides Michx.) grown in boreal mixed-species stands in Alberta. The model is based on a three-parameter Chapman–Richards function fitted to data from 164 permanent sample plots using the parameter prediction method. It is age independent and expresses tree height as a function of tree diameter, tree basal area, stand density, species composition, site productivity, and stand average diameter. This height-prediction model was fitted by weighted nonlinear regression for spruce and unweighted nonlinear regression for aspen. Almost all estimates of parameters were significant at α = 0.05 and model R2-values were high (0.9192 for white spruce and 0.9087 for aspen). No consistent underestimate or overestimate of tree heights was evident in plots of studentized residuals against predicted heights. The model was also tested on an independent data set representing the population on which the model was to be used. Results showed that the average prediction biases were not significant at α = 0.05 for either species, indicating that the model appropriately described the data and performed well when predictions were made.

Estimating a system of nonlinear simultaneous individual tree models for white spruce in boreal mixed-species stands

1999 ◽  
Vol 29 (11) ◽  
pp. 1805-1811 ◽  
Author(s):  
Shongming Huang ◽  
Stephen J Titus
Keyword(s):  
Picea Glauca ◽  
Tree Height ◽  
White Spruce ◽  
Ordinary Least Squares ◽  
Tree Level ◽  
Parameter Estimates ◽  
Mixed Species ◽  
Individual Tree ◽  
Left Hand ◽  
Diameter Increment

A system of three interdependent, tree-level nonlinear equations was fitted. The system was used in an individual tree simulator to predict total tree height, periodic tree diameter increment, and height increment for white spruce (Picea glauca (Moench) Voss) grown in boreal mixed-species stands in Alberta. Because the variables appeared on the left-hand side of the equations also appeared on the right-hand side of the equations in the system, the system was estimated using nonlinear simultaneous techniques. Testing of cross-equation correlations using the Breusch and Pagan statistic indicated that the error terms of the related equations in the system are significantly correlated, suggesting that the parameter estimates obtained from simultaneous techniques are consistent and asymptotically more efficient than those obtained from ordinary least squares procedures applied to individual equations of the system.

Age structure and growth of understory white spruce under aspen

1996 ◽  
Vol 26 (6) ◽  
pp. 1002-1007 ◽  
Author(s):  
Victor J. Lieffers ◽  
Kenneth J. Stadt ◽  
Stan Navratil
Keyword(s):  
Growth Rates ◽  
Tree Height ◽  
Ground Level ◽  
White Spruce ◽  
Height Growth ◽  
Height Increment ◽  
Stem Analysis ◽  
Diameter Increment ◽  
Understory Trees ◽  
Normal Forest

Juvenile white spruce (Piceaglauca (Moench) Voss) under an aspen (Populustremuloides Michx.) overstory were studied in nine boreal mixedwood stands in west-central Alberta. In each stand, 50 understory white spruce were cut for stem analysis at ground level, 30, 70, 130 cm, and every 100 cm to tree height. In four stands, recruitment of these understory spruce occurred immediately after the disturbance, while in others the recruitment was delayed several decades. The period of recruitment was as short as 15–20 years or continued for decades, producing an uneven-aged understory. Trees initiated on rotten logs had a slightly lower initial annual diameter increment but did not differ in height growth compared with those initiated on normal forest floor. The annual height increment increased as the trees grew in height, presumably as they overtopped successive layers of shading vegetation. When seedlings were less than 30 cm tall they grew less than 10 cm per year, but attained growth rates of 30 cm per year or more when they were taller than 230 cm. Height growth rates for these understory trees were comparable to reported growth rates of white spruce of similar size and age from clearcut areas.

scholarly journals Development and Performance Evaluation of a Very Low-Cost UAV-Lidar System for Forestry Applications

2020 ◽  
Vol 13 (1) ◽  
pp. 77
Author(s):  
Tianyu Hu ◽  
Xiliang Sun ◽  
Yanjun Su ◽  
Hongcan Guan ◽  
Qianhui Sun ◽  
...  
Keyword(s):  
Forest Inventory ◽  
Low Cost ◽  
Canopy Cover ◽  
Tree Height ◽  
Flying Height ◽  
Tree Level ◽  
Forest Site ◽  
Lidar System ◽  
Individual Tree ◽  
Gap Fraction

Accurate and repeated forest inventory data are critical to understand forest ecosystem processes and manage forest resources. In recent years, unmanned aerial vehicle (UAV)-borne light detection and ranging (lidar) systems have demonstrated effectiveness at deriving forest inventory attributes. However, their high cost has largely prevented them from being used in large-scale forest applications. Here, we developed a very low-cost UAV lidar system that integrates a recently emerged DJI Livox MID40 laser scanner (~$600 USD) and evaluated its capability in estimating both individual tree-level (i.e., tree height) and plot-level forest inventory attributes (i.e., canopy cover, gap fraction, and leaf area index (LAI)). Moreover, a comprehensive comparison was conducted between the developed DJI Livox system and four other UAV lidar systems equipped with high-end laser scanners (i.e., RIEGL VUX-1 UAV, RIEGL miniVUX-1 UAV, HESAI Pandar40, and Velodyne Puck LITE). Using these instruments, we surveyed a coniferous forest site and a broadleaved forest site, with tree densities ranging from 500 trees/ha to 3000 trees/ha, with 52 UAV flights at different flying height and speed combinations. The developed DJI Livox MID40 system effectively captured the upper canopy structure and terrain surface information at both forest sites. The estimated individual tree height was highly correlated with field measurements (coniferous site: R2 = 0.96, root mean squared error/RMSE = 0.59 m; broadleaved site: R2 = 0.70, RMSE = 1.63 m). The plot-level estimates of canopy cover, gap fraction, and LAI corresponded well with those derived from the high-end RIEGL VUX-1 UAV system but tended to have systematic biases in areas with medium to high canopy densities. Overall, the DJI Livox MID40 system performed comparably to the RIEGL miniVUX-1 UAV, HESAI Pandar40, and Velodyne Puck LITE systems in the coniferous site and to the Velodyne Puck LITE system in the broadleaved forest. Despite its apparent weaknesses of limited sensitivity to low-intensity returns and narrow field of view, we believe that the very low-cost system developed by this study can largely broaden the potential use of UAV lidar in forest inventory applications. This study also provides guidance for the selection of the appropriate UAV lidar system and flight specifications for forest research and management.

scholarly journals Adjudicating Perspectives on Forest Structure: How Do Airborne, Terrestrial, and Mobile Lidar-Derived Estimates Compare?

2021 ◽  
Vol 13 (12) ◽  
pp. 2297
Author(s):  
Jonathon J. Donager ◽  
Andrew J. Sánchez Meador ◽  
Ryan C. Blackburn
Keyword(s):  
Ponderosa Pine ◽  
Laser Scanning ◽  
Canopy Cover ◽  
Basal Area ◽  
Tree Height ◽  
Absolute Error ◽  
Forest Monitoring ◽  
Individual Tree ◽  
Structural Configurations ◽  
Individual Trees

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.

scholarly journals Direct and indirect effects of environmental limitations on white spruce xylem anatomy at treeline

2021 ◽  
Author(s):  
Timo Pampuch ◽  
Mario Trouillier ◽  
Alba Anadon-Rosell ◽  
Jelena Lange ◽  
Martin Wilmking
Keyword(s):  
Tree Growth ◽  
Environmental Conditions ◽  
Indirect Effects ◽  
Tree Height ◽  
White Spruce ◽  
Vegetation Period ◽  
Lumen Diameter ◽  
Xylem Anatomy ◽  
Direct And Indirect Effects ◽  
Mixed Effect

<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>

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