scholarly journals Height-diameter allometry for tropical forest in northern Amazonia

PLoS ONE ◽  
2021 ◽  
Vol 16 (12) ◽  
pp. e0255197
Author(s):  
Robson Borges de Lima ◽  
Eric Bastos Görgens ◽  
Fernando Elias ◽  
Jadson Coelho de Abreu ◽  
Aldine Luiza Baia ◽  
...  
Keyword(s):  
New Technologies ◽  
Environmental Variability ◽  
Forest Biomass ◽  
Tree Height ◽  
Weibull Model ◽  
Accurate Estimation ◽  
Individual Tree ◽  
Allometric Models ◽  
True Tree ◽  
Tree Height Growth

Height measurements are essential to manage and monitor forest biomass and carbon stocks. However, accurate estimation of this variable in tropical ecosystems is still difficult due to species heterogeneity and environmental variability. In this article, we compare and discuss six nonlinear allometric models parameterized at different scales (local, regional and pantropical). We also evaluate the height measurements obtained in the field by the hypsometer when compared with the true tree height. We used a dataset composed of 180 harvested trees in two distinct areas located in the Amapá State. The functional form of the Weibull model was the best local model, showing similar performance to the pantropical model. The inaccuracy detected in the hypsometer estimates reinforces the importance of incorporating new technologies in measuring individual tree heights. Establishing accurate allometric models requires knowledge of ecophysiological and environmental processes that govern vegetation dynamics and tree height growth. It is essential to investigate the influence of different species and ecological gradients on the diameter/height ratio.

scholarly journals Height-diameter allometry for tropical forest in northern Amazonia

2021 ◽  
Author(s):  
Robson Borges de Lima ◽  
Eric Bastos Görgens ◽  
Fernando Elias ◽  
Jadson Coelho de Abreu ◽  
Aldine Luiza Baia ◽  
...  
Keyword(s):  
New Technologies ◽  
Environmental Variability ◽  
Forest Biomass ◽  
Tree Height ◽  
Weibull Model ◽  
Accurate Estimation ◽  
Individual Tree ◽  
Allometric Models ◽  
True Tree ◽  
Tree Height Growth

Height measurements are essential to manage and monitor forest biomass and carbon stocks. However, accurate estimation of this variable in tropical ecosystems is still difficult due to species heterogeneity and environmental variability. In this article, we compare and discuss six nonlinear allometric models parameterized at different scales (local, regional and pantropical). We also evaluate the height measurements obtained in the field by the hypsometer when compared with the true tree height. We used a dataset composed of 180 harvested trees in two distinct areas located in the Amapá State. The functional form of the Weibull model was the best local model, showing similar performance to the pantropical model. The inaccuracy detected in the hypsometer estimates reinforces the importance of incorporating new technologies in measuring individual tree heights. Establishing accurate allometric models requires knowledge of ecophysiological and environmental processes that govern vegetation dynamics and tree height growth. It is essential to investigate the influence of different species and ecological gradients on the diameter/height ratio.

Genetic resistance to western gall rust in jack pine and its relationship with tree height growth

2015 ◽  
Vol 45 (8) ◽  
pp. 970-977 ◽  
Author(s):  
Y.H. Weng ◽  
P. Lu ◽  
Q.F. Meng ◽  
M. Krasowski
Keyword(s):  
Growth Traits ◽  
Tree Height ◽  
Jack Pine ◽  
Height Growth ◽  
Progeny Testing ◽  
Gene Effects ◽  
Individual Tree ◽  
Improvement Programs ◽  
Heritability Estimates ◽  
Tree Height Growth

Developing resistance to western gall rust (WGR) is important for maintaining healthy and productive jack pine plantations. In this study, we estimated genetic parameters of resistance to WGR and its relationship with tree height growth, based on data collected from three second-generation full-sib progeny testing series of jack pine planted in New Brunswick, Canada. Results indicated that (i) resistance to WGR in jack pine was controlled by both additive and dominance gene effects, with the latter playing a greater role; (ii) narrow-sense heritability estimates for resistance to WGR were low (mean = 0.05; series range = 0.00∼0.09), and broad-sense heritability estimates were moderate on an individual-tree basis (mean = 0.53) and considerably higher on the full-sib family mean basis (mean = 0.87); (iii) additive genetic correlation between tree height growth and WGR incidence was low (≤0.06) in two series and only slightly higher and favorable (–0.19) in one series, suggesting that selection on growth traits would not negatively affect WGR resistance; and (iv) mid-parental additive genetic and dominance effects on WGR were empirically correlated (>0.65), indicating that incorporating breeding for WGR resistance into current jack pine tree improvement programs with a seed orchard approach could partly capture the benefit from dominance effects. Although genetic gains in WGR resistance could be realized through various breeding and deployment schemes, it appeared that rapid improvement could be achieved through backward selection on full-sib family means.

Climate-based Allometric Biomass Equations for Five Major Canadian Timber Species

2021 ◽  
Author(s):  
Kun Xu ◽  
Jinghe Jiang ◽  
Fangliang He
Keyword(s):  
Aboveground Biomass ◽  
Forest Biomass ◽  
Allometric Equations ◽  
Accurate Estimation ◽  
Biomass Estimation ◽  
Change Scenario ◽  
Mean Annual Temperature ◽  
Timber Species ◽  
Trembling Aspen ◽  
Allometric Models

Accurate estimation of forest biomass is essential to quantify the role forests play at balancing terrestrial carbon. Allometric equations based on tree size have been used for this purpose worldwide. There is little quantitative understanding on how environmental variation may affect tree allometries. Even less known is how to incorporate environmental factors into such equations to improve estimation. Here we tested the effects of climate on tree allometric equations and proposed to model forest biomass by explicitly incorporating climatic factors. Among the five major Canadian timber species tested, the incorporation of climate was not found to improve the allometric models. For trembling aspen and tamarack, the residuals of their conventional allometric models were found strongly related to frost-free period and mean annual temperature, respectively. The predictions of the two best climate-based models were significantly improved, which indicate that trembling aspen and tamarack store more aboveground biomass when growing in warmer than in colder regions. We showed that, under the RCP4.5 modest climate change scenario, there would be a 10% underestimation of aboveground biomass for these two species if the conventional non-climate models would still be in use in 2030. This study suggests the necessity to proactively develop climate-based allometric equations for more accurate and reliable forest biomass estimation.

scholarly journals Modeling Effects of Overstory Density and Competing Vegetation on Tree Height Growth

2008 ◽  
Vol 54 (1) ◽  
pp. 107-122
Author(s):  
Christian Salas ◽  
Albert R. Stage ◽  
Andrew P. Robinson
Keyword(s):  
Habitat Type ◽  
Predictor Variable ◽  
Tree Height ◽  
Height Growth ◽  
Tree Age ◽  
Individual Tree ◽  
Vegetation Control ◽  
Index Site ◽  
Linear Differential ◽  
Tree Height Growth

Abstract We developed and evaluated an individual-tree height growth model for Douglas-fir [Pseudotsuga menziesii (Mirbel) Franco] in the Inland Northwest United States. The model predicts growth for all tree sizes continuously, rather than requiring a transition between independent models for juvenile and mature growth phases. The model predicts the effects of overstory and understory vegetative competition on height growth. Our model requires attained height rather than tree age as a predictor variable, thereby avoiding the problems of site index. Site effects are introduced as a function of ecological habitat type, elevation, aspect, and slope. We used six data sets totaling 3,785 trees in 314 plots. The structure of the data and the model indicated the need for a mixed-effects, nonlinear modeling approach using maximum likelihood in a linear differential equation with a power transformation. Behavior of the model was analyzed using a state-space approach. Our results show that both overstory and understory density affect height growth, allowing a manager to make informed decisions about vegetation control.

scholarly journals Allometric Equations for Estimating Aboveground Biomass of Eucalyptus urophylla S.T. Blake in East Nusa Tenggara

2021 ◽  
Vol 27 (1) ◽  
pp. 24-31
Author(s):  
R Sadono ◽  
◽  
W Wahyu ◽  
F Idris
Keyword(s):  
Aboveground Biomass ◽  
Tree Height ◽  
Allometric Equation ◽  
Allometric Equations ◽  
Accurate Estimation ◽  
Eucalyptus Urophylla ◽  
Individual Tree ◽  
Eucalyptus Plantation ◽  
Diameter At Breast Height ◽  
Breast Height

Understanding the essential contribution of eucalyptus plantation for industry development and climate change mitigation requires the accurate quantification of aboveground biomass at the individual tree species level. However, the direct measurement of aboveground biomass by destructive method is high cost and time consuming. Therefore, developing allometric equations is necessary to facilitate this effort. This study was designed to construct the specific allometric models for estimating aboveground biomass of Eucalyptus urophylla in East Nusa Tenggara. Forty two sample trees were utilized to develop allometric equations using regression analysis. Several parameters were selected as predictor variables, i.e. diameter at breast height (D), quadrat diameter at breast height combined with tree height (D2H), as well as D and H separately. Results showed that the mean aboveground biomass of E. urophylla was 143.9 ± 19.44 kg tree-1. The highest biomass were noted in stem (80.06%), followed by bark (11.89%), branch (4.69%), and foliage (3.36%). The relative contribution of stem to total aboveground biomass improved with the increasing of diameter class while the opposite trend was recorded in bark, branch, and foliage. The equation lnŶ = lna + b lnD was best and reliable for estimating the aboveground biomass of E. urophylla since it provided the highest accurate estimation (91.3%) and more practical than other models. Referring to these findings, this study concluded the use of allometric equation was reliable to support more efficient forest mensuration in E. urophylla plantation.

scholarly journals ESTIMATION OF ABOVE GROUND FOREST BIOMASS USING ULTRA HIGH RESOLUTION UAV IMAGES: A CASE STUDY FROM BARANDABHAR FOREST, NEPAL

2019 ◽  
Vol XLII-5/W3 ◽  
pp. 77-83
Author(s):  
U. S. Panday ◽  
N. Shrestha ◽  
S. Maharjan
Keyword(s):  
High Resolution ◽  
Forest Biomass ◽  
Tree Height ◽  
Dry Weight ◽  
Accurate Estimation ◽  
Projection Area ◽  
Crown Cover ◽  
Crown Projection Area ◽  
Uav Images

Abstract. Forest biomass is the sum of above ground living organic material contained in trees which is expressed as dry weight per unit area. Forest biomass acts as substantial terrestrial carbon sinks, they are estimated to absorb 2.7 Petagrams of carbon per year, as such accurate estimation of forest carbon stock is very important. The estimation of biomass is also important because of its application in commercial exploitation as well as in global carbon cycle. Particularly in the latter context, the estimation of the total above-ground biomass (TAGB) with sufficient accuracy is vital in reporting the spatial and temporal state of forest under the United Nations Framework Convention on Climate Change (UNFCCC), Reducing Emissions from Deforestation in Developing Countries (REDD). In this research, tree height, DBH and crown cover were measured using field instruments. Individual ultra-high-resolution UAV images acquired using customized Visible-NIR, were georeferenced and tree crown were extracted using multi-resolution segmentation. A regression equation between field measured biomass and Crown Projection Area (CPA) was developed. The paper presents results from Barandabhar Forest of Chitwan District, Nepal. RMSE of ortho-mosaic was found to be 18 cm. While R2 value of 89% was obtained for relationship between DBH and biomass, that of 61% was attained for relationship between CPA and biomass.

scholarly journals Leaf Abundance Affects Tree Height Estimation Derived from UAV Images

Forests ◽  
2019 ◽  
Vol 10 (10) ◽  
pp. 931 ◽  
Author(s):  
Hongyu Huang ◽  
Shaodong He ◽  
Chongcheng Chen
Keyword(s):  
Point Cloud ◽  
Tree Height ◽  
Forest Monitoring ◽  
Accurate Estimation ◽  
Structural Parameter ◽  
Deciduous Trees ◽  
Individual Tree ◽  
Height Estimation ◽  
Uav Images ◽  
Mean Square Errors

Tree height is an important vegetative structural parameter, and its accurate estimation is of significant ecological and commercial value. We collected UAV images of six tree species distributed throughout a subtropical campus during three periods from March to late May, during which some deciduous trees shed all of their leaves and then regrew, while other evergreen trees kept some of their leaves. The UAV imagery was processed by computer vision and photogrammetric software to generate a three-dimensional dense point cloud. Individual tree height information extracted from the dense photogrammetric point cloud was validated against the manually measured reference data. We found that the number of leaves in the canopy affected tree height estimation, especially for deciduous trees. During leaf-off conditions or the early season, when leaves were absent or sparse, it was difficult to reconstruct the 3D canopy structure fully from the UAV images, thus resulting in the underestimation of tree height; the accuracy improved considerably when there were more leaves. For Terminalia mantaly and Ficus virens, the root mean square errors (RMSEs) of tree height estimation reduced from 2.894 and 1.433 m (leaf-off) to 0.729 and 0.597 m (leaf-on), respectively. We provide direct evidence that leaf-on conditions have a positive effect on tree height measurements derived from UAV photogrammetric point clouds. This finding has important implications for forest monitoring, management, and change detection analysis.

scholarly journals The Importance of Tree Height in Estimating Individual Tree Biomass while Considering Errors in Measurements and Allometric Models

2018 ◽  
Vol 40 (1) ◽  
Author(s):  
Thuch Phalla ◽  
Tetsuji Ota ◽  
Nobuya Mizoue ◽  
Tsuyoshi Kajisa ◽  
Shigejiro Yoshida ◽  
...  
Keyword(s):  
Tree Height ◽  
Tree Biomass ◽  
Individual Tree ◽  
Allometric Models

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.

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