scholarly journals Including tree spatial extension in the evaluation of neighbourhood competition effects in Bornean rain forest

2020 ◽  
Author(s):  
David M. Newbery ◽  
Peter Stoll
Keyword(s):  
Alternative Hypothesis ◽  
Species Abundance ◽  
Abundant Species ◽  
Root Competition ◽  
Light Limitation ◽  
Tree Level ◽  
Model Parameters ◽  
Individual Tree ◽  
Stem Size ◽  
Tree Survival

AbstractClassical tree neighbourhood models use size variables acting at point distances. In a new approach here, trees were spatially extended as a function of their crown sizes, represented impressionistically as points within crown areas. Extension was accompanied by plasticity in the form of crown removal or relocation under the overlap of taller trees. Root systems were supposedly extended in a similar manner. For the 38 most abundant species in the focal size class (10 - <100 cm stem girth) in two 4-ha plots at Danum (Sabah), for periods P1 (1986-1996) and P2 (1996-2007), stem growth rate and tree survival were individually regressed against stem size, and neighbourhood conspecific (CON) and heterospecific (HET) basal areas within incremented steps in radius. Model parameters were critically assessed, and statistical robustness in the modelling set by randomization testing. Classical and extended models differed importantly in their outcomes. Crown extension weakened the relationship of CON effect on growth versus plot species’ abundance, showing that models without plasticity over-estimated negative density dependence. A significant negative trend of difference in CON effects on growth (P2 − P1) versus CON or HET effect on survival in P1 was strongest with crown extension. Model outcomes did not then support an explanation of CON and HET effects being due to (asymmetric) competition for light alone. An alternative hypothesis is that changes in CON effects on small trees, largely incurred by a drought phase (relaxing light limitation) in P2, and following the more shaded (suppressing) conditions in P1, were likely due to species-specific (symmetric) root competition and mycorrhizal processes. The very high variation in neighbourhood composition and abundances led to a strong ‘neighbourhood stochasticity’, and hence to largely idiosyncratic species’ responses. A need to much better understand the roles of rooting structure and processes at the individual tree level was highlighted.

scholarly journals An integrated system for modeling tree and stand survival

2017 ◽  
Vol 47 (10) ◽  
pp. 1405-1409 ◽  
Author(s):  
Quang V. Cao
Keyword(s):  
Survival Probability ◽  
Mathematical Structure ◽  
Survival Model ◽  
Integrated System ◽  
Survival Models ◽  
Tree Level ◽  
Individual Tree ◽  
Tree Survival ◽  
Different Levels ◽  
Model Approach

Traditionally, separate models have been used to predict the number of trees per unit area (stand-level survival) and the survival probability of an individual tree (tree-level survival) at a certain age. This study investigated the development of integrated systems in which survival models at different levels of resolution are related in a mathematical structure. Two approaches for modeling tree and stand survival were considered: deriving a stand-level survival model from a tree-level survival model (approach 1) and deriving a tree survival model from a stand survival model (approach 2). Both approaches rely on finding a tree diameter that yields a tree survival probability equal to the stand-level survival probability. The tree and stand survival models from either approach are conceptually compatible with each other but not numerically compatible. Parameters of these models can be estimated either sequentially or simultaneously. Results indicated that approach 2, with parameters estimated sequentially (first from the stand survival model and then from the derived tree survival model), performed best in predicting both tree- and stand-level survival. Although disaggregation did not help improve prediction of tree-level survival, this method can be used when numerical consistency between stand and tree survival is desired.

scholarly journals Tree Species Traits Determine the Success of LiDAR-Based Crown Mapping in a Mixed Temperate Forest

2020 ◽  
Vol 12 (2) ◽  
pp. 309 ◽  
Author(s):  
Jack H. Hastings ◽  
Scott V. Ollinger ◽  
Andrew P. Ouimette ◽  
Rebecca Sanders-DeMott ◽  
Michael W. Palace ◽  
...  
Keyword(s):  
Temperate Forest ◽  
Spectral Characteristics ◽  
Species Abundance ◽  
Remote Sensing Data ◽  
Parameter Tuning ◽  
Species Traits ◽  
Tree Level ◽  
Species Evenness ◽  
Individual Tree ◽  
Crown Delineation

The ability to automatically delineate individual tree crowns using remote sensing data opens the possibility to collect detailed tree information over large geographic regions. While individual tree crown delineation (ITCD) methods have proven successful in conifer-dominated forests using Light Detection and Ranging (LiDAR) data, it remains unclear how well these methods can be applied in deciduous broadleaf-dominated forests. We applied five automated LiDAR-based ITCD methods across fifteen plots ranging from conifer- to broadleaf-dominated forest stands at Harvard Forest in Petersham, MA, USA, and assessed accuracy against manual delineation of crowns from unmanned aerial vehicle (UAV) imagery. We then identified tree- and plot-level factors influencing the success of automated delineation techniques. There was relatively little difference in accuracy between automated crown delineation methods (51–59% aggregated plot accuracy) and, despite parameter tuning, none of the methods produced high accuracy across all plots (27—90% range in plot-level accuracy). The accuracy of all methods was significantly higher with increased plot conifer fraction, and individual conifer trees were identified with higher accuracy (mean 64%) than broadleaf trees (42%) across methods. Further, while tree-level factors (e.g., diameter at breast height, height and crown area) strongly influenced the success of crown delineations, the influence of plot-level factors varied. The most important plot-level factor was species evenness, a metric of relative species abundance that is related to both conifer fraction and the degree to which trees can fill canopy space. As species evenness decreased (e.g., high conifer fraction and less efficient filling of canopy space), the probability of successful delineation increased. Overall, our work suggests that the tested LiDAR-based ITCD methods perform equally well in a mixed temperate forest, but that delineation success is driven by forest characteristics like functional group, tree size, diversity, and crown architecture. While LiDAR-based ITCD methods are well suited for stands with distinct canopy structure, we suggest that future work explore the integration of phenology and spectral characteristics with existing LiDAR as an approach to improve crown delineation in broadleaf-dominated stands.

Stand, species, and tree dynamics of an uneven-aged, mixed conifer forest type

1995 ◽  
Vol 25 (5) ◽  
pp. 803-812 ◽  
Author(s):  
John P. McTague ◽  
William F. Stansfield
Keyword(s):  
Tree Mortality ◽  
Forest Type ◽  
Species Abundance ◽  
Basal Area ◽  
Logistic Function ◽  
Conifer Forest ◽  
Individual Tree ◽  
Recovery Method ◽  
Parameter Recovery ◽  
Tree Survival

Stand-level equations are presented that project future merchantable tree survival, pole-tree basal area, and sawtimber basal area. Total basal area (excluding ingrowth) is the sum of the pole-tree and sawtimber components. Ratio equations are used for eight species (seven softwoods and one hardwood) to compute the change in species abundance and species basal area over time. Individual-tree mortality is predicted with a logistic function, while individual-tree diameter growth is predicted as a function of stand and individual-tree attributes. The individual-tree and species-level equations are adjusted so that tree frequency and basal area are consistent with the stand-level projection equations. Total ingrowth is computed with a stand-level projection equation and is distributed with a parameter recovery method using the uniform distribution. The presence or absence of ingrowth for a given species is determined with a discriminant function, while the proportion of total ingrowth allocated to a species is predicted with a logistic function.

Long-term trends in tree mortality rates in the Alberta foothills are driven by stand development

2012 ◽  
Vol 42 (9) ◽  
pp. 1687-1696 ◽  
Author(s):  
H.C. Thorpe ◽  
L.D. Daniels
Keyword(s):  
Mortality Risk ◽  
Forest Structure ◽  
Tree Mortality ◽  
Mortality Rates ◽  
Tree Level ◽  
Model Parameters ◽  
Stem Density ◽  
Stand Development ◽  
Individual Tree ◽  
Local Competition

Tree mortality is a critical driver of stand dynamics, influencing forest structure, composition, and capacity for ecosystem service provision. In recent years, tree mortality has been gaining attention as dramatic occurrences of forest die-off have been linked to climate change. Using permanent sample plot data, we examined tree mortality rates in mature forests in west-central Alberta from 1956 to 2007. We quantified mortality risk at an individual-tree level as a function of size, local competition, and calendar year, a proxy for increasing temperature, and used maximum likelihood methods to estimate species-specific model parameters. Tree size and local competition were both important predictors of mortality risk. However, once these factors were included in our model, no additional variation could be attributed to calendar year, indicating that the trend of increasing tree mortality over time found in our raw data is primarily a result of stand development processes. This finding is supported by the changes in forest structure and composition that we documented over the study period. Stands generally increased in basal area and stem density, and lodgepole pine ( Pinus contorta var. latifolia Engelm. ex S. Watson) declined in abundance relative to the more shade-tolerant black spruce ( Picea mariana (Mill.) B.S.P.) and white spruce ( Picea glauca (Moench) Voss). Our results indicate that warming-related changes did not affect background tree mortality rates in mature forests in the Alberta foothills over the study period. These results also provide critical information for future studies of forest dynamics in the region.

scholarly journals A method to derive a tree survival model from any existing stand survival model

2019 ◽  
Vol 49 (12) ◽  
pp. 1598-1603 ◽  
Author(s):  
Quang V. Cao
Keyword(s):  
Survival Data ◽  
Survival Model ◽  
Integrated System ◽  
Survival Models ◽  
Tree Level ◽  
Survival Prediction ◽  
Tree Model ◽  
Simple Method ◽  
Individual Tree ◽  
Tree Survival

This study addresses a situation in which a forest manager has been using a whole-stand model that seems to predict well for their stands and now wants to derive an individual-tree model from it to form an integrated system that can perform well at both stand and tree levels. A simple method was developed to derive tree survival models from three existing stand-level survival models. The derived tree survival models were based on the difference between the diameter of a given tree and the diameter at which tree and stand survival probabilities are equal. For stand survival prediction, each stand model performed less adequately than its derived tree model, and one of the derived tree survival models was the best overall. For tree survival prediction, the same derived tree model also performed best overall. Even though only three stand-level survival models were considered in this study, the method presented here should be applicable to any stand survival model. When no tree survival data were available, tree survival models derived from stand survival models ranked lowest in terms of performance but produced acceptable evaluation statistics for predicting tree-level survival.

scholarly journals Deriving a Tree Growth Model from Any Existing Stand Growth Model

2021 ◽  
Author(s):  
Quang V. Cao
Keyword(s):  
Growth Model ◽  
Tree Growth ◽  
Poor Performance ◽  
Tree Level ◽  
Growth Data ◽  
Tree Model ◽  
Individual Tree ◽  
Tree Survival ◽  
Tree Models ◽  
Level Model

In this study, a new method was developed to derive a tree survival and diameter growth model from any existing stand-level model, without the need for individual-tree growth data. Predictions from the derived tree model are constrained to match number of trees and basal area per ha as outputted by the stand model. The tree models derived from three different stand models were evaluated against a tree model, in both unadjusted and disaggregated forms. For the same stand-level model, the derived tree model outperformed its counterpart, the disaggregated tree model. Furthermore, except for one stand model with poor performance, the tree models derived from the remaining two stand models delivered comparable results to those obtained from the unadjusted tree model. The tree model derived from one stand model even performed slightly better than the unadjusted tree model. This is significant because the coefficients of the unadjusted and disaggregated tree models had to be estimated from tree-level growth data, whereas the derived tree model required no tree growth data at all. The methodology presented in this study should be applicable when there is no ingrowth or recruitment.

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 SISFLOR: A COMPUTATIONAL SYSTEM TO DETERMINE THE OPTIMAL TREE BUCKING

2020 ◽  
Vol 28 ◽  
pp. 192-201
Author(s):  
Rodrigo Freitas Silva ◽  
Marcelo Otone Aguiar ◽  
Mayra Luiza Marques Da Silva ◽  
Gilson Fernandes Da Silva ◽  
Adriano Ribeiro De Mendonça
Keyword(s):  
Optimization Technique ◽  
Wood Products ◽  
Tree Level ◽  
Economic Losses ◽  
Computational System ◽  
Individual Tree ◽  
Optimal Tree ◽  
Cutting Pattern ◽  
Forest Enterprises ◽  
The Individual

A continuously competitive forest market and tied to the demands for wood products promotes the study and development of applications that increase the revenue of the forest enterprises. At harvesting, the cutting pattern (forest assortment) in which the trees are traced is traditionally determined by the experience of the chainsaw operator without using any optimization technique, which may result in economic losses in relation to the commercialized products. In general, there are numerous distinct assortments that can be chosen and hardly processed by a brute-force algorithm. This is the forest assortment problem at the individual tree level with the objetice of maximizing the commercial values of the felled trees. stem-level bucking optimization problem. The aim is to maximize the sales value of harvested trees. Dynamic Programming (DP) is an efficient optimization technique to determine the optimum bucking tree as it significantly reduces the number of calculations to be made. Thus, the objective of this work was to develop a modern and intuitive computational system that is able to find the optimum tree stem bucking through DP to help companies over the bole tracing, therefore, characterizing itself as a tool that supports decision making. After the execution of the system, the optimum assortment is shown by sequentially detailing all products that should be removed from the analyzed bole as well as their respective volumes and revenue.

scholarly journals Spatial Models With Inter-Tree Competition From Airborne Laser Scanning Improve Estimates of Genetic Variance

2021 ◽  
Vol 11 ◽  
Author(s):  
David Pont ◽  
Heidi S. Dungey ◽  
Mari Suontama ◽  
Grahame T. Stovold
Keyword(s):  
Laser Scanning ◽  
Management Practices ◽  
Spatial Models ◽  
Airborne Laser Scanning ◽  
Tree Level ◽  
Residual Variance ◽  
Spatial Effects ◽  
Individual Tree ◽  
Airborne Laser ◽  
Individual Trees

Phenotyping individual trees to quantify interactions among genotype, environment, and management practices is critical to the development of precision forestry and to maximize the opportunity of improved tree breeds. In this study we utilized airborne laser scanning (ALS) data to detect and characterize individual trees in order to generate tree-level phenotypes and tree-to-tree competition metrics. To examine our ability to account for environmental variation and its relative importance on individual-tree traits, we investigated the use of spatial models using ALS-derived competition metrics and conventional autoregressive spatial techniques. Models utilizing competition covariate terms were found to quantify previously unexplained phenotypic variation compared with standard models, substantially reducing residual variance and improving estimates of heritabilities for a set of operationally relevant traits. Models including terms for spatial autocorrelation and competition performed the best and were labelled ACE (autocorrelation-competition-error) models. The best ACE models provided statistically significant reductions in residuals ranging from −65.48% for tree height (H) to −21.03% for wood stiffness (A), and improvements in narrow sense heritabilities from 38.64% for H to 14.01% for A. Individual tree phenotyping using an ACE approach is therefore recommended for analyses of research trials where traits are susceptible to spatial effects.

Sign in / Sign up

Export Citation Format

Share Document