scholarly journals Height-Diameter Allometry for Tree Species in Tanzania Mainland

2019 ◽  
Vol 2019 ◽  
pp. 1-17 ◽  
Author(s):  
W. A. Mugasha ◽  
E. W. Mauya ◽  
A. M. Njana ◽  
K. Karlsson ◽  
R. E. Malimbwi ◽  
...  
Keyword(s):  
Forest Structure ◽  
Forest Type ◽  
Model Development ◽  
Basal Area ◽  
Tree Height ◽  
Forest Stand ◽  
Miombo Woodlands ◽  
Mixed Effect ◽  
Nonlinear Mixed Effect ◽  
Stand Attributes

Total tree height (H) and diameter at beast height (D) are important independent variables in predicting volume, biomass, and other forest stand attributes. However, unlikeDmeasurement, which is easy to measure with high accuracy,Hmeasurement is laborious. This study, therefore, developedH-Drelationships for ten different forest types in Tanzania Mainland. Extents in which climate and forest stand variables explain the variation inH-Dallometry were also assessed. A total of 31782 sample trees covering miombo woodlands, humid montane, lowland forests, bushlands, grasslands, mangroves, cultivated land, wetlands forests, and pines andEucalyptusspecies plantations were used for model development. TheHestimating model without climate and forest stand variables referred herein as “base model” was first developed followed by “generalized model” which included climate and stand variables. All the data were fitted using nonlinear mixed effect modelling approach. Results indicated that generalizedHestimating models had better fit than the base models. We therefore confirm a significant contribution of climate and forest structure variables in improvingH-Dallometry. Among the forest structure variables, basal area (BA) was far more important explanatory variable than other variables. In addition, it was found that the mean treeHtends to increase with the increase of mean precipitation (PRA). We therefore conclude that forest specific generalizedHmodel is to be applied when predictingH. When forest type information is not available, generalized regional model may be applied. Base model may be applied when forest stand or climate information are missing.

scholarly journals A Multivariate Hybrid Stochastic Differential Equation Model for Whole-Stand Dynamics

Mathematics ◽  
2020 ◽  
Vol 8 (12) ◽  
pp. 2230
Author(s):  
Petras Rupšys ◽  
Martynas Narmontas ◽  
Edmundas Petrauskas
Keyword(s):  
Differential Equation ◽  
Stochastic Differential Equation ◽  
Diffusion Processes ◽  
Basal Area ◽  
Equation Model ◽  
Forest Stand ◽  
Growth And Yield ◽  
Stand Dynamics ◽  
Mixed Effect ◽  
Pine Tree

The growth and yield modeling of a forest stand has progressed rapidly, starting from the generalized nonlinear regression models of uneven/even-aged stands, and continuing to stochastic differential equation (SDE) models. We focus on the adaptation of the SDEs for the modeling of forest stand dynamics, and relate the tree and stand size variables to the age dimension (time). Two different types of diffusion processes are incorporated into a hybrid model in which the shortcomings of each variable types can be overcome to some extent. This paper presents the hybrid multivariate SDE regarding stand basal area and volume models in a forest stand. We estimate the fixed- and mixed-effect parameters for the multivariate hybrid stochastic differential equation using a maximum likelihood procedure. The results are illustrated using a dataset of measurements from Mountain pine tree (Pinus mugo Turra).

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

scholarly journals The importance of forest structure to biodiversity–productivity relationships

2017 ◽  
Vol 4 (1) ◽  
pp. 160521 ◽  
Author(s):  
Friedrich J. Bohn ◽  
Andreas Huth
Keyword(s):  
Species Distribution ◽  
Forest Structure ◽  
Basal Area ◽  
Tree Height ◽  
National Forest Inventory ◽  
National Forest ◽  
Forest Stands ◽  
Annual Productivity ◽  
Structure Indices ◽  
Modelling Approach

While various relationships between productivity and biodiversity are found in forests, the processes underlying these relationships remain unclear and theory struggles to coherently explain them. In this work, we analyse diversity–productivity relationships through an examination of forest structure (described by basal area and tree height heterogeneity). We use a new modelling approach, called ‘forest factory’, which generates various forest stands and calculates their annual productivity (above-ground wood increment). Analysing approximately 300 000 forest stands, we find that mean forest productivity does not increase with species diversity. Instead forest structure emerges as the key variable. Similar patterns can be observed by analysing 5054 forest plots of the German National Forest Inventory. Furthermore, we group the forest stands into nine forest structure classes, in which we find increasing, decreasing, invariant and even bell-shaped relationships between productivity and diversity. In addition, we introduce a new index, called optimal species distribution, which describes the ratio of realized to the maximal possible productivity (by shuffling species identities). The optimal species distribution and forest structure indices explain the obtained productivity values quite well ( R 2 between 0.7 and 0.95), whereby the influence of these attributes varies within the nine forest structure classes.

scholarly journals A meta-analysis on the impacts of partial cutting on forest structure and carbon storage

2013 ◽  
Vol 10 (1) ◽  
pp. 787-813 ◽  
Author(s):  
D. Zhou ◽  
S. Q. Zhao ◽  
S. Liu ◽  
J. Oeding
Keyword(s):  
Forest Structure ◽  
Forest Floor ◽  
Management Practices ◽  
Forest Type ◽  
Meta Analysis ◽  
Mineral Soil ◽  
Basal Area ◽  
Partial Cutting ◽  
Soil C ◽  
C Storage

Abstract. Partial cutting, which removes some individual trees from a forest, is one of the major and widespread forest management practices that can significantly alter both forest structure and carbon (C) storage. Using 746 observations from 82 publications, we synthesized the impacts of partial cutting on three variables associated with forest structure (i.e. mean annual growth of diameter at breast height (DBH), basal area (BA), and volume) and four variables related to various C stock components (i.e. aboveground biomass C (AGBC), understory C, forest floor C, and mineral soil C). Results shows that the growth of DBH elevated by 112% after partial cutting, compared to the uncut control, while stand BA and volume reduced immediately by 34% and 29%, respectively. On average, partial cutting reduced AGBC by 43%, increased understory C storage by 392%, but did not show significant effects on C storages on forest floor and in mineral soil. All the effects on DBH growth, stand BA, volume, and AGBC intensified linearly with cutting intensity (CI) and decreased linearly with the number of recovery years (RY). In addition to the strong impacts of CI and RY, other factors such as climate zone and forest type also affected forest responses to partial cutting. The data assembled in this synthesis were not sufficient to determine how long it would take for a complete recovery after cutting because long-term experiments were rare. Future efforts should be tailored to increase the duration of the experiments and balance geographic locations of field studies.

scholarly journals Factors Influencing Liana Species Richness and Structure following Anthropogenic Disturbance in a Tropical Forest, Ghana

ISRN Forestry ◽  
2013 ◽  
Vol 2013 ◽  
pp. 1-11 ◽  
Author(s):  
Patrick Addo-Fordjour ◽  
Philip El Duah ◽  
David Kafui Kudjo Agbesi
Keyword(s):  
Species Richness ◽  
Forest Structure ◽  
Forest Type ◽  
Basal Area ◽  
Forest Tree ◽  
Stepwise Multiple Regression ◽  
Importance Value Index ◽  
Importance Value ◽  
Soil Variables ◽  
Species Richness And Abundance

The study was conducted to determine the factors that influenced liana species richness and structure in forests of different disturbance intensities (high, moderate, and low disturbance forests) in the Southern Scarp Forest Reserve, Ghana. Within each forest, lianas (dbh  cm) were enumerated in six  m2 plots located along transects. Soil physicochemical properties and forest structure were determined within the plots. Liana species richness and abundance were significantly lower in the high disturbance forest () whereas basal area was significantly higher in the low disturbance forest (). Tree abundance and dbh significantly predicted liana species richness and structure in the study (). On the basis of the importance value index, three main liana communities, each corresponding with a forest type, were identified. Stepwise multiple regression analysis revealed that exchangeable magnesium and calcium, and total exchangeable bases were the main soil variables that affected liana species richness. Liana structure was influenced by the above-mentioned soil variables as well as exchangeable potassium and sodium, and pH. The present study has demonstrated that changes in liana species richness and structure following human disturbance may be due to variations in soil properties and forest structure.

Modeling of tree height–diameter relationships in the Atlantic Forest: effect of forest type on tree allometry

2020 ◽  
Vol 50 (12) ◽  
pp. 1289-1298
Author(s):  
Vinicius Costa Cysneiros ◽  
Allan Libanio Pelissari ◽  
Tatiana Dias Gaui ◽  
Luan Demarco Fiorentin ◽  
Daniel Costa de Carvalho ◽  
...  
Keyword(s):  
Atlantic Forest ◽  
Linear Models ◽  
Forest Type ◽  
Tree Height ◽  
Local Environment ◽  
Forest Types ◽  
Mixed Effect ◽  
Tree Allometry ◽  
Specific Effects ◽  
Geographical Regions

Tree height is one of the most important variables for quantitative assessment of forest stocks, but it is difficult to directly measure. Such allometric relationships of trees can vary between geographical regions, however, mainly due to climatic, edaphic, and floristic gradients. Based on the hypothesis that different forest types influence the generic modeling of tree height–diameter relationships on geographical scales, this study aimed to (i) fit equations to estimate tree height in Atlantic Forest types in the state of Rio de Janeiro, Brazil; (ii) compare efficiency and precision between generic and specific equations for forest types; and (iii) test the effect of different forest types and species on the height–diameter relationship. Four allometric models were tested for all forests (generic) and three main forest types (specific). Effects of tree size, forest types, and species on tree height estimation were analyzed using multiple linear models and mixed-effect linear models. A significant effect of forest type and species on tree height was seen, showing the need to apply local specific equations to minimize the effects that are not captured by generic equations. Differences in tree allometry between forest types were associated with temperature, rainfall, soil, and forest structure. These results confirm the effect of the local environment on the height–diameter relationship of trees as found over large scales in tropical forests.

scholarly journals Height-diameter allometry of tropical forest trees

2011 ◽  
Vol 8 (5) ◽  
pp. 1081-1106 ◽  
Author(s):  
T. R. Feldpausch ◽  
L. Banin ◽  
O. L. Phillips ◽  
T. R. Baker ◽  
S. L. Lewis ◽  
...  
Keyword(s):  
Tropical Forest ◽  
Large Scale ◽  
Amazon Basin ◽  
Stand Structure ◽  
Forest Type ◽  
Structural Characteristics ◽  
Basal Area ◽  
Tree Height ◽  
Geographic Region ◽  
True Value

Abstract. Tropical tree height-diameter (H:D) relationships may vary by forest type and region making large-scale estimates of above-ground biomass subject to bias if they ignore these differences in stem allometry. We have therefore developed a new global tropical forest database consisting of 39 955 concurrent H and D measurements encompassing 283 sites in 22 tropical countries. Utilising this database, our objectives were: 1. to determine if H:D relationships differ by geographic region and forest type (wet to dry forests, including zones of tension where forest and savanna overlap). 2. to ascertain if the H:D relationship is modulated by climate and/or forest structural characteristics (e.g. stand-level basal area, A). 3. to develop H:D allometric equations and evaluate biases to reduce error in future local-to-global estimates of tropical forest biomass. Annual precipitation coefficient of variation (PV), dry season length (SD), and mean annual air temperature (TA) emerged as key drivers of variation in H:D relationships at the pantropical and region scales. Vegetation structure also played a role with trees in forests of a high A being, on average, taller at any given D. After the effects of environment and forest structure are taken into account, two main regional groups can be identified. Forests in Asia, Africa and the Guyana Shield all have, on average, similar H:D relationships, but with trees in the forests of much of the Amazon Basin and tropical Australia typically being shorter at any given D than their counterparts elsewhere. The region-environment-structure model with the lowest Akaike's information criterion and lowest deviation estimated stand-level H across all plots to within amedian −2.7 to 0.9% of the true value. Some of the plot-to-plot variability in H:D relationships not accounted for by this model could be attributed to variations in soil physical conditions. Other things being equal, trees tend to be more slender in the absence of soil physical constraints, especially at smaller D. Pantropical and continental-level models provided less robust estimates of H, especially when the roles of climate and stand structure in modulating H:D allometry were not simultaneously taken into account.

scholarly journals Height-diameter allometry of tropical forest trees

2010 ◽  
Vol 7 (5) ◽  
pp. 7727-7793 ◽  
Author(s):  
T. R. Feldpausch ◽  
L. Banin ◽  
O. L. Phillips ◽  
T. R. Baker ◽  
S. L. Lewis ◽  
...  
Keyword(s):  
Tropical Forest ◽  
Large Scale ◽  
Amazon Basin ◽  
Stand Structure ◽  
Forest Type ◽  
Structural Characteristics ◽  
Basal Area ◽  
Tree Height ◽  
Geographic Region ◽  
True Value

Abstract. Tropical tree height-diameter (H:D) relationships may vary by forest type and region making large-scale estimates of above-ground biomass subject to bias if they ignore these differences in stem allometry. We have therefore developed a new global tropical forest database consisting of 39 955 concurrent H and D measurements encompassing 283 sites in 22 tropical countries. Utilising this database, our objectives were:   1. to determine if H:D relationships differ by geographic region and forest type (wet to dry forests, including zones of tension where forest and savanna overlap).   2. to ascertain if the H:D relationship is modulated by climate and/or forest structural characteristics (e.g. stand-level basal area, A).   3. to develop H:D allometric equations and evaluate biases to reduce error in future local-to-global estimates of tropical forest biomass. Annual precipitation coefficient of variation (PV), dry season length (SD), and mean annual air temperature (TA) emerged as key drivers of variation in H:D relationships at the pantropical and region scales. Vegetation structure also played a role with trees in forests of a high A being, on average, taller at any given D. After the effects of environment and forest structure are taken into account, two main regional groups can be identified. Forests in Asia, Africa and the Guyana Shield all have, on average, similar H:D relationships, but with trees in the forests of much of the Amazon Basin and tropical Australia typically being shorter at any given D than their counterparts elsewhere. The region-environment-structure model with the lowest Akaike's information criterion and lowest deviation estimated stand-level H across all plots to within a median –2.7 to 0.9% of the true value. Some of the plot-to-plot variability in H:D relationships not accounted for by this model could be attributed to variations in soil physical conditions. Other things being equal, trees tend to be more slender in the absence of soil physical constraints, especially at smaller D. Pantropical and continental-level models provided only poor estimates of H, especially when the roles of climate and stand structure in modulating H:D allometry were not simultaneously taken into account.

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