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... Stand productivity depends directly on the inherent characteristics of the site, such as soil type, temperature, solar radiation, altitude, climatic variables, etc., as well as those characteristics that affect its growth and yield [10][11][12][13]. Previous studies have reported better forest site productivity classification when the models include climatic and topographic variables to determine the factors that affect tree development [14][15][16][17]. ...
... Patula pine has the highest commercial value for timber production in the region [28,29]. characteristics that affect its growth and yield [10][11][12][13]. Previous studies have reported better forest site productivity classification when the models include climatic and topographic variables to determine the factors that affect tree development [14][15][16][17]. ...
... By incorporating topographic and climatic variables in dominant height models, several learning opportunities appear; e.g., Mensah et al. [12] concluded this type of model represents an opportunity to learn about the behavior of forests in a changing environment. Another study, Leites et al. [76] mentioned that these models allow for a description of the response of the relationships among site variables, and at the same time, improved the prediction of forest site productivity [16] by distinguishing the abiotic feature differences between sites [77]. ...
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Sustainable forest management requires accurate biometric tools to estimate forest site quality. This is particularly relevant for prescribing adequate silvicultural treatments of forest management planning. The aim of this research was to incorporate topographic and climatic variables into dominant height growth models of patula pine stands to improve the estimation of forest stand productivity. Three generalized algebraic difference approach (GADA) models were fit to a dataset from 66 permanent sampling plots, with six re-measurements and 77 temporary inventory sampling plots established on forest stands of patula pine. The nested iterative approach was used to fit the GADA models, and goodness-of-fit statistics such as the root mean square error, Akaike’s Information Criterion, and Bias were used to assess their performance. A Hossfeld IV GADA equation type that includes altitude, slope percentage, mean annual precipitation, and mean annual minimum temperature produced the best fit and estimation. Forest site productivity was negatively affected by altitude, while increasing the mean annual minimum temperature suggested the fastest-growing rates for dominant tree height.
... The growth-hydraulic model shows that the numerical value of the H vs. D scaling exponent differs across species and tree size (Niklas and Spatz, 2004). Numerous empirical research showed that the H vs. D scaling exponent changes among and within species (Feldpausch et al., 2011;Loubota Panzou et al., 2018;Mensah et al., 2018;Zhang et al., 2019a). Previous studies indicated that trees can alter their architecture and thus their strategy to compete with rivals (Lintunen and Kaitaniemi, 2010;Zhang et al., 2020). ...
... and inferior trees is consistent with the observation that inferior trees are likely to ultimately die. This study indicates that in addition to competition (Trouve et al., 2015;Qiu et al., 2021), climate (Hulshof et al., 2015;Fortin et al., 2018), forest structure (Feldpausch et al., 2011), and species composition (Mensah et al., 2018), the numerical values of the H vs. D scaling exponent differ as a function of tree performance (growth vigor) within the particular species examined in this study. In addition, the results do not support the 2/3-scaling (elastic self-similarity) law between tree height and trunk diameter at the intraspecific level, which is consistent with previous research (Russo et al., 2007;Mensah et al., 2018;Zhang et al., 2020a). ...
... This study indicates that in addition to competition (Trouve et al., 2015;Qiu et al., 2021), climate (Hulshof et al., 2015;Fortin et al., 2018), forest structure (Feldpausch et al., 2011), and species composition (Mensah et al., 2018), the numerical values of the H vs. D scaling exponent differ as a function of tree performance (growth vigor) within the particular species examined in this study. In addition, the results do not support the 2/3-scaling (elastic self-similarity) law between tree height and trunk diameter at the intraspecific level, which is consistent with previous research (Russo et al., 2007;Mensah et al., 2018;Zhang et al., 2020a). ...
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Premise of study: Competition is an important driver of tree mortality, and thus affects forest structure and dynamics. Tree architectural traits, such as height-to-diameter (H-D) and branch length-to-diameter (L-d) relationships are thought to influence species competitiveness by affecting light capture. Unfortunately, little is known about how the H vs. D and L vs. d scaling exponents are related to tree performance (defined in the context of growth vigor) in competition. Methods: Using field survey data for 1547 individuals and destructively sampled data for 51 trees with 1086 first-order branches from a high-density Pinus massoniana forest, we explored whether the H vs. D and the L vs. d scaling exponents respectively numerically differed across tree performance and branch vertical position in crowns. Key results: The results indicated that (1) the H vs. D scaling exponent decreased as tree performance declined; (2) the L vs. d scaling exponent differed across tree performance classes (i.e., the scaling exponent of "inferior" trees was significantly larger than that of "moderate" and "superior" trees); (3) the L vs. d scaling exponent decreased as branch position approached ground level; and (4) that, overall, the branch scaling exponent decreased as tree performance improved in each crown layer, but decreased significantly in the intermediate layer. Conclusions: This study highlights the variation within (and linkage among) length-to-diameter scaling relationships across tree performance at the individual and branch levels. This linkage provides new insights into potential mechanisms of tree growth variation (and even further mortality) under competition in subtropical forests. This article is protected by copyright. All rights reserved.
... Allometric growth of the same species was found to be almost identical under the same stand conditions (Niklas, 1994;Ducey, 2012). Even if the effects of competition are ignored, the use of a simple model to represent multiple species in a mixed forest would not be appropriate (Sharma, 2016;Mensah et al., 2018). ...
... In order to ensure independence of individual tree species within structure groups, we used mixed-effects models with tree species as random-effect. Mensah et al. (2018) also used a mixed-effects H-D model for a natural forest with 45 species in four forest types in South Africa. ...
... Our study considered the characteristics of each species in order to develop H-D models using fewer equations than the number of species (see O'Brien and Hubbell, 1995). The use of such mixed-effects H-D models can explain the stochastic variation among tree species in a structure group (Mensah et al., 2018). It can also predict fixed-effect and randomeffect parameters to enrich the tools for tree height prediction (Patrício et al., 2022). ...
Article
Tree height-diameter (H-D) models are essential for estimating tree volume and forest production. The development of such models can be especially challenging in multi-species natural forests. We present new generalized mixed-effects models based on a set of 456 sample plots and 77,908 individual tree measurements. Tree species were assigned to one of four structure groups according to their life forms, regeneration modes and stand structure characteristics: (1) Understory tree species with an L-shaped D distribution (UL); (2) Sub-canopy tree species with an L-shaped D distribution (SL); (3) Sub-canopy tree species with a bell-shaped D distribution (SB); and (4) Canopy tree species with a bell-shaped D distribution (CB). A distance-dependent competition index (DCI) was included in the base model of the structure groups, and a mixed-effects model for each group with tree species as random-effect. The four models represent unique allometric relationships for the four structure groups. Model accuracy was improved for all groups after adding DCI. Two sets of mixed-effects H-D models (with or without DCI) are presented to improve the estimates of productivity and carbon stock in the temperate natural forests of Northeastern China. The general approach adopted in this study may serve as an example for similar studies in other multi-species and multi-layered forest stands.
... Tropical humid forests are formed by a high diversity of species, a complex vertical structure, a dense canopy and high relative humidity. These characteristics make height measurements difficult, inefficient and with a a1111111111 a1111111111 a1111111111 a1111111111 a1111111111 high error [2,3]. As a result, biometrists and forest ecologists tend to measure only the diameter of the trees and estimate the height using allometric models. ...
... Some studies have evaluated the potential of alternative fitted models on a larger scale (continental and pan-tropical) based on the inclusion of environmental variables intrinsic to each region of the tropics [6,7]. Studies using the power-law model [6,8,9] and the Weibull model demonstrate a considerable reduction in errors in height estimates when fitted for local-scale [1,3,10,11]. In addition, approaches with monomolecular and hyperbolic models based on diameter growth [12], and including spatial information [13,14], resulted in high precision using a reduced set of predictor variables. ...
... Several efforts have been made to develop height-diameter allometric models for tropical forests at continental scales in Africa [3] and Asia [15]. In South America, we noticed several proposals for models at regional scales [6,7,16,17]. ...
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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.
... Understanding tree allometric relationships is vital to consistently estimate woody volume, the amount of carbon stored in aboveground biomass and provides essential support for forest inventory and management. Typically, basic generic models that describe tree allometric relationships are locally developed and subjected to uncertainty when used in different locations and over large spatial scales (Magnabosco Marra et al., 2016;Kearsley et al., 2017;Fayolle et al., 2018;Mensah et al., 2018;Fortin et al., 2019). To improve accuracy, recent studies have been using generalized models at individual tree and plot levels (Fang and Bailey, 1998;Banin et al., 2012;Forrester et al., 2017a;Fortin et al., 2019), including a number of explanatory variables associated with forest environmental heterogeneity and tree species intrinsic variation (Temesgen and Gadow, 2004). ...
... For all models, Kolmogorov-Smirnov normality tests were used to investigate residuals normality assumptions (α = 0.01). For homoscedasticity assumptions, we plotted models Pearson residuals vs. predicted values (Mensah et al., 2018) and used graphic inspection analysis to check for possible heteroscedasticity trends. Models were compared by both the Akaike and Bayesian information criterions (AIC and BIC; Burnham and Anderson, 2002). ...
... Site effect for shaping tree allometry (Table S2) is consistent with many other large-scale studies (Marshall et al., 2012;Hunter et al., 2013;Kearsley et al., 2017;Fayolle et al., 2018;Mensah et al., 2018;Barbosa et al., 2019); including elevation (da Scaranello et al., 2012) and forest types effects in the Atlantic Forest (Vibrans et al., 2015a(Vibrans et al., , 2015b. This finding supports the hypothesis that tree regional allometries are local environmentally dependent in Atlantic Forest and corroborates with previous findings showing that climate and stand structure can explain much of the existing variation in tree allometry at large scales (Banin et al., 2012;Feldpausch et al., 2011;Chave et al., 2014;Fortin et al., 2019). ...
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Article
Tree allometric models are generally developed at local scales and thus potentially biased when used for different locations and at broader spatial scales. Because allometric relationships vary with forest structure, climatic conditions and edaphic properties, one potential way to address this issue and consistently estimate tree allometry, may involve including new explanatory variables into allometric models. Here, using an extensive dataset of 566 trees widely distributed over Rio de Janeiro state, Brazil, we investigated the influence of stand structure, climate, soil fertility and texture in tree allometry (bark thickness, height, and stem volume) in hyperdiverse and structurally complex Atlantic Forest. Water stress, soil texture and to a lesser extent basal area, soil fertility and precipitation, were strong predictors of tree height and volume. Wetter forests with richer soils support higher-statured trees with greater woody volume, whilst drier environments with moderate to low nutrient availability are associated with small-statured and low tree volume. In contrast, bark thickness was solely determined by soil fertility and ph. Negligible relationship between bark thickness and climatic variables is likely associated with our studied gradient that did not encompass dry forests that are adapted to frequent and intense fires, and where bark investment to stem protection ensures survival. These findings suggest that more appropriate approach to reliably estimate tree height, volume and bark thickness at regional and landscape scale, should incorporate environmental descriptors that are strongly associated with forest structure.
... Errors in tree height prediction may lead to large errors when estimating carbon stocks. In addition, height-diameter relationships are also used for evaluating mechanical stability and timber quality (King 1990;Mensah et al. 2018). Accounting for both diameter and height provides a flexible perspective to understand differences in growth allocation of species or functional groups (Mensah et al. 2018). ...
... In addition, height-diameter relationships are also used for evaluating mechanical stability and timber quality (King 1990;Mensah et al. 2018). Accounting for both diameter and height provides a flexible perspective to understand differences in growth allocation of species or functional groups (Mensah et al. 2018). ...
... A common rule is that there is no multicollinearity when the VIF < 5 ). Mensah et al. (2018) found that the power function had excellent performance in terms of fitting the height-diameter model for 45 species in South Africa. The allometry model including the selected variables had the following structure: ...
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Tree height-diameter allometry reflects the response of specific species to above and belowground resource allocation patterns. However, traditional methods (e.g. stepwise regression (SR)) may ignore model uncertainty during the variable selection process. In this study, 450 trees of Chinese fir (Cunninghamia lanceolata (Lamb.) Hook.) grown at five spacings were used. We explored the height-diameter allometry in relation to stand and climate variables through Bayesian model averaging (BMA) and identifying the contributions of these variables to the allometry, as well as comparing with the SR method. Results showed the SR model was equal to the model with the third highest posterior probability of the BMA models. Although parameter estimates from the SR method were similar to BMA, BMA produced estimates with slightly narrower 95% intervals. Heights increased with increasing planting density, dominant height, and mean annual temperature, but decreased with increasing stand basal area and summer mean maximum temperature. The results indicated that temperature was the dominant climate variable shaping the height-diameter allometry for Chinese fir plantations. While the SR model included the mean coldest month temperature and winter mean minimum temperature, these variables were excluded in BMA, which indicated that redundant variables can be removed through BMA.
... Many natural and biological factors affecting the tree height-diameter allometric relationship have been identified through research. For example, precipitation, temperature, geographic location, and site conditions have been shown to have significant effects on height-diameter allometry, and forest structure, tree species, and genetic variability within a species have also been shown to play a role [1,4,18,[21][22][23][24][25][26]. However, our understanding is limited with regard to how anthropogenous measures, such as thinning, affect the tree height-diameter allometry in residual stems. ...
... Mathematical equations are widely used to quantify the allometric relationship between tree height and stem diameter [1,61,84]. Many studies have shown that different regions and tree species have different optimum height-diameter allometry models [4,25,62]. To more accurately analyze the effects of thinning on Masson pine plantations, we first compared the ability of five commonly used height-diameter allometric models to estimate heights from diameters. ...
... The results showed that the power function had the best goodness of fit for our data. This function has several desirable properties, such as its flexible integrated and logarithmic representation [74,76,[85][86][87], and it has also been widely used to described allometric relationships for pine and other species in America, Europe, Asia, and South Africa [1,18,25,88]. ...
Article
Monocultural coniferous plantations have prevailed worldwide in recent decades, which supplied much of the world’s timber, but also exerted some negative effects on local ecologies and environmental systems. Continuous development has increased the various demands of human society for forests and it is necessary to balance concerns for the ecological and economic functions. Ample evidence indicates that mixed forests are an ideal option for providing more diversified ecological services and forest goods. Converting pure forests into mixed forests by introducing broad-leaved hardwood species below coniferous plantations has become an increasingly popular forest management strategy. Yet, there has been not enough research to date on suitable management methods for enhancing forest diversity and resilience in the context of forest conversion. To comprehensively examine how the intensity in Masson pine thinning influences forest evolution, seedlings of two native hardwood species were introduced below unthinned and thinned (varying intensity) Masson pine plantations. The effects of thinning on residual tree growth, seedling survival and growth, and understory vegetation development were analyzed using a generalized additive mixed model (GAMM). Monitoring results over 10 years indicate that thinning is a necessary management measure to accelerate forest succession in the conversion process; thinning exerts significant effects on the growth of residual trees, the survival and growth of seedlings, and the development of understory vegetation. Intense thinning results in more residual tree growth and enhances the richness and diversity of herbaceous species. However, excessive thinning can reduce the likelihood of seedling survival and growth as well as the richness and diversity of shrubs. Optimal thinning intensities appear to fall between 50% and 60% depending on the specific introduced species; light-demanding species may need higher overstory thinning intensity than shade-tolerant species. The biological characteristics of the introduced species must be taken into account to design an effective thinning strategy for pine plantations conversion.
... Thus, estimating height as a function of diameter is a common practice in tropical forest inventories (Mensah et al. 2018). These models can be used to improve forest biomass and carbon estimation, especially in inventories in which only the diameter has been measured Hunter et al. 2013;Lewis et al. 2013;Chave et al. 2014). ...
... Additionally, models that express the tree height-diameter relationship (h × d) are an alternative to determining forest com-munity structure patterns (Hulshof et al. 2015) when height measurements are not feasible (Vibrans et al. 2015). They are also essential tools for understanding forest dynamics through growth equations based on ecophysiological processes (Li et al. 2015;Mensah et al. 2018). Such models are important components for calibrating remote sensing products used to estimate natural forest stocks (Kearsley et al. 2017). ...
... Generic models describing the relationship between tree allometric variables of the total dataset are simple equations that do not have specific coefficients for each species and (or) vegetation type (Mensah et al. 2018;Xing et al. 2019). Variability in the h × d relationship is still an obstacle for model calibration in natural forests (Vibrans et al. 2015). ...
Article
Tree height is one of the most important variables for quantitative assessment of forest stocks but is difficult to directly measure. However, such allometric relationships of trees can vary between geographical regions, 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 1) fit equations to estimate tree height in Atlantic Forest types in the state of Rio de Janeiro, Brazil; 2) compare efficiency and precision between generic and specific equations for forest types; and 3) 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 for large scales in tropical forests.
... The intrinsic parsimony of the two-parameter model makes it an excellent match in various contexts (Bronisz and Mehtätalo, 2020). We adopted Eq. (1) as the base model, which is extensively employed in forestry studies due to its simple model form and high prediction accuracy (Eerikäinen, 2003;Eby et al., 2017;Mensah et al., 2018;Qiu et al., 2021). ...
... The diversity and complexity of mixed forest species make it challenging to evaluate H-D relationships compared to single-species stands. This study used a simple power function as the base model for 14 target species after comparing several two-parameter and three-parameter base models, considering the simplicity of tree H-D models (Eerikäinen, 2003;Eby et al., 2017;Mensah et al., 2018;Qiu et al., 2021). Species heterogeneity led to variations in the fitted H-D curves and the scaling exponents of each tree species (Figs. 5 and 6). ...
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Models based on height-diameter (H-D) are helpful for estimating forest biomass and carbon storage on a large scale. Climate change has an impact on allometric height-diameter growth. H-D models explaining climatic effects are still inadequate due to the complexity of mixed forests. This paper developed climate-sensitive mixed-effects models for 14 tree species based on 316 natural mixed forest plots in Northeastern China and compared the response of tree height growth to environmental gradients for multiple species. The results showed that the species heterogeneity leads to the differences in scaling exponents in varying degrees. The analysis revealed that incorporating mean annual temperature (MAT), mean annual precipitation (MAP), dominant tree height (HT), basal area of the larger trees (BAL), and Shannon diversity index significantly enhanced the predictive ability of the model. By exploring the tree height change patterns of each tree species under different gradients of environmental factors, we found that increases in temperature, precipitation, site quality, and competition intensity positively affected height growth in mixed forests. In contrast, increases in species diversity inhibited height growth. The degree to which environmental factors regulate the H-D allometric growth of trees in mixed forests is related to species specificity. This paper provides theoretical support for tree height estimates of major tree species in mixed forests under global climate change by introducing environmental factors to improve the H-D model of 14 tree species.
... Several studies have used such functions to model tree heightdiameter relationships in temperate ( Sharma and Breidenbach, 2015 ;Liu et al., 2017 ;Sharma et al., 2019 ;Ogana and Gorgoso-Varela, 2020 ) and tropical forests ( Valbuena et al., 2016 ;Kearsley et al., 2017 ;Mensah et al., 2018 ;Mugasha et al., 2019 ). Although these functions can produce satisfactory fits for forest sites where sample data was taken, they are site-specific and may produce large errors when used for tree height predictions at other sites ( Zhang, 1997 ). ...
... The power function was selected as the most appropriate model for predicting tree height across the species groups based on its performance statistics. The power function has also been found suitable for predicting tree height in some tropical forests ( Mensah et al., 2017( Mensah et al., , 2018Imani et al., 2017 ). SA1 is selection approach using subsample of 3 trees from 3 diameter classes per plot; SA2 is selection approach using subsample of 4 trees from 4 diameter classes per plot; SA3 is selection approach using subsample of 4 smallest per plot; RSE is residual standard error; e is mean bias. ...
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Article
The height and diameter of trees are important variables in estimating the aboveground biomass of trees. Tree height measurements are often difficult in tropical forests hence tree height–diameter models are often used as an alternative for predicting tree heights. This study was carried out to develop height–diameter models for tree species in Omo strict nature forest reserve in Nigeria. Height and diameter data used for the study comprised of 100 tree species, which were classified into three groups using cluster analysis. Eight commonly used non-linear height–diameter functions were tested for predicting heights of the species groups using nonlinear least squares (Nls) method. The power function was selected based on its performance, and fitted using mixed-effects modeling approach to account for between-plot height variability. The Mixed-effects models were evaluated using the Akaike information criteria and Residual standard error. The models were calibrated using three subsample selection approaches. The best calibration results were obtained using subsamples of four trees from four diameter classes per plot. The best calibrated mixed-effect models outperformed the Nls models for all the tree species groups; increasing the accuracy of tree height prediction.
... R 2 > 0.65) for all tree components in the two climatic zones. This type of equation is widely reported by many authors in the tropical zones of Africa (Henry et al., 2011;Antin et al., 2013;Laminou Manzo et al., 2015;Xiang et al., 2016;Dimobe et al., 2018;Mensah et al., 2018). In addition, the power models are simple and practical in estimating the biomass of several woody species, and this fact lead several authors to prefer them than polynomial and logarithmic equations that have high elasticity (Xiang et al., 2016;Yuen et al., 2016). ...
... At tree level, including CD as additional predictor improved the equations in the Sudano-Sahelian zone, but this had no significant improvement on Sahelian zone equations. This suggests that equation improvement through incorporation of additional dendrometric parameters is not a general case for trees (Dimobe et al., 2018;Mensah et al., 2018), but also stand while climatic parameters affect predictors contribution in fitting equations. The important findings are that tree trunk size (dbh or D 20 ) is the best predictor for aboveground biomass estimates. ...
... R 2 > 0.65) for all tree components in the two climatic zones. This type of equation is widely reported by many authors in the tropical zones of Africa (Henry et al., 2011;Antin et al., 2013;Laminou Manzo et al., 2015;Xiang et al., 2016;Dimobe et al., 2018;Mensah et al., 2018). In addition, the power models are simple and practical in estimating the biomass of several woody species, and this fact lead several authors to prefer them than polynomial and logarithmic equations that have high elasticity (Xiang et al., 2016;Yuen et al., 2016). ...
... At tree level, including CD as additional predictor improved the equations in the Sudano-Sahelian zone, but this had no significant improvement on Sahelian zone equations. This suggests that equation improvement through incorporation of additional dendrometric parameters is not a general case for trees (Dimobe et al., 2018;Mensah et al., 2018), but also stand while climatic parameters affect predictors contribution in fitting equations. The important findings are that tree trunk size (dbh or D 20 ) is the best predictor for aboveground biomass estimates. ...
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Balanites aegyptiaca (L.) Delile is native to semi-arid regions in Africa where it is a well-known and conspicuous component of savannas. The species is highly preferred by local people because of its high socio-economic, cultural and ecological values. However, the species faces multiple environmental challenges such as desertification and human pressure. This study aimed to develop allometric models to predict aboveground biomass (AGB) of B. aegyptiaca in two climatic zones in Burkina Faso. Overall, thirty trees were sampled using destructive method in six study stands along two climatic zones. We assessed the biomass allocation to the different components of trees by computing its fraction. Furthermore, allometric models based on diameter at breast height (dbh) and basal diameter at 20 cm height (D20) were fitted separately as well as combined with crown diameter (CD) and/or tree total height (Ht). For each biomass component, non-linear allometric models were fitted. Branch biomass accounted for 64% of the AGB in the two climatic zones and increased with dbh. No significant difference in carbon content was found. However, biomass allotment (except leaves) varied across climatic zones. Although both dbh and D20 are typically used as independent variables for predicting AGB, the inclusion of the height in the equations did not significantly improve the statistical fits for B. aegyptica. However, adding CD to dbh improved significantly the equations only in the Sudano-Sahelian zone. The established allometric models can provide reliable and accurate estimation of individual tree biomass of the species in areas of similar conditions and may contribute to relevant ecological and economical biomass inventories.
... Therefore, change in elevation can lead to significant change in numerous environmental factors (Mao et al., 2015). Tree growth rate differs at different elevations due to change in characteristics of soil properties and climate (Mensah et al., 2018;Sharma et al., 2020). For example, water availability and soil nutrient may be limiting for tree growth in the upland compare to low elevation positions (Lopez et al., 2021). ...
Article
Spatial species diversity and size inequality contribute to maintenance of tree species diversity in tropical forests. Coexistence of tree species requires interactions within and between spatial species and size diversity. However, elevation gradient has significant impact on growth and species interactions. Failure of most conservation efforts is due to inability to identify and maintain coexistence mechanisms existing in the forest. Understanding the contribution of elevation gradient to coexistence of tree species will improve conservation efforts and terrestrial carbon budgeting. Therefore, association between tree diversity and size inequality on elevation gradient of Elephant Camp Natural Forest was investigated. Eight (30m x 30m) plots were systematically demarcated on 1km line transects in each identified elevation (Hilltop and Valley-Bottom stands). Trees diameter-at-breast height (dbh) were enumerated and identified to species level. Tree dbh was measured and density estimated. Tree species diversity (Shannon-Weiner, Simpson and Margalef indices) and size inequality (Gini coefficient, skewness and Coefficient of variation) were computed. Stem volume and biomass were computed and converted to biomass carbon. Data collected were analysed using descriptive, correlation analysis and principal component analysis. Tree density varied from 435/ha to 767/ha. There was positive correlation between Skewness and Gini coefficient in Hilltop stand and negative correlation between Skewness and Simpson index in Valley-Bottom stand. The measures of tree size inequality and species diversity were strongly associated with each other in Valley-Bottom stand and not in Hilltop stand. Structural diversity and species diversity determined the competitive interaction among tree communities in Hilltop and Valley-Bottom stands, respectively.
... Then, the dry weights are determined by drying each component of tree in the laboratory conditions. First, the trunk mass is calculated using the volume and then the AGB parts of the trees is calculated by multiplying the trunk mass with the biomass expansion factor (BEF) (Jalkanen et al., 2005;Keleş, 2016;Feldpausch et al., 2011;Mensah et al., 2018;Tak and Kakde, 2020). This method requires cut down the trees to investigate for new destructive reduction method (Pinard and Putz, 1996;Medjibe et al., 2011;Hu et al., 2020). ...
... Diameter at breast height (D) and total tree height (H) are the two most important variables for measuring forest inventory, and are often used to estimate site index, biomass, growth and yield, and other important parameters [1][2][3][4][5]. Measuring D is a quick, easy and reliable process, while measuring H is difficult and time-consuming [6]. ...
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In the process of modeling height-diameter models for Mongolian pine (Pinus sylvestris var. mongolica), the fitting abilities of six models were compared: (1) a basic model with only diameter at breast height (D) as a predictor (BM); (2) a plot-level basic mixed-effects model (BMM); (3) quantile regression with nine quantiles based on BM (BQR); (4) a generalized model with stand or competition covariates (GM); (5) a plot-level generalized mixed-effects model (GMM); and (6) quan-tile regression with nine quantiles based on GM (GQR). The prediction bias of the developed models was assessed in cases of total tree height (H) predictions with calibration or without calibration. The results showed that extending the Chapman-Richards function with the dominant height and relative size of individual trees improved the prediction accuracy. Prediction accuracy was improved significantly when H predictions were calibrated for all models, among which GMM performed best because random effect calibration provided the lowest prediction bias. When at least 8% of the trees were selected from a new plot, relatively accurate and low-cost prediction results were obtained by all models. When predicting the H values of Mongolian pine for a new stand, GMM and BMM were preferable if there were available height measurements for calibration; otherwise, GQR was the best choice.
... When data are limited, as applies in the current case, a one-parameter regression model is relatively straightforward to calibrate (Vanclay, 2009). Though over-simplistic compared to multi-parameter models (Mensah et al., 2018), one-parameter models can still be useful for providing forest stand production estimates (Vanclay, 2009(Vanclay, , 2010. Here, we used the steps suggested by Grant et al. (2012), where height and DBH are estimated using equations (2) and (3), respectively: ...
Article
This study was developed in the context of the Provision of Adequate Tree Seed Portfolios (PATSPO) initiative in Ethiopia. PATSPO aims to strengthen the existing tree-seed system by ensuring access to high-quality tree germplasm. Here, we estimate the socioeconomic impact of establishing a breeding seedling orchard (BSO) and distributing quality planting material of the tree Grevillea robusta (grevillea) in Ethiopia. Grevillea is a commercially important and popular agroforestry tree species grown in East African smallholder farms. Our study starts by modelling tree growth with a one-parameter regression fitted to literature-sourced growth characteristics. For the purpose of modelling, we identify three ‘quality scenarios’ (related to the germplasm used) and two ‘planting options’. Based on the model’s outputs, we investigate the effects of increased tree productivity on farmland economy, on the provision of environmental services, and on the wider forestry sector. Findings are outscaled based on the demand for grevillea planting material in Ethiopia and an assumed reach of PATSPO-derived high-quality germplasm. Our growth models indicated that higher than baseline quality scenarios could produce a significant increase in volume (and biomass productivity). This resulted in several-fold increases in the net present value over the production cycle of agroforestry and woodlot plantings, as well as significant benefits in other economic indicators. At the country scale, our analysis estimated that after 50 years the increase in cumulative net present value of on-farm grevillea plantings should be between Birr 2.7 billion and 1.9 billion when using high-quality germplasm compared to an unimproved germplasm baseline, a significant boost (38 Birr = 1 USD at the time of calculations in 2021). We therefore reveal that establishing a grevillea BSO in Ethiopia could produce significant economic returns for tree growers that are much higher than the initial investment that we determine to be required. Furthermore, using BSO germplasm compared to an unimproved germplasm baseline could over 50 years after the BSO’s establishment sequester an extra 1.7 million tonnes of CO2 equivalents annually and achieve an increase in net present value annually of Birr 44 million in roundwood milling into sawnwood. In summary, our current analysis indicated that a focus on grevillea’s germplasm quality is predicted to bring significant economic and environmental benefits in Ethiopia. Our approach to estimate the benefits of using quality germplasm in tree planting represents an advance on previous methods and can be widely applied to a broad range of species, production systems and locations.
... Muito embora o modelo Pan-tropical evidencie estimativas confiáveis de altura, o uso indiscriminado de modelos de outras regiões pode acarretar consideráveis vieses na estimativa de altura, sendo não recomendado para determinadas tipologias florestais (Feldpausch et al., 2011;Sullivan et al., 2018). A escolha de um modelo de altura-diâmetro apropriado é, portanto, crucial para uma análise precisa da dinâmica e funções da floresta (Mensah et al., 2018). However, few studies address the analysis of the diameter structure through probability density functions in managed and unmanaged areas, and knowledge about asymmetry, kurtosis as well as validation of the functions in relation to the theoretical distribution of diameter data still remains. ...
... Muito embora o modelo Pan-tropical evidencie estimativas confiáveis de altura, o uso indiscriminado de modelos de outras regiões pode acarretar consideráveis vieses na estimativa de altura, sendo não recomendado para determinadas tipologias florestais (Feldpausch et al., 2011;Sullivan et al., 2018). A escolha de um modelo de altura-diâmetro apropriado é, portanto, crucial para uma análise precisa da dinâmica e funções da floresta (Mensah et al., 2018). However, few studies address the analysis of the diameter structure through probability density functions in managed and unmanaged areas, and knowledge about asymmetry, kurtosis as well as validation of the functions in relation to the theoretical distribution of diameter data still remains. ...
... The parameters of the NRH provide easily comprehended linear descriptions of three elements of tree growth in a specific environment, namely a, H a and b. Application of the NRH across different environments would require modifications, as have been made to power (Lines et al. 2012;Zhao et al. 2021), logarithmic Chave et al. 2014;Cysneiros et al. 2021), Weibull and exponential (Banin et al. 2012;Mensah et al. 2018) models. An advantage of the NRH is that variations in environmental resource availability as reflected in forest type (Cysneiros et al. 2020), site quality (Vanclay 2009) and tree density (Vanclay 1992;Deng et al. 2019) may be identified and described quantitatively as factors independently altering a, b and H a , and other dependent parameters, including crown dimensions and biomass. ...
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Context Allometric equations describing the relationships between tree height (H) and breast height diameter (D) should be both statistically efficient and biologically relevant. Aims To determine whether selected allometric equations can meet established criteria for both efficiency and relevance. Methods Nine equations were compared to define the H–D relationships of 1122 individuals and 18 species from an Australian subtropical rainforest. Key results Three-parameter asymptotic equations described initial slope (a), curvature (b), and asymptotic height (Ha). Each equation was evaluated for precision (root mean square error, RMSE) and bias in H estimates, and ease of interpretation of function parameters. For both individual species and all stems, a non-rectangular hyperbola (NRH) provided almost equally high precision and low bias as did the statistically most parsimonious generalised Michaelis–Menten function, plus linear parameter values easily relatable to tree structural and functional attributes. The value of NRH a increased linearly with wood density for canopy species, but not for understorey and subdominant species, whereas the value of NRH b decreased as Ha increased from understorey to canopy species. Conclusions Species within understorey, subdominant, and canopy structural groups shared similar ranges of parameter values within groups that reflect both intrinsic architectural and developmental patterns, and environmental limitations to Ha. Implications The NRH can be used to visualise both early and later tree development stages and differences among the growth patterns of species occupying different positions within a forest.
... In addition, individual tree was treated as a random factor allowing its intercept to vary randomly (Zuur et al. 2009). The inclusion of tree as random effects allows to model the variability among tree without having to determine their exact effect (Mensah et al. 2018). We tested the random effects of individual trees by comparing the model to a fixed effect model (i.e. ...
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Key Message Strychnos spinosa growth was less responsive than its fruit production, to tree size, protection status and climate; its fruit production increased with tree size, and more so on protected sites. Abstract Abiotic and biotic mechanisms (e.g. climate, human perturbations) are presumed to shape tree growth and reproductive performances. Using the wild fruit tree Strychnos spinosa Lam., as a case study in Benin, we tested whether (and how) tree growth and fruit production were influenced by protection status (non-protected vs. protected sites), climatic zones (Sudanian vs. Sudano-Guinean zones) and size classes (tree diameter < 15 cm; 15–20 cm and > 20 cm). We also tested which climatic variables were important in predicting tree growth/fruit production. Tree growth was only influenced by size class, with higher growth rate in smaller than bigger size classes. Unlike tree growth, fruit production varied significantly with climate and protection status (higher fruit production in Sudano-Guinean than in sudanian zone, and on protected sites than non-protected sites). Fruit production also increased with tree size, and more so on protected sites than non-protected sites. The effect of protection status on fruit production also varied with climatic zones, with protected trees having more fruits than non-protected trees in Sudano-Guinean zone, while both protected and non-protected trees showed similar fruit production in the Sudanian zone. There was a trade-off mechanism between fruit production and growth, which was more pronounced on protected sites. Our study showed that both climate and protection status were considerably important for fruit production, in significant positive (resp. negative) effects of temperature and relative humidity, via mediation by tree size in protected (resp. non-protected) sites. These underlying drivers should be taken into account when predicting scenario for fruit yield under future climate.
... Site-specific variations in H-D allometric equation are widely reported in the tropical Africa using pooled-species datasets (Fayolle et al., 2016;Imani et al., 2017;Kearsley et al., 2017;Loubota Panzou et al., 2018a;Mensah et al., 2018). In this study, we found that the same pattern is observed for one particular species. ...
Article
Reliable tree height-diameter (H-D) allometric equations are a key tool for the estimation of forest productivity and Above Ground Biomass (AGB). Most existing H-D allometric equations developed for the tropical region are based on large-scale multi-species datasets, and their use to derive information on productivity and AGB at the species level is prone to uncertainties. The single-species H-D allometric equations available are mainly focused on monocultures or stands with simple tree species mixtures and did not account for the site effects. Here we measured the height and diameter of 2,288 trees of the emergent tree species Pericopsis elata (Harms) Meeuwen in the Democratic Republic of the Congo (DRC) and in Cameroon. We first examined how accurate multispecies H-D allometric equations are in predicting the total height of P. elata. We then tested whether single-species H-D allometric equations vary between sites. We developed the first H-D allometric equation of P. elata and tested whether and how stand-level and environmental variables induce changes in H-D allometric relationship of P. elata at the regional level. We additionally evaluated whether tree-level variables are important at the local level where climate and stand development stage are expected to be less variable. We found that pantropical, regional and local H-D allometric equations significantly underestimate the total height of P. elata. The local multi-species H-D allometric equation developed for Yangambi showed the highest underestimation in all the studied sites. This result supports the need for an H-D allometric equation specific for P. elata. The species-level H-D allometric equation developed showed significant underestimations for trees from the disturbed and undisturbed forests in DRC, while overestimations were observed for similar sites in Cameroon. Using a mixed-effect H-D allometric equation, we showed that even within a single species, a substantial variation exists between sites. This variation showed to be driven by the differences in the maximum asymptotic height (H max) between sites. We found that P. elata trees are taller and attain higher H max in DRC than in Cameroon. The basal area showed to be a significant covariate accounting for the site effects at the regional-scale where climate variables showed minor effects. However, at the local-scale, none of climate or stand variables showed to be significant. Local-scale variation showed to be associated with differences in light availability, highlighting the potential of management options that shape the local environment in driving species productivity.
... Most models for tree height involved simple linear regression using dbh as a single explanatory variable (Hulshof et al., 2015;Mensah et al., 2018). It is therefore not surprising that the proposed FSGARF method would select dbh to explain the tree height since this variable is present in many models and provide a good explanation of height variation (Barbosa et al., 2019;Costa et al., 2016). ...
Article
Tree height is an important trait in forest science and is highly associated with the site quality from which the trees are measured. However, other factors, such as competition and species interaction, may yield better estimates for individual tree height when taken into account, but these variables have so far been challenging in model fitting. We propose a hybrid approach using genetic algorithms for variables selection and a machine learning algorithm (random forest) for fitting models of individual tree heights. We compare our proposed hybrid method with a mixed-effects model and random forest model using a dataset of 5,608 trees and 189 environmental variables (forest inventory-based variables, soil, topographic, climate, spectral, and geographic) from sites in southeastern Brazil. The tree height models were evaluated using the coefficient of determination, absolute bias, and root means square error (RMSE) based on the validation of dataset performance. The optimal set of variables of the proposed method include the ratio of diameter at breast height to quadratic mean diameter, distance independent competition index, dominant height, the soil silt and boron content. Our findings showed that the proposed hybrid method achieved an accuracy comparable with other methodologies in estimating the total height of the individual trees, and such a modelling approach could have broader applications in forestry and ecological science where a studied response trait has a large number of potential explanatory variables.
... Biomass of trees refers to the weight of all organic matter (Focardi, 2008) Houghton 2008Basu 2018;Edomah 2018). Its prediction is estimated by the use of allometric equations (Chave et al. 2005;Mensah et al. 2018). The equations used for this purpose are derived based on the diameter at breast height (DBH) and the height of trees (Maniatis et al. 2011;Mensah et al. 2017). ...
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Trichilia emetica is a coastal fruit tree species from sub-Saharan Africa that has a potential for commercial harvest for its edible and useful seed oils. However, the prediction of its fruit and seed yields is necessary to plan a profitable harvest. This study aims to calibrate allometric equations that predict the amount of fruits and the biomass of seeds of T. emetica. A total of 35 trees were selected based on seven classes of the diameter at breast height (DBH) in the Umkhanyakude district. The trees were measured during fruit maturation period. The measurements included the DBH, the canopy diameter, and the total height. Fruits were counted on each tree using randomized branch sampling technique. Twelve fruits were harvested per tree and were brought to the laboratory for the determination of biomass. Six allometric models were identified and fitted to the data using ordinary least squares method. The Akaike information criterion (AIC) was used to select the best-fit models. The results suggested that simple linear models, basing solely on DBH (in cm), were the best predictors of both the number of fruits on the trees (NF) and the fresh seed biomass (SB; in kg) of T. emetica. The exponential forms of the best-fit general models were: (1) NF = 375.364 × DBH 1.009; and (2) SB = 1.858 × DBH 1.009. The prediction tests of these models indicated that the errors were large when predicting the fruit number and the seed biomass of smaller trees (DBH ≤ 20 cm) and bigger trees (DBH ≥ 30 cm). For medium-size trees (20 cm < DBH < 30 cm), the error was small. On the other hand, tree size category models developed in this study improved statistically the accuracy of predictions. The findings recommend the use of the fitted tree size category equations.
... Est.std., standardized estimates; SE, standard error; CWM, community weighted mean; FDvar, functional diversity; Hm, tree maximum height; WD, wood density; AGC, aboveground carbon; . . ., indicates the nonsignificant path that was excluded to fit a non-saturated partial mediation SEM. and biomass because species and individuals with the same diameter often exhibit different tree heights and would probably have different allometries (Mensah et al. 2018a). This insight is also evidenced by the direct effect of CWM of maximum height on AGC and its indirect effect which operated through basal area (Fig. 3). ...
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Various studies have shown that plant species richness can promote ecosystem functions such as biomass storage. However, it is less well known whether this is mostly driven by the dominance of a few species and their associated traits (functional identity), or by complementarity among species that highly vary in their traits (functional diversity). The relative contribution of functional diversity and functional identity on biomass and carbon storage may in part depend on the type of functional traits that are considered, and on ecosystem type. Here, we used forest inventory data from West African semi‐arid environments, and functional traits (wood density and tree maximum height) to examine the effects of functional trait identity (FI or community weighted mean; CWM) and diversity (FD or single functional divergence; FDvar) on aboveground carbon (AGC) storage in both forests and savannas. We fitted simple linear and structural equation models to test the direct and indirect effects of functional traits on AGC, while accounting for potential effects of vegetation stand structure such as stand density and basal area. When evaluated independently, CWM of tree maximum height and FDvar of wood density correlated positively with AGC, in both forests and savannas, whereas species richness was unrelated to AGC. However, structural equation models indicated different mechanisms by which these biodiversity components drove AGC in forests and savannas. In forests, species richness had an indirect, positive effect on AGC via basal area, but also an indirect, negative effect, through a reduction in CWM of maximum height. In savannas, species richness had a direct, negative effect on AGC, while both CWM of maximum height (through an increase in basal area) and FDvar of wood density had positive effects. Our study suggests that integrative models are crucial for understanding the effects of species richness, functional trait diversity, and identity on AGC across forests. Furthermore, our study shows that relationships between biodiversity and AGC differ among ecosystem types. In both forests and savannas, FI played an important role, as AGC was maximized in communities dominated by species with a high maximum height. However, only in savannas a high FD additionally promoted AGC.
... The right time to harvest trees is one of the important factors affecting these two stakeholder groups (Kang et al., 2016;Xiang et al., 2020). The stand age of plantations affects tree size, biomass allocation, soil nutrient conditions, water use, and consequently the supply of multiple ESs (Porté et al., 2002;Mensah et al., 2018;Jonsson et al., 2020;Xiang et al., 2020). Meanwhile, temporal aspects also introduce further complexity to the measurement of multifunctionality, yet are nonetheless essential for understanding the stability, resistance, and resilience of overall ecosystem performance and its long-term benefits for human well-being (Allan et al., 2011;Byrnes et al., 2014;Oliver et al., 2015;Manning et al., 2018). ...
Article
Establishing forest plantations is an important solution to the growing conflict between an increasing human population and mounting pressure to protect the natural forests, as plantations also harbor great potential for providing multiple ecosystem services (ESs). However, because of the trade-offs between multiple ESs and the conflicts between different stakeholders, the sustainable management of plantations has been exceedingly challenging. Especially in recent years, with China’s emphasis on ecological civilization construction and sustainable development, forestry departments have begun to focus on long-term ecological benefits, which conflict with farmers’ attention to short-term economic gains. In this study, we quantified 15 field-based ES indicators from the data measured in Chinese fir (Cunninghamia lanceolata) plantations aged 4 to 32 years. Corresponding to the concerns of two different stakeholders (forestry departments and farmers), we calculated ES-multifunctionality with different thresholds under four management scenarios: equal weight, production only, production multifunctionality, and supporting multifunctionality. Our results suggested pronounced stand age effects on both individual ESs and ES-multifunctionality of plantations. For individual ESs, stand age had a greater impact on provisioning services than on supporting services. High degree of trade-offs existed between plantation provisioning ESs and soil nutrient supporting ESs, and between water relevant ESs and the other ESs. With respect to ES-multifunctionality, the values under different scenarios were all augmented with stand age, but to differing degrees. The values for supporting multifunctionality were higher than those of production multifunctionality and production only before 21 years of stand development, but completely reversed once the fir plantations reached an age of 25 years. Finally, several stage-based plantation management recommendations are proposed to minimize conflicts between different stakeholders. Our results combined measures of temporal stability and multifunctionality, thereby providing valuable and timely insight into the multifunctional stability of plantations represented by Chinese fir.
... The sigmoidal functions such as the Weibull-type function, the modified logistic function, the Chapman-Richards functions have been reported as the best functions in temperate tree species [9]. The power function was found most suitable for height-diameter allometry for tree species of southern and eastern Africa [25].The effect of stand variables such as basal area and climate on tree height-diameter allometry has been reported earlier [26,36]. Different species have different physiological characteristics and functional traits related to wood density, specific radial variation, light requirement, that probably determine species-specific growth rate [24] leading to different heightdiameter allometry in different species. ...
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Sweet orange has great socioeconomic value in India and other parts of the world for their important role in human diet and other properties like sweet flavour, sweet aroma, source of vitamin C etc. Despite its numerous commercial values, and large acreages under cultivation little has been studied on the role of sweet orange orchards in carbon management and environmental sustainability. Therefore, the present study was conducted to (1) develop appropriate models for estimation of sweet orange tree biomass, and (2) assess biomass and ecosystem carbon stock for sweet orange orchards in North East India. Allometric models for biomass estimation were developed using data from 58 harvested orange trees. The height-diameter relationships and allometric scaling between above-ground biomass (AGB), culm height (H) and diameter at breast height (D) were examined using various models. Total biomass carbon and soil organic carbon stock of the sweet orange orchard were estimated at 7.69 and 100.2 Mg C ha −1 respectively. Our finding on biomass carbon stock of the sweet orange orchard was comparable with other fruit orchards across the world. However, the age of the orchard and management systems are two major determinants for carbon sink potential of such systems. We recommend upscaling of sweet orange based agroforestry for restoration of degraded shifting cultivated lands in North East India for environmental sustainability and socioeconomic upliftment of the farmers.
... A review of biomass equations for Sub-Saharan African forests reported that only 24% of equations contained more than one explanatory variable, the majority using only DBH (Henry et al. 2011). Since the height-diameter ratio reflects tree shape and is partially affected by environmental conditions (Mensah et al. 2018), it is believed that including H as an additional predictor variable may explain site effects and may improve prediction accuracy (Dutcä et al. 2018), and precision by 55-65% compared with equations based on DBH alone (Picard et al. 2015). Meanwhile, wood density has also been suggested as a variable for allometric equations because it is highly heritable and not only explains some of the inter-specific variability in allometry but also biomass partitioning (Rozenberg et al. 2001;Poorter et al. 2012Poorter et al. , 2015. ...
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Although stand age affects biomass partitioning and allometric equations, the size of these effects and whether it is worth incorporating stand age into allometric equations, requires further attention. We sampled a total of 90 trees for 10 Chinese fir (Cunninghamia lanceolata) plantations at seven stand age classes to obtain the data of tree component biomass using destructive harvesting. A multilevel modeling approach was applied to examine how stand age effects differ among tree components and predictor variables (diameter at breast height, DBH and tree height, H). Age class-specific allometric equations and the best fitting generalized equation that included stand age as a complementary variable were developed for each tree component. Large differences in both the intercept and slope for different stand age classes indicated that stand age affected allometric models. Branch and leaves were more sensitive to the environment and were the tree components most affected by stand age. Age class-specific allometric equations fitted well (R2 > 0.65, p < 0.001) using DBH and the combined form DBH2H as predictor variables. Including stand age as a complementary variable improved the fit of generalized allometric equations. Stem, aboveground and total tree biomass predicted by the multilevel model and generalized equation were comparable to the observed data. However, the multilevel model and generalized equations had a relatively low predictive capacity for branch, leaf and root biomass. These results could improve our capacity to evaluate carbon sequestration and other ecosystem functions in plantations.
... We then tested for significant main and interaction effects of vegetation type and size class on species richness, tree density, basal area and AGC using separate Generalized Linear Mixed effects models (GLMM). In these GLMMs, vegetation type and size class were considered as fixed, and plot was treated as a random factor nested within vegetation, to account for unknown heterogeneity effects (Mensah et al., 2018b;Zuur et al., 2009). Species richness and density were analyzed as count data using Negative binomial GLMM. ...
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The importance of terrestrial ecosystems for carbon sequestration and climate regulation is acknowledged globally. However, the underlying structural drivers are still not well understood, particularly across distinct tropical forest ecosystems where trees species have different growth habits and potential to reach different maximal size. In particular, how important are different tree size classes in contributing to stand aboveground carbon (AGC) remains unclear across forest ecosystems. Here, we hypothesized that (i) tree size classes would contribute differently to stand AGC across forest ecosystems; and (ii) few species, possibly dominant, would determine most of stand AGC. We tested these hypotheses using a 17-ha sampled inventory data from gallery forests, woodlands and savannahs in the Republic of Benin. We examined (i) how AGC stocks vary among small- (40 cm diameter at breast height - dbh) trees; (ii) how the large size class and its individual species contribute to AGC; and (iii) how size class-based taxonomic and structural variables influence AGC?Stand AGC was 23 ± 5, 30 ± 8 and 42 ± 12 MgC ha−1 in savannah, woodland and gallery forest, respectively. There were significant main and interaction effects of vegetation types and size classes. As expected, medium and large-size classes contained more of the AGC, irrespective of the vegetation type. However, gallery forests had the lowest AGC in the
... If accurate H data are available, no local or even specific volume model is required for P. angolensis, rather a robust model that includes DBH and H. A problem is that accurate H measurements are often lacking in the study area, and that good site-specific H:DBH relations need to be developed (Chave et al., 2014;Mensah et al., 2018). Development of local and accurate H:DBH relations that feed into volume or biomass models with H as predictor is a more efficient and less expensive method than the development of site-specific volume or biomass models. ...
Article
The development of site-specific allometric models for tree species of natural tropical forests is hampered by limited resources while there is little quality control of the models developed. This study compares site- and species-specific models with generic and regional or pantropical models for Pterocarpus angolensis, the most widely exploited timber tree of southern Africa. We developed regional models with diameter at breast height (DBH) and tree height for the total and merchantable wood volume of P. angolensis with a dataset of 415 trees collected by destructive and non-destructive methods at 14 different sites in the Baikiaea – Pterocarpus woodlands of Namibia and southern Angola. Sources of data heterogeneity, such as site, collector and method, were investigated using mixed models and climate variables as model predictors. The study compared the ability of the new models with ten other site and species-specific volume models and nine generic volume and biomass models to estimate wood volume at tree and stand level. Stand data of 129 sample plots, representing a rainfall gradient from 480 mm to 750 mm, were used. Results showed that the three best performing models with DBH as single predictor (error 28% − 30%), including our new model, were developed for Namibia and Zambia. Adding tree height as predictor to our model removed the heterogeneity caused by site and reduced the error to 22%. One regional generic and one pantropical generic model, both with tree height, performed as well and outperformed other Pterocarpus specific models. Our models showed that the mean portion of merchantable wood was 35% of the total wood volume, of which 58% was heartwood. Although addition of climate variables improved our models, they did not perform well at stand level. Estimated merchantable volume of P. angolensis at stand level varied from 1.9 to 2.7 m³ ha⁻¹, depending on the models employed. Total growing stock is estimated between 36 and 52 m³ ha⁻¹ in our study area, depending on the model, with the contribution of P. angolensis approximately 13%. Our results suggest that site-specificity of models is needed when they only include DBH. The use of pantropical and regional DBH-height based models that are adapted to site conditions through the collection of accurate height and wood density data for biomass conversion factors, is advised rather than developing site-specific DBH based allometric models.
... Many of these fruit trees, such as S. birrea, S. madagascariensis, S. spinosa, and suffrutices such as S. krausii and P. curatellifolia exist in great abundance with potential for Dietze et al., 2008 ;Jackson et al., 2018 ). In forestry, allometry is used to quantify and predict the biomass of a tree or a compartment of a tree from parameters such as stem diameter ( Maniatis et al., 2011 ;Fayolle et al., 2013a ), height ( Alemdag, 1981 ;Ebuy et al., 2011 ;Mensah et al., 2017 ;Mensah et al., 2018 ), and wood specific density ( Brown et al., 1989 ;Chave et al., 2005 ). The choice of the specific tree compartment whose biomass is to be estimated depends on the outcome desired and the forest type involved ( Fortier et al., 2017 ). ...
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Savannah woodlands of South Africa are dominated by fruit tree species that have a potential for commercial harvest from the wild. However, allometric equations that enable the quantification of fruit biomass of trees are non-existent. The aim of this study was to develop fruit-based allometric equations for Strychnos madagascariensis and S. spinosa species. A total of 80 trees were selected by applying a stratified sampling approach according to four stem diameter classes during fruit ripening period. For each tree, the following parameters were measured: fruit biomass, diameter at breast height (DBH), canopy diameter, and total height. Six forms of the allometric models were fitted to the data using ordinary least squares method. The Akaike information criterion was used to select the best models and the Root Mean Squared Error (RMSE) was used to evaluate the quality of the predictions. DBH was the only appropriate variable in the prediction of the fruit biomass and explained 99.9% of the variation in fruit biomass. The simple linear regressions linking the DBH (in cm) to the total fresh fruit biomass (FB; in kg) were the best models and were expressed by (1) FB = 1.0243 × DBH1.1841; and (2) FB = 1.0297 × DBH1.1956; respectively for Strychnos madagascariensis and Strychnos spinosa. These equations provided realistic predictions of fresh fruit biomass. They induced on average a prediction error of 5.4 kg on the total fresh fruit biomass of a tree. Larger trees (DBH > 25 cm for S. madagascariensis; DBH > 11 cm for S. spinosa) were more susceptible to fruit biomass prediction errors than smaller trees. This study showed that simple linear regression basing on DBH is the best approach to estimate fresh fruit biomass of trees in savannah woodlands.
... Height-diameter equations enable a better understanding of the rates of changes in tree-size variables and the development of stand volume, forest biomass, and carbon stocks [19,20]. Previous studies have summarized a great number of available height-diameter linear and nonlinear relationships and compared their performance for different tree species [1,21]. It should be noted that the main limitation of the height-diameter equations is that they can produce very different results if applied to stands that differ from fitted stands. ...
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This study proposes a general bivariate stochastic differential equation model of population growth which includes random forces governing the dynamics of the bivariate distribution of size variables. The dynamics of the bivariate probability density function of the size variables in a population are described by the mixed-effect parameters Vasicek, Gompertz, Bertalanffy, and the gamma-type bivariate stochastic differential equations (SDEs). The newly derived bivariate probability density function and its marginal univariate, as well as the conditional univariate function, can be applied for the modeling of population attributes such as the mean value, quantiles, and much more. The models presented here are the basis for further developments toward the tree diameter–height and height–diameter relationships for general purpose in forest management. The present study experimentally confirms the effectiveness of using bivariate SDEs to reconstruct diameter–height and height–diameter relationships by using measurements obtained from mountain pine tree (Pinus mugo Turra) species dataset in Lithuania.
... The simple power form of the model of Huxley and Teissier (1936) is widely used model and best fitted for prediction of height from DBH, biomass and volume from DBH or DBH and height or DBH, and height and wood density in Nepal (B. K. et al., 2019;Bhandari and Chhetri, in press;Sharma et al., 2017;Shrestha et al., 2018) and in other countries as well (Evans et al., 2015;Mensah et al., 2018;Mitra et al., 2019;Sillett et al., 2019;Stage, 1975). For our analysis, we plotted height against diameter of dominant trees of all the ASBs in the same graph. ...
Article
Implementation of sustainable forest management approaches, balancing mass timber production and intact ecosystem services through maintaining species diversity, has ever been the challenges for policy makers and practitioners in tropical forestry. Scientific forest management (SciFM) is a popular management approach that is increasingly adopted in Sal (Shorea robusta) dominated forests of Nepal, aiming to accelerate timber production and to improve forest condition. Being based on specific management plan, SciFM practices involve application of various silvicultural practices to manipulate forest composition and stand structure referring to the whole rotation period of a particular forest stand. Of the various aspects of SciFM, we aim to quantify the effect of SciFM on species diversity and regeneration dynamics, and compare diversity indices and regeneration attributes between managed and unmanaged forest stand in lowlands of Nepal, through establishment of permanent sample plots and its measurement in 2014 and 2018. Data collection about plant species and regeneration attributes was carried out in 50 sample plots of size 10 m × 10 m, established by stratified random sampling using quadrat method. Data analysis was done by using various diversity indices and compared through paired t-test. We also carried out correlation and regression analysis of diversity indices with predictor variables; such as canopy cover, number of individuals ha−1, basal area ha−1 and site productivity index. Our study found that plant diversity is significantly decreased but the concentration of dominance is significantly increased in managed forest blocks. Diversity indices were found to have a higher degree of relationship with number of individuals ha−1 and canopy cover as compared to site productivity index and basal area ha−1. Similarly, seedling density and sapling density is found to be increased in managed blocks, ensuring the production and productivity of forest stand sustainably. Based on our analysis, we argue that opening of canopy through regeneration felling is important in promoting regeneration establishment and growth but further research is needed to balance the species diversity along with the practice of intensive management interventions.
... In forest resource inventory, total tree height (H) and diameter at breast height (D) are the two most basic factors, which hold crucial implications for biomass and carbon estimation, along with forest growth and yield models [31]. Generally, tree height is measured by hypsometer or LIDAR data, which are labor-intensive, time-consuming, and costly. ...
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The mixture of tree species has gradually become the focus of forest research, especially native species mixing. Mixed-species plantations of Manchurian ash (Fraxinus mandshurica Rupr.) and Changbai larch (Larix olgensis Henry) have successfully been cultivated in Northeast China. Height–diameter (H–D) models were found to be effective in designing the silvicultural planning for mixed-species plantations. Thus, this study aimed to develop a new system of H–D models for juvenile ash and larch mixed-species plantations, based on competition information and tree and stand attributes. The leave-one-out cross-validation was utilized for model validation. The result showed that the H–D relationship was affected not only by the tree attributes (i.e., tree size and competition information) but also by stand characteristics, such as site quality and species proportion of basal area. The best model explained more than 80% and 85% variation of the tree height of ash and larch, respectively. Moreover, model validation also confirmed the high accuracy of the newly developed model’s predictions. We also found that, in terms of total tree height, ash in middle rows were higher than those in side rows, while larch in the middle rows were higher in the early growth period but then became lower than those in the side rows, as the diameter increased. The newly established H–D models would be useful for forestry inventory practice and have the potential to aid decisions in mixed-species plantations of ash and larch.
... We used boxplots to explore the variation in plot-level species diversity (species richness), structures (tree diameter, tree height and branching patterns) and AGC among the four vegetation types (see Figure S4). We then tested for significant effects of vegetation types on species richness, structures and AGC using separate GLMM, in which vegetation type effects were considered as fixed, and plot as a random factor to account for unknown heterogeneity effects Mensah, Pienaar, et al., 2018). Above-ground carbon, CV of tree height, diameter and branching pattern, were modelled as continuous response variables, by applying GLMM with Gaussian distribution after log-transformation. ...
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It is prominently claimed that enhancing forest diversity would play a dual role of nature conservation and climate regulation. While the idea is intuitively appealing, studies show that species richness effects on aboveground carbon (AGC) are not always positive, but instead unpredictable especially across scales and complex terrestrial systems having large‐diameter and tall‐stature trees. Previous studies have further considered structural complexity and larger trees as determinants of AGC. Yet it remains unclear what drives differential diversity‐AGC relationships across vegetation types. Here, we test whether structural complexity and large‐sized trees play an influential role in explaining shifting diversity‐AGC relationships across vegetation types, using a 22.3 ha sampled dataset of 124 inventory plots in woodlands, gallery forests, tree/shrub savannahs and mixed plantations in West Africa. Natural vegetation had greater species richness and structural complexity than mixed plantations, as expected. In addition, AGC was highest in gallery forests and mixed plantations, which is consistent with favorable environmental conditions in the former and high stocking densities and presence of fast‐growing species in the latter. Significant interaction effects of species richness and vegetation on AGC revealed a vegetation‐dependent species richness‐AGC relationship: consistently, we found positive species richness‐AGC relationship in both mixed plantations and woodlands, and nonsignificant patterns in gallery forests and tree/shrub savannah. Further, there was a vegetation‐dependent mediation of structural complexity in linking species richness to AGC, with stronger positive structural complexity effects where species richness‐AGC relationships were positive, and stronger positive large‐sized trees’ effect where species richness‐AGC relationships were neutral. Our study provides strong evidence of vegetation‐dependent species richness‐AGC relationships, which operated through differential mediation by structural complexity of the species richness and large trees’ effects. We conclude that even higher species richness in diversified ecosystems may not always relate positively with AGC, and that neutral pattern may arise possibly as a result of larger dominant individual trees imposing a slow stand dynamic flux and overruling species richness effects.
... Hoek natural forest can be found in recent studies by the authors (Mensah et al., 2016b(Mensah et al., , 2017aMensah et al., 2018c). ...
Article
Studies on how biodiversity influences ecosystem multifunctionality (EMF) help elucidate ecological mechanisms (e.g. niche complementarity and selection) underlying provision of multiple ecosystem services. While it is acknowledged that biodiversity contributes to EMF, the relative importance of functional traits diversity (niche complementarity) and dominance (selection effects) for EMF needs further investigation. To address this gap, we analysed how tree species diversity influences EMF, using data on species functional traits (specific wood density, specific leaf area and maximum plant height) and four ecosystem functions (carbon storage, habitat quality, forage provision and rockfall protection) in an Afromontane forest in South Africa. We tested the hypotheses that (i) trait diversity rather than dominance would link species richness to EMF; and (ii) diversity rather than species richness effects would increase with the level of EMF. For all possible scenarios of EMF indices, functional trait diversity metrics, especially functional divergence and functional richness correlated positively with EMF. On the other hand, functional dominance also influenced EMF, but played limited role in mediating EMF response to species richness, when compared with functional diversity. Results further revealed that total diversity effects, not species richness effect, generally increased with the level of EMF. In summary, we show that species richness does not fully capture the functional contribution of different species. Compared to dominance, trait diversity had significant advantage in explaining biodiversity-EMF relationship, stressing a greater role of niche complementarity as mechanism underpinning delivery of multiple functions. We argue that functional dominance reflects more the competitive dominance of traits and species within a given community and therefore is more likely to have greater effects on single functions than on multifunctionality.
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Allometric relationships between crown width (CW) and stem diameter at breast height (DBH) contribute in understanding forest dynamics and estimating forest biomass and carbon stocks. Nevertheless, the response of tree crown allometry to gap management and climate interactions remain unclear. We used 934 paired CW and DBH of Robinia pseudoacacia trees from 38 man-made gap forest sites (GPFs) of different sizes and 40 unmanaged forest sites (UMFs) in three counties with different climatic conditions in the Loess Plateau to (1) evaluate potential deviations in CW estimation from existing crown allometry models for R. pseudoacacia; (2) compare the predictive ability of nine common theoretical functions for crown allometry; (3) analyze scaling exponents variations of crown allometry, and test their fit to theoretical predictions; and (4) examine the influence of stand-level and climatic variables on crown allometric relationships. The existing CW-DBH equations provided better fit for GPFs than for UMFs, although substantial deviations were observed. The power function outperformed other theoretical forms for crown allometry in both GPFs and UMFs. The scaling exponents of the allometric relationships were lower in UMFs than in GPFs, which was closer to the metabolic-scaling theory predictions. Distance-independent competition considering average DBH accounted for major variations in crown allometric relationships in both gap-managed and unmanaged forests. Variations in scaling exponents in GPFs were also explained by diffuse light availability and climatic (annual precipitation and wind speed) variables. Our results highlight the significant role of climatic variables in affecting crown allometric relationships in forest gaps. These results have implications for developing vegetation models and long-term forest management in the context of climate change.
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The Combretum-Terminalia woodlands and wooded grasslands (CTW) are widely distributed in East Africa. While these landscapes may have the potential to act as key global carbon sinks, relatively little is known about their carbon storage capacity. Here we developed a set of novel aboveground biomass (AGB) models and tested for species and site variation effects to quantify the potential for CTW to store carbon. In total, 321 trees were sampled from 13 dominant tree species, across three sites in the Northwest lowlands of Ethiopia. Overall, fitted species-specific models performed the best, with diameter at breast height explaining 94–99% of the AGB variations. Interspecific tree allometry differences among species were more substantial than intraspecific tree allometry among sites. Incorporating wood density and height in the mixed-species models significantly improved the model performance relative mean absolute error (MAPE) of 2.4–8.0%, while site variation did not affect the model accuracy substantially. Large errors (MAPE%) were observed when using existing pantropical models, indicating that model selection remains an important source of uncertainty. Although the estimates of selected site-specific models were accurate for local sites, mixed-species and species-specific models performed better when validation data collated from different sites were incorporated together. We concluded that including site- and species-level data improved model estimates of AGB for the CTW of Ethiopia.
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Underground fires are slow spreading, long-lasting and low temperature smoldering combustion without flames, mainly occurring in peatlands and wetlands with rich organic matter. The spread of the smoldering is maintained by heat released during combustion and monitoring this is an important approach to detect underground fires. The Daxing’an Mountains region is a hotspot for underground fires in northeast China. This study examined a Larix gmelinii plantation in the Tatou wetlands of the Daxing’an Mountains and determined the maximum temperature variation of humus of varying particle sizes, and the temperature rising process based on non-linear mixed effects models by an indoor combustion experiment. Maximum combustion temperatures up to 897.5 °C, increased with humus depth; among the three models tested, Richard’s equations were best for characterizing temperature variations; a non-linear equation with three parameters had the highest accuracy in fitting the combustion temperature variations with varying humus particle sizes. These results are informative for predicting temperature variations and provide technical support for underground fire monitoring.
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Height-diameter relationships are significantly modulated by microsite (elevation, aspect and slope), climate and competition. Traditionally, tree height-diameter relationships are modelled or examined using linear or nonlinear regression models, in which the microsite influences or species-habitat relationships are largely ignored. The study on height-diameter modelling was carried out on 24years old Wasangare Parkia Plantation, Nigeria. Total enumeration of four accessions (Senegal, Cameroon, Ghana, and Mali) selected were carried out. Data on tree height and diameter at breast height (dbh) were subjected to ten (10) nonlinear models to predict the height-diameter relationships. Harmonic Decline model was observed to give the best fit for Senegal (= 4.452 (1 + ℎ −58.032 ⁄) ⁄ , RMSE = 2.329 and AIC = 83.239) and Ghana (= 4.141 (1 + ℎ −17.000 ⁄) ⁄ , RMSE = 0.989 and AIC = 1.190) accessions while Ratkowsky and Modified Exponential models were observed to be the best for Cameroon (= 11.814 (1 + (3.958−0.275 ℎ)) ⁄ , RMSE = 3.441 and AIC = 140.126) and Mali (= 11.161 * −3.682 ℎ ⁄ , RMSE = 3.605 and AIC = 152.391), respectively. Due to the availability of other accessions stands in the study area, the method and the best models developed for height-diameter relationships in this study can be further used for predictions.
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Research
The height-diameter (H-D) model is an important tool for predicting tree height (H) based on the diameter at breast height (DBH). However, the performance of the H-D model varies with the model structure. The purpose of this study was to examine the performances of H-D models with various model structures. The research site was located in central Taiwan. Data were collected from a Taiwania (Taiwania cryptomerioides Hayata) plantation at the Huisun Forest Station, and in total, the DBH and H of 104 individual trees were obtained. We adopted various H-D models with different structures to establish the models. The residual sum of squares (RSS), root mean square error (RMSE), Akaike information criterion (AIC), and relative ranking (R-rank) performance cri- teria were employed as criteria. A paired sample t-test and two-way analysis of variance (ANOVA) were used to assess model performances. Results showed that H = a + bD + cD2 + d log D stood out among all models. Nonlinear models had better performances when they were constrained to pass through the origin. In linear models, the performances of 3- and 4-parameter models were better than those of 2-parameter models. In a comparison of the number of parameters between models, nonlinear models performed better than linear models at the 2-parameter level due to large biases in the linear models. 樹高曲線式(height-diameter (H-D) model)係採用胸高直徑(diameter at breast height (DBH))推估 樹高(tree height (H))的重要工具,然而H之模擬效果會隨著H-D model的結構而改變。本研究旨在探 討模式結構對H-D model模擬表現之影響。研究區域位於臺灣中部地區惠蓀林場之臺灣杉(Taiwania cryptomerioides Hayata)人工林林分,共獲104株具DBH與H之單木資料。本研究採用不同種模式型態 之H-D model進行建模,採用residual sum of squares (RSS)、root mean square error (RMSE)、Akaike information criterion (AIC)及relative rank (R-rank)等指標評估模式。並以成對樣本t-test (paired sample t-test)及二因子變異數分析(two-way analysis of variance (ANOVA))分析模式模擬之效果。結果顯示, 在所有模式中H = a + bD + cD 2 + d log D表現最佳。而非線性模式方面,約束模式通過原點可提升模擬 效果;然而在線性模式方面,3及4參數模式模擬結果較2參數為佳。比較2種模式型態在參數間的模擬 效果,非線性模式在2參數結果較佳,而在3及4參數則與線性模式效果相同。 關鍵詞:約束模式、惠蓀林場、參數數目、模式型態、臺灣杉。
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Preprint
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.
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Tree height-diameter allometry is fundamental in estimating growth and biomass, analyzing community structure, and simulating forest dynamics. In this study, we formulated the relationships based on the Chapman-Richards (von Bertalanffy) equation for 75 major species in Japan from data on about 26,000 individuals. Results for each species are shown in the main text, and sources of data and scatter plots of tree height and diameter are shown in the electronic material. We hope that this report will be widely used for forest management and research.
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Changes in temperature and precipitation affect tree growth. Height-diameter (h-d) models that include stand characteristics and climatic factors effectively predict tree height. We assessed 3,425 pine trees in Zambia (P. merkusii and P. michoacana) to (i) test the effectiveness of the existing general h-d model on these species; (ii) develop mixed-effect h-d allometric models that provide the best fit; and (iii) assess the effect of stand characteristics and climate on the predictive ability of the h-d models. The existing h-d model for pine significantly (p < 0.001) over-estimated height for P. merkusii (i.e., 20.5 m vs. 19.2 m) and P. michoacana (i.e., 22.2 m vs. 20.4 m). After incorporating random effects, the newly developed h-d models based on the mixed-effect modeling framework exhibited a high precision and accuracy in estimating height from diameter for P. merkusii and P. michoacana. A single and species-specific h-d models developed in the present study are recommended for inventory applications in Zambia. The temperature, dominant height, and basal area in large trees modulate the height to diameter relationship in P. merkusii and P. michoacana. This finding implies that the increasing temperature and decreasing precipitation beyond the optimum for these species will implicitly reduce tree growth and increase the rotation age.
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Quercus mongolica secondary forest is widely distributed in the northeast of China, but it usually has low productivity, unstable structure, poor health, and low biodiversity. Diameter is a tree variable that is commonly used for forest growth measurement, to provide the basis for forest management decision. Two level generalized linear mixed effects individual diameter growth model were developed using data from two times surveys of 12 Q. mongolica secondary forest permanent plots that were distributed among Wangqing forest farms. Random effects of 14 tree species and 12 plots were introduced into the basic model consisting of three factors: tree size, competition of surrounding trees, and site quality. The results showed that initial diameter at breast height(DBH) was the most important variable affecting diameter growth, followed by competition, while the effect of site quality on diameter growth was not significant. Compared with the basic model, the prediction accuracy of the mixed effect model was improved by 17.69 %, where R2 reached to 0.6805, indicating that it is suitable for the individual-tree diameter growth prediction of the secondary forest of Q. mongolica.
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Chapter
The estimation of foliage and woody biomass is often difficult because it requires destructive sampling, while tree species and natural forests in interest are strictly protected. This chapter presents a non-destructive field sampling method for quantifying foliage and woody biomass in such protected forests ecosystems. The approach is based on the measurement of tree and branch diameters at different level on the standing trees, extraction of core samples and selection smaller branches. Measured tree diameters and core samples are used to reconstruct the biomass of the trunk and main stem sections, while both sampled and non-sampled branch are used for crown and leaf biomass. The analytical framework consisted of (i) developing leaf and branch wood biomass equation, and (ii) applying Smalian's formula for stem volume estimation, and (iii) up-scaling biomass from branch to tree level. The non-destructive sampling approach proposed here is less labor-and less time consuming in the field. It could also serve as an example for estimation of leaf biomass from fodder tree and potential of wood biomass in places where trees species are threatened of extension and protected or where the wood resource is scarce.
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Chapter
Non-Timber Forest Products (NTFPs) designate goods of biological origin other than timber from natural, modi ed or managed forested landscapes. A number of short cycle and cultivated species contributing to food security that remain traditional tend to get less research attention, training and extension. Such plant resources are termed Orphan Crops (OCs), also referred to as minor crops. Due to the increased demands, harvest/ collection of minor crops has tremendously escalated threat of biodiversity loss. Besides, the increased market value of minor crops and their importance in improving livelihood of people in the rural areas raises the need of sustainable management of those crops, which entails e orts toward domestication, selection and improvement. This chapter presents the methods and principles for the genetic improvement of Non- Timber Forest Products & Orphan Crops. It established a 7 steps general roadmap for breeding minor crops. The exercise begins with appropriate goals setting, then germplasm is gathered through collection missions, followed by their morphological and molecular characterization, to provide basic information of lines and guide choice of parental lines. It is very common to encounter narrow genetic base in minor crops. This is dealt with by creating new variants through massive hybridization and more speedily, using mutagenesis. Hybridization has got many designs that serve various purposes, also selection methods are diverse. In case of low inherited traits, the detection of Quantitative Trait Loci (QTL) that set prospects for marker-assisted selection (MAS) has been emphasized. Also, newer breeding tools such as genome-wide association studies (GWAS) and genomic selections (GS) have been discussed. Keywords: Hybridization, Genetic improvement, Marker-assisted selection, Mutation, Orphan Crops
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Research on Non-Timber Forest Products (NTFPs) in West Africa has made considerable progress. This provides a collection of hug number of scientific evidences that can be pooled in the form of book for the characterization and monitoring of changes in NTFPs. Numerous observations point out the difficulties in efficiently pooling data in view of their disparity due to various attempts to contextualize methods. To solve this problem, this book is initiated to provide the approaches and methods for monitoring, assessment and conservation of NTFPs. The purpose of this book is to serve as a practical guide to sampling methods, data collection and analysis techniques of NTFPs. This book meets the imperatives of quest for performance and excellence imposed by the dynamics of science. It outlines different sampling approaches for NTFPs inventories and also presents appropriate statistical tools and methods for processing different types of data. Undoubtedly, this book meets a need for scientific information from researchers and students on NTFPs. The book is a guide which remains open to innovations and scientific progress that could enrich possible news editions. This book will be very useful for the scientific community with interest in the sciences of NTFPs.
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This study evaluated the total height of trees based on diameter at breast height by using 23 widely used height-diameter non-linear regression models for mixed-species forest stands consisting of Caucasian oak, field maple, and hornbeam from forests in Northwest Iran. 1920 trees were measured in 6 sampling plots (every sampling plot has 1 ha area). The fit of the best height–diameter models for each species were compared based on R2, Root Mean Square Error (RMSE), Akaike information criterion (AIC), standard error, and relative ranking performance criteria. In the final step, verification of results was performed by paired sample t-test to compare the observed height and estimated height. Results showed that among 23 height-diameter models, the best models were obtained from the top five ones including Modified-logistic, Prodan, Sibbesen, Burkhart, and Exponential. Comparison between the actual observed height and estimated height for Caucasian oak showed that Modified–Logistic, Prodan, Sibbesen, Burkhart, and Exponential performed better than the others, respectively (There were no statistically significant differences between observed heights and predicted height (p≥0.05)). Prodan, Modified-Logistic, Burkhart, and Loetch evaluated field maple tree height correctly, and Modified-Logistic, Burkhart, and Loetch had better fitness compared to the others for hornbeam, respectively. Although other models were introduced as appropriate criteria, they could not reliably predict the height of trees. Using the Rank analysis, the Modified-Logistic model for the Caucasian oak and Prodan model for field maple and hornbeam had the best performance. Finally, to complement the results of this study, it is suggested to assess how environmental factors such as elevation, climate parameters, forest protection policy and forest structure will modify height-diameter allometry models and will enhance the prediction accuracy of tree heights prediction in mixed stands.
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Key message: This study assessed the effect of ecological variables on tree allometry and provides more accurate aboveground biomass (AGB) models through the involvement of large samples representing major islands, biogeographical zones and various succession and degradation levels of natural lowland forests in the Indo-Malay region. The only additional variable that significantly and largely contributed to explaining AGB variation is grouping based on wood-density classes. Context: There is a need for an AGB equation at tree level for the lowland tropical forests of the Indo-Malay region. In this respect, the influence of geographical, climatic and ecological gradients needs to be assessed. Aims: The overall aim of this research is to provide a regional-scale analysis of allometric models for tree AGB of lowland tropical forests in the Indo-Malay region. Methods: A dataset of 1300 harvested trees (5 cm ≤ trunk diameter ≤ 172 cm) was collected from a wide range of succession and degradation levels of natural lowland forests through direct measurement and an intensive literature search of principally grey publications. We performed ANCOVA to assess possible irregular datasets from the 43 study sites. After ANCOVA, a 1201-tree dataset was selected for the development of allometric equations. We tested whether the variables related to climate, geographical region and species grouping affected tree allometry in the lowland forest of the Indo-Malay region. Results: Climatic and major taxon-based variables were not significant in explaining AGB variations. Biogeographical zone was a significant variable explaining AGB variation, but it made only a minor contribution on the accuracy of AGB models. The biogeographical effect on AGB variation is more indirect than its effect on species and stand characteristics. In contrast, the integration of wood-density classes improved the models significantly. Conclusion: Our AGB models outperformed existing local models and will be useful for improving the accuracy on the estimation of greenhouse gas emissions from deforestation and forest degradation in tropical forests. However, more samples of large trees are required to improve our understanding of biomass distribution across various forest types and along geographical and elevation gradients.
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The study aimed to investigate the relative significance of effects of climatic variability and human disturbance on the population structure of the threatened species Afzelia africana Sm. ex Pers. in the Republic of Benin in West Africa. Forest inventory data such as regeneration density, tree diameter and total height were compiled from A. africana forest stands under different disturbance regimes in the three climatic zones of Benin. Multiple generalised linear models and non-linear diameter–height equations were fitted to contrast the individual effects of categorical variables, such as climatic zone and disturbance level. Results revealed significantly higher scaling coefficients in less drier regions and low-disturbance stands. The diameter–height relationship was more controlled by the climatic zone than by the disturbance level. Accordingly, the disturbance level contributed only to the intercept of the diameter–height model, whereas the climatic zone significantly influenced both intercept and slope. In addition, when climatic zone and disturbance level were considered as sources of variation in the diameter–height model, the former explained the greater marginal variance. It was concluded that climate has the greater effect on population structure of A. africana in natural stands.
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A total of 26 models that estimate the relationship between height and diameter in terms of stand variables (basal area, quadratic mean diameter, maximum diameter, dominant diameter, dominant height, arithmetic mean height, age, number of trees per hectare and site index), were fitted to data corresponding to 9686 trees, using linear and non-linear regression procedures. The precision of the models was then evaluated by cross-validation. The data were collected during two inventories of 182 permanent plots of radiata pine (Pinus radiata D. Don) situated throughout Galicia, in the Northwest of Spain. Comparison of the models was carried out by studying the coefficient of determination, bias, mean square error, Akaike's information criterion and by using a F-test to compare predicted and observed values. Best results were obtained with those models that included any independent variable related to the height of the stand (mean or dominant height), although this implies a greater sampling effort for its application. The model of Tomé gave the best height estimates.
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One of the frequent questions by users of the mixed model function lmer of the lme4 package has been: How can I get p values for the F and t tests for objects returned by lmer? The lmerTest package extends the 'lmerMod' class of the lme4 package, by overloading the anova and summary functions by providing p values for tests for fixed effects. We have implemented the Satterthwaite's method for approximating degrees of freedom for the t and F tests. We have also implemented the construction of Type I - III ANOVA tables. Furthermore, one may also obtain the summary as well as the anova table using the Kenward-Roger approximation for denominator degrees of freedom (based on the KRmodcomp function from the pbkrtest package). Some other convenient mixed model analysis tools such as a step method, that performs backward elimination of nonsignificant effects - both random and fixed, calculation of population means and multiple comparison tests together with plot facilities are provided by the package as well.
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Key message Two artificially debarked Afrotemperate tree species showed different trade-offs between wound closure and compartmentalisation of decay in the stem. One species had a relaxed trade-off but inefficient defence, and the other showed more efficient defence but a substantial trade-off. Abstract Bark stripping for medicinal use is a common cause of damage in several indigenous tree species in natural forests of South Africa. Ocotea bullata and Curtisia dentata are in high demand for their bark for medicinal purposes. The study aimed at revealing intra-specific and inter-specific differences of tree growth rates wound closure and decay containment responses ten years after experimental bark harvesting. The results obtained on computer tomography scans of twenty trees showed that C. dentata had significantly higher decay percentages compared to O. bullata, indicating that O. bullata was able to more efficiently contain decay than C. dentata. While decay in O. bullata was confined at the wounded tissues, decay in the C. dentata extended below and above the wounded area. Intra-specifically, O. bullata showed strong positive correlations between tree growth rates and wound closure rates, and wound closure rates with relative volume of decayed wood, indicating that individuals with higher rates of growth and wound closure suffered higher percentages of decay. Results confirmed an intra-specific trade-off between growth rate and defense investment, with fast growing trees showing high percentage decay (poor compartmentalization of decay). Inter-specifically, however, growth versus defense trade-off did not present itself. For C. dentata, no correlations were found between rates of wound closure and percentage decay. The findings and conclusions derived from this study reveal complex, species-specific responses to damage. This study highlights the need to gain an in-depth understanding of underlying morphological, phylogenic, physiological characteristics of species to further explain the observed species differences.
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Accurate estimation of tree biomass is necessary to provide realistic values of the carbon stored in the terrestrial biosphere. A recognized source of errors in tree above-ground biomass (AGB) estimation is introduced when individual tree height values (H) are not directly measured but estimated from diameter at breast height (DBH) using allometric equations. In this paper we evaluate the performance of 12 alternative DBH:H equations and compare their effects on AGB estimation for three tropical forests that occur in contrasting climatic and altitudinal zones. We found that fitting a 3-parameter Weibull function using data collected locally generated the lowest errors and bias in H estimation, and that equations fitted to these data were more accurate than equations with parameters derived from the literature. For computing AGB, the introduced error values differed notably among DBH:H allometric equations, and in most cases showed a clear bias that resulted in either over- or under-estimation of AGB. Fitting the 3-parameter Weibull function minimized errors in AGB estimates in our study and we recommend its widespread adoption for carbon stock estimation. We conclude that many previous studies are likely to present biased estimates of AGB due to the method of H estimation. This article is protected by copyright. All rights reserved.
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The relationship between biodiversity and ecosystem function has increasingly been debated as the cornerstone of the processes behind ecosystem services delivery. Experimental and natural field-based studies have come up with nonconsistent patterns of biodiversity–ecosystem function, supporting either niche complementarity or selection effects hypothesis. Here, we used aboveground carbon (AGC) storage as proxy for ecosystem function in a South African mistbelt forest, and analyzed its relationship with species diversity, through functional diversity and functional dominance. We hypothesized that (1) diversity influences AGC through functional diversity and functional dominance effects; and (2) effects of diversity on AGC would be greater for functional dominance than for functional diversity. Community weight mean (CWM) of functional traits (wood density, specific leaf area, and maximum plant height) were calculated to assess functional dominance (selection effects). As for functional diversity (complementarity effects), multitrait functional diversity indices were computed. The first hypothesis was tested using structural equation modeling. For the second hypothesis, effects of environmental variables such as slope and altitude were tested first, and separate linear mixed-effects models were fitted afterward for functional diversity, functional dominance, and both. Results showed that AGC varied significantly along the slope gradient, with lower values at steeper sites. Species diversity (richness) had positive relationship with AGC, even when slope effects were considered. As predicted, diversity effects on AGC were mediated through functional diversity and functional dominance, suggesting that both the niche complementarity and the selection effects are not exclusively affecting carbon storage. However, the effects were greater for functional diversity than for functional dominance. Furthermore, functional dominance effects were strongly transmitted by CWM of maximum plant height, reflecting the importance of forest vertical stratification for diversity–carbon relationship. We therefore argue for stronger complementary effects that would be induced also by complementary light-use efficiency of tree and species growing in the understory layer.
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Tree diameter at breast height (dbh) and height are the most important variables used in forest inventory and management as well as forest carbon-stock estimation. In order to identify the key stand variables that influence the tree height-dbh relationship and to develop and validate a suit of models for predicting tree height, data from 5961 tree samples aged from 6 years to 53 years and collected from 80 Chinese-fir plantation plots were used to fit 39 models, including 33 nonlinear models and 6 linear models, were developed and evaluated into two groups. The results showed that composite models performed better in height estimate than one-independent-variable models. Nonlinear composite Model 34 and linear composite Model 6 were recommended for predicting tree height in Chinese fir plantations with a dbh range between 4 cm and 40 cm when the dbh data for each tree and the quadratic mean dbh of the stand (Dq) and mean height of the stand (Hm) were available. Moreover, Hm could be estimated by using the formula Hm=11.707×ln(Dq)-18.032. Clearly, Dq was the primary stand variable that influenced the height-dbh relationship. The parameters of the models varied according to stand age and site. The inappropriate application of provincial or regional height-dbh models for predicting small tree height at local scale may result in larger uncertainties. The method and the recommended models developed in this study were statistically reliable for applications in growth and yield estimation for even-aged Chinese-fir plantation in Huitong and Changsha. The models could be extended to other regions and to other tree species only after verification in subtropical China.
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The relationship between tree height and diameter is fundamental in determining community and ecosystem structure as well as estimates of biomass and carbon storage. Yet our understanding of how tree allometry relates to climate and whole organismal function is limited. We used the Forest Inventory and Analysis National Program database to determine height–diameter allometries of 2,976,937 individuals of 293 tree species across the United States. The shape of the allometric relationship was determined by comparing linear and nonlinear functional forms. Mixed-effects models were used to test for allometric differences due to climate and floristic (between angiosperms and gymnosperms) and functional groups (leaf habit and shade tolerance). Tree allometry significantly differed across the United States largely because of climate. Temperature, and to some extent precipitation, in part explained tree allometric variation. The magnitude of allometric variation due to climate, however, had a phylogenetic signal. Specifically, angiosperm allometry was more sensitive to differences in temperature compared to gymnosperms. Most notably, angiosperm height was more negatively influenced by increasing temperature variability, whereas gymnosperm height was negatively influenced by decreasing precipitation and increasing altitude. There was little evidence to suggest that shade tolerance influenced tree allometry except for very shade-intolerant trees which were taller for any given diameter. Tree allometry is plastic rather than fixed and scaling parameters vary around predicted central tendencies. This allometric variation provides insight into life-history strategies, phylogenetic history, and environmental limitations at biogeographical scales.
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Information about competition responses is mainly available for monospecific stands or mixed stands with a small number of species. Studies on complex multi-species and highly structured forest ecosystems are scarce. Accordingly, the objective of this study was to quantify competition effects and analyse competition responses in a species-diverse afrotemperate forest in South Africa, based on an observational study with mapped tree positions and long-term diameter increment records. The sensitivity to competition was analysed for individual species and involved the calculation of the slope of the linear relation between the value of a competition index (CI) and diameter growth as a measure of sensitivity. In a next step different competition indices were combined and tree diameters were grouped in three classes as surrogates for canopy status and ontogenetic stage. Five competition indices were found to be effective in showing sensitivity to competition for a number of canopy and sub-canopy species. Significant linear regressions were fitted for 18 of a total of 25 species. Species reactions varied significantly in their sensitivity to the different CIs. The indices were classified as belonging to two groups, those that responded more to local crowding and those that are more sensitive to overtopping, which revealed species-specific sensitivities to both factors. The analysis based on diameter classes revealed that species clearly changed their sensitivity to crowding or overtopping depending on diameter. Canopy and sub-canopy species showed distinct differences in their reactions. The application of multiple CIs brought novel insights relating to the dynamics of afrotemperate forests. The response patterns to different competition indices that focus on crowding and overtopping are varied and tree diameter dependent, indicating that oversimplified assumptions are not warranted in the interpretation of CI- growth relations.
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Tree height is a key variable for estimating tree biomass and investigating tree life history, but it is difficult to measure in forests with tall, dense canopies and wide crowns. The traditional method, which we refer to as the ‘tangent method’, involves measuring horizontal distance to the tree and angles from horizontal to the top and base of the tree, while standing at a distance of perhaps one tree height or greater. Laser rangefinders enable an alternative method, which we refer to as the ‘sine method’; it involves measuring the distances to the top and base of the tree, and the angles from horizontal to these, and can be carried out from under the tree or from some distance away.We quantified systematic and random errors of these two methods as applied by five technicians to a size‐stratified sample of 74 trees between 5.7 and 39.2 m tall in a Neotropical moist forest in Panama. We measured actual heights using towers adjacent to these trees.The tangent method produced unbiased height estimates, but random error was high, and in 6 of the 370 measurements, heights were overestimated by more than 100%.The sine method was faster to learn, displayed less variation in heights among technicians, and had lower random error, but resulted in systematic underestimation by 20% on average.We recommend the sine method for most applications in tropical forests. However, its underestimation, which is likely to vary with forest and instrument type, must be corrected if actual heights are needed.
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Terrestrial carbon stock mapping is important for the successful implementation of climate change mitigation policies. Its accuracy depends on the availability of reliable allometric models to infer oven-dry aboveground biomass of trees from census data. The degree of uncertainty associated with previously published pantropical aboveground biomass allometries is large. We analyzed a global database of directly harvested trees at 58 sites, spanning a wide range of climatic conditions and vegetation types (4004 trees ≥ 5 cm trunk diameter). When trunk diameter, total tree height, and wood specific gravity were included in the aboveground biomass model as co-variates, a single model was found to hold across tropical vegetation types, with no detectable effect of region or environmental factors. The mean percent bias and variance of this model was only slightly higher than that of locally fitted models. Wood specific gravity was an important predictor of aboveground biomass, especially when including a much broader range of vegetation types than previous studies. The generic tree diameter-height relationship depended linearly on a bioclimatic stress variable E, which compounds indices of temperature variability, precipitation variability and drought intensity. For cases in which total tree height is unavailable for aboveground biomass estimation, a pantropical model incorporating wood density, trunk diameter and the variable E outperformed previously published models without height. However, to minimize bias, the development of locally derived diameter-height relationships is advised whenever possible. Both new allometric models should contribute to improve the accuracy of biomass assessment protocols in tropical vegetation types, and to advancing our understanding of architectural and evolutionary constraints on woody plant development.This article is protected by copyright. All rights reserved.
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The relationship between tree height (h) and tree diameter at breast height (dbh) is an important element describing forest stands. In addition, h often is a required variable in volume and biomass models. Measurements of h are, however, more time consuming compared to those of dbh, and visual obstructions, rounded crown forms, leaning trees and terrain slopes represent additional error sources for h measurements. The aim of this study was therefore to develop h–dbh relationship models for natural tropical forest in Tanzania. Both general forest type specific models and models for tree species groups were developed. A comprehensive data set with 2 623 trees from 410 different tree species collected from a total of 1 191 plots and 38 sites covering the four main forest types of miombo woodland, acacia savanna, montane forest and lowland forests was applied. Tree species groups were constructed by using a k-means clustering procedure based on the h–dbh allometry, and a number of different non-linear model forms were tested. When considering the complexity of natural tropical forests in general and in particular variations of h–dbh relationships due to high species diversity in such forests, the model fit and performance were considered to be appropriate. Results also indicate that tree species group models perform better than forest type models. Despite the fact that the residual errors level associated with the models were relatively high, the models are still considered to be applicable for large parts of Tanzanian forests with an appropriate level of reliability.