Equations For Aboveground Biomass Research Articles

Carbon Storage Potential of Ethiopian Highland Bamboo (Arundinaria alpina (K. schum): A Case Study of Adiyo Woreda, South West Ethiopia

Estimation of above ground biomass are required for better planning, sustainable management and monitoring of change in carbon stock in natural stands of bamboo ecosystem. Biomass assessment, the selection or development of reliable allometric biomass equations is an essential step which determines largely the accuracy of the resulted biomass estimates. Unfortunately, only few studies on biomass estimation and allometric biomass equations have been conducted for Ethiopia Highland bamboo and the results are usually not publicly accessible or well documented. Thus, the objective of this study was to estimate carbon storage capacity of natural bamboo stand and develop species-specific allometric equations for above-ground biomass (AGB) estimations for Ethiopia Highland bamboo (Arundinaria alpine). The study site was divided into three landforms based on slope percent from the bottom to the top of the mountain. Accordingly, the three landforms were categorized as flat-gentle slopping (0-20) Slope (20-40) and steep slope (40-60). In each of three land- forms four plots of size of 10 x10m each were laid at every 200m distance between each plot. A total of twelve study plots were taken from the three land forms. Age and DBH of the plants of each plot was taken and plants were grouped into three age class as 3 years of age.

Taxon-specific modeling systems for improving reliability of tree aboveground biomass and its components estimates in tropical dry dipterocarp forests

The dry dipterocarp forest (DDF) is a major and unique forest type in Asia providing both protection and production functions. DDF's role as a carbon sink is important in Asia, but there is a deficiency in existing biomass models for these forests. This study aimed to develop simultaneous modeling systems to estimate tree above-ground biomass (AGB) and its components for mixed species, dominant family, genera, and species. Twenty-eight 0.25 ha plots in the Central highlands and one 1 ha plot in the Southeast ecoregion in Viet Nam were measured. A total of 329 trees were destructively sampled to obtain a dataset of the dry biomass of the stem (Bst), branches (Bbr), leaves (Ble), bark (Bba), and AGB. Using K-fold cross validation, we compared AGB predictions from independently developed AGB equation and from a system of biomass equations that estimated component biomass and AGB simultaneously. The estimation methods for independent equation was weighted nonlinear regression fit by maximum likelihood and for simultaneous system it was weighted nonlinear seemingly unrelated regression (SUR) fit by generalized least squares. We also examined different modeling systems for different plant classification at taxonomic levels. The selected form of taxon-specific modeling systems were AGB = a1 × Db11 × Hb12 × WDb13 + a2 × Db21 + a3 × Db31 + a4 × Db41 for mixed species and dominant Dipterocarpaceae family and AGB = a1 × Db11 + a2 × Db21 + a3 × Db31 + a4 × Db41 for dominant genera of Dipterocarpus and Shorea. The predictors of D, H, and WD are diameter at breast height, tree height and wood density, respectively. Compared to the mixed species modeling system, genus-specific modeling systems improved the reliability of AGB estimation substantially and will reduce the cost of application because the only predictor required for measurement is D. The pantropical genus-specific modeling systems are more reliable than pantropical mixed species models.

Additive aboveground biomass equations based on different predictors for natural Tilia Linn

Biomass is a basic quantitative character of forest ecosystem. Biomass data are foundation of researching many forestry and ecology problems. Accurate quantification of tree biomass is critical and essential for calculating carbon storage, as well as for studying climate change, forest health, forest productivity, nutrient cycling, etc. Constructing biomass models is considered a good approach to estimate forest biomass. Based on biomass data of 97 sampling trees of natural Tilia Linn. in Xiaoxing'an Mountains and Zhangguangcai ranges, three additive systems of individual tree biomass equations were developed: based on tree diameter at breast height (D) only, based on tree diameter at breast height and height (H), and based on the best models. The nonlinear seemly unrelated regression was used to estimate the parameters in the additive system of biomass equations. The heteroscedasticity in model residuals was addressed by applying a unique weight function to each equation. The individual tree biomass model validation was accomplished by Jackknifing technique. The results showed that three additive systems of individual tree biomass equations could fit and predict the biomass of Tilia Linn. well (adjusted coefficient of determination Ra2>0.84, mean predicted error percentage MPE<8.5%, mean absolute error MAE<16.3 kg,mean standard error percentage MPSE<28.5%). The biomass equations of stem and aboveground were better than biomass equations of branch, foliage and crown. Adding total tree height and crown factor in the additive systems of biomass equations could significantly improve model fitting performance and predicting precision (Ra2 improved from 0.01 to 0.04, MAE decreased from 0.01 to 4.55 kg), narrow the confidence interval of the predicted value and the biomass of stem, foliage and aboveground were increased more than the biomass of branch and crown. In general, the equations of the additive system based on the best models produced the best model fitting, followed by that of the additive system based on D and H, and that based on D. It was essential to develop biomass model by adding total tree height and crown factor.

Aboveground biomass equations for the predominant conifer species of the Inland Northwest USA

Assessment of aboveground biomass stocks in the coniferous forests of the inland northwest USA is important for timber, bioenergy, and carbon inventories, as well as for wildfire risk determination. In this study, individual tree biomass equation systems are developed for 7 regionally important conifer species using data from 470 felled trees sampled across 84 stands and spanning a range of diameters at breast height (1.37 m; dbh) running from 5 cm to 105 cm. The equation systems permit estimation of crown biomass components (i.e., foliage, dead branches, and live branches by size class) and stem components (abovestump stemwood and stembark), as well as compatible estimates of (sub)totals. The systems draw on commonly collected inventory variables including dbh, tree height, and live crown length. All biomass components scaled approximately linearly with dbh on the logarithmic scale, but equation systems drawing on both dbh and height provided more accurate estimates for all species; systems drawing additionally on live crown length provided more accurate estimates still for all species but one. In line with previous work, incorporation of live crown length improved live crown component equations most, but also improved stem component equations for two species. Across species and systems, stem components and subtotals were most accurately estimated (mean absolute errors ∼10%) while dead branch biomass estimation proved least tractable (mean absolute errors >50%). Overall, the reported biomass equation systems draw on the largest felled tree samples collected from the region, and provide the most comprehensive basis developed to date for regional forest biomass assessments over the inland northwest.

Compatible above-ground biomass equations and carbon stock estimation for small diameter Turkish pine (Pinus brutia Ten.).

Small trees and saplings are important for forest management, carbon stock estimation, ecological modeling, and fire management planning. Turkish pine (Pinus brutia Ten.) is a common coniferous species and comprises 25.1% of total forest area of Turkey. Turkish pine is also important due to its flammable fuel characteristics. In this study, compatible above-ground biomass equations were developed to predict needle, branch, stem wood, and above-ground total biomass, and carbon stock assessment was also described for Turkish pine which is smaller than 8cm diameter at breast height or shorter than breast height. Compatible biomass equations are useful for biomass prediction of small diameter individuals of Turkish pine. These equations will also be helpful in determining fire behavior characteristics and calculating their carbon stock. Overall, present study will be useful for developing ecological models, forest management plans, silvicultural plans, and fire management plans.

Allometric equations for aboveground biomass estimation of Olea europaea L. subsp. cuspidata in Mana Angetu Forest

ABSTRACTIntroduction: African wild olive, Olea europaea L. subsp. cuspidata (Wall. ex G. Don) Cif., L ‘Olivicoltore is widely distributed in dry forest and forest margins, often with Juniperus procera, in east Africa and Ethiopia. It reaches southern Africa, also India and China, ranging from tall trees to stunted shrubs. Does best in good forest soil, but hardy and drought resistant once established, even in poor soils. It is used for firewood, charcoal, poles, posts, timber (furniture, carving, floors, and paneling), medicine (stem, bark, and leaves), bee forage, milk flavoring (smoking wood), toothbrushes (twigs), and walking sticks. Although the species has many economic and ecological functions, its environmental uses like carbon storage and climate change mitigation are less assessed. Therefore, the objective of the study was to develop species-specific allometric equations for O. europaea L. subsp. cuspidata using semi-destructive method and evaluate allometric models for estimating the aboveground biomass (AGB).Results and Discussions: After all the necessary biomass calculations were done, seven AGB equations were developed. These regression equations relate AGB with diameter at breast height (DBH), height (H), and density (ρ) individually and in combination. Out of seven, four allometric equations were chosen based on goodness-of-fit statistics and three were rejected. The selected models were tested for accuracy based on observed data. The best models selected have higher R2-adj and lower residual standard error and Akaike information criterion than rejected equations. The relations for all selected models are significant (p < 0.000), which showed strong correlation of AGB with selected dendrometric variables. Accordingly, the AGB was strongly correlated with DBH and was not significantly correlated with wood density and height individually in O. europaea L. subsp. cuspidata allometric equation development. In combination, AGB was strongly correlated with DBH and height; DBH and wood density; and the combination of DBH, height, and wood density. Species-specific equations are used for better carbon assessment than general equations.

Aboveground Biomass Equations for Small Trees of Brutian Pine in Turkey to Facilitate Harvesting and Management

Brutian pine (Pinus brutia Ten.) is the most widespread conifer species in the Eastern Mediterranean. Aboveground biomass equations for small diameter brutian pine trees are needed for accurate fuel inventory and to assess carbon sequestration potential. In this study, we developed tree biomass models based on 143 brutian pine saplings measured in 11 research plots. Aboveground biomass (AGB) was modeled with a nonlinear mixed effects model which accounted for the variability among plots. The predicted total AGB was then distributed into foliage, branch and stem components. The Beta, Dirichlet, and multinomial logistic regressions were unbiased in their estimates of biomass component proportions. The Dirichlet regression has the advantage of an additive property and does not require non-standard data.

Compatible biomass models of natural spruce (Picea asperata)

By using nonlinear measurement error method, the compatible tree volume and above ground biomass equations were established based on the volume and biomass data of 150 sampling trees of natural spruce (Picea asperata). Two approaches, controlling directly under total aboveground biomass and controlling jointly from level to level, were used to design the compatible system for the total aboveground biomass and the biomass of four components (stem, bark, branch and foliage), and the total ground biomass could be estimated independently or estimated simultaneously in the system. The results showed that the R2 of the one variable and bivariate compatible tree volume and aboveground biomass equations were all above 0.85, and the maximum value reached 0.99. The prediction effect of the volume equations could be improved significantly when tree height was included as predictor, while it was not significant in biomass estimation. For the compatible biomass systems, the one variable model based on controlling jointly from level to level was better than the model using controlling directly under total above ground biomass, but the bivariate models of the two methods were similar. Comparing the imitative effects of the one variable and bivariate compatible biomass models, the results showed that the increase of explainable variables could significantly improve the fitness of branch and foliage biomass, but had little effect on other components. Besides, there was almost no difference between the two methods of estimation based on the comparison.

Rubber tree allometry, biomass partitioning and carbon stocks in mountainous landscapes of sub-tropical China

Expansion of rubber plantations into sub-optimal environments has been a dominating land conversion in continental South-East Asia in the last decade. Regional evaluation of the carbon sequestration potential of rubber trees depends largely on the selection of suitable allometric equations and the biomass-to-carbon conversion factor. Most equations are age-, elevation-, or clone-specific, and their application therefore gives uncertain results at the landscape level with varying age groups, elevation ranges, and clone types. Currently, for rubber-based systems, none of the allometric equations takes environmental factors (e.g. climate, topographic condition, soil properties, and management scheme) into consideration to allow pan-tropical usage. Against this background, 30 rubber trees with a root profile of up to 2m were destructively harvested and 882 rubber trees were measured non-destructively in 27 plots, covering rotation lengths of 4–35years, elevation gradients of 621–1127m, and locally used clone types (GT1, PRIM600, Yunyan77-4) in mountainous South Western China. Allometric equations for aboveground biomass (AGB) estimations considering diameter at breast height (DBH), tree height (H), and wood density were superior to other equations. A simpler model with similar performance (AGB=0.0419DBH2.316H0.478) can be used if tree-specific wood density is not available. For belowground biomass (BGB) a model using only DBH can provide a robust prediction (BGB=0.207DBH1.668). We also tested goodness of fit for the recently proposed pan-tropical forest model, which includes a bioclimatic factor E, combining indices of temperature and precipitation variability and drought intensity. Prediction of AGB by the model calibrated with the harvested rubber tree biomass and wood density was more accurate than the results produced by the pan-tropical forest model adjusted to local conditions. The relationships between DBH and height and between DBH and biomass were influenced by tapping, therefore biomass and C stock calculations for rubber have to be done using species-specific allometric equations. Based on the analysis of environmental factors acting at the landscape level, we found that above- and belowground carbon stocks were mostly affected by stand age, soil clay content, aspect, and planting density. Increasing planting density to >570 trees per ha according to the regional plantation management strategy had a negative impact on aboveground carbon stock of old rubber plantations. The integration of bioclimatic and regional management factors is a further approach to build widely applicable biomass models for pan-tropical rubber-based systems. The results of this study provide reference for reliable carbon accounting in other rubber-cultivated regions.

Allometric Equations for Estimating Biomass and Carbon Stocks in the Temperate Forests of North-Western Mexico

This paper presents new equations for estimating above-ground biomass (AGB) and biomass components of seventeen forest species in the temperate forests of northwestern Mexico. A data set corresponding to 1336 destructively sampled oak and pine trees was used to fit the models. The generalized method of moments was used to simultaneously fit systems of equations for biomass components and AGB, to ensure additivity. In addition, the carbon content of each tree component was calculated by the dry combustion method, in a TOC analyser. The results of cross-validation indicated that the fitted equations accounted for on average 91%, 82%, 83% and 76% of the observed variance in stem wood and stem bark, branch and foliage biomass, respectively, whereas the total AGB equations explained on average 93% of the total observed variance in AGB. The inclusion of total height (h) or diameter at breast height2 × total height (d2h) as a predictor in the d-only based equations systems slightly improved estimates for stem wood, stem bark and total above-ground biomass, and greatly improved the estimates produced by the branch and foliage biomass equations. The predictive power of the proposed equations is higher than that of existing models for the study area. The fitted equations were used to estimate stand level AGB stocks from data on growing stock in 429 permanent sampling plots. Three machine-learning techniques were used to model the estimated stand level AGB and carbon contents; the selected models were used to map the AGB and carbon distributions in the study area, for which mean values of respectively 129.84 Mg ha−1 and 63.80 Mg ha−1 were obtained.

Integrating regional climate change into allometric equations for estimating tree aboveground biomass of Masson pine in China

A climate-sensitive aboveground biomass (AGB) equation, in combination with nonlinear mixed-effects modeling and dummy variable approach, was developed to examine how climate change may affect the allometric relationships between tree diameter and biomass. We showed that such changes in allometry need to be taken into account for estimating tree AGB in Masson pine. As a native species and being widely distributed in subtropical China, Masson pine (Pinus massoniana Lamb.) forests play a pivotal role in maintaining forest ecosystem functions and mitigation of carbon concentration increase at the atmosphere. Traditional biomass allometric equations do not account for a potential effect of climate on the diameter–biomass relationships. The amplitude of such an effect remains poorly documented. We presented a novel method for detecting the long-term (2041–2080) effects of climate change on the diameter–biomass relationships and the potential consequences for long-term changes of biomass accumulation for Masson pine. Our approach was based on a climate-sensitive AGB model developed using a combined nonlinear mixed-effects model and dummy variable approach. Various climate-related variables were evaluated for their contributions to model improvement. Heteroscedasticity was accounted for by three residual variance functions: exponential function, power function, and constant plus function. The results showed that diameter at breast height, together with the long-term average of growing season temperature, total growing season precipitation, mean temperature of wettest quarter, and precipitation of wettest quarter, had significant effects on values of AGB. Excessive rain during the growing season and high mean temperature in the wettest quarter reduced the AGB, while a warm growing season and abundant precipitation in the wettest quarter increased the AGB. Climate change significantly affected the allometric scale of biomass equation. The new climate-sensitive allometric model developed in this study may improve biomass predictions compared with the traditional model without climate effects. Our findings suggested that the AGB of Masson pine trees with the same diameter at breast height under three climate scenarios including representative concentration pathway (RCP) 2.6, RCP 4.5, and RCP 8.5 in the future period 2041–2080 would increase by 24.8 ± 32.7% (mean ± standard deviation), 27.0 ± 33.4%, and 27.7 ± 33.8% compared with the constant climate (1950–2000), respectively. As a consequence, we may expect a significant regional variability and uncertainty in biomass estimates under climate change.

Biomass equations for European beech growing on dry sites

Abstract: Biomass equations for European beech (Fagus sylvatica L.) trees growing on dry sites have not been published, although such equations are needed for a proper estimation of the biomass of beech trees growing naturally at their drought limit in dry forests. We aimed to: (1) develop new allometric above-ground biomass equations for European beech trees growing on dry sites; (2) compare these equations with existing biomass equations. We harvested 86 plants, ranging from saplings to trees, from forest stands on south-facing slopes at 5 locations in Germany and Switzerland. Whole plant weights were measured in the field after felling, and samples from stem, branches and leaves of every harvested plant were brought to the laboratory. We developed diameter- and height-based regression equations for the total above-ground biomass, stem with bark biomass, and biomass of the branches with leaves and further compared them with the existing equations from the literature. Our results showed that the 5 current diameter-based equations available in the literature significantly overestimate the total above-ground biomass, the stem with bark biomass and the biomass of branches and leaves. With increasing tree size, the proportion of the biomass of branches and leaves to the total tree biomass decreased significantly. We also found that the inclusion of height in biomass models did not influence the prediction of total above-ground biomass, but significantly improved the prediction of stem biomass. We recommend that researchers and foresters use the equations developed in this study to quantify the biomass of beech trees growing under similar site conditions.

Allometric models for height and aboveground biomass of dominant tree species in South African Mistbelt forests

Novel species-specific equations for the estimation of height and aboveground biomass were established for four dominant tree species (Syzygium gerrardii Burtt Davy, Combretum kraussii Hochst., Trichilia dregeana Sond. and Croton sylvaticus Hochst.), in the Northern Mistbelt Forests of South Africa. A non-destructive sampling methodology was applied, which was based on measuring standing trees, selecting smaller branches and taking core samples. The species-specific aboveground biomass equations were fitted using predictor variables such as diameter at breast height (DBH) and total height (H). The relative error of estimation was used to examine the accuracy of a pantropical biomass equation versus our established specific model. Biomass values were afterwards up-scaled from tree to stand level for each species, based on the selected models and the forest inventory data. As expected, the DBH–height relationship varied among studied species. The incorporation of both DBH and H in the biomass models significantly improved their precision. A model with DBH2 × H as a single variable was suitable for three out of the four studied species, with more than 98% of explained variance. An existing pantropical biomass equation for moist forests showed larger relative error of estimation, especially in the upper range of tree diameter. The estimated aboveground biomass density varied significantly among studied species, with the highest values recorded for S. gerrardii (87.7 ± 15.4 Mg ha−1), followed by T. dregeana (29.4 ± 14.7 Mg ha−1), C. sylvaticus (24.3 ± 11.5 Mg ha−1) and C. kraussii (20.1 ± 6.7 Mg ha−1). It is also found that species-specific production of biomass at the tree level is not always sufficient to reflect the stand-level biomass density. The results from this study contribute to accurately predict aboveground biomass, thereby improving the reliability of the estimates of forest biomass and carbon balance.

Aboveground biomass equations for evergreen broadleaf forests in South Central Coastal ecoregion of Viet Nam: Selection of eco-regional or pantropical models

As part of Viet Nam’s effort to participate in REDD+ (reducing emissions from deforestation and forest degradation), selected biomass equations were evaluated for their predictive abilities using data collected from destructively sampled 110 trees from 41 species of the evergreen broadleaf forests of the South Central Coastal region of Viet Nam. Different power models that used diameter at breast height (DBH), tree height (H), wood density (WD), and crown area (CA) as covariates to predict aboveground biomass (AGB) were evaluated. Best models were selected based on the coefficient of determination (R2), the Akaike information criterion (AIC), and root mean square percent error (RMSE). AGB was strongly related to four covariates - DBH, H, WD, and CA. While seldom mentioned in the existing literature, CA improved the accuracy of the AGB estimation. Accuracy of the selected models was validated using the random validation dataset and the model with four explanatory variables (AGB=a×(DBH2HWD)b×CAc) had the lowest mean absolute percent error of 16.9%. Using local data, a simple power model based on DBH only (AGB=a×DBHb) produced higher accuracy than the generic pantropical models that used up to three variables.

Allometric Equations for Aboveground and Belowground Biomass Estimations in an Evergreen Forest in Vietnam.

Allometric regression models are widely used to estimate tropical forest biomass, but balancing model accuracy with efficiency of implementation remains a major challenge. In addition, while numerous models exist for aboveground mass, very few exist for roots. We developed allometric equations for aboveground biomass (AGB) and root biomass (RB) based on 300 (of 45 species) and 40 (of 25 species) sample trees respectively, in an evergreen forest in Vietnam. The biomass estimations from these local models were compared to regional and pan-tropical models. For AGB we also compared local models that distinguish functional types to an aggregated model, to assess the degree of specificity needed in local models. Besides diameter at breast height (DBH) and tree height (H), wood density (WD) was found to be an important parameter in AGB models. Existing pan-tropical models resulted in up to 27% higher estimates of AGB, and overestimated RB by nearly 150%, indicating the greater accuracy of local models at the plot level. Our functional group aggregated local model which combined data for all species, was as accurate in estimating AGB as functional type specific models, indicating that a local aggregated model is the best choice for predicting plot level AGB in tropical forests. Finally our study presents the first allometric biomass models for aboveground and root biomass in forests in Vietnam.

Developing Aboveground Biomass Equations Both Compatible with Tree Volume Equations and Additive Systems for Single-Trees in Poplar Plantations in Jiangsu Province, China

We developed aboveground biomass equations for poplar plantations in Jiangsu Province, China, both compatible with tree volume equations and additive systems. Biomass equations were fitted with 80 selected and previously harvested sample trees. Additivity property was assured by applying a “controlling directly under total biomass proportion function” approach. Weighted regression was used to correct heteroscedasticity. Parameters were estimated using a nonlinear error-in-variable model. The results indicated that (1), on average, stems constituted the largest proportion (71.5%) of total aboveground biomass; (2) the aboveground biomass equations, both compatible with tree volume equations and additive systems, obtained good model fitting and prediction, of which the coefficient of determination ranged from 0.903 to 0.987, and the total relative error and the mean prediction error were less than 2.0% and 10.0%, respectively; (3) adding H and CW into the additive system of biomass equations did not improve model fitting and performance as expected, especially for branches and foliage biomass; and (4) the additive systems of biomass equations presented here provided more reliable and accurate biomass predictions than the independent biomass equations fitted by ordinary least square regression. This system of additive biomass equations will prove to be applicable for estimating biomass of poplar plantations in Jiangsu Province of China.

Aboveground biomass equations for sustainable production of fuelwood in a native dry tropical afro-montane forest of Ethiopia

Biomass equations are presented for five tree species growing in a natural forest in Ethiopia. Fitted models showed more accurate estimations than published generalized models for this dry tropical forest. Biomass equations are needed to correctly quantify harvestable stock and biomass for sustainability efforts in forest management, but this kind of information is scarce in Ethiopia. This study sought to develop biomass models for five of the most common native tree species in the Chilimo dry afro-montane mixed forest in the central highlands of Ethiopia: Allophyllus abyssinicus, Olea europaea ssp. cuspidata, Olinia rochetiana, Rhus glutinosa, and Scolopia theifolia. Comparison with generalized models was intended to show the greater accuracy of the specific models. A total of 90 trees from different diameter classes were selected, felled, and divided into different biomass compartments. Biomass equation models were fitted using joint-generalized least squares regression to ensure the additivity property between the biomass compartments and total biomass. These were the first models developed for these species in African tropical forests. Models were including diameter at breast height and total height as independent variables, obtaining more accurate biomass estimations using these models than from generalized models. Fitted models are reliable for estimating aboveground biomass in the Chilimo forest and for more general application in similar forest types. Model applicability for biomass or carbon estimation is high within forest inventory data contexts.

Solar radiation as a global driver of hillslope asymmetry: Insights from an ecogeomorphic landscape evolution model

AbstractObservations at the field, catchment, and continental scales across a range of arid and semiarid climates and latitudes reveal aspect‐controlled patterns in soil properties, vegetation types, ecohydrologic fluxes, and hillslope morphology. Although the global distribution of solar radiation on earth's surface and its implications on vegetation dynamics are well documented, we know little about how variation of solar radiation across latitudes influence landscape evolution and resulting geomorphic difference. Here, we used a landscape evolution model that couples the continuity equations for water, sediment, and aboveground vegetation biomass at each model element in order to explore the controls of latitude and mean annual precipitation (MAP) on the development of hillslope asymmetry (HA). In our model, asymmetric hillslopes emerged from the competition between soil creep and vegetation‐modulated fluvial transport, driven by spatial distribution of solar radiation. Latitude was a primary driver of HA because of its effects on the global distribution of solar radiation. In the Northern Hemisphere, north‐facing slopes (NFS), which support more vegetation cover and have lower transport efficiency, get steeper toward the North Pole while south‐facing slopes (SFS) get gentler. In the Southern Hemisphere, the patterns are reversed and SFS get steeper toward the South Pole. For any given latitude, MAP is found to have minor control on HA. Our results underscore the potential influence of solar radiation as a global control on the development of asymmetric hillslopes in fluvial landscapes.

Modeling the above and belowground biomass of planted and coppiced Eucalytpus globulus stands in NW Spain

The study developed equations for predicting aboveground and belowground biomass of planted and coppiced Eucalyptus globulus in NW Spain. It was the first published work considering site effects on aboveground biomass and first work for predicting root biomass, for this species in this region, where it covers about 310,000 ha. Eucalyptus globulus is a species of great economic relevance, being increasingly used for bioenergy. In Galicia (NW Spain), where most of the E. globulus in the country is growing, there are scarce studies modeling aboveground biomass fractions of that species, together with a lack of information on its belowground biomass. The objective of this study was to develop new and more accurate allometries for predicting E. globulus tree aboveground biomass fractions and coarse belowground biomass in NW Spain. Aboveground biomass models were calibrated by two approaches: nonlinear seemingly unrelated regressions (NSUR), using tree and stand variables, and nonlinear mixed effects (nlme) equations adding the site factor effect. Validation was made with an independent dataset (85 trees). Belowground biomass equations were constructed for planted and coppiced trees. Crown length and dominant height substantially improved the precision in leaf and branch biomass estimation (NSUR). An added value of our study was the modeling of root/shoot ratio, as a function of diameter of planted and coppiced trees, for first time in this species. This study confirms the importance of site and stand stage to explain aboveground biomass variability. Although different belowground biomass accumulation patterns were observed for planted and coppice trees, aboveground biomass equations were common.

Aboveground biomass and leaf area equations for three common tree species of Hyrcanian temperate forests in northern Iran

Biomass equations are essential for evaluating the climate change mitigation potential of forests through biomass accumulation and carbon sequestration. In northern Iran’s Hyrcanian forests, topographic relief is so extreme that developing biomass equations from destructive sampling of trees is physically challenging. In this paper, allometric biomass and leaf area equations were developed for three common Hyrcanian tree species: Oriental beech (Fagus orientalis Lipsky), chestnut-leaved oak (Quercus castaneifolia C.A.Mey.), and common hornbeam (Carpinus betulus L.). A total of 30 trees, ranging in diameter at breast height (DBH) from 21 to 90 cm, were felled and stems, branches, twigs, and leaves from each tree were measured and weighed. Allometric equations for estimating biomass from DBH and height and their combinations were derived. Model comparison and selection were based on R2, Akaike’s information criterion (AIC), prediction error sums of squares, model standard error estimate (SEE), ΔAIC, and correction factor. The best-fit equations had adjusted R2values between 0.81 to 0.98 and SEE values between 0.351 and 0.681. The allometric equations provide improved methods for predicting forest biomass and carbon storage in Hyrcanian forests from standard forestry measurements, which means these equations may be applied to historical and new forest data.