Equations For Aboveground Biomass Research Articles

UAV-RGB-image-based aboveground biomass equation for planted forest in semi-arid Inner Mongolia, China

The acquisition of high-resolution aboveground biomass (AGB) data cost-effectively and expeditiously represents a formidable challenge within the domain of current ecosystem surveillance. Plot-based inventory, the conventional approach for estimating and validating remote sensing data, is nonetheless costly and constrained in terms of spatial coverage. The expeditious advancements in unmanned-aerial-vehicle (UAV) technology furnish the potential to devise AGB equations that transcend traditional diameter-height-based equations alongside techniques for quantifying forest structural parameters through standard RGB aerial imagery. Since the canopy diameter (CD) and tree height (H) can be directly ascertained from UAV-derived datasets, biomass equations parameterized by CD and H may be more valuable. In the present investigation, we established AGB equations predicated on data procured from a UAV outfitted with a high-resolution RGB camera, specifically for planted sparsely Pinus sylvestris forest in central Inner Mongolia, China. Utilizing the aerial imagery, we generated the digital terrain model (DTM), digital surface model (DSM) and the digital orthophoto image (DOM). Then, the canopy height model (CHM) was obtained by subtracting DSM from DTM to extract the H and CD of individual trees. This methodology's CD (R2 = 0.85, RMSE = 0.203 m) and H (R2 = 0.77 and RMSE = 0.671 m) obtained closely mirrored the in-situ measurements. Six prospective AGB equations were constructed for the Pinus sylvestris forest, taking H and CD extracted from UAV aerial survey datasets as the dependent variables. The accuracy of the AGB estimation was appraised by employing extant allometric growth equations, which were parameterized using the ground-measured tree diameter at breast height (DBH) and H. The most efficacious biomass equation, predicated on H and CD data extracted from UAV aerial surveys, was delineated as W=2.3442CD∗H0.9057(R2 = 0.731, RMSE = 2.46 kg), thus presenting a convenient tool for estimating the AGB of sparse Pinus sylvestris forests in semi-arid locales.

Species-specific and generalized allometric equations for improving aboveground biomass estimations of 33 understory woody species in northeastern China forest ecosystems

Understory small trees and shrubs play a crucial role in the biogeochemical cycles in forest ecosystems. However, their biomass in northeastern China is still uncertain and has been heavily disregarded due to the limited number of available allometric equations. For this study, 782 plants from 33 species obtained by the destructive method were used to develop species-specific and generalized aboveground allometric biomass equations based on collar diameter ( D) and height ( H) using weighted nonlinear seemingly unrelated regression. Each biomass component was shown to be well predicted by D alone, with R2 adj. values mostly greater than 0.80. The majority of species performed better in the models for wood and aboveground biomass when H was included as D2 H. Furthermore, generalized equations for the two components showed a comparatively large coefficient of variation but comparable Bias to species-specific equations, especially for small trees. It is recommended to estimate biomass using generalized equations for mixed species only when species-specific equations are unavailable at a given site. However, in the event when precision is not the primary concern, generalized equations are also suggested. The developed equations will help to improve the accuracy of biomass assessment of understory woody plants in northeastern China forest ecosystems.

New aboveground biomass equations by components for small black spruce in peatland ecosystems of Western Canada

Black spruce is the most common tree species in Canada, dominating treed peatlands where they are usually stunted. We used 495 destructively sampled trees from 56 plots to develop allometric models of aboveground biomass by components (stem, branches, and needles) for small (<5 m tall) black spruce from peatlands in the Taiga Plains and Boreal Plains Ecozones of Western Canada, for which there were no specific models available of biomass by components. We used leave-one-plot-out cross-validation to assess transferability and compare our models with existing national and ecozone-specific equations. Our models predicted total tree biomass with better accuracy and less biased estimates than the national model (relative RMSE: 30% versus 35% national; relative bias: +1% versus –12% national). Similar results were obtained in other external datasets. Existing ecozone equations performed worse than either our models or the national ones. When we applied the models at the plot level to predict aboveground biomass density (Mg·ha−1), our models outperformed the national model again (relative RMSE: 15.9% versus 18.6% national, relative bias: +3.5% versus –13.6% national). These results indicate that at least for peatlands of Western Canada, our models provide better aboveground biomass estimates for small black spruce trees than existing models.

Using terrestrial laser scanning to evaluate non-destructive aboveground biomass allometries in diverse Northern California forests

A crucial part of carbon accounting is quantifying a tree’s aboveground biomass (AGB) using allometric equations, but species-specific equations are limited because data to inform these equations requires destructive harvesting of many trees which is difficult and time-consuming. Here, we used terrestrial laser scanning (TLS) to non-destructively estimate AGB for 282 trees from 5 species at 3 locations in Northern California using stem and branch volume estimates from quantitative structure models (QSMs) and wood density from the literature. We then compared TLS QSM estimates of AGB with published allometric equations and used TLS-based AGB, diameter at breast height (DBH), and height to derive new species-specific allometric AGB equations for our study species. To validate the use of TLS, we used traditional forestry approaches to collect DBH (n = 550) and height (n = 291) data on individual trees. TLS-based DBH and height were not significantly different from field inventory data (R2 = 0.98 for DBH, R2 = 0.95 for height). Across all species, AGB calculated from TLS QSM volumes were approximately 30% greater than AGB estimates using published Forest Service’s Forest Inventory and Analysis Program equations, and TLS QSM AGB estimates were 10% greater than AGB calculated with existing equations, although this variation was species-dependent. In particular, TLS AGB estimates for Quercus agrifolia and Sequoia sempervirens differed the most from AGB estimates calculated using published equations. New allometric equations created using TLS data with DBH and height performed better than equations that only included DBH and matched most closely with AGB estimates generated from QSMs. Our results support the use of TLS as a method to rapidly estimate height, DBH, and AGB of multiple trees at a plot-level when species are identified and wood density is known. In addition, the creation of new TLS-based non-destructive allometric equations for our 5 study species may have important applications and implications for carbon quantification over larger spatial scales, especially since our equations estimated greater AGB than previous approaches.

Allometric Equations for the Biomass Estimation of Calophyllum inophyllum L. in Java, Indonesia

Reliable data on CO2 quantification is increasingly important to quantify the climate benefits of forest landscape restoration and international commitments, such as the Warsaw REDD+ Framework and Nationally Determined Contributions under the Paris Agreement. Calophyllum inophyllum L. (nyamplung as a local name or tamanu tree for the commercial name) is an increasingly popular tree species in forest landscape restoration and bioenergy production for a variety of reasons. In this paper, we present allometric equations for aboveground biomass (AGB), belowground biomass (BGB), and total above- and belowground biomass (TABGB) predictions of C. inophyllum L. Data collection was carried out twice (2017 and 2021) from 40 trees in Java, Indonesia. Allometric equations using the natural logarithm of diameter at breast height (lnDBH) and ln height (lnH) for biomass prediction qualified the model’s fit with statistical significance at 95% of the confidence interval for AGB, BGB, and TABGB predictions. The results showed that the linear models using both lnDBH and lnH were well fit and accurate. However, the model with lnDBH is more precise than the model using lnH. Using lnDBH as a predictor, the R2 values were 0.923, 0.945, and 0.932, and MAPE were 24.7, 37.0, and 25.8 for AGB, BGB, and TABGB, respectively. Using lnH as a predictor, the R2 values were 0.887, 0.918, and 0.898 and MAPE were 37.4, 49.0, and 39.8 for AGB, BGB, and TABGB, respectively. Consequently, the driven allometric equations can help accurate biomass quantification for carbon-trading schemes of C. inophyllum L.

Using TLS-Measured Tree Attributes to Estimate Aboveground Biomass in Small Black Spruce Trees

Research Highlights: This study advances the effort to accurately estimate the biomass of trees in peatlands, which cover 13% of Canada’s land surface. Background and Objectives: Trees remove carbon from the atmosphere and store it as biomass. Terrestrial laser scanning (TLS) has become a useful tool for modelling forest structure and estimating the above ground biomass (AGB) of trees. Allometric equations are often used to estimate individual tree AGB as a function of height and diameter at breast height (DBH), but these variables can often be laborious to measure using traditional methods. The main objective of this study was to develop allometric equations using TLS-measured variables and compare their accuracy with that of other widely used equations that rely on DBH. Materials and Methods: The study focusses on small black spruce trees (<5 m) located in peatland ecosystems of the Taiga Plains Ecozone in the Northwest Territories, Canada. Black spruce growing in peatlands are often stunted when compared to upland black spruce and having models specific to them would allow for more precise biomass estimates. One hundred small trees were destructively sampled from 10 plots and the dry weight of each tree was measured in the lab. With this reference data, we fitted biomass models specific to peatland black spruce using DBH, crown diameter, crown area, height, tree volume, and bounding box volume as predictors. Results: Our best models had crown size and height as predictors and outperformed established AGB equations that rely on DBH. Conclusions: Our equations are based on predictors that can be measured from above, and therefore they may enable the plotless creation of accurate biomass reference data for a prominent tree species in a common ecosystem (treed peatlands) in North America’s boreal.

Equations for estimating the above- and belowground biomass of grey alder (Alnus incana (L.) Moench.) and common alder (Alnus glutinosa L.) in Latvia

ABSTRACT This study aims to derive individual tree allometric equations for the above- and belowground biomass components of grey and common alder based on data sets obtained in Latvia. The species aboveground biomass data consisted of 81 trees collected in 27 forest stands. The belowground biomass data were obtained from 27 common alder and 28 grey alder trees sampled throughout Latvia. For grey and common alder, the root-to-shoot ratio decreased with increasing tree dimensions. Our analysis revealed that biomass functions currently used in the national forest inventory overestimate grey alder and underestimate common alder biomass stocks in Latvia. Our findings indicate that the existing local aboveground biomass equation has an overall satisfactory predictive ability compared to the derived equations in this study. The equations from southern Sweden underestimate biomass for mature trees and overestimate small tree biomass, suggesting that even in the hemiboreal region, the grey and common alder populations could have a different distribution of biomass allocated to various components. Model examinations indicated that the derived allometric functions for grey and common alder were unbiased and performed well within the data range and are the best available to substantially improve national estimates of carbon sequestration and biomass resources in Latvia.

Allometric Equations for Aboveground Biomass Estimation of <i>Osyris quadripartita</i> (African Sandalwood) in Semi-arid Woodlands, Southern Ethiopia

African sandalwood, Osyris quadripartita Salzm. ex Decne is cosmopolitan in dry evergreen forest, rocky ridges, and forest edges, habitually with Olea europaea as well as Dodonaea angustifolia woodland in East Africa and Ethiopia. It reaches in Africa from Ethiopia to Algeria and Kenya to South Africa, starting from stunted shrubs to tall trees. Osyris quadripartita is culturally important for herbal medicine and religious activities, and also, commercially for the perfumery oil industry. Recently, the population of the species is endangered in some places, because of overexploitation for commercial values. Even though the species has many economic and ecological functions, its environmental uses like carbon storage and global climate change mitigation are less assessed. Therefore, the study aimed to develop species-specific allometric equations for Osyris quadripartita using a destructive method and to evaluate allometric models for estimating the aboveground biomass (AGB) within the semi-arid woodlands forest of Southern Ethiopia. Subsequently, all the needed biomass calculations were done, eight AGB equations were developed. Based on regression equations AGB is related with a diameter at breast height (DBH), height (H), and density (ρ) both individually and in combination. Out of eight, four allometric equations were chosen based on goodness-of-fit statistics, and the others four are rejected. The chosen models were tested for accuracy supported on observed data. The selected models have best fitted with higher R2-adj and lower residual standard error and Akaike information criterion than rejected equations. The relations for four selected models are significant (p < 0.001), which showed a strong correlation of AGB with selected dendrometric variables. Accordingly, the AGB was strongly correlated with three variables combination DBH, Height & Wood density. Individually, AGB was strongly interrelated with DBH, but not significantly interrelated with height and wood density. A specific species equations are better for determining biomass and carbon evaluation than general equations.

Allometric Equations for Shrub and Short-Stature Tree Aboveground Biomass within Boreal Ecosystems of Northwestern Canada

Aboveground biomass (AGB) of short-stature shrubs and trees contain a substantial part of the total carbon pool within boreal ecosystems. These ecosystems, however, are changing rapidly due to climate-mediated atmospheric changes, with overall observed decline in woody plant AGB in boreal northwestern Canada. Allometric equations provide a means to quantify woody plant AGB and are useful to understand aboveground carbon stocks as well as changes through time in unmanaged boreal ecosystems. In this paper, we provide allometric equations, regression coefficients, and error statistics to quantify total AGB of shrubs and short-stature trees. We provide species- and genus-specific as well as multispecies allometric models for shrub and tree species commonly found in northwestern boreal forest and peatland ecosystems. We found that the three-dimensional field variable (volume) provided the most accurate prediction of shrub multispecies AGB (R2 = 0.79, p &lt; 0.001), as opposed to the commonly used one-dimensional variable (basal diameter) measured on the longest and thickest stem (R2 = 0.23, p &lt; 0.001). Short-stature tree AGB was most accurately predicted by stem diameter measured at 0.3 m along the stem length (R2 = 0.99, p &lt; 0.001) rather than stem length (R2 = 0.29, p &lt; 0.001). Via the two-dimensional variable cross-sectional area, small-stature shrub AGB was combined with small-stature tree AGB within one single allometric model (R2 = 0.78, p &lt; 0.001). The AGB models provided in this paper will improve our understanding of shrub and tree AGB within rapidly changing boreal environments.

Can fallen trees enhance aboveground biomass estimation? A proposal for the Brazilian Atlantic Forest

Introduction: Estimating aboveground biomass (AGB) in protected forests is a challenge, due to high costs and legal restrictions for direct assessments, and also to frequently weak estimation provided by general AGB equations. Objective: We propose a new approach that uses dead fallen trees (DFTs) to improve AGB estimation. We aim to analyse if the adjustment of allometric models based on DFTs provides a suitable local equation for AGB estimation or helps to validate existing pantropical or regional allometric equations. Methods: The study was carried out at the Dois Irmãos State Park (PEDI), Pernambuco, Northeast Brazil. Along 4 000 m, using the line intersect technique, we sampled 37 recent dead fallen trees ranging from 7.6 to 92.3 cm in diameter and from 8.6 to 29.4 m in height. Nine models were adjusted, and the best equation (local) was compared to regional and pantropical equations. Results: One equation (AGBkg= 1.5292* DBH2.0601*TH-0.2187) produced biomass estimates which did not differ from the observed values (P &gt; 0.05). Differently from the others, this equation overestimated AGB in only 2.8 % and, along with other parameters of analysis (R2adj and Syx %) had the best overall performance. Analysing the performance of the local equation versus available equations for estimating AGB, we found that only the local and the pantropical equations by Pearson et al. (2005) estimated values that were not significantly different from observed values. However, the local equation is more appropriate for local estimation of AGB, since it has the lowest RSME and CV. Conclusions: Based on the proposed approach, we were able to offer a local equation for tree AGB estimation based on fallen trees. The DFT method is efficient regarding time and costs, avoiding tree logging in protected forests and helps to guide the choice of a proper equation for forest AGB demands.

Single-species allometric equations for above-ground biomass of most abundant long-lived pioneer species in semi-deciduous rain forests of the central region of Cameroon

The implementation of REDD+ and AFR100 mechanisms require the availability of reliable allometric models, which are mathematical functions for estimating forest biomass from independent variables such as diameter at breast height (dbh), crown diameter, wood density and tree height. Although many equations have been developed to estimate tree biomass in undegraded forests, very few models have been developed for secondary forest species. The aim of this study was to establish single-species allometric models for estimating biomass of pioneer species in semi-deciduous forests in the central region of Cameroon and to evaluate their accuracy. Data of above-ground biomass were obtained from destructive sampling of 103 pioneer trees belonging to three species: Distemonanthus benthamianus, Musanga cecropioides and Trema orientalis. Model comparison were based on Akaike Information Criterion (AIC), average deviation and the coefficient R2adj. The different tests with combinations of dendrometric variables shows that whatever the species considered, the diameter at breast height appears as a good single predictor of biomass (Adjuted R²adj ˃ 0.97 in all three species). The use of the crown diameter in the model in Musanga cecropioides has considerably improved the quality of the fit. However, the consideration of these three variables in the model gave even better results (Adj.R² = 0.978-0.988). The comparison of these present models with the equations previously developed shows that the models in this article provide a better estimate of biomass. However, several important data from semi-deciduous forest remain essential for the adjustment of multi-specie models.

Single-species allometric equations for above-ground biomass of most abundant long-lived pioneer species in semi-deciduous rain forests of the central region of Cameroon.

Single-species allometric equations for above-ground biomass of most abundant long-lived pioneer species in semi-deciduous rain forests of the central region of Cameroon.

Estimation and Spatio-temporal Patterns of Carbon Emissions from Grassland Fires in Inner Mongolia, China

Grassland fires results in carbon emissions, which directly affects the carbon cycle of ecosystems and the carbon balance. The grassland area of Inner Mongolia accounts for 22% of the total grassland area in China, and many fires occur in the area every year. However, there are few models for estimation of carbon emissions from grassland fires. Accurate estimation of direct carbon emissions from grassland fires is critical to quantifying the contribution of grassland fires to the regional balance of atmospheric carbon. In this study, the regression equations for aboveground biomass (AGB) of grassland in growing season and MODIS NDVI (Normalized Difference Vegetation Index) were established through field experiments, then AGB during Nov.–Apr. were retrieved based on that in Oct. and decline rate, finally surface fuel load was obtained for whole year. Based on controlled combustion experiments of different grassland types in Inner Mongolia, the carbon emission rate of grassland fires for each grassland type were determined, then carbon emission was estimated using proposed method and carbon emission rate. Results revealed that annual average surface fuel load of grasslands in Inner Mongolia during 2000–2016 was approximately 1.1978 × 1012 kg. The total area of grassland which was burned in the Inner Mongolia region over the 17-year period was 5298.75 km2, with the annual average area of 311.69 km2. The spatial distribution of grassland surface fuel loads is characterized by decreasing from northeast to southwest in Inner Mongolia. The total carbon emissions from grassland fires amounted to 2.24 × 107 kg with an annual average of 1.32 × 106 for the study area. The areas with most carbon emissions were mainly concentrated in Old Barag Banner and New Barag Right Banner and on the right side of the Oroqin Autonomous Banner. The spatial characteristics of carbon emission depend on the location of grassland fire, mainly in the northeast of Inner Mongolia include Hulunbuir City, Hinggan League, Xilin Gol League and Ulanqab City. The area and spatial location of grassland fires can directly affect the total amount and spatial distribution of carbon emissions. This study provides a reference for estimating carbon emissions from steppe fires. The model and framework for estimation of carbon emissions from grassland fires established can provide a reference value for estimation of carbon emissions from grassland fires in other regions.

Tree-Level Above-Ground Biomass Equations for Pinus sylvestris L. in Mongolia

Allometric equations have been used as a main tool to quantify forest above-ground biomass. Therefore, the development of species-specific allometric equations is essential to accurately estimate forest biomass. The present study aims at developing species-specific equations for above-ground biomass (AGB) estimation for Pinus sylvestris L. in northern Mongolia. A total of 35 sample trees were harvested from natural Scots pine forests in the northeastern Khangai and western Khentii forest regions. Evaluating the statistical relationships of AGB against predictor variables, three allometric equations were formulated. Stem diameter at breast height (D) and height (H) were measured, and the biomass of stem, branches and needles were weighed, separately. AGB was regressed against stem D and H individually, and in combination. The best-fitting equations with a higher coefficient of determination and lower residual standard error were selected using model performance statistics. The most well performing biomass model was the logarithmic equation lnŶ = lna + b x lnD + c x lnH for the estimation of the total AGB, the stem, branch and needle masses. The biomass model is the important tool for accurate estimation of Scots pine forest biomass and carbon stocks in Mongolia.

Allometric equations for total aboveground dry biomass and carbon content of Pinus occidentalis trees

Although precise species-specific aboveground tree biomass equations are needed in the Dominican Republic to quantify potential carbon storage in the context of climate change and sustainable forest management, there has been a lack of available information concerning total aboveground biomass and/or carbon content for naturally occurring Pinus occidentalis trees. The objectives of the study were to develop species-specific allometric biomass models for P. occidentalis, as well as to assess variation in carbon concentration among stem plus bark, branches and foliage by means of chemical analyses. Predictor variables included diameter at breast height (DBH) and total tree height (H), alone and in combination. Model fitting methods employing linear and nonlinear regression techniques were used and evaluated based on goodness-of-fit criteria. Two competing biomass models produced similar goodness-of-fit statistics: model 4, fitted by the Weighted Non-linear Least Squares technique, , and model 6, fitted by modeling the variance component and applying the Maximum Likelihood method, . Average carbon concentration (%) was highest in foliage tissue (49.8%), followed by branches (46.37%) and, lastly, stem plus bark (45.95%). On average, each individual tree is storing 175 kg of total aboveground carbon. To our knowledge, this is the first account reporting carbon fraction for this tropical species. Calculated wood carbon fractions from the study can be easily incorporated into forest C accounting, and may reduce errors in forest C valuations, which nowadays are performed using global estimates published elsewhere.

Challenges in estimating forest biomass: use of allometric equations for three boreal tree species

Regionally fitted allometric equations for individual trees and root-to-shoot ratio values are normally used to estimate local aboveground and belowground forest biomass, respectively. However, uncertainties arising from such applications are poorly understood. We developed equations for both aboveground and belowground biomass using destructive sampling for three dominant upland boreal tree species in northwestern Alberta, Canada. Compared with our equations, the diameter-based national equations derived for use across Canada underestimated aboveground biomass for Picea glauca (Moench) Voss but gave reasonable estimates for Populus balsamifera L. and Populus tremuloides Michx. The national equations based on both tree diameter and height overestimated aboveground biomass for the Populus species but underestimated it for Picea glauca in our study area. The approach of root-to-shoot ratio proposed by the Intergovernmental Panel on Climate Change (IPCC) overestimated belowground biomass by 16%–41%, depending on forest cover type, in comparison with our values estimated directly on site, with the greatest bias in deciduous-dominated stands. When the general allometric equations for aboveground biomass and the root-to-shoot ratio for belowground biomass were combined to estimate stand biomass, overestimation could be as high as 18% in our study area. The results of our study support the development of improved regional allometric equations for more accurate local-scale estimations. Incorporating intraspecific variation of important traits such as tree taper may be especially helpful.

Development of a dynamic growth model for sweet chestnut coppice: A case study in Northwest Spain

Sweet chestnut coppice (Castanea sativa Mill.) is a species of great importance in the northwest of Spain, due to its potential for producing valuable timber in relatively short rotations. However, abandonment has resulted in unstable and degraded stands. Thus, there is a need to improve forestry decision making tools. The objective of this study is the development of a dynamic stand growth model for the sweet chestnut comprised of three transition functions (dominant height, basal area and number of stems per hectare). They are used to estimate rates of change in the stand between an initial point in time and a point in the future. The data comes from two inventories of an unmanaged network of plots which incorporate all the variability in conditions in the region for the study species (climate, soil, stocking, site quality etc.). ADA and GADA approaches were used to develop the three transition functions. The model achieved high accuracy (explaining >90% of variability). The model incorporates an initialization function (explaining 60% of variability) for predicting initial stand basal area in stands without diameter inventories, which can be used to establish the starting point for the simulation, and, in addition, the biomass expansion factor (BEF) for this species (expressed as a constant value of 0.60) and a new single aboveground biomass equation (explaining almost 80% of variability) were calculated. A case study shows how to apply these decision making tools for the sustainable management of sweet chestnut coppice.

Biomass estimation equations for mesquite trees in the Americas.

Mesquite trees are the preferred dendroenergy sources in arid and semi-arid forests. In spite of their relative importance, regional aboveground biomass (AGB) equations for mesquite trees are scarce in the scientific literature. For that reason, the aims of this study were to: (a) harvest trees and develop regional biomass equations; (b) contrast measured data with equations developed previously; and (c) test the applicability of the fitted equation for mesquite trees in the arid and semi-arid forests of the Americas. We harvested 206 new mesquite trees from arid and semi-arid forests in northern Mexico (Coahuila, Nuevo Leon, and Tamaulipas) in addition to using two other previously compiled data sets from Mexico (N = 304) to develop a regional equation. To test the validity of this equation, for biomass equations reported for the rest of the country, as well as for North and South American mesquite trees, we contrasted AGB measurements with predictions of fitted equations. Statistical analysis revealed the need for a single, regional, semi-empirical equation as together the three data sets represented the variability of the aboveground biomass of mesquite trees across northern Mexico, as well as mesquite trees in America’s arid and semiarid regions. Due to the large quantity of mesquite trees harvested for sampling and their variability, the regional biomass equation developed encompasses all other North and South American equations, and is representative of mesquite trees throughout the arid and semi-arid forests of the Americas.

Carbon sequestration and nitrogen uptake in a temperate silvopasture system

Agroforestry systems (AFS) have the potential to foster long-term carbon sequestration and nutrient uptake. Yet, information on sequestration rates is still scarce, especially for AFS in temperate regions and for maturing AFS. This study aims to determine the rate and amount of carbon and nitrogen uptake in a 17-year-old northern red oak (Quercus rubra)–pecan (Carya illinoinensis) silvopastoral planting in Fayetteville, AR, USA. Seven oak and pecan trees were felled to develop AFS-specific allometric equations for above-ground biomass, carbon, and nitrogen. Tree-stand woody biomass (DWw), carbon (Cw) and nitrogen (Nw) and leaf biomass (DWL), carbon (CL), and nitrogen (NL) were calculated with these equations. Diameter at 1.37 m above ground (DBH) was measured annually, and a non-linear mixed-effect model was used to estimate absolute (AGR) and relative growth rates. DWw and Cw was 7.1 and 3.4 Mg ha−1 for pecan and 26.6 and 12.7 Mg ha−1 for oak, which corresponds to a carbon sequestration rate of 0.75 and 0.20 Mg C ha−1 yr−1, respectively. Total N uptake was approximately 66 and 71 g N tree−1 yr−1 for oak and pecan. The mixed-effect model with individual-tree-level random effects for all parameters provided the best representation of DBH growth of oak and pecan, likely due to the high heterogeneity of site characteristics. The AGR explained the non-linear plant growth and reached its maximum of 0.017 and 0.0179 m yr−1 for oak and pecan, respectively, 11 years after planting. This suggests that carbon and nitrogen uptake also declined after 11 years.

A comparison of multiple methods for mapping local-scale mesquite tree aboveground biomass with remotely sensed data

A local-scale mesquite tree (Prosopis glandulosa Torr.) aboveground biomass map contribute to our understanding of the spatial distribution of woody plant aboveground biomass, and carbon stocks and fluxes in rangeland ecosystems. The objective of the study was examining a methodological approach to use airborne lidar data and multispectral imagery to create very high spatial resolution local-scale mesquite tree aboveground biomass maps by comparing three statistical methods and identifying significant prediction variables. The three statistical methods were the stepwise regression, the least absolute shrinkage and selection operator (LASSO), and the random forests. These methods were applied to establish the mesquite tree aboveground biomass equations and model from the in-situ mesquite tree aboveground biomass with the lidar metrics and multispectral data. The results showed the stepwise regression and LASSO had limited adj-R2 and MSE. However, the random forests method with combined multispectral imagery and lidar data presented acceptable MSE and R2 (1.08 Mg ha−1 and 0.37). In summary, the random forests method with combined multispectral imagery and lidar data offered the most reliable and reasonable combination to generate a very high spatial resolution local-scale mesquite tree aboveground biomass map.