An Inventory of the Above Ground Biomass in the Mau Forest Ecosystem, Kenya

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.

Tree biomass plays a key role in sustainable management by providing different aspects of ecosystem. Estimation of above ground biomass by non-destructive means requires the development of allometric equations. Most researchers used DBH (diameter at breast height) and TH (total height) to develop allometric equation for a tree. Very few species-specific allometric equations are currently available for shrubs to estimate of biomass from measured plant attributes. Therefore, we used some of readily measurable variables to develop allometric equations such as girth at collar-height (GCH) and height of girth measuring point (GMH) with total height (TH) for A. rotundifolia, a mangrove species of Sundarbans of Bangladesh, as it is too dwarf to take DBH and too irregular in base to take Girth at a fixed height. Linear, non-linear and logarithmic regression techniques were tried to determine the best regression model to estimate the above-ground biomass of stem, branch and leaf. A total of 186 regression equations were generated from the combination of independent variables. Best fit regression equations were determined by examining co-efficient of determination (R2), co-efficient of variation (CV), mean-square of the error (MSerror), residual mean error (Rsme), and F-value. Multiple linear regression models showed more efficient over other types of regression equation. The performance of regression equations was increased by inclusion of GMH as an independent variable along with total height and GCH.

Estimating aboveground volume of diverse urban tree species: Developing allometric equations for higher taxonomic levels

The high activity of urban communities anthropogenic especially in Jakarta City cause high rates of carbon emissions. This problem is increased with the high rate of deforestation which is high enough in urban areas. One of ecosystem that can reduce carbon emissions is coastal forest ecosystem. Forests can reduce carbon emissions in the atmosphere and storing it in various compartments such as vegetation, litter and soil organic matter. One of the islands which have a coastal forest with good enough condition is Kotok Besar Island, the cluster of Seribu Islands. This study aims to estimate the carbon stored in tree stands at coastal forest region of west side of Kotok Besar Island, Seribu Islands. Methods of calculating carbon stock was done by making the observation plots and distributed by random sampling method to calculate diameter at breast height (dbh) and identify the type of tree stands were found in the observation plots. dbh data was inserted into allometric equation to obtain the potential of stored carbon estimates. The results showed that the coastal forest of west side of the Kotok Besar Island have the number of plant species that dominate as many as four species, which consists of Thespesia populnea, Casuarina sp., Calophyllum sp., and Cocos nucifera. Biomass value is 853.94 tons / ha and potential of carbon stored is 426.97 tons/ha.

Allometric equations for estimating the aboveground volume of five common urban street tree species in Daegu, Korea

Regrowth of native woody vegetation has the potential to provide an economically valuable source of carbon storage and other ecosystem services. There is a lack of readily applicable examples of how regrowth of forests and woodlands can be integrated with existing grazing production systems and provide soil-protection and water-retention benefits. A system of integrated vegetation bands (IVB) was applied to patchy regrowth of acacia and eucalypt vegetation in a grazed landscape of southern Queensland, Australia. Across a 39.8-ha catchment with 3–5% slope, regrowth of scattered native vegetation (18.4 ha) was surveyed and diameter at breast height and height for all woody plants were recorded. The IVB (6.3 ha) were then marked out as 25-m-wide bands set 100 m apart and offset at ~2–3% gradient to the contour line, retaining the densest/largest regrowth where possible. The data on diameter at breast height and height were analysed using allometric equations to compare aboveground biomass in the original regrowth condition (‘Original’) to that retained in the installed IVB (‘IVB-Riparian’). Estimates of aboveground biomass were calculated for the Original and IVB-Riparian and compared with three other potential regrowth-vegetation management ‘treatments’ in a desktop-modelling study. The models were designated as: (1) ‘Original’; (2) ‘Broad’ (broad-scale cleared with only a few large trees along a creek retained)’; (3) ‘Big Trees’ (only large trees >40 cm diameter at breast height retained); (4) ‘Riparian-IVB (bands of vegetation); and (5) ‘Riparian-IVB-Big Trees’ (large trees together with ‘IVB-Riparian’). In the non-forested area of the catchment, ‘Riparian-IVB-Big Trees’ (301 t), ‘Big Trees’ (249 t) and ‘Riparian-IVB’ (200 t) had the highest aboveground biomass retained, whereas ‘Broad’ resulted in the most pasture area (~33 ha) followed by ‘Riparian-IVB’ (~26 ha). The ‘Riparian-IVB’ treatment had the highest tree density within the vegetation bands and more than half (53%) of the original woody biomass in regrowth was retained on just under a quarter (23%) of the land area minimising the impact on the area of pasture/grazing land. This subsequently resulted in the ‘Riparian-IVB’ treatment having the highest carbon offset value (A$605 ha–1). The results demonstrate that the retention of native regrowth vegetation in either IVB or as large paddock trees can retain a large amount of aboveground biomass, with IVB having greater returns per hectare.

Estimating the biomass of terrestrial forests generally, and mangrove forests in particular, is an area of considerable interest. Most approaches rely on empirically derived allometric models to predict tree biomass. The single parameter with the strongest predictive ability in most studies is diameter at breast height (DBH); however the use of DBH arose primarily out of convenience, not from an analysis of tree form. While DBH explains a lot of variability in other tree metrics such as height or above ground biomass, its utility in smaller species is uncertain. Here we used measurements from 302 destructively sampled mangrove trees of four species to test which of three bole diameter measurements, basal stem diameter (BSD), diameter at 30 cm (D30), and DBH, is the best predictor of aboveground biomass. D30 had the highest mean coefficient of determination (R2) and lowest mean root mean squared error (RMSE) across all site/species combinations. However, the improvement over DBH was modest, with a mean across all site/species combinations of 1.58 kg RMSE and R2 of 0.948 for D30, compared to 1.63 kg RMSE and R2 of 0.917 for DBH. Nevertheless, D30 may have utility in future studies as it allows for lower size thresholds and has better overall explanatory power than DBH.

Mathematical relations that use easily measured variables to predict difficult-to-measure variables are important to resource managers. In this paper we develop allometric relations to predict total aboveground biomass and individual components of biomass (e.g., leaves, stems, branches) for three species of mangroves for Everglades National Park, Florida, USA. The Greater Everglades Ecosystem is currently the subject of a 7.8-billion-dollar restoration program sponsored by federal, state, and local agencies. Biomass and production of mangroves are being used as a measure of restoration success. A technique for rapid determination of biomass over large areas is required. We felled 32 mangrove trees and separated each plant into leaves, stems, branches, and for Rhizophora mangle L., prop roots. Wet weights were measured in the field and subsamples returned to the laboratory for determination of wet-to-dry weight conversion factors. The diameter at breast height (DBH) and stem height were also measured. Allometric equations were developed for each species for total biomass and components of biomass. We compared our equations with those from the same, or similar, species from elsewhere in the world. Our equations explained ≥93% of the variance in total dry weight using DBH. DBH is a better predictor of dry weight than is stem height and DBH is much easier to measure. Furthermore, our results indicate that there are biogeographic differences in allometric relations between regions. For a given DBH, stems of all three species have less mass in Florida than stems from elsewhere in the world.

The changes in the land use and land cover (LULC), above ground biomass (AGB) and the associated above ground carbon (AGC) stocks were assessed in Lidder Valley, Kashmir Himalaya using satellite data (1980–2013), allometric equations and phytosociological data. Change detection analysis of LULC, comprising of eight vegetation and five non-vegetation types, indicated that 6% (74.5 km2) of the dense evergreen forest has degraded. Degraded forest and settlement increased by 20 and 52.8 km2, respectively. Normalized difference vegetation index was assessed and correlated with the field-based biomass estimates to arrive at best-fit models for remotely sensed AGB estimates for 2005 and 2013. Total loss of 1.018 Megatons of AGB and 0.5 Megatons of AGC was estimated from the area during 33-year period which would have an adverse effect on the carbon sequestration potential of the area which is already facing the brunt of climate change.

Allometric equations and carbon sequestration potential of mango (Mangifera indica) and avocado (Persea americana) in Kenya

Studies on mangroves in Sri Lanka are mostly confined to the western, north-western and southern parts. Thus, the main objective of this study was to determine the distribution, abundance and diversity of true mangrove species, identify mangrove communities and calculate the carbon stocks of five mangrove ecosystems in the Eastern coast of Sri Lanka namely Pottuvil, Hada Oya, Ragamwela, Panama and Okanda. Mangroves were sampled using 84 randomly allocated 1010 m2 plots. True mangrove species were identified, height and diameter at breast height (dbh) of trees >10 cm dbh were recorded. Species density, frequency, dominance and different diversity indices were calculated. Plant communities were identified using multivariate analysis procedures. Biomass and carbon stocks were estimated using allometric equations. Soil samples were collected from top 0.3 m layer in five randomly selected locations in each plot. Pooled samples were used to determine soil organic carbon (loss on ignition method), salinity, conductivity, pH and total dissolved solutes. Light intensity below and away from the canopy was determined and net photosynthesis rate was estimated. Nine true mangroves were recorded in Panama estuarine lagoon and the least number of species (3) were recorded from Ragamwela creek. Highest Shannon diversity value (H’=1.7) and the lowest Simpson index (0.22) was obtained for the Panama mangrove. Nearly half of the true mangrove species (11) that have been recorded from Sri Lanka occurs in the five study sites. Seven different plant communities were identified in the analysis. Soil salinity showed a significant difference among sites, while pH did not vary very much. Highest total organic carbon was recorded in Pottuvil lagoon (558.4±131.8 t/ha), and the lowest in Ragamwela creek (200.9±38.5 t/ha). The highest above ground carbon was recorded in Hada Oya estuary (336.0±123.0 t/ha), while lowest in Ragamwela creek (76.1±60.2 t/ha). Net photosynthesis rates were similar among study sites, the highest was recorded in Hada Oya estuary (2,445.1±553.3 gcm-2/year). It can be concluded that the mangroves in the Eastern province have a moderate diversity with high carbon stock. However, as most mangroves are under different anthropogenic threats, it is immediately required to take measures to conserve them. Keywords: Mangrove ecosystem, Community structure, Species diversity

Multiple linear regression based on the crown diameter (the most explicative biometric variable for pollarded trees) and diameter at breast height indices produced the more parsimonious model with moderate accuracy to estimate leaf biomass used to feed livestock in strongly seasonal silvopastures. The aim of this study is to develop allometric equation to estimate leaf biomass of pollarded Lebanon oak trees, a species used as fodder tree in western Iran. A pollarded stand (6.6 ha in area including 560 Lebanon oak trees) was selected. Full callipering of all trees (collar diameter ≥5 cm) was conducted: collar diameter and diameter at breast height (DBH) of stem, tree height, trunk height, and crown diameters (CDs) were measured. At the time of pollarding, the fresh weight of leafy branches resulting from pollarding of each tree was measured. Finally, dry weight of leaf biomass for entire crown was determined. Biometric indices as predictor variables for estimating dry weight of leaf biomass were used. Multiple linear regression based on CD and stem DBH produced the more parsimonious model. The results indicated that natural logarithmic transformation of dry weight of leaf biomass improved the model’s goodness of fit. The moderate accuracy of the proposed allometric equation is explained by the scattered distribution of the trees and the strong modification of canopy structure through periodical pollarding. Leaf biomass estimate is used to evaluate the impact of pollarding on nutrient cycling and carbon sequestration in forest.

Better information regarding the spatial variability of height, Diameter at Breast Height (DBH) and stocking could improve inventory estimates at the operational Planning Unit since these parameters are used extensively in allometric equations, including stem volume, biomass and carbon calculations. In this study, the influence of stand stocking on height and DBH of two even aged radiata pine (Pinus radiata D. Don) stands were investigated using airborne Light Detection and Ranging (LiDAR) data at a study site in New South Wales, Australia. Both stands were characterized by irregular stocking due to patchy establishment and self-thinning in the absence of any silvicultural thinning events. For the purpose of this study, a total of 34 plots from a 34 year old site and 43 plots from a nine year old site were established, from which a total of 447 trees were sampled. Within these plots, DBH and height measurements were measured and their relationships with stocking were evaluated. LiDAR was used for height estimation as well as stem counts in fixed plots (stocking). The results showed a significant relationship between stem DBH and stocking. At both locations, trees with larger diameters were found on lower stocking sites. Height values were also significantly correlated with stocking, with taller trees associated with high stocking. These results were further verified of additional tree samples, with independent field surveys for DBH and LiDAR-derived metrics for height analysis. This study confirmed the relationship between P. radiata tree heights and stem diameter with stocking and demonstrated the capacity of LiDAR to capture sub-compartment variation in these tree-level attributes.

Abstract. Karyati, Ipor IB, Jusoh I, Wasli ME. 2019. Allometric equations to estimate the above-ground biomass of trees in the tropical secondary forests of different ages. Biodiversitas 20: 2427-2436. The allometric equations for trees of secondary forests of different ages in abandoned lands after shifting cultivation are still rarely available. The objective of this study was to develop allometric equations to estimate the above-ground biomass (AGB) of trees (DBH of > 5 cm) in the tropical secondary forest of different ages, namely 5, 10, and 20 years after abandonment. The selected trees in this study represented the dominant and rare species and DBH classes in each study site. The trunk dry biomass and AGB showed strong correlations (adjusted R2= 0.59-0.95) with diameter at breast height (DBH) and height. The leaf and branch dry biomass had weak correlations with height (adjusted R2=0.36-0.50). The developed allometric equations were suitable for trees of secondary forests of different ages, because the selected samples used in the destructive method were based on a field inventory data of forest structure and floristic composition.

ABSTRACTAim It is increasingly accepted that the mean wood density of trees within a forest is tightly coupled to above‐ground forest biomass. It is unknown, however, if a positive relationship between forest biomass and mean community wood density is a general phenomenon across forests. Understanding spatial variation in biomass as a function of wood density both within and among forests is important for predicting changes in stored carbon in response to global change, and here we evaluated the generality of a positive biomass–wood density relationship within and among six tropical forests.Location Costa Rica, Panama, Puerto Rico and Ecuador.Methods Individual stem data, including diameter at breast height and spatial position, for six forest dynamics plots were merged with an extensive wood density database. Individual stem biomass values were calculated from these data using published statistical models. Total above ground biomass, total basal area and mean community wood density were also quantified across a range of subcommunity plot sizes within each forest.Results Among forests, biomass did not vary with mean community wood density. The relationship between subcommunity biomass and mean wood density within a forest varied from negative to null to positive depending on the size of subcommunities and forest identity. The direction of correlation was determined by the associated total basal area–mean wood density correlation, the slope of which increased strongly with whole forest mean wood density.Main conclusions There is no general relationship between forest biomass and wood density, and in some forests, stored carbon is highest where wood density is lowest. Our results suggest that declining wood density, due to global change, will result in decreased or increased stored carbon in forests with high or low mean wood density, respectively.