Allometric Equations for Estimating Carbon Stocks in Natural Forest in New Zealand

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 provide a quantitative framework that aids in forest management, carbon accounting, and ecological research. Nevertheless, few studies have developed allometric equations for this species in this part of India, which differs ecologically from the other parts of India where most allometric studies have been done. To fill this gap, we developed allometric equations to estimate the volume, biomass, and carbon In the Sal forest of the Poanta Sahib Forest Division of Himachal Pradesh. We selected the pure plantation area of Shorea robusta. Thirty trees were selected randomly in each of the diameter classes (10-20 to 80-90 cm), and in each diameter class, ten trees each In the large, medium, and small categories were measured for diameter at breast height (DBH) and tree height. Therefore, in all240samples, trees were measured. The tree volume, biomass, and carbon were estimated using linear and non-linear functions. For each dependent variable (volume, biomass, or carbon), we compared models using multiple measures of goodness-of-fit as well as Thell's-U statistics and, lastly, cross-validation to assure further adequacy. For all of the selected parameters, the power function (Y =a (D2H) x), where Y is the dependent variable, D is the diameter at breast height, and H is the tree height, was the best fitted. To estimate stem volume based on dbh with an adjusted R2 value of (0.981), based on height (R2 value 0.722), basal area (R2 value 0.981), and D2H (R2 value 0.999), homogenously for biomass, the power function was best fitted with adjusted values of (0.918) based on diameter at breast height, (0.722) height, (0.981) based on basal area, and (0.999) based on D2H. Similarly, an adjusted R2 value for biomass carbon with diameter at breast height as an independent variable was 0.981, height as an independent variable was 0.722, basal area was 0.981, and D2H was 0.999. After testing the model, the power function fit the best among all linear and non-linear functions, and the combination of both diameter and height (D2H) was the best variable with 99 percent accuracy.

: Problem statement: There was no information about the relationship between growth parameters, such as diameter and height and tree component biomass of Khaya ivorensis plantations with different soil types. The objectives of this study were, first, to determine and compare the growth of K. ivorensis in three different (Padang Besar, Durian and Rengam) soil series of Ultisols and, second, to develop an allometric equation that estimates the biomass accumulation of the K. ivorensis plantation in three different soil series five years after planting. Approach: This study was conducted at a K. ivorensis plantation in the Forest Research Institute Malaysia (FRIM) Research Station in Segamat, Johor, Malaysia. The tree height (H) and Diameter at Breast Height (DBH) were measured to evaluate the growth performance of the K. ivorensis plantation. Five sampled or trees stand of K. ivorensis in each soil series were destructively analyzed. Results: The highest growth rates in terms of MAI diameter and height, and basal area were found for the Padang Besar soil series, which was followed by the Durian and Rengam soil series. The best fit regression of site-specific equations developed from the independent variable D are recommended for estimating tree component biomass and stem volume in each site. A single allometric equation using D was applicable for the estimation of biomass and stem volume however, in Padang Besar, stem biomass and stem volume were estimated with an equation using D2H. The highest stem volume and biomass accumulation value were recorded at Padang Besar (77.99 m3 h-1 and 63.16 t ha-1, respectively), which was followed by the Durian (53.10 m3 h-1 and 46.33t ha-1, respectively) and Rengam soil series (43.13 m3 h-1 and 40.96 t ha-1, respectively). Conclusion: Differences in the growth and biomass accumulation data indicate that forest productivity of K. ivorensis was affected by different site conditions. The higher growth performance and productivity of K. ivorensis in terms of the stem volume and biomass accumulation in Padang Besar compared those in the Durian and Rengam soil series shows that the species was able to adapt to the soil characteristics of the Padang Besar soil series.

Amazonian tropical forests are critical to global carbon cycling and sequestration, and in direct danger from deforestation. In order to contribute to limited existing literature on the carbon sequestration potential of secondary forest ecosystems and their aboveground biomass (AGB), we established permanent 0.2-ha plots in a primary and a secondary forest near Iquitos, Loreto, Peru. We measured diameter at breast height (DBH), tree height, and wood density for trees ≥10 cm DBH and took the diameter of lianas at 30 cm shoot extension, then used published allometric equations to estimate AGB and compare it between forests. Trees within the primary forest plot had a significantly greater mean DBH and higher mean wood density, as well as a greater overall AGB than trees within the secondary forest. AGB was calculated to be 322.05 Mg/ha for the primary forest and 51.17 Mg/ha for the secondary forest. Sequestered carbon quantities were 151.36 Mg/ha and 24.05 Mg/ha, respectively. Higher estimates of stored carbon within the primary forest are attributed to old- growth trees with large DBH values and increased wood density, and discrepancies between our carbon estimates for the secondary forest and past estimates for the same site suggest the need to focus more research and attention on allometric equation use. The results of this study provide a potential incentive for carbon sequestration funding to be awarded to the primary forest property studied and establish a foundation for future estimations of the carbon storage capacities of tropical secondary forests.

Key messageWe used lightweight terrestrial laser scanning (TLS) to detect over 3000 stems per hectare across a 12-ha permanent forest plot in French Guiana, 81% of them < 10 cm in trunk diameter. This method retrieved 85% of the trees of a classic inventory. Finally, TLS revealed that stem positions of the classic inventory had geolocation errors of up to 6 m.ContextAccurate position mapping of tropical rainforest trees is crucial for baseline studies of tropical forest ecology but is labor-intensive. Terrestrial lidar scanning (TLS) is broadly used in temperate forest inventories, but its use in rainforests is restricted to the determination of individual tree volumes within small survey areas.AimsMapping tree stems across one large (12-ha) rainforest plot, including trees less than 10 cm DBH, and evaluating the precision of traditional mapping approaches.MethodsWe used lightweight TLS, co-registered the acquisitions, and developed a new efficient algorithm to process the TLS data.ResultsWe detected 36,422 stems of which 29,665 (81%) were < 10 cm in diameter at breast height (DBH). Of the trees ≥ 10 cm DBH previously censused in the plot, 85% were identified by TLS. Automatic DBH estimation from TLS data had an RMSE of 6 cm. RMSE was improved to 3 cm by a manual verification of the shape and quality of the stem points. The initial census map had substantial bias in tree geolocation with a maximum value around 6 m.ConclusionLightweight TLS technology is a promising tool for the estimation of stem tapering and volume. Here, we show that it also facilitates the establishment of large tropical forest inventories, by improving the positioning of trees, thus increasing the accuracy of forest inventories and their cost-effectiveness.

Tropical forests are becoming increasingly alien-dominated through the establishment of timber plantations and secondary forests. Despite widespread recognition that afforestation results in increased evapotranspiration and lower catchment yields, little is known of the impacts of timber plantations on water balance relative to native forest. Native forest trees have been claimed to use water conservatively and enhance groundwater recharge relative to faster-growing alien species, and this argument should motivate native forest preservation and restoration. However, data have been available primarily for leaf-level gas exchange rather than for whole-plant and stand levels. We measured sap flow of dominant tree and tree fern species over eight weeks in native Metrosideros polymorpha forest and adjacent alien timber plantations on the island of Hawai'i and estimated total stand transpiration. Metrosideros polymorpha had the lowest values of sap flux density and whole-tree water use (200 kg m(-2) sapwood d(-1), or 8 kg/d for trees of 35 cm mean diameter at breast height, D), substantially less than timber species Eucalyptus saligna or Fraxinus uhdei (33 and 34 kg/d for trees of 73 and 30 cm mean D, respectively). At the stand level, E. saligna and F. uhdei trees had three- and ninefold higher water use, respectively, than native M. polymorpha trees. Understory Cibotium tree ferns were most abundant in M. polymorpha-dominated forest where they accounted for 70% of water use. Overall, F. uhdei plantation had the highest water use at 1.8 mm/d, more than twice that of either E. saligna plantation or M. polymorpha forest. Forest water use was influenced by species composition, stem density, tree size, sapwood allocation, and understory contributions. Transpiration varied strongly among forest types even within the same wet tropical climate, and in this case, native forest had strikingly conservative water use. Comparisons of vegetation cover in water use should provide additional resolution to ecosystem valuation and land management decisions.

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Stem volume is a critical factor in managing and evaluating forest resources. At present, stem volume is commonly estimated indirectly by constructing a taper model that utilizes sampling, diameter at breast height (DBH), and tree height. However, these estimates are constrained by errors arising from spatial and stand environment variations as well as uncertainties in height measurements. To address these issues, this study aimed to accurately estimate stem volume using light detection and ranging (LiDAR) technology, a key tool in modern precision forestry. LiDAR data were used to build comprehensive three-dimensional models of forests with multi-platform LiDAR systems. This approach allowed for precise measurements of tree heights and stem diameters at various heights, effectively mitigating the limitations of earlier measurement methods. Based on these data, a Kozak taper curve was developed at the individual tree level using LiDAR-derived tree height and diameter estimates. Integrating this curve with LiDAR data enabled a hybrid approach to estimating stem volume, facilitating the calculation of diameters at points not directly identifiable from LiDAR data alone. The proposed method was implemented and evaluated for two economically significant tree species in Korea: Pinus koraiensis and Larix kaempferi. The RMSE comparison between the taper curve-based approach and the hybrid volume estimation method showed that, for Pinus koraiensis, the RMSE was 0.11 m3 using the taper curve-based approach and 0.07 m3 for the hybrid method, while for Larix kaempferi, the RMSE was 0.13 m3 and 0.05 m3, respectively. The estimation error of the hybrid method was approximately half that of the taper curve-based approach. Consequently, the hybrid volume estimation method, which integrates LiDAR and the taper model, overcomes the limitations of conventional taper curve-based approaches and contributes to improving the accuracy of forest resource monitoring.

The influence of scan mode and circle fitting on tree stem detection, stem diameter and volume extraction from terrestrial laser scans

Accurate derivation of stem curve and volume using backpack mobile laser scanning

Summary Allometric equations are currently used to estimate above‐ground biomass (AGB) based on the indirect relationship with tree parameters. Terrestrial laser scanning (TLS) can measure the canopy structure in 3D with high detail. In this study, we develop an approach to estimate AGB from TLS data, which does not need any prior information about allometry. We compare these estimates against destructively harvested AGB estimates and AGB derived from allometric equations. We also evaluate tree parameters, diameter at breast height (DBH) and tree height, estimated from traditional field inventory and TLS data. Tree height, DBH and AGB data are collected through traditional forest inventory, TLS and destructive sampling of 65 trees in a native Eucalypt Open Forest in Victoria, Australia. Single trees are extracted from the TLS data and quantitative structure models are used to estimate the tree volume directly from the point cloud data. AGB is inferred from these volumes and basic density information and is then compared with the estimates derived from allometric equations and destructive sampling. AGB estimates derived from TLS show a high agreement with the reference values from destructive sampling, with a concordance correlation coefficient (CCC) of 0·98. The agreement between AGB estimates from allometric equations and the reference is lower (CCC = 0·68–0·78). Our TLS approach shows a total AGB overestimation of 9·68% compared to an underestimation of 36·57–29·85% for the allometric equations. The error for AGB estimates using allometric equations increases exponentially with increasing DBH, whereas the error for AGB estimates from TLS is not dependent on DBH. The TLS method does not rely on indirect relationships with tree parameters or calibration data and shows better agreement with the reference data compared to estimates from allometric equations. Using 3D data also enables us to look at the height distributions of AGB, and we demonstrate that 80% of the AGB at plot level is located in the lower 60% of the trees for a Eucalypt Open Forest. This method can be applied in many forest types and can assist in the calibration and validation of broad‐scale biomass maps.

The influence of scanner parameters on the extraction of tree metrics from FARO Photon 120 terrestrial laser scans

Tree ferns (order Cyatheales) are a key component of wet forests globally, providing critical forest understorey structure and ecosystem functions. Tree ferns may be impacted by ungulates in novel habitats, but the extent and severity of these impacts are often uncertain. We aimed to determine the impact of introduced deer on tree ferns in wet forests of south‐eastern Australia. Using both broadscale deer abundance and impact surveys and targeted tree fern assessments, we surveyed browsing impacts on tree ferns at over 200 sites across a range of wet forest types in south‐eastern Australia where deer are present. Tree fern species, plant height and estimates of foliage biomass removed by browsing were recorded for over 4500 individual tree ferns including 1871 Cyathea australis , 2622 Dicksonia antarctica and 41 Todea barbara . Browsing impacts on tree ferns were recorded at 96% of surveyed sites, with a third to a half of tree ferns typically impacted by browsing at each site. There were no differences in recorded impact between tree fern species. Browsing of tree ferns was strongly height dependent, regardless of species, and associated with indices of deer density. Tree ferns &lt; 100 cm were often highly impacted (mean &gt; 20% foliage browsed), with impact declining approximately linearly with height to 200 cm, typically low 200 to 300 cm, and absent thereafter. The widespread and in many cases severe browsing on tree ferns recorded can be largely attributable to introduced deer. These impacts potentially threaten tree fern populations and diminish the vegetation structure and ecosystem function of these wet forests. Management interventions to reduce deer populations in the wet forests of south‐eastern Australia are critical to protect forest integrity and function.

The competitive neighbourhood surrounding an individual tree can have a significant influence on its diameter at breast height (DBH) and individual tree stem volume (SV). Distance dependent competition index metrics are rarely recorded in traditional field campaigns because they are laborious to collect and are spatially limited. Remote sensing data could overcome these limitations while providing estimation of forest attributes over a large area. We used unoccupied aerial vehicle laser scanning data to delineate individual tree crowns (ITCs) and calculated crown size and distance-dependent competition indices to estimate DBH and SV. We contrasted two methods: (i) Random Forest (RF) and (ii) backwards-stepwise, linear multiple regression (LMR). We utilized an existing experiment in Pinus taeda L. plantations including multiple planting densities, genotypes and silvicultural levels. While the tree planting density did affect the correct delineation of ITCs, between 61% and 99% (mean 86%) were correctly linked to the planting location. The most accurate RF and LMR models all included metrics related to ITC size and competitive neighbourhood. The DBH estimates from RF and LMR were similar: RMSE 3.05 and 3.13 cm (R2 0.64 and 0.62), respectively. Estimates of SV from RF were slightly better than for LMR: RMSE 0.06 and 0.07 m3 (R2 0.77 and 0.70), respectively. Our results provide evidence that ITC size and competition index metrics may improve DBH and SV estimation accuracy when analysing laser-scanning data. The ability to provide accurate, and near-complete, forest inventories holds a great deal of potential for forest management planning.

Allometric relationships of stem volume and stand level carbon stocks at varying stand density in Swietenia macrophylla King plantations, Bangladesh