Search Results (72)

Teak (Tectona grandis L.f.) is a leading tropical plantation species valued for high-quality timber and carbon (C) storage. This study assessed stand growth across ages and sites, quantified biomass and C by tree component and stand, and developed DBH-based allometric equations for biomass and C estimation. Six stand ages (5, 6, 9, 11, 14, and 17 years) were assessed in three municipalities of Nayarit, Mexico. Dendrometric inventories in permanent plots and destructive sampling of 35 trees provided calibration data for leaves, branches, stem, and roots. C concentration was determined with an elemental analyzer, and nonlinear regression models were adjusted and validated. Stand biomass and C increased with age, peaking at ages 11–14 (>130 Mg ha⁻¹; >60 Mg C ha⁻¹), with lower values at age 17. San Blas and Rosamorada accumulated significantly more than Tuxpan, reflecting site quality. C concentration was stable across sites and ages, with stem and roots consistently ranging between 48% and 50%, and leaves and branches averaging 45%–46%. Allometric equations were most accurate for stem and total biomass/C (R² = 0.73–0.79), while foliage showed higher variability. On average, 60%–70% of biomass was allocated to the stem and 15%–20% to roots. Indicators were stable, with an aboveground-to-belowground ratio (A:B) ≈ 4.9 and a biomass expansion factor (BEF) ≈ 1.5. The current annual increment (CAI) presented two main peaks: ~20 Mg ha⁻¹ yr⁻¹ at ages 5–6 and ~11 Mg ha⁻¹ yr⁻¹ at ages 9–11, followed by a decline after age 14. Teak in western Mexico reaches peak productivity at ages 6–11, with belowground biomass essential for accurate C accounting. Full article

Pinus yunnanensis is a significant native tree species in southwestern China, contributing substantially to the area’s ecological stability and economic growth. However, its growth rate tends to be relatively slow during the seedling stage, and fertilization is crucial to promote seedling growth. This study used two-year-old P. yunnanensis seedlings as experimental materials and applied a 3 × 3 factorial design, combining three nitrogen (N) levels (0, 0.4, and 0.8 g·plant⁻¹) supplied in the form of urea with three levels of phosphorus (P) (0, 0.8, and 1.6 g·plant⁻¹) supplied in the form of superphosphate to form nine treatments, denoted as T1 to T9. This study was carried out in the open-air nursery of Southwest Forestry University, with fertilization beginning in July and observations continuing until December of the same year. Using allometric growth analysis and constructing the fertilizer response regression equation, we investigated the effects of fertilization on biomass accumulation in P. yunnanensis. The findings revealed that fertilization significantly increased the biomass allocation ratio to roots but decreased the allocation to needles and aboveground parts (p < 0.05). Allometric growth analysis showed that root growth was more rapid than stem and needle growth, and the growth rate of belowground parts exceeded that of aboveground parts. Allometric growth between organs differed among treatments, whereas the allometric growth relationship between aboveground and belowground biomass showed no significant difference across treatments. Moderate N and P fertilizer application promoted biomass accumulation in all organs, with T5 (N: 0.4 g·plant⁻¹; P: 0.8 g·plant⁻¹) exhibiting the highest biomass accumulation. Based on the comprehensive analysis of optimal N and P fertilizer requirements for biomass accumulation across different organs, the recommended fertilizer application rates are as follows: N 0.5–0.6 g·plant⁻¹ and P 0.5–0.9 g·plant⁻¹, with an optimal N:P ratio ranging from 1:0.8 to 1:1.8. The results establish a scientific rationale for enhancing fertilization methods in P. yunnanensis seedling cultivation, contributing to the slow growth issue during the seedling stage. Full article

In late August and mid-November 2024, and late February and mid-May 2025, four surveys were conducted in the Kalasuke Reservoir section of the Irtysh River, resulting in the collection of 296 samples of P. fluviatilis. Sampling tools included drift gillnets with a mesh size of 5 cm and an outer mesh size of 10 cm, bottom cages with a mesh size of 1 cm, and fishing rods (4.5 m and 5.4 m). The age structure and growth characteristics of P. fluviatilis in the reservoir were analyzed. Results showed that the body length of the sampled fish ranged from 100.53 to 305.30 mm, with the dominant length group being 100.53–150.00 mm, accounting for 90.09% of the total. Body mass ranged from 24.20 to 490.20 g, with the dominant mass group below 66.5 g, accounting for 89.86%. The age composition of the population consisted of age classes 1–5, with ages 1–2 years old being dominant, accounting for 96.2% of the total samples. Among these, 1-year-old individuals were the most abundant, accounting for 78.3%, while older fish were relatively scarce. The relationship between body length (L_t) and body mass (W_t) was modeled as W_t = 4.298 × 10⁻⁵ L_t^2.85 (R² = 0.998, n = 296). The von Bertalanffy growth equations were L_t = 652.866 [1 − e^−0.108(^t+0.778)] and W_t = 4990.21 [1 − e^−0.108(^t+0.778)]^2.85, with a growth coefficient K = 0.108. The inflection point of growth was determined to be 1.9 years by fitting growth rate and acceleration equations. The b < 3 indicates allometric growth, where body length increases faster than body mass, suggesting that P. fluviatilis prioritizes elongating its body to enhance swimming ability and expand its range, while accumulating muscle and fat at a slower pace. Principal component analysis (PCA) revealed that the cumulative contribution rate of the first three principal components was 55.45%, reflecting the morphological characteristics of the species. The accuracy of discriminant analysis for sex determination based on external morphology was 67.20%, indicating limited reliability in gender identification using only morphological traits. Full article

Climate change alters plant biomass allocation and aboveground–belowground trade-offs in grassland ecosystems, potentially affecting critical functions such as carbon sequestration. However, uncertainties persist regarding how precipitation gradients regulate (1) responses of aboveground biomass (AGB), belowground biomass (BGB), and total biomass in alpine grasslands, and (2) precipitation-mediated AGB-BGB allocation strategies. To address this, we conducted a large-scale field survey across precipitation gradients (400–700 mm/y) in the Sanjiangyuan alpine grasslands, Qinghai–Tibet Plateau. During the 2024 growing season, a total of 63 sites (including 189 plots and 945 quadrats) were sampled along five aridity classes: <400, 400–500, 500–600, 600–700, and >700 mm/y. Our findings revealed precipitation as the dominant driver of biomass dynamics: AGB exhibited equal growth rates relative to BGB within the 600–700 mm/y range, but accelerated under drier/wetter conditions. This suggests preferential allocation to aboveground parts under most precipitation regimes. Precipitation explained 31.71% of AGB–BGB trade-off variance (random forest IncMSE), surpassing contributions from AGB (17.61%), specific leaf area (SLA, 13.87%), and BGB (12.91%). Structural equation modeling confirmed precipitation’s positive effects on SLA (β = 0.28, p < 0.05), AGB (β = 0.53, p < 0.05), and BGB (β = 0.60, p < 0.05), with AGB-mediated cascades (β = 0.33, p < 0.05) dominating trade-off regulation. These results advance our understanding of mechanistic drivers governing allometric AGB–BGB relationships across climatic gradients in alpine ecosystems of the Sanjiangyuan Region on the Qinghai–Tibet Plateau. Full article

International efforts are underway to implement carbon neutrality policies in rapidly changing climate conditions. This situation has strongly demanded the discovery of novel carbon sinks. The Salix genus has attracted attention as a promising carbon sink owing to its rapid growth and efficient use as a biofuel in short-rotation cultivation. The present study aims to derive an allometric equation and conduct stem analysis as fundamental tools for estimating net primary productivity (NPP) in Salix pierotii Miq. stand, which is increasingly acknowledged as an important emerging carbon sink. The allometric equations derived showed a high explanatory rate and fitness (R² ranged from 0.74 to 0.99). The allometric equations between DBH and stem volume and biomass derived in the process of stem analysis also showed a high explanatory rate and fitness (R² ranged from 0.87 to 0.94). The NPPs calculated based on the allometric equation derived and stem analysis were 11.87 tonC∙ha⁻¹∙yr⁻¹ and 15.70 tonC∙ha⁻¹∙yr⁻¹, respectively. These results show that the S. pierotii community, recognized as the representative riparian vegetation, could play an important role as a carbon sink. In this context, an assessment of the carbon absorption capacity of riparian vegetation such as willow communities could contribute significantly to achieving carbon neutrality goals. Full article

The focus of this study was on young populations of Kandelia obovata within a constructed coastal wetland in Haicang Bay, Xiamen, Southeast China. The objective was to systematically examine their allometric growth characteristics and carbon sequestration potential over an 8-year monitoring period (2016–2024). Allometric equations were developed to estimate biomass, and the spatiotemporal variation in both plant and soil carbon stocks was estimated. There was a significant increase in total biomass per tree, from 120 ± 17 g at initial planting to 4.37 ± 0.59 kg after 8 years (p < 0.001), with aboveground biomass accounting for the largest part (72.2% ± 7.3%). The power law equation with D²H as an independent variable yielded the highest predictive accuracy for total biomass (R² = 0.957). Vegetation carbon storage exhibited an annual growth rate of 4.2 ± 0.8 Mg C·ha⁻¹·yr⁻¹. In contrast, sediment carbon stocks did not show a significant increase throughout the experimental period, although long-term accumulation was observed. The restoration of mangroves in urban coastal constructed wetlands is an effective measure to sequester carbon, achieving a carbon accumulation rate of 21.8 Mg CO₂eq·ha⁻¹·yr⁻¹. This rate surpasses that of traditional restoration methods, underscoring the pivotal role of interventions in augmenting blue carbon sinks. This study provides essential parameters for allometric modeling and carbon accounting in urban mangrove afforestation strategies, facilitating optimized restoration management and low-carbon strategies. Full article

China has implemented large-scale mangrove restoration and afforestation initiatives in recent years. However, there has been a paucity of research on the growth of mangrove seedlings in a composite stress environment and the allometric growth equation of mangrove seedlings. To enhance juvenile mangrove survival rates and develop precise carbon sequestration models, this study examines biomass accumulation patterns and allometric equation development under diverse environmental and biological conditions. A manipulative field experiment employed a three-factor full factorial design using seedlings from eight mangrove species. The experimental design incorporated three variables: salinity, flooding (environmental stressors), and aboveground interspecific competition (a biological factor). Following a two-year growth period, measurements of surviving seedlings’ basal diameter, plant height, and above- and belowground biomass were collected to assess growth responses and construct allometric models. Results indicated that high salinity reduced total mangrove biomass, whereas prolonged flooding increased tree height. Interspecific competition favored fast-growing species (e.g., Sonneratia caseolaris) while suppressing slow-growing counterparts (e.g., Avicennia marina). Synergistic effects between salinity and flooding influenced biomass and basal diameter, whereas salinity–flooding and salinity–competition interactions demonstrated antagonistic effects on tree height. High salinity, prolonged flooding, and competition elevated the proportion of aboveground biomass allocation. The results suggest that salinity stress and flooding stress were major growth-limiting factors for juvenile mangroves. Slow-growing species are not suitable to be mixed with fast-growing species in mangrove afforestation projects. Allometric models fitting for juvenile mangroves growing under different environmental factors were also developed. This study deepens our understanding of the growth of mangrove seedlings under composite stress conditions, provides effective tools for assessing the carbon sink potential of mangrove seedlings, and provides scientific guidance for future mangrove restoration projects. Full article

This study was conducted on New Zealand White male and female rabbits over a period of 133 days to ascertain their potential growth rates, body composition for major body parts, and chemical makeup. A total of 220 New Zealand White rabbits, evenly distributed between males and females, were used for this study. One hundred rabbits for potential growth were weighed from day 14 to day 140, while twelve rabbits, six males and six females, were randomly selected at days 14, 21, 28, 35, 42, 56, 70, 84, 112, and 140 for carcass analysis. Although the rate of maturation was faster in females than in males, the Gompertz equation fitted separately to the growth data for males and females indicated that the body weights were similar throughout the trial (0.0243 vs. 0.0239), but males had a higher mature weight (315 g) than the females (309 g). Mature body protein weights averaged 1497 g in males and 843 g in females, and mature body lipid contents averaged 252 and 227 g, respectively. The rate of maturation per day of pelt-free body protein of males and females was 0.0103 and 0.0172, while that of body lipids was 0.0410 and 0.0471, respectively. Separate equations were required for males and females to describe the allometric relationship between protein and lipids in the pelt-free body. The rate of maturation of pelts in females was higher than in males (0.0249 vs. 0.0214/d), and the mature weight was lower (456 vs. 523 g, respectively). Full article

The goal of this study was to develop a GIS-based Decision Support Model for selecting the best timber harvesting systems on steep terrain. The model combines multiple layers, each representing an important factor in mechanized logging. These layers are used to create a final map that functions as a spatially explicit Decision Support Model that helps decide which machines are best suited for different forest areas. A key idea of this study is to consider not only operational criteria (slope, ruggedness, wetness, and road accessibility), but also a fundamental silvicultural aspect, i.e., the assessment of tree growth classes to enable the integration of silvicultural deliberations into timber harvest planning. The data used for this model come from orthophoto image and a Digital Terrain Model (DTM). The operational factors were analyzed using GIS tools, while the silvicultural aspects were assessed using the deep learning algorithm DeepForest and tree growth equations (allometric functions). The model was tested by comparing its results with field data taken in a Norway Spruce stand in South Tyrol/Italy. The findings show that the model reliably evaluates operational factors. For silvicultural aspects, it tends to underestimate the number of small trees, but provides a good representation of tree size classes within a forest stand. The innovation of this method is that it relies on low-cost, open-source tools instead of expensive 3D scanning devices. Full article

Urban trees grow in diverse environments where site conditions and human management may influence their growth patterns. However, few allometric equations (AEs) have been developed for urban trees, and the effects of environmental variations across urban land use categories on tree biomass remain largely unexplored. Therefore, this study developed urban land-use-specific AEs for major urban tree species in South Korea. We selected eight major urban tree species groups (at genus level), harvested 201 trees, and non-destructively measured the stem volumes of 1995 trees using a laser dendrometer. Species-specific and generalized AEs to estimate stem volume were developed under three urban land use categories: street trees, urban parks, and others. The results indicated that differences in stem volume across urban land use categories varied by species, with street trees generally showing smaller stem volumes. Furthermore, due to the high variation in stem volume within species, sampling designs that encompass diverse size distributions are necessary when developing AEs for urban trees. Our findings indicate that various factors in urban environments influence tree volume and considering these differences is essential for improving biomass estimation accuracy. Full article

Forests are invaluable natural resources that provide essential ecosystem services, and their carbon storage capacity is critical for climate mitigation efforts. Quantifying this capacity would require accurate estimation of forest structural attributes for deriving their aboveground biomass (AGB). Traditional field measurements, while precise, are labor-intensive and often spatially limited. Handheld Mobile Laser Scanning (HMLS) offers a rapid alternative for building forest inventories; however, its effectiveness and accuracy in diverse subtropical forests with complex canopy structure remain under-investigated. In this study, we employed both HMLS and traditional surveys within structurally complex subtropical forest plots, including old-growth forests (Fung Shui Woods) and secondary forests. These forests are characterized by dense understories with abundant shrubs and lianas, as well as high stem density, which pose challenges in Light Detection and Ranging (LiDAR) point cloud data processing. We assessed tree detection rates and extracted tree attributes, including diameter at breast height (DBH) and canopy height. Additionally, we compared tree-level and plot-level AGB estimates using allometric equations. Our findings indicate that HMLS successfully detected over 90% of trees in both forest types and precisely measured DBH (R² > 0.96), although tree height detection exhibited relatively higher uncertainty (R² > 0.35). The AGB estimates derived from HMLS were comparable to those obtained from traditional field measurements. By producing highly accurate estimates of tree attributes, HMLS demonstrates its potential as an effective and non-destructive method for rapid forest inventory and AGB estimation in subtropical forests, making it a competitive option for aiding carbon storage estimations in complex forest environments. Full article

Mowing is a crucial grassland management practice; however, its effects on biomass allocation and compensatory mechanisms across different growth stages remain insufficiently understood. This study investigated five Elymus forage species (Elymus nutans ‘Aba’, Elymus sibiricus ‘Qingmu No.1’, Elymus submuticus ’Tongde’, Elymus breviaristatus ‘Tongde’, and Elymus sibiricus ‘Tongde’). Four mowing intensities (control, light, moderate, and heavy) were applied at three phenological stages (jointing, booting, and flowering). Biomass allocation patterns among plant components (roots, stems, leaves, and spikes) were assessed, and allometric growth relationships were analyzed. Structural equation modeling (SEM) was used to evaluate the contributions of mowing timing and organ biomass to overall compensatory ability. The results showed that mowing significantly altered biomass allocation patterns, characterized by an increase in root-biomass proportion, a decrease in stem and spike proportions, and species- and stage-specific changes in leaf proportion. The allometric growth relationships between plant organs varied across growth stages and were significantly influenced by mowing intensity, affecting organ growth coordination. SEM analysis revealed that mowing timing and root biomass were the primary drivers of total biomass compensation, with root biomass playing a particularly critical role under moderate to heavy mowing. Mowing exerts complex regulatory effects on biomass allocation and compensatory growth in Elymus species, with impacts varying by intensity, growth stage, and species. To enhance overcompensatory growth, moderate mowing at the jointing stage is recommended, while heavy mowing during the flowering stage should be avoided. Furthermore, maintaining root health is crucial for improving compensatory growth capacity. These findings provide valuable insights for the sustainable management of Elymus grasslands. Full article

In this study, we present a methodology for predicting timber board foot volume using a forest landscape model, incorporating allometric equations and forest inventory data. The research focuses on the Ozark Plateau, a 48,000-square-mile region characterized by productive soils and varied precipitation. To simulate timber volume, we used the LANDIS PRO forest landscape model, initialized with forest composition data derived from the USDA Forest Service’s Forest Inventory and Analysis (FIA) plots. The model accounted for species-specific growth rates and was run from the year 2000 to 2100 at five-year intervals. Timber volume estimates were calculated using both quadratic mean diameter (QMD) and tree diameter in the Hahn and Hansen board foot volume equation. These estimates were compared across different forest types—deciduous, coniferous, and mixed stands—and verified against FIA plot data using a paired permutation test. Results showed high correlations between QMD and tree diameter methods, with a slightly lower volume estimate from the QMD approach. Projections indicate significant increases in board foot volume for key species groups such as red oak and white oak while showing declines toward the end of the model period in groups like shortleaf pine due to age-related mortality and regeneration challenges. The model’s estimates closely align with state-level FIA data, underscoring the effectiveness of the integrated approach. The study highlights the utility of integrating landscape models and forest inventory data to predict timber volume over time, offering valuable insights for forest management and policy planning. Full article

The quantification of urban tree biomass allocation has primarily relied on estimations using allometric equations (AEs) developed for nondestructive harvest methods. However, the lack of harvest-based AEs that account for belowground biomass, nutrient concentration, and annual growth rates poses challenges in accurately quantifying the greenhouse gas inventory for urban land uses. In this study, we aimed to develop AEs using a log-transformed linear model for eight urban landscaping tree species, taking into account belowground biomass. We purchased 117 urban landscaping trees from tree farms in South Korea and investigated their biomass fractions, carbon and nutrient concentrations, and annual growth rate using a destructive method. We also developed AEs for different tree compartments using diameter at breast height as an independent variable. The AEs obtained exhibited high suitability, as evidenced by their high R² values (0.853–0.982 and 0.806–0.923 for aboveground and belowground biomass, respectively). The mean belowground biomass fraction across the different species was approximately 30%, suggesting that urban trees could allocate more belowground biomass than forest trees. Conversely, carbon and nitrogen concentrations varied significantly across species and compartments, and the mean annual carbon sequestration rate was 3.96 kg C year⁻¹ tree⁻¹. Therefore, the application of the AEs for urban trees may enhance the accuracy of the national greenhouse gas inventory for the settlement sector. Full article

Two Amazonian species of açaí palm trees (Euterpe oleracea and Euterpe precatoria) are exploited in the commercial production of açaí pulp or juice. While E. oleracea benefits from developed cultivation technologies, E. precatoria lacks such advancements. Studies on the morphology and development of açaí palms under cultivation conditions can contribute to increasing the productivity of the species. The aim of this study was to carry out morphological characterization, assess growth and development in the juvenile phase of the plants, and obtain allometric models for E. precatoria and E. oleracea. Evaluations were conducted between 44 and 48 months post-planting. Allometric equations were formulated to accurately estimate leaf area. The results showed that E. oleracea begins reproduction earlier and exhibits greater growth in stem dimensions and leaf areas compared to E. precatoria, indicating that E. precatoria can be cultivated at higher planting densities. Allometric models, based on leaf length and width, effectively predicted individual leaf areas for both species, demonstrating their utility in optimizing cultivation strategies. Full article