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In the Southern Ocean, myctophids (family Myctophidae) are speciose, dominate the mesopelagic fish biomass, and are important in the diets of many fishes, squids, seabirds, and marine mammals. Consequently, they play a key role in carbon export and energy transfer from primary consumers to top predators. However, they are delicate and rarely found intact in predator stomachs, which makes them difficult to identify to species. Fortunately, their otoliths (sagittae) are mostly distinctive and therefore useful for species identification. Previous studies describing Southern Ocean myctophid otoliths were often limited by small sample sizes or focused on only a few species. To facilitate myctophid identifications in diet studies, we provide scanning electron microscope images of otoliths with brief descriptions for 37 species of Southern Ocean myctophids. The identities of problematic taxa were confirmed with DNA. Most species were found to have distinctive otoliths, which can be used to identify them to the species level. Large Gymnoscopelus piabilis otoliths comprised two types, which may represent different species. In addition, allometric equations are provided for 32 species to enable back calculation of fish size. [ABSTRACT FROM AUTHOR]

Purpose: Transhumance has rarely been analyzed through LCA approaches, and there is little evidence about its emissions level when conducted under different practices (by truck or on foot) or compared to sedentary livestock systems. Moreover, mobile pastoralism is strongly linked to natural resources by its seasonal grazing patterns, thereby occupying the niche of wild herbivores. Considering natural emission baselines in these ecosystems could have relevant effects when estimating their carbon footprint. Materials and methods: Inventory data of 20 sheep farms was collected to estimate the carbon footprint (CF) of lamb meat produced. Farms were divided into three sub-groups representing typical management practices in the region: (1) sedentary (SED), (2) transhumance by truck (THT), and (3) transhumance on foot (THF). Livestock GHG emissions were modeled according to herd structure and IPCC guidelines. Off-farm emissions from external feeds and fuels were accounted based on existent LCA databases. A natural baseline of wild herbivores was established from the population of red deer reported in a hunting preserve, previously considered to be a reference for the natural carrying capacity in Mediterranean ecosystems. GHG emissions of wild herbivores were estimated through two methods based on (1) IPCC guidelines and (2) allometric regression equations. Results and discussion: Carbon footprint ranged from 16.5 up to 26.9 kgCO2-eq/kg of lamb liveweight (LW). Significant differences were identified among sedentary and transhumant farms, the latter consistently showing lower CF values (SED: 25.1 kg CO2-eq/kg LW, THT: 18.3 kg CO2-eq/kg LW, THF: 18.2 kg CO2-eq/kg LW). Sedentary farms resulted in higher GHG emissions (+ 27%) and higher CO2 and N2O, contributions derived from the consumption of additional feeds. Both methods applied to compute emissions for wild herbivores led to similar results (25.3–26.8 Mg CO2-eq/km2), comparatively lower than estimation for transhumant sheep (47.7 Mg CO2-eq/km2). When considering natural baseline emissions, the CF of transhumant lamb meat is reduced by almost 30%, reaching values quite below those reported for intensive lamb production systems in Spain. Conclusions: From our results, mobility of grazing livestock can be considered as a strategy promoting climate change mitigation. This is achieved mainly by reducing the need of external feeds, while maximizing the use of local forage resources that otherwise would be difficult to valorize. Further reductions in the CF result when considering natural baseline emissions. The application of this new GHG accounting perspective could have relevant implications when aiming at climate neutrality of grazing-based ruminant systems. [ABSTRACT FROM AUTHOR]

Many allometric models to predict tree aboveground biomass have been developed in tropical moist forests, but few models are available for tree belowground biomass. Theory predicts that belowground biomass scales in an isometric way with aboveground biomass. Estimates of belowground biomass could then be derived from aboveground biomass using the root:shoot ratio. Using a dataset of 118 tropical trees for which both aboveground and belowground biomass and other tree and species characteristics were measured in Gabon and Cameroon, we found a near isometric, yet significantly allometric, relationship between belowground biomass (B , in kilograms) and aboveground biomass (A , in kilograms): B  = 0.324 A 0.939. The root:shoot ratio was 0.20–0.22, regardless of tree size. An efficient model to predict belowground biomass from tree diameter (D , in centimeters), height (H , in meters) and wood density (ρ, in grams per cubic centimeter) was B  = 0.0188 (ρ D 2 H)0.977. A significant residual effect of species and leaf habit was found in this model, indicating that further tree and species characteristics are likely to explain additional variation in belowground biomass. Yet, the future development of belowground allometric models can benefit from the many models already developed for aboveground biomass. On the basis of this unprecedented sampling effort on tree belowground biomass in the dense tropical forests of the Congo Basin, we conclude that the scaling of belowground biomass with aboveground biomass should be the relationship to focus on. [ABSTRACT FROM AUTHOR]

Sapota fruit tree biomass cannot be estimated using general forest tree allometric equations involving measurement of diameter at breast height (DBH) as grafted sapota tree branches below this height. Therefore grafted sapota trees of commercial orchards require an independent allometric equation for nondestructive estimation of tree biomass. Sapota allometric equations were hence developed with a destructive sampling of grafted sapota trees using parameters other than DBH and compared with other equations developed for grafted mangoes. The selected allometric parameters were significantly related to the age of the trees. The root-to-shoot ratio also differed from those reported for forest trees. The biomass expansion factor by and large attained stability beyond 16 years of tree age. The equations so developed generally fitted the data well, and in most cases, more than 50% of the observed variation in biomass was explained by primary branch girth x number of primary branches. There was a good agreement between the observed and the predicted biomass using both multiple linear regression and power model equations. Further, our purpose was to see if the grafted mango tree equation can predict sapota tree biomass. The results of this study confirmed that the mango equation equally predicts sapota tree biomass and hence the mango tree allometric equation can also be used for estimating sapota tree biomass efficiently. [ABSTRACT FROM AUTHOR]

This study aims to explore the forest aboveground biomass relationship to C-band backscatter. A one-hectare area in Wytham Woods, located west of Oxford, was selected for this research. The area has a total of 525 trees of seven different tree species. The Michigan Microwave Canopy Scattering Model (MIMICS), a two-layer radiative transfer model, was applied to simulate canopy backscatter responses in this deciduous UK forest. Model parameters related to forest structure were derived from previously published terrestrial laser (LiDAR) data. Simulated backscatter was performed for co-polarized and cross-polarized modes at a C-band frequency range and incidence angles (20° to 45° at 5° increments). The research includes five objectives: i) backscatter sensitivity analysis from the variation of different model parameters; ii) backscatter seasonal effect under spring–summer (leaf-on) and autumn–winter (leaf-off) periods; iii) backscatter comparison between species as well as between simulated and satellite observations in a spatial pattern; iv) relationship between simulated backscatter and aboveground biomass; and v) relationship between MIMICS forest structure parameters and simulated backscatter. Sensitivity analysis results showed significant differences in backscatter from changes in leaf distribution, leaf thickness and water content (leaf, trunk and soil) for both polarization modes in leaf-on scenarios. Leaf-off scenarios presented significant differences from changes in branch distribution but only for the co-polarized mode. Seasonal variations presented significant backscatter differences between spring–summer and autumn–winter scenarios; additionally, backscatter differences among species for each seasonality in the co-polarized mode were observed. The computation of the grid resolution (20 m × 20 m) showed a range of backscatter values depending on the grid and incidence angle. Higher backscatter values were observed for the satellite data than for the simulated data. Finally, the aboveground biomass and the MIMICS input parameters presented high random variability and little systematic co-variation with the total backscatter on both simulated seasons, suggesting that more robust allometric equations for biomass estimation are required. [ABSTRACT FROM AUTHOR]

BackgroundAimsMethodsResultsConclusionCork oak (Quercus suber) forests and woodlands cover an area of ca. 2.1 M ha in the Mediterranean Basin. Cork oak stands are important for biodiversity conservation, and ecosystem services (carbon storage and the provision of cork, timber, and firewood). Their sustainable management is essential for their continued multifunctional existence and for providing ecosystem services.The aims of this study were to estimate the biomass production of the species and quantify its potential carbon storage capacity in the Mediterranean Basin and to make management recommendations.We used a literature survey of allometric equations and cork annual total tree-ring growth data and applied them to determine the productivity of the species. Estimate biomass by using regression models and dendrometric characteristics is very important for cork oak in the Mediterranean region.The studies reported a wide-ranging above-ground biomass for cork oak: 42 Mg ha−1 for Italy, 64–120 Mg ha−1 for Morocco, 41–50 Mg ha−1 for Portugal, 29–328 Mg ha−1 for Spain, and 80–312 Mg ha−1 for Tunisia. The radial wood increment ranged from 0.78 to 8.01 mm yr−1. The annual increment of cork-ring growth was between 0.8 mm yr−1 (northern Algeria) and 5.25 mm yr−1 (Spain), with most values being between 2 and 4.4 mm yr−1. In dry years, major reductions (10−15%) in the growth of Quercus suber were observed.Most studies showed stand-specific growth responses to climate variables, with the radial growth of cork oak being greater in relatively mesic and cool conditions. [ABSTRACT FROM AUTHOR]

This study aimed to analyze the existing conditions and prediction of future carbon stocks in the planting of mangroves of the REMAJA PHE ONWJ program in Mekarpohaci Village, Karawang Regency, Indonesia. The observation began with the planting of 1200 seedlings of R. mucronata and A. marina, respectively. Furthermore, the monitoring of life graduation and diameter growth in the 2021-2023 period was carried out. Existing carbon stocks were analyzed by an allometric equation approach and carbon fraction values. Meanwhile, the prediction of future carbon stocks was modeled using Stella v.9.0.2 software concerning the growth rate of seedling stand diameter. The results of the study showed that carbon stocks reached 0.275 tons C in 2021, 3.66 tons C in 2022, and 5,765 tons C in 2023. Meanwhile, future carbon stock predictions indicate that the largest carbon stock in the 10-year growth projection is found in R. mucronata, with a value of 107.79kg C/tree, which includes 5.80kg AGC and 31.99kg BGC. In contrast, A. marina has the lowest carbon stock at 75.54kg C/tree (52.54kg AGC and 22.99kg BGC). The total contribution of carbon sequestration by 2033 is projected to reach 807.36 tons of CO2e, comprised of 474.69 tons of CO2e from R. mucronata and 332.67 tons of CO2e from A. marina. The carbon sequestration indicates that mangrove planting in the REMAJA PHE ONWJ program contributes to the reduction of CO2 gas concentrations in the atmosphere and climate change mitigation and can realize the principles of sustainable development (SDGs). [ABSTRACT FROM AUTHOR]

Predicting the distribution, structure, and biomass of mangrove forests is an area of high research interest. Across the Atlantic East Pacific biogeographic region, three species are common and abundant members of local mangrove communities; Rhizophora mangle, Avicennia germinans, and Laguncularia racemosa. Biomass prediction for these species has relied on two approaches: site‐specific allometries based on the idea that environmental/climatic differences between sites drive growth differences, or the use of common allometric equations based on the idea that site driven differences are minimal. Meta‐analyses of global compilations of interspecific plot level data (e.g., mean canopy height, stand basal area) show trends in size and structure with climatic variables, however this has not been critically evaluated across these species using empirical allometric growth functions. We compared allometric equations derived from 590 individuals within and across nine broadly distributed sites at interspecific and intraspecific levels and explored the influence of climatic variables on allometric slopes and intercepts. Assessing variables that can be used to predict biomass in the field (height, diameter at breast height (DBH), canopy spread), we find interspecific root mean squared errors similar to or smaller than most intraspecific or site‐specific equations, particularly when examining sites with sample sizes above recommended values. We also find significant effects of several climatic variables on growth allometries with the strongest effects from minimum temperature followed by precipitation seasonality. Our results suggest that while climate has a clear influence on mangrove allometric growth, common equations may have utility in biomass prediction. Future methodological improvements, particularly larger sample sizes across the entire available size range, combined with data from a broader range of growth conditions will further inform which allometric relationships exhibit the most variability within and across sites and which variables best predict mangrove biomass. [ABSTRACT FROM AUTHOR]

Societal Impact Statement: Free‐air CO2 enrichment (FACE) experiments provide essential data on forest responses to increasing atmospheric CO2 for evaluations of climate change impacts on humanity. Understanding and reducing the uncertainty in the experimental results is critical to ensure scientific and public confidence in the models and policy initiatives that derive therefrom. One source of uncertainty is the estimation of tree biomass using mathematical relationships between biomass and easily obtained and non‐destructive measurements (allometry). We evaluated the robustness of the allometric relationships established at the beginning of a FACE experiment and discuss the challenges and opportunities for the new generation of FACE experiments. Summary: Long‐term field experiments to elucidate forest responses to rising atmospheric CO2 concentration require allometric equations to estimate tree biomass from non‐destructive measurements of tree size. We analyzed whether the allometric equations established at the beginning of a free‐air CO2 enrichment (FACE) experiment in a Liquidambar styraciflua plantation were still valid at the end of the 12 year experiment.Aboveground woody biomass was initially predicted by an equation that included bole diameter, taper, and height, assuming that including taper and height as predictors would accommodate changes in tree structure that might occur over time and in response to elevated CO2. At the conclusion of the FACE experiment, we harvested 23 trees, measured dimensions and dry mass of boles and branches, and extracted and measured the woody root mass of 10 trees.Although 10 of the harvested trees were larger than the trees used to establish the allometric relationship, measured aboveground woody biomass was well predicted by the original allometry. The initial linear equation between bole basal area and woody root biomass underestimated final root biomass by 28%, but root biomass was just 21% of total wood mass, and errors in aboveground and belowground estimates were offsetting.The allometry established at the beginning of the experiment provided valid predictions of tree biomass throughout the experiment. New allometric approaches using terrestrial laser scanning should reduce an important source of uncertainty in decade‐long forest experiments and in assessments of centuries‐long forest biomass accretion used in evaluating carbon offsets and climate mitigation. [ABSTRACT FROM AUTHOR]

Climate change is rapidly progressing as the carbon budget balance is broken due to excessive energy and land use. This study was conducted to find and quantify new carbon sinks to implement the carbon neutrality policy prepared by the international community to solve these problems. To reach this goal, an allometric equation of the willow community, which dominates riparian vegetation, was developed and applied to calculate the net primary productivity of the willow community. Furthermore, after the amount of carbon emitted via soil respiration was quantified, the net ecosystem production was calculated by subtracting the amount of soil respiration from the net primary productivity. In comparisons of the results obtained via this process with those obtained from forest vegetation, the willow community, representative of riparian vegetation, showed a much higher carbon sequestration rate than forest vegetation. Considering these results comprehensively, the willow community could be a new and significant carbon absorption source. In this context, proper river restoration should be realized to contribute to carbon neutrality and secure various ecosystem service functions. [ABSTRACT FROM AUTHOR]

Sweetgum (Liquidambar styraciflua) is an excellent short-rotation woody crop species for producing hardwood pulp and biofuel feedstock on marginal sites. A recent development which may improve growth is the production of hybrid sweetgum (L. formosana x styraciflua) clones. We compared the productivity and attributes, e.g., wood specific gravity and stand growth, of operational plantations of hybrid sweetgum clones to improved native sweetgum half-sib families in 36 stands in Oklahoma, Texas, and Louisiana, U.S. The least square means (LSMean) of wood specific gravity was significantly greater for hybrids clones than the half-sibs (0.49 vs. 0.46 g/cm3), and the hybrid clones had less taper which necessitated developing genotype-specific volume and biomass equations. Despite having less fertilizer inputs on average, the hybrids had greater standing green stem biomass than the half-sibs at an age of 8.5 years (LSMean of 73.3 vs. 51.9 Mg/ha). The hybrids as a group also exhibited greater green biomass growth during the 2022 growing season when compared to the half-sibs at 8.5 years (LSMean of 15.8 vs. 11.4 Mg/ha/y). Therefore, the hybrids provide growth and wood quality advantages that may provide an opportunity to increase productivity and profitability of hardwood SRWC plantings. [ABSTRACT FROM AUTHOR]

Introduction: Extreme weather becomes increasingly frequent and severe under climate change, causing unexpected damage to trees. Among them, sleet damage is particularly harmful to evergreen trees in subtropical area. Camphor trees (Cinnamomum camphora), as dominant street trees in central China, are prone to sleet damage, resulting in loss of valuable ecosystem functions. Methods: By measuring tree size characteristics of 118 camphor trees before and after a record-breaking sleet event in Wuhan, a mega-city in central China, we built allometric equations between size and volume of broken branches and used the random forest regression to model sleet damage to camphor trees. Results: We identified that larger trees with intermediate bole height suffered more than smaller trees with tall bole height from the sleet event. We estimated the volume of broken branches of a camphor tree with DBH at 35.0 cm as 106.4 dm3, equivalent to 55.3 kg biomass loss, from the sleet event. Discussion: We suggest that pruning the branches instead of topping the main stems of small camphor trees would reduce the sleet hazard. To mitigate the negative impacts of climate change, regular pruning should be practiced on street camphor trees to protect them from future heavy sleet events. [ABSTRACT FROM AUTHOR]

Precise estimation of forest above ground biomass (AGB) is essential for assessing its ecological functions and determining forest carbon stocks. It is difficult to directly obtain diameter at breast height (DBH) based on remote sensing imagery. Therefore, it is crucial to accurately estimate the AGB with features extracted directly from RS. This paper demonstrates the feasibility of estimating AGB from crown radius (R) and tree height (H) features extracted from multi-source RS data. Accurate information on tree height (H), crown radius (R), and diameter at breast height (DBH) can be obtained through point clouds generated by airborne laser scanning (ALS) and terrestrial laser scanning (TLS), respectively. Nine allometric growth equations were used to fit coniferous forests (Larix principis-rupprechtii) and broadleaf forests (Fraxinus chinensis and Sophora japonica). The fitting performance of models constructed using only "H" or "R" was compared with that of models constructed using both combined. The results showed that the quadratic polynomial model constructed with "H+R" fitted the AGB estimation better in each vegetation type, especially in the scenario of mixed tall and short coniferous forests, in which the R2 and RMSE were 0.9282 and 25.30 kg (rRMSE 17.31%), respectively. Therefore, using high-resolution data to extract crown radius and tree height can achieve high-precision, global-scale estimation of forest above ground biomass. [ABSTRACT FROM AUTHOR]

This study aims to assess the woody species carbon stock in the Munessa dry Afromontane forest and its variations within plant community types, as well as altitudinal, slope, and aspect gradients. A systematic sampling technique was used to acquire vegetation data. At a 100-m altitudinal drop, five transect lines were established. Ten quadrats were laid on each transect line (total 50 quadrants) at 200-m distance intervals. The woody carbon was estimated using an appropriate allometric equation formulated for tropical forests. The data was analyzed using one-way ANOVA in R software. The results show that the total woody carbon stock of the Munessa forest is 210.43 t/ha. The analysis of variance revealed that woody carbon stock varied significantly along altitude, slope, and aspect gradients, whereas community types had no significant effect. Middle elevations (2367–2533 m above sea level (m.a.s.l.)), lower slopes (0–13%), and west-facing aspects had the highest mean carbon stock. The Podocarpus falcatus–Croton macrostachyus community type also contributed a higher woody carbon stock since larger tree size classes and older trees are dominant. Overall, the carbon sequestration potential of woody species in the studied forest is strongly associated with environmental variables. Furthermore, the uneven distribution of species with larger diameter at breast height (DBH) in the studied forest might be linked to anthropogenic factors, as the current forest growth indicates characteristics of a secondary forest. Therefore, the present study suggests developing and implementing a sustainable forest management strategy particularly prioritizing middle elevation, lower slope, and west aspects of the forest to maximize the forest's carbon sequestration capacity. [ABSTRACT FROM AUTHOR]

Studying tree growth processes helps us evaluate the success of restoration efforts in recovering ecosystem processes such as carbon accumulation. Here, we study aboveground biomass dynamics in four common‐endemic tree species from the tropical Andes (Quercus humboldtii, Retrophyllum rospigliosii, Citharexylum subflavescens, and Croton magdalenensis), established in the main water supply basins of Medellín, Colombia. We use measurements from 19 permanent plots from five censuses between 2010 and 2023 to develop biomass equations as a function of t for each species (B = f[t]) by combining tree growth models of diameter (D) as a function of time (t) and pre‐existing allometric equations of biomass (B) developed in the same site as a function of D and wood density (ρ). We found that, because of initially higher growth rates characteristic of species belonging to the fast‐growing end of the fast‐slow growth economic spectrum, C. magdalenensis and C. subflavescens were the species with higher biomass accumulation at 13 years (142 and 132 kg, respectively). However, the potential of the slow‐growing species (Q. humboldtii and R. rospigliosii) for carbon sequestration initiatives in the long term was highlighted. To our knowledge, this is the first study in the region examining the dynamics of aboveground biomass in Andean restoration programs. It combines growth models and allometric equations, which can be useful for measuring the success of the implementation of ecological restoration programs and evaluating the need to apply adaptive management strategies. [ABSTRACT FROM AUTHOR]

Background: The body weight (BW) of animals at various growth stages is an important piece of information for the decision-making process. In the current "livestock 4.0" or precision livestock farming it becomes necessary to know if body measurements obtained from the dorsal view of an animal are related to its BW. Objective: To evaluate the relationship between BW and dorsal area (DA) of water buffaloes (Bubalus bubalis) reared in southeastern Mexico. Methods: The BW (340 ± 161.68 kg), hip width (HW), thorax width (TW), and body length (BL) were measured in 215 female Murrah buffaloes aged between 3 months and 5 years. The DA (m2) was calculated using the mathematical formulae for the area of a trapezoid, considering HW, TW, and BL in the calculation. The relationship between BW and DA was assessed with correlation and regression models. Results: The correlation coefficient between BW and AD was 0.96 (p<0.001). The linear equation had the highest determination coefficient (R2 = 0.94) along with the lowest mean square error (MSE = 1716.86), root MSE (RMSE = 41.43), Akaike Information Criterion (AIC = 1603.36), and Bayesian Information Criterion (BIC = 1610.10). Conversely, the allometric equation exhibited the highest values of MSE, RMSE, AIC, and BIC. Based on the quality of fit by the k-folds technique, the three proposed equations showed consistent adjustments, with more than 90% accuracy (R2 = 0.92). The quadratic equation exhibited the lowest mean squared prediction error and mean absolute error. Conclusion: The DA can be used as a good predictor of BW in buffaloes, especially when incorporated into first and second-degree linear equations. [ABSTRACT FROM AUTHOR]

Aim: Tirzepatide (Tzp), a novel dual agonist glucose‐dependent insulinotropic polypeptide/glucagon‐like peptide‐1, is approved for treating insulin resistance and obesity, and menopausal women consuming a high‐calorie diet are a target to study the Tzp effect. Therefore, we aimed to allometrically scale body weight (BW) in Tzp‐treated obese diabetic menopausal mice. Materials and Methods: Three‐month‐old C57BL/6 female mice had bilateral ovariectomy (Ovx) or a sham procedure and for 12 weeks were fed a control diet or a high‐fat and high sucrose diet (n = 120/each group [control (C), obese diabetic (Od), Ovx (O), sham (S), Tzp (T)]). Tzp was subcutaneously administered (10 nmol/kg) or vehicle once a day for an additional 4 weeks. The analysis considered log‐transformed data and the allometric equation log y = log a + b log x. Results: Od and OdO showed more upward slopes than C and CO. In C, BW was non‐allometric by T administration. Od and OdO showed slightly positive slopes (more prominent in OdO than Od). OdT and OdOT showed negative slopes, significant intercepts, and more robust Pearson coefficients than untreated ones. A potent drug effect was seen with BW allometric decline. Interactions between diet versus Ovx and diet versus Tzp affected weight gain. Diet versus Ovx versus Tzp affected food intake. Conclusions: A model was developed to show three usual factors observed in mature women. Notably, Tzp improved the metabolism and weight loss of OdO mice. Tzp‐treated mice showed negative allometric BW across treatment time, which is a quantitative assessment that allows better comparison between results. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Accurate estimation of biomass and carbon stocks in forest ecosystems is critical for understanding their roles in carbon sequestration and climate change mitigation. Currently, the development of stand biomass models and carbon stock estimation at the regional scale has emerged as a prominent research priority. In this study, 225 Populus spp. (poplar) trees in Shandong Province, China, were destructively sampled to obtain the biomass of their components. Two models (MS1 and MS2) were developed using allometric equations and the seemingly unrelated regression (SUR) method to ensure additive properties across tree components. The model evaluation employed the leave-one-out jackknife (LOO) method, considering statistics such as adjusted R-squared ( R a 2 ), root mean square error (RMSE), mean absolute percent error (MAPE), and mean absolute error (MAE). The results from our models demonstrated high accuracy, with MS2 slightly outperforming MS1 after incorporating tree height as an independent variable. The models reliably estimated component-specific biomass and carbon stocks, with distinct variations observed in the carbon content among foliage (47.14 ± 2.07%), branches (47.26 ± 2.48%), stems (47.67 ± 2.21%), and roots (46.37 ± 2.78%). Carbon stocks in poplar plantations increased with the diameter class, ranging from 5 to 35 cm and correspondingly from 3.670 to 172.491 Mg C ha−1. As the diameter class increases, the carbon allocation strategy of poplars aligns with the CSR strategy, transitioning from prioritizing growth competition to emphasizing self-stabilization. Our research proposes a robust framework for assessing biomass and carbon stocks in poplar plantations, which is essential for evidence-based forest management strategies. [ABSTRACT FROM AUTHOR]

Agroforestry is an alternative to unsustainable agricultural practices, aiding in the mitigation of greenhouse gas emissions and climate change. However, accurately assessing the carbon sequestration potential of agroforestry tree species remains challenging due to reliance on destructive, time-consuming, and resource-intensive methods that hinder forest cover restoration in Côte d'Ivoire. Commonly used pantropical allometric equations lack specificity and precision, complicating carbon sequestration estimates. To address this, our study focused on four agroforestry species in Côte d'Ivoire: Theobroma cacao, Hevea brasiliensis, Coffea canephora, and Anacardium occidentale. We compared aboveground biomass estimates obtained using general and specific allometric equations for these species, collecting dendrometric measurements from 655T. cacao, 69 H. brasiliensis, 90 C. canephora, and 73 A. occidentale individuals. No concordance was found between generic and specific allometric equations using a linear regression model. The general equation significantly underestimated aboveground biomass by 20.06 kg, 1.10 kg, 7.28 kg, and 11.50 kg per tree for T. cacao, H. brasiliensis, C. canephora, and A. occidentale, respectively. The differences indicated a carbon sequestration potential 17.2% to 18.7% higher when using specific equations in cocoa-based agroforestry systems. This study underscores the urgency of developing customized allometric equations for more precise carbon sequestration assessments, enhancing the accuracy of agroforestry's contribution to climate change mitigation. [ABSTRACT FROM AUTHOR]

Mangroves on the islands along the Java Sea play a crucial role in supporting biodiversity, protecting coastlines, and sequestering carbon. However, there is a lack of information on mangrove structure and biomass in the area. This study aimed to assess the mangrove structures and biomass on Desa Daun, located on the Bawean Islands, and Kemujan Island, located on the Karimunjawa Islands, respectively. The study utilized a combination of line transect and quadrant plot methods with a size plot of 10x10 m. We established 7 line transects and 28 quadrant plots in the mangrove forest of Desa Daun and similarly set up 7 line transects and 21 quadrant plots on Kemujan Island. Within each quadrant, the mangrove species were identified, and their diameters at breast height (DBH) were recorded. To assess the relative significance of each species, the importance value index (IVI) was calculated, and allometric equations were applied to estimate biomass and carbon storage in the trees. PlanetScope imagery was also used to quantify the carbon stock of mangroves on those islands. In Desa Daun, 13 mangrove species were identified, while 12 species were recorded on Kemujan Island. The species Nypa fruticans and Excoecaria agallocha exhibited the highest IVI in Desa Daun and Kemujan Island, respectively. Notably, Rhizophora apiculata demonstrated the greatest biomass in both locations, with measurements of 43.08 Mg B/ha in Desa Daun and 102.22 Mg B/ha in Kemujan Island. Overall, mangrove stands on Desa Daun stored biomass of 113.60 Mg B/ha and carbon of 50.98 Mg C/ha, whereas mangrove stands on Kemujan Island stored biomass of 295.04 Mg B/ha and carbon of 131.95 Mg C/ha. Mangrove stands of the whole Bawean Islands sequestered 22,941 Mg C, while Karimunjawa Islands hold much higher C stocks, 79,451 Mg C. Despite being smaller in size, the Karimunjawa Islands have more extensive mangrove coverage compared to the Bawean Islands due to their geomorphological characteristics, which in turn influence their mangrove structures and carbon stocks. However, the loss of mangroves in the Karimunjawa Islands due to aquaculture expansions could increase carbon loss in the islands. [ABSTRACT FROM AUTHOR]

Using non-destructive and low-cost methods to determine leaf area has gained important applications. The research objectives were (i) to propose a non-destructive method to estimate the leaf area of castor bean crops and (ii) to build equations that accurately and quickly estimate the leaf area of specie. One thousand healthy and expanded leaves of five castor bean cultivars (New Zealand Purple, Sipeal, Carmencita, Amarelo de Irecê, and IAC-80) were collected, and 200 leaves were collected from each. The maximum length, maximum width, and leaf area were calculated for each leaf. The product between length and width (LW) were calculated. We performed tests with different linear and non-linear regression models between leaf area and linear leaf dimensions of each cultivar. The models used were linear, linear without intercept, and power. The criteria for choosing the best models to estimate the leaf area of castor beans were a higher coefficient of determination, more elevated Pearson’s linear correlation coefficient, lower Akaike information criterion, higher Willmott agreement index, and smallest root mean square error. The equations that presented the best criteria for estimating the leaf area of castor bean cultivars were those that used the product between length and width, compared to equations that used only one leaf dimension. The model ŷ = 0.439 × LW can be used to accurately and quickly estimate the castor bean leaf area through linear measurements of the leaves, using the product between length and width (LW), regardless of the cultivar chosen. [ABSTRACT FROM AUTHOR]

Shrubland ecosystems cover a large part of the five Mediterranean regions of the world, and monitoring their biomass is crucial for assessing fire risk and carbon sequestration. However, biomass models for multi-stemmed shrubs remain scarce, making the quantitative assessment of shrubland biomass imprecise and often unreliable. Here, we measured, harvested, and weighed 411 specimens at two representative sites to quantify aboveground biomass (AGB) in 14 shrub species. To develop species-specific and general models of AGB, we used observations on total height (HT), diameter at collar height (DCH), number of stems (NS), and crown size as well as different geometric shapes representing crown area (CA) and bulk volume (BV). General models including all species were fit, including species identity as a random effect to take variation across species into account. A k-fold cross-validation was used to assess and compare the ability of the models to predict independent data. Individual AGB varied markedly both within and among the 14 species, with on average higher values at the site characterized by lower shrub density and species richness. Two biomass components, woody and leaf + twig, were distinguished, and species-specific means of the woody and leaf + twig proportion varied between 30 and 60%. We found that crown BV assessed on different geometric shapes was suitable to predict the biomass for different shrub species and that additional variables were rarely beneficial. The best general model included BV represented as an inverted truncated cone, derived from crown diameter (CD), HT and the DCH of the longest stem. This study provides novel allometric equations essential for assessing AGB shrublands in central Chile. Our general multi-species models based on BV geometry could prove very useful for future studies in Mediterranean shrublands, allowing us to estimate biomass through indirect, non-destructive methods. [ABSTRACT FROM AUTHOR]

• The equations that use the product between L and W are the most suitable for predicting LA. • The linear and power models are the most suitable for estimating the leaf area of sweet potato cultivars;. • The proposed non-destructive method presents high accuracy for four sweet potato cultivars. Many researchers consider the leaf area the most critical parameter for plant growth and physiology studies. Using allometric equations is considered an effective and non-destructive method for estimating the leaf area of plants. The objectives of this study were to construct allometric equations to predict the leaf area of sweet potato cultivars as a function of leaf dimensions and to verify the effectiveness of the allometric equations constructed for each cultivar individually and for the grouped data. Two hundred fifty leaves of the sweet potato cultivars Beauregard, BRS Amélia, BRS Cuia, and Coquinho were collected, and then the length and width of each leaf were measured. Subsequently, the product between leaf length and width and the actual leaf area was calculated. Linear, linear without intercept, power, and exponential regression models were used to construct allometric equations to predict leaf area. The best equations were chosen according to the highest coefficients of determination and correlation, Willmott agreement index, and lowest Akaike information criterion and root mean square error. The equations obtained with the linear models without intercept and power using the length and width of the leaves were the most indicated for predicting the leaf area of sweet potato cultivars. [ABSTRACT FROM AUTHOR]

Estimation of plant community composition, aboveground biomass and carbon stock is crucial for understanding forest ecology, strengthening environmental management, and developing effective tools and policies for forest restoration. This study was conducted in nine different forest reserves in Sri Lanka from 2012 to 2018 to examine the impact of community-based forest restoration (CBFR) on stand structural attributes, aboveground biomass, and carbon stock compared to state-managed forests. In total, 180 plots (90 plots in community-managed restoration blocks (CMRBs) and 90 plots assigned to state-managed restoration blocks (SMRBs)) were sampled at the study site. To conduct an inventory of standing trees, circular plots with a radius of 12.6 m (equivalent to an area of 500 square meters) were established. The Shannon diversity index, Allometric equations and Difference in Differences (DID) estimation were used to assess the data. Our study provides evidence of the positive impact of the CBFR program on enriching trees diversity. Considering stand structural attributes of both blocks showed higher trees density in the smaller diameter at breast height (DBH) category, indicating growth in both CMRBs and SMRBs. The results showed that tree biomass and carbon density were disproportionally distributed across the nine different forest reserves. On average, tree biomass and carbon density were higher in SMRBs (79.97 Mg ha−1, 37.58 Mg C ha−1) compared to CMRBs (33.51 Mg ha−1, 15.74 Mg C ha−1). However, CMRBs in Madigala reserve represent the highest biomass (56.53 and 59.92 Mg ha−1) and carbon density (26.57 and 28.16 Mg C ha−1). The results of biomass and carbon estimates were higher in all SMRBs in the nine different forest reserves compared to CMRBs. The findings suggest that future forest restoration programs in Sri Lanka should enhance participatory approaches to optimize tree species diversity, density and carbon storage, particularly in community-controlled forests. Our findings could assist developing tropical nations in understanding how CBFR impacts forest restoration objectives and improves the provision of ecological services within forests. [ABSTRACT FROM AUTHOR]

Tropical forests play an important role in mitigating global climate change, emphasizing the need for reliable estimates of forest carbon stocks at regional and global scales. This is essential for effective carbon management, which involves strategies like emission reduction and enhanced carbon sequestration through forest restoration and conservation. However, reliable sample-based estimations of forest carbon stocks require accurate allometric equations, which are lacking for the rainforests of the Atlantic Forest Domain (AFD). In this study, we fitted biomass equations for the three main AFD forest types and accurately estimated the amount of carbon stored in their above-ground biomass (AGB) in Rio de Janeiro state, Brazil. Using non-destructive methods, we measured the total wood volume and wood density of 172 trees from the most abundant species in the main remnants of rainforest, semideciduous forest, and restinga forest in the state. The biomass and carbon stocks were estimated with tree-level data from 185 plots obtained in the National Forest Inventory conducted in Rio de Janeiro. Our locally developed allometric equations estimated the state's biomass stocks at 70.8 ± 5.4 Mg ha−1 and carbon stocks at 35.4 ± 2.7 Mg ha−1. Notably, our estimates were more accurate than those obtained using a widely applied pantropical allometric equation from the literature, which tended to overestimate biomass and carbon stocks. These findings can be used for establishing a baseline for monitoring carbon stocks in the Atlantic Forest, especially in the context of the growing voluntary carbon market, which demands more consistent and accurate carbon stock estimations. [ABSTRACT FROM AUTHOR]

The present study is an attempt to determine the carbon stock and carbon sequestration potential of forest growing stocks around a thermal power plant near Bilaspur smart city in Chhattisgarh, Central India. The non-destructive sampling method is used to estimate above-ground biomass and below-ground biomass. The height and diameter at breast height (DBH) is measured for each individual tree. The allometric equation was made for estimation of carbon storage of tree species. 35 tree species were recorded around the national thermal power plant at a radius of 30 km in four different directions (east, west, north, and south). The results revealed that Ficus benghalensis was the species that found the maximum amount of carbon storage, followed by Ficus religiosa. According to the present study, the allometric models developed can further estimate carbon stocks in forest vegetation in and around National Thermal Power Corporation power plants, and other tropical deciduous forests. [ABSTRACT FROM AUTHOR]

Forests are the largest carbon sinks in the world. They play a crucial role in mitigating climate change through carbon storage. Assessing carbon storage in forests is essential for policy formulation, management planning, and as a strategy to reduce the impacts of global warming. The aims of this research were to explore plant diversity, assess tree biomass, and evaluate carbon storage and carbon credits in urban forestry areas under the Thailand Voluntary Emission Reduction Program (T-VER). The study was conducted in the forested area of Rajamangala University of Technology Isan, Surin Campus, Thailand, and encompassed 60.96 ha. The methodology involved the creation of 10 temporary sample plots, each measuring 40 × 40 m. We then surveyed the species types and measured tree diameter at breast height (DBH) and the total height. Biomass was calculated using allometric equations and the stored carbon was quantified. In this study, we identified 85 species of plants. The analysis of tree biomass averaged 23,1781.25 kg/ha or 231.81 ton/ha. The carbon storage was estimated to be 108.94 tC/ha. When aggregating the data for the entire project, the total carbon storage amounted to 6851.55, with an equivalent carbon sequestration capacity of 25,122 tCO2e in the base year (baseline). We calculated that the carbon storage capacity could increase to 28,741.00 tCO2e with proper maintenance of the urban forest area over a 10-year period, equivalent to a carbon sequestration capacity of 3619 tCO2e. This would result in a carbon credit value equivalent to USD 90,475. [ABSTRACT FROM AUTHOR]

The adaptation measures in the forestry sector are essential to mitigate climate change and to support sustainable development. Reducing emissions through improved forest management is a critical approach for climate change adaptation. Several previous investigations have estimated carbon stock for forest ecosystems. However, the drivers of this function are less understood, especially in the tropical context. Hence, this investigation intended to explore the factors affecting the carbon stock potential of dry Afromontane forest in southern Ethiopia. Employing a systematic sampling system, ten transects were laid out with 125-m intervals along the altitudinal gradient. The main plots (size 20 m × 20 m each and two subplots (each: 10 m × 10 m) were laid out in the opposite corner of the main plots and in total 46 main plots and 92 subplots were used for vegetation and dead wood data collection respectively. The plots were arranged on transects at 125 m interval to measure trees and shrubs, respectively. Moreover, a total of 230 sub-sub plots (1 m × 1 m) were arranged at the four corners and in the center of the main plots to collect herbs and litters for the assessment of non-woody carbon stocks. The altitude and topographic aspects of the sample plots were recorded using Garmin GPS and Silva compass, respectively. The carbon stock was calculated using allometric equations developed for the estimation of dry Afromontane forest carbon stocks. The effect of species type, altitude, and topographic aspects on above-ground and below-ground carbon stock was analyzed by using one-way ANOVA. The results revealed that the total above-ground and belowground carbon stock of dry Afromontane forest is 1943.2 tons/ha. The carbon stock of woody species stock increased with increasing altitudinal gradient but opposite trend was found for non-woody species. Moreover, the carbon stock of both woody and non-woody species significantly varied among topographic aspects and plant family types. The carbon stock was higher for Cupressaceae (811.5 tons/ha) followed by Podocarpaceae (630.9 tons/ha). The highest carbon stock of woody biomass was recorded in the southwest aspect (663.30 tones/ha), and the lowest carbon (141.8 tons/ha) was recorded in the northwest topographic aspect. In conclusion, the environmental and vegetation structure need to be considered in devising forest conservation strategy for climate change mitigation and adaptation. [ABSTRACT FROM AUTHOR]

The standardized methods used in carbon markets require measurement of the biomass and carbon stored in trees, which can be quantified through allometric equations. The objective of this study was to analyze aboveground biomass estimates with allometric models in three mangrove species and compare them with those used by the Climate Action Reserve (CAR) standard. The mangrove forest in Tabasco, Mexico, was certified with the Forest Protocol for Mexico Version 2.0 (FPM) of the CAR standard. Allometric equations for mangrove species were reviewed to determine the most suitable equation for the calculation of biomass. The predictions of the allometric equations of the FPM were analyzed with data from Tabasco from the National Forest and Soil Inventory 2015–2020, and the percentages of trees within the ranges of diameters of the FPM equations were determined. The FPM equations generated higher biomass values for Rhizophora mangle and lower values for Avicennia germinans than the seven equations with which they were compared. In the mangrove swamp of Ejido Úrsulo Galván, Tabasco, 81.8% of the biomass of A. germinans, 34.4% of Laguncularia racemosa and 24.0% of R. mangle were within the diameter range of the FPM equations, and in Tabasco, 28.5% of A. germinans, 16.7% of L. racemosa and 5.7% of R. mangle were within the diameter range. For A. germinans and R. mangle, we recommend using the equation that considers greater maximum diameters. The allometric equations of the FPM do not adequately predict a large percentage of the biomass. [ABSTRACT FROM AUTHOR]

Fluralaner is a recent external parasiticide, first of a new class of drugs (isoxazoline parasiticides). It is widely used in companion animals both for its wide spectrum (fleas, ticks and other mites) but also for its ease of use (oral tablets given once for 1 to three months). It is known to be eliminated primarily via the feces (>90%) as the unchanged compound. In zoo carnivores, controlling external parasites is also important and there are no specific products with a marketing authorization to control them. The first objective of this study was to evaluate the pharmacokinetic profile of fluralaner in zoo carnivores. The second objective was to demonstrate that fluralaner can be eliminated over a prolonged period of time, thereby raising questions about its potential impact on non-target species such as arthropods. After adjusting the oral dose using allometric equations, animals were dosed and fecal samples were collected on a regular basis for up to three months to determine the fecal elimination curve of fluralaner as a surrogate of plasma kinetics (for ethical and safety reasons, plasma samples were not considered). All samples were analyzed with a validated LC-MSMS technique. Our results show that, despite limitations and a limited number of animals included, most carnivores eliminate fluralaner in their feces for several weeks to months (in Lions, fluralaner was still detectable after 89 days). To our knowledge, this is the first study demonstrating such a long elimination period in animals. Further studies would be required to investigate the risk associated with the presence of active residues in other carnivore feces for the environment, especially in dogs and cats, considering the large use of this class of compounds. [ABSTRACT FROM AUTHOR]

Quantifying the vegetation aboveground biomass (AGB) is crucial for evaluating environment quality and estimating blue carbon in coastal wetlands. In this study, a UAV-LiDAR was first employed to quantify the canopy height model (CHM) of coastal Phragmites australis (common reed). Statistical correlations were explored between two multispectral remote sensing data (Sentinel-2 and JL-1) and reed biophysical parameters (CHM, density, and AGB) estimated from UAV-LiDAR data. Consequently, the reed AGB was separately estimated and mapped with UAV-LiDAR, Sentinel-2, and JL-1 data through the allometric equations (AEs). Results show that UAV-LiDAR-derived CHM at pixel size of 4 m agrees well with the observed stem height (R2 = 0.69). Reed height positively correlates with the basal diameter and negatively correlates with plant density. The optimal AGB inversion model was derived from Sentinel-2 data and JL-1 data with R2 = 0.58, RMSE = 216.86 g/m2 and R2 = 0.50, RMSE = 244.96 g/m2, respectively. This study illustrated that the synergy of UAV-LiDAR data and multispectral remote sensing images has great potential in coastal reed monitoring. [ABSTRACT FROM AUTHOR]

A system of allometric equations was generated and evaluated to estimate the total biomass and its components during the reforestation of Pinus patula in Sierra Norte of Oaxaca State, Mexico. For this purpose, 18 trees were directly sampled, which represented the growth potential of the site. Using this destructive method, the fresh weight in situ, and samples of each component of the tree were obtained to estimate the dry weight. The total tree biomass was related to its normal diameter by adjusting allometric equations using regression techniques. The exponential equation was selected to estimate the total biomass because it presented the best statistical indicators. The exponential model was again fitted to each component by using a system of simultaneous equations. The allometric equations obtained showed good performance in estimating aerial biomass in components and total tree biomass in the reforestation of Pinus patula, with similar diameters and environmental conditions. The distribution of aerial biomass estimated in the field was 69.8 % for stems, 20.5 % for branches, and 9.7 % for foliage. [ABSTRACT FROM AUTHOR]

Quantifying nitrogen uptake rates across different forest types is critical for a range of ecological questions, including the parameterization of global climate change models. However, few measurements of forest nitrogen uptake rates are available due to the intensive labor required to collect in situ data. Here, we seek to optimize data collection efforts by identifying measurements that must be made in situ and those that can be omitted or approximated from databases. We estimated nitrogen uptake rates in 18 mature monodominant forest stands comprising 13 species of diverse taxonomy at the Morton Arboretum in Lisle, IL, USA. We measured all nitrogen concentrations, foliage allocation, and fine root biomass in situ. We estimated wood biomass increments by in situ stem diameter and stem core measurements combined with allometric equations. We estimated fine root turnover rates from database values. We analyzed similar published data from monodominant forest FACE sites. At least in monodominant forests, accurate estimates of forest nitrogen uptake rates appear to require in situ measurements of fine root productivity and are appreciably better paired with in situ measurements of foliage productivity. Generally, wood productivity and tissue nitrogen concentrations may be taken from trait databases at higher taxonomic levels. Careful sorting of foliage or fine roots to species is time consuming but has little effect on estimates of nitrogen uptake rate. By directing research efforts to critical in situ measurements only, future studies can maximize research effort to identify the drivers of varied nitrogen uptake patterns across gradients. [ABSTRACT FROM AUTHOR]

Neolicaphrium recens (Mammalia, Litopterna) was a slender South American Native Ungulate (SANU). The assessment of its body size is a big challenge because there are no living representatives and no clear close morphological analogues. In this contribution, we report for the first time a femur of N. recens exhumed from Late Pleistocene sediments of Uruguay, improving the knowledge of the postcranial skeleton of the species. This stylopodial element is important for doing palaeobiological inferences, including estimating the body mass. We performed body mass estimations by previous allometric equations. As a method to directly test the models and their usefulness in fossils, we applied the equations on six specimens of extant deers of known body weight and with skeletons preserved. According to the obtained data, the transverse width at the middle of the diaphysis and the circumference of the bone at that level can be used with confidence to estimate the body mass of fossil ungulates. We point out a set of more probable values of body mass for N. recens: 28.76298 ± 10.6412, 27.78496 ± 8.0576, and 26.72 ± 10.42 kg. Morphological variables as well as the models for estimating body masses in fossils are widely discussed. [ABSTRACT FROM AUTHOR]

Deforestation and forest degradation in the tropics have led to significant carbon (C) emissions. Agroforestry (AF) practices are suitable land-use options for tackling such declines in ecosystem services, including climate change (CC) mitigation and biodiversity conservation. However, it is unclear how biomass models, AF practices, and socioecological factors determine these roles, which hinder the implementation of climate change mitigation initiatives. This study aimed to i) evaluate the biomass carbon and soil organic carbon (SOC) stocks of the three AF practices in relation to socioecological variables in central Ethiopia, and ii) compare the biomass carbon stock using different allometric models. Three AF practices were considered, namely, homegardens, parklands, and woodlots. A total of 432 soil samples were collected from 0–30 and 30–60 cm soil depths. Out of this total, 216 samples were used to determine the soil organic carbon fraction (%C), while the remaining 216 samples were used to calculate the bulk density. The study found that the currently developed allometric equations were the most accurate to estimate biomass carbon stocks in the landscape when compared to previous models. The study found a higher overall biomass C stock in woodlots (165.6 Mg ha−1) than in homegardens (134.1 Mg ha−1) and parklands (20.0 Mg ha−1). Conversely, overall, SOC stock was higher for homegardens (143.9 Mg ha−1), but lower for parklands (53.4 Mg ha−1). The total C stock (biomass carbon and SOC stocks) was comparable between homegardens (277.9 Mg ha−1) and woodlots (275.4 Mg ha−1). The study found that elevation, wealth levels, AF farm age, and size have a positive and significant (P < 0.05) effect on overall biomass C stock but non-significant with slope (P > 0.05). Similarly, SOC stock increased with increasing elevation, AF farm age, and wealth status but decreased with slope and non-significant with AF farm size. The study also showed that species diversity had a positive (P < 0.05) effect on overall biomass C stock in homegardens. The overall study highlights that AF practices have great potential to lock up more carbon in biomass and soils; however, these potentials were determined by socioecological variables. Thus, these factors should be considered in management strategies that preserve trees in agricultural landscapes in order to mitigate climate change and support the livelihoods of farmers. [ABSTRACT FROM AUTHOR]

Bamboo forests in Colombia and the Andean region of South America represent high-value ecosystems that provide ecological and economic benefits with local and global impacts. One of the ecosystem services provided by these forests is associated with their capacity to store carbon. In this study, data collected from monitoring plots were used to estimate the carbon content in different pools. Bamboo biomass (Bba), tree biomass (Btree), litter (Cli) and soil organic carbon (SOC) were assessed. The approximate total ecosystem carbon stock (TECaprox) ranged from 198.4 Mg C ha−1 to 330.9 Mg C ha−1 and bamboo carbon Cba represents approximately 50%. In addition, considering the relevance of developing tools to facilitate bamboo inventory and biomass estimates, allometric equations (AE) to estimate bamboo aboveground biomass (AGB) were fitted using the diameter of culms at breast height (dbh) and the total culm length (l) as predictor variables. The fitted AEs included the weighted linear, weighted log-transformed and weighted nonlinear fixed effect models. To compliance the additivity of biomass components a simultaneous systems of biomass equations (seemingly unrelated regressions) were also fitted. The precision and accuracy were assessed considering the residual diagnostic plots and statistics, such as the root-mean-square error (RMSE), RMSE percentage error (RMSEPE) and the Furnival's index (Fln) for weighted log-transformed models and cross-validation. The performance of the models was similar with an RMSE of approximately 10 kg and 26% of RMSEPE, with slightly lower error for the weighted log-transformed model for the fitting and validation phases. A proper performance was also evidenced for the simultaneous approach for predicting AGB. Bamboo forests showed high relevance as carbon sinks and therefore might be considered strategic tropical ecosystems for climate change mitigation. On the other hand, the fitted AE exhibited proper performance and therefore provided reliable possibilities for estimating the AGB of bamboo during inventories. For practical reasons, the use of models with dbh as a predictor variable is recommended. [ABSTRACT FROM AUTHOR]

Background: The leaf area index (LAI) is one of the structural indices of forests and a key variable in the state of forest ecosystems. This index is one of the major structural indices of forests that plays an important role in the processes of evaporation and transpiration and in monitoring the growth of trees. The role of LAI is very important in the changes in the structural quantitative characteristics of forest stands. There is a general relationship between the LAI and the quantitative characteristics of the mass. The leaf area of each tree can be estimated using allometric equations of quantitative characteristics. This research focuses on the effects of changes in the quantitative characteristics, such as tree density (n.ha-1), basal area (m2.ha-1), volume (m3.ha-1), mean height (m), mean diameter at breast height (DBH, cm), crown area (m2.ha-1), and crown volume (m3.ha-1) on the LAI and preparation of their allometric equations in the broadleaf forests of Golestan province. Methods: To collect ground information on LAI, 227 circular sample plots with an area of 1000 m2 with a systematic sampling method and a 100 × 100 m grid were dismounted in five habitats from west to east (Kordkoy, Shasat Kalathe, Zarrin, Gol, Sorkhdari, and Loveh). In the center of each sample plot, the LAI was measured using a leaf harvesting trap with dimensions of 60 × 60 cm. The geographic center of each sample was recorded using a Differential Global Positioning System device. The species type, breast diameter greater than 12.5 cm, the height of trees, large diameter, and small crown diameter are measured, then as tree density (n.ha-1), basal area (m2.ha-1), volume (m3.ha-1), mean height (m), mean DBH (cm), crown area (m2.ha-1), and crown volume (m3.ha-1) located in each sample plot were calculated in each plot. To calculate the LAI, it is first necessary to measure the specific leaf area of all species in the study area. To calculate the LAI, 20 trees were separated from each tree in each habitat and five leaf samples were separated from each tree in four geographical directions. In total, more than 15,000 leaf samples were analyzed and scanned in five habitats. The area of each leaf was measured using ImageJ software. The wet and dry weight and surface area were measured simultaneously using a digital scale with an accuracy of 0.01 and then scanned with a high-resolution scanner. After scanning, the leaves were dried in an oven at 72 °C for 48 hours to obtain their dry weights. Non-linear rational function, Gaussian, hyperbolic, heat capacity, and exponential models were used to investigate the relationship between LAI and the structural characteristics of the stand. Results: The results of the analysis of descriptive statistics showed that the minimum, maximum, average, and standard deviation of the LAI were calculated for 227 samples (1.86, 13.45, 6.33, and 2.33), respectively. The results of the analysis of descriptive statistics also showed that the mean and standard deviation for the characteristics of volume (m3.ha-1), tree density (n.ha-1), basal area (m2.ha-1), crown area (m2.ha-1), crown volume (m3.ha-1), mean height (m), and mean DBH (cm) were respectively (96.96) 298 and 18.205), (24.05 and 12.82), (24.05 and 12.82), (51.148 and 54.155), (2.781 and 05.95), (41.36 and 9.97), and (25.81 and 4.93). The results of the relationships between the LAI and the quantitative characteristics of the volume (m3.ha-1), tree density (n.ha-1), basal area (m2.ha-1), crown area (m2.ha-1), crown volume (m3.ha- 1), mean height (m), and mean DBH (cm) of the coefficients of determination showed (36-0.96) R2 = 0.00 with a mean square error of MSE = 0.48-2.06. Among the investigated quantitative traits, the average height, crown volume per hectare, and volume per hectare gained the highest R2 values (0.36-0.96) and the MSE (0.48-2.06) with Gaussian, Richard, and heat capacity allometric models, and the tree density trait (n.ha-1). The lowest R2 (0.36) and MSE (2.06) in the study of LAI were obtained with the Gaussian model. The results also showed large changes in the LAI for the crown volume trait up to 400 (m3.ha-1), followed by a uniform trend. For the average height of up to 40 (m), many changes were found in the LAI. For the volume trait (m3.ha-1), the LAI increased up to 800 (m3.ha-1) and then showed a uniform and even downward trend until 1200 (m3.ha-1). Conclusion: The results of this research demonstrate that the three quantitative traits, viz. crown volume (m3.ha-1), mean height, and volume (m3.ha-1), have the greatest effect on the changes in the LAI. Thus, these three traits can better explain the LAI. The LAI can estimated using the three crown volume (m3.ha-1), mean height, and volume (m3.ha-1) traits. Based on these three traits, the LAI can explained on a large scale, and the estimated results can be used in climate models and the development of appropriate climate change policies. [ABSTRACT FROM AUTHOR]

Coastal wetlands are of paramount importance as major reservoirs of blue carbon (C), playing a crucial role in providing nature-based solutions to mitigate climatic changes. This research aimed to analyse the dynamics of total blue C (TBC) and its components; viz. soil organic C (SOC), below ground C, and above ground C; as well how they are influenced by land use/ land cover (LULC) categories and wetland situations. Subsequently, study were identified as one restored wetland and another degraded wetland in the Medinipur Coastal Plain, India. The LULC categories were analyzed using Pleiades 1A and 1B satellite imagery, corresponding to the restored and degraded wetland, respectively. The quantification of SOC was based on point-specific sample data collected from both wetlands (nr=250; nd=84). Above ground biomass (AGB) was appraised employing allometric relationships involving field-measured dendrometric variables. Below ground biomass values were calculated using indirect allometric equations that take into account the AGB values. Integrating all the components, TBC stock of the restored and degraded wetlands were estimated at 246710.91 Mg and 7865.49 Mg, respectively. In the restored wetland, dense mangrove and open mangrove exhibited higher concentrations of blue C components, while other LULC categories demonstrated moderate to low densities. In the degraded wetland, the open mangrove category rec-high densities of C pools, whereas herbaceous vegetation, bare earth and sand, and waterbody exhibited lower concentrations. The results portrayed significant disparities (P<0.05) in blue C pools among different LULC categories in both wetlands. Furthermore, it was evident that wetland type and LULC category had notable (P<0.001) impacts on TBC dynamics, both individually and in combination. Overall, this research may aid in effective management of coastal wetlands as blue C sinks, emphasizing their significance as essential elements of climate mitigation strategies. [ABSTRACT FROM AUTHOR]

Promoting nature-based carbon sinks may contribute to minimise global warming. Different forest types may have different carbon sink capacity. Many areas of central Spain are covered by coexisting patches of monospecific plantations of Pinus halepensis, established since the 1960's, and native Quercus forest coppiced up to the 1960´s. We aimed to compare the carbon stock between both types of forests, considering both above and belowground compartments. In each plot, we measured the dimensions of every adult tree, the shrub cover, and we collected samples of litter and soil. The carbon pool of trees and shrubs was calculated using allometric equations, and for roots, litter, and soil, using the carbon content analysed in a laboratory or obtained from the literature. Carbon pools were analysed separately for three independent variables: plot type (Quercus/Pinus), tree basal area and slope. Overall, Quercus forests stored more carbon than Pinus plantations, thanks to a larger carbon stock in roots and shrubs in the former, which compensated for the larger aboveground carbon stock in tree biomass of Pinus plots. The carbon stock increased with basal area in all compartments except the soil. The carbon allocation pattern across compartments greatly varied between the two forest types, Pinus plots storing more than half (55%) of its carbon in the aboveground biomass of trees, while Quercus storing more carbon belowground (60%) in roots and soil. Given that belowground carbon stock is more resistant against disturbances, we conclude that native Quercus forests are more suitable for a long-term carbon storage. [ABSTRACT FROM AUTHOR]

BACKGROUND AND OBJECTIVES: Mangrove silvofishery, a unique system that combine aquaculture with mangrove forests, presents a promising sustainable solution for Indonesia's coastal communities. However, in order to achieve broad implementation, it is essential to bridge the existing knowledge gap concerning the economic and environmental benefits associated with it. The aim of this study was to assess the four primary services rendered by the Blanakan mangrove silvofishery area in Subang District, West Java: carbon sequestration, fisheries productivity, naturebased tourism, and bird sanctuary. METHODS: Carbon storage was calculated by conducting vegetation surveys and utilizing allometric equations, which took into account both aboveground and belowground biomass. During the vegetation survey, data regarding the types of mangrove plants and the diameter of each tree at breast height was gathered. To quantify fisheries production, interviews were conducted with area managers and pond farmers who are engaged in silvofishery practices within the region. The pointcount method was used to inventory the diversity of bird species. The analysis of natural tourism services encompassed an examination of visitor statistics, the state of the mangroves as a popular tourist destination, and the range of tourist activities available. FINDINGS: The study revealed the high capacity of the mangrove stands at the study location for carbon storage, with an estimated 137.9 tonnes carbon per hectare aboveground and 79 tonnes carbon per hectare belowground. Local communities actively engage in silvofishery practices within the Blanakan mangroves, cultivating fish and shrimp, with an average annual income of around 1,513 United States dollar per hectare. 2. The natural beauty of the Blanakan mangrove area attracts tourists with its diverse ecosystem and opportunities to see crocodile breeding facilities. Visitor numbers vary, averaging around 128 people per month until mid-2023. The Blanakan mangroves are home to a total of 23 bird species, contributing to a species diversity index of 2.1. Two species with significant conservation value were found: the critically endangered Javan Blue-banded Kingfisher (Alcedo euryzona) and the vulnerable Black-capped Kingfisher (Halcyon pileata). CONCLUSION: The results emphasize the importance of advancing and advocating for silvofishery as a primary alternative in Indonesia's mangrove conservation and rehabilitation initiatives, enhancing coastal environmental management. Community engagement is of utmost importance in the successful development of mangrove silvofishery, as it aims to tackle the issue of limited awareness and participation among the local community. [ABSTRACT FROM AUTHOR]

Forests play a crucial role in mitigating the impacts of climate change by sequestering carbon in their biomass and soil. However, Ethiopia faces the threat of soil carbon emissions due to deforestation and continuous cultivation. This study reviewed the analogies in phytobiomass and soil carbon evaluation methods in Ethiopia. Index-base and year-wise analysis methods were used for the compilation of the study. Developing nations, such as Ethiopia, duly enhance resilient measures to assess forest carbon stocks for effective climate change mitigation, particularly with reference to emissions from deforestation and degradation. Even though more than 90% of Ethiopia’s energy comes from forest biomass, deforestation significantly affects the carbon stored in aboveground biomass, which is the largest reservoir. Estimating forest biomass and carbon emissions entails uncertainties, with error ranges around ±50% for aboveground pools and ±90% for soil carbon pools. Various tier methodologies are employed by experts to estimate forest biomass and carbon stock emissions, with Tier 2 factors serving as default emissions but country-specific factors offering improved accuracy over Tier 1. Tier 3 methodologies require highly specific inventory data on carbon stocks in different pools and common measurements of key carbon stocks. Forest conservation enhances biodiversity, ecosystem resilience, and essential ecosystem services, fostering soil health, regulating water cycles, and supporting diverse plant and animal species. In conclusion, directing efforts towards forest conservation not only helps maintain biodiversity and ecosystem services but also significantly contributes to mitigating climate change by enhancing carbon storage capacities and reducing greenhouse gas emissions.

The von Bertalanffy growth function has been widely used by hydrobiologists to study the lifetime pattern of somatic growth in fishes. Recently, the new ontogenetic growth model has been introduced as a special case of the von Bertalanffy equation based on allometric scaling which has also been of particular importance since it offers the basic tools for deriving allometric associations for fish growth rates and the timing of life history events. In this manuscript, we extend these models by introducing four different fractal growth models based on the concept of fractal calculus. From mathematics perspectives, these models extend and generalize both the traditional and the ontogenetic growth models to new time scales and offer a number of motivating features not found in the basic models and in agreement with observations. The best of these models, in our opinion, corresponds to the one which takes into account anisotropy in a reservoir. Additional points have been obtained and discussed accordingly. [ABSTRACT FROM AUTHOR]

Dicranopteris dichotoma is a pioneer herbaceous plant species that is tolerant to barrenness and drought. Mapping its biomass spatial distribution is valuable for understanding its important role in reducing soil erosion and restoring ecosystems. This research selected Luodihe watershed in Changting County, Fujian Province, China, where soil erosion has been a severe problem for a long time, as a case study to explore the method to estimate biomass, including total and aboveground biomass, through the integration of field measurements, handheld laser scanning (HLS), and airborne laser scanning (ALS) data. A stepwise regression model and an allometric equation form model were used to develop biomass estimation models based on Lidar-derived variables at typical areas and at a regional scale. The results indicate that at typical areas, both total and aboveground biomass were best estimated using an allometric equation form model when HLS-derived height and density variables were extracted from a window size of 6 m × 6 m, with the coefficients of determination (R2) of 0.64 and 0.58 and relative root mean square error (rRMSE) of 28.2% and 35.8%, respectively. When connecting HLS-estimated biomass with ALS-derived variables at a regional scale, total and aboveground biomass were effectively predicted with rRMSE values of 17.68% and 17.91%, respectively. The HLS data played an important role in linking field measurements and ALS data. This research provides a valuable method to map Dicranopteris biomass distribution using ALS data when other remotely sensed data cannot effectively estimate the understory vegetation biomass. The estimated biomass spatial pattern will be helpful to understand the role of Dicranopteris in reducing soil erosion and improving the degraded ecosystem. [ABSTRACT FROM AUTHOR]

Carbon stocks provide information that is essential for analyzing the role of forests in global climate mitigation, yet they are highly vulnerable to wildfires in Mediterranean ecosystems. These carbon stocks' exposure to fire is usually estimated from specific allometric equations relating tree height and diameter to the overall amount of aboveground carbon storage. Assessments of vulnerability to fire additionally allow for specific fire resistance (bark thickness, crown basal height) and post-fire recovery traits (cone mass for regeneration, and fine branches or leaves mass for flammability) to be accounted for. These traits are usually considered as static, and their temporal dynamic is rarely assessed, thus preventing a full assessment of carbon stocks' vulnerability and subsequent cascading effects. This study aimed to measure the pools of carbon stocks of individual trees varying between 30 and 96 years old in the Djbel Mansour Aleppo pine (Pinus halepensis) forest in semi-arid central Tunisia in the southern range of its distribution to fit a sigmoid equation of the carbon pools and traits recovery according to age as a vulnerability framework. Allometric equations were then developed to establish the relationships between fire vulnerability traits and dendrometric independent variables (diameter at breast height, height, and live crown length) for further use in regional vulnerability assessments. The total carbon stocks in trees varied from 29.05 Mg C ha−1 to 92.47 Mg C ha−1. The soil organic carbon stock (SOC) at a maximum soil depth of 0–40 cm varied from 31.67 Mg C ha−1 to 115.67 Mg C ha−1 at a soil depth of 0–70 cm. We could identify an increasing resistance related to increasing bark thickness and basal crown height with age, and enhanced regeneration capacity after 25 years of age with increasing cone biomass, converging toward increasing vulnerability and potential cascading effects under shorter interval fires. These results should be considered for rigorous forest carbon sequestration assessment under increasing fire hazards due to climate and social changes in the region. [ABSTRACT FROM AUTHOR]

Summary: Large trees in plantations generally produce more wood per unit of resource use than small trees. Two processes may account for this pattern: greater photosynthetic resource use efficiency or greater partitioning of carbon to wood production.We estimated gross primary production (GPP) at the individual scale by combining transpiration with photosynthetic water‐use efficiency of Eucalyptus trees. Aboveground production fluxes were estimated using allometric equations and modeled respiration; total belowground carbon fluxes (TBCF) were estimated by subtracting aboveground fluxes from GPP. Partitioning was estimated by dividing component fluxes by GPP.Dominant trees produced almost three times as much wood as suppressed trees. They used 25 ± 10% (mean ± SD) of their photosynthates for wood production, whereas suppressed trees only used 12 ± 2%. By contrast, dominant trees used 27 ± 19% of their photosynthate belowground, whereas suppressed trees used 58 ± 5%. Intermediate trees lay between these extremes. Photosynthetic water‐use efficiency of dominant trees was c. 13% greater than the efficiency of suppressed trees.Suppressed trees used more than twice as much of their photosynthate belowground and less than half as much aboveground compared with dominant trees. Differences in carbon partitioning were much greater than differences in GPP or photosynthetic water‐use efficiency. [ABSTRACT FROM AUTHOR]

Accompanying climate change and sea level rise, tidal marsh mortality in coastal wetlands has been globally observed that urges the documentation of high-resolution, 3D marsh inventory to assist resilience planning. Drone Lidar has proven useful in extracting the fine-scale bare earth terrain and canopy height. Beyond that, this study performed marsh biomass mapping from drone Lidar point cloud in a S. alterniflora-dominated estuary on the Southeast U.S. coast. Three point classes (ground, low-veg, and high-veg) were classified via point cloud deep learning. Considering only vegetation points in the vertical profile, a profile area-weighted height (HPA) was extracted at a grid size of 50 cm × 50 cm. Vegetation point densities were also extracted at each grid. Adopting the plant-level allometric equations of stem biomass from long-term S. alterniflora surveys, a Lidar biomass index (Lidar_BI) was built to represent the relative quantity of marsh biomass in a range of [0, 1] across the estuary. Compared with the clipped dry biomass samples, it achieved a comparable and slightly better performance (R2 = 0.5) than the commonly applied spectral index approaches (R2 = 0.4) in the same marsh field. This study indicates the feasibility of the drone Lidar point cloud for marsh biomass mapping. More advantageously, the drone Lidar approach yields information on plant community architecture, such as canopy height and plant density distributions, which are key factors in evaluating marsh habitat and its ecological services. [ABSTRACT FROM AUTHOR]

Biomass allocation in plants is the foundation for understanding dynamics in ecosystem carbon balance, species competition, and plant–environment interactions. However, existing work on plant allometry has mainly focused on trees, with fewer studies having developed allometric equations for grasses. Grasses with different life histories can vary in their carbon investment by prioritizing the growth of specific organs to survive, outcompete co‐occurring plants, and ensure population persistence. Further, because grasses are important fuels for wildfire, the lack of grass allocation data adds uncertainty to process‐based models that relate plant physiology to wildfire dynamics. To fill this gap, we conducted a greenhouse experiment with 11 common California grasses varying in photosynthetic pathway and growth form. We measured plant sizes and harvested above‐ and belowground biomass throughout the life cycle of annual species, while for the establishment stage of perennial grasses to quantify allometric relationships for leaf, stem, and root biomass, as well as plant height and canopy area. We used basal diameter as a reference measure of plant size. Overall, basal diameter is the best predictor for leaf and stem biomass, height, and canopy area. Including height as another predictor can improve model accuracy in predicting leaf and stem biomass and canopy area. Fine root biomass is a function of leaf biomass alone. Species vary in their allometric relationships, with most variation occurring for plant height, canopy area, and stem biomass. We further explored potential trade‐offs in biomass allocation across species between leaf and fine root, leaf and stem, and allocation to reproduction. Consistent with our expectation, we found that fast‐growing plants allocated a greater fraction to reproduction. Additionally, plant height and specific leaf area negatively influenced the leaf‐to‐stem ratio. However, contrary to our hypothesis, there were no differences in root‐to‐leaf ratio between perennial and annual or C4 and C3 plants. Our study provides species‐specific and functional‐type‐specific allometry equations for both above‐ and belowground organs of 11 common California grass species, enabling nondestructive biomass assessment in California grasslands. These allometric relationships and trade‐offs in carbon allocation across species can improve ecosystem model predictions of grassland species interactions and environmental responses through differences in morphology. [ABSTRACT FROM AUTHOR]

Biogenic volatile organic compounds (BVOCs) are emitted by vegetation and react with other compounds to form ozone and secondary organic matter (OM). In regional air quality models, biogenic emissions are often calculated using a plant functional type approach, which depends on the land use category. However, over cities, the land use is urban, so trees and their emissions are not represented. Here, we develop a bottom-up inventory of urban tree biogenic emissions in which the location of trees and their characteristics are derived from the tree database of the Paris city combined with allometric equations. Biogenic emissions are then computed for each tree based on their leaf dry biomass, tree-species-dependent emission factors, and activity factors representing the effects of light and temperature. Emissions are integrated in WRF-CHIMERE air quality simulations performed over June–July 2022. Over Paris city, the urban tree emissions have a significant impact on OM, inducing an average increase in the OM of about 5 %, reaching 14 % locally during the heatwaves. Ozone concentrations increase by 1.0 % on average and by 2.4 % during heatwaves, with a local increase of up to 6 %. The concentration increase remains spatially localized over Paris, extending to the Paris suburbs in the case of ozone during heatwaves. The inclusion of urban tree emissions improves the estimation of OM concentrations compared to in situ measurements, but they are still underestimated as trees are still missing from the inventory. OM concentrations are sensitive to terpene emissions, highlighting the importance of favoring urban tree species with low-terpene emissions. [ABSTRACT FROM AUTHOR]

Background: Carbon (C) sink and stock are among the most important ecosystem services provided by forests in climate change mitigation policies. In this context, old-growth forests constitute an essential reference point for the development of close-to-nature silviculture, including C management techniques. Despite their small extent in Europe, temperate old-growth forests are assumed to be among the most prominent in terms of biomass and C stored. However, monitoring and reporting of C stocks is still poorly understood. To better understand the C stock amount and distribution in temperate old-growth forests, we estimated the C stock of two old-growth stands in the Dinaric Alps applying different assessment methods, including direct and indirect approaches (e.g., field measurements and allometric equations vs. IPCC standard methods). This paper presents the quantification and the distribution of C across the five main forest C pools (i.e., aboveground, belowground, deadwood, litter and soil) in the study areas and the differences between the applied methods. Results: We report a very prominent C stock in both study areas (507 Mg C ha− 1), concentrated in a few large trees (36% of C in 5% of trees). Moreover, we found significant differences in C stock estimation between direct and indirect methods. Indeed, the latter tended to underestimate or overestimate depending on the pool considered. Conclusions: Comparison of our results with previous studies and data collected in European forests highlights the prominence of temperate forests, among which the Dinaric Alps old-growth forests are the largest. These findings provide an important benchmark for the development of future approaches to the management of the European temperate forests. However, further and deeper research on C stock and fluxes in old-growth stands is of prime importance to understand the potential and limits of the climate mitigation role of forests. [ABSTRACT FROM AUTHOR]