Crown Biomass Research Articles

Accurate Calculation of Upper Biomass Volume of Single Trees Using Matrixial Representation of LiDAR Data

This paper introduces a novel method for accurately calculating the upper biomass of single trees using Light Detection and Ranging (LiDAR) point cloud data. The proposed algorithm involves classifying the tree point cloud into two distinct ones: the trunk point cloud and the crown point cloud. Each part is then processed using specific techniques to create a 3D model and determine its volume. The trunk point cloud is segmented based on individual stems, each of which is further divided into slices that are modeled as cylinders. On the other hand, the crown point cloud is analyzed by calculating its footprint and gravity center. The footprint is further divided into angular sectors, with each being used to create a rotating surface around the vertical line passing through the gravity center. All models are represented in a matrix format, simplifying the process of minimizing and calculating the tree’s upper biomass, consisting of crown biomass and trunk biomass. To validate the proposed approach, both terrestrial and airborne datasets are utilized. A comparison with existing algorithms in the literature confirms the effectiveness of the new method. For a tree dimensions estimation, the study shows that the proposed algorithm achieves an average fit between 0.01 m and 0.49 m for individual trees. The maximum absolute quantitative accuracy equals 0.49 m, and the maximum relative absolute error equals 0.29%.

Hydromulches suppress weeds and maintain fruit production in organically managed strawberry systems

Polyethylene (PE) mulches are widely used in strawberry (Fragaria×ananassaDuch) production for weed suppression and crop growth optimization. However, PE mulches are not biodegradable and contribute to plastic pollution. Our objective was to develop and test biodegradable liquid-applied ‘hydromulches’ (HMs) as a sustainable alternative to PE mulch. HM weed suppression efficacy, strawberry plant growth, and yield were evaluated. HM formulations consisted of shredded newsprint paper (NP), water, and a tackifier, either guar gum (GG) or psyllium husk (PH) added at 2 or 6%. Experiments were conducted at two environmentally distinct locations: northwest Washington (WA) and eastern North Dakota (ND). Five HM formulations were compared to black PE mulch within a randomized complete block design with four replications. PE mulch suppressed weeds completely at peak weed emergence and peak weed vegetative growth at both locations. Formulations of HM containing GG provided superior weed suppression compared to other HM formulations at peak weed emergence (4–6 vs. 18–22 plants m-2, respectively). At peak vegetative growth, HM formulations containing GG had the lowest weed density compared to other HMs in ND (1 vs. 9–12 plants m-2), whereas these differences were not observed in WA. Total weed biomass did not differ among HMs across both locations. GG HM formulations deteriorated similarly to PE mulch (3–5% vs. 2%, respectively) in ND, whereas other HMs deteriorated more substantially. In WA, all HMs deteriorated more than PE mulch (6–12% vs. 1%, respectively). Fruit yield did not differ among treatments in weedy and weed-free subplots (194–254 g plant-1) in WA. In ND, yield was greater in all HM treatments compared to PE mulch in both weedy and weed-free subplots. Across both locations, strawberry canopy cover was greater in PE mulch (56.1% canopy cover) compared to 2%GG and NP (42.4 and 39.8% canopy cover). Strawberry plant biomass was similar among mulch treatments. However, strawberry leaf and crown biomass were slightly lower in 2%PH compared to other mulch treatments. Results demonstrate HMs with GG tackifier are a promising alternative to PE mulch in organic strawberry systems based on ability to suppress weeds, enhance strawberry growth, and maintain yield.

Estimating Crown Biomass in a Multilayered Fir Forest Using Airborne LiDAR Data

The estimation of individual biomass components within tree crowns, such as dead branches (DB), needles (NB), and branch biomass (BB), has received limited attention in the scientific literature despite their significant contribution to forest biomass. This study aimed to assess the potential of multispectral LiDAR data for estimating these biomass components in a multi-layered Abies borissi-regis forest. Destructive (i.e., 13) and non-destructive (i.e., 156) field measurements were collected from Abies borisii-regis trees to develop allometric equations for each crown biomass component and enrich the reference data with the non-destructively sampled trees. A set of machine learning regression algorithms, including random forest (RF), support vector regression (SVR) and Gaussian process (GP), were tested for individual-tree-level DB, NB and BB estimation using LiDAR-derived height and intensity metrics for different spectral channels (i.e., green, NIR and merged) as predictors. The results demonstrated that the RF algorithm achieved the best overall predictive performance for DB (RMSE% = 17.45% and R2 = 0.89), NB (RMSE% = 17.31% and R2 = 0.93) and BB (RMSE% = 24.09% and R2 = 0.85) using the green LiDAR channel. This study showed that the tested algorithms, particularly when utilizing the green channel, accurately estimated the crown biomass components of conifer trees, specifically fir. Overall, LiDAR data can provide accurate estimates of crown biomass in coniferous forests, and further exploration of this method’s applicability in diverse forest structures and biomes is warranted.

Pipe Model Can Accurately Estimate Crown Biomass of Larch (Larix olgensis) Plantation Forest in Northeast China

The pipe model theory has been applied to estimate allometry of trees in many regions; however, its reliability and generality need more verification for estimating crown biomass in China. In the present study, the crown biomass of Larix olgensis plantations in four sites in northeast China was estimated using the pipe model, and the correlation efficiency index of larch crown biomass for pipe model estimation was 0.953. The crown biomass of larch plantations could be accurately estimated by the tree height, crown base height, and stem area at breast height. Meanwhile, the effects of site, stand density, and age on the accuracy of crown biomass estimated by the pipe model were detected. The covariance analysis showed that the effect of age on crown biomass was 0.024, indicating that age had a significant effect on the estimation accuracy in this model, while site and stand density had no significant effects (p = 0.180 and p = 0.169). Our study showed that the crown biomass of L. olgensis plantations in northeast China could be accurately estimated using the pipe model, and we recommend considering the age effect in practical applications.

Crown-Level Structure and Fuel Load Characterization from Airborne and Terrestrial Laser Scanning in a Longleaf Pine (Pinus palustris Mill.) Forest Ecosystem

Airborne Laser Scanners (ALS) and Terrestrial Laser Scanners (TLS) are two lidar systems frequently used for remote sensing forested ecosystems. The aim of this study was to compare crown metrics derived from TLS, ALS, and a combination of both for describing the crown structure and fuel attributes of longleaf pine (Pinus palustris Mill.) dominated forest located at Eglin Air Force Base (AFB), Florida, USA. The study landscape was characterized by an ALS and TLS data collection along with field measurements within three large (1963 m2 each) plots in total, each one representing a distinct stand condition at Eglin AFB. Tree-level measurements included bole diameter at breast height (DBH), total height (HT), crown base height (CBH), and crown width (CW). In addition, the crown structure and fuel metrics foliage biomass (FB), stem branches biomass (SB), crown biomass (CB), and crown bulk density (CBD) were calculated using allometric equations. Canopy Height Models (CHM) were created from ALS and TLS point clouds separately and by combining them (ALS + TLS). Individual trees were extracted, and crown-level metrics were computed from the three lidar-derived datasets and used to train random forest (RF) models. The results of the individual tree detection showed successful estimation of tree count from all lidar-derived datasets, with marginal errors ranging from −4 to 3%. For all three lidar-derived datasets, the RF models accurately predicted all tree-level attributes. Overall, we found strong positive correlations between model predictions and observed values (R2 between 0.80 and 0.98), low to moderate errors (RMSE% between 4.56 and 50.99%), and low biases (between 0.03% and −2.86%). The highest R2 using ALS data was achieved predicting CBH (R2 = 0.98), while for TLS and ALS + TLS, the highest R2 was observed predicting HT, CW, and CBD (R2 = 0.94) and HT (R2 = 0.98), respectively. Relative RMSE was lowest for HT using three lidar datasets (ALS = 4.83%, TLS = 7.22%, and ALS + TLS = 4.56%). All models and datasets had similar accuracies in terms of bias (<2.0%), except for CB in ALS (−2.53%) and ALS + TLS (−2.86%), and SB in ALS + TLS data (−2.22%). These results demonstrate the usefulness of all three lidar-related methodologies and lidar modeling overall, along with lidar applicability in the estimation of crown structure and fuel attributes of longleaf pine forest ecosystems. Given that TLS measurements are less practical and more expensive, our comparison suggests that ALS measurements are still reasonable for many applications, and its usefulness is justified. This novel tree-level analysis and its respective results contribute to lidar-based planning of forest structure and fuel management.

Estimation of Biomass Dynamics and Allocation in Chinese Fir Trees Using Tree Ring Analysis in Hunan Province, China

Studying tree biomass dynamics and allocation is crucial to understanding the forest carbon cycle and the adaptation of trees to the environment. However, traditional biomass surveys are time-consuming and labor-intensive, so few studies have specifically examined biomass formation in terms of the increase in individual tree biomass, and the role that tree age and site conditions play in this process, especially tree roots, is unclear. We studied the tree ring characteristics of 87 sample trees (8–40 years old) from 29 Chinese fir plantations with different site conditions and measured the biomass of their stems, crowns, and roots. The biomass increment at various age stages during tree growth was determined via using tree ring analysis, and a generalized additive mixed model (GAMM) was used to analyze biomass formation and allocation, as well as the specific impact of site conditions on them. The results showed that the biomass increment of Chinese fir trees first increased and then decreased with age, and improving site conditions delayed the carbon maturation of the trees. The proportion of stem biomass increased with age, while the proportion of crown biomass decreased and the proportion of root biomass increased and then decreased. The effect of the site conditions on the tree biomass allocation showed a nonlinear trend. Tree ring analysis provides a feasible and effective method for assessing tree growth and biomass dynamics. Forest managers can use the findings of this study to scientifically optimize the management of increasing forest carbon sequestration.

Soybean growth and yield on corn cob compost application

The continuous use of chemical fertilizers contributes to gas emissions that cause global warming, climate change and low nutrient use efficiency. Compost is an effort to increase nutrient supply to improve soil quality and nutrient efficiency in food crops. The aim of the study was to examine the role of corn cob compost on soybean growth and yield. The study used a complete randomized block design with one factor, namely the dose of corn cob compost with six levels, namely chemical fertilizer 0.225 ton/ha, corn cob compost dose 2; 3; 4;5; 6 tonnes/ha. The dose of compost affects the root biomass. Corn cob compost 5 tons/ha was able to increase soybean yields by 2.28 tons and was not significantly different from chemical fertilizers. Corn cob compost 5 tons/ha produced the highest weight of 100 seeds, namely 41.33 g. Soybean yields were positively correlated with root biomass, number of leaves and crown biomass. Compost from corn cobs is an organic nutrient that can promote soybean growth and yield.

Effect of Grazing Treatments on Phenotypic and Reproductive Plasticity of Kobresia humilis in Alpine Meadows of the Qinghai-Tibet Plateau

Plant phenotypic and reproductive plasticity is strongly influenced by long-term grazing activities. It is important to understand the life history of dominant plant species, such as Kobresia humilis of alpine meadow, for the stability and sustainable grazing administration meadow on the Qinghai-Tibetan Plateau (QTP). We compared the effects of different grazing treatments (grazing yak, Y; grazing Tibetan sheep, S; and grazing Tibetan sheep and yak, S+Y) on the reproductive and phenotypic plasticity of K. humilis in an alpine meadows on the northeastern margin of the Qilian Mountains in China. The results showed that different grazing treatments had significantly effects on the K. humilis phenotype and reproductive plasticity. The Y treatment significantly reduced the plant height, crown width and K. humilis biomass, but increased the density, which was 1.27 and 1.53 times higher than that in the S+Y and S treatments, respectively. Further, the S+Y treatment significantly increased the crown width, biomass, and future life expectancy of K. humilis. Whereas the S treatment increased the height of K. humilis significantly, which was 1.57 and 1.10 times higher than that in the Y and S+Y treatments, respectively. Both Y and S treatments significantly increased the sexual reproduction efficacy of K. humilis but reduced the storage efficacy. The storage efficacy at S+Y treatment was highest among these treatments. Further, grazing treatments did not change the resource allocation strategy of K. humilis, while the sexual reproductive efficacy was significantly higher than the vegetative reproduction efficacy. The storage efficacy was significantly higher than the growth efficacy among the different grazing treatments. The increase of Cyperaceae indicates the degradation of Cyperaceae—Poaceae meadows. This study showed that grazing Tibetan sheep is a more sustainable grazing method in cold season pastures of alpine meadows on the QTP.

Simultaneous Compatible System of Models of Height, Crown Length, and Height to Crown Base for Natural Secondary Forests of Northeast China

Individual trees are characterized by various sizes and forms, such as diameter at breast height, total height (H), height to crown base (HCB), crown length (CL), crown width, and crown and stem forms. Tree characteristics are strongly related to each other, and studying their relationships is very important. The knowledge of the compatibility and additivity properties of the major tree characteristics, such as H, CL, and HCB, is essential for informed decision-making in forestry. H can be used to represent site quality and CL represents biomass and photosynthesis of crown, which is the performance of individual tree vigor and light interception, and the longer the crown length (or shorter HCB) is, the more vigorous the tree would be. However, none of the studies have uncovered their inherent relationships quantitatively. This study attempts to explore such relationships through the application of appropriate modeling approaches. We applied seemingly unrelated regression, such as nonlinear seemingly unrelated regression (NSUR), which is commonly used for exploring the compatibility and additivity properties of the variables, for the proposes. The NSUR involves the variance and covariance matrices of the sub-models that are used for the interpretation of the correlations among the variables of interest. The data set acquired from Mongolian oak forest and spruce-fir forest in the Jingouling forest farm of the Wangqing Forest Bureau in the Northeast of China were used to construct two types of model systems: a compatible model system (the model system of H, CL, and HCB can be estimated simultaneously) and an additive model system (the sum of HCB and CL is H, the form of the H sub-model equals the sum of the HCB and CL sub-models) from the individual models of H, CL, and HCB. Among the various tree-level and stand-level variables evaluated, D (diameter at breast), Dg (quadratic mean diameter), DT (dominant diameter), CW (crown width), SDI (stand density index), and BAS (basal area of stand) contributed significantly highly to the variations of the response of the variables of interest in the model systems. Modeling results showed the existence of the compatibility and additivity of H, CL, and HCB simultaneously. The additive model system exhibited better fitting performance on H and HCB but poorer fitting on CL compared with the simultaneous model system, indicating that the performance of the additive model system could be higher than that of the simultaneous model system. Model tests against the validation data set also confirmed such results. This study contributes a novel approach to solving the compatibility and additivity of the problems of H, CL, and HCB models through the application of the robust estimating method, NSUR. The results and algorithm presented will be useful for constructing similar compatible and additive model systems of multiple tree-level models for other tree species.

Determination of relationships between leaf area Index and Stand characteristics in anatolian black pine stands of kastamonu region, Türkiye

Background: Leaf area index (LAI) is an important stand characteristic in terms of forest productivity and stand growth, and it shows significant correlations with other stand characteristics. In this study, it is aimed to reveal the relationships between LAI and some other stand characteristics, i.e. mean diameter, stand age, dominant height, site index, number of trees, stand basal area, stand density, total crown biomass and crown dimensions for Anatolian black pine (Pinus nigra J.F. Arnold subsp. pallasiana (Lamb.) Holmboe) stands in Kastamonu region, which is one of the economically important tree species in Türkiye, and to develop a regression model for LAI estimations by using these relationships. Results: The data obtained from 119 temporary sample plots were used in the study. According to the results, stand basal area, stand density, total crown biomass, dominant height, number of trees, mean diameter, and site index positively correlated with LAI. LAI values were significantly different in terms of stand density and site classes. Among the candidate models for LAI estimations, the model containing site index and stand density as independent variables was the most successful model with the adjusted coefficient of determination ( R adj 2 ) of 0,63 and the Akaike information criterion ( AIC) of -67,25. Conclusion: The LAI, which is difficult to measure directly in practice, of Anatolian black pine stands in Kastamonu region of Türkiye could be estimated accurately with the help of the equation developed.

Volume, biomass, carbon sequestration and potential of desert lands’ afforestation irrigated by wastewater on examples of three species

A study was conducted on three species (Khaya senegalensis, Corymbia citriodora and Casuarina equisetifolia) planted in desert lands of Egypt and irrigated with basic treated municipal wastewater. Every single tree is permanently drip irrigated and at the same time fertilised by the nutrient-rich wastewater. Trees of different classes of the diameter at breast height (eight for each species) were felled to determine the form factor and stem volume, as well as the biomass and carbon sequestration of stem, crown and root of the individual trees. In addition, a scenario for the development of un-thinned stands from ages 5 to 35 years was constructed. The age of the sample trees at felling was: 128, 66 and 82 months for K. senegalensis, C. citriodora and C. equisetifolia, respectively. The vigorous sampled trees had a stem volume of 0.289, 0.162 and 0.229 m3 and an aboveground and belowground biomass of 451, 161 and 264 kg for K. senegalensis, C. citriodora and C. equisetifolia, respectively. Results of the scenario showed an unexpectedly high growth rate of afforestation in desert lands using municipal wastewater. At the age of 25, the stem volume for all three species exceeds 398 m3/ha. At the same age of 25 years, K. senegalensis, C. citriodora and C. equisetifolia sequester 1131, 1068 and 860 CO2 t/ha, respectively. Afforestation in desert areas presents a unique situation in forestry, as growth is stimulated by sufficient sunlight, water and nutrients. Competition for water and nutrients is strongly diminished. Self-thinning of stands under such conditions is expected to be much slower than in rain-fed plantation forests. On the other hand, tree maturity span is curtailed. This opens new possibilities for different forest management and practices towards resilient forest-based mitigation of climate change. For its unexpected role as an effective mitigation measure, afforestation in desert lands should be encouraged and further research conducted.

Hydrolysis of pineapple crown biomass by cellulolytic enzymes produced by Fusarium oxysporum

The development of microbial enzymes is of great importance in biochemical process industries. Among the enzymes of industrial importance, cellulolytic and xylanolytic enzymes stand out, which are responsible for the degradation of lignocellulosic material that is usually discarded by the agro-industrial sector. In order to produce the enzymes CMCase, β-glycosidase, xylanase and β-xylosidase, the fungus Fusarium oxysporum was used in liquid fermentation using pre-treated pineapple crown biomass as a carbon source. In order to optimize the production of these enzymes, cultures were carried out for 168 hours, 30 °C at 180 rpm. The biomass underwent a pre-treatment in two stages, the first being submitted to 121 °C for 7 min, while the second was added diluted sulfuric acid to 1%, in the proportion of 1:5 (m/v), at 121 °C for 27 minutes. The partial characterization of the crude extract showed a temperature of 50 ºC as the most satisfactory for the action of these enzymes, and the ideal pH range ranged from 3.5 to 5.5. The enzymatic hydrolysis of pineapple crown, with and without pretreatment, was performed using lyophilized crude extract (CMCase = 9.78 U/mL, β-glucosidase = 10.86 U/mL, xylanase = 27.90 U/mL and β-xylosidase = 0.018 U/ml). An experimental design of the Central Composite Rotational Design was carried out. It was possible to evaluate the effect and influence of pH, biomass concentration and incubation time on the release of glucose in the medium (R2>0.85); pH and biomass (%) had a significant effect on glucose release.

Generic Additive Allometric Models and Biomass Allocation for Two Natural Oak Species in Northeastern China

Current models for oak species could not accurately estimate biomass in northeastern China, since they are usually restricted to Mongolian oak (Quercus mongolica Fisch. ex Ledeb.) on local sites, and specifically, no biomass models are available for Liaodong oak (Quercuswutaishanica Mayr). The goal of this study was, therefore, to develop generic biomass models for both oak species on a large scale and evaluate the biomass allocation patterns within tree components. A total of 159 sample trees consisting of 120 Mongolian oak and 39 Liaodong oak were harvested and measured for wood (inside bark), bark, branch and foliage biomass. To account for the belowground biomass, 53 root systems were excavated following the aboveground harvest. The share of biomass allocated to different components was assessed by calculating the ratios. An aboveground additive system of biomass models and belowground equations were fitted based on predictors considering diameter (D), tree height (H), crown width (CW) and crown length (CL). Model parameters were estimated by jointly fitting the total and the components’ equations using the weighted nonlinear seemingly unrelated regression method. A leave-one-out cross-validation procedure was used to evaluate the predictive ability. The results revealed that stem biomass accounts for about two-thirds of the aboveground biomass. The ratio of wood biomass holds constant and that of branches increases with increasing D, H, CW and CL, while a reverse trend was found for bark and foliage. The root-to-shoot ratio nonlinearly decreased with D, ranging from 1.06 to 0.11. Tree diameter proved to be a good predictor, especially for root biomass. Tree height is more prominent than crown size for improving stem biomass models, yet it puts negative effects on crown biomass models with non-significant coefficients. Crown width could help improve the fitting results of the branch and foliage biomass models. We conclude that the selected generic biomass models for Mongolian oak and Liaodong oak will vigorously promote the accuracy of biomass estimation.

Improving tree biomass models through crown ratio patterns and incomplete data sources

Aboveground biomass quantification is essential for determining carbon stocks in forests. Multiple tree biomass models are available, but estimations can be biased outside the fitting range. This is due to the lack of data for larger trees, mainly because of the cost and time required. This study proposed a methodology based on tree crown biomass ratio (crown biomass: total aboveground biomass) modelling. The original data used in the existing biomass models in Spain have been notably extended by the inclusion of stem data from First Spanish National Forest Inventory and other databases, covering better tree size variability. The analysis of the crown biomass ratio against tree size (d2h), allowed us to distinguish three different patterns: an increasing pattern, a constant one, and a decreasing pattern. A new system of biomass models was fitted simultaneously by species, including a model for crown biomass ratio according to the identified pattern, a stem biomass model, and a total aboveground biomass model. Using this methodology, models were fitted for the 29 most important species in Spain. The fitted models result in more accurate and unbiased predictions for stem biomass, and realistic estimations for the crown biomass. This methodology means more robust and flexible biomass estimations with the possibility of using different data sources. The absence of crown information is not an obstacle because this component is a percentage of total aboveground biomass. Moreover, determining the crown biomass ratio pattern allows improving the accuracy of tree biomass estimation beyond the range of tree sizes (2–70 cm) for which these models were fitted.

HOW TO ESTIMATE BLACK WATTLE ABOVEGROUND BIOMASS FROM HETEROSCEDASTIC DATA?

This study developed a system of equations for predicting total aboveground and component biomass in black wattle trees. A total of 140 black wattle trees at age 10 years were measured regarding their diameter at 1.30 m height above the ground (d), total tree height (h), basic wood density (branches and stem), and biomass (stem, crown, and aboveground). We evaluated the performance of linear and nonlinear allometric models by comparing the statistics of R2adj., RRMSE%, and BIC. Nonlinear models performed better when predicting crown biomass (using only d as an independent variable), and stem and aboveground biomass (using d and h as independent variables). Adding basic density did not significantly improve biomass modeling. The residuals had non-homogeneous variance; thus, the fitted equations were weighted, with weights derived from a function containing the same independent variables of the fitted biomass function. Subsequently, we used a simultaneous set of equations to ensure that the sum of each component's estimated biomass values was equal to the total biomass values. Simultaneous fitting improved the performance of the equations by guaranteeing the components' additivity, and weighted regression allowed to stabilize error variance, ensuring the homoscedasticity of the residuals.

Influence of shade intensity on growth, biomass allocation, yield and quality of pineapple in mango-based intercropping system

Fruit tree-based intercropping system is commonly practiced in India; however, optimization of light environment for intercrops is essentially required to enhance their productivity. Influence of three shade intensities were examined on growth, biomass allocation pattern, leaf chlorophyll content, nutrient uptake, fruit yield and quality of pineapple in mango-based intercropping system. Compared to the monoculture pineapple system (LE0), the mean shade intensity under LE1, LE2 and LE3 were 23.8 %, 48.6 % and 73.3 %, respectively, whereas the mean PAR availability was 76.2 %, 51.4 % and 26.7 %, respectively. Significantly higher absolute growth rate (AGR), crop growth rate (CGR) and relative growth rate (RGR) was recorded under medium shade intensity (LE2). Dry matter accumulation was significantly high under LE2 followed by LE3. The biomass accumulation was significantly high in leaf followed by fruit and stem, whereas root system exhibited minimum biomass accumulation. Biomass of leaf and crown decreased with the plant biomass, whereas the biomass of fruit, stem and sucker increased. Contents of Chl a, Chl b and Chl a + b increased with the shade intensity and were found maximum under LE3. A gradual increase in N and P contents were observed in the leaves of pineapple with the reduction in PAR transmittance. However, the K content was relatively high under LE2. Increased fruit yield, fruit weight and fruit/crown ratio were recorded under moderate shade intensity (LE2). Total soluble solids and sugar content marginally decreased with the reduction in light intensity, whereas titratable acidity increased. Sunburn intensity significantly reduced under LE2 and LE3. Path analysis studies indicated that plant biomass was that most important predictor for fruit yield in pineapple. Our findings demonstrate that in eastern tropical region of India pineapple may be cultivated as an intercrop with ∼50 % shade intensity since the performance of crop is significantly affected under monoculture system.

Are There Differences in the Reaction of the Light-Tolerant Subgenus Pinus spp. Biomass to Climate Change as Compared to Light-Intolerant Genus Picea spp.?

Currently, the problem of the impact of climate change on the productivity of forest ecosystems and their carbon-depositing capacity is far from being solved. Therefore, this paper presents the models for the stand biomass of the two-needled subgenus’ (Pinus spp.) and the genus Picea spp.’s trends along the trans-Eurasian hydrothermal gradients, designed for pure stands in a number of 2110- and 870-sample plots with Pinus and Picea correspondingly. It was found that in the case of an increase in mean winter temperatures by 1 °C, pine and spruce respond by increasing the biomass of most components, and in the case of an increase in the annual sum of precipitation by 100 mm, the total, aboveground, stem and root biomasses of pine and spruce react the same way, but crown biomass reacts in the opposite way. Therefore, all identified trends are species-specific.

Allometric equations coupled with remotely sensed variables to estimate carbon stocks in date palms

This study aims at developing specific allometric biomass equations that can be integrated into a remote sensing (RS) based model for assessing carbon sequestered in date palms. Assessing the potential of date palms to improve soil carbon sequestration was another objective. In a previous study, the authors demonstrated that combinations of visible and short wave single bands (Red, SWIR1, SWIR2) besides vegetation indices (DVI, NDI and RVI) derived from Landsat imagery correlated significantly with date palms’ biomass. Here and based on field and lab work, relevant structural variables were identified and used in the development of allometric equations. Results showed that the crown area (CA) best estimated both crown biomass (CB) and soil organic carbon (SOC). Likewise, the trunk height (Ht) was the best estimator of trunk biomass (TB). Using these variables, allometric equations were developed for date palms at different age stages and were used to estimate CB, TB and SOC with coefficients of determination (R2) of: 0.884, 0.835 and 0.952, respectively. Furthermore, the average ratios of below ground biomass (BGB) to above ground biomass (AGB) varied with palm maturity stages averaging 0.332, 0.925 and 0.496 for young, medium and mature palms, respectively. Moreover, the present study demonstrated that the amounts of organic carbon (OC) stored in date palms were considerable with values of: 15.88 kg/palm for young, 96.62 kg/palm for medium, and 225.58 kg/palm for mature palms. Substantially higher amounts of SOC were measured compared to other local plants with values of: 18.092 kg/palm, 62.594 kg/palm, and 92.908 kg/palm under young, medium and mature palms, respectively. The main achievement of the current study was the development of new and unprecedented allometric equations for date palm species in arid land. Such equations allow the development and calibration of a RS-based model for estimating biomass and Carbon Sequestration (CS) of date palms in the region with high accuracy.

Allometric Biomass Model for Aquilaria Malaccensis Lam. in Bangladesh: A Nondestructive Approach

ABSTRACT Aquilaria malaccensis: Lam. is an important commercial tree species of Bangladesh. This species is widely planted for the increased demand for an essential oil locally knows as “Agar”. A nondestructive method was adopted to derive the allometric biomass model for A. malaccensis. Stem volume of 254 trees and the model of biomass expansion factor (BEF) were used to estimate the total above-ground biomass (TAGB). A total of five allometric equations with natural logarithm were tested to derive best-fit biomass models for crown, stem, and total above-ground biomass (TAGB). The best-fit allometric model was selected based on the lowest value of akaike information criteria (AIC), residual standard error (RSE), and the highest value of the coefficient of determination (R2) and akaike information criteria weighted (AICw). The best-fit model of BEF was BEF = exp(2.112318 – (DBH*TH)^0.1066121). The best-fit allometric biomass models for crown, stem and TAGB were crown biomass = exp(−0.6031 + 0.4279*Ln(DBH^2*TH), steam biomass = exp(−3.2483 + 1.7910*Ln(DBH) + 0.7881*Ln(TH) and TAGB = exp(−1.9121 + 1.5937*Ln(DBH) + 0.6152*Ln(TH). The best-fit TAGB model showed the highest efficiency in biomass estimation compared to commonly used pan-tropical biomass models in terms of model prediction error (MPE), model efficiency (ME).

Long-term dynamics of loblolly pine crown structure and aboveground net primary production as affected by site quality, planting density and cultural intensity

Crown attributes respond readily to silvicultural manipulations and mediate many aspects of stand structure, consequently they dynamically influence stand production. Numerous studies reported crown structure responses to intensive cultures or stand density and the relation between foliage quantity and growth efficiency at early stages of stand development. Long-term temporal patterns of crown structure and its relation to growth have been much less studied. With long-term remeasurement data from two loblolly pine culture-by-density studies, the roles of planting density, cultural intensity and site quality on crown structure, stand aboveground net primary production (ANPP), and growth efficiency were investigated using ANCOVA and linear mixed-effects modeling approaches. Using data from 480 destructively sampled trees, the Dirichlet regression modeling approach was used to analyze foliage and crown biomass allocations among the lower-, middle- and upper-third crown sections. Stands under different cultural intensities showed different temporal patterns of foliage biomass. Increased planting density or higher site quality enhanced wood production of loblolly pine. ANPP generally increased with increasing site quality, due to increased stand foliage biomass in the early stage of stand development, and mainly due to increased growth efficiency in the late stages of stand development. More intensive cultural treatments increased foliage biomass, thus increased ANPP at early ages; thereafter cultural intensity did not affect foliage biomass, ANPP, and growth efficiency. The trend of early age increases in both foliage biomass and ANPP resulting from increased planting density did not hold true with stand development. After correcting for the effects of tree size and dominance, cultural intensity still altered the vertical distribution of foliage biomass. More intensive culture resulted in an upward shift of foliage biomass.