Crown Volume Research Articles

Decoupling of Tree‐Ring Cellulose δ18O and δ2H Highlighted by Their Contrasting Relationships to Climate and Tree Intrinsic Variables

ABSTRACTOxygen (δ18O) and hydrogen (δ2H) stable isotope ratios are tightly coupled in precipitation and, albeit damped, in leaf water, but are often decoupled in tree‐ring cellulose. The environmental and physiological conditions in which this decoupling occurs are not yet well understood. We investigated the relationships between δ18O and δ2H and tree‐ring width (TRW), tree crown volume, tree age and climate in silver fir and Douglas‐fir and found substantial differences between δ18O and δ2H. Overall, δ18O–δ2H correlations were weak to absent but became significantly negative under high summer vapour pressure deficit (VPD). δ18O and δ2H had positive and negative nonlinear relationships with TRW, respectively, with clear relationships at the site and tree levels for silver fir and, to a lesser extent, for Douglas‐fir. Age trends for silver fir were weakly negative in δ18O but positive in δ2H. Tree crown volume and δ18O or δ2H had no significant relationships. Most strikingly, δ18O strongly depended on spring climate (precipitation and VPD), whereas δ2H depended on summer climate (temperature and VPD) for both species. Our study shows that the δ18O–δ2H decoupling in tree‐ring cellulose in two temperate conifer species could be highlighted by their contrasting relationships to climate and tree intrinsic variables (TRW, age).

Comparative study of five scab resistant apple cultivars

Vegetative and reproductive characteristics of five resistant apple cultivars budded on ‘М9-Т337’ rootstock were compared in the intensive orchard, planted at the density of 2380 trees per hectare (3.5 × 1.2 m) in the period 2017-2023. Trees were formed as tall spindle, under an insecticidal net against hail. Trees were grown under drip irrigation and sod-mulch system was applied. The cultivars FUJIONpbr and ENTERPRISE demonstrate greater trunk-cross section area, higher trees and greater crown volume to the tested cultivars. The smallest trees were noted in Cultivar GEMINI*. The lowest yield per unit area was obtained on cultivar FUJIONpbr. There was no significant difference among other cultivars. Despite of generally good characteristics the cultivar GEMINI* has relatively small fruits. Keywords: apple, vigor, productivity, fruit weight, yield

Enhancing outdoor comfort in urban hot climates: investigating the cooling impact of two tropical trees through shade provision and transpiration

ABSTRACT One key ecosystem service widely known and attributed to trees in the urban environment is their ability to provide shade through their canopies and undertake evapotranspiration cooling. These in turn contribute to reduced atmospheric temperatures. A lesser-known aspect with little quantitative data is the heterogeneous temperature environment beneath the canopies at pedestrian or street level where the cooling will benefit thermal comfort. This study was conducted throughout 2022. It collected data where air temperature was measured under the canopies of two urban tropical tree species, Samanea saman and Peltophotum pterocarpum, at three different heights, which were 1, 3 and 5 m, respectively, from the ground. This was to investigate whether crown architectures and the associated shade and cooling effects via transpiration can have a significant change in the surrounding temperature. The study observed surface and air temperatures coupled with meteorological data across cool, warm, and hot periods of the year. It was observed that soil temperature increased alongside increases in atmospheric temperatures with a more significant rise observed for P. pterocarpum despite the observation of greater wind speeds for both night and day at the site where this species was situated. The soil moisture potential data indicated the reverse where S. saman showed more negative values with the greatest increase under warm conditions. Interestingly, sap flow rates also indicated that P. pterocarpum had more efficient rates whether conditions were cool, warm, or hot, suggestive of more active transpirational cooling. This was despite a lower leaf area index, smaller crown volume and sap wood area for this species. Relationship analyses between sap flow and air temperatures at different heights under the canopies showed a positive correlation. This demonstrates that apart from shade provided by the canopies, transpiration is also an important parameter for cooling. The mean daytime air temperature indicated that the greatest cooling effect was experienced at the lowest level from the ground (at 1 m), and this was consistent for both species across cool, warm, and hot conditions with a significant cooling effect of between 2.3 and 4°C. Temperature data under the canopy (1 to 5 m from the ground) compared to the air temperature of the grass that was shaded indicated temperature differences of between 2.3 and 7.9°C at 5 m and between 1.9 and 5.6°C at 1 m (for both species) with a bigger reduction attributed to S. saman.

Aboveground woody biomass estimation of young bioenergy plantations of Populus and its hybrids using mobile (backpack) LiDAR remote sensing

Woody aboveground biomass (AGB) including short-rotation Populus is used as a feedstock for renewable and carbon-neutral bioenergy. While woody AGB can be estimated with allometric equations requiring labor-intensive field data, remote sensing technologies like mobile terrestrial light detection and ranging (LiDAR) can estimate woody AGB quickly and accurately. Therefore, the goals of this study were to develop a model to predict woody AGB of 2-year-old Populus spp. from three taxa (P. deltoides, P. deltoides × P. maximowiczii and P. deltoides × P. trichocarpa) using allometric (height and diameter at breast height (DBH)) or LiDAR-derived metrics from a mobile terrestrial (backpack) system. Likewise, we sought to compare LiDAR-estimated tree height and DBH with field-measured values. We found that a taxa-specific model containing LiDAR-measured tree height, crown volume, and taxa interactions with the height of the 10th percentile, and the density of the lowest interval (density metric 0) explained 84 % of the variation in woody AGB with a root mean square error (RMSE) of 28.7 % and performed slightly better than the allometric model. The best model excluding taxa had a slightly higher RMSE but lower bias than the allometric model. LiDAR-derived tree heights were highly correlated with field-measured heights, but DBH could not be estimated accurately. Therefore, terrestrial mobile LiDAR systems can accurately estimate woody AGB and tree height of Populus in short rotation systems to aid in the fast and efficient quantification of woody bioenergy production and renewable energy resources.

YOLOTree-Individual Tree Spatial Positioning and Crown Volume Calculation Using UAV-RGB Imagery and LiDAR Data

Individual tree canopy extraction plays an important role in downstream studies such as plant phenotyping, panoptic segmentation and growth monitoring. Canopy volume calculation is an essential part of these studies. However, existing volume calculation methods based on LiDAR or based on UAV-RGB imagery cannot balance accuracy and real-time performance. Thus, we propose a two-step individual tree volumetric modeling method: first, we use RGB remote sensing images to obtain the crown volume information, and then we use spatially aligned point cloud data to obtain the height information to automate the calculation of the crown volume. After introducing the point cloud information, our method outperforms the RGB image-only based method in 62.5% of the volumetric accuracy. The AbsoluteError of tree crown volume is decreased by 8.304. Compared with the traditional 2.5D volume calculation method using cloud point data only, the proposed method is decreased by 93.306. Our method also achieves fast extraction of vegetation over a large area. Moreover, the proposed YOLOTree model is more comprehensive than the existing YOLO series in tree detection, with 0.81% improvement in precision, and ranks second in the whole series for mAP50-95 metrics. We sample and open-source the TreeLD dataset to contribute to research migration.

Point cloud-based crown volume improves tree biomass estimation: Evaluating different crown volume extraction algorithms

Accurately estimating aboveground biomass (AGB) is increasingly crucial for a better understanding of terrestrial ecosystem carbon balance and its relationship with global climate change. Terrestrial laser scanning (TLS) enables detailed reconstruction of tree crown three-dimensional structures, such as tree crown volume (CV), which has been proven to have a strong correlation with AGB. In this study, a coupled algorithm framework for extracting “optimal biomass” CV to improve AGB estimation using allometric models is proposed. The coupled algorithm framework was compared with commonly used tree CV extraction algorithms (model prediction, convex hull, alpha-shape, and voxel) based on point cloud data from 19 artificial Korean pine plots. The results reveal that the alpha-shape coupled with the voxel algorithm provides the closest approximation to the “optimal biomass” CV, exhibiting the highest correlation with AGB (r = 0.7905). α values and voxel size significantly influence the accuracy of CV extraction, while small variations in point cloud density have minimal impact on the extracted CV. Furthermore, the explanatory power of the “optimal biomass” CV for tree AGB was tested using 30 destructively harvested sampled trees. It was observed that the allometric model incorporating both “optimal biomass” volume and DBH (R2 = 0.966, RMSE = 15.321 kg) outperformed the allometric model incorporating both H and DBH (R2 = 0.953, RMSE = 16.131 kg) and the DBH-only model (R2 = 0.948, RMSE = 16.615 kg), particularly in reducing underestimation of AGB for larger trees. These findings demonstrate that the proposed alpha-shape coupled with the voxel algorithm provides an effective solution for extracting “optimal biomass” CV, significantly improving the accuracy of tree-level AGB estimation.

Assessing Normalized Difference Vegetation Index as a proxy of urban greenspace exposure

The Normalized Difference Vegetation Index (NDVI) is a popular proxy of urban greenspace (UGS). However, it’s unclear how NDVI approximates physical characteristics of UGS in the context of urban health studies, causing ambiguities in translating research findings to UGS management. Therefore, we collected data from Landsat and MODIS satellites and Lidar 3D scans in New York City as of circa 2013, and we evaluated linear and non-linear relationships between NDVI and UGS characteristics. We found that: (1) % UGS was the best predicted UGS characteristic by NDVI (R2: 0.35–0.90, varies by data source and unit of analysis), whereas average tree height was the worst (R2: 0.09–0.46). The predictive power on % canopy cover, tree density, and crown volume density was in a similar range (R2: 0.10–0.67). Prediction improved with finer-resolution NDVI sources and larger units of analysis at the cost of losing useful variations; (2) There was a saturation effect where a linear relationship underestimated UGS characteristics in areas of high NDVI. These areas typically had NAIP-NDVI greater than the range of 0.08–0.25, Landsat-NDVI greater than the range of 0.42–0.65, and MODIS-NDVI greater than the range of 0.49–0.75; (3) Smaller absolute errors from a linear NDVI-UGS relationship were often found in more developed locations. We therefore recommend NDVI as a reliable predictor of UGS coverage and its use in longitudinal studies. Future studies should also consider fine resolution land cover maps and Lidar, which are increasingly available to derive detailed UGS characteristics.

Evaluating airborne, mobile and terrestrial laser scanning for urban tree inventories: A case study in Ghent, Belgium

In urban tree inventories, structural measurements such as diameter at breast height (DBH), tree height (H), crown projection area (CPA) and crown volume (CV) are essential for diverse applications, including accurate ecosystem service estimation and management decisions. Traditionally, tree measurements are obtained using range finders and diameter tape. These measurements can be integrated into urban tree inventories through 3D laser scanning (also known as LiDAR). Multiple platforms for laser scanning exist, each with its own advantages and disadvantages, which have not yet been compared explicitly for urban tree inventories. We collected terrestrial laser scanning (TLS), mobile laser scanning (MLS) and airborne laser scanning (ALS) in leaf-on (TLS, MLS, ALS) and leaf-off conditions (TLS, MLS) in Ghent, Belgium. We evaluated the DBH, H, CPA and CV of 95 individual trees acquired from each acquisition platform, benchmarking against TLS. Our results show accurate DBH derivation from both TLS and MLS (bias < 2 cm, concordance correlation coefficient (CCC) ≈ 1). However, during leaf-on conditions, occlusion from shrubs and ivy is observed. For leaf-on MLS, point clouds of large trees exhibited occlusion in the top canopy, impacting crown volume (CV MLS leaf-on: bias = −116 m², CCC=0.85) and, to a lesser extent, tree height (H MLS leaf-on: bias = −0.38 m, CCC=0.99). Crown projected area was less affected (bias = 0.49 m², CCC=0.99), with differences more attributed to varying point precision among sensors. The difference between the metric and benchmark increased with tree size and the structural complexity of the surroundings (e.g. buildings), especially for MLS, for which limited GNSS coverage, traffic, and suboptimal walking patterns impeded ideal data collection. Our results will help city councils and tree managers choose the most optimal LiDAR platform for urban tree inventories, accounting for their purpose, site complexity and budget.

Common field measures and geometric assumptions of tree shape produce consistently biased estimates of tree and canopy structure in mixed Mediterranean forests

Crown shape and canopy structure are crucial determinants of tree and forest performance, and forest-climate interactions, but methods of quantifying these from field measurements are based on untested assumptions. Historically, measurements of crown size, shape and interactions have been limited to what can be quantified using simple tools such as a tape measure or clinometer, which are then combined with simple geometric assumptions to calculate metrics including crown area, crown volume and canopy cover and overlap. Terrestrial Laser Scanning (TLS) captures the three-dimensional structure of trees and can derive such metrics directly, bypassing the need for geometric assumptions. Here we use TLS data from c. 2500 trees in mixed Mediterranean forests to present a first test of the validity of common assumptions of tree shape. We simulate field measurements from TLS, use these to estimate crown and canopy properties based on geometric assumptions and compare with direct TLS estimates. We find that commonly used methods produce consistently biased estimates of individual tree crown area and crown volume, and whole-plot crown projected area and crown overlap. Although TLS is often not the practical choice for forest measurement, we show that it can guide best practice and here present recommendations of ground measurements that minimise errors.

Dynamic Analysis of Street Trees in Vehicle-mounted LiDAR Point Clouds

Street trees, as key elements of urban road scenes, play a significant role in the overall ecological environment and aesthetics of city roads through their dynamic growth and changes. With the continuous development of urban roads, the growth conditions of street trees are also constantly changing. Therefore, studying how to infer the dynamic changes of roads through the variations in street trees is a highly valuable technical issue. This paper delves into several critical parameters of street trees, including diameter at breast height (DBH), tree height, trunk height, crown volume, and crown spread. By updating these parameters, determining transplantation and replanting decisions, and analyzing growth states, we comprehensively analyze the dynamic changes of street trees. To achieve this goal, we integrated multiple parameters into the analysis process of street trees and established a comprehensive analysis system centered on the DBH parameter. Combining this with data visualization technology, we provide an intuitive dynamic analysis method. Experimental results indicate that, compared to single-parameter analysis methods, the multi-parameter comprehensive analysis method demonstrates higher accuracy and stronger persuasive power in the study of dynamic changes in street trees, thereby validating the superiority and practicality of the proposed research algorithm. This research can provide more scientific and reliable references for urban road planning and management.

Spectral-temporal traits in Sentinel-1 C-band SAR and Sentinel-2 multispectral remote sensing time series for 61 tree species in Central Europe

Tree species maps derived from satellite imagery increasingly support forest administrations and nature conservation authorities with large-scale and up-to-date information. However, many species are often excluded or aggregated in classification tasks due to a limited knowledge of the most suitable predictors. Our study aims to gain a better understanding of optical and polarimetric traits for tree species mapping by examining Sentinel-1 and Sentinel-2 time series from 61 tree species in temperate Europe. For a selection of 32 optical, polarimetric and structural variables, the principal component analysis revealed that Sentinel-2 variables mainly explain the variance in the data by contributing to the “seasonality” and “foliage color” components. Sentinel-1 contribute most to the “texture” component. The Normalized Difference Vegetation Index (NDVI), Tasseled Cap Greenness (TCG) and Radar Vegetation Index (RVI) were chosen as key variables for further analysis. Seasonality was found to be the most dominant aspect in all vegetation indices. Furthermore, the TCG was found to be useful to distinguish between early and late budding species. The RVI showed a large potential to discriminate conifers, which is attributed to the crown volume effect of C-band SAR. Using exploratory data analysis, we further examined the influence of management, biogeographical and meteorological factors on the time series from Fagus sylvatica, Pinus sylvestris, and Picea abies. The NDVI and TCG are relatively robust to different conditions. For the two conifer species however, we found strong spatial variations of the RVI which are presumably caused by different crown conditions across the study area. Using Sentinel-1 data could therefore lead to uncertainties in tree species mapping across large biogeographical gradients. This study contributes to the improvement of tree species mapping based on optical and dual-polarimetric data and thus benefits forest authorities and other stakeholders in their monitoring tasks and decision-making.

Comparison of Crown Volume Increment in Street Trees among Six Cities in Western Countries and China

The tree crown volume (CV), as a major indicator in the evaluation of ecological environment quality, can assess the health and carbon sequestration of urban trees. In this study, a new low-cost method, the plane calculation of angle disparity (PCAD), was employed to obtain the CV in China using satellite images from Google Earth. Meanwhile, primary data on street trees from four Western cities were acquired from online datasets. Nonparametric statistical methods showed no significant difference in CV per street tree between Beijing and Shanghai in China, ranging from 10 to 150 m3, almost one-seventh of that in the four cities (Paris and London in Europe and Los Angeles and Seattle in America). The CV of Platanus acerifolia in Paris and London exhibited values five times higher than those in Beijing and Shanghai. The annual crown volume increment (CVI) was less than 5 m3 in Beijing and Shanghai, significantly lower than in Seattle (66.55 m3). The purpose of the research was to verify the operability of the PCAD and compare the CVI in different cities all over the world, providing new ideas for urban tree management and carbon sequestration evaluation and a basis for government decision making in areas with a low CVI.

Peculiarities of bacteriosis development in agrocenosis of pome fruit orchards

Goal. Was to determine ssources of bacterium diseases of pome fruits in agrocenoses and their seasonal development study and factors, which impacts on plants defeating level.&#x0D; Methods. Field (route, selective and continuous studies) and laboratory (extracting pure bacterium cultures, determining pathogenicity, identifying through the sum of morpho-cultural and their physiological and biochemical features).&#x0D; Results. There were determined the defeating peculiarities of pome fruits by bacteriosis defeating on pome fruits during the investigation in 2011—2015 and 2021—2023. Their causative agents was conformed by bacterium extraction from plant material. The most intensive bacterial necrosis happened in spring, during the period of juice intensive movement, when the tree is the most favorable to defeating. The defeating observed only on some shoots in summer (to 5% from the volume of tree crown), but the cancer development continued on the trunk’s bark. The first symptoms of fire blight observed during blossoming and at the beginning of fruit setting. The full picture opened during the shoots’ active growth. The shoots` defeating level was in the scope of 3—12% and only on some trees reached 15—18%. The fire blight strong defeat (to 55% of crown tree) observed in 2015 through the mass propagation pear-tree psylla. New fire blight sources were not identified in Chernivtsi region in 2021—2023.There were only presence of bacterial necrosis causative agent.&#x0D; Conclusions. The bacteriosis defeating determined and researched in plantations Chernivtsi and Vinnytsia regions. The highest fire blight defeating level (to 55% of crown) connected with mass propagations of pear-tree psylla. It is the main pathogen carrier. The bacterium necroses defeating depends upon the weather conditions of weather period and following the necessary level of agrotechnical measures. The investigation scheme for pome fruits bacteriosis determined developed with phenological phases terms considerations and periods of the most plants susceptibility to phytopathogens defeating.

Automated forest inventory: Analysis of high-density airborne LiDAR point clouds with 3D deep learning

Detailed forest inventories are critical for sustainable and flexible management of forest resources, to conserve various ecosystem services. Modern airborne laser scanners deliver high-density point clouds with great potential for fine-scale forest inventory and analysis, but automatically partitioning those point clouds into meaningful entities like individual trees or tree components remains a challenge. The present study aims to fill this gap and introduces a deep learning framework, termed ForAINet, that is able to perform such a segmentation across diverse forest types and geographic regions. From the segmented data, we then derive relevant biophysical parameters of individual trees as well as stands. The system has been tested on FOR-Instance, a dataset of point clouds that have been acquired in five different countries using surveying drones. The segmentation back-end achieves over 85% F-score for individual trees, respectively over 73% mean IoU across five semantic categories: ground, low vegetation, stems, live branches and dead branches. Building on the segmentation results our pipeline then densely calculates biophysical features of each individual tree (height, crown diameter, crown volume, DBH, and location) and properties per stand (digital terrain model and stand density). Especially crown-related features are in most cases retrieved with high accuracy, whereas the estimates for DBH and location are less reliable, due to the airborne scanning setup.

Forest thinning and prescribed burning treatments reduce wildfire severity and buffer the impacts of severe fire weather

BackgroundThe capacity of forest fuel treatments to moderate the behavior and severity of subsequent wildfires depends on weather and fuel conditions at the time of burning. However, in-depth evaluations of how treatments perform are limited because encounters between wildfires and areas with extensive pre-fire data are rare. Here, we took advantage of a 1200-ha randomized and replicated experiment that burned almost entirely in a subsequent wildfire under a wide range of weather conditions. We compared the impacts of four fuel treatments on fire severity, including two thin-only, a thin-burn, a burn-only, and an untreated control. We evaluated four fire severity metrics—tree mortality, average bole char height, percent crown volume consumed (PCVC), and percent crown volume affected (PCVA)—and leveraged data from pre-fire surface and canopy fuels to better understand the mechanisms driving differences in wildfire severity among treatments and how they changed with fire weather.ResultsWe found strong mitigating effects of treatments on fire behavior and tree mortality, despite 20 years having elapsed since mechanical thinning and 10 years since the second entry of prescribed fire. The thin-burn treatment resulted in the lowest fire severity across all four metrics and the untreated control the highest. All four fire severity metrics were positively associated with pre-fire canopy and surface fuel loads, with the exception that PCVC (a fire severity metric related to crown fire behavior) was not associated with surface fuel load. The fire weather conditions under which fuel treatment was most effective varied among fire severity metrics. Fuel treatment benefit was maximized at intermediate burning index values for tree mortality, intermediate to high burning index values for PCVA, and high burning index for bole char height and PCVC.ConclusionsWe conclude that reducing canopy bulk density via mechanical thinning treatments can help to limit crown fire behavior for 20 years or more. However, reducing surface fuels is necessary to limit scorching and the total crown impacts associated with tree mortality. Further, while fuel treatment effectiveness may decline under the most severe fire weather conditions for fire severity metrics associated with tree mortality, it is maximized under severe fire weather conditions for fire severity metrics associated with crown fire behavior (bole charring and torching). Our results provide strong evidence for the use of fuel treatments to mitigate fire behavior and resulting fire severity even under extreme fire weather conditions.

Enigmatic fossil plants with three-dimensional, arborescent-growth architecture from the earliest Carboniferous of New Brunswick, Canada

The evolution of arborescence in Devonian plants, followed by their architectural radiation in the Carboniferous, is a transition fundamental to Earth-system processes and ecological development. However, this evolutionary transition in trees is based on preserved trunks, of which only a few known specimens possess crowns. We describe Mississippian-aged (Tournaisian) trees with a unique three-dimensional crown morphology from New Brunswick, Canada. The trees were preserved by earthquake-induced, catastrophic burial of lake-margin vegetation. The tree architecture consists of an unbranched, 16-cm-diameter trunk with compound leaves arranged in spirals of ∼13 and compressed into ∼14cm of vertical trunk length. Compound leaves in the upper ∼0.75m of the trunk measure >1.75m in length and preserve alternately arranged secondary laterals beginning at 0.5m from the trunk; the area below the trunk bears only persistent leaf bases. The principal specimen lacks either apical or basal sections, although an apex is preserved in another. Apically, the leaves become less relaxed toward horizontal and are borne straight at an acute angle at the crown. The compact leaf organization and leaf length created a crown volume of >20-30 m3. This growth strategy likely maximized light interception and reduced resource competition from groundcover. From their growth morphology, canopy size, and volume, we propose that these fossils represent the earliest evidence of arborescent subcanopy-tiering. Moreover, although systematically unresolved, this specimen shows that Early Carboniferous vegetation was more complex than realized, signaling that it was a time of experimental, possibly transitional and varied, growth architectures.

An Open Benchmark Dataset for Forest Characterization from Sentinel-1 and -2 Time Series

Earth observation satellites offer vast opportunities for quantifying landscapes and regional land cover composition and changes. The integration of artificial intelligence in remote sensing is essential for monitoring significant land cover types like forests, demanding a substantial volume of labeled data for effective AI model development and validation. The Wald5Dplus project introduces a distinctive open benchmark dataset for mid-European forests, labeling Sentinel-1/2 time series using data from airborne laser scanning and multi-spectral imagery. The freely accessible satellite images are fused in polarimetric, spectral, and temporal domains, resulting in analysis-ready data cubes with 512 channels per year on a 10 m UTM grid. The dataset encompasses labels, including tree count, crown area, tree types (deciduous, coniferous, dead), mean crown volume, base height, tree height, and forested area proportion per pixel. The labels are based on an individual tree characterization from high-resolution airborne LiDAR data using a specialized segmentation algorithm. Covering three test sites (Bavarian Forest National Park, Steigerwald, and Kranzberg Forest) and encompassing around six million trees, it generates over two million labeled samples. Comprehensive validation, including metrics like mean absolute error, median deviation, and standard deviation, in the random forest regression confirms the high quality of this dataset, which is made freely available.

ПОДБОР ПОДВОЕВ ПРИ СОЗДАНИИ МАТОЧНО-ЧЕРЕНКОВЫХ НАСАЖДЕНИЙ ЯБЛОНИ КАТЕГОРИИ «БАЗИСНЫЕ»

The increase in high-temperature stress in recent years during the summer growing season complicates the realization of the production potential of the apple tree. Therefore, it is very relevant to use scion-rootstock combinations based on rootstocks with high drought resistance in creation mother-cutting orchards of apple trees in the “Basic” category. In the conditions of Krasnodar, the summer months of 2018-2023 became hotter, which is confirmed by data on the excess of the average monthly temperature over long-term values. July was the hottest in 2018, 2020 and 2021. (38.0, 38.0 and 36.3 ºC, respectively). In August, the excess of the long-term norm was greatest in 2018, 2021 and 2023. The trend of increasing temperatures in the autumn months has led to a lengthening of the growing season and a decrease in the resistance of apple plants to unfavorable overwintering conditions, which can negatively affect the quality of cuttings. The purpose of the research was to identify the most adaptive apple tree rootstocks for use in mother-cutting plantings of the «Basic» category. We assessed the drought resistance of the most common introduced apple rootstocks M 9, MM-106 and the rootstock breed by FSBSI NCFSCHVW SK 2U under conditions of high-temperature stress during the summer growing season. Leaf water content in particularly hot years (2020, 2021, 2023) was predominantly higher in the M 9 and SK 2U rootstocks. The best water-holding capacity of leaves was observed in the rootstocks M 9 and SK 2U, the worst – in the rootstock MM-106. Preference should be given to the semi-dwarf rootstock SK 2U when designing mother-cutting apple tree plantings of the “Basic” category. SK 2u will be able to maintain the intensity of growth processes and ensure the production of cuttings of a standard size and the required quality in greater quantities under conditions of summer high-temperature stress than mother trees on a dwarf rootstock M 9 with a smaller crown volume than on SK 2U.

Fine-Scale Quantification of Absorbed Photosynthetically Active Radiation (APAR) in Plantation Forests with 3D Radiative Transfer Modeling and LiDAR Data.

Quantifying the relationship between light and stands or individual trees is of great significance in understanding tree competition, improving forest productivity, and comprehending ecological processes. However, accurately depicting the spatiotemporal variability of light under complex forest structural conditions poses a challenge, especially for precise forest management decisions that require a quantitative study of the relationship between fine-scale individual tree structure and light. 3D RTMs (3-dimensional radiative transfer models), which accurately characterize the interaction between solar radiation and detailed forest scenes, provide a reliable means for depicting such relationships. This study employs a 3D RTM and LiDAR (light detection and ranging) data to characterize the light environment of larch plantations at a fine spatiotemporal scale, further investigating the relationship between absorbed photosynthetically active radiation (APAR) and forest structures. The impact of specific tree structural parameters, such as crown diameter, crown area, crown length, crown ratio, crown volume, tree height, leaf area index, and a distance parameter assessing tree competition, on the daily-scale cumulative APAR per tree was investigated using a partial least squares regression (PLSR) model. Furthermore, variable importance in projection (VIP) was also calculated from the PLSR. The results indicate that among the individual tree structure parameters, crown volume is the most important one in explaining individual tree APAR (VIP = 4.19), while the competition from surrounding trees still plays a role in explaining individual tree APAR to some extent (VIP = 0.15), and crown ratio contributes the least (VIP = 0.03). Regarding the spatial distribution of trees, the average cumulative APAR per tree of larch plots does not increase with an increase in canopy gap fraction. Tree density and average cumulative APAR per tree were fitted using a natural exponential equation, with a coefficient of determination (R2 = 0.89), and a small mean absolute percentage error (MAPE = 0.03). This study demonstrates the potential of combining 3D RTM with LiDAR data to quantify fine-scale APAR in plantations, providing insights for optimizing forest structure, enhancing forest quality, and implementing precise forest management practices, such as selective breeding for superior tree species.

Evaluating the Influence of Row Orientation and Crown Morphology on Growth of Pinus taeda L. with Drone-Based Airborne Laser Scanning.

The tree crown's directionality of growth may be an indicator of how aggressive the tree is in terms of foraging for light. Airborne drone laser scanning (DLS) has been used to accurately classify individual tree crowns (ITCs) and derive size metrics related to the crown. We compare ITCs among 6 genotypes exhibiting different crown architectures in managed loblolly pine (Pinus taeda L.) in the United States. DLS data are classified into ITC objects, and we present novel methods to calculate ITC shape metrics. Tree stems are located using (a) model-based clustering and (b) weighting cluster-based size. We generated ITC shape metrics using 3-dimensional (3D) alphashapes in 2 DLS acquisitions of the same location, 4 years apart. Crown horizontal distance from the stem was estimated at multiple heights, in addition to calculating 3D volume in specific azimuths. Crown morphologies varied significantly (P < 0.05) spatially, temporally, and among the 6 genotypes. Most genotypes exhibited larger crown volumes facing south (150° to 173°). We found that crown asymmetries were consistent with (a) the direction of solar radiation, (b) the spatial arrangement and proximity of the neighboring crowns, and (c) genotype. Larger crowns were consistent with larger increases in stem volume, but that increases in the southern portions of crown volume were consistent with larger stem volume increases, than in the north. This finding suggests that row orientation could influence stem growth rates in plantations, particularly impacting earlier development. These differences can potentially reduce over time, especially if stands are not thinned in a timely manner once canopy growing space has diminished.