Tree Height Research Articles

A Case Study on Biomass Assessment in a Semi-Arid Olive Rainfed System in Morocco

Thanks to its potential life span of hundreds of years, olive can develop great biomass and sequester large amounts of carbon (C). It may therefore play a critical role in reducing atmospheric C and improving farmer livelihoods by providing additional revenue from C credits. Predicting olive’s impacts on C cycling relies on allometric models. In our specific conditions, such models reliably predicted biomass accumulation with a minimum of three dendrometric measurements: tree age, height, and diameter at 10 cm.

Determinants of carbon sequestration in thinned forests

Given global climate change and the projected increases in the greenhouse effect, enhancing the carbon storage capacity of forest ecosystems is especially critical. To fully realize the potential carbon sequestration, it is imperative to understand the drivers affecting carbon storage in forest ecosystems, particularly with disturbances that disrupt existing balance. In this study, we explored the effects of stem-only harvest at various thinning intensities on forest structure and carbon density in middle-aged natural secondary forests, located in the northern temperate zone. Carbon density included aboveground carbon density (ACD), soil organic carbon stocks (SOCD), and total carbon density (TCD), which was the sum of ACD and SOCD. We employed the random forest analysis method to identify significant variables influencing changes in carbon density. Structural equation modelling (SEM) was then used to determine the drivers of changes in forest carbon density. The results showed that moderate thinning (20 %–35 % trees removed), is an effective management practice for increasing the TCD in forests. Although heavy thinning (35.1 %–59.9 % trees removed) accelerated individual growth, it did not fully offset the carbon removed due to thinning. It is noteworthy that light thinning (0–19.9 % trees removed) not only reduced the species richness but also caused a significant number of tree deaths. Large live trees were an important direct determining factor of ACD, but not the only one. In addition, thinning indirectly influenced ACD by reducing canopy density and deformed tree density. The increase in dead tree density had an adverse impact on SOCD, and this phenomenon increased with the passage of recovery time. Conversely, greater thinning intensity enhanced SOCD. Moreover, TCD was directly influenced by tree height, large live trees, and stand density. Furthermore, thinning altered the conifer ratio, thereby influencing tree growth and indirectly controlling the TCD. We believe that this knowledge will be highly beneficial for successful forest management and enhancing the carbon sequestration capacity of forest ecosystems.

Dynamics of resin yield in Pinus brutia: A quantitative analysis using bark streak tapping

The sustainable harvesting of resin yield from forests plays a crucial role in providing valuable renewable resources. Specifically, Pinus brutia forests in Türkiye are significant for their oleoresin, utilized in various industries. Yet, understanding how dendrometric and meteorological factors influence resin yield is essential for optimizing production while ensuring forest sustainability. This study aimed to estimate oleoresin yield in Pinus brutia plantations using dendrometric parameters (such as diameter at breast height and tree height, basal area, volume and canopy closure) and meteorological parameters (including monthly; minimum, maximum, and average temperature, precipitation, humidity, vapor pressure, and wind speed), to identify the key factors affecting resin production. Resin was collected from 389 Pinus brutia trees of varying diameters across 27 different plots using the bark streak tapping method, with data recorded every 15 days over a year. Weighted Leased Square regression analysis was conducted to explore the relationship between resin yield and the aforementioned dendrometric and meteorological parameters. The analysis revealed that diameter at breast height, monthly average temperature, wind speed, and precipitation significantly influence resin yield. The study underscores the intricate interplay between these factors and resin production, indicating that larger diameters and specific meteorological conditions—especially average temperature, wind speed, and precipitation—are positively correlated with increased resin output. The findings suggest that sustainable resin extraction practices in Pinus brutia forests should account for not only the physical characteristics of the trees but also the local meteorological conditions to maximize yield without compromising forest health. This research contributes to the development of more effective guidelines for oleoresin harvesting, ensuring both economic viability and ecological preservation.

Development of Local Volume Table for Pinus caribbaea var. hondurensis (Senecl) in Area J4, Omo Forest Reserve, Nigeria

Volume estimation is a crucial part of every forest or plantation because it provides the quantity of timber or wood available at a given period and predicts future or expected growth of the forest. Unfortunately, local volume table are not readily available for some–economically important tree species in Nigeria. Hence, it is of paramount importance that local volume tables for economic tree species such as Pinus caribbaea in Area J4, Omo Forest reserve, Ogun state, Nigeria. Aim: The aim of this study is to develop a local volume table for Pinus caribbaea in Area J4, Omo Forest Reserve, Ogun State, Nigeria. Study Design: Simple random sampling was used for this study. Ten Temporary Sample Plots (TSP) of equal size 25m x 25m were randomly located in the selected plantation (P. caribbaea: established in 1997). All the trees with diameter at breast height (dbh) ≥ 10cm in each TSP were enumerated. Place and Duration of Study: The study was carried out in the Pinus caribbaea plantation in Area J4, Omo forest reserve, Ogun State from November 9th to 20th, 2023. Methodology: The total tree height, merchantable height, diameters at the top, middle, base, and dbh were measured and used to estimate stand volume. A volume table was developed using five selected models, and the best model was selected using least Akaike Information Criterion (AIC), Bayesian Information Criterion (BIC) and Root Mean Square Error (RMSE). Data were analyzed using descriptive statistics and regression at α0.05 with R statistical software. Results: The results obtained in P. caribbaea plantation revealed that the dbh and height were 27.93±6.95 cm and 28.72±3.47 m, respectively, while individual tree volume was 0.83±0.57m3. The combined variable model ( was selected as the best model to develop local volume table for P. caribbaea (AIC = -54.73, BIC = -45.49 and RMSE = 0.20). The statistical metrics implied a suitable selected model which can be use for future predictions with minimal error. Conclusion: The developed volume table for estimating the quantity of wood or timber available in the Pinus caribaea plantation at a given time. The volume model and local volume table developed are to be applied only to the Pinus caribaea plantation in the study area for continuous estimation and valuation of the species.

Detailed height mapping of trees and buildings (HiTAB) in Chicago and its implications to urban climate studies

Abstract The vertical dimensions of urban morphology, specifically the heights of trees and buildings, exert significant influence on wind flow fields in urban street canyons and the thermal environment of the urban fabric, subsequently affecting the microclimate, noise levels, and air quality. Despite their importance, these critical attributes are less commonly available and rarely utilized in urban climate models compared to planar land use and land cover data. In this study, we explicitly mapped the height of trees and buildings (HiTAB) across the city of Chicago at 1 m spatial resolution using a data fusion approach. This approach integrates high-precision light detection and ranging (LiDAR) cloud point data, building footprint inventory, and multi-band satellite images. Specifically, the digital terrain and surface models were first created from the LiDAR dataset to calculate the height of surface objects, while the rest of the datasets were used to delineate trees and buildings. We validated the derived height information against the existing building database in downtown Chicago and the Meter-scale Urban Land Cover map from the Environmental Protection Agency, respectively. The co-investigation on trees and building heights offers a valuable initiative in the effort to inform urban land surface parameterizations using real-world data. Given their high spatial resolution, the height maps can be adopted in physical-based and data-driven urban models to achieve higher resolution and accuracy while lowering uncertainties. Moreover, our method can be extended to other urban regions, benefiting from the growing availability of high-resolution urban informatics globally. Collectively, these datasets can substantially contribute to future studies on hyper-local weather dynamics, urban heterogeneity, morphology, and planning, providing a more comprehensive understanding of urban environments.

Seasonal Variations in Hydraulic Regulation of Whole-Tree Transpiration in Mongolian Pine Plantations: Insights from Semiarid Deserts in Northern China

Seasonal precipitation variance significantly alters soil water content, potentially inducing water stress and affecting plant transpiration in semiarid deserts. This study explored the effects of environmental variables and hydraulic conductance on whole-tree transpiration (ET) in Mongolian pines (Pinus sylvestris var. mongolica) across different forest stages in the semiarid deserts of Northern China. We measured ET using sap flow in mature (MMP), half-mature (HMP), and young (YMP) Mongolian pine plantations. Measurements included soil-leaf water potential difference (ΔΨ), atmospheric conditions, and soil moisture contents on sunny days, both in dry and wet periods. Seasonally variable rainfall distinctly affected soil moisture; during the dry periods, both stomatal and hydraulic conductance influenced ET, whereas stomatal conductance primarily regulated it during the wet periods. Discrepancies between predicted and measured ET were noticed: compared to the predicted ET, the measured ET was lower during dry periods while higher during wet periods. Hydraulic conductance (KT) increased with tree height (H) and ΔΨ. The KT values in the dry period were lower than those in the wet period, indicating that the hydraulic resistance in the dry period was higher. The hydraulic compensation occurred and was observed between 11:00 and 13:00, aligned with increased hydraulic resistance during dry periods. Decreasing hydraulic conductance intensified leaf water stress in dry periods, especially when photosynthetically active radiation (PAR) and vapor pressure deficit (VPD) were heightened, potentially increasing stomatal sensitivity to drought, promoting water conservation and plant survival. A linear relationship between predawn and midday leaf water potentials was noticed, indicating extreme anisohydric behavior across forest stages during dry and wet periods. Although stomatal and hydraulic conductance influenced ET during the dry period, MMP and YMP were more susceptible to drought conditions. Understanding these dynamics could help evaluate semiarid desert ecological functions for water conservation amidst uneven seasonal precipitation in Northern China.

Current understanding and future prospects for ash dieback disease with a focus on Britain

Abstract Hymenoscyphus fraxineus is an introduced ascomycete fungus which causes ash dieback and has resulted in widespread mortality of ash throughout Europe. Although H. fraxineus has been present on the continent for at least four decades, it was not identified until 2006. The first record of the pathogen in Britain came in 2012 although it was probably present a decade earlier. The most common host European ash (Fraxinus excelsior L.) is economically and ecologically important to Britain where the cost of ash dieback is estimated at billions of pounds. The impact of ash dieback has stimulated a major research response which we review with the aim of providing up-to-date information relevant to Britain and identifying knowledge gaps where research would contribute to improved disease mitigation. Hymenoscyphus fraxineus is an outcrossing fungus with high genotypic diversity; ascospores produced via sexual reproduction are critical to aerial dispersal and infection. Temperature, moisture, and ground cover influence pathogen fruit body development, the timing of ascospore release, and extent of ascospore germination; they also interact together to affect the likelihood of infection. In addition, stand characteristics, including tree density, tree height, and landscape fragmentation, affect disease dynamics with increased disease severity on moist sites with high ash density. Efforts at finding natural resistance in ash have identified genetic markers associated with disease tolerance, and gene expression analysis is providing insights into the basis of that resistance. Mainland European findings indicate that ash dieback makes trees more vulnerable to other pathogens, whilst endophytes in the ash phyllosphere can suppress infection by H. fraxineus. Possible tools for long-term control of ash dieback include (1) deployment of resistant ash, (2) quantitatively informed management practices based on microclimate models and better understanding of the pathogen life cycle, and (3) manipulation of biocontrol agents from the ash microbiome or pathogen mycoviruses.

Distribution and Habitat Selection of Indian Flying Fox, Pteropus medius (Temminck, 1825) in Uttar Pradesh, India

The present study examines the distribution and habitat selection of Indian flying fox, Pteropus medius in Uttar Pradesh, India. A through field work conducted across six districts revealed 22 roosting locations with a total population of approximately 12,023 bats. These sites were located at rural (12), semi-urban (2), urban (1), agricultural (5), and industrial (2) areas, and a majority of roost sites observed close to human habitations. Pteropus medius preferred to roost on 20 species of trees which indicate wide-ranging habitat preferences. Although there were considerable differences in tree attributes across different species, such as tree height (ranging from 9.54 to 26.03 meters), canopy width (varying from 8.59 to 25.09 meters), crown height (ranging from 1.19 to 18.90 meters), circumference (ranging from 0.54 to 3.65 meters), and DBH (ranging from 0.17 to 3.73 meters), and there was no notable variation in bat occupancy per roost tree. The results of the regression analysis emphasized the significance of canopy width as a predictor of colony size, indicating its importance in identifying suitable roosting habitats for P. medius. ANOVA analysis indicated differences in tree characteristics across species, highlighting the necessity for through habitat evaluations. Subsequent post-hoc examination clarified distinct clusters of tree species with significant variations in roosting site features. These results underscore the intricate relationship between tree attributes and bat populations, emphasizing the significance of well-informed conservation approaches for the sustainable preservation of P. medius and the overall ecosystem well-being.

Intensifying aridity induces tradeoffs among biodiversity and ecosystem services supported by trees

AbstractAimChanges in climate are likely to have major impacts on benefits (i.e., biodiversity and ecosystem services) supported by trees. Here we explore the extent to which trees can support multiple benefits, and the potential tradeoffs among them, under increasing dryness.LocationEastern Australia.Time period2018–2019.Major taxa studiedTrees.MethodsWe evaluated changes in biodiversity and services supported by trees and the nature of potential tradeoffs in response to increasing aridity, our proxy of drying regional climates. We assessed six benefits (biodiversity and five ecosystem services) supported by trees at 126 sites across a gradient from Australia's mesic coast to the arid interior.ResultsThe value of average benefits did not vary with aridity, with winners and losers in biodiversity and ecosystem services as aridity intensified. Tradeoffs between biodiversity and soil stability declined with increasing aridity, but only in mesic environments, whereas tradeoffs between wood production potential and carbon storage intensified under greater aridity levels, but only in mesic environments. Aridity and tree structure were the major regulators of these tradeoffs, particularly under dry environments. Increasing aridity affected tradeoffs directly or indirectly by either suppressing the positive effect of tree height or exacerbating the negative effect of tree canopy size.Main conclusionsOur results indicate that biodiversity and most ecosystem services supported by trees are likely to decline under future climate change scenarios and demonstrate the importance of targeting afforestation programs to specific services in particular climatic areas rather than attempting to improve multiple services.

New tree height allometries derived from terrestrial laser scanning reveal substantial discrepancies with forest inventory methods in tropical rainforests.

Tree allometric models, essential for monitoring and predicting terrestrial carbon stocks, are traditionally built on global databases with forest inventory measurements of stem diameter (D) and tree height (H). However, these databases often combine H measurements obtained through various measurement methods, each with distinct error patterns, affecting the resulting H:D allometries. In recent decades, terrestrial laser scanning (TLS) has emerged as a widely accepted method for accurate, non-destructive tree structural measurements. This study used TLS data to evaluate the prediction accuracy of forest inventory-based H:D allometries and to develop more accurate pantropical allometries. We considered 19 tropical rainforest plots across four continents. Eleven plots had forest inventory and RIEGL VZ-400(i) TLS-based D and H data, allowing accuracy assessment of local forest inventory-based H:D allometries. Additionally, TLS-based data from 1951 trees from all 19 plots were used to create new pantropical H:D allometries for tropical rainforests. Our findings reveal that in most plots, forest inventory-based H:D allometries underestimated H compared with TLS-based allometries. For 30-metre-tall trees, these underestimations varied from -1.6 m (-5.3%) to -7.5 m (-25.4%). In the Malaysian plot with trees reaching up to 77 m in height, the underestimation was as much as -31.7 m (-41.3%). We propose a TLS-based pantropical H:D allometry, incorporating maximum climatological water deficit for site effects, with a mean uncertainty of 19.1% and a mean bias of -4.8%. While the mean uncertainty is roughly 2.3% greater than that of the Chave2014 model, this model demonstrates more consistent uncertainties across tree size and delivers less biased estimates of H (with a reduction of 8.23%). In summary, recognizing the errors in H measurements from forest inventory methods is vital, as they can propagate into the allometries they inform. This study underscores the potential of TLS for accurate H and D measurements in tropical rainforests, essential for refining tree allometries.

No Field Evidence of Grass Fuel Structure effects on Postfire Tree Mortality in Juniperus virginiana

Prescribed fires are an important management tool for containing woody plant encroachment in rangeland ecosystems. Grasses are the dominant fuel type in rangelands. Past work has shown that grass canopy architecture, which varies among grass species, can influence flammability. Whether variation in grass fuel structure can influence postfire plant responses has not yet been tested. To bridge this gap, we set up field burning experiments with different fuel treatments and examined postfire mortality of Juniperus virginiana L. in a tallgrass prairie in southwestern Missouri. We sampled 60 trees and measured tree height and diameter at breast height before the fire. Fuels surrounding each tree were manipulated to vary independently in both fuel load and fuel structure. Flame temperatures were measured during the fire, and both stem and canopy injuries were evaluated 1 d after the fire. We surveyed tree mortality 7 mo after the fire. We found no effects of either fuel load or fuel structure on postfire mortality or on canopy injury in J. virginiana. Canopy injury was a critical fire severity measurement determining postfire mortality in J. virginiana, and taller trees are more fire resilient. Despite laboratory-observed fuel structure effects on flammability, this study finds no evidence for the importance of grass fuel load and canopy architecture in influencing postfire tree response. This result might arise from the low crown depth and low canopy water content of J. virginiana, which can promote canopy fire and result in a high mortality rate across fuel treatments. Notwithstanding the negative results, testing laboratory-based findings in field settings is important for further examining laboratory observations and upscaling individual-level processes to ecosystems to help identify the key ecological processes determining population dynamics and community assembly. Our study also suggests that prescribed fire is an effective tool to remove encroaching J. virginiana in tallgrass prairies at an early stage.

Scale effect of landscape characteristics on undergrowth vegetation variance with different ecological traits

Herbaceous understory vegetation plays a significant role in temperate forested ecosystems, with its diversity strongly dependent on both local and landscape conditions. However, the contribution of these factors across different spatial scales (e.g., scale effect) remains inadequately understood. The objective of this study was to determine the most important landscape and local characteristics influencing the species richness of the herb layer. We surveyed and sampled 53 sites in a mountainous forest within the Baihuashan National Nature Reserve of Beijing. Using generalized linear models, we investigated the simultaneous effect of local (e.g. tree density, average tree height, and cover of tree, shrub, and ground vegetation) and landscape (e.g. Area-weighted Mean Patch Size, Area-weighted Mean Euclidean Nearest Neighbor Distance, Area-weighted Mean Fractal Dimension Index, forest area, and shrubbery area) variables on the richness of species in the understory herb layer. Variation partitioning was used to examine the individual contribution of local and landscape variables. Our results identified 366 plant species from 95 families across 53 sampling sites. Significant differences in species richness were found among life forms, seed dispersal types, and habitat preferences (P < 0.001). Parsimonious models indicated that combining local and landscape factors at a 2 km scale explained the most variation in phanerophytes (R2 = 0.658). Locally, average tree height significantly influenced the species richness of biotic dispersal, phanerophytes, and geophytes. At the landscape level, variables such as the Area-weighted Mean Fractal Dimension Index and farmland area significantly impacted plant community traits across different scales. Understanding these effects is crucial for developing effective sustainable forest ecosystem management strategies and for establishing robust ecological conservation policies.

Optimizing leaf nutrient status, growth, and yield parameters in high-density apple orchards (cv. Super chief) via integrated drip irrigation and fertigation techniques

Nutrients and water are important ecophysiological components for apples' development and productivity. The combination of high-density plantation, drip irrigation, and weekly fertigation not only conserves irrigation water, but also reduces cultivation costs compared to conventional methods. Leaf nutrient analysis provides insight into nutrient levels and assists in determining irrigation and fertigation schedules. We conducted the current research over two years (2021–22 and 2022–23) to evaluate different drip-fertigation effects on leaf nutrient status, vegetative growth, and yield of high-density apples. The experimental study employed a factorial randomised block design, replicating 16 different treatment combinations three times each. Each replication consisted of three plants, and the treatments included four irrigation levels (100 %, 80 %, 60 %, and control) and four fertigation levels (absolute control, 100 %, 75 %, and 50 % of the recommended NPK dosage). Analysis of the leaves indicated that IR1 (Drip irrigation at 100 % ETc) showed notably higher levels of nitrogen at (3.06 %), phosphorus at (0.48 %) and potassium at (2.07 %) compared to other treatments. Regarding fertigation levels, FN1 [100 % (AD) NPK] showed the highest nitrogen (3.12 %), phosphorus (0.50 %), and potassium (2.09 %) content. Parameters related to vegetative growth, including tree height, plant spread in both east-west (EW) and north-south (NS) directions, trunk girth, annual extension growth, and leaf area showed significant increases with higher irrigation and fertigation levels, surpassing conventional irrigation (IR4) by 6.17 percent, 7.78 percent (EW), 8.62 percent (NS), 10.49 percent, 4.53 percent and 1.96 percent, respectively. Among fertigation, FN1- 100 % AD (NPK) registered a maximum increase in growth parameters. Our analysis demonstrated that combining irrigation and fertigation improved leaf nutrient status and vegetative growth characteristics, which are critical determinants of fruit yield.

Evaluation of Different Container Types on Root Structure and Performance of Nursery-grown Citrus Plants

Health and quality of the root system are imperative to ensure the successful establishment of a citrus tree after transplant from the nursery into the field. Containerized citrus production in enclosed nurseries restricts root growth and can result in root circling and intertwining. This may hinder root expansion and result in root girdling after transplant, negatively affecting tree establishment and growth. The root structure of a transplanted citrus tree can also be affected by the container type used in the nursery. Containers with root-pruning properties like chemical pruning or air pruning reduce root circling and may produce superior root systems compared with regular, nonpruning containers. The aim of this study was to evaluate the effects of different nursery containers on root physiological and morphological traits and plant performance over 15 months of growth in the nursery. Three container types, chemical pruning containers, air-pruning containers, and standard nursery containers, were compared. The chemical pruning containers were standard citrus nursery containers with a mixture of copy hydroxide [Cu(OH)2] and copper carbonate (CuCO3) [10% copper (Cu)] applied to the inner wall. Pruning occurs upon contact of the roots with the Cu on the wall of the containers. The air-pruning containers were custom-sized Air-Pots in which pruning occurs on holes in the wall of the containers upon contact of the roots with the air. Two rootstocks, US-812 and US-942 (Citrus reticulata × Poncirus trifoliata), were included for comparison in the nongrafted stage and 12 months after grafting with ‘Valencia’ orange (Citrus sinensis). Chemical root pruning positively influenced tree height, shoot mass, leaf area, rootstock trunk diameter, and the nonfibrous root biomass. No differences among container types were observed for the fibrous root biomass, but chemical pruning produced more roots that were finer with a higher specific root length and a higher respiration rate. In contrast, air pruning produced more roots that were thicker compared with the other containers. Most of the leaf nutrients were lower in trees grown in the chemical pruning containers compared with the standard containers, except for Cu and zinc (Zn), which were highest in the former. Trees growing in air-pruning containers were not significantly different in growth from trees growing in standard containers.

Plasticity of leaf functional traits and growth responses to disturbance among cutting cultivars of Cryptomeria japonica in southern Japan

ABSTRACT Cryptomeria japonica (Thunb. ex L. f.) D. Don is the most major plantation species in Japan, and cultivars have been developed and planted under variable environmental conditions across the country. Productivity of clonal plantations is influenced by the ability of the genotype to acclimate to edaphic- and geographic-scale variation in environmental conditions and disturbance regimes. Because all individuals are genetically identical in a clonal plantation, the trait differences among individuals represent phenotypic plasticity. Here, we investigated how phenotypic plasticity and response to disturbance vary among cutting cultivars of C. japonica. We compared tree height, leaf morphology, nitrogen content, and frequency/intensity of growth-release observed in tree rings after thinning and disturbance among six cutting cultivars in 45-year-old provenance trials in south-western Japan. Nitrogen use efficiency was higher in the site where maximum tree height (H max) was taller, while shoot mass per area (SMA) was larger in the site where H max was shorter. Cultivars that grew well had high leaf nitrogen content (N G) and showed more efficient nitrogen use with high nitrogen-resorption efficiency (NRE). Yabukuguri, an intermediate-growth cultivar, was characterized by large SMA and greater plasticity in SMA and tree height in response to topographical and regional variation, as well as greater intensity of growth-release in tree-ring series indicating growth resilience following disturbance. Our results provide guidelines for selecting cultivars with high acclimation potential and resilience to environmental perturbation, which is important for sustaining plantation forests in uncertain environmental conditions expected by future climate change.

Tree Height Estimation of Chinese Fir Forests Based on Geographically Weighted Regression and Forest Survey Data

Tree Height Estimation of Chinese Fir Forests Based on Geographically Weighted Regression and Forest Survey Data

A Novel Point Cloud Adaptive Filtering Algorithm for LiDAR SLAM in Forest Environments Based on Guidance Information

To address the issue of accuracy in Simultaneous Localization and Mapping (SLAM) for forested areas, a novel point cloud adaptive filtering algorithm is proposed in the paper, based on point cloud data obtained by backpack Light Detection and Ranging (LiDAR). The algorithm employs a K-D tree to construct the spatial position information of the 3D point cloud, deriving a linear model that is the guidance information based on both the original and filtered point cloud data. The parameters of the linear model are determined by minimizing the cost function using an optimization strategy, and a guidance point cloud filter is subsequently constructed based on these parameters. The results demonstrate that, comparing the diameter at breast height (DBH) and tree height before and after filtering with the measured true values, the accuracy of SLAM mapping is significantly improved after filtering. The Mean Absolute Error (MAE) of DBH before and after filtering are 2.20 cm and 1.16 cm; the Root Mean Square Error (RMSE) values are 4.78 cm and 1.40 cm; and the relative RMSE values are 29.30% and 8.59%. For tree height, the MAE before and after filtering are 0.76 m and 0.40 m; the RMSE values are 1.01 m and 0.50 m; the relative RMSE values are 7.33% and 3.65%. The experimental results validate that the proposed adaptive point cloud filtering method based on guided information is an effective point cloud preprocessing method for enhancing the accuracy of SLAM mapping in forested areas.

Spatial Pattern of Forest Age in China Estimated by the Fusion of Multiscale Information

Forest age is one of most important biological factors that determines the magnitude of vegetation carbon sequestration. A spatially explicit forest age dataset is crucial for forest carbon dynamics modeling at the regional scale. However, owing to the high spatial heterogeneity in forest age, accurate high-resolution forest age data are still lacking, which causes uncertainty in carbon sink potential prediction. In this study, we obtained a 1 km resolution forest map based on the fusion of multiscale age information, i.e., the ninth (2014–2018) forest inventory statistics of China, with high accuracy at the province scale, and a field-observed dataset covering 6779 sites, with high accuracy at the site scale. Specifically, we first constructed a random forest (RF) model based on field-observed data. Utilizing this model, we then generated a spatially explicit forest age map with a 1 km resolution (random forest age map, RF map) using remotely sensed data such as tree height, elevation, meteorology, and forest distribution. This was then used as the basis for downscaling the provincial-scale forest inventory statistics of the forest ages and retrieving constrained maps of forest age (forest inventory constrained age maps, FIC map), which exhibit high statistical accuracy at both the province scale and site scale. The main results included the following: (1) RF can be used to estimate the site-scale forest age accurately (R2 = 0.89) and has the potential to predict the spatial pattern of forest age. However, (2) owing to the impacts of sampling error (e.g., field-observed sites are usually located in areas exhibiting relatively favorable environmental conditions) and the spatial mismatch among different datasets, the regional-scale forest age predicted by the RF model could be overestimated by 71.6%. (3) The results of the downscaling of the inventory statistics indicate that the average age of forests in China is 35.1 years (standard deviation of 21.9 years), with high spatial heterogeneity. Specifically, forests are older in mountainous and hilly areas, such as northeast, southwest, and northwest China, than in southern China. The spatially explicit dataset of the forest age retrieved in this study encompasses synthesized multiscale forest age information and is valuable for the research community in assessing the carbon sink potential and modeling carbon dynamics.

Spatial Distribution Pattern of Response of Quercus Variabilis Plantation to Forest Restoration Thinning in a Semi-Arid Area in China

Plantations are increasing in frequency and extent across the landscape, especially in China, and forest thinning can accelerate the development of late-successional attributes, thereby enhancing plantation stand structural heterogeneity. To quantify the effect of forest restoration thinning on the spatial heterogeneity and the structure of Quercus variabilis plantations, a restoration thinning experiment in a 40-year-old Quercus variabilis plantation by removing trees from the upper canopy level was conducted; two one-hectare sample plots with thinning and a control (i.e., unlogged) were sampled; and geostatistics methods were used to analyze the spatial distribution pattern of the DBH, height, and density of the stand. We found that restoration forest thinning in the Quercus variabilis plantation had a significant impact on the average DBH and tree height of the stand. Meanwhile, the coefficient of variation and structure ratio of the DBH, tree height, and stand density in the thinning plot were larger than those in the control plot. The range and spatial autocorrelation distance of the DBH and stand density in the thinning plot were smaller than those in the control plot, but the fractal dimension showed the opposite trend. The range and spatial autocorrelation distance of tree height in the thinning plot were higher than those in the control plot. These findings suggested that, compared with the control plot, the stereoscopic distribution of the DBH and stand density in the thinning plot fluctuated less and changed gentler, and its spatial continuity was not high but its variation was significant; meanwhile, the stereoscopic distribution of the tree height in the thinning plot was highly fluctuating and changed more significantly, with a strong spatial dependence and strip gradient distribution. Hence, forest restoration thinning could improve the distribution of the DBH and stand density and adjust the spatial heterogeneity of the DBH, tree height, and stand density of Quercus variabilis plantations.

Architectural approach to evaluate the design and management of almond cultivars suitable for super high-density orchards.

The almond tree is a major global nut crop, and its production has surged dramatically in recent years. Super high-density (SHD) planting systems, designed to optimize resource efficiency and enhance precocity, have gained prominence in almond cultivation. A shift in cropping systems toward sustainable intensification (SI) pathways is imperative, and so maximizing branching density within the canopies of SHD trees is crucial to establish and maintain productive potential, especially for hedge-pruned trees. This study investigates the influence of different almond cultivars grafted onto a novel growth-controlling rootstock on tree architectural and growth parameters in a SHD orchard. This open field research provided valuable insights for the development and application of new tools and methods to increase productivity and sustainability in almond growing. Three cultivars (Lauranne® Avijour, Guara Tuono, and Filippo Cea) were evaluated in Gravina in Puglia (BA) over a two-year period. Canopy growth parameters, such as canopy volume and trunk cross-sectional area, and architectural traits, like branching density, branching angle, number and length of subterminal shoots, and number of brachyblasts, were measured through qualitative and quantitative measurements. Results revealed significant differences in tree height, canopy thickness, width, volume, and vigor among the cultivars. Architectural traits, including branch parameters, brachyblast parameters, and subterminal shoots, varied among the cultivars. Lauranne displayed a more compact well-distributed canopy and exhibited the lowest vigor. Filippo Cea showed the highest vigor and the greatest canopy volume. Tuono had a higher number of buds and bud density. The best ideotype for SHD orchards is a smaller tree, with high branching density and smaller trunk diameters, i.e. the vigor. Cv. Lauranne seemed to be the best cultivar, mostly with the lowest tree vigor of all the cultivars involved. These findings provide valuable insights for almond growers and breeders seeking to optimize orchard design and management for enhanced SHD orchards productivity and sustainability. Future research will explore the relationship between canopy architecture and yield parameters, considering different scion/rootstock combinations in different environmental conditions.