Tree Location Research Articles

Constructing a Model of Poplus spp. Growth Rate Based on the Model Fusion and Analysis of Its Growth Rate Differences and Distribution Characteristics under Different Classes of Environmental Indicators

Poplar (Poplus spp.) is an important forest species widely distributed in China of great significance in identifying factors that clearly influence its growth rate in order to achieve effective control of poplar growth. In this study, we selected 16 factors, including tree size, competition, climate, location, topography, and soil characteristics, to construct linear regression (LR), multilayer perceptron (MLP), k-nearest neighbor regression (KNN), gradient boosting decision tree (GBDT), extreme gradient boosting (XGB), random forest (RF), and deep neural network (DNN) models based on the poplar growth rate. Using model fusion methods, the fitting accuracy and estimation capability were improved. The relative importance of each variable in estimating the poplar growth rate was analyzed using the permutation importance evaluation. The results showed the following: (1) the model fusion approach significantly improved the estimation accuracy of the poplar growth rate model with an R2 of 0.893; (2) the temperature and precipitation exhibited the highest importance in poplar growth; (3) the forest stand density, precipitation, elevation, and temperature had significant variations in growth rates among different-sized poplar trees within different ranges; (4) low-forest stand density, high-precipitation, low-elevation, and high-temperature environments significantly increased the poplar growth rate and had a larger proportion of large-sized individuals with high growth rates. In conclusion, environmental factors significantly influence poplar growth, and corresponding planting and protection measures should be tailored to different growth environments to effectively enhance the growth of poplar plantations.

Variability in Water Capacity of Small-Leaved Linden Associated with Both the Presence of Honeydew and Various Sources of Pollution.

The process of water retention on the surface of the assimilation apparatus of plants is inextricably linked with the water capacity of tree crowns and depends mainly on the condition of the leaf itself. The main objective of the present study was to investigate how the honeydew coverage and the location of trees related to the content of polycyclic aromatic hydrocarbons affected the differences in the capability of small-leaved linden leaves to capture water. Honeydew coverage was determined with the use of AutoCAD, whereas the content of polycyclic aromatic hydrocarbons was determined using gas chromatography. The value of S (water capacity) was much lower before the appearance of honeydew on the leaf than at the peak moment of honeydew collection. This is due to the hydrophobic properties of the substance. It was also found that the content of polycyclic aromatic hydrocarbons (PAH) in leaves varied depending on the distance of trees from pollution sources, and it was found that the amount of PAHs increased with the growth of honeydew on leaves and in locations exposed to pollution. The highest S and the total amount of PAHs occurred with the combination of the largest amount of pyrogenic impurities with the highest amount of honeydew. Combing pollutants from the air by plants is a very important function, but it may also change the physical properties of leaves, such as wettability.

Recreating structurally realistic tree maps with airborne laser scanning and ground measurements

The estimation of forest attributes representing aspects of structural biodiversity from vast areas is difficult not only because of the lack of agreement on what constitutes a structurally diverse forest, but also due to difficulties in the detection of small trees. However, a structurally diverse forest should have large variation in tree size (i.e., height and diameter), as well as some clustering of trees, as regular tree pattern is typical for managed forests. In this work we developed a framework for building structurally representative tree maps using airborne laser scanning data and a limited number of ground measurements using data from two locations in Finland. In the proposed method, an individual tree detection algorithm is optimized so that the number of undetected trees and false detections is minimized. The ground measurements are then used to train models for predicting the number and location of undetected trees and false detections by resampling the attributes of undetected trees in the training data. This model can then be applied to other areas in the proximity of the ground measurements to build tree maps, with the location, height, and diameter for each tree. The methodology was shown to reproduce the number of trees, the height distribution, and the spatial pattern of the trees with sufficient accuracy for practical use in large-scale mapping of forest attributes. For example, the individual tree detection could find at best about 54% of the trees with an additional 7% of false detections, resulting in a bias of approximately −30%, while with the new method the bias was reduced to ±10% of the stem density. Further research is needed on how to account for tree species when building tree maps.

Phylogenetic Relationships among some Species of the Genus Hypericum (Hypericaceae) in Kurdistan-Rgeion Iraq

Phylogenetic hypotheses for the large cosmopolitan genus Hypericum (St. John’s wort) have previously been based on morphology, and molecular studies have thus far included only a few species. In this study, we used Eight taxa representing 2 sections of the genus Hypericum were analyzed along with one representatives of Thornea calcicola using nuclear internal transcribed spacer ITS and 28SrRNA sequences in order to assess the scope of phylogenetic relationships in this species-rich genus. The resulting parsimony analysis and Bayesian Inference corroborates the actual classification and interspecific affinities. The molecular data provide support for the monophyletic assemblage of the sections in both ITS and 28SrRNA regions trees shows four different clades with minimum changes between species location in both tree. We used Maximum Parsimony and Bayesian approach to reconstruct ancestral states of selected characters, which resulted in recognition of characters that support major clades within the genus Hypericum. The obtained results encourage the use of ITS and 28SrRNA sequence analysis in resolving the phylogenetic relationships within the member rich genus Hypericum. Our results differ somewhat from those of recent morphological and cytological studies. The phylogenetic relationships among Hypericum species have now been mostly resolved via 28SrRNA phylogeny.

Distribution of giant trees in the urban areas and western suburbs of Tokyo, Japan

ABSTRACT Giant trees reflect site environmental conditions and to elucidate the distribution pattern of the giant trees, we investigated relationships between giant tree locations and landforms. On the basis of elevation, the landforms of Tokyo were divided into four types (lowland, plateau, hill, and mountain), and tree distribution patterns were divided into five groups, including three sub-types, with occurrence patterns of representative species [I: Frequently lowlands, often plateaux and mountain type (Machilus thunbergi); II: Frequently plateaux, often lowland, hill, or mountain type (Quercus acuta, Prunus speciosa, Taxodium distichum, Liriodendron tulipifera, Cedrus deodara, Aphananthe aspera, and Prunus × yedoensis “Somei-yoshino”) with two subtypes, II-1: Typically plateaux (Cinnamomum camphora, Castanopsis sieboldii, and Ginkgo biloba) and II-2: Frequently plateaux and hills (Zelkova serrata); III: Typically plateaux and hill type (Certis sinensis var. japonica, Torreya nucifera, Carpinus tschonoskii, Quercus myrsinifolia, and Quercus serrata) with one subtype, Frequently plateaux (Prunus jamasakura); IV: Mountains often with plateaux or hill type (Acer pictum subsp. mono, Aesculus turbinate, Abies firma, Cryptomeria japonica, and Cercidiphyllum japonicum); and V: Mountain-limited type (Castanea crenata, Pterocarya rhoifolia, and Fraxinus platypoda)]. Some giant trees, including Quercus crispula, Fagus japonica, Fagus crenata, and Tsuga sieboldii, were distributed in mountainous areas but not on plateaux, hills, or in lowlands. Some unique giant trees (Aphananthe aspera, Certis sinensis var. japonica, and Carpinus tschonoskii) are self-seeding in the wild and found in plateau areas but not mountainous or hilly areas. These results suggest that the distribution of giant trees is influenced by site ecological characteristics, tree physiology, and human management and land-use.

Method and Device for Measuring the Diameter at Breast Height and Location of Trees in Sample Plots

The diameter at breast height (DBH) and location of trees are important factors when surveying forest resources and ecological functions. In this study, a device mainly comprising a self-made DBH-measuring instrument and positioning base station was used. The hardware consisted of two devices to simultaneously measure the DBH and location of trees within a sample plot. Specifically, DBH is acquired by processing angle data with an algorithm, and locations are obtained by a five-sided ranging and positioning algorithm based on the received signal strength indicator and ultra-wideband (UWB) sensor. Data uploading, storage and analysis are performed by an upper computer. The device was used for the actual measurement of eight 24 m × 24 m square plots. The measurements of this device are essentially consistent with those of the DBH tape and calliper, with biases of −0.03 cm and −0.29 cm, respectively. Compared with a compass for location measurement, the device had a mean range bias of 25.41 cm, overall bias along the X-axis of 2.40 cm and overall bias along the Y-axis of 1.99 cm. Therefore, the device is considered to be sufficiently portable and practical and can reduce the heavy workload for surveyors to meet the requirements of accurate and smart measurements in forest resource surveys.

Modelling the spread of tree pests and pathogens in urban forests

Understanding the potential dynamics of tree pests and pathogens is a vital component for creating resilient urban treescapes. Epidemiologically relevant features include differences in environmental stress and tree management between street and garden trees, and variation in the potential for human-mediated spread due to intensity of human activity, traffic flow and buildings. We extend a standard spatially explicit raster-based model for pest and pathogen spread by dividing the urban tree population into roadside trees and park/garden trees. We also distinguish between naturally-driven radial spread of pests and pathogens and human-mediated linear spread along roads. The model behaviour is explored using landscape data for tree locations in an exemplar UK town. Two main sources of landscape data were available: commercially collated aerial data, which have high coverage but no information on species; and, an urban tree inventory, with low, non-random, coverage but with some species data. The data were insufficient to impute a species-specific host landscape accurately; however, by combining the two data sources, and applying either random or Matérn cluster point process driven selection of a subset of all trees, we create two sets of potential host landscapes. We find that combining the two mechanisms of dispersal has a non-additive effect, with the enhanced linear dispersal enabling new foci of infection to be established more rapidly than with radial dispersal alone; and clustering of trees by species slows down the expansion of epidemics when compared with random distribution of tree species within known host locations.

Entomophthoralean fungi overwinter with the bird cherry-oat aphid on bird cherry trees

In Scandinavia, the bird cherry-oat aphid Rhopalosiphum padi overwinter as eggs on the bird cherry tree Prunus padus. Branches of P. padus were collected at the late February / early March from 17 locations in Norway over a three-year period. We found 3599 overwintering aphid eggs, 59.5% of which were dead. Further, a total of 879 overwintering fungus-killed cadavers were observed. These cadavers were found close to bud axils, where overwintering eggs were also usually attached. Cadavers were infected with either Zoophthora cf. aphidis or Entomophthora planchoniana. All the fungal-killed cadavers were filled with overwintering structures of Z. cf. aphidis (as resting spores) or E. planchoniana (as modified hyphal bodies). We found a significant negative correlation between eggs and cadavers per branch. However, both numbers of eggs and cadavers varied greatly between years and among tree locations. This is the first report of E. planchoniana overwintering in R. padi cadavers as modified hyphal bodies. We discuss whether P. padus may act as an inoculum reservoir for fungi infecting aphids in cereals in spring.

Optimization of tree locations to reduce human heat stress in an urban park

Trees provide cooling benefits through shading and evapotranspiration; they are regarded as an important measure in heat-resilient urban planning and policies. Knowing where to plant trees for maximum cooling benefits, given practical and resource constraints, remains a challenge in both practice and research. Literature in the field of tree modeling and location optimization is limited, either by the incompleteness in accounting for tree shading, evapotranspiration, and the modifying effect of wind, or by the slow-running speed of the Computational Fluid Dynamics model, making them less applicable in practice. This paper describes a novel method to search for the optimal locations for trees to maximize their cooling benefits in an urban environment. A rapid simulation model was applied to assess on-site heat stress under the influences of trees, which was evaluated using field measurements conducted under hot, temperate, and cool weather conditions in an urban park in Hong Kong. It was then linked to a genetic algorithm in search of a near-optimal tree layout. The proposed method was tested in the same park, and it can automatically identify locations to plant new trees to minimize heat stress, subject to practical constraints such as avoiding existing buildings and utilities. It can also identify the optimal locations to rearrange the existing 55 trees, hypothetically, which can cool the park by up to 0.3 ℃ in on-site average equivalent temperature compared with the worse scenario. Trees can cool the most if they are concentrated on the leeward side of the park, rather than spread evenly. The proposed method runs significantly faster than existing approaches, and it can inform research and landscape design practices concerning park cooling as a goal.

Imaging the time course, morphology, neuronal tissue compression, and resolution of cerebral microhemorrhages in mice using intravital two-photon microscopy: insights into arteriolar, capillary, and venular origin.

Cerebral microhemorrhages (CMHs, microbleeds), a manifestation of age-related cerebral small vessel disease, contribute to the pathogenesis of cognitive decline and dementia in older adults. Histological studies have revealed that CMHs exhibit distinct morphologies, which may be attributed to differences in intravascular pressure and the size of the vessels of origin. Our study aimed to establish a direct relationship between the size/morphology of CMHs and the size/anatomy of the microvessel of origin. To achieve this goal, we adapted and optimized intravital two-photon microscopy-based imaging methods to monitor the development of CMHs in mice equipped with a chronic cranial window upon high-energy laser light-induced photodisruption of a targeted cortical arteriole, capillary, or venule. We assessed the time course of extravasation of fluorescently labeled blood and determined the morphology and size/volume of the induced CMHs. Our findings reveal striking similarities between the bleed morphologies observed in hypertension-induced CMHs in models of aging and those originating from different targeted vessels via multiphoton laser ablation. Arteriolar bleeds, which are larger (> 100μm) and more widely dispersed, are distinguished from venular bleeds, which are smaller and exhibit a distinct diffuse morphology. Capillary bleeds are circular and smaller (< 10μm) in size. Our study supports the concept that CMHs can occur at any location in the vascular tree, and that each type of vessel produces microbleeds with a distinct morphology. Development of CMHs resulted in immediate constriction of capillaries, likely due to pericyte activation and constriction of precapillary arterioles. Additionally, tissue displacement observed in association with arteriolar CMHs suggests that they can affect an area with a radius of ~ 50μm to ~ 100μm, creating an area at risk for ischemia. Longitudinal imaging of CMHs allowed us to visualize reactive astrocytosis and bleed resolution during a 30-day period. Our study provides new insights into the development and morphology of CMHs, highlighting the potential clinical implications of differentiating between the types of vessels involved in the pathogenesis of CMHs. This information may help in the development of targeted interventions aimed at reducing the risk of cerebral small vessel disease-related cognitive decline and dementia in older adults.

Developing a three-dimensional urban surface model for spatiotemporal analysis of thermal comfort with respect to street direction

Understanding the urban heat problem, which is intensifying owing to urbanization and climate change, has become a great challenge. Evaluating the thermal environment of urban spaces and predicting changes based on urban planning are essential for developing optimal urban cooling plans. This study addresses the pressing challenge of urban heat by developing a three-dimensional urban surface model (3D-USM) and conducting spatiotemporal thermal comfort simulations, providing valuable insights for the development of effective urban cooling strategies in the face of urbanization and climate change. Mean radiant temperature (MRT), the key element of thermal comfort of humans by reflecting complex urban environments was simulated in east-west streets which are vulnerable to heat, and results demonstrate that a small change of street angle has a significant effect on pedestrian thermal comfort. Specifically, at 0900 LST, the southern sidewalk of the street rotated by 12.5° was more vulnerable than the northern sidewalk. This resulted in a shift in the optimal location of trees that provide effective cooling, highlighting the importance of considering street orientation in the placement of urban greenery. This suggests that spatiotemporal thermal comfort simulations considering urban form in detail are necessary to efficiently cool the city. The proposed 3D-USM, capable of accurately and efficiently simulating the thermal environment and MRT thermal comfort in complex urban environments using simple input data, holds great potential for guiding the development of efficient cooling strategies to foster sustainable cities.

Designing profitable and climate-smart farms using virtual reality.

Many pastoral farmers are searching for ways to lower the carbon emission footprint that is generated by livestock. Planting trees on the farm is currently a popular option for farmers to offset their emissions yet requires knowledge of suitable tree species and locations to plant them. This paper describes a decision-support tool aimed at helping farmers to create and visualise different planting designs while balancing the objectives of sequestering carbon and maintaining farm profitability. We take an innovative approach by combining virtual reality technology with biophysical models to create an environment where the user can actively create virtual future farm scenarios. Through the creation process, the user can simultaneously balance multiple objectives including farm aesthetics, economic returns, business and environmental ambitions, and carbon emissions (net) balance. For this proof-of-concept study, we incorporate virtual reality technology in Unreal Engine, environmental and financial data, and high-resolution spatial layers from an operational 400-hectare livestock farm in New Zealand.

Assessment and representation of Urban Trees Ecosystem Services: a case study in Pryzamkovyi park

Abstract The research was aimed at verification of the possibility and expediency of applying i-Tree Eco tools in order to assess the value of ecosystem trees and bushes by the example of one of the parks in Ukraine and representation of the obtained information on an interactive map. For this purpose, the inventory of 228 urban trees in Pryzamkovyi park was conducted and the possibility of its adjustment to the conditions in Ukraine was assessed. The obtained information was analysed and visualised, and the advantages and disadvantages of this process were determined. The scope of the provided ecosystem services for park spaces was specified and it was determined that urban trees in Pryzamkovyi park have a €12.38 million replacement value and the average indicator of annual usefulness of ecosystem services provided by one tree plant or one bush plant in the park is equal to €15.75 per year, according to i-Tree Eco assessment. In order to improve the process of obtaining, processing and visualising materials, an orthophotomap based on unmanned aerial vehicle survey materials was applied. It allowed increasing the accuracy and improving the visualisation of the geolocation of trees and bushes. In order to familiarise a greater number of users with this information, electronic maps of vegetation that display the location of trees and bushes and their ecosystem services, both in quantity and monetary terms, were offered. The peculiarity and the scientific novelty of the approaches to solving the assigned task is the improvement of the process of informing the interested parties about the ecosystem services of a specific tree in the park and green plantations in the park as a whole. The suggested approaches to assessing the value of urban trees and their ecosystem services give ground to emphasise the value of these plants for urban ecosystems, to substantiate the expediency of implementing environmental measures as well as the need to increase the funding of these measures as a compensation for the services provided by trees and plants. At the same time, it is worth mentioning the expediency of conducting further research on this subject and the related issues, which requires follow-up studying.

Forest Vertical Structure Mapping Using Multi-Seasonal UAV Images and Lidar Data via Modified U-Net Approaches

With the acceleration of global warming, research on forests has become important. Vertical forest structure is an indicator of forest vitality and diversity. Therefore, further studies are essential. The investigation of forest structures has traditionally been conducted through in situ surveys, which require substantial time and money. To overcome these drawbacks, in our previous study, vertical forest structure was mapped through machine learning techniques and multi-seasonal remote sensing data, and the classification performance was improved to a 0.92 F1-score. However, the use of multi-seasonal images includes tree location errors owing to changes in the timing and location of acquisition between images. This error can be reduced by using a modified U-Net model that generates a low-resolution output map from high-resolution input data. Therefore, we mapped vertical forest structures from a multi-seasonal unmanned aerial vehicle (UAV) optic and LiDAR data using three modified U-Net models to improve mapping performance. Spectral index maps related to forests were calculated as optic images, and canopy height maps were produced using the LiDAR-derived digital surface model (DSM) and digital terrain model (DTM). Spectral index maps and filtered canopy height maps were then used as input data and applied to the following three models: (1) a model that modified only the structure of the decoder, (2) a model that modified both the structure of the encoder and decoder, and (3) a model that modified the encoder, decoder, and the part that concatenated the encoder and decoder. Model 1 had the best performance with an F1-score of 0.97. The F1-score value was higher than 0.9 for both Model 2 and Model 3. Model 1 improved the performance by 5%, compared to our previous research. This implies that the model performance is enhanced by reducing the influence of position error.

Studi habitat Meranti Merah di Desa Oki Lama Kecamatan Namrole Kabupaten Buru Selatan

This study aims to determine the Red Meranti species' growing place (habitat) (Shorea selanica B.L) in Oki Lama Village, Namrole District, South Buru Regency. This research was carried out by sampling method; 100 m x 100m observation blocks were taken, and vegetation data were taken utilizing pathways with a systematic sampling inventory method. Vegetation analysis to determine relative density dominance, relative dominance, frequency, relative frequency, and essential value index. The types of trees found in the research location of red meranti trees, pulai, resin, Langsatt, and durian. On line 2 can be seen the largest INP value in red meranti trees, amounting to 249.4641. The habitat conditions of the Red Meranti tree (Shorea selenic) found during the study were all trees growing in places with kambisol soil types overgrown with shrubs with hilly and mountainous conditions at an altitude of 134 m above sea level. At the research site, the air temperature of all trees was 29 ° C and 30 ° C, as well as soil pH and soil moisture, where the pH was 6.2 and 7.06, and light intensity ranged from 212-583 lux.

Synthesis of the parameters of a nonlinear predictive model using a genetic algorithm

The article deals with the definition and estimation of the parameters of a nonlinear regression model using a genetic algorithm. Parameter estimation is a type of optimization problem that can be solved using stochastic algorithms, which presents the possibility of using such algorithms to fit nonlinear regression models. The trees data set, which displays the non-linear relationship between traits, was investigated. The nonlinear method of least squares (NLS) was used to find the coefficients of the regression equation using a genetic algorithm on the trees data set belonging to the spuRs library. The set contains 1200 observations and three variables: tree ID; age of the tree; volume of wood. Visual analysis revealed the presence of additional signs that affect the volume of wood. Only data for trees with a certain location are selected for further work. As a result, the sample has 12 observations and two variables. The dependence of the volume of wood (Vol) on the age of the tree (Age) was analyzed. Attention to tree locations made it possible to choose the Richards logistic function as a functional dependence, nonlinear both in terms of parameters and variables. A genetic algorithm was used to estimate the parameters of the Richards function. The result of the work of the genetic algorithm depends on how its parameters are configured. When implementing the genetic algorithm, the following parameters were set: population size; the maximum number of iterations after which the work of the genetic algorithm stops; the number of consecutive generations without any improvement in the value of the fitness function before stopping the algorithm. A random scheme was used for the selection operation. A mutation operation involves changing a randomly selected bit. The type of crossover operation is one-point. Coefficients of nonlinear models were calculated for randomly selected tree locations. The coefficient of determination R2 was used to assess the quality of the models.

Estimating Individual Tree Mortality in the Sierra Nevada Using Lidar and Multispectral Reflectance Data

AbstractWidespread tree mortality events occur during periods of severe drought in temperate conifer forests and are expected to become more frequent in many areas due to climate change. Improved mapping of individual tree mortality is needed to identify risk factors and design effective conservation strategies. In this study, we used National Ecological Observatory Network (NEON) lidar and multispectral reflectance airborne observations to map individual tree mortality over a 160 km2 area during and after the 2012–2016 drought for two sites in California's Sierra National Forest. We used NEON lidar to derive tree locations and crown perimeters and multispectral data to map tree mortality for more than 1 million trees. We found that 25.4% of the trees in our study area died between 2013 and 2017, with considerably higher mortality at the lower‐elevation Soaproot Saddle site. Between 2017 and 2019, an additional 2.0%–2.8% of the trees died each year. Two wildfires in 2020 and 2021 increased tree mortality within burned area perimeters by 49%–89% between 2019 and 2021. Consistent with previous work, we found that tree mortality risk increased as a function of tree height. Tree mortality was positively associated with distance from rivers, trees per hectare, and decreasing slope at the lower elevation site. In contrast, increasing slope was positively associated with tree mortality at the higher elevation site. Our approach and dataset provide a means to study the combined effects of drought and wildfire on tree mortality and may improve projections of forest resilience under a changing climate.

Using machine learning to identify urban forest crown bounding boxes (CBB): Exploring a new method to develop urban forest policy

Collecting and managing individual tree data is a critical activity for green sustainability strategies. Local governments are able to easily collect detailed public tree inventories, however data on trees located on private land are much more challenging and costly to collect. This means that new regulations to limit the removal of trees on private land go untested prior to their implementation, or fail to pass regulatory review processes. Without knowledge of the location of trees or the range of their different sizes, Local Government Authorities (LGAs) are unable to predict where a new policy to prohibit the removal of trees of a certain size is likely to have the greatest effect, where enforcement should be concentrated, or to convince government, the development sector and local communities of the need for action to preserve trees.The aim of this study was to explore the potential of a supervised machine learning algorithm as a cost-efficient method to understand tree sizes and locations on private land and to discuss how this information could be used for sustainable urban greening. We conclude by discussing some of the affordances of this approach to better target native vegetation protection and protect large trees; and report on the precision and recall of the detection of the urban forest.

Evaluation of the non-climatic (age-related) trends of stable oxygen and carbon isotopes in Swiss stone pine (Pinus cembra L.) tree rings from the Eastern Carpathians, Romania

The presence, magnitude, and duration of age and/or size-related trends in the stable isotopes in tree-ring cellulose time series has been a subject of scientific debate. Where present, their evaluation and removal are key to the development of robust climate calibrations and reconstructions, especially in the low-frequency domain and where sample replication levels are low. Where reported, results suggest that the age/size/height-related trend of stable oxygen (δ18O) and carbon (δ13C) isotope compositions in tree-ring cellulose may vary according to the tree species and the individual tree location. For this reason, it is important when developing long palaeoclimate reconstructions for a new species, geographical region or ecological setting to perform studies to investigate non-climatic (age-related) trends. This study evaluates the ontogenetic pattern in the δ18O and δ13C data in Swiss stone pine trees from the Eastern Carpathians, Romania. For this, we used a new multi-centennial dataset consisting of 5 living and 10 relict Swiss stone pine samples collected from the Eastern Carpathians, which were annually resolved for δ18O and δ13C composition. Age-related trends were evaluated using the conventional “slope of the mean” approach as well as the “mean of the slope” method. The results suggest that neither the traditional “slope-of-the mean” nor the “mean-of-the-slope” approach indicates a persistent linear trend in the Swiss stone pine δ18O data, while for the δ13C data a systematic enrichment in 13C was observed over a < 40 year-long period after germination. Despite the limited sample size of this developing dataset these findings help to inform more detailed analyses and future sampling strategies in the Eastern Carpathian Swiss stone pine stands.

Feasibility of Low-Cost LiDAR Scanner Implementation in Forest Sampling Techniques

Despite the growing impact of remote sensing technology in forest inventories globally, there is a continuous need for ground measurements on sample plots. Even though the newest volume assessment methodology requires fewer sample plots, the accuracy of ground-recorded data influences the final accuracy of forest stand modeling. Therefore, effective and economically justified tools are in the continuous interest of foresters. In the presented research, a consumer-grade light detection and ranging (LiDAR) sensor mounted on iPad was used for forest inventory sample plot data collection—including tree location and diameter breast height. In contrast to other similar research, feasibility and user-friendliness were also documented and emphasized. The study was conducted in 63 real sample plots used for the inventory of Polish forests. In total, 776 trees were scanned in 3 types of forest stands: pine, birch, and oak. The root mean square error was 0.28 m for tree locations and 0.06 m for diameter breast height. Various additional analyses were performed to describe the usage of an iPad in tree inventories. It was contended that low-cost LiDAR scanners might be successfully used in real forest conditions and can be considered a reliable and easy-to-implement tool in forest inventory measurements.