Sample Trees Research Articles

Genotype-Environment Interaction and Horizontal and Vertical Distributions of Heartwood for Acacia melanoxylon R.Br.

Acacia melanoxylon (blackwood) is a valuable wood with excellent-quality heartwood extensively utilized worldwide. The main aim of this study was to confirm the horizontal and vertical variation and provide estimated values of genetic gains and clonal repeatabilities for improving breeding program of A. melanoxylon. Six blackwood clones at 10 years old were analyzed in Heyuan and Baise cities in China. Stem trunk analysis was conducted for sample trees to explore the differences between heartwood and sapwood. The heartwood radius (HR), heartwood area (HA), and heartwood volume (HV) in heartwood properties decreased as tree height (H) in growth traits increased, and the HV = 1.2502 DBH (diameter at breast height)1.7009 model can accurately estimate the heartwood volume. Furthermore, G × E analysis showed that the heritabilities of the eleven indices, including DBH, DGH (diameter at ground height), H, HR, SW (sapwood width), BT (bark thickness), HA, SA (sapwood area), HV, HRP (heartwood radius percentage), HAP (heartwood area percentage), and HVP (heartwood volume percentage) were between 0.94 and 0.99, and repeatabilities of the eleven indices were between 0.74 and 0.91. Clonal repeatability of DBH (0.91), DGH (0.88), and H (0.90) in growth traits, HR (0.90), HVP (0.90), and HV (0.88) in heartwood properties were slightly higher than for SA (0.74), SW (0.75), HAP (0.75), HRP (0.75), and HVP (0.75). These data also implied that the growth characteristics of heartwood and sapwood of blackwood clones were less affected by the environment and had substantial heritability.

AN ITS GENE-MEDIATED MOLECULAR DETECTION OF FUNGI ASSOCIATED WITH NATURAL AND ARTIFICIAL AGARWOOD FROM Aquilaria malaccensis

The current study examined fungal diversity in manufactured and natural agarwood samples perceived from A. malecensis trees in a plantation and the East Malaysia rainforest. Isolated fungi were also subjected to molecular analysis. The fungal community composition of healthy and damaged tree samples from both plantation and the wild forest was identified using PCR amplification of the internal transcribed spacer (ITS) region from fungal isolates. Meanwhile, ten groups of fungi isolates are expected to be placed in both natural and inoculated based on 1000 bootstrap values. They validated earlier genomic identification; 55 fungal isolates were discovered in artificial and natural agarwood, including agarwood and healthy wood. Ten fungal groupings were developed based on morphological characterization similarities. Based on NCBI BLAST analysis, molecular identification revealed Fusarium solani, Botryosphaeria theobromae, Polyporales spp, Schizophyllum commune, Aspergillus aculeatus, and Lasiodiplodia theobromae. Fusarium solani excelled in A. aculeatus and Polyporales spp. in agarwood samples and healthy wood. The presence of more fungi species in natural agarwood than in artificial agarwood may be due to the favourable humid and shaded habitat for fungal growth. Nonetheless, synthetic agarwood was able to synthesize agarwood-related chemical compounds. Considering F. solani was often identified in both agarwood, agarwood inoculant may act as a booster for F. solani to begin pathogenicity in artificial agarwood. The current research shows that artificial agarwood may provide quality comparable to natural agarwood and is not influenced by fungus interacting with the tree.

Machine Learning: Volume and Biomass Estimates of Commercial Trees in the Amazon Forest

Accurate estimation of the volume and above-ground biomass of exploitable trees by the practice of selective logging is essential for the elaboration of a sustainable management plan. The objective of this study is to develop machine learning models capable of estimating the volume and biomass of commercial trees in the Southwestern Amazon, based on dendrometric, climatic and topographic characteristics. The study was carried out in the municipality of Porto Acre, Acre state, Brazil. The volume and biomass of sample trees were determined using dendrometric, climatic and topographic variables. The Boruta algorithm was applied to select the best set of variables. Support Vector Machines (SVM), Artificial Neural Networks (ANN), Random Forests (RF) and the Generalized Linear Model (GLM) were the machine learning methods evaluated. In general, the evaluated methods showed a satisfactory generalization power. The results showed that the volume and biomass predictions of commercial trees in the Amazon rainforest differed between the techniques (p < 0.05). ANNs showed the best performance in predicting the volume and biomass of commercial trees, with the highest ryŷ and the lowest RSME and MAE. Thus, machine learning methods such as SVM, ANN, RF and GLM are shown to be useful and efficient tools for estimating the volume and biomass of commercial trees in the Amazon rainforest. These methods can be useful tools to improve the accuracy of estimates in forest management plans.

Automated Segmentation of Individual Tree Structures Using Deep Learning over LiDAR Point Cloud Data

Deep learning techniques have been widely applied to classify tree species and segment tree structures. However, most recent studies have focused on the canopy and trunk segmentation, neglecting the branch segmentation. In this study, we proposed a new approach involving the use of the PointNet++ model for segmenting the canopy, trunk, and branches of trees. We introduced a preprocessing method for training LiDAR point cloud data specific to trees and identified an optimal learning environment for the PointNet++ model. We created two learning environments with varying numbers of representative points (between 2048 and 8192) for the PointNet++ model. To validate the performance of our approach, we empirically evaluated the model using LiDAR point cloud data obtained from 435 tree samples scanned by terrestrial LiDAR. These tree samples comprised Korean red pine, Korean pine, and Japanese larch species. When segmenting the canopy, trunk, and branches using the PointNet++ model, we found that resampling 25,000–30,000 points was suitable. The best performance was achieved when the number of representative points was set to 4096.

Efficient Resistance Distance Computation: The Power of Landmark-based Approaches

Resistance distance is a fundamental metric to measure the similarity between two nodes in graphs which has been widely used in many real-world applications. In this paper, we study two problems on approximately computing resistance distance: (i) single-pair query which aims at calculating the resistance distance r(s, t) for a given pair of nodes (s, t); and (ii) single-source query which is to compute all the resistance distances r(s, u) for all nodes u in the graph with a given source node s. Existing algorithms for these two resistance distance query problems are often costly on large graphs. To efficiently solve these problems, we first establish several interesting connections among resistance distance, a new concept called v-absorbed random walk, random spanning forests, and a newly-developed v-absorbed push procedure. Based on such new connections, we propose three novel and efficient sampling-based algorithms as well as a deterministic algorithm for single-pair query; and we develop an online and two index-based approximation algorithms for single-source query. We show that the two index-based algorithms for single-source query take almost the same running time as the algorithms for single-pair query with the aid of a linear-size index. The striking feature of all our algorithms is that they are allowed to select an easy-to-hit node by random walks on the graph. Such an easy-to-hit landmark node v can make the v-absorbed random walk sampling, spanning tree sampling, as well as the v-absorbed push more efficient, thus significantly improving the performance of our algorithms. Extensive experiments on 5 real-life datasets show that our algorithms substantially outperform the state-of-the-art algorithms for two resistance distance query problems in terms of both running time and estimation errors.

Detecting Individual Plants Infected with Pine Wilt Disease Using Drones and Satellite Imagery: A Case Study in Xianning, China

In recent years, remote sensing techniques such as satellite and drone-based imaging have been used to monitor Pine Wilt Disease (PWD), a widespread forest disease that causes the death of pine species. Researchers have explored the use of remote sensing imagery and deep learning algorithms to improve the accuracy of PWD detection at the single-tree level. This study introduces a novel framework for PWD detection that combines high-resolution RGB drone imagery with free-access Sentinel-2 satellite multi-spectral imagery. The proposed approach includes an PWD-infected tree detection model named YOLOv5-PWD and an effective data augmentation method. To evaluate the proposed framework, we collected data and created a dataset in Xianning City, China, consisting of object detection samples of infected trees at middle and late stages of PWD. Experimental results indicate that the YOLOv5-PWD detection model achieved 1.2% higher mAP compared to the original YOLOv5 model and a further improvement of 1.9% mAP was observed after applying our dataset augmentation method, which demonstrates the effectiveness and potential of the proposed framework for PWD detection.

A Comparison between the Standard Heterogeneity Test and the Simplified Segregation Free Analysis for Sampling Protocol Optimisation

Estimating the heterogeneity of base and precious metal mineralisation is a great challenge for mining engineers and geologists who undertake resource evaluation, grade control and reconciliation. The calculation of the minimum broken sample mass to represent a given lot of mineralisation at a given comminution size is based on the estimation of IHL, the constant factor of constitution heterogeneity. IHL can be derived by different heterogeneity testwork or calibration approaches. Three methodologies are well known in the mining industry: the standard heterogeneity test, the segregation free analysis, and the sampling tree experiment or duplicate sample analysis. However, the methodologies often show different results, especially when it comes to gold. These differences are due to many reasons. Assuming the variances added by sample preparation and analysis to be equivalent for all tests, the reasons for the differences may include the nugget effect (particularly the presence of coarse gold), the segregation effect and the procedure of collecting/splitting the samples when performing the tests. This paper analyses and compares two heterogeneity tests: the original heterogeneity test and the simplified segregation free analysis, both performed on mineralisation from different Brazilian operations. The results show clear differences between the tests, highlighting the complexity of estimating the heterogeneity of mineral deposits. The study reports the importance of using proper methodologies for constitution heterogeneity estimation so that minimum sample masses and relative standard deviations of the fundamental sampling error can be relied upon. It also provides recommendations for practitioners on the application of testwork/calibration studies.

Tree Species Classification in a Complex Brazilian Tropical Forest Using Hyperspectral and LiDAR Data

This study experiments with different combinations of UAV hyperspectral data and LiDAR metrics for classifying eight tree species found in a Brazilian Atlantic Forest remnant, the most degraded Brazilian biome with high fragmentation but with huge structural complexity. The selection of the species was done based on the number of tree samples, which exist in the plot data and in the fact the UAV imagery does not acquire information below the forest canopy. Due to the complexity of the forest, only species that exist in the upper canopy of the remnant were included in the classification. A combination of hyperspectral UAV images and LiDAR point clouds were in the experiment. The hyperspectral images were photogrammetric and radiometric processed to obtain orthomosaics with reflectance factor values. Raw spectra were extracted from the trees, and vegetation indices (VIs) were calculated. Regarding the LiDAR data, both the point cloud—referred to as Peak Returns (PR)—and the full-waveform (FWF) LiDAR were included in this study. The point clouds were processed to normalize the intensities and heights, and different metrics for each data type (PR and FWF) were extracted. Segmentation was preformed semi-automatically using the superpixel algorithm, followed with manual correction to ensure precise tree crown delineation before tree species classification. Thirteen different classification scenarios were tested. The scenarios included spectral features and LiDAR metrics either combined or not. The best result was obtained with all features transformed with principal component analysis with an accuracy of 76%, which did not differ significantly from the scenarios using the raw spectra or VIs with PR or FWF LiDAR metrics. The combination of spectral data with geometric information from LiDAR improved the classification of tree species in a complex tropical forest, and these results can serve to inform management and conservation practices of these forest remnants.

Density and Seasoning Characteristics of Pinus caribaea Lumber Grown at Suba Forest, Oromia, Ethiopia

Determination of the seasoning characteristics, physical and mechanical properties of lumber species is helpful in identifying the main factors affecting the quality, suitability and overall performance of wood and wood-based products. The Pinus caribaea has been considered as industrial lumber species and there is a little study conducted in identifying the physical characteristics which on turn affects the quality of product derived from the lumber. Therefore, this study aimed at evaluating the density and seasoning characteristics of P. caribaea lumber. Sample trees were harvested from Suba Forest Oromia, Ethiopia. The experiments were carried out using air and kiln seasoning methods. To measure the initial moisture content, seasoning rate, shrinkage, wood density, and seasoning defects, six replicates of samples from each tree portions were prepared when green and promptly weighed. Analysis of variance (ANOVA) has been employed in interpreting the experimental results. The obtained results have shown that the mean initial moisture content for air stacks was 78.2% while for the kiln seasoning stacks 82.9%. Seasoning time for sawn boards of 3 cm thick to reach 17% moisture continent (MC) required 61 days, while for kiln seasoning took 4.3 days to reach 14.62% MC. This showed that kiln seasoning was about 14 times faster than air seasoning. In air seasoning the MC (%) of the lumber from 78.2% to 16.9%; and, the obtained mean values of shrinkages were tangential (3.6%), radial (1.9%) and volumetric (5.4%). The initial moisture content (IMC) and green density (GD) of the lumber were significant difference along the tree height at a 95% probability level. The seasoning rate % and final MC (%) along the tree height were significant difference at 95% probability level, while the seasoning rate % and final MC were significant difference between seasoning methods at 99% probability level. Seasoning defects such as cup, bow, twist, and crook were observed on kiln seasoned. In addition, end checks and splits were observed on air seasoned boards. Therefore, the experimental factors should be monitored and optimized properly to obtain the lumber with good quality and utilize it for different purposes, including construction and industrial applications.

Statistical summaries of unlabelled evolutionary trees.

Rooted and ranked phylogenetic trees are mathematical objects that are useful in modelling hierarchical data and evolutionary relationships with applications to many fields such as evolutionary biology and genetic epidemiology. Bayesian phylogenetic inference usually explores the posterior distribution of trees via Markov chain Monte Carlo methods. However, assessing uncertainty and summarizing distributions remains challenging for these types of structures. While labelled phylogenetic trees have been extensively studied, relatively less literature exists for unlabelled trees that are increasingly useful, for example when one seeks to summarize samples of trees obtained with different methods, or from different samples and environments, and wishes to assess the stability and generalizability of these summaries. In our paper, we exploit recently proposed distance metrics of unlabelled ranked binary trees and unlabelled ranked genealogies, or trees equipped with branch lengths, to define the Fréchet mean, variance and interquartile sets as summaries of these tree distributions. We provide an efficient combinatorial optimization algorithm for computing the Fréchet mean of a sample or of distributions on unlabelled ranked tree shapes and unlabelled ranked genealogies. We show the applicability of our summary statistics for studying popular tree distributions and for comparing the SARS-CoV-2 evolutionary trees across different locations during the COVID-19 epidemic in 2020. Our current implementations are publicly available at https://github.com/RSamyak/fmatrix.

Mitochondrial Genome Uncovered Hidden Genetic Diversity in Microdous chalmersi (Teleostei: Odontobutidae)

The Hainan small-toothed sleeper, Microdous chalmersi, is an endemic species disjunctly distributed in Hainan and Guangxi provinces of China. Morphological differences have been previously observed between these populations. We sequenced the mitochondrial genomes of M. chalmersi from Hainan and Guangxi in order to test whether there is a cryptic species. We reconstructed a phylogenetic tree of samples collected from the two populations along with eight representative species of other odontobutids using thirteen mitochondrial coding genes and two rRNA genes. The results showed that five individuals of M. chalmersi from each population clustered into reciprocal monophyletic clades. Furthermore, genetic distance between individuals of the two populations was much larger than that between individuals from the same population. The genetic distance between the two Microdous populations was comparable to interspecific genetic distance of a closely related genus, Odontobutis. We propose that M. chalmersi from Guangxi and Hainan could belong to two different species, but detailed morphological and genetic studies should be carried out to test this hypothesis.

East Timor as an important source of cashew (Anacardium occidentale L.) genetic diversity.

Cashew (Anacardium occidentale L.) is a crop currently grown in several tropical countries because of the economic importance of cashew nuts. Despite its enormous economic worth, limited research has been conducted on the molecular diversity of cashew genetic resources. In this study, a wide comprehensive assessment of the genetic diversity of cashew trees in East Timor was performed using microsatellites (SSRs) to evaluate intraspecific diversity and population structuring. A total of 207 individual cashew trees, including trees from East Timor (11), and outgroup populations from Indonesia (one) and Mozambique (two), were analyzed with 16 cashew-specific SSRs. A comprehensive sampling of cashew trees within East Timor was performed, covering the distribution of cashew orchards in the country. Genetic diversity indices were calculated, and population structuring was determined using three different approaches: genetic distances (UPGMA and NJ), AMOVA, and individual-based clustering methods through Bayesian (STRUCTURE) and multivariate (DAPC) analyses. The population structuring analysis revealed that the genetic diversity of cashew populations in East Timor was higher in this study than previously reported for cashew trees. A higher allelic richness was found within cashew populations in East Timor compared with the outgroup populations (Mozambique and Indonesia), reinforced by the presence of private alleles. Moreover, our study showed that cashew populations in East Timor are grouped into two dissimilar genetic groups, which may suggest multiple cashew introductions over time. These new cashew genetic resources could be explored for future crop improvement. Crop diversity underpins the productivity, resilience, and adaptive capacity of agriculture. Therefore, this study provides useful information regarding genetic diversity and population structure that can be harnessed to improve cashew production in East Timor. This data is also important to creating a country-specific genetic cashew signature to increase cashew market value.

Streptomyces phytophilus sp. nov., an endophytic actinobacterium with biosynthesis potential as an antibiotic producer.

An endophytic actinobacterium, strain PIP175T, was isolated from the root sample of a native apricot tree (Pittosporum angustifolium) growing on the Bedford Park campus of Flinders University, Adelaide, South Australia. This strain is a Gram stain-positive, aerobic actinobacterium with well-developed substrate mycelia. Aerial mycelia rarely produce spores and the spore chain is spiral. Strain PIP175T showed the highest 16S rRNA gene sequence similarity to Streptomyces aculeolatus DSM 41644T (99.4 %). Other closely related phylogenetic representatives include Streptomyces synnematoformans DSM 41902T (98.3 %), Streptomyces albospinus NBRC 13846T (97.6 %), Streptomyces cacaoi subsp. cacaoi NRRL B-1220T (97.5 %) and Streptomyces ruber NBRC 14600T (97.4 %). The major cellular fatty acid of this strain was iso-C16 : 0 and the major menaquinone was MK-9(H6). The whole-cell sugar contained galactose, glucose and mannose. Chemotaxonomic data confirmed that strain PIP175T belonged to the genus Streptomyces. Digital DNA-DNA hybridization, average nucleotide identity based on blast and OrthoANIu results between strain PIP175T and S. aculeolatus DSM 41644T were 60.0, 94.1 and 94.9 %, respectively. Genotypic and phenotypic data and genome analysis results allowed the differentiation of strain PIP175T from its closest species with validly published names. Strain PIP175T showed good activity against methicillin-resistant Staphylococcus aureus 03120385. Genome mining of strain PIP175T revealed biosynthetic genes encoding proteins relating to antibiotic production, plant growth promotion and biodegradation enzymes. The name proposed for the new species is Streptomyces phytophilus sp. nov. The type strain is PIP175T (=DSM 103379T=TBRC 6026T).

An Investigation on the Relationship Between Mineral Nutrition of Lemon and Rumple

This study investigated the relationship between Rumple and tree crown parts regarding direction, fruit development stages and fruit rind nutrient content. A Lemon orchard on which Rumple disorders have shown severely were chosen among Erdemli and Silifke region where the majority of grown lemon cultivar is Kütdiken. In this orchard, from healthy and contaminated trees samples were taken from the South and West half parts of crown and the North and East parts of the crown separately. Also, fruit samples were taken at four fruit development stages which were hazelnut-sized fruit, end of fruit enlargement, the beginning of maturation and fully mature fruit stages. The rind of samples fruit was analyzed, and their content of N, P, K, Ca, Mg, S, Mn, Fe, Zn, B, Cl and Na was determined. PCA was used to analyze these data. Biplot scheme of the 2nd Sampling from the part one-half of the trees which includes the South and West directions, that is, from the Healthy (G2S) and Rumple signed trees (G2B) taken were examined. The increase in K, Zn, Fe, Ca, and Mg is associated with Na, P and Cl concentration reduction. Besides this, in this period, it was observed that fruit rind has higher N, S, Mn and B content which were taken from part one, that is, the South and West sides, of healthy plants. The relationship identified here is important because Rumple’s symptoms become visible after this stage.

Tree Architecture Model and Tree Health Assessment Using Sonic 3D Tomograph Relationship in Bali Botanical Garden

The incident of fallen trees or broken branches is dangerous for tourists visiting Bali Botanical Garden. Tree health monitoring in locations with high human activity and near valuable properties is mandatory to minimize the potency of tree failure. Since the stand stability is influenced by biological and physical factors, multiple variables consisting of species characteristics (stem form), tree dimensions (height, diameter, and slenderness coefficient), and tree health were used as parameters of tree health. The aim of this study is to examine the health condition of trees located in XIV.G Bali Botanical Garden and to identify the most significant morphological character related to the result of tomograph measurement. A purposive sampling technique was adopted for locations which highly visited. A total of 80 trees were examined as samples to measure tree health. The evaluation used visual observation and tomograph technology. The result showed the most tree defect found were branches covered with epiphyte and moss. However, tomograph examination found only one tree classified at high risk (Bischofia javanica) and seven trees classified at medium risk (Syzygium polyanthum, Syzygium racemosum, Bischofia javanica, Pittosporum mollucanum, Pittosporum sp. and Dacrycarpus imbricatus (2 trees)). This study suggests the use of tree architecture model as the most significant morphological character on tree samples with medium decay.

Rational design of a survey protocol for avocado sunblotch viroid in commercial orchards to demonstrate pest freedom.

Avocado sunblotch viroid (ASBVd) is a subcellular pathogen of avocado that reduces yield from a tree, diminishes the appearance of the fruit by causing unsightly scarring and impedes trade because of quarantine conditions that are imposed to prevent spread of the pathogen via seed-borne inoculum. For countries where ASBVd is officially reported, permission to export fruit to another country may only be granted if an orchard can be demonstrated to be a pest free production site. The survey requirements to demonstrate pest freedom are usually defined in export protocols that have been mutually agreed upon by the trading partners. In this paper, we introduce a flexible statistical protocol for use in optimizing sampling strategies to establish pest free status from ASBVd in avocado orchards. The protocol, which is supported by an interactive app, integrates statistical considerations of multistage sampling of trees in orchards with a RT-qPCR assay allowing for detection of infection in pooled samples of leaves taken from multiple trees. While this study was motivated by a need to design a survey protocol for ASBVd, the theoretical framework and the accompanying app have broader applicability to a range of plant pathogens in which hierarchical sampling of a target population is coupled with pooling of material prior to diagnosis.

Tree Biomass and Leaf Area Allometric Relations for Betula pendula Roth Based on Samplings in the Western Carpathians.

Biomass allometric relations are necessary for precise estimations of biomass forest stocks, as well as for the quantification of carbon sequestered by forest cover. Therefore, we attempted to create allometric models of total biomass in young silver birch (Betula pendula Roth) trees and their main components, i.e., leaves, branches, stem under bark, bark, and roots. The models were based on data from 180 sample trees with ages up to 15 years originating from natural regeneration at eight sites in the Western Carpathians (Slovakia). Sample trees represented individuals with stem base diameters (diameter D0) from about 4.0 to 113.0 mm and tree heights between 0.4 to 10.7 m. Each tree component was dried to constant mass and weighed. Moreover, subsamples of leaves (15 pieces of each tree) were scanned, dried, and weighed. Thus, we also obtained data for deriving a model expressing total leaf area at the tree level. The allometric models were in the form of regression relations using diameter D0 or tree height as predictors. The models, for instance, showed that while the total tree biomass of birches with a D0 of 50 mm (and a tree height of 4.06 m) was about 1653 g, the total tree biomass of those with a D0 of 100 mm (tree height 6.79 m) reached as much as 8501 g. Modeled total leaf areas for the trees with the above-mentioned dimensions were 2.37 m2 and 8.54 m2, respectively. The results prove that diameter D0 was a better predictor than tree height for both models of tree component biomass and total leaf area. Furthermore, we found that the contribution of individual tree components to total biomass changed with tree size. Specifically, while shares of leaves and roots decreased, those of all other components, especially stems with bark, increased. The derived allometric relations may be implemented for the calculation of biomass stock in birch-dominant or birch-admixed stands in the Western Carpathians or in other European regions, especially where no species- and region-specific models are available.

Description of Laimaphelenchus shanxiensis sp. n. (Rhabditida: Aphelenchoididae) from Shanxi province, P.R. China

Summary Laimaphelenchus shanxiensis sp. n. was recovered from the bark samples of Chinese pine tree (Pinus tabuliformis) in Shanxi province, China. The new species is characterised by having 888-1049 μm long females, the cephalic region with six labial sectors divided by ribs, stylet 11-13 μm long, the excretory pore located at the same level with, or slightly posterior to nerve ring, lateral field with four incisures, post-vulval uterine sac 54-83 μm long, vulva with a well-developed anterior flap, tail having a single stalk at terminus ending to a flat structure with 4-7 finger-like appendages in scanning electron microscopy; male spicules 20-22 μm long and two pairs of caudal papillae present. In addition, molecular phylogenetic trees inferred from the partial small subunit (SSU) and D2-D3 segments of large subunit (LSU) of rRNA genes, revealed that this nematode belongs to the Laimaphelenchus and is different from all currently sequenced species of Laimaphelenchus for their SSU and LSU markers.

Влияние аэротехногенных выбросов магнезитового производства на надземную фитомассу Betula pendula Roth в зависимости от плодородия почвы

The study of the test crop European birch elevated phytomass at the magnesite production impact zone (the Southern Urals, Satka) was carried out. Two plots of test crops of the same age (created in 1983) growing 3 km away from the source of technogenic pollution from magnesite production and with different soil fertility were studied. The elevated phytomass of the stand was calculated using sample trees. The selection of trees was carried out from different thickness levels within the entire range. A regression method was used to estimate the phytomass of the stand. In the course of our work, we tested the null hypothesis that soil fertility is a significant factor for the adaptation of the Betula pendula Roth to pollution since it was noted that stands on rich soils have the best growth (height, diameter) and the vital condition of the stand. A comparative analysis of the elevated phytomass of test crops with the same level of pollution by magnesite production emissions, but growing on soils of different fertility, allowed us to assess the effect of the soil factor on the ability of the European birch to adapt to technogenic pollution. Under the conditions of magnesite production emissions, the elevated phytomass of experimental Betula pendula Roth crops growing on highly fertile soils is not reduced to the same extent as that of birch growing on low-fertile soils. Under the negative emissions impact, the mass of wood and branches of the Betula pendula Roth growing on highly fertile soils decreases to a smaller extent than the mass of other fractions. The wood and branches weight of the Betula pendula Roth growing on highly fertile soils is 3.8 and 3.0 times higher, respectively, and the weight of leaves and bark is 2.3 and 2.4 respectively, compared with test plot No. 5 on low-fertile soils.

Ophiostomatální houby v porostech borovice lesní (Pinus sylvestris L.) postižených dlouhodobým suchem

In this study, presence of ophiostomatiod fungi (absence, presence) on wood cross-section samples (total 72) from freshly cut Scots pine (Pinus sylvestris L.) trees (total 24) at four sites (Valtice, Příšťpo, Brodce, Vrbová Lhota) affected by long-term drought was evaluated in relation to: sampling period (spring, summer, autumn), tree age (30–40, 50–90 years), wood sample origin (bottom trunk, middle trunk, twigs), tree defoliation (>25–60%, >60–99%), and presence of other taxa. Ophiostomatoid fungi were present on 33% wood cross-section samples from 50% trees. Presence of ophiostomatoid fungi was significantly different in relation to sampling period (i.e. the highest in autumn, the lowest in spring), and was directly proportional to both presence of mites and Nematocera larvae; it was insignificantly different in relation to site, tree age, wood sample origin, defoliation, and presence of other taxa. These results show: (1) frequent presence of ophiostomatoid fungi in wood tissues of Scots pine trees, (2) insignificant effect of ophiostomatoid fungi on health status of the trees, (3) relationship of presence of ophiostomatoid fungi with both presence of mites and Nematocera larvae.