Ubiquity of methanogenic archaea in the trunk of coniferous and broadleaved tree species in a mountain forest.

Wetwood of living trees is a habitat of methanogenic archaea, but the ubiquity of methanogenic archaea in the trunk of various trees has not been revealed. The present study analysed methanogenic archaeal communities inside coniferous and broadleaved trees in a cold temperate mountain forest by culture-dependent or independent techniques. Heartwood and sapwood segments were obtained from the trunk of seven tree species, Cryptomeria japonica, Quercus crispula, Fraxinus mandshurica, Acer pictum, Aesculus turbinata, Magnolia obovata, and Populus tremula. Amplicon sequencing analysis of 16S rRNA genes showed that Methanobacteriaceae predominated the archaeal communities and Methanomassiliicoccaceae also inhabited some trees. Real-time PCR analysis detected methanogenic archaeal mcrA genes from all the tree species, with a maximum of 107 copies g-1 dry wood. Digital PCR analysis also detected mcrA genes derived from Methanobacterium spp. and Methanobrevibacter spp. from several samples, with a maximum of 105 and 104 copies g-1 dry wood. The enumeration by the most probable number method demonstrated the inhabitation of viable methanogenic archaea inside the trees; 106 cells g-1 dry wood was enumerated from a heartwood sample of C. japonica. Methanogenic archaea related to Methanobacterium beijingense were cultivated from a heartwood sample of Q. crispula and F. mandshurica. The present study demonstrated that the inside of various trees is a common habitat for methanogenic archaeal communities and a potential source of methane in forest ecosystems.

Navigation of an Autonomous Spraying Robot for Orchard Operations Using LiDAR for Tree Trunk Detection.

Traditional Japanese orchards control the growth height of fruit trees for the convenience of farmers, which is unfavorable to the operation of medium- and large-sized machinery. A compact, safe, and stable spraying system could offer a solution for orchard automation. Due to the complex orchard environment, the dense tree canopy not only obstructs the GNSS signal but also has effects due to low light, which may impact the recognition of objects by ordinary RGB cameras. To overcome these disadvantages, this study selected LiDAR as a single sensor to achieve a prototype robot navigation system. In this study, density-based spatial clustering of applications with noise (DBSCAN) and K-means and random sample consensus (RANSAC) machine learning algorithms were used to plan the robot navigation path in a facilitated artificial-tree-based orchard system. Pure pursuit tracking and an incremental proportional-integral-derivative (PID) strategy were used to calculate the vehicle steering angle. In field tests on a concrete road, grass field, and a facilitated artificial-tree-based orchard, as indicated by the test data results for several formations of left turns and right turns separately, the position root mean square error (RMSE) of this vehicle was as follows: on the concrete road, the right turn was 12.0 cm and the left turn was 11.6 cm, on grass, the right turn was 12.6 cm and the left turn was 15.5 cm, and in the facilitated artificial-tree-based orchard, the right turn was 13.8 cm and the left turn was 11.4 cm. The vehicle was able to calculate the path in real time based on the position of the objects, operate safely, and complete the task of pesticide spraying.

Tree Trunk Recognition in Orchard Autonomous Operations under Different Light Conditions Using a Thermal Camera and Faster R-CNN.

In an orchard automation process, a current challenge is to recognize natural landmarks and tree trunks to localize intelligent robots. To overcome low-light conditions and global navigation satellite system (GNSS) signal interruptions under a dense canopy, a thermal camera may be used to recognize tree trunks using a deep learning system. Therefore, the objective of this study was to use a thermal camera to detect tree trunks at different times of the day under low-light conditions using deep learning to allow robots to navigate. Thermal images were collected from the dense canopies of two types of orchards (conventional and joint training systems) under high-light (12-2 PM), low-light (5-6 PM), and no-light (7-8 PM) conditions in August and September 2021 (summertime) in Japan. The detection accuracy for a tree trunk was confirmed by the thermal camera, which observed an average error of 0.16 m for 5 m, 0.24 m for 15 m, and 0.3 m for 20 m distances under high-, low-, and no-light conditions, respectively, in different orientations of the thermal camera. Thermal imagery datasets were augmented to train, validate, and test using the Faster R-CNN deep learning model to detect tree trunks. A total of 12,876 images were used to train the model, 2318 images were used to validate the training process, and 1288 images were used to test the model. The mAP of the model was 0.8529 for validation and 0.8378 for the testing process. The average object detection time was 83 ms for images and 90 ms for videos with the thermal camera set at 11 FPS. The model was compared with the YOLO v3 with same number of datasets and training conditions. In the comparisons, Faster R-CNN achieved a higher accuracy than YOLO v3 in tree truck detection using the thermal camera. Therefore, the results showed that Faster R-CNN can be used to recognize objects using thermal images to enable robot navigation in orchards under different lighting conditions.

Rotational Activity of Trunk Parts in Scots Pine Trees: Seasonal Dynamics and Patterns.

The seasonal dynamics and relationships between the characteristics of the angles of rotation of outer sapwood layers in trunks of Scots pine (Pinus sylvestris L.) trees growing in natural stands have been studied for two years in order to improve the understanding of the trunk twisting phenomenon and its role in the tree growth and morphogenesis. The trunk twisting phenomenon is observed in all trees during the entire vegetation period, and its characteristics do not depend on the exposition and differ in various trunk parts. The rotation angles and directions of rotation of the adjacent trunk parts are positively correlated with each other. The counterclockwise direction of rotation dominates, which provides an increase in the total rotation angle over time. The directions and values of the forces causing rotation of outer sapwood layers seem to be explained by the gradients of mechanical stresses appearing between neighboring xylem parts due to their nonuniform moisture content.

Application of Ground-Penetrating Radar for Detecting Internal Anomalies in Tree Trunks with Irregular Contours.

To assess the health conditions of tree trunks, it is necessary to estimate the layers and anomalies of their internal structure. The main objective of this paper is to investigate the internal part of tree trunks considering their irregular contour. In this respect, we used ground penetrating radar (GPR) for non-invasive detection of defects and deteriorations in living trees trunks. The Hilbert transform algorithm and the reflection amplitudes were used to estimate the relative dielectric constant. The point cloud data technique was applied as well to extract the irregular contours of trunks. The feasibility and accuracy of the methods were examined through numerical simulations, laboratory and field measurements. The results demonstrated that the applied methodology allowed for accurate characterizations of the internal inhomogeneity. Furthermore, the point cloud technique resolved the trunk well by providing high-precision coordinate information. This study also demonstrated that cross-section tomography provided images with high resolution and accuracy. These integrated techniques thus proved to be promising for observing tree trunks and other cylindrical objects. The applied approaches offer a great promise for future 3D reconstruction of tomographic images with radar wave.

[Effects of germplasm and host tree trunk on endophytic fungal communities in epiphytic Dendrobium catenatum].

In order to investigate the effects of germplasm and host tree trunk on endophytic fungal communities in epiphytic Dendrobium catenatum, a total of 3 835 isolates were recovered from roots, stems and leaves of four D. catenatum germplasms attached to one kind of host tree trunk and one germplasm attached to four kinds of epiphyte-host tree trunks. A total of 152 taxa were identified and classified based on the fungal cultural characteristics and phylogenetic analyses of ITS sequences. The taxa were assigned to 60 genera, 35 families, 21 orders and 5 classes of 2 phyla. The results indicated that D. catenatum cultivated in stereo cultivation harbor variety of fungi. The dominant fungal groups were different between Lin'an and Yiwu. Moreover, several groups showed geographical specificity, such as Arthrinium, Coniochaeta, Fusarium, Neofusicoccum and Zopfiella only dominating in Panshan of Lin'an, while Alternaria, Bjerkandera, Cercophora, Nigrospora and Trichoderma only dominating in Shangxi of Yiwu. There was no significant difference in diversity or species richness of endophytic fungi neither among germplasm nor host tree trunk. However, the richness and diversity indices exhibited a strong dependence on tissue type (P<0.05). The germplasm and host tree trunk impact the distribution patterns of endophytic fungi less than tissue type. Nevertheless, the relative frequencies of the dominant fungal groups were different among germplasms or host tree trunk types. Furthermore, there were some fungal species specific to certain germplasm or host tree trunk. This might be due to the distinctions in growth traits and chemical compositions of D. catenatum owning to the differences in D. catenatumgenetic background and microenvironment of host tree. Most of fungal taxa exhibit tissue specificity or preference. These results provide the basis for the study on the relationship between endophytic fungi and D. catenatum in stereo cultivation mode.

Vertical Optical Scanning with Panoramic Vision for Tree Trunk Reconstruction.

This paper presents a practical application of a technique that uses a vertical optical flow with a fisheye camera to generate dense point clouds from a single planimetric station. Accurate data can be extracted to enable the measurement of tree trunks or branches. The images that are collected with this technique can be oriented in photogrammetric software (using fisheye models) and used to generate dense point clouds, provided that some constraints on the camera positions are adopted. A set of images was captured in a forest plot in the experiments. Weighted geometric constraints were imposed in the photogrammetric software to calculate the image orientation, perform dense image matching, and accurately generate a 3D point cloud. The tree trunks in the scenes were reconstructed and mapped in a local reference system. The accuracy assessment was based on differences between measured and estimated trunk diameters at different heights. Trunk sections from an image-based point cloud were also compared to the corresponding sections that were extracted from a dense terrestrial laser scanning (TLS) point cloud. Cylindrical fitting of the trunk sections allowed the assessment of the accuracies of the trunk geometric shapes in both clouds. The average difference between the cylinders that were fitted to the photogrammetric cloud and those to the TLS cloud was less than 1 cm, which indicates the potential of the proposed technique. The point densities that were obtained with vertical optical scanning were 1/3 less than those that were obtained with TLS. However, the point density can be improved by using higher resolution cameras.

High-quality genome assembly and genetic transformation system of Lasiodiplodia theobromae strain LTTK16-3, a fungal pathogen of Chinese hickory.

Lasiodiplodia theobromae, as one of the causative agents associated with Chinese hickory trunk cankers, has caused huge economic losses to the Chinese hickory industry. Although the biological characteristics of this pathogen and the occurrence pattern of this disease have been well studied, few studies have addressed the related mechanisms due to the poor molecular and genetic study basis of this fungus. In this study, we sequenced and assembled L. theobromae strain LTTK16-3, isolated from a Chinese hickory tree (cultivar of Linan) in Linan, Zhejiang province, China. Phylogenetic analysis and comparative genomics analysis presented crucial cues in the prediction of LTTK16-3, which shared similar regulatory mechanisms of transcription, DNA replication, and DNA damage response with the other four Chinese hickory trunk canker-associated Botryosphaeria strains including, Botryosphaeria dothidea, Botryosphaeria fabicerciana, Botryosphaeria qingyuanensis, and Botryosphaeria corticis. Moreover, it contained 18 strain-specific protein clusters (not conserved in the other L. theobromae strains, AM2As and CITRA15), with potential roles in specific host-pathogen interactions during the Chinese hickory infection. Additionally, an efficient system for L. theobromae protoplast preparation and polyethylene glycol (PEG) -mediated genetic transformation was firstly established as the foundation for its future mechanisms study. Collectively, the high-quality genome data and the efficient transformation system of L. theobromae here set up the possibility of targeted molecular improvements for Chinese hickory canker control.IMPORTANCEFungi with disparate genomic features are physiologically diverse, possessing species-specific survival strategies and environmental adaptation mechanisms. The high-quality genome data and related molecular genetic studies are the basis for revealing the mechanisms behind the physiological traits that are responsible for their environmental fitness. In this study, we sequenced and assembled the LTTK16-3 strain, the genome of Lasiodiplodia theobromae first obtained from a diseased Chinese hickory tree (cultivar of Linan) in Linan, Zhejiang province, China. Further phylogenetic analysis and comparative genomics analysis provide crucial cues in the prediction of the proteins with potential roles in specific host-pathogen interactions during the Chinese hickory infection. An efficient PEG-mediated genetic transformation system of L. theobromae was established as the foundation for the future mechanisms exploration. The above genetic information and tools set up valuable clues to study L. theobromae pathogenesis and assist in Chinese hickory canker control.

Methane concentration in the heartwood of living trees in a cold temperate mountain forest: variation, transport and emission.

Forest soils are the largest terrestrial sink of methane, but CH4 produced in tree trunks by methanogenic archaea and emitted into the atmosphere can significantly offset CH4 oxidation in the soil. However, our mechanistic understanding of CH4 accumulation in tree trunks, in relation with CH4 emission from the trunk surface, is still limited. We characterised temporal variations in the molar fraction of CH4 in the heartwood of trees ([CH4]HW) of four different species in a mountain forest and addressed the relationship between [CH4]HW and emission from the surface of the trunk (${F}_{CH_4}$), in connection with the characteristics of the wood. [CH4]HW were measured monthly for 15 months using gas-porous tubes permanently inserted into the trunk. [CH4]HW were above ambient CH4 molar fraction for all trees, lower than 100 ppm for seven trees, higher for the nine other trees and greater than 200,000 ppm (> 20%) for two of these nine trees. [CH4]HW varied monthly but were not primarily determined by trunk temperature. Heartwood diffusive resistance for CH4 was variable between trees, not only due to heartwood characteristics but probably also related to source location. ${F}_{CH_4}$were weakly correlated with [CH4]HW measured a few days after. The resulting apparent diffusion coefficient was also variable between trees suggesting variations in the size and location of the CH4 production sites as well as resistance to gas transport within the trunk. Our results highlight the challenges that must be overcome before CH4 emissions can be simulated at the tree level.

The magnetic signal from trunk bark of urban trees catches the variation in particulate matter exposure within and across six European cities.

Biomagnetic monitoring increasingly is applied to assess particulate matter (PM) concentrations, mainly using plant leaves sampled in small geographical area and from a limited number of species. Here, the potential of magnetic analysis of urban tree trunk bark to discriminate between PM exposure levels was evaluated and bark magnetic variation was investigated at different spatial scales. Trunk bark was sampled from 684 urban trees of 39 genera in 173 urban green areas across six European cities. Samples were analysed magnetically for the Saturation isothermal remanent magnetisation (SIRM). The bark SIRM reflected well the PM exposure level at city and local scale, as the bark SIRM (i) differed between the cities in accordance with the mean atmospheric PM concentrations and (ii) increased with the cover of roads and industrial area around the trees. Furthermore, with increasing tree circumferences, the SIRM values increased, as a reflection of a tree age effect related to PM accumulation over time. Moreover, bark SIRM was higher at the side of the trunk facing the prevailing wind direction. Significant relationships between SIRM of different genera validate the possibility to combine bark SIRM from different genera to improve sampling resolution and coverage in biomagnetic studies. Thus, the SIRM signal of trunk bark from urban trees is a reliable proxy for atmospheric coarse to fine PM exposure in areas dominated by one PM source, as long as variation caused by genus, circumference and trunk side is taken into account.

A Wireless Acoustic Emission Sensor System with ACMD-IGWO-XGBoost Algorithm for Living Tree Moisture Content Diagnosis.

Trunk water has an important influence on the metabolism and ecological balance of living trees, which affects the vegetation growth and moisture cycle of the whole forest ecosystem. The accurate and real-time measurement of moisture content (MC) is of vital guiding meaning to living tree cultivation and forest management. In this paper, a water content diagnosis system based on a wireless acoustic emission sensor network (WASN) was designed and implemented with the aim of the nondestructive detection of water content in living wood trunks. Firstly, the acoustic emission (AE) signal of the trunk epidermis was sampled at high speed; then, its characteristic parameters were calculated and transmitted wirelessly to the gateway. Furthermore, the optimal characteristic wavelet sequence was decomposed by the adaptive chirp mode decomposition (ACMD), and the improved grey wolf optimizer (IGWO) optimization XGBoost established the MC prediction model, which was improved by the multi-strategy joint optimization. Finally, field monitoring was carried out on Robinia Pseudoacacia, Photinia serrulata, Pinus massoniana and Toona sinensis. The average diagnostic accuracy reached 96.75%, which shows that the diagnosis system has excellent applicability in different working conditions.

"Tree-Trunk" Design for Flexible Quasi-Solid-State Electrolytes with Hierarchical Ion-Channels Enabling Ultralong-Life Lithium-Metal Batteries.

The construction of robust (quasi)-solid-state electrolyte (SSE) for flexible lithium-metal batteries is desirable but extremely challenging. Herein, a novel, flexible, and robust quasi-solid-state electrolyte (QSSE) with a "tree-trunk" design is reported for ultralong-life lithium-metal batteries (LMBs). An in-situ-grown metal-organic framework (MOF) layer covers the cellulose-based framework to form hierarchical ion-channels, enabling rapid ionic transfer kinetics and excellent durability. A conductivity of 1.36 × 10-3  S cm-1 , a transference number of 0.72, an electrochemical window of 5.26 V, and a good rate performance are achieved. The flexible LMBs fabricated with as-designed QSSEs deliver areal capacity of up to 3.1 mAh cm-2 at the initial cycle with high mass loading of 14.8 mg cm-2 in Li-NCM811 cells and can retain ≈80% capacity retention after 300 cycles. An ultralong-life of 3000 cycles (6000 h) is also achieved in Li-LiFePO4 cells. This work presents a promising route in constructing a flexible QSSE toward ultralong-life LMBs, and also provides a design rationale for material and structure development in the area of energy storage and conversion.

Fine Spatial Scale Variation of Soil Microbial Communities under European Beech and Norway Spruce.

The complex interactions between trees and soil microbes in forests as well as their inherent seasonal and spatial variations are poorly understood. In this study, we analyzed the effects of major European tree species (Fagus sylvatica L. and Picea abies (L.) Karst) on soil bacterial and fungal communities. Mineral soil samples were collected from different depths (0-10, 10-20 cm) and at different horizontal distances from beech or spruce trunks (0.5, 1.5, 2.5, 3.5 m) in early summer and autumn. We assessed the composition of soil bacterial and fungal communities based on 16S rRNA gene and ITS DNA sequences. Community composition of bacteria and fungi was most strongly affected by soil pH and tree species. Different ectomycorrhizal fungi (e.g., Tylospora) known to establish mutualistic associations with plant roots showed a tree species preference. Moreover, bacterial and fungal community composition showed spatial and seasonal shifts in soil surrounding beech and spruce. The relative abundance of saprotrophic fungi was higher at a depth of 0-10 vs. 10-20 cm depth. This was presumably a result of changes in nutrient availability, as litter input and organic carbon content decreased with soil depth. Overall bacterial community composition showed strong variations under spruce with increasing distance from the tree trunks, which might be attributed in part to higher fine root biomass near spruce trunks. Furthermore, overall bacterial community composition was strongly affected by season under deciduous trees.

Perch-height specific predation on tropical lizard clay models: implications for habitat selection in mainland neotropical lizards

Predation has been hypothesized to be a strong selective force structuring communities of tropical lizards. Comparisons of perch height and size-based predation frequencies can provide a unique window into understanding how predation might shape habitat selection and morphological patterns in lizards, especially anoles. Here i use plasticine clay models, placed on the trunks of trees and suspended in the canopy to show that predation frequency on clay models differs primarily according to habitat (canopy vs. trunk-ground), but not according to size. These data are discussed in light of observed lizard abundances in the lowland forests of Costa Rica, and are presented as partial explanation for why fewer lizards are found in tree canopies, and more lizards are found on ground-trunk habitats. Rev. Biol. Trop. 57 (3): 859-864. Epub 2009 September 30.

Existe la hipótesis de que la depredación es una fuerte fuerza selectiva que estructura las comunidades de lagartijas tropicales. Las comparaciones de las frecuencias de altura de la percha y de depredación con base en el tamaño pueden proveer una ventana única en el entendimiento de cómo la depredación podría moldear la selección del hábitat y los patrones morfológicos en las lagartijas, especialmente anoles. En este estudio uso modelos de plasticina, ubicados en troncos de árboles y suspendidos en el dosel para mostrar que la frecuencia de depredación en los modelos de plasticina difiere primariamente según el hábitat (dosel vs. tronco-suelo) pero no según el tamaño. Estos datos se discuten a la luz de las abundancias de lagartijas observadas en los bosques de bajura de Costa Rica, y se presentan como una explicación parcial a porqué menos lagartijas se encuentran en los doseles, y más lagartijas se encuentran en los hábitats suelo-tronco.