Tree trunk instance segmentation is crucial for under-canopy unmanned aerial vehicles (UAVs) to autonomously extract standing tree stem attributes. Using cameras as sensors makes these UAVs compact and lightweight, facilitating safe and flexible navigation in dense forests. However, their limited onboard computational power makes real-time, image-based tree trunk segmentation challenging, emphasizing the urgent need for lightweight and efficient segmentation models. In this study, we present RT-Trunk, a model specifically designed for real-time tree trunk instance segmentation in complex forest environments. To ensure real-time performance, we selected SparseInst as the base framework. We incorporated ConvNeXt-T as the backbone to enhance feature extraction for tree trunks, thereby improving segmentation accuracy. We further integrate the lightweight convolutional block attention module (CBAM), enabling the model to focus on tree trunk features while suppressing irrelevant information, which leads to additional gains in segmentation accuracy. To enable RT-Trunk to operate effectively under diverse complex forest environments, we constructed a comprehensive dataset for training and testing by combining self-collected data with multiple public datasets covering different locations, seasons, weather conditions, tree species, and levels of forest clutter. Compared with the other tree trunk segmentation methods, the RT-Trunk method achieved an average precision of 91.4% and the fastest inference speed of 32.9 frames per second. Overall, the proposed RT-Trunk provides superior trunk segmentation performance that balances speed and accuracy, making it a promising solution for supporting under-canopy UAVs in the autonomous extraction of standing tree stem attributes. The code for this work is available at https://github.com/NEFU-CVRG/RT-Trunk.
Rhododendron micranthum Turcz. is a shrub esteemed for its ornamental and medicinal attributes within the Changbai Mountain range of China. We selected 3-year saplings and subjected them to four distinct light conditions: full light (CK), 70% light (L1), 50% light (L2), and 30% light (L3) to investigate variations in morphology, photosynthetic responses, stomatal ultrastructure as well as the mechanisms through which these saplings adapt to differing lighting environments. The results indicate that L2 leaves exhibit significantly greater length, width, and petiole development compared to other treatments across varying intensities. Over time, chlorophyll content and PSII levels in L2-treated saplings surpass those observed in other treatments; Proline (PRO), malondialdehyde (MDA), and soluble protein (SP) contents are markedly lower under L2 treatment. Catalase (CAT) and superoxide dismutase (SOD) demonstrate significant correlations across various light conditions but respond differently among treatments, indicating distinct species sensitivities to light intensity while both contribute to environmental stress resistance mechanisms. Findings reveal that R. micranthum saplings at 50% light intensity benefit from enhanced protection via antioxidant enzymes, and shading reduces osmotic adjustment substances yet increases chlorophyll content. Stomatal length/width along with conductance rates and net photosynthesis rates for L2 exceed those of CK, suggesting an improved photosynthetic structure conducive to efficient photosynthesis under this condition. Thus, moderate shading represents optimal growth at 50% illumination, a critical factor promoting sapling development. This research elucidates the ideal environment for R. micranthum adaptation to varying light conditions supporting future conservation initiatives.
Tree endophytic fungi play an important role in reducing insect herbivory, either by repelling them or killing them directly. Identifying which fungi show such activity could lead to new environmentally friendly pesticides. In this study, the Mediterranean basin climate conditions are projected to harshen in the next decades, will increase vulnerability of tree species to pest invasions. Endophytic fungi were isolated from wood and leaves of Quercus pyrenaica, Q. ilex and Q. suber and tested for virulence against adults of the mealworm beetle, Tenebrio molitor L. using a direct contact method. Only 3 of 111 sporulating isolates had entomopathogenic activity, all identified as Lecanicillium lecanii. The pathogenicity of L. lecanii on T. molitor resulted in a median lethal time (TL50) of 14–16 d. Compared with commercial products, L. lecanii caused faster insect death than the nematode Steinernema carpocapsae and nuclear polyhedrosis virus (no effect on T. molitor survival), and slower than Beauveria bassiana (TL50 = 5), Beauveria pseudobassiana (TL50 = 8d) and Bacillus thuriengensis (80% mortality first day after inoculation). Mortality was also accelerated under water stress, reducing TL50 by an additional 33%. Remarkably, water stress alone had a comparable effect on mortality to that of L. lecanii isolates. This study confirms T. molitor as a good model insect for pathogenicity testing and agrees with management policies proposed in the EU Green Deal.
Photodegradation is considered as a universal contributing factor to litter decomposition and carbon (C) cycling within the Earth’s biomes. Identifying how solar radiation modifies the molecular structure of litter is essential to understand the mechanism controlling its decomposition and reaction to shifts in climatic conditions and land-use. In this study, we performed a spectral-attenuation experiment following litter decomposition in an understory and gap of a temperate deciduous forest. We found that short-wavelength visible light, especially blue light, was the main factor driving variation in litter molecular structure of Fagus crenata Blume, Quercus crispula Blume, Acer carpinifolium Siebold & Zuccarini and Betula platyphylla Sukaczev, explaining respectively 56.5%, 19.4%, 66.3%, and 16.7% of variation in its chemical composition. However, the variation also depended on canopy openness: Only in the forest gap was lignin aromatic C negatively associated with C-oxygen (C–O) bonding in polysaccharides receiving treatments containing blue light of the full spectrum of solar radiation. Regardless of species, the decomposition index of litter that explained changes in mass and lignin loss was driven by the relative content of C–O stretching in polysaccharides and lignin aromatic C. The results suggest that the availability of readily degradable polysaccharides produced by the reduction in lignin aromatic C most plausibly explains the rate of litter photodegradation. Photo-products of photodegradation might augment the C pool destabilized by the input of readily degradable organic compounds (i.e., polysaccharides).
Petroleum extraction and its organic pollutants have numerous negative consequences on the composition and ecological function of grasslands, such as vegetation degradation, reduction in species diversity, and salinization. Thus, finding a comprehensive method for polluted soil and restoring grasslands faces many challenges, and the mechanism to influence soil environments and microbial community composition remains unclear. In this study, container experiments explored the potential of sulfonic acid group (–SO3H groups) modified biochar combined with isolated bacterium (named Y-1, Acinetobacter-spp.) on physicochemical properties and microbial communities of polluted soil. The results show that modified biochar and Y-1 combined addition had the highest petroleum degradation rate (39.4%), and soil nutrients such as dissolved organic carbon (DOC), cation exchange capacity (CEC), available nitrogen, invertase and urease activities in CK were decreased by 35.4, 12.1, 30, 43.2 and 32.5% compared to treatments. The contents of available phosphorus in CM treatment were increased 2.4 times compared to CK. The –SO3H groups efficiently improve salinity by accumulating Ca2+ and Mg2+ and inhibiting the aggregation of Na+. The correlation heatmap indicated that soil organic carbon, total nitrogen and CEC markedly interact with microbial communities. High-throughput sequencing indicated that the biomarkers enriched by the present integrated treatment are crucial for stimulating nitrogen and phosphorus cycles. The results indicate that -SO3H groups modified biochar, and Y-1 has great potential to serve as a novel bioremediation technology to remediate soil from petroleum pollutants and alkalization and achieve better restoration of degradation grasslands.
Human activities contribute to elevated nitrogen input in terrestrial ecosystems, influencing the composition of soil nutrients and microbial diversity in forest ecosystems. In this study, we built four addition treatments (0, 20, 40, and 80 kg ha−1 a−1 N for 6 a) at a Korean pine plantation of different soil horizons (organic (O) horizon, ranging from 0 to 10 cm, and organomineral (A) horizon, extending from 10 to 20 cm) to evaluate responses of the structure of saprophytic fungal communities. Here, 80 kg ha−1 a−1 N treatment significantly decreased the community richness in soil A horizon with the Chao1 index decreasing by 12.68%. Nitrogen addition induced changes in the composition of saprophytic fungi community between the different soil horizons. The co-occurrence network and its associated topological structure were utilized to identify mycoindicators for specific fungi to both soil horizons and nitrogen addition levels. In soil O horizon, the mycoindicators included Penicillium, Trichoderma, Aspergillus, and Pseudeurotium across control, low, medium, and high nitrogen treatments. In soil A horizon, Geomyces, Cladophialophora, Penicillium, and Pseudeurotium were identified as mycoindicators. Structural equation modeling determined NH4 +-N as the key factor driving changes in saprotrophic fungal communities. Our study aimed to screen mycoindicators that can respond to the increasing global nitrogen deposition and to assess the roles of these mycoindicators in the saprophytic fungal community structure within Korean pine plantations in northeast China.
To better understand the effects of ground-level ozone (O3) on nutrients and stoichiometry in different plant organs, urban tree species Celtis sinensis, Cyclocarya paliurus, Quercus acutissima, and Quercus nuttallii were subjected to a constant exposure to charcoal-filtered air (CF), nonfiltered air (NF), or NF + 40, 60, or 80 nmol O3 mol–1 (NF40, NF60, and NF80) starting early in the summer of the growing season. At the end of summer, net CO2 assimilation rate (A), stomatal conductance (g s), leaf mass per area (LMA), and/or leaf greenness (SPAD) either were not significantly affected by elevated O3 or were even higher in some cases during the summer compared with the CF or NF controls. LMA was significantly lower in autumn only after the highest O3 exposures. Compared to NF, NF40 caused a large increase in g s across species in late summer and more K and Mn in stems. At the end of the growing season, nutrient status and stoichiometric ratios in different organs were variously altered under O3 stress; many changes were large and often species-specific. Across O3 treatments, LMA was primarily associated with C and Mg levels in leaves and Ca levels in leaves and stems. NF40 enriched K, P, Fe, and Mn in stems, relative to NF, and NF60 enhanced Ca in leaves relative to CF and NF40. Moreover, NF resulted in a higher Ca/Mg ratio in leaves of Q. acutissima only, relative to the other O3 regimes. Interestingly, across species, O3 stress led to different nutrient modifications in different organs (stems + branches vs leaves). Thus, ambient and/or elevated O3 exposures can alter the dynamics and distribution of nutrients and disrupt stoichiometry in different organs in a species-specific manner. Changes in stoichiometry reflect an important defense mechanism in plants under O3, and O3 pollution adds more risk to ecological stoichiometries in urban areas.
Biological invasions, driven mainly by human activities, pose significant threats to global ecosystems and economies, with fungi and fungal-like oomycetes playing a pivotal role. Ink disease, caused by Phytophthora cinnamomi and P. × cambivora, is a growing concern for sweet chestnut stands (Castanea sativa) in Europe. Since both pathogens are thermophilic organisms, ongoing climate change will likely exacerbate their impact. In this study, we applied species distribution modeling techniques to identify potential substitutive species for sweet chestnut in the light of future climate scenarios SSP126 and SSP370 in southern Switzerland. Using the presence-only machine learning algorithm MaxEnt and leveraging occurrence data from the global dataset GBIF, we delineated the current and projected (2070–2100) distribution of 28 tree species. Several exotic species emerged as valuable alternatives to sweet chestnut, although careful consideration of all potential ecological consequences is required. We also identified several native tree species as promising substitutes, offering ecological benefits and potential adaptability to climatic conditions. Since species diversification fosters forest resilience, we also determined communities of alternative species that can be grown together. Our findings represent a valuable decision tool for forest managers confronted with the challenges posed by ink disease and climate change. Given that, even in absence of disease, sweet chestnut is not a future-proof tree species in the study region, the identified species could offer a pathway toward resilient and sustainable forests within the entire chestnut belt.
Pinus koraiensis (Sieb. et Zucc.) is a coniferous tree species naturally distributed in northeastern China. However, the effects of gene flow on its genetic diversity and structure remain unclear. This study investigates these dynamics in seven populations using ten microsatellite markers. The results show a high level of genetic diversity within the populations (Ho = 0.633, He = 0.746). In addition, molecular analysis of variance (AMOVA) shows that 98% of genetic diversity occurs within populations, with minimal differentiation between populations (Fst = 0.009–0.033). Gene flow analysis shows significant migration rates between specific population pairs, particularly C-TH (87%), LS-Y (69%) and TH-LS (69%), suggesting genetic homogenization. Bayesian clustering (STRUCTURE) supports admixture and weak population differentiation. Environmental factors, especially temperature-related variables, significantly influence genetic patterns. Partial Mantel tests and multiple matrix regression show strong correlations between genetic distance and adaptations to cold temperatures (bio6 and bio11). Overall, this study emphasizes the robust genetic diversification and high migration rates in the populations of P. koraiensis and highlights their resilience. These results emphasize the importance of incorporating genetic and ecological factors into conservation strategies for sustainable forest management. This research provides valuable insights into the complex interplay of genetic variation, gene flow and environmental influences in forest tree species and improves our understanding of their adaptive mechanisms.