搜索结果：Forestry research

This study systematically investigated the influence of different detection distances on the spectral detection models of moisture content and Soluble Solid Content in small white apricots, aiming to provide distance parameter references for the practical application of portable spectrometers. Using 98 samples of small white apricots as the subjects, visible/near-infrared diffuse reflectance spectra were collected at five distances of 0.1, 0.2, 0.3, 0.4, and 0.5 m using a self-built adjustable distance platform. During the modeling process, different distances are treated as external variables, and spectral reflectance data at various distances are used as inputs for the predictive model, which is then followed by the introduction of the Partial Least Squares Regression (PLSR) model. After preprocessing the original spectral data and eliminating abnormal samples through Monte Carlo cross-validation, the competitive adaptive re-weighted algorithm was employed to screen characteristic wavelengths. The models for moisture content and soluble solids retained 109 and 89 key variables, respectively (out of the original 601). The results indicate that after applying different optimal preprocessing methods to spectra from various detection distances and using CARS for variable selection, the model performance was significantly improved: the coefficient of determination and RPIQ of the optimal model for moisture content increased from 0.8630 to 3.9785 to 0.9245 and 5.3667, respectively, while the root mean square error of the prediction set decreased from 2.4354 to 2.0157; the evaluation metrics of the optimal model for soluble solids increased from the original values of 0.6845 and 1.8691 to 0.7793 and 2.8745, and the root mean square error of the prediction set decreased from the original value of 0.8734 to 0.6834. The optimal detection distance for moisture content is 0.3 m (with moving window smoothing preprocessing), while the optimal detection distance for soluble solids is 0.4 m (with multi-scattering correction preprocessing). Furthermore, the preliminarily explored segmented weighted multi-distance spectral fusion strategy can integrate complementary spectral features, further enhancing the robustness of the model. This study confirms that the detection distance significantly affects the accuracy of spectral detection of fruit internal quality, providing methodological references for multi-source information fusion modeling and the on-site application of spectral technology.

Superfolder green fluorescent protein (sfGFP) is an engineered GFP variant best known for its robust folding, reliable chromophore maturation, and high tolerance to fusion partners. This review argues that the principal value of sfGFP lies not in universal superiority in brightness or photostability, but in its ability to preserve fluorescence under conditions that compromise the folding or performance of conventional GFP variants. These contexts include difficult fusion proteins, split-fragment complementation systems, circularly permuted biosensor scaffolds, recombinant expression platforms, and secretion-associated workflows. Because sfGFP is directly encoded by a DNA sequence, it can be expressed in living cells as a fusion tag and generate fluorescence through autocatalytic chromophore maturation without requiring exogenous cofactors or synthetic fluorophores, enabling live-cell localization, protein detection, and dynamic biosensing. Its high solubility and folding robustness can also improve soluble recovery, reduce aggregation, and facilitate the purification of recombinant fusion proteins. However, sfGFP is not without limitations: its fluorescence remains pH-sensitive, its monomeric behavior can be context-dependent, and its photostability is not optimized for prolonged high-intensity illumination. Therefore, sfGFP should be selected according to application-specific requirements and benchmarked against newer green fluorescent proteins in terms of folding robustness, brightness, maturation kinetics, monomericity, pH tolerance, and photostability. Future integration of sfGFP with cell-free systems, synthetic biology, and protein-design strategies is likely to further establish it as a robust fluorescent scaffold for biotechnology.

Insect symbionts play essential roles in host biology, influencing nutrition, immunity, reproduction, and environmental adaptation, ultimately shaping insect physiology, ecology, and evolution. With the rapid growth of functional and genomic datasets on insect symbionts, there remains a critical need for a dedicated platform to systematically compile, organize, and analyze these datasets from an integrative ecological perspective. Here, we developed an insect Symbiont database, named as iSymBase, by manually curating functional records and genomic datasets of insect symbionts from published academic literature. Currently, iSymBase contains over 2657 insect symbiont functional records spanning 795 host species, along with 1494 metagenomes, 14 992 amplicon datasets, and standardized genome and gene catalogs, providing a comprehensive resource for ecological and comparative insect symbiont researches. iSymBase offers standardized query functionalities, such as data browsing, keyword associative search, sequence alignment, data download, and submission. Beyond conventional database functionalities, iSymBase provides several innovative tools: insect-symbiont interaction network for host-symbiont ecological relationships, a batch annotation tool for detecting ecologically functional symbionts from microbiome profiles, and an artificial intelligence (AI)-powered chatbot iSymSeek designed to assist researchers with related knowledge queries. Taken together, iSymBase will serve as an open-access and continually updated platform for storing, querying, and analyzing insect symbiont data, supporting ecological exploration of host-symbiont interactions, symbiont functional diversity, and microbiome-driven adaptation. Database URL: http://symbiont.insect-genome.com/.

Non-fused ring electron acceptors (NFREAs) exhibit substantial commercial application potential. Nevertheless, their subpar electron transport performance results in slightly low power conversion efficiencies (PCEs) of organic solar cells (OSCs). Herein, we put forward an innovative supramolecular side-chain-induced multi-dimensional charge transport strategy to exploit two NFREAs 3TT-Ph2 and 3TT-Ph4 with terminal phenyl/fluorinated phenyl side chains. In comparison to the unfunctionalized control molecule 3TT-2, both 3TT-Ph2 and 3TT-Ph4 form additional phenyl-acceptor (Ph-A) supramolecular interactions between the phenyl side groups and the cyanoindanone end groups. Meanwhile, these fluorinated terminal phenyl groups can induce the formation of multiple supramolecular interactions, including F···F, F···H and F···C. The synergistic effect of these supramolecular interactions promotes the tight and ordered stacking of molecules, facilitates the construction of multi-dimensional charge transport channel. Finally, D18:3TT-Ph4-based device achieved a record-breaking PCE of 19.12% and a fill factor of 80.65%. Our research pave an effective strategy for the molecular design of high-performance NFREAs.

Fermented soymilk has emerged as a potential functional food due to its nutritional and health-promoting properties. Enhancing its functionality by enriching it with gamma-aminobutyric acid (GABA), a neurotransmitter with various health benefits, is an area of active research. This study aims to develop a novel GABA-enriched fermented soymilk using a newly isolated Lactiplantibacillus plantarum strain with both probiotic and GABA-producing capabilities. Five L. plantarum strains isolated from Vietnamese soybean whey were screened for GABA production and probiotic characteristics. Strain W12, which exhibited superior performance, was selected for optimisation. Response surface methodology with a central composite design was used to optimise monosodium glutamate (MSG) and sucrose amounts for maximal GABA yield. A time-course study was then conducted to monitor bacterial growth, pH changes, organic acid production, and GABA accumulation during fermentation under the optimised conditions. L. plantarum W12 demonstrated exceptional probiotic traits: 97.1 % survival at pH=2.5, 96.5 % survival in bile salts/pancreatin, 97.3 % pepsin tolerance, 96.7 % auto-aggregation and 85.4 % hydrophobicity in chloroform. Initial GABA production reached (9.1±0.4) mM. Response surface optimisation predicted a maximum GABA concentration of 34.2 mM at 1.564 mg/mL MSG and 10.93 % sucrose, which was experimentally validated at (34.5±1.0) mM (15 h, 45 °C). Lactic acid was the predominant organic acid produced ((182.4±8.0) mg/g at 18 h), with viable cell counts exceeding 7.9 log CFU/mL, meeting probiotic thresholds. This study presents the first comprehensive characterisation of L. plantarum W12, a strain combining exceptional GABA biosynthesis with robust probiotic properties. The systematic response surface methodology (RSM) optimisation framework and detailed metabolic profiling provide reproducible protocols for developing multifunctional fermented soy beverages with applications in neurological and gastrointestinal health promotion.

The success of biological control of insect pests by parasitoids ultimately depends on effective host foraging by the agents, which involves multiple processes and various cues associated with hosts' habitat, host-associated symbionts and other microbial organisms, and/or hosts themselves. In general, parasitoid interactions with concealed hosts such as wood-boring beetles differ significantly from those that attack exposed hosts (eg surface-feeding caterpillars, aphids) as they must rely on a more complex hierarchy of cues to first locate hosts' microhabitats and then hosts for their reproduction. These differences influence the parasitoid's host-finding strategies, specificity, and their efficacy in suppressing their host populations. Here, we review the major steps in host finding by parasitoids of wood-boring beetles and synthesize current knowledge on the chemical, vibrational, visual, and other cues that mediate each stage of the process. We highlight how these cues operate across different spatial scales, interact with parasitoid morphology and behavior, and shape the success of biological control programs targeting economically important wood-boring pests. Finally, we identify key knowledges gaps and point to some future research directions aimed at improving the selection, deployment, and monitoring of parasitoid biological control agents in forest ecosystems.

Meat is an important part of the human diet, providing the body with abundant protein, fat, vitamins, and various minerals, and plays an irreplaceable role in ensuring the nutritional needs of the human body. However, the off-flavors limits the production and consumption of meat products. Systematically clarifying the key substances of off-flavors and their formation mechanisms is crucial for controlling this off-flavors and enhancing the production and consumption of meat products. Therefore, this paper summarizes the core flavor components responsible for the off-flavors, including aldehydes, ketones, sulfides, and amines, as well as the formation mechanisms of off-flavors such as bio-enrichment, protein oxidation and degradation, microbial action, and lipid oxidation. Furthermore, the research and application progress of off-flavors regulation technologies based on physical, chemical, biological, and composite strategies was analyzed, aiming to provide references for the production, processing, and quality improvement of meat products.

This study develops a high-resolution Geo-AI framework to quantify the impact of future climate change on PM2.5 concentrations using Taiwan as a subtropical, monsoon-influenced island case. The model integrates long-term ground-based monitoring data (1994-2019), multi-scale geo-environmental predictors, and statistically downscaled CMIP6 meteorology, implemented using a Gradient Boosting Machine. The resulting model demonstrates strong predictive performance (R2 = 0.81 and RMSE = 8.69 μg/m3) and effectively captures PM2.5 dynamics within complex islands and coastal environments. By explicitly coupling a Geo-AI model with Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report (AR6) climate scenarios, this study extends data-driven PM2.5 modeling from historical estimation to climate-conditioned future projection, addressing a key methodological gap in existing air-quality research. SHAP-based interpretability analysis identifies temperature and precipitation as dominant predictors, underscoring their central role in shaping future aerosol variability. The SHAP results further indicate that both temperature and precipitation exhibit nonlinear relationships across different temporal and regional scales and overall inverse associations with PM2.5 concentrations, clarifying the climate-driven effects of warming and hydrological change on PM2.5 dynamics under humid subtropical conditions. Across four Shared Socioeconomic Pathway scenarios, projected PM2.5 concentrations consistently decline in the near and midterm (between -1.25 and -1.5 μg/m3), followed by increasing spatial heterogeneity in the long term, with localized PM2.5 hotspots emerging under severe warming conditions. These findings suggest that climate change may generate uneven air-quality responses across space, highlighting the limitations of regional mean assessments and the need for high-resolution, climate-informed mitigation and adaptation strategies. The proposed framework provides a transferable tool for climate-responsive air-quality planning in humid subtropical, monsoon-influenced, and densely populated regions worldwide.

As global agricultural soils face the escalating challenge of salt stress, understanding mechanisms of plant resilience becomes critical. Salt stress severely constrains crop production worldwide by limiting plant growth and productivity through ionic toxicity, osmotic imbalance and disruption of reactive oxygen species (ROS) homeostasis leading to oxidative damage. In the era of population explosion and climate change, there is an urgent need to adopt innovative strategies that fortify the resilience of agricultural systems to salt stress. Amidst these challenges, jasmonic acid (JA) has emerged as key regulator of ROS homeostasis and signaling, acting as a central leverage point of plant defense responses, regulating complex physiological, biochemical and molecular networks under salt stress conditions. This comprehensive review highlights the indispensable role of JA in modulating salt stress, how its signaling pathways reprogram plant metabolism to regulate ROS production and scavenging by driving the accumulation of antioxidants and secondary metabolites including flavonoids, alkaloids, terpenes and phenolics. Crucially, we unpack the intricate hormonal crosstalk between JA and key plant growth regulators (PGRs), such as abscisic acid (ABA), ethylene (ET), salicylic acid (SA), gibberellins (GA) and auxins, revealing how ROS-mediated hormonal crosstalk enables plants to balance complex growth-defense trade-offs under salt stress. This review also discusses the role of redox homeostasis and spatiotemporal ROS dynamics in shaping plant adaptive responses under salt stress. Furthermore, recent biotechnological advancements, including CRISPR/Cas9 mediated genetic modulation of JA biosynthesis and signaling pathways to engineer salt-tolerant crops. Future research integrating multi-omics, gene editing and field-based validation of JA mediated regulatory pathways will accelerate the development of salt tolerant cultivars for sustainable agriculture.

This dataset presents 352 nuclear genes assembled from whole genome skimming data of 43 Rhododendron samples. The data were generated from 14 Rhododendron dauricum collected from seven distinct geographical populations in Northeast China, together with sequence data from 29 additional Rhododendron samples downloaded from the NCBI database. Using the universal set of 353 angiosperm nuclear genes as a reference, all genes were assembled with the HybPiper v2.1.1 pipeline. The dataset contains raw assembly sequences in FASTA format for each gene. Sequence alignment, trimming, and phylogenetic analysis were performed to construct phylogenetic trees. The resulting phylogenies based on concatenated 352-gene dataset and the screened 17-gene sub-dataset clearly distinguished R. dauricum from other Rhododendron species. Moreover, both datasets resolved individuals from the same population into distinct clades, enabling geographical origin traceability for the protected species R. dauricum. This dataset provides high-resolution molecular markers for research on Rhododendron phylogenomics, population genetics, conservation, and molecular identification.

Digital environments have become important contexts in which consumers form sensory expectations and evaluate food quality prior to consumption. Drawing on the elaboration likelihood model and attribution theory, this study develops a theoretically grounded process model to explain how visual and textual cues in online presentations of natural foods shape food-related cognition. Specifically, we propose that perceived naturalness serves as an initial perceptual input that can trigger cognitive engagement through multiple mechanisms: directly, via credibility as a validation mechanism, via taste inference as an experiential simulation, and through a sequential chain in which credibility enables taste inference that subsequently sustains elaboration. A 2 (platform type: content-oriented vs. transaction-oriented) × 2 (image scene: lifestyle-oriented vs. nature-oriented) × 2 (text framing: consumption-oriented vs. production-oriented) between-subjects experiment (N = 320) was conducted. Partial least squares structural equation modeling was employed to test direct and indirect effects; multi-group analysis examined boundary conditions across experimental contexts; and necessary condition analysis identified minimum required levels of predictors for high engagement states. The results indicate that perceived naturalness has a significant direct effect on cognitive engagement, as well as indirect effects through credibility and taste inference independently and in sequence. The indirect pathway is more pronounced in content-oriented environments, particularly when nature-oriented images and consumption-oriented text are used. Taste inference emerged as the strongest necessary condition for high cognitive engagement, followed by credibility; perceived naturalness showed a weaker but significant necessity effect. These findings demonstrate how visual and textual cues jointly guide anticipatory sensory processing and cognitive engagement in digital food contexts, offering both theoretical contributions to cue-based processing research and practical implications for the design of online presentations of natural foods.

Magnesium (Mg²⁺) is essential for chlorophyll synthesis, enzyme activation, and photosynthesis, but the differential regulation of Mg²⁺ homeostasis between the two founding Saccharum species (Saccharum officinarum and Saccharum spontaneum) remains unknown. We systematically characterized the MGR gene family in S. spontaneum and S. officinarum and uncovered distinct physiological responses to Mg²⁺ availability between the two species. Comparative expression analysis across the leaf developmental gradient and diurnal cycles revealed species-specific transcriptional dynamics of MGR2, suggesting divergent regulatory mechanisms underlying Mg²⁺ management. Functional complementation in the Mg²⁺-deficient Salmonella typhimurium MM281 mutant demonstrated that both SsMGR2 and SoMGR2 restore Mg²⁺ uptake, confirming their conserved transport capability. Overexpression of SsMGR2 in rice conferred increased biomass under Mg²⁺ deficiency and enhanced tolerance to Mg²⁺ excess, indicating a broad role for this gene in Mg²⁺ homeostasis. Promoter architecture and transcription factor prediction further revealed interspecific divergence, with BBX25, COL5, and WRKY19-2 exhibiting species-dependent regulatory interactions that potentially explain the observed differences in MGR2 expression. Overall, the research results indicate that S. spontaneum and S. officinarum exhibit different Mg²⁺ responses and MGR2 regulatory patterns, highlighting the distinct strategies for Mg²⁺ homeostasis in these two founding species. This work provides new insights into the transport mechanism of Mg²⁺ in sugarcane and preliminarily identifies candidate genes and regulatory factors for improving nutrient efficiency and stress recovery ability.

An alternative strategy to mitigate the ecological and economic challenges posed by invasive fish species is to transform these organisms into valuable resources, generating economic benefits while simultaneously addressing ecosystem-related concerns. However, while the search for sustainable feedstocks continues, the specific potential of highly resilient invasive fish species for high-yield biodiesel production has not yet been evaluated. The aim of this study was to address this research gap by producing high-yield biodiesel using the invasive fish Carassius gibelio as an oil source. In this context, lipase immobilized MnFe2O4- polyhydroxymethyl methacrylate magnetic nanogels were prepared and the production system conditions (lipase amount, methanol/oil molar ratio, and temperature) were optimized. Optimal conditions were obtained using a 4000 U lipase amount, a 5:1 methanol/oil molar ratio and a temperature of 55 °C. A 97.45% biodiesel yield was achieved with this system prepared under optimum conditions, and this prepared biocatalysis system was able to produce biodiesel with at least 50% yield 13 times. This study is the first to use the highly invasive C. gibelio as a sustainable raw material for biodiesel production. It introduces a novel biocatalytic approach by integrating invasive fish species utilization with a reusable MnFe2O4-pHEMA nanogel system, achieving both high efficiency and operational stability.

Minimum Unit Pricing (MUP) is one regulatory approach to alcohol pricing in regions around the world. Broadly, MUP establishes a lowest price threshold for retail per a standardized unit of ethanol in a beverage alcohol product. Illicit drinkers are people whose drinking is often criminalized (i.e., people who drink in public and are subject to harassment or sanctions from law enforcement) and/or people who consume non-beverage alcohol (e.g., hand sanitizer, rubbing alcohol, mouthwash). The provincial government of British Columbia, Canada has proposed reforms to the existing framework for MUP, which is likely to disproportionately impact illicit drinkers. These reforms to MUP would increase the price of the lowest cost, high alcohol-level drinks. We draw from a community dialogue facilitated by the local Eastside Illicit Drinkers Group for Education (EIDGE) to critically examine these proposed reforms. Through a narrative review of recent international research, we describe some projected negative impacts of BC's proposed reforms, which intend to reduce access to low-cost alcohol beverages. We outline how this is likely to - paradoxically and systematically - push some drinkers, particularly those most disenfranchised by the intersecting social relations of racial capitalism and settler colonization, toward more harmful modes of alcohol consumption, including the use of unregulated alcohol and/or non-beverage alcohol. Likewise, the reforms are likely to unevenly target local Indigenous populations, who experience disproportionate criminalization; and for whom accessing consumable alcohol, healthcare services, and places to drink safely is more fraught than for non-Indigenous drinkers. Ultimately, our essay provides critical considerations for the implementation of MUP in BC that could inform alternative models/options in place of blanket increases in unit pricing.

This data article presents a multi-source dataset of satellite-based auxiliary data designed for forest modelling and monitoring. The dataset integrates annual medoid composites derived from Sentinel-1, Sentinel-2, and Landsat imagery, together with spectral indices, Landsat-based 3I3D change metrics, forest mask and forest type layers, and terrain variables derived from the Copernicus GLO-30 DEM, offering comprehensive information on forest cover, spectral behavior, and change metrics. It provides harmonized predictors across seven European countries, ensuring consistency, scalability, and ease of use for researchers developing or validating models to understand forest dynamics and estimate forest-related variables such as biomass or canopy recovery. A curated subset of the dataset is distributed via Zenodo, along with direct public access links to the complete multi-terabyte archive. The data support applications in forest biodiversity conservation, carbon monitoring, biomass modelling, and climate-change impact assessment.

Climate change is fundamentally reshaping forest disease dynamics through direct effects on pathogen biology and indirect impacts on host physiology. Rising temperatures, altered precipitation patterns, and extreme weather events are driving disease emergence by disrupting ecological relationships between trees and their microbial associates. This review examines how climate change compounds biotic and abiotic risks to forest health, distinguishing between climate-pathogen diseases, where climatic shifts directly favor pathogen activity, and climate-stress diseases, where physiological stress predisposes trees to decline. We explore the continuum from native pathogens gaining new opportunities to exotic pathogens establishing in previously unsuitable environments while considering distinctions among endophytes and latent and nonlatent pathogens. The review emphasizes critical knowledge gaps and highlights emerging research directions, including integration of genomics, remote sensing, and predictive modeling for disease surveillance, adaptive forest management strategies balancing disease mitigation with climate adaptation and new solutions for enhancing forest resilience under accelerating environmental change.

Bacillus velezensis is known for producing and secreting antimicrobial lipopeptides, yet the regulatory mechanisms behind these processes remain unclear. In this study, we constructed arsenite transporter protein gene (acr3)-deficient strains (HN-1ΔQ acr3) and complementary strains (HN-1ΔC acr3) to elucidate the roles of ACR3 in antimicrobial lipopeptide synthesis and efflux. Our findings demonstrate that ACR3 dysfunction compromised swarming and biofilm formation, completely abolishing the antifungal capabilities of the HN-1ΔQ acr3 strains. Transcriptomic analysis and reverse transcription-quantitative PCR revealed significant downregulation of lipopeptide biosynthesis genes, including sfp, fenD and bmyC, in HN-1ΔQ acr3. Notably, the addition of purified ACR3 protein restored the expression of lipopeptide biosynthesis genes and partially rescued antifungal activities in the HN-1ΔQ acr3 strains. Furthermore, yeast two-hybrid assays indicated an interaction between ACR3 and proteins involved in cell survival, substrate uptake and antifungal activities, such as ribose ABC transporter substrate-binding protein (RbsB), fengycin synthetases and phosphopantetheine transferases. In parallel, our findings indicate that ACR3 interacts with the ABC transporter pathway to tune antifungal lipopeptide transport in Bacillus velezensis. Collectively, these results suggest that ACR3 functions as a crucial regulator, mediating both the synthesis and efflux of lipopeptides in B. velezensis. These research establish an experimental foundation for elucidating the mechanisms of antimicrobial compound synthesis and secretion in B. velezensis and provide a theoretical basis for the optimisation and engineering of high-yield biocontrol strains.

Soil aggregates are the basic structure of soil. To investigate the distribution characteristics of karst soil aggregates in southwest China and the response of their stability to long-term vegetation restoration, we took karst areas and their restored successional transects in Caohai Nature Reserve of Weining, Guizhou Province, as the research subject. The result showed that: (1) soil water stable macroaggregates (R0.25), soil geometric mean diameter MWD, and mean weight diameter GMD were significantly reduced with vegetation restoration. (2) generalized linear mixed model (GLMM) and structural equation models revealed that vegetation type exhibited a highly significant effect on soil aggregates (p < 0.001), including both karst soil and vegetation-restored soil, during a homogeneous garden experiment. Vegetation type is the core factor affecting the formation and stability of soil aggregates, while topographic characteristics have no significant effect on soil aggregates during vegetation restoration.

Mountain temperate forests are being reshaped simultaneously by climate warming and contrasting management legacies, yet species-specific growth responses under these combined pressures remain poorly quantified. We analysed 3590 tree-ring series from silver fir (Abies alba Mill.), European beech (Fagus sylvatica L.) and Norway spruce (Picea abies L. Karst.) sampled in 915 plots that span 1477&#x202f;m of elevation gradient across the Carpathian mountain range and paired managed versus unmanaged stands. Linear mixed-effects models were used to quantify species-specific growth responses to growing-season air temperature and climatic water balance while accounting for canopy position, region, and management. Drought resilience was further assessed using joint resistance-recovery (Rt-Rc) analyses across major regional drought years, complemented by tree-ring synchrony analyses to evaluate the strength of common climatic control. Species differed strongly in climate sensitivity and post-drought recovery strategies. Growth responses to warming ranged from positive to negative, depending on species and management context, whereas higher climatic water balance consistently enhanced growth. Climate signals were amplified in upper canopy layers and intensified along regional climatic gradients. Resistance-recovery analyses showed that most trees compensated for drought-induced growth reductions, but recovery efficiency depended on species, management regime, and canopy position. Unmanaged forests maintained stronger species differentiation in post-drought recovery, while management tended to homogenise responses. Our results demonstrate that warming, drought, and silviculture interact in contrasting ways across dominant Central European tree species, highlighting that species- and structure-specific management strategies may help sustain forest productivity and resilience under ongoing climate change.