Soil respiration is the key process driving CO2 exchange between forest soils and the atmosphere and regulated by soil organic carbon (SOC) characteristics and extracellular enzyme activities. However...

The root-to-shoot (R/S) ratio is a critical indicator of the balance between root biomass and shoot biomass, representing the ecological strategies and adaptive responses of plants to environmental co...

Populus species, important economic species combining rapid growth with broad ecological adaptability, play a critical role in sustainable forestry and bioenergy production. In this study, we performed whole-genome resequencing of 707 individuals from a full-sib family to develop comprehensive single nucleotide polymorphism (SNP) markers and constructed a high-density genetic linkage map of 19 linkage groups. The total genetic length of the map reached 3623.65 cM with an average marker interval of 0.34 cM. By integrating multidimensional phenotypic data, 89 quantitative trait loci (QTL) associated with growth, wood physical and chemical properties, disease resistance, and leaf morphology traits were identified, with logarithm of odds (LOD) scores ranging from 3.13 to 21.72 and phenotypic variance explained between 1.7 and 11.6%. Notably, pleiotropic analysis revealed significant colocalization hotspots on chromosomes LG1, LG5, LG6, LG8, and LG14, with epistatic interaction network analysis confirming genetic basis of coordinated regulation across multiple traits. Functional annotation of 207 candidate genes showed that R2R3-MYB and bHLH transcription factors and pyruvate kinase-encoding genes were significantly enriched, suggesting crucial roles in lignin biosynthesis and carbon metabolic pathways. Allelic effect analysis indicated that the frequency of favorable alleles associated with target traits ranged from 0.20 to 0.55. Incorporation of QTL-derived favorable alleles as random effects into Bayesian-based genomic selection models led to an increase in prediction accuracy ranging from 1 to 21%, with Bayesian ridge regression as the best predictive model. This study provides valuable genomic resources and genetic insights for deciphering complex trait architecture and advancing molecular breeding in poplar.

Detailed individual tree crown segmentation is highly relevant for the detection and monitoring of Fraxinus excelsior L. trees affected by ash dieback, a major threat to common ash populations across Europe. In this study, both fine and coarse crown segmentation methods were applied to close-range multispectral UAV imagery. The fine tree crown segmentation method utilized a novel unsupervised machine learning approach based on a blended NIR–NDVI image, whereas the coarse segmentation relied on the segment anything model (SAM). Both methods successfully delineated tree crown outlines, however, only the fine segmentation accurately captured internal canopy gaps. Despite these structural differences, mean NDVI values calculated per tree crown revealed no significant differences between the two approaches, indicating that coarse segmentation is sufficient for mean vegetation index assessments. Nevertheless, the fine segmentation revealed increased heterogeneity in NDVI values in more severely damaged trees, underscoring its value for detailed structural and health analyses. Furthermore, the fine segmentation workflow proved transferable to both individual UAV images and orthophotos from broader UAV surveys. For applications focused on structural integrity and spatial variation in canopy health, the fine segmentation approach is recommended.