Forestry research最新文献

Due to climate change, the timing of budbreak is occurring earlier in temperate and boreal tree species. Since the warmer conditions also cause snow to melt earlier in the spring, the hypothesis that bud reactivation of tree species of the mixedwood forests of Québec would occur under drier conditions in the future and that species from the temperate forests with late budbreak would be most exposed to dry conditions was tested. The thermal-time bud phenology model was used to predict the timing of budbreak for early and late species using 300 and 500 growing degree-days as the threshold for the timing of budbreak. Climate data was obtained from four CMIP6 climate models from 1950-2100 for two socioeconomic pathways at two locations, one in the temperate forest and one in the boreal mixedwood forest. Using linear regressions, the anomaly, which results from the difference between the historical mean (1950-1980) and the yearly values in timing of budbreak was predicted by the anomaly in drought index (SPEI) per site, climate model, socioeconomic pathways, and species with early or late budbreak timing. Budbreak is expected to occur earlier in the future, whereas the temporal trends in SPEI remained weak during April and May. When paired with the anomalies in both timing of budbreak and drought index, analyses showed that budbreak could be expected to occur under drier conditions in the future. However, due to differences between climate models, it remains uncertain whether drought stress will begin earlier in the future.

In forestry genetics and industry, tree morphological traits such as height, crown size, and shape are critical for understanding growth dynamics and productivity. Traditional methods for measuring these traits are limited in efficiency, scalability, and accuracy, posing challenges for large-scale forest assessments. This study focuses on integrating unmanned aerial vehicle (UAV) technology with GWAS to improve genomic association studies in slash pine (Pinus elliottii). Seven key morphological traits have been identified (canopy area (CA), crown base height (CBH), crown length (CL), canopy volume (CV), crown width (CW), crown width height (CWH), and tree height (H)) through advanced UAV-based phenotyping. These associations account for a remarkable range of heritability in slash pine, with traits such as CBH, CL, CV, and H showing relatively high heritability across both Single nucleotide polymorphisms (SNP) and pedigree methods, indicating strong genetic influence, while traits such as CWH show lower heritability, suggesting greater environmental influence or non-additive genetic variance. The GWAS identified 28 associations, including 22 different SNPs localized to 16 candidate genes, that were significantly associated with the morphological traits of Slash Pine. Notably, two of these candidate genes, annotated as putative DEAD-like helicase and ethylene-responsive element binding factor (ERF), were present at different mutation sites and were significantly associated with CW and CA traits, respectively. These results demonstrate that the UAV imaging enables a comprehensive analysis of the Morphological growth response of slash pine and can facilitate the discovery of informative alleles to elucidate the genetic structure underlying complex phenotypic variation in conifers.

Chinese fir is the most important native softwood tree in China and has significant economic and ecological value. Accurate assessment of the growth status is critical for both seedling cultivation and germplasm evaluation of this commercially significant tree. Needle leaf chlorophyll content (LCC) and needle leaf water content (LWC), which are determinants of plant health and photosynthetic efficiency, are important indicators of the growth status in plants. In this study, for the first time, the LCC and LWC of Chinese fir seedlings were estimated based on hyperspectral reflectance spectra and machine learning algorithms. A line-scan hyperspectral imaging system with a spectral range of 870 to 1,720 nm was used to capture hyperspectral images of seedlings with varying LCC and LWC. The spectral data of the canopy area of the seedlings were extracted and preprocessed using the Savitzky-Golay smoothing (SG) algorithm. Subsequently, the Successive Projection Algorithm (SPA) and Competitive Adaptive Reweighted Sampling (CARS) methods were employed to extract the most informative wavelengths. Moreover, SVM, PLSR and ANNs were utilized to construct models that predict LCC and LWC based on effective wavelengths. The results indicated that the CARS-ANNs were the best for predicting LCC, with R²_C = 0.932, RSME_C = 0.224, and R²_P = 0.969, RSME_P = 0.157. Similarly, the SPA-ANNs model exhibited the best prediction performance for LWC, with R²_C = 0.952, RSME_C = 0.049, and R²_P = 0.948, RSME_P = 0.051. In conclusion, the present study highlights the significant potential of combining hyperspectral imaging (HSI) with machine learning algorithms as a rapid, non-destructive, and highly accurate method for estimating LCC and LWC in Chinese fir.

This study aims to understand the genetic basis of key industrial traits in Slash pine (Pinus elliottii Engelm. var. elliottii) to enhance improvement efficiency. Detailed analyses were conducted on inter-family differences, genetic parameters, correlations, and breeding values (BVs) for growth, wood properties, and resin traits of Slash pine planted in Changle Forest Farm of Hangzhou, leading to the identification of elite families. It indicates that growth traits are primarily influenced by environmental effects, while wood properties exhibit a significant impact of genetic effects. The variation in resin traits arises from both genetic and environmental effects. Notably, Beta-pinene exhibits the highest variability and genetic gains among the traits analyzed. The family heritability ranges for growth, wood properties, and resin traits are 0.543-0.794, 0.870-0.885, and 0.285-0.695, respectively. Significant positive correlations are evident between growth and resin traits, while a negative correlation is observed between growth and wood properties. Elite families identified through single-trait and multi-trait combined selection are 8-126 for growth traits, 2-325 and 0-373 for wood properties, and 8-131 for resin traits. The average genetic gains for these elite families are 7.44%, 7.17%, and 8.84%, respectively. These findings provide valuable insights for high-generation breeding of Slash pine and lay a genetic foundation for formulating effective breeding strategies for conifers.

UV-B radiation and drought majorly restrict plant growth, particularly in summer. ELONGATED HYPOCOTYL 5 (HY5), a bZIP transcription factor (TF), has a beneficial impact on photomorphogenesis. However, the sequence of HY5 from Betula platyphylla (BpHY5) has not been identified and the gene functions remain unclarified. We cloned the sequence of BpHY5, which was targeted to the nucleus. The hypocotyl phenotypes of heterologous expression in Arabidopsis thaliana and reverse mutation showed that BpHY5 is homologous to AtHY5. The expression of BpHY5 was increased in response to UV-B radiation, drought conditions, and the presence of abscisic acid (ABA). The overexpression of BpHY5 resulted in increased tolerance to UV-B radiation and drought and decreased ABA sensitivity with higher germination and greening rate, more developmental root system, stronger reactive oxygen species scavenging ability, and lower damage degree. The lignin content under UV-B condition of BpHY5/Col was higher than that of Col. Furthermore, overexpressing BpHY5 up-regulated the expression of genes related to tolerance (NCED3/9, ABI5, DREB2A, RD20, ERF4, NDB2, and APX2). In brief, the study suggests that BpHY5 from birch serves as a beneficial modulator of plant responses to UV-B radiation and drought stress.

Real-time quantitative reverse transcription polymerase chain reaction (RT-qPCR) plays a crucial role in relative gene expression analysis, and accurate normalization relies on suitable reference genes (RGs). In this study, a pipeline for identifying candidate RGs from publicly available stem-related RNA-Seq data of different Populus species under various developmental and abiotic stress conditions is presented. DESeq2's median of ratios yielded the smallest coefficient of variance (CV) values in a total of 292 RNA-Seq samples and was therefore chosen as the method for sample normalization. A total of 541 stably expressed genes were retrieved based on the CV values with a cutoff of 0.3. Universal gene-specific primer pairs were designed based on the consensus sequences of the orthologous genes of each Populus RG candidate. The expression levels of 12 candidate RGs and six reported RGs in stems under different abiotic stress conditions or in different Populus species were assessed by RT-qPCR. The expression stability of selected genes was further evaluated using ΔCt, geNorm, NormFinder, and BestKeeper. All candidate RGs were stably expressed in different experiments and conditions in Populus. A test dataset containing 117 RNA-Seq samples was then used to confirm the expression stability, six candidate RGs and three reported RGs met the requirement of CV ≤ 0.3. In summary, this study was to propose a systematic and optimized protocol for the identification of constitutively and stably expressed genes based on RNA-Seq data, and Potri.001G349400 (CNOT2) was identified as the best candidate RG suitable for gene expression studies in poplar stems.

Populus species, particularly P. trichocarpa, have long served as model trees for genomics research, owing to fully sequenced genomes. However, the high heterozygosity, and the presence of repetitive regions, including centromeres and ribosomal RNA gene clusters, have left 59 unresolved gaps, accounting for approximately 3.32% of the P. trichocarpa genome. In this study, the callus induction method was improved to derive a doubled haploid (DH) callus line from P. ussuriensis anthers. Leveraging long-read sequencing, we successfully assembled a nearly gap-free, telomere-to-telomere (T2T) P. ussuriensis genome spanning 412.13 Mb. This genome assembly contains only seven gaps and has a contig N50 length of 19.50 Mb. Annotation revealed 34,953 protein-coding genes in this genome, which is 465 more than that of P. trichocarpa. Notably, centromeric regions are characterized by higher-order repeats, we identified and annotated centromere regions in all DH genome chromosomes, a first for poplars. The derived DH genome exhibits high collinearity with P. trichocarpa and significantly fills gaps present in the latter's genome. This T2T P. ussuriensis reference genome will not only enhance our understanding of genome structure, and functions within the poplar genus but also provides valuable resources for poplar genomic and evolutionary studies.

Point cloud registration is a necessary prerequisite for conducting precise, large-scale forest surveys and management. This paper focuses on providing a systematic overview and summary of the work on forest point cloud registration over the past 20 years. The developmental process of forest point cloud registration methods, spanning from the early reliance on manual markers to the subsequent evolution towards automatic registration based on feature matching, and then to the advanced technology based on deep learning were reviewed. Furthermore, the paper offered detailed discussions on the registration between different point cloud platforms: ground platforms, between ground platforms and aerial platforms, and between aerial platforms. Additionally, the paper delved into mainstream datasets and evaluation metrics in the domain of forest point cloud registration. Finally, the paper summarized the current state of research in this area, highlighted challenges, and provided future research outlooks. This review aims to provide researchers with a comprehensive understanding of forest point cloud registration, and to promote the advancement of point cloud technology, hopefully inspiring further applications in the field.

Walnut is an important economic tree species that is susceptible to osmotic stress. Scientific cultivation management is an important way to improve the yield and quality of walnuts, which requires understanding the regulatory mechanisms in response to osmotic stress. Therefore, in this study, 15 protein phosphatase 2A (PP2A) genes were identified from the walnut transcriptome (named JrPP2A01~15) and their potential function responses to osmotic stress were elucidated. The open reading frame (ORF) of JrPP2A01~15 ranges from 651 to 1,764 bp in length, the molecular weight of the encoded proteins are 24.15-65.61 kDa, and the theoretical isoelectric points are 4.80-8.37. These JrPP2As were unevenly distributed on 10 chromosomes and divided into five groups based on the composition of conserved domains, motifs, and exon/intron organizations. The five groups are JrPP2AAs, JrPP2AB's, JrPP2AB''s, JrPP2AB55s, and JrPP2ACs, including 1, 5, 2, 3, and 4 members, accordingly. The cis-elements in JrPP2As' promoters were involved in responses to hormone and abiotic stress. Most JrPP2A genes, excluding JrPP2A01, JrPP2A02, JrPP2A05, JrPP2A06, and JrPP2A13, could be induced significantly by PEG₆₀₀₀, NaCl, CaCl₂ and ABA. JrPP2A02, JrPP2A05, JrPP2A07, JrPP2A09, and JrPP2A14, could independently interact with a bZIP transcription factor JrVIP1. Moreover, overexpression of JrPP2A07, JrPP2A09, and JrPP2A14 could significantly decrease ROS accumulation while increasing calcium (Ca) uptake exposed to PEG₆₀₀₀ and NaCl stresses, which was mediated by exogenous CaCl₂ and ABA. These results suggested that JrPP2A genes play potential key roles in walnut response to drought and salt-inducing osmotic stress involving Ca- and ABA-dependent signaling pathways.