Accurate phenotyping is essential for genetic evaluation in forest breeding, but repeated measurements in large clonal trials are labor-intensive and can be confounded by within-site environmental heterogeneity. Unmanned aerial vehicles (UAVs) equipped with red–green–blue (RGB) sensors provide a scalable approach for repeated structural and spectral phenotyping. We hypothesized spatial correction and RGB covariates may improve prediction precision, while reaction norms reveal genotype-specific environmental sensitivity. Therefore, we evaluated UAV-derived canopy height and RGB vegetation indices in two Brazilian Eucalyptus clonal trials. The site from São José dos Campos (SP) included pure E. grandis and E. grandis × E. urophylla genotypes (45 clones, 2,576 trees; five campaigns at 419, 470, 530, 645, and 956 days after planting [DAP]). The site from Três Lagoas (MS), included pure E. urophylla and E. urophylla × E. grandis genotypes (72 clones, 6,048 trees; four campaigns at 272, 341, 403, and 463 DAP). Four mixed models were compared: a randomized complete block model (M1), M1 plus a spectral covariate (M2), a two-dimensional spatial P-spline model (M3), and the spatial model plus a spectral covariate (M4). UAV canopy height was validated against 777 field measurements (R² = 0.74, r = 0.86, RMSE = 1.61 m, relative error = 23.33
Niche-based models have been widely used to identify potential species for deployment in target environments; however, these approaches rely primarily on natural distribution data and may underestimate the full adaptive potential of commercial species. In contrast, large-scale tree breeding trial networks provide direct empirical evidence of performance, but their implementation is costly and time-consuming. This study aimed to evaluate the extent to which niche-based species suitability approaches align with empirical performance observed in multi-environment progeny trial networks and to assess whether genetic trial data can refine deployment recommendations beyond species-level climatic suitability. Using a multi-country network of E. urophylla progeny trials, we evaluated patterns of genetic performance and stability across Köppen (1936) classes and investigated whether genotype-by-environment interactions could be structured into operational environmental domains. Observed genetic performance was compared with conventional niche-based suitability classifications. Results revealed that productivity showed substantial variation across environments, with mean annual increment ranging from 1.4 to 34.1 m³ ha⁻¹ yr⁻¹. The highest estimated marginal mean (EMM) productivity was observed in humid tropical climates, particularly tropical rainforest (Af; 17.95 m³ ha⁻¹ yr⁻¹) and tropical monsoon (Am; 13.99 m³ ha⁻¹ yr⁻¹), whereas tropical savanna (Aw; 9.39 m³ ha⁻¹ yr⁻¹) and temperate dry-winter, warm-summer (Cwb; 8.94 m³ ha⁻¹ yr⁻¹) climates showed reductions of up to 50
In the course of the 4th German National Forest Inventory about 5,000 samples of Scots pine have been collected all over Germany. Analysis of 21 mitochondrial SNP markers on the collected samples allowed the detection of a clear spatial genetic structure separating Northeast and Southwest Germany. This spatial genetic structure is continued in neighbouring European countries and Germany appears to represent a border region between different genetic lineages of Scots pine. Analysis of more than 30,000 nuclear SNPs from the PiSy50k SNP array also allowed the detection of a weak but spatially coherent genetic structure mirroring the Northeast and Southwest separation detected with the mitochondrial markers. Northeast Germany appears to have been populated quite evenly by two relatively distinct genetic lineages of different origin and shows a slightly increased genetic diversity in contrast to the rest of Germany. Southwest Germany has been populated by two less distinct genetic lineages, one of them dominating in the West and one of them in the South. Additionally, a large haplotype block or potential inversion on linkage group/chromosome 12 which is mainly distributed in Northwest Germany has been identified.
Populus nigra L. is an ecologically important floodplain tree species whose declining and increasingly fragmented populations are exposed to the increased risk of inbreeding. This paper aimed to study mating processes that can occur in such populations. Offspring of mother trees with different levels of inbreeding and three types of pollination (inbred, outbred, and open pollination) were compared based on their vitality, assessed through seed germination and growth characteristics, over three consecutive years. Inbred crosses produced offspring that were the worst in most of the studied traits and in all observation years, demonstrating inbreeding depression. A negative association between inbreeding coefficients and the studied characteristics was confirmed in most cases. Parentage analysis of open-pollinated seedlings using eight microsatellite loci identified up to 49
The huge genome of coniferous trees and the extremely scarce validation genes lead to a long-term inefficiency in the exploration of stress-resistant genes. This study proposes the cross-species adaptive transfer learning framework CLAP-HMM v2, which systematically integrates domain adversarial (DANN), dynamic MMD regularization, and MAML few-shot meta-learning, successfully solving the negative transfer problem caused by the over 320 million years of evolutionary distance between poplar and pine trees. Across four representative pine species, including Pinus taeda, Pinus tabuliformis, Pinus albicaulis, and Pinus radiata, the model achieved an F1-score of 0.912 (improving by 14.1
