Research Highlights: Although a number of forestry studies have found that hydrogel improves tree performance, studies that are located in semi-arid regions and that include a broad spectrum of tree species and the assessment of multiple physiological traits are lacking. Background and Objectives: The objective of the current study was to evaluate the effects of hydrogel treatments (with sawdust, organic fertilizer, compost, wheat straw, subsoil, or subsoil with a cobble cover) applied during planting on the survival, growth, and physiological traits of 20 tree species. Materials and Methods: In a field experiment (factorial design with seven treatments including a control, 20 species, and ten replicates) in a semi-arid part of Iran, we applied water alone (control) or water with hydrogel and other materials to recently planted samplings. We evaluated tree height, health, osmotic potential, and biochemical properties after 6 months and survival after 12 months. Results: Hydrogel treatment (regardless of other material) significantly improved the performance of drought-sensitive but not of drought-tolerant species. Conclusions: The benefits of hydrogel treatment are substantial for drought-sensitive species but are insignificant for drought-resistant species.

Norway spruce has a broad natural distribution range, which results in a substantial variety of its physiological and genetic variation. There are three distinct altitudinal ecotypes described in this tree species. The physiological optimum of each ecotype may be shifted due to ongoing climate change, especially in traits associated with water demand that might be crucial for adaptation. Dehydrins are proteins that help to mitigate the adverse effects of dehydration. Dehydrin gene expression patterns appeared to be a suitable marker for plant stress assessment. Genetically determined differences in response between individuals and populations were formerly studied, however, mainly in controlled conditions. We evaluated ecotypic variation in dehydrin gene expression in a clonal bank comprised of all three ecotypes. A genetic relationship among targeted trees was uncovered utilizing GBS (Genotyping by Sequencing) platform. We sampled 4–6 trees of each ecotype throughout 15 months period. Subsequently, we assessed the RNA expression of dehydrin genes by qRT-PCR. For this study, we deliberately selected dehydrins from different categories. Our findings detected significant differences among ecotypes in dehydrin expression. The association of recorded climatic variables and individual gene expression across the study period was evaluated and revealed, for certain genes, a correlation between dehydrin gene expression and precipitation, temperature, and day-length.

Norway Spruce (Picea abies (L.) H. Karst.), a timber species of significant economic and ecological importance in the Northern Hemisphere, faces increasing threats imposed by drought and bark beetle infestation intensified by ongoing climate change. Despite the extensive mortality within stands, a small proportion of mature trees remarkably survive during severe bark beetle outbreaks. Hypothesizing that bark beetle resilience is genetically determined and thus is under natural selection, we anticipated that there is a genetic variation in genome regions linked to the respective resistance in surviving trees. In the Bohemian Forest, restricted to the area of the Czech–Austrian–German border, we identified those resistant individuals, referred to as the “Last Trees Standing” (LTS). Concurrently, we collected reference samples from randomly selected individuals from natural regeneration within concerned sites (seedlings, young trees) and in adjacent unaffected stands (mature trees). Genomic data were generated on a 50K SNPs genotyping array. We conducted a population genetic study based on the Discriminant Analysis of Principal Components (DAPC) method as well as the Genome-Wide Association Study (GWAS). We identified 12 markers (SNPs) significantly associated with tree survival using this approach. Three of those SNPs are located within the genes with the known function in Arabidopsis thaliana orthologs. After further confirmation, we argue that the identified SNPs can be instrumental in identifying trees of higher resistance to bark beetle infestation.

Spontaneous variation in appearance was studied in bacterial colonies of Serratia marcescens F morphotype ¹ : (i) A defined array of non-heritable phenotype variations does appear repeatedly; (ii) The presence of colonies of different bacterial species will narrow the variability toward the typical F appearance, as if such an added environmental factor curtailed the capacity of colony morphospace; (iii) Similarly the morphospace becomes reduced by random mutations leading to new, heritable morphotypes—at the same time opening a new array of variations typical for the mutant but not accessible directly from the original F morphospace. Results are discussed in context with biphasic model of early morphogenesis applicable to all multicellular bodies.

Key message : Leveraging affordable red-green-blue (RGB) imaging and neural network algorithms, this study delivers a high-throughput method to quantify seasonal color shifts and genetic variation in Scots pine seedlings. Hue-saturation-brightness (HSB) color analysis, and RGB values can be used for population and seasonal differentiation and hold potential for advancing breeding programs in forestry under changing climatic conditions. Context: Scots pine ( Pinus sylvestris L.) displays remarkable genetic and phenotypic diversity, with seasonal color changes such as autumn reddening, reflecting population-level responses to local environmental conditions. Advances in imaging and deep learning now enable precise quantification of such phenotypic variation, providing new insights into population-level variation. Aims: This study assesses seasonal color variation within and among Scots pine seedling populations, compares the effectiveness of RGB and HSB systems for population and seasonal differentiation, and investigates phenological patterns across progenies of three seed orchards from ecologically distinct populations. Methods: One-year-old seedlings from lowland (Plasy, Trebon) and upland (Decin) populations were imaged in a common garden trial in September, October, and January using a handheld camera. Needle-level segmentation was performed via a convolutional neural network. Genetic variability and population differences were analyzed using linear mixed models. Results: Population differentiation reached the highest values in the RGB blue channel ( Q _ST-blue = 0.64 in September and Q _ST-blue = 0.94 in October) and in HSB ( Q _ST-hue = 0.61, Q _{ST-saturation} = 0.62 in September and Q _{ST-saturation} = 0.64 in October). Color wheel visualizations revealed converging hue and saturation trajectories, indicating gradual phenological changes in the post-growing season. September values exhibited the highest heritability ( h ² _RGB = 0.12–0.25; h ² _HSB = 0.12–0.29) among measured optical traits. Conclusion: This study demonstrates that RGB and HSB color parameters, extracted from high-throughput image analysis using CNN-based needle segmentation, capture both seasonal and genetic variation in Scots pine seedlings. The highest genetic differentiation and heritability occurred during early autumn, particularly in the blue and saturation parameters. These findings suggest that autumn color traits, quantifiable using simple digital imaging, can serve as cost-effective indicators in tree breeding programs.

As a result of climate change, Norway spruce (Picea abies [L.] Karst.) is dying across Europe. One of the primary reasons for this is the cultivation of unsuitable spruce provenances and ecotypes. This study deals with the growth and genetics of the ecotypes of Norway spruce, the most important tree species of the Czech Republic. At the study site, namely Cukrák, an experimental site was established in 1964 to plant three basic spruce ecotypes: low-elevation (LE), medium-elevation (ME) and high-elevation (HE) ecotype. A dendrometric inventory, dendrochronological sampling and genetic analyses were carried out on individual trees in 45 to 46 years old spruce stands. The ME ecotype was the most productive in terms of its carbon sequestration potential, while the HE ecotype had the lowest radial growth. All ecotypes exhibited a noteworthy negative correlation between tree-ring growth and seasonal temperature, annual temperature, previous year September to current year August temperature, June to July temperature, as well as individual monthly temperatures from previous May to current August. The relationship of annual and seasonal precipitation to growth was significant only for the LE and ME ecotypes, but precipitation from previous year September to current year August and precipitation from current June to July were the most significant for all ecotypes, where the ME had the highest r value. The HE ecotype does not adapt well to a dry climate and appears to be unsuitable compared to the other ecotypes under the studied conditions. This study also documented intra-population genetic variation within years of low growth, as evidenced by significant clonal heritability. The selection of the appropriate spruce ecotypes is essential for the stability and production of future stands and should become an important pillar of forest adaptation to climate change.