Height to crown base (HCB) of a tree is an important variable often included as a predictor in various forest models that serve as the fundamental tools for decision-making in forestry. We developed spatially explicit and spatially inexplicit mixed-effects HCB models using measurements from a total 19,404 trees of Norway spruce (Picea abies (L.) Karst.) and European beech (Fagus sylvatica L.) on the permanent sample plots that are located across the Czech Republic. Variables describing site quality, stand density or competition, and species mixing effects were included into the HCB model with use of dominant height (HDOM), basal area of trees larger in diameters than a subject tree (BAL- spatially inexplicit measure) or Hegyi's competition index (HCI-spatially explicit measure), and basal area proportion of a species of interest (BAPOR), respectively. The parameters describing sample plot-level random effects were included into the HCB model by applying the mixed-effects modelling approach. Among several functional forms evaluated, the logistic function was found most suited to our data. The HCB model for Norway spruce was tested against the data originated from different inventory designs, but model for European beech was tested using partitioned dataset (a part of the main dataset). The variance heteroscedasticity in the residuals was substantially reduced through inclusion of a power variance function into the HCB model. The results showed that spatially explicit model described significantly a larger part of the HCB variations [R2adj = 0.86 (spruce), 0.85 (beech)] than its spatially inexplicit counterpart [R2adj = 0.84 (spruce), 0.83 (beech)]. The HCB increased with increasing competitive interactions described by tree-centered competition measure: BAL or HCI, and species mixing effects described by BAPOR. A test of the mixed-effects HCB model with the random effects estimated using at least four trees per sample plot in the validation data confirmed that the model was precise enough for the prediction of HCB for a range of site quality, tree size, stand density, and stand structure. We therefore recommend measuring of HCB on four randomly selected trees of a species of interest on each sample plot for localizing the mixed-effects model and predicting HCB of the remaining trees on the plot. Growth simulations can be made from the data that lack the values for either crown ratio or HCB using the HCB models.

• MeSH
• biologické modely * MeSH
• buk (rod) růst a vývoj   MeSH
• smrk růst a vývoj   MeSH
• Publikační typ
• časopisecké články MeSH
• validační studie MeSH

Here, we perform cross-generational GS analysis on coastal Douglas-fir (Pseudotsuga menziesii), reflecting trans-generational selective breeding application. A total of 1321 trees, representing 37 full-sib F1 families from 3 environments in British Columbia, Canada, were used as the training population for (1) EBVs (estimated breeding values) of juvenile height (HTJ) in the F1 generation predicting genomic EBVs of HTJ of 136 individuals in the F2 generation, (2) deregressed EBVs of F1 HTJ predicting deregressed genomic EBVs of F2 HTJ, (3) F1 mature height (HT35) predicting HTJ EBVs in F2, and (4) deregressed F1 HT35 predicting genomic deregressed HTJ EBVs in F2. Ridge regression best linear unbiased predictor (RR-BLUP), generalized ridge regression (GRR), and Bayes-B GS methods were used and compared to pedigree-based (ABLUP) predictions. GS accuracies for scenarios 1 (0.92, 0.91, and 0.91) and 3 (0.57, 0.56, and 0.58) were similar to their ABLUP counterparts (0.92 and 0.60, respectively) (using RR-BLUP, GRR, and Bayes-B). Results using deregressed values fell dramatically for both scenarios 2 and 4 which approached zero in many cases. Cross-generational GS validation of juvenile height in Douglas-fir produced predictive accuracies almost as high as that of ABLUP. Without capturing LD, GS cannot surpass the prediction of ABLUP. Here we tracked pedigree relatedness between training and validation sets. More markers or improved distribution of markers are required to capture LD in Douglas-fir. This is essential for accurate forward selection among siblings as markers that track pedigree are of little use for forward selection of individuals within controlled pollinated families.

• MeSH
• genomika MeSH
• lineární modely MeSH
• modely genetické MeSH
• Pseudotsuga genetika   růst a vývoj   MeSH
• šlechtění rostlin MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH
• Geografické názvy
• Britská Kolumbie MeSH

BACKGROUND: Genomic selection (GS) can offer unprecedented gains, in terms of cost efficiency and generation turnover, to forest tree selective breeding; especially for late expressing and low heritability traits. Here, we used: 1) exome capture as a genotyping platform for 1372 Douglas-fir trees representing 37 full-sib families growing on three sites in British Columbia, Canada and 2) height growth and wood density (EBVs), and deregressed estimated breeding values (DEBVs) as phenotypes. Representing models with (EBVs) and without (DEBVs) pedigree structure. Ridge regression best linear unbiased predictor (RR-BLUP) and generalized ridge regression (GRR) were used to assess their predictive accuracies over space (within site, cross-sites, multi-site, and multi-site to single site) and time (age-age/ trait-trait). RESULTS: The RR-BLUP and GRR models produced similar predictive accuracies across the studied traits. Within-site GS prediction accuracies with models trained on EBVs were high (RR-BLUP: 0.79-0.91 and GRR: 0.80-0.91), and were generally similar to the multi-site (RR-BLUP: 0.83-0.91, GRR: 0.83-0.91) and multi-site to single-site predictive accuracies (RR-BLUP: 0.79-0.92, GRR: 0.79-0.92). Cross-site predictions were surprisingly high, with predictive accuracies within a similar range (RR-BLUP: 0.79-0.92, GRR: 0.78-0.91). Height at 12 years was deemed the earliest acceptable age at which accurate predictions can be made concerning future height (age-age) and wood density (trait-trait). Using DEBVs reduced the accuracies of all cross-validation procedures dramatically, indicating that the models were tracking pedigree (family means), rather than marker-QTL LD. CONCLUSIONS: While GS models' prediction accuracies were high, the main driving force was the pedigree tracking rather than LD. It is likely that many more markers are needed to increase the chance of capturing the LD between causal genes and markers.

• MeSH
• dřevo chemie   genetika   MeSH
• exom * MeSH
• genomika MeSH
• genotyp MeSH
• lineární modely MeSH
• lokus kvantitativního znaku MeSH
• modely genetické * MeSH
• Pseudotsuga genetika   růst a vývoj   MeSH
• selekce (genetika) * MeSH
• šlechtění rostlin * MeSH
• vysoce účinné nukleotidové sekvenování MeSH
• Publikační typ
• časopisecké články MeSH

Conifers and other trees are constantly adapting to changes in light conditions, water/nutrient supply and temperatures by physiological and morphological modifications of their foliage. However, the relationship between physiological processes and anatomical characteristics of foliage has been little explored in trees. In this study we evaluated needle structure and function in Norway spruce families exposed to different light conditions and transpiration regimes. We compared needle characteristics of sun-exposed and shaded current-year needles in a control plot and a thinned plot with 50% reduction in stand density. Whole-tree transpiration rates remained similar across plots, but increased transpiration of lower branches after thinning implies that sun-exposed needles in the thinned plot were subjected to higher water stress than sun-exposed needles in the control plot. In general, morphological and anatomical needle parameters increased with increasing tree height and light intensity. Needle width, needle cross-section area, needle stele area and needle flatness (the ratio of needle thickness to needle width) differed most between the upper and lower canopy. The parameters that were most sensitive to the altered needle water status of the upper canopy after thinning were needle thickness, needle flatness and percentage of stele area in needle area. These results show that studies comparing needle structure or function between tree species should consider not only tree height and light gradients, but also needle water status. Unaccounted for differences in needle water status may have contributed to the variable relationship between needle structure and irradiance that has been observed among conifers.

• MeSH
• aklimatizace MeSH
• dehydratace MeSH
• dusík metabolismus   MeSH
• listy rostlin anatomie a histologie   metabolismus   fyziologie   MeSH
• půda analýza   MeSH
• sluneční záření MeSH
• smrk anatomie a histologie   metabolismus   fyziologie   MeSH
• transpirace rostlin MeSH
• vlhkost MeSH
• voda analýza   fyziologie   MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH
• srovnávací studie MeSH

What causes individual tree death in tropical forests remains a major gap in our understanding of the biology of tropical trees and leads to significant uncertainty in predicting global carbon cycle dynamics. We measured individual characteristics (diameter at breast height, wood density, growth rate, crown illumination and crown form) and environmental conditions (soil fertility and habitat suitability) for 26 425 trees ≥ 10 cm diameter at breast height belonging to 416 species in a 52-ha plot in Lambir Hills National Park, Malaysia. We used structural equation models to investigate the relationships among the different factors and tree mortality. Crown form (a proxy for mechanical damage and other stresses) and prior growth were the two most important factors related to mortality. The effect of all variables on mortality (except habitat suitability) was substantially greater than expected by chance. Tree death is the result of interactions between factors, including direct and indirect effects. Crown form/damage and prior growth mediated most of the effect of tree size, wood density, fertility and habitat suitability on mortality. Large-scale assessment of crown form or status may result in improved prediction of individual tree death at the landscape scale.

• MeSH
• biologické modely MeSH
• dřevo chemie   MeSH
• ekosystém MeSH
• fyziologický stres MeSH
• lesy * MeSH
• stromy fyziologie   MeSH
• tropické klima MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH
• Research Support, U.S. Gov't, Non-P.H.S. MeSH
• Geografické názvy
• Malajsie MeSH

The aim of this study was to evaluate (1) effects of bark stripping and climatic factors on radial growth of Picea abies /L./ Karst., (2) production and structural differences between stands established on the forestland and abandoned farmland (afforested farmland-henceforth, farmland), and (3) interaction among the losses caused by ungulate damages, production, diversity, and soil types. Data acquired from four permanent research plots (PRPs) located on the forestland and eight PRPs on the farmland were used. A number of tree- and stand-level models, stand structural indices, tree-rings, and climate characteristics were analysed to evaluate the hypotheses. The results show significantly higher means of DBH, tree height and basal area on the forestland compared to those on the farmland. There was a larger mean standing stem volume on the forestland (466 m3 ha-1) compared to farmland (770 m3 ha-1). Significant difference was observed between the mean DBH and mean stem volume of healthy trees compared to those of the trees with substantial damage (girth damage >1/3 of stem circumference). A greater extent of the girth damage was found on 86% trees on the farmland, while 54% damage on the forestland. About 62% bark-strip damage was further deteriorated by rot infection on the farmland, while on the forestland such an infection was only for 39% trees. The precipitation significantly positively affected the radial growth of trees that were largely affected by ungulate damages on the farmland.

• MeSH
• biologické modely * MeSH
• farmy * MeSH
• kůra rostlin * MeSH
• lesy * MeSH
• podnebí * MeSH
• smrk růst a vývoj   MeSH
• vysoká zvěř fyziologie   MeSH
• zvířata MeSH
• Check Tag
• zvířata MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH

Narrow sense heritability [Formula: see text] is a key concept in quantitative genetics, as it expresses the proportion of the observed phenotypic variation that is transmissible from parents to offspring. [Formula: see text] determines the resemblance among relatives, and the rate of response to artificial and natural selection. Classical methods for estimating [Formula: see text] use random samples of individuals with known relatedness, as well as response to artificial selection, when it is called realized heritability. Here, we present a method for estimating realized [Formula: see text] based on a simple assessment of a random-mating population with no artificial manipulation of the population structure, and derive SE of the estimates. This method can be applied to arbitrary phenotypic segments of the population (for example, the top-ranking p parents and offspring), rather than random samples. It can thus be applied to nonpedigreed random mating populations, where relatedness is determined from molecular markers in the p selected parents and offspring, thus substantially saving on genotyping costs. Further, we assessed the method by stochastic simulations, and, as expected from the mathematical derivation, it provides unbiased estimates of [Formula: see text] We compared our approach to the regression and maximum-likelihood approaches utilizing Galton's dataset on human heights, and all three methods provided identical results.

• MeSH
• algoritmy MeSH
• fenotyp MeSH
• kvantitativní znak dědičný MeSH
• lidé MeSH
• modely genetické * MeSH
• počítačová simulace MeSH
• populační genetika * MeSH
• rodokmen MeSH
• selekce (genetika) MeSH
• tělesná výška MeSH
• typy dědičnosti * MeSH
• Check Tag
• lidé MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH

Maximization of genetic gain in forest tree breeding programs is contingent on the accuracy of the predicted breeding values and precision of the estimated genetic parameters. We investigated the effect of the combined use of contemporary pedigree information and genomic relatedness estimates on the accuracy of predicted breeding values and precision of estimated genetic parameters, as well as rankings of selection candidates, using single-step genomic evaluation (HBLUP). In this study, two traits with diverse heritabilities [tree height (HT) and wood density (WD)] were assessed at various levels of family genotyping efforts (0, 25, 50, 75, and 100%) from a population of white spruce (Picea glauca) consisting of 1694 trees from 214 open-pollinated families, representing 43 provenances in Québec, Canada. The results revealed that HBLUP bivariate analysis is effective in reducing the known bias in heritability estimates of open-pollinated populations, as it exposes hidden relatedness, potential pedigree errors, and inbreeding. The addition of genomic information in the analysis considerably improved the accuracy in breeding value estimates by accounting for both Mendelian sampling and historical coancestry that were not captured by the contemporary pedigree alone. Increasing family genotyping efforts were associated with continuous improvement in model fit, precision of genetic parameters, and breeding value accuracy. Yet, improvements were observed even at minimal genotyping effort, indicating that even modest genotyping effort is effective in improving genetic evaluation. The combined utilization of both pedigree and genomic information may be a cost-effective approach to increase the accuracy of breeding values in forest tree breeding programs where shallow pedigrees and large testing populations are the norm.

• MeSH
• chov MeSH
• genetické markery MeSH
• genotypizační techniky metody   MeSH
• opylení genetika   MeSH
• rodokmen MeSH
• smrk genetika   MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH
• Research Support, U.S. Gov't, Non-P.H.S. MeSH

BACKGROUND: Mutations in the melanocortin 4 receptor gene (MC4R) represent the most common known cause of monogenic human obesity. AIMS: The aims of this study were the following: 1) to estimate the prevalence of MC4R mutations in obese Czech children; 2) to evaluate phenotypic features of the mutation carriers; 3) to compare weight, height, and body mass index of MC4R mutation carriers with noncarriers in longitudinal studies; 4) to determine the effect of a weight management program among MC4R mutation carriers; and 5) to perform a functional analysis of a novel variant. SUBJECTS AND METHODS: We analyzed the coding region of MC4R in a cohort of 289 Czech children and adolescents with early-onset obesity by direct sequencing. Information on weight, height, body mass index, baseline biochemical data, and a weight loss follow-up study was obtained. In vitro functional analysis of one novel variant was performed. RESULTS: We identified six different mutations in seven probands: one novel missense mutation Cys84Arg and five previously reported variants, Arg7Cys, Ser19fsdelA, Phe51Leu, Ser127Leu, and Gly181Asp. The Gly181Asp variant was detected in one homozygous carrier from unrelated parents. None of the mutation carriers fulfilled the MC4R syndrome criteria. A comparison of anthropometrics in mutation carriers and noncarriers during 13 yr of follow-up did not reveal any significant differences. MC4R mutation carriers exhibited a similar ability to lose weight as obese noncarriers. The novel variant Cys84Arg showed a significant reduction in cAMP signal properties of the MC4R. CONCLUSIONS: Among obese Czech children, we found a prevalence of 2.4% of MC4R homozygous and heterozygous mutations and showed a similar response to diet management of MC4R mutation carriers and noncarriers.

• MeSH
• biologické modely MeSH
• dítě MeSH
• dospělí MeSH
• fenotyp MeSH
• financování organizované MeSH
• frekvence genu MeSH
• hmotnostní úbytek fyziologie   MeSH
• lidé MeSH
• mladiství MeSH
• mutace MeSH
• mutační analýza DNA MeSH
• následné studie MeSH
• obezita dietoterapie   genetika   patofyziologie   MeSH
• předškolní dítě MeSH
• receptor melanokortinový typ 4 genetika   fyziologie   MeSH
• rodokmen MeSH
• studie případů a kontrol MeSH
• tělesná hmotnost genetika   MeSH
• tělesná výška genetika   MeSH
• Check Tag
• dítě MeSH
• dospělí MeSH
• lidé MeSH
• mladiství MeSH
• mužské pohlaví MeSH
• předškolní dítě MeSH
• ženské pohlaví MeSH
• Publikační typ
• srovnávací studie MeSH
• Geografické názvy
• Česká republika MeSH

Genomic selection (GS) potentially offers an unparalleled advantage over traditional pedigree-based selection (TS) methods by reducing the time commitment required to carry out a single cycle of tree improvement. This quality is particularly appealing to tree breeders, where lengthy improvement cycles are the norm. We explored the prospect of implementing GS for interior spruce (Picea engelmannii × glauca) utilizing a genotyped population of 769 trees belonging to 25 open-pollinated families. A series of repeated tree height measurements through ages 3-40 years permitted the testing of GS methods temporally. The genotyping-by-sequencing (GBS) platform was used for single nucleotide polymorphism (SNP) discovery in conjunction with three unordered imputation methods applied to a data set with 60% missing information. Further, three diverse GS models were evaluated based on predictive accuracy (PA), and their marker effects. Moderate levels of PA (0.31-0.55) were observed and were of sufficient capacity to deliver improved selection response over TS. Additionally, PA varied substantially through time accordingly with spatial competition among trees. As expected, temporal PA was well correlated with age-age genetic correlation (r=0.99), and decreased substantially with increasing difference in age between the training and validation populations (0.04-0.47). Moreover, our imputation comparisons indicate that k-nearest neighbor and singular value decomposition yielded a greater number of SNPs and gave higher predictive accuracies than imputing with the mean. Furthermore, the ridge regression (rrBLUP) and BayesCπ (BCπ) models both yielded equal, and better PA than the generalized ridge regression heteroscedastic effect model for the traits evaluated.

• MeSH
• genotyp MeSH
• genotypizační techniky metody   MeSH
• jednonukleotidový polymorfismus MeSH
• modely genetické * MeSH
• populační genetika MeSH
• selekce (genetika) * MeSH
• smrk genetika   MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH
• srovnávací studie MeSH
• Geografické názvy
• Britská Kolumbie MeSH