Genotype by environment interactions in forest tree breeding: review of methodology and perspectives on research and application

Genotype by environment interaction (G×E) refers to the comparative performances of genotypes differing among environments, representing differences in genotype rankings or differences in the level of expression of genetic differences among environments. G×E can reduce heritability and overall genetic gain, unless breeding programmes are structured to address different categories of environments. Understanding the impact of G×E, the role of environments in generating G×E and the problems and opportunities is vital to efficient breeding programme design and deployment of genetic material. We review the current main analytical methods for identifying G×E: factor analytic models, biplot analysis and reaction norm. We also review biological and statistical evidence of G×E for growth, form and wood properties in forest species of global economic importance, including some pines, eucalypts, Douglas-fir, spruces and some poplars. Among these species, high levels of G×E tend to be reported for growth traits, with low levels of G×E for form traits and wood properties. Finally, we discuss possible ways of exploiting G×E to maximise genetic gain in forest tree breeding. Characterising the role of environments in generating interactions is seen as the basic platform, allowing efficient testing of candidate genotypes. We discuss the importance of level-of-expression interaction, relative to rank-change interaction, as being greater than in many past reports, especially for deployment decisions. We examine the impacts of G×E on tree breeding, some environmental factors that cause G×E and the strategies for dealing with G×E in tree breeding, and the future role of genomics.     

Genotype by environment interactions for Pinus radiata in New South Wales, Australia

Historical data from 26 progeny trials in the NSW breeding program was analyzed to determine the extent and practical importance of genotype by environment (G×E) interactions for a range of traits. Significant G×E interaction was present for diameter (DBH) with 75% of the 35 estimated between-site genetic correlations falling below the threshold value of 0.6 where regionalization should be considered. Estimated genetic correlations for stem straightness, branch quality, and outerwood density were much higher, indicating these traits are not as affected by G×E. Levels of G×E for DBH are sufficient to have serious impacts on the expression of genetic gain in deployed material. For DBH, altitude differences between sites appear to be the key factor driving the G×E with a difference of greater than 280 m in altitude leading to a breakdown in correlations. Two groups of sites were identified as having limited G×E within each group: one for sites above 900 m elevation plus a lower-altitude group. Sites included in the higher-altitude group were located across the entire north–south geographic range of NSW. Equations for prediction of site mean DBH indicate that altitude, prior land use, and underlying geology are key driving variables. A more complex model was developed for predicting the between-site genetic correlations for DBH with the model accounting for approximately 50% of the observed variation.     

A novel method for identifying nonlinear gene–environment interactions in case–control association studies

The genetic influences on complex disease traits generally depend on the joint effects of multiple genetic variants, environmental factors, as well as their interplays. Gene × environment (G × E) interactions play vital roles in determining an individual’s disease risk, but the underlying genetic machinery is poorly understood. Traditional analysis assuming linear relationship between genetic and environmental factors, along with their interactions, is commonly pursued under the regression-based framework to examine G × E interactions. This assumption, however, could be violated due to nonlinear responses of genetic variants to environmental stimuli. As an extension to our previous work on continuous traits, we proposed a flexible varying-coefficient model for the detection of nonlinear G × E interaction with binary disease traits. Varying coefficients were approximated by a non-parametric regression function through which one can assess the nonlinear response of genetic factors to environmental changes. A group of statistical tests were proposed to elucidate various mechanisms of G × E interaction. The utility of the proposed method was illustrated via simulation and real data analysis with application to type 2 diabetes.     

Microsatellite marker-based genetic diversity analysis of elite lentil lines differing in grain iron and zinc concentration

Trial comprising fifty lentil genotypes was conducted at three locations in India during year 2013–2014 for estimation of grain Fe and Zn concentrations and to analyze G × E interactions by employing the additive main effect and multiplication interaction model. The study revealed significant effects for genotype, environment and genotype by environment interaction for both grain Fe and Zn concentration. In this model genotypes with the IPCA score of nearly zero and mean greater than grand mean are considered as adaptable to the studied environments. For grain Fe concentration genotypes P13143, P13135, ILL2581, P2130, LL147, L4603, PL101 and Globe mutant and for grain Zn concentration genotypes P13122, P2239, P3204 and L11-245 were found stable. The diversity analysis using 20 genomic and 54 EST-SSR markers indicated that the studied genotypes were diverse. The EST-SSRs revealed lower polymorphism as compare to genomic SSRs. Two major clusters were identified with 37 % similarity. Indigenous genotypes were grouped in cluster I and all exotic accessions were grouped in cluster II indicating the role of geographic origin in diversity. Based on multi location evaluation for grain Fe and Zn concentrations and molecular characterization crosses are proposed for development of grain Fe and Zn rich varieties (P3220 × L4649 and VL103 × P2130) and development of mapping populations (P13122 × L11-287 and LL931 × P3220) for study of genetics and mapping of QTLs/gene(s).     

Gene-environment interactions and obesity traits among postmenopausal African-American and Hispanic women in the Women’s Health Initiative SHARe Study

Genome-wide association studies (GWAS) of obesity measures have identified associations with single nucleotide polymorphisms (SNPs). However, no large-scale evaluation of gene-environment interactions has been performed. We conducted a search of gene-environment (G × E) interactions in post-menopausal African-American and Hispanic women from the Women’s Health Initiative SNP Health Association Resource GWAS study. Single SNP linear regression on body mass index (BMI) and waist-to-hip circumference ratio (WHR) adjusted for multidimensional-scaling-derived axes of ancestry and age was run in race-stratified data with 871,512 SNPs available from African-Americans (N = 8,203) and 786,776 SNPs from Hispanics (N = 3,484). Tests of G × E interaction at all SNPs for recreational physical activity (m h/week), dietary energy intake (kcal/day), alcohol intake (categorical), cigarette smoking years, and cigarette smoking (ever vs. never) were run in African-Americans and Hispanics adjusted for ancestry and age at interview, followed by meta-analysis of G × E interaction terms. The strongest evidence for concordant G × E interactions in African-Americans and Hispanics was for smoking and marker rs10133840 (Q statistic P = 0.70, beta = ?0.01, P = 3.81 × 10^?7) with BMI as the outcome. The strongest evidence for G × E interaction within a cohort was in African-Americans with WHR as outcome for dietary energy intake and rs9557704 (SNP × kcal = ?0.04, P = 2.17 × 10^?7). No results exceeded the Bonferroni-corrected statistical significance threshold.     

Genome-wide investigation of gene–environment interactions in colorectal cancer

Colorectal cancer (CRC), one of the most frequent neoplasias worldwide, has both genetic and environmental causes. As yet, however, gene–environment (G × E) interactions in CRC have been studied mostly for a small number of candidate genes only. Therefore, we investigated the possible interaction, in CRC etiology, between single-nucleotide polymorphisms (SNPs) on the one hand, and overweight, smoking and alcohol consumption on the other, at a genome-wide level. To this end, we adopted a two-tiered approach comprising a case-only screening stage I (314 cases) and a case–control validation stage II (259 cases, 1,002 controls). Interactions with the smallest p value in stage I were verified in stage II using multiple logistic regression analysis adjusted for sex and age. In addition, we specifically studied known CRC-associated SNPs for possible G × E interactions. Upon adjustment for sex and age, and after allowing for multiple testing, however, only a single SNP (rs1944511) was found to be involved in a statistically significant interaction, namely with overweight (multiplicity-corrected p = 0.042 in stage II). Several other G × E interactions were nominally significant but failed correction for multiple testing, including a previously reported interaction between rs9929218 and alcohol consumption that also emerged in our candidate SNP study (nominal p = 0.008). Notably, none of the interactions identified in our genome-wide analysis was with a previously reported CRC-associated SNP. Our study therefore highlights the potential of an “agnostic” genome-wide approach to G × E analysis.     

Characterisation of terminal sire sheep farm systems,based on a range of environmental factors: a case study in the context of genotype by environment interactions using Charollais lambs

The objective of this study was to define different terminal sire flock environments, based on a range of environmental factors, and then investigate the presence of genotype by environment interactions (G×E) between the environments identified. Data from 79 different terminal sire flocks (40 Texel, 21 Charollais and 18 Suffolk), were analysed using principal coordinate and non-hierarchical cluster analyses, the results of which identified three distinct environmental cluster groups. The type of grazing, climatic conditions and the use of vitamins and mineral supplements were found to be the most important factors in the clustering of flocks. The presence of G×E was then investigated using data from the Charollais flocks only. Performance data were collected for 12 181 lambs, between 1990 and 2010, sired by 515 different sires. Fifty six of the sires had offspring in at least two of the three different cluster groups and pedigree information was available for a total of 161 431 animals. Traits studied were the 21-week old weight (21WT), ultrasound muscle depth (UMD) and log transformed backfat depth (LogUFD). Heritabilities estimated for each cluster, for each trait, ranged from 0.32 to 0.45. Genetic correlations estimated between Cluster 1 and Cluster 2 were all found to be significantly lower than unity, indicating the presence of G×E. They were 0.31 (±0.17), 0.68 (±0.14) and 0.18 (±0.21) for 21WT, UMD and LogUFD, respectively. Evidence of sires re-ranking across clusters was also observed. Providing a suitable strategy can be identified, there is potential for the optimisation of future breeding programmes, by taking into account the G×E observed. This would enable farmers to identify and select animals with an increased knowledge as to how they will perform in their specific farm environment thus reducing any unexpected differences in performance.     

Inheritance of growth and solid wood quality traits in a large Norway spruce population tested at two locations in southern Sweden

Unfavorable genetic correlations between growth and wood quality traits are one of the biggest challenges in advanced conifer breeding programs. To examine and deal with such correlation, increment cores were sampled at breast height from 5,618 trees in 524 open-pollinated families in two 21-year-old Norway spruce progeny trials in southern Sweden, and age trends of genetic variation, genetic correlation, and efficiency of selection were investigated. Wood quality traits were measured on 12-mm increment cores using SilviScan. Heritability was moderate (~0.4–0.5) for wood density and modulus of elasticity (MOE) but low (~0.2) for microfibril angle (MFA). Different age trends were observed for wood density, MFA, and MOE, and the lower heritability of MFA relative to wood density and MOE in Norway spruce contrasted with general trends of the three wood quality traits in pine. Genetic correlations among growth, wood density, MFA, and MOE increased to a considerably high value from pith to bark with unfavorable genetic correlations (?0.6 between growth and wood density, ?0.74 between growth and MOE). Age–age genetic correlations reached 0.9 after ring 4 for diameter at breast height (DBH), wood density, MFA, and MOE traits. Early selections at ring 10 for diameter and at ring 6 or 7 for wood quality traits had similar effectiveness as selection conducted at reference ring 15. Selection based on diameter alone produced 19.0 % genetic gain in diameter but resulted in 4.8 % decrease in wood density, 9.4 % decrease in MOE, and 8.0 % increase in MFA. Index selection with a restriction of no change in wood density, MOE, and MFA, respectively, produced relatively lower genetic gains in diameter (16.4, 12.2, and 14.1 %, respectively), indicating such index selection could be implemented to maintain current wood density. Index selection using economic weights is, however, recommended for maximum economic efficiency.     

Association of single nucleotide polymorphisms with form traits in three New Zealand populations of radiata pine in the presence of genotype by environment interactions

Associations of single nucleotide polymorphisms (SNP) with the form traits, branch cluster frequency and stem straightness, were studied in three radiata pine (Pinus radiata D. Don) breeding populations. For branch cluster frequency, high genotype by environment (G×E) interactions were found between two sites of the POP1 trial series (Tarawera and Glenledi) and between two sites of the POP2 trial series (Tarawera and Woodhill). For stem straightness, high G×E interactions were found between two sites (Tarawera and Woodhill) in both the POP2 and POP3 trial series. Thirty-two and 26 SNPs were associated with branch cluster frequency and stem straightness respectively, across a number of sites and trial series in a genetic model assuming heterogeneous additive genetic variances across sites. These SNPs had significant associations with branch cluster frequency or stem straightness either in one site only, across sites within a trial series or across different trial series. Seven SNPs had significant associations with branch cluster frequency and seven SNPs with stem straightness across two of three trial series. One SNP had significant association with stem straightness across all three trial series. Strong G×E interactions resulted in fewer significant SNPs in common across the sites among which there were large effect differences. The percentage of genetic variance explained by SNPs showing significant associations ranged from 0.23 to 8.76 % for branch cluster frequency and from 0.37 to 12.75 % for stem straightness. This study showed that SNP effects for a trait change across environments if G×E interactions exist for that trait.     

Genomic reaction norm models exploiting genotype × environment interaction on sexual precocity indicator traits in Nellore cattle

Brazilian beef cattle are raised predominantly on pasture in a wide range of environments. In this scenario, genotype by environment (G×E) interaction is an important source of phenotypic variation in the reproductive traits. Hence, the evaluation of G×E interactions for heifer’s early pregnancy (HP) and scrotal circumference (SC) traits in Nellore cattle, belonging to three breeding programs, was carried out to determine the animal’s sensitivity to the environmental conditions (EC). The dataset consisted of 85 874 records for HP and 151 553 records for SC, from which 1800 heifers and 3343 young bulls were genotyped with the BovineHD BeadChip. Genotypic information for 826 sires was also used in the analyses. EC levels were based on the contemporary group solutions for yearling body weight. Linear reaction norm models (RNM), using pedigree information (RNM_A) or pedigree and genomic information (RNM_H), were used to infer G×E interactions. Two validation schemes were used to assess the predictive ability, with the following training populations: (a) forward scheme—dataset was split based on year of birth from 2008 for HP and from 2011 for SC; and (b) environment-specific scheme—low EC (−3.0 and −1.5) and high EC (1.5 and 3.0). The inclusion of the H matrix in RNM increased the genetic variance of the intercept and slope by 18.55 and 23.00% on average respectively, and provided genetic parameter estimates that were more accurate than those considering pedigree only. The same trend was observed for heritability estimates, which were 0.28–0.56 for SC and 0.26–0.49 for HP, using RNM_H, and 0.26–0.52 for SC and 0.22–0.45 for HP, using RNM_A. The lowest correlation observed between unfavorable (−3.0) and favorable (3.0) EC levels were 0.30 for HP and −0.12 for SC, indicating the presence of G×E interaction. The G×E interaction effect implied differences in animals’ genetic merit and re-ranking of animals on different environmental conditions. SNP marker–environment interaction was detected for Nellore sexual precocity indicator traits with changes in effect and variance across EC levels. The RNM_H captured G×E interaction effects better than RNM_A and improved the predictive ability by around 14.04% for SC and 21.31% for HP. Using the forward scheme increased the overall predictive ability for SC (20.55%) and HP (11.06%) compared with the environment-specific scheme. The results suggest that the inclusion of genomic information combined with the pedigree to assess the G×E interaction leads to more accurate variance components and genetic parameter estimates.     

A reaction norm model for genomic selection using high-dimensional genomic and environmental data

Key message

New methods that incorporate the main and interaction effects of high-dimensional markers and of high-dimensional environmental covariates gave increased prediction accuracy of grain yield in wheat across and within environments.

Abstract

In most agricultural crops the effects of genes on traits are modulated by environmental conditions, leading to genetic by environmental interaction (G × E). Modern genotyping technologies allow characterizing genomes in great detail and modern information systems can generate large volumes of environmental data. In principle, G × E can be accounted for using interactions between markers and environmental covariates (ECs). However, when genotypic and environmental information is high dimensional, modeling all possible interactions explicitly becomes infeasible. In this article we show how to model interactions between high-dimensional sets of markers and ECs using covariance functions. The model presented here consists of (random) reaction norm where the genetic and environmental gradients are described as linear functions of markers and of ECs, respectively. We assessed the proposed method using data from Arvalis, consisting of 139 wheat lines genotyped with 2,395 SNPs and evaluated for grain yield over 8 years and various locations within northern France. A total of 68 ECs, defined based on five phases of the phenology of the crop, were used in the analysis. Interaction terms accounted for a sizable proportion (16 %) of the within-environment yield variance, and the prediction accuracy of models including interaction terms was substantially higher (17–34 %) than that of models based on main effects only. Breeding for target environmental conditions has become a central priority of most breeding programs. Methods, like the one presented here, that can capitalize upon the wealth of genomic and environmental information available, will become increasingly important.     

Evidence of gene–environment interaction for the IRF6 gene and maternal multivitamin supplementation in controlling the risk of cleft lip with/without cleft palate

Although multiple genes have been identified as genetic risk factors for isolated, non-syndromic cleft lip with/without cleft palate (CL/P), a complex and heterogeneous birth defect, interferon regulatory factor 6 gene (IRF6) is one of the best documented genetic risk factors. In this study, we tested for association between markers in IRF6 and CL/P in 326 Chinese case–parent trios, considering gene–environment interaction for two common maternal exposures, and parent-of-origin effects. CL/P case–parent trios from three sites in mainland China and Taiwan were genotyped for 22 single nucleotide polymorphisms (SNPs) in IRF6. The transmission disequilibrium test was used to test for marginal effects of individual SNPs. We used PBAT to screen the SNPs and haplotypes for gene–environment (G × E) interaction and conditional logistic regression models to quantify effect sizes for SNP–environment interaction. After Bonferroni correction, 14 SNPs showed statistically significant association with CL/P. Evidence of G × E interaction was found for both maternal exposures, multivitamin supplementation and environmental tobacco smoke (ETS). Two SNPs showed evidence of interaction with multivitamin supplementation in conditional logistic regression models (rs2076153 nominal P = 0.019, rs17015218 nominal P = 0.012). In addition, rs1044516 yielded evidence for interaction with maternal ETS (nominal P = 0.041). Haplotype analysis using PBAT also suggested interaction between SNPs in IRF6 and both multivitamin supplementation and ETS. However, no evidence for maternal genotypic effects or significant parent-of-origin effects was seen in these data. These results suggest IRF6 gene may influence risk of CL/P through interaction with multivitamin supplementation and ETS in the Chinese population.     

Genotype by environment interaction for index traits that combine growth and wood density in loblolly pine

 Genotype×environment interactions of individual traits have been assessed in numerous experiments with forest trees. However, since breeding programs rarely aim at the improvement of a single trait, the impact of G×E on index or composite traits must also be assessed. In a study with 12-year-old loblolly pine families in the southeastern U.S., G×E variance was of relatively little importance compared to genetic variance for wood density but was of greater significance for several growth traits. An index that combined stem volume and wood density to improve dry weight but maintain wood density constant (restricted selection index) resulted in substantially greater G×E variance compared to either of the component traits. The interaction variance of an index trait is shown to be a function of the index coefficients and the G×E variances and covariances for its constituent traits. As a result, for some conditions it surpasses the magnitude of G×E variance for each component trait. Received: 5 September 1996 / Accepted: 25 October 1996     

Mapping soybean aphid resistance genes in PI 567598B

The soybean aphid (Aphis glycines Matsumura) has been a major pest of soybean [Glycine max (L.) Merr.] in North America since it was first reported in 2000. Our previous study revealed that the strong aphid resistance of plant introduction (PI) 567598B was controlled by two recessive genes. The objective of this study was to locate these two genes on the soybean genetic linkage map using molecular markers. A mapping population of 282 F_4:5 lines derived from IA2070 × E06902 was evaluated for aphid resistance in a field trial in 2009 and a greenhouse trial in 2010. Two quantitative trait loci (QTLs) were identified using the composite and multiple interval mapping methods, and were mapped on chromosomes 7 (linkage group M) and 16 (linkage group J), respectively. E06902, a parent derived from PI 567598B, conferred resistance at both loci. In the 2010 greenhouse trial, each of the two QTLs explained over 30 % of the phenotypic variation. Significant epistatic interaction was also found between these two QTLs. However, in the 2009 field trial, only the QTL on chromosome 16 was found and it explained 56.1 % of the phenotypic variation. These two QTLs and their interaction were confirmed with another population consisting of 94 F_2:5 lines in the 2008 and 2009 greenhouse trials. For both trials in the alternative population, these two loci explained about 50 and 80.4 % of the total phenotypic variation, respectively. Our study shows that soybean aphid isolate used in the 2009 field trial defeated the QTL found on chromosome 7. Presence of the QTL on chromosome 16 conferred soybean aphid resistance in all trials. The markers linked to the aphid-resistant QTLs in PI 567598B or its derived lines can be used in marker-assisted breeding for aphid resistance.     

Heterogeneous variances and genetics by environment interactions in genetic evaluation of crossbred lambs

Accounting for environmental heteroscedasticity and genetics by environment interaction (G×E) in genetic evaluation is important because animals may not perform predictably across environments. The objectives of this study were to evaluate the presence and consequences of heteroscedasticity and G×E on genetic evaluation. The population considered was crossbred lambs sired by terminal sires and reared under commercial conditions in the UK. Data on 6325 lambs sired by Charollais, Suffolk and Texel rams were obtained. The experiment was conducted between 1999 and 2002 on three farms located in England, Scotland and Wales. There were 2322, 2137 and 1866 lambs in England, Scotland and Wales, respectively. A total of 89 sires were mated to 1984 ewes of two types (Welsh and Scottish Mules). Most rams were used for two breeding seasons with some rotated among farms to create genetic links. Lambs were reared on pasture and had their parentage, birth, 5 week, 10 week, and slaughter weights recorded. Lambs were slaughtered at a constant fatness, at which they were ultrasonically scanned for fat and muscle depth. Heteroscedasticity was evaluated in two ways. First, data were separated into three subsets by farm. Within-farm variance component estimates were then compared with those derived from the complete data (Model 1). Second, the combined data were fitted, but with a heterogeneous (by farm) environmental variance structure (Model 2). To investigate G×E, a model with a random farm by sire (F×S) interaction was used (Model 3). The ratio of the F×S variance to total variance was a measure of the level of G×E in the population. Heterogeneity in environmental variability across farm was identified for all traits (P<0.01). Rank correlations of sire estimated breeding value between farms differed for Model 1 for all traits. However, sires ranked similarly (rank correlation of 0.99) for weight traits with Model 2, but less so for ultrasonic measures. Including the F×S interaction (Model 3) improved model fit for all traits. However, the F×S term explained a small proportion of variation in weights (<2%) although more in ultrasonic traits (at least 10%). In conclusion, heteroscedasticity and G×E were not large for these data, and can be ignored in genetic evaluation of weight but, perhaps, not ultrasonic traits. Still, before incorporating heteroscedasticity and G×E into routine evaluations of even ultrasonic traits, their consequences on selection response in the breeding goal should be evaluated.     

Survival and genetic stability of Picea abies embryogenic cultures after cryopreservation using a pregrowth-dehydration method

A vitrification method enabled efficient cryopreservation of embryogenic tissue (ETs) of Norway spruce (Picea abies L.) at ?196 °C in liquid nitrogen (LN). Correctly formed, normal somatic embryos were generated from ETs that had been thawed after removal from LN. The pregrowth-dehydration method involved preculture of ETs with sucrose (0.25–1.00 M) in the presence or absence of 10 μM abscisic acid (ABA), followed by air-drying for 2 h and rapid freezing in LN. Pretreatment of ETs with both sucrose and ABA promoted ET growth after preculture and thawing more effectively than treatment with sucrose alone. Survival of ETs after thawing from LN using both sucrose and ABA was 54.4 % compared to pretreatment with sucrose alone which was 20 %. Addition of ABA in the preculture medium also improved the ability of ETs to form cotyledonary stage somatic embryos. The somatic embryos, which had normal shoot and root apices and the correct number of cotyledons, were indistinguishable from regenerants obtained from control cultures. Genetic analysis of control and cryopreserved ETs, as well as somatic embryos derived from cryopreserved ETs, indicated that the cryopreservation method had no effect on any of the five microsatellite loci (SpAGC1, SpAGC2, SpAGG3, SpAC1H8, and SpAC1F7) tested. The cryopreservation protocol outlined should enable the long-term storage of valuable clones of Norway spruce in LN, potentially for hundreds of years.     

Post-fallow decomposition of woody roots in the West African savanna

Potassium (K), calcium (Ca), iron (Fe) and aluminium (Al) release from Norway spruce (Picea abies Karsten), Scots pine (Pinus sylvestris L.) and silver birch (Betula pendula Roth.) logging residues (fine roots, foliage and small branches) were studied by means of litterbags over a period of three years in clear-cut area and adjacent uncut Norway spruce dominated mixed boreal forest in eastern Finland (63°51′ N, 28°58′ E, 220 m a.s.l) to determine the amounts and rates of release for these elements and to evaluate whether clear-cutting accelerates mineralization. Almost all K was released from logging residues already during the first year. Calcium was released from foliage and roots but accumulated in branches. Most of the roots Fe and Al content were released during three years while the absolute amounts of Fe and Al in branches and foliage generally increased with decomposition. The results indicate that mineralization is slightly accelerated as a result of clear-cutting since K from foliage and branches of all studied tree species and Ca from pine and spruce roots was released significantly faster at the clear-cut plot than at the forest plot. In three years the initial K pool in the logging residues declined by 90%, Ca by 8%, Fe by 55% and Al by 61% in the clear-cut area. These results indicate that Ca is retained a long time; but Fe, Al and in particular, K are soon released from logging residues. Fine roots of the logged trees release large amounts of Fe and Al and can significantly affect Fe and Al fluxes.     

Effect of partial drying and desiccation on somatic seedling quality in Norway and Serbian spruce

Somatic embryo quality is still a problem for many researchers. To improve the efficiency of germination, special procedures are used, such as partial drying of somatic embryos at high relative humidity or desiccation in the presence of supersaturated solutions of salt. In this work, cotyledonary somatic embryos of Norway spruce (Picea abies) and Serbian spruce (P. omorika) were placed on culture media (ME or BM-5) to germinate. We found that after 4 weeks of incubation on these media, hypocotyl and radicle growth of control (non-dried) somatic embryos of both species was not adequate to yield seedlings able to acclimatize to greenhouse conditions. Therefore, somatic embryos were partly dried at relative humidity of 97 % or desiccated at relative humidity of 79 %, for 2 or 3 weeks, and then placed on the Margara (ME) medium. Partial drying of somatic embryos at the higher relative humidity (97 %) enabled an improvement of radicle growth of germinating somatic embryos in both species. The highest conversion rate (45 %) was obtained for embryos of Norway spruce maintained for 2 weeks at relative humidity of 97 %. This treatment contributed to the improvement of germination and conversion efficiency of somatic embryos of Norway spruce, regardless of the drying period. Improved radicle growth facilitated development of better quality seedlings of this spruce species. In Serbian spruce, we did not obtain seedlings of sufficient quality, due to poor hypocotyl growth. Desiccation at humidity of 79 % for 3 weeks proved to be lethal to somatic embryos of both species.     

Divergent growth of Norway spruce on Babia Góra Mountain in the western Carpathians

Growth divergence – i.e. the expression of divergent growth trends of neighboring trees – has certain implications for dendrochronological research, for instance in the context of climate reconstructions but also in terms of estimating net ecosystem productivity. Thus, understanding the underlying mechanisms is essential to extend our fundamental dendroecological knowledge. In this context, the Picea genus plays an important role since several of its species were reported to exhibit growth divergence. Here, we investigate a well sampled Norway spruce (Picea abies (L.) Karst) data set for growth divergence comprising ring-width and Blue Intensity measurements from seven sites on Babia Góra Mountain, at the border between Poland and Slovakia. By means of Principal Component Gradient Analysis, inter-series correlations, and climate growth relationships, we are able to show that I) Norway spruce on Babia Góra expressed growth divergence since the 1970s, II) the definition of groups increased the strength of population signals and the stability of climate-growth relationships, and III) Blue Intensity appeared as a more robust proxy for environmental conditions. We discuss soil heterogeneity, genetics, and air pollution as possible underlying mechanisms, thereby indicating further research avenues to obtain a better understanding of growth divergence.     

Response of Norway spruce root system to elevated atmospheric CO2 concentration

Root structure parameters, root biomass and allometric relationships between above- and belowground biomass were investigated in young Norway spruce (Picea abies [L.] Karst.) trees cultivated inside the glass domes with ambient (AC, 375 μmol(CO₂) mol^?1) and elevated (EC, A + 375 μmol(CO₂) mol^?1) atmospheric CO₂ concentrations ([CO₂]). After 8 years of fumigation, a mean EC tree in comparison with AC one exhibited about 37 % higher belowground biomass. The growth of primary root structure was unaffected by elevated [CO₂]; however, the biomass of secondary roots growing on the primary root structure and the biomass of secondary roots growing in the zone between the soil surface and the first primary root ramification were significantly higher in EC comparing with AC treatment about 58 and 70 %, respectively. The finest root’s (diameter up to 1 mm) biomass as well as length and surface area of both primary and secondary root structures showed the highest difference between the treatments; advancing EC to AC by 43 % on average. Therefore, Norway spruce trees cultivated under well-watered and rather nitrogen-poor soil conditions responded to the air elevated [CO₂] environment by the enhancement of the secondary root structure increment, by enlargement of root length and root absorbing area, and also by alternation of root to aboveground organ biomass proportion. Higher root to leaf and root to stem basal area ratios could be beneficial for Norway spruce trees to survive periods with limited soil water availability.