Quantitative Genetics of Traits Indicative of Biomass Production and Heterosis in 34 Full-sib F1 Salix eriocephala Families

This project examined the heritability of traits that affect biomass production of Salix eriocephala, a shrub willow native to North America and an essential species in the breeding of bioenergy crop varieties. Using an incomplete factorial design, seven females and eight males were crossed to produce 34 full-sib F₁ families. Five to 12 entries per family were planted in four-plant plots in a randomized complete block design on two sites. Melampsora rust incidence was scored in the fall of the first growing season (prior to coppice). Height of the tallest stem, cross-sectional stem area per stool, and number of stems per stool were recorded in the winter after the first growing season post-coppice. Plants were harvested 3 years post-coppice and biomass yield was determined. A large percentage of the total variance was additive for all of the traits studied and heritability estimates were low to moderate, suggesting that phenotypic expression of these traits is predictable and can be improved through breeding. Based on yield 3 years after coppice, 29 of the 34 families displayed midparent heterosis, ranging from 1–115%, for the composite trait—biomass yield, strongly indicating that offspring often perform better than their parents in this population. This study will assist in selecting parents which may produce superior progeny in the breeding program.     

Influence of Plant Community Composition on Biomass Production in Planted Grasslands

United States energy policy mandates increased use of renewable fuels. Restoring grasslands could contribute to a portion of this requirement through biomass harvest for bioenergy use. We investigated which plant community characteristics are associated with differences in biomass yield from a range of realistic native prairie plantings (n = 11; i.e., conservation planting, restoration, and wildlife cover). Our primary goal was to understand whether patterns in plant community composition and the Floristic Quality Index (FQI) were related to productivity as evidenced by dormant season biomass yield. FQI is an objective measure of how closely a plant community represents that of a pre-European settlement community. Our research was conducted in planted fields of native tallgrass prairie species, and provided a gradient in floristic quality index, species richness, species diversity, and species evenness in south-central Wisconsin during 2008 and 2009. We used a network of 15 randomly located 1 m² plots within each field to characterize the plant community and estimate biomass yield by clipping the plots at the end of each growing season. While plant community composition and diversity varied significantly by planting type, biomass yield did not vary significantly among planting types (ANOVA; P >0.05). Biomass yield was positively correlated with plant community evenness, richness, C4 grass cover, and floristic quality index, but negatively correlated with plant species diversity in our multi-season multiple linear mixed effects models. Concordantly, plots with biomass yield in the lowest quartile (biomass yield < 3500 kh/ha) had 8% lower plant community evenness and 9% lower FQI scores than those in the upper quartile (biomass yield > 5800 kh/ha). Our results suggest that promoting the establishment of fields with high species evenness and floristic quality may increase biomass yield, while simultaneously supporting biodiversity.     

杉木育种亲本生长和结实性状早期测评与选择

为推进杉木(Cunninghamia lanceolata)育种进程,对广东乐昌市龙山林场和韶关市曲江区国有小坑林场杉木第3代育种园亲本群体的早期(3 a生)生长和结实性状进行分析.结果表明,同一育种园亲本无性系在生长性状(树高、胸径、单株材积、冠幅)和结实能力上存在显著差异,生长性状的差异甚至达到极显著水平(P<0....     

Breeding of Brassica rapa for Biogas Production: Heterosis and Combining Ability of Biomass Yield

The use of plant biomass as substrate for biogas production has recently become of major interest in Europe. Winter Brassica rapa produces high early biomass and could be grown as a pre-crop harvested early in the year followed by a second crop such as maize. The objectives of this study were to estimate heterosis and combining ability of 15 European winter B. rapa cultivars for biomass yield at end of flowering. A half-diallel without reciprocals was conducted among cultivars to produce 105 crosses. These crosses and their parents were evaluated in two years at two locations in Northern Germany. Data collected were days to flowering (DTF), fresh biomass yield (FBY), dry matter content (DMC) and dry biomass yield (DBY). The mean DBY was 5.3 t/ha for the parental cultivars and 5.6 t/ha for their crosses. The crosses surpassed on average their parents by 7.6% for FBY and 5.9% for DBY whereas DMC was 1.4% higher in the parents. Maximum mid parent heterosis was 21.0% for FBY and 30.4% for DBY. Analysis of variance showed that genetic variance was mainly due to specific combining ability (SCA). The correlation between parental performance and general combining ability (GCA) was 0.42** for FBY and 0.53** for DBY. In conclusion, the amount of heterosis in crosses between European winter B. rapa cultivars is not very high on average, but can be up to 30% in the best crosses. Selection of parental combinations with high specific combining ability to produce synthetic cultivars can rapidly improve biomass yield.     

Herbaceous Layer Net Primary Production of Oak-Hornbeam Forest: Comparing Six Methods of Assessment Based on the Seasonal Dynamics of Biomass Increments

Ecosystems - Proper estimation of the herb layer annual net primary production (ANPP) can help to appreciate the role of this layer in carbon assimilation and nutrient cycling. Simple methods of...     

Biodiversity Effects on Biomass Production and Invasion Resistance in Annual versus Perennial Plant Communities

In a field experiment we constructed two different communities using both annual and perennial plant species, in which species diversity is experimentally manipulated. We want to test the relationships between species diversity and biomass production and invasibility and the possible mechanisms driving this relationships, especially, whether the identical mechanisms drive both diversity-production and diversity-invasibility relationships. Our results indicated that a positive diversity-production relationship and negative diversity-invasibility and production-invasibility relationships emerged in two different communities. However, the mechanisms underlying are different in two communities. In the annual communities, the observed positive diversity-production and negative diversity-invasibility relationships are linked by the sampling effect. In the perennial communities, however, the mechanism responsible for these observed relationships are the complementarity effect. Our results also found that, in addition to species diversity, species composition also play an important role in governing the observed relationship. The results of our study suggest that because species in different communities may differ in their life history, biological and physiological traits, mechanisms responsible for the observed relationship between diversity and biomass production and invasibiltiy are likely different.     

Prediction of Genetic Values of Quantitative Traits in Plant Breeding Using Pedigree and Molecular Markers

The availability of dense molecular markers has made possible the use of genomic selection (GS) for plant breeding. However, the evaluation of models for GS in real plant populations is very limited. This article evaluates the performance of parametric and semiparametric models for GS using wheat (Triticum aestivum L.) and maize (Zea mays) data in which different traits were measured in several environmental conditions. The findings, based on extensive cross-validations, indicate that models including marker information had higher predictive ability than pedigree-based models. In the wheat data set, and relative to a pedigree model, gains in predictive ability due to inclusion of markers ranged from 7.7 to 35.7%. Correlation between observed and predictive values in the maize data set achieved values up to 0.79. Estimates of marker effects were different across environmental conditions, indicating that genotype × environment interaction is an important component of genetic variability. These results indicate that GS in plant breeding can be an effective strategy for selecting among lines whose phenotypes have yet to be observed.PEDIGREE-BASED prediction of genetic values based on the additive infinitesimal model (Fisher 1918) has played a central role in genetic improvement of complex traits in plants and animals. Animal breeders have used this model for predicting breeding values either in a mixed model (best linear unbiased prediction, BLUP) (Henderson 1984) or in a Bayesian framework (Gianola and Fernando 1986). More recently, plant breeders have incorporated pedigree information into linear mixed models for predicting breeding values (Crossa et al. 2006, 2007; Oakey et al. 2006; Burgueño et al. 2007; Piepho et al. 2007).The availability of thousands of genome-wide molecular markers has made possible the use of genomic selection (GS) for prediction of genetic values (Meuwissen et al. 2001) in plants (e.g., Bernardo and Yu 2007; Piepho 2009; Jannink et al. 2010) and animals (Gonzalez-Recio et al. 2008; VanRaden et al. 2008; Hayes et al. 2009; de los Campos et al. 2009a). Implementing GS poses several statistical and computational challenges, such as how models can cope with the curse of dimensionality, colinearity between markers, or the complexity of quantitative traits. Parametric (e.g., Meuwissen et al. 2001) and semiparametric (e.g., Gianola et al. 2006; Gianola and van Kaam 2008) methods address these problems differently.In standard genetic models, phenotypic outcomes, , are viewed as the sum of a genetic value, , and a model residual, ; that is, . In parametric models for GS, is described as a regression on marker covariates (j = 1,  …  , p molecular markers) of the form , such that(or , in matrix notation), where is the regression of on the jth marker covariate .Estimation of via multiple regression by ordinary least squares (OLS) is not feasible when p > n. A commonly used alternative is to estimate marker effects jointly using penalized methods such as ridge regression (Hoerl and Kennard 1970) or the Least Absolute Shrinkage and Selection Operator (LASSO) (Tibshirani 1996) or their Bayesian counterpart. This approach yields greater accuracy of estimated genetic values and can be coupled with geostatistical techniques commonly used in plant breeding to model multienvironments trials (Piepho 2009).In ridge regression (or its Bayesian counterpart) the extent of shrinkage is homogeneous across markers, which may not be appropriate if some markers are located in regions that are not associated with genetic variance, while markers in other regions may be linked to QTL (Goddard and Hayes 2007). To overcome this limitation, many authors have proposed methods that use marker-specific shrinkage. In a Bayesian setting, this can be implemented using priors of marker effects that are mixtures of scaled-normal densities. Examples of this are methods Bayes A and Bayes B of Meuwissen et al. (2001) and the Bayesian LASSO of Park and Casella (2008).An alternative to parametric regressions is to use semiparametric methods such as reproducing kernel Hilbert spaces (RKHS) regression (Gianola and van Kaam 2008). The Bayesian RKHS regression regards genetic values as random variables coming from a Gaussian process centered at zero and with a (co)variance structure that is proportional to a kernel matrix K (de los Campos et al. 2009b); that is, , where , are vectors of marker genotypes for the ith and jth individuals, respectively, and is a positive definite function evaluated in marker genotypes. In a finite-dimensional setting this amounts to modeling the vector of genetic values, , as multivariate normal; that is, where is a variance parameter. One of the most attractive features of RKHS regression is that the methodology can be used with almost any information set (e.g., covariates, strings, images, graphs). A second advantage is that with RKHS the model is represented in terms of n unknowns, which gives RKHS a great computational advantage relative to some parametric methods, especially when p ≫ n.This study presents an evaluation of several methods for GS, using two extensive data sets. One contains phenotypic records of a series of wheat trials and recently generated genomic data. The other data set pertains to international maize trials in which different traits were measured in maize lines evaluated under severe drought and well-watered conditions.     

Nonparametric Method for Genomics-Based Prediction of Performance of Quantitative Traits Involving Epistasis in Plant Breeding

Genomic selection (GS) procedures have proven useful in estimating breeding value and predicting phenotype with genome-wide molecular marker information. However, issues of high dimensionality, multicollinearity, and the inability to deal effectively with epistasis can jeopardize accuracy and predictive ability. We, therefore, propose a new nonparametric method, pRKHS, which combines the features of supervised principal component analysis (SPCA) and reproducing kernel Hilbert spaces (RKHS) regression, with versions for traits with no/low epistasis, pRKHS-NE, to high epistasis, pRKHS-E. Instead of assigning a specific relationship to represent the underlying epistasis, the method maps genotype to phenotype in a nonparametric way, thus requiring fewer genetic assumptions. SPCA decreases the number of markers needed for prediction by filtering out low-signal markers with the optimal marker set determined by cross-validation. Principal components are computed from reduced marker matrix (called supervised principal components, SPC) and included in the smoothing spline ANOVA model as independent variables to fit the data. The new method was evaluated in comparison with current popular methods for practicing GS, specifically RR-BLUP, BayesA, BayesB, as well as a newer method by Crossa et al., RKHS-M, using both simulated and real data. Results demonstrate that pRKHS generally delivers greater predictive ability, particularly when epistasis impacts trait expression. Beyond prediction, the new method also facilitates inferences about the extent to which epistasis influences trait expression.     

Effects of Plant Biomass, Plant Diversity, and Water Content on Bacterial Communities in Soil Lysimeters: Implications for the Determinants of Bacterial Diversity

Soils may comprise tens of thousands to millions of bacterial species. It is still unclear whether this high level of diversity is governed by functional redundancy or by a multitude of ecological niches. In order to address this question, we analyzed the reproducibility of bacterial community composition after different experimental manipulations. Soil lysimeters were planted with four different types of plant communities, and the water content was adjusted. Group-specific phylogenetic fingerprinting by PCR-denaturing gradient gel electrophoresis revealed clear differences in the composition of Alphaproteobacteria, Betaproteobacteria, Bacteroidetes, Chloroflexi, Planctomycetes, and Verrucomicrobia populations in soils without plants compared to that of populations in planted soils, whereas no influence of plant species composition on bacterial diversity could be discerned. These results indicate that the presence of higher plant species affects the species composition of bacterial groups in a reproducible manner and even outside of the rhizosphere. In contrast, the environmental factors tested did not affect the composition of Acidobacteria, Actinobacteria, Archaea, and Firmicutes populations. One-third (52 out of 160) of the sequence types were found to be specifically and reproducibly associated with the absence or presence of plants. Unexpectedly, this was also true for numerous minor constituents of the soil bacterial assemblage. Subsequently, one of the low-abundance phylotypes (beta10) was selected for studying the interdependence under particular experimental conditions and the underlying causes in more detail. This so-far-uncultured phylotype of the Betaproteobacteria species represented up to 0.18% of all bacterial cells in planted lysimeters compared to 0.017% in unplanted systems. A cultured representative of this phylotype exhibited high physiological flexibility and was capable of utilizing major constituents of root exudates. Our results suggest that the bacterial species composition in soil is determined to a significant extent by abiotic and biotic factors, rather than by mere chance, thereby reflecting a multitude of distinct ecological niches.     

Assessment of Sugarcane Billet Harvester on Recovery of Sweet Sorghum Biomass for Ethanol Production

Sweet sorghum (Sorghum bicolor L. Moench) is a promising bioenergy crop for the production of ethanol and bio-based products. Sugarcane billet harvesters can be used to harvest sweet sorghum. Multiple extractor fan speed settings of these harvesters allow for separating the extraneous matter in the feedstock, which has been associated with increased milling throughput and better juice quality at the processing facility. This removal is not completely selective, and some stalk material is also lost. These losses can be higher for sweet sorghum than sugarcane due its lower weight. This paper presents an assessment of how the speed of the primary extractor fan of a sugarcane billet combine used for harvesting sweet sorghum affects the biomass yield, biomass losses, and quality at delivery for the production of ethanol from extracted juice and fiber. Three primary extractor fan speeds (0, 800, and 1100 rpm) were evaluated. Higher fan speeds decreased fresh biomass yields by up to 28.3 Mg ha^?1. Juice quality was not significantly different among treatments. Ethanol yield calculated from sweet sorghum harvested at 0 rpm was 6075 L ha^?1. This value decreased by about half for material harvested at 1100 rpm due to the differences in biomass yield.     

Pollen Production in the Androdioecious Datisca glomerata (Datiscaceae): Implications for Breeding System Equilibrium

Abstract Androdioecy (the presence of males and hermaphrodites in a breeding population) is a rare reproductive system in plants, with Datisca glomerata (Datiscaceae) representing the only well-documented example. Recent reports of high outcrossing rates, inbreeding depression, and high male pollen production satisfy theoretical predictions for the continued maintenance of androdioecy in populations of this species. However, in prior studies pollen production was measured indirectly in terms of numbers of anthers per flower—based on the assumption that male and hermaphroditic plant have equal numbers of flowers and that anthers from the two sexual morphs produce equivalent amounts of pollen. Herein, we demonstrate that male and hermaphrodite plants do not differ significantly in terms of flower number, but that pollen production in anthers from hermaphroditic plants is 12.6% higher than in anthers from male plants, thus refining the estimate of relative pollen fecundity of male versus hermaphrodite plants. The differential lowers the frequency of males predicted by theory, but is still consistent with the maintenance of androdioecy in this species.     

On Polydispersity of Plant Biomass Recalcitrance and Its Effects on Pretreatment Optimization for Sugar Production

This paper discusses a property associated with plant biomass recalcitrance to enzyme and microbial deconstructions in sugar production from cellulose and hemicelluloses. The hemicelluloses are more readily hydrolyzed to sugars than is cellulose. As a result, optimization to maximize individual glucose and hemicellulose sugar recovery is not possible. This property is an inherent feature of plant biomass and is named polydispersity of plant biomass recalcitrance (PPBR) in this study. A set of pretreatment experiments using eucalyptus and sulfite pretreatment to overcome recalcitrance of lignocelluloses was conducted. The results were used to predict the conditions for individually maximizing enzymatic glucose and xylose yields. The predicted maximal yields were used to quantitatively illustrate the PPBR concept. The effect of PPBR on pretreatment optimization and strategies for maximal sugar recovery using two-stage pretreatment are discussed.     

香港桃金娘灌木群落植物生物量和净第一性生产量

本文研究香港桃金娘灌木林植物生物量和净第一性生产量。结果表明：（１）桃金娘茎的直径与高度与各组分的生物量有明显的相关关系。（２）桃金娘叶子占地上部活植物生物量的２０．２％,花和果如果以它的峰值计算,其占地上部活植物生物量的９．６％,茎和枝占７０．４％。（３）地上部和地下部活植物生物量分别为１５５３ｇｍ－２和１４０８ｇｍ－２,其中桃金娘分别占８５％和８２％。（４）桃金娘叶子生物量在研究期间的波动较大,但没有以年为周期的季节变化。花和果的变化则较有规律,花蕾通常于３或４月开始形成,到７月底达到峰值,然后开始下降。（５）桃金娘的净生产量为８２０ｇｍ－２ａ－１,其中,花和果占１５．２％,茎和枝占１８．８％,根和叶分别占２１．３％和４３．７％。灌木林的净第一性生产量为１０１０ｇｍ－２ａ－１。（６）由于未考虑草食和根系的枯死损失,本研究所得的净第一性生产量（尤其是根的生产量）可能偏低。     

Effects of Elevated Carbon Dioxide on Plant Biomass Production and Competition in a Simulated Neutral Grassland Community

Using open-top chambers, four prominent species (Lolium perenne,Cynosurus cristatus, Holcus lanatusandAgrostis capillaris) ofIrish neutral grasslands were grown at ambient and elevated(700 µmol mol^-1) atmospheric CO₂for a period of 8 months.The effects of interspecific competition on plant responsesto CO₂enrichment were investigated by growing the species ina four-species mixture. The results indicate that the speciesdiffer in their ability to respond to elevated CO₂. CO₂-enrichmenthad the largest effect on the biomass production ofH. lanatus,but substantial stimulations in biomass production were alsofound for the other three species. The CO₂-stimulation of biomassproduction forH. lanatuswas accompanied by increased tillering.In addition, reductions in specific leaf area were found forall species. Exposure to elevated CO₂increased the communitybiomass of the four-species mixture. This increase can be mainlyattributed to a significant increase in the biomass ofH. lanatusatelevated CO₂. No statistically-significant changes in speciescomposition of community biomass were found. However,H. lanatusdidincrease its share of community biomass at each of the harvests,with the other three species, mainlyL. perenne, suffering lossesin their shares at elevated CO₂. The results show that: (1)the species varied in their response to elevated CO₂; and (2)species composition in natural plant communities is likely tochange at elevated CO₂, but these changes may occur rather slowly.Much longer periods of exposure to elevated atmospheric CO₂maybe required to permit detection of significant changes in speciescomposition.Copyright 1998 Annals of Botany Company Carbon dioxide (CO₂) enrichment, competition, Lolium perenne,Cynosurus cristatus, Holcus lanatus, Agrostis capillaris, biomass, specific leaf area, tillering.     

Heterogeneity of Soils and Vegetation in an Eastern Amazonian Rain Forest: Implications for Scaling Up Biomass and Production

Transferring fine-scale ecological knowledge into an understanding of earth system processes presents a considerable challenge to ecologists. Our objective here was to identify and quantify heterogeneity of, and relationships among, vegetation and soil properties in terra firme rain forest ecosystems in eastern Amazonia and assess implications for generating regional predictions of carbon (C) exchange. Some of these properties showed considerable variation among sites; soil textures varied from 11% to 92% clay. But we did not find any significant correlations between soil characteristics (percentage clay, nitrogen [N], C, organic matter) and vegetation characteristics (leaf area index [LAI], foliar N concentration, basal area, biomass, stem density). We found some evidence for increased drought stress on the sandier sites: There was a significant correlation between soil texture and wood δ¹³C (but not with foliar δ¹³C); volumetric soil moisture was lower at sandier sites; and some canopy foliage had large, negative dawn water potentials (ψ_ld), indicating limited water availability in the rooting zone. However, at every site at least one foliage sample indicated full or nearly full rehydration, suggesting significant interspecific variability in drought vulnerability. There were significant differences in foliar δ¹⁵N among sites, but not in foliar % N, suggesting differences in N cycling but not in plant access to N. We used an ecophysiological model to examine the sensitivity of gross primary production (GPP) to observed inter- and intrasite variation in key driving variables—LAI, foliar N, and ψ_ld. The greatest sensitivity was to foliar N; standard errors on foliar N data translated into uncertainty in GPP predictions up to ±10% on sunny days and ±5% on cloudy days. Local variability in LAI had a minor influence on uncertainty, especially on sunny days. The largest observed reductions in ψ_ld reduced GPP by 4%–6%. If uncertainty in foliar N estimates is propagated into the model, then GPP estimates are not significantly different among sites. Our results suggest that water restrictions in the sandier sites are not enough to reduce production significantly and that texture is not the key control on plant access to N. Received 28 June 2001; accepted 13 March 2002.     

Variability of Life History Traits in Iris pumila Juvenile Plants: Ramet Dynamics

In this study I analyzed dynamic of ramet number on 18 half-sib and 63 full-sib families of rhizomatous perennial herb Iris pumila originating from two Deliblato Sand populations and grown in two nutrient levels (full strength and 1/10 of full strength Hoagland solution). Contrary to most studies dealing with response to different nutrient availability, I failed to detect significant mean nutrient level effect on dynamic of module emergence. Such absence of consistent response to tenfold variation in solution strength indicate that I. pumila have low saturation rates of nutrient uptake and presumably experienced both utilized nutrition levels as rich ones. Genetic variability for plastic response was lacking either. On the other hand, presence of between-population differentiation for the trait itself indicates that I. pumila harbors considerable amounts of within-species genetic variability for ramet dynamics.     

Effects of Native and Non-Native Grassland Plant Communities on Breeding Passerine Birds: Implications for Restoration of Northwest Bunchgrass Prairie

One common problem encountered when restoring grasslands is the prominence of non-native plant species. It is unclear what effect non-native plants have on habitat quality of grassland passerines, which are among the most imperiled groups of birds. In 2004 and 2005, we compared patterns of avian reproduction and the mechanisms that might influence those patterns across a gradient of 13 grasslands in the Zumwalt Prairie in northeastern Oregon that vary in the degree of non-native plant cover (0.9–53.4%). We monitored the fate of 201 nests of all the breeding species in these pastures and found no association of percent non-native cover with nest densities, clutch size, productivity, nest survival, and nestling size. Regardless of the degree of non-native cover, birds primarily fed on Coleoptera, Orthoptera, and Araneae. But as percent non-native cover in the pastures increased, Orthoptera made up a greater proportion of diet and Coleoptera made up a smaller proportion. These diet switches were not the result of changes in terrestrial invertebrate abundance but may be related to decreases in percent bare ground associated with increasing cover of non-native vegetation. Measures of nest crypticity were not associated with cover of non-native vegetation, suggesting that predation risk may not increase with increased cover of non-native vegetation. Thus, the study results show that increased non-native cover is not associated with reduced food supplies or increased predation risk for nesting birds, supporting the growing body of evidence that grasslands with a mix of native and non-native vegetation can provide suitable habitat for native grassland breeding birds.     

The Rengen Grassland Experiment: Effect of Soil Chemical Properties on Biomass Production, Plant Species Composition and Species Richness

The Rengen Grassland Experiment (RGE), set up on a Nardus grassland in 1941, consists of a control and five fertilizer treatments (Ca, CaN, CaNP, CaNP-KCl and CaNP-K₂SO₄). In 2005, soil chemical properties were analyzed to investigate the effect of soil variables on biomass production, plant species composition and species richness of vascular plants. Further, the effect of sampling scale (from 0.02 to 5.76 m²) on species richness was investigated. Soil properties (plant-available contents of K, P, C:N ratio, and pH) and biomass production were found to be strictly dependent on the fertilizers applied. Diversification of soil P content between treatments with and without P application is still in progress. Biomass production was most positively affected by P and K soil contents under N application. Furthermore, pH had a small positive effect on biomass production, and C:N ratio a moderately negative one. Two types of nutrient limitation were recognized: (1) limitation of total biomass production and (2) limitation of individual plant species. Long-term addition of a limiting nutrient affected the grassland ecosystem in three ways: (1) causing a change in plant species composition without significant increase in total biomass production, (2) causing no change in species composition but with significant increase in total biomass production, and (3) causing substantial change in plant species composition accompanied by significant increase in total biomass production. The explanatory power of all measured soil properties on plant species composition was almost the same as the power of the treatment effect (61.7% versus 62% of explained variability in RDA). The most powerful predictors of plant species composition were soil P, K and Mg contents, pH, and biomass production. The soil P content and biomass production were the only variables leading to a significant negative effect on species richness. An almost parallel increase in species richness with increasing sampling area was detected in all treatments. Constant differences among treatments were independent of sampling area.     

Life Cycle Assessment of Electric and Fuel Cell Vehicle Transport Based on Forest Biomass

Use of biomass‐based electricity and hydrogen in alternative transport could provide environmentally sustainable transport options with possible improvements in greenhouse gas balance. We perform a life cycle assessment of electric vehicle (EV) and fuel cell vehicle (FCV) powered by bioelectricity and biohydrogen, respectively, derived from Norwegian boreal forest biomass, considering the nonclimate neutrality of biological carbon dioxide (CO₂) emissions and alteration in surface albedo resulting from biomass harvesting—both with and without CO₂ capture and storage (CCS)—while benchmarking these options against EVs powered by the average European electricity mix. Results show that with due consideration of the countering effects from global warming potential (GWP) factors for biogenic CO₂ emissions and change in radiative forcing of the surface for the studied region, bioenergy‐based EVs and FCVs provide reductions of approximately 30%, as compared to the reference EV powered by the average European electricity mix. With CCS coupled to bioenergy production, the biomass‐based vehicle transport results in a net global warming impact reduction of approximately 110% to 120% (giving negative GWP and creating a climate‐cooling benefit from biomass use). Other environmental impacts vary from ?60% to +60%, with freshwater eutrophication showing maximum reductions (40% for the EV case and 60% for the FCV case) and photochemical oxidation showing a maximum increase (60% in the FCV value chain).