71 resultados para functional group diversity

em BORIS: Bern Open Repository and Information System - Berna - Suiça


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Fungal plant pathogens are common in natural communities where they affect plant physiology, plant survival, and biomass production. Conversely, pathogen transmission and infection may be regulated by plant community characteristics such as plant species diversity and functional composition that favor pathogen diversity through increases in host diversity while simultaneously reducing pathogen infection via increased variability in host density and spatial heterogeneity. Therefore, a comprehensive understanding of multi-host multi-pathogen interactions is of high significance in the context of biodiversity-ecosystem functioning. We investigated the relationship between plant diversity and aboveground obligate parasitic fungal pathogen (''pathogens'' hereafter) diversity and infection in grasslands of a long-term, large-scale, biodiversity experiment with varying plant species (1-60 species) and plant functional group diversity (1-4 groups). To estimate pathogen infection of the plant communities, we visually assessed pathogen-group presence (i.e., rusts, powdery mildews, downy mildews, smuts, and leaf-spot diseases) and overall infection levels (combining incidence and severity of each pathogen group) in 82 experimental plots on all aboveground organs of all plant species per plot during four surveys in 2006. Pathogen diversity, assessed as the cumulative number of pathogen groups on all plant species per plot, increased log-linearly with plant species diversity. However, pathogen incidence and severity, and hence overall infection, decreased with increasing plant species diversity. In addition, co-infection of plant individuals by two or more pathogen groups was less likely with increasing plant community diversity. We conclude that plant community diversity promotes pathogen-community diversity while at the same time reducing pathogen infection levels of plant individuals.

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The diversity–stability hypothesis states that current losses of biodiversity can impair the ability of an ecosystem to dampen the effect of environmental perturbations on its functioning. Using data from a long-term and comprehensive biodiversity experiment, we quantified the temporal stability of 42 variables characterizing twelve ecological functions in managed grassland plots varying in plant species richness. We demonstrate that diversity increases stability i) across trophic levels (producer, consumer), ii) at both the system (community, ecosystem) and the component levels (population, functional group, phylogenetic clade), and iii) primarily for aboveground rather than belowground processes. Temporal synchronization across studied variables was mostly unaffected with increasing species richness. This study provides the strongest empirical support so far that diversity promotes stability across different ecological functions and levels of ecosystem organization in grasslands

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In the literature, contrasting effects of plant species richness on the soil water balance are reported. Our objective was to assess the effects of plant species and functional richness and functional identity on soil water contents and water fluxes in the experimental grassland of the Jena Experiment. The Jena Experiment comprises 86 plots on which plant species richness (0, 1, 2, 4, 8, 16, and 60) and functional group composition (zero to four functional groups: legumes, grasses, tall herbs, and small herbs) were manipulated in a factorial design. We recorded meteorological data and soil water contents of the 0·0–0·3 and 0·3–0·7 m soil layers and calculated actual evapotranspiration (ETa), downward flux (DF), and capillary rise with a soil water balance model for the period 2003–2007. Missing water contents were estimated with a Bayesian hierarchical model. Species richness decreased water contents in subsoil during wet soil conditions. Presence of tall herbs increased soil water contents in topsoil during dry conditions and decreased soil water contents in subsoil during wet conditions. Presence of grasses generally decreased water contents in topsoil, particularly during dry phases; increased ETa and decreased DF from topsoil; and decreased ETa from subsoil. Presence of legumes, in contrast, decreased ETa and increased DF from topsoil and increased ETa from subsoil. Species richness probably resulted in complementary water use. Specific functional groups likely affected the water balance via specific root traits (e.g. shallow dense roots of grasses and deep taproots of tall herbs) or specific shading intensity caused by functional group effects on vegetation cover. Copyright © 2013 John Wiley & Sons, Ltd.

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Plant diversity drives changes in the soil microbial community which may result in alterations in ecosystem functions. However, the governing factors between the composition of soil microbial communities and plant diversity are not well understood. We investigated the impact of plant diversity (plant species richness and functional group richness) and plant functional group identity on soil microbial biomass and soil microbial community structure in experimental grassland ecosystems. Total microbial biomass and community structure were determined by phospholipid fatty acid (PLFA) analysis. The diversity gradient covered 1, 2, 4, 8, 16 and 60 plant species and 1, 2, 3 and 4 plant functional groups (grasses, legumes, small herbs and tall herbs). In May 2007, soil samples were taken from experimental plots and from nearby fields and meadows. Beside soil texture, plant species richness was the main driver of soil microbial biomass. Structural equation modeling revealed that the positive plant diversity effect was mainly mediated by higher leaf area index resulting in higher soil moisture in the top soil layer. The fungal-to-bacterial biomass ratio was positively affected by plant functional group richness and negatively by the presence of legumes. Bacteria were more closely related to abiotic differences caused by plant diversity, while fungi were more affected by plant-derived organic matter inputs. We found diverse plant communities promoted faster transition of soil microbial communities typical for arable land towards grassland communities. Although some mechanisms underlying the plant diversity effect on soil microorganisms could be identified, future studies have to determine plant traits shaping soil microbial community structure. We suspect differences in root traits among different plant communities, such as root turnover rates and chemical composition of root exudates, to structure soil microbial communities.

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In the course of the biodiversity-ecosystem functioning debate, the issue of multifunctionality of species communities has recently become a major focus. Elemental stoichiometry is related to a variety of processes reflecting multiple plant responses to the biotic and abiotic environment. It can thus be expected that the diversity of a plant assemblage alters community level plant tissue chemistry. We explored elemental stoichiometry in aboveground plant tissue (ratios of carbon, nitrogen, phosphorus, and potassium) and its relationship to plant diversity in a 5-year study in a large grassland biodiversity experiment (Jena Experiment). Species richness and functional group richness affected community stoichiometry, especially by increasing C:P and N:P ratios. The primacy of either species or functional group richness effects depended on the sequence of testing these terms, indicating that both aspects of richness were congruent and complementary to expected strong effects of legume presence and grass presence on plant chemical composition. Legumes and grasses had antagonistic effects on C:N (−27.7% in the presence of legumes, +32.7% in the presence of grasses). In addition to diversity effects on mean ratios, higher species richness consistently decreased the variance of chemical composition for all elemental ratios. The diversity effects on plant stoichiometry has several non-exclusive explanations: The reduction in variance can reflect a statistical averaging effect of species with different chemical composition or a optimization of nutrient uptake at high diversity, leading to converging ratios at high diversity. The shifts in mean ratios potentially reflect higher allocation to stem tissue as plants grew taller at higher richness. By showing a first link between plant diversity and stoichiometry in a multiyear experiment, our results indicate that losing plant species from grassland ecosystems will lead to less reliable chemical composition of forage for herbivorous consumers and belowground litter input.

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Ecosystems are faced with high rates of species loss which has consequences for their functions and services. To assess the effects of plant species diversity on the nitrogen (N) cycle, we developed a model for monthly mean nitrate (NO3-N) concentrations in soil solution in 0-30 cm mineral soil depth using plant species and functional group richness and functional composition as drivers and assessing the effects of conversion of arable land to grassland, spatially heterogeneous soil properties, and climate. We used monthly mean NO3-N concentrations from 62 plots of a grassland plant diversity experiment from 2003 to 2006. Plant species richness (1-60) and functional group composition (1-4 functional groups: legumes, grasses, non-leguminous tall herbs, non-leguminous small herbs) were manipulated in a factorial design. Plant community composition, time since conversion from arable land to grassland, soil texture, and climate data (precipitation, soil moisture, air and soil temperature) were used to develop one general Bayesian multiple regression model for the 62 plots to allow an in-depth evaluation using the experimental design. The model simulated NO3-N concentrations with an overall Bayesian coefficient of determination of 0.48. The temporal course of NO3-N concentrations was simulated differently well for the individual plots with a maximum plot-specific Nash-Sutcliffe Efficiency of 0.57. The model shows that NO3-N concentrations decrease with species richness, but this relation reverses if more than approx. 25 % of legume species are included in the mixture. Presence of legumes increases and presence of grasses decreases NO3-N concentrations compared to mixtures containing only small and tall herbs. Altogether, our model shows that there is a strong influence of plant community composition on NO3-N concentrations.

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Ecosystem functioning in grasslands is regulated by a range of biotic and abiotic factors, and the role of microbial communities in regulating ecosystem function has been the subject of much recent scrutiny. However, there are still knowledge gaps regarding the impacts of rainfall and vegetation change upon microbial communities and the implications of these changes for ecosystem functioning. We investigated this issue using data from an experimental mesotrophic grassland study in south-east England, which had been subjected to four years of rainfall and plant functional composition manipulations. Soil respiration, nitrogen and phosphorus stocks were measured, and the abundance and community structure of soil microbes were characterised using quantitative PCR and multiplex-TRFLP analysis, respectively. Bacterial community structure was strongly related to the plant functional composition treatments, but not the rainfall treatment. However, there was a strong effect of both rainfall change and plant functional group upon bacterial abundance. There was also a weak interactive effect of the two treatments upon fungal community structure, although fungal abundance was not affected by either treatment. Next, we used a statistical approach to assess whether treatment effects on ecosystem function were regulated by the microbial community. Our results revealed that ecosystem function was influenced by the experimental treatments, but was not related to associated changes to the microbial community. Overall, these results indicate that changes in fungal and bacterial community structure and abundance play a relatively minor role in determining grassland ecosystem function responses to precipitation and plant functional composition change, and that direct effects on soil physical and chemical properties and upon plant and microbial physiology may play a more important role.

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In this perspective article, we revise some of the empirical and semi-empirical strategies for predicting how hydrogen bonding affects molecular and atomic polarizabilities in aggregates. We use p-nitroaniline and hydrated oxalic acid as working examples to illustrate the enhancement of donor and acceptor functional-group polarizabilities and their anisotropy. This is significant for the evaluation of electrical susceptibilities in crystals; and the properties derived from them like the refractive indices.

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Two recent scanning probe techniques were applied to investigate the bipolar twin state of 4-iodo-4′-nitrobiphenyl (INBP) crystals. Solution grown crystals of INBP show typically a morphology which does not express that of a mono-domain polar structure (Fdd2, mm2). From previous X-ray diffraction a twinning volume ratio of [similar]70 : 30 is now explained by two unipolar domains (Flack parameter: 0.075(29)) of opposite orientation of the molecular dipoles, joined by a transition zone showing a width of [similar]140 μm. Scanning pyroelectric microscopy (SPEM) demonstrates a continuous transition of the polarization P from +P into −P across the zone. Application of piezoelectric force microscopy (PFM) confirms unipolar alignment of INBP molecules down to a resolution of [similar]20 nm. A previously proposed real structure for INBP crystals built from lamellae with antiparallel alignment is thus rejected. Anomalous X-ray scattering was used to determine the absolute molecular orientation in the two domains. End faces of the polar axis 2 are thus made up by NO2 groups. Using a previously determined negative pyroelectric coefficient pc leads to a confirmation also by a SPEM analysis. Calculated values for functional group interactions (DA), (AA), (DD) and the stochastic theory of polarity formation allow us to predict that NO2 groups should terminate corresponding faces. Following the present analysis, INBP may represent a first example undergoing dipole reversal upon growth to end up in a bipolar state.

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We have recently developed a method to obtain distributed atomic polarizabilities adopting a partitioning of the molecular electron density (for example, the Quantum Theory of Atoms in Molecules, [1]), calculated with or without an applied electric field. The procedure [2] allows to obtained atomic polarizability tensors, which are perfectly exportable, because quite representative of an atom in a given functional group. Among the many applications of this idea, the calculation of crystal susceptibility is easily available, either from a rough estimation (the polarizability of the isolated molecule is used) or from a more precise estimation (the polarizability of a molecule embedded in a cluster representing the first coordination sphere is used). Lorentz factor is applied to include the long range effect of packing, which is enhancing the molecular polarizability. Simple properties like linear refractive index or the gyration tensor can be calculated at relatively low costs and with good precision. This approach is particularly useful within the field of crystal engineering of organic/organometallic materials, because it would allow a relatively easy prediction of a property as a function of the packing, thus allowing "reverse crystal engineering". Examples of some amino acid crystals and salts of amino acids [3] will be illustrated, together with other crystallographic or non-crystallographic applications. For example, the induction and dispersion energies of intermolecular interactions could be calculated with superior precision (allowing anisotropic van der Waals interactions). This could allow revision of some commonly misunderstood intermolecular interactions, like the halogen bonding (see for example the recent remarks by Stone or Gilli [4]). Moreover, the chemical reactivity of coordination complexes could be reinvestigated, by coupling the conventional analysis of the electrostatic potential (useful only in the circumstances of hard nucleophilic/electrophilic interaction) with the distributed atomic polarizability. The enhanced reactivity of coordinated organic ligands would be better appreciated. [1] R. F. W. Bader, Atoms in Molecules: A Quantum Theory. Oxford Univ. Press, 1990. [2] A. Krawczuk-Pantula, D. Pérez, K. Stadnicka, P. Macchi, Trans. Amer. Cryst. Ass. 2011, 1-25 [3] A. S. Chimpri1, M. Gryl, L. H.R. Dos Santos1, A. Krawczuk, P. Macchi Crystal Growth & Design, in the press. [4] a) A. J. Stone, J. Am. Chem. Soc. 2013, 135, 7005−7009; b) V. Bertolasi, P. Gilli, G. Gilli Crystal Growth & Design, 2013, 12, 4758-4770.

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Leptospiral pulmonary haemorrhage syndrome (LPHS) is a particularly severe form of leptospirosis. LPHS is increasingly recognized in both humans and animals and is characterized by rapidly progressive intra-alveolar haemorrhage leading to high mortality. The pathogenic mechanisms of LPHS are poorly understood which hampers the application of effective treatment regimes. In this study a 2-D guinea pig proteome lung map was created and used to investigate the pathogenic mechanisms of LPHS. Comparison of lung proteomes from infected and non-infected guinea pigs via differential in-gel electrophoresis revealed highly significant differences in abundance of proteins contained in 130 spots. Acute phase proteins were the largest functional group amongst proteins with increased abundance in LPHS lung tissue, and likely reflect a local and/or systemic host response to infection. The observed decrease in abundance of proteins involved in cytoskeletal and cellular organization in LPHS lung tissue further suggests that infection with pathogenic Leptospira induces changes in the abundance of host proteins involved in cellular architecture and adhesion contributing to the dramatically increased alveolar septal wall permeability seen in LPHS. BIOLOGICAL SIGNIFICANCE The recent completion of the complete genome sequence of the guinea pig (Cavia porcellus) provides innovative opportunities to apply proteomic technologies to an important animal model of disease. In this study, the comparative proteomic analysis of lung tissue from experimentally infected guinea pigs with leptospiral pulmonary haemorrhage syndrome (LPHS) revealed a decrease in abundance of proteins involved in cellular architecture and adhesion, suggesting that loss or down-regulation of cytoskeletal and adhesion molecules plays an important role in the pathogenesis of LPHS. A publically available guinea pig lung proteome map was constructed to facilitate future pulmonary proteomics in this species.

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The general goal of this thesis is correlating observable properties of organic and metal-organic materials with their ground-state electron density distribution. In a long-term view, we expect to develop empirical or semi-empirical approaches to predict materials properties from the electron density of their building blocks, thus allowing to rationally engineering molecular materials from their constituent subunits, such as their functional groups. In particular, we have focused on linear optical properties of naturally occurring amino acids and their organic and metal-organic derivatives, and on magnetic properties of metal-organic frameworks. For analysing the optical properties and the magnetic behaviour of the molecular or sub-molecular building blocks in materials, we mostly used the more traditional QTAIM partitioning scheme of the molecular or crystalline electron densities, however, we have also investigated a new approach, namely, X-ray Constrained Extremely Localized Molecular Orbitals (XC-ELMO), that can be used in future to extracted the electron densities of crystal subunits. With the purpose of rationally engineering linear optical materials, we have calculated atomic and functional group polarizabilities of amino acid molecules, their hydrogen-bonded aggregates and their metal-organic frameworks. This has enabled the identification of the most efficient functional groups, able to build-up larger electric susceptibilities in crystals, as well as the quantification of the role played by intermolecular interactions and coordinative bonds on modifying the polarizability of the isolated building blocks. Furthermore, we analysed the dependence of the polarizabilities on the one-electron basis set and the many-electron Hamiltonian. This is useful for selecting the most efficient level of theory to estimate susceptibilities of molecular-based materials. With the purpose of rationally design molecular magnetic materials, we have investigated the electron density distributions and the magnetism of two copper(II) pyrazine nitrate metal-organic polymers. High-resolution X-ray diffraction and DFT calculations were used to characterize the magnetic exchange pathways and to establish relationships between the electron densities and the exchange-coupling constants. Moreover, molecular orbital and spin-density analyses were employed to understand the role of different magnetic exchange mechanisms in determining the bulk magnetic behaviour of these materials. As anticipated, we have finally investigated a modified version of the X-ray constrained wavefunction technique, XC-ELMOs, that is not only a useful tool for determination and analysis of experimental electron densities, but also enables one to derive transferable molecular orbitals strictly localized on atoms, bonds or functional groups. In future, we expect to use XC-ELMOs to predict materials properties of large systems, currently challenging to calculate from first-principles, such as macromolecules or polymers. Here, we point out advantages, needs and pitfalls of the technique. This work fulfils, at least partially, the prerequisites to understand materials properties of organic and metal-organic materials from the perspective of the electron density distribution of their building blocks. Empirical or semi-empirical evaluation of optical or magnetic properties from a preconceived assembling of building blocks could be extremely important for rationally design new materials, a field where accurate but expensive first-principles calculations are generally not used. This research could impact the community in the fields of crystal engineering, supramolecular chemistry and, of course, electron density analysis.