846 resultados para Functional-structural Plant Modelling


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A kutatás célja a marketingeszközök hosszú távú hatásának pontosabb megértése szervezetközi viszonylatban a vevőértékelési modellek egyik nehezen számszerűsíthető tényezője, az ajánlás hatásának vizsgálata által. A hatások elemzésére a strukturális egyenlőségek módszerét (Structural Equation Modelling) alkalmazta a szerző. Rámutatott, hogy az ajánlással szerzett ügyfelek elégedettebbek, lojálisabbak és gyakrabban ajánlják a vállalatot a más módon szerzett ügyfeleknél. Az összefüggések feltárása és bizonyítása különösen az ajánlás kumulatív hatása miatt jelentős. Az eredmények gyakorlati alkalmazásával lehetőség nyílik az ügyfélkör differenciáltabb, értékalapú szegmentációjára, amely pontosabb célcsoport-meghatározást lesz lehetővé, és hosszú távon hozzájárul a vállalat optimális ügyfélportfóliójának kialakításához. ______ The research is aimed at more precise understanding of longterm effects of marketing tools in business to business relations by analysing the impacts of recommendation potential, one of the hardly measurable factors of customer value concept. Structural Equation Modelling is applied for conducting effect analysis. The results show that customers acquired with recommendation are more satisfied, more loyal, and make more recommendation that other customer. These results are more interesting if we take the cumulative effect of recommendation in account. They provide bases for a more differentiated segmentation of customers, which results in a more accurate identification of target groups. In the long-run, the application of the customer-value concept considerably contributes to creating an optimal customer portfolio for companies.

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Objectives: Because there is scientific evidence that an appropriate intake of dietary fibre should be part of a healthy diet, given its importance in promoting health, the present study aimed to develop and validate an instrument to evaluate the knowledge of the general population about dietary fibres. Study design: The present study was a cross sectional study. Methods: The methodological study of psychometric validation was conducted with 6010 participants, residing in ten countries from 3 continents. The instrument is a questionnaire of self-response, aimed at collecting information on knowledge about food fibres. For exploratory factor analysis (EFA) was chosen the analysis of the main components using varimax orthogonal rotation and eigenvalues greater than 1. In confirmatory factor analysis by structural equation modelling (SEM) was considered the covariance matrix and adopted the Maximum Likelihood Estimation algorithm for parameter estimation. Results: Exploratory factor analysis retained two factors. The first was called Dietary Fibre and Promotion of Health (DFPH) and included 7 questions that explained 33.94 % of total variance ( = 0.852). The second was named Sources of Dietary Fibre (SDF) and included 4 questions that explained 22.46% of total variance ( = 0.786). The model was tested by SEM giving a final solution with four questions in each factor. This model showed a very good fit in practically all the indexes considered, except for the ratio 2/df. The values of average variance extracted (0.458 and 0.483) demonstrate the existence of convergent validity; the results also prove the existence of discriminant validity of the factors (r2 = 0.028) and finally good internal consistency was confirmed by the values of composite reliability (0.854 and 0.787). Conclusions: This study allowed validating the KADF scale, increasing the degree of confidence in the information obtained through this instrument in this and in future studies.

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Tomato (Solanum lycopersicum L.) is an important vegetable crop and often cultivated in regions exposed to salinity and high temperatures (HT) which change plant architecture, decrease canopy light interception and disturb physiological functions. However, the long-term effects of salinity and HT combination (S+HT) on plant growth are still unclear. A dynamic functional-structural plant model (FSPM) of tomato was parameterized and evaluated for different levels of S+HT combinations. The evaluated model was used to quantify the contributions of morphological changes (architectural effects) and physiological disturbances (non-architectural effects) on the reduction of shoot dry mass under S+HT. The model predicted architectural variables with high accuracy (>85%), which ensured the reliability of the model analyses. HT enhanced architectural effects but reduced non-architectural effects of salinity on dry mass production. The stronger architectural effects of salinity under HT could not be counterbalanced by the smaller non-architectural effects. Therefore, long-term influences of HT on shoot dry mass under salinity were negative at the whole plant level. Our model analysis highlights the importance of plant architecture at canopy level in studying the plant responses to the environments and shows the merits of dynamic FSPMs as heuristic tools.

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Plant-plant interactions are driven by environmental conditions, evolutionary relationships (ER) and the functional traits of the plants involved. However, studies addressing the relative importance of these drivers are rare, but crucial to improve our predictions of the effects of plant-plant interactions on plant communities and of how they respond to differing environmental conditions. To analyze the relative importance of - and interrelationships among - these factors as drivers of plant-plant interactions, we analyzed perennial plant co-occurrence at 106 dryland plant communities established across rainfall gradients in nine countries. We used structural equation modelling to disentangle the relationships between environmental conditions (aridity and soil fertility), functional traits extracted from the literature, and ER, and to assess their relative importance as drivers of the 929 pairwise plant-plant co-occurrence levels measured. Functional traits, specifically facilitated plants' height and nurse growth form, were of primary importance, and modulated the effect of the environment and ER on plant-plant interactions. Environmental conditions and ER were important mainly for those interactions involving woody and graminoid nurses, respectively. The relative importance of different plant-plant interaction drivers (ER, functional traits, and the environment) varied depending on the region considered, illustrating the difficulty of predicting the outcome of plant-plant interactions at broader spatial scales. In our global-scale study on drylands, plant-plant interactions were more strongly related to functional traits of the species involved than to the environmental variables considered. Thus, moving to a trait-based facilitation/competition approach help to predict that: (1) positive plant-plant interactions are more likely to occur for taller facilitated species in drylands, and (2) plant-plant interactions within woody-dominated ecosystems might be more sensitive to changing environmental conditions than those within grasslands. By providing insights on which species are likely to better perform beneath a given neighbour, our results will also help to succeed in restoration practices involving the use of nurse plants. (C) 2014 Geobotanisches Institut ETH, Stiftung Ruebel. Published by Elsevier GmbH. All rights reserved.

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The pace of on-going climate change calls for reliable plant biodiversity scenarios. Traditional dynamic vegetation models use plant functional types that are summarized to such an extent that they become meaningless for biodiversity scenarios. Hybrid dynamic vegetation models of intermediate complexity (hybrid-DVMs) have recently been developed to address this issue. These models, at the crossroads between phenomenological and process-based models, are able to involve an intermediate number of well-chosen plant functional groups (PFGs). The challenge is to build meaningful PFGs that are representative of plant biodiversity, and consistent with the parameters and processes of hybrid-DVMs. Here, we propose and test a framework based on few selected traits to define a limited number of PFGs, which are both representative of the diversity (functional and taxonomic) of the flora in the Ecrins National Park, and adapted to hybrid-DVMs. This new classification scheme, together with recent advances in vegetation modeling, constitutes a step forward for mechanistic biodiversity modeling.

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Lys49-phospholipases A2 (Lys49-PLA2s) are proteins found in bothropic snake venoms (Viperidae family) and belong to a class of proteins which presents a phospholipase A2 scaffold but are catalytically inactive. These proteins (also known as PLA2s-like toxins) exert a pronounced local myotoxic effect and are not neutralized by antivenom, being their study relevant in terms of medical and scientific interest. Despite of the several studies reported in the literature for this class of proteins only a partial consensus has been achieved concerning their functional-structural relationships. In this work, we present a comprehensive structural and functional study with the MjTX-II, a dimeric Lys49-PLA2 from Bothrops moojeni venom which includes: (i) high-resolution crystal structure; (ii) dynamic light scattering and bioinformatics studies in order to confirm its biological assembly; (iii) myographic and electrophysiological studies and, (iv) comparative studies with other Lys49-PLA2s. These comparative analyses let us to get important insights into the role of Lys122 amino acid, previously indicated as responsible for Lys49-PLA2s catalytic inactivity and added important elements to establish the correct biological assembly for this class of proteins. Furthermore, we show two unique sequential features of MjTX-II (an amino acid insertion and a mutation) in comparison to all bothropic Lys49-PLA2s that lead to a distinct way of ligand binding at the toxin's hydrophobic channel and also, allowed the presence of an additional ligand molecule in this region. These facts suggest a possible particular mode of binding for long-chain ligands that interacts with MjTX-II hydrophobic channel, a feature that may directly affect the design of structure-based ligands for Lys49-PLA2s. © 2013 Elsevier Ltd.

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Plant species richness of permanent grasslands has often been found to be significantly associated with productivity. Concentrations of nutrients in biomass can give further insight into these productivity- plant species richness relationships, e.g. by reflecting land use or soil characteristics. However, the consistency of such relationships across different regions has rarely been taken into account, which might significantly compromise our potential for generalization. We recorded plant species richness and measured above-ground biomass and concentrations of nutrients in biomass in 295 grasslands in three regions in Germany that differ in soil and climatic conditions. Structural equation modelling revealed that nutrient concentrations were mostly indirectly associated with plant species richness via biomass production. However, negative associations between the concentrations of different nutrients and biomass and plant species richness differed considerably among regions. While in two regions, more than 40% of the variation in plant species richness could be attributed to variation in biomass, K, P, and to some degree also N concentrations, in the third region only 15% of the variation could be explained in this way. Generally, highest plant species richness was recorded in grasslands where N and P were co-limiting plant growth, in contrast to N or K (co-) limitation. But again, this pattern was not recorded in the third region. While for two regions land-use intensity and especially the application of fertilizers are suggested to be the main drivers causing the observed negative associations with productivity, in the third region the little variance accounted for, low species richness and weak relationships implied that former intensive grassland management, ongoing mineralization of peat and fluctuating water levels in fen grasslands have overruled effects of current land-use intensity and productivity. Finally, we conclude that regional replication is of major importance for studies seeking general insights into productivity-diversity relationships.

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Most existing studies addressing the effects of invasive species on biodiversity focus on species richness ignoring better indicators of biodiversity and better predictors of ecosystem functioning such as the diversity of evolutionary histories (phylodiversity). Moreover, no previous study has separated the direct effect of alien plants on multiple ecosystem functions simultaneously (multifunctionality) from those indirect ones mediated by the decrease on biodiversity caused by alien plants. We aimed to analyze direct and indirect effects, mediated or not by its effect on biodiversity, of the invasive tree Ailanthus altissima on ecosystem multifunctionality of riparian habitats under Mediterranean climate. We measured vegetation attributes (species richness and phylodiversity) and several surrogates of ecosystem functioning (understory plant biomass, soil enzyme activities, available phosphorous and organic matter) in plots infested by A. altissima and in control (non-invaded) ones. We used structural equation modelling to tease apart the direct and indirect effects of A. altissima on ecosystem multifunctionality. Our results suggest that lower plant species richness, phylodiversity and multifunctionality were associated to the presence of A. altissima. When analyzing each function separately, we found that biodiversity has the opposite effect of the alien plant on all the different functions measured, therefore reducing the strength of the effect (either positive or negative) of A. altissima on them. This is one of the few existing studies addressing the effect of invasive species on phylodiversity and also studying the effect of invasive species on multiple ecosystem functions simultaneously.

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Angadenia berteroi is a tropical perennial subshrub of the pine rocklands with large yellow flowers that set very few fruits. My dissertation seeks to elucidate the factors that affect the reproductive fitness of Angadenia berteroi a native species of the south Florida pine rocklands. I provide novel information on the pollination biology of this native species. I also assess the effects of herbivory on growth and the reproductive success of A. berteroi. Finally, I elucidate how habitat fragmentation and quality are correlated with reproductive fitness of this native perennial plant. Using a novel experimental approach, I determined the most effective pollinator group. I used nylon fishing line of widths corresponding to proboscis diameter of the major groups of visitors to examine pollen removal and deposition. In the field, I estimated visitation frequency and efficacy of each pollinator type. Using potted plants, I exposed flowers to single visit from different types of pollinators to measure fruit set. I performed artificial defoliation with scissors on plants growing in the greenhouse to assess the effects of defoliation before flowering as well as during flowering. Additionally, I used structural equation modelling (SEM) to elucidate how A. berteroi reproductive fitness was affected by habitat fragmentation and quality. My experiments provide evidence that Angadenia berteroi is specialized for bee pollination; though butterflies, skippers and others also visit its flowers, A. berteroi is exclusively pollinated by two native bees of the South Florida pine rocklands . This research also demonstrated that herbivory by the oleander moth may have direct and indirect effects on Angadenia berteroi growth and reproductive success. The SEM results suggested that habitat quality (litter depth and subcanopy cover) may favor reproduction in native species of the South Florida pine rocklands that are properly maintained by periodic fires and exotic control. Insights from this threatened and charismatic species may provide impetus to properly manage remaining pine rocklands in South Florida for this and other endemic understory species.

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Angadenia berteroi is a tropical perennial subshrub of the pine rocklands with large yellow flowers that set very few fruits. My dissertation seeks to elucidate the factors that affect the reproductive fitness of Angadenia berteroi a native species of the south Florida pine rocklands. I provide novel information on the pollination biology of this native species. I also assess the effects of herbivory on growth and the reproductive success of A. berteroi. Finally, I elucidate how habitat fragmentation and quality are correlated with reproductive fitness of this native perennial plant.^ Using a novel experimental approach, I determined the most effective pollinator group. I used nylon fishing line of widths corresponding to proboscis diameter of the major groups of visitors to examine pollen removal and deposition. In the field, I estimated visitation frequency and efficacy of each pollinator type. Using potted plants, I exposed flowers to single visit from different types of pollinators to measure fruit set. I performed artificial defoliation with scissors on plants growing in the greenhouse to assess the effects of defoliation before flowering as well as during flowering. Additionally, I used structural equation modelling (SEM) to elucidate how A. berteroi reproductive fitness was affected by habitat fragmentation and quality. ^ My experiments provide evidence that Angadenia berteroi is specialized for bee pollination; though butterflies, skippers and others also visit its flowers, A. berteroi is exclusively pollinated by two native bees of the South Florida pine rocklands . This research also demonstrated that herbivory by the oleander moth may have direct and indirect effects on Angadenia berteroi growth and reproductive success. The SEM results suggested that habitat quality (litter depth and subcanopy cover) may favor reproduction in native species of the South Florida pine rocklands that are properly maintained by periodic fires and exotic control. Insights from this threatened and charismatic species may provide impetus to properly manage remaining pine rocklands in South Florida for this and other endemic understory species.^

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The characterization of a coffee gene encoding a protein similar to miraculin-like proteins, which are members of the plant Kunitz serine trypsin inhibitor (STI) family of proteinase inhibitors (PIs), is described. PIs are important proteins in plant defence against insects and in the regulation of proteolysis during plant development. This gene has high identity with the Richadella dulcifica taste-modifying protein miraculin and with the tomato protein LeMir; and was named as CoMir (Coffea miraculin). Structural protein modelling indicated that CoMir had structural similarities with the Kunitz STI proteins, but suggested specific folding structures. CoMir was up-regulated after coffee leaf miner (Leucoptera coffella) oviposition in resistant plants of a progeny derived from crosses between C. racemosa (resistant) and C. arabica (susceptible). Interestingly, this gene was down-regulated during coffee leaf miner herbivory in susceptible plants. CoMir expression was up-regulated after abscisic acid application and wounding stress and was prominent during the early stages of flower and fruit development. In situ hybridization revealed that CoMir transcripts accumulated in the anther tissues that display programmed cell death (tapetum, endothecium and stomium) and in the metaxylem vessels of the petals, stigma and leaves. In addition, the recombinant protein CoMir shows inhibitory activity against trypsin. According to the present results CoMir may act in proteolytic regulation during coffee development and in the defence against L. coffeella. The similarity of CoMir with other Kunitz STI proteins and the role of CoMir in plant development and plant stress are discussed.

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Recent advances in computer technology have made it possible to create virtual plants by simulating the details of structural development of individual plants. Software has been developed that processes plant models expressed in a special purpose mini-language based on the Lindenmayer system formalism. These models can be extended from their architectural basis to capture plant physiology by integrating them with crop models, which estimate biomass production as a consequence of environmental inputs. Through this process, virtual plants will gain the ability to react to broad environmental conditions, while crop models will gain a visualisation component. This integration requires the resolution of the fundamentally different time scales underlying the approaches. Architectural models are usually based on physiological time; each time step encompasses the same amount of development in the plant, without regard to the passage of real time. In contrast, physiological models are based in real time; the amount of development in a time step is dependent on environmental conditions during the period. This paper provides a background on the plant modelling language, then describes how widely-used concepts of thermal time can be implemented to resolve these time scale differences. The process is illustrated using a case study. (C) 1997 Elsevier Science Ltd.

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Understanding the distribution and composition of species assemblages and being able to predict them in space and time are highly important tasks io investigate the fate of biodiversity in the current global changes context. Species distribution models are tools that have proven useful to predict the potential distribution of species by relating their occurrences to environmental variables. Species assemblages can then be predicted by combining the prediction of individual species models. In the first part of my thesis, I tested the importance of new environmental predictors to improve species distribution prediction. I showed that edaphic variables, above all soil pH and nitrogen content could be important in species distribution models. In a second chapter, I tested the influence of different resolution of predictors on the predictive ability of species distribution models. I showed that fine resolution predictors could ameliorate the models for some species by giving a better estimation of the micro-topographic condition that species tolerate, but that fine resolution predictors for climatic factors still need to be ameliorated. The second goal of my thesis was to test the ability of empirical models to predict species assemblages' characteristics such as species richness or functional attributes. I showed that species richness could be modelled efficiently and that the resulting prediction gave a more realistic estimate of the number of species than when obtaining it by stacking outputs of single species distribution models. Regarding the prediction of functional characteristics (plant height, leaf surface, seed mass) of plant assemblages, mean and extreme values of functional traits were better predictable than indices reflecting the diversity of traits in the community. This approach proved interesting to understand which environmental conditions influence particular aspects of the vegetation functioning. It could also be useful to predict climate change impacts on the vegetation. In the last part of my thesis, I studied the capacity of stacked species distribution models to predict the plant assemblages. I showed that this method tended to over-predict the number of species and that the composition of the community was not predicted exactly either. Finally, I combined the results of macro- ecological models obtained in the preceding chapters with stacked species distribution models and showed that this approach reduced significantly the number of species predicted and that the prediction of the composition is also ameliorated in some cases. These results showed that this method is promising. It needs now to be tested on further data sets. - Comprendre la manière dont les plantes se répartissent dans l'environnement et s'organisent en communauté est une question primordiale dans le contexte actuel de changements globaux. Cette connaissance peut nous aider à sauvegarder la diversité des espèces et les écosystèmes. Des méthodes statistiques nous permettent de prédire la distribution des espèces de plantes dans l'espace géographique et dans le temps. Ces modèles de distribution d'espèces, relient les occurrences d'une espèce avec des variables environnementales pour décrire sa distribution potentielle. Cette méthode a fait ses preuves pour ce qui est de la prédiction d'espèces individuelles. Plus récemment plusieurs tentatives de cumul de modèles d'espèces individuelles ont été réalisées afin de prédire la composition des communautés végétales. Le premier objectif de mon travail est d'améliorer les modèles de distribution en testant l'importance de nouvelles variables prédictives. Parmi différentes variables édaphiques, le pH et la teneur en azote du sol se sont avérés des facteurs non négligeables pour prédire la distribution des plantes. Je démontre aussi dans un second chapitre que les prédicteurs environnementaux à fine résolution permettent de refléter les conditions micro-topographiques subies par les plantes mais qu'ils doivent encore être améliorés avant de pouvoir être employés de manière efficace dans les modèles. Le deuxième objectif de ce travail consistait à étudier le développement de modèles prédictifs pour des attributs des communautés végétales tels que, par exemple, la richesse en espèces rencontrée à chaque point. Je démontre qu'il est possible de prédire par ce biais des valeurs de richesse spécifiques plus réalistes qu'en sommant les prédictions obtenues précédemment pour des espèces individuelles. J'ai également prédit dans l'espace et dans le temps des caractéristiques de la végétation telles que sa hauteur moyenne, minimale et maximale. Cette approche peut être utile pour comprendre quels facteurs environnementaux promeuvent différents types de végétation ainsi que pour évaluer les changements à attendre au niveau de la végétation dans le futur sous différents régimes de changements climatiques. Dans une troisième partie de ma thèse, j'ai exploré la possibilité de prédire les assemblages de plantes premièrement en cumulant les prédictions obtenues à partir de modèles individuels pour chaque espèce. Cette méthode a le défaut de prédire trop d'espèces par rapport à ce qui est observé en réalité. J'ai finalement employé le modèle de richesse en espèce développé précédemment pour contraindre les résultats du modèle d'assemblage de plantes. Cela a permis l'amélioration des modèles en réduisant la sur-prédiction et en améliorant la prédiction de la composition en espèces. Cette méthode semble prometteuse mais de nouveaux tests sont nécessaires pour bien évaluer ses capacités.