45 resultados para soil nitrogen


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Studying patterns of species distributions along elevation gradients is frequently used to identify the primary factors that determine the distribution, diversity and assembly of species. However, despite their crucial role in ecosystem functioning, our understanding of the distribution of below-ground fungi is still limited, calling for more comprehensive studies of fungal biogeography along environmental gradients at various scales (from regional to global). Here, we investigated the richness of taxa of soil fungi and their phylogenetic diversity across a wide range of grassland types along a 2800 m elevation gradient at a large number of sites (213), stratified across a region of the Western Swiss Alps (700 km(2)). We used 454 pyrosequencing to obtain fungal sequences that were clustered into operational taxonomic units (OTUs). The OTU diversity-area relationship revealed uneven distribution of fungal taxa across the study area (i.e. not all taxa are everywhere) and fine-scale spatial clustering. Fungal richness and phylogenetic diversity were found to be higher in lower temperatures and higher moisture conditions. Climatic and soil characteristics as well as plant community composition were related to OTU alpha, beta and phylogenetic diversity, with distinct fungal lineages suggesting distinct ecological tolerances. Soil fungi, thus, show lineage-specific biogeographic patterns, even at a regional scale, and follow environmental determinism, mediated by interactions with plants.

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Colloidal transport has been shown to enhance the migration of plutonium in groundwater downstream from contaminated sites, but little is known about the adsorption of ⁹⁰Sr and plutonium onto colloids in the soil solution of natural soils. We sampled soil solutions using suction cups, and separated colloids using ultrafiltration to determine the distribution of ²³⁹Pu and ⁹⁰Sr between the truly dissolved fraction and the colloidal fraction of the solutions of three Alpine soils contaminated only by global fallout from the nuclear weapon tests. Plutonium was essentially found in the colloidal fraction (>80%) and probably associated with organic matter. A significant amount of colloidal ⁹⁰Sr was detected in organic-rich soil solutions. Our results suggest that binding to organic colloids in the soil solutions plays a key role with respect to the mobility of plutonium in natural alpine soils and, to a lesser extent, to the mobility of ⁹⁰Sr.

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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.

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The amount of nitrogen required to complete an insect's life cycle may vary greatly among species that have evolved distinct life history traits. Myrmecophilous caterpillars in the Lycaenidae family produce nitrogen-rich exudates from their dorsal glands to attract ants for protection, and this phenomenon has been postulated to shape the caterpillar's host-plant choice. Accordingly, it was postulated that evolution towards myrmecophily in Lycaenidae is correlated with the utilization of nitrogen-rich host plants. Although our results were consistent with the evolutionary shifts towards high-nutrient host plants serving as exaptation for the evolution of myrmecophily in lycaenids, the selection of nitrogen-rich host plants was not confined to lycaenids. Butterfly species in the nonmyrmecophilous family Pieridae also preferred nitrogen-rich host plants. Thus, we conclude that nitrogen is an overall important component in the caterpillar diet, independent of the level of myrmecophily, as nitrogen can enhance the overall insect fitness and survival. However, when nitrogen can be obtained through alternative means, as in socially parasitic lycaenid species feeding on ant brood, the selective pressure for maintaining the use of nutrient-rich host plants is relaxed, enabling the colonization of nitrogen-poor host plants.

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Natural fluctuations in soil microbial communities are poorly documented because of the inherent difficulty to perform a simultaneous analysis of the relative abundances of multiple populations over a long time period. Yet, it is important to understand the magnitudes of community composition variability as a function of natural influences (e.g., temperature, plant growth, or rainfall) because this forms the reference or baseline against which external disturbances (e.g., anthropogenic emissions) can be judged. Second, definition of baseline fluctuations in complex microbial communities may help to understand at which point the systems become unbalanced and cannot return to their original composition. In this paper, we examined the seasonal fluctuations in the bacterial community of an agricultural soil used for regular plant crop production by using terminal restriction fragment length polymorphism profiling (T-RFLP) of the amplified 16S ribosomal ribonucleic acid (rRNA) gene diversity. Cluster and statistical analysis of T-RFLP data showed that soil bacterial communities fluctuated very little during the seasons (similarity indices between 0.835 and 0.997) with insignificant variations in 16S rRNA gene richness and diversity indices. Despite overall insignificant fluctuations, between 8 and 30% of all terminal restriction fragments changed their relative intensity in a significant manner among consecutive time samples. To determine the magnitude of community variations induced by external factors, soil samples were subjected to either inoculation with a pure bacterial culture, addition of the herbicide mecoprop, or addition of nutrients. All treatments resulted in statistically measurable changes of T-RFLP profiles of the communities. Addition of nutrients or bacteria plus mecoprop resulted in bacteria composition, which did not return to the original profile within 14 days. We propose that at less than 70% similarity in T-RFLP, the bacterial communities risk to drift apart to inherently different states.

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Urea nitrogen, creatinine, and uric acid are relatively stable in postmortem serum and may, therefore, be used for diagnostic purposes when chronic kidney disease and end-stage renal failure are investigated as causes of death. Nevertheless, uncertainties remain in defining the best alternative to postmortem serum for the identification and assessment of significantly decreased kidney function. In this study, we investigated urea nitrogen, creatinine, and uric acid levels in postmortem serum, pericardial fluid, and vitreous humor in a series of medico-legal cases (500 autopsies) with various causes of death. No postmortem interval-related differences were observed in any of the investigated fluids for any analyzed parameter, confirming the biochemical stability of all compounds after death. Data analysis failed to reveal statistically significant differences between postmortem serum and pericardial fluid urea nitrogen, creatinine, and uric acid concentrations. Conversely, statistically significant differences were observed in all analyzed biomarkers between postmortem serum and vitreous humor levels, with lower concentrations of all markers measured in vitreous. The results of this study suggest that, in order to estimate as accurately as possible blood analyte concentrations at the time of death, pericardial fluid should be preferred to vitreous humor.

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It is often thought that the coexistence of plants and plant diversity is determined by resource heterogeneity of the abiotic environment. However, the presence and heterogeneity of biotic plant resources, such as arbuscular mycorrhizal fungi (AMF), could also affect plant species coexistence. In this study, Brachypodium pinnatum and Prunella vulgaris were grown together in pots and biotic resource heterogeneity was simulated by inoculating these pots with one of three different AMF taxa, with a mixture of these three taxa, or pots remained uninoculated. The AMF acted as biotic plant resources since the biomass of plants in pots inoculated with AMF was on average 11.8 times higher than uninoculated pots. The way in which the two plant species coexisted, and the distribution of phosphorus and nitrogen between the plant species, varied strongly depending on which AMF were present. The results showed that the composition of AMF communities determines how plant species coexist and to which plant species nutrients are allocated. Biotic plant resources such as AMF should therefore be considered as one of the factors that determine how plant species coexist and how soil resources are distributed among co-occurring plant species.

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The aim of the present study was to compare, under the same nursing conditions, the energy-nitrogen balance and the protein turnover in small for gestational age (SGA) and appropriate for gestational age (AGA) low birthweight infants. We compared 8 SGA's (mean +/- s.d.: gestational age 35 +/- 2 weeks, birthweight 1520 +/- 330 g) to 11 AGA premature infants (32 +/- 2 weeks, birthweight 1560 +/- 240 g). When their rate of weight gain was above 15 g/kg/d (17.6 +/- 3.0 and 18.2 +/- 2.6 g/kg/d, mean postnatal age 18 +/- 10 and 20 +/- 9 d respectively) they were studied with respect to their metabolizable energy intake, their energy expenditure, their energy and protein gain and their protein turnover. Energy balance was assessed by the difference between metabolizable energy and energy expenditure as measured by indirect calorimetry. Protein gain was calculated from the amount of retained nitrogen. Protein turnover was estimated by a stable isotope enrichment technique using repeated nasogastric administration of 15N-glycine for 72 h. Although there was no difference in their metabolizable energy intakes (110 +/- 12 versus 108 +/- 11 kcal/kg/d), SGA's had a higher rate of resting energy expenditure (64 +/- 8 versus 57 +/- 8 kcal/kg/d, P less than 0.05). Protein gain and composition of weight gain was very similar in both groups (2.0 +/- 0.4 versus 2.1 +/- 0.4 g protein/kg/d; 3.5 +/- 1.1 versus 3.3 +/- 1.4 g fat/kg/d in SGA's and AGA's respectively). However, the rate of protein synthesis was significantly lower in SGA's (7.7 +/- 1.6 g/kg/d) as compared to AGA's (9.7 +/- 2.8 g/kg/d; P less than 0.05). It is concluded that SGA's have a more efficient protein gain/protein synthesis ratio since for the same weight and protein gains, SGA's show a 20 per cent slower protein turnover. They might therefore tolerate slightly higher protein intakes. Postconceptional age seems to be an important factor in the regulation of protein turnover.

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Time-lapse geophysical data acquired during transient hydrological experiments are being increasingly employed to estimate subsurface hydraulic properties at the field scale. In particular, crosshole ground-penetrating radar (GPR) data, collected while water infiltrates into the subsurface either by natural or artificial means, have been demonstrated in a number of studies to contain valuable information concerning the hydraulic properties of the unsaturated zone. Previous work in this domain has considered a variety of infiltration conditions and different amounts of time-lapse GPR data in the estimation procedure. However, the particular benefits and drawbacks of these different strategies as well as the impact of a variety of key and common assumptions remain unclear. Using a Bayesian Markov-chain-Monte-Carlo stochastic inversion methodology, we examine in this paper the information content of time-lapse zero-offset-profile (ZOP) GPR traveltime data, collected under three different infiltration conditions, for the estimation of van Genuchten-Mualem (VGM) parameters in a layered subsurface medium. Specifically, we systematically analyze synthetic and field GPR data acquired under natural loading and two rates of forced infiltration, and we consider the value of incorporating different amounts of time-lapse measurements into the estimation procedure. Our results confirm that, for all infiltration scenarios considered, the ZOP GPR traveltime data contain important information about subsurface hydraulic properties as a function of depth, with forced infiltration offering the greatest potential for VGM parameter refinement because of the higher stressing of the hydrological system. Considering greater amounts of time-lapse data in the inversion procedure is also found to help refine VGM parameter estimates. Quite importantly, however, inconsistencies observed in the field results point to the strong possibility that posterior uncertainties are being influenced by model structural errors, which in turn underlines the fundamental importance of a systematic analysis of such errors in future related studies.

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The top soil of a 14.5 km(2) region at la Chaux-de-Fonds in the Swiss Jura is exceptionally rich in cadmium. It contains an average of 1.3 mg per kg of soil. The spatial distribution of the metal has no simple pattern that could be explained by atmospheric deposition or agricultural practices. Thin soil contained most of its Cd at the surface; in thicker soil Cd is mainly concentrated between 60 and 80 cm depth. No specific minerals or soil fractions could account for these accumulation, and the vertical distribution of Cd is best explained by leaching from the topsoil and further adsorption within layers of nearly neutral pH. The local Jurassic sedimentary rocks contained too little Cd to account for the Cd concentrations in the soil. Alpine gravels from glacial till were too sparse in soils to explain such a spreading of Cd. Moreover this origin is contradictory with the fact that Cd is concentrated in the sand fraction of soils. The respective distributions of Fe and Cd in soils, and soil fractions, suggested that the spreading of iron nodules accumulated during the siderolithic period (Eocene) was not the main source of Cd. Atmospheric deposition, and spreading of fertiliser or waste from septic tanks seem the only plausible explanation for the Cd concentrations, but at present few factors allow us to differentiate between them.

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The opportunistic pathogen Pseudomonas aeruginosa PAO1 has a remarkable capacity to adapt to various environments and to survive with limited nutrients. Here, we report the discovery and characterization of a novel small non-coding RNA: NrsZ (nitrogen-regulated sRNA). We show that under nitrogen limitation, NrsZ is induced by the NtrB/C two component system, an important regulator of nitrogen assimilation and P. aeruginosa's swarming motility, in concert with the alternative sigma factor RpoN. Furthermore, we demonstrate that NrsZ modulates P. aeruginosa motility by controlling the production of rhamnolipid surfactants, virulence factors notably needed for swarming motility. This regulation takes place through the post-transcriptional control of rhlA, a gene essential for rhamnolipids synthesis. Interestingly, we also observed that NrsZ is processed in three similar short modules, and that the first short module encompassing the first 60 nucleotides is sufficient for NrsZ regulatory functions.

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Plants influence the behavior of and modify community composition of soil-dwelling organisms through the exudation of organic molecules. Given the chemical complexity of the soil matrix, soil-dwelling organisms have evolved the ability to detect and respond to these cues for successful foraging. A key question is how specific these responses are and how they may evolve. Here, we review and discuss the ecology and evolution of chemotaxis of soil nematodes. Soil nematodes are a group of diverse functional and taxonomic types, which may reveal a variety of responses. We predicted that nematodes of different feeding guilds use host-specific cues for chemotaxis. However, the examination of a comprehensive nematode phylogeny revealed that distantly related nematodes, and nematodes from different feeding guilds, can exploit the same signals for positive orientation. Carbon dioxide (CO(2)), which is ubiquitous in soil and indicates biological activity, is widely used as such a cue. The use of the same signals by a variety of species and species groups suggests that parts of the chemo-sensory machinery have remained highly conserved during the radiation of nematodes. However, besides CO(2), many other chemical compounds, belonging to different chemical classes, have been shown to induce chemotaxis in nematodes. Plants surrounded by a complex nematode community, including beneficial entomopathogenic nematodes, plant-parasitic nematodes, as well as microbial feeders, are thus under diffuse selection for producing specific molecules in the rhizosphere that maximize their fitness. However, it is largely unknown how selection may operate and how belowground signaling may evolve. Given the paucity of data for certain groups of nematodes, future work is needed to better understand the evolutionary mechanisms of communication between plant roots and soil biota.

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In recent research, both soil (root-zone) and air temperature have been used as predictors for the treeline position worldwide. In this study, we intended to (a) test the proposed temperature limitation at the treeline, and (b) investigate effects of season length for both heat sum and mean temperature variables in the Swiss Alps. As soil temperature data are available for a limited number of sites only, we developed an air-to-soil transfer model (ASTRAMO). The air-to-soil transfer model predicts daily mean root-zone temperatures (10cm below the surface) at the treeline exclusively from daily mean air temperatures. The model using calibrated air and root-zone temperature measurements at nine treeline sites in the Swiss Alps incorporates time lags to account for the damping effect between air and soil temperatures as well as the temporal autocorrelations typical for such chronological data sets. Based on the measured and modeled root-zone temperatures we analyzed. the suitability of the thermal treeline indicators seasonal mean and degree-days to describe the Alpine treeline position. The root-zone indicators were then compared to the respective indicators based on measured air temperatures, with all indicators calculated for two different indicator period lengths. For both temperature types (root-zone and air) and both indicator periods, seasonal mean temperature was the indicator with the lowest variation across all treeline sites. The resulting indicator values were 7.0 degrees C +/- 0.4 SD (short indicator period), respectively 7.1 degrees C +/- 0.5 SD (long indicator period) for root-zone temperature, and 8.0 degrees C +/- 0.6 SD (short indicator period), respectively 8.8 degrees C +/- 0.8 SD (long indicator period) for air temperature. Generally, a higher variation was found for all air based treeline indicators when compared to the root-zone temperature indicators. Despite this, we showed that treeline indicators calculated from both air and root-zone temperatures can be used to describe the Alpine treeline position.