998 resultados para envelope models


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Aim Conservation strategies are in need of predictions that capture spatial community composition and structure. Currently, the methods used to generate these predictions generally focus on deterministic processes and omit important stochastic processes and other unexplained variation in model outputs. Here we test a novel approach of community models that accounts for this variation and determine how well it reproduces observed properties of alpine butterfly communities. Location The western Swiss Alps. Methods We propose a new approach to process probabilistic predictions derived from stacked species distribution models (S-SDMs) in order to predict and assess the uncertainty in the predictions of community properties. We test the utility of our novel approach against a traditional threshold-based approach. We used mountain butterfly communities spanning a large elevation gradient as a case study and evaluated the ability of our approach to model species richness and phylogenetic diversity of communities. Results S-SDMs reproduced the observed decrease in phylogenetic diversity and species richness with elevation, syndromes of environmental filtering. The prediction accuracy of community properties vary along environmental gradient: variability in predictions of species richness was higher at low elevation, while it was lower for phylogenetic diversity. Our approach allowed mapping the variability in species richness and phylogenetic diversity projections. Main conclusion Using our probabilistic approach to process species distribution models outputs to reconstruct communities furnishes an improved picture of the range of possible assemblage realisations under similar environmental conditions given stochastic processes and help inform manager of the uncertainty in the modelling results

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A crucial step in the arenavirus life cycle is the proteolytic processing of the viral envelope glycoprotein precursor (GPC) by the cellular proprotein convertase (PC) subtilisin kexin isozyme-1 (SKI-1)/site-1 protease (S1P). Here we conducted a systematic and quantitative analysis of SKI-1/S1P processing of peptides derived from the recognition sites of GPCs of different Old World and New World arenaviruses. We found that SKI-1/S1P showed a strong preference for arenaviral sequences resembling its autoprocessing sites, which are recurrent motifs in arenaviral GPCs. The African arenaviruses Lassa, Mobala, and Mopeia resemble the SKI-1/S1P autoprocessing C-site, whereas sequences derived from Clade B New World viruses Junin and Tacaribe have similarities to the autoprocessing B-site. In contrast, analogous peptides derived from cellular SKI-1/S1P substrates were remarkably poor substrates. The data suggest that arenavirus GPCs evolved to mimic SKI-1/S1P autoprocessing sites, likely ensuring efficient cleavage and perhaps avoiding competition with SKI-1/S1P's cellular substrates.

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In this paper we highlight the importance of the operational costs in explaining economic growth and analyze how the industrial structure affects the growth rate of the economy. If there is monopolistic competition only in an intermediate goods sector, then production growth coincides with consumption growth. Moreover, the pattern of growth depends on the particular form of the operational cost. If the monopolistically competitive sector is the final goods sector, then per capita production is constant but per capita effective consumption or welfare grows. Finally, we modify again the industrial structure of the economy and show an economy with two different growth speeds, one for production and another for effective consumption. Thus, both the operational cost and the particular structure of the sector that produces the final goods determines ultimately the pattern of growth.

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[eng] This paper provides, from a theoretical and quantitative point of view, an explanation of why taxes on capital returns are high (around 35%) by analyzing the optimal fiscal policy in an economy with intergenerational redistribution. For this purpose, the government is modeled explicitly and can choose (and commit to) an optimal tax policy in order to maximize society's welfare. In an infinitely lived economy with heterogeneous agents, the long run optimal capital tax is zero. If heterogeneity is due to the existence of overlapping generations, this result in general is no longer true. I provide sufficient conditions for zero capital and labor taxes, and show that a general class of preferences, commonly used on the macro and public finance literature, violate these conditions. For a version of the model, calibrated to the US economy, the main results are: first, if the government is restricted to a set of instruments, the observed fiscal policy cannot be disregarded as sub optimal and capital taxes are positive and quantitatively relevant. Second, if the government can use age specific taxes for each generation, then the age profile capital tax pattern implies subsidizing asset returns of the younger generations and taxing at higher rates the asset returns of the older ones.

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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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Summary Detection, analysis and monitoring of slope movements by high-resolution digital elevation modelsSlope movements, such as rockfalls, rockslides, shallow landslides or debris flows, are frequent in many mountainous areas. These natural hazards endanger the inhabitants and infrastructures making it necessary to assess the hazard and risk caused by these phenomena. This PhD thesis explores various approaches using digital elevation models (DEMs) - and particularly high-resolution DEMs created by aerial or terrestrial laser scanning (TLS) - that contribute to the assessment of slope movement hazard at regional and local scales.The regional detection of areas prone to rockfalls and large rockslides uses different morphologic criteria or geometric instability factors derived from DEMs, i.e. the steepness of the slope, the presence of discontinuities, which enable a sliding mechanism, and the denudation potential. The combination of these factors leads to a map of susceptibility to rockfall initiation that is in good agreement with field studies as shown with the example of the Little Mill Campground area (Utah, USA). Another case study in the Illgraben catchment in the Swiss Alps highlighted the link between areas with a high denudation potential and actual rockfall areas.Techniques for a detailed analysis and characterization of slope movements based on high-resolution DEMs have been developed for specific, localized sites, i.e. ancient slide scars, present active instabilities or potential slope instabilities. The analysis of the site's characteristics mainly focuses on rock slopes and includes structural analyses (orientation of discontinuities); estimation of spacing, persistence and roughness of discontinuities; failure mechanisms based on the structural setting; and volume calculations. For the volume estimation a new 3D approach was tested to reconstruct the topography before a landslide or to construct the basal failure surface of an active or potential instability. The rockslides at Åknes, Tafjord and Rundefjellet in western Norway were principally used as study sites to develop and test the different techniques.The monitoring of slope instabilities investigated in this PhD thesis is essentially based on multitemporal (or sequential) high-resolution DEMs, in particular sequential point clouds acquired by TLS. The changes in the topography due to slope movements can be detected and quantified by sequential TLS datasets, notably by shortest distance comparisons revealing the 3D slope movements over the entire region of interest. A detailed analysis of rock slope movements is based on the affine transformation between an initial and a final state of the rock mass and its decomposition into translational and rotational movements. Monitoring using TLS was very successful on the fast-moving Eiger rockslide in the Swiss Alps, but also on the active rockslides of Åknes and Nordnesfjellet (northern Norway). One of the main achievements on the Eiger and Aknes rockslides is to combine the site's morphology and structural setting with the measured slope movements to produce coherent instability models. Both case studies also highlighted a strong control of the structures in the rock mass on the sliding directions. TLS was also used to monitor slope movements in soils, such as landslides in sensitive clays in Québec (Canada), shallow landslides on river banks (Sorge River, Switzerland) and a debris flow channel (Illgraben).The PhD thesis underlines the broad uses of high-resolution DEMs and especially of TLS in the detection, analysis and monitoring of slope movements. Future studies should explore in more depth the different techniques and approaches developed and used in this PhD, improve them and better integrate the findings in current hazard assessment practices and in slope stability models.Résumé Détection, analyse et surveillance de mouvements de versant à l'aide de modèles numériques de terrain de haute résolutionDes mouvements de versant, tels que des chutes de blocs, glissements de terrain ou laves torrentielles, sont fréquents dans des régions montagneuses et mettent en danger les habitants et les infrastructures ce qui rend nécessaire d'évaluer le danger et le risque causé par ces phénomènes naturels. Ce travail de thèse explore diverses approches qui utilisent des modèles numériques de terrain (MNT) et surtout des MNT de haute résolution créés par scanner laser terrestre (SLT) ou aérien - et qui contribuent à l'évaluation du danger de mouvements de versant à l'échelle régionale et locale.La détection régionale de zones propices aux chutes de blocs ou aux éboulements utilise plusieurs critères morphologiques dérivés d'un MNT, tels que la pente, la présence de discontinuités qui permettent un mécanisme de glissement ou le potentiel de dénudation. La combinaison de ces facteurs d'instabilité mène vers une carte de susceptibilité aux chutes de blocs qui est en accord avec des travaux de terrain comme démontré avec l'exemple du Little Mill Campground (Utah, États-Unis). Un autre cas d'étude - l'Illgraben dans les Alpes valaisannes - a mis en évidence le lien entre les zones à fort potentiel de dénudation et les sources effectives de chutes de blocs et d'éboulements.Des techniques pour l'analyse et la caractérisation détaillée de mouvements de versant basées sur des MNT de haute résolution ont été développées pour des sites spécifiques et localisés, comme par exemple des cicatrices d'anciens éboulements et des instabilités actives ou potentielles. Cette analyse se focalise principalement sur des pentes rocheuses et comprend l'analyse structurale (orientation des discontinuités); l'estimation de l'espacement, la persistance et la rugosité des discontinuités; l'établissement des mécanismes de rupture; et le calcul de volumes. Pour cela une nouvelle approche a été testée en rétablissant la topographie antérieure au glissement ou en construisant la surface de rupture d'instabilités actuelles ou potentielles. Les glissements rocheux d'Åknes, Tafjord et Rundefjellet en Norvège ont été surtout utilisés comme cas d'étude pour développer et tester les diverses approches. La surveillance d'instabilités de versant effectuée dans cette thèse de doctorat est essentiellement basée sur des MNT de haute résolution multi-temporels (ou séquentiels), en particulier des nuages de points séquentiels acquis par SLT. Les changements topographiques dus aux mouvements de versant peuvent être détectés et quantifiés sur l'ensemble d'un glissement, notamment par comparaisons des distances les plus courtes entre deux nuages de points. L'analyse détaillée des mouvements est basée sur la transformation affine entre la position initiale et finale d'un bloc et sa décomposition en mouvements translationnels et rotationnels. La surveillance par SLT a démontré son potentiel avec l'effondrement d'un pan de l'Eiger dans les Alpes suisses, mais aussi aux glissements rocheux d'Aknes et Nordnesfjellet en Norvège. Une des principales avancées à l'Eiger et à Aknes est la création de modèles d'instabilité cohérents en combinant la morphologie et l'agencement structural des sites avec les mesures de déplacements. Ces deux cas d'étude ont aussi démontré le fort contrôle des structures existantes dans le massif rocheux sur les directions de glissement. Le SLT a également été utilisé pour surveiller des glissements dans des terrains meubles comme dans les argiles sensibles au Québec (Canada), sur les berges de la rivière Sorge en Suisse et dans le chenal à laves torrentielles de l'Illgraben.Cette thèse de doctorat souligne le vaste champ d'applications des MNT de haute résolution et particulièrement du SLT dans la détection, l'analyse et la surveillance des mouvements de versant. Des études futures devraient explorer plus en profondeur les différentes techniques et approches développées, les améliorer et mieux les intégrer dans des pratiques actuelles d'analyse de danger et surtout dans la modélisation de stabilité des versants.

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This study aims to improve the accuracy of AASHTO Mechanistic-Empirical Pavement Design Guide (MEPDG) pavement performance predictions for Iowa pavement systems through local calibration of MEPDG prediction models. A total of 130 representative pavement sites across Iowa were selected. The selected pavement sites represent flexible, rigid, and composite pavement systems throughout Iowa. The required MEPDG inputs and the historical performance data for the selected sites were extracted from a variety of sources. The accuracy of the nationally-calibrated MEPDG prediction models for Iowa conditions was evaluated. The local calibration factors of MEPDG performance prediction models were identified to improve the accuracy of model predictions. The identified local calibration coefficients are presented with other significant findings and recommendations for use in MEPDG/DARWin-ME for Iowa pavement systems.

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This study aims to improve the accuracy of AASHTO Mechanistic-Empirical Pavement Design Guide (MEPDG) pavement performance predictions for Iowa pavement systems through local calibration of MEPDG prediction models. A total of 130 representative pavement sites across Iowa were selected. The selected pavement sites represent flexible, rigid, and composite pavement systems throughout Iowa. The required MEPDG inputs and the historical performance data for the selected sites were extracted from a variety of sources. The accuracy of the nationally-calibrated MEPDG prediction models for Iowa conditions was evaluated. The local calibration factors of MEPDG performance prediction models were identified to improve the accuracy of model predictions. The identified local calibration coefficients are presented with other significant findings and recommendations for use in MEPDG/DARWin-ME for Iowa pavement systems.

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Aim: Climatic niche modelling of species and community distributions implicitly assumes strong and constant climatic determinism across geographic space. This assumption had however never been tested so far. We tested it by assessing how stacked-species distribution models (S-SDMs) perform for predicting plant species assemblages along elevation. Location: Western Swiss Alps. Methods: Using robust presence-absence data, we first assessed the ability of topo-climatic S-SDMs to predict plant assemblages in a study area encompassing a 2800 m wide elevation gradient. We then assessed the relationships among several evaluation metrics and trait-based tests of community assembly rules. Results: The standard errors of individual SDMs decreased significantly towards higher elevations. Overall, the S-SDM overpredicted far more than they underpredicted richness and could not reproduce the humpback curve along elevation. Overprediction was greater at low and mid-range elevations in absolute values but greater at high elevations when standardised by the actual richness. Looking at species composition, the evaluation metrics accounting for both the presence and absence of species (overall prediction success and kappa) or focusing on correctly predicted absences (specificity) increased with increasing elevation, while the metrics focusing on correctly predicted presences (Jaccard index and sensitivity) decreased. The best overall evaluation - as driven by specificity - occurred at high elevation where species assemblages were shown to be under significant environmental filtering of small plants. In contrast, the decreased overall accuracy in the lowlands was associated with functional patterns representing any type of assembly rule (environmental filtering, limiting similarity or null assembly). Main Conclusions: Our study reveals interesting patterns of change in S-SDM errors with changes in assembly rules along elevation. Yet, significant levels of assemblage prediction errors occurred throughout the gradient, calling for further improvement of SDMs, e.g., by adding key environmental filters that act at fine scales and developing approaches to account for variations in the influence of predictors along environmental gradients.