151 resultados para Parameter Estimation


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The ground-penetrating radar (GPR) geophysical method has the potential to provide valuable information on the hydraulic properties of the vadose zone because of its strong sensitivity to soil water content. In particular, recent evidence has suggested that the stochastic inversion of crosshole GPR traveltime data can allow for a significant reduction in uncertainty regarding subsurface van Genuchten-Mualem (VGM) parameters. Much of the previous work on the stochastic estimation of VGM parameters from crosshole GPR data has considered the case of steady-state infiltration conditions, which represent only a small fraction of practically relevant scenarios. We explored in detail the dynamic infiltration case, specifically examining to what extent time-lapse crosshole GPR traveltimes, measured during a forced infiltration experiment at the Arreneas field site in Denmark, could help to quantify VGM parameters and their uncertainties in a layered medium, as well as the corresponding soil hydraulic properties. We used a Bayesian Markov-chain-Monte-Carlo inversion approach. We first explored the advantages and limitations of this approach with regard to a realistic synthetic example before applying it to field measurements. In our analysis, we also considered different degrees of prior information. Our findings indicate that the stochastic inversion of the time-lapse GPR data does indeed allow for a substantial refinement in the inferred posterior VGM parameter distributions compared with the corresponding priors, which in turn significantly improves knowledge of soil hydraulic properties. Overall, the results obtained clearly demonstrate the value of the information contained in time-lapse GPR data for characterizing vadose zone dynamics.

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As modern molecular biology moves towards the analysis of biological systems as opposed to their individual components, the need for appropriate mathematical and computational techniques for understanding the dynamics and structure of such systems is becoming more pressing. For example, the modeling of biochemical systems using ordinary differential equations (ODEs) based on high-throughput, time-dense profiles is becoming more common-place, which is necessitating the development of improved techniques to estimate model parameters from such data. Due to the high dimensionality of this estimation problem, straight-forward optimization strategies rarely produce correct parameter values, and hence current methods tend to utilize genetic/evolutionary algorithms to perform non-linear parameter fitting. Here, we describe a completely deterministic approach, which is based on interval analysis. This allows us to examine entire sets of parameters, and thus to exhaust the global search within a finite number of steps. In particular, we show how our method may be applied to a generic class of ODEs used for modeling biochemical systems called Generalized Mass Action Models (GMAs). In addition, we show that for GMAs our method is amenable to the technique in interval arithmetic called constraint propagation, which allows great improvement of its efficiency. To illustrate the applicability of our method we apply it to some networks of biochemical reactions appearing in the literature, showing in particular that, in addition to estimating system parameters in the absence of noise, our method may also be used to recover the topology of these networks.

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Osteoporosis (OP) is a systemic skeletal disease characterized by a low bone mineral density (BMD) and a micro-architectural (MA) deterioration. Clinical risk factors (CRF) are often used as a MA approximation. MA is yet evaluable in daily practice by the trabecular bone score (TBS) measure. TBS is very simple to obtain, by reanalyzing a lumbar DXA-scan. TBS has proven to have diagnosis and prognosis values, partially independent of CRF and BMD. The aim of the OsteoLaus cohort is to combine in daily practice the CRF and the information given by DXA (BMD, TBS and vertebral fracture assessment (VFA)) to better identify women at high fracture risk. The OsteoLaus cohort (1400 women 50 to 80 years living in Lausanne, Switzerland) started in 2010. This study is derived from the cohort COLAUS who started in Lausanne in 2003. The main goal of COLAUS is to obtain information on the epidemiology and genetic determinants of cardiovascular risk in 6700 men and women. CRF for OP, bone ultrasound of the heel, lumbar spine and hip BMD, VFA by DXA and MA evaluation by TBS are recorded in OsteoLaus. Preliminary results are reported. We included 631 women: mean age 67.4 ± 6.7 years, BMI 26.1 ± 4.6, mean lumbar spine BMD 0.943 ± 0.168 (T-score − 1.4 SD), and TBS 1.271 ± 0.103. As expected, correlation between BMD and site matched TBS is low (r2 = 0.16). Prevalence of VFx grade 2/3, major OP Fx and all OP Fx is 8.4%, 17.0% and 26.0% respectively. Age- and BMI-adjusted ORs (per SD decrease) are 1.8 (1.2-2.5), 1.6 (1.2-2.1), and 1.3 (1.1-1.6) for BMD for the different categories of fractures and 2.0 (1.4-3.0), 1.9 (1.4-2.5), and 1.4 (1.1-1.7) for TBS respectively. Only 32 to 37% of women with OP Fx have a BMD < − 2.5 SD or a TBS < 1.200. If we combine a BMD < − 2.5 SD or a TBS < 1.200, 54 to 60% of women with an osteoporotic Fx are identified. As in the already published studies, these preliminary results confirm the partial independence between BMD and TBS. More importantly, a combination of TBS subsequent to BMD increases significantly the identification of women with prevalent OP Fx which would have been misclassified by BMD alone. For the first time we are able to have complementary information about fracture (VFA), density (BMD), micro- and macro architecture (TBS and HAS) from a simple, low ionizing radiation and cheap device: DXA. Such complementary information is very useful for the patient in the daily practice and moreover will likely have an impact on cost effectiveness analysis.

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Multi-center studies using magnetic resonance imaging facilitate studying small effect sizes, global population variance and rare diseases. The reliability and sensitivity of these multi-center studies crucially depend on the comparability of the data generated at different sites and time points. The level of inter-site comparability is still controversial for conventional anatomical T1-weighted MRI data. Quantitative multi-parameter mapping (MPM) was designed to provide MR parameter measures that are comparable across sites and time points, i.e., 1 mm high-resolution maps of the longitudinal relaxation rate (R1 = 1/T1), effective proton density (PD(*)), magnetization transfer saturation (MT) and effective transverse relaxation rate (R2(*) = 1/T2(*)). MPM was validated at 3T for use in multi-center studies by scanning five volunteers at three different sites. We determined the inter-site bias, inter-site and intra-site coefficient of variation (CoV) for typical morphometric measures [i.e., gray matter (GM) probability maps used in voxel-based morphometry] and the four quantitative parameters. The inter-site bias and CoV were smaller than 3.1 and 8%, respectively, except for the inter-site CoV of R2(*) (<20%). The GM probability maps based on the MT parameter maps had a 14% higher inter-site reproducibility than maps based on conventional T1-weighted images. The low inter-site bias and variance in the parameters and derived GM probability maps confirm the high comparability of the quantitative maps across sites and time points. The reliability, short acquisition time, high resolution and the detailed insights into the brain microstructure provided by MPM makes it an efficient tool for multi-center imaging studies.

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PURPOSE: To use measurement by cycling power meters (Pmes) to evaluate the accuracy of commonly used models for estimating uphill cycling power (Pest). Experiments were designed to explore the influence of wind speed and steepness of climb on accuracy of Pest. The authors hypothesized that the random error in Pest would be largely influenced by the windy conditions, the bias would be diminished in steeper climbs, and windy conditions would induce larger bias in Pest. METHODS: Sixteen well-trained cyclists performed 15 uphill-cycling trials (range: length 1.3-6.3 km, slope 4.4-10.7%) in a random order. Trials included different riding position in a group (lead or follow) and different wind speeds. Pmes was quantified using a power meter, and Pest was calculated with a methodology used by journalists reporting on the Tour de France. RESULTS: Overall, the difference between Pmes and Pest was -0.95% (95%CI: -10.4%, +8.5%) for all trials and 0.24% (-6.1%, +6.6%) in conditions without wind (<2 m/s). The relationship between percent slope and the error between Pest and Pmes were considered trivial. CONCLUSIONS: Aerodynamic drag (affected by wind velocity and orientation, frontal area, drafting, and speed) is the most confounding factor. The mean estimated values are close to the power-output values measured by power meters, but the random error is between ±6% and ±10%. Moreover, at the power outputs (>400 W) produced by professional riders, this error is likely to be higher. This observation calls into question the validity of releasing individual values without reporting the range of random errors.

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In the current issue of epidemiology, Danaei and colleagues elegantly estimated both the direct effect and the indirect effect-that is, the effect mediated by blood pressure, cholesterol, glucose, fibrinogen, and high-sensitivity C-reactive protein-of body mass index (BMI) on the risk of coronary heart disease (CHD). they analyzed data from 9 cohort studies including 58,322 patients and 9459 CHD events, with baseline measurements between 1954 and 2001. Using sophisticated and cutting-edge methods for direct and indirect effect estimations, the authors estimated that half of the risk of overweight and obesity would be mediated by blood pressure, cholesterol, and glucose. Few additional percentage points of the risk would be mediated by fibrinogen and hs-CRP. How should we understand these estimates? Can we say that if obese persons reduce their body weight and reach a normal body weight, their excess risk of CHD would be reduced by half through an improvement in these mediators and by half through the reduction in BmI itself? Is that also true if these individuals are prevented from becoming obese in the first place? Can we also conclude that if these mediators are well controlled in obese individuals through other means than a body weight reduction, their excess risk of CHD would be reduced by half? Let us confront these estimates with observations from studies evaluating 2 interventions to reduce body weight, that is, bariatric surgery in patients with severe obesity and intensive lifestyle intervention in overweight patients with diabetes

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Les modèles hydrologiques développés pour les pluies extrêmes de type PMP sont difficiles à paramétrer en raison du manque de données disponibles pour ces évènements et de la complexité du terrain. Cet article présente les processus et les résultats de l'ajustement des paramètres pour un modèle hydrologique distribué. Ce modèle à une échelle fine a été développé pour l'estimation des crues maximales probables dans le cas d'une PMP. Le calcul effectué pour deux bassins versants test suisses et pour deux épisodes d'orages d'été concerne l'estimation des paramètres du modèle, divisé en deux groupes. La première concerne le calcul des vitesses des écoulements et l'autre la détermination de la capacité d'infiltration initiale et finale pour chaque type de sol. Les résultats validés avec l'équation de Nash montrent une bonne corrélation entre les débits simulés et ceux observés.

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Estimer la filtration glomérulaire chez les personnes âgées, tout en tenant compte de la difficulté supplémentaire d'évaluer leur masse musculaire, est difficile et particulièrement important pour la prescription de médicaments. Le taux plasmatique de la creatinine dépend à la fois de la fraction d'élimination rénale et extra-rénale et de la masse musculaire. Actuellement, pour estimer là filtration glomérulaire différentes formules sont utilisées, qui se fondent principalement sur la valeur de la créatinine. Néanmoins, en raison de la fraction éliminée par les voies tubulaires et intestinales la clairance de la créatinine surestime généralement le taux de filtration glomérulaire (GFR). Le but de cette étude est de vérifier la fiabilité de certains marqueurs et algorithmes de la fonction rénale actuellement utilisés et d'évaluer l'avantage additionnel de prendre en considération la masse musculaire mesurée par la bio-impédance dans une population âgée (> 70 ans) et avec une fonction rénale chronique compromise basée sur MDRD eGFR (CKD stades lll-IV). Dans cette étude, nous comparons 5 équations développées pour estimer la fonction rénale et basées respectivement sur la créatinine sérique (Cockcroft et MDRD), la cystatine C (Larsson), la créatinine combinée à la bêta-trace protéine (White), et la créatinine ajustée à la masse musculaire obtenue par analyse de la bio-impédance (MacDonald). La bio-impédance est une méthode couramment utilisée pour estimer la composition corporelle basée sur l'étude des propriétés électriques passives et de la géométrie des tissus biologiques. Cela permet d'estimer les volumes relatifs des différents tissus ou des fluides dans le corps, comme par exemple l'eau corporelle totale, la masse musculaire (=masse maigre) et la masse grasse corporelle. Nous avons évalué, dans une population âgée d'un service interne, et en utilisant la clairance de l'inuline (single shot) comme le « gold standard », les algorithmes de Cockcroft (GFR CKC), MDRD, Larsson (cystatine C, GFR CYS), White (beta trace protein, GFR BTP) et Macdonald (GFR = ALM, la masse musculaire par bio-impédance. Les résultats ont montré que le GFR (mean ± SD) mesurée avec l'inuline et calculée avec les algorithmes étaient respectivement de : 34.9±20 ml/min pour l'inuline, 46.7±18.5 ml/min pour CKC, 47.2±23 ml/min pour CYS, 54.4±18.2ml/min pour BTP, 49±15.9 ml/min pour MDRD et 32.9±27.2ml/min pour ALM. Les courbes ROC comparant la sensibilité et la spécificité, l'aire sous la courbe (AUC) et l'intervalle de confiance 95% étaient respectivement de : CKC 0 68 (055-0 81) MDRD 0.76 (0.64-0.87), Cystatin C 0.82 (0.72-0.92), BTP 0.75 (0.63-0.87), ALM 0.65 (0.52-0.78). ' En conclusion, les algorithmes comparés dans cette étude surestiment la GFR dans la population agee et hospitalisée, avec des polymorbidités et une classe CKD lll-IV. L'utilisation de l'impédance bioelectrique pour réduire l'erreur de l'estimation du GFR basé sur la créatinine n'a fourni aucune contribution significative, au contraire, elle a montré de moins bons résultats en comparaison aux autres equations. En fait dans cette étude 75% des patients ont changé leur classification CKD avec MacDonald (créatinine et masse musculaire), contre 49% avec CYS (cystatine C), 56% avec MDRD,52% avec Cockcroft et 65% avec BTP. Les meilleurs résultats ont été obtenus avec Larsson (CYS C) et la formule de Cockcroft.

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Introduction: « Osteo-Mobile Vaud » is a mobile osteoporosis (OP) screening program. The women > 60 years living in the region Vaud will be offered OP screening with new equipment installed in a bus. The main goal is to evaluate the fracture risk with the combination of clinical risk factors (CRF) and informations extracted by a single DXA: bone mineral density (BMD), vertebral fracture assessment (VFA), and micro-architecture (MA) evaluation. MA is yet evaluable in daily practice by the Trabecular Bone Score (TBS) measure. TBS is a novel grey-level texture measurement reflecting bone MA based on the use of experimental variograms of 2D projection images. TBS is very simple to obtain, by reanalyzing a lumbar DXA-scan. TBS has proven to have diagnosis and prognosis value, partially independent of CRF and BMD. A 55-years follow- up is planned. Method: The Osteo-Mobile Vaud cohort (1500 women, > 60 years, living in the region Vaud) started in July 2010. CRF for OP, lumbar spine and hip BMD, VFA by DXA and MA evaluation by TBS are recorded. Preliminary results are reported. Results: In July 31th, we evaluated 510 women: mean age 67 years, BMI 26 kg/m². 72 women had one or more fragility fractures, 39 had vertebral fracture (VFx) grade 2/3. TBS decreases with age (-0.005 / year, p<0.001), and with BMI (-0.011 per kg/m², p<0.001). Correlation between BMD and site matched TBS is low (r=0.4, p<0.001). For the lowest T-score BMD, odds ratio (OR, 95% CI) for VFx grade 2/3 and clinical OP Fx are 1.8 (1.1-2.9) and 2.3 (1.5-3.4). For TBS, age-, BMI- and BMD adjusted ORs (per SD decrease) for VFx grade 2/3 and clinical OP Fx are 1.9 (1.2-3.0) and 1.8 (1.2-2.7). The TBS added value was independent of lumbar spine BMD or the lowest T-score (femoral neck, total hip or lumbar spine). Conclusion: As in the already published studies, these preliminary results confirm the partial independence between BMD and TBS. More importantly, a combination of TBS and BMD may increase significantly the identification of women with prevalent OP Fx. For the first time we are able to have complementary information about fracture (VFA), density (BMD), and micro-architecture (TBS) from a simple, low ionizing radiation and cheap device: DXA. The value of such informations in a screening program will be evaluated.

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MOTIVATION: Comparative analyses of gene expression data from different species have become an important component of the study of molecular evolution. Thus methods are needed to estimate evolutionary distances between expression profiles, as well as a neutral reference to estimate selective pressure. Divergence between expression profiles of homologous genes is often calculated with Pearson's or Euclidean distance. Neutral divergence is usually inferred from randomized data. Despite being widely used, neither of these two steps has been well studied. Here, we analyze these methods formally and on real data, highlight their limitations and propose improvements. RESULTS: It has been demonstrated that Pearson's distance, in contrast to Euclidean distance, leads to underestimation of the expression similarity between homologous genes with a conserved uniform pattern of expression. Here, we first extend this study to genes with conserved, but specific pattern of expression. Surprisingly, we find that both Pearson's and Euclidean distances used as a measure of expression similarity between genes depend on the expression specificity of those genes. We also show that the Euclidean distance depends strongly on data normalization. Next, we show that the randomization procedure that is widely used to estimate the rate of neutral evolution is biased when broadly expressed genes are abundant in the data. To overcome this problem, we propose a novel randomization procedure that is unbiased with respect to expression profiles present in the datasets. Applying our method to the mouse and human gene expression data suggests significant gene expression conservation between these species. CONTACT: marc.robinson-rechavi@unil.ch; sven.bergmann@unil.ch SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

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La biologie de la conservation est communément associée à la protection de petites populations menacées d?extinction. Pourtant, il peut également être nécessaire de soumettre à gestion des populations surabondantes ou susceptibles d?une trop grande expansion, dans le but de prévenir les effets néfastes de la surpopulation. Du fait des différences tant quantitatives que qualitatives entre protection des petites populations et contrôle des grandes, il est nécessaire de disposer de modèles et de méthodes distinctes. L?objectif de ce travail a été de développer des modèles prédictifs de la dynamique des grandes populations, ainsi que des logiciels permettant de calculer les paramètres de ces modèles et de tester des scénarios de gestion. Le cas du Bouquetin des Alpes (Capra ibex ibex) - en forte expansion en Suisse depuis sa réintroduction au début du XXème siècle - servit d?exemple. Cette tâche fut accomplie en trois étapes : En premier lieu, un modèle de dynamique locale, spécifique au Bouquetin, fut développé : le modèle sous-jacent - structuré en classes d?âge et de sexe - est basé sur une matrice de Leslie à laquelle ont été ajoutées la densité-dépendance, la stochasticité environnementale et la chasse de régulation. Ce modèle fut implémenté dans un logiciel d?aide à la gestion - nommé SIM-Ibex - permettant la maintenance de données de recensements, l?estimation automatisée des paramètres, ainsi que l?ajustement et la simulation de stratégies de régulation. Mais la dynamique d?une population est influencée non seulement par des facteurs démographiques, mais aussi par la dispersion et la colonisation de nouveaux espaces. Il est donc nécessaire de pouvoir modéliser tant la qualité de l?habitat que les obstacles à la dispersion. Une collection de logiciels - nommée Biomapper - fut donc développée. Son module central est basé sur l?Analyse Factorielle de la Niche Ecologique (ENFA) dont le principe est de calculer des facteurs de marginalité et de spécialisation de la niche écologique à partir de prédicteurs environnementaux et de données d?observation de l?espèce. Tous les modules de Biomapper sont liés aux Systèmes d?Information Géographiques (SIG) ; ils couvrent toutes les opérations d?importation des données, préparation des prédicteurs, ENFA et calcul de la carte de qualité d?habitat, validation et traitement des résultats ; un module permet également de cartographier les barrières et les corridors de dispersion. Le domaine d?application de l?ENFA fut exploré par le biais d?une distribution d?espèce virtuelle. La comparaison à une méthode couramment utilisée pour construire des cartes de qualité d?habitat, le Modèle Linéaire Généralisé (GLM), montra qu?elle était particulièrement adaptée pour les espèces cryptiques ou en cours d?expansion. Les informations sur la démographie et le paysage furent finalement fusionnées en un modèle global. Une approche basée sur un automate cellulaire fut choisie, tant pour satisfaire aux contraintes du réalisme de la modélisation du paysage qu?à celles imposées par les grandes populations : la zone d?étude est modélisée par un pavage de cellules hexagonales, chacune caractérisée par des propriétés - une capacité de soutien et six taux d?imperméabilité quantifiant les échanges entre cellules adjacentes - et une variable, la densité de la population. Cette dernière varie en fonction de la reproduction et de la survie locale, ainsi que de la dispersion, sous l?influence de la densité-dépendance et de la stochasticité. Un logiciel - nommé HexaSpace - fut développé pour accomplir deux fonctions : 1° Calibrer l?automate sur la base de modèles de dynamique (par ex. calculés par SIM-Ibex) et d?une carte de qualité d?habitat (par ex. calculée par Biomapper). 2° Faire tourner des simulations. Il permet d?étudier l?expansion d?une espèce envahisseuse dans un paysage complexe composé de zones de qualité diverses et comportant des obstacles à la dispersion. Ce modèle fut appliqué à l?histoire de la réintroduction du Bouquetin dans les Alpes bernoises (Suisse). SIM-Ibex est actuellement utilisé par les gestionnaires de la faune et par les inspecteurs du gouvernement pour préparer et contrôler les plans de tir. Biomapper a été appliqué à plusieurs espèces (tant végétales qu?animales) à travers le Monde. De même, même si HexaSpace fut initialement conçu pour des espèces animales terrestres, il pourrait aisément être étndu à la propagation de plantes ou à la dispersion d?animaux volants. Ces logiciels étant conçus pour, à partir de données brutes, construire un modèle réaliste complexe, et du fait qu?ils sont dotés d?une interface d?utilisation intuitive, ils sont susceptibles de nombreuses applications en biologie de la conservation. En outre, ces approches peuvent également s?appliquer à des questions théoriques dans les domaines de l?écologie des populations et du paysage.<br/><br/>Conservation biology is commonly associated to small and endangered population protection. Nevertheless, large or potentially large populations may also need human management to prevent negative effects of overpopulation. As there are both qualitative and quantitative differences between small population protection and large population controlling, distinct methods and models are needed. The aim of this work was to develop theoretical models to predict large population dynamics, as well as computer tools to assess the parameters of these models and to test management scenarios. The alpine Ibex (Capra ibex ibex) - which experienced a spectacular increase since its reintroduction in Switzerland at the beginning of the 20th century - was used as paradigm species. This task was achieved in three steps: A local population dynamics model was first developed specifically for Ibex: the underlying age- and sex-structured model is based on a Leslie matrix approach with addition of density-dependence, environmental stochasticity and culling. This model was implemented into a management-support software - named SIM-Ibex - allowing census data maintenance, parameter automated assessment and culling strategies tuning and simulating. However population dynamics is driven not only by demographic factors, but also by dispersal and colonisation of new areas. Habitat suitability and obstacles modelling had therefore to be addressed. Thus, a software package - named Biomapper - was developed. Its central module is based on the Ecological Niche Factor Analysis (ENFA) whose principle is to compute niche marginality and specialisation factors from a set of environmental predictors and species presence data. All Biomapper modules are linked to Geographic Information Systems (GIS); they cover all operations of data importation, predictor preparation, ENFA and habitat suitability map computation, results validation and further processing; a module also allows mapping of dispersal barriers and corridors. ENFA application domain was then explored by means of a simulated species distribution. It was compared to a common habitat suitability assessing method, the Generalised Linear Model (GLM), and was proven better suited for spreading or cryptic species. Demography and landscape informations were finally merged into a global model. To cope with landscape realism and technical constraints of large population modelling, a cellular automaton approach was chosen: the study area is modelled by a lattice of hexagonal cells, each one characterised by a few fixed properties - a carrying capacity and six impermeability rates quantifying exchanges between adjacent cells - and one variable, population density. The later varies according to local reproduction/survival and dispersal dynamics, modified by density-dependence and stochasticity. A software - named HexaSpace - was developed, which achieves two functions: 1° Calibrating the automaton on the base of local population dynamics models (e.g., computed by SIM-Ibex) and a habitat suitability map (e.g. computed by Biomapper). 2° Running simulations. It allows studying the spreading of an invading species across a complex landscape made of variously suitable areas and dispersal barriers. This model was applied to the history of Ibex reintroduction in Bernese Alps (Switzerland). SIM-Ibex is now used by governmental wildlife managers to prepare and verify culling plans. Biomapper has been applied to several species (both plants and animals) all around the World. In the same way, whilst HexaSpace was originally designed for terrestrial animal species, it could be easily extended to model plant propagation or flying animals dispersal. As these softwares were designed to proceed from low-level data to build a complex realistic model and as they benefit from an intuitive user-interface, they may have many conservation applications. Moreover, theoretical questions in the fields of population and landscape ecology might also be addressed by these approaches.