882 resultados para Predicted Distribution Data
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The use of Railroad Flatcars (RRFCs) as the superstructure on low-volume county bridges has been investigated in a research project conducted by the Bridge Engineering Center at Iowa State University. These bridges enable county engineers to replace old, inadequate county bridge superstructures for less than half the cost and in a shorter construction time than required for a conventional bridge. To illustrate their constructability, adequacy, and economy, two RRFC demonstration bridges were designed, constructed, and tested: one in Buchanan County and the other in Winnebago County. The Buchanan County Bridge was constructed as a single span with 56-ft-long flatcars supported at their ends by new, concrete abutments. The use of concrete in the substructure allowed for an integral abutment at one end of the bridge with an expansion joint at the other end. Reinforced concrete beams (serving as longitudinal connections between the three adjacent flatcars) were installed to distribute live loads among the RRFCs. Guardrails and an asphalt milling driving surface completed the bridge. The Winnebago County Bridge was constructed using 89-ft-long flatcars. Preliminary calculations determined that they were not adequate to span 89 ft as a simple span. Therefore, the flatcars were supported by new, steel-capped piers and abutments at the RRFCs' bolsters and ends, resulting in a 66-ft main span and two 10-ft end spans. Due to the RRFC geometry, the longitudinal connections between adjacent RRFCs were inadequate to support significant loads; therefore, transverse, recycled timber planks were utilized to effectively distribute live loads to all three RRFCs. A gravel driving surface was placed on top of the timber planks, and a guardrail system was installed to complete the bridge. Bridge behavior predicted by grillage models for each bridge was validated by strain and deflection data from field tests; it was found that the engineered RRFC bridges have live load stresses significantly below the AASHTO Bridge Design Specification limits. To assist in future RRFC bridge projects, RRFC selection criteria were established for visual inspection and selection of structurally adequate RRFCs. In addition, design recommendations have been developed to simplify live load distribution calculations for the design of the bridges. Based on the results of this research, it has been determined that through proper RRFC selection, construction, and engineering, RRFC bridges are a viable, economic replacement system for low-volume road bridges.
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Recent reports indicate that of the over 25,000 bridges in Iowa, slightly over 7,000 (29%) are either structurally deficient or functionally obsolete. While many of these bridges may be strengthened or rehabilitated, some simply need to be replaced. Before implementing one of these options, one should consider performing a diagnostic load test on the structure to more accurately assess its load carrying capacity. Frequently, diagnostic load tests reveal strength and serviceability characteristics that exceed the predicted codified parameters. Usually, codified parameters are very conservative in predicting lateral load distribution characteristics and the influence of other structural attributes. As a result, the predicted rating factors are typically conservative. In cases where theoretical calculations show a structural deficiency, it may be very beneficial to apply a "tool" that utilizes a more accurate theoretical model which incorporates field-test data. At a minimum, this approach results in more accurate load ratings and many times results in increased rating factors. Bridge Diagnostics, Inc. (BDI) developed hardware and software that are specially designed for performing bridge ratings based on data obtained from physical testing. To evaluate the BDI system, the research team performed diagnostic load tests on seven "typical" bridge structures: three steel-girder bridges with concrete decks, two concrete slab bridges, and two steel-girder bridges with timber decks. In addition, a steel-girder bridge with a concrete deck previously tested and modeled by BDI was investigated for model verification purposes. The tests were performed by attaching strain transducers on the bridges at critical locations to measure strains resulting from truck loading positioned at various locations on the bridge. The field test results were used to develop and validate analytical rating models. Based on the experimental and analytical results, it was determined that bridge tests could be conducted relatively easy, that accurate models could be generated with the BDI software, and that the load ratings, in general, were greater than the ratings, obtained using the codified LFD Method (according to AASHTO Standard Specifications for Highway Bridges).
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A statewide study was performed to develop regional regression equations for estimating selected annual exceedance- probability statistics for ungaged stream sites in Iowa. The study area comprises streamgages located within Iowa and 50 miles beyond the State’s borders. Annual exceedanceprobability estimates were computed for 518 streamgages by using the expected moments algorithm to fit a Pearson Type III distribution to the logarithms of annual peak discharges for each streamgage using annual peak-discharge data through 2010. The estimation of the selected statistics included a Bayesian weighted least-squares/generalized least-squares regression analysis to update regional skew coefficients for the 518 streamgages. Low-outlier and historic information were incorporated into the annual exceedance-probability analyses, and a generalized Grubbs-Beck test was used to detect multiple potentially influential low flows. Also, geographic information system software was used to measure 59 selected basin characteristics for each streamgage. Regional regression analysis, using generalized leastsquares regression, was used to develop a set of equations for each flood region in Iowa for estimating discharges for ungaged stream sites with 50-, 20-, 10-, 4-, 2-, 1-, 0.5-, and 0.2-percent annual exceedance probabilities, which are equivalent to annual flood-frequency recurrence intervals of 2, 5, 10, 25, 50, 100, 200, and 500 years, respectively. A total of 394 streamgages were included in the development of regional regression equations for three flood regions (regions 1, 2, and 3) that were defined for Iowa based on landform regions and soil regions. Average standard errors of prediction range from 31.8 to 45.2 percent for flood region 1, 19.4 to 46.8 percent for flood region 2, and 26.5 to 43.1 percent for flood region 3. The pseudo coefficients of determination for the generalized leastsquares equations range from 90.8 to 96.2 percent for flood region 1, 91.5 to 97.9 percent for flood region 2, and 92.4 to 96.0 percent for flood region 3. The regression equations are applicable only to stream sites in Iowa with flows not significantly affected by regulation, diversion, channelization, backwater, or urbanization and with basin characteristics within the range of those used to develop the equations. These regression equations will be implemented within the U.S. Geological Survey StreamStats Web-based geographic information system tool. StreamStats allows users to click on any ungaged site on a river and compute estimates of the eight selected statistics; in addition, 90-percent prediction intervals and the measured basin characteristics for the ungaged sites also are provided by the Web-based tool. StreamStats also allows users to click on any streamgage in Iowa and estimates computed for these eight selected statistics are provided for the streamgage.
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Summary Due to their conic shape and the reduction of area with increasing elevation, mountain ecosystems were early identified as potentially very sensitive to global warming. Moreover, mountain systems may experience unprecedented rates of warming during the next century, two or three times higher than that records of the 20th century. In this context, species distribution models (SDM) have become important tools for rapid assessment of the impact of accelerated land use and climate change on the distribution plant species. In my study, I developed and tested new predictor variables for species distribution models (SDM), specific to current and future geographic projections of plant species in a mountain system, using the Western Swiss Alps as model region. Since meso- and micro-topography are relevant to explain geographic patterns of plant species in mountain environments, I assessed the effect of scale on predictor variables and geographic projections of SDM. I also developed a methodological framework of space-for-time evaluation to test the robustness of SDM when projected in a future changing climate. Finally, I used a cellular automaton to run dynamic simulations of plant migration under climate change in a mountain landscape, including realistic distance of seed dispersal. Results of future projections for the 21st century were also discussed in perspective of vegetation changes monitored during the 20th century. Overall, I showed in this study that, based on the most severe A1 climate change scenario and realistic dispersal simulations of plant dispersal, species extinctions in the Western Swiss Alps could affect nearly one third (28.5%) of the 284 species modeled by 2100. With the less severe 61 scenario, only 4.6% of species are predicted to become extinct. However, even with B1, 54% (153 species) may still loose more than 80% of their initial surface. Results of monitoring of past vegetation changes suggested that plant species can react quickly to the warmer conditions as far as competition is low However, in subalpine grasslands, competition of already present species is probably important and limit establishment of newly arrived species. Results from future simulations also showed that heavy extinctions of alpine plants may start already in 2040, but the latest in 2080. My study also highlighted the importance of fine scale and regional. assessments of climate change impact on mountain vegetation, using more direct predictor variables. Indeed, predictions at the continental scale may fail to predict local refugees or local extinctions, as well as loss of connectivity between local populations. On the other hand, migrations of low-elevation species to higher altitude may be difficult to predict at the local scale. Résumé La forme conique des montagnes ainsi que la diminution de surface dans les hautes altitudes sont reconnues pour exposer plus sensiblement les écosystèmes de montagne au réchauffement global. En outre, les systèmes de montagne seront sans doute soumis durant le 21ème siècle à un réchauffement deux à trois fois plus rapide que celui mesuré durant le 20ème siècle. Dans ce contexte, les modèles prédictifs de distribution géographique de la végétation se sont imposés comme des outils puissants pour de rapides évaluations de l'impact des changements climatiques et de la transformation du paysage par l'homme sur la végétation. Dans mon étude, j'ai développé de nouvelles variables prédictives pour les modèles de distribution, spécifiques à la projection géographique présente et future des plantes dans un système de montagne, en utilisant les Préalpes vaudoises comme zone d'échantillonnage. La méso- et la microtopographie étant particulièrement adaptées pour expliquer les patrons de distribution géographique des plantes dans un environnement montagneux, j'ai testé les effets d'échelle sur les variables prédictives et sur les projections des modèles de distribution. J'ai aussi développé un cadre méthodologique pour tester la robustesse potentielle des modèles lors de projections pour le futur. Finalement, j'ai utilisé un automate cellulaire pour simuler de manière dynamique la migration future des plantes dans le paysage et dans quatre scénarios de changement climatique pour le 21ème siècle. J'ai intégré dans ces simulations des mécanismes et des distances plus réalistes de dispersion de graines. J'ai pu montrer, avec les simulations les plus réalistes, que près du tiers des 284 espèces considérées (28.5%) pourraient être menacées d'extinction en 2100 dans le cas du plus sévère scénario de changement climatique A1. Pour le moins sévère des scénarios B1, seulement 4.6% des espèces sont menacées d'extinctions, mais 54% (153 espèces) risquent de perdre plus 80% de leur habitat initial. Les résultats de monitoring des changements de végétation dans le passé montrent que les plantes peuvent réagir rapidement au réchauffement climatique si la compétition est faible. Dans les prairies subalpines, les espèces déjà présentes limitent certainement l'arrivée de nouvelles espèces par effet de compétition. Les résultats de simulation pour le futur prédisent le début d'extinctions massives dans les Préalpes à partir de 2040, au plus tard en 2080. Mon travail démontre aussi l'importance d'études régionales à échelle fine pour évaluer l'impact des changements climatiques sur la végétation, en intégrant des variables plus directes. En effet, les études à échelle continentale ne tiennent pas compte des micro-refuges, des extinctions locales ni des pertes de connectivité entre populations locales. Malgré cela, la migration des plantes de basses altitudes reste difficile à prédire à l'échelle locale sans modélisation plus globale.
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The objective of this study was to evaluate the performance of stacked species distribution models in predicting the alpha and gamma species diversity patterns of two important plant clades along elevation in the Andes. We modelled the distribution of the species in the Anthurium genus (53 species) and the Bromeliaceae family (89 species) using six modelling techniques. We combined all of the predictions for the same species in ensemble models based on two different criteria: the average of the rescaled predictions by all techniques and the average of the best techniques. The rescaled predictions were then reclassified into binary predictions (presence/absence). By stacking either the original predictions or binary predictions for both ensemble procedures, we obtained four different species richness models per taxa. The gamma and alpha diversity per elevation band (500 m) was also computed. To evaluate the prediction abilities for the four predictions of species richness and gamma diversity, the models were compared with the real data along an elevation gradient that was independently compiled by specialists. Finally, we also tested whether our richness models performed better than a null model of altitudinal changes of diversity based on the literature. Stacking of the ensemble prediction of the individual species models generated richness models that proved to be well correlated with the observed alpha diversity richness patterns along elevation and with the gamma diversity derived from the literature. Overall, these models tend to overpredict species richness. The use of the ensemble predictions from the species models built with different techniques seems very promising for modelling of species assemblages. Stacking of the binary models reduced the over-prediction, although more research is needed. The randomisation test proved to be a promising method for testing the performance of the stacked models, but other implementations may still be developed.
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We consider the problem of estimating the mean hospital cost of stays of a class of patients (e.g., a diagnosis-related group) as a function of patient characteristics. The statistical analysis is complicated by the asymmetry of the cost distribution, the possibility of censoring on the cost variable, and the occurrence of outliers. These problems have often been treated separately in the literature, and a method offering a joint solution to all of them is still missing. Indirect procedures have been proposed, combining an estimate of the duration distribution with an estimate of the conditional cost for a given duration. We propose a parametric version of this approach, allowing for asymmetry and censoring in the cost distribution and providing a mean cost estimator that is robust in the presence of extreme values. In addition, the new method takes covariate information into account.
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Climate-driven range fluctuations during the Pleistocene have continuously reshaped species distribution leading to populations of contrasting genetic diversity. Contemporary climate change is similarly influencing species distribution and population structure, with important consequences for patterns of genetic diversity and species' evolutionary potential1. Yet few studies assess the impacts of global climatic changes on intraspecific genetic variation2, 3, 4, 5. Here, combining analyses of molecular data with time series of predicted species distributions and a model of diffusion through time over the past 21 kyr, we unravel caribou response to past and future climate changes across its entire Holarctic distribution. We found that genetic diversity is geographically structured with two main caribou lineages, one originating from and confined to Northeastern America, the other originating from Euro-Beringia but also currently distributed in western North America. Regions that remained climatically stable over the past 21 kyr maintained a high genetic diversity and are also predicted to experience higher climatic stability under future climate change scenarios. Our interdisciplinary approach, combining genetic data and spatial analyses of climatic stability (applicable to virtually any taxon), represents a significant advance in inferring how climate shapes genetic diversity and impacts genetic structure.
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Risk maps summarizing landscape suitability of novel areas for invading species can be valuable tools for preventing species' invasions or controlling their spread, but methods employed for development of such maps remain variable and unstandardized. We discuss several considerations in development of such models, including types of distributional information that should be used, the nature of explanatory variables that should be incorporated, and caveats regarding model testing and evaluation. We highlight that, in the case of invasive species, such distributional predictions should aim to derive the best hypothesis of the potential distribution of the species by using (1) all distributional information available, including information from both the native range and other invaded regions; (2) predictors linked as directly as is feasible to the physiological requirements of the species; and (3) modelling procedures that carefully avoid overfitting to the training data. Finally, model testing and evaluation should focus on well-predicted presences, and less on efficient prediction of absences; a k-fold regional cross-validation test is discussed.
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We present a new indicator taxa approach to the prediction of climate change effects on biodiversity at the national level in Switzerland. As indicators, we select a set of the most widely distributed species that account for 95% of geographical variation in sampled species richness of birds, butterflies, and vascular plants. Species data come from a national program designed to monitor spatial and temporal trends in species richness. We examine some opportunities and limitations in using these data. We develop ecological niche models for the species as functions of both climate and land cover variables. We project these models to the future using climate predictions that correspond to two IPCC 3rd assessment scenarios for the development of 'greenhouse' gas emissions. We find that models that are calibrated with Swiss national monitoring data perform well in 10-fold cross-validation, but can fail to capture the hot-dry end of environmental gradients that constrain some species distributions. Models for indicator species in all three higher taxa predict that climate change will result in turnover in species composition even where there is little net change in predicted species richness. Indicator species from high elevations lose most areas of suitable climate even under the relatively mild B2 scenario. We project some areas to increase in the number of species for which climate conditions are suitable early in the current century, but these areas become less suitable for a majority of species by the end of the century. Selection of indicator species based on rank prevalence results in a set of models that predict observed species richness better than a similar set of species selected based on high rank of model AUC values. An indicator species approach based on selected species that are relatively common may facilitate the use of national monitoring data for predicting climate change effects on the distribution of biodiversity.
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OBJECTIVES: Little is known regarding the distribution and the determinants of leptin and adiponectin levels in the general population. DESIGN: Cross-sectional study. PATIENTS: Women (3004) and men (2552) aged 35-74 living in Lausanne, Switzerland. MEASUREMENTS: Plasma levels of leptin and adiponectin (ELISA measurement). RESULTS: Women had higher leptin and adiponectin levels than men. In both genders, leptin and adiponectin levels increased with age. After adjusting for fat mass, leptin levels were significantly and negatively associated with age in women: 18.1 +/- 0.3, 17.1 +/- 0.3, 16.7 +/- 0.3 and 15.5 +/- 0.4 ng/ml (adjusted mean +/- SE) for age groups [35-44], [45-54], [55-64] and [65-75], respectively, P < 0.001. A similar but nonsignificant trend was also found in men. Conversely, the age-related increase of adiponectin was unrelated to body fat in both genders. Post-menopausal women had higher leptin and adiponectin levels than premenopausal women, independently of hormone replacement therapy. Although body fat mass was associated with leptin and adiponectin, the associations were stronger with body mass index (BMI), waist and hip in both genders. Finally, after adjusting for age and anthropometry, no relationships were found between leptin or adiponectin levels with alcohol, caffeine consumption and physical activity, whereas smoking and diabetes decreased leptin and adiponectin levels in women only. CONCLUSIONS: The age-related increase in leptin levels is attributable to changes in fat mass in women and probably also in men. Leptin and adiponectin levels are more related to BMI than to body fat mass. The effects of smoking and diabetes appear to be gender-specific.
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The objective of this work was to evaluate the density, dynamics and vertical distribution of a Hrabeiella periglandulata population in a forest soil at Brno, Czech Republic. From December 2003 to November 2004, two plots covered by mixed stands and two covered by coniferous stands were sampled monthly. Six soil cores per plot were taken down to 15 cm and subdivided into layers, which were subjected to wet funnel extraction. Missing in one of the coniferous stands H. periglandulata was abundant in the mixed stand with the highest soil pH. In this stand, monthly sampling continued until November 2005, with three additional samplings up to January 2007. Mean annual density was 2,672±1,534 individuals m-2. Population dynamics differed from those reported from Germany. Highest densities were reached in early summer, lowest between August and December. Due to aggregated horizontal distribution, differences between monthly values were often nonsignificant. No significant correlation with climatic data was found. Nevertheless, the observed dynamics corresponded to the climatic conditions, showing particularly the negative effect of drought. The population was evenly distributed in the sampled soil profile, only avoiding the organic layer. Except for a locality in Poland, this is the easternmost record of the species.
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The purposes of this study were to determine the distribution and climatic patterns of current and future physic nut (Jatropha curcas) cultivation regions in Mexico, and to identify possible locations for in vivo germplasm banks establishment, using geographic information systems. Current climatic data were processed by Floramap software to obtain distribution maps and climatic patterns of regions where wild physic nuts could be found. DIVA-GIS software analyzed current climatic data (Worldclim model) and climatic data generated by CCM3 model to identify current and future physic nut cultivation regions, respectively. The distribution map showed that physic nut was present in most of the tropical and subtropical areas of Mexico, which corresponded to three agroclimatic regions. Climate types were Aw2, Aw1, and Bs1, for regions 1, 2 and 3, respectively. Nontoxic genotypes were associated with region 2, and toxic genotypes were associated with regions 1 and 3. According to the current and future cultivation regions identified, the best suitable ones to establish in vivo germplasm collections were the coast of Michoacán and the Isthmus of Tehuantepec, located among the states of Veracruz, Oaxaca and Chiapas.
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Abstract: The expansion of a recovering population - whether re-introduced or spontaneously returning - is shaped by (i) biological (intrinsic) factors such as the land tenure system or dispersal, (ii) the distribution and availability of resources (e.g. prey), (iii) habitat and landscape features, and (iv) human attitudes and activities. In order to develop efficient conservation and recovery strategies, we need to understand all these factors and to predict the potential distribution and explore ways to reach it. An increased number of lynx in the north-western Swiss Alps in the nineties lead to a new controversy about the return of this cat. When the large carnivores were given legal protection in many European countries, most organizations and individuals promoting their protection did not foresee the consequences. Management plans describing how to handle conflicts with large predators are needed to find a balance between "overabundance" and extinction. Wildlife and conservation biologists need to evaluate the various threats confronting populations so that adequate management decisions can be taken. I developed a GIS probability model for the lynx, based on habitat information and radio-telemetry data from the Swiss Jura Mountains, in order to predict the potential distribution of the lynx in this mountain range, which is presently only partly occupied by lynx. Three of the 18 variables tested for each square kilometre describing land use, vegetation, and topography, qualified to predict the probability of lynx presence. The resulting map was evaluated with data from dispersing subadult lynx. Young lynx that were not able to establish home ranges in what was identified as good lynx habitat did not survive their first year of independence, whereas the only one that died in good lynx habitat was illegally killed. Radio-telemetry fixes are often used as input data to calibrate habitat models. Radio-telemetry is the only way to gather accurate and unbiased data on habitat use of elusive larger terrestrial mammals. However, it is time consuming and expensive, and can therefore only be applied in limited areas. Habitat models extrapolated over large areas can in turn be problematic, as habitat characteristics and availability may change from one area to the other. I analysed the predictive power of Ecological Niche Factor Analysis (ENFA) in Switzerland with the lynx as focal species. According to my results, the optimal sampling strategy to predict species distribution in an Alpine area lacking available data would be to pool presence cells from contrasted regions (Jura Mountains, Alps), whereas in regions with a low ecological variance (Jura Mountains), only local presence cells should be used for the calibration of the model. Dispersal influences the dynamics and persistence of populations, the distribution and abundance of species, and gives the communities and ecosystems their characteristic texture in space and time. Between 1988 and 2001, the spatio-temporal behaviour of subadult Eurasian lynx in two re-introduced populations in Switzerland was studied, based on 39 juvenile lynx of which 24 were radio-tagged to understand the factors influencing dispersal. Subadults become independent from their mothers at the age of 8-11 months. No sex bias neither in the dispersal rate nor in the distance moved was detected. Lynx are conservative dispersers, compared to bear and wolf, and settled within or close to known lynx occurrences. Dispersal distances reached in the high lynx density population - shorter than those reported in other Eurasian lynx studies - are limited by habitat restriction hindering connections with neighbouring metapopulations. I postulated that high lynx density would lead to an expansion of the population and validated my predictions with data from the north-western Swiss Alps where about 1995 a strong increase in lynx abundance took place. The general hypothesis that high population density will foster the expansion of the population was not confirmed. This has consequences for the re-introduction and recovery of carnivores in a fragmented landscape. To establish a strong source population in one place might not be an optimal strategy. Rather, population nuclei should be founded in several neighbouring patches. Exchange between established neighbouring subpopulations will later on take place, as adult lynx show a higher propensity to cross barriers than subadults. To estimate the potential population size of the lynx in the Jura Mountains and to assess possible corridors between this population and adjacent areas, I adapted a habitat probability model for lynx distribution in the Jura Mountains with new environmental data and extrapolated it over the entire mountain range. The model predicts a breeding population ranging from 74-101 individuals and from 51-79 individuals when continuous habitat patches < 50 km2 are disregarded. The Jura Mountains could once be part of a metapopulation, as potential corridors exist to the adjoining areas (Alps, Vosges Mountains, and Black Forest). Monitoring of the population size, spatial expansion, and the genetic surveillance in the Jura Mountains must be continued, as the status of the population is still critical. ENFA was used to predict the potential distribution of lynx in the Alps. The resulting model divided the Alps into 37 suitable habitat patches ranging from 50 to 18,711 km2, covering a total area of about 93,600 km2. When using the range of lynx densities found in field studies in Switzerland, the Alps could host a population of 961 to 1,827 residents. The results of the cost-distance analysis revealed that all patches were within the reach of dispersing lynx, as the connection costs were in the range of dispersal cost of radio-tagged subadult lynx moving through unfavorable habitat. Thus, the whole Alps could once be considered as a metapopulation. But experience suggests that only few disperser will cross unsuitable areas and barriers. This low migration rate may seldom allow the spontaneous foundation of new populations in unsettled areas. As an alternative to natural dispersal, artificial transfer of individuals across the barriers should be considered. Wildlife biologists can play a crucial role in developing adaptive management experiments to help managers learning by trial. The case of the lynx in Switzerland is a good example of a fruitful cooperation between wildlife biologists, managers, decision makers and politician in an adaptive management process. This cooperation resulted in a Lynx Management Plan which was implemented in 2000 and updated in 2004 to give the cantons directives on how to handle lynx-related problems. This plan was put into practice e.g. in regard to translocation of lynx into unsettled areas. Résumé: L'expansion d'une population en phase de recolonisation, qu'elle soit issue de réintroductions ou d'un retour naturel dépend 1) de facteurs biologiques tels que le système social et le mode de dispersion, 2) de la distribution et la disponibilité des ressources (proies), 3) de l'habitat et des éléments du paysage, 4) de l'acceptation de l'espèce par la population locale et des activités humaines. Afin de pouvoir développer des stratégies efficaces de conservation et de favoriser la recolonisation, chacun de ces facteurs doit être pris en compte. En plus, la distribution potentielle de l'espèce doit pouvoir être déterminée et enfin, toutes les possibilités pour atteindre les objectifs, examinées. La phase de haute densité que la population de lynx a connue dans les années nonante dans le nord-ouest des Alpes suisses a donné lieu à une controverse assez vive. La protection du lynx dans de nombreux pays européens, promue par différentes organisations, a entraîné des conséquences inattendues; ces dernières montrent que tout plan de gestion doit impérativement indiquer des pistes quant à la manière de gérer les conflits, tout en trouvant un équilibre entre l'extinction et la surabondance de l'espèce. Les biologistes de la conservation et de la faune sauvage doivent pour cela évaluer les différents risques encourus par les populations de lynx, afin de pouvoir rapidement prendre les meilleuresmdécisions de gestion. Un modèle d'habitat pour le lynx, basé sur des caractéristiques de l'habitat et des données radio télémétriques collectées dans la chaîne du Jura, a été élaboré afin de prédire la distribution potentielle dans cette région, qui n'est que partiellement occupée par l'espèce. Trois des 18 variables testées, décrivant pour chaque kilomètre carré l'utilisation du sol, la végétation ainsi que la topographie, ont été retenues pour déterminer la probabilité de présence du lynx. La carte qui en résulte a été comparée aux données télémétriques de lynx subadultes en phase de dispersion. Les jeunes qui n'ont pas pu établir leur domaine vital dans l'habitat favorable prédit par le modèle n'ont pas survécu leur première année d'indépendance alors que le seul individu qui est mort dans l'habitat favorable a été braconné. Les données radio-télémétriques sont souvent utilisées pour l'étalonnage de modèles d'habitat. C'est un des seuls moyens à disposition qui permette de récolter des données non biaisées et précises sur l'occupation de l'habitat par des mammifères terrestres aux moeurs discrètes. Mais ces méthodes de- mandent un important investissement en moyens financiers et en temps et peuvent, de ce fait, n'être appliquées qu'à des zones limitées. Les modèles d'habitat sont ainsi souvent extrapolés à de grandes surfaces malgré le risque d'imprécision, qui résulte des variations des caractéristiques et de la disponibilité de l'habitat d'une zone à l'autre. Le pouvoir de prédiction de l'Analyse Ecologique de la Niche (AEN) dans les zones où les données de présence n'ont pas été prises en compte dans le calibrage du modèle a été analysée dans le cas du lynx en Suisse. D'après les résultats obtenus, la meilleure mé- thode pour prédire la distribution du lynx dans une zone alpine dépourvue d'indices de présence est de combiner des données provenant de régions contrastées (Alpes, Jura). Par contre, seules les données sur la présence locale de l'espèce doivent être utilisées pour les zones présentant une faible variance écologique tel que le Jura. La dispersion influence la dynamique et la stabilité des populations, la distribution et l'abondance des espèces et détermine les caractéristiques spatiales et temporelles des communautés vivantes et des écosystèmes. Entre 1988 et 2001, le comportement spatio-temporel de lynx eurasiens subadultes de deux populations réintroduites en Suisse a été étudié, basé sur le suivi de 39 individus juvéniles dont 24 étaient munis d'un collier émetteur, afin de déterminer les facteurs qui influencent la dispersion. Les subadultes se sont séparés de leur mère à l'âge de 8 à 11 mois. Le sexe n'a pas eu d'influence sur le nombre d'individus ayant dispersés et la distance parcourue au cours de la dispersion. Comparé à l'ours et au loup, le lynx reste très modéré dans ses mouvements de dispersion. Tous les individus ayant dispersés se sont établis à proximité ou dans des zones déjà occupées par des lynx. Les distances parcourues lors de la dispersion ont été plus courtes pour la population en phase de haute densité que celles relevées par les autres études de dispersion du lynx eurasien. Les zones d'habitat peu favorables et les barrières qui interrompent la connectivité entre les populations sont les principales entraves aux déplacements, lors de la dispersion. Dans un premier temps, nous avons fait l'hypothèse que les phases de haute densité favorisaient l'expansion des populations. Mais cette hypothèse a été infirmée par les résultats issus du suivi des lynx réalisé dans le nord-ouest des Alpes, où la population connaissait une phase de haute densité depuis 1995. Ce constat est important pour la conservation d'une population de carnivores dans un habitat fragmenté. Ainsi, instaurer une forte population source à un seul endroit n'est pas forcément la stratégie la plus judicieuse. Il est préférable d'établir des noyaux de populations dans des régions voisines où l'habitat est favorable. Des échanges entre des populations avoisinantes pourront avoir lieu par la suite car les lynx adultes sont plus enclins à franchir les barrières qui entravent leurs déplacements que les individus subadultes. Afin d'estimer la taille de la population de lynx dans le Jura et de déterminer les corridors potentiels entre cette région et les zones avoisinantes, un modèle d'habitat a été utilisé, basé sur un nouveau jeu de variables environnementales et extrapolé à l'ensemble du Jura. Le modèle prédit une population reproductrice de 74 à 101 individus et de 51 à 79 individus lorsque les surfaces d'habitat d'un seul tenant de moins de 50 km2 sont soustraites. Comme des corridors potentiels existent effectivement entre le Jura et les régions avoisinantes (Alpes, Vosges, et Forêt Noire), le Jura pourrait faire partie à l'avenir d'une métapopulation, lorsque les zones avoisinantes seront colonisées par l'espèce. La surveillance de la taille de la population, de son expansion spatiale et de sa structure génétique doit être maintenue car le statut de cette population est encore critique. L'AEN a également été utilisée pour prédire l'habitat favorable du lynx dans les Alpes. Le modèle qui en résulte divise les Alpes en 37 sous-unités d'habitat favorable dont la surface varie de 50 à 18'711 km2, pour une superficie totale de 93'600 km2. En utilisant le spectre des densités observées dans les études radio-télémétriques effectuées en Suisse, les Alpes pourraient accueillir une population de lynx résidents variant de 961 à 1'827 individus. Les résultats des analyses de connectivité montrent que les sous-unités d'habitat favorable se situent à des distances telles que le coût de la dispersion pour l'espèce est admissible. L'ensemble des Alpes pourrait donc un jour former une métapopulation. Mais l'expérience montre que très peu d'individus traverseront des habitats peu favorables et des barrières au cours de leur dispersion. Ce faible taux de migration rendra difficile toute nouvelle implantation de populations dans des zones inoccupées. Une solution alternative existe cependant : transférer artificiellement des individus d'une zone à l'autre. Les biologistes spécialistes de la faune sauvage peuvent jouer un rôle important et complémentaire pour les gestionnaires de la faune, en les aidant à mener des expériences de gestion par essai. Le cas du lynx en Suisse est un bel exemple d'une collaboration fructueuse entre biologistes de la faune sauvage, gestionnaires, organes décisionnaires et politiciens. Cette coopération a permis l'élaboration du Concept Lynx Suisse qui est entré en vigueur en 2000 et remis à jour en 2004. Ce plan donne des directives aux cantons pour appréhender la problématique du lynx. Il y a déjà eu des applications concrètes sur le terrain, notamment par des translocations d'individus dans des zones encore inoccupées.
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This paper introduces a mixture model based on the beta distribution, without preestablishedmeans and variances, to analyze a large set of Beauty-Contest data obtainedfrom diverse groups of experiments (Bosch-Domenech et al. 2002). This model gives a bettert of the experimental data, and more precision to the hypothesis that a large proportionof individuals follow a common pattern of reasoning, described as iterated best reply (degenerate),than mixture models based on the normal distribution. The analysis shows thatthe means of the distributions across the groups of experiments are pretty stable, while theproportions of choices at dierent levels of reasoning vary across groups.
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Background Dugesia sicula is the only species of its genus not presenting an endemic or restricted distribution within the Mediterranean area. It mostly comprises fissiparous populations (asexual reproduction by body division and regeneration), most likely sexually sterile, and characterized by an extremely low genetic diversity interpreted as the consequence of a recent anthropic expansion. However, its fissiparous reproduction can result in an apparent lack of diversity within the species, since genetic variation within individuals can be as large as between them because most individuals within a population are clones. We have estimated haplotype and nucleotide diversity of cytochrome oxidase I within and among individuals along the species distribution of a broad sample of D. sicula, including asexual and the two only sexual populations known today; and predicted its potential distribution based on climatic variables. Our aim was to determine the centre of colonisation origin, whether the populations are recent, and whether the species is expanding. Results The species presents 3 most frequent haplotypes, differing in a maximum of 11 base pairs. As expected from their fissiparous mode of reproduction, in half of all the analysed localities many individuals have multiple heteroplasmic haplotypes. The distribution of haplotypes is not geographically structured; however, the distribution of haplotypes and heteroplasmic populations shows higher diversity in the central Mediterranean region. The potential distribution predicted by climatic variables based modelling shows a preference for coastal areas and fits well with the observed data. Conclusions The distribution and frequency of the most frequent haplotypes and the presence of heteroplasmic individuals allow us to gain an understanding of the recent history of the species, together with previous knowledge on its phylogenetic relationships and age: The species most probably originated in Africa and dispersed through the central Mediterranean. After one or multiple populations became triploid and fissiparous, the species colonized the Mediterranean basin, likely both by its own means and helped by human activities. Its present distribution practically fulfils its potential distribution as modelled with climatic variables. Its prevalence in coastal regions with higher water temperatures predicts a likely future expansion to northern and more interior areas following the increase in temperatures due to climate change.