Can climate shape flight activity patterns of Plebeia remota Hymenoptera, Apidae)?

Flight activity of foragers of four colonies of Plebeia remota (Holmberg, 1903) was registered from December 1998 to December 1999, using an automated system (photocells and PLC system). The colonies originated from two different regions: Cunha, state of São Paulo, and Prudentópolis, state of Paraná, Brazil. Flight activity was influenced by different climatic factors in each season. In the summer, the intensity of the correlations between flight activity and climatic factors was smaller than in the other seasons. During the autumn and winter, solar radiation was the factor that most influenced flight activity, while in the spring, this activity was influenced mainly by temperature. Except in the summer, the various climatic factors similarly influenced flight activity of all of the colonies. Flight activity was not affected by geographic origin of the colonies. Information concerning seasonal differences in flight activity of P. remota will be useful for prediction of geographic distribution scenarios under climatic changes.

The distribution of intestinal helminth infections in a rural village in Guatemala

Fecal egg count scores were used to investigate the distribution and abundance of intestinal helminths in the population of a rural village. Prevalences of the major helminths were 41% with Ascaris lumbricoides 60% with Trichuris trichiura and 50% with Necator americanus. All three parasites showed a highly aggregated distribution among hosts. Age/prevalence and age/intensity profiles were typical for both A. lumbricoides and T. trichiura with the highest worm burdens in the 50-10 year old children. For hookworm both prevalence and intensity curves were convex in shape with maximum infection levels in the 30-40 year old age class. Infected females had higher burdens of T. trichiura than infected males in all age classes of the population; there were no other effects of host gender. Analysis of associations between parasites within hosts revealed strong correlations between A. lumbricoides and T. lumbricoides and T. trichiura. Individuals with heavy infections of A. lumbricoides and T. trichiura showed highly significant aggregation within households. Associations between a variety of household features and heavy infections with A. lumbricoides and T. trichiura are described.

What do we gain from simplicity versus complexity in species distribution models?

Species distribution models (SDMs) are widely used to explain and predict species ranges and environmental niches. They are most commonly constructed by inferring species' occurrence-environment relationships using statistical and machine-learning methods. The variety of methods that can be used to construct SDMs (e.g. generalized linear/additive models, tree-based models, maximum entropy, etc.), and the variety of ways that such models can be implemented, permits substantial flexibility in SDM complexity. Building models with an appropriate amount of complexity for the study objectives is critical for robust inference. We characterize complexity as the shape of the inferred occurrence-environment relationships and the number of parameters used to describe them, and search for insights into whether additional complexity is informative or superfluous. By building 'under fit' models, having insufficient flexibility to describe observed occurrence-environment relationships, we risk misunderstanding the factors shaping species distributions. By building 'over fit' models, with excessive flexibility, we risk inadvertently ascribing pattern to noise or building opaque models. However, model selection can be challenging, especially when comparing models constructed under different modeling approaches. Here we argue for a more pragmatic approach: researchers should constrain the complexity of their models based on study objective, attributes of the data, and an understanding of how these interact with the underlying biological processes. We discuss guidelines for balancing under fitting with over fitting and consequently how complexity affects decisions made during model building. Although some generalities are possible, our discussion reflects differences in opinions that favor simpler versus more complex models. We conclude that combining insights from both simple and complex SDM building approaches best advances our knowledge of current and future species ranges.

Role of Particle Shape on the Stress Propagation in Granular Packings

We present an experimental and numerical study on the influence that particle aspect ratio has on the mechanical and structural properties of granular packings. For grains with maximal symmetry (squares), the stress propagation in the packing localizes forming chainlike forces analogous to the ones observed for spherical grains. This scenario can be understood in terms of stochastic models of aggregation and random multiplicative processes. As the grains elongate, the stress propagation is strongly affected. The interparticle normal force distribution tends toward a Gaussian, and, correspondingly, the force chains spread leading to a more uniform stress distribution reminiscent of the hydrostatic profiles known for standard liquids

Bilinear models for spatio-temporal point distribution analysis: application to extrapolation of left ventricular, biventricular and whole heart cardiac dynamics

In this work we describe the usage of bilinear statistical models as a means of factoring the shape variability into two components attributed to inter-subject variation and to the intrinsic dynamics of the human heart. We show that it is feasible to reconstruct the shape of the heart at discrete points in the cardiac cycle. Provided we are given a small number of shape instances representing the same heart atdifferent points in the same cycle, we can use the bilinearmodel to establish this. Using a temporal and a spatial alignment step in the preprocessing of the shapes, around half of the reconstruction errors were on the order of the axial image resolution of 2 mm, and over 90% was within 3.5 mm. From this, weconclude that the dynamics were indeed separated from theinter-subject variability in our dataset.

The role of biotic interactions in shaping distributions and realised assemblages of species: implications for species distribution modelling.

Predicting which species will occur together in the future, and where, remains one of the greatest challenges in ecology, and requires a sound understanding of how the abiotic and biotic environments interact with dispersal processes and history across scales. Biotic interactions and their dynamics influence species' relationships to climate, and this also has important implications for predicting future distributions of species. It is already well accepted that biotic interactions shape species' spatial distributions at local spatial extents, but the role of these interactions beyond local extents (e.g. 10 km(2) to global extents) are usually dismissed as unimportant. In this review we consolidate evidence for how biotic interactions shape species distributions beyond local extents and review methods for integrating biotic interactions into species distribution modelling tools. Drawing upon evidence from contemporary and palaeoecological studies of individual species ranges, functional groups, and species richness patterns, we show that biotic interactions have clearly left their mark on species distributions and realised assemblages of species across all spatial extents. We demonstrate this with examples from within and across trophic groups. A range of species distribution modelling tools is available to quantify species environmental relationships and predict species occurrence, such as: (i) integrating pairwise dependencies, (ii) using integrative predictors, and (iii) hybridising species distribution models (SDMs) with dynamic models. These methods have typically only been applied to interacting pairs of species at a single time, require a priori ecological knowledge about which species interact, and due to data paucity must assume that biotic interactions are constant in space and time. To better inform the future development of these models across spatial scales, we call for accelerated collection of spatially and temporally explicit species data. Ideally, these data should be sampled to reflect variation in the underlying environment across large spatial extents, and at fine spatial resolution. Simplified ecosystems where there are relatively few interacting species and sometimes a wealth of existing ecosystem monitoring data (e.g. arctic, alpine or island habitats) offer settings where the development of modelling tools that account for biotic interactions may be less difficult than elsewhere.

Constant fluctuating asymmetry but not directional asymmetry along the geographic distribution of Drosophila antonietae (Diptera, Drosophilidae)

ABSTRACT The population dynamics of a species tends to change from the core to the periphery of its distribution. Therefore, one could expect peripheral populations to be subject to a higher level of stress than more central populations (the center–periphery hypothesis) and consequently should present a higher level of fluctuating asymmetry. To test these predictions we study asymmetry in wing shape of five populations of Drosophila antonietae collected throughout the distribution of the species using fluctuating asymmetry as a proxy for developmental instability. More specifically, we addressed the following questions: (1) what types of asymmetry occur in populations of D. antonietae? (2) Does the level of fluctuating asymmetry vary among populations? (3) Does peripheral populations have a higher fluctuating asymmetry level than central populations? We used 12 anatomical landmarks to quantify patterns of asymmetry in wing shape in five populations of D. antonietae within the framework of geometric morphometrics. Net asymmetry – a composite measure of directional asymmetry + fluctuating asymmetry – varied significantly among populations. However, once net asymmetry of each population is decomposed into directional asymmetry and fluctuating asymmetry, most of the variation in asymmetry was explained by directional asymmetry alone, suggesting that populations of D. antonietae have the same magnitude of fluctuating asymmetry throughout the geographical distribution of the species. We hypothesize that larval development in rotting cladodes might play an important role in explaining our results. In addition, our study underscores the importance of understanding the interplay between the biology of a species and its geographical patterns of asymmetry.

Spatial Exploration of Age Distribution in Catalan Municipalities

This paper takes the shelf and digs into the complex population’s age structure of Catalan municipalities for the year 2009. Catalonia is a very heterogeneous territory, and age pyramids vary considerably across different areas of the territory, existing geographical factors shaping municipalities’ age distributions. By means of spatial statistics methodologies, this piece of research tries to assess which spatial factors determine the location, scale and shape of local distributions. The results show that there exist different distributional patterns across the geography according to specific local determinants. Keywords: Spatial Models. JEL Classification: C21.

Providing more informative projections of climate change impact on plant distribution in a mountain environment

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.

Wave-height hazard analysis in Eastern Coast of Spain : Bayesian approach using generalized Pareto distribution

Standard practice of wave-height hazard analysis often pays little attention to the uncertainty of assessed return periods and occurrence probabilities. This fact favors the opinion that, when large events happen, the hazard assessment should change accordingly. However, uncertainty of the hazard estimates is normally able to hide the effect of those large events. This is illustrated using data from the Mediterranean coast of Spain, where the last years have been extremely disastrous. Thus, it is possible to compare the hazard assessment based on data previous to those years with the analysis including them. With our approach, no significant change is detected when the statistical uncertainty is taken into account. The hazard analysis is carried out with a standard model. Time-occurrence of events is assumed Poisson distributed. The wave-height of each event is modelled as a random variable which upper tail follows a Generalized Pareto Distribution (GPD). Moreover, wave-heights are assumed independent from event to event and also independent of their occurrence in time. A threshold for excesses is assessed empirically. The other three parameters (Poisson rate, shape and scale parameters of GPD) are jointly estimated using Bayes' theorem. Prior distribution accounts for physical features of ocean waves in the Mediterranean sea and experience with these phenomena. Posterior distribution of the parameters allows to obtain posterior distributions of other derived parameters like occurrence probabilities and return periods. Predictives are also available. Computations are carried out using the program BGPE v2.0

Robust Estimators of the Generalized Log-Gamma Distribution

We propose robust estimators of the generalized log-gamma distribution and, more generally, of location-shape-scale families of distributions. A (weighted) Q tau estimator minimizes a tau scale of the differences between empirical and theoretical quantiles. It is n(1/2) consistent; unfortunately, it is not asymptotically normal and, therefore, inconvenient for inference. However, it is a convenient starting point for a one-step weighted likelihood estimator, where the weights are based on a disparity measure between the model density and a kernel density estimate. The one-step weighted likelihood estimator is asymptotically normal and fully efficient under the model. It is also highly robust under outlier contamination. Supplementary materials are available online.

Tree cover at fine and coarse spatial grains interacts with shade tolerance to shape plant species distributions across the Alps

The role of competition for light among plants has long been recognized at local scales, but its potential importance for plant species' distribution at larger spatial scales has largely been ignored. Tree cover acts as a modulator of local abiotic conditions, notably by reducing light availability below the canopy and thus the performance of species that are not adapted to low-light conditions. However, this local effect may propagate to coarser spatial grains. Using 6,935 vegetation plots located across the European Alps, we fit Generalized Linear Models (GLM) for the distribution of 960 herbs and shrubs species to assess the effect of tree cover at both plot and landscape grain sizes (~ 10-m and 1-km, respectively). We ran four models with different combinations of variables (climate, soil and tree cover) for each species at both spatial grains. We used partial regressions to evaluate the independent effects of plot- and landscape-scale tree cover on plant communities. Finally, the effects on species' elevational range limits were assessed by simulating a removal experiment comparing the species' distribution under high and low tree cover. Accounting for tree cover improved model performance, with shade-tolerant species increasing their probability of presence at high tree cover whereas shade-intolerant species showed the opposite pattern. The tree cover effect occurred consistently at both plot and landscape spatial grains, albeit strongest at the former. Importantly, tree cover at the two grain sizes had partially independent effects on plot-scale plant communities, suggesting that the effects may be transmitted to coarser grains through meta-community dynamics. At high tree cover, shade-intolerant species exhibited elevational range contractions, especially at their upper limit, whereas shade-tolerant species showed elevational range expansions at both limits. Our findings suggest that the range shifts for herb and shrub species may be modulated by tree cover dynamics.

How Party Linkages Shape Austerity Politics: Clientelism and Fiscal Adjustment in Greece and Portugal during the Eurozone Crisis

Drawing on an analysis of austerity reforms in Greece and Portugal during the sovereign debt crisis from 2009 onwards, we show how the nature of the linkages between parties and citizens shapes party strategies of fiscal retrenchment. We argue that parties which rely to a greater extent on the selective distribution of state resources to mobilize electoral support (clientelistic linkages) are more reluctant to agree to fiscal retrenchment because their own electoral survival depends on their ability to control state budgets to reward clients. In Greece, where parties relied extensively on these clientelistic linkages, austerity reforms have been characterized by recurring conflicts and disagreements between the main parties, as well as a fundamental transformation of the party system. By contrast, in Portugal, where parties relied less on clientelistic strategies, austerity reforms have been more consensual because fiscal retrenchment challenged to a lesser extent the electoral base of the mainstream parties.

Theoretical background for market emergence framework : Case: Electricity Distribution Industry

Both the competitive environment and the internal structure of an industrial organization are typically included in the processes which describe the strategic management processes of the firm, but less attention has been paid to the interdependence between these views. Therefore, this research focuses on explaining the particular conditions of an industry change, which lead managers to realign the firm in respect of its environment for generating competitive advantage. The research question that directs the development of the theoretical framework is: Why do firms outsource some of their functions? The three general stages of the analysis are related to the following research topics: (i) understanding forces that shape the industry, (ii) estimating the impacts of transforming customer preferences, rivalry, and changing capability bases on the relevance of existing assets and activities, and emergence of new business models, and (iii) developing optional structures for future value chains and understanding general boundaries for market emergence. The defined research setting contributes to the managerial research questions “Why do firms reorganize their value chains?”, “Why and how are decisions made?” Combining Transaction Cost Economics (TCE) and Resource-Based View (RBV) within an integrated framework makes it possible to evaluate the two dimensions of a company’s resources, namely the strategic value and transferability. The final decision of restructuring will be made based on an analysis of the actual business potential of the outsourcing, where benefits and risks are evaluated. The firm focuses on the risk of opportunism, hold-up problems, pricing, and opportunities to reach a complete contract, and finally on the direct benefits and risks for financial performance. The supplier analyzes the business potential of an activity outside the specific customer, the amount of customer-specific investments, the service provider’s competitive position, abilities to revenue gains in generic segments, and long-term dependence on the customer.

Dry biomass distribution in a cerrado sensu stricto site in Brazil central

The Cerrado has been the main source of firewood and charcoal in Brazil, but despite being one of the hot spots for conservation of the world's biodiversity, neither plantations of native species nor sustainable management has been adopted in the region. The aim of this work was to investigate the biomass distribution and the potential for energy production of the cerrado species. The study was conducted in a cerrado sensu stricto site at the Água Limpa Farm (15º 56'14'' S and 47º 46'08'' W) in the Cerrado Biosphere Reserve. An area of 63.54ha was divided in 20 x 50m plots and, a random sample consisting of ten of these plots, representing 1.56% of the study-site, was assessed. All woody individuals from 5 cm diameter at 30 cm above ground level were identified and measured. Each individual was felled, the twigs thinner than 3cm were discarded while the larger branches and the trunks, both with bark, were weighted separately. After that, 2.5cm transverse sections of the trunk with bark were taken at 0, 25, 50, 75 and 100% of the length. A similar sample was also taken at the base of each branch. A total of 47 species in 35 genera and 24 families were found, with an average density of 673 individuals per ha. The diameter distribution showed a reversed-J shape with 67% of the individuals up to 13cm, while the maximum diameter was 32.30cm. Seven species represented 72% of the total biomass. In general, the species with higher production per tree were among those with higher production per ha. This content was distributed by diameter classes, reaching a maximum of 2.5ton/ha between 9 to 13cm and then, decreasing to 0.96 ton/ha between 29 to 33cm diameter. Carbon sequestering was 6.2ton/ha (until the actual stage of cerrado) based on an average 50% carbon content in the dry matter. The heat combustion of the wood varied from 18,903kj/kg to 20,888kj/kg with an average of 19,942kj/kg. The smaller diameter classes fix more carbon due to the large number of small plants per ha. But, for a species that reached larger dimensions and contained individuals in all diameter classes, Vochysia thyrsoidea, one can verify an increase in carbon fixation from 1.41 kg/ha in the first class (5 to 9cm) to 138,3kg/ha in the last (25 to 33cm). That indicates that it is possible to select species that reach larger size with a higher capacity of carbon accumulation per plant. The species that reached larger dimensions, with a production per tree above average and had high calorific power values were Dalbergia miscolobium, Pterodon pubescens and Sclerolobium paniculatum. These species have potential for use in fuelwood plantations and sustainable management.