Maize yield and rainfall on different spatial and temporal scales in Southern Brazil

This study aimed to establish relationships between maize yield and rainfall on different temporal and spatial scales, in order to provide a basis for crop monitoring and modelling. A 16-year series of maize yield and daily rainfall from 11 municipalities and micro-regions of Rio Grande do Sul State was used. Correlation and regression analyses were used to determine associations between crop yield and rainfall for the entire crop cycle, from tasseling to 30 days after, and from 5 days before tasseling to 40 days after. Close relationships between maize yield and rainfall were found, particularly during the reproductive period (45-day period comprising the flowering and grain filling). Relationships were closer on a regional scale than at smaller scales. Implications of the crop-rainfall relationships for crop modelling are discussed.

Do stacked species distribution models reflect altitudinal diversity patterns?

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.

Spatial visualization of DNA in solution.

An image analysis method is presented which allows for the reconstruction of the three-dimensional path of filamentous objects from two of their projections. Starting with stereo pairs, this method is used to trace the trajectory of DNA molecules embedded in vitreous ice and leads to a faithful representation of their three-dimensional shape in solution. This computer-aided reconstruction is superior to the subjective three-dimensional impression generated by observation of stereo pairs of micrographs because it enables one to look at the reconstructed molecules from any chosen direction and distance and allows quantitative analysis such as determination of distances, curvature, persistence length, and writhe of DNA molecules in solution.

Conservation of the Eurasian Lynx (Lynx lynx) in a fragmented landscape - habitat models, dispersal and potential distribution

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.

Comparison and validation of tissue modelization and statistical classification methods in T1-weighted MR brain images.

This paper presents a validation study on statistical nonsupervised brain tissue classification techniques in magnetic resonance (MR) images. Several image models assuming different hypotheses regarding the intensity distribution model, the spatial model and the number of classes are assessed. The methods are tested on simulated data for which the classification ground truth is known. Different noise and intensity nonuniformities are added to simulate real imaging conditions. No enhancement of the image quality is considered either before or during the classification process. This way, the accuracy of the methods and their robustness against image artifacts are tested. Classification is also performed on real data where a quantitative validation compares the methods' results with an estimated ground truth from manual segmentations by experts. Validity of the various classification methods in the labeling of the image as well as in the tissue volume is estimated with different local and global measures. Results demonstrate that methods relying on both intensity and spatial information are more robust to noise and field inhomogeneities. We also demonstrate that partial volume is not perfectly modeled, even though methods that account for mixture classes outperform methods that only consider pure Gaussian classes. Finally, we show that simulated data results can also be extended to real data.

Effects of sample size on the performance of species distribution models

A wide range of modelling algorithms is used by ecologists, conservation practitioners, and others to predict species ranges from point locality data. Unfortunately, the amount of data available is limited for many taxa and regions, making it essential to quantify the sensitivity of these algorithms to sample size. This is the first study to address this need by rigorously evaluating a broad suite of algorithms with independent presence-absence data from multiple species and regions. We evaluated predictions from 12 algorithms for 46 species (from six different regions of the world) at three sample sizes (100, 30, and 10 records). We used data from natural history collections to run the models, and evaluated the quality of model predictions with area under the receiver operating characteristic curve (AUC). With decreasing sample size, model accuracy decreased and variability increased across species and between models. Novel modelling methods that incorporate both interactions between predictor variables and complex response shapes (i.e. GBM, MARS-INT, BRUTO) performed better than most methods at large sample sizes but not at the smallest sample sizes. Other algorithms were much less sensitive to sample size, including an algorithm based on maximum entropy (MAXENT) that had among the best predictive power across all sample sizes. Relative to other algorithms, a distance metric algorithm (DOMAIN) and a genetic algorithm (OM-GARP) had intermediate performance at the largest sample size and among the best performance at the lowest sample size. No algorithm predicted consistently well with small sample size (n < 30) and this should encourage highly conservative use of predictions based on small sample size and restrict their use to exploratory modelling.

What matters for predicting spatial distributions of trees: techniques, data, or species' characteristics?

Data characteristics and species traits are expected to influence the accuracy with which species' distributions can be modeled and predicted. We compare 10 modeling techniques in terms of predictive power and sensitivity to location error, change in map resolution, and sample size, and assess whether some species traits can explain variation in model performance. We focused on 30 native tree species in Switzerland and used presence-only data to model current distribution, which we evaluated against independent presence-absence data. While there are important differences between the predictive performance of modeling methods, the variance in model performance is greater among species than among techniques. Within the range of data perturbations in this study, some extrinsic parameters of data affect model performance more than others: location error and sample size reduced performance of many techniques, whereas grain had little effect on most techniques. No technique can rescue species that are difficult to predict. The predictive power of species-distribution models can partly be predicted from a series of species characteristics and traits based on growth rate, elevational distribution range, and maximum elevation. Slow-growing species or species with narrow and specialized niches tend to be better modeled. The Swiss presence-only tree data produce models that are reliable enough to be useful in planning and management applications.

The Spatial Effects of Trade Openness: A Survey

This paper surveys the literature on the implications of trade liberalisation for intra-national economic geographies. Three results stand out. First, neither urban systems models nor new economic geography models imply a robust prediction for the impact of trade openness on spatial concentration. Whether trade promotes concentration or dispersion depends on subtle modelling choices among which it is impossible to adjudicate a priori. Second, empirical evidence mirrors the theoretical indeterminacy: a majority of cross-country studies find no significant effect of openness on urban concentration or regional inequality. Third, the available models predict that, other things equal, regions with inherently less costly access to foreign markets, such as border or port regions, stand to reap the largest gains from trade liberalisation. This prediction is confirmed by the available evidence. Whether trade liberalisation raises or lowers regional inequality therefore depends on each country's specific geography.

Spatial prediction of monthly wind speeds in complex terrain with adaptive general regression neural networks

This paper presents the general regression neural networks (GRNN) as a nonlinear regression method for the interpolation of monthly wind speeds in complex Alpine orography. GRNN is trained using data coming from Swiss meteorological networks to learn the statistical relationship between topographic features and wind speed. The terrain convexity, slope and exposure are considered by extracting features from the digital elevation model at different spatial scales using specialised convolution filters. A database of gridded monthly wind speeds is then constructed by applying GRNN in prediction mode during the period 1968-2008. This study demonstrates that using topographic features as inputs in GRNN significantly reduces cross-validation errors with respect to low-dimensional models integrating only geographical coordinates and terrain height for the interpolation of wind speed. The spatial predictability of wind speed is found to be lower in summer than in winter due to more complex and weaker wind-topography relationships. The relevance of these relationships is studied using an adaptive version of the GRNN algorithm which allows to select the useful terrain features by eliminating the noisy ones. This research provides a framework for extending the low-dimensional interpolation models to high-dimensional spaces by integrating additional features accounting for the topographic conditions at multiple spatial scales. Copyright (c) 2012 Royal Meteorological Society.

Effect of spatial processes on the evolution of ecological niches and dispersal in metacommunity systems

RésuméLa coexistence de nombreuses espèces différentes a de tout temps intrigué les biologistes. La diversité et la composition des communautés sont influencées par les perturbations et l'hétérogénéité des conditions environnementales. Bien que dans la nature la distribution spatiale des conditions environnementales soit généralement autocorrélée, cet aspect est rarement pris en compte dans les modèles étudiant la coexistence des espèces. Dans ce travail, nous avons donc abordé, à l'aide de simulations numériques, la coexistence des espèces ainsi que leurs caractéristiques au sein d'un environnement autocorrélé.Afin de prendre en compte cet élément spatial, nous avons développé un modèle de métacommunauté (un ensemble de communautés reliées par la dispersion des espèces) spatialement explicite. Dans ce modèle, les espèces sont en compétition les unes avec les autres pour s'établir dans un nombre de places limité, dans un environnement hétérogène. Les espèces sont caractérisées par six traits: optimum de niche, largeur de niche, capacité de dispersion, compétitivité, investissement dans la reproduction et taux de survie. Nous nous sommes particulièrement intéressés à l'influence de l'autocorrélation spatiale et des perturbations sur la diversité des espèces et sur les traits favorisés dans la métacommunauté. Nous avons montré que l'autocorrélation spatiale peut avoir des effets antagonistes sur la diversité, en fonction du taux de perturbations considéré. L'influence de l'autocorrélation spatiale sur la capacité de dispersion moyenne dans la métacommunauté dépend également des taux de perturbations et survie. Nos résultats ont aussi révélé que de nombreuses espèces avec différents degrés de spécialisation (i.e. différentes largeurs de niche) peuvent coexister. Toutefois, les espèces spécialistes sont favorisées en absence de perturbations et quand la dispersion est illimitée. A l'opposé, un taux élevé de perturbations sélectionne des espèces plus généralistes, associées avec une faible compétitivité.L'autocorrélation spatiale de l'environnement, en interaction avec l'intensité des perturbations, influence donc de manière considérable la coexistence ainsi que les caractéristiques des espèces. Ces caractéristiques sont à leur tour souvent impliquées dans d'importants processus, comme le fonctionnement des écosystèmes, la capacité des espèces à réagir aux invasions, à la fragmentation de l'habitat ou aux changements climatiques. Ce travail a permis une meilleure compréhension des mécanismes responsables de la coexistence et des caractéristiques des espèces, ce qui est crucial afin de prédire le devenir des communautés naturelles dans un environnement changeant.AbstractUnderstanding how so many different species can coexist in nature is a fundamental and long-standing question in ecology. Community diversity and composition are known to be influenced by heterogeneity in environmental conditions and disturbance. Though in nature the spatial distribution of environmental conditions is frequently autocorrelated, this aspect is seldom considered in models investigating species coexistence. In this work, we thus addressed several questions pertaining to species coexistence and composition in spatially autocorrelated environments, with a numerical simulations approach.To take into account this spatial aspect, we developed a spatially explicit model of metacommunity (a set of communities linked by dispersal of species). In this model, species are trophically equivalent, and compete for space in a heterogeneous environment. Species are characterized by six life-history traits: niche optimum, niche breadth, dispersal, competitiveness, reproductive investment and survival rate. We were particularly interested in the influence of environmental spatial autocorrelation and disturbance on species diversity and on the traits of the species favoured in the metacommunity. We showed that spatial autocorrelation can have antagonistic effects on diversity depending on disturbance rate. Similarly, spatial autocorrelation interacted with disturbance rate and survival rate to shape the mean dispersal ability observed in the metacommunity. Our results also revealed that many species with various degrees of specialization (i.e. different niche breadths) can coexist together. However specialist species were favoured in the absence of disturbance, and when dispersal was unlimited. In contrast, high disturbance rate selected for more generalist species, associated with low competitive ability.The spatial structure of the environment, together with disturbance and species traits, thus strongly impacts species diversity and, more importantly, species composition. Species composition is known to affect several important metacommunity properties such as ecosystem functioning, resistance and reaction to invasion, to habitat fragmentation and to climate changes. This work allowed a better understanding of the mechanisms responsible for species composition, which is of crucial importance to predict the fate of natural metacommunities in changing environments

Spatial predictions of land-use transitions and associated threats to biodiversity: the case of forest regrowth in mountain grasslands

Question Can we predict where forest regrowth caused by abandonment of agricultural activities is likely to occur? Can we assess how it may conflict with grassland diversity hotspots? Location Western Swiss Alps (4003210m a.s.l.). Methods We used statistical models to predict the location of land abandonment by farmers that is followed by forest regrowth in semi-natural grasslands of the Western Swiss Alps. Six modelling methods (GAM, GBM, GLM, RF, MDA, MARS) allowing binomial distribution were tested on two successive transitions occurring between three time periods. Models were calibrated using data on land-use change occurring between 1979 and 1992 as response, and environmental, accessibility and socio-economic variables as predictors, and these were validated for their capacity to predict the changes observed from 1992 to 2004. Projected probabilities of land-use change from an ensemble forecast of the six models were combined with a model of plant species richness based on a field inventory, allowing identification of critical grassland areas for the preservation of biodiversity. Results Models calibrated over the first land-use transition period predicted the second transition with reasonable accuracy. Forest regrowth occurs where cultivation costs are high and yield potential is low, i.e. on steeper slopes and at higher elevations. Overlaying species richness with land-use change predictions, we identified priority areas for the management and conservation of biodiversity at intermediate elevations. Conclusions Combining land-use change and biodiversity projections, we propose applied management measures for targeted/identified locations to limit the loss of biodiversity that could otherwise occur through loss of open habitats. The same approach could be applied to other types of land-use changes occurring in other ecosystems.

Semivariogram models for estimating fig fly population density throughout the year

The objective of this work was to select semivariogram models to estimate the population density of fig fly (Zaprionus indianus; Diptera: Drosophilidae) throughout the year, using ordinary kriging. Nineteen monitoring sites were demarcated in an area of 8,200 m2, cropped with six fruit tree species: persimmon, citrus, fig, guava, apple, and peach. During a 24 month period, 106 weekly evaluations were done in these sites. The average number of adult fig flies captured weekly per trap, during each month, was subjected to the circular, spherical, pentaspherical, exponential, Gaussian, rational quadratic, hole effect, K-Bessel, J-Bessel, and stable semivariogram models, using ordinary kriging interpolation. The models with the best fit were selected by cross-validation. Each data set (months) has a particular spatial dependence structure, which makes it necessary to define specific models of semivariograms in order to enhance the adjustment to the experimental semivariogram. Therefore, it was not possible to determine a standard semivariogram model; instead, six theoretical models were selected: circular, Gaussian, hole effect, K-Bessel, J-Bessel, and stable.

Theoretical Analysis and Simulations of Vertically Vibrated Granular Materials

The dynamical properties ofshaken granular materials are important in many industrial applications where the shaking is used to mix, segregate and transport them. In this work asystematic, large scale simulation study has been performed to investigate the rheology of dense granular media, in the presence of gas, in a three dimensional vertical cylinder filled with glass balls. The base wall of the cylinder is subjected to sinusoidal oscillation in the vertical direction. The viscoelastic behavior of glass balls during a collision, have been studied experimentally using a modified Newton's Cradle device. By analyzing the results of the measurements, using numerical model based on finite element method, the viscous damping coefficient was determinedfor the glass balls. To obtain detailed information about the interparticle interactions in a shaker, a simplified model for collision between particles of a granular material was proposed. In order to simulate the flow of surrounding gas, a formulation of the equations for fluid flow in a porous medium including particle forces was proposed. These equations are solved with Large Eddy Simulation (LES) technique using a subgrid-model originally proposed for compressible turbulent flows. For a pentagonal prism-shaped container under vertical vibrations, the results show that oscillon type structures were formed. Oscillons are highly localized particle-like excitations of the granular layer. This self-sustaining state was named by analogy with its closest large-scale analogy, the soliton, which was first documented by J.S. Russell in 1834. The results which has been reportedbyBordbar and Zamankhan(2005b)also show that slightly revised fluctuation-dissipation theorem might apply to shaken sand, which appears to be asystem far from equilibrium and could exhibit strong spatial and temporal variations in quantities such as density and local particle velocity. In this light, hydrodynamic type continuum equations were presented for describing the deformation and flow of dense gas-particle mixtures. The constitutive equation used for the stress tensor provides an effective viscosity with a liquid-like character at low shear rates and a gaseous-like behavior at high shear rates. The numerical solutions were obtained for the aforementioned hydrodynamic equations for predicting the flow dynamics ofdense mixture of gas and particles in vertical cylindrical containers. For a heptagonal prism shaped container under vertical vibrations, the model results were found to predict bubbling behavior analogous to those observed experimentally. This bubbling behavior may be explained by the unusual gas pressure distribution found in the bed. In addition, oscillon type structures were found to be formed using a vertically vibrated, pentagonal prism shaped container in agreement with computer simulation results. These observations suggest that the pressure distribution plays a key rolein deformation and flow of dense mixtures of gas and particles under vertical vibrations. The present models provide greater insight toward the explanation of poorly understood hydrodynamic phenomena in the field of granular flows and dense gas-particle mixtures. The models can be generalized to investigate the granular material-container wall interactions which would be an issue of high interests in the industrial applications. By following this approach ideal processing conditions and powder transport can be created in industrial systems.

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.

Evolutionary Games in Networked Populations: Models and Experiments

Cooperation and coordination are desirable behaviors that are fundamental for the harmonious development of society. People need to rely on cooperation with other individuals in many aspects of everyday life, such as teamwork and economic exchange in anonymous markets. However, cooperation may easily fall prey to exploitation by selfish individuals who only care about short- term gain. For cooperation to evolve, specific conditions and mechanisms are required, such as kinship, direct and indirect reciprocity through repeated interactions, or external interventions such as punishment. In this dissertation we investigate the effect of the network structure of the population on the evolution of cooperation and coordination. We consider several kinds of static and dynamical network topologies, such as Baraba´si-Albert, social network models and spatial networks. We perform numerical simulations and laboratory experiments using the Prisoner's Dilemma and co- ordination games in order to contrast human behavior with theoretical results. We show by numerical simulations that even a moderate amount of random noise on the Baraba´si-Albert scale-free network links causes a significant loss of cooperation, to the point that cooperation almost vanishes altogether in the Prisoner's Dilemma when the noise rate is high enough. Moreover, when we consider fixed social-like networks we find that current models of social networks may allow cooperation to emerge and to be robust at least as much as in scale-free networks. In the framework of spatial networks, we investigate whether cooperation can evolve and be stable when agents move randomly or performing Le´vy flights in a continuous space. We also consider discrete space adopting purposeful mobility and binary birth-death process to dis- cover emergent cooperative patterns. The fundamental result is that cooperation may be enhanced when this migration is opportunistic or even when agents follow very simple heuristics. In the experimental laboratory, we investigate the issue of social coordination between indi- viduals located on networks of contacts. In contrast to simulations, we find that human players dynamics do not converge to the efficient outcome more often in a social-like network than in a random network. In another experiment, we study the behavior of people who play a pure co- ordination game in a spatial environment in which they can move around and when changing convention is costly. We find that each convention forms homogeneous clusters and is adopted by approximately half of the individuals. When we provide them with global information, i.e., the number of subjects currently adopting one of the conventions, global consensus is reached in most, but not all, cases. Our results allow us to extract the heuristics used by the participants and to build a numerical simulation model that agrees very well with the experiments. Our findings have important implications for policymakers intending to promote specific, desired behaviors in a mobile population. Furthermore, we carry out an experiment with human subjects playing the Prisoner's Dilemma game in a diluted grid where people are able to move around. In contrast to previous results on purposeful rewiring in relational networks, we find no noticeable effect of mobility in space on the level of cooperation. Clusters of cooperators form momentarily but in a few rounds they dissolve as cooperators at the boundaries stop tolerating being cheated upon. Our results highlight the difficulties that mobile agents have to establish a cooperative environment in a spatial setting without a device such as reputation or the possibility of retaliation. i.e. punishment. Finally, we test experimentally the evolution of cooperation in social networks taking into ac- count a setting where we allow people to make or break links at their will. In this work we give particular attention to whether information on an individual's actions is freely available to poten- tial partners or not. Studying the role of information is relevant as information on other people's actions is often not available for free: a recruiting firm may need to call a job candidate's refer- ences, a bank may need to find out about the credit history of a new client, etc. We find that people cooperate almost fully when information on their actions is freely available to their potential part- ners. Cooperation is less likely, however, if people have to pay about half of what they gain from cooperating with a cooperator. Cooperation declines even further if people have to pay a cost that is almost equivalent to the gain from cooperating with a cooperator. Thus, costly information on potential neighbors' actions can undermine the incentive to cooperate in dynamical networks.