229 resultados para Environmental cooperation


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Environmental chemicals with estrogenic activities have been suggested to be associated with deleterious effects in animals and humans. To characterize estrogenic chemicals and their mechanisms of action, we established in vitro and cell culture assays that detect human estrogen receptor [alpha] (hER[alpha])-mediated estrogenicity. First, we assayed chemicals to determine their ability to modulate direct interaction between the hER[alpha] and the steroid receptor coactivator-1 (SRC-1) and in a competition binding assay to displace 17ss-estradiol (E(2)). Second, we tested the chemicals for estrogen-associated transcriptional activity in the yeast estrogen screen and in the estrogen-responsive MCF-7 human breast cancer cell line. The chemicals investigated in this study were o,p'-DDT (racemic mixture and enantiomers), nonylphenol mixture (NPm), and two poorly analyzed compounds in the environment, namely, tris-4-(chlorophenyl)methane (Tris-H) and tris-4-(chlorophenyl)methanol (Tris-OH). In both yeast and MCF-7 cells, we determined estrogenic activity via the estrogen receptor (ER) for o,p'-DDT, NPm, and for the very first time, Tris-H and Tris-OH. However, unlike estrogens, none of these xenobiotics seemed to be able to induce ER/SRC-1 interactions, most likely because the conformation of the activated receptor would not allow direct contacts with this coactivator. However, these compounds were able to inhibit [(3)H]-E(2) binding to hER, which reveals a direct interaction with the receptor. In conclusion, the test compounds are estrogen mimics, but their molecular mechanism of action appears to be different from that of the natural hormone as revealed by the receptor/coactivator interaction analysis.

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A procedure was developed for determining 241Pu activity in environmental samples. This beta emitter isotope of plutonium was measured by ultra low level liquid scintillation, after several separation and purification steps that involved the use of a highly selective extraction chromatographic resin (Eichrom-TEVA). Due to the lack of reference material for 241Pu, the method was nevertheless validated using four IAEA reference sediments with information values for 241Pu. Next, the method was used to determine the 241Pu activity in alpine soils of Switzerland and France. The 241Pu/239,240Pu and 238Pu/239,240Pu activity ratios confirmed that Pu contamination in the tested alpine soils originated mainly from global fallout from nuclear weapon tests conducted in the fifties and sixties. Estimation of the date of the contamination, using the 241Pu/241Am age-dating method, further confirmed this origin. However, the 241Pu/241Am dating method was limited to samples where Pu-Am fractionation was insignificant. If any, the contribution of the Chernobyl accident is negligible.

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The rate of environmental niche evolution describes the capability of species to explore the available environmental space and is known to vary among species owing to lineage-specific factors. Trophic specialization is a main force driving species evolution and is responsible for classical examples of adaptive radiations in fishes. We investigate the effect of trophic specialization on the rate of environmental niche evolution in the damselfish, Pomacentridae, which is an important family of tropical reef fishes. First, phylogenetic niche conservatism is not detected in the family using a standard test of phylogenetic signal, and we demonstrate that the environmental niches of damselfishes that differ in trophic specialization are not equivalent while they still overlap at their mean values. Second, we estimate the relative rates of niche evolution on the phylogenetic tree and show the heterogeneity among rates of environmental niche evolution of the three trophic groups. We suggest that behavioural characteristics related to trophic specialization can constrain the evolution of the environmental niche and lead to conserved niches in specialist lineages. Our results show the extent of influence of several traits on the evolution of the environmental niche and shed new light on the evolution of damselfishes, which is a key lineage in current efforts to conserve biodiversity in coral reefs.

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Cooperation among unrelated individuals can arise if decisions to help others can be based on reputation. While working for dyadic interactions, reputation-use in social dilemmas involving many individuals (e.g. public goods games) becomes increasingly difficult as groups become larger and errors more frequent. Reputation is therefore believed to have played a minor role for the evolution of cooperation in collective action dilemmas such as those faced by early humans. Here, we show in computer simulations that a reputation system based on punitive actions can overcome these problems and, compared to reputation system based on generous actions, (i) is more likely to lead to the evolution of cooperation in sizable groups, (ii) more effectively sustains cooperation within larger groups, and (iii) is more robust to errors in reputation assessment. Punishment and punishment reputation could therefore have played crucial roles in the evolution of cooperation within larger groups of humans.

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Abstract The object of game theory lies in the analysis of situations where different social actors have conflicting requirements and where their individual decisions will all influence the global outcome. In this framework, several games have been invented to capture the essence of various dilemmas encountered in many common important socio-economic situations. Even though these games often succeed in helping us understand human or animal behavior in interactive settings, some experiments have shown that people tend to cooperate with each other in situations for which classical game theory strongly recommends them to do the exact opposite. Several mechanisms have been invoked to try to explain the emergence of this unexpected cooperative attitude. Among them, repeated interaction, reputation, and belonging to a recognizable group have often been mentioned. However, the work of Nowak and May (1992) showed that the simple fact of arranging the players according to a spatial structure and only allowing them to interact with their immediate neighbors is sufficient to sustain a certain amount of cooperation even when the game is played anonymously and without repetition. Nowak and May's study and much of the following work was based on regular structures such as two-dimensional grids. Axelrod et al. (2002) showed that by randomizing the choice of neighbors, i.e. by actually giving up a strictly local geographical structure, cooperation can still emerge, provided that the interaction patterns remain stable in time. This is a first step towards a social network structure. However, following pioneering work by sociologists in the sixties such as that of Milgram (1967), in the last few years it has become apparent that many social and biological interaction networks, and even some technological networks, have particular, and partly unexpected, properties that set them apart from regular or random graphs. Among other things, they usually display broad degree distributions, and show small-world topological structure. Roughly speaking, a small-world graph is a network where any individual is relatively close, in terms of social ties, to any other individual, a property also found in random graphs but not in regular lattices. However, in contrast with random graphs, small-world networks also have a certain amount of local structure, as measured, for instance, by a quantity called the clustering coefficient. In the same vein, many real conflicting situations in economy and sociology are not well described neither by a fixed geographical position of the individuals in a regular lattice, nor by a random graph. Furthermore, it is a known fact that network structure can highly influence dynamical phenomena such as the way diseases spread across a population and ideas or information get transmitted. Therefore, in the last decade, research attention has naturally shifted from random and regular graphs towards better models of social interaction structures. The primary goal of this work is to discover whether or not the underlying graph structure of real social networks could give explanations as to why one finds higher levels of cooperation in populations of human beings or animals than what is prescribed by classical game theory. To meet this objective, I start by thoroughly studying a real scientific coauthorship network and showing how it differs from biological or technological networks using divers statistical measurements. Furthermore, I extract and describe its community structure taking into account the intensity of a collaboration. Finally, I investigate the temporal evolution of the network, from its inception to its state at the time of the study in 2006, suggesting also an effective view of it as opposed to a historical one. Thereafter, I combine evolutionary game theory with several network models along with the studied coauthorship network in order to highlight which specific network properties foster cooperation and shed some light on the various mechanisms responsible for the maintenance of this same cooperation. I point out the fact that, to resist defection, cooperators take advantage, whenever possible, of the degree-heterogeneity of social networks and their underlying community structure. Finally, I show that cooperation level and stability depend not only on the game played, but also on the evolutionary dynamic rules used and the individual payoff calculations. Synopsis Le but de la théorie des jeux réside dans l'analyse de situations dans lesquelles différents acteurs sociaux, avec des objectifs souvent conflictuels, doivent individuellement prendre des décisions qui influenceront toutes le résultat global. Dans ce cadre, plusieurs jeux ont été inventés afin de saisir l'essence de divers dilemmes rencontrés dans d'importantes situations socio-économiques. Bien que ces jeux nous permettent souvent de comprendre le comportement d'êtres humains ou d'animaux en interactions, des expériences ont montré que les individus ont parfois tendance à coopérer dans des situations pour lesquelles la théorie classique des jeux prescrit de faire le contraire. Plusieurs mécanismes ont été invoqués pour tenter d'expliquer l'émergence de ce comportement coopératif inattendu. Parmi ceux-ci, la répétition des interactions, la réputation ou encore l'appartenance à des groupes reconnaissables ont souvent été mentionnés. Toutefois, les travaux de Nowak et May (1992) ont montré que le simple fait de disposer les joueurs selon une structure spatiale en leur permettant d'interagir uniquement avec leurs voisins directs est suffisant pour maintenir un certain niveau de coopération même si le jeu est joué de manière anonyme et sans répétitions. L'étude de Nowak et May, ainsi qu'un nombre substantiel de travaux qui ont suivi, étaient basés sur des structures régulières telles que des grilles à deux dimensions. Axelrod et al. (2002) ont montré qu'en randomisant le choix des voisins, i.e. en abandonnant une localisation géographique stricte, la coopération peut malgré tout émerger, pour autant que les schémas d'interactions restent stables au cours du temps. Ceci est un premier pas en direction d'une structure de réseau social. Toutefois, suite aux travaux précurseurs de sociologues des années soixante, tels que ceux de Milgram (1967), il est devenu clair ces dernières années qu'une grande partie des réseaux d'interactions sociaux et biologiques, et même quelques réseaux technologiques, possèdent des propriétés particulières, et partiellement inattendues, qui les distinguent de graphes réguliers ou aléatoires. Entre autres, ils affichent en général une distribution du degré relativement large ainsi qu'une structure de "petit-monde". Grossièrement parlant, un graphe "petit-monde" est un réseau où tout individu se trouve relativement près de tout autre individu en termes de distance sociale, une propriété également présente dans les graphes aléatoires mais absente des grilles régulières. Par contre, les réseaux "petit-monde" ont, contrairement aux graphes aléatoires, une certaine structure de localité, mesurée par exemple par une quantité appelée le "coefficient de clustering". Dans le même esprit, plusieurs situations réelles de conflit en économie et sociologie ne sont pas bien décrites ni par des positions géographiquement fixes des individus en grilles régulières, ni par des graphes aléatoires. De plus, il est bien connu que la structure même d'un réseau peut passablement influencer des phénomènes dynamiques tels que la manière qu'a une maladie de se répandre à travers une population, ou encore la façon dont des idées ou une information s'y propagent. Ainsi, durant cette dernière décennie, l'attention de la recherche s'est tout naturellement déplacée des graphes aléatoires et réguliers vers de meilleurs modèles de structure d'interactions sociales. L'objectif principal de ce travail est de découvrir si la structure sous-jacente de graphe de vrais réseaux sociaux peut fournir des explications quant aux raisons pour lesquelles on trouve, chez certains groupes d'êtres humains ou d'animaux, des niveaux de coopération supérieurs à ce qui est prescrit par la théorie classique des jeux. Dans l'optique d'atteindre ce but, je commence par étudier un véritable réseau de collaborations scientifiques et, en utilisant diverses mesures statistiques, je mets en évidence la manière dont il diffère de réseaux biologiques ou technologiques. De plus, j'extrais et je décris sa structure de communautés en tenant compte de l'intensité d'une collaboration. Finalement, j'examine l'évolution temporelle du réseau depuis son origine jusqu'à son état en 2006, date à laquelle l'étude a été effectuée, en suggérant également une vue effective du réseau par opposition à une vue historique. Par la suite, je combine la théorie évolutionnaire des jeux avec des réseaux comprenant plusieurs modèles et le réseau de collaboration susmentionné, afin de déterminer les propriétés structurelles utiles à la promotion de la coopération et les mécanismes responsables du maintien de celle-ci. Je mets en évidence le fait que, pour ne pas succomber à la défection, les coopérateurs exploitent dans la mesure du possible l'hétérogénéité des réseaux sociaux en termes de degré ainsi que la structure de communautés sous-jacente de ces mêmes réseaux. Finalement, je montre que le niveau de coopération et sa stabilité dépendent non seulement du jeu joué, mais aussi des règles de la dynamique évolutionnaire utilisées et du calcul du bénéfice d'un individu.

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Host-pathogen interactions are a major evolutionary force promoting local adaptation. Genes of the major histocompatibility complex (MHC) represent unique candidates to investigate evolutionary processes driving local adaptation to parasite communities. The present study aimed at identifying the relative roles of neutral and adaptive processes driving the evolution of MHC class IIB (MHCIIB) genes in natural populations of European minnows (Phoxinus phoxinus). To this end, we isolated and genotyped exon 2 of two MHCIIB gene duplicates (DAB1 and DAB3) and 1665 amplified fragment length polymorphism (AFLP) markers in nine populations, and characterized local bacterial communities by 16S rDNA barcoding using 454 amplicon sequencing. Both MHCIIB loci exhibited signs of historical balancing selection. Whereas genetic differentiation exceeded that of neutral markers at both loci, the populations' genetic diversities were positively correlated with local pathogen diversities only at DAB3. Overall, our results suggest pathogen-mediated local adaptation in European minnows at both MHCIIB loci. While at DAB1 selection appears to favor different alleles among populations, this is only partially the case in DAB3, which appears to be locally adapted to pathogen communities in terms of genetic diversity. These results provide new insights into the importance of host-pathogen interactions in driving local adaptation in the European minnow, and highlight that the importance of adaptive processes driving MHCIIB gene evolution may differ among duplicates within species, presumably as a consequence of alternative selective regimes or different genomic context.

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By the end of the 1970s, contaminated sites had emerged as one of the most complex and urgent environmental issues affecting industrialized countries. The authors show that small and prosperous Switzerland is no exception to the pervasive problem of sites contamination, the legacy of past practices in waste management having left some 38,000 contaminated sites throughout the country. This book outlines the problem, offering evidence that open and polycentric environmental decision-making that includes civil society actors is valuable. They propose an understanding of environmental management of contaminated sites as a political process in which institutions frame interactions between strategic actors pursuing sometimes conflicting interests. In the opening chapter, the authors describe the influences of politics and the power relationships between actors involved in decision-making in contaminated sites management, which they term a "wicked problem." Chapter Two offers a theoretical framework for understanding institutions and the environmental management of contaminated sites. The next five chapters present a detailed case study on environmental management and contaminated sites in Switzerland, focused on the Bonfol Chemical Landfill. The study and analysis covers the establishment of the landfill under the first generation of environmental regulations, its closure and early remediation efforts, and the gambling on the remediation objectives, methods and funding in the first decade of the 21st Century. The concluding chapter discusses the question of whether the strength of environmental regulations, and the type of interactions between public, private, and civil society actors can explain the environmental choices in contaminated sites management. Drawing lessons from research, the authors debate the value of institutional flexibility for dealing with environmental issues such as contaminated sites.

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Interspecific competition, life history traits, environmental heterogeneity and spatial structure as well as disturbance are known to impact the successful dispersal strategies in metacommunities. However, studies on the direction of impact of those factors on dispersal have yielded contradictory results and often considered only few competing dispersal strategies at the same time. We used a unifying modeling approach to contrast the combined effects of species traits (adult survival, specialization), environmental heterogeneity and structure (spatial autocorrelation, habitat availability) and disturbance on the selected, maintained and coexisting dispersal strategies in heterogeneous metacommunities. Using a negative exponential dispersal kernel, we allowed for variation of both species dispersal distance and dispersal rate. We showed that strong disturbance promotes species with high dispersal abilities, while low local adult survival and habitat availability select against them. Spatial autocorrelation favors species with higher dispersal ability when adult survival and disturbance rate are low, and selects against them in the opposite situation. Interestingly, several dispersal strategies coexist when disturbance and adult survival act in opposition, as for example when strong disturbance regime favors species with high dispersal abilities while low adult survival selects species with low dispersal. Our results unify apparently contradictory previous results and demonstrate that spatial structure, disturbance and adult survival determine the success and diversity of coexisting dispersal strategies in competing metacommunities.

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In cooperative multiagent systems, agents interac to solve tasks. Global dynamics of multiagent teams result from local agent interactions, and are complex and difficult to predict. Evolutionary computation has proven a promising approach to the design of such teams. The majority of current studies use teams composed of agents with identical control rules ("geneti- cally homogeneous teams") and select behavior at the team level ("team-level selection"). Here we extend current approaches to include four combinations of genetic team composition and level of selection. We compare the performance of genetically homo- geneous teams evolved with individual-level selection, genetically homogeneous teams evolved with team-level selection, genetically heterogeneous teams evolved with individual-level selection, and genetically heterogeneous teams evolved with team-level selection. We use a simulated foraging task to show that the optimal combination depends on the amount of cooperation required by the task. Accordingly, we distinguish between three types of cooperative tasks and suggest guidelines for the optimal choice of genetic team composition and level of selection

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Flow cytometry (FCM) is emerging as an important tool in environmental microbiology. Although flow cytometry applications have to date largely been restricted to certain specialized fields of microbiology, such as the bacterial cell cycle and marine phytoplankton communities, technical advances in instrumentation and methodology are leading to its increased popularity and extending its range of applications. Here we will focus on a number of recent flow cytometry developments important for addressing questions in environmental microbiology. These include (i) the study of microbial physiology under environmentally relevant conditions, (ii) new methods to identify active microbial populations and to isolate previously uncultured microorganisms, and (iii) the development of high-throughput autofluorescence bioreporter assays

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ABSTRACT The purpose of this research is to clarify the contribution of international dispute adjudication mechanisms in regard to environmental protection. Most specifically, the study aims to identify and develop the criterion adopted by the international judge in relation to the compensation for environmental damages. In this perspective, the study identifies some gaps between international responsibility and environmental protection interests. The premise sustained all along the study is that compensation is determinant to conciliate environmental prerogatives with mechanisms of international adjudication, in particular the system of international responsibility. Supported by the analysis of treaties, international decisions and secondary sources, the thesis defends the idea that some elements of international law allow the adjudicator to adapt the compensation to attend certain environmental interests, creating a new approach which was entitled 'fair compensation'. The antithesis of this approach is the idea that compensation in international law is limited exclusively to the strict reparation of the material losses incurred by the victim. As a synthesis, the study defends the specificity of environmental damages in relation to other kind of damages that are subject to compensation under international law. The measure upon which compensation for environmental damages could be classified as a specific type of damage under international law remains to be determined. The main conclusion of the study is that the existing standard of compensation defined by the theory and practice of international law is impossible to be strictly respected in cases involving environmental damages. This limitation is mainly due to the complexity of the notion of environment, which is constantly conflicting with the anthropologic view of legal theory. The study supports the idea that the establishment of a 'fair compensation' which takes into account the political, legal and technical context of the environmental damage, is the best possible approach to conciliate internationally responsibility and environmental interests. This could be implemented by the observance of certain elements by the international judge/arbitrator through a case-by-case analysis.

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Recent evidence supports and reinforces the concept that environmental cues may reprogramme somatic cells and change their natural fate. In the present review, we concentrate on environmental reprogramming and fate potency of different epithelial cells. These include stratified epithelia, such as the epidermis, hair follicle, cornea and oesophagus, as well as the thymic epithelium, which stands alone among simple and stratified epithelia, and has been shown recently to contain stem cells. In addition, we briefly discuss the pancreas as an example of plasticity of intrinsic progenitors and even differentiated cells. Of relevance, examples of plasticity and fate change characterize pathologies such as oesophageal metaplasia, whose possible cell origin is still debated, but has important implications as a pre-neoplastic event. Although much work remains to be done in order to unravel the full potential and plasticity of epithelial cells, exploitation of this phenomenon has already entered the clinical arena, and might provide new avenues for future cell therapy of these tissues.

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Recently, kernel-based Machine Learning methods have gained great popularity in many data analysis and data mining fields: pattern recognition, biocomputing, speech and vision, engineering, remote sensing etc. The paper describes the use of kernel methods to approach the processing of large datasets from environmental monitoring networks. Several typical problems of the environmental sciences and their solutions provided by kernel-based methods are considered: classification of categorical data (soil type classification), mapping of environmental and pollution continuous information (pollution of soil by radionuclides), mapping with auxiliary information (climatic data from Aral Sea region). The promising developments, such as automatic emergency hot spot detection and monitoring network optimization are discussed as well.