774 resultados para ecological psychology


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We propose a multivariate approach to the study of geographic species distribution which does not require absence data. Building on Hutchinson's concept of the ecological niche, this factor analysis compares, in the multidimensional space of ecological variables, the distribution of the localities where the focal species was observed to a reference set describing the whole study area. The first factor extracted maximizes the marginality of the focal species, defined as the ecological distance between the species optimum and the mean habitat within the reference area. The other factors maximize the specialization of this focal species, defined as the ratio of the ecological variance in mean habitat to that observed for the focal species. Eigenvectors and eigenvalues are readily interpreted and can be used to build habitat-suitability maps. This approach is recommended in Situations where absence data are not available (many data banks), unreliable (most cryptic or rare species), or meaningless (invaders). We provide an illustration and validation of the method for the alpine ibex, a species reintroduced in Switzerland which presumably has not yet recolonized its entire range.

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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

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The main objective of this study was todo a statistical analysis of ecological type from optical satellite data, using Tipping's sparse Bayesian algorithm. This thesis uses "the Relevence Vector Machine" algorithm in ecological classification betweenforestland and wetland. Further this bi-classification technique was used to do classification of many other different species of trees and produces hierarchical classification of entire subclasses given as a target class. Also, we carried out an attempt to use airborne image of same forest area. Combining it with image analysis, using different image processing operation, we tried to extract good features and later used them to perform classification of forestland and wetland.

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The Goliath grouper, Epinephelus itajara, a large-bodied (similar to 2.5 m TL, > 400 kg) and critically endangered fish (Epinephelidae), is highly Vulnerable to overfishing. Although protected from fishing in many countries, its exploitation in Mexico is unregulated; a situation that puts its populations at risk. Fishery records of E. itajara are scarce, which prevents determination of its fishery status. This work aimed to elucidate the E itajara fishery in the northern Yucatan Peninsula by 1) analyzing available catch records and 2) interviewing veteran fishermen (local ecological knowledge) from two traditional landing sites: Dzilam de Bravo and Puerto Progreso. Historic fishery records from two fishing cooperatives were analyzed in order to elucidate the current situation and offer viable alternatives for conservation and management. Catches have decreased severely. Local knowledge obtained from fishermen represented a very important source of information for reconstructing the fisheries history of this species. Conservation measures that incorporate regional and international regulations on critically endangered fish species are suggested

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Neurological disorders disrupt the equilibrium within the brain and spinal cord ecosystems. Ecology reuses, recycles, and reduces to help maintain the balance across ecosystems. Likewise, neuroprosthetics can help the brain help itself with ecoprosthetic designs that integrate the principles of the "three 'R's."

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River restoration can enhance river dynamics, environmental heterogeneity and biodiversity, but the underlying processes governing the dynamic changes need to be understood to ensure that restoration projects meet their goals, and adverse effects are prevented. In particular, we need to comprehend how hydromorphological variability quantitatively relates to ecosystem functioning and services, biodiversity as well as ground-and surface water quality in restored river corridors. This involves (i) physical processes and structural properties, determining erosion and sedimentation, as well as solute and heat transport behavior in surface water and within the subsurface; (ii) biogeochemical processes and characteristics, including the turnover of nutrients and natural water constituents; and (iii) ecological processes and indicators related to biodiversity and ecological functioning. All these aspects are interlinked, requiring an interdisciplinary investigation approach. Here, we present an overview of the recently completed RECORD (REstored CORridor Dynamics) project in which we combined physical, chemical, and biological observations with modeling at a restored river corridor of the perialpine Thur River in Switzerland. Our results show that river restoration, beyond inducing morphologic changes that reshape the river bed and banks, triggered complex spatial patterns of bank infiltration, and affected habitat type, biotic communities and biogeochemical processes. We adopted an interdisciplinary approach of monitoring the continuing changes due to restoration measures to address the following questions: How stable is the morphological variability established by restoration? Does morphological variability guarantee an improvement in biodiversity? How does morphological variability affect biogeochemical transformations in the river corridor? What are some potential adverse effects of river restoration? How is river restoration influenced by catchment-scale hydraulics [GRAPHICS] and which feedbacks exist on the large scale? Beyond summarizing the major results of individual studies within the project, we show that these overarching questions could only be addressed in an interdisciplinary framework.

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The interplay between selection and aspects of the genetic architecture of traits (such as linkage, dominance, and epistasis) can either drive or constrain speciation [1-3]. Despite accumulating evidence that speciation can progress to "intermediate" stages-with populations evolving only partial reproductive isolation-studies describing selective mechanisms that impose constraints on speciation are more rare than those describing drivers. The stick insect Timema cristinae provides an example of a system in which partial reproductive isolation has evolved between populations adapted to different host plant environments, in part due to divergent selection acting on a pattern polymorphism [4, 5]. Here, we demonstrate how selection on a green/melanistic color polymorphism counteracts speciation in this system. Specifically, divergent selection between hosts does not occur on color phenotypes because melanistic T. cristinae are cryptic on the stems of both host species, are resistant to a fungal pathogen, and have a mating advantage. Using genetic crosses and genome-wide association mapping, we quantify the genetic architecture of both the pattern and color polymorphism, illustrating their simple genetic control. We use these empirical results to develop an individual-based model that shows how the melanistic phenotype acts as a "genetic bridge" that increases gene flow between populations living on different hosts. Our results demonstrate how variation in the nature of selection acting on traits, and aspects of trait genetic architecture, can impose constraints on both local adaptation and speciation.

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Freshwater ecosystems and their biodiversity are presently seriously threatened by global development and population growth, leading to increases in nutrient inputs and intensification of eutrophication-induced problems in receiving fresh waters, particularly in lakes. Climate change constitutes another threat exacerbating the symptoms of eutrophication and species migration and loss. Unequivocal evidence of climate change impacts is still highly fragmented despite the intensive research, in part due to the variety and uncertainty of climate models and underlying emission scenarios but also due to the different approaches applied to study its effects. We first describe the strengths and weaknesses of the multi-faceted approaches that are presently available for elucidating the effects of climate change in lakes, including space-for-time substitution, time series, experiments, palaeoecology and modelling. Reviewing combined results from studies based on the various approaches, we describe the likely effects of climate changes on biological communities, trophic dynamics and the ecological state of lakes. We further discuss potential mitigation and adaptation measures to counteract the effects of climate change on lakes and, finally, we highlight some of the future challenges that we face to improve our capacity for successful prediction.

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Crassulacean acid metabolism (CAM) photosynthesis is an adaptation to water and atmospheric CO2 deficits that has been linked to diversification in dry-adapted plants. We investigated whether CAM evolution can be associated with the availability of new or alternative niches, using Eulophiinae orchids as a case study. Carbon isotope ratios, geographical and climate data, fossil records and DNA sequences were used to: assess the prevalence of CAM in Eulophiinae orchids; characterize the ecological niche of extant taxa; infer divergence times; and estimate whether CAM is associated with niche shifts. CAM evolved in four terrestrial lineages during the late Miocene/Pliocene, which have uneven diversification patterns. These lineages originated in humid habitats and colonized dry/seasonally dry environments in Africa and Madagascar. Additional key features (variegation, heterophylly) evolved in the most species-rich CAM lineages. Dry habitats were also colonized by a lineage that includes putative mycoheterotrophic taxa. These findings indicate that the switch to CAM is associated with environmental change. With its suite of adaptive traits, this group of orchids represents a unique opportunity to study the adaptations to dry environments, especially in the face of projected global aridification.

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The increasing presence of and claim for dialogue in today"s society has already had an impact on the theory and practice of learning. Whereas in the past individual and cognitive elements were seen as crucial to learning, since about two decades ago, scientific literature indicates that culture, interaction and dialogue are the key factors. In addition, the research project of highest scientific rank and with most resources dedicated to the study of school education in the Framework Program of the European Union: INCLUD-ED shows that the practices of successful schools around Europe are in line with the dialogic approach to learning. This article presents the dialogic turn in educational psychology, consisting of moving from symbolic conceptions of mind and internalist perspectives that focus on mental schemata of previous knowledge, to theories that see intersubjectivity and communication as the primary factors in learning. The paper deepens on the second approach.

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BACKGROUND: In the context of the European Surveillance of Congenital Anomalies (EUROCAT) surveillance response to the 2009 influenza pandemic, we sought to establish whether there was a detectable increase of congenital anomaly prevalence among pregnancies exposed to influenza seasons in general, and whether any increase was greater during the 2009 pandemic than during other seasons. METHODS: We performed an ecologic time series analysis based on 26,967 pregnancies with nonchromosomal congenital anomaly conceived from January 2007 to March 2011, reported by 15 EUROCAT registries. Analysis was performed for EUROCAT-defined anomaly subgroups, divided by whether there was a prior hypothesis of association with influenza. Influenza season exposure was based on World Health Organization data. Prevalence rate ratios were calculated comparing pregnancies exposed to influenza season during the congenital anomaly-specific critical period for embryo-fetal development to nonexposed pregnancies. RESULTS: There was no evidence for an increased overall prevalence of congenital anomalies among pregnancies exposed to influenza season. We detected an increased prevalence of ventricular septal defect and tricuspid atresia and stenosis during pandemic influenza season 2009, but not during 2007-2011 influenza seasons. For congenital anomalies, where there was no prior hypothesis, the prevalence of tetralogy of Fallot was strongly reduced during influenza seasons. CONCLUSIONS: Our data do not suggest an overall association of pandemic or seasonal influenza with congenital anomaly prevalence. One interpretation is that apparent influenza effects found in previous individual-based studies were confounded by or interacting with other risk factors. The associations of heart anomalies with pandemic influenza could be strain specific.