180 resultados para Environmental disturbance


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The distribution range of Lactuca serriola, a species native to the summer-dry mediterranean climate, has expanded northwards during the last 250 years. This paper assesses the influence of climate on the range expansion of this species and highlights the importance of anthropogenic disturbance to its spread. Location Central and Northern Europe. Methods Data on the geographic distribution of L. serriola were assembled through a literature search as well as through floristic and herbarium surveys. Maps of the spread of L. serriola in Central and Northern Europe were prepared based on herbarium data. The spread was assessed more precisely in Germany, Austria and Great Britain by pooling herbarium and literature data. We modelled the bioclimatic niche of the species using occurrence and climatic data covering the last century to generate projections of suitable habitats under the climatic conditions of five time periods. We tested whether the observed distribution of L. serriola could be explained for each time period, assuming that the climatic niche of the species was conserved across time. Results The species has spread northwards since the beginning of the 19th century. We show that climate warming in Europe increased the number of sites suitable for the species at northern latitudes. Until the late 1970s, the distribution of the species corresponded to the climatically suitable sites available. For the last two decades, however, we could not show any significant relationship between the increase in suitable sites and the distributional range change of L. serriola. However, we highlight potential areas the species could spread to in the future (Great Britain, southern Scandinavia and the Swedish coast). It is predominantly non-climatic influences of global change that have contributed to its rapid spread. Main conclusions The observation that colonizing species are not filling their climatically suitable range might imply that, potentially, other ruderal species could expand far beyond their current range. Our work highlights the importance of historical floristic and herbarium data for understanding the expansion of a species. Such historical distributional data can provide valuable information for those planning the management of contemporary environmental problems, such as species responses to environmental change.

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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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Disentangling the mechanisms mediating the coexistence of habitat specialists and generalists has been a long-standing subject of investigation. However, the roles of species traits and environmental and spatial factors have not been assessed in a unifying theoretical framework. Theory suggests that specialist species are more competitive in natural communities. However, empirical work has shown that specialist species are declining worldwide due to habitat loss and fragmentation. We addressed the question of the coexistence of specialist and generalist species with a spatially explicit metacommunity model in continuous and heterogeneous environments. We characterized how species' dispersal abilities, the number of interacting species, environmental spatial autocorrelation, and disturbance impact community composition. Our results demonstrated that species' dispersal ability and the number of interacting species had a drastic influence on the composition of metacommunities. More specialized species coexisted when species had large dispersal abilities and when the number of interacting species was high. Disturbance selected against highly specialized species, whereas environmental spatial autocorrelation had a marginal impact. Interestingly, species richness and niche breadth were mainly positively correlated at the community scale but were negatively correlated at the metacommunity scale. Numerous diversely specialized species can thus coexist, but both species' intrinsic traits and environmental factors interact to shape the specialization signatures of communities at both the local and global scales.

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Several models have been proposed to understand how so many species can coexist in ecosystems. Despite evidence showing that natural habitats are often patchy and fragmented, these models rarely take into account environmental spatial structure. In this study we investigated the influence of spatial structure in habitat and disturbance regime upon species' traits and species' coexistence in a metacommunity. We used a population-based model to simulate competing species in spatially explicit landscapes. The species traits we focused on were dispersal ability, competitiveness, reproductive investment and survival rate. Communities were characterized by their species richness and by the four life-history traits averaged over all the surviving species. Our results show that spatial structure and disturbance have a strong influence on the equilibrium life-history traits within a metacommunity. In the absence of disturbance, spatially structured landscapes favour species investing more in reproduction, but less in dispersal and survival. However, this influence is strongly dependent on the disturbance rate, pointing to an important interaction between spatial structure and disturbance. This interaction also plays a role in species coexistence. While spatial structure tends to reduce diversity in the absence of disturbance, the tendency is reversed when disturbance occurs. In conclusion, the spatial structure of communities is an important determinant of their diversity and characteristic traits. These traits are likely to influence important ecological properties such as resistance to invasion or response to climate change, which in turn will determine the fate of ecosystems facing the current global ecological crisis.

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A burn patient was infected with Acinetobacter baumannii on transfer to the hospital after a terrorist attack. Two patients experienced cross-infection. Environmental swab samples were negative for A. baumannii. Six months later, the bacteria reemerged in 6 patients. Environmental swab samples obtained at this time were inoculated into a minimal mineral broth, and culture results showed widespread contamination. No case of infection occurred after closure of the unit for disinfection.

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This paper reviews the literature on clinical signs such as imitation behavior, grasp reaction, manipulation of tools, utilization behavior, environmental dependency, hyperlexia, hypergraphia and echolalia. Some aspects of this semiology are of special interest because they refer to essential notions such as free-will and autonomy.

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Aim:  Determine the frequency and predictors of sleep disorders in boys with Duchenne Muscular Dystrophy (DMD). Method:  Cross-sectional study by postal questionnaire. Sleep disturbances were assessed using the Sleep Disturbance Scale for Children (validated on 1157 healthy children). A total sleep score and six sleep disturbance factors representing the most common sleep disorders were computed. Potential associations between pathological scores and personal, medical and environmental factors were assessed. Results:  Sixteen of 63 boys (25.4%) had a pathological total sleep score compared with 3% in the general population. The most prevalent sleep disorders were disorders of initiating and maintaining sleep (DIMS) 29.7%, sleep-related breathing disorders 15.6% and sleep hyperhydrosis 14.3%. On multivariate analysis, pathological total sleep scores were associated with the need to be moved by a carer (OR = 9.4; 95%CI: 2.2-40.7; p = 0.003) and being the child of a single-parent family (OR = 7.2; 95%CI: 1.5-35.1; p = 0.015) and DIMS with the need to be moved by a carer (OR = 18.0; 95%CI: 2.9-110.6; p = 0.002), steroid treatment (OR = 7.7; 95%CI: 1.4-44.0; p = 0.021) and being the child of a single-parent family (OR = 7.0; 95%CI: 1.3-38.4; p = 0.025). Conclusion:  Sleep disturbances are frequent in boys with DMD and are strongly associated with immobility. Sleep should be systematically assessed in DMD to implement appropriate interventions.

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The aim of the present study was to assess the influence of local environmental olfactory cues on place learning in rats. We developed a new experimental design allowing the comparison of the use of local olfactory and visual cues in spatial and discrimination learning. We compared the effect of both types of cues on the discrimination of a single food source in an open-field arena. The goal was either in a fixed or in a variable location, and could be indicated by local olfactory and/or visual cues. The local cues enhanced the discrimination of the goal dish, whether it was in a fixed or in a variable location. However, we did not observe any overshadowing of the spatial information by the local olfactory or visual cue. Rats relied primarily on distant visuospatial information to locate the goal, neglecting local information when it was in conflict with the spatial information.

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Humans can recognize categories of environmental sounds, including vocalizations produced by humans and animals and the sounds of man-made objects. Most neuroimaging investigations of environmental sound discrimination have studied subjects while consciously perceiving and often explicitly recognizing the stimuli. Consequently, it remains unclear to what extent auditory object processing occurs independently of task demands and consciousness. Studies in animal models have shown that environmental sound discrimination at a neural level persists even in anesthetized preparations, whereas data from anesthetized humans has thus far provided null results. Here, we studied comatose patients as a model of environmental sound discrimination capacities during unconsciousness. We included 19 comatose patients treated with therapeutic hypothermia (TH) during the first 2 days of coma, while recording nineteen-channel electroencephalography (EEG). At the level of each individual patient, we applied a decoding algorithm to quantify the differential EEG responses to human vs. animal vocalizations as well as to sounds of living vocalizations vs. man-made objects. Discrimination between vocalization types was accurate in 11 patients and discrimination between sounds from living and man-made sources in 10 patients. At the group level, the results were significant only for the comparison between vocalization types. These results lay the groundwork for disentangling truly preferential activations in response to auditory categories, and the contribution of awareness to auditory category discrimination.

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This book combines geostatistics and global mapping systems to present an up-to-the-minute study of environmental data. Featuring numerous case studies, the reference covers model dependent (geostatistics) and data driven (machine learning algorithms) analysis techniques such as risk mapping, conditional stochastic simulations, descriptions of spatial uncertainty and variability, artificial neural networks (ANN) for spatial data, Bayesian maximum entropy (BME), and more.