194 resultados para ECOLOGICAL NETWORKS
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The distribution of living organisms, habitats and ecosystems is primarily driven by abiotic environmental factors that are spatially structured. Assessing the spatial structure of environmental factors, e.g., through spatial autocorrelation analyses (SAC), can thus help us understand their scale of influence on the distribution of organisms, habitats, and ecosystems. Yet SAC analyses of environmental factors are still rarely performed in biogeographic studies. Here, we describe a novel framework that combines SAC and statistical clustering to identify scales of spatial patterning of environmental factors, which can then be interpreted as the scales at which those factors influence the geographic distribution of biological and ecological features. We illustrate this new framework with datasets at different spatial or thematic resolutions. This framework is conceptually and statistically robust, providing a valuable approach to tackle a wide range of issues in ecological and environmental research and particularly when building predictors for ecological models. The new framework can significantly promote fundamental research on all spatially-structured ecological patterns. It can also foster research and application in such fields as global change ecology, conservation planning, and landscape management.
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MOTIVATION: Understanding gene regulation in biological processes and modeling the robustness of underlying regulatory networks is an important problem that is currently being addressed by computational systems biologists. Lately, there has been a renewed interest in Boolean modeling techniques for gene regulatory networks (GRNs). However, due to their deterministic nature, it is often difficult to identify whether these modeling approaches are robust to the addition of stochastic noise that is widespread in gene regulatory processes. Stochasticity in Boolean models of GRNs has been addressed relatively sparingly in the past, mainly by flipping the expression of genes between different expression levels with a predefined probability. This stochasticity in nodes (SIN) model leads to over representation of noise in GRNs and hence non-correspondence with biological observations. RESULTS: In this article, we introduce the stochasticity in functions (SIF) model for simulating stochasticity in Boolean models of GRNs. By providing biological motivation behind the use of the SIF model and applying it to the T-helper and T-cell activation networks, we show that the SIF model provides more biologically robust results than the existing SIN model of stochasticity in GRNs. AVAILABILITY: Algorithms are made available under our Boolean modeling toolbox, GenYsis. The software binaries can be downloaded from http://si2.epfl.ch/ approximately garg/genysis.html.
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The actual geographic distribution of the two sibling mouse-eared bat species Myotis myotis and Myotis blythii, which occur widely sympatrically in the western Palaearctic region, remains largely controversial. This concerns particularly the specific attribution of marginal populations from the Mediterranean islands and from adjacent areas of North Africa and Asia, which are morphologically intermediate between continental M. myotis and M. blythii from Europe. This study attempts to clarify this question by using four different approaches: cranial morphology, external morphology, genetics and trophic ecology. The three latter methods show unambiguously that North Africa, Malta, Sardinia and Corsica are presently inhabited by monospecific populations of M. myotis. In contrast, cranial morphometrics do not yield conclusive results. These results contradict all recent studies, which attribute North African and Maltese mouse-eared bats to M. blythii and consider that Sardinia and Corsica harbour sympatric populations of the two species. As concerns south-eastern populations, doubts are also expressed about the attribution of the subspecific taxon omari which may actually refer to M. myotis instead of M. blythii. Protein electrophoresis is presently the only absolute method available for determining M. myotis and M. blythii throughout their distribution ranges. However, species identification may be approached by relying on less sophisticated morphometrical methods as presented in this study. Species-specific habitat specializations are probably responsible for the differences observed between the geographic distributions of M. myotis and M. blythii, as they provide a logical groundwork for a coherent model of speciation for these two bat species.
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Background: One characteristic of post traumatic stress disorder is an inability to adapt to a safe environment i.e. to change behavior when predictions of adverse outcomes are not met. Recent studies have also indicated that PTSD patients have altered pain processing, with hyperactivation of the putamen and insula to aversive stimuli (Geuze et al, 2007). The present study examined neuronal responses to aversive and predicted aversive events. Methods: Twenty-four trauma exposed non-PTSD controls and nineteen subjects with PTSD underwent fMRI imaging during a partial reinforcement fear conditioning paradigm, with a mild electric shock as the unconditioned stimuli (UCS). Three conditions were analyzed: actual presentations of the UCS, events when a UCS was expected, but omitted (CS+), and events when the UCS was neither expected nor delivered (CS-). Results: The UCS evoked significant alterations in the pain matrix consisting of the brainstem, the midbrain, the thalamus, the insula, the anterior and middle cingulate and the contralateral somatosensory cortex. PTSD subjects displayed bilaterally elevated putamen activity to the electric shock, as compared to controls. In trials when USC was expected, but omitted, significant activations were observed in the brainstem, the midbrain, the anterior insula and the anterior cingulate. PTSD subjects displayed similar activations, but also elevated activations in the amygdala and the posterior insula. Conclusions: These results indicate altered fear and safety learning in PTSD, and neuronal activations are further explored in terms of functional connectivity using psychophysiological interaction analyses.
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Notre consommation ne cesse d'augmenter et la planète est exsangue. Confier notre salut au progrès technologique et à l'économie relève de l'illusion.
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Mountain regions and UNESCO Mountain Biosphere Reserves (MBRs) encapsulate broad elevational ranges, cover large gradients of geological, topographical and climatic diversity, and thus host greater biodiversity than the surrounding lowlands. Much of the biological richness in MBRs results from the interaction of climatic contrasts and gravitational forces along elevational gradients. External forces such as atmospheric change and human land use interact with these gradients, and result in distinct landscape patchiness, ie mosaics of land cover types within and across elevational belts. The management of MBRs influences land use and land cover, which affects biodiversity and ecosystem processes, both of which provide goods and services to society. Due to their broad environmental and biological diversity, MBRs are ideally suited for global change research and will be increasingly important in illustrating biodiversity conservation. This article summarizes the ecologically relevant results of an international workshop on elevational gradients that aimed to achieve a synthesis of the major ecosystem and biodiversity conditions and drivers in an altitude context. The workshop developed a core research agenda for MBRs that prioritizes long-term research and changes in land use across a broad elevational range.
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The European genus Ophrys (Orchidaceae) is famous for its insect-like floral morphology, an adaptation for a pseudocopulatory pollination strategy involving Hymenoptera males. A large number of endemic Ophrys species have recently been described, especially within the Mediterranean Basin, which is one of the major species diversity hotspots. Subtle morphological variation and specific pollinator dependence are the two main perceptible criteria for describing numerous endemic taxa. However, the degree to which endemics differ genetically remains a challenging question. Additionally, knowledge regarding the factors underlying the emergence of such endemic entities is limited. To achieve new insights regarding speciation processes in Ophrys, we have investigated species boundaries in the Fly Orchid group (Ophrys insectifera sensu lato) by examining morphological, ecological and genetic evidence. Classically, authors have recognized one widespread taxon (O. insectifera) and two endemics (O. aymoninii from France and O. subinsectifera from Spain). Our research has identified clear morphological and ecological factors segregating among these taxa; however, genetic differences were more ambiguous. Insights from cpDNA sequencing and amplified fragment length polymorphisms genotyping indicated a recent diversification in the three extant Fly Orchid species, which may have been further obscured by active migration and admixture across the European continent. Our genetic results still indicate weak but noticeable phylogeographic clustering that partially correlates with the described species. Particularly, we report several isolated haplotypes and genetic clusters in central and southeastern Europe. With regard to the morphological, ecological and genetic aspects, we discuss the endemism status within the Fly Orchid group from evolutionary, taxonomical and conservation perspectives.
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The genetic characterization of unbalanced mixed stains remains an important area where improvement is imperative. In fact, with current methods for DNA analysis (Polymerase Chain Reaction with the SGM Plus™ multiplex kit), it is generally not possible to obtain a conventional autosomal DNA profile of the minor contributor if the ratio between the two contributors in a mixture is smaller than 1:10. This is a consequence of the fact that the major contributor's profile 'masks' that of the minor contributor. Besides known remedies to this problem, such as Y-STR analysis, a new compound genetic marker that consists of a Deletion/Insertion Polymorphism (DIP), linked to a Short Tandem Repeat (STR) polymorphism, has recently been developed and proposed elsewhere in literature [1]. The present paper reports on the derivation of an approach for the probabilistic evaluation of DIP-STR profiling results obtained from unbalanced DNA mixtures. The procedure is based on object-oriented Bayesian networks (OOBNs) and uses the likelihood ratio as an expression of the probative value. OOBNs are retained in this paper because they allow one to provide a clear description of the genotypic configuration observed for the mixed stain as well as for the various potential contributors (e.g., victim and suspect). These models also allow one to depict the assumed relevance relationships and perform the necessary probabilistic computations.
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Introduction: There is little information regarding the impact of diet on disease incidence and mortality in Switzerland. Objectives: We aimed at assessing the associations between food availability and disease using ecological correlations. Methods: Time-trend ecologic study for period 1970 to 2009. Food availability was measured through the FAO food balance sheets. Standardized mortality rates (SMRs) were obtained from the Swiss Federal Office of Statistics. Cancer incidence data was obtained from the WHO Health for all database and the Vaud cancer registry. Association between food availability and mortality/incidence was assessed at lags 0, 5, 10 and 15 years by Spearman correlation. Results: Alcoholic beverages and fruit availability were positively associated with SMRs from all types of cardiovascular disease, while fish availability was negatively associated. Animal products, meat and animal fats were positively associated with SMR from ischemic heart disease only. For cancers, opposite results were found whether the association used SMRs or incidence rates. For all cancers, alcoholic beverages and fruits were positively associated with SMRs but negatively associated with incidence rates. Similar findings were obtained for all other foods, with the exception of vegetables, which were weakly and negatively associated with SMRs and incidence rates. Finally, a 15 years lag time reversed the association for animal and vegetal products, weakened the association for alcohol and fruits and strengthened the association for fish. Conclusion: Ecologic associations between food availability and disease vary considerably whether mortality or incidence rates are used. Great care should be taken when interpreting the results.
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Using optimized voxel-based morphometry, we performed grey matter density analyses on 59 age-, sex- and intelligence-matched young adults with three distinct, progressive levels of musical training intensity or expertise. Structural brain adaptations in musicians have been repeatedly demonstrated in areas involved in auditory perception and motor skills. However, musical activities are not confined to auditory perception and motor performance, but are entangled with higher-order cognitive processes. In consequence, neuronal systems involved in such higher-order processing may also be shaped by experience-driven plasticity. We modelled expertise as a three-level regressor to study possible linear relationships of expertise with grey matter density. The key finding of this study resides in a functional dissimilarity between areas exhibiting increase versus decrease of grey matter as a function of musical expertise. Grey matter density increased with expertise in areas known for their involvement in higher-order cognitive processing: right fusiform gyrus (visual pattern recognition), right mid orbital gyrus (tonal sensitivity), left inferior frontal gyrus (syntactic processing, executive function, working memory), left intraparietal sulcus (visuo-motor coordination) and bilateral posterior cerebellar Crus II (executive function, working memory) and in auditory processing: left Heschl's gyrus. Conversely, grey matter density decreased with expertise in bilateral perirolandic and striatal areas that are related to sensorimotor function, possibly reflecting high automation of motor skills. Moreover, a multiple regression analysis evidenced that grey matter density in the right mid orbital area and the inferior frontal gyrus predicted accuracy in detecting fine-grained incongruities in tonal music.