995 resultados para ECOLOGICAL NETWORKS
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1406 I. 1407 II. 1408 III. 1410 IV. 1411 V. 1413 VI. 1416 VII. 1418 1418 References 1419 SUMMARY: Almost all land plants form symbiotic associations with mycorrhizal fungi. These below-ground fungi play a key role in terrestrial ecosystems as they regulate nutrient and carbon cycles, and influence soil structure and ecosystem multifunctionality. Up to 80% of plant N and P is provided by mycorrhizal fungi and many plant species depend on these symbionts for growth and survival. Estimates suggest that there are c. 50 000 fungal species that form mycorrhizal associations with c. 250 000 plant species. The development of high-throughput molecular tools has helped us to better understand the biology, evolution, and biodiversity of mycorrhizal associations. Nuclear genome assemblies and gene annotations of 33 mycorrhizal fungal species are now available providing fascinating opportunities to deepen our understanding of the mycorrhizal lifestyle, the metabolic capabilities of these plant symbionts, the molecular dialogue between symbionts, and evolutionary adaptations across a range of mycorrhizal associations. Large-scale molecular surveys have provided novel insights into the diversity, spatial and temporal dynamics of mycorrhizal fungal communities. At the ecological level, network theory makes it possible to analyze interactions between plant-fungal partners as complex underground multi-species networks. Our analysis suggests that nestedness, modularity and specificity of mycorrhizal networks vary and depend on mycorrhizal type. Mechanistic models explaining partner choice, resource exchange, and coevolution in mycorrhizal associations have been developed and are being tested. This review ends with major frontiers for further research.
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Developmental biology, polymorphism and ecological aspects of Stiretrus decemguttatus (Hemiptera, Pentatomidae), an important predator of cassidine beetles. Stiretrus decemguttatus is an important predator of two species of cassidine beetles, Botanochara sedecimpustulata (Fabricius, 1781) and Zatrephina lineata (Fabricius, 1787) (Coleoptera, Cassidinae), on the Marajó Island, Brazil. It attacks individuals in all development stages, but preys preferentially on late-instar larvae. Its life cycle in the laboratory was 43.70 ± 1.09 days, with an egg incubation period of six days and duration from nymph and adult stages of 16.31 ± 0.11 and 22.10 ± 1.67 days, respectively. The duration of one generation (T) was 12.65 days and the intrinsic population growth rate (r) 0.25. These data reveal the adjustment of the life cycle of S. decemgutattus with those of the two preys, but suggest greater impact on Z. lineata. However, no preference over cassidine species was shown in the laboratory. Up to 17 different color patterns can be found in adults of S. decemguttatus, based on combinations of three basic sets of color markings. Some of them resemble the markings of chrysomelids associated with Ipomoea asarifolia (Convolvulaceae) and are possibly a mimetic ring. Three color patterns were identified in nymphs, none of which was associated with any specific adult color pattern.
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In this paper, we introduce the concept of dyadic pulsations as a measure of sustainability in online discussion groups. Dyadic pulsations correspond to new communication exchanges occurring between two participants in a discussion group. A group that continuously integrates new participants in the on-going conversation is characterized by a steady dyadic pulsation rhythm. On the contrary, groups that either pursue close conversation or unilateral communication have no or very little dyadic pulsations. We show on two examples taken from Usenet discussion groups, that dyadic pulsations permit to anticipate future bursts in response delay time which are signs of group discussion collapses. We discuss ways of making this measure resilient to spam and other common algorithmic production that pollutes real discussions
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Understanding factors that shape ranges of species is central in evolutionary biology. Species distribution models have become important tools to test biogeographical, ecological and evolutionary hypotheses. Moreover, from an ecological and evolutionary perspective, these models help to elucidate the spatial strategies of species at a regional scale. We modelled species distributions of two phylogenetically, geographically and ecologically close Tupinambis species (Teiidae) that occupy the southernmost area of the genus distribution in South America. We hypothesized that similarities between these species might have induced spatial strategies at the species level, such as niche differentiation and divergence of distribution patterns at a regional scale. Using logistic regression and MaxEnt we obtained species distribution models that revealed interspecific differences in habitat requirements, such as environmental temperature, precipitation and altitude. Moreover, the models obtained suggest that although the ecological niches of Tupinambis merianae and T. rufescens are different, these species might co-occur in a large contact zone. We propose that niche plasticity could be the mechanism enabling their co-occurrence. Therefore, the approach used here allowed us to understand the spatial strategies of two Tupinambis lizards at a regional scale.
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This paper describes an optimized model to support QoS by mean of Congestion minimization on LSPs (Label Switching Path). In order to perform this model, we start from a CFA (Capacity and Flow Allocation) model. As this model does not consider the buffer size to calculate the capacity cost, our model- named BCA (Buffer Capacity Allocation)- take into account this issue and it improve the CFA performance. To test our proposal, we perform several simulations; results show that BCA model minimizes LSP congestion and uniformly distributes flows on the network
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This work proposes an original contribution to the understanding of shermen spatial behavior, based on the behavioral ecology and movement ecology paradigms. Through the analysis of Vessel Monitoring System (VMS) data, we characterized the spatial behavior of Peruvian anchovy shermen at di erent scales: (1) the behavioral modes within shing trips (i.e., searching, shing and cruising); (2) the behavioral patterns among shing trips; (3) the behavioral patterns by shing season conditioned by ecosystem scenarios; and (4) the computation of maps of anchovy presence proxy from the spatial patterns of behavioral mode positions. At the rst scale considered, we compared several Markovian (hidden Markov and semi-Markov models) and discriminative models (random forests, support vector machines and arti cial neural networks) for inferring the behavioral modes associated with VMS tracks. The models were trained under a supervised setting and validated using tracks for which behavioral modes were known (from on-board observers records). Hidden semi-Markov models performed better, and were retained for inferring the behavioral modes on the entire VMS dataset. At the second scale considered, each shing trip was characterized by several features, including the time spent within each behavioral mode. Using a clustering analysis, shing trip patterns were classi ed into groups associated to management zones, eet segments and skippers' personalities. At the third scale considered, we analyzed how ecological conditions shaped shermen behavior. By means of co-inertia analyses, we found signi cant associations between shermen, anchovy and environmental spatial dynamics, and shermen behavioral responses were characterized according to contrasted environmental scenarios. At the fourth scale considered, we investigated whether the spatial behavior of shermen re ected to some extent the spatial distribution of anchovy. Finally, this work provides a wider view of shermen behavior: shermen are not only economic agents, but they are also foragers, constrained by ecosystem variability. To conclude, we discuss how these ndings may be of importance for sheries management, collective behavior analyses and end-to-end models.
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A new strategy for incremental building of multilayer feedforward neural networks is proposed in the context of approximation of functions from R-p to R-q using noisy data. A stopping criterion based on the properties of the noise is also proposed. Experimental results for both artificial and real data are performed and two alternatives of the proposed construction strategy are compared.
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Chromatin remodeling at specific genomic loci controls lymphoid differentiation. Here, we investigated the role played in this process by Kruppel-associated box (KRAB)-associated protein 1 (KAP1), the universal cofactor of KRAB-zinc finger proteins (ZFPs), a tetrapod-restricted family of transcriptional repressors. T-cell-specific Kap1-deleted mice displayed a significant expansion of immature thymocytes, imbalances in CD4(+)/CD8(+) cell ratios, and altered responses to TCR and TGFβ stimulation when compared to littermate KAP1 control mice. Transcriptome and chromatin studies revealed that KAP1 binds T-cell-specific cis-acting regulatory elements marked by the H3K9me3 repressive mark and enriched in Ikaros/NuRD complexes. Also, KAP1 directly controls the expression of several genes involved in TCR and cytokine signaling. Among these, regulation of FoxO1 seems to play a major role in this system. Likely responsible for tethering KAP1 to at least part of its genomic targets, a small number of KRAB-ZFPs are selectively expressed in T-lymphoid cells. These results reveal the so far unsuspected yet important role of KAP1-mediated epigenetic regulation in T-lymphocyte differentiation and activation.
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This PhD thesis addresses the issue of scalable media streaming in large-scale networking environments. Multimedia streaming is one of the largest sink of network resources and this trend is still growing as testified by the success of services like Skype, Netflix, Spotify and Popcorn Time (BitTorrent-based). In traditional client-server solutions, when the number of consumers increases, the server becomes the bottleneck. To overcome this problem, the Content-Delivery Network (CDN) model was invented. In CDN model, the server copies the media content to some CDN servers, which are located in different strategic locations on the network. However, they require heavy infrastructure investment around the world, which is too expensive. Peer-to-peer (P2P) solutions are another way to achieve the same result. These solutions are naturally scalable, since each peer can act as both a receiver and a forwarder. Most of the proposed streaming solutions in P2P networks focus on routing scenarios to achieve scalability. However, these solutions cannot work properly in video-on-demand (VoD) streaming, when resources of the media server are not sufficient. Replication is a solution that can be used in these situations. This thesis specifically provides a family of replication-based media streaming protocols, which are scalable, efficient and reliable in P2P networks. First, it provides SCALESTREAM, a replication-based streaming protocol that adaptively replicates media content in different peers to increase the number of consumers that can be served in parallel. The adaptiveness aspect of this solution relies on the fact that it takes into account different constraints like bandwidth capacity of peers to decide when to add or remove replicas. SCALESTREAM routes media blocks to consumers over a tree topology, assuming a reliable network composed of homogenous peers in terms of bandwidth. Second, this thesis proposes RESTREAM, an extended version of SCALESTREAM that addresses the issues raised by unreliable networks composed of heterogeneous peers. Third, this thesis proposes EAGLEMACAW, a multiple-tree replication streaming protocol in which two distinct trees, named EAGLETREE and MACAWTREE, are built in a decentralized manner on top of an underlying mesh network. These two trees collaborate to serve consumers in an efficient and reliable manner. The EAGLETREE is in charge of improving efficiency, while the MACAWTREE guarantees reliability. Finally, this thesis provides TURBOSTREAM, a hybrid replication-based streaming protocol in which a tree overlay is built on top of a mesh overlay network. Both these overlays cover all peers of the system and collaborate to improve efficiency and low-latency in streaming media to consumers. This protocol is implemented and tested in a real networking environment using PlanetLab Europe testbed composed of peers distributed in different places in Europe.
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We described the colonization dynamics of Staphylococcus aureus in a group of 266 healthy carriers over a period of approximately 1 year. We used precise genotyping methods, i.e., amplified fragment length polymorphism (AFLP), spa typing, and double-locus sequence typing (DLST), to detect changes in strain identity. Strain change took place rather rarely: out of 89 carriers who had initially been colonized, only 7 acquired a strain different from the original one. Approximately one-third of the carriers eliminated the colonization, and a similar number became newly colonized. Some of these events probably represent detection failure rather than genuine colonization loss or acquisition. Lower bacterial counts were associated with increased probability of eliminating the colonization. We have confirmed a high mutation rate in the spa locus: 6 out of 53 strains underwent mutation in the spa locus. There was no overall change in S. aureus genotype composition.
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Understanding how communities of living organisms assemble has been a central question in ecology since the early days of the discipline. Disentangling the different processes involved in community assembly is not only interesting in itself but also crucial for an understanding of how communities will behave under future environmental scenarios. The traditional concept of assembly rules reflects the notion that species do not co-occur randomly but are restricted in their co-occurrence by interspecific competition. This concept can be redefined in a more general framework where the co-occurrence of species is a product of chance, historical patterns of speciation and migration, dispersal, abiotic environmental factors, and biotic interactions, with none of these processes being mutually exclusive. Here we present a survey and meta-analyses of 59 papers that compare observed patterns in plant communities with null models simulating random patterns of species assembly. According to the type of data under study and the different methods that are applied to detect community assembly, we distinguish four main types of approach in the published literature: species co-occurrence, niche limitation, guild proportionality and limiting similarity. Results from our meta-analyses suggest that non-random co-occurrence of plant species is not a widespread phenomenon. However, whether this finding reflects the individualistic nature of plant communities or is caused by methodological shortcomings associated with the studies considered cannot be discerned from the available metadata. We advocate that more thorough surveys be conducted using a set of standardized methods to test for the existence of assembly rules in data sets spanning larger biological and geographical scales than have been considered until now. We underpin this general advice with guidelines that should be considered in future assembly rules research. This will enable us to draw more accurate and general conclusions about the non-random aspect of assembly in plant communities.