Landscape structure affects dispersal in the greater white-toothed shrew: inference between genetic and simulated ecological distances

Animal dispersal in a fragmented landscape depends on the complex interaction between landscape structure and animal behavior. To better understand how individuals disperse, it is important to explicitly represent the properties of organisms and the landscape in which they move. A common approach to modelling dispersal includes representing the landscape as a grid of equal sized cells and then simulating individual movement as a correlated random walk. This approach uses a priori scale of resolution, which limits the representation of all landscape features and how different dispersal abilities are modelled. We develop a vector-based landscape model coupled with an object-oriented model for animal dispersal. In this spatially explicit dispersal model, landscape features are defined based on their geographic and thematic properties and dispersal is modelled through consideration of an organism's behavior, movement rules and searching strategies (such as visual cues). We present the model's underlying concepts, its ability to adequately represent landscape features and provide simulation of dispersal according to different dispersal abilities. We demonstrate the potential of the model by simulating two virtual species in a real Swiss landscape. This illustrates the model's ability to simulate complex dispersal processes and provides information about dispersal such as colonization probability and spatial distribution of the organism's path

Gauge group and reality conditions in Ashtekar's complex formulation of canonical gravity

We discuss reality conditions and the relation between spacetime diffeomorphisms and gauge transformations in Ashtekars complex formulation of general relativity. We produce a general theoretical framework for the stabilization algorithm for the reality conditions, which is different from Diracs method of stabilization of constraints. We solve the problem of the projectability of the diffeomorphism transformations from configuration-velocity space to phase space, linking them to the reality conditions. We construct the complete set of canonical generators of the gauge group in the phase space which includes all the gauge variables. This result proves that the canonical formalism has all the gauge structure of the Lagrangian theory, including the time diffeomorphisms.

Kinematically complete analysis of the CLAS data on the proton structure Function F2 in a Regge-Dual model

The recently measured inclusive electron-proton cross section in the nucleon resonance region, performed with the CLAS detector at the Thomas Jefferson Laboratory, has provided new data for the nucleon structure function F2 with previously unavailable precision. In this paper we propose a description of these experimental data based on a Regge-dual model for F2. The basic inputs in the model are nonlinear complex Regge trajectories producing both isobar resonances and a smooth background. The model is tested against the experimental data, and the Q2 dependence of the moments is calculated. The fitted model for the structure function (inclusive cross section) is a limiting case of the more general scattering amplitude equally applicable to deeply virtual Compton scattering. The connection between the two is discussed.

Clustering in complex networks. II. Percolation properties

The percolation properties of clustered networks are analyzed in detail. In the case of weak clustering, we present an analytical approach that allows us to find the critical threshold and the size of the giant component. Numerical simulations confirm the accuracy of our results. In more general terms, we show that weak clustering hinders the onset of the giant component whereas strong clustering favors its appearance. This is a direct consequence of the differences in the k-core structure of the networks, which are found to be totally different depending on the level of clustering. An empirical analysis of a real social network confirms our predictions.

Self-similar community structure in a network of human interactions

We propose a procedure for analyzing and characterizing complex networks. We apply this to the social network as constructed from email communications within a medium sized university with about 1700 employees. Email networks provide an accurate and nonintrusive description of the flow of information within human organizations. Our results reveal the self-organization of the network into a state where the distribution of community sizes is self-similar. This suggests that a universal mechanism, responsible for emergence of scaling in other self-organized complex systems, as, for instance, river networks, could also be the underlying driving force in the formation and evolution of social networks.

MORPHOLOGICAL AND MICROMORPHOLOGICAL CHANGES IN THE STRUCTURE OF A RHODIC HAPLUDOX AS A RESULT OF AGRICULTURAL MANAGEMENT

In evaluation of soil quality for agricultural use, soil structure is one of the most important properties, which is influenced not only by climate, biological activity, and management practices but also by mechanical and physico-chemical forces acting in the soil. The purpose of this study was to evaluate the influence of conventional agricultural management on the structure and microstructure of a Latossolo Vermelho distroférrico típico (Rhodic Hapludox) in an experimental area planted to maize. Soil morphology was described using the crop profile method by identifying the distinct structural volumes called Morphologically Homogeneous Units (MHUs). For comparison, we also described a profile in an adjacent area without agricultural use and under natural regrowth referred to as Memory. We took undisturbed samples from the main MHUs so as to form thin sections and blocks of soil for micromorphological and micromorphometrical analyses. Results from the application of the crop profile method showed the occurrence of the following structural types: loose (L), fragmented (F) and continuous (C) in both profiles analyzed. In the Memory soil profile, the fragmented structures were classified as Fptμ∆+tf and Fmt∆μ, whose micromorphology shows an enaulic-porphyric (porous) relative distribution with a great deal of biological activity as indicated by the presence of vughs and channels. Lower down, from 0.20 to 0.35 m, there was a continuous soil volume (sub-type C∆μ), with a subangular block microstructure and an enaulic-porphyric relative distribution, though in this case more compact and with aggregate coalescence and less biological activity. The micromorphometrical study of the soil of the Memory Plot showed the predominance of complex pores in NAM (15.03 %), Fmt∆μ (11.72 %), and Fptμ∆+tf (7.73 %), and rounded pores in C∆μ (8.21 %). In the soil under conventional agricultural management, we observed fragmented structures similar to the Memory Plot from 0.02 to 0.20 m, followed by a volume with a compact continuous structure (C∆μ), without visible porosity and with few roots. In the MHUs under conventional management, reduction in the packing pores (40 %) was observed, mainly in the continuous units (C). The microstructure had well-defined blocks, with the occurrence of planar pores and less evidence of biological activity. In conclusion, the morphological and micromorphological analyses of the soil profiles studied offered complementary information regarding soil structural quality, especially concerning the changes in pore types as result of mechanical stress undergone by the soil.

Static and dynamic structure of liquid metals: Role of the different parts of the interaction potential

The influence of different parts of the interaction potential on the microscopic behavior of simple liquid metals is investigated by molecular dynamics simulation. The role of the soft-core repulsive, short-range attractive, and long-range oscillatory forces on the properties of liquid lithium close to the triple point is analyzed by comparing the results from simulations of identical systems but truncating the potential at different distances. Special attention is paid to dynamic collective properties such as the dynamic structure factors, transverse current correlation functions, and transport coefficients. It is observed that, in general, the effects of the short-range attractive forces are important. On the contrary, the influence of the oscillatory long-range interactions is considerably less, being the most pronounced for the dynamic structure factor at long wavelengths. The results of this work suggest that the influence of the attractive forces becomes less significant when temperature and density increase.

Impact of community structure on information transfer

The observation that real complex networks have internal structure has important implication for dynamic processes occurring on such topologies. Here we investigate the impact of community structure on a model of information transfer able to deal with both search and congestion simultaneously. We show that networks with fuzzy community structure are more efficient in terms of packet delivery than those with pronounced community structure. We also propose an alternative packet routing algorithm which takes advantage of the knowledge of communities to improve information transfer and show that in the context of the model an intermediate level of community structure is optimal. Finally, we show that in a hierarchical network setting, providing knowledge of communities at the level of highest modularity will improve network capacity by the largest amount.

Estimation of the correlation structure of crustal velocity heterogeneity from seismic reflection data

Numerous sources of evidence point to the fact that heterogeneity within the Earth's deep crystalline crust is complex and hence may be best described through stochastic rather than deterministic approaches. As seismic reflection imaging arguably offers the best means of sampling deep crustal rocks in situ, much interest has been expressed in using such data to characterize the stochastic nature of crustal heterogeneity. Previous work on this problem has shown that the spatial statistics of seismic reflection data are indeed related to those of the underlying heterogeneous seismic velocity distribution. As of yet, however, the nature of this relationship has remained elusive due to the fact that most of the work was either strictly empirical or based on incorrect methodological approaches. Here, we introduce a conceptual model, based on the assumption of weak scattering, that allows us to quantitatively link the second-order statistics of a 2-D seismic velocity distribution with those of the corresponding processed and depth-migrated seismic reflection image. We then perform a sensitivity study in order to investigate what information regarding the stochastic model parameters describing crustal velocity heterogeneity might potentially be recovered from the statistics of a seismic reflection image using this model. Finally, we present a Monte Carlo inversion strategy to estimate these parameters and we show examples of its application at two different source frequencies and using two different sets of prior information. Our results indicate that the inverse problem is inherently non-unique and that many different combinations of the vertical and lateral correlation lengths describing the velocity heterogeneity can yield seismic images with the same 2-D autocorrelation structure. The ratio of all of these possible combinations of vertical and lateral correlation lengths, however, remains roughly constant which indicates that, without additional prior information, the aspect ratio is the only parameter describing the stochastic seismic velocity structure that can be reliably recovered.

TWEAK-FN14 signaling induces lysosomal degradation of a cIAP1-TRAF2 complex to sensitize tumor cells to TNFalpha.

Synthetic inhibitor of apoptosis (IAP) antagonists induce degradation of IAP proteins such as cellular IAP1 (cIAP1), activate nuclear factor kappaB (NF-kappaB) signaling, and sensitize cells to tumor necrosis factor alpha (TNFalpha). The physiological relevance of these discoveries to cIAP1 function remains undetermined. We show that upon ligand binding, the TNF superfamily receptor FN14 recruits a cIAP1-Tnf receptor-associated factor 2 (TRAF2) complex. Unlike IAP antagonists that cause rapid proteasomal degradation of cIAP1, signaling by FN14 promotes the lysosomal degradation of cIAP1-TRAF2 in a cIAP1-dependent manner. TNF-like weak inducer of apoptosis (TWEAK)/FN14 signaling nevertheless promotes the same noncanonical NF-kappaB signaling elicited by IAP antagonists and, in sensitive cells, the same autocrine TNFalpha-induced death occurs. TWEAK-induced loss of the cIAP1-TRAF2 complex sensitizes immortalized and minimally passaged tumor cells to TNFalpha-induced death, whereas primary cells remain resistant. Conversely, cIAP1-TRAF2 complex overexpression limits FN14 signaling and protects tumor cells from TWEAK-induced TNFalpha sensitization. Lysosomal degradation of cIAP1-TRAF2 by TWEAK/FN14 therefore critically alters the balance of life/death signals emanating from TNF-R1 in immortalized cells.

Generation and nonlinear evolution of shore-oblique/transverse sand bars

The coupling between topography, waves and currents in the surf zone may selforganize to produce the formation of shore-transverse or shore-oblique sand bars on an otherwise alongshore uniform beach. In the absence of shore-parallel bars, this has been shown by previous studies of linear stability analysis, but is now extended to the finite-amplitude regime. To this end, a nonlinear model coupling wave transformation and breaking, a shallow-water equations solver, sediment transport and bed updating is developed. The sediment flux consists of a stirring factor multiplied by the depthaveraged current plus a downslope correction. It is found that the cross-shore profile of the ratio of stirring factor to water depth together with the wave incidence angle primarily determine the shape and the type of bars, either transverse or oblique to the shore. In the latter case, they can open an acute angle against the current (upcurrent oriented) or with the current (down-current oriented). At the initial stages of development, both the intensity of the instability which is responsible for the formation of the bars and the damping due to downslope transport grow at a similar rate with bar amplitude, the former being somewhat stronger. As bars keep on growing, their finite-amplitude shape either enhances downslope transport or weakens the instability mechanism so that an equilibrium between both opposing tendencies occurs, leading to a final saturated amplitude. The overall shape of the saturated bars in plan view is similar to that of the small-amplitude ones. However, the final spacings may be up to a factor of 2 larger and final celerities can also be about a factor of 2 smaller or larger. In the case of alongshore migrating bars, the asymmetry of the longshore sections, the lee being steeper than the stoss, is well reproduced. Complex dynamics with merging and splitting of individual bars sometimes occur. Finally, in the case of shore-normal incidence the rip currents in the troughs between the bars are jet-like while the onshore return flow is wider and weaker as is observed in nature.

Structure-function analysis of the human TFIIB-related factor II protein reveals an essential role for the C-terminal domain in RNA polymerase III transcription.

The transcription factors TFIIB, Brf1, and Brf2 share related N-terminal zinc ribbon and core domains. TFIIB bridges RNA polymerase II (Pol II) with the promoter-bound preinitiation complex, whereas Brf1 and Brf2 are involved, as part of activities also containing TBP and Bdp1 and referred to here as Brf1-TFIIIB and Brf2-TFIIIB, in the recruitment of Pol III. Brf1-TFIIIB recruits Pol III to type 1 and 2 promoters and Brf2-TFIIIB to type 3 promoters such as the human U6 promoter. Brf1 and Brf2 both have a C-terminal extension absent in TFIIB, but their C-terminal extensions are unrelated. In yeast Brf1, the C-terminal extension interacts with the TBP/TATA box complex and contributes to the recruitment of Bdp1. Here we have tested truncated Brf2, as well as Brf2/TFIIB chimeric proteins for U6 transcription and for assembly of U6 preinitiation complexes. Our results characterize functions of various human Brf2 domains and reveal that the C-terminal domain is required for efficient association of the protein with U6 promoter-bound TBP and SNAP(c), a type 3 promoter-specific transcription factor, and for efficient recruitment of Bdp1. This in turn suggests that the C-terminal extensions in Brf1 and Brf2 are crucial to specific recruitment of Pol III over Pol II.

Ecology and life history affect different aspects of the population structure of 27 high-alpine plants.

A plant species' genetic population structure is the result of a complex combination of its life history, ecological preferences, position in the ecosystem and historical factors. As a result, many different statistical methods exist that measure different aspects of species' genetic structure. However, little is known about how these methods are interrelated and how they are related to a species' ecology and life history. In this study, we used the IntraBioDiv amplified fragment length polymorphisms data set from 27 high-alpine species to calculate eight genetic summary statistics that we jointly correlate to a set of six ecological and life-history traits. We found that there is a large amount of redundancy among the calculated summary statistics and that there is a significant association with the matrix of species traits. In a multivariate analysis, two main aspects of population structure were visible among the 27 species. The first aspect is related to the species' dispersal capacities and the second is most likely related to the species' postglacial recolonization of the Alps. Furthermore, we found that some summary statistics, most importantly Mantel's r and Jost's D, show different behaviour than expected based on theory. We therefore advise caution in drawing too strong conclusions from these statistics.

The geometric structure of the brain fiber pathways.

The structure of the brain as a product of morphogenesis is difficult to reconcile with the observed complexity of cerebral connectivity. We therefore analyzed relationships of adjacency and crossing between cerebral fiber pathways in four nonhuman primate species and in humans by using diffusion magnetic resonance imaging. The cerebral fiber pathways formed a rectilinear three-dimensional grid continuous with the three principal axes of development. Cortico-cortical pathways formed parallel sheets of interwoven paths in the longitudinal and medio-lateral axes, in which major pathways were local condensations. Cross-species homology was strong and showed emergence of complex gyral connectivity by continuous elaboration of this grid structure. This architecture naturally supports functional spatio-temporal coherence, developmental path-finding, and incremental rewiring with correlated adaptation of structure and function in cerebral plasticity and evolution.

Deciphering the global organization of clustering in real complex networks

We uncover the global organization of clustering in real complex networks. To this end, we ask whether triangles in real networks organize as in maximally random graphs with given degree and clustering distributions, or as in maximally ordered graph models where triangles are forced into modules. The answer comes by way of exploring m-core landscapes, where the m-core is defined, akin to the k-core, as the maximal subgraph with edges participating in at least m triangles. This property defines a set of nested subgraphs that, contrarily to k-cores, is able to distinguish between hierarchical and modular architectures. We find that the clustering organization in real networks is neither completely random nor ordered although, surprisingly, it is more random than modular. This supports the idea that the structure of real networks may in fact be the outcome of self-organized processes based on local optimization rules, in contrast to global optimization principles.