Relative effects of fragment size and connectivity on bird community in the Atlantic Rain Forest: Implications for conservation

It is known that large fragment sizes and high connectivity levels are key components for maintaining species in fragments; however, their relative effects are poorly understood, especially in tropical areas. In order to test these effects, we built models for explaining understory birds occurrence in a fragmented Atlantic Rain Forest landscape with intermediate habitat cover (3%). Data from over 9000 mist-net hours from 17 fragments differing in size (2-175 ha) and connectivity (considering corridor linkages and distance to nearby fragments) were ranked under a model selection approach. A total 1293 individuals of 62 species were recorded. Species richness, abundance and compositional variation were mainly affected by connectivity indices that consider the capacity of species to use corridors and/or to cross short distances up to 30 m through the matrix. Bird functional groups were differently affected by area and connectivity: while terrestrial insectivores, omnivores and frugivores were affected by both area and connectivity, the other groups (understory insectivores, nectarivores, and others) were affected only by connectivity. In the studied landscape, well connected fragments can sustain an elevated number of species and individuals. Connectivity gives the opportunity for individuals to use multiple fragments, reducing the influence of fragment size. While preserving large fragments is a conservation target worldwide and should continue to be, our results indicated that connectivity between fragments can enhance the area functionally connected and is beneficial to all functional groups and therefore should be a conservation priority. (C) 2008 Elsevier Ltd. All rights reserved.

Biogeography of Glandulocaudinae (Teleostei : Characiformes : Characidae) revisited: phylogenetic patterns, historical geology and genetic connectivity

The biogeography of the Glandulocaudinae ( former Glandulocaudini) is reviewed. The major pattern of diversification presented by this group of freshwater fishes can be clearly associated to the main aspects of the tectonic evolution of the southern portion of the Cis-Andean South American Platform. The phylogenetic relationships within the group suggest that the clade represented by Lophiobrycon is the sister-group of the more derived clade represented by the genus Glandulocauda and Mimagoniates. Lophiobrycon and Glandulocauda occur in areas of the ancient crystalline shield of southeastern Brazil and their present allopatric distribution is probably due to relict survival and tectonic vicariant events. Populations of Glandulocauda melanogenys are found in contiguous drainages in presently isolated upper parts of the Tiete, Guaratuba, Itatinga, and Ribeira de Iguape basins and this pattern of distribution is probably the result of river capture caused by tectonic processes that affected a large area in eastern and southeastern Brazil. The species of Mimagoniates are predominantly distributed along the eastern and southeastern coastal areas, but M. microlepis is additionally found in the rio Iguacu and Tibagi basins. Mimagoniates barberi occurs in both SW margin of the upper rio Parana basin and the lower Paraguay and Mimagoniates sp. occurs in the upper Paraguay river basin. Tectonic activations of the Continental Rift of Southeastern Brazil along the eastern margin of the Upper Parana basin promoted population fragmentation responsible of the present day distribution presented by Glandulocauda melanogenys. We hypothesize that occurrence of Mimagoniates along the lowland area around the Parana basin was due to a single or a multiple fragmentation of populations along the W-SW border of the upper Parana Basin, probably due to the major tectonic origin of the Chaco-Pantanal wetland foreland basins since the Miocene as well as Cenozoic tectonic activity along the borders of the upper Parana basin, such as in the eastern Paraguay, in the Asuncion Rift. Distributional pattern of Mimagoniates suggests that its initial diversification may be related to the tectonic evolution of the Chaco-Pantanal foreland basin system and a minimum age of 2.5 M.Y are proposed for this monophyletic group. Previous hypotheses on sea level fluctuations of the late Quaternary as being the main causal mechanism promoting cladogenesis and speciation of the group are critically reviewed. Phylogeographic studies based on molecular data indicate significant differences among the isolated populations of M. microlepis. These findings suggest that a much longer period of time and a paleogeographic landscape configuration of the Brazilian southeastern coastal region explain the present observed phylogenetic and biogeographic patterns.

Modeling connectivity in terms of network activity

A new complex network model is proposed which is founded on growth, with new connections being established proportionally to the current dynamical activity of each node, which can be understood as a generalization of the Barabasi-Albert static model. By using several topological measurements, as well as optimal multivariate methods (canonical analysis and maximum likelihood decision), we show that this new model provides, among several other theoretical kinds of networks including Watts-Strogatz small-world networks, the greatest compatibility with three real-world cortical networks.

Performance evaluation of routing protocols for MANETs with known connectivity patterns using evolving graphs

The assessment of routing protocols for mobile wireless networks is a difficult task, because of the networks` dynamic behavior and the absence of benchmarks. However, some of these networks, such as intermittent wireless sensors networks, periodic or cyclic networks, and some delay tolerant networks (DTNs), have more predictable dynamics, as the temporal variations in the network topology can be considered as deterministic, which may make them easier to study. Recently, a graph theoretic model-the evolving graphs-was proposed to help capture the dynamic behavior of such networks, in view of the construction of least cost routing and other algorithms. The algorithms and insights obtained through this model are theoretically very efficient and intriguing. However, there is no study about the use of such theoretical results into practical situations. Therefore, the objective of our work is to analyze the applicability of the evolving graph theory in the construction of efficient routing protocols in realistic scenarios. In this paper, we use the NS2 network simulator to first implement an evolving graph based routing protocol, and then to use it as a benchmark when comparing the four major ad hoc routing protocols (AODV, DSR, OLSR and DSDV). Interestingly, our experiments show that evolving graphs have the potential to be an effective and powerful tool in the development and analysis of algorithms for dynamic networks, with predictable dynamics at least. In order to make this model widely applicable, however, some practical issues still have to be addressed and incorporated into the model, like adaptive algorithms. We also discuss such issues in this paper, as a result of our experience.

Functional and Structural Connectivity Between the Perigenual Anterior Cingulate and Amygdala in Bipolar Disorder

Objective: Abnormalities in the morphology and function of two gray matter structures central to emotional processing, the perigenual anterior cingulate cortex (pACC) and amygdala, have consistently been reported in bipolar disorder (BD). Evidence implicates abnormalities in their connectivity in BD. This study investigates the potential disruptions in pACC-amygdala functional connectivity and associated abnormalities in white matter that provides structural connections between the two brain regions in BD. Methods: Thirty-three individuals with BD and 31 healthy comparison subjects (HC) participated in a scanning session during which functional magnetic resonance imaging (fMRI) during processing of face stimuli and diffusion tensor imaging (DTI) were performed. The strength of pACC-amygdala functional connections was compared between BD and HC groups, and associations between these functional connectivity measures from the fMRI scans and regional fractional anisotropy (FA) from the DTI scans were assessed. Results: Functional connectivity was decreased between the pACC and amygdala in the BD group compared with HC group, during the processing of fearful and happy faces (p < .005). Moreover, a significant positive association between pACC-amygdala functional coupling and FA in ventrofrontal white matter, including the region of the uncinate fasciculus, was identified (p < .005). Conclusion: This study provides evidence for abnormalities in pACC-amygdala functional connectivity during emotional processing in BD. The significant association between pACC-amygdala functional connectivity and the structural integrity of white matter that contains pACC-amygdala connections suggest that disruptions in white matter connectivity may contribute to disturbances in the coordinated responses of the pACC and amygdala during emotional processing in BD.

Mudanças no Código Florestal e seu impacto na ecologia e diversidade dos mamíferos no Brasil

Os ecossistemas florestais do Brasil abrigam um dos mais altos níveis de diversidade de mamíferos da Terra, e boa parte dessa diversidade se encontra nas áreas legalmente protegidas em áreas de domínio privado. As reservas legais (RLs) e áreas de proteção permanente (APPs) representam estratégias importantes para a proteção e manutenção dessa diversidade. Mudanças propostas no Código Florestal certamente trarão efeitos irreversíveis para a diversidade de mamíferos no Brasil. Os mamíferos apresentam papéis-chave nos ecossistemas, atuando como polinizadores e dispersores de sementes. A extinção local de algumas espécies pode reduzir os serviços ecológicos nas RLs e APPs. Outra consequência grave da redução de áreas de vegetação nativa caso a mudança no Código Florestal seja aprovada será o aumento no risco de transmição de doenças, trazendo sério problemas a saúde pública no Brasil.

Recovery and upgrading bovine rumen protein by extrusion: effect of lipid content on protein disulphide cross-linking, solubility and molecular weight

Bovine rumen protein with two levels of residual lipids (1.9 per cent or 3.8 per cent) was subjected to thermoplastic extrusion under different temperatures and moisture contents. Protein solubility in different buffers, disulphide cross-linking and molecular weight distribution were determined on the extrudates. After extrusion, samples with 1.9 per cent residual lipids content had a higher concentration of protein insoluble by undetermined forces, irrespective of feed moisture and processing temperature used. Lipid content of 3.8 per cent in the feed material resulted in more protein participating in the extrudate network through non-covalent interactions (hydrophobic and electrostatic) and disulphide bonds. A small dependency of the extrusion process on moisture and temperature and a marked dependency on lipid content, especially phospholipid, was observed, Electrophoresis under non-reducing conditions showed that protein extrusion with low feed moisture promoted high molecular breakdown inside the barrel, probably due to intense shear force, and further protein aggregation at the die end

The Brain as a Distributed Intelligent Processing System: An EEG Study

Background: Various neuroimaging studies, both structural and functional, have provided support for the proposal that a distributed brain network is likely to be the neural basis of intelligence. The theory of Distributed Intelligent Processing Systems (DIPS), first developed in the field of Artificial Intelligence, was proposed to adequately model distributed neural intelligent processing. In addition, the neural efficiency hypothesis suggests that individuals with higher intelligence display more focused cortical activation during cognitive performance, resulting in lower total brain activation when compared with individuals who have lower intelligence. This may be understood as a property of the DIPS. Methodology and Principal Findings: In our study, a new EEG brain mapping technique, based on the neural efficiency hypothesis and the notion of the brain as a Distributed Intelligence Processing System, was used to investigate the correlations between IQ evaluated with WAIS (Whechsler Adult Intelligence Scale) and WISC (Wechsler Intelligence Scale for Children), and the brain activity associated with visual and verbal processing, in order to test the validity of a distributed neural basis for intelligence. Conclusion: The present results support these claims and the neural efficiency hypothesis.

Integration and visualization of systems biology data in context of the genome

Background: High-density tiling arrays and new sequencing technologies are generating rapidly increasing volumes of transcriptome and protein-DNA interaction data. Visualization and exploration of this data is critical to understanding the regulatory logic encoded in the genome by which the cell dynamically affects its physiology and interacts with its environment. Results: The Gaggle Genome Browser is a cross-platform desktop program for interactively visualizing high-throughput data in the context of the genome. Important features include dynamic panning and zooming, keyword search and open interoperability through the Gaggle framework. Users may bookmark locations on the genome with descriptive annotations and share these bookmarks with other users. The program handles large sets of user-generated data using an in-process database and leverages the facilities of SQL and the R environment for importing and manipulating data. A key aspect of the Gaggle Genome Browser is interoperability. By connecting to the Gaggle framework, the genome browser joins a suite of interconnected bioinformatics tools for analysis and visualization with connectivity to major public repositories of sequences, interactions and pathways. To this flexible environment for exploring and combining data, the Gaggle Genome Browser adds the ability to visualize diverse types of data in relation to its coordinates on the genome. Conclusions: Genomic coordinates function as a common key by which disparate biological data types can be related to one another. In the Gaggle Genome Browser, heterogeneous data are joined by their location on the genome to create information-rich visualizations yielding insight into genome organization, transcription and its regulation and, ultimately, a better understanding of the mechanisms that enable the cell to dynamically respond to its environment.

Beyond the Fragmentation Threshold Hypothesis: Regime Shifts in Biodiversity Across Fragmented Landscapes

Ecological systems are vulnerable to irreversible change when key system properties are pushed over thresholds, resulting in the loss of resilience and the precipitation of a regime shift. Perhaps the most important of such properties in human-modified landscapes is the total amount of remnant native vegetation. In a seminal study Andren proposed the existence of a fragmentation threshold in the total amount of remnant vegetation, below which landscape-scale connectivity is eroded and local species richness and abundance become dependent on patch size. Despite the fact that species patch-area effects have been a mainstay of conservation science there has yet to be a robust empirical evaluation of this hypothesis. Here we present and test a new conceptual model describing the mechanisms and consequences of biodiversity change in fragmented landscapes, identifying the fragmentation threshold as a first step in a positive feedback mechanism that has the capacity to impair ecological resilience, and drive a regime shift in biodiversity. The model considers that local extinction risk is defined by patch size, and immigration rates by landscape vegetation cover, and that the recovery from local species losses depends upon the landscape species pool. Using a unique dataset on the distribution of non-volant small mammals across replicate landscapes in the Atlantic forest of Brazil, we found strong evidence for our model predictions - that patch-area effects are evident only at intermediate levels of total forest cover, where landscape diversity is still high and opportunities for enhancing biodiversity through local management are greatest. Furthermore, high levels of forest loss can push native biota through an extinction filter, and result in the abrupt, landscape-wide loss of forest-specialist taxa, ecological resilience and management effectiveness. The proposed model links hitherto distinct theoretical approaches within a single framework, providing a powerful tool for analysing the potential effectiveness of management interventions.

Chain motifs: The tails and handles of complex networks

A great part of the interest in complex networks has been motivated by the presence of structured, frequently nonuniform, connectivity. Because diverse connectivity patterns tend to result in distinct network dynamics, and also because they provide the means to identify and classify several types of complex network, it becomes important to obtain meaningful measurements of the local network topology. In addition to traditional features such as the node degree, clustering coefficient, and shortest path, motifs have been introduced in the literature in order to provide complementary descriptions of the network connectivity. The current work proposes a different type of motif, namely, chains of nodes, that is, sequences of connected nodes with degree 2. These chains have been subdivided into cords, tails, rings, and handles, depending on the type of their extremities (e.g., open or connected). A theoretical analysis of the density of such motifs in random and scale-free networks is described, and an algorithm for identifying these motifs in general networks is presented. The potential of considering chains for network characterization has been illustrated with respect to five categories of real-world networks including 16 cases. Several interesting findings were obtained, including the fact that several chains were observed in real-world networks, especially the world wide web, books, and the power grid. The possibility of chains resulting from incompletely sampled networks is also investigated.

Transport properties in nontwist area-preserving maps

Nontwist systems, common in the dynamical descriptions of fluids and plasmas, possess a shearless curve with a concomitant transport barrier that eliminates or reduces chaotic transport, even after its breakdown. In order to investigate the transport properties of nontwist systems, we analyze the barrier escape time and barrier transmissivity for the standard nontwist map, a paradigm of such systems. We interpret the sensitive dependence of these quantities upon map parameters by investigating chaotic orbit stickiness and the associated role played by the dominant crossing of stable and unstable manifolds. (C) 2009 American Institute of Physics. [doi: 10.1063/1.3247349]

Supergraph techniques for D=3, N=1 broken supersymmetric theories

We enlarge the usual D = 3 N = 1 supergraph techniques to include the case of (explicitly or spontaneously) broken supersymmetric gauge theories. To illustrate the utility of these techniques, we calculate the two-loop effective potential of the SQED(3) by using the tadpole and the vacuum bubble methods. In these methods, to investigate the possibility of supersymmetry breaking, the superfields must be shifted by theta(alpha) dependent classical superfields (vacuum expectation values), what implies in the explicit breakdown of supersymmetry in the intermediate steps of the calculation. Nevertheless, after studying the minimum of the resulting effective potential, we find that supersymmetry is conserved, while gauge symmetry is dynamically broken, with a mass generated for the gauge superfield.

Communication structure of cortical networks

Large-scale cortical networks exhibit characteristic topological properties that shape communication between brain regions and global cortical dynamics. Analysis of complex networks allows the description of connectedness, distance, clustering, and centrality that reveal different aspects of how the network's nodes communicate. Here, we focus on a novel analysis of complex walks in a series of mammalian cortical networks that model potential dynamics of information flow between individual brain regions. We introduce two new measures called absorption and driftness. Absorption is the average length of random walks between any two nodes, and takes into account all paths that may diffuse activity throughout the network. Driftness is the ratio between absorption and the corresponding shortest path length. For a given node of the network, we also define four related measurements, namely in-and out-absorption as well as in-and out-driftness, as the averages of the corresponding measures from all nodes to that node, and from that node to all nodes, respectively. We find that the cat thalamo-cortical system incorporates features of two classic network topologies, Erdos-Renyi graphs with respect to in-absorption and in-driftness, and configuration models with respect to out-absorption and out-driftness. Moreover, taken together these four measures separate the network nodes based on broad functional roles (visual, auditory, somatomotor, and frontolimbic).

Automatic Network Fingerprinting through Single-Node Motifs

Complex networks have been characterised by their specific connectivity patterns (network motifs), but their building blocks can also be identified and described by node-motifs-a combination of local network features. One technique to identify single node-motifs has been presented by Costa et al. (L. D. F. Costa, F. A. Rodrigues, C. C. Hilgetag, and M. Kaiser, Europhys. Lett., 87, 1, 2009). Here, we first suggest improvements to the method including how its parameters can be determined automatically. Such automatic routines make high-throughput studies of many networks feasible. Second, the new routines are validated in different network-series. Third, we provide an example of how the method can be used to analyse network time-series. In conclusion, we provide a robust method for systematically discovering and classifying characteristic nodes of a network. In contrast to classical motif analysis, our approach can identify individual components (here: nodes) that are specific to a network. Such special nodes, as hubs before, might be found to play critical roles in real-world networks.