1,028 research outputs found

    Case report 220

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    Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/46818/1/256_2004_Article_BF00352557.pd

    Stochastic population growth in spatially heterogeneous environments

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    Classical ecological theory predicts that environmental stochasticity increases extinction risk by reducing the average per-capita growth rate of populations. To understand the interactive effects of environmental stochasticity, spatial heterogeneity, and dispersal on population growth, we study the following model for population abundances in nn patches: the conditional law of Xt+dtX_{t+dt} given Xt=xX_t=x is such that when dtdt is small the conditional mean of Xt+dtiXtiX_{t+dt}^i-X_t^i is approximately [xiμi+j(xjDjixiDij)]dt[x^i\mu_i+\sum_j(x^j D_{ji}-x^i D_{ij})]dt, where XtiX_t^i and μi\mu_i are the abundance and per capita growth rate in the ii-th patch respectivly, and DijD_{ij} is the dispersal rate from the ii-th to the jj-th patch, and the conditional covariance of Xt+dtiXtiX_{t+dt}^i-X_t^i and Xt+dtjXtjX_{t+dt}^j-X_t^j is approximately xixjσijdtx^i x^j \sigma_{ij}dt. We show for such a spatially extended population that if St=(Xt1+...+Xtn)S_t=(X_t^1+...+X_t^n) is the total population abundance, then Yt=Xt/StY_t=X_t/S_t, the vector of patch proportions, converges in law to a random vector YY_\infty as tt\to\infty, and the stochastic growth rate limtt1logSt\lim_{t\to\infty}t^{-1}\log S_t equals the space-time average per-capita growth rate \sum_i\mu_i\E[Y_\infty^i] experienced by the population minus half of the space-time average temporal variation \E[\sum_{i,j}\sigma_{ij}Y_\infty^i Y_\infty^j] experienced by the population. We derive analytic results for the law of YY_\infty, find which choice of the dispersal mechanism DD produces an optimal stochastic growth rate for a freely dispersing population, and investigate the effect on the stochastic growth rate of constraints on dispersal rates. Our results provide fundamental insights into "ideal free" movement in the face of uncertainty, the persistence of coupled sink populations, the evolution of dispersal rates, and the single large or several small (SLOSS) debate in conservation biology.Comment: 47 pages, 4 figure

    Distinctive features of the microbiota associated with different forms of apical periodontitis

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    Microorganisms infecting the dental root canal system play an unequivocal role as causative agents of apical periodontitis. Although fungi, archaea, and viruses have been found in association with some forms of apical periodontitis, bacteria are the main microbial etiologic agents of this disease. Bacteria colonizing the root canal are usually organized in communities similar to biofilm structures. Culture and molecular biology technologies have demonstrated that the endodontic bacterial communities vary in species richness and abundance depending on the different types of infection and different forms of apical periodontitis. This review paper highlights the distinctive features of the endodontic microbiota associated with diverse clinical conditions

    Towards modeling the retailer as a brand: A social construction of the grocery store from the customer standpoint

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    As a highly customer-sensitive business, retailing is one of the most socially active industries. Nevertheless, when addressing retailers as brands, the retailing literature has failed to account for their unique social orientation, exposing a gap in the literature. This paper utilizes the sociological view of brands to socially construct a conceptual retail brand model from the customer standpoint. An ethnographic study of grocery retailing revealed that the store has, metaphorically, a tree-shaped culture, which can organically model the interplay between building the retailer brand as a culture and the phases constituting the social-self concept

    Neural Network Mechanisms Underlying Stimulus Driven Variability Reduction

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    It is well established that the variability of the neural activity across trials, as measured by the Fano factor, is elevated. This fact poses limits on information encoding by the neural activity. However, a series of recent neurophysiological experiments have changed this traditional view. Single cell recordings across a variety of species, brain areas, brain states and stimulus conditions demonstrate a remarkable reduction of the neural variability when an external stimulation is applied and when attention is allocated towards a stimulus within a neuron's receptive field, suggesting an enhancement of information encoding. Using an heterogeneously connected neural network model whose dynamics exhibits multiple attractors, we demonstrate here how this variability reduction can arise from a network effect. In the spontaneous state, we show that the high degree of neural variability is mainly due to fluctuation-driven excursions from attractor to attractor. This occurs when, in the parameter space, the network working point is around the bifurcation allowing multistable attractors. The application of an external excitatory drive by stimulation or attention stabilizes one specific attractor, eliminating in this way the transitions between the different attractors and resulting in a net decrease in neural variability over trials. Importantly, non-responsive neurons also exhibit a reduction of variability. Finally, this reduced variability is found to arise from an increased regularity of the neural spike trains. In conclusion, these results suggest that the variability reduction under stimulation and attention is a property of neural circuits

    Planetary science and exploration in the deep subsurface: results from the MINAR Program, Boulby Mine, UK

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    The subsurface exploration of other planetary bodies can be used to unravel their geological history and assess their habitability. On Mars in particular, present-day habitable conditions may be restricted to the subsurface. Using a deep subsurface mine, we carried out a program of extraterrestrial analog research – MINe Analog Research (MINAR). MINAR aims to carry out the scientific study of the deep subsurface and test instrumentation designed for planetary surface exploration by investigating deep subsurface geology, whilst establishing the potential this technology has to be transferred into the mining industry. An integrated multi-instrument suite was used to investigate samples of representative evaporite minerals from a subsurface Permian evaporite sequence, in particular to assess mineral and elemental variations which provide small-scale regions of enhanced habitability. The instruments used were the Panoramic Camera emulator, Close-Up Imager, Raman spectrometer, Small Planetary Linear Impulse Tool, Ultrasonic drill and handheld X-ray diffraction (XRD). We present science results from the analog research and show that these instruments can be used to investigate in situ the geological context and mineralogical variations of a deep subsurface environment, and thus habitability, from millimetre to metre scales. We also show that these instruments are complementary. For example, the identification of primary evaporite minerals such as NaCl and KCl, which are difficult to detect by portable Raman spectrometers, can be accomplished with XRD. By contrast, Raman is highly effective at locating and detecting mineral inclusions in primary evaporite minerals. MINAR demonstrates the effective use of a deep subsurface environment for planetary instrument development, understanding the habitability of extreme deep subsurface environments on Earth and other planetary bodies, and advancing the use of space technology in economic mining

    Predicted Impact of Barriers to Migration on the Serengeti Wildebeest Population

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    The Serengeti wildebeest migration is a rare and spectacular example of a once-common biological phenomenon. A proposed road project threatens to bisect the Serengeti ecosystem and its integrity. The precautionary principle dictates that we consider the possible consequences of a road completely disrupting the migration. We used an existing spatially-explicit simulation model of wildebeest movement and population dynamics to explore how placing a barrier to migration across the proposed route (thus creating two disjoint but mobile subpopulations) might affect the long-term size of the wildebeest population. Our simulation results suggest that a barrier to migration—even without causing habitat loss—could cause the wildebeest population to decline by about a third. The driver of this decline is the effect of habitat fragmentation (even without habitat loss) on the ability of wildebeest to effectively track temporal shifts in high-quality forage resources across the landscape. Given the important role of the wildebeest migration for a number of key ecological processes, these findings have potentially important ramifications for ecosystem biodiversity, structure, and function in the Serengeti
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