An Updated Algorithm for the Generation of Neutral Landscapes by Spectral Synthesis

Background: Patterns that arise from an ecological process can be driven as much from the landscape over which the process is run as it is by some intrinsic properties of the process itself. The disentanglement of these effects is aided if it possible to run models of the process over artificial landscapes with controllable spatial properties. A number of different methods for the generation of so-called ‘neutral landscapes’ have been developed to provide just such a tool. Of these methods, a particular class that simulate fractional Brownian motion have shown particular promise. The existing methods of simulating fractional Brownian motion suffer from a number of problems however: they are often not easily generalisable to an arbitrary number of dimensions and produce outputs that can exhibit some undesirable artefacts. Methodology: We describe here an updated algorithm for the generation of neutral landscapes by fractional Brownian motion that do not display such undesirable properties. Using Monte Carlo simulation we assess the anisotropic properties of landscapes generated using the new algorithm described in this paper and compare it against a popular benchmark algorithm. Conclusion/Significance: The results show that the existing algorithm creates landscapes with values strongly correlated in the diagonal direction and that the new algorithm presented here corrects this artefact. A number of extensions of the algorithm described here are also highlighted: we describe how the algorithm can be employed to generate landscapes that display different properties in different dimensions and how they can be combined with an environmental gradient to produce landscapes that combine environmental variation at the local and macro scales

Temporal variance of disturbance did not affect diversity and structure of a marine fouling community in north-eastern New Zealand

Natural heterogeneity in ecological parameters, like population abundance, is more widely recognized and investigated than variability in the processes that control these parameters. Experimental ecologists have focused mainly on the mean intensity of predictor variables and have largely ignored the potential to manipulate variances in processes, which can be considered explicitly in experimental designs to explore variation in causal mechanisms. In the present study, the effect of the temporal variance of disturbance on the diversity of marine assemblages was tested in a field experiment replicated at two sites on the northeast coast of New Zealand. Fouling communities grown on artificial settlement substrata experienced disturbance regimes that differed in their inherent levels of temporal variability and timing of disturbance events, while disturbance intensity was identical across all levels. Additionally, undisturbed assemblages were used as controls. After 150 days of experimental duration, the assemblages were then compared with regard to their species richness, abundance and structure. The disturbance effectively reduced the average total cover of the assemblages, but no consistent effect of variability in the disturbance regime on the assemblages was detected. The results of this study were corroborated by the outcomes from simultaneous replicate experiments carried out in each of eight different biogeographical regions around the world

Testing Evolutionary and Dispersion Scenarios for the Settlement of the New World

Background: Discussion surrounding the settlement of the New World has recently gained momentum with advances in molecular biology, archaeology and bioanthropology. Recent evidence from these diverse fields is found to support different colonization scenarios. The currently available genetic evidence suggests a ""single migration'' model, in which both early and later Native American groups derive from one expansion event into the continent. In contrast, the pronounced anatomical differences between early and late Native American populations have led others to propose more complex scenarios, involving separate colonization events of the New World and a distinct origin for these groups. Methodology/Principal Findings: Using large samples of Early American crania, we: 1) calculated the rate of morphological differentiation between Early and Late American samples under three different time divergence assumptions, and compared our findings to the predicted morphological differentiation under neutral conditions in each case; and 2) further tested three dispersal scenarios for the colonization of the New World by comparing the morphological distances among early and late Amerindians, East Asians, Australo-Melanesians and early modern humans from Asia to geographical distances associated with each dispersion model. Results indicate that the assumption of a last shared common ancestor outside the continent better explains the observed morphological differences between early and late American groups. This result is corroborated by our finding that a model comprising two Asian waves of migration coming through Bering into the Americas fits the cranial anatomical evidence best, especially when the effects of diversifying selection to climate are taken into account. Conclusions: We conclude that the morphological diversity documented through time in the New World is best accounted for by a model postulating two waves of human expansion into the continent originating in East Asia and entering through Beringia.Fondo Nacional de Desarrollo Cientifico y Tecnologico (FONDECYT)[11070091]Fundacao de Amparo a Ciencia do Estado de Sao Paulo (FAPESP)[04/01253-0]Conselho Nacional de Pesquisa (CNPq)[301126-04.6]Max Planck GesellschaftEVAN Marie Curie Research Training Network[MRTN-CT-019564

Landscape Ecology of Sylvatic Chikungunya Virus and Mosquito Vectors in Southeastern Senegal

The risk of human infection with sylvatic chikungunya (CHIKV) virus was assessed in a focus of sylvatic arbovirus circulation in Senegal by investigating distribution and abundance of anthropophilic Aedes mosquitoes, as well as the abundance and distribution of CHIKV in these mosquitoes. A 1650 km2 area was classified into five land cover classes: forest, barren, savanna, agriculture and village. A total of 39,799 mosquitoes was sampled from all classes using human landing collections between June 2009 and January 2010. Mosquito diversity was extremely high, and overall vector abundance peaked at the start of the rainy season. CHIKV was detected in 42 mosquito pools. Our data suggest that Aedes furcifer, which occurred abundantly in all land cover classes and landed frequently on humans in villages outside of houses, is probably the major bridge vector responsible for the spillover of sylvatic CHIKV to humans

Global diversity and biogeography of deep-sea pelagic prokaryotes

The deep-sea is the largest biome of the biosphere, and contains more than half of the whole ocean/'s microbes. Uncovering their general patterns of diversity and community structure at a global scale remains a great challenge, as only fragmentary information of deep-sea microbial diversity exists based on regional-scale studies. Here we report the first globally comprehensive survey of the prokaryotic communities inhabiting the bathypelagic ocean using high-throughput sequencing of the 16S rRNA gene. This work identifies the dominant prokaryotes in the pelagic deep ocean and reveals that 50{\%} of the operational taxonomic units (OTUs) belong to previously unknown prokaryotic taxa, most of which are rare and appear in just a few samples. We show that whereas the local richness of communities is comparable to that observed in previous regional studies, the global pool of prokaryotic taxa detected is modest (\~{}3600 OTUs), as a high proportion of OTUs are shared among samples. The water masses appear to act as clear drivers of the geographical distribution of both particle-attached and free-living prokaryotes. In addition, we show that the deep-oceanic basins in which the bathypelagic realm is divided contain different particle-attached (but not free-living) microbial communities. The combination of the aging of the water masses and a lack of complete dispersal are identified as the main drivers for this biogeographical pattern. All together, we identify the potential of the deep ocean as a reservoir of still unknown biological diversity with a higher degree of spatial complexity than hitherto considered.En prensa8,951

Stimulant Reduction Intervention using Dosed Exercise (STRIDE) - CTN 0037: Study protocol for a randomized controlled trial

<p>Abstract</p> <p>Background</p> <p>There is a need for novel approaches to the treatment of stimulant abuse and dependence. Clinical data examining the use of exercise as a treatment for the abuse of nicotine, alcohol, and other substances suggest that exercise may be a beneficial treatment for stimulant abuse, with direct effects on decreased use and craving. In addition, exercise has the potential to improve other health domains that may be adversely affected by stimulant use or its treatment, such as sleep disturbance, cognitive function, mood, weight gain, quality of life, and anhedonia, since it has been shown to improve many of these domains in a number of other clinical disorders. Furthermore, neurobiological evidence provides plausible mechanisms by which exercise could positively affect treatment outcomes. The current manuscript presents the rationale, design considerations, and study design of the National Institute on Drug Abuse (NIDA) Clinical Trials Network (CTN) CTN-0037 Stimulant Reduction Intervention using Dosed Exercise (STRIDE) study.</p> <p>Methods/Design</p> <p>STRIDE is a multisite randomized clinical trial that compares exercise to health education as potential treatments for stimulant abuse or dependence. This study will evaluate individuals diagnosed with stimulant abuse or dependence who are receiving treatment in a residential setting. Three hundred and thirty eligible and interested participants who provide informed consent will be randomized to one of two treatment arms: Vigorous Intensity High Dose Exercise Augmentation (DEI) or Health Education Intervention Augmentation (HEI). Both groups will receive TAU (i.e., usual care). The treatment arms are structured such that the quantity of visits is similar to allow for equivalent contact between groups. In both arms, participants will begin with supervised sessions 3 times per week during the 12-week acute phase of the study. Supervised sessions will be conducted as one-on-one (i.e., individual) sessions, although other participants may be exercising at the same time. Following the 12-week acute phase, participants will begin a 6-month continuation phase during which time they will attend one weekly supervised DEI or HEI session.</p> <p>Clinical Trials Registry</p> <p>ClinicalTrials.gov, <a href="http://www.clinicaltrials.gov/ct2/show/NCT01141608">NCT01141608</a></p> <p><url>http://clinicaltrials.gov/ct2/show/NCT01141608?term=Stimulant+Reduction+Intervention+using+Dosed+Exercise&rank=1</url></p

Stochastic isotropic hyperelastic materials: constitutive calibration and model selection

Biological and synthetic materials often exhibit intrinsic variability in their elastic responses under large strains, due to microstructural inhomogeneity or when elastic data are extracted from viscoelastic mechanical tests. For these materials, although hyperelastic models calibrated to mean data are useful, stochastic representations accounting also for data dispersion carry extra information about the variability of material properties found in practical applications. We combine finite elasticity and information theories to construct homogeneous isotropic hyperelastic models with random field parameters calibrated to discrete mean values and standard deviations of either the stress-strain function or the nonlinear shear modulus, which is a function of the deformation, estimated from experimental tests. These quantities can take on different values, corresponding to possible outcomes of the experiments. As multiple models can be derived that adequately represent the observed phenomena, we apply Occam’s razor by providing an explicit criterion for model selection based on Bayesian statistics. We then employ this criterion to select a model among competing models calibrated to experimental data for rubber and brain tissue under single or multiaxial loads