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373 results for “stochastic”
Data from: A stochastic generative model for citation networks among academic papers
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Data and scripts from: Experimental evidence of size-selective harvest and environmental stochasticity effects on population demography, fluctuations, and nonlinearity
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Stochastic Modeling of Subglacial Topography Exposes Uncertainty in Water Routing at Jakobshavn Glacier
<p>Abstract:</p> <p>These data products accompany the paper "Stochastic Modeling of Subglacial Topography Exposes Uncertainty in Water Routing at Jakobshavn Glacier" (MacKie et al., in review). In this study, geostatistical techniques were used to generate an ensemble of topographic realizations that retain the spatial statistics of radar bed elevation measurements. The simulation was conditioned to local radar data and mass conservation bed estimates. This repository contains the radar and mass conservation conditioning data, the ensemble of topographic realizations, and coordinate data.</p> <p> </p> <p>Content and processing steps:</p> <p>The study area is 75.15 x 48.90 km^2. The grid cell resolution is 150 meters. Each digital elevation model (DEM) has 501 x 326 grid cells. The mass conservation DEM was obtained from BedMachine Greenland (Morlighem and others, 2017). The radar data were acquired from the Center for Remote Sensing of Ice Sheets (CReSIS) 2009 flights (Gogineni, 2012; Gogineni and others, 2014). A probabilistic modeling technique called sequential Gaussian co-simulation (Verly, 1993; Almeida and Journel, 1994; Journel, 1999; Remy, 2005) was used to generate the topographic realizations. The datasets are as follows:</p> <p> </p> <p>1) Jakobshavn_mass_conservation.txt - Mass conservation conditioning data</p> <p>2) Jakobshavn_radar_data.txt - Radar conditioning data</p> <p>3) Jakobshavn_simulation.txt - 250 topographic realizations. The shape of this file is 250 x 163326, where each column corresponds to one topographic realization. Each column should be reshaped to 501 x 326 to view the DEM.</p> <p>4) Jakobshavn_x_data.txt - Polar stereographic X coordinates in meters</p> <p>5) Jakobshavn_y_data.txt - Polar stereographic Y coordinates in meters</p> <p> </p> <p>References:</p> <p>Almeida, A. S., & Journel, A. G. (1994). Joint simulation of multiple variables with a Markov-type coregionalization model. <em>Mathematical Geology</em>, <em>26</em>(5), 565-588.</p> <p>Gogineni, P. (2012). CReSIS radar depth sounder data. <em>Center for Remote Sensing of Ice Sheets, Lawrence, KS https://data. cresis.-ku. edu</em>.</p> <p>Gogineni, S., Yan, J. B., Paden, J., Leuschen, C., Li, J., Rodriguez-Morales, F., ... & Gauch, J. (2014). Bed topography of Jakobshavn Isbræ, Greenland, and Byrd Glacier, Antarctica. <em>Journal of Glaciology</em>, <em>60</em>(223), 813-833.</p> <p>Journel, A. G. (1999). Markov models for cross-covariances. <em>Mathematical Geology</em>, <em>31</em>(8), 955-964.</p> <p>Morlighem, M., Williams, C. N., Rignot, E., An, L., Arndt, J. E., Bamber, J. L., ... & Fenty, I. (2017). BedMachine v3: Complete bed topography and ocean bathymetry mapping of Greenland from multibeam echo sounding combined with mass conservation. <em>Geophysical research letters</em>, <em>44</em>(21), 11-051.</p> <p>Remy, N. (2005). S-GeMS: the stanford geostatistical modeling software: a tool for new algorithms development. In <em>Geostatistics banff 2004</em> (pp. 865-871). Springer, Dordrecht.</p> <p>Verly, G. W. (1993). Sequential Gaussian cosimulation: a simulation method integrating several types of information. In <em>Geostatistics Troia’92</em> (pp. 543-554). Springer, Dordrecht.</p>
Pressure control using stochastic cell rescaling - dataset
<p>Supporting data related to manuscript "Pressure control using stochastic cell rescaling"</p>
Data from: A comment on the use of stochastic character maps to estimate evolutionary rate variation in a continuously valued trait
Phylogenetic comparative biology has progressed considerably in recent years. One of the most important developments has been the application of likelihood-based methods to fit alternative models for trait evolution in a phylogenetic tree with branch lengths proportional to time. An important example of this type of method is O'Meara et al.'s (2006) "noncensored" test for variation in the evolutionary rate for a continuously valued character trait through time or across the branches of a phylogenetic tree. According to this method, we first hypothesize evolutionary rate regimes on the tree (called "painting" in Butler and King, 2004); and then we fit an evolutionary model, specifically the popular Brownian model, in which the instantaneous variance of the Brownian random diffusion process has different values in different parts of the phylogeny. The authors suggest that to test a hypothesis that the state of a discrete character influenced the rate of a continuous character, one could use the approach of Neilsen (2002) to first stochastically map the discretely valued trait, and then "test to see whether the portions of the tree with one state for the discrete character have a different rate of evolution for the continuous character than portions of the tree to which the other discrete state has been mapped" (O'Meara et al., 2006, p. 931). Indeed, this has become common practice for this and other closely related methods. Here, I examine this practice. In particular, I show that evolutionary rates estimated this way (i.e., by using maximum likelihood [ML] to fit a multirate model on each stochastically mapped tree; and then averaging across trees) are systematically biased to be more similar to each other than are the underlying generating parameters. My analysis also reveals that this effect is dependent on the rate of evolution for the discrete trait. Specifically, if the rate of evolution for the discrete character is low then the difference between the true history and any stochastically mapped 1 history is generally small. This results in evolutionary rates for the continuous trait that are estimated with little bias. Conversely, if the rate of evolution for the discrete character is very high, then the true and hypothesized character histories are often extremely dissimilar, evolutionary rate estimates are biased to be more similar to each other than their underlying generating values, and we lose power to distinguish evolutionary rates on the tree.
Data from: Sex in an uncertain world: environmental stochasticity helps restore competitive balance between sexually and asexually reproducing populations
Like many organisms, individuals of the freshwater ostracod species Eucypris virens can have either obligate sexual or asexual reproductive modes. Both types of individual routinely co-occur, including in the same temporary freshwater pond (their natural habitat in which they undergo seasonal diapause). Given the well-known two-fold cost of sex, this begs the question of how sexually reproducing individuals are able to co-exist with their asexual counterparts in spite of such overwhelming costs. Environmental stochasticity in the form of "false dawn" inundations (where the first hydration is ephemeral and causes loss of early hatching individuals) may provide an advantage to the sexual subpopulation, which exhibits greater variation in hatching times following inundation. We explore the potential role of environmental stochasticity in this system using life-history data analysis, climate data and matrix projection models. In the absence of environmental stochasticity, the population growth rate is significantly lower in sexual subpopulations. Climate data reveal that "false dawn" inundations are common. Using matrix projection modeling with and without environmental stochasticity, we demonstrate that this phenomenon can restore appreciable balance to the system, in terms of growth rates. This provides support for the role of environmental stochasticity in helping to explain the maintenance of sex and the occurrence of geographic parthenogenesis.
Data from: A stochastic rate-calibrated method for time-scaling phylogenies of fossil taxa
1.) Applying phylogeny-based analyses of trait evolution and diversification in the fossil record generally involves transforming an unscaled cladogram into a phylogeny scaled to geologic time. Current methods produce single time-scaled phylogenies with artificial zero-length branches and no indication of the uncertainty in the temporal relationships. 2.) Here I present a stochastic algorithm for time-scaling phylogenies of fossil taxa by randomly sampling node ages from a constrained distribution, with the ultimate goal of producing large samples of time-scaled phylogenies for a given dataset as the basis for phylogeny-based analyses. I describe how this stochastic approach can be extended to consider potential ancestral relationships and resolve polytomies. 3) The stochastic selection of node ages in this algorithm is weighted by the probability density of the total inferable unobserved evolutionary history at single divergence events in a tree, a distribution dependent on rates of branching, extinction and sampling in the fossil record. 4) The combined time-scaling method must be calibrated with explicit estimates of three rates: branching, extinction and sampling, and thus is named the cal3 time-scaling method, included in the R library paleotree. I test the time-scaling capabilities of the cal3 and older time-scaling methods in simulations. cal3 produces samples of time-scaled trees that better bracket the uncertainty in the true node ages than existing time-scaling methods. This is true even in simulations under a 'terminal-taxon' model of differentiation that violates many of the assumptions of the cal3 method. 5) The cal3 method provides a new approach for time-scaling paleontological cladograms, calibrated to estimated sampling and diversification rates, allowing for better estimates of uncertainty in the phylogenetic time-scaling. The cal3 method is robust to relaxation of at least some model assumptions. Additional work is needed to analyze the impact of time-scaling approaches on macroevolutionary analyses and to integrate time-scaling with phylogenetic inference.
Data from: Within-host stochastic emergence dynamics of immune-escape mutants
Predicting the emergence of new pathogenic strains is a key goal of evolutionary epidemiology. However, the majority of existing studies have focussed on emergence at the population level, and not within a host. In particular, the coexistence of pre-existing and mutated strains triggers a heightened immune response due to the larger total pathogen population; this feedback can smother mutated strains before they reach an ample size and establish. Here, we extend previous work for measuring emergence probabilities in non-equilibrium populations, to within-host models of acute infections. We create a mathematical model to investigate the emergence probability of a fitter strain if it mutates from a self-limiting strain that is guaranteed to go extinct in the long-term. We show that ongoing immune cell proliferation during the initial stages of infection causes a drastic reduction in the probability of emergence of mutated strains; we further outline how this effect can be accurately measured. Further analysis of the model shows that, in the short-term, mutant strains that enlarge their replication rate due to evolving an increased growth rate are more favoured than strains that suffer a lower immune-mediated death rate ('immune tolerance'), as the latter does not completely evade ongoing immune proliferation due to inter-parasitic competition. We end by discussing the model in relation to within-host evolution of human pathogens (including HIV, hepatitis C virus, and cancer), and how ongoing immune growth can affect their evolutionary dynamics.
Data from: Demographic stochasticity alters expected outcomes in experimental and simulated non-neutral communities
Theory has shown that the effects of demographic stochasticity on communities may depend on the magnitude of fitness differences between species. In particular, it has been suggested that demographic stochasticity has the potential to significantly alter competitive outcomes when fitness differences are small (nearly neutral), but that it has minimal effects when fitness differences are large (highly non-neutral). Here we test such theory experimentally and extend it to examine how demographic stochasticity affects exclusion frequency and mean densities of consumers in simple, but non-neutral, consumer-resource communities. We used experimental microcosms of protists and rotifers feeding on a bacterial resource to test how varying absolute population sizes (a driver of demographic stochasticity) affected the probability of competitive exclusion of the weakest competitor. To explore whether demographic stochasticity could explain our experimental results, and to generalize beyond our experiment, we paired the experiment with a continuous-time stochastic model of resource competition, which we simulated for 11 different fitness inequalities between competiting consumers. Consistent with theory, in both our experiments and our simulations we found that demographic stochasticity altered competitive outcomes in communities where fitness differences were small. However, we also found that demographic stochasticity alone could affect communities in other ways, even when fitness differences between competitors were large. Specifically, demographic stochasticity altered mean densities of both weak and strong competitors in experimental and simulated communities. These findings highlight how demographic stochasticity can change both competitive outcomes in non-neutral communities and the processes underlying overall community dynamics.
Data from: Congestion reduction through efficient container movement under stochastic demand
<p>In today's world, there is a significant amount of investigation regarding how to efficiently distribute loaded containers from the ports to the consignees. However, to fully maximize the process and become more environmentally friendly, one should also study how to allocate the empty containers created by these consignees. This is an essential part in the study of container movement since it balances out the load flow at each location.</p> <p>The problem of coordinating the container movement to reuse empty containers and lower truck miles is called the "Empty Container Problem". In this work, we develop a scheduling assignment for loaded and empty containers that builds on earlier models but incorporates stochastic (random) future demand. It is worth mentioning that in the previous research [5], the empty container problem was divided into two subproblems, including an assignment problem and a vehicle routing problem (VRP).</p> <p>The previous research only considered the problem as a one-day horizon. But in reality, the container movements are not only to fulfill today's demand at each location but also prepare for the next day's delivery. Thus, incorporating future demand is an essential aspect of the problem.</p> <p>By considering the future demand, a better solution can be constructed compared to solving the problem as a one-day horizon problem. This report shows that the truck miles needed to satisfy the demand at all locations is reduced by about 4-7% when considering future stochastic demand as opposed to only considering today's demand, thus, leading to a cleaner and greener solution, creating less congestion and lowering the impact of freight movement on the environment.</p>
Data from: Increasing phylogenetic stochasticity at high elevations on summits across a remote North American wilderness
At the intersection of ecology and evolutionary biology, community phylogenetics can provide insights into overarching biodiversity patterns, particularly in remote and understudied ecosystems. To understand community assembly of the high-alpine flora of the Sawtooth National Forest, USA, we analyzed phylogenetic structure within and between nine summit communities. We used high-throughput sequencing to supplement existing data and infer a nearly completely sampled community phylogeny of the alpine vascular flora. We calculated mean nearest taxon distance (MNTD) and mean pairwise distance (MPD) to quantify phylogenetic divergence within summits, and assessed whether maximum elevation explains phylogenetic structure. To evaluate similarities between summits we quantified phylogenetic turnover, taking into consideration micro-habitats (talus vs. meadows). We found different patterns of community phylogenetic structure within the six most species-rich orders, but across all vascular plants phylogenetic structure was largely not different from random. There was a significant negative correlation between elevation and tree-wide phylogenetic diversity (MPD) within summits: overdispersion degraded as elevation increased. Between summits we found high phylogenetic turnover, which was driven by greater niche heterogeneity on summits with alpine meadows. This study provides further evidence that stochastic processes may also play an important role in the assembly of vascular plant communities in the high-alpine at regional scales. However, order-specific patterns suggest that adaptations are still important for assembly of specific sectors of the plant tree of life. Further studies quantifying functional diversity will be important to disentangle the interplay of eco-evolutionary processes that likely shape broad community phylogenetic patterns in extreme environments. Please be aware that if you ask to have your user record removed, we will retain your name in the records concerning manuscripts for which you were an author, reviewer, or editor. In compliance with data protection regulations, you may request that we remove your personal registration details at any time. (Use the following URL: https://www.editorialmanager.com/ajb/login.asp?a=r) Please contact the publication office if you have any questions.
Data from: Stochastic faunal exchanges drive diversification in widespread Wallacean and Pacific island lizards (Squamata: Scincidae: Lamprolepis smaragdina)
Aim: Widespread species found in disturbed habitats are often expected to be human commensals. In island systems, this association predicts that dispersal will be mediated by humans. We investigated the biogeographical relationships among populations of a widespread tree skink that inhabits coastal forest and human-cultivated plantations in Southeast Asia. We sought to determine whether populations of the emerald tree skink, Lamprolepis smaragdina, dis- persed via mechanisms that were not human-mediated ('natural' dispersal) or whether dispersal was mediated by humans. The latter scenario predicts low levels of genetic differentiation across a species' range, coupled with a genetic signature of recent range expansion. Location: Southeast Asia, the Philippines, Wallacea and the south-western Pacific. Methods: We analysed sequences of mitochondrial DNA from 204 samples collected throughout the range of this species. We use phylogenetic and popu- lation genetic methods to distinguish between predicted geographical patterns of genetic variation that might indicate natural or human-mediated dispersal. Results: In contrast to predictions derived from similar studies of taxonomy and natural history, we found L. smaragdina to be characterized by highly structured and seemingly geographically stable mitochondrial gene lineages. Main conclusions: Our results demonstrate a novel pattern of widespread species distribution, never before observed in vertebrates of the Indo-Australian Archipelago. Although this widespread and highly dispersive species is capable of long-distance dispersal, and has a clear history of over-water dispersal, it exhibits sharp genetic differentiation across its range. Our results suggest that random waif dispersal has been a pervasive ongoing phenomenon throughout the evolutionary history of this species.
Data from: Individual variation, population-specific behaviours, and stochastic processes shape marine migration phenologies
1. The phenology of long distance migrations can influence individual fitness, moderate population dynamics, and regulate the availability of ecosystem services to other trophic levels. Phenology varies within and among populations, and can be influenced by conditions individuals experience both prior to departure and encounter en route. 2. Assessing how intrinsic and extrinsic factors (e.g. individual physical condition vs. environmental conditions) interact to influence variation in migratory phenologies across ecological scales is often limited due to logistical constraints associated with tracking large numbers of individuals from multiple populations simultaneously. 3. We used two natural tags, DNA and otolith microstructure analysis, to estimate the relative influence of individual traits (life history strategy, body size at departure, and growth during migration), population-specific strategies, and interannual variability on the phenology of marine migrations in juvenile sockeye salmon Oncorhynchus nerka. 4. We show that the timing and duration of juvenile sockeye salmon migrations were correlated with both life history strategy and body size, while migration duration was also correlated with departure timing and growth rates during migration. Even after accounting for the effect of individual traits, several populations exhibited distinct migration phenologies. Finally, we observed substantial interannual and residual variation, suggesting stochastic environmental conditions moderate the influence of carry-over effects that develop prior to departure, as well as population-specific strategies. 5. Migratory phenologies are shaped by complex interactions between drivers acting at multiple ecological and temporal scales. Given evidence that intraspecific diversity can stabilize ecological systems, conservation efforts should seek to maintain migratory variation among populations and preserve locally adapted phenotypes; however, variation within populations, which may buffer systems from environmental stochasticity, should also be regularly assessed and preserved.
Data from: Stochastic character mapping of state-dependent diversification reveals the tempo of evolutionary decline in self-compatible Onagraceae lineages
A major goal of evolutionary biology is to identify key evolutionary transitions that correspond with shifts in speciation and extinction rates. Stochastic character mapping has become the primary method used to infer the timing, nature, and number of character state transitions along the branches of a phylogeny. The method is widely employed for standard substitution models of character evolution. However, current approaches cannot be used for models that specifically test the association of character state transitions with shifts in diversification rates such as state-dependent speciation and extinction (SSE) models. Here we introduce a new stochastic character mapping algorithm that overcomes these limitations, and apply it to study mating system evolution over a time-calibrated phylogeny of the plant family Onagraceae. Utilizing a hidden state SSE model we tested the association of the loss of self-incompatibility with shifts in diversification rates. Confirming long standing theory, we found that self-compatible lineages have higher extinction rates and lower net diversification rates compared to self-incompatible lineages. Furthermore, these results provide empirical evidence for the "senescing" diversification rates predicted in highly selfing lineages: our mapped character histories show that the loss of self-incompatibility is followed by a short-term spike in speciation rates, which declines after a time lag of several million years resulting in negative net diversification. Lineages that have long been self-compatible such as Fuchsia and Clarkia are in a previously unrecognized and ongoing evolutionary decline. Our results demonstrate that stochastic character mapping of SSE models is a powerful tool for examining the timing and nature of both character state transitions and shifts in diversification rates over the phylogeny.
Data from: A stochastic model for annual reproductive success
Demographic stochasticity can have large effects on the dynamics of small populations as well as on the persistence of rare genotypes and lineages. Survival is sensibly modeled as a binomial process, but annual reproductive success (ARS) is more complex and general models for demographic stochasticity do not exist. Here we introduce a stochastic model framework for ARS and illustrate some of its properties. We model a sequence of stochastic events: nest completion, the number of eggs or neonates produced, nest predation, and the survival of individual offspring to independence. We also allow multiple nesting attempts within a breeding season. Most of these components can be described by Bernoulli or binomial processes; the exception is the distribution of offspring number. Using clutch and litter size distributions from 53 vertebrate species, we demonstrate that among‐individual variability in offspring number can usually be described by the generalized Poisson distribution. Our model framework allows the demographic variance to be calculated from underlying biological processes and can easily be linked to models of environmental stochasticity or selection because of its parametric structure. In addition, it reveals that the distributions of ARS are often multimodal and skewed, with implications for extinction risk and evolution in small populations.
Data from: Experiments and modelling of rate-dependent transition delay in a stochastic subcritical bifurcation
Complex systems exhibiting critical transitions when one of their governing parameters varies are ubiquitous in nature and in engineering applications. Despite a vast literature focusing on this topic, there are few studies dealing with the effect of the rate of change of the bifurcation parameter on the tipping points. In this work, we consider a subcritical stochastic Hopf bifurcation under two scenarios: the bifurcation parameter is first changed in a quasi-steady manner and then, with a finite ramping rate. In the latter case, a rate-dependent bifurcation delay is observed and exemplified experimentally using a thermoacoustic instability in a combustion chamber. This delay increases with the rate of change. This leads to a state transition of larger amplitude compared to the one that would be experienced by the system with a quasi-steady change of the parameter. We also bring experimental evidence of a dynamic hysteresis caused by the bifurcation delay when the parameter is ramped back. A surrogate model is derived in order to predict the statistic of these delays and to scrutinise the underlying stochastic dynamics. Our study highlights the dramatic influence of a finite rate of change of bifurcation parameters upon tipping points and it pinpoints the crucial need of considering this effect when investigating critical transitions.
Computer codes (in Python) for 'The reproduction number and its probability distribution for stochastic viral dynamics'
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STOCHASTIC COMPETENCE OF THE FUTURE MATHEMATICS TEACHER.
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Koopman-based Control for Stochastic Systems: Application to Enhanced Sampling
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Data and climate variable selection from: Effects of density, species interactions and environmental stochasticity on the dynamics of British bird communities
<p>Our knowledge of the factors affecting species abundances is mainly based on time-series analyses of a few well-studied species at single or few localities, but we know little about whether results from such analyses can be extrapolated to the community level. We apply a Joint Species Distribution Model to long-term time-series data on British bird communities to examine the relative contribution of intra- and interspecific density dependence at different spatial scales, as well as the influence of environmental stochasticity, to spatio-temporal interspecific variation in abundance. Intraspecific density dependence has the major structuring effect on these bird communities. In addition, environmental fluctuations affect spatiotemporal differences in abundance. In contrast, species interactions had a minor impact on variation in abundance. Thus, important drivers of single-species dynamics are also strongly affecting dynamics of communities in time and space.</p>
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.