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373 results for “stochastic”
A stochastic framework for predicting epidemiological risk areas using the Ornstein-Uhlenbeck process: Software and supplementary material
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Data from: Interacting effects of unobserved heterogeneity and individual stochasticity in the life-history of the Southern fulmar
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Data from: The effect of demographic correlations on the stochastic population dynamics of perennial plants
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The cost of noise: Stochastic punishment falls short of sustaining cooperation in social dilemma experiments
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Simulation scripts and data for the stochastic modelling of evolutionary rescue in resistance to pesticides
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Ungulate herbivores promote beta diversity and drive stochastic plant community assembly by selective defoliation and trampling: From a four-year simulation experiment
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Data and code for: The role of indirect interspecific effects in the stochastic dynamics of a simple trophic system
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Stochastic hydro-financial watershed modeling for environmental impact bonds
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Data and code for: Stochastic bacterial population dynamics restrict the establishment of antibiotic resistance from single cells
<p>This dataset contains experimental data and custom R code for likelihood-based model-fitting associated with the manuscript "Stochastic bacterial population dynamics restrict the establishment of antibiotic resistance from single cells". In particular, we estimate the per-cell establishment probability (i.e. probability that a single cell gives rise to a large population) of a resistant strain, in the presence of antibiotics at concentrations below its standard minimum inhibitory concentration. The experiments are conducted here with <em>Pseudomonas aeruginosa</em>, while the model and methods can be applied more generally.</p>
Stochastic processes and ecological connectivity drive stream invertebrate community responses to short-term drought
1. Community responses to and recovery from disturbances depend on local (e.g. presence of refuges) and regional (connectivity to recolonization sources) factors. Droughts are becoming more frequent in boreal regions, and are likely to constitute a severe disturbance for boreal stream communities where organisms largely lack adaptations to such hydrological extremes. 2. We conducted an experiment in 24 seminatural stream flumes to assess the effects of local and regional factors on the responses of benthic invertebrate communities to a short-term drought. We manipulated flow (drought vs. constant-flow), spatial arrangement of leaf litter patches (aggregated vs. evenly distributed) and colonization from regional species pool (enhanced vs. ambient connectivity) to test the combined effects of disturbance, connectivity, and resource arrangement on the structural and functional responses of benthic invertebrate communities. 3. We found that a drought as short as one week reduced invertebrate richness and abundances, mainly through stochastic extinctions. Such changes in richness were not reflected in functional diversity. This suggests that communities were characterized by a high degree of functional redundancy, which allowed maintenance of functional diversity despite species losses. Feeding groups responded differently to drought, with organic matter decomposers responding more than scrapers and predators. 4. Three weeks was insufficient for a complete invertebrate community recovery from the drought. However, recovery was greater in channels subjected to enhanced connectivity, which increased taxonomic diversity and abundance of certain taxa. Spatial configuration of resources explained the least variation in our response variables, having a significant effect only on invertebrate abundance and evenness (both sampling occasions) and species richness (end of recovery period). 5. Even a short drought, if occurring late to the season, may not allow communities to recover before the onset of winter, thus having a potentially long-lasting effect on stream communities. For boreal headwaters, extreme dewatering poses a novel disturbance regime that may trigger substantial and potentially irreversible changes. An improved understanding of such changes is needed to underpin adaptive management strategies in these increasingly fragmented and disturbed ecosystems. 18-Dec-2020
Data from: Evidence for a stochastic geometry of biodiversity: the effects of species abundance, richness and intraspecific clustering
Most ecological theories that aim to explain coexistence in megadiverse communities employ a set of three rules to describe the stochastic geometry of biodiversity: (i) individuals exhibit intraspecific clustering; (ii) species abundances vary according to a log-normal distribution and (iii) the spatial arrangement between species is independent. The first two rules have received strong empirical support, but the third remains largely unexplored. To address this deficiency, we evaluated the independent species arrangement rule in a species-rich shrubland and its potential drivers, that is, the levels of species richness and intraspecific clustering exhibited by a given species at different scales, and the relative abundance of such species in the community. We found that interspecific associations were rare and that independence was positively related to species richness and intraspecific clustering, but negatively related to relative species abundances. Synthesis. Our results agree with the independent species arrangement rule and they provide empirical support for the stochastic geometry of biodiversity. In the context of species-rich plant communities, the likelihood of two species encountering is very small. However, our study demonstrated a novel feature of this context, where both intraspecific clustering (due limitations on dispersal) and relative species abundances play fundamental roles in determining the probability of two species encountering and interacting, especially at very fine spatial scales.
Data from: Ecological incumbency impedes stochastic community assembly in Holocene foraminifera from the Huon Peninsula, Papua New Guinea
Persistence in the structure of ecological communities can be predicted both by deterministic and by stochastic theory. Evaluating ecological patterns against the neutral theory of biodiversity provides an appropriate methodology for differentiating between these alternatives. We traced the history of benthic foraminiferal communities from the Huon Peninsula, Papua New Guinea. From the well-preserved uplifted reef terrace at Bonah River we reconstructed the benthic foraminiferal communities during a 2200-year period (9000–6800 yr B.P.) of reef building during the Holocene transgressive sea-level rise. We found that the similarity of foraminiferal communities was consistently above 60%, even when comparing communities on either side of a massive volcanic eruption that smothered the existing reef system with ash. Similarly, species diversity and rank dominance were unchanged through time. However, similarity dropped dramatically in the final stages of reef growth, when accommodation space was reduced as sea-level rise slowed. We compared the community inertia index (CII) computed from the observed species abundances with that predicted from neutral theory. Despite the differences in foraminiferal community composition in the younger part of the reef sequence, we found an overall greater degree of community inertia with less variance in observed communities than was predicted from neutral theory, regardless of foraminiferal community size or species migration rate. Thus, persistent species assemblages could not be ascribed to neutral predictions. Ecological incumbency of established foraminiferal species likely prevented stochastic increases in both migrant and rare taxa at the Bonah River site. Regardless of the structuring mechanisms, our reconstruction of Holocene foraminiferal assemblages provides historical context for the management and potential restoration of degraded species assemblages.
Data from: Stochastic population dynamics and life-history variation in marine fish species
We examined whether differences in life-history characteristics can explain interspecific variation in stochastic population dynamics in nine marine fish species living in the Barents Sea system. After observation errors in population estimates were accounted for, temporal variability in natural mortality rate, annual recruitment, and population growth rate was negatively related to generation time. Mean natural mortality rate, annual recruitment, and population growth rate were lower in long-lived species than in short-lived species. Thus, important species-specific characteristics of the population dynamics were related to the species position along the slow-fast continuum of life-history variation. These relationships were further associated with interspecific differences in ecology: species at the fast end were mainly pelagic, with short generation times and high natural mortality, annual recruitment, and population growth rates, and also showed high temporal variability in those demographic traits. In contrast, species at the slow end were long-lived, deepwater species with low rates and reduced temporal variability in the same demographic traits. These interspecific relationships show that the life-history characteristics of a species can predict basic features of interspecific variation in population dynamical characteristics of marine fish, which should have implications for the choice of harvest strategy to facilitate sustainable yields.
Data from: Stochasticity and infectious disease dynamics: density and weather effects on a fungal insect pathogen
In deterministic models of epidemics, there is a host abundance threshold, above which the introduction of a few infected individuals leads to a severe epidemic. Studies of weather-driven animal pathogens often assume that abundance thresholds will be overwhelmed by weather-driven stochasticity, but tests of this assumption are lacking. We collected observational and experimental data for a fungal pathogen, {\it Entomophaga maimaiga}, that infects the gypsy moth, {\it Lymantria dispar}. We used an advanced statistical-computing algorithm to fit mechanistic models to our data, such that different models made different assumptions about the effects of host density and weather on {\it E. maimaiga} epizootics (epidemics in animals). We then used AIC analysis to choose the best model. In the best model, epizootics are driven by a combination of weather and host density, and the model does an excellent job of explaining the data, whereas models that allow only for weather effects, or only density-dependence effects, do a poor job of explaining the data. Density-dependent transmission in our best model produces a host-density threshold, but this threshold is strongly blurred by the stochastic effects of weather. Our work shows that host-abundance thresholds may be important even if weather strongly affects transmission, suggesting that epidemiological models that allow for weather have an important role to play in understanding animal pathogens. The success of our model means that it could be useful for managing the gypsy moth, an important pest of hardwood forests in North America.
Stochastic fluctuations in apoptotic threshold of tumor cells can enhance apoptosis and combat fractional killing
Fractional killing, which is a significant impediment to successful chemotherapy, is observed even in a population of genetically identical cancer cells exposed to apoptosis-inducing agents. This phenomenon arises not from genetic mutation but from cell-to-cell variation in the activation timing and level of the proteins that regulate apoptosis. To understand the mechanism behind the phenomenon, we formulate complex fractional killing processes as a first-passage time (FPT) problem with a stochastically fluctuating boundary. Analytical calculations are performed for the FPT distribution in a toy model of stochastic p53 gene expression, where the cancer cell is killed only when the p53 expression level crosses an activity apoptotic threshold. Counterintuitively, we find that threshold fluctuations can effectively enhance cellular killing by significantly decreasing the mean time that the p53 protein reaches the threshold level for the first time. Moreover, faster fluctuations lead to the killing of more cells. These qualitative results imply that dynamic variability in threshold is an unneglectable stochastic source, and can be taken as a strategy for combating fractional killing of cancer cells.
Data from: The sensitivity of seabird populations to density-dependence, environmental stochasticity and anthropogenic mortality
1.The balance between economic growth and wildlife conservation is a priority for many governments. Enhancing realism in assessment of population‐level impacts of anthropogenic mortality can help achieve this balance. Population Viability Analysis (PVA) is commonly applied to investigate population vulnerability, but outcomes of PVA are sensitive to formulations of density‐dependence, environmental stochasticity and life‐history. Current practice in marine assessments is to use precautionary models that assume no compensation from density‐dependence or rescue‐effects via "re‐seeding" from other colonies. However, if we could empirically quantify regulatory population processes, the responses of populations to additional anthropogenic mortality may be assessed with more realism in PVA. 2. Using Bayesian state‐space models fitted to population time‐series from three sympatric seabird populations, selected for varied life histories, we inferred the extent to which their dynamics are driven by environmental stochasticity and density‐dependence. 3. Based on these inferences, we conducted an exhaustive PVA across credible parameterisations for intrinsic and extrinsic population regulation, simulated as a closed and re‐seeded system. Scenarios of anthropogenic mortality, along a sliding scale of precaution, were applied both proportionally and as a fixed quota using Potential Biological Removal (PBR). 4. Baseline results from fitting revealed clear environmental regulation in two of our three species. Crucially, we found that for our empirically derived, realistic model parameterisations there are risks of decline to real populations even under very precautionary mortality scenarios. We find that PBR is dubious in application as a sustainable tool for population assessment when we account for regulation. Closed versus re‐seeded models showed a large divergence in outcomes, with sharper declines in closed simulations. Fixed‐quota mortality typically induced greater population declines comparative to proportional mortality, subject to regulation and re‐seeding. 5. Synthesis and applications: Practitioners using arbitrary formulations of population regulation risk over‐precaution (economic constraint) or under‐precaution (endangering populations). The demands of increased economic development and preservation of wildlife require that methodologies apply techniques that confer reality and rigour to assessment. The current practice of employing models lacking density‐dependence and empirical environmental information imposes limitations in the efficacy of estimating impacts. Here, we provide a method to quantify the conditions that predominantly regulate a population and exacerbate the risk of decline from anthropogenic mortality. It is in the interests of both developers and conservationists to apply methods in population impact assessments that capture realism in the processes driving population dynamics.
Data from: Stochastic and deterministic processes drive wetland community assembly across a gradient of environmental filtering
The role of deterministic and stochastic processes in community assembly is a key question in community ecology. We evaluated the effect of an abiotic filter (hydroperiod) on the partitioned diversity of three taxonomic groups (birds, vegetation, macroinvertebrates) from prairie pothole wetlands in Alberta, Canada, which naturally vary in water permanence. We observed that alpha and gamma diversity were higher in permanent than temporary wetlands (16-25% and 34-47% respectively, depending on the taxon). This suggests an influence of deterministic constraints on the number of species a wetland can support. Taxa which cannot persist in shallow, temporary wetlands are excluded by the deterministic constraints that a shortened hydroperiod imposes. In contrast, we observed that beta diversity was significantly higher (2-12%) in temporary wetlands than permanent ones, and temporary wetlands supported more unique combinations of community composition than permanent wetlands, despite having a smaller regional species pool. This observation contradicts prior mesocosm studies that found beta diversity mirrored the pattern in gamma diversity along an environmental filtering gradient. We conclude that deterministic processes are more influential in more stable permanent wetlands, whereas stochastic processes play a more important role in assembly in dynamic temporary wetlands that must disassemble and re-establish annually. Considering three distinct taxonomic groups differing in their relative mobility, our large-scale field study demonstrates that both stochastic and deterministic processes act together to influence the assembly of multiple communities and that the relative importance of the two processes varies consistently along a gradient of environmental filtering.
Data from: Spatial variability in plant predation determines the strength of stochastic community assembly
High diversity is often poorly explained by trait-based deterministic models, in part because stochastic processes also influence community assembly. Testing how deterministic and stochastic processes combine to regulate diversity, however, has been limited by the spatial complexity of these interactions. Here, we demonstrate how spatial variability in small-mammal predation on plants, mostly by granivory, results in fine-scale switching between deterministically and stochastically regulated plant community assembly in an otherwise environmentally homogeneous tallgrass prairie. We initiated assembly with the uniform application of a 24-species mixture of prairie grasses and forbs, thereby setting the maximum level of diversity (γ-diversity). In field edges with higher densities of small mammals, traits reducing seed palatability deterministically produced homogeneous subsets of less palatable plant species within the first few months after planting (low α and β diversity). As small-mammal densities decreased in more open areas, assembly unfolded stochastically on the basis of which planted species happened to land at a given location (high α and β diversity). We used randomization models to validate that this higher β diversity was explained by true differences in community structure among plots rather than by the hidden effects of increasing α diversity. The net effect at the site level was a spatially structured array of prairie species, including a positive relationship between diversity and environmental suitability relating to reduced predator intensity.
Data from: Asynchronous changes in abundance over large scales are explained by demographic variation rather than environmental stochasticity in an invasive flagellate
Environmental stochasticity is important in explaining the persistence and establishment of invasive species, but the simultaneous effects of environmental and demographic factors are difficult to separate. Understanding how demography and environmental factors affect invasive species abundance over large temporal and spatial scales is essential to anticipate populations at risk of becoming established and setting appropriate management measures. Using a hierarchical mixed modeling approach we analyzed the spatial and interannual dynamics of the invasive raphidophyte Gonyostomum semen, a noxious flagellate which is spreading in northern Europe, in response to demographic and environmental variation. We used data from 76 lakes distributed across two biogeographical regions in Sweden (Central Plains in the south and Fennoscandian region in the north) and sampled during 14 years. We found a strong asynchrony in the density dynamics of G. semen populations between the two regions. G. semen showed positive trends (i.e. increasing frequency of high density peaks) in most southern lakes, forming established populations with recurrent blooms in successive years in some of them. In contrast, G. semen populations were smaller and more stochastic in the north. G. semen previous year's abundance, a proxy for cyst production and recruitment, had a strong control on the dynamics, likely contributing to the stability of high density populations in southern lakes. Conversely, the effects of climate and habitat were weaker and their influence varied across regions. Temperature was the limiting factor in the north whereas local habitat was more important in the south. Synthesis: A full understanding of the mechanisms driving abundance changes across large scales can only be gained if endogenous and environmental factors are analyzed together. For phytoplankton species, and specially, noxious microalgae, this implies that proxies for cyst production and recruitment, which are the inoculum for next year population, should be included in e.g. distribution, bloom formation and climate models, as these may modify establishment and population response to environmental variation. Asynchronous changes in abundance across regions also indicate that management plans should be developed for small regions, as inference at a large scale may obscure the mechanisms driving local population changes.
Data from: Resources alter the structure and increase stochasticity in bromeliad microfauna communities
Although stochastic and deterministic processes have been found to jointly shape structure of natural communities, the relative importance of both forces may vary across different environmental conditions and across levels of biological organization. We tested the effects of abiotic environmental conditions, altered trophic interactions and dispersal limitation on the structure of aquatic microfauna communities in Costa Rican tank bromeliads. Our approach combined natural gradients in environmental conditions with experimental manipulations of bottom-up interactions (resources), top-down interactions (predators) and dispersal at two spatial scales in the field. We found that resource addition strongly increased the abundance and reduced the richness of microfauna communities. Community composition shifted in a predictable way towards assemblages dominated by flagellates and ciliates but with lower abundance and richness of algae and amoebae. While all functional groups responded strongly and predictably to resource addition, similarity among communities at the species level decreased, suggesting a role of stochasticity in species-level assembly processes. Dispersal limitation did not affect the communities. Since our design excluded potential priority effects we can attribute the differences in community similarity to increased demographic stochasticity of resource-enriched communities related to erratic changes in population sizes of some species. In contrast to resources, predators and environmental conditions had negligible effects on community structure. Our results demonstrate that bromeliad microfauna communities are strongly controlled by bottom-up forces. They further suggest that the relative importance of stochasticity may change with productivity and with the organizational level at which communities are examined.
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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.