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27 results for “Individual-based models”
Disturbance legacies and resilience simulation using an individual-based forest landscape model on the Andrews Experimental Forest
Disturbances are key drivers of forest ecosystem dynamics, and forests are well adapted to their natural disturbance regimes. However, as a result of climate change, disturbance frequency is expected to increase in the future in many regions. It is not yet clear how such changes might affect forest ecosystems, and which mechanisms contribute to (current and future) disturbance resilience. We here studied the 6364-ha HJ Andrews Experimental Forest landscape to investigate how patches of remnant old-growth trees (as one important class of biological legacies) affect the resilience of forest ecosystems to disturbance. Using the spatially explicit, individual-based forest landscape model iLand we analyzed the effect of three different levels of remnant patches (0%, 12%, and 24% of the landscape) on 500-year recovery trajectories after a large, high severity wildfire. In addition, we evaluated how three different levels of fire frequency (no fire, a historic fire return interval of 262 years, and a reduced fire return interval of 131 years) modulate the effects of initial legacies. The study investigated effects of legacies on the resilience of forest ecosystem structure (represented by canopy complexity as described by the rumple index), composition (proportion of late-seral species), and functioning (total ecosystem carbon storage). For each scenario of initial legacy and fire return interval 25 replicates were simulated. More information on the simulation methodology as well as the code and executable used for this study can be obtained at http://iLand.boku.ac.at. The dataset is completed and no further analyses are planned at this point. The results are published in Ecological Applications http://dx.doi.org/10.1890/14-0255.1.
Individual-based simulation model of annual movement paths for the Darwin's frog (R code and data)
<p>Desprition of the R code</p> <p>I constructed an individual-based simulation model that describes the movement path of an individual<em> Rhinoderma darwinii</em> through 3-month displacement steps. This model was primarily developed to evaluate the age-specific movement behaviour of Darwin's frogs, however, I also used it to provide better estimates (i.e. alleviating for movement censoring) of age-specific annual displacements in the species. I developed several variations of this model through a combination of different random walk sub-models for juveniles and adults: uncorrelated non-stationary random walks (NRW), correlated non-stationary random walks (CRW), and stationary random walks (SRW). The NRW and CRW were modelled as a first-order Markovian process where the location of an individual <em>i</em> in time<em> t</em> depends on its spatial location in <em>t </em>- 1. The NRW is unbiased, i.e., there is no preferred direction in each movement step. In contrast, the CRW includes persistence in the directionality of movement, so there is a correlation between successive step orientations. Finally, the SRW assumes that individuals have an activity centre to which all their spatial locations are related.</p> <p>Related data are provided (y.txt, x.txt and age.txt)</p>
Core individual-based model simulation script and landscape data
<p>Habitat loss and isolation caused by landscape fragmentation represent a growing threat to global biodiversity. Existing theory suggests that the process will lead to a decline in metapopulation viability. However, since most metapopulation models are restricted to simple networks of discrete habitat patches, the effects of real landscape fragmentation, particularly in stochastic environments, are not well understood. To close this major gap in ecological theory, we developed a spatially explicit, individual-based model applicable to realistic landscape structures, bridging metapopulation ecology and landscape ecology. This model reproduced classical metapopulation dynamics under conventional model assumptions, but on fragmented landscapes, it uncovered general dynamics that are in stark contradiction to the prevailing views in the ecological and conservation literature. Notably, fragmentation can give rise to a series of dualities: a) positive and negative responses to environmental noise, b) relative slowdown and acceleration in density decline, and c) synchronization and desynchronization of local population dynamics. Furthermore, counter to common intuition, species that interact locally ("residents") were often more resilient to fragmentation than long-ranging "migrants". This set of findings signals a need to fundamentally reconsider our approach to ecosystem management in a noisy and fragmented world.</p>
Figure 2 in Adaptations in wild radish (Raphanus raphanistrum) flowering time, Part 1: Individual-based modeling of a polygenic trait
Figure 2. The relationship between the number of semidominant larger M1 alleles and days to first flower (DFF), needed to model the long-day selections. Note that six smallereffect M2 genes will add another 0 to 18 days to DFF. If each M1 allele added the same amount in the long-day selections, the relationship would be linear.
Figure 1 in Adaptations in wild radish (Raphanus raphanistrum) flowering time, Part 1: Individual-based modeling of a polygenic trait
Figure 1. Goodness of fit of the modeled data (A) when compared with the recorded glasshouse data (B). Graphs show cumulative days to first flowering (DFF) adaptations in Raphanus raphanistrum populations as a result of repeated early and late days to flowering selection. In both graphs, the basal population is the black solid line in the center,the darker lines are the matched generations of early flowering (EF1, EF3, FE4,and EF5; colored orange), and late flowering (LF2 and LF3; colored purple), with and late flowering (LF2 and LF3),with the two unmatched generations (EF2 and LF2) shown in lighter tones.The far-left population (early flowering EF5) displays very little phenotypic variability, whereas the far-right population (late flowering 3) is very diverse.
Core individual-based model simulation script and landscape data
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An individual-based model trained on multiple data sources estimates population connectivity and facilitates aggregation of harvest management units
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Data from: Evaluating the effects of wolf culling on livestock predation when considering wolf population dynamics in an individual-based model
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SARS-CoV-2 transmission and control in a hospital setting: an individual-based modelling study
<p><strong>Background</strong>: Development of strategies for mitigating the severity of COVID-19 is now a top public health priority. We sought to assess strategies for mitigating the COVID-19 outbreak in a hospital setting via the use of non-pharmaceutical interventions.</p> <p><strong>Methods</strong>: We developed an individual-based model for COVID-19 transmission in a hospital setting. We calibrated the model using data of a COVID-19 outbreak in a hospital unit in Wuhan. The calibrated model was used to simulate different intervention scenarios and estimate the impact of different interventions on outbreak size and workday loss.</p> <p><strong>Findings</strong>: The use of high efficacy facial masks was shown to be able to reduce infection cases and workday loss by 80% (90% CrI: 73.1% - 85.7%) and 87% (CrI: 80.0% - 92.5%), respectively. The use of social distancing alone, through reduced contacts between healthcare workers, had a marginal impact on the outbreak. Our results also indicated that a quarantine policy should be coupled with other interventions to achieve its effect. The effectiveness of all these interventions was shown to increase with their early implementation.</p> <p><strong>Conclusions</strong>: Our analysis shows that a COVID-19 outbreak in a hospital's non-COVID-19 unit can be controlled or mitigated by the use of existing non-pharmaceutical measures.</p>
Dataset for the manuscript: Modelling the within-host spread of SARS-CoV-2 infection, and the subsequent immune response, using a hybrid, multiscale, individual-based model. Part I: Macrophages.
<p>Dataset for the manuscript:</p> <p>Modelling the within-host spread of SARS-CoV-2 infection, and the subsequent immune response, using a hybrid, multiscale, individual-based model. Part I: Macrophages. preprint, bioRxiv, 2022. DOI: 10.1101/2022.05.06.490883</p> <p>Each zip file contains the raw computational data (as a gzip compressed tarball), YAML input files, as well as Python plotting scripts. The Python plotting scripts have dependencies on the packages: <em>tarfile</em>, <em>multiprocessing</em>, <em>numpy</em>, <em>scipy</em>, and <em>matplotlib</em>. Note that the Python plotting scripts plot directly from the gzip compressed tarballs.</p> <p>The corresponding code can be found on GitHub: https://github.com/Ruth-Bowness-Group/CAModel</p>
Limiting scaring activities reduces economic costs associated with foraging barnacle geese: results from an individual-based model
<ol> <li>With increasing numbers of large grazing birds on agricultural grassland, conflict with farmers is rising. One management approach to alleviate conflict allows foraging on dedicated agricultural land (accommodation areas) and nature reserves, combined with scaring on remaining agricultural land. Here, we examine the cost-effectiveness of these measures by studying the influence on barnacle goose distribution and associated economic damage.</li> <li>We present an individual/agent-based model of barnacle geese (<em>Branta</em> <em>leucopsis</em>) foraging on grasslands in Fryslân, the Netherlands. The model is parameterized using field observations and GPS-tracks and allows simulation of management scenarios, differing in scaring probability and accommodation area size, with different potential management costs. </li> <li>Our model shows that, while yield loss decreases with higher scaring probabilities, costs of damage appraisal increase because geese graze on more fields. With small accommodation areas, achieving high scaring probabilities takes more effort and could result in goose population decline. Total management costs are lowest without scaring activity. </li> <li> <em>Synthesis and applications</em>: Considering costs of active scaring and the need to maintain the barnacle goose population in a favourable conservation status, our model suggests that the most cost-effective scenario is to prevent disturbance of geese. A high scaring probability could be beneficial if applied in small areas, for example around sensitive crops or airfields. Scaring in large areas could result in costs outweighing benefits and a declining barnacle goose population.</li> </ol>
Associated model data for: Size-selective predation effects on juvenile Chinook salmon cohort survival off Central California evaluated with an individual-based model
<p><span>T</span>his dataset corresponds to the paper "Size-selective predation effects on juvenile Chinook salmon cohort survival off Central California evaluated with an individual-based model" which is in press at Fisheries Oceanography. The abstract for this paper is as follows: </p> <p>Variation in the recruitment of salmon is often found to be correlated with marine climate indices, but mechanisms behind environment-recruitment relationships remain unclear and correlations often break down over time. We used an ecosystem modeling approach to explore bottom-up and top-down mechanisms linking a variable environment to salmon recruitment variations. Our ecosystem model incorporates a regional ocean circulation sub-model for hydrodynamics, a nutrient-phytoplankton-zooplankton sub-model for producing planktonic prey fields, and an individual-based model (IBM) representing juvenile Chinook salmon (<em>Oncorhynchus</em> <em>tshawytscha</em>), combined with observations of foraging distributions and diet of a seabird predator. The salmon IBM consists of modules, including a juvenile salmon growth module based on temperature and salmon-prey availability, a behavior-based movement module, and a juvenile salmon predation mortality module based on juvenile salmon size distribution and predator-prey interaction probability. Seabird-salmon interactions depend on spatial overlap and juvenile salmon size, whereby salmon that grow past the size range of the prey distribution of the predator will escape predation. We used a 21-year historical simulation to explore interannual variability in juvenile Chinook salmon growth and predation-mediated survival under a range of ocean conditions for sized-based mortality scenarios. We based a series of increasingly complex predation scenarios on seabird observational data to explore variability in predation mortality on juvenile Chinook salmon. We initially included information about the predator spatial distribution, then added population size, and finally, the predator's diet percentage made up of juvenile salmon. Model agreement improves with added predator complexity, especially during periods when predator abundance is high. Overall, our model found that when the fraction of juvenile salmon in seabird diet increased relative to alternate prey (e.g., Northern anchovy <em>Engraulis</em> <em>mordax</em>, and juvenile rockfish <em>Sebastes</em> spp.), there was a concomitant decrease in salmon cohort survival during their first year at sea.</p>
Supporting reintroduction planning: A framework integrating habitat suitability, connectivity and individual-based modelling. A case study with the Eurasian lynx in the Apennines
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Data from: Cost-effectiveness of leveraging existing HIV primary health systems and community health workers for hypertension screening and treatment in Africa: An individual-based modelling study
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Associated model data for: Size-selective predation effects on juvenile Chinook salmon cohort survival off Central California evaluated with an individual-based model
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Data from: Modeling multilocus selection in an individual-based, spatially-explicit landscape genetics framework
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Hybridization selects for prime-numbered life cycles in Magicicada: an individual-based simulation model of a structured periodical cicada population
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SARS-CoV-2 transmission and control in a hospital setting: an individual-based modelling study
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Limiting scaring activities reduces economic costs associated with foraging barnacle geese: results from an individual-based model
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Shelled Pteropod individual-based model output for the publication: The impact of aragonite saturation variability on shelled pteropods: An attribution study in the California current system
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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.