Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
15
datasets available to search
ShareScore release 0.9.0
Dataset results
15 results for “individual-based simulation”
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>
Core individual-based model simulation script and landscape data
Open the record for dataset details and reuse information.
Code for individual-based simulations in "Environmental fluctuations can promote evolutionary rescue in high-extinction-risk scenarios"
<p>Substantial environmental change can force a population onto a path towards extinction, but under some conditions, adaptation by natural selection can rescue the population and allow it to persist. This process, known as evolutionary rescue, is believed to be less likely to occur with greater magnitudes of random environmental fluctuations because environmental variation decreases expected population size, increases variance in population size, and increases evolutionary lag. However, previous studies of evolutionary rescue in fluctuating environments have only considered scenarios in which evolutionary rescue was likely to occur. We extend these studies to assess how baseline extinction risk (which we manipulated via changes in the initial population size, degree of environmental change, or mutation rate) influences the effects of environmental variation on evolutionary rescue following an abrupt environmental change. Using a combination of analytical models and stochastic simulations, we show that autocorrelated environmental variation hinders evolutionary rescue in low-extinction-risk scenarios but facilitates rescue in high-risk scenarios. In these high-risk cases, the chance of a run of good years counteracts the otherwise negative effects of environmental variation on evolutionary demography. These findings can inform the development of effective conservation practices that consider evolutionary responses to abrupt environmental changes.</p>
Data from: Exploring the macroevolutionary impact of ecosystem engineers using an individual-based eco-evolutionary simulation
<p>Ecosystem engineers can radically reshape ecosystems by modulating the availability of resources to other organisms through modifying either physical or biological aspects of the environment. The introduction or removal of ecosystem engineers from otherwise stable ecosystems can impact the diversity of co-occurring species, such as driving local extinctions of native taxa. While these impacts are well established over ecological timescales for a wealth of taxa, the macroevolutionary implications of the onset of ecosystem engineering behaviours are less clear. Despite this uncertainty, ecosystem engineering has been implicated in several major transitions in Earth's history including the appearance of extensive bioturbation during the Cambrian substrate revolution and associated Ediacaran-Cambrian turnover and the Great Oxygenation Event. Whether ecosystem engineers are frequently associated with turnover and extinction in deep time is not known. Here we investigate this with an eco-evolutionary simulation framework in which we assign lineages the ability to impact the fitness of co-occurring taxa through phenotype-environment feedback. We explore numerous conditions, including how frequently these feedbacks occur, and whether ecosystem engineers modify or create niches. We show that there is no general expected outcome from the introduction of ecosystem engineers. In a minority of runs, ecosystem engineering lineages completely dominate, rendering all others extinct, but in others, they persist (but do not dominate), or die out. We suggest that ecosystem engineers have complex impacts but possess the capacity to profoundly shape diversity, and it is appropriate to consider them alongside other exogenous extinction drivers in deep time. </p>
Productivity, niche availability, species richness and extinction risk: Untangling relationships using individual-based simulations
It has been widely hypothesised that the productivity of an ecosystem affects the number of species that it can support. Despite decades of study, the nature, extent, and underlying mechanisms of this relationship are unclear. One suggested mechanism is the "more individuals" hypothesis (MIH). This proposes that productivity controls the number of individuals in the ecosystem, and that more individuals can be divided into a greater number of species before their population size is sufficiently small for each to be at substantial risk of extinction. Here, we test this hypothesis using REvoSim: an individual-based eco-evolutionary system that simulates the evolution and speciation of populations over geological time, allowing phenomena occurring over timescales that cannot be easily observed in the real world to be evaluated. The individual-based nature of this system allows us to remove assumptions about the nature of speciation and extinction that previous models have had to make. Many of the predictions of the MIH are supported in our simulations: rare species are more likely to undergo extinction than common species, and species richness scales with productivity. However, we also find support for relationships that contradict the predictions of the strict MIH: species population size scales with productivity, and species extinction risk is better predicted by relative than absolute species size. Furthermore, we show that the scaling of species richness with productivity depends upon the ability of species to partition niche space. Consequently, we suggest that the MIH is applicable only to ecosystems where niches are not already saturated with species, and where partitioning is therefore still possible. Some hypotheses regarding patterns of biodiversity implicitly or explicitly overlook niche theory in favour of neutral explanations, as has historically been the case with the MIH. Our simulations demonstrate that niche theory exerts a control on the applicability of the MIH. --
Productivity, niche availability, species richness and extinction risk: Untangling relationships using individual-based simulations
Open the record for dataset details and reuse information.
Code for individual-based simulations in "Environmental fluctuations can promote evolutionary rescue in high-extinction-risk scenarios"
Open the record for dataset details and reuse information.
Data from: Exploring the macroevolutionary impact of ecosystem engineers using an individual-based eco-evolutionary simulation
Open the record for dataset details and reuse information.
Hybridization selects for prime-numbered life cycles in Magicicada: an individual-based simulation model of a structured periodical cicada population
Open the record for dataset details and reuse information.
Individual-based simulations for: Population rescue through an increase of the selfing rate under pollen limitation: Plasticity vs. evolution
<p>The file contains the individual-based simulation code that is used in the paper "Population rescue through an increase of the selfing rate under pollen limitation: plasticity vs. evolution". This study built eco-evolutionary models and individual-based simulations to explore the demographic and genetic conditions in which higher self-fertilization by plasticity and/or evolution rescues populations, following deficits due to sudden onset of pollen limitation. The code is written in C++. Please first read the README.txt file for instructions and details.</p>
Individual-based simulations for: Population rescue through an increase of the selfing rate under pollen limitation: Plasticity vs. evolution
Open the record for dataset details and reuse information.
Data from: The evolution of marine larval dispersal kernels in spatially structured habitats: analytical models, individual-based simulations, and comparisons with empirical estimates
Open the record for dataset details and reuse information.
Individual-based simulations of genome evolution and ancestry: the GENOMEADMIXR R package
Open the record for dataset details and reuse information.
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
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.