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Simulation is a key tool in population genetics for both methods development and empirical research, but producing simulations that recapitulate the main features of genomic data sets remains a major obstacle. Today, more realistic simulations are possible thanks to large increases in the quantity and quality of available genetic data, and to the sophistication of inference and simulation software. However, implementing these simulations still requires substantial time and specialized knowledge. These challenges are especially pronounced for simulating genomes for species that are not well-studied, since it is not always clear what information is required to produce simulations with a level of realism sufficient to confidently answer a given question. The community-developed framework stdpopsim seeks to lower this barrier by facilitating the simulation of complex population genetic models using up-to-date information. The initial version of stdpopsim focused on establishing this framework using six well-characterized model species (Adrion et al., 2020). Here, we report on major improvements made in the new release of stdpopsim (version 0.2), which includes a significant expansion of the species catalog and substantial additions to simulation capabilities. Features added to improve the realism of the simulated genomes include non-crossover recombination and provision of species-specific genomic annotations. Through community-driven efforts, we expanded the number of species in the catalog more than three-fold and broadened coverage across the tree of life. During the process of expanding the catalog, we have identified common sticking points and developed best practices for setting up genome-scale simulations. We describe the input data required for generating a realistic simulation, suggest good practices for obtaining the relevant information from the literature, and discuss common pitfalls and major considerations. These improvements to stdpopsim aim to further promote the use of realistic whole-genome population genetic simulations, especially in non-model organisms, making them available, transparent, and accessible to everyone.
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This content will become publicly available on May 27, 2026
The NCAR-TIEGCM Version 3.0
A new version of the US National Science Foundation National Center forAtmospheric Research (NSF NCAR) thermosphere-ionosphere-electrodynamicsgeneral circulation model (TIEGCM) has been developed and released. Thispaper describes the changes and improvements of the new version 3.0since its last major release (2.0) in 2016. These include: 1) increasingthe model resolution in both the horizontal and vertical dimensions, aswell as the ionospheric dynamo solver; 2) upward extension of the modelupper boundary to enable more accurate simulations of the topsideionosphere and neutral density in the lower exosphere; 3) improvedparameterization for thermal electron heating rate; 4) resolvingtransport of minor species N(2D); 5) treating helium as a major species;6) parameterization for additional physical processes, such as SAPS andelectrojet turbulent heating; 7) including parallel ion drag in theneutral momentum equation; 8) nudging of prognostic fields near thelower boundary from external data; 9) modification to the NO reactionrate and auroral heating rate; 10) outputs of diagnostic analysis termsof the equations; 11) new functionalities enabling model simulations ofcertain recurrent phenomena, such as solar flares and eclipse. Wepresent examples of the model validation during a moderate storm andcompare simulation results by turning on/off new functionalities todemonstrate the related new model capabilities. Furthermore, the modelis upgraded to comply with the new computer software environment at NSFNCAR for easy installation and run setup and with new visualizationtools. Finally, the model limitations and future development plans arediscussed.
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- Award ID(s):
- 2120511
- PAR ID:
- 10635874
- Author(s) / Creator(s):
- ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; more »
- Publisher / Repository:
- ESS Open Archive
- Date Published:
- Format(s):
- Medium: X
- Institution:
- ESS Open Archive
- Sponsoring Org:
- National Science Foundation
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Simulation is a key tool in population genetics for both methods development and empirical research, but producing simulations that recapitulate the main features of genomic datasets remains a major obstacle. Today, more realistic simulations are possible thanks to large increases in the quantity and quality of available genetic data, and the sophistication of inference and simulation software. However, implementing these simulations still requires substantial time and specialized knowledge. These challenges are especially pronounced for simulating genomes for species that are not well-studied, since it is not always clear what information is required to produce simulations with a level of realism sufficient to confidently answer a given question. The community-developed framework stdpopsim seeks to lower this barrier by facilitating the simulation of complex population genetic models using up-to-date information. The initial version of stdpopsim focused on establishing this framework using six well-characterized model species (Adrion et al., 2020). Here, we report on major improvements made in the new release of stdpopsim (version 0.2), which includes a significant expansion of the species catalog and substantial additions to simulation capabilities. Features added to improve the realism of the simulated genomes include non-crossover recombination and provision of species-specific genomic annotations. Through community-driven efforts, we expanded the number of species in the catalog more than threefold and broadened coverage across the tree of life. During the process of expanding the catalog, we have identified common sticking points and developed the best practices for setting up genome-scale simulations. We describe the input data required for generating a realistic simulation, suggest good practices for obtaining the relevant information from the literature, and discuss common pitfalls and major considerations. These improvements to stdpopsim aim to further promote the use of realistic whole-genome population genetic simulations, especially in non-model organisms, making them available, transparent, and accessible to everyone.more » « less
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