pr2database
The protist reference database keeps widening past the rRNA gene it was built on.
A side-by-side editorial comparison of rsofun and slendr — release velocity, themes, recent moves, and the top alternatives to consider.
An ecosystem model starts tracking carbon isotopes and land-use change.
rsofun wraps the P-model and BiomeE vegetation models in R with Fortran cores, covering photosynthesis, water balance and forest demography, plus Bayesian calibration. The 5.1.0 release is the first in the window to widen what the models simulate rather than reorganise them. Before it, the history is renaming, cost-function rewrites and output-format consistency work.
Population-genetic simulation in R, opened up to selection and finally easier to install.
slendr specifies spatial and non-spatial population-genetic models in R and simulates them through SLiM or msprime, returning tree sequences that tskit then analyses. Two threads dominate the current releases: keeping in step with fast-moving backends, with SLiM 5.1, pyslim 1.1.0 and Python 3.13 now required, and reducing the setup burden that its Python dependency imposes. Version 1.5.0 adds ephemeral uv-based virtual environments, so init_env(uv = TRUE) can stand in for creating a permanent environment with setup_env().
rsofun wraps the P-model and BiomeE vegetation models in R with Fortran cores, covering photosynthesis, water balance and forest demography, plus Bayesian calibration. The 5.1.0 release is the first in the window to widen what the models simulate rather than reorganise them. Before it, the history is renaming, cost-function rewrites and output-format consistency work.
The direction is from a calibration harness toward a model that can answer different questions: isotope fractionation now comes out of the P-model, BiomeE handles land use and land-use change, and forcing can be recycled when a simulation outruns its data. Version stamps are unreliable here, with a v5.0 tag carrying only a build fix and predating v4.4, so the arc reads better through content than through numbering.
The isotope work is explicitly unfinished, with a constant atmospheric signature standing in for daily d13c forcing, so the next likely step is accepting that as model input.
slendr specifies spatial and non-spatial population-genetic models in R and simulates them through SLiM or msprime, returning tree sequences that tskit then analyses. Two threads dominate the current releases: keeping in step with fast-moving backends, with SLiM 5.1, pyslim 1.1.0 and Python 3.13 now required, and reducing the setup burden that its Python dependency imposes. Version 1.5.0 adds ephemeral uv-based virtual environments, so init_env(uv = TRUE) can stand in for creating a permanent environment with setup_env().
Since the 1.0.0 release added non-neutral simulation, the work has shifted from capability to friction. A large share of recent notes concerns Python environment handling, conda activation races on Windows, dependency pruning that made shiny optional, and argument names that misled users, as when gene_flow()'s rate argument turned out to mean total ancestry proportion rather than a rate. That is the profile of a package whose scientific surface is settled and whose remaining problems are the ones users actually hit.
Expect the uv-based environment path to move from fallback to default once it has proven itself, given the notes already describe an environment variable for making it so. The deprecated rate argument in gene_flow() is explicitly slated for removal in a future major release, which is the clearest signal here of what a 2.0 would contain.
Other Infra & APIs products tracked by Sparkpulse, ranked by recent ship velocity. Each card links to a full editorial trajectory and lets you pivot into a head-to-head comparison with either rsofun or slendr.
The protist reference database keeps widening past the rRNA gene it was built on.
Composable aligned layouts, rebuilt on S7 while ggplot2 4.0 lands underneath.
Conservation planning absorbs the literature's target-setting rules as code.
Joint species distribution models in Gibbs-sampled C++, quiet since 2023.
Ten years in, US mapping splits its data out and finally adds Puerto Rico.
Fitness-tracking analysis in slow maintenance, still absorbing upstream breakage.
See all rsofun alternatives → · See all slendr alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
They serve adjacent needs but don't currently overlap on shipped themes. rsofun and slendr are shipping at a similar cadence (velocity 0.0 vs 0.0, both within Sparkpulse's "active" band). See the at-a-glance table above for a side-by-side breakdown of velocity, recent sparks, and editorial themes.
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. rsofun and slendr are shipping at a similar cadence (velocity 0.0 vs 0.0, both within Sparkpulse's "active" band). For your specific use case, the alternatives sections above list other Infra & APIs products to evaluate alongside.
Top rsofun alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "rsofun alternatives" section above for the current picks, or visit /alternatives/rsofun for the full list with editorial commentary on each.
Top slendr alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "slendr alternatives" section above for the current picks, or visit /alternatives/slendr for the full list with editorial commentary on each.