Package: rangr 1.0.5

Katarzyna Markowska

rangr: Mechanistic Simulation of Species Range Dynamics

Integrates population dynamics and dispersal into a mechanistic virtual species simulator. The package can be used to study the effects of environmental change on population growth and range shifts. It allows for simple and straightforward definition of population dynamics (including positive density dependence), extensive possibilities for defining dispersal kernels, and the ability to generate virtual ecologist data. Learn more about the 'rangr' at <https://docs.ropensci.org/rangr/>.

Authors:Katarzyna Markowska [aut, cre], Lechosław Kuczyński [aut], Tad Dallas [rev], Joanne Potts [rev]

rangr_1.0.5.tar.gz
rangr_1.0.5.zip(r-4.5)rangr_1.0.5.zip(r-4.4)rangr_1.0.5.zip(r-4.3)
rangr_1.0.5.tgz(r-4.5-any)rangr_1.0.5.tgz(r-4.4-any)rangr_1.0.5.tgz(r-4.3-any)
rangr_1.0.5.tar.gz(r-4.5-noble)rangr_1.0.5.tar.gz(r-4.4-noble)
rangr_1.0.5.tgz(r-4.4-emscripten)rangr_1.0.5.tgz(r-4.3-emscripten)
rangr.pdf |rangr.html
rangr/json (API)
NEWS

# Install 'rangr' in R:
install.packages('rangr', repos = c('https://ropensci.r-universe.dev', 'https://cloud.r-project.org'))

Reviews:rOpenSci Software Review #595

Bug tracker:https://github.com/ropensci/rangr/issues

Pkgdown site:https://docs.ropensci.org

Datasets:

On CRAN:

4.11 score 2 stars 5 scripts 9 exports 6 dependencies

Last updated 21 hours agofrom:0de890f0b0 (on main). Checks:6 OK, 1 FAILURE, 1 ERROR. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKFeb 13 2025
R-4.5-winOKFeb 13 2025
R-4.5-macOUTDATEDFeb 03 2025
R-4.5-linuxOKFeb 13 2025
R-4.4-winOKFeb 13 2025
R-4.4-macOKFeb 13 2025
R-4.3-winOKFeb 13 2025
R-4.3-macERRORFeb 13 2025

Exports:dispexponentialget_observationsgompertzinitialiseK_get_interpolationrickersimto_rast

Dependencies:assertthatlatticepbapplyRcppterrazoo

How to use rangr?

Rendered fromrangr.Rmdusingknitr::rmarkdownon Feb 13 2025.

Last update: 2024-07-26
Started: 2023-05-26

Readme and manuals

Help Manual

Help pageTopics
Simulating Dispersaldisp
Observation Processget_observations
Population Growth Functionsexponential gompertz growth ricker
Prepare Data Required To Perform A Simulationinitialise
Example Of Carrying Capacity Map (Big)K_big_lon_lat.tif
Example Of Carrying Capacity Map (Big)K_big.tif
Prepare Time-Varying Carrying Capacity MapsK_get_interpolation
Example Of Changing Carrying Capacity Maps (Small)K_small_changing_lon_lat.tif
Example Of Changing Carrying Capacity Maps (Small)K_small_changing.tif
Example Of Carrying Capacity Map (Small)K_small_lon_lat.tif
Example Of Carrying Capacity Map (Small)K_small.tif
Example Of Abundance Map At First Time Step Of The Simulation (Big)n1_big_lon_lat.tif
Example Of Abundance Map At First Time Step Of The Simulation (Big)n1_big.tif
Example Of Abundance Map At First Time Step Of The Simulation (Small)n1_small_lon_lat.tif
Example Of Abundance Map At First Time Step Of The Simulation (Small)n1_small.tif
Example Of Observation Points Listobservations_points
Plot 'sim_results' Objectplot.sim_results
Print 'sim_data' Objectprint.sim_data
Print 'sim_results' Objectprint.sim_results
Print 'summary.sim_data' Objectprint.summary.sim_data
Print 'summary.sim_results' Objectprint.summary.sim_results
Mechanistic Metapopulation Simulatorsim
Subset of Given Time Points from 'sim_results' Objectsubset.sim_results
Summary Of 'sim_data' Objectsummary.sim_data
Summary Of 'sim_results' Objectsummary.sim_results
Transformation 'sim_results' To Rasterto_rast
Update 'sim_data' Objectupdate.sim_data