Used for generating randomized community matrices under
             strict range cohesion. The package can handle data where species occurrence
             are recorded across sites ordered along gradients such as elevation and latitude, as well as species occurrences recorded on spatial grids with known geographic coordinates.

A fast implementation of Random Forests, particularly suited for high
          dimensional data. Ensembles of classification, regression, survival and
          probability prediction trees are supported. Data from genome-wide association
          studies can be analyzed efficiently. In addition to data frames, datasets of
          class 'gwaa.data' (R package 'GenABEL') and 'dgCMatrix' (R package 'Matrix') 
          can be directly analyzed.

Displays palette of 5 colors based on photos depicting the unique 
             and vibrant culture of Punjab in Northern India. Since Punjab translates 
             to ``Land of 5 Rivers'' there are 5 colors per palette. If users need 
             more than 5 colors, they can merge 2 to 3 palettes to create their own 
             color-combination, or they can cherry-pick their own custom colors. 
             Users can view up to 3 palettes together. Users can also list all the 
             palette choices. And last but not least, users can see the photo that 
             inspired a particular palette.

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/>. This work was supported by 
    the National Science Centre, Poland, grant no. 2018/29/B/NZ8/00066 and 
    the Poznań Supercomputing and Networking Centre (grant no. pl0090-01).