Introducing a novel and updated database showcasing Peru's endemic plants. This meticulously compiled and revised botanical collection encompasses a remarkable assemblage of over 7,898 distinct species. The data for this resource was sourced from the work of Govaerts, R., Nic Lughadha, E., Black, N. et al., titled 'The World Checklist of Vascular Plants: A continuously updated resource for exploring global plant diversity', published in Sci Data 8, 215 (2021) <doi:10.1038/s41597-021-00997-6>.

Implements projection pursuit forest algorithm for supervised classification.

Methods for fitting point processes with parameters of generalised additive 
      model (GAM) form are provided. For an introduction to point processes see Cox, D.R & 
      Isham, V. (Point Processes, 1980, CRC Press), GAMs see Wood, S.N. (2017) 
      <doi:10.1201/9781315370279>, and the fitting approach see Wood, S.N., Pya, N. & 
      Safken, B. (2016) <doi:10.1080/01621459.2016.1180986>.

Reconstruction of paleoclimate niches using phylogenetic comparative 
    methods and projection reconstructed niches onto paleoclimate maps.
    The user can specify various models of trait evolution or estimate the best fit
    model, include fossils, use one or multiple phylogenies for inference, and make
    animations of shifting suitable habitat through time. This model was first used
    in Lawing and Polly (2011), and further implemented in Lawing et al (2016) and 
    Rivera et al (2020).
    Lawing and Polly (2011) <doi:10.1371/journal.pone.0028554> "Pleistocene climate,
    phylogeny and climate envelope models: An integrative approach to better 
    understand species' response to climate change"
    Lawing et al (2016) <doi:10.1086/687202> "Including fossils in phylogenetic 
    climate reconstructions: A deep time perspective on the climatic niche evolution
    and diversification of spiny lizards (Sceloporus)"
    Rivera et al (2020) <doi:10.1111/jbi.13915> "Reconstructing historical shifts 
    in suitable habitat of Sceloporus lineages using phylogenetic niche modelling.".