Color palettes based on nature inspired colours in "Sri Lanka".

Get or set UNIX priority (niceness) of running R process.

Species Identification using DNA Barcodes Integrated with 
             Environmental Niche Models.

Implementation of a probabilistic method to calculate 'nicheROVER' (_niche_ _r_egion and niche _over_lap) metrics using multidimensional niche indicator data (e.g., stable isotopes, environmental variables, etc.). The niche region is defined as the joint probability density function of the multidimensional niche indicators at a user-defined probability alpha (e.g., 95%).  Uncertainty is accounted for in a Bayesian framework, and the method can be extended to three or more indicator dimensions.  It provides directional estimates of niche overlap, accounts for species-specific distributions in multivariate niche space, and produces unique and consistent bivariate projections of the multivariate niche region.  The article by Swanson et al. (2015) <doi:10.1890/14-0235.1> provides a detailed description of the methodology.  See the package vignette for a worked example using fish stable isotope data.

Provides functions complementary to packages 'nicheROVER' and 'SIBER'
        allowing the user to extract Bayesian estimates from data objects created 
        by the packages 'nicheROVER' and 'SIBER'. Please see the following 
        publications for detailed methods on 'nicheROVER' and 'SIBER' 
        Hansen et al. (2015) <doi:10.1890/14-0235.1>, 
        Jackson et al. (2011) <do i:10.1111/j.1365-2656.2011.01806.x>, and
        Layman et al. (2007) <doi:10.1890/0012-9658(2007)88[42:CSIRPF]2.0.CO;2>,
        respectfully.

A collection of tools that allow users to perform critical steps 
    in the process of assessing ecological niche evolution over phylogenies, with
    uncertainty incorporated explicitly in reconstructions. The method proposed
    here for ancestral reconstruction of ecological niches characterizes species'
    niches using a bin-based approach that incorporates uncertainty in estimations.
    Compared to other existing methods, the approaches presented here reduce risk
    of overestimation of amounts and rates of ecological niche evolution. The
    main analyses include: initial exploration of environmental data in occurrence
    records and accessible areas, preparation of data for phylogenetic analyses,
    executing comparative phylogenetic analyses of ecological niches, and plotting
    for interpretations. Details on the theoretical background and methods used 
    can be found in: Owens et al. (2020) <doi:10.1002/ece3.6359>,
    Peterson et al. (1999) <doi:10.1126/science.285.5431.1265>,
    Soberón and Peterson (2005) <doi:10.17161/bi.v2i0.4>,
    Peterson (2011) <doi:10.1111/j.1365-2699.2010.02456.x>,
    Barve et al. (2011) <doi:10.1111/ecog.02671>, 
    Machado-Stredel et al. (2021) <doi:10.21425/F5FBG48814>,
    Owens et al. (2013) <doi:10.1016/j.ecolmodel.2013.04.011>, 
    Saupe et al. (2018) <doi:10.1093/sysbio/syx084>, and 
    Cobos et al. (2021) <doi:10.1111/jav.02868>.