Functions for calculating metrics for the measurement biodiversity
    and its changes across scales, treatments, and gradients. The methods 
    implemented in this package are described in:
    Chase, J.M., et al. (2018) <doi:10.1111/ele.13151>, 
    McGlinn, D.J., et al. (2019) <doi:10.1111/2041-210X.13102>,
    McGlinn, D.J., et al. (2020) <doi:10.1101/851717>, and
    McGlinn, D.J., et al. (2023) <doi:10.1101/2023.09.19.558467>.

Simulation, analysis and sampling of spatial
    biodiversity data (May, Gerstner, McGlinn, Xiao & Chase 2017)
    <doi:10.1111/2041-210x.12986>.
    In the simulation tools user define the numbers of
    species and individuals, the species abundance distribution and species
    aggregation. Functions for analysis include species rarefaction 
    and accumulation curves, species-area relationships and the distance
    decay of similarity.

Implements the Multi-Objective Clustering Algorithm Guided by a-Priori Biological Knowledge (MOC-GaPBK) which was proposed by Parraga-Alava, J. et. al. (2018) <doi:10.1186/s13040-018-0178-4>.

Provides methods to analyze cluster alternatives based on multi-objective optimization of cluster validation indices. For details see Kraus et al. (2011) <doi:10.1007/s00180-011-0244-6>.

The two main functionalities of this package are creating
    mock objects (functions) and selectively intercepting calls to a given
    function that originate in some other function. It can be used with
    any testing framework available for R. Mock objects can be injected
    with either this package's own stub() function or a similar
    with_mocked_binding() facility present in the 'testthat' package.

Provides a means to mock a package function, i.e.,
    temporarily substitute it for testing. Designed as a drop-in
    replacement for the now deprecated 'testthat::with_mock()' and
    'testthat::local_mock()'.

With the deprecation of mocking capabilities shipped with
    'testthat' as of 'edition 3' it is left to third-party packages to replace
    this functionality, which in some test-scenarios is essential in order to
    run unit tests in limited environments (such as no Internet connection).
    Mocking in this setting means temporarily substituting a function with a
    stub that acts in some sense like the original function (for example by
    serving a HTTP response that has been cached as a file). The only exported
    function 'with_mock()' is modeled after the eponymous 'testthat' function
    with the intention of providing a drop-in replacement.