get_delta_stats: Conduct the MoB tests on drivers of biodiversity across...

In MoBiodiv/mobr: Measurement of Biodiversity

Conduct the MoB tests on drivers of biodiversity across scales.

Description

There are three tests, on effects of 1. the shape of the SAD, 2. treatment/group-level density, 3. degree of aggregation. The user can specifically to conduct one or more of these tests.

Usage

get_delta_stats(
  mob_in,
  env_var,
  group_var = NULL,
  ref_level = NULL,
  tests = c("SAD", "N", "agg"),
  spat_algo = NULL,
  type = c("continuous", "discrete"),
  stats = NULL,
  inds = NULL,
  log_scale = FALSE,
  min_plots = NULL,
  density_stat = c("mean", "max", "min"),
  n_perm = 1000,
  overall_p = FALSE
)

Arguments

mob_in	an object of class mob_in created by make_mob_in()
env_var	a character string specifying the environmental variable in mob_in$env to be used for explaining the change in richness
group_var	an optional character string in mob_in$env which defines how samples are pooled. If not provided then each unique value of the argument env_var is used define the groups.
ref_level	a character string used to define the reference level of env_var to which all other groups are compared with. Only makes sense if env_var is a factor (i.e. type == 'discrete')
tests	specifies which one or more of the three tests ('SAD', N', 'agg') are to be performed. Default is to include all three tests.
spat_algo	character string that can be either: 'kNN' or 'kNCN' for k-nearest neighbor and k-nearest centroid neighbor sampling respectively. It defaults to k-nearest neighbor which is a more computationally efficient algorithm that closely approximates the potentially more correct k-NCN algo (see Details of ?rarefaction).
type	"discrete" or "continuous". If "discrete", pair-wise comparisons are conducted between all other groups and the reference group. If "continuous", a correlation analysis is conducted between the response variables and env_var.
stats	a vector of character strings that specifies what statistics to summarize effect sizes with. Options include: c('betas', 'r2', 'r2adj', 'f', 'p') for the beta-coefficients, r-squared, adjusted r-squared, F-statistic, and p-value respectively. The default value of NULL will result in only betas being calculated when type == 'discrete' and all possible stats being computed when type == 'continuous'. Note that for a discrete analysis all non-betas stats are meaningless because the model has zero degrees of freedom in this context.
inds	effort size at which the individual-based rarefaction curves are to be evaluated, and to which the sample-based rarefaction curves are to be interpolated. It can take three types of values, a single integer, a vector of integers, and NULL. If inds = NULL (the default), the curves are evaluated at every possible effort size, from 1 to the total number of individuals within the group (slow). If inds is a single integer, it is taken as the number of points at which the curves are evaluated; the positions of the points are determined by the "log_scale" argument. If inds is a vector of integers, it is taken as the exact points at which the curves are evaluated.
log_scale	if "inds" is given a single integer, "log_scale" determines the position of the points. If log_scale is TRUE, the points are equally spaced on logarithmic scale. If it is FALSE (default), the points are equally spaced on arithmetic scale.
min_plots	minimal number of plots for test 'agg', where plots are randomized within groups as null test. If it is given a value, all groups with fewer plots than min_plot are removed for this test. If it is NULL (default), all groups are kept. Warnings are issued if 1. there is only one group left and "type" is discrete, or 2. there are less than three groups left and "type" is continuous, or 3. reference group ("ref_group") is removed and "type" is discrete. In these three scenarios, the function will terminate. A different warning is issued if any of the remaining groups have less than five plots (which have less than 120 permutations), but the test will be carried out.
density_stat	reference density used in converting number of plots to numbers of individuals, a step in test "N". It can take one of the three values: "mean", "max", or "min". If it is "mean", the average plot-level abundance across plots (all plots when "type" is "continuous, all plots within the two groups for each pair-wise comparison when "type" is "discrete") are used. If it is "min" or "max", the minimum/maximum plot-level density is used.
n_perm	number of iterations to run for null tests, defaults to 1000.
overall_p	Boolean defaults to FALSE specifies if overall across scale p-values for the null tests. This should be interpreted with caution because the overall p-values depend on scales of measurement yet do not explicitly reflect significance at any particular scale.

Value

a "mob_out" object with attributes

Author(s)

Dan McGlinn and Xiao Xiao

See Also

rarefaction

Examples

data(inv_comm)
data(inv_plot_attr)
inv_mob_in = make_mob_in(inv_comm, inv_plot_attr, coord_names = c('x', 'y'))
inv_mob_out = get_delta_stats(inv_mob_in, 'group', ref_level='uninvaded',
                           type='discrete', log_scale=TRUE, n_perm=3)
plot(inv_mob_out)

MoBiodiv/mobr documentation built on Jan. 31, 2024, 6:15 p.m.