getOverlap goes through all m-wise combinations of species
and returns the amount of overlap between species in functions they perform
for each combination
getOverlap(
overData,
m = 2,
type = "positive",
index = "sorensen",
denom = "set"
)Matrix of functions and which species affect them from getRedundancy.
Number of functions. Defaults to 2.
Are the kinds of effects we're looking at "positive", "negative" or "all".
Type of overlap index to be used. Defaults to "sorenson" but currently incorporates "mountford" and "jaccard" as well.
Should the denominator be "all" species or just the "set" of species with the types of interactions being considered? Defaults to "set".
Returns a vector of overlap indices.
getOverlap takes a matrix of 1s and -1s, and depending on whether we're interested in positive, negative, or both types of interactions looks for the m-wise overlap between species and returns the overlap index for each combination
data(all_biodepth)
allVars <- qw(biomassY3, root3, N.g.m2, light3, N.Soil, wood3, cotton3)
germany <- subset(all_biodepth, all_biodepth$location == "Germany")
vars <- whichVars(germany, allVars)
species <- relevantSp(germany, 26:ncol(germany))
# re-normalize N.Soil so that everything is on the
# same sign-scale (e.g. the maximum level of a function is the "best" function)
germany$N.Soil <- -1 * germany$N.Soil + max(germany$N.Soil, na.rm = TRUE)
res.list <- lapply(vars, function(x) sAICfun(x, species, germany))
names(res.list) <- vars
redund <- getRedundancy(vars, species, germany)
getOverlap(redund, m = 2)
#> [1] 0.1818182 0.6666667 0.4615385 0.3333333 0.3636364 0.3333333 0.0000000
#> [8] 0.1538462 0.3333333 0.0000000
getOverlap(redund, m = 2, index = "jaccard")
#> [1] 0.10000000 0.50000000 0.30000000 0.20000000 0.22222222 0.20000000
#> [7] 0.00000000 0.08333333 0.20000000 0.00000000
getOverlap(redund, m = 2, index = "mountford")
#> [1] 0.04081633 0.33333333 0.13333333 0.08333333 0.10526316 0.08695652
#> [7] 0.00000000 0.02816901 0.08333333 0.00000000
#########
# getOverlap takes a matrix of 1s and -1s, and depending on whether we're
# interested in positive, negative, or both types of interactions looks for the
# m-wise overlap
#########