divNeeded | R Documentation |
divNeeded
Determines, for every combination of functions, how many species
influence those functions.
divNeeded(overData, type = "positive")
overData |
Matrix of functions and which species affect them from |
type |
Are the kinds of effects we're looking at "positive", "negative" or "all". |
Iterates over all possible combinations of functions. Checks the matrix of which species have positive, negative, or both influences on those functions. Tally's total number of species that have an effect on those functions
Returns a data frame of all combinations and how many species are needed to influence all of them.
Jarrett Byrnes.
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) posCurve <- divNeeded(redund, type = "positive")
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