sum_func_groups: summarize functional groups

In SrivastavaLab/bwgtools: Access data from the bromeliad working group

Description

summarize functional groups

Usage

sum_func_groups(merged_data, grps = list(~site, ~site_brom.id, ~predation,
  ~functional_group))

Arguments

merged_data	data formed by merging insect data to trait data
grps	using the formula, indicate the grouping factors required

Value

summarized data. NOTE that this data will be grouped!

Examples

invert_data <- combine_tab(c("Argentina", "French_Guiana", "Colombia","Macae", "PuertoRico","CostaRica"),"bromeliad.final.inverts")
bwg_names <- get_bwg_names()
invert_traits <- merge_func(invert_data, bwg_names)
# Functional Groups
func_groups <- sum_func_groups(invert_traits,
                              grps = list(~site,
                                          ~site_brom.id,
                                          ~functional_group))
func_groups
library(ggplot2) #require the 'ggplot2' package
## plot by functional group abundance
func_groups %>%
 ggplot(aes(x = as.factor(functional_group), y = total_abundance)) +
 geom_point(position = position_jitter(width = 0.25), alpha = 0.5) +
 stat_summary(fun.data = "mean_cl_boot", colour = "red", size = 0.6) +
 facet_wrap(~site, scales = "free_y") +
 ggtitle("Functional group abundance")
# Trophic level
# To summarize by trophic level group, simply switch \code{~functional_group} to \code{~predation}:
predprey <- sum_func_groups(invert_traits,
                         grps = list(~site,
                                     ~site_brom.id,
                                     ~predation))
predprey
## plot by trophic level abundance
predprey %>%
 ggplot(aes(x = as.factor(predation), y = total_abundance)) +
 geom_point(position = position_jitter(width = 0.25), alpha = 0.5) +
 stat_summary(fun.data = "mean_cl_boot", colour = "red", size = 0.6) +
 facet_wrap(~site, scales = "free_y") +
 ggtitle("Trophic level abundance")

SrivastavaLab/bwgtools documentation built on May 9, 2019, 1:54 p.m.