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Merged
Pakillo merged 2 commits into from
Feb 19, 2026
Merged

Canopy_service_test #36

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f2b2e0d
Update canopy_service_test.R
aliciamontesinos Feb 19, 2026
77200f3
Fix typos and improve vector initialization
Pakillo Feb 19, 2026
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40 changes: 21 additions & 19 deletions R/canopy_service_test.R
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Original file line number Diff line number Diff line change
@@ -1,21 +1,23 @@
#' Title
#' Identifies whether a species acts as depressing, enhancing or neutral
#' @description
#' Tests whether a canopy species has a depressing, enhancing or neutral
#' effect on recruitment in general (i.e., at the community level) compared
#' to the "Open", independently considering all the recruit species together.
#'
#' @param int_data
#' @param cover_data
#'
#' @returns
#' @inheritParams check_interactions
#' @inheritParams check_cover
#'
#'
#' @returns Data frame with the same variables provided by the function
#' [int_significance()] but without distinguishing between recruit species.
#'
#' @export
#'
#' @examples
#' canopy_service_test(Amoladeras_int, Amoladeras_cover)
#'
#' #como canopy_service_test_UNI pero sin quitar especies de reclutas
#que no tienen cover ( solo las canopy que no tienen cover)
#sustituimos pre_associndex_UNISITE_UNI por
#associndex(int_data,cover_data, expand="yes", rm_sp_no_cover="onlycanopy")
#calcula para cada especie de nodriza, si alberga bajo su copa una mayor (o menor)
# densidad de reclutas (de cualquier especie) que la esperada en funcion del area que ocupa.
#The input data are two files: the field data containing interactions and species cover
#'

canopy_service_test <- function(int_data,cover_data){

df<-associndex(int_data,cover_data, expand="yes", rm_sp_no_cover="onlycanopy")
Expand All @@ -34,21 +36,22 @@ canopy_service_test <- function(int_data,cover_data){

df$Ftot <- df$Fc+df$Fro

extreme_p <- c()
# extreme_p <- c()
extreme_p <- vector(mode = "numeric", length = nrow(df))
for(i in 1:n_tests){
extreme_p[i] <- min(df$exp_p[i], 1-df$exp_p[i])
}
df$extreme_p <- extreme_p

testability <- c()
testability <- vector(mode = "numeric", length = nrow(df))
for(i in 1:n_tests) {
testability[i] <- binom.test(df$Ftot[i], df$Ftot[i], df$extreme_p[i], alternative ="two.sided")$p.value
testability[i] <- stats::binom.test(df$Ftot[i], df$Ftot[i], df$extreme_p[i], alternative ="two.sided")$p.value
}
df$testability <- testability

# Binomial (or Chi square) Test Significance

Significance <- c()
Significance <- vector(mode = "numeric", length = nrow(df))
for(i in 1:n_tests) {
ifelse(((df$Fc[i]+df$Fro[i])*(df$Ac[i]/(df$Ac[i]+df$Ao[i]))<=5 | (df$Fc[i]+df$Fro[i])*(df$Ao[i]/(df$Ac[i]+df$Ao[i]))<=5),
Significance[i] <- binom.test(df$Fc[i], df$Fc[i]+df$Fro[i], df$exp_p[i], alternative ="two.sided")$p.value,
Expand All @@ -57,7 +60,7 @@ canopy_service_test <- function(int_data,cover_data){
}
df$Significance <- Significance

Test_type <- c()
Test_type <- vector(mode = "character", length = nrow(df))
for(i in 1:n_tests) {
ifelse(((df$Fc[i]+df$Fro[i])*(df$Ac[i]/(df$Ac[i]+df$Ao[i]))<=5 | (df$Fc[i]+df$Fro[i])*(df$Ao[i]/(df$Ac[i]+df$Ao[i]))<=5),
Test_type[i] <- "Binomial",
Expand All @@ -68,7 +71,7 @@ canopy_service_test <- function(int_data,cover_data){

if(length(unique(df$Test_type))>1) message("Different tests were used for different canopy-recruit pairs. Check column Test_type")

Effect_int <- c()
Effect_int <- vector(mode = "character", length = nrow(df))
for(i in 1:n_tests) {
ifelse((df$testability[i]>0.05),
Effect_int[i] <- "Not testable",
Expand All @@ -86,4 +89,3 @@ canopy_service_test <- function(int_data,cover_data){
df <- df[ , !(names(df) %in% drops)]
return(df)
}