add trophic sensitivity and adjust cumul

DESCRIPTION

@@ -17,7 +17,8 @@ LazyData: true
 Roxygen: list(markdown = TRUE)
 RoxygenNote: 7.2.3
 Imports:
-    motifcensus
+    motifcensus,
+    stars
 Suggests: 
     knitr,
     rmarkdown,

R/cumul.R

@@ -7,7 +7,12 @@
 #' @export
 cumul <- function(dat) {
   library(stars)
-  do.call("c", dat) |>
-  stars::st_redimension() |>
-  stars::st_apply(c(1,2), sum, na.rm = TRUE)      
+
+  # Combine if in list
+  if (class(dat) == "list") dat <- do.call("c", dat)
+
+  # Redimension and sum 
+  stars::st_redimension(dat) |>
+  stars::st_apply(c(1,2), sum, na.rm = TRUE) |>
+  setNames("Footprint")     
 }

R/data.R

@@ -0,0 +1,20 @@
+#' Trophic sensitivity
+#'
+#' A dataset containing the simplified values for trophic sensitivity as measured by Beauchesne et al. 2021 (DOI: 10.1111/ele.13841) and used by Beauchesne et al. 2020 for network-scale cumulative effects assessments
+#'
+#' @format ## `trophic_sensitivity`
+#' A data frame with 124 rows and 10 columns:
+#' \describe{
+#'   \item{Motif}{Name of motifs: apparent competition (ap); disconnected (di); exploitative competition (ex); omnivory (om); partially connected (pa); tri-trophic interaction (tt)}
+#'   \item{Species}{Position of species in motif (x,y,z)}
+#'   \item{px, py, pz}{Pathways of effects, whether species x, y or z are affected by disturbances}
+#'   \item{Sensitivity}{Trophic sensitivity scaled between 0 and 1}
+#'   \item{sensitivity_original}{Original value of trophic sensitivity}
+#'   \item{pathID}{Unique identifier of pathway of effect}
+#'   \item{speciesID}{Numeric ID for species position in motifs}
+#'   \item{motifID}{Numeric ID for motifs}
+#' }
+#' @source <https://github.com/david-beauchesne/FoodWeb-MultiStressors/blob/master/Data/vulnerability.RData>
+#' @source <https://onlinelibrary.wiley.com/doi/abs/10.1111/ele.13841>
+#' @source <https://semaphore.uqar.ca/id/eprint/1922/1/David_Beauchesne_decembre2020.pdf>
+"trophic_sensitivity"