diff --git a/DESCRIPTION b/DESCRIPTION index 2208f52..231f7fd 100644 --- a/DESCRIPTION +++ b/DESCRIPTION @@ -17,7 +17,8 @@ LazyData: true Roxygen: list(markdown = TRUE) RoxygenNote: 7.2.3 Imports: - motifcensus + motifcensus, + stars Suggests: knitr, rmarkdown, diff --git a/R/cumul.R b/R/cumul.R index f254686..0d0d89b 100644 --- a/R/cumul.R +++ b/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") } diff --git a/R/data.R b/R/data.R new file mode 100644 index 0000000..89f7abc --- /dev/null +++ b/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 +#' @source +#' @source +"trophic_sensitivity" \ No newline at end of file diff --git a/data/TrophicSensitivity.RData b/data/TrophicSensitivity.RData new file mode 100644 index 0000000..a232ce3 Binary files /dev/null and b/data/TrophicSensitivity.RData differ diff --git a/man/direct_cea.Rd b/man/direct_cea.Rd index ae719e0..a6035ed 100644 --- a/man/direct_cea.Rd +++ b/man/direct_cea.Rd @@ -11,7 +11,7 @@ direct_cea(drivers, vc, sensitivity) \item{vc}{list of stars or terra objects} -\item{sensitivity}{matrix of \link{drivers x vc}} +\item{sensitivity}{matrix of drivers x vc} } \description{ Function to assess cumulative effects considering only direct effects, i.e. the Halpern et al. (2008) methodology diff --git a/man/trophic_sensitivity.Rd b/man/trophic_sensitivity.Rd new file mode 100644 index 0000000..3403d57 --- /dev/null +++ b/man/trophic_sensitivity.Rd @@ -0,0 +1,36 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/data.R +\docType{data} +\name{trophic_sensitivity} +\alias{trophic_sensitivity} +\title{Trophic sensitivity} +\format{ +\subsection{\code{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{ +\url{https://github.com/david-beauchesne/FoodWeb-MultiStressors/blob/master/Data/vulnerability.RData} + +\url{https://onlinelibrary.wiley.com/doi/abs/10.1111/ele.13841} + +\url{https://semaphore.uqar.ca/id/eprint/1922/1/David_Beauchesne_decembre2020.pdf} +} +\usage{ +trophic_sensitivity +} +\description{ +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 +} +\keyword{datasets}