#' Create Projection Matrix
#' @description Create projection matrix with growth, stasis, retrogression, survival, and sexual reproduction rates. Assumptions about the recruitment rate, seed bank, and fertilities follow Stubben (2007).
#' @param trans_data transition data
#' @param SeedSurvival seed survival estimate
#' @param SeedBankSize seed bank size estimate
#' @param SeedsPerFruit average number of seeds per fruit
#' @return Return a projection matrix
#' @reference Stubben, C., & Milligan, B. (2007). Estimating and analyzing demographic models using the popbio package in R. Journal of Statistical Software.
#' @export
createProjectionMatrix <- function(
trans_data,
SeedBankSize,
SeedsPerFruit,
SeedSurvival
) {
Seedlings <- trans_data %>% filter(stage =="Seedling") %>% nrow
seeds.from.plants <- sum(trans_data$Repro, na.rm=T) * SeedsPerFruit
# so the recruitment rate declines as the seed bank size increases?
recruitment.rate <- Seedlings/(SeedBankSize + seeds.from.plants)
trans_data$Seedling <- trans_data$Repro/sum(trans_data$Repro, na.rm=T)*
seeds.from.plants * recruitment.rate
trans_data$Seed <- trans_data$Repro * SeedsPerFruit * SeedSurvival
# return projection matrix
projection.matrix(
transitions = trans_data,
stage=stage,
fate=fate,
fertility=Repro,
add = c(
# transition from seed to seedling
2, 1, recruitment.rate
),
sort = levels(trans_data$stage)
)
}
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