Calculate downstream survival given dam passage scenario.

Function used to create population-level survival during out-migration through dams.

Usage

make_downstream(
  river,
  species = c("AMS", "ALE", "BBH"),
  downstream,
  upstream,
  historical = FALSE,
  custom_habitat = NULL
)

Arguments

river

Character string specifying river name.

species

Species for which population dynamics will be simulated. Choices include American shad ("AMS"), alewife ("ALE"), and blueback herring ("BBH").

downstream

Numeric indicating proportional downstream survival through a single dam.

upstream

Numeric indicating proportional upstream passage through a single dam.

historical

Logical indicating whether to use contemporary or historical habitat data.

custom_habitat

A dataframe containing columns corresponding to the those in the output from custom_habitat_template(). NEED TO ADD LINK.

Value

Numeric of length 1 representing catchment-scale downstream migration mortality for juvenile or adult fish.

Details

This function assigns cumulative downstream passage values to all features in habitat corresponding to river. It then calculates the proportion of habitat in each habitat segment of a river, and weights downstream mortality at the catchment-scale by proportion of habitat. This implicitly assumes that fish are distributed throughout the river during spawning in proportion to available habitat.

Examples

# Example usage
if (FALSE) { # \dontrun{
  
# Example 1. ----  
# Calculate population-level survival during outmigration
# for fixed upstream and downstream dam passage probabilities
s_down <- make_downstream(
  habitat_data = habitat,
  river = 'Susquehanna',
  downstream = 0.95,
  upstream = 0.80
  )
  
# Example 2. ----
# Explore how upstream passage affects catchment-wide survival
# during outmigration for a fixed downstream passage
upstream_p <- seq(from=0, to=1, by=0.01)
s_down <- vector(mode='numeric', length=length(upstream_p))
for(i in 1:length(upstream_p)){
  s_down[i] <- make_downstream(
    habitat_data = habitat,
    river = 'Susquehanna',
    downstream = 0.5,
    upstream = upstream_p[i]
    )  
} 

Zd = 1 - s_down

plot(x=upstream_p, y=Zd, type = 'l',
     xlab='Upstream passage',
     ylab = 'Total downstream mortality',
     main = 'Susquehanna River'
     )

# Example 3. ----
# Explore interactions between upstream and downstream 
# passage probabilities when both vary. This changes
# drastically from one river to another depending on
# habitat above and below dams, and number of dams.
upstream_p <- seq(from=0, to=1, by=0.01)
downstream_p <- seq(from=0, to=1, by=0.01)
s_down <- matrix(data = NA, nrow=length(upstream_p), ncol = length(downstream_p))

for(i in 1:length(upstream_p)){
  for(t in 1:length(downstream_p)){
    s_down[i,t] <- make_downstream(
      habitat_data = habitat,
      river = 'Susquehanna',
      downstream = downstream_p[t],
      upstream = upstream_p[i]
      )  
  }   
}

zd <- 1 - s_down
filled.contour(x=upstream_p, y=downstream_p, z=zd,
               xlab = 'Upstream passage probability',
               ylab = 'Downstream survival per dam',
               main = 'Catchment-wide dam mortality'
               )

} # }