sdd_update_probs: Update short distance dispersal probabilities

In Sz-Tim/gbPopMod: Mechanistic species distribution model for glossy buckthorn (*Frangula alnus*)

Description

Update dispersal probabilities for each affected cell following land cover changes. Because SDD probabilities are weighted by land cover based on bird habitat preferences, the probabilities must be recalculated for each cell that contains an affected cell as its target. Each layer k in [1:i, 1:j, k, source.id] is the SDD neighborhood for cell n. k=1 contains pr(SDD | source.id,i,j); k=2 contains the grid id for each cell in the neighborhood.

Usage

sdd_update_probs(lc.df, g.p, sdd.alter, sdd.0, lc.col = 4:9)

Arguments

lc.df	Dataframe or tibble with xy coords, land cover proportions, and cell id info
g.p	Named list of global parameters
sdd.alter	Vector of indexes of cells that need to have their SDD neighborhood recalculated
sdd.0	Original (non-sparse) SDD neighborhoods generated by sdd_set_probs; i.e., sdd_set_probs()$i
lc.col	4:9 Column indexes for land cover proportions
edges	"wall" Boundary behavior

Value

List with full neighborhoods,i, sparse representation, sp, and sparse dataframe sp.df. The full array has dim(disp.rows, disp.cols, 2, ncell) where the third dimension contains grid id's for the neighborhood or probabilities to each target cell. The sparse representation contains a list with containing the cells dispersing into each cell and a list with the associated probabilities. The sparse dataframe is a dataframe with a row for each non-zero i-j pair with columns for i, j, and dispersal probability

Sz-Tim/gbPopMod documentation built on Dec. 7, 2020, 1:07 p.m.