A species object (list) to carry out demographic modelling.

Description

It was made from the demoniche_setup function. See the example file and the manual for further details.

Usage

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Format

The format is: List of 25 $ Orig_Populations :'data.frame': 34 obs. of 4 variables: ..$ PatchID : int [1:34] 8000 8001 8002 8003 8004 8005 8006 8007 8008 8009 ... ..$ XCOORD : int [1:34] 2 3 6 7 9 11 12 17 18 19 ... ..$ YCOORD : int [1:34] 29 29 29 29 29 29 29 29 29 29 ... ..$ area_population: int [1:34] 2 2 2 2 2 2 2 2 2 2 ... $ fraction_SDD : num 0.5 $ dispersal_probabilities : num [1:900, 1:900] 0.0 8.7e-08 0.0 0.0 0.0 ... ..- attr(*, "dimnames")=List of 2 .. ..$ : chr [1:900] "5000" "5001" "5002" "5003" ... .. ..$ : chr [1:900] "5000" "5001" "5002" "5003" ... $ dist_latlong : num [1:900, 1:900] 0 1 2 3 4 5 6 7 8 9 ... ..- attr(*, "dimnames")=List of 2 .. ..$ : chr [1:900] "5000" "5001" "5002" "5003" ... .. ..$ : chr [1:900] "5000" "5001" "5002" "5003" ... $ neigh_index : num [1:2] 1 1.4 $ Niche_ID :'data.frame': 900 obs. of 4 variables: ..$ Niche_ID : int [1:900] 5000 5001 5002 5003 5004 5005 5006 5007 5008 5009 ... ..$ X : int [1:900] 1 2 3 4 5 6 7 8 9 10 ... ..$ Y : int [1:900] 1 1 1 1 1 1 1 1 1 1 ... ..$ PopulationID: num [1:900] 0 0 0 0 0 0 0 0 0 0 ... $ Niche_values :'data.frame': 900 obs. of 9 variables: ..$ period2000: num [1:900] 0 0 0 0 0 0 0 0 0 0 ... ..$ period2010: num [1:900] 0 0 0 0 0 0 0 0 0 0 ... ..$ period2020: num [1:900] 0 0 0 0 0 0 0 0 0 0 ... ..$ period2030: num [1:900] 0 0 0 0 0 0 0 0 0 0 ... ..$ period2040: num [1:900] 0 0 0 0 0 0 0 0 0 0 ... ..$ period2050: num [1:900] 0 0 0 0 0 0 0 0 0 0 ... ..$ period2060: num [1:900] 0 0 0 0 0 0 0 0 0 0 ... ..$ period2070: num [1:900] 0 0 0 0 0 0 0 0 0 0 ... ..$ period2080: num [1:900] 0 0 0 0 0 0 0 0 0 0 ... $ years_projections : chr [1:9] "period2000" "period2010" "period2020" "period2030" ... $ matrices : num [1:36, 1:5] 0.4995 0.0004 0 0 0 ... ..- attr(*, "dimnames")=List of 2 .. ..$ : NULL .. ..$ : chr [1:5] "Reference_matrix" "Mx1" "Mx2" "Mx3" ... $ matrices_var : num [1:36, 1] 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 ... ..- attr(*, "dimnames")=List of 2 .. ..$ : NULL .. ..$ : chr "sd" $ prob_scenario : num [1:2] 0.5 0.5 $ noise : num [1] 0.95 $ stages : chr [1:6] "seed" "seedlings" "tiny" "small" ... $ proportion_initial : num [1:6] 0.98181 0.000691 0.006908 0.003684 0.005756 ... $ density_individuals : num 20000 $ fraction_LDD : num 0.05 $ no_yrs : num 10 $ K : num 100 $ populationmax_all : num [1:900] 4e+06 4e+06 4e+06 4e+06 4e+06 4e+06 4e+06 4e+06 4e+06 4e+06 ... $ n0_all : num [1:900, 1:6] 0 0 0 0 0 0 0 0 0 0 ... $ list_names_matrices :List of 5 ..$ : chr "Reference_matrix" ..$ : chr "Mx1" ..$ : chr "Mx2" ..$ : chr "Mx3" ..$ : chr "Mx4" $ sumweight : num [1:6] 0 1 1 1 1 1 $ transition_affected_env : int [1:24] 1 2 9 13 14 15 16 19 20 21 ... $ transition_affected_niche : num [1:2] 1 3 $ transition_affected_demogr: int [1:24] 1 2 9 13 14 15 16 19 20 21 ... $ env_stochas_type : chr "normal"

Examples

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data(Hmontana)
str(Hmontana) 
demoniche_model(modelname = "Hmontana", Niche = FALSE, 
   Dispersal = FALSE, repetitions =  2,
   foldername = "noCC_nodispersal")