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Runs a series of simulations, using iterate.graph, allows changing the simulations parameters in several sequential simulations.
manage_landscape_sim(par_df, parameters_spom, full.output)Arguments data frame to be used by iterate.graph (each row of this data frame is a set of Arguments). The data frame has to have the following columns in this order (the name of the column is not relevant):
MDST - Minimum inter-patch distance (in meters).
NPATCH - Number of patches in the landscape.
AREA_M - Mean area of the patches (in hectares).
AREA_SD - SD of the patches' area.
MAPSIZE - Landscape mosaic side length (in meters).
SPAN - Number of time steps in the simulation.
ITER - Number of iterations of the simulation.
PAR1_SPAN - parm1 for the span.graph function.
PAR2_SPAN - parm2 for the span.graph function.
PAR3_SPAN - parm3 for the span.graph function.
PAR4_SPAN - parm4 for the span.graph function.
PAR5_SPAN - parm5 for the span.graph function.
NSEW_SPECIES - Argument nsew for the species.graph function.
PARM_SPECIES - Argument parm for the species.graph function.
METHOD_SPECIES - Argument method for the species.graph function.
KERN - Argument kern for the spom function.
CONN - Argument conn for the spom function.
COLNZ - Argument colnz for the spom function.
EXT - Argument ext for the spom function.
BETA1 - Argument beta1 for the spom function.
B - Argument b for the spom function.
C1 - Argument c1 for the spom function.
C2 - Argument c2 for the spom function.
Z - Argument z for the spom function.
R2 - Argument R for the spom function.
DISPERSAL - Species mean dispersal ability (in meters).
SUCCESSION - Species successional preference (early, mid or late).
Parameters data frame, as given by parameter.estimate.
Creates a folder named 'output' to which it saves the full results of the simulations made with the parameters in each row of 'par_df'. It will generate as many objects as the number of rows in this data frame.
Returns a data frame with the parameters used for the simulations and the results (mean occupation, mean number of patches, mean turnover, mean distance and mean area).
For details regarding the arguments see the respective functions.
# NOT RUN {
#Setup the parameters for each simulation:
PAR1_SPAN2 <- rep("ncsd",820)#parameter 1 for the span function
PAR2_SPAN2 <- rep(seq(from=0,to=80,by=2), each=20)#parameter 2 for the span function
PAR3_SPAN2 <- rep(seq(from=0,to=80,by=2),20)#parameter 3 for the span function
PAR4_SPAN2 <- rep(2,820)#parameter 4 for the span function
PAR5_SPAN2 <- rep(2,820)#parameter 5 for the span function
NSEW_SPECIES2 <- rep("none",820)#where to start populating the landscape
PARM_SPECIES2 <- rep(5,820)#parameter for the species function
METHOD_SPECIES2 <- rep("percentage",820)#method for populating the landscape
MAPSIZE2 <- rep(10000,820)#dimension of the landscape
SPAN2 <- rep(100,820)#number of time steps of each simulation
ITER2 <- rep(5,820)#number of iterations of each simulation
NPATCH2 <- rep(800,820)#number of patches
AREA_M2 <- rep(0.45,820)#mean area
AREA_SD2 <- rep(0.2,820)#area sd
MDST2 <- rep(0,820)#minimum distance between
KERN <- rep("op1",820)#kernel
CONN <- rep("op1",820)#connectivity function
COLNZ <- rep("op1",820)#colonization function
EXT <- rep("op1",820)#extinction function
BETA1 <- rep("NULL",820)
B <- rep(1,820)
C1 <- rep("NULL",820)
C2 <- rep("NULL",820)
Z <- rep("NULL",820)
R2 <- rep("NULL",820)
DISPERSAL2 <- rep(800,820)#mean dispersal ability of the species
SUCC <- rep("early",820)
#Build parameter data frame (keep the order of the parameters):
simulation <- data.frame(MDST2,NPATCH2,AREA_M2,AREA_SD2,
MAPSIZE2,SPAN2,ITER2,PAR1_SPAN2,PAR2_SPAN2,PAR3_SPAN2,PAR4_SPAN2,PAR5_SPAN2,
NSEW_SPECIES2,PARM_SPECIES2,METHOD_SPECIES2,KERN,CONN,COLNZ,EXT,BETA1,B,C1,C2,Z,R2,DISPERSAL2,SUCC)
#Delete vectors used for data frame creation:
rm('PAR1_SPAN2','PAR2_SPAN2','PAR3_SPAN2','PAR4_SPAN2','PAR5_SPAN2',
'NSEW_SPECIES2','PARM_SPECIES2','METHOD_SPECIES2','MAPSIZE2','SPAN2','ITER2',
'NPATCH2','AREA_M2','AREA_SD2','MDST2','KERN','CONN','COLNZ','EXT',
'BETA1','B','C1','C2','Z','R2','DISPERSAL2','SUCC')
# }
# NOT RUN {
data(param1)
ms2 <- manage_landscape_sim(par_df=simulation,parameters_spom=param1)
# }
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