BC_model | R Documentation |
Transforms environmental niche in base to species interactions
BC_model(
x,
y,
A.matrix = NULL,
C.matrix = NULL,
D = 1,
method = c("composition", "densities"),
eval = TRUE,
relative.niche = T,
K = NULL,
sample.pseudoabsences = TRUE,
R = 100,
res = NULL,
plot.eval = FALSE,
rep = 100,
th = NULL,
ras = NULL,
best.th = c("accuracy", "similarity"),
combine.regions = F,
cor = F,
type = c("region", "global")
)
x |
NINA EN model object for species group one |
y |
NINA EN model object for species group two |
A.matrix |
m by n matrix indicating the association coefficient (-1 to 1). m are species to be modeled as rows and n interactions as columns |
C.matrix |
n by n matrix indicating the competition coefficient between interactions (0 to 1). |
D |
Numeric value indicating independence from biotic associations. Value must be comprised between 0 and 1. |
method |
Method; abundances or composition |
eval |
Boolean whether to evaluate the model |
relative.niche |
Logical |
K |
= Carrying capacity of each environmental cell |
sample.pseudoabsences |
Boolean to whether sample pseudo-absences |
R |
Integer. size of the grid for the niche space estimate. R represents number of columns and rows |
res |
spatial resolution |
plot.eval |
Logical to whether plot the evaluation |
rep |
number of randomzation tests |
th |
threshold to perform cut off for model evaluation |
ras |
raster to constrain pseudoabsences sampling in model evalluation |
best.th |
method to select the best thresholt. Default is "similarity" |
combine.regions |
Logical. Whether to combine regional niche models into a global one |
cor |
Logical |
type |
String indicating whether to perform at a region or a global level. Note that if models have not been estimated at a region level and it is selected it will produce an error |
NINA model
## Not run:
EN1 <- EN_model(env_data, occ_data1, cluster = "env", n.clus = 5)
EN2 <- EN_model(env_data, occ_data2, cluster = "env", n.clus = 5)
BC <- BC_model(EN1, EN2, A.matrix = int_matrix)
## End(Not run)
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