Running ‘tests.R’ [80s/131s]
Running the tests in ‘tests/tests.R’ failed.
Complete output:
  > library(virtualspecies)
  Loading required package: terra
  terra 1.7.71
  > a <- matrix(rep(dnorm(1:100, 50, sd = 25)),
  +             nrow = 100, ncol = 100, byrow = TRUE)
  > env <- c(rast(a * dnorm(1:100, 50, sd = 25)),
  +          rast(a * 1:100))
  > names(env) <- c("variable1", "variable2")
  > plot(env) # Illustration of the variables
  > 
  > # Easy creation of the parameter list:
  > # see in real time the shape of the response functions
  > parameters <- formatFunctions(variable1 = c(fun = 'dnorm', mean = 1e-04,
  +                                              sd = 1e-04),
  +                               variable2 = c(fun = 'linearFun', a = 1, b = 0))
  > 
  > plotResponse(x = env, parameters = parameters, 
  +              approach = "response")
  No default value was defined for rescale.each.response, setting rescale.each.response = TRUE
  No default value was defined for rescale.each.response, setting rescale.each.response = TRUE
  > 
  > sp1 <- generateSpFromFun(env, parameters, plot = TRUE)
  Generating virtual species environmental suitability...
  
   - The response to each variable was rescaled between 0 and 1. To
              disable, set argument rescale.each.response = FALSE
  
   - The final environmental suitability was rescaled between 0 and 1. To disable, set argument rescale = FALSE
  
  > 
  > # If you provide env, then you can see the shape of response functions:
  > parameters <- formatFunctions(x = env,
  +                               variable1 = c(fun = 'dnorm', mean = 1e-04,
  +                                              sd = 1e-04),
  +                               variable2 = c(fun = 'linearFun', a = 1, b = 0))
  No default value was defined for rescale.each.response, setting rescale.each.response = TRUE
  No default value was defined for rescale.each.response, setting rescale.each.response = TRUE
  > 
  > sp1 <- generateSpFromFun(env, parameters, plot = TRUE)
  Generating virtual species environmental suitability...
  
   - The response to each variable was rescaled between 0 and 1. To
              disable, set argument rescale.each.response = FALSE
  
   - The final environmental suitability was rescaled between 0 and 1. To disable, set argument rescale = FALSE
  
  > sp1 <- generateSpFromFun(env, parameters, plot = TRUE,
  +                          formula = NULL,
  +                          species.type = "additive")
  Generating virtual species environmental suitability...
  
   - The response to each variable was rescaled between 0 and 1. To
              disable, set argument rescale.each.response = FALSE
  
   - The final environmental suitability was rescaled between 0 and 1. To disable, set argument rescale = FALSE
  
  > sp1 <- generateSpFromFun(env, parameters, plot = TRUE,
  +                          formula = NULL,
  +                          species.type = "multiplicative")
  Generating virtual species environmental suitability...
  
   - The response to each variable was rescaled between 0 and 1. To
              disable, set argument rescale.each.response = FALSE
  
   - The final environmental suitability was rescaled between 0 and 1. To disable, set argument rescale = FALSE
  
  > sp1 <- generateSpFromFun(env, parameters, plot = TRUE,
  +                          formula = NULL,
  +                          species.type = "multiplicative",
  +                          rescale = FALSE)
  Generating virtual species environmental suitability...
  
   - The response to each variable was rescaled between 0 and 1. To
              disable, set argument rescale.each.response = FALSE
  
  > sp1 <- generateSpFromFun(env, parameters, plot = TRUE,
  +                          formula = NULL,
  +                          species.type = "multiplicative",
  +                          rescale = FALSE,
  +                          rescale.each.response = FALSE)
  Generating virtual species environmental suitability...
  
  > sp1 <- generateSpFromFun(env, parameters, plot = TRUE,
  +                          formula = "variable1 + variable2",
  +                          species.type = "multiplicative",
  +                          rescale = FALSE,
  +                          rescale.each.response = TRUE)
  Generating virtual species environmental suitability...
  
   - The response to each variable was rescaled between 0 and 1. To
              disable, set argument rescale.each.response = FALSE
  
  [1] "variable1 + variable2"
  > sp1 <- generateSpFromFun(env, parameters, plot = TRUE,
  +                          formula = "sqrt(variable1) + variable2 + 2 * variable2^2 + variable2^3",
  +                          species.type = "multiplicative",
  +                          rescale = FALSE,
  +                          rescale.each.response = TRUE)
  Generating virtual species environmental suitability...
  
   - The response to each variable was rescaled between 0 and 1. To
              disable, set argument rescale.each.response = FALSE
  
  [1] "sqrt(variable1) + variable2 + 2 * variable2^2 + variable2^3"
  > sp1 <- generateSpFromFun(env, parameters, plot = TRUE,
  +                          formula = "sqrt(variable1) + variable2 + 2 * variable2^2 + variable2^3",
  +                          species.type = "multiplicative",
  +                          rescale = TRUE,
  +                          rescale.each.response = TRUE)
  Generating virtual species environmental suitability...
  
   - The response to each variable was rescaled between 0 and 1. To
              disable, set argument rescale.each.response = FALSE
  
   - The final environmental suitability was rescaled between 0 and 1. To disable, set argument rescale = FALSE
  
  [1] "sqrt(variable1) + variable2 + 2 * variable2^2 + variable2^3"
  > 
  > 
  > sp2 <- convertToPA(sp1,
  +                    PA.method = "threshold")
     --- Generating a random value of beta for the threshold conversion
  
  
     Threshold conversion finished:
                
  - cutoff = 0.428428428428428
  - species prevalence =0.1298
  
  
  > sp2 <- convertToPA(sp1,
  +                    PA.method = "threshold",
  +                    beta = 0.5)
     Threshold conversion finished:
                
  - cutoff = 0.5
  - species prevalence =0.1023
  
  
  > sp2 <- convertToPA(sp1,
  +                    PA.method = "threshold",
  +                    beta = 0)
     Threshold conversion finished:
                
  - cutoff = 0
  - species prevalence =0.9999
  
  
  > sp2 <- convertToPA(sp1,
  +                    PA.method = "threshold",
  +                    beta = 1)
     Threshold conversion finished:
                
  - cutoff = 1
  - species prevalence =0
  
  
  > sp2 <- convertToPA(sp1,
  +                    PA.method = "threshold",
  +                    beta = "random")
     --- Generating a random value of beta for the threshold conversion
  
  
     Threshold conversion finished:
                
  - cutoff = 0.265265265265265
  - species prevalence =0.2256
  
  
  > sp2 <- convertToPA(sp1,
  +                    PA.method = "threshold",
  +                    species.prevalence = .2)
     Threshold conversion finished:
                
  - cutoff = 0.298037629032326
  - species prevalence =0.2
  
  
  > sp2 <- convertToPA(sp1,
  +                    PA.method = "threshold",
  +                    species.prevalence = .02)
     Threshold conversion finished:
                
  - cutoff = 0.8172017320348
  - species prevalence =0.0199
  
  
  > sp2 <- convertToPA(sp1,
  +                    PA.method = "threshold",
  +                    species.prevalence = .9)
     Threshold conversion finished:
                
  - cutoff = 0.0470198966430044
  - species prevalence =0.9
  
  
  > sp2 <- convertToPA(sp1,
  +                    PA.method = "threshold",
  +                    species.prevalence = .99)
     Threshold conversion finished:
                
  - cutoff = 0.00959072698507723
  - species prevalence =0.9899
  
  
  > sp2 <- convertToPA(sp1,
  +                    PA.method = "probability",
  +                    prob.method = "logistic",
  +                    beta = "random",
  +                    a = NULL,
  +                    b = NULL,
  +                    species.prevalence = .99)
     --- Determing beta automatically according to alpha and species.prevalence
  
  
     Logistic conversion finished:
                
  - beta = -0.1328125
  - alpha = -0.05
  - species prevalence =0.9893
  
  
  > sp2 <- convertToPA(sp1,
  +                    PA.method = "probability",
  +                    prob.method = "logistic",
  +                    beta = "random",
  +                    a = NULL,
  +                    b = NULL,
  +                    species.prevalence = .5)
     --- Determing beta automatically according to alpha and species.prevalence
  
  
     Logistic conversion finished:
                
  - beta = 0.14892578125
  - alpha = -0.05
  - species prevalence =0.4955
  
  
  > sp2 <- convertToPA(sp1,
  +                    PA.method = "probability",
  +                    prob.method = "logistic",
  +                    beta = .5,
  +                    a = NULL,
  +                    b = NULL)
     --- Determing species.prevalence automatically according to alpha and beta
  
  
     Logistic conversion finished:
                
  - beta = 0.5
  - alpha = -0.05
  - species prevalence =0.1062
  
  
  > 
  > 
  > sp3 <- generateRandomSp(env)
   - Determining species' response to predictor variables
  
   - Calculating species suitability
  
  Generating virtual species environmental suitability...
  
   - The response to each variable was rescaled between 0 and 1. To
              disable, set argument rescale.each.response = FALSE
  
   - The final environmental suitability was rescaled between 0 and 1. To disable, set argument rescale = FALSE
  
   - Converting into Presence - Absence
  
     --- Generating a random value of beta for the logistic conversion
  
  
     --- Determing species.prevalence automatically according to alpha and beta
  
  
     Logistic conversion finished:
                
  - beta = 0.702702702702703
  - alpha = -0.1
  - species prevalence =0.1896
  
  
  > 
  > a <- matrix(rep(dnorm(1:100, 50, sd = 25)),
  +             nrow = 100, ncol = 100, byrow = TRUE)
  > 
  > env1 <- c(rast(a * dnorm(1:100, 50, sd = 25)),
  +           rast(a * 1:100),
  +           rast(a),
  +           rast(t(a)))
  > names(env1) <- c("var1", "var2", "var3", "var4")
  > b <- matrix(rep(dnorm(1:100, 25, sd = 50)),
  +             nrow = 100, ncol = 100, byrow = TRUE)
  > 
  > env2 <- c(rast(b * dnorm(1:100, 50, sd = 25)),
  +           rast(b * 1:100),
  +           rast(b),
  +           rast(t(b)))
  > 
  > names(env2) <- c("var1", "var2", "var3", "var4")
  > 
  > # Generating a species with the BCA
  > sp4 <- generateSpFromBCA(raster.stack.current = env1, raster.stack.future = env2)
  Reading raster values. If it fails for very large rasters, use arguments 'sample.points = TRUE' and define a number of points to sample with 'nb.point'.
   - Perfoming the between component analysis
  
   - Defining the response of the species along the axis
  
   - Calculating current suitability values
  
   - Calculating future suitability values
  
     The final environmental suitability was rescaled between 0 and1. To disable, set argument rescale = FALSE
   - Ploting response and suitability
  
  > plotResponse(sp4)
  > 
  > sp4 <- convertToPA(sp4)
     --- Generating a random value of beta for the logistic conversion
  
  
     --- Determing species.prevalence automatically according to alpha and beta
  
  
     Logistic conversion finished:
                
  - beta = 0.868817919823679
  - alpha = -0.05
  - species prevalence =0.2619
  
  
  > plotSuitabilityToProba(sp4)
  > 
  > sp4 <- convertToPA(sp4,
  +                    PA.method = "threshold")
     --- Generating a random value of beta for the threshold conversion
  
  
     Threshold conversion finished:
                
  - cutoff = 0.858808496784236
  - species prevalence =0.2985
  
  
  > plotSuitabilityToProba(sp4)
  > sp4 <- convertToPA(sp4,
  +                    PA.method = "threshold",
  +                    beta = 0.5)
     Threshold conversion finished:
                
  - cutoff = 0.5
  - species prevalence =0.6484
  
  
  > plotSuitabilityToProba(sp4)
  > sp4 <- convertToPA(sp4,
  +                    PA.method = "threshold",
  +                    beta = 0)
     Threshold conversion finished:
                
  - cutoff = 0
  - species prevalence =0.9999
  
  
  > plotSuitabilityToProba(sp4)
  > sp4 <- convertToPA(sp4,
  +                    PA.method = "threshold",
  +                    beta = 1)
     Threshold conversion finished:
                
  - cutoff = 1
  - species prevalence =0
  
  
  Warning message:
  In convertToPA(sp4, PA.method = "threshold", beta = 1) :
    beta is higher than all values in your suitability raster. 
                  The species will most likely be absent everywhere
  > plotSuitabilityToProba(sp4)
  > sp4 <- convertToPA(sp4,
  +                    PA.method = "threshold",
  +                    beta = "random")
     --- Generating a random value of beta for the threshold conversion
  
  
     Threshold conversion finished:
                
  - cutoff = 0.125117787993041
  - species prevalence =0.9316
  
  
  > plotSuitabilityToProba(sp4)
  > sp4 <- convertToPA(sp4,
  +                    PA.method = "threshold",
  +                    species.prevalence = .2)
     Threshold conversion finished:
                
  - cutoff = 0.909265865289973
  - species prevalence =0.1999
  
  
  > plotSuitabilityToProba(sp4)
  > sp4 <- convertToPA(sp4,
  +                    PA.method = "threshold",
  +                    species.prevalence = .02)
     Threshold conversion finished:
                
  - cutoff = 0.989971709449041
  - species prevalence =0.02
  
  
  > plotSuitabilityToProba(sp4)
  > sp4 <- convertToPA(sp4,
  +                    PA.method = "threshold",
  +                    species.prevalence = .9)
     Threshold conversion finished:
                
  - cutoff = 0.154929320988893
  - species prevalence =0.9
  
  
  > plotSuitabilityToProba(sp4)
  > sp4 <- convertToPA(sp4,
  +                    PA.method = "threshold",
  +                    species.prevalence = .99)
     Threshold conversion finished:
                
  - cutoff = 0.0144422372020715
  - species prevalence =0.9899
  
  
  > plotSuitabilityToProba(sp4)
  > sp4 <- convertToPA(sp4,
  +                    PA.method = "probability",
  +                    prob.method = "logistic",
  +                    beta = "random",
  +                    a = NULL,
  +                    b = NULL,
  +                    species.prevalence = .99)
     --- Determing beta automatically according to alpha and species.prevalence
  
  
     Logistic conversion finished:
                
  - beta = -0.0468722513268931
  - alpha = -0.05
  - species prevalence =0.9887
  
  
  > plotSuitabilityToProba(sp4)
  > sp4 <- convertToPA(sp4,
  +                    PA.method = "probability",
  +                    prob.method = "logistic",
  +                    beta = "random",
  +                    a = NULL,
  +                    b = NULL,
  +                    species.prevalence = .5)
     --- Determing beta automatically according to alpha and species.prevalence
  
  
     Logistic conversion finished:
                
  - beta = 0.699177748959489
  - alpha = -0.05
  - species prevalence =0.5019
  
  
  > plotSuitabilityToProba(sp4)
  > sp4 <- convertToPA(sp4,
  +                    PA.method = "probability",
  +                    prob.method = "logistic",
  +                    beta = .5,
  +                    a = NULL,
  +                    b = NULL)
     --- Determing species.prevalence automatically according to alpha and beta
  
  
     Logistic conversion finished:
                
  - beta = 0.5
  - alpha = -0.05
  - species prevalence =0.648
  
  
  > plotSuitabilityToProba(sp4)
  > 
  > 
  > for(i in 1:100){
  +   sp5 <- generateRandomSp(env)
  + }
   - Determining species' response to predictor variables
  
   - Calculating species suitability
  
  Generating virtual species environmental suitability...
  
   - The response to each variable was rescaled between 0 and 1. To
              disable, set argument rescale.each.response = FALSE
  
   - The final environmental suitability was rescaled between 0 and 1. To disable, set argument rescale = FALSE
  
   - Converting into Presence - Absence
  
     --- Generating a random value of beta for the logistic conversion
  
  
     --- Determing species.prevalence automatically according to alpha and beta
  
  
     Logistic conversion finished:
                
  - beta = 0.741741741741742
  - alpha = -0.1
  - species prevalence =0.093
  
  
   - Determining species' response to predictor variables
  
   - Calculating species suitability
  
  Generating virtual species environmental suitability...
  
   - The response to each variable was rescaled between 0 and 1. To
              disable, set argument rescale.each.response = FALSE
  
   - The final environmental suitability was rescaled between 0 and 1. To disable, set argument rescale = FALSE
  
   - Converting into Presence - Absence
  
     --- Generating a random value of beta for the logistic conversion
  
  
     --- Determing species.prevalence automatically according to alpha and beta
  
  
     Logistic conversion finished:
                
  - beta = 0.326326326326326
  - alpha = -0.1
  - species prevalence =0.1151
  
  
   - Determining species' response to predictor variables
  
   - Calculating species suitability
  
  Generating virtual species environmental suitability...
  
   - The response to each variable was rescaled between 0 and 1. To
              disable, set argument rescale.each.response = FALSE
  
   - The final environmental suitability was rescaled between 0 and 1. To disable, set argument rescale = FALSE
  
   - Converting into Presence - Absence
  
     --- Generating a random value of beta for the logistic conversion
  
  
     --- Determing species.prevalence automatically according to alpha and beta
  
  
     Logistic conversion finished:
                
  - beta = 0.342342342342342
  - alpha = -0.1
  - species prevalence =0.2329
  
  
   - Determining species' response to predictor variables
  
   - Calculating species suitability
  
  Generating virtual species environmental suitability...
  
   - The response to each variable was rescaled between 0 and 1. To
              disable, set argument rescale.each.response = FALSE
  
   - The final environmental suitability was rescaled between 0 and 1. To disable, set argument rescale = FALSE
  
   - Converting into Presence - Absence
  
     --- Generating a random value of beta for the logistic conversion
  
  
     --- Determing species.prevalence automatically according to alpha and beta
  
  
     Logistic conversion finished:
                
  - beta = 0.306306306306306
  - alpha = -0.1
  - species prevalence =0.1896
  
  
   - Determining species' response to predictor variables
  
   - Calculating species suitability
  
  Generating virtual species environmental suitability...
  
   - The response to each variable was rescaled between 0 and 1. To
              disable, set argument rescale.each.response = FALSE
  
   - The final environmental suitability was rescaled between 0 and 1. To disable, set argument rescale = FALSE
  
   - Converting into Presence - Absence
  
     --- Generating a random value of beta for the logistic conversion
  
  
     --- Determing species.prevalence automatically according to alpha and beta
  
  
     Logistic conversion finished:
                
  - beta = 0.468468468468468
  - alpha = -0.1
  - species prevalence =0.2927
  
  
   - Determining species' response to predictor variables
  
   - Calculating species suitability
  
  Generating virtual species environmental suitability...
  
   - The response to each variable was rescaled between 0 and 1. To
              disable, set argument rescale.each.response = FALSE
  
   - The final environmental suitability was rescaled between 0 and 1. To disable, set argument rescale = FALSE
  
   - Converting into Presence - Absence
  
     --- Generating a random value of beta for the logistic conversion
  
  
     --- Determing species.prevalence automatically according to alpha and beta
  
  
     Logistic conversion finished:
                
  - beta = 0.332332332332332
  - alpha = -0.1
  - species prevalence =0.2935
  
  
   - Determining species' response to predictor variables
  
   - Calculating species suitability
  
  Generating virtual species environmental suitability...
  
   - The response to each variable was rescaled between 0 and 1. To
              disable, set argument rescale.each.response = FALSE
  
   - The final environmental suitability was rescaled between 0 and 1. To disable, set argument rescale = FALSE
  
   - Converting into Presence - Absence
  
     --- Generating a random value of beta for the logistic conversion
  
  
     --- Determing species.prevalence automatically according to alpha and beta
  
  
     Logistic conversion finished:
                
  - beta = 0.951951951951952
  - alpha = -0.1
  - species prevalence =0.0453
  
  
   - Determining species' response to predictor variables
  
   - Calculating species suitability
  
  Generating virtual species environmental suitability...
  
   - The response to each variable was rescaled between 0 and 1. To
              disable, set argument rescale.each.response = FALSE
  
   - The final environmental suitability was rescaled between 0 and 1. To disable, set argument rescale = FALSE
  
   - Converting into Presence - Absence
  
     --- Generating a random value of beta for the logistic conversion
  
  
     --- Determing species.prevalence automatically according to alpha and beta
  
  
     Logistic conversion finished:
                
  - beta = 0.492492492492492
  - alpha = -0.1
  - species prevalence =0.0572
  
  
   - Determining species' response to predictor variables
  
   - Calculating species suitability
  
  Generating virtual species environmental suitability...
  
   - The response to each variable was rescaled between 0 and 1. To
              disable, set argument rescale.each.response = FALSE
  
   - The final environmental suitability was rescaled between 0 and 1. To disable, set argument rescale = FALSE
  
   - Converting into Presence - Absence
  
     --- Generating a random value of beta for the logistic conversion
  
  
     --- Determing species.prevalence automatically according to alpha and beta
  
  
     Logistic conversion finished:
                
  - beta = 0.529529529529529
  - alpha = -0.1
  - species prevalence =0.5969
  
  
   - Determining species' response to predictor variables
  
   - Calculating species suitability
  
  Generating virtual species environmental suitability...
  
   - The response to each variable was rescaled between 0 and 1. To
              disable, set argument rescale.each.response = FALSE
  
   - The final environmental suitability was rescaled between 0 and 1. To disable, set argument rescale = FALSE
  
   - Converting into Presence - Absence
  
     --- Generating a random value of beta for the logistic conversion
  
  
     --- Determing species.prevalence automatically according to alpha and beta
  
  
     Logistic conversion finished:
                
  - beta = 0.535535535535536
  - alpha = -0.1
  - species prevalence =0.0846
  
  
   - Determining species' response to predictor variables
  
   - Calculating species suitability
  
  Generating virtual species environmental suitability...
  
   - The response to each variable was rescaled between 0 and 1. To
              disable, set argument rescale.each.response = FALSE
  
   - The final environmental suitability was rescaled between 0 and 1. To disable, set argument rescale = FALSE
  
   - Converting into Presence - Absence
  
     --- Generating a random value of beta for the logistic conversion
  
  
     --- Determing species.prevalence automatically according to alpha and beta
  
  
     Logistic conversion finished:
                
  - beta = 0.755755755755756
  - alpha = -0.1
  - species prevalence =0.03
  
  
   - Determining species' response to predictor variables
  
   - Calculating species suitability
  
  Generating virtual species environmental suitability...
  
   - The response to each variable was rescaled between 0 and 1. To
              disable, set argument rescale.each.response = FALSE
  
   - The final environmental suitability was rescaled between 0 and 1. To disable, set argument rescale = FALSE
  
   - Converting into Presence - Absence
  
     --- Generating a random value of beta for the logistic conversion
  
  
     --- Determing species.prevalence automatically according to alpha and beta
  
  
     Logistic conversion finished:
                
  - beta = 0.0690690690690691
  - alpha = -0.1
  - species prevalence =0.8632
  
  
   - Determining species' response to predictor variables
  
   - Calculating species suitability
  
  Generating virtual species environmental suitability...
  
   - The response to each variable was rescaled between 0 and 1. To
              disable, set argument rescale.each.response = FALSE
  
   - The final environmental suitability was rescaled between 0 and 1. To disable, set argument rescale = FALSE
  
   - Converting into Presence - Absence
  
     --- Generating a random value of beta for the logistic conversion
  
  
     --- Determing species.prevalence automatically according to alpha and beta
  
  
     Logistic conversion finished:
                
  - beta = 0.836836836836837
  - alpha = -0.1
  - species prevalence =0.0037
  
  
   - Determining species' response to predictor variables
  
   - Calculating species suitability
  
  Generating virtual species environmental suitability...
  
   - The response to each variable was rescaled between 0 and 1. To
              disable, set argument rescale.each.response = FALSE
  
   - The final environmental suitability was rescaled between 0 and 1. To disable, set argument rescale = FALSE
  
   - Converting into Presence - Absence
  
     --- Generating a random value of beta for the logistic conversion
  
  
     --- Determing species.prevalence automatically according to alpha and beta
  
  
     Logistic conversion finished:
                
  - beta = 0.812812812812813
  - alpha = -0.1
  - species prevalence =0.1502
  
  
   - Determining species' response to predictor variables
  
   - Calculating species suitability
  
  Generating virtual species environmental suitability...
  
   - The response to each variable was rescaled between 0 and 1. To
              disable, set argument rescale.each.response = FALSE
  
   - The final environmental suitability was rescaled between 0 and 1. To disable, set argument rescale = FALSE
  
   - Converting into Presence - Absence
  
     --- Generating a random value of beta for the logistic conversion
  
  
     --- Determing species.prevalence automatically according to alpha and beta
  
  
     Logistic conversion finished:
                
  - beta = 0.354354354354354
  - alpha = -0.1
  - species prevalence =0.2016
  
  
   - Determining species' response to predictor variables
  
   - Calculating species suitability
  
  Generating virtual species environmental suitability...
  
   - The response to each variable was rescaled between 0 and 1. To
              disable, set argument rescale.each.response = FALSE
  
   - The final environmental suitability was rescaled between 0 and 1. To disable, set argument rescale = FALSE
  
   - Converting into Presence - Absence
  
     --- Generating a random value of beta for the logistic conversion
  
  
     --- Determing species.prevalence automatically according to alpha and beta
  
  
     Logistic conversion finished:
                
  - beta = 0.332332332332332
  - alpha = -0.1
  - species prevalence =0.341
  
  
   - Determining species' response to predictor variables
  
   - Calculating species suitability
  
  Generating virtual species environmental suitability...
  
   - The response to each variable was rescaled between 0 and 1. To
              disable, set argument rescale.each.response = FALSE
  
   - The final environmental suitability was rescaled between 0 and 1. To disable, set argument rescale = FALSE
  
   - Converting into Presence - Absence
  
     --- Generating a random value of beta for the logistic conversion
  
  
     --- Determing species.prevalence automatically according to alpha and beta
  
  
     Logistic conversion finished:
                
  - beta = 0.795795795795796
  - alpha = -0.1
  - species prevalence =0.4293
  
  
   - Determining species' response to predictor variables
  
   - Calculating species suitability
  
  Generating virtual species environmental suitability...
  
   - The response to each variable was rescaled between 0 and 1. To
              disable, set argument rescale.each.response = FALSE
  
   - The final environmental suitability was rescaled between 0 and 1. To disable, set argument rescale = FALSE
  
   - Converting into Presence - Absence
  
     --- Generating a random value of beta for the logistic conversion
  
  
     --- Determing species.prevalence automatically according to alpha and beta
  
  
     Logistic conversion finished:
                
  - beta = 0.666666666666667
  - alpha = -0.1
  - species prevalence =0.146
  
  
   - Determining species' response to predictor variables
  
   - Calculating species suitability
  
  Generating virtual species environmental suitability...
  
   - The response to each variable was rescaled between 0 and 1. To
              disable, set argument rescale.each.response = FALSE
  
   - The final environmental suitability was rescaled between 0 and 1. To disable, set argument rescale = FALSE
  
   - Converting into Presence - Absence
  
     --- Generating a random value of beta for the logistic conversion
  
  
     --- Determing species.prevalence automatically according to alpha and beta
  
  
     Logistic conversion finished:
                
  - beta = 0.717717717717718
  - alpha = -0.1
  - species prevalence =0.0793
  
  
   - Determining species' response to predictor variables
  
   - Calculating species suitability
  
  Generating virtual species environmental suitability...
  
   - The response to each variable was rescaled between 0 and 1. To
              disable, set argument rescale.each.response = FALSE
  
   - The final environmental suitability was rescaled between 0 and 1. To disable, set argument rescale = FALSE
  
   - Converting into Presence - Absence
  
     --- Generating a random value of beta for the logistic conversion
  
  
     --- Determing species.prevalence automatically according to alpha and beta
  
  
     Logistic conversion finished:
                
  - beta = 0.791791791791792
  - alpha = -0.1
  - species prevalence =0.0047
  
  
   - Determining species' response to predictor variables
  
   - Calculating species suitability
  
  Generating virtual species environmental suitability...
  
   - The response to each variable was rescaled between 0 and 1. To
              disable, set argument rescale.each.response = FALSE
  
   - The final environmental suitability was rescaled between 0 and 1. To disable, set argument rescale = FALSE
  
   - Converting into Presence - Absence
  
     --- Generating a random value of beta for the logistic conversion
  
  
     --- Determing species.prevalence automatically according to alpha and beta
  
  
     Logistic conversion finished:
                
  - beta = 0.38038038038038
  - alpha = -0.1
  - species prevalence =0.2706
  
  
   - Determining species' response to predictor variables
  
   - Calculating species suitability
  
  Generating virtual species environmental suitability...
  
   - The response to each variable was rescaled between 0 and 1. To
              disable, set argument rescale.each.response = FALSE
  
   - The final environmental suitability was rescaled between 0 and 1. To disable, set argument rescale = FALSE
  
   - Converting into Presence - Absence
  
     --- Generating a random value of beta for the logistic conversion
  
  
     --- Determing species.prevalence automatically according to alpha and beta
  
  
     Logistic conversion finished:
                
  - beta = 0.590590590590591
  - alpha = -0.1
  - species prevalence =0.5129
  
  
   - Determining species' response to predictor variables
  
   - Calculating species suitability
  
  Generating virtual species environmental suitability...
  
   - The response to each variable was rescaled between 0 and 1. To
              disable, set argument rescale.each.response = FALSE
  
   - The final environmental suitability was rescaled between 0 and 1. To disable, set argument rescale = FALSE
  
   - Converting into Presence - Absence
  
     --- Generating a random value of beta for the logistic conversion
  
  
     --- Determing species.prevalence automatically according to alpha and beta
  
  
     Logistic conversion finished:
                
  - beta = 0.64964964964965
  - alpha = -0.1
  - species prevalence =0.5246
  
  
   - Determining species' response to predictor variables
  
   - Calculating species suitability
  
  Generating virtual species environmental suitability...
  
   - The response to each variable was rescaled between 0 and 1. To
              disable, set argument rescale.each.response = FALSE
  
   - The final environmental suitability was rescaled between 0 and 1. To disable, set argument rescale = FALSE
  
   - Converting into Presence - Absence
  
     --- Generating a random value of beta for the logistic conversion
  
  
     --- Determing species.prevalence automatically according to alpha and beta
  
  
     Logistic conversion finished:
                
  - beta = 0.325325325325325
  - alpha = -0.1
  - species prevalence =0.654
  
  
   - Determining species' response to predictor variables
  
   - Calculating species suitability
  
  Generating virtual species environmental suitability...
  
   - The response to each variable was rescaled between 0 and 1. To
              disable, set argument rescale.each.response = FALSE
  
   - The final environmental suitability was rescaled between 0 and 1. To disable, set argument rescale = FALSE
  
   - Converting into Presence - Absence
  
     --- Generating a random value of beta for the logistic conversion
  
  
     --- Determing species.prevalence automatically according to alpha and beta
  
  
     Logistic conversion finished:
                
  - beta = 0.336336336336336
  - alpha = -0.1
  - species prevalence =0.5936
  
  
   - Determining species' response to predictor variables
  
   - Calculating species suitability
  
  Generating virtual species environmental suitability...
  
   - The response to each variable was rescaled between 0 and 1. To
              disable, set argument rescale.each.response = FALSE
  
   - The final environmental suitability was rescaled between 0 and 1. To disable, set argument rescale = FALSE
  
   - Converting into Presence - Absence
  
     --- Generating a random value of beta for the logistic conversion
  
  
     --- Determing species.prevalence automatically according to alpha and beta
  
  
     Logistic conversion finished:
                
  - beta = 0.412412412412412
  - alpha = -0.1
  - species prevalence =0.402
  
  
   - Determining species' response to predictor variables
  
   - Calculating species suitability
  
  Generating virtual species environmental suitability...
  
   - The response to each variable was rescaled between 0 and 1. To
              disable, set argument rescale.each.response = FALSE
  
   - The final environmental suitability was rescaled between 0 and 1. To disable, set argument rescale = FALSE
  
   - Converting into Presence - Absence
  
     --- Generating a random value of beta for the logistic conversion
  
  
     --- Determing species.prevalence automatically according to alpha and beta
  
  
     Logistic conversion finished:
                
  - beta = 0.792792792792793
  - alpha = -0.1
  - species prevalence =0.0926
  
  
   - Determining species' response to predictor variables
  
   - Calculating species suitability
  
  Generating virtual species environmental suitability...
  
   - The response to each variable was rescaled between 0 and 1. To
              disable, set argument rescale.each.response = FALSE
  
   - The final environmental suitability was rescaled between 0 and 1. To disable, set argument rescale = FALSE
  
   - Converting into Presence - Absence
  
     --- Generating a random value of beta for the logistic conversion
  
  
     --- Determing species.prevalence automatically according to alpha and beta
  
  
     Logistic conversion finished:
                
  - beta = 0.342342342342342
  - alpha = -0.1
  - species prevalence =0.5358
  
  
   - Determining species' response to predictor variables
  
   - Calculating species suitability
  
  Generating virtual species environmental suitability...
  
   - The response to each variable was rescaled between 0 and 1. To
              disable, set argument rescale.each.response = FALSE
  
   - The final environmental suitability was rescaled between 0 and 1. To disable, set argument rescale = FALSE
  
   - Converting into Presence - Absence
  
     --- Generating a random value of beta for the logistic conversion
  
  
     --- Determing species.prevalence automatically according to alpha and beta
  
  
     Logistic conversion finished:
                
  - beta = 0.995995995995996
  - alpha = -0.1
  - species prevalence =0.0139
  
  
   - Determining species' response to predictor variables
  
   - Calculating species suitability
  
  Generating virtual species environmental suitability...
  
   - The response to each variable was rescaled between 0 and 1. To
              disable, set argument rescale.each.response = FALSE
  
   - The final environmental suitability was rescaled between 0 and 1. To disable, set argument rescale = FALSE
  
   - Converting into Presence - Absence
  
     --- Generating a random value of beta for the logistic conversion
  
  
     --- Determing species.prevalence automatically according to alpha and beta
  
  
     Logistic conversion finished:
                
  - beta = 0.275275275275275
  - alpha = -0.1
  - species prevalence =0.4425
  
  
   - Determining species' response to predictor variables
  
   - Calculating species suitability
  
  Generating virtual species environmental suitability...
  
   - The response to each variable was rescaled between 0 and 1. To
              disable, set argument rescale.each.response = FALSE
  
   - The final environmental suitability was rescaled between 0 and 1. To disable, set argument rescale = FALSE
  
   - Converting into Presence - Absence
  
     --- Generating a random value of beta for the logistic conversion
  
  
     --- Determing species.prevalence automatically according to alpha and beta
  
  
     Logistic conversion finished:
                
  - beta = 0.349349349349349
  - alpha = -0.1
  - species prevalence =0.2645
  
  
   - Determining species' response to predictor variables
  
   - Calculating species suitability
  
  Generating virtual species environmental suitability...
  
   - The response to each variable was rescaled between 0 and 1. To
              disable, set argument rescale.each.response = FALSE
  
   - The final environmental suitability was rescaled between 0 and 1. To disable, set argument rescale = FALSE
  
   - Converting into Presence - Absence
  
     --- Generating a random value of beta for the logistic conversion
  
  
     --- Determing species.prevalence automatically according to alpha and beta
  
  
     Logistic conversion finished:
                
  - beta = 0.633633633633634
  - alpha = -0.1
  - species prevalence =0.0718
  
  
   - Determining species' response to predictor variables
  
   - Calculating species suitability
  
  Generating virtual species environmental suitability...
  
   - The response to each variable was rescaled between 0 and 1. To
              disable, set argument rescale.each.response = FALSE
  
   - The final environmental suitability was rescaled between 0 and 1. To disable, set argument rescale = FALSE
  
   - Converting into Presence - Absence
  
     --- Generating a random value of beta for the logistic conversion
  
  
     --- Determing species.prevalence automatically according to alpha and beta
  
  
     Logistic conversion finished:
                
  - beta = 0.157157157157157
  - alpha = -0.1
  - species prevalence =0.8046
  
  
   - Determining species' response to predictor variables
  
   - Calculating species suitability
  
  Generating virtual species environmental suitability...
  
   - The response to each variable was rescaled between 0 and 1. To
              disable, set argument rescale.each.response = FALSE
  
   - The final environmental suitability was rescaled between 0 and 1. To disable, set argument rescale = FALSE
  
   - Converting into Presence - Absence
  
     --- Generating a random value of beta for the logistic conversion
  
  
     --- Determing species.prevalence automatically according to alpha and beta
  
  
     Logistic conversion finished:
                
  - beta = 0.556556556556557
  - alpha = -0.1
  - species prevalence =0.1929
  
  
   - Determining species' response to predictor variables
  
   - Calculating species suitability
  
  Generating virtual species environmental suitability...
  
   - The response to each variable was rescaled between 0 and 1. To
              disable, set argument rescale.each.response = FALSE
  
   - The final environmental suitability was rescaled between 0 and 1. To disable, set argument rescale = FALSE
  
   - Converting into Presence - Absence
  
     --- Generating a random value of beta for the logistic conversion
  
  
     --- Determing species.prevalence automatically according to alpha and beta
  
  
     Logistic conversion finished:
                
  - beta = 0.201201201201201
  - alpha = -0.1
  - species prevalence =0.7007
  
  
   - Determining species' response to predictor variables
  
   - Calculating species suitability
  
  Generating virtual species environmental suitability...
  
   - The response to each variable was rescaled between 0 and 1. To
              disable, set argument rescale.each.response = FALSE
  
   - The final environmental suitability was rescaled between 0 and 1. To disable, set argument rescale = FALSE
  
   - Converting into Presence - Absence
  
     --- Generating a random value of beta for the logistic conversion
  
  
     --- Determing species.prevalence automatically according to alpha and beta
  
  
     Logistic conversion finished:
                
  - beta = 0.754754754754755
  - alpha = -0.1
  - species prevalence =0.0796
  
  
   - Determining species' response to predictor variables
  
   - Calculating species suitability
  
  Generating virtual species environmental suitability...
  
   - The response to each variable was rescaled between 0 and 1. To
              disable, set argument rescale.each.response = FALSE
  
   - The final environmental suitability was rescaled between 0 and 1. To disable, set argument rescale = FALSE
  
   - Converting into Presence - Absence
  
     --- Generating a random value of beta for the logistic conversion
  
  
     --- Determing species.prevalence automatically according to alpha and beta
  
  
     Logistic conversion finished:
                
  - beta = 0.857857857857858
  - alpha = -0.1
  - species prevalence =0.0086
  
  
   - Determining species' response to predictor variables
  
   - Calculating species suitability
  
  Generating virtual species environmental suitability...
  
   - The response to each variable was rescaled between 0 and 1. To
              disable, set argument rescale.each.response = FALSE
  
   - The final environmental suitability was rescaled between 0 and 1. To disable, set argument rescale = FALSE
  
   - Converting into Presence - Absence
  
     --- Generating a random value of beta for the logistic conversion
  
  
     --- Determing species.prevalence automatically according to alpha and beta
  
  
     Logistic conversion finished:
                
  - beta = 0.027027027027027
  - alpha = -0.1
  - species prevalence =0.8728
  
  
   - Determining species' response to predictor variables
  
   - Calculating species suitability
  
  Generating virtual species environmental suitability...
  
   - The response to each variable was rescaled between 0 and 1. To
              disable, set argument rescale.each.response = FALSE
  
   - The final environmental suitability was rescaled between 0 and 1. To disable, set argument rescale = FALSE
  
   - Converting into Presence - Absence
  
     --- Generating a random value of beta for the logistic conversion
  
  
     --- Determing species.prevalence automatically according to alpha and beta
  
  
     Logistic conversion finished:
                
  - beta = 0.824824824824825
  - alpha = -0.1
  - species prevalence =0.1089
  
  
   - Determining species' response to predictor variables
  
   - Calculating species suitability
  
  Generating virtual species environmental suitability...
  
   - The response to each variable was rescaled between 0 and 1. To
              disable, set argument rescale.each.response = FALSE
  
   - The final environmental suitability was rescaled between 0 and 1. To disable, set argument rescale = FALSE
  
   - Converting into Presence - Absence
  
     --- Generating a random value of beta for the logistic conversion
  
  
     --- Determing species.prevalence automatically according to alpha and beta
  
  
     Logistic conversion finished:
                
  - beta = 0.357357357357357
  - alpha = -0.1
  - species prevalence =0.6246
  
  
   - Determining species' response to predictor variables
  
   - Calculating species suitability
  
  Generating virtual species environmental suitability...
  
   - The response to each variable was rescaled between 0 and 1. To
              disable, set argument rescale.each.response = FALSE
  
   - The final environmental suitability was rescaled between 0 and 1. To disable, set argument rescale = FALSE
  
   - Converting into Presence - Absence
  
     --- Generating a random value of beta for the logistic conversion
  
  
     --- Determing species.prevalence automatically according to alpha and beta
  
  
     Logistic conversion finished:
                
  - beta = 0.379379379379379
  - alpha = -0.1
  - species prevalence =0.1959
  
  
   - Determining species' response to predictor variables
  
   - Calculating species suitability
  
  Generating virtual species environmental suitability...
  
   - The response to each variable was rescaled between 0 and 1. To
              disable, set argument rescale.each.response = FALSE
  
   - The final environmental suitability was rescaled between 0 and 1. To disable, set argument rescale = FALSE
  
   - Converting into Presence - Absence
  
     --- Generating a random value of beta for the logistic conversion
  
  
     --- Determing species.prevalence automatically according to alpha and beta
  
  
     Logistic conversion finished:
                
  - beta = 0.595595595595596
  - alpha = -0.1
  - species prevalence =0.1827
  
  
   - Determining species' response to predictor variables
  
   - Calculating species suitability
  
  Generating virtual species environmental suitability...
  
   - The response to each variable was rescaled between 0 and 1. To
              disable, set argument rescale.each.response = FALSE
  
   - The final environmental suitability was rescaled between 0 and 1. To disable, set argument rescale = FALSE
  
   - Converting into Presence - Absence
  
     --- Generating a random value of beta for the logistic conversion
  
  
     --- Determing species.prevalence automatically according to alpha and beta
  
  
     Logistic conversion finished:
                
  - beta = 0.469469469469469
  - alpha = -0.1
  - species prevalence =0.0146
  
  
   - Determining species' response to predictor variables
  
   - Calculating species suitability
  
  Generating virtual species environmental suitability...
  
   - The response to each variable was rescaled between 0 and 1. To
              disable, set argument rescale.each.response = FALSE
  
   - The final environmental suitability was rescaled between 0 and 1. To disable, set argument rescale = FALSE
  
   - Converting into Presence - Absence
  
     --- Generating a random value of beta for the logistic conversion
  
  
     --- Determing species.prevalence automatically according to alpha and beta
  
  
     Logistic conversion finished:
                
  - beta = 0.73973973973974
  - alpha = -0.1
  - species prevalence =0.0105
  
  
   - Determining species' response to predictor variables
  
   - Calculating species suitability
  
  Generating virtual species environmental suitability...
  
   - The response to each variable was rescaled between 0 and 1. To
              disable, set argument rescale.each.response = FALSE
  
   - The final environmental suitability was rescaled between 0 and 1. To disable, set argument rescale = FALSE
  
   - Converting into Presence - Absence
  
     --- Generating a random value of beta for the logistic conversion
  
  
     --- Determing species.prevalence automatically according to alpha and beta
  
  
     Logistic conversion finished:
                
  - beta = 0.378378378378378
  - alpha = -0.1
  - species prevalence =0.2983
  
  
   - Determining species' response to predictor variables
  
   - Calculating species suitability
  
  Generating virtual species environmental suitability...
  
   - The response to each variable was rescaled between 0 and 1. To
              disable, set argument rescale.each.response = FALSE
  
   - The final environmental suitability was rescaled between 0 and 1. To disable, set argument rescale = FALSE
  
   - Converting into Presence - Absence
  
     --- Generating a random value of beta for the logistic conversion
  
  
     --- Determing species.prevalence automatically according to alpha and beta
  
  
     Logistic conversion finished:
                
  - beta = 0.723723723723724
  - alpha = -0.1
  - species prevalence =0.0612
  
  
   - Determining species' response to predictor variables
  
   - Calculating species suitability
  
  Generating virtual species environmental suitability...
  
   - The response to each variable was rescaled between 0 and 1. To
              disable, set argument rescale.each.response = FALSE
  
   - The final environmental suitability was rescaled between 0 and 1. To disable, set argument rescale = FALSE
  
   - Converting into Presence - Absence
  
     --- Generating a random value of beta for the logistic conversion
  
  
     --- Determing species.prevalence automatically according to alpha and beta
  
  
     Logistic conversion finished:
                
  - beta = 0.189189189189189
  - alpha = -0.1
  - species prevalence =0.23
  
  
   - Determining species' response to predictor variables
  
   - Calculating species suitability
  
  Generating virtual species environmental suitability...
  
   - The response to each variable was rescaled between 0 and 1. To
              disable, set argument rescale.each.response = FALSE
  
   - The final environmental suitability was rescaled between 0 and 1. To disable, set argument rescale = FALSE
  
   - Converting into Presence - Absence
  
     --- Generating a random value of beta for the logistic conversion
  
  
     --- Determing species.prevalence automatically according to alpha and beta
  
  
     Logistic conversion finished:
                
  - beta = 0.359359359359359
  - alpha = -0.1
  - species prevalence =0.2719
  
  
   - Determining species' response to predictor variables
  
   - Calculating species suitability
  
  Generating virtual species environmental suitability...
  
   - The response to each variable was rescaled between 0 and 1. To
              disable, set argument rescale.each.response = FALSE
  
   - The final environmental suitability was rescaled between 0 and 1. To disable, set argument rescale = FALSE
  
   - Converting into Presence - Absence
  
     --- Generating a random value of beta for the logistic conversion
  
  
     --- Determing species.prevalence automatically according to alpha and beta
  
  
     Logistic conversion finished:
                
  - beta = 0.912912912912913
  - alpha = -0.1
  - species prevalence =0.3344
  
  
   - Determining species' response to predictor variables
  
   - Calculating species suitability
  
  Generating virtual species environmental suitability...
  
   - The response to each variable was rescaled between 0 and 1. To
              disable, set argument rescale.each.response = FALSE
  
   - The final environmental suitability was rescaled between 0 and 1. To disable, set argument rescale = FALSE
  
   - Converting into Presence - Absence
  
     --- Generating a random value of beta for the logistic conversion
  
  
     --- Determing species.prevalence automatically according to alpha and beta
  
  
     Logistic conversion finished:
                
  - beta = 0.408408408408408
  - alpha = -0.1
  - species prevalence =0.2891
  
  
   - Determining species' response to predictor variables
  
   - Calculating species suitability
  
  Generating virtual species environmental suitability...
  
   - The response to each variable was rescaled between 0 and 1. To
              disable, set argument rescale.each.response = FALSE
  
   - The final environmental suitability was rescaled between 0 and 1. To disable, set argument rescale = FALSE
  
   - Converting into Presence - Absence
  
     --- Generating a random value of beta for the logistic conversion
  
  
     --- Determing species.prevalence automatically according to alpha and beta
  
  
     Logistic conversion finished:
                
  - beta = 0.0560560560560561
  - alpha = -0.1
  - species prevalence =0.4277
  
  
   - Determining species' response to predictor variables
  
   - Calculating species suitability
  
  Generating virtual species environmental suitability...
  
   - The response to each variable was rescaled between 0 and 1. To
              disable, set argument rescale.each.response = FALSE
  
   - The final environmental suitability was rescaled between 0 and 1. To disable, set argument rescale = FALSE
  
   - Converting into Presence - Absence
  
     --- Generating a random value of beta for the logistic conversion
  
  
     --- Determing species.prevalence automatically according to alpha and beta
  
  
     Logistic conversion finished:
                
  - beta = 0.109109109109109
  - alpha = -0.1
  - species prevalence =0.8193
  
  
   - Determining species' response to predictor variables
  
   - Calculating species suitability
  
  Generating virtual species environmental suitability...
  
   - The response to each variable was rescaled between 0 and 1. To
              disable, set argument rescale.each.response = FALSE
  
   - The final environmental suitability was rescaled between 0 and 1. To disable, set argument rescale = FALSE
  
   - Converting into Presence - Absence
  
     --- Generating a random value of beta for the logistic conversion
  
  
     --- Determing species.prevalence automatically according to alpha and beta
  
  
     Logistic conversion finished:
                
  - beta = 0.981981981981982
  - alpha = -0.1
  - species prevalence =0.0155
  
  
   - Determining species' response to predictor variables
  
   - Calculating species suitability
  
  Generating virtual species environmental suitability...
  
   - The response to each variable was rescaled between 0 and 1. To
              disable, set argument rescale.each.response = FALSE
  
   - The final environmental suitability was rescaled between 0 and 1. To disable, set argument rescale = FALSE
  
   - Converting into Presence - Absence
  
     --- Generating a random value of beta for the logistic conversion
  
  
     --- Determing species.prevalence automatically according to alpha and beta
  
  
     Logistic conversion finished:
                
  - beta = 0.582582582582583
  - alpha = -0.1
  - species prevalence =0.018
  
  
   - Determining species' response to predictor variables
  
   - Calculating species suitability
  
  Generating virtual species environmental suitability...
  
   - The response to each variable was rescaled between 0 and 1. To
              disable, set argument rescale.each.response = FALSE
  
   - The final environmental suitability was rescaled between 0 and 1. To disable, set argument rescale = FALSE
  
   - Converting into Presence - Absence
  
     --- Generating a random value of beta for the logistic conversion
  
  
     --- Determing species.prevalence automatically according to alpha and beta
  
  
     Logistic conversion finished:
                
  - beta = 0.650650650650651
  - alpha = -0.1
  - species prevalence =0.1405
  
  
   - Determining species' response to predictor variables
  
   - Calculating species suitability
  
  Generating virtual species environmental suitability...
  
   - The response to each variable was rescaled between 0 and 1. To
              disable, set argument rescale.each.response = FALSE
  
   - The final environmental suitability was rescaled between 0 and 1. To disable, set argument rescale = FALSE
  
   - Converting into Presence - Absence
  
     --- Generating a random value of beta for the logistic conversion
  
  
     --- Determing species.prevalence automatically according to alpha and beta
  
  
     Logistic conversion finished:
                
  - beta = 0.028028028028028
  - alpha = -0.1
  - species prevalence =0.9317
  
  
   - Determining species' response to predictor variables
  
   - Calculating species suitability
  
  Generating virtual species environmental suitability...
  
   - The response to each variable was rescaled between 0 and 1. To
              disable, set argument rescale.each.response = FALSE
  
   - The final environmental suitability was rescaled between 0 and 1. To disable, set argument rescale = FALSE
  
   - Converting into Presence - Absence
  
     --- Generating a random value of beta for the logistic conversion
  
  
     --- Determing species.prevalence automatically according to alpha and beta
  
  
     Logistic conversion finished:
                
  - beta = 0.221221221221221
  - alpha = -0.1
  - species prevalence =0.4407
  
  
   - Determining species' response to predictor variables
  
   - Calculating species suitability
  
  Generating virtual species environmental suitability...
  
   - The response to each variable was rescaled between 0 and 1. To
              disable, set argument rescale.each.response = FALSE
  
   - The final environmental suitability was rescaled between 0 and 1. To disable, set argument rescale = FALSE
  
   - Converting into Presence - Absence
  
     --- Generating a random value of beta for the logistic conversion
  
  
     --- Determing species.prevalence automatically according to alpha and beta
  
  
     Logistic conversion finished:
                
  - beta = 0.136136136136136
  - alpha = -0.1
  - species prevalence =0.8571
  
  
   - Determining species' response to predictor variables
  
   - Calculating species suitability
  
  Generating virtual species environmental suitability...
  
   - The response to each variable was rescaled between 0 and 1. To
              disable, set argument rescale.each.response = FALSE
  
   - The final environmental suitability was rescaled between 0 and 1. To disable, set argument rescale = FALSE
  
   - Converting into Presence - Absence
  
     --- Generating a random value of beta for the logistic conversion
  
  
     --- Determing species.prevalence automatically according to alpha and beta
  
  
     Logistic conversion finished:
                
  - beta = 0.507507507507508
  - alpha = -0.1
  - species prevalence =0.6317
  
  
   - Determining species' response to predictor variables
  
   - Calculating species suitability
  
  Generating virtual species environmental suitability...
  
   - The response to each variable was rescaled between 0 and 1. To
              disable, set argument rescale.each.response = FALSE
  
   - The final environmental suitability was rescaled between 0 and 1. To disable, set argument rescale = FALSE
  
   - Converting into Presence - Absence
  
     --- Generating a random value of beta for the logistic conversion
  
  
     --- Determing species.prevalence automatically according to alpha and beta
  
  
     Logistic conversion finished:
                
  - beta = 0.641641641641642
  - alpha = -0.1
  - species prevalence =0.8638
  
  
   - Determining species' response to predictor variables
  
   - Calculating species suitability
  
  Generating virtual species environmental suitability...
  
   - The response to each variable was rescaled between 0 and 1. To
              disable, set argument rescale.each.response = FALSE
  
   - The final environmental suitability was rescaled between 0 and 1. To disable, set argument rescale = FALSE
  
   - Converting into Presence - Absence
  
     --- Generating a random value of beta for the logistic conversion
  
  
     --- Determing species.prevalence automatically according to alpha and beta
  
  
     Logistic conversion finished:
                
  - beta = 0.385385385385385
  - alpha = -0.1
  - species prevalence =0.5381
  
  
   - Determining species' response to predictor variables
  
   - Calculating species suitability
  
  Generating virtual species environmental suitability...
  
   - The response to each variable was rescaled between 0 and 1. To
              disable, set argument rescale.each.response = FALSE
  
   - The final environmental suitability was rescaled between 0 and 1. To disable, set argument rescale = FALSE
  
   - Converting into Presence - Absence
  
     --- Generating a random value of beta for the logistic conversion
  
  
     --- Determing species.prevalence automatically according to alpha and beta
  
  
     Logistic conversion finished:
                
  - beta = 0.358358358358358
  - alpha = -0.1
  - species prevalence =0.4483
  
  
   - Determining species' response to predictor variables
  
   - Calculating species suitability
  
  Generating virtual species environmental suitability...
  
   - The response to each variable was rescaled between 0 and 1. To
              disable, set argument rescale.each.response = FALSE
  
   - The final environmental suitability was rescaled between 0 and 1. To disable, set argument rescale = FALSE
  
   - Converting into Presence - Absence
  
  Error in seq.default(min_p, max_p, length = 1000) : 
    'from' must be a finite number
  Calls: generateRandomSp -> convertToPA -> sample -> seq -> seq.default
  Execution halted