Running 'tests.R' [134s]
Running the tests in 'tests/tests.R' failed.
Complete output:
  > library(virtualspecies)
  Loading required package: terra
  terra 1.7.55
  > 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 = 0.676676676676677
  - species prevalence =0.0497
  
  
  > 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 = 0.233233233233233
  - species prevalence =0.2542
  
  
  > 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 = -0.125
  - alpha = -0.05
  - species prevalence =0.989
  
  
  > 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 = 0.1483154296875
  - alpha = -0.05
  - species prevalence =0.5014
  
  
  > 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 =0.1068
  
  
  > 
  > 
  > 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 = 0.682682682682683
  - alpha = -0.1
  - species prevalence =0.1502
  
  
  > 
  > 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 = 0.810810810810811
  - alpha = -0.05
  - species prevalence =0.2025
  
  
  > plotSuitabilityToProba(sp4)
  > 
  > sp4 <- convertToPA(sp4,
  +                    PA.method = "threshold")
     --- Generating a random value of beta for the threshold conversion
  
  
     Threshold conversion finished:
                
  - cutoff = 0.615615615615616
  - species prevalence =0.3773
  
  
  > plotSuitabilityToProba(sp4)
  > sp4 <- convertToPA(sp4,
  +                    PA.method = "threshold",
  +                    beta = 0.5)
     Threshold conversion finished:
                
  - cutoff = 0.5
  - species prevalence =0.4425
  
  
  > 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
  
  
  > plotSuitabilityToProba(sp4)
  > sp4 <- convertToPA(sp4,
  +                    PA.method = "threshold",
  +                    beta = "random")
     --- Generating a random value of beta for the threshold conversion
  
  
     Threshold conversion finished:
                
  - cutoff = 0.565565565565566
  - species prevalence =0.4063
  
  
  > plotSuitabilityToProba(sp4)
  > sp4 <- convertToPA(sp4,
  +                    PA.method = "threshold",
  +                    species.prevalence = .2)
     Threshold conversion finished:
                
  - cutoff = 0.812892380555876
  - species prevalence =0.2
  
  
  > plotSuitabilityToProba(sp4)
  > sp4 <- convertToPA(sp4,
  +                    PA.method = "threshold",
  +                    species.prevalence = .02)
     Threshold conversion finished:
                
  - cutoff = 0.993164349727508
  - species prevalence =0.02
  
  
  > plotSuitabilityToProba(sp4)
  > sp4 <- convertToPA(sp4,
  +                    PA.method = "threshold",
  +                    species.prevalence = .9)
     Threshold conversion finished:
                
  - cutoff = 0.000674936950456548
  - species prevalence =0.8999
  
  
  > plotSuitabilityToProba(sp4)
  > sp4 <- convertToPA(sp4,
  +                    PA.method = "threshold",
  +                    species.prevalence = .99)
     Threshold conversion finished:
                
  - cutoff = 2.74550458610582e-06
  - 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 = -0.16015625
  - alpha = -0.05
  - species prevalence =0.9891
  
  
  > 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 = 0.390625
  - alpha = -0.05
  - species prevalence =0.4984
  
  
  > 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 =0.4393
  
  
  > 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 = 0.419419419419419
  - alpha = -0.1
  - species prevalence =0.5584
  
  
   - 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 = 0.794794794794795
  - alpha = -0.1
  - species prevalence =0.0643
  
  
   - 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 = 0.125125125125125
  - alpha = -0.1
  - species prevalence =0.743
  
  
   - 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 = 0.842842842842843
  - alpha = -0.1
  - species prevalence =0.0567
  
  
   - 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 = 0.960960960960961
  - alpha = -0.1
  - species prevalence =0.0306
  
  
   - 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 = 0.870870870870871
  - alpha = -0.1
  - species prevalence =0.1812
  
  
   - 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 = 0.421421421421421
  - alpha = -0.1
  - species prevalence =0.7854
  
  
   - 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 = 0.926926926926927
  - alpha = -0.1
  - species prevalence =0.0991
  
  
   - 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 = 0.706706706706707
  - alpha = -0.1
  - species prevalence =0.1017
  
  
   - 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 = 0.74974974974975
  - alpha = -0.1
  - species prevalence =0.2428
  
  
   - 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 =0.0067
  
  
   - 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 = 0.145145145145145
  - alpha = -0.1
  - species prevalence =0.799
  
  
   - 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 = 0.368368368368368
  - alpha = -0.1
  - species prevalence =0.2605
  
  
   - 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 = 0.0960960960960961
  - alpha = -0.1
  - species prevalence =0.9544
  
  
   - 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 = 0.986986986986987
  - alpha = -0.1
  - species prevalence =0.102
  
  
   - 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 = 0.743743743743744
  - alpha = -0.1
  - species prevalence =0.2854
  
  
   - 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 = 0.181181181181181
  - alpha = -0.1
  - species prevalence =0.5654
  
  
   - 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 = 0.484484484484485
  - alpha = -0.1
  - species prevalence =0.1997
  
  
   - 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 = 0.528528528528528
  - alpha = -0.1
  - species prevalence =0.2285
  
  
   - 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 = 0.233233233233233
  - alpha = -0.1
  - species prevalence =0.9275
  
  
   - 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 = 0.887887887887888
  - alpha = -0.1
  - species prevalence =0.1969
  
  
   - 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 = 0.510510510510511
  - alpha = -0.1
  - species prevalence =0.069
  
  
   - 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 = 0.627627627627628
  - alpha = -0.1
  - species prevalence =0.2325
  
  
   - 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 = 0.171171171171171
  - alpha = -0.1
  - species prevalence =0.1926
  
  
   - 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 = 0.86986986986987
  - alpha = -0.1
  - species prevalence =0.217
  
  
   - 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 = 0.2002002002002
  - alpha = -0.1
  - species prevalence =0.6045
  
  
   - 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 = 0.394394394394394
  - alpha = -0.1
  - species prevalence =0.2393
  
  
   - 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 = 0.43043043043043
  - alpha = -0.1
  - species prevalence =0.6812
  
  
   - 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 = 0.39039039039039
  - alpha = -0.1
  - species prevalence =0.2619
  
  
   - 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 = 0.626626626626627
  - alpha = -0.1
  - species prevalence =0.4179
  
  
   - 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 = 0.341341341341341
  - alpha = -0.1
  - species prevalence =0.6985
  
  
   - 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 = 0.627627627627628
  - alpha = -0.1
  - species prevalence =0.5727
  
  
   - 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 = 0.632632632632633
  - alpha = -0.1
  - species prevalence =0.4824
  
  
   - 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 =0.7284
  
  
   - 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 =0.8681
  
  
   - 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 = 0.778778778778779
  - alpha = -0.1
  - species prevalence =0.2689
  
  
   - 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 = 0.98998998998999
  - alpha = -0.1
  - species prevalence =0.0245
  
  
   - 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 = 0.02002002002002
  - alpha = -0.1
  - species prevalence =0.9328
  
  
   - 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 = 0.548548548548549
  - alpha = -0.1
  - species prevalence =0.0536
  
  
   - 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 = 0.387387387387387
  - alpha = -0.1
  - species prevalence =0.2734
  
  
   - 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 = 0.705705705705706
  - alpha = -0.1
  - species prevalence =0.0726
  
  
   - 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 = 0.403403403403403
  - alpha = -0.1
  - species prevalence =0.1996
  
  
   - 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 = 0.304304304304304
  - alpha = -0.1
  - species prevalence =0.8562
  
  
   - 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 = 0.485485485485485
  - alpha = -0.1
  - species prevalence =0.384
  
  
   - 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 = 0.646646646646647
  - alpha = -0.1
  - species prevalence =0.1462
  
  
   - 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 = 0.612612612612613
  - alpha = -0.1
  - species prevalence =0.1383
  
  
   - 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 = 0.584584584584585
  - alpha = -0.1
  - species prevalence =0.0225
  
  
   - 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 = 0.514514514514514
  - alpha = -0.1
  - species prevalence =0.3015
  
  
   - 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 =0.9548
  
  
   - 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 = 0.0530530530530531
  - alpha = -0.1
  - species prevalence =0.892
  
  
   - 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 = 0.431431431431431
  - alpha = -0.1
  - species prevalence =0.4225
  
  
   - 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 = 0.541541541541542
  - alpha = -0.1
  - species prevalence =0.137
  
  
   - 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 = 0.017017017017017
  - alpha = -0.1
  - species prevalence =0.5823
  
  
   - 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 = 0.274274274274274
  - alpha = -0.1
  - species prevalence =0.0832
  
  
   - 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 = 0.123123123123123
  - alpha = -0.1
  - species prevalence =0.7425
  
  
   - 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 = 0.227227227227227
  - alpha = -0.1
  - species prevalence =0.5361
  
  
   - 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 = 0.742742742742743
  - alpha = -0.1
  - species prevalence =0.2578
  
  
   - 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 = 0.259259259259259
  - alpha = -0.1
  - species prevalence =0.5885
  
  
   - 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 = 0.621621621621622
  - alpha = -0.1
  - species prevalence =0.312
  
  
   - 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 = 0.254254254254254
  - alpha = -0.1
  - species prevalence =0.7795
  
  
   - 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 = 0.302302302302302
  - alpha = -0.1
  - species prevalence =0.0553
  
  
   - 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 = 0.184184184184184
  - alpha = -0.1
  - species prevalence =0.8558
  
  
   - 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 = 0.496496496496497
  - alpha = -0.1
  - species prevalence =0.0706
  
  
   - 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 = 0.386386386386386
  - alpha = -0.1
  - species prevalence =0.7769
  
  
   - 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 = 0.842842842842843
  - alpha = -0.1
  - species prevalence =0.0607
  
  
   - 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 = 0.508508508508508
  - alpha = -0.1
  - species prevalence =0.391
  
  
   - 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 = 0.735735735735736
  - alpha = -0.1
  - species prevalence =0.3489
  
  
   - 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 = 0.604604604604605
  - alpha = -0.1
  - species prevalence =0.2066
  
  
   - 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 = 0.95995995995996
  - alpha = -0.1
  - species prevalence =0.1656
  
  
   - 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 = 0.267267267267267
  - alpha = -0.1
  - species prevalence =0.4231
  
  
   - 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 = 0.780780780780781
  - alpha = -0.1
  - species prevalence =0.2642
  
  
   - 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 = 0.322322322322322
  - alpha = -0.1
  - species prevalence =0.9136
  
  
   - 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 = 0.334334334334334
  - alpha = -0.1
  - species prevalence =0.8972
  
  
   - 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 = 0.548548548548549
  - alpha = -0.1
  - species prevalence =0.1593
  
  
   - 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 = 0.915915915915916
  - alpha = -0.1
  - species prevalence =0.0412
  
  
   - 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 = 0.241241241241241
  - alpha = -0.1
  - species prevalence =0.7274
  
  
   - 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 = 0.3003003003003
  - alpha = -0.1
  - species prevalence =0.4299
  
  
   - 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 = 0.0920920920920921
  - alpha = -0.1
  - species prevalence =0.3818
  
  
   - 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 = 0.305305305305305
  - alpha = -0.1
  - species prevalence =0.6362
  
  
   - 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 = 0.932932932932933
  - alpha = -0.1
  - species prevalence =0.1147
  
  
   - 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 = 0.898898898898899
  - alpha = -0.1
  - species prevalence =0.0512
  
  
   - 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 =0.8501
  
  
   - 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 = 0.166166166166166
  - alpha = -0.1
  - species prevalence =0.4552
  
  
   - 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 = 0.61961961961962
  - alpha = -0.1
  - species prevalence =0.4148
  
  
   - 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 = 0.35035035035035
  - alpha = -0.1
  - species prevalence =0.3516
  
  
   - 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 = 0.298298298298298
  - alpha = -0.1
  - species prevalence =0.5986
  
  
   - 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 = 0.61961961961962
  - alpha = -0.1
  - species prevalence =0.672
  
  
   - 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 = 0.763763763763764
  - alpha = -0.1
  - species prevalence =0.5989
  
  
   - 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 = 0.534534534534534
  - alpha = -0.1
  - species prevalence =0.3575
  
  
   - 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 = 0.706706706706707
  - alpha = -0.1
  - species prevalence =0.0723
  
  
   - 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 = 0.392392392392392
  - alpha = -0.1
  - species prevalence =0.3591
  
  
   - 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 = 0.657657657657658
  - alpha = -0.1
  - species prevalence =0.1176
  
  
   - 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 = 0.561561561561562
  - alpha = -0.1
  - species prevalence =0.4029
  
  
   - 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 = 0.278278278278278
  - alpha = -0.1
  - species prevalence =0.3668
  
  
   - Determining species' response to predictor variables
  
  Error in seq.default(min_, max_, length = 1e+05) : 
    'from' must be a finite number
  Calls: generateRandomSp -> sample -> seq -> seq.default
  Execution halted