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Table S2. Predictor variables used to model ecological niches.

Table S3. Pearson correlations for environmental variables used to model ecological niches ranked by the absolute value of the correlation coefficient.

Table S4. Spearman rank-order correlations between performance criteria and sample size for each modelling protocol.

Figure S1. Rescaled histograms of nine predictor variables used to model ecological

Figure S2. Frequency with which consistent models could be obtained as a function of observations in the data set using (A) Method 1, (B) Method 2, (C) Method 3. Red line represents best-fit logistic regression (P<0.0001 for panels A and B; P=0.0001 for panel C).

Figure S3. Performance of Method 1 (support vector machine without k-whitening using nine environmental variables) is a function of the number of observations in the dataset used for model fitting. Circles represent models that were optimized by the consistency criterion. Crosses represent models for which no consistent model could be obtained (performance evaluations are based on the simplest model). Performance criteria are (A) false negative rate, (B) false positive rate, (C) precision, and (D) recall.

Figure S4. Performance of Method 2 (support vector machine using k-whitening with nine environmental variables) is a function of the number of observations in the dataset used for model fitting. Circles represent models that were optimized by the consistency criterion. Crosses represent models for which no consistent model could be obtained (performance evaluations are based on the simplest model). Performance criteria are (A) false negative rate, (B) false positive rate, (C) precision, and (D) recall.

Figure S5. Performance of Method 3 (support vector machine without k-whitening using four environmental variables) is a function of the number of observations in the dataset used for model fitting. Circles represent models that were optimized by the consistency criterion. Crosses represent models for which no consistent model could be obtained (performance evaluations are based on the simplest model). Performance criteria are (A) false negative rate, (B) false positive rate, (C) precision, and (D) recall.

Figure S6. Summary measures of performance for Method 1 (support vector machine without k-whitening using nine environmental variables) are a function of the number of observations in the dataset used for model fitting. Circles represent models that were optimized by the consistency criterion. Crosses represent models for which no consistent model could be obtained (performance evaluations are based on the simplest model). Performance criteria are (top) summary performance criterion f1, and (bottom) area under the receiver-operator curve (AUC).

Figure S7. Summary measures of performance for Method 2 (support vector machine using k-whitening with nine environmental variables) are a function of the number of observations in the dataset used for model fitting. Circles represent models that were optimized by the consistency criterion. Crosses represent models for which no consistent model could be obtained (performance evaluations are based on the simplest model). Performance criteria are (top) summary performance criterion f1, and (bottom) area under the receiver-operator curve (AUC).

Figure S8. Summary measures of performance for Method 3 (support vector machine without k-whitening using four environmental variables) are a function of the number of observations in the dataset used for model fitting. Circles represent models that were optimized by the consistency criterion. Crosses represent models for which no consistent model could be obtained (performance evaluations are based on the simplest model). Performance criteria are (top) summary performance criterion f1, and (bottom) area under the receiver-operator curve (AUC).

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JPE1141_FigS1.pdf19KSupporting info item
JPE1141_FigS2.pdf87KSupporting info item
JPE1141_FigS3.pdf31KSupporting info item
JPE1141_FigS4.pdf29KSupporting info item
JPE1141_FigS5.pdf30KSupporting info item
JPE1141_FigS6.pdf22KSupporting info item
JPE1141_FigS7.pdf21KSupporting info item
JPE1141_FigS8.pdf22KSupporting info item
JPE1141_TableS1.pdf26KSupporting info item
JPE1141_TableS2.pdf17KSupporting info item
JPE1141_TableS3.pdf34KSupporting info item
JPE1141_TableS4.pdf16KSupporting info item

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