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Appendix S1. Additional figures, tables and available Rcode.

Fig. S1. Plots of test statistic, d, and associated quartiles (25% and 75%) measuring lack of fit (lower is better) for two-phase adaptive approach and traditional single-season occupancy approach when n=100, J=3, overall occupancy rate = 0.2- 0.3, and for three different levels of detection, p=0.25, 0.5, 0.75.

Fig. S2. Plots of test statistic, d, and associated quartiles (25% and 75%) measuring lack of fit (lower is better) for two-phase adaptive approach and traditional single-season occupancy approach when there is a weak simulated relationship between habitat and occupancy (slope = 0.5) for n=100, J=3, overall occupancy rate = 0.2 – 0.3, and for three different levels of detection, p=0.25, 0.5, 0.75.

Fig. S3. Plots of test statistic, d, and associated quartiles (25% and 75%) measuring lack of fit (lower is better) for two-phase adaptive approach and traditional single-season occupancy approach when n=100, J=3, overall occupancy rate = 0.7- 0.8, and for three different levels of detection, p=0.25, 0.5, 0.75.

Fig. S4. Plots of test statistic, d, and associated quartiles (25% and 75%) measuring lack of fit (lower is better) for two-phase adaptive approach and traditional single-season occupancy approach when there is a weak simulated relationship between habitat and occupancy (slope = 0.5) for n=100, J=3, overall occupancy rate = 0.7 – 0.8, and for three different levels of detection, p=0.25, 0.5, 0.75.

Table S1. Average value from 1000 simulations of test statistic measuring lack of fit, d, test statistic measuring goodness of fit, GOF, estimate of Ntot, \widehat{N}^{tot}, bias associated in estimating Ntot, and mean-squared-error, MSE, associated with estimating Ntot.

Table S2. Average value from 1000 simulations of test statistic measuring lack of fit, d, test statistic measuring goodness of fit, GOF, estimate of Ntot, \widehat{N}^{tot}, bias associated in estimating Ntot, and mean-squared-error, MSE, associated with estimating Ntot.

Table S3. Average value from 1000 simulations for estimates of coefficients in the logit-linear model for occupancy probability, \widehat{β}_{0} and \widehat{β}_{1}, along with average bias and mean-squared-error (MSE).

Table S4. Average value from 1000 simulations for estimates of coefficients in the logit-linear model for occupancy probability, \widehat{β}_{0} and \widehat{β}_{1}, along with average bias and mean-squared-error (MSE).

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