Table 1.

Posterior mean ± SD for parameters estimated under models I and II, with their respective verbal descriptions.

	Model I		Model II		Parameter description
${\mathrm{\psi }}_1$	0.20 ± 0.037		0.63 ± 0.121		Initial infestation probability
${\mathrm{\alpha }}_{\mathrm{\gamma }}$	−1.36 ± 0.048		−1.65 ± 0.106		Mean logit colonization
${\mathrm{\beta }}_{\mathrm{\gamma }}$	−1.05 ± 0.048		−0.90 ± 0.150		Amplitude logit colonization
$\mathrm{\tau }{0}_{\mathrm{\gamma }}$	0.53 ± 0.009		0.54 ± 0.019		Maximum colonization time
${\mathrm{\alpha }}_{\mathrm{\epsilon }}$	−1.64 ± 0.043		−3.55 ± 0.101		Mean logit local extinction
${\mathrm{\beta }}_{\mathrm{\epsilon }}$	2.91 ± 0.071		0.50 ± 0.124		Amplitude logit local extinction
$\mathrm{\tau }{0}_{\mathrm{\epsilon }}$	0.61 ± 0.002		0.73 ± 0.048		Maximum local extinction time
$p$	0.37 ± 0.002		–		Fixed detection probability
${\mathrm{\mu }}_p$	–		0.15 ± 0.016		Random-effect mean detection
${\mathrm{\sigma }}_p$	–		0.22 ± 0.022		Random-effect standard deviation detection
${\mathrm{\psi }}_{\max }^{\mathrm{(eq)}}$	0.97 ± 0.002	Febuary 4–7	0.94 ± 0.005	Febuary 1–26	Maximum equilibrium infestation probability.
${\mathrm{\psi }}_{\min }^{\mathrm{(eq)}}$	0.10 ± 0.003	July 21–28	0.66 ± 0.033	Jul 30–August 21	Minimum equilibrium infestation probability.
${\mathit{s}}_{\text{γ},\text{max}}$	1.95 ± 0.119	May 15–21	3.10 ± 0.777	July 13–August 5	Sensitivity to change in colonization
${\mathit{s}}_{\text{ε},\text{max}}$	3.45 ± 0.249	April 3–9	7.20 ± 1.323	May 22–July 8	Sensitivity to change in local extinction

Parameters are organized in three groups: the first (${\mathrm{\psi }}_1$–$\mathrm{\tau }{0}_{\mathrm{\epsilon }}$, from Equations 1–4) describes occupancy dynamics; the second ($p$–${\mathrm{\sigma }}_p$, from Equations 5–8) describes detection; and the third (${\mathrm{\psi }}_{\max }^{\mathrm{(eq)}}$ – ${\mathit{s}}_{\text{ε},\text{max}}$, based on Equations 9, 12, and 13) shows extreme values of equilibrium occupancy (maximum and minimum) and sensitivity (only maximum). Time intervals indicate the 95% credible intervals for the date with the most extreme value of the corresponding parameter and model. The first two groups of parameters are directly estimated from the data, the third is derived.