Summary output of binomial GLMM shows significant effects, but graph shows overlapping CI error bars?

Question

I have run this binomial GLMM:

m17 <- glmer(Attendance ~ Day + Sex + (1|AgeClass) + (1|Year) + (1|Plastic), data = test2, family = binomial(link = "logit"))

This is the summary output of the model:

Generalized linear mixed model fit by maximum likelihood (Laplace  Approximation)
 [glmerMod]
 Family: binomial  ( logit )
Formula: Attendance ~ Day + Sex + (1 | AgeClass) + (1 | Year) + (1 | Plastic)
   Data: test2

     AIC      BIC   logLik deviance df.resid 
 16138.4  16182.7  -8063.2  16126.4    11868 

Scaled residuals: 
    Min      1Q  Median      3Q     Max 
-1.5394 -0.9688 -0.5740  0.9656  1.8762 

Random effects:
 Groups   Name        Variance  Std.Dev.
 Plastic  (Intercept) 0.1374817 0.3708  
 Year     (Intercept) 0.0531973 0.2306  
 AgeClass (Intercept) 0.0009734 0.0312  
Number of obs: 11874, groups:  Plastic, 237; Year, 4; AgeClass, 3

Fixed effects:
             Estimate Std. Error z value Pr(>|z|)    
(Intercept)  0.135928   0.137669   0.987  0.32347    
Day         -0.005972   0.002061  -2.897  0.00377 ** 
SexFemales  -0.248756   0.063937  -3.891    1e-04 ***
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Correlation of Fixed Effects:
           (Intr) Day   
Day        -0.378       
SexFemales -0.240  0.004

As evidenced by the p-values, both Day and Sex have a significant effect on attendance. However, when I use plot_model to graph it, I get this result:

As you can see, the error bars are nearly overlapping, or overlapping, the predicted probability values for each sex. I haven't had this issue before with other graphs I've made with plot_model, so I'm confused as to why I'm getting these contradictory results. Does it have to do with the conversion of log-odds beta coefficients to predicted probability values? Or, is there something wrong with my code below?

plot_model(m17, type = "pred" ,
                    terms = c("Day [all]", "Sex"), 
                    colors = c("blue", "red"), 
                    ci.lvl = .95,
                    legend.title = NA,
                    line.size = 1,
                    show.legend = FALSE) +
  labs(x = "Days Relative to Clutch Initiation", y = "P(Attend at night)", title = NULL) +
  scale_x_continuous(expand = c(0, 0), breaks = breaks, labels = labels) + 
  scale_y_continuous(limit = c(0, 1), expand = c(0, 0)) + 
  theme_classic() + 
  guides(fill=guide_legend(nrow=2,byrow=TRUE)) +
  theme(axis.text=element_text(size=22, color = "black", family = "serif"), 
        axis.title=element_text(size=22, color = "black", family = "serif"), 
        axis.title.x = element_text(vjust=-0.5),
        axis.title.y = element_text(vjust=2.5),
        axis.ticks.length=unit(0.1,"inch"), 
        legend.key.size = unit(1, 'cm'), 
        legend.position = c(0.15, 0.92),
        legend.text = element_text(colour="black", size=20, family = "serif"),
        plot.margin = margin(1,.5,1,1, "cm"))

All help is appreciated, and please let me know if there is another place I should post this question!