GlmmTMB model and emmeans

Question

I am new to glmmtmb models, so i have ran into a problem. I build a model and then based on the AICtab and DHARMa this was the best:

Insecticide_2<- glmmTMB(Insect_abundace~field_element+land_distance+sampling_time+year+treatment_day+(1|field_id),
                           data=Insect_002,
                           family= nbinom2)

After glmmTMB i ran Anova (from Car), and then emmeans, but the results of p-values in emmeans are the same (not lower.CL or upper.CL). What may be the problem? Is the model overfitted? Is the way i am doing the emmeans wrong?

Anova also showed that the land_distance, sampling_time, treatment_day were significant, year was almost significant (p= 0.07)

comp_emmeans1<-emmeans(Insect_002, pairwise ~ land_distance|year , type = "response") 

> comp_emmeans1
$emmeans
Year = 2018:
land_distance response    SE  df lower.CL upper.CL
 30m           2.46 0.492 474    1.658     3.64
 50m           1.84 0.369 474    1.241     2.73
 80m           1.36 0.283 474    0.906     2.05
 110m          1.25 0.259 474    0.836     1.88

Year = 2019:
land_distance response    SE  df lower.CL upper.CL
 30m           3.42 0.593 474    2.434     4.81
 50m           2.56 0.461 474    1.799     3.65
 80m           1.90 0.335 474    1.343     2.68
 110m          1.75 0.317 474    1.222     2.49

Results are averaged over the levels of: field_element, sampling_time, treatment_day
Confidence level used: 0.95 
Intervals are back-transformed from the log scale 

$contrasts
year = 2018:
 contrast    ratio  SE  df   null t.ratio p.value
 30m / 50m   1.34 0.203 474    1   1.906  0.2268
 30m / 80m   1.80 0.279 474    1   3.798  0.0009
 30m / 110m  1.96 0.311 474    1   4.239  0.0002
 50m / 80m   1.35 0.213 474    1   1.896  0.2311
 50m / 110m  1.47 0.234 474    1   2.405  0.0776
 80m / 110m  1.09 0.176 474    1   0.516  0.9552

year = 2019:
 contrast    ratio SE   df   null t.ratio p.value
 30m / 50m   1.34 0.203 474    1   1.906  0.2268
 30m / 80m   1.80 0.279 474    1   3.798  0.0009
 30m / 110m  1.96 0.311 474    1   4.239  0.0002
 50m / 80m   1.35 0.213 474    1   1.896  0.2311
 50m / 110m  1.47 0.234 474    1   2.405  0.0776
 80m / 110m  1.09 0.176 474    1   0.516  0.9552

Results are averaged over the levels of: field_element, sampling_time, treatment_day
P value adjustment: tukey method for comparing a family of 4 estimates 
Tests are performed on the log scale 

Should i use different comparison way? I saw that some use poly~, I tried that, results picture is the same. Also am I comparing the right things?

Last and also important question is how should i report the glmmTMB, Anova and emmeans results?