How to calculate % change with GLM Poisson output

Question

Background: I have count data (beetle count) and I am looking at the effects of a gradient of a treatment on the count data. The gradient is a continuous predictor variable that consists of "7 levels" (i.e., -100% reduction, -80% reduction, -60% reduction, -40% reduction, -20% reduction, 0% reduction and 50% addition). The '0% reduction' means no change, or that is the control. I would like to compare the treatment '-60% reduction' (for example) to '0% reduction' using the GLM output.

How can I use the GLMM output with poisson distribution and log link in R to calculate the % change in count data between '-60% reduction' and '0% reduction'?

This is a sample of the model:

glmmTMB(count_data ~ continuous_predictor + (1|random_effect),
        family=poisson(link=log), data=data)

plot number	treatment	beetle count
1	-60	4
2	-20	13
3	0	23
4	-100	2
5	50	10
6	-80	3
7	-40	5
8	0	14
9	-20	9
10	-60	7
11	-100	1
12	-40	2