I was asked to build a mixed effect model using 'lmer' and 'lmerTest'. The data is shown below:

The full Question is :
"Use the lme4 and lmerTest R packages to run a linear mixed-effects model examining how herbivores (Herbivory), pollinators (Pollination), plant defences (HCN) and all interactions influence the length of banner petals (Avg.Bnr.Wdth) produced by plants while accounting for variation due to spatial block and plant genotype. Allow the intercept for Genotype to vary across the levels of the herbivory treatment (Hint: are Genotype and Herbivory crossed or nested?)"
My attempt to build a model:
model_2a <- lmer(data = plant_data, Avg.Bnr.Wdth ~ Herbivory * Pollination +
Herbivory * HCN +
Pollination * HCN +
(1|Block) +
(1|Genotype))
summary(model_2a)
However, the output is odd:
Scaled residuals:
Min 1Q Median 3Q Max
-4.7400 -0.5967 0.0692 0.6326 3.2019
Random effects:
Groups Name Variance Std.Dev.
Genotype (Intercept) 0.068569 0.2619
Block (Intercept) 0.003272 0.0572
Residual 0.046580 0.2158
Number of obs: 595, groups: Genotype, 49; Block, 6
Fixed effects:
Estimate Std. Error df t value Pr(>|t|)
(Intercept) 3.270378 0.062366 58.163245 52.438 <2e-16 ***
HerbivoryReduced 0.005644 0.031429 540.971084 0.180 0.8575
PollinationSupp -0.051416 0.031547 538.253166 -1.630 0.1037
HCNYes -0.110019 0.081633 58.795573 -1.348 0.1829
HerbivoryReduced:PollinationSupp 0.013405 0.036148 539.473352 0.371 0.7109
HerbivoryReduced:HCNYes 0.062927 0.036135 539.454401 1.741 0.0822 .
PollinationSupp:HCNYes 0.071009 0.035959 539.235883 1.975 0.0488 *
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Correlation of Fixed Effects:
(Intr) HrbvrR PllntS HCNYes HrR:PS HR:HCN
HerbvryRdcd -0.262
PollintnSpp -0.246 0.328
HCNYes -0.640 0.132 0.117
HrbvryRd:PS 0.150 -0.589 -0.609 0.001
HrbvrR:HCNY 0.156 -0.581 0.012 -0.241 0.022
PllntS:HCNY 0.133 0.038 -0.536 -0.214 -0.021 -0.036
First. I have no idea how to "vary the Genotype intercept across the Herbivory treatment."
Second. Why it's "HerbivoryReduced","PollinationSupp" in the output, I tried to as.factor Pollination, Herbivory and HCN, but it still shows the same thing