How to set zero-inflated GLM intercept to positive in R?

I am trying to run some zero-inflated GLM's using the zeroinfl function, but a lot of them are giving me negative intercepts which don't make sense for my variables. Is there a way to set the intercept above zero? Thank you! For example:

zeroinfl(formula = crab.burrows.m2 ~ Algae, data = vegdata)

Pearson residuals:
    Min      1Q  Median      3Q     Max 
-1.0557 -1.0557 -0.7236  0.1067 11.8967 

Count model coefficients (poisson with log link):
            Estimate Std. Error z value Pr(>|z|)    
(Intercept)  2.40350    0.03991  60.216   <2e-16 ***
Algae        0.03964    0.02067   1.918   0.0551 .  

Zero-inflation model coefficients (binomial with logit link):
            Estimate Std. Error z value Pr(>|z|)  
(Intercept) -0.30108    0.20093  -1.498   0.1340  
Algae        0.18556    0.09047   2.051   0.0403 *
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

Number of iterations in BFGS optimization: 1 
Log-likelihood: -525.5 on 4 Df```

Solution

You won't need to set the intercept to zero for the "Zero-inflation" part of the model.

The zero-inflation model has two parts:

the count part (upper bit of the output) which should not have negative intercepts.
the zeroinflation part that models whether an observation is zero or not. This is estimated with either a logit or probit model, that in turn can have negative intercepts.