Inference, logistic regression

Dear list,

Please pardon this beginner's-level question, I feel it's not quite up 
to the same caliber as recent discussions.

I'm working with a simple logistic regression model comparing the 
presence/absence of an insect species against an index of plant 
species turnover:

foo<-glm(bout.psol$pres.de~bout.psol$index,family=binomial)

The term bout.psol$pres.de is binary 0,1; and bout.psol$index is 
continuous.

I'd like to use a likelihood ratio statistic to test the significance 
of this regression, but I'm a little uncertain as how to proceed.  
When I call summary(foo), I get...

Call:
glm(formula = bout.psol$pres.de ~ bout.psol$index,
    family = binomial)

Deviance Residuals:
    Min       1Q   Median       3Q      Max
-1.7180  -1.1289   0.6314   1.0323   1.7499

Coefficients:
                     Estimate Std. Error z value Pr(>|z|)
(Intercept)           0.30584    0.23095   1.324  0.18542
bout.psol.edit$index  0.04552    0.01439   3.163  0.00156 **
---
Signif. codes:  0 ?***? 0.001 ?**? 0.01 ?*? 0.05 ?.? 0.1 ? ? 1

(Dispersion parameter for binomial family taken to be 1)

    Null deviance: 130.14  on 93  degrees of freedom
Residual deviance: 118.17  on 92  degrees of freedom
AIC: 122.17

Taking (Null dev) - (Redid dev), I get 11.97, which I assume to be 
equal to -2log(L,full/L,reduced).  That's the desired test statistic, 
so is it as simple as calling:

pchisq(11.97,df=92)

[1] 2.911346e-25          ?

That's an awfully small p-value, I think I'm interpreting something 
wrong.  Any advice would be very welcomed.

Thanks very much in advance
Andy Rominger