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interaction terms interpretation

Hi all, I?m running a mixed model with poisson error distribution as I have
count data of a shorebird species. My predictors are AMGP (another
shorebird that is usually associated to "my" species and probably has
ecological influence on it), grass height and field distance to the lagoon.

I?m having a hard time trying to interpret second order interactions. I
appreciate your comments of references recommendations. Here is the output
of my model. All the best, Joaqu?n.

Call:glmmadmb(formula = BBSA ~ AMGP * Grass_height *
Distance_to_lagoon +     (1 | Field_name) + offset(log(Field_area.o)),
data = my4S,     family = "nbinom1", zeroInflation = TRUE)
AIC: 226
Coefficients:                                     Estimate Std. Error
z value Pr(>|z|)    (Intercept)                           -5.8797
1.2250   -4.80  1.6e-06 ***AMGP
3.3086     1.0246    3.23   0.0012 ** Grass_height
     -4.1592     1.9961   -2.08   0.0372 *  Distance_to_lagoon
           -0.5029     1.3929   -0.36   0.7180    AMGP:Grass_height
                  2.9442     1.5142    1.94   0.0518 .
AMGP:Distance_to_lagoon               -2.4695     0.9632   -2.56
0.0104 *  Grass_height:Distance_to_lagoon        0.0339     2.0065
0.02   0.9865    AMGP:Grass_height:Distance_to_lagoon  -4.0363
1.3264   -3.04   0.0023 ** ---Signif. codes:  0 ?***? 0.001 ?**? 0.01
?*? 0.05 ?.? 0.1 ? ? 1
Number of observations: total=64, Field_name=16 Random effect
variance(s):Group=Field_name            Variance StdDev(Intercept)
0.03721 0.1929
Negative binomial dispersion parameter: 20.633 (std. err.:
7.4042)Zero-inflation: 1e-06  (std. err.:  6.8336e-09 )
Log-likelihood: -102