[R-sig-eco] Marrying Tukey's HSD and ANOVA results

[Lara R. Appleby 04]

I've done a standard two way ANOVA using glm on the dependent variable "clutchsize"  
with the two factors "treatment" (which has 3 levels called 1, 2, and 3) and "species"  
(which has two levels called 1 and 2). Apparently there is no significant interaction  
term. Then I did Tukey's HSD and found that there were significant differences  
between species at only one of the three treatment levels, treatment level 1.  
Are these in fact conflicting results?

##ANOVA RESULTS
>  summary(aov((clutchsize~treatment*species)))
                    Df Sum Sq Mean Sq F value   Pr(>F)
treatment           1  29.26  29.264  7.0230  0.00884 **
species             1 138.14 138.143 33.1526 4.13e-08 ***
treatment:species   1   8.11   8.110  1.9464  0.16487
Residuals         163 679.20   4.167
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

##TUKEY HSD RESULTS
>  TukeyHSD(aov(clutchsize~treatment*species))
   Tukey multiple comparisons of means
     95% family-wise confidence level

Fit: aov(formula = clutchsize ~ treatment * species)

$treatment
           diff        lwr       upr     p adj
2-1  1.3245614  0.4184292 2.2306936 0.0020030
3-1  1.0416667  0.1316071 1.9517262 0.0204117
3-2 -0.2828947 -1.1806793 0.6148899 0.7368331

$species
         diff       lwr       upr p adj
2-1 -1.89988 -2.544747 -1.255013     0

$`treatment:species`
               diff         lwr        upr     p adj
2:1-1:1  1.1791506 -0.19269072  2.5509919 0.1364846
3:1-1:1  0.6476190 -0.73345324  2.0286913 0.7550479
1:2-1:1 -2.4225564 -4.08045729 -0.7646555 0.0005858
2:2-1:1 -0.8357143 -2.46652980  0.7951012 0.6787094
3:2-1:1 -0.6357143 -2.26652980  0.9951012 0.8706501
3:1-2:1 -0.5315315 -1.89354633  0.8304833 0.8701101
1:2-2:1 -3.6017070 -5.24376636 -1.9596476 0.0000000
2:2-2:1 -2.0148649 -3.62957317 -0.4001566 0.0055886
3:2-2:1 -1.8148649 -3.42957317 -0.2001566 0.0177862
1:2-3:1 -3.0701754 -4.71995456 -1.4203963 0.0000041
2:2-3:1 -1.4833333 -3.10589150  0.1392248 0.0944158
3:2-3:1 -1.2833333 -2.90589150  0.3392248 0.2077935
2:2-1:2  1.5868421 -0.27701672  3.4507009 0.1438444
3:2-1:2  1.7868421 -0.07701672  3.6507009 0.0684872
3:2-2:2  0.2000000 -1.63980803  2.0398080 0.9995894