3.1. Variation in Sexual Size Dimorphism (SSD)
Overall, the average body size differed significantly across the four
study populations (Kruskal-Wallis; chi-squared=64.713, df=3,P <0.0001) (Figure 3). Males were significantly larger
than females in both Singapore populations (Kruskal-Wallis: CCNR:
chi-squared=18.451, df=1, P <0.0001, Pulau Ubin:
chi-squared=38.501, df=1, P <0.0001) and Langkawi
(Kruskal-Wallis; chi-squared=7.931, df=1, P <0.01),
indicating a clear male-biased SSD. Although males in Central Peninsula
MY were also larger than females but this difference was not
statistically significant (Kruskal-Wallis; chi-squared=1.818, df=1,P >0.05). In addition, the SDI was more pronounced in
Singapore populations (CCNR=-1.09, Pulau Ubin=-1.12; Central Peninsular
MY=-1.03 and Langkawi=-1.03), even though the average body size of males
in Malaysia populations are bigger than Singapore population.
The average body size of females differed significantly among all
populations (Kruskal-Wallis; chi-squared=69.037, df=3,P <0.0001). Females from Malaysia populations were
significantly larger than females from Singapore populations (post-hoc
Dunn’s test; Central Peninsular MY versus CCNR and Pulau Ubin:P <0.0001, P <0.0001; Langkawi versus
CCNR and Pulau Ubin: P <0.0001,P <0.0001). The average body size of males also
differed significantly among all populations (Kruskal-Wallis;
chi-squared=16.145, df=3, P <0.01). Using post-hoc
Dunn’s test, males from Langkawi were significantly larger than males
from Singapore populations (CCNR: P <0.01; Pulau Ubin:P <0.01) but did not differ significantly with Central
Peninsular MY. Body size also did not differ significantly between the
Singapore populations and Central Peninsular MY (post-hoc Dunn’s test;
Central Peninsular MY versus CCNR and Pulau Ubin:P >0.05) (Figure 3).
3.2 Variation in male
reproductive traits as a function of body
size
Using a log-transformed data and the breakpoint model, a hyperallometric
relationship (allometric coefficient, β>1, Figure 4a, Table
1) was found between horn length and body size (pronotum width) for all
four populations of O . babirussa (see Appendix 3 for the
best fit model for each population). The adjusted R2 values for equation
one of the breakpoint model were high for all four populations,
signalling a strong positive correlation. In addition, 95% confidence
intervals (CI) for equation one of all populations excluded zero, ruling
out the likelihood of a zero slope, indicating a significant
relationship between horn length and body size. On the other hand, 95%
CI for equation two includes zero for all populations except Pulau Ubin,
signalling a non-significant relationship, hence only the allometric
coefficient of equation one (β1) was taken into consideration. Together,
these results suggest that body size is a significant factor in
explaining horn length variation, where larger males have
disproportionately longer horns. Interestingly, there is an overlap in
CI values for all populations which suggests that there were no
significant population-level differences in allometric relationships.
Next, using log-transformed data, a positive and hypoallometric
relationship (allometric coefficient β<1, Figure 4b, Table 1)
was found between testes weight and body size (pronotum width) for CCNR,
Pulau Ubin and Langkawi, and a hyperallometric relationship was found
for Central Peninsular MY. The adjusted R2 values for the linear model
of all populations were low, indicating a weak correlation. In addition,
the p-values of the slopes of the four linear models
(P>0.05, Table 1) and 95% CI (includes zero) suggests that
body size is not a significant factor in explaining testes weight
variation.
Following that, using log-transformed data, a positive and
hypoallometric relationship (allometric coefficient β<1,
Figure 4c, Table 1) was found between sperm length and body size
(pronotum width) for CCNR, Pulau Ubin and Langkawi, and a negative and
hypoallometric relationship was found for Central Peninsular MY. The
adjusted R2 values for the linear model of all populations were low,
signalling a weak correlation. In addition, the p-values of the slopes
of the four linear models (P>0.05, Table 1) and 95% CI
(includes zero) suggests that body size is not a significant factor in
explaining sperm length variation.