15 replications or even more, especially at low initial densities of prey offered.
The low number of replicates can increase variations and in turn, standard error of
mean among different treatments lead to incorrect estimations of searching efficiency or handling time. Additionally, again, the control treatment has not been used
to correct observed mortality. Moreover, in some outdated investigations, only the
Holling’s disc model was used before testing the Roger’s random predator equation,
which is more realistic and considers prey depletion during the experimental period.
2.5.2 Numerical Response
The numerical response is another crucial aspect of predation. By definition,
the numerical response is an increase in the number of predator densities in response
to increasing prey density (Holling 1959). It has three primary forms, direct, no
response and inverse (Solomon 1949).
Compare to functional response, there are very few numerical response studies
and these kinds of surveys have been done scarcely in Iran. Partially, this due
to complicated set-ups of numerical response experiments, which is more time
consuming than a short-term experiment. Another point is that there is not a standard
set-up or even standard data analysis method for these kinds of investigations. A
brief review revealed puzzling variations in data-analysis and set-ups. Most carried
out together with functional response studies concomitantly. Many researchers used
the same set-up of functional response with slight modifications (i.e., they used a
longer experimental duration for numerical response experiments instead of 24 h
commonly used for functional response (Zarghami et al. 2015). Actually, the functional and numerical respons experimental set-ups are similar to each other apparently, but the different point is that in numerical response experiments, the number of
eggs laid by predator in response to increasing prey densities is recorded. In contrast,
the functional response considers the number of killed prey in response to initial
different prey densities. Even though, there were more sophisticated studies with up
to two weeks or longer as experimental duration (Mokhtari and Madadi 2013;
Zarghami et al. 2015). Generally, at nearly all numerical response experiments, it
has been exhibited that oviposition increases with increasing prey density (Sabaghi
et al. 2011a ; Mokhtari and Madadi 2013). It has been suggested that the number of
eggs laid by H . variegata to A. fabae increases curvilinearly up to an asymptote and
then levelled up at density of 96 black bean aphids (Mokhtari and Madadi 2013).
Moreover, there was an inverse density-dependent relationship between increasing
prey density and premature developmental time. The numerical response of Nephus
arccuatus to Nipaecoccus viridis (Newstead) eggs was also curvilinear reached a
plateau at 115 spherical mealybugs (Zarghami et al. 2015). This value was 80 for
the reproductive numerical response of S. syriacus to black bean aphid (Sabaghi
et al. 2011a ). Sohrabi and Shishehbor (2007) showed a linear numerical response
between Tetranychus turkestani density and S. gilvifrons oviposition and the lower
egg production threshold was eight T. turkestani females.
2 Lady Beetles; Lots of Efforts but few Successes
71
The low number of replicates can increase variations and in turn, standard error of
mean among different treatments lead to incorrect estimations of searching efficiency or handling time. Additionally, again, the control treatment has not been used
to correct observed mortality. Moreover, in some outdated investigations, only the
Holling’s disc model was used before testing the Roger’s random predator equation,
which is more realistic and considers prey depletion during the experimental period.
2.5.2 Numerical Response
The numerical response is another crucial aspect of predation. By definition,
the numerical response is an increase in the number of predator densities in response
to increasing prey density (Holling 1959). It has three primary forms, direct, no
response and inverse (Solomon 1949).
Compare to functional response, there are very few numerical response studies
and these kinds of surveys have been done scarcely in Iran. Partially, this due
to complicated set-ups of numerical response experiments, which is more time
consuming than a short-term experiment. Another point is that there is not a standard
set-up or even standard data analysis method for these kinds of investigations. A
brief review revealed puzzling variations in data-analysis and set-ups. Most carried
out together with functional response studies concomitantly. Many researchers used
the same set-up of functional response with slight modifications (i.e., they used a
longer experimental duration for numerical response experiments instead of 24 h
commonly used for functional response (Zarghami et al. 2015). Actually, the functional and numerical respons experimental set-ups are similar to each other apparently, but the different point is that in numerical response experiments, the number of
eggs laid by predator in response to increasing prey densities is recorded. In contrast,
the functional response considers the number of killed prey in response to initial
different prey densities. Even though, there were more sophisticated studies with up
to two weeks or longer as experimental duration (Mokhtari and Madadi 2013;
Zarghami et al. 2015). Generally, at nearly all numerical response experiments, it
has been exhibited that oviposition increases with increasing prey density (Sabaghi
et al. 2011a ; Mokhtari and Madadi 2013). It has been suggested that the number of
eggs laid by H . variegata to A. fabae increases curvilinearly up to an asymptote and
then levelled up at density of 96 black bean aphids (Mokhtari and Madadi 2013).
Moreover, there was an inverse density-dependent relationship between increasing
prey density and premature developmental time. The numerical response of Nephus
arccuatus to Nipaecoccus viridis (Newstead) eggs was also curvilinear reached a
plateau at 115 spherical mealybugs (Zarghami et al. 2015). This value was 80 for
the reproductive numerical response of S. syriacus to black bean aphid (Sabaghi
et al. 2011a ). Sohrabi and Shishehbor (2007) showed a linear numerical response
between Tetranychus turkestani density and S. gilvifrons oviposition and the lower
egg production threshold was eight T. turkestani females.
2 Lady Beetles; Lots of Efforts but few Successes
71