The European hazelnut, Corylus spp. L. is one of the world major nut
crops (Boccacci and Botta, 2008). Its geographic distribution
extends from the Mediterranean coast of northward to British Isles and Scandinavian
Peninsula and eastward to Ural Mountains of Russia, the Caucasus Mountain, Iran
and Lebanon (Boccacci and Botta, 2008). Iran hazelnut
production is about 14000 metric tons from 18000 hectares. Filbert aphid, Myzocallis
coryly is one of the most important pests of Corylus avellana L.
in Iran (Alikhani et al., 2010). M. coryli
is cosmopolitan aphid pest that widely distributed in Europe. The aphid feed
and breeds on the underside leaves of host plants and forming open colonies
of scattered individuals. The aphid excretes sticky honeydew which drops down
and contaminates the underlying foliage. Foliage on infested trees is not distorted.
However, leaves may become contaminated by honeydew and blackened by sooty mould
that reduces photosynthetic activity (Alford, 2007). M.
coryli is a serious pest of commercial hazelnut in areas such as western
Oregon, USA, Turkey and England (Naeem and Compton, 2000;
Tuncer et al., 1997).
Decision-making in integrated pest management program is based on information
about pest density and its spatial distribution (Messing
and Aliniazee, 1989; Madadi et al., 2011;
Pedigo, 2002). Analysis of spatial distribution pattern
is recognized as a necessary procedure for insect population studies and provides
basic information for designing efficient and cost-effective sampling plans
for population estimation and pest management (Madadi et
al., 2011). The present studies were conducted to determine seasonal
population dynamics and spatial distribution of M. coryli on C. avellana
in Lorestan province, West of Iran.
MATERIALS AND METHODS
Experimental design: The experiments were carried out during April 2010 to October 2011 at a commercial orchard (8 ha) in Boroujerd, Lorestan, Iran. The orchard included twenty 22-years-old hazelnut trees that distributed among other trees. No insecticide treatments were applied during trial period.
Seasonal population dynamics of Myzocallis coryli: The population densities of M. coryli were monitored weekly by leaf count method. Ten hazelnut trees were chosen and tagged to sampling. Each sampling date, three leaves from different height levels (top, middle and bottom) of the each side (North, east, west and south) of the plant canopy were randomly chosen and the adult and nymph stages of the aphid were counted in situ by a 20Χ LED lighted loupe magnifier.
Spatial distribution: The spatial distribution of the aphid on hazelnut was evaluated by using the parameters of Taylor's power law. This law describes the regression between logarithm of population variance and logarithm of population mean according to the equation as follows:
where, S2 is the population variance,
is population mean, a is the Y-intercept and b is slope
of regression line. This equation can transform as follows:
where, a is the antilogarithm of a and constitutes
a scaling factor depending on the sampling unit and b is an index
of organism species spatial pattern with b<1, b = 1 and b>1 indicating
uniform, random and aggregated spatial pattern, respectively (Southwood,
1978; Tomanovic et al., 2008). Also, Correlation
coefficient (r) was calculated to goodness of fit of Taylor's power law. Two
tailed t-test at n-2 df was conducted to determine if slope and correlation
coefficient values of the regression relation differ significantly from 1 and
0, respectively (Snedecor and Cochran, 1980).
Data analyses: Analysis of variance (ANOVA) was performed to compare population densities of M. coryli in different heights and sides of hazelnut canopy. All analyses were carried out using the SPSS software version 16 (SPSS Inc., Chicago, USA).
Seasonal population dynamics of Myzocallis coryli: Population dynamics of M. coryli on hazelnut were shown in Fig. 1 and 2 during 2010 and 2011, respectively. The aphid observed on hazelnut during moderate temperature months of year (April to July) in Lorestan province. During the months, average weather temperature was 12.5-31.5°C.
During 2010, the first adults and nymphs were observed at 12 April. The adult
densities increased slowly from 0.5 to 9.3 aphids per leaf during 12 April to
3 June. Adult densities peaked at a mean of 9.3 aphids per leaf on 3 June. The
adult decreased gradually after 26 June. The nymph densities built up exponentially
from 2 to 47.7 aphids per leaf during 12 April to 2 May. From 2 May to 10 June,
population of the nymphs fluctuated around 35-42 aphids per leaf. Peak densities
of nymph stage was 47.7 aphids per leaf at 3 June.
|| Seasonal population dynamics of Myzocallis coryli
on hazelnut in 2010
|| Seasonal population dynamics of Myzocallis coryli
on hazelnut in 2011
Nymph population decreased from 3 June to end of sampling period. No adult
and nymph stages of the aphid were observed after 16 July during 2010 (Fig.
In 2011, adult densities of M. coryli increased from 0 to 9.3 aphids per leaf from 8 April to 8 June. Adult peak density of 46.9 aphids per leaf was recorded at 31 May. The population densities of adults decreased after 31 May as reached 0.05 aphids per leaf at 18 July.
The nymph densities were rapidly increased from 9.6 to 38.7 aphids per leaf during 8 April to 12 May. Three distinct density peaks of 38.7, 46.9 and 22.5 aphids per leaf were observed at 12 May, 31 May and 30 June, respectively. The nymph densities were dropped after 30 June. Nymph and adult stages of the aphid finally disappeared in samples in 25 July.
No significant differences were found between population densities of the aphid in different heights and sides of hazelnut canopy (df = 11, 192; F = 1.86; p>0.05) (Fig. 2).
Spatial distribution: The regression relationship between logarithm mean and logarithm variance of M. coryli is showed in Fig. 3. The correlation coefficient value for Taylor's model was significantly different from 0. Therefore, this model accurately describes the mean-variance linear relation for the M. coryli data set (p = 0.00, df = 19, t = 9.7). Slope value of the regression (b) was significantly different from 1(p = 0.00, df = 19, t = 7.8) that indicated an aggregated distribution pattern for M. corylion hazelnut leaves.
|| Regression relationship between logarithm mean and logarithm
variance of Myzocallis coryli
M. coryli was observed during moderate months of year (from August to
July) on hazelnut. In this period, weather temperature was 12.5-31.5°C in
Boroujerd during 2010-2011. The adult and nymph densities decreased with increasing
weather temperature above 25°C. The negative effect of high temperature
on aphids has also been reported by other authors. For example, temperature
above 25°C had a harmful effect on Macrosiphum rosae L. (Mehrparvar
and Hatami, 2007). Wang et al. (2002) showed
that temperatures higher than 32°C reduced developmental rate of Aphis
spiraecola. Similarly, study of Satar and Yokomi (2002)
indicated that developmental rate of Brachycaudus scwartzi nymphs decreased
at temperature above 25°C.
Result showed that M. coryli observed on hazelnut during April to July
in Lorestan province, Iran. This result conflicts with those observed by Naeem
and Compton (2000). They showed that the aphids were presented during May
to September and peaked at July in North of England. Different climatic condition
of west of Iran and north of England may be due to the conflict result. Aphid
populations from geographically separated areas respond to temperature differently
(Olmez et al., 2003; Mehrparvar
and Hatami, 2007).
Havelka and Stary (2007) reported that Myzocallis
walshii Monell observed eight months (from April to November) on red oak,
Quercus rubra L. in Czech Republic. Differences between aphid species,
climatic condition and host plant may be due to conflict of they results with
our study. Kidd (1985) showed that host plant quality
affect population dynamic of aphids.
Spatial distribution of M. coryli was aggregative on hazelnut. Analysis
of spatial distribution pattern is recognized as a necessary procedure for insect
population studies and provides basic information to designing efficient and
cost effective sampling plans for population estimation and pest management
(Madadi et al., 2011).
We thank S. Yarahmadi, Dr. Mohiseni, Pirhadi for their technical assistance. Research received financial support from research deputy of Ramin Agricultural and Natural Resources University which is appreciated.