Agricultural and Forest Entomology (2014), DOI: 10.1111/afe.12075

Population dynamics and economic losses caused by Zeuzerapyrina, a cryptic wood-borer moth, in an olive orchard in Egypt

Esmat Hegazi∗, Fredrik Schlyter†, Wedad Khafagi‡, Atwa Atwa§¶, Essam Agamy∗∗ and Maria Konstantopoulou††

∗Department of Entomology, Faculty of Agriculture, Alexandria University, 542245, Aflaton Str., Alexandria, Egypt, †Unit of Chemical Ecology,Department of Plant Protection Biology, Swedish University of Agricultural Sciences, PO Box 102, SE-230 53 Alnarp, Sweden, ‡Biological Control,

Plant Protection Research Institute, 3236, Bacoos, Alexandria, Egypt, §Plant Protection Research Institute, 77688, Nadi El Seid Str., Cairo, Egypt,¶King Abdul-Aziz University, Jeddah, Kingdom of Saudi Arabia, ∗∗Department of Entomology, Faculty of Agriculture, Cairo University, Cairo, Egypt,and ††Chemical Ecology and Natural Products Laboratory, NCSR ‘Demokritos’, 15310, Paraskevi Str., Attikis, Greece

Abstract 1 The leopard moth Zeuzera pyrina L. (ZP) is an invasive pest from Europe of increasingsignificance in North Africa, in particular for olive cultivation. We followed thetemporal dynamics by combined light/pheromone trapping over a 10-year period(2002–2011) in a 240-ha olive farm in Northern Egypt.

2 The ZP had an annual cycle with one or two peak flights, from late April until October.Time series analysis showed a 2-year cycle of trap catch. This cycle is likely related tothe ‘on/off’ bearing pattern of the olive, where years of high and low yield are observedto alternate.

3 Larval damage in both ‘on’ and ‘off’ years in the infested trees gave fruit yield lossesof 37–42%. The loss was estimated to 2.1–4.8 t/ha among susceptible varieties. Therelative losses were the same during on and off years.

4 Infestation of four susceptible and five resistant olive cultivars in different croppingsystems varied within and between adjacent plots. The results suggest less infestationby intercropping of resistant varieties, which could assist in ZP management.

5 Both temporal and spatial dynamics strongly influence population dynamics and thedynamics are related to variation in the moth host plant.

Keywords ARIMA, leopard moth, olive, periodic oscillations, population dynamics,Zeuzera pyrina.

Introduction

The olive tree (Olea europea L.) plays an important part in thelives of Mediterranean people. Its role is multiple: nutritional,social, cultural, economic and political. The key insect pestsof Mediterranean olives are the olive fruit fly Bactrocera oleae(Gmelin), the olive moth Prays oleae (Bernard), and the blackscale Saissetia oleae (Olivier). However, another insect pest, theleopard moth Zeuzera pyrina L. (ZP) (Lepidoptera: Cossidae),has become of increasing impact in North Africa in the lastfew decades (Katsoyannos, 1992). Little is known of its ecol-ogy in this new context. The larvae of ZP are cryptic wood-borers affecting a wide variety of trees and shrubs, comprisingover 150 plant species from 20 genera (Balachowsky & Mesnil,1935; Carter, 1984; Castellari, 1986; Gratwick, 1992; Kutinkova

Correspondence: Esmat Hegazi. Tel.: +2 (3) 5908497; fax: +2 (3)5922780; e-mail: eshegazi@hotmail.com

et al., 2006). Newly-established olive orchards suffer the great-est damage, including the death of young trees. In nurseries, thedamage can be particularly extensive (Liotta & Giuffrida, 1967;Castellari, 1986). In Egypt, damage caused by ZP led to uproot-ing of olive groves by growers (E. Hegazi, unpublished data).The damage caused by the larval tunnels in structurally criticalwood can be extremely serious to a tree already bearing a fruitload; it causes ordinary branches to break under a medium load,whereas it may cause complete death of young trees with a heavyload as a result of damage to the major branches and trunk.

Monitoring and control of this cryptic moth is extremelydifficult because the larvae bore deep into twigs, branches andtrunks. Visual inspection of larval activity has been used asmain method of monitoring this pest (Kutinkova et al., 2006).However, night-active adult moths are difficult to observe in thefield. Many moth pests of agricultural importance are commonlymonitored using pheromone traps (Durant et al., 1986; Delisle,1992), although other monitoring techniques such as black-lighttraps are also used (Steinbauer, 2003; Szabo et al., 2007).

© 2014 The Royal Entomological Society

2 E. Hegazi et al.

Methods of monitoring ZP adults by using pheromone-baitedtraps have been investigated (Tonini et al., 1986; Pasqualiniet al., 1992; Pasqualini & Natale, 1999). There are, however,some limitations with respect to using light (Blomberg et al.,1976; Baker & Sadovy, 1978) or pheromone traps (Malo et al.,2001) alone. Light traps are less competitive than calling femaleswith respect to capture males, whereas pheromone traps do notcapture females. The available data on the flight phenology andbiology of ZP in Egypt are scarce and often contradictory (Ismailet al., 1992). Hence, we have used trapping stations combiningpheromone and black light trapping (Hegazi et al., 2009)

In our study area, a major outbreak of ZP occurred in July toOctober 2001, causing massive damage. Of the 240-ha planta-tion, 12 ha were severely infested by ZP and the owner had aplan to uproot this area. Initiation of insect outbreaks is poorlyunderstood. Factors causing such outbreaks remain enigmatic asa result of the requirement for many years of data, as well as theexamination of detailed mechanisms (Maron et al., 2001; Nel-son et al., 2013). In addition, the olive has a strong year-to-yeardeviation cycle in yield, known as ‘on/off’ years (Lavee, 2007).This alternate bearing is highly dependent on the climate ineach growing region (Morettini, 1950; Hartmann, 1951). Thesedistinct ‘on/off’ years in the host tree are expected to co-varywith the population dynamics of the moth, although no detailsare known.

In the present study, we aimed to investigate relevant aspectsof the population dynamics and the impact of this upcomingpest in North Africa, leading to an improved integrated pestmanagement of this invasive pest.

We document the population dynamics on seasonal and yearlyscales by full season pheromone and black light trapping (Hegaziet al., 2009) for the months of April to November over 10 years,including five pairs of ‘on/off’ years. The dynamics are modelledby an autoregressive integrated moving average (ARIMA) timeseries. Intensive damage records (visual) and loss estimates(grower’s data) were recorded for 2 years for estimates ofeconomic loss, in addition to a 1-year study of infestation atdifferent scales of variety intercropping.

Materials and methods

Experimental fields

The present study was conducted in a commercial olive farm(Fig. 1) with drip-irrigation, located in the arid growing areabetween Alexandria and Cairo (30∘51′21′′E; 30∘08′27′′N),177 km south of Alexandria, 60 km north of Cairo. The farm(240 ha, 336 trees/ha) is divided into 88 plots (3.0–3.5 ha, eachcomprising two varieties/plots) isolated by windbreak hedges.The olive trees were 11–12 years old, 3–4 m in height, plantedat a distance of 5 m along the row and 6 m between rows.The principal cultivars of table olives at the orchard (61 774olive trees) were Picual representing approximately 27.2%,Manzanello representing approximately 26.1% and Toffahirepresenting approximately 12.4%. Less than 10% were foundfor six cultivars; Kalamata, Akss, Sennara, Dolcie, Hamed andShami, representing approximately 8.1%, 6.2%, 5.8%, 5.3%,4.7% and 4.2%, respectively, of the total bearing. Varietiesconsidered as susceptible (Hegazi & Khafagi, 2005) are shownin italics.

Each quadratic plot was divided into 10 sectors or ‘strips’,each comprising approximately 30 trees. Each strip combinedthree lines of one cultivar alternating with another strip of threelines of the second cultivar, and so on, in a ‘strip intercroppingsystem’. Thus, the width of each strip was similar. It wasestablished in 1996, drip irrigated and not in close proximity to anapple plantation or other known host plants of ZP grown within15 km, and only palm trees and naturally occurring wild plantswere nearby.

No chemical control was applied on monitoring or experimen-tal plots during the experimental period. The arid climate (datafor 2006–2009) comprised rainy seasons lasting from Novem-ber /December to January/February with a mean annual rainfallof 9.2 mm. The mean monthly minimum temperature varied from10.2 ∘C in January to 23.9 ∘C in August and the mean monthlymaximum temperature varied from 18.9 ∘C in January to 35.6 ∘Cin July. The mean relative humidity ranged from 47.8% in Aprilto 63.8% in January.

Detection of infested trees, natural enemies and larvalphenology

Infestations were recognized (Fig. 2) by the presence of (i) cylin-drical yellowish to brown excrement pellets in bark crevices,around the entrance of larval tunnels and on the ground; (ii) pro-truding empty pupal skins on the infested parts by ZP, indicatingthe emergence of moths from larval tunnels; (iii) several partlybroken branches as a result of fruit load and wind mechanicaldamage with dead brown foliage hanging in tree crowns, char-acteristic of heavy infestation; and (iv) secreting gum near theinfested parts. In September 2007 and 2009, we collected lar-vae during this larval monitoring for quantification of parasitoidincidence.

Phenology of larvae was investigated by careful field dissectionof branches, twigs and trunks of heavily-infested trees in the lateand early 2010 and 2011 olive seasons, respectively, to estimatelarval abundance in relation to spring flight period of the moths.

Trapping for temporal variation

To study the population cycles, the flight phenology of the adultleopard moth was studied for 10 consecutive seasons with anultraviolet–light pheromone sticky trap combination (Fig. 1C)(Hegazi et al., 2009). Five traps (one trap every 3 ha) were usedper season in plots that combined susceptible olive varieties(Toffahi, as well as Sennara or Sennara and Hamed). Each trapwas baited with pheromone dispenser (Fersex ZP; SEDQ, Spain).The main components of the product are: (E,Z)-2,13-octadecenylacetate and (E,Z)-3,13-octadecenyl acetate. For each trap, ahollow metal stake was placed in the ground of the selectedarea. A wooden pole of a slightly smaller diameter than thehollow metal stake was cut to the appropriate height and slippedinside the metal stake. The trap was mounted on the top of thewooden pole. The hollow metal stakes acted as rat guard (i.e.to prevent rats from climbing up to the trapping insects). Trapheight was adjusted to 50–100 cm above the level of the canopy.Light was run from sunrise to sunset only. The distance betweentraps was >200 m. The position of the traps was switchedat each visit to minimize the possible effects of microhabitat

© 2014 The Royal Entomological Society, Agricultural and Forest Entomology, doi: 10.1111/afe.12075

Population cycles of Z. pyrina 3

(A) (C)

(B)

Figure 1 (A) The olive farm from satellite view. (B) Close up of part of the olive farm from satellite. A and B imagery from Google Earth(http://www.google.com/earth/). (C) The pheromone-light trap.

structure between the plots and rebaited with fresh dispensersevery 40 days. Trapping was initiated in mid-April and endedin the second week of November of each season. Trap capturesof male and female moths of ZP were counted every other dayduring which the sticky pad was changed. Data are presented asmean catches/trap per week or per month for additional detail.Females were carefully dissected to determine their reproductivestate.

Yield and economic losses

In 2006 and 2007, efforts were made at the experimental farm toensure uniform ZP infestation plots by using highly susceptiblelocal varieties (Toffahi and Sennara/plot) and adjusting both thetime of fertilizer application and irrigation, keeping the exper-imental plots free of chemical or mechanical insect control todocument the level of damage by an unmanaged ZP infestation.The design could use only two naturally severely injured oliveplots with ZP with plantings of susceptible local olive varieties(Sennara & Toffahi) exactly similar to those available in this partof the olive farm in the 2006 and 2007 olive seasons. There is adrawback to this design because only two plots were included,although the 15-fold sampling of each variety and the naturalpresence of infested and uninfested trees ensured sufficient andsome degree of independent variation of observations. However,only the effect of the infested/uninfested categories can be for-mally tested without pseudoreplication (Hurlbert, 2009) and notthe direct effects of the different susceptibility of varieties.

Economic losses as a result of ZP were measured basedon actual yield losses. Crop loss can be defined (de Groote,

2002) as the difference between the actual yield by the infestedtrees and the potential yield or, more precisely, as the yieldthat would have been obtained in the absence of the pestunder study, estimated from ‘apparently uninfested trees’. Two,3-ha naturally badly infested olive plots with leopard mothplanted with the same susceptible local varieties/plot (Sennaraand Toffahi) were selected to study the economic loss causedby the pest for two successive years (2006 & 2007). Alltrees/variety/sector were checked every other week from Julyuntil late September to record the presence of active tunnels ofZP larvae, the number of broken branches bearing fruit and theobserved tunnels marked. In each inspection, fruit weight/brokenbranches (infested) was also recorded. At harvest time, treeswere classified into infested and apparently uninfested. Severely(i.e. with extensive signs of injury) or moderately injured trees(three to six broken limbs) as a result of ZP larvae wereconsidered as infested. Dead or fruit-free trees (9%) werenot included. At harvest time, the fruit yield of three treesof both infested and apparently uninfested/sector (i.e. each,3 trees× 5 sectors= 15 trees/variety/plot= 120 trees/season) wasselected randomly to estimate the real fruit yield/tree.

The real fruit yield (Y r)= yield of infested trees+ yield ofuninfested trees.

The theoretical or ‘potential yield’/sector (Yp)= number oftrees/sector×mean of fruit weight/uninfested tree of the samesector.

The difference between real and theoretical yield gives the croploss weight (LW):

Yp – Yr = Lw (1)

© 2014 The Royal Entomological Society, Agricultural and Forest Entomology, doi: 10.1111/afe.12075

4 E. Hegazi et al.

(A) (B) (C)

(D) (E) (F) (G) (H)

Figure 2 (A) Badly infested tree by Zeuzera pyrina (ZP). (B) Larval tunnel in broken branch. (C) Branch of susceptible tree containing 21 ZP larvae. (D)Protruding empty pupal skins indicating the emergence of ZP moth. (E) Secreting gum near the infested parts. (F) Emergence hole of larval tunnel. (G)Yellowish to brown faecal pellets. (H) Low fruiting yield of infested tree.

Multiplication of crop loss with the price of olive fruits perweight ($W) gives the economic loss (LE) of ZP per area(Table 1):

Lw × $W = LE (2)

Spatial variation of infestation and yield

After making informal observations during 2006 and 2007indicating a possible lower infestation in susceptible-varietyplots near resistant-variety plots, we made a small study ofspatial variation of infestation. In 2009, six target plots, eachcomprising 3-ha naturally-infested olive plots with ZP plantedwith olives varying in their tolerance to ZP, were selected tostudy the possible effects of variety intercropping [i.e. some weresusceptible (S) and some were resistant (R)] (i.e. variety mixturesin target plots as S+S, S+R, R+R). In addition, each treatmentplot had ‘pure’ neighbouring plots of only resistant (RR) orsusceptible (SS) trees on both sides (Table 2). All trees of eachtarget plot were inspected for activity of the cryptic larvae everyother week, as described above. At harvest time, trees of each plotwere classified into apparently uninfested, moderately infested(less than six broken branches/tree) and severely (more than eightbroken branches/tree) infested trees. The fruit yield of six treesof each category for each variety/target plot was harvested andweighed.

The number and combination types of resistant and suscep-tible varieties pairs did not allow for a full factorial analysisof variance (anova), testing for both the effect of the identityof varieties inside target plots and the influence of resistantor susceptible neighbours on the infestation rate (Table 2).However, without resorting to pseudoreplication (Hurlbert,2009), we could contrast the influence of neighbouring plots

(RR- or SS-types) on yield loss in target plots that had at leastone resistant variety (R+R or R+ S). The restriction of pos-sible contrasts was a result of the paucity of target plots withS-varieties present.

Statistical analysis

Trapping counts were analyzed for cyclic patterns at differentmulti-annual levels by ARIMA time series algorithms (Yaffee &McGee, 2000) using ibm spss, version 19 (IBM Corp., Armonk,New York) with procedures TSMODEL and TSPLOT. Thistype of model is only a statistical fitting to data and does notaddress any biological detail of the population dynamics suchas rates of birth or deaths as in a population dynamics-basedmodel (Turchin, 2013). ARIMA time series models are the mostgeneral class of models for forecasting a time series that canbe stationarized by transformations such as differencing andlogging (Yaffee & McGee, 2000). This type of model can beseen as a fine-tuned version of random-walk models, wherethe fine-tuning consists of adding lags of the differenced seriesand/or lags of the forecast errors to the prediction equation, asneeded to remove any last traces of autocorrelation from theforecast errors. The numerical outputs of the ARIMA modelsare not given in the results; instead, only the correspondingauto-correlation function (ACF) and partial ACF (PACF) plotsare provided, which give visual information on the best supportedpopulation cycle lengths obtained from the data by the models.We included an estimate of the yearly trapping total for the first‘outbreak’ in 2001 to gain an 11-year series allowing analysisof somewhat longer cycles. The added conservative estimate for2001 was found by rounding up to the one-significant digit highervalue compared with the 2009 total, because 2001 was observedto have a clearly higher damage magnitude.

© 2014 The Royal Entomological Society, Agricultural and Forest Entomology, doi: 10.1111/afe.12075

Population cycles of Z. pyrina 5

Table 1 Economic losses in local susceptible olive cultivars caused by Zeuzera pyrina in two plots estimated under natural infestation in ‘high-fruitingyear’ 2006 and ‘low-fruiting year’ 2007

Infested trees Apparently uninfested trees Losses/hac

Trees Limb fruit Fruit yield Trees Yield Real yield TheoreticalPlot Variety Number loss(t) Total (t) Per tree (kg) Number Total (t) Per tree (kg) (Y r)

a (t) yield (Yp)b (t) LW (t) LE ($)

Season 20061 Sennara 163 1.3 5.6 34.9±1.7 227 12.5 56.7±4.8 18.1 22.1 3.1 1800

Toffahi 239 2.3 7.4 31.6±2.1 151 8.2 55.0±3.5 15.7 21.4 4.8 32002 Sennara 127 0.6 4.5 35.2±2.8 263 15.8 61.0±3.9 20.3 23.8 2.8 1700

Toffahi 119 0.8 4.3 37.1±2.8 271 16.1 59.5±3.3 20.5 23.2 2.3 1500Season 2007

1 Sennara 161 0.6 4.8 29.6±1.5 229 11.7 51.0±1.3 16.4 19.9 2.9 1700Toffahi 162 0.8 4.5 28.5±2.2 228 10.8 47.1±1.8 15.3 18.4 2.6 1700

2 Sennara 143 0.6 3.9 27.7±2.8 247 11.9 48.6±1.5 15.9 18.9 2.6 1500Toffahi 134 0.7 4.0 28.7±2.6 256 12.1 47.3±1.2 16.0 18.4 2.1 1400

aThe harvest of infested and non-infested trees, based on the samples of 15 trees/variety/plot.bThe theoretical or potential yield (Yp) is calculated as number of trees×mean yield of uninfested trees (per variety and plot).cWeight of crop loss (LW) and economic loss (LE) is the difference between Yp and Yr and the product of LW and price per weight ($W), in accordancewith Eqns 1 and 2, respectively (see Materials and methods).

Table 2 Infestation rate (%) and yield losses in target olive plots and the effect thereon of neighbouring plots with different combinations of susceptibleand resistant olive trees in 2009

Target plot fruit yield/tree (kg)

Target plot’scultivarsa

Infestation rate(%)b

Apparentlynon-infested

Moderatelyinfested

Severelyinfested Mean/infested tree Loss (t/ha)

Olive cultivars ofneighbouring plotsc

Picual (R) 0.0 49.0±4.3 0.0 0.0 0.0 0.0 RR ‘Dolcie & Shami’Manzanello (R) 0.0 59.0±4.3 0.0 0.0 0.0 0.0Dolcie (R) 0.0 80.0±3.5 0.0 0.0 0.0 0.0 RR ‘Dolcie & Kalamata’Kalamata (R) 0.0 26.4±2.7 0.0 0.0 0.0 0.0Picual (R) 8.2 37.6±2.5 10.2± 1.6 0.7±0.3 5.4±1.7 0.9 SS ‘Toffahi & Sennara’Manzanello (R) 10.3 45.0±3.5 13.0± 2.1 0.6±0.4 6.8±2.3 1.3Shami (R) 9.1 55.0±3.5 18.6± 1.9 2.8±0.9 10.7±2.8 1.4 SS ‘Hamed & Sennara’Toffahi (S) 18.9 81.0±4.3 26.4± 2.7 0.0 13.2±4.6 4.3Kalamata (R) 11.1 26.6±2.6 11.0± 1.2 0.0 5.5±1.9 0.8 SS ‘Toffahi & Sennara’Toffahi (S) 17.5 75.0±3.5 20.2± 1.8 1.1±0.6 10.6±3.3 3.8Sennara (S) 25.3 67.0±4.6 19.4± 1.7 3.6±1.2 11.5±2.8 4.7 SS ‘Toffahi & Sennara’Hamed (S) 39.8 16.0±1.4 3.6±0.8 0.1±0.1 1.8±0.7 1.9

aType of variety in plot: S, susceptible; R, resistant.bTarget plots are sorted by mean target plot infestation rate of the two target plot cultivars.cType of variety of neighbouring plots: SS, both cultivars susceptible; RR, both cultivars resistant.

The field surveys were conducted using a complete random-ized block design and data were subjected to anova (SAS,2000). Data are presented as the means of moth catches and fruityield/tree. Means were normalized using log(x+ 0.5) transfor-mation to increase variance homogeneity. For the infestation rate,we had to use nonparametric statistics as a result of the many zerovalues.

Results

Trapping study: within and between years variation

Moth catches and larval phenology. Monthly catches inlight-pheromone traps for ZP, over the period 2002–2011,are presented in Fig. 3. The first capture occurred during lateApril or early May and then continuously from May throughout

the growing season until mid-November (i.e. moths were presentall season). The population trends of ZP showed one annualpeak in some years (2005, 2008 and 2009) and two peaks inmost years. Moth emergence takes place from late April tomid-November. The highest number of trapped moths occurredin September or August to September (Fig. 3). The flight periodof the minor peak was only observed during May (2005) or June(2002, 2004, 2010 and 2011). Field dissection of infested woodshowed that a large number of larvae of different ages remainedin a dormant stage over the 2010 winter, whereas, in the springof 2011, they started feeding and boring into the tree. A cohortof larger ones (10–28% of total larvae) become full-grown inlate spring and could change to pupal stage and these may createthe minor flight. Most of the ZP larvae were much smaller,continuing to feed throughout the season and become fullygrown only in the late summer, creating the larger peak.

© 2014 The Royal Entomological Society, Agricultural and Forest Entomology, doi: 10.1111/afe.12075

6 E. Hegazi et al.

0

10

20

30

40

50

60

(A) (B)

(C) (D)

(E)

70

80

Mot

hs/T

rap/

Mon

th

2002"on"2003"off"

0

10

20

30

40

50

60

70

802004"on"

2005"off"

0

10

20

30

40

50

60

70

80

Mot

hs/T

rap/

Mon

th

2006"on"

2007"off"

0

50

100

150

200

250

300

3502008"on"

2009"off"

0

10

20

30

40

50

60

70

80

Mot

hs/T

rap/

Mon

th

Month

2010"on"2011"off"

2010 "on"

Figure 3 (A–E) Monthly number of Zeuzera pyrina captured/trap in pheromone-light traps during the 2002–2011 olive seasons. Vertical bars representthe mean±SD.

The yearly total season-long capture of leopard moths is shownin Fig. 4(A). Generally, higher numbers of ZP moths weretrapped in ‘off’-years versus smaller ones in ‘on’-years. A 2-yearcycle can be seen directly in raw trap counts for 2002–2011(Fig. 4A). This is supported by time series analysis, as indi-cated by the ACF plot in Fig. 4(B) showing yearly alternatingpeaks. All seven of these were significant by a Ljung–Box test(P< 0.05). However, PACF, which removes effect of correlationto intermediate lag years, contains only one peak crossing the

confidence interval of no effect, the first lag peak (Fig. 4C). Thisfirst lag (t= t− 1) corresponds to a 2-year cycle (a previous yearis the most different, or in other words; years that are 2 yearsapart are the most similar). From the original 10-series data,no longer cycles, corresponding to higher lags, were discernible(Fig. 4B,C).

When we included an estimate of trapping level for thefirst ‘outbreak’ in year 2001, an 11-year series with two large‘outbreak’ peaks is clearly seen (Fig. 4D). The ACF plot for this

© 2014 The Royal Entomological Society, Agricultural and Forest Entomology, doi: 10.1111/afe.12075

Population cycles of Z. pyrina 7

Year20112010200920082007200620052004200320022001

Lag Number87654321

AC

F

1.0

0.5

0.0

−0.5

−1.0

Lag Number87654321

Par

tial

AC

F

1.0

0.5

0.0

−0.5

−1.0

Year2011201020092008200720062005200420032002

Tra

p c

atch

ln

(y)

6.5

6.0

5.5

5.0

4.5

(A)

Lag Number7654321

AC

F

1.0

0.5

0.0

−0.5

−1.0

(B)

Lag Number7654321

Par

tial

AC

F

1.0

0.5

0.0

−0.5

−1.0

(C)

(D)

(E)

(F)

Figure 4 Full season counts of captured Zeuzera pyrina moths during the 2002–2011 olive seasons. (A) Yearly catches for 10 years of trapping,2002–2011, transformed by ln(x). •, ‘on’ years with high fruiting. (B) Autocorrelation function (ACF) plot among years for the 10-year series at differentlags (past years). The series was differentiated by 1 year to achieve stationarity (constant mean and variance over time). (C) Partial ACF plot (whichremoves the effects of intervening years) for the 10-year series. (D) Yearly catches with an added, conservative estimate of catch for 2001 based on theoutbreak level observed that year, giving a 11-year series [transformed by ln(x)]. (E) ACF for the 11-year series, differentiated by 1. (F) Partial ACF for the11-year series. In (A) and (B), the horizontal line is the mean of the series. In (B), (C), (E) and (F), solid lines give the 95% confidence limits for coefficients.

© 2014 The Royal Entomological Society, Agricultural and Forest Entomology, doi: 10.1111/afe.12075

8 E. Hegazi et al.

new 11-year series again shows many strong values, passing the95% confidence lines at a lag of 1 and at a lag of 7 and 8 (Fig. 4E),indicating that there might be both a 2-year cycle (peak yearsare 2 years apart) and a possible 8- or 9-year cycle (peaks are8 or 9 years apart) (Fig. 4E). However, the partial ACF stronglysupports only a signature of cycles at lag 1 (corresponding to a2-year cycle), just as the original data set of only 10 years does(Fig. 4F).

Female catches and natural enemies. Female catches were verysmall. However, during the whole trapping season, of all trappedleopard moths (218 and 505 moths/trap) in ‘off’-years of 2007and 2009, only 10% and 13% were female, respectively. In‘on’-years of 2008 and 2010, females represented 4.1% and2.9%, respectively. Almost all females caught in the trap werealready mated and gravid, bearing approximately 500–2000eggs at various developmental stages. Very few leopard mothswere females during April to June of the trapping season.From August until late October, the trapped females laid theireggs on the sticky sheet of the trap (400–950 eggs/female).On 3 September 2007, 245 mid- to large-sized leopard mothlarvae were dissected from heavily-infested trees. We deter-mined that 1.2% of larvae were parasitized by an ecto-parasitoidwasp (Hymenoptera: Eulophidae: Hyssopus sp.), 1.6% wereinfected by the entomopathogenic fungus Beauveria bassiana,1.2% were infected by Metarhizium anisopliae and only onelarva was infected with entomopathogenic nematodes (Stein-ernema sp.). On 15 September 2009, we dissected 155 ZPlarvae, although only 1.9% were infected by M. anisopliae,whereas ants were seen to be busy collecting newly-hatched ZPlarvae.

Yield and economic losses

Figure 5 shows the fruit harvest/tree of apparently uninfestedand ZP infested trees in year 2006 (a ‘high fruiting year’) and2007 (a ‘low fruiting year’). A very significant difference as aresult of infestation was clear, with a much higher fruit yieldfrom uninfested trees compared with infested ones (P< 0.0001).However, not only the infestation factor (infested tree/apparentlyuninfested), but also the year was a very significant factorin yield (P< 0.0001), whereas there was no interaction at all(P> 0.10, factorial anova) for infestation× year. This meansthat the relative importance of infestation by ZP was the same,irrespective of the fruiting level of the host tree (Fig. 5). Thedata in Table 1 summarize the economic loss in two plotsof a cropping system [Sennara (S)+Toffahi (S)] caused byZP under a natural infestation (n≈ 390 trees/variety/plot). Thetwo varieties appeared to have very similar yields within eachcategory of infestation and year (Table 1). Crop losses in weight[LW in Eqn 1] were a function of the final infestation and theolive yield of the year. In 2006, the final infestation near harvesttime varied between 30% and 61% for different varieties andplots. The average annual crop losses (LW) were calculated asbetween 2 and 5 t/ha, respectively, implying economic losses[LE in Eqn 2] of some 1500 and 3200 $/ha. The average lossesof fruits on broken branches reached up to 8 and 6 kg/infestedtree for Sennara and Toffahi trees, respectively (Table 1). In

Year2007 Low fruiting2006 High fruiting

95%

CI Y

ield

/tre

e (k

g)

70

60

50

40

30

20

10

0

Infested tree

Apparently unifestedInfestation

Figure 5 The fruit harvest in two badly infested plots by Zeuzera pyrina,in a 2006 season ‘on’ year and 2007 season ‘off’ year (mean±SEM).Infestation and year are both very highly significant factors by analysis ofvariance at P>0.0001 (F1,12, both >50) (***) but not the interaction ofinfestation× year (F1,12 =2.9, P>0.10) (not significant; NS).

the low fruiting year of 2007, the infestation near harvest timewas 34–41%. The average annual crop loss corresponded toeconomic losses of some 1400–1700 $/ha (Table 1).

Spatial variation of infestation and yield with varietyintercropping

We observed the response of five pairs of different olive vari-eties with two different cropping systems, namely adjacent plotswith a pair of either susceptible or resistant varieties (Table 2).Losses of yield (t/ha) for the susceptible varieties were sim-ilar to those in Table 1, although much less in the resistantvarieties (Table 2). The three first rows of Table 2, all withresistant varieties in the target plots (R+R), show the clear-est pattern. When the olive trees neighbouring the first two ofthese plots were resistant olive cultivars (only RR-type), infes-tation and losses were at zero levels. By contrast, for the plotwith Picual (R)+Manzanello (R) as the third row, with thesusceptible olive cultivars of Toffahi and Sennara as neigh-bouring plots (SS-type plots), infestation was 8–10% in thetarget plot (R+R). When two partly resistant cultivar mixes(S+R) were surrounded by SS-type plots, infestation appearedto be higher, 9–19%, and, with all cultivars susceptible (S+Swith SS-type neighbour plots), achieved 25–40% (Table 2, lastrows).

In target plots that had at least one resistant cultivar (R+Ror R+ S; n= 10), the influence on infestation rate by the twotypes of neighbouring plots [RR- or SS-types, mean±SE;0.0± 0.0% (n= 4) and 12.5± 1.9% (n= 6), respectively] wasquite significant (Mann–Whitney U = 24, P= 0.010).

© 2014 The Royal Entomological Society, Agricultural and Forest Entomology, doi: 10.1111/afe.12075

Population cycles of Z. pyrina 9

Discussion

We have clearly shown temporal variation in a yearly cycleand a 2-year cycle of population dynamics. In addition, thecorresponding economic damage was quantified in detail fordifferent varieties. We also observed a spatial variation indamage related to intercropping of resistant/susceptible varieties,indicating a possible associational resistance.

Subsequent to early 1995, nine olive cultivars have beenplanted in monoculture mixing olive varieties in desert areanear Cairo. In this area, an outbreak of the leopard moth ZPwas observed in 2001. One approach for understanding theZP population cycle comprises performing experiments onlong-term insect density during the initiation phase of a naturaloutbreak (Myers, 1988; Krebs, 1991). Accordingly, we per-formed long-term monitoring 1 year after the outbreak of theleopard moth ZP. When studying normal annual cycling of thisinsect in 2002–2011, we observed a new outbreak in 2009. Thestrict isolation of this area, not in proximity to apple plantationsor any other known host plants of ZP and surrounded by sanddesert habitat, makes it ideal for studying a local populationwithout biotic influence from landscape scale.

Temporal variation

Annual. The trapping study indicated that the ZP has an annualbiological cycle in olive trees in Egypt. Captures show theoccurrence of an early-season flight that continued throughoutthe growing season and into the autumn and the beginning ofharvest. The largest flight of the year began near the end of theseason. The observation of a large number of larvae of differentsizes in a dormant stage over the winter of 2010 indicates a cohortof larger individuals becoming full-grown in late spring resultinga minor peak, whereas the smaller individuals become full grownin late summer and create the major flight peak. In both cases,this constitutes a single yearly cycle of reproduction. Thus, thenumber of flight peaks appears to depend on the population agestructure of ZP larva, which is likely dependent on multi-yeartemperature patterns.

The 2-year cycle. Our data and ARIMA time series analysisclearly show a 2-year cycle in total catches. When attempting toexplain such annual trends in trapping the leopard moth, recordscan be associated with alternative bearing in some fruit trees.Olive (Olea europea) has very high tendency for year-to-yeardeviation in yield (Lavee et al., 1996; Seyyednejad et al., 2001;Lavee, 2007). Studies on changes in carbohydrate componentsof leaves from ‘on’ (bearing) and ‘off’ (nonbearing) years cyclehave shown that sugars are much higher at the beginning of anon- than of an off-year yield (Lavee et al., 1996; Seyyednejadet al., 2001; Lavee, 2007; Erel et al., 2013). Also, the degreeof alternate bearing is highly dependent on the environmentalconditions and might be very different in accordance with theclimate in each growing region (Morettini, 1950; Hartmann,1951; Sadok et al., 2013; Turktas et al., 2013; Yanik et al.,2013). The depletion of stored carbohydrates during the on-year(high yield) (Bustan et al., 2011) and environmental conditionsmay affect the availability and quality of living wood as foodmaterial for ZP larvae (Hoch et al., 2013). Thus, it appears that

living wood during the off-year is of a high ‘nutritional quality’that accelerates larval growth, leading to a decline in naturallarval mortality, an increase in female fecundity and, in turn,an increase in the annual trapped ZP moths in the subsequentoff-year season.

Outbreaks. Initiation of insect outbreaks is poorly understoodand the factors involved in the initiation of insect outbreaksremain enigmatic (Maron et al., 2001; Myers & Cory, 2013).There is a general asuumption that insect outbreak risk is higherin plant monocultures than in natural and more diverse habi-tats, although empirical studies investigating this relationship arescarce (Jactel & Brockerhoff, 2007; Dalin et al., 2009). Otherexplanations have been reported, including changes in food-plantquality (Schultz & Baldwin, 1982; Mattson & Haack, 1987;Rossiter, 1992), favourable weather (Martinat, 1987) and reduc-tions in predation, parasitism or disease (Myers, 1988; Walsh,1990), although satisfactory tests are difficult to employ. Theinteraction of ZP with the parasitoids–pathogens observed inthe present study area appears to be too low to cause populationcycles. However, the results provide strong evidence of periodicbehaviour in population densities. It appears that the bearing pat-tern (food-plant quality) in the monoculture farm may generateherbivore periodic oscillations.

There is no apparent reason why large numbers were recordedin most traps in 2009. Most studies of the population dynamicsof forest-defoliating insects suggest outbreak cycles rangingfrom 8 to 12 years (Liebhold & Kamata, 2000). The gradualreduction of infestation of forest tree by lepidopteran insectsis the manifestation of a 9-year cycle that includes 3 years ofpopulation increase, 3 years of population at high levels and3 years of population decline (Myers, 1988). It is reasonable tospeculate that outbreak cycles of ZP are within 8–9 years.

Spatial variation

Entomological studies on interplanted perennial crop plants arescarce but indicate an effect of lower herbivore damage at ahigher tree diversity and the effects of specific semiochemicalsknown as nonhost volatiles (Jactel & Brockerhoff, 2007; Jactelet al., 2011). The present data are interesting in terms of rep-resenting the first estimate of losses in olive yield caused byZP. The observed trend suggests that mixing olive cultivars canassist in pest control and provide yield advantages. Neighbour-ing olive varieties can also influence the rate of ZP colonization.The results suggest that focal plants may gain protection fromherbivores because of their proximity to neighbouring plants andthereby be defended by neighboring plants’ anti-herbivore phys-ical or chemical traits (Baraza et al., 2006; González-Teuber &Gianoli, 2008), forming a case of associational resistance (Bar-bosa et al., 2009).

The present study is not intended to provide a generalizeddefinition for the attack threshold at which action should betaken against ZP but rather indicates that the intercropping ofinsect-resistant crop varieties among the susceptible varieties inolive orchards is economically, ecologically and environmentallyadvantageous. Ecological and environmental benefits arise fromincreases in species diversity in the agroeco-system, in part

© 2014 The Royal Entomological Society, Agricultural and Forest Entomology, doi: 10.1111/afe.12075

10 E. Hegazi et al.

because of reduced use of insecticide (Teetes, 1994). Many olivevariety combinations are possible and each can have differenteffects on beneficial/harmful insect populations. For example,the choice of tall resistant and short companion olives canmagnify these effects.

In all trapping seasons, larger numbers of ZP males werecaught compared with females in combined pheromone-blacklight traps. We speculate that, because the females areheavy-bodied, they might be extremely poor fliers. How-ever, the specific reason for the relatively higher female catch inan ‘off’-year compared with that in an ‘on’-year is not knownand may need further investigation. These seasonal flightscan be readily identified with pheromone-black light traps innaturally-infested susceptible olive cultivars, as indicated in thepresent study.

Conclusions

The present data are interesting, providing the first detailedestimate of heavy economic losses in olive yield caused by ZP.Control with conventional insecticides in this pest is almostimpossible because it is cryptic for most of the life cycle andthe use of systemic insecticides is more or less impossible in aslowly maturing food crop. Integrated management, however,allows both augmentation of beneficial and chemical ecologybased management options such as mass-trapping (Hegazi et al.,2009), mating-disruption (Hegazi et al., 2010) and an increaseof semiochemical diversity by intercropping (Zhang & Schlyter,2003). As shown in the present study, the most directly appli-cable method for this invasive pest comprises the monitoring ofdistribution and population levels by pheromone traps. A moredetailed and replicated study of the spatial variation of damagein relation to the composition of olive tree varieties and the quan-tification of volatiles released from foliage is now under way.

Acknowledgements

We appreciate the constructive criticism of the referees. A criticalreading of an earlier draft by Dr S. Hagenbucher improvedclarity. We gratefully acknowledge grower-collaborator Mr M.Sheta for providing several research plots in his orchards, as wellas more than 25 co-workers who provided invaluable help inthe field. EH thanks the Alexander von Humboldt foundationfor a research donation used in the present study. This studywas carried out with the financial support of SIDA/VR MENASwedish Research Links funds to FS and EH. FS was supportedby the Linnaeus programme ‘Insect Chemical Ecology, Ethologyand Evolution’ (ICE3)

References

Baker, R.R. & Sadovy, Y. (1978) The distance and nature of the light-trapresponse of moths. Nature, 276, 818–821.

Balachowsky, A. & Mesnil, L. (1935) Les insectes nuisibles aux plantescultivees. Leurs moeurs. Leur destruction. Traite d’entomologie agri-cole concernant la France, la Corse, l’Afrique du Nord et les regionslimitrophes. Paul Lechevalier, France.

Baraza, E., Zamora, R. & Hódar, J.A. (2006) Conditional outcomesin plant–herbivore interactions: neighbours matter. Oikos, 113,148–156.

Barbosa, P., Hines, J., Kaplan, I. et al. (2009) Associational resistance andassociational susceptibility: having right or wrong neighbors. AnnualReview of Ecology, Evolution, and Systematics, 40, 1–20.

Blomberg, O., Itämies, J. & Kuusela, K. (1976) Insect catches in ablended and a black light-trap in northern Finland. Oikos, 27, 57–63.

Bustan, A., Avni, A., Lavee, S. et al. (2011) Role of carbohydrate reservesin yield production of intensively cultivated oil olive (Olea europaeaL.) trees. Tree Physiology, 31, 519–530.

Carter, D.J. (1984) Pest Lepidoptera of Europe with Special Reference tothe British Isles. Dr W. Junk, The Netherlands.

Castellari, P.L. (1986) Zeuzera pyrina L. (Lep. Cossidae): biologicalinvestigations and field tests on the attractiveness of mixtures ofsex pheromone components. Bollettino dell’Istituto di Entomologia’Guido Grandi’ della Universita degli Studi di Bologna, 40, 239–270.

Dalin, P., Kindvall, O. & Björkman, C. (2009) Reduced populationcontrol of an insect pest in managed willow monocultures. PLoS One,4, e5487.

Delisle, J. (1992) Monitoring the seasonal male flight activity of Choris-toneura rosaceana (Lepidoptera: Tortricidae) in eastern Canada usingvirgin females and several different pheromone blends. EnvironmentalEntomology, 21, 1007–1012.

Durant, J., Manley, D. & Cardé, R. (1986) Monitoring of the Euro-pean corn borer (Lepidoptera: Pyralidae) in South Carolina usingpheromone traps. Journal of Economic Entomology, 79, 1539–1543.

Erel, R., Yermiyahu, U., Van Opstal, J. et al. (2013) The importance ofolive (Olea europaea L.) tree nutritional status on its productivity.Scientia Horticulturae, 159, 8–18.

González-Teuber, M. & Gianoli, E. (2008) Damage and shade enhanceclimbing and promote associational resistance in a climbing plant.Journal of Ecology, 96, 122–126.

Gratwick, M. (1992) Crop Pests in the UK: Collected Edition of MAFFLeaflets. Chapman & Hall, U.K.

de Groote, H. (2002) Maize yield losses from stemborers in Kenya. InsectScience and its Application, 22, 89–96.

Hartmann, H.T. (1951) Time of floral differentiation of the olive inCalifornia. Botanical Gazette, 112, 323–327.

Hegazi, E.M. & Khafagi, W.E. (2005) Varietal sensitivity of olive treesto the leopard moth, Zeuzera pyrina L. (Lepidoptera: Cossidae).IOBC/WPRS Bulletin, 28, 121–131.

Hegazi, E., Khafagi, W., Konstantopoulou, M. et al. (2009) Efficientmass-trapping method as an alternative tactic for suppressing popu-lations of leopard moth (Lepidoptera: Cossidae). Annals of the Ento-mological Society of America, 102, 809–818.

Hegazi, E., Khafagi, W., Konstantopoulou, M. et al. (2010) Suppressionof Leopard moth (Lepidoptera: Cossidae) populations in olive trees inEgypt through mating disruption. Journal of Economic Entomology,103, 1621–1627.

Hoch, G., Siegwolf, R.T., Keel, S.G. et al. (2013) Fruit production inthree masting tree species does not rely on stored carbon reserves.Oecologia, 171, 653–662.

Hurlbert, S.H. (2009) The ancient black art and transdisciplinary extentof pseudoreplication. Journal of Comparative Psychology, 123, 434.

Ismail, I., Abouzeid, N.A. & Abdallah, F.F. (1992) Population-dynamicsof the leopard moth, Zeuzera pyrina L, and its control on olive trees inEgypt. Journal of Plant Diseases and Protection, 99, 519–524.

Jactel, H. & Brockerhoff, E.G. (2007) Tree diversity reduces herbivoryby forest insects. Ecology Letters, 10, 835–848.

Jactel, H., Birgersson, G., Andersson, S. & Schlyter, F. (2011) Non-hostvolatiles mediate associational resistance to the pine processionarymoth. Oecologia, 166, 703–711.

Katsoyannos, P. (1992) Olive Pests and their Control in the Near East.Plant Production and Protection Paper, 115. Food and AgricultureOrganization of the United Nations, Italy.

Krebs, C.J. (1991) The experimental paradigm and long-term populationstudies. Ibis, 133, 3–8.

© 2014 The Royal Entomological Society, Agricultural and Forest Entomology, doi: 10.1111/afe.12075

Population cycles of Z. pyrina 11

Kutinkova, H., Andreev, R. & Arnaoudov, V. (2006) The leopard mothborer, Zeuzera pyrina L. (Lepidoptera: Cossidae) – important pest inBulgaria. Journal of Plant Protection Research, 46, 111–115.

Lavee, S. (2007) Biennial bearing in olive (Olea europaea). AnnalesSeries Historia Naturalis, 17, 101–112.

Lavee, S., Rallo, L., Rapoport, H.F. & Troncoso, A. (1996) The floralbiology of the olive: effect of flower number, type and distribution onfruitset. Scientia Horticulturae, 66, 149–158.

Liebhold, A. & Kamata, N. (2000) Introduction – are population cyclesand spatial synchrony a universal characteristic of forest insectpopulations? Population Ecology, 42, 205–209.

Liotta, G. & Giuffrida, I. (1967) Biological observations on Z. pyrinain Sicily. Bollettino dell’Istituto di Entomologia Agraria e dell’Osservatorio di Fitopatologia di Palermo, 6, 29–60.

Malo, E.A., Cruz-Lopez, L., Valle-Mora, J., Virgen, A., Sanchez, J.A.& Rojas, J.C. (2001) Evaluation of commercial pheromone lures andtraps for monitoring male fall armyworm (Lepidoptera: Noctuidae)in the coastal region of Chiapas, Mexico. Florida Entomologist, 84,659–664.

Maron, J.L., Harrison, S. & Greaves, M.E. (2001) Origin of an insectoutbreak: escape in space or time from natural enemies? Oecologia,126, 595–602.

Martinat, P. J. (1987) The role of climatic variation and weather inforest insect outbreaks. Insect Outbreaks (ed. by P. Barbosa and J. C.Schultz), pp. 241-268. Academic Press, Inc., San Diego, California.

Mattson, W.J. & Haack, R.A. (1987) The role of drought in outbreaks ofplant-eating insects. Bioscience, 37, 110–118.

Morettini, A. (1950) Olive Growing. Ramo Editoriale degli Agricoltori,Italy.

Myers, J.H. (1988) Can a general hypothesis explain population-cycles offorest Lepidoptera? Advances in Ecological Research, 18, 179–242.

Myers, J.H. & Cory, C. (2013) Population cycles in forest lepidopterarevisited. Annual Review of Ecology, Evolution, and Systematics, 44,565–592.

Nelson, W.A., Bjørnstad, O.N. & Yamanaka, T. (2013) Recurrent insectoutbreaks caused by temperature-driven changes in system stability.Science, 341, 796–799.

Pasqualini, E. & Natale, D. (1999) Zeuzera pyrina and Cossus cossus(Lepidoptera, Cossidae) control by pheromones: four years advancesin Italy. Bulletin OILB/SROP, 22, 115–124.

Pasqualini, E., Antropoli, A. & Faccioli, B. (1992) Attractant perfor-mance of a synthetic sex pheromone for Zeuzera pyrina L. (Lep.,Cossidae). Bollettino dell’Istituto di Entomologia ‘Guido Grandi’della Universita degli Studi di Bologna, 46, 101–108.

Rossiter, M. C. (1992) The impact of resource variation on pop-ulation quality in herbivorous insects: a critical aspect of pop-ulation dynamics. Effects of Resource Distribution on Animal–

Plant Interactions (ed. by M. D. Hunter, T. Ohgushi and P. W. Price),pp. 13–42. Academic Press, San Diego, California.

Sadok, I.B., Celton, J.-M., Essalouh, L. et al. (2013) QTL mapping offlowering and fruiting traits in olive. PLoS One, 8, e62831.

SAS (2000) SAS/STAT User’s Guide. SAS Institute, Cary, North Car-olina.

Schultz, J.C. & Baldwin, I.T. (1982) Oak leaf quality declines in responseto defoliation by gypsy moth larvae. Science, 217, 149–151.

Seyyednejad, M., Ebrahimzadeh, H. & Talaie, A. (2001) Carbohydratecontent in olive Zard cv and alternate bearing pattern. InternationalSugar Journal, 103, 84–87.

Steinbauer, M.J. (2003) Using ultra-violet light traps to monitor autumngum moth, Mnesampela privata (Lepidoptera: Geometridae), insouth-eastern Australia. Australian Forestry, 66, 279–286.

Szabo, S., Arnyas, E., Tothmeresz, B. & Varga, Z. (2007) Long-term lighttrap study on the macro-moth (Lepidoptera: Macroheterocera) faunaof the Aggtelek National Park. Acta Zoologica Academiae ScientiarumHungaricae, 53, 257–269.

Teetes, G.L. (1994) Adjusting crop management recommendations forinsect-resistant crop varieties. Journal of Agricultural Entomology, 11,191–200.

Tonini, C., Cassani, G., Massardo, P., Guglielmetti, G. & Castellari,P. (1986) Study of female sex pheromone of leopard moth, Zeuzerapyrina L. Isolation and identification of three components. Journal ofChemical Ecology, 12, 1545–1558.

Turchin, P. (2013) Complex Population Dynamics: A Theoreti-cal/Empirical Synthesis. Princeton University Press, Princeton,New Jersey.

Turktas, M., Inal, B., Okay, S. et al. (2013) Nutrition metabolism plays animportant role in the alternate bearing of the olive tree (Olea europaeaL.). PLoS One, 8, e59876.

Walsh, P. J. (1990) Site factors, predators and pine beauty moth mortality.Population Dynamics of Forest Insects (ed. by A. Watt, S. Leather, M.Hunter and N. Kidd), pp. 245-252. Intercept, Andover, Massachusetts.

Yaffee, R.A. & McGee, M. (2000) An Introduction to Time SeriesAnalysis and Forecasting: with Applications of SAS® and SPSS®.Academic Press, San Diego, California.

Yanik, H., Turktas, M., Dundar, E., Hernandez, P., Dorado, G. & Unver,T. (2013) Genome-wide identification of alternate bearing-associatedmicroRNAs (miRNAs) in olive (Olea europaea L.). BMC PlantBiology, 13, 10.

Zhang, Q.H. & Schlyter, F. (2003) Redundancy, synergism and activeinhibitory range of non-host volatiles in reducing pheromone attrac-tion of European spruce bark beetle Ips typographus. Oikos, 101,299–310.

Accepted 10 May 2014

© 2014 The Royal Entomological Society, Agricultural and Forest Entomology, doi: 10.1111/afe.12075

All in-text references underlined in blue are linked to publications on ResearchGate, letting you access and read them immediately.