jear2012 Abstract The paper deals with the development, parametrization and validation of a phenology model of the overwintering process of European grapevine moth Lobesia botrana (Denis & Schiffermüller) populations in northern latitudes. The model is built on diapause and poikilothermic population development theories and represents the phenological events of entries into and emergence from pre-diapause, diapause and post-diapause phases. The rate sum models for pre-diapause and post-diapause devel- opment are based on published non-linear temperature dependent rate functions. The rate sum model for diapause, however, is negatively affected by the photoperiod during diapause and positively influenced by the photoperiod at the time of diapause entry. The diapause model is parametrized with 3-year data from 25 locations in Europe and Cyprus, and validated with 1-3 year observations from 18 locations in Europe and California. Despite restrictive assumptions and limitations imposed by weather data recorded at variable distances from the observation sites, and the variable qualities of observation data, the model’s predictive and explanatory capabilities are useful for adaptive pest management and assessments of the invasive potential. The need for controlled experi- ments is recognized and suggestions are made for improving the model. Introduction The polyphagous European grapevine moth [Lobesia botrana (Denis & Schiffermüller): Tortricidae] is found in Southern Russia, Japan, the Middle East, the near East, and Northern and Western Africa, and the Mediterranean Basin where it is considered the most important pest of grapes (Savopoulou-Soultani et al., 1990; Venette et al., 2003; Frolov and Saulich, 2005; Thiéry and Moreau, 2005; De Yong, 2010). In 2009, L. botrana was discovered in Napa County, California (Varela et al., 2010), and in their prospective analysis of the invasive potential in California, Gutierrez et al. (2012) use the extensive European experi- mental and modeling literature. However, most of these studies focused on population development during the grape growing season and only a few dealt with aspects of diapause during overwintering (Kharazinov et al., 1980; Tzanakakis et al., 1988; Roditakis and Karandinos, 2001; Andreadis et al., 2005). Annual cycles in resources and unfavorable conditions characterize virtually all biological environments, and according to Nechols et al. (1999), insects have developed a set of adaptations that leads to appro- priate timing of recurring events in their life cycles. Among them is diapause which is a hormonally mediated state of low metabolic activ- ity associated with reduced morphogenesis, increased resistance to environmental extremes, and altered or reduced behavioral activity. Diapausing stimuli are perceived only during species-specific, geneti- cally determined life stages in response to token environmental cues that precede unfavorable conditions. The life stages with diapause in the life cycle may be different from those responding to diapausing stimuli. Photoperiod and temperature are the most important stimuli. Diapause development is mainly, but not exclusively, controlled by a combination of temperature and photoperiod (Tauber and Tauber, 1976; Tauber et al. 1986; Nechols et al., 1999). According to Leather et al. (1993), one of the major functions of temperature is to maintain the condition by acting as a regulatory factor on the rate of diapause development. In many species, the temperature range over which dia- pause development occurs is different from that for non-diapause development; in such insects, the low optimum temperatures for dia- pause development ensure that warm autumn conditions do not result in the resumption of development. According to Leather et al. (1993), the length of day at the time of induction has no effect on the mainte- nance or termination of diapause in many insects, while in others the Correspondence: Johann Baumgärtner, Dipartimento di Protezione dei Sistemi Agroalimentare e Urbano e Valorizzazione delle Biodiversità (Di.P.S.A.), Università degli Studi di Milano, via G. Celoria 2, 20133, Milano, Italy. E-mail: j.baumgaertner@bluewin.ch Key words: Lobesia botrana phenology, pre-diapause, diapause, post-dia- pause, rate sum model, first flight. Acknowledgments: are grateful to all colleagues listed in the text for provid- ing information on the first flight and for critically reviewing an initial draft of the paper. We are also grateful to an unknown reviewer for corrections and suggestions that clarified the paper. Received for publication: 2 March 2012. Revision received: 23 March 2012. Accepted for publication: 27 March 2012. ©Copyright J. Baumgärtner et al., 2012 Licensee PAGEPress, Italy Journal of Entomological and Acarological Research 2012; 44:e2 doi:10.4081/jear.2012.e2 This article is distributed under the terms of the Creative Commons Attribution Noncommercial License (by-nc 3.0) which permits any noncom- mercial use, distribution, and reproduction in any medium, provided the orig- inal author(s) and source are credited. A model for the overwintering process of European grapevine moth Lobesia botrana (Denis & Schiffermüller) (Lepidoptera, Tortricidae) populations J. Baumgärtner,1 A.P. Gutierrez,2,3 S. Pesolillo,4 M. Severini4 1Dipartimento di Protezione dei Sistemi Agroalimentare e Urbano e Valorizzazione delle Biodiversità (Di.P.S.A.), Università degli Studi di Milano, Italy; 2Division of Ecosystem Science, University of California, Berkeley, CA, USA; 3Centre for the Analysis of Sustainable Agricultural Systems (CASAS), Kensington, CA, USA; 4Università della Tuscia, Viterbo, Italy [page 8] [Journal of Entomological and Acarological Research 2012; 44:e2] Journal of Entomological and Acarological Research 2012; volume 44:e2 No n- co mm er cia l u se on ly conditions prevailing at this point have been shown to affect the dura- tion of the diapause period. Many insects appear to have evolved to take advantage of the seasonal progression of photoperiods during winter, and diapause development often involves responses to a series of pho- toperiods that exert their influence as diapause proceeds rather than to a single critical photoperiod (Tauber et al., 1986; Leather et al., 1993). The study is a phenology model for overwintering of L. botrana popula- tions across a wide geographical range where the pest may occur. Phenology deals with the timing of recurring biological events, the caus- es of their timing with regard to biotic and abiotic forces, and the interre- lation among phases of the same or different species (Lieth, 1976). The model should have satisfactory predictive and explanatory capabilities and be useful for further developing the population model (e.g. Gutierrez et al. 2012) by explicitly dealing with overwintering in a wide range of lat- itudes. Model development, parametrization and validation rely on the efficient use of available information within the conceptual framework provided by the theory of diapause (Leather et al., 1993; Nechols et al., 1999) and the rate sum approach to poikilothermic development formal- ized by Stinner et al. (1974) and Curry and Feldman (1987). Materials and methods Model description and initialization Overwintering process The L. botrana overwintering model starts with diapause induction and represents the development through pre-diapause (j=1), dia- pause (j=2) and post-diapause (j=3) phases that eventually lead to the emergence and the flight of the adults (Figure 1). With a decrease in the length of day during late summer and fall, eggs and larvae respond increasingly to photoperiod and enter the pre-diapause phase. Newly formed pupae pass first through diapause followed by a post-diapause phase (Gutierrez et al., 2012). Of particular interest in this paper are the first individuals (labeled with subscript b) and the last individuals (labeled with subscript e) stimulated to enter the win- ter diapause on days Db and De, respectively (i.e. cohorts 1 and 2). As poikilotherms, they develop at temperature-dependent rates. In late summer and fall, both cohorts become overwintering diapause pupae on day DTb and DTe with diapause terminated on days DPb and DPe, respectively. After passing through the post-diapause phase, the two cohorts emerge as adults on days DFb and DFe, respectively. Also of interest is the size of the cohorts entering the pre-diapause phase during the period DDb-DDe as these produce the flight patterns of adults during the DFb-DFe period. Diapause induction Riedl (1983) published data on life cycle of Cydiapomonella that showed a linear dependence of the critical length of day (DLc) of dia- pause initiation on latitude L measured in decimal degrees in California. Specifically, DLc for 50% of the larvae entering diapause is: DLc = 10.242 + 0.1226 L (1) Roditakis and Karandinos (2001) working at Heraklion with a local L. botrana population showed that the diapause depends on length of day (DL). Gutierrez et al. (2012) obtained DL values for the beginning and the ending of the diapause induction (DLb = 14.15 h, and DLe = 11.98 h). Assuming that Riedl’s (1983) equation can also be applied to L. botrana overwintering at different latitudes (L), the length of day for the beginning and the ending of diapause entry (DLb, DLe) is: DLb = Ab + Bb · L DLe = Ae + Be · L (2) To apply (2) to the Roditakis and Karandinos (2001) data, we have a system of two equations with four unknowns (Ab, Bb, Ae, Be). In order to solve the system, we assume from Riedl (1983) that Bb = Be = 0.1226. Now, we are able to calculate the numerical values Ab = 9.83 and Ae = 7.66 and obtain two equations for determining the lengths of day (DLb, DLe) at the beginning and the ending of diapause induction: DLb = 9.83 + 0.1226 · L DLe = 7.66 + 0.1226 · L (3) Once these latitude-dependent day lengths are known, the method of Glarner (2010) can be used to calculate the dates DDb and DDe, i.e. the latitude-specific Julian days on that cohort 1 (DDb) and cohort 2 (DDe) enter pre-diapause development. [Journal of Entomological and Acarological Research 2012; 44:e2] [page 9] Article Figure 1. The overwintering phases of L. botrana (pre-diapause, diapause, and post-diapause) for cohorts 1 and 2 responding to length of day on days DDb and DDe, entering diapause on days DTb and DTe, terminating diapause on days DPb and DPe and emerging as adults on days DFb and DFe. No n- co mm er cia l u se on ly [page 10] [Journal of Entomological and Acarological Research 2012; 44:e2] Overwintering model Stinner et al. (1974) and Curry and Feldman (1987) represent the duration Dj of a life stage j by the sum rsj of daily rates rj(D): (4) and state that the stage j is completed once the sum reaches unity (rsj(Dj)=1). For poikilotherms, the developmental rates depend on daily temperatures where rj(D)=rj(TD) where rj(TD) is called rate function of the j-th stage. Knowledge of the beginning of phase j, the temperature profile during phase j, and the rate function rj(TD) allows the emergence on day Dj to be predicted. Here, this model is applied to the three overwintering phases of L. botrana (Figure 1) and different rate functions are used as if these phases were life-stages. In addition, hourly (TnD) rather than daily temperatures are calculated. For n=24, the rate sum for the pre-dia- pause (j=1) and post-djapause (j=3) phase becomes: (5) For diapausing pupae, however, the development rate, summed up over 24 time increments per day, is modified by photoperiodic effects and the rate sum for the diapause phase (j=2) becomes: (6) where P0 = photoperiod at the time of entry into diapause (DTb, DTe), PD= photoperiod on the D-th day, a and b = constants. As to the ana- lytical form of rj(TnD) in eqs. 2 and 3, Gutierrez et al. (2012) used a modified form of the Brière and Pracros (1998) model to represent Article Table 1. Overwintering model for L. botrana: data set used for parameter estimation. DDb and DDe are the calculated beginnings and endings of the entry into the pre-diapause phase; DFb and DFe are the observed beginnings and endings of the first flight; the temper- atures for the different weather stations are from Yang et al. (2010). Region Location DDb, DDe Flight data Source with latitude year, station (DFb – DDe) Sachsen (D) 1 Dresden-Radebeul/Coswig 203, 237 18.04-22.05 Mrs. E. Harbrecht 51°06’40” 2007-2009 07.05-18.06 Sächsisches Landesamt für Umwelt, Altenburg-Nobitz* 12.05-22.06 Landwirtschaft und Geologie 2 Dresden-Pillnitz 203, 237 16.05-23.06 D - 01326 Dresden-Pillnitz 51°00’31” 2003-2005 28.04-16.06 Altenburg- Nobitz* 12.05-22.06 Rheinland-Pfalz (D) 3 Ahr 202, 237 09.05-11.06 Mr. Fr.-J. Treis 50°27’53” 2001-2003 26.04-03.06 Dienstleistungszentrum Ländlicher Raum, Mendig* 17.04-08.05 D - 54470 Bernkastel-Kues 4 Bernkastel 202, 238 10.05-22.06 49°54’40” 2001-2003 24.04-03.06 Hahn* 17.04-26.05 5 Piesport 202, 238 28.04-01.06 49°52’44” 2004-2006 01.05-02.06 Hahn* 05.05-11.06 Franken (D) 6 Altmannsdorf 202, 238 29.04-10.05 http://www.lwg.bayern.de/weinbau/ (Sonnenwinkel) 2003-2005 03.05-30.05 rebschutz_lebensraum_weinberg/34270/ 49°56’10” Giebelstadt* 04.05-29.05 7 Castell (Kirchberg) 200, 238 24.04-27.05 49°44’34” 2002-2004 23.04-30.05 Illesheim* 03.05-31.05 Bratislava (SK) 8 Modra-Horné 200, 239 15.04-24.06 Gabel and Mocko (1984) 48°20’34” 1978-1980 29.04-24.06 Bratislava* 23.04-25.06 North- and 9 Wädenswil 199, 241 21.04-18.06 Dr. H. Hoehn, Southeastern 47°13’36” 2000-2002 30.04-08.06 AGROSCOPE, Switzerland (CH) Wädenswil° 10.04-10.06 CH - 8820 Wädenswil 10 Maienfeld (Malans) 199, 241 30.04-07.06 47°01’28” 2001-2003 24.04-01.06 Chur 28.04-01.06 Southern 11 Carasso 198, 242 04.04-07.05 Dr. M. Jermini, AGROSCOPE, Centro di Ricerca Switzerland (CH) 46°12’15” 2007-2009 23.04-16.05 di Cadenazzo,CH - 6594 Contone Mr. L. Colombi, Magadino 13.04-22.05 Servizio fitosanitario cantonale CH - 6500 Bellinzona 12 Mezzana 198, 242 12.04-09.05 45°51’11” 2007-2009 23.04-19.05 Lugano 17.04-07.05 *Temperatures corrected for altitude; °if not available, data from Zurich. No n- co mm er cia l u se on ly the developmental rates of eggs and larvae combined, and of non-dia- pausing pupae. The same model is applied here for simulating the three overwintering phases: (7) TnD indicates the ambient hourly temperature, and jTl and jTu are the phase-specific lower and upper temperature thresholds, respec- tively, αj and βj are phase-specific constants, and ξj is a factor chang- ing the developmental rate of the combined egg and larval develop- ment (Gutierrez et al., 2012) into the pre-diapause phase. The factor ξj is applied to phase j=1 and set to 1 for j≠1. Model parametrization Information available The beginning (DFb) and the end (DFe) of the first flight at 25 dif- ferent locations in Europe and Cyprus were provided by extension services personnel, retrieved from the internet or obtained from the scientific literature (Tables 1 and 2). The information consisted of verbal and written communications, published tables or graphics. All the latitudes were obtained from www.google.com using information provided by the data sources. When available, observations over three consecutive years were used (Tables 1 and 2). For the overwintering periods of the two cohorts (i.e. DDb, DDe), daily maximum and minimum temperature from nearby weather sta- tions were retrieved from Yang et al. (2010). The cosine intrapolation [Journal of Entomological and Acarological Research 2012; 44:e2] [page 11] Article Table 2. Overwintering model for L. botrana: data set used for parameter estimation. DDb and DDe are the calculated beginnings and endings of the entry into the pre-diapause phase; DFb and DFe are observed dates of the beginning and endings of the first flight; the temperatures for the different weather stations are from Yang et al. (2010). Region Location DDb, DDe Flight data Source with latitude years, station (DFb – DDe) Emilia-Romagna (I) 13 Carpi 197, 244 06.04-06.05 Dr. Alda Butturini, Dr. T. Rocco, 44°46’59” 2007-2009 12.04-14.05 Servizio fitosanitario regionale, Parma° 08.04-16.05 I - 40127 Bologna 14 San Lodovico di Rio Saliceto 197, 244 08.04-16.05 44°47’59” 2007-2009 06.04-28.05 Parma° 09.04-19.05 Aquitaine (F) 15 Villenave d’Ornon 197, 244 03.04-n.a. Delbac (2010) 44°46’20” 2007-2009 09.04-n.a. Agen 06.04-n.a. Puglia (I) 16 Ruvo 197, 250 09.04-23.05 Moleas (1979) 41°07’06’’ 1976-1978 05.04-18.04 Bari* 09.04-23.05 Ribatejo (P) 17 Lezirão 198, 255 28.03-26.04 Gonçalves (1989) 39°14’10” 1985-1987 20.03-24.05 Lisboa 27.03-20.05 Extremadura (E) 18 San Servàn 198, 256 28.03-28.05 Martín-Vertedor et al. (2010) 38°48’06” 2006, 2007 28.03-30.05 Badajoz* Attiki (GR) 19 Spata 199, 258 29.03-n.a. Moschos et al. (2004) 37°57’44” 1996-1998 05.04-n.a. Lamia* 28.03-n.a. Western and 20 Marsala 199, 258 02.05-21.05 Prof. Gaetano Siscaro, University of Catania I - 95123 Catania Central Sicily (I) 37°47’57” 2008-2010 11.04-07.05 Dr. Luigi Neri, Assessorato Regionale delle Trapani n.a.-03.06 Risorse Agricole e Alimentari I - 93013 Mazzarino 21 Mazzarino 199, 260 05.05-29.05 37°18’20” 2008-2010 18.04-29.05 Enna* 25.04-19.05 Southeastern Sicily (I) 22 Ispica 200, 261 23.04-26.04 36°47’08” 2008-2010 29.04-22.05 Gela* 26.04-21.05 23 Licata 199, 263 16.05-30.06 37°06’08” 2008-2010 21.04-18.05 Gela 11.05-28.05 Andalucia (E) 24 Jerez 200, 261 12.03-01.04 Del Tio et al. (2001) 36°41’12” 1990-1992 27.03-01.05 Jerez# 07.03-28.04 Vassilis (2009) Limassol (CY) 25 Pissouri 203, 268 14.03-9.05 34°40’00” 2005-2006 22.03-3.05 Larrnaca* *Temperatures corrected for altitude; °if not available, data from Bologna; #temperature 1989. Available from: http://www.tutiempo.net/en/Climate/Jerez_de_la_Frontera_aeropuerto/84510.htm No n- co mm er cia l u se on ly [page 12] [Journal of Entomological and Acarological Research 2012; 44:e2] method of Bianchi et al. (1990) was used to compute hourly tempera- tures. At some locations (Tables 1 and 2), temperature differences between phenological observation sites and corresponding weather stations were corrected for altitude using an environmental lapse rate of 0.7°C per 100 m, as used by the International Civil Aviation Organization (Aguado and Burt, 2007). Development of larvae stimulated to become diapause pupae Based on twice weekly data, Gutierrez et al. (2012) estimated that cohorts (e.g. DDb) completed 5/6 of the combined egg and larval devel- opment at the time of entry into diapause (DTb), and are presumed to emerge as the first adults on day DFb (Figure 1). The same pattern is assumed for other cohorts during the period (DDbDDe) (Figure 1). This assumption is made because during fall, eggs and young larvae are unlikely to survive pre-diapause development. Estimates of DFb and DFe, and on the duration of post-diapause development allows the calculation of DTb and DTe. Values for the parameters for the rate sum functions of pre-diapause and post-diapause phase obtained from Gutierrez et al. (2012) are listed in Table 3. Diapause development The values for βj are given by Gutierrez et al. (2012), while the Article Table 3. Developmental rate parameter estimates for the model on overwintering L. botrana. Parameter Overwintering phases Pre-diapause diapause Post-diapause (mature larvae)* (j=1) (pupae) (j=2) (pupae)* (j=3) α�j 0.00225 3.02579E-04 0.00785 β�j 5 1.5 4.5 jTl 8.9 7.1 11.5 jTu 33.0 28.5 33.0 ξ j 6.0 1.0 1.0 a n.a. -3.0258E-06 n.a. b n.a. 2.42064E-04 n.a. *Parameters provided by Gutierrez et al. (2012); αj, βj and ξj are constants of the basic rate sum function; jTl, jTu are lower and upper temperature thresholds; a and b are constants for the linear latitude correc- tion; n.a., not applicable. Table 4. Overwintering model for L. botrana: data set used for validation purposes. Predictions of the beginning and the ending of the first flight. DDb and DDe are the calculated beginnings and endings of the entry into pre-diapause; DFb and DFe are the observed begin- nings and endings of the first flight; the temperatures for the different weather stations were obtained from Yang et al. (2010). Region Location DDb, DDe Flight data Source with latitude year, station (DFb – DDe) Franken (D) 26 Hammelburg 202, 238 9.05-30.05 http://www.lwg.bayern.de/weinbau/ 50°06’55” 2005 rebschutz_lebensraum_weinberg/34270/ Giebelstadt* Rheingau (D) 27 Eltville 202, 238 17.04° Reineke (2008) 50°01’30” 2008 Zweibrücken Burgenland (A) 28 Rust 200, 240 28.04-15.05 Polesny et al.(2000) 47°48’09” 1998 Eisenstadt Moldava (R) 29 Iaşi 199, 241 13.05-08.06 Cazacu et al. (2009) 47°09’25” 2007 Iaşi Western Switzerland (CH) 30 Begnins 198, 242 9.04-20.06 Charmillot et al. (1998) 46°26’31” 1997 Genève* 31 Venthône* 198, 242 2.04-15.06 46°18’23” 1997 Sion* Valtellina (I) 32 Albosaggia 198, 242 19.04-22.05 Pavese (1996) 46°08’55” 1995 Sondrio* Piemonte (I) 33 Ghemme 198, 243 8.05-29.05 45°36’03” 1995 Novara* Veneto (I) 34 Colli goriziano 198, 242 9.05-2.06 Zangheri et al. (1987) 45°57’04” 1980 Ronchi dei Legionari* *Temperatures corrected for altitudes; °only beginning of the first flight. No n- co mm er cia l u se on ly parameters αj, jTl, jTu, a, b were estimated by simulating the overwin- tering process for the two cohorts at all the locations and years given in Tables 1 and 2. The values for the parameters αj, βj, jTl, jTu a and b are obtained as follows. For varying parameter values, the diapause model, applied to the calculated diapause duration at the different locations (Tables 1 and 2) for the two cohorts, yielded different mean rate sums with associated variances. The parameter values producing the smallest coefficient of variation were accepted as model parame- ter estimates. Model validation The intended use of the model has improved understanding of the overwintering process for use in pest emergence forecasting (Rykiel, 1996). Implicitly, the models representing pre-diapause and post-dia- pause development have been examined by Gutierrez et al. (2012), allowing us to focus here on the diapause process. For model valida- tion, we make use of information on DFb and DFe at 17 different loca- tions in Europe and one location in California (Tables 4 and 5) and calculate the observed date of diapause termination by means of the post-diapause function described by Gutierrez et al. (2012). As in the aforementioned case of model parametrization, the information was provided by extension services personnel, retrieved from the Internet or obtained from the scientific literature. Likewise, an altitude- dependent correction of some data was carried out. Results The location-specific days for the beginning (DDb) and the end (DDe) of diapause induction are reported in Tables 1, 2, 4 and 5. Across the latitudes, the earliest entries occur during a small time period delimitated by the central location 40 (DDb=196) and both the northernmost and southernmost locations (DDb=203). The latest entries occur in a longer period extending from the northernmost locations (DDe= 237) to the southernmost location (DDe= 268). Table 3 lists the parameters for the overwintering model. The model for pre-diapause development (j=1) predicts the entry into diapause after about 1-3 weeks after DDb and DDe at all 18 loca- tions, depending on temperature (eq. 3). According to Figure 2, dia- pause is terminated in cohort 1 on December 21 at location 42 in Sicily and on February 23 at location 27 in Germany’s Rheingau. Cohort 2 terminates diapause between March 19 at location 39 in Portugal and on May 27 at location 29 in Romania. Hence, for cohort 1, the earliest and latest dates of diapause termination are in the southernmost and northernmost regions under study. However, the corresponding extreme dates for diapause termination in cohort 2 are in the westernmost and easternmost European regions under study. Figure 2 shows the predicted and observed dates for diapause ter- mination at the 18 locations listed in Tables 4 and 5. The average dif- ference between the predicted and the observed diapause duration is [Journal of Entomological and Acarological Research 2012; 44:e2] [page 13] Article Table 5. Overwintering model for L. botrana: data set used for validation purposes. Predictions of the beginning and the ending of the first flight. DDb and DDe are the calculated beginnings and endings of the entry into pre-diapause; DFb and DFe are the observed begin- nings and endings of the first flight; the temperatures for the different weather stations were obtained from Yang et al. (2010). Region Location DDb, DDe Flight data Source with latitude year, station (DFb – DDe) Aquitaine(F) 35 Dordogne 198, 243 8.04-1.06 Maille (2010) 45°08’49” 2009 Bergerac Acquitaine (F) 36 Pessac 196, 243 28.04-9.06 Fargeas (2005) 44°48’14” 2005 Bordeaux Aquitaine (F) 37 Pont de la Maye 197, 244 18.04-6.06 Roehrich et al. (1976) 44°46’51” 1974 Bordeaux Lazio (I) 38 Cerveteri 197, 249 7.05-2.06 Cafarelli and Di Cicco (1983) 41°59’38” 1981 Roma* Northwestern 39 Arcos de Valdevez 197, 249 20.03-8.05 Agular et al. (2008) Portugal (P) 41°50’50” 1999 Pedras rubras* Macedonia (GR) 40 Kavala 197, 251 20.04-01.06 Stavraki et al (1987) 40°56’12” 1985 Bitola* (MK) California (USA) 41 Napa 198, 257 19.02.-30.05 Gutierrez et al. (2012) 38°18’17” 2009 Napa Sicily (I) 42 Camporeale 199, 258 30.04-26.05 Prof. Gaetano Siscaro 37°53’67” 2010 University of Catania I - 95123 Catania Palermo* Dr. Luigi Neri Assessorato Regionale delle Risorse Agricole e Alimentari I - 93013 Mazzarino 43 Noto 200, 261 26.04-21.05 36°53’30” 2010 Gela* *Temperatures corrected for altitudes. No n- co mm er cia l u se on ly [page 14] [Journal of Entomological and Acarological Research 2012; 44:e2] 8.3 days for cohort 1 and 21.4 days for cohort 2, respectively. If the observation on day 45 is disregarded, the average difference among the data for cohort 1 is only 6.8 days. Accordingly, eq. 3 is better able to predict diapause development in cohort 1 than in cohort 2. In gen- eral, the predicted number of days for cohort 1 are slightly higher than the observed number of days, while the corresponding numbers of days for cohort 2 are scattered around the line of correspondence (Figure 2). Discussion The model is based on the diapause theory which states that devel- opment is mainly but not exclusively controlled by a combination of temperature and photoperiod (Tauber and Tauber, 1976; Tauber et al. 1986; Nechols et al., 1999). Driven by photoperiod and temperature, the model satisfactorily predicts the overwintering of L. botrana under the conditions considered in this study. Since satisfactory fore- casting on solid theoretical grounds is possible, the model exhibits adequate predictive and explanatory capacities. The favorable qualification of the model is possible in spite of short- comings in the data used for model parametrization and validation. First, model development relied primarily on information on the begin- nings and the endings of the first flight recorded by pheromone traps. The quality of this information, however, is limited, since pheromone trap catches are negatively affected by adverse weather conditions. Pheromone trap catches represent activities of males and may, there- fore, provide more reliable information on flight beginnings than end- ings. To some extent, this may explain the difference between the qual- ity of the predictions for cohort 1 and cohort 2 (Figure 2). Moreover, the pheromone traps were deployed for supervised pest management rather than research purposes and hence, the observations focused on specific periods rather than on the entire flight period. In many cases, the time resolution of the observations was imprecise making it diffi- cult to estimate the beginning and the end of flights. Since vineyards are generally set up in environments favorable for grape production, we assume that the temperature experienced by L. botrana is higher than those recorded even after the altitude correction. The quality of the temperature data is further limited by the variable distances between the weather stations and vineyards being monitored. The correction of temperatures is particularly important since it may influence the tem- perature range for diapause development discussed below. Biased tem- perature data may also explain the deviation of location 42 from the line of corresponding observations and predictions in Figure 2. Furthermore, the effects of adverse weather on flight activities, the quality of observations and the difference between vineyard and weath- er station temperatures may have varied through time. This would also jelp explain the difference in the quality of the predictions for the flights of the two cohorts (Figure 2). The model has been developed on the basis of restrictive, albeit plausible assumptions. First, we assumed that the response seen in C. pomonella to latitude (Riedl, 1983) can be used as a model for L. botrana. Next, we assumed that both cohorts consist exclusively of mature larvae that do not suffer from overwintering mortality and successfully pass the pre-diapause, diapause and post-diapause phas- es. To be able to use the information available for modeling the pop- ulation phenology, we had to assume that male trap catches were related to population densities. Finally, the model for diapause devel- opment assumes only additive effects of temperature and photoperi- ods and disregards possible interactions. The northernmost and southernmost locations considered for model parametrization and validation are Dresden-Radebeul/Coswig at 51°06’40” and Pissouri at 34°40’00” (Tables 1 and 2). The former location may be at the limit of the distribution in the north (Frolov and Saulich, 2005; De Yong, 2010). Portuguese locations in the West and Cypriot locations in the East further delimitate the palaearctic area providing information for model parametrization and validation. The literature suggests, however, that the explicit consideration of other environmental factors may be needed when dealing with loca- tions outside this area. For example, the distribution in the Palaearctics extends further to the south and towards desert environ- ments than taken into account in this paper (Al-Zyoud and Elmosa, 2001; El-Wakeil et al., 2009). For these areas, it may be necessary to build the effect of relative humidity explicitly into the overwintering model. In Israel, Rakefet et al. (2009) reported a significant effect of cultivars on the numbers of trapped males and a cultivar effect on female host choice. In this case, the explicit consideration of host plant effects may be necessary for obtaining satisfactory forecasts. Sciarretta et al. (2008) studied the spatial distribution of pheromone trap catches in Mediterranean landscape. Since a time-varying part of the population inhabits areas outside vineyards, an explicit consider- ation of a wide range of plant species and movements between vine- yards and their surroundings may improve predictive and explanato- ry model capabilities. The explanatory capabilities of the model allow us to tentatively assign L. botrana to an insect diapause type characterized by temperature and photoperiod influence on diapause development (Leather et al., 1993). In comparison to pre- and post-diapausing individuals (Table 3), the pattern of the diapause development rates occurs in a slightly lower temperature range (the lower threshold β2 is smaller than the thresholds β1 and β3, Table 3) and the temperature allowing fastest development is shifted towards lower temperatures. A shift of the temperature range for dia- pause development has been recorded for other insects and may prevent individuals from resuming development under warm autumn conditions (Nechols et al., 1999). The sensitivity to the photoperiod at the time of entry into diapause is known for other insects (Leather et al. 1993). To verify these assumptions, to study alternative models for representing photoperiodic and temperature influences, and to explicitly include other environmental factors and ascertain the shift in the temperature response curve, observations from other sites may be useful. To over- come the limitations of observation and temperature data, specific meas- urements should be to provide more reliable data for model development. Article Figure 2. Validation of the diapause model for L. botrana: observed and predicted days for diapause termination for the first (filled diamonds) and the last (empty triangles) cohort of pupae entering diapause at different geographical locations (the refer- ence day is 1 January, the 45 degree line represents correspon- dence between observed and predicted values, observed days’ refer to the dates obtained by subtracting post-diapause development from observations on the beginning and the end of the first flight). No n- co mm er cia l u se on ly More promising for model improvements, however, are experiments under controlled conditions, possibly complemented with gas exchange measurements (Kharizanov et al., 1980). In conclusion, the conceptual framework provided by diapause the- ory (Leather et al., 1993; Tauber and Tauber, 1976; Tauber et al., 1986; Nechols et al., 1999) and the rate sum approach to poikilothermic development formalized by Stinner et al. 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