Introduction
Noctuid moths are major pests of cotton and several other broad-acre crops worldwide (Reed & Pawar, Reference Reed, Pawar, Reed and Kumble1982). Transgenic cotton (Bt), which includes toxins derived from the bacterium, Bacillus thuringiensis, is commonly grown to help control these pests (Fitt, Reference Fitt2000; Shelton et al., Reference Shelton, Zhao and Roush2002; Cattaneo et al., Reference Cattaneo, Yafuso, Schmidt, Huang, Rahman, Olson, Ellers-Kirk, Orr, Marsh, Antilla, Dutilleul and Carrière2006). The vast majority of the cotton (Gossypium hirsutum L.) that is currently grown in eastern Australia includes Bt traits to reduce damage by two key pests, Helicoverpa armigera (Hübner) and Helicoverpa punctigera (Wallengren) (Lepidoptera: Noctuidae) (Downes & Mahon, Reference Downes and Mahon2012a , Reference Downes and Mahon b ; Cotton Australia, 2013; Maas, Reference Maas2014). Single Bt gene cotton (Ingard®, with Cry 1Ac toxin) was grown in Australia from 1996 to 2004, with a precautionary cap of 30% allowed within the total cotton production area at that time. Since 2005, two gene Bt cotton (Bollgard II®, with Cry1Ac and Cry2Ab) has been grown, with no area cap, such that approximately 90% of the cotton crop is based on such Bt cotton varieties. Three Bt gene cotton (Bollgard 3®, with Cry1Ac, Cry2Ab and VIP3A) is now planned for commercial release during the 2016/17 season (Downes & Mahon, Reference Downes and Mahon2012a , Reference Downes and Mahon b ). Bt cotton varieties provide major benefits for farmers, such as a significant reduction in insecticide spray applications to control H. armigera and H. punctigera (Fitt et al., Reference Fitt, Mares and Llewellyn1994; Fitt, Reference Fitt2000, Reference Fitt and Swanepoel2004, Reference Fitt, Romeis, Shelton and Kennedy2008). However, the development of Bt resistance in Helicoverpa is an ongoing major threat for the Australian cotton industry (Fitt, Reference Fitt2000; Fitt & Cotter, Reference Fitt, Cotter and Sharma2004; Downes et al., Reference Downes, Mahon and Olsen2007, Reference Downes, Parker and Mahon2009, Reference Downes, Mahon, Rossiter, Kauter, Leven, Fitt and Baker2010a , Reference Downes, Parker and Mahon b ; Mahon et al., Reference Mahon, Olsen, Garsia and Young2007, Reference Mahon, Downes and James2012), as it is elsewhere (Tabashnik et al., Reference Tabashnik, Gassmann, Crowder and Carrière2008, Reference Tabashnik, Van Rensburg and Carrière2009, Reference Tabashnik, Brévault and Carrière2013).
When Bt cotton was first deployed in Australia, most emphasis in Bt resistance management was focussed on H. armigera. This was because H. armigera, unlike H. punctigera, had a history of developing resistance to conventional pesticides (Zalucki et al., Reference Zalucki, Daglish, Firempong and Twine1986; Fitt, Reference Fitt1989, Reference Fitt2000; Forrester et al., Reference Forrester, Cahill, Bird and Layland1993). H. armigera over-winters in the cropping regions in eastern Australia (Wilson et al., Reference Wilson, Lewis and Cunningham1979; Fitt & Daly, Reference Fitt and Daly1990; Murray, Reference Murray1992) and was therefore considered more likely to be exposed to insecticides than the more migratory H. punctigera, which is thought to rarely over-winter there (Fitt, Reference Fitt1989; Fitt & Daly, Reference Fitt and Daly1990; Fitt & Cotter, Reference Fitt, Cotter and Sharma2004). H. punctigera has previously been believed to emigrate in large numbers in spring from inland Australia, to the eastern cropping regions (Zalucki et al., Reference Zalucki, Daglish, Firempong and Twine1986, Reference Zalucki, Gregg, Fitt, Murray, Twine and Jones1994, Reference Zalucki, Adamson and Furlong2009; Fitt, Reference Fitt1989; Fitt et al., Reference Fitt, Zalucki and Twine1989, Reference Fitt, Gregg, Zalucki and Twine1990; Gregg et al., Reference Gregg, Fitt, Zalucki, Murray, McDonald, Corey, Dall and Milne1993, Reference Gregg, Fitt, Zalucki, Murray, Drake and Gatehouse1995; Rochester et al., Reference Rochester, Dillon, Fitt and Zalucki1996; Fitt & Cotter, Reference Fitt, Cotter and Sharma2004; Zalucki & Furlong, Reference Zalucki and Furlong2005). Wet winters in the inland enable dense populations to develop on local native plants. Subsequent drying off of these host plants then stimulates migration. The reliable arrival of large numbers of Bt susceptible H. punctigera moths in the cropping regions in spring, originating from the inland where exposure to Bt would be minimal, was thought likely to limit the development of Bt resistance in the cropping regions that might otherwise arise from the relatively few individuals that survive there through winter carrying resistance alleles (Fitt, Reference Fitt and Kalaitzandonakes2003; Fitt & Cotter, Reference Fitt, Cotter and Sharma2004). However, unexpectedly high frequencies of Bt resistance alleles observed in H. punctigera in cropping regions in recent years (Downes et al., Reference Downes, Mahon, Rossiter, Kauter, Leven, Fitt and Baker2010a , Reference Downes, Parker and Mahon b ) and the lack of correlation between pheromone and light trap catches of H. punctigera moths in northern New South Wales with preceding winter weather patterns in inland Australia over a lengthy time period (1992–2002) (Baker et al., Reference Baker, Tann and Fitt2011) has questioned if our understanding of the ecology of this pest remains sound.
This paper reports the results of continuously monitoring the abundance of H. punctigera in pheromone traps for 23 years (1992–2015) within the same cotton (and other crop) production landscape in northern New South Wales, Australia, as used by Baker et al. (Reference Baker, Tann and Fitt2011). The study spanned the advent of both Ingard® and Bollgard II® cotton on this landscape. In particular, the work sought evidence of (1) the ongoing reliability of large scale arrivals of H. punctigera from inland Australia in spring, and (2) any broad-scale change in the abundance of H. punctigera that could be attributed to the use of Bt cotton. Whilst the pheromone traps used in the study were spread across a rural area approximately 10 km in radius, thus enabling landscape-scale appreciation of population changes in the moths, the habitats around individual traps varied. The latter thereby allowed evaluation of the influence of local habitat on trap catches as well. Pheromone traps were also set for H. armigera, at the same sites reported here for H. punctigera. Results for H. armigera will be published separately (Baker & Tann, Reference Baker and Tann2016).
Materials and methods
H. punctigera moths were caught using a grid of 7–14 Agrisense™ canister pheromone traps, which was maintained continuously within about a 10 km radius near the Australian Cotton Research Institute (ACRI), Narrabri, in northern New South Wales, Australia from July 1992 to June 2015 (fig. 1). The traps were usually emptied weekly, with occasional slight variations in timing due to inclement weather and resultant access difficulties. Lures, specific for H. punctigera, were changed monthly, and pesticide strips (dichlorvos) were changed bi-monthly. The traps were mounted on metal poles, approximately 1.5 m above the ground, and adjacent to agricultural fields. The traps only caught male moths. Trap sites were fixed, with the exception of Wire Lagoon/Merinda, which was shifted 500 m in 2010/11, because of ongoing access problems after heavy rainfall. From an initial 7 sites in 1992, the trapping effort was expanded to 9 sites in 1994, 11 sites by 1999, and a maximum of 14 sites by 2009. The trap at Lochelgin only operated for four seasons (1994–1998). Access problems also prevented its further use.
Fig. 1. Locations of the 15 pheromone trap sites near Narrabri, northern New South Wales. Main rivers (bold lines); roads (faint lines).
Previous work (Baker et al., Reference Baker, Tann and Fitt2011) compared the catches of H. punctigera moths, made over a decade, using pheromone and light traps in the vicinity of Narrabri. That work recognized a 1st generation of moths, which was caught between weeks 8–20 inclusive (weeks being counted from July 1), a 2nd generation caught between weeks 21–30, and 3rd+ generations caught between weeks 31–44. In general, we use the same temporal categorization of generations here, except where we highlight individual years and note variations from such a pattern. A somewhat similar recognition of these separate generations was also used for H. punctigera by Maelzer et al. (Reference Maelzer, Zalucki and Laughlin1996) and also H. armigera by Maelzer & Zalucki (Reference Maelzer and Zalucki1999). The 1st generation of moths must be mostly immigrants to the Namoi region; the majority are caught before local over-wintering pupae are due to emerge from the soil (Baker et al., Reference Baker, Leven, May and Tann2016).
The spring and summer crops, that were grown in the two fields nearest to each trap, were recorded each year. These crops mostly included cotton (Gossypium hirsutum L. – transgenic and conventional), soy bean (Glycine max Merr.), sorghum (Sorghum bicolor (L.)), wheat (Triticum aestivum L.) or wheat stubble, and chickpea (Cicer arietinum L.). Often, one or both of the fields was in fallow, which was also recorded. In many instances, the trapping sites were bordered, on one side, by land that was not used for cropping (referred to here as verge). Verge was recorded instead of crop if greater in area than the second nearest crop. Verge was variable in nature and included, for example, patches of native and weedy roadside vegetation.
Temporal trends in moth catches (1992–2015) were sought using data for (1) all the traps set throughout the study (thus local habitats varied between traps in space and time) and (2) where local habitat was the same for subsets of the traps being run. For the latter, we used data associated with fallow fields in spring and cotton fields in summer, because they were the most common land use at these times.
Rainfall and temperature data were sourced from the Australian Government's Bureau of Meteorology website (http://www.bom.gov.au). Rainfall data were used for Narrabri (Mollee) (meteorological station number 53026; 30°26′S149°68′E). Initially, temperature data were used for Narrabri at Narrabri West Post Office (station number 53030; 30°34′S149°76′E), but with the closure of that station in 2002, data were subsequently used from the Narrabri Airport (station number 54038; 30°32′S149°83′E). Rainfall data were also accessed for 36 additional recording stations in inland Australia (northern South Australia, southern Northern Territory, south-western Queensland and north-western New South Wales), as indicated in Baker et al. (Reference Baker, Tann and Fitt2011).
Data for the hectares sown to major crops that H. punctigera feeds on (cotton, chickpea and canola, Brassica spp.) in the Narrabri Statistical Local Area (SLA) (where the traps were set) throughout 1992–2014 were provided by Neil Clark Business Intelligence (Bendigo, Vic.).
Data analysis
Data were analyzed using statistical methods in Statistix® (Statistix 10, Analytical Software; Tallahassee, FL, USA). Methods included General One Way Analysis of Variance, Multiple and Linear Regression (with data transformed to log (x) or log (x + 1) where appropriate to stabilise variances in the highly variable data) and Pearson's Correlation Coefficient (r).
Results
Moth generations
Overall, the 1st generation of moths (caught between weeks 8 and 20) dominated the trap catches (fig. 2). At least one more generation (between weeks 21 and 30) was also vaguely discernible in the aggregated data (fig. 2). There was, however, much variability between individual years. In several years (e.g. 1993/94), only a 1st generation was discernible, in some other years (e.g. 1996/97) a 1st and 2nd generation were trapped, and very occasionally (e.g. 2009/10) three or more generations were apparent (fig. 3). 2013/14 was an unusual year, when three apparent generations were trapped, more or less in equal abundance, and the 3rd generation occurred earlier than expected, i.e. mostly before week 31 (fig. 4).
Fig. 2. Mean numbers of H. punctigera moths caught each week near Australian Cotton Research Institute (ACRI) throughout 1992–2015. Weeks are scored from July 1.
Fig. 3. Mean numbers of H. punctigera moths caught near Australian Cotton Research Institute (ACRI) in three separate time periods, (a) 1993/94, (b) 1996/97, and (c) 2009/10. Note the different scales used on the Y-axes.
Fig. 4. Mean numbers of H. punctigera moths caught near Australian Cotton Research Institute (ACRI) in 2013/14.
Trap catches in relation to local habitats
The most common habitats near the pheromone traps were fallow fields, wheat crops and verge during spring, and cotton crops, fallow fields and verge during summer (table 1). The incidence of these varied throughout the 23 years of the study (figs 5 and 6) and between sites, presumably reflecting, in the main, farmer decisions in response to weather patterns and market demands. Most notably, cotton was rare during 2007–2010 and 2014/15, reflecting a general scarcity of cotton plantings across the Australian cotton industry in those years (Dowling, Reference Dowling2015).
Fig. 5. Frequencies (%) of the most common habitat types adjacent to pheromone traps during spring each year throughout the trapping period near Australian Cotton Research Institute (ACRI).
Fig. 6. Frequencies (%) of the most common habitat types adjacent to pheromone traps during summer each year throughout the trapping period near Australian Cotton Research Institute (ACRI).
Table 1. Frequency scores for habitat types near trapping sites (2 scores for each site, for each of spring and summer, throughout 1992–2015).
The average numbers of H. punctigera moths caught in the pheromone traps set at the 15 separate sites varied markedly within each generation (table 2). However, some of these traps were set for more years than others. Including all such data in an analysis of variability between sites could create temporal bias. When we selected only those traps which were set for all, or very nearly all, years of the study (at least 20 of the 23 years; N = 8) (table 2) for analysis (One Way ANOVA), no significant differences in catch could be detected between trap sites for either 1st generation moths (F = 0.63, P > 0.05), 2nd generation moths (F = 1.12, P > 0.05), or 3rd+ generation moths (F = 1.40, P > 0.05), using total catch for each generation at each site in each season as the primary data (data transformed to log x for analysis).
Table 2. Trap site locations near Australian Cotton Research Institute (ACRI), numbers of years sampled and the mean numbers (±SE) of H. punctigera moths caught at each site each year in the 1st generation (weeks 8–20), 2nd generation (weeks 21–30) and 3rd+ generation (weeks 31–44).
Multiple regression analyses, using the data available for all 15 sites, demonstrated that the total numbers of 1st generation moths caught each spring decreased throughout the 23 years of study (table 3). More moths were caught when wheat or verge were present in at least one of the two fields adjacent to a trap. The presence of fallow had no effect. Large numbers of 1st generation moths were occasionally caught in the few traps in spring where chickpea was nearby (table 1) (up to 3365 in total in one trap in 2000, mean ± SE = 753.3 ± 319.2; this compares with 408.2 ± 55.8 for traps near wheat).
Table 3. Multiple regression outcomes from testing for relationships between total trap catches of 1st, 2nd and 3rd+ generations of H. punctigera moths and year, as well as concurrent presence of wheat, verge, fallow and cotton in at least one nearby field at Narrabri, New South Wales. Data transformed to log x + 1 for analysis.
Numbers in bold highlight significance. Slight variations in df reflect occasional faulty traps, which had to be ignored.
The numbers of 2nd generation moths caught in summer also decreased in time, with the presence of cotton in at least one field near traps having a negative effect on catch (table 3). The presence of neither fallow nor verge near traps influenced the catch of 2nd generation moths. Similarly, the catch of 3rd+ generation moths decreased in time, but no local influence of cotton, fallow or verge on catch was discernible (table 3). In addition, the average numbers of moths that were caught in the few traps in summer where sorghum and soybean were nearby (table 1) were 23.4 ± 9.1 and 6.7 ± 2.3, for 2nd and 3rd+ generations respectively for sorghum and 127.9 ± 50.8 and 42.6 ± 19.1, for 2nd and 3rd+ generations respectively for soybean. These data compare with the 120.4 ± 15.3 and 26.8 ± 3.4 for 2nd and 3rd+ generations respectively caught near cotton.
When these same data for moth catches were separated into subsets of the three cotton production eras, i.e. (1) Pre-Ingard® (1992–1996), (2) Ingard® (1996–2005) and (3) Bollgard II® (2005–2015), a relationship (negative) between moth numbers (2nd and 3rd+ generations) and the presence of cotton nearby could only be demonstrated through multiple regression (including year as a factor) during the Bollgard II® era (table 4; data for the other two eras not shown here).
Table 4. Multiple regression outcomes from testing for relationships between total trap catches of 2nd and 3rd+ generations of H. punctigera moths during the Bollgard II® era and year, as well as concurrent presence of cotton in at least one nearby field at Narrabri, New South Wales.
Data transformed to log x + 1 for analysis. Numbers in bold highlight significance.
Long-term changes in trap catches at larger scale
The average numbers of moths caught in the traps, irrespective of local habitat types, varied between years (fig. 7). For 1st generation moths (caught during weeks 8–20), One Way ANOVA F = 16.24, P < 0.0001; for 2nd generation moths (weeks 21–30), F = 41.05, P < 0.0001; and for 3rd+ generation moths (weeks 31–44), F = 15.71, P < 0.0001 (total collections of moths, at each trap site, within the prescribed time periods, taken as the primary data; data transformed to log x + 1 for analysis). As well as erratic variability between consecutive years, there was a general decline in numbers in time, in particular for 1st generation moths (Linear Regression: Mean catch of 1st generation = 14.99–0.70 × YEAR; R 2 = 0.320, F = 9.89, P < 0.005) (where average numbers of moths caught/trap/night, i.e. as depicted in fig. 7, were taken as the primary data, and years were taken as 1–23). However, there was no evidence to suggest a similar decline in the numbers of 2nd generation moths (Mean catch of 2nd generation = 1.66–0.02 × YEAR; R 2 = 0.004, F = 0.08, P > 0.05). For the 3rd+ generation, there was a significant decline in numbers over time (Mean catch of 3rd+ generation = 0.52–0.02 × YEAR; R 2 = 0.207, F = 5.47, P < 0.05), but given that 2013/14 was such an exceptional year, in which the 3rd generation occurred unusually early (fig. 4), it seems valid to recalculate the regressions omitting data for the 2nd and 3rd+ generations in that year. If so, there was still no temporal decline in catch for the 2nd generation, but very nearly so (Mean catch of 2nd generation = 2.12–0.08 × YEAR; R 2 = 0.164, F = 3.92, P = 0.06). A significant temporal decline remained in the catch of the 3rd+ generation (Mean catch of 3rd+ generation = 0.52–0.02 × YEAR; R 2 = 0.200, F = 5.01, P < 0.05).
Fig. 7. Pheromone trap catches of male H. punctigera moths near Australian Cotton Research Institute (ACRI) throughout 1992–2015. Data are separated into moths in the 1st generation (caught during weeks 8–20), 2nd generation (weeks 21–30) and 3rd+ generations (weeks 31–44), with weeks taken from 1 July. Ingard® cotton was commercially released in 1996/97; Bollgard II® cotton in 2005/06.
There was also a significant decrease in the number of 1st generation moths caught in traps set where fallow fields predominated in spring (n = 36 cases where the two nearby fields were both fallow) throughout the 23 years of study (Total catch of 1st generation = 2.93–0.05 × YEAR; R 2 = 0.16, F = 6.28, P < 0.05) (data transformed to log (x + 1) for analysis). However, no similar decrease in catch could be demonstrated for traps set near two cotton fields in summer (n = 24) (Total catch of 2nd generation = 2.16–0.03 × YEAR; R 2 = 0.10, F = 2.49, P > 0.05) (Total catch of 3rd+ generation = 1.58–0.04 × YEAR; R 2 = 0.15, F = 4.00, P = 0.06) (data also transformed to log (x + 1)).
In addition, there was no correlation between the average numbers of 1st and 2nd generation moths caught in the traps (Pearson r = 0.228, P > 0.05), nor between 2nd and 3rd+ generation moths (r = 0.181, P > 0.05), but there was between 1st and 3rd+ generation moths (r = 0.585, P < 0.005) (where data for all years and traps were included, but data for years were treated separately, thus N = 23). In contrast, there was no correlation between the average numbers of 1st and 2nd generation moths caught in the traps (r = 0.448, P > 0.05), but there was between 2nd and 3rd+ generation moths (r = 0.675, P < 0.01) and 1st and 3rd+ generation moths (r = 0.544, P < 0.05) (where data for all years and traps were again included, but data for sites were treated separately, thus N = 15). Thus analysing the data in a temporal context (across years) yielded a slightly different result than analysing it in a spatial context (across sites). There was also a significant correlation between the catch of 3rd+ generation moths in 1 year and the number of 1st generation moths in the next (r = 0.520, P < 0.05).
There were no significant associations, detected by multiple regression, between the catch of 1st generation moths (as per fig. 7) and the hectares of canola and chickpea grown in the Narrabri SLA (data analyzed along with year as an additional factor) (table 5). There were also no significant associations detected between the catch of 2nd generation moths and the hectares of canola, chickpea or cotton. However, there was a negative relationship between the catch of 3rd+ generation moths and the hectares of cotton grown (table 5).
Table 5. Multiple regression outcomes from testing for relationships between average trap catches of 1st, 2nd and 3rd+ generations of H. punctigera moths and year and annual total hectares of crops grown throughout the Narrabri Statistical Local Area from 1992 to 2014.
Numbers in bold highlight significance. Details for variables only provided where overall regression was significant.
The catches of 1st generation moths during both the Ingard® and Bollgard II® eras were lower than those during the preceding years when only conventional cotton was grown (One Way ANOVA, F = 7.30, P < 0.005; where annual averages of the numbers of moths caught/trap/night, i.e. as depicted in fig. 7, were taken as the primary data). Note, for this calculation, the catch for spring 1996 was included with the preceding conventional years and the catch for spring 2005 was included with the preceding Ingard® years, because 1st generation moths were caught prior to the sowing of cotton). Tukey's Comparison Test indicated no significant difference between the catches in the Ingard® and Bollgard II® eras. In contrast, there was no difference between catches of 2nd generation moths across the three cotton eras (F = 0.47, P > 0.05), but there was for the 3rd generation (F = 6.05, P < 0.01; differences between eras were as per 1st generation).
Rainfall varied greatly between years at Narrabri and was particularly high during the summers of 1996/97 and 2011/12 (fig. 8), but there were no significant associations, detected by multiple regression, between local rainfalls and average trap catches of 1st and 2nd generation moths each year (as per fig. 7), where rainfalls were calculated (as relevant for the particular moth generations) for the (1) preceding autumn (March–May inclusive), (2) preceding winter (June–August), (3) spring (September–November), (4) summer (December–February), and finally (5) autumn at the end of the cotton season (March and April)(1–3 deemed appropriate for 1st generation, 1–4 for 2nd generation and 1–5 for 3rd+ generation)(table 6). However, a significant, but weak, negative association was found between spring rainfall and the catch of 3rd+ generation moths (table 6). For all three generational groupings, rainfall variables were analyzed along with year as an additional factor.
Fig. 8. Rainfalls (mm) recorded at Narrabri (Mollee) (Australian Bureau of Meteorology Station No: 53026). Data are provided for the autumn (March, April, May) and winter (June, July, August) preceding the moth activity season, spring (September, October, November) at the start of the moth activity season, and summer (December, January, February) at the end of the activity season. On a few occasions, when data were not available for this meteorological station, equivalent data were used from records at Narrabri Airport (Station No: 54308).
Table 6. Multiple regression outcomes from testing for relationships between average trap catches of 1st, 2nd and 3rd+ generations of H. punctigera moths and year, total rainfall (mm) and average maximum temperature (°C) at Narrabri, New South Wales from 1992 to 2015.
MAMmm, preceding autumn rainfall; JJAmm, preceding winter rainfall; SONmm, preceding spring rainfall; DJFmm, prevailing summer rainfall; MAmm, prevailing autumn rainfall; MAM°C, preceding autumn temperature; JJA°C, preceding winter temperature; SON°C, preceding spring temperature; DJF°C, prevailing summer temperature; MA°C, prevailing autumn temperature.
Numbers in bold highlight significance. Details for variables only provided where overall regression was significant.
Air temperatures at Narrabri showed little variation across the two decades of observation. The most notable outliers were the relatively cool season (spring–summer) in 2011/12 (mean maximum air temperature = 28.1°C) and the relatively warm season in 2013/14 (32.5°C) (fig. 9). Again, no associations were detected between temperature and the catches of 1st and 2nd generations of moths, using the same seasonal groupings as mentioned above in relation to rainfall (table 6). Some significant associations were detected for temperature and 3rd generation moths; positive for the preceding winter and prevailing summer temperature , negative for spring and autumn (end of season) (table 6).
Fig. 9. Average daily maximum temperatures (°C) recorded at Narrabri West Post Office (Australian Bureau of Meteorology Station No: 53030) until December 2001; thereafter at Narrabri Airport (Station No: 54308). Data are provided for the autumn (March, April, May) and winter (June, July, August) preceding the moth activity season, spring (September, October, November) at the start of the moth activity season, and summer (December, January, February) at the end of the activity season.
The above is not to say that trap catches and weather at finer temporal scales (e.g. weekly) were not related (such data are not presented here).
Rainfall has varied greatly over the past 4 decades in inland Australia (fig. 10). However, there was no significant correlation between average rainfalls in autumn –winter (April–July inclusive) at the 36 meteorological stations in inland Australia and the numbers of 1st generation H. punctigera moths caught subsequently (weeks 8–20) in the trapping grid near Narrabri throughout 1992–2014 (r = 0.094, P > 0.05); nor was there any correlation with those caught throughout the moth's active season, thus including 2nd–3rd+ generations (weeks 8–44) (r = −0.090, P > 0.05). In addition, no significant correlations were obtained using rainfalls for individual months (April–July), nor the annual rainfalls (e.g. 1992 rainfall paired with the 1992/93 moth catch, and so on) (data not shown here).
Fig. 10. Average autumn to winter (April–July inclusive) rainfalls (mm) recorded across 36 meteorological stations in inland Australia from 1970 to 2014.
Discussion
The Bt resistance management strategy for H. punctigera as a pest of cotton in Australia has historically assumed, in part, that sufficient Bt susceptible moths would migrate into the eastern cotton cropping regions in spring each year and reduce the likelihood of development of resistance there. However, 23 years of continuous pheromone trapping for H. punctigera near Narrabri in northern New South Wales now suggests that the reliability of such influxes of H. punctigera moths has diminished in recent years. Pheromone traps were also run in the same region near Narrabri during the 7 cotton growing seasons (1985/86–1991/92) prior to the work reported here (G. Fitt, unpublished data). More traps were often used during these earlier seasons, but because the traps were not set then in the same positions as those run from 1992 to 2015 (and also varied in their locations between years), the data sets for the two periods have been kept separate. Nevertheless, during the earlier period, means of 14.6 1st generation moths (range 5.7–25.5), 5.9 2nd generation moths (range 2.0–9.7) and 1.0 3rd+ generation moths (range 0.2–4.1) were caught/trap/night. These trap catches for the early years were relatively high in comparison with those we recorded in the present study. They lend extra support to the view that the numbers of H. punctigera migrating into the vicinity of Narrabri each spring have declined over time. The earlier data also suggest that more moths could be found late in cotton growing seasons in the past compared with more recently, which the present study could not demonstrate persuasively on its own.
The numbers of H. punctigera in the 1st generation not only declined over the 23 years of study, but were highly erratic between consecutive years. Similar erratic annual variability has been previously reported using both light and pheromone traps (Wilson, Reference Wilson1983; Fitt et al., Reference Fitt, Zalucki and Twine1989; Gregg et al., Reference Gregg, Fitt, Zalucki, Murray, Drake and Gatehouse1995; Maelzer et al., Reference Maelzer, Zalucki and Laughlin1996; Oertel et al., Reference Oertel, Zalucki, Maelzer, Fitt and Sutherst1999; Baker et al., Reference Baker, Tann and Fitt2011). Some authors have argued (based on light trap catches) that autumn–winter rainfall in inland Australia and the Southern Oscillation Index (Oertel et al., Reference Oertel, Zalucki, Maelzer, Fitt and Sutherst1999; Maelzer & Zalucki, Reference Maelzer and Zalucki2000; Zalucki & Furlong, Reference Zalucki and Furlong2005) are sufficiently correlated with the numbers of 1st generation H. punctigera moths trapped near Narrabri such that long range forecasts of moth abundance might be made using these data. However, Baker et al. (Reference Baker, Tann and Fitt2011) could not show a similar significant relationship between inland autumn–winter rainfall and subsequent spring moth captures near Narrabri, using either light or pheromone traps. The data used in the Baker et al. (Reference Baker, Tann and Fitt2011) study was collected later (1992–2002) than the other authors’ work (1973–78 and 1981–1987), but the studies were of a similar duration overall (11 years). The pheromone trapping now reported here substantially extends that of Baker et al. (Reference Baker, Tann and Fitt2011) to 23 years. Again, there is no statistical evidence of a correlation between inland autumn–winter rainfalls and spring catches of H. punctigera moths near Narrabri, and thus the utility in using rainfall data per se to predict the likely pest status of this pest in the subsequent cropping season still seems doubtful.
Autumn–winter rainfalls in inland Australia were generally similar during the periods studied by Oertel et al. (Reference Oertel, Zalucki, Maelzer, Fitt and Sutherst1999); Maelzer & Zalucki (Reference Maelzer and Zalucki2000) and the present study (fig. 10). However, autumn–winter rainfall was particularly high in 1990, and that year was preceded by 2 years of above average rainfall as well. This relatively wet period appears unique (fig. 10) and by chance occurred in between the studies discussed here, but as noted above, pheromone traps were operated near Narrabri during these years, albeit in different spatial configurations (G. Fitt, unpublished data). The abundance of 1st generation H. punctigera moths in these traps during 1988, 1989 and 1990 was 5.7, 13.7 and 22.0 moths/trap/night respectively. i.e. well within the range of catches recorded in the same region in subsequent years, rather than extreme. In contrast, 1991 (also not included in the analyzed datasets referred to above) was relatively dry in inland Australia during autumn–winter (fig. 10), yet well above the average numbers of 1st generation moths were trapped that year near Narrabri (25.5 moths/trap/night; G. Fitt, unpublished data). These data therefore also reduce confidence that autumn–winter inland rainfall per se is a good predictor of spring numbers of H. punctigera in eastern cropping regions (at least near Narrabri). That is not to say that migrations of H. punctigera (from the inland to eastern cropping regions) have not happened to greater or lesser extents during these, and other previous and subsequent years. Indeed, Gregg et al. (Reference Gregg, Fitt, Zalucki, Murray, McDonald, Corey, Dall and Milne1993) presented evidence that migration was quite plausible in 1989 and 1990 (based on observations of insect abundance in the inland in winter, host food plant availability, wind patterns and presence of pollen characteristic of the inland on moths caught in the cropping regions). As several authors have indicated, the environmental factors influencing long-range movements of H. punctigera in spring are likely to be quite complex (Gregg et al., Reference Gregg, Fitt, Zalucki, Murray, Drake and Gatehouse1995; Rochester et al., Reference Rochester, Dillon, Fitt and Zalucki1996; Oertel et al., Reference Oertel, Zalucki, Maelzer, Fitt and Sutherst1999; Maelzer & Zalucki, Reference Maelzer and Zalucki2000; Zalucki & Furlong, Reference Zalucki and Furlong2005). For example, it may well be that migration from the inland to the Narrabri region has been impeded in recent years because inland host plants have struggled to recover since severe and extended drought. Alternatively, it may be that in some recent years there has been sufficient inland rainfall in spring – early summer (or floodplains there have remained moist enough, fed by rainfall from other regions) to maintain host plants for longer and thus reduce emigration. Studies aimed at identifying the key host plant communities that influence the large-scale, spring movements of H. punctigera are in progress (P. Gregg and K. Le Mottee, University of New England, pers. comm.).
There was a weak, but significant positive correlation between the abundance of 3rd+ generation moths in the traps in 1 year and that of the 1st generation moths in the following year, throughout 1992–2015. This is suggestive of local over-wintering, but we note that Maelzer & Zalucki (Reference Maelzer and Zalucki1999) did not find a similar relationship in their earlier study (in the 1970s and 1980s) using light traps near Narrabri. Perhaps there has been a temporal shift in the over-wintering ecology of H. punctigera. Alternatively, if spring influxes of moths into cropping regions have declined recently, it seems quite possible a correlation in moth numbers between 1 year and the next could be more easily detected there now. More importantly, we need to know if there is still significant gene flow for H. punctigera between the inland and eastern cotton cropping landscapes, and how instrumental this is in reducing the development of Bt resistance. The development of modern molecular tools to characterize Bt resistance genes and enable rapid throughput of samples to recognize their frequency in populations would greatly enable such studies (Tay et al., Reference Tay, Mahon, Heckel, Walsh, Downes, James, Lee, Reineke, Williams and Gordon2015).
The particularly high catches of H. punctigera moths in the summer of 2013/14 corresponded with the warmest air temperatures recorded in the 23 cotton seasons surveyed. Perhaps there was a causative link between the two. The depiction of a relatively high number of ‘2nd’ generation moths in 2013/14 (fig. 7) is probably explained, at least in part, as being due to many of the 3rd generation being caught earlier in this season (i.e. during weeks 21–30) (fig. 4) than otherwise would be expected (Baker et al., Reference Baker, Tann and Fitt2011). Perhaps the warmer weather in 2013/14 accelerated insect development, especially of the 3rd+ generation. An alternative explanation is that there was an additional/larger immigration later than usual in that season. More detailed analyses of rainfall, vegetation and wind patterns in the inland are merited, with special focus on this odd season.
Maelzer et al. (Reference Maelzer, Zalucki and Laughlin1996) and Maelzer & Zalucki (Reference Maelzer and Zalucki1999, Reference Maelzer and Zalucki2000), using light trap data collected from near Narrabri, reported that the abundance of the 2nd generation of H. punctigera moths was positively correlated with the abundance of the earlier 1st generation moths. Maelzer et al. (Reference Maelzer, Zalucki and Laughlin1996) and Maelzer & Zalucki (Reference Maelzer and Zalucki1999) also found that the abundance of both the 2nd and 3rd generation moths was positively correlated with the preceding local winter rainfall, whilst rain in spring and early summer was associated with lower numbers of these moths. They suggested that rain in winter would enable increased availability of suitable host plants for the offspring of 1st generation moths, either in the form of weeds or sown lucerne. They also suggested the later rain would dislodge eggs and larvae from host plants. Maelzer et al. (Reference Maelzer, Zalucki and Laughlin1996) and Maelzer & Zalucki (Reference Maelzer and Zalucki1999, Reference Maelzer and Zalucki2000) therefore argued that the likely scale of pest pressure by H. punctigera in late season could be predicted by a combination of the abundance of moths during early season and local rainfall. However, we could find no evidence of a correlation between the abundance of 1st and 2nd generation moths (although we did find such between 1st and 3rd+ and 2nd and 3rd+ generations), nor could we find a positive association between local winter rainfall and the abundance of 2nd or 3rd+ generation moths, or a negative association between abundance of these generations and summer rainfall. We did, however, find a weak negative association between spring rainfall and the 3rd+ generation catch. In addition, Baker et al. (Reference Baker, Tann and Fitt2011) reported a positive correlation between the abundance of 1st and 3rd+ generations using light traps, but not with pheromone traps, and, in agreement with the present (extended) study, failed to find correlations between local winter rainfall and the abundance of 2nd and 3rd+ generation moths using either light or pheromone traps. They did, however, find a negative correlation between the abundance of the 3rd+ generation (but not the 2nd) moths and spring rainfall using pheromone traps (but not with light traps). These inconsistencies in results are difficult to explain, even given that light and pheromone traps have their various weaknesses (see later), but do suggest the trends that have been reported are not particularly reliable in terms of predictive power.
The multiple regression analyses used in the present study also detected some significant relationships between moth catches and local temperatures, but only involving the 3rd+ generation. These relationships were erratic (positive for preceding winter and prevailing summer and negative for preceding spring and prevailing autumn). We can provide no adequate explanation for such patterns. Their biological significance, if any, remains obscure.
Trap catches, whatever their design, measure a mix of abundance and activity. Both pheromone and light traps have their limitations and therefore need to be used with caution (Gregg & Wilson, Reference Gregg, Wilson and Zalucki1991). Several factors, other than the obvious one of weather variability, can influence catch (e.g. the pheromone traps used here catch only males; seasonal availability of mating female moths may confound trap efficacy) (Hartstack & Witz, Reference Hartstack and Witz1981; Morton et al., Reference Morton, Tuart and Wardhaugh1981; Wilson, Reference Wilson1984; Dent & Pawar, Reference Dent and Pawar1988; Wilson & Morton, Reference Wilson and Morton1989; Gregg & Wilson, Reference Gregg, Wilson and Zalucki1991). Baker et al. (Reference Baker, Tann and Fitt2011) showed substantial differences between seasonal patterns in the catches of H. punctigera recorded using pheromone and light traps; e.g. pheromone traps caught more 1st generation male moths than 2nd generation male moths, and the reverse was the case for light traps. However, by trapping continuously and making comparisons at generation level, the importance of these limitations with trapping data was reduced. One particular factor already known to influence catch is the proximity of different habitats (Gregg & Wilson, Reference Gregg, Wilson and Zalucki1991; Maelzer et al., Reference Maelzer, Zalucki and Laughlin1996). Our study demonstrated that placing traps near cotton decreased the catch of H. punctigera (when year was included as a concurrent variable), but suggested an increase for soybean and chickpea (although trap replication was low in these latter cases). On the other hand, sorghum was associated with reduced catches. Such contrasting results are probably best explained by a combination of the suitability, or otherwise, of these crops as host plants for H. punctigera and differential use of toxins to control these and other pests (Fitt, Reference Fitt1989; Sequeira & Moore, Reference Sequeira and Moore2003; Duffield, Reference Duffield2004; Fitt & Cotter, Reference Fitt, Cotter and Sharma2004; Sequeira, Reference Sequeira2004; Duffield et al., Reference Duffield, Winder and Chapple2005; Baker et al., Reference Baker, Tann and Fitt2008). However, it is not clear from our data whether the moths were caught, to greater or lesser extents, because of the level of attractiveness of these nearby crops and/or their relative abilities to produce moths.
Several authors have suggested that the use of Bt crops (single Bt gene) has not only reduced lepidopteran pest damage but also suppressed, or at least helped suppress, the abundance of the target pest insects at large spatial scales, using either pheromone traps (Carrière et al., Reference Carrière, Ellers-Kirk, Sisterson, Antilla, Whitlow, Dennehy and Tabashnik2003; Adamczyk & Hubbard, Reference Adamczyk and Hubbard2006) or direct counts of eggs and larvae on crops (Wu et al., Reference Wu, Lu, Feng, Jiang and Zhao2008; Hutchison et al., Reference Hutchison, Burkness, Mitchell, Moon, Leslie, Fleisher, Abrahamson, Hamilton, Steffey, Gray, Hellmich, Kaster, Hunt, Wright, Pecinovsky, Rabaey, Flood and Raun2010; Wan et al., Reference Wan, Huang, Tabashnik, Huang and Wu2012). However, there was little evidence that the numbers of H. punctigera trapped near Narrabri decreased in concert with the introduction of Ingard® cotton during the 1996/97 season. The numbers of 1st generation moths caught during the Ingard® era, averaged across all traps, were less than those in earlier years, but these moths are believed to be mostly immigrants that have not been exposed to Bt (Fitt, Reference Fitt and Kalaitzandonakes2003; Fitt & Cotter, Reference Fitt, Cotter and Sharma2004). In addition, the greatest reduction in the numbers of 1st generation moths occurred pre 1996/97 (fig. 7). The 2nd generation moths showed no reduction in catch associated with Ingard® cotton, and whilst the 3rd generation moths were rarer in the Ingard® era than they were earlier, this generation was generally very scarce throughout.
It is perhaps not surprising to find little evidence of Ingard® cotton influencing H. punctigera. Ingard® cotton was limited to a maximum of 30% of the overall Australian cotton production area, thus reducing the likelihood that Bt cotton per se, or changes in farming practices associated with it, could suppress H. punctigera numbers at a large scale. Carrière et al. (Reference Carrière, Ellers-Kirk, Sisterson, Antilla, Whitlow, Dennehy and Tabashnik2003) and Wan et al. (Reference Wan, Huang, Tabashnik, Huang and Wu2012) have suggested that a threshold of approximately 65% of cotton planted as Bt cotton in regions of the USA and China respectively is needed to suppress populations of the pink bollworm (Pectinophora gossypiella). Pink bollworm is a specialist feeder, in contrast to the polyphagous H. punctigera. Higher exposure than a 65% Bt cotton area might therefore be considered necessary to suppress H. punctigera numbers at large spatial scales. Bollgard II® cotton, which now represents approximately 90% of the total cotton crop in Australia, would thus seem to have had a greater chance of suppressing H. punctigera’s numbers than did Ingard® cotton. However, no reduction in the abundance of H. punctigera from Ingard® to Bollgard II® cotton was recorded, for any of the three generations, when average catches across all traps were compared. It is noteworthy, however, that when catches of 2nd and 3rd+ generation moths in individual traps were compared, with respect to the presence of cotton growing nearby, it was only during the Bollgard II® era that a significant relationship (negative) was recorded.
Overall, this long-term study of H. punctigera in an eastern Australian cropping region, based on pheromone trapping, demonstrated annual variation in population numbers, which can at least in part be explained by local habitat changes and weather factors, and a long-term, downward trend in abundance, which most probably reflects reduced recruitment of migrant moths from inland Australia. The latter has relevance to ongoing revisions to the Bt cotton resistance management strategy developed for these moths.
Acknowledgements
This work was funded by research grants from the Cotton Research and Development Corporation, Australia. We thank Sarina Macfadyen for helpful comments on a draft manuscript, Melinda Haley (Neil Clark Business Intelligence) for providing data on crop plantings and Peter Verwey (NSW DPI) for creating the map in fig. 1 for us. We especially thank Gary Fitt (CSIRO) for his foresight in establishing the pheromone trap grid and for the use of his early, unpublished data on catches near Narrabri.
