Environmentally friendly methods for managing insect pests are crucial for ecosystem functioning, biodiversity, and conservation (Araújo et al., 2023; Arp et al., 2023). Behavioural manipulation, using specific chemical signals (semiochemicals), is a strategy that has received much attention in the past 80 years (Steurer et al., 2024, but see Foster and Harris, 1997 for a review). One approach to manipulating the behaviour of insect pests is through pheromones, including sex pheromones (Bengtsson et al., 1994; Witzgall et al., 2010; Miller and Gut, 2015). Sex pheromones are crucial for the recognition, attraction, and selection of potential conspecific mates, and for preventing the attraction of heterospecific individuals to maintain species integrity (Wyatt, 2003; De Pasqual et al., 2021). Since the identification of the pheromone bombykol in the silkworm moth Bombyx mori L. (Lepidoptera: Bombycidae) in the 1950s, the first description of an insect sex pheromone (Butenandt et al., 1959), the identification, isolation, and use of sex pheromones has advanced and is now an essential tool in area-wide integrated pest management (AW-IPM) strategies (Stern et al., 1959; Wright, 1964; Witzgall et al., 2010; Gao et al., 2020). These strategies exploit the response of male insects to female sex pheromones, in particular male attraction, using inanimate objects baited with the specific female sex pheromone blend (Regnier and Law, 1968). However, sex pheromones (see De Pasqual et al., 2021 for a detailed review), the key signals for sexual communication, can overlap interspecifically (De Pasqual et al., 2021), and vary intraspecifically in many insects, including pests with wide geographic distributions (Rodriguez-Saona and Stelinski, 2009; Gao et al., 2020; De Pasqual et al., 2021).

In moth species, geographic variation may arise as a result of avoiding inbreeding with closely related sympatric species that share key pheromone components (McElfresh and Millar, 1999; Groot et al., 2008; Sadek et al., 2012). Variation can also be manifested in the timing of sexual behaviours or be a consequence of physiological, biotic, and abiotic factors such as age (Swier et al., 1977; Noldus and Potting, 1990; Xavier et al., 2018), nutrition (Casimero et al., 2001), temperature (Conner et al., 1985; Delisle and McNeil, 1987), relative humidity (Webster and Cardé, 1982; Royer and McNeil, 1991), photoperiod (Delisle and McNeil, 1986; Noldus and Potting, 1990; Kamimura and Tatsuki, 1994), host plants (Landolt and Phillips, 1997), wind speed (Conner et al., 1985), and insecticides (Shen et al., 2013; Navarro-Roldán and Gemeno, 2017). Therefore, it is essential to understand the local sex pheromone blends and local timings of sexual communication for effective field implementation of sex pheromone-dependent control tools (Gao et al., 2020).

The False Codling Moth (hereafter “FCM”), Thaumatotibia leucotreta Meyrick (Lepidoptera: Tortricidae), endemic to sub-Saharan Africa (hereafter “SSA”), is a pest of several economically important crops, including citrus, corn, cotton, pepper, pomegranate, peach, and plum (Venette et al., 2003; Hofmeyr et al., 2005; Adom et al., 2020). FCM is one of the biggest biotic threats to the citrus industry of southern Africa because of its classification as a phytosanitary or quarantine pest in international markets, such as the United States of America (USA), European Union (EU), and the Far East (Venette et al., 2003; Moore, 2021). Rejection of export consignments due to FCM detection is devastating to the economies of affected countries in SSA, such as the southern African citrus industry, comprising three citrus-exporting countries (South Africa, Zimbabwe, and Eswatini), with an estimated annual export of 2.2 million tons, valued at USD 1.5 billion (CGA, 2021). Consequently, FCM is diligently controlled in citrus orchards in South Africa (Hattingh et al., 2020). Due to the stringent restrictions on synthetic chemical pesticide residues on exported fruit by certain markets, FCM control is focused on IPM; the most important options of IPM against FCM are based on the use of female sex pheromones (Hofmeyr and Pretorius, 2010; Hattingh et al., 2020; Moore, 2021). This includes monitoring, attract-and-kill and mating disruption (Moore and Hattingh, 2012).

Existing reports of the composition of the female FCM pheromone are remarkably varied, in terms of both the particular compounds and the ratios of different isomers (reviewed in Levi-Zada et al., 2020). The most recent study of female moths from Israel reported eleven compounds in the female FCM sex pheromone blend (Levi-Zada et al., 2020). Corroborating previous studies, only (E)-8-dodecenyl acetate (E8–12:Ac) and (Z)-8-dodecenyl acetate (Z8–12:Ac) were shown to play a key role in FCM sexual communication (Zagatti et al., 1983; Hall et al., 1984; Attygalle et al., 1986; Levi-Zada et al., 2020). However, studies from SSA have reported discrepant ratios of these two compounds as the optimal blend both in laboratory assays and field evaluations. To date, there is no clarity on the composition of the most effective blend of the pheromone for IPM or the natural ratio of isomers in SSA FCM populations. For example, following the extraction and evaluation of female sex pheromone glands, Persoons et al. (1977) reported the E/Z ratio as 1:1, Angélini et al. (1981) and Zagatti et al. (1983) found 3:1, Hall et al. (1984) reported 2:3, while Attygalle et al. (1986) found 9:1. Newton et al. (1993) highlighted 8:2 and 9:1 as effective blends. Recently, Levi-Zada et al. (2020) reported 9:1, but the population tested by the latter authors was from Israel, not SSA. The discrepancies in the published isomer ratios from different populations may reflect intraspecific variation in the sex pheromone across SSA. Attygalle et al. (1986) took this one step further and postulated the occurrence of subspecies of FCM in SSA, which differ in the ratio of E8–12:Ac and Z8–12:Ac. More recent laboratory and field studies performed in South Africa provide some support for the possibility of FCM subspecies (e.g., Timm et al., 2008; 2010; Joubert, 2018; Upfold, 2019).

Considering that the functionality of the established IPM programme for FCM in southern Africa relies on sex pheromone-based control tools (i.e., monitoring, attract-and-kill, mating disruption, and SIT), it is paramount to fully establish whether the FCM pheromone blend varies geographically and whether intraspecific variation in the pheromone blend may influence the effectiveness of existing control tools. Exploring the potential role of intraspecific variation in the pheromone blend in premating isolation would also inform discussions of incipient speciation within FCM. This study specifically addresses these questions by investigating the mating compatibility of FCM from different geographic populations in South Africa and assessing the ratios of E8–12:Ac and Z8–12:Ac in females from these populations. The implications of our findings are discussed in the context of AW-IPM of FCM.

This study investigated genetic differentiation and mating compatibility in five geographically isolated populations of the False Codling Moth (FCM) Thaumatotibia leucotreta in South Africa. The obtained data showed genetic differentiation between these populations whereby three genetically distinct groups with high genetic distances between each other were identified, i.e., Nelspruit, Marble Hall, and a group formed by Old Colony, Citrusdal and Addo (Tables 1, 2). These genetic differences were reflected in the mating choices made during pairwise choice tests where individuals from genetically distant groups were selected against (Table 3). Nonetheless, in the absence of a choice, males did successfully mate with females from any other population. The mating success, measured as the number of transferred spermatophores, was similar in inter- and intra-population mating events (Figure 2); however, males from populations with high genetic diversity participated more actively in mating with females from both their own and different populations compared to males from populations with a low genetic diversity.

Assessing the levels of genetic variation between different populations is a powerful method to identify or confirm gene flow limitations that can lead to reproductive isolation and eventually speciation (Riesch et al., 2017; Taylor and Friesen, 2017; Doellman et al., 2019). With regard to pest insects, geographically isolated populations with restricted gene flow can rapidly diverge in traits targeted by region-wide applied pest management strategies and cause these to become less effective (Riesch et al., 2017; Taylor and Friesen, 2017; Gao et al., 2020). In the case of FCM, the currently available data from SSA indicate divergence, particularly with regard to the composition of the female sex pheromone which is widely used in FCM control tools (Attygalle et al., 1986; Upfold, 2019). Consequently, local changes in mating behaviour are worth testing as these may require adjusting the commonly used sex pheromone-based management strategies on a local basis.

Previous studies with geographically isolated FCM populations in SSA found both high genetic diversity (Timm et al., 2008; 2010) as well as low genetic diversity, regardless of host crops, geographical locations, and country (e.g., Mkiga et al., 2021). However, to date, no study has assessed genetic diversity of, and differentiation between, populations on a smaller geographic scale, i.e., within a single country. This study is the first to focus on a smaller geographic scale, combining data for FCM populations from four South African provinces, encompassing the southern and northern parts of South Africa, including the Eastern Cape, Limpopo, Mpumalanga, and Western Cape provinces, and a population of mixed origin (Old Colony). Remarkably, even at this geographic scale, there were significant differences in genetic diversity with the five studied populations falling into three distinct genetic groups, indicating divergence of FCM within South Africa. Low genetic diversity was found in samples from the Marble Hall and Nelspruit populations, which both formed their own genetic groups (Figure 1). These were separate from the third genetic group, comprising the other three studied populations (Figure 1). High genetic diversity was found in samples from the Addo and Citrusdal populations, while the Old Colony population was intermediate.

Males from populations with a higher recorded genetic diversity were observed to be more competitive (significant MRPI values) and participated in more mating events with females of both their own and other populations, than were males from populations with a low calculated genetic diversity (Tables 1, 3). Although not significant, this observed trend indicates that maintaining high genetic diversity amongst commercially produced cultures used in AW-IPM programmes, in particular the sterile insect technique (SIT), could be crucial to improve the competitiveness of SIT males in the field. Maintaining genetic diversity and avoiding phenotypic, as well as genetic, effects are key challenges faced in the mass rearing of insects (Leftwich et al., 2021). Inbreeding depression and random genetic drift may result in the loss of genetic diversity, which can lead to loss of fitness and reduced field performance (Mackauer, 1976; Willi et al., 2006; Hoffmann et al., 2017). A decrease in vigour (phenotypic effect) often results from overcrowding and poor diet (Reynolds, 2012). Genetic effects and changes in behaviour may arise as a result of a ‘domestication’ effect when long-term laboratory rearing results in selection for traits better adapted to the laboratory rearing conditions, which in turn affects the reproductive or behavioural traits of the insect (Bartlett, 1984; Hoffmann and Ross, 2018). In order to counteract the “evolution” of laboratory strains, the genetic pool of cultured populations should be re-supplied intermittently with field collected individuals from the corresponding wild populations.

The genetic divergence between the five populations identified in this study was partly reflected in the mating choices during mating compatibility assays with males and females of two different populations. While mating was random in assays with population pairs from the same genetic group, mating was selective towards the own population in choice assays with populations from two different genetic groups (Table 3). This indicates that individuals are capable of identifying conspecifics on a population level, which allows us to assume divergence in recognition signals, likely the sex pheromone, and pre-mating reproductive isolation between some of the South African populations. the FRPI values were never significantly different (Table 3) which indicates that males actively choose female mating partners (“male mate choice”, Bonduriansky, 2001) and thereby select on female phenotypic traits – most likely the female sex pheromone. However, in the absence of a choice, males from all the populations would mate with any female and were able to transfer spermatophores to females originating from a different population with similar success as to females from their own population (Figures 2, 3). It was not assessed in this study whether the resulting offspring of inter-population mating events would be viable. However, previous studies did not find significant differences in the number of viable offspring produced in no-choice cross-mating tests. Thus, while pre-mating reproductive isolation seems established at a certain level, post-mating reproductive isolation among South African FCM populations does not (yet) exist, as previously underscored by Mgocheki and Addison (2016).

Many other lepidopteran pests also in South Africa have formed locally adapted populations, due to fragmented host ranges and in part due to limited hosts, such as Grapholita molesta (Busck) (Lepidoptera: Tortricidae), Cydia pomonella (L.) (Lepidoptera: Tortricidae), Thaumatotibia batrachopa (Meyrick) (Lepidoptera: Tortricidae) and Cryptophlebia peltastica (Meyrick) (Lepidoptera: Tortricidae) (Meyrick, 1930; Quilici et al., 1988; Newton, 1998). The genetic differences amongst locally and regionally adapted FCM populations raises apprehensions and questions of whether the efficacy of semiochemical-based technologies can be enhanced through the manufacturing of regionally specific pheromone lures and dispensers.

Studies investigating sexual behaviour in other lepidopteran species found that in cases where males exhibited a significant selection for females of their own population compared to females of a different population, the composition of the sex pheromone was different between both populations (e.g., Tòth et al., 1992; Groot et al., 2008; Duménil et al., 2014). Over time, these differences in the sex pheromone or intraspecific variation may act as a driver for sexual selection and mating incompatibility via reproductive isolation (see De Pasqual et al., 2021 for a detailed review). It has been abundantly clarified that even subtle differences in pheromone composition may influence the degree of attraction within species populations (Campion and Nesbitt, 1981; Newton et al., 1993; Ando et al., 2004; Ando and Yamakawa, 2011). Hence, chemical analyses of sex pheromones in pest insects with a wide distribution range is important to understand locally manifested pre-mating reproductive isolation (Gao et al., 2020).

In fact, there are contradictory data regarding the composition of the female sex pheromone (Read et al., 1968; Persoons et al., 1977; Angélini et al., 1981; Zagatti et al., 1983; Hall et al., 1984; Attygalle et al., 1986) and it is unknown whether these differences are simply a result of different methodologies used or indeed reflect geographic isolation. Attygalle et al. (1986) concluded that the differences were most likely a result of populations originating from different geographic ranges and that sympatric speciation may have occurred due to ecological boundaries, encompassing spatial structure and functions, and temporal dynamics.

Earlier attempts to investigate intraspecific sex pheromone variation between geographically isolated FCM populations in South Africa using sample enrichment probes (Burger et al., 2017) were unsuccessful (Upfold, 2019). Here a solvent extraction method established by Attygalle et al. (1986), and recently validated by researchers in Israel (Levi-Zada et al., 2020), was used to assess differences in the ratios of the main pheromone components E8–12:Ac and Z8–12:Ac. These isomers are the main attractant for males and have been shown to play a key role in FCM mating behaviour. However, there is controversy in the precise ratio of the two isomers published in earlier studies (Zagatti et al., 1983; Attygalle et al., 1986; Levi-Zada et al., 2020). We have determined a E:Z-ratio of c. 4:1 and found this to be consistent across all five studied populations (Table 4). The absence of variation in the key attractive components E8–12:Ac and Z8–12:Ac could explain the general mating compatibility between all five studied populations when mating partners from the own population are not available. This finding provides important empirical evidence that South African FCM populations have not diverged in the key sexual signal. However, the observed trends for intra-population mating preferences and “male mate choice” (MRPI values) in choice-tests between the five studied FCM populations suggests some divergence in the female sex pheromone composition. It is thus very likely that other minor components of the sex pheromone (not explored in this study) vary between the populations and that such variation accounts for intra-population recognition and mating preference, which over time could lead to pre-mating reproductive isolation between geographically isolated FCM populations.

The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.

The animal study was approved by Animal Research Ethics Committee at Rhodes University. The study was conducted in accordance with the local legislation and institutional requirements.

PA: Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Project administration, Resources, Software, Validation, Visualization, Writing – original draft, Writing – review & editing. AH: Data curation, Formal analysis, Investigation, Methodology, Project administration, Software, Validation, Visualization, Writing – review & editing. JU: Investigation, Writing – review & editing. AS: Formal analysis, Funding acquisition, Methodology, Project administration, Resources, Software, Supervision, Validation, Visualization, Writing – review & editing. SM: Conceptualization, Funding acquisition, Project administration, Resources, Supervision, Validation, Visualization, Writing – review & editing. MH: Conceptualization, Funding acquisition, Project administration, Resources, Supervision, Validation, Visualization, Writing – review & editing. CC: Conceptualization, Funding acquisition, Methodology, Project administration, Resources, Supervision, Validation, Visualization, Writing – review & editing.