No evidence of responding individuals constraining the evolution of the pheromone signal in the pine engraver Ips avulsus

Chemical signals are important mediators of interactions within forest ecosystems. In insects, pheromone signals mediate intraspecific interactions such as mate location and acceptance. The evolution of pheromones in insects has been mostly studied from a theoretical perspective in the Lepidoptera. With this study, we aimed to broaden our understanding of pheromone communication in bark beetles. We first demonstrated that the enantiomeric ratios of ipsdienol produced by male I. avulsus, showed little variation. Subsequently, with field trapping trials we characterized the influence of the enantiomeric ratio of ipsdienol (pheromone component of I. avulsus) on I. avulsus captures and observed a great amount of variation in the receiver preference function. Most importantly, we demonstrated that responding individuals responded indiscriminately to all the enantiomeric ratios produced by the emitting individuals. These observations are consistent with the asymmetric tracking model which postulates that if the limiting sex is the emitting sex, responding individuals should not discriminate between emitted ratios. Consequently, responding individuals do not constrain the evolution of the signal. Our data suggest that, in I. avulsus, the composition of the aggregation pheromone signal might be more responsive to external selection forces, such as predation and metabolic constraints, as suggested by the asymmetric tracking model.Louisiana State University AgCenter. Open Access provided by Natural Resources Canada.https://link.springer.com/journal/10886hj2023Forestry and Agricultural Biotechnology Institute (FABI)Zoology and Entomolog

Allele size of microsatellite markers in S. noctilio and R script for the model predicting sex ratios

A table of allele sizes was compiled for 13 microsatellites for 67 males Sirex noctilio from the Western Cape province of South Africa and 77 males from the KwaZulu-Natal province. The dataset also contains (ii) a script for the design of a state-space model predicting the sex-ratio within a population of S. noctilio.Tree Protection Cooperative Programme, Department of Agriculture, Forestry and Fisheries and National Research Foundation of South Africa- QueffelecJetal_data_microsatellite.xlsx - QueffelecJetal_SpaceStateModel_fig1_Rscript.tx

Remnants of horizontal transfers of Wolbachia genes in a Wolbachia-free woodwasp

BACKGROUND: Wolbachia is a bacterial endosymbiont of many arthropod and nematode species. Due to its capacity to alter host biology, Wolbachia plays an important role in arthropod and nematode ecology and evolution. Sirex noctilio is a woodwasp causing economic loss in pine plantations of the Southern Hemisphere. An investigation into the genome of this wasp revealed the presence of Wolbachia sequences. Due to the potential impact of Wolbachia on the populations of this wasp, as well as its potential use as a biological control agent against invasive insects, this discovery warranted investigation. RESULTS: In this study we first investigated the presence of Wolbachia in S. noctilio and demonstrated that South African populations of the wasp are unlikely to be infected. We then screened the full genome of S. noctilio and found 12 Wolbachia pseudogenes. Most of these genes constitute building blocks of various transposable elements originating from the Wolbachia genome. Finally, we demonstrate that these genes are distributed in all South African populations of the wasp. CONCLUSION: Our results provide evidence that S. noctilio might be compatible with a Wolbachia infection and that the bacteria could potentially be used in the future to regulate invasive populations of the wasp. Understanding the mechanisms that led to a loss of Wolbachia infection in S. noctilio could indicate which host species or host population should be sampled to find a Wolbachia strain that could be used as a biological control against S. noctilio.Additional file 1: Figure S1. Maximum likelihood tree. It was constructed with the protein sequence of ORF1 compared to similar protein sequences of 11 Wolbachia strains and one protein sequence from Diplorickettsia massiliensis (Gammaproteobacteria: Coxiellaceae) (out group). The branch indicated in red represents the position of ORF1 among other Wolbachia protein sequences. All Wolbachia strains are named after their hosts as follows: wAus, Plutella australiana; wCauA, Carposina sasakii; wDi, Diaphorina citri; wNfla, Nomada flava; wNleu, Nomada leucophthalma; wNo, Drosophila simulans; wNpa, Nomada panzeri; wPip, Culex quinquefasciatus; wPnig, Pentalonia nigronervosa; wStri, Laodelphax striatellus; wVulC, Armadillidium vulgare.Additional file 2: Figure S2. Maximum likelihood tree. It was constructed with the protein sequence of ORF2 compared to similar protein sequences of 12 Wolbachia strains and one protein sequence from Herpetosiphon llansteffanense (Terrabacteria: Herpetosiphonales) (out group). The branch indicated in red represents the position of ORF2 among other Wolbachia protein sequences. All Wolbachia strains are named after their hosts as follows: wAna, Drosophila ananassae; wCauA, Carposina sasakii; wCobs, Cardiocondyla obscurior; wCon, Cylisticus convexus; wHa, Drosophila simulans; wKgib, Kradibia gibbosae; wLug, Nilaparvata lugens; wMelPop, Drosophila melanogaster; wPnig, Pentalonia nigronervosa; wUni, Muscidifurax uniraptor; wTpre, Trichogramma pretiosum; wVulC, Armadillidium vulgare.Additional file 3: Figure S3. Maximum likelihood tree. It was constructed with the protein sequence of ORF3 compared to similar protein sequences of two Wolbachia strains and one protein sequence from Mastigocladopsis repens (Cyanobacteria: Symphyonemataceae) (out group). The branch indicated in red represents the position of ORF3 among other protein sequences. The two Wolbachia strains are named after their hosts as follows: wFcan, Folsomia candida; wVulC, Armadillidium vulgare.Additional file 4: Figure S4. Maximum likelihood tree. It was constructed with the protein sequence of ORF4 compared to similar protein sequences of seven Wolbachia strains and one protein sequence from Legionella pneumophila (Gammaproteobacteria: Legionellaceae) (out group). The branch indicated in red represents the position of ORF4 among other Wolbachia protein sequences. All Wolbachia strains are named after their hosts as follows: wAu, Drosophila simulans; wDac, Dactylopius coccus; wHa, Drosophila simulans; wMelPop, Drosophila melanogaster; wOne, Nasonia oneida; wUni, Muscidifurax uniraptor; wVulC, Armadillidium vulgare.Additional file 5: Figure S5. Maximum likelihood tree. It was constructed with the protein sequence of ORF6 compared to similar protein sequences of 23 Wolbachia strains and one protein sequence from Holospora undulata (Alphaproteobacteria: Holosporaceae) (out group). The branch indicated in red represents the position of ORF6 among other Wolbachia protein sequences. All Wolbachia strains are named after their hosts as follows: wAna, Drosophila ananassae; wBt, Bemisia tabaci; wCauA, Carposina sasakii; wCobs, Cardiocondyla obscurior; wCon, Cylisticus convexus; wDac, Dactylopius coccus; wDi, Diaphorina citri; wFcan, Folsomia candida; wKgib, Kradibia gibbosae; wLug, Nilaparvata lugens; wMau, Drosophila mauritiana; wMeg, Chrysomya megacephala; wMelPop, Drosophila melanogaster; wNfe, Nomada ferruginata; wNo, Drosophila simulans; wOne, Nasonia oneida; wPip, Culex quinquefasciatus; wPip_Mol, Culex molestus; wPnig, Pentalonia nigronervosa; wStri, Laodelphax striatellus; wTei, Drosophila teissieri; wVulC, Armadillidium vulgare; wYak, Drosophila yakuba.Additional file 6: Figure S6. Maximum likelihood tree. It was constructed with the protein sequence of ORF7 compared to similar protein sequences of 22 Wolbachia strains and one protein sequence from Holospora undulata (Alphaproteobacteria: Holosporaceae). The branch indicated in red represents the position of ORF7 among other Wolbachia protein sequences. All Wolbachia strains are named after their hosts as follows: wBt, Bemisia tabaci; wCauA, Carposina sasakii; wCfeT, Ctenocephalides felis; wCobs, Cardiocondyla obscurior; wCon, Cylisticus convexus; wDac, Dactylopius coccus; wDi, Diaphorina citri; wFcan, Folsomia candida; wGmo, Glossina morsitans; wInc, Drosophila incompta; wKgib, Kradibia gibbosae; wLug, Nilaparvata lugens; wMau, Drosophila mauritiana; wMeg, Chrysomya megacephala; wNleu, Nomada leucophthalma; wNo, Drosophila simulans; wNpa, Nomada panzeri; wPip, Culex quinquefasciatus; wPnig, Pentalonia nigronervosa; wStri, Laodelphax striatellus; wVulC, Armadillidium vulgare.Additional file 7: Figure S7. Maximum likelihood tree. It was constructed with the protein sequence of ORF9 compared to similar protein sequences of 20 Wolbachia strains and one protein sequence from Moorea producens (Cyanobacteria: Oscillatoriaceae). The branch indicated in red represents the position of ORF9 among other Wolbachia protein sequences. All Wolbachia strains are named after their hosts as follows: wAna, Drosophila ananassae; wAu, Drosophila simulans; wBt, Bemisia tabaci; wCfeT, Ctenocephalides felis; wCon, Cylisticus convexus; wDac, Dactylopius coccus; wDi, Diaphorina citri; wInc, Drosophila incompta; wKgib, Kradibia gibbosae; wMeg, Chrysomya megacephala; wMel, Drosophila melanogaster; wOb, Operophtera brumata; wOne, Nasonia oneida; wPip, Culex quinquefasciatus; wPol, Atemnus politus; wSan, Drosophila santomea; wStri, Laodelphax striatellus; wTei, Drosophila teissieri; wVulC, Armadillidium vulgare; wYak, Drosophila yakuba.Additional file 8: Figure S8. Maximum likelihood tree. It was constructed with the protein sequence of ORF10 compared to similar protein sequences of 21 Wolbachia strains and one protein sequence from Diplorickettsia massiliensis (Gammaproteobacteria: Coxiellaceae). The branch indicated in red represents the position of ORF10 among other Wolbachia protein sequences. All Wolbachia strains are named after their hosts as follows: wAlbB, Aedes albopictus ; wAna, Drosophila ananassae; wAus, Plutella australiana ; wCauA, Carposina sasakii; wCfeJ, Ctenocephalides felis; wCle, Cimex lectularius; wCobs, Cardiocondyla obscurior; wCon, Cylisticus convexus; wDi, Diaphorina citri; wFcan, Folsomia candida; wMau, Drosophila mauritiana; wMel, Drosophila melanogaster; wNfe, Nomada ferruginata; wNo, Drosophila simulans; wOb, Operophtera brumata; wPip, Culex quinquefasciatus; wPnig, Pentalonia nigronervosa; wSan, Drosophila santomea; wStri, Laodelphax striatellus; wVulC, Armadillidium vulgare.Additional file 9: Figure S9. Maximum likelihood tree. It was constructed with the protein sequence of ORF11 compared to similar protein sequences of 10 Wolbachia strains. The branch indicated in red represents the position of ORF11 among other Wolbachia protein sequences. All Wolbachia strains are named after their hosts as follows: wAlbB, Aedes albopictus; wAus, Plutella australiana; wBlon, Brontispa longissima; wCobs, Cardiocondyla obscurior; wDi, Diaphorina citri; wMau, Drosophila mauritiana; wNo, Drosophila simulans; wPip, Culex quinquefasciatus; wPnig, Pentalonia nigronervosa; wStri, Laodelphax striatellus.Additional file 10: Figure S10. Maximum likelihood tree. It was constructed with the protein sequence of ORF12 compared to similar protein sequences of seven Wolbachia strains. The branch indicated in red represents the position of ORF12 among other Wolbachia protein sequences. All Wolbachia strains are named after their hosts as follows: wAlbB, Aedes albopictus; wAus, Plutella australiana; wDi, Diaphorina citri; wPip, Culex quinquefasciatus; wPip_Mol, Culex molestus; wPnig, Pentalonia nigronervosa; wStri, Laodelphax striatellus.Additional file 11: Table S1. PCR cycling protocol. Tm = Annealing temperature specific to the primer pair (Table 2); * T° decreases by 0.5°C at the start of each cycle.Tree Protection Cooperative Programme (TPCP), the Department of Agriculture, Forestry and Fisheries (DAFF), National Research Foundation (NRF) of South Africa, Natural Resources Canada and the USDA-FS FHP.https://bmcecolevol.biomedcentral.comBiochemistryForestry and Agricultural Biotechnology Institute (FABI)GeneticsMicrobiology and Plant PathologyZoology and Entomolog

Influence of reproductive biology on establishment capacity in introduced Hymenoptera species

Introduced species face numerous biological barriers before they can establish in a new environment. Understanding how they overcome these obstacles is crucial for the development of effective risk assessment and regulation. Reproductive biology is known to influence establishment capacity in plants and is widely used for risk assessment. This biological field should receive more attention, and particularly in the case of insects, as they display a wide range of reproductive traits and have a great impact on the economy and environment. Among insects, the order Hymenoptera is of interest for its diversity, both in terms of reproductive traits and introduction history, as invasive species and biological control agents. We review the main reproductive strategies of Hymenoptera, spanning parthenogenesis, sex determination, reproductive parasites and mating strategies, and evaluate their effect on invasive potential. For instance, thelytoky could decrease the strength of Allee effects while Arrhenotoky could increase adaptive potential. A species with complementary sex determination could be more affected by inbreeding than other species, while paternal genome elimination could lead to high levels of homozygosity. Finally, some reproductive behaviours could decrease inbreeding, facilitate mate location or adaptation by encouraging admixture. The two invasive species Apis mellifera scutellata and Leptocybe invasa and the biocontrol agent Aphidius ervi serve as case studies to illustrate the effect of reproductive traits on species capacities to become established in a new area.The Tree Protection Cooperative Programme (TPCP), Natural Resources Canada and the U.S. Department of Agriculture.http://link.springer.com/journal/105302021-10-08hj2021BiochemistryForestry and Agricultural Biotechnology Institute (FABI)GeneticsMicrobiology and Plant PathologyZoology and Entomolog

Enantiospecific response of Ips avulsus (Coleoptera: Curculionidae: Scolytinae) to ipsdienol depends on semiochemical context

DATA AVAILABILITY : The data underlying the results of this study are openly available on the Open Government Canada portal at https://doi.org/10.23687/197171a9-9d38-42bf-8a98-891f35f6f539.Colonization of hosts by bark beetles is generally mediated by aggregation pheromones. Species competing for the same resource can limit interspecific interactions and maintain reproductive isolation by using different pheromones. In the southern United States, 3 sympatric species of Ips breed in pine hosts, each with a different pheromone blend. Ips avulsus (Eichhoff) uses ipsdienol and lanierone; Ips calligraphus (Germar) uses ipsdienol, cis-verbenol, and trans-verbenol; and Ips grandicollis (Eichhoff) uses ipsenol. Different species can also minimize cross-attraction by using different enantiomeric ratios of the same pheromones. Studies on the enantiomeric ratio of ipsdienol used by I. avulsus have come to contradictory conclusions in part because of geographic and seasonal variation. There is growing evidence that semiochemical context, in the form of different co-baits used in trapping experiments, may also play a role in the responses of I. avulsus to enantiomeric ratios of ipsdienol. We conducted a trapping study at 2 locations with traps baited with (+)-ipsdienol or racemic ipsdienol and co-baited with ipsenol, lanierone, or both ipsenol and lanierone. We found context-dependent effects of both lanierone and ipsenol on the response of I. avulsus to ipsdienol. We suggest that responses to different bait and co-bait combinations may have been shaped by different types of interactions such as the absence of conspecifics or a related species, or the presence of beneficial or antagonistic interspecific interactions.The Louisiana State University AgCenter for funding. Open Access was provided by Natural Resources Canada.https://academic.oup.com/ee2024-10-03hj2023Forestry and Agricultural Biotechnology Institute (FABI)Zoology and EntomologySDG-15:Life on lan

Mechanisms that influence sex ratio variation in the invasive hymenopteran Sirex noctilio in South Africa

Sirex noctilio is an economically important invasive pest of commercial pine forestry in the Southern Hemisphere. Newly established invasive populations of this woodwasp are characterized by highly male‐biased sex ratios that subsequently revert to those seen in the native range. This trend was not observed in the population of S. noctilio from the summer rainfall regions in South Africa, which remained highly male‐biased for almost a decade. The aim of this study was to determine the cause of this persistent male bias. As an explanation for this pattern, we test hypotheses related to mating success, female investment in male versus female offspring, and genetic diversity affecting diploid male production due to complementary sex determination. We found that 61% of females in a newly established S. noctilio population were mated. Microsatellite data analysis showed that populations of S. noctilio from the summer rainfall regions in South Africa are far less genetically diverse than those from the winter rainfall region, with mean Nei's unbiased gene diversity indexes of 0.056 and 0.273, respectively. These data also identified diploid males at low frequencies in both the winter (5%) and summer (2%) rainfall regions. The results suggest the presence of a complementary sex determination mechanism in S. noctilio, but imply that reduced genetic diversity is not the main driver of the male bias observed in the summer rainfall region. Among all the factors considered, selective investment in sons appears to have the most significant influence on male bias in S. noctilio populations. Why this investment remains different in frontier or early invasive populations is not clear but could be influenced by females laying unfertilized eggs to avoid diploid male production in populations with a high genetic relatedness.The Tree Protection Cooperative Programme (TPCP), the Department of Agriculture, Forestry and Fisheries (DAFF), and the National Research Foundation (NRF) of South Africa.http://www.ecolevol.orgam2020BiochemistryForestry and Agricultural Biotechnology Institute (FABI)GeneticsMicrobiology and Plant PathologyZoology and Entomolog