Selecting biological control agents
Predicting direct non-target impacts
Modelling non-target impacts
Phenology models often use the thermal requirements for development of an insect to predict the duration and timing of life stages in a novel environment (Barlow et al. 1994, Kean and Kumarasinghe 2007). Several phenology modelling approaches have been advanced to inform the risk of species introductions. Circle map analysis (Gurney et al. 1992, Powell and Logan 2005) was used to assess the ability of the parasitoid Microctonus aethiopoides to survive and persist in nontarget native weevil hosts in Otago. Logged air and litter temperatures from three tussock grassland sites were used together with parasitoid development rates (Goldson et al. 1990) to show that 2-3 parasitoid generations were possible and that resident parasitoids were unlikely to be present as potentially cold-susceptible pupae and adults in winter. However, depending on the timing of introduction, survival of first generation immigrants may be unlikely. Nevertheless, the models suggest that there are no major temperature constraints on the ability of M. aethiopoides to parasitise nontarget weevils in mid-altitude tussock grasslands. This contributes to the understanding of this system, which has been an influential case study for understanding nontarget effects of BCAs.
Another use for phenology modelling in estimating likely impacts is to examine the generation time of a natural enemy relative to that of its host (generation time ratio, GTR). It has been shown that for aphids and their predators GTR is a strong predictor of host suppression (Kindlmann and Dixon 1999). The theory has also been applied to parasitoid-host systems (Mills 2006), and the success and failure of some classical biological control introductions to New Zealand have been assessed in terms of their GTR (Barlow et al. 2002). Preliminary work has shown that the thermal development and diapause requirements of BCAs and their hosts can be used to estimate the GTRs on a spatially-explicit basis, potentially identifying areas of high and low likely impacts. Further work is needed to validate the GTR hypothesis in this context.
Microctonus hyperodae parasitising the Argentine stem weevil, Listronotus bonariensis.
© Copyright AgResearch, used with permission.
Phenology models may also be used to assess the likely synchrony of BCAs with their potential hosts. This has particular potential for identifying periods of high risk of nontarget attack by BCAs. For example, Barlow et al. (1994) developed a phenological model to help plan and monitor the classical biological control introduction of the parasitoid Microctonus hyperodae against the Argentine stem weevil, Listronotus bonariensis, in New Zealand. The model also suggested that parasitoid adults would be likely to peak in spring at a time when relatively few adult weevils would be available for attack, and this has subsequently been shown to occur in the field (Goldson et al. 1998, Phillips et al. 1998). Historical records of nontarget pasture weevils have been used to map the seasonal abundance of these species in relation to M. hyperodae and L. bonariensis. This suggests that the risk of nontarget attack during the spring may be relatively high, especially for the more abundant species at this time, Steriphus variabilis in Canterbury and Irenimus aequalis in the Waikato. Indeed, low levels of parasitism of these species by M. hyperodae have been observed at these sites (Barratt et al. 1997, Barratt et al. 2000). This work demonstrates the potential for phenology models for introduced species, together with knowledge of resident species' populations, to predict when nontarget attacks might occur, and thereby guide monitoring and management.
Barlow N.D., Goldson S.L. and McNeill M.R. (1994). A prospective model for the phenology of Microctonus hyperodae (Hymenoptera: Braconidae), a potential biological control agent of Argentine stem weevil in New Zealand. Biocontrol Science and Technology 4: 375-386.
Barlow N.D., Kean J.M. and Goldson S.L. (2002). Biological control lessons from modeling of New Zealand successes and failures. Proceedings of the First International Symposium on Biological Control of Arthropods: 105-107.
Barratt B.I.P., Evans A.A., Ferguson C.M., Barker G.M., McNeill M.R. and Phillips C.B. (1997). Laboratory nontarget host range of the introduced parasitoids Microctonus aethiopoides and Microctonus hyperodae (Hymenoptera: Braconidae) compared with field parasitism in New Zealand. Environmental Entomology 26: 694-702.
Barratt B.I.P., Evans A.A., Ferguson C.M., McNeill M.R. and Addison P. (2000). Phenology of native weevils (Coleoptera: Curculionidae) in New Zealand pastures and parasitism by the introduced braconid, Microctonus aethiopoides Loan (Hymenoptera: Braconidae). New Zealand Journal of Zoology 27: 93-110.
Goldson S.L., Proffitt J.R. and Baird D.B. (1998). Establishment and phenology of the parasitoid Microctonus hyperodae (Hymenoptera: Braconidae) in New Zealand. Environmental Entomology 27: 1386-1392.
Goldson S.L., Proffitt J.R. and McNeill M.R. (1990). Seasonal biology and ecology in New Zealand of Microctonus aethiopoides (Hymenoptera: Braconidae), a parasitoid of Sitona spp. (Coleoptera: Curculionidae), with special emphasis on atypical behaviour. Journal of Applied Ecology 27: 703-722.
Gurney W., Crowley P. and Nisbet R. (1992). Locking life-cycles onto seasons: Circle-map models of population dynamics and local adaptation. Journal of Mathematical Biology 30: 251-279.
Kean J.M. and Kumarasinghe L. (2007). Predicting the seasonal phenology of fall webworm (Hyphantria cunea) in New Zealand. New Zealand Plant Protection 60: 279-285.
Kindlmann P. and Dixon A.F.G. (1999). Generation time ratios - determinants of prey abundance in insect predator-prey interactions. Biological Control 16: 133-138.
Mills N.J. (2006). Accounting for differential success in the biological control of homopteran and lepidopteran pests. New Zealand Journal of Ecology 30: 61-72.
Phillips C.B., Proffitt J.R. and Goldson S.L. (1998). Potential to enhance the efficacy of Microctonus hyperodae Loan. Proceedings of the New Zealand Plant Protection Conference 51: 16-22.
Powell J.A. and Logan J.A. (2005). Insect seasonality: circle map analysis of temperature-driven life cycles. Theoretical Population Biology 67: 161-179.
Detailed population models