The complexities of knowing what it is you are trapping

The effectiveness of any trapping system is highly dependent on the ability to accurately identify the specimens collected. For many fruit fly species, accurate identification (= diagnostics) using morphological or molecular techniques is relatively straightforward and poses few technical challenges. However, nearly all genera of pest tephritids also contain groups of species where single, stand-alone tools are not sufficient for accurate identification: such groups include the Bactrocera dorsalis complex, the Anastrepha fraterculus complex and the Ceratitis FAR complex. Misidentification of high-impact species from such groups can have dramatic consequences and negate the benefits of an otherwise effective trapping program. To help prevent such problems, this chapter defines what is meant by a species complex and describes in detail how the correct identification of species within a complex requires the use of an integrative taxonomic approach. Integrative taxonomy uses multiple, independent lines of evidence to delimit species boundaries, and the underpinnings of this approach from both the theoretical speciation literature and the systematics/taxonomy literature are described. The strength of the integrative approach lies in the explicit testing of hypotheses and the use of multiple, independent species delimitation tools. A case is made for a core set of species delimitation tools (pre- and post-zygotic compatibility tests, multi-locus phylogenetic analysis, chemoecological studies, and morphometric and geometric morphometric analyses) to be adopted as standards by tephritologists aiming to resolve economically important species complexes. In discussing the integrative approach, emphasis is placed on the subtle but important differences between integrative and iterative taxonomy. The chapter finishes with a case study that illustrates how iterative taxonomy applied to the B. dorsalis species complex led to incorrect taxonomic conclusions, which has had major implications for quarantine, trade, and horticultural pest management. In contrast, an integrative approach to the problem has resolved species limits in this taxonomically difficult group, meaning that robust diagnostics are now available.

Zygosity diagnosis in the absence of genotypic data: An approach using latent class analysis

For zygosity diagnosis in the absence of genotypic data, or in the recruitment phase of a twin study where only single twins from same-sex pairs are being screened, or to provide a test for sample duplication leading to the false identification of a dizygotic pair as monozygotic, the appropriate analysis of respondents' answers to questions about zygosity is critical. Using data from a young adult Australian twin cohort (N = 2094 complete pairs and 519 singleton twins from same-sex pairs with complete responses to all zygosity items), we show that application of latent class analysis (LCA), fitting a 2-class model, yields results that show good concordance with traditional methods of zygosity diagnosis, but with certain important advantages. These include the ability, in many cases, to assign zygosity with specified probability on the basis of responses of a single informant (advantageous when one zygosity type is being oversampled); and the ability to quantify the probability of misassignment of zygosity, allowing prioritization of cases for genotyping as well as identification of cases of probable laboratory error. Out of 242 twins (from 121 like-sex pairs) where genotypic data were available for zygosity confirmation, only a single case was identified of incorrect zygosity assignment by the latent class algorithm. Zygosity assignment for that single case was identified by the LCA as uncertain (probability of being a monozygotic twin only 76%), and the co-twin's responses clearly identified the pair as dizygotic (probability of being dizygotic 100%). In the absence of genotypic data, or as a safeguard against sample duplication, application of LCA for zygosity assignment or confirmation is strongly recommended.