7. Invasive arthropod species detection, identification and implications for island biodiversity
Non-native arthropod species within insular environments represent a fundamental dimension of the ongoing biodiversity crisis (Borges, Rigal, Ros-Prieto, & Cardoso, 2020). The typically depauperate biotas of islands contribute to increased sensitivity to invasive species when compared with continental areas (Bellard et al., 2017), and it is generally understood that early warning and rapid response to new arrivals is necessary to head off establishment and spread, highlighting a need for robust and rapid island monitoring (Borges et al., 2018). A strong argument for the continued effort toward global arthropod barcoding reference databases is the added value these can provide for HTS-based approaches for the biosurveillance of non-indigenous species. Traditional detection methods are expensive, prone to time lags, and require specialised expertise, creating a need for rapid and accurate biosurveillance tools, tailored to the needs of particular biogeographic regions (Westfall, Therriault, & Abbott, 2020). As reference barcode sequences accumulate globally for both recognised and potential arthropod pest species, HTS barcoding for biosurveillance becomes a more powerful alternative to traditional approaches. Even in the absence of reference sequences for taxonomic assignment, genetic signatures can be leveraged for the inference of probable non-native species. Using insects and spiders on the island of Moorea, Andersen et al. (2019) have demonstrated a novel approach to categorise species as being either likely native or likely non-native, based solely on measures of nucleotide diversity. When coupled with spatially structured and temporally replicated haplotype-level wocDNA metabarcoding, novel appearance and increasing site occupancy data could also potentially be leveraged to infer novel non-native species and range expansions. The advent of high-throughput multiplex HTS barcoding also allows for testing the resilience of natural habitats against invasive species. Baloğlu et al. (2018) showed that the rich chironomid midge fauna (ca. 300 spp) of a very small remnant of a swamp forest (90 ha) was resilient against invasion by ca. 50 species of “reservoir” chironomid midge species from three adjacent man made reservoirs: only 8 species accounting for ca. 3% of the 14,000 barcoded specimens were shared.
Well-inventoried island systems can be used to test fundamental invasive species theory (Schaefer, Hardy, Silva, Barraclough, & Savolainen, 2011) and, when coupled with temporal sampling, the dynamics of introduced arthropod species abundances can be used to guide management strategy (Matthews, Sadler, Carvalho, Nunes, & Borges, 2019). The often relatively simplified nature of island ecosystems provides opportunities for both island-wide and community-level sampling to contribute to a more general understanding of the properties and dynamics of introduced and invasive species (Borges et al., 2020). Schaefer et al. (2011) sampled the entire Azorean flora for a phylogenetic understanding of evolutionary relatedness as a predictor of invasion potential. In concert with mitogenome backbone trees (see section 1 above), similar opportunities arise for arthropod fractions of island biodiversity with HTS barcode data. Indeed, if combined with DNA sequence-based frameworks to assign likelihood for native or non-native species status, such as that of Andersen et al. (2019), spatially explicit HTS barcode data can address the uncertainty of species status for more robust inferences. Detailed sampling of arthropods to quantity functional trait structure in the Azores has revealed that, in agricultural landscapes, non-native species may contribute positively to the maintenance of some ecosystem functions (Rigal et al., 2018; Ferrante et al., 2022). Barcode reference libraries with relevant trait data, together with HTS barcoding of arthropods across comparable natural and agricultural gradients in other islands, provide a cost effective and logistically feasible pathway to assess the broader generality of these findings.