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.