Strenghts and limitations of the dDNA metabarcoding approach
The dDNA approach offers several notable advantages over traditional
methods used for monitoring tropical freshwater communities. First, it
is cost-effective and easy to implement in the field, requiring minimum
equipment. Using just a few baited traps and net hauls, we were able to
collecte large numbers of shrimp (>30 specimens for M.
olferssi and M. brasilience ) within just a few days along
riverbanks and in rapid zones. Encapsulated in the stomach, dDNA samples
can be easily preserved in ethanol with minimal contamination risk until
extraction in the laboratory (Siegenthaler et al., 2019). This makes it
especially suitable for tropical environments, where logistical
challenges often hinder extensive sampling campaigns. This method avoids
the capture and handling of fish, which is particularly relevant in
protected areas or when monitoring threatened species. The shrimp used
as biosamplers are highly abundant and occupy basal levels of food webs,
meaning that collecting a few dozen individuals likely has a limited
impact on population dynamic and ecosystem stability.
Another significant strength of this method is its remarkable efficiency
and low selectivity. The metabarcoding analysis shrimp dDNA enabled the
detection of as many species as an intensive 10-days deep inventory of
the study area. This approach uncovered nearly three times more species
than the 2022 WFD survey and exceeded the total number of species
recorded over the 11 years of WFD campaigns. As expected, given the
generalist and opportunistic feeding behaviours of these detritivorous
organisms, dietary DNA analysis detected a broad spectrum of species in
terms of size. Indeed, our analyses revealed no significant difference
in the size ranges of species identified through using dDNA and those
recorded during our deep inventory. This suggests that the dDNA
metabarcoding of detrivorous crustaceans does not present any particular
size-related detection bias, in contrast to WFD gillnet-based campaigns
that preferentially captured large fish. Dietary DNA analysis also
detected elusive species that live in specific microhabitats and are
rarely captured when using traditional sampling methods. For instance,Cyphocharax biocellatus and Jupiaba abramoides are small,
abundant species inhabiting shallow waters along riverbanks or
vegetation in fast-flowing zones were detected using dDNA but never
during WFD campaigns using gillnets. However, nearly 20% of the species
from the deep inventory were absent from the shrimp dDNA samples. Some
of theses species (e.g. Anchovia surinamensis or Moenkhausia aff
grandisquamis ) are relatively common but undetected due to gaps in the
reference barcoding databases. Other species are rarer, with low capture
rates and increasing the sampling effort with additional biosampler
specimens might help detect them. The use of easily accessible,
generalist invertebrate species for large-scale monitoring has already
been demonstrated in other ecosystems. For instance, dDNA analysis of
brown shrimp (Crangon crangon ) detected twice as many species
than traditional net surveys in coastal marine areas (Siegenthaler et
al., 2019). Similarly, molecular gut content analysis of mussels has
proven effective in monitoring planktonic communities, identifying a
broad range of dietary taxa that mirror the diversity in surrounding
water samples (Weber et al., 2023).
The dDNA approach is also notable for its high taxonomic resolution
combined with its minimal reliance on taxonomic experts. Despite the
small size of the DNA barcodes, we successfully identified most fish
taxa at the species level, with only minor corrections needed, primarily
due to recent taxonomic updates. This is a critical point because
taxonomic identification can be challenging in highly diverse
environments, especially when dealing with cryptic species complexes.
However, this success was greatly supported by the well-documented fish
fauna in French Guiana (Le Bail, 2012) and the availability of nearly
exhaustive barcoding reference databases. Accurate taxonomic assignment
through metabarcoding depends largely on the completeness and accuracy
of reference databases (Hilário et al., 2023; Keck et al., 2022) and
significant gaps still exist for tropical fish species (Marques et al.,
2021; Sales et al., 2018). This underscores why the development of
open-acess, highly-quality and complete reference databases has been
identified as the top priority for the field (Blackman et al., 2024).