Can Environmental DNA Benthic Macroinvertebrates Surveys Replace Microscopy?

This review asserts that molecular monitoring tools can effectively track the spatiotemporal dynamics of river ecosystems. Historically, however, mapping the biodiversity of these waters was a labour-intensive ordeal, requiring taxonomists to spend countless hours hunched over microscopes to identify specimens based on physical traits. This morphological method, though slow, provided the foundational data for our current ecological theories.

These results were observed under controlled laboratory conditions, so real-world performance may differ.

Validating Environmental DNA Benthic Macroinvertebrates Data

The transition to environmental DNA benthic macroinvertebrates analysis represents a significant shift in methodology. The review highlights that while eDNA is non-invasive and highly sensitive, current research focuses too heavily on optimising sampling protocols rather than answering fundamental ecological questions. Consequently, broader ecological investigations remain fragmented. We have amassed data, yet it remains unresolved whether the community ecology theories built on decades of morphological classification hold true when the data source changes to molecular signals.

A significant technical blind spot arises regarding the reliability of reconstruction. The source text notes that while eDNA offers high sensitivity, 'methodological constraints' persist that challenge our ability to perfectly mirror traditional findings. Unlike a taxonomist who classifies organisms based on established physical structures, eDNA relies on detecting molecular traces. The review indicates that we have not yet confirmed if these molecular signals can reliably reconstruct the complex benthic community structures previously defined by physical identification. Until these methodological limitations are resolved, the data may not fully support existing ecological frameworks.

From Description to Mechanism

The authors note that while empirical progress is evident, the field is largely stuck in a descriptive phase. We can list what DNA is in the water, but we often lack the mechanistic understanding to link these signals to ecosystem functions as reliably as traditional methods. The review suggests that future efforts must prioritise long-term monitoring networks and the integration of multidimensional data. Only by deeply engaging with community ecology theories can we bridge this gap, moving eDNA from a tool for list-making to a source of scientific support for the precise management of river ecosystems.