Environmental DNA (eDNA) as a Transformative Tool for Biodiversity Monitoring: Applications, Methods, Challenges and Future Directions
DOI:
https://doi.org/10.71317/kjard.2.4.2026.484Keywords:
eDNA, Biodiversity monitoring, Metabarcoding, Next-generation sequencing, Species detectionAbstract
Every organism leaves a trace of itself behind, through mucus, waste, gametes, shed skin cells, or decaying tissue, in the form of genetic material known as environmental DNA (eDNA). Over the past decade, this genetic residue has become a valuable, non-invasive, and relatively inexpensive tool for tracking biodiversity across aquatic, terrestrial, and even airborne ecosystems. This review examines the core principles behind eDNA-based research, along with the methods used to collect and analyse it, its growing range of applications, the challenges that still limit its use, and where the field is likely headed next. Samples taken from water, soil, sediment, or air can be processed through techniques such as quantitative PCR (qPCR), droplet digital PCR (ddPCR), and next-generation sequencing (NGS)-based metabarcoding, all of which allow researchers to detect and track species without ever having to see or capture them directly. These tools have opened up a wide range of practical uses, from catching invasive species early, to tracking rare and endangered wildlife, surveying fish and amphibian populations, conducting large-scale marine biodiversity assessments, supporting fisheries management, monitoring pathogens in aquaculture systems, and even studying disease spread through wastewater. Still, the technology comes with its own set of hurdles. DNA can break down quickly depending on environmental conditions, samples can produce false positives when genetic material drifts downstream from its source, reference databases are often incomplete, and estimating how many individuals of a species are actually present remains difficult. Even so, as molecular techniques continue to improve, reference libraries grow more comprehensive, and eDNA data gets combined with machine learning, remote sensing, and ecological modelling, this approach is steadily becoming one of the most important tools available for biodiversity assessment, ecological monitoring, and conservation planning.
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Copyright (c) 2026 Azmat Ali, Taj Ali Shah, Muhammad Alam (Author)

This work is licensed under a Creative Commons Attribution 4.0 International License.



