Biomonitoring Breakthrough: DNA Analysis Uncover Local Biodiversity Changes Hidden in Plain Sight
The study leveraged samples from the STREAM (Sequencing The Rivers for Environmental Assessment and Monitoring) program — a community-based biomonitoring network — focusing on benthic macroinvertebrates from sites across the Canadian Rockies.
- CBG Media & Communications
- July 4, 2025
A new study published in BMC Biology unveils a transformative method for tracking biodiversity with unprecedented resolution — capable of detecting not just which species are present, but how local populations are shifting across landscapes.
The research, led by scientists from the University of Guelph and the University of New Brunswick, introduces Biomonitoring 2.0 Refined, an enhanced approach to environmental DNA (eDNA) metabarcoding. By analyzing subtle genetic variation within species (intraspecific diversity), researchers can now trace how organisms respond to natural barriers like mountain ranges — information critical to conservation planning, ecological assessments, and habitat restoration.
“Conventional tools tell us which species or groups of species (genera) are present, but often miss the local nuances that matter most for conservation,” says Dr. Mehrdad Hajibabaei, co-lead author and professor at the Centre for Biodiversity Genomics. “This new method lets us zoom in and see biodiversity change in action — at the level of populations of species or cryptic species.”
The study leveraged samples from the STREAM (Sequencing The Rivers for Environmental Assessment and Monitoring) program — a community-based biomonitoring network — focusing on benthic macroinvertebrates from sites across the Canadian Rockies. By targeting two non-overlapping regions of mitochondrial DNA, the team demonstrated that genetic patterns reliably reflected geographical separation, even within individual species. “Mountains act as natural barriers to movement,” explains Hajibabaei. “We were able to show that even small differences in DNA from insect populations on either side of the Rockies matched those physical barriers — a powerful signal for local change.”
What makes the approach especially valuable is its scalability and reproducibility. The researchers used multiple genetic markers to confirm results and applied strict filtering to separate real biological signals from sequencing noise — setting a new benchmark for precision in eDNA analysis.
With governments, regulators, and industries increasingly relying on biodiversity data for environmental impact assessments and sustainability planning, the implications are far-reaching.
“This isn’t just a scientific advance — it’s a tool we need right now,” adds Dr. Hajibabaei. “At a time when ecosystems are under intense pressure, we need fast, scalable, and fine-grained biodiversity data to guide decisions. Biomonitoring 2.0 Refined delivers just that.”
The study points the way forward for integrating genetics into next-generation environmental monitoring systems, offering insights that were previously difficult — or impossible — to obtain using traditional ecological methods.
