Scotland aims to become nature positive by 2030 and to restore biodiversity by 2045. To track progress, it needs monitoring that can measure species diversity and habitat health across the whole country.

NatureScot, SEPA and the Scottish Government’s Marine Directorate worked with NatureMetrics to test eDNA as a national monitoring tool. We combined eDNA with machine learning across four of Scotland’s key habitats. From 358 samples, we detected around 9,000 species and showed that eDNA can classify habitat condition, map species distributions and track restoration at scale. The work gives Scotland a blueprint for adding eDNA to its national biodiversity monitoring and reporting.

Conventional monitoring methods are valuable, but they can’t deliver the scale or coverage needed to assess biodiversity across a whole nation.

The partners needed an eDNA-based framework that could:

• Measure biodiversity and habitat condition across Scotland’s land and water ecosystems
• Fill critical data gaps and complement existing survey methods
• Support post-2020 national biodiversity reporting
• Inform conservation, restoration and ongoing monitoring
• Help Scotland meet its 2030 nature positive and 2045 biodiversity restoration targets

• Surveys across four habitats: working alongside project partners, NatureMetrics carried out eDNA surveys in marine lochs, freshwater lochs, woodlands and peatlands.
• Advanced lab analysis: we processed 358 samples using custom eDNA metabarcoding assays, bioinformatics pipelines and statistical analyses.
• Machine learning for habitat condition: we used state-of-the-art machine learning to classify the condition of each habitat.
• Reports for national use: we produced a series of custom reports to support integrating eDNA into Scotland’s national biodiversity assessment and reporting.

eDNA detected around 9,000 species across the sampled ecosystems, including threatened, invasive and indicator species.

The results showed that eDNA can:

• Outperform conventional methods for characterising ecological communities
• Measure ecological condition sensitively using novel bioindicators
• Classify sites by habitat status, for example degraded or restored, based on the species detected
• Map species distributions cost-effectively at regional scale

In marine environments, eDNA also compared favourably with traditional methods for assessing sediment quality.

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A scalable tool for national monitoring
With simple, standardised sampling, eDNA can survey whole ecosystems and detect species that are hard to find with other methods.

A national first
The machine learning restoration tracking model, which classifies habitat condition, is one of the first of its kind applied at national scale. This puts Scotland at the forefront of eDNA-based biodiversity monitoring.

Tracking progress over time
Repeat surveys can track changes in biodiversity and conservation status and map species distributions. This gives Scotland the evidence it needs for its 2030 and 2045 nature targets.

A blueprint for other nations
The findings offer a model for other countries looking to build eDNA into their biodiversity reporting frameworks.

Explore the official SEPA reports here: Our research | Beta | SEPA | Scottish Environment Protection Agency