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Soil biodiversity underpins essential ecosystem functions and reflects woodland condition yet is difficult to monitor using traditional methods. Environmental DNA (eDNA) metabarcoding offers a scalable, non-invasive approach to assess fungi and invertebrates. Integrated into the National Forest Inventory, it will generate baseline data to track biodiversity patterns and woodland condition...

This project expanded Forest Research’s intensive forest monitoring network to seven sites, enabling assessment of environmental change impacts on riparian and ancient woodland. This data, analysed within the context of UK International Co-operative Programme (ICP) Forest network, will deepen understanding of forest ecosystems and strengthen the scientific basis for air‑pollution...

The NCEA Trees Outside Woodland (TOW) survey maps and assesses individual trees, small groups, and hedgerows across England. These non‑woodland trees support biodiversity, improve habitat links, store carbon, and help cool urban areas. This survey strengthens the monitoring and management of these important features.

The NCEA Air Quality project assesses data availability, suitability, and gaps to improve quantification of forests’ natural capital in air‑pollution mitigation and the impacts of pollutants on forest ecosystems. It supports modelling using long‑term monitoring and inventory datasets, and expands ongoing air‑pollution monitoring across Forest Research’s intensive ICP Forests Level...

Woodland canopy arthropods are sensitive indicators of ecological condition but are difficult to sample and identify at scale using traditional methods. DNA metabarcoding offers a cost‑effective alternative, enabling comprehensive biodiversity assessment. Integrated into the National Forest Inventory, it will generate baseline data to track spatial and temporal trends in arthropod...

This research project aimed to integrate eDNA metabarcoding into the National Forest Inventory survey to assess ecological condition through monitoring of woodland mammals. eDNA offers a non‑invasive, scalable alternative to traditional surveys by detecting species from environmental traces, providing an efficient, cost‑effective way to capture mammal diversity across woodland ecosystems....

A national assessment of forest soil condition integrating chemical, physical and biological indicators to inform soil health, ecosystem services, sustainable forest management and environmental policy.

This project aimed to overcome common challenges in the study of soil biodiversity in terms of taxonomy and sampling replication, with the development of a machine learning-based ‘MESOSCAN’ dataset and tool, for soil biodiversity identification (mesofauna).

Woodland water services improve water quality and reduce flood risk, but limited data restrict investment in new woodland. This project strengthens evidence by measuring water quality across diverse woodland streams in England, helping to quantify and value water improvements so woodland creation can be targeted where benefits are most needed.

​​Assessing changes in British woodland condition is essential for biodiversity, resilience, and statutory monitoring. These projects use scalable DNA and eDNA metabarcoding to monitor mammals, soil biodiversity, and canopy arthropods across England, overcoming the limitations of traditional methods and providing new insights into forest form and function through incorporation into...

This research project explores the ecological, social and economic dimensions of food forests (FF) in England and Wales. The research explored the benefits, opportunities and challenges associated with the establishment of FF and the potential to increase food production from FF in the UK. Three main categories of FF were...