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Research
Increasing engagement with plant biosecurity certification
This research aims to add to our understanding of the factors related to businesses in the plant retail and landscape and design sectors engaging with biosecurity certification based on the Plant Health Management Standard, and to co-develop interventions to increase this engagement.
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Research
Broadening participation in citizen science for early warning of tree pests and diseases
Increased participation in tree health reporting could improve our ability to plan for, prevent or mitigate tree health risks. This project investigates opportunities to increase participation in tree health recording, focusing on existing well-used apps, and to utilise these data within Britain’s official reporting route, Tree Alert.
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Research
NCEA eDNA Soil Biodiversity
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...
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Research
NCEA Expansion of International Co-operative Programme Plots
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...
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Research
The NCEA Trees Outside Woodland survey
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.
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Research
NCEA People Pressure
The NCEA People Pressure project tested remote technologies to monitor woodland recreation and assess how forest use contributes to threats, social benefits and landscape understanding within England’s National Forest Inventory.
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Research
NCEA Air Quality
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...
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Research
NCEA DNA Woodland Canopy
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...
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Research
NCEA eDNA Woodland Mammals
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....
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Research
NCEA Soil Condition and Health
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.
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Research
Soil Biodiversity Monitoring: Investigating a novel remote ecoacoustic-based methodology
Ecoacoustics is being explored as a tool for monitoring soil biodiversity by listening to below‑ground soundscapes associated with forest health. A newly developed acoustic pitfall trap captures invertebrate movement sounds using low‑power sensors and LoRaWAN transmission, providing a low‑impact and non-destructive approach to assessing hidden soil life and ecosystem condition...
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Research
MESOSCAN: Machine learning for soil biodiversity identification
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).