Research topics Publications
Measuring, modelling and forecasting
Simultaneous estimation of Pinus nigra Arn. ssp. salzmannii natural regeneration emergence and survival through lifetime analysis
We developed a climatic sensitive model to simultaneously estimate the emergence and survival of Corsican pine natural regeneration in Spain through lifetime analysis. This work is highly relevant for managing the species in a context of climate change. Our modelling approach represents a breakthrough in the state of the art of lifetime analysis.
The National Forest Estate Biodiversity Index
Forest Research, Forestry & Land Scotland and Forestry England have co-developed an evidence based, repeatable approach for assessing the biodiversity potential of the National Forest Estate. Several extent, condition, connectivity and diversity metrics are measured and aggregated into a Combined Biodiversity Index. An online, interactive tool allows users to explore mapped scores.
Dynamic top height models for several major forest tree species in Great Britain
New dynamic top height models for 10 major species in Great Britain for pure, even-aged stands
Forest damage by deer depends on cross‐scale interactions between climate, deer density and landscape structure
This journal paper investigates the factors that drive deer damage to woodlands using the National Forest Inventory sample square data. We found that the likelihood of damage to trees depends on cross-scale interactions between climate, deer density and landscape structure. The complex interactive effects uncovered are difficult to interpret. We therefore provide an interactive Deer Damage Tool for practitioners to visualize how afforestation is likely to influence the probability of deer damage in different forests and regions across Britain.
A sequential multi-level framework to improve habitat suitability modelling
We provide a sequential framework for improved multi-scale habitat suitability modelling or species distribution modelling. We apply it to the lesser horseshoe bat in Britain to demonstrate its improved accuracy and ecological inference.
Predicting hedgehog mortality risks on British roads using habitat suitability modelling
An analysis of citizen science hedgehog roadkill data has revealed why, when and where vehicle-hedgehog collisions are most likely to occur. The approach involved a multi-scale habitat suitability model. Suburban areas with mixtures of urban and grassland were found to be roadkill hotspots.
BioCoRe: An interactive/adaptable landscape ecology approach for targeting restoration
How we manage priority habitats within increasingly fragmented landscapes is a critical conservation issue. Practitioners and policy makers are often faced with the dilemma of deciding where to focus limited…
Forestry Facts & Figures 2019
A summary of statistics about woodland and forestry in the UK.
Exploring changes in ecosystem services under varying scenarios
Exploration of the resilience of woodlands to future change by assessing how ecosystem service values and natural capital stocks of woodlands may be affected by change through the application of the UK National Ecosystem Assessment (UK NEA) scenarios and different management approaches, e.g. forest diversification through the application of forest management alternatives
Detecting young trees from space
FR have established how to detect young trees from space using synthetic aperture RADAR and machine learning techniques. This will support the monitoring of the planting of tens of thousands of restock sites and new woodland across Britain. In searching for a solution researchers hypothesised that even if the trees are too small to see, maybe we could ‘feel’ them using Synthetic Aperture Radar (SAR). A different technique to utilising optical data, SAR provides ‘fuzzy’ data on the presence of objects, their size, orientation and texture. The research found that this was possible and data on whether sites had tree cover or not has been derived for extensive areas of Britain and NFI are working to operationalise the process.