This dataset contains inputs for wildfire simulations in Fire Dynamics Simulator (FDS) in forest environments. It includes five segmented point clouds in LAS format, representing different fuel classes from a forest plot, each with an associated BDF (Bulk Density Files) file. The forest plot consists of a 40 x 40 m Pinus ponderosa plot scanned with a Riegl-VZ400i in Sycan Marsh, Oregon, USA, during the summer of 2019. The dataset also contains Fire Dynamics Simulator (FDS) input files detailing the configuration for three separate simulations. These resources support modelling and simulation efforts to better understand fire behaviour in forest ecosystems. Full details about this dataset can be found at https://doi.org/10.5285/467a735f-b03c-4c30-8781-82f0e11aec28

Here we collate a database of all known birds, bryophytes, fungi, invertebrates, lichens and mammals that use Sitka spruce (Picea sitchensis) in the UK. Sitka spruce is the most commonly planted commercial tree species in the UK. In total 564 species are listed in the database. For each species we provide a level of association with Sitka spruce, ranging from obligate (only found on Sitka spruce) to cosmopolitan (found on a wide range of other tree species). Data on the ecology of each Sitka spruce associated species were collated: part of tree used, and use made of tree (feeding, roosting, breeding). Data on use or otherwise of 34 other tree species were also collated for each of the 564 species. Full details about this dataset can be found at https://doi.org/10.5285/1ce52c10-e3ab-4996-b9b7-052c70b3c1ba

This dataset contains forest structure measurements for a wooded area where the liana Hendra helix (common ivy) is present. The dataset comprises two overlapping 3D point clouds for a small wooded area covering nearly 18000 m2 of Bramcote Hills Park (Nottinghamshire, UK) for a sample of trees infested with liana as well as a non-infested sample of trees. This datasets was acquired using a terrestrial Light Detection And Ranging (LiDAR) scanner on 13 January 2023, as part of a study assessing the diversity and composition of soil and litter dwelling organisms associated with liana infestations within forests. The work was supported by the Natural Environment Research Council (Grant NE/X018083/1). Full details about this dataset can be found at https://doi.org/10.5285/174ef670-6db9-4fb9-9961-27b2cee57adc

This dataset scores the relative risks of Phytophthora x alni infection for 50034 fragments in Scotland identified as containing any of the three alder species susceptible to the pathogen (common alder, Italian alder and grey alder). Fragment risk scores integrate climate suitability (using pathogen-specific temperature-dependent growth curves and a relative humidity threshold), proximity to rivers/flooding, connectivity to other alder fragments via flood events and recent planting of alder under forestry grant schemes. Data and models used to score risk factors are variable in their time frames, but are broadly representative of the period from 2013 to 2023. Phytophthora disease of alder has been widespread in southern England since at least 1995 and became more prevalent in annual surveys between 1994 and 2003. It has been confirmed at several riparian sites in Scotland. P. x alni diseases are reported only from the alder genus. Full details about this dataset can be found at https://doi.org/10.5285/824f9ba8-7d1c-4a82-b5ec-a4f850f1d370

This dataset maps the risks of Phytophthora ramorum infection for 79062 larch fragments identified in Scotland, of which 79060 were assigned a risk score. Two fragments without climate and/or habitat suitability scores were excluded. Fragment risk scores integrate multiple risk factors. The primary risk factor is climate suitability for P. ramorum using pathogen-specific temperature-dependent growth curves and a relative humidity threshold. Other risk factors integrated are proximity to larch/infected larch within 500m or 5000m and other (non-Larch) wider environment infections within 1500m. Presence of alternative hosts are scored using habitat suitability within the fragment for sporulating hosts (Vaccinium myrtillus, V. vitis-idaea, Acrostaphylos uva-versi) and the reservoir host Rhododendron ponticum. Additionally, proximity to inspected premises with confirmed infections and the presence of water courses are also assessed. The maximum possible risk score for a larch fragment is 12. Fragments were also classified as low, medium or high risk. Full details about this dataset can be found at https://doi.org/10.5285/f6809e00-91cb-494d-babd-5d60d938ad97

This dataset maps the potential vulnerability to Phytophthora pinifolia infection for 82 core fragments of the Caledonian Pinewood Inventory (CPI) in Scotland. Fragment risk scores integrate climate suitability for pathogen growth, proximity to other pine fragments and inspected premises and recent planting under forestry grant schemes. Data and models used to assess risks are variable in their time frames, but are broadly representative of the period from 2013 to 2023. The risk maps for Caledonian Pine assess the vulnerability of CPI fragments, if P. pinifolia were to arrive, and the most probable areas of introduction and establishment. P. pinifolia has not been detected in the UK but is on the UK Plant Health Risk Register. All known host species are within the genus Pinus, either recorded as naturally occurring disease affecting the shoots and needles of Pinus radiata, or established through pathogenicity trials on other species within the genus, albeit with varying levels of susceptibility. The only known source region for the pathogen is Chile. P. pinifolia has been ranked 8th among Phytophthora species mostly likely to arrive among the 109 Phytophthora species assessed, with this higher risk predominantly driven by the model component describing climatic similarity between forest, agricultural and urban habitats in Chile and the UK. A Rapid Pest Risk Analysis for P. pinifolia considered it unlikely to enter the UK due to restrictions on import of living pine species from non-EU countries, though transport may still be possible with other, unknown, hosts. Full details about this dataset can be found at https://doi.org/10.5285/ddee75ae-2ad0-4d16-81a9-20928d89e872

This dataset is a ranked list of risks to Scotland from 196 Phytophthora species, including most of the approximately 240 formally described or provisionally named species in the genus globally. Arrival and establishment risks are scored and joined with information on surveillance of known hosts within inspected premises in Scotland (introduction risks). Potential impacts are scored using information on global Phytophthora-host interactions extracted from a global database of Phytophthora records to identify at risk hosts and score the level of threat to hosts and habitats within Scotland. The ranked list was developed to support prioritisation among future Phytophthora threats to Scotland. All risks were scored by the UKCEH project team, informed by a self-completion survey and two workshops with 15 stakeholders from across Scotland's plant health sector, including forestry, conservation, horticulture, and government agencies. Full details about this dataset can be found at https://doi.org/10.5285/72e8f817-01a6-42d2-b187-a5ebf43853a1

This dataset maps the risks of Phytophthora pluvialis infection for 11098 forest fragments in Scotland identified as containing the known hosts Douglas fir or western hemlock. Key risk factors and their scoring were agreed with 15 cross-sectoral stakeholders through a self-completion survey and two workshops. Fragment risk scores integrate climate suitability and proximity to other fragments/infected sites, recent planting of these hosts (forestry grant schemes), inspected premises and water courses. Infections of P. pluvialis have been reported on Douglas fir and Western hemlock in Cornwall, Devon, Cumbria, Wales and Scotland since the outbreak was first detected in 2021. Outside of the UK, pine species (Pinus radiata, P. strobus, P. patula) are also susceptible to the pathogen. The scored fragment data were intersected with the boundaries of conservancies, local authorities and active P. pluvialis demarcated areas to summarise the distribution of risks across regions in Scotland. Full details about this dataset can be found at https://doi.org/10.5285/921fcc2e-7491-4058-a21b-3d1de0be1507