In support of the monitoring programme, the Welsh Government commissioned the UK Centre for Ecology and Hydrology, with support from the British Geological Survey and Natural Resources Wales, to develop an updated map of peat extent and condition for Wales. A full description and assessment of the peat map, including an analysis of current land-use and condition of peatlands, and their associated greenhouse gas emissions, are provided in Evans et al. (2015).

This map represents a considerable advance on previous attempts to map the deep peat resource of Wales (e.g. Taylor & Tucker, 1968) and yields a significantly larger estimate than that based on the Soil Survey of England and Wales alone (ca. 706 km2; ECOSSE, 2007). Another recent assessment of peat cover also utilised multiple data-sources (Vangeulova et al., 2012) but included the data from the Soil Survey of England and Wales, which were omitted from this study due to the scale of mapping, which tended to omit smaller peat units particularly in lowland areas, whilst over-estimating peat cover in some upland areas due to the merging of different soil types in mixed landscapes into peat-dominated soil associations.

The new map highlights the wide distribution of peatlands across much of Wales, with large areas of upland blanket bog in Northeast and North-central Wales (Migneint, Berwyn) and central Wales (Cambrian Mountains), as well as smaller areas of upland peat in and around the Brecon Beacons National Park. The new unified map also provides a much more detailed picture of the distribution of deep peat in the lowlands, many of which retain significant biodiversity interest. Large numbers of small peat units are found in many lowland areas of Wales, with the largest numbers mapped in Anglesey, Penllŷn, coastal Ceredigion, Pembrokeshire and Carmarthenshire. Larger lowland raised bogs occur at Cors Fochno on the Dyfi estuary, Cors Caron in Ceredigion, and Fenn’s and Whixall Moss on the border with Shropshire.

Living England is a multi-year project which delivers a broad habitat map for the whole of England, created using satellite imagery, field data records and other geospatial data in a machine learning framework. The Living England habitat map shows the extent and distribution of broad habitats across England aligned to the UKBAP classification, providing a valuable insight into our natural capital assets and helping to inform land management decisions. Living England is a project within Natural England, funded by and supports the Defra Natural Capital and Ecosystem Assessment (NCEA) Programme and Environmental Land Management (ELM) Schemes to provide an openly available national map of broad habitats across England.This dataset includes very complex geometry with a large number of features so it has a default viewing distance set to 1:80,000 (City in the map viewer).Process Description:A number of data layers are used to develop a ground dataset of habitat reference data, which are then used to inform a machine-learning model and spatial analyses to generate a map of the likely locations and distributions of habitats across England. The main source data layers underpinning the spatial framework and models are Sentinel-2 and Sentinel-1 satellite data from the ESA Copernicus programme, Lidar from the EA's national Lidar Programme and collected data through the project's national survey programme. Additional datasets informing the approach as detailed below and outlined in the accompanying technical user guide.Datasets used:OS MasterMap® Topography Layer; Geology aka BGS Bedrock Mapping 1:50k; Long Term Monitoring Network; Uplands Inventory; Coastal Dune Geomatics Mapping Ground Truthing; Crop Map of England (RPA) CROME; Lowland Heathland Survey; National Grassland Survey; National Plant Monitoring Scheme; NE field Unit Surveys; Northumberland Border Mires Survey; Sentinel-2 multispectral imagery; Sentinel-1 backscatter imagery; Sentinel-1 single look complex (SLC) imagery; National forest inventory (NFI); Cranfield NATMAP; Agri-Environment HLS Monitoring; Living England desktop validation; Priority Habitat Inventory; Space2 Eye Lens: Ainsdale NNR, State of the Bog Bowland Survey, State of the Bog Dark Peak Condition Survey, State of the Bog Manchester Metropolitan University (MMU) Mountain Hare Habitat Survey Dark Peak, State of the Bog; Moors for the Future Dark Peak Survey; West Pennines Designation NVC Survey; Wetland Annex 1 inventory; Soils-BGS Soil Parent Material; Met Office HadUK gridded climate product; Saltmarsh Extent and Zonation; EA LiDAR DSM & DTM; New Forest Mires Wetland Survey; New Forest Mires Wetland Survey; West Cumbria Mires Survey; England Peat Map Vegetation Surveys; NE protected sites monitoring; ERA5; OS Open Built-up Areas; OS Boundaries dataset; EA IHM (Integrated height model) DTM; OS VectorMap District; EA Coastal Flood Boundary: Extreme Sea Levels; AIMS Spatial Sea Defences; LIDAR Sand Dunes 2022; EA Coastal saltmarsh species surveys; Aerial Photography GB (APGB); NASA SRT (Shuttle Radar Topography Mission) M30; Provisional Agricultural Land Classification; Renewable Energy Planning Database (REPD); Open Street Map 2024.Attribute descriptions: Column Heading Full Name Format Description

SegID SegID Character (100) Unique Living England segment identifier. Format is LEZZZZ_BGZXX_YYYYYYY where Z = release year (2223 for this version), X = BGZ and Y = Unique 7-digit number

Prmry_H Primary_Habitat Date Primary Living England Habitat

Relblty Reliability
Character (12) Reliability Metric Score

Mdl_Hbs Model_Habs Interger List of likely habitats output by the Random Forest model.

Mdl_Prb Model_Probs Double (6,2) List of probabilities for habitats listed in ‘Model_Habs’, calculated by the Random Forest model.

Mixd_Sg Mixed_Segment Character (50) Indication of the likelihood a segment contains a mixture of dominant habitats. Either Unlikely or Probable.

Source Source

Description of how the habitat classification was derived. Options are: Random Forest; Vector OSMM Urban; Vector Classified OS Water; Vector EA saltmarsh; LE saltmarsh & QA; Vector RPA Crome, ALC grades 1-4; Vector LE Bare Ground Analysis; LE QA Adjusted

SorcRsn Source_Reason

Reasoning for habitat class adjustment if ‘Source’ equals ‘LE QA Adjusted’

Shap_Ar Shape_Area

Segment area (m2) Full metadata can be viewed on data.gov.uk.

This layer will help you identify some of the strategic opportunities in your area for positive change and work out plans with land managers to enhance carbon, whatever the current land use. Carbon abatement is the reduction in carbon dioxide presently being released to the atmosphere from the environment when land use and management are in conflict with the best carbon outcome. This layer compliments the carbon sequestration map and shows where different types of actions can be taken to maximise carbon storage and sequestration. The approach here has been to highlight the worst areas of the country for carbon loss and abatement potential. Where existing high quality semi natural habitat already exists there is likely to be opportunities to enhance carbon, but much of this is fine scale management decisions that a national data set cannot determine. So, a more precautionary approach has been applied that if a habitat presently exists on a site, land-use change has not been recommended. There will be places where an existing habitat could be enhanced or changed to another habitat to give carbon benefits. Many habitats have become degraded through management practices over time, such as drainage, which means it now sits in a lower carbon state & is losing carbon and as such has abatement potential such as conversion from a dry grassland habitat with drainage to much wetter fenland habitat. In the worse cases some habitats in our current priority habitat classification system are degraded versions of other habitats and have the potential to move between habitats and so abating carbon. This layer has made a broad assessment of which land use may be changed to an appropriate higher carbon variant. In the case of very productive grassland and pasture we have assumed only a change to high carbon management practices where clear abatement gains are present. This is because high value agricultural land is a key non-renewable resource which is needed for food security. In addition, such land generates a good economic revenue for agricultural goods.

This map was created differently to the others, by using a Python script to run the analysis. Firstly, a table was designed that looked at habitats and possible soil types they could develop upon. This was then used to create a logic table showing areas which were now not on suitable soil types, for example arable land on deep fen peat. Scoring was awarded from scientific review, using expert judgement by the team, and insights in developing the previous layers results, on the potential sequestration enhancement or land use of each type of land management action or change. All the technical information is available in the accompany technical report. The classes used in the abatement maps and models are shown in Table 1 with the Logic tables are found in -Appendix 4 Abatement logic rules in full technical report. Code/ Class / Notes 1/ Maintain - enhance existing habitats / Some of our existing habitats for example, blanket bog vegetation deep peat, are not in the best ecological condition they can be. This is particularly the case for peatlands and heather moorlands which have been drained to change blanket bog vegetation into heathland vegetation or to obtain a grazing value out of the blanket bog. 2/ Low/ On productive agricultural land (intensive grassland and arable) there are possibilities to enhance carbon by changing land management practice. 3/ Low/medium/ This was given where the habitat could be replaced with a more suitable habitats ; 4/ Medium/ This is allocated where changing land use could result in a fairly good enhancement of carbon sequestration. 6/ High /The highest benefits to abatement are restoring the deep peats which are currently under arable and intensive grazing. i.e. the fenlands area 7/ Urban / It was not in scope for this project to look at carbon values in urban areas as the data accuracy is to poor too make an informed decision. 8/ Water / It was not in scope for this project to look at carbon values within water bodies as the data accuracy is too poor to make an informed decision. NE PHI/ Ancient Woodland - OGL NE Living England - OGL NE Peat Map [2008] - Non- commercial licence NE SSSI data NFI-National Forest Inventory (NFI) Forest Research- OGL Soilscapes - Cranfield University/ HMSO- NE Bespoke Licence SRTM- NASA Shuttle Radar Topography- Open Topography

Bioclimatic data and environmental data for all 56 European peatland site (geo referenced by longitude [long], latitude [lat] and altitude [ALT]. MAT = Mean annual temperature (°C), TS = Seasonality in temperature, MAP = Mean annual precipitation (mm), PS = Seasonality in precipitation, tot_sox = Total sulphur deposition SOx (mg m-2 yr-1), tot_noy = Total oxidized nitrogen deposition (mg m-2 yr-1), tot_nhx = Total reduced nitrogen deposition (mg m-2), PT warm = Lang’s moisture index. The four bioclimatic variables (MAT, TS, MAP, PS) were extracted from the WorldClim database (Hijmans, R. J., Cameron, S. E., Parra, J. L., Jones, P. G. & Jarvis, A. Very high resolution interpolated climate surfaces for global land areas. Int. J. Climatol. 25, 1965–1978 (2005)), and averaged over the 2000-2009 period. Atmospheric deposition data were produced using the EMEP (European Monitoring and Evaluation Programme)-based IDEM (Integrated Deposition Model) model (Pieterse, G., Bleeker, A., Vermeulen, A. T., Wu, Y. & Erisman, J. W. High resolution modelling of atmosphere‐canopy exchange of acidifying and eutrophying components and carbon dioxide for European forests. Tellus B 59, 412–424 (2007)) and consisted of grid cell averages of total reduced (NHx) and oxidised (NOy) nitrogen and sulphur (SOx) deposition. The moisture index (PTwarm) was calculated as the ratio between mean precipitation and mean temperature in the warmest quarter (Thornwaite, C. W. & Holzman, B. Measurement of evaporation from land and water surfaces. USDA Technical Bulletin 817, 1–143 (1942))