Following a review of approaches used in Ireland and other countries, it was clear that the approach should consider the number of occupied hectads (10 km × 10 km squares). Following discussion with other experts, we set the following thresholds:

• Rare species occur in 10 hectads or fewer. 10 hectads equates to about 1% of the land area of Ireland.
• Scarce species occur in between 11 and 50 hectads. 50 hectads equates to about 6% of the land area of Ireland.

We tested these on existing datasets for macro-moths and water beetles. We developed a set of PostgreSQL/PostGIS views that consistently processed and analysed these raw biodiversity datasets. We also generated standardised distribution maps for all 861 insect species through a novel use of atlas functionality in QGIS.

We also pushed the process further to provide additional insights into the distribution of each species. This included:

• Distinguishing coastal species, defined as species where 75% of occupied hectads were within 1 km of the coastline. To aid interpretation, inland and coastal hectads were shaded differently on the maps.
• Identifying geographic skew in species distributions, calculated using the spatial distribution of the underlying records. This skew was presented on each map as standard box-and-whisker plots, and using cardinal and intercardinal compass directions (e.g. north-eastern).
• Recognising species that had a patchy distribution using a DBSCAN cluster analysis algorithm. This helped to identify species that had no clear geographic skew but were nonetheless geographically restricted.

We also considered whether it was possible to assess the abundance of a species in the hectads from which it was recorded. This needed to overcome the effect of variable recording effort, which means that abundances in different datasets are not comparable. We therefore developed a Normalized Hectad Abundance Score, which scored the abundance of each species from 0 (lowest abundance, which is usually an average of 1 record per hectad) to 1 (the species with the highest average number of records per hectad) within each dataset.

All this information was clearly included on the maps, to facilitate the expert review of the results.

Further information from Mike Lush.

Deer are large animals that are a potential hazard to vehicles on the road. Each year in the UK alone, it is thought that over 700 people suffer injuries or fatalities and over £17 million is spent on vehicle repairs because of Deer Vehicle Collisions (DVCs). In Scotland, a combination of increasing deer populations, especially in the central belt, and a growth in traffic has led to an increase in DVCs.

Exegesis was awarded a contract to collect and analyse data on Deer Vehicle Collisions (DVCs) in Scotland between 2019 and 2021. This work involved obtaining DVC records from a variety of sources in the public, private and third sectors, collating it into a consistent database, and analysing the data to identify trends and highlight areas of concern. This continued work undertaken since 2008 that had established data collation, processing and analysis protocols.

We added 5,479 records of DVC incidents in Scotland, bringing the total in the database for 2008 to 2021 up to 22,753 records. These were analysed in detail and a full report produced. Key findings included:

• Whilst there has been no recent significant increase in DVCs in Scotland overall, there has been a general increase in the central belt that has been offset by a decrease in northern Scotland (see map).
• Dusk is the worst time for DVCs, especially in May and June when overall numbers of DVCs are higher. This information can be used to target mitigation activities.
• There was no evidence of a decrease in DVC incidents resulting from travel restrictions introduced due to the Covid-19 pandemic (shown below). This contradicts claims of an anthropause where human impacts on wildlife were reduced. Nevertheless, the number of DVCs reported by members of the public, who would have been affected by the restrictions, were clearly suppressed. This suggests that freight traffic, which was largely unaffected by travel restrictions, was the cause of many DVCs during this time.

We also developed a new approach to analysing DVC risk on sections of the trunk road network, by using a moving window algorithm to identify the parts of roads with the most DVCs. We identified the blackspots with the highest DVC risk from the results. Most of these proved to be junctions surrounded by woodland in the more urban central belt. We recommended actions to mitigate the risk at the 10 worst blackspots.

The report will be published by NatureScot.

Further information from Mike Lush.

The objectives of this review were to:

• Review the ecosystem effects of common cord-grass
• Map the distribution and extent of common cord-grass in Ireland
• Review the options for the control and management of common cord-grass
• Develop a common cord grass control action plan that can be applied to coastal sites in Ireland

Literature review suggested that the perceived impacts of common cord-grass are often speculative. There was evidence of an impact on macrobenthos diversity, which may explain reported impacts on wading birds that feed on these organisms. There is also evidence that it can impact eelgrass Zostera beds. However, few other reported impacts had strong support and there were suggestions that common cord-grass might facilitate other species. There are also uncertainties about the relationship of sediment regimes and common cord-grass, and the potential impact of management and dieback.

Data analysis was undertaken in PostGIS. The extent of common cord-grass was determined based on the two Saltmarsh Monitoring Projects and the SAMFHIRES project. These provided excellent and up to date coverage, suggesting that the extent of common cord-grass was in the range 688 to 1,223 ha. These data combined with presence based records of the species showed that common cord-grass was widely distributed in Ireland, with records intersecting 167 out of 214 coastal sites.

The threat posed by common cord-grass to Annex I habitats was assessed. It was found to pose a substantial threat to three Annex I habitats, with particular concern for the rarest habitat considered (H1420).

Based on the literature review, a mixture of cutting, smothering, excavation and herbicide application could be used to control common cord-grass. However, this came with caveats, as some techniques, such as cutting, are unlikely to be effective on their own, and all techniques risk impacting other species and habitats in the vicinity. We therefore developed a management decision tool to help guide managers though the analysis required to determine the amount of survey and management action required for a site. This was provisionally implemented on the 167 coastal sites with records of common cord-grass to estimate the extent and costs of actions required.

Note that common cord-grass is currently subject to a degree of nomenclatural uncertainty. Formerly known as Spartina anglica, it is now considered to be a member of the genus Sporobolus, as Sporobolus anglicus. However, this change has not been universally accepted.

Further information from Mike Lush.

The aim of the project was to establish the suitability of aerial imagery taken from Unmanned Aerial Vehicles (UAV) to investigate the spatial and temporal extent of bait digging at selected sites in Wales.

Sites were flown at low tides and ortho-rectified seamless mosaics produced. Shore survey and ground truthing was also undertaken, and control holes dug to investigate the persistence of bait digging evidence on different shores. The shores were revisited to assess whether the control holes were still visible, to give an indication of the persistence of damage. The ortho-rectified imagery was used to create bait digging intensity maps on a variety of shore types.

Further information from Mike Lush.

Zero Waste Scotland contracted Exegesis to support Scottish local authorities in meeting the requirement for land zoning data. This involved:

• Providing practical technical advice to local authority staff on the use of GIS to zone land.
• Creating first cut spatial datasets of relevant land to be zoned.
• Processing data on behalf of local authorities in various ways.
• Supporting local authority staff as they determine and apply zones to their data.
• Quality assuring data and preparing it for the Litter Monitoring System.

Data processing was generally undertaken in the PostgreSQL extension PostGIS, using QGIS to view the data in PostGIS. Some processing was also undertaken in GRASS where this was beneficial, such as cleaning and removing small areas from the spatial data (using v.clean, especially the rmarea tool). Advice to local authority staff was tailored to their corporate GIS, mainly ESRI ArcGIS and Pitney Bowes MapInfo.

One of the requirements was that zoned land was split into 1,000 m² sample locations. Each sample location defined an area of land that could be surveyed as part of litter monitoring. Part of the support provided to local authorities was to run the pre-existing QGIS Polygon Divider plugin on supplied data to create the sample locations. This highlighted the need to enhance the Polygon Divider, which we undertook following discussion with Zero Waste Scotland. This included:

• The addition of an approach to split complex polygons into more manageable chunks to the Polygon Divider interface.
• Improved data handling to use memory more efficiently and reduce crashes and failures.
• Implementation of PostGIS compatibility.
• Improved message logging.
• Various minor bug fixes.

The changes to the Polygon Divider were submitted for inclusion in the released tool.

Further information from Mike Lush.

The project outputs consisted of a web interface for configuring the mapper, a modern and feature-rich web application for displaying maps, and consultancy services to JNCC in managing their database and web mapping services.

The project drew on our knowledge of managing large spatial datasets, optimising web mapping services, familiarity with marine habitat classification systems, and expertise in creating interactive web mapping applications.

The new system is currently used to display marine protected area boundaries (MPAs) in UK waters by JNCC. It is also used for a diverse set of habitat and environmental variable datasets as part of the European Marine Observation and Data Network (EMODnet).

The mapper can be configured by JNCC staff, who decide which layers should be available, which are displayed by default, and how they may be filtered. It is not restricted to marine mapping and could be configured to display any tiled web mapping services.

Users of the map can search and browse layers, view information about specific habitats by clicking on the map, zoom to areas of interest using a gazetteer, change base maps, and filter layers for specific habitats for species. A permalink system allows users to save their current view of the map and share it with others via a URL.

The mapper is easily deployed and can run as a standalone application or it can be displayed within a content management system to maintain corporate identity. The styling of the mapper itself is customisable so that it can also be themed to meet the style guidelines of the hosting organisation.

This mapper has been one of several marine mapping web applications we have created over the last few years including the United Kingdom Directory of Marine Observing Systems (UKDMOS) ArcGIS desktop application and the Integrated Marine Data and Information System (iMarDIS) https://portal.imardis.org/.

Further information from Andy Brewer.

NRW contracted Exegesis to establish a vegetation monitoring programme that would allow the development of the saltmarsh to be assessed and better understood. This involved:

• Collection of high-resolution aerial photography using out fixed-wing drone.
• The generation of an accurate height model.
• Capture of vegetation communities based on species dominance from the aerial photography and data collected in the field. The resolution of the aerial photography made sub-metre precision mapping possible.
• The selection of three transects across the main site.
• Detailed survey of a series of randomly located 2×2 metre quadrats along the transects, located using a high precision GPS.
• Photographs of transects, quadrats and features of interest.
• A full technical report detailing the methodology and results.

The report recommended repeat monitoring surveys following the same methodology and using the same quadrat locations, so that future vegetation change could be quantified and characterised.

Further information from Mike Lush.

Exegesis was commissioned by Zero Waste Scotland (ZWS) to develop a website and mobile app, plus the underlying database and API, to enable local authorities and other stakeholders in Scotland to monitor litter and fly-tipping incidents.

ZWS is the body responsible for reducing waste and promoting a circular economy in Scotland and has been a FlyMapper partner organisation since 2013. The Litter Monitoring System (LMS) took the pre-existing functionality of FlyMapper and added the ability to record and analyse detailed surveys of street litter. These surveys are used to support the requirements of the Scottish Government's Code of Practice on Litter and Refuse (CoPLAR).

The LMS mobile app is built using Xamarin, a cross-platform development tool that allows the sharing of a codebase between Android and iOS app versions.

The LMS web site allows management of both the fly-tipping and litter monitoring elements and is built within a cloudscribe Content Management System. It already contains details of previously recorded fly-tipping incidents in Scotland.

Data taken from the Technical support for CoPLAR Land Zoning in Scotland project is imported into LMS as local authorities continue to come on-board.

Further information from Richard Griffiths.

Under the Commons Registration Act 1965, the Council is obliged to maintain a register of all the areas registered as Common Land or as Town or Village Greens, along with details of ownership, rights holders and rights particulars. Managing these data in CAMS allowed integration of the map features for the commons & greens with their database records, something that had not previously been possible. For the first time it enabled users to view a common and all its associated tenements (land holdings with rights over the common) with one click. In addition, holding all the data within CAMS makes it easily available and searchable to a wider range of users.

Exegesis developed a new CAMS module to manage the Common land and Village Green Register, allowing users to easily find information on a range of criteria, such as "who has rights on this common?" or "which commons does this farm have rights over?", and easily keep on top of the day-to-day management of the data. The new Commons module handles all the data from the Commons Register and enables easy production of the hard-copy register sheets as well as various application forms and reports. In addition, tools in the Commons Module assist users with the process of reapportioning tenements when properties change hands.

Further information from Timothy Derbyshire

The first stage was to digitise the route of the new section into the Authority's CAMS. This included correcting the alignment of the path against OS MasterMap and dividing the route into Link sections.

The data were then loaded to the CAMS Mobile table application for survey in the field. The information captured included spatial and text data on all the signage, gates seating and other furniture along the Trail, along with photographs. In addition, detailed information, including mapping and photographs, was captured of all problems encountered along the Thames Path.

The collected data were analysed and loaded into the client's CAMS solution, and copies of map layers, geo-tagged photos and reports were made available to Transport for London.

More information from Timothy Derbyshire.

Prior to the National HLC (NHLC) project, virtually all of England had been characterised through individual HLC projects, but these were at county or sub-regional level, with each of the studies using slightly different methodologies and categorisation methods. In early 2016, Natural England appointed Exegesis to compile a national HLC dataset, drawing together the existing sub-regional HLC datasets and applying a common framework, structure and terminology to a new unified dataset. The aim of the project was to improve the awareness, understanding, appreciation and ability to manage and monitor the historic dimension of England’s landscape at a national scale, for both professional and non-professional end-users.

The database containing the terminology applied to all the different sub-regional datasets was cleaned and then the original terms used were mapped to a bespoke thesaurus, created to ensure that all could be mapped to a suitable, equivalent new term. The associated spatial data was also processed so that the irregular polygons were firstly imported to a merged dataset and then generalised into a gridded dataset. The gridded approach eliminated discrepancies in polygon size or accuracy, and overcame issues where there were small amounts of missing data in the original datasets.

The final gridded dataset was produced at 500m and 1000m scale, with each grid cell having a single associated record with information about the historic landscape character types (both broad types and narrower, character types) and period information. The datasets can be viewed and interrogated in GIS software packages, and when viewed alongside other datasets, the NHLC data can act as an indicator of historic landscape character and can therefore feed in to decisions about landscape management, planning, heritage asset management or research priorities.

View the outputs.

Further information from Abby Hunt.

The dataset was based upon Ordnance Survey MasterMap data, filtered to remove features that were unlikely to be hedges and excluding built up areas as garden hedges were not being targeted. These were then reviewed on the aerial imagery and assigned to one of the following types:

• Not a hedge
• Intensively managed
• Trimmed & dense
• Overgrown
• Line of trees
• Defunct
• Newly planted
• Recently coppiced
• Recently laid
• Woodland
• Uncertain

Hedges not included in the MasterMap data were also added, leading to a dataset of 22,370 features of which 17,013 were thought to be hedges. This was all undertaken in an incredibly short timescale, with data attribution starting on the 15th and finishing on the 27th December 2016.

Further information from Mike Lush.

The surprising answer is 'probably yes'.

We identified the Saproxylic Quality Index (SQI) as the best available measure of quality, as it was felt that a site's saproxylic (wood decay) beetle fauna would be a good surrogate of wider wood decay habitat quality, which is one of the most important elements of wood pasture and parkland. We combined available SQI scores with the wood-pasture and parkland inventory we had previously created for Natural England to create a sample dataset of 98 sites. We then analysed the sample data against other available data, including tree records from the Ancient Tree Hunt, geography, climate, designations and habitat networks using PostGIS and multiple regression analysis in the statistical package R. The models produced were refined to identify the model best able to predict wood-pasture and parkland quality.

Eleven site attributes were included in the final model for predicting SQI score. Sites in the south east and lowland sites tended to have higher scores, suggesting that warmer and less exposed sites were better for saproxylic beetles. Unsurprisingly sites with higher numbers and densities of veteran or ancient trees also tended to have higher scores, owing to the increased volume of wood decay habitat present.Sites that were in a landscape with other wood-pasture and parkland were also found to have higher SQI scores.

The best model proved to be remarkably good at predicting the SQI score of the sample. It suggested that sites with a predicted score of 600 or more were likely to have an actual score of at least 400 - itself quite a high score. This suggests that if the model were applied to the wider wood-pasture and parkland inventory it could be used to predict SQI scores and identify sites that could be targeted for survey.

However, this was a proof of concept study, so the model needs more work before we can conclusively state that wood-pasture and parkland quality can be predicted. This includes further refinements to identify attributes that help predict quality. It then needs to be tested to determine how well it predicts SQI scores for sites that were not part of the sample. We hope to be able to continue this work, as we believe the improved model could be very valuable for targeting entomological survey effort.

Further information from Mike Lush.

The two GIS were not always completely comparable, so notes were made on many of the items of functionality to give a more nuanced assessment. These notes covered those instances where no direct comparison was possible, where functions behaved subtly differently, where almost identical results could be obtained through different means and where ArcGIS specific concepts applied that were not replicated in any other GIS. QGIS lacked some advanced functionality required by JNCC, but it would be possible to develop much of this for QGIS. The lack of QGIS support for the ESRI map document (mxd) format was a particular issue, as JNCC required these for sharing data with partner organisations, but since the format is proprietary it would not be possible to develop this functionality.

We also assessed any changes to JNCC’s IT infrastructure required as a result of implementing QGIS, as well as the associated costs. There were no obvious issues with delivering QGIS via their existing Citrix system, though this was not tested. Whilst QGIS is open source, leading to significant reductions in licensing and annual maintenance costs, this needed to be balanced by the loss of functionality not available in QGIS, the lack of support and the need to retrain staff. The assessment suggested that whilst it would certainly be possible to implement QGIS within JNCC, ideally alongside a spatial database, with PostGIS offering the best QGIS integration, it would be necessary to retain at least some ArcGIS licences to ensure that some required functionality remained available.

Read the report.

Further information from Mike Lush.

To support local authorities in meeting their duty to provide route maps of existing safe footpaths and cycle-ways, Exegesis were contracted to specify the structure of datasets and design a web based data management system. At the same time Sustrans carried out an initial survey of existing paths and infrastructure to populate the system.

Exegesis created a structured national road and public rights of way network ready for the survey, then presented the survey data via a web mapping interface. The Sustrans survey data was added and thematically displayed. The LAs then defined their routes by clicking on the existing paths and roads and entering route details. The routes were inspected to assess the condition, hazards and suitability for an Active Travel route.

The resulting data could be visualised and edited on the web site by all of the Welsh LAs, minimising costs and helping to ensure that a consistent data set was created. The public consultation maps could then be printed directly from the website, providing consistently styled and annotated maps.

The Active Travel data set became the first national system for managing Active Travel paths and cycle-ways in the UK and will be used to improve the network and plan for the future.

Further information from Crispin Flower.

The work involved consultation with staff at JNCC and the British Oceanographic Data Centre (BODC) to ensure a faithful import and production of meaningful layers that are useful to JNCC marine staff when assessing the current extent of UK marine monitoring according to each, broad marine discipline (e.g. biodiversity, physical oceanography and fisheries). In addition, users can create custom layers, selecting only the monitoring parameters that may be relevant to a particular analysis.

Further information from Andy Brewer

A major aim of the project was to develop an online faculty application system for the Church of England. This system is used to digitally process applications which propose changes to the fabric of church buildings, features within the church and the churchyard. The system aims to simplify the faculty application process by automatically inputting information about each asset from the Church Heritage Record (which has shared development with Church in Wales Church Heritage Record).

Exegesis have developed a number of tools to simplify and automate the faculty application process. The system allows for the creation of legal forms for each application, required by the Church of England. It also allows users to keep up to date with their workload, providing them with a dashboard showing the applications and messages relevant to their role and any cases which require their attention. Users are also notified by email if they are required to work on an application. We have added a number of other useful tools, for example the automatic production of meeting agendas for the Diocesan Advisory Committee.

Since its launch at the beginning of 2015, 21 dioceses have signed up and well over 1000 applications have been processed.

Further information from Crispin Flower or Steve Ellwood.

The work involved assessing data originally from the National Land Use Database of Previously Developed Land, British Geological Society BRITPITS data and Environment Agency Historic Landfill data. Each feature was interpreted on aerial photography to determine whether OMH was likely to be present. Where OMH was not thought to be present the feature was removed from the inventory. Where OMH was thought to be present the feature was replaced with an accurately mapped boundary. Attributes were recorded for each retained feature detailing the sources of information, the confidence that OMH was present and notes describing the reasons for any uncertainty.

The result was the first ever inventory that separated OMH from brownfield sites more generally. In total 141,153 features were checked, but only 8,410 (32,602 hectares) of these were believed to be possible OMH and were therefore retained in the inventory. Greater London was shown to have the highest density of possible OMH, though Middlesbrough and St Austell in Cornwall were also found to be hotspots (shown above).

The process of inventory creation and the results were recorded in a rule base and project report.

Further information from Mike Lush.

Natural England had collated a series of spatial datasets relating to surveys of subtidal and intertidal marine habitats. Though all were in digital Geographical Information System format, they were from a variety of sources with differing formats. These were standardised to MESH Translated Habitat DEF, including an assessment of MESH confidence, data cleansing and validation, quality assurance and production of MEDIN metadata. We used a range of tools within ArcGIS, QGIS, GRASS and MapInfo in order to quickly and efficiently produce accurate and reliable outputs. We also utilised four standard habitat translation tables to manually assure the EUNIS habitat identified. A generic process diagram was also created, that can be used to guide all future MESH translation work.

The data to be imported into Marine Recorder were reviewed so that issues could be identified and the approach to import could be agreed. Biotopes were assigned through expert assessment of the data, based upon faunal groupings from Bray-Curtis analysis, particle size distribution, geographic location and field survey notes for each sample. These were then compared with the Marine Habitat Classification for Britain and Ireland (Connor et al., 2004) for the final biotope assignment. The Marine Recorder spreadsheet import function was used to import the resulting data, with particle size and biotope entered manually. The imported data in the snapshot were then independently checked to ensure they were correctly attributed.

Further information from Mike Lush.