Research completed: January 2025

DOI: http://dx.doi.org/10.7488/era/5650

Executive summary

Background

The planning system in Scotland is used to make decisions about future developments and use of land in towns, cities and countryside. Planning authorities are required to prepare evidence reports as part of the local development plan (LDP) process. These provide a summary of the baseline data used and explain the implications of the LDP.

Supported by National Planning Framework 4 (NPF4), planning LDPs should account for and address current and future climate risks, and enable places to adapt accordingly. Accurate, sub-national spatial data, which identifies geographic features such as rivers and utilities, is vital to create effective plans with a sound evidence base to evaluate climate risks. Fully evidencing climate risk requires an understanding of hazards, but also exposure and vulnerability, typically requiring interpretation of multiple datasets at once.

This report explores the geospatial resources that are available to support the evidence gathering stage with a view to improving access to geospatial data on climate risk. It identifies existing data, data gaps, barriers, and resources needed for evidence-based planning and delivery.

Key findings

Through engagement with a selection of Scottish Planning Authorities, we found:

Data for evidence reports

• A wide range of data is required to assess climate vulnerabilities and impacts, some of which require substantial climate and data expertise to interpret.
• Most required data is free for planning authorities.
• Planning authorities tend to rely on datasets familiar to them – such as Flood Maps (SEPA), Dynamic Coast, Scottish Index of Multiple Deprivation (SIMD), and OS MasterMap to assess climate risks like flooding, coastal erosion, and social vulnerability. These datasets are highly usable, with consistent coverage and quality across Scotland, but sometimes require geospatial expertise for analysis.
• There are additional datasets and tools which would benefit from further adoption by Planning Authorities, especially the Local Authority Climate Service. Additional datasets related to wildfire risk, air quality and land use may offer value, but would require some transformation, processing and interpretation to the climate context.
• Significant data gaps exist for urban heat islands, storm damage, health, water, infrastructure and landslides. Proxies (e.g. combining urban form, green space, and housing quality data) are suggested for urban heat island assessments. However, these must be approached in a considered way, which balances the potential effort to develop the interpretation against the likely risk.

Planning authorities’ approach

• There is a knowledge gap on how climate risk impacts planning. Some planning authorities have limited prior experience on climate risk, fewer technical data skills within their teams and no dedicated climate change professional. This leads to planning authorities mainly focusing on flood risk, where they have more familiarity.
• Planning authority use of spatial data is limited, despite support for it in the Local Development Planning Guidance. This underuse may result from limited awareness of the guidance and expectations of evidence reports, and a lack of capacity and skills to interpret geospatial data.
• Planners expressed a wish for a simplified approach to incorporate climate adaptation considerations into their plans.
• Planning authorities find it challenging and time-consuming to gather data from multiple providers.
• There is value in carrying out Climate Risk and Vulnerability Assessments (CRVAs) to better direct the use of data but there is no consistent approach or simple tool available for planning authorities to use.
• Collaboration across planning authorities allows knowledge and resources sharing, which leads to more consistent and effective outcomes.
• Given the wide range of potential data and analysis, planning authorities benefit from instances where work had been undertaken ahead of the LDP process to provide a view of which risks are most impactful, allowing a more focused approach to data.

Briefing note for planning authorities

• Many planning authorities lack clarity on which data should be used for assessing climate risks and vulnerabilities, and how to interpret it. We have created an accompanying briefing note (Section 9.5), which should help by providing guidance on more usable and interpretable data.

Glossary / Abbreviations table

Context and approach

Context

The reduction of emissions and adaptation to current and future risks of climate change is a challenge which is vital to be addressed via the planning system. The planning system provides opportunities to adapt to both current and future risks of climate change, as well as the potential to promote nature recovery and restoration in the area.

As part of the effort to modernise and update the planning system, the Scottish Government aims to align land-use planning with an outcomes-based approach to deliver sustainable development. This approach supports the National Performance Framework National Outcomes (Scottish Government, 2015) and supports the United Nations Sustainable Development Goals (United Nations, 2015).

Development planning, which outlines how places should change and where development should and should not happen, requires planning authorities to prepare and publish a local development plan (LDP)^[1], updating on a 5 yearly basis.

The National Planning Framework 4 (NPF4) (Scottish Government, 2023c),puts climate change adaptation and resilience front and centre. A clear understanding of the impact of hazards and risks related to climate is required for an effective plan, and this must be underpinned by the effective use of climate risk data.

Defining climate risk

In this report, we refer climate risk in line with existing climate literature. Risk is defined as a combination of hazard, exposure and vulnerability (IPCC 2014).

Hazards are physical events which may have adverse effects, such as sea level rise & increased heat.

Exposure indicates the presence of people, resources, infrastructure which could be impacted by the hazard, and the extent to which they can be reached by the hazard. Physical proximity is one key consideration in understanding degree of exposure.

Vulnerability indicates to which extent people, resources or infrastructure could be more or less impacted by a hazard

Crucially, data can indicate hazard, exposure, vulnerability, or potentially a combination of the factors if indicating risk. However, if a dataset was not designed with the above in mind, it would need to be reinterpreted to a climate risk context. As an example, Ordnance Survey provides extensive data on the location of buildings, infrastructure and natural features, but geospatial analysis would be required to derive metrics such location to flood zones to indicate risk of flooding.

There is a substantial range of potential hazards associated with climate change in Scotland (Grace et. Al 2025). For this report, our engagement with the planning authorities focussed on the applicability of data, therefore a simplified grouping of hazards and risks was used (Table 1). In instances where datasets were particularly applicable to vulnerability and exposure, this is discussed in detail in Section 4.

Table 1 – Hazards and risks, as summarised in this report

Local development plan evidence reports

Evidence reports are an early, statutory step in the development of a local plan. It provides a summary of the baseline data and other information which will form the basis of the plan.

This research focuses on the evidence gathering stage for climate risk – specifically, the tasks of early engagement and data collection, preparation of the evidence reports and a gate check by the Planning and Environmental Appeals Division (DPEA).

Evidence reports should be proportionate, with planning authorities having the discretion to tailor them to local characteristics and conditions. The Local Development Planning Guidance (Scottish Government, 2023b) provides guidance to support planning authorities in preparing evidence reports, including potential datasets relevant to NPF4 policies for climate change adaptation planning.

In addition to data access, there is a need to draw out implications of the data for the plan. It is not just about accessing the geospatial climate risk dataset but also ensuring its usability to accurately inform local development plans.

Rationale for this research

The lack of easily accessible spatial data on climate risk at a sub-national resolution has been identified as a key barrier to localised understanding of climate change adaptation by local authority planning officers.

Data gaps and accessibility issues create barriers to planning authorities producing proportionate, evidence-based plans. The aim of this research is to establish options for improved, simplified access by Scottish planning authorities to geospatial data that enables consistent, collaborative climate adaptation in local planning.

The intended audience for this research includes the Scottish Government and planning authorities. The work was commissioned on behalf of the Scottish Government, with particular interest for colleagues from the Climate Change Division and Planning, Architecture and Regeneration Directorate. A standalone briefing note and data catalogue (see Section 9.5) has also been produced specifically for planning authorities to showcase the available datasets.

Research methodology

The research involved an evidence review including a review of relevant literature, planning requirements and an in-depth data analysis of available risk data and its characteristics. Stakeholder engagement was conducted with planning authorities which were at various stages of evidence report development (see Figure 1) from early planning to successful completion. The engagement included interviews, as well as a wider workshop (See 9.3). Findings from these activities were the analysed to understand current needs, challenges and possible solutions to improve the process.

Figure 1 – Planning authorities engaged with in this study included Western Isles, Moray, West Dumbarton, Glasgow City, the Lothians, the Borders and Fife

Climate risk data

Effective data is central to the local development plan, and it is key that the right data is used and referenced for the evidence report. Additionally, the evidence report is expected to rely on spatial data, for which baseline evidence sources should be accessible.

There is a large range of data potentially available for use in evidence reports. This section provides a consolidated assessment of key datasets.

Our engagement with planning authorities identified:

• Five climate-related datasets that were familiar to planning authorities and were – or were intended to be – used to produce the evidence report.
• Eight datasets which would be valuable if used more extensively by planning authorities in the preparation of evidence reports.
• Five areas of concern to planning authorities in relation to the evidence report which did not have a dataset available, or a clear methodology, documented below as data gaps.

In this section, key aspects of the data are provided, such as name, the organisation providing the data. The data license under which the data is made available is provided, the full implications of the license to usage by planning authorities is detailed in Section 9.1.2.

The majority of datasets reviewed are updated and published at a rate sufficient for their purpose, though we have noted instances where there may not be a clear long term plan for the maintenance of the data.

Several other datasets were identified as having potential value. For the full list of all data sources reviewed please see the accompanying data catalogue (Section 9.5)., which catalogue includes details of the metadata and access links.

Key datasets already in use

Through the interviews and workshop, there were multiple datasets already in use by planning authorities in the production of the evidence reports, though not consistently in all cases. The most popular datasets are discussed in this section, along with a narrative of how the datasets were applied and if any issues were faced.

Table 4.1 – Key datasets already in use by planning authorities

Flood Maps

The consensus among most participants was that the Flood Maps from the Scottish Environment Protection Agency (SEPA) were a useful source for assessing increased flooding risks, which could be an outcome of both increased magnitude and frequency of rainfall, storms and sea level rise. The SEPA data is presented using a simple index (high, medium and low risk) down to ‘street’ level, which lends to easy interpretation by all stakeholders. The SEPA data also distinguishes between current flood risk, and future flood risk up to the 2080s, in the ‘Future Flood Maps’ layer. One participant also commented that the support provided by SEPA is also incredibly useful. Given the flood data also overlaps with other planning use cases out with the evidence report, there is a lot of familiarity with the data.

Dynamic Coast

Data from Dynamic Coast is used by multiple planning authorities. This project undertook a wide range of analyses, from coastal change due to sea level rise to the social disadvantage of the population exposed to coastal erosion. The output is a series of datasets on coastal erosion, intended as a broad planning tool for ‘street’ to ‘regional scale’ mitigation. The data also includes social vulnerability as an indicator. For coastal planning authorities, the data was seen as valuable and usable, though may not be as accurate or applicable in estuarine areas. The outputs include a mixture of OGL and PSGA data, so while most of the data is fully open, not all layers can be supplied to all stakeholders.

Scottish Index of Multiple Deprivation

The Scottish Index of Multiple Deprivation (SIMD) dataset provides a range of indices which can be used to highlight areas of high deprivation that may face a higher impact from climate risks. The data is presented at Lower Layer Super Output Area (LSOA) level (e.g. ‘neighbourhood’ level) and summarises social issues in simple to interpret indices. The housing index specifically accounts for houses which are overcrowded, and those which do not have central heating – key factors to consider when assessing risks related to several climate hazards.

OS MasterMap

There is a large range of data available from the Ordnance Survey (OS), which can cover a range of topics from housing, infrastructure to green space and biodiversity. OS also provides products which can be used as backdrop maps to improve the accessibility of data when shared with stakeholders. The OS MasterMap range of datasets has been used in local government for various purposes since its launch in 2001, so there is likely to be organisational familiarity, especially in GIS teams. OS has been in the process of refreshing its key products with the introduction of the National Geographic Database (NGD). This is intended to add additional data to OS’s products to serve further analytical use cases and adds data such as the presence of green roofs and solar panels on buildings (coming in future release), habitat classifications and building ages. OS data is largely licensed under PSGA or OGL, and access is provided via the OS Datahub. OS also has products which identify areas of greenspace, namely MasterMap Greenspace and OS Open Greenspace. OS data is all high resolution, ‘street’ level data.

OS data is of high quality and coverage, providing street level data across Great Britain, which is updated frequently. Indicators for climate hazards, however would need to be derived through analysis. This would generally require geospatial skills and tools, but additionally, OS datasets tend to be large and complex. OS has made some efforts to address the complexity of accessing large data, including ‘Select+Build’ features, and API access. All planning authorities, as PSGA members, can access direct technical support from OS.

Light Detection and Ranging (LiDAR)

LiDAR data from the Scottish Remote Sensing portal is valuable for assessing risks related to flooding. Digital Surface Model (DSM)/Digital Terrain Model (DTM) data from LiDAR can be easily interpreted and integrated with other steps in the analysis. The Scottish Remote Sensing portal has OGL licensed LiDAR data in a relatively easily accessible form – however, the coverage of the data is mostly focussed on the Central Belt, limiting the ability for some planning authorities to use. Additional coverage for the data was announced as part of the Future Farming Investment Scheme^[5], which should improve the usability of this data in the future. The data is high resolution, supporting analysis at ‘street’ level.

Suggested datasets for future wider use

The following datasets were discussed in interviews and workshops, but we found that not all planning authorities sampled were using them. For some datasets, the low uptake by planning authorities was due to difficulty in the use, or accessing of the dataset, whereas for others low uptake was down to a lack of familiarity.

In this section we have provided a narrative for these datasets to indicate where they may be of value for planning authorities to use going forward.

Table 4.2 – Suggested datasets which could be used by Planning authorities for further value

Local Authority Climate Service

The newly launched Local Authority Climate Service (LACS) from the Met Office aims to provide planning authorities across the UK with crucial information on climate change to support decision-making. The LACS provides a simple interface for analysing changes related to key hazards and includes climate averages and climate indicators. A Climate Report can be generated through the Climate Explorer. Planning authorities can add data and then use it in other applications such as Excel and Power BI. It is built using geospatial technology from Esri UK and is part of the Climate Data Portal (Met Office, 2024b) which hosts the information within the Local Authority Climate Projections Explorer. The LACS also includes guidance on the process of assessing climate risk with ‘regional’ level data. The Met Office launched the new beta service on 9 October, so as a new service has not yet seen widespread adoption in planning authorities. The Met Office are inviting feedback to help drive improvements of the LACS – the conclusions of which could be used as the basis to feed into this improvement process. Additionally, it could increase the number of Scottish planning authorities involved, increasing their awareness and knowledge of the system, and also make sure the LACS delivers the service that Scottish planners need. The LACS is not currently configured to provide reports for National Park planning authorities, but does cover all Scottish local authorities.

Habitat Map of Scotland

The Habitat Map of Scotland (HabMoS) is a composite dataset including different layers of detailed habitat data. All have been given a common Habitat Coding from the European Nature Information System (EUNIS). Using this data, a mapping of the existing habitats in a planning authority can be created. High value, or at risk habitats can then be identified, and habitat loss due to hazards such as sea level rise can be accounted for . The data is OGL licensed, with ‘street’ level resolution. HabMoS brings together habitat and land use data from multiple sources into one map, but the data is not interpreted in the context of climate hazards, so further interpretation and combination with additional datasets would be required to draw conclusions.

European Local Climate Zones

The European Local Climate Zone (LCZ) data creates a simple typology for the built environment and landcover which is intended to support decision-making around climate risks. The data aims to characterise the urban landscape into broad categories (such as low-rise and high-rise housing) so that interactions between urban form and risks such as poor air quality, flooding and heatwaves can be modelled. Data is provided at ‘neighbourhood’ level resolution. One workshop participant reported that they had undertaken a ground truthing exercise in their local authority and confirmed that the data was broadly valid. As the data was recently, in 2022 and was aimed at the climate academic community, this dataset has not yet found widespread use in planning authorities. There are not currently any regular updates or revisions published for the LCZ data. Given the data is at ‘neighbourhood’ resolution, there is less need for it to be updated frequently, as only large changes to the urban landscape would be detected. As well as the detailed methodology being public, an LCZ Generator tool is provided by Ruhr University Bochum^[9] which provides potential opportunities for updated datasets to be created for Scotland in the future.

UK Climate Risk Indicators (UK-CRI)

UK-CRI data simplifies analysis of many risks into indices. For temperature related risks, the data includes an estimation of days (or events) per year of events including heat waves, amber heat-health alerts, tropical nights (nights with a minimum temp of 20 °C). This extends to heat related impacts on infrastructure, such as road melting and high temperatures on rail. The impact of hazards on agriculture such as growing season and heat stress are also reported. Rather than creating new climate data, the UK-CRI is an interface on existing datasets (primarily Met Office) which simplifies complex data into more easily interpreted indices. The Met Office publishes annual updates to its climate data, though the UK-CRI tool does not receive updates as frequently. At ‘regional’ scale, it is less critical that the data is frequently updated, though after 5-10 years if the tool does not receive data updates, it may become far less appropriate to use.

River Basin Management Plans

River basin management plans set out actions to address current issues affecting water quality, water resources and fish. The management plans can be used in context with other data sources to understand risks which impact river health. River basin management plans are not explicitly geospatial datasets but relate to river basins which can be represented geospatially. The issues faced using this data mainly lie in the river basin boundaries not aligning with local authority boundaries, so requires some analysis. In addition, the key use case of the dataset is not climate risk or hazard related, so will require reinterpreting to the climate context.

Neighbourhood Flood Vulnerability Index (NFVI) and Social Flood Risk Index (SFRI)

A national flood vulnerability dataset was created by the Joseph Rowntree Foundation and is publicly available via the ClimateJust Maps tool. This dataset provides and easily to use, ready-made index describing flood vulnerability by combing physical flood risk with several factors which represent socio-economic vulnerability to flooding. However, it is based on ‘street level’ data published in 2011, which at this scale becomes quickly outdated. England and Wales had their index updated in 2022. An updated Scottish equivalent would be a useful tool for planning authorities to explore the vulnerability to this specific and pressing hazard.

UK Climate Projections 2018 (UKCP18)

The Met Office is the authoritative source for key climate projection data for the UK. UKCP18 products are commonly used for temperature and precipitation projections, but it can also provide data on humidity, wind and sea level rise. The climate projections generally support analysis at a ‘neighbourhood’ to ‘regional’ level, dependent on the specific data UKCP18 product.

The Met Office provides a UKCP18 User Interface for querying and extracting the data, graphs and pre-paired maps (plus access to the full data catalogue for those experienced in handling large datasets), but this does require some expertise in the underlying data to navigate, limiting its usability to planning authorities that have GIS teams or capability. This was reflected in the workshops, as some participants expressed concern that the climate data accessed from the UKCP18 portal was sometimes difficult to use. In addition, there is further interpretation work required to convert a numerical value from the data into a clear indicator which can be used to influence a decision. This interpretation of the climate data and translation into implications for the LDP was also found challenging , with some planning authorities being unable to fully explore what the data means for their plan.

The UKCP18 data is a crucial underpinning to climate analysis and has been used by some planning authorities. More recently the data has been made more usable with a set of pre-prepared indicators by tools such as the Met Office Local Authority Climate Service (where GIS users can also visualise the mapped data and also add their own geospatial data), and UK Climate Risk Indicators.

GeoSure, GeoCoast and GeoClimate

Participants expressed an interest in data from the British Geological Survey, which has the potential to address risks such as coastal erosion and landslides. The BGS GeoSure, GeoCoast and GeoClimate datasets indicate risks arising from multiple hazards, with a range of open and licensed datasets. The use of BGS data was not widespread among participants, partly due to the licensing cost associated with the premium datasets.

There may be more value to be gained from these datasets, but it would likely require the supporting geotechnical knowledge and interpretation, unless a simpler way of indicating future risks is provided.

Perceived gaps and ways to address gaps

When discussing risks, participants expressed several areas where they felt there was insufficient data available to meet their needs. This was due more to the limited understanding of what data was required to support the analysis, rather than specific datasets lacking appropriate spatial and temporal resolution or having gaps in coverage.

It should also be considered that if these data gaps were closed, what value would they provide to the evidence reports in each planning authority, and to what extent would the planning process be able to take useful action on the data. Urban heat islands serve as a useful example – while it would be possible to carry out a detailed analysis in each planning authority, for rural, or northerly authorities, the risk could be understood to be minimal by using an understanding of the local context and long term heat risk from tools like the Local Authority Climate Data Service (see 4.2.1).

In this section, we list the key gaps and explore some datasets and approaches which could be used to address those gaps.

Urban heat islands

Participants generally expressed a lack of data to understand the risks associated with the urban heat island (UHI) effect. The overheating risk methodology can be derived from both UKCCRA3 (Built Environment chapter) and the previous Environmental Audit Committee evidence reviews (e.g. 2018). Determining the extent of the effect of UHIs in urban areas can be done using a temperature sensor network (at high spatial resolution), modelling (e.g. using dedicated products such as Envi-MET, adapting more commonly used modelling approaches, e.g. atmospheric dispersion modelling systems (ADMS) (Zhong et al., 2024), or analysis of high-resolution satellite data products. However, these approaches may not be suitable for all planning authorities due to resource or lack of specialist knowledge. Overheating risk is likely to be greater in areas where urban form is compact, where there is less green and open space, and where the housing quality is poor. As such, combining datasets on Local Climate Zones (to give urban form), green space, and Scottish Index of Multiple Deprivation may act as a proxy for estimating urban heat island magnitude (e.g. Ferranti et al., 2023). Housing quality can also be indicated in further detail by Home Analytics data from the Energy Savings Trust which provides specific attributes on building fabric. This is a simpler approach using GIS datasets that planning authorities may be able to use for their evidence reports.

Storm and wind damage

While there are multiple datasets for inundation and coastal erosion, we did not find much work done to understand wind damage to buildings, or from trees. Tree fall risk is a statutory responsibility so it may be that planning authorities have some of this data held within parks or urban forestry teams. There are datasets which use remote sensing techniques to identify trees. One such dataset is National Tree Map from BlueSky – however, as this is a proprietary, licensed dataset it is unclear if the cost of this dataset outweighs the value which can be gained.

Landslides

While participants did discuss landslide risk, there was no broad consensus on the approach, nor most appropriate data. The open data published by the BGS could serve as a potential baseline assessment of current risk which, if found to be sufficiently high, further research could be carried out incorporating premium data, or input from specialists.

Health infrastructure

Data on the locations of key health infrastructure are available from NHS Scotland and accessible via the Spatial Hub. However, the use of these datasets in the context of the evidence reports would require further interpretation in order to drive decision making in the climate context. Whilst it would be possible to interpret which areas could be exposed to hazards such flooding and coastal erosion, understanding the magnitude of the risk on health infrastructure from hazards such as heating would require additional data to determine vulnerability such as building age and fabric. In the workshops, these aspects were not raised by participants, suggesting that this has not been a focus for planning authorities thus far.

Water infrastructure

Relevant data on water infrastructure, from Scottish Water for example, for the climate context is either available piecemeal, or not published. To understand which data would be required, planning authorities would need more knowledge as to which risks are likely to require water infrastructure data to assess.

Further observations

Wildfire risk was one aspect investigated by some planning authorities. Seasonal risk forecasts, as well as real-time monitoring is published by the European Forest Fire Information System^[10] (EFFIS). This is a valuable resource for assessing the current risk landscape for fires, but additional context would be required for evaluating future risk (see UK-CRI in Section 4.3 above).

Datasets such as the Scottish Air Quality Database^[11] provide information on air quality monitoring, analysis and interpretation of data, and pollutant trends at national and local levels. Historical data can also be accessed via the Met Office. Since these are observational datasets, they can be used for assessing current risk, but additional context would be required for evaluating future risk.

For more rural or agricultural planning authorities, there was also value in land use and land cover data from NatureScot, which allows risk to peatlands and croplands to be assessed. For coastal areas this data could also be analysed alongside Dynamic Coast data.

Based on the interviews and workshop discussions, participants expressed several areas where they had difficulty using data for specific outcomes or were not sure what to use.

Most of the datasets which were found to be of value for the evidence report were not hosted by a single source such as the Improvement Service Spatial Hub. The overhead effort of data acquisition for the planning authorities could be improved by more of the data providers providing a copy of their data to the Spatial Hub. However, this approach would not be straightforward with all datasets, such as those which are licensed (e.g. BGS), or those were the provider includes an analytical interface for extracting key indicators (Met Office LACS or UK-CRI).

Analytical tools

We reviewed several different analytical tools, such as CLIMADA^[12] and OpenCLIM^[13] which are designed to support users in analysing climate datasets and produce new data outputs indicating risk. These tools are open source, adaptable and suitable for academic use cases. In our interviews and workshops, we did not receive any feedback from planning authorities on these tools, suggesting they do not use them. As they require a high degree of specific technical proficiency (e.g. running python code), they may not be particularly suited to the planning authority teams who are producing evidence reports.

Current Approach

Climate Risk and Vulnerability Assessments

Climate Risk and Vulnerability Assessments (CRVAs) or Climate Change Risk Assessments (CCRAs) are available for some planning authorities and some regions of Scotland. These include the Clyde area, and one in preparation for south east Scotland.

Nationally, there is the UK CCRA Independent Assessment (Climate Change Committee, 2021a) and the National Summary for Scotland (Sniffer, 2021). These documents are long, difficult to navigate, and have a comprehensive list of wide-ranging risks. For anyone with limited familiarity with climate science and/or individual sectors, it is hard to understand which risks are most relevant to their planning authority or which risks are most important to planning. Risks in these documents are categorised with urgency and magnitude scores, and there is no scoring of impact or likelihood (apart from flooding likelihood) at a national, regional or local scale. Planning authorities need this information for their evidence report requirements, but it is not provided in the national CCRA3.

National documentation on adaptation (i.e. Scottish Climate Change Adaptation Programme: progress report 2023 to 2024) does not directly relate to local planning process and/or is difficult for the untrained person to see the links. The wider list of literature reviewed is given in Section 9.4.1.

Local climate risk assessment barriers and challenges – findings from the academic literature

Research related to mapping climate risk has increased rapidly in recent years. Studies are usually area- and problem-specific, which means that there is no standardised approach. Some maps focus on the local level, such as a city scale, but some have also looked nationally. Some also consider both spatial scales. Similarly, maps that assess climate risk can vary in perspective, such as focusing on one climate hazard because it disproportionately affects the study area the map is produced for. While many do take a multi-hazard approach, some focus on specific challenges such as heat, flooding, and drought.

Methodological process can also vary greatly across such assessments which may affect results so, for decision-makers, it can be challenging to decide which method is most appropriate to use. One key feature of many CRVA maps is the weighting of variables, which affects the extent of which specific variables may influence overall scoring. The SIMD dataset from the Scottish Government, as an example, weights income and employment indicators more heavily than housing in its determination of the deprivation index. However, in a climate risk context, a different weighting may be more appropriate. From a local perspective, weighting variables may be beneficial as they can provide more accurate results for decision-makers. However, in some cases it is difficult to achieve and an unweighted approach is preferred. Reasons can include

• a lack of data or local studies
• the risk of politicisation that may underpin the decisions upon weighting which links to subjectivity and
• complexities around how different climate hazards may weight other variables differently.

Ultimately, adaptation to climate change should be a process that is iterative and embedded into organisational practices. Knowledge underpinning decisions may be imperfect, incomplete, or comprise other challenges such as those outlined above. It is important nevertheless that the process is started with the best knowledge and data available at the time. In repeating the process, more experience is gained, and the challenges can begin to be addressed (Greenham et al., 2024b).

Approach to the evidence report

Current position

In both the interviews and workshop, the planning authorities were at different stages of preparing their evidence reports. This ranged from those at very early stages of preparation through to authorities who have drafted their evidence report and received feedback from the Gate Check^[14]. It is important to note that the small number of authorities having received the Gate Check at the point of the interviews and workshop, meaning a small sample may have impacted some of the feedback, alongside the relatively small sample of planning authorities that could be engaged during this short project.

The participants’ attitudes towards producing the evidence report were slightly more positive than their understanding of climate risks in general, with a generally positive sentiment (Figure 2)

Figure 2 – Sentiment captured during the workshop from the participants

Different approaches

The approaches used by planning authorities varied significantly, with different methods to identify data including policy review, evidence audits and workshops.

The teams undertaking evidence reports ranged in number of staff from 1-2 to 4-5 people. The use of specialist data or climate specialist colleagues in other departments within the planning authorities varied.

There appears to be a disparity on the anticipated timescales and resources required to undertake the evidence report. This depends on the extent to which planning authorities have already undertaken a climate change risk or vulnerability assessment and could be more reflective of local authority capabilities to conduct and deliver the output.

Some authorities have access to pre-prepared local or regional climate risk assessments or are part of existing climate ready projects (see Section 5.6). Others have access to climate change profiles, which provided an overview of expected future climate change. We also found some authorities had not explored climate risk and therefore had little existing evidence or experience to work from.

However, it was noted that even those planning authorities which had undertaken previous assessments found it difficult to access primary data. They were mainly using the conclusions of the past risk assessments to inform their evidence reports.

The implications of interpreting the data in a climate context and what the evidence actual means for informing or changing the local development plans was not always clear.

Using data to produce the reports

Concerns were raised by participants over the dynamic nature of the data, new data being published, and old data being updated. Not only did this make it hard to identify the latest datasets, but it also gave rise to concerns about evidence becoming out of date soon after reports were developed^[15].

Concerns were also raised about the complex array of caveats and limitations that are inherent in much of the data. This included concerns about their own understanding and interpretation, and how these limitations should be portrayed in the reports in a non-technical manner.

Another issue raised was an inability to find locally specific data at a sub-local authority resolution; one local authority wanted to take a ‘neighbourhood’-level approach but felt that data did not exist to support this.

Data accessibility challenges

Challenges in accessing and fully utilising data exist at several points, and in ways which varied across planning authorities.

Firstly, a very broad set of potential datasets which could be used exists. The planning authorities had to locate many different data sources to compile the data they needed.

Next, the data needed to be downloaded and formatted from the different data sources and while most of the data required is licensable freely to planning authorities, we found a subset where the licensing implications and restrictions were unclear. In the case where the work was being carried out by organisations external to the planning authorities (e.g. Sniffer), additional barriers were faced as access to PSGA licensed data is not immediately granted, and additional contractor licenses need to be provided. PSGA contractor licenses are free, and they limit the scope of external use of the data to specifically the contracted work.

Once the data is obtained, its application to understanding climate risks and hazards is not always straightforward. Some information is in a readily usable format, while others require expert input before analysis is possible. In the case of datasets such as Dynamic Coast, or data presented via the Met Office Local Authority Climate Service, data is pre-transformed and interpreted in a climate context. As an example, the Met Office LACS provides simple indices such as “Average Number of Extreme Summer Days”. This contrasts with datasets such as UKCP18, where a user will need to download the dataset, isolate the area of interest, extract the climate values, and determine what metric to rate them against. This is a time-consuming process, requiring both geospatial and climate expertise.

Understanding how to link the data back to the guidance and the requirements of the evidence report is a key required outcome, and the extent to which accessing this insight from the data can be achieved varies widely across the datasets used.

Understanding climate risks

Concerns were expressed in the workshop by participants from smaller planning and development teams about resourcing, where there was little or no dedicated resource within the team, or even access to a dedicated individual with climate change knowledge. This makes the process more difficult and time consuming for these planning authorities.

Risks vary from area to area, but additionally will vary over time as the climate changes. We found that many workshop participants were focused on a current view of risk, rather than being informed on how risks might change based on future projections. Risks across different hazard areas discussed, and whether they seemed well represented or potentially underrepresented in the workshops are outlined in Table 1. Additionally, not all planning authorities had fully defined which hazards were most appropriate for their region.

Given many planning authorities already have a track record in modelling flood risk, and have a greater understanding of flood risks specifically, there is a heavy focus on flooding. There is less awareness of other climate risks, specifically future climate risks, and how they may relate to development planning. In some cases, there is confusion between climate mitigation (through reduction of greenhouse gas emissions) and adaption to reduce climate risk.

The value of pre-existing work

In some instances, planning authorities were (or will be) able to build upon pre-existing work. Of particular value is work focused on climate risk, and the production of data layers specifically to allow easy interpretation from a wide range of users.

The data and findings from examples like Climate Ready Clyde and Climate Ready South East Scotland can be re-used and built upon for consistency, as well as reducing the effort required for an evidence report specifically. However, planning authorities who have not benefited from these will be at a relative disadvantage.

Climate Ready Clyde

Climate Ready Clyde (CRC)^[16] is a leading cross-sector initiative funded by 12 member organisations and supported by Scottish Government to create and deliver a shared vision, strategy and action plan for an adapting Glasgow City Region. CRC have produced Glasgow City Region’s Adaptation Strategy and Action Plan (Sniffer, 2024a) which includes a webmap (created by Clydeplan) that shows the location of postcodes most vulnerable to the impacts of climate change (Clydeplan, 2022). This includes heat risk (derived from the 4EI Heat Hazard Index^[17]) and a layer highlighting postcodes within the top two heat risk bands. The work from CRC on the Climate Risk and Opportunity Assessment and data layers in the vulnerability map directly informed Glasgow City Council’s Evidence report.

Figure 3 – Glasgow City Region Climate Vulnerability Map

Climate Ready South East Scotland

A new project to support collaborative climate action in the Edinburgh and south east Scotland City Region. Climate Ready South East Scotland^[18] is led by Sniffer, working in partnership with the region’s six local authorities: City of Edinburgh, East Lothian, Fife, Midlothian, Scottish Borders and West Lothian.

Climate Ready South East Scotland plans to:

• Identify and prioritise the risks and opportunities from climate change to Edinburgh and south east Scotland’s society, economy and environment between now and 2080.
• Lay the foundation for a transformational approach to climate adaptation and resilience for the city region.
• Support a just transition to a net zero and climate resilient economy, in a way that delivers fairness and tackles inequality and injustice.

A detailed assessment of the climate risks and opportunities faced by the Edinburgh and south east Scotland City Region will be carried out, and is intended to be published by March 2025. This assessment will both draw on the best available scientific evidence, and work with communities across the region to gather and share their experiences of climate change. It will inform decision-making across the region, laying the foundation for collaborative climate adaptation action (Sniffer, 2024b).

Overall observations planning authorities’ approaches

We collated six overall observations, looking across the literature review, interviews and workshop.

A focus on flooding and a lack of awareness of available non-flood data

Knowledge and understanding of flood risk and applicable datasets is much more established with planning authorities. While this experience is valuable, it does lead to a focus on flooding to the detriment of the consideration of other risks.

In general, the participants revealed a lack of awareness around climate change projection data, including where to source it and how to use it. As an example, whilst some participants with backgrounds and expertise in climate had knowledge of the data, planners in general were far less familiar with UKCP18 data, when asked about data they used. Most questions on data were directed back to flood information. In one interview, when questioned more on UKCP18 there appeared to be no knowledge of where this data can be located and how to access it. Some statements suggested a lack of understanding of what climate projections are and different scenarios used, however this was not fully probed in the interviews. This data is key in understanding the risks that planning authorities will face in the future and the degree of potential impact.

Spatial data not always used

The use of spatial data appears limited even though the use of it in evidence reports is supported by the Local Development Planning Guidance (Scottish Government, 2023b). Whilst some spatial datasets are well known by planning authorities (e.g. SEPA flood maps) the use of further datasets is not extensive due to poor understanding of the geospatial data required and/or ability and access to staff with the right skills to use and interpret geospatial data.

Simple indices support interpretation

Interviewees generally favoured datasets which provide simple indices tailored to the climate risk context, such as SEPA flood maps and Dynamic Coast. These datasets allow interpretation by users without specific climate or data expertise. This contrasts with the UKCP18 data, as an example, which provides users with hazard data like temperature and rainfall values over time. Considerable interpretation would need to be done to translate this data into a measure of risk which can be interpreted. Users without climate or geospatial data experience can be supported in understanding the implications if the data is pre-prepared, and presented with relatively simple indicators.

Section 9.2 provides examples of tools and datasets which have been developed outwith Scotland, used to support users without climate expertise in understanding risks.

Simplification of the approach is needed

There is a need to simplify the approach that planners adopt, to enable them to incorporate climate adaptation into their plans. The evidence report is an important part of this process to help development of a baseline and support understanding of the climate risks faced by planning authorities now and in the future. To do this, a Climate Risk and Vulnerability Assessment (CRVA), which considers key hazard, vulnerability and exposure data, is a valuable prerequisite to identify those risks which can be mitigated by planning. Spatial data is key to undertaking an accurate and specific assessment, although there is currently no simple tool to support it. An example of this would be the methods and approach taken by the University of Birmingham for work done for one local authority (Birmingham) and one regional authority (West Midlands) in England (see Section 9.2). Aside from a tool, authorities would benefit from greater understanding of the key datasets which provide the best outcomes. This mirrors findings from the evidence report gate checks completed to date.

Prior work and climate data skills are advantageous

There was a general observation (which was also identified by several stakeholders) that some planning authorities faced greater challenges in the evidence report process. This is because they have little prior work on climate risk, less technical data skills within the team and no dedicated climate change professional within the Council.

Planning support and guidance is not specific on the application of data

The literature review illustrates that there is little information on climate risks and resilience that is written to support either local authority planners or the evidence report process. There is a wide range of data available, which could be used in many different approaches to be applied to understanding climate risk and appropriate adaptations. Furthermore, there is a gap in knowledge on how climate risk impacts planning and how planners can enhance climate resilience through planning requirements and the local development plan. Such information contextualised for Scottish planners would be invaluable to support the evidence report process and would allow adaptation to become business as usual within planning processes.

Conclusions

The following conclusions drawn from this research project to improve the evidence base for climate resilient planning policy are:

Accessibility and usability of data

• There are numerous and varied datasets required to consider the range of vulnerabilities to, and impacts from, climate risks. There are several key datasets which are underutilised by planning authorities currently.
• Many planning authorities do not have a clear and specific understanding of what data is needed to assess climate risk and vulnerabilities. The accompanying Briefing Note for Scottish Planning authorities to this research report (see Section 9.5) should provide support in providing signposted usable data.
• Significant data gaps exist for urban heat islands, storm damage, health, water infrastructure and landslides. Proxies can be used, e.g. combining urban form, green space, and housing quality to assess urban heat island risk. However, consideration should be taken to ensure a consistent methodology, and a proportional amount of effort given potential risk.
• The most useable and accessible data sources, such SEPA, Dynamic Coast, and Met Office LACS provide pre-determined, simple indices which provide a clear indication of climate risk. These allow planners to make clear decisions, without having to apply climate or data expertise to determine risk themselves.
• Not all datasets provide simple indices, however, there are several datasets which could be used by planning authorities in the evidence reports which are not widely used currently. A consistent methodology for planners on how the indicators can be derived and used to incorporate adaptation and resilience into local planning would be advantageous.
• Longer term, a single entry-point to these datasets would make this process easier for the planners and ensure that all Planning authorities have similar data to undertake the assessments
• The data required is also mostly free for planning authorities, however, there are some licensing differences to be aware of when publishing to the public. See 9.1.2 – Data Licensing for further detail.
• Accessibility could also be improved with further guidance on certain requirements mean and how they can be achieved. For example, the requirements ask planning authorities to assess the likelihood of risks occurring. This is a complex task, requiring knowledge of the climate hazards, how they will change, uncertainties, the ranges of climate outcomes depending on scenarios. Guidance on how to define likelihood and how to use data to evaluate likelihood is important, and can be paired with a specific indication of which dataset can be used for that purpose.

Understanding and capacity

• Planning authorities find it time-consuming and difficult to get the required data from all the different providers.
• Undertaking climate change risk assessments prior to the evidence report would provide a better understanding of which risks and hazards are most impactful.
• However, planning authorities may need help doing this (especially the smaller planning authorities and/or those without climate and GIS and data experts), including:
• Direct funding to outsource.
• Support to identify partners and apply for funding.
• Sharing or secondment of staff with climate resilience/climate science and GIS and data skills.
• Collaboration and co-funding with neighbouring/regional planning authorities, like the ‘Climate Ready’ regional projects.
• As an example, Sniffer is an independent charity that supports and coordinates the climate ready programmes in Scotland, including work such as webinars which discuss the use of different datasets. Sniffer currently hold a Scottish Government funded contract (Adaptation Scotland) to provide some capacity building support to planning authorities. This could be expanded to provide wider support for the climate change risk assessment process and support planners in translating the findings into the evidence report and the local development plans.
• It should also be noted that the assessment of likelihood of risks occurring, beyond flood risk, is not undertaken in the UKCCRA3 or Scotland’s national summary.
• It is useful to understand and address vulnerability at the evidence report stage, although stakeholders did not seem familiar with this as a concept or how it might be assessed.

Potential for action

Based on the findings from this research, the following actions could be explored in the short term to enhance and improve the coverage and usefulness of evidence reports:

• Engage with the Met Office for a review of planner-specific user experience when accessing the latest UK Climate Projections (UKCP18)
• The impression from most stakeholders was that UKCP18 projections are daunting and avoided by planners. The Met Office Local Authority Climate Service (LACS) (Met Office, 2024a) is still in beta, and feedback should be provided on how it could further meet the needs of Scottish planners.
• Explore whether non-flood related climate data could be sourced directly via an existing data service for the creation of bespoke Climate Risk and Vulnerability Assessment indices and geospatial data portal relevant to planning in Scotland.
• Explore the inclusion of features to support the National Park planning authorities in the LACS.
• Engage with the British Geological Survey (BGS) to explore expansion of access for the assessment of landslide risk – and potential inclusion of licensed data.
• Provide planners with further detail on which aspects of various datasets are valuable for their local plans, including the climate risks which planning should address (e.g. overheating, surface water flooding).
• Encourage cross-authority engagement and collaboration. Given the inconsistent availability of knowledge, skills and capacity, peer learning and support can potentially provide a valuable approach to improving quality and consistency.
• Share and promote the list of data (from this research) as a standalone resource, cross referenced with the relevant climate risks. See accompanying data catalogue (Section 9.5).
• This research also clarifies which data licences may be required to support evidence report production, and further guidance on the impacts of the different license types.
• Investigate funding options for regional Climate Risk and Vulnerability Assessments. As a first step, a CRVA provides a clear steer on what the key risks are, therefore allowing a more targeted approach to the Evidence reports.
• Scope out the requirements for a Climate Risk and Vulnerability Assessment data platform for centralising the hosting of key datasets. In addition, this should include the development of new datasets and indicators which allow interpretation to non-climate, or non-geospatial users more easily. This could be delivered as a new tool or an extension to an existing one.

There is potential in the longer term to make the key national datasets available, with pre-interpreted indices available in one location. The data could have simple (e.g. high, medium, low) indices with user friendly guidance on what the data is, what it means and caveats (this could be 4-5 key hazards, with a climate vulnerability index). It could link directly to the datasets that have been identified in this report and could also potentially use some of the data from the analytics tools. This would require further research and dialogue with potential providers.

References

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Clydeplan (2022) Glasgow City Region Climate Vulnerability Map. Available online: https://climatereadyclyde.org.uk/climate-vulnerability-map/ [last accessed October 2024]

Environmental Audit Committee (2018) Heatwaves: Adapting to Climate Change. UK Parliament Commons Select Committee. Environmental Audit. 2018. Available online: https://publications.parliament.uk/pa/cm201719/cmselect/cmenvaud/826/82604.htm [last accessed October 2024].

Ferranti, E., Cook, S., Greenham, S.V., Grayson, N., Futcher, J. and Salter, K., (2023) Incorporating Heat Vulnerability into Local Authority Decision Making: An Open Access Approach. Sustainability, 15(18), p.13501. https://doi.org/10.3390/su151813501

Grace, E., Marcinko, C., Paterson, C., & Stobbs, W. (2025). Using future climate scenarios to support today’s decision making. CXC/Government Actuary’s Department.

Greenham, SV., Jones, SA., Ferranti, EJS., Zhong, J., Acton, WJF., MacKenzie, AR., Grayson, N., (2023) Mapping climate risk and vulnerability with publicly available data. A guidance document produced by the WM-Air project, University of Birmingham. Available online: https://doi.org/10.25500/epapers.bham.00004259 [last accessed October 2024]

Greenham, S, Ferranti, E, Jones, S, Zhong, J, Grayson, N, Needle, S, Acton, J, MacKenzie, AR & Bloss, W. (2024a) An open access approach to mapping climate risk and vulnerability for decision-making: A case study of Birmingham, United Kingdom, Climate Services, vol. 36, 100521. https://doi.org/10.1016/j.cliser.2024.100521

Greenham, SV., Ferranti, EJS., Cork, NA., Jones, SA., Zhong, J., Haskins, B., Grayson, N., Needle, S., Acton, WJF., MacKenzie, AR., Bloss, WJ. (2024b). Mapping climate risk and vulnerability in the West Midlands. A guidance document produced by the WM-Air project, University of Birmingham. https://doi.org/10.25500/epapers.bham.00004371

IPCC (2014a). Summary for policymakers. In: Climate Change 2014: Impacts, Adaptation, and Vulnerability. Part A: Global and Sectoral Aspects. Contribution of Working Group II to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, pp. 1-32. Available at https://www.ipcc.ch/report/ar5/wg2/.

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Met Office (2024b) Met Office Climate Data Portal. Available online at: https://climatedataportal.metoffice.gov.uk/ [last accessed September 2024]

Scottish Government (2015) National Performance Framework National Outcomes. Available online at: https://nationalperformance.gov.scot/national-outcomes [last accessed October 2024].

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Scottish Government (2023b) Local development planning Guidance, May 2023. Available online at: https://www.gov.scot/binaries/content/documents/govscot/publications/advice-and-guidance/2023/05/local-development-planning-guidance/documents/local-development-planning-guidance/local-development-planning-guidance/govscot%3Adocument/local-development-planning-guidance.pdf [last accessed September 2024].

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Appendices

Definition of Terms

Usability

Usability is summarised as follows:

• ‘High’ – a dataset which provides simple indices in a climate hazard and risk context and access and can be interpreted easily. Users will not need specific GIS or climate expertise to understand planning outcomes from these datasets.
• ‘Medium’ – data is relatively accessible but requires expertise to interpret or transform. To understand the data in a climate hazard and risk context, as well as planning outcomes, specific expertise in either climate, or GIS will be required.
• ‘Low’ – a dataset which requires specialist knowledge, expertise or skills. Extensive expertise, as well as time and effort will need to be applied to this data in order to arrive at indicators that can be used to make planning decisions.

Data Licensing

The information is provided as guidance on the description and general consequences of the common license types encountered for data. However, care should always be taken to ensure that if any data is used, the license and its limits should be validated before use or distribution.

Table 9.1 – Relevant data licences and their impact on planning authorities

Data Scale and Resolution

Table 9.2 – Description of the shorthand terms used to describe spatial resolution as used in this report. Inset maps © OpenStreetMap contributors

Scale	Spatial Resolution	Example
‘street’	<50cm
‘neighbourhood’	50cm – 1km
‘town’	1km – 15km
‘regional’	15km+
‘national’	100km+

Example Tools to support Interpretation

Climate Risk Vulnerability Assessment methods – the University of Birmingham

A Climate Risk and Vulnerability Assessment (CRVA) map is a method co-developed by the WM-Air project team at the University of Birmingham with local and regional stakeholders across Birmingham and the West Midlands. A CRVA map shows how geospatial climate risk data may be used by local planning authorities. It is pulled together using different environmental, physical, and socio-economic datasets to understand how climate risk varies across an area. The mapping approach prioritises using publicly accessible data and can be replicated by other planning authorities to improve climate resilience (Greenham et al., 2023).

Figure 4 – Birmingham City Council Climate Risk and Vulnerability Assessment map

Birmingham City Council recently published their CRVA (Greenham et al., 2023) on the city’s website (Birmingham City Council, 2024). The CRVA map scores areas of Birmingham based on compiling the presence and extent of 11 different factors that may influence the impact of climate change, where the higher the score, the more at-risk and vulnerable an area and its citizens are likely to be to climate change. The approach is considered a Minimum Viable Product (MVP), i.e. it works, and refinements can be made through use.

West Midlands Climate Risk and Vulnerability Assessment (WM-CRVA) Map

Figure 5 – West Midlands Combined Authority Climate Risk and Vulnerability Assessment Map

The University of Birmingham also collaborated with the West Midlands Combined Authority (WMCA); co-developing a CRVA map for the wider West Midlands (Greenham et al., 2024a). It takes forward the Birmingham MVP approach by including greater consideration of vulnerability. The overall CRVA map scores are based on 24 different factors, each of which is considered one of either a hazard, vulnerability, or exposure factor influencing climate risk.

Methodology

Our approach included two key phases the Discovery phase and the Analysis phase. The discovery phase involved a continuation of planning and refining the scope, and identifying the key tasks needed to ensure we had the full background and context to successfully undertake the research. The Analysis phase involved the main research tasks, including stakeholder engagement and a deep dive analysis of currently available climate risk and hazard data. Both are described in more detail below.

Discovery Phase

• A desktop literature review was conducted (August 2024). The literature included covered information on climate change methods, past climate risk or vulnerability studies (where spatial data was used), and information relevant to climate risk in Scotland as well as the latest policy documents around climate adaptation for Scotland. Here we identified which risks were commonly highlighted within Scotland and what data has been used by others to represent those risks. As well as summarising the key policies relevant to the topic climate change risk and adaptation for the Evidence reports. The literature review findings were summarised in an excel spreadsheet. The full references to the literature are included in Appendix Literature review (Section 9.4.1).
• Three of the currently available evidence reports were also reviewed, this allowed us to understand the current work by planning authorities and what approaches they took. We also began to identify gaps between the produced Evidence reports and the requirements.
• A long list of potential workshop invitees was developed, this was to be refined within the analysis phase.
• Identified a proposed list of relevant data with key search parameters for deep dive assessment. Research partners the University of Birmingham shared the data lists for both their CRVA mapping projects for Birmingham City Council and the West Midlands Combined Authority for review in the context of identifying the same UK wide datasets of their Scottish equivalents.
• Set out an initial stakeholder engagement plan for the approach to both the interviews and a workshop, which was reviewed by and agreed with CXC.

Analysis Phase

• Undertook the dataset deep dive and identified key practical characteristics including cost, availability, and accessibility
• In the stakeholder engagement plan the approach for both the interviews and workshops were also set out. For the interviews we identified a list of stakeholders, this included three planning authorities that had or were in the process of undertaking the Evidence reports. We asked to speak to relevant individuals who had written the reports or who would be or were significantly involved in gathering climate evidence. Here, knowledge gained from the literature review was used to develop appropriate questions to help us better understand the local authority’s approach to gathering evidence, their understanding of the requirements and any difficulties they had faced or anticipated facing, and confidence with the topic (a full list of the interview questions can be found in Appendix Interview responses, Section 9.4.2).
• When selecting stakeholders for both interviews and workshops we aimed to get a mix of stages within the development report process. We also ensured we had a good geographic spread of participants representing the wide range of planning authorities in Scotland. This included, coastal, city based, and Island based planning authorities.
• During this analysis phase we held three interviews with representatives of Fife Council (21^st August 2024), Comhairle Nan Eilean Siar (28^th August 2024) and Glasgow City Council (3^rd September 2024). Interviews included multiple members of the Arup team representing planning, Climate and data expertise as well as a note taker. All interviews were recorded with the permission of the participants. Interview findings were summarised in Appendix Interview responses (Section 9.4.2).
• After the initial interviews a virtual ‘Prioritisation Workshop’ (17^th September 2024) which included representatives from the planning authorities we interviewed, other planning authorities (across a geographic spread and at differing stages in their LDP) and other relevant wider stakeholders (such as representative from Sniffer). The workshop was developed using the findings of the interviews, so that the activities probed at areas of interest and or areas not fully covered by the interviews. The aim of this workshop was to further discuss how planning authorities can improve their access to geospatial data for climate adaptation.

Underlying assumptions

CXC facilitated introductions to key stakeholders for engagement. Engagements were virtual, via Microsoft Teams.

The sample of planning authorities involved was not aiming to be extensive or include all Scottish LPAs, given the scope, size and duration of this research project, but aimed to have good representation across geography, size and stage of progress with the Evidence report.

Literature review and stakeholder engagement

Literature review

A desktop literature review was conducted during the discovery phase, and a full list of references is provided here.

Table 9.3: Full list of references for literature review

Interview responses

This section provides the interview questions and a summary of the answer given by all three planning authorities interviewed.

Q1: What is your role in preparing the Evidence report?

• Most stakeholders interviewed were planning officers based in planning services or equivalent.
• Teams working on this topic of the Evidence report ranged from 1-2 to 4-5 members of staff as the core team. Though generally one or two key individuals took responsibility or a key co-ordination role.
• Use of expertise outside of teams also varied including some drawing on data individuals or climate and sustainability officers.

Q2: What is the status of your Evidence report? And what are the next steps?

• Ranged from early stages of prep to just complete and complete and addressing feedback.

Q3: How clear to you were the requirements / guidance for assessing climate risk through the Evidence report?

• Responses to this question were mixed, some stated the guidance “left a lot open to interpretation”, feeling it was hard to understand what they actually needed to do.
• One Local Authority said the guidance was clear in answer to this question but after further probing it appeared they were not sure on several of the elements within the requirements.
• One response stated that requirements were easier to interpret due to knowledge of other resources.

Q4: How did you assess climate risk/climate change within your Evidence report?

• In one interview the approach had not been developed and it was too early to discuss.
• The other two planning authorities relied heavily on information that had been previously produced for the area, such as past climate profiles or regional risk assessments. Using this information and interpreting it rather than new information or raw data designed specifically for the Evidence report.
• One Local Authority took a place-based approach but struggled with assessing climate risk on this level.

Q5: How have you assessed vulnerability to climate change and inequalities?

• This question was generally not well answered indicating that there was a lack of understanding on the requirements around assessing vulnerability.
• One Local Authority alluded to have a copy of a vulnerability index, but not sure where it was sourced from (potentially from SEPA).

Q6: Do you know what datasets were required to undertake climate risk assessment? 

• One Council in the early stages indicated that they did not yet know what datasets would be required to complete assessments but were aware of the recommended data sets.
• Another realised on using report summarising previous regional risk assessments and interpreted screenshots from these reports. They had tried to get the data but had difficulty locating/accessing it.
• Generally, when talking about data the focus was flood data. No participant mentioned raw climate projection data. Heat hazard data was mentioned by a single Local Authority but in the context of difficulties getting the data.

Q7: Do you know how to/have the ability to access them (within the team)?

• Answers for this question were mixed some had dedicated contacts they could reach out too for data others stated they struggled knowing which data was relevant.
• When probed there generally seemed to be a lack of knowledge on what data was out there, without even thinking about how to access, use and interpret the data.
• General staff resources were flagged as an issue and time needed to use datasets.
• One Local Authority had external GIS support for these kind of tasks from a cross local authority collaboration to share resource, with a 2-year secondment, though this was a resource with a limited timescale.

Q8: Is there anything else you would like to share about the process?

• One set of interviews mentioned that they were beginning to realise the size and scope of the task of gathering and analysing climate risk data as they begin process of evidence gathering.
• One Local Authority mentioned concern about understanding how all of this actually linked into to planning and how in general the evidence would be used to influence planning.
• One also mentioned they had a lot of support from their climate team and could sense check and problem solve with their guidance. This was an invaluable resource.

Workshop

Arup and the University of Birmingham undertook a stakeholder workshop on 17 September 2024 for ClimateXChange Scotland and the Scottish Government on Improving access to geospatial climate risk data. The purpose of this workshop was to discuss together how planning authorities can improve their access to geospatial data for climate adaptation in the context of development planning.

The online workshop brought together planning authorities (across a geographic spread and at differing stages in their LDP) to better understand their needs as a local planning authority and/or climate policy team:

• to prepare Evidence reports, 
• as users of this geospatial climate risk data and;
• understand any current challenges or gaps that need addressing

The workshop provided information on key hazards and risks the planning authorities had been or anticipated focussing on and what data would or had been used. The workshop built on the interviews by delving deeper into the data and methods of analysis. Providing further insight on data gaps, ease of use and challenges faced by the planning authorities.

Additional Resources

Data catalogue

The data catalogue spreadsheet is available online:

Improving access to geospatial climate risk data – Data catalogue

Briefing note for planning authorities

The briefing note for planning authorities is available online:

Geospatial climate data for evidence reports briefing note

How to cite this publication:

Corrigan, J., McNeill, C., Kent, N., Keane, M., Brown, C., Hanson, D., Halliday, C., Ferranti, E., Greenham, S., Horrocks, L., Doherty, J. (2025) ‘Improving access to geospatial climate risk data’, ClimateXChange. http://dx.doi.org/10.7488/era/5650

© The University of Edinburgh, 2025
Prepared by Arup and the University of Birmingham on behalf of ClimateXChange, The University of Edinburgh. All rights reserved.

While every effort is made to ensure the information in this report is accurate, no legal responsibility is accepted for any errors, omissions or misleading statements. The views expressed represent those of the author(s), and do not necessarily represent those of the host institutions or funders.

This work was supported by the Rural and Environment Science and Analytical Services Division of the Scottish Government (CoE – CXC).

ClimateXChange

Edinburgh Climate Change Institute

High School Yards

Edinburgh EH1 1LZ

+44 (0) 131 651 4783

info@climatexchange.org.uk

www.climatexchange.org.uk

1. 
   

   The LDP is required under The Town and Country Planning (Scotland) Act 1997 (Scottish Government, 1997), as amended by the Planning (Scotland) Act 2019 (Scottish Government, 2019). Relevant secondary legislation and published guidance includes The Town and Country Planning (Development Planning) (Scotland) Regulations 2023 (Scottish Government, 2023a) as well as Local Development Planning Guidance (Scottish Government, 2023b). ↑

   
   
2. 
   

   A detailed description of licensing terms and their implication, such as OGL, PSGA, BSD and CC-BY are provided in 9.1.2 – Data Licensing ↑

   
   
3. 
   

   The relevance of the dataset to the hazard groups as discussed with participants. Definitions are shown in Table 1 ↑

   
   
4. 
   

   Captures ease of use by local authority officials. See 9.1.1 – Usability for more detail ↑

   
   
5. 
   

   New deal for agriculture – gov.scot ↑

   
   
6. 
   

   A detailed description of licensing terms and their implication, such as OGL, PSGA, BSD and CC-BY are provided in 9.1.2 – Data Licensing ↑

   
   
7. 
   

   The relevance of the dataset to the hazard groups as discussed with participants. Definitions are shown in Table 1 ↑

   
   
8. 
   

   Captures ease of use by local authority officials. See 9.1.1 – Usability for more detail ↑

   
   
9. 
   

   LCZ Generator ↑

   
   
10. 
    

    https://forest-fire.emergency.copernicus.eu/apps/effis_current_situation/index.html ↑

    
    
11. 
    

    https://www.scottishairquality.scot/ ↑

    
    
12. 
    

    https://wcr.ethz.ch/research/climada.html ↑

    
    
13. 
    

    https://tyndall.ac.uk/projects/openclim/ ↑

    
    
14. 
    

    Administered by the Planning and Environmental Appeals Division, the Gate Check is a process through which the sufficiency of the evidence report is assessed, to confirm there is a sound evidence base on which to prepare a Local Development Plan ↑

    
    
15. 
    

    From an LDP guidance perspective the evidence available at the time of writing the report is proportionate and sufficient. ↑

    
    
16. 
    

    https://climatereadyclyde.org.uk/ ↑

    
    
17. 
    

    https://www.4earthintelligence.com/capabilities/heat/ ↑

    
    
18. 
    

    https://climatereadyses.org.uk/ ↑

    
    
19. 
    

    https://www.ordnancesurvey.co.uk/customers/public-sector/public-sector-licensing/publish-share-data ↑

    
    

The agriculture policies outlined in the Update to the Climate Change Plan (CCP) provide a route map for agricultural transformation to reduce greenhouse gas emissions. They take a co-development approach and work with stakeholders and farmer-led groups to secure increased uptake of low-emission farming measures through new schemes and approaches.

This project examined the potential reductions in livestock methane emissions through breeding, and the policy levers that could motivate these changes.

Findings

• Breeding could reduce methane emissions from the digestive process in livestock by up to 9.5% by 2045.
• Actions and behaviour changes will be required of Government policymakers, pre- and post-farm gate actors and farmers, with key barriers being lack of knowledge and perceived cost.
• Scotland has a well-developed research base around breeding livestock for reduced emissions, placing it in good stead to develop further work in this area.
• Relevant technologies that could be mainstream in Scotland by 2030 include a national breeding programme, sexed semen and the breeding potential of an animal for a specific trait.
• There are very few instances of methane detection methods being used on farm in the UK. The use of proxies such as mid-infrared spectra in milk could be encouraged to determine methane emissions.
• There are many reproductive technologies already in use, particularly in the dairy industry. The report estimates these to be mainstream across the cattle sector by 2045, with lower uptake in the sheep sector due to artificial insemination being a complex procedure.

For further details, please read the report.

If you require the report in an alternative format, such as a Word document, please contact info@climatexchange.org.uk or 0131 651 4783.

Research completed: May 2024

DOI: http://dx.doi.org/10.7488/era/5569

Executive summary

The agriculture policies outlined in the Update to the Climate Change Plan (CCP) provide a route map for agricultural transformation, to reduce greenhouse gas emissions. They take a co-development approach and work with stakeholders and farmer-led groups to secure increased uptake of low-emission farming measures through new schemes and approaches.

This project examined the potential reductions in livestock methane emissions through breeding, and the policy levers that could motivate these changes.

We began by exploring the technologies that detect and measure methane, manage data and are used in the breeding process. This included considering the availability of these technologies in Scotland in 2030 and 2045, with practical considerations for a Scottish context, and identifying the breeding traits that can lead to lower methane emissions.

We then identified the relevant policy levers and behaviour changes and considered what Government, the post-farm market, pre-farm gate actors and farmers can do differently to encourage methane reductions through breeding.

Key findings

• By 2045, breeding could reduce methane emissions from the digestive process in livestock, known as enteric methane, by up to 9.5% (382.2 kt CO₂ equivalent). This is under the “Policy changes” scenario, where legislation will require farmers to introduce methane reducing breeding techniques to their herds (with uptake rates of 100% in dairy, 80% in beef, and 60% in sheep).
  • This includes a 6.8% reduction in emissions from beef, 6% from dairy and 17.5% from sheep.
  • This reduction is achieved by selecting traits for methane efficiency (methane production, intensity and yield), feed efficiency, offspring carcass weight, milk yield and milk fat and protein when choosing breeding stock.
  • Our research highlighted selective breeding for feed efficiency as a promising option. This is because, despite its lower methane reduction potential, it builds on a practice that is already well understood by farmers.
• To achieve emission reductions, actions and behaviour changes will be required of Government policymakers, pre- and post-farm gate actors and farmers. We found key barriers were lack of knowledge and perceived cost.
• Scotland has a well-developed research base around breeding livestock for reduced emissions, placing it in good stead to develop further work in this area. Funding could be targeted towards building on this research, with more data points to support innovation and enhance the robustness of results. Further research could include the potential for a specific methane reduction target to increase clarity and focus action. Funding would be useful if targeted to better communication of the research findings to inform farm advisers, pre- and post-farm actors and supporting farmer peer-to-peer learning. Collaboration between stakeholder groups will achieve greater progress.
• Relevant technologies include methods to detect and measure enteric methane in animals, data management, reproductive technologies and genomics. Those that could be mainstream in Scotland by 2030 include a national breeding programme, sexed semen and the breeding potential of an animal for a specific trait, known as estimated breeding values. The interaction between technologies is key to success. For instance, the wide use of data management tools will depend on the wide use of genomics to collect data.
• We found very few instances of methane detection methods being used on farm in the UK. We therefore believe it is unlikely these will be used beyond research and innovators by 2045. As such, we recommend encouraging the use of proxies such as mid-infrared (MIR) spectra in milk to determine methane emissions.
• Many reproductive technologies are already in use, particularly in the dairy industry, so we estimate these to be mainstream across the cattle sector by 2045. We estimate lower uptake in the sheep sector due to artificial insemination being a complex procedure. However, as sheep start breeding at an early age and often have multiple births per animal, there is greater potential for emission reductions if low-emitting traits are introduced into the herd such as through a ram.

On this basis, we think there is a strong foundation for breeding for reduced methane emissions to contribute to Scottish Government’s methane and climate commitments and to support Scottish livestock farmers’ future resilience. 

Glossary / Abbreviations

Introduction

Methane is a powerful greenhouse gas (GHG), 28 times more potent than CO₂, produced as a by-product of the ruminant digestive process called enteric fermentation. During enteric fermentation, microbes digest feed in a specialised stomach, known as the rumen, subsequently releasing enteric methane. In 2021, enteric fermentation from ruminant livestock, such as cattle and sheep, was responsible for 48% of GHG emissions from agriculture in Scotland.

The UK signed the Paris Agreement, committing to limit global warming to 1.5°C and is a signatory of the Global Methane Pledge, aiming to reduce global methane emissions by at least 30% from 2020 levels by 2030. The Climate Change (Emissions Reduction Targets) (Scotland) Act 2019 outlines a net zero target for Scotland by 2045, with a 75% reduction in emissions by 2030. The strategy to meet these targets is laid out in Scotland’s Climate Change Plan (CCP) 2018-2032 and Climate Change Plan Update (CCPU).

One potential way to reduce emissions from the livestock sector is to select breeding traits in livestock that lead to lower methane emissions.

Traditional breeding programmes select cows or ewes producing offspring with desirable characteristics to either produce meat, milk or fibre, or to continue in the breeding herd. This method relies on waiting for the offspring to mature before the desired traits can be identified. The use of genetic technologies allows desired traits to be chosen at the point of breeding, giving a more assured outcome at an earlier stage.

Genetics are already used to facilitate precision breeding to improve livestock performance. As genetic changes are permanent and cumulative, it is an attractive option for targeting and reducing GHG emissions from ruminants (González-Recio et al., 2020; Manzanilla-Pech et al., 2021; Rowe et al., 2021).

Scottish research is at the forefront in breeding livestock for reduced methane. A recent project by the Roslin Institute highlighted the strong relationship between the rumen microbiome and methane emissions; SRUC has several relevant research studies (published and ongoing), with research facilities such as GreenCow measuring GHG emissions, and Moredun has researched the impact of livestock health and welfare on methane emissions. In 2023, Defra awarded £2.9 million to the sheep sector to launch ‘Breed for Ch4nge’ which aims to measure methane from 13,500 sheep to improve the efficiency of the UK flock; some of the research is taking place on Scottish farms.

The issue is of interest internationally. New Zealand research has shown that breeding for reduced emissions in sheep does not impact productivity and health; Canadian traders are marketing dairy semen with methane efficiency traits, and beef farmers in Ireland are being paid to take part in genomic programmes.

Please note, reducing methane through dietary amendments (such as feed additives) is out of scope for this project.

Project aims

This research project has two key aims:

1. To understand the methane emission reductions that could be achieved in Scotland through breeding. We do this by identifying technologies that detect and measure methane, manage data and are involved in the breeding process. We look at the likely availability of these technologies in Scotland in 2030 and 2045, with practical considerations. Finally, we identify the breeding traits that can lead to lower methane emissions and quantify these.
2. To identify what is needed to support this through policy levers and behaviour change. Using the findings of our literature review and stakeholder consultation, we suggest behaviour changes and discuss their impacts.

Identifying the evidence

To better understand where and how methane emissions could be reduced for project aim 1, we performed a Rapid Evidence Assessment (REA) and a series of stakeholder interviews^[1] (now on referred to as our review) to understand:

• The technologies involved in reduced emission breeding;
• The important traits to select for reduced emissions;
• Emission reduction values;
• The benefits and challenges of breeding for reduced emissions;

The review also sought evidence on what is needed to support further uptake of these technologies in Scotland, for project aim 2.

The technologies involved in breeding for reduced emissions

We grouped the technologies used to identify livestock with low methane emissions into four categories: detection methods, data management, reproductive technologies and animal genomics.

We found little information regarding the timeline of availability for the technologies on farms in Scotland. In the stakeholder interviews, many were not aware of specific technologies being used unless they were directly involved in research. Our research did find international evidence, for example, portable accumulation chambers (PAC) in New Zealand support The Cool Sheep™ Programme. Due to this limited data on timing, we categorised the availability of the technology in Scotland in 2030 and 2045 under the following headings:

Experimental (E): used in research only, with no use on Scottish farms.

Innovative (I): used in trials on Scottish farms by a few innovators.

Mainstream (M): considered mainstream and being used on Scottish farms.

Future possibility (FP): unlikely the technology will be used by 2030 or 2045, however not ruling out its availability in the future.

Not applicable (NA): not relevant to the sector.

The rate of technology uptake will differ between and within sectors. For instance, dairy cattle are milked multiple times a day, providing an opportunity to closely assess individuals interacting with the technology. For the same assessment in the beef and sheep sectors, the grazing nature of the system may require cultural and habitual change for widespread uptake (Jones and Haresign, 2020). Farmers also have different interests, business structures, cash flow etc which impacts their decisions on changing farm practices.

Cost was excluded from our review due to the complexities in estimation. The cost of a technology is likely to depend on the individual farm situation, for example, the number of livestock or proximity to infrastructure or manufacturers. Technologies requiring installation may vary depending on whether adjustments are required to an existing building.

We understand the technologies presented below have the potential to be used in Scotland. The full list of technologies discovered in our research can be found in Appendix A, section 9.1.

Detection methods

Detection methods are used to detect and measure enteric methane to identify which animals emit less. Examples include a respiration chamber which measures the difference in methane emissions with and without the animal, while spot sampling uses head chamber systems or hand-held lasers to take short-term measurements from the animal’s breath (Tedeschi et al., 2022). Further examples can be seen in Table 1.

We found very few instances of detection methods being used in UK research, but we estimate that some will be available in 2030 and more by 2045 (see Table 1). However, as detection methods are primarily a research tool, it is unlikely they will be used beyond innovators by 2045. Practical constraints such as large technological components and measuring a few animals at a time make it challenging to introduce respiration chambers (which are considered the ‘gold standard’ of measurements) on a large scale (Manzanilla-Pech et al., 2021; Rowe et al., 2020). As such, we recommend encouraging use of proxies such as mid-infrared (MIR) spectra in milk to determine methane emissions.

Portable Accumulation Chambers (PACs) have been launched recently by scientists at Scotland’s Rural College (SRUC) for use across the UK. The two units (of 12 trailers) are currently only being used for research purposes. Each trailer holds 12 chambers and is capable of measuring between 60 – 80 sheep per day providing breeding values for methane emissions for representative samples of sheep within a breeding programme (Duthie et al., 2024)

New Zealand currently incorporates the use of PACs in breeding programmes through The Cool Sheep™ Programme, where breeders use PACs to measure and select for low-emitting rams available for breeding. Research trials are underway in countries such as Australia, Norway and Uruguay and now the UK. This technology provides a promising option for Scotland as it is transportable between farms and has a short measurement period which limits stress in livestock. However, current research trials on UK sheep systems need to be completed before PACs can be used widely (Duthie et al., 2024).

Data management

Data management technologies are essential to store, share and analyse data, while also tracking individuals and breeding lines with desired traits to improve target outcomes (including emissions reductions).

The dairy sector is advanced in this area compared to beef and sheep sectors, with established tools for monitoring and measuring production characteristics. Stakeholders discussed the possibility to enhance or repackage these tools and platforms, such as ScotEID, to incorporate methane traits. Using a tool that is familiar for farmers might reduce resistance for adoption.

1. Case study: New Zealand

N-Prove is a free website tool for New Zealand farmers to find the best rams for breeding. Using a series of button­­­­­s and slider scales, farmers can customise what traits they are looking for in a ram. NProve then generates a list of breeders with rams that best fit. Farmers can select terminal or maternal traits, as well as breeders based on location, breed and exclude certain flocks from results. Methane production is an option to select from the maternal traits. The tool is free to use and registration is not required. The tools anonymity means farmers can gather their options for the best breeder for their farm. NProve sources data from a central database and genetic evaluation service (SIL database) that holds information for more than 600 flocks, making it one of the largest genetic evaluations of sheep in the world. This tool could be used in a similar fashion for other species in other geographies as long as an appropriate database was available or was developed to source information.

Data technologies rely on wider infrastructure, such as website portals or cross-country collaboration, making it challenging to estimate the availability for 2030 and 2045. However, there is high potential. Stakeholders discussed that a risk for these technologies is the lack of interest and uptake from farmers, so it is important to inform and engage the industry regarding their benefits.

These technologies offer benefits for farmers by improving the understanding of the genetic qualities of their livestock and having a head-start on understanding the genetics and traits being brought into the herd. See Table 2 for the relevant data management technologies.

Table 1. Examples of the detection methods involved in breeding livestock for reduced methane emissions. Please see Appendix A, section 9.1 for the full list of the technologies found in our review.

Table 2. Examples of data management tools involved in the process of breeding livestock for reduced methane emissions. Please see Appendix A, section 9.1 for the full list of the technologies found in our review.

Reproductive technologies

Reproductive technologies are directly used for breeding. With many already in use on Scottish dairy farms, we estimate that it is likely most will be mainstream in the cattle sectors by 2045. We estimate lower progress in the sheep sector reflecting the current low uptake. Stakeholders discussed the reasons for low uptake in the sheep sector are due to the extensive nature of sheep farming in Scotland and less infrastructure for sheep in this area, such as semen collection and storage, the availability of which determines uptake. In addition to this, artificial insemination (AI) in sheep requires a vet to perform a surgical procedure (in cattle it can be done by a qualified farmer), adding a practical and financial hurdle.

Table 3. Examples of reproductive technologies involved in the process of breeding livestock for reduced methane emissions. Please see Appendix A, section 9.1 for the full list of the technologies found in our review.

Animal Genomics

Genomics is the study of the genome, a complete set of an organism’s DNA^[2]. Genomics provides the opportunity to better understand how well an animal will perform based on its DNA profile. DNA and management both determine performance qualities, such as milk yield. Precision breeding (which is not genetic modification) amends sections of DNA by adding or moving genetic material. This has been used in the cropping sector to improve yields and/or disease resistance. In the livestock sector, research focusses on increased resilience to bovine tuberculosis and mastitis. In 2023, England introduced The Precision Breeding Act, outlining classifications for using precision breeding on crops and livestock, including how the products from them should be regulated, “Neither the Scottish nor Welsh Parliaments have granted legislative consent to the Bill.”.

Table 4. Examples of animal genomic technologies involved in the process of breeding livestock for reduced methane emissions. Please see Appendix A, section 9.1 for the full list of the technologies found in our review.

Traits

Traits are specific characteristics of an individual (physical or behavioural) that are influenced by genes and environmental factors. Understanding the traits that lead to lower methane emissions is key to a successful breeding programme for methane emissions reduction.

It should be noted that the breeding focus, and therefore traits selected, depends on the farmer’s goals. For example, breeding for breeding stock would focus on selecting offspring traits, such as calving or lambing ease, while farms producing fat or store stock would focus on product traits, such as increased liveweight gain (Stakeholder comment, 2023). Currently, most traits are associated with productivity, such as increasing milk yield in the dairy sector. Progress in the beef and sheep sectors has been much slower, with fewer examples found of genetics used in breeding programmes.

The traits in Table 5 are used for breeding in global research to reduce methane emissions directly and indirectly. We have categorised these traits into the following groups:

Production – offspring: Traits associated with reproduction.

Production – product: Traits associated with products from the animal.

Functional: Traits that underpin the function of the animal and are not specific to production or emissions improvements.

Climate: Traits directly linked to reducing methane emissions.

Stakeholders and the literature emphasised that selection for methane reduction traits should ensure production traits, such as health, are not compromised (Stakeholder comment, 2023; Llonch et al., 2017). To look into this further, we examined performance and methane efficiency data from SEMEX. For their Holstein bulls with above average methane efficiency scores, we could not identify any clear relationship between this trait and the other traits. However, this is only for one breed of cattle from one company.

1. Case study: New Zealand
2. Research in New Zealand genotyped low emitting sheep which identified traits that lead to reduced methane emission. The research found no negative impacts on physiology, productivity and health when selecting for reduced emissions.

Our research highlighted the importance of selecting for feed efficiency. Despite this trait having a lower methane reduction potential than others, it will benefit farmers through more efficient use of feed through better feed conversion (Stakeholder comment, 2023).

Table 6 presents the traits that were selected for further analysis, including quantification and the technologies used to detect or select them. Only a few of the traits found in our review were taken forward because some of the traits did not have robust emission reduction values, so were therefore excluded from our calculations.

Table 5. Traits included in breeding indexes around the world, split by sector and type.

Table 6. The quantifiable traits in each sector, with the technologies which can be used to detect or select them.

Quantifying the potential emission savings

We calculated the potential methane emission reductions under different traits for dairy, beef and sheep. Further information can be found in Appendix E.

The traits identified in our review (see Section 4.2) were further evaluated to assess their applicability to emission reduction calculations, based on requirements for defined quantification of methane emission values (either absolute or relative) and values to have a comparative emission baseline. A summary of the applicable traits used in the quantification calculations are presented in Table 7 below, with further information presented in Appendix E, Section 10.6.4.

Table 7. Traits used in the calculations of emissions savings

The current uptake of genetic traits focused on methane emissions is estimated based on our review and discussions with Scottish Government. This was based on an understanding on the currently uptake of AI and breeding technologies used within the sector from expert knowledge and limited research able to be found online. This rate provides a baseline for the quantification of additional uptake in 2030 and 2045 under four scenarios (further described in Appendix E, Section 10.6.4). The scenarios include: no additional intervention, voluntary uptake, supplier demand and policy changes. Scenario uptake percentages are presented with the current baselines in Table 8 below. These values were developed based on technical expertise and discussion with both stakeholders and Scottish Government, as well as published research. The impact of other traits (such as functional, health related traits) could not be estimated in this work as relevant values for methane reduction potential could not be identified in the literature. Further information in the calculation methodology, including additional detail on the selected scenarios, traits selected and limitations to the data is presented in Appendix E, Section 10.6.

Table 8. Scenario implementation values for dairy, beef and sheep

Baseline enteric fermentation methane emissions for beef, dairy cattle and sheep in Scotland in 2021 (totalling 4,020 kt CO2e ), show beef cattle emitted the most at 59% (2,370 kt CO2e ), sheep emitted 26% (1,061 kt CO2e ), and dairy cattle 15% of (590 kt CO2e).

Our calculations found that methane focused traits (methane production/intensity/yield) presented the highest emission reductions for all livestock categories. As the impact of the interaction between traits are unknown, reductions from traits focused on feed efficiency, offspring carcass weight (beef specific) and milk yield, milk fat and protein (dairy specific) are not presented in the maximum reduction potential. However, we acknowledge that reductions for these traits were found within the three livestock categories. Results are presented in Figure 1, Figure 2 and Figure 3 below. These figures show that in each sector, up to 2030, the reductions are relatively steady, but there is a greater reduction at 2045, influenced by the proposed increase in uptake. Due to the proposed uptake percentages the policy change scenario presents the greatest reduction under all traits, with the no intervention scenario showing the smallest reduction due to a 5% increase in uptake in 2030 and no further uptake in 2045.

In the policy change scenario, choosing climate traits, we estimate that emissions would reduce in 2045 up to 382.2 kt CO₂e or 9.5% of enteric methane emissions. This includes a 6.8% reduction from beef cattle (161.1 kt CO₂e), 6% in dairy cattle (35.4 kt CO₂e) and 17.5% in sheep (185.6 kt CO₂e). Smaller reductions are feasible from traits focused on feed efficiency, offspring carcass weight (beef specific) and milk yield, milk fat and protein (dairy specific). Further details presented in Appendix E.

Figure 1. Methane emissions for beef cattle traits against the 2021 baseline enteric methane emissions of beef cattle in Scotland. Please note the y-axes do not start at zero to allow for greater visibility of results.

Figure 2. Methane emissions for dairy traits against the 2021 baseline enteric emissions of dairy cattle in Scotland. Please note the y-axes do not start at zero to allow for greater visibility of results.

Figure 3. Methane emissions for sheep traits against the 2021 baseline enteric emissions of sheep in Scotland. Please note the y-axes do not start at zero to allow for greater visibility of results.

Identifying policy drivers and behaviour change needs

This section examines actions to encourage behaviour change. We understand that behaviour change is needed by four stakeholder groups:

1. Government, which would be policy drivers
2. Post-farm gate market, such as supermarkets, wholesalers, caterers, hospitality etc
3. Pre-farm gate, such as livestock markets, breed societies
4. Farmers

We explored how actions taken by each stakeholder group can enable further behaviour change in the other groups, and present three national level case studies to show actions that promote breeding practices to reduce methane emissions. Examples from these case studies are dispersed through the report in text boxes where the surrounding information was relevant. The countries are as follows:

• Ireland, which has incentivised and subsidised breeding practices.
• Canada, which has incentivised and subsidised breeding practices.
• New Zealand, which has started to take a regulatory approach and has incentivised breeding practices.

All three countries have strong research programmes supporting their policies.

Government action

Scottish Government have an important role in supporting uptake of new breeding techniques through policy. Below are policy drivers that can influence behaviour changes across the other stakeholder groups (post-farm gate market, pre-farm gate actors and farmers).

Legislation and targets

1. Setting a legal target for methane reduction in Scotland can help to shift the focus of the agricultural industry to methane emissions and align with climate commitments that have been made, such as the Global Methane Pledge at COP26. Other countries have set separate targets for biogenic methane, nitrous oxide, and carbon dioxide, such as New Zealand.
2. Case study: New Zealand
3. New Zealand aims to achieve net-zero emissions by 2050 and has a target to reduce biogenic methane by 10% relative to 2017 levels by 2030 and 24 – 47% by 2050. This ‘split-gas’ approach helped focus policy development and action, informed by strong research programmes and stakeholder dialogue. A split-gas approach can also give farmers flexibility to determine the most efficient, cost-effective mitigation practices for their farms (Stakeholder comment, 2023).
4. A methane target for Scotland could encourage constructive conversations among stakeholders about how to reduce emissions, leading to a higher uptake of relevant practices.

Financial incentives

The concept of breeding livestock for reduced methane emissions may be new for many farmers in Scotland. Methane emissions from ruminant livestock are viewed by many as a natural part of livestock farming, particularly in upland farming systems (Bruce, 2013). Therefore, the economic benefits of breeding for reduced methane emissions will need to be clearly demonstrated to farmers.

Cost was mentioned by some stakeholders as a barrier to selecting livestock based on lower emissions. However, there was little understanding of what the specific costs are. Given this, the perceived cost of adopting new breeding techniques might become just as significant as the barrier of cost itself. However, measuring methane from individual animals in a herd using the technologies in Table 1 is labour intensive and not widely available, which creates financial and labour bottlenecks (CIEL, 2023).

6.1.2.1 Subsidies

Some stakeholders believe that new policies could drive financial incentives (Stakeholder comment, 2023). For example, payments for using the technologies presented in section 4.1.

1. Case study: Ireland
2. In Ireland, the Beef Data and Genomics Programme (BDGP) provided payments to suckler beef farmers to improve the genetic merit and GHG emissions of their herd through data collection and genotyping. It was succeeded by the Suckler Carbon Efficiency Programme.

6.1.2.2. Specific funds incentivising measuring emissions

New Zealand supported a programme via funding to enable every stud ram breeder to use PAC chambers to measure emissions. This service was oversubscribed in 2023, indicating that the adoption of measurement techniques could be encouraged by government funding.

1. Case study: New Zealand

The Cool Sheep™ Programme, launched in 2022, is a three-year programme aiming to offer genetic selection to every sheep farmer in New Zealand to reduce GHG emissions. It gathers phenotype data to provide a methane breeding value which will be available on NProve. Breeders wanting to produce low-methane rams can measure a proportion of their flock using a PAC.

6.1.2.3. Research

All three case study countries have strong Government funded research programmes. The outputs from these informs the policies and actions designed to reduce emissions. Scotland is at the forefront of research on breeding livestock for reduced methane, so this just emphasises the importance of focussing research in this area.

1. Case study: Canada
2. Canada’s Agricultural Methane Reduction Challenge will award up to $12 million CD$ to innovators designing practices, processes, and technologies to reduce enteric methane emissions.

Education and advice

Effective communication around breeding for reduced methane and the climate benefits for reducing methane are essential to support uptake. Farmers are crucial stakeholders and while some may be confident in trialling new approaches, advice must be available to help all understand why and how to implement innovative techniques on their farm, manage their farm in a new system and where to ask for help (Stakeholder comment, 2023). Training could also be provided by the private sector.

1. Case study: New Zealand
2. The Pastoral Greenhouse Gas Research Consortium (PGgRc) published a series of factsheets to increase understanding of methane research.

Peer to peer learning is very successful as it provides an informal opportunity to ask practical questions of farmers who have already tried and hopefully succeeded.

1. Example: Northern Ireland farmers visit Scotland

As part of the Farm Innovation Visits, a group of dairy farmers from Northern Ireland visited farms in Scotland to see breeding technologies in practice, such as genetic reports and use of sexed semen.

Farm advisers would be essential to ensure consistent and clear messaging to farmers. Training and communication material could be provided for advisers through existing Government schemes such as the Scottish Farm Advisory Service.

Consumers should be made aware of the importance of reducing methane emissions and of the industry’s associated actions .

Behaviour change

Table 10 shows the outcome of our review on possible Government actions that could lead to behaviour change among farmers, the post-farm gate market and pre-farm gate actors. The three key actions we identified are 1) legislative targets for methane reductions, 2) financial incentives and 3) education and advice programmes.

Table 107: Behaviour changes caused by actions taken by Government

Post-farm gate market

The post-farm gate market includes supermarkets, farm shops, other retailers, consumers and food chain assurance schemes. It has an important role in supporting uptake of new breeding techniques through demonstrating demand and providing price signals. Using our review, we explored actions where the market can influence behaviour change across the other stakeholder groups.

Price signals

Stakeholders discussed the important role of supermarkets, retailers, hospitality businesses, and their suppliers and consumers as these groups can set standards for better prices or to meet customer/societal demands. For example, Tesco aims to be net zero from farm to fork by 2050 , Waitrose has committed to source only from net zero carbon farms in the UK by 2035, and Morrisons aim to be supplied by ‘Net Zero’ carbon British farms as a whole by 2030. Others along the supply chain may need to start to provide evidence of emission reductions as these different retailers and suppliers reduce their Scope 3 emissions, for example as outlined in the British Retail Consortium’s Net Zero Roadmap for the Retail Industry.

Validation of the claims through assurance schemes are important to ensure trust in the food chain. A stakeholder said, “if you take an animal to a ‘normal’ livestock market and claim it has reduced methane emissions, you’ll probably get the same price as any other animal regardless of the additional effort”.

Consumer demand

Consumers paying a premium price are likely to drive new practice adoption. Transparent communication about low emission breeding practices, supply chains and actions on farm is important to demonstrate to consumers the benefits of their choices and reduce the risk of ‘greenwashing’.

1. International example: Sweden
2. In 2022, methane-reduced beef was sold in Sweden. It was well received by consumers, selling out in less than a week. There was however backlash in the media with claims of greenwashing. This example emphasises consumers’ interests in climate-friendly options. while ensuring transparency.

Behaviour change

How the market influences other stakeholders is explored in more detail in Table 10. The key actions are 1) improved price signals from retailers and 2) increased consumer demand which is realised at the sales point.

Table 11: Behaviour changes caused by post-farm gate market actions

Pre-farm gate actors

Pre-farm gate actors refers to industry representatives, levy groups, research institutions, breed societies, and livestock markets. They have an important role in supporting uptake of new techniques through increasing understanding and supporting data collection. Below are actions that can influence behaviour change.

Improving data and data sharing

A key infrastructure need is an accessible database of genetic information, including methane emissions, to enable benchmarking (Stakeholder comment, 2023). Stakeholders noted that farmers may struggle to envision new practices on their farms, and a database can help to conceptualise the traits.

Case study: New Zealand

The ram selection tool nProve provides a user-friendly platform to select required traits in a ram, including methane production.

Existing platforms already used by farmers, such as ScotEID, the Beef Efficiency Scheme (BES), and SRUC’s genetic tool EGENES could add new elements around methane (Stakeholder comment, 2023). For example, Nprove allows farmers to assess methane elements in a user-friendly way.

The Beef Efficiency Scheme (BES) required farmers and land managers to submit tissue samples and other metrics of their beef herd to develop an understanding of the genes within the herd to improve efficiency. Uptake from the industry was low, with only 30% of the national breeding herd participating in the scheme. It currently remains unclear in the literature if the captured data has been incorporated into any local breeding schemes or progressed following the end of the scheme. This scheme could provide valuable learning on the integration of positive genetic traits across the herd in Scotland.

In our review, a stakeholder commented that as only a handful of breeds make up most of the livestock sector in Scotland, the establishment of a database would not take long to create (Stakeholder comment, 2023). This comment however shows the lack of understanding that the genetic material for breeding for methane is independent of breed and based on individual animals.

Case study: Ireland

The Irish Cattle Breeding Federation (ICBF) launched the National Genotyping Programme (NGP) in 2023 to achieve a fully genotyped cattle herd in Ireland. The programme offers beef and dairy farmers a low-cost option to collect DNA samples from calves at birth. The collected information is used to identify specific traits which contribute to national genetic indexes, including methane traits. It also allows farmers to optimise the health and productivity of their herd, while reducing the emissions intensity. The ICBF further publish methane evaluations for AI sires when methane data has been recorded.

Ireland’s NGP and New Zealand’s N Prove provide examples of the development of national databases. In Ireland, the use of metrics like Residual Methane Emissions (RME) index and predicted transmitting ability (PTA) aim to provide an easy way of comparing livestock to the average and to other farmers. Stakeholders noted that a challenge in the Scottish context could be a reluctance by stakeholders to pool data. However this has been successfully achieved in the Scottish pig industry with a number of health and productivity benefits to the individual farmers and to the sector. The NGP also allowed for subsidising DNA sampling of calves which helps to genotype the national herd

Stakeholders discussed the potential for livestock markets to display information on methane emissions. In many markets, a screen displays the weight of the animal and the name of the seller; it could be possible to add the expected or benchmarked methane emissions.

Case study: New Zealand

A methane breeding value was launched in 2019 by Beef and Lamb New Zealand, giving the sector a practical decision making tool. This led to the development of The Cool Sheep™ Programme (see section 6.1.2).

Metrics for methane emissions

Stakeholders recommend adding methane as an estimated breeding value (EBV) as this would allow farmers to benchmark. Stakeholders emphasised that metrics would only be used if they are adopted consistently across Scotland (and perhaps the UK) with cross sector collaboration and there was some incentive for farmers to reduce methane emissions from their livestock. Similarly, to the adoption of RME and PTA figures in Ireland, regulation and guidance from Scottish Government would be advisable to make sure the most sensible metric was adopted.

Case study: Ireland

Residual methane emissions (RME) index is a metric to understanding the difference between the expected methane emissions based on feed intake and the actual emissions. High RME is undesirable and low RME is desirable.

ICBF methane predicted transmitting ability (PTA) values have been produced by recording methane emissions from over 1,500 animals from 19 breeds. These are publicly available for AI beef and dairy bulls. Bulls are classed as favourable or unfavourable compared with the average sire.

Behaviour change

1. The two key take-aways from our review are 1) improved data and data sharing amongst farmers, researchers and across stakeholders and 2) developing metrics for methane emissions to enable benchmarking between farmers and products. Table 12 describes how actions by pre-farm gate actors could support behaviour change among other stakeholders.

Table 12: Behaviour change due to actions taken by the pre-farm gate actors

Farmers

Farmer behaviour change in this context relates to choosing animals with low methane traits to breed, and implementing systems on farm that support this. Some farmers could measure emissions from their livestock to verify the effectiveness of breeding for reduced emissions. Uptake of technologies outlined in section 4 provides the opportunity to better track genetics and traits in their herd.

Farmers will need support to make these changes and to enable behaviour change from the pre-market, post-market and government stakeholder groups identified in the sections above. In addition, the adoption of new practices will likely vary between dairy, beef and sheep producers, and the challenges they face will be different. Farmers who are already using reproductive technologies, such as sexed semen and AI, are expected to progress fastest in this area, given their familiarity with the processes. It is likely that the dairy sector will lead the way, and to a smaller extent, the beef sector. Rapid uptake of AI (and therefore sexed semen) in the sheep sector faces practical challenges, therefore it may be best to prioritise low-emitting traits in rams.

The financial benefit of farmers selecting methane traits is currently unclear. It is likely that the primary motivation will come from the supply chain; it will be important to have specific supply chain indicators. For example, if a milk buyer sets methane reduction goals, suppliers will need to respond. Behaviour change is also influenced by seeing neighbours or peers taking on new practices for example. Below are some points for each of the different livestock sectors groups that should be considered to enable the behaviour change actions identified in the previous sections.

Cummins et al (2022) advise that further research is needed on how breeding for low methane emissions affects the productive and profitable genes that make an animal appealing to farmers. However, research in New Zealand on genotyped low emitting sheep showed no negative impacts on physiology, productivity and health when selecting for reduced emissions and preliminary economic analysis shows that low-emitting sheep could lead to higher profits, primarily due to higher growth rates, a greater proportion of meat, and increased wool production. This section also briefly covers some actions that could be undertaken on farm to support farmers to shift to breeding lower methane emitting livestock.

Sheep farmers

Sheep farmers deal with a large number of animals which tend to be farmed extensively in Scotland, so using methane detecting technologies is potentially more difficult than for other livestock sectors. Despite this challenge, the shorter time to slaughter means that low-emitting traits can be introduced regularly and methane reductions can accumulate quickly (Stakeholder comment, 2023). In addition, other countries such as New Zealand have implemented programmes to begin to measure the national flock such as The Cool Sheep Programme (see section 6.1.2). Stakeholders discussed how the sheep sector produces a lower-value product compared to the cattle sector, so cash flow may be a prohibiting factor in taking on new practices.

Beef farmers

Stakeholders asserted that the beef sector is complicated by several commercial interests in the market which influence genetic improvement. Unlike the dairy sector, AI is not widely used in the beef sector (Stakeholder comment, 2023). However, there are opportunities to influence the genetics of the herd by encouraging bull breeders or bull stud farms to take on practices to support low-emitting traits.

As it is common for dairy cow offspring to enter the beef system, there is the opportunity to use lower emitting dairy animals to feed into emissions reductions in the beef sector (Stakeholder comment, 2023).

Dairy farmers

The dairy sector is the most advanced ruminant sector in using genetic technology and tools for selective breeding. For example, AI is fairly common practice, currently with the objective of increasing productivity rather than targeting emissions. Progress in the sheep and beef sectors is much slower due to challenges around practicalities, sufficient data and uptake of technologies in these sectors. The dairy industry also has a steadier cashflow than beef and sheep (Stakeholder comment, 2023), and is more progressive when it comes to real-time data collection and data management. This puts the dairy sector in a good position to advance breeding for reduced methane emissions.

Cross-farm actions to support breeding lower methane livestock

Strong and structured communication, sharing of ideas and engagement locally are important drivers to enable behaviour change in farming communities. Peer to peer support, for example through breeding groups, to share ideas, showcase technologies and discuss successful and disappointing technologies will enable neighbours and other local farmers to progress faster. Organising local workshops, either by Government supported advisers or leading farmers, would help to spread the word about the importance of breeding for reduced emissions and provide practical examples. The more discussion about the overall aim, the need to reduce emissions, the potential actions, outcomes and successes, the more likely that breeding for reduced methane emissions will become mainstream.

Gaps in the research

We identified the following gaps in research:

• Timeline of availability for the technologies. Due to a lack of robust information in many cases, we made an expert judgement on the availability of the technologies in Scotland up to 2030 and 2045.
• Quantified impact of introducing methane traits in case study countries. We did not find evidence for the actions and policies introduced in the case study countries reducing overall country emissions. A reason for this is that many of the examples presented in the case studies in the appendices are very recent, therefore there has not been enough time to quantify the emission savings. In addition, it could be challenging to see whether these actions had a specific impact emissions due to other surrounding factors, for example changes in stocking rate, or outbreak in disease.
• Evidence for current level of uptake in Scotland and the UK. The review did not find much evidence for current levels of uptake of breeding livestock for reduced emissions.
• Mitigation potentials of some traits. Many sources did not present methane emission values, but instead covered genetic correlations between traits. This meant that due to a lack of data many of the traits identified in the REA (see Table 5) were excluded from quantification. In other cases, some mitigation potentials were not comparative to the baseline used in our study because it presented changes from an entire lifecycle or system.
• The interaction between traits. Emission calculations were quantified for individual traits, rather than combining the mitigation potential for all traits because the relationship and interaction between traits is unknown.
• Due to the smaller quantity of literature available on methane efficiency focused traits, the reduction potential values may be less robust. Greater consistency in measurement, modelling, and presentation and their impacts on emissions savings and animal production would fill this knowledge gap.

Conclusions

We estimate that, by 2045, breeding for reduced methane emissions could achieve a reduction in enteric methane emissions of 9.5% from the baseline, including 6.8% reduction from beef, 6% from dairy and 17.5% from sheep assuming livestock numbers remain constant. This would be achieved by selecting breeding traits for methane efficiency (methane production, intensity and yield), feed efficiency, offspring carcass weight, milk yield and milk fat and protein. Selecting for these traits brings cumulative and permanent emission savings. A limited number of studies researched the impacts of selecting low-methane traits on productivity and health and found that these qualities were not compromised.

Scotland has a well-developed research base around breeding livestock for reduced methane emissions, placing it in good stead in developing further work and providing validation and trust. Research programmes in New Zealand, Canada and Ireland have successfully interacted with farmers, for example, by the development of user-friendly, accessible tools. Our stakeholder comments implies that a comparable interaction between research and on-farm activities and innovation is currently lacking in Scotland.

To achieve the emissions reductions, actions and behaviour change will be required by four stakeholder groups: Scottish Government, pre- and post-farm gate industry and markets, and farmers. Change will need to be co-created across the stakeholder groups.

The financial benefit of farmers selecting methane traits remains uncertain. Therefore, it is likely that the primary motivation will be the supply chain which will need supply chain indicators. For example, if a milk buyer sets methane reduction goals, suppliers will need to respond. Behaviour change is also influenced by neighbours or peers taking on new practices.

The key barriers to uptake are around knowledge and perceived cost. To alleviate these, Government funding could be targeted towards more data collection and research with farmer involvement to improves robustness. Investment in adviser training and farmer peer-to-peer will enable local farmers to progress faster. Organising local workshops, either by Government supported advisers or leading farmers, would help to spread the word about the importance of breeding for reduced emissions and provide practical examples. The more discussion about the overall aim, the actions, outcomes and successes, the more likely it is that breeding for reduced methane emissions will become mainstream.

The technologies we estimate could be mainstream by 2030 include a national breeding programme, sexed semen, artificial insemination (AI) and estimated breeding values (EBVs). However, their success will be about but the interactions between them. For example, data will inform EVBs, which in turn will inform a national breeding programme. If the constant use of methane detecting technologies is required, this may be difficult to implement in extensive farming systems. However, if a proxy measurement was used or the breeding stock was known to provide the necessary traits, this would allow existing systems to continue.

On this basis, we think there is a strong foundation for breeding for reduced emissions to become part of Scottish Government’s commitments.

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UK Parliament, 2023. Genetic Technology (Precision Breeding) Bill 2022-23. Available from: https://commonslibrary.parliament.uk/research-briefings/cbp-9557/

UK Research and Innovation, 2022. Where livestock agriculture fits in a net zero future. Available from: https://www.ukri.org/who-we-are/how-we-are-doing/research-outcomes-and-impact/bbsrc/where-livestock-agriculture-fits-in-a-net-zero-future/#:~:text=Cattle%20breeders%20can%20now%20use,immediate%20fall%20in%20methane%20emissions.

van Breukelen, A.E., Aldridge, M.N., Veerkamp, R.F., Koning, L., Sebek, L.B. and de Haas, Y., 2023. Heritability and genetic correlations between enteric methane production and concentration recorded by GreenFeed and sniffers on dairy cows. Journal of Dairy Science, 106(6), pp.4121-4132.

van Staaveren, N., Oliveira, H.R., Houlahan, K., Chud, T.C., Oliveira Jr, G.A., Hailemariam, D., Kistemaker, G., Miglior, F., Plastow, G., Schenkel, F.S. and Cerri, R., 2023. The Resilient Dairy Genome Project–a general overview of methods and objectives related to feed efficiency and methane emissions. Journal of dairy science.

Wellmann, R., 2023. Selection index theory for populations under directional and stabilizing selection. Genetics Selection Evolution, 55(1), p.10.

Worden, D. and Hailu, G., 2020. Do genomic innovations enable an economic and environmental win-win in dairy production?. Agricultural Systems, 181, p.102807.

Appendix / Appendices

Technologies involved in breeding for reduced methane, full tables

Table 13. Examples of the detection methods involved in the process of breeding livestock for reduced methane emissions.

Table 14. Examples of data management tools involved in the process of breeding livestock for reduced methane emissions.

Table 15. Examples of reproductive technologies involved in the process of breeding livestock for reduced methane emissions.

Table 16. Examples of animal genomics involved in the process of breeding livestock for reduced methane emissions.

Appendix A: REA and stakeholder interviews methodology

REA methodology

The REA methodology used for this project aligned with NERC methodology (Collins et al., 2015) and comprised of the following steps.

1. Define the search strategy protocol, identify key search words or terms, define inclusion/exclusion criteria. This step helped to focus the review on the most relevant sources. Inclusion and exclusion criteria were also defined. For example, studies related to reducing emissions through feed additives were excluded.
2. Searching for evidence and recording findings. Due to the short timescales of this REA, we searched for literature using Google Scholar, utilising our accounts with Science Direct and Research Gate to access restricted pdfs where required. For each search, we recorded the date, search string and number of results found, each search string was assigned a reference number. Examples of search strings include:
   1. breeding for reduced methane emissions
   2. policy drivers for reduced methane emissions in livestock “breeding”
   3. breeding for reduced methane emissions in livestock “Scotland”
3. Screening. Evidence was then screened, initially by title and a selection of sources were screened by the abstract, applying the criteria developed in step 1. This step ensures the relevance and robustness of the evidence that was included in the study.
4. Extract and appraise the evidence. Evidence was then extracted from the papers after screening, this included methane reduction values, traits that lead to reduced emissions and the technologies involved in the process.

Stakeholder interview methodology

Stakeholder interviews were used to collect information that may have been absent from the literature, for example on trials currently taking place that will not yet be included in publications. The stakeholders included researchers and individuals from farmer representative groups. We invited farmers for interview, however, only confirmed one farmer for an interview.

The semi-structured interviews took place over Microsoft Teams, with questions covering all parts of the study. For instance, asking for views on the key traits to select for, any examples of farmers choosing livestock based on emissions and the benefits and risks.

We did seven one-to-one interviews (with four stakeholders based in Scotland) and a group interview with nine stakeholders, all located in Scotland. The group interview was done to allow space for conversation and discussion between stakeholders. During this meeting, we presented the key themes raised in the one-to-one interviews. This included the barriers and drivers to uptake, the availability of technologies and the structural needs to support uptake.

Appendix B: New Zealand sheep case study

Country information

New Zealand is an island nation in the South Pacific and has many similarities to Scotland in terms of its geography and climate. Agriculture is integral to the New Zealand economy with the sector accounting for 10% of gross domestic product (GDP), over 65% of export revenue and almost 12% of the workforce. In 2023 there were 26,821,846 sheep in New Zealand, down from approximately 70,000,000 in the 1980s.

Around half of GHG emissions in New Zealand (49% in 2021) and 91% of biogenic methane emissions stem from agriculture, with sheep farming a key contributor.

New Zealand has relevant international and domestic emissiontargets, including the Global Methane Pledge, and the Climate Change Response (Zero Carbon) Amendment Act 2019, which sets a net zero target by 2050. There is a specific reduction target for biogenic methane of 10% relative to 2017 levels by 2030, and 24 – 47% by 2050. New Zealand also has emissions’ budgets and emissions’ reduction plans which sets out policies and strategies for meeting the budgets.

Accelerating new mitigations such as breeding for low-methane sheep is seen as an important way to reduce emissions alongside the pricing of agriculture emissions, as well as support initiatives.

Relevant research, programmes and technologies

The New Zealand Agricultural Greenhouse Gas Research Centre (NZAGRC) and the Pastoral Greenhouse Gas Research Consortium (PGgRc) are key leaders in the robust and comprehensive programme of research in New Zealand.

• The NZAGRC is a Government funded centre which invests and coordinates research for practical and cost-effective reductions of agricultural GHG. One of its main targets of reducing enteric methane emissions.
• The PGgRc is a joint initiative of the New Zealand Government and the agricultural sector which funds research into ways to reduce methane emissions, including from sheep, such as breeding. It also provides knowledge and tools for farmers to help mitigate GHG, for instance research reports (‘Sheep farmers now able to breed “low methane” sheep’), and fact sheets, with the aim of increasing understanding around the research.

The NZAGRC and PGgRc led the following research programmes related to breeding for reduced methane emissions:

• Low emitting sheep were genotyped and markers were used to identify low emitting traits which confirmed a genetic basis for the variation in methane emissions. After 13 years of selecting for low emitting traits, a 16% difference in methane emissions was found between low and high emitting sheep. Other key findings include no negative impacts on physiology, productivity and health when selecting for reduced emissions. Predications have also been made that with the low emitting flock a 1% decrease in methane emissions per year is achievable The low emitting flock has been producing more wool and leaner meat and the emissions savings are both permanent and cumulative. This programme is ongoing and has produced one of the most comprehensive datasets in the world.
• A methane breeding value was launched in 2019 from research undertaken by NZAGRC and PGRC. This was made available to selected ram breeders through Beef + Lamb Genetics and gives the sector a practical tool to make decisions with. This has then led to the development of the Cool Sheep Programme.
• The Cool Sheep™ Programme was launched in 2022. This three-year programme aims to provide every sheep farmer in New Zealand the chance to use genetic selection to reduce GHG emissions. As well as supporting farmers, this programme gathers phenotype data which feeds back into research. This is available to farmers who are reviewing rams for selection on N Prove. Breeders wanting to produce low-methane rams do so by measuring a proportion of their flock using PAC. When combined with other information and sheep genotyping, this is used to provide a methane breeding value. In November 2023, bookings for use of the PAC chambers by stud breeders were fully subscribed, indicating uptake is high. They note that progress is slow in terms of methane emissions reduction around 2-3% per year, with single trait selection, although this is cumulative.

The four workstreams of the project are:

1. Ram supply: Measuring rams with PAC to make low-emitting rams available for breeding.
2. nProve enhancement: adding methane to nProve.nz.
3. National Impact: using GHG calculators on farms to show methane reductions, rewarding farmers for their efforts.
4. Awareness and outreach: increasing knowledge for farmers, improving public awareness of efforts to reduce emissions while improving national productivity.

Key policies

There is no government policy legislating livestock breeding for reduced methane emissions in New Zealand. However, there are policies that that may contribute to introducing this in the future.

The Emissions Trading Scheme (ETS) is a key tool in New Zealand to help reduce emissions. Under the ETS, businesses must measure and report on their GHG emissions, and surrender one ‘emissions unit’ (an NZU) to the Government for each tonne of emissions emitted. They do this by purchasing NZU. The Government sets and reduces the number of NZU supplied into the scheme over time. This limits the quantity that emitters can emit, in line with emission reduction targets. Businesses who participate in the ETS can also buy and sell units from each other i.e. emitters can buy NZU from forestry companies or farmers to offset emissions. The price for units reflects supply and demand in the scheme. All sectors of New Zealand’s economy, apart from agriculture, pay for their emissions through their ETS surrender obligations. The agriculture sector must report its emissions but does not have surrender obligations.

Currently, no major incentive exists for agricultural producers to reduce their emissions. The ETS was not seen as the right mechanism to price agricultural emissions.

Instead, Government, industry representatives and Māori formed the He Waka Eke Noa – Primary Sector Climate Action Partnership (the Partnership) to reduce agricultural emissions. It is committed to designing an on-farm pricing system that ensures New Zealand’s agricultural products remain internationally competitive while reducing emissions.

Key Stakeholders

Key stakeholders involved in the research, technologies, programmes and policies include:

• Agricultural Greenhouse Gas Research Centre, Government-funded centre which invests and coordinates research for reductions of agricultural GHG.
• Crown Research Institutes, Crown-owned companies that carry out scientific research.
• Beef + Lamb New Zealand, a farmer-owned, industry organisation representing New Zealand’s sheep and beef farmers.
• Dairy Companies Association of New Zealand, representing dairy manufacturing and exporting companies.
• Dairy NZ, industry organisation that represents all dairy farmers.
• Farmers.
• He Pou a Rangi – Climate Change Commission, an independent Crown entity that provides advice to government on climate issues
• Iwi Māori, tribal entities and largest social units in Māori society that represent a group of people and land area
• Māori Landowner groups, groups that represent Māori land that is governed and protected under specific statutes
• Meat Industry Association, voluntary trade association representing red meat processors, marketers and exporters
• Ministry for the Environment, New Zealand Government’s primary adviser on environmental matters
• Pastoral Greenhouse Gas Research Consortium, provides knowledge and tools for farmers, to mitigate GHG
• Public
• Scientists and academics

Successes of research, technologies, programmes and policies

There are many successes in New Zealand for identifying emissions savings, policy drivers and behaviour change which would lead to improved breeding for reduced emissions.

• Full subscription of the Cool Sheep programme to use genetic selection to reduce GHG emissions highlights the keen interest in this programme from farmers

Research indicated that sheep can be bred to produce less methane without sacrificing productivity.

Within the proposal for emission pricing, there have been the following successes that are likely to help drive behaviour change to uptake methane emission reduction breeding selection:

• A farm level, split-gas levy gives farmers flexibility to determine the most efficient, cost-effective mitigation practices for their farms (Stakeholder comment, 2023).
• The He Waka Eke Noa partnership involved key stakeholders discussing practical solutions to reducing emissions (Stakeholder comment, 2023).
• While a policy for pricing agricultural emissions has not yet been legislated and implemented, discussions about a policy helped make New Zealand farmers more aware of their emissions and how to manage them.

Challenges of research, technologies, programmes and policies

There are some challenges with the New Zealand scenario that are relevant for identifying emissions savings, policy drivers and behaviour change which would lead to improved breeding for reduced emissions.

• The fully prescribed uptake of the Cool Sheep programme in 2023 may highlight potential challenges with sourcing enough infrastructure to support all farmers interested in the programme.

In particular, there are challenges related to the agriculture emissions pricing:

Mitigation options under proposed policies are more currently more suited to dairy farmers than sheep and beef farmers.

The sheep and beef sectors are expected to be impacted by the pricing of emissions more than other farming sectors. There are likely to be disproportionate impacts on Māori due to the large proportion of Māori ownership in the sheep and beef sectors and historical context.

Potentially ancillary challenges and unforeseen challenges from the proposal such as environmental and social challenges due to land use changes due to the need to reduce emissions i.e. increased planting of forest may lead to landscapes changes etc.

The recent change in Government has posed a challenge. The 2025 implementation target for implementing the pricing of emissions is expected to be pushed back until 2030 (Stakeholder comment, 2023) and uptake of other methane related programmes could waver too.

Relevance in Scotland

There are some key learnings from the New Zealand scenario that are relevant for identifying emissions savings, policy drivers and behaviour change which would lead to improved breeding for reduced emissions.

• At this stage, it is hard to determine exactly what has encouraged uptake of the Cool Sheep Programme and PAC measurements by sheep farmers. However it is assumed that discussions around agriculture emissions pricing and increased awareness, as well as financial assistance, has no doubt contributed to uptake.
• The He Waka Eke Noa partnership highlighted that each livestock sector has different requirements. In Scotland, for example, stakeholders interviewed for this project suggested that it may be difficult to introduce breeding practices in the sheep sector due to its extensive nature. In addition, there is less frequent cashflow in the sheep and beef sectors compared to dairy, making it more difficult to introduce new practices. In New Zealand suggestions have been made that the dairy industry has had a better lobbying influence in the development of the policy than the sheep and beef industry and have been more successful at influencing a policy that better suits their needs (Stakeholder comment, 2023). Therefore, any consultations or partnerships must include different livestock types and stakeholders, and consider the differences between upland or lowland systems.

New Zealand is one of the first countries in the world to attempt to price agriculture emissions therefore can provide a huge amount of learning that should be considered by Scotland in developing policy around methane reduction.

Having an emissions number to reduce from makes it easier to see how actions will impact. This will encourage the consideration of emission reductions as part of general on-farm decision making, on-farm investment decisions and other considerations.

• The policy impacts on certain farmers and Māori may be of relevance to island farmers and crofters with unique challenges, who may be disproportionately impacted by any climate policies in Scotland.
• Research from the NZAGRC and the PGgRc has produced schemes like the Cool Sheep Programme.
• The ram selection tool nProve provides a user-friendly platform for farmers to select the traits they want from a ram, including methane production. It gives farmers a tool to compare emissions between different animals before purchasing a ram, bull or semen. Because of the Cool Sheep programme and because there are planned policies to reduce emissions, there may be an incentive to use this metric. It may be possible to build on existing tools such as ScotEID and RamCompare in the future to create a similar platform (not only for sheep).

A policy for pricing agricultural emissions has not yet been legislated and therefore whether it has/will contribute to reduced emissions is yet to be realised. However government modelling suggests that the levy could achieve sufficient emissions reductions to meet or exceed methane targets. Discussions about a policy helped make New Zealand farmers more aware of their emissions and how to manage them.

Appendix C: Canada dairy case study

Country information

Canada has similarities in climate and geography to Scotland. Agriculture is a key aspect of the Canadian economy with agriculture and the agri-food system generating $143.8 billion Canadian Dollars (CD$) (around 7%) of Canada’s GDP. Canada is also the fifth-largest exporter of agri-food and seafood in the world. Dairy is a key part of the sector and is a top commodity in five of Canada’s provinces/territories.

In 2020, agriculture was responsible for 30% of Canada’s total methane emissions, with 86% of that being attributed to enteric fermentation. Canada has an emissions reduction target of 40% below 2005 levels by 2030 and to be net-zero by 2050 and joined the Global Methane Pledge. The advocacy group, Dairy Farmers of Canada, have voluntarily set a goal to reach net-zero by 2050.

Description of relevant research, programmes and technologies

Canada is undertaking research and programmes focused on breeding and new genomic technologies for reduced methane emissions in dairy production systems:

• The Efficient Dairy Genome Project (EDGP) developed genomic-based methods for selecting dairy cattle with reduced methane emissions and improved feed efficiency. The project was underpinned by an extensive database used for genomic analysis. For example, correlating MIR with reduced methane emissions. The project also recognised the necessity of featuring the economic, environmental and social benefits of selecting for reduced methane emissions.
• The Resilient Dairy Genome Project (RDGP) aims to integrate genomic approaches to improve dairy cattle resilience and industry sustainability. The project builds on the EDGP, with a focus on additional data collection, management and visualisation to support genomic analyses. Researchers noted an essential component is understanding the interaction between enteric methane emissions and specific farm conditions. For example, predicting methane emissions of individual animals and whole herds using milk MIR spectroscopy. By acknowledging the crucialness of collaboration with industry partners, the project will ensure results will render user-friendly products to enable technological uptake.
• An ongoing commercial endeavour between genetic evaluation provider, Lactanet Canada and genetics supplier, Semex Alliance aims to develop a reliable methane efficiency index that can be easily integrated with common selection indices such as fertility, disease resistance and lifetime profitability.

Description of key policies related to reducing methane emissions through breeding

There are currently no government policies legislating livestock breeding for reduced methane emissions in Canada, however there are some policies that are likely to eventually incentivise it.

• Agricultural Methane Reduction Challenge provided funding awarding up to $12 million CD$ to innovators designing practices, processes, and technologies to reduce enteric methane emissions.

Key Stakeholders

Key stakeholders involved in the research, technologies, programmes and policies include:

• Dairy Farmers of Canada, an advocacy group represent over 10,000 dairy farms, and have set a goal to reach net-zero by 2050
• National Farmers Union, representing Canadian farmers to achieve policy and reform
• Semex the world’s largest provider of cattle genetics
• Genome Canada, a non-profit organisation funding EDGP and RDGP
• University of Guelph, and University of Alberta, orchestrate EDGP and RDGP

Successes of research, technologies, programmes and policies

There are many successes in the Canadian scenario that are relevant to identifying potential emissions savings, and in identifying policy drivers and behaviour change which would lead to improved breeding for reduced emissions.

• Researchers from the EDGP and RDGP recorded enteric methane emissions of reference populations predominantly via a GreenFeed system, a device measuring air composition exhaled by each cow during feeding. Exploiting the correlation between milk composition and emissions instigated the proposal of a genomic evaluation of methane efficiency without sacrificing other production traits. The projects demonstrated a 30% difference either side of average in enteric methane emissions between Holstein cows. This result highlights the importance of genetic selection if breeding for reduced methane emissions is to be an effective option.
• Public-Private Partnerships (PPP) between research and industry can be accredited for the establishment of Canada’s major EDGP and RDGP, and were paramount in the development of the sophisticated database. Stakeholders Lactanet Canada and Semex Alliance effectively utilised this database, and in April 2023, Canada became the first country in the world to commercially market dairy semen containing methane efficiency as a relative breeding value (RBV). Their database and AI catalogue now includes 26 Holstein bulls with proven methane reduction capabilities, and a further 165 predicted. Semex Alliance also estimate widespread adoption of the low-methane trait could reduce methane emissions from Canada’s dairy herd by 1.5% annually, and up to 20-30% by 2050. The collective effort of all members of the Canadian dairy industry has enabled significant progression, to which the inclusion of a methane efficiency genetic valuation can be traced to.
• A GHG Offset Credit System can incentivise farmers to undertake innovative projects that reduce GHGs for financial reward.

Challenges of research, technologies, programmes and policies

There are some challenges with the Canadian scenario that are relevant to identifying potential emissions savings, and in identifying policy drivers and behaviour change for improved breeding for reduced emissions.

• Scottish dairy farmers will likely question the validity of the two major Canadian research projects, as the methane efficiency RBV derives from controlled experimental environments. While this research does account for breed type, it does not reflect Scottish production systems including specific types of feed, pasture type and composition, etc, which may lead to lack of assurance. Furthermore, some Canadian dairy industry officials believe that cattle selected for reduced enteric CH₄ emissions may develop digestion problems, an allegation which generates considerable doubt of widespread adoption success.

Relevance in Scotland

There are some key learnings from the Canadian scenario that are relevant for Scotland in terms of identifying potential emissions savings, and in identifying policy drivers and behaviour change for improved breeding for reduced emissions.

• When compared to other livestock sectors, the data gathering process in the dairy industry is unique as daily milking and feeding activities provide a non-invasive opportunity to measure individual animals without major management changes. Coupling the simplistic nature of data collection with advanced existing genetic databases and the widespread use of artificial insemination (AI), the Scottish dairy industry is capable of reducing enteric methane emissions efficiently. Applying knowledge or making predictions from existing information has great potential to eliminate and/or significantly reduce cost, data collection periods and the requirement of on-farm experimentation.
• Genetic change is a simple and low-cost approach to reduce enteric methane emissions in dairy production systems. Owing to modern technologies and transport capabilities, the methane efficiency RBV developed in Canada is compatible with the Scottish dairy herd and can be purchased and administered via AI to help begin reducing enteric methane emissions.
• Canada has precedented instigating good working relationships with farmers, a goal achieved by highlighting the primary objective of research is to enhance industry sustainability. In response, many Canadian dairy farmers have also recognised constructive engagement with research and industry is fundamental. The establishment of a comprehensive and transparent database has provided assurance and confidence to adopt new best management practices.
• Scotland could consider monitoring the effectiveness of the Offset Credit System currently being considered in Ottawa to see if it incentivises behaviour change or changes finances and markets.
• Canada does not currently offer incentives for low-methane cattle breeding, and livestock breeders do not charge a premium for methane efficiency traits. However, discussions on this topic are ongoing between stakeholders and policy makers and it is looking likely a financial benefit will be introduced in the future.

Appendix D: Ireland beef case study

Country information

Ireland has a similar climate and geography to Scotland. Agriculture is key aspect of the Irish economy with the agriculture, forestry and fishing GDP valued at €3,672m in 2020. In 2020, 55% of farms were specialist beef, with many others including cattle as part of a mixed farm.

In 2022, agriculture was responsible for 38.4% of GHG emissions, making it the sector with the biggest share of emissions. 62.6% was caused by enteric fermentation.

Ireland is part of the Global Methane pledge and legally obliged as an EU Member State to reduce emissions under the EU’s Effort Sharing Regulation, including in agriculture. Ireland’s 2030 target is to deliver at least a 42% reduction by 2030 compared to 2005 levels.

Ireland has developed the Food Vision 2030 Strategy for the Irish agri-food sector which commits to reducing biogenic methane. This includes the ‘Ag Climatise’ Roadmap, covering animal breeding, with an aim to genotype the entire national herd by 2030 to develop and enhance dairy and beef breeding programmes.

Description of relevant research, programmes and technologies

The Irish Cattle Breeding Federation (ICBF) launched the National Genotyping Programme (NGP) for cattle in 2023. This offers beef and dairy farmers a low-cost option to collect DNA samples from calves at birth which can be used for genotyping to identify specific traits or characteristics. The aim of the programme is to achieve a fully genotyped herd in Ireland. This has made national genetic indexes available to farmers, including methane traits. It also allows farmers to optimise the health and productivity of their herd, reducing its emissions intensity. The ICBF also publish methane evaluations for AI sires that have had methane data recorded.

Teagasc has an important role in the research in Ireland. Animal breeding is one of the four solutions from Teagasc to reduce methane emissions from livestock. Current research projects include:

• GREENBREED: Measured methane at the Tully Progeny Test centre using a GreenFeed automated head chamber system. This research led to the publication of genomic evaluations for methane emissions in Irish beef cattle and sheep. It found notable differences in methane emissions from livestock being fed the same diet, 11% of these in cattle were found to be due to genetic differences. This indicates that breeding programmes to reduce methane will be effective in Ireland.
• Collaborative research by Teagasc and ICBF found a 30% difference in methane emissions from beef cattle of a similar size. This lead to the residual methane emissions (RME)[10] index being identified as a metric to rank animals.

Description of key policies

There is no legislation on livestock breeding for reduced methane emissions in Ireland, but the following policies related to GHGs may support this.

• The Beef Data and Genomics Programme (BDGP) paid suckler farmers to improve the genetic merit of their herd through data collection and genotyping, with the aim of lowering GHG emissions by improving quality and efficiency.
  • Payments were made of €142.50/ha for the first 6.66 ha and €120/ha for the remaining eligible hectares (the equivalent of €95 for the first 10 cows and €80 for the remaining cows), farmers have to undertake specific requirements.
  • These requirements include calf registration, detailed surveys of animal characteristics, genotyping and tissue tag sampling, and implementing a replacement strategy based on high genetic merit animals.
  • Additional support in the form of the carbon navigator decision making tool and training courses for farmers are also provided.
  • Participants of the programme were found to be achieving improvements at a faster rate compared to farms not taking part. The impact of the programme can help to promote smaller, more efficient suckler cows to produce more efficient beef.
• The Suckler Carbon Efficiency Programme:

As part of its Common Agriculture Policy Strategic Plan (CSP), Ireland developed ENVCLIM (70) 53SCEP as a follow-on from the BDGP, providing support to beef farmers who implement breeding actions that aim to lower the overall GHG emissions. The BDGP was shown to deliver on both environmental and productive efficiency and emissions per suckler cow are being reduced through breeding strategies. Another measure in the CSP, 53SCT, targets training to complement the Suckler Carbon Efficiency Programme.

Key Stakeholders

Key stakeholders involved in the research, technologies, programmes and policies include:

• Teagasc, Agriculture and Food Development Authority providing research, advisory and training to the agriculture and food industry and rural communities.
• Department of Agriculture, Food and the Marine, Irish government department leading, developing and regulating the agri-food sector, protecting public health and optimising social, economic and environmental benefits.
• Irish Cattle Breeding Federation (ICBF), non-profit organisation charged with providing cattle breeding information services.
• Irish Environmental Protection Agency, independent public body to protect, improve and restore the environment through regulation, scientific knowledge and working with others.
• Irish Farmers Association, Ireland’s largest farming representative organisation.
• Farmers.
• Food Vision Sheep and Beef Group, group of stakeholders established by the Minister for Agriculture Food and the Marine to identify measures that the sector can take to contribute to reducing emissions from the agricultural sector

Successes of research, technologies, programmes and policies

There are many successes in the Irish scenario that are relevant to identifying potential emissions savings, and in identifying policy drivers and behaviour change which would lead to improved breeding for reduced emissions.

• The NGP is a useable database of genotyped methane information available for farmers to use. This is the result of comprehensive research programmes, collaboration between breed societies, and creating useful systems for farmers to benefit from. Making this data easily available to all farmers across Ireland can encourage behaviour change and is a successful programme that could be considered in Scotland. The creation of the ICBF has been essential for this, as it means there is one body overseeing all genotyping and data storage.
• The BDGP is an example of how payments to farmers can be used to gather data and reward farmers for adopting positive practices.
• Research from GREENBREED indicates that breeding programs to reduce methane emissions will be effective for selecting low-emitting livestock, especially combined with the national genomic evaluations, and will have no negative impact on performance and profitability.
• Ireland has produced methane evaluations to enable farmers to identify opportunities to reduce emissions and improve the sustainability of their enterprise.
• Overall, the authors did not find evidence of a quantifiable impact from introducing methane related actions and policies. This may be because the relevant research, programmes and technologies as mentioned above are still relatively new and it is too early to quantify. For example, the NGP is to only be completed by 2027, whereas following on from data collected from methane evaluations, methods are still being developed on how best to incorporate methane traits into beef and dairy production.

Challenges of research, technologies, programmes and policies

Additional research would be required to understand how the policies and programmes were received by farmers and how successful the agricultural community views them to be. We contacted Ireland representatives for involvement in stakeholder interviews however we did not get a response.

Relevance to Scotland

There are some key learnings from Ireland that are relevant for Scotland in terms of identifying potential emissions savings, and in identifying policy drivers and behaviour change for improved breeding for reduced emissions.

• A national database was suggested by Scottish stakeholders (Stakeholder comment, 2023). Therefore, Ireland’s NGP provides an example for Scotland if this was to develop. In particular:
• The use of metrics like Residual methane emissions (RME) index and

predicted transmitting ability (PTA) could give Scottish farmers and crofters an easy way of comparing their livestock to other farmers and understanding where they are compared to the average.

• Challenges in the Scottish context could include reluctance on the part of different breed societies to pool data.
• Ireland have shown that emissions for cattle can be reduced through appropriate breeding strategies and incentives for farmers. Such as subsidising DNA sampling of calves which helps to genotype the national herd.
• The creation of the Food Vision Beef and Sheep Group to chart a path for the sector to meet the emissions emission targets is a potential model for ways that Scotland might bring key stakeholders into the development of key policies to reduce emissions.
• The main ways behaviour change has been encouraged is by making the programmes and policies mentioned above easy to access, for example, the ICBF also provides information to help farmers make decisions about their herd through HerdPlus.
• The BDGP and CSP provides training to farmers who are using the scheme, for which funding is provided.

Appendix E: Methodology and results for the quantification of potential emission savings

Methane emission savings are achievable through breeding and new genomic technologies. The main sources of methane from cattle and sheep in Scotland are enteric fermentation and managed manures. We have chosen to focus our calculations on emissions from enteric fermentation for two reasons:

1. Methane emissions from managed manures are much smaller.
2. Changes to livestock by selecting traits which lead to lower methane emissions will have a greater impact on the emissions from enteric fermentation rather than the emissions produced from livestock manures.

To align with the CCP’s targets, of achieving net zero in Scotland by 2045 and a 75% reduction in emissions by 2030, we present data for potential emission reductions for 2030 and 2045. The following data were used to quantify the potential emission savings:

• Key traits leading to reduced methane emissions, from the REA.
• Methane reduction values associated with traits, from the REA.
• Note: A particular challenge was identifying emission reduction values that were associated with specific traits, that we could use in our calculations. We have used the data available to draw conclusions.
• Baseline emissions data for Scotland from the National Atmospheric Emissions Inventory (NAEI, 2023).
• Uptake values (sector specific) for adoption of chosen traits through breeding, based on findings in the REA, stakeholder interviews and expert judgement.

Baseline methane emissions

To calculate the baseline methane emissions for dairy, beef and sheep, the enteric fermentation emissions of the livestock types for Scotland in 2021 were extracted from the NAEI (2023)^[11]. 

Current uptake rate for adoption of traits

The current uptake rate is an estimated current baseline based on evidence gathered in the REA review of evidence and technical knowledge. This provides a baseline for additional uptake under the scenarios presented below.

Current uptake is set at 75% for dairy cattle, due to the high usage of reproductive technologies (see Section 4.1.3), in particular use of sexed semen and artificial insemination (AI) using Holstein Friesian semen, a key breed which already has proven methane efficiency ratings published as part of the breeding profile. It is understood that methane efficiency ratings are also being developed for other key dairy breeds as observed on UK dairy and beef cattle semen sales websites.

Beef cattle uptake has been set at a 40% baseline as findings show that methane efficiency ratings are less regularly published as part of the beef breed profile on UK semen sales websites. However, artificial insemination of beef cattle is relatively common, although it is not a standard practice as in the dairy industry. It is understood adoption of breeding for reduced emissions is developing and evidence is being gathered (see Section 4).

The current baseline for sheep has been set at 10% based on a comparison with New Zealand where there is an uptake rate of 30% (Rowe et al. in 2020). Following discussions with Scottish Government it is acknowledged that there is some technology usage around the world, but that adoption in Scotland is not yet as high as in New Zealand. Therefore, 10% has been chosen as the baseline. This links to understanding of technology uptake in Section 4.

Scenarios

The quantification of emissions savings was based on four different scenarios to reflect various levels of uptake:

• The no intervention scenario reflects an increase in uptake of 5% from the current baseline by 2030 and remains at the same level until 2045 for all livestock types.
• The voluntary uptake scenario is designed to reflect levels of uptake expected with no other push such as a financial incentive or a relevant policy.  This scenario reflects a 5% increase in uptake from the current baseline by 2030, and an additional 5% increase in uptake by 2045 for all livestock types.
• The supplier demand scenario is based on companies along the supply chain offering financial incentives to farmers that implement breeding techniques to reduce methane emissions.  This value is set at a mid-point between the voluntary uptake and the regulatory scenario.
• The policy changes scenario represents the uptake where legislation has been introduced that will require farmers to introduce methane reducing breeding techniques to their herds. This scenario reflects a 10% increase in uptake from the current baseline by 2030. By 2045 it is assumed there would be 100% uptake for dairy cattle due to the large-scale usage of AI within the industry and progress seen on methane efficiency profiling already published within the key breed profile. It is assumed that beef cattle could reach 80% uptake by 2045, and sheep could reach a 60% uptake by 2045 under a regulatory scenario.

Scenario uptake values are presented for dairy, beef and sheep in Table 17.

Table 17. Scenario implementation values for dairy, beef and sheep

Traits

Traits and technologies with a possible relationship with methane emissions and emission reductions were identified through a REA of relevant literature (see Section 4).

Traits identified were further reviewed to assess their applicability to emission reduction calculations. When assessing each trait to quantify the emissions savings, appropriate values were found to be scarce in the literature. There were two key reasons that led to studies and/or traits being excluded from use in this task:

1. A significant portion of the literature did not present methane emission values and was instead looking at genetic correlations between traits. Therefore, literature that did not present methane emission values or change in methane emissions, either as absolute or relative values, were excluded.
2. Often the changes in methane emission were comparative to a baseline that was not appropriate for our calculations focusing on methane emission from enteric fermentation. For example, papers excluded in our review presented changes to emissions from the entire lifecycle or system.

A summary of the traits, where appropriate values were obtained, are presented in Table 17 below.

Table 18. Traits identified with appropriate methane reduction values used in the calculations of emissions savings

Feed efficiency

References: (Alford, A.R. et al. 2006; Worden, D. et al. 2020; Rowe, S.J. et al. 2021)

The ability of animals to optimally convert feed into liveweight with minimal losses of energy, meaning that animals with high feed efficiency consume less than their peers with equivalent liveweight and weight gain. This trait was identified across all three livestock types and has been highlighted by the stakeholders and the literature as a key trait for emission reductions (see Section 4).

Methane focused climate traits

References: (Quinton, C.D. et al. 2018; De Haas, Y. et al. 2021; Jonker, A. et al. 2018)

Methane traits are likely to have the greatest impact on methane emissions. Here the methane related traits were focused on manipulating the gut microbiome and selecting for animals with certain microbial populations that led to lower methane emissions. While methane traits were identified for all three livestock types, they were presented differently across the literature.

Offspring carcass weight – Specific to beef cattle

References: (Martínez-Álvaro, M. et al., 2022)

Focus on offspring carcass weight in beef cattle reduces methane emissions through increased quantity of product per animal, therefore reducing the number of animals required to produce the same amount of beef product.

Milk yield and Milk fat and protein – Specific to dairy cattle

References: (Bell, M.J. et al. 2010)

Traits reduce methane emissions per kg of milk while maintaining production levels and quality.

Emissions reduction

To calculate the emission reduction of different traits under the different scenarios the following formula is used:

Where:

= Emissions savings (kt CH₄ for the livestock type)

= Baseline emissions (kt CH₄ for the livestock type)

= Uptake (U) for the projected year (y)

= Emission reduction coefficient (%)

This formula calculates a percentage of emissions based on emissions reduction potential and uptake rate and subtracts this portion from baseline emissions. The result is an estimate of methane emissions if the reduction potential and uptake for the trait is achieved. The savings were then calculated by subtracting the estimated emissions from the baseline emissions, and both were calculated in units of percentage of baseline and absolute values (kt CO₂e). This calculation was completed for each trait found in beef, dairy, and sheep sectors, for the years 2030 and 2045.

Limitations in the data:

• All traits have been presented separately as the interaction between traits and the impact this would have on emission reductions is unknown.
• It is acknowledged that traits found within the literature are presented in different units (see Table 7). Traits selected from the literature also presented a percentage change which was used within the change calculations. The percentage change has been applied to total emissions from the relevant livestock sector due to limited data on specific emissions related to more specific production categories such as CH4 emissions per kg milk produced.
• Methane efficiency focused traits have shown to have the greatest methane reduction potential for all three livestock types. However, it is noted that there was less literature available on this subject compared to feed efficiency. Due to the smaller quantity of literature available the reduction potential values selected for methane efficiency could be less robust. Greater consistency in measurement, modelling, and presentation of methane efficiency traits and their impacts on emissions savings and animal performance production could be useful research to fill this knowledge gap.
• Traits reduction factors compiled within the review were presented in different units, however, all presented a percentage reduction. It has been assumed that the percentage reduction would be applicable to be used as a reduction factor as this would have a direct impact on methane reductions independent of the unit the factor was recorded in.
• Limited data was provided within the literature reviewed on the length of time until each trait reaches maximum potential within the population. However, it is assumed that once the trait has been bred into the total population there will be no additional improvements unless new breeding traits are selected. Within the calculations we have assumed that traits will account for their maximum potential to the selected population at the assessment point (i.e., in 2030 100% of the trait will apply to the current baseline uptake with the additional percentage uptake).
• There is the possibility that, due to the nature of genetics, when selecting for certain traits, that they will not fully spread throughout the entire population where the trait is applied. This is a complicated process, and it has been assumed that at each assessment point (2030 and 2045) each trait has reached maximum spread in the portion of the population that has taken up the measure (i.e., in 2030 100% of the trait will apply to the current baseline uptake with the additional percentage uptake).

Results

Figures 4-7 show that in each sector, up to 2030, the reductions are relatively steady, but there is a greater reduction at 2045, influenced by the proposed increase in uptake. Due to the proposed uptake percentages the policy change scenario presents the greatest reduction under all traits, with the no intervention scenario showing the smallest reduction due to a 5% increase in uptake in 2030 and no further uptake in 2045.

Figure 4 presents the methane emissions under the four scenarios for the three traits selected for beef cattle: feed efficiency, offspring carcass weight and methane production. The methane production focused trait has the largest emission reduction (reduction of 161.1 kt CO2e in 2045 under the policy changes scenario), whereas the offspring carcass weight focused trait has the smallest impact at less than 12.4 kt CO2e reduced by 2045 under the maximum reduction scenario.

In correlation with beef trait reductions, methane intensity traits have the largest reduction to methane emissions in dairy cattle, with a reduction of 35.4 kt CO2e observed under the policy change scenario by 2045, as presented in Figure 5. While breeding for methane reductions through feed efficiency has the least change at 7.4 kt CO2e reduced by 2045, this could be due to the work already completed on feed efficiency breeding within dairy. Traits focused on milk fat and protein and milk yield provide similar reduction level levels, however there is the potential for overlapping improvements with feed efficiency as breeding focused on improvements to milk production traits could also link to improvements to feed efficiency.

Reduction potential for sheep is presented in Figure 6 for the two selected traits: feed efficiency and methane yield. As with the cattle categories, the trait focused on methane improvements (methane yield) had the largest potential reduction at 185.6 kt CO2e reduced by 2045 under the policy change scenario, whilst feed efficiency traits saw a smaller reduction of 37.1 kt CO2e by 2045 under the policy change scenario.

Figure 4. Methane emissions for beef cattle traits against the 2021 baseline enteric methane emissions of beef cattle in Scotland. Please note the y-axes do not start at zero to allow for greater visibility of results.

Figure 5. Methane emissions for dairy traits against the 2021 baseline enteric emissions of dairy cattle in Scotland. Please note the y-axes do not start at zero to allow for greater visibility of results.

Figure 6. Methane emissions for sheep traits against the 2021 baseline enteric emissions of sheep in Scotland. Please note the y-axes do not start at zero to allow for greater visibility of results.

Figure 7 presents the methane emissions by 2045 under all scenarios for all traits for each livestock type. The difference in total enteric fermentation emissions for each livestock type can be seen by the dotted baseline line. Beef cattle emitted the majority of the methane from enteric fermentation in Scotland in 2021, with sheep emissions being less than half those of beef cattle, and dairy under a quarter those of beef cattle.

Figure 7. Methane emissions for all livestock for all traits presented against baseline enteric emissions of beef, dairy and sheep in Scotland.

How to cite this publication:

Jenkins, B., Herold, L., de Mendonça, M., Loughnan, H., Willcocks, J., David, T., Ginns, B., Rock, L., Wilshire, J., Avis, K (2024) ‘Breeding for reduced methane emissions in livestock’, ClimateXChange. http://dx.doi.org/10.7488/era/5569

© The University of Edinburgh, 2024
Prepared by Ricardo PLC on behalf of ClimateXChange, The University of Edinburgh. All rights reserved.

While every effort is made to ensure the information in this report is accurate, no legal responsibility is accepted for any errors, omissions or misleading statements. The views expressed represent those of the author(s), and do not necessarily represent those of the host institutions or funders.

ClimateXChange

Edinburgh Climate Change Institute

High School Yards

Edinburgh EH1 1LZ

+44 (0) 131 651 4783

info@climatexchange.org.uk

www.climatexchange.org.uk

1. 
   

   See methodology in Appendix A, section 9.1 ↑

   
   
2. 
   

   DNA contains the information required to create the entire organism, a unit of DNA containing specific information to create a protein or set of proteins is referred to as a gene. It is these proteins which make up the body and control chemical reactions between cells. the study of genes is referred to as genetics. ↑

   
   
3. 
   

   The productive lifespan of livestock. For beef and dairy – a longer productive lifetime would reduce the number of replacement heifers needed to maintain a constant herd size. For sheep – the longer ewes can produce lambs, production efficiency improves. ↑

   
   
4. 
   

   The number of lambs born per number of ewes mated, expressed as a percentage. ↑

   
   
5. 
   

   For beef and dairy – less feed is used for the same output of product and less loss of energy to methane (kg CO₂e/kg product). For sheep – this is CO₂e but as far as can be told it is only methane in this value. Less feed is used for the same output of product and less loss of energy to methane (kg CO₂e/kg product). ↑

   
   
6. 
   

   The number of kilograms gained by the animal per day, measured in kg/day. ↑

   
   
7. 
   

   Overall production of the animal (including feed efficiency), supporting the animal to reach its full genetic potential and ensuring it reaches the highest possible level of performance. ↑

   
   
8. 
   

   ME is expressed as a Relative Breeding Value (RBV) with a mean score of 100 and a standard deviation (how much a point differs from the average), of five. A score below 100 indicates below average and a score above 100 indicates above average. A higher RBV indicates a higher methane reduction potential. ↑

   
   
9. 
   

   The amount of methane produced per unit of milk or sheepmeat produced (kg CH4/kg milk/sheepmeat). ↑

   
   
10. 
    

    RME is the difference between the expected methane emissions from an animal based on its size and feed intake, compared to what it actually produces. High RME is undesirable and low RME is desirable. ↑

    
    
11. 
    

    © Crown 2024 copyright Defra & BEIS via naei.beis.gov.uk, licenced under the Open Government Licence (OGL). ↑

    
    

The generation of energy from organic matter, such as plants, is called bioenergy. The Update to the Climate Change Plan (CCPu) identifies the significant role that bioenergy could play in delivering Scotland’s legally binding commitment to achieve net zero by 2045.

This research examines the economic potential of perennial energy crops (PECs) for farmers and land-managers in Scotland, as well as the wider economic implications.

The three PECs considered are miscanthus, short rotation coppice (SRC) and short rotation forestry (SRF).

Findings

• PECs have the potential to generate income for farmers and land-managers in Scotland.  
• Miscanthus showed the highest average gross margin of the three crops studied but in Scotland there is more suitable land for growing SRC and SRF.
• Farmers and land managers may view PECs as a risky proposition due to uncertainty about market demand and achievable crop sale prices, combined with the need for upfront investment to establish production.
• The most economically and environmentally advantageous approach is likely to be site-specific and determined by local circumstances. 

For further information on the findings please download the report.

If you require the report in an alternative format, such as a Word document, please contact info@climatexchange.org.uk or 0131 651 4783.

Research completed in December 2023

DOI: http://dx.doi.org/10.7488/era/5478

Executive summary

Background

The generation of energy from organic matter, such as plants, is called bioenergy. The Update to the Climate Change Plan (CCPu) identifies the significant role that bioenergy could play in delivering Scotland’s legally binding commitment to achieve net zero by 2045. This could be achieved whilst also supporting a green economic recovery from the effects of the Covid-19 pandemic and a just transition that creates jobs and supports people and rural communities.

To meet this expanded role for bioenergy in Scotland, a scaling up of domestic biomass production would be required. The UK Climate Change Committee (CCC) highlighted the opportunity for domestic production as a key pillar for delivering the CCPu ambition.

This research examines the economic potential of perennial energy crops (PECs) for farmers and land-managers, as well as the wider economic implications. The three PECs considered are miscanthus, short rotation coppice (SRC) and short rotation forestry (SRF).

Key findings

Profitability of perennial energy crops

• PECs have the potential to generate income for farmers and land-managers in Scotland.
• Comparison of gross margins shows income from PECs is likely to be lower than from other typical farm enterprises on suitable land, such as lowland cattle and sheep and ‘mixed agriculture’. This is assessed on the basis of yearly average gross margins over the lifetime of the PEC in comparison to equivalent gross margins for other farm enterprises.
• Income (gross margin calculation) from PECs compared very favourably in the analysis compared to the farming type known as ‘general cropping: forage’. This is growing crops for animal consumption, usually on lower quality land, and it typically makes a significant loss.
• There is a need for greater confidence that PECs will deliver good economic returns in order for them to be viewed as an attractive, economically viable option by farmers and land managers in Scotland. High upfront establishment costs for perennial energy crops and low revenue potential are both likely to hinder uptake.
• Miscanthus showed the highest average gross margin of the three crops studied, at £382 per hectare per year. However, there are some potentially limiting factors:
  • There is uncertainty about achievable yields in the Scottish climate and on the grades of land above category 4.1 in the Land Capability for Agriculture in Scotland.
  • There is limited theoretical growing area in Scotland, which is much lower than for SRF or SRC.
• SRF and SRC showed lower profitability for farmers: £80 and £87 per hectare per year over their lifetime respectively for ‘SRF: broadleaved’ and SRC. However, there is more suitable land for growing these.
• SRF conifer would see a negative gross margin, given that the production costs outweigh the value of the crop sold.

Potential opportunities

• PECs could help diversify a business, creating additional income, without adding significant additional labour requirements or ongoing input costs because minimal management time and inputs are required once crops are established.

Potential barriers

• Cash flow could pose a barrier to uptake. The distribution of costs and income year-on-year for PECs is significantly different to typical farming activities which have an annual profit cycle. PECs need investment in site preparation and planting upfront, but income only arrives after first harvest several years later. This is 2-3 years for miscanthus with subsequent annual harvests, 6 years for SRC with periodical harvests thereafter, and 15 years for SRF first and only harvest.
• Farmers and land managers may view PECs as a risky proposition due to uncertainty about market demand and achievable crop sale prices, combined with the need for upfront investment to establish production.
• Other potential barriers to uptake include: farmer and land-manager unfamiliarity with PEC production, low appetite for risk, need for new skills, access to equipment and services, concerns about community perception of land-use change, and impacts on other agricultural production, e.g. available animal feed.

Enhancing economic potential and production

Potential approaches to improve the economic potential of PECs in Scotland include:

• Financial incentives, such as government specific subsidies under future agricultural support or other market-focused incentives.
• Risk reduction strategies, such as secure, attractively priced contracts with end markets, alongside expansion of the market.
• Innovations to allow processing at the farm and to improve transportability of crops could also help to increase the economically viable travel distance.
• Improving access to skills and knowledge to produce PECs could also remove a barrier to uptake, if economic prospects are improved.

Implications for wider Scottish economy

• Future demand for PECs to support the Scottish Government’s climate ambition is likely to require increased production, and previous research suggests 38,000 hectares could be feasibly planted by 2032 and 90,000 by 2045.
• We modelled two demand scenarios to illustrate the potential range in results if land was transitioned to growing PECs:
• Scenario 1: conversion of approximately 38,000 hectares. This would result in an economic gain in terms of increased gross margin of around £9.6 million. This would however result in a shortfall in non-PEC agricultural yield (crops, stock-feeding crops and grass) of between 537,600 and 700,000 tonnes.
• Scenario 2: conversion of approximately 90,000 hectares. This would result in an economic loss of around £9.5 million per year, based on gross margin, and a shortfall in non-PEC agricultural yield (crops, stock-feeding crops and grass) of between 708,200 and 1.6 million tonnes. The financial loss is because under this scenario more economically advantageous land is transitioned to PECs and the PECs perform less well economically.

Economically viable production locations

• Economically viable production locations for PECs are influenced by multiple factors including proximity to markets and local access to services and facilities for crop management, such as harvesting contractors, to avoid incurring excessive costs.
• The research identified suitable growing regions (some SRC/miscanthus and most for SRF) within an economically viable transport distance to existing biomass plants and potential sites for Bioenergy with Carbon Capture and Storage (BECCS) near the proposed east coast carbon capture and storage feeder pipeline (assumed 50-100 km).
• Economic viability may be a barrier to SRF production increases even if suitable land is available, given that it is economically uncompetitive against other land use options.

Potential further steps

Key debates and areas for further research include:

• Considering more in-depth ‘whole farm’ economic analysis. This study focused on gross margin comparison, which is useful for comparing specific crops and farm enterprises, but has limitations in terms of how well it allows assessment of integration of energy crops into a whole farm business. This will vary farm to farm but could be explored through farm case studies. This could include considering a wider range of costs for farmers and that after initial set up the PECs would require less workload.
• Comparing the economic and environmental potential of using land for energy crops with utilising the same land for other renewable energy options, such as using the land for solar panels alongside grazing.
• Exploring the potential role for on-farm use of perennial energy crops.
• Considering future biomass markets, including how future Greenhouse Gas Removal (GGR) schemes, global demand and demand from biotechnology sector may impact it.
• Identifying how to make domestic biomass from energy crops a more attractive option than imports and a more profitable use of land, and on what basis this can be justified. For example, taking account of full LCA and rewarding greatest emission saving.
• Considering in more detail the role of PECs in the context of how the agriculture sector is changing and how it may have to change to reduce GHG emissions.
• Considering the value, including the financial value, of other benefits of energy crops, such as flood mitigation or animal shelter, relative to existing or potential alternative land-uses.
• Exploring how PECs support/interact with tier 2 or 3 objectives of the ARP.
• Considering the impact of subsidies.

The most economically and environmentally advantageous approach is likely to be site-specific and determined by local circumstances. Making judgements about the best use of land is complex for policy makers, farmers and land managers alike. Guidance on this decision-making is likely to be needed.

Abbreviations table

Introduction

This evidence assessment focuses on examining the economic potential of perennial energy crops (PECs) for farmers and land-managers in Scotland, along with considering the wider economic implications for Scotland. The assessment builds upon recent ClimateXChange reports which demonstrated that there are significant opportunities for the expansion of perennial energy crop cultivation in Scotland (Martin et al, 2020) and that increased supply of biomass for energy generation from such crops will be needed to meet forecast future demand in the context of Scotland’s climate mitigation plan goals (Meek et al, 2022). However, in scaling up domestic biomass production it is important to consider how the economics intersect with other relevant issues including biodiversity, land-use, water management and a ‘just transition’. This report aims to consider these issues, alongside the economics and support the Scottish Government’s development of policy in relation to perennial energy crop production.

The policy context for energy crops in Scotland

The Scottish Government’s Update to the Climate Change Plan (CCPu) forecast a role for Negative Emissions Technologies (NETs) , including bioenergy with carbon capture and storage (BECCS), to remove carbon dioxide from the atmosphere to compensate for residual emissions. ). The UK Climate Change Committee (CCC) acknowledges Scotland’s opportunity to scale up domestic biomass production to meet this aim, recommending careful consideration of impacts on land-use and agriculture. In line with Scottish Government’s Vision for Agriculture, and set out in the Scottish Agricultural Bill, future subsidy support which will replace Common Agricultural Policy, will be split across unconditional support and support targeted to sustainable food production and environmental outcomes, including low carbon farming and biodiversity. Scotland’s draft ‘Energy Strategy and Just Transition Plan’ aims to use bioenergy where it can best support Scotland’s Net Zero Journey, and aligns with and supports Scotland’s goals for protecting and restoring nature. Considering the role for production of PECs in the evolving Scottish policy landscape will be critical.

Alongside this the UK Government has also published a new biomass strategy, which aims to support sector growth and strengthen biomass sustainability. The strategy acknowledges that bioenergy policy involves a mix of reserved and non-reserved powers, and so as the Scottish Government develops its Bioenergy Policy Statement, Scotland has an opportunity to build on UK policies and develop policies appropriate for Scotland. Further policy information is included in Appendix A.

Introduction to perennial energy crops for Scotland:

Previous research for CXC identified that perennial energy crops (PEC) present opportunities for scaling up biomass production in Scotland, with short-rotation coppice (SRC), short-rotation forestry (SRF) and energy grass Miscanthus, showing most potential (Martin et al, 2020). Details of each crop can be found in Appendix B. PECs support climate mitigation by providing a renewable energy source; displacing fossil fuel use; helping to reverse soil carbon loss, and acting as a carbon sink. When used for energy generation and combined with carbon capture and storage (CCS), such crops have the potential to generate negative emissions and contribute towards Scotland’s net zero ambitions. PECs can also bring additional benefits, such as flood mitigation (see Section 4 below for further details).

Figure 3.2: Schematic diagram of bioenergy with carbon capture and storage ^[1]

Currently, Scotland grows only a small area of PECs – about 250 ha (Martin et al, 2020). Previous geo-spatial mapping work for Scotland (Martin et al, 2020) has shown theoretical potential for approximately 900 kha of land, to be suitable for PECs (913kha SRF, 219 kha SRC and 52kha Miscanthus – with some overlap between suitable areas) mainly in the east and the lowlands. This analysis considered topography, soil type, climatic variables and suitable land capability classes^[2] to identify these theoretically feasible growing areas. Future demand for PECs to support the Scottish Government’s climate ambition is likely to require increased production of such crops.

Markets for PEC Biomass in Scotland

Research^[3] has identified the following potential uses of biomass via ‘Negative Emissions Technologies’:

• BECCS Power – bioenergy with carbon capture and storage (BECCS) for electricity in a power station
• BECCS hydrogen – either via gasification of biomass or steam methane reforming of biomethane, with carbon capture and storage
• BECCS in industry (for heat and other industrial processes)
• BECCS Biomethane – processing of biomass via Anaerobic Digestion (AD), gasification or pyrolysis, with carbon capture and storage
• Biochar – pyrolysis of biomass, with carbon capture and storage

PEC biomass can also be used in combined heat and power plants and biomass boilers at a variety of scales. The market for the biomass produced from PECs is relatively immature in Scotland. There are several biomass energy plants ranging in size from large scale industrial units and power stations to small units supplying individual farms. These mostly utilise wood from local forests, waste wood from Scotland sawmills and other industries so the market for further PEC biomass is currently limited^[4]. Scotland’s largest wood-fuelled power station, is located in Markinch, with 55MW capacity utilising mostly recovered wood, some virgin wood chip. The next biggest is Steven’s Croft, in Lockerbie which generates 44MW of electricity and 6MW of heat which initially planned to source fuel from local forests (60%), SRC willow (20%) grown within a 60-mile radius (and requiring around 4,000 hectares land) and recycled wood fibre (20%) (Warren et al., 2016), but the latest data suggests it mostly uses a mix of wood and waste wood^[5]. BECCS plants are not expected to deploy in Scotland until 2030.

Evaluating economic potential of PEC in Scotland

To understand the real potential, it is critical to consider not just the overall economic viability of PECs, but also how the demand for land for PECs can be balanced against, or integrated with other uses such as food and fodder production and biodiversity, and the skills, knowledge and attitudes of the farmers or land managers.

The economic potential of energy crops

A Rapid Evidence Assessment (REA) seeking evidence of the economic potential of energy crops in Scotland was undertaken and identified peer-reviewed and grey literature. The methodology can be found in Appendix C. The review focused on Miscanthus, SRC and SRF to specifically identify:

• The positive and negative economic potential of energy crops.
• Other (non-economic) opportunities and barriers to deployment.
• Further economic potential (e.g., in relation to employment; technologies; wider decarbonisation, just transition).

Key insights are presented here, along with relevant insights from the stakeholder research. For full details of information found in the literature review and references to information sources (please see Appendix d), for details of stakeholder interviews conducted see Appendix G.

Key findings of the rapid evidence assessment and stakeholder engagement 

Evidence of positive economic potential

• There is evidence that PECs can be profitable, but there are limited studies directly applicable to Scotland and to the current economic climate (Appendix D: 15.1)
• Economic performance of biomass production is influenced by production costs, crop yields, crop price and end-use/market opportunities. (Appendix D: 15.1)
• Several studies comparing energy crops reported a high return per hectare for miscanthus primarily due to low maintenance cost along with the low requirement for field operations. (Appendix D: 15.1)
• The tree species chosen for SRF influences plantation establishment costs and therefore profitability as costs vary between species. Initial indications from trials underway in Scotland suggest hybrid apsen to have most potential, with common alder, silver birch and Sitka spruce having potential at some sites. (Appendix D: 15.1)

Evidence of negative economic impacts

• The most prominent evidence of negative economic impacts in the literature was the high upfront cost to establish PECs, lack of established markets, and the uncertainty over the stability of the long-term market. (Appendix D: 15.2)
• Profitability and economic considerations for farmers are dominated by high establishment costs, uncertainties about the market, a delayed period of revenue, and biomass yield. (Appendix D: 15.2)

Economic potential of PECs in comparison to other land uses

• The literature review did not provide clear evidence of how the three key PECs compare economically to other crops, annual crops and agricultural land-uses – some studies showed favourable comparison and others did not. Limited insights can be gained from the literature given the recent economic changes affecting agricultural costs and market prices (Appendix D: 15.3)

Influences on decisions to plant PECs

• One of the main factors affecting the uptake of PEC is economic profitability (Appendix D: 15.4)
• Appetite for and perception of financial risk, skills, attitudes and access to markets can influence farmer and land-manager decisions. (Appendix D: 15.4)
• Even where PECs, or energy crops in general, can deliver positive economic results for farmers and land managers, this on its own is not always sufficient to convince them to start growing PECs. (Appendix D: 15.4)

Other features of PEC production that influence economic potential

• Producing PECs has specific economic implications for growers which influence their economic potential and attractiveness. These include lack of flexibility of land-use, reduced market responsiveness, and opportunities for diversification alongside current farming enterprises. (Appendix D: 15.5)
• To view PECs as economically worthwhile, farmers need confidence that they can achieve an acceptable and secure market price into the future. As farms typically operate in a risk-averse manner, reduced risk is an important factor in farmer decision-making for PECs. (Appendix D: 15.5)
• The way PECs are deployed on farms influences their economic potential. Integration of PECs alongside other enterprises and on land which is not performing well could be advantageous. (Appendix D: 15.5)

Opportunities to improve economic potential

• Cultivation techniques, crop variety choice and other technological developments can influence economic potential of PECs in Scotland and have potential to improve profitability for farmers and land managers in future. (Appendix D: 15.6)
• There are factors which can negatively affect the economics of PEC production, which if addressed are potential opportunities to improve economic performance. (Appendix D: 15.6)
• Gaps in the crop (i.e. patches where it didn’t grow) was a key factor reducing profitability of miscanthus in the UK.
• Ensuring access and enabling harvesting equipment is essential for economics of SRF to be viable
• For SRF effective plantation establishment is important for the economics and general success of a SRF plantation
• Single species monocultures can offer greatest economic return by providing higher yields per hectare
• Highest yield are achieved on fertile soil or under intensive management systems, including weed control, fertilizer application and irrigation

Evidence of potential for wider economy

• There was limited research addressing the potential contribution to the wider Scottish economy and a just transition, but some opportunities and challenges can be inferred. These include sales for local energy generation and other industrial uses, employment opportunities in contract services, along with potential payments for environmental outcomes. (Appendix D: 15.7)

Evidence of non-economic opportunities

• Non-economic opportunities and benefits of PECs were identified including several relating to positive environmental outcomes such as reduced agro-chemical use, reduced soil and water pollution, carbon sequestration, and biodiversity benefits. (Appendix D: 15.8)
• The opportunities for environmental improvements resulting from PECs vary depending on planting, prior land-use and landscape context. (Appendix D: 15.8)

Challenges and deployment barriers

• Non-economic challenges facing the production of PECs in Scotland, relate to skills, land-use commitment, compatibility with current culture and habits, farm businesses, perceived land suitability and environmental concerns. (Appendix D: 15.9)
• Deployment barriers include the need for farmers to commit land for a long period of time, land quality, knowledge, profitability, time to financial return and social resistance relating to whether land should be used for energy or food production. In addition for SRC and SRF, converting land once planted is challenging, and additionally for SRF conversion be restricted by regulations as land will no longer be classed as agricultural. (Appendix D: 15.9)
• Lack of access to specialist skills and to specialist contractors and machinery was identified as a barrier to deployment. While there is interest amongst farmers in diversification, appetite for change is tempered by concern about moving into unfamiliar activities which require new skills.
• Culture and attitudes can be a barrier to PEC deployment. (Appendix D: 15.9)
• There are concerns about the impact on biodiversity from PECs. (Appendix D: 15.9)
• Energy generation from biomass is a potential source of direct and indirect emissions and limiting these emissions would need consideration. (Appendix D: 15.9)

Other relevant crops and planting regimes

• Hemp has the potential to provide high yields or returns with little or no pesticides and insecticides, significant potential in carbon sequestration, fits well into crop rotations with food and feed crops and helps improve soil structure and soil-borne pests. Constraints on producing hemp in Scotland includes the current lack of market as there are no large processing facilities in or near Scotland, strict regulations on growing hemp including the need to obtain a costly license, and some reports of low profitability according to Scottish growers. (Appendix D: 15.10)
• Specific studies focused on Scotland to show how PECs could be grown in agroforestry systems were not found, but provided the design of agroforestry systems can allow for economically efficient planting, management and harvesting it could provide an advantageous model. (Appendix D: 15.10)

Key evidence gaps

The research found some uncertainties – due to lack of Scottish specific data and in relation to climate impacts on PECs – which are described in the relevant sections above, and also some key gaps in the evidence which are summarised here.

Lack of Scottish data and research leading to economic uncertainty

Research related to the production and economic potential of energy crops in Scotland is limited. SRC is currently grown, but only at a small scale, and miscanthus still requires further trials and research before implementing at a commercial scale. SRF trials are currently underway in Scotland with findings slowly emerging as plantations reach maturity (Parratt, 2017). There is therefore uncertainty regarding the economic potential in Scotland.

The literature is inconclusive regarding the financial performance of PEC production. Conflicting results are found across studies, for example, a study in Ireland found miscanthus production to be an economically viable option (Zimmermann et al., 2014), yet in France, Miscanthus was found to be less profitable compared to conventional cropping systems (Glithero et al., 2013). Research by Warren (2014) reported that the soils and climate across Scotland offer significant biophysical potential, especially for SRC willow cultivation, which can also achieve good growth rates. However, with such limited data on Scotland and in light of the less favourable climate than found in locations of many studies there is uncertainty about the economic viability in Scotland.

Climate change

The effects of climate change on PECs are to some extent unknown. Research suggests that SRC willow yield may reduce as a result of rising temperatures, while miscanthus performs favourably (Alexander et al., 2014). However, as the temperature rises, this may change the habitat suitability, further research is required to establish the suitability and risks that a changing climate may have on seed development in miscanthus throughout the UK (Martin et al., 2020). We did not find research which commented on how extreme weather such as storms, flooding and drought would affect PECs. Some research suggests that water-logged soils hinder growth of PECs (Martin et al, 2020), but a recent technical webinar from Biomass Connect suggested that willow SRC is not negatively affected by water-logging, and can help improve water management when established.

Active debates within the sector

It is evident from the literature and stakeholder interviews that there are some topics with differing views including what types of land are most suitable for PEC growing considering the wider land-use debates, and likely impacts on biodiversity.

Land use and use of unproductive areas of land

In Scotland, there is competition for land to deliver food, materials, environmental services (such as carbon sequestration), leisure opportunities and more (Martin et al., 2020; Scottish Government, 2021). Scotland has the potential to produce 9.25TWh/yr and 1.75Modt/yr for SRC (Martin et al., 2020) such as SRC willow, however amongst the farming community there is social resistance relating to land being used for energy instead of food production (Anejionu and Woods 2019). The Scottish Government’s Land-use Strategy (Scottish Government, 2021) highlights the complexity of balancing the need for land to support the move to net zero with other essential activities such as food production, and that whilst land-use decisions are often determined by the land suitability, much land is suited to multiple different uses. In these cases multiple factors need to be considered as to whether PECs are a suitable use for the land.

Literature identifies that using ‘marginal’ land, for energy crop production could be a solution to this land use debate. However, there are several challenges in understanding whether this ‘solution’ could usefully apply in Scotland. Ranacher et al., 2021 found there is a gap in the available literature regarding farmers’ willingness to adopt short rotation plantations on marginal lands. There is also no agreed definition in the literature of what comprises ‘marginal’ land, so it is unclear how this would apply in the Scottish context. Much discussion in research focuses on cropland, yet in Scotland grasslands including rough grasslands, which may be viewed as ‘marginal’ from some perspectives, are a critical part of the Scottish rural economy and environment and so a more indepth analysis of the potential social, environmental and economic implications of PECs on grasslands is needed. Additionally, not all literature agrees on whether PECS will successfully grow on marginal land.

Biodiversity & ecosystem services

Converting land to energy production in Scotland will have direct impacts on biodiversity, wildlife, and landscape connectivity, yet the exact nature of these is unclear from the literature. Research shows that bioenergy crop choice and location influence biodiversity outcomes – choosing appropriate bioenergy crops in the right location is vital for the protection of biodiversity and ecosystems and to prevent damage to the surrounding ecosystem.^[6] Contradictory evidence has been found throughout the REA on the effects of converting land for energy crop production in Scotland. Existing sustainability criteria for the use of biomass to produce heat or electricity require that PECs are not grown on land of high biodiversity value^[7]. Beyond application of these criteria, the research could create uncertainty about how to select the right crops for the right locations in Scotland to ensure good outcomes for biodiversity and ecosystem services. Extrapolation of potential biodiversity effects from conversion of ‘marginal’ land has low confidence (Holland, et al., 2015) (Vanbeverena & Ceulemansa, 2019), and application of this research to the Scottish context with different land-use types is therefore very difficult.

The impact on biodiversity from SRC, SRF and Miscanthus differ depending on location, previous land use and crop type and management (e.g., cultivations, pesticide, and fertiliser use). The replacement of any semi-natural habitat by a dedicated bioenergy crop is likely to result in significant biodiversity losses due to creating a monoculture habitat (Martin et al., 2020). Significant areas of land classified as ‘Less Favoured Areas’ (LFA) in Scotland which were identified as potential PEC growing areas could be described as semi-natural – and seen as ‘marginal’ – but there is a risk of biodiversity loss if this is converted to PEC.

The REA identified a conflict in opinion as to whether PECs provide a biodiversity gain or loss. Firstly, factors such as reduced ground disturbance, increased diversity of nectar and pollen sources, and the potential to provide over wintering sites which are associated with energy crop production will benefit pollinating species. Conversely the monoculture nature of energy crops is likely to be detrimental to pollinator species as landscape homogenisation is widely accepted to be a driver for the current loss of pollinating species (Martin et al., 2020). Holland et al. (2015) identified ecosystem services such as hazard regulation, disease and pest control, water, and soil quality may benefit from the conversion of arable land to energy crop production, and that the transition of marginal land^[8][9] to bioenergy crops will likely deliver benefits for some ecosystem services while remaining broadly neutral for others. On the other hand, conversion of forest to energy crops will likely have a negative impact due to the increased disturbance associated with the management cycle.

Estimating economic potential

This research looked at perennial energy crops (PECs), SRF, SRC and Miscanthus and included two core economic analyses:

• Farm-scale economic analysis and comparison with typical land-use options:
• A farm scale economic analysis of the net economic benefit for a farmer or land-manager from producing and selling the Miscanthus, SRC and SRF.
• A comparison of this net economic benefit for a farmer or land-manager with typical existing land-uses.
• Assessment of wider economic implications: drawing on geo-spatial data about existing farming and land-use types, the study analysed what the economics implications would be for the wider Scottish economy of a transition to growing more energy crops.

Farm Scale Economic Analysis

Methodology overview

• For the farm-scale economic analysis high, medium and low-cost scenarios were developed for the production costs for: Miscanthus; short rotation coppice: willow; short rotation forestry: conifer; and short rotation forestry: broadleaved. The higher scenario includes high output/high price minus low costs, the medium scenario scenario includes medium output/medium price minus medium costs and the low scenario includes low output/low price minus high costs.
• The following production costs were included; pre-planting/land preparation, planting, post-planting, harvesting and storage and reversion.
• Capital investment costs were not included: where specialist equipment would be needed, which a farmer would not typically have on a farm, such as cutting equipment for SRF, we have assumed services of a specialist contractor would be utilised and this cost has been included within the production costs.
• Estimates of likely income from PEC sales were combined with costs to create a ‘gross margin^[10]’ (income minus costs) for each bioenergy crop. Because the PECs all have a long lifespan, time series charts are used to show the income minus costs over the lifetime of the crop. The results of which can be found in section 5.1.3. Depending on the crop, the yield changes over the lifespan of the rotation, for example due to lower yields in early years after establishment and harvest only occurring in some years. Details on the yields during rotation can be found in Appendix D. For Miscanthus and SRF a low, medium and high price presented, whereas for SRC a single price is used due to limited data. Prices used in the analysis are in Appendix D.
• To compare to the economics of current land use, three farm types were used these were lowland cattle and sheep; mixed farming^[11]; and general cropping – forage. These were selected because they are feasible on the land capability of grades; 4.1, 4.2, 5.1, 5.2, 5.3 and 6.1, – typically suitable for mixed agriculture, improved grassland and high-quality rough grazing, and also the land capability grades assumed suitable for PECs . To calculate the gross margins for the farm types used in the analysis the latest data from the ‘Scottish farm business income: annual estimates 2020-2021’ were used^[12].
• Subsidies are not included in this analysis.
• Total average output in the farm business survey^[13] includes the output categories; total crop output, total livestock output and miscellaneous output. For the ‘general cropping – forage’ category census data is used and output represents the estimated farm-gate worth (£s) of crops and animals without taking account of the costs incurred in production.

A more detailed description the methodology used, assumptions and data sources is included in Appendix E.

Limitations with the methodology

The calculations for the farm types used in the analysis are based on data from the Scotland Farm Business Income Survey, therefore the estimates are based on averages and so any other factors that might influence the costs and output for example climate, soil type will not be accounted for. This is the same for the costs and output estimates for the bioenergy crops. We have not allocated an economic value to any additional benefits a farmer may gain for the other farm enterprises, such as shelter for livestock on adjacent land.

It should also be noted that this study focused on gross margin comparison, which is useful for comparing specific crops and farm enterprises, but has limitations in terms of how well it allows assessment of integration of energy crops into a whole farm business. This will vary farm to farm and would require more in depth ‘whole farm’ economic analysis to be fully understood.

Results of Farm Scale Economic Analysis

Figure 5‑1 shows what land managers could earn on average in a year if costs and yield were spread equally over the lifecycle of the bioenergy crop as well as for farm types (for full details on the method please see Appendix E). There are gross margins for a low, medium and high scenario for each of the bioenergy crops and for the farm types (except for general cropping, forage^[14]). The low, medium and high scenario for lowland cattle and sheep and mixed farming includes the lower (25%), average and upper (25%) of data from the farm business income data respectively, average data from 6 years 2016-17 to 2021-22 uprate to reflect 2023 prices^[15].

Figure 5-1 ‑Yearly average gross margins for each of the PECs over the lifetime of the PEC and for each farm type £/ha (2023 prices)

If costs and income were spread equally over the lifetime of the crop, the medium scenario suggests:

• Miscanthus produces a positive average annual gross margin of £382 per hectare, SRC £87 per hectare and SRF broadleaved £80 per hectare.
• SRF conifer would see a negative gross margin i.e., the production costs outweigh the value of the crop sold. The planting and the ground preparation costs are the main drivers behind this negative gross margin (see Appendix D for more detailed costs).
• Mixed farming and and lowland cattle and sheep farms both show a greater average annual gross margin than all of the PECs examined.
• The average gross margin per year for general cropping, forage is negative at around £990 per hectare, significantly lower than for all of the PECs. Based on these average annual gross margins, growing PECs in lowland cattle and sheep and mixed farming would reduce financial returns in the farm. Whereas, growing PECs in farms in the general cropping forage category could improve their financial returns.

Figure 5‑2, Figure 5-3, Figure 5-4, Figure 5-5 shows the low, medium and high scenario gross margins (output minus variable costs) over time of each of the PECs: Miscanthus, SRC, SRF broadleaved (silver birch) and SRF conifer (Sitka spruce). The higher scenario includes high output/high price minus low costs, the medium scenario includes the medium output/medium price minus medium costs and the lower scenario includes low output/low price minus high costs.

Costs included in the calculations included:

• Site preparation / land preparation (including from different prior land-uses where data is available)
• Establishment / planting
• Crop management costs e.g., during initial growth
• Harvesting
• Reversion (where relevant)

Detailed breakdowns of these costs for the PECs are included in Appendix E.

Figure 5-2 Gross margins for Miscanthus (£/ha) (2023 prices)

• Miscanthus shows an initial negative gross margin in the first two years during the site preparation and plant stages, but then picks up in the following years with harvesting driving the positive gross margins in the following years. The gross margin drops slightly in the year 21 when the costs of reversion take place.

Figure 5-3 Gross margins for short rotation coppice (£/ha) (2023 prices)

• Short rotation coppice shows a negative gross margin for the first 3 years, in part driven by the pre-planting/land preparation costs in years -1 and 0. Gross margin is then positive in the years 3, 6, 9, 12, 15 and 18 reflecting when harvesting takes place.

Figure 5-4 Gross margins for short rotation forestry – Sitka Spruce (£/ha) (2023 prices)

Figure 5-5 Gross margins for short rotation forestry – Silver Birch (£/ha) (2023 prices)

• Short rotation forestry for silver birch and Sitka spruce shows a negative gross margin except for the year 15 when harvesting takes place.

Linking back to Figure 5-1 with the lowland cattle and sheep category on average earning £433 per hectare per year, the mixed farming category £597 per hectare per year and the general forage making a loss of £990 per ha per year the results show;

• Miscanthus, initially has a lower gross margin than all the other farm types, however, after the first few years, land managers would be better off planting Miscanthus.
• SRC, produces a better gross margin than general cropping-forage after the first few years but is outperformed by all other categories when the yield is harvested in years five, eight, 11, 14, 17, 20 and 23.
• SRF, again outperforms general cropping- forage, but has a lower gross margin than the other farm types, except for when harvest takes place in year 18.

Assessment of implications for Scotland’s rural economy

To consider the potential implications of growing more PECs, the results from the farm-scale economic analysis (Section 5.1) were extrapolated across Scottish regions, to consider a transition of approximately 40,000 to 90,000 hectares of suitable land to grow PECs – the area judged to be feasible by 2032 and 2045 respectively (see below for the source of these estimates).

Key findings:

This transition of land in mixed holdings and non-LFA cattle and sheep to PECs would create a shortfall of non-energy crops and and reduced income across the Scottish rural economy due. Because PECs would be more profitable than ‘general cropping: forage’ land-use, there would be an economic gain from transition, but loss of production of animal feed, which may have knock-on implications for livestock production costs (which have not been quantified here).

This research found that, if land to match the level of demand as set out in these scenarios, was utilised for perennial energy crops it would create:

• a gain in gross margin^[16] of around £9.6 million (scenario 1) or a loss of around £9.5 million (scenario 2) per year across the regions.^[17]
• a shortfall in agricultural yields (of farm outputs generated by existing land-use activity, which would not be available when the activity ceased to be replaced with PECs) across the regions between 537,600 tonnes (scenario 1) and 708,200 tonnes (scenario 2).

Our analysis which forms the basis of this assessment is set out below – with details of each scenario (approximately 40,000 and 90,000 hectares).

Limitations:

This assessment does not consider potential loss or additions to the economy due to changes in associated services. Some additional contracting employment for PECs servicing is likely based on the research, but this, and any potential shortfall in other employment from reducing other farm enterprises have not been assessed.

It should also be noted that the findings relate solely to gross margin comparison. Actual farm income – whole farm business income – is very different, comprising multiple farm enterprises (livestock, crops, diversifications) and may be supplemented with off-farm income. For the farm types considered here typical farm income levels are shown in Table 5-1 below (note General Cropping, Forage is not a type assessed in the Scottish Farm Business Income Survey so data is not available). Assessment of implications for PECs on the overall farm costs and income has not been fully assessed here and may reveal additional positive and negative economic implications of PECs.

Table 5-1: Annual Farm Business Income (£) (average of 6 years 2016-17 to 2021-2022)

Method and results

For each of non-LFA cattle & sheep, mixed holdings, general cropping; forage, areas that would be suitable to grow PECs have been identified (see Table 5-1). (See Appendix E for further details on how these areas were selected.) This was done by using the GIS mapping done in previous work for CxC (Martin et al,2020) which identified land suitable for PECs to identify the percentage of land in region which was suitable for PECs. This percentage was then applied to the land area estimated to be in each farm type in the region, to derive the land are potentially suitable for PECs by farm type. There is some overlap between the types of land suitable for each of the three types of PECs so the areas in the table cannot be summed to give a total area.

Table 5-1 Potential land suitable for each bioenergy crop on different farm types (hectares)

A previous CXC study (Meek et al, 2022) indicated that, bearing in mind land suitability, an estimated total of approximately 27,000 ha PECs^[18] could be planted by 2030, 38,000 by 2032 and 90,250 hectares by 2045. Using these estimates and the potential land that can grow bioenergy crops two illustrative scenarios have been created to estimate the potential economic gain/loss of growing bioenergy crops at the Scottish level.

Scenario 1:

From the results presented in section 5.1 it was financially beneficial to grow bioenergy crops on general cropping, forage land. Furthermore, of all the PECs, growing miscanthus was the most financially beneficial. Therefore, the first scenario assumes that two-thirds (66%) of the general cropping, forage land suitable for SRF and for SRC will be converted and 100% for Miscanthus. Only 66% of land for SRF and SRC are assumed to be converted to avoid double counting due to the likelihood that some areas identified are suitable for both PECs and thus appear in both estimates of suitable areas. Although the results in section 5.1 show that growing bioenergy crops on both non-LFA cattle and sheep and mixed holdings would not be financially beneficial, the loss was less on non-LFA cattle and sheep land. Therefore, to get to the 38,000 hectares, it was assumed that 15% of the land suitable for both SRF and SRC in non-LFA cattle and sheep holdings will be converted and 30% for Miscanthus (see Table 5-2). Overall this means that about 20% of total land in Non-LFA Cattle and Sheep^[19] and 1.1% of land in general cropping, forage are converted to PECs.

Table 5-2 Land that is converted for each bioenergy crop for each farm type in scenario 1 (hectares)

Results: scenario 1

Figure 5-6, shows that, for Scenario 1 there would be an economic gain for converting land used for general cropping and forage to PECs. This is because PECs have a positive, albeit small gross margin, compared to the large negative gross margin for general cropping and forage. The total gain in gross margins across the region is around £16.6 million, of which almost half occurs in Grampian.

Figure 5-6 Change in gross margin for converting General Cropping, Forage land to Miscanthus, SRC and SRF (Scenario 1)

Figure 5-7, shows there would be potential economic loss for converting non-LFA cattle and sheep land to Miscanthus, SRC and SRF in table 5-2 (scenario 1) with Grampian showing a loss of a total of about £1.8 million. SRF showed the greatest loss in the majority of the regions, as it has the lowest gross margin of all the PECs but has more land suitable for it. Miscanthus showed the smallest loss across all regions. The total loss in gross margins across regions is just under £7 million. This loss is lower than the gain in gross margin from growing PECs on general cropping and forage farms, suggesting that achieving 38,000 ha of PECs could give a net increase in gross margins across the two farm categories of £9.6 million.

Figure 5-6 Change in gross margin from converting Non-LFA Cattle and Sheep land to Miscanthus, SRC and SRF (Scenario 1)

Figure 5-8 shows the reduction in production (crops, stock-feeding crops and grass from grazing land) that could occur when converting the land shown in Table 5-2 to PECs. From converting land to PECs, there is an estimated yield loss of 537,600 tonnes: 263,000 tonnes for crops replaced by with SRF, 85,300 tonnes for crops replaced by Miscanthus and 189,000 tonnes for crops replaced with SRC.

Figure 5-8 Reduction in production (barley, stock-feeding crops and grass) resulting from converting land to PECs (thousand tonnes) (Scenario 1)

Scenario 2:

For the second scenario to get to around 90,000 hectares of land, it was assumed that more of the suitable general cropping and forage land was converted to SRF and SRC (66%), and more of the non-LFA cattle and sheep land (30% of land suitable for SRF and SRC and 60% of land suitable for Miscanthus). It was assumed that a small percentage of the suitable land on mixed holdings was converted (50% of land suitable for SRF and SRC and 50% of land suitable for Miscanthus). Overall, this means that about 40% of the total land in non-LFA cattle and sheep farms, around 9% of total mixed holdings and 1.3% of total general cropping /forage land are converted to PECs.

Table 5-3 Land that is converted for each bioenergy crop for each farm type in scenario two (hectares) (Scenario 2)

Results: scenario 2

Figure 5-9, show the results of the conversion rates set out in table 5-3 (scenario 2). The only farm type which shows an increase in gross margin for conversion to PECs is general cropping and forage (due to its current large negative gross margin). Conversions on the other farm types (necessary to meet the target planting area of around 90,000 ha) give a loss in gross margins. Overall, the increase in income in general and cropping farms of £18.6 million is not enough to offset losses in the other two farm types, (£13.9 million in non-LFA cattle and sheep farms and £14. 2 million on mixed holdings) meaning there is a net loss in gross margin of £9.5 million.

Figure 5-9 Change in gross margins from converting Non-LFA Cattle and Sheep land to Miscanthus, SRC and SRF (Scenario 2)

Figure 5-10 shows the crop production that could potentially be lost from converting the land shown in table 5-3 (scenario 2) to PECs. This based on loss of stock feeding crops (barley, maize and lupin) and grass silage and hay produced on each farm type. From converting land to PECs, there is estimated yield loss of 708,200 tonnes for replacing with SRF, 248,100 tonnes for replacing with Miscanthus and 523,900 tonnes for replacing with SRC.

Figure 5-10 Reduction in crop production (barley, stock-feeding crops and grass) resulting from converting land to PECs (thousand tonnes) (Scenario 2)

Preferred locations: considerations

Preferred locations for economically viable production of PECs are influenced by multiple factors including proximity to markets (current biomass energy plants and potential future BECCS plants) and local enough access to services and facilities for crop management (e.g. harvesting contractors) to avoid excessive costs. We assessed preferred locations for economically viable energy crops in Scotland considering the locations of end markets in relation to viable growing areas for PECs.^[20]. Insights from our rapid evidence assessment and stakeholder consultation were also considered, for example comments on economically viable transport distance.

Our analysis showed economically viable areas for PEC production bearing in mind future anticipated demand resulting from Scotland’s net zero ambitions, but only SRF could provide quantity needed, due to lack of availability of suitable land for SRC and miscanthus. As SRF is economically uncompetitive against current land-use, this suggests economic viability may be a barrier to PEC production increases even if suitable land within economically viable distance of end markets is available.

Proximity to users of biomass for energy

Biomass energy crops are bulky to transport and so haulage cost from the location where they are grown to where they are used is a factor which determines which growing locations are economically viable – a crop grown too far from its end destination will be prohibitively expensive to transport. It has been difficult to identify a specific economically viable distance in the available research. Stakeholder comments suggest that whilst 100km is a typical maximum distance to haul wood to a sawmill, a significantly lower distance is economic for biomass crops, as their value is lower than wood which will become sawn timber. In our economic analysis transport costs pre-farm gate e.g. for delivery of planting material are included, but haulage of the bioenergy crops to biomass plants has not been included in the costs as this will depend on the distance and whether the price paid to the farmer is at the farm gate or at delivery to the bioenergy plant. For the purposes of the analysis here, we assume a maximum viable distance of 100km, and consider a shorter 50km distance to reflect stakeholder feedback.

Proximity to existing biomass plants:

Biomass plants in Scotland were identified from DESNZ’ Renewable Energy Planning database which lists both existing and planned plants^[21]. Existing sites vary in scale and use – some are generating power for the grid, others are located on industrial sites such as distilleries, sawmills and papermills supplying heat and power for the industry, whilst others are small supplying e.g. a hotel. Eight sites were selected from the list as being most likely to consider using PECs as a fuel (See Appendix J). Plant which are located on sites where there is already a ready supply of fuel (e.g. sawmills, paper and pulp) were excluded as were very small sites and sites which were not yet operational or under construction.

A buffer of 50km and 100km from these biomass plants has been applied in Figure 6-1, to show the potential geographical areas which could supply biomass markets in Scotland.

Figure 6-1: Biomass plant locations

Proximity to future BECCS facilities:

CCC^[22] highlights that Scotland has very good potential for deploying Bioenergy with Carbon Capture and Storage (BECCS) due to its access to a potential CO₂ storage site in the North Sea, along with its ability to produce domestic BECCS feedstocks. A pilot facility, the Acorn Transport and Storage Facility in Aberdeenshire looks set for further investment after the UK government announced in March 2023 that it considers this site to be one of the two best placed to deliver its objective of capturing 20-30 megatonnes of CO₂ across the UK economy by 2030^[23]. The proposed access points to this facility are via a feeder pipeline along Scotland’s east coast which starts at Bathgate and ends at St Fergus, with two injection points at Kirriemuir and Garlogie. Large scale BECCS plants for electricity, biomass gasification for hydrogen, or biofuel production^[24] may be located in proximity to these access points to benefit from easy access to the pipeline. This study assesses how much land suitable for growing bioenergy crops is within 50km and 100km of these access points. This mapping is presented in Figure 6-2.

Kirriemuir

St. Fergus

Garlogie

Bathgate

Figure 6-2 Feeder pipeline locations and nearby land suitable for PECs

Table 6-1 shows the total potential PEC growing areas with these distances.

A previous CXC study (Meek et al, 2022) indicated that, bearing in mind land suitability, an estimated total of approximately 27,000 ha PECs^[25] could be planted by 2030 and 38,000 by 2032; With this area of land, depending on the yields obtained for PECs and the efficiency of the power plant, PECs could provide feedstock for a BECCs power plant producing between 60 and 80 MWe. The data in Table 6-1 suggests that this land is available, within 50km of all proposed access points along the east coast feeder pipeline for SRC and Miscanthus, but this would require a large portion of the suitable land to be used. A larger land area which is suitable for growing SRF is available.

Table 6-1: Total potential PEC growing areas within 50km and 100km of potential BECCS sites, and existing biomass plant locations.

Access to service and facilities for crop management, harvesting and processing.

Access to services and facilities for crop management harvesting and processing, such as local contractors with suitable equipment has been identified in the research and by stakeholders as a factor which would influence the suitability of growing areas for PACs. The evidence review did not provide information on the availability and access to these services in Scotland, or the speed with which services could develop if a growth in production were planned. Easy access should not be assumed, particularly given the shortage of forestry skills in Scotland and constraint on travel distance which influence the economic viability – access issues would need to be addressed before an area could be suitable for economically viable PEC growing.

Other location considerations

As is evident from the REA, biodiversity and other ecosystem services can impacted by PEC cultivation. Choice of crop, cultivation regime and location need to be carefully considered to optimise environmental benefits and avoid negative impacts. The impact is highly situation specific and could not be assessed in detail within scope of this research but should be considered carefully when selecting locations.

SWOT & PESTLE Analysis

This section provides analysis of the strengths and weaknesses of these crops, and the factors supporting or hindering uptake, drawing together the research findings. A PESTLE analysis was also carried to understand the potential enabling and preventative factors which could influence the economic viability of energy crops in Scotland. Further detailed SWOT and PESTLE analyses are available in Appendix I.

SWOT Analysis of energy crop economic potential

Table 7-1 presents SWOT analysis common to PECs assessed in this research. Further discussion of variations between Miscanthus, SRC and SRF is included in Section 9.

Table 7-1: Summary of strengths, weaknesses, opportunities and threats for PEC in Scotland.

PESTLE Analysis

The PESTLE analysis considersthe political, economic, social technical, legal and environmental factors which currently enable or prevent energy crops becoming an economically viable prospect for farmers in Scotland. The summary PESTLE is set out in Table 7-2 below, discussion of the results follows in Section 9.

Table 7.2: Summary of PESTLE analysis for growing PECs in Scotland.

Discussion

The research and analysis show multiple positive and negative features of the PECs. The implications of these for economic viability of PECs in Scotland is discussed here.

Economic potential to farmers and land managers

Economic potential of PECs in Scotland for farmer and land managers

Overall, the economic analysis showed Miscanthus could be most profitable over the life cycle, but though SRC and SRF broadleaves appear to achieve lower profitability, there are larger areas suited to these crops and less uncertainty about their suitability to the Scottish climate.

Achievable biomass yields, which significantly influences economic viability, is still subject to some uncertainty as commercial growing and trials in Scotland are limited, particularly for SRF and Miscanthus. The analysis shows a significant difference between high, medium and low costs and income from the three PECs considered. It could be reasonably assumed that this level of uncertainty may lead to farmers and land-managers having low confidence to plant the crops. Forthcoming results of Scottish research trials and developments may improve confidence, for example Miscanthus varieties more suitable to Scotland’s climate are in development (see Appendix H) which could extend the range or improve yields in Scotland.

Equipment needs, and therefore costs and economic potential, vary for the different PECs:

Miscanthus can be harvested by typical harvesting equipment which an arable or mixed farmer would either own, or have easy access to via local contractors; whereas for SRC and SRF the equipment needs are more specialist, so requires significant investment or access to local contractors, which is currently constrained in Scotland.

The PESTLE analysis shows that, of the factors which are likely to prevent farmers and land-managers from currently viewing PECs as an attractive proposition and hinder the uptake across Scotland. The most important, are:

• the low or negative income from the crops,
• upfront investment requirement, and
• uncertain market for the crops.

Stakeholder feedback suggested some approaches which may addressing these issues:

• Financial support for farmers, land-managers and other necessary parts of the sector including to enable adoption of forthcoming innovations aimed at improving yields and cutting costs, such as new harvesting techniques and mobile machinery for processing materials on farms.
• Fixed price and long-term contracts for future crops, at prices higher than production costs. However, given imported biomass and fossil fuels appear to be available at lower cost it is unlikely that end-users will find it feasible to offer attractively priced contracts.
• Greater clarity over the likely environmental impacts in Scottish context – both local impacts such as on biodiversity and wider impacts for example indirect land-use change from competition for food / animal feed crops – and how to design of PEC planting in Scotland to maximise positive environmental benefits.

Locational and temporal issues

In terms of suitable and preferred locations for energy crop production in Scotland, as described in Section 6, the proximity to biomass markets (such as power plants) is a key determining factor. The research has shown that there are suitable growing regions, primarily for SRC and SRF within 50km to 100km of existing biomass plants, or potential sites for BECCS plants close to the proposed east coast feeder pipeline, which are likely to be the dominant market demand in a future, more mature biomass market aligned to the Scottish Governments climate ambition. There is some uncertainty about the economically viable distance to transport energy crops, with stakeholders suggesting it would be significantly less than the typical 100km for sawmill quality wood. The number of viable production areas with 50km of potential sites is lower, but they are most advantageous due to lower transport costs (and GHG emissions).

The study did not explore in detail the potential for on-farm use of biomass, but stakeholder consultation suggested this may be an economically viable alternative, particularly for farms not located close to a suitable biomass plant, and given the context of high energy costs. On farm use of PECs is not a negative emissions technology, as it is not feasible to apply carbon capture to small scale plants, but it would contribute to decarbonising agriculture if it replaced fossil fuel use for power and heating in farm buildings.

Looking ahead, if demand for biomass grows in Scotand, UK and elsewhere as countries expand BECCS capacity the market prices for PECs may change. Input costs can also vary significantly. It is beyond scope of this research to deliver a full analysis of future scenarios for the market, or local market dynamics related to specific BECCS sites, but it is clear from the range of profitability demonstrated in Section 5.1, that a range of scenarios should be planned for.

Interactions between PECs and adjacent land-use and wider landscapes and ecology was shown to be an important location factor to consider. Impacts could be beneficial, such as shading / shelter for livestock and to reduce wind exposure for adjacent crops, or could be negative depending on local landscape features, for example reduced yields in adjacent crops due to shading. Positive potential biodiversity impacts have been suggested by some stakeholders, such as habitat for birds, mammals and beneficial insects if edges between PEC and other land-use is maximised, but there was also concern about negative consequences of land-use change and monoculture PECs on biodiversity. Water management benefits also vary across the crops, and the lifecycle of the crops. The implication of the research is that the effective integration of PECs into natural landscapes and farming systems in Scotland to deliver maximum additional environmental benefits will require careful design in relation to the specific local environmental context.

A key issue for economic viability of PECs is the distribution of costs and income over time. Poor cashflow for farmers and land-managers is typical for PECs, because initial costs of establishment are not recouped until harvest after several years. The time from establishment to first harvest varies so the time where a farmer/ land-manager would likely experience cash flow challenges would also vary. The shortest time to first harvest was for Miscanthus, at around 2-3 years for full harvest with potentially a small harvest in the first year, SRC is typically 3 years for first harvest, and 6 years to first full harvest, and for SRF there is typically around 15 years till first harvest. Sequential planting can help create a more regular income because a portion of the crop would be ready for harvest each year. For SRC/ SRF this can be feasible if the harvesting equipment is already available on the farm, or the yearly harvest would be enough to warrant a visit from a contractor. For Miscanthus, there is an annual harvest once established so sequential planting of a portion of land intended for Miscanthus each year would allow for some of initial income to be used for subsequent planting reducing the size of initial outlay whilst increasing the area allocated to the crop over time.

Income diversification

Stakeholder comments suggest that the current levels of interest from farmers in diversification, including into crops with lower input costs and stable income, could be a significant enabler to the uptake of PECs. However, the economic analysis suggests that this would only be the case, if the core barriers around profitability, cashflow and financial risk were addressed.

Other factors influencing PEC uptake

The research found that farmer and land manager attitudes, habits, skills and perceptions, as well as those of the wider community are likely to be influential, alongside the economics, in determining the degree to which energy crops are adopted in Scotland. Low appetite for financial risk is a key preventative factor, with most farmers looking to reduce their exposure to risk and so only likely to be interested in energy crops if they are perceived as a low risk strategy in their own right, or a beneficial diversification of income as part of a wider business risk reduction strategy. The research suggests that, without clearer evidence of favourable market, price and productivity the current perception of these crops as relatively risky is unlikely to change. Concerns about competition with other crops, sustainability credentials, and public perception of the ‘morality’ of energy crops is also likely to influence farmers and land-manager attitudes. Alongside these factors, it was highlighted during the research that farmers often have a strong preference for their current farming enterprises and so may be reluctant to adopt new crops even if they appear financially advantageous and that a significantly higher financial return may be needed to persuade a shift to energy crops in these circumstances.

State of the evidence base and identification of any key gaps

The key gaps and debates in the literature were described in Section 4, and limitations in economic analysis in Section 5. The research shows a need for more robust evidence on potential yields, production costs and environmental impacts specifically for Scotland.

Quantification of potential wider farm benefits, such as shelter for livestock, and estimation of economic value of these benefits to farmers was not identified through this research, but could help create a fuller picture of the economic potential of energy crops for Scotland.

We found limited research on the risks for crop failure / poor productivity from pest, diseases, extreme weather which hampers full assessment of the financial risk exposure of farmers and land-managers associated with planting PECs.

This study has not included a detailed comparison of PECs for NETs with annual bioenergy crops and other bioenergy technologies, such as anaerobic digestion or smaller scale use of PECs on farms for direct energy generation. The REA and stakeholder feedback indicated potential for farmers to benefit from energy security and reduce energy costs if they were to utilise energy crops for their own energy generation. This study has not modelled the current economics of investment in relevant plant and ongoing cost: benefit of this scenario. This research would be potentially beneficial to understand how local small-scale use compares to larger scale use in NETs, and therefore fully understand the relative economic potential of PECs in Scotland.

The research found debates and discussions about how land should be used to fulfil societies various material needs (food, fuel, fibre etc.) and provide space for biodiversity and deliver other ecosystem services. To inform this debate various additional factors, beyond the scope of this research are relevant including the relative benefits of using land for PECs vs other types of renewable energy such as wind and solar energy. Stakeholders highlighted that solar, for example compares, well and there is growing interest in agrivoltaics – solar voltaic panels within agricultural land that may still retain some of its agricultural use such as livestock grazing.

Conclusions

Perennial energy crops have the potential to generate income for farmers and land-managers in Scotland.

• However, income is likely to be lower than they could earn from other farm enterprises, such as lowland cattle and sheep and ‘mixed agriculture’, that are typical on the types of land which may be suitable.
• The exception is where PEC profitability is compared to ‘general cropping: forage’ farming type (growing crops for animal consumption, usually on lower quality land) this activity typically makes a significant loss, so PECs compared very favourably in the analysis.
• for PECs to be viewed as an attractive, economically viable option by farmers and land managers there is a need for greater confidence that it will deliver good economic returns. The high upfront establishment costs for perennial energy crops and low revenue potential are both likely to hinder uptake.

Profitability of perennial energy crops based on gross margin calculations

If costs and income were spread equally over the lifetime of the crop and compared, PECs are less profitable than current farming enterprises, except for ‘general cropping: forage’ which is not typically making a profit.

• Of the three crops studied, Miscanthus showed the highest average gross margin at £382 per hectare per year but there are some potentially limiting factors:
  • uncertainty about achievable yields in the Scottish climate and on the grades of land above category 4.1 in the Land Capability for Agriculture in Scotland. If yields were lower, then profit may be lower.
  • Limited theoretical growing area in Scotland – much lower than for SRF or SRC based on analysis of land quality and characteristics and Scotland’s climate.
• SRF and SRC showed lower profitability for farmers: £80 and £87 per hectare per year over their lifetime respectively for SRF: broadleaved and SRC, making them less attractive but there is more suitable land for growing these. SRF conifer would see a negative gross margin i.e., the production costs outweigh the value of the crop sold.

Potential opportunities

• The research also identified some potential positive attributes of PECs which might encourage uptake – PECs could help diversify a business, creating additional income, without adding significant additional labour requirements or ongoing input costs – minimal management time and inputs are required once crops are established.

Potential barriers

• Cash flow could pose a problem – the distribution of costs and income year-on-year for PECs is significantly different to typical farming activities which have an annual profit cycle. PECs need investment in site preparation and planting upfront, but income only arrives after first harvest several years later (2-3 years Miscanthus, 6 for SRC, 15 for SRF) and then only periodically after that.
• Coupled with uncertainty about market demand and achievable crop sale prices, the need for upfront investment to establish PEC production, means farmers and land managers may view them as a risky proposition and be reluctant to grow them.
• We identified other potential barriers to uptake, including farmer and land-manager unfamiliarity with PEC production, low appetite for risk, need for new skills, access to equipment and services, and concerns about community perception of land-use change and impacts on other agricultural production, e.g. available animal feed.

Enhancing economic potential and production of PECs

Potential approaches to improve economic potential in Scotland include:

• financial incentives, such as government specific subsidies under future agricultural support,
• risk reduction strategies such as secure, attractively-priced contracts with end markets, alongside expansion of the market.
• Innovations to allow processing at the farm and to improve transportability of crops could also help to increase the economically viable travel distance.

Implications for wider Scottish economy:

• Previous research suggests 38000 could be feasibly planted by 2032 (scenario one) and 90,000 by 2045 (scenario two).
• We found that, if land to match this level of demand, was utilised for perennial energy crops (using the scenarios as defined in section 5.2), it would create a gain in gross margin of around £9.6 million (scenario 1) or a loss of around £9.5 million (scenario two) across the regions.

Economically viable production locations:

Economically viable production locations for PECs are influenced by multiple factors including proximity to markets (current biomass energy plants and potential future BECCS plants) and local enough access to services and facilities for crop management (e.g. harvesting contractors) to avoid excessive costs.

• We identified suitable growing regions (some SRC/Miscanthus and most for SRF) within an economically viable transport distance to existing biomass plants and potential sites for BECCS near the proposed east coast carbon capture and storage feeder pipeline (assumed 50-100 km).
• As SRF is economically uncompetitive against current land-use, this suggests economic viability may be a barrier to PEC production increases even if suitable land is available.

Potential further steps

Key debates and areas for further research include:

• Considering more in-depth ‘whole farm’ economic analysis.  This study focused on gross margin comparison, which is useful for comparing specific crops and farm enterprises, but has limitations in terms of how well it allows assessment of integration of energy crops into a whole farm business. This will vary farm to farm but could be explored through farm case studies. This could include considering a wider range of costs for farmers and that after initial set up the PECs would require less workload.
• Comparing, the economic and environmental potential of using land for energy crops with utilising the same land for other renewable energy options (for example using the land for solar panels alongside grazing) and
• Potential role for on-farm use of perennial energy crops.
• Considering future biomass markets, including how future Greenhouse Gas Removal (GGR) schemes, global demand and demand from biotechnology sector may impact it.
• Identifying how to make domestic biomass from energy crops a more attractive option than imports and a more profitable use of land, and on what basis this can be justified. For example, taking account of full LCA and rewarding greatest emission saving.
• Considering in more detail the role of PECs in the context of how the agriculture sector is changing and how it may have to change to reduce GHG emissions.
• Considering the value, including the financial value, of other benefits of energy crops, such as flood mitigation or animal shelter, relative to existing or potential alternative land-uses.
• Exploring how PECs support/interact with tier 2 or 3 objectives of the ARP.
• Considering the impact of subsidies.

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Appendix A: Policy Context for Energy Crops in Scotland

Climate Change Policy

The Update to the Climate Change Plan (CCPu)^[27], published by the Scottish Government in December 2020, whilst focused on reducing emissions, identifies the need to also remove carbon dioxide from the atmosphere to compensate for residual emissions. It foresees a role for technologies to achieve a net reduction in emissions – often referred to as Negative Emissions technologies (NETs). It identifies several NETs pathways with potential in Scotland, including bioenergy with carbon capture and storage (BECCS). Climate Committee’s (CCC) 6^th Carbon Budget sets out that achieving the required scale of BECCS will necessitate a significant increase in the domestic production of biomass feedstocks^[28].

The CCC’s 2022 review of Scotland’s progress^[29] highlighted that Scotland’s planned deployment of NETs was ambitious, comprising two thirds of UK government overall ambition for 2030, but also notes the advantage of Scotland’s large land area and potential to draw on substantial biomass stocks. It recommends consideration of the impacts and interactions that increased domestic biomass production could have on land use and agriculture. The Scottish Government has acknowledged that these targets can’t be met – the NETs feasibility study gives more realistic targets^[30]. Failure to meet NETs targets for Scotland implies deeper emissions reductions in harder-to-decarbonise sectors, such as aviation and agriculture, and so it is critical to consider how farmers and land-managers can deliver the necessary biomass feedstocks. The CCPu includes a proposal to develop rural support policy to enable, encourage planting of biomass crops within broader measures on sustainable, low carbon farming^[31]. The CCC recommends maintenance and enhancement of support for agroforestry^[32], and a target of 5% trees on farmland by 2035.

Agricultural policy

Scottish Government’s Vision for Agriculture recognises the essential role agriculture has in delivering sustainable food production, climate adaptation and mitigation, biodiversity recovery and nature restoration and proposes that future subsidy support for agriculture will be split across unconditional support and support targeted to environmental outcomes, including low carbon farming and biodiversity The new Scottish Agriculture Bill as introduced to parliament on 28th September 2023 provides a replacement for the Common Agricultural Policy (CAP) and has been drafted to provide the required powers and framework to deliver the Vision for Agriculture. The bill would require Scottish Ministers to prepare a five-year Rural Support Plan for farming, forestry, and rural development. The Agricultural Reform Route Map (ruralpayments.org) sets out the milestones and timescales for change. The Agriculture Bill and Rural Support Plan will have implications for how economically viable it may be in future for farmers and land-managers to grow energy crops. Whilst the details are yet to be confirmed, it is clear that any expansion of perennial energy crops will need to take these policy developments into account.

Other key policies:

Principles of ‘just transition’ are defined in legislation^[33] and Scotland’s draft ‘Energy Strategy and Just Transition Plan’^[34] was published in January 2023. It describes Scotland’s aim to use bioenergy where it can best support Scotland’s Net Zero Journey, and aligns with and supports Scotland’s goals for protecting and restoring nature. It contains a commitment to review the potential to scale up domestic biomass supply chains. Bioenergy crops, if economically viable, could offer the agricultural sector a new income stream and support the rural economy, which would be consistent with the draft plan. The draft plan also includes a proposal to develop a strategic framework for the most appropriate use of finite bio-resources (published in a Bioenergy Action Plan), acknowledging the potential for competing demands on land and natural resources. CCPu also acknowledges the need for open a discussion on optimum land uses beyond just farming and food production to multi-faceted land use including forestry, peatland restoration and management and biomass production.

UK biomass policy context

The UK Government’s Department for Energy Security and Net Zero (DESNZ) published a Biomass Strategy in August 2023 which set out the Government’s view that well-regulated BECCS can deliver negative emissions and ensure positive outcomes for people, the environment, and the climate. It commits the UK Government to strengthen sustainability criteria and verification processes for biomass, acknowledging challenges with international supply chains, and creating a cross-sector sustainability framework for biomass (subject to consultation). The focus will be on addressing greenhouse gas emissions, indirect land-use change, and potentially soil carbon changes. The strategy anticipates a key role for both domestic and imported biomass use across the economy, on a limited timescale. It also sets out how the government is actively developing demand side policies to support emerging technologies such as BECCS and Greenhouse Gas Reduction (GGR) business models, for example the potential for a ‘Contracts for Difference’ (CfD)^[35] approach. The strategy acknowledges that bioenergy policy involves a mix of reserved and non-reserved powers, and so as the Scottish Government develops its draft Bioenergy Policy Statement, Scotland has an opportunity to build on UK policies and develop policies appropriate for Scotland.

Appendix B: Introduction to Perennial Energy Crops

Introduction to Miscanthus

Miscanthus is a tall perennial grass with woody canes like bamboo, of East Asian Origin. The most common variety of Miscanthus grown is the sterile hybrid Miscanthus x giganteus (M. giganteus). Miscanthus is a renewable source of fibre which has a wide potential range of uses as biomass or fibre. Whilst Miscanthus can be grown in parts of Scotland, it is not currently grown at commercial scale and further trials are required to verify its potential future contribution (Meek et al., 2022). Nonetheless, Martin, et al 2020 found 51,800ha of land is theoretically suitable in Scotland to grow Miscanthus which could produce 2.59TWh/yr and 0.52Modt/yr.

To grow, the crop must be established by planting pieces of rhizome (underground plant stem capable of producing the shoot and root systems) which have been collected from fields where Miscanthus is already established^[36]. Prior to planting, site preparation may typically involve breaking up compacted soil, removing weeds (using herbicides), ploughing to 30cm depth, then further levelling and soil cultivation to create a fine level soil to around 15cm^[37]. Equipment which is typically available on an arable farm can be used for this site preparation and planting. Planting using specialist equipment achieves best results, but a potato planter could alternatively be used^[38]. Biodegradable plastic film to prevent frost damage and retain moisture and fencing to prevent rabbits damage can improve success of crop establishment. Once planted, some gap filling might be needed (done manually) and chemical weed control in the first year or so. Fertilisers are not usually needed. After the first year the material is cut back and left in the field. In year 2, depending on the growth rate, there will be a small harvest, or another cut back. Once established a Miscanthus crop is harvested annually, usually in early spring when moisture content is lower, and can be productive for around 15 years. The material is baled, or sometime chipped, to enable easier transport and storage. Sometimes drying is required in storage (natural or mechanical ventilation). At the end of the crop lifetime, to revert the land to other uses, a herbicide is often used to kill Miscanthus shoots and rhizome, followed by ploughing.

Introduction to short rotation coppice^[39]

Short Rotation Coppice (SRC) commonly consists of high-yielding varieties of either poplar or willow, densely planted on a piece of land. The solid, woody biomass provides a source of biofuel that is either used alone or combined with other fuels to power district heating systems and electric power generation stations^[40],^[41]. It was noted previously by Martin et al. (2020), that the production of energy crops in Scotland has in the past been limited, with only SRC currently grown at small commercial scale (250ha). There is greater potential for further SRC cultivation in Scotland provided that suitable land area is available.

Most types of land, except for heavy clay soils and water-logged land, are suitable for SRC. The initial steps to establishment include removing weeds using herbicide, ploughing to 30cm and further cultivation to 15cm. Rods or cuttings are planted with a specialist planter. Gap filling and protection using rabbit or deer fencing may also be needed. During the first year weed control using herbicides and control of plant diseases using pesticides may be needed. Once established, SRC plantations are typically harvested at 3-year intervals using a forage harvester with a specific cutting system, then chipped and stored outside on a concrete base or in the field. Plantations typically remain productive for 15-25 years^[42]. After this, a new planting can be established, or the field reverted through a process that involves stump grinding and the application of herbicides to prevent regrowth.

Introduction to short rotation forestry

Short rotation forestry (SRF) involves planting relatively fast-growing tree species and harvesting them for biomass after around 15-20 years, which is much quicker than conventional forestry. Species can be coniferous (e.g., Sitka spruce, Douglas fir) or broadleaved (e.g., aspen, poplar, silver birch, downy birch, sycamore). SRF is not currently operated commercially in Scotland although there are some trial plots. Nonetheless 912,600 ha of suitable land is theoretically currently suitable for planting of SRF in Scotland (Martin et al., 2020). Limited, recent literature material and evidence was found in the REA relating to the economic potential of SRF in and around the UK.

Process steps are like conventional forestry: the plantation is grown from seedlings or cuttings, or sometimes direct seeding, into land prepared through steps such as drainage, ploughing, and fencing. Some weed control or replacement planting may be needed initially, but after this limited maintenance is required. All the trees in a growing area are harvested at the same time using specialist cutting equipment, then either cut into lengths and stacked to air dry ready for collection or chipped on site. With SRC the shorter rotation, and the higher planting density, reduces the potential for co-production of logs for sawmill timber^[43]. After harvest the site can be cleared, using machinery and herbicides as per SRC and then replanted or reverted to other land-use. Alternatively new stems can be allowed to regrow for coppicing, or a single good stem selected to continue growing for harvest after 15-20 years. Broadleaved varieties tend to produce higher wood density which is advantageous for use as bioenergy.

Appendix C: Methodology to Rapid Evidence Review

• The Rapid Evidence Assessment (REA) methodology used for this project aligns with NERC methodology^[44] and comprised of the following steps.
• Define the search strategy protocol, identify key search words or terms, define inclusion/exclusion criteria. A list of key words, terms and search strings was created and reviewed by Ricardo’s bioenergy and agriculture technical experts and the project steering group to direct the REA review to the most relevant sources. This list was and divided into six relevant categories ‘Energy Crops’; ‘Economic potential’; ‘Farm business and agronomic considerations’; ‘Preferred/feasible locations’; ‘Agricultural & land-use options’; ‘Other considerations e.g., just transition, decarbonisation’ to ensure that all appropriate aspects of the economic potential of energy crops were identified which supported the focus the review. Any literature that is considered out of scope based on our list of assumptions was excluded from the search. We also excluded literature that is older than 10 years, unless it was from a credible source and was the only piece of evidence available (particularly for data).
• Searching for evidence and recording findings. Literature was searched using Google Scholar and Science Direct, utilising our accounts with Science Direct and Research Gate to access restricted pdfs where required. Grey literature, such as farming press and industry reports were used to provide examples and case studies of the economic potential of energy crops. In addition to the search engines, two existing evidence reviews, prepared by Ricardo were used to sources relevant literature: ‘Evidence review: Perennial energy crops and their potential in Scotland’ and ‘Evidence review: Increasing Sustainable Bioenergy Feedstocks Feasibility Study’. Academic paper ‘Greenhouse Gas Removal Technologies –approaches and implementation pathways in Scotland’ (Haszeldine et al, 2019) was also provided to us to supplement our evidence base. For each individual search a unique search reference was assigned, the date, search string used, total number of results found, and the total number of relevant papers found were recorded. Our search strings can be found in the table below.

TableA‑2: Search strings used for REA

All results were recorded in an excel spreadsheet with information extracted on the following:

• Country
• Type of energy crop (SRC, SFC or Miscanthus)
• Additional information on crop type
• Scale of deployment
• Positive economic potential
• Negative economic potential
• Issues/barriers of deployment (non-economic uptake considerations)
• Temporal considerations (e.g., agronomic/climatic conditions)
• Further economic potential (e.g., decarbonisation of agricultural practices and creation of new jobs)

A RAG (red, amber, green) rating was assigned to each source, based on the g criteria:

• Screening. Sources of evidence was then screened initially by title and then accepted papers were then screened again using the summary or abstract. Literature was screened for information on the following inclusion criteria:
• SRC, SRF, Miscanthus (and hemp / alternatives if strong evidence to show economic viability)
• Economic potential (positive and negative) of energy crops – qualitative and quantitative information
• How farmers / land-managers are making decisions about which enterprises and land-uses to adopt and research which provides evidence of likely preferences and decision-making influences.
• Agronomic or other considerations which would influence viability / adoption by farmers / land-managers.
• Extract and appraise the evidence. The screening provided an organised list of papers which enabled evidence to be extracted directly from the literature into the report. Literature extracted also guided the internal workshop and supported information included in the SWOT and PESTLE tables.