Academic Advisory Panel – monitoring and evaluation of the agricultural policy outcomes: advisory note

Items and actions

Introduction

The monitoring and evaluation (M&E) framework for the Agricultural Reform Programme, set out in the rural support plan, is guided by legal requirements under the Agricultural and Rural Communities (Scotland) Act. Monitoring covers two main areas:

• delivery - what support is provided and to whom (e.g., payments, scheme participation, land types supported)
• impact - the outcomes achieved

M&E will assess whether schemes reach the right people effectively and track progress towards key goals such as high-quality food production, resilient farm businesses, tackling climate change, restoring nature, and ensuring a just transition. Indicators will be developed at three levels: programme-wide, tier-specific, and scheme-specific. Work is also underway to account for external factors influencing outcomes, ensuring accurate assessment of impact.

The academic advisory panel (AAP) was invited to review the proposed indicators for sub-outcomes, assessing their balance, identifying gaps, and advising on relevant data sources. The Panel was also asked to suggest additional opportunities, which could strengthen the outcomes framework and improve support for farmers and crofters. This note summarises the discussion held during the AAP meeting on 1 September 2025.

Key Summary:

Effective M&E are vital as the agricultural support budget is no longer ring-fenced nor fixed. Current M&E approaches are under-resourced, rely on broad regional land categories, and miss key insights on land use or land capability. Strengthening M&E requires balancing rigour with practicality, combining outcome-based evaluation, more accurate land-use data, and indicators reflecting land managers’ decision making. Aligning Scotland’s approach with UK, EU, and international standards can improve transparency, comparability, and the integration of innovative tools such as LiDAR. The Whole Farm Plan (WFP) framework provides a strong foundation, but data must be systematically collected, standardised, and linked to existing and enhanced datasets on soils and habitats to deliver an evidence-based view of farm performance and sustainability progress.

Monitoring should focus on meaningful, outcome-driven indicators across economic, environmental, and social measures using sector-specific data. Key outcomes should be monitored using straightforward indicators and practical metrics. Broader food system indicators should link productivity to ‘One Health’ outcomes, integrating agricultural production with environmental and public health impacts. Meaningful indicators of animal health and welfare include disease surveillance, notifiable disease records, abattoir data, and veterinary medicine usage. Climate change mitigation and adaptation demands practical metrics for soil structure, erosion, soil greenhouse gas (GHG) emissions, soil loss (including change in soil organic matter content), runoff risk, riparian tree planting, land cover changes, livestock emissions, and fertiliser use. Biodiversity data should be collected alongside soil metrics in a national sampling approach to support the Scottish Biodiversity Strategy. Tracking land managers’ attitudes towards technology adoption, and awareness of climate risks can help assess readiness for adaptation to agricultural practice required to delivered improvement as measured by other indicators. Key indicators to assess economic performance should include total income from farming, agricultural labour, and regional economic impacts rather than headline productivity or subsidy levels. Integrating biodiversity, soil, carbon, land ownership, and cadastral data within a transparent national framework will enable a fair and evidence-based transition toward climate-smart, nature-positive, resilient, and high-quality food production in Scotland.

AAP recommends to:

• increase investment in monitoring and evaluation and adopt best-practice guidance from UK, EU CAP, and international networks. Ensure assessments are robust, transparent, outcome-focused, and informed by consistent methodologies across programmes
• develop a coordinated soil, land-use, biodiversity, and carbon monitoring programme using representative sites and simple, high-impact indicators (matching other UK countries). This approach will improve integration and consistency across existing datasets, and hence potential for better advice and policy
• enhance the detail of data collection. Replace broad regional categories with more detailed land-use and capability measures. Expand the use of innovative monitoring tools, such as remote sensing and eDNA to achieve efficiencies. Incorporate social and behavioural indicators to better understand land managers’ decision-making
• align with Climate Change Plan and Scottish Biodiversity Strategy, through a focus on indicators reflecting sustainable outcomes such as soil health, biodiversity, water quality, and greenhouse gas emissions
• align with ‘One Health’ principles, through use of evidence-based metrics such as disease surveillance, abattoir data, and veterinary medicine records to monitor animal health, welfare, and food quality
• develop an integrated socio-economic monitoring framework linking real price data, cost structures, and market dynamics. Track farm profitability, income distribution, labour engagement, and wider economic impacts through agriculture-specific data and enhanced surveys. Include indicators for self-sufficiency, trade, and food quality (combining calories, nutrient density, and sustainability)
• improve land data integration (e.g., cadastral and LPIS) and ensure environmental and socio-economic M&E can be jointly analysed at appropriate scales
• provide tailored support, including retraining and simplified reporting, to reduce data burdens on smallholders. Ensure monitoring frameworks capture both environmental progress and social fairness in Scotland’s agricultural transition

Key discussion points:

• monitoring and evaluation – a key priority for Scottish agricultural policy. Monitoring and evaluation are increasingly critical as the agricultural budget is no longer ring-fenced. Past evaluations have been under-resourced and inconsistent. Effective M&E should capture both outcomes and overall value with transparency and clarity for all audiences. Drawing on guidance from UK and EU CAP networks can make monitoring more robust and well-informed. Effective M&E must balance technical and statistical rigour, available resource and data, and stakeholder acceptance, and should take advantage of technological innovations
• land Monitoring: The current land monitoring relies on overly broad regional categories (e.g., region 1, region 2) rather than actual land use or capability. A more granular dataset on land use and capability would facilitate the ability to track funding and outcomes more accurately

Monitoring should include finer land cover categorisation (e.g. grassland with or without legumes) and social indicators capturing land manager’s awareness and decision-making which strongly affects sustainability. Aligning with international standards (e.g. ISO/TC347 work) could improve precision and comparability.

• value of peer-learning: Scottish Government should engage more actively with UK and EU networks to share lessons and adopt innovations especially in areas where Scotland currently lags behind
• whole Farm Plan (WFP) Data. Scotland’s Whole Farm Plan includes soil analysis, biodiversity audits, integrated pest management plan, animal health and welfare plan, and carbon audit, offers a solid base for sustainable farming. However, outputs are not systematically collected. Collecting and analysing WFP data, even through sub-sampling, could create a consistent, evidence-based picture of progress and good practice
• use and Enhancement of Existing Datasets. Existing datasets on soils, habitats, and carbon should be better integrated and linked with advisory services. Enhancement of monitoring will also be required to deliver necessary statistical quality and resolution, e.g. for environmental and biodiversity analysis linked to particular land uses. Ensuring accurate, consistent input data will support a more holistic and reliable approach to monitoring just transition, biodiversity and both environmental and economic sustainability

Strategic Outcomes

1. High Quality Food Production

• current discussions on high-quality food production often overlook factors such as pesticide use, veterinary medicine use, pest, or drought resistant crop varieties, and broader ‘One Health’ links between production, environmental and public health outcomes. These aspects could serve as valuable indicators of change, especially as the number of approved pesticide active ingredients decline
• defining “high quality” in livestock is complex and market dependent. Quality varies across the carcase, for example, pig trotters and ears may have limited valued domestically but are prized abroad, illustrating the role of trade and comparative advantage in maximising overall product value

Value produced - maintain the aggregate value of output produced.

• maintaining value assumes current value is appropriate, but assessing the value of domestic produce, requires using real, inflation adjusted figures and accounting for retail-farm dynamics. Aggregate values should specify whether they represent annual figures or rolling averages, as production fluctuates year to year. While increasing domestic fruit and vegetable production is desirable, economic realities and supermarket buying power make this challenging, highlighting the need to consider the relationship between retail and farming
• production values alone are insufficient; assessments must also account for cost, subsidies and economic drivers that determine true viability and sustainability of farming

Total calories produced from agricultural land

• using calories as a metric of food quality is misleading because it captures only the energy content of food, not nutritional value, diversity, or health impact. A more meaningful measure would combine calories with nutrient density, dietary diversity, and sustainability to provide a fuller picture of food quality

Nature intensity

• high nature value and “nature intensity” are useful concepts but remain poorly defined and difficult to measure. Indicators should directly reflect ecological outcomes rather than relying on proxies. Existing indicators, such as water quality, nutrient balance, and greenhouse gas emissions, are easier to monitor, but biodiversity is more complex
• effective monitoring of farmland bird populations requires considering factors beyond agricultural practices, including predation, and surrounding habitats. Both ground-nesting and other farmland-feeding bird species can offer insights into farm conditions, but population data must be interpreted in context, not attributed solely to management practices. eDNA can help reveal predation and other ecological processes and should be incorporated into data collection
• monitoring nature intensity should include Ecological Focus Areas (EFAs), considering their location, extent, and management, as these can have long-term impacts. Habitats such as permanent grasslands and their ecological value depends heavily on active management, as unmanaged areas can quickly lose their biodiversity and functional qualities

Mean food self-sufficiency

• monitoring of food self-sufficiency requires clarity on scale, e.g. whether Scotland, UK, or EU, or globally, and recognition of trade patterns. Scotland is a net exporter of some products, particularly livestock from poorer-quality land, but relies heavily on imports for other foods. Any assessment must consider these trade-offs within the framework of comparative advantage

Animal Health and Welfare

• evaluations of animal health and welfare should focus on improvement, not just maintenance. Currently, there is a discrepancy between the strategic outcome framework (which aims to improve standards) and the sub-outcome wording (which only focuses on maintaining them).
• farm assurance membership is an unreliable indicator of high quality food production, as it does not directly reflect health and welfare outcomes. More meaningful indicators include:

• disease surveillance data from SRUC, which provides detailed insights into endemic diseases that directly affect food quality and animal wellbeing
• notifiable disease records, freely available from the Scottish Government, offering a straightforward proxy for livestock health status
• abattoir data, carcass rejection rates downgrading, and causes linked to poor health or welfare, link animal condition to food quality
• veterinary medicines usage data, and antimicrobial resistance (AMR) trends, support a ‘One Health’ approach by recognising the interconnectedness of animal, human, and environmental health

Veterinary records and medicine use data extracted from animal health plans, combined with stocking rates could also provide valuable indicators for environmental outcomes, such as water quality. Using these data together can enable a more accurate, evidence-based framework for monitoring animal health, food quality, and a healthy environment.

2. Thriving Agricultural Business

• monitoring agricultural performance requires sector-specific data, not broad economic datasets that mix agriculture with forestry or fisheries. Datasets such as the Gross Value Added (GVA) figures, Annual Business Survey (ABS), and UK input-output tables are compiled using different survey methods and are unsuitable for direct comparison with agriculture surveys such as the June Agricultural Census, Farm Business Survey, or Farm Practice Survey
• caution is required when relying on Office for National Statistics (ONS) data and input-output tables, as the treatment of self-employment is unclear, making GVA estimates at the farm level unreliable. These figures are indicative at best and may not reflect structural changes

This is especially true when analysing small geographies such as Shetland or Orkney, where a single surveyed business may disproportionately represent an entire sector in ONS data.

• to improve monitoring, better collection and dissemination of key indicators, such as Total Income from Farming (TIFF) is needed. Discontinuation of the Economic Report for Scottish Agriculture (ERSA) limits ongoing analysis. While resource constraints are acknowledged, prioritising accurate, locally relevant data is essential given the significant role of farming in the economy. Inaccurate data misrepresents on-farm figures and distorts estimates of upstream inputs, downstream outputs, and supply-chain jobs
• understanding agricultural labour in Scotland, requires enhanced survey methods to capture data more reliably, as current sources such as 2016 EU Farm Structure Survey and the June Agricultural Census show discrepancies. Adjusting questions in modular surveys or incorporating softer data sources could clarify labour engagement and its connection to farm operations and inform more effective labour and productivity policies
• to understand the impact of farming on the wider economy requires tracking of farm spending on equipment, services, or local businesses. Analysis at regional level provide a clearer picture of the full economic impact of farming

Support Payments – maintain reformed direct payments and ensure timely delivery of agricultural support to businesses.

• indicators  should go beyond timely delivery of support payments. Assessing payments distribution would address criticisms that support favours large landowners and could incorporate redistributive or small-recipient schemes
• focus should be on increasing farmers’ underlying income rather than support payments alone, prioritising genuine improvements in farm profitability and financial stability
• rural income, while challenging to measure, provides a more meaningful picture of the economic resilience of rural communities than payment levels alone

Profitability – supporting agricultural business profitability through productivity gains

• high farm productivity does not always equate to profitability; for example, some highly productive dairy farms can still incur significant losses. Financial efficiency gains should be emphasised over productivity, as high outputs do not always translate into profit

Minimum Agricultural Wage – ensure that all working in the agricultural sector are receiving an agricultural minimum wage.

• clarification is needed on whether the aim is related only to employees or also to farm occupiers

3. Climate Change Mitigation and Adaptation

Adaptation: soil structure

• to better support climate change adaptation and mitigation in agriculture, soil indicators should be collected, including physical, chemical, and biological soil properties, as well as soil erosion, runoff risk, and riparian tree planting. Scotland can build on research using LiDAR data to monitor riparian vegetation and runoff risks. However, a direct sampling scheme is required for more complete soil monitoring. Scotland currently lacks a centralised and longitudinal soil dataset to evaluate change. Scotland has an opportunity to learn from other administrations (e.g. Welsh Government ERAMMP scheme) to develop a coordinated standardised soil monitoring approach
• technologies such as eDNA and LiDAR should be integrated into the next Environment, Natural Resources and Agriculture (ENRA) strategic programme and validated across Scotland’s soil types. Measurements made using these technologies must be checked on the ground using direct soil physical, biological, and chemical data, focusing on key attributes such as how stable the soil is (aggregate stability), worm diversity, and organic matter content. Existing soil datasets from SRUC and the James Hutton Institute (JHI), should be better utilised, even if incomplete
• strengthening soil health and reducing erosion requires better use of existing land cover and cropping data alongside farmer-led soil assessments. Tools like the Agriculture and Horticulture Development Board (AHDB) soil health scorecard are widely used, but the data are not systematically recorded. Establishing a process to capture these assessments could provide a valuable national dataset on soil condition
• cropping plans should be surveyed and used to identify high-risk periods and areas, such as carrot and potato land on the Moray coast, which is vulnerable to wind erosion when bare in spring and autumn. Incorporating short-term grassland into arable rotations and forage legumes into grassland can improve soil structure, increase organic matter, and reduce nitrogen use. Current statistics should be updated to capture these practices
• soil resilience depends on management practices, such as stocking rates on permanent grassland, which affect compaction and erosion. Including data on such measures in monitoring frameworks would provide a more rounded and practical picture of pressures and opportunities to improve soil sustainability, especially if linked to enhanced data on soil structure
• for climate change mitigation in agriculture, key indicators should focus on land cover changes (e.g. conversion between grassland, arable land, and woodland) as these drive major carbon storage changes. Livestock emissions can be tracked through livestock numbers, density, and slurry management, while fertiliser use should be monitored via imports, application rates, and nitrogen inputs. Metrics like nitrogen use efficiency are misleading on their own and should not be used as primary indicators
• for adaptation, straightforward and practical indicators are most effective, particularly on economics and management approaches. Farm profitability indicates resilience and capacity to invest in adaptation. Crop diversity reflects flexibility, showing farm’s ability to adjust production in response to changing conditions

Carbon Stores and Emissions

• scotland can generate farm-level carbon stock data for hedgerows, trees, and woodlands using LiDAR, providing valuable insights for climate mitigation. However, soil organic carbon data from whole farm plans is less reliable, as it comes from multiple providers with inconsistent sampling methods. Rather than investing in fragmented datasets, it is better that a standardised monitoring approach, similar to the UKCEH Countryside Survey or Wales’ ERAMMP scheme, should be adopted to ensure accuracy and comparability
• to improve soil data quality, focus on a number of representative sites, sampled systematically. This would create robust baselines across different land uses and support reliable monitoring and comparison
• for monitoring carbon storage and soil health, it is best to begin with simple, high-impact indicators, such as land cover (grass, arable, woodland, peatland), and soil erosion risk and above-ground carbon in trees. At the same time, a uniform soil monitoring system across Scotland (see above) should be developed for data that cannot be surveyed remotely. Even if implemented at a restricted level of detail initially, there is value in targeting key soil types using a consistent, standardised methodology before expanding to more complex measurements, in line with international best practice
• collecting data on technological or genetic advances for livestock greenhouse gas emissions is vital. Adoption of feed additives that reduce methane is currently limited, but monitoring any changes in uptake, and particularly outcomes, will be challenging. Genetic improvements in livestock aim to increase efficiency, which can indirectly reduce emissions. Adoption can be monitored by tracking participation in livestock genotyping programmes, but outcomes may be difficult to determine
• to improve monitoring of agricultural greenhouse gas emissions, several measures are recommended:
• national GHG emissions: Strengthened links between SRUC and national inventory managers can further enhance data for reporting
• machinery emissions: Track data on the age, type, and usage of farm machinery by reinstating census questions on tractors and equipment
• technological and genetic uptake: Collect data through ScotEID or SAOS, potentially using a data co-op model to gather and hold routine information from land managers
• soil emissions data : Soils can act as both a source of emissions and as a sink by storing carbon. Monitor soil carbon stocks, erosion, and emissions across locations and over time to capture impact of farming practices. This recommendation links to Adaptation: soil structure monitoring recommendations in the previous sub-section

4. Nature Restoration

• farmland biodiversity arises in two main ways: through actively managed habitats, where practices such as maintaining open areas or low intensity grazing support diverse plants, insects, and birds; and through remnant or uncultivated habitats, such as field corners, ditch banks, or other marginal areas, which naturally retain high biodiversity. Effective monitoring should capture both, yet many existing schemes focus mainly on managed areas and overlook the value of remnant habitats
• Sscotland’s Nature 30 programme (formerly Other Effective Area-Based Conservation Measures - OECM) aims to increase land beneficial for biodiversity from 18% to 30% by 2030, much of which will be on farmland habitats. This voluntary initiative includes checks on actual biodiversity value. Nature30 nomination data from NatureScot should be included in M&E as offering a practical way to track outputs for nature
• tools such as LiDAR and other remote sensing methods can assess some habitats by measuring landscape variability, identifying less intensive farming areas, and tracking land cover. The capacity for remote sensing to providing national data for monitoring nature-rich habitats and soil conservation across upland and lowland farmland should be developed, for more effective M&E

• for more complete monitoring of nature status and restoration, a coordinated national sampling approach for biodiversity (again, similar to Wales’ ERAMMP scheme), should be adopted to ensure accuracy and comparability. Biodiversity data (species, habitat condition) obtained using a national sampling approach should be collected alongside local land use and soils data (see Section 3 above). Together these data generate robust, systems level understanding of environment, nature, and land-use to underpin better evaluation of monitoring and more coordinated policy making

5. Support for a Just Transition

• a just transition means enabling people to make informed decisions about the future of land. Key metrics include transparency of land ownership, public access to land parcel information, and availability of government data on land values. The cadastral map already provides publicly accessible records of land transactions. However, this data lack alignment with the Land Parcel Identification System (LPIS), limiting its integration for wider planning and analysis. Improving access and dataset integration would support fairer and better informed land management decisions
• monitoring should also cover both those who remain in farming and those leaving agriculture or land management, ensuring that transitions are made with dignity and informed choice. Past departures often occurred without retraining or guidance, often moving into unrelated jobs without support. Current challenges, including complex farm plans, administrative burdens, and new CPD (Continuing Professional Development) requirements, risk driving further departures, particularly among smallholders

To make the transition fair and effective, government data collection and its delivery should focus on:

• reporting targeted retraining and reskilling, to track the provision of viable options within or beyond agriculture
• supporting small-scale producers, through thresholds and derogations to reduce administrative and operational burdens
• allowing time for adaptation, recognising long production cycles and ecological goals
• maintaining government leverage, so that departing or transitioning farmers continue contributing positively to land management and sustainability outcomes

Without such measures, Scotland risks losing valuable knowledge, undermining both nature and production outcomes, and creating workforce gaps. Indicators such as attitudes, awareness, and access to support could help monitor and guide these transitions more effectively.