What works best where? Balancing multiple environmental and socio-economic demands for integrating trees into agricultural settings

Agroforestry (integrating trees with crops or livestock) is widely considered as a ‘climate smart’ or ‘nature-based’ regenerative farming solution with multiple benefits. These include improvements to biodiversity, flood and drought mitigation, carbon storage, farm productivity, and resilience to climate change. However, whether and how these benefits are achieved and who benefits from them depends on a wide range of environmental, landscape and socio-economic factors. Scotland has significant potential for tree planting in rural environments, but this is relatively unexplored. Government aims to substantially increase agroforestry, but such expansion must be carefully planned to enhance ecosystem services, while avoiding unintended impacts. This complex task demands a multidisciplinary approach and tools to evaluate various factors and their interplay within the landscape, aiding decision-makers in exploring different options.

Here, we aimed to investigate the environmental and socio-economic potential and barriers for different types of agroforestry across diverse landscapes in Scotland. To help decision making and lower barriers for tree expansion on farmland with environmental benefits, we explored optimal planting scenarios in different settings. We conducted > 30 farmer interviews to evaluate the factors relating to adoption of agroforestry practices. We also developed a novel coupled carbon and hydrological model to assess the environmental effects of various agroforestry scenarios across Scotland. For riparian planting as a specific type of agroforestry, we then collaborated with > 100 stakeholders to explore the complexity of prioritising additional research needs and addressing national-level barriers to implementation.

While there is significant interest among farmers to integrate trees on their land, barriers such as insufficient knowledge on planting strategies, limited awareness of grant schemes, and inflexible policies persist. Overall, our results revealed that depending on motivation, socio-economic factors and business models, optimal planting scenarios can be vastly different. This is also constrained by site specificity, where additional evidence is needed by stakeholders to determine optimal tree placement and density to maximise multiple benefits. Modelling results aligned with the importance of selecting tree species and spatial planting designs based on site specific conditions. However, generally, for a finite number of trees, distributing broadleaved species over larger areas yields greater carbon storage and hydrological benefits per tree compared to planting them in dense clusters.

Finally, results were incorporated into the development of an interactive spatial multi-criteria mapping tool aiming to identify suitable and best locations for agroforestry in the landscape. The outcomes of this work support decision makers to deliver multiple objectives and improve accessibility and implementation of agroforestry as a nature-based agricultural solution with relevance to other parts of the UK and Europe.