Abstract

ContextThe global demand for food is expected to continue increasing for decades, which may drive both agricultural expansion and intensification. The associated environmental impacts are potentially considerable but will depend on how the agricultural sector develops. Currently, there are contrasting regional developments in agriculture; expansion and/or intensification in some regions and abandonment in others, as well as changes in the type of farming. However, the environmental consequences of changes in farm type are not well understood. ObjectiveWe have evaluated the impacts of farm type on food production and three key environmental variables—landscape openness, grassland biodiversity and greenhouse gas (GHG) emissions—in three marginal agricultural regions in Sweden. MethodsWe do this by first dividing the population of farms in each region into types, based on their land-use and livestock holdings using an innovative clustering method. Thereafter we analysed changes in production activities for farm types over time and evaluated the environmental and food-production impacts, where landscape openness is quantified using a novel indicator. Results and conclusionOur results show that there is not one single farm type that would simultaneously maximize food production, grassland biodiversity, and landscape openness, whilst minimizing GHG emissions. However, there exists considerable potential to manage the trade-offs between food production and these environmental variables. For example, by reducing land use for dairying and instead increasing both cropping for food production and extensive livestock grazing to maintain landscape openness and biodiversity-rich semi-natural pastures, it would keep food production at similar levels. SignificanceOur farm typology allows us to assess the multifunctionality of farming, by relating contrasting production activities to multiple ecosystem services, grassland biodiversity and GHG emissions for informing policy towards more sustainable agriculture. We have demonstrated this with examples under Swedish conditions, but it should to a large extent also be applicable for other countries.

Highlights

  • Agricultural ecosystems cover around 37% of the terrestrial surface (Food Agriculture Organization of the United Nations, 1997)

  • We have evaluated the impacts of farm type on food production and three key environmental varia­ bles—landscape openness, grassland biodiversity and greenhouse gas (GHG) emissions—in three marginal agricultural regions in Sweden

  • We have developed a spatially explicit approach for mapping a large population of farms to farm types based on their major production ac­ tivities, and related those production activities to their potential for providing food, landscape openness, and grassland biodiversity while limiting their GHG emissions

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Summary

Introduction

Agricultural ecosystems cover around 37% of the terrestrial surface (Food Agriculture Organization of the United Nations, 1997). Agricultural expansion and abandonment are influenced by multiple socio-economic drivers, including: changes in the global demand for food (Tilman et al, 2011), loss of agricultural profitability in marginal areas (Ustaoglu and Collier, 2018), and loss of agricultural land because of, e.g., urbanization. In partic­ ular, ecological heterogeneity is lost at multiple spatial scales due to within-field intensification, loss of semi-natural habitat and increasing farm specialization (Emmerson et al, 2016). These changes may have consequences for both biodiversity and ecosystem services (Benton et al, 2003). The consequences of agricultural expansion or abandonment cannot be understood without accounting for concomitant structural changes in farming and landscapes. In some parts of the world, declining animal production could lead to the abandonment of semi-natural grasslands where extensive grazing has shaped highly valued species-rich communities of conservation concern (Auffret et al, 2018; Springmann et al, 2018) and which contribute to landscape multifunctionality (Bengtsson et al, 2019)

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