Abstract/Summary

Sustainable development of the agricultural sector has become the leading edge of the agricultural scientific debate and policy making both in the UK as well as in the international level. This has arisen due to the need for an agricultural sector that is continuously able to provide food, generate economic outputs and preserve environmental quality. This study uses physical and financial farm-level data on farm businesses in the Less Favoured Areas of England, as well as data regarding environmental, weather and landscape characteristics, to create a framework enabling the sustainable development of hill farming systems. Statistical techniques including a Principal Component Analysis (PCA) and a Multiple Linear Regression (MLR) were used to identify drivers of performance within upland farms, whilst mathematical programming methods that regard Linear Programming (LP) modelling were incorporated to study the impacts of farm management, environmental conditions and socioeconomic context. Furthermore, through a spatial analysis within Geographic Information Systems (GIS), this study reveals geographical insights regarding the sustainable development of the uplands, creating knowledge for the design future policy support. The empirical results highlight a range of parameters that trigger leading or lagging performances relative to farm-level management decisions such as financial dependency and the social characteristics of the farmer as well as inherent landscape characteristics that regard proximity to abattoirs or level of physical disadvantage. Additionally, in examining practices that promote sustainable development, results point out that integration of crop and livestock production systems (ICLS) allows enhanced farm-level performance and sustainability. Moreover, results from the geographical analysis point out the spatial variability of such factors among the regions of Cumbria, Northumberland and the Peak District, highlighting the need for a new agricultural policy that will spatially target support by taking into consideration the potential opportunities as well as the natural handicaps that exist across the various landscapes.