Assessing regional farming system diversity using a mixed methods typology: the value of comparative agriculture tested in broadacre Australia - Lacoste, Myrtille; Lawes, R.; Ducourtieux, O.; Flower, K. (Pergamon-Elesevier Science Ltd, 2018)
Most farm and farmer typologies focus on specific aspects and use standard structural and socio-economic indicators. Regional assessments of agricultural diversity based on farming systems are rarely done, as detailed and representative information is difficult to collect. The discipline of comparative agriculture addresses these challenges but remains little known, and seldom applied to broadacre situations. This study demonstrates in Western Australia the value of its mixed methods and multi-disciplinary concepts to determine the level and nature of regional farming system heterogeneity. The typology built comprised six farming systems based on 36 farms that represented half the farming population of a 4000 km 2 area (broadacre rainfed systems dominated by winter cereals and sheep, Mediterranean climate). The farm groups corresponding to these farming systems differed across 36 variables representing biophysical, technical, and social aspects at varied spatial and temporal scales. Results were compared with five sets of farm clusters produced through multivariate clustering procedures commonly employed to build typologies. These farm clusters differed across fewer variables than the farm groups of the comparative agriculture typology. The analytical, methodological and conceptual tools used in comparative agriculture to solve the challenges associated with the holistic study of farming system heterogeneity are discussed. These included basing data collection and analysis on an empirical approach that assessed groups of farms rather than individuals, solving data scarcity through a range of qualitative techniques, and progressively informing the choice of typology criteria. Comparative agriculture thus provides an alternative to standard typology paradigms that deserves wider application.