Geographic information systems approaches to investigate the production environment descriptors of local breeds

In accordance with the Global Plan of Action for Animal Genetic Resources (FAO, 2007), a set of production environment descriptors (PEDs) has been established to be used throughout the world as a common framework for describing the geographic and socio-economic features of the breeds’ production environments. The aim of this research is to test geographic information systems (GIS) approaches for the description of production environment of local breeds at different spatial scales of analysis. We used as case study the Rendena cattle, a dual purpose breed of the Eastern Italian Alps. The breed originated from a small valley (Val Rendena) in the Alps, but in the last two centuries spread towards the lowlands. The PED approach implemented on DADIS overestimated the actual distribution of the breed, and produced a highly variable range in terms of elevation, climate and land use. A second approach followed what suggested by Alderson (2009) to estimate breeds risk status; in case of epidemiological outbreaks, a breed is considered at risk when the circle including 75% of population has a radius shorter than 25 km. For Rendena cattle this radius was 63 km, and the native area of the breed was excluded from the circle, suggesting that the expansion in other areas contributed to the viability of the breed. Finally, we analysed geographic features at the farm level on the 25 singlebreed farms, with 849 cows and 3912 land parcels, of the Rendena Valley. Here, geographic features of the productive environment were typical of mountain regions. The average elevation and size of farms were 823 m asl (SD=197 m) and 14.4 ha (SD=9.3 ha). Utilizable agricultural area comprised mostly meadows, with arable crops almost absent; all the farms moved cows to highland pastures during summer. In conclusion, GIS approaches are helpful to characterize local breeds. The approach and scale of analysis and the data standardization must be tailored to the different descriptive targets.