Abstract
Farm fragmentation refers to spatial disaggregation of a farm into smaller, often highly separated parcels of land. Ireland has a high proportion of fragmented farms; an issue not unique to Ireland. Spatial analysis of farms depends on assigning a location to the livestock. Where a farm is heavily fragmented, this becomes problematic and introduces uncertainty. With increasingly sophisticated analytical techniques, reducing this uncertainty is imperative. We explore techniques to quantify the extent and regional variation in fragmentation and the between-fragment distances of fragmented farms in Ireland. We then explore methodologies to help account for farm fragmentation in geospatial analysis and to assist in surveillance and field epidemiology.
Farms in Ireland are recorded on a Land Parcel Identification System (LPIS) allowing for interrogation by GIS. The most commonly used point representation of a farm is the centroid of the largest single fragment. However, laneways, roads, streams and other physical features break up farms on a GIS so they are not seen as a genuine spatial/epidemiological unit. Alternative spatial representations such as weighted centroid, geographic medians, density based clustering, etc. are useful but often place the estimated location outside of the actual farm. This becomes increasingly problematic as fragment separation distances become greater. To better represent farms split by local features, we utilised the Integrate tool (ArcGIS 10.7, ESRI Redlands CA) to allow same-farm boundaries to snap together across these features. For fragmented farms, the largest integrated fragment was assigned as ‘home’ and all other integrated fragments were assigned as ‘away’. Distance metrics were calculated from ‘home’ to ‘away’ fragments creating a fragment profile.
A methodology to better describe contiguity between farms was devised. Integrated farm fragments were placed into 3 categories based on their relative size to total farm size; A=>50%, B=20%-50%, C=<20%. A scoring matrix was generated to define the relative importance of adjacency between fragments based on their size category; A-A=1, A-B=2, B-B=3, A-C=4, B-B=5, C-C=6.
A spatial profile was generated for farms based on the number of integrated fragments and the fragment-fragment distances. Summary metrics (and maps) were generated by County and by uniform hexagonal grid.
A Neighbourhood matrix was generated for all contiguous between-farm fragments and coupled with shared boundary distance. This was appended to additional farm information such as head count, stocking densities, Bovine Tuberculosis (bTB) testing history and farm enterprise type to assist in prioritising farm surveillance in bTB outbreaks.
Farm fragmentation in Ireland was quantified and described through distance and neighbourhood metrics allowing for greater accuracy in application of exposure variables in geospatial analytics. In addition, they aid in prioritisation of epidemiological field investigations and contiguous surveillance for bTB and other transmissible diseases of livestock.