Fig 1.
Simplified overview of the GENMON Process.
GENMON takes into account five main categories (or indices) aggregated into one final score: pedigree information (pedig-index); introgression (introg); geographic distribution (geog); cryo conservation plan (cryo); socio-economic and environmental information (BAS, standing for breed agriculture sustainability). Some of these indices come from an aggregation of criteria themselves.
Fig 2.
The process starts with data input followed by criteria processing, integration and aggregation; GI: generation interval, GIS: Geographic Information System, Pedig-Index: index accounting for pedigree and genetic diversity, Introg-Index: introgression index, LAS/BAS Index: Local/Breed Agriculture Sustainability indices, accounting for socio-economic and environmental sustainability of breeding conditions; swisstopo is the Swiss Federal Office of Topography (http://www.swisstopo.admin.ch/, WSL is the Swiss Federal Institute for Forest, Snow and Landscape Research.
Table 1.
Description of the variables to be provided from the breeding organizations at the individual level.
Table 2.
Description of the variables required to characterize the breed to be monitored, provided by the breeding association.
Table 3.
Data input and characteristics for socio-economic and environmental assessment.
Fig 3.
Link between the different geographic data types (point, polygons and grids).
All components are brought to the ZIP code level. The links are done either by joining attributes (ZIP code number, BFS ID) or according to geometries. BFS ID: unique identifier from the statistical office.
Fig 4.
Criterion scaling with the MACABETH method for the variable “Evolution of the number of jobs in agriculture”.
Evolution of the number of jobs in agriculture represents the difference of the number of jobs in agriculture between 2010 and 2012 (in %); the upper arrow indicates the initial values while the lower arrow represents the values that have been normalized between 0 and 1 (sj). The satisfaction thresholds for this criterion is defined as being 0 and 10%. The values of the satisfaction thresholds are given in S1 Appendix.
Fig 5.
Summary output table of the GENMON application.
The global index and its different components for three Swiss breeds. The colors give the degree of satisfaction of each criterion (red: not satisfactory, dark green: totally satisfactory). The breeds are ordered from the most threatened on top to the healthiest at the bottom. (GI: generation interval, F: inbreeding coefficient, Ne: population size. The description of the indices is given in section 2; VBN: Valais Blacknose sheep, FM Franches-Montagnes horse, OBV Swiss Original Braunvieh cattle). The colors are assigned according to the following thresholds (expressed in satisfaction score): 10% is the limit between red and yellow; 50% defines the limit between yellow and light-green; 95% corresponds to the threshold between light and dark green.
Fig 6.
The geographical distribution of inbreeding coefficients per ZIP-code for the Valais Blacknose (VBN) sheep.
The mean inbreeding is computed over the last generation interval (2010–2012).
Fig 7.
Inbreeding and coancestry coefficient for the Valais Blacknose (VBN) sheep breed between 1994 and 2012.
Progression of more than 0.04 of the inbreeding and 0.02 of the coancestry in 15 years; the current average inbreeding is remarkable and exceeds 0.1 while the coancestry exceeds 0.04.
Fig 8.
Geographical distribution of the local agriculture sustainability (LAS) index.
The computation based on weights and thresholds described in S1 Appendix. The colors of the areas that do not contain any Valais Blacknose sheep are faded. Sustainable areas are shown in green (e.g. area 1) while low sustainability is represented in red (e.g. area 2 situated in an urban low-land zone). The pale yellow shows intermediate values.