In  dominant livestock systems of Sahelian countries herds have to move across the territories. Their mobility is often  source of conflict with farmers of the crossed areas , and engender the spread of diseases such as Rift Valley Fever. Knowledge of the routes followed by herds is therefore central to guide the implementation of preventive and control measures for transboundary animal diseases, land use planning and conflict management. However, the lack of quantitative data on livestock movements, together with the high temporal and spatial variability of herd movements, has so far hampered the production of fine resolution maps of passage of animals . This paper proposes a general framework for mapping potential paths for livestock movements and identify areas of high potential of animal passage for these movements. The method consists in coupling the information contained in livestock mobility network with landscape connectivity  based on different mobility conductance layers. We illustrate our approach with a livestock mobility network in Senegal and Mauritania in  dry and wet seasons in 2014.
In the dominant livestock systems of Sahelian countries herds have to move across territories. Their mobility is often a source of conflict with farmers in the areas crossed, and helps spread diseases such as Rift Valley Fever. Knowledge of the routes followed by herds is therefore core to guiding the implementation of preventive and control measures for transboundary animal diseases, land use planning and conflict management. However, the lack of quantitative data on livestock movements, together with the high temporal and spatial variability of herd movements, has so far hampered the production of fine resolution maps of animal movements . This paper proposes a general framework for mapping potential paths for livestock movements and identifying areas of high animal passage potential for those movements. The method consists in combining the information contained in livestock mobility networks with landscape connectivity , based on different mobility conductance layers. We illustrate our approach with a livestock mobility network in Senegal and Mauritania in the 2014 dry and wet seasons .
A
the
D
the
A
a
R
of the crossed areas , and engender the spread of
in the areas crossed, and helps spread
R
central to guide
core to guiding
R
passage of animals
animal movements
R
identify
identifying
R
potential of animal passage for these
animal passage potential for those
R
coupling
combining
R
network
networks
A
,
A
the 2014
R
in 2014.
.