In livestock genetic resource conservation, decision making about conservation priorities is based on the simultaneous analysis of several different criteria that may contribute to long-term sustainable breeding conditions, such as genetic and demographic characteristics, environmental conditions, and role of the breed in the local or regional economy. Here we address methods to integrate different data sets and highlight problems related to interdisciplinary comparisons. Data integration is based on the use of geographic coordinates and Geographic Information Systems (GIS). In addition to technical problems related to projection systems, GIS have to face the challenging issue of the non homogeneous scale of their data sets. We give examples of the successful use of GIS for data integration and examine the risk of obtaining biased results when integrating datasets that have been captured at different scales.

Joost, S., Colli, L., Baret, P., Garcia, J., Boettcher, P., Tixier Boichard, M., Ajmone Marsan, P., Integrating geo-referenced multiscale and multidisciplinary data for the management of biodiversity in livestock genetic resources, <<ANIMAL GENETICS>>, 2010; 41 (1): 47-63. [doi:10.1111/j.1365-2052.2010.02037.x] [http://hdl.handle.net/10807/15151]

Integrating geo-referenced multiscale and multidisciplinary data for the management of biodiversity in livestock genetic resources

Joost, Stephane;Colli, Licia;Ajmone Marsan, Paolo
2010

Abstract

In livestock genetic resource conservation, decision making about conservation priorities is based on the simultaneous analysis of several different criteria that may contribute to long-term sustainable breeding conditions, such as genetic and demographic characteristics, environmental conditions, and role of the breed in the local or regional economy. Here we address methods to integrate different data sets and highlight problems related to interdisciplinary comparisons. Data integration is based on the use of geographic coordinates and Geographic Information Systems (GIS). In addition to technical problems related to projection systems, GIS have to face the challenging issue of the non homogeneous scale of their data sets. We give examples of the successful use of GIS for data integration and examine the risk of obtaining biased results when integrating datasets that have been captured at different scales.
2010
Inglese
Joost, S., Colli, L., Baret, P., Garcia, J., Boettcher, P., Tixier Boichard, M., Ajmone Marsan, P., Integrating geo-referenced multiscale and multidisciplinary data for the management of biodiversity in livestock genetic resources, <<ANIMAL GENETICS>>, 2010; 41 (1): 47-63. [doi:10.1111/j.1365-2052.2010.02037.x] [http://hdl.handle.net/10807/15151]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10807/15151
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