Universidade de Brasília, Instituto de Ciências Biológicas, Asa Norte, CEP: 70910-900, Brasília, DF, Brazil.
Centro de Energia Nuclear na Agricultura da Universidade de São Paulo (CENA/USP), Av. Centenário, 303 - São Dimas, CEP: 13416-000, Piracicaba, SP, Brazil.
LSIE, Departamento de Geografia, ICC Norte, Universidade de Brasília, Asa Norte, CEP: 70910-900, Brasília, DF, Brazil.
LSIE, Departamento de Geografia, ICC Norte, Universidade de Brasília, Asa Norte, CEP: 70910-900, Brasília, DF, Brazil.
LSIE, Departamento de Geografia, ICC Norte, Universidade de Brasília, Asa Norte, CEP: 70910-900, Brasília, DF, Brazil.
CEUB, 707/907 - Campus Universitário - Asa Norte, CEP: 70790-075, Brasília, DF, Brazil.
Universidade de Brasília, Instituto de Ciências Biológicas, Asa Norte, CEP: 70910-900, Brasília, DF, Brazil.
Embrapa Recursos Genéticos e Biotecnologia, Parque Estação Biológica, PqEB, Av. W5 Norte (final) Caixa Postal 02372, CEP: 70770-917, Brasília, DF, Brazil.
Instituto Federal Catarinense, Campus Araquari, Rodovia BR 280, km 27, CEP: 89245-000, Araquari, SC, Brazil.
The use of georeferencing technologies and genetic information has increased to integrate management and planning of livestock production systems, predict adaptive capacities, and aid in developing strategies for national Animal Genetic Resource Conservation Programs. Researchers and farmers can use this information to define conservation objectives for individual breeds and examine environmental factors that affect extinction risk, such as disease threats. Molecular markers and geographic information come together in landscape genetics, a combination of landscape ecology and population genetics, to provide information on the interaction between landscape and evolutionary processes. Results reveal attributes that affect genetic adaptation to specific environmental stressors such as diseases, parasites, extreme heat, vegetation type, lack of water, or combinations. Recent preliminary studies in Brazil used these tools to identify the regional usage patterns for animal production based on environmental criteria and breed distribution data. The results have been used as a further criterion to optimise in situ, and ex situ conservation schemes and plan expansion and adaptation of production systems. The use of production environment descriptors and climatic and genetic information will help maintain animal production systems in a changing world.
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