Use of geographic information system tools to predict animal breed suitability for different agro-ecological zones

Research output: Contribution to journalArticleAcademicpeer-review

Abstract

Predicting breed-specific environmental suitability has been problematic in livestock production. Native breeds have low productivity but are thought to be more robust to perform under local conditions than exotic breeds. Attempts to introduce genetically improved exotic breeds are generally unsuccessful, mainly due to the antagonistic environmental conditions. Knowledge of the environmental conditions that are shaping the breed would be needed to determine its suitability to different locations. Here, we present a methodology to predict the suitability of breeds for different agro-ecological zones using Geographic Information Systems tools and predictive habitat distribution models. This methodology was tested on the current distribution of two introduced chicken breeds in Ethiopia: the Koekoek, originally from South Africa, and the Fayoumi, originally from Egypt. Cross-validation results show this methodology to be effective in predicting breed suitability for specific environmental conditions. Furthermore, the model predicts suitable areas of the country where the breeds could be introduced. The specific climatic parameters that explained the potential distribution of each of the breeds were similar to the environment from which the breeds originated. This novel methodology finds application in livestock programs, allowing for a more informed decision when designing breeding programs and introduction programs, and increases our understanding of the role of the environment in livestock productivity.

LanguageEnglish
Pages1536-1543
JournalAnimal
Volume13
Issue number7
Early online date13 Nov 2018
DOIs
Publication statusPublished - Jul 2019

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agroecological zones
geographic information systems
breeds
animals
environmental factors
livestock
chicken breeds
livestock production
methodology
Ethiopia
Egypt
South Africa

Keywords

  • agro-ecology
  • breeding programs
  • distribution models
  • livestock
  • local adaptation

Cite this

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title = "Use of geographic information system tools to predict animal breed suitability for different agro-ecological zones",
abstract = "Predicting breed-specific environmental suitability has been problematic in livestock production. Native breeds have low productivity but are thought to be more robust to perform under local conditions than exotic breeds. Attempts to introduce genetically improved exotic breeds are generally unsuccessful, mainly due to the antagonistic environmental conditions. Knowledge of the environmental conditions that are shaping the breed would be needed to determine its suitability to different locations. Here, we present a methodology to predict the suitability of breeds for different agro-ecological zones using Geographic Information Systems tools and predictive habitat distribution models. This methodology was tested on the current distribution of two introduced chicken breeds in Ethiopia: the Koekoek, originally from South Africa, and the Fayoumi, originally from Egypt. Cross-validation results show this methodology to be effective in predicting breed suitability for specific environmental conditions. Furthermore, the model predicts suitable areas of the country where the breeds could be introduced. The specific climatic parameters that explained the potential distribution of each of the breeds were similar to the environment from which the breeds originated. This novel methodology finds application in livestock programs, allowing for a more informed decision when designing breeding programs and introduction programs, and increases our understanding of the role of the environment in livestock productivity.",
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Use of geographic information system tools to predict animal breed suitability for different agro-ecological zones. / Lozano-Jaramillo, M.; Bastiaansen, J.W.M.; Dessie, T.; Komen, H.

In: Animal, Vol. 13, No. 7, 07.2019, p. 1536-1543.

Research output: Contribution to journalArticleAcademicpeer-review

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