Bioclimatic Zoning for Sheep Farming through Geostatistical Modeling in the State of Pernambuco, Brazil

Area of Science:

• Agricultural Science
• Climate Science
• Animal Science

Background:

• Developing countries face significant climate change vulnerability, impacting food and income security.
• Sheep farming is crucial for families in vulnerable semiarid regions like Pernambuco, Brazil.
• Pernambuco experiences harsh climatic conditions including high temperatures and low humidity.

Purpose of the Study:

• To identify suitable regions in Pernambuco for different sheep breeds.
• To assess sheep farming potential based on climatic suitability.
• To utilize non-parametric statistics and kriging maps for regional analysis.

Main Methods:

• Calculated the temperature and humidity index (THI) using mean annual temperature and wind speed data.
• Extracted climate data from the TerraClimate remote sensing database.
• Employed non-parametric statistics and kriging maps for spatial analysis of THI values.

Main Results:

• Pernambuco's THI values range from 66 to 79.
• Hair sheep breeds show high potential across most of Pernambuco, including meat-producing types.
• East Friesian (dairy) and wool breeds (Suffolk, Poll Dorset, Texel) are suited to specific mesoregions and microregions.

Conclusions:

• Kriging maps of THI effectively identified strategic regions for sheep breeding development in Pernambuco.
• The study provides a framework for climate-informed sheep breed selection in vulnerable agricultural areas.
• Optimizing sheep farming can enhance food and income security in climate-vulnerable Brazilian territories.