Climate change scenarios and their impact on adaptive and productive mechanisms in farm animals: What will be the sustainable strategies for animal production in the coming decades?

• Grant number: 24/23335-2
• Support Opportunities: Scholarships in Brazil - Post-Doctoral
• Start date: August 01, 2025
• End date: July 31, 2028
• Field of knowledge: Agronomical Sciences - Agricultural Engineering - Rural Buildings and Ambience
• Principal Investigator: Iran José Oliveira da Silva
• Grantee: Robson Mateus Freitas Silveira
• Host Institution: Escola Superior de Agricultura Luiz de Queiroz (ESALQ). Universidade de São Paulo (USP). Piracicaba , SP, Brazil

Abstract

Climate change is one of the main challenges for global livestock production because food security is likely to be compromised by increased heat stress in livestock. The need to conduct studies on the impacts of climate change on the Brazilian livestock sector is urgent, especially in a country that relies heavily on animal genetic material imported from regions with temperate climates, which means that these breeds/ lineages were not selected for tropical climate. Here, we propose to evaluate and model the impact of climate change on the thermoregulatory and productive responses of swine and poultry until the end of the century using different climate models. Specifically, we aim to (i) evaluate the impact of the thermal environment on the thermoregulatory and productive responses of livestock; (ii) analyze the adaptive mechanisms that livestock has used in response to the main effects of climate change; (iii) determine which breeds/lineages for each species studied will be more resistant to climate change at the end of the century considering the current genetic base; (iv) model climate scenarios for 2050, 2075 and 2100 in thermoregulatory and productive responses using the RCP 4.5 and 8.5 models; both used by the IPCC; and (v) identify which animal species will be more susceptible or resistant to climate change. Meteorological, productive, and thermoregulatory variables will be collected in different production systems in different regions of Brazil. The statistical methods used will be a combination of multivariate models and machine learning algorithms. Our results will allow (1) predicting how the effects of climate change may affect productive efficiency and animal welfare; (2) planning adaptation strategies, since based on the projected scenarios, it is possible to develop adaptation strategies to minimize negative impacts. This may include the implementation of thermal control technologies, genetic improvement to increase animal resilience and nutritional management strategies; (3) ensure food security, as animal production is an essential source of food for many populations and (4) support the formulation of public policies that aim to mitigate climate impacts on the agricultural sector, ensuring the maintenance of animal production in uncertain future conditions.