Brazilian livestock provides a significant fraction of the food consumed globally, making the country one of the largest producers and exporters of meat, milk and eggs. However, current advances in the production of protein from Brazilian animal origin may be directly impacted by climate change and the resulting biophysical effects. Therefore, it is strategically consistent to develop measures to deal with the resulting environmental heat stress on domesticated animal species, especially the need in developing countries. This work aims to (1) evaluate the impacts of climate change on livestock (cattle-dairy, cattle-beef, goats, sheep, pigs, poultry-general) in different regions of Brazil and (2) discuss possible response strategies, associated with animal comfort and welfare. From our results, we can draw better strategies to mitigate the impacts of climate change on livestock production. The results presented show an increase of high heat stress in South and Southeast and an increase of extreme heat stress in North and Central-West areas of Brazil. The rise in extreme heat stress tends to occur mostly during spring and summer and tends to vary considering the different evaluated species. Within the evaluated species, the ones that seem to be more affected by climate changes are Poultry, pigs, cattle-beef and general (temperature-humidity index value). The differences between the results for the five geographic regions in Brazil suggests that different mitigation measures need to be considered to cope with future heat stress in livestock. To ensure the long-term success of Brazil's influence on the global market for proteins of animal origin, it must achieve sustainable production systems more intensively.

Climate change is causing an increase in global temperatures, with significant impacts on dairy production. This systematic review analyzes the challenges of new climate scenarios, focusing on the resilience and adaptation strategies of dairy systems. The PRISMA methodology guided the review process using the Scopus and Web of Science databases. After applying exclusion criteria, 30 articles published between 2015 and 2025 were selected. The studies included analyses of the effects of heat stress on animal parameters (I), socioeconomic parameters (II), and technological adaptation tools (III) in various geographic regions. Most research over the last decade addresses category (I), with a greater concentration in the Northern Hemisphere. The Temperature Humidity Index (THI) emerged as the main indicator of heat stress, associated with the physiological responses of dairy cattle. Heat stress reduces milk production, feed intake, reproductive performance, and overall animal health, often leading to increased slaughter rates. Adaptation strategies include genetic selection for heat tolerance, improved environmental monitoring, cooling technologies, and optimized nutritional and management practices, applicable to both pasture and feedlot systems. Despite being among the main producers, studies on the topic in South American countries are still scarce in the literature.

Transmission line towers are highly exposed to weather hazards. In southern Brazil, several damages to transmission lines have been reported due to severe weather events. Climate change projections indicate that the frequency and magnitude of extreme events may increase, making planning and adaptation of the transmission system exposure even more critical. In this work, we propose a severe weather index (SWI) as a proxy for detecting severe storms that can potentially result in extreme weather events. The SWI combines thresholds of instability indices based on observed severe events around the transmission tower-line systems. These indices were calculated using the downscaling by the Eta model at 20 km resolution of three global climate model projections and at 5 km of one global climate model for the historical period and the near future. The results show that the SWI captures the severe storms observed in the region. All downscaling projections agree with the increase of extreme weather events in the near future and the expansion of vulnerable areas. The constructed index can be employed to assess the risks and to plan the power transmission system better.

The objective of this work is to evaluate the subseasonal precipitation simulations of the Eta model during the onset of the rainy season in the Sao Francisco River Basin (SFB). Accumulated precipitation every 20 days in September and October (2011 to 2015) was evaluated based on subseasonal simulations (integration period of up to 60 days) of the Eta-20-km model, nested within the Climate Forecast System Reanalysis (CFSR), here called Eta-CFSR. MERGE precipitation data were used to evaluate Eta-CFSR simulated precipitation. A statistical method was employed to evaluate the model’s ability to simulate the onset of the rainy season in the Upper SFB. The main results are: i) The Eta-CFSR accurately represents the seasonality of the precipitation pattern in the SFB and the seasonal and interannual variation of the accumulated precipitation in all of the chosen three consecutive 20-day periods of years 2011 to 2015; ii) The model can represent the transition pattern from the dry to the rainy season, showing better results in 2011 and 2015, which were marked, respectively, by La Niña and El Niño, and by anomalies of sea surface temperature favorable and unfavorable for the occurrence of precipitation; iii) Although the model underestimates the amount of precipitation, it effectively captures the seasonal patterns and the onset of the rainy season, with a maximum advancement of two pentads in wetter years and delaying it in drier years.