The objective of the present study was to establish the bioclimatic zoning by the temperature and humidity index (THI), considering a historical period and a future scenario, in order to represent the thermal environment for broiler breeding in the State of Minas Gerais. A historical series (1976 - 2014) of THI minimum, average and maximum calculated based on data from 48 conventional meteorological stations was used, belonging to the National Institute of Meteorology of the State of Minas Gerais. The analysis of the temporal series was based on the Mann-Kendall test and linear regression. A geostatistical analysis was also carried out to determine the comfort zoning of broilers as a function of the THI intervals. In this way, the THI spatial mapping methodologies and trend analysis for the prediction of a possible future climate scenario can help in the development of risk maps for monitoring thermal comfort of broilers, being indispensable in the planning of actions for the mitigation of the climatic change impacts on the productive chain of the State of Minas Gerais.

Local-level, bioclimatic regression models that relate stand characteristics (forest composition, height, site quality class and wood stocking) to site climate (temperature sums, base 5°C, and dryness index) were developed to predict the stand structure of dark-needled forest (Pinus sibirica and Abies sibirica) climax successions and their transformations in a changing climate over the Sayan mountain range in southern Siberia.The models explained up to 80% of the variation in forest growth and productivity characteristics. Productivity varied widely and depended on heat supply rather than moisture. Stand tree species composition depended on moisture: dark-needled species and light-needled tree species (Pinus sylvestris) were separated by a dryness index value of 1.0. Living phytomass was calculated from a wood stocking model. Tree heights and living phytomass were mapped over the mountain range under current climate conditions and a regional climate change scenario. The model predicts that total dark-needled forest phytomass will decrease by 17% in a warmed climate.

The aim of the present research was to propose a bioclimatic mapping to classify the thermal comfort and discomfort of rural workers within the state of Minas Gerais, considering historical and future scenarios. Monthly historical series (1976-2014) of minimum, mean and maximum temperature-humidity index (THI), determined through the values of air temperature (minimum, mean and maximum) and relative humidity from 48 weather stations located in the state of Minas Gerais were used to analyze the trends through Mann-Kendall and linear regression assays. The bioclimatic mapping of human comfort, obtained via geostatistical analysis, was developed as a function of the minimum, medium and maximum THI for the historical period (1976-2014) and future scenario (2024). Results indicate an overall trend of increasing in thermal discomfort conditions throughout the mesoregions of the state of Minas Gerais during the weather seasons, being more incisive in summer and spring.