Coffee is one of the most consumed beverages in the world, and its international market has been growing for many years. Unfortunately, the Brazilian coffee production is threatened by high temperatures projected by climate change models. We evaluated three schemes of low levels of shade, which avoid the loss of production, as a strategy to adapt coffee to possible climate change. Additionally, as field measurements are expensive and often difficult to implement, we used numerical simulation to complement the evaluation. The microclimate simulator software Envi-met is a computer program often used to simulate urban environments, and we tested it on agriculture design. We verified that the shaded schemes assessed in the field decreased the air temperature in 0.6 °C in the studied period and reduced other possible climate stressors such as wind speed, radiation and raised air humidity in the dry period. Envi-met described the studied meteorological variable cycle very well, showing that combining numerical modelling and field research may be an important tool for planning the adaptation of the coffee sector to possible climate change, allowing growers choose a proper technique for their regions and environmental conditions. Finally, we highlighted the importance of planning the shade scheme on coffee areas in an interdisciplinary approach, including local climate evaluation to achieve a balance between temperature attenuation and production.

Coffee is one of the most important crops in Brazil. Monitoring the crop is necessary to understand future production and a sound understanding of coffee's biophysical properties improves such monitoring. Biophysical properties such as dry biomass can be estimated using remote sensing, including the new generation of high-resolution images (GeoEye-1, for instance). In this study we aim to investigate the relationship between vegetation indices (VI) of high-resolution images (GeoEye-1) and coffee biophysical properties, including dry biomass and carbon. The study also aims at establishing an empirical relationship between remote sensing data (vegetation indices), simple field measurements and dry biomass, allowing calculation of coffee biomass and carbon without resorting to destructive methods. Individual GeoEye-1 satellite's bands (NIR, RED and GREEN) showed significant correlation with biomass, but the best correlation occurred with vegetation index. There is a strong correlation between NDVI, RVI, GNDVI and dry biomass, allowing the estimation of coffee crops' carbon stock. RVI had correlation with plant area index (PAI). The empirical correlation was established and the forecast equation of coffee biomass was created.

Mudanças climáticas tem se tornado um tema de discussão em diferentes áreas da sociedade, inclusive na educação, onde esse tópico é considerado recente no contexto brasileiro. Frente ao exposto buscou-se, a partir de uma revisão integrativa da literatura, compreender como vem ocorrendo as pesquisas e a difusão de conhecimentos sobre a educação em mudanças climáticas no Brasil. Para isso, utilizou-se o Google Acadêmico, uma plataforma de livre acesso a pesquisadores e professores da rede básica de ensino, e palavras-chaves em português, a partir das quais foi possível encontrar 25 artigos que se encaixavam nas diretrizes estabelecidas para essa pesquisa. Dentre os resultados, 11 foram artigos teóricos e 14 práticos, os quais demonstraram uma grande preocupação com a compreensão do tema por parte dos estudantes, dada sua complexidade. Nesse sentido, esta pesquisa também evidenciou que algumas vezes a educação ambiental aparece correlata a educação em mudanças climáticas, o que pode ocasionar problemas conceituais. Notou-se também, que há carência de estudos sobre a formação de professores em mudanças climáticas.