Search

Copyright of Geosul is the property of Geosul and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The Renewable Energy Program of Minas Gerais is one of the initiatives which aims at the intensification in the use of renewable sources in the state. The present paper applies a methodology to evaluate the effectiveness of such instrument to expand the number of renewable energy projects and its contribution to achieve the goals of the energy sector of the Brazilian Nationally Determined Contributions, that is, to increase the use of renewable energy by 45% until 2030. It has been observed that the expansion of the renewable energy sources at regional level has advanced by incentive policies with clearly defined goals and guidelines. However, the analyzed program does not attend to all the requirements and it is possible to conclude that the main state public policy of renewable energy expansion did not accomplish its objectives suggesting that a balanced mix of public policies must be implemented in order to promote an effective energy transition. [ABSTRACT FROM AUTHOR]

In hydrological modelling, it is important to consider the uncertainties related to a model's structures and parameters when different hydrological models are used to represent a system. Therefore, an adequate analysis of daily discharge forecasts that takes into account the performance of hydrological models can assist in identifying the best extreme discharge forecasts. In this context, this study aims to evaluate the performance of three hydrological models—Lavras Simulation of Hydrology (LASH), Variable Infiltration Capacity (VIC), and Distributed Hydrological Model (MHD-INPE) in the Verde River basin. The results demonstrate that LASH and MHD can accurately simulate discharges, thereby establishing them as crucial tools for managing water resources in the study region's basins. Moreover, these findings could serve as a cornerstone for future studies focusing on food and water security, particularly when examining their connection to climate change scenarios. [ABSTRACT FROM AUTHOR]

Global changes increasingly worry researchers and policymakers and may have irreversible impacts on Earth's biodiversity. Similar to other phytophysiognomies, natural grasslands suffer from the effects of land use changes and rising temperatures, threatening animal and plant communities. Birds, being very sensitive to these changes, are widely studied and fundamental to understand the dynamics of ecosystems in relation to climate and land use changes. The Campo Miner Geositta poeciloptera is a grassland bird endemic to the Brazilian Cerrado and threatened with extinction that has been widely studied in recent years. We analyze the decrease in its extent of occurrence (EOO) and the effects of climate and land use change to understand the environmental suitability of the species in current and future scenarios. We used 5 common algorithms to produce ecological niche models. For future predictions, we use two general circulation models for two different greenhouse gas emission scenarios with different climate policies, an optimistic (ssp245) and a pessimistic (ssp585), plus two land use models focusing on increasing farmlands and reducing native grasslands. The current EOO represents ~45% of that presented by the IUCN EOO. The models generated for the present were satisfactory (TSS = 0.77 and ROC = 0.90) and showed high environmental suitability in areas where the species is currently found and low suitability where it is already extinct. All future scenarios have reduced suitable areas for the species, and the models of a greater increase in temperature and increase in farmlands and a greater decrease in grasslands were the worse. Our results reinforce the need to care about biome awareness disparity and the importance of actively preserving grassy‐shrub areas. Apparently, the state of Minas Gerais will be the only stronghold of the species in the coming years; however, the lack of protected areas that guarantee its survival needs attention. [ABSTRACT FROM AUTHOR]

Brown eye spot (Cercospora coffeicola) is one of the main fungal diseases of coffee, leading to a significant drop in crop productivity and beverage quality in Brazil. The identification of potential risk areas for the development of the disease provides promising information for the management of the pathogen. This study aimed to elaborate an agroclimatic zoning for the incidence of brown eye spot on coffee under climate change scenarios, as suggested by IPCC (IPCC-AR5), in the main coffee-growing regions. Climate data of air temperature, precipitation, and relative humidity were collected from the National Aeronautics and Space Administration/Prediction of Worldwide Energy Resources (NASA/POWER) platform from 1989 to 2020 for 46 municipalities in the states of Paraná, São Paulo, Minas Gerais, Espírito Santo, Goiás, and Bahia. The ideal climate for brown eye spot occurrence consists of an air temperature (Tmean) between 18 and 30 °C, relative humidity (RHmean) > 90%, and leaf wetness duration (LWD) > 9 h. The number of hours of leaf wetness was determined by the sum of hours with relative humidity > 90%. Relative humidity was estimated for each hour of the day using air temperature and estimated data of mean dew point temperature, maximum relative humidity, and minimum relative humidity. Climate change scenarios were designed based on sets of climate simulations for the twenty-first century. Scenario S1 is the current scenario without changes, while scenarios S2 and S3 show Tmean + 1.5 °C and 3.0 °C, respectively, with RHmean without changes. Scenarios S4 and S5 present RHmean varying from − 30% to + 30%, respectively, with Tmean unchanged. In the current scenario (S1), Minas Gerais presented a predominance of 100% for low climate risk to brown eye spot in September. Paraná presented a medium risk in 76.15% of the state in April. Scenarios S2 and S3 showed significant changes, increasing the average fitness class in the study region, mainly in the states of São Paulo, Minas Gerais, Rio de Janeiro, and Paraná. Scenario S4 showed 100% predominance of the low-risk class. In contrast, S5 showed the occurrence of the high-risk class for the study region with a + 30% increase in relative humidity. Minas Gerais presented a predominance of the high-risk class for the development of C. coffeicola in 76%, 100%, 97.83%, 89.30%, 93.46%, 80.64%, and 57.77% from November to May, respectively. The presence of high relative humidity represents the main factor for the expansion of the high-risk class for the development of C. coffeicola. Producers knowing the months of the year and the places in Brazil with the highest incidence of brown eye spot will be able to prevent the disease in a more sustainable way, using more ecological products, such as the early application of copper. [ABSTRACT FROM AUTHOR]

The knowledge of the climatic conditions of a region is crucial for its agricultural development. It is also extremely important for understanding the fact that certain cultures have to develop under prevailing temperature and humidity conditions and assist in the adoption of a suitable irrigation technique, as well as its management and operationalization. The Köppen system of climate classification is widely used for the identification of homogeneous climate zones as it considers only rainfall and temperature as the meteorological elements for classification. For this study, we used climatic databases of rainfall and temperature in a raster format, with a spatial resolution of 30″ of arc (an approximate area of 0.86 km pixel), from 1961 to 1990. Through geoprocessing techniques, we obtained a map of climatic classification for the state of Minas Gerais. We found that the state has the following three major climatic groups: A, B and C, which correspond to tropical rainy, dry and warm temperate climates, respectively. The climate classes obtained were Aw, Am, BSh, Cwa and Cwb, with Aw, Cwa and Cwb classes occupying 99.89% of the territorial area of the state. The validation of the results showed a satisfactory agreement, with 93.75% reliability. [ABSTRACT FROM AUTHOR]