RESUMO

The aim of this study was to model, based on the overall distribution of extreme values, the probability of occurrence of a particular level of annual maximum daily rainfall in three Brazilian regions (Midwest, Southeast and South) and study their behavior over the past 71 years. The parameters of the general distribution of extreme values were estimated by the maximum likelihood method. The Mann–Kendall test showed that there is a positive trend in the annual maximum daily rainfall data series. The non-stationarity was rejected by the augmented Dickey–Fuller test supporting the use of the density function of extreme value distribution to describe the values of the occurrence of annual maximum daily rainfall. The Kolmogorov–Smirnov/Lilliefors goodness-of-fit test showed the good fit of the studied variable to the probability distribution function. The Midwest region has a return period of more frequent annual maximum daily rainfall below 300 mm in comparison with other regions. There is a clear change in the behavior of this extreme event in the Southern region. According to the literature, in past decades annual maximum daily rainfall of 248 mm has been estimated for a return period of 100 years for the state of Santa Catarina-South region, while the results found with the current series, annual maximum daily rainfall of 250 mm was estimated for a return period of 10 years. Extreme annual maximum daily rainfalls for return periods smaller were also found in other regions. Clique aqui para acessar a publicação

RESUMO

In this paper we calculated soil carbon stocks in Brazil studying 17 paired sites where soil stocks were determined in native vegetation, pastures and crop-livestock systems (CPS), and in other regional samplings encompassing more than 100 pasture soils, from 6.58 to 31.53° S, involving three major Brazilian biomes: Cerrado, Atlantic Forest, and the Pampa. The average native vegetation soil carbon stocks at 10, 30 and 60 cm soil depth were equal to approximately 29, 64, and 92 Mg ha−1, respectively. In the paired sites, carbon losses of 7.5 Mg ha−1 and 11.6 Mg ha−1 in CPS systems were observed at 10 cm and 30 cm soil depths, respectively. In pasture soils, carbon losses were similar and equal to 7.5 Mg ha−1 and 11.0 Mg ha−1 at 10 cm and 30 cm soil depths, respectively. Differences at 60 cm soil depth were not significantly different between land uses. The average soil δ13C under native vegetation at 10 and 30 cm depth were equal to −25.4‰ and −24.0‰, increasing to −19.6‰ and −17.7‰ in CPS, and to −18.9‰, and −18.3‰ in pasture soils, respectively; indicating an increasing contribution of C4 carbon in these agrosystems. In the regional survey of pasture soils, the soil carbon stock at 30 cm was equal to approximately 51 Mg ha−1, with an average δ13C value of −19.67‰. Key controllers of soil carbon stock in pasture sites were sand content and mean annual temperature. Collectively, both could explain approximately half of the variance of soil carbon stocks. When pasture soil carbon stocks were compared with the average soil carbon stocks of native vegetation estimated for Brazilian biomes and soil types by Bernoux et al. (2002) there was a carbon gain of 6.7 Mg ha−1, which is equivalent to a carbon gain of 15% compared to the carbon soil stock of the native vegetation. The findings of this study are consistent with differences found between regional comparisons like our pasture sites and plot-level paired study sites in estimating soil carbon stocks changes due to land use changes. Clique aqui para acessar a publicação

RESUMO

The aim of this study was to model the occurrence of extreme dry spells in the Midwest, Southeast and Southern regions of Brazil and estimate the return period of the phenomenon indicating the time when the occurrence is more severe. The generalized extreme value distribution was the best fit for a series of maximum dry spell number and the parameters estimated by the maximum likelihood method. The data series adherence to the probability distribution was verified by the Kolmogorov–Smirnov test and the percentile–percentile charts. The positive trend of dry spells was verified by the Mann–Kendall test and non-stationarity rejected by Dickey–Fuller and augmented Dickey–Fuller tests. The irregular distribution of rainfall in the growing season for the Midwest region has increased the number of dry spells. The increase of rainy days in the Southeast and the South resulted in a decrease of dry spells in these regions. Regarding the return period of one year, dry spells occurred from 5 to 25 days in the Midwest region meaning a loss of productivity for Brazilian agriculture if it happened between the flowering and grain filling phases, making it, therefore the region with the largest agricultural risk. When the intensity of the dry spells was analyzed for different return periods, the Southern region was the most vulnerable. Clique aqui para acessar a publicação

RESUMO

The objective of this work was to evaluate the effect of the temperature increase forecasted by the Intergovernmental Panel on Climate Change (IPCC) on agricultural zoning of cotton production in Brazil. The Northeastern region showed the highest decrease in the low-risk area for cotton cultivation due to the projected temperature increase. This area in the Brazilian Northeast may decrease from 83 million ha in 2010 to approximately 71 million ha in 2040, which means 15% reduction in 30 years. Southeastern and Center-Western regions had small decrease in areas suitable for cotton production until 2040, while the Northern region showed no reduction in these areas. Temperature increase will not benefit cotton cultivation in Brazil because dimension of low-risk areas for economic cotton production may decrease. Clique aqui para acessar a publicação