Measurements of litter production, and the surface litter pool were made over a 1 year period in a tropical transitional forest near Sinop, Mato Grosso Brazil with the aim of quantifying the seasonal variation of nitr...Measurements of litter production, and the surface litter pool were made over a 1 year period in a tropical transitional forest near Sinop, Mato Grosso Brazil with the aim of quantifying the seasonal variation of nitrogen and phosphorus in the litter and the annual contribution of nutrients to the soil. Average annual litterfall （＋95% confidence interval （CI）） was 8.20 ton.ha^-1 year^-1 and forest floor litter mass was 58.63 ton＇hal. Nitrogen and phosphorus in the forest floor litter mass was highest during the dry and dry-wet season, being 38% higher than in the wet and wet-dry season. Seasonal variation in the litter and concentration of nutrients was explained by seasonal variations in the climate, for example in the precipition and soil humidity. Average annual nitrogen and phosphorus concentrations in the forest floor mass were 17.24 ton.ha^-1 and 16.46 ton.ha^-1, respectively. The more significant forest floor mass fraction for returning soil nutrients was the leaves. The concentration of nutrients was higher in the soil superficial layer （at depths between 0-5 cm） than at depths between 30-70 cm, approximately 83% and 93% for total nitrogen and available phosphorus, respectively.展开更多
Geosciences and statistics were applied to develop predictive models to study the areas of risk to soybean rust （Phakopsora pachyrhizi Sydow） in soybean （Glycine max L.）, coffee leaf rust （Hemileia vastatrix Berk...Geosciences and statistics were applied to develop predictive models to study the areas of risk to soybean rust （Phakopsora pachyrhizi Sydow） in soybean （Glycine max L.）, coffee leaf rust （Hemileia vastatrix Berk ＆ Br） in coffee and Black Sigatoka （Mycosphaerella fijiensis var. difformis） in banana, considering to Brazilian climatic characterization and distribution of soybean, coffee and banana crops in the period of observed data of 1950 to 2000 and A2 climate change scenarios of simulated data of 2020, 2050 and 2080. The technique of principal components allowed generating 1 variable based on 57 variables in order to determine an index explaining 87%, 88% and 90% of the variability of soybean, coffee and banana crops in Brazilian municipal districts. The climatic model of each disease was used to generate the zoning of the coffee rust, soybean rust and black sigatoka based on temperature and leaf wetness. Areas of favorability of the diseases were plotted inside to the main coffee, soybean and banana growing in Brazil. The applied methodology enabled to visualize the variation of favorable areas of epidemics according to the studied scenarios of climate change.展开更多
文摘Measurements of litter production, and the surface litter pool were made over a 1 year period in a tropical transitional forest near Sinop, Mato Grosso Brazil with the aim of quantifying the seasonal variation of nitrogen and phosphorus in the litter and the annual contribution of nutrients to the soil. Average annual litterfall （＋95% confidence interval （CI）） was 8.20 ton.ha^-1 year^-1 and forest floor litter mass was 58.63 ton＇hal. Nitrogen and phosphorus in the forest floor litter mass was highest during the dry and dry-wet season, being 38% higher than in the wet and wet-dry season. Seasonal variation in the litter and concentration of nutrients was explained by seasonal variations in the climate, for example in the precipition and soil humidity. Average annual nitrogen and phosphorus concentrations in the forest floor mass were 17.24 ton.ha^-1 and 16.46 ton.ha^-1, respectively. The more significant forest floor mass fraction for returning soil nutrients was the leaves. The concentration of nutrients was higher in the soil superficial layer （at depths between 0-5 cm） than at depths between 30-70 cm, approximately 83% and 93% for total nitrogen and available phosphorus, respectively.
文摘Geosciences and statistics were applied to develop predictive models to study the areas of risk to soybean rust （Phakopsora pachyrhizi Sydow） in soybean （Glycine max L.）, coffee leaf rust （Hemileia vastatrix Berk ＆ Br） in coffee and Black Sigatoka （Mycosphaerella fijiensis var. difformis） in banana, considering to Brazilian climatic characterization and distribution of soybean, coffee and banana crops in the period of observed data of 1950 to 2000 and A2 climate change scenarios of simulated data of 2020, 2050 and 2080. The technique of principal components allowed generating 1 variable based on 57 variables in order to determine an index explaining 87%, 88% and 90% of the variability of soybean, coffee and banana crops in Brazilian municipal districts. The climatic model of each disease was used to generate the zoning of the coffee rust, soybean rust and black sigatoka based on temperature and leaf wetness. Areas of favorability of the diseases were plotted inside to the main coffee, soybean and banana growing in Brazil. The applied methodology enabled to visualize the variation of favorable areas of epidemics according to the studied scenarios of climate change.
