First-order decay models to describe soil C-CO2 Loss after rotary tillage

Para entendimento do impacto do preparo do solo sobre as emissões de CO2 desenvolvemos e aplicamos dois modelos conceituais que são capazes de prever a emissão de CO2 do solo após seu preparo em função da emissão da parcela sem distúrbio, acrescida de uma correção devido ao preparo. Os modelos assumem que o carbono presente na matéria orgânica lábil segue uma cinética de decaimento de primeira ordem, dada pela seguinte equação: dCsoil (t) / dt = -k Csoil (t), e que a emissão de C-CO2 é proporcional a taxa de decaimento do C no solo, onde Csolo(t) é a quantidade de carbono lábil disponível no tempo (t) e k é a constante de decaimento (tempo-1). Duas suposições foram testadas para determinação das emissões após o preparo do solo (Fp): a constante de decaimento do carbono lábil do solo (k) antes e após o preparo é igual (Modelo 1) ou desigual (Modelo 2). Conseqüentemente, a relação entre os fluxos de C das parcelas sem distúrbio (F SD) e onde o preparo do solo foi conduzido (F P) são dadas por: F P = F SD + a1 e-a2t (modelo 1) e F P = a3 F SD e-a4t (modelo 2), onde t é o tempo após o preparo. Fluxos de CO2 previstos e observados relevam um bom ajuste dos resultados com coeficiente de determinação (R²) tão alto quanto 0,91. O modelo 2 produz um ajuste ligeiramente superior quando comparado com o outro modelo. A velocidade das pás da enxada rotativa foi relacionada a um aumento na quantidade de carbono lábil e nas modificações do tempo de residência médio do carbono lábil do solo após preparo. A vantagem desta metodologia é que a variabilidade temporal das emissões induzidas pelo preparo do solo pode ser descrita a partir de uma função analítica simples, que inclui a emissão da parcela sem distúrbio e um termo exponencial modulado por parâmetros dependentes do preparo e de condições ambientais onde o experimento foi conduzido.To further understand the impact of tillage on CO2 emission, the applicability of two conceptual models was tested, which describe the CO2 emission after tillage as a function of the non-tilled emission plus a correction due to the tillage disturbance. Models assume that C in readily decomposable organic matter follows a first-order reaction kinetics equation as: dCsoil (t) / dt = -k Csoil (t), and that soil C-CO2 emission is proportional to the C decay rate in soil, where Csoil(t) is the available labile soil C (g m-2) at any time (t) and k is the decay constant (time-1). Two possible assumptions were tested to determine the tilled (F T) fluxes: the decay constants (k) of labile soil C before and after tillage are different (Model 1) or not (Model 2). Accordingly, C flux relationships between non-tilled (F NT) and tilled (F T) conditions are given by: F T = F NT + a1 e-a2t (model 1) and F T = a3 F NT e-a4t (model 2), where t is time after tillage. Predicted and observed CO2 fluxes presented good agreement based on the coefficient of determination (R² = 0.91). Model comparison revealed a slightly improved statistical fit of model 2, where all C pools are assigned with the same k constant. Rotary speed was related to increases in the amount of labile C available and to changes of the mean resident labile C pool available after tillage. This approach allows describing the temporal variability of tillage-induced emissions by a simple analytical function, including non-tilled emission plus an exponential term modulated by tillage and environmentally dependent parameters

Spatial and temporal variability of soil CO2 flux in sugarcane green harvest systems

The sugarcane green harvest system, characterized by mechanized harvesting and the absence of crop burning, affects soil quality by increasing crop residue on the soil surface after harvest; thus, it contributes to improving the physical, chemical, and microbiological properties and influences the soil carbon content and CO2 flux (FCO2). This study aimed to evaluate the spatial and temporal variability of soil FCO2 in sugarcane green harvest systems. The experiment was conducted in two areas of sugarcane in São Paulo, Brazil: the first had a 5-year history of sugarcane green harvest (SG-5) and the second had a longer history of 10 years (SG-10). The temporal FCO2 were evaluated in the dry and rainy periods, and spatial variability in the dry period, and related to soil chemical and physical properties, including organic C porosity, bulk density, soil penetration resistance, mean weight diameter of soil aggregates, clay, P, S, Ca, Mg and Fe. The temporal variability indicated no differences between the dry and rainy periods in SG-10, while in SG-5 soil moisture was increased by 33 % in the rainy period. The spatial variability indicated a different pattern from the temporal one, where FCO2 in SG-10 was correlated with soil temperature, air-filled pore space, total porosity, soil moisture, and the Ca and Mg contents; in the SG-5 area, FCO2 was correlated with soil mean weight diameter of soil aggregates and the sulfur content.4

Soil management of sugarcane fields affecting CO2 fluxes

The harvesting system of green sugarcane, characterized by mechanized harvesting and no crop burning, affects soil quality by increasing the remaining straw left on the soil surface after harvesting, thus, contributing to the improvement of physical, chemical, and microbiological soil attributes, influencing CO2 fluxes. This study aimed to evaluate CO2 fluxes and their relation to soil properties in sugarcane crops under different harvesting managements: burned (B), Green harvesting for 5 years (G-5) and Green harvesting for ten years (G-10). For this, a 1 ha sampling grid with 30 points was installed in each area, all located in the Northeast of São Paulo State, Brazil. In each point, CO2 fluxes were measured and the soil was sampled to analyze the microbial biomass, physical (soil moisture and temperature, mean weight diameter, bulk density, clay, macroporosity and microporosity) and chemical characterization (pH, organic C, base saturation and P). The CO2 fluxes were divided into four quantitative criteria: high, moderate, low and very low from the Statistical Division (mean, first quartile, median and third quartile) and the other data were classified according this criterion. The Principal Component Analysis (PCA) was used to identify the main soil attributes that influence CO2 fluxes. The results showed that G-10 CO2 fluxes were 28 and 41 % higher than those in the G-5 and B treatments, respectively. The PCA analysis showed that macroporosity was the main soil attribute that influenced the high CO2 fluxes