Soil CO2 emission and its relation to soil properties in sugarcane areas under Slash-and-burn and Green harvest

SUMMARYThe soil CO 2 emission has high spatial variability because it depends strongly on soil properties. The purpose of this study was to (i) characterize the spatial variability of soil respiration and related properties, (ii) evaluate the accuracy of results of the ordinary kriging method and sequential Gaussian simulation, and (iii) evaluate the uncertainty in predicting the spatial variability of soil CO 2 emission and other properties using sequential Gaussian simulations. The study was conducted in a sugarcane area, using a regular sampling grid with 141 points, where soil CO 2 emission, soil temperature, air-filled pore space, soil organic matter and soil bulk density were evaluated. All variables showed spatial dependence structure. The soil CO 2 emission was positively correlated with organic matter (r = 0.25, p < 0.05) and air-filled pore space (r = 0.27, p < 0.01) and negatively with soil bulk density (r = -0.41, p < 0.01). However, when the estimated spatial values were considered, the air-filled pore space was the variable mainly responsible for the spatial characteristics of soil respiration, with a correlation of 0.26 (p < 0.01). For all variables, individual simulations represented the cumulative distribution functions and variograms better than ordinary kriging and E-type estimates. The greatest uncertainties in predicting soil CO 2 emission were associated with areas with the highest estimated values, which produced estimates from 0.18 to 1.85 t CO 2 ha -1 , according to the different scenarios considered. The knowledge of the uncertainties generated by the different scenarios can be used in inventories (r = 0,25, p < 0,05) e a porosidade livre de água (r = 0,27, p <0,01) e negativa com a densidade do solo (r = -0,41, p < 0,01)

Section: Resultscontrasting

confidence: 67%

“…Spatial variations in FCO 2 are primarily the result of physical, chemical and biological soil properties such as organic matter content (Søe & Buchmann, 2005), carbon stock (Panosso et al, 2011), cation exchange capacity (La Scala et al, 2000 ), microbial biomass (Søe & Buchmann, 2005) and soil mineralogy (La Scala et al, 2000).…”

Section: Introductionmentioning

confidence: 99%

Uncertainties in the prediction of spatial variability of soil CO2 emissions and related properties

Teixeira

Bicalho

Panosso

et al. 2012

“…The sugarcane green harvest system promotes soil protection by the deposition of larger quantities of straw (average 10 to 30 Mg ha -1 ) which provides higher C accumulation in the soil, leading to a positive CO 2 balance (Razafimbelo et al, 2006) as the C that would be emitted directly by burning remains in the system, it can be incorporated into the soil, favoring microbiota (Panosso et al, 2011).…”

Section: Introductionmentioning

confidence: 99%

Spatial and Temporal Variability of Soil CO2 Flux in Sugarcane Green Harvest Systems

Tavares

Souza

Scala

et al. 2016

ABSTRACT: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 CO 2 flux (FCO 2 ). This study aimed to evaluate the spatial and temporal variability of soil FCO 2 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 FCO 2 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 FCO 2 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, FCO 2 was correlated with soil mean weight diameter of soil aggregates and the sulfur content.

“…To extend these periods, it would be necessary to perform a large number of measurements (Panosso et al, 2012). According to Perez-Quezada et al (2016), this is possible, and despite the high cost of the equipment, the IRGA methodology has a better cost/benefit ratio than others.…”

Section: Rev Bras Cienc Solo 2018;42:e0160563mentioning

confidence: 99%

“…Soil CO 2 efflux (ECO 2 ), also referred to as soil respiration, is an important component of the global carbon balance, returning about 80 × 10 9 tons of C to the atmosphere each year (Raich et al, 2002). Therefore, ECO 2 can have a large influence on global atmospheric CO 2 (Ryan and Law, 2005;Zheng et al, 2014) and the increase of ECO 2 may promote disturbing climatic changes (Pinto-Junior et al, 2009;Panosso et al, 2012).…”

Section: Introductionmentioning

confidence: 99%

Soil CO2 Efflux Measurements by Alkali Absorption and Infrared Gas Analyzer in the Brazilian Semiarid Region

Ferreira

Antonino

Sampaio

et al. 2018

ABSTRACT:The CO 2 emission from the soil surface, commonly referred to as soil CO 2 efflux (ECO 2 ) or soil respiration, is the sum of processes that include root respiration and microbial activity. Measuring this evolution is important to establish sustainable land use models and to estimate global fluxes of carbon, which affect climate change. Despite its importance, few measurements have been made in areas of the semiarid Brazilian Northeast region, and most of them were made using the alkali absorption method (AA), which can underestimate ECO 2 . Measurements using AA were compared to measurements using the infrared gas analyzer method (IRGA) over ten months (in rainy and dry seasons), during the day and night, in areas of Caatinga (xeric shrubland and thorn forest) and pasture in the Agreste region of the state of Pernambuco. The ECO 2 measurements from AA varied little from night to day and throughout the year or in the rainy and dry seasons. However, those obtained from IRGA were higher in the rainy than in the dry season, but also without significant differences from day to night. The values of both methods were similar in the dry season, but in the rainy season they were higher with the IRGA. Therefore, AA seems to have little sensitivity to seasonal variations, in contrast with measurements from the IRGA, and it may underestimate soil ECO 2 when it attains higher values. This result indicates that some of the soil ECO 2 values determined in areas of the Brazilian semiarid region, and consequently annual C losses, may have been underestimated.