Evaluations of soil organic carbon (SOC) stocks are often based on assigning a carbon density to each one of a number of ecosystems or soil classes considered, using data from soil profiles within these categories. A better approach, in which the use of classification methods by which extrapolation of SOC data to larger areas is avoided, can only be used if enough data are available at a sufficiently small scale. Over 190 000 SOC measurements (0–24 cm) have been made in the Flemish cropland (the Northern part of Belgium) in the 1989–2000 period. These SOC data were grouped into 3‐year periods and as means plus standard deviation per (part of) community (polygons). This large dataset was used to calculate SOC stocks and their evolution with time, without data extrapolation. Using a detailed soil map, larger spatial groups of polygons were created based on soil texture and spatial location. Linear regression analysis showed that in the entire study area, SOC stocks had decreased or at best had remained stable. In total, a yearly decrease of 354 kton OC yr−1 was calculated, which corresponds with a net CO2 emission of 1238 kton CO2 yr−1. Specific regions with a high carbon sequestration potential were identified, based on SOC losses during the 1989–2000 period and the mean 1999 SOC content, compared to the average SOC content of soils in Flanders with a similar soil texture. When restoring the SOC stocks to their 1990 level, we estimated the carbon sequestration potential of the Flemish cropland soils to be some 300 kton CO2 yr−1 at best, which corresponds to a 40‐year restoration period. In conclusion, we can say that in regions where agricultural production is very intense, carbon sequestration in the cropland may make only a very modest contribution to a country's effort to reduce greenhouse gas emissions.
-Different European Biomass Expansion Factors (BEFs) were compared for the inventory-based quantification of total aboveground and belowground biomass in forests. Therefore a qualitative analysis is performed on the biomass results obtained through the BEF approach and those from experimentally established allometric relations based on destructively sampled and fully excavated trees. Total organic carbon (OC) stock in aboveground and belowground living biomass of Flemish forests amounts to 12 Mt on average, with a significantly larger OC stock per hectare in deciduous forests compared to coniferous or mixed forest types. Total forest biomass seems to be fairly well approximated by a multiplication of the standing stock with either one of the applied BEFs. However an indication of the volume and age class for which the BEFs are established and a refined diameter-volume-biomass relation for oak trees in Europe, are required to gain more accurate results.
Total soil organic-carbon (SOC) stocks for grassland soils in Flanders (N Belgium) were determined for the Kyoto Protocol reference year 1990 and 2000 in order to investigate whether these soils have been CO 2 sinks or sources during that period. The stocks were calculated by means of detailed SOC datasets, which were available at the community scale for the whole of Flanders. The total SOC stocks for Flemish grassland soils (1 m depth) were estimated at 38 Mt SOC in 1990 and 34 Mt SOC in 2000. The loss of SOC resulted from a decrease in the SOC content of grassland soils (71%) and could also partly (29%) be explained by a decline in grassland area. Significant decreases in %SOC for the 0-6 cm depth layer were found for the 1990s for the coarser-textured soils with SOC losses ranging between -0.3% and -0.5% over the 10 y period. Specific management practices that disturb the SOC balance such as conversion to temporary grassland and a reduction of animal-manure application are hypothesized to have contributed to the observed loss of SOC stocks. We furthermore conducted an analysis of uncertainty of the 1990 and 2000 grassland SOC-stocks calculation using Monte Carlo analysis. Probability-distribution functions were determined for each of the inputs of the SOC-stock calculation, enabling us to assess the uncertainty on the 1990 and 2000 SOC stocks. The frequency distributions of these simulated stocks both closely approached lognormal distributions, and their 95%-confidence intervals ranged between 150% and 50% of the calculated mean SOC stock. The standard error on the measured decrease in SOC stocks in Flemish grassland soils during the 1990s was calculated to be 7-8 Tg SOC, which is equivalent to twice this decrease. This clearly shows that large-scale changes in SOC stocks are uncertainty-ridden, even when they are based on detailed datasets.
The different management regimes on grassland soils were examined to determine the possibilities for improved and/or changed land management of grasslands in Flanders (Belgium), with respect to article 3.4 of the Kyoto Protocol. Grassland soils were sampled for soil organic carbon (SOC) and for bulk density.For all grasslands under agricultural use, grazing and mowing + grazing led to higher SOC stocks compared with mowing, and grazing had higher SOC stocks compared with mowing + grazing. Overall, 15.1 ± 4.9 kg OC m–2 for the clayey texture, 9.8 ± 3.0 kg OC m–2 for the silty texture, and 11.8 ± 3.8 kg OC m–2 for the sandy texture were found for grassland under agricultural use to a depth of 60 cm. For seminatural grasslands, different results were found. For both the clayey and silty texture, mowing and mowing + grazing led to higher SOC stocks compared with grazing. The clayey texture had a mean stock of 15.1 ± 6.6, the silty texture of 10.9 ± 3.0, and the sandy texture of 12.1 ± 3.9 kg OC m–2 (0–60 cm). Lower bulk densities were found under grazed agricultural grassland compared with mown grassland but for seminatural grassland, no clear trends for the bulk density were found. The best management option for maintaining or enhancing SOC stocks in agricultural grassland soils may be permanent grazed grassland. For seminatural grassland, no clear conclusions could be made. The water status of the sampled mown fields was influencing the results for the clayey texture.Overall, the mean SOC stock was decreasing in the order clay > sand > silt. The higher mean SOC concentrations found for the sandy texture, compared to the finer silty texture, may be explained by the historical land use of these soils.
SU MMARYFor the determination of soil organic carbon (OC) concentrations, the availability of a fast, low-cost analysis method is required. The aim of the present study was to evaluate the possibilities of near infrared reflectance spectroscopy (NIRS) to build a spectral database and to develop calibrations for the prediction of organic carbon concentrations in grassland soils. NIRS spectra of 1626 soil samples from different grasslands (both agricultural and natural) were collected between 1100 and 2500 nm. NIRS calibrations were developed with modified partial least square regression and tested with independent validation samples. The best equations were obtained with the first derivative of the spectra without scatter corrections. For the global calibration, containing the samples of all origins, the standard errors of calibration (SEC) and of prediction (SEP) were respectively 3 . 70 g OC/kg dry soil (R 2 =0 . 89) and 3 . 95 g OC/kg dry soil (R 2 =0 . 88). The ratio of the standard deviation of the reference validation data to the SEP (RPD), indicating the performance of the calibration, was 2 . 9. Dividing the samples into groups according to their practice (agricultural or natural grassland), improved SEP by 5 . 8 and 7 . 7 %, respectively. Dividing the samples into texture groups (clay, silt, sand) improved SEP for agricultural grassland by, on average, 7 . 4 % and for natural grassland by 16 . 2 %.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.