Luis Rodríguez-Lado

Mapping soil organic carbon content using spectroscopic and environmental data: A case study in acidic soils from NW Spain.

In this study we present a methodology to estimate and map the content of soil organic carbon (SOC) in topsoils using spectroscopic (FTIR-ATR) and environmental raster data. We determined the SOC content in 221 topsoil samples in Galicia (NW Spain) using the Walkley-Black method. FTIR-ATR spectroscopic data was measured upon the same set of samples. The Random Forest (RF) technique was used to link the measured SOC concentrations to the FTIR-ATR measurements in order to identify the relevant absorbance bands explaining most of the variability in SOC. We then used linear regression (MLR) to predict SOC concentrations from the selected FTIR-ATR bands as independent proxy. This model showed a good predictive performance (r-squared=0.88; RSME=2.14; ME=0.05; RPD=3.14), indicating that SOC can be effectively estimated from the identified spectral bands. Finally, we used Partial Least Squares (PLS) to model the spatial distribution of the predictor bands using a number of environmental raster maps (climate, land use and geology) as covariates. This new raster was used within the MLR model previously created to generalize the predictions of SOC in the whole study area. This approach shows that FTIR data can be used to map SOC while minimizing analytical costs and time efforts.

Long-Term (∼57 ka) Controls on Mercury Accumulation in the Souther Hemisphere Reconstructed Using a Peat Record from Pinheiro Mire (Minas Gerais, Brazil)

Natural archives have been used to reconstruct mercury atmospheric deposition at different spatial and temporal scales during the Holocene in the Northern Hemisphere. In this study, we present the results from a Brazilian mountain mire (Pinheiro mire, Minas Gerais, SE Brazil), extending back to ∼57 ka. The core was analyzed for mercury concentration, organic matter content, organic carbon isotopic composition, and tracers of mineral matter flux. Principal components analysis followed by principal components regression enabled us to determine the evolution of the weight of the latent processes governing the accumulation of mercury through time. We show that climate change was the main driver for the variations of mercury concentrations, either indirectly by (i) enhancing soil erosion in the mires catchment, which led to a decrease in mercury concentration due to dilution by low mercury-containing mineral matter, (ii) increasing regional dust deposition, which resulted in increased concentrations, or directly, by long-term changes in atmospheric wet deposition (arid vs humid periods). Internal peat processes (i.e., decomposition and mass loss) had a minor influence at the time scale represented by the core.

Understanding the spatial distribution of factors controlling topsoil organic carbon content in European soils

Soil Organic Carbon (SOC) constitutes the largest terrestrial carbon pool. The understanding of its dynamics and the environmental factors that influence its behaviour as sink or source of atmospheric CO2 is crucial to quantify the carbon budget at the global scale. At the European scale, most of the existing studies to account for SOC stocks are centred in the fitting of predictive model to ascertain the distribution of SOC. However, the development of methodologies for monitoring and identifying the environmental factors that control SOC storage in Europe remains a key research challenge. Here we present a modelling procedure for mapping and monitoring SOC contents that uses Visible-Near Infrared (VNIR) spectroscopic measurements and a series of environmental covariates to ascertain the key environmental processes that have a major contribution into SOC sequestration processes. Our results show that it follows a geographically non-stationary process in which the influencing environmental factors have different weights depending on the spatial location. This implies that SOC stock modelling should not rely on a single model but on a combination of different statistical models depending on the environmental characteristics of each area. A cluster classification of European soils in relation to those factors resulted in the determination of four groups for which specific models have been obtained. Differences in climate, soil pH, content of coarse fragments or land cover type are the main factors explaining the differences in SOC in topsoil from Europe. We found that climatic conditions are the main driver of SOC storage at the continental scale, but we also found that parameters like land cover type influence SOC content found at the local scales in certain areas. Our methodology developed at continental scale could be used in future research aimed to improve the predictive performance of SOC assessments at European scale.