Our findings indicate the importance of paleoclimatic information to improve quantitative predictions of global soil C stocks.
Quantify direct and indirect relationships between soil microbial community properties (potential basal respiration, microbial biomass) and abiotic factors (soil, climate) in three major land\uffe2\uff80\uff90cover types.
LocationEurope.
Time period2018.
Major taxa studiedMicrobial community (fungi and bacteria).
MethodsWe collected 881 soil samples from across Europe in the framework of the Land Use/Land Cover Area Frame Survey (LUCAS). We measured potential soil basal respiration at 20\uffc2\uffa0\uffc2\uffbaC and microbial biomass (substrate\uffe2\uff80\uff90induced respiration) using an O2\uffe2\uff80\uff90microcompensation apparatus. Soil and climate data were obtained from the same LUCAS survey and online databases. Structural equation models (SEMs) were used to quantify relationships between variables, and equations extracted from SEMs were used to create predictive maps. Fatty acid methyl esters were measured in a subset of samples to distinguish fungal from bacterial biomass.
ResultsSoil microbial properties in croplands were more heavily affected by climate variables than those in forests. Potential soil basal respiration and microbial biomass were correlated in forests but decoupled in grasslands and croplands, where microbial biomass depended on soil carbon. Forests had a higher ratio of fungi to bacteria than grasslands or croplands.
Main conclusionsSoil microbial communities in grasslands and croplands are likely carbon\uffe2\uff80\uff90limited in comparison with those in forests, and forests have a higher dominance of fungi indicating differences in microbial community composition. Notably, the often already\uffe2\uff80\uff90degraded soils of croplands could be more vulnerable to climate change than more natural soils. The provided maps show potentially vulnerable areas that should be explicitly accounted for in future management plans to protect soil carbon and slow the increasing vulnerability of European soils to climate change.
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In agronomy, soil organic carbon (SOC) content is important for the development and growth of crops. From an environmental monitoring viewpoint, SOC sequestration is essential for mitigating the emission of greenhouse gases into the atmosphere. SOC dynamics in cropland soils should be further studied through various approaches including remote sensing. In order to predict SOC content over croplands in southwestern France (area of 22,177 km\u00b2), this study addresses (i) the influence of the dates on which Sentinel-2 (S2) images were acquired in the springs of 2017\u20132018 as well as the influence of the soil sampling period of a set of samples collected between 2005 and 2018, (ii) the use of soil moisture products (SMPs) derived from Sentinel-1/2 satellites to analyze the influence of surface soil moisture on model performance when included as a covariate, and (iii) whether the spatial distribution of SOC as mapped using S2 is related to terrain-derived attributes. The influences of S2 image dates and soil sampling periods were analyzed for bare topsoil. The dates of the S2 images with the best performance (RPD \u2265 1.7) were 6 April and 26 May 2017, using soil samples collected between 2016 and 2018. The soil sampling dates were also analyzed using SMP values. Soil moisture values were extracted for each sample and integrated into partial least squares regression (PLSR) models. The use of soil moisture as a covariate had no effect on the prediction performance of the models; however, SMP values were used to select the driest dates, effectively mapping topsoil organic carbon. S2 was able to predict high SOC contents in the specific soil types located on the old terraces (mesas) shaped by rivers flowing from the southwestern Pyr\u00e9n\u00e9es.
Our findings indicate the importance of paleoclimatic information to improve quantitative predictions of global soil C stocks.