Abstract. Future global change is likely to give rise to novel combinations of the factors which enhance or inhibit soil erosion by water. Thus, there is a need for erosion models, necessarily process-focused ones, which are able to reliably represent the rates and extents of soil erosion under unprecedented circumstances. The process-focused cellular automaton erosion model RillGrow is, given initial soil surface microtopography for a plot-sized area, able to predict the emergent patterns produced by runoff and erosion. This study explores the use of structure-from-motion photogrammetry as a means to calibrate and evaluate this model by capturing detailed, time-lapsed data for soil surface height changes during erosion events. Temporally high-resolution monitoring capabilities (i.e. 3D models of elevation change at 0.1 Hz frequency) permit the evaluation of erosion models in terms of the sequence of the formation of erosional features. Here, multiple objective functions using three different spatio-temporal averaging approaches are assessed for their suitability in calibrating and evaluating the model's output. We used two sets of data from field- and laboratory-based rainfall simulation experiments lasting 90 and 30 min, respectively. By integrating 10 different calibration metrics, the outputs of 2000 and 2400 RillGrow runs for, respectively, the field and laboratory experiments were analysed. No single model run was able to adequately replicate all aspects of either the field or the laboratory experiments. The multiple objective function approaches highlight different aspects of model performance, indicating that no single objective function can capture the full complexity of erosion processes. They also highlight different strengths and weaknesses of the model. Depending on the focus of the evaluation, an ensemble of objective functions may not always be necessary. These results underscore the need for more nuanced evaluation of erosion models, e.g. by incorporating spatial-pattern comparison techniques to provide a deeper understanding of the model's capabilities. Such calibrations are an essential complement to the development of erosion models which are able to forecast the impacts of future global change. For the first time, we use data with a very high spatio-temporal resolution to calibrate a soil erosion model.

Abstract. Soil respiration (Rs) is an important carbon flux in terrestrial ecosystems, and knowledge about this CO2 release process and the drivers involved is a key topic in the context of global change. However, temporal and spatial variability has not been studied extensively in semi-arid systems such as olive groves. In this study, we show a full year of continuous measurements of Rs with six automatic chambers in a fertigated olive grove with bare soil in the Mediterranean accompanied by modeled ecosystem respiration (Reco) estimated by decomposing net ecosystem exchange (NEE) measured using the eddy covariance (EC) technique. To study spatial variability, the automatic chambers were distributed equally under the canopy (Rs Under-Tree) and in the center of the alley (Rs Alley), and the gradient of Rs between both locations was measured in several manual campaigns in addition to angular changes about the olive trees. The results indicate that Rs Under-Tree was 3 times higher than Rs Alley in the annual computations. Higher Rs was found on the southern face, and an exponential decay of Rs was observed until the alley's center was reached. These spatial changes were used to weigh and project Rs onto the ecosystem scale, whose annual balance was 1.6–2.3 times higher than the Reco estimated using EC-derived models. Rs Under-Tree represented 39 % of the Rs of the olive grove. We found values of Q10<1 in the vicinity of the olive tree in the warm period. Outbursts of CO2 emissions associated with precipitation events were detected, especially in the alley, during dry periods and after extended periods without rain, but they were not accurately detected by EC-derived respiration models. We point out an interaction between several effects that vary in time, that are different under the canopy than in the alleys, and that the accepted models for estimating Q10 and Reco do not consider. These results show high spatial and temporal heterogeneity in soil respiration and the factors involved, which must be considered in future works in semi-arid agroecosystems.

Abstract. Substantial input of exogenous organic matter (EOM) may be required to offset the projected decline in soil organic carbon (SOC) stocks in croplands caused by global warming. However, information on the effectivity of the EOM application dose in preserving SOC stocks is surprisingly limited. Therefore, we set up a 90 d incubation experiment with large soil volumes (sandy loam and silt loam) to compare the mineralization of EOM (13C-labelled ryegrass) and SOC as a function of three EOM application doses (0.5, 1.5, and 5 g dry matter kg−1 soil). The percentage of mineralized EOM was expected to increase linearly with a higher EOM dose in sandy loam soil and to level off in silt loam soil due to the limited O2 supply in order to maintain aerobic microbial activity. In the sandy loam soil, the percentage of mineralized EOM was not affected by EOM dose, while SOC mineralization increased proportionally with an increasing EOM dose (+49.6 mg C g−1 EOM). Likewise, the formation of microbial biomass carbon was proportional to EOM dose, suggesting no reduction in microbial growth efficiency at a higher C concentration. In the silt loam soil, a decreasing tendency in the percentage of mineralized EOM was apparent but could not be confirmed statistically. We therefore conclude that, as in the sandy loam, the proportion of EOM mineralization was not affected with an increasing EOM dose, while SOC mineralization increased at a higher rate than in the sandy loam soil (+117.2 mg C g−1 EOM). Consistently with this lack of response in the proportion of EOM mineralization to EOM dose, soil EH did not decrease with an increasing EOM dose, indicating no O2 limitations. In both soils, an increasing EOM dose possibly supplied energy for microbial growth and enzyme production, which, in turn, stimulated mineralization of native SOC (i.e. co-metabolism). The observed stimulation of soil macroporosity at higher EOM doses in the silt loam soil might have contributed to sustaining the aerobic conditions required for SOC mineralization. In sum, this experiment and our previous research suggest that EOM mineralization is mostly independent of EOM dose, but EOM dose modulates the mineralization of native SOC. Provisional C balances compared to unamended controls indicated that, at low doses, less C remained than when EOM was added at normal or high doses in sandy loam soil, while no effect was found in silt loam soil. These findings tentatively indicate that using larger EOM doses could help preserve more added EOM-C, but longer-term confirmation in the field will firstly be required before we can draw any conclusion for soil C management.

Abstract. Fertilised soils are a significant source of nitrous oxide (N2O), a highly active greenhouse gas and a stratospheric ozone depleter. Nitrogen (N) fertilisers, while boosting crop yield, also lead to N2O emissions into the atmosphere, impacting global warming. We investigated relationships between mineral N fertilisation rates and additional manure amendment with different crop types through the analysis of abundances of N cycle functional genes, soil N2O and N2 emissions, nitrogen use efficiency (NUE), soil physicochemical analysis and biomass production. Our study indicates that N2O emissions are predominantly dependent on the mineral N fertilisation rate and enhance with an increased mineral N fertilisation rate. Crop type also has a significant impact on soil N2O emissions. Higher N2O emissions were attained with the application of manure in comparison to mineral fertilisation. Manure amendment also increased the number of N cycle genes that are significant in the variations of N2O. The study indicates that N2O emissions were mainly related to nitrification in the soil. Quantification of nitrogen cycle functional genes also showed the potential role of denitrification, comammox (complete ammonia oxidation) and dissimilatory nitrate reduction to ammonium (DNRA) processes as a source of N2O. Our study did not find soil moisture to be significantly linked to N2O emissions. The results of the study provide evidence that, for wheat, a fertilisation rate of 80 kg N ha−1 is closest to the optimal rate for balancing biomass yield and N2O emissions and achieving a high NUE. Sorghum showed good potential for cultivation in temperate climates, as it showed a similar biomass yield compared to the other crop types and fertilisation rates but maintained low N2O emissions and N losses in a mineral N fertilisation rate of 80 kg N ha−1.

Abstract. The concept of soil organic carbon (SOC) saturation emerged a bit more than 2 decades ago as our mechanistic understanding of SOC stabilization increased. Recently, the further testing of the concept across a wide range of soil types and environments has led some people to challenge the fundamentals of soil C saturation. Here, we argue that, to test this concept, one should pay attention to six fundamental principles or “rights” (R's): the right measures, the right units, the right dispersive energy and application, the right soil type, the right clay type, and the right saturation level. Once we take care of those six rights across studies, we find a maximum of C stabilized by minerals and estimate based on current data available that this maximum stabilization is around 82 ± 4 g C kg−1 silt + clay for 2 : 1-clay-dominated soils while most likely being only around 46 ± 4 g C kg−1 silt + clay for 1 : 1-clay-dominated soils. These estimates can be further improved using more data, especially for different clay types across varying environmental conditions. However, the bigger challenge is a matter of which C sequestration strategies to implement and how to implement them in order to effectively reach this 82/46 g C kg−1 silt + clay in soils across the globe.

Abstract. Conventional laboratory analysis of soil properties is often expensive and requires much time if various soil properties are to be measured. Visual and near-infrared (vis–NIR) spectroscopy offers a complementary and cost-efficient way to gain a wide variety of soil information at high spatial and temporal resolutions. Yet, applying vis–NIR spectroscopy requires confidence in the prediction accuracy of the infrared models. In this study, we used soil data from six agricultural fields in eastern Switzerland and calibrated (i) field-specific (local) models and (ii) general models (combining all fields) for soil organic carbon (SOC), permanganate oxidizable carbon (POXC), total nitrogen (N), total carbon (C) and pH using partial least-squares regression. The 30 local models showed a ratio of performance to deviation (RPD) between 1.14 and 5.27, and the root mean square errors (RMSE) were between 1.07 and 2.43 g kg−1 for SOC, between 0.03 and 0.07 g kg−1 for POXC, between 0.09 and 0.14 g kg−1 for total N, between 1.29 and 2.63 g kg−1 for total C, and between 0.04 and 0.19 for pH. Two fields with high carbonate content and poor correlation between the target properties were responsible for six local models with a low performance (RPD < 2). Analysis of variable importance in projection, as well as of correlations between spectral variables and target soil properties, confirmed that high carbonate content masked absorption features for SOC. Field sites with low carbonate content can be combined with general models with only a limited loss in prediction accuracy compared to the field-specific models. On the other hand, for fields with high carbonate contents, the prediction accuracy substantially decreased in general models. Whether the combination of soils with high carbonate contents in one prediction model leads to satisfying prediction accuracies needs further investigation.

Abstract. Woody-plant encroachment into grasslands and savannas has been globally widespread during the past century, likely driven by interactions between grazing, fire suppression, rising atmospheric CO2, and climate change. In the southernmost US Great Plains, Ashe juniper and live oak have increased in abundance. To evaluate potential interactions between this vegetation change and the underlying soil parent material on ecosystem biogeochemistry, we quantified soil organic carbon (SOC), total nitrogen (TN), total phosphorus (TP), and δ13C of SOC in soils obtained from trenches passing through grassland, juniper, and oak patches on soils lying atop the respective Edwards and Buda limestone formations in central Texas. Soils on the Edwards formation are more shallow and have more rock outcropping than those on Buda. The δ13C values of SOC under grasslands was −19 ‰, whereas those under woody patches were −21 ‰ to −24 ‰, indicating that wooded areas were relatively recent components of the landscape. Compared with grasslands, areas now dominated by juniper or oak had elevated SOC, TN, and TP storage in soils lying atop Edwards limestone. In Buda soils, only oak patches had increased SOC, TN, and TP storage compared with grasslands. Woody encroachment effects on soil nutrients were higher in soils on the Edwards formation, perhaps because root and litter inputs were more concentrated in the relatively shallow layer of soil atop the Edwards bedrock. Our findings suggest that geological factors should be considered when predicting nutrient store responses in savannas following vegetation change. Given that woody encroachment is occurring globally, our results have important implications for the management and conservation of these ecosystems. The potential interactive effects between vegetation change and soil parent material on C, N, and P storage warrant attention in future studies aimed at understanding and modeling the global consequences of woody encroachment.

Abstract. An assessment of the soil and bedrock thermal structure of the Sierra de Guadarrama, in central Spain, is provided using subsurface and ground surface temperature data coming from four deep (20 m) monitoring profiles belonging to the Guadarrama Monitoring Network (GuMNet) and two shallow profiles (1 m) from the Spanish Meteorology Service (Agencia Estatal de Meteorología, AEMET) covering the time spans of 2015–2021 and 1989–2018, respectively. An evaluation of air and ground surface temperature coupling showed that soil insulation due to snow cover is the main source of seasonal decoupling, being especially relevant in winter at high-altitude sites. Temperature propagation in the subsurface was characterized by assuming a heat conductive regime by considering apparent thermal diffusivity values derived from the amplitude attenuation and phase shift of the annual cycle with depth. This methodology was further extended to consider the attenuation of all harmonics in the spectral domain, which allowed for analysis of thermal diffusivity from high-frequency changes in the soil near the surface at short timescales. For the deep profiles, the apparent thermal diffusivity ranges from 1 to 1.3×10-6 m2 s−1, which is consistent with values for gneiss and granite, the major bedrock components in the Sierra de Guadarrama. However, thermal diffusivity is lower and more heterogeneous in the soil layers close to the surface (0.4–0.8×10-6 m2 s−1). An increase in diffusivity with depth was observed that was generally larger in the soil–bedrock transition at 4–8 m depth. The outcomes are relevant for the understanding of soil thermodynamics in relation to other soil properties. Results with the spectral method suggest that changes in near-surface thermal diffusivity are related to changes in soil moisture content, which makes it a potential tool to gain information about soil drought and water resource availability from soil temperature data.

Abstract. Soil organic matter (SOM) plays an important role in the global carbon cycle, especially in alpine ecosystems. However, ongoing forest expansion in high-elevation systems potentially alters SOM storage through changes in organic matter (OM) inputs and microclimate. In this study, we investigated the effects of an Picea abies L. afforestation chrono-sequence (0 to 130 years) of a former subalpine pasture in Switzerland on soil organic carbon (SOC) stocks and SOM dynamics. We found that SOC stocks remained constant throughout the chrono-sequence, with comparable SOC stocks in the mineral soils after afforestation and previous pasture (SOC forest40 = 11.6 ± 1.1 kg m−2, SOC forest130 = 11.0 ± 0.3 kg m−2 and SOC pasture = 11.5 ± 0.5 kg m−2). However, including the additional carbon of the organic horizons in the forest, reaching up to 1.7 kg m−2 in the 55-year old forest, resulted in an increase in the overall SOC stocks following afforestation. We found that the soil C:N ratio in the mineral soil increased in the topsoil (0–5 cm) with increasing forest stand age, from 11.9 ± 1.3 in the pasture to 14.3 ± 1.8 in the 130-year old forest. In turn, we observed a decrease in the soil C:N ratio with increasing depth in all forest stand ages. This suggests that litter-derived organic matter (C:N from 35.1 ± 1.9 to 42.4 ± 10.8) is likely to be incorporated and translocated from the organic horizon to the mineral topsoil (0–10 cm) of the profiles. Due to the high root C:N ratio (pasture 63.5 ± 2.8 and forests between 54.7 ± 3.9 and 61.2 ± 2.9), particulate root-derived organic matter seems to have a rather small effect on forest soil C:N ratios, as well as on SOC accumulation in the mineral soil. These results suggest that, although afforestation does not change the SOC stock in the mineral soil, there is an apparent alteration in the SOM dynamics through changes in the litter composition caused by the vegetation shift. We conclude that, at our study site, spruce afforestation on a former subalpine pasture does not change the total SOC stock and that, consequently, there is no additional SOC sequestration on a decadal to centennial scale.

Abstract. Quantifying soil redistribution rates is a global challenge addressed with direct sediment measurements (e.g. traps), models, and isotopic, geochemical, and radionuclide tracers. The isotope of plutonium, namely 239+240Pu, is a relatively new soil redistribution tracer in this challenge. Direct validation of 239+240Pu as a soil redistribution tracer is, however, still missing. We used a unique sediment yield time series in southern Italy, reaching back to the initial fallout of 239+240Pu to verify 239+240Pu as a soil redistribution tracer. Distributed soil samples (n=55) were collected in the catchment, and at undisturbed reference sites (n=22), 239+240Pu was extracted, measured with inductively coupled plasma mass spectrometry (ICP-MS), and converted to soil redistribution rates. Finally, we used a generalized additive model (GAM) to regionalize soil redistribution estimates for the catchment. For the catchment sites, mean 239+240Pu inventories were significantly reduced (16.8 ± 10.2 Bq m−2) compared to the reference inventory (40.5 ± 3.5 Bq m−2), indicating the dominance of erosion. Converting these inventory losses into soil erosion rates resulted in an average soil loss of 22.2 ± SD 7.2 t ha−1 yr−1. The uncertainties of the approach stemmed mainly from the high measurement uncertainties of some low-activity samples where samples have been bulked over depth. Therefore, we recommend taking incremental soil samples and extracting larger soil volumes (∼ 20 g). The geographic coordinates and the flow accumulation best described the spatial pattern of erosion rates in the GAM model. Using those predictors to upscale Pu-derived soil redistribution rates for the entire catchment resulted in an average on-site loss of 20.7 t ha−1 yr−1, which corresponds very well to the long-term average sediment yield of 18.7 t ha−1 yr−1 measured at the catchment outlet and to 137Cs-derived soil redistribution rates. Overall, this comparison of Pu-derived soil redistribution rates with measured sediment yield data validates 239+240Pu as a suitable retrospective soil redistribution tracer.