Search

In the last decades, soils and their agricultural management have received great scientific and political attention due to their potential to act as a sink of atmospheric carbon dioxide (CO2). Agricultural management has strong potential to accelerate soil redistribution, and, therefore, it is questioned if soil redistribution processes affect this potential CO2 sink function. Most studies analysing the effect of soil redistribution upon soil organic carbon (SOC) dynamics focus on water erosion and analyse only relatively small catchments and relatively short time spans of several years to decades. The aim of this study is to widen this perspective by including tillage erosion as another important driver of soil redistribution and by performing a model-based analysis in a 200 km2 sized arable region of northeastern Germany for the period since the conversion from forest to arable land (approx. 1000 years ago). The spatially explicit soil redistribution and carbon (C) turnover model SPEROS-C was applied to simulate lateral soil and SOC redistribution and SOC turnover. The model parameterisation uncertainty was estimated by simulating different realisations of the development of agricultural management over the past millennium. The results indicate that, in young moraine areas, which are relatively dry but have been intensively used for agriculture for centuries, SOC patterns and dynamics are substantially affected by tillage-induced soil redistribution processes. To understand the landscape-scale effect of these redistribution processes on SOC dynamics, it is essential to account for long-term changes following land conversion as typical soil-erosion-induced processes, e.g. dynamic replacement, only take place after former forest soils reach a new equilibrium following conversion. Overall, it was estimated that, after 1000 years of arable land use, SOC redistribution by tillage and water results in a current-day landscape-scale C sink of up to 0.66 ‰ yr−1 of the current SOC stocks.

Soils are generally accepted as sinks for microplastics (MPs) but at the same time might be an MP source for inland waters. However, little is known regarding the potential MP delivery from soils to aquatic systems via surface runoff and erosion. This study provides, for the first time, an estimate of the extent of soil-erosion-induced MP delivery from an arable-dominated mesoscale catchment (390 km2) to its river network within a typical arable region of southern Germany. To do this, a soil erosion model was used and combined with the potential particular MP load of arable land from different sources (sewage sludge, compost, atmospheric deposition, and tyre wear) from 1950 onwards. The modelling resulted in an annual mean MP flux into the stream network of 6.33 kg MP a−1 in 2020, which was dominated by tyre wear (80 %). Overall, 0.11 %–0.17 % of the MPs applied to arable soils between 1950 and 2020 were transported into the stream network. In terms of mass, this small proportion was in the same range as the MP inputs from wastewater treatment plants within the test catchment. More MP (0.5 %–1 % of input between 1950 and 2020) was deposited in the grassland areas along the stream network, and this could be an additional source of MP during flood events. Most (5 % of the MP applied between 1950 and 2020) of the MP translocated by tillage and water erosion was buried under the plough layer. Thus, the main part of the MP added to arable land remained in the topsoil and is available for long-term soil erosion. This can be illustrated based on a “stop MP input in 2020” scenario, indicating that MP delivery to the stream network until 2100 would only be reduced by 14 %. Overall, arable land at risk of soil erosion represents a long-term MP sink but also a long-term MP source for inland waters.

Soil erosion rates on arable land frequently exceed the pace at which new soil is formed. This imbalance leads to soil thinning (i.e. truncation), whereby subsoil horizons and their underlying parent material become progressively closer to the land surface. As soil erosion is a selective process and subsurface horizons often have contrasting properties to the original topsoil, truncation-induced changes to soil properties might affect erosion rates and runoff formation through a soil erosion feedback system. However, the potential interactions between soil erosion and soil truncation are poorly understood due to a lack of empirical data and the neglection of long-term erodibility dynamics in erosion simulation models. Here, we present a novel model-based exploration of the soil erosion feedback system over a period of 500 years using measured soil properties from a diversified database of 265 agricultural soil profiles in the UK. For this, we adapted the Modified Morgan–Morgan–Finney model (MMMF) to perform a modelling experiment in which topography, climate, land cover, and crop management parameters were held constant throughout the simulation period. As selective soil erosion processes removed topsoil layers, the model gradually mixed subsurface soil horizons into a 0.2 m plough layer and updated soil properties using mass-balance mixing models. Further, we estimated the uncertainty in model simulations with a forward error assessment. We found that modelled erosion rates in 99 % of the soil profiles were sensitive to truncation-induced changes in soil properties. The soil losses in all except one of the truncation-sensitive profiles displayed a decelerating trend, which depicted an exponential decay in erosion rates over the simulation period. This was largely explained by decreasing silt contents in the soil surface due to selective removal of this more erodible particle size fraction and the presence of clayey or sandy substrata. Moreover, the soil profiles displayed an increased residual stone cover, which armoured the land surface and reduced soil detachment. Contrastingly, the soils with siltier subsurface horizons continuously replenished the plough layer with readily erodible material, which prevented the decline of soil loss rates over time. Although our results are limited by the edaphoclimatic conditions represented in our data, as by our modelling assumptions, we have demonstrated how modelled soil losses can be sensitive to erosion-induced changes in soil properties. These findings are likely to affect how we calculate soil lifespans and make long-term projections of land degradation.

The accelerated sediment supply from agricultural soils to riverine and lacustrine environments leads to negative off-site consequences. In particular, the sediment connectivity from agricultural land to surface waters is strongly affected by landscape patchiness and the linear structures that separate field parcels (e.g. roads, tracks, hedges, and grass buffer strips). Understanding the interactions between these structures and sediment transfer is therefore crucial for minimising off-site erosion impacts. Although soil erosion models can be used to understand lateral sediment transport patterns, model-based connectivity assessments are hindered by the uncertainty in model structures and input data. Specifically, the representation of linear landscape features in numerical soil redistribution models is often compromised by the spatial resolution of the input data and the quality of the process descriptions. Here we adapted the Water and Tillage Erosion Model and Sediment Delivery Model (WaTEM/SEDEM) using high-resolution spatial data (2 m × 2 m) to analyse the sediment connectivity in a very patchy mesoscale catchment (73 km2) of the Swiss Plateau. We used a global sensitivity analysis to explore model structural assumptions about how linear landscape features (dis)connect the sediment cascade, which allowed us to investigate the uncertainty in the model structure. Furthermore, we compared model simulations of hillslope sediment yields from five subcatchments to tributary sediment loads, which were calculated with long-term water discharge and suspended sediment measurements. The sensitivity analysis revealed that the assumptions about how the road network (dis)connects the sediment transfer from field blocks to water courses had a much higher impact on modelled sediment yields than the uncertainty in model parameters. Moreover, model simulations showed a higher agreement with tributary sediment loads when the road network was assumed to directly connect sediments from hillslopes to water courses. Our results ultimately illustrate how a high-density road network combined with an effective drainage system increases sediment connectivity from hillslopes to surface waters in agricultural landscapes. This further highlights the importance of considering linear landscape features and model structural uncertainty in soil erosion and sediment connectivity research.

Heterotrophic soil respiration is an important component of the global terrestrial carbon (C) cycle, driven by environmental factors acting from local to continental scales. For tropical Africa, these factors and their interactions remain largely unknown. Here, using samples collected along topographic and geochemical gradients in the East African Rift Valley, we study how soil chemistry and fertility drive soil respiration of soils developed from different parent materials even after many millennia of weathering. To address the drivers of soil respiration, we incubated soils from three regions with contrasting geochemistry (mafic, felsic and mixed sediment) sampled along slope gradients. For three soil depths, we measured the potential maximum heterotrophic respiration under stable environmental conditions and the radiocarbon content (Δ14C) of the bulk soil and respired CO2. Our study shows that soil fertility conditions are the main determinant of C stability in tropical forest soils. We found that soil microorganisms were able to mineralize soil C from a variety of sources and with variable C quality under laboratory conditions representative of tropical topsoil. However, in the presence of organic carbon sources of poor quality or the presence of strong mineral-related C stabilization, microorganisms tend to discriminate against these energy sources in favour of more accessible forms of soil organic matter, resulting in a slower rate of C cycling. Furthermore, despite similarities in climate and vegetation, soil respiration showed distinct patterns with soil depth and parent material geochemistry. The topographic origin of our samples was not a main determinant of the observed respiration rates and Δ14C. In situ, however, soil hydrological conditions likely influence soil C stability by inhibiting decomposition in valley subsoils. Our results demonstrate that, even in deeply weathered tropical soils, parent material has a long-lasting effect on soil chemistry that can influence and control microbial activity, the size of subsoil C stocks and the turnover of C in soil. Soil parent material and its control on soil chemistry need to be taken into account to understand and predict C stabilization and rates of C cycling in tropical forest soils.

Stabilization of soil organic carbon (SOC) against microbial decomposition depends on several soil properties, including the soil weathering stage and the mineralogy of parent material. As such, tropical SOC stabilization mechanisms likely differ from those in temperate soils due to contrasting soil development. To better understand these mechanisms, we investigated SOC dynamics at three soil depths under pristine tropical African mountain forest along a geochemical gradient from mafic to felsic and a topographic gradient covering plateau, slope and valley positions. To do so, we conducted a series of soil C fractionation experiments in combination with an analysis of the geochemical composition of soil and a sequential extraction of pedogenic oxides. Relationships between our target and predicting variables were investigated using a combination of regression analyses and dimension reduction. Here, we show that reactive secondary mineral phases drive SOC properties and stabilization mechanisms together with, and sometimes more strongly than, other mechanisms such as aggregation or C stabilization by clay content. Key mineral stabilization mechanisms for SOC were strongly related to soil geochemistry, differing across the study regions. These findings were independent of topography in the absence of detectable erosion processes. Instead, fluvial dynamics and changes in soil moisture conditions had a secondary control on SOC dynamics in valley positions, leading to higher SOC stocks there than at the non-valley positions. At several sites, we also detected fossil organic carbon (FOC), which is characterized by high C/N ratios and depletion of N. FOC constitutes up to 52.0 ± 13.2 % of total SOC stock in the C-depleted subsoil. Interestingly, total SOC stocks for these soils did not exceed those of sites without FOC. Additionally, FOC decreased strongly towards more shallow soil depths, indicating decomposability of FOC by microbial communities under more fertile conditions. Regression models, considering depth intervals of 0–10, 30–40 and 60–70 cm, showed that variables affiliated with soil weathering, parent material geochemistry and soil fertility, together with soil depth, explained up to 75 % of the variability of SOC stocks and Δ14C. Furthermore, the same variables explain 44 % of the variability in the relative abundance of C associated with microaggregates vs. free-silt- and-clay-associated C fractions. However, geochemical variables gained or retained importance for explaining SOC target variables when controlling for soil depth. We conclude that despite long-lasting weathering, geochemical properties of soil parent material leave a footprint in tropical soils that affects SOC stocks and mineral-related C stabilization mechanisms. While identified stabilization mechanisms and controls are similar to less weathered soils in other climate zones, their relative importance is markedly different in the tropical soils investigated.

The African Tropics are hotspots of modern-day land use change and are, at the same time, of great relevance for the cycling of carbon (C) and nutrients between plants, soils, and the atmosphere. However, the consequences of land conversion on biogeochemical cycles are still largely unknown as they are not studied in a landscape context that defines the geomorphic, geochemical, and pedological framework in which biological processes take place. Thus, the response of tropical soils to disturbance by erosion and land conversion is one of the great uncertainties in assessing the carrying capacity of tropical landscapes to grow food for future generations and in predicting greenhouse gas fluxes from soils to the atmosphere and, hence, future earth system dynamics. Here we describe version 1.0 of an open-access database created as part of the project “Tropical soil organic carbon dynamics along erosional disturbance gradients in relation to variability in soil geochemistry and land use” (TropSOC). TropSOC v1.0 (Doetterl et al., 2021, https://doi.org/10.5880/fidgeo.2021.009) contains spatially and temporally explicit data on soil, vegetation, environmental properties, and land management collected from 136 pristine tropical forest and cropland plots between 2017 and 2020 as part of monitoring and sampling campaigns in the eastern Congo Basin and the East African Rift Valley system. The results of several laboratory experiments focusing on soil microbial activity, C cycling, and C stabilization in soils complement the dataset to deliver one of the first landscape-scale datasets to study the linkages and feedbacks between geology, geomorphology, and pedogenesis as controls on biogeochemical cycles in a variety of natural and managed systems in the African Tropics. The hierarchical and interdisciplinary structure of the TropSOC database allows linking of a wide range of parameters and observations on soil and vegetation dynamics along with other supporting information that may also be measured at one or more levels of the hierarchy. TropSOC's data mark a significant contribution to improve our understanding of the fate of biogeochemical cycles in dynamic and diverse tropical African (agro-)ecosystems. TropSOC v1.0 can be accessed through the Supplement provided as part of this paper or as a separate download via the websites of the Congo Biogeochemistry Observatory and GFZ Data Services where version updates to the database will be provided as the project develops.

Due to the rapidly growing population in tropical Africa, a substantial rise in food demand is predicted in upcoming decades, which will result in higher pressure on soil resources. However, there is limited knowledge on soil redistribution dynamics following land conversion into arable land in tropical Africa that is partly caused by infrastructure limitations for long-term landscape-scale monitoring. In this study, fallout radionuclides 239+240Pu are used to assess soil redistribution along topographic gradients at two cropland sites and at three nearby pristine forest sites located in the DR Congo, Uganda and Rwanda. In the study area, a 239+240Pu baseline inventory is found that is higher than typically expected for tropical regions (mean forest inventory 41 Bq m−2). Pristine forests show no indication of soil redistribution based on 239+240Pu along topographical gradients. In contrast, soil erosion and sedimentation on cropland reached up to 37 cm (81 Mg ha−1 yr−1) and 40 cm (87 Mg ha−1 yr−1) within the last 55 years, respectively. Cropland sites show high intra-slope variability with locations showing severe soil erosion located in direct proximity to sedimentation sites. This study shows the applicability of a valuable method to assess tropical soil redistribution and provides insight into soil degradation rates and patterns in one of the most socio-economically and ecologically vulnerable regions of the world.

Soil macronutrient availability is one of the abiotic controls that alters the exchange of greenhouse gases (GHGs) between the soil and the atmosphere in tropical forests. However, evidence on the macronutrient regulation of soil GHG fluxes from central African tropical forests is still lacking, limiting our understanding of how these biomes could respond to potential future increases in nitrogen (N) and phosphorus (P) deposition. The aim of this study was to disentangle the regulation effect of soil nutrients on soil GHG fluxes from a Ugandan tropical forest reserve in the context of increasing N and P deposition. Therefore, a large-scale nutrient manipulation experiment (NME), based on 40 m×40 m plots with different nutrient addition treatments (N, P, N + P, and control), was established in the Budongo Central Forest Reserve. Soil carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O) fluxes were measured monthly, using permanently installed static chambers, for 14 months. Total soil CO2 fluxes were partitioned into autotrophic and heterotrophic components through a root trenching treatment. In addition, soil temperature, soil water content, and nitrates were measured in parallel to GHG fluxes. N addition (N and N + P) resulted in significantly higher N2O fluxes in the transitory phase (0–28 d after fertilization; p) because N fertilization likely increased soil N beyond the microbial immobilization and plant nutritional demands, leaving the excess to be nitrified or denitrified. Prolonged N fertilization, however, did not elicit a significant response in background (measured more than 28 d after fertilization) N2O fluxes. P fertilization marginally and significantly increased transitory (p=0.05) and background (p=0.01) CH4 consumption, probably because it enhanced methanotrophic activity. The addition of N and P (N + P) resulted in larger CO2 fluxes in the transitory phase (p=0.01), suggesting a possible co-limitation of both N and P on soil respiration. Heterotrophic (microbial) CO2 effluxes were significantly higher than the autotrophic (root) CO2 effluxes (p) across all treatment plots, with microbes contributing about two-thirds of the total soil CO2 effluxes. However, neither heterotrophic nor autotrophic respiration significantly differed between treatments. The results from this study suggest that the feedback of tropical forests to the global soil GHG budget could be disproportionately altered by increases in N and P availability over these biomes.

Soil redistribution on arable land is a major threat for a sustainable use of soil resources. The majority of soil redistribution studies focus on water erosion, while wind and tillage erosion also induce pronounced redistribution of soil materials. Tillage erosion especially is understudied, as it does not lead to visible off-site damages. The analysis of on-site/in-field soil redistribution is mostly based on tracer studies, where radionuclide tracers (e.g. 137Cs, 239+240Pu) from nuclear weapon tests are commonly used to derive the erosion history over the past 50–60 years. Tracer studies allow us to determine soil redistribution patterns but integrate all types of soil redistribution processes and hence do not allow us to unravel the contribution of individual erosion processes. The aim of this study is to understand the contribution of water and tillage erosion leading to soil patterns found in a small hummocky ground moraine kettle hole catchment under intensive agricultural use. Therefore, 239+240Pu-derived soil redistribution patterns were analysed using an inverse modelling approach accounting for water and tillage erosion processes. The results of this analysis clearly point out that tillage erosion is the dominant process of soil redistribution in the study catchment, which also affects the hydrological and sedimentological connectivity between arable land and the kettle hole. A topographic change up to 17 cm (53 yr)−1 in the eroded parts of the catchment is not able to explain the current soil profile truncation that exceeds the 239+240Pu-derived topographic change substantially. Hence, tillage erosion already started before the onset of intense mechanisation since the 1960s. In general, the study stresses the urgent need to consider tillage erosion as a major soil degradation process that can be the dominant soil redistribution process in sloped arable landscapes.

Surface runoff generation on arable fields is an important driver of flooding, on-site and off-site damages by erosion, and of nutrient and agrochemical transport. In general, three different processes generate surface runoff (Hortonian runoff, saturation excess runoff, and return of subsurface flow). Despite the developments in our understanding of these processes it remains difficult to predict which processes govern runoff generation during the course of an event or throughout the year, when soil and vegetation on arable land are passing many states. We analysed the results from 317 rainfall simulations on 209 soils from different landscapes with a resolution of 14 286 runoff measurements to determine temporal and spatial differences in variables governing surface runoff, and to derive and test a statistical model of surface runoff generation independent from an a priori selection of modelled process types. Measured runoff was related to 20 time-invariant soil properties, three variable soil properties, four rain properties, three land use properties and many derived variables describing interactions and curvilinear behaviour. In an iterative multiple regression procedure, six of these properties/variables best described initial abstraction and the hydrograph. To estimate initial abstraction, the percentages of stone cover above 10% and of sand content in the bulk soil were needed, while the hydrograph could be predicted best from rain depth exceeding initial abstraction, rainfall intensity, soil organic carbon content, and time since last tillage. Combining the multiple regressions to estimate initial abstraction and surface runoff allowed modelling of event-specific hydrographs without an a priori assumption of the underlying process. The statistical model described the measured data well and performed equally well during validation. In both cases, the model explained 71 and 58% of variability in accumulated runoff volume and instantaneous runoff rate (RSME: 5.2 mm and 0.23 mm min−1, respectively), while RMSE of runoff volume predicted by the curve number model was 50% higher (7.7 mm). Stone cover, if it exceeded 10%, was most important for the initial abstraction, while time since tillage was most important for the hydrograph. Time since tillage is not taken into account either in typical lumped hydrological models (e.g. SCS curve number approach) or in more mechanistic models using Horton, Green and Ampt, or Philip type approaches to address infiltration although tillage affects many physical and biological soil properties that subsequently and gradually change again. This finding should foster a discussion regarding our ability to predict surface runoff from arable land, which seemed to be dominated by agricultural operations that introduce man-made seasonality in soil hydraulic properties.

Soil moisture is one of the fundamental variables in hydrology, meteorology and agriculture. Nevertheless, its spatio-temporal patterns in agriculturally used landscapes that are affected by multiple natural (rainfall, soil, topography etc.) and agronomic (fertilisation, soil management etc.) factors are often not well known. The aim of this study is to determine the dominant factors governing the spatio-temporal patterns of surface soil moisture in a grassland and an arable test site that are located within the Rur catchment in Western Germany. Surface soil moisture (0–6 cm) was measured in an approx. 50×50 m grid during 14 and 17 measurement campaigns (May 2007 to November 2008) in both test sites. To analyse the spatio-temporal patterns of surface soil moisture, an Empirical Orthogonal Function (EOF) analysis was applied and the results were correlated with parameters derived from topography, soil, vegetation and land management to link the patterns to related factors and processes. For the grassland test site, the analysis resulted in one significant spatial structure (first EOF), which explained 57.5% of the spatial variability connected to soil properties and topography. The statistical weight of the first spatial EOF is stronger on wet days. The highest temporal variability can be found in locations with a high percentage of soil organic carbon (SOC). For the arable test site, the analysis resulted in two significant spatial structures, the first EOF, which explained 38.4% of the spatial variability, and showed a highly significant correlation to soil properties, namely soil texture and soil stone content. The second EOF, which explained 28.3% of the spatial variability, is linked to differences in land management. The soil moisture in the arable test site varied more strongly during dry and wet periods at locations with low porosity. The method applied is capable of identifying the dominant parameters controlling spatio-temporal patterns of surface soil moisture without being affected by single random processes, even in intensively managed agricultural areas.

The Northeast German Lowland Observatory (TERENO-NE) was established to investigate the regional impact of climate and land use change. TERENO-NE focuses on the Northeast German lowlands, for which a high vulnerability has been determined due to increasing temperatures and decreasing amounts of precipitation projected for the coming decades. To facilitate in-depth evaluations of the effects of climate and land use changes and to separate the effects of natural and anthropogenic drivers in the region, six sites were chosen for comprehensive monitoring. In addition, at selected sites, geoarchives were used to substantially extend the instrumental records back in time. It is this combination of diverse disciplines working across different time scales that makes the observatory TERENO-NE a unique observation platform. We provide information about the general characteristics of the observatory and its six monitoring sites and present examples of interdisciplinary research activities at some of these sites. We also illustrate how monitoring improves process understanding, how remote sensing techniques are fine-tuned by the most comprehensive ground-truthing site DEMMIN, how soil erosion dynamics have evolved, how greenhouse gas monitoring of rewetted peatlands can reveal unexpected mechanisms, and how proxy data provides a long-term perspective of current ongoing changes.