Soil

Journal: Soil

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Copernicus

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2199-3971
2199-398X

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Publications 1 - 10 of 32

The interdisciplinary nature of soil
Brevik, Eric C.; Cerdà, Artemi; Mataix-Solera, Jorge; et al. (2015)
Soil
The holistic study of soils requires an interdisciplinary approach involving biologists, chemists, geologists, and physicists, amongst others, something that has been true from the earliest days of the field. In more recent years this list has grown to include anthropologists, economists, engineers, medical professionals, military professionals, sociologists, and even artists. This approach has been strengthened and reinforced as current research continues to use experts trained in both soil science and related fields and by the wide array of issues impacting the world that require an in-depth understanding of soils. Of fundamental importance amongst these issues are biodiversity, biofuels/energy security, climate change, ecosystem services, food security, human health, land degradation, and water security, each representing a critical challenge for research. In order to establish a benchmark for the type of research that we seek to publish in each issue of SOIL, we have outlined the interdisciplinary nature of soil science research we are looking for. This includes a focus on the myriad ways soil science can be used to expand investigation into a more holistic and therefore richer approach to soil research. In addition, a selection of invited review papers are published in this first issue of SOIL that address the study of soils and the ways in which soil investigations are essential to other related fields. We hope that both this editorial and the papers in the first issue will serve as examples of the kinds of topics we would like to see published in SOIL and will stimulate excitement among our readers and authors to participate in this new venture.
Managing soil organic carbon in tropical agroecosystems: evidence from four long-term experiments in Kenya
Laub, Moritz; Corbeels, Marc; Couëdel, Antoine; et al. (2023)
Soil
In sub-Saharan Africa, maize is one of the most important staple crops, but long-term maize cropping with low external inputs has been associated with the loss of soil fertility. While adding high-quality organic resources combined with mineral fertilizer has been proposed to counteract this fertility loss, the long-term effectiveness and interactions with site properties still require more understanding. This study used repeated measurements over time to assess the effect of different quantities and qualities of organic resource addition combined with mineral nitrogen (N) on the change of soil organic carbon (SOC) contents over time (and SOC stocks in the year 2021) in four ongoing long-term experiments in Kenya. These experiments were established with identical treatments in moist to dry climates, on coarse to clayey soil textures, and have been conducted for at least 16 years. They received organic resources in quantities equivalent to 1.2 and 4 t C ha(-1) yr(-1) in the form of Tithonia diversifolia (high quality, fast turnover), Calliandra calothyrsus (high quality, intermediate turnover), Zea mays stover (low quality, fast turnover), sawdust (low quality, slow turnover) and local farmyard manure (variable quality, intermediate turnover). Furthermore, the addition of 240 kg N ha(-1) yr(-1) as mineral N fertilizer or no fertilizer was the split-plot treatment. At all four sites, a loss of SOC was predominantly observed, likely because the sites had been converted to cropland only a few decades before the start of the experiments. Across sites, the average decline of SOC content over 19 years in the 0 to 15 cm topsoil layer ranged from 42 % to 13 % of the initial SOC content for the control and the farmyard manure treatments at 4 t C ha(-1) yr(-1), respectively. Adding Calliandra or Tithonia at 4 t C ha(-1) yr(-1) limited the loss of SOC contents to about 24 % of initial SOC, while the addition of sawdust, maize stover (in three of the four sites) and sole mineral N addition showed no significant reduction of SOC loss over the control. Site-specific analyses, however, did show that at the site with the lowest initial SOC content (about 6 g kg(-1)), the addition of 4 t C ha(-1) yr(-1) farmyard manure or Calliandra with mineral N led to a gain in SOC contents. The other sites lost SOC in all treatments, albeit at site-specific rates. While subsoil SOC stocks in 2021 were little affected by organic resource additions (no difference in three of the four sites), the topsoil SOC stocks corroborated the results obtained from the SOC content measurements (0-15 cm) over time. The relative annual change of SOC contents showed a higher site specificity in farmyard manure, Calliandra and Tithonia treatments than in the control treatment, suggesting that the drivers of site specificity in SOC buildup (soil mineralogy, soil texture, climate) need to be better understood for effective targeting management of organic resources. Farmyard manure showed the highest potential for reducing SOC losses, but the necessary quantities to build SOC are often not realistic for smallholder farmers in Africa. Therefore, additional agronomic interventions such as intercropping, crop rotations or the cultivation of crops with extended root systems are necessary to maintain or increase SOC.
On-farm study reveals positive relationship between gas transport capacity and organic carbon content in arable soil
Colombi, Tino; Walder, Florian; Büchi, Lucie; et al. (2019)
Soil
Arable soils may act as a sink in the global carbon cycle, but the prediction of their potential for carbon sequestration remains challenging. Amongst other factors, soil aeration is known to influence root growth and microbial activity and thus inputs and decomposition of soil organic carbon. However, the influence of soil aeration on soil organic carbon content has been explored only little, especially at the farm level. Here, we investigated relationships between gas transport properties and organic carbon content in the topsoil and subsoil of 30 fields of individual farms, covering a wide range of textural composition. The fields were managed either conventionally, organically, or according to no-till practice. Despite considerable overlap between the management systems, we found that tillage increased soil gas transport capability in the topsoil, while organic farming resulted in higher soil organic carbon content. Remarkably, higher gas transport capability was associated with higher soil organic carbon content, both in the topsoil and subsoil (0.53 < R2 < 0.71). Exogenous organic carbon inputs in the form of crop residues and organic amendments, in contrast, were not related to soil organic carbon content. Based on this, we conjecture that higher gas transport capability resulted in improved conditions for root growth, which eventually led to increased input of soil organic carbon. Our findings show the importance of soil aeration for carbon storage in soil and highlight the need to consider aeration in the evaluation of carbon sequestration strategies in cropping systems.
Uncertainty indication in soil function maps – transparent and easy-to-use information to support sustainable use of soil resources
Greiner, Lucie; Nussbaum, Madlene; Papritz, Andreas Jürg; et al. (2018)
Soil
Spatial information on soil function fulfillment (SFF) is increasingly being used to inform decision-making in spatial planning programs to support sustainable use of soil resources. Soil function maps visualize soils abilities to fulfill their functions, e.g., regulating water and nutrient flows, providing habitats, and supporting biomass production based on soil properties. Such information must be reliable for informed and transparent decision-making in spatial planning programs. In this study, we add to the transparency of soil function maps by (1) indicating uncertainties arising from the prediction of soil properties generated by digital soil mapping (DSM) that are used for soil function assessment (SFA) and (2) showing the response of different SFA methods to the propagation of uncertainties through the assessment. For a study area of 170 km2 in the Swiss Plateau, we map 10 static soil sub-functions for agricultural soils for a spatial resolution of 20 × 20 m together with their uncertainties. Mapping the 10 soil sub-functions using simple ordinal assessment scales reveals pronounced spatial patterns with a high variability of SFF scores across the region, linked to the inherent properties of the soils and terrain attributes and climate conditions. Uncertainties in soil properties propagated through SFA methods generally lead to substantial uncertainty in the mapped soil sub-functions. We propose two types of uncertainty maps that can be readily understood by stakeholders. Cumulative distribution functions of SFF scores indicate that SFA methods respond differently to the propagated uncertainty of soil properties. Even where methods are comparable on the level of complexity and assessment scale, their comparability in view of uncertainty propagation might be different. We conclude that comparable uncertainty indications in soil function maps are relevant to enable informed and transparent decisions on the sustainable use of soil resources.
Best performances of visible-near-infrared models in soils with little carbonate - a field study in Switzerland
Oberholzer, Simon; Summerauer, Laura; Steffens, Markus; et al. (2024)
Soil
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.
Effect of biochar and liming on soil nitrous oxide emissions from a temperate maize cropping system
Hüppi, Roman; Felber, Raphael; Neftel, Albrecht; et al. (2015)
Soil
Biochar, a carbon-rich, porous pyrolysis product of organic residues may positively affect plant yield and can, owing to its inherent stability, promote soil carbon sequestration when amended to agricultural soils. Another possible effect of biochar is the reduction in emissions of nitrous oxide (N2O). A number of laboratory incubations have shown significantly reduced N2O emissions from soil when mixed with biochar. Emission measurements under field conditions however are more scarce and show weaker or no reductions, or even increases in N2O emissions. One of the hypothesised mechanisms for reduced N2O emissions from soil is owing to the increase in soil pH following the application of alkaline biochar. To test the effect of biochar on N2O emissions in a temperate maize cropping system, we set up a field trial with a 20t ha−1 biochar treatment, a limestone treatment adjusted to the same pH as the biochar treatment (pH 6.5), and a control treatment without any addition (pH 6.1). An automated static chamber system measured N2O emissions for each replicate plot (n = 3) every 3.6 h over the course of 8 months. The field was conventionally fertilised at a rate of 160 kg N ha−1 in three applications of 40, 80 and 40 kg N ha−1 as ammonium nitrate. Cumulative N2O emissions were 52 % smaller in the biochar compared to the control treatment. However, the effect of the treatments overall was not statistically significant (p = 0.27) because of the large variability in the data set. Limed soils emitted similar mean cumulative amounts of N2O as the control. There is no evidence that reduced N2O emissions with biochar relative to the control is solely caused by a higher soil pH.
Developing the Swiss mid-infrared soil spectral library for local estimation and monitoring
Baumann, Philipp; Helfenstein, Anatol; Gubler, Andreas; et al. (2021)
Soil
Information on soils' composition and physical, chemical and biological properties is paramount to elucidate agroecosystem functioning in space and over time. For this purpose, we developed a national Swiss soil spectral library (SSL; n = 4374) in the mid-infrared (mid-IR), calibrating 16 properties from legacy measurements on soils from the Swiss Biodiversity Monitoring program (BDM; n = 3778; 1094 sites) and the Swiss long-term Soil Monitoring Network (NABO; n = 596; 71 sites). General models were trained with the interpretable rule-based learner CUBIST, testing combinations of {5, 10, 20, 50, and 100} ensembles of rules (committees) and {2, 5, 7, and 9} nearest neighbors used for local averaging with repeated 10-fold cross-validation grouped by location. To evaluate the information in spectra to facilitate long-term soil monitoring at a plot level, we conducted 71 model transfers for the NABO sites to induce locally relevant information from the SSL, using the data-driven sample selection method RS - LOCAL. In total, 10 soil properties were estimated with discrimination capacity suitable for screening (R-2 >= 0.72; ratio of performance to interquartile distance (RPIQ) >= 2.0), out of which total carbon (C), organic C (OC), total nitrogen (N), pH and clay showed accuracy eligible for accurate diagnostics (R-2 > 0.8; RPIQ >= 3.0). CUBIST and the spectra estimated total C accurately with the root mean square error (RMSE) = 8.4 g kg(-1) and the RPIQ = 4.3, while the measured range was 1-583 g kg(-1) and OC with RMSE = 9.3 g kg(-1) and RPIQ = 3.4 (measured range 0-583 g kg(-1)). Compared to the general statistical learning approach, the local transfer approach - using two respective training samples - on average reduced the RMSE of total C per site fourfold. We found that the selected SSL subsets were highly dissimilar compared to validation samples, in terms of both their spectral input space and the measured values. This suggests that data-driven selection with RS - LOCAL leverages chemical diversity in composition rather than similarity. Our results suggest that mid-IR soil estimates were sufficiently accurate to support many soil applications that require a large volume of input data, such as precision agriculture, soil C accounting and monitoring and digital soil mapping. This SSL can be updated continuously, for example, with samples from deeper profiles and organic soils, so that the measurement of key soil properties becomes even more accurate and efficient in the near future.
Evaluation of digital soil mapping approaches with large sets of environmental covariates
Nussbaum, Madlene; Spiess, Kay; Baltensweiler, Andri; et al. (2018)
Soil
The spatial assessment of soil functions requires maps of basic soil properties. Unfortunately, these are either missing for many regions or are not available at the desired spatial resolution or down to the required soil depth. The field-based generation of large soil datasets and conventional soil maps remains costly. Meanwhile, legacy soil data and comprehensive sets of spatial environmental data are available for many regions.Digital soil mapping (DSM) approaches relating soil data (responses) to environmental data (covariates) face the challenge of building statistical models from large sets of covariates originating, for example, from airborne imaging spectroscopy or multi-scale terrain analysis. We evaluated six approaches for DSM in three study regions in Switzerland (Berne, Greifensee, ZH forest) by mapping the effective soil depth available to plants (SD), pH, soil organic matter (SOM), effective cation exchange capacity (ECEC), clay, silt, gravel content and fine fraction bulk density for four soil depths (totalling 48 responses). Models were built from 300–500 environmental covariates by selecting linear models through (1) grouped lasso and (2) an ad hoc stepwise procedure for robust external-drift kriging (georob). For (3) geoadditive models we selected penalized smoothing spline terms by component-wise gradient boosting (geoGAM). We further used two tree-based methods: (4) boosted regression trees (BRTs) and (5) random forest (RF). Lastly, we computed (6) weighted model averages (MAs) from the predictions obtained from methods 1–5.Lasso, georob and geoGAM successfully selected strongly reduced sets of covariates (subsets of 3–6 % of all covariates). Differences in predictive performance, tested on independent validation data, were mostly small and did not reveal a single best method for 48 responses. Nevertheless, RF was often the best among methods 1–5 (28 of 48 responses), but was outcompeted by MA for 14 of these 28 responses. RF tended to over-fit the data. The performance of BRT was slightly worse than RF. GeoGAM performed poorly on some responses and was the best only for 7 of 48 responses. The prediction accuracy of lasso was intermediate. All models generally had small bias. Only the computationally very efficient lasso had slightly larger bias because it tended to under-fit the data. Summarizing, although differences were small, the frequencies of the best and worst performance clearly favoured RF if a single method is applied and MA if multiple prediction models can be developed.
Mulch application as the overarching factor explaining increase in soil organic carbon stocks under conservation agriculture in two 8-year-old experiments in Zimbabwe
Shumba, Armwell; Chikowo, Regis; Thierfelder, Christian; et al. (2024)
Soil
Conservation agriculture (CA), combining reduced or no tillage, permanent soil cover, and improved rotations, is often promoted as a climate-smart practice. However, our understanding of the impact of CA and its respective three principles on top- and subsoil organic carbon stocks in the low-input cropping systems of sub-Saharan Africa is rather limited. This study was conducted at two long-term experimental sites established in Zimbabwe in 2013. The soil types were abruptic Lixisols at Domboshava Training Centre (DTC) and xanthic Ferralsol at the University of Zimbabwe farm (UZF). The following six treatments, which were replicated four times, were investigated: conventional tillage (CT), conventional tillage with rotation (CTR), no tillage (NT), no tillage with mulch (NTM), no tillage with rotation (NTR), and no tillage with mulch and rotation (NTMR). Maize (Zea mays L.) was the main crop, and treatments with rotation included cowpea (Vigna unguiculata L. Walp.). The soil organic carbon (SOC) concentration and soil bulk density were determined for samples taken from depths of 0-5, 5-10, 10-15, 15-20, 20-30, 30-40, 40-50, 50-75 and 75-100cm. Cumulative organic inputs to the soil were also estimated for all treatments. SOC stocks at equivalent soil mass were significantly (p<0.05) higher in the NTM, NTR and NTMR treatments compared with the NT and CT treatments in the top 5cm and top 10cm layers at UZF, while SOC stocks were only significantly higher in the NTM and NTMR treatments compared with the NT and CT treatments in the top 5cm at DTC. NT alone had a slightly negative impact on the top SOC stocks. Cumulative SOC stocks were not significantly different between treatments when considering the whole 100cm soil profile. Our results show the overarching role of crop residue mulching in CA cropping systems with respect to enhancing SOC stocks but also that this effect is limited to the topsoil. The highest cumulative organic carbon inputs to the soil were observed in NTM treatments at the two sites, and this could probably explain the positive effect on SOC stocks. Moreover, our results show that the combination of at least two CA principles including mulch is required to increase SOC stocks in these low-nitrogen-input cropping systems.
Heterotrophic soil respiration and carbon cycling in geochemically distinct African tropical forest soils
Bukombe, Benjamin; Fiener, Peter; Hoyt, Alison M.; et al. (2021)
Soil
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 (Delta C-14) 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 Delta C-14. 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.

Publications 1 - 10 of 32

Journal: Soil

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