Tracing macroplastics redistribution and fragmentation by tillage translocation.

Soil is polluted with plastic waste from macro to submicron level. Our understanding of macroplastics (> 5 mm) occurrence and behavior has remained comparatively elusive, mainly due to a lack of a tracing mechanism. This study set up a methodology to trace macroplastic displacement, which combined magnetic iron oxide-tagged soil and macroplastic pieces tagged by an adhesive passive radiofrequency identification transponder. By utilizing these techniques, a field study was carried out to analyze the effect of tillage implement and plastic sizes on plastic displacement, to understand the fate of macroplastics in arable land. Results indicated that the displacement of macroplastics did not depend upon plastic sizes but did depend upon the tillage implement used. The mean macroplastics displacement per tillage pass was 0.36 ± 0.25 m with non-inversion chisel tillage and 0.15 ± 0.13 m with inversion disk tillage, which was similar to bulk soil displacement. However, only inversion disk tillage caused fragmentation (41 %) of macroplastics and generated microplastics (< 5 mm). In contrast, both tillage implements drove to similar burial of surface macroplastics into the tilled layer (74 % on average). These results highlight that tillage is a major process for macroplastics fate in arable soils, being one of the first studies to investigate it.

Enhancing sub-catchment sediment source fingerprinting using chemometric models for DRIFTS in different particle size subfractions.

Understanding the origins of sediment within stream networks is critical to developing effective strategies to mitigate sediment delivery and soil erosion in larger drainage basins. Sediment fingerprinting is a widely accepted approach to identifying sediment sources; however, it typically relies on labor-intensive and costly chemical analyses. Recent studies have recognized diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS) as a non-destructive, cost-effective, and efficient alternative for estimating sediment contributions from multiple sources. This study aimed to assess (i) the effects of different particle size fractions on DRIFTS and conservatism tests, (ii) the effects of spectral pre-processing on discriminating sub-catchment spatial sediment sources, (iii) the efficiency of partial least squares regression (PLSR) and support vector machine regression (SVMR) chemometric models across different spectral resolutions and particle size fractions, and (iv) the quantification of sub-catchment spatial sediment source contributions using chemometric models across different particle size fractions. DRIFTS analysis was performed on three particle size fractions (<38 µm, 38-63 µm, and 63-125 µm) using 54 sediment samples from three different sub-catchments and 26 target sediment samples from the Andajrood catchment in Iran. Results showed significant effects of particle size fractions on DRIFTS for both sub-catchment sediment sources and target sediment samples. Conservatism tests indicated that DRIFTS behave conservative for the majority of target sediment samples. Spectral pre-processing techniques including SNV + SGD1 and SGD1 effectively discriminated sources across all particle size fractions and spectral resolutions. However, the optimal combination of pre-processing, spectral resolution, and regression models varied between sub-fractions. Validated model estimates revealed that sub-catchment 1 consistently contributed the most sediment across all particle size fractions, followed by sub-catchments 3 and 2. These results highlight the effectiveness of DRIFTS as a rapid, cost-effective, and precise method for discriminating and apportioning sediment sources within spatial sub-catchments.

First evidence of widespread, severe soil erosion underneath centre-pivot irrigation systems.

Centre-pivot systems are widely used for irrigation in agriculture. However, excessive water application rates under low pressure centre-pivot systems can lead to soil erosion, which degrades soil structure and increases crop vulnerability to droughts. Although efforts have been deployed to measure soil erosion underneath individual centre pivots, a large-scale systematic assessment of extent and severity of soil erosion in centre-pivot irrigated fields is currently lacking. Here we used Google Earth™ satellite images to provide first evidence of widespread, severe soil erosion in centre-pivot irrigated agricultural land. We focused on the municipality of Cristalina (6154 km2), in the Brazilian Central Highlands, where centre pivots irrigate approximately 60,000 ha of cropland. The study area is in the Cerrado biome, which is one of the most important grain-producing regions in the world and Brazil's main centre-pivot irrigation area. By mapping erosion features under centre pivots, we found that 29 % of centre-pivot fields displayed signs of rill erosion, with individual rills up to a length of 1200 m. Most erosion features were identified during the dry season of the Brazilian Cerrado, which coincided with the period of greater satellite-image availability. Moreover, we found that compacted centre-pivot-wheel tracks often triggered rill incision and that eroding centre-pivot fields displayed higher slope gradients and were better connected to surface waters than the non-eroding fields. Ultimately, the frequent identification of severe erosion features in the centre-pivot fields during the dry season indicates that irrigation causes and/or aggravates soil erosion in Cristalina and likely in other parts of the Brazilian Cerrado. This first systematic evidence of widespread soil erosion underneath centre-pivot systems highlights that irrigation erosion is an important but neglected driver of land degradation, and that urgent action is required to protect affected soils for future generations.

Soil carbon stocks in stable tropical landforms are dominated by geochemical controls and not by land use.

Soil organic carbon (SOC) dynamics depend on soil properties derived from the geoclimatic conditions under which soils develop and are in many cases modified by land conversion. However, SOC stabilization and the responses of SOC to land use change are not well constrained in deeply weathered tropical soils, which are dominated by less reactive minerals than those in temperate regions. Along a gradient of geochemically distinct soil parent materials, we investigated differences in SOC stocks and SOC (Δ14 C) turnover time across soil profile depth between montane tropical forest and cropland situated on flat, non-erosive plateau landforms. We show that SOC stocks and soil Δ14 C patterns do not differ significantly with land use, but that differences in SOC can be explained by the physicochemical properties of soils. More specifically, labile organo-mineral associations in combination with exchangeable base cations were identified as the dominating controls over soil C stocks and turnover. We argue that due to their long weathering history, the investigated tropical soils do not provide enough reactive minerals for the stabilization of C input in either high input (tropical forest) or low-input (cropland) systems. Since these soils exceeded their maximum potential for the mineral related stabilization of SOC, potential positive effects of reforestation on tropical SOC storage are most likely limited to minor differences in topsoil without major impacts on subsoil C stocks. Hence, in deeply weathered soils, increasing C inputs may lead to the accumulation of a larger readily available SOC pool, but does not contribute to long-term SOC stabilization.

Soil geochemistry - and not topography - as a major driver of carbon allocation, stocks, and dynamics in forests and soils of African tropical montane ecosystems.

The lack of field-based data in the tropics limits our mechanistic understanding of the drivers of net primary productivity (NPP) and allocation. Specifically, the role of local edaphic factors - such as soil parent material and topography controlling soil fertility as well as water and nutrient fluxes - remains unclear and introduces substantial uncertainty in understanding net ecosystem productivity and carbon (C) stocks. Using a combination of vegetation growth monitoring and soil geochemical properties, we found that soil fertility parameters reflecting the local parent material are the main drivers of NPP and C allocation patterns in tropical montane forests, resulting in significant differences in below- to aboveground biomass components across geochemical (soil) regions. Topography did not constrain the variability in C allocation and NPP. Soil organic C stocks showed no relation to C input in tropical forests. Instead, plant C input seemingly exceeded the maximum potential of these soils to stabilize C. We conclude that, even after many millennia of weathering and the presence of deeply developed soils, above- and belowground C allocation in tropical forests, as well as soil C stocks, vary substantially due to the geochemical properties that soils inherit from parent material.

Tillage exacerbates the vulnerability of cereal crops to drought.

Soils used for crop production cover 15.5 million km2 and almost all have been tilled at some point in their history. However, it is unclear how the changes in soil depth and soil properties associated with tillage affect crop yields. Here we show that tillage on slopes thins soils and reduces wheat and maize yields. At the landscape scale, tillage erosion gradually reduces crop yields as the duration and intensity of tillage increase. Over the next 50-100 yr, the overall yields are likely to further decline as modern mechanized agriculture accelerates the process of tillage erosion compared with centuries of non-mechanized tillage. Arresting this downward trend will require more widespread adoption of no-tillage practices and avoidance of down-slope cultivation. The downward pressure on landscape-scale yields due to tillage erosion is expected to be amplified by climate-change-induced increases in dry spells during crop growth.

Soil erosion as transport pathway of microplastic from agriculture soils to aquatic ecosystems.

Soil erosion is a potentially important source of microplastic (MP) entering aquatic ecosystems. However, little is known regarding the erosion and transport processes of MP from agricultural topsoils. The aim of this study is to analyze the erosion and transport behavior of MP during heavy rainfall events, whereas a specific focus is set to preferential MP transport and MP-soil interactions potentially leading to a more conservative transport behavior. The study is based on a series of rainfall simulations on paired-plots (4.5 m × 1.6 m) of silty loam and loamy sand located in Southern Germany. The simulations (rainfall intensity 60 mm h-1) were repeated 3 times within 1.5 years. An amount of 10 g m-2 of fine (MPf, size 53-100 µm) and 50 g m-2 of coarse (MPc, size 250-300 µm) high-density polyethylene as common polymer was added to the topsoil (<10 cm) of the plots. The experiments show a preferential erosion and transport of the MP leading to a mean enrichment ratio of 3.95 ± 3.71 (MPc) and 3.17 ± 2.58 (MPf) in the eroded sediment. There was a higher MP enrichment on the loamy sand but a higher sediment delivery on the silty loam resulting in nearly equal MP deliveries from both soil types. An increasing interaction with mineral soil particles or aggregates leads to a decreasing MP delivery over time. Within 1.5 years, up to 64% of the eroded MP particles were bound to soil particles. Overall, more of the MPc was laterally lost via soil erosion, while for the MPf the vertical transport below the plough layer was more important. In general, our study indicates that arable land susceptible to soil erosion can be a substantial MP source for aquatic ecosystems.

Soil erosion modelling: A bibliometric analysis.

Soil erosion can present a major threat to agriculture due to loss of soil, nutrients, and organic carbon. Therefore, soil erosion modelling is one of the steps used to plan suitable soil protection measures and detect erosion hotspots. A bibliometric analysis of this topic can reveal research patterns and soil erosion modelling characteristics that can help identify steps needed to enhance the research conducted in this field. Therefore, a detailed bibliometric analysis, including investigation of collaboration networks and citation patterns, should be conducted. The updated version of the Global Applications of Soil Erosion Modelling Tracker (GASEMT) database contains information about citation characteristics and publication type. Here, we investigated the impact of the number of authors, the publication type and the selected journal on the number of citations. Generalized boosted regression tree (BRT) modelling was used to evaluate the most relevant variables related to soil erosion modelling. Additionally, bibliometric networks were analysed and visualized. This study revealed that the selection of the soil erosion model has the largest impact on the number of publication citations, followed by the modelling scale and the publication's CiteScore. Some of the other GASEMT database attributes such as model calibration and validation have negligible influence on the number of citations according to the BRT model. Although it is true that studies that conduct calibration, on average, received around 30% more citations, than studies where calibration was not performed. Moreover, the bibliographic coupling and citation networks show a clear continental pattern, although the co-authorship network does not show the same characteristics. Therefore, soil erosion modellers should conduct even more comprehensive review of past studies and focus not just on the research conducted in the same country or continent. Moreover, when evaluating soil erosion models, an additional focus should be given to field measurements, model calibration, performance assessment and uncertainty of modelling results. The results of this study indicate that these GASEMT database attributes had smaller impact on the number of citations, according to the BRT model, than anticipated, which could suggest that these attributes should be given additional attention by the soil erosion modelling community. This study provides a kind of bibliographic benchmark for soil erosion modelling research papers as modellers can estimate the influence of their paper.

Soil erosion modelling: A global review and statistical analysis.

To gain a better understanding of the global application of soil erosion prediction models, we comprehensively reviewed relevant peer-reviewed research literature on soil-erosion modelling published between 1994 and 2017. We aimed to identify (i) the processes and models most frequently addressed in the literature, (ii) the regions within which models are primarily applied, (iii) the regions which remain unaddressed and why, and (iv) how frequently studies are conducted to validate/evaluate model outcomes relative to measured data. To perform this task, we combined the collective knowledge of 67 soil-erosion scientists from 25 countries. The resulting database, named 'Global Applications of Soil Erosion Modelling Tracker (GASEMT)', includes 3030 individual modelling records from 126 countries, encompassing all continents (except Antarctica). Out of the 8471 articles identified as potentially relevant, we reviewed 1697 appropriate articles and systematically evaluated and transferred 42 relevant attributes into the database. This GASEMT database provides comprehensive insights into the state-of-the-art of soil- erosion models and model applications worldwide. This database intends to support the upcoming country-based United Nations global soil-erosion assessment in addition to helping to inform soil erosion research priorities by building a foundation for future targeted, in-depth analyses. GASEMT is an open-source database available to the entire user-community to develop research, rectify errors, and make future expansions.

Using catchment characteristics to model seasonality of dissolved organic carbon fluxes in semi-arid mountainous headwaters.

Prediction of dissolved organic carbon (DOC) based on catchment characteristics is a useful tool for efficient and effective water management, but in the case of arid and semi-arid regions, such predictive capacity is scarce. Accordingly, the main objective of this study was to evaluate the significance of principal components for predicting DOC concentrations and fluxes in nine headwater catchments of the Hiv catchment located in the Southern Alborz Mountains in the west of Tehran, Iran. To achieve this aim, data were assembled on 24 headwater catchment characteristics comprising soil properties, physiography, seasonal rainfall, and flow attributes, as well as estimates of DOC concentrations and fluxes across four seasons. The results revealed a major positive correlation between DOC and soil organic matter parameters related to soil biological processes. Using general linear modelling, an organic matter component related to soil biology, a seasonal component related to the dummy effect of sampling seasons, and a soil physical component related to soil texture were found to be the best predictors for DOC responses in the study area.