Fine silt and clay content is the main factor defining maximal C and N accumulations in soils: a meta-analysis

Carbon footprints of tailings dams' disasters: A study in the Brumadinho region (Brazil)

Tailings dams' breaks are environmental disasters with direct and intense degradation of soil. This study analyzed the impacts of B1 tailings dam rupture occurred in the Ribeirão Ferro-Carvão watershed (Brumadinho, Brazil) in January 25, 2019. Soil organic carbon (SOC) approached environmental degradation. The analysis encompassed wetlands (high-SOC pools) located in the so-called Zones of Decreasing Destructive Capacity (DCZ5 to DCZ1) defined along the Ferro-Carvão's stream bed and banks after the disaster. Remote sensed water indices were extracted from Landsat 8 and Sentinel-2 satellite images spanning the 2017-2021 period and used to distinguish the wetlands from other land covers. The annual SOC was extracted from the MapBiomas repository inside and outside the DCZs in the same period, and assessed in the field in 2023. Before the dam collapse, the DCZs maintained stable levels of SOC, while afterwards they decreased substantially reaching minimum values in 2023. The reductions were abrupt: for example, in the DCZ3 the decrease was from 51.28 ton/ha in 2017 to 4.19 ton/ha in 2023. Besides, the SOC increased from DCZs located near to DCZs located farther from the dam site, a result attributed to differences in the percentages of clay and silt in the tailings, which also increased in the same direction. The Ferro-Carvão stream watershed as whole also experienced a slight reduction in the average SOC levels after the dam collapse, from nearly 43 ton/ha in 2017 to 38 ton/ha in 2021. This result was attributed to land use changes related with the management of tailings, namely opening of accesses to remove them from the stream valley, creation of spaces for temporary deposits, among others. Overall, the study highlighted the footprints of tailings dams' accidents on SOC, which affect not only the areas impacted with the mudflow but systemically the surrounding watersheds. This is noteworthy.

Machine Learning and Feature Selection for soil spectroscopy. An evaluation of Random Forest wrappers to predict soil organic matter, clay, and carbonates

Soil spectroscopy estimates soil properties using the absorption features in soil spectra. However, modelling soil properties with soil spectroscopy is challenging due to the high dimensionality of spectral data. Feature Selection wrapper methods are promising approaches to reduce the dimensionality but are barely used in soil spectroscopy. The aim of this study is to evaluate the performance of two feature selection wrapper methods, Sequential Forward Selection (SFS) and Sequential Flotant Forward Selection (SFFS) built using the Random Forest (RF) algorithm, for dimensionality reduction of spectral data and predictive modelling of modelling soil organic matter (SOM), clay and carbonates. The reflectance of 100 soil samples, acquired from Sierra de las Nieves (Spain), was measured under laboratory conditions using ASD FieldSpec Pro JR. Four different datasets were obtained after applying two spectral preprocessing methods to raw spectra: raw spectra, Continuum Removal (CR), Multiplicative Scatter Correction (MSC), and a so-called "Global" dataset composed of raw, CR and MSC features. The performance of RF models built with feature selection methods was compared to that of Partial Least Squares Regression (PLSR) and RF (alone). RF models built with SFS and SFFS outperformed PLSR and RF alone models: The best RF models with feature selection had a respective ratio of performance to interquartile distance of 1.93, 0.38 and 2.56. PLSR models had an accuracy of 1.41, 0.29 and 1.81 for SOM, carbonates, and clay, respectively. RF alone had a respective performance of 1.29, 0.29 and 1.81. The application of feature selection wrapper methods reduced the number of features to less than 1 % of the starting features. Features were selected across all spectra for SOM and clay, and around 900 nm, 1900 nm, and 2350 nm for carbonates. However, feature selection highlighted features around 1100 nm in SOM modelling, as well as other features around 2200 nm, which is considered a main absorption feature of clay. The application of feature selection with Random Forest was very important in improving modelling accuracy, reducing the redundant features and avoiding the curse of dimensionality or Hughes effect. Thus, this research showed an alternative to dimensionality reduction approaches that have been applied to date to model soil properties with spectroscopy and paves the way for further scientific investigation based on feature selection methods and machine learning.

Rhizosphere engineering for soil carbon sequestration

The rhizosphere is the central hotspot of water and nutrient uptake by plants, rhizodeposition, microbial activities, and plant-soil-microbial interactions. The plasticity of plants offers possibilities to engineer the rhizosphere to mitigate climate change. We define rhizosphere engineering as targeted manipulation of plants, soil, microorganisms, and management to shift rhizosphere processes for specific aims [e.g., carbon (C) sequestration]. The rhizosphere components can be engineered by agronomic, physical, chemical, biological, and genomic approaches. These approaches increase plant productivity with a special focus on C inputs belowground, increase microbial necromass production, protect organic compounds and necromass by aggregation, and decrease C losses. Finally, we outline multifunctional options for rhizosphere engineering: how to boost C sequestration, increase soil health, and mitigate global change effects.

High organic carbon content constricts the potential for stable organic carbon accrual in mineral agricultural soils in Finland

Sequestering carbon into agricultural soils is considered as a means of mitigating climate change. We used agronomic soil test results representing c. 95% of the farmed land area in Finland to estimate the potential of the uppermost 15 cm soil layer of mineral agricultural soils to sequester organic carbon (OC) and to contribute to the mitigation of climate change. The estimation of the maximum capacity of mineral matter to protect OC in stable mineral-associated form was based on the theory that clay and fine-sized (fines = clay + silt) particles have a limited capacity to protect OC. In addition, we used the clay/OC and fines/OC ratios to identify areas with a risk of erosion and reduced productivity, thus indicating priority areas potentially benefitting from the increased soil OC contents. We found that 32-40% of the mineral agricultural soils in Finland have the potential to further accumulate mineral-associated OC (MOC), while in the majority of soils, the current OC stock in the uppermost 15 cm exceeded the capacity of mineral matter to protect OC. The nationwide soil OC sequestration potential of the uppermost 15 cm in mineral agricultural soils ranged between 0.21 and 0.26 Tg, which corresponds to less than 2% of annual greenhouse gas emissions in Finland. The fields with the highest potential for SOC accrual were found in the southern and southwestern parts of the country, including some of the most intensively cultivated high-clay soils. Although the nationwide potential for additional OC sequestration was estimated to be relatively small, the current OC storage in Finnish arable mineral soils (0-15 cm) is large, 128 Tg. Farming practices enabling maximum OC input into the soil play an important role as a tool for mitigating the loss of carbon from high-OC soils in the changing climate. Furthermore, especially in high-clay areas with potential for MOC accrual, efforts to increase soil OC could help improve soil structural stability and therefore reduce erosion and the loss of nutrients to the aquatic environments.

Prokaryotic communities inhabiting a high-radon subterranean ecosystem (Castañar Cave, Spain): Environmental and substrate-driven controls

Castañar Cave (Caceres, Spain) is a unique show cave known for its high natural radiation levels. This study presents a comprehensive analysis of its prokaryotic diversity, specifically focusing on investigating the influence of environmental conditions and substrate characteristics on the prokaryotic community structure in the cave sediments. Additionally, the research aims to evaluate the potential impact of human activities on the cave ecosystem. The identification of distinct bioclimatic zones within the cave was made possible through a combination of environmental and microbial monitoring (ATP assays). The results reveal sediment texture as a significant factor, notably affecting the structure, diversity, and phylogenetic variability of the microbial community, including both Bacteria and Archaea. The proportion of clay minerals in sediments plays a crucial role in regulating moisture levels and nutrient availability. These substrate properties collectively exert a significant selective pressure on the structure of prokaryotic communities within cave sediments. The molecular approach shows that heterotrophic bacteria, including those with chitinolytic enzymes, primarily inhabit the cave. Furthermore, chemoautotrophic nitrifiers such as the archaea Nitrososphaeria and the genus Nitrospira, as well as methanotrophic bacteria from the phyla Methylomirabilota, Pseudomonadota, and Verrucomicrobiota, are also present. Remarkably, despite being a show cave, the cave microbiota displays minimal impacts from human activities and the surface ecosystem. Prokaryotic populations exhibit stability in the innermost areas, while the tourist trail area experiences slightly higher biomass increases due to visitor traffic. This suggests that conservation efforts have successfully limited the entry of external nutrients into the innermost cave areas. Additionally, the results suggest that integrating biomarkers like ATP into environmental monitoring can significantly enhance the methods used to study the negative impacts of tourism on cave ecosystems.

The effect of silvicultural systems on soil function depends on bedrock geology and altitude

Soil quality and function in forest environments are influenced by the interaction of soil-forming parameters and silvicultural systems. Hyrcanian forests were recently accepted as a UNESCO World Heritage Site, which extends across an area of approximately 1.8 million hectares and ascend to an elevation of 2800 m above sea level (m.a.s.l). In these woodlands, Oriental Beech (Fagus orientalis Lipsky) is the predominant tree species and could be observed at 700-1500 m.a.s.l., and occur on different parent rocks. Shelterwood and single-tree selection techniques have been the primary management methods for beech forests for the past forty years. Studies investigating the impacts of silvicultural systems have not yet been done on soil and forest floor features on different bedrock geology and altitudes. Therefore, in this study, we examined the influence of single-tree selection and shelterwood methods, 25 years after employing those methods, on soil quality and function compared to control areas (intact forests) in Hyrcanian beech stands. For this purpose, 15 forest floor (30 × 30 cm) and topsoil (0-10 cm depth) samples in each silvicultural systems (i.e., single-tree selection and shelterwood methods and control zones) × 4 regions (including Rasht, Nowshahr, Sari and Gorgan) × 4 altitude levels (with averages of 800, 1000, 1200 and 1400 m.a.s.l.) were considered. According to our findings, the investigated forest regions, forest floor and soil characteristics across various locations spots could be separated by principal component analysis output, and more than 85% of the variance was explained by the first and second axes. The structural equation model showed that the region, altitude and silvicultural systems had an effective role in the changes in soil biological activities by influencing the forest floor, and the soil physicochemical features. Based upon the network model, the C/N ratio, the sand content, the soil aggregate stability, the available K, the fulvic acid, and the Acarina density were found to be prominent factors with regard to soil function. In the control sites, increased soil organic material fractions, microbial/enzyme and biota activities were detected, particularly at the lower altitudes of the Nowshahr site, which had geological formations of dolomite and calcic layers. Taken together, it seems that the single-tree method, commonly referred to as the close-to-nature technique produces more suitable conditions for soil functioning compared to the shelterwood management approach. Silvicultural systems, bedrock geology and altitude can have major detrimental effects on soil function and fertility, over the long-term, impacts may increase with harvest intensity.

Divergent contribution of particulate and mineral-associated organic matter to soil carbon in grassland

Sequestration of soil organic carbon (SOC) is an effective means to draw atmospheric CO2. Grassland restoration is one of the fastest methods to increase soil C stocks, and particulate-associated C and mineral-associated C play critical roles in soil C stocks during restoration. Herein, we developed a conceptual mechanistic frame regarding the contributions made by mineral-associated organic matter to soil C during the restoration of temperate grasslands. Compared to 1-year grassland restoration, 30-year restoration increased mineral-associated organic C (MAOC) by 41% and particulate organic C (POC) by 47%. The SOC changed from microbial MAOC predominance to plant-derived POC predominance, as the POC was more sensitive to grassland restoration. The POC increased with plant biomass (mainly litter and root biomass), while the increase in MAOC was mainly caused by the combined effects of increasing microbial necromass and leaching of the base cations (Ca-bound C). Plant biomass accounted for 75% of the increase in POC, whereas bacterial and fungal necromass contributed to 58% of the variance in MAOC. POC and MAOC contributed to 54% and 46% of the increase in SOC, respectively. Consequently, the accumulation of the fast (POC) and slow (MAOC) pools of organic matter are important for the sequestration of SOC during grassland restoration. Overall, simultaneous tracing of POC and MAOC helps further understand the mechanisms and predict soil C dynamics combined with the input of plant C, microbial properties, and availability of soil nutrients during grassland restoration.

No detectable upper limit of mineral-associated organic carbon in temperate agricultural soils

Soil organic carbon (SOC) sequestration is a promising climate change mitigation option. In this context, the formation of the relatively long-lived mineral-associated organic carbon (MAOC) is key. To date, soils are considered to be limited in their ability to accumulate MAOC, mainly by the amount of clay and silt particles present. Using the comprehensive German Agricultural Soil Inventory, we selected 189 samples with a wide range of SOC (5-118 g kg-1 ) and clay contents (30-770 g kg-1 ) to test whether there is a detectable upper limit of MAOC content. We found that the proportion of MAOC was surprisingly stable for soils under cropland and grassland use across the whole range of bulk SOC contents. Soil texture influenced the slope of the relationship between bulk SOC and MAOC, but no upper limit was observed in any texture class. Also, C content in the fine fraction (g C kg-1 fraction) was negatively correlated to fine fraction content (g kg-1 bulk soil). Both findings challenge the notion that MAOC accumulation is limited by soil fine fraction content per se.

Atmospheric deposition of particulate matter from beef cattle feedlots is a likely contributor of pyrethroid occurrence in isolated wetland sediment: Source apportionment and ecological risk assessment

Industrial cattle feeding operations (feedlots) have been subject to public scrutiny in recent decades regarding environmental impacts of site runoff and aerial dispersion of agrochemical-laden particulate matter (PM). However, source apportionment of multi-use pesticides is challenging in mixed agricultural settings. Beef cattle on feed and row crop production are heavily concentrated in the Southern Great Plains of North America, where playa wetlands are vulnerable to agrochemical inputs and sedimentation from surrounding land use. In the current study, playa basin sediment (n = 33) was analyzed via UHPLC-MS for 21 agrochemicals spanning eight classes (macrocyclic lactones, neonicotinoids, organophosphates, pyrethroids, triazoles, β-methoxyacrylates, a carboximide, and phenylpyrazole). Pyrethroids were detected most frequently (75.8% of basins). Sediment pyrethroid concentrations were also significantly correlated (R² = 0.178, p = 0.007) with feedlot proximity (<1-50 km). Principal component analysis (PCA) of land use metrics extracted three principal components (74.3% of total variance), with principal component regression (PCR) showing the greatest agrochemical occurrence in basins heavily weighted by cropland buffer acreage (≤1 km) and feedlot proximity. Sediment toxicity benchmarks protective of two benthic invertebrates (Hyallela azteca and Chironomus spp.) identified λ-cyhalothrin, fenvalerate, and esfenvalerate as individual compounds exceeding levels of acute (RQ > 0.5) and chronic (RQ > 1) concern in >5% and >50% of cases, respectively. However, additive toxicity of co-occurring pyrethroids represents an acute high risk (RI > 1; median RI; acute = 2.4, chronic = 38.6) to benthic invertebrates in >75% of cases, which may threaten higher-order wetland taxa via bioaccumulation and trophic transfer.

Climate change induces carbon loss of arable mineral soils in boreal conditions

One-fourth of the global soil organic carbon (SOC) is stored in the boreal region, where climate change is predicted to be faster than the global average. Planetary warming is accelerated if climate change promotes SOC release into the atmosphere as carbon dioxide. However, the soil carbon-climate feedbacks have been poorly confirmed by SOC measurements despite their importance on global climate. In this study, we used data collected as part of the Finnish arable soil monitoring program to study the influence of climate change, management practices, and historical land use on changes in SOC content using a Bayesian approach. Topsoil samples (n = 385) collected nationwide in 2009 and 2018 showed that SOC content has decreased at the rate of 0.35% year-1 on average. Based on the Bayesian modeling of our data, we can say with a certainty of 79%-91% that increase in summertime (May-Sep) temperature has resulted in SOC loss while increased precipitation has resulted in SOC loss with a certainty of 90%-97%. The exact percentages depend on the climate dataset used. Historical land use was found to influence the SOC content for decades after conversion to cropland. Former organic soils with a high SOC-to-fine-fraction ratio were prone to high SOC loss. In fields with long cultivation history (>100 years), however, the SOC-to-fine-fraction ratio had stabilized to approximately 0.03-0.04 and the changes in SOC content leveled off. Our results showed that, although arable SOC sequestration can be promoted by diversifying crop rotations and by cultivating perennial grasses, it is unlikely that improved management practices are sufficient to counterbalance the climate change-induced SOC losses in boreal conditions. This underlines the importance of the reduction of greenhouse gas emissions to avoid the acceleration of planetary warming.

Modeling Soil Organic Carbon Changes under Alternative Climatic Scenarios and Soil Properties Using DNDC Model at a Semi-Arid Mediterranean Environment

Soil organic carbon (SOC) is one of the central issues in dealing with soil fertility as well as environmental and food safety. Due to the lack of relevant data sources and methodologies, analyzing SOC dynamics has been a challenge in Morocco. During the last two decades, process-based models have been adopted as alternative and powerful tools for modeling SOC dynamics; whereas, information and knowledge on the most sensitive model inputs under different climate, and soil conditions are still very limited. For this purpose, a sensitivity analysis was conducted in the present work, using the DeNitrification-DeComposition (DNDC) model based on the data collected at a semi-arid region (Merchouch station, Morocco). The objective is to identify the most influential factors affecting the DNDC-modeled SOC dynamics in a semi-arid region across different climatic and soil conditions. The results of sensitivity analysis highlighted air temperature as the main determinant of SOC. A decrease in air temperature of 4 °C results in an almost 161 kg C ha−1 yr−1 increase in C sequestration rate. Initial SOC was also confirmed to be one of the most sensitive parameters for SOC. There was a 96 kg C ha−1 yr−1 increase in C sequestration rate under low initial SOC (0.005 kg C ha−1). In the DNDC, air temperature in climatic factors and initial SOC in variable soil properties had the largest impacts on SOC accumulation in Merchouch station. We can conclude that the sensitivity analysis conducted in this study within the DNDC can contribute to provide a scientific evidence of uncertainties of the selected inputs variables who can lead to uncertainties on the SOC in the study site. The information in this paper can be helpful for scientists and policy makers, who are dealing with regions of similar environmental conditions as Merchouch Station, by identifying alternative scenarios of soil carbon sequestration.