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A special issue of Environments (ISSN 2076-3298).

Deadline for manuscript submissions: closed (30 April 2023) | Viewed by 29411

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Dr. Sutie Xu

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Guest Editor

Department of Agronomy, Horticulture, and Plant Science, South Dakota State University, Brookings, SD 57007, USA
Interests: soil health; soil biogeochemistry; carbon sequestration; nutrient management; sustainable agriculture; pasture management
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Dr. Virginia L. Jin

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Guest Editor

USDA ARS, Lincoln, NE 68583 USA
Interests: soil microbial ecology; carbon and nutrient cycling in agroecosystems; soil fertility; soil carbon storage; green-house gas production; agricultural management
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Dr. Navreet Kaur Mahal

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Guest Editor

Department of Horticultural Sciences, Texas A&M University, 2133 TAMU, College Station, TX 77843-2133, USA
Interests: soil organic matter; soil health; soil organic carbon; soil nitrogen management

Dr. Jing Hu

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Guest Editor

Geosystems Research Institute, Mississippi State University, Starkville, MS 39759, USA
Interests: soil health; soil biogeochemistry; precision agriculture; uncrewed aircraft systems
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Dear Colleagues,

Soil organic carbon (SOC) is the largest terrestrial C pool, and it plays a critical role in sustaining soil health. Multiple soil properties and processes are influenced by SOC, such as soil structure, nutrient dynamics, water conservation, and microorganism composition. Land-use conversion and management may result in higher SOC loss and CO₂ emission, while improved management strategies can promote SOC sequestration and mitigate greenhouse gas emissions. Thus, assessing SOC in natural and agricultural ecosystems is critical in order to provide insights on ecosystem services influenced by anthropogenic activities.

This Special Issue aims to present original research articles, reviews, and short communications concerning the following topics: (1) Measuring and assessing SOC stocks and characteristics under sustainable agroecosystem management; (2) monitoring and modeling SOC dynamics in natural ecosystems affected by land uses; (3) investigating SOC influenced by microbial processes; (4) plant root–soil interactions and SOC sequestration; and (5) SOC and greenhouse gas emissions influenced by temporal or spatial variability in the environment.

Dr. Sutie Xu
Dr. Virginia L. Jin
Dr. Navreet Kaur Mahal
Dr. Jing Hu
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Environments is an international peer-reviewed open access monthly journal published by MDPI.

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Keywords

carbon sequestration
carbon cycling
carbon pools
soil organic matter decomposition
land use
sustainable agriculture
rhizodeposition
soil microbial activities
soil respiration

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Related Special Issue

Soil Organic Carbon Assessment, 2nd Edition in Environments (3 articles)

Published Papers (8 papers)

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Research

14 pages, 711 KiB

Open AccessArticle

Soil Organic Carbon Stock Assessment for Volunteer Carbon Removal Benefit: Methodological Approach in Chestnut Orchard for Fruit Production

by Mauro De Feudis, Gilmo Vianello and Livia Vittori Antisari

Environments 2023, 10(5), 83; https://doi.org/10.3390/environments10050083 - 9 May 2023

Cited by 1 | Viewed by 2077

Abstract

The implementation of a protocol for supporting a reliable soil C market is needed. This paper aims to propose a methodology for evaluating soil organic C (SOC) stock changes for the C credit market. A 15-year-old chestnut orchard (CO) and a chestnut coppice (CC) as reference land were selected in the northern part of the Apennine chain (Italy). The CO is the result of the CC conversion carried out in 2005. The soil sampling by pedogenetic horizons till parent material was carried out in 2005, 2010, 2015 and 2020 in CO and in 2005 and 2020 in CC. For each sample, the concentration and stock of the total SOC and of the most recalcitrant SOC form were estimated. Unlike the CC, in CO, an increase over time of SOC stocks was observed throughout the entire soil profile indicating the suitability of CO for C credit gaining. Most of the SOC was stored within the deepest soil horizon. The methodology can be considered eligible for the C credit market because, replicable, the CO was intentionally realized by humans after 1990, and the additionality was evaluated. Moreover, soil functionality was considered through the evaluation of SOC forms and of the pedogenetic horizons. Full article

(This article belongs to the Special Issue Soil Organic Carbon Assessment)

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12 pages, 621 KiB

Open AccessArticle

Near-Term Effects of Perennial Grasses on Soil Carbon and Nitrogen in Eastern Nebraska

by Salvador Ramirez II, Marty R. Schmer, Virginia L. Jin, Robert B. Mitchell and Kent M. Eskridge

Environments 2023, 10(5), 80; https://doi.org/10.3390/environments10050080 - 6 May 2023

Cited by 1 | Viewed by 2495

Abstract

Incorporating native perennial grasses adjacent to annual row crop systems managed on marginal lands can increase system resiliency by diversifying food and energy production. This study evaluated (1) soil organic C (SOC) and total N stocks (TN) under warm-season grass (WSG) monocultures and a low diversity mixture compared to an adjacent no-till continuous-corn system, and (2) WSG total above-ground biomass (AGB) in response to two levels of N fertilization from 2012 to 2017 in eastern Nebraska, USA. The WSG treatments consisted of (1) switchgrass (SWG), (2) big bluestem (BGB), and (3) low-diversity grass mixture (LDM; big bluestem, Indiangrass, and sideoat grama). Soils were sampled at fixed depth increments (0–120 cm) in the WSG plots and in the adjacent corn experiment in 2012 and 2017. Soil stocks (Mg ha⁻¹) of SOC and TN were calculated on an equivalent soil mass (ESM) basis and compared within the three WSG treatments as well as between experiments (corn compared to the mean of all WSGs). Soil organic C and TN stocks within soil layers and cumulative stocks responded to the main effect of WSG (P_WSG < 0.05) but were no different when comparing the WSGs to corn (P_expt = NS). Both SOC/TN stocks and cumulative stocks were generally greater in the LDM compared to the BGB. Neither SOC nor TN changed over time under either the WSGs or corn. Warm-season grass AGB responded to a three-way interaction of year, N rate, and WSG (p = 0.0007). Decreases in AGB over time were significant across WSGs and N levels except for SWG at 56 kg N ha⁻¹ and LDM at 112 kg N ha⁻¹. Above-ground biomass was generally greater in the LDM after the first harvest year (2013). Results suggest that incorporating WSGs into marginal cropland can maintain SOC and TN stocks while providing a significant source of biomass to be used in energy production or in integrated livestock systems. Full article

(This article belongs to the Special Issue Soil Organic Carbon Assessment)

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18 pages, 735 KiB

Open AccessArticle

Comparative Analysis of Machine and Deep Learning Models for Soil Properties Prediction from Hyperspectral Visual Band

by Dristi Datta, Manoranjan Paul, Manzur Murshed, Shyh Wei Teng and Leigh Schmidtke

Environments 2023, 10(5), 77; https://doi.org/10.3390/environments10050077 - 4 May 2023

Cited by 7 | Viewed by 3802

Abstract

Estimating various properties of soil, including moisture, carbon, and nitrogen, is crucial for studying their correlation with plant health and food production. However, conventional methods such as oven-drying and chemical analysis are laborious, expensive, and only feasible for a limited land area. With the advent of remote sensing technologies like multi/hyperspectral imaging, it is now possible to predict soil properties non-invasive and cost-effectively for a large expanse of bare land. Recent research shows the possibility of predicting those soil contents from a wide range of hyperspectral data using good prediction algorithms. However, these kinds of hyperspectral sensors are expensive and not widely available. Therefore, this paper investigates different machine and deep learning techniques to predict soil nutrient properties using only the red (R), green (G), and blue (B) bands data to propose a suitable machine/deep learning model that can be used as a rapid soil test. Another objective of this research is to observe and compare the prediction accuracy in three cases i. hyperspectral band ii. full spectrum of the visual band, and iii. three-channel of RGB band and provide a guideline to the user on which spectrum information they should use to predict those soil properties. The outcome of this research helps to develop a mobile application that is easy to use for a quick soil test. This research also explores learning-based algorithms with significant feature combinations and their performance comparisons in predicting soil properties from visual band data. For this, we also explore the impact of dimensional reduction (i.e., principal component analysis) and transformations (i.e., empirical mode decomposition) of features. The results show that the proposed model can comparably predict the soil contents from the three-channel RGB data. Full article

(This article belongs to the Special Issue Soil Organic Carbon Assessment)

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15 pages, 2676 KiB

Open AccessArticle

Effects of Cover Crops and Soil Amendments on Soil CO₂ Flux in a Mississippi Corn Cropping System on Upland Soil

by Jing Hu, Dana M. Miles, Ardeshir Adeli, John P. Brooks, Frances A. Podrebarac, Renotta Smith, Fangni Lei, Xiaofei Li, Johnie N. Jenkins and Robert J. Moorhead II

Environments 2023, 10(2), 19; https://doi.org/10.3390/environments10020019 - 26 Jan 2023

Cited by 8 | Viewed by 3785

Abstract

Agroecosystems, accounting for more than one-third of arable land worldwide, play an essential role in the terrestrial carbon (C) cycle. The development of agricultural practices, which maximize soil C sequestration from the atmosphere, is receiving growing attention due to the recognition of agroecosystems’ great potential to serve as sinks of atmospheric carbon dioxide (CO₂). In particular, cover crop and soil amendment applications are generating much interest in mitigating climate change and enhancing agricultural ecosystem services. The objective of this study was to evaluate the effects of winter cover crop and soil amendments, including broiler litter (BL), flue gas desulfurization (FGD) gypsum and lignite, on soil CO₂ flux from cropping systems in southeastern USA, where related studies were limited. A field study was conducted from 2019 to 2021 in a Mississippi upland corn cropping system with measurements of soil CO₂ flux, moisture and temperature during cash crop growing seasons. We observed high temporal variability in soil CO₂ flux with flux peaks between late June and early July, which is likely due to the temporal changes in soil moisture. A significant increase in soil CO₂ flux was found with BL application (p < 0.05). Co-application of FGD gypsum and lignite with BL-reduced soil CO₂ flux by 15–23% but did not fully eliminate the rising effects. Significantly higher soil CO₂ flux and lower soil temperature were observed from fields with cover crops than those without cover crops in the third year of this study (p < 0.05), which is likely attributed to the higher organic C content accumulated in soil with cover crops. Future research should assess year-round soil greenhouse gas fluxes in both cash crop and cover crop growing seasons using a high temporal resolution measurement scheme. Full article

(This article belongs to the Special Issue Soil Organic Carbon Assessment)

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24 pages, 4018 KiB

Open AccessArticle

Spontaneous Plants Improve the Inter-Row Soil Fertility in a Citrus Orchard but Nitrogen Lacks to Boost Organic Carbon

by Fernando Visconti, Enrique Peiró, Carlos Baixauli and José Miguel de Paz

Environments 2022, 9(12), 151; https://doi.org/10.3390/environments9120151 - 4 Dec 2022

Cited by 4 | Viewed by 3497

Abstract

The inter-row soils in conventionally run citrus orchards in Eastern Spain lose fertility, either physically, chemically, or biologically, as a consequence of machinery traffic and the use of herbicides. In order to regain inter-row soil fertility, two grass-cover management alternatives to the commonly used herbicide-kept bare management, namely, spontaneous plants and fescue, were established and left for four years until their effects on several physical, chemical, and biological parameters were monitored for two years more. The fescue ground cover exhibited lower average and maximum soil temperatures due to higher evapotranspiration rates but also higher annual soil water content on average and, additionally, higher rhizodeposition. Despite the fact that these new beneficial conditions helped enhance the soil’s biological fertility under fescue, the physical or chemical fertilities did not improve and neither did the organic carbon (SOC). The spontaneous plants also enhanced the biological fertility, but in this case, beneficial conditions were reflected by improvements in the chemical fertility, particularly the exchangeable potassium, and in the physical fertility by increasing the surface hydraulic conductivity and decreasing the bulk density. In the inter-rows of this citrus orchard, a seeded grass cover does not seem able to provide any soil fertility enhancement in comparison to a spontaneous one; rather the opposite. However, a lack of natural or man-driven nitrogen inputs poses a constraint to SOC gains. For this aim, the annual surface application of organic nitrogen-rich materials or even better, the fostering of N-fixing organisms would be recommended. Full article

(This article belongs to the Special Issue Soil Organic Carbon Assessment)

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18 pages, 3524 KiB

Open AccessArticle

Using Mid-Infrared Spectroscopy to Optimize Throughput and Costs of Soil Organic Carbon and Nitrogen Estimates: An Assessment in Grassland Soils

by Paulina B. Ramírez, Samantha Mosier, Francisco Calderón and M. Francesca Cotrufo

Environments 2022, 9(12), 149; https://doi.org/10.3390/environments9120149 - 25 Nov 2022

Cited by 2 | Viewed by 4090

Abstract

Low-cost techniques, such as mid-infrared (MIR) spectroscopy, are increasingly necessary to detect soil organic carbon (SOC) and nitrogen (N) changes in rangelands following improved grazing management. Specifically, Adaptive Multi-Paddock (AMP) grazing is being implemented to restore grassland ecosystems and sequester SOC often for commercialization in C markets. To determine how the accuracy of SOC and N predictions using MIR spectroscopy is affected by the number of calibration samples and by different predictive models, we analyzed 1000 samples from grassland soils. We tested the effect of calibration sample size from 100 to 1000 samples, as well as the predictive ability of the partial least squares (PLS), random forest (RF) and support vector machine (SVM) algorithms on SOC and N predictions. The samples were obtained from five different farm pairs corresponding to AMP and Conventional Grazing (CG), covering a 0–50 cm soil depth profile along a latitudinal gradient in the Southeast USA. Overall, the sample size had only a moderate influence on these predictions. The predictive accuracy of all three models was less affected by variation in sample size when >400 samples were used. The predictive ability of non-linear models SVM and RF was similar to classical PLS. Additionally, all three models performed better for the deeper soil samples, i.e., from below the A horizon to the –50 cm depth. For topsoil samples, the particulate organic matter (POM) content also influenced the model accuracy. The selection of representative calibration samples efficiently reduces analysis costs without affecting the quality of results. Our study is an effort to improve the efficiency of SOC and N monitoring techniques. Full article

(This article belongs to the Special Issue Soil Organic Carbon Assessment)

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16 pages, 829 KiB

Open AccessArticle

Fe-Bound Organic Carbon and Sorption of Aromatic Dissolved Organic Carbon in Surface Soil: Comparing a Forest, a Cropland, and a Pasture Soil in the Central Appalachian Region, West Virginia, U.S.A

by Lili Lei, Ida Holásková, James A. Thompson and Louis M. McDonald

Environments 2022, 9(9), 113; https://doi.org/10.3390/environments9090113 - 2 Sep 2022

Cited by 1 | Viewed by 3378

Abstract

The essential roles of Fe oxides in stabilizing long-term soil organic carbon (SOC), especially aromatic dissolved organic carbon (DOC_aro), are well-established in forest soils and sediments. We chose to focus on these processes in agricultural soils in which the input and translocation of native DOC to deeper soils are impacted by management practices. We quantified SOC, Fe oxide bound SOC (Fe-bound OC), and the DOC_aro sorption in a forest, a cropland, and a pasture soil at 0–10 and 10–25 cm. Significantly larger amounts of Fe oxides in the cropland soil were observed compared to the forest and pasture soils at both depths (p < 0.05). Land management practices and depth both significantly influenced the Fe-bound OC percentage (p < 0.05). Larger maximum sorptions of DOC in the cropland (315.0 mg kg⁻¹) and pasture (395.0 mg kg⁻¹) soils than the forest soil (96.6 mg kg⁻¹) at 10–25 cm weres found. DOC_aro sorption decreased in the three soils at 0–10 cm (slope of −0.002 to −0.014 L² mg⁻² m⁻¹) as well as the forest soil at 10–25 cm (−0.016 L² mg⁻² m⁻¹) with increasing equilibrium DOC concentration. Conversely, the cropland and pasture soils at 10–25 cm increased (0.012 to 0.014 L² mg⁻² m⁻¹). The different sorption behaviors of DOC_aro in these surface soils indicate that the forest, cropland, and pasture-managed soils may have more complex and various sorption behaviors in stabilizing DOC_aro and non-DOC_aro. Full article

(This article belongs to the Special Issue Soil Organic Carbon Assessment)

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16 pages, 2558 KiB

Open AccessArticle

Dynamics of Soil Organic Carbon and CO₂ Flux under Cover Crop and No-Till Management in Soybean Cropping Systems of the Mid-South (USA)

by Alexandra G. Firth, John P. Brooks, Martin A. Locke, Dana J. Morin, Ashli Brown and Beth H. Baker

Environments 2022, 9(9), 109; https://doi.org/10.3390/environments9090109 - 27 Aug 2022

Cited by 14 | Viewed by 4570

Abstract

The transition of natural landscapes to agricultural uses has resulted in severe loss of soil organic carbon, significantly contributing to CO₂ emissions and rising global temperatures. However, soil has the largest store of terrestrial carbon (C), a considerable sink and effective strategy for climate change mitigation if managed properly. Cover crops (CC) and no-till (NT) management are two management strategies that are known to increase percent organic carbon (%OC); however, adoption of these practices has been low in the mid-South due to lack of region-specific research and resistance to unproven practices. Therefore, the purpose of this study was to evaluate the impacts of CC-NT treatments in soybean cropping systems on soil percent organic carbon (%OC) and CO₂ flux following long-term implementation. Results showed significantly greater %OC in NT (1.27% ± 0.03) than reduced till (RT; 1.10% ± 0.03; p < 0.001) and greater in both CC (rye: 1.23% ± 0.03, rye + clover: 1.22% ± 0.03) than no cover (1.11% ± 0.03; p < 0.001). Bacterial abundance (p = 0.005) and pH (p = 0.006) were significant predictors of %OC. There was no overall significant difference in CO₂ flux between tillage or CC treatments; however, there were significant differences between NT and RT in July of 2020 when %RH increased (p < 0.001). Bacterial abundance negatively impacted CO₂ flux (p < 0.05), which contradicts most studies. The rate of proportional change and pattern of variability in C pools suggested loss of %OC in RT treatments that were not apparent when considering %OC alone. The results of this study provide valuable insight into C turnover and the effectiveness of CC use in the Mid-South to increase soil C stocks. Full article

(This article belongs to the Special Issue Soil Organic Carbon Assessment)

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