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Editorial

Assessment of Soil Organic Carbon in Different Ecosystems by Using Field, Lab, and Modeling Methods

1
Department of Land, Air and Water Resources, University of California, Davis, CA 95616, USA
2
Department of Agronomy, Horticulture and Plant Science, South Dakota State University, Brookings, SD 57707, USA
3
Department of Civil, Environmental and Construction Engineering, University of Central Florida, Orlando, FL 32816, USA
4
Department of Horticultural Sciences, Texas A&M University, College Station, TX 77843, USA
5
USDA ARS, Lincoln, NE 68583, USA
*
Author to whom correspondence should be addressed.
Environments 2025, 12(9), 298; https://doi.org/10.3390/environments12090298
Submission received: 22 August 2025 / Accepted: 26 August 2025 / Published: 28 August 2025
(This article belongs to the Special Issue Soil Organic Carbon Assessment)
As the largest terrestrial carbon (C) pool, soil organic C (SOC) and its evaluation are important for understanding soil functions in different ecosystems. Specifically, monitoring the responses of SOC to ecosystem management strategies by selecting a good SOC assessment method is essential to provide meaningful information for future decision-making. This Special Issue, Soil Organic Carbon Assessment, was developed to present studies on SOC dynamics by using field and lab techniques and modeling methods.
Sustainable agriculture management practices, such as cover cropping, no-till, and organic amendment, have been used to improve the ability of soils in SOC sequestration. A study in the mid-south U.S. on soybean production fields showed a 15% increase in SOC under no-till compared to reduced till management and a 10% increase under cover cropping than no cover cropping fields (contribution 1). In a Mississippi Corn Cropping System, soil CO2 flux was increased under broiler litter application, but this increase was reduced by 15–23% when flue gas desulfurization (FGD) gypsum and lignite were applied together with broiler litter (contribution 2). From the same study, cover cropping increased soil CO2 flux while decreasing soil temperature. Similarly to cover cropping, managing ecosystems by increasing plant diversity, such as spontaneous plants and the incorporation of perennial grasses, is an alternative strategy for soil management. In a Citrus Orchard in Eastern Spain, fescue ground cover increased the soil water content and rhizodeposition, but this had little impact on SOC (contribution 3). Thus, the surface application of organic nitrogen-rich materials was suggested to foster N-fixing organisms and promote SOC accumulation. On a marginal land in eastern Nebraska, USA, warm-season grass monocultures and a low diversity mixture were planted adjacent to a no-till continuous-corn system (contribution 4). This study observed greater SOC and total nitrogen stocks in a low-diversity grass mixture compared to a big bluestem monoculture, while there was no change in SOC in these systems over time, suggesting the potential of warm season grass incorporation to maintain SOC and total nitrogen stocks along with good biomass production. Among different ecosystems, SOC stabilization may vary. A study in the Central Appalachian Region, West Virginia, U.S., was conducted to understand the SOC, Fe oxide bound SOC (Fe-bound SOC), and the aromatic dissolved organic carbon (DOCaro) sorption in a forest, a cropland, and a pasture soil (contribution 5). It was found that cropland soil had more Fe oxides than forest and pasture soils. Crop land soils also had larger maximum sorptions of DOC than forest soils (315.0 vs. 96.6 mg kg−1) at 10–25 cm, and both were smaller than that in pasture soil (395.0 mg kg−1).
Besides traditional field and lab assessments of SOC, advanced technologies with a lower cost such as mid-infrared spectroscopy and modeling can be used. A study was conducted to test the accuracy of using mid-infrared spectroscopy by testing three predictive models: partial least squares (PLS), random forest (RF), and support vector machine (SVM) algorithms (contribution 6). It was found that all three models had good predictive ability when >400 samples were used, especially for the deeper soil samples. Alternatively, soil parameters can be predicted by machine and deep learning techniques using only the red (R), green (G), and blue (B) bands data (contribution 7). Moreover, methodology for evaluating SOC change for the C credit market is needed. A 15-year-old chestnut orchard converted from a chestnut coppice showed C credit gaining, especially in deep soils, with soil sampling by pedogenetic horizons (contribution 8).
This Special Issue highlighted the importance of considering and selecting different methods for SOC assessment according to specific research goals. For future studies, it will be necessary to integrate field experiments and modeling to have a better understanding on the dynamics of SOC in different ecosystems. We would like to express our gratitude to the authors who have contributed to this Special Issue, and to the reviewers, editors, and staff of MDPI for their efforts in completing and publishing this Special Issue.

Conflicts of Interest

The authors declare no conflicts of interest.

List of Contributions

  • Firth, A.G.; Brooks, J.P.; Locke, M.A.; Morin, D.J.; Brown, A.; Baker, B.H. Dynamics of soil organic carbon and CO2 flux under cover crop and no-till management in soybean cropping systems of the mid-south (USA). Environments 2022, 9, 109.
  • Hu, J.; Miles, D.M.; Adeli, A.; Brooks, J.P.; Podrebarac, F.A.; Smith, R.; Lei, F.; Li, X.; Jenkins, J.N; Moorhead, R.J. Effects of cover crops and soil amendments on soil CO2 Flux in a Mississippi Corn cropping system on Upland soil. Environments  2023, 10, 19.
  • Visconti, F.; Peiró, E.; Baixauli, C.; de Paz, J.M. Spontaneous Plants improve the inter-row soil fertility in a Citrus orchard but nitrogen Lacks to Boost organic carbon. Environments 2022, 9, 151.
  • Ramirez, S.; Schmer, M.R.; Jin, V.L.; Mitchell, R.B.; Eskridge, K.M. Near-term effects of perennial grasses on soil carbon and nitrogen in eastern Nebraska. Environments 2023, 10, 80.
  • Lei, L.; Holásková, I.; Thompson, J.A.; and McDonald, L.M. 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, USA. Environments 2022, 9, 113.
  • Ramírez, P.B.; Mosier, S.; Calderón, F.; Cotrufo, M.F. Using mid-infrared spectroscopy to optimize throughput and costs of soil organic carbon and nitrogen estimates: An assessment in grassland soils. Environments 2022, 9, 149.
  • Datta, D.; Paul, M.; Murshed, M.; Teng, S.W; Schmidtke, L. Comparative analysis of machine and deep learning models for soil properties prediction from hyperspectral visual band. Environments 2023, 10, 77.
  • De Feudis, M.; Vianello, G.; Vittori Antisari, L. Soil Organic Carbon Stock Assessment for Volunteer Carbon Removal Benefit: Methodological Approach in Chestnut Orchard for Fruit Production. Environments 2023, 10, 83.
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MDPI and ACS Style

Xu, S.; Hu, J.; Mahal, N.K.; Jin, V.L. Assessment of Soil Organic Carbon in Different Ecosystems by Using Field, Lab, and Modeling Methods. Environments 2025, 12, 298. https://doi.org/10.3390/environments12090298

AMA Style

Xu S, Hu J, Mahal NK, Jin VL. Assessment of Soil Organic Carbon in Different Ecosystems by Using Field, Lab, and Modeling Methods. Environments. 2025; 12(9):298. https://doi.org/10.3390/environments12090298

Chicago/Turabian Style

Xu, Sutie, Jing Hu, Navreet Kaur Mahal, and Virginia L. Jin. 2025. "Assessment of Soil Organic Carbon in Different Ecosystems by Using Field, Lab, and Modeling Methods" Environments 12, no. 9: 298. https://doi.org/10.3390/environments12090298

APA Style

Xu, S., Hu, J., Mahal, N. K., & Jin, V. L. (2025). Assessment of Soil Organic Carbon in Different Ecosystems by Using Field, Lab, and Modeling Methods. Environments, 12(9), 298. https://doi.org/10.3390/environments12090298

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