Journal Paper Digests

Reading time ~6 minutes

Journal Paper Digests 2021 #16

  • Soil carbon dynamics during drying vs. rewetting: Importance of antecedent moisture conditions
  • Air-drying and long time preservation of soil do not significantly impact microbial community composition and structure
  • Organic carbon pools and organic matter chemical composition in response to different land uses in southern Brazil
  • Introducing digital twins to agriculture
  • A review of geostatistical simulation models applied to satellite remote sensing: Methods and applications

Soil carbon dynamics during drying vs. rewetting: Importance of antecedent moisture conditions

Soil moisture influences soil carbon dynamics, including microbial growth and respiration. The response of such ‘soil respiration’ to moisture changes is generally assumed to be linear and reversible, i.e. to depend only on the current moisture state. Current models thus do not account for antecedent soil moisture conditions when determining soil respiration or the available substrate pool. We conducted a laboratory incubation to determine how the antecedent conditions of drought and flood influenced soil organic matter (SOM) chemistry, bioavailability, and respiration. We sampled soils from an upland coastal forest, Beaver Creek, WA USA, and subjected them to drying and rewetting treatments. For the drying treatment, field moist soils were saturated and then dried to 75, 50, 35, and 5% saturation. In the rewetting treatment, field moist soils were air-dried and then rewet to 35, 50, 75, and 100% saturation. We measured respiration and water extractable organic carbon (WEOC) concentrations and used H-1-NMR and FT-ICR-MS to characterize the WEOC pool across the treatments. The drying vs. wetting treatment strongly influenced SOM bioavailability, as rewet soils (with antecedent drought) had greater WEOC concentrations and respiration fluxes compared to the drying soils (with antecedent flood). In addition, air-dry soils had the highest WEOC concentrations, and the NMR-resolved peaks showed a strong contribution of protein groups in these soils. Both NMR and FT-ICR-MS analyses indicated increased contribution of complex aromatic groups/molecules in the rewet soils, compared to the drying soils. We suggest that drying introduced organic matter into the WEOC pool via desorption of aromatic molecules and/or by microbial cell lysis, and this stimulated microbial mineralization rates. Our work indicates that even short-term shifts in antecedent moisture conditions can strongly influence soil C dynamics at the core scale. The predictive uncertainties in current soil models may be reduced by a more accurate representation of soil water and C persistence that includes a mechanistic and quantitative understanding of the impact of antecedent moisture conditions.

Air-drying and long time preservation of soil do not significantly impact microbial community composition and structure

To determine whether archived air-dried soils can be potentially used to explore microbial information upon sampling, we examined microbial community dynamics during soil air-drying and long time preserving. Fresh soils from five long-term fertilization treatments were sampled, air-dried, and preserved. Soil microbial community was characterized at specific intervals (from 0 h to 8192 h) by Illumina sequencing. The results showed that both prokaryotic and fungal community profiles did not substantially change during air-drying and long time preserving. The fertilization effects on microbial community structure could still be identified using the airdried soils. These findings suggest that air-drying and preserving exerts an almost negligible impact on soil microbial community profiles, laying the foundation for utilizing worldwide archived soils to investigate microbial community.

Organic carbon pools and organic matter chemical composition in response to different land uses in southern Brazil

The adoption of conservation agriculture (e.g., no-till system) has been recognized as pivotal to maintaining soil functions, but the potential of this system to enhance organic carbon (OC) quantity and quality and how this OC is stabilized in soils are not well established. In this study, we evaluated the effects of land-use types (native vegetation (NV) vs. no-till system (NT)) on OC stocks and on the chemical composition of organic matter (OM), and sought to understand the mechanisms that govern OC protection in the studied highly weathered soils. To achieve these objectives, we used an OC fractionation scheme in a combination of solid-state C-13 nuclear magnetic resonance (NMR) spectroscopic analyses in soils from six farms in southern Brazil. Our results showed smaller OC stocks (whole soil) under NT than under NV in four of the six sites. In addition, the OC stock differences between land-use types were larger in coarser textured soils and in those where conventional tillage was used before the adoption of NT. Among fractions, particulate organic carbon (POC) represented only 8% of the whole OC stock but was the fraction most affected by land-use type. In contrast, the humus organic carbon (HOC) fraction contributed 78% of the whole OC stock and was little altered by land-use type. Resistant organic carbon (ROC) represented 14% of the whole OC stock and it was altered by land-use type, demonstrating that this fraction is not as inert as previously thought. Overall, OM chemical composition was quite similar between land uses, with O-alkyl-C being the predominant C type. This labile component was further highly correlated with OC stock and silt + clay contents, indicating that the accumulation of OC in these highly weathered soils is mainly a response to the association between labile C compounds and minerals.

A review of geostatistical simulation models applied to satellite remote sensing: Methods and applications

Despite an ever-increasing number of spaceborne, airborne, and ground-based data acquisition platforms, remote sensing data are still often spatially incomplete or temporally irregular. While deterministic interpolation techniques are often used, they tend to create unrealistic spatial patterns and generally do not provide uncertainty quantification. Geostatistical simulation models are effective in generating an ensemble of realistic and equally probable realizations of an unmeasured phenomenon, allowing data uncertainty to be propagated. These models are commonly used in several fields of earth science, and in recent years, they have been applied widely to remotely sensed data. This study provides the first review of the applications of geostatistical simulation to remote sensing data. We review recent geostatistical simulation models relevant to satellite remote sensing data and discuss the characteristics and advantages of each approach. Finally, the applications of each geostatistical simulation model are categorized in different domains of natural sciences, including soil, vegetation, topography, and atmospheric science.

Introducing digital twins to agriculture

Digital twins are being adopted by increasingly more industries, transforming them and bringing new opportunities. Digital twins provide previously unheard levels of control over physical entities and help to manage complex systems by integrating an array of technologies. Recently, agriculture has seen several technological advancements, but it is still unclear if this community is making an effort to adopt digital twins in its operations. In this work, we employ a mixed-method approach to investigate the added-value of digital twins for agriculture. We examine the extent of digital twin adoption in agriculture, shed light on the concept and the benefits it brings, and provide an application-based roadmap for a more extended adoption. We report a literature review of digital twins in agriculture, covering years 2017-2020. We identify 28 use cases, and compare them with use cases in other disciplines. We compare reported benefits, service categories, and technology readiness levels to assess the level of digital twin adoption in agriculture. We distill the digital twin characteristics that can provide addedvalue to agriculture from the examined digital twin applications in agriculture and in other disciplines. Then, inspired by digital twin applications in other disciplines, we propose a roadmap for digital twins in agriculture, consisting of examples of growing complexity. We conclude this paper by identifying the distinctive characteristics of agricultural digital twins.

Journal Paper Digests

## Journal Paper Digests 2021 #21* Soil organic carbon estimation using VNIR-SWIR spectroscopy: The effect of multiple sensors and scanni...… Continue reading

Journal Paper Digests

Published on July 01, 2021

Journal Paper Digests

Published on June 24, 2021