Iodine Fractions in Soil and Their Determination

Iodine is an essential micronutrient for most living beings, including humans. Despite efforts through various iodine deficiency disorders elimination programs, such as salt iodization, this problem still persists. Sub-clinical deficiencies have often an endemic character, and they are characteristic to certain areas, where iodine is low or inaccessible in the geochemical environment. Thus, the monitoring of iodine speciation and fractionation—especially in soil, drinking water, and food—is needed. Therefore, the aim of this work is to review the iodine distribution in most common soil fractions which relate to its bioavailability; and briefly summarize the available methods for their identification in the environmental matrices as well.

Assessing Drought Vegetation Dynamics in Semiarid Grass- and Shrubland Using MESMA

Drought intensity and duration are expected to increase over the coming century in the semiarid western United States due to anthropogenic climate change. Historic data indicate that megadroughts in this region have resulted in widespread ecosystem transitions. Landscape-scale monitoring with remote sensing can help land managers to track these changes. However, special considerations are required: traditional vegetation indices such as NDVI often underestimate vegetation cover in semiarid systems due to short and multimodal green pulses, extremely variable rainfall, and high soil fractions. Multi-endmember spectral mixture analysis (MESMA) may be more suitable, as it accounts for both green and non-photosynthetic soil fractions. To determine the suitability of MESMA for assessing drought vegetation dynamics in the western US, we test multiple endmember selection and model parameters for optimizing the classification of fractional cover of green vegetation (GV), non-photosynthetic vegetation (NPV), and soil (S) in semiarid grass- and shrubland in central New Mexico. Field spectra of dominant vegetation species were collected at the Sevilleta National Wildlife Refuge over six field sessions from May–September 2019. Landsat Thematic Mapper imagery from 2009 (two years pre-drought), and Landsat Operational Land Imager imagery from 2014 (final year of drought), and 2019 (five years post-drought) was unmixed. The best fit model had high levels of agreement with reference plots for all three classes, with R2 values of 0.85 (NPV), 0.67 (GV), and 0.74 (S) respectively. Reductions in NPV and increases in GV and S were observed on the landscape after the drought event, that persisted five years after a return to normal rainfall. Results indicate that MESMA can be successfully applied for monitoring changes in relative vegetation fractions in semiarid grass and shrubland systems in New Mexico.

Bioavailable Nickel and Zinc in Polluted Soil Alter the Growth of Non-pioneer Trees in the Brazilian Atlantic Forest

Background and aimsThe Brazilian Atlantic forest has been affected by the deposition of Ni and Zn, among other heavy metals adsorbed from atmospheric particles, which can be incorporated into the soil. If available in the soil, they can be absorbed by plant roots. The study aimed at testing experimentally the hypotheses: 1) Ni and Zn depositions increase their bioavailable fractions in the soil; 2) pioneer tree species demonstrate a greater potential to absorb Ni and Zn from the soil and less growth changes than non-pioneer species.MethodsThe experiment was carried out with six pioneer and non-pioneer species native to the Atlantic Forest, grown for 90 days in soil from an urban fragment of the Atlantic Forest, according to the treatments: soil with balanced fertilization (control) and soil enriched with Ni, Zn and Ni+Zn. At the end, the concentrations of Ni and Zn were determined in four soil fractions (F1: soluble; F2: linked oxides/hydroxides; F3: organic matter: F4: residual metals) and in leaves, stems/branches and roots. Mobility factors in soil, concentration ratios between treatments and respective controls, translocation index and relative growth rate in height, leaf number and total biomass were also calculated.ResultsThe results showed that Ni and Zn concentrations increased significantly in the bioavailable soil fractions (F1, F2). The absolute content of Ni and Zn in the plants directly reflected the soil level in the available forms.ConclusionsThe metal accumulation in the species occurred regardless of the successional group to which they belonged. Non-pioneer species showed greater susceptibility to the metals.

Site-level simulations of measurable soil fractions with Millennial Version 2

<p>Soil carbon (C) models are used to predict C sequestration responses to climate and land use change. Yet, the soil models embedded in Earth system models typically do not represent processes that reflect our current understanding of soil C cycling, such as microbial decomposition, mineral association, and aggregation. Rather, they rely on conceptual pools with turnover times that are fit to bulk C stocks and/or fluxes. As measurements of soil fractions become increasingly available, soil C models that represent these measurable quantities can be evaluated more accurately. Here we present Version 2 (V2) of the Millennial model, a soil model developed to simulate C pools that can be measured by extraction or fractionation, including particulate organic C, mineral-associated organic C, aggregate C, microbial biomass, and dissolved organic C. Model processes have been updated to reflect the current understanding of mineral-association, temperature sensitivity and reaction kinetics, and different model structures were tested within an open-source framework. We evaluated the ability of Millennial V2 to simulate total soil organic C (SOC), as well as the mineral-associated and particulate fractions, using three soil fractionation data sets spanning a range of climate and geochemistry in Australia (N=495), Europe (N=176), and across the globe (N=730). Millennial V2 (RMSE = 1.98 – 4.76 kg, AIC = 597 – 1755) generally predicts SOC content better than the widely-used Century model (RMSE = 2.23 – 4.8 kg, AIC = 584 – 2271), despite an increase in process complexity and number of parameters. Millennial V2 reproduces between-site variation in SOC across a gradient of plant productivity, and predicts SOC turnover times similar to those of a global meta-analysis. Millennial V2 updates the conceptual Century model pools and processes and represents our current understanding of the roles that microbial activity, mineral association and aggregation play in soil C sequestration.</p>

Site-level simulations of measurable soil fractions with the Millennial V2 soil model

<p>Soil carbon (C) models are used to predict C sequestration responses to climate and land use change. Yet, the soil models embedded in Earth system models typically do not represent processes that reflect our current understanding of soil C cycling, such as microbial decomposition, mineral association, and aggregation. Rather, they rely on conceptual pools with turnover times that are fit to bulk C stocks and/or fluxes. As measurements of soil fractions become increasingly available, it is necessary for soil C models to represent these measurable quantities so that model processes can be evaluated more accurately. Here we present Version 2 (V2) of the Millennial model, a soil model developed in 2018 to simulate C pools that can be measured by extraction or fractionation, including particulate organic C, mineral-associated organic C, aggregate C, microbial biomass, and dissolved organic C. Model processes have been updated to reflect the current understanding of mineral-association, temperature sensitivity and reaction kinetics, and different model structures were tested within an open-source framework. We evaluated the ability of Millennial V2 to simulate total soil organic C (SOC), as well as the mineral-associated and particulate fractions, using three independent data sets of soil fractionation measurements spanning a range of climate and geochemistry in Australia (N=495), Europe (N=176), and across the globe (N=716). Considering RMSE and AIC as indices of model performance, site-level evaluations show that Millennial V2 predicts soil organic carbon content better than the widely-used Century model, despite an increase in process complexity and number of parameters. Millennial V2 also reproduces between-site variation in SOC across gradients of climate, plant productivity, and soil type. By including the additional constraints of measured soil fractions, we can predict site-level mean residence times similar to a global distribution of mean residence times measured using SOC/respiration rate under an assumption of steady state. The Millennial V2 model updates the conceptual Century model pools and processes and represents our current understanding of the roles that microbial activity, mineral association and aggregation play in soil C sequestration.</p>

Effects of climate change on soil organic matter chemical composition and carbon content in different physical fractions

<p>Soil organic matter (SOM) is composed of many pools with different properties (e.g. turnover times) which are generally used in biogeochemical models to predict carbon (C) dynamics. Physical fractionation methods are applied to isolate soil fractions that correspond to these pools. This allows the characterisation of chemical composition and C content of these fractions. There is still a lack of knowledge on how these individual fractions are affected by different climate change drivers, and therefore the fate of SOM remains elusive. We sampled soils from a multifactorial climate change experiment in a managed grassland in Austria four years after starting the experiment to investigate the response of SOM in physical soil fractions to temperature (eT: ambient and elevated by +3°C), atmospheric CO<sub>2</sub>-concentration (eCO<sub>2</sub>: ambient and elevated by +300 ppm) and to a future climate treatment (eT x eCO<sub>2</sub>: +3°C and + 300 ppm). A combination of slaking and wet sieving was used to obtain three size classes: macro-aggregates (maA, > 250 µm), micro-aggregates (miA, 63 µm – 250 µm) and free silt & clay (sc, < 63 µm). In both maA and miA, four different physical OM fractions were then isolated by density fractionation (using sodium polytungstate of ρ = 1.6 g*cm<sup>-3</sup>, ultrasonication and sieving): Free POM (fPOM), intra-aggregate POM (iPOM), silt & clay associated OM (SCaOM) and sand-associated OM (SaOM). We measured C and N contents and isotopic composition by EA-IRMS in all fractions and size classes and used a Pyrolysis-GC/MS approach to assess their chemical composition. For eCO<sub>2</sub> and eT x eCO<sub>2 </sub>plots, an isotope mixing-model was used to calculate the proportion of recent C derived from the elevated CO<sub>2 </sub>treatment. Total soil C and N did not significantly change with treatments.  eCO<sub>2</sub> decreased the relative proportion of maA-mineral-associated C and increased C in fPOM and iPOM. About 20% of bulk soil C was represented by the recent C derived from the CO<sub>2</sub> fumigation treatment. This significantly differed between size classes and density fractions (p < 0.001), which indicates inherent differences in OM age and turnover. Warming reduced the amount of new C incorporated into size classes. We found that each size class and fraction possessed a unique chemical fingerprint, but this was not significantly changed by the treatments. Overall, our results show that while climate change effects on total soil C were not significant after 4 years, soil fractions showed specific effects. Chemical composition differed significantly between size classes and fractions but was unaffected by simulated climate change. This highlights the importance to separate SOM into differing pools, while including changes to the molecular composition might not be necessary for improving model predictions.    </p>