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The stabilizing properties of mineral-organic carbon interactions have been studied in many soil environments (temperate soils, podzol lateritic soils, paddy soils). Recently, interest in their role in permafrost regions is increasing as permafrost was identified as a hotspot of change. In thawing ice-rich permafrost regions, such as the Yedoma domain, 327-466 Gt of frozen organic carbon (OC) is buried in deep sediments. Interactions between minerals and OC are important since the OC is located in close contact with the mineral matrix. Mineral surfaces and elements could mitigate recent and future greenhouse gas emissions through physical and/or physico-chemical protection of OC. The dynamic changes of redox and pH conditions associated with thermokarst lake formation and drainage, trigger metal-oxide dissolution and precipitation, likely influencing OC stabilization and microbial mineralization. However, the influence of thermokarst processes on mineral-OC interactions remains poorly constrained. In this study, we aim to characterize Fe, Mn, Al and Ca minerals and their potential protective role for OC. Total and selective extractions were used to assess the crystalline and amorphous oxides or complexed metal pools as well as the organic acids found within these pools. We analyzed four sediment cores from an ice-rich permafrost area in Central Yakutia, which were drilled i) in undisturbed Yedoma uplands, ii) beneath a recent lake formed within Yedoma deposits, iii) in a drained thermokarst lake basin, and iv) beneath a mature thermokarst lake from the early Holocene period. We find a decrease in the amount of reactive Fe, Mn, Al and Ca in the deposits upon lake formation (promoting reduction reactions), and this was largely balanced by an increase in the amount of reactive metals in the deposits upon lake drainage (promoting oxidation reactions). We demonstrate an increase in the metal:C molar ratio upon thermokarst process, which may indicate an increase of metal-C bindings and could provide a higher protective role against microbial mineralization of organic matter. Finally, we find that an increase in mineral-OC interactions corresponded to a decrease in CO2 and CH4 gas emissions upon thermokarst process. Mineral-OC interactions could mitigate greenhouse gas production from permafrost thaw as soon as lake drainage occurs.

Volcanic ashfall negatively affects crops, causing major economic losses and jeopardising the livelihood of farmers in developing countries where agriculture is at volcanic risk. Ash on plant foliage reduces the amount of incident light, thereby limiting photosynthesis and plant yield. An excessive ash load may also result in mechanical plant damages, such as defoliation and breakage of the stem and twigs. Characterising crop vulnerability to ashfall is critical to conduct a comprehensive volcanic risk analysis. This is normally done by describing the relationship between the ash deposit thickness and the corresponding reduction in crop yield, i.e. a fragility function. However, ash depth measured on the ground surface is a crude proxy of ash retention on plant foliage as this metrics neglects other factors, such as ash particle size, leaf pubescence and condition of humidity at leaf surfaces, which are likely to influence the amount of ash that stays on leaves.Here we report the results of greenhouse experiments in which we measured the percentage of leaf surface area covered by ash particles for one hairy leaf plant (tomato, Solanum lycopersicum L.) and one hairless leaf plant (chilli pepper, Capsicum annuum L.) exposed to simulated ashfalls. We tested six particle size ranges (≤ 90, 90-125, 125-250, 250-500, 500-1000, 1000-2000 µm) and two conditions of humidity at leaf surfaces, i.e. dry and wet. Each treatment consisted of 15 replicates. The tomato and chilli pepper plants exposed to ash were at the seven- and eight-leaf stage, respectively. An ash load of ~570 g m-2 was applied to each plant using a homemade ashfall simulator. We estimated the leaf surface area covered by ash from pictures taken before and immediately after the simulated ashfall. The ImageJ software was used for image processing and analysis.Our results show that leaf coverage by ash increases with decreasing particle size. Exposure of tomato and chilli pepper to ash ≤ 90 μm always led to ~90% coverage of the leaf surface area. For coarser particles sizes (i.e. between 125 and 500 µm) and dry condition at leaf surfaces, a significantly higher percentage (on average 29 and 16%) of the leaf surface area was covered by ash in the case of tomato compared to chilli pepper, highlighting the influence of leaf pubescence on ash retention. In addition, for particle sizes between 90 and 500 µm, wetting of the leaf surfaces prior to ashfall enhanced the ash cover by 19 ± 5% and 34 ± 11% for tomato and chilli pepper, respectively.These findings highlight that ash deposit thickness alone cannot describe the hazard intensity accurately. A thin deposit of fine ash (≤ 90 µm) will likely cover the entire leaf surface area, thereby eliciting a disproportionate effect on plant foliage compared to a thicker but coarser deposit. Similarly, for a same ash depth, leaf pubescence and humid conditions at the leaf surfaces will enhance ash retention, thereby increasing the likelihood of damage. Our study will contribute to improve the reliability of crop fragility functions used in volcanic risk assessment.

The Ecuadorian páramo, a neotropical ecosystem located in the upper Andes, acts as a constant source of high-quality water. It also stores significant amounts of C at the regional scale. In this region, volcanic ash soils sustain most of the paramo, and C storage results partly from their propensity to accumulate organic matter. Vegetation type is known to influence the balance between plant C inputs and soil C losses, ultimately affecting the soil organic C (SOC) content and stock. Tussock-forming grass (spp. Calamagrostis Intermedia; TU), cushion-like plants (spp. Azorella pedunculata; CU) and shrubs and trees (Polylepis stands) are commonly found in the páramo. Our understanding of SOC stocks and dynamics in the páramo remains limited, despite mounting concerns that human activities are increasingly affecting vegetation and potentially, the capacity of these ecosystems to store C.Here, we compare the organic C content and stock in soils under tussock-forming grass (spp. Calamagrostis Intermedia; TU) and soils under cushion-like plants (spp. Azorella pedunculata; CU). The study took place at Jatunhuayco, a watershed on the western slopes of Antisana volcano in the northern Ecuadorian Andes. Two areas of similar size (~0.35 km2) were surveyed. Fourty soil samples were collected randomly in each area to depths varying from 10 to 30 cm (A horizon) and from 30 to 75 cm (2Ab horizon). The soils are Vitric Andosols and the 2Ab horizon corresponds to a soil buried by the tephra fall from the Quilotoa eruption about 800 yr. BP. Sixteen intact soil samples were collected in Kopecky's cylinders for bulk density (BD) determination of each horizon.The average SOC content in the A horizon of the CU sites (9.4±0.5%) is significantly higher (Mann-Whitney U test, p2,respectively. These values are almost two times greater than the global average reported for Vitric Andosols (~8.2 kg/m2 ), but are lower than the estimates obtained for some wetter Andean páramos (22.5±5 kg/m2, 270% higher rainfall) from Ecuador. Our stock values further indicate that vegetation type has a limited effect on C storage in the young volcanic ash soils found at Jatunhuyaco. Despite a higher SOC content, the CU soils store a stock of organic C similar to that estimated for the TU soils. This likely reflects the comparatively lower BD of the former soils (650±100 vs. 840±30 kg/m3). Additional studies are needed in order to establish the vegetation-related factors driving the SOC content and stability in the TU and CU soils.

Permafrost are permanently frozen ground found in northern latitudes. Deposits in permafrost regions store significant amounts of carbon, estimated at 1400 - 1600 GtC. Yedoma deposits, defined as ice-rich permafrost, contribute significantly to this carbon stock. With global warming, Yedoma deposits are likely to undergo abrupt thaw leading to thermokarst collapse, resulting in the formation of Alas deposits. The organic carbon stored in these frozen deposits could be exposed to microbial mineralization upon thaw, be released as CO2 or CH4 in the atmosphere and amplify global warming. However, many uncertainties remain on the subject, including the role of mineral elements on the mineralization rate of this carbon. This study focuses on the evolution of the different forms of iron (i.e., crystalline, amorphous or complexed forms) during abrupt thaw of an ice-rich permafrost profile and its impact on organic carbon release. We analyzed four sediment cores from central Yakutia (Siberia) representative for progressive stages of thermokarst processes (i.e., Yedoma dry, Yedoma lake, Alas dry and Alas lake). The concentrations of total iron and iron selectively extracted using dithionite-citrate-bicarbonate (DCB), ammonium oxalate, and Na-pyrophosphate were measured. The organic carbon bound to these iron pools was also selectively extracted. We found i) a lower concentration of well-crystallized iron in Yedoma deposits that have already undergone abrupt thawing during the Holocene, and ii) a lower concentration of complexed carbon in samples underneath lakes, under anoxic conditions, compared to samples from drier areas (Figure 1).

Combining data originating from two or more geochemical surveys can be highly beneficial for establishing geochemical maps with increased resolution and/or coverage area. However this practice requires assessing the equivalence between datasets and, if needed, applying data leveling to correct possible biases between datasets. Here we propose two original methods for assessing equivalence and for leveling data when datasets contain records that are located within the same perimeter. The first method is designed for datasets that are similarly spatially distributed and is based on the Kolmogorov-Smirnov test and quantile regression. The second method does not require datasets to be similarly spatially distributed and is based on prior knowledge about the factors explaining the geochemical concentrations and on BLS (Bivariate Least Squares) regression. The scope of application, pros, cons and detailed practical recommendations are presented for each method. Both methods were applied to a case study involving Fe, V and Y datasets originating from two European geochemical mapping projects: the Geochemical Mapping of Agricultural Soils of Europe (GEMAS) and the Baltic Soil Survey (BSS). Both methods for assessing the equivalence and obtaining leveling equations yielded comparable results thereby illustrating their effectiveness and their feasibility.

Merging several already existing geochemical datasets can be highly profitable for obtaining geochemical maps with increased resolution and/or coverage area. However, this practice can lead to potential problems due to varying quality of the datasets and biases between datasets. In this paper, we present a general method which addresses these issues thereby making it possible to pool together multiple pre-existing datasets to produce one reliable dataset for geochemical mapping. The method first consists in performing four data quality checks that evaluate the relevance of existing data for the intended geochemical map. The checks pertain to georeferencing, temporal variability, spatial structure and presence of censored values. Next, a procedure is applied to detect biases between datasets and, where needed, to level the data using linear transformation. We then applied this method to a case study in Wallonia (Southern Belgium) involving the mapping of nickel in agricultural soils and create a new dataset based on multiple pre-existing geochemical datasets. We conclude by quantifying the new dataset's improved reliability for geochemical mapping thereby demonstrating the potential benefits of applying this proposed method to real-life situations.

As a result of the important role played by phosphorus (P) in surface water eutrophication, the susceptibility of soils to release P requires evaluation. The degree of phosphorus saturation, assessed by oxalate extraction (DPS(ox)), has been used as an indicator. However, most laboratories do not include DPS(ox) in routine soil tests because of cost and time. This study evaluates the suitability of the ammonium acetate extraction in the presence of EDTA (AAEDTA), the standard soil test P (STP) in Wallonia (Southern Belgium), to predict DPS(ox); we also compared it with the Mehlich 3 extraction. Ninety-three topsoil samples were collected in agricultural soils throughout Wallonia. Good correlations were found between the AAEDTA and the Mehlich 3 methods for P, Fe and Al (r = 0.85, 0.77 and 0.86, respectively). An exponential relationship was found between P(AAEDTA) and DPS(ox). Results of principal component analysis and regression demonstrated that STP can be used to predict DPS(ox) (r = 0.93) after logarithmic transformation. Soil test Al was also a good indicator of the P sorption capacity (PSC(ox)) of soils (r = 0.86). Including the clay fraction in regression equations only slightly improved the prediction of PSC(ox) (r = 0.90), while other readily available data (such as pH or organic carbon) did not significantly improve either DPS(ox) or PSC(ox) predictions.

Arctic warming and permafrost degradation are modifying northern ecosystems through changes in microtopography, soil water dynamics, nutrient availability, and vegetation succession. Upon permafrost degradation, the release of deep stores of nutrients, such as nitrogen and phosphorus, from newly thawed permafrost stimulates Arctic vegetation production. More specifically, wetter lowlands show an increase in sedges (as part of graminoids), whereas drier uplands favor shrub expansion. These shifts in the composition of vegetation may influence local mineral element cycling through litter production. In this study, we evaluate the influence of permafrost degradation on mineral element foliar stocks and potential annual fluxes upon litterfall. We measured the foliar elemental composition (Al, Ca, Fe, K, Mn, P, S, Si, and Zn) of ∼ 500 samples of typical tundra plant species from two contrasting Alaskan tundra sites, i.e., an experimental sedge-dominated site (Carbon in Permafrost Experimental Heating Research, CiPEHR) and natural shrub-dominated site (Gradient). The foliar concentration of these mineral elements was species specific, with sedge leaves having relatively high Si concentration and shrub leaves having relatively high Ca and Mn concentrations. Therefore, changes in the species biomass composition of the Arctic tundra in response to permafrost thaw are expected to be the main factors that dictate changes in elemental composition of foliar stocks and maximum potential foliar fluxes upon litterfall. We observed an increase in the mineral element foliar stocks and potential annual litterfall fluxes, with Si increasing with sedge expansion in wetter sites (CiPEHR), and Ca and Mn increasing with shrub expansion in drier sites (Gradient). Consequently, we expect that sedge and shrub expansion upon permafrost thaw will lead to changes in litter elemental composition and therefore affect nutrient cycling across the sub-Arctic tundra with potential implications for further vegetation succession.

With permafrost thaw, significant amounts of organic carbon (OC) previously stored in frozen deposits are unlocked and become potentially available for microbial mineralization. This is particularly the case in ice-rich regions such as the Yedoma domain. Excess ground ice degradation exposes deep sediments and their OC stocks, but also mineral elements, to biogeochemical processes. Interactions of mineral elements and OC play a crucial role for OC stabilization and the fate of OC upon thaw, and thus regulate carbon dioxide and methane emissions. In addition, some mineral elements are limiting nutrients for plant growth or microbial metabolic activity. A large ongoing effort is to quantify OC stocks and their lability in permafrost regions, but the influence of mineral elements on the fate of OC or on biogeochemical nutrient cycles has received less attention. The reason is that there is a gap of knowledge on the mineral element content in permafrost regions. Here, we use a portable X-ray fluorescence device (pXRF) to provide (i) the first large-scale Yedoma domain Mineral Concentrations Assessment (YMCA) dataset (https://doi.pangaea.de/10.1594/PANGAEA.922724; Monhonval et al., in review), and (ii) estimates of mineral element stocks in never thawed (since deposition) ice-rich Yedoma permafrost and previously thawed and partly refrozen Alas deposits. The pXRF method for mineral element quantification is non-destructive and offers a complement to the classical dissolution and measurement by optical emission spectrometry (ICP-OES) in solution. This allowed a mineral element concentration (Si, Al, Fe, Ca, K, Ti, Mn, Zn, Sr and Zr) assessment on 1292 sediment samples from the Yedoma domain with lower analytical effort and affordable costs relative to the classical ICP-OES method. pXRF measured concentrations were calibrated using standard alkaline fusion and ICP-OES measurements on a subset of 144 samples (R2 from 0.725 to 0.996). The results highlight that (i) the most abundant mineral element in the Yedoma domain is Si (2739 ± 986 Gt) followed by Al, Fe, K, Ca, Ti, Mn, Zr, Sr, and Zn, and that (ii) Al and Fe (598 ± 213 and 288 ± 104 Gt) are present in the same order of magnitude than OC (327–466 Gt).