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Abstract. One of the critical aspects in modelling soil organic carbon (SOC) predictions is the lack of access to soil information which is usually concentrated in regions of high agricultural interest. In Chile, most soil and SOC data to date is highly concentrated in 25 % of the territory that has intensive agricultural or forestry use. Vast areas beyond those forms of land use have few or no soil data available. Here, we present a new database of SOC for the country, which is the result of an unprecedented national effort under the frame of the Global Soil Partnership that help to build the largest database on SOC to date in Chile named “CHLSOC" comprising 13,612 data points. This dataset is the product of the compilation from numerous sources including unpublished and difficult to access data, allowing to fill numerous spatial gaps where no SOC estimates were publicly available before. The values of SOC compiled in CHLSOC range from 6×10−5 to 83.3 percent, reflecting the variety of ecosystems that exists in Chile. Profiting from the richness of geochemical, topographic and climatic variability in Chile, the dataset has the potential to inform and test models trying to predict SOC stocks and dynamics at larger spatial scales. Dataset available at https://www.doi.org/10.17605/OSF.IO/NMYS3 (Pfeiffer et al., 2019b).

Studies of hyper‐arid sites contribute to our understanding on how life adapted to extreme conditions. They are often used to further deduce implications for extraterrestrial biology by the so‐called analogue site‐approach. The Atacama Desert, Chile, is one of the most prominent analogue sites despite its neighboring productive ecosystems due to its hyper‐aridity and geochemical features resembling Martian environments. We hypothesize that many drivers of extremophile life in analogue sites are only mistakenly attributed to aridity alone, thus obscuring a clear view of the far more complex process interactions originating in nearby earthly ecosystems. To test this, we investigated 54 soil profiles up to 60 cm of soil depth along of four transects in the Atacama Desert, either running parallel (S‐N) or perpendicular (W‐E) to the Andes. Our objective was to reveal the processes controlling the formation of soil organic carbon (SOC) as the most reliable proxy for microbial life in order to understand the boundary conditions of life in extreme habitats. Further, we aimed at identifying analogue sites as uncompromised as possible by external influences of for example, vegetated or marine ecosystems. We found a mixture of influences driving habitable conditions on gradients perpendicular to the Andes, for example, fog and precipitation scavenging caused by altitudinal variations and differing proximity to the Pacific Ocean, while transects parallel to the Andes were much less biased by external factors. Our results show that studies on life under extreme conditions should clarify the explanatory strength of the investigated factors by a gradient study approach.

The major priority of research in the present day is to conserve the environment by reducing GHG emissions. A proposed solution by an expert panel from 195 countries meeting at COP 21 was to increase global SOC stocks by 0.4% year−1 to compensate for GHG emissions, the ‘4 per 1000′ agreement. In this context, the application of biocrusts is a promising framework with which to increase SOC and other soil functions in the soil–plant continuum. Despite the importance of biocrusts, their application to agriculture is limited due to: (1) competition with native microbiota, (2) difficulties in applying them on a large scale, (3) a lack of studies based on carbon (C) balance and suitable for model parameterization, and (4) a lack of studies evaluating the contribution of biocrust weathering to increase C sequestration. Considering these four challenges, we propose three perspectives for biocrust application: (1) natural microbiome engineering by a host plant, using biocrusts; (2) quantifying the contribution of biocrusts to C sequestration in soils; and (3) enhanced biocrust weathering to improve C sequestration. Thus, we focus this opinion article on new challenges by using the specialized microbiome of biocrusts to be applied in a new environment to counteract the negative effects of climate change.

Manganese (Mn) oxidation is performed through oxidative Mn-oxidizing bacteria (MnOxb) as the main bio-weathering mechanism for Mn(III/IV) deposits during soil formation. However, with an increase in temperature, the respiration rate also increases, producing Reactive Oxygen Species (ROS) as by-products, which are harmful to microbial cells. We hypothesize that bacterial ROS oxidize Mn (II) to Mn (III/IV) as a secondary non-enzymatic temperature-dependent mechanism for cell protection. Fourteen MnOxb were isolated from Antarctic soils under the global warming effect, and peroxidase (PO) activity, ROS, and Mn (III/IV) production were evaluated for 120 h of incubation at 4 °C, 15 °C, and 30 °C. ROS contributions to Mn oxidation were evaluated in Arthrobacter oxydans under antioxidant (Trolox) and ROS-stimulated (menadione) conditions. The Mn (III/IV) concentration increased with temperature and positively correlated with ROS production. ROS scavenging with Trolox depleted the Mn oxidation, and ROS-stimulant increased the Mn precipitation in A. oxydans. Increasing the Mn (II) concentration caused a reduction in the membrane potential and bacterial viability, which resulted in Mn precipitation on the bacteria surface. In conclusion, bacterial ROS production serves as a complementary non-enzymatic temperature-dependent mechanism for Mn (II) oxidation as a response in warming environments.

Mathematical-statistical problem on estimation of soil-forming processes. This paper raises a mathematical-statistical problem that finally can be found in any chronosequence of a specific Quaternary-based process (e.g. soil mass, clay content accumulation). The problem arises when interval-specific rates of a component f(t) are intended by dividing the stock by the given age t. The procedure implies that only an average specific rate is calculated in a linear form, for example when soil organic carbon often tends to an asymptotic end-value. For any other parameters (e.g. sedimentation rates, soil horizons thickness), the same holds true. The mathematical-statistical problem arises if the rates are derived using a linear calculation (individual stocks, f(t) divided by time, t) and then plotted as a function of time, in circumstances where there is no correlation between t and the components f(t).To illustrate this problem, we used a random generator function where the plot t versus f(t) are not correlated. We also give examples of the chronosequence approaches of soil organic carbon and soil mass, where, at a given point, the real specific rate corresponds to the slope (first derivative) of the obtained non-linear regression function. The random generator function for the plot t versus f(t) showed no significant relationship (R 2 = 0.0), but f(t)t −1 and t showed highly significant correlation (R 2 = 0.62). The error in calculating the component rate by dividing by time instead of using the derivative function when the processes are not linear ranged between 22% and > 500%. We conclude that non-independent variables plotted in a chronosequence can infer correlations even when they might not exist. Carefully observation is needed on the dataset when the time is involved, particularly in Quaternary-based studies, since the mass component not necessarily is related with time. Avoid in calculating the change of the mass component simply dividing by time, because an over-or under-estimation from real rate (obtained by derivative function) occurs when the process under study is not linear.