Manganese (Mn) is a key cofactor in enzymes responsible for lignin decay (mainly Mn peroxidase), regulating the rate of litter degradation and carbon (C) turnover in temperate and boreal forest biomes.While soil Mn is mainly derived from bedrock, atmospheric Mn could also contribute to soil Mn cycling, especially within the surficial horizon, with implications for soil C cycling. However, quantification of the atmospheric Mn cycle, which comprises emissions from natural (desert dust, sea salts, volcanoes, primary biogenic particles, and wildfires) and anthropogenic sources (e.g. industrialization and land-use change due to agriculture) transport, and deposition into the terrestrial and marine ecosystem, remains uncertain. Here, we use compiled emission datasets for each identified source to model and quantify the atmospheric Mn cycle with observational constraints. We estimated global emissions of atmospheric Mn in aerosols (<10 µm in aerodynamic diameter) to be 1500 Gg Mn yr-1. Approximately 32% of the emissions come from anthropogenic sources. Deposition of the anthropogenic Mn shortened soil Mn “pseudo” turnover times in surficial soils about 1-m depth (ranging from 1,000 to over 10,000,000 years) by 1-2 orders of magnitude in industrialized regions. Such anthropogenic Mn inputs boosted the Mn-to-N ratio of the atmospheric deposition in non-desert dominated regions (between 5×10-5 and 0.02) across industrialized areas, but still lower than soil Mn-to-N ratio by 1-3 orders of magnitude. Correlation analysis revealed a negative relationship between Mn deposition and topsoil C density across temperate and (sub)tropical forests, illuminating the role of Mn deposition in these ecosystems.

In dry regions, millions of people depend on freshwater provided by the mountain cryosphere. Its likely depletion would make productive land-use management and access to water supply an even more urgent priority. Therefore water-security-oriented policies increasingly rely on solid information feedbacks for projections provided by Earth Sciences. Nevertheless, this type of research still has a lot to understand regarding headwater catchment hydrology, the top global “water towers.” For example, there are many theoretical and logistical uncertainties: “data deserts” in isolated areas, outdated legislation, or scarce research funding. Yet, one more important issue to highlight is the evolving nature of hydric resources, particularly where baselines have a large uncertainty and supply to many as in dry regions in the Andes or the Himalayas. The main concern here is the legislative inadequacy for evolving hydric resources as their baselines change. For example, groundwater within transboundary or paleowater aquifers could have unaccounted climate-sensitive recharge sources (e.g., permafrost thaw). Hence, the specific way of legislating mountain groundwater could turn ambiguous and useless. By reviewing particular legislation and landing the discussion on study cases in mountainous areas, we commit to showing the inadequacy of current legislation on hydric-potential evolution. Overall, water-security-oriented legislation will not assess and protect headwater catchments within the spectrum of different recharge processes throughout different hydroclimatic zones. First, the “evolving value” of specific catchments changes the nominal priority and purpose for protection. Secondly, a consistent failure to assess incommensurable (latent), climate-sensitive fractions of water supply structure is also found. Therefore, the policy recommendation is to use a hydric scale absorbing all nested processes necessary for hydric supply to persist, requiring defining a lifespan for legislation.

Data-model comparisons are common when addressing (paleo)climate questions. Many applications require deriving continuous surface fields of scalar variables from a set of irregularly distributed data points, typically for model validation against data or data-derived model input as initial or boundary conditions. While various interpolation techniques and interfaces exist, few can simultaneously: (1) interpolate across local to global spatial scales, (2) perform anisotropic interpolation using the spatial structure derived from the data instead of an assumed one, and (3) explicitly derive uncertainty in the interpolated fields due to both data density and measurement error. We present a standalone interpolation toolbox including a graphical user interface (GUI), which is aimed at the general earth science community. It uses a kriging algorithm whose distance metric is the geodesic on an oblate spheroid, be it the WGS-84 reference ellipsoid for applications on the surface of the Earth, or an equivalent ellipsoid with varying radii for interpolation on vertical levels above the surface. While kriging algorithms exist that perform interpolation on such non-Euclidean distances, they do not provide a check for conditionally negative semi-definiteness (CNSD) of the variogram matrix, which is a requisite for the kriging method. Since mathematical theory of kriging on spheroids or ellipsoids has not yet provided a set of authorized variance-distance functions, we incorporated a numerical check for CNSD condition for each data realization and variance-distance modeling scheme. The GUI will allow the user a high degree of customization. Preliminary results are promising, with robust results for isotropic interpolation. The derivation of CNSD variogram matrices for anisotropic interpolation remains the major challenge of the project. When completed, ClimAG-Krigger will provide the community with an easy-to-use, robust tool for anisotropic global kriging that will be specifically tailored for (paleo)climate applications.