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Soil carbon has been measured for over a century in applications ranging from understanding biogeochemical processes in natural ecosystems to quantifying the productivity and health of managed systems. Consolidating diverse soil carbon datasets is increasingly important to maximize their value, particularly with growing anthropogenic and climate change pressures. In this progress report, we describe recent advances in soil carbon data led by the International Soil Carbon Network and other networks. We highlight priority areas of research requiring soil carbon data, including (a) quantifying boreal, arctic and wetland carbon stocks, (b) understanding the timescales of soil carbon persistence using radiocarbon and chronosequence studies, (c) synthesizing long-term and experimental data to inform carbon stock vulnerability to global change, (d) quantifying root influences on soil carbon and (e) identifying gaps in model–data integration. We also describe the landscape of soil datasets currently available, highlighting their strengths, weaknesses and synergies. Now more than ever, integrated soil data are needed to inform climate mitigation, land management and agricultural practices. This report will aid new data users in navigating various soil databases and encourage scientists to make their measurements publicly available and to join forces to find soil-related solutions. 

Abstract Light‐absorbing particles in atmospheric dust deposited on snow cover (dust‐on‐snow, DOS) diminish albedo and accelerate the timing and rate of snow melt. Identification of these particles and their effects is relevant to snow‐radiation modeling and water‐resource management. Laboratory‐measured reflectance of DOS samples from the San Juan Mountains (USA) were compared with DOS mass loading, particle sizes, iron mineralogy, carbonaceous matter type and content, and chemical compositions. Samples were collected each spring for water years 2011–2016, when individual dust layers had merged into one (all layers merged) at the snow surface. Average reflectance values of the six samples were 0.2153 (sd, 0.0331) across the visible wavelength region (0.4–0.7 μm) and 0.3570 (sd, 0.0498) over the full‐measurement range (0.4–2.50 μm). Reflectance values correlated inversely to concentrations of ferric oxide, organic carbon (1.4–10 wt.%), magnetite (0.05–0.13 wt.%), and silt (PM_63‐3.9;median grain sizes averaged 21.4 μm) but lacked correspondence to total iron and PM₁₀contents. Measurements of reflectance and Mössbauer spectra and magnetic properties indicated that microcrystalline hematite and nano‐size goethite were primarily responsible for diminished visible reflectance. Positive correlations between organic carbon and metals attributed to fossil‐fuel combustion, with observations from electron microscopy, indicated that some carbonaceous matter occurred as black carbon. Magnetite was a surrogate for related light‐absorbing minerals, dark rock particles, and contaminants. Similar analyses of DOS from other areas would help evaluate the influences of varied dust sources, wind‐storm patterns, and anthropogenic inputs on snow melt and water resources in and beyond the Colorado River Basin. 

Abstract In recent years, the availability of airborne imaging spectroscopy (hyperspectral) data has expanded dramatically. The high spatial and spectral resolution of these data uniquely enable spatially explicit ecological studies including species mapping, assessment of drought mortality and foliar trait distributions. However, we have barely begun to unlock the potential of these data to use direct mapping of vegetation characteristics to infer subsurface properties of the critical zone. To assess their utility for Earth systems research, imaging spectroscopy data acquisitions require integration with large, coincident ground‐based datasets collected by experts in ecology and environmental and Earth science. Without coordinated, well‐planned field campaigns, potential knowledge leveraged from advanced airborne data collections could be lost. Despite the growing importance of this field, documented methods to couple such a wide variety of disciplines remain sparse.We coordinated the first National Ecological Observatory Network Airborne Observation Platform (AOP) survey performed outside of their core sites, which took place in the Upper East River watershed, Colorado. Extensive planning for sample tracking and organization allowed field and flight teams to update the ground‐based sampling strategy daily. This enabled collection of an extensive set of physical samples to support a wide range of ecological, microbiological, biogeochemical and hydrological studies.We present a framework for integrating airborne and field campaigns to obtain high‐quality data for foliar trait prediction and document an archive of coincident physical samples collected to support a systems approach to ecological research in the critical zone. This detailed methodological account provides an example of how a multi‐disciplinary and multi‐institutional team can coordinate to maximize knowledge gained from an airborne survey, an approach that could be extended to other studies.The coordination of imaging spectroscopy surveys with appropriately timed and extensive field surveys, along with high‐quality processing of these data, presents a unique opportunity to reveal new insights into the structure and dynamics of the critical zone. To our knowledge, this level of co‐aligned sampling has never been undertaken in tandem with AOP surveys and subsequent studies utilizing this archive will shed considerable light on the breadth of applications for which imaging spectroscopy data can be leveraged.