Decreasing duration and occurrence of northern hemisphere ice cover due to recent climate warming is well-documented; however, biogeochemical dynamics underneath the ice are poorly understood. We couple time-series analyses of water column and sediment water interface (SWI) geochemistry with hydrodynamic data to develop a holistic model of iron (Fe), manganese (Mn), and phosphorus (P) behavior underneath the ice of a shallow eutrophic freshwater bay. During periods of persistent subfreezing temperatures, a highly reactive pool of dissolved and colloidal Fe, Mn, and P develops over time in surface sediments and bottom waters due to reductive dissolution of Fe/Mn(oxy)hydroxides below the SWI. Redox dynamics are driven by benthic O2 consumption, limited air-water exchange of oxygen due to ice cover, and minimal circulation. During thaw events, the concentration, distribution and size partitioning of all species changes, with the highest concentrations of P and "truly dissolved" Fe near the water column surface, and a relatively well-mixed "truly dissolved" Mn and "colloidal" Fe profile due to the influx of geochemically distinct river water and increased circulation. The partitioning and flux of trace metals and phosphorus beneath the ice is dynamic, and heavily influenced by climate-dependent physical processes that vary in both time and space.

Physical samples are foundational entities for research across biological, Earth, and environmental sciences. Data generated from sample-based analyses are not only the basis of individual studies, but can also be integrated with other data to answer new and broader-scale questions. Ecosystem studies increasingly rely on multidisciplinary team-science to study climate and environmental changes. While there are widely adopted conventions within certain domains to describe sample data, these have gaps when applied in a multidisciplinary context. In this study, we reviewed existing practices for identifying, characterizing, and linking related environmental samples. We then tested practicalities of assigning persistent identifiers to samples, with standardized metadata, in a pilot field test involving eight United States Department of Energy projects. Participants collected a variety of sample types, with analyses conducted across multiple facilities. We address terminology gaps for multidisciplinary research and make recommendations for assigning identifiers and metadata that supports sample tracking, integration, and reuse. Our goal is to provide a practical approach to sample management, geared towards ecosystem scientists who contribute and reuse sample data.

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Abstract. In water-stressed regions of the world, managed aquifer recharge (MAR), the process of intentionally recharging depleted aquifers, is an essential tool for combating groundwater depletion. Many groundwater-dependent regions, including the Central Valley in California, USA, are underlain by thick unsaturated zones (ca. 10 to 40 m thick), nested within complex valley-fill deposits that can hinder or facilitate recharge. Within the saturated zone, interconnected deposits of coarse-grained material (sands and gravel) can act as preferential recharge pathways, while fine-textured facies (silts and clays) accommodate the majority of the long-term increase in aquifer storage. However, this relationship is more complex within the vadose zone. Coarse facies can act as capillary barriers that restrict flow, and contrasts in matric potential can draw water from coarse-grained flow paths into fine-grained, low-permeability zones. To determine the impact of unsaturated-zone stratigraphic heterogeneity on MAR effectiveness, we simulate recharge at a Central Valley almond orchard surveyed with a towed transient electromagnetic system. First, we identified three outcomes of interest for MAR sites: infiltration rate at the surface, residence time of water in the root zone and saturated-zone recharge efficiency, which is defined as the increase in saturated-zone storage induced by MAR. Next, we developed a geostatistical approach for parameterizing a 3D variably saturated groundwater flow model using geophysical data. We use the resulting workflow to evaluate the three outcomes of interest and perform Monte Carlo simulations to quantify their uncertainty as a function of model input parameters and spatial uncertainty. Model results show that coarse-grained facies accommodate rapid infiltration rates and that contiguous blocks of fine-grained sediments within the root zone are >20 % likely to remain saturated longer than almond trees can tolerate. Simulations also reveal that capillary-driven flow draws recharge water into unsaturated, fine-grained sediments, limiting saturated-zone recharge efficiency. Two years after inundation, fine-grained facies within the vadose zone retain an average of 37 % of recharge water across all simulations, where it is inaccessible to either plants or pumping wells. Global sensitivity analyses demonstrate that each outcome of interest is most sensitive to parameters that describe the fine facies, implying that future work to reduce MAR uncertainty should focus on characterizing fine-grained sediments.