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Glacial meltwater contributions to streams depend on watershed characteristics that impact water quantity and quality, with potential changes as glaciers continue to recede. The purpose of our study was to investigate the influence of glacier and bedrock controls on water chemistry in glacial streams, focusing on a range of small to large watersheds in Alaska. Southcentral Alaska provides an ideal study area due to diverse geologic characteristics and varying amounts of glacial coverage across watersheds. To investigate spatial and temporal variability due to glacial coverage and bedrock type, we analyzed water samples (n= 343) from seven watersheds over 2 years for major and trace element concentrations and water stable isotopes. We found variable water chemistry across the glacial rivers related to glacial coverage and the relative amount of metamorphic, sedimentary, and igneous bedrock. Some sites had elevated concentrations of harmful trace elements like As and U from glacier melt or groundwater. Longitudinal (upstream to downstream) variability was apparent within each river, with increasing inputs from tributaries, and groundwater altering the water chemistry relative to glacier meltwater contributions. The water chemistry and isotopic composition of river samples compared with endmember sources suggested a range from glacier-dominated to groundwater-dominated sites along stream transects. For example, water chemistry in the Knik and Matanuska rivers (with large contributing glaciers) was more influenced by glacier meltwater, while water chemistry in the Little Susitna River (with small glaciers) was more influenced by groundwater. Across all rivers, stream chemistry was controlled by glacier inputs near the headwaters and groundwater inputs downstream, with the water chemistry reflecting bedrock type. Our study provides a greater understanding of geochemical and hydrological processes controlling water resources in rapidly changing glacial watersheds. 

Abstract Estuaries are among the most productive ecosystems on Earth, yet they are at risk in high-latitude regions due to climate-driven effects on the connected terrestrial and marine realms. Northern Hemisphere warming exceeds the global average and accelerates the melting of glaciers. As a result, the magnitude of freshwater discharge into estuaries may increase during the peak in glacial meltwater, ultimately affecting the riverine flux of organic matter (OM) from the land to coastal environments and food webs within. We investigated the extent to which terrestrial OM subsidizes nearshore food webs in northern Gulf of Alaska watersheds and if differences in the relative proportion of terrestrial versus marine OM supporting these food webs are explained by watershed glacial cover and/or by seasonal glacial discharge regimes. A stable isotope mixing model was employed to determine the contribution of marine (phytoplankton, macroalgae) and terrestrial (vascular plant) sources to the diets of grazing/detritivore and filter/suspension-feeding coastal invertebrates at the outflows of watersheds of varying glacial influence and across three distinct discharge periods. Additionally, a distance-based redundancy analysis was conducted to investigate the effects of watershed-characteristic (e.g., slope, vegetation cover) sourcing and transport of terrestrial OM on consumer diets. The diets of both feeding groups were predominantly marine (> 90%) and varied little among estuarine study sites at watersheds of different glacial cover or glacial discharge periods. Our findings suggest that terrestrial OM is not readily used by nearshore food webs in this productive study system, presumably due to the high quantity and quality of available marine OM. 

Southwestern North America is currently experiencing a multidecadal megadrought, with severe consequences for water resources. However, significant uncertainty remains about 21st century precipitation changes in this semi-arid region. Paleoclimatic records are essential for both contextualizing current change, and for helping constrain the sensitivity of regional hydroclimate to large-scale global climate. In this paper, we present a new 2.8 Ma to present compound-specific isotopic record from Clayton Valley, the site of a long-lived paleolake in the southern Great Basin. Hydrogen and carbon isotopes from terrestrial plant leaf waxes provide evidence of past shifts in rainfall seasonality as well as ecosystem structure, and help contextualize the formation of this lithium-rich lacustrine basin. Our results suggest that regional hydroclimates underwent a substantial reorganization at the Plio-Pleistocene boundary, especially between 2.6 and 2.0 Ma. In this interval, a reduced latitudinal temperature gradient in the North Pacific likely resulted in a northward shift in storm tracks, and a reduction in winter rainfall over the southern Great Basin. This occurred against a background of increased summer rainfall and a greater accumulation of lithium in the lake basin. Our interpretation is corroborated by a compilation of Plio-Pleistocene north Pacific sea surface temperature records, as well as an isotope-enabled model simulation. Overall, these results suggest that past shifts in rainfall seasonality helped set the stage for the development and dessication of lithium-rich lacustrine deposits. 

Proteoforms, the different forms of a protein with sequence variations including post-translational modifications (PTMs), execute vital functions in biological systems, such as cell signaling and epigenetic regulation. Advances in top-down mass spectrometry (MS) technology have permitted the direct characterization of intact proteoforms and their exact number of modification sites, allowing for the relative quantification of positional isomers (PI). Protein positional isomers refer to a set of proteoforms with identical total mass and set of modifications, but varying PTM site combinations. The relative abundance of PI can be estimated by matching proteoform-specific fragment ions to top-down tandem MS (MS2) data to localize and quantify modifications. However, the current approaches heavily rely on manual annotation. Here, we present IsoForma, an open-source R package for the relative quantification of PI within a single tool. Benchmarking IsoForma's performance against two existing workflows produced comparable results and improvements in speed. Overall, IsoForma provides a streamlined process for quantifying PI, reduces the analysis time, and offers an essential framework for developing customized proteoform analysis workflows. The software is open source and available at https://github.com/EMSL-Computing/isoforma-lib. 

Abstract Because geostationary satellite (Geo) imagery provides a high temporal resolution window into tropical cyclone (TC) behavior, we investigate the viability of its application to short-term probabilistic forecasts of TC convective structure to subsequently predict TC intensity. Here, we present a prototype model that is trained solely on two inputs: Geo infrared imagery leading up to the synoptic time of interest and intensity estimates up to 6 h prior to that time. To estimate future TC structure, we compute cloud-top temperature radial profiles from infrared imagery and then simulate the evolution of an ensemble of those profiles over the subsequent 12 h by applying a deep autoregressive generative model (PixelSNAIL). To forecast TC intensities at hours 6 and 12, we input operational intensity estimates up to the current time (0 h) and simulated future radial profiles up to +12 h into a “nowcasting” convolutional neural network. We limit our inputs to demonstrate the viability of our approach and to enable quantification of value added by the observed and simulated future radial profiles beyond operational intensity estimates alone. Our prototype model achieves a marginally higher error than the National Hurricane Center’s official forecasts despite excluding environmental factors, such as vertical wind shear and sea surface temperature. We also demonstrate that it is possible to reasonably predict short-term evolution of TC convective structure via radial profiles from Geo infrared imagery, resulting in interpretable structural forecasts that may be valuable for TC operational guidance. Significance Statement This work presents a new method of short-term probabilistic forecasting for tropical cyclone (TC) convective structure and intensity using infrared geostationary satellite observations. Our prototype model’s performance indicates that there is some value in observed and simulated future cloud-top temperature radial profiles for short-term intensity forecasting. The nonlinear nature of machine learning tools can pose an interpretation challenge, but structural forecasts produced by our model can be directly evaluated and, thus, may offer helpful guidance to forecasters regarding short-term TC evolution. Since forecasters are time limited in producing each advisory package despite a growing wealth of satellite observations, a tool that captures recent TC convective evolution and potential future changes may support their assessment of TC behavior in crafting their forecasts.