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Abstract Climate change is increasing sulfate export and changing wetland extent in mountain regions. These changes may increase microbially mediated production of the neurotoxic substance methylmercury due to enhanced sulfate metabolism in mountain environments. Here, we assess methylmercury concentrations and formation rates across high-elevation wetlands in the Colorado Rocky Mountains. We also investigate sulfate controls on methylmercury production within subalpine peatlands by amending soils with sulfate to mimic increased stream export of sulfate from the alpine zone and measuring methylmercury formation rates for different sulfate treatments. We found that subalpine peatlands have statistically significant higher methylmercury concentrations and formation rates compared to alpine, mineral-soil wetlands. Methylmercury production in subalpine peatlands also increased significantly (p< 0.05) following sulfate additions; the highest rates occurred in sediments with intermediate extractable sulfate concentrations (∼0.60–1.4 mg sulfate g⁻¹dry soil). Our study is the first to identify soil sulfate-related thresholds for methylmercury production and sulfate-limitation of methylmercury production in subalpine peatlands. These findings highlight important linkages between climate-driven mineral weathering and mercury cycling in mountain regions globally. 

Abstract Ice thaw and enhanced bedrock weathering are increasing sulfate export in alpine streams, which may change sulfur (S) and other biogeochemical cycles in adjacent wetlands. We compared S and carbon (C) concentrations and sulfate reduction rates (SRRs) across three wetland types in the Colorado Rocky Mountains, USA: snowmelt‐fed wetlands (SFWs), periglacial solifluction lobes (PSLs), and subalpine wetlands (SAWs). We found that each wetland type had unique biogeochemical characteristics. Subalpine wetlands had the highest soil C (37.2 ± 8.7%C) and SRRs (29.3 ± 21 nmol mL⁻¹ soil day⁻¹) compared with SFWs and PSLs, which had lower %C and moderate to low SRRs, respectively. Subalpine wetlands accumulated little sulfate, whereas PSLs had high concentrations (0.04 ± 0.04 vs. 0.6 ± 1.4 mg S g⁻¹ dry soil respectively); SFWs had low sulfate concentrations (0.02 ± 0.01 mg S g⁻¹ dry soil). Sulfate‐S stable isotope data suggest different sources of S in the SFWs and PSLs: atmospheric and geologic, respectively. The data indicate that high C supports high SRRs in SAWs, whereas SRRs may be C‐limited and co‐limited by C and S in PSLs and SFWs, respectively. With climate warming, SAWs have the greatest potential to release more C to the atmosphere, SFWs will likely decrease in size and experience changes in plant community composition, and PSLs may be sources of acid rock drainage. These data demonstrate different biogeochemical fates of S and C in three wetland types present across alpine landscapes, and notable consequences for biogeochemical cycling as warming continues. 

Critical Zone (CZ) science investigates the interconnected processes occurring from the top of the vegetation canopy to the base of the groundwater. Recognizing the need to foster cross- disciplinary collaboration among early-career researchers (ECRs), graduate students organized two workshops in 2024 and 2025 aimed at building community, sharing research approaches, and discussing the future of CZ science. These workshops brought together participants from diverse disciplines, institutions, and career stages, and included research talks, structured discussions, and community-building activities. Survey results demonstrated increased confidence in cross-disciplinary collaboration and highlighted the value of supportive, in-person settings for networking and broadening scientific perspectives. Recommendations include expanding support for small, ECR-focused workshops and prioritizing institutional structures that sustain collaborative, transdisciplinary CZ research. 

Abstract Critical Zone (CZ) scientists have advanced understanding of Earth's surface through process‐based research that quantifies water, energy, and mass fluxes in predominantly undisturbed systems. However, the CZ is being increasingly altered by humans through climate and land use change. Expanding the scope of CZ science to include both human‐ and non‐human controls on the CZ is important for understanding anthropogenic impacts to Earth's surface processes and ecosystem services. Here, we share perspectives from predominantly U.S.‐based, early career CZ scientists centered around broadening the scope of CZ science to focus on societally relevant science through a transdisciplinary science framework. We call for increased training on transdisciplinary methods and collaboration opportunities across disciplines and with stakeholders to foster a scientific community that values transdisciplinary science alongside physical science. Here, we build on existing transdisciplinary research frameworks by highlighting the need for institutional support to include and educate graduate students throughout the research processes. We also call for graduate‐student‐led initiatives to increase their own exposure to transdisciplinary science through activities such as transdisciplinary‐focused seminars and symposiums, volunteering with local conservation groups, and participating in internships outside academia. 

Knot mosaics are a model of a quantum knot system. A knot mosaic is a m-by-n grid where each location on the grid may contain any of 11 possible tiles such that the final layout has closed loops. Oh et al. proved a recurrence relation of state matrices to count the number of m-by-n knot mosaics. Our contribution is to use ALLSAT solvers to count knot mosaics and to experimentally try different ways to encode the AT MOST ONE constraint in SAT. We plan to use our SAT method as a tool to list knot mosaics of interest for specific classes of knots. 

Signed networks (networks with positive and negative edges) commonly arise in various domains from molecular biology to social media. The edge signs -- i.e., the graph signage -- represent the interaction pattern between the vertices and can provide insights into the underlying system formation process. Generative models considering signage formation are essential for testing hypotheses about the emergence of interactions and for creating synthetic datasets for algorithm benchmarking (especially in areas where obtaining real-world datasets is difficult).In this work, we pose a novel Maximum-Likelihood-based optimization problem for modeling signages given their topology and showcase it in the context of gene regulation. Regulatory interactions of genes play a key role in the process of organism development, and when broken can lead to serious organism abnormalities and diseases. Our contributions are threefold: First, we design a new class of signage models for a given topology, and, based on the parameter setting, we discuss its biological interpretations for gene regulatory networks (GRNs). Second, we design algorithms computing the Maximum Likelihood -- depending on the parameter setting, our algorithms range from closed-form expressions to MCMC sampling. Third, we evaluated the results of our algorithms on synthetic datasets and real-world large GRNs. Our work can lead to the prediction of unknown gene regulations, novel biological hypotheses, and realistic benchmark datasets in the realm of gene regulation. 

Mathematical knots are interesting topological objects. Using simple arcs, lines, and crossings drawn on eleven possible tiles, knot mosaics are a representation of knots on a mosaic board. Our contribution is using SAT solvers as a tool for enumerating nontrivial knot mosaics. By encoding constraints for local knot mosaic properties, we computationally reduce the search space by factors of up to 6600. Our future research directions include encoding constraints for global properties and using parallel SAT techniques to attack larger boards.