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Abstract The cardiovascular system functions under continuous cyclic mechanical stretch, with disruptions in mechanical and biochemical signals contributing to disease progression. In cardiovascular disorders, these disruptions activate cardiac fibroblasts (CFs) and promote cellular senescence, yet it remains unclear whether mechanical stimuli alone can initiate this phenotype. Here, primary murine CFs are exposed to uniaxial stretch, and systematically varied mechanical parameters assessed their role in senescence induction. Loss of stretch magnitude and increase in frequency, mimicking a pathologic hypertrophy and fibrosis, led to a senescence phenotype, identified through cell cycle arrest, decreased lamin B expression, and DNA damage. Mechanically‐induced CF senescence depends on p53/p21, whereas senescence triggered by oxidative stress or lamin A/C mutation proceeded via p16. Notably, mechanically‐induced premature senescence is accompanied by reduced levels of the nuclear envelope protein emerin. These findings demonstrate that altered mechanical signals are sufficient to trigger premature senescence and implicate compromised nuclear integrity in the underlying mechanism. 

Liquid crystalline elastomers (LCEs) exhibit reversible macroscopic shape changes in response to a temperature change. Mechanistically, the thermomechanical response of LCEs is associated with the thermotropic nature of the liquid crystalline units (i.e., mesogens) in the polymer network. Upon heating, the mesogen‐mesogen interaction in the LCE is disrupted, which transitions the organization of the polymer network from an ordered to a disordered state. The disruption in order affects the volumetric distribution of macromolecular chains in the polymer network and results in a large directional contraction along the alignment axis. Prior reports detail that the magnitude of actuation depends strongly on the connectivity of LC mesogens (i.e., main‐chain or pendant) within the network. In this study, pendant end‐on mesogens are introduced into a primarily main‐chain supramolecular LCE composition to further reduce crosslink density while preserving overall LC concentration. The introduction of pendant end‐on mesogens to supramolecular LCE compositions further improves thermomechanical properties by enhancing strain‐temperature coupling and reducing actuation temperatures. By systematically varying the concentrations of end‐on and supramolecular mesogens, direct relationships are established between mesogen composition, polymer architecture, and the resulting thermomechanical performance of LCEs. 

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 Large dendritic valley networks observed on Mars present a paleoclimate paradox. Geologic observations of Noachian units on Mars reveal a global extent of valley networks, which are believed to have been formed through incisions made by flowing water. However, most climate models predict global surface temperatures too far below the freezing point of water to support an active hydrological system. Conflicting observations and models have led to disparate theories for the climate of early Mars. In this work, we surveyed a large region of the cratered southern highlands to identify the location, elevation, and distribution of observed valley heads. These valley head locations were compared to landscape evolution simulations in which the spatial distribution of runoff was varied. The measured valley head distributions were compared to predictions from landscape evolution models for two end‐member hypotheses: (a) a warm wet climate that supported spatially distributed precipitation, and (b) surface runoff from ice cap margins, as envisioned by the Late Noachian Icy Highland model (LNIH). The observed elevation distribution in valley heads is consistent with the prediction of precipitation‐fed models, and inconsistent with models in which runoff derives exclusively from a single line‐source of high‐elevation ice‐melt. The results support the view that it is unlikely for ice caps to be the sole source of water and are consistent with the hypothesis that precipitation significantly contributed to valley network formation on ancient Mars. 

Abstract Soil microorganisms play outsized roles in nutrient cycling, plant health, and climate regulation. Despite their importance, we have a limited understanding of how soil microbes are affected by habitat fragmentation, including their responses to conditions at fragment edges, or “edge effects.” To understand the responses of soil communities to edge effects, we analyzed the distributions of soil bacteria, archaea, and fungi in an experimentally fragmented system of open patches embedded within a forest matrix. In addition, we identified taxa that consistently differed among patch, edge, or matrix habitats (“specialists”) and taxa that showed no habitat preference (“nonspecialists”). We hypothesized that microbial community turnover would be most pronounced at the edge between habitats. We also hypothesized that specialist fungi would be more likely to be mycorrhizal than nonspecialist fungi because mycorrhizae should be affected more by different plant hosts among habitats, whereas specialist prokaryotes would have smaller genomes (indicating reduced metabolic versatility) and be less likely to be able to sporulate than nonspecialist prokaryotes. Across all replicate sites, the matrix and patch soils harbored distinct microbial communities. However, sites where the contrasts in vegetation and pH between the patch and matrix were most pronounced exhibited larger differences between patch and matrix communities and tended to have edge communities that differed from those in the patch and forest. There were similar numbers of patch and matrix specialists, but very few edge specialist taxa. Acidobacteria and ectomycorrhizae were more likely to be forest specialists, while Chloroflexi, Ascomycota, and Glomeromycota (i.e., arbuscular mycorrhizae) were more likely to be patch specialists. Contrary to our hypotheses, nonspecialist bacteria were not more likely than specialist bacteria to have larger genomes or to be spore‐formers. We found partial support for our mycorrhizal hypothesis: arbuscular mycorrhizae, but not ectomycorrhizae, were more likely to be specialists. Overall, our results indicate that soil microbial communities are sensitive to edges, but not all taxa are equally affected, with arbuscular mycorrhizae in particular showing a strong response to habitat edges. In the context of increasing habitat fragmentation worldwide, our results can help inform efforts to maintain the structure and functioning of the soil microbiome. 

Abstract Changes in the properties of rainfall distributions at sub‐daily scales are key to assessing soil erosion rates under climate transition. However, such changes are difficult to detect and model, especially over landscape evolution timescales. In this contribution, we validate a new catchment‐scale landscape evolution model against event‐scale runoff and sediment records. Through multi‐century numerical experiments, we also show that changes in the sub‐daily rainfall distribution, like those observed under modern climate change, can increase soil erosion rates by 40% but cannot be accurately inferred from changes in the average event properties and total rainfall. We quantify erosion and topographic trajectories associated with plausible changes in the sub‐daily rainfall distribution, highlighting scenarios in which shifting tail properties impact landscape evolution, at times, contrary to expectations based on changes in total rainfall. 

Abstract The Ensemble Streamflow Prediction (ESP) framework combines a probabilistic forecast structure with process‐based models for water supply predictions. However, process‐based models require computationally intensive parameter estimation, increasing uncertainties and limiting usability. Motivated by the strong performance of deep learning models, we seek to assess whether the Long Short‐Term Memory (LSTM) model can provide skillful forecasts and replace process‐based models within the ESP framework. Given challenges inimplicitlycapturing snowpack dynamics within LSTMs for streamflow prediction, we also evaluated the added skill ofexplicitlyincorporating snowpack information to improve hydrologic memory representation. LSTM‐ESPs were evaluated under four different scenarios: one excluding snow and three including snow with varied snowpack representations. The LSTM models were trained using information from 664 GAGES‐II basins during WY1983–2000. During a testing period, WY2001–2010, 80% of basins exhibited Nash‐Sutcliffe Efficiency (NSE) above 0.5 with a median NSE of around 0.70, indicating satisfactory utility in simulating seasonal water supply. LSTM‐ESP forecasts were then tested during WY2011–2020 over 76 western US basins with operational Natural Resources Conservation Services (NRCS) forecasts. A key finding is that in high snow regions, LSTM‐ESP forecasts using simplified ablation assumptions performed worse than those excluding snow, highlighting that snow data do not consistently improve LSTM‐ESP performance. However, LSTM‐ESP forecasts that explicitly incorporated past years' snow accumulation and ablation performed comparably to NRCS forecasts and better than forecasts excluding snow entirely. Overall, integrating deep learning within an ESP framework shows promise and highlights important considerations for including snowpack information in forecasting. 

Abstract Following the largest magnetic storm in 20 years (10 May 2024), REPTile‐2 on NASA's CIRBE satellite identified two new radiation belts containing 1.3–5 MeV electrons aroundL = 2.5–3.5 and 6.8–20 MeV protons aroundL = 2. The region aroundL = 2.5–3.5 is usually devoid of relativistic electrons due to wave‐particle interactions that scatter them into the atmosphere. However, these 1.3–5 MeV electrons in this new belt seemed unaffected until a magnetic storm on 28 June 2024, perturbed the region. The long‐lasting nature of this new electron belt has physical implications for the dependence of electron wave‐particle interactions on energy, plasma density, and magnetic field strength. The enhancement of protons aroundL = 2 exceeded an order of magnitude between 6.8 and 15 MeV forming a distinct new proton belt that appears even more stable. CIRBE, after a year of successful operation, malfunctioned 25 days before the super storm but returned to functionality 1 month after the storm, enabling these discoveries. 

Abstract Historically, clumped isotope thermometry (T(∆₄₇)) of soil carbonates has been interpreted to represent a warm‐season soil temperature based dominantly on coarse‐grained soils. Additionally, T(∆₄₇) allows the calculation of the oxygen isotope composition of soil water (δ¹⁸O_w) in the past using the temperature‐dependent fractionation factor between soil water and pedogenic carbonate, but previous work has not measured δ¹⁸O_wvalues with which to compare to these archives. Here, we present clumped isotope thermometry of modern soil carbonates from three soils in Colorado and Nebraska, USA, that have a fine‐to‐medium grain size, contain clay, and are representative of many carbonate‐bearing paleosols preserved in the rock record. At two of the three sites, Briggsdale, CO and Seibert, CO, T(∆₄₇) overlaps with mean annual soil temperature (MAST), and the calculated δ¹⁸O_woverlaps within uncertainty with measured δ¹⁸O_wat carbonate bearing depths. At the third site, in Oglala National Grassland, NE, mean T(∆₄₇) is 8–11°C warmer than MAST, and the calculated δ¹⁸O_whas a significantly higher isotope value than any observations of δ¹⁸O_w. At all three sites, even in the fall season, δ¹⁸O_wvalues at carbonate bearing depths overlap with spring rainfall δ¹⁸O_w, and there is little to no evaporative enrichment of δ²H_wand δ¹⁸O_wvalues. These data challenge long‐held assumptions that all pedogenic carbonate records a warm‐season bias, and that δ¹⁸O_wat carbonate‐bearing depths is affected by evaporative enrichment.