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This dataset is part of a project studying the effects of wildfire on the Illilouette Creek Basin, a watershed within Yosemite National Park. Three temporary weather stations were installed under distinct types of vegetation cover. Each station measures air temperature, relative humidity, rainfall (the rain gage is not heated, so only the portion of snowfall that melts within the gage is measured), wind speed and direction, solar radiation, and both soil moisture and temperature at three depths. These measurements are recorded every 10 minutes, beginning in the summer of 2015 through June 2021. Snow depths and percent cover were estimated from time lapse imagery up to four times per day, and field measurements of snow depth and density were conducted up to two times each winter. The west-facing hillside where these stations are located most recently burned in 2004 and 2017 (Empire Fire). Photos are included of the stations both before and after the Empire Fire. For descriptions of the data format and units, see the included WeatherStnMetadata.xlsx file. 

Abstract Thinning silicon wafers via wet etching is a common practice in the microelectromechanical system (MEMS) industry to produce membranes and other structures Wang (Nano Lett 13(9): 4393–4398, 2013). Controlling the thickness of a membrane is a critical aspect to optimize the functionality of these devices. Our research specifically focuses on the production of bio-membranes for lung-on-a-chip (LoaC) applications. In our fabrication, it is crucial for us to determine the membranes’ thickness in a non-invasive way. This study aims to address this issue by attempting to develop a tool that uses the optical properties of light transmission through silicon to find a correlation with thickness. To find this correlation, we conducted a small experimental study where we fabricated ultra-thin membranes and captured images of the light transmission through these samples. This paper will report the correlation found between calculated average intensities of these images and measurements done using scanning electron microscopy (SEM). Graphical abstract 

On hillslopes with patchy vegetation cover, vegetation is a significant factor controlling surface hydraulic and hydrological properties.  Soil permeability is often greater within vegetated areas than in surrounding bare soil areas, leading to the redistribution of rainfall from bare, runoff-generating areas to permeable, vegetated areas. While many studies have examined the hydrological consequences of permeability contrasts, the hydrodynamic effects of greater surface roughness in vegetated patches compared to bare areas remain under-investigated. The role of roughness is not obvious: greater roughness in vegetated patches provides greater resistance to flow, slowing water movement and thus extending the time frame over which infiltration can occur. However, greater roughness may also cause partial blocking and flow diversion, reducing the volume of water traversing vegetated areas, a mechanism that could reduce rainfall redistribution to these sites. To differentiate the roles of spatially-varying roughness and permeability on rainfall redistribution, the two-dimensional Saint Venant Equations are employed to model the hydrologic outcomes of permeability and roughness contrasts under varying rainfall intensities.The simulations consider the dynamically interesting case of an idealized vegetated patch surrounded by runoff-generating unvegetated areas. The model results indicate that greater resistance causes flow diversion around vegetation. However, vegetative resistance only reduces rainfall redistributed to the vegetation under the specific conditions of low rainfall intensity and high soil permeability. Otherwise, prolonged ponding during the recession period, due to greater vegetative resistance, creates additional time for infiltration, compensating for increased flow diversion around the vegetation.  

Abstract Describing flow resistance from the properties of an underlying surface is a challenge in surface hydrology. Runoff models must specify a resistance formulation or “roughness scheme”—describing the functional relationship between flow resistance and flow depth/velocity—and its parameters. Uncertainty in runoff predictions derives from both the selected roughness scheme (e.g., Darcy Weisbach, Manning's, or laminar flow equations), and its parameterization with a roughness coefficient (e.g., Manning's ). Both choices are informed by model calibration to data, usually discharge, and, if available, velocity. In this study, a Saint Venant Equation‐based runoff model is calibrated to discharge and velocity data from 112 rainfall simulator experiments. The results are used to identify the optimal roughness scheme among four widely‐used options for each experiment, and to explore whether surface properties can be used to select the optimal roughness scheme and its coefficient. Among the tested roughness schemes, a transitional flow equation provided the best fit to the plurality of experiments. The most suitable roughness scheme for a given experiment was not related to measured surface properties. Regression models predicted the calibrated roughness coefficients with adjusted values between 0.48 and 0.54, depending on the roughness scheme used. Litter cover was the best predictor of the roughness coefficient, followed by soil cover and average canopy gap size. The results suggest that selection of an optimal roughness scheme based on surface properties alone remains difficult, but that once a scheme is selected, roughness coefficients can be estimated from surface properties. 

Abstract Observations show vulnerability segmentation between stems and leaves is highly variable within and between environments. While a number of species exhibit conventional vulnerability segmentation (stem leaf ), others exhibit no vulnerability segmentation and others reverse vulnerability segmentation (stem leaf ). We developed a hydraulic model to test hypotheses about vulnerability segmentation and how it interacts with other traits to impact plant conductance. We do this using a series of experiments across a broad parameter space and with a case study of two species with contrasting vulnerability segmentation patterns:Quercus douglasiiandPopulus trichocarpa. We found that while conventional vulnerability segmentation helps to preserve conductance in stem tissues, reverse vulnerability segmentation can better maintain conductance across the combined stem‐leaf hydraulic pathway, particularly when plants have more vulnerable s and have hydraulic segmentation with greater resistance in the leaves. These findings show that the impacts of vulnerability segmentation are dependent upon other plant traits, notably hydraulic segmentation, a finding that could assist in the interpretation of variable observations of vulnerability segmentation. Further study is needed to examine how vulnerability segmentation impacts transpiration rates and recovery from water stress. 

Abstract In the last decade, organ-on-a-chip technology has been researched as an alternative to animal and cell culture models (Buhidma et al. in NPJ Parkinson’s Dis, 2020; Pearce et al. in Eur Cells Mater 13:1–10, 2007; Huh et al. in Nat Protoc 8:2135–2157, 2013). While extensive research has focused on the biological functions of these chips, there has been limited exploration of functional materials that can accurately replicate the biological environment. Our group concentrated on a lung-on-a-chip featuring a newly fabricated porous silicon bio-membrane. This bio-membrane mimics the interstitial space found between epithelial and endothelial cells in vivo, with a thickness of approximately 1 μm (Ingber in Cell 164:1105–1109, 2016). This study aims to establish a fabrication method for producing a thin, uniform porous silicon membrane with a predictablereduced modulus. We conducted mechanical and morphological characterization using scanning electron microscopy and nanoindentation. A small, parametric study was conducted to determine the reduced modulus of the porous silicon and how it may relate to the morphological features of the membrane. We compare our results to other works. Graphical Abstract