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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 

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 

Abstract. Plant transpiration downregulation in the presence of soil water stress is a critical mechanism for predicting global water, carbon, and energy cycles. Currently, many terrestrial biosphere models (TBMs) represent this mechanism with an empirical correction function (β) of soil moisture – a convenient approach that can produce large prediction uncertainties. To reduce this uncertainty, TBMs have increasingly incorporated physically based plant hydraulic models (PHMs). However, PHMs introduce additional parameter uncertainty and computational demands. Therefore, understanding why and when PHM and β predictions diverge would usefully inform model selection within TBMs. Here, we use a minimalist PHM to demonstrate that coupling the effects of soil water stress and atmospheric moisture demand leads to a spectrum of transpiration responses controlled by soil–plant hydraulic transport (conductance). Within this transport-limitation spectrum, β emerges as an end-member scenario of PHMs with infinite conductance, completely decoupling the effects of soil water stress and atmospheric moisture demand on transpiration. As a result, PHM and β transpiration predictions diverge most for soil–plant systems with low hydraulic conductance (transport-limited) that experience high variation in atmospheric moisture demand and have moderate soil moisture supply for plants. We test these minimalist model results by using a land surface model at an AmeriFlux site. At this transport-limited site, a PHM downregulation scheme outperforms the β scheme due to its sensitivity to variations in atmospheric moisture demand. Based on this observation, we develop a new “dynamic β” that varies with atmospheric moisture demand – an approach that overcomes existing biases within β schemes and has potential to simplify existing PHM parameterization and implementation.