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In an increasingly flammable world, wildfire is altering the terrestrial carbon balance. However, the degree to which novel wildfire regimes disrupt biological function remains unclear. Here, we synthesize the current understanding of above- and belowground processes that govern carbon loss and recovery across diverse ecosystems. We find that intensifying wildfire regimes are increasingly exceeding biological thresholds of resilience, causing ecosystems to convert to a lower carbon-carrying capacity. Growing evidence suggests that plants compensate for fire damage by allocating carbon belowground to access nutrients released by fire, while wildfire selects for microbial communities with rapid growth rates and the ability to metabolize pyrolysed carbon. Determining controls on carbon dynamics following wildfire requires integration of experimental and modelling frameworks across scales and ecosystems.Fire severity is expected to increase as a result of warming. This will potentially amplify climate change due to its impact on the carbon cycle. This Review discusses ecosystem carbon loss and recovery following wildfire, and highlights where further work is needed to inform model predictions.

21st‐century modeling of greenhouse gas (GHG) emissions from bioenergy crops is necessary to quantify the extent to which bioenergy production can mitigate climate change. For over 30 years, the Century‐based biogeochemical models have provided the preeminent framework for belowground carbon and nitrogen cycling in ecosystem and earth system models. While monthly Century and the daily time‐step version of Century (DayCent) have advanced our ability to predict the sustainability of bioenergy crop production, new advances in feedstock generation, and our empirical understanding of sources and sinks of GHGs in soils call for a re‐visitation of DayCent's core model structures. Here, we evaluate current challenges with modeling soil carbon dynamics, trace gas fluxes, and drought and age‐related impacts on bioenergy crop productivity. We propose coupling a microbial process‐based soil organic carbon and nitrogen model with DayCent to improve soil carbon dynamics. We describe recent improvements to DayCent for simulating unique plant structural and physiological attributes of perennial bioenergy grasses. Finally, we propose a method for using machine learning to identify key parameters for simulating N2O emissions. Our efforts are focused on meeting the needs for modeling bioenergy crops; however, many updates reviewed and suggested to DayCent will be broadly applicable to other systems. This review evaluates current challenges with biogeochemical modeling of soil carbon dynamics, trace gas fluxes, and drought and age‐related impacts on bioenergy crop productivity. We propose coupling a microbial process‐based soil organic carbon and nitrogen model with DayCent, or other Century‐based biogeochemical models, to improve representation of soil carbon dynamics. We describe recent improvements to DayCent for simulating unique plant structural and physiological attributes of perennial bioenergy grasses. Finally, we propose a method for using machine learning to identify key parameters for simulating N2O emissions.

In the age of biofuel innovation, bioenergy crop sustainability assessment has determined how candidate systems alter the carbon (C) and nitrogen (N) cycle. These research efforts revealed how perennial crops, such as switchgrass, increase belowground soil organic carbon (SOC) and lose less N than annual crops, like maize. As demand for bioenergy increases, land managers will need to choose whether to invest in food or fuel cropping systems. However, little research has focused on the C and N cycle impacts of reverting purpose‐grown perennial bioenergy crops back to annual cropping systems. We investigated this knowledge gap by measuring C and N pools and fluxes over 2 years following reversion of a mature switchgrass stand to an annual maize rotation. The most striking treatment difference was in ecosystem respiration (ER), with the maize‐converted treatment showing the highest respiration flux of 2,073.63 (± 367.20) g C m−2 year−1 compared to the switchgrass 1,412.70 (± 28.72) g C m−2 year−1 and maize‐control treatments 1,699.16 (± 234.79) g C m−2 year−1. This difference was likely driven by increased heterotrophic respiration of belowground switchgrass necromass in the maize‐converted treatment. Predictions from the DayCent model showed it would take approximately 5 years for SOC dynamics in the converted treatment to return to conditions of the maize‐control treatment. N losses were highest from the maize‐converted treatment when compared to undisturbed switchgrass and maize‐control, particularly during the first conversion year. These results show substantial C and N losses occur within the first 2 years after reversion of switchgrass to maize. Given farmers are likely to rotate between perennial and annual crops in the future to meet market demands, our results indicate that improvements to the land conversion approach are needed to preserve SOC built up by perennial crops to maintain the long‐term ecological sustainability of bioenergy cropping systems. With biofuel innovation comes a need to sustainably manage this fuel source, and understanding how different bioenergy crop varieties can alter ecosystem carbon and nitrogen cycles is one way to achieve this. We quantified these changes by reverting a mature perennial switchgrass cropping system to an annual maize cropping system. Soil organic carbon built up under the perennial switchgrass was quickly consumed by enhanced heterotrophic respiration and nitrogen loss increased from the reverted system, with the reverted system resembling the reference maize treatment within 5 years.

Advancing our predictive understanding of bioenergy systems is critical to design decision tools that can inform which feedstock to plant, where to plant it, and how to manage its production to provide both energy and ecosystem carbon (C) benefits. Here, we lay the foundation for that advancement by integrating recent developments in the science of belowground processes in shaping the C cycle into a new bioenergy model, FUN‐BioCROP (Fixation and Uptake of Nitrogen‐Bioenergy Carbon, Rhizosphere, Organisms, and Protection). We show that FUN‐BioCROP can approximate the historical trajectory of soil C dynamics as natural ecosystems were successively converted into intensive agriculture and bioenergy systems. This ability relies in part on a novel tillage representation that mechanistically models tillage as a process that increases microbial access to C. Importantly, the impacts of tillage and feedstock choice also influence FUN‐BioCROP simulations of warming responses with no‐till perennial feedstocks, miscanthus, and switchgrass, having more C that is unprotected and susceptible to warming than tilled annual feedstocks like corn–corn–soybean. However, this susceptibility to warming is balanced by a greater potential for increases in belowground C allocation to enhance soil C stocks in perennial systems. Collectively, our model results highlight the importance of belowground processes in evaluating the ecosystem C benefits of bioenergy production. Bioenergy has the potential to help slow climate change. This potential relies on bioenergy being carbon neutral. To achieve neutrality, bioenergy crops must enhance carbon sequestration in soils. However, predictions of bioenergy impacts on soil carbon remain uncertain. We addressed this uncertainty by developing a predictive model that includes how plants fuel the activity of soil microbes and how tillage leads to soil carbon losses by increasing the ability of microbes to break down soil carbon. Our model aids predictions of the best combination of crop, management, and location that enhance bioenergy’s ability to achieve carbon neutrality.

Complex hemodynamics plays a role in the localization and development of atherosclerosis. Endothelial cells (ECs) lining blood vessel walls are directly influenced by various hemodynamic forces: simultaneous wall shear stress (WSS), normal stress, and circumferential stress/strain (CS) due to pulsatile flow, pressure, and diameter changes. ECs sense and transduce these forces into biomolecular responses that may affect intercellular junctions. In this study, a hemodynamic simulator was used to investigate the combined effects of WSS and CS on EC junctions with emphasis on the stress phase angle (SPA), the temporal phase difference between WSS and CS. Regions of the circulation with highly negative SPA, such as the coronary arteries and carotid bifurcation, are more susceptible to the development of atherosclerosis. At 5 h, expression of the tight junction (TJ) protein zonula occludens-1 was significantly higher for the atheroprotective SPA = 0° compared to the atherogenic SPA = −180° while the apoptosis rate was significantly higher for SPA = −180° than SPA = 0°. This decrease in TJ protein and increase in apoptosis and associated leaky junctions suggest a decreased junctional stability and a higher paracellular permeability for atherogenic macromolecules for the atherogenic SPA = −180° compared to SPA = 0°.

Although local wall shear stress (WSS) induced by blood flow has been implicated in atherogenesis, another prominent and often neglected hemodynamic feature, circumferential strain (CS) driven by pressure, is induced concurrently. To investigate endothelial cell (EC) responses to pathologic hemodynamics and their possible manipulation by pharmaceuticals, we simulated complete hemodynamic conditions comprised of simultaneous WSS and CS during treatment with conjugated linoleic acid (CLA), a known PPAR (-alpha and -gamma) activator and anti-atherogenic agent, on cultured EC and examined effects on gene and metabolite expression. Two hemodynamic conditions representative of distinct regions of the circulation, coronary arteries: pro-atherogenic (asynchronous WSS and CS) and straight descending aorta: non-atherogenic (synchronous WSS and CS), were applied to cultured EC during treatment with the nutraceutical CLA. Competitive-quantitative RT-PCR showed that asynchronous hemodynamics significantly reduced ( approximately 2-fold) eNOS and PPAR-gamma mRNA levels compared to synchronous hemodynamics at 5 and 12 h. ET-1 showed an opposite trend at 12 h. CLA treatment mitigated pro-atherogenic eNOS, ET-1, PPAR-alpha and -gamma mRNA expression profiles and NO and ET-1 secretion patterns during asynchronous hemodynamics. This study demonstrates the potential for a pharmacological treatment (CLA) to normalize pro-atherogenic gene expression profiles induced by hemodynamics inherent to the circulation.

Cellulosic bioenergy crops have potential to meet United States greenhouse gas (GHG) reduction targets and provide energy self-sufficiency. The Renewable Fuel Standard (RFS) calls for increasing the volume of cellulosic biofuel by 16 billion gallons while reducing lifecycle GHG emissions by 60%. Consideration of crop selection, location, and management strategies is critical to meet these goals and prevent environmental and economic costs from outweighing benefits. Depending on the productivity of selected land, 33 to >50 million hectares are required for cellulosic bioenergy production to meet RFS targets. Because a variety of factors are critical to a successful transition to cellulosic bioenergy, biogeochemical modeling is an essential tool to assessing potential scenarios. Models can evaluate potential yield, carbon pools and fluxes, and other GHG and nitrogen fluxes (e.g. nitrous oxide and methane emissions, nitrate leaching) with varying landscapes and management. The first chapter of this dissertation is a review on the current state of biogeochemical modeling and what improvements are necessary to evaluate the sustainability of varying crops, locations, and management to better inform economic models and policy decisions to meet RFS targets.Representation of soil carbon dynamics in most models is oversimplified with decay constant (i.e. first-order kinetics) driven decomposition and soil carbon pool structures that do not align with measurable pools or current understanding of soil carbon stabilization. Increasing microbial representation in models has shown to reduce uncertainty of predicted soil carbon. This is important not only from a GHG perspective, but also because soil carbon dynamics are intertwined with soil health attributes that increase landscape resiliency (i.e. soil fertility, water holding capacity, and erosion resistance). The second chapter integrates and evaluates microbial explicit mechanisms of decomposition into a new soil sub-model within a version of DayCent that was recently updated to encompass plant traits specific to perennial bioenergy crops. Specifically, the new soil sub-model uses reverse Michaelis-Menten kinetics that incorporate feedbacks between microbial biomass and decomposition rate to simulate soil carbon fluxes. Along with a modified decomposition function the Michaelis-Menten (MM) version of the soil model split the original active soil carbon pool into a live microbial biomass pool and a dead microbial biomass pool with more realistic routing of soil carbon through the pool structure. With these changes, the new MM soil sub-model improved daily representation of ecosystem carbon fluxes and simulated different ratios of protected to unprotected soil carbon in response to disturbance and climate compared to the original first order soil sub-model.With improvements to the soil model, DayCent will be better suited to evaluate yield, soil health, and GHG balances across landscapes. Identifying appropriate locations for a particular crop is paramount to meeting GHG atmospheric loading reductions, fulfilling socioeconomic needs, and achieving sustainable land use. In comparison to traditional agricultural crops, some bioenergy crops have physiological attributes (e.g. low N requirements, high belowground biomass, no tillage) that will outweigh the potential negatives if planted strategically. However, there is still much uncertainty and controversy surrounding where cellulosic bioenergy crops will be grown. Conversion of land to cellulosic bioenergy crops that is currently used for food production raises concerns about food-scarcity and sequential conversion of uncultivated land converted for food production (indirect landuse change) resulting in catastrophic losses of sequestered carbon and ecosystem services that will not be recouped through annual row crop production. Conversion of land to bioenergy crops that is not currently used for agricultural production also raises environmental concerns including the effects on GHG balances, biodiversity and ecosystem services, increasing reactive nitrogen through fertilizer, and water use. These potential side effects of conversion are thought to be largely avoided if bioenergy crops are produced on land that has been deemed marginal, or unproductive land that was used for agriculture in the recent past. Chapter three identifies current cropland that is likely to experience increased yield losses as a result of increasing climate variability (aka \"marginal land\") and analyzes the potential for growing more tolerant bioenergy crops using updated features of the DayCent model. Targeting low-lying, flood susceptible fields for conversion to switchgrass would provide a path to adapt agricultural practices to changing precipitation regimes, mitigate increasing climate variability, and reduce negative environmental impacts of corn production. Documented benefits of perennial grasses in riparian zones include reduced phosphorus and nitrate exports to waterways, decreased nitrous oxide emissions and increased soil carbon sequestration. In comparison to corn-soy production, I found that perennial bioenergy crops in selected flood prone areas will have 1) similar to higher yield, 2) higher soil carbon sequestration, and 3) lower GHG emissions and nitrate exports in flood prone areas because of lower risk to losses attributed to flooding, higher belowground biomass, decreased erosion, and greater productivity. Lower rates of nitrate leaching and nitrous oxide emissions are expected because switchgrass does not require fertilization.

Forests have an important role in the global carbon cycle, are a known regulator of climate, and are valued globally for the ecosystem services they provide to society. It is critical to improve our understanding about the exchange of carbon dioxide between forest ecosystems and Earth’s atmosphere. Specifically, there is a need for improved mechanistic understanding of the component fluxes of soil respiration (Rs): autotrophic respiration (Ra; roots and associated mycorrhizae) and heterotrophic respiration (Rh; free-living soil microbes and soil fauna involved in decomposition). We examined the responses and relative contributions of these components to manipulated soil moisture. We found that heterotrophic respiration significantly responds to moisture additions regardless of season while autotrophic respiration did not. We also found that widely used and accepted methods for survey measurements (versus automated) were not sufficient to build relationships with abiotic factors for diurnal, monthly, and annual scaling, thus eliminating commonly used gap-filling procedures. Because survey measurements are often used to validate model results, it is critical that they be done over varying time periods (some diurnal) and be paired with automated measurements. When comparing our experimental data to modeled results, we found that DayCent, a daily time-step process-based biogeochemical model, underestimates annual heterotrophic respiration by several magnitudes compared to our temperate mixed conifer forest site. This is likely because DayCent, like most traditional ecosystem models, simulates decomposition through first order kinetics which inadequately represents microbial processes. Recent research has found that including microbial mechanisms explains 20 percent more spatial heterogeneity. We manipulated the DayCent heterotrophic respiration model to include a more mechanistic representation of microbial dynamics and compared the new model with our continuous and survey observations. By using a more representative and fully calibrated model of soil carbon dynamics, we are better able to predict feedbacks between climate and soil carbon pools to inform decisions and provide benefits to society through improvements to ecosystem modeling.

Complex hemodynamics play a role in the localization and development of atherosclerosis. Endothelial cells (ECs) lining blood vessel walls are directly influenced by various hemodynamic forces: simultaneous wall shear stress (WSS), normal stress, and circumferential strain (CS) due to pulsatile flow, pressure, and diameter changes. As such, ECs may sense and transduce these forces into biomolecular responses at intercellular junctions. A hemodynamic simulator is used to investigate the combined effects of WSS and CS on EC junctions with emphasis on the stress phase angle (SPA), the temporal phase difference between WSS and CS. Regions of the circulation with highly negative SPA, such as the coronary arteries and carotid bifurcation, are more susceptible to the development of atherosclerosis. At 5 hours, zonula occludens-1 relative protein expression was significantly higher for the atheroprotective SPA = 0° compared to the atherogenic SPA = -180° while apoptosis was significantly higher for SPA = -180° than SPA = 0°. This decrease in tight junction protein and increase in cell turnover, and thus leaky junction presence, may indicate a decreased junctional stability and a higher paracellular permeability for the atherogenic SPA = -180° than for SPA = 0°. Meanwhile, at 12 hours, protein expression levels and mitosis were not significantly different between SPA = -180° and SPA = 0°. Finally, changes in cell elongation and alignment were negligible at these time points. Additionally, using a parallel plate flow chamber, the effects of short- and long-term exposure of ECs to WSS were examined for junctional markers as ECs remodel and align in the direction of flow over time. Indeed, ECs exposed to WSS for 24 hours significantly increased the alignment and elongation while significantly decreasing mitosis.