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Abstract Previous research has examined individual factors contributing to wildfire risk, but the compounding effects of these factors remain underexplored. Here, we introduce the “Integrated Human-centric Wildfire Risk Index (IHWRI)” to quantify the compounding effects of fire-weather intensification and anthropogenic factors—including ignitions and human settlement into wildland—on wildfire risk. While climatic trends increased the frequency of high-risk fire-weather by 2.5-fold, the combination of this trend with wildland-urban interface expansion led to a 4.1-fold increase in the frequency of conditions conducive to extreme-impact wildfires from 1990 to 2022 across California. More than three-quarters of extreme-impact wildfires—defined as the top 20 largest, most destructive, or deadliest events on record—originated within 1 km from the wildland-urban interface. The deadliest and most destructive wildfires—90% of which were human-caused—primarily occurred in the fall, while the largest wildfires—56% of which were human-caused—mostly took place in the summer. By integrating human activity and climate change impacts, we provide a holistic understanding of human-centric wildfire risk, crucial for policy development. 

abstract: Farmers have time and again adopted new methods or technologies. However, recent increases in global temperatures and occurrences of extreme weather events, call for an urgency to address and reduce the risks associated with climate change. Irrigation is a key adaptation that reduces crop heat stress and enhances agricultural production. Alabama is considered water-rich but lately has experienced increased rainfall variability and temperature extremes. Various state-wide initiatives to increase irrigation have been implemented, but adoption remains limited. Existing studies have explored factors influencing irrigation uptake, but none have engaged in a state-level assessment of its adoption potential. In this study, we provide spatially explicit estimates of the potential to implement irrigation practices across the state. Moreover, we derive an irrigation adoption index map for Alabama to identify areas where implementation is more or less likely based on a multi-criteria analysis. The results highlight a large potential for expansion in areas that have high shares of existing irrigation. Such an analysis can enable targeted mobilization of resources towards areas where uptake is currently low but feasible through increased adaptation efforts. Additionally, these estimates can be further used to evaluate future water demands or conduct other regional analyses. 

Abstract This study investigates the influence of land surface processes on short-spell monsoonal heavy rainfall events under varying soil wetness conditions in India, using the Weather Research and Forecasting Model coupled with two land surface schemes: Noah and SLAB. To represent contrasting soil conditions, four rainfall events are chosen, two in onset (June) and two in active (August) months, during the Indian summer monsoon season. The results indicate that rainfall sensitivity differs notably between onset and active cases. Specifically, in onset, the SLAB overpredicts rainfall to the north of the storm compared to the Noah. The northward displacement of rainfall is attributed to the sensitivity of evapotranspiration to the preferential soil moisture regime in onset. Furthermore, the higher surface air saturation deficit in onset favors plant transpiration, resulting in increased boundary layer moisture. This contributes to enhanced moist static energy, thereby affecting potential vorticity and precipitation. In contrast, evapotranspiration sensitivity is modest during active months, under wet soil and lower surface air saturation deficit conditions. The study reveals the distinct soil moisture feedback mechanisms during the onset and active phases, through variations in evapotranspiration sensitivity. Variations in soil moisture and surface air saturation deficit in these phases play a crucial role in modulating evapotranspiration, which in turn affects precipitation. These findings underscore the importance of land surface initialization and land data assimilation in land–atmosphere interaction studies. 

This work demonstrates APCVD synthesis of stable 2D CrOCl, a magnetic oxyhalide for spintronics and quantum devices. It reveals controllable gas-phase growth, with characterization confirming high-quality CrOCl free from Cr₂O₃and oxidation. 

Evaporative Stress Index (ESI), also sometimes referred as Evaporative Stress Ratio (ESR), has been widely used as an indicator of vegetation evaporative stress, and is often used to track forest and agriculture droughts. Lower the stress, higher is the value of ESI or ESR. The goal of this study is to assess the suitability of these indices for tracking vegetation evaporative stress. As the dynamics of water loss from vegetation through transpiration (T) can be different than that of evapotranspiration (ET) from the ecosystem, it is hypothesized that ESI or ESR may not be sufficiently representative of the vegetation evaporative stress. Using eddy covariance flux tower data of 518 site years, distributed across 49-sites and 9 land covers globally, our findings reveal underestimation of vegetation evaporative stress by ESI during periods of high vapor pressure deficit (VPD) and overestimation during dry, low-VPD periods. The results highlight the need to improve representativeness of ESI for monitoring vegetation evaporative stress. Notably, this may entail accurate estimation of ecosystem T in systems lacking in-situ data, a challenge that warrants further attention. 

We investigated the formation of Schottky barriers at the interface between rare-earth tritelluride (RTe3) crystals and n-type silicon (n-Si) substrates. This study explores the rectifying characteristics of RTe3/n-Si junctions (R = Dy, Ho, Er) and their relation to the charge density wave (CDW) transition. Using the thermionic emission model, we analyzed current–voltage (I–V) measurements to obtain the Schottky barrier height (ϕSBH) and the ideality factor (η). The temperature dependence of the extracted ϕSBH and η reveals kink features near the CDW transition temperature. The Schottky–Mott model is employed to explain these kink features in the derivatives of ϕSBH and 1/η and attributes them to changes in the work function of RTe3 during the CDW transition. Our findings suggest that Schottky junctions can be utilized to probe the electronic states of RTe3, enabling potential RTe3 device applications in electronics and optoelectronics. 

The US corn area footprint has changed significantly since the 20th century, declining in the southeastern states while exhibiting an increase or stable variations in the Midwest. As harvested acreage directly impacts the total corn production, understanding the influencing factors is crucial. This study assesses the role of potential drivers on the contrasting trajectories of harvested corn acreage between midwestern and southeastern US. Profit acreage analysis reveals that antecedent profits/losses have a statistically significant influence on corn acreage changes, with southeastern US, which experienced more loss-making years, also experiencing more frequent reductions in corn acreage. The high number of loss-making years in the Southeast is primarily attributed to the region’s low corn yield, influenced by climate and other agro-environmental factors. Using a panel regression model, we find that the loss-making years in the Southeast could have reduced to fewer than 26 out of the considered 45 years, or almost similar to the average in the Midwest, by just increasing the irrigated corn area to 50 %, a realistic irrigated corn area fraction already achieved in several Georgia counties. This underscores the potential for early policy interventions like irrigation facilitation to sustain and expand cropped acreage. However, we also find that this would only be economically feasible with incentives for both the installation and sustained operation of irrigation infrastructure. 

Abstract Achieving large-scale, transformative climate change adaptations in agriculture while mitigating further climate impacts and supporting sustainable and equitable rural livelihoods is a grand challenge for society. Transformation of the agri-food system is necessary and inevitable, but the extent to which transformation can be intentionally guided toward desirable states remains unclear. We argue that instead of targeting leverage points in isolation, coordinated interventions multiple leverage points and their interactions are necessary to create broader system transformation towards more adaptive futures. Using the Southeastern U.S. as a case study, we conceptualize a way of doing transformation research in agri-food systems that integrates multiple theoretical and practical perspectives of how transformative pathways can be constructed from ‘chains’ of interacting leverage points. We outline several principles for transformative research; the core of which are participatory, transdisciplinary, and convergence research methods needed for articulating a shared vision. These principles embrace an action-oriented approach to research in which the act of assembling diverse networks of researchers, stakeholders, and community partners itself can activate community- and regional-level leverage points to scale-up changes. Finally, we present tangible examples of specific leverage points and their interactions targeted by agri-food systems interventions currently underway or planned. This work offers an ‘anticipatory’ vision for agri-food systems transformation research that recognizes the need to normatively create an enabling environment to build momentum toward shared visions of secure, equitable, and sustainable regional agri-food systems. 

Abstract Drought poses a major threat to agricultural production and food security. This study evaluates the changes in drought-induced crop yield loss risk for six crops (alfalfa, barley, corn, soybean, spring wheat, and winter wheat) between 1971–2000 and 1991–2020 across the contiguous US. Using a copula-based probabilistic framework, our results reveal a spatially heterogeneous change in yield risk to meteorological droughts, which varies with crop types. Regional analyses identify the largest temporal decline in yield risk in the Southeast and Upper Midwest, while the Northwest and South show an increase in risk. Among the considered anthropogenic and climatic drivers of crop productivity, changes in climatic variables such as high temperatures (e.g., killing degree days), vapor pressure deficit and precipitation show significantly stronger associations with changes in yield risk than irrigated area and nitrogen fertilizer application. Among the counties that observe drier drought events, only 55% exhibit an increase in crop yield loss risk due to drier droughts. The rest 45% show a decrease in yield loss risk due to mediation of favorable climatic and anthropogenic factors. Alarmingly, more than half (for barley and spring wheat), and one-third (for alfalfa, corn, soybean and winter wheat) of that the risk increasing regions have outsized influence on destabilizing national crop production. The findings provide valuable insights for policymakers, agricultural stakeholders, and decision-makers in terms of the potential ways and locations to be prioritized for enhancing local and national agricultural resilience and ensuring food security. 

Abstract Evapotranspiration (ET) is a critical process influencing energy, water, and carbon cycles. Numerous methods have been developed to estimate ET accurately and robustly across diverse scales. Many of these methods are constrained by reliance on remote sensing data, which is prone to gaps, or by the need for model calibration and training. This study evaluates the performance of the calibration‐free surface flux equilibrium theory (SFET) for ET estimation at 33 Ameriflux sites in the continental USA. SFET‐derived ET estimates are intercompared with widely used continental remote sensing products, including ECOsystem Spaceborne Thermal Radiometer Experiment on Space Station, Moderate Resolution Imaging Spectroradiometer, and SSEBop. Results indicate that SFET consistently outperforms these ET products. SFET's performance is found to be better under wet conditions and clear skies, with reduced accuracy under arid and high evaporative stress conditions. Overall, SFET exhibits significant potential for providing accurate, continuous, long‐term ET estimates, paving the way for operational application in uninstrumented regions over large scales.