Search for: All records

Abstract Flash droughts are rapidly developing subseasonal climate extreme events that are manifested as suddenly decreased soil moisture, driven by increased evaporative demand and/or sustained precipitation deficits. Over each climate region in the contiguous United States (CONUS), we evaluated the forecast skill of weekly root-zone soil moisture (RZSM), evaporative demand (ET_o), and relevant flash drought (FD) indices derived from two dynamic models [Goddard Earth Observing System model V2p1 (GEOS-V2p1) and Global Ensemble Forecast System version 12 (GEFSv12)] in the Subseasonal Experiment (SubX) project between years 2000 and 2019 against three reference datasets: Modern-Era Retrospective Analysis for Research and Applications version 2 (MERRA-2), North American Land Data Assimilation System, phase 2 (NLDAS-2), and GEFSv12 reanalysis. The ET_oand its forcing variables at lead week 1 have moderate-to-high anomaly correlation coefficient (ACC) skill (∼0.70–0.95) except downwelling shortwave radiation, and by weeks 3–4, predictability was low for all forcing variables (ACC < 0.5). RZSM (0–100 cm) for model GEFSv12 showed high skill at lead week 1 (∼0.7–0.85 ACC) in the High Plains, West, Midwest, and South CONUS regions when evaluated against GEFSv12 reanalysis but lower skill against MERRA-2 and NLDAS-2 and ACC skill are still close to 0.5 for lead weeks 3–4, better than ET_oforecasts. GEFSv12 analysis has not been evaluated against in situ observations and has substantial RZSM anomaly differences when compared to NLDAS-2, and our analysis identified GEFSv12 reforecast prediction limit, which can maximally achieve ACC ∼0.6 for RZSM forecasts between lead weeks 3 and 4. Analysis of major FD events reveals that GEFSv12 reforecast inconsistently captured the correct location of atmospheric and RZSM anomalies contributing to FD onset, suggesting the needs for improving the dynamic models’ assimilation and initialization procedures to improve subseasonal FD predictability. Significance StatementFlash droughts are rapidly developing climate extremes which reduce soil moisture through enhanced evaporative demand and precipitation deficits, and these events can have large impacts on the ecosystem and crop health. We evaluated the subseasonal forecast skill of soil moisture and evaporative demand against three reanalysis datasets and found that evaporative demand skill was similar between forecasts and reanalyses while soil moisture skill is dependent on the reference dataset. Skill of evaporative demand decreases rapidly after week 1, while soil moisture skill declines more slowly after week 1. Case studies for the 2012, 2017, and 2019 United States flash droughts identified that forecasts could capture rapid decreases in soil moisture in some regions but not consistently, implying that long-lead forecasts still need improvements before being used in early warning systems. Improvements in flash drought predictability at longer lead times will require less biased initial conditions, better model parameterizations, and improved representations of large-scale teleconnections. 

Abstract Flavobacterium covaeand virulentAeromonas hydrophilaare prevalent bacterial pathogens within the US catfish industry that can cause high mortality in production ponds. An assessment of in vivo bacterial coinfection with virulentA. hydrophila(ML09‐119) andF. covae(ALG‐00‐530) was conducted in juvenile channel catfish (Ictalurus punctatus). Catfish were divided into seven treatments: (1) mock control; (2) and (3) high and low doses of virulentA. hydrophila; (4) and (5) high and low doses ofF. covae; (6) and (7) simultaneous challenge with high and low doses of virulentA. hydrophilaandF. covae. In addition to the mortality assessment, anterior kidney and spleen were collected to evaluate immune gene expression, as well as quantify bacterial load by qPCR. At 96 h post‐challenge (hpc), the high dose of virulentA. hydrophilainfection (immersed in 2.3 × 10⁷ CFU mL⁻¹) resulted in cumulative percent mortality (CPM) of 28.3 ± 9.5%, while the high dose ofF. covae(immersed in 5.2 × 10⁶ CFU mL⁻¹) yielded CPM of 23.3 ± 12.9%. When these pathogens were delivered in combination, CPM significantly increased for both the high‐ (98.3 ± 1.36%) and low‐dose combinations (76.7 ± 17.05%) (p < .001). Lysozyme activity was found to be different at 24 and 48 hpc, with the high‐dose vAh group demonstrating greater levels than unexposed control fish at each time point. Three proinflammatory cytokines (tnfα,il8,il1b) demonstrated increased expression levels at 48 hpc. These results demonstrate the additive effects on mortality when these two pathogens are combined. The synthesis of these mortality and health metrics advances our understanding of coinfections of these two important catfish pathogens and will aid fish health diagnosticians and channel catfish producers in developing therapeutants and prevention methods to control bacterial coinfections. 

Abstract Understanding contributions of climate and management intensifications to crop yield trends is essential to better adapt to climate changes and gauge future food security. Here we quantified the synergistic contributions of climate and management intensifications to maize yield trends from 1961 to 2017 in Iowa (United States) using a process-based modeling approach with a detailed climatic and agronomic observation database. We found that climate (management intensifications) contributes to approximately 10% (90%), 26% (74%), and 31% (69%) of the yield trends during 1961–2017, 1984–2013, and 1982–1998, respectively. However, the climate contributions show substantial decadal or multi-decadal variations, with the maximum decadal yield trends induced by temperature or radiation changes close to management intensifications induced trends while considerably larger than precipitation induced trends. Management intensifications can produce more yield gains with increased precipitation but greater losses of yields with increased temperature, with extreme drought conditions diminishing the yield gains, while radiation changes have little effect on yield gains from management intensifications. Under the management condition of recent years, the average trend at the higher warming level was about twice lower than that at the lower warming level, and the sensitivity of yield to warming temperature increased with management intensifications from 1961 to 2017. Due to such synergistic effects, management intensifications must account for global warming and incorporate climate adaptation strategies to secure future crop productions. Additional research is needed to understand how plausible adaptation strategies can mitigate synergistic effects from climate and management intensifications. 

Abstract Flash droughts are recently recognized subseasonal extreme climate phenomena, which develop with rapid onset and intensification and have significant socio‐environmental impacts. However, their historical trends and variability remain unclear largely due to the uncertainty associated with existing approaches. Here we comprehensively assessed trends, spatiotemporal variability, and drivers of soil moisture (SM) and evaporative demand (ED) flash droughts over the contiguous United States (CONUS) during 1981–2018 using hierarchical clustering, wavelet analysis, and bootstrapping conditional probability approaches. Results show that flash droughts occur in all regions in CONUS with Central and portions of the Eastern US showing the highest percentage of weeks in flash drought. ED flash drought trends are significantly increasing in all regions, while SM flash drought trends were relatively weaker across CONUS, with small significant increasing trends in the South and West regions and a decreasing trend in the Northeast. Rising ED flash drought trends are related to increasing temperature trends, while SM flash drought trends are strongly related to trends in weekly precipitation intensity besides weekly average precipitation and evapotranspiration. In terms of temporal variability, high severity flash droughts occurred every 2–7 years, corresponding with ENSO periods. For most CONUS regions, severe flash droughts occurred most often during La Niña and when the American Multidecadal Oscillation was in a positive phase. Pacific Decadal Oscillation negative phases and Artic Oscillation positive phases were also associated with increased flash drought occurrences in several regions. These findings may have implications for informing long‐term flash drought predictions and adaptations. 

Abstract Coronavirus Disease 2019 (COVID‐19) is spreading around the world, and the United States has become the epicenter of the global pandemic. However, little is known about the causes behind the large spatial variability of the COVID‐19 incidence. Here we use path analysis model to quantify the influence of four potential factors (urban vegetation, population density, air temperature, and baseline infection) in shaping the highly heterogeneous transmission patterns of COVID‐19 across the United States. Our results show that urban vegetation can slow down the spread of COVID‐19, and each 1% increase in the percentage of urban vegetation will lead to a 2.6% decrease in cumulative COVID‐19 cases. Additionally, the mediating role of urban vegetation suggests that urban vegetation could reduce increases in cumulative COVID‐19 cases induced by population density and baseline infection. Our findings highlight the importance of urban vegetation in strengthening urban resilience to public health emergencies. 

Effective science communication and stakeholder engagement are crucial skills for climate scientists, yet formal training in these areas remains limited in graduate education. The National Science Foundation Research Traineeship (NRT) at Auburn University (AU) addresses this gap through an innovative program combining science communication training with co-production approaches to enhance climate resiliency of built, natural, and social systems within the Southeastern United States (US). This paper evaluates the effectiveness of two novel graduate-level courses: one focused on science communication for non-technical audiences and another combining co-production methods with practical internship experience. Our research employed a mixed-methods approach, including a comprehensive analysis of course catalogs from 146 research-intensive universities and qualitative assessment of student experiences through surveys and descriptive exemplars. Analysis revealed that AU’s NRT program is unique among peer institutions in offering both specialized science communication training and co-production internship opportunities to graduate students across departments. Survey data from 11 program participants and detailed case studies of three program graduates demonstrated significant professional development benefits. Key outcomes included enhanced stakeholder engagement capabilities, improved science communication skills, and better preparation for both academic and non-academic careers. These findings suggest that integrating structured science communication training with hands-on co-production experience provides valuable preparation for climate scientists. The success of AU’s program model indicates that similar curriculum structures could benefit graduate programs nationwide, particularly in preparing students to effectively communicate complex scientific concepts to diverse audiences and engage with stakeholders in climate resilience efforts. 

Active learning and science communication have previously been separated in the literature. A science communication course was developed for graduate students within a Geosciences department to educate students on how to communicate about the research they are completing while pursuing their degree. This course used active learning techniques throughout the education of the material to engage students. This article aids in bridging the gap between active learning and science communication in this graduate level science communication course. The initial premise of this study was to see how graduate students connected using active learning techniques to enhance their science communication. However, through class observations and one-on-one interviews, it was found that students did not realize the methods that were being used in class for instruction were active learning techniques. Students were not connecting the dots with the information that they were learning about communication was given to them in active learning formats. Those active learning formats could also be used to enhance their own communication techniques when discussing the research that is being conducted. Conclusions from this work generate methods of how active learning can be incorporated in science communication to improve how students learn how to talk about their research which also contributes to the advancement in the scholarship of teaching and learning around science communication. 

Tidal freshwater forested wetlands (TFFWs) typically occur at the interface between upriver non-tidal forests and downstream tidal marshes. Due to their location, these forests are susceptible to estuarine and riverine influences, notably periodic saltwater intrusion events. The Mobile-Tensaw (MT) River Delta, one of the largest river deltas in the United States, features TFFWs that are understudied but threatened by sea level rise and human impacts. We surveyed 47 TFFW stands across a tidal gradient previously determined using nine stations to collect continuous water level and salinity data. Forest data were collected from 400 m2 circular plots of canopy and midstory species composition, canopy tree diameter and basal area, stem density, and tree condition. Multivariate hierarchical clustering identified five distinct canopy communities (p = 0.001): Mixed Forest, Swamp Tupelo, Water Tupelo, Bald Cypress, and Bald Cypress and Mixed Tupelo. Environmental factors, such as river distance (p = 0.001) and plot elevation (p = 0.06), were related to community composition. Similar to other TFFWs along the northern Gulf of Mexico, forests closest to Mobile Bay exhibited lower basal areas, species density, diversity, and a higher proportion of visually stressed individual canopy trees compared to those in the upper tidal reach. Results indicate a strong tidal influence on forest composition, structure, and community-level responses.