South-central United States Research Articles

Detection of Anaplasma bovis-like agent in the Southcentral United States

Detection of Anaplasma bovis-like agent in the Southcentral United States

Ethnic discrimination, cultural identification, and well-being among undocumented Hispanic immigrants in the United States: A test of the rejection-identification model.

This study aimed to examine the rejection-identification model (RIM) within a community sample of undocumented Hispanic immigrants in the United States, a unique and vulnerable population who face distinct legal and sociopolitical challenges. The RIM posits that ethnic discrimination is associated with increased identification with one's ethnic group, which, in turn, is positively associated with well-being. Data were collected from a community sample of 140 undocumented Hispanic immigrants living in the South-Central United States during the height of the 2015 Trump presidential campaign. Path analysis was employed to examine direct and indirect effects of perceived ethnic discrimination vis-à-vis ethnic identity, U.S. identity, and two forms of well-being (life satisfaction and flourishing). Age (M = 34.83), gender (50% men), and time spent in the United States were included as covariates. Higher ethnic discrimination was associated with lower U.S. and ethnic identity. Both ethnic and U.S. identity were positively associated with flourishing, whereas only U.S. identity was positively associated with life satisfaction. We also found a significant indirect effect of ethnic identity in the relationship between ethnic discrimination and flourishing. Findings are inconsistent with the RIM, as ethnic discrimination was negatively rather than positively associated with ethnic group identification. Undocumented Hispanic immigrants are a vulnerable population who may experience dual disidentification from both U.S. and ethnic cultural streams when perceiving ethnic discrimination during adverse sociopolitical periods. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

The flash droughts across the south-central United States in 2022: Drivers, predictability, and impacts

A rare subseasonal-to-seasonal phenomenon – two consecutive flash drought events interrupted by a period of recovery – occurred across eastern Oklahoma, Arkansas, and southern Missouri, spanning the summer and early fall of 2022. These flash drought events (the first in June–July, the second in August–September) led to severe (D2) and extreme (D3) drought conditions via the United States Drought Monitor across much of the region following the first period of rapid drought intensification, and extreme (D3) and exceptional (D4) drought conditions by the end of the second event. A notable driver of both flash drought events included a persistent upper-level ridge either centered over or shifted west and upstream of the flash drought region, leading to broad-scale subsidence and reduced mid-level moisture which acted to limit precipitation development and increase evaporative demand. In addition, several heatwave events developed during the warm season in 2022 and either (1) acted to drive flash drought development via increased evaporative demand or (2) were enhanced by land surface desiccation and land-atmosphere feedbacks following rapid drought intensification. Furthermore, S2S composite forecasts predicted drought development for both events. However, only 20% of the ensembles predicted rapid drought development associated with flash drought for the first event and 16% of the ensembles predicted rapid drought development during the second event. This result highlights a key challenge in S2S prediction of rapidly developing drought conditions versus that of more conventional and slower drought development. The ensembles that did predict rapid drought intensification were associated with the forecasting of positive 500 hPa geopotential height anomalies over the south-central United States (first event) or an amplified wave pattern centered over the west-central United States (second event). Lastly, the compounding effects of two flash droughts in a single warm season led to substantial impacts on agricultural, environmental, and hydrologic sectors across the region.

Association of Accelerometer-Measured Physical Activity With College Student Success and Retention.

This study examined the relationship between physical activity (PA) and academic performance and retention among college students using accelerometer data while controlling for sex and socioeconomic background. Data were collected from 4643 first-year college students at a private university in the south-central United States who began their studies in the Fall semesters between 2015 and 2022. Daily step counts were collected using accelerometers worn as part of the institutions PA requirements. The expected family contribution was calculated based on information provided on the Free Application for Federal Student Aid. Grade point average (GPA) and retention data were collected directly from official university databases. Female students generally had lower median age and steps count and a higher median GPA than males. The retention rates from fall to spring and fall to fall were 95.9% and 83.8%, respectively, with no significant difference in retention rates between males and females. GPA was significantly positively correlated with steps, expected family contribution, and age, and negatively correlated with being male and having an expected family contribution of zero. The fall to spring retention rate was significantly positively correlated with steps and GPA. The study's findings suggest that increasing levels of PA, as measured by daily step counts, may be effective in promoting academic performance and retention, even when controlling for sex and socioeconomic background. The use of device-based measures of PA in this study contributes to the literature on this topic, and policymakers and educational institutions should consider interventions focused on academic performance and physical activity to help students persist.

Using AI-Enabled Tools to Support Minority Students’ Success in HE

Generative AI and large language models (LLMs) are transforming workplace literacy practices in the fourth industrial revolution. This study explored how master's students in educational leadership and teacher education programs at a minority-serving university in a low SES urban metroplex in the south-central USA perceive and experience using LLMs and AI-assisted software. The focus was on how these tools support their learning and help them demonstrate knowledge. Key themes include equitable access to AI tools, diverse applications in academic and professional contexts, building student confidence through support and training, using AI to enhance academic readiness and skills, identifying individual needs, enabling higher order thinking opportunities, and promoting ethical use and academic integrity.By addressing various issues of AI usage, institutions can better support underserved students in using disruptive technologies, contributing to their academic success and professional preparedness. Faculty must ensure students' needs are met before requiring the use of new technologies like generative AI and AI-enabled tools.

Teachers Embodying Acceptance for Marginalised Students in the English Language Arts Classroom

ABSTRACT The role of educators in mitigating the negative experiences faced by marginalised students has garnered increasing attention. This study highlights the key attributes of teachers who create a supportive environment for these learners, particularly in English Language Arts classrooms. Through an integration of Positioning Theory, Critical Discourse Analysis, and the Critical Incident Technique, the research underscores how educators can exemplify acceptance and inclusivity through purposeful discourse practices. Preliminary findings from four different upper-secondary English classrooms in the South-central United States suggest that these supportive behaviours and spoken interactions have significant implications for the well-being and academic success of marginalised students.

Vascular streak dieback: A novel threat to redbud and other woody ornamental production in the United States.

Eastern redbud (Cercis canadensis L.) is a popular and high-value woody ornamental plant native to the eastern and south-central United States of America (U.S.A.). In recent years, redbud production in the Southeastern U.S.A. has been greatly affected by a novel threat: vascular streak dieback (VSD). Infected plants exhibit a common set of symptoms, including leaf scorch, tip dieback, and vascular streaking that creates a marbled pattern in stem cross-section. Based on both conventional diagnosis and molecular identification, it has been found that the fungus Ceratobasidium sp. D.P. Rogers (Csp) is consistently associated with VSD-symptomatic eastern redbuds. However, the causal agent(s) of VSD has not yet been conclusively confirmed. Although eastern redbud has been the most frequently identified host tree, more than 25 other native plant genera have been confirmed to have VSD associated with Csp. The near-obligate nature of this fungus has made it challenging to culture, extract DNA, and conduct further studies to confirm its pathogenicity. This article highlights the emerging challenges of VSD, focusing on the following: 1) the recent history of VSD; 2) the increasing importance of VSD to woody ornamental nursery production in the U.S.A.; 3) the currently available protocols for isolating, culturing, storing, and maintaining the putative causal agent; 4) the rapid molecular detection of Csp; 5) phylogenetic findings on the origin and relatedness of Csp to previously recorded diseases, especially VSD in cacao (Theobroma cacao L.); and 6) preliminary results and observations from fungicide trials and cultivar screening in Tennessee. The article also outlines research needed to comprehensively understand VSD and accelerate the development of effective management strategies.

Landcover-categorized fires respond distinctly to precipitation anomalies in the South-Central United States

Satellite detection of active fires has contributed to advance our understanding of fire ecology, fire and climate dynamics, fire emissions, and how to better manage the use of fires as a tool. In this study, we use active fire data of 12 years (2012–2023) combined with landcover information in the South-Central United States to derive a monthly, open-access dataset of categorized fires. This is done by calculating a fire predominance index used to rank fire-prone landcovers, which are then grouped into four main landscapes: grassland, forest, wildland, and crop fires. County-level aggregated analyses reveal spatial distributions, climatologies, and peak fire months that are particular to each fire type. Using the Standardized Precipitation Index (SPI), it was found that during the climatological fire peak-month, the SPI and fires exhibit an inverse relationship in forests and crops, whereas grassland and wildland fires show less consistent inverse or even direct relationship with the SPI. This varied behavior is discussed in the context of landscapes’ responses to anomalies in precipitation and fire management practices, such as prescribed fires and crop residue burning. In a case study of Osage County (OK), we find that large wildfires, known to be closely related to climate anomalies, occur where forest fires are located in the county and absent in areas of grassland fires. Weaker grassland fire response to precipitation anomalies can be attributed to the use of prescribed burning, which is normally planned under environmental conditions that facilitate control and thus avoided during droughts. Crop fires, on the other hand, are set to efficiently burn residue and are practiced more intensely in drier years than in wetter years, explaining the consistently strong inverse correlation between fires and precipitation anomalies. In our increasingly volatile climate, understanding how fires, vegetation, and precipitation interact has become imperative to prevent hazardous fire conflagrations and to better manage ecosystems.

The Allelopathy of the Invasive Plant Species Ludwigia decurrens against Rice and Paddy Weeds

Ludwigia decurrens Walter, belonging to the Onagraceae family, is native to southeastern and southcentral USA and has spread quickly, colonizing wetlands in South and Central America, East and South Asia and Africa. Ludwigia decurrens also infests rice paddy fields and causes serious damage to rice production. The phenomenon of allelopathy is often observed in invasive plant species and contributes to their invasive characteristics. However, no information has been made available on the allelopathy of L. decurrens against wetland species, including Oryza sativa (rice), or on its allelochemicals. Aqueous methanol extracts of whole L. decurrens plants showed allelopathic activity against O. sativa and paddy weeds, Echinochloa crus-galli and Monochoria vaginalis in an extract-concentration-dependent manner. Two allelochemicals, loliolide and dehydrololiolide, were isolated from the L. decurrens extracts through a bioassay-guided separation process using O. sativa as the test plant species. Loliolide and dehydrololiolide also suppressed the growth of O. sativa and E. crus-galli in a concentration-dependent manner. Thus, loliolide and dehydrololiolide may be involved in the allelopathy of L. decurrens and may provide a competitive advantage for L. decurrens due to their growth inhibitory activity. However, the inhibitory activity of loliolide was about 3-fold greater than that of dehydrololiolide. These investigations suggest the allelopathy of L. decurrens may play an important role in the invasion of the species into rice paddy fields and other wetlands. This is the first report on the allelopathy of L. decurrens against wetland species and the isolation and identification of the allelochemicals in L. decurrens.

Predicting flood stages in watersheds with different scales using hourly rainfall dataset: A high-volume rainfall features empowered machine learning approach

Accurate prediction of instantaneous high lake water levels and flood flows (flood stages) from micro-catchments to big river basins are critical for flood forecasting. Lake Carl Blackwell, a small-watershed reservoir in the south-central USA, served as a primary case study due to its rich historical dataset. Bearing knowledge that both current and previous rainfall contributes to the reservoirs' water body, a series of hourly rainfall features were created to maximize predicting power, which include total rainfall amounts in the current hour, the past 2 h, 3 h, …, 600 h in addition to previous-day lake levels. Notedly, the rainfall features are the accumulated rainfall amounts from present to previous hours rather than the rainfall amount in any specific hour. Random Forest Regression (RFR) was used to score the features' importance and predict the flood stages along with Neural Network – Multi-layer Perceptron Regression (NN-MLP), Support Vector Regression (SVR), Extreme Gradient Boosting (XGBoost), and the ordinary multi-variant linear regression (MLR) together with dimension reduced linear models of Principal Component Regression (PCR) and Partial Least Square Regression (PLSR). The prediction accuracy for the lake flood stages can be as high as 0.95 in R2, 0.11 ft. in mean absolute error (MAE), and 0.21 ft. in root mean square error (RMSE) for the testing dataset by the RFR (NN-MLP performed equally well), with small accuracy decreases by the other two non-linear algorithms of XGBoost and SVR. The linear regressions with dimension reductions had the lowest accuracy. Furthermore, our approach demonstrated high accuracy and broad applicability for surface runoff and streamflow predictions across three different-sized watersheds from micro-catchment to big river basins in the region, with increases of predicting power from earlier rainfall for larger watersheds and vice versa.

Performance of heifers grazing native or introduced mixed warm-season grasses during summer months in south-central United States

Performance of heifers grazing native or introduced mixed warm-season grasses during summer months in south-central United States

Exploring the social acceptability of hybrid sweetgum plantations in the south-central United States

Hybrid sweetgum has potential as a dual-purpose plantation in the southern United States due to its rapid growth and suitability for planting on a wide range of sites. To understand its social acceptability, a survey instrument was administered among 3,000 private landowners in the states of Texas, Oklahoma, Louisiana, and Arkansas. The survey results showed that a considerable percentage of landowners (41 %) were uncertain and would probably benefit from more information available to them on the topic. A multinomial logit analysis found that landowners who had timber management objectives were more interested in growing hybrid sweetgum if it was profitable and practically feasible. Similarly, female landowners and those having higher education were found to be more interested in growing hybrid sweetgum. Study findings suggest a need for outreach on economic feasibility, management, start-up costs, and tax implications concerning hybrid sweetgum plantations.

Climate Change Curricula in Family Medicine Residency Programs: Program Directors' Perspectives From a CERA Survey.

Climate change is a major threat to the health of people worldwide. The health care system deals with the immediate health-related effects of climate change and, at the same time, is a major emitter of greenhouse gas. This study aimed to investigate (a) the awareness and perception of climate change among family medicine residency program directors, and (b) the state of climate change education in family medicine residency programs. The Council of Academic Family Medicine Educational Research Alliance (CERA) conducted a cross-sectional survey of family medicine program directors in the United States in April 2023. We analyzed anonymous data using descriptive and bivariate statistics. We analyzed responses from 284 family medicine residency program directors (response rate 41.1%). Of these, 56.8% indicated not having any lectures/seminars dedicated to climate change and no plans to introduce such curricula, with considerably higher rates in East South Central United States (92.8%). A majority considered principles of climate change, carbon emissions emitted by the health care system, and discussion of climate change with patients of lesser importance for residency program education. While climate change is an emerging topic affecting health and the provision of health care worldwide, our study suggests that many family medicine residency programs do not teach about it. Family medicine trainees may not always receive sufficient education about the risks posed to their patients by climate change, which could lead to them having limited knowledge and skills when discussing this topic with their patients in the future.

TRPV1-Dependent Antiproliferative Activity of Dioecious Maclura pomifera Extracts in Estrogen Receptor-Positive Breast Cancer Cell Lines Involves Multiple Apoptotic Pathways.

Globally, breast cancer is a significant cause of mortality. Recent research focused on identifying compounds regulating the transient receptor potential vanilloid 1 (TRPV1) ion channel activity for the possibility of developing cancer therapeutics. In this study, the antiproliferative properties and mechanisms of action through TRPV1 of Maclura pomifera, a dioecious tree native to the south-central USA, have been investigated. Male and female extracts of spring branch tissues and leaves (500 µg/mL) significantly reduced the viability of MCF-7 and T47D cells by 75-80%. M. pomifera extracts induced apoptosis by triggering intracellular calcium overload via TRPV1. Blocking TRPV1 with the capsazepine antagonist and pretreating cells with the BAPTA-AM chelator boosted cell viability, revealing that M. pomifera phytochemicals activate TRPV1. Both male and female M. pomifera extracts initiated apoptosis through multiple pathways, the mitochondrial, ERK-induced, and endoplasmic reticulum-stress-mediated apoptotic pathways, demonstrated by the expression of activated caspase 3, caspase 9, caspase 8, FADD, FAS, ATF4, and CHOP, the overexpression of phosphorylated PERK and ERK proteins, and the reduction of BCL-2 levels. In addition, AKT and pAKT protein expressions were reduced in female M. pomifera-treated cells, revealing that female plant extract also inhibits PI3K/Akt signaling pathways. These results suggest that phytochemicals in M. pomifera extracts could be promising for developing breast cancer therapeutics.

Additive and Moderating Effect of Parents and Friends on Health and Behavior Outcomes During Emerging Adulthood

Relationships with parents and friends may work together to increase the risk of adjustment problems in emerging adulthood. However, it is still undetermined if social relationships act in an additive (i.e., serve as unique predictors) or moderating (i.e., interact with other predictors) fashion. In a cross-sectional sample of 859 female college students ( M age = 19.53, SD = 1.49; 73.9% White) from a large university in the south-central United States, we assessed how parents and best friends impact emerging adult internalizing symptoms, risky behavior, and health problems. We found that low levels of best friend risky behavior attenuated the links between father-emerging adult relationship quality and risky behavior and internalizing symptoms, and high levels of father-emerging adult relationship quality magnified the association between mother-emerging adult relations and internalizing symptoms. Ultimately, these results indicate that relationships with parents and friends served as additive or unique predictors of emerging adult health and behavior.

Perceptions of UDL Teaching Practices among University Students with Disabilities

The purpose of this study was to investigate how students’ disabilities impacted their learning at the university and to measure their perceptions of universal design for learning (UDL). An online survey was administered at a large public research university in the south-central United States; 160 students with disabilities completed the survey. These students with disabilities described how their disabilities influenced their learning in the following aspects: attention issues, slow processing, absence, accessibility issues, reading and writing challenges, mental health challenges, and social interaction challenges. The results also revealed that some UDL teaching practices were not being fully utilized by instructors based on the perceptions of students with disabilities. We discussed those UDL practices which were not being used by instructors and highlighted the impact of using the practices on students’ learning. These practices include effective teaching methods such as helping students organize and summarize learning content, using technology to increase accessibility, providing flexibility in assessments and assignments, providing meaningful feedback, and recruiting students’ attention and engagement.

Teachers’ Perceptions, Knowledge, and Interactions with Scripted Curriculum

As shortages of teachers increase and student standardized test scores remain low and unchanged, there is a push for increasing instructional effectiveness using scripted curriculum and direct instruction. However, scripted curriculum is likely inconsistent with teachers’ professional visions and needs, leading to conflicting goals for adopting scripted curriculum and teachers’ professional goals. We determined the gaps in the literature support the need to collectively explore how teachers define and consider scripted curriculum, particularly the extent to which they think the curriculum is culturally responsive, motivates students to learn, are involved in adopting the curriculum, and their preferences for teaching with scripted curriculum. Using a cross-section survey design, we gathered quantitative and qualitative data from 292 K-12 teachers working in the south-central United States. We found teachers did not perceive scripted curriculum as culturally responsive, did not think the curriculum motivates students to learn, did not like teaching with the curriculum or preferred to use it as a resource, and tended to be marginally involved in selecting the curriculum. Our research empirically documents the narrative teachers tend to share about scripted curriculum. We conclude our report by discussing our results, implications for our findings, and recommendations for future research.

False springs and spring phenology: Propagating effects of downscaling technique and training data

AbstractProjected changes to spring phenological indicators (such as first leaf and first bloom) are of importance to assessing the impacts of climate change on ecosystems and species. The risk of false springs (when a killing freeze occurs after plants of interest bloom), which can cause ecological and economic damage, is also projected to change across much of the United States. Given the coarse nature of global climate models, downscaled climate projections have commonly been used to assess local changes in spring phenological indices. Few studies that examine the influence of the sources of uncertainty sources in the downscaling approach on projections of phenological changes. This study examines the influence of sources of uncertainty on projections of spring phenological indicators and false spring risk using the South Central United States. The downscaled climate projections were created using three statistical downscaling techniques applied with three gridded observation datasets as training data and three global climate models. This study finds that projections of spring phenological indicators and false spring risk are primarily sensitive to the choice of global climate models. However, this study also finds that the formulation of the downscaling approach can cause errors representing the daily low‐temperature distribution, which can cause errors in false spring risk by failing to capture the timing between the last spring freeze and the first bloom. One should carefully consider the downscaling approach used when using downscaled climate projections to assess changes to spring phenology and false spring risk.

Perceived Obstacles in Land Use Change for Hybrid Sweetgum Plantations: Landowner Opinions from the South Central United States

Abstract Hybrid sweetgum (Liquidambar styraciflua × L. formosana) has received considerable attention as a potential feedstock for traditional and nontraditional forest-based enterprises due to its fast growth and large specific gravity. However, the perceptions of landowners are important to understand the degree of acceptance concerning land use change to consider this opportunity in the United States. We administered a survey instrument to three thousand landowners representing the states of Texas, Oklahoma, Louisiana, and Arkansas where hybrid sweetgum plantations would be feasible. A seemingly unrelated regression analysis was used to explore the attributes that may influence the environmental and economic obstacles in land use change for hybrid sweetgum plantations. Study results suggest that landowners who perceived higher importance of marketing aspects of hybrid sweetgum expressed greater economic concerns for land use change. In contrast, those having higher planted pine acres had higher environmental concerns about land use change. Female landowners were more concerned than their male counterparts. Landowners need access to accurate information from their trusted sources to make informed management decisions, especially when making decisions to adopt new opportunities such as hybrid sweetgum. Study Implications: Study results reveal the need for outreach to landowners in the south central United States, as many were not aware of fast-growing hardwood species such as hybrid sweetgum. Information on growth potential, economics, and management techniques can help facilitate the adoption of hybrid sweetgum. Field visits and peer-to-peer learning facilitated by early adopters can be effective strategies for outreach.

Structural diversity is better associated with forest productivity than species or functional diversity.

Understanding the relationship between biodiversity and productivity can be advanced by improving metrics used to quantify biodiversity. Structural diversity, that is, variation of size and form of plant organs, is an emerging biodiversity metric. However, compared with the other biodiversity metrics, its relative importance in specific components of forest productivity, for example, recruitment of new individuals, biomass net change after accounting for mortality, is largely unknown, particularly across a large spatial scale with multiple influential gradients. To address the knowledge gap, we used USDA Forest Service Forest Inventory and Analysis (FIA) data across the southcentral USA from 2008 to 2017. We calculated forest biomass increments due to recruitment and growth and net change in biomass. Then, we quantified the effects of a range of abiotic and biotic variables on the biomass increments and net change. Our results showed that (1) Structural diversity was negatively associated with the two biomass increments and net change in biomass. The negative effects were supported by increased occurrences of insects and diseases with greater structural diversity. (2) Compared with species and functional diversity, structural diversity showed a better association with biomass increments and net change, suggested by its larger absolute values of standardized coefficients, and the effects of structural diversity were negative in contrast to species diversity. (3) The effects of structural diversity, stand age, and elevation differed between natural and planted forests that may stem from the differences in stand development and species composition between the two forest types. Together, structural diversity may represent an important dimension of biodiversity impacts on plant productivity, which could be related to the exacerbated disturbances with greater structural diversity.