Search Results (95)

The 2019 Mississippi River floods were among the most severe in recent U.S. history, impacting 11 states and driven by multiple tributary flood events rather than a single episode. This study focuses on the Lower Mississippi River Basin in Mississippi, examining how flood frequency interacts with land ownership patterns to influence agricultural losses in the Yazoo–Mississippi Delta. Using Sentinel-2 imagery within Google Earth Engine, land use and land cover were classified with a random forest algorithm, followed by change detection and a flood recurrence–persistence modeling framework to map and characterize inundation. Results indicate that mid-year floods (April–July) caused the greatest crop losses, particularly in soybeans (4475 ha), cotton (501 ha), and corn (546 ha). Most impacts were associated with short-duration, low-recurrence floods, which affected many structures (1812) and extensive agricultural areas due to their broad spatial reach. Small agricultural parcels (≤48 ha) experienced the highest proportional exposure across flood zones, while medium and large parcels showed comparatively lower vulnerability. These findings highlight the importance of targeted resilience and mitigation strategies that account for flood frequency, land use, and land ownership patterns across the Delta. Full article

A substantial proportion of U.S. third graders cannot read at grade level. However, few models in the literature are known to be effective in ameliorating third-grade reading deficits, where learning to read shifts to reading to learn. This study presents findings from an evaluation of Literacy Fellows, a one-year, intensive, small-group reading intervention designed for third graders lacking decoding skills needed for comprehension. The study sample included 484 third-grade students from low-income, predominantly Black school districts, 120 of whom scored below the cutoff on a standardized, beginning-of-the-year reading test and were assigned to the Literacy Fellows intervention. The analytical sample draws on cohorts from the 2015–2016, 2016–2017, and 2017–2018 academic years. The effectiveness of Literacy Fellows was investigated using a quasi-experimental regression discontinuity design. The results indicate an improvement of 68 scale points (12 percentile rank points) on a third-grade reading test designed to determine readiness for entering the fourth grade for intervention students. The findings have policy implications for third-grade reading interventions that help foster grade-proficient reading, reduce equity gaps in reading success, and offer actionable suggestions, including the implementation of daily small-group, decoding-focused instruction for struggling third-grade readers in low-income school districts. Full article

Microplastic (MP) pollution in agricultural settings is an emerging field of study, with interest focusing on potential resource contamination of soil and water due to the use of plastic materials in farming practices. The Mississippi Delta, a highly agricultural region, is prone to both natural and intentional flooding, potentially exacerbating this issue. This exploratory study investigated MP (>30 µm) concentrations, sizes, and polymer compositions in floodwater, irrigation water, and surface runoff from soybean fields across two counties in the Mississippi Delta using micro-Fourier transform infrared spectroscopy (µ-FTIR). Mean ± SE concentrations (MPs/L) were 72 ± 66 in floodwater (n = 18), 169 ± 121 in source (irrigation pond) water (n = 4), and 30 ± 37 in runoff (n = 3) in Sunflower County, MS. In Coahoma County, MS, mean ± SE runoff concentration was 88 ± 76 MPs/L (n = 24). Mean concentrations were elevated as compared to other MP studies in agricultural environments. The most common polymers present were polyethylene terephthalate (PET), polyethylene (PE), polyethylene-ethyl vinyl acetate (PE/EVA), and thermoplastic elastomers (TPEs), which are commonly used in the manufacturing of agricultural materials. MPs from the smallest size fraction measured (30–100 µm) were the most common in all floodwater samples, ranging from 75.5–91% abundance. Using Attenuated Total Reflectance (ATR)-FTIR, larger plastic litter was identified as mostly PE and PET, which is consistent with polymer distributions in floodwater samples. Overall, MPs were prevalent in both floodwater and runoff, with relatively consistent concentrations and polymer compositions across samples. However, further research is needed to fully elucidate their fate and potential impacts on agricultural systems. Full article

The once-extensive coastal forested wetlands (CFWs) of the Mississippi River Delta (MRD) are declining under the combined pressures of pervasive hydrologic change, unregulated harvesting, relative water level rise (due to the combination of geological subsidence and sea-level rise—SLR), and climate change. We synthesize here over 50 years of research conducted in the MRD to examine the history of the CFWs and their management, their ecosystem functions and services, and the nature, extent, and severity of ongoing changes. Seedling recruitment failure and increasing salinity levels are the most immediate threats to forest persistence, necessitating management that restores hydrologic function and sediment and nutrient supply to allow seedling survival and minimizes saltwater intrusion. Collectively, the evidence indicates that managed inflows can bolster accretion and sustain forest function, and long-term resilience requires hydrologic restoration at landscape scales coupled with site-level actions that secure recruitment and address local degradation trajectories. These include freshwater and sediment introduction, protection from herbivory, and, in some cases, planting. Our research findings have important implications for worldwide CFWs, and tidal freshwater ecosystems in general, which occur mainly in tropical deltas. Full article

Background: Individuals with intellectual and developmental disabilities (IDD) experience persistent health disparities that result in poorer health outcomes, reduced quality of life, and inequitable access to healthcare. Objective: This narrative review synthesized existing literature to identify key barriers to health equity and contributors to health disparities among individuals with IDD. Method: This study was a narrative (non-systematic) review that adopted a qualitative synthesis approach. A literature review was conducted across PubMed, CINAHL, PsycINFO, Medline, and Google Scholar to identify peer-reviewed articles published between 2010 and 2025 that address health disparities, health inequities, healthcare barriers, and social determinants of health among individuals with IDD. Thematic analysis was employed to synthesize the included studies and identify recurring patterns and themes. Results: A total of 88 articles were included. Two overarching domains shaping health disparities were identified: barriers to health equity and contributing factors. Seven barrier categories emerged: attitudinal, communication, policy, programmatic, social, physical, and transportation. Five key contributors were also identified: limited access to healthcare, comorbid conditions, low health literacy, adverse social determinants of health, and caregiver burden. Conclusions: Health disparities among individuals with IDD are driven by intersecting social, structural, and healthcare system barriers rather than individual limitations alone. This review informs policymakers, public health professionals, and interventionists on how to advance health equity for individuals with IDD through targeted, person-centered interventions. Full article

The Yazoo–Mississippi Delta is an agricultural production zone and flyway for migratory birds. During winter, agricultural field-flooding practices are routinely used to support bird conservation and local recreational hunting opportunities. In response to the 2010 Deepwater Horizon oil spill, federal agencies incentivized flooding in summer and fall to mitigate the risks to migratory bird populations. This funding ceased in 2017, yet the United States Department of Agriculture Natural Resources Conservation Service Environmental Quality Incentives Program Practice 644 and a local non-profit continue to incentivize flooding during fall. Ensuring that contractual water levels are met is challenging to determine. To that end, we developed the Field Inundation Tool/Survey, an integrated remote sensing approach using PlanetScope imagery (Planet Labs, San Francisco, CA, USA) to quantify associated hydrology patterns. We used the Normalized Difference Water Index and an Iso Cluster Unsupervised Classification to estimate field inundation and associated habitat types over a three-year period. The results indicate dynamic field inundation can be estimated via PlanetScope imagery. Derived inundation metrics were comparable with in situ sensor and digital elevation models among some treatment types. We documented future refinements for image quality and soil patterns. Our work can improve conservation incentivization by tracking spatial and temporal patterns in adoption and has applicability to other agroecosystems. Full article

Invasive insects increasingly threaten ecosystems worldwide, with wetlands especially vulnerable to unpredictable climate. Phragmites australis is a dominant plant species in Louisiana’s Mississippi River Delta and a critically important component of the wetland ecosystem. However, the invasive scale insect, Nipponaclerda biwakoensis, has contributed to large-scale dieback of this foundation species, jeopardizing erosion control, water filtration, and wildlife habitat. Despite rapid regional spread, the fine-scale dispersal of N. biwakoensis within host plants remains poorly understood. We examined whether the crawler-stage of N. biwakoensis scales preferentially settled on the bottom or top sections of P. australis stems, and whether plant nutritional and/or defensive traits shaped this preference. In field surveys, scale densities varied along the length of P. australis stems, with gravid females occurring 3.5× more frequently at the stem base than at the top; parasitism rates were similarly elevated, reaching 12× higher at the base. To evaluate potential drivers of this pattern, we quantified carbon, nitrogen, water, and phenolic content in lower and upper stem tissues and conducted complementary laboratory assays to test crawler settlement preferences. Under controlled conditions, crawlers settled most densely on middle stem sections, with lower densities at the base and the fewest near the top. The basal sections also contained 50% less nitrogen and 47% lower phenolic concentrations compared to the upper stem. The divergence in crawler settlement patterns between field and controlled conditions likely reflects the influence of additional environmental factors present in the field—such as habitat structure, microclimate, and natural enemies—that are absent or minimized in laboratory conditions. By applying a trait-based approach to insect dispersal, we link plant functional traits to N. biwakoensis crawler settlement patterns, strengthening our understanding of of insect distribution and guiding predictions of long-term dispersal in N. biwakoensis. Full article

Background/Introduction: Alzheimer’s disease (AD) is a progressive neurological disorder and one of the leading causes of death among older adults in the United States. It causes gradual cognitive decline, memory loss, and impaired functioning. Vulnerable populations—especially those living in rural and predominantly Black communities like the Mississippi Delta—are disproportionately affected. Despite high Alzheimer’s disease mortality rates in Mississippi, limited research has analyzed recent trends disaggregated by race, gender, and geography. This study evaluated trends in AD mortality in the Mississippi Delta between 2016 and 2022 to inform equitable public health responses. Methods: This trend study used age-adjusted mortality rates (AAMRs) for adults aged 65 and older to examine Alzheimer’s disease deaths. AAMRs allow for fair comparisons across groups by adjusting for differences in population age structures. Mortality data were obtained from the Mississippi Statistically Automated Health Resource System (MSTAHRS), a statewide health surveillance system managed by the Mississippi State Department of Health. Joinpoint regression analysis was used to identify statistically significant changes in mortality trends over time using Annual Percent Change (APC) and Average Annual Percent Change (AAPC), with 95% confidence intervals (CIs). AAPC denotes an average percentage change in mortality trends over a seven-year period. Joinpoint regression is an appropriate method for detecting points at which linear trends change significantly, especially in chronic disease mortality analysis. Results: From 2016 to 2022, Alzheimer’s disease mortality significantly increased among Black individuals (AAPC = 8.3%, 95% CI [2.6 to 16.0]; p < 0.05) and declined among White individuals (AAPC = −2.9%, 95% CI [−12.3 to 7.6] p < 0.05). Gender-specific analyses showed slight, non-significant increases among both males and females. County-level disparities were evident: counties such as Sharkey experienced increases exceeding 10%, while Humphreys counties showed declines. Racial disparities in AD mortality were more pronounced than gender differences. Conclusions: This study reveals widening racial and geographic disparities in Alzheimer’s disease mortality across the Mississippi Delta. The statistically significant increase among Black seniors highlights structural inequities in early diagnosis, access to culturally appropriate care, and chronic disease management. These findings support the need for targeted public health interventions, such as the expansion of rural memory clinics, culturally competent outreach, and Medicaid-supported long-term care. Strengthening surveillance systems like MSTAHRS is critical to tracking disparities and advancing equity in dementia-related mortality. Full article

The estuaries of the Mississippi River Delta are among the most productive coastal ecosystems in the world and have attracted human fishing communities for centuries. Beginning in the early 20th century, the oil and gas industry also emerged as a powerful economic force in exploiting coastal fossil fuel deposits. This paper reviews the complex history of the oil and gas industry in Southeast Louisiana, including its relationships with political corruption, inequality, pollution, and environmental catastrophe; and also its role in supporting coastal fishing communities with complementary economic opportunities. In the 21st century, a series of disasters—above all Hurricane Katrina in 2005 and the B.P. oil spill in 2010—drew attention to the risks inherent to the region, as well as its crucial role in buffering the impacts of tropical storms for inland urban communities. This paper examines the evolution of fisheries regulations and their consequences of small-scale fishers, focusing especially on the banning of gill net use in 1990s. By combining historical information with ethnographic interviews and participant observation, this paper examines the complex political–economic forces involved in shifting regulatory frameworks and policies, and it shows their negative consequences for fishing communities facing an existentially threatening combination of coastal erosion, fisheries declines, and various macroeconomic headwinds. This paper argues that resilient coastal communities are crucial to combating the environmental problems facing coastal regions and that rethinking fisheries regulations may be a dynamic tool in enhancing community resilience. Full article

Background/Objectives: As healthcare increasingly utilizes digital delivery systems, equitable access and engagement are critical, particularly for caregivers of older adults in rural regions. This study examines how education levels and geographic rurality influence health information-seeking in Mississippi, a state with persistent structural inequities, through the theoretical lenses of Digital Divide Theory and Theory of Planned Behavior. Methods: A statewide survey was conducted among caregivers in Mississippi (N = 452) who support adults aged 50+. The survey assessed rurality level, educational attainment, attitudes toward various health information sources, perceived digital accessibility, and reported challenges in obtaining necessary health guidance. Results: Findings challenged conventional assumptions regarding rural digital engagement. Rural caregivers reported higher trust in both internet and interpersonal health information sources. Rurality did not significantly predict internet use or reported difficulty finding information. However, a significant interaction between education and rurality revealed an “Outcome Divide”: while higher education correlated with more positive attitudes toward online health information in urban areas, this association weakened and reversed in highly rural contexts. Conclusions: These results underscore the need for strategies beyond merely improving access to bridge digital health equity gaps. Policy and interventions must address contextual barriers, such as digital health literacy and relevance, limiting the effectiveness of digital tools, even when internet access is available. Promoting digital health literacy, integrating trusted local interpersonal networks, and adapting educational initiatives to rural realities are essential for advancing equitable and effective digital health engagement. Full article

Coastal vegetated ecosystems, including tidal marshes, vegetated dunes, and shrub- and forest-dominated wetlands, can mitigate hurricane impacts such as coastal flooding and erosion by increasing surface roughness and reducing wave energy. Land cover maps can be used as input to improve simulations of surface roughness in advanced hydro-morphological models. Consequently, there is a need for efficient tools to develop up-to-date land cover maps that include the accurate distribution of vegetation types prior to an extreme storm. In response, we developed the RUSH tool (Rapid remote sensing Updates of land cover for Storm and Hurricane forecast models). RUSH delivers high-resolution maps of coastal vegetation for near-real-time or historical conditions via a Jupyter Notebook application and a graphical user interface (GUI). The application generates 3 m spatial resolution land cover maps with classes relevant to coastal settings, especially along mainland beaches, headlands, and barrier islands, as follows: (1) open water; (2) emergent wetlands; (3) dune grass; (4) woody wetlands; and (5) bare ground. These maps are developed by applying one of two seasonal random-forest machine learning models to Planet Labs SuperDove multispectral imagery. Cool Season and Warm Season Models were trained on 665 and 594 reference points, respectively, located across study regions in the North Carolina Outer Banks, the Mississippi Delta in Louisiana, and a portion of the Florida Gulf Coast near Apalachicola. Cool Season and Warm Season Models were tested with 666 and 595 independent points, with an overall accuracy of 93% and 94%, respectively. The Jupyter Notebook application provides users with a flexible platform for customization for advanced users, whereas the GUI, designed with user-experience feedback, provides non-experts access to remote sensing capabilities. This application can also be used for long-term coastal geomorphic and ecosystem change assessments. Full article

Groundwater depletion poses a critical challenge to global water security, threatening ecosystems, agriculture, and sustainable development. The Mississippi Delta, a region heavily reliant on groundwater for agriculture, has experienced significant groundwater level declines due to intensive irrigation. Traditional in situ monitoring methods, while valuable, lack the spatial coverage necessary to capture regional groundwater dynamics comprehensively. This study addresses these limitations by leveraging downscaled Gravity Recovery and Climate Experiment (GRACE) data to estimate groundwater levels using random forest modeling (RFM). We applied a machine-learning approach, utilizing the “Forest-based and Boosted Classification and Regression” tool in ArcGIS Pro, (ESRI, Redlands, CA) to predict groundwater levels for April and October over a 10-year period. The model was trained and validated with well-water level records from over 400 monitoring wells, incorporating input variables such as NDVI, temperature, precipitation, and NLDAS data. Cross-validation results demonstrate the model’s high accuracy, with R² values confirming its robustness and reliability. The outputs reveal significant groundwater depletion in the central Mississippi Delta, with the lowest water level observed in the eastern Sunflower and western Leflore Counties. Notably, April 2014 recorded a minimum water level of 18.6 m, while October 2018 showed the lowest post-irrigation water level at 54.9 m. By integrating satellite data with machine learning, this research provides a framework for addressing regional water management challenges and advancing sustainable practices in water-stressed agricultural regions. Full article

Driven by the need to expand urban/industrial complexes, and/or mitigate anticipated environmental impacts (e.g., tropical storms), many coastal countries have long implemented large-scale land reclamation initiatives. Some areas, like coastal Louisiana, USA, have relied heavily on restoration activities (i.e., beneficial use of dredged material) to counter extensive long-term wetland loss. Despite these prolonged engagements, the quantifiable benefits of these activities have lacked comprehensive documentation. Therefore, this study leveraged remote sensing data and advanced machine learning techniques to enhance the classification and evaluation of restoration efficacy within the wetlands adjacent to the Mississippi River’s Southwest Pass (SWP). By utilizing air- and space-borne imagery, land and water data were extracted and used to compare land cover changes during two distinct restoration periods (1978 to 2008 and 2008 to 2020) to historical trends. The classification methods employed achieved an overall accuracy of 85% with a Cohen’s kappa value of 0.82, demonstrating substantial agreement beyond random chance. To further assess the success of the SWP reclamation efforts in a global context, broad-based land cover data were generated using biennial air- and space-borne imagery. Results show that restoration activities along SWP have resulted in a significant recovery of degraded wetlands, accounting for approximately a 30 km² increase in land area, ranking among the most successful land reclamation projects in the world. The findings from this study highlight beneficial use of dredged material as a critical component in large-scale, recurring restoration activities aimed at mitigating degradation in coastal landscapes. The integration of remote sensing and machine learning methodologies provides a robust framework for monitoring and evaluating restoration projects, offering valuable insights into the optimization of ecosystem services. Overall, the research advocates for a holistic approach to coastal restoration, emphasizing the need for continuous innovation and adaptation in restoration practices to address the dynamic challenges faced by coastal ecosystems globally. Full article

As a distinct musical form, blues music from the Mississippi Delta has been extensively studied across various academic disciplines. While much of this attention has treated blues primarily as an auditory experience, I argue that it represents far more than just sound or entertainment. This research project examines Delta blues as a comprehensive cultural phenomenon, exploring its evolution through a series of distinct diffusionary pathways that reveal complex global interactions and transcultural exchange. This study posits that Delta blues emerged from a broad cultural milieu, shaped by multiple layers of geographical processes ranging from ancient African trade routes to twentieth-century migration patterns. I position Delta blues within the context of the African diaspora, emphasizing not only its strong roots in African and African American cultural traditions but also its crucial role as a vehicle for cultural resistance and consciousness-raising. By mapping the evolution of blues music and culture through specific circuits of exchange, I illuminate the intricate interrelationships between different peoples and places across time and space. This approach reveals how global interactions generated a unique musical and cultural expression that both embodies and transcends the complex social dynamics inherent in the African diaspora. Full article

The increasing demand for food and rapid population growth have made advanced crop monitoring essential for sustainable agriculture. Deep learning models leveraging multispectral satellite imagery, like Sentinel-2, provide valuable solutions. However, transferring these models to diverse regions is challenging due to phenological differences in crop growth stages between training and target areas. This study proposes the Adaptive Month Matching (AMM) method to align the phenological stages of crops between training and target areas for enhanced transfer learning in cropland segmentation. In the AMM method, an optimal Sentinel-2 monthly time series is identified in the training area based on deep learning model performance for major crops common to both areas. A month-matching process then selects the optimal Sentinel-2 time series for the target area by aligning the phenological stages between the training and target areas. In this study, the training area covered part of the Mississippi River Delta, while the target areas included diverse regions across the US and Canada. The evaluation focused on major crops, including corn, soybeans, rice, and double-cropped winter wheat/soybeans. The trained deep learning model was transferred to the target areas, and accuracy metrics were compared across different time series chosen by various phenological alignment methods. The AMM method consistently demonstrated strong performance, particularly in transferring to rice-growing regions, achieving an overall accuracy of 98%. It often matched or exceeded other phenological matching techniques in corn segmentation, with an average overall accuracy across all target areas exceeding 79% for cropland segmentation. Full article