Increasing on-farm crop diversity is one agroecological approach to enhancing food self-sufficiency that helps small-scale farmers keep their food systems stable by reducing risks associated with stressors, such as a pest outbreaks or droughts. But understanding how crop diversity and food self-sufficiency are related is unknown. To explore this complex relation, this study presents household data (n = 1664) from Nepal to test the hypothesis that families with high crop diversity enjoy greater household food self-sufficiency. Data are presented for three districts that are representative of three distinct agroecological regions of the country: (1) Sarlahi, which is affluent, market-oriented, and on the plains; (2) Makwanpur District in the hills, which has well-developed integrated farm production; and (3) the mountainous District of Humla, which has the poorest quality environment and is the most remote. Results show that in the Humla District, families with greater crop diversity were more self-sufficient. In contrast, farmers in Makwanpur, who have already established a high degree of crop diversity based on vegetable production, do not benefit from additional crop diversity in terms of their ability to provide for themselves. Finally, data from Sarlahi show that families' food selfsufficiency benefits from crop diversification. We conclude that boosting crop diversity is a viable strategy for maintaining stability in food systems, but this varies depending on the accessibility of a farm and, in particular, access to markets.

The United States has a geographically mature and stable land use and land cover system including land used as irrigated cropland; however, changes in irrigation land use frequently occur related to various drivers. We applied a consistent methodology at a 250 m spatial resolution across the lower 48 states to map and estimate irrigation dynamics for four map eras (2002, 2007, 2012, and 2017) and over four 5-year mapping intervals. The resulting geospatial maps (called the Moderate Resolution Imaging Spectroradiometer (MODIS) Irrigated Agriculture Dataset or MIrAD-US) involved inputs from county-level irrigated statistics from the U.S. Department of Agriculture, National Agricultural Statistics Service, agricultural land cover from the U.S. Geological Survey National Land Cover Database, and an annual peak vegetation index derived from expedited MODIS satellite imagery. This study investigated regional and periodic patterns in the amount of change in irrigated agriculture and linked gains and losses to proximal causes and consequences. While there was a 7% overall increase in irrigated area from 2002 to 2017, we found surprising variability by region and by 5-year map interval. Irrigation land use dynamics affect the environment, water use, and crop yields. Regionally, we found that the watersheds with the largest irrigation gains (based on percent of area) included the Missouri, Upper Mississippi, and Lower Mississippi watersheds. Conversely, the California and the Texas–Gulf watersheds experienced fairly consistent irrigation losses during these mapping intervals. Various drivers for irrigation dynamics included regional climate fluctuations and drought events, demand for certain crops, government land or water policies, and economic incentives like crop pricing and land values. The MIrAD-US (Version 4) was assessed for accuracy using a variety of existing regionally based reference data. Accuracy ranged between 70% and 95%, depending on the region.

Biodegradable and biocompatible polymeric nanoparticles (NPs) stand out as a key tool for improving drug bioavailability, reducing the inherent toxicity, and targeting the intended site. Most importantly, the ease of polymer synthesis and its derivatization to add functional properties makes them potentially ideal to fulfill the requirements for intended therapeutic applications. Among many polymers, US FDA-approved poly­(l-lactic-co-glycolic) acid (PLGA) is a widely used biocompatible and biodegradable co-polymer in drug delivery and in implantable biomaterials. While many studies have been conducted using PLGA NPs as a drug delivery system, less attention has been given to understanding the effect of NP weight on cellular behaviors such as uptake. Here we discuss the synthesis of PLGA NPs with varying NP weights and their colloidal and biological properties. Following nanoprecipitation, we have synthesized PLGA NP sizes ranging from 60 to 100 nm by varying the initial PLGA feed in the system. These NPs were found to be stable for a prolonged period in colloidal conditions. We further studied cellular uptake and found that these NPs are cytocompatible; however, they are differentially uptaken by cancer and immune cells, which are greatly influenced by NPs’ weight. The drug delivery potential of these nanoparticles (NPs) was assessed using doxorubicin (DOX) as a model drug, loaded into the NP core at a concentration of 7.0 ± 0.5 wt % to study its therapeutic effects. The results showed that both concentration and treatment time are crucial factors for exhibiting therapeutic effects, as observed with DOX-NPs exhibiting a higher potency at lower concentrations. The observations revealed that DOX-NPs exhibited a higher cellular uptake of DOX compared to the free-DOX treatment group. This will allow us to reduce the recommended dose to achieve the desired effect, which otherwise required a large dose when treated with free DOX. Considering the significance of PLGA-based nanoparticle drug delivery systems, we anticipate that this study will contribute to the establishment of design considerations and guidelines for the therapeutic applications of nanoparticles.

This research builds upon the extensive body of work to model exotic annual grass (EAG) characteristics and invasion. EAGs increase wildland fire risk and intensifies wildland fire behavior in western U.S. rangelands. Therefore, understanding characteristics of EAG growth increases understanding of its dynamics and can inform rangeland management decisions. To better understand EAG phenology and spatial distribution, monthly weather (precipitation, minimum and maximum temperature) variables were analyzed for 24 level III ecoregions. This research characterizes EAGs’ phenology identified by a normalized difference vegetation index (NDVI) threshold-based interpolation technique. An EAG phenology metric model was used to estimate a growing season dynamic for the years 2017–2021 for shrub and herbaceous land cover types in the western conterminous United States (66% of the area). The EAG phenology metrics include six growing season metrics such as start of season time, end of season time, and time of maximum NDVI during the growing season. The models’ cross validation results for Pearson’s r ranged from 0.88 to 0.95. Increased understanding of the effects that weather conditions have on EAG growth and spatial distribution can help land managers develop time-sensitive plans to protect entities deemed valuable to society like native habitat, wildlife, recreational areas, and air quality.