Locations In Texas Research Articles

Self-rated health of Latino day laborers during the COVID-19 pandemic: a cross-sectional study.

This study assesses the relationship between trust in sources of information in regard to the Coronavirus Disease 2019 (COVID-19) pandemic and self-rated health (SRH) in a sample of Latino Day Laborers (LDLs) and explores whether these associations were mediated by mental health measures. A rapid needs assessment survey was conducted with 300 LDLs, recruited at randomly selected hiring locations in Houston, Texas, during November and December 2021. Two measures of trust were developed, and SRH was measured by a single item. Depression, anxiety, and stress were measured by previously validated scales. We applied the product of coefficients approach to assess our mediation model. Using Hayes' PROCESS version 4.2 in SPSS, linear regression models were generated simultaneously to assess the total effect of trust on SRH, effect of trust on the mental health mediator, and effect of the mediator on SRH, controlling for trust. Demographic characteristics were entered as covariates. Greater trust in formal sources of information (such as Spanish-speaking television networks) as well as greater levels of anxiety and depression were associated with lower SRH. There were no significant associations between formal trust and mental health measures. As such, the association between formal trust and decreased SRH was not mediated by mental health. Trust in informal sources of information (conversations with friends, family, and coworkers) was not significantly associated with SRH or mental health. Higher levels of depression and anxiety, however, were associated with lower SRH. LDLs' perception of their health was inversely associated with their level of trust in formal sources of information and with greater levels of depression and anxiety. Nevertheless, these pathways were independent of each other. The results indicate the direct impact of COVID-19 public information on subjective well-being, a relationship that merits further exploration.

Pathogen and Host Associations of Soft Ticks Collected in South Texas.

Background: Soft ticks (Family: Argasidae) are vectors of relapsing fever Borrelia in the United States and are potential vectors of African swine fever virus, a pathogen that could have a devastating effect on the U.S. swine industry if introduced to the U.S. mainland. Much of the tick-borne disease research in the U.S. focuses on hard ticks, and less is known about the ecology of soft ticks. Some soft tick species found in the southern U.S. have a wide host range and may feed on cattle, swine, native and exotic ungulates, small mammals, reptiles, and humans. Because the feeding habit of most soft tick species involves taking short, repeated blood meals that may include multiple host species, pathogen transmission among hosts is a concern both for human and animal health. Materials and Methods: Sampling was carried out at four locations in south Texas using dry ice traps placed in or near animal burrows and other sheltering cracks and crevasses that may provide refuge for soft ticks. Collected ticks were identified and subsequently screened for Rickettsia and Borrelia species and for host bloodmeal detection using conventional polymerase chain reaction and Sanger sequencing for pathogen and host species identification. Results: In total, 256 ticks of two Ornithodorinae species were screened. Borrelia species were identified in three samples. Bloodmeal detections were made in 22 tick specimens, representing eight vertebrate host species. Conclusions: Results demonstrate that the soft tick species detected herein feed on a range of wildlife hosts in south Texas and are associated with agents of human disease.

A stochastic optimization model for patient evacuation from health care facilities during hurricanes

We propose a rigorous modeling and methodological effort that integrates statistical implementation of hydrology models in predicting inland and coastal flood scenarios due to hurricanes and a scenario-based stochastic integer programming model which suggests resource and staging area decisions in the first stage and the evacuation decisions in the second stage. This novel study combines physics-based flood prediction models and stochastic optimization for large-scale multi-facility coordination of hospital and nursing home evacuations before impending hurricanes. The optimization model considers scenario-dependent evacuation demand, transport vehicles with varying capacities, and both critical and non-critical patients. Utilizing Hurricane Harvey of 2017 as a case study and actual healthcare facility locations in southeast Texas, we explore various evacuation policies, demonstrating the impact of routing strategies, staging area decisions, flood thresholds, and receiving facility capacities on evacuation outcomes. One of the findings is that choosing staging area(s) and deploying evacuation vehicles optimally considering the uncertainty of the hurricane’s path at the time of decision making could have significant effect on the total cost of the operation and evacuation time experienced by the evacuees. We also show the non-negligible value of the scenario-based staging and routing solution conservatively calculated in relation to a single scenario solution using the concept of value of stochastic solution.

Quantifying the Chemical Composition and Real-Time Mass Loading of Nanoplastic Particles in the Atmosphere Using Aerosol Mass Spectrometry.

Plastic debris, including nanoplastic particles (NPPs), has emerged as an important global environmental issue due to its detrimental effects on human health, ecosystems, and climate. Atmospheric processes play an important role in the transportation and fate of plastic particles in the environment. In this study, a high-resolution time-of-flight aerosol mass spectrometer (HR-ToF-AMS) was employed to establish the first online approach for identification and quantification of airborne submicrometer polystyrene (PS) NPPs from laboratory-generated and ambient aerosols. The fragmentation ion C8H8+ is identified as the major tracer ion for PS nanoplastic particles, achieving an 1-h detection limit of 4.96 ng/m3. Ambient PS NPPs measured at an urban location in Texas are quantified to be 30 ± 20 ng/m3 by applying the AMS data with a constrained positive matrix factorization (PMF) method using the multilinear engine (ME-2). Careful analysis of ambient data reveals that atmospheric PS NPPs were enhanced as air mass passed through a waste incinerator plant, suggesting that incineration of waste may serve as a source of ambient NPPs. The online quantification of NPPs achieved through this study can significantly improve our understanding of the source, transport, fate, and climate effects of atmospheric NPPs to mitigate this emerging global environmental issue.

Understanding fatality patterns and sex ratios of Brazilian free-tailed bats (Tadarida brasiliensis) at wind energy facilities in western California and Texas

Background Operation of wind turbines has resulted in collision fatalities for several bat species, and one proven method to reduce these fatalities is to limit wind turbine blade rotation (i.e., curtail turbines) when fatalities are expected to be highest. Implementation of curtailment can potentially be optimized by targeting times when females are most at risk, as the proportion of females limits the growth and stability of many bat populations. The Brazilian free-tailed bat (Tadarida brasiliensis) is the most common bat fatality at wind energy facilities in California and Texas, and yet there are few available data on the sex ratios of the carcasses that are found. Understanding the sex ratios of fatalities in California and Texas could aid in planning population conservation strategies such as informed curtailment. Methods We used PCR to determine the sex of bat carcasses collected from wind energy facilities during post-construction monitoring (PCM) studies in California and Texas. In California, we received samples from two locations within the Altamont Pass Wind Resource Area in Alameda County: Golden Hills (GH) (n = 212) and Golden Hills North (GHN) (n = 312). In Texas, we received samples from three wind energy facilities: Los Mirasoles (LM) (Hidalgo County and Starr County) (n = 252), Los Vientos (LV) (Starr County) (n = 568), and Wind Farm A (WFA) (San Patricio County and Bee County) (n = 393). Results In California, the sex ratios of fatalities did not differ from 50:50, and the sex ratio remained stable over the survey years, but the seasonal timing of peak fatalities was inconsistent. In 2017 and 2018, fatalities peaked between September and October, whereas in 2019 and 2020 fatalities peaked between May and June. In Texas, sex ratios of fatalities varied between locations, with Los Vientos being female-skewed and Wind Farm A being male-skewed. The sex ratio of fatalities was also inconsistent over time. Lastly, for each location in Texas with multiple years studied, we observed a decrease in the proportion of female fatalities over time. Discussion We observed unexpected variation in the seasonal timing of peak fatalities in California and differences in the sex ratio of fatalities across time and facility location in Texas. In Texas, proximity to different roost types (bridge or cave) likely influenced the sex ratio of fatalities at wind energy facilities. Due to the inconsistencies in the timing of peak female fatalities, we were unable to determine an optimum curtailment period; however, there may be location-specific trends that warrant future investigation. More research should be done over the entirety of the bat active season to better understand these trends in Texas. In addition, standardization of PCM studies could assist future research efforts, enhance current monitoring efforts, and facilitate research on post-construction monitoring studies.

Spatio-Temporal Assessment of Heavy-Duty Truck Incident and Inspection Data

Vehicular incidents, especially those involving tractor trailers, are increasing in number every year. These events are extremely costly for fleets, in terms of damage or loss of property, loss of efficiency, and certainly in terms of loss of life. Although the U.S. Department of Transportation (DOT) is responsible for performing inspections, and fleet managers are encouraged to maintain their fleet and participate in regular inspections, it is uncertain whether these inspections are occurring at a frequency that is necessary to prevent incidents. The Federal Motor Carrier Safety Administration (FMCSA) of the DOT manages and maintains the Motor Carrier Management Information System (MCMIS) dataset, which contains all incident and inspection data regarding commercial vehicles in the U.S. The purpose of this preliminary analysis was to explore the MCMIS dataset through spatiotemporal analyses, to uncover findings that may hint at potential improvements in the DOT inspection process and highlight location-specific trends in the dataset. These analyses are novel, as previous research using the MCMIS dataset only examined the data at the state or county level, not at a national scale. The results from the analyses pinpointed specific major metropolitan areas, namely Harris County (Houston), Texas, and three of the New York boroughs (Kings, Queens, and the Bronx), which were found to have increasing incident rates during the study period (2016–2020). An overview of potential causal factors contributing to this increase are provided as well as an overview of the inspection process, and suggestions for improvement relative to the highlighted locations in Texas and New York are also provided. Ultimately, it is suggested that the incorporation of advanced technology and automation may prove beneficial in reducing the occurrence of events that lead to incidents and may also help in the inspection process.

Evaluation of aerosol- and gas-phase tracers for identification of transported biomass burning emissions in an industrially influenced location in Texas, USA

Abstract. As criteria pollutants from anthropogenic emissions have declined in the US in the last 2 decades, biomass burning (BB) emissions are becoming more important for urban air quality. Tracking the transported BB emissions and their impacts is challenging, especially in areas that are also burdened by anthropogenic sources like the Texas Gulf Coast. During the Corpus Christi and San Antonio (CCSA) field campaign in spring 2021, two long-range-transport BB events (BB1 and BB2) were identified. The observed patterns of an absorption Ångström exponent (AAE), a high-resolution time-of-flight aerosol mass spectrometer (HR-ToF-AMS) BB tracer (f60), equivalent black carbon (eBC), acetonitrile and carbon monoxide (CO) during BB1 and BB2 indicated differences in the mixing of transported BB plumes with local anthropogenic sources. The combined information from HYSPLIT backward-trajectory (BT) and satellite observations revealed that BB1 had mixed influence of transported smoke plumes from fires in central Mexico, the Yucatán Peninsula and the central US, whereas BB2 was influenced by fires in the central US. The estimated transport times of smoke from the Mexican fires and the central US fires to our study site were not too different (48–54 and 24–36 h, respectively), and both events appeared to have undergone similar levels of atmospheric processing, as evident in the elemental ratios of bulk organic aerosol (OA). We observed an aging trend for f44 vs. f60 and f44 vs. f43 as a function of time during BB2 but not during BB1. Positive matrix factorization (PMF) analysis of OA showed that BB1 had a mixture of organics from aged BB emissions with an anthropogenic marine signal, while the oxidized organic compounds from aged BB emissions dominated the aerosols during BB2. The size distribution of aerosol composition revealed distinct characteristics between BB1 and BB2, where BB1 was found to be externally mixed, exhibiting a combination of BB and anthropogenic marine aerosols. On the other hand, BB2 exhibited internal mixing dominated by aged BB aerosol. Our analysis from mobile and stationary measurements highlights that both CO and acetonitrile are likely impacted by local sources even during the BB events and specifically that acetonitrile cannot be used as a unique BB tracer for dilute BB plumes in an industrially influenced location. A suitable volatile organic compound (VOC) tracer would need to be emitted in high concentrations during BB, resistant to degradation during transport, unique to BB and able to be measured in the field. This study effectively demonstrates that AAE and aerosol BB tracers served as precise and effective tracers in these complex emission scenarios. Network deployment of multiwavelength photometers holds promise for enhancing our understanding of BB impacts on air quality and supporting informed decision-making for effective mitigation strategies in locations with mixed sources and influence of dilute BB plumes. To demonstrate the relevance of such an aerosol optical network, we provide evidence of the potential regional impacts of these transported BB events on urban O3 levels using measurements from the surface air quality monitoring network in Texas.

Pedigree-based QTL analysis of flower size traits in two multi-parental diploid rose populations.

Rose (Rosa spp.) is one of the most economically important ornamental species worldwide. Flower diameter, flower weight, and the number of petals and petaloids are key flower-size parameters and attractive targets for DNA-informed breeding. Pedigree-based analysis (PBA) using FlexQTL software was conducted using two sets of multi-parental diploid rose populations. Phenotypic data for flower diameter (Diam), flower weight (fresh (FWT)/dry (DWT)), number of petals (NP), and number of petaloids (PD) were collected over six environments (seasons) at two locations in Texas. The objectives of this study were to 1) identify new and/or validate previously reported QTL(s); 2) identify SNP haplotypes associated with QTL alleles (Q-/q-) of a trait and their sources; and 3) determine QTL genotypes for important rose breeding parents. Several new and previously reported QTLs for NP and Diam traits were identified. In addition, QTLs associated with flower weight and PD were identified for the first time. Two major QTLs with large effects were mapped for all traits. The first QTL was at the distal end of LG1 (60.44-60.95 Mbp) and was associated with Diam and DWT in the TX2WOB populations. The second QTL was consistently mapped in the middle region on LG3 (30.15-39.34 Mbp) and associated with NP, PD, and flower weight across two multi-parent populations (TX2WOB and TX2WSE). Haplotype results revealed a series of QTL alleles with differing effects at important loci for most traits. This work is distinct from previous studies by conducting co-factor analysis to account for the DOUBLE FLOWER locus while mapping QTL for NP. Sources of high-value (Q) alleles were identified, namely, 'Old Blush' and Rosa wichuraiana from J14-3 for Diam, while 'Violette' and PP-J14-3 were sources for other traits. In addition, the source of the low-value (q) alleles for Diam was 'Little Chief', and Rosa wichuraiana through J14-3 was the source for the remaining traits. Hence, our results can potentially inform parental/seedling selections as means to improve ornamental quality in roses and a step towards implementing DNA-informed techniques for use in rose breeding programs.

Genotyping of Jujube (Ziziphus spp.) Germplasm in New Mexico and Southwestern Texas.

Since the early 19th century, a substantial amount of jujube (Ziziphus spp.) germplasm has been introduced from China and Europe into the United States. However, due to a lack of passport data, cultivar mislabeling is common and the genetic background of the introduced germplasm remains unknown. In the present study, a low-density SNP array was employed to genotype 204 jujube trees sampled from multiple locations in New Mexico, Texas, Missouri, and Kentucky. Multilocus matching of SNP profiles revealed a significant rate of genetic redundancy among these jujube samples. A total of 14 synonymous groups were detected, comprising 48 accessions. Bayesian clustering analysis and neighbor-joining tree partitioned the US jujube germplasm into two major clusters. The first cluster included cultivated genotypes (Ziziphus jujuba Mill.), whereas the other major cluster comprised the wild/sour jujube (Ziziphus spinosa Hu.). The results also revealed a unique jujube population at Fabens/Tornillo, Texas, and a semi-naturalized population at Tucumcari, NM. These findings will provide valuable guidance to jujube growers and researchers on the effective utilization of jujube germplasm in the horticultural industry.

Emission Ratios and Diurnal Variability of Volatile Organic Compounds and Influence of Industrial Emissions in Two Texas Cities

Changing urban emission landscapes and increasing population make it imperative to understand the driving forces for air quality in growing urban areas. Recent field studies in an industrial area in Houston and a semiurban area in San Antonio reveal unique emission signatures for these two growing Texas cities. A comparison of benzene, toluene, xylenes, isoprene, and methyl ethyl ketone (MEK) was conducted for these two Texas locations and previous studies in other megacities. It was found that San Antonio had similar emission ratios as these megacities for benzene, toluene, and xylenes (1.10, 4.57, and 3.60 pptv ppbv−1 of CO, respectively), likely indicating a similar traffic emission source. Isoprene and MEK were of biogenic origin in San Antonio. However, analysis of emission ratios, diurnal trends, and comparison with emission inventories indicated that benzene, toluene, and MEK were likely associated with fugitive and stack emissions in the industrial corridor in Houston. Isoprene in Houston appeared to have mixed fugitive and biogenic sources in Houston, based on diurnal trends and emission ratio. The peak nighttime concentrations for benzene, toluene, xylene, isoprene, and MEK observed during the campaign were 66, 533, 21, 138, and 731 ppbv, respectively, in the Houston site. The emission ratio for xylenes (3.37 pptv ppbv−1 of CO) for the Houston site was similar to Paris, London, and Mexico City, despite emission inventories indicating high fugitive and stack emissions. The conditional probability function (CPF) analysis closely matched the direction of the industrial sources with the highest recorded emission levels as listed in the emission inventory for the Houston site. The estimated ozone production efficiency (OPE) for the industrial area in Houston indicated volatile organic compound (VOC)–limited conditions in the morning, which transitioned to nitrogen oxide (NOx)–limited conditions in the afternoon. Texas cities have complex emission scenarios, and future efforts to mitigate ozone and particulate matter may have to consider a variety of emission reduction strategies.

Coastal response to global warming during the Paleocene-Eocene Thermal Maximum

Global warming during the Paleocene-Eocene Thermal Maximum (PETM) is hypothesized to have had a profound effect on the paleohydrologic cycle, including enhanced seasonality and increased water and sediment discharge. Although the PETM may represent the closest geologic analog for future global climate changes, the effects of this event on ancient coastal systems are poorly understood. We examined drill core from two locations in eastern Texas that preserve a record of tidally influenced deltaic sedimentation associated with the paleo-Colorado River that drained up to 2 × 106 km2 of central North America, approximately two-thirds of the area of the modern Mississippi River catchment. In these cores, the development of a regionally extensive sand-rich unit (the Carrizo Formation) at the onset of the PETM is identified from a negative carbon isotope excursion and supported by detrital zircon UPb geochronology and pollen occurrence data. The basal Carrizo Formation indicates that the onset of the PETM was characterized by an increase in the delivery of coarser-grained sediments and progradation of the coastline, which occurred despite rising sea level. Using a mass-balance framework for equilibrium deltaic systems, we estimate that sediment delivery to the coastline increased by ca. 46% (2-σ: 13% to 167%). Our findings of enhanced sediment delivery to the coast are consistent with proxy climatic and sedimentologic data indicating heightened precipitation seasonality in the interior of North America during the PETM. Thus, the effects of a regional change in climate forced by greenhouse events were transmitted downstream by large river systems to produce shifts in coastal sediment supply, progradation, and coastline evolution.

Regional Variation in Feeding Patterns of Sheepshead (Archosargus probatocephalus) in the Northwest Gulf of Mexico

Feeding patterns of sheepshead, Archosargus probatocephalus, in the northwest Gulf of Mexico were examined from samples collected at two locations in Texas, USA; Galveston and Port Aransas. A total of 53 sheepshead stomachs (Galveston, n = 35; Port Aransas, n = 18) had their contents analyzed along with tissue samples from the muscle and liver for a stable isotope analysis (δ13C, δ15N, and δ34S) because they provide a contrast between short-term (liver) and long-term (muscle) measurements. Multiple species of amphipods made up the majority of the prey items in sheepshead from Galveston (%IRI = 61.79), whereas barnacles were the primary diet item for sheepshead collected in Port Aransas (%IRI = 39.53). We observed diet shifts prior to and during the spawning season. MANOVA revealed significant differences in δ13C, δ15N, and δ34S stable isotope values from the muscle and liver tissue of sheepshead based on the location. In both muscle and liver samples, δ13C values were lower in Galveston than Port Aransas, but δ15N and δ34S values were higher in Galveston than Port Aransas. Niche size and overlap also differed between sheepshead from both locations and tissue types. Sheepshead collected in Galveston had a larger niche size in the muscle and liver samples ((mean ± SD) 479.3 ± 131.2, muscle; 433.3 ± 120.3, liver) than Port Aransas (178.8 ± 54.3, muscle; 270.0 ± 80.9, liver). The trophic niche of sheepshead from Galveston overlapped Port Aransas in muscle samples by 16.47% and 18.56% in liver samples. The trophic niche overlap of sheepshead from Port Aransas measured in muscle samples overlapped with sheepshead from Galveston by 18.49% and by 39.17% in liver samples. This study shows that there are subtle but significant differences between the diets of sheepshead along the Texas coast, with the majority of the differences potentially attributable to differences in the prey field along the natural salinity gradient of the Texas coast. This work provides an insight into the widely generalist grazing behavior of sheepshead, which potentially changes during the springtime spawning season.

Pedigree-based analysis in multi-parental diploid rose populations reveals QTLs for cercospora leaf spot disease resistance.

Cercospora leaf spot (CLS) (Cercospora rosicola) is a major fungal disease of roses (Rosa sp.) in the southeastern U.S. Developing CLS-resistant cultivars offers a potential solution to reduce pesticide use. Yet, no work has been performed on CLS resistance. This study aimed to identify QTLs and to characterize alleles for resistance to CLS. The study used pedigree-based QTL analysis to dissect the genetic basis of CLS resistance using two multi-parental diploid rose populations (TX2WOB and TX2WSE) evaluated across five years in two Texas locations. A total 38 QTLs were identified across both populations and distributed over all linkage groups. Three QTLs on LG3, LG4, and LG6 were consistently mapped over multiple environments. The LG3 QTL was mapped in a region between 18.9 and 27.8 Mbp on the Rosa chinensis genome assembly. This QTL explained 13 to 25% of phenotypic variance. The LG4 QTL detected in the TX2WOB population spanned a 35.2 to 39.7 Mbp region with phenotypic variance explained (PVE) up to 48%. The LG6 QTL detected in the TX2WSE population was localized to 17.9 to 33.6 Mbp interval with PVE up to 36%. Also, this study found multiple degrees of favorable allele effects (q-allele) associated with decreasing CLS at major loci. Ancestors 'OB', 'Violette', and PP-M4-4 were sources of resistance q-alleles. These results will aid breeders in parental selection to develop CLS-resistant rose cultivars. Ultimately, high throughput DNA tests that target major loci for CLS could be developed for routine use in a DNA-informed breeding program.

A Deep Learning Based Method to Delineate the Wet/Dry Shoreline and Compute Its Elevation Using High-Resolution UAS Imagery

Automatically detecting the wet/dry shoreline from remote sensing imagery has many benefits for beach management in coastal areas by enabling managers to take measures to protect wildlife during high water events. This paper proposes the use of a modified HED (Holistically-Nested Edge Detection) architecture to create a model for automatic feature identification of the wet/dry shoreline and to compute its elevation from the associated DSM (Digital Surface Model). The model is generalizable to several beaches in Texas and Florida. The data from the multiple beaches was collected using UAS (Uncrewed Aircraft Systems). UAS allow for the collection of high-resolution imagery and the creation of the DSMs that are essential for computing the elevations of the wet/dry shorelines. Another advantage of using UAS is the flexibility to choose locations and metocean conditions, allowing to collect a varied dataset necessary to calibrate a general model. To evaluate the performance and the generalization of the AI model, we trained the model on data from eight flights over four locations, tested it on the data from a ninth flight, and repeated it for all possible combinations. The AP and F1-Scores obtained show the success of the model’s prediction for the majority of cases, but the limitations of a pure computer vision assessment are discussed in the context of this coastal application. The method was also assessed more directly, where the average elevations of the labeled and AI predicted wet/dry shorelines were compared. The absolute differences between the two elevations were, on average, 2.1 cm, while the absolute difference of the elevations’ standard deviations for each wet/dry shoreline was 2.2 cm. The proposed method results in a generalizable model able to delineate the wet/dry shoreline in beach imagery for multiple flights at several locations in Texas and Florida and for a range of metocean conditions.

Planning for Bike Share Connectivity to Rail Transit

Bike sharing can play a role in providing access to transit stations and then to final destinations, but early implementation of these systems in North America has been opportunistic rather than strategic. This study evaluates local intermodal plan goals using trip data and associated infrastructure such as transit stops and bike share station locations in Austin, Texas, and Chicago, Illinois. Bike sharing use data from both cities suggest a weak relationship with existing rail stations that could be strengthened through collaborative, intermodal planning. The study suggests a planning framework and example language that could be tailored to help address the linkage between bike sharing and transit. Rather than an exhaustive study of the practice, this study provides evidence from these two cities that identify opportunities to improve intermodal planning. Cities that are planning or expanding a bike sharing system should consider carefully how to leverage this mode with existing modes of transport. Regardless of a city’s status in implementing a bike sharing system, planners can leverage information on existing transport systems for planning at regional and local levels.

Trends in Lesser Prairie-Chicken Habitat Extent and Distribution on the Southern High Plains

The lesser prairie-chicken (Tympanuchus pallidicinctus) is a species of prairie grouse that occupies grassland ecosystems in the Southern and Central High Plains of the Great Plains. Reduced abundance and occupied ranges have led to increased conservation efforts throughout the species’ range. Habitat loss is considered the predominant cause of these declines. In the Southern High Plains of Texas and New Mexico, lesser prairie-chicken habitat corresponds to the Sand Shinnery Oak Prairie Ecoregion, which is comprised of a mixture of sand shinnery oak (Quercus havardii)-dominated grasslands, sand sagebrush (Artemisia filifolia)-dominated grasslands, and mixed grasslands. In sand shinnery oak–grassland communities, conversion to row-crop agriculture, continuous unmanaged livestock grazing, restriction of natural fire, invasive plant species (e.g., mesquite (Prosopis spp.)), extensive use of herbicides, energy development, and a variety of other factors have also negatively affected ecosystem extent and function. We integrated historical maps and remote sensing-derived information to measure trends in the extent and geographical distribution of sand shinnery oak prairies in eastern New Mexico and northwest Texas. Potential lesser prairie-chicken habitat was reduced by 56% from a potential of 43,258 km2 to 18,908 km2 in ~115 years (since pre-settlement). Our assessment indicated both mixed grasslands and sand shinnery oak-dominated grasslands were transformed from large parcels of existing vegetation communities to urban settlements, row crops, roads, and industrial land uses by the 1970s. Currently, potential habitat is highly fragmented and restricted to isolated locations in Texas and New Mexico, with an increasing dominance in mixed grasslands, especially in the southeastern portion of the lesser prairie-chicken range. Sand shinnery oak-dominated grasslands have been declining rapidly, from 69% of its potential extent in 1985, 65% in 1995, 54% in 2005, to 42% in 2015. Mixed grasslands drastically declined to 50% of its potential distribution by 1985. Since then, it has been stable until the 2005–2015 period when it declined to 45% of its potential extent. Based on the 2015 assessment, the current potential habitat for lesser prairie-chicken is estimated at 18,908 km2 (1,890,800 ha or 4.6 million acres), where 13,126 km2 corresponds to mixed grasslands and 5782 km2 corresponds to sand shinnery oak-dominated grasslands.

Use of a Latin square design to assess experimental errors in field evaluation of cotton for resistance to Fusarium wilt Race 4

AbstractField evaluation of cotton for resistance to Fusarium oxysporum f. sp. vasinfectum Race 4 (FOV4) is important in breeding. In this study, an 8 × 8 Latin square design was arranged in two FOV4‐infested fields each with two trials to evaluate eight cotton (Gossypium hirstum) cultivars based on mortality rate (MR) and root vascular staining (RVS). For a comparison, two trials of the same design were grown in the greenhouse. Consistent with the mapping pattern of MR in the Texas field, the analysis of variance confirmed the existence of effects due to tiers not planting rows in the Texas location only. Significant variation due to cultivars was consistently detected in the two trials of both locations. The repeatability was confirmed by significant correlation coefficients between most tiers (replications) and between the two trials in each field. The greenhouse test had the highest mean MR (72–78%) and lowest coefficients of variation (CV; 17–28%), followed by the Texas field with a lower MR (36–57%) and similar CV (22–29%); and the New Mexico test had the highest CV (59–73%) and the lowest MR (13–18%). The MR between the two fields and between the fields and the greenhouse were significantly correlated. ‘Pima S‐7’ had the highest MR (79–93%), whereas ‘FM 2334GLT’ had the lowest (15–35%), consistent with RVS at crop maturity. Among randomized complete block designs (RCBD) with three to seven replications, the mean squared error and CV were the lowest in RCBD with three replications.

QTL mapping and characterization of black spot disease resistance using two multi-parental diploid rose populations.

Black spot disease (BSD) (Diplocarpon rosae) is the most common and damaging fungal disease in garden roses (Rosa sp.). Although qualitative resistance to BSD has been extensively investigated, the research on quantitative resistance lags behind. The goal of this research was to study the genetic basis of BSD resistance in two multi-parental populations (TX2WOB and TX2WSE) through a pedigree-based analysis approach (PBA). Both populations were genotyped and evaluated for BSD incidence over five years in three locations in Texas. A total of 28 QTLs, distributed over all linkage groups (LGs), were detected across both populations. Consistent minor effect QTLs included two on LG1 and LG3 (TX2WOB and TX2WSE), two on LG4 and LG5 (TX2WSE), and one QTL on LG7 (TX2WOB). In addition, one major QTL detected in both populations was consistently mapped on LG3. This QTL was localized to an interval ranging from 18.9 to 27.8 Mbp on the Rosa chinensis genome and explained 20 and 33% of the phenotypic variation. Furthermore, haplotype analysis showed that this QTL had three distinct functional alleles. The parent PP-J14-3 was the common source of the LG3 BSD resistance in both populations. Taken together, this research presents the characterization of new SNP-tagged genetic determinants of BSD resistance, the discovery of marker-trait associations to enable parental choice based on their BSD resistance QTL haplotypes, and substrates for the development of trait-predictive DNA tests for routine use in marker-assisted breeding for BSD resistance.

Environmental Determinates of Distribution for Dragonfly Nymphs (Odonata: Anisoptera) in Urban and Non-Urban East Texas Streams, USA

We collected environmental and habitat data for nymphs of 12 dragonfly species (Odonata: Anisoptera) from 91 stream sites throughout eastern Texas, including urban and non-urban locations. Understanding the relationship of dragonflies to habitat structure and other environmental variables is crucial for the purpose of conserving these insects and better using them as predictive tools for water quality assessments, and refining tolerance values. The objectives of this study were to determine the key environmental variables influencing the diversity and distribution of dragonflies in eastern Texas streams, and further determine if differences in those factors could be observed between urban and nonurban sites. We collected samples separately from benthic habitats and woody snag habitats. Significantly fewer sites were observed to have dragonfly species on snag habitat (mean = 1.25) compared to benthic samples (mean = 14.67) (t-test, p = 0.001). The number of dragonfly species collected among non-urban streams (mean = 9.83) was not significantly different than urban streams (mean = 6.08; t-test, p = 0.07). Detrended correspondence analysis of benthic and snag habitat data collected from non-urban and urban locations showed that most of the species are oriented most closely to benthic habitats in non-urban streams. Snag habitat was shown to be poorly ordinated for all of the species. A canonical correspondence analysis of 29 water quality and habitat variables as environmental determinants of dragonfly diversity and distribution showed that distributional relationships among species are complex and often described by multiple environmental factors.

This Month in Anesthesiology

This Month in Anesthesiology