IMPLICATIONS OF TREATING PARASITIC INFECTION IN NORTHERN BOBWHITE (COLINUS VIRGINIANUS) ON OVERALL HELMINTH LIFE CYCLE

This study was conducted to determine how reducing the parasite burden in a definitive host may affect the prevalence in intermediate hosts. Here we used the eyeworm Oxyspirura petrowi and cecal worm Aulonocephalus pennula as model species. Northern bobwhite quail (Colinus virginianus) were provided an anthelmintic medicated feed in wild systems because of convincing evidence that these parasites were suppressing their populations. Eyeworm and cecal worm prevalence were measured in Orthopterans, which act as intermediate hosts, using polymerase chain reaction. Individuals were collected from a control site, a site treated for 2 yr, and a site treated for 5 yr. Orthopteran community composition was significantly different among the sites; however, an interaction between subfamily and site was not significant for the eyeworm. There was a significant reduction in eyeworm-infected Orthopterans on the 5-yr site compared with the other 2, suggesting that treatment of a definitive host may indeed affect the prevalence of eyeworms during other life-cycle stages. There was an interaction between the Orthopteran subfamily and the site for the cecal worm, so results were analyzed within each subfamily. A significant reduction in the prevalence of cecal worms was only found in the Cyrtacanthacridinae subfamily on the 5-yr site when compared with the other sites. However, the greatest prevalence in the Gomphocerinae and Oedipodinae subfamilies across all 3 sites was 4.1%. This indicates an unknown degree of cecal worm host specificity. Therefore, conclusions could not be made through the simple assessment of prevalence.

Identification of eyeworm (Oxyspirura petrowi) and caecal worm (Aulonocephalus pennula) infection levels in Northern bobwhite quail (Colinus virginianus) of the Rolling Plains, TX using a mobile research laboratory: Implications for regional surveillance

Over the last few decades, there has been a decline in Northern bobwhite quail (Colinus virginianus) throughout their native range. While there are various factors that may be influencing this decline, it is suggested that parasites should be taken into consideration as a potential contributor in the Rolling Plains Ecoregion. High prevalence of the eyeworm (Oxyspirura petrowi) and caecal worm (Aulonocephalus pennula) in bobwhite of this region, coupled with a continuous decline, creates a need to assess infection through alternative methods for regional surveillance. Previous studies have developed a qPCR method and mobile research laboratory as an option for nonlethal procedures. However, there is still a need for standardization of these techniques. Therefore, this study builds on previous protocols to develop an application that considers factors that may influence qPCR results. In this study, cloacal swabs are collected from bobwhite in three locations throughout the Rolling Plains and scaled based on amount of feces present on the swab. This data is compared to qPCR standards as a limit of quantification for both eyeworm and caecal worm to define parasitic infection levels. Binary logistic regressions confirm that the probability of detection increases for both eyeworm (Odds Ratio: 2.3738; 95% Confidence Interval: [1.7804, 3.1649]) and caecal worm (Odds Ratio: 2.8516; 95% Confidence Interval: [2.2235, 3.6570]) as swab score increases. Infection levels for eyeworm and caecal worm are based on the generated cycle threshold value averages of qPCR standards. Based on the results of this study, this method can be applied in the mobile research laboratory to quantitatively assess regional parasitic infection in bobwhite throughout the Rolling Plains.

Predicting seasonal infection of eyeworm (Oxyspirura petrowi) and caecal worm (Aulonocephalus pennula) in northern bobwhite quail (Colinus virginianus) of the Rolling Plains Ecoregion of Texas, USA

The northern bobwhite quail (Colinus virginianus) is a popular gamebird in the Rolling Plains Ecoregion of West Texas. However, there has been a population decline in this area over recent decades. Consistent reports indicate a high prevalence of the eyeworm (Oxyspirura petrowi) and caecal worm (Aulonocephalus pennula), which may be of major influence on the bobwhite population. While research has suggested pathological consequences and genetic relatedness to other pathologically significant parasites, little is known about the influence of climate on these parasites. In this study, we examined whether seasonal temperature and precipitation influences the intensity of these parasites in bobwhite. We also analyzed quantitative PCR results for bobwhite feces and cloacal swabs against temperature and precipitation to identify climatic impacts on parasite reproduction in this region. Multiple linear regression analyses were used for parasite intensity investigation while binary logistic regression analyses were used for parasite reproduction studies. Our analyses suggest that caecal worm intensity, caecal worm reproduction, and eyeworm reproduction are influenced by temperature and precipitation. Temperature data was collected 15, 30, and 60 days prior to the date of collection of individual bobwhite and compared to qPCR results to generate a temperature range that may influence future eyeworm reproduction. This is the first preliminary study investigating climatic influences with predictive statistics on eyeworm and caecal worm infection of northern bobwhite in the Rolling Plains.

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Bobwhite quail in West Texas, USA have high prevalence of eyeworm and caecal worm.

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Wild quail were necropsied and fecal samples collected.

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Parasite intensity and reproduction from this data compared to climate data of study location.

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Caecal worm intensity, reproduction, and eyeworm reproduction influenced by climate.

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Eyeworm reproduction influenced by temperature 60 days prior to bobwhite collection.

Inference for reliability and stress-strength for a scaled Burr type X distribution

Inference for R = P(Y < X) is considered when X and Y are independently distributed as scaled Burr type X random variables. Under this model, exact inference procedures for R cannot be found. Hence, based on the expected Fisher information matrix which is derived here, asymptotic inference procedures for R and other general functions of the parameters are developed. A bootstrap method to estimate variance for the maximum likelihood estimators is also discussed. To illustrate these techniques, an example using carbon fiber strength data is given. Simulations to assess the effectiveness of these techniques, as well as other concerns, are presented.