Examining characteristics and sampling methods of phosphor dynamics in lowland catchments

Despite over two decades since the EU Water Framework Directive have passed, achieving the desired water quality in German surface waters remains challenging, regardless of efforts to reduce phosphorus inputs and associated environmental impacts. This study aims at analyzing the characteristics governing the concentrations of four key water quality parameters (total phosphorus, orthophosphate, particulate phosphate, and suspended solids) in two lowland catchments: the 50 km2 catchment of the Kielstau, Germany, and its 7 km2 tributary, the Moorau, which are dominated by agricultural land use. To this end, different sampling methods, particularly high-resolution precipitation event-based sampling and daily mixed samples, are conducted and evaluated, and their effectiveness is compared. The identification of sources and characteristics that affect phosphorus and suspended sediment dynamics, both in general and specifically during heavy precipitation events, is one focus of the study. Over a 15-year period, increasing concentrations of these parameters were observed in daily mixed samples, exhibiting distinct seasonal patterns-higher in summer and lower in winter-consistent with lowland catchment behavior. Particularly during heavy precipitation events, the smaller catchment exhibits a more complex and less predictable response to chemical concentrations compared with the dilution effect observed in the larger catchment. The results underline the complexity of phosphorus dynamics in small catchments and emphasize the importance of event-based sampling for capturing short-term concentration peaks for all four parameters, particularly beneficial regarding measuring suspended solids. While daily mixed samples capture average phosphorus concentrations, event-based sampling is crucial for detecting short-term spikes, providing a more comprehensive understanding of phosphorus dynamics.

Innovative analytical methodologies for characterizing chemical exposure with a view to next-generation risk assessment

The chemical burden on the environment and human population is increasing. Consequently, regulatory risk assessment must keep pace to manage, reduce, and prevent adverse impacts on human and environmental health associated with hazardous chemicals. Surveillance of chemicals of known, emerging, or potential future concern, entering the environment-food-human continuum is needed to document the reality of risks posed by chemicals on ecosystem and human health from a one health perspective, feed into early warning systems and support public policies for exposure mitigation provisions and safe and sustainable by design strategies. The use of less-conventional sampling strategies and integration of full-scan, high-resolution mass spectrometry and effect-directed analysis in environmental and human monitoring programmes have the potential to enhance the screening and identification of a wider range of chemicals of known, emerging or potential future concern. Here, we outline the key needs and recommendations identified within the European Partnership for Assessment of Risks from Chemicals (PARC) project for leveraging these innovative methodologies to support the development of next-generation chemical risk assessment.

Evaluating sample sizes and design for monitoring and characterizing the spatial variations of potentially toxic elements in the soil

Cost-effective, representative and spatial coverage sampling designs are required to monitor the effects of potentially toxic elements (PTEs) in the soil. This study aims to evaluate the minimum sample sizes and placement of soil sampling designs to monitor and characterize the spatial variation of the PTEs (Cu, Zn, Cd, Cr, Pb, and Ni) in the soils. However, there is no standardized approach for evaluating the optimum soil sample size and monitoring location because of the spatial heterogeneity of PTEs in the soil. As a result, three broad techniques were applied. The first step was to use Global Moran's I and q-statistic values to describe the variability of soil PTEs and select appropriate evaluation methods. Second, using simple random sampling (SRS), ordinary kriging (OK), and Mean of Surface with Non-homogeneity (MSN), we estimated and evaluated soil PTEs in the current soil sampling schemes. Finally, MSN and spatial simulated annealing (SSA) optimization techniques were used to assess the required sample sizes and placements in the existing designs. Method performance was evaluated using a standard error (SE) and a relative standard error of the mean (RSE). Except for Zn and Cd, all PTEs tested showed heterogeneous distributions over the area. The MSN lowered the predicted SE by 79-86 % compared with SRS. The OK approach also outperformed the SRS method regarding mean estimated values of soil PTEs by 42-57 %. After SSA refined the initial design, the predicted SE by MSN of Cr and Zn was lowered by 13 % and 39 %, respectively. The MSN was effective with small sample sizes, reducing sample sizes and surveying costs by 39 % after SSA optimized the existing sample numbers. Thus, integrating various sampling strategies may be efficient for building optimal sample designs to monitor PTEs in the soil.

Microplastic sampling from wastewater treatment plant effluents: Best-practices and synergies between thermoanalytical and spectroscopic analysis

Wastewater treatment plants (WWTPs) may represent point sources for microplastic discharge into the environment. Quantification of microplastic in effluents of WWTPs has been targeted by several studies although standardized methods are missing to enable a comparability of results. This study discusses theoretical and practical perspectives on best practices for microplastic sampling campaigns of WWTPs. One focus of the study was the potential for synergies between thermoanalytical and spectroscopic analysis to gain more representative sampling using the complementary information provided by the different analytical techniques. Samples were obtained before and after sand filtration from two WWTPs in Germany using cascade filtration with size classes of 5,000 - 100 µm, 100 - 50 µm, and 50 - 10 µm. For spectroscopic methods samples were treated by a Fenton process to remove natural organic matter, whereas TED-GC-MS required only sample extraction from the filter cascade. µFTIR spectroscopy was used for the 100 µm and 50 µm basket filters and µRaman spectroscopy was applied to analyze particles on the smallest basket filter (10 µm). TED-GC-MS was used for all size classes as it is size independent. All techniques showed a similar trend, where PE was consistently the most prominent polymer in WWTP effluents. Based on this insight, PE was chosen as surrogate polymer to investigate whether it can describe the total polymer removal efficiency of tertiary sand filters. The results revealed no significant difference (ANOVA) between retention efficiencies of tertiary sand filtration obtained using only PE and by analyzing all possible polymers with µFTIR and µRaman spectroscopy. Findings from this study provide valuable insights on advantages and limitations of cascade filtration, the benefit of complementary analyses, a suitable design for future experimental approaches, and recommendations for future investigations.

Diabetes mellitus risk prediction in the presence of class imbalance using flexible machine learning methods

Background

Early detection and prediction of type two diabetes mellitus incidence by baseline measurements could reduce associated complications in the future. The low incidence rate of diabetes in comparison with non-diabetes makes accurate prediction of minority diabetes class more challenging.

Methods

Deep neural network (DNN), extremely gradient boosting (XGBoost), and random forest (RF) performance is compared in predicting minority diabetes class in Tehran Lipid and Glucose Study (TLGS) cohort data. The impact of changing threshold, cost-sensitive learning, over and under-sampling strategies as solutions to class imbalance have been compared in improving algorithms performance.

Results

DNN with the highest accuracy in predicting diabetes, 54.8%, outperformed XGBoost and RF in terms of AUROC, g-mean, and f1-measure in original imbalanced data. Changing threshold based on the maximum of f1-measure improved performance in g-mean, and f1-measure in three algorithms. Repeated edited nearest neighbors (RENN) under-sampling in DNN and cost-sensitive learning in tree-based algorithms were the best solutions to tackle the imbalance issue. RENN increased ROC and Precision-Recall AUCs, g-mean and f1-measure from 0.857, 0.603, 0.713, 0.575 to 0.862, 0.608, 0.773, 0.583, respectively in DNN. Weighing improved g-mean and f1-measure from 0.667, 0.554 to 0.776, 0.588 in XGBoost, and from 0.659, 0.543 to 0.775, 0.566 in RF, respectively. Also, ROC and Precision-Recall AUCs in RF increased from 0.840, 0.578 to 0.846, 0.591, respectively.

Conclusion

G-mean experienced the most increase by all imbalance solutions. Weighing and changing threshold as efficient strategies, in comparison with resampling methods are faster solutions to handle class imbalance. Among sampling strategies, under-sampling methods had better performance than others.

Assessing population-sampling strategies for reducing the COVID-19 incidence

As long as critical levels of vaccination have not been reached to ensure heard immunity, and new SARS-CoV-2 strains are developing, the only realistic way to reduce the infection speed in a population is to track the infected individuals before they pass on the virus. Testing the population via sampling has shown good results in slowing the epidemic spread. Sampling can be implemented at different times during the epidemic and may be done either per individual or for combined groups of people at a time. The work we present here makes two main contributions. We first extend and refine our scalable agent-based COVID-19 simulator to incorporate an improved socio-demographic model which considers professions, as well as a more realistic population mixing model based on contact matrices per country. These extensions are necessary to develop and test various sampling strategies in a scenario including the 62 largest cities in Spain; this is our second contribution. As part of the evaluation, we also analyze the impact of different parameters, such as testing frequency, quarantine time, percentage of quarantine breakers, or group testing, on sampling efficacy. Our results show that the most effective strategies are pooling, rapid antigen test campaigns, and requiring negative testing for access to public areas. The effectiveness of all these strategies can be greatly increased by reducing the number of contacts for infected individual.

Inclusiveness Plus Mixed-Methods: An Innovative Research Design on Transnational Practices of Older Adults

This paper assesses the challenges and the benefits of two methodological approaches for improving the study of transnational mobilities of older adults: mixed-methods and inclusiveness. The first approach refers to a mixed-methods research design based on surveys and qualitative interviews. We share our experience of conducting a "fully-mixed-concurrent-equal-status-design" research project, for which we collected data through quantitative surveys on transnational practices of people aged 55+. Furthermore, we conducted semi-structured interviews with adults aged 64+ living or who have lived in Switzerland and spend part of the year in Spain. The second approach relates to the use of an inclusive sample diversified in terms of nationality and migration backgrounds. The inclusive design affects the formulation of questions asked to all participants (and the response options provided in the survey), as well as decisions related to language choices and translations. These factors have to be considered to ensure that older adults from different backgrounds feel included. In a research project on transnational mobility of older adults, conducting an inclusive plus mixed-methods research project pushes researchers to find strategies to balance research objectives with available resources. Maximizing the research team's methodological background appears to be a suitable approach to address different population groups whilst working within a budget.

Occupancy modeling and resampling overcomes low test sensitivity to produce accurate SARS-CoV-2 prevalence estimates

Background

We evaluated whether occupancy modeling, an approach developed for detecting rare wildlife species, could overcome inherent accuracy limitations associated with rapid disease tests to generate fast, accurate, and affordable SARS-CoV-2 prevalence estimates. Occupancy modeling uses repeated sampling to estimate probability of false negative results, like those linked to rapid tests, for generating unbiased prevalence estimates.

Methods

We developed a simulation study to estimate SARS-CoV-2 prevalence using rapid, low-sensitivity, low-cost tests and slower, high-sensitivity, higher cost tests across a range of disease prevalence and sampling strategies.

Results

Occupancy modeling overcame the low sensitivity of rapid tests to generate prevalence estimates comparable to more accurate, slower tests. Moreover, minimal repeated sampling was required to offset low test sensitivity at low disease prevalence (0.1%), when rapid testing is most critical for informing disease management.

Conclusions

Occupancy modeling enables the use of rapid tests to provide accurate, affordable, real-time estimates of the prevalence of emerging infectious diseases like SARS-CoV-2.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12889-021-10609-y.

Specimen Types, Collection, and Transport for Influenza A Viruses of Swine

Detection of influenza A virus (IAV), viral antigen, nucleic acid, or antibodies in swine is dependent upon the collection of the appropriate specimen type, the quality of the specimen, and the proper storage and handling of the specimen. The diagnostic tests to be performed should be considered prior to specimen collection. Sera are acceptable specimens for ELISA or hemagglutination inhibition tests but not for real-time RT-PCR. Likewise, swabs, wipes, and/or tissues are acceptable for real-time RT-PCR and virus isolation. The specimen type will also depend on the age of the swine being tested; oral fluids can be successfully collected from weaned pigs usually greater than 3 weeks of age, whereas nasal or oral swabs should be collected from suckling pigs in the first weeks of life. The sensitivity of the RT-PCR test is such that IAV can be detected in not only the pig itself but also on surfaces that the pig contacts and in the air. This chapter will outline the collection of different specimen types and procedures for proper specimen handling.

Optimization of multidimensional MR data acquisition for relaxation and diffusion

Multidimensional MR experiments of relaxation and diffusion have been successful for material characterization and have attracted attention recently for biomedical applications. However, such experiments typically require many scans of data acquisition and are time-consuming. This work discusses a method for systematic optimization of the pulse-sequence parameters to obtain optimal resolution within the experimental conditions, such as the number of acquisitions. Other optimization goals can also be incorporated in this framework.

Common sampling and modeling approaches to analyzing readmission risk that ignore clustering produce misleading results

Background

There is little consensus on how to sample hospitalizations and analyze multiple variables to model readmission risk. The purpose of this study was to compare readmission rates and the accuracy of predictive models based on different sampling and multivariable modeling approaches.

Methods

We conducted a retrospective cohort study of 17,284 adult diabetes patients with 44,203 discharges from an urban academic medical center between 1/1/2004 and 12/31/2012. Models for all-cause 30-day readmission were developed by four strategies: logistic regression using the first discharge per patient (LR-first), logistic regression using all discharges (LR-all), generalized estimating equations (GEE) using all discharges, and cluster-weighted (CWGEE) using all discharges. Multiple sets of models were developed and internally validated across a range of sample sizes.

Results

The readmission rate was 10.2% among first discharges and 20.3% among all discharges, revealing that sampling only first discharges underestimates a population’s readmission rate. Number of discharges was highly correlated with number of readmissions (r = 0.87, P < 0.001). Accounting for clustering with GEE and CWGEE yielded more conservative estimates of model performance than LR-all. LR-first produced falsely optimistic Brier scores. Model performance was unstable below samples of 6000–8000 discharges and stable in larger samples. GEE and CWGEE performed better in larger samples than in smaller samples.

Conclusions

Hospital readmission risk models should be based on all discharges as opposed to just the first discharge per patient and utilize methods that account for clustered data.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12874-020-01162-0.

Males of a sexually cannibalistic spider chemically assess relative female quality

Background

Mate choice is a taxonomically wide-spread phenomenon, mostly exerted by females although male mate choice occurs as well. While costs and benefits of choosiness have been well studied, the underlying mechanisms are largely unclear. Different models exist, namely best-of-n or threshold rules, based on sequential or simultaneous sampling, which differ in the required cognitive demands. We applied an experimental approach to shed light on the underlying mechanisms of male mate choice in the sexually cannibalistic spider Argiope bruennichi. Males are limited to two copulations and preferentially monopolise large females, while they may leave smaller females after a single copulation and resume mate search. Here, we utilised significant size-differences between females from Northern and Southern populations and presented males with three different-sized females that were matched for origin: all three females originated either from the same Northern European population as the males or from Southern populations where the smallest female was about the same size as the largest Northern female. This allowed testing the hypothesis that males base their mating tactic on a fixed local size threshold. We predicted Northern males to be choosy among Northern females, but to accept all Southern females since they would all be above that threshold.

Results

Males copulated with the first female they encountered, which was independent of her body size. Regardless of the females’ origins, males chose a monogynous tactic with the largest female in the trio, while they left the smallest female after one copulation. The same pattern applied to Southern females even though the smallest females in the trio were of a similar size as monopolised Northern females. Since males have poor eyesight and did not actively sample all females, they likely have gained information about relative size differences between females based on volatile chemical cues only.

Conclusions

Our findings suggest that male A. bruennichi can assess relative differences in mate quality and adjust their mating tactic to the prevailing conditions (Northern vs. Southern). We reject the presence of a locally-adapted fixed threshold and argue that our results are best explained by an adjustable threshold that was raised under Southern conditions.

Application of multi-criteria decision analysis to assess sampling strategies in eutrophic urbanized waterbodies

Different water quality sampling practices such as location selection or frequency can inform future watershed management strategies. The objective of this work was to compare water quality sampling strategies based on different weighted criteria to determine the optimal sampling frequency and sampling location for an urbanized, eutrophic, freshwater system. Weekly water sampling was conducted over a 2-year period at five locations for six water quality parameters. This high frequency (HF) dataset was then deconstructed into a lower frequency (LF) dataset to simulate a monthly sampling strategy. Statistical analyses conducted showed that for all sampling locations the LF datasets were not significantly different from the HF datasets, suggesting monthly sampling is sufficient to capture the overall water quality conditions in this system. A multi-criteria decision analysis was constructed for statistical and operational criteria to determine the optimal sampling locations given different criteria weights. Results showed that the optimal sampling location changed depending on the criteria weighting, suggesting that statistical analyses alone would not be sufficient to determine optimal sampling locations in this system. This analysis was then used if optimal sampling location depended on specific water quality monitoring goals. Results showed that the optimal location depends on the particular water quality monitoring goals and that this effect should also be considered in the design of future sampling programs.

The impact of wipe sampling variables on method performance associated with indoor pesticide misuse and highly contaminated areas

Pesticide misuse incidents in residential indoor areas are typically associated with misapplications that are inconsistent with the label directions of the product. Surface wipe sampling and analysis procedures are relied upon to evaluate the extent of indoor contamination and the remediation efforts successfully. In general, surface wipe sampling procedures are widely varied, which can complicate the comparison of the results and data interpretation. Wipe sampling parameters were studied for the insecticides malathion and carbaryl. The parameters evaluated include wipe media, wetting solvents, composite sampling, surface concentration, and the influence of differing product formulations. Porous and nonporous surfaces tested include vinyl tile, plywood and painted drywall (porous/permeable) and stainless steel and glass (nonporous/impermeable). Specific wipe materials included pre-packaged sterile-cotton gauze, pre-cleaned cotton twill, cotton balls, and a pre-packaged, pre-wetted wipe. Commercially available insecticide formulations were tested, and the results were compared to surfaces fortified with neat analytes to determine surface recovery results (efficiency). A sampling procedure to measure pesticide residues was developed, and variables associated with the sampling methods were evaluated to clarify how estimations of surface residues are impacted. Malathion recoveries were 73-86% for twill and pre-wetted, pre-packaged isopropanol wipes on nonporous materials. Malathion formulations ranged from 78 to 124% for pre-wetted, pre-packaged isopropanol wipes and cotton gauze wipes on nonporous materials. Carbaryl and carbaryl formulation recoveries were 82-115% and 77-110%, respectively, on nonporous surfaces for all tested wipe materials. While not every wipe sampling variable could be tested, the collected information from this study may be useful and applied to sampling plans for classes of chemicals with similar physicochemical properties.

Sampling Methods for Leafhopper, Planthopper, and Psyllid Vectors

To reduce the spread of phytoplasmas in a crop or in a certain geographic area, epidemiological studies are of crucial importance in determining which insect species transmit these pathogens. In this chapter, we describe methods of capturing the insect vectors of phytoplasmas and the criteria for choosing the method(s) according to the objective to be achieved.

Assessment of sampling strategies for estimation of site mean concentrations of stormwater pollutants

The estimation of stormwater pollutant concentrations is a primary requirement of integrated urban water management. In order to determine effective sampling strategies for estimating pollutant concentrations, data from extensive field measurements at seven different catchments was used. At all sites, 1-min resolution continuous flow measurements, as well as flow-weighted samples, were taken and analysed for total suspend solids (TSS), total nitrogen (TN) and Escherichia coli (E. coli). For each of these parameters, the data was used to calculate the Event Mean Concentrations (EMCs) for each event. The measured Site Mean Concentrations (SMCs) were taken as the volume-weighted average of these EMCs for each parameter, at each site. 17 different sampling strategies, including random and fixed strategies were tested to estimate SMCs, which were compared with the measured SMCs. The ratios of estimated/measured SMCs were further analysed to determine the most effective sampling strategies. Results indicate that the random sampling strategies were the most promising method in reproducing SMCs for TSS and TN, while some fixed sampling strategies were better for estimating the SMC of E. coli. The differences in taking one, two or three random samples were small (up to 20% for TSS, and 10% for TN and E. coli), indicating that there is little benefit in investing in collection of more than one sample per event if attempting to estimate the SMC through monitoring of multiple events. It was estimated that an average of 27 events across the studied catchments are needed for characterising SMCs of TSS with a 90% confidence interval (CI) width of 1.0, followed by E.coli (average 12 events) and TN (average 11 events). The coefficient of variation of pollutant concentrations was linearly and significantly correlated to the 90% confidence interval ratio of the estimated/measured SMCs (R² = 0.49; P < 0.01) as well as the number of events required to achieve certain accuracy, and hence could be a promising surrogate for determining the sampling frequency needed to accurately estimate SMCs of pollutants.

Detection of subgingival periodontal pathogens--comparison of two sampling strategies

OBJECTIVE

The aim of the study is to compare detection frequency of periodontal pathogens in patients with aggressive/severe chronic periodontitis using pooled plaque samples from the deepest pockets per quadrant/per sextant.

METHODS

In 100 patients with aggressive/chronic periodontitis, subgingival plaque was sampled from the deepest pockets per quadrant (MT4) and per sextant (MT6). Plaque samples were taken using two sterile paper points simultaneously. One paper point from each pocket was pooled with the three other paper points of the pockets (MT4). Subsequently, the remaining four paper points were pooled with two paper points from the deepest pockets from the two remaining sextants (MT6). The content of each vial was analyzed with nucleic-acid based methods for Aggregatibacter actinomycetemcomitans, Tannerella forsythia, Porphyromonas gingivalis, Treponema denticola, Prevotella intermedia, Parvimonas micra, Fusobacterium nucleatum, Campylobacter rectus, Eubacterium nodatum, Eikenella corrodens, and Capnocytophaga sp.

RESULTS

The detection frequency of A. actinomycetemcomitans (MT4/MT6) at 22/24 %, T. forsythia at 93/96 %, P. gingivalis at 78/79 %, T. denticola at 88/90 %, P. intermedia at 40/46 %, P. micra at 75/79 %, F. nucleatum at both 99 %, C. rectus at 84/89 %, E. nodatum at 62/65 %, E. corrodens at 80/87 %, and Capnocytophaga sp. at 49/58 % was higher with MT6 than with MT4. None of these differences were statistically significant.

CONCLUSION

The detection frequency of the investigated periopathogens was statistically insignificant higher with the sampling method MT6 compared with MT4.

CLINICAL RELEVANCE

In daily dental practice, the plaque sampling of the deepest pockets per quadrant seems to be sufficient.

The effect of sampling strategies on assessment of water quality criteria attainment

Sample locations for large river studies affect the representativeness of data, and thus can alter decisions made regarding river conditions and the need for interventions to improve water quality. The present study evaluated three water-quality sampling programs for Total Dissolved Solid (TDS) assessment in the Monongahela River from 2008 to 2012. The sampling plans cover the same 145 km of river but differ in frequency, sample location and type (e.g., river water sample vs drinking water plant intake sample). Differences resulting from temporal and spatial variability in sampling lead to different conclusions regarding water quality in the river (including regulatory listing decisions), especially when low flow leads to concentrations at or near the water quality criteria (500mg/L TDS). Drinking water samples exceeded the criteria 82 out of 650 samples (12.6%), while river water samples exceeded the criteria 47 out of 464 samples (10.1%). Different water sample types could provide different pictures of water quality in the river and lead to different regulatory listing decisions.

Impacts of human activities and sampling strategies on soil heavy metal distribution in a rapidly developing region of China

The impacts of industrial and agricultural activities on soil Cd, Hg, Pb, and Cu in Zhangjiagang City, a rapidly developing region in China, were evaluated using two sampling strategies. The soil Cu, Cd, and Pb concentrations near industrial locations were greater than those measured away from industrial locations. The converse was true for Hg. The top enrichment factor (TEF) values, calculated as the ratio of metal concentrations between the topsoil and subsoil, were greater near industrial location than away from industrial locations and were further related to the industry type. Thus, the TEF is an effective index to distinguish sources of toxic elements not only between anthropogenic and geogenic but also among different industry types. Target soil sampling near industrial locations resulted in a greater estimation in high levels of soil heavy metals. This study revealed that the soil heavy metal contamination was primarily limited to local areas near industrial locations, despite rapid development over the last 20 years. The prevention and remediation of the soil heavy metal pollution should focus on these high-risk areas in the future.

Does more sequence data improve estimates of galliform phylogeny? Analyses of a rapid radiation using a complete data matrix

The resolution of rapid evolutionary radiations or "bushes" in the tree of life has been one of the most difficult and interesting problems in phylogenetics. The avian order Galliformes appears to have undergone several rapid radiations that have limited the resolution of prior studies and obscured the position of taxa important both agriculturally and as model systems (chicken, turkey, Japanese quail). Here we present analyses of a multi-locus data matrix comprising over 15,000 sites, primarily from nuclear introns but also including three mitochondrial regions, from 46 galliform taxa with all gene regions sampled for all taxa. The increased sampling of unlinked nuclear genes provided strong bootstrap support for all but a small number of relationships. Coalescent-based methods to combine individual gene trees and analyses of datasets that are independent of published data indicated that this well-supported topology is likely to reflect the galliform species tree. The inclusion or exclusion of mitochondrial data had a limited impact upon analyses upon analyses using either concatenated data or multispecies coalescent methods. Some of the key phylogenetic findings include support for a second major clade within the core phasianids that includes the chicken and Japanese quail and clarification of the phylogenetic relationships of turkey. Jackknifed datasets suggested that there is an advantage to sampling many independent regions across the genome rather than obtaining long sequences for a small number of loci, possibly reflecting the differences among gene trees that differ due to incomplete lineage sorting. Despite the novel insights we obtained using this increased sampling of gene regions, some nodes remain unresolved, likely due to periods of rapid diversification. Resolving these remaining groups will likely require sequencing a very large number of gene regions, but our analyses now appear to support a robust backbone for this order.