High Level Of Variation Research Articles

Metagenomic Detection and Genome Assembly of Novel PRRSV-2 Strain Using Oxford Nanopore Flongle Flow Cell.

Porcine reproductive and respiratory syndrome virus (PRRSV) is the causative agent of a syndrome characterized by reproductive failure and respiratory complications (PRRS). Early detection and classification of PRRSV strains are vital for appropriate management strategies to minimize loss following outbreaks. The most widely used classification method for PRRSV is based on open reading frame 5 (ORF5) sequences. However, the effectiveness of the ORF5-based classification system in accurately representing genetic variation is under scrutiny because ORF5 constitutes less than 5% of the 15kb-long genome. In this study, a single Oxford Nanopore Flongle flow cell was used to identify and assemble the genome of a strain sampled in May of 2022 from a Midwest research farm. Based on comparisons with available PRRSV genomes, the assembled genome was determined to be a novel PRRSV-2 strain belonging to the 1-4-4 L1C.5 ORF5-based lineage. Phylogenetic analyses of ORF5 and whole-genome sequences demonstrated differences in clustering between PRRSV strains, supporting the inability of ORF5 to capture genome-wide variation. For example, high levels of variation were observed within ORF1a, which encodes the hypervariable nsp2 protein. Comparison of the newly assembled genome with the genome of a highly characterized strain (VR2332 PRRSV-2) identified a 100 amino acid deletion within nsp2 characteristic of NADC34-like PRRSV. Oxford Nanopore Technologies' Flongle flow cell has been proven in this study to provide a rapid, cost-effective and accessible approach for whole-genome sequencing of PRRSV strains present within clinical samples necessary for strain-specific genome-wide characterization.

A Model for Selecting Kiwifruit (Actinidia eriantha) Germplasm Resources with Excellent Fruit Quality.

The evaluation of quality traits is an important procedure for kiwifruit breeding and comprehensive utilization. The present study aimed to establish a comprehensive system to assess Actinidia eriantha germplasms by analyzing 22 quality traits on kiwifruit samples collected from a wild population of 236 plants grown in the Jiangxi Province, China. Variability, correlation, principal components, and cluster analyses were carried out using the data collected from fruit quality evaluations. The coefficients of variation (CV) of fruit quality traits ranged from 11.66 to 66.16% (average coefficient = 35.09%), indicating a high level of variation among the 236 plants. In addition, different degrees of correlations were found between the traits, with similar traits demonstrating strong correlations. Principal component analysis (PCA) generated eight comprehensive and independent principal components, accounting for 77.93% of the original fruit quality information. Furthermore, an extensive evaluation from PCA ranked the plants based on cluster analysis and grouped them into seven categories. A stepwise regression analysis generated a prediction model, demonstrating a good fit (0.945) with the principal components of the comprehensive evaluation score. Overall, this study identifies nine quality traits, representing fruit appearance, sweetness, acidity, flavor, and nutritional attributes, as important traits for a comprehensive evaluation of A. eriantha fruits.

Identification of veterinary and medically important blood parasites using contrastive loss-based self-supervised learning.

Zoonotic diseases caused by various blood parasites are important public health concerns that impact animals and humans worldwide. The traditional method of microscopic examination for parasite diagnosis is labor-intensive, time-consuming, and prone to variability among observers, necessitating highly skilled and experienced personnel. Therefore, an innovative approach is required to enhance the conventional method. This study aimed to develop a self-supervised learning (SSL) approach to identify zoonotic blood parasites from microscopic images, with an initial focus on parasite species classification. We acquired a public dataset featuring microscopic images of Giemsa-stained thin blood films of trypanosomes and other blood parasites, including Babesia, Leishmania, Plasmodium, Toxoplasma, and Trichomonad, as well as images of both white and red blood cells. The input data were subjected to SSL model training using the Bootstrap Your Own Latent (BYOL) algorithm with Residual Network 50 (ResNet50), ResNet101, and ResNet152 as the backbones. The performance of the proposed SSL model was then compared to that of baseline models. The proposed BYOL SSL model outperformed supervised learning models across all classes. Among the SSL models, ResNet50 consistently achieved high accuracy, reaching 0.992 in most classes, which aligns well with the patterns observed in the pre-trained uniform manifold approximation and projection representations. Fine-tuned SSL models exhibit high performance, achieving 95% accuracy and a 0.960 area under the curve of the receiver operating characteristics (ROC) curve even when fine-tuned with 1% of the data in the downstream process. Furthermore, 20% of the data for training with SSL models yielded ≥95% in all other statistical metrics, including accuracy, recall, precision, specification, F1 score, and ROC curve. As a result, multi-class classification prediction demonstrated that model performance exceeded 91% for the F1 score, except for the early stage of Trypanosoma evansi, which showed an F1 score of 87%. This may be due to the model being exposed to high levels of variation during the developmental stage. This approach can significantly enhance active surveillance efforts to improve disease control and prevent outbreaks, particularly in resource-limited settings. In addition, SSL addresses significant challenges, such as data variability and the requirement for extensive class labeling, which are common in biology and medical fields.

The Year-By-Year Primary and Secondary Education Histories of Homeschooled Individuals and the Implications for Empirical Homeschooling Research

ABSTRACT This study uses three nationally representative data sets of U.S. school-aged children who are currently homeschooled and two nationally representative data sets of U.S. adults who have ever been homeschooled to empirically document the amount of time homeschooled individuals are homeschooled, how much time they spend in public- or private-school settings, and the amount of exit out of or entry into homeschooling over the course of their primary and secondary education. Findings reveal high levels of variation in when and how long individuals are homeschooled. Implications for researching the homeschooling population are also discussed.

A Detailed Survey of the Parallel Mean Free Path of Solar Energetic Particle Protons and Electrons

In this work, more than a dozen solar energetic particle (SEP) events are identified where the source region is magnetically well connected to at least one spacecraft at 1 au. The observed intensity–time profiles, for all available proton and electron energy channels, are compared to results computed using a numerical one-dimensional SEP transport model in order to derive the parallel mean free paths (pMFPs) as a function of energy (or rigidity) at 1 au. These inversion results are then compared to theoretical estimates of the pMFP, using observed turbulence quantities with observationally motivated variations as input. For protons, a very good comparison between inversion and theoretical results is obtained. It is shown that the observed inter-event variations in the inversion pMFP values can be explained by natural variations in the background turbulence values. For electrons, there is relatively good agreement with pMFPs derived assuming the damping model of dynamical turbulence, although the theoretical values are extremely sensitive to the details of the turbulence dissipation range, which themselves display a high level of variation.

Environmental DNA concentrations vary greatly across productive and degradative conditions, with implications for the precision of population estimates

Population size is an important metric to inform the conservation and management of species. For aquatic species, environmental DNA (eDNA) concentration has been suggested for non-invasively estimating population size. However, many biotic and abiotic factors simultaneously influence the production and degradation of eDNA which can alter the relationship between population size and eDNA concentration. We investigated the influence of temperature, salinity, and ranavirus infection on eDNA concentrations using tadpole mesocosms. Using linear regression models, we tested the influence of each experimental treatment on eDNA concentrations at three time points before and during epidemics. Prior to infection, elevated temperatures lowered eDNA concentrations, indicating that degradation was the driving force influencing eDNA concentrations. During early epidemics, no treatments strongly influenced eDNA concentrations and in late epidemics, productive forces dominated as ranavirus intensity and dead organisms increased eDNA concentrations. Finally, population size was only an important predictor of eDNA concentration in late epidemics and we observed high levels of variation between samples of replicate mesocosms. We demonstrate the complexities of several interacting factors influencing productive and degradative forces, variation in influences on eDNA concentration over short time spans, and examine the limitations of estimating population sizes from eDNA with precision in semi-natural conditions.

Multilocus sequence typing of pathogenic treponemes isolated from contagious ovine digital dermatitis stage five lesions: Implications for disease transmission dynamics

Contagious ovine digital dermatitis (CODD) causes a severe, infectious foot disease and lameness of sheep, is common within the UK and is now also emerging in other countries. As well as causing severe animal welfare issues, huge economic losses emerge from the disease due to weight loss/lack of weight gain, and veterinary treatments. CODD lesion progress is measured, with a scoring system from 1 (early lesions) to 5 (healed). Here, using samples from an experimental flock infected by natural means, samples were taken from CODD stage 5 lesions, post treatment, and subjected to bacterial isolation and MLST using previously published methods. Sequences were compared to others from the same flock, and those from previous studies.All CODD 5 lesions produced viable Treponema spp. bacteria. High levels of variation of bacteria were seen, with 12 sequence types (STs) for T. medium phylogroup (11 new), 15 STs for T. phagedenis phylogroup (9 new) and six T. pedis STs, of which two were new. This study shows that CODD stage 5 lesions still contain viable bacteria, representing all three known pathogenic Treponema spp. phylogroups, and these may thus play a role in disease transmission and epidemiology despite appearing healed after treatment. The high level CODD treponeme variability within an infected flock where sheep were bought from different sources, as might occur in common agricultural practice, may suggest reasons as to why the bacterial disease is difficult to treat, control and eradicate, and adds further complexity to the polybacterial pathogenesis of these lesions.

Biometric variability of inflorescence and flower traits among ex situ accessions of the neotropical oilseed palm Acrocomia Mart.

The oilseed palm genus Acrocomia is suitable for sustainable oil production in South America. The high phenotypic diversity of wild populations poses a challenge for the delimitation of the genus. Comparing the inflorescence architecture, a first-order panicle, and staminate and pistillate flower traits could be a valuable tool in resolving the taxonomic disarray. Thus, this study aims to characterize the differences in the inflorescence architecture and floral structures of three common and economically significant Acrocomia species: A. aculeata, A. totai, and A. intumescens. Biometric traits of the inflorescence architecture and floral structures of various Acrocomia accessions in an ex situ germplasm collection in Brazil were assessed. The unweighted pair group method with arithmetic mean (UPGMA) cluster analysis based on the Gower distance was used to measure dissimilarities between the individual plants of the accessions. To our best knowledge, this study provides the first evidence of the presence of second-order rachillae in the genus Acrocomia. Evaluated traits showed a high level of variation within and between accessions, emphasizing the phenotypic diversity of the genus. The accessions of A. totai were distinguishable from those of the other two species by their inflorescence architecture and flower traits. The dissimilarities between A. aculeata and A. intumescens were not sufficient to differentiate both. In conclusion, the quantitative assessment of inflorescence and floral traits is a valuable tool for taxonomic resolution of the genus.

Molecular organisation and chromosomal localisation of 5S rDNA tandem arrays in evolutionary polyploid cyprinids from the genera Carassius and Barbus

Some evolutionary polyploid Carassius and Barbus species are poorly differentiated morphologically and hybridise to form viable intrageneric hybrids. 5S rDNA arrays and their chromosomal localisation were studied in C. carassius, C. gibelio, B. barbus, B. carpathicus and B. waleckii distributed throughout Poland, in order to contribute to the knowledge of their genetic and cytogenetic differences. Two 5S rDNA array classes in C. carassius (203 bp, 380 bp) and in three Barbus species (196 bp, 215 bp) were characterised by a highly-conserved coding region. The adjacent non-transcribed spacer (NTS) of C. Carassius exhibited a relatively high level of variation due to base substitutions and insertions/deletions, whereas the NTS of the Barbus species were highly conserved. Fluorescence in situ hybridisation with 5S rDNA array classes as probes indicated their syntenic chromosomal location and the utility of these sites as suitable marker of the analysed Carassius taxa ploidy. 5S rDNAs in two chromosomes of the Barbus species was discovered. The observed low variability of 5S rDNA arrays makes them an inappropriate tool for an investigation of the Barbus species, whereas the suitable for investigation within karyologically varied in the Carassius taxa.

Unprecedented genetic variability of PFam54 paralogs among Eurasian Lyme borreliosis-causing spirochetes.

Lyme borreliosis (LB) is the most common vector-borne disease in the Northern Hemisphere caused by spirochetes belonging to the Borrelia burgdorferi sensu lato (Bbsl) complex. Borrelia spirochetes circulate in obligatory transmission cycles between tick vectors and different vertebrate hosts. To successfully complete this complex transmission cycle, Bbsl encodes for an arsenal of proteins including the PFam54 protein family with known, or proposed, influences to reservoir host and/or vector adaptation. Even so, only fragmentary information is available regarding the naturally occurring level of variation in the PFam54 gene array especially in relation to Eurasian-distributed species. Utilizing whole genome data from isolates (n = 141) originated from three major LB-causing Borrelia species across Eurasia (B. afzelii, B. bavariensis, and B. garinii), we aimed to characterize the diversity of the PFam54 gene array in these isolates to facilitate understanding the evolution of PFam54 paralogs on an intra- and interspecies level. We found an extraordinarily high level of variation in the PFam54 gene array with 39 PFam54 paralogs belonging to 23 orthologous groups including five novel paralogs. Even so, the gene array appears to have remained fairly stable over the evolutionary history of the studied Borrelia species. Interestingly, genes outside Clade IV, which contains genes encoding for proteins associated with Borrelia pathogenesis, more frequently displayed signatures of diversifying selection between clades that differ in hypothesized vector or host species. This could suggest that non-Clade IV paralogs play a more important role in host and/or vector adaptation than previously expected, which would require future lab-based studies to validate.

Who prioritizes what? A cross‐jurisdictional comparative analysis of salmon fish passage strategies in Western Washington

AbstractConservation planners often rely on heuristic indices when challenged with prioritizing potential projects under a constrained budget. This paper presents a comparative analysis of several prioritization indices (PIs) of culvert fish passage barriers, which can contribute to declines in anadromous fish populations. A federal injunction requires Washington state to restore 90% of habitat blocked by state‐owned culverts by 2030, prompting the development of numerous PIs, by various entities (i.e., counties, cities) within the injunction area. Our comparative analysis of PIs within the injunction Case Area investigates their ability to distinguish between barriers, their transferability in terms of scoring metrics, how scoring weights differ, and the preferences implied thereby. We document the use of six distinct PI methods by 10 entities and find that some PIs used many shared metrics, whereas others used a high percentage of unique metrics that would be difficult to replicate outside the entity's jurisdiction. Although habitat potential, habitat quantity, and connectivity were considered across all PIs, we found a high level of variation in terms of the metric weights. Our methods can be employed in other geographies or for other restoration PI planning efforts, and our results may facilitate the development and refinement of future PIs.

Suicide Screening, Risk Assessment, and Lethal Means Counseling During Zero Suicide Implementation.

The authors measured implementation of Zero Suicide (ZS) clinical practices that support identification of suicide risk and risk mitigation, including screening, risk assessment, and lethal means counseling, across mental health specialty and primary care settings. Six health care systems in California, Colorado, Michigan, Oregon, and Washington participated. The sample included members ages ≥13 years from 2010 to 2019 (N=7,820,524 patients). The proportions of patients with suicidal ideation screening, suicide risk assessment, and lethal means counseling were estimated. In 2019, patients were screened for suicidal ideation in 27.1% (range 5.0%-85.0%) of mental health visits and 2.5% (range 0.1%-35.0%) of primary care visits among a racially and ethnically diverse sample (44.9% White, 27.2% Hispanic, 13.4% Asian, and 7.7% Black). More patients screened positive for suicidal ideation in the mental health setting (10.2%) than in the primary care setting (3.8%). Of the patients screening positive for suicidal ideation in the mental health setting, 76.8% received a risk assessment, and 82.4% of those identified as being at high risk received lethal means counseling, compared with 43.2% and 82.4%, respectively, in primary care. Six health systems that implemented ZS showed a high level of variation in the proportions of patients receiving suicide screening and risk assessment and lethal means counseling. Two opportunities emerged for further study to increase frequency of these practices: expanding screening beyond patients with regular health care visits and implementing risk assessment with lethal means counseling in the primary care setting directly after a positive suicidal ideation screening.

Mid-Pliocene not analogous to high-CO2 climate when considering Northern Hemisphere winter variability

Abstract. In this study, we address the question of whether the mid-Pliocene climate can act as an analogue for a future warm climate with elevated CO2 concentrations, specifically regarding Northern Hemisphere winter variability. We use a set of sensitivity simulations with the global coupled climate model CESM1.0.5 (CCSM4-Utr), which is part of the PlioMIP2 model ensemble, to separate the response to a CO2 doubling and to mid-Pliocene boundary conditions other than CO2. In the CO2 doubling simulation, the Aleutian low deepens, and the Pacific–North American pattern (PNA) strengthens. In response to the mid-Pliocene boundary conditions, sea-level pressure variance decreases over the North Pacific, the PNA becomes weaker and the North Pacific Oscillation (NPO) becomes the dominant mode of variability. The mid-Pliocene simulation shows a weak North Pacific jet stream that is less variable in intensity but has a high level of variation in jet latitude, consistent with a dominant NPO and indicating that North Pacific atmospheric dynamics become more North Atlantic-like. We demonstrate that the weakening of the Aleutian low, and subsequent relative dominance of the NPO over the PNA, is related to shifts in tropical Pacific convection. Variability in the North Atlantic shows little variation between all simulations. The opposite response in North Pacific winter variability to elevated CO2 or mid-Pliocene boundary conditions demonstrates that the mid-Pliocene climate cannot serve as a future analogue in this regard.

A Social Network Analysis of a Multi-sector Service System for Intimate Partner Violence in a Large US City

About one in four women in the US report having experienced some form of intimate partner violence (IPV) during their lifetime and an estimated 15.5 million children live in families in which IPV occurred in the past year. Families of young children with IPV experiences often face complex needs and require well-coordinated efforts among service providers across social and health sectors. One promising partnership aims to support pregnant and parenting IPV survivors through coordination between IPV agencies and community-based maternal and early childhood home visiting programs. This study used social network analysis (SNA) to understand the interconnectedness of the system of IPV prevention and intervention for families with young children in a large US city. The SNA included 43 agencies serving this population across various service domains spanning IPV, legal, maternal and child health, and public benefit programs. An SNA survey collected data on four forms of collaboration between agencies, including formal administrative relationship, referral reciprocity, case consultation, and shared activities in community committees/organizing bodies. Density and centrality were the primary outcomes of interest. A community detection analysis was performed as a secondary analysis. The overall level of interconnectedness between the 43 responding agencies was low. Making referrals to each other was the most common form of collaboration, with a network density of 30%. IPV agencies had the highest average number of connections in the networks. There was a high level of variation in external collaborations among home visiting agencies, with several home visiting agencies having very few connections in the community but one home visiting program endorsing collaborative relationships with upwards of 38 partner agencies in the network. In serving families at risk for IPV, home visiting agencies were most likely to have referral relationships with mental health provider agencies and substance use disorder service agencies. A community detection analysis identified distinct communities within the network and demonstrated that certain agency types were more connected to one another while others were typically siloed within the network. Notably, the IPV and home visiting communities infrequently overlapped. Sensitivity analyses showed that survey participants’ knowledge of their agencies’ external collaborations varied by their work roles and agencies overall had low levels of consensus about their connectedness to one another. We identified a heterogeneous service system available to families of young children at-risk for or experiencing IPV. Overall inter-agency connectedness was low, with many siloed agencies and a lack of shared knowledge of community resources. Understanding current collaborations, silos, and centrality of agencies is an effective public health tool for allocating scarce resources across diverse service sectors to efficiently improve the system serving families experiencing IPV.

Evaluating Decadal Changes in Determinants of Early Childhood Stunting and Assessing Their Contribution to Socio-economic Disparity in Child Nutritional Status Across India

Various efforts have been made over the years to bring about reduction in child malnutrition; the latest among them involves Goal 2 of the SDGs. The SDG Target 2.2 recognizes the global dimension of the nutrition issue and aims to end all forms of malnutrition by 2030, including achieving, by 2025, (WHO, 2015). The present evidence on childhood malnutrition suggests that while improvement in maternal and child covariates have resulted in decline of childhood stunting over time. The present study aims to investigate how the effect of maternal and child covariates on early childhood malnutrition have changed over the last decade and examining the socio-economic disparity in the nutritional status of children across India. The present study utilizes data from the last two rounds of the National Family Health Survey, NFHS-3 in 2005-06 and NFHS-4 in 2015-16 of children in the age group 6-23 months for whom data on height-for-age was available from the last two rounds of the National Family Health Survey (NFHS-3 and NFHS-4). After dropping the missing and flagged cases, the total sample size was 12,507 and 68,246 children from NFHS-3 (2005-06) and NFHS-4 (2015-16), respectively. The selected indicator of childhood under nutrition for this study is stunting. The exposure variables selected for the study were child factors such as sex, age, birth order, size at birth, place of delivery, diet diversity, meal frequency and early initiation of breastfeeding. Maternal factors such as maternal education, media exposure, and mother’s BMI were taken into account. For healthcare service utilization we considered the variable of complete antenatal care. Other background characteristics like religion, caste, wealth index, place of residence and geographical region were also considered. We utilized chi-square test to test for the association of various factors with early childhood stunting followed by t-test to assess the changes in prevalence by each factor. We also carried out bivariate and multivariate logistic analysis to effect of various factors on childhood stunting. Lastly, we carried out Oaxaca decomposition to examine the contribution of the determinants of childhood stunting towards the changes in its prevalence over the last ten years. Concentration Index was calculated to examine the disparity in early childhood stunting across India for both rounds of the National Family Health Survey. The predictive probabilities were calculated for each category of the wealth index after fitting a logistic model to control for other determinants of early childhood stunting to assess the change in prevalence of stunting across each socio-economic group in the last ten years. The study reveals an overall decline in prevalence of early childhood stunting across India over the last ten years from 2005-16. However, high levels of variation continue to exist across all the states in India. The study reveals institutional delivery as the highest contributing factor for this decline. Maternal education, body mass index and complete antenatal care during pregnancy also contribute significantly to the improvement in childhood stunting

MARTin-an open-source platform for microarray analysis.

Background: Microarray technology has brought significant advancements to high-throughput analysis, particularly in the comprehensive study of biomolecular interactions involving proteins, peptides, and antibodies, as well as in the fields of gene expression and genotyping. With the ever-increasing volume and intricacy of microarray data, an accurate, reliable and reproducible analysis is essential. Furthermore, there is a high level of variation in the format of microarrays. This not only holds true between different sample types but is also due to differences in the hardware used during the production of the arrays, as well as the personal preferences of the individual users. Therefore, there is a need for transparent, broadly applicable and user-friendly image quantification techniques to extract meaningful information from these complex datasets, while also addressing the challenges posed by specific microarray and imager formats, which can flaw analysis and interpretation. Results: Here we introduce MicroArray Rastering Tool (MARTin), as a versatile tool developed primarily for the analysis of protein and peptide microarrays. Our software provides state-of-the-art methodologies, offering researchers a comprehensive tool for microarray image quantification. MARTin is independent of the microarray platform used and supports various configurations including high-density formats and printed arrays with significant x and y offsets. This is made possible by granting the user the ability to freely customize parts of the application to their specific microarray format. Thanks to built-in features like adaptive filtering and autofit, measurements can be done very efficiently and are highly reproducible. Furthermore, our tool integrates metadata management and integrity check features, providing a straightforward quality control method, along with a ready-to-use interface for in-depth data analysis. This not only promotes good scientific practice in the field of microarray analysis but also enhances the ability to explore and examine the generated data. Conclusion: MARTin has been developed to empower its users with a reliable, efficient, and intuitive tool for peptidomic and proteomic array analysis, thereby facilitating data-driven discovery across disciplines. Our software is an open-source project freely available via the GNU Affero General Public License licence on GitHub.

Host Genetic Variation Impacts SARS-CoV-2 Vaccination Response in the Diversity Outbred Mouse Population.

The COVID-19 pandemic led to the rapid and worldwide development of highly effective vaccines against SARS-CoV-2. However, there is significant individual-to-individual variation in vaccine efficacy due to factors including viral variants, host age, immune status, environmental and host genetic factors. Understanding those determinants driving this variation may inform the development of more broadly protective vaccine strategies. While host genetic factors are known to impact vaccine efficacy for respiratory pathogens such as influenza and tuberculosis, the impact of host genetic variation on vaccine efficacy against COVID-19 is not well understood. To model the impact of host genetic variation on SARS-CoV-2 vaccine efficacy, while controlling for the impact of non-genetic factors, we used the Diversity Outbred (DO) mouse model. We found that DO mice immunized against SARS-CoV-2 exhibited high levels of variation in vaccine-induced neutralizing antibody responses. While the majority of the vaccinated mice were protected from virus-induced disease, similar to human populations, we observed vaccine breakthrough in a subset of mice. Importantly, we found that this variation in neutralizing antibody, virus-induced disease, and viral titer is heritable, indicating that the DO serves as a useful model system for studying the contribution of genetic variation of both vaccines and disease outcomes.

Rapid Targeted Assembly of the Proteome Reveals Evolutionary Variation of GC Content in Avian Lice.

Nucleotide base composition plays an influential role in the molecular mechanisms involved in gene function, phenotype, and amino acid composition. GC content (proportion of guanine and cytosine in DNA sequences) shows a high level of variation within and among species. Many studies measure GC content in a small number of genes, which may not be representative of genome-wide GC variation. One challenge when assembling extensive genomic data sets for these studies is the significant amount of resources (monetary and computational) associated with data processing, and many bioinformatic tools have not been optimized for resource efficiency. Using a high-performance computing (HPC) cluster, we manipulated resources provided to the targeted gene assembly program, automated target restricted assembly method (aTRAM), to determine an optimum way to run the program to maximize resource use. Using our optimum assembly approach, we assembled and measured GC content of all of the protein-coding genes of a diverse group of parasitic feather lice. Of the 499 426 genes assembled across 57 species, feather lice were GC-poor (mean GC = 42.96%) with a significant amount of variation within and between species (GC range = 19.57%-73.33%). We found a significant correlation between GC content and standard deviation per taxon for overall GC and GC3, which could indicate selection for G and C nucleotides in some species. Phylogenetic signal of GC content was detected in both GC and GC3. This research provides a large-scale investigation of GC content in parasitic lice laying the foundation for understanding the basis of variation in base composition across species.

Evaluating Growth Patterns and Soil Dynamics of the Endangered African Rosewood (Pterocarpus erinaceus Poir.) in Contrasting Ecological Regions in Ghana

Pterocarpus erinaceus (Poir.) is an endemic and endangered species of the Guinea‐Sudano‐Sahelian​ zones currently overexploited for timber, fodder, and medicinal purposes. Therefore, plantations are critical to meeting the high demand in the international market while reducing pressure on natural stands, but its growth performance across different ecological zones is not well documented. Thus, we assessed the influence of ecological zones and soil properties on the survival and growth performance of P. erinaceus. Data were collected from 12 subplots of P. erinaceus stands in the Dry Semi‐Deciduous Fire Zone (DSFZ) and 16 subplots in the Moist Semi‐Deciduous North West Zone (MSNW). We assessed the survival and growth performance of P. erinaceus using one‐way ANOVA, variation in soil properties using the Generalized Linear Model, and the influence of soil properties on P. erinaceus growth characteristics via correlation analysis. We found that the percentage survival of P. erinaceus was similar in both ecological zones. However, P. erinaceus demonstrated a high level of variation in growth attributes, growing taller with deeper canopies in wetter conditions and larger crown spread in drier conditions. The aboveground biomass carbon stocks of P. erinaceus stands were similar in both ecological zones, highlighting the potential role of the species as a carbon sink in the ecological zones. Soil organic matter, nitrogen, and calcium contents were higher in soils of the MSNW stands than those of the DSFZ stands. However, potassium, magnesium, sodium, and phosphorus contents were stable across the ecological zones. We concluded that wetter conditions enhance the growth performance of P. erinaceus as a timber species.

Environmental heterogeneity modifies the link between personality and survival in fluctuating small mammal populations.

Despite numerous studies examining the fitness consequences of animal personalities, predictions concerning the relationship between personality and survival are not consistent with empirical observations. Theory predicts that individuals who are risky (i.e. bold, active and aggressive) should have higher rates of mortality; however, empirical evidence shows high levels of variation in behaviour-survival relationships in wild populations. We suggest that this mismatch between predictions under theory and empirical observations results from environmental contingencies that drive heterogeneity in selection. This uncertainty may constrain any universal directional relationships between personality traits and survival. Specifically, we hypothesize that spatiotemporal fluctuations in perceived risk that arise from variability in refuge abundance and competitor density alter the relationship between personality traits and survival. In a large-scale manipulative experiment, we trapped four small mammal species in five subsequent years across six forest stands treated with different management practices in Maine, United States. Stands all occur within the same experimental forest but contain varying amounts of refuge and small mammal densities fluctuate over time and space. We quantified the effects of habitat structure and competitor density on the relationship between personality traits and survival to assess whether directional relationships differed depending on environmental contingencies. In the two most abundant species, deer mice and southern red-backed voles, risky behaviours (i.e. higher aggression and boldness) predicted apparent monthly survival probability. Mice that were more aggressive (less docile) had higher survival. Voles that were bolder (less timid) had higher survival, but in the risky forest stands only. Additionally, traits associated with stress coping and de-arousal increased survival probability in both species at high small mammal density but decreased survival at low density. In the two less abundant study species, there was no evidence for an effect of personality traits on survival. Our field experiment provides partial support for our hypothesis: that spatiotemporal fluctuations in refuge abundance and competitor density alter the relationship between personality traits and survival. Our findings also suggest that behaviours associated with stress coping and de-arousal may be subject to density-dependent selection and should be further assessed and incorporated into theory.