Statistical Support Research Articles

From host individual traits to community structure and composition: Bartonella infection insights

BackgroundPhylogeny, combined with trait-based measures, offers insights into parasite sharing among hosts. However, the specific traits that mediate transmission and the aspects of host community diversity that most effectively explain parasite infection rates remain unclear, even for the Bartonella genus, a vector-borne bacteria that causes persistent blood infections in vertebrates.MethodsThis study investigated the association between rodent host traits and Bartonella infection, as well as how rodent community diversity affects the odds of infection in the Atlantic Forest, using generalized linear models. Additionally, we assessed how host traits and phylogenetic similarities influence Bartonella infection among mammal species in Brazil. To this end, rodents were sampled from ten municipalities in Rio de Janeiro, southeastern Brazil. Then, we calculated several diversity indices for each community, including Rényi’s diversity profiles, Fisher’s alpha, Rao’s quadratic entropy (RaoQ), Functional Diversity (FDis), Functional Richness (FRic), and Functional Evenness (FEve). Finally, we compiled a network encompassing all known interactions between mammal species and Bartonella lineages recorded in Brazil.ResultsWe found no significant relationship between diversity indices and the odds of Bartonella infection in rodent communities. Furthermore, there was no statistical support for the influence of individual-level traits (e.g., body length, sex, and age) or species-level ecological traits (e.g., locomotor habitat, dietary guild, and activity period) on Bartonella infection in rodents. A country-scale analysis, considering all mammal species, revealed no effect of host traits or phylogeny on Bartonella infection.ConclusionsThis study highlighted wild mammals that share Bartonella lineages with livestock, synanthropic, and domestic animals, underscoring the complexity of their maintenance cycle within the One Health framework. A key question arising from our findings is whether molecular host–cell interactions outweigh host body mass and ecological traits in influencing Bartonella infection, potentially opening new avenues for understanding host–parasite relationships and infection ecology.Graphical

Description of the new species Mallomonas okhapkinii (Synurales, Chrysophyceae) based on morphological and molecular data

This paper describes a new species of Mallomonas discovered in a swamp area in Russia. The species was identified based on scale morphology, examined using scanning and transmission electron microscopy, and subjected to molecular analysis. The new species, Mallomonas okhapkinii sp. nov., belongs to the section Planae and is most similar in scale and bristle ultrastructure to M. matvienkoae sensu stricto. Phylogenetic analysis, performed using a concatenated dataset of nuclear-encoded small subunit rRNA and plastid-encoded rbcL genes, revealed that the strains of the new species form a distinct clade with high statistical support, closely related to the clade of M. paragrandis and M. sorohexareticulata. This species was found in only one habitat.

The meaning and measure of concordance factors in phylogenomics.

As phylogenomic datasets have grown in size, researchers have developed new ways to measure biological variation and to assess statistical support for specific branches. Larger datasets have more sites and loci, and therefore less sampling variance. While we can more accurately measure the mean signal in these datasets, lower sampling variance is often reflected in uniformly high measures of branch support-such as the bootstrap and posterior probability-limiting their utility. Larger datasets have also revealed substantial biological variation in the topologies found across individual loci, such that the single species tree inferred by most phylogenetic methods represents a limited summary of the data for many purposes. In contrast to measures of statistical support, the degree of underlying topological variation among loci should be approximately constant regardless of the size of the dataset. "Concordance factors" and similar statistics have therefore become increasingly important tools in phylogenetics. In this review, we explain why concordance factors should be thought of as descriptors of topological variation rather than as measures of statistical support, and argue that they provide important information about the predictive power of the species tree not contained in measures of support. We review a growing suite of statistics for measuring concordance, compare them in a common framework that reveals their interrelationships, and demonstrate how to calculate them using an example from birds. We also discuss how measures of topological variation might change in the future as we move beyond estimating a single "tree of life" towards estimating the myriad evolutionary histories underlying genomic variation.

Hematocrits of red blood cell units increase during storage due to changes in mean corpuscular volume, impacting outcomes of red cell exchange procedures

Abstract Introduction Hematocrits of red blood cell (RBC) units are generally not measured by blood centers or transfusion services. Red blood cell exchange (RCE) is commonly used to treat sickle cell disease, and a key parameter needed in RCE is the average hematocrit of RBC units. However, there is no consensus on the average hematocrit to use or how it is affected by storage. The goal of our study is to determine the average hematocrit of RBC units by measuring hematologic parameters RBC units during storage and performing statistical modeling of hematocrit changes over time. Methods We sampled aliquots of leukoreduced RBC units in AS-1 (n=10) using the Terumo TSCD-II Sterile Tubing Welder to sterilely collect ~15mL of RBCs in transfer-pack containers. Aliquots were collected weekly from Day 7 to Day 42 of storage. Complete blood counts were performed using the Sysmex XN-3100 Hematology Analyzer. We statistically modeled changes in RBC units during storage by utilizing Bayesian multilevel linear regression models, allowing for capturing effects at the individual RBC-unit level. Posterior distributions of model parameters were estimated and processed using Stan and the rethinking and rstan packages in R. Posterior distributions are summarized with posterior means and 95%-credible intervals in parentheses. Model selection was done by calculating Akaike weights using the widely applicable information criterion (WAIC) to signify statistical support for each model. Results Multilevel linear regression models of hematologic parameters as a function of storage time were developed. Hematocrits increased with a posterior mean of 1.4% (0.98–1.75%) per week of storage, with posterior mean hematocrits of: 61.9% (60.2–63.6%) on Day 7, 63.9% (61.5–66.4%) on Day 21, and 66.0% (62.8–69.7%) on Day 42. These results indicate that a single average cannot be used for RBC units since hematocrits dramatically increase during storage. Mean corpuscular volume (MCV) increased with a posterior mean of 2.31 fL (1.4–3.71) per week whereas hemoglobin remained stable with a posterior mean increase of 0.008 g/dL (-0.016–0.031) per week. Using these results, we subsequently developed a multilevel regression model of hematocrit as a function of MCV. The model using MCV (WAIC=100.2, weight=100%) was favored over the model using time (WAIC=120.0, weight=0%), suggesting that changes in MCV are driving the increasing hematocrits. Conclusion Our study is the first to leverage Bayesian statistics to carefully quantify the average hematocrits of RBC units during storage time and to demonstrate that increasing hematocrits are caused by changes in MCV. These results indicate that transfusion protocols must consider the age of RBC units for RCE calculations, and provisions (e.g., requiring use of fresh units for RCE) may help minimize the variability in post-exchange testing. Moreover, our findings suggest that transfusion services should regularly measure hematocrits of RBC units in their inventory.

Statistical Support for Federal and Regional Decisions on the Well-Being Standard

Modern Russia is going through difficult trials and as a state, as a civil society, it is in search of new ideas, meanings and goals for further development. Therefore, a more mature approach to the implementation of social policy is needed both at the federal, regional and local levels. This approach can become a standard of well-being. The general idea of the welfare standard implies equal access of citizens to public goods in any locality of the country. At the moment, programs are being implemented in a number of regions of Russia that can be called components of the well-being standard, but no universal concept has been created that would describe this standard. The authors of the study offer their vision of the standard of well-being and show that the process of its creation requires the efforts of the scientific community and active discussion. The result of the implementation of the well-being standard may be a gradual solution to the accumulated problems that concern Russian citizens. The study presents the successful experience of the regions, as well as analyzes the most common difficulties that hinder the successful implementation of state social projects and the development of individual regions. In the course of the study, it was proposed to supplement the federal standard with regional standards of well-being due to the specifics of a particular region.

Causal effect estimation in survival analysis with high dimensional confounders.

With the ever advancing of modern technologies, it has become increasingly common that the number of collected confounders exceeds the number of subjects in a data set. However, matching based methods for estimating causal treatment effect in their original forms are not capable of handling high-dimensional confounders, and their various modified versions lack statistical support and valid inference tools. In this article, we propose a new approach for estimating causal treatment effect, defined as the difference of the restricted mean survival time (RMST) under different treatments in high-dimensional setting for survival data. We combine the factor model and the sufficient dimension reduction techniques to construct propensity score and prognostic score. Based on these scores, we develop a kernel based doubly robust estimator of the RMST difference. We demonstrate its link to matching and establish the consistency and asymptotic normality of the estimator. We illustrate our method by analyzing a dataset from a study aimed at comparing the effects of two alternative treatments on the RMST of patients with diffuse large B cell lymphoma.

Epidemiology and genetic diversity of bocavirus in wild rodents in urban areas of Guangzhou, Southern China

Members of the genus Bocaparvovirus have a significant impact on human health and can infect a wide range of hosts, increasing the likelihood of crossing species barriers. Among the various mammalian hosts, rodents are widely recognized as important reservoirs for emerging and zoonotic viruses. However, despite recent reports of bocavirus infections in rodents, our current understanding of rat bocavirus (RBoV) genetic diversity and evolution is limited. In this study, rodent samples were collected from the urban areas of Guangzhou city, Southern China, to investigate the presence and genetic diversity of RBoV. Through PCR-based screening of 296 rodent spleens, 54 samples were determined to be positive for RBoV infection, and 12 nearly complete genome sequences of RBoV were recovered. Phylogenetic analysis revealed distinct lineages and sub-lineages of RBoV, and six recombination events with strong statistical support were identified, with five of these events involving sequences obtained from this study. These results highlight the genetic diversity of RBoV circulating in rodents in Guangzhou city and emphasize the importance of extensive surveillance to gain a better understanding of RBoV epidemiology, evolutionary characteristics, and potential for cross-species transmission.

Patients carrying pathogenic SCN8A variants with loss‐ and gain‐of‐function effects can be classified into five subgroups exhibiting varying developmental and epileptic components of encephalopathy

AbstractObjectivePhenotypic heterogeneity presents challenges in providing clinical care to patients with pathogenic SCN8A variants, which underly a wide disease spectrum ranging from neurodevelopmental delays without seizures to a continuum of mild to severe developmental and epileptic encephalopathies (DEEs). An important unanswered question is whether there are clinically important subgroups within this wide spectrum. Using both supervised and unsupervised machine learning (ML) approaches, we previously found statistical support for two and three subgroups associated with loss‐ and gain‐ of‐ function vari‐ants, respectively. Here, we test the hypothesis that the unsupervised subgroups (U1–U3) are distinguished by differential contributions of developmental and epileptic components.MethodsWe predicted that patients in the U1 and U2 subgroups would differ in timing of developmental delay and seizure onset, with earlier and concurrent onset of both features for the U3 subgroup. Standard statistical procedures were used to test these predictions, as well as to investigate clinically relevant associations among all five subgroups.ResultsTwo‐population proportion and Kruskal–Wallis tests supported the hypothesis of a reversed order of developmental delay and seizure onset for patients in U1 and U2, and nearly synchronous developmental delay/seizure onset for the U3 (termed DEE) subgroup. Association testing identified subgroup variation in treatment response, frequency of initial seizure type, and comorbidities, as well as different median ages of developmental delay onset for all five subgroups.SignificanceUnsupervised ML approaches discern differential developmental and epileptic components among patients with SCN8A‐related epilepsy. Patients in U1 (termed developmental encephalopathy) typically gain seizure control yet rarely experience improvements in development, whereas those in U2 (termed epileptic encephalopathy) have fewer if any developmental impairments despite difficulty in achieving seizure control. This understanding improves prognosis and clinical management and provides a framework to discover mechanisms underlying variability in clinical outcome of patients with SCN8A‐related disorders.

The Enhancement of Statistical Literacy: A Cross-Institutional Study Using Data Analysis and Text Mining to Identify Statistical Issues in the Transition to University Education

Statistics modules are included in most university degrees, independent of the degree area, and this means that many students face these modules underprepared and struggle because of a lack of statistics knowledge. The Maths Support Centre (MSC) in the University College Dublin (UCD) provides support for various mathematics-related subjects, with statistics students being the second-largest cohort of visitors. The overall goal of this paper is to identify the common statistical issues students face during the transition from secondary education to tertiary education. The main data set for this study is the data from UCD students who have accessed the UCD MSC since 2015/16 for statistics support; the categorization of statistical concepts has been made with the statistics module description for each statistics subject at the Universidad Rey Juan Carlos (URJC). First, we conducted a categorization of statistical concepts taught in university (based on URJC’s catergorization); after that, UCD MSC tutor comments were categorized and validated, and subsequently descriptive analyses and text mining were used on the UCD MSC comments to achieve a deeper understanding of the statistical issues. The statistical issues presented were categorized as descriptive statistics (22.8%), probability (44%), statistical inference (29.2%), and statistical software (4%). Students struggled with material that was introduced at university level rather than material seen at secondary level. Our findings on students’ main statistical issues contribute to the development of a suite of evidence-based educational applications and games to support undergraduate students internationally in first- and second-year statistical modules.

B - 7 Factor Structure of the Beck Depression Inventory-II in Epilepsy

Abstract Objective This study aimed to explore the factor structure of the Beck Depression Inventory, Second Edition (BDI-II) in persons with epilepsy (PWE) and assess its correspondence with validated BDI-II cognitive and somatic-affective factors associated with depression in other populations. Method Retrospective data from 69 PWE (ages 18–72) who completed the BDI-II at a National Association of Epilepsy Centers level 4 epilepsy center were analyzed. Patients with diagnoses of bipolar disorder and schizophrenia spectrum disorders were excluded. An Exploratory Factor Analysis (EFA) using the psych package in R Studio was conducted, allowing factors to correlate with oblique factor rotation. The number of factors was determined using eigenvalues >1 and scree plots. Results Statistical support is strongest for a one-factor solution with eigenvalue 7.91; however, a two-factor solution (Factor two eigenvalue = 1.16) also met criteria. These factors accounted for 30% and 10% of the variance, respectively. Due to the low eigenvalue, few item loadings (3), and low variance explained by the second factor, item-level considerations were implemented to determine whether a two-factor solution added clinically relevant information. Conclusion Although a one-factor solution was best supported by the data, a second factor including sadness, feeling of punishment, and suicidal thoughts may be clinically relevant given elevated suicide risk and qualitative research reporting punishment feelings among PWE.

Quantifying microbial DNA in metagenomes improves microbial trait estimation

Abstract Shotgun metagenomics is a powerful tool for studying the genomic traits of microbial community members, such as genome size, gene content, etc. While such traits can be used to better understand the ecology and evolution of microbial communities, the accuracy of their estimations can be critically influenced by both known and unknown factors. One factor that can bias trait estimations is the proportion of eukaryotic and viral DNA in a metagenome, as some bioinformatic tools assume that all DNA reads in a metagenome are bacterial or archaeal. Here, we add to a recent debate about the influence of eukaryotic DNA in the estimation of average genome size from a global soil sample dataset using a new bioinformatic tool. Contrary to what was assumed, our reanalysis of this dataset revealed that soil samples can contain a substantial proportion of non-microbial DNA, which severely inflated the original estimates of average genome size. Correcting for this bias significantly improves the statistical support for the negative relationship between average bacterial genome size and soil pH. These results highlight that metagenomes can contain large quantities of non-microbial DNA, and that new methods that correct for this can improve microbial trait estimation.

COI DNA barcoding to differentiate Haemagogus janthinomys and Haemagogus capricornii (Diptera: Culicidae) mosquitoes

The genus Haemagogus (Diptera: Culicidae) includes species that are important vectors of pathogens such as the yellow fever virus. The accurate identification of these species is essential for the control of zoonoses. Females of Hg. capricornii and Hg. janthinomys are morphologically indistinguishable, which makes the use of alternative identification techniques desirable. This study aimed to obtain sequences of the mitochondrial cytochrome c oxidase I (COI) gene, in the region widely used for DNA barcoding, of Haemagogus specimens from the state of São Paulo, Brazil, to evaluate the effectiveness of these sequences in the molecular identification of the species. A total of 37 female and 2 male mosquitoes were collected in various locations in the state of São Paulo, using methods such as hand-nets, Shannon traps, CDC light traps with CO2 bait and Nasci aspirators. The sequences of a 710 bp fragment of the COI gene were amplified by PCR and sequenced. A phylogenetic tree reconstruction was conducted using the Bayesian approach implemented in MrBayes v3.2.2, providing support values for taxa where genetic clusters may indicate the presence of new or cryptic species. We obtained 39 COI sequences representing three species: Haemagogus capricornii, Haemagogus leucocelaenus, and Haemagogus janthinomys. Bayesian analysis of the sequences produced clades that corroborate the morphological identification of the species. The separation of Hg. capricornii and Hg. janthinomys received 100 % statistical support and the Hg. capricornii was very well supported (91 %). The two sequences from male specimens, morphologically identified as Hg. capricornii, were grouped in the same clade, a sister clade of Hg. janthinomys. It is important to highlight that the Hg. janthinomys were positioned in several subclades, showing a polymorphism of this species within the state, a situation not observed for Hg. capricornii. For the first time, sequences of the mtCOI gene from Hg. capricornii were obtained and related to morphologically identified specimens. COI sequences proved effective in the molecular identification of Haemagogus species. This study contributes to the expansion of the GenBank database, providing the first sequences of Hg. capricornii and new sequences for Hg. janthinomys and Hg. leucocelaenus.

Insights into the Metabolite Profiles of Two Camellia (Theaceae) Species in Yunnan Province through Metabolomic and Transcriptomic Analysis.

Tea (Camellia sinensis) falls into the family Theaceae, is a valuable commercial crop, and tea products made from its buds and young leaves are favored by consumers all over the world. The more common Thea plant is Camellia sinensis (C. sinensis), but its most important relative, Camellia taliensis (C. taliensis), is also utilized by locals in the area of cultivation to manufacture tea. In this investigation, C. taliensis (DL) and C. sinensis (QJZ) were characterized in terms of their agronomic traits, physicochemical indices, metabolomics, and transcriptomics. The leaf area of DL is larger than that of QJZ; the color of DL's buds and leaves is yellowish-green, while that of QJZ's is green. DL's buds and leaves are more densely velvety than those of QJZ. The HPLC results indicated that the physicochemical contents varied considerably between the two samples, with DL having greater concentrations of EGCG and GABA than QJZ, while QJZ had remarkably higher concentrations of C, CA, and EGC than DL. A total of 2269 metabolites and 362,190,414 genes were positively identified, with the number of DAMs and DEGs being 1001 and 34,026, respectively. The flavonoids, phenolic acids, and alkaloid metabolites were dramatically different between the two tea group plants. Bioinformatics profiling revealed that the DAMs and DEGs of the two tea group plants interacted with each other and were involved in metabolic pathways, including "biosynthesis of secondary metabolites", "biosynthesis of amino acids", "biosynthesis of cofactors", "phenylpropanoid biosynthesis", and "flavonoid biosynthesis". Overall, these results provide statistical support for germplasm conservation and production for both C. taliensis and C. sinensis.

The Impact of Augmented Reality Tourism on Tourist Experience and Behavior —A Case Study of the Mogao Caves Cultural Heritage

Background and Aim: The Mogao Caves, representing the pinnacle of Chinese cave art evolution, enjoy esteemed historical significance. With backing from the local government's "Belt and Road" initiative and the establishment of the "Dunhuang Cultural Tourism Economic Circle," Mogao Caves tourism is undergoing high-quality development. However, the surge in tourist numbers has compromised the visitor experience, posing challenges to heritage conservation and tourism development balance. To address this, the Dunhuang Academy has integrated AR technology, safeguarded the heritage while enriched visitor experiences. This study aims to understand tourists' experiences and intentions in virtual Mogao Caves exploration, investigating factors influencing AR tourism experiences. By examining AR's impact and proposing management enhancements, this research contributes to Mogao Caves' sustainable development. Materials and Methods: This study utilizes a quantitative approach with two main stages: literature analysis and statistical analysis. Initially, it defines concepts and establishes the conceptual framework of AR technology by reviewing SOR theory, tourist experiences, behavioral intentions, and relevant studies. It then refines the SOR theory's origin, concept, characteristics, and application areas, analyzing variables such as stimulating factors, tourist experiences, and behavioral intentions. Research hypotheses are formulated, and a theoretical model is constructed. Offline questionnaires from 400 Mogao Caves AR tourists were collected, and data were analyzed using PLS-SEM. The study aims to understand the relationship between tourist experiences and behavioral intentions, analyze mediating effects, validate hypotheses, and confirm the structural model, offering reliable statistical support and a scientific basis for the findings. Results: The results indicate that in AR tourism, content quality, system quality, and interaction quality have a positive impact on tourist experiences. AR tourism experiences significantly influence behavioral intentions. Particularly surprising is that the impact of tourism experiences on behavioral intentions exceeds expectations, demonstrating its importance in AR tourism. This finding highlights the potential of AR technology in enhancing tourist experiences and provides new development opportunities for tourism destinations. Conclusion: AR technology holds immense promise for tourism development at the Mogao Caves heritage site. Factors like content, system, and interaction quality significantly enhance tourist experiences and behavioral intentions in AR tourism there. Quality content not only shapes a positive brand image but also opens up commercial and collaborative opportunities. System stability ensures smooth AR experiences, while interactive design boosts engagement and spending. However, the potential negative impacts of AR technology on tourism require further exploration in future research.

Analyzing the Impact of Metaverse Technology on Social Development: A Field Study on Generation Z in the United Arab Emirates

Considering the current role of technology, this research aims to investigate the impact of the metaverse on social development and psychological well-being in the United Arab Emirates (UAE). The focus remains on Generation Z, as an important portion of the country’s metaverse users. Supported by the technology determinism theory, this research used a structured questionnaire to gather data from 363 respondents. The analysis indicates that metaverse technology significantly impacts social development and psychological well-being. The effect of metaverse technology on social development remained positive, with the p-value at p > 0.000. In addition, metaverse technology also has a significant positive effect on psychological well-being (p > 0.000), with the findings showing strong statistical support for this relationship. These results confirm that metaverse technology plays a significant role in improving both social and psychological facets. Thus, it is concluded that the metaverse creates immersive virtual environments that help unique forms of social interaction and connectivity, confounding geographical barriers. This can improve social skills and communication and promote a strong sense of community. The metaverse offers a directed and engaging space to practice social interactions and gain confidence, indicating its positive, constructive role in society.

The development of the Autism Stigma and Knowledge Questionnaire, Second edition (ASK-Q-2), through a cross-cultural psychometric investigation.

The Autism Stigma and Knowledge Questionnaire (ASK-Q) was developed to assess autism knowledge across cultural contexts. The current study aimed to examine cultural equivalence of the measure using a large, international database. These analyses identified 18 items in need of examination for removal or revision. A team of autism experts recommended several additional changes to reduce stigma and increase cross-cultural sensitivity and accuracy of the items on the measure. These changes resulted in a briefer measure with maintained statistical support.

Phylogenetic and taxonomic evidence reveal Punctulariopsis yunnanensis sp. nov. (Punctulariaceae, Basidiomycota) from southwest China

A new wood-rotting fungal species, Punctulariopsis yunnanensis, is proposed based on a combination of morphology and molecular data. The species is characterized by the resupinate basidiomata with a pinkish buff salmon hymenial surface, a monomitic system, generative hyphae with clamp connections, and subhymenial generative hyphae thick-walled, and the presence of dendrohyphidia, and broadly ellipsoid basidiospores measuring 7.8–12.8 × 6–9.8 µm. Phylogenetic analyses of the combined ITS and nLSU nrDNA gene regions demonstrated that P. yunnanensis formed an independent lineage and was sister to P. subglobispora with strong statistical support. A full description, illustrations and phylogenetic analysis results of the new species are provided.

Detecting statistically significant changes in connectedness: A bootstrap-based technique

Connectedness quantifies the extent of interlinkages within economies or markets based on a network approach. Connectedness is measured by the Diebold–Yilmaz spillover index, and abrupt increases in this measure are thought to result from major events. However, formal statistical evidence of events causing such increases is scant. We develop a bootstrap-based technique to evaluate the probability that the value of the spillover index changes at a statistically significant level following an exogenously defined event. We further show how our procedure can detect the dates of unknown events endogenously. The results of a simulation exercise support the effectiveness of our method. We revisit the original dataset from Diebold and Yilmaz’s seminal work and obtain statistical support that the spillover index increases quickly in the wake of adverse shocks. Our methodology accounts for small sample bias and is robust with respect to modifications of the pre-event period and forecast horizon.

Short-term effects of an unprecedented heatwave on intertidal bivalve populations: fisheries management surveys provide an incomplete picture

IntroductionCoastal marine ecosystems, are particularly susceptible to climate change. One such threat is atmospheric heatwaves, which are predicted to increase in frequency, duration, and intensity. Many intertidal organisms already live at the edge of their thermal tolerance limits and heatwaves can outstretch an organism’s ability to compensate in the short term. In June 2021 the Pacific Northwest region of North America, including the Salish Sea, experienced a significant atmospheric heatwave during some of the lowest tides of the year. This was followed by numerous reports of dead and dying intertidal marine organisms region-wide. A semi-quantitative rapid assessment found a range of both species- and location-specific effects but generally recorded widespread negative impacts to intertidal shellfish species across the Salish Sea. MethodsFollowing these results, we opportunistically analyzed data collected by intertidal bivalve resource managers from the region. These datasets allowed us to examine regional density and size data for clam and oyster populations before and after the heatwave to increase our quantitative understanding of heatwave effects. ResultsWe found a range of responses including positive and negative effects of the heatwave on clam and oyster density. While we generally found small changes in bivalve size, some site-species combinations displayed large shifts in size frequency. Many of our analyses did not indicate even moderate statistical support, even with large changes in the mean, driven in part by high variability in the data. Time intervals between surveys, ranging from 2 to over 25 months, had little effect on observed variability indicating that any heatwave-induced effects may be masked by variability inherent to the population ecology and/or survey methodology. DiscussionThis analysis has highlighted the need for intertidal resource managers, and the greater research community, to consider alternative survey approaches designed to constrain variability in order to detect the effects of acute or extreme events. With the effects of climate change predicted to become more intense, targeted survey approaches may be needed to detect the effects and implications of such events and to continue effective management of intertidal bivalves in the Salish Sea and worldwide.

Genetic Variation among Rare Florida Endemic Hymenocallis henryae Populations and the Implication for Conservation and Management

Hymenocallis henryae is a rare, charismatic spider lily endemic to the Florida panhandle. Currently under review to determine if listing under the Endangered Species Act is warranted, this species has undescribed genetic diversity, information crucial to the listing process. We conducted field observations of 21 historic populations across the species’ geographical range and performed genomic analyses of 279 individuals from 19 extant populations. Most populations had fewer than 40 individuals, while populations with >100 individuals were found exclusively on managed lands. Genetic diversity was uniformly low within populations (HE: 0.074–0.093), with low to moderate inbreeding coefficients (FIS: 0.068–0.431). Genetic differentiation was relatively low among most populations (FST: 0–0.098), although there was statistical support for isolation by distance. In addition, we found high genetic similarity and lack of population structure across the species range. Clonal propagation through fused bulbs is a common reproductive strategy. We confirmed current threats (habitat change, residential development, fire suppression) and identified several coastal populations threatened by sea level rise. It is recommended to continue with in situ protection and management as well as the establishment of ex situ living collections to preserve populations most at risk of extirpation from habitat loss and degradation.