Ancient DNA confirms diverse origins of early post-Columbian cattle in the Americas.

Before the arrival of Europeans, domestic cattle (Bos taurus) did not exist in the Americas, and most of our knowledge about how domestic bovines first arrived in the Western Hemisphere is based on historical documents. Sixteenth-century colonial accounts suggest that the first cattle were brought in small numbers from the southern Iberian Peninsula via the Canary archipelago to the Caribbean islands where they were bred locally and imported to other circum-Caribbean regions. Modern American heritage cattle genetics and limited ancient mtDNA data from archaeological colonial cattle suggest a more complex story of mixed ancestries from Europe and Africa. So far little information exists to understand the nature and timing of the arrival of these mixed-ancestry populations. In this study we combine ancient mitochondrial and nuclear DNA from a robust sample of some of the earliest archaeological specimens from Caribbean and Mesoamerican sites to clarify the origins and the dynamics of bovine introduction into the Americas. Our analyses support first arrival of cattle from diverse locales and potentially confirm the early arrival of African-sourced cattle in the Americas, followed by waves of later introductions from various sources over several centuries.

Computer vision for assessing species color pattern variation from web-based community science images.

Openly available community science digital vouchers provide a wealth of data to study phenotypic change across space and time. However, extracting phenotypic data from these resources requires significant human effort. Here, we demonstrate a workflow and computer vision model for automatically categorizing species color pattern from community science images. Our work is focused on documenting the striped/unstriped color polymorphism in the Eastern Red-backed Salamander (Plethodon cinereus). We used an ensemble convolutional neural network model to analyze this polymorphism in 20,318 iNaturalist images. Our model was highly accurate (∼98%) despite image heterogeneity. We used the resulting annotations to document extensive niche overlap between morphs, but wider niche breadth for striped morphs at the range-wide scale. Our work showcases key design principles for using machine learning with heterogeneous community science image data to address questions at an unprecedented scale.

Analysis of the earliest complete mtDNA genome of a Caribbean colonial horse (Equus caballus) from 16th-century Haiti.

Unlike other European domesticates introduced in the Americas after the European invasion, equids (Equidae) were previously in the Western Hemisphere but were extinct by the late Holocene era. The return of equids to the Americas through the introduction of the domestic horse (Equus caballus) is documented in the historical literature but is not explored fully either archaeologically or genetically. Historical documents suggest that the first domestic horses were brought from the Iberian Peninsula to the Caribbean in the late 15th century CE, but archaeological remains of these early introductions are rare. This paper presents the mitochondrial genome of a late 16th century horse from the Spanish colonial site of Puerto Real (northern Haiti). It represents the earliest complete mitogenome of a post-Columbian domestic horse in the Western Hemisphere offering a unique opportunity to clarify the phylogeographic history of this species in the Americas. Our data supports the hypothesis of an Iberian origin for this early translocated individual and clarifies its phylogenetic relationship with modern breeds in the Americas.

Artificial Intelligence for Biology.

Despite efforts to integrate research across different subdisciplines of biology, the scale of integration remains limited. We hypothesize that future generations of Artificial Intelligence (AI) technologies specifically adapted for biological sciences will help enable the reintegration of biology. AI technologies will allow us not only to collect, connect, and analyze data at unprecedented scales, but also to build comprehensive predictive models that span various subdisciplines. They will make possible both targeted (testing specific hypotheses) and untargeted discoveries. AI for biology will be the cross-cutting technology that will enhance our ability to do biological research at every scale. We expect AI to revolutionize biology in the 21st century much like statistics transformed biology in the 20th century. The difficulties, however, are many, including data curation and assembly, development of new science in the form of theories that connect the subdisciplines, and new predictive and interpretable AI models that are more suited to biology than existing machine learning and AI techniques. Development efforts will require strong collaborations between biological and computational scientists. This white paper provides a vision for AI for Biology and highlights some challenges.

Expanding the purview of wellness indicators: validating a new measure that includes attitudes, behaviors, and perspectives.

OBJECTIVE: The present study validated the DeltaQuest Wellness Measure (DQ Wellness), a new 15-item measure of wellness that spans relevant attitudes, behaviors, and perspectives. DESIGN: This cross-sectional web-based study recruited chronically-ill patients and/or caregivers (n = 3,961) and a nationally representative comparison group (n = 855). MAIN OUTCOME MEASURES: The DQ Wellness assesses: a way of being in the world that involves seeing and embracing the good and expressing kindness toward others; engagement in one's activities and self-care; downplaying negative thoughts that reduce one's energy; and an ability to feel joy. Six widely used measures of physical and mental health, cognition, and psychological well-being enabled construct-validity comparisons. Item-response theory (IRT) methods evaluated reliability, factor structure, and differential item functioning (DIF) by gender. RESULTS: The DQ Wellness showed strong cross-sectional reliability (marginal reliability = 0.89) and fit a bifactor model (RMSEA = 0.063, CFI = 0.982, TLI = 0.983). The DQ Wellness general score demonstrated construct validity, convergent and divergent validity, unique variance, and known-groups validity, and minimal gender DIF. The study is limited to addressing cross-sectional reliability and validity, and response rates are not known due to the recruitment source. CONCLUSION: The DQ Wellness is a relatively brief measure, taps novel content, and could be useful for observational or interventional studies.

Climate drivers of adult insect activity are conditioned by life history traits.

Insect phenological lability is key for determining which species will adapt under environmental change. However, little is known about when adult insect activity terminates and overall activity duration. We used community-science and museum specimen data to investigate the effects of climate and urbanisation on timing of adult insect activity for 101 species varying in life history traits. We found detritivores and species with aquatic larval stages extend activity periods most rapidly in response to increasing regional temperature. Conversely, species with subterranean larval stages have relatively constant durations regardless of regional temperature. Species extended their period of adult activity similarly in warmer conditions regardless of voltinism classification. Longer adult durations may represent a general response to warming, but voltinism data in subtropical environments are likely underreported. This effort provides a framework to address the drivers of adult insect phenology at continental scales and a basis for predicting species response to environmental change.

Ancient DNA from the extinct Haitian cave-rail (Nesotrochis steganinos) suggests a biogeographic connection between the Caribbean and Old World.

Worldwide decline in biodiversity during the Holocene has impeded a comprehensive understanding of pre-human biodiversity and biogeography. This is especially true on islands, because many recently extinct island taxa were morphologically unique, complicating assessment of their evolutionary relationships using morphology alone. The Caribbean remains an avian hotspot but was more diverse before human arrival in the Holocene. Among the recently extinct lineages is the enigmatic genus Nesotrochis, comprising three flightless species. Based on morphology, Nesotrochis has been considered an aberrant rail (Rallidae) or related to flufftails (Sarothruridae). We recovered a nearly complete mitochondrial genome of Nesotrochis steganinos from fossils, discovering that it is not a rallid but instead is sister to Sarothruridae, volant birds now restricted to Africa and New Guinea, and the recently extinct, flightless Aptornithidae of New Zealand. This result suggests a widespread or highly dispersive most recent common ancestor of the group. Prior to human settlement, the Caribbean avifauna had a far more cosmopolitan origin than is evident from extant species.

Response-shift effects in neuromyelitis optica spectrum disorder: estimating response-shift-adjusted scores using equating.

BACKGROUND: In our companion paper, random intercept models (RIMs) investigated response-shift effects in a clinical trial comparing Eculizumab to Placebo for people with neuromyelitis optica spectrum disorder (NMOSD). RIMs predicted Global Health using the EQ-5D Visual Analogue Scale item (VAS) to encompass broad criteria that people might consider. The SF36™v2 mental and physical component scores (MCS and PCS) helped us detect response shift in VAS. Here, we sought to "back-translate" the VAS into the MCS/PCS scores that would have been observed if response shift had not been present. METHODS: This secondary analysis utilized NMOSD clinical trial data evaluating the impact of Eculizumab in preventing relapses (n = 143). Analyses began by equating raw scores from the VAS, MCS, and PCS, and computing scores that removed response-shift effects. Correlation analysis and descriptive displays provided a more comprehensive examination of response-shift effects. RESULTS: MCS and PCS crosswalks with VAS equated the scores that include and exclude response-shift effects. These two sets of scores had low shared variance for MCS for both groups, suggesting that corresponding mental health constructs were substantially different. The shared variance contrast for physical health was distinct only for the Placebo group. The larger MCS response-shift effects were found at end of study for Placebo only and were more prominent at extremes of the MCS score distribution. CONCLUSIONS: Our results reveal notable treatment group differences in MCS but not PCS response shifts, which can explain null results detected in previous work. The method introduced herein provides a way to provide further information about response-shift effects in clinical trial data.

Climate, urbanization, and species traits interactively drive flowering duration.

A wave of green leaves and multi-colored flowers advances from low to high latitudes each spring. However, little is known about how flowering offset (i.e., ending of flowering) and duration of populations of the same species vary along environmental gradients. Understanding these patterns is critical for predicting the effects of future climate and land-use change on plants, pollinators, and herbivores. Here, we investigated potential climatic and landscape drivers of flowering onset, offset, and duration of 52 plant species with varying key traits. We generated phenology estimates using >270,000 community-science photographs and a novel presence-only phenometric estimation method. We found longer flowering durations in warmer areas, which is more obvious for summer-blooming species compared to spring-bloomers driven by their strongly differing offset dynamics. We also found that higher human population density and higher annual precipitation are associated with delayed flowering offset and extended flowering duration. Finally, offset of woody perennials was more sensitive than herbaceous species to both climate and urbanization drivers. Empirical forecast models suggested that flowering durations will be longer in 2030 and 2050 under representative concentration pathway (RCP) 8.5, especially for summer-blooming species. Our study provides critical insight into drivers of key flowering phenophases and confirms that Hopkins' Bioclimatic Law also applies to flowering durations for summer-blooming species and herbaceous spring-blooming species.

Response-shift effects in neuromyelitis optica spectrum disorder: a secondary analysis of clinical trial data.

BACKGROUND: Researchers have long posited that response-shift effects may obfuscate treatment effects. The present work investigated possible response-shift effects in a recent clinical trial testing a new treatment for Neuromyelitis Optica Spectrum Disorder (NMOSD). This pivotal trial provided impressive support for the drug Eculizumab in preventing relapse, but less strong or null results as the indicators became more subjective or evaluative. This pattern of results suggests that response-shift effects are present. METHODS: This secondary analysis utilized data from a randomized, double-blind trial evaluating the impact of Eculizumab in preventing relapses in 143 people with NMOSD. Treatment arm and then relapse status were hypothesized 'catalysts' of response shift in two series of analyses. We devised a "de-constructed" version of Oort structural-equation modeling using random-effects modeling for use in small samples. This method begins by testing an omnibus response-shift hypothesis and then, pending a positive result, implements a series of random-effects models to elucidate specific response-shift effects. RESULTS: In the omnibus test, the 'standard quality-of-life (QOL) model' captured substantially less well the experience of placebo as compared to Eculizumab group. Recalibration and reconceptualization response-shift effects were detected. Detected relapse-related response shifts included recalibration, reprioritization, and reconceptualization. CONCLUSIONS: Trial patients experienced response shifts related to treatment- and relapse-related experiences. Published trial results likely under-estimated Eculizumab vs. Placebo differences due to recalibration and reconceptualization, and relapse effects due to recalibration, reprioritization, and reconceptualization. This novel random-effects- model application builds on response-shift theory and provides a small-sample method for better estimating treatment effects in clinical trials.

Transforming the study of organisms: Phenomic data models and knowledge bases.

The rapidly decreasing cost of gene sequencing has resulted in a deluge of genomic data from across the tree of life; however, outside a few model organism databases, genomic data are limited in their scientific impact because they are not accompanied by computable phenomic data. The majority of phenomic data are contained in countless small, heterogeneous phenotypic data sets that are very difficult or impossible to integrate at scale because of variable formats, lack of digitization, and linguistic problems. One powerful solution is to represent phenotypic data using data models with precise, computable semantics, but adoption of semantic standards for representing phenotypic data has been slow, especially in biodiversity and ecology. Some phenotypic and trait data are available in a semantic language from knowledge bases, but these are often not interoperable. In this review, we will compare and contrast existing ontology and data models, focusing on nonhuman phenotypes and traits. We discuss barriers to integration of phenotypic data and make recommendations for developing an operationally useful, semantically interoperable phenotypic data ecosystem.

Machine Learning Using Digitized Herbarium Specimens to Advance Phenological Research.

Machine learning (ML) has great potential to drive scientific discovery by harvesting data from images of herbarium specimens-preserved plant material curated in natural history collections-but ML techniques have only recently been applied to this rich resource. ML has particularly strong prospects for the study of plant phenological events such as growth and reproduction. As a major indicator of climate change, driver of ecological processes, and critical determinant of plant fitness, plant phenology is an important frontier for the application of ML techniques for science and society. In the present article, we describe a generalized, modular ML workflow for extracting phenological data from images of herbarium specimens, and we discuss the advantages, limitations, and potential future improvements of this workflow. Strategic research and investment in specimen-based ML methods, along with the aggregation of herbarium specimen data, may give rise to a better understanding of life on Earth.

Maximizing human effort for analyzing scientific images: A case study using digitized herbarium sheets.

PREMISE: Digitization and imaging of herbarium specimens provides essential historical phenotypic and phenological information about plants. However, the full use of these resources requires high-quality human annotations for downstream use. Here we provide guidance on the design and implementation of image annotation projects for botanical research. METHODS AND RESULTS: We used a novel gold-standard data set to test the accuracy of human phenological annotations of herbarium specimen images in two settings: structured, in-person sessions and an online, community-science platform. We examined how different factors influenced annotation accuracy and found that botanical expertise, academic career level, and time spent on annotations had little effect on accuracy. Rather, key factors included traits and taxa being scored, the annotation setting, and the individual scorer. In-person annotations were significantly more accurate than online annotations, but both generated relatively high-quality outputs. Gathering multiple, independent annotations for each image improved overall accuracy. CONCLUSIONS: Our results provide a best-practices basis for using human effort to annotate images of plants. We show that scalable community science mechanisms can produce high-quality data, but care must be taken to choose tractable taxa and phenophases and to provide informative training material.

Does response shift impact interpretation of change even among scales developed using item response theory?

BACKGROUND: Response-shift effects impact the interpretation of change in quality-of-life (QOL) measures developed with classical test theory (CTT) methods. This study evaluated the impact of response shift on measures developed using Item Response Theory (IRT), as compared to CTT. METHODS: Chronically ill patients and caregivers (n = 1481) participated in a web-based survey at baseline and 17 months later. Patients completed the IRT-based PROMIS-10; NeuroQOL Applied Cognition, Positive Affect & Well-Being short-forms; and the CTT-based Ryff Environmental Mastery subscale. Response-shift effects were evaluated using regression residual modeling and the QOL Appraisal Profile-v2. The sample was divided into positive and negative catalyst groups on the basis of marital, work, job-status, and comorbidity change. Regression models predicted residualized QOL change scores as a function of catalysts and appraisal changes. RESULTS: In this sample 859 (58%) reported a catalyst. No catalyst was associated with change in scales developed using IRT, but positive work change was associated with the CTT-based measure. Catalyst variables were associated with changes in appraisal, which in turn were related to all outcomes, particularly for global mental health after a positive work-change. CONCLUSIONS: Appraisal processes are relevant to interpreting IRT measures, particularly for global mental health in the face of life changes.

Ancient DNA and high-resolution chronometry reveal a long-term human role in the historical diversity and biogeography of the Bahamian hutia.

Quaternary paleontological and archaeological evidence often is crucial for uncovering the historical mechanisms shaping modern diversity and distributions. We take an interdisciplinary approach using multiple lines of evidence to understand how past human activity has shaped long-term animal diversity in an island system. Islands afford unique opportunities for such studies given their robust fossil and archaeological records. Herein, we examine the only non-volant terrestrial mammal endemic to the Bahamian Archipelago, the hutia Geocapromys ingrahami. This capromyine rodent once inhabited many islands but is now restricted to several small cays. Radiocarbon dated fossils indicate that hutias were present on the Great Bahama Bank islands before humans arrived at AD ~800-1000; all dates from other islands post-date human arrival. Using ancient DNA from a subset of these fossils, along with modern representatives of Bahamian hutia and related taxa, we develop a fossil-calibrated phylogeny. We found little genetic divergence among individuals from within either the northern or southern Bahamas but discovered a relatively deep North-South divergence (~750 ka). This result, combined with radiocarbon dating and archaeological evidence, reveals a pre-human biogeographic divergence, and an unexpected human role in shaping Bahamian hutia diversity and biogeography across islands.

Methods for broad-scale plant phenology assessments using citizen scientists' photographs.

PREMISE: Citizen science platforms for sharing photographed digital vouchers, such as iNaturalist, are a promising source of phenology data, but methods and best practices for use have not been developed. Here we introduce methods using Yucca flowering phenology as a case study, because drivers of Yucca phenology are not well understood despite the need to synchronize flowering with obligate pollinators. There is also evidence of recent anomalous winter flowering events, but with unknown spatiotemporal extents. METHODS: We collaboratively developed a rigorous, consensus-based approach for annotating and sharing whole plant and flower presence data from iNaturalist and applied it to Yucca records. We compared spatiotemporal flowering coverage from our annotations with other broad-scale monitoring networks (e.g., the National Phenology Network) in order to determine the unique value of photograph-based citizen science resources. RESULTS: Annotations from iNaturalist were uniquely able to delineate extents of unusual flowering events in Yucca. These events, which occurred in two different regions of the Desert Southwest, did not appear to disrupt the typical-period flowering. DISCUSSION: Our work demonstrates that best practice approaches to scoring iNaturalist records provide fine-scale delimitation of phenological events. This approach can be applied to other plant groups to better understand how phenology responds to changing climate.

Positive emotions despite substantial burden: The alchemy of haemophilia caregiving.

INTRODUCTION: Qualitative interviews when developing the haemophilia caregiver impact measure© (HCI) documented the importance of capturing the positive aspects of caregiving, not just the negative. AIM: The present study thus investigates the construct underlying the positive emotions HCI subscale and tests models proposing a more comprehensive way of thinking about this construct. METHODS: Secondary analysis was implemented on longitudinal web-based survey data (n = 323) from haemophilia A or haemophilia B caregivers. Person-reported outcomes (PROs) included the HCI, the PROMIS-10 and Ryff psychological well-being subscales. Predictors included caregiver demographics; patient haemophilia characteristics; exercise; adherence; and quality-of-life (QOL) appraisal processes as measured by the brief appraisal inventory (BAI) which yields composite scores assessing awareness of challenges, fulfillment and growth, stay positive, social comparison and interpersonal problem-solving. Second-order factor analysis, structural equation modelling and residual modelling were implemented. RESULTS: A structural equation model fit the data well that contained bifactor representation of well-being with a general factor comprised of environmental mastery, positive relations with others, physical functioning and emotional functioning. Positive emotions was modelled as a component of well-being, with a unique component ('Alchemy') characterized by its associations with stay positive, and awareness of challenges appraisals, and difficulty paying bills. Alchemy had positive linear relationships with the first two, and a positive quadratic relationship with difficulty paying bills. CONCLUSIONS: Adopting positive-focused ways of thinking about one's life limitations may transform the negatives of haemophilia caregiving into something positive. Such cognitive habits reflect an awareness and acceptance of the limitations imposed by haemophilia caregiving.

The effect of urbanization on plant phenology depends on regional temperature.

Plant and animal phenology is shifting in response to urbanization, with most hypotheses focusing on the 'urban heat island' (UHI) effect as the driver. However, generalities regarding the direction and magnitude of phenological response to urbanization have not yet emerged because most studies have focused on remote-sensed vegetative phenologies or at local scales with relatively few species. Furthermore, how urbanization interacts with broad-scale climate gradients remains an unknown but important component of anthropogenically driven phenological change. Here, we used a database with >22 million in situ plant phenological observations from the United States and Europe to study the joint influence of varying human population density, which serves as an urbanization measure, and of regional temperature on median flowering and leaf-out dates across a wide plant phylogenetic spectrum. Separately, increasing population density and warmer regional temperature both advanced plant flowering and leaf-out. However, the influence of human population density on plant flowering and leaf-out depends on the regional temperature: high population density advanced plant phenology in cold areas but this effect disappeared or even reversed in warm areas. UHI effects (as measured by daily land surface temperature) alone cannot explain the overall influence of urbanization on plant phenology, suggesting that urbanization also affects plant phenology via other mechanisms. Shorter plants with large specific leaf areas and early flower or leaf-out dates were most affected by urbanization and temperature changes. Our study provides strong empirical evidence that the influence of urbanization on plant phenology varies with regional temperature. Therefore, robust understanding and accurate prediction of phenological changes must take this interaction into account.

Is the link between socioeconomic status and resilience mediated by reserve-building activities: mediation analysis of web-based cross-sectional data from chronic medical illness patient panels.

OBJECTIVES: The purpose of this study is to test the hypothesis that the link between socioeconomic status (SES) and resilience is mediated by reserve-building activities. DESIGN: Cross-sectional observational study. Structural equation modelling (SEM) was used to test the mediation hypothesis. SETTING: Web-based survey. PARTICIPANTS: Participants with a chronic medical condition were recruited from Rare Patient Voice. PRIMARY AND SECONDARY OUTCOME MEASURES: DeltaQuest Reserve-Building Measure; demographic variables to capture SES; Centers for Disease Control Healthy Days Core Module; Self-Administered Comorbidity Questionnaire. Resilience was operationalised using residual modelling. RESULTS: The study sample included 442 patients (mean age 49, 85% female). SES was modelled as a bifactor model composed of general SES and specific factors for personal finance and parent's education. A series of simple mediation models predicting resilience led to the selection of three reserve-building activities for subsequent SEM-based mediation models: Active in the World, Outdoor and Exercise. The full SEM model supported the hypothesis that the relationships from both general SES and personal finance to resilience were mediated by engaging in the three reserve-building activities. In addition, the number of comorbidities partially mediated the relationship between personal finance and reserve-building. Those with more comorbidities generally had lower levels of resilience. CONCLUSIONS: This study provides suggestive evidence that reserve-building activities may be one pathway by which SES is associated with resilience: people of higher SES are more likely to engage in reserve-building activities that are intellectually stimulating, involve Outdoor pursuits and include physical Exercise. These reserve-building activities are not costly to pursue. These findings may empower patients to introduce more such reserve-building activities into their lives.

Integrating herbarium specimen observations into global phenology data systems.

PREMISE OF THE STUDY: The Plant Phenology Ontology (PPO) was originally developed to integrate phenology observations of whole plants across different global observation networks. Here we describe a new release of the PPO and associated data pipelines that supports integration of phenology observations from herbarium specimens, which provide historical and modern phenology data. METHODS AND RESULTS: Critical changes to the PPO include key terms that describe how measurements from parts of plants, which are captured in most imaged herbarium specimens, relate to whole plants. We provide proof of concept for ingesting annotations from imaged herbarium sheets of Prunus serotina, the common black cherry. We then provide an example analysis of changes in flowering timing over the past 125 years, demonstrating the value of integrating herbarium and observational phenology data sets. CONCLUSIONS: These conceptual and technical advances will support the addition of phenology data from herbaria, but also could be expanded upon to facilitate the inclusion of data from photograph-based citizen science platforms. With the incorporation of herbarium phenology data, new historical baseline data will strengthen the capability to monitor, model, and forecast plant phenology changes.