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the Americas, and most of our knowledge about how domestic bovines first arrived in the Western Hemisphere is based on historical documents.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.

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.

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.

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.

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.