The Ontology of Biological Attributes (OBA)-computational traits for the life sciences.

Existing phenotype ontologies were originally developed to represent phenotypes that manifest as a character state in relation to a wild-type or other reference. However, these do not include the phenotypic trait or attribute categories required for the annotation of genome-wide association studies (GWAS), Quantitative Trait Loci (QTL) mappings or any population-focussed measurable trait data. The integration of trait and biological attribute information with an ever increasing body of chemical, environmental and biological data greatly facilitates computational analyses and it is also highly relevant to biomedical and clinical applications. The Ontology of Biological Attributes (OBA) is a formalised, species-independent collection of interoperable phenotypic trait categories that is intended to fulfil a data integration role. OBA is a standardised representational framework for observable attributes that are characteristics of biological entities, organisms, or parts of organisms. OBA has a modular design which provides several benefits for users and data integrators, including an automated and meaningful classification of trait terms computed on the basis of logical inferences drawn from domain-specific ontologies for cells, anatomical and other relevant entities. The logical axioms in OBA also provide a previously missing bridge that can computationally link Mendelian phenotypes with GWAS and quantitative traits. The term components in OBA provide semantic links and enable knowledge and data integration across specialised research community boundaries, thereby breaking silos.

The Ontology of Biological Attributes (OBA) - Computational Traits for the Life Sciences.

Existing phenotype ontologies were originally developed to represent phenotypes that manifest as a character state in relation to a wild-type or other reference. However, these do not include the phenotypic trait or attribute categories required for the annotation of genome-wide association studies (GWAS), Quantitative Trait Loci (QTL) mappings or any population-focused measurable trait data. Moreover, variations in gene expression in response to environmental disturbances even without any genetic alterations can also be associated with particular biological attributes. The integration of trait and biological attribute information with an ever increasing body of chemical, environmental and biological data greatly facilitates computational analyses and it is also highly relevant to biomedical and clinical applications. The Ontology of Biological Attributes (OBA) is a formalised, species-independent collection of interoperable phenotypic trait categories that is intended to fulfil a data integration role. OBA is a standardised representational framework for observable attributes that are characteristics of biological entities, organisms, or parts of organisms. OBA has a modular design which provides several benefits for users and data integrators, including an automated and meaningful classification of trait terms computed on the basis of logical inferences drawn from domain-specific ontologies for cells, anatomical and other relevant entities. The logical axioms in OBA also provide a previously missing bridge that can computationally link Mendelian phenotypes with GWAS and quantitative traits. The term components in OBA provide semantic links and enable knowledge and data integration across specialised research community boundaries, thereby breaking silos.

Unifying the identification of biomedical entities with the Bioregistry.

The standardized identification of biomedical entities is a cornerstone of interoperability, reuse, and data integration in the life sciences. Several registries have been developed to catalog resources maintaining identifiers for biomedical entities such as small molecules, proteins, cell lines, and clinical trials. However, existing registries have struggled to provide sufficient coverage and metadata standards that meet the evolving needs of modern life sciences researchers. Here, we introduce the Bioregistry, an integrative, open, community-driven metaregistry that synthesizes and substantially expands upon 23 existing registries. The Bioregistry addresses the need for a sustainable registry by leveraging public infrastructure and automation, and employing a progressive governance model centered around open code and open data to foster community contribution. The Bioregistry can be used to support the standardized annotation of data, models, ontologies, and scientific literature, thereby promoting their interoperability and reuse. The Bioregistry can be accessed through https://bioregistry.io and its source code and data are available under the MIT and CC0 Licenses at https://github.com/biopragmatics/bioregistry .

A solution to the challenges of interdisciplinary aggregation and use of specimen-level trait data.

Understanding variation of traits within and among species through time and across space is central to many questions in biology. Many resources assemble species-level trait data, but the data and metadata underlying those trait measurements are often not reported. Here, we introduce FuTRES (Functional Trait Resource for Environmental Studies; pronounced few-tress), an online datastore and community resource for individual-level trait reporting that utilizes a semantic framework. FuTRES already stores millions of trait measurements for paleobiological, zooarchaeological, and modern specimens, with a current focus on mammals. We compare dynamically derived extant mammal species' body size measurements in FuTRES with summary values from other compilations, highlighting potential issues with simply reporting a single mean estimate. We then show that individual-level data improve estimates of body mass-including uncertainty-for zooarchaeological specimens. FuTRES facilitates trait data integration and discoverability, accelerating new research agendas, especially scaling from intra- to interspecific trait variability.

Late quaternary biotic homogenization of North American mammalian faunas.

Biotic homogenization-increasing similarity of species composition among ecological communities-has been linked to anthropogenic processes operating over the last century. Fossil evidence, however, suggests that humans have had impacts on ecosystems for millennia. We quantify biotic homogenization of North American mammalian assemblages during the late Pleistocene through Holocene (~30,000 ybp to recent), a timespan encompassing increased evidence of humans on the landscape (~20,000-14,000 ybp). From ~10,000 ybp to recent, assemblages became significantly more homogenous (>100% increase in Jaccard similarity), a pattern that cannot be explained by changes in fossil record sampling. Homogenization was most pronounced among mammals larger than 1 kg and occurred in two phases. The first followed the megafaunal extinction at ~10,000 ybp. The second, more rapid phase began during human population growth and early agricultural intensification (~2,000-1,000 ybp). We show that North American ecosystems were homogenizing for millennia, extending human impacts back ~10,000 years.

Decoding the dynamics of dental distributions: insights from shark demography and dispersal.

Shark teeth are one of the most abundant vertebrate fossils, and because tooth size generally correlates with body size, their accumulations document the size structure of populations. Understanding how ecological and environmental processes influence size structure, and how this extends to influence these dental distributions, may offer a window into the ecological and environmental dynamics of past and present shark populations. Here, we examine the dental distributions of sand tigers, including extant Carcharias taurus and extinct Striatolamia macrota, to reconstruct the size structure for a contemporary locality and four Eocene localities. We compare empirical distributions against expectations from a population simulation to gain insight into potential governing ecological processes. Specifically, we investigate the influence of dispersal flexibility to and from protected nurseries. We show that changing the flexibility of initial dispersal of juveniles from the nursery and annual migration of adults to the nursery explains a large amount of dental distribution variability. Our framework predicts dispersal strategies of an extant sand tiger population, and supports nurseries as important components of sand tiger life history in both extant and Eocene populations. These results suggest nursery protection may be vital for shark conservation with increasing anthropogenic impacts and climate change.

Investigating Biotic Interactions in Deep Time.

Recent renewed interest in using fossil data to understand how biotic interactions have shaped the evolution of life is challenging the widely held assumption that long-term climate changes are the primary drivers of biodiversity change. New approaches go beyond traditional richness and co-occurrence studies to explicitly model biotic interactions using data on fossil and modern biodiversity. Important developments in three primary areas of research include analysis of (i) macroevolutionary rates, (ii) the impacts of and recovery from extinction events, and (iii) how humans (Homo sapiens) affected interactions among non-human species. We present multiple lines of evidence for an important and measurable role of biotic interactions in shaping the evolution of communities and lineages on long timescales.

Publisher Correction: Open Science principles for accelerating trait-based science across the Tree of Life.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Open Science principles for accelerating trait-based science across the Tree of Life.

Synthesizing trait observations and knowledge across the Tree of Life remains a grand challenge for biodiversity science. Species traits are widely used in ecological and evolutionary science, and new data and methods have proliferated rapidly. Yet accessing and integrating disparate data sources remains a considerable challenge, slowing progress toward a global synthesis to integrate trait data across organisms. Trait science needs a vision for achieving global integration across all organisms. Here, we outline how the adoption of key Open Science principles-open data, open source and open methods-is transforming trait science, increasing transparency, democratizing access and accelerating global synthesis. To enhance widespread adoption of these principles, we introduce the Open Traits Network (OTN), a global, decentralized community welcoming all researchers and institutions pursuing the collaborative goal of standardizing and integrating trait data across organisms. We demonstrate how adherence to Open Science principles is key to the OTN community and outline five activities that can accelerate the synthesis of trait data across the Tree of Life, thereby facilitating rapid advances to address scientific inquiries and environmental issues. Lessons learned along the path to a global synthesis of trait data will provide a framework for addressing similarly complex data science and informatics challenges.

Exploring the influence of ancient and historic megaherbivore extirpations on the global methane budget.

Globally, large-bodied wild mammals are in peril. Because "megamammals" have a disproportionate influence on vegetation, trophic interactions, and ecosystem function, declining populations are of considerable conservation concern. However, this is not new; trophic downgrading occurred in the past, including the African rinderpest epizootic of the 1890s, the massive Great Plains bison kill-off in the 1860s, and the terminal Pleistocene extinction of megafauna. Examining the consequences of these earlier events yields insights into contemporary ecosystem function. Here, we focus on changes in methane emissions, produced as a byproduct of enteric fermentation by herbivores. Although methane is ∼ 200 times less abundant than carbon dioxide in the atmosphere, the greater efficiency of methane in trapping radiation leads to a significant role in radiative forcing of climate. Using global datasets of late Quaternary mammals, domestic livestock, and human population from the United Nations as well as literature sources, we develop a series of allometric regressions relating mammal body mass to population density and CH4 production, which allows estimation of methane production by wild and domestic herbivores for each historic or ancient time period. We find the extirpation of megaherbivores reduced global enteric emissions between 2.2-69.6 Tg CH4 y(-1) during the various time periods, representing a decrease of 0.8-34.8% of the overall inputs to tropospheric input. Our analyses suggest that large-bodied mammals have a greater influence on methane emissions than previously appreciated and, further, that changes in the source pool from herbivores can influence global biogeochemical cycles and, potentially, climate.

Metabolic heat production and thermal conductance are mass-independent adaptations to thermal environment in birds and mammals.

The extent to which different kinds of organisms have adapted to environmental temperature regimes is central to understanding how they respond to climate change. The Scholander-Irving (S-I) model of heat transfer lays the foundation for explaining how endothermic birds and mammals maintain their high, relatively constant body temperatures in the face of wide variation in environmental temperature. The S-I model shows how body temperature is regulated by balancing the rates of heat production and heat loss. Both rates scale with body size, suggesting that larger animals should be better adapted to cold environments than smaller animals, and vice versa. However, the global distributions of ∼9,000 species of terrestrial birds and mammals show that the entire range of body sizes occurs in nearly all climatic regimes. Using physiological and environmental temperature data for 211 bird and 178 mammal species, we test for mass-independent adaptive changes in two key parameters of the S-I model: basal metabolic rate (BMR) and thermal conductance. We derive an axis of thermal adaptation that is independent of body size, extends the S-I model, and highlights interactions among physiological and morphological traits that allow endotherms to persist in a wide range of temperatures. Our macrophysiological and macroecological analyses support our predictions that shifts in BMR and thermal conductance confer important adaptations to environmental temperature in both birds and mammals.

Body-size trends of the extinct giant shark Carcharocles megalodon: a deep-time perspective on marine apex predators.

The extinct shark Carcharocles megalodon is one of the largest marine apex predators ever to exist. Nonetheless, little is known about its body-size variations through time and space. Here, we studied the body-size trends of C. megalodon through its temporal and geographic range to better understand its ecology and evolution. Given that this species was the last of the megatooth lineage, a group of species that shows a purported size increase through time, we hypothesized that C. megalodon also displayed this trend, increasing in size over time and reaching its largest size prior to extinction. We found that C. megalodon body-size distribution was left-skewed (suggesting a long-term selective pressure favoring larger individuals), and presented significant geographic variation (possibly as a result of the heterogeneous ecological constraints of this cosmopolitan species) over geologic time. Finally, we found that stasis was the general mode of size evolution of C. megalodon (i.e., no net changes over time), contrasting with the trends of the megatooth lineage and our hypothesis. Given that C. megalodon is a relatively long-lived species with a widely distributed fossil record, we further used this study system to provide a deep-time perspective to the understanding of the body-size trends of marine apex predators. For instance, our results suggest that (1) a selective pressure in predatory sharks for consuming a broader range of prey may favor larger individuals and produce left-skewed distributions on a geologic time scale; (2) body-size variations in cosmopolitan apex marine predators may depend on their interactions with geographically discrete communities; and (3) the inherent characteristics of shark species can produce stable sizes over geologic time, regardless of the size trends of their lineages.

Sizing ocean giants: patterns of intraspecific size variation in marine megafauna.

What are the greatest sizes that the largest marine megafauna obtain? This is a simple question with a difficult and complex answer. Many of the largest-sized species occur in the world's oceans. For many of these, rarity, remoteness, and quite simply the logistics of measuring these giants has made obtaining accurate size measurements difficult. Inaccurate reports of maximum sizes run rampant through the scientific literature and popular media. Moreover, how intraspecific variation in the body sizes of these animals relates to sex, population structure, the environment, and interactions with humans remains underappreciated. Here, we review and analyze body size for 25 ocean giants ranging across the animal kingdom. For each taxon we document body size for the largest known marine species of several clades. We also analyze intraspecific variation and identify the largest known individuals for each species. Where data allows, we analyze spatial and temporal intraspecific size variation. We also provide allometric scaling equations between different size measurements as resources to other researchers. In some cases, the lack of data prevents us from fully examining these topics and instead we specifically highlight these deficiencies and the barriers that exist for data collection. Overall, we found considerable variability in intraspecific size distributions from strongly left- to strongly right-skewed. We provide several allometric equations that allow for estimation of total lengths and weights from more easily obtained measurements. In several cases, we also quantify considerable geographic variation and decreases in size likely attributed to humans.