Skills and Knowledge for Data-Intensive Environmental Research.

The scale and magnitude of complex and pressing environmental issues lend urgency to the need for integrative and reproducible analysis and synthesis, facilitated by data-intensive research approaches. However, the recent pace of technological change has been such that appropriate skills to accomplish data-intensive research are lacking among environmental scientists, who more than ever need greater access to training and mentorship in computational skills. Here, we provide a roadmap for raising data competencies of current and next-generation environmental researchers by describing the concepts and skills needed for effectively engaging with the heterogeneous, distributed, and rapidly growing volumes of available data. We articulate five key skills: (1) data management and processing, (2) analysis, (3) software skills for science, (4) visualization, and (5) communication methods for collaboration and dissemination. We provide an overview of the current suite of training initiatives available to environmental scientists and models for closing the skill-transfer gap

Enhancing the FAIRness of Arctic Research Data Through Semantic Annotation

The National Science Foundation’s Arctic Data Center is the primary data repository for NSF-funded research conducted in the Arctic. There are major challenges in discovering and interpreting resources in a repository containing data as heterogeneous and interdisciplinary as those in the Arctic Data Center. This paper reports on advances in cyberinfrastructure at the Arctic Data Center that help address these issues by leveraging semantic technologies that enhance the repository’s adherence to the FAIR data principles and improve the Findability, Accessibility, Interoperability, and Reusability of digital resources in the repository. We describe the Arctic Data Center’s improvements. We use semantic annotation to bind metadata about Arctic data sets with concepts in web-accessible ontologies. The Arctic Data Center’s implementation of a semantic annotation mechanism is accompanied by the development of an extended search interface that increases the findability of data by allowing users to search for specific, broader, and narrower meanings of measurement descriptions, as well as through their potential synonyms. Based on research carried out by the DataONE project, we evaluated the potential impact of this approach, regarding the accessibility, interoperability, and reusability of measurement data. Arctic research often benefits from having additional data, typically from multiple, heterogeneous sources, that complement and extend the bases – spatially, temporally, or thematically – for understanding Arctic phenomena. These relevant data resources must be ‘found’, and ‘harmonized’ prior to integration and analysis. The findings of a case study indicated that the semantic annotation of measurement data enhances the capabilities of researchers to accomplish these tasks

Gelatinous Zooplankton Biomass In the Global Oceans: Geographic Variation and Environmental Drivers

Aim Scientific debate regarding the future trends, and subsequent ecological, biogeochemical and societal impacts, of gelatinous zooplankton (GZ) in a changing ocean is hampered by lack of a global baseline and an understanding of the causes of biogeographic patterns. We address this by using a new global database of GZ records to test hypotheses relating to environmental drivers of biogeographic variation in the multidecadal baseline of epipelagic GZ biomass in the world\u27s oceans. Location Global oceans. Methods Over 476,000 global GZ data and metadata items were assembled from a variety of published and unpublished sources. From this, a total of 91,765 quantitative abundance data items from 1934 to 2011 were converted to carbon biomass using published biometric equations and species-specific average sizes. Total GZ, Cnidaria, Ctenophora and Chordata (Thaliacea) biomass was mapped into 5° grid cells and environmental drivers of geographic variation were tested using spatial linear models. Results We present JeDI (the Jellyfish Database Initiative), a publically accessible database available at http://jedi.nceas.ucsb.edu. We show that: (1) GZ are present throughout the world\u27s oceans; (2) the global geometric mean and standard deviation of total gelatinous biomass is 0.53 ± 16.16 mg C m−3, corresponding to a global biomass of 38.3 Tg C in the mixed layer of the ocean; (3) biomass of all gelatinous phyla is greatest in the subtropical and boreal Northern Hemisphere; and (4) within the North Atlantic, dissolved oxygen, apparent oxygen utilization and sea surface temperature are the principal drivers of biomass distribution. Main conclusions JeDI is a unique global dataset of GZ taxa which will provide a benchmark against which future observations can be compared and shifting baselines assessed. The presence of GZ throughout the world\u27s oceans and across the complete global spectrum of environmental variables indicates that evolution has delivered a range of species able to adapt to all available ecological niches

Best practices for virtual participation in meetings : experiences from synthesis centers

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The environment ontology in 2016: bridging domains with increased scope, semantic density, and interoperation

Background The Environment Ontology (ENVO; http://www.environmentontology.org/), first described in 2013, is a resource and research target for the semantically controlled description of environmental entities. The ontology's initial aim was the representation of the biomes, environmental features, and environmental materials pertinent to genomic and microbiome-related investigations. However, the need for environmental semantics is common to a multitude of fields, and ENVO's use has steadily grown since its initial description. We have thus expanded, enhanced, and generalised the ontology to support its increasingly diverse applications. Methods We have updated our development suite to promote expressivity, consistency, and speed: we now develop ENVO in the Web Ontology Language (OWL) and employ templating methods to accelerate class creation. We have also taken steps to better align ENVO with the Open Biological and Biomedical Ontologies (OBO) Foundry principles and interoperate with existing OBO ontologies. Further, we applied text-mining approaches to extract habitat information from the Encyclopedia of Life and automatically create experimental habitat classes within ENVO. Results Relative to its state in 2013, ENVO's content, scope, and implementation have been enhanced and much of its existing content revised for improved semantic representation. ENVO now offers representations of habitats, environmental processes, anthropogenic environments, and entities relevant to environmental health initiatives and the global Sustainable Development Agenda for 2030. Several branches of ENVO have been used to incubate and seed new ontologies in previously unrepresented domains such as food and agronomy. The current release version of the ontology, in OWL format, is available at http://purl.obolibrary.org/obo/envo.owl. Conclusions ENVO has been shaped into an ontology which bridges multiple domains including biomedicine, natural and anthropogenic ecology, ‘omics, and socioeconomic development. Through continued interactions with our users and partners, particularly those performing data archiving and sythesis, we anticipate that ENVO’s growth will accelerate in 2017. As always, we invite further contributions and collaboration to advance the semantic representation of the environment, ranging from geographic features and environmental materials, across habitats and ecosystems, to everyday objects in household settings

The bien r package: A tool to access the Botanical Information and Ecology Network (BIEN) database

There is an urgent need for largeâ scale botanical data to improve our understanding of community assembly, coexistence, biogeography, evolution, and many other fundamental biological processes. Understanding these processes is critical for predicting and handling humanâ biodiversity interactions and global change dynamics such as food and energy security, ecosystem services, climate change, and species invasions.The Botanical Information and Ecology Network (BIEN) database comprises an unprecedented wealth of cleaned and standardised botanical data, containing roughly 81 million occurrence records from c. 375,000 species, c. 915,000 trait observations across 28 traits from c. 93,000 species, and coâ occurrence records from 110,000 ecological plots globally, as well as 100,000 range maps and 100 replicated phylogenies (each containing 81,274 species) for New World species. Here, we describe an r package that provides easy access to these data.The bien r package allows users to access the multiple types of data in the BIEN database. Functions in this package query the BIEN database by turning user inputs into optimised PostgreSQL functions. Function names follow a convention designed to make it easy to understand what each function does. We have also developed a protocol for providing customised citations and herbarium acknowledgements for data downloaded through the bien r package.The development of the BIEN database represents a significant achievement in biological data integration, cleaning and standardization. Likewise, the bien r package represents an important tool for open science that makes the BIEN database freely and easily accessible to everyone.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/142458/1/mee312861_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/142458/2/mee312861.pd

Habitat area and climate stability determine geographical variation in plant species range sizes

Despite being a fundamental aspect of biodiversity, little is known about what controls species range sizes. This is especially the case for hyperdiverse organisms such as plants. We use the largest botanical data set assembled to date to quantify geographical variation in range size for ∼ 85 000 plant species across the New World. We assess prominent hypothesised range-size controls, finding that plant range sizes are codetermined by habitat area and long- and short-term climate stability. Strong short- and long-term climate instability in large parts of North America, including past glaciations, are associated with broad-ranged species. In contrast, small habitat areas and a stable climate characterise areas with high concentrations of small-ranged species in the Andes, Central America and the Brazilian Atlantic Rainforest region. The joint roles of area and climate stability strengthen concerns over the potential effects of future climate change and habitat loss on biodiversity