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Modeling is an important aspect of scientific problem-solving. However, modeling is a difficult cognitive process for novice learners in part due to the high dimensionality of the parameter search space. This work investigates 50 college students’ parameter search behaviors in the context of ecological modeling. The study revealed important differences in behaviors of successful and unsuccessful students in navigating the parameter space. These differences suggest opportunities for future development of adaptive cognitive scaffolds to support different classes of learners.

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.

The citizen Continental-America Telescopic Eclipse (CATE) Experiment was a new type of citizen science experiment designed to capture a time sequence of white-light coronal observations during totality from 17:16 to 18:48 UT on 2017 August 21. Using identical instruments the CATE group imaged the inner corona from 1 to 2.1 RSun with 1.″43 pixels at a cadence of 2.1 s. A slow coronal mass ejection (CME) started on the SW limb of the Sun before the total eclipse began. An analysis of CATE data from 17:22 to 17:39 UT maps the spatial distribution of coronal flow velocities from about 1.2 to 2.1 RSun, and shows the CME material accelerates from about 0 to 200 km s−1 across this part of the corona. This CME is observed by LASCO C2 at 3.1–13 RSun with a constant speed of 254 km s−1. The CATE and LASCO observations are not fit by either constant acceleration nor spatially uniform velocity change, and so the CME acceleration mechanism must produce variable acceleration in this region of the corona.

The Encyclopedia of Life currently hosts ~8M attribute records for ~400k taxa (March 2019, not including geographic categories, Fig. 1). Our aggregation priorities include Essential Biodiversity Variables (Kissling et al. 2018) and other global scale research data priorities. Our primary strategy remains partnership with specialist open data aggregators; we are also developing tools for the deployment of evolutionarily conserved attribute values that scale quickly for global taxonomic coverage, for instance: tissue mineralization type (aragonite, calcite, silica...); trophic guild in certain clades; sensory modalities. To support the aggregation and integration of trait information, data sets should be well structured, properly annotated and free of licensing or contractual restrictions so that they are ‘findable, accessible, interoperable, and reusable’ for both humans and machines (FAIR principles; Wilkinson et al. 2016). To this end, we are improving the documentation of protocols for the transformation, curation, and analysis of EOL data, and associated scripts and software are made available to ensure reproducibility. Proper acknowledgement of contributors and tracking of credit through derived data products promote both open data sharing and the use of aggregated resources. By exposing unique identifiers for data products, people, and institutions, data providers and aggregators can stimulate the development of automated solutions for the creation of contribution metrics. Since different aspects of provenance will be significant depending on the intended data use, better standardization of contributor roles (e.g., author, compiler, publisher, funder) is needed, as well as more detailed attribution guidance for data users. Global scale biodiversity data resources should resolve into a graph, linking taxa, specimens, occurrences, attributes, localities, and ecological interactions, as well as human agents, publications and institutions. Two key data categories for ensuring rich connectivity in the graph will be taxonomic and trait data. This graph can be supported by existing data hubs, if they share identifiers and/or create mappings between them, using standards and sharing practices developed by the biodiversity data community. Versioned archives of the combined graph could be published at intervals to appropriate open data repositories, and open source tools and training provided for researchers to access the combined graph of biodiversity knowledge from all sources. To achieve this, good communication among data hubs will be needed. We will need to share information about preferred vocabularies and identifier management practices, and collaborate on identifier mappings.

Encyclopedia of Life (EOL) has developed TraitBank (http://eol.org/traitbank), a new repository for organism attribute (trait) data. TraitBank aggregates, manages and serves attribute data for organisms across the tree of life, including life history characteristics, habitats, distributions, ecological relationships and other data types. We describe how TraitBank ingests and manages these data in a way that leverages EOL's existing infrastructure and semantic annotations to facilitate reasoning across the TraitBank corpus and interoperability with other resources. We also discuss TraitBank's impact on users and collaborators and the challenges and benefits of our lightweight, scalable approach to the integration of biodiversity data.

In the version of this Perspective originally published, the first author of reference 39 was incorrectly listed as W. Cornwell and the publication year was incorrect. The reference should have read as follows: “Flores-Moreno, H. et al. fungaltraits aka funfun: a dynamic functional trait database for the world's fungi (GitHub, 2019); https://doi.org/10.5281/zenodo.1216257”. This has now been corrected.

Citizen scientists have the potential to expand scientific research. The virtual research assistant called VERA empowers citizen scientists to engage in environmental science in two ways. First, it automatically generates simulations based on the conceptual models of ecological phenomena for repeated testing and feedback. Second, it leverages the Encyclopedia of Life biodiversity knowledgebase to support the process of model construction and revision.

The size of biodiversity data sets, and the size of people's questions around them, are outgrowing the capabilities of desktop applications, single computers, and single developers. Numerous articles in the corporate sector (Delgado 2016) have been written on how much time professionals spend manipulating and formatting large data sets compared to the time they spend on the important work of doing analysis and modeling. To efficiently move large research questions forward, the biodiversity domain needs to transition towards shared infrastructure with the goal of providing a mise en place for researchers to do research with large data. The GUODA (Global Unified Open Data Access) collaboration was formed to explore tools and use cases for this type of collaborative work on entire biodiversity data sets. Three key parts of that exploration have been: the software and hardware infrastructure needed to be able to work with hundreds of millions of records and terabytes of data quickly, removing the impediment of data formatting and preparation, and workflows centered around GitHub for interacting with peers in an open and collaborative manner. We will describe our experiences building an infrastructure based on Apache Mesos, Apache Spark, HDFS, Jupyter Notebooks, Jenkins, and Github. We will also enumerate what resources are needed to do things like join millions of records, visualize patterns in whole data sets like iDigBio and the Biodiversity Heritage Library, build graph structures of billions of nodes, analyze terabytes of images, and use natural language processing to explore gigabytes of text. In addition to the hardware and software, we will describe the kinds of skills needed by staff to design, build, and use this sort of infrastructure and highlight some experiences we have with training students. Our infrastructure is one of many that are possible. We hope that by showing the amount and type of work we have done to the wider community, other organizations can understand what they would need to speed up their research programs by developing their own collaborative computation and development environments.

Previous CSCW studies on citizen science have focused on supporting data collection, rather than data sharing among a wider audience. Here we describe the process by which citizen science data are collaboratively shared by individual and organizational social actors. Three sets of collabora-tive efforts are essential for enabling data to travel through the online environments: creating shareable data, assuring data quality, and setting up data sharing partnerships.

The Biodiversity Heritage Library is the world’s largest digital library of biodiversity literature. Currently containing almost 40 million pages, the library can be explored with a search interface employing keyword-matching, which unfortunately fails to address issues brought about by ambiguity. Helping alleviate these issues are tools that automatically attach semantic metadata to documents, e.g., biodiversity concept recognisers. However, gold standard, semantically annotated textual corpora are critical for the development of these advanced tools. In the biodiversity domain, such corpora are almost non-existent especially since the construction of semantically annotated resources is typically a time-consuming and laborious process. Aiming to accelerate the development of a corpus of biodiversity documents, we propose a text mining framework that hastens curation through an iterative feedback-loop process of (1) manual annotation, and (2) training and application of statistical concept recognition models. Even after only a few iterations, our curators were observed to have spent less time and effort on annotation.

Mass strandings of beaked whales (family Ziphiidae) have been reported in the scientific literature since 1874. Several recent mass strandings of beaked whales have been reported to coincide with naval active sonar exercises. To obtain the broadest assessment of surface ship naval active sonar operations coinciding with beaked whale mass strandings, a list of global naval training and antisubmarine warfare exercises was compiled from openly available sources and compared by location and time with historic stranding records. This list includes activities of navies of other nations but emphasizes recent U.S. activities because of what is available in publicly accessible sources. Of 136 beaked whale mass stranding events reported from 1874 to 2004, 126 occurred between 1950 and 2004, after the introduction and implementation of modern, high-power mid-frequency active sonar (MFAS). Of these 126 reports, only two reported details on the use, timing, and location of sonar in relation to mass strandings. Ten other mass strandings coincided in space and time with naval exercises that may have included MFAS. An additional 27 mass stranding events occurred near a naval base or ship but with no direct evidence of sonar use. The remaining 87 mass strandings have no evidence for a link with any naval activity. Six of these 87 cases have evidence for a cause unrelated to active sonar. The large number of global naval activities annually with potential MFAS usage in comparison to the relative rarity of mass stranding events suggests that most MFAS operations take place with no reported stranding events and that for an MFAS operation to cause a mass stranding of beaked whales, a confluence of several risk factors is probably required. Identification of these risk factors will help in the development of measures to reduce the risk of sonar-related strandings.

The tropical root weevil Diaprepes abbreviatus (L. 1758) (Coleoptera: Curculionidae) is a polyphagous insect from the Caribbean Islands and an invasive insect in the southern part of the United States where it is pest of citrus crops and ornamental trees. Adults feed upon foliage where aggregation, mating and oviposition take place. Here, the headspace volatiles from Citrus macrophylla Wester (Rutaceae), D. abbreviatus adults feeding on this plant, adults alone and adult feces, were collected by aeration and solid-phase microextraction (SPME) for analysis by gas chromatography-linked mass spectrometry (GC-MS). Electrophysiological responses of weevil antennal receptors to volatile headspace extracts and synthetic analogues were recorded by gas chromatography-linked electroantennographic detection (GC-EAD) and electroantennograms (EAGs). Antennal responses were recorded to the monoterpenes (R)-(−)-linalool, citronellal, nerol, citral, and geraniol; all present in the headspace of C. macrophylla. Antennal responses were also recorded to carvacrol, present in the headspace of adults and adult feces. The green leaf volatiles cis-3-hexen-1-ol and trans-2-hexen-1-ol, produced by other host plants, elicited reliable responses on the D. abbreviatus antenna. When comparing EAGs between (±)-linalool and (R)-(−)-linalool, no significant difference was found; responses to (R)-(+)-citronellal were larger than for (S)-(−)-citronellal. Among the individual compounds and blends tested using an open T-track dual choice olfactometer, only the blend of (±)-linalool, cis-3-hexen-1-ol and carvacrol (source dose 25:25:2.5 μg) elicited significant attraction of females, the same blend was repellent for males. The biologically active compounds found here likely play a role in host finding by D. abbreviatus and other interactions of the insect with its hostplant.

Using a servosphere (locomotion compensator), locomotory behavior of Colorado potato beetle Leptinotarsa decemlineata Say (Coleoptera: Chrysomelidae) larvae was measured in detail in response to pulsed and non-pulsed odors of hostplant and conspecific pheromone. Second instars showed decreased straightness of movement, and all larvae showed decreased speed, in response to potato odor. Change in straightness by 2nd instars was also significantly affected by the interaction of pheromone and pulsing treatments. Fourth instars showed increased positive anemotaxis in response to the combined hostplant and pheromone odors. To our knowledge, this is the first demonstration of larval behavioral responses to adult pheromone in a holometabolous insect.

Biodiversity data are well-indexed by taxonomic names. While names reconciliation remains a challenge, there has been tremendous progress in recent years, and integration with available phylogenetic information can support sophisticated analyses for evolutionary questions. However, organisms are also linked to each other by relationships of ecology, geographic proximity, shared habitat, management categories, and other attributes, not yet recorded in a well-structured way. These data are best modeled as a graph, which makes these relationships explicit, and available for reasoning across - just like taxonomic relationships. This would support broad analyses of life on Earth not only from an evolutionary perspective but also across many other axes. This case study will describe how several categories of data are being modeled in the Encyclopedia of Life (EOL) v3 using ontology terms. It will focus on several areas where we anticipate sufficient taxonomic coverage to underlie significant search and analytical power: habitat, distribution, body size and metabolism, and provenance. Habitat and distribution terms are good examples of data terms in well structured hierarchies that could support powerful search. Habitat terms are available from and hierarchically organized in the Environment Ontology (ENVO). Geographic distribution knowledge can often be structured by geographic terms based on verbatim locality text when geocoordinates are not available. Geographic terms are available from several providers, notably Geonames (geonames.org), Marineregions.org and Wikidata. Both habitat and distribution terms can also be connected to simpler and less formalized but commonly used hierarchies like the World Wildlife Fund (WWF) Ecoregions. The hierarchy information made available for habitat and geography by the semantic structure of these ontologies supports searches like "wetland plants of South America," which requires the intersection of taxonomic, geographic, and habitat hierarchies. Body size and metabolism traits interact in a particular use case, illustrating the importance of precision of categorical data terms for informing calculations of quantitative traits. The use case EOL is currently working to support is the parameterization of food web interactions in ecological modelling software. Default or starting values are needed for the content of energy (or carbon) within an organism, and the rate of loss thereof through metabolism. This, plus assimilation efficiency, allows the modeling of carbon flow through the food web. Traits available for estimating carbon content and metabolic rate include various measures of body size, for which conversion factors and formulae are available. For phytoplankton, for instance, size may be reported as cell dimensions, cell volume, cell wet mass, cell dry mass, and/or carbon biomass. For an automated tool to derive parameters from these which are fit for use, the different types of data must all be findable, but the measurement types must be distinguished from one another so the correct conversions are performed for each - all in a machine readable way, so the process can be automated. The need for semantically structured data terms in this case is different, but just as critical to the success of the use case. Future work: Other important structured connections can be made through provenance metadata. These connect taxa and specimens to literature, authors, collectors, wildlife observers and other agents. The Social Media of biodiversity data, rendered explicit, could increase connectivity and communication in the global community - particularly benefitting young researchers in isolated regions without the benefit of professional travel or literature subscriptions. To accomplish this, we must leverage human identifiers such as those made available by Open Researcher And Contributor ID (ORCID) and Wikidata.

Summary: The association of organisms to their environments is a key issue in exploring biodiversity patterns. This knowledge has traditionally been scattered, but textual descriptions of taxa and their habitats are now being consolidated in centralized resources. However, structured annotations are needed to facilitate large-scale analyses. Therefore, we developed ENVIRONMENTS, a fast dictionary-based tagger capable of identifying Environment Ontology (ENVO) terms in text. We evaluate the accuracy of the tagger on a new manually curated corpus of 600 Encyclopedia of Life (EOL) species pages. We use the tagger to associate taxa with environments by tagging EOL text content monthly, and integrate the results into the EOL to disseminate them to a broad audience of users. Availability and implementation: The software and the corpus are available under the open-source BSD and the CC-BY-NC-SA 3.0 licenses, respectively, at http://environments.hcmr.gr Contact: pafilis@hcmr.gr or lars.juhl.jensen@cpr.ku.dk Supplementary information: Supplementary data are available at Bioinformatics online.

Social network visualization is useful for understanding the complex structure of collaborative efforts such as citizen science projects. It has been widely accepted by social network analysts for exploring and analyzing networks by visually showing their members, the relationships among them, and their behaviors and attributes. The strength of social network visualization can be increased even further, by incorporating the time dimension of evolving networks. We analyzed the conversation network of a collaborative citizen science web platform called the Encyclopedia of Life using dynamic network visualization methods. This paper shows how the temporal visualization was applied to the social collaboration analysis of EOL and presents the findings. We found that some EOL web site features increased the interactive as well as individual member activities. We also found evidence that EOL curator activities encouraged the activities of other members.

In this thesis, the relationships of olfactory sensitivity to three biological variables were tested. The sensitivity of a marine mammal, the sea otter (Enhydra lutris) was measured in order to determine whether a marine lifestyle results in impaired olfaction. The effect of dietary relevance on sensitivity to specific odorants was evaluated. Finally, a new morphometric model of olfactory uptake efficiency was developed and tested against behavioral measurements of olfactory sensitivity in twelve mammalian species from five orders. Olfactory thresholds were obtained for the first time from two sea otters for seven odorant compounds from various natural sources. Otters were trained using operant conditioning to participate in direct behavioral testing. Sea otter olfactory sensitivity was comparable to that of previously studied terrestrial mammals. The incidence of an odorant in the diet of the olfactor was found to influence specific sensitivity to that compound but to varying degrees among different mammalian orders. Nasal cavity specimens were measured using radiologic (CT scan) and histologic (light microscopy) techniques. Surface areas and volumes of the nasal cavity were used to calculate the Olfactory Uptake Efficiency (OUE). OUE is significantly related to olfactory bulb volume. A possible relationship was found between OUE and general olfactory sensitivity.