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.

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.

Challenges and opportunities of open data in ecology.

Ecology is a synthetic discipline benefiting from open access to data from the earth, life, and social sciences. Technological challenges exist, however, due to the dispersed and heterogeneous nature of these data. Standardization of methods and development of robust metadata can increase data access but are not sufficient. Reproducibility of analyses is also important, and executable workflows are addressing this issue by capturing data provenance. Sociological challenges, including inadequate rewards for sharing data, must also be resolved. The establishment of well-curated, federated data repositories will provide a means to preserve data while promoting attribution and acknowledgement of its use.

Advancing ecological research with ontologies.

Ecology is inherently cross-disciplinary, drawing together many types of information to address questions about the natural world. Finding and integrating relevant data to assist in these analyses is crucial, but is difficult owing to ambiguous terminology and the lack of sufficient information about datasets. Ontologies provide a formal mechanism for defining terms and their relationships, and can improve the location, interpretation and integration of data based on its inherent meaning. Ontologies have assisted other disciplines (e.g. molecular biology) in unifying and enriching descriptions of data, and ecology can benefit from similar approaches. We review ontology efforts in ecology, and describe how these can benefit research by enhancing the location and interpretation of relevant data for confronting crucial ecological questions.

THE COSTS OF CHANGING SEX AND THE ONTOGENY OF MALES UNDER CONTEST COMPETITION FOR MATES.

In its simplest form, the size-advantage hypothesis predicts that individuals should change sex in order to increase their reproductive success. In terms of lifetime expectations, this must be true for the hypothesis to hold. However, as we review here, some loss of reproductive success may occur immediately after sex change. Unavoidable costs (e.g., those resulting from a restructuring of the gonad) have not been adequately distinguished from adaptive allocations of resources which diminish current reproduction in favor of large increases in future mating success. This strategy can become particularly important for species in which a few males monopolize matings. To illustrate this idea, we describe the changes in mating frequency as mature females become sexually active males in three species of protogynous wrasses. In one species, a male defends a permanent, all-purpose territory composed of up to 12 females. When he is removed, a single female changes sex and successfully completes mating sequences with all females in the territory within an average of 5.6 days. This duration roughly corresponds to the time required for functional transformation of gonads; thus, individuals in this species suffer few reproductive losses as a result of changing sex. The largest males in two other species mate with an average of 25 to 50 females per day, but only by successfully defending reproductive territories. In one of those species, individuals that changed sex mated infrequently over a two-year period after sexual transformation and, by the end of the study, were still well below the average size of males that consistently obtained territories. Sex-changed individuals in the other species had very low reproductive success for up to 45% of the maximum lifespan as a male. It is improbable that the substantial cost of changing sex in the latter two species results from gonad restructuring or from mistakes due to imprecise cues for sex change. Instead, the cost appears to represent an investment in growth rather than current reproduction as a means of rapidly attaining a size advantage when individuals face intense competition for extraordinarily successful mating territories.