Hypotheses in urban ecology: building a common knowledge base.

Urban ecology is a rapidly growing research field that has to keep pace with the pressing need to tackle the sustainability crisis. As an inherently multi-disciplinary field with close ties to practitioners and administrators, research synthesis and knowledge transfer between those different stakeholders is crucial. Knowledge maps can enhance knowledge transfer and provide orientation to researchers as well as practitioners. A promising option for developing such knowledge maps is to create hypothesis networks, which structure existing hypotheses and aggregate them according to topics and research aims. Combining expert knowledge with information from the literature, we here identify 62 research hypotheses used in urban ecology and link them in such a network. Our network clusters hypotheses into four distinct themes: (i) Urban species traits & evolution, (ii) Urban biotic communities, (iii) Urban habitats and (iv) Urban ecosystems. We discuss the potentials and limitations of this approach. All information is openly provided as part of an extendable Wikidata project, and we invite researchers, practitioners and others interested in urban ecology to contribute additional hypotheses, as well as comment and add to the existing ones. The hypothesis network and Wikidata project form a first step towards a knowledge base for urban ecology, which can be expanded and curated to benefit both practitioners and researchers.

A conceptual map of invasion biology: Integrating hypotheses into a consensus network.

BACKGROUND AND AIMS: Since its emergence in the mid-20th century, invasion biology has matured into a productive research field addressing questions of fundamental and applied importance. Not only has the number of empirical studies increased through time, but also has the number of competing, overlapping and, in some cases, contradictory hypotheses about biological invasions. To make these contradictions and redundancies explicit, and to gain insight into the field's current theoretical structure, we developed and applied a Delphi approach to create a consensus network of 39 existing invasion hypotheses. RESULTS: The resulting network was analysed with a link-clustering algorithm that revealed five concept clusters (resource availability, biotic interaction, propagule, trait and Darwin's clusters) representing complementary areas in the theory of invasion biology. The network also displays hypotheses that link two or more clusters, called connecting hypotheses, which are important in determining network structure. The network indicates hypotheses that are logically linked either positively (77 connections of support) or negatively (that is, they contradict each other; 6 connections). SIGNIFICANCE: The network visually synthesizes how invasion biology's predominant hypotheses are conceptually related to each other, and thus, reveals an emergent structure - a conceptual map - that can serve as a navigation tool for scholars, practitioners and students, both inside and outside of the field of invasion biology, and guide the development of a more coherent foundation of theory. Additionally, the outlined approach can be more widely applied to create a conceptual map for the larger fields of ecology and biogeography.

Identifying overlapping and hierarchical thematic structures in networks of scholarly papers: a comparison of three approaches.

The aim of this paper is to introduce and assess three algorithms for the identification of overlapping thematic structures in networks of papers. We implemented three recently proposed approaches to the identification of overlapping and hierarchical substructures in graphs and applied the corresponding algorithms to a network of 492 information-science papers coupled via their cited sources. The thematic substructures obtained and overlaps produced by the three hierarchical cluster algorithms were compared to a content-based categorisation, which we based on the interpretation of titles, abstracts, and keywords. We defined sets of papers dealing with three topics located on different levels of aggregation: h-index, webometrics, and bibliometrics. We identified these topics with branches in the dendrograms produced by the three cluster algorithms and compared the overlapping topics they detected with one another and with the three predefined paper sets. We discuss the advantages and drawbacks of applying the three approaches to paper networks in research fields.

Collaboration and distances between German immunological institutes--a trend analysis.

BACKGROUND: The hypothesis that distance matters but that in recent years geographical proximity has become less important for research collaboration was tested. We have chosen a sample--authors at German immunological institutes--that is relatively homogeneous with regard to research field, language and culture, which beside distance are other possible factors influencing the willingness to co-operate. We analyse yearly distributions of co-authorship links between institutes and compare them with the yearly distributions of distances of all institutes producing papers in journals indexed in the Science Citation Index, editions 1992 till 2002. We weight both types of distributions properly with paper numbers. RESULTS: One interesting result is that place matters but if a researcher has to leave the home town to find a collaborator distance does not matter any longer. This result holds for all years considered, but is statistically most significant in 2002. The tendency to leave the own town for collaborators has slightly increased in the sample. In addition, yearly productivity distributions of institutes have been found to be lognormal. CONCLUSION: The Internet did not change much the collaboration patterns between German immunological institutes.