Integration of speciation research (IOS)

Speciation research has progressed mainly through the accumulation of individual case studies, many of which focused on a few model systems. Although this has led to significant insights, we still lack a broad comparative framework that could inform us about general patterns and processes underlying speciation. Yet, classic work, including for example Coyne & Orr studies of Drosophila, clearly demonstrates the potential value of synthesizing information across studies.

Speciation involves the evolution of reproductive isolation (RI) through the accumulation of barriers to gene exchange. Evolutionary processes like natural selection and drift (including mutation order effects) can lead to the evolution of extrinsic (environment-dependent) and intrinsic barriers. Although these processes and barrier types have been identified in individual taxa, a general picture of their relative importance and timing of appearance is lacking. Similarly, much effort has been dedicated in individual systems to map genomic regions containing barrier loci with genomic techniques (e.g. genome scans). However, to compare genetic architectures across studies, we need to acknowledge the technical issues with genome scans and identify best practices for comparative analyses. Finally, there is a pressing need for a unifying framework across scales that allows us to understand how population-level processes shape macroevolutionary patterns of diversity at broader taxonomic and spatial scales.

Aims of IOS:

Since many speciation studies have now been conducted in non-model organisms, the time is ripe for a synthesis. The broad aim of IOS is to move speciation research towards making greater use of systematic and comparative analyses across studies and systems. IOS has four objectives that focus on areas of active speciation research:
i) To understand the relative importance of different barriers to gene flow and outline best practices to measure them.
ii) To survey the role of interactions and coupling between barriers in increasing RI.
iii) To seek common genomic patterns underlying barriers as RI increases.
iv) To bridge the knowledge gap between what is known of speciation mechanisms at a microevolutionary scale and the knowledge of speciation rates & their determinants at a macroevolutionary scale.

IOS will promote a framework for integrative speciation research and develop tools for comparative analyses. We will outline best practices for data generation and analysis (such as consistent methods for quantification of reproductive isolation), encourage data sharing, and perform comparative analyses of existing speciation studies from across the tree of life. To this end, we will set up a speciation database. This can be used for comparative speciation studies and will consist of data on components of RI. We also plan to organize workshops and run a regular online seminar discussion. Contributions to society journals are planned (e.g. a publication on data standards in speciation research and a Special Issue drawing together synthetic analyses and comparative work).

For more information contact:

Twitter: @Speciation_net

Committee Chairs:

Jonna Kulmuni, Organismal and Evolutionary Biology, University of Helsinki, Finland.
Chris Cooney, Ecology and Evolutionary Biology, School of Biosciences, Sheffield, UK.
Sean Stankowski, Institute of Science and Technology (IST), Austria.
Carole Smadja, CNRS, Institut des Sciences de l’Evolution de Montpellier (ISEM), France.

Organizing committee:

Nick Barton (Treasurer), Institute of Science and Technology (IST), Austria.
Sonal Singhal (Diversity and inclusion officer), Department of Biology, CSU Dominguez Hills, USA.
Roger Butlin, Ecology and Evolutionary Biology, School of Biosciences, Sheffield, UK, and Department of Marine Sciences, University of Gothenburg, Sweden.
Joana Meier, Department of Zoology, University of Cambridge, UK.
Richard Merrill, Division of Evolutionary Biology, Faculty of Biology, LMU, Munich, Germany.
Konrad Lohse, Institute of Evolutionary Biology, University of Edinburgh, UK.
Liz Scordato, Department of Biological Sciences, California State Polytechnic University, Pomona, CA, USA.