Geophylogenies – Uniting space and time

Graphic images designed to interrelate evolutionary models and geography have been important in the development and illustration of evolutionary concepts and hypotheses (Hewitt 2001). Images have been particularly important in phylogeography (Avise et al. 1987, Avise 2000) and panbiogeography (Croizat 1958, Craw et al. 1999). The majority of images, with the exception of panbiogeography, have been cartographic in nature in that they are drawn with license with the specific purpose of depicting a particular aspect of the data rather than being directly rendered from the data itself.

Recently there has been move toward direct rendering of visualizations from data using geographical information systems (GIS) (Kidd & Ritchie 2006) and Google Earth™ (Janies et al. 2007).This change has been stimulated by ever increasing data volumes and complexity, the desire for quick and simple data exploration, and a growing interest in integrating evolutionary models with external geographical information to identify and quantify the geographical flow of lineages, selection, niche evolution and population connectivity for conservation planning (Kidd & Ritchie 2006, Storfer et al. 2007). Direct rendering of visualizations from data has the advantage of reflecting current database state, uniform presentation of high numbers of graphic elements and flexible editing; however it may sometimes be difficult to create clear images, e.g. in areas of high data density, as graphical license is restricted.

‘Geophylogenies’ are phylogenetic models transformed into spatial networks through the application of a biogeographical model (Kidd & Liu in press). Geographical coordinates are associated with the nodes and links of the phylogenetic tree; observed tip nodes are associated with coordinates defining where the entity (genotype or species) is observed while internal nodes and branch paths are inferred from a biogeographical model. The simplest biogeographical model is to place inferred nodes at the spatial centroid of observations of the subclade it defines. Alternative historical models could be derived from ecological niche models (Guisan & Zimmerman 2000) or historical biogeographical approaches, e.g DIVA (Ronquist 1997) or LaGrange (Ree et al. 2005).

Example 1: Evolution of the Artiodactyla in Space and Time.

My colleague Sam Price (NESCent) and I recently received third prize in a Visualizing Network Dynamics competition (http://vw.indiana.edu/07netsci/entries/) with a 2D visualization (Figure 1; and see http://vw.indiana.edu/07netsci/entries/#evolution for entire image).

Figure 1.- Geophylogeny of 174 extant species of Artiodactyla (even-toed hoofed mammals) with some ancestral nodes positioned on the basis of fossil evidence. Here the entire geophylogeny is displayed on a polar projection with arrows showing ‘flow’ from geophylogeny root to extant tip species. Red dots are the spatial centroid of extant taxa ranges. The light red dot is the root node (positioned from fossil evidence). Form here the group extensively radiated across the Eurasian and African continents with the exception of arctic and desert ecosystems. A fewer lineages crossed the Bearing strait to radiate in the Americas. Care should be taken interpreting this image as extinct species, e.g. North America camels are fully incorporated.

Example 2: H5N1 Bird Flu virus spread and evolution with Google Maps.

Janies et al.(2007) provide an excellent example using Google Earth™ to trace the global spread and evolution of H1N5 avian influenza. Google Earth™ (http://earth.google.com/) is a freely available platform-independent global desk mapping client with a user friendly interface. The geophylogeny can be displayed in its entirety or by year illuminating temporal change. Terminal nodes are symbolized to indicate organism host to which ‘description boxes’ are attached detaining key amino acid states, surface protein mutations, ancestral and sister nodes and the source of the data. Hyperlinks directly link to the corresponding GenBank record. Branches are colour coded to indicate genotype or host vector and also have linked description boxes detailing inferred mutational change along the branch. The model is downloadable from Systematic Biology online (aiTrees.kmz from http://systbio.org/?q=node/184).

Figure 2. H5N1 Bird Flu phylogeny with branches colour-coded to indicate dispersal vector overlaid onto population density.

Resources

For other examples and methodological details:

http://evoviz.org/GeoPhyloBuilder. Includes ‘Geophylobuilder – The Movie’ a short animated video of geophylogenies.

http://evoviz.org/GoogleEarth

http://iphylo.blogspot.com/2007/06/earth-not-flat-official.html

http://iphylo.blogspot.com/2007/06/google-earth-phylogenies.html

Creating geophylogenies:

GeoPhyloBuilder for ArcGIS. ARC Geodatabases, shapefiles and KML for Google Earth (needs Arc license), http://www.nescent.org/informatics/software.php

CIPRES Experimental Google Earth Phylogenetic Tree Server. Bill Piel’s (Yale) Internet service that builds geophylogenies in KML for display in Google Earth, http://www.treebase.org/getrees/

Pie Charts on Google Earth:

Phylogeoviz Yi-Hsin Erica Tsai’s (Duke University) Internet service that puts pie charts on Google Earth, http://www.phylogeoviz.org/

Workshop:

A ‘Visualizing Evolution in Space and Time’ workshop is planned for the 4^th International Biogeography Society Meeting, Mérida, Mexico, January 2009.

David Michael Kidd, National Evolutionary Synthesis Center (NESCent), Durham. North Carolina, USA.

References

Avise, J.C. (2000) Phylogeography Harvard University Press, Cambridge, Massachusetts.

Avise, J.C., Arnold, J., Ball, R.A., Bermingham, E., Lamb, T., Neigel, J.E., Reeb, C.A. & Saunders, N.C. (1987) Intraspecific phylogeography: the mitochondrial DNA bridge between population genetics and systematics. Annual Review of Ecology and Systematics, 18, 489-522.

Craw, R.C., Grehan, J.R. & Heads, M.J. (1999) Panbiogeography: Tracking the History of Life. Oxford University Press.

Croizat, L. (1958) Panbiogeography. Published by the Author, Caracas.

Guisan, A. & Zimmerman, N.E. (2000) Predictive habitat distribution modelling in ecology. Ecological Modelling, 135, 147-86.

Hewitt, G.M. (2001) Speciation, hybrid zones and phylogeography - or seeing genes in space and time. Molecular Ecology, 10, 537-49.

Janies, D., Hill, A.W., Guralnick, R., Habib, F., Waltari, E. & Wheeler, W.C. (2007). Genomic Analysis and Geographic Visualization of the Spread of Avian Influenza (H5N1). Systematic Biology, 56, 321 - 29.

Kidd, D.M. & Ritchie, M.G. (2006) Phylogeographic information systems; Putting the geography into phylogeography. Journal of Biogeography, 33, 1851-65.

Kidd, D.M. & Liu, X. (in press) GEOPHYLOBUILDER 1.0: an ArcGIS extension for creating 'geophylogenies'. Molecular Ecology Notes.

Ree, R., Moore, B.R., Webb, C.O. & Donoghue, M.J. (2005) A liklihood framework for inferring the evolution of geographic range on phlyogenetic trees. Evolution, 59(11), 2299-311.

Ronquist, F. (1997) Dispersal-vicariance analysis: a new approach to the quantification of historical biogeography. Systematic Biology, 46(1), 195-203.

Storfer, A., Murphy, M.A., Evans, J.S., Goldberg, C.S., Robinson, S., Spear, S.F., Dezzani, R., Delmelle, E., Vierling, L. & Waits, L.P. (2007) Putting the ‘landscape’ in landscape genetics. Heredity, 98(3), 128-42.