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S-DIVA (Statistical Dispersal-Vicariance Analysis): A tool for inferring
biogeographic histories
Article in Molecular Phylogenetics and Evolution · August 2010
DOI: 10.1016/j.ympev.2010.04.011 · Source: PubMed
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Molecular Phylogenetics and Evolution 56 (2010) 848–850
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journal homepage: www.elsevier.com/locate/ympev
Short Communication
S-DIVA (Statistical Dispersal-Vicariance Analysis): A tool for inferring
biogeographic histories
Yan Yu a, A.J. Harris b, Xingjin He a,*
a
b
College of Life Sciences, Sichuan University, Chengdu 610064, China
Curriculum for the Environment and Ecology, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
a r t i c l e
i n f o
Article history:
Received 4 December 2009
Revised 10 March 2010
Accepted 6 April 2010
Available online 22 April 2010
Keywords:
DIVA
Biogeographic
Program
Phylogeny
Statistics
a b s t r a c t
Dispersal-Vicariance Analysis (DIVA) is one of the most widely used methods of inferring biogeographic
histories. Here we present a simple tool that complements DIVA and uses a Statistical Dispersal-Vicariance Analysis (S-DIVA) to statistically evaluate the alternative ancestral ranges at each node in a tree
accounting for phylogenetic uncertainty and uncertainty in DIVA optimization. S-DIVA provides a
point-and-click user interface and displays results as, high-resolution, exportable graphics. S-DIVA is
freely available for download for Windows at http://mnh.scu.edu.cn/S-DIVA.
Ó 2010 Elsevier Inc. All rights reserved.
1. Introduction
Studies in historical biogeography based on phylogeny have
accumulated rapidly in the literature due to the exponential increase in phylogenetic studies (see Xiang et al., 1998, 2004, 2005,
2006; Wen, 1999; Sanmartín et al., 2001; Donoghue and Smith,
2004; Sanmartín and Ronquist, 2004; Soltis et al., 2006; Harris
et al., 2009; Alexandre et al., 2009). Dispersal-Vicariance Analysis
(DIVA) (Ronquist, 1997, 2001) is one of the most widely used
methods of inferring biogeographic histories. This is evidenced
by an advanced Google scholar search for ‘‘DIVA” and ‘‘biogeography” in 2009 returning greater than 50 relevant results. DIVA
reconstructs the ancestral distribution in a phylogeny by optimizing a three-dimensional cost matrix, in which extinctions and dispersals ‘‘cost” more than vicariance (Ronquist, 1997; Lamm and
Redelings, 2009). Although model-based methods for inferring biogeography are available (e.g., Ree et al., 2005; Ree and Smith, 2008;
Sanmartín et al., 2008), DIVA remains popular because it provides
rapid results, requires little prior information, and gives results
comparable to the model-based likelihood method Lagrange of
Ree et al. (2005) and Ree and Smith (2008) (e.g., Ree et al., 2005;
Burbrink and Lawson, 2007; Ree and Smith, 2008; Velazco and
Patterson, 2008; Xiang et al., 2008; Xiang et al., 2009).
One problem with the current implementation of DIVA is that it
ignores the uncertainty in phylogenetic inference because ancestral
ranges are reconstructed onto a fixed tree topology assumed to be
* Corresponding author. Fax: +86 02885415006.
E-mail address: xjhe@scu.edu.cn (X. He).
1055-7903/$ - see front matter Ó 2010 Elsevier Inc. All rights reserved.
doi:10.1016/j.ympev.2010.04.011
without error (Nylander et al., 2008). A second source of uncertainty
in DIVA is that associated with ancestral area optimization; multiple
equally optimal reconstructions often result in multiple ranges suggested at ancestral nodes (Ronquist, 1997; Nylander et al., 2008).
To account for these uncertainties, Nylander et al. (2008) recently
showed the utility of a non-parametric empirical Bayesian approach
to DIVA. Their approach handles phylogenetic uncertainty and
uncertainty in DIVA optimization. Harris and Xiang (2009) proposed
an alternative approach to Bayes-DIVA, which differs in its ability to
handle uncertainty at some nodes.
We have written Statistical Dispersal-Vicariance Analysis (SDIVA), a program which complements DIVA, implements the methods of Nylander et al. (2008) and Harris and Xiang (2009), and determines statistical support for ancestral range reconstructions using a
novel method, the S-DIVA value. In S-DIVA, the frequencies of an
ancestral range at a node in ancestral reconstructions are averaged
over all trees and each alternative ancestral range at a node is
weighted by the frequency of the node occurring or by some other
measure of support for the node. S-DIVA is easy-to-install, provides
a user-friendly graphical interface, and generates exportable, graphical results (Fig. 1a and b).
2. Description
2.1. Program features
The S-DIVA program requires a set of trees from phylogenetic
analysis (a ‘‘trees file”), a final representative tree, and range infor-
Author's personal copy
Y. Yu et al. / Molecular Phylogenetics and Evolution 56 (2010) 848–850
849
Fig. 1. Graphical output from S-DIVA. (a) Graphical results of ancestral distributions for simulated phylogeny with 9 species and 3 areas. A, B and C are ranges of terminals. Pie
charts at nodes show probabilities of alternative ancestral ranges; (b) Alternative ancestral ranges of the node of ((4, 9), 2) displayed as a pie chart and bar charts by S-DIVA.
The node of terminals 2, 4 and 9 has two possible ancestral ranges ‘‘AB or BC”, the occurrence of each range is AB: 60%, BC: 40%. Probability of this result may be interpreted as
100% since the frequency of occurrence of the node (pn) is 100%; (c–g) Five optimal reconstructions resulting in probabilities in a and b. Numbered nodes (roman numerals)
correspond to those in Table 1. Note that node numbers are not part of the S-DIVA output.
mation for terminal taxa. Tree file formats generated by the programs BEAST (Drummond and Rambaut, 2006), PAUP* (Swofford,
2003) and MrBayes (Huelsenbeck and Ronquist, 2003) are currently
supported by S-DIVA. Range information may be loaded as a comma
separated values file or entered directly into S-DIVA through the user
interface. S-DIVA allows users a variety of options, which customize
analyses for individual needs. Dispersal-Vicariance Analyses in
S-DIVA are performed by DIVA 1.2 (Ronquist, 2001).
In an S-DIVA analysis with default settings, ancestral reconstructions are performed using DIVA 1.2 for all trees in the trees
file. The probability (p) of an ancestral range x at node n on the final
P
tree is calculated as pðxn Þ ¼ m
t¼1 Fðxn Þt pn where t is the selected
tree, m is the total number of sampled trees, F(xn)t is the occurrence
of an ancestral range x at node n for tree t, and pn is the support for
the node. F(xn)t is calculated as the actual frequency of x within the
pool of ancestral range reconstructions (Harris and Xiang, 2009):
Fðxn Þ ¼ i=Dt . The value i is the number of times the range x occurs
in the total number of alternative reconstructions D at node n in
Pm
tree t. S-DIVA output includes
t¼1 Fðxn Þ and the frequency of
occurrence of each node of the final tree in the sample of trees.
The latter may be interpreted as pn or an estimate of pn and can
P
thus be multiplied by m
t¼1 Fðxn Þ to determine p(xn). Alternatively,
other means, independent of S-DIVA, may be used to determine
pn. Default settings in S-DIVA generally implement the Bayes-DIVA
method described by Nylander et al. (2008) except that i/Dt is used
to calculate F(xn) and trees from sources other than Bayesian analysis are allowed (e.g., Micó et al., 2009).
The S-DIVA value, SV, of an optimal reconstruction of the final
P
tree, is calculated as SV ¼ c1
n¼1 Pðxn Þ, where c is the total number
of terminal taxa and c 1 is the total number of nodes. The higher
the S-DIVA value the greater the probability of a reconstruction
(Fig. 1a–g, Table 1).
The graphical output of S-DIVA (Fig. 1a and b) is designed for easy
visualization and navigation of results with displays for the final tree,
each node, and each optimal reconstruction. Graphics are high resolution and may be browsed on-screen or exported as .jpg or .png files.
Other options in S-DIVA include:
1. Perform biogeographic analysis for a user-specified lineage with
an undefined sister group as in the method of Harris and Xiang
(2009) and as an alternative to the Nylander et al. (2008)
method.
2. Estimate the probability of optimal ancestral ranges at a single,
user-specified node.
3. Add distribution information for an omitted taxon at a userspecified node.
4. Limit analysis to a random sample of trees from the trees file.
5. Exclude the first specified number of trees in the trees file from
analysis by setting a burn-in.
6. Apply DIVA options in S-DIVA through graphical user interface
and command line formats.
S-DIVA has been tested using the simulated dataset of 100 randomly sampled trees from Harris and Xiang (2009). Harris and
Xiang (2009) used these trees to estimate the biogeographic histories of four lineages using the Bayes-DIVA method of Nylander
et al. (2008) and their own method. Results obtained from S-DIVA
were identical to those reported from manual calculations by Harris and Xiang (2009) except for several slight differences observed
beyond the second significant digit to the right of the decimal.
These differences are probably explained entirely by the greater
precision of S-DIVA calculations compared to the manual method
of Harris and Xiang (2009) using Microsoft Excel.
2.2. Implementation details
The main routine in S-DIVA is written in VB.net and uses the
program DIVA 1.2 for handling DIVA analysis. The S-DIVA web site
Author's personal copy
850
Y. Yu et al. / Molecular Phylogenetics and Evolution 56 (2010) 848–850
Table 1
Table for optimal reconstructions in Fig. 1c–g.
I
II
III
IV
V
VI
VII
VIII
SV
1 (Fig. 1c)
Range (x)
V(n)
AB
100
AC
100
AB
60
B
80
AB
80
AC
60
A
60
AC
60
–
600
2 (Fig. 1d)
Range (x)
V(n)
AB
100
AC
100
AB
60
B
80
AB
80
BC
40
B
40
BC
40
–
540
3 (Fig. 1e)
Range (x)
V(n)
AB
100
AC
100
AB
60
AB
20
A
20
AC
60
A
60
AC
60
–
480
4 (Fig. 1f)
Range (x)
V(n)
AB
100
AC
100
BC
40
B
80
AB
80
AC
60
A
60
AC
60
–
580
5 (Fig. 1g)
Range (x)
V(n)
AB
100
AC
100
BC
40
B
80
AB
80
BC
40
B
40
BC
40
–
520
Calculations of P(xn) assume that pn for all nodes is equal to 1.0.
gives a detailed example illustrating how to use the program.
Example files and a user’s manual are provided with the S-DIVA
download. A web server is available for running S-DIVA analyses
and can be accessed at http://mnh.scu.edu.cn/sdiva_web. The online version of the program offers a full user interface and makes
the software accessible to MAC and Linux users. The S-DIVA web
service is still in beta and we recommend the offline version of
S-DIVA. We are continually working to improve S-DIVA’s functionality and usability. Our next objective is for S-DIVA to handle trees
with polytomies.
Acknowledgments
The authors would like to thank Dr. Jenny Xiang (North Carolina
State University) for her helpful comments and Dr. Johan Nylander
(Stockholm University, Sweden), Dr. Xiaoguo Xiang and Dr. Qiang
Zhang (Institute of Botany, Chinese Academy of Sciences, China)
for testing the software.
Funding: This work was supported by grants from the National
Natural Science Foundation of China (Grant No. 30670146), the
National Infrastructure of Natural Resources for Science and
Technology (Grant No. 2005DKA21403), the Research Fund for
the Large-scale Scientific Facilities of the Chinese Academy of Sciences (Grant No. 2009-LSF-GBOWS-01) and Technology Innovation
Team Programs of Inner Mongolia Agricultural University (Grant
No. NDTD201011).
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