PHYLOGENETIC CONSERVATISM IN PLANT PHENOLOGY
T. Jonathan Davies1*, Elizabeth M. Wolkovich2, Nathan J. B. Kraft3, Nicolas Salamin4,5, Jenica
M. Allen6, Toby R. Ault7, Julio L. Betancourt8, Kjell Bolmgren9,10, Elsa E. Cleland11, Benjamin
I. Cook12, 13, Theresa M. Crimmins14, Susan J. Mazer15, Gregory J. McCabe16, Stephanie Pau17,
Jim Regetz17, Mark D. Schwartz18, & Steven Travers19.
1
Department of Biology, McGill University, Montreal, QC, Canada
Biodiversity Research Centre, University of British Columbia, Vancouver, BC, Canada
3
Department of Biology, University of Maryland, College Park, MD, 20742 , USA
4
Department of Ecology and Evolution, University of Lausanne, Lausanne, Switzerland
5
Swiss Institute of Bioinformatics, Quartier Sorge, 1015 Lausanne, Switzerland
6
Department of Ecology & Evolutionary Biology, University of Connecticut, Storrs, CT 06269
USA
7
National Center for Atmospheric Research, Boulder, Colorado
8
U.S. Geological Survey, Reston, VA
9
Theoretical Population Ecology and Evolution, Lund University, Lund, Sweden
10
Swedish University of Agricultural Sciences, Swedish National Phenology Network, Sweden
11
Ecology, Behavior & Evolution Section, University of California San Diego, La Jolla, CA
92103 USA
12
NASA Goddard Institute for Space Studies, New York, New York
13
Ocean and Climate Physics, Lamont-Doherty Earth Observatory, Palisades, New York
14
USA National Phenology Network, Tucson, Arizona
15
Department of Ecology, Evolution and Marine Biology, University of California – Santa
Barbara, Santa Barbara, California
16
U.S. Geological Survey, Denver, Colorado
17
National Center for Ecological Analysis and Synthesis, Santa Barbara, California
18
Department of Geography, University of Wisconsin-Milwaukee, Milwaukee, Wisconsin
19
Department of Biological Sciences, North Dakota State University, Fargo, North Dakota
2
Supporting Information: Construction of phylogeny from molecular sequence data, Author
contributions, Table S1, Figure S1 and Newick tree file generated using Phylomatic.
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SUPPORTING INFORMATION
Construction of phylogeny from molecular sequence data
An initial survey of available genetic data in GenBank for the list of species present in the
phenology dataset indicated that seven DNA regions (cpDNA: atpB, matK, ndhF, rbcL, trnL-F;
ntDNA: lfy, phyB) maximised the number of genera included without introducing more than
10% of missing data in the supermatrix. Every genus was considered monophyletic and we
selected, for each DNA region, the longest DNA sequence available for each genus. This
resulted in a combined DNA matrix that included 1246 different genera and that is available
from the Dryad database (10.5061/dryad.td03p886).
Multiple alignments were done with the software Mafft using default options. However, we
followed a taxonomic approach to perform the alignments by creating initial matrices for each
plant family in the dataset. Once multiple alignments were done for every plant family, we used
profile alignment to merge family-level alignments into taxonomically wider matrices. These
steps followed again a taxonomic hierarchy.
Maximum likelihood (ML) analyses were done in RaxML, using a GTR+G model for each of the
seven DNA regions analysed. The support of the resulting tree was assessed using 100 bootstrap
replicates. Because of the size of the DNA matrix, we used the ML tree to fix the topology
during the divergence times analyses and set a single GTR model of evolution for the whole
DNA matrix. This reduced the complexity of the MCMC analyses and allowed to better sample
the other parameters of the models, in particular the dates of the different nodes of the
phylogenetic tree. We further constrained the age of several nodes using the list of fossil
calibrations from Smith and Donoghue (2008) that corresponded to lineages present in the ML
tree. Normal prior distributions were used on each calibration with means set to represent the
fossil dates from Smith and Donoghue (2008) and standard deviations arbitrarily set to 5.0 Mya.
We ran a single MCMC chain for 100 * 106 generations, sampling parameters every 1000
generations. We repeated the analyses twice to assess the convergence of the posterior
distribution and the effective sample size using Tracer..
All analyses were performed on the vital-IT facilities of the Swiss Institute of Bioinformatics.
LITERATURE CITED
Smith, S. & Donoghue, M. (2009) Rates of molecular evolution are linked to life history in
flowering plants. Science 322: 86-89.
Author contributions
All authors contributed to editing of the manuscript. In addition EMW and TJD conceived the
idea, EMW, NJBK and TJD performed analyses and wrote the paper, BIC, JR and NS performed
additional analyses.
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Table S1. Strength and significance of phylogenetic signal in times of first flower [FF], first leaf
[FF] and variance in first flower (var[FF]) within sites, estimated on the Phylomatic tree.
Site
FF Kthinned ±s.d.
Arnell 1877
0.695±0
Arnell
0.342±0.013**
BCI
0.443±0.013*
Concord
0.514±0.023**
0.342±0.01**
Fargo
0.487±0.019**
0.239±0.008
Fitter
0.593±0.032**
0.247±0.011**
Gothic
0.459±0.021**
0.456±0.029
Gunnar
0.772±0.031*
0.952±0.163
Harvard
1.366±0.203**
Kochmer
0.374±0.009**
Konza
0.637±0.030**
0.219±0.008
Luquillo
0.576±0.020*
0.333±0.005
OPG
0.516±0
0.963±0*
Robertson
0.572±0.026**
Sevilleta
0.364±0.028*
0.430±0.020
0.290±0.012
Soederstroem
0.318±0.005**
0.673±0.017
0.317±0.005
UWM
FL Kthinned ±s.d.
var(FF) Kthinned ±s.d.
0.627±0
0.559±0.001
0.207±0.003
0.550±0
Washington D. C. 0.352±0.023**
0.232±0.009*
WPS
0.616±0.020
0.459±0.011**
* = K significant from random at P<0.05, ** = K significant from random at P<0.01
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FIGURE S1. Phylogenetic distribution of day of year for FF at Harvard. Branches are shaded in
proportion to the weighted average of descendent tips (contrast with Figure 1 and S2).
FIGURE S2. Phylogenetic distribution of day of year for FF at Chinnor. Branches are shaded in
proportion to the weighted average of descendent tips (contrast with Figure 1 and S1).
FIGURE S3. Histograms illustrating phylogeographic clustering of floras within sites. Vertical
red lines indicate the observed phylogenetic diversity (summed phylogenetic branch lengths)
captured by the set of species within each site. Frequency histograms represent expected
phylogenetic diversity from re-sampling the same number of species at random from the global
dataset (1000 randomisations). Analyses conducted using the ML phylogenetic topology.
FIGURE S4. High resolution image of the complete species-level ML phylogenetic tree with
species names shaded by day of year of FF; red values indicating events occurring towards the
start of the year and violet indicates events occurring towards the end of the year y.
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