Early evolutionary history of the flowering plant family Annonaceae ... · ORIGINAL ARTICLE Early evolutionary history of the flowering plant family Annonaceae: steady diversification

ORIGINALARTICLE

Early evolutionary history of theflowering plant family Annonaceae:steady diversification and boreotropicalgeodispersal

Thomas L. P. Couvreur1*, Michael D. Pirie2, Lars W. Chatrou3, Richard M.

K. Saunders4, Yvonne C. F. Su4, James E. Richardson5,6 and Roy H. J. Erkens7

1The New York Botanical Garden, 200th St

and Kazimiroff Blvd, Bronx, NY 10458-5126,

USA, 2Department of Biochemistry, University

of Stellenbosch, Private Bag X1, Matieland

7602, Western Cape, South Africa, 3Nationaal

Herbarium Nederland – Wageningen branch,

Biosystematics Group, Wageningen University,

Generaal Foulkesweg 37, 6703 BL,

Wageningen, The Netherlands, 4Division of

Ecology & Biodiversity, School of Biological

Sciences, The University of Hong Kong,

Pokfulam Road, Hong Kong, China, 5Royal

Botanic Garden Edinburgh, 20A Inverleith

Row, Edinburgh EH3 5LR, UK, 6Depto de

Ciencias Biologicas, Universidad de Los Andes,

Cra 1A No. 18A-10, Edificio J – Piso 4, Bogota,

Colombia, 7Institute of Environmental Biology,

Ecology and Biodiversity group, Utrecht

University, Padualaan 8, 3584 CH Utrecht,

The Netherlands

*Correspondence: Thomas L. P. Couvreur, The

New York Botanical Garden, 200th St and

Kazimiroff Blvd, Bronx, NY 10458-5126, USA.

E-mails: [email protected];

[email protected]

ABSTRACT

Aim Rain forest-restricted plant families show disjunct distributions between the

three major tropical regions: South America, Africa and Asia. Explaining these

disjunctions has become an important challenge in biogeography. The

pantropical plant family Annonaceae is used to test hypotheses that might

explain diversification and distribution patterns in tropical biota: the museum

hypothesis (low extinction leading to steady accumulation of species); and

dispersal between Africa and Asia via Indian rafting versus boreotropical

geodispersal.

Location Tropics and boreotropics.

Methods Molecular age estimates were calculated using a Bayesian approach

based on 83% generic sampling representing all major lineages within the family,

seven chloroplast markers and two fossil calibrations. An analysis of

diversification was carried out, which included lineage-through-time (LTT)

plots and the calculation of diversification rates for genera and major clades.

Ancestral areas were reconstructed using a maximum likelihood approach that

implements the dispersal–extinction–cladogenesis model.

Results The LTT plots indicated a constant overall rate of diversification with

low extinction rates for the family during the first 80 Ma of its existence. The

highest diversification rates were inferred for several young genera such as

Desmopsis, Uvariopsis and Unonopsis. A boreotropical migration route was

supported over Indian rafting as the best fitting hypothesis to explain present-day

distribution patterns within the family.

Main conclusions Early diversification within Annonaceae fits the hypothesis

of a museum model of tropical diversification, with an overall steady increase in

lineages possibly due to low extinction rates. The present-day distribution of

species within the two largest clades of Annonaceae is the result of two

contrasting biogeographic histories. The ‘long-branch clade’ has been diversifying

since the beginning of the Cenozoic and underwent numerous geodispersals via

the boreotropics and several more recent long-distance dispersal events. In

contrast, the ‘short-branch clade’ dispersed once into Asia via the boreotropics

during the Early Miocene and further dispersal was limited.

Keywords

Biogeographic hypothesis testing, boreotropical hypothesis, diversification rates,

Indian rafting, K/Pg boundary, LTT plots, molecular dating, museum model.

Journal of Biogeography (J. Biogeogr.) (2011) 38, 664–680

664 http://wileyonlinelibrary.com/journal/jbi ª 2010 Blackwell Publishing Ltddoi:10.1111/j.1365-2699.2010.02434.x

INTRODUCTION

Tropical rain forests cover c. 7% of all continental land surface

and are the most biodiverse terrestrial ecosystems on the planet

(Whitmore, 1998; Morley, 2000). The South American rain

forests alone hold 30% of the world’s plant diversity (Smith

et al., 2004). Rain forests are currently restricted to a belt

spanning the equator in Southeast Asia, northern Australasia,

Africa, South/Central America, India–Sri Lanka and some

Pacific Islands. Plant families whose species are mainly

restricted to rain forests are frequently distributed across all

three continents, i.e. their distributions are disjunct, separated

by large expanses of ocean.

A number of hypotheses have been advanced to explain how

such intercontinental disjunctions could have originated.

These include vicariance resulting from the break up of the

Gondwanan supercontinent (Raven & Axelrod, 1974), con-

certed migrations across land bridges (van Steenis, 1962;

Thorne, 1972; Davis et al., 2002) during times when the

climate was favourable (geodispersal), continental rafting

(Conti et al., 2002), and long-distance dispersal (LDD)

(Renner et al., 2001). Providing evidence for any of these

hypotheses will give important insights into the evolutionary

history of tropical rain forest ecosystems. Analyses of diver-

sification through time on the basis of dated molecular

phylogenies have been undertaken in several families within

most major clades of angiosperms (asterids, basal eudicots,

basal core eudicots, monocots and rosids). However, such

studies are lacking within the early diverging Magnoliales

(Angiosperm Phylogeny Group, 2009).

Annonaceae are a large pantropical family of trees and

lianas. Although this family (c. 2440 species; Table 1) is not as

diverse in terms of species richness as some core angiosperm

families (Rubiaceae, c. 13,000; Asteraceae, c. 25,000 species) it

is the most diverse family within the Magnoliales (Keßler,

1993). The family contributes significantly to tree diversity in

rain forests around the world (Gentry, 1993; Tchouto et al.,

2006; Punyasena et al., 2008) and provides one of the best

examples of tropical plant families for which abundance and

species richness, and temperature and rainfall, respectively, are

positively correlated (see Punyasena et al., 2008). This suggests

that the evolution of Annonaceae may be informative on the

historical development of tropical rain forests in general.

Molecular phylogenetic analyses within the family have

identified two main sister clades containing the majority of

species richness and initially characterized by their molecular

attributes (Richardson et al., 2004): the long-branch clade

(LBC) and the short-branch clade (SBC). On average, the LBC

has twice the level of chloroplast sequence divergence

compared with the SBC. In addition, the LBC contains more

than twice the species richness when compared with the SBC

(Table 1). Based on fossil data and past molecular date

estimates within the family, intercontinental disjunctions

between genera have been attributed mainly to boreotropical

geodispersal during the Late Eocene (Doyle & Le Thomas,

1997; Richardson et al., 2004). In the light of new age estimates

for major nodes within the family, geodispersal via Indian

rafting (McKenna, 1973; Morley, 2000) was suggested as being

an important factor in determining how this clade reached

Southeast Asia (Su & Saunders, 2009).

The goal of this study is to undertake a detailed analysis of

the diversification and general biogeographic history of

Annonaceae using DNA sequence data from nearly all genera

in the family. It represents the most comprehensive study on

diversification-rate patterns in the magnoliids so far. We tested

models involving shifts in rates of diversification (as opposed

to a more constant rate) and high versus low levels of

extinction (the latter corresponding to the ‘museum’ model, in

which low levels of extinction have been invoked to explain the

richness of tropical biota). Molecular age estimates calibrated

using the fossil record were used to discriminate between

alternative biogeographic hypotheses: boreotropical geodis-

persal, LDD and Indian rafting. These explanations are tested

explicitly within a maximum likelihood (ML) framework.

MATERIALS AND METHODS

Taxon and character sampling

For this study, we selected all genera with sequence data

available. Most genera were represented by one species,

although for genera that have been shown to be polyphyletic

(e.g. Polyalthia, Oxandra and Orophea; Mols et al., 2004), one

species per known monophyletic group was sampled. In total,

100 ingroup taxa were included, representing 93 out of the 112

(Table 1) currently recognized genera (83%). In addition, four

outgroup taxa were selected: Eupomatia bennettii (Eupomat-

iaceae are recovered as sister to Annonaceae; Qiu et al., 2000;

Sauquet et al., 2003), Degeneria vitiensis (Degeneriaceae),

Galbulimima belgraveana (Himantandraceae) and Magnolia

kobus (Magnoliaceae).

We adopted a supermatrix approach (de Queiroz & Gatesy,

2007), concatenating all available sequence data for the selected

taxa (mostly sourced from our own published work; Mols

et al., 2004; Richardson et al., 2004; Pirie et al., 2005, 2006;

Scharaschkin & Doyle, 2006; Erkens et al., 2007, 2009;

Couvreur et al., 2008a, 2009; Nakkuntod et al., 2009). Data

from seven chloroplast markers were available: three coding

(rbcL, matK and ndhF) and four non-coding (trnS–trnG,

Table 1 Total number of species and genera in Annonaceae and

per major clade, and number (percentage) of these sampled for

this study.

Species Genera

Total Sampled Total Sampled

Anaxagorea 26 1 (3.8) 1 1 (100)

Ambavioids 57 8 (14) 8 8 (100)

Long-branch clade 1631 40 (2.5) 52 39 (75)

Short-branch clade 726 51 (7.2) 51 45 (88)

Total 2440 100 (4.8) 112 93 (83)

Evolutionary history of the Annonaceae

Journal of Biogeography 38, 664–680 665ª 2010 Blackwell Publishing Ltd

trnL–trnF, psbA–trnH and atpB–rbcL). GenBank numbers are

given in Appendix S1 in the Supporting Information.

The total length of the aligned molecular data matrix was

8823 characters. Gaps were not coded as separate indel

characters because binary characters could not be analysed

under the combined phylogenetic inference and molecular

dating approach (see below). In total, 47% of characters were

missing (including gaps; Appendix S2), with 55 taxa having up

to 50% of characters missing, and 49 with more than 50% of

characters missing. Woodiellantha and Pseudephedranthus had

the greatest proportion of missing characters with 83 and 80%,

respectively. Sequences of rbcL and trnL–trnF were available for

all taxa. In contrast, atpB–rbcL was available for only 40 taxa

(Appendix S2). Taxa with a high proportion of missing

characters can be included successfully in phylogenetic analyses

(Wiens, 2003; Wiens & Moen, 2008), and the supermatrix

approach is often used for family-wide phylogenies (Baker

et al., 2009; Couvreur et al., 2010) as it allows the inclusion of

data from disparate sources.

Fossil calibration

The present study used two fossils as minimum age constraints

for two separate nodes (see Discussion). The first fossil was

Endressinia (Mohr & Bernardes-de-Oliveira, 2004) from the

Aptian of Brazil of c. 115 Ma (Gradstein et al., 2004). The

phylogenetic positions of this and other relevant fossils were

evaluated recently by Doyle & Endress (2010) by optimizing

morphological characters over a molecular phylogeny of ‘basal’

angiosperms. Doyle & Endress (2010) showed that both

Endressinia and the more recent Archaeanthus (100 Ma)

(Dilcher & Crane, 1984) provide a minimum age for the

crown node of Magnoliineae (the clade comprising Magnoli-

aceae, Degeneria, Galbulimima, Eupomatia and Annonaceae;

Sauquet et al., 2003). Archaeanthus was widely used in

previous molecular dating analyses of Annonaceae (Doyle

et al., 2004; Richardson et al., 2004; Scharaschkin & Doyle,

2005; Pirie et al., 2006; Couvreur et al., 2008a; Erkens et al.,

2009; Su & Saunders, 2009), thus the use of Endressinia results

in a considerable increase in the minimum age for the

Magnoliineae crown node (Doyle & Endress, 2010; Pirie &

Doyle, in press). The second fossil, Futubanthus (Takahashi

et al., 2008), found in Japan and dating from 89 Ma, was

recognized as the earliest probable fossil of Annonaceae.

Futabanthus exhibits characters, such as a trimerous perianth

and numerous stamens and carpels, that are not unique in

Magnoliineae but that, in combination with the small size of

the stamens and their packing into a dome-like structure, may

be synapomorphies with Annonaceae as a whole (Pirie &

Doyle, in press). As it also lacks inner staminodes, a primitive

character found in Anaxagorea (sister to the rest of Annon-

aceae), Eupomatia, Degeneria and Galbulimima, Futabanthus is

associated with the crown rather than the stem node of the

family (Takahashi et al., 2008; Su & Saunders, 2009; Pirie &

Doyle, in press). Besides Futabanthus, no other fossils are

currently known that are both unequivocally associated with

nodes within Annonaceae and of an age that is likely to further

constrain the ages of those nodes (Pirie & Doyle, in press).

To calibrate the molecular tree, we used the older of the two

fossils (Endressinia), which is associated with the deepest node,

effectively to fix the age of the Magnoliineae crown node (the

root node in our analyses) using a uniform prior with minimal

bounds (115.1–114.9 Ma). This means that, assuming the

molecular method (see below) is accurate, all resulting ages

reported here should be interpreted as minima. We applied the

second, more recent fossil Futabanthus as a minimum

constraint at the crown node of Annonaceae by applying an

exponential prior distribution with a mean of 5 and a hard

bound offset of 89 (the age of the fossil). The mean value

allowed the tail of the distribution (soft bound) to reach

115 Ma (the fixed age of the root node), thus assuming that

Annonaceae could have originated at any time between 115

and 89 Ma, but biased towards the younger age.

Molecular dating

Molecular dating was undertaken using the beast package

(Drummond & Rambaut, 2007) version 1.5.3. Seven partitions

were created, one for each marker, using BEAUti 1.5.3. The

best performing evolutionary model for each partition was

determined using the Akaike information criterion (AIC;

Akaike, 1973) as implemented in MrModeltest (Nylander,

2004). The GTR+G model was selected for rbcL and ndhF,

whereas the GTR model + gamma + invariant sites model was

selected for the other five markers.

The dataset was run separately using a strict clock model

and an uncorrelated relaxed clock model (URC) assuming a

lognormal distribution of rates. We used a Bayes Factor (BF)

test as implemented in Tracer 1.5 (Rambaut & Drummond,

2003) to compare the two clock models statistically under the

smoothed marginal likelihood estimate and with 100 bootstrap

replicates (Suchard et al., 2001). The strict clock model was

significantly rejected over the relaxed clock model.

For each analysis, a total of 30 independent runs of 10

million generations, sampling every 1000th generation, were

undertaken on the online cluster of the Computational Biology

Service Unit from Cornell University (http://cbsuapps.tc.cor-

nell.edu/beast.aspx). The starting tree for each independent

run was derived from an ML tree found using RAxML

(Stamatakis, 2006) and rendered ultrametric using the penal-

ized likelihood method implemented in the program r8s

(Sanderson, 2003). The RAxML analysis was performed using

the web-server program version 7.0.4 (Stamatakis et al., 2008)

available at the CIPRES portal in San Diego (http://

www.phylo.org). Tracer 1.5 was used to check for conver-

gence of the model likelihood and parameters between each

run. The resulting log files were combined (each independent

run with the first 10% samples as burn-in) using LogCom-

biner 1.5.2 (Rambaut & Drummond, 2003). Results were

considered reliable once the effective sampling size (ESS) for all

parameters exceeded 200 (see Results for the total number of

generations). For the tree files, we resampled from each run to

T. L. P. Couvreur et al.

666 Journal of Biogeography 38, 664–680ª 2010 Blackwell Publishing Ltd

achieve a reduced sampling density of one in every 5000

generations. The maximum clade credibility topology with a

posterior probability limit of 0.85 and mean branch lengths

was then summarized from this sample using TreeAnnona-

tor 1.5.2 (Rambaut & Drummond, 2003).

Diversification analyses

To provide an indication of net diversification rates within the

family, we generated a semi-logarithmic lineage-through-time

(LTT) plot of the resulting dated trees using the laser package

version 2.2 (Rabosky, 2006). A mean LTT plot with 95%

confidence intervals was computed from a collection of 1000

posterior trees sampled every 200,000 generations from the

beast output file (which contained a total of 270,000,000 trees

after burn-in).

Our species-level sampling of the family is very incomplete,

with 95.2% of all species missing (Table 1). However, our

sampling strategy was not random and 83% of genera were

represented, covering all the known major lineages of the

family. This has important implications for the interpretations

of the LTT plots: the older ends of the LTT plots should be

accurate, as most of the missing taxa should be attached to the

tree after the stem node of each genus. The missing genera are

mostly monotypic, representing only a fraction of the total

number of species (31). In order to test for a constant rate of

diversification under incomplete taxon sampling, null models

are generally constructed (Pybus & Harvey, 2000) where a

number of phylogenies are generated to a true standing species

richness of the group and then pruned randomly to the

number of taxa sampled. We argue that this method is not

appropriate in our case because of the non-randomness of our

taxon sampling (phylogenetically informed sampling; Cusi-

mano & Renner, 2010). Rather, changes in rates of diversifi-

cation can be interpreted directly from the resulting LTT plot

because, under this sampling strategy, the deeper nodes of the

phylogeny are well represented. For that, we define a threshold

up to which our LTT plot is considered accurate, that is, the

point at which our LTT plot will not be significantly influenced

by the sampling of extra tips (or species). This threshold is

arbitrarily defined to include 85% of all genera stem nodes.

This threshold was estimated for the whole family, the LBC

and the SBC.

In order to test the null hypothesis of no rate change

(constant diversification) versus a variable-rate change in

diversification, we used an ML approach implemented in the

laser package version 2.2 (Rabosky, 2006). The test statistic

for diversification rate-constancy is calculated as: DAICRC =

AICRC ) AICRV, where AICRC is the AIC score for the best

fitting rate-constant diversification model, and AICRV is the

AIC for the best fitting variable-rate diversification model.

Thus a negative value for DAICRV indicates that the data are

best approximated by a rate-constancy model. For each clade

(Annonaceae, LBC and SBC), we tested five different models,

of which two are rate-constant and three are rate-variable: (1)

the constant-rate birth model (the Yule process; Yule, 1924)

with speciation (k) and extinction (l) set to zero; (2) the

constant-rate birth–death model with two parameters, speci-

ation (k) and extinction (l); (3) a pure birth rate-variable

model where the speciation rate k1 shifts to rate k2 at time ts,

with three parameters (k1, k2, ts); (4) an exponential

density-dependent speciation rate ‘DDX’ model; and (5) a

logistic density-dependent speciation rate ‘DDL’ model. The

LTT plot derived from the maximum clade credibility tree was

used for this part. In addition, we used the ‘truncateTree’

function to prune terminals of the LTT, corresponding to the

nodes found after the threshold age set as explained in the

previous paragraph.

Absolute net diversification rates (speciation minus extinc-

tion) were calculated for all non-monotypic genera by using

the stem age under a high level of extinction (b = 0.95) and no

extinction (b = 0) following Magallon & Sanderson (2001).

These rates were computed using the laser package version

2.2 (Rabosky, 2006). A standard boxplot was generated in

order to identify 10th and 90th percentile outliers. Diversifi-

cation rates calculated from stem and crown nodes (when

available) of major clades in Annonaceae as well as for the

family were compared with values for angiosperms as a whole

and Magnoliales (relaxed values, obtained from Magallon &

Castillo, 2009). Genera of uncertain taxonomic status were

excluded from these analyses as their species richness estima-

tion could be inaccurate (see Appendix S3).

Maximum likelihood ancestral area reconstruction

For this analysis, six taxa were pruned from the maximum

clade credibility (MCC) tree in line with our generic level

sampling (insofar as genera can be considered comparable) as

they are known to be nested within broader generic circum-

scriptions: Enicosanthum fuscum, Friesodielsia sp., Haplosti-

chanthus longirostris, Orophea creaghii, Polyalthia cf. longifolia

and Pseudephedranthus fragrans.

Seven areas were delimited based on distribution data of

genera and continental divisions past and present: A, South

America; B, North/Central America; C, Africa; D, Madagascar;

E, India; F, Southeast Asia (west of Wallace’s Line); G,

Southeast Asia (east of Wallace’s Line), Melanesia and

northern Australia (Fig. 1).

Distribution data, taken from different taxonomic sources

(monographs and revisions), were used to assign each genus to

one or more areas (Fig. 2; Appendix S1). When data were

available, genera occurring in several areas were coded with the

inferred ancestral distribution of the genus (see Fig. 2 for

references to these studies) as recommended by Ronquist

(1996). For example, Guatteria is distributed in South and

Central America and Erkens et al. (2007) inferred that the

ancestral distribution of this genus was located in Central

America. Thus Guatteria was coded as operational unit B

(Central/North American).

Ancestral area reconstruction was performed using an ML

method under the divergence–extinction–cladogenesis model

(DEC; Ree et al., 2005; Ree & Smith, 2008) as implemented in



the software Lagrange build 20091004 (Ree & Smith, 2008).

Python scripts were all generated using the online helper

(http://www.reelab.net/lagrange). Ancestral areas were limited

to two, under the assumption that past distributions were

about as wide as current ones and to limit the complexity of

the analysis. Given the low dispersal ability of extant Annon-

aceae, we assume that dispersal was possible only between

adjacent areas (i.e. no dispersal allowed between areas A and D

or E, and between B and D or E). Ancestral areas were

estimated for five nodes relevant to this study (Fig. 2).

The goodness of fit of the data to three alternative

biogeographic models was evaluated in an ML framework:

model 0 was unconstrained with dispersal events between all

adjacent areas possible (probability = 1.0) during the whole

period considered (100–0 Ma). For models 1 and 2, we

incorporated prior information on range evolution as well as

dispersal probabilities between areas given discrete periods of

time. Both models were formulated based on past climatic

data, tectonic history and postulated presence/absence of land

bridges (Morley, 2000, 2003, 2007; Tiffney & Manchester,

2001; Zachos et al., 2001). Five time frames were delimited

(Fig. 1) and dispersal probabilities were assigned between all

adjacent areas. Dispersal probabilities were divided into five

categories: low or no dispersal = 0.01; low dispersal = 0.25;

medium dispersal = 0.5; high dispersal = 0.75; areas adjacent

or very close = 1. For model 1, dispersal into India from the

other areas coded was allowed and dispersal probabilities were

assigned as shown in Fig. 1. Model 2 was identical to model 1,

except that dispersal into India was not allowed from 100 to

5 Ma. We thus forced model 2 to represent the hypothesis that

Annonaceae did not successfully raft with India and that India

played no role in explaining present-day distribution patterns

(see Discussion). Finally, we investigated the influence of the

different number of categories of the dispersal probabilities on

the outcome of the analysis. We did this by analysing the data

under models 2 and 3 using just three probability categories

(instead of five) set to 0.01, 0.5 and 1. Differences between

models were assessed by directly comparing their respective

log-likelihoods. Following Ree et al. (2005), we used the

conventional cut-off value of two log-likelihood units to assess

statistical significance of likelihood differences.

RESULTS

Phylogeny

Weakly supported nodes (posterior probability, PP < 0.90) are

indicated by arrows in Fig. 2 and are mainly concentrated in

Model 0: Unconstrained

A B C D E F GA 1 1 0.01 1B 1 0.010.01

0.011

11

C 1 1 1 1D 1 1 1E 1 0.01F 1G

Model 1: Dispersal into India viable

A B C D E F G A B C D E F G A B C D E F G A B C D E F G A B C D E F GA 1 0.01 0.01 0.01 0.01 0.01 A 0.25 0.01 0.01 0.01 0.01 0.01 A 0.01 0.25 0.01 0.01 0.01 0.01 A 0.25 0.5 0.01 0.01 0.01 0.01 A 0.5 1 0.01 0.01 0.01 0.75B 0.01 0.01 0.01 0.01 0.01 B 0.01 0.01 0.01 0.01 0.01 B 0.01 0.01 0.01 0.01 0.01 B 0.75 0.01 0.01 0.75 0.01 B 0.25 0.01 0.01 0.5 0.01C 0.25 0.25 0.25 0.01 C 0.5 0.25 0.25 0.01 C 0.5 0.01 0.25 0.01 C 0.5 0.01 0.25 0.01 C 1 1 0.01 0.5D 0.25 0.25 0.01 D 0.25 0.25 0.01 D 0.01 0.25 0.01 D 0.01 0.25 0.01 D 1 0.01 0.75E 1 0.01 E 1 0.01 E 0.75 0.25 E 0.25 0.25 E 0.01 0.75F 1 F 0.75 F 0.25 F 0.01 F 0.01G G G G G

A B C D E F G A B C D E F G A B C D E F G A B C D E F G A B C D E F GA 1 0.01 0.01 0.01 0.01 0.01 A 0.25 0.01 0.01 0.01 0.01 0.01 A 0.01 0.25 0.01 0.01 0.01 0.01 A 0.25 0.5 0.01 0.01 0.01 0.01 A 0.5 1 0.01 0.01 0.01 0.75B 0.01 0.01 0.01 0.01 0.01 B 0.01 0.01 0.01 0.01 0.01 B 0.01 0.01 0.01 0.01 0.01 B 0.75 0.01 0.01 0.75 0.01 B 0.25 0.01 0.01 0.5 0.01C 0.25 0.25 0.25 0.01 C 0.5 0.01 0.25 0.01 C 0.5 0.01 0.25 0.01 C 0.5 0.01 0.25 0.01 C 1 0.01 0.01 0.5D 0.25 0.25 0.01 D 0.01 0.25 0.01 D 0.01 0.25 0.01 D 0.01 0.25 0.01 D 0.01 0.01 0.75E 1 0.01 E 0.01 0.01 E 0.01 0.01 E 0.01 0.01 E 0.01 0.01F 1 F 0.75 F 0.25 F 0.01 F 0.01G G G G G

A

B

C

D

EF

G

30-45 Myr 45-65 Myr 65-100 Myr

5-30 Myr 30-45 Myr 45-65 Myr 65-100 Myr

5-30 Myr0-5 Myr

0-100 Myr

0-5 Myr

Model 2: Dispersal into India not viable

Figure 1 Delimitation of the seven areas assigned to the genera included and parameters of the three alternative biogeographic models

tested in this study. A, South America; B, Central/North America; C, Africa; D, Madagascar; E, Indian plate F, Mainland Asia/Sundaland/

west of Wallace’s Line; G, Sahul/Australia/Pacific/east of Wallace’s Line. Probabilities of dispersal: 0.01, none or low; 0.25, medium-low; 0.5,

medium; 0.75, medium-high; 1, high.

Figure 2 Maximum clade credibility tree of the Annonaceae with 95% highest probability density bars. Arrows indicate nodes with <0.9

posterior probability support. Numbers represent references to ancestral area coding for genera found in several areas. 1, Scharaschkin &

Doyle (2005); 2, L.W. Chatrou, pers. comm.; 3, Erkens et al. (2007); 4, Zhou et al. (2009); 5, Couvreur et al. (2008a); 6, Su & Saunders

(2009). Stars represent nodes used for calibrating the tree. Lower-case letters indicate nodes for which the ancestral areas were estimated

(Table 3). Letters next to taxon names represent coding of areas. When no box is present, the taxon was deleted from the Lagrange analysis.



0102030405060708090100110120

Enicosanthum fuscumPolyalthia cf longifoliaPolyalthia xanthopetalaNeo uvaria paralelliveniaSageraea lanceolataMiliusa mollisFitzalania heteropetalaMeiogyne virgataMitrephora albaPhaeanthus ebracteolatusPopowia hirta Tridimeris sp.Sapranthus viridiflorusStenanona panamensisDesmopsis microcarpaStelechocarpus buraholGuamia sp.Orophea creaghiiOrophea kerriiWoodiellantha sp.Orophea celebicaPlatymitra macrocarpaAlphonsea kinabaluensisMarsypopetalum pallidumPseuduvaria pamattonis [6]Haplostichanthus longirostrisPolyalthia suberosaTrivalvaria macrophyllaPolyalthia stuhlmanniiMonocarpia euneuraKlarobelia inundataPseudephedranthus fragransOxandra espintanaPseudomalmea diclinaOxandra macrophylla Ephedranthus sp.Ruizodendron ovaleMosannona costaricensisPseudoxandra lucidaCremastosperma brevipesMalmea dielsianaBocageopsis canescensOnychopetalum periquinoUnonopsis stipitataMaasia sumatranaPiptostigma mortehaniPolyceratocarpus pellegriniMwasumbia albaGreenwayodendron oliveriAnnickia affinisFriesodielsia desmoidesDesmos elegansDasymaschalon macrocalyxFriesodielsia sp.Monanthotaxis whyteiMelodorum fruticosumSphaerocoryne gracilisToussaintia orientalisMitrella kentiiFissistigma glaucescensUvaria lucida [4]Dielsiothamnus divaricatusHexalobus salicifoliusUvariastrum insculptum Asteranthe asteriasMonodora myristicaIsolona campanulata [5]Uvariopsis vanderystii Monocyclanthus vegneiUvariodendron molundenseMischogyne michelioidesSanrafaelia rufonammariOphrypetalum odoratumAsimina trilobaDisepalum platypetalumAnnona muricataGoniothalamus griffithiiNeostenanthera myristicifoliaAnonidium maniiGuatteria anomala [3]Pseudartabotrys letestuiLetestudoxa bellaDuguetia staudtiiFusaea peruvianaXylopia peruvianaArtabotrys hexapetalus [2]Hornschuchia citriodoraTrigynaea lanceipetalaCymbopetalum brasiliensePorcelia steinbachiiMkilua fragransMezzettia parvifloraAmbavia gerrardiiCleistopholis glaucaTetrameranthus duckeiCananga odorataCyathocalyx martabanicusLettowianthus stellatusMeiocarpidium lepidotumAnaxagorea silvatica [1]Eupomatia bennettiiDegeneria vitiensisGalbulimima belgraveanaMagnolia kobus

Long-branchclade

Ambavioids

Anaxagorea

South/Central Americanclade

AfricanLBC

AfricanSBC

miliusoidclade

Uvariaclade

Bocageeae

Short-branchclade

annonoid clade

Duguetiaclade

Outgroups

Lower Cretaceous Upper Cretaceous Palaeocene OligoceneEocene Miocene PPL

a

b

c

d

e

EFFEG

F

BBBBFB

EF

F

FF

FCFAAAAAAAAAAAAAAFCCCCCF

CECF

CDFCCCCCCCCCCCCCBFAFCCBCCAACCAAAACFDCAFFCCA

F

F G

E F GE F G

E F G

F

E F

E F GG

D F

F G

F G

FD

C D F

G

G

C

A



the SBC. In general, the topology and support values agree well

with previous phylogenetic analyses (Mols et al., 2004; Rich-

ardson et al., 2004; Pirie et al., 2006; Couvreur et al., 2008b;

Erkens et al., 2009; Su & Saunders, 2009).

Molecular dating

The maximum clade credibility tree is presented in Fig. 2. A

total of 300 million generations (30 runs of 10 million

generations each) were necessary to reach sufficient ESS. All

parameters between independent runs were equal. For all runs,

stationarity was achieved relatively quickly, within 100,000

generations, which was presumably the result of using a nearly

optimal starting tree. In general, most parameters and age

estimations reached ESS values >200, and all reached ESS

values >150.

The dataset was strongly non-clock-like according to a BF

test (ln BF > 1000 in favour of relaxed clock analysis), thus

only the results using the relaxed clock model are presented

here. For all five partitions, the rate of covariance was centred

on zero, which can be interpreted as a lack of evidence for rate

autocorrelation among lineages (Peng et al., 2006; Drummond

& Rambaut, 2007; Ho, 2009). The first 200 sampled trees of

each run were treated as burn-in and deleted, and the

remaining 16,000 in total were combined into a single file.

Ages of major clades obtained for this study are given in

Table 2.

Diversification

The thresholds for the LTT plots were calculated as 25 Ma for

the whole family, 31 Ma for the long-branch clade and 16 Ma

for the short-branch clade (Fig. 3). Following our assump-

tions, these dates represent the point in time before which our

LTTs are assumed to depict a fairly accurate picture of

diversification rates. Overall, the family level and LBC LTT

plots were fairly linear. At the family and clade level (LBC and

SBC), the data better fitted a constant rate model of

diversification with the diversification rate-constancy statistic

DAICRV being )1.05 (Annonaceae), )1.0 (LBC) and )3.4

(SBC) when compared with the second-best model. In all three

cases, the pure birth model was identified as having the lowest

AIC value amongst the other models tested.

The total number of genera analysed for the diversification

rate was 75. Eight genera were outliers with higher rates (>90th

percentile; Appendix S3; Fig. 4a) under no extinction (b = 0).

When extinction was factored in, eight genera were outliers

with higher rates (>90th percentile; Appendix S3; Fig. 4b). In

addition, nine genera (under both b = 0 and b = 0.95) were

outliers with lower rates (>10th percentile; Appendix S3;

Fig. 4a). Diversification rates calculated for the stem and

crown nodes within Annonaceae were more or less the same,

except in the case of the SBC, where a significant difference was

seen (Fig. 5, grey panel). The diversification rate of Annon-

aceae as a whole (Fig. 5) was higher than that of angiosperms

and the Magnoliales (Magallon & Castillo, 2009). At the level

of the major clades within the family, the LBC and SBC had the

highest diversification rates (Fig. 5), while Anaxagorea and the

ambavioids had the lowest. The SBC had a higher diversifi-

cation rate when the crown node, as opposed to the stem node,

was used for the calculation.

Biogeographic reconstruction analyses

All models returned similar ancestral areas for the five nodes

(Table 3). Model 2, in which rafting with India was not

allowed, returned a significantly better likelihood score com-

pared with models 0 and 1. Lowering the number of

probabilities to three had no major effects on the results

under model 2 (Table 3), indicating that our choice of

dispersal probability categories did not significantly influence

the results.

We coded widespread genera according to the ancestral

areas inferred in previous studies, with a single exception: in

Table 2 Differences in age (Ma) between recent Annonaceae family-wide molecular dating studies.

Clade

Penalized likelihood method beast

Age (Ma) (SD in parentheses) Mean age (95% HPD in parentheses)

Pirie & Doyle (in press) Su & Saunders (2009) This study

Annonaceae stem age 90.9 (1.6) 98.0 (101.46–94.91) 106.29 (110.37–102.02)

Annonaceae crown age 75.5 (1.7) 89.4 (90.41–89) (cal) 90.44 (92.98–89) (cal)

Ambavioids/LBC/SBC crown 65.3 (1.9) 74.6 (84.4–63.6) 76.08 (82.5–69)

Ambavioids crown age – – 69.40 (60.2–78)

LBC/SBC crown 62.8 (1.9) 67.3 (78.1–55.2) 71.71 (78.26–64.77)

LBC crown age 57.6 (2.1) 59.6 (70.5–48.1) 65.85 (72.42–59.16)

SBC crown age 55.3 (2.4) 39.8 (55.1–26.8) 32.768 (40–25.8)

SAC/miliusoid clade crown 45.5 (2.9) 29.1 (39.2–20.2) 23.60 (28.79–19.16)

SAC crown age 44.0 (2.5) 24.3 (37.7–15.7) 21.38 (26.09–16.85)

Miliusoid crown age 40.3 (3.4) 23.0 (31.1–16) 19.72 (24.04–15.89)

HPD, highest posterior density; SD, standard deviation; LBC, long-branch clade of Annonaceae; SBC, short-branch clade of Annonaceae; cal, node

used for calibration.



the absence of a detailed phylogeny, this was not possible for

the large pantropical genus Xylopia. We thus undertook three

analyses in order to test the impact of different plausible

ancestral areas for Xylopia: Africa, South America and

Southeast Asia. Of the three reconstructions, the best likeli-

hood score was obtained with Africa as the ancestral area for

Xylopia and, as the overall results for nodes focal to this study

were otherwise unaffected (data not shown), we used this

coding in all further analyses.

DISCUSSION

Clade ages within Annonaceae

In general, the minimum ages estimated here using the URC as

implemented in beast are slightly older for deeper parts of the

chronogram, and significantly younger for shallower parts of

the chronogram, than those of Pirie & Doyle (in press),

generated using the same calibrations but with the penalized

likelihood method of Sanderson (2002), which assumes

autocorrelation of rates (Table 2). The discrepancies between

some previous estimates (Richardson et al., 2004; Pirie &

Doyle, in press) and those presented here could be related to

several different factors, such as taxon sampling density

(Linder et al., 2005; Pirie et al., 2005), molecular marker

sampling (Magallon & Sanderson, 2005), alternative dating

methods (Drummond et al., 2006), and the use of different

fossils as calibration points (in particular compared with

studies of Doyle et al., 2004; Richardson et al., 2004; Pirie

et al., 2006 that used the relatively recent fossil Archaeanthus).

Su & Saunders (2009) also used the URC model with a

comparable age calibration and recovered age estimations

similar to those presented here (Table 2) despite having only

approximately one-third of the taxon sampling included here.

The molecular dating method may thus explain at least some

of the inconsistencies, which should therefore be interpreted in

terms of the fit of the underlying assumptions to the data (rate

autocorrelation versus uncorrelated distribution of rates;

Drummond et al., 2006). The URC model is more general: it

neither assumes nor excludes rate autocorrelation, and in fact

provides a means to test for autocorrelated rates as indicated

by the posterior distribution of the covariance parameter

(Drummond et al., 2006; although a possible bias against

discovering rate autocorrelation in this manner has been

suggested, e.g. Moore & Donoghue, 2007). As our results do

not indicate significant rate autocorrelation in Annonaceae, we

interpret the ages derived under the URC model as being more

plausible.

Annonaceae originated at least 110–102 Ma [95% highest

posterior density (HPD), stem node] and started to diversify

by c. 89 Ma. Our mean (minimum) estimates for the three

major lineages are c. 69 Ma (crown node ambavioids),

c. 66 Ma (crown node LBC) and c. 33 Ma (crown node

SBC). Besides the major clades, the age estimations for stem

nodes of genera reported here correspond closely with previous

analyses under higher levels of infra-generic species sampling

(Table 2).

Diversification at family and generic levels

The Cretaceous–Palaeogene (K/Pg) boundary mass extinction

at 65 Ma had profound effects on marine biodiversity and

(a)

(b)

(c)

Annonaceae

long-branch clade

short-branch clade

0204060801

10

100

1000

0204060801

10

100

1000

1

10

100

1000

020406080100120

Millions of years ago (Ma)

Ln n

umbe

r of l

inea

ges

Ln n

umbe

r of l

inea

ges

Ln n

umbe

r of l

inea

ges

Figure 3 Semi-logarithmic lineage-through-time (LTT) plots

within (a) Annonaceae, (b) long-branch and (c) short-branch

clades. Triangles: mean LTT plot from 1000 posterior trees; solid

lines represent 95% confidence limits. Squares on the right rep-

resent the extant number of taxa for each clade. The grey column

in (a) represents the Cretaceous–Palaeogene boundary, that in (b,

c) represents the Early Eocene Climatic Optimum event. Vertical

bars represent threshold limit of LTT plots indicating where the

plot is assumed to be accurate (not influenced by missing taxa).



Desmopsis

Uvariopsis

Stenanona

Desmos*, Friesodielsia

Unonopsis

Sphaerocoryne

Monanthotaxis

Guatteria

Artabotrys

Xylopia

Goniothalamus

Annona

Uvaria

Duguetia

Pseuduvaria

Anaxagorea

Millions of years since origin

Div

ersi

ficat

ion

rate

s with

b=0

.95

Div

ersi

ficat

ion

rate

s rat

e b=

0

Guatteria

Artabotrys

Xylopia

Goniothalamus

Annona

Uvaria

Duguetia

Fissistigma

Pseuduvaria

Anaxagorea

Desmopsis

Uvariopsis

Stenanona

Unonopsis

Monanthotaxis

0 20 40 60 80 1000

0.1

0.2

0.3

0.4

0.5

0.6

0 20 40 60 80 1000

0.02

0.04

0.06

0.08

0.1

0.12

0.14

0.16

Desmos*, Friesodielsia*

Dasymachalon

*

*

*

*

* **

*

*

***

*

(a)

(b)

Figure 4 Diversification rates of genera as a

function of time for (a) no extinction (b = 0)

and (b) high extinction (b = 0.95). Circle size

is proportional to species richness within

each genus. Asterisks indicate genera for

which diversification rates were identified as

90th percentile outliers.

Stem

Stem

Stem

Stem

Stem

Stem

Cro

wn

Cro

wn

Cro

wn

Cro

wn

Cro

wn

Cro

wn

b, D

iver

sific

atio

n ra

te

0.00

0.05

0.10

0.15

0.20

0.25

0

50

100

150

200

250

300

350

400

Annonaceae

Anax

agor

ea

Ambavioids

LBC

SBC

MagnolialesAngiosperms

Stem

Millions of years ago (M

a)

Figure 5 Diversification rates for several

plant groups as a function of the estimated

stem and crown nodes. Left axis, diversifica-

tion rate: no extinction (b = 0; diamonds);

high extinction (b = 0.95; squares). Right

axis, mean age of stem and crown nodes in

Ma (grey triangles). SBC, short-branch clade

of Annonaceae; LBC, long-branch clade of

Annonaceae.



Tab

le3

Max

imu

mli

keli

ho

od

reco

nst

ruct

ion

for

maj

or

no

des

wit

hin

An

no

nac

eae

un

der

thre

ed

iffe

ren

tm

od

els

of

geo

grap

hic

ran

geev

olu

tio

n.

Mo

del

lnL

Dis

per

sal

Ext

inct

ion

Cro

wn

An

no

nac

eae

[a]

Cro

wn

LB

C/S

BC

/am

bav

ioid

[b]

Cro

wn

LB

C/S

BC

[c]

Cro

wn

SBC

[d]

Cro

wn

LB

C[e

]

0)

196

0.00

390.

0020

[A|C

]0.

38[C

|C]

0.64

[C|C

]0.

71[C

|A]

0.53

[C|C

]0.

80

[A|A

C]

0.21

[C|A

C]

0.21

[C|A

C]

0.11

[C|F

]0.

42[A

C|C

]0.

14

[AC

|C]

0.12

[C|C

]0.

08

[A|A

]0.

06

1)

191

0.01

670.

0016

[A|A

C]

0.65

[C|A

C]

0.4

[C|C

]0.

55[C

|F]

0.86

[C|C

]0.

59

[A|C

]0.

21[C

|C]

0.31

[AC

|C]

0.34

[AC

|C]

0.36

2 Fiv

ed

isp

ersa

lp

rob

abil

itie

s)

187

0.01

860.

0017

[A|A

C]

0.6

[C|A

C]

0.37

[C|C

]0.

59[C

|F]

0.86

[C|C

]0.

61

[A|C

]0.

24[C

|C]

0.37

[AC

|C]

0.31

[AC

|C]

0.33

[AC

|C]

0.23

Th

ree

dis

per

sal

pro

bab

ilit

ies

)19

00.

0139

20.

0015

46[A

|AC

]0.

72[C

|AC

]0.

41[C

|C]

0.54

[C|F

]0.

9[C

|C]

0.56

[A|C

]0.

18[A

C|C

]0.

3[A

C|C

]0.

38[A

C|C

]0.

39

[C|C

]0.

25

Mo

del

0:u

nco

nst

rain

ed;

mo

del

1:d

isp

ersa

lin

toIn

dia

po

ssib

le;

mo

del

2:d

isp

ersa

lin

toIn

dia

no

tal

low

ed.

Mo

del

2w

asfu

rth

eran

alys

edu

sin

gfi

vean

dth

ree

dis

per

sal

pro

bab

ilit

ies

(see

text

for

det

ails

).L

ette

rs

rep

rese

nt

alte

rnat

ive

ance

stra

lar

eare

con

stru

ctio

ns

that

fall

wit

hin

two

log-

like

lih

oo

du

nit

so

fth

eo

pti

mal

scen

ario

.F

oll

ow

ing

Fig

.2,

the

vert

ical

bar

sep

arat

esth

ean

cest

ral

area

reco

nst

ruct

edfo

rth

elo

wer

bra

nch

(lef

tle

tter

)fr

om

the

on

ere

con

stru

cted

for

the

up

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bra

nch

(rig

ht

lett

er)

aris

ing

fro

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od

e.Si

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tter

sin

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ea;

two

-are

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rict

edto

two

area

s.V

alu

esre

pre

sen

tth

ere

lati

vep

rob

abil

ity

of

that

infe

ren

ce.

Bo

ldte

xtre

pre

sen

tsth

em

od

elw

ith

asi

gnifi

can

tly

bet

ter

like

lih

oo

dw

hen

com

par

edw

ith

the

oth

erm

od

els

test

ed(m

ore

than

two

log-

like

lih

oo

ds

bet

ter)

.

lnL

,lo

g-li

keli

ho

od

of

the

test

edm

od

el;

LB

C,

lon

g-b

ran

chcl

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of

An

no

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,sh

ort

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clad

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on

acea

e.



terrestrial animals, such as the extinction of non-avian

dinosaurs. However, the effect of such a mass extinction on

plant terrestrial ecosystems has been controversial (McElwain

& Punyasena, 2007). Some authors argue that, in comparison

with animals or marine ecosystems, plant communities were

little affected by such drastic events (Traverse, 1988). Other

authors indicate, mainly based on the plant fossil record, that

the K/Pg boundary resulted in massive extinction of land

plants (Wolfe & Upchurch, 1986; Wilf & Johnson, 2004;

Nichols & Johnson, 2008). One major difference noted for

plants is that, even though species extinction could have been

relatively high, it did not eradicate entire genera or families

(McElwain & Punyasena, 2007; Nichols & Johnson, 2008). In

our analysis of diversification through time in Annonaceae, the

LTT plot reveals a brief pause in diversification (gap) after the

K/Pg mass extinction (Fig. 3a). However, after a mass extinc-

tion event, LTT plots should reveal a clear anti-sigmoid curve

(Harvey et al., 1994; Crisp & Cook, 2009), which is not

observed here. Thus our data do not indicate that Annonaceae

diversification was severely affected by the events of the K/Pg

boundary. It could be that tropical rain forests proved more

resilient to such drastic changes, despite the fact that some

studies suggested that evergreen taxa were more affected than

deciduous taxa during those times (Wolfe & Upchurch, 1986;

McElwain & Punyasena, 2007). Our results, however, pertain

to the origination of major lineages, and the effects of the K/Pg

boundary at the specific level would have to be investigated

more closely using the fossil record. Unfortunately, studies of

fossil flora diversity in tropical regions across the K/Pg

boundary are rare, being more centred in North America

(McElwain & Punyasena, 2007; Nichols & Johnson, 2008).

The overall shapes of the LTT plots for the whole family, the

LBC and the SBC are otherwise fairly linear (Fig. 3). Such

patterns are generally associated with a constant rate of

diversification (Nee et al., 1994; Nee, 2006; Ricklefs, 2007).

This was confirmed by the test statistic for diversification rate-

constancy (DAICRC), which was negative at the family and

clade (LBC and SBC) levels. Thus the overall picture indicates

no major shifts of diversification throughout the family’s

evolutionary history (at least up to 25 Ma). Interestingly,

equivalent family or higher-order level LTT plots within

different plant groups do not show an early diversification

scenario consistent with a constant diversification rate. Diver-

sification analyses within clades such as Burmanniaceae

(Merckx et al., 2008), Brassicaceae (Couvreur et al., 2010),

Proteaceae (Sauquet et al., 2009) and the rosid clade (Wang

et al., 2009) all indicate an early and rapid increase in

diversification followed by a decrease. In addition, the order

Malpighiales was shown to have undergone a rapid increase in

diversification shortly after its origin c. 114 Ma (Davis et al.,

2005). Such a contrast could be the result of several factors,

possibly linked to the strictly tropical ecology of Annonaceae.

One hypothesis advanced to explain high levels of diversity in

tropical ecosystems is the ‘museum model’, whereby lineages

accumulated steadily through time due to low background

extinction (Stebbins, 1974). This pattern is supported by the

fact that the diversification model that best fitted our data was

the pure birth model, where the speciation rate is constant and

the extinction rate is fixed to 0. Such a pattern was also

recorded for the liverwort family Lejeuneaceae (Wilson et al.,

2007), although this family had representatives in more

temperate as well as tropical climates. More data should be

gathered from other plant families with similar tropical

distributions to confirm this.

Finally, despite a common origin, it is apparent in Fig. 2

that diversification within the LBC and SBC started at

significantly different times. Based on crown node ages,

present-day species richness within the SBC appears to be

the result of higher diversification rates when compared with

the LBC, although diversification rates are similar when the

stem node is used (Fig. 5).

As we indicated above, the estimation of the minimum stem

node age of genera is reliable across the family, even in the

absence of dense taxon sampling within each genus. Thus

diversification rates taken from stem node ages should not be

sensitive to taxon undersampling within genera. Under a zero

extinction model, the seven largest genera of Annonaceae (>95

species: Annona, Artabotrys, Duguetia, Goniothalamus, Guatte-

ria, Uvaria, Xylopia) do not have the highest diversification

rates within the family (Fig. 4; Appendix S3). This was also the

case under a high extinction-rate model, with the exception of

Uvaria, for which the rate estimation increased considerably

(Fig. 4; Appendix S3). The largest genus associated with the

highest levels of diversification with or without extinction was

the African liana genus Monanthotaxis (Fig. 4a; Appendix S3),

with c. 86 species. The highest diversification rates were instead

identified in smaller genera with stem nodes younger than

8 Ma (Fig. 4; Appendix S3). The four fastest-diversifying

genera under no extinction are Uvariopsis, Unonopsis, Desm-

opsis and Stenanona (Fig. 4; Appendix S3), representing 17, 48,

18 and 13 described species, respectively. Net diversification of

a clade is a function between species and the age of that clade

(Magallon & Sanderson, 2001), and in Annonaceae the larger

genera are not associated with the highest diversification rates

(large circles concentrated to the right in Fig. 4). Such a

pattern was also found at the angiosperm level (Magallon &

Sanderson, 2001). Diversification rates of these large genera

could, however, be underestimated because they were calcu-

lated using stem ages. If their crown ages are estimated to be

young, this would lead to higher diversification rates (Mag-

allon & Castillo, 2009). For example, Linder (2008) regarded

Guatteria as a recent and rapid radiation (in which recent

speciation overwhelmed extinction) based on its age and

species richness. In a well sampled species-level molecular

phylogeny of the genus, the crown node age was estimated to

be 11.4 (±1.4) Ma (Erkens et al., 2007). This would provide a

diversification rate of 0.44 under no extinction, placing it

amongst the fastest-diversifying genera in Annonaceae

(Appendix S3; Fig. 4). Goniothalamus, a Southeast Asian genus

with c. 150 species (Nakkuntod et al., 2009), was found to have

the most significant rate increase along its stem branch

(Erkens, 2007). Based on very restricted sampling of species



within the genus, the crown node was estimated to be fairly

young, varying from 4.8 to 3.6 Ma (three species sampled;

Richardson et al., 2004) to c. 10 Ma (two species sampled; Su

& Saunders, 2009). This could indicate a rapid radiation within

Goniothalamus, which we would fail to identify here on the

basis of its stem node age alone. Further sampling of taxa is

likely to identify more distantly related species, thus increasing

the estimated age of the crown node of Goniothalamus.

A dated species-level phylogeny is necessary to reconstruct

the diversification history of the family during more recent

times and beyond our arbitrary threshold. Many geological

events have occurred from the Miocene (23 Ma) onwards that

could have influenced diversification rates within the family,

including major uplifts of the Andes, the New Guinea highlands

and the East African rift system; the collision of Sundanian and

Papuasian shelves around Wallace’s Line; and closure of the

Isthmus of Panama and the Tethys Sea. The combination of

these events could have had a profound impact on rates of

diversification and extinction in the tropics along with all other

parts of the world. For example, diversification in the genus Inga

(Fabaceae), which comprises c. 350 species, has been shown to

have been concentrated within the past 10 Myr (Richardson

et al., 2001), over a similar period to that of Guatteria (if not

younger). Substantial diversification of tropical plant lineages

has therefore taken place during comparatively recent times and

could have been caused by some of the events discussed above.

Modern tropical species diversity therefore seems to be the

result of gradual accumulation of lineages through time, as

suggested by the ‘museum hypothesis’ coupled with rapid and

comparatively recent diversification in a few lineages. Similar

patterns are evident in studies of tropical lineages of leaf beetles

(McKenna & Farrell, 2006).

Origins and diversification of the long- and

short-branch clades

Both the LBC and SBC are inferred to have an African

ancestral area. However, our results reveal that these lineages

have different patterns of diversification in both space and

time (Fig. 2; Fig. 3b,c). During the Early Eocene Climatic

Optimum (EECO), numerous speciation events leading to

extant taxa are observed within the LBC, whereas for the SBC

there is a period of apparent stasis (Fig. 2). Speciation in the

SBC is concentrated at more recent nodes of the miliusoid and

Neotropical clades (c. 30 Ma), as is apparent in the SBC LTT

plot (Fig. 3c).

The SBC has more geographic structure than the LBC. In the

former we have four major clades confined to specific regions:

the African short-branch clade (Couvreur et al., 2009)

restricted to Africa; the South/Central American clade (SAC)

restricted to the Neotropics (Pirie et al., 2006); the miliusoid

clade restricted mainly to Southeast Asia (Mols et al., 2004);

and the weakly supported Central American clade (which also

includes the Southeast Asian genus Stelechocarpus) nested

within the miliusoid clade. Finally, the genus Maasia is

restricted to Asia (Mols et al., 2008). The spatial and temporal

differences between the LBC and SBC could reflect alternative

diversification responses to the overall change in ecology and

climate that affected rain forest taxa during the Cenozoic.

Disjunct distributions between the tropics of South America,

Africa and Southeast Asia of clades younger than Gondwanan

break-up are currently often assumed to be the result of a

migration through Laurasia during the EECO, when climatic

conditions supported tropical vegetation at those latitudes

(Wolfe, 1975; Lavin & Luckow, 1993). Indeed, the connections

and climatic conditions at that time would have facilitated

migration between the tropical floras of Africa, Indochina and

North America. Molecular dating analyses, for example in

Malpighiaceae (Davis et al., 2002), Meliaceae (Muellner et al.,

2006), Melastomataceae s. str. (Renner et al., 2001) and Rubi-

aceae (Antonelli et al., 2009), all indicate that these families

have tropical disjunctions with lineages splitting up at a time

consistent with the disruption of boreotropical ranges around

the Eocene–Oligocene boundary. Such a scenario appears to fit

well with the patterns and tempo of diversification found in the

LBC (e.g. Erkens et al., 2009), where numerous splitting events

occurred during the EECO as well as from 45 Ma until 32 Ma

when global temperatures were dropping (Zachos et al., 2001).

Such widespread distribution of tropical rain forests in

northern latitudes would have allowed migration of lineages

amongst Southeast Asia, the New World and Africa, resulting in

a lack of strong geographic clustering within the LBC. Most of

the intercontinental splits found in the LBC are estimated to

have originated during the Eocene (Fig. 2).

Based on a prior age estimation of c. 62–53 Ma for the crown

node of the SBC (Richardson et al., 2004), it was suggested that

distribution patterns within this clade also resulted from

boreotropical geodispersal (Richardson et al., 2004; Pirie et al.,

2006). Such claims could be supported by the presence of seeds

with typical SBC-type spiniform ruminations in the London

Clay, at 50 Ma (Reid & Chandler, 1933; Doyle et al., 2004), but

the dates recovered here for the crown node of the SBC

(32.8 Ma, 95% HPD 40.1–26.1) are more recent. This may

suggest that these seeds represent stem SBC lineages, rather

than the crown group, and that they are therefore not the direct

ancestors of taxa that subsequently dispersed out of Africa. An

alternative explanation, suggested by Su & Saunders (2009), is

that the SBC dispersed ‘out of India’ into Southeast Asia

(McKenna, 1973; Morley, 2000). The out-of-India hypothesis

suggests that plants inhabiting the Deccan plate (India) prior to

its separation from Gondwana ‘rafted’ across the Indian Ocean

during the Cretaceous and then dispersed into the newly

contiguous landmass of Southeast Asia when the plates

collided. Corroborative evidence has been inferred from frogs

(Bossuyt & Milinkovitch, 2001) and plant families such as

Crypteroniaceae (Conti et al., 2002; Rutschmann et al., 2004),

Dipterocarpaceae (Morley, 2003), Melastomataceae (Morley &

Dick, 2003), and Lowiaceae (Kress & Specht, 2006). Evidence

potentially supporting this hypothesis with regard to the SBC

includes putative Annonaceae fossils found in the Maastrich-

tian of India (Bonde, 1993), indicating the presence of the

family in India before its collision with Asia; and the estimated



timing of dispersal of the SBC into Southeast Asia (30–19 Ma;

Fig. 2), which post-dates the collision of the Indian plate with

the Asian continent c. 35 Ma (Ali & Aitchison, 2008).

The results of the ML analysis provide significant support

for the boreotropical dispersal route over the Indian rafting

route. Our model 2, in which India played no role in

explaining the present-day distribution of Annonaceae species,

fitted the data significantly better than the two other models

(M0 and M1), being 4 and 9 log units better, respectively

(Table 3). Thus, given the phylogeny and the biogeographic

models used here, the boreotropics would have been the main

dispersal route of the SBC into Southeast Asia. The fossil taxon

found in India during the Maastrichtian could represent a

lineage that subsequently went extinct during the rapid

movement of India across the Indian Ocean (see below); and

because its rumination is lamelliform, rather than the spini-

form type restricted to the SBC, it might even represent a

different lineage altogether. The split between the African

short-branch clade and the rest of the SBC, estimated at

32 Ma, could be explained by the drastic Oligocene global

temperature drop, which affected rain forest vegetation world-

wide (Morley, 2000; Zachos et al., 2001), effectively breaking

up any direct tropical rain forest connection between Africa

and Southeast Asia (via Europe). However, during the Late

Miocene, changes towards more seasonal climates led to the

disappearance of rain forests across much of India, restricting

them to western parts of the country and Sri Lanka (Morley,

2000). These changes potentially could have led to numerous

extinctions, ultimately weakening the signal in the data (India

contains no endemic Annonaceae genera today). Future

support for either hypothesis should come from a comparative

approach comparing several species-level dated molecular

phylogenies of genera in both Southeast Asia and India. Under

a boreotropical hypothesis, we would expect most Indian

species to be nested within the Southeast Asian ones, whereas

under the Indian rafting hypothesis, we would expect the

Southeast Asian species to be nested within Indian lineages.

The LBC and SBC thus provide contrasting evolutionary

scenarios. The LBC diversified from the Early Palaeogene and

migrated by geodispersal from Africa through the boreotropics

into other major tropical regions, resulting in lower geographic

clustering. In contrast, the SBC started to diversify only during

the Early Oligocene and mid Miocene, and migration events

were limited, resulting in strong geographic clustering.

ACKNOWLEDGEMENTS

We thank Pauline Ladiges, Jim Doyle, Angela Whittaker and

an anonymous reviewer for their comments and improve-

ments to the article. Jing Wang is also thanked for providing

sequence data for Desmos.

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SUPPORTING INFORMATION

Additional Supporting Information may be found in the

online version of this article:

Appendix S1 GenBank numbers and area coding for all taxa

included in the Lagrange analysis.

Appendix S2 Number of missing characters per taxon, per

marker and in total.

Appendix S3 Diversification rates under no extinction

(b = 0) and high extinction (b = 0.95).

As a service to our authors and readers, this journal

provides supporting information supplied by the authors.

Such materials are peer-reviewed and may be reorganized

for online delivery, but are not copy-edited or typeset.

Technical support issues arising from supporting informa-

tion (other than missing files) should be addressed to the

authors.



BIOSKETCH

Thomas Couvreur completed his doctorate under the auspices of the National Herbarium of the Netherlands in 2008, working on

systematics and biogeography of African Annonaceae, and is currently a postdoctoral researcher at the New York Botanical Garden.

In December 2010 he will start as a researcher at the Institut de Recherche pour le Developpement (IRD) in Montpellier, France. His

main research interests focus on evolution, biogeography and systematics of tropical plant families, mainly Annonaceae and palms.

The main research interest of the authors is centred on the systematics, evolution and biogeography of flowering plants, mainly of

tropical lineages.

Author contributions: T.L.P.C., R.H.J.E. and M.D.P. conceived the ideas; T.L.P.C., R.H.J.E., M.D.P., R.M.K.S., Y.C.F.S and L.W.C.

contributed data; T.L.P.C. collected and analysed the data; T.L.P.C., R.H.J.E., J.E.R. and M.D.P. led the writing; all authors made

significant comments on and improvements to the manuscript.

Editor: Pauline Ladiges



Early evolutionary history of the flowering plant family Annonaceae ... · ORIGINAL ARTICLE Early evolutionary history of the flowering plant family Annonaceae: steady diversification

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