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Biogeography is the study of the distribution of life forms
over geographic space and time. Two subdisciplines of bioge-
ography have often been recognized: ecological biogeography
and historical biogeography (Lieberman, 2003; Crisci, 2006;
Lomolino & al., 2010a). New integrative trends in biogeography
as well as the utilization of phylogenetics in both subdisci-
plines have weakened this dichotomy, nevertheless, this review
focuses on the latter, which emphasizes studies on the distri-
butional patterns through time at macroevolutionary scales.
Biogeography has a long and interesting history, and vari-
ous starting points can be selected (Briggs & Humphries, 2004).
One can begin with Alexander von Humboldt (1769–1859), who
is often recognized as the father of plant biogeography. The
publication of his 24-volume work (1805–1837) covering his
five years of exploration in South America (1789–1804) ex-
cited the public as well as the scientific community in Europe
and inspired a whole generation of natural history explorers
to travel around the world, including Darwin, Hooker, and
Wallace (see below).
Charles Darwin’s observations and comparisons (Darwin,
1845) on his five-year around-the-world journey (1831–1836)
stimulated his theory about descent with modifications and its
mechanisms (Mayr, 1982; Crisci & Katinas, 2009). In fact he
dedicated two of the fifteen chapters of the Origin to geographic
distributions (chapters 12 and 13, Darwin, 1859). Darwin (1859)
also acknowledged the importance of migration from one part
of the world to another, the inf luence of climatic changes, and
the many means of dispersal in shaping modern distribution
patterns rather than separate creations in the context of plant dis-
junctions between eastern Asia and North America (Wen & al.,
2010). However, a great deal of the credit for the development
of biogeography as a fact-based science should go to Joseph
Dalton Hooker (1817–1911), a colleague and friend of Darwin,
whose various voyages around the globe such as Antarctica in
Biogeography: Where do we go from here?
Jun We n,1 Richard H. Ree,2 Stefanie M. Ickert-Bond,3 Zelong Nie4 & Vicki Funk1
1 Department of Botany, National Museum of Natural History, MRC166, Smithsonian Institution, Washington, D.C. 20013-7012, U.S.A.
2 Department of Botany, The Field Museum, 1400 South Lake Shore Drive, Chicago, Illinois 60605, U.S.A.
3 UA Museum of the North Herbarium and Department of Biology and Wildlife, University of Alaska Fairbank s, Fairbanks, Alaska
99775-6 96 0, U.S . A.
4 Key Laboratory of Biodiversity and Biogeography, Kunming Institute of Botany, Chinese Academy of Sciences, Kunming, Yunnan
650204, P.R. China
Author for correspondence: Jun Wen, firstname.lastname@example.org
Biogeography is a multidisciplinary science concerned with how and why organisms are distributed as they are on
Earth. It links fields such as systematics, ecology, paleontology, and climatology, and occupies a central position in evolutionary
biology, being fundamental to the study of processes such as speciation and adaptive radiation. Here we provide a brief overview
of some particularly dynamic areas of inquir y and offer some perspectives on future directions for the f ield. We hope that some
historical debates, such as those over the importance of dispersal, or the validity of molecular dating, are finally being put to
rest. Over the last decade, biogeography has become increasingly integrative, and has benefited from advances in statistical
methods for inferring geographic range dynamics in a phylogenetic context, molecular estimation of lineage divergence times,
and modeling lineage bir th and death. These are enabling greater insights into patter ns of organismal diversification in time and
space. In the next decade, analytical challenges are emerging on several fronts. For example, phylogenies are increasing in size
and taxonomic breadth and new sequencing technologies enabling phylogenetic and phylogeographic datasets are increasingly
genomic in depth. In addition, geographic occurrence data are accumulating in online repositories, yet tools for data mining
and synthetic analysis are lacking for comparative multi-lineage st udies. Biogeography is thus entering an era characterized by
phylogenomic datasets, increasingly comprehensive sampling of clades, and interdisciplinar y synthesis. We anticipate continued
progress in our understanding of biodiversity patterns at regional and global scales, but this will likely require greater collabo-
ration with specialists in bioinformatics and computational science. Finally, it is clear that biogeography has an increasingly
important role to play in the discovery and conservation of biodiversity. Lessons learned from biogeographic studies of islands
are being applied to better understand extinction dynamics as continental ecosystems become more fragmented, and phylogeog-
raphy and ecological niche modeling offer innovative paths toward the discovery of previously unk nown species distributions
and priority areas for conservation. The future of biogeography is bright and filled with exciting challenges and opportunities.
biogeography; biogeography data portal; historical biogeography; parametric models; phylogenomics;
Received: 21 July 2013; accepted: 25 Aug. 2013. DOI: http://dx.doi.org/10.12705/625.15
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1839–1843, the Himalayas and India in 1847–1851, Palestine in
1860, Morocco in 1871, and the western U.S.A. in 1877, led to
his development of what was probably the first explicit biogeo-
graphic method, expressed in his discussion of the distributions
of plants in the Southern Hemisphere (see Hooker, 1844–1860).
Hooker’s method was to place species from the areas in question
into groups that summarized their total distribution and then
compare them across localities (Brundin, 1966). After exam-
ining the shared species he came to the conclusion that these
“bands of affinity” demonstrated that there had been a single
center of evolution in the Southern Hemisphere that had been
broken up. Darwin, in contrast, preferred long-distance disper-
sal over a “permanent geography” (Darwin, 1859).
Alfred Russel Wallace (1823–1913) was another great ex-
plorer who used his years of fieldwork, in the Amazon Basin
(1848–1852) and the Malay Archipelago (1854–1862), to de-
velop important concepts about biogeography (Wallace’s line)
and evolution (natural selection and divergence). He was a key
founder of zoogeography, and his six biogeographic regions
of the world based on animal distributions (Wallace, 1876;
modified from Sclater’s treatment of 1858) are still of relevance
today (Brown & Lomolino, 1998; Holt & al., 2013). Over the
next 100 years the concepts of evolution and the role of disper-
sal in geographic patterns were expanded, but there was little
real change in methodology (see Brown & Lomolino, 1998).
Historical biogeography experienced a wave of conceptual
and methodological developments in the 1970s through the 1990s
(see reviews by Morrone & Crisci, 1995; Funk, 2004; Posadas
& al., 2006; Morrone, 2009) based partially on work done in the
1950s and 1960s. These changes were fueled by the introduc-
tion of two new areas of scientific research: (1) the theory of
continental drift and plate tectonics, and (2) the recognition of
the importance of having a phylogeny-based method for evalu-
ating biogeographic patterns. Several analytical biogeographic
approaches became available such as phylogenetic biogeogra-
phy (Hennig, 1950, 1966; Brundin, 1966, 1988), panbiogeogra-
phy (not phylogeny-based; e.g., Croizat, 1962), and vicariance
biogeography (Nelson & Platnick, 1981), which developed into
cladistic biogeography (Humphries & Parenti, 1999). Ronquist
(1994, 1995, 1996) referred to the above approaches as “pattern-
based” methods, because they are based on the idea that taxa
sharing similar phylogenetic and/or distributional relationships
have a shared biogeographic history. Additional examples of the
pattern-based approaches include Brooks Parsimony Analysis
(Brooks, 1985), Bremer’s Ancestral Area Analysis (Bremer,
1992, 1995), and Component Analysis (Nelson & Platnick, 1981;
Page, 1990). However while some biogeographers hold that area
cladograms (a combination of the cladogram of a group of taxa
and their distributions) indicated the past biogeographic history
of the clade others do not use a phylogeny at all.
Each of these methods has its own strengths and weak-
nesses, and they have been previously reviewed (Funk, 2004;
Posadas & al., 2006; Ronquist & Sanmartín, 2011), eliminating
the need to do so here. However there are a few key points that
are relevant to the discussion of the current and future trends
in historical biogeography. One is the disagreement among the
methods on the relative importance of dispersal and extinction.
The cladistic biogeographic approach emphasizes vicariance in
forming biogeographic patterns, but diminishes or ignores the
impact of processes such as dispersal and extinction (Ronquist,
1996). In fact both dispersal and extinction were/are often con-
demned as untestable and unimportant in many biogeographic
papers in the 1980s to today (Nelson & Rosen, 1981; Craw & al.,
1999; Parenti & Ebach, 2009; Heads, 2012). In recent years the
preponderance of well-supported and dated phylogenies that
effectively demonstrate long-distance dispersal makes it clear
that the preference of vicariance over dispersal cannot be used
as a general rule (Lieberman, 2003; Sanmartín, 2003; Renner,
2004a, b; De Queiroz, 2005). There are hundreds of examples
that show that dispersal and vicariance as well as combinations
of both must be considered when developing biogeographic
hypotheses (e.g., Sanmartín & Ronquist, 2004; Wen & Ickert-
Bond, 2009; Wen & al., 2010). The search for general patterns
is made difficult because of the tendency of different groups
of organisms to respond differently to various biogeographic
barriers, and because organisms diversified at different times
in geologic history so they were exposed to different types of
barriers (Wen, 1999; Tiffney & Manchester, 2001; Lieberman,
2003; Sanmartín & Ronquist, 2004).
In the last decade, the vast majority of those that prac-
tice historical biogeography have moved on to adopt what has
been called event-based biogeography because it allows the
data to be used to evaluate various models (Ronquist, 1995,
1996; Sanmartín, 2007; Ronquist & Sanmartín, 2011). Ronquist
(1996, 1997, 2001) introduced dispersal-vicariance analysis
(DIVA) as a quantitative method of parsimoniously recon-
structing ancestral distributions and patterns of vicariance on
a phylogeny using a three-dimensional step matrix. Although
DIVA favors vicariance over dispersal (Ronquist & Sanmartín,
2011), it was, nevertheless, a useful tool to help determine any
underlying patterns in the data. Nylander & al. (2008) proposed
the Bayes-DIVA method, which uses DIVA to reconstruct an-
cestral areas over a sample of Bayesian topologies resulting
from phylogenetic analysis (also see a similar method by Harris
& Xiang, 2009). The Bayes-DIVA method provides a statistical
framework to evaluate the results from DIVA analyses, and
has been used in many empirical studies (e.g., Antonelli & al.,
2009; Jønsson & al., 2011; Nie & al., 2012). It is implemented
in the Statistical Dispersal-Vicariance Analysis (S-DIVA) (Yu
& al., 2010) and Reconstruct Ancestral State in Phylogenies
(RASP) (Yu & al., 2011).
During the last decade, much progress has been made on
developing parametric methods of inferring biogeographic his-
tory that can more fully exploit the information contained in
molecular phylogenies (reviewed by Lamm & Redelings, 2009;
Ree & Sanmartín, 2009; Ronquist & Sanmartín, 2011). These
methods have been more profitably used in combination with
the profusion of time-calibrated trees made available by in-
creasingly sophisticated algorithms of relaxed molecular-clock
analysis and divergence-time estimation (Sanderson, 2002,
2003; Thorne & Kishino, 2002; Renner, 2005; Rutschmann,
2006). These methods for reconstructing range evolution and
divergence times are briefly reviewed in the following sections,
with an eye toward future developments.
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Biogeography and ecology continue to converge in a
number of areas, especially concerning phylogeography and
analyses such as those related to niche modeling, biogeo-
graphic diversifications, and phylogenetic community assem-
bly (Cavender-Bares & al., 2009; Jenkins & Ricklefs, 2011;
Ricklefs & Renner, 2012). Phylogenetic biogeographic analy-
ses that infer geographic range evolution provide a means of
tracing the evolution of geography and ecological tolerances
(Ronquist, 1997; Ree & al., 2005) and the recent and future
development of model-based biogeographic approaches allows
investigators to explore important processes, such as ecologi-
cal interactions and climate changes, in biogeographic infer-
ence (Ree & Smith, 2008; Ree & Sanmartin, 2009; Ronquist
& Sanmartin, 2011). However, biogeographers still need to in-
corporate ecology better especially when exploring the origins
of large-scale biogeographic patterns (Donoghue & Moore,
2003; Ricklefs, 2004; Wiens & Donoghue, 2004; Wiens, 2011).
It is abundantly clear that historical biogeography is an
integrative science that continues to intrigue scientists. Our
goal in this paper is to encourage this fascination by providing
our perspectives on recent advances and by discussing what one
might expect during the next decade. As the methodological de-
tails of pattern-based and event-based biogeographic methods
have been reviewed recently (see Morrone, 2009, and Ronquist
& Sanmartín, 2011, respectively), this paper focuses on current
challenges where we think the field is headed. We hope that it
will encourage discussions on where we are and where we need
to go in our quest to understand the distributions of organisms
through space and time.
PARAMETRIC MODELS OF RANGE
A recent trend in biogeographic research has been the de-
velopment and adoption of methods that use parametric models
for the evolution of geographic ranges in a phylogenetic context.
Some of these extend directly from DIVA, while others adopt
models closer to those employed in studies of character evolution.
An example of the former is the dispersal-extinction-
cladogenesis (DEC) method (Ree & al., 2005; Ree & Smith,
2008), which takes the conceptual framework of DIVA and
applies it to an explicit model of stochastic dispersal and local
extinction in which probabilities of ancestor-descendant range
evolution are a function of phylogenetic branch length (time).
This method thus provides a means of calculating the likelihood
of a phylogenetic tree with geographic range data at its tips. It
also allows various kinds of temporal and spatial information,
such as from fossils, sea levels, climate, and continental posi-
tions, to be brought to bear on establishing model constraints.
For example, the positions of continental landmasses through
time were used to construct temporally stratified constraints on
dispersal in reconstructing the biogeographic histories of the
conifer family Cupressaceae (Mao & al., 2012) and monocot
family Araceae (Nauheimer & al., 2012).
DIVA and DEC are based on the premise that a single lin-
eage may be widespread, i.e., occupy more than one out of a set
of discrete areas, and that ranges develop by dispersal and local
extinction events. By contrast, for some study systems, a more
suitable model is that lineages have only single-area ranges,
and transitions between them are analogous to the evolution
of a multistate character.
This is the case for the Bayesian continuous-time Markov
chain (CTMC) method of Lemey & al. (2009), which is de-
signed for discrete-area phylogeographic analysis in which the
number of areas, and hence the number of potential area-to-area
transition rates, may be large. The method uses a statistical
technique known as Bayesian stochastic search variable selec-
tion (BSSVS), in which a Markov-chain Monte Carlo (MCMC)
sampling procedure determines which rates (cells in the transi
tion matrix) are not supported by the data and may be set to
zero. It integrates over uncertainty in the phylogeny and model
parameters to yield posterior probability estimates for ancestral
areas at internal nodes. The assumptions of Bayesian CTMC
render it best applied to shallow time frames (Lemey & al.,
2010; Drummond & al., 2012; Filipowicz & Renner, 2012).
In the future, we see a particular need for methods that em-
phasize general inferences about range dynamics drawn from
multiple lineages. A promising step in this direction is a Bayes-
ian method for island biogeography (Sanmartín & al., 2008),
implemented in the forthcoming MrBayes v.4.0. This method
takes as input molecular sequence alignments and range data
for multiple clades of co-distributed taxa, and uses MCMC to
estimate carrying capacities (equilibrium frequencies of spe-
cies diversity) and rates of dispersal between geographically
isolated areas (islands). These biogeographic parameters are
estimated simultaneously with the dated tree of each group,
allowing for differences in root ages, models of sequence
evolution, and area-specific dispersal rates. It was originally
presented as a means of studying lineage dynamics in island
systems, but Sanmartín & al. (2010) have also demonstrated
its use in a continental setting.
THE USE OF FOSSILS IN BIOGEOGRAPHIC
Fossils, in recording the occurrence of taxa in geological
time and geographic space, have been important in testing
hypotheses about the biotic connections between areas (Tiffney
& Manchester, 2001; Lieberman, 2003), but their utility in
phylogenetic biogeography has largely been relegated to cali-
brating molecular-clock estimates of lineage divergence times
(Rutschmann & al., 2007; Forest, 2009). In other words, their
use has mostly benefited the temporal, but not spatial, com-
ponent of biogeographic inference on a phylogeny. Statistical
methods for molecular dating continue to be improved, in terms
of methods that implement increasingly complex models of
substitution rate heterogeneity and prior densities for calibra-
tions (Drummond & al., 2006; Drummond & Rambaut, 2007),
and optimized algorithms for large trees (Smith & O’Meara,
2012). Nevertheless, major challenges persist, including the in-
completeness of fossil record, taphonomic biases, and the prob-
lem of accurately deter mining where in a tree a fossil should be
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placed as a calibration point (Magallón, 2004; Ho & Phillips,
2009; Sauquet & al., 2012). Clade age estimates might also
improve if factors such as fossil abundance and stratigraphic
confidence intervals are incorporated into methods and tools
Recent developments may spur progress along these lines
on incorporating the use of fossils in biogeography. In a no-
table shift away from considering fossils solely as post hoc age
constraints applied to internal nodes on a phylogeny, Pyron
(2011) and Ronquist & al. (2012) proposed that fossils should
be explicitly incorporated into phylogenetic analysis as extinct
(non-contemporaneous) terminal taxa, such that the topology
and node ages of a chronogram are estimated simultaneously
based on “total evidence”: namely, a combination of molecular
and morphological data for the extant taxa, and morphological
data and age priors for the fossil taxa. In a Bayesian MCMC
framework, as implemented in MrBayes v.3.2 (Ronquist & al.,
2012), this allows posterior distributions of node ages to be es-
timated while integrating over uncertainty in the phylogenetic
positions of fossil taxa and other model parameters.
We are still at the infancy of exploring how fossil evidence
may be integrated into phylogenetic inferences of ancestral
areas and range dynamics. Just as a fossil placed on a phy-
logeny can be used to constrain a node’s age, it can also be
thought of as a constraint on its ancestral range; in other words,
it records both the time and place of an ancestral lineage (Ree
& Sanmartín, 2009). The spatial component can be encoded as
a constraint in a Lagrange (likelihood analysis of geographic
range evolution) analysis (Ree & Smith, 2008) if the fossil can
be placed at a particular node or branch on the tree; ranges
inferred for the node of interest are consequently required to
include the area of fossil occurrence. In practice, however,
using fossils as node-based spatial constraints entails many of
the same assumptions and potential pitfalls that are associated
with node-based age calibrations.
Looking toward the future, a promising approach that com-
bines total-evidence fossil dating with parametric inference
of ancestral areas is demonstrated by Wood & al. (2013). In
their analyses of archaeid spiders, fossils are treated as non-
contemporaneous terminal taxa in reconstr ucting the phylog-
eny itself (using BEAST) and in estimating ancestral areas
(using Lagrange and DIVA). They argue that treating the fossils
as terminal taxa within a Bayesian framework removes the
subjectivity involved in assigning priors to node calibrations.
Their results, which indicate that diversification of the northern
and southern archaeid lineages was congruent with breakup
of Pangaea, are more precise and sensible than those obtained
when fossils are used only as node constraints.
IN BIOGEOGRAPHY IN THE
Phylogenetic uncertainty has been a challenging issue
for biogeographic inferences (Nylander & al., 2008; Harris
& Xiang, 2009; Lee & al., 2009; Smith, 2009; Harris & al.,
2013). Evolutionary radiations are common in the history of life
and represents hard phylogenetic uncertainty (Linder, 2008;
Alfaro & al., 2009; Funk & al., 2009; Givnish & al., 2011;
Drummond & al., 2012). Much higher phylogenetic resolution
can be achieved for lineages using multigene or phylogenomic
approaches (Moore & al., 2007, 2010; Zimmer & Wen, 2012).
The advent of next-generation sequencing (NGS) has revolu-
tionized genomic and transcriptomic approaches to evolution-
ary biology (Davey & al., 2011). These new sequencing tools
are also valuable for the discovery, validation and assessment
of genetic markers for phylogenetics, hence benefiting studies
of historical biogeography. The rapid advances in plant phy-
logenomics afforded by the speed and decreasing cost of NGS
methodology also may soon become the standard for produc-
tion of large numbers of phylogenetically informative sites for
many previously unresolvable lineages (Straub & al., 2012;
McCormack & al., 2013; also see other papers from a special
issue of the American Journal of Botany, Feb. 2012).
Many labs have been successful in generating near-
complete chloroplast genomes or plastomes on an NGS platform
(Cronn & al., 2008; Parks & al., 2009; Parks, 2011; Straub & al.,
2012). In an analysis of 21 species of strawberry (Fragaria L .)
using plastome data, Njuguna & al. (2013) hypothesized an
eastern Asian origin of the group, while the clade containing
the diploid F. vesca L. subsp. bracteata (A. Heller) Staudt,
the octaploids F. viriginiana Mill., F. chiloensis Duchesne,
and F. ×ananassa (Weston) Duchesne ex Rozier subsp. cunei-
folia (Nutt. ex Howell) Staudt and the decaploid F. iturupensis
Staudt are inferred to have a North/South American origin.
Furthermore, the western North American octaploid F. vesca
subsp. bracteata is inferred as the sister to the remaining North/
South American octaploid/decaploid Fragaria species. The use
of whole plastomes in phylogenomic studies is not without chal-
lenges, for example: large genome sizes in non-model organ-
isms, extensive variation in the proportion of organellar DNA
as compared to the total DNA, polyploidy, and gene number/
redundancy (Cronn & al., 2012). To overcome these challenges
additional approaches for generating targeted enrichment strat-
egies are being developed (summarized in Cronn & al., 2012).
To resolve recent shallow divergences, some labs have
focused on genomic reduction approaches such as reduced-
representation libraries (RRLs; Carstens & al., 2012; Lemmon
& Lemmon, 2012; McCormack & al., 2012; Zellmer & al.,
2012) by sequencing a subset of the genome. McCormack & al.
(2012) showed the utility of the RLL approach to resolve re-
cent divergence in four phylogenetically diverse avian systems.
Using single nucleotide polymorphisms (SNPs) mined from
the hundreds of loci in 20 individuals each from the four avian
systems, they detected a case of ecological speciation in rails
(Rallus), a rapid postglacial radiation in the genus Junco, recent
in situ speciation among hummingbirds (Trochilus) in Jamaica,
and subspecies population structure of white-crowned spar-
rows (Zonotrichia leucophrys) along the Pacific coast. Zellmer
& al. (2012) studied deep divergences of Sarracenia alata
(Alph. Wood) Alph. Wood using the reduced-representation
library approach from 86 individuals across ten populations
from throughout the range of the species. They found that the
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pattern of diversification in Sarracenia L. implies that riverine
barriers are the primary factor promoting diversification in this
group, with divergence across the Mississippi River dating to
60,000 generations before present in the Pleistocene.
Biogeographic analyses can benefit from new genomic
data, which provide resolution at deep phylogenetic levels. For
example, transcriptome sequences recently have been shown
to provide a rich set of characters to produce phylogenies in
eukaryotes and are more eff icient and cost-effective than tra-
ditional PCR-based and EST (expressed sequence tag)-based
methods (Hittinger & al., 2010). Recent studies have demon-
strated the utility of transcriptome data for resolving the re-
lationships of mosquitoes (Hittinger & al., 2010), mollusks
(Kocot & al., 2011; Smith S.A. & al., 2011a), the large group
consisting of turtles, birds and crocodiles (Chiari & al., 2012),
and plants (Wen & al., in press). For example, even though
the phylum has an excellent fossil record, deep relationships
of mollusks have been uncertain when molecular phylogenies
used a few genes. With a transcriptome approach, the major
groups were resolved with highly significant statistical support.
The growing ease of use of NGS and even 3rd-generation
sequencing technologies no doubt accelerates the growth rate
of phylogenetic data matrices (Zimmer & Wen, 2012). Yet an
emerging challenge lies in the interpretation of the strength
and the assessment of the quality of the phylogenetic signal
in constructing phylogenomic trees (Meusemann & al., 2010;
Wen & al., in press). As phylogenetic trees become much big-
ger, it also adds computational complications for biogeographic
inferences. Most existing parametric statistical biogeographic
programs will need to be improved or developed to handle
large and more complex data from phylogenomics. The need of
input from computer scientists into integrated phylogenetic and
biogeographic pipeline development has become more urgent
than ever. With genomic data and difficulties in resolving deep
relationships, supertrees (also see Smith & al., 2009) may be
used for phylogenies. But supertree approaches will not enable
the effective use of statistic biogeographic methods, such as
DEC, because these comparative methods assume accurate
branch lengths calibrated to units of time.
Phylogeography is concerned with range dynamics over
relatively shallow time frames and with relatively fine-grained
distribution data at or below the species level (Avise, 1989,
2000, 2008). Phylogeography bridges ecological and historical
biogeography and has been a highly dynamic subdiscipline;
we thus include a brief discussion on it in this review. Phylo-
geographic analyses can be conducted on single species or on
several unrelated species (comparative phylogeography). The
latter seeks to elucidate the mechanisms responsible for the cur-
rent patterns of phylogenetic relationships and co-distribution
of different unrelated species (Avise, 2000; Riddle & al., 2000;
Soltis & al., 2006).
Phylogeography has developed very rapidly in the last
decade especially concerning statistical phylogeography
(Knowles & Maddison, 2002), which uses statistical ap-
proaches based on coalescent models for parameter estima-
tion and hypothesis testing, even though phylogeography was
earlier criticized as being highly descriptive. The new advances
of statistical phylogeography have been discussed by Hickerson
& al. (2010; also see Lemey & al., 2009, 2010).
So far comparative phylogeographic studies have had
mixed success in identifying common phylogeographic pat-
terns among co-distributed taxa in various regions. Some have
found similar general patterns across multiple co-distributed
taxa (e.g., Hewitt, 2000; Riddle & al., 2000; Smith C.I. & al.,
2011), but many others have found that the histories of dif-
ferent species are much less congruent, especially when the
time or dating component is considered (e.g., Qiu & al., 2011;
Ornelas & al., 2013). As an example, Ornelas & al. (2013) used
comparative phylogeographic analyses to identify patterns
of co-vicariance among 15 species of seed plants, birds and
rodents that are co-distributed in the cloud forest habitats of
northern Mesoamerica. The hierarchical approximate Bayesian
computation (HABC) method as implemented in the program
msBayes (Hickerson & al., 2007) was used to test simultane-
ous versus non-simultaneous divergence of the cloud forest
lineages. Shared phylogeographic breaks were detected that
correspond to the Isthmus of Tehuantepec, Los Tuxtlas, and
the Chiapas Central Depression, with the Isthmus representing
the most frequently shared break among taxa. Yet dating analy-
ses support that the phylogeographic breaks corresponding to
the Isthmus occurred at different times in different taxa. This
complexity is likely attributable to differences among species
in ecological niche requirements and dispersal capabilities.
Phylogeography in plants is generally hampered by the
lack of DNA-sequence regions that provide sufficient varia-
tion in intra-specific lineages to reveal historical patterns.
Recent advances in next-generation sequencing can provide
a fast and cost-effective way to generate multilocus sequences
for phylogeographic analysis. As the sequencing of whole
plastomes via the NGS platform becomes more and more af-
fordable, whole plastomes can be utilized in phylogeographic
analyses in plants. Several other methods such as restriction
site–associated DNA tags (RAD tags; Baird & al., 2008), and
double digest RAD sequencing (ddRAD; Peterson & al., 2012)
have been used recently in various animal groups, and they can
be developed and employed in plant phylogeographic studies
in the near future.
The RAD tags were recently shown to resolve previously
unresolved genetic structure and detect direction of evolution in
the pitcher plant mosquito, Wyeomyia smithii, from a refugium
in the southern Appalachian Mountains following recession
of the Laurentide Ice Sheet at 22,000–19,000 B.P. (Emerson
& al., 2010). RAD sequencing or RADseq uses multiplex-
ing and is a cost-effective way to sequence multiple samples
(about 50 samples) per individual lane using high-throughput
platforms such as an Illumina HiSeq (Baird & al., 2008). It
uses restriction enzymes to shear genomic DNA into smaller
fragments, and ligates adapter sequences (tags) to both end of
the fragments so that primers containing the sequence of the
adapters can be used to sequence the fragment. A drawback of
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the RADseq method is the inability to target a specific frac-
tion of the sampled genome (Peterson & al., 2012). The RAD
tag method provided detailed patterns of phylogeography in
this nonmodel species without any prior genomic data, and
identified incipient speciation and genome-wide variation in
natural populations. It has been recently used to explore plant
evolution (Eaton & Ree, 2013) and phylogenetics (Rubin & al.,
2012; Cariou & al., 2013).
An approach similar to RAD tags, the ddRAD method
(Peterson & al., 2012) is a very cost effective NGS method and
is suited for studies that need a large amount of genomic data
such as single nucleotide polymorphisms (SNPs). Instead of
randomly shearing DNA fragments after the treatment with
restriction enzymes which is done in RADseq, ddRAD se-
quencing uses a double restriction enzyme digestion and a size-
selection for DNA fragments, thereby allowing a more precise
as well as more flexible selection of fragments as compared to
Phylogeographic parameter estimates and model testing
can be integrated with ecological niche models (Hugall & al.,
2002; also see the following section) to elucidate how phylo-
geographic patterns are directly or indirectly linked to abiotic
factors (Kozak & al., 2008). Comparative phylogeography can
be integrated with analyses of community assembly to provide
insights into the processes of range expansion and contrac-
tion of major component taxa in the community (Emerson
& Gillespie, 2008; Cavender-Bares & al., 2009). Like in bio-
geographic inferences at higher taxonomic levels, the statistical
tools for comparative phylogeography across multiple lineages
are still in their infancy (Hickerson & al., 2010).
NICHE MODELS AND BIOGEOGRAPHY
A challenge in biogeographic studies is often to reconstruct
the distribution of a species in geographic space as well as on
a temporal scale and to determine why species are present in
certain areas, but are lacking from others (Wiens & Graham,
2005). Range limits of species or lineages of species are often
determined by ecological factors and, of course, the dispers-
ability of the species (Wiens, 2011, also see Sexton & al., 2009),
but another interesting dimension are the temporal dynamics
of a species. Stochastic processes such as colonization and
extinction dynamics need to be considered when trying to un-
derstand species distributions at both regional and global scales
(Ricklefs, 2004; Chase & Meyers, 2011).
The future synergy between ecology and biogeography
will depend on the integration of scales. Ecological biogeog-
raphers are mainly working at temporal scales that are much
shallower than those typically aimed at in historical biogeo-
graphic studies. Nevertheless, an increasingly large number of
studies are being devoted to niche modeling at both regional
and global scales (Hugall & al., 2002; Graham & al., 2004;
Phillips & al., 2006; Carstens & Richards, 2007; Loarie & al.,
2008; Crisp & al., 2009; Evans & al., 2009; Ackerly & al.,
2010; Loera & al., 2012). Ecological Niche Modeling (ENM) or
Species Distribution Modeling (SDM) combines distribution
data from specimens with data on climate, topography, soil
properties, species interactions, and physiological conditions
to predict the areas where a species could exist, given its eco-
logical requirements. Progress in understanding large-scale
biogeographic patterns will be made by carefully integrating
niche modeling with biogeographic approaches. The inclusion
of trait-based assembly mechanism in studying biogeography
diversifications might also yield important insights (Weiher
& al., 2011).
At a shallow level, by projecting niche models onto recon-
structions of the climate during Pleistocene glacial cycles, it is
possible to identify refugia where species might have weath-
ered such events and understand speciation dynamics at dif-
ferent temporal, spatial and ecological scales (Knowles, 2004;
Knowles & al. 2007; Hope & al., 2013). Another aspect of these
modeling approaches is to predict the future distributions of
species and clades under a climate change scenario, which is
of particular interest to conservation management (Ackerly
& al., 2010; Wiens, 2011; Diazgranados, 2012; Hof & al., 2012).
Niche modeling of paleo-distributions (Maguirea & Stigall,
2009; Wiens, 2011) may also provide an additional line of evi-
dence toward the resolution of biogeographic histories. Smith
& Donoghue (2010) recently used climatic niche modeling and
divergence time estimates to explore the evolution of climate
variables in the Caprifolium clade of Lonicera L. with 25 spe-
cies distributed around the Northern Hemisphere. Divergence
time estimation and biogeographic analyses over the posterior
distribution of dated trees suggest that a widespread ancestor
was distributed across the Northern Hemisphere some 7 to
17 million years ago. Climatic models were projected from one
continent (such as North America) into the others (e.g., Asia
and Europe) to examine whether species living in these areas
occupy similar climates. This study demonstrates the utility
of combining niche modeling with historical biogeographic
analyses and documents significant climatic niche evolution
within a group of species distributed throughout the Northern
Hemisphere. These results suggest a possible model of con-
vergent shift to drier Mediterranean climates in western North
America and Europe for the origin of the Madrean–Tethyan
disjunction pattern (also see review by Axelrod, 1975; Wen
& Ickert-Bond, 2009; Kadereit & Baldwin, 2012), supporting
convergent evolution in some lineages of the Madrean–Tethyan
disjunction in the broad Northern Hemisphere intercontinental
biogeographic disjunction (Wen, 1999, 2001; Donoghue & al.,
2001; Donoghue & Smith, 2004).
Maguirea & Stigall (2009) used ecological niche model-
ing to reconstruct the geographic distribution of species of the
subfamily Equinae in the Great Plains region of North America
during two time slices from the middle Miocene through early
Pliocene. Their method combines known species occurrence
points with environmental parameters inferred from sedimen-
tological variables to model each species’ fundamental niche.
The geographic range of each species is then predicted to oc-
cupy the geographic area within the study region wherever the
set of environmental parameters that constrain the fundamental
niche occurs. They report that patchy geographic distributions
were more common in the middle Miocene when speciation
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rates were high. During the late Miocene, when speciation
rates were lower, continuous geographic ranges were common.
Equid species tracked their preferred habitat within the Great
Plains as well as throughout North America. However, as cli-
mate continued to deteriorate in the late Miocene, extinction
rates increased for species of all range sizes.
It is known that the recently developed niche models have
various sources of error and uncertainties such as model mis-
specification, missing variables, small sample size, and data
error such as misidentifications from publicly available online
data (Barry & Elith, 2006; Lozier & al., 2009). It is also im-
portant to bear in mind that paleo-niche models predict the
potential ranges under the assumption of niche conservatism
(Losos, 2008). Model-based biogeographic inferences can be
used in the future to test ancestral range predictions inferred
based on alternative niche assumptions (also see Crisp & al.,
2011). Also comparative niche modeling analyses across mul-
tiple lineages of taxa with a common biogeographic pattern
such as the eastern Asian-North American disjunctions (Wen,
1999; Wen & al., 2010) and the Madrean–Tethyan disjunctions
(Wen & Ickert-Bond, 2009) may provide insights into extinc-
tion processes in the formation of important intercontinental
disjunct patterns formed in the Tertiary.
GEOGRAPHIC ASPECTS OF LINEAGE
Molecular phylogenies and the relaxed molecular clocks
provide a framework for analyzing species diversif ication pat-
terns and processes (Harvey & al., 1994; Nee, 2006; Moore
& Donoghue, 2009). Statistical methods for inferring rates of
speciation and extinction from time-calibrated phylogenies
have seen dramatic developments over the past decade, and the
trend shows no signs of abating (e.g., Rabosky, 2006; Rabosky
& al., 2007; Alfaro & al., 2009; Wertheim & Sanderson, 2010;
Silvestro & al., 2011). The tempo of lineage diversification has
often been explored using lineage-through-time (LTT) plots,
which are graphical representations of the cumulative number
of reconstructed lineages over time based on a chronogram
(Harvey & al., 1994; Nee, 2006). To test whether the temporal
pattern of diversification in a lineage departs from a constant
rate model, a gamma statistic (Pybus & Harvey, 2000) and/or a
birth-death likelihood (BDL) method (Rabosky, 2006; Rabosky
& al., 2007) are commonly used to test several variable-rate
models against the null hypothesis of constant diversification
rate. The method MEDUSA (Alfaro & al., 2009) has been em-
ployed as an extension to the birth-death likelihood approach
(Rabosky & al., 2007) and allows inference of rate shifts at
one or more topological positions. MEDUSA minimizes the
problem of unresolved incomplete and/or nonrandomly sam-
pled lineages, and is analogous to maximizing the likelihood
while including a penalty for additional parameters (Burnham
& Anderson, 2002). The methodological developments have
stimulated many broad to local-scale diversification analyses,
which have identified numerous radiations throughout the Tree
of Life in the past decade.
Insights into patterns of lineage diversifications using a
dated phylogenetic framework are limited by incomplete sam-
pling, nonrandom sampling, background extinction, and uncer-
tainties associated with divergence time estimates (Rabosky,
2006; Stadler, 2009; Cusimano & Renner, 2010; Wertheim
& Sanderson, 2010; Cusimano & al., 2012). Nevertheless,
nearly complete phylogenies are emerging. Jetz & al. (2012)
present the first complete dated phylogeny of extant bird spe-
cies (9993 species) and explore global patterns and rates of
diversifications. They report the main geographic differences
in diversification rates are east-west hemispheric, rather than
latitudinal (cf. Weir & Schluter, 2007), with average rates dis-
tinctly lower in the Eastern Hemisphere than that in the West-
ern Hemisphere (cf. Xiang & al., 2004 for different results in
plant diversification in eastern Asia and North America). Yet
no significant difference in rates is found between Northern
and Southern Hemisphere species. Also a strong increase in
diversification rate is detected from about 50 million years ago
to the near present, with a number of radiations in the temperate
zone. Furthermore, the past diversification rate shifts are scat-
tered throughout the avian tree and across geographic space.
Leslie & al. (2013) were also able to sample 80% of all
extant conifer species to explore the impact of the large-scale
distribution of the Earth’s landmasses on patterns of biological
diversity in the Northern and Southern Hemispheres. Their
dated phylogeny of conifers, calibrated with well-documented
fossils, suggests a much older distribution of divergence ages in
the Southern Hemisphere than those of the taxa in the Northern
Hemisphere. The distribution and abundance of more recent
divergences in the Northern clades are mostly concentrated to
western North America and southern China in eastern Asia
and are not directly related to the latitudes nor habitat types.
The Southern Hemisphere older clades seem to have survived
in scattered wet environments. The conifer diversif ication pat-
terns are interpreted to have resulted from large-scale differ-
ences in climatic and landscape history.
The analysis of diversification rates in the context of ana-
genetic change, e.g., the evolution of phenotypic or ecological
traits, has been transformed by the development of models
that unite both character evolution and species diversification,
avoiding biases that occur when the two are treated separately.
The first of these was the binary-state speciation and extinction
(BiSSE) model (Maddison & al., 2007), which estimates the
speciation and extinction rates separately for each state of a
binary character as well as the rate of change between states.
BiSSE has been extended in various ways, e.g., to allow for
the analysis of multi-state characters (MuSSE; Fitzjohn, 2012)
and continuous traits (QuaSSE; Fitzjohn, 2010). For biogeo
graphic inference, the BiSSE framework was extended with
principles drawn from the DEC model of geographic range
evolution (Ree & al., 2005; Ree & Smith, 2008) to produce the
geographic-state speciation and extinction (GeoSSE) model
(Goldberg & al., 2011). GeoSSE enables testing of hypotheses
of range-dependent diversification, such as: Are regional dif-
ferences in the standing diversity of a clade due to asymmetry
in diversification or migration? Does range expansion increase
the probability of lineage divergence?
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BiSSE, GeoSSE, and related models offer the prospect of
macro-evolutionary inferences that integrate anagenetic and
cladogenetic processes much more effectively than previous
methods; however, they come with associated caveats related to
data sampling and model complexity (Davis & al., 2013). Most
importantly, they implicitly assume that the phylogenetic posi-
tions of all extant species are known, if not sampled, with the
consequence that gaps in taxon sampling must be accounted for
statistically (Fitzjohn & al., 2009). This is because the models
explicitly incorporate diversification parameters (speciation
and extinction) and thus require unbiased samples of diversity
as inputs. At a more pragmatic level, the mathematical methods
used to jointly infer anagenetic and cladogenetic processes do
not yet scale well with model complexity—that is, for GeoSSE,
the number of potential free parameters increases geometrically
with the number of component areas. This poses significant
computational challenges for even “simple” biogeographic
problems involving a handful of areas.
Empirical application of GeoSSE has been hampered
by such computational considerations, but the simpler
BiSSE method has made inroads into biogeographic studies.
Drummond & al. (2012) evaluate the hypothesis of multiple
radiations in the genus Lupinus L. (Leguminosae), which ex-
hibits some of the highest known rates of net diversification in
plants. They detected three significant shifts to increased rates
of net diversification relative to background levels in the genus.
Bayesian ancestral state reconstructions and BiSSE analyses
indicated that increased rates of speciation are strongly asso-
ciated with the derived evolution of perennial life history and
invasion of the montane ecosystems.
Empirical analyses also showed the importance of bio-
geography in understanding the patterns of species diversity
(Rabosky & al., 2007; Wiens & al., 2009; Almeida & al., 2012).
Analyses in the past decade have often investigated the evo-
lutionary patterns at higher levels (Magallón & Sanderson,
2001; McPeek & Brown, 2007; Smith S.A. & al., 2011b ; Jetz
& Fine, 2012; Jetz & al., 2012). Nevertheless, future work
needs to emphasize analyses of evolutionary radiations and
rate shifts at lower taxonomic scales with complete sampling
and better integration of geographic and ecological parameters
to gain insights into the lineage diversification processes and
mechanisms. Integration of patterns and rates of lineage di-
versifications in the context of space, time and form provides
an important dimension on integrative biogeography and the
mechanisms behind species diversif ication and persistence
(Lexer & al., 2013) and should be emphasized in the future.
Many biogeographic studies involve islands. While neither
the patterns nor the processes of diversification on islands are
unique to islands, it is their special circumstances that make
islands “natural laboratories” for the development and testing
of theories. These laboratories have drawn the attention of a
wide variety of naturalists, many of whom have developed
theories that have furthered our understanding of evolution as
well as biogeography. Perhaps the chief characteristic of im-
portance in islands is their isolation since that influences both
gene flow and colonization. The early, now classic publications
based on magnificent voyages bear careful study since these
naturalists were greatly influenced by the time they spent on
islands. As early as 1778, the writings of Forster introduced the
ideas of species-isolation and species–area relationships. He
was followed by Darwin (1859), Hooker (1867), and Wallace
(1911). More recently MacArthur & Wilson (1967), Carlquist
(1974), and others inspired generations of biogeographers by
introducing conceptual ideas such as adaptive radiation, taxon
cycles, assembly rules, and an equilibrium theory of island
biogeography. Because islands have higher extinction rates than
continental areas, biogeographic studies on islands have played
a big role in conservation biology (Whittaker & al., 2007). Of
course, island biogeography does not just apply to islands but
serves as a model for a variety of ecosystems that are isolated
in some way: sky islands (high-mountain habitats), land-locked
lakes, and disjunct populations of wide ranging species. This
ensures that biogeographic concepts developed on islands can
be tested on a broader scale.
Island biogeography is undergoing a resurgence as is evi-
denced by two recent standalone meetings that focused mostly
on the current research and future possibilities: “The theor y
of island biogeography revisited” (Losos & Ricklefs, 2010)
and in 2011 the conference on “Evolution of life on Pacific
islands and reefs: Past, present and future” (http://botany.si.edu
/events/2011_pacific/). Currently there is an ever-increasing
amount of research on islands combining systematic, ecologi-
cal, and evolutionary studies; one example is the work on com-
munity assembly (Emerson & Gillespie, 2008). Also, there is a
push to develop an Integrative Theory of Island Biogeography
that works across scales (Lomolino & al., 2010b). Finally, the
development of testable hypotheses for long-distance dispersal
may temper some of the negative discussions on dispersal vs.
vicariance (Gillespie & al., 2012) especially with the addition
of Bayesian methods (Sanmartín & al., 2008). These advances
ensure that island studies will continue to provide theories
that can then be tested in continental ecosystems (Sanmartín
& al., 2010).
EMPIRICAL BIOGEOGRAPHIC ANALYSES
AT GLOBAL AND LOCAL SCALES
As molecular phylogenetics moves into the next decade
with better sampling and increased resolution, it will be logical
for biogeographers to explore more empirical biogeographic
analyses at the global scale (e.g., Xiang & al., 2004; Jønsson
& al., 2011; Jetz & al., 2012; Leslie & al., 2013) which will
enable the analyses of large-scale patterns in space and time.
The availability of user-friendly software packages should
inspire more biogeographic analyses at both the global and
local scales. Empirical biogeographers need to emphasize
hypothesis-testing in their biogeographic analyses, as mod-
els are becoming increasingly more complex, sophisticated
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and realistic (Crisp & al., 2011). The models can be used for
hypothesis testing by varying the degree of parameters within
a statistical framework (Nathan & al., 2008).
Increased interest in empirical biogeographic analyses may
also be due to much easier sampling in different continents
due to easier travel to more remote places and more efficient
communications and collaborations among colleagues. Sci-
ence advancement in developing countries that harbor rich
biodiversity is vitally important for healthy development of
biogeography as a field, especially at the local level and in the
subdiscipline of conservation biogeography (Whittaker & al.,
2005). It will be more fruitful if western biogeographers can
train local biologists and students and involve them in the field
as well as during analytical phases of biogeographic studies,
and inspire the interests of local biologists to pursue biogeo-
In-depth biogeographic and phylogeographic analyses
have been increasingly conducted in various regions in devel-
oping countries, especially with the advancement of in-country
biogeographic expertise, such as in China, Brazil, Argentina,
and Mexico, as witnessed by many excellent publications led by
colleagues there (e.g., Fiaschi & Pirani, 2009; Morrone, 2009;
Xie & al., 2009; Hoorn & al., 2010; Yu & al., 2010; Qiu & al.,
2011; Nie & al., 2012; Ornelas & al., 2013). Yet it is necessary
to enhance capacity building in biogeography in many other re-
gions, especially in mega-diverse regions such as Indonesia, the
island of New Guinea, the Philippines, Vietnam, Madagascar,
India, many parts of Africa, and other parts of the Neotropics
such as Colombia, Peru, and Bolivia. The international bioge-
ography community needs to establish coordinated efforts in
capacity building and training in developing countries.
Large volumes of distributional, genetic, phylogenetic,
ecological, and fossil data are accumulating in online data-
bases (e.g., GBIF - www.gbif.org/; Museum collection records
such as those from the National Museum of Natural History
- http://collections.mnh.si.edu/search/, TreeBase - treebase.org;
GenBank - www.ncbi.nlm.nih.gov/genbank/; World Climate
Data - www.worldclim.org/; U.S.A. National Phenology Net-
work - www.usanpn.org/; Time Tree Of Life - www.timetree
.org/; Paleobiology - paleodb.org/; Barcode of Life - http://
www.barcodeoflife.org/). As a result, it seems inevitable that
data mining methods will become essential tools of the trade
for biogeographic research. In the phylogenetic front, Peters
& al. (2011) offered a bioinformatics pipeline for retrieving,
processing, filtering, editing and analyzing large amounts of
sequence data from GenBank in a phylogenetic context, with
its open nature and applicability to any taxonomic group of
interest. However, while the potential increase in data for bio-
geographic studies using such online resources is huge, one
must keep in mind that such online data are not the same as
the personally developed much smaller amounts of data that
individual scientists and groups have accumulated (Soberon
& Peterson, 2004; Lozier & al., 2009). For instance, in many,
if not most, online portals no one has checked the identifica-
tions of the specimens: some are even made up of the original
catalogue records and so have many misapplied names. Also
important is that the georeferencing (prior to the common use
of GPS devices) was often done based on gazetteer records of
the nearest landmark. All these data must be vetted carefully
before they can be used.
Even though there are many current databases available
that contain biogeographic information, none of them currently
focuses on biogeography. The biogeography community needs
to develop such a data portal (Fig. 1) with biogeography as the
core, one that has the capacity to integrate data from phylogeny,
ecology, paleobiology, specimens, distribution, and genomics,
and synthesize the biogeographic diversification of plants and
animals. The portal needs to be effective to disseminate the
biogeographic data to the scientific community, guide conser-
vation efforts, and educate the public about the exciting results
of biogeography! Perhaps an organization like the International
Biogeography Society (IBS) should be involved in developing
such a portal.
International biogeography data portal — toward a vision of a
data core with biogeography as its central mission, with a few exem-
plar data sources.
Choice of Inference Methods
(DEC, GeoSSE, BEAST, MrBayes …)
Elucidate evoluon of past
& present distribuon,
guide conservaon eﬀorts,
Global Climate Change GenBank
TimeTree of Life
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Biogeography has become increasingly integrative and is
closely linked to systematics, ecology, paleontology, and con-
servation biology. It has a central role in evolutionary biology
and tackles questions on space, time and form. The investiga-
tion of many processes of evolution such as adaptive radiation
(Gavrilets & Losos, 2009; Losos, 2010; Givnish & al., 2011;
Diazgranados, 2012), rates of evolution (Knope & al., 2012),
and speciation (Avise & al., 1987; Barraclough & al., 1998;
Losos & Glor, 2003; Pyron & Burbrink, 2010) can only be
examined within the context of biogeography. Phylogeography
and ecological niche modeling using recent locality records and
readily available environmental coverage data offer innovative
potential for the discovery of unknown distributional areas and
unknown species (e.g., Raxworthy & al., 2003). The combina-
tion of biogeography and niche modeling is powerful in identi-
fying areas for conservation (Crisp & al., 2009; Ackerly & al.,
2010). In addition, islands have had a higher rate of extinction
than continents, partially because of their isolation. However
the rates of extinction in continental ecosystems are rising,
mostly because of ongoing fragmentation of ecosystems creat-
ing virtual islands or habitat islands. Predictive models from
island biogeography are being used to understand the dynam-
ics in these habitat islands (Whittaker & al., 2005, 2007). The
new subdiscipline of conservation biogeography has emerged,
which applies the concepts and methods of biogeography to ad-
dress conservation problems (Ladle & Whittaker, 2011; Herzog
& al., 2013).
The last decade has witnessed the development of bio-
geographic methods and the integration of biogeography with
diverse sources of data associated with the development of para-
metric methods. In turn, global and local patterns of biogeogra-
phy are once again being rigorously tested. Meanwhile, advances
in the fields of molecular dating and historical biogeography can
be combined to provide insights into patterns of species diver-
sification across both time and space, with the development of
new methods to estimate rates of speciation and extinction from
phylogenetic data. We envision more statistical methods to be
developed in the phylogenomic era of biogeography with very
large datasets and big phylogenies. Biogeography is moving
toward multidimensional syntheses of geography, phylogeny,
ecology, geology, paleontology, physiology and genomics. In
this regard, powerful statistical methods need to be developed
to integrate data of biogeography, geology, diversification, trait
evolution and ecology, and to explore the mechanisms of species
diversification and persistence across space and through time. A
few recent studies (e.g., Hoorn & al., 2010; Almeida & al., 2012;
Jetz & Fine, 2012; Jetz & al., 2012; Leslie & al., 2012; Holt & al.,
2013) have illustrated a definite trend in that for certain clades, it
is now (or soon will be) feasible to generate near-complete dated
phylogenies and global-scale datasets, which allow large-scale
patterns to emerge. With rapid advances in empirical biogeog-
raphy of many lineages, multi-lineage synthesis is needed for
various biogeographic regions as well as at the global scale in
the next decade. Some broader syntheses have been produced
for certain regions (Hughes & al., 2013).
We thank IAPT and the organizers of the symposium “Where is
Plant Systematics Headed in the Next Ten Years?”, held at the Botany
2012 Meeting, for the invitation to par ticipate in the symposium and
prepare a paper. We are grateful to Mauricio Diazgranados, Dick
Olmstead, Beryl Simpson, Tod Stuessy and Editor-in-Chief Joachim
Kadereit for their constructive comments.
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