Hypothesis testing in biogeography

Abstract

Often, biogeography is applied only as a narrative addition to phylogenetic studies and lacks scientific rigour. However, if research questions are framed as hypotheses, biogeographical scenarios become testable. In this review, we explain some problems with narrative biogeography and show how the use of explicit hypotheses is changing understanding of how organisms came to be distributed as they are. Developing synergies between biogeography, ecology, molecular dating and palaeontology are providing novel data and hypothesis-testing opportunities. New approaches are challenging the classic 'Gondwana' paradigm and a more complicated history of the Southern Hemisphere is emerging, involving not only general drivers such as continental drift and niche conservatism, but also drowning and re-emergence of landmasses, biotic turnover and long-distance colonization.

Full text

Hypothesis testing in biogeography
Michael D. Crisp
1
, Steven A. Trewick
2
and Lyn G. Cook
3
1
Research School of Biology, The Australian National University, Canberra, ACT 0200, Australia
2
Institute of Natural Resources, Massey University, Palmerston North, New Zealand
3
The University of Queensland, School of Biological Sciences, Brisbane, Qld 4072, Australia
Often, biogeography is applied only as a narrative addi-
tion to phylogenetic studies and lacks scientific rigour.
However, if research questions are framed as hypothe-
ses, biogeographical scenarios become testable. In this
review, we explain some problems with narrative bio-
geography and show how the use of explicit hypotheses
is changing understanding of how organisms came to be
distributed as they are. Developing synergies between
biogeography, ecology, molecular dating and palaeon-
tology are providing novel data and hypothesis-testing
opportunities. New approaches are challenging the clas-
sic ‘Gondwana’ paradigm and a more complicated his-
tory of the Southern Hemisphere is emerging, involving
not only general drivers such as continental drift and
niche conservatism, but also drowning and re-emer-
gence of landmasses, biotic turnover and long-distance
colonization.
What is biogeography?
Biogeography is the study of the distribution and evolution
of organisms through space and time [1]. New methods
have given impetus to the discipline: for example, geo-
graphic information systems (GIS) for spatial analysis
[2]; Bayesian molecular phylogenetics for dating diver-
gences between lineages [3]; and integrative models for
reconstructing distributional change through evolutionary
time, using either maximum likelihood [4] or Bayesian
inference [5]. Above all, renewed recognition that ecologi-
cal factors (e.g. climatic tolerance and dispersal limitation)
underlie deep historical events (i.e. speciation, extinction
and distributional change) [6,7] has rekindled interest in
old questions, such as ‘how do ecological factors influence
the processes of vicariance and long-distance dispersal and
establishment (LDDE)?’ (see Glossary) [6–8]. It has also
stimulated new questions, such as ‘what is the role of niche
conservatism in large-scale community assembly?’ [8–10].
In the beginning, with Wallace and Darwin, biogeography
was an exploration of evolution and it is popular today
because, with new methods, it can open windows on the
geographical dimensions of speciation. Although hypothe-
ses about ancient ecological processes are not testable by
direct observation or experiment, their predictions about
present-day biota can potentially be tested. These include
predictions about distributional patterns, fossils, likeli-
hoods of dispersal, and the shapes and timing of phyloge-
nies [11].
A purely inductive approach (‘pattern before process’) is
not science
Unfortunately, biogeography often lacks rigour when it is
presented as a geo-historical narrative for a single taxon,
commonly as an addendum to a phylogenetic analysis.
Biogeography deals with historical events that can neither
be observed directly nor manipulated experimentally, and
this limitation has been used to justify inductivism; that is,
the view that researchers should first observe and analyse
the present-day pattern and only then might explanations
emerge in terms of historical processes (‘pattern before
process’) [12,13]. In a commonly used inductivist approach,
Opinion
Glossary
Area cladogram: a phylogeny in which the names of the organisms at
the tips are replaced by those of the areas in which they occur (e.g.
[13,19]).
Ancestral area reconstruction (AAR): inference of hypothetical ances-
tral areas at the internal nodes (and root) of a phylogeny by ‘optimiz-
ing’ from known areas at the tips of an area cladogram. Several
methods are used for AAR, including parsimony and increasingly
complex models using maximum likelihood and Bayesian inference.
Biotic turnover: extinction and replacement of floras and faunas in
the fossil record, usually driven by global environmental change.
Crown age: the age of the most recent common ancestor shared by
the extant species of a monophyletic lineage. The crown age of a
lineage might be considerably younger than its stem age (Box 3,
Figure Ia). See also ‘Stem age’.
Stem age: the time when a lineage diverged from its sister group;
that is, from the lineage that includes its nearest living relatives. See
also ‘Crown age’.
Long-distance dispersal and establishment (LDDE)*: allopatric (geo-
graphical) speciation caused by an exceptional dispersal event,
establishing a new population on the far side of a barrier that
sufficiently limits subsequent gene flow between the parent and
daughter populations. See also ‘Vicariance’.
Niche conservatism: the notion that major ecological niches are
more conserved than expected through evolutionary time is based
on the observation from phylogenetic studies that major niche shifts
have been relatively rare [9].
Vicariance*: allopatric (geographical) speciation caused by the orig-
ination of a barrier within the range of the ancestral species, dis-
rupting gene flow between the now separated subpopulations. See
also ‘LDDE’.
West Wind Drift: the strongly asymmetrical flow of wind and ocean
currents from west to east in the temperate latitudes of the Southern
Hemisphere, thought to be responsible for directionally biased LDDE
in that hemisphere [19,20].
*Note that allopatric speciation requires processes in addition to
those that cause the disjunction and establishment of disjunct
populations. See examples in main text; for example, plant species
shared by Tasmania and New Zealand. However, the speciation
processes should be similar under either the vicariance or the LDDE
model.
Corresponding author: Crisp, M.D. (mike.crisp@anu.edu.au).
66 0169-5347/$ –see front matter ß2010 Elsevier Ltd. All rights reserved. doi:10.1016/j.tree.2010.11.005 Trends in Ecology and Evolution, February 2011, Vol. 26, No. 2

Box 1. The pattern-first and hypothesis-testing approaches can lead to different conclusions
A common question in biogeography asks ‘what is the geographical
origin of taxon A?’ Recent examples include Nilsson et al. [65] in
respect of marsupials and Brown et al. [48] in respect of Rhododen-
dron sect. Vireya. Here, we illustrate two different approaches to
formulating and testing biogeographical hypotheses, using the
Southern Hemisphere Callitroid clade of the cypress family (Cupres-
saceae) as a hypothetical example. Each approach results in a
different interpretation of the biogeographical history.
The first is a ‘pattern before process’ approach (Figure Ia), in which
the distributions of extant taxa are mapped at the tips of a phylogeny
and ancestral areas are reconstructed at internal nodes using any of
several methods [14]. Here, both parsimony (mapped in Figure Ia) and
maximum likelihood infer that the common ancestor of the Callitroid
clade probably originated in Australia and that its descendants
subsequently dispersed to New Zealand (green), New Caledonia
(red, twice), Patagonia (purple, three times) and South Africa (yellow).
However, this commonly used trait-mapping approach fails to
consider alternative hypotheses or data that are independent of the
tree.
The second approach (Figure Ib) uses the same molecular
phylogeny to illustrate how process-based hypothesis testing gives
a different conclusion. Fossils can be used to test vicariance versus
dispersal hypotheses by adding extinct lineages and their distribu-
tions to the phylogeny (Figure Ib), and by adding a time calibration
to the tree. Here, interpretation of fossils indicates that most
Callitroid genera were once more widespread across Gondwana
but have suffered extensive extinction [56–58].Knowingthis
enables one to frame hypotheses of vicariance for some nodes
(those with daughter lineages distributed among continents) and
assess them using the tests detailed in Box 2. This approach leads,
in many cases, to the conclusions that vicariance (nodes labelled
V?) cannot be rejected as the cause of divergence. For example,
Fitzroya cupressoides in Patagonia (extant) probably diverged from
its sister Fitzroya tasmaniensis in Australia (now extinct) between
30 and 40 mya, about the time when these landmasses separated as
East Gondwana broke up (yellow bar). Not all labelled divergences
overlap the geological separation bars (e.g. Papuacedrus,Wid-
dringtonia and Austrocedrus) but their confidence intervals prob-
ably would, in which case vicariance hypotheses could not be ruled
out for these either. (This is a hypothetical example and the
relations of fossils have not yet been fully verified by experts. A
more rigorous approach to estimating divergence times would also
use the fossils to calibrate nodes in a molecular dating analysis; e.g.
using BEAST [3].)
[()TD$FIG]
Aust - SAm - Ant
Gondwana - NZ
0
102030
40
506070
80
90
100
Million years before present
Character: Areas
Key:
Parsimony reconstruction
Unordered
Northern Hemisphere
Patagonia
Australia - New Guinea
New Zealand
New Caledonia
Africa
Antarctica
Gondwana
Actinostrobus
Callitris
Neocallitropsis
Fitzroya
Diselma
Widdringtonia
Austrocedrus
Libocedrus plumosa
Libocedrus bidwillii
Pilgerodendron
Libocedrus yateensis
Papuacedrus papuana
Cupressoids
Taxodium
Glyptostrobus
Cryptomeria
(a)
Actinostrobus
Callitris leaensis X
Callitris
Neocallitropsis
Fitzroya
Fitzroya tasmanensis X
Diselma
Widdringtonia americana X
Widdringtonia
Austrocedrus tasmanica X
Austrocedrus
Libocedrus sp X
Libocedrus acutifolius X
Libocedrus spp X
Libocedrus plumosa
Libocedrus bidwillii
Pilgerodendron
Libocedrus yateensis
Papuacedrus shenii X
Papuacedrus sp X
Papuacedrus papuana
Papuacedrus australis X
Cupressoids
Taxodium
Glyptostrobus
Cryptomeria
Papuacedrus prechilensis X
(b)
V?
V?
V?
V?
CC CC
TRENDS in Ecology & Evolution
Figure I.(a) Ancestral area reconstruction using parsimony to map distributions of cypresses on a phylogeny redrawn from [66] infers an Australian origin for the
Callitroid clade followed by dispersal to other Southern Hemisphere landmasses. (b) Adding relationships of fossils (and thus a time calibration) to the phylogeny leads
to a failure to reject vicariance hypotheses based on the break up of Gondwana. The blue-shaded bar indicates separation of Zealandia from the remainder of Gondwana
and the geological origin of New Zealand [26,59]; the yellow-shaded bar indicates separation of Australia, Antarctica and Patagonia. Extinct taxa are labelled with cross
symbols. The most recent common ancestor of the Callitroid clade is labelled ‘CC’. Divergences for which vicariance is not rejected as the cause of the disjunction are
labelled ‘V?’.
Opinion Trends in Ecology and Evolution February 2011, Vol. 26, No. 2
67

ancestral areas are reconstructed at internal nodes of the
phylogeny; for example, using ancestral area reconstruc-
tion (AAR) methods (reviewed in [14,15]), which are some-
times combined with relaxed molecular-clock dating of
nodes (Box 1).
Conceptually, AAR does not differ from mapping pheno-
typic traits (‘standard’ or ‘morphological’ characters) onto
phylogenies. Geographical distribution is also a trait that
can be modelled and, similar to any trait, it can change
through time. Thus, standard ancestral trait reconstruction
models, based on parsimony, maximum likelihood and
Bayesian inference [5,16], have been used in biogeography.
Subsequently, complex biogeographical models have been
developed to take account of: (i) geological, ecological and
geographical factors relevant to distributional change; and
(ii) causal links between distributional change (e.g. vicari-
ance or LDDE), speciation and extinction ([4,17,18] and
references therein). AAR models differ in their (sometimes
unspecified) assumptions about processes, such as whether
speciation is constrained to accompany LDDE or whether
vicariance is favoured over LDDE [14]. Methods also differ
in whether, and to what extent, they enable ancestors to
occupy multiple areas (a required assumption for vicariance
[14]), and whether they model directional bias in LDDE
[19,20]. Ancestral area reconstructions are then typically
used to describe a sequence of distributional change through
time. Correlates between the inferred distributional
changes and ‘events’, such as continental break up or climate
change, are sought and often inferred as causative.
A logical problem with this type of approach, which is
not exclusive to biogeography, is that a finite set of obser-
vations can be consistent with an almost unlimited set of
alternative explanations [1,21–23]. Moreover, ‘observa-
tions’ could be subjective or biased if the observer filters
the data through an explanatory theory, even if this pro-
cess is subconscious [1,21]. Proponents of inductive (‘pat-
tern before process’) biogeography commonly work from
implicit process assumptions, usually of vicariance [22,23].
The inductive approach has been criticised as storytelling
and unscientific: alone, it cannot progress beyond being a
speculative first attempt to understand the biogeography
of a group, because it tends to generate, rather than test,
hypotheses [1,13].
Biogeography becomes a science in the Popperian sense
when it frames and tests hypotheses [1,13]. Biogeographi-
cal knowledge can progress beyond the inductive hypothe-
sis-creation stage by framing restrictive propositions and
testing specific predictions that can rule out many of the
alternatives [1]. Thus, an untestable question, such as
‘where did Nothofagus (southern beeches) first evolve?’
does not express a specific prediction and could be replaced
by a testable hypothesis, such as ‘the disjunction between
Nothofagus sister taxa in Australia and South America
was caused by vicariance’. A hypothesis about an unob-
served process can be tested if it predicts an observable
outcome (e.g. pattern or timing) that contrasts with that
from an alternative hypothesis [24]. How biogeographical
questions are phrased dictates how they are addressed,
and can affect the interpretation of past events (Box 1).
To avoid circularity, it is important to test a hypothesis
using data that are independent of those used to frame it in
the first place [23,24]. For example, the hypothesis that the
entire terrestrial biota of New Zealand established and
diversified after the Oligocene was proposed on the basis of
multiple lines of geological evidence that indicate total
marine inundation of the landscape before 23 million years
ago (mya) [23,25]. This hypothesis can be tested by its
prediction that no terrestrial lineage occupied New Zeal-
and continuously through the Oligocene. The drowning
hypothesis would be falsified by the existence in New
Zealand of an endemic radiation with a crown age reliably
dated to the Oligocene (23–34 mya) or older [23,26]. Phy-
logenies used for the test should be calibrated using inde-
pendent data (e.g. from fossils or stratigraphy), rather than
the non-independent geological data used to erect the
drowning hypothesis.
Here, we discuss some specific approaches to testing
hypotheses, using as examples the well-known models of
vicariance and dispersal that have been used to explain
disjunct distributions. Examples of biogeographical hy-
potheses and their testable predictions are detailed in
Table S1 (supplementary material online).
Testing alternative hypotheses to explain current
disjunct distributions
Vicariance and LDDE are both geographical (allopatry-
based) explanations for the process of speciation and,
although both probably had a role in the diversification
of lineages [8,27], many biogeographers treat them as
exclusive alternative models. Vicariance, by definition,
results from processes that restrict the dispersal of indi-
viduals within the range of a species [6] and this can occur
only after the range of a species has already expanded via
dispersal. Long-distance dispersal and establishment
requires that organisms overcome some barrier to gene
flow, but infrequently enough that populations on either
side of the barrier (or filter) speciate [19].
The relative contributions of dispersal and vicariance to
distributions of organisms in the Southern Hemisphere,
where closely related terrestrial species are disjunct across
wide oceanic gaps, have been debated extensively. Follow-
ing the recognition of plate tectonics [28], these distribu-
tions have often been explained as arising by vicariance
through continental drift [13,29]. Vicariance biogeography
under this scenario postulates that, as Gondwana broke
up, populations were sundered, isolated on the newly
formed landmasses and subsequently diverged to become
different species [13,29]. This scenario requires that each
species was widespread across much of Gondwana before
the break up of the supercontinent. Vicariance has mean-
ing in the evolutionary sense only when it is tied to a
divergence event. Thus, continental drift leading to the
separation of lineages across oceans is not a cause of
vicariance if the lineages were already diverged by the
time continental drift separated the landmasses.
The alternative LDDE model for transoceanic disjunc-
tions posits that, driven by rare events (such as storms or
tsunamis), organisms have been carried across gaps, such
as oceans, that are not normally traversed. The model also
allows for cases where propagule dispersal is more fre-
quent but survival and establishment is rare (possibly
linked with ecological and genetic factors) [30,31]. With
Opinion Trends in Ecology and Evolution February 2011, Vol. 26, No. 2
68

no (or minimal) gene flow, the separated (allopatric) popu-
lations evolve independently and, ultimately, speciate.
Tests of vicariance
If the pattern and timing of the origin of potential vicari-
ance events are known from geological data, vicariance
hypotheses are testable because they make several pre-
dictions (Table S1 in Supplementary Material Online). The
advent of molecular dating has led to the ability to test the
timing of divergences and thus test hypotheses of vicari-
ance (Box 2). Surprisingly, most transoceanic plant dis-
junctions [8] and many of those in animal taxa [26,32,33]
have been determined to be asynchronous or too young to
be fully explained by the break up of Gondwana. This
applies even in the case of iconic taxa, such as Nothofagus
[34] and kauri pines (Agathis)[35] in New Zealand,
ostriches in Africa [36] and primates and rodents in South
America [37].
Importantly, divergences can be too old to have been
caused by a particular geological event [26,31]: the predic-
tion of timing requires a two-tailed test (Box 2). By this
criterion, many of the cases of species-poor lineages that
are presented as evidence of long-term occupancy resulting
from vicariance, for example, tuatara in New Zealand and
Amborella in New Caledonia, fail the test of a vicariance
explanation [26].
Another important prediction from a hypothesis of vi-
cariance is that multiple lineages will probably be affected
by the origin of the putative barrier [7,29]. Thus, a further
prediction is that there should be divergences in multiple
taxa either side of that barrier dating to that time [7,38,39].
For example, alternative vicariance hypotheses have been
proposed for the middle of the Baja Peninsula, California,
putatively owing to either climate change during the Pleis-
tocene or marine incursion during the late Miocene–early
Pliocene [38]. These were tested for coincident divergence
times across the barrier in multiple animal and plant taxa,
with some support found for vicariance at the earlier time
in nine taxa [40].
Are hypotheses of dispersal testable?
Commonly, dispersal is inferred as the default explanation
of a biogeographical disjunction following rejection of a
vicariance hypothesis, for example by molecular dating.
Therefore, it is important that LDDE hypotheses should be
testable using independent evidence. Despite claims that
hypotheses of dispersal are not testable [13], careful fram-
ing of hypotheses enables some to be tested. As illustrated
by the following examples, ecology has an increasing role in
testing dispersal hypotheses in historical biogeography.
Example 1. Model-fitting approaches can be used to test
dispersal-based hypotheses. For example, Sanmartı
´net al.
[20] used parsimony-based tree fitting to test the predic-
tion [19,41,42] that atmospheric and oceanic West Wind
Drift should cause an easterly bias in plant dispersals in
the Southern Hemisphere. Inferred LDDE events in 23
phylogenies were significantly asymmetrical in the pre-
dicted direction, rejecting the null hypothesis of equal rates
of inferred dispersal in both directions, as determined from
randomizations.
Example 2. Stepping-stone dispersal routes have often
been inferred to explain what, for some, might be seeming-
ly impossible LDDE events across extreme barriers. This
approach has been especially adopted for terrestrial taxa
that are disjunct across oceans, such as between Australia,
New Zealand and New Caledonia [43,44], Antarctica and
Africa via the Kerguelen Plateau [36] and between Africa
and Madagascar [32]. However, stepping-stone routes
might be even more problematic than a single jump across
a wider gap, because a stepping-stone hypothesis assumes
that an intermediate, reproducing population was large
enough and existed long enough to produce a ‘propagule (or
migrant) pressure’ [30] sufficient to colonize the next land-
mass along the chain. For example, it has been suggested
that a single extreme LDDE event could be more probable
than multiple shorter LDDE (stepping-stone model)
events. Long-distance seed ‘dispersal kernels’ (i.e. proba-
bility distributions of LDDE) appear to be ‘fat tailed’
[45,46]; that is, extreme LDDE is not much less probable
than LDDE over much shorter distances. This is partly
because of stochasticity and partly because of infrequent
atypical processes (e.g. cyclones and tsunamis) [45]. Given
that probabilities multiply in a chain of independent
Box 2. Tests of vicariance are two-tailed
Divergence times in molecular phylogenies can be used to test
hypotheses of vicariance [27]. Vicariance hypotheses predict that the
divergence time between taxa on either side of a barrier should
coincide with the timing of the origin of that barrier. The test is two
tailed. Vicariance is rejected if the divergence between the taxa is
too young (post-dates the origin of the barrier) or too old (pre-dates
origin of barrier) and, thus, the barrier could not have caused the
divergence (Figure I). The test of vicariance is explicit as it addresses
a specific divergence (node) in the phylogeny, which is hypothe-
sized to be caused by the origin of a particular barrier. A rejection of
one vicariance event does not equate to ‘vicariance does not explain
the distribution of this taxon’. It can reject only the hypothesis that
‘vicariance event X explains node Y’.
[()TD$FIG]
0
20
40
60
80
100
Geological timing
of vicariance
(Australia-South America)
Geological timing of vicaria
-nce (Australia/South
America-New Zealand)
Australia
South America
New Zealand
Australia
South America
New Zealand
Australia
South America
New Zealand
Australia
South America
New Zealand
Ma
(a) (b) (c) (d)
Current geographic
distribution of lineage
TRENDS in Ecology & Evolution
Figure I. Four scenarios showing different timing of divergences between
three lineages. Each phylogeny enables the testing of two hypotheses of
vicariance: one between South America and Australia (with red confidence
interval bars) and another between Australia + South America and New
Zealand (with dark-blue confidence interval bars). All vicariance hypotheses
cannot be rejected in (a) and (b) because the divergence-time error bar
overlaps the relevant geological time bar in each case. In (c) and (d), all
vicariance hypotheses are rejected because the respective error bars and
divergence time bars do not overlap.
Opinion Trends in Ecology and Evolution February 2011, Vol. 26, No. 2
69

events, a single, long LDDE is likely to be more probable
than are multiple, shorter steps. Using the hypothetical
dispersal kernel of Nathan ([45]: Figure 2, corrected ver-
sion, published 17 October 2006), the probability of a single
seed arrival over 500 km is P=10
–16
and that of a single
seed arrival over 1000 km is P=10
–18
. However, the
probability of two consecutive jumps over 500 km, with
the second contingent on the first, is P= (10
–16
)
2
=10
–32
;
that is, more improbable than the single jump over
1000 km.
Example 3. Ecological parameters, such as the above
dispersal probability kernels, can be included in model-
based tests of alternative dispersal hypotheses [4,18]. This
approach integrates ‘historical’ and ‘ecological’ biogeogra-
phy, two domains once thought to be independent because
of their differing time scales and treatment of evolution
(ancient and evolutionary versus recent and non-evolution-
ary, respectively) [47]. Webb and Ree [18] compared two
alternative hypotheses from [48] to explain the occurrence
of species of Rhododendron sect. Vireya on both sides of
Wallace’s Line, a putatively ancient division between the
biotas of South-east Asia and Australasia, caused by plate
tectonics [49]. Webb and Ree used SHIBA [18], a program
that simulates lineage movement on a changing historical
landscape, as determined from geological data, and makes
probabilistic estimates of ancestral ranges. Their model
also included ecological parameters from the theory of
island biogeography [50], namely survival versus area,
and dispersal versus distance. The authors then used this
model to test contrasting hypotheses about the age of the
radiation of Rhododendron sect Vireya in the island archi-
pelago of Malesia by comparing the likelihoods of bio-
geographical reconstructions using the alternative root
ages (55 mya vs 12 mya). Their test determined that a
single LDDE event at 55 mya was more probable than
shorter stepping-stone dispersals through islands that
came into existence more recently.
The problem of extinction
Extinction has long been acknowledged as a key determi-
nant of observable biogeographical patterns, but is often
considered intractable and ignored [13]. One reason is that
it is difficult to reconstruct (Box 3) unless the fossil record
provides compelling evidence of the former presence of taxa
in areas where they are no longer found [51]. The reverse,
lack of fossil evidence of a former presence of a taxon in a
given area, should not be accepted prima facie as evidence
that it was always absent, given the stochastic nature of
the fossil record (Box 3,Figure Ib).
Despite the difficulties, it is essential to consider extinc-
tion in testing biogeographical hypotheses because it can
result in false reconstructions that appear to be well
supported (Box 3). Biotic turnover has probably been over-
looked because fossils of extinct lineages have been mis-
assigned to younger, related lineages that have
immigrated more recently, giving a false impression of
long-term occupancy of a region by the original lineage
(Box 3, Figure Ic). For example, in New Zealand, evidence
is emerging of previously overlooked floristic turnover
through the Cenozoic [52], for example in Nothofagus
[34], Ericaceae [53] and Agathis [35].
Thus, the fossil record, and the probable biases and/or
uncertainty it implies, should be considered as far as
possible in biogeographical analysis [51]. For example,
some extant ‘Gondwanan’ groups have an unequivocal,
even extensive, ancient fossil record in the Northern Hemi-
sphere, where they have apparently gone extinct (cf. Box 3,
Figure Id); for example, marsupials [54], Rhynchocephalia
(tuatara) [55], southern conifers such as Araucariaceae and
many Podocarpaceae [56]. Similarly, there are fossils of
several genera of the cypress family (Cupressaceae) from
Southern Hemisphere areas where they are now extinct
[56–58];Box 1 illustrates how incorporating this fossil
evidence into hypotheses can change how researchers
assess the biogeographical history of the family.
Geographically restricted taxa that are species poor and
sister to a species-rich lineage (often referred to as ‘relicts’)
Box 3. Extinction needs to be considered in hypothesis
formulation
No current method of AAR using phylogenies can reconstruct as
ancestral an area that has not been observed in present-day species
and, consequently, has not been included in the analysis, cf. [67].
Only the fossil record (if available) can provide evidence of former
occurrences of taxa in areas where they are now extinct (e.g.
[51,64]). Extinction can mislead by differentially erasing any kind of
biogeographical pattern, including dispersal pattern, and it can
remove evidence from either a particular time period or a particular
region.
[()TD$FIG]
Space
Time
(a) (c) (d)(b)
(a) (c) (d)
TRENDS in Ecology & Evolution
Figure I. Biogeographical histories of hypothetical lineages. Open circles
represent living taxa, filled circles indicate fossil taxa, black lines indicate actual
phylogenetic relationships and coloured bars indicate hypothetical locations
through time. As biogeographical history is ‘known’, one can intuit that: (a) the
age of a crown group does not equate to the age of the lineage in a particular
area; (b) current absence of a lineage does not equate to past absence; (c)
current presence of a lineage (pink area) does not equate to continuous past
presence; and (d) relict taxa or living fossils do not necessarily indicate long
occupation of an area, but might reflect high levels of extinction. Using a
phylogeny from sequence data for extant taxa (at bottom of figure), rate
modelling and AAR, a biogeographer could infer a common ancestor for each
of (c) and (d) but could not infer where the ancestor existed through time.
Inclusion of one available dated fossil (solid-black circle) could result in correct
time calibration and inference of ancestral locality. Alternatively, inclusion of a
different dated fossil (solid-red circle) could lead to incorrect inferences of both
the location and age of the common ancestor. Thus, uncertainty about the
placement of fossils yields uncertainty about biogeographical inference,
regardless of the sophistication of the phylogenetic tools.
Opinion Trends in Ecology and Evolution February 2011, Vol. 26, No. 2
70

tend to invite speculation about their origins and biogeog-
raphy. Examples include Ginkgo in China, tuatara and
Agathis in New Zealand, and the endemic shrub Amborella
in New Caledonia. However, extant taxa indicate persis-
tence in time only, not in space (Box 3, Figure Id), and
‘relict’ lineages cannot be assumed to have occupied the
present space throughout the existence of the lineage. Such
lineages have probably been subject to considerable extinc-
tion and, in the absence of additional data, are essentially
uninformative about biogeographical history, presenting
little scope for erecting testable hypotheses. Even though
the above taxa (except Amborella) have an excellent an-
cient fossil record and have been geographically wide-
spread in the past, their restriction to a single surviving
species in a localized area is shrouded in mystery.
Conclusions and the way ahead
Understanding of how lineages became distributed as they
are has changed dramatically because biogeographers are
taking a more focused, critical approach. Sweeping ques-
tions such as ‘where did cypresses evolve?’ are being
replaced with focused, testable hypotheses, such as ‘the
ancestor of the extant cypress species of Libocedrus in New
Zealand arrived by LDDE after the Oligocene drowning’.
Consequently, it has been learned that the geographical
evolution of biota has been driven by a greater diversity of
processes with a more complex history than under a simple
vicariance (or dispersal) paradigm. For example, tests of
predictions from geology and ecology have shown that, to a
large degree, New Zealand and New Caledonia resemble
‘oceanic’ islands with young, immigrant biota, rather than
‘continental’ islands with relictual ‘Gondwanan’ biota
[26,59,60].
Future biogeographical models will become more com-
plex, sophisticated and realistic, as they incorporate esti-
mates of ecological parameters, such as dispersal kernels
[7,61]. Models can be used to test hypotheses by varying
the parameter under question while holding others con-
stant, within a statistical framework [7,11,18]. However,
models require validation with independent empirical data
on crucially important parameter values [19,23] and these
are difficult to obtain, especially in an historical context.
Important parameters to include are the shape of the tail of
the LDDE distribution and the distances beyond which
reduced gene flow leads to divergence. Such parameters
are difficult to quantify and are likely to be species or
ecology specific. Current historical models use parameter
values that are either best guesses, or worse, are estimated
from phylogenies and, thus, not independent of them.
Increasingly, geo-referenced ecological and climatic
parameters are being integrated into tests of alternative
spatial models of community diversification and distribu-
tion [7]. Current climatic models are well validated and
implemented in GIS at fine geographical and seasonal
scales. Extending such models to ancient time periods is
challenging, partly because past climates are commonly
reconstructed using fossil evidence, so using the recon-
structions for testing biogeographical hypotheses could
be circular.
The fossil record is emerging again as being crucially
important in biogeography (e.g. [51]), and we have reiter-
ated here, with examples, that ignorance of the role of
extinction can lead to misinterpretation. Auspiciously, new
collaborations between palaeontologists and molecular
systematists [8,35,53,62,63] are leading to reinterpretion
of fossils, resulting in improvement of the phylogenetic
placement of calibration points and more reliable diver-
gence time estimates. In addition, ecological parameters
estimated from extant organisms can help explain distri-
butional changes when compared with the fossil record.
For example, ecophysiological tolerances were measured in
living conifer genera, some of which are extinct in
Australia but have a fossil record there [64]. It was found
that, unlike the extant Australian genera, those that are
extinct probably had moisture tolerances that fell outside
the current range of climates in Australia [64]. This type of
integrative approach is resulting in more critical tests of
biogeographical hypotheses and is changing the current
view of the history of the biota of the world.
Acknowledgements
We thank the ‘papers-in-the-pub’ systematics discussion group at The
University of Queensland, especially Nate Hardy, and the Biogeography
and Systematics group, Massey University, especially Ian Henderson and
Mary Morgan-Richards, for their input that helped improve the article.
We also acknowledge funding support from the Australian Biological
Resources Study and the Australian Research Council.
Appendix A. Supplementary data
Supplementary data associated with this article can be
found, in the online version, at doi:10.1016/j.tree.2010.
11.005.
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