Graham Slater's Phyloseminar Slides 12-10-2013

Phylogenetic Paleobiology: What do we stand to gain from integrating fossils and

phylogenies in macroevolutionary analyses?

SmithsonianNational Museum of Natural History

Graham SlaterDepartment of Paleobiology, National Museum of Natural History

SmithsonianNational Museum of Natural Historywww.fourdimensionalbiology.com

@grahamjslater

http://www.fourdimensionalbiology.com

http://www.fourdimensionalbiology.com

40 30 20 10 0

get a time-calibrated phylogeny

gather some trait data

40 30 20 10 0

fit some models

“insert_model” explains the evolution of “insert_trait” in

“insert_clade” !

LETTERdoi:10.1038/nature10516

Multiple routes to mammalian diversityChris Venditti1, Andrew Meade2 & Mark Pagel2,3

The radiation of themammals provides a 165-million-year test casefor evolutionary theories of how species occupy and then fill eco-logical niches. It is widely assumed that species often divergerapidly early in their evolution, and that this is followed by alonger, drawn-out period of slower evolutionary fine-tuning asnatural selection fits organisms into an increasingly occupiedniche space1,2. But recent studies have hinted that the processmay not be so simple3–5. Here we apply statistical methods thatautomatically detect temporal shifts in the rate of evolutionthrough time to a comprehensive mammalian phylogeny6 and dataset7 of body sizes of 3,185 extant species. Unexpectedly, themajorityof mammal species, including two of the most speciose orders(Rodentia and Chiroptera), have no history of substantial and sus-tained increases in the rates of evolution. Instead, a subset of themammals has experienced an explosive increase (between 10- and52-fold) in the rate of evolution along the single branch leading tothe common ancestor of their monophyletic group (for exampleChiroptera), followed by a quick return to lower or backgroundlevels. The remaining species are a taxonomically diverse assem-blage showing a significant, sustained increase or decrease in theirrates of evolution.These results necessarily decouplemorphologicaldiversification from speciation and suggest that the processes thatgive rise to the morphological diversity of a class of animals are farmore free to vary than previously considered. Niches do not seem tofill up, and diversity seems to arise whenever, wherever and at what-ever rate it is advantageous.Our approach uses a generalized least-squares model8,9 of trait

evolution in a Bayesian reversible-jump10 framework that allows ratesof evolution to vary in individual branches or entire monophyleticsubgroups of a phylogeny (Supplementary Information). This allowsus to trace the evolutionary history of shifts in the rate and timing ofevolutionwithout specifying in advancewhere these events are located,and to derive posterior probability density estimates of their magni-tudes and probability of occurrence (Supplementary Information).The null model states that evolution has proceeded at a constant ratethroughout the classMammalia. Applied to log-transformed body sizedata (n5 3,185 species) arrayed on the mammalian tree6 , this modelreturns a Bayesian posterior density of log-likelihoods with a mean of2939.346 0.99 (Fig. 1a), and a mean instantaneous rate of body sizeevolution of 1.02 g per million years. If rates are allowed to varythroughout the tree, the posterior density improves to a mean log-likelihood of 2364.136 23.01 (log(Bayes factor)5 993.51; values.10 considered ‘very strong’ support11; Fig. 1a). We detect evidencefor a shift or change in the rate of evolution in approximately one-third, or 1,494 branches, of the tree, where to be included in this countbranches had to either experience a change in rate in that branch orinherit that change from its immediate ancestral lineage, in at least 95%of the trees in the posterior sample. These shifts range from a 3-folddecrease to a 52-fold increase in the rate of evolution along a branch(Fig. 1b).It has long been believed that the radiation of extant mammals

underwent a burst of body-size evolution that occurred early in itshistory and coincided with the appearance of the mammalian orders,

and that this was followed by a gradual slowdown towards the pre-sent4,12–14. Explanations for this pattern suppose that mammals movedinto a largely unoccupied niche and geographical space as they came tobe the dominant vertebrate group on Earth. Then, as time went on,niche space and unexplored geographical regions became scarce,reducing opportunities for diversification4. In striking contrast to thispicture, we do not find any evidence for either a generalized burst ofevolution early inmammalian evolution or for the rates of evolution todecrease as time moves towards the present (Fig. 2a). Instead, rates ofevolution were low and stable for about the first 60 million years, onlystarting to increase around 90million years ago and then showing onlyabout a twofold increase over the previous ‘baseline’ rate. This increaseoccurred before the origin of the present-daymammalian orders and is

1Department of Biological Sciences, University of Hull, Hull HU6 7RX, UK. 2School of Biological Sciences, University of Reading, Reading RG6 6BX, UK. 3Santa Fe Institute, 1399 Hyde Park Road, Santa Fe,New Mexico 87501, USA.

Log-likelihood

Fold rate increase or decrease

500

1,000

1,500

2,000

2,500

12,000

–970 –870 –770 –670 –570 –470 –370 –270

0 5 10 15 20 25 30 35 40 45 50 55

Variable-rates model

Equal-rates modela

Freq

uenc

y

100

200

300

400

2,250b

Figure 1 | Log-likelihood of trait models when rates are allowed to vary.a, Posterior distribution of log-likelihoods from a model with equal rates ofevolution (red), compared with the posterior distribution of log-likelihoodsfrom the model in which evolutionary rates are allowed to vary (green):log(Bayes factor)5 993.51 (calculated from the log-harmonic means of thelikelihoods); values.10 considered ‘very strong’ support. b, The coloured barsshow distributions of rates for the one-third of the branches (1,494) for whichthe posterior probability of having a rate shift was greater than 0.95. Blue barssignify x-fold rate increases and yellow bars indicate x-fold rate decreases. Greybars show the distribution of the mean fold rates for all the branches in themammal phylogeny, independent of the level of posterior support.

0 0 M O N T H 2 0 1 1 | V O L 0 0 0 | N A T U R E | 1

Macmillan Publishers Limited. All rights reserved©2011

phylogenies don’t really look like this

40 30 20 10 0

they look like this

40 30 20 10 0

Finarelli and Flynn 2006 Sys. Biol.

adding fossils improves ancestral state estimates

do those extinct things matter for testing macroevolutionary

hypotheses?

do those extinct things matter for testing macroevolutionary hypotheses?


• how much macroevolutionary information do fossils hold relative to extant taxa?



• does a paleontological perspective change the way we formulate our hypotheses?




• can we use fossil information when we have no phylogeny including extinct species?





simulate trait evolution

prune to extant taxa only



fit models



replace a proportion of extant taxa for fossils



fit models


replace a proportion of extant taxa for fossils

TimeTime

Phen

otyp

eBrownian motion

Time

0.0 0.2 0.4 0.6 0.8 1.00.0

0.2

0.4

0.6

0.8

1.0

swapping fossils for extant taxa has no effect if BM is the true model of evolution

Akaik

e Weig

hts

proportion of taxa that are extinct

0.0 0.2 0.4 0.6 0.8 1.00.0

0.2

0.4

0.6

0.8

1.0

swapping fossils for extant taxa has no effect if BM is the true model of evolution

Akaik

e Weig

hts

proportion of taxa that are extinct

BM is a special case of most current models

AIC = 2k - 2ln(L)

BM is a special case of most current models

# parameters Likelihood

trend

Time

Phen

otyp

e

trend

Time

Phen

otyp

e

Benson et al. 2013 PLoS ONE

Cope’s rule -- an evolutionary trend

no trends can be detected from extant taxa only

0 1 2 3 4 5 60.0

0.2

0.4

0.6

0.8

1.0

Akaik

e Weig

hts

root - tip increase in mean

0/100 fossils

0 1 2 3 4 5 60.0

0.2

0.4

0.6

0.8

1.0

but a few fossils have a substantial effectAk

aike W

eight

s

0/100 fossils

5/100


0 1 2 3 4 5 60.0

0.2

0.4

0.6

0.8

1.0

and more fossils improves ability to detect weaker trends

Akaik

e Weig

hts

0/100 fossils

5/100

50 /100

95 /100


Early Burst - Declining rates

Time

Phen

otyp

e

Early Burst - Declining rates

Time

Phen

otyp

e

ORIGINAL ARTICLE

doi:10.1111/j.1558-5646.2010.01025.x

EARLY BURSTS OF BODY SIZE AND SHAPEEVOLUTION ARE RARE IN COMPARATIVEDATALuke J. Harmon,1,2,3 Jonathan B. Losos,4 T. Jonathan Davies,5 Rosemary G. Gillespie,6 John L. Gittleman,7

W. Bryan Jennings,8 Kenneth H. Kozak,9 Mark A. McPeek,10 Franck Moreno-Roark,11 Thomas J. Near,12

Andy Purvis,13 Robert E. Ricklefs,14 Dolph Schluter,2 James A. Schulte II,11 Ole Seehausen,15,16

Brian L. Sidlauskas,17,18 Omar Torres-Carvajal,19 Jason T. Weir,2 and Arne Ø. Mooers20

1Department of Biological Sciences, University of Idaho, Moscow, Idaho 838442Biodiversity Centre, University of British Columbia, Vancouver, BC V6T1Z4, Canada

3E-mail: [email protected] of Organismic and Evolutionary Biology, Harvard University, Cambridge, Massachusetts 021385National Center for Ecological Analysis and Synthesis, University of California, Santa Barbara, 735 State Street, Suite 300,

Santa Barbara, California 931016Department of Environmental Science, Policy and Management, University of California, Berkeley, California 947207Odum School of Ecology, University of Georgia, Athens, Georgia 306028Department of Biological Sciences, Humboldt State University, Arcata, California 955219Department of Fisheries, Wildlife, and Conservation Biology, University of Minnesota, St. Paul, Minnesota 5510810Department of Biological Sciences, Dartmouth College, Hanover, New Hampshire 0375511Department of Biology, Clarkson University, Potsdam, New York 1369912Department of Ecology and Evolutionary Biology, Yale University, New Haven, Connecticut 0652013Division of Biology, Imperial College London, Silwood Park Campus, Ascot, SL5 7PY United Kingdom14Department of Biology, University of Missouri—St. Louis, St. Louis, Missouri 6312115Institute of Ecology & Evolution, Division of Aquatic Ecology & Macroevolution, University of Bern, CH-3012 Bern,

Switzerland16Eawag Centre of Ecology, Evolution and Biogeochemistry, Department of Fish Ecology & Evolution, Seestrasse 79,

CH-6047 Kastanienbaum, Switzerland17National Evolutionary Synthesis Center, Durham, North Carolina 2770518Oregon State University, Department of Fisheries and Wildlife, 104 Nash Hall, Corvallis, Oregon, 9733119Escuela de Biologıa, Pontificia Universidad Catolica del Ecuador, Apartado 17-01-2184, Quito, Ecuador20Department of Biological Sciences, Simon Fraser University, Burnaby, BC V5A1S6, Canada

Received May 11, 2009

Accepted February 21, 2010

2 3 8 5C⃝ 2010 The Author(s). Journal compilation C⃝ 2010 The Society for the Study of Evolution.Evolution 64-8: 2385–2396

Slater and Pennell (in press) Syst. Biol

early bursts need lots of taxa and big changes in rate


Akaike Weight

0.2

0.4

0.6

0.8

1.0

weight

50 100 150 200

0

2

4

6

8

10

number of taxa

# of

hal

f liv

es

0

2

4

6

8

10

0.2

0.4

0.6

0.8

# elapsedrate half lives

50 100 150 200

# taxa

1.0



Akaike Weight

0.2

0.4

0.6

0.8

1.0

weight

50 100 150 200

0

2

4

6

8

10

number of taxa

# of

hal

f liv

es

0

2

4

6

8

10

0.2

0.4

0.6

0.8


50 100 150 200

# taxa

1.0



Akaike Weight

0.2

0.4

0.6

0.8

1.0

weight

50 100 150 200

0

2

4

6

8

10

number of taxa

# of

hal

f liv

es

0

2

4

6

8

10

0.2

0.4

0.6

0.8


50 100 150 200

# taxa

1.0

0.2

0.4

0.6

0.8

1.0

weight

50 100 150 200

0

2

4

6

8

10

number of taxa

# of

hal

f liv

es


0 2 4 6 80.0

0.2

0.4

0.6

0.8

1.0

we need a lot of fossils to detect weaker early bursts

Akaik

e Weig

hts

# elapsed rate half-lives

0/100

5/100

50 /10

095

/100

Time

Phen

otyp

eLate Burst - Accelerating rates

Time

Phen

otyp

eLate Burst - Accelerating rates

0 2 4 6 80.0

0.2

0.4

0.6

0.8

1.0

Akaik

e Weig

hts

# elapsed rate doubling times

no ability to detect accelerating rates from ultrametric trees

0/100 fossils

0 2 4 6 80.0

0.2

0.4

0.6

0.8

1.0

Akaik

e Weig

hts


no ability to detect accelerating rates from ultrametric trees

0/100 fossils

0 2 4 6 80.0

0.2

0.4

0.6

0.8

1.0

Akaik

e Weig

hts


and may be mistaken for other “low-signal” processes like Ornstein-Uhlenbeck

0/100 fossils

0 2 4 6 80.0

0.2

0.4

0.6

0.8

1.0

Akaik

e Weig

hts


swapping extant tips for fossils increases support for accelerating rates over OU

5/100 fossils

0 2 4 6 80.0

0.2

0.4

0.6

0.8

1.0

Akaik

e Weig

hts



50/100 fossils

0 2 4 6 80.0

0.2

0.4

0.6

0.8

1.0

Akaik

e Weig

hts



95/100 fossils

how much macroevolutionary information do fossils hold relative to extant taxa?


on a “per-taxon” basis, fossils contribute more macroevolutionary

information than extant taxa


on a “per-taxon” basis, fossils contribute more macroevolutionary

information than extant taxa

impact of fossils depends on the underlying evolutionary process





do we test the right models?

How fast...do animals evolve...? That is one of

the fundamental questions regarding

evolution

Photo: Florida Museum of Natural HistorySimpson (1944, 1953)

Illustration by Mark Hallet

Eoce

neO

ligoc

ene

Mio

cene

Alroy (1999) Systematic Biology

fossils suggest an increase in mean and variance of body size after the K-Pg

K Pg Ng K Pg Ng

standard deviation massmean mass

Venditti et al. (2011) Nature

K Pg NgJ

relative rate

Phylogenetic approaches find no rate increase in the Cenozoic

do we really think mammals changed their rate of body

size evolution?

From Simpson (1953)

Simpson’s adaptive zones

Mesozoic CenozoicT J PgK Ng

body sizethe mammalian adaptive zone


body sizethe mammalian adaptive zone

variation in tempo


body size

variation in tempo

evolution slow


body size

variation in tempo

evolution slow

evolution fast


body size

images from http://dinosaurs.about.com


body size

http://dinosaurs.about.com/


variation in mode



body size



variation in mode


evolution constrained


body size



variation in mode


evolution constrained

evolution unconstrained


body size



3 paleo-motivated models for mammalian body size evolution

Slater (2013) Methods Ecol. Evol.


Mesozoic Cenozoic

BM rate 1 BM rate 2

K-Pg Shift



Mesozoic Cenozoic

BM rate 1 BM rate 2

K-Pg Shift

Mesozoic Cenozoic

Ornstein-Uhlenbeck BM

ecological release



Mesozoic Cenozoic

BM rate 1 BM rate 2

K-Pg Shift

Mesozoic Cenozoic

Ornstein-Uhlenbeck BM

ecological release

Mesozoic Cenozoic

BM*

release and radiate

Ornstein-Uhlenbeck


Q

Ng

Pg

K

J

T

P

02.59

23

66

145

201.3

252.2

264.94

time calibrated phylogeny of living and fossil mammals

Cenozoic

Mesozoic

Pz


Q

Ng

Pg

K

J

T

P

02.59

23

66

145

201.3

252.2

264.94

Cenozoic

Mesozoic

Pz


standard models paleo-inspired models

BrownianMotion

Directional Trend

Ornstein Uhlenbeck

AC /DC

White Noise

K-Pg shift

Ecological release

Release & radiate

0.0

0.2

0.4

0.6

0.8

1.0

Aka

ike

Wei

ghts

release & radiate fits best


BrownianMotion

Directional Trend

Ornstein Uhlenbeck

AC /DC

White Noise

K-Pg shift

Ecological release

Release & radiate

0.0

0.2

0.4

0.6

0.8

1.0

Aka

ike

Wei

ghts

Parameters Mesozoic Cenozoic

rate (σ2) 0.97 0.1

OU param (α) 0.01 -

faster rates of body size evolution in the Mesozoic?


rate (σ2) 0.97 0.1


faster rates of body size evolution in the Mesozoic?

Brownian motion is a diversifying process

time

phen

otyp

e


time

phen

otyp

e

starting state


time

phen

otyp

e

rate σ2

starting state


time

phen

otyp

e

rate σ2

starting state


time

phen

otyp

e

rate σ2

starting state starting state


time

phen

otyp

e

rate σ2


σ2 * time

time

phen

otyp

e

OU is an equilibrium process

time

phen

otyp

e


starting state

time

phen

otyp

e


rate σ2

starting state

time

phen

otyp

e

rubber band parameter α


rate σ2

starting state

time

phen

otyp

e



rate σ2

starting state

time

phen

otyp

e



rate σ2


time

phen

otyp

e

σ2 / 2α



rate σ2


time

phen

otyp

eBrownian motionOrnstein-Uhlenbeck

BM and OU simulated at the same rate give very different disparities

the OU process has an equilibrium disparity

250 200 150 100 50 0

variance

millions of years ago

CenozoicMesozoic

the OU process has an equilibrium disparity

250 200 150 100 50 0

variance


CenozoicMesozoic

250 200 150 100 50 0

variance


CenozoicMesozoic

a low BM rate increases disparity


size evolution?


size evolution?✗



evolution




evolution


...hang on a minute

D

A

B

C

8 6 4 2 0

D

A

B

C

8 6 4 2 0

B

C

D

A B C D

A 8.24 0.00 0.00 0.00

B 0.00 8.24 0.61 0.61

C 0.00 0.61 4.65 4.10

D 0.00 0.61 4.10 8.24

B

C D

D

A

B

C

8 6 4 2 0

B

C

D

A B C D

A 8.24 0.00 0.00 0.00

B 0.00 8.24 0.61 0.61

C 0.00 0.61 4.65 4.10

D 0.00 0.61 4.10 8.24

B

C D

D

A

B

C

8 6 4 2 0

B

C

D

A B C D

A 8.24 0.00 0.00 0.00

B 0.00 8.24 0.61 0.61

C 0.00 0.61 4.65 4.10

D 0.00 0.61 4.10 8.24

B

C D

D

A

B

C

8 6 4 2 0

B

C

D

A B C D

A 4.04 0.00 0.00 0.00

B 0.00 4.04 0.18 0.13

C 0.00 0.18 3.03 1.75

D 0.00 0.13 1.75 4.04D

A

B

C

8 6 4 2 0

OU VCV transformation DC

BB

C

D

A B C D

A 4.04 0.00 0.00 0.00

B 0.00 4.04 0.18 0.13

C 0.00 0.18 3.03 1.75

D 0.00 0.13 1.75 4.04D

A

B

C

8 6 4 2 0


BB

C

D

A B C D

A 4.04 0.00 0.00 0.00

B 0.00 4.04 0.18 0.13

C 0.00 0.18 3.03 1.75

D 0.00 0.13 1.75 4.04D

A

B

C

8 6 4 2 0


BB

C

D

A B C D

A 4.04 0.00 0.00 0.00

B 0.00 4.04 0.18 0.13

C 0.00 0.18 3.03 1.75

D 0.00 0.13 1.75 4.04D

A

B

C

8 6 4 2 0


BB

C

D

A B C D

A 4.04 0.00 0.00 0.00

B 0.00 4.04 0.13 0.13

C 0.00 0.13 1.48 1.22

D 0.00 0.13 1.22 4.04D

A

B

C

8 6 4 2 0

OU branch length transformation DC

BB

C

D

BrownianMotion

Directional Trend

Ornstein Uhlenbeck

AC /DC

White Noise

K-Pg shift

Ecological release

Release & radiate

0.0

0.2

0.4

0.6

0.8

1.0

Aka

ike

Wei

ghts


release & radiate still fits best...

BrownianMotion

Directional Trend

Ornstein Uhlenbeck

AC /DC

White Noise

K-Pg shift

Ecological release

Release & radiate

0.0

0.2

0.4

0.6

0.8

1.0

Aka

ike

Wei

ghts


but ecological release is almost as good


rate (σ2) 0.2 0.1


a less pronounced rate decrease ...

250 200 150 100 50 0

variance


CenozoicMesozoic

but σ2 / 2α makes more sense

250 200 150 100 50 0

variance


CenozoicMesozoic

but σ2 / 2α makes more sense

Tree transformations under OU don’t work for non-ultrametric

trees!





a touch of realism

most comparative biologists don’t have this

40 30 20 10 0

40 30 20 10 0

but have this

††

†

†

40 30 20 10 0

†

40 30 20 10 0

†

40 30 20 10 0

†

40 30 20 10 0

†

density.default(x = X)

-4 -2 0 2 4 6

0.00

0.10

0.20

0.30

ln(mass)

Density

caniform carnivores span a huge range of body sizes


30-250 grams


30-250 grams > 3, 000 Kg

Finarelli and Flynn 2006 Sys. Biol.

do caniform carnivores exhibit a trend towards large body size?

-2.5 7.5ln(body mass)

50 40 30 20 10 0Millions of Years Ago

Canidae

UrsidaeOdobenidaeOtariidae

Phocidae

MephitidaeAiluridae

Procyonidae

Mustelidae

Slater et al. 2012 Evolution

-2.5 7.5ln(body mass)

50 40 30 20 10 0Millions of Years Ago

Canidae

UrsidaeOdobenidaeOtariidae

Phocidae

MephitidaeAiluridae

Procyonidae

Mustelidae

Slater et al. 2012 Evolution

12 node priors - 11 internal - root

0.1 1 10 100 10000.0

0.2

0.4

0.6

0.8

1.0

0.1 1 10 100 10000.0

0.2

0.4

0.6

0.8

1.0

0.1 1 10 100 10000.0

0.2

0.4

0.6

0.8

1.0

0.1 1 10 100 10000.0

0.2

0.4

0.6

0.8

1.0

BM

OU

Trend

AC/DCextant

nodes

nodes + root

mass mass

mass mass

dens

ityde

nsity

dens

ityde

nsity

ancestral size is too large based on extant taxa ...

0.1 1 10 100 10000.0

0.2

0.4

0.6

0.8

1.0

0.1 1 10 100 10000.0

0.2

0.4

0.6

0.8

1.0

0.1 1 10 100 10000.0

0.2

0.4

0.6

0.8

1.0

0.1 1 10 100 10000.0

0.2

0.4

0.6

0.8

1.0 extantfossilsfossils + root

BM

OU

Trend

AC/DCextant

nodes

nodes + root

... but is more realistic with fossil priors

mass mass

mass mass

dens

ityde

nsity

dens

ityde

nsity

Trend ACDC OU

-10

12

32*

Ln(B

ayes

Fac

tor)

extant.onlyfossilsfossils.plus.root

Trend OUAC/DC

extant

nodes

nodes + root

Trend ACDC OU

-10

12

32*

Ln(B

ayes

Fac

tor)


Trend OUAC/DC

extant

nodes

nodes + rootpositive

Trend ACDC OU

-10

12

32*

Ln(B

ayes

Fac

tor)


Trend OUAC/DC

extant

nodes

nodes + root

Trend ACDC OU

-10

12

32*

Ln(B

ayes

Fac

tor)


Trend OUAC/DC

extant

nodes

nodes + root

root-tip increase in Ln(mass)

dens

itymode = 1.55

-1 0 1 2 3 4 5

0

5

10

15

20

25

the estimated change in mean mass is subtle

0 1 2 3 4 5 60.0

0.2

0.4

0.6

0.8

1.0

Akaik

e Weig

hts

root - tip change in mean

0/100 fossils

5/100

50 /100

95 /100

which is difficult to detect using AIC

-1012345

0.5 1 10ancestral mass (Kg)

root

-tip

incre

ase

in Ln

(mas

s)

joint marginal distribution of root state and trend parameter

-1012345



root

-tip

incre

ase

in Ln

(mas

s)

PP(Mu> 0) = 0.97

-1012345



root

-tip

incre

ase

in Ln

(mas

s)

no fossils with fossils

ancestral size

mode of evolution

how do fossils change our picture of caniform size evolution?


ancestral size large (~25kg) small (~2 kg)

mode of evolution



ancestral size large (~25kg) small (~2 kg)

mode of evolution Brownian motionBrownian motion + trend to large

size


can we use fossil information when we have no phylogeny including extinct species?

can we use fossil information when we have no phylogeny including extinct species?

even using fossil traits as informative node priors improves model fitting

do those extinct things matter for testing macroevolutionary

hypotheses?

today’s model systems for macroevolutionary studies

images: wikipedia

tomorrow’s model systems for macroevolutionary studies

images: www.amnh.oig., wikipedia

http://www.amnh.oig

http://www.amnh.oig

Technology

Graham Slater's Phyloseminar Slides 12-10-2013