diversification in amazonian woody plant lineages...

Centre d’Etude de la Biodiversité Amazonienne - © 2012

DIVERSIFICATION IN AMAZONIAN

WOODY PLANT LINEAGES AND THE

FUTURE OF AMAZONIA

Jerome Chave

CNRS,

laboratoire Evolution Diversité Biologique,

Université Paul Sabatier

Toulouse, FRANCE


Davidson et al. Nature (2012)

The Amazon basin in

transition


It is our moral responsibility to

know and protect biodiversity

Act so that the consequences of

your actions are compatible with

the permanence of a genuine

human life on Earth

Hans Jonas (1979)


Engaging citizen in the study

of biodiversity


Outline

1. The pace of diversification in the

Neotropical tree flora

2. Environmental drivers of

diversification

3. Modelling the future of Amazonian

forest ecosystems


1. At what pace has

the Neotropical flora

diversified?

Photo credit: Oliver Phillips, Leeds U


The Neotropics

Top-canopy

height (m)


Vertebrates

MammalsBirds Amphibians

Jenkins et al. PNAS (2013)


‘One of the outstanding features of

the neotropical flora is it extreme

richness in species (90,000 species

according to Raven 1976)’

Gentry Ann Miss Bot Garden (1982)


Time‘Museum’ diversification

‘Cradle’ diversification

Rate of change are calibrated using the fossil record

Phylogenetic trees and the fossil record

provide a crucial information on the

tempo of diversification

Origin

OLD

RECENT

Centre d’Etude de la Biodiversité Amazonienne - © 2012Science (2010)

Age of genera


Roncal et al. Bot J Linn Soc (2013)Genus Astrocaryum

(palm) in the Neotropics

Centre d’Etude de la Biodiversité Amazonienne - © 2012Fine et al. Evolution (2014)

Protiae (fam.

Burseraceae) in the

Neotropics


Meliaceae

Koenen et al. New Phytol (2015)

Cedrela

Trichilia

Ruagea/

Guarea

Centre d’Etude de la Biodiversité Amazonienne - © 2012Lohmann et al. Bot J Linn Soc (2013)

Bignoniaceae


Program

1. Provide/streamline plastid DNA genomic

resources across tree species in Amazonia

2. Document the evolutionary history of more

major tree families in Amazonia

3. Search for commonalities across these

lineages


The Neotropical plant plastid

genome project


Methods

1. Extract DNA from dry leaf material

2. Prepare one high throughput

sequencing library per species

3. Multiplex 24 libraries per HiSeq run

4. Reconstruct the plastid DNA genome by

‘genome walking assembly’ technique

5. Align and annotate genomes

6. Construct a phylogenetic hypothesis


Total sequencing effort

• 200 plastid genomes from ‘focal’

tree families

– Chrysobalanaceae (ca. 100 spp/533)

– Sapotaceae: Chrysophylloideae (ca.

100 spp/500)

• 200 plastid genomes from ‘other’

tree families


What a plastid genome

looks like


Plastid genome size statistics

0

100

200

300

400

500

600

700

800

900

140000 150000 160000 170000 180000 190000

Genome length

Se

qu

en

cin

gd

ep

th n=82

Chaunochiton kappleri (Olacaceae)

Amphirrhox longifolia (Violaceae)Apocynaceae, Annonaceae


Target tree families

Percentage of trees per family

Fabaceae

Arecaceae

Lecythidaceae

Sapotaceae

Malvaceae

Moraceae

Burseraceae

Chrysobalanaceae

Euphorbiaceae

Myristicaceae

Annonaceae

Lauraceae

rest


Mid-sized family with ca 500

species, 80% of them in the

Neotropics

Taxonomy of the family has

been carefully researched

since the 1960s

Chrysobalanaceae


Jud et al. Am J Bot (2016)

Fossil record


Chrysobalanaceae

•50 plastid genomes for

Chrysobalanaceae (+80

addtl spp)

RAxML tree

reconstruction

Neotropical clade

Bardon et al. Am J Bot (2016)Léa Bardon

Centre d’Etude de la Biodiversité Amazonienne - © 2012 Hirtella duckei s

Hirtella elongata s

Hirtella magnifolia s

Hirtella pilosissima s

Hirtella rodriguesii s

Hirtella glandulosa sHirtella bicornis s

Hirtella glabrata s

Hirtella suffulta pHirtella tenuifolia s

Hirtella macrosepala pHirtella dorvalii s

Hirtella glandistipula sHirtella hebeclada s

Hirtella ciliata s

Hirtella araguariensis s

Hirtella punctillata sHirtella triandra s

Hirtella margae s

Hirtella paniculata sHirtella bullata s

Hirtella davisii s

Hirtella arenosa s

Hirtella physophora p

Hirtella racemosa p

Licania laevigata sLicania latifolia s

Licania amapaensis s

Licania heteromorpha p

Licania egleri s

Licania intrapetiolaris s

Afrolicania elaeosperma p

Licania glabriflora p

Licania macrophylla pLicania licaniiflora s

Gaulettia amaraliae s

Gaulettia elata pGaulettia canomensis s

Licania lanceolata s

Licania micrantha pLicania cordata s

Licania densiflora s

Licania caudata s

Licania membranacea p

Licania ovalifolia p

Licania hypoleuca s

Licania parvifructa s

Licania gracilipes s

Licania leptostachya s

Licania canescens pLicania incana s

Licania orbicularis s

Licania alba pLicania laxiflora s

Licania discolor s

Licania irwinii s

Licania unguiculata sLicania urceolaris s

Licania majuscula pLicania octandra s

Licania sprucei p

Licania cf.longistyla p

Licania emarginata s

Licania granvillei sLicania lata s

57

56

87

91

63

55

87

92

87

85

100

95

81

79

84

55

51

54

88

76

99

75

70

40 20 0

Oligocene Miocene Plio.

Par inariopsis

Lican ia ss

Gaulet t ia

Afrolicania

Leptoba lanus

Hym enopus

Hym enopus

Chrysobalanaceae

New generic delineation for

Licania (Sothers et al. 2017)

Now 6 genera (Geobalanus,

Moquilea, Leptobalanus, Licania,

Parinariopsis, Hymenopus)

75% of the family belongs to a

single Neotropical clade that

diversified < 30 Ma ago


• Faster rate of diversification

in the Neotropics

Chrysobalanaceae

Neotropical clade


Chrysobalanaceae

• A paleotropical family, that diversified ca

50 Ma ago

• 75% of the diversity is contained in a

single Neotropical clade which diversified

rapidly

• The Neotropical evolutionary history for

this family is concentrated in the past 25

Ma


Second example:

Sapotaceae

• A pantropical family of trees with

ca. 1000 species

• Includes useful species (argan,

chicle, massaranduba)

• Subfamily Chrysophylloideae (ca.

500 spp) is predominantly

Neotropical


Previous work

60 Ma!!

Bartish et al. J

Biogeogr (2010)

Molecular phylogeny

suggests a single

Neotropical clade in the

subfamily

But with an old age (60

Ma)


Preliminary: A new

phylogenetic tree

for Sapotaceae

Paleotropical

Neotrop.

Low support

rapid radiation

Chrysophylloideae

104 species

with full plastid

genomes

In progress


Sapotoideae

Pouteria

Micropholis

Chrysophyllum

Pradosia

Elaeoluma

Ecclinusa

Chrysophylloideae Chrysophyllum

Synsepalum

Neotropics

Neotropical node

In progress


Part 1: conclusions

• The origins of many plant lineages that

are currently predominantly Neotropical

is usually less than 40 Ma.

• After their arrival in the Neotropics, many

lineages seem to have evolved in situ,

with very rare dispersal from the

Neotropics

• For the lineages studied, diversification

rates have been consistently higher in the

Neotropics than in Africa


2. Are Amazonian

forests homogeneous

environmentally?


Allopatric speciation

Genetic

reinforcement

Creation of a

barrier

Mayr (1963)

Time

Centre d’Etude de la Biodiversité Amazonienne - © 2012•Pennington et al. PNAS 2010

Cyathostegia.


Finding environmental

regions for Amazonia• Define an environmental space for each pixel of

the Amazon

• Define a distance metric for pairs of pixels in the

environmental space

• Define a graph where each node is a pixel, and

the edge materialize the connection between

most similar pixels in environmental space

(adaptive nearest neighbor)

• Construct ‘natural’ clusters using a clsutering

algorithm


Canopy height

Sao

Paulo

Sao

Pedro

Top-canopy

height (m)


Topography

SRTM instrument

(space shuttle) NASA

Elevation

(m a.s.l)


Rainfall

Monthly

rainfall

(mm)

CHIRPS product

(Funk et al. 2015)


Soil moisture

SMOS satellite

(2010-2016) soil

moisture product

Moist

Dry


Canopy moisture

Quickscat satellite

(1999-2009) top leaf

moisture product

Saatchi et al. PNAS

(2011)

Moist

Dry


Cloudiness

Low cloud cover

High cloud cover

MODIS cloud cover

(Wilson & Jetz 2016)


Finding environmental

regions for Amazonia• Define an environmental space for each pixel of

the Amazon

• Define a distance metric for pairs of pixels in the

environmental space

• Define a graph where each node is a pixel, and

the edge materialize the connection between

most similar pixels in environmental space

(adaptive nearest neighbor)

• Construct ‘natural’ clusters using a clsutering

algorithm


Result: environmental regions

for Amazonia

S Tao, J Murienne, A Fouquet, J Chave, unpublished results


Implications

• The Amazon is more environmentally diverse than

any single environmental layer would suggest

(topography, climate, forest structure)

• This implies that biogeographic barriers, which

trigger diversification, are common in Amazonia –we should not only consider rivers

• Looking into the past of these environments is a

necessity, but will require a careful exploration of

how past environmental variables correlate with

each other


Caveat – Amerindian

footprint in Amazonia


The future of remote sensing in

Amazonia (and the globe)


Several mission designs are in preparation for launch (EnMAP by

Germany, PRISMA by Italy)

New mission designs are needed(NASA, Israel, ESA, China are working

on this)

•Map of alpha-

diversity

Feret and Asner Ecol Appl (2014)

Shannon’s diversity index

Inferring biodiversity from

space: hyperspectral sensing


Outline

1. The pace of diversification in the

Neotropical tree flora

2. Environmental drivers of

diversification

3. Modelling the future of Amazonian

forest ecosystems


3. Can we model the

Amazonian forest to

predict its future

state(s)?

Centre d’Etude de la Biodiversité Amazonienne - © 2012•Cox et al. 2000 Nature; Cox et al. 2004 Theor. Appl. Climatol; Good et al. 2013 Journal of Climate

Towards an Amazonian dieback ?

First model

2001, 2004

Modified model

2013

An uncertain future


CO2

Photosynthesis Respiration

Mortality

Roots, leaves, fruits …

Mortalit

Net Primary Production of Wood

Sitch et al. GCB (2003) 9, 161-185

Dynamic vegetation models


Current limits in land-surface

models

Model inter-comparison in

Amazonia

Delbart et al. Biogeosciences (2010)

Johnson et al. Global Change Biology (2016)


Current limits in climate

forecasting models

Joetzjer et al. Clim Dyn (2014)

Observed climatology

(GPCC)

Emilie Joetzjer


Individual-based forest dynamics

models

• Scaling from individual processes and

dimensions to ecosystem-level dynamics

• Ability to model genetic flux, and speciation


‘turbid medium’

approximation

3D voxel space

Light diffusion

• Autotrophic respiration:

Atkin et al. (2015)

• Photosynthesis: Farquhar

model (Vcmax, Jmax, G)

• Stomatal control: Plant-

averaged stomatal

conductance model; Medlyn

et al. (2011)

•Chave Ecol Modell (1999); Maréchaux & Chave Ecological Monographs (2017)

TROLL model

Isabelle Maréchaux


TROLL model

Maréchaux & Chave Ecological Monographs (2017)


•PARACOU

•NOURAGUES

163 species

parameterized.

Parameterizing TROLL: sites

and data


Early-regeneration plot

Undisturbed mature forest plots

Forest regeneration from

bare ground

0 100 200 300 400 500

0

100

200

300

400

Aboveground biomass (in tons/hectare)

Time (in years)



0 100 200 300 400 500

0

10

20

30

40

50

60

70

Bonal et al. 2008 Global Change Biology; Malhi 2012 Journal of Ecology

Time (years)

GPP = NPP + Rmaintenance + Rgrowth

Carbon flux (in Mg C ha-1 year-1)

GPP

Rmaintenance

NPP

Rgrowth

Guyaflux

Paracou

French Guiana


bare ground


0 100 200 300 400 500

0

2

4

6

8

Species relative abundances (%)

Time (in years)

0 100 200 300 400 500

0

2

4

6

8Laetia proceraCecropia obtusaDicorynia guianensisEschweilera grandifloraPouteria guyanensisEperua grandifloraGoupia_glabraMicropholis cayennensis

Laetia procera

Cecropia obtusa

Dicorynia guianensis

Eschweilera grandiflora

Pouteria guyanensis

Eperua grandiflora

Goupia glabra

Micropholis cayennensis


bare ground


Centre d’Etude de la Biodiversité Amazonienne - © 2012313100 313300 313500

4512

0045

1400

4516

0045

1800

4520

00

0

10

20

30

40

50

v

Freq

uenc

y

0 10 30 50

010

000

2000

030

000

4000

0

Histogram of Canopy_height

Canopy_height

Freq

uenc

y

0 10 20 30 40 50 60

010

000

2000

030

000

4000

0

•Canopy height (in m)

•Simulated

canopy

structure

•LiDAR-

measured

canopy

structure

•0

•0

•40

0

0 100 200 300 400

01

00

200

300

400

0

10

20

30

40

50

60


bare ground

Fabian Fischer


Biodiversity and ecosystem

functioning

Tilman et al 2007


Test of the effect of biodiversity on forest productivity

by changing simulated species richness and composition.

5 LEVELS

OF

SPECIES RICHNESS

100 SIMULATIONS

EACH

500 SIMULATIONS THAT DIFFER IN SPECIES RICHNESS AND COMPOSITION

2 species 5 species 10 species 50 species 100 species

…

…

…

…

…


A virtual biodiversity experiment




2 5 10 50 100

25

30

35

40

45

50

55

2 5 10 50 100

0

10

20

2 5 10 50 100

0

10

20

2 5 10 50 100

−1.5

−1.0

−0.5

0.0

0.5

1.0

1.5

2 5 10 50 100

100

200

300

400

500

2 5 10 50 100

−200

−100

0

100

200

300

2 5 10 50 100

−200

−100

0

100

200

300

2 5 10 50 100

−20

−10

0

10

20

a

a,b

b

b b

Species richness

GP

P (

in M

g C

ha

-1 y

ear-1

)

GPP





2 5 10 50 100

25

30

35

40

45

50

55

2 5 10 50 100

0

10

20

2 5 10 50 100

0

10

20

2 5 10 50 100

−1.5

−1.0

−0.5

0.0

0.5

1.0

1.5

2 5 10 50 100

100

200

300

400

500

2 5 10 50 100

−200

−100

0

100

200

300

2 5 10 50 100

−200

−100

0

100

200

300

2 5 10 50 100

−20

−10

0

10

20

a

a,b

b

b b

***

a

***

a,b

***

a,b

***

b

***

ΔG

PP

(in

Mg C

ha

-1 y

ea

r-1)

Species richness (S) Species richness (S)

GP

P (

in M

g C

ha

-1 y

ear-1

)

Net biodiversity effectGPP

- + + + + S

Net

biodiversity

effect=



2 5 10 50 100

25

30

35

40

45

50

55

2 5 10 50 100

0

10

20

2 5 10 50 100

0

10

20

2 5 10 50 100

−1.5

−1.0

−0.5

0.0

0.5

1.0

1.5

2 5 10 50 100

100

200

300

400

500

2 5 10 50 100

−200

−100

0

100

200

300

2 5 10 50 100

−200

−100

0

100

200

300

2 5 10 50 100

−20

−10

0

10

20

a

a,b

b

b b

***

a

***

a,b

***

a,b

***

b

*** ******

a***

a

***

a

***

a

**

b,c

***

c

a,b,c

a,ba

ΔG

PP

(in

Mg C

ha

-1 y

ea

r-1)

SE

GP

P(in

Mg C

ha

-1 y

ea

r-1)

CE

GP

P(in

Mg C

ha

-1 y

ea

r-1)

Species richness (S) Species richness (S) Species richness (S) Species richness (S)

GP

P (

in M

g C

ha

-1 y

ear-1

)

Net biodiversity effectGPP Complementarity effectSelection effect

selection effect



Loreau & Hector 2001 Nature

Net

biodiversity

effect= +

complementarity

effect



Conclusions

1. The pace of diversification in the Neotropical tree

flora– Chrysobalanaceae and Sapotaceae tell similar stories:

one dispersal event and in-situ diversification, consistent

with other plant groups

– The in-situ diversification history is more recent than 40 Ma

2. Environmental drivers of diversification– Careful exploration into the environmental diversity today

holds key to understand past events

– Tropical forest observation by remote sensing is entering a

new era

3. Modelling the future of Amazonian forest

ecosystems– New modelling tools are emerging and they help

reconcile questions in environmental science and

biodiversity research


It is our moral responsibility to

know and protect biodiversity

Act so that the consequences of

your actions are compatible with

the permanence of a genuine

human life on Earth

Hans Jonas (1979)

diversification in amazonian woody plant lineages...

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