Global

and

regional

drivers

of

accelerating

emissions

Michael

R.

Raupach

Gregg

Marland

Philippe

Ciais

Corinne

Le

Quere

Josep

G.

Canadell

Gernot

Klepper

and

Christopher

B.

Field

Global

Carbon

Project

Commonwealth

Scientific

and

Industrial

Research

Organisation

Marine

and

Atmospheric

Research

Canberra

ACT

Australia

Carbon

Dioxide

Information

Analysis

Center

Oak

Ridge

National

Laboratory

Oak

Ridge

TN

Commissariat

a

l'Energie

Atomique

Laboratorie

des

Sciences

du

Climat

et

de

l'Environnement

Gif

sur

Yvette

France

School

of

Environment

Sciences

University

of

East

Anglia

Norwich

United

Kingdom

British

Antarctic

Survey

Cambridge

OET

United

Kingdom

Kiel

Institute

for

the

World

Economy

D

Kiel

Germany

and

Carnegie

Institution

of

Washington

Department

of

Global

Ecology

Stanford

CA

Edited

by

William

C.

Clark

Harvard

University

Cambridge

MA

and

approved

April

-LRB-

received

for

review

January

-RRB-

emissions

from

fossil-fuel

burning

and

industrial

processes

have

been

accelerating

at

a

global

scale

with

their

growth

rate

increasing

from

y

for

to

y

for

The

emissions

growth

rate

since

was

greater

than

for

the

most

fossil-fuel

intensive

of

the

Intergovernmental

Panel

on

Climate

Change

emissions

scenarios

developed

in

the

late

Global

emissions

growth

since

was

driven

by

a

cessation

or

reversal

of

earlier

declining

trends

in

the

energy

intensity

of

gross

domestic

product

-LRB-

GDP

-RRB-

-LRB-

energy/GDP

-RRB-

and

the

carbon

intensity

of

energy

-LRB-

emissions/energy

-RRB-

coupled

with

continuing

increases

in

population

and

per-capita

GDP

Nearly

constant

or

slightly

increasing

trends

in

the

carbon

intensity

of

energy

have

been

recently

observed

in

both

developed

and

developing

regions

No

region

is

decarbonizing

its

energy

supply

The

growth

rate

in

emissions

is

strongest

in

rapidly

developing

economies

particularly

China

Together

the

developing

and

least-developed

economies

-LRB-

forming

of

the

world

's

population

-RRB-

accounted

for

of

global

emissions

growth

in

but

only

of

global

emissions

and

only

of

global

cumulative

emissions

since

the

century

The

results

have

implications

for

global

equity

carbon

intensity

of

economy

carbon

intensity

of

energy

scenarios

fossil

fuels

Kaya

identity

emissions

concerted

action

that

a

broad

portfolio

of

mitigation

measures

is

required

-LRB-

-RRB-

and

that

mitigation

is

not

only

feasible

but

highly

desirable

on

economic

as

well

as

social

and

ecological

grounds

-LRB-

-RRB-

The

global

emission

flux

from

fossil

fuel

combustion

and

industrial

processes

-LRB-

F

-RRB-

includes

contributions

from

seven

sources

national-level

combustion

of

solid

liquid

and

gaseous

fuels

flaring

of

gas

from

wells

and

industrial

processes

cement

production

oxidation

of

nonfuel

hydrocarbons

and

fuel

from

international

bunkers

used

for

shipping

and

air

transport

-LRB-

separated

because

it

is

often

not

included

in

national

inventories

-RRB-

Hence

F

FSolid

F

Liquid

F

Gas

F

Flare

F

Cement

F

NonFuelHC

F

Bunkers

-LSB-

-RSB-

where

the

fractional

contribution

of

each

source

to

the

total

F

for

is

indicated

The

Kaya

identity

-LRB-

-RRB-

expresses

the

global

F

as

a

product

of

four

driving

factors

F

P

G

P

E

G

F

E

Pgef

-LSB-

-RSB-

tmospheric

presently

contributes

of

the

gaseous

radiative

forcing

responsible

for

anthropogenic

climate

change

-LRB-

-RRB-

The

mean

global

atmospheric

concentration

has

increased

from

ppm

in

the

to

ppm

in

at

a

progressively

faster

rate

each

decade

-LRB-

-RRB-

This

growth

is

governed

by

the

global

budget

of

atmospheric

-LRB-

-RRB-

which

includes

two

major

anthropogenic

forcing

fluxes

-LRB-

i

-RRB-

emissions

from

fossil-fuel

combustion

and

industrial

processes

and

-LRB-

ii

-RRB-

the

flux

from

land-use

change

mainly

land

clearing

A

survey

of

trends

in

the

atmospheric

budget

-LRB-

-RRB-

shows

these

two

fluxes

were

respectively

gigatonnes

of

carbon

-LRB-

GtC

-RRB-

y

and

GtC

y

in

with

the

former

growing

rapidly

over

recent

years

and

the

latter

remaining

nearly

steady

This

paper

is

focused

on

emissions

from

fossil-fuel

combustion

and

industrial

processes

the

dominant

anthropogenic

forcing

flux

We

undertake

a

regionalized

analysis

of

trends

in

emissions

and

their

demographic

economic

and

technological

drivers

using

the

Kaya

identity

-LRB-

defined

below

-RRB-

and

annual

time-series

data

on

national

emissions

population

energy

consumption

and

gross

domestic

product

-LRB-

GDP

-RRB-

Understanding

the

observed

magnitudes

and

patterns

of

the

factors

influencing

global

emissions

is

a

prerequisite

for

the

prediction

of

future

climate

and

earth

system

changes

and

for

human

governance

of

climate

change

and

the

earth

system

Although

the

needs

for

both

understanding

and

governance

have

been

emerging

for

decades

-LRB-

as

demonstrated

by

the

United

Nations

Framework

Convention

on

Climate

Change

in

and

the

Kyoto

Protocol

in

-RRB-

it

is

now

becoming

widely

perceived

that

climate

change

is

an

urgent

challenge

requiring

globally

PNAS

June

vol

no.

A

where

P

is

global

population

G

is

world

GDP

or

gross

world

product

E

is

global

primary

energy

consumption

g

G/P

is

the

per-capita

world

GDP

e

E/G

is

the

energy

intensity

of

world

GDP

and

f

F/E

is

the

carbon

intensity

of

energy

Upper

and

lowercase

symbols

distinguish

extensive

and

intensive

variables

Author

contributions

M.R.R.

P.C.

C.L.Q.

J.G.C.

and

C.B.F.

designed

research

M.R.R.

G.M.

P.C.

and

J.G.C.

performed

research

M.R.R.

G.M.

P.C.

and

G.K.

analyzed

data

and

M.R.R.

G.M.

G.K.

and

C.B.F.

wrote

the

paper

The

authors

declare

no

conflict

of

interest

This

article

is

a

PNAS

Direct

Submission

Freely

available

online

through

the

PNAS

open

access

option

Abbreviations

GDP

gross

domestic

product

MER

market

exchange

rate

PPP

purchasing

power

parity

IPCC

Intergovernmental

Panel

on

Climate

Change

EU

European

Union

FSU

Former

Soviet

Union

developed

countries

developing

countries

leastdeveloped

countries

CDIAC

U.S.

Department

of

Energy

Carbon

Dioxide

Information

and

Analysis

Center

EIA

U.S.

Department

of

Energy

Energy

Information

Administration

To

whom

correspondence

should

be

addressed

E-mail

michael.raupach@csiro.au

CO

data

are

available

at

Yamaji

K.

Matsuhashi

R.

Nagata

Y.

Kaya

Y.

An

Integrated

System

for

GNP

Analysis

Case

Studies

on

Economic

Measures

for

Reduction

in

Japan

Workshop

on

Reduction

and

Removal

Measures

for

the

Next

Century

March

International

Institute

for

Applied

Systems

Analysis

Laxenburg

Austria

This

article

contains

supporting

information

online

at

by

The

National

Academy

of

Sciences

of

the

USA

cgi

doi

pnas

respectively

Combining

e

and

f

into

the

carbon

intensity

of

GDP

-LRB-

h

F/G

ef

-RRB-

the

Kaya

identity

can

also

be

written

as

F

P

Pgh

-LSB-

-RSB-

Emissions

-LRB-

GtC

-RRB-

Emissions

-LRB-

GtC

-RRB-

SUSTAINABILITY

SCIENCE

G

P

F

G

Defining

the

proportional

growth

rate

of

a

quantity

X

-LRB-

t

-RRB-

as

r

-LRB-

X

-RRB-

X

-LRB-

with

units

-LSB-

time

-RSB-

-RRB-

the

counterpart

of

the

Kaya

identity

for

proportional

growth

rates

is

rF

rP

rP

r

g

r

g

re

rh

r

f

-LSB-

-RSB-

Actual

emissions

CDIAC

stabilization

stabilization

which

is

an

exact

not

linearized

result

The

world

can

be

disaggregated

into

regions

-LRB-

distinguished

by

a

subscript

i

-RRB-

with

emission

Fi

population

Pi

GDP

Gi

energy

consumption

Ei

and

regional

intensities

gi

Gi/Pi

ei

Ei/Gi

fi

Fi/Ei

and

hi

Fi/Gi

e

i

fi

Writing

a

Kaya

identity

for

each

region

the

global

emission

F

can

be

expressed

by

summation

over

regions

as

F

i

Fi

i

Pi

gi

ei

fi

i

P

i

g

i

h

i

-LSB-

-RSB-

and

regional

contributions

to

the

proportional

growth

rate

in

global

emissions

r

-LRB-

F

-RRB-

are

rF

i

Fi

r

Fi

F

Actual

emissions

CDIAC

Actual

emissions

EIA

stabilization

stabilization

-LSB-

-RSB-

This

analysis

uses

nine

noncontiguous

regions

that

span

the

globe

and

cluster

nations

by

their

emissions

and

economic

profiles

The

regions

comprise

four

individual

nations

-LRB-

U.S.

China

Japan

and

India

identified

separately

because

of

their

significance

as

emitters

-RRB-

the

European

Union

-LRB-

EU

-RRB-

the

nations

of

the

Former

Soviet

Union

-LRB-

FSU

-RRB-

and

three

regions

spanning

the

rest

of

the

world

consisting

respectively

of

developed

-LRB-

-RRB-

developing

-LRB-

-RRB-

and

least-developed

-LRB-

-RRB-

countries

excluding

countries

in

other

regions

GDP

is

defined

and

measured

by

using

either

market

exchange

rates

-LRB-

MER

-RRB-

or

purchasing

power

parity

-LRB-

PPP

-RRB-

respectively

denoted

as

GM

and

GP

The

PPP

definition

gives

more

weight

to

developing

economies

Consequently

wealth

disparities

are

greater

when

measured

by

GM

than

GP

and

the

growth

rate

of

GP

is

greater

than

that

of

GM

-LSB-

supporting

information

-LRB-

SI

-RRB-

Fig.

-RSB-

Our

measure

of

Ei

is

commercial

primary

energy

including

-LRB-

i

-RRB-

fossil

fuels

-LRB-

ii

-RRB-

nuclear

and

-LRB-

iii

-RRB-

renewables

-LRB-

hydro

solar

wind

geothermal

and

biomass

-RRB-

when

used

to

generate

electricity

Total

primary

energy

additionally

includes

-LRB-

iv

-RRB-

other

energy

from

renewables

mainly

as

heat

from

biomass

Contribution

iv

can

be

large

in

developing

regions

but

it

is

not

included

in

Ei

except

in

the

U.S.

where

it

makes

a

small

-LRB-

-RRB-

contribution

-LRB-

SI

Text

Primary

Energy

-RRB-

Results

Global

Emissions

A

sharp

acceleration

in

global

emissions

oc

Fig.

Observed

global

emissions

including

all

terms

in

Eq

from

both

the

EIA

-LRB-

-RRB-

and

global

CDIAC

-LRB-

-RRB-

data

compared

with

emissions

scenarios

-LRB-

-RRB-

and

stabilization

trajectories

-LRB-

-RRB-

EIA

emissions

data

are

normalized

to

same

mean

as

CDIAC

data

for

to

account

for

omission

of

FCement

in

EIA

data

-LRB-

see

Materials

and

Methods

-RRB-

The

and

points

in

the

CDIAC

data

set

are

provisional

The

six

IPCC

scenarios

-LRB-

-RRB-

are

spline

fits

to

projections

-LRB-

initialized

with

observations

for

-RRB-

of

possible

future

emissions

for

four

scenario

families

and

which

emphasize

globalized

vs.

regionalized

development

on

the

A

B

axis

and

economic

growth

vs.

environmental

stewardship

on

the

axis

Three

variants

of

the

-LRB-

globalized

economically

oriented

-RRB-

scenario

lead

to

different

emissions

trajectories

-LRB-

intensive

dependence

on

fossil

fuels

-RRB-

-LRB-

alternative

technologies

largely

replace

fossil

fuels

-RRB-

and

-LRB-

balanced

energy

supply

between

fossil

fuels

and

alternatives

-RRB-

The

stabilization

trajectories

are

spline

fits

approximating

the

average

from

two

models

-LRB-

-RRB-

which

give

similar

results

They

include

uncertainty

because

the

emissions

pathway

to

a

given

stabilization

target

is

not

unique

curred

in

the

early

-LRB-

Fig.

Lower

-RRB-

This

trend

is

evident

in

two

data

sets

-LRB-

Materials

and

Methods

-RRB-

from

U.S.

Department

of

Energy

Energy

Information

Administration

-LRB-

EIA

-RRB-

data

the

proportional

growth

rate

in

global

emissions

-LSB-

r

-LRB-

F

-RRB-

-LRB-

-RRB-

dF/dt

-RSB-

was

y

for

the

period

inclusive

whereas

for

the

same

growth

rate

was

From

U.S.

Department

of

Energy

Carbon

Dioxide

Information

and

Analysis

Center

-LRB-

CDIAC

-RRB-

data

growth

rates

were

y

through

the

and

y

for

The

small

difference

arises

mainly

from

differences

in

estimated

emissions

from

China

for

-LRB-

Materials

and

Methods

-RRB-

Raupach

et

al.

Fig.

compares

observed

global

emissions

-LRB-

including

all

terms

in

Eq

-RRB-

with

six

Intergovernmental

Panel

on

Climate

Change

-LRB-

IPCC

-RRB-

emissions

scenarios

-LRB-

-RRB-

and

also

with

stabilization

trajectories

describing

emissions

pathways

for

stabilization

of

atmospheric

at

and

ppm

-LRB-

-RRB-

Observed

emissions

were

at

the

upper

edge

of

the

envelope

of

IPCC

emissions

scenarios

The

actual

emissions

trajectory

since

was

close

to

the

highest-emission

scenario

in

the

envelope

More

importantly

the

emissions

growth

rate

since

exceeded

that

for

the

scenario

Emissions

since

were

also

far

above

the

mean

stabilization

trajectories

for

both

and

ppm

A

breakdown

of

emissions

among

sources

shows

that

solid

liquid

and

gas

fuels

contributed

-LRB-

for

-RRB-

and

respectively

to

global

emissions

-LRB-

Eq

-RRB-

However

this

distribution

varied

strongly

among

regions

solid

-LRB-

mainly

coal

-RRB-

fuels

made

up

a

larger

and

more

rapidly

growing

share

of

PNAS

June

vol

no.

F

P

gM

GM/P

eM

E/GM

f

F/E

hM

F/GM

F

P

gP

GP/P

eP

E/GP

f

F/E

hP

F/GP

Fig.

Factors

in

the

Kaya

identity

F

Pgef

Pgh

as

global

averages

All

quantities

are

normalized

to

at

Intensities

are

calculated

by

using

GM

-LRB-

Left

-RRB-

and

GP

-LRB-

Right

-RRB-

In

both

Left

and

Right

the

black

line

-LRB-

F

-RRB-

is

the

product

of

the

red

-LRB-

P

-RRB-

orange

-LRB-

g

-RRB-

green

-LRB-

e

-RRB-

and

light

blue

-LRB-

f

-RRB-

lines

-LRB-

Eq

-RRB-

or

equivalently

of

the

red

-LRB-

P

-RRB-

orange

-LRB-

g

-RRB-

and

dark

blue

-LRB-

h

-RRB-

lines

-LRB-

Eq

-RRB-

Because

h

ef

the

dark

blue

line

is

the

product

of

the

green

and

light

blue

lines

Sources

are

as

in

Table

emissions

in

developing

regions

-LRB-

the

sum

of

China

India

and

-RRB-

than

in

developed

regions

-LRB-

U.S.

EU

Japan

and

-RRB-

and

the

FSU

region

had

a

much

stronger

reliance

on

gas

than

the

world

average

-LRB-

SI

Fig.

-RRB-

To

diagnose

drivers

of

trends

in

global

emissions

Fig.

superimposes

time

series

for

of

the

Kaya

factors

F

P

g

e

f

and

h

ef

-LRB-

Eqs

and

-RRB-

Fig.

Left

and

Right

respectively

use

the

MER

and

PPP

forms

of

GDP

-LRB-

GM

and

GP

-RRB-

to

calculate

intensities

All

quantities

are

normalized

to

in

the

year

to

show

the

relative

contributions

of

changes

in

Kaya

factors

to

changes

in

emissions

Table

gives

recent

-LRB-

-RRB-

values

without

normalization

In

Fig.

Left

-LRB-

MER-based

-RRB-

the

Kaya

identity

is

F

PgMeMf

PgMhM

-LRB-

with

gM

GM/P

eM

E/GM

and

hM

F/GM

-RRB-

The

increase

in

the

growth

rate

of

F

after

is

clear

Before

F

increased

as

a

result

of

increases

in

both

P

and

gM

at

roughly

equal

rates

offset

by

a

decrease

in

eM

with

f

declining

very

slowly

Therefore

hM

eMf

declined

slightly

more

quickly

than

eM

After

the

increases

in

P

and

gM

continued

at

about

their

rates

but

eM

and

f

-LRB-

and

therefore

hM

-RRB-

ceased

to

decrease

leading

to

a

substantial

increase

in

the

growth

rate

of

F

In

fact

both

eM

and

f

have

increased

since

Similar

trends

are

evident

in

Fig.

Right

-LRB-

PPP-based

-RRB-

using

the

Kaya

identity

F

PgP

ePf

PgP

hP

-LRB-

with

gP

GP/P

eP

E/GP

and

hP

F/GP

-RRB-

The

long-term

-LRB-

since

-RRB-

rate

of

increase

of

gP

and

the

rates

Table

Values

of

extensive

and

intensive

variables

in

Fi

MtC/y

U.S.

EU

Japan

FSU

China

India

World

344 578 696

Pi

million

295 437 128 150

GMi

G$

y

of

decrease

of

eP

and

hP

were

all

larger

than

for

their

counterparts

gM

eM

and

hM

associated

with

the

higher

global

growth

rate

of

GP

than

of

GM

-LRB-

SI

Fig.

-RRB-

There

was

a

change

in

the

trajectory

of

eP

after

similar

to

that

for

eM

but

superimposed

on

a

larger

long-term

rate

of

decrease

Hence

Fig.

Left

and

Right

both

identify

the

driver

of

the

increase

in

the

growth

rate

of

global

emissions

after

as

a

combination

of

reductions

or

reversals

in

long-term

decreasing

trends

in

the

global

carbon

intensity

of

energy

-LRB-

f

-RRB-

and

energy

intensity

of

GDP

-LRB-

e

-RRB-

Regional

Emissions

The

regional

distribution

of

emissions

-LRB-

Fig.

-RRB-

is

similar

to

that

of

-LRB-

commercial

-RRB-

primary

energy

consumption

-LRB-

Ei

-RRB-

but

very

different

from

that

of

population

-LRB-

Pi

-RRB-

with

Fi

and

Ei

weighted

toward

developed

regions

and

Pi

toward

developing

regions

Drivers

of

regional

emissions

are

shown

in

Fig.

by

plotting

the

normalized

factors

in

the

nine

regional

Kaya

identities

using

GDP

-LRB-

PPP

-RRB-

Equivalent

plots

with

GDP

-LRB-

MER

-RRB-

are

nearly

identical

-LRB-

SI

Fig.

-RRB-

In

the

developed

regions

-LRB-

U.S.

Europe

Japan

and

-RRB-

Fi

increased

from

to

as

a

result

of

relatively

rapid

growth

in

mean

income

-LRB-

gi

-RRB-

and

slow

growth

in

population

-LRB-

Pi

-RRB-

offset

in

most

regions

by

decreases

in

the

energy

intensity

of

GDP

-LRB-

ei

-RRB-

Declines

in

ei

indicate

a

progressive

decoupling

in

most

developed

regions

between

energy

use

and

GDP

growth

The

carbon

intensity

of

energy

-LRB-

fi

-RRB-

remained

nearly

steady

Ei

EJ/y

GPi

G$

y

gPi

GPi/Pi

k

y

ePi

Ei/GPi

MJ

fi

Fi/Ei

gC/MJ

hPi

Fi/GPi

gC

Fi/Pi

tC/y

Ei/Pi

kW

All

dollar

amounts

-LRB-

-RRB-

are

in

constant-price

-LRB-

-RRB-

U.S.

dollars

Data

sources

EIA

-LRB-

Fi

Ei

-RRB-

UNSD

-LRB-

Pi

GMi

-RRB-

and

WEO

-LRB-

GPi

-RRB-

cgi

doi

pnas

Raupach

et

al.

8000 7000 6000 5000

4000 3000 2000 1000

Emissions

-LRB-

MtC

y

-RRB-

India

China

FSU

Japan

EU

USA

Fig.

EIA

Fossil-fuel

emissions

-LRB-

MtC

y

-RRB-

for

nine

regions

Data

source

is

USA

EU

Japan

F

P

gP

GP/P

eP

E/GP

f

F/E

hP

F/GP

FSU

China

India

1980 1985 1990 1995

1980 1985 1990 1995

1980 1985 1990 1995

Fig.

Factors

in

the

Kaya

identity

F

Pgef

Pgh

for

nine

regions

All

quantities

are

normalized

to

at

Intensities

are

calculated

with

GPi

-LRB-

PPP

-RRB-

For

FSU

normalizing

GPi

in

was

back-extrapolated

Other

details

are

as

for

Fig.

Raupach

et

al.

PNAS

June

vol

no.

SUSTAINABILITY

SCIENCE

In

the

FSU

emissions

decreased

through

the

because

of

the

fall

in

economic

activity

after

the

collapse

of

the

Soviet

Union

Incomes

-LRB-

gi

-RRB-

decreased

in

parallel

with

emissions

-LRB-

Fi

-RRB-

and

a

shift

toward

resource-based

economic

activities

led

to

an

increase

in

ei

and

hi

In

the

late

incomes

started

to

rise

again

but

increases

in

emissions

were

slowed

by

more

efficient

use

of

energy

from

on

due

to

higher

prices

and

shortages

because

of

increasing

exports

In

China

gi

rose

rapidly

and

Pi

slowly

over

the

whole

period

Progressive

decoupling

of

income

growth

from

energy

consumption

-LRB-

declining

ei

-RRB-

was

achieved

up

to

through

improvements

in

energy

efficiency

during

the

transition

to

a

market

based

economy

Since

the

early

there

has

been

a

recent

rapid

growth

in

emissions

associated

with

very

high

growth

rates

in

incomes

-LRB-

gi

-RRB-

and

a

reversal

of

earlier

declines

in

ei

In

other

developing

regions

-LRB-

India

and

-RRB-

increases

in

Fi

were

driven

by

a

combination

of

increases

in

Pi

and

gi

with

no

strong

trends

in

ei

or

fi

Growth

in

emissions

-LRB-

Fi

-RRB-

exceeded

growth

in

income

-LRB-

gi

-RRB-

Unlike

China

and

the

developed

countries

strong

technological

improvements

in

energy

efficiency

have

not

yet

occurred

in

these

regions

with

the

exception

of

India

over

the

last

few

years

where

ei

declined

Differences

in

intensities

across

regions

are

both

large

-LRB-

Table

-RRB-

and

persistent

in

time

There

are

enormous

differences

in

Gi/Pi

-RRB-

the

variation

being

smaller

-LRB-

although

still

income

-LRB-

gi

large

-RRB-

for

gPi

than

for

gMi

The

energy

intensity

and

carbon

Ei/Gi

and

hi

Fi/Gi

ei

fi

-RRB-

vary

intensity

of

GDP

-LRB-

ei

significantly

between

regions

although

less

than

for

income

-LRB-

gi

-RRB-

The

carbon

intensity

of

energy

-LRB-

fi

Fi/Ei

-RRB-

varies

much

less

than

other

intensities

for

most

regions

it

is

between

and

grams

of

carbon

per

megajoule

-LRB-

gC/MJ

-RRB-

although

for

China

and

India

it

is

somewhat

higher

gC/MJ

In

time

fi

has

decreased

slowly

from

to

as

a

global

average

-LRB-

Fig.

-RRB-

and

in

most

regions

-LRB-

Fig.

-RRB-

This

indicates

that

the

commercial

energy

supply

mix

has

changed

only

slowly

even

on

a

regional

level

The

global

average

f

has

increased

slightly

since

The

regional

per-capita

emissions

Fi/Pi

gihi

and

per-capita

primary

energy

consumption

Ei/Pi

giei

are

important

indicators

of

global

equity

Both

quantities

vary

greatly

across

regions

but

much

less

in

time

-LRB-

Table

and

SI

Fig.

-RRB-

The

interregion

range

a

factor

of

extends

from

the

U.S.

-LRB-

for

which

both

quantities

are

times

the

global

average

-RRB-

to

the

region

-LRB-

for

which

they

India

China

Cumul

Flux

Growth

Pop

FSU

Japan

EU

USA

Fig.

Relative

contributions

of

nine

regions

to

cumulative

global

emissions

-LRB-

-RRB-

current

global

emission

flux

-LRB-

-RRB-

global

emissions

growth

rate

-LRB-

year

smoothed

for

-RRB-

and

global

population

-LRB-

-RRB-

Data

sources

as

in

Table

with

cumulative

emissions

from

CDIAC

are

of

the

global

average

-RRB-

From

to

global

average

per-capita

emissions

-LRB-

F/P

gh

-RRB-

and

per-capita

primary

energy

consumption

-LRB-

E/P

ge

-RRB-

were

both

nearly

steady

at

tC/y

per

person

and

kW

per

person

respectively

but

F/P

rose

by

and

E/P

by

over

the

years

Temporal

Perspectives

In

the

period

developing

countries

had

a

greater

share

of

emissions

growth

than

of

emissions

themselves

-LRB-

Fig.

-RRB-

Here

we

extend

this

observation

by

considering

cumulative

emissions

throughout

the

industrial

era

-LRB-

taken

to

start

in

-RRB-

The

global

cumulative

fossil-fuel

emission

C

-LRB-

t

-RRB-

-LRB-

in

gigatonnes

of

carbon

-RRB-

is

defined

as

the

time

integral

of

the

global

emission

flux

F

-LRB-

t

-RRB-

from

to

t.

Regional

cumulative

emissions

Ci

-LRB-

t

-RRB-

are

defined

similarly

Fig.

compares

the

relative

contributions

in

of

the

nine

regions

to

the

global

cumulative

emission

C

-LRB-

t

-RRB-

the

emission

flux

F

-LRB-

t

-RRB-

-LSB-

the

first

derivative

of

C

-LRB-

t

-RRB-

-RSB-

the

emissions

growth

rate

-LSB-

the

second

derivative

of

C

-LRB-

t

-RRB-

-RSB-

and

population

The

measure

of

regional

emissions

growth

used

here

is

the

weighted

proportional

growth

rate

-LRB-

Fi/F

-RRB-

r

-LRB-

Fi

-RRB-

which

shows

the

contribution

of

each

region

to

the

global

r

-LRB-

F

-RRB-

-LRB-

Eq

-RRB-

In

the

developed

regions

contributed

most

to

cumulative

emissions

and

least

to

emissions

growth

and

vice

versa

for

developing

regions

China

in

had

a

larger

than

pro-rata

share

-LRB-

on

a

population

basis

-RRB-

of

the

emissions

growth

but

still

a

smaller

than

pro-rata

share

of

actual

emissions

and

a

very

small

share

of

cumulative

emissions

India

and

the

and

regions

had

smaller

than

pro-rata

shares

of

emissions

measures

on

all

time

scales

-LRB-

growth

actual

emissions

and

cumulative

emissions

-RRB-

recent

rapid

growth

in

atmospheric

-LRB-

ppm

y

-RRB-

is

high

and

rising

emissions

mostly

from

fossil

fuels

The

strong

global

fossil-fuel

emissions

growth

since

was

driven

not

only

by

long-term

increases

in

population

-LRB-

P

-RRB-

and

per-capita

global

GDP

-LRB-

g

-RRB-

but

also

by

a

cessation

or

reversal

of

earlier

declining

trends

in

the

energy

intensity

of

GDP

-LRB-

e

-RRB-

and

the

carbon

intensity

of

energy

-LRB-

f

-RRB-

In

particular

steady

or

slightly

increasing

recent

trends

in

f

occurred

in

both

developed

and

developing

regions

In

this

sense

no

region

is

decarbonizing

its

energy

supply

Continuous

decreases

in

both

e

and

f

-LRB-

and

therefore

in

carbon

intensity

of

GDP

h

ef

-RRB-

are

postulated

in

all

IPCC

emissions

scenarios

to

-LRB-

-RRB-

so

that

the

predicted

rate

of

global

emissions

growth

is

less

than

the

economic

growth

rate

Without

these

postulated

decreases

predicted

emissions

over

the

coming

century

would

be

up

to

several

times

greater

than

those

from

current

emissions

scenarios

-LRB-

-RRB-

In

the

unfolding

reality

since

the

global

average

f

has

actually

increased

and

there

has

not

been

a

compensating

faster

decrease

in

e.

Consequently

there

has

been

a

cessation

of

the

earlier

declining

trend

in

h

This

has

meant

that

even

the

more

fossil-fuel-intensive

IPCC

scenarios

underestimated

actual

emissions

growth

during

this

period

The

recent

growth

rate

in

emissions

was

strongest

in

rapidly

developing

economies

particularly

China

because

of

very

strong

economic

growth

-LRB-

gi

-RRB-

coupled

with

increases

in

ei

fi

and

therefore

hi

ei

fi

These

trends

reflect

differences

in

trajectories

between

developed

and

developing

nations

developed

nations

have

used

two

centuries

of

fossil-fuel

emissions

to

achieve

their

present

economic

status

whereas

developing

nations

are

currently

experiencing

intensive

development

with

a

high

energy

requirement

much

of

the

demand

being

met

by

fossil

fuels

A

significant

factor

is

the

physical

movement

of

energy-intensive

activities

from

developed

to

developing

countries

-LRB-

-RRB-

with

increasing

globalization

of

the

economy

Finally

we

note

-LRB-

Fig.

-RRB-

that

the

developing

and

leastdeveloped

economies

-LRB-

China

India

and

-RRB-

representing

of

the

world

's

population

accounted

for

of

global

emissions

growth

in

However

they

accounted

for

only

of

global

emissions

in

that

year

and

only

of

global

cumulative

emissions

since

the

start

of

the

industrial

revolution

A

long-term

-LRB-

multidecadal

-RRB-

perspective

on

emissions

is

essential

because

of

the

long

atmospheric

residence

time

of

Therefore

Fig.

has

implications

for

long-term

global

equity

and

for

burden

sharing

in

global

responses

to

climate

change

Materials

and

Methods

Annual

time

series

at

a

national

and

thence

regional

scale

-LRB-

for

except

where

otherwise

stated

-RRB-

were

assembled

for

emissions

-LRB-

Fi

-RRB-

population

-LRB-

Pi

-RRB-

GDP

-LRB-

GMi

and

GPi

-RRB-

and

primary

energy

consumption

-LRB-

Ei

-RRB-

from

four

public

sources

the

EIA

for

Fi

and

Ei

the

CDIAC

for

historic

Fi

from

-LRB-

-RRB-

the

United

Nations

Statistics

Division

for

Pi

and

GMi

and

the

World

Economic

Outlook

of

the

International

Monetary

Fund

for

GPi

We

inferred

GPi

from

country

shares

of

global

GP

and

the

annual

growth

rate

of

global

GP

in

constant-price

U.S.

dollars

taking

GM

GP

in

We

analyzed

nine

noncontiguous

regions

-LRB-

U.S.

EU

Japan

FSU

China

India

and

see

Introduction

and

SI

Text

Definition

of

Regions

-RRB-

Because

only

aggregated

data

were

available

for

FSU

provinces

before

all

new

countries

issuing

from

the

FSU

around

remained

allocated

to

the

FSU

region

after

that

date

even

though

some

-LRB-

Estonia

Latvia

and

Lithua

EIA

Discussion

emissions

need

to

be

considered

in

the

context

of

the

whole

carbon

cycle

Of

the

total

cumulative

anthropogenic

emission

from

both

fossil

fuels

and

land

use

change

less

than

half

remains

in

the

atmosphere

the

rest

having

been

taken

up

by

land

and

ocean

sinks

-LRB-

ref

SI

Text

The

Global

Carbon

Cycle

-RRB-

For

the

recent

period

the

fraction

of

total

anthropogenic

emissions

remaining

in

the

atmosphere

-LRB-

the

airborne

fraction

-RRB-

was

This

fraction

has

increased

slowly

with

time

-LRB-

J.

G.

Canadell

C.L.Q.

M.R.R.

C.B.F.

E.

T.

Buitenhaus

et

al.

unpublished

data

-RRB-

implying

a

slight

weakening

of

sinks

relative

to

emissions

However

the

dominant

factor

accounting

for

the

cgi

doi

pnas

CDIAC

http

cdiac.esd.ornl.gov

trends/emis/tre

coun.htm

United

Nations

Statistics

Division

http

and

World

Economic

Outlook

of

the

International

Monetary

Fund

download.aspx

Raupach

et

al.

nia

-RRB-

are

now

members

of

the

EU

European

nations

who

are

not

members

of

the

EU

-LRB-

Norway

and

Switzerland

-RRB-

were

placed

in

group

Regions

and

were

defined

by

using

United

Nations

Statistics

Division

classifications

Region

includes

all

other

nations

Comparisons

were

made

among

three

different

emissions

data

sets

CDIAC

global

total

emissions

CDIAC

country-level

emissions

and

EIA

country-level

emissions

These

revealed

small

discrepancies

with

two

origins

First

different

data

sets

include

different

components

of

total

emissions

Eq

The

CDIAC

global

total

includes

all

terms

CDIAC

country-level

data

omit

FBunkers

and

FNonFuelHC

and

EIA

country-level

data

omit

FCement

but

include

FBunkers

by

accounting

at

country

of

purchase

The

net

effect

is

that

the

EIA

and

CDIAC

countrylevel

data

yield

total

emissions

-LRB-

by

summation

-RRB-

that

are

within

of

each

other

although

they

include

slightly

different

components

of

Eq

and

the

CDIAC

global

total

is

larger

than

both

sums

over

countries

The

second

kind

of

Hofmann

DJ

Butler

JH

Dlugokencky

EJ

Elkins

JW

Masarie

K

Montzka

SA

Tans

P

-LRB-

-RRB-

Tellus

Ser

B

Etheridge

DM

Steele

LP

Langenfelds

RL

Francey

RJ

Barnola

JM

Morgan

VI

-LRB-

-RRB-

J

Geophys

Res

Atmos

Raupach

MR

Canadell

JG

-LRB-

-RRB-

in

Observing

the

Continental

Scale

Greenhouse

Gas

Balance

of

Europe

eds

Dolman

H

Valentini

R

Freibauer

A

-LRB-

Springer

Berlin

-RRB-

in

press

Sabine

CL

Heimann

M

Artaxo

P

Bakker

DCE

Chen

C-TA

Field

CB

Gruber

N

Le

Quere

C

Prinn

RG

Richey

JD

et

al.

-LRB-

-RRB-

in

The

Global

Carbon

Cycle

Integrating

Humans

Climate

and

the

Natural

World

eds

Field

CB

Raupach

MR

-LRB-

Island

Washington

DC

-RRB-

pp

Hoffert

MI

Caldeira

K

Benford

G

Criswell

DR

Green

C

Herzog

H

Jain

AK

Kheshgi

HS

Lackner

KS

Lewis

JS

et

al.

-LRB-

-RRB-

Science

Caldeira

K

Granger

Morgan

M

Baldocchi

DD

Brewer

PG

Chen

C-TA

Nabuurs

G-J

Nakicenovic

N

Robertson

GP

-LRB-

-RRB-

in

The

Global

Carbon

Cycle

Integrating

Humans

Climate

and

the

Natural

World

eds

Field

CB

Raupach

MR

-LRB-

Island

Washington

DC

-RRB-

pp

Stern

N

-LRB-

-RRB-

Stern

Review

on

the

Economics

of

Climate

Change

-LRB-

Cambridge

Univ

Press

Cambridge

UK

-RRB-

discrepancy

arises

from

differences

at

the

country

level

the

main

issue

being

with

data

for

China

Emissions

for

China

from

the

EIA

and

CDIAC

data

sets

both

show

a

significant

slowdown

in

the

late

which

is

a

recognized

event

-LRB-

-RRB-

associated

mainly

with

closure

of

small

factories

and

power

plants

and

with

policies

to

improve

energy

efficiency

-LRB-

-RRB-

However

the

CDIAC

data

suggest

a

much

larger

emissions

decline

from

to

than

the

EIA

data

-LRB-

SI

Fig.

-RRB-

The

CDIAC

emissions

estimates

are

based

on

the

UN

energy

data

set

which

is

currently

undergoing

revisions

for

China

Therefore

we

use

EIA

as

the

primary

source

for

emissions

data

subsequent

to

We

thank

Mr.

Peter

Briggs

for

assistance

with

preparation

of

figures

This

work

has

been

a

collaboration

under

the

Global

Carbon

Project

-LRB-

GCP

-RRB-

of

the

Earth

System

Science

Partnership

-LRB-

-RRB-

Support

for

the

GCP

from

the

Australian

Climate

Change

Science

Program

is

appreciated

Nakicenovic

N

Alcamo

J

Davis

G

de

Vries

B

Fenhann

J

Gaffin

S

Gregory

K

Grubler

A

Jung

TY

Kram

T

et

al.

-LRB-

-RRB-

IPCC

Special

Report

on

Emissions

Scenarios

-LRB-

Cambridge

Univ

Press

Cambridge

UK

-RRB-

Nakicenovic

N

-LRB-

-RRB-

in

The

Global

Carbon

Cycle

Integrating

Humans

Climate

and

the

Natural

World

eds

Field

CB

Raupach

MR

-LRB-

Island

Washington

DC

-RRB-

pp

Houghton

JT

Ding

Y

Griggs

DJ

Noguer

M

van

der

Linden

PJ

Dai

X

Maskell

K

Johnson

CA

-LRB-

-RRB-

Climate

Change

The

Scientific

Basis

eds

Houghton

JT

Ding

Y

Griggs

DJ

Noguer

M

van

der

Linden

PJ

Dai

X

Maskell

K

Johnson

CA

-LRB-

Cambridge

Univ

Press

Cambridge

UK

-RRB-

Wigley

TML

Richels

R

Edmonds

JA

-LRB-

-RRB-

Nature

Joos

F

Plattner

GK

Stocker

TF

Marchal

O

Schmittner

A

-LRB-

-RRB-

Science

Edmonds

JA

Joos

F

Nakicenovic

N

Richels

RG

Sarmiento

JL

-LRB-

-RRB-

in

The

Global

Carbon

Cycle

Integrating

Humans

Climate

and

the

Natural

World

eds

Field

CB

Raupach

MR

-LRB-

Island

Washington

DC

-RRB-

pp

Rothman

DS

-LRB-

-RRB-

Ecol

Econ

Marland

G

Rotty

RM

-LRB-

-RRB-

Tellus

Ser

B

Streets

DG

Jiang

KJ

Hu

XL

Sinton

JE

Zhang

XQ

Xu

DY

Jacxobson

MZ

Hansen

JE

-LRB-

-RRB-

Science

Wu

L

Kaneko

S

Matsuoka

S

-LRB-

-RRB-

Energy

Pol

Raupach

et

al.

PNAS

June

vol

no.

SUSTAINABILITY

SCIENCE

O O B O O O B B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O B O B O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O B O O O O O O O B O O O O O O O O O O O O O B O O O B O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O B O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O B B O O O O O O O O O O O B O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B B O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O B B O O O O O O O O B O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O B B O O O O O O O O O O O O O B B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O B O O O O O O O O O O O O O O O B O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O B O O O O O O O O O O O B B O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O B O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O B O O B O B O O O O O O O O O O B O O O O O B O O O O O O O O O O O B O O O O O O O O O B B O O O O B O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O B B O O B O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B B O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B B O O O O O O O O O O O O O O O O O O O O B B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O B O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O B O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O B O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O B B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O B O O O O O O O B O O O O O O O O O O O O O O B O O O O O O O O O B O O O B O O O O O O O B O O O O O O O O O O B O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O B B O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O B O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O B O O O O O O O O O O O B O O O O O O O O O O O O O O O B O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O B O O O O O O O O O O O O O O B B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B B O O O O O O O O O O B O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O B B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O B O O O B O O O O B O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O B O O O O O O O O O O O O O O O O O O O O O B O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O

ipcc co2 climate regional emissions economics projections carbon


Relating

Three-Dimensional

Structures

to

Protein

Networks

Provides

Evolutionary

Insights

Philip

M.

Kim

et

al.

Science

-LRB-

-RRB-

DOI

science

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The

title

Science

is

a

registered

trademark

of

AAAS

Downloaded

from

on

May

CORRECTED

JANUARY

SEE

LAST

PAGE

REPORTS

Our

findings

reveal

that

TLR

signaling

is

not

required

for

robust

antibody

responses

to

antigen

when

given

in

four

commonly

used

adjuvants

in

particular

FCA

which

is

widely

thought

to

depend

on

TLR

signaling

for

its

adjuvant

effect

-LRB-

-RRB-

However

ligands

that

signal

through

the

and

TRIF

pathways

can

costimulate

these

responses

and

affect

the

antibody

class

of

the

response

as

has

been

known

for

LPS

for

many

years

-LRB-

-RRB-

and

is

indicated

by

the

modest

boost

seen

in

mice

immunized

with

Ribi

adjuvant

-LRB-

Fig.

-RRB-

By

exclusion

our

data

suggest

the

likelihood

that

non-TLR

mediated

innate

signals

may

be

involved

in

the

augmentation

of

adaptive

antibody

responses

It

is

also

formally

possible

that

independent

modes

of

TLR

signaling

are

yet

to

be

discovered

possibly

through

TRAM

and

TIRAP

although

so

far

there

is

no

evidence

for

this

Our

results

extend

and

clarify

previous

studies

A

recent

paper

involving

mice

asserted

that

T

cell

dependent

antibody

responses

require

activation

of

TLRs

in

B

cells

-LRB-

-RRB-

However

that

inference

was

based

on

the

use

of

LPS

as

an

adjuvant

rather

than

more

commonly

used

adjuvants

such

as

FCA

or

alum

Indeed

an

earlier

study

found

that

although

mice

failed

to

make

an

response

to

ovalbumin

given

in

FCA

they

still

made

good

and

IgE

antibody

responses

and

antigen

given

in

alum

could

promote

an

IgE

response

-LRB-

-RRB-

However

in

those

studies

the

remaining

antibody

responses

in

mice

could

conceivably

have

involved

TLR

signaling

through

TRIF-dependent

pathways

a

caveat

that

does

not

apply

to

our

data

We

clearly

find

that

-LRB-

also

known

as

-RRB-

responses

to

protein

antigen

given

in

alum

or

FCA

are

robust

in

Trif

mice

in

apparent

contradiction

to

both

studies

of

mice

mentioned

-LRB-

-RRB-

and

other

studies

implicating

a

requirement

of

or

TLR

signaling

in

the

generation

of

antibodies

It

may

be

that

TLR

ligand

driven

suppression

of

production

occurs

in

mice

with

intact

TRIF

signaling

that

lack

for

example

through

cytokine-driven

polarization

of

the

T

helper

response

-LRB-

-RRB-

The

response

is

promoted

by

IFN-a/b

or

IFN-g

-LRB-

-RRB-

In

viral

infection

the

response

is

lost

in

mice

lacking

both

IFN-a/bR

and

IFN-gR

-LRB-

-RRB-

Because

we

found

good

responses

upon

immunization

of

Trif

mice

our

results

may

indicate

that

these

immunizations

can

stimulate

TLRindependent

IFN

production

The

antibody

response

to

the

T

cell

independent

type

II

antigen

TNP-Ficoll

was

relatively

normal

in

Trif

mice

although

it

was

slightly

lower

at

later

time

points

Interestingly

the

component

of

the

antigenspecific

response

of

Trif

mice

was

not

significantly

lower

than

normal

despite

their

reduced

preimmune

total

serum

levels

It

has

been

argued

that

the

class

switch

to

requires

cytokines

produced

by

accessory

cells

-LRB-

-RRB-

If

this

is

so

it

is

clear

from

these

results

that

production

of

the

cytokines

in

question

does

not

require

TLR

stimulation

of

B

cells

or

accessory

cells

That

B

cells

can

respond

to

autologous

DNA

and

RNA

through

TLR

signaling

-LRB-

-RRB-

raised

the

possibility

that

TLRs

could

affect

preimmune

development

or

maintenance

of

B

cell

subsets

particularly

the

marginal

zone

and

compartments

However

our

findings

that

Trif

mice

generate

abundant

and

marginal

zone

B

cells

appear

to

rule

out

definitively

a

required

role

for

TLR

signaling

in

their

development

Our

data

do

not

contest

the

long-held

understanding

that

TLR

ligands

can

augment

antibody

responses

However

it

is

surprising

given

the

recent

emphasis

on

the

importance

of

TLRs

in

the

initiation

of

the

adaptive

immune

response

that

we

fail

to

find

a

deficit

in

the

early

antibody

responses

of

Trif

mice

using

conventional

antigens

and

immunization

regimens

Our

data

are

more

consistent

with

a

model

in

which

TLRs

play

roles

in

early

microbial

suppression

regulation

of

the

antibody

class

and

sustaining

antibody

secretion

at

late

times

after

immunization

rather

than

as

an

essential

component

of

the

self/nonself

discrimination

of

the

adaptive

immune

response

These

data

have

implications

for

vaccine

design

because

they

indicate

that

robust

antibody

responses

to

moderate

doses

of

antigens

can

be

achieved

when

given

in

the

total

absence

of

TLR

ligands

Because

TLR-mediated

signals

can

be

toxic

our

findings

raise

the

possibility

that

unwanted

side

effects

of

adjuvants

may

be

avoided

by

excluding

TLR

ligands

from

adjuvants

References

and

Notes

K.

Takeda

S.

Akira

Int

Immunol

-LRB-

-RRB-

B.

Beutler

et

al.

Annu

Rev.

Immunol

-LRB-

-RRB-

J.

Andersson

O.

Sjoberg

G.

Moller

Transplant

Rev.

-LRB-

-RRB-

C.

Pasare

R.

Medzhitov

Nature

-LRB-

-RRB-

D.

Nemazee

A.

Gavin

K.

Hoebe

B.

Beutler

Nature

-LRB-

-RRB-

K.

Hoebe

et

al.

Nature

-LRB-

-RRB-

M.

Yamamoto

et

al.

Science

-LRB-

-RRB-

E.

Janssen

et

al.

Immunity

-LRB-

-RRB-

Materials

and

methods

are

available

as

supporting

material

on

Science

Online

C.

Pasare

R.

Medzhitov

Curr

Opin

Immunol

-LRB-

-RRB-

M.

Schnare

et

al.

Nat

Immunol

-LRB-

-RRB-

T.

Kaisho

et

al.

Int

Immunol

-LRB-

-RRB-

C.

M.

Snapper

W.

E.

Paul

Science

-LRB-

-RRB-

F.

D.

Finkelman

et

al.

J.

Exp

Med

-LRB-

-RRB-

M.

F.

van

den

Broek

U.

Muller

S.

Huang

M.

Aguet

R.

M.

Zinkernagel

J.

Virol

-LRB-

-RRB-

C.

M.

Snapper

et

al.

J.

Exp

Med

-LRB-

-RRB-

E.

A.

Leadbetter

et

al.

Nature

-LRB-

-RRB-

C.

M.

Lau

et

al.

J.

Exp

Med

-LRB-

-RRB-

We

thank

D.

Kono

and

A.

Theofilopoulos

for

comments

on

the

manuscript

A.

Rolink

for

antibody

and

G.

Nemerow

and

N.

Sarvetnick

for

use

of

instruments

Supported

by

NIH

grants

to

D.N.

to

B.B.

and

to

B.D.

Supporting

Online

Material

Materials

and

Methods

Figs

to

Tables

and

References

September

accepted

November

science

Relating

Three-Dimensional

Structures

to

Protein

Networks

Provides

Evolutionary

Insights

Philip

M.

Kim

Long

J.

Lu

Yu

Xia

Mark

B.

Most

studies

of

protein

networks

operate

on

a

high

level

of

abstraction

neglecting

structural

and

chemical

aspects

of

each

interaction

Here

we

characterize

interactions

by

using

atomic-resolution

information

from

three-dimensional

protein

structures

We

find

that

some

previously

recognized

relationships

between

network

topology

and

genomic

features

-LRB-

e.g.

hubs

tending

to

be

essential

proteins

-RRB-

are

actually

more

reflective

of

a

structural

quantity

the

number

of

distinct

binding

interfaces

Subdividing

hubs

with

respect

to

this

quantity

provides

insight

into

their

evolutionary

rate

and

indicates

that

additional

mechanisms

of

network

growth

are

active

in

evolution

-LRB-

beyond

effective

preferential

attachment

through

gene

duplication

-RRB-

P

rotein

interaction

networks

are

principal

components

of

a

systems-level

description

of

the

cell

-LRB-

-RRB-

Many

previous

studies

have

explored

global

aspects

of

network

topology

clearly

linking

it

to

protein

function

expression

dynamics

and

other

genomic

features

-LRB-

-RRB-

In

particular

a

protein

's

degree

-LRB-

number

of

interaction

partners

-RRB-

is

an

important

factor

and

proteins

with

high

degree

-LRB-

hubs

-RRB-

have

been

found

VOL

SCIENCE

to

be

essential

-LRB-

-RRB-

However

most

network

studies

have

not

considered

the

structural

and

chemical

aspects

of

interactions

only

recently

have

there

been

proposals

to

use

structural

information

for

systems

biology

-LRB-

-RRB-

One

specific

problem

with

the

current

treatment

is

that

protein

interaction

networks

do

not

differentiate

between

many

types

of

relationships

e.g.

high-affinity

and

direct

versus

loose

and

transient

Sometimes

DECEMBER

Downloaded

from

on

May

REPORTS

in

fact

interactions

are

reported

that

connect

two

proteins

that

never

touch

each

other

physically

but

are

only

linked

through

a

third

protein

-LRB-

-RRB-

Here

we

address

this

problem

by

combining

structural

modeling

with

network

analysis

In

particular

we

compiled

a

consensus

yeast

interaction

network

from

various

sources

-LRB-

-RRB-

filtering

out

low-confidence

interactions

by

using

statistical

methodologies

-LRB-

-RRB-

We

then

annotated

Department

of

Molecular

Biophysics

and

Biochemistry

Yale

University

New

Haven

CT

USA

of

Computer

Science

Yale

University

New

Haven

CT

USA

in

Computational

Biology

and

Bioinformatics

Yale

University

New

Haven

CT

USA

Program

Boston

University

Boston

MA

USA

of

Chemistry

Boston

University

Boston

MA

USA

To

whom

correspondence

should

be

addressed

E-mail

mark.gerstein@yale.edu

Fig.

The

creation

of

the

structural

interaction

network

-LRB-

SIN

-RRB-

data

set

All

interactions

from

the

filtered

protein

interaction

data

set

are

mapped

to

Pfam

domains

-LRB-

-RRB-

The

Pfam

domains

are

mapped

to

known

structures

of

protein

interactions

by

means

of

iPfam

-LRB-

-RRB-

Only

those

interactions

in

which

both

interaction

partners

-LRB-

or

a

homologous

domain

of

either

-RRB-

can

be

found

in

a

structure

of

a

protein

complex

are

kept

All

interactions

are

then

classified

into

mutually

exclusive

and

simultaneously

possible

by

structural

exclusion

When

a

protein

has

more

than

one

simultaneously

possible

interaction

the

number

of

interaction

interfaces

is

counted

Interactome

Map

all

interactions

to

available

homologous

structures

of

interfaces

PDB

Interaction

with

structurally

resolved

interface

Distinguish

overlaping

from

non-overlapping

interfaces

Table

Differences

of

simultaneously

possible

versus

mutually

exclusive

interactions

with

respect

to

GO

annotations

-LRB-

shared

by

the

interacting

proteins

-RRB-

and

coexpression

correlation

coefficients

GO

biological

process

molecular

function

and

cellular

component

are

taken

from

SGD

lite

-LRB-

-RRB-

and

coexpression

correlation

from

the

compendium

expression

data

set

-LRB-

-RRB-

All

differences

are

significant

with

P

Simultaneously

Mutually

possible

exclusive

interactions

interactions

Fraction

with

same

biological

process

Fraction

with

same

molecular

function

Fraction

with

same

cellular

component

Coexpression

correlation

Simultaneously

possible

interactions

Multi-interface

hub

Simultaneously

possible

interaction

Multi-interface

hub

Mutually

exclusive

interactions

Singlish-interface

hub

Mutually

exclusive

interaction

Singlishinterface

hub

SCIENCE

VOL

DECEMBER

Downloaded

from

on

May

many

of

the

edges

in

this

network

structurally

on

the

basis

of

sequence

similarity

to

known

complexes

-LRB-

Fig.

-RRB-

We

used

simple

three-dimensional

-LRB-

-RRB-

structural

exclusion

to

distinguish

the

interfaces

of

each

interaction

Consider

two

or

more

proteins

interacting

with

a

common

partner

protein

If

they

use

the

same

interface

on

the

partner

-LRB-

as

known

from

the

structures

-RRB-

the

interactions

are

classified

as

mutually

exclusive

Conversely

if

they

use

different

interfaces

the

interactions

are

simultaneously

possible

-LRB-

Fig.

-RRB-

The

network

resulting

from

this

analysis

-LRB-

the

structural

interaction

network

SIN

-RRB-

contains

nodes

-LRB-

proteins

-RRB-

and

edges

-LRB-

interactions

-RRB-

of

which

are

mutually

exclusive

-LRB-

fig

-RRB-

It

contains

parts

of

complexes

suggesting

that

it

covers

a

representative

range

of

interactions

-LSB-

For

the

SIN

data

set

and

further

discussion

see

SOM

Text

tables

and

and

-LRB-

-RRB-

-RSB-

After

building

the

SIN

we

examined

its

two

different

kinds

of

interactions

with

respect

to

the

properties

of

the

linked

proteins

As

shown

in

Table

proteins

connected

by

simultaneously

possible

interactions

are

more

likely

to

share

the

same

function

than

are

those

connected

by

mutually

exclusive

ones

-LSB-

in

terms

of

Gene

Ontology

-LRB-

GO

-RRB-

cellular

component

molecular

function

and

biological

process

designations

-RSB-

also

they

are

more

likely

to

be

expressed

at

the

same

time

Consequently

we

expect

most

of

the

mutually

exclusive

interactions

to

be

temporary

or

transient

because

they

can

not

occur

at

the

same

time

Likewise

the

simultaneously

possible

interactions

are

enriched

in

permanent

associations

connecting

members

of

the

same

complex

-LRB-

table

-RRB-

Turning

to

global

statistics

of

the

SIN

we

find

that

it

has

a

degree

distribution

with

a

notably

shorter

tail

than

either

the

complete

yeast

interactome

or

a

core

filtered

subset

of

this

-LRB-

fig

-RRB-

In

particular

hubs

in

the

SIN

have

a

maximum

of

interaction

partners

This

is

similar

to

the

number

of

close-packed

neighbors

in

crystal

lattices

-LRB-

in

hexagonal

packing

-RRB-

and

reflects

the

direct

physical

constraints

on

interactions

in

the

SIN

In

contrast

in

early

yeast

interactomes

some

hubs

had

interaction

partners

and

even

in

newer

data

sets

partners

are

noted

for

some

proteins

-LRB-

-RRB-

Within

hubs

in

the

SIN

we

compared

those

with

many

physical

interfaces

-LRB-

as

detected

by

our

approach

-RRB-

to

those

with

a

few

to

uncouple

degree

from

interface

number

-LRB-

which

are

correlated

-RRB-

We

defined

hubs

by

setting

an

arbitrary

cutoff

of

interaction

partners

variations

in

this

cutoff

did

not

affect

our

results

-LRB-

table

-RRB-

We

detected

differences

in

the

properties

between

multi

and

single-interface

hubs

However

more

statistically

significant

differences

were

evident

if

we

distinguished

between

hubs

with

one

or

two

interfaces

-LRB-

singlish-interface

-RRB-

and

those

with

more

REPORTS

than

two

interfaces

-LRB-

multi-interface

-RRB-

First

we

examined

the

essentiality

of

both

kinds

of

hubs

Although

hubs

in

general

are

more

likely

than

other

proteins

to

be

essential

for

cellular

viability

-LRB-

-RRB-

as

shown

in

Table

multi-interface

hubs

are

twice

as

likely

to

be

essential

as

singlish-interface

ones

which

in

turn

are

no

more

likely

to

be

essential

than

the

average

protein

in

the

SIN

This

result

suggests

the

notion

of

hubs

having

a

higher

essentiality

due

to

their

network

centrality

is

somewhat

incomplete

It

is

the

number

of

interaction

interfaces

that

leads

to

higher

essentiality

Furthermore

Table

shows

that

multi-interface

hubs

are

more

likely

to

be

coexpressed

with

their

neighbors

than

are

singlish-interface

ones

This

provides

a

straightforward

structural

explanation

for

the

existence

of

two

types

of

expression

dynamics

for

hubs

-LRB-

-RRB-

date

and

party

hubs

-LRB-

-RRB-

In

particular

singlish-interface

hubs

seem

to

correspond

to

date

hubs

-LRB-

which

are

expressed

at

different

times

than

their

interaction

partners

table

-RRB-

and

multi-interface

hubs

correspond

to

party

hubs

-LRB-

which

are

expressed

at

the

same

times

as

their

interaction

partners

-RRB-

It

is

quite

reasonable

that

the

interaction

partners

of

singlish-interface

hubs

are

not

coexpressed

because

they

would

compete

for

the

same

binding

interface

On

the

other

hand

for

the

partners

of

multi-interface

hubs

it

makes

sense

to

be

expressed

simultaneously

because

they

bind

to

different

interfaces

Multi-interface

hubs

in

fact

correspond

to

central

members

of

protein

complexes

as

is

evident

from

cross-referencing

them

with

known

complexes

-LRB-

table

-RRB-

A

representative

multi-interface

hub

for

example

is

a

member

of

the

complex

Conversely

a

good

example

for

a

singlish-interface

hub

is

a

central

protein

kinase

-LRB-

see

SOM

Text

and

table

-RRB-

There

has

been

some

controversy

over

whether

hubs

are

slower-evolving

than

other

proteins

-LRB-

-RRB-

A

commonly

used

measure

of

evolutionary

rate

is

the

dN/dS

ratio

-LRB-

the

ratio

of

nonsynonymous

to

synonymous

substitutions

also

referred

to

as

Ka/Ks

ratio

-RRB-

Table

shows

that

it

is

significantly

lower

for

multi-interface

hubs

than

for

the

average

SIN

protein

but

not

so

for

singlish-interface

hubs

Although

the

dependence

of

evolutionary

rate

on

protein

degree

has

been

attributed

to

an

underlying

effect

of

expression

level

-LRB-

-RRB-

we

find

that

the

relationship

of

evolutionary

rate

to

the

number

of

interfaces

is

independent

of

expression

level

-LRB-

whereas

that

to

the

degree

is

not

-RRB-

-LRB-

fig

-RRB-

The

aforementioned

controversy

may

have

arisen

because

previous

studies

did

not

differentiate

between

singlish

and

multi-interface

hubs

A

larger

number

of

interfaces

may

give

rise

to

a

lower

evolutionary

rate

because

a

larger

fraction

of

residues

participate

in

interactions

Indeed

Fig.

shows

that

the

variation

in

a

protein

's

evolutionary

rate

can

be

accounted

for

better

by

changes

in

the

fraction

of

its

accessible

surface

area

involved

in

interactions

than

by

degree

This

result

can

be

explained

simply

from

a

structural

point

of

view

The

average

mutational

rate

for

exposed

surface

residues

is

more

than

twice

as

high

as

for

those

at

an

interface

which

in

turn

is

slightly

higher

than

the

one

for

buried

residues

-LRB-

table

-RRB-

-LRB-

-RRB-

Thus

as

suggested

previously

-LRB-

-RRB-

and

shown

in

our

analysis

the

proportion

of

a

protein

's

available

surface

area

involved

in

interactions

should

correlate

inversely

with

evolutionary

rate

Finally

we

examined

network

evolution

from

a

structural

perspective

The

existing

scale-free

network

topology

-LRB-

the

dominance

of

hubs

-RRB-

may

have

evolved

through

preferential

attachment

-LRB-

-RRB-

Gene

duplication

is

one

possible

cause

of

such

an

evolutionary

process

-LRB-

-RRB-

but

other

factors

such

as

preferential

rewiring

could

contribute

as

well

-LRB-

-RRB-

As

depicted

in

Fig.

if

a

hub

evolves

by

duplication

its

interaction

partners

are

expected

to

be

enriched

in

paralogs

-LRB-

products

of

homologous

genes

originating

from

withingenome

duplications

-RRB-

As

expected

-LRB-

-RRB-

we

found

that

two

proteins

are

significantly

more

likely

to

be

em

-LCB-

r

-LCB-

-RCB-

-RCB-

rr

r

Adjusted

Interface

Surface

Area

Evolutionary

rate

-LRB-

dN/dS

ratio

-RRB-

Fig.

Dependence

of

the

average

evolutionary

rate

-LRB-

dN/dS

ratio

-RRB-

of

a

protein

with

the

degree

and

the

interacting

accessible

surface

area

-LRB-

adjusted

by

protein

size

as

estimated

from

molecular

weight

-RRB-

For

the

degree

correlation

coefficient

we

get

r

and

for

the

adjusted

interface

surface

area

r

suggesting

that

more

than

twice

as

much

of

the

variation

in

dN/dS

is

accounted

for

by

adjusted

interface

surface

area

-LRB-

-RRB-

than

by

the

degree

-LRB-

-RRB-

Table

Correlation

of

genomic

features

with

singlish

and

multi-interface

hubs

The

fraction

of

proteins

that

are

products

of

essential

genes

-LRB-

-RRB-

the

average

expression

correlation

with

their

neighbors

-LRB-

-RRB-

and

the

evolutionary

rate

-LSB-

dN/dS

ratio

from

-LRB-

-RRB-

-RSB-

was

calculated

for

the

entire

proteome

the

entire

SIN

singlish-interface

protein

hubs

and

multi-interface

protein

hubs

The

Pvalues

of

the

differences

between

the

whole

data

set

and

the

singlish

interface

hubs

-LRB-

all-singlish

-RRB-

and

the

singlish

and

multi-interface

hubs

-LRB-

singlish-multi

-RRB-

were

calculated

with

the

Wilcoxon

ranksum

test

-LRB-

see

Methods

in

the

SOM

-RRB-

Entire

All

in

P-value

Singlish-interface

P-value

Multi-interface

proteome

data

set

-LRB-

all-singlish

-RRB-

hubs

only

-LRB-

singlish-multi

-RRB-

hubs

only

Protein

essentiality

Expression

correlation

Evolutionary

rate

Table

Fraction

of

protein

pairs

that

are

paralogs

of

each

other

Random

pair

randomly

chosen

protein

pair

from

our

data

set

-LRB-

average

-RRB-

Same

partner

fraction

of

pairs

with

the

same

interaction

partner

that

are

paralogs

Same

partner

same

interface

Fraction

of

pairs

that

bind

to

the

same

interface

that

are

paralogs

Same

partner

different

interface

fraction

of

pairs

with

the

same

interaction

partner

but

different

interacting

interface

that

are

paralogs

-LRB-

calculated

from

the

platinum

standard

set

only

see

Methods

in

the

SOM

-RRB-

Random

pair

Fraction

paralogs

Same

partner

Same

partner

same

interface

Same

partner

different

interface

DECEMBER

VOL

SCIENCE

Downloaded

from

on

May

Degree

REPORTS

A

C

A

I.

Lee

S.

V.

Date

A.

T.

Adai

E.

M.

Marcotte

Science

-LRB-

-RRB-

P.

M.

Kim

thesis

-LRB-

MIT

Cambridge

MA

-RRB-

pp.

P.

Aloy

R.

B.

Russell

Nat

Rev.

Mol

Cell

Biol

-LRB-

-RRB-

P.

Aloy

R.

B.

Russell

Nat

Biotechnol

-LRB-

-RRB-

G.

D.

Bader

C.

W.

Hogue

Nat

Biotechnol

-LRB-

-RRB-

See

supporting

information

on

Science

Online

for

details

For

updates

to

the

SIN

and

interactive

viewing

using

tYNA

see

P.

Uetz

et

al.

Nature

-LRB-

-RRB-

H.

B.

Fraser

A.

E.

Hirsh

L.

M.

Steinmetz

C.

Scharfe

M.

W.

Feldman

Science

-LRB-

-RRB-

I.

K.

Jordan

Y.

I.

Wolf

E.

V.

Koonin

BMC

Evol

Biol

-LRB-

-RRB-

S.

Wuchty

Genome

Res

-LRB-

-RRB-

J.

D.

Bloom

C.

Adami

BMC

Evol

Biol

-LRB-

-RRB-

W.

S.

Valdar

J.

M.

Thornton

Proteins

-LRB-

-RRB-

H.

B.

Fraser

A.

E.

Hirsh

BMC

Evol

Biol

-LRB-

-RRB-

R.

Albert

A.

L.

Barabasi

Rev.

Mod

Phys

-LRB-

-RRB-

A.

Vazquez

Phys

Rev.

E

-LRB-

-RRB-

A.

Wagner

Proc

Biol

Sci

-LRB-

-RRB-

E.

Eisenberg

E.

Y.

Levanon

Phys

Rev.

Lett

-LRB-

-RRB-

J.

Espadaler

et

al.

Proc

Natl.

Acad

Sci

U.S.A.

-LRB-

-RRB-

L.

Issel-Tarver

et

al.

Methods

Enzymol

-LRB-

-RRB-

T.

R.

Hughes

et

al.

Cell

-LRB-

-RRB-

G.

Giaever

et

al.

Nature

-LRB-

-RRB-

D.

P.

Wall

et

al.

Proc

Natl.

Acad

Sci

U.S.A.

-LRB-

-RRB-

A.

Bateman

et

al.

Nucleic

Acids

Res

-LRB-

-RRB-

R.

D.

Finn

M.

Marshall

A.

Bateman

Bioinformatics

-LRB-

-RRB-

We

thank

J.

Korbel

T.

Gianoulis

A.

Paccanaro

and

H.

Yu

for

helpful

comments

on

the

manuscript

We

also

thank

the

anonymous

referees

for

valuable

suggestions

This

work

was

supported

by

the

NIH

Y.X.

was

supported

by

a

fellowship

from

the

Jane

Coffin

Childs

Memorial

Fund

for

Medical

Research

A

Duplicate

Gene

-LRB-

preferential

attachment

-RRB-

A

A

is

an

equal

interaction

partner

of

A.

and

A

actually

evolve

a

new

binding

interface

Fig.

The

concept

of

network

evolution

by

gene

duplication

A

given

protein

may

acquire

a

new

interaction

by

duplication

of

an

existing

one

Given

equal

likelihood

of

any

gene

to

be

duplicated

a

protein

with

many

partners

is

more

likely

to

get

a

new

partner

than

one

with

few

hence

there

is

effective

preferential

attachment

For

singlish-interface

hubs

this

mechanism

is

straightforward

However

for

multi-interface

hubs

it

would

then

require

coevolution

of

the

hub

and

the

duplicated

gene

to

form

a

new

interface

paralogs

if

they

share

a

common

partner

-LRB-

Table

-RRB-

However

this

is

true

only

if

they

also

share

an

interaction

interface

We

did

not

find

enrichment

for

paralogs

among

interaction

partners

binding

to

different

interfaces

-LRB-

Table

-RRB-

That

is

our

analysis

is

consistent

with

the

evolution

of

singlish-interface

hubs

through

duplication-mutation

whereas

it

does

not

support

such

an

evolution

of

multiinterface

hubs

-LRB-

Fig.

-RRB-

Because

multi-interface

hubs

are

often

parts

of

larger

protein

complexes

it

appears

that

protein-complex

evolution

could

follow

a

different

mechanism

From

our

structural

analysis

of

protein

interaction

networks

we

find

that

we

can

distinguish

two

fundamentally

different

types

of

network

edges

On

the

one

hand

we

find

a

group

of

interactions

that

are

simultaneously

possible

and

a

set

of

multi-interface

hubs

associated

with

these

Multi-interface

hubs

correspond

in

many

respects

to

our

classic

notion

of

network

hubs

They

are

more

likely

to

be

essential

and

more

conserved

They

are

most

likely

members

of

large

and

stable

complexes

However

they

do

not

follow

canonical

models

of

network

evolution

growing

through

gene

duplication

On

the

other

hand

we

find

a

second

class

of

interactions

mutually

exclusive

ones

which

have

a

transient

character

and

occur

in

singlish-interface

hubs

Singlish-interface

hubs

are

distinctly

nonclassical

They

are

neither

likely

to

be

essential

nor

conserved

However

in

respect

to

network

growth

they

do

follow

the

canonical

preferential

gene

duplication

model

References

and

Notes

A.

L.

Barabasi

Z.

N.

Oltvai

Nat

Rev.

Genet

-LRB-

-RRB-

A.

C.

Gavin

et

al.

Nature

-LRB-

-RRB-

H.

Jeong

S.

P.

Mason

A.

L.

Barabasi

Z.

N.

Oltvai

Nature

-LRB-

-RRB-

R.

Jansen

et

al.

Science

-LRB-

-RRB-

U.

de

Lichtenberg

L.

J.

Jensen

S.

Brunak

P.

Bork

Science

-LRB-

-RRB-

R.

Kelley

T.

Ideker

Nat

Biotechnol

-LRB-

-RRB-

J.

D.

Han

et

al.

Nature

-LRB-

-RRB-

Supporting

Online

Material

Materials

and

Methods

SOM

Text

Figs

to

Tables

to

References

October

accepted

November

science

Characterizing

a

Mammalian

Circannual

Pacemaker

Gerald

A.

Lincoln

Iain

J.

Clarke

Roelof

A.

Hut

David

G.

Many

species

express

endogenous

cycles

in

physiology

and

behavior

that

allow

anticipation

of

the

seasons

The

anatomical

and

cellular

bases

of

these

circannual

rhythms

have

not

been

defined

Here

we

provide

strong

evidence

using

an

in

vivo

Soay

sheep

model

that

the

circannual

regulation

of

prolactin

secretion

and

its

associated

biology

derive

from

a

pituitary-based

timing

mechanism

Circannual

rhythm

generation

is

seen

as

the

product

of

the

interaction

between

melatoninregulated

timer

cells

and

adjacent

prolactin-secreting

cells

which

together

function

as

an

intrapituitary

pacemaker-slave

timer

system

These

new

insights

open

the

way

for

a

molecular

analysis

of

long-term

timing

mechanisms

E

ndogenous

circannual

rhythms

drive

many

long-term

cycles

in

physiology

and

behavior

in

long-lived

vertebrates

-LRB-

-RRB-

including

reproduction

-LRB-

-RRB-

hibernation

-LRB-

-RRB-

migration

-LRB-

-RRB-

and

pelage

growth

-LRB-

-RRB-

but

the

anatomical

and

cellular

bases

of

such

rhythm

SCIENCE

VOL

generation

remain

a

mystery

We

investigated

whether

a

circannual

rhythm

may

be

generated

through

a

pituitary

mechanism

itself

dependent

on

the

circadian

system

We

focused

on

the

anterior

pituitary

control

of

prolactin

secretion

but

similar

cell-cell

interactions

in

the

brain

may

DECEMBER

Downloaded

from

on

May

C

A

CORRECTIONS

CLARIFICATIONS

ERRATUM

Post

date

January

SCIENCE

ERRATUM

POST

DATE

JANUARY

Downloaded

from

on

May

Reports

Relating

three-dimensional

structures

to

protein

networks

provides

evolutionary

insights

by

P.

M.

Kim

et

al.

-LRB-

Dec.

p.

-RRB-

In

note

the

funding

acknowledgment

should

read

This

work

was

supported

by

NIH

grants

and

Additionally

on

page

a

maximum

degree

of

was

reported

for

the

SIN

this

number

refers

to

an

earlier

version

of

the

SIN

-LRB-

-RRB-

The

SIN

as

reported

in

the

paper

has

one

node

with

a

degree

of

higher

than

All

versions

of

the

SIN

and

current

statistics

on

them

are

available

at

O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O B O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B B O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O

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