LPJ-GUESS

• Vegetation state representation

• Plant functional types

• Processes

• Application examples

• Future prospects in large-scale ecosystem

modelling

a large-scale ecosystem model

NGEN02 Ecosystem Modelling 2014

LPJ-GUESS population mode – typical representation of vegetation

in a DGVM of intermediate complexity*

Modelled area (grid cell) c. 100-2500 km2

Average individual

for PFT population

PFT 1 PFT 2 PFT 3 uncolonised

fractional cover (FPC) PFT

Average individual for PFT population

tree grass

crown area

height

fine roots

leaves

LAI

sapwood

heartwood

0-50 cm

50-100 cm

leaves / LAI

fine

roots

stem

diameter

*Sitch et al. 2003 Global Change Biology 9: 161-185

Average individual for PFT or species cohort

in patch

Modelled area (stand) c. 10 ha - 2500 km2

replicate patches in various

stages of development

Patch

0.1 ha

tree grass

crown area

height

fine roots

leaves

LAI

sapwood

heartwood

0 - 50 cm 50 - 100 cm

leaves / LAI

fine

roots

stem

diameter

crown area

height

fine roots

leaves

LAI

sapwood

heartwood

sapwood

heartwood

0 - 50 cm 50 - 100 cm

leaves / LAI

fine

roots

stem

diameter

Cohort mode – detailed representation distinguished

individual trees and patches with different disturbance histories*

*Smith et al. 2001 Global Ecology and Biogeography 10: 621

Parameter

max establishment

rate (ha1 yr1)

max longevity (yr)

survival in shade

optimal temp for

photosynthesis (°C)

bioclimatic

distribution

allocation to stem

growth

leaf:sapwood area

ratio (m2 cm2)

leaf phenology

crown spreading

boreal

10-25

evergreen

0.3

150

0.05

high

900

1250

temperate

15-25

summergreen

0.4

250

0.05

high

900

1250

boreal-temperate

10-25

summergreen

0.4

250

0.1

low

300

2500

no limits

10-30

summergreen-

raingreen

-

-

-

low

-

-

Trait differences influence functioning and interactions

among plant functional types / species

• Colonisation of unvegetated areas (primary succession)

• Inter- and intraspecific competition for light, space and soil resources

• Landscape as aggregate of stands / patches with differential history of disturbance, colonisation and succession

• Disturbances leading to complete or partial destruction of individual stands

• differential establishment, growth and mortality of species with alternative trade-offs between productivity and survivorship under stress

Elements of structural and compositional dynamics of vegetation

simulated by LPJ-GUESS b

iom

ass (

kg

C m

2)

year

Hickler et al. 2004.

Ecology 85: 519-530

Coupled plant carbon and water balance

)(),,APAR(

),,(min max

maxVfR

TcfJ

TcVfJA leaf

iE

iC

n

leafNkV max

),( cai gcfc

soil water supply

PAR

APAR =

PAR · [1 exp( k · LAI )]

AET

Ci

AET

Ci

stomatal conductance, gc

gc

AET Monteith 1995 D

S

CO2

• physiological representation at leaf-level (modified Farquhar-model)

• light extinction in vegetation canopy (Beer’s law)

• humid boundary-layer increases stomatal conductance (Monteith 1995)

(Beer’s law)

Autotrophic (plant) respiration

RA = Rm + Rg

Temperature response of maintenance respiration Rm

Living tissue maintenance respiration

Growth respiration Rg = 1/3 of NPP

NPP = GPP Rm Rg

46

1

56

1309exp)(

TTg

)(N:C

TgC

rRm

Rg = 0.25 (GPP Rm)

Net primary production

T

Rm

T

Rm

Tree allometry and carbon allocation

Leaf-sapwood area ratio (Shinozaki et al. 1964)

Leaf-root mass ratio (functional balance)

Height-stem diameter relationship (forestry literature)

Diameter-population density relationship

(Reineke 1933)

rootlrleaf CkC

3/2

2 DkH

SAkLA lasa

D

H

D

CA

average individual

structure accrued C

(annual NPP)

allometric constraints

’old’

structure

new

structure

3 / 5 1

−5/3

1

D k CA

N CA

D N

×

age

proportion of

cohort surviving

to age

max sapling

establishment

rate

juvenile

phase

adult

phase

recruitment-

juvenile growth

rate relationship

maximum

non-stressed

longevity

Cohort mode population dynamics

resource-stress

mortality

constant parameter

dynamic process

Wildfire disturbance and biomass burning

0.0 0.1 0.2 0.3 0.4 0.5 0.6

Litter moisture (%AWC)

0

0.2

0.4

0.6

0.8

1.0

Daily

fire p

robabili

ty

0 100 200 300

Fire season (days)

0

0.1

0.6

0.5

0.4

0.3

0.2

Fra

ction

al a

rea

bu

rnt

* Thonicke et al 2001

Global Ecol. & Biogeog. 10: 661-677

Daily probability of fire

• function of litter load, moisture, flammability

Annual fire season length

• sum of daily fire probabilities

Fractional area burnt (ffire)

• function of fire season length

Sample applications of LPJ-GUESS

• Simulate transient vegetation response to climate and [CO2] change

Potential natural vegetation change in Sweden

• Generate hypotheses for experiments and monitoring

vegetation NPP response to multiple drivers

• Quantify and attribute uncertainty

GCM-derived uncertainty in future terrestrial ecosystem C balance

• Predict complex system dynamics

→ C-N interactions under future climate and CO2

• Account for biosphere-atmosphere feedback

evapotranspiration and albedo feedback in RCM-simulated future

climate

Potential 21st century vegetation change in Sweden*

Re

lative

co

ve

r (le

af a

rea

in

de

x)

Norway spruce

Scots pine

other conifer

beech

elm

ash

oak

alder

birch

other broadleaved

herbaceous

* Smith et al. 2007

SOU 2007:60

LPJ-GUESS

RCA3

A2

emissions

ECHAM4

Sarek

anim

T+P+R+C

T+P+C

T

P

T = change i temperature

P = change in precipitation

R = change in incoming

SW radiation

C = change in CO2

Scenario

R

C

Year in climate model scenario RCA3-ECHAM4/OPYC3-A2

Net

pri

mary

pro

du

cti

on

(kg

C m

2 y

r1)

N Sweden

S Sweden

Vegetation NPP response to multiple environmental drivers*

*Smith et al. 2007

SOU 2007:60

GCP residual land flux 0.8 PgC

LPJ-GUESS

other DGVMs

Interannual variation in net ecosystem C balance

Sitch et al. 2015

Biogeosciences 12: 653-679

uptake

release

drought-induced anomaly 2005

Re

sid

ua

l la

nd

C s

ink (

Pg

C y

r1)

Global terrestrial ecosystem C balance

under a ”business-as-usual” future climate scenario

from different climate models (GCMs)

Terr

estr

ial ecosyste

m C

pool (G

tC)

sink

source

neutral

Ahlström et al. 2012

Environmental Research Letters 7

LPJ-GUESS

RCP8.5

radiative

forcing

AR5 GCM

increased sink / reduced source

reduced sink / increased source

Robust patterns for some global regions

kgC m2 yr1

0.150

0.150

0

∆ Net ecosystem C balance

(2071-2100)(1961-1990)

latitude

earlier leaf-out → photosynthesis

milder autumn → respiration

increased productivity in parts of tropics

Some robust seasonal and regional trends

month

increased sink / reduced source

reduced sink / increased source

J F M A M J J A S O N D

increased sink / reduced source

reduced sink / increased source

Ahlström et al. 2012

Environmental Research Letters 7

total

uncertainty total

uncertainty

Terr

estr

ial ecosyste

m C

pool (G

tC)

sink

source

neutral uncertainty

due to

factor A

(e.g. NPP)

uncertainty

due to

factor B

(e.g. biomass

turnover)

remaining

uncertainty

LPJ-GUESS

RCP8.5

radiative

forcing

AR5 GCM

Contributions of individual model factors

to simulation spread

Factor Contribution to

uncertainty (%)

NPP 57

biomass turnover biome shifts 6

stand dynamics 2

wildfires 11

non-fire disturbance 3

environmental sensitivity of

soil respiration

21

Total 100

Anders Ahlström

unpublished data

Contributions of individual model factors

to simulation spread

Hungate et al. 2003

Science 302: 1512

Will the biosphere store more or less carbon under

future climate and CO2?

Smith et al. 2014

Biogeosciences 11: 2027-2054

LPJ-GUESS

model

nitrogen feedback reduces CO2 effect on C storage ...

... but climate change compensates via increased N mineralisation in warming soils

*Wårlind et al. 2014

Biogeosciences 11: 6131-6146

kgC m2 yr1

Additional C storage 1990-2100

due to C-N interactions

Increased stature, density and distribution of boreal forest

explains increased C sequestration*

latent heat

(evapo-

transpiration) sensible

heat

incoming

shortwave radiation

incoming

shortwave radiation

Vegetation cover and leafiness affect

partitioning of return heat flux from surface

– more latent heat reduces near-surface warming

sensible

heat latent heat

(evapotranspiration)

15

10

5

2.5

–2.5

–5

–10

–15

15

10

5

2.5

–2.5

–5

–10

–15

Feedback contribution

LEdynLEstat

Temperature change JJA °C

(2071-2100)(1961-1990) Tdyn

Latent heat flux change LEdyn

Feedback contribution TdynTstat

2000 2100 2020 2040 2060 2080

0

5

4

3

2

1

2000 2100 2020 2040 2060 2080

0

8

6

4

2

Leaf area index

LPJ-GUESS

RCA3

A1B

emissions

ECHAM5

Changed latent heat flux enhances summer warming in

southern Europe, dampens warming i central Europe*

*Wramneby et al. 2010. J. Geophys. Res. 115

Vegetation change in the Arctic*

*Zhang et al. 2014

Biogeosciences 11: 5503-5519.

Feedbacks to climate*

LPJ-GUESS

RCA4

RCP

forcing

EC-EARTH

Additional temperature change due to vegetation feedback

(2071-2100)(1961-1990)

*Zhang et al. 2014

Biogeosciences 11: 5503-5519.

Feedbacks to climate*

• Seasonality shift – longer growing season, earlier temperature peak

• Evaporative cooling evens out growing season temperature profile

• Ecological implications?

Additional temperature change due to biogeophysical feedback

-0.4

-0.2

0

0.2

0.4

0.6

0.8

1

2000 2020 2040 2060 2080 2100

RCP26RCP45RCP85

(a)

Te

mp

era

ture

( C

)

-3

-2

-1

0

1

2

3

J F M A M J J A S O N D

(b)

Te

mp

era

ture

( C

)

∆T (

°C)

albedo feedback

evapotranspiration feedback

(2071-2100)(1961-1990)

*Zhang et al. 2014

Biogeosciences 11: 5503-5519.

State-of-the-art and prospects in vegetation and ecosystem modelling

• Nutrient cycles, ozone toxicity, long-term response to elevated CO2

• Non-CO2 trace gases – methane, N2O, biogenic volatile organic

compounds

• Crops, forest management, land use change

• Migration

• Habitat change and biodiversity

• Coupled component in global and regional Earth system models

(ESMs)