Controls over ecosystem functioning across spatial scales as derived from studies in drylands José...

Controls over ecosystem functioning across spatial scales as derived from

studies in drylands

José M. Grünzweig Hebrew University of Jerusalem, Rehovot, Israel

in colloboration withMarcelo Sternberg, Tel Aviv University, Israel

Katja Tielbörger, University of Tübingen, Germany

ClimMani & INTERFACE Workshop, Scaling climate change experiments across space and time: Challenges of informing large-scale models with small-scale experiments, Mikulov, Czech Republic, June 2013

Climate anomalies, Europe, summer 2003

Ciais et al. 2005 Nature

Climate extremes in systems not adapted to those extremes

Global extent of drylands

Levant (SE Mediterranean)

Research in regions adapted to heat and/or drought

Climate

The physical properties of the Levant (SE Mediterranean)

Shrubland as spatially heterogeneous, mosaic-type ecosystem composed of different microsites

The physical properties of the Levant (SE Mediterranean)

Biomes/ecosystem types

Outline of questions

• Can we predict ecosystem functioning across a precipitation range with common biological and abiotic drivers?

• What processes control carbon pools and fluxes when it gets drier?

• Do climate-change experiments reveal tipping points in ecosystem structure and functioning?

• What can we learn from climate-extremes studies in drylands?

• Where are we going from here?

Rainfall manipulations along an aridity gradient

Aridity gradient – GLOWA Jordan River project

– South facing slopesshallow soil (Terra Rossa to lithosol) onsimilar bedrock

– Similar seasonal temperture range

– Eight-fold difference in mean annual rainfall

– Large difference in rainfall variability

Mediterranean: 540 mm, CV 30%

Semiarid: 300 mm, CV 37%

~ 2

45 k

m

Arid: 90 mm, CV 51%

Mesic Mediterranean: 780 mm, CV 22%

Biomes/ecosystem types

300 mm

Semiarid550 mm

Mediterranean

-30% +30%

Experimental rainfall manipulations

Control

Rainfall manipulations

Rainfall manipulations along an aridity gradient

Observed Rs (μmol m-2 s-1)

Pred

icte

d R s (

μmol

m-2

s-1

)

r2 = 0.48

Talmon et al. 2011 GCB

Soil respiration at the herbaceous microsite during the growing season?

Prediction:Rs = soil respiration; Ts = soil temperature; θ = soil moisture

Site- and treatment- specific equations better fits

Overall inter-site and inter-treatment controls?

Can we predict ecosystem functioning across a precipitation range with common biological and abiotic drivers?

two sites, three climate-change treatments


Pred

icte

d R s (

μmol

m-2

s-1

)

r2 = 0.48

Ts , θ


r2 = 0.73

Ts , θ , cover

Pred

icte

d R s (

μmol

m-2

s-1

)

Vegetation cover is a factor that explains part of the inter-site and inter-treatment variation in soil respiration climate change modeling

Addition of vegetation cover as a driver of soil respiration

Prediction of ecosystem functioning with common biological and abiotic drivers?


0 100 200 300 400 500 600 700 8000.0

0.5

1.0

1.5

2.0

2.5

3.0

Mean annual precipitation (mm)

Soi

l org

anic

C s

tock

(kg

m-2)

What processes control carbon pools and fluxes when it gets drier?

Soil organic carbon stocks at the herbaceous microsite along the aridity gradient

0 100 200 300 400 500 600 700 8000

10

20

30

40

y=2.75x0.402

R2=0.968

An

nu

al li

tter

dec

om

po

siti

on

(%

)


2002-2005

0 100 200 300 400 500 600 700 8000

50

100

150

200

250

300

350

2003-2011

Ab

ove

gro

un

d N

PP

(g

m-2 y

r-1)


y=0.0153x1.492

R2=0.998

0 100 200 300 400 500 600 700 8000.0

0.5

1.0

1.5

2.0

2.5

3.0


Soi

l org

anic

C s

tock

(kg

m-2)


Carbon loss

Carbon addition

Changes in plant strategies with increasing aridity


Unweighted community mean

2.0

3.0

4.0

Log (

specific

leaf

are

a)

aab

b b

p<0.001 10

30

50

Leaf

Nitro

gen (

mg

g1) a

ab

cbc

p<0.001

4.5

5.5

6.5

Log (

leaf

dry

matt

er

conte

nt)

ns

-1.0

0.0

1.0

Log (

tensile

str

ength

)ns

B L M Y

12

34

Log (

pla

nt

heig

ht)

a

ab

b

b

p<0.05

B L M Y

-3-1

13

Log (

leaf

siz

e) ns

Unweighted community average of species leaf traits

Site

300 78055090300 78055090

Mean annual precipitation (mm)Sternberg & Lebrija


Alternative drivers of litter decay in the dry season


0 30 40 50 60 70 80 90 1000

10

20

30

40 Shrub Intershrub Lab

Mois

ture

conte

nt (%

)

Relative humidity (%)

y = 3.10 + 0.414 e0.0451x

r2 = 0.998

Dirks et al. 2010 GCB

Dew Water vapor < saturation

Solar radiation

To what extent is soil respiration along the aridity gradient directly controlled by changes in climatic variables and indirectly controlled by shifts in shrub cover?

0 300 600 9000

300

600

900

ecosystem

shrub microsite

An

nu

al s

oil

resp

irat

ion

(g

C m

-2 y

r-1)


herbaceous microsite


0 200 400 600 8000

200

400

600

800

1000

Ann

ual s

oil r

espi

ratio

n (g

C m

-2 y

r-1)


0 200 400 600 8000

200

400

600

800

1000

-12%-15%

-20% -21%

-60%

Ann

ual s

oil r

espi

ratio

n (g

C m

-2 y

r-1)


assuming no change in shrub cover assuming change in shrub cover

-64%

13% 35% 55% 75%Shrub cover

-15%-12%

-21%-20%

-60%-64%


Kigel & Konsens

0 100 200 300 400 500 600 700 8000

50

100

150

200

250

300

350

2003-2011

Ab

ove

gro

un

d N

PP

(g

m-2 y

r-1)


y=0.0153x1.492

R2=0.998

0 100 200 300 400 500 600 700 8000

50

100

150

200

250

300

350

Control Dry tmt. Wet tmt.

2003-2011

Ab

ove

gro

un

d N

PP

(g

m-2 y

r-1)


y=0.0153x1.492

R2=0.998

Do climate-change experiments reveal tipping points in ecosystem structure and functioning?


Sternberg & Navon

0 100 200 300 400 500 600 700 8000

10

20

30

40

y=2.75x0.402

R2=0.968

An

nu

al li

tter

dec

om

po

siti

on

(%

)


2002-2005

0 100 200 300 400 500 600 700 8000

10

20

30

40

50

y=2.75x0.402

R2=0.968

An

nu

al li

tter

dec

om

po

siti

on

(%

)


2002-2005

Control Dry tmt. Wet tmt.

Rainfall manipulations had no significant effect on species diversity at the semiarid site (same for the Mediterranean site)

Kigel et al., unpublished

2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 20110.8

1

1.2

1.4

1.6

1.8

2

Species diversity

Dry Control Irrig

Sh

ann

on

in

dex

2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 20112

3

4

5

Species diversity

Dry Control Irrig

Sim

pso

n r

ecip

roca

l in

dex

Year

Year*** Treatment NS

T x Y*

Year*** Treatment NS

T x Y*


Spe

cies

ric

hnes

s

Spe

cies

eve

nnes

s (J

’)

Mediter.

arid

mesic Mediter.

semiarid

2001 2002 2003 2004 2005 2006 2007 2008 20090

10

20

30

40

50Station *** Year *** S x Y ***

2001 2002 2003 2004 2005 2006 2007 2008 20090

0.5

1

1.5

2

2.5

3

3.5

4Station *** Year *** S x Y **

2001 2002 2003 2004 2005 2006 2007 2008 20090

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

Station *** Year *** SxY **

Spe

cies

div

ersi

ty (

H’)


Species diversity along the aridity gradient

What can we learn from climate-extremes studies in drylands?

Rs = soil respiration; Ts = soil temperature; θ = soil moisture; PPFD = photon flux density

Moist season:Dry season:

R s

Grünzweig et al. 2009 JGR

R s

Testing extreme conditions: irrigation during the hot summer

Rs = soil respiration; Ts = soil temperature; θ = soil water content; PPFD = photon flux density

PredictionsIrrigation:Control:

Grünzweig et al. 2009 JGR

Final ConferenceLimassol, Cyprus, 2011 Katja Geissler, Martin Köchy, Florian Jeltsch, Dan Malkinson

Scaling of output: the model Wadiscape

topographic and

Spatial information

GIS

slopes (DEM)

MAP

(characterization of region by mean

annual precipitation )

1.0 km

geographic variation

•Experiments (GLOWA)•Surveys (GLOWA)•Literature•Experts (GLOWA)

global circulation

models

pattern (GLOWA)

Modeling (semi-) natural vegetation

Final ConferenceLimassol, Cyprus, 2011 Katja Geissler, Martin Köchy, Florian Jeltsch

Modeling (semi-) natural vegetation

(Over)grazed vegetation is highly vulnerable to climate change

climate changeclimate change, moderate grazing

climate change, current grazing

Summary

Vegetation cover is a driver of soil respiration together with climatic drivers.

The relative distribution of vegetation types has a small impact on ecosystem-scale soil respiration under a drier climate; the decrease in soil respiration is mainly driven by the decline in biological activity.

The decrease in soil organic carbon storage with increased aridity is related to greatly reduced productivity and less drastically reduced decomposition; alternative drivers start to become important under drier conditions.

Climate change studies might reveal tipping points in species richness.

Where are we going from here?

• Climate-change studies in systems adapted to drought provide better understanding of ecosystem functioning under more realistic conditions• Climate-extremes studies, even unrealistic ones, can teach us about processes and potentially about thresholds and tipping points

Funding sourcesInternational Arid Lands Consortium(IALC) Climate Change and Impact Research: the Mediterranean Environment (CIRCE) (EU FP6)German Federal Ministry of Education and Research (BMBF)Israeli Ministry of Science and Technology (MOST)

CollaboratorsHebrew University Tel Aviv University Haifa UniversityJaime Kigel Yael Navon Dan MalkinsonYiftach Talmon Edwin LebrijaIrit KonsensRita Dumbur

Acknowledgements

Thank you for your attention!

Controls over ecosystem functioning across spatial scales as derived from studies in drylands José...

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