Land use intensification increases soil greenhouse gas

emissions in peri-urban environments

by

Lona van DeldenEloise Larsen

David Rowlings

Clemens Scheer

Peter Grace

Queensland University of TechnologyInstitute for Future Environments

2

Background

• Urban populations exceed rural populations

• 90 % of Australians will live in urban areas by 2050

• Land use change leads to- loss in soil quality- loss in soil quantity- reduce C sequestration- increase greenhouse gas (GHG) emissions

• Local climates affecting the global climate

• Global Warming Potential (GWP)

Queensland University of TechnologyInstitute for Future Environments

3

GWP is calculated from CO2 equivalents (CO2-e) according to IPCC (2007)

• CO2 = = * 1

• CH4 = = * 25

• N2O = = *298

Global Warming Potential

Queensland University of TechnologyInstitute for Future Environments

4

Area of interest

Queensland University of TechnologyInstitute for Future Environments

SERF

Samford Valley: 82 km2, 20 km from Brisbane City

Population density: 0.69 P ha-1

Samford Ecological Research Facility (SERF)

5

Experimental Design

SERF

• 51 ha

• Humid subtropics

• Avg min 13°C & Avg max 26°C

• Avg 1110 mm rain

• Chromosol

Queensland University of TechnologyInstitute for Future Environments

6

Materials & Method

• 4 land use types – native forest, pasture, turf grass, fallow

• Static chamber technique

• Fluxes from 4 concentrations over 1 hour of closure time

• Annual measurements twice a month (Mar 2009 – Feb 2010)

• High frequency measurements – 8 fluxes per day for 80 days (Jun – Aug 2013)

• GWP [CO2-e] = 1 * CO2 + 25 * CH4 + 298 * N2O

Queensland University of TechnologyInstitute for Future Environments

7

Results

CH4

• Forest-10.1 g ha-1 d-1

• Pasture-1.4 g ha-1 d-1

+13 g ha-1 d-1

• Turf grass-4.7 g ha-1 d-1

• Fallow-3.1 g ha-1 d-1

Queensland University of TechnologyInstitute for Future Environments

2013

17/06/13 1/07/13 15/07/13 29/07/13 12/08/13 26/08/13

So

il mo

istu

re [%

]

-20

-10

0

10

20

30

40

50

CH

4 [g h

a-1

d-1

]

-15

-10

-5

0

5

10

15

20Soil moistureForestPastureTurf grassFallow

2009/2010

Mar Apr May Jun Jul Aug Sep Oct Nov Dec Jan Feb Mar

So

il mo

istu

re [%

]

-40

-30

-20

-10

0

10

20

30

40

CH

4 [g h

a-1

d-1

]

-15

-10

-5

0

5

10

15

20Soil moistureForestPasture

8

Results

N2O

• Forest0.03 g ha-1 d-1

• Pasture0.6 g ha-1 d-1

• Turf grass18.7 g ha-1 d-1

• Fallow1.57 g ha-1 d-1

Queensland University of TechnologyInstitute for Future Environments

2013

17/06/13 1/07/13 15/07/13 29/07/13 12/08/13 26/08/13

So

il mo

isture [%

]

0

10

20

30

40

50

N2O [g

ha

-1 d

-1]

0

10

20

30

40

50

60Soil moistureForestPastureTurf grassFallow

2009/2010

Mar Apr May Jun Jul Aug Sep Oct Nov Dec Jan Feb Mar

So

il mo

isture [%

]

0

10

20

30

40

N2O

[g h

a-1

d-1

]

0

10

20

30

40

50

60Soil moistureForestPasture

9

Results

Forest Pasture Turf grass

Fallow-1000

-5000

50010001500

N₂OCH₄

[g h

a-1

d-1]

Queensland University of TechnologyInstitute for Future Environments

Forest Pasture Turf grass

Fallow-100

0

100

200

300

400

500

GWP

[kg

CO

2-e

ha-1

80

d-1]

GWP

Pasture → Turf grass426 kg CO2-e ha-1 80-1

Forest → Turf grass454 kg CO2-e ha-1 80-1

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Conclusion

• ½ of world population occupies 2.4 % of land with cities

• E.g. turf grass in USA covers 160,000 km2

• Include peri-urban environments into climate forecasts

• High quality data & clear definitions needed

• Long term effects of turf grass on ecosystems

Queensland University of TechnologyInstitute for Future Environments

11

Acknowledgements

Eloise Larsen

David Rowlings

Clemens Scheer

Peter Grace

Institute for Future Environments, QUT

Samford Ecological Research Facility (SERF)

Terrestrial Ecosystem Research Network (TERN)

Queensland University of TechnologyInstitute for Future Environments