Improving GPP, NPP, and NEE predictions from space

Post on 29-Jan-2016

40 views 0 download

Tags:

description

I R S S. Improving GPP, NPP, and NEE predictions from space. Richard Waring 1 Nicholas Coops 2 Joe Landsberg 3 1 Oregon State University 2 University of British Columbia 3 Mt Wilson, NSW 2786, Australia. Eucalyptus plantation GPP =6,000 g C m -2 yr -1. Brazilian rainforest - PowerPoint PPT Presentation

Transcript of Improving GPP, NPP, and NEE predictions from space

Improving GPP, NPP, and NEE predictions from space

Improving GPP, NPP, and NEE predictions from space

I R S S

Richard Waring1

Nicholas Coops2

Joe Landsberg3

1 Oregon State University 2 University of British Columbia3 Mt Wilson, NSW 2786, Australia

Richard Waring1

Nicholas Coops2

Joe Landsberg3

1 Oregon State University 2 University of British Columbia3 Mt Wilson, NSW 2786, Australia

Photo: Courtesy of Auro Almeida

Eucalyptus plantationGPP =6,000 g C m-2 yr-1

Brazilian rainforestGPP =3,000 g C m-2 yr-1

0.0

1.0

2.0

3.0

4.0

5.0

6.0

7.0

8.0

09/97

03/98

09/98

03/99

09/99

03/00

09/00

03/01

09/01

03/02

09/02

03/03

09/03

03/04

Date

LA

I

Eucalyptus Native forest

Brazilian plantation LAI decreases with age as trees approach 40 m in heightat 7 years when harvested. Drought reduces LAI more when stand is young than older

Drought

Auro Almeida, CSIRO Tasmania, unpublished

Drought

0

50

100

150

200

250

300

08/19

99

04/20

00

12/20

00

08/20

01

04/20

02

12/20

02

08/20

03

04/20

04

Date

Av

aila

ble

so

il w

ate

r (m

m)

Eucalyptus Native forest

In the Atlantic Coastal Region of Brazil,native rainforests and eucalyptus plantations usesimilar amounts of water although LAI differs by > 2 fold.Reason: eucalypts are fertilized & have twice the photosynthetic capacity and twice the max. canopy conductance of the rainforest.

Auro Almeida, CSIRO Tasmania, unpublished

Objective: to provide ecological insights to improve predictions of GPP, NPP, and NEE from space

I. GPP: set limits and identify constraints

II. NPP: allocation above and below ground

III. NEE: correlation with GPP

Ecosystem Model Structure

Waring, Coops, & Landsberg 2009 For. Ecol & Mgmt (in press)

Leaf chlorophyll conc. linearly related to maximum photosynthetic

capacity (link to soil fertility)

Waring et al. 1995. Plant Cell & Env. 18: 1201-1218. Zhang et al. 2009. Remote Sen. Env. 113: 880-888.

Leaf conductance (g) and photosynthetic capacity (A) decrease with (relative) tree height & hydraulic conductivity

(KL)

Ambrose et al. 2009. Plant, Cell & Env. 32: 743-757.Hubbard et al. 2001. Plant, Cell & Env. 24: 113-121.

Stomatal response to vpd varies by an order of

magnitude among species in boreal forests

Dang et al. 1997. Tree Physiology 17: 521-535.

VPD response is a function of maximum canopy conductance

Stomatal sensitivity to vpd is a negative log function (slope =0.6) to maximum conductance at 1 kPa (r2 = 0.75).

Oren et al. 1999. Plant, Cell & Env.22:1515-1535.

As the soil water deficit increases beyond a threshold, water loss through transpiration is progressively reduced below its potential as stomata close

Source: Landsberg & Gower 1997. Fig. 4.5. “Application of Physiological Ecology to Forest Management.” Academic Press, San Diego, CA

Eucalyptus maculata

Root depth determines access to water

28 m

Photo: courtesy of Keith Smettem,University of Western Australia

Eucalyptus

marginata

depth that roots penetrate

Photo: courtesy of E.D. Schulze

To evaluate soil water limitations, need to assess changes in canopy properties

(LAI, fPAR, PRI, & wetness)

Canadell et al. 1996. Oecologia 108:583-595

Photosynthetic Reflectance Index(Gamon et al. 1992. Rem. Sen. Env. 41:35-44)

Suarez et al. 2009. Rem.Sen. Env. 113:730-744.Trotter et al. 2002. Int. J. Rem. Sen.23: 1207-1212.

8 species in New Zealand Olive trees

Hall et al. 2008. Remote Sensing of Env. 112: 3201-3211

Douglas-fir (sunlite) Campbell River, B.C.

Partitioning of forest NPP below ground ranges from 20% to 60% (Waring et al. (1998). When GPP 2500 g C m-2 yr-1

(respiration + NPPb) ~ minimum

Litton et al.

0.0

2.0

4.0

6.0

8.0

10.0

0 2000 4000 6000 8000

GPP, gC m-2 yr-1

Rat

io o

f bel

ow

gro

un

d c

arb

on

al

loca

tion

to a

bo

veg

rou

nd

NP

P

Litton et al. 2007. Global Change Biology 13: 2080-2109Chen et al. 2003. Oecologia 137: 405-416Stape et al. 2008. For. Ecol. & Mgmt. 255: 920-930.Waring et al. 1998. Tree Physiol. 18:129-134.

tropical savanna

young ponderosa pine

aspen

black sprucejack pineold ponderosa pine

N =38

plantations

NEE varies seasonally by type of vegetation, as does GPP

After Baldocchi 2009 Aust. J. Bot. (in press)

After Baldocchi 2009 Aust. J. Bot. (in press)

Predicting Ecosystem Respiration or NEE (GPP-Reco) as a function of eddy-flux measured GPP

r2 = 0.9 =0.77

=0.94

To improve predictions of GPP, NPP, and NEE from space

• Chlorophyll light absorbance is better than nitrogen content to estimate max. conductance and photosynthetic capacity.

• Max. conductance and photosynthetic capacity are reduced as trees approach site & species-specific maximum height.

• PRI is a good check on modeled constraints on GPP

• GPP is more important to estimate accurately than NPP, although NPPA would be helpful to validate model predictions of growth allocation.

• Allocation of NPP (& respiration) increases below-ground if water and nutrients are not available, generally not the case if GPP 2500 g C m-2 yr-1.

• Ecosystem respiration is ~ 75% of GPP in undisturbed systems, ~ 95% in disturbed systems. Be able to distinguish disturbed systems & recovery.

Email: Richard.Waring@oregonstate.edu Nicholas Coops [nicholas.coops@ubc.ca] Joe Landsberg [jlandsberg@netspeed.com.au]

Waring, Coops, & Landsberg. 2009. Improving predictions of forest growth using the 3-PGS model with observations made by remote sensing. For. Ecol. & Mgmt. (in press). (RHW Pub. No. 108). www.fsl.orst.edu/~waring