Elizabeth Traver University of Wyoming

Quantifying spatial patterns in time of transpiration in aspen, alder, and sugar maple

dominated forests

Why spatial transpiration?

• There is solid evidence that VPD is a major driver of transpiration in time, but it does not explain the variable spatial patterns within species.

• Stands of trees tend to be more heterogeneous than homogeneous, with significant boundary areas--what causes these spatial patterns?

• Finding the--possibly edaphic—causes of these spatial patterns, we can use that knowledge to scale up to larger, heterogeneous landscapes.

Hypotheses

• VPD explains the temporal variability in spatial autocorrelation of transpiration.

• At high VPD, edaphic conditions will explain the spatial autocorrelation of variability in transpiration

total N impacts on root properties

soil texture impacts on root cavitation

Sites

• Aspen—Alder: SE of the WLEF tower – 120 m by 120 m with 144 plots in a 3/7 cyclic design– Runs from wetlands in NW to dry upland in SE

• Sugar Maple—Red Pine: NW of the WLEF tower– 120 m by 120 m with 144 plots in a 3/7 cyclic design– Mostly sugar maple crossed by swath of red pine

Aspen-Alder site

Sugar Maple-Red Pine site

WLEF Tower

3/7 Cyclic sampling design.

Methods

• Measure sap flux spatially-- Granier: constant heat flux sensors

• Measure or acquire environmental factors-- micrometeorology from WLEF tower: μ, Q, rh, temp

• Measure soil characteristics within the 3/7 cyclic plots already established– Soil moisture curves– Soil texture– Total N

• Intra-tree scaling -- Asap

• Spatial sampling/analysis -- cyclic, ‘variograms, geostatistics, GIS

Various measurements

and instruments in

action

June 2005

VP

D (

kPa)

0.0

0.5

1.0

1.5

2.0

2.5

3.0

Tra

nsp

ira

tio

n (

g t

ree-1

s-1

)

0.0

0.1

0.2

0.3

0.4

0.5

0.6

VPDAlder wet Aspen transitionAspen upland

0.00

0.25

0.50

0.75 20022003

EL

(mm

da

y-1 )

0.0

0.5

1.0

1.5

2.0

20022003

DZ (kPa)

0.0 0.5 1.0 1.50.00

0.25

0.50

20002001

A

B

C

SV

WC

HC

ChEAS A. saccharum

R2 = 0.77

R2 = 0.69

R2 = 0.72

R2 = 0.73

R2 = 0.80 ChEAS

GSref (mmol m-2 s-1)

0 20 40 60 80 100 120

m [

mm

ol m

-2 s

-1 ln

(kP

a)-1

]

0

20

40

60

m = 0.6 GSref

HC 2000HC 2001WC 2002WC 2003 SV 2002SV 2003

A. saccharum

Ewers et al. 2006 Ag For Met

EC n

ugge

t (g

tree

-1 s

-1)2

0

20

40

60

80

EC n

ugge

t (g

tree

-1 s

-1)2

0.0000

0.0002

0.0004

0.0006

EC s

ill (

g tr

ee-1

s-1

)2

0.00

0.01

0.02

0.03

0.04

EC s

ill (

g tr

ee-1

s-1

)2

0.000

0.002

0.004

0.006

VPD (kPa)

0.0 0.5 1.0 1.5 2.0 2.5

EC r

ange

(m

)

0

10

20

30

40

50

VPD (kPa)

0.0 0.5 1.0 1.5 2.0 2.5

EC r

ange

(m

)

0

50

100

150

R2 = 0.95

R2 = 0.98

R2 = 0.85 R2 = 0.75

R2 = 0.54

R2 = 0.55

Nugget, sill, and range of transpiration plotted against VPD.

As transpiration variation increases with VPD, spatial autocorrelation decreases.

(Data from the aspen-alder stand.)

Distance (m)

0 20 40 60 80 100 120 140

Vol

umet

ric S

oil M

oist

ure

()

(%

2 )

0

200

400

600

800

1000

= 26% = 32%

Future work

Using what is already known about the temporal variability of transpiration, look at edaphic conditions to explain the spatial variability.