Redwoods go wireless:discovering the links between

treesand the hydrological cycle

Todd DawsonCenter for Stable Isotope Biogeochemistry

&Department of Integrative Biology, University of California - Berkeley

Global Context:Global Context:

• • Forests cover 32% of the Earth’s surfaceForests cover 32% of the Earth’s surface• • Forests recycle ~66% of all the fresh water on Earth each yearForests recycle ~66% of all the fresh water on Earth each year (~7,500,000 km(~7,500,000 km3 3 moves through trees each year)moves through trees each year)• • The “climate” system has long been thought to ‘drive’ this waterThe “climate” system has long been thought to ‘drive’ this water movement through forestsmovement through forests

BUT . . . BUT . . .

• • Trees and forests significantly modify the climate and micro-Trees and forests significantly modify the climate and micro- climates that are known to drive water lossclimates that are known to drive water loss

• • There is a pressing need to determine the relative importance ofThere is a pressing need to determine the relative importance ofbiological & physical drivers of the hydrological cycle via,biological & physical drivers of the hydrological cycle via,» » Precise characterizations of the biological activities of treesPrecise characterizations of the biological activities of trees» » Precise characterizations of the environmental driversPrecise characterizations of the environmental drivers

Local Context:Local Context:

Coast redwood occupy a unique hydrological zone Coast redwood occupy a unique hydrological zone near the land-sea interface are characterized by:near the land-sea interface are characterized by:

Maritime FogMaritime FogWhat is unknown is its importance for:What is unknown is its importance for:

(a) redwood tree ecology and physiology,(a) redwood tree ecology and physiology,(b) the water balance of redwood forests,(b) the water balance of redwood forests,(c) California’s water resource issues(c) California’s water resource issues

Fog, and its importance in coastal California’s Fog, and its importance in coastal California’s hydrology is unknown, yet could be central to hydrology is unknown, yet could be central to understanding what links ocean and land systems understanding what links ocean and land systems and impacts coastal ecology.and impacts coastal ecology.

In other coastal zones (Chile, W. Africa) fog is part of In other coastal zones (Chile, W. Africa) fog is part of water resource management and conservation water resource management and conservation issues.issues.

Redwood Program ObjectivesRedwood Program Objectives::

Elucidate the role of fog for/on:Elucidate the role of fog for/on:

- The ecophysiology of redwood - The ecophysiology of redwood treestrees

- The functioning of redwood - The functioning of redwood forestsforests with a with a focus on marine subsides of waterfocus on marine subsides of water

Place such an understanding into the broader Place such an understanding into the broader view of how TREES shape the hydrological view of how TREES shape the hydrological cycle and in particular the hydrology of cycle and in particular the hydrology of California’s water limited environsCalifornia’s water limited environs

Present-day Coast RedwoodPresent-day Coast RedwoodGeographical DistributionGeographical Distribution

Berkeley/SFBerkeley/SFInfluenced by Maritime Fog in SummerInfluenced by Maritime Fog in Summer

PAST APPROACHPAST APPROACH::

Deployment of gear is done Deployment of gear is done by us (read: by us (read: Homo sapiensHomo sapiens))

» » Sensors are all “wired” Sensors are all “wired” andandtherefore can only sample a therefore can only sample a very small fraction of what very small fraction of what we need to samplewe need to sample

But…how do you determine the role of redwood treesBut…how do you determine the role of redwood treesin the hydrological cycle when canopy heights exceedin the hydrological cycle when canopy heights exceed100m and environmental variation is perhaps the100m and environmental variation is perhaps thegreatest we’ll ever find?greatest we’ll ever find?

THINK WIRELESS!THINK WIRELESS!

intelintel wireless sensor networks wireless sensor networks

Weather mote

Burrow mote

2002 Weather moteRedwoods go Redwoods go wireless!wireless!

Temperature vs. Time

8

13

18

23

28

33

7/7/039:40

7/7/0313:41

7/7/0317:43

7/7/0321:45

8/7/031:47

8/7/035:49

8/7/039:51

8/7/0313:53

8/7/0317:55

8/7/0321:57

9/7/031:59

9/7/036:01

9/7/0310:03

Date

Tem

pera

ture

(C

)

Humidity vs. Time

35

45

55

65

75

85

95

Rel H

um

idit

y (

%)

101 104 109 110 111

2003, unpublished

Bottom Top

36m

34m

30m

20m

10m

What’s next?What’s next?Gather data in 3-D - play the movieGather data in 3-D - play the movieRender data and place trees into contextRender data and place trees into contextModel the plant-environment systemModel the plant-environment systemCompare to other systemsCompare to other systems

XXXX

YYYY

ZZZZ

Now MATCH with other Field Methods:Now MATCH with other Field Methods:

TREE-SCALE: Sap flow sensors TREE-SCALE: Sap flow sensors (heat ratio method) placed in the (heat ratio method) placed in the lower stem, upper stem (50+ m) lower stem, upper stem (50+ m) and upper branches of a 60-110 m and upper branches of a 60-110 m redwood tree in coastal Californiaredwood tree in coastal California

Ecosystem methods that permit us Ecosystem methods that permit us to characterize site water balanceto characterize site water balance

A time of tremendous biological activityA time of tremendous biological activityDawson, 1998Dawson, 1998

Typical Pattern of Rainfall and Fog Occurrence in Coastal CaliforniaTypical Pattern of Rainfall and Fog Occurrence in Coastal California

Remove Trees andFog inputs decline

by 33 to 50%

Dawson, 1998Dawson, 1998

Total = 1,845mmTotal = 1,845mm

465mm465mm

020406080

100120

1200 33

019

00

1030 20

0

1730 90

0 30

1600

0.1

1

10

100

1000

10000

RH

Foginess

Leafwetness

WET leavesWET leaves

Heat Ratio SapflowHeat Ratio SapflowMethod Method (Burgess et al. (Burgess et al. 2001)2001)

Data logger,Data logger,storage module &storage module &battery in treebattery in tree

Well-organizedWell-organizedmultiplexer &multiplexer &wiring set-upwiring set-up

Probe setProbe set

SolarSolarpowerpower

Because of its Because of its symmetric symmetric configuration, configuration, the HRM can the HRM can resolve zero resolve zero flows as well as flows as well as reverse flows!reverse flows!

TT22

TT11

Heat Ratio MethodHeat Ratio Method

Zero sap Zero sap flowflow

HeaterHeater

Heat Ratio MethodHeat Ratio Method

Active sap Active sap flowflow

V = thermal diffusivity x Ln T1

probe distance T2

TT22

TT11

HeaterHeater

Flow velocity (V) Flow velocity (V) is logarithmically is logarithmically related to the ratio related to the ratio of temperature of temperature increases up- and increases up- and down-stream from down-stream from a heatera heater

Active sap Active sap flowflow

0

20

40

60

80

100

RH

(%

)

0.01

0.1

1

10

100

1000

10000

Le

af

we

tne

ss

(0

= w

et,

10

00

0+

= d

ry)

RH

leaf wetness

-10

0

10

20

30

40

50

60

70

80

90

100

0:0

2

6:0

2

12

:02

18

:02

0:0

2

6:0

2

12

:02

18

:02

0:0

2

6:0

2

12

:02

18

:02

0:0

2

6:0

2

12

:02

18

:02

0:0

2

6:0

2

Xy

lem

sa

p f

lux

(%

of

ma

xim

um

)

Branch at 50 m

Stem at 50 m

Stem at 1 m

Low HumidityLow HumidityNightNight

NighttimeNighttimeTranspirationTranspiration[10-40% of day][10-40% of day]

0

20

40

60

80

100

RH

(%

)

0.01

0.1

1

10

100

1000

10000

Le

af

we

tne

ss

(0

= w

et,

10

00

0+

= d

ry)

RH

leaf wetness

-10

0

10

20

30

40

50

60

70

80

90

100

0:0

2

6:0

2

12

:02

18

:02

0:0

2

6:0

2

12

:02

18

:02

0:0

2

6:0

2

12

:02

18

:02

0:0

2

6:0

2

12

:02

18

:02

0:0

2

6:0

2

Xy

lem

sa

p f

lux

(%

of

ma

xim

um

)

Branch at 50 m

Stem at 50 m

Stem at 1 m

High RH

Wet leaves

No transpiration

Reverse Reverse flowflow

[in daytime [in daytime too]too]

5-7% of daily 5-7% of daily maxmax

y = 0.0035x2 - 0.13x - 28.16

R2 = 0.91

y = 0.0038x2 - 0.28x - 23.60

R2 = 0.95

y = 0.0025x2 - 0.11x - 28.18

R2 = 0.90

-31.00

-30.00

-29.00

-28.00

-27.00

-26.00

-25.00

-24.00

-23.00

13C

Sonoma EdgeSonoma InteriorBig Basin

y = -0.06x 2 + 2.12x + 250.46

R2 = 0.91

y = -0.06x 2 + 4.46x + 177.98

R2 = 0.95

y = -0.04x 2 + 1.76x + 250.72

R2 = 0.90

150.00

170.00

190.00

210.00

230.00

250.00

270.00

290.00

0.00 10.00 20.00 30.00 40.00 50.00 60.00 70.00 80.00

Height (m)

Ci (

ml l

-1)

Sonoma Edge

Sonoma InteriorBig Basin

13

13C

(‰

)C

(‰

)CC

ii (p

pm

) (

pp

m)

Plant or Plant or environment?environment?

How do oceanic subsidies ofHow do oceanic subsidies ofwater shape stand water use?water shape stand water use?

Can we use natural gradients toCan we use natural gradients tohelp us obtain comparative data?help us obtain comparative data?

Can we elucidate the importanceCan we elucidate the importanceof various controls: the “donor”,of various controls: the “donor”,the plant, the microbes?the plant, the microbes?

From: Gilliam 1962From: Gilliam 1962

Ecosystem ScaleEcosystem Scale

Monthly totals

0

2000

4000

6000

8000

10000

12000

Jan

-06

Sap

flow

(m

Sap

flow

(m

3

3 x

10

x 1

033 m

on

t h m

on

th- 1-1))

FOGFOG

44

22

66

88

1010

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

For 2001:For 2001:»»Big Basin trees use more water than do trees in Sonoma (drier nights?) Big Basin trees use more water than do trees in Sonoma (drier nights?) »»Interior trees use more than edge trees (unless its very foggy; Aug + Sept)Interior trees use more than edge trees (unless its very foggy; Aug + Sept)»»Trees in winter use 30-75 L/day but in summer use 175-350 L/dayTrees in winter use 30-75 L/day but in summer use 175-350 L/day

20012001

Inter-annual comparison: Inter-annual comparison: 20012001 vs. vs. 20022002

Rain fall (mm) Fog drip (mm) VPDRain fall (mm) Fog drip (mm) VPDsummersummer (kPa) H (kPa) H22O use (L)O use (L)

1285

1340

355

240

1.9-3.3

2.2-3.1

70,700

61,350

1390

1455

440

415

1.2-2.6

1.3-2.8

57,300

73,140

1390

1455

370

350

1.1-2.4

0.9-2.6

64,450

75,210

BBBB

SESE

SISI

20012001

20022002

20012001

20022002

20012001

20022002

Tree water use and stand water balance is a function of:Tree water use and stand water balance is a function of:» » Fog inputs and evaporative demand for summer waterFog inputs and evaporative demand for summer water

(supply vs. demand)(supply vs. demand)» » Water stress in summerWater stress in summer

(influences both supply and demand)(influences both supply and demand)

PDO & ENSO influence SST and in turn fog formationPDO & ENSO influence SST and in turn fog formation

warmwarm

coolcool