High throughput phenotyping at the cottonwood common gardens

Chris Doughty and Eleanor Thomson

Asner et al 2016

R E F L E C T A N C E S I G N A T U R E S

• Many leaf traits, including photosynthesis (Amax), can be predicted via leaf spectral properties.

Using leaf spectroscopy to predict leaf traits

Doughty et al 2011

Can we predict other non-leaf traits?

Amax-sunlit

predicted

0 2 4 6 8 10 12 14

me

asure

d

0

5

10

15

20

25

Amax

X Data

400 600 800 1000

-3e-5

-2e-5

-1e-5

0

1e-5

2e-5

3e-5

we

ighting

s

-0.0002

-0.0001

0.0000

0.0001

0.0002

1st PC

2nd PC

r2 = 0.28

RMSE = 2.9

RMSE/mean = 0.46

Asat-sunlit

X Data

0 5 10 15 20 25

me

asure

d

0

5

10

15

20

25

30

35

Asat

X Data

400 600 800 1000

-4e-5

-2e-5

0

2e-5

4e-5

we

ighting

s

-0.0004

-0.0002

0.0000

0.0002

0.0004

1st PC

2nd PC

Leaf Veination-sunlit

X Data

0 5 10 15 20 25

me

asure

d

0

5

10

15

20

25

30Leaf Veination

X Data

400 600 800 1000

-0.00010

-0.00005

0.00000

0.00005

0.00010

we

ighting

s

-0.010

-0.005

0.000

0.005

0.010

1st PC

2nd PC

r2 =0.53

RMSE=3.8

RMSE/mean = 0.31

Leaf wettness-sunlit

predicted

30 40 50 60 70 80 90 100 110

me

asure

d

30

40

50

60

70

80

90

100

110

Leaf wettness

spectra (nm)

400 600 800 1000

we

ighting

s

-0.002

-0.001

0.000

0.001

0.002

0.003

1st PC

2nd PC

r2 = 0.83

RMSE = 9.6

RMSE/mean = 0.15

r2=0.19

RMSE=5.0

RMSE/mean = 0.46

• We can predict traits like photosynthesis, wood density, veination and leaf wetness with spectroscopy

Doughty et al 2017

A two-environment reaction norm showing the components of phenotypic variation of four genotypes: G = trait variation due to

population genetics within a single environment, E = trait variation due to change in environment (plasticity), GxE = the variation in plasticity among genotypes. Phenotypic variation (VP) = VG + VE + VGxE. From

Cooper et al. 2018 Global Change Biology.

Genetics-based

responses to

climate change

Plasticity

Genetic Variation

in Plasticity

Genetic

Reciprocal common gardens show finer scale local adaptation

within the Sonoran desert ecotype

Reciprocal

Common

Gardens

TNC

Dugout Ranch, Canyonlands

Cooler Garden – MAT 10.7 °C

AZG&F

Horseshoe Ranch

Intermediate – MAT 17.2 °C

BLM

Mittry Lake, Yuma

Hot Garden – MAT 22.8 °C

(Cooper et al. 2018 Global Change Biology)

Preliminary Methods

• Hierarchical cluster analysis

• Partial least squares regression

• Need more traits for comparison!

Hierarchical cluster analysis applied to the average spectra of each population sampled in each garden.

Strong predictions of both genotypes and plant

height

Ind

ividu

al traits

Ecosystem properties

Co

mm

un

itie

s

Remote sensing

Genes-to-Ecosystems: Scaling from Critical Plant Species to Global Ecosystems for Precision Conservation & Security of Natural Resources

NEEDS DESCRIPTION

• We have demonstrated that individual leaf spectroscopy predicts key plant traits.

• A suite of technologies is needed to scale trait detection to landscape and global levels.

• We can succeed by combining Raytheon’s expertise and capacities in hyperspectral remote sensing with NAU’s infrastructure and expertise in genetics, ecology and remote sensing.

• We can integrate genetics and environment to develop predictive models of landscape scale shifts as a function of the environment.

• Hyperspectral remote sensing and lidar predicts tree genetics and phenotype, enabling prediction of future plant traits that promote drought tolerance needed in a warmer world.

• Predict vulnerable environmental regions before an environmental catastrophe leads to famine, instability and migration.

• Customers: DoD, DHS, FEMA

• Climate change and invasive species are altering ecosystems at an unprecedented rate, leading to massive mortality of plants that provide key ecosystem services including food, fiber, fuel, and clean water.

• By combining high performing plant genotypes with microbes that promote stress tolerance, we will restore ecosystem services to degraded lands, promoting global health and security.

deep Shallow roots

roots

Water table

Populus fremontii

field trial Field Trials

Early Warning System Remote measurement of genotype

• Infer gene by environment interactions to predict vulnerability to climate change.

• Customers: USFS, NPS, USDA, BLM, BOR

MISSION

WIN STRATEGY/KEY TECHNOLOGIES

END USER/CUSTOMER Shallow roots