Ecological Applications of Imaging
Spectrometry: Examples from Fire
Danger, Plant Functional Types and
Disturbance
Roberts, D.A.,1, Asner, G.P.2, Dennison, P.E.3,
Halligan, K.E.1, and Ustin*, S.L.4
1 Department of Geography, University of California, Santa Barbara,
California 2 Department of Global Ecology, Carnegie Institution,
Stanford, California 94305
3Department of Geography, University of Utah, Salt Lake City, Utah,
84112
4 Department of Land, Air and Water Resources, University of
California, Davis, California, 95616
*Presenting author
Talk Outline
• Background: Important Ecological Function
and Process
• Why use Imaging Spectrometry
• Example Applications
– Fire Danger Assessment
– Invasive Species on the Hawaiian Islands
– Invasive Species in Coastal California
Important Ecological Functions & Processes
• Natural Disturbance/Hazards
Wildfires
Insect outbreaks
Erosion
Severe weather
Climate Change
Flooding
After
Hurricane
Katrina
Insect Mortality
Wildfire
Important Ecological Functions & Processes
• Anthropogenic Disturbance Factors
Agriculture
Forestry
Other Land Use
Roads
Contamination
Events
Invasive Species
Logging Patterns
Oil Spill
Fragmentation
Irrigated Agriculture
The Importance of Plant Functional Types
•What is a Plant Functional Type (PFT)?
Poorly defined, ad hoc ecological definitions
• Plant species or communities with similar
ecological functions
Example: Southern California shrublands
• Facultative seeders – stump resprout
(Chamise)
• Obligate seeders – (big pod Ceanothus)
Example: Hawaiian Islands
Facultative Seeder: Chamise
• Nitrogen fixing trees/shrubs (fire tree)
• Fire adapted fountain grass
•PFTs mapping specific plants species often
easiest
•PFTs often “adapted” to specific disturbance
regimes
Obligate Seeder: Ceanothus
Feedbacks Between Disturbance
and PFTS: Examples with
invasive grasses
Invasive Cheatgrass
Fire - Grass Feedback
– Grasses replace natives
– Act as a fine fuel Æ fire
ignition & fire spread
– Increased fire frequency Æ
eradicates natives
Æ promotes invasive grass
Specific Examples:
Palouse Plateau
Low, Medium, High Cover
– Cheat grass altering fire
regime across western US
– Fountain grass in the
Hawaiian Islands
• Invades uncolonized basalt
flows; produces fine fuels
• Connects Kipukas (isolated
forests), promoting fire spread
– Increased fire frequency in So.
California shrublands
• Removes obligate seeders
• Grasses & sprouters Æ fire
• eliminates big pod Ceanothus
Why Use Imaging Spectrometry?
• Imaging spectrometry has considerable potential
for…
– Improve ability to identify PFTs
• Enhanced discrimination based on spectroscopy
– Quantify plant biophysical properties
• Directly detect & Quantify Light Use Efficiency,
Chlorophyll and Water content, etc. using narrow
spectral features
– Improve monitoring of vegetation change
• Ability to characterize & retrieve surface reflectance
• Accurate change detection of PFTs
• Accurate change detection of plant function
Example 1: Fire Danger Assessment
Fire danger depends on physical and biophysical
properties:
• Physical: Weather, topography,
ignition sources, people
• Biophysical:
–
–
–
–
Live fuel moisture (LFM)
Green live biomass
Ratios of live to dead materials
Species composition
• Response to disturbance
• Fire promoting “adaptations”
Plant Spectroscopy and Fuels
• Changes in visible, NIR and
SWIR reflectance:
– Varies with chlorophyll
– Varies with NPV content
– Varies with LAI
• Ligno-cellulose bands
– differentiates dead/dry
fuels from soils
• Depth of liquid water bands
– differentiates moisture
content
Roberts et al., 2006
Relationship Between AVIRIS-Measures
and LFM
13 AVIRIS scenes acquired between 1994 and 2001
LFM measured by LACFD & correlated to AVIRIS measures
LFM sampled ~ biweekly from 1984 to present
AVIRIS Measures of Live Fuel Moisture
•
•
LFM highly correlated to greenness & moisture
• Threshold linear relationship
Below 60% LFM is constant, above 60% fuel condition (live to dead
ratios) changed, impacting indices
• Relationship varied with PFT
Roberts et al., 2006
Mapping Plant Functional Types using MESMA
Adenostoma fasciculatum
Ceanothus megacarpus
Arctostaphylos spp.
Quercus agrifolia
Grass
Soil
Accuracy: 87%
Dennison and Roberts, 2003
Plant Functional Types and Plant Moisture
Seasonal changes in EWT varies with PFT
Relationship between LFM and remote sensing measures varies
with PFT
Ustin et al., 2004
Example 2: Invasive Species in Hawaiian
Forest Ecosystems
Why it’s important:
• Alter ecosystem functioning,
including carbon &
hydrological dynamics
Myrica faya
• Invasive species change
habitat conditions
• Invasive species cost $B’s
annually in management
& mitigation
Hedychium
African grasses
Measurement of Canopy Chemistry to Detect
Invasive Species of Hawaiian Rainforest
Total Canopy Water Content = LAI * leaf water
Top-of-canopy “Leaf Nitrogen Concentration”
Leaf
Nitrogen
Canopy
Water
Kilauea Iki
Kilauea Iki
Kilauea Volcano
Kilauea Volcano
0 μm
Canopy Water
2500 μm
0%
Leaf Nitrogen
2.5 %
Asner and Vitousek 2005
Canopy Chemistry Æ Invasive
Species
Myrica invasion front
(high leaf nitrogen)
Myrica infestations
(high leaf nitrogen
and high canopy water)
Kilauea Caldera
Hedychium in
forest understory
(high canopy water)
High Canopy Water
High Leaf Nitrogen
High Water & Nitrogen
Low Water & Nitrogen
Fire Danger, Vegetation and Climate
A19
A03
A05
● PV
● NPV
● Bare soil
Asner et al. 2005
Climatic Impacts on Fractional Cover
100
PV
NPV
Bare
90
Fractional Cover (%)
80
70
NPV dominates drier sites
PV dominates moisture sites
60
50
40
30
20
10
0
250
500
750
1000 1250 1500 1750 2000 2250 2500 2750 3000
Mean Annual Precipitation (mm)
• Moisture drives fire susceptibility
– Low elevation drier sites dominated by fire prone
grasslands
• Invasive grasses replace native shrubs, connect forest
patches
Species Mapping at
Vandenberg AFB
Mixed coastal
chaparral & coastal
scrub communities
Jubata invaded chaparral
Iceplant invaded scrub
Masked
Intact chaparral
Iceplant invaded chaparral
Road
Intact scrub
Blue gum
Coast
Underwood, Ustin, & Ramirez, (Ecol. Monitoring * Assessment) In press; Underwood and Ustin, 2003
GIS Based Classification and Regression Trees (CART)
Candidate Physical Factors to Predict Suitable Habitat Sites
Probability of Invasion created by CART physical site models
Probability of Coastal
Sage Scrub invasion by
iceplant
Probability of Maritime
Chaparral invasion by
iceplant
Probability of Maritime
Chaparral invasion by
jubata grass
Anthropogenic site factors also modeled by CART permitting
independent management decisions
Probability of Invasion created by CART Anthropogenic models
Probability
of Coastal
(a) Probability of
Sage Scrub
invasion by
scrub invaded by
iceplant iceplant
Probability
of Coastal
(b) Probability
of
Sage Scrub
invasion
chaparral invaded byby
iceplant iceplant
Probability
of Maritime
(c)Probability
of
Chaparral
invasion
chaparral invaded by by
jubata jubata
grassgrass
Summary
• Anthropogenic and natural disturbances
have a major impact on ecosystem function
• Rates of disturbance are increasing
• There is a strong relationship between
disturbance, PFTs and Biological Invasions
• Imaging spectrometry is a powerful tool for
monitoring disturbance and mapping
invasive plant species