Ecological Applications of Imaging Spectrometry: Examples from Fire Danger, Plant Functional Types and Disturbance

Transcription

1 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 Department of Geography, University of Utah, Salt Lake City, Utah, Department of Land, Air and Water Resources, University of California, Davis, California, *Presenting author

2 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

3 Important Ecological Functions & Processes Natural Disturbance/Hazards Wildfires Insect outbreaks Erosion Severe weather Climate Change Flooding After Hurricane Katrina Insect Mortality

4 Important Ecological Functions & Processes Anthropogenic Disturbance Factors Logging Patterns Agriculture Forestry Other Land Use Roads Contamination Events Invasive Species Fragmentation Oil Spill Irrigated Agriculture

5 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 Nitrogen fixing trees/shrubs (fire tree) Fire adapted fountain grass PFTs mapping specific plants species often easiest PFTs often adapted to specific disturbance regimes Facultative Seeder: Chamise Obligate Seeder: Ceanothus

6 Feedbacks Between Disturbance and PFTS: Examples with invasive grasses Palouse Plateau Invasive Cheatgrass Low, Medium, High Cover Fire - Grass Feedback Grasses replace natives Act as a fine fuel fire ignition & fire spread Increased fire frequency eradicates natives promotes invasive grass Specific Examples: 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 fire eliminates big pod Ceanothus

7 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

8 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

9 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

10 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

11 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

12 Mapping Plant Functional Types using MESMA Adenostoma fasciculatum Ceanothus megacarpus Arctostaphylos spp. Quercus agrifolia Grass Soil Accuracy: 87% Dennison and Roberts, 2003

13 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

14 Example 2: Invasive Species in Hawaiian Forest Ecosystems Why it s important: Alter ecosystem functioning, including carbon & hydrological dynamics Invasive species change habitat conditions Myrica faya Invasive species cost $B s annually in management & mitigation Hedychium African grasses

15 Measurement of Canopy Chemistry to Detect Invasive Species of Hawaiian Rainforest Top-of-canopy Leaf Nitrogen Concentration Leaf Nitrogen Canopy Water Total Canopy Water Content = LAI * leaf water Kilauea Iki Kilauea Iki Kilauea Volcano Kilauea Volcano 0 μm Canopy Water 2500 μm 0 % Leaf Nitrogen 2.5 % Asner and Vitousek 2005

16 Canopy Chemistry Invasive Species Myrica invasion front (high leaf nitrogen) Hedychium in forest understory (high canopy water) Kilauea Caldera Myrica infestations (high leaf nitrogen and high canopy water) High Canopy Water High Leaf Nitrogen High Water & Nitrogen Low Water & Nitrogen

17 Fire Danger, Vegetation and Climate A19 A03 A05 PV NPV Bare soil Asner et al. 2005

18 Climatic Impacts on Fractional Cover 100 Fractional Cover (%) PV NPV Bare NPV dominates drier sites PV dominates moisture sites 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

19 Species Mapping at Vandenberg AFB Mixed coastal chaparral & coastal scrub communities Jubata invaded chaparral Intact chaparral Intact scrub Iceplant invaded scrub Iceplant invaded chaparral Blue gum Masked Road Coast nderwood, Ustin, & Ramirez, (Ecol. Monitoring * Assessment) In press; Underwood and Ustin, 2003

20 GIS Based Classification and Regression Trees (CART) Candidate Physical Factors to Predict Suitable Habitat Sites

21 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

22 Probability of Invasion created by CART Anthropogenic models Probability of Coastal Sage Scrub invasion by iceplant (a) Probability of scrub invaded by iceplant Probability of Coastal Sage Scrub invasion by iceplant (b) Probability of chaparral invaded by iceplant Probability of Maritime Chaparral invasion by jubata grass (c)probability of chaparral invaded by jubata grass

23 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