Erica Lindgren-- MS candidate Committee Members: Barry Rock, Elizabeth Middleton (GSFC), John Aber Anthocyanins as Antioxidants in Trees: Finding a Way Towards the Truth

Leaf Pigments Tannins Anthocyanins Carotenoids Chlorophylls

Anthocyanin Roles Temperature regulation Anti-herbivory Anti-fungal UV protection Assist transport of sugars Drought Freezing Modify light within the leaf Potassium deficiency Nitrogen deficiency Phosphorus deficiency Antioxidant

Anthocyanins in Sugar Maple Spring Cyanidin-3- monoglucoside 41% Cyanidin-3-rutinoside 10.5% Cyanidin-3- galloylglucoside 16% Cyanidin-3- galloylrutinoside 1% Delphinidin-3-glucoside 12% Delphinidin-3-rutinoside 17.5% Fall Cyanidin-3- monoglucoside (82%) Cyanidin-3- galloylglucoside (17%) Ji, Shi-bao et al Distribution of Anthocyanins in Aceraceae Leaves. Biochemical Systematics and Ecology. Vol. 20, p

What I am interested to learn… If cyanidin-3-monoglucoside is related to antioxidant power of a sugar maple leaf in the fall Is the predominance of this pigment in the fall due to oxidative stress or providing one of the other functions?

FIA, predictions by 2100

Anthocyanin Detection Inform us about individual stresses Could be used as a general stress indicator Track fall foliage Sugar Maples Environmental conditions affect oxidative stress the most Track fall-to-fall and see if there are long-term trends

Rather than… It would be easier to track anthocyanin concentrations through non-destructive analysis 1. Less time consuming 2. Could track more frequently Which leads to remote sensing of anthocyanins

Gitelson et al Optical properties and nondestructive estimation of anthocyanin content in plant leaves. Photochemistry and photobiology. Vol. 74, p

Rough ARI Comparison

Which might be useful?

Thank you to: The Research and Discover Program Barry Rock, Elizabeth Middleton, John Aber Paul Schaberg and Paula Murakami The authors whose papers are in my desk

Antioxidant Methods Oxygen Radical absorbance capacity TRAP Total oxidant scavenging capacity Chemiluminescence Photochemiluminescen ce Croton or Beta Carotene bleaching Low-density lipoprotein oxidation Ferric reducing antioxidant power Copper reduction assay TEAC/ ABTS DPPH Folin-Ciocalteu

Antioxidant Methods Oxygen Radical absorbance capacity TRAP Total oxidant scavenging capacity Chemiluminescence Photochemiluminescen ce Croton or Beta Carotene bleaching Low-density lipoprotein oxidation Ferric reducing antioxidant power Copper reduction assay TEAC/ ABTS DPPH Folin-Ciocalteu HAT SET HAT/SET

Hypotheses H1-A satellite-derived spectral index will detect and characterize the amount of anthocyanin within sugar and red maple canopies during fall senescence. H2- This satellite-derived spectral index will allow detection and quantification of variations in timing and intensity of fall senescence between 2002 and 2008.

Objectives Determine anthocyanin concentration range for sugar and red maple, including how this concentration affects spectral characteristics. Ten trees will be tested throughout the season as senescence occurs. Determine spectral characteristics though analysis with the VIRIS. Determine leaf color visually using Munsell’s color chart and digitally photograph leaves. Determine chlorophyll and anthocyanin concentrations spectrophotometically. For testing red maples, an additional site may be required.

Objectives Find best estimation of anthocyanin by comparing results from lab experiments (yielding anthocyanin concentrations) to modeled MODIS/MERIS bands from the VIRIS (giving spectral anthocyanin estimations). These results can then be compared to actual MODIS/MERIS imagery obtained throughout the fall. Compare anthocyanin concentrations from lab experiments to spectral signature obtained through VIRIS. Apply and analyze optimized relationships from the MODIS/Hyperion/MERIS investigation (see objective 3). Compare to actual anthocyanin concentrations. Compare modeled band results (within known deviation from actual anthocyanin concentrations) to values from MODIS and MERIS imagery obtained during the fall.

Objectives Compare Hyperion image with MODIS and MERIS images acquired on the same day to identify differences in the electromagnetic signature. By comparing the sensors the best optimization of the ARI can be determined. These images will be similarly manipulated in terms of methods for removing effects from clouds, shadows, and aerosols. Compare images in 550nm range for both land and ocean bands in MODIS, MERIS and Hyperion. Compare images in 700nm range for both land and ocean bands in MODIS, MERIS and Hyperion. Distinguish other areas for chlorophyll signature in both MODIS land and ocean bands and MERIS by viewing differences in a) other wavelengths, b) chlorophyll florescence, and c) red edge parameters.

Objectives Track temporal changes in spectrally-deduced anthocyanin concentrations over a number of years and compare to possibly environmental influences such as temperature, date of first killing frost, ozone concentrations, rainfall, etc. (See contingency plan).

Some additional thoughts… I think that MERIS will work best due to band placement. I would like to focus on using this rather than MODIS or Landsat, but I would still compare field data to see potential of these systems. Keep comparison to Hyperion. MERIS also has good placement for carotenoid estimation (focus on sugar maple). If I focused on MERIS I could possible estimate this as well. Ideal = (R480 or R500 – R678)/R800 Band 8, nm, 7.5 nm Band 3, 490 nm, 10nm Band 12, 775 nm, 15nm

Detection is possible

Reduced Resolution Full Resolution

Issues Homogeneity for field study Size of pixels Number of useable images Sugar maple or red maple or both Anthocyanin only or carotenoids as well

Questions?