1. Jin Wu 1, Neill Prohaska 1, Kenia T. Wiedemann 1,2, Loren P. Albert 1, Alfredo R. Huete 3*, and Scott R. Saleska 1* Observing canopy demography of a tropical moist forest with spectral unmixing of hyperspectral images: a model of HyspIRI science application Email Contact: jinwu@email.arizona.edu or saleska@email.arizona.edujinwu@email.arizona.edusaleska@email.arizona.edu (1: Department of Ecology and Evolutionary Biology, University of Arizona; 2: School of Engineering and Applied Sciences, Harvard University; 3: Plant Functional Biology & Climate Change Cluster, University of Technology Sydney) *: Corresponding Authors

2. Outline of the Talk 1: Motivation—leaf demography matters ecological processes of forest systems 2: Methodology—remote sensing perspective of demography 3: Case study from a tower mounted hyperspectral vegetation imaging system in a tropical moist forest system 4: Inference to HyspIRI study

3. Motivation Photosynthesis is one of the most important features that define environment-vegetation interaction O2CO2, H2O

4. Motivation O2CO2, H2O Both environments and phenology are important controls on plant photosynthesis; Phenology includes Seasonality of LAI and Demography Soil Moisture Nutrients Environments Leaf Area Index Canopy leaf average physiology Phenology

5. Motivation Soil Moisture Nutrients Leaf Area Index CO2, H2O, O2 Canopy leaf average physiology Environments Phenology Both environments and phenology are important controls on plant photosynthesis; Phenology includes Seasonality of LAI and Demography

6. Motivation Photosynthesis and Photosynthesis Seasonality Soil Moisture Nutrients Leaf Area Index CO2, H2O, O2 Canopy leaf average physiology Environments Phenology Both environments and phenology are important controls on plant photosynthesis; Phenology includes Seasonality of LAI and Demography

7. Motivation (cont..) Deciduous Forests & Evergreen Tropical Forests Deciduous Broadleaf Forest, Takayama, Japan Muraoka et al. 2010. J Plant Research

8. Motivation (cont..) Deciduous Forests & Evergreen Tropical Forests Deciduous Broadleaf Forest, Takayama, Japan Muraoka et al. 2010. J Plant Research Albert & Wu. 1-m Branch Sample from Uxi Lista, 08/24/2012. Albert et al. In Preparation Leaf Age Tapajos National Primary Forest, Para, Brazil

9. Motivation (cont..) Deciduous Forests & Evergreen Tropical Forests Deciduous Broadleaf Forest, Takayama, Japan Muraoka et al. 2010. J Plant Research Albert & Wu. 1-m Branch Sample from Uxi Lista, 08/24/2012. Albert et al. In Preparation Leaf Age Tapajos National Primary Forest, Para, Brazil Leaf amount seasonality and demography seasonality are both important to tropical photosynthesis processes

10. Model perspective of tropical photosynthesis seasonality ED: Ecosystem Demographic Model Restrepo-Coupe et al. (In Review) IBIS: the Integrated Biosphere Simulator CLM: the NCAR Community Land Model JULES: the joint UK Land Environment Simulator Motivation (cont..) Key Mechanisms are missing in the models

11. Model perspective of tropical photosynthesis seasonality ED: Ecosystem Demographic Model Restrepo-Coupe et al. (In Review) IBIS: the Integrated Biosphere Simulator CLM: the NCAR Community Land Model JULES: the joint UK Land Environment Simulator Motivation (cont..) Key Mechanisms are missing in the models Albert & Wu. 1-m Branch Sample from Uxi Lista, 08/24/2012. (1)Leaf demography is an important component of leaf phenology; (2) Leaf demography is especially important for tropical forest photosynthesis processes; (3) currently, there is still lacking study on tropical demography

12. Methodology: Leaf demography Field methods (1) leaf level—tagging leaves and revisiting; (2) canopy level—regular harvesting branch sample and conducting demographic survey Remote sensing methods Seasonal RGB Images of a deciduous forest (Bartlett Forest, USA) in 2008 Richardson. 2010. Dublin Land Product Validation Subgroup. How about evergreen tropical forests?

13. Case Study: TNF-KM67, Para, Brazil months 10 0 -10 -20 -50-60-70-80 0 2 4 6 8 10 12 TNF-KM67 Monthly Precipitation (TRMM) <100 mm Study Site: Tapajos National Primary Forest, KM67 site (TNF-KM67), Para, Brazil B. RGB Image A. SOC Camera C. SOC Composited Image Key parameters: * Spectral resolution: 4nm, 128 bands from 385nm to 1050 nm * Field of view: 36×27 degree * Temporal resolution: image/10 minutes, July-December, 2012

14. Tree #/Name Nome CientíficoFamília Tr# 9 Erisma uncinatum Warm. Vochysiaceae Tr# 11 Ocotea sp.Lauraceae Tr# 118 Tachigali eriopetala (Ducke) L.G.Silva & H.C.Lima Leguminosae -Caesalp. Tr# 500 Manilkara huberi (Ducke) A.Chev. Sapotaceae Tr# 504 Coussarea paniculata (Vahl) Standl. Rubiaceae Sap Flow Tree Chamaecrista scleroxylon (Ducke) H.S.Irwin & Barneby Leguminosae -Caesalp. 2012 Fall Phenology Campaign (Saleska Lab, UofA) * 6 focal trees+14 understory trees were selected; * samples were collected in the early, middle, and late of dry season (Mid-Aug to Early-Dec) Case Study (cont..)

15. Bud scarsYoung LeavesOld Leaves Collected one meter branches multiple times throughout the dry season. Branches from sun and shade microenvironments within the trees. Counted young, mature and old leaves on sampled branches. Leaf demography survey

16. Ecosystem Level Leaf Demography Case Study (cont..)

17. Ecosystem Level Leaf Demography Inference to HyspIRI Study

18. Acknowledgments Sensor Calibration and Discussion William van Leeuwen (UofA) Nikolaus Anderson (UofA) Stuart Biggar (UofA) David J. Moore (UofA) Joost van Haren (UofA) Field Work & Help Cecilia Chavana-Bryant (Oxford U) Mick Eltringham (UK) Kleber Silva Campos (UFOPA) Marielle Smith (UofA) Ty Taylor (UofA) Scott Stark (MSU) Brad Christofferson (Uof Edinburgh) Rodrigo da Silva (UFOPA) Raimundo Cosme Oliveiera (UFOPA) Steve Bissell (US) Funding Amazon-PIRE NANA Terrestrial Ecology Program Photo Credit: Neill Prohaska