1. Lecture 19: Linking in situ IOP with biogeochemistry, case studies (multi-instructor presentation and discussion) Concept of optical proxies

2. Proxies itunes

3. Optical Properties as Proxies Variable interacts with light Volts or Counts IOP or AOP Proxy Variable –> real thing ( = phytoplankton, etc.)

4. “There’s two ways to skin a cat” Variable IOP or AOP What information does the IOP/AOP contain (multiple variables)? a b cb VSF K Rrs How to measure the variable (combination of proxies?) POC Phytoplankton Dead organics Suspended minerals Biogenic minerals (coccoliths) DOC

5. Variable: phytoplankton biomass – pigment (long history: HPPU, CPR, trichromatic equ., fluorescence, HPLC, remote sensing absorption coefficient direct IOP or inversion from AOPs: but –phytoplankton is only part of total a phyt, all pigments a ps photosynthetically competent pigments fluorescence quasi-IOP or AOP (solar fluorescence) caution because of variable  f determine pigment, then what? Convert to carbon? Use for physiology or PP model?

6. Variable: phytoplankton biomass – carbon IOPs:c– phytoplankton is only part b– phytoplankton is only part b b – phytoplankton is only part AOPs:b b – phytoplankton is only part Can b b /b or b b /c ratio help to better resolve if c, b or b b is dominated by organics ?

7. Variable: phytoplankton functional grouping eg: SIZE or TAXON IOP:spectrum beam c – mean particle size VSF – particle size distribution AOP:inversion spectrum b b – mean particle size -dependence of a – pigment packaging –> pico vs. microplankton; key groups

8. Ancillary data to guide interpretation/model/etc. * temperature – algal growth rate, carbon flux, nutrient effects, etc. * salinity – terrestrial CDOM, stratification * winds – mixing, storms * depth – MLD, euphotic depth, water column depth * geographic regime and distance from shore * what else?