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Hilker, T; Coops, NC; Hall, FG; Nichol, CJ; Lyapustin, A; Black, TA; Wulder, MA; Leuning, R; Barr, A; Hollinger, DY; Munger, B; Tucker, CJ (2011). Inferring terrestrial photosynthetic light use efficiency of temperate ecosystems from space. JOURNAL OF GEOPHYSICAL RESEARCH-BIOGEOSCIENCES, 116, G03014.

Terrestrial ecosystems absorb about 2.8 Gt C yr(-1), which is estimated to be about a quarter of the carbon emitted from fossil fuel combustion. However, the uncertainties of this sink are large, on the order of +/- 40%, with spatial and temporal variations largely unknown. One of the largest factors contributing to the uncertainty is photosynthesis, the process by which plants absorb carbon from the atmosphere. Currently, photosynthesis, or gross ecosystem productivity (GEP), can only be inferred from flux towers by measuring the exchange of CO(2) in the surrounding air column. Consequently, carbon models suffer from a lack of spatial coverage of accurate GEP observations. Here, we show that photosynthetic light use efficiency (epsilon), hence photosynthesis, can be directly inferred from spaceborne measurements of reflectance. We demonstrate that the differential between reflectance measurements in bands associated with the vegetation xanthophyll cycle and estimates of canopy shading obtained from multiangular satellite observations (using the CHRIS/PROBA sensor) permits us to infer plant photosynthetic efficiency, independently of vegetation type and structure (r(2) = 0.68, compared to flux measurements). This is a significant advance over previous approaches seeking to model global-scale photosynthesis indirectly from a combination of growth limiting factors, most notably pressure deficit and temperature. When combined with modeled global-scale photosynthesis, satellite-inferred epsilon can improve model estimates through data assimilation. We anticipate that our findings will guide the development of new spaceborne approaches to observe vegetation carbon uptake and improve current predictions of global CO(2) budgets and future climate scenarios by providing regularly timed calibration points for modeling plant photosynthesis consistently at a global scale.



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