The global distribution of leaf chlorophyll content and seasonal controls on carbon uptake
Abstract
Leaf chlorophyll (ChlLeaf) is crucial to biosphere-atmosphere exchanges of carbon and water, and the functioning of terrestrial ecosystems. Improving the accuracy of modelled photosynthetic carbon uptake is a central priority for understanding ecosystem response to a changing climate. A source of uncertainty within gross primary productivity (GPP) estimates is the failure to explicitly consider seasonal controls on leaf photosynthetic potential. Whilst the inclusion of ChlLeafinto carbon models has shown potential to provide a physiological constraint, progress has been hampered by the absence of a spatially-gridded, global chlorophyll product. Here, we present the first spatially-continuous, global view of terrestrial ChlLeaf, at weekly intervals. Satellite-derived ChlLeaf was modelled using a physically-based radiative transfer modelling approach, with a two stage model inversion method. 4-Scale and SAIL canopy models were first used to model leaf-level reflectance from ENIVSAT MERIS 300m satellite data. The PROSPECT leaf model was then used to derive ChlLeaf from the modelled leaf reflectance. This algorithm was validated using measured ChlLeaf data from 248 measurements within 26 field locations, covering six plant functional types (PFTs). Modelled results show very good relationships with measured data, particularly for deciduous broadleaf forests (R2 = 0.67; p<0.001) and croplands (R2 = 0.42; p<000.1). With all PFTs considered together, the overall validation against measured data was strong (R2 = 0.50; p<0.001). The incorporation of chlorophyll within a light-use efficiency GPP modelling approach and a Terrestrial Biosphere Model demonstrated that neglecting to account for seasonality in leaf physiology resulted in over-estimations in GPP at the start/end of a deciduous growing season, due to a divergence in canopy structure and leaf function. Across nine PFTs, Fluxnet eddy-covariance data was used to validate TBM GPP estimates using ChlLeaf-constrained Vcmax; reducing the seasonal bias and explaining 13%-49% of daily variations in GPP. This work demonstrates the importance of considering leaf pigment status in modelling photosynthetic carbon uptake. We anticipate that the global ChlLeaf product will make an important step towards improving the accuracy of global carbon budgets.
- Publication:
-
AGU Fall Meeting Abstracts
- Pub Date:
- December 2017
- Bibcode:
- 2017AGUFM.B24C..05C
- Keywords:
-
- 0439 Ecosystems;
- structure and dynamics;
- BIOGEOSCIENCES;
- 0480 Remote sensing;
- BIOGEOSCIENCES;
- 1622 Earth system modeling;
- GLOBAL CHANGE;
- 1640 Remote sensing;
- GLOBAL CHANGE