Combining isotopic and sap flux data to estimate GPP: an alternative ecophysiological approach to eddy-covariance based data

Stand-scale estimates of gross primary production (GPP) commonly depend on eddy-covariance or eddy-covariance derived models. Chamber-based methods provide an alternative, but they are tricky to scale up to the stand. We estimate GPP by combining isotopic δ¹³C of phloem sugars with sap-flow measurements. The method consists of calculating intrinsic water-use efficiency and transpiration to determine GPP. We have improved this approach by considering mesophyll conductance and seasonal variation in photosynthetic capacity and then compared our results to a semi-empirical eddy-covariance based model, PRELES. We compared a fertilised plot and an unfertilised plot in a monospecific Scots pine forest in northern Sweden. The method captured both the stand response to fertilisation and seasonal patterns, as PRELES did. Our results demonstrate the importance of considering a finite mesophyll conductance value to avoid an unreasonable overestimate of GPP. We have now applied the method in a mixed boreal forest where we will partition total stand GPP among the three dominant tree species (pine, spruce, and birch). This approach provides an independent test of GPP estimates and provides a means of estimating GPP where eddy-covariance assumptions are not met.