Mechanisms responsible for lags in the development of photosynthetic capacity of deciduous forests in the spring and their implications for the TG model of gross photosynthesis.

We have recently developed a new Temperature and Greenness (TG) model for estimation of GPP at local to global scales. This model is based entirely on the enhanced vegetation index (EVI) and land surface temperature (LST) from MODIS and consequently outputs are obtained on a per pixel basis. In most cases, the predictions of the TG model have been as good as or better than the more complex MOD17 product from MODIS. However, there are still some areas where the TG model could be improved. For the deciduous forest sites, there is a lag in the development of tower measured GPP relative to modeled GPP. In this study, we examined the causes of this lag so that we can understand how to modify the TG model to better predict it. Specifically, we wished to know to what extent this lag is due to a lag in development of maximum light use efficiency (LUE) as opposed to a lag in development of leaf area? We used data from a wide range of eddy covariance flux towers across North America in combination with MODIS data for the 3 km region around each flux tower. Results suggest that both of these factors are important. In deciduous forest sites, increases in EVI, indicating expansion of leaf area, lag the increase in LST in the spring. But LUE also lags the increase in both EVI and LST, indicating that not only do leaves expand slowly in the spring but that their photosynthetic capacity is initially low. In contrast, evergreen forest sites show LUE values that are more constant during the growing season and have a more linear response to LST when low temperatures limit photosynthetic performance. Potential modifications to the TG model to account for these lags will also be discussed.