Lidar remote sensing for modeling gross primary production of deciduous forests

Abstract

The influence of foliage vertical distribution on vegetation gross primary production (GPP) is investigated in this study. A new photosynthesis model has been created that combines the standard sunlit/shaded leaf separation (two-leaf) and the multiple layer approaches and uses vertical foliage profiles measured by SLICER (the Scanning Lidar Imager of Canopies by Echo Recovery). Daily gross carbon assimilation rates calculated by this model were compared with the rates calculated by two other models, the two-leaf model and the combined two-leaf multilayer model utilizing uniform foliage profiles. The comparison was made over a wide range of profiles and weather conditions for two mixed deciduous forest stands in eastern Maryland, measured by SLICER in September 1995. Incident radiation pattern, environmental parameters and total amounts of sunlit and shaded leaves were the same for all three models. The difference was in the distributions of radiation and sunlit/shaded leaves inside the canopy. For the combined models, these distributions were calculated based on the vertical foliage profiles, while for the two-leaf model, empirical equations were used to account for the average amounts of absorbed radiation. The simulations showed that: (1) the use of a uniform foliage distribution instead of the actual one results in large differences in the calculated GPP values, up to 46.4% and 50.7% for the days with partial and total cloud cover; (2) the performance of the two-leaf model is extremely sensitive to the absorbed radiation pattern, its disagreement with the proposed model becomes insignificant when the average amounts of absorbed radiation are the same; (3) days with partial cloud cover and a greater fraction of diffuse radiation are characterized by higher GPP rates. These findings highlight the importance of vertical foliage profile and separate treatments of diffuse and direct radiation for photosynthesis modeling.