Reliability of net ecosystem productivity estimation in an Alaskan boreal forest from satellites

点击翻译按钮获取中文摘要

We focused on a larch forest in eastern Siberia and a spruce forest in Alaska as representative forests that exist on permafrost. Larch and spruce occupies 80% and 70% of the area in eastern Siberia and Alaska, respectively. We estimated net ecosystem productivity (NEP) and forest fire effects on the NEP using sensors onboard earth observation satellites. We evaluated carbon budgets of forests that were not damaged by forest fires, fire severity of Alaskan black forest, and crown and surface fires in eastern Siberia. Based on field spectral observations of mosses and forest component, we built a methodology for estimating forest floor vegetation as well as canopy net primary productivity (NPP) and leaf area index from the remotely sensed data, and we applied to Alaskan spruce and Siberian larch forests. We estimated canopy leaf area index and forest floor vegetation composition. Based on these relationships and field observations, we evaluated the relationship between canopy leaf area index and canopy NPP, forest floor vegetation composition and forest floor NPP, and geographical distribution of NEP. Further, we measured spectral reflectances of forest floor including mosses, lichens, and burnt scars to evaluate effects of burnt scars and vegetation recovery after the fire. In the Alaskan black spruce forest, fractional area of mosses were estimated from the ratio of green and red bands averaged in 50m×50m area using a linear equation (coefficient of determination R^2=0.6). As the many portion of the mosses remained, recovery of spruce will be predominant. As small part of mosses remained, broad leaf trees such as birch will be predominant. The estimated fractional area of remained mosses was the main index for estimating NEP after the fire.