North American Forest Dynamics - Scott Powell, Ph.D.

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Synopsis

The critical role of forests in the global carbon cycle is well known, but significant uncertainties remain about the specific role of disturbance. For example, in North American forests, a growing carbon sink associated with recovery from past disturbances has been well documented, but the uncertainty about the role of forest disturbance in the carbon cycle is the challenge of incorporating spatial and temporal detail in the fate of this sink is highly uncertain in the face of continued forest maturation and increased rates of forest disturbance. A significant element of the characterization of disturbance processes. Two common approaches to characterizing carbon flux at broad spatial and temporal scales are the stock change method and the age structure - carbon accumulation method. The stock change method, so-called because biomass stocks are periodically re-measured at forest inventory plots is currently the cornerstone for large area monitoring and reporting to the United Nations Framework Convention on Climate Change. Periodic re-measurement of biomass stocks yields estimates of net change, meaning that disturbance processes are only implicitly captured, making it difficult to separate mortality from growth. Direct attribution of change to disturbance processes (forest management, land use, fire, insect, etc.) is challenging. Moreover, the stock change method is constrained by the temporal frequency (up to 10 years in the western U.S.) and spatial distribution of plot samples. Thus, periodic short-term pulses of forest disturbance, or changes on marginal forest lands might not be adequately captured, despite their dramatic impacts on the carbon cycle. The age structure - carbon accumulation method relies upon scaled-up inventory-based estimates of forest-age distributions to simulate the growth of biomass across a landscape. In conjunction with a process-based model, the age structure – carbon accumulation method can explicitly partition the separate effects of forest growth and mortality on net carbon balance. However, because the spatial locations of disturbance are not typically known, generalized assumptions about biomass densities are required to estimate the effect of disturbance on biomass stocks. Remote sensing approaches can help to inform when, where, and by what intensity disturbances occur, but a direct linkage to forest inventory data is essential for understanding the impact of disturbance on carbon flux. In this study, we link forest inventory data to remote sensing data to derive estimates of pre- and post-disturbance biomass, and then use biennial remote sensing observations of forest disturbance to characterize biomass loss associated with disturbance. We report on the results of sample-based empirical observation of aboveground biomass loss in forests due to disturbance across the conterminous U.S. between 1986 and 2004. Landsat remote-sensing based estimates of disturbance rates and associated biomass consequences affords a consistent and synoptic assessment of the trends and relative importance of disturbance to the forest carbon sink.

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