Regional estimation of current and future forest biomass

Abstract

The 90,674 wildland fires that burned 2.9 million ha at an estimated suppression cost of $1.6 billion in the United States during the 2000 fire season demonstrated that forest fuel loading has become a hazard to life, property, and ecosystem health as a result of past fire exclusion policies and practices. The fire regime at any given location in these regions is a result of complex interactions between forest biomass, topography, ignitions, and weather. Forest structure and biomass are important aspects in determining current and future fire regimes. Efforts to quantify live and dead forest biomass at the local to regional scale has been hindered by the uncertainty surrounding the measurement and modeling of forest ecosystem processes and fluxes. The interaction of elevated CO 2 with climate, soil nutrients, and other forest management factors that affect forest growth and fuel loading will play a major role in determining future forest stand growth and the distribution of species across the southern United States. The use of satellite image analysis has been tested for timely and accurate measurement of spatially explicit land use change and is well suited for use in inventory and monitoring of forest carbon. The incorporation of Landsat Thematic Mapper data coupled with a physiologically based productivity model (PnET), soil water holding capacity, and historic and projected climatic data provides an opportunity to enhance field plot based forest inventory and monitoring methodologies. We use periodic forest inventory data from the USDA Forest Service's Forest Inventory and Analysis (FIA) project to obtain estimates of forest area and type to generate estimates of carbon storage for evergreen, deciduous, and mixed forest classes for use in an assessment of remotely sensed forest cover at the regional scale for the southern United States. The displays of net primary productivity (NPP) generated from the PnET model show areas of high and low forest carbon storage potential and their spatial relationship to other landscape features for the southern United States. At the regional scale, predicted annual NPP in 1992 ranged from 836 to 2181 g/m 2 /year for evergreen forests and 769-2634 g/m 2 /year for deciduous forests with a regional mean for all forest land of 1448 g/m 2 /year. Prediction of annual NPP in 2050 ranged from 913 to 2076 g/m 2 /year for evergreen forest types to 1214-2376 g/m 2 /year for deciduous forest types with a regional mean for all forest land of 1659 g/m 2 /year. The changes in forest productivity from 1992 to 2050 are shown to display potential areas of increased or decreased forest biomass. This methodology addresses the need for spatially quantifying forest carbon in the terrestrial biosphere to assess forest productivity and wildland fire fuels. #

Biomass carbon stocks in China’s forests between 2000 and 2050: A prediction based on forest biomass-age relationships

“…However, we do not see a universally accepted approach for predicting future changes in forest biomass C stock [17,18].…”

Climate change effects on northern Great Lake (USA) forests: A case for preserving diversity

“…The effects of CO 2 fertilization, without considering additional limits to growth, will increase the photosynthetic rate of future forests (Mickler et al 2002, Norby et al 2005. Growth enhancement by CO 2 fertilization will be limited by Nitrogen (Kö rner 2006, Hyvö nen et al 2007, Reich and Hobbie 2012, which we did not include as a dynamic process.…”

Estimating potential forest NPP, biomass and their climatic sensitivity in New England using a dynamic ecosystem model

“…Modeling both spatial and temporal variations in forest NPP is important for improving estimates of the terrestrial carbon cycle (Cao et al 2004) and for explaining variation in atmospheric carbon content (Potter et al 1998). Modeling forest biomass is important not only for policy-makers to deal with greenhouse gas mitigation (Morales et al 2007, Zhao and Running 2010 but also for forest managers to determine forest change and wildfire regimes (Mickler et al 2002). Accurate estimates of forest NPP and biomass therefore have implications for (1) analyzing long-term, large-scale changes in carbon stocks over space and time (Houghton 2005); (2) examining the dynamics of forest distribution and composition like the conversion of forested land to cultivated fields; and (3) providing data that are useful for model-based inter-comparison studies on forest carbon and biomass change , Jenkins et al 2001.…”