B23E-0252:
Statistical Estimates of the Long-Term Impact of Land-Use Disturbance on Woody Biomass in the Midwest (USA)

Tuesday, 16 December 2014
Jason S McLachlan1, David J Moore2, Jun Zhu3, Xiaoping Feng3, Christopher J Paciorek4, John W Williams5, Simon J Goring6 and Kyle Alan Hartfield2, (1)University of California Davis, Davis, CA, United States, (2)University of Arizona, Tucson, AZ, United States, (3)University of Wisconsin Madison, Statistics, Madison, WI, United States, (4)University of California, Berkeley, CA, United States, (5)University of Wisconsin, Madison, WI, United States, (6)University of Wisconsin Madison, Madison, WI, United States
Abstract:
The impact on carbon balance of land-use transformations in eastern North America since the time of Euroamerican settlement is important at the global scale. And yet, our understanding of the baseline conditions of pre-settlement vegetation is generally weak. Many estimates of terrestrial carbon pools before Euroamerican settlement are based on hypothetical potential vegetation, and even data-derived estimates of biomass do not have statistical estimates of uncertainty. We fit a spatial statistical model to forest survey (PLS) data from the time of settlement across Midwesterm states from Minnesota to Indiana. Our spatial model scales diameter data from the PLS surveys by standard allometries to produce maps at 8km resolution of biomass with associated uncertainty for all major tree taxa and plant functional types and for total woody biomass. General trends in biomass are consistent with previous estimates, but fine scale heterogeneity is more revealed in our biomass product. A full accounting of uncertainty in settlement-era biomass allows us to assess the extent to which biomass has recovered across a vegetation gradient from subboreal forests to oak savannas and prairies and across land-use histories ranging from preserved old-growth forests through areas reforesting after intensive logging and agriculture to areas currently experiencing a range of intensive human activity.