PARENT SESSION
Oral Session #30: Landscape Ecology: Dynamics and patterns. Presiding: A. Hansen.
Tuesday, August 7, 2001. 1:00 PM to 5:00 PM. Madison Ballroom D.
A spatially explicit model to assess environmental constraints on historic tree distributions across southern Wisconsin.
Bolliger, Janine1, Mladenoff, David1, 1
ABSTRACT- Current goals to restore large-scale landscape patterns and their driving processes stress the need to improve our knowledge of historic landscapes at times before European settlement. To address such issues, historic U.S. General Land Office Surveys have been widely used. Although not collected for ecological purposes, the surveys are statistically representative, and available at large spatial scales. Before settlers arrived, southern Wisconsin (67,589 km2) consisted of a distinct landscape pattern of grasslands, savannas, and woodlands. This landscape pattern is generally agreed to be a result of differing fire regimes. In this paper, we analyze the relative role of fire disturbance versus climatic and soil properties in shaping the historical landscape of southern Wisconsin. Using a tree-species specific, spatially-explicit regression model, the relative governing roles of a variety of statistically independent factors are analyzed: Climatic variables (precipitation, temperature) are derived from high-resolution long-term monthly means; soil properties (texture) are based on the STATSGO data base; indicators for disturbance (fire) rely on tree densities and diameters, filtered with vegetation community information (e.g., low densities in tamarack-dominated areas qualify as swamps rather than fire-prone savannas, whereas low densities of burr-oak qualify as savannas). Since the climatic properties of the study area do not vary to the same extent as disturbance, it is hypothesized that fire - in combination with soils - is the primary driving variable in shaping the historic landscape.
KEY WORDS: u.s. general land office surveys, southern wisconsin, fire disturbance, large-scale ecological model