PS 50-155
Using Landsat sensor data as a management tool for oak woodland and savanna ecosystem restoration

Wednesday, August 7, 2013
Exhibit Hall B, Minneapolis Convention Center
Peter T. Wolter, Natural Resource Ecology and Management, Iowa State University, Ames, IA
Elizabeth A. Berkley, Arapaho National Wildlife Refuge, United States Fish and Wildlife Service, Walden, CO
Scott D. Peckham, Department of Botany, University of Wyoming, Laramie, WY
Aditya Singh, Department of Forest and Wildlife Ecology, University of Wisconsin - Madison, Madison, WI

The structure and function of oak savanna/oak woodland ecosystems in the North American Midwest were originally maintained by an active disturbance regime (often fire).  Subsequent reductions in the frequency of disturbance after European settlement have facilitated rapid conversion of these ecosystems to more closed canopy forest.  Hence, management strategies are now needed to restore critical spatial gradients of light, temperature, soil moisture, and soil organic matter for recovery and sustenance of the unique mosaic of understory grass and forb species assemblages that define oak savannas and woodlands.  Tree species composition, distribution, mortality, basal area (BA), and canopy cover (CC) are important forest structural parameters that are intrinsically linked to oak savanna/woodland restoration ecology in the upper Midwest region of the United States.  In this study we ask whether satellite imagery can be used to accurately predict critical aspects of oak savanna/woodland structure that are needed to guide and monitor restoration and management efforts.  Ground data collected at the Sherburne National Wildlife Refuge in central Minnesota were use with multi-temporal Landsat sensor data and iterative exclusion partial least squares (xPLS) regression to calibrate six predictive overstory structure models. 


Model calibrations produced moderate to high accuracy results with respective adjusted R2 and RMSE values as follows: 0.859, 9.3% (canopy cover); 0.855, 2.95 m2ha-1 (total basal area); 0.741, 11.6 % (red oaks relative basal area); 0.781, 11.9 % (bur oak relative basal area); 0.861, 3.20 m2ha-1 (living oak basal area); and  0.833, 9.1% (dead oak relative basal area).  Structure models were then used to produce spatially explicit maps for the refuge.  We provide theoretical examples of how these Landsat-derived forest structure data can be used to effectively help managers prioritize areas within management zones for restorative treatments.  This Landsat-based method of forest structure estimation is not refuge-specific and may be easily extended as a large-scale assessment tool to improve management, planning, and implementation of oak savanna restoration efforts elsewhere.