Maple-Basswood Restoration Planning

SUMMARY

The purpose of this project was to develop a model to identify and prioritize suitable restoration sites for maple-basswood forest. Using GIS-based datasets including MLCCS, soil, and topography data, we used both statistical analysis and GIS-based spatial analysis to select and prioritize restoration sites.

Big Woods Project Area

INTRODUCTION

The purpose of this project is to develop a model to identify suitable restoration sites for maple-basswood forest within the project area. Maple-basswood forest was once dominant in the Big Woods subsection of Minnesota, but only scattered remnants remain. Much of the maple-basswood forest has been converted to agriculture or development, and it is not readily apparent which sites would be suitable for restoration. The MN DNR and the Big Woods Partnership (a collaboration of local agencies, governments, organizations and individuals) are interested in restoring some of this forest type, and a method to select the best sites was needed.

METHODS

The project area is defined as the area within the Big Woods subsection boundary where Minnesota Land Cover Classification system (MLCCS) mapping has been completed (Figure 1). A total of approximately 150,000 ha of MLCCS-mapped lands were included. The model had three primary components: 1. polygon selection, 2. statistical analysis and application, and 3. prioritization filters.

MLCCS polygon selection

Polygon selection The primary unit for analysis was the polygon, as delineated by the MLCCS. The first step in developing the model was to categorize polygons mapped using the MLCCS into three groups, “unusable, “natural communities” and “restorable”. Polygons were placed in the “unusable” group for several reasons such as the site had a disturbed soil type, high percent of impervious surface, or was mostly water. Polygons mapped as natural areas to the most detailed (fifth) level of the MLCCS were placed in the “Natural Communities” category and used as the maple-basswood forest reference polygons. All remaining polygons not categorized as Unusable or Natural Communities were labeled as “Restorable”.

Topography and shade
Topography and Shade
MLCCS
MLCCS
Soils
Soils

Statistical analysis and application

Statistical analysis was used (linear discriminant function analysis) to determine the relationship between maple-basswood forest and several environmental variables, including soil drainage, slope, aspect and shading.

Prioritization filters

Sites categorized as suitable restorable Polygons were prioritized using the following four filters:

  • Probability of planting success & persistence
  • Strength of statistical prediction
  • Resource (cost) efficiency
  • Patch size & landscape connectivity
Suitable restoration sites priorities

Cooperative project between: Ecological Strategies, LLC, the Minnesota Department of Natural Resources (MN DNR) and Great River Greening (GRG). Funds for this project were provided by MN DNR.