The Impacts Of Clearcut Harvest And Management Implications On Soil Health Across The Chippewa National Forest

Abstract

Clearcut harvest (CCH) accounts for over 70% of harvesting activities in the state of Minnesota. CCH is known to influence soil nutrient levels, soil physical properties, and long-term ecosystem recovery. We assessed the impacts of CCH on dynamic soil chemical and physical properties across a gradient of parent material, time since harvest, FSDMP class, and soil depth on stands in the Chippewa National Forest in northern Minnesota. The effects of CCH on soil health were generally parent material specific and occurred in the upper soil (0-20 cm), with coarse-textured outwash soils being more susceptible to P losses over time post harvest. Conversely, long-term concerns related to Mg recovery were identified in fine-textured till soils. We found elevated soil bulk density levels that may persist past 15-20 years post harvest in both glacial outwash and glacial till and various changes in soil nutrients across disturbance gradients.Based on the effects of CCH being confined to the upper 0-20 cm we then evaluated if k-means clustering could influence forest management decisions on the Chippewa National Forest by grouping upper soil (0-20 cm) properties that are important for effective timber management into six forest soil health groupings. We evaluated if the k-means clusters explained more variation in eight soil health indicators than what forest managers are currently using, which are landtype associations and soil taxonomy. Landtype associations explained more variation than soil taxonomy and k-means clusters. Soil taxonomy and k-means clusters explained equal variation for the soil health indicators. The study area scale is more local than previous research that has been done to classify upper soil properties using k-means clustering. We compared this study to others that were at a larger scale and found that clustering may improve the identification of local patterns, but at a larger scale, k-means clusters are more informative than soil taxonomy reducing regional complexity. We effectively grouped upper soil properties into six, easy to interpret, forest soil health clusters that can be used to enhance silvicultural prescriptions and aid in reducing detrimental impacts on soil health post harvest.