Northern Great Lakes forests have become significantly more homogeneous due to Euro-American settlement era land use changes; and in the future will be under increasing stress due to climate change, insects and diseases, development, and other stressors. Land management agencies and conservation organizations have developed landscape scale strategies to restore compositional and structural diversity to help sustain forest ecosystem services such as biodiversity, carbon storage, wood products, and water quality. Adaptive management is a key component of these strategies, requiring knowledge of forest change and the effectiveness of management actions. Using field and remotely sensed data, we monitored changes in forest condition over a 20 year period in the 42,000 ha Manitou Forest landscape in northeastern Minnesota. We used multi-temporal remote sensing data to assess landscape-scale changes in disturbance rates, spatial patterns, cover type, and age structure. With field data, we used a chronosequence approach to assess management effects over time on finer scale characteristics such as tree regeneration, dead wood, and vertical structure. By coupling remotely-sensed and field data, we are better able to assess changes and adapt conservation management strategies.
Results/Conclusions
At the landscape scale, severe disturbance (> 50% canopy removal) rate peaked in the year 2000 at 1.21%/year and then declined to 0.50%/year by 2011. Severe disturbances here are primarily even-age timber harvest. As disturbance rate declined, key landscape structure indicators shifted towards desired future conditions as mean patch size, relative contagion and the proportion of forest in later successional growth stages all increased from year 2000 levels. Finer scale data show that past management along with stressors such as deer herbivory have led to regeneration failure of key species (Pinus strobus, Thuja occidentalis). Results also showed a legacy of simplified structure in young and mature growth stages. Much of the mature forest transitioning into later-successional growth stages lacks the long-lived species and structural characteristics needed to develop late-successional conditions. These landscape monitoring results have led to increased efforts to regenerate key species, improve structural complexity in young and mature forests, and identify and manage high quality mature forest patches.