Quantifying the ecological benefits of lakeshore restoration in northern Wisconsin

Housing development has increased dramatically in the Midwest with a high concentration around lakes. This development plays an important role in the economy of Northwoods communities. However, poorly planned development has the potential to alter a lake’s ecological processes and integrity. Studies have documented the impacts of housing developments and reported dramatic, negative changes to the flora and fauna in Vilas County, Wisconsin. One component of my research included examining the previously unstudied effects of residential development on the abundance and diversity of medium to large-bodied mammals using lakeshore ecosystems. The results suggest that a higher diversity of mammals were detected on low-development lakes. Coyotes were the most numerous species detected with the majority encountered on low-development lakes. White-tailed deer and red fox were more abundant on high-development lakes as compared to low-development lakes. I concluded that high-development lakes are having a negative affect on the mammal community in this area. Recently, lakeshore restoration has occurred on privately owned property in Vilas County and elsewhere in the Northwoods, but little is known about the benefit, if any, from these restoration efforts. A partnership between government agencies and academia has launched a long-term research project investigating the ecological benefits of lakeshore restoration. I investigated the impacts of using down woody material (DWM) to increase the success of restoration projects. Specifically, I tested the hypothesis that down woody material would reduce the variation in soil temperature, retain soil moisture, and improve plant survival and growth rates. I randomly assigned three DWM coverage treatments (0%, 25%, and 50%) on 3 m × 3 m experimental plots (n = 10 per treatment). The mean maximum soil temperature, temperature variation, and change in soil moisture content were significantly lower in the 25% and 50% DWM plots. I found no difference in survival, but snowberry (Symphoricarpos albus) and Barren strawberry (Waldstenia fragaroides) growth was significant greater in the 25% and 50% DWM plots. DWM addition can be considered a useful technique to physically manipulate soil properties and improve plant growth. Finally, I provided baseline data on vegetation structure, bird and small mammal community diversity and abundance for three lakes targeted for restoration efforts and their paired reference lakes. This study is one of the first of it kind in the area and continuing to document the degree of change in subsequent years will provide insight into the way the local ecosystem functions and how ecological communities are structured.

Comparing remote sensing and ground-based methods of quantifying cover type and carbon storage in an urban forest

Understanding the canopy cover of an urban environment leads to better estimates of carbon storage and more informed management decisions by urban foresters. The most commonly used method for assessing urban forest cover type extent is ground surveys, which can be both timeconsuming and expensive. The analysis of aerial photos is an alternative method that is faster, cheaper, and can cover a larger number of sites, but may be less accurate. The objectives of this paper were (1) to compare three methods of cover type assessment for Los Angeles, CA: handdelineation of aerial photos in ArcMap, supervised classification of aerial photos in ERDAS Imagine, and ground-collected data using the Urban Forest Effects (UFORE) model protocol; (2) to determine how well remote sensing methods estimate carbon storage as predicted by the UFORE model; and (3) to explore the influence of tree diameter and tree density on carbon storage estimates. Four major cover types (bare ground, fine vegetation, coarse vegetation, and impervious surfaces) were determined from 348 plots (0.039 ha each) randomly stratified according to land-use. Hand-delineation was better than supervised classification at predicting ground-based measurements of cover type and UFORE model-predicted carbon storage. Most error in supervised classification resulted from shadow, which was interpreted as unknown cover type. Neither tree diameter or tree density per plot significantly affected the relationship between carbon storage and canopy cover. The efficiency of remote sensing rather than in situ data collection allows urban forest managers the ability to quickly assess a city and plan accordingly while also preserving their often-limited budget.