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The field work done at the Wissahickon was aimed at collecting soil biochemical health indicators. The indicator data collected were soil respiration and soil organic matter content. Soil respiration is defined as the production of carbon dioxide as a result of the aerobic or anaerobic decomposition of organic matter by microbes (Das et al., 2014). Soil organic matter is defined as biologically derived plant tissue such as leaf litter and root material. The data were collected at two separate study areas within the park (Figure 1). The first study area at the park is heavily forested with moderate human disturbance. The second is a grass field which has been developed and disrupted by human activity (figure 10).

These two study areas with varying levels of impact, allowed for investigation into the following research questions. First, is soil respiration correlated with soil organic matter? Secondly, will the two sites, with varying levels of impact, show differing biochemical indicator values? The research hypothesis is therefore composed of two parts. First, there will be a significant positive correlation between respiration and organic matter content. Secondly, site 2 (heavily impacted) will show lower levels of both respiration and organic matter content compared to site 1 (moderately impacted). The reason soil respiration and organic matter content have been selected to analyze the soils is for their common use as biochemical indicators of soil health in published soil biochemical research. While researching potential correlations between organic matter pools and respiration rates, the two study area’s soil health, according to these biochemical indicators, can also be assessed.

The main sources of data collection were soil basal respiration—collected using a field respirometer—and organic matter content, collected using laboratory techniques provided by Penn State’s Agricultural Services Laboratory. Regional geologic data, as well as open source regional soils data, have also been included in the research in order to better understand the building blocks of the research site soil. Knowing the geologic building blocks of the soil, as well as the specific soil type being studied, will allow for more detailed observations relating to the biochemical indicators. All of the mentioned data were then used in combination with several software packages including ArcGIS, and Excel. These programs were chosen to represent data and observations both statistically and geospatially.

After statistical analysis was performed, it was concluded that the first hypothesis cannot be confidently accepted. The correlation coefficients (R-values) between the respiration and organic matter values at both sites were less than 0.50, indicating a weak relationship. Site 1 had an R value of -0.26, meaning there was a weak negatively correlated relationship between the organic matter and respiration data. Site 2 had an R value of 0.47, meaning there was a weak positively correlated relationship between the organic matter and respiration data.

On the other hand, the second hypothesis was accepted. The statistical data shows strong differences in mean respiration rates between sites 1 and 2, as well as strong differences in mean organic matter content between sites 1 and 2. Also, site 2 consistently showed much lower levels of both respiration and organic matter in comparison to site 1.



Date Posted: 09 March 2018