PS 21-35
A spatial analysis of biophysical watershed characteristics affecting stream response to land-use changes in Maine, U.S.A.
Maine currently has 28 federally-registered impaired streams that do not attain Maine Department of Environmental Protection (DEP) standards for macroinvertebrate species composition, a measure of ecosystem health, due the urban areas in their watersheds. Percent total impervious area (PTIA) is a surrogate measure of development and is strongly correlated with stream degradation. In Maine watersheds, as PTIA exceeds ~6%, stream species richness decreases abruptly. However, some streams with greater than 6% PTIA continue to attain DEP biotic standards while other streams do not. Here we hypothesize that watershed characteristics such as slope, soil drainage and bedrock geology can either counteract or exaggerate the deleterious effects of development on stream water quality. In this spatial analysis, we compare biophysical characteristics of the 28 watersheds containing urban-impaired streams to 28 separate watersheds characterized by similar amounts of impervious cover but without stream impairment. If we can understand the driving forces behind stream resistance to degradation, we can predict which streams will be more sensitive to future land-use changes and avert future impairment.
Results/Conclusions
In a geographic information system (GIS), eleven spatial variables were examined for all watersheds throughout Maine, including the 28 containing impaired streams. Variables included: mean annual temperature, mean annual precipitation, slope, elevation, percent wetland area, percent forested area, percent impervious area, percent agriculture, percent of area with well-drained soil, percent of area with calcareous bedrock, and the percent of a 50-meter stream buffer that is forested. A random subset of 28 catchments was selected from all the non-impaired watersheds with a mean PTIA greater than 6%. A Multivariate Analysis of Variance (MANOVA) on the remaining ten spatial variables indicated a significant difference between the impaired watersheds and the non-impaired watersheds (p-value <0.001). Paired t-tests indicated that the two watershed groups have significantly different elevation, percent wetlands, percent forest, percent forested buffer, percent agriculture, slope and temperature. These preliminary results suggest that these variables may play a role in controlling stream sensitivity to degradation. The next step in this research will be to create a stakeholder-driven Bayesian Belief Network using these and other spatial variables to predict which watersheds in Maine are at risk of future degradation.