1. Effects of Stream Restoration: A Comparative Study of Pine Run in Felton, Pennsylvania Luke Mummert, Department of Biological Sciences, York College of Pennsylvania Introduction  In agricultural areas, cattle have a major impact on streams by grazing along stream banks and eating most of the vegetation, increasing erosion and increasing water temperature due to decreased shade levels (Herbst and Kane 2009).  Erosion can increase sediment and nutrient levels in water, decreasing oxygen levels (Selvakumar 2010).  Stream restorations decrease erosion and increase stream water quality (Rosi-Marshall et al. 2006).  Macroinvertebrates are sensitive to changes in water quality, making them good biological indicators for measuring stream health (Herbst and Kane 2009).  Only 10% of streams are being monitored before, during, or after restorations are complete (Morandi et al. 2014).  Pine Run, near Felton, PA, had a stream restoration completed in 2013, with a focus of increasing trout populations. The stream is an important trout stream in Southern York County. The stream was divided into 3 sections for this study, an area upstream of the restoration project with tree cover, a restored section with a riparian buffer planted, and a downstream area with no improvements (Figure 1). Acknowledgements I would like to thank Dr. Jessica Nolan, Dr. Bridgette Hagerty, and the York College Biology Department Faculty for their support and guidance over the course of this project. I would also like to thank Tracy Jones for her assistance in collecting and counting samples over the course of the study and also Scott and Brita Runkle for the use of their property, making the project possible. Objectives  Monitor the impact of the restoration project on Pine Run  Compare biological and physical elements between upstream, restored, and downstream locations  Establish a baseline of physical and biological parameters for any future studies Hypotheses 1) Macroinvertebrate abundance will vary seasonally and be highest during summer months. 2) Upstream and restored sections will have higher macroinvertebrate abundance and diversity than downstream. 3) Downstream section will have higher nutrient and periphyton levels than that of upstream and restored due to cattle grazing. Literature Cited Herbst, David B. and Kane, Jeffrey M. 2009. Responses of aquatic macroinvertebrates to a stream channel reconstruction in a degraded rangeland creek in the Sierra Nevada. Ecological Restoration. 27(1): 76-88. Morandi, B., Piegay, H., Lamouroux, N., and Vaudor, L. 2014. How is success or failure in river restoration project evaluated? Feedback from French restoration projects. Journal of Environmental Management. 137:178-188. Rosi-Marshall, Emma J., Moerke, Ashley H. and Lamberti, Gary A. 2006. Ecological responses to trout habitat restoration in a Northern Michigan stream. Environmental Management. 38(1): 99-107. Selvakumar, Ariamalar, O’Conner, Thomas P., and Struck, Scott D. 2010. Role of stream restoration on improving benthic macroinvertebrates and in-stream water quality in an urban watershed: case study. Journal of Environmental Engineering. 136(1):127-139. A B C http://www.muddycreektu.org/whoweare.html Results Methods  Upstream, restored & downstream areas determined by location of a riffle and a nearby pool  Samples collected once monthly at each site  5 meter kick samples taken from stream bed for macroinvertebrates  Macroinvertebrates identified down to order  Abundance of macroinvertebrates  Diversity calculated using Shannon-Weaver index  Species Richness & Evenness calculated  Water properties tested after collection  Temperature and nitrate levels  Rocks scrubbed for periphyton  Samples tested for chlorophyll fluorescence Methods Pine Run Upstream Restored Downstream Collection of Samples MacroinvertebratesWater PropertiesPeriphyton Abundance Diversity Nitrates Temperature Chlorophyll Richness Evenness Figure 1 : Sampling sites of Pine Run; located in Felton, PA. The upstream sampling section that had minor restorations is labeled “A”, restored section with majority of improvements and riparian buffer planted as “B” and downstream area with no improvements as “C”. Future Studies  Given the interest in trout, use an electroshocking device in order to accurately monitor trout and other fish populations.  Sample annually and over a longer study period in order establish if restoration has been successful.  Increase sample size to quantify variation. Conclusions  Abundance of macroinvertebrates did not vary among locations or months.  Abundance and diversity of macroinvertebrates were not different among sampling areas.  Nitrate and periphyton levels did not differ between locations; although levels differed monthly.  Downstream was consistently warmer and had lower species richness when compared to other sections  Lack of riparian buffer and tree canopy may result in less organic material for macroinvertebrates to feed upon, decreasing richness of species Results Continued Table 1: Three dominant macroinvertebrate orders and total number of species identified during monthly kick samples. Figure 2: Abundance of macroinvertebrates in Pine Run from upstream, restored and downstream locations during trout season, 2015. Abundance of the stream was not significant between sections (F 2, 10 = 3.715. p= 0.0621) or time (F 5, 10 = 2.532, p= 0.0990). Figure 3: Diversity of macroinvertebrates in Pine Run from upstream, restored and downstream locations during trout season, 2015. Diversity was calculated using Shannon- Weaver index and was not significant between locations (F 5, 10 = 9.509, p= 0.4906) or between months (F 5, 10 = 0.9129, p= 0.5102). Figure 4: Richness of macroinvertebrates in Pine Run from upstream, restored, and downstream locations during trout season, 2015. Richness differed between locations (F 2, 10 = 7.175, p= 0.0117) but not between months (F 5, 10 = 1.819, p= 0.1968). Figure 5: Water temperatures in Pine Run from upstream, restored, and downstream locations during trout season, 2015. Temperature was found significant between months (F 2, 10 = 562.1, p<0.0001) and locations (F 2, 10 = 8.428, p= 0.0072)