BIOLOGICAL FIELD STATION Cooperstown, New York

47th ANNUAL REPORT 2014 * Otsego Lake Dissolved Oxygen Concentrations 1988 1995

2005 2014

*See inside cover for figure explanation.

STATE UNIVERSITY OF NEW YORK COLLEGE AT ONEONTA

OCCASIONAL PAPERS PUBLISHED BY THE BIOLOGICAL FIELD STATION

No. 1. The diet and feeding habits of the terrestrial stage of the common newt, Notophthalmus viridescens (Raf.). M.C. MacNamara, April 1976 No. 2. The relationship of age, growth and food habits to the relative success of the whitefish (Coregonus clupeaformis) and the cisco (C. artedi) in Otsego Lake, New York. A.J. Newell, April 1976. No. 3. A basic limnology of Otsego Lake (Summary of research 1968-75). W. N. Harman and L. P. Sohacki, June 1976. No. 4. An ecology of the Unionidae of Otsego Lake with special references to the immature stages. G. P. Weir, November 1977. No. 5. A history and description of the Biological Field Station (1966-1977). W. N. Harman, November 1977. No. 6. The distribution and ecology of the aquatic molluscan fauna of the Black River drainage basin in northern New York. D. E Buckley, April 1977. No. 7. The fishes of Otsego Lake. R. C. MacWatters, May 1980. No. 8. The ecology of the aquatic macrophytes of Rat Cove, Otsego Lake, N.Y. F. A Vertucci, W. N. Harman and J. H. Peverly, December 1981. No. 9. Pictorial keys to the aquatic mollusks of the upper Susquehanna. W. N. Harman, April 1982. No. 10. The dragonflies and damselflies (Odonata: Anisoptera and Zygoptera) of Otsego County, New York with illustrated keys to the genera and species. L.S. House III, September 1982. No. 11. Some aspects of predator recognition and anti-predator behavior in the Black-capped chickadee (Parus atricapillus). A. Kevin Gleason, November 1982. No. 12. Mating, aggression, and cement gland development in the crayfish, Cambarus bartoni. Richard E. Thomas, Jr., February 1983. No. 13. The systematics and ecology of Najadicola ingens (Koenike 1896) (Acarina: Hydrachnida) in Otsego Lake, New York. Thomas Simmons, April 1983. No. 14. Hibernating bat populations in eastern New York State. Donald B. Clark, June 1983. No. 15. The fishes of Otsego Lake (2nd edition). R. C MacWatters, July 1983. No. 16. The effect of the internal seiche on zooplankton distribution in Lake Otsego. J. K. Hill, October 1983. No. 17. The potential use of wood as a supplemental energy source for Otsego County, New York: A preliminary examination. Edward M. Mathieu, February 1984. No. 18. Ecological determinants of distribution for several small mammals: A central New York perspective. Daniel Osenni, November 1984. No. 19. A self-guided tour of Goodyear Swamp Sanctuary. W. N. Harman and B. Higgins, February 1986. No. 20. The Chironomidae of Otsego Lake with keys to the immature stages of the subfamilies Tanypodinae and Diamesinae (Diptera). J. P. Fagnani and W. N. Harman, August 1987. No. 21. The aquatic invertebrates of Goodyear Swamp Sanctuary, Otsego Lake, Otsego County, New York. Robert J. Montione, April 1989. No. 22. The lake book: a guide to reducing water pollution at home. Otsego Lake Watershed Planning Report #1. W. N. Harman, March 1990. No. 23. A model land use plan for the Otsego Lake Watershed. Phase II: The chemical limnology and water quality of Otsego Lake, New York. Otsego Lake Watershed Planning Report Nos. 2a, 2b. T. J. Iannuzzi, January 1991. No. 24. The biology, invasion and control of the Zebra Mussel (Dreissena polymorpha) in North America. Otsego Lake Watershed Planning Report No. 3. Leann Maxwell, February 1992. No. 25. Biological Field Station safety and health manuel. W. N. Harman, May 1997. No. 26. Quantitative analysis of periphyton biomass and identification of periphyton in the tributaries of Otsego Lake, NY in relation to selected environmental parameters. S. H. Komorosky, July 1994. No. 27. A limnological and biological survey of Weaver Lake, Herkimer County, New York. C.A. McArthur, August 1995. No. 28. Nested subsets of songbirds in Upstate New York woodlots. D. Dempsey, March 1996. No. 29. Hydrological and nutrient budgets for Otsego lake, N. Y. and relationships between land form/use and export rates of its sub -basins. M. F. Albright, L. P. Sohacki, W. N. Harman, June 1996. No. 30. The State of Otsego Lake 1936-1996. W. N. Harman, L. P. Sohacki, M. F. Albright, January 1997. No. 31. A Self-guided tour of Goodyear Swamp Sanctuary. W. N. Harman and B. Higgins (Revised by J. Lopez),1998. No. 32. Alewives in Otsego Lake N. Y.: A Comparison of their direct and indirect mechanisms of impact on transparency and Chlorophyll a. D. M. Warner, December 1999. No.33. Moe Pond limnology and fish population biology: An ecosystem approach. C. Mead McCoy, C. P. Madenjian, V. J. Adams, W. N. Harman, D. M. Warner, M. F. Albright and L. P. Sohacki, January 2000. No. 34. Trout movements on Delaware River System tail-waters in New York State. Scott D. Stanton, September 2000. No. 35. Geochemistry of surface and subsurface water flow in the Otsego lake basin, Otsego County New York. Andrew R. Fetterman, June 2001. No. 36 A fisheries survey of Peck Lake, Fulton County, New York. Laurie A. Trotta. June 2002. No. 37 Plans for the programmatic use and management of the State University of New York College at Oneonta Biological Field Station upland natural resources, Willard N. Harman. May 2003. No. 38. Biocontrol of Eurasian water-milfoil in central New York State: Myriophyllum spicatum L., its insect herbivores and associated fish. Paul H. Lord. August 2004. No. 39. The benthic macroinvertebrates of Butternut Creek, Otsego County, New York. Michael F. Stensland. June 2005. No. 40. Re-introduction of walleye to Otsego Lake: re-establishing a fishery and subsequent influences of a top Predator. Mark D. Cornwell. September 2005. No. 41. 1. The role of small lake-outlet streams in the dispersal of zebra mussel (Dreissena polymorpha) veligers in the upper Susquehanna River basin in New York. 2. Eaton Brook Reservoir boaters: Habits, zebra mussel awareness, and adult zebra mussel dispersal via boater. Michael S. Gray. No. 42. The behavior of lake trout, Salvelinus namaycush (Walbaum, 1972) in Otsego Lake: A documentation of the strains, movements and the natural reproduction of lake trout under present conditions. Wesley T. Tibbitts. No. 43. The Upper Susquehanna watershed project: A fusion of science and pedagogy. Todd Paternoster. No. 44. Water chestnut (Trapa natans L.) infestation in the Susquehanna River watershed: Population assessment, control, and effects. Willow Eyres. No. 45. The use of radium isotopes and water chemistry to determine patterns of groundwater recharge to Otsego Lake, Otsego County, New York. Elias J. Maskal. No. 46. The state of Panther Lake, 2014 and the management of Panther Lake and its watershed. Derek K. Johnson. 2015. No. 47. The state of Hatch Lake and Bradley Brook Reservoir, 2015 & a plan for the management of Hatch Lake and Bradley Brook Reservoir. Jason E. Luce. 2015. No. 48. Monitoring of Seasonal Algal Succession and Characterization of the Phytoplankton Community: Canadarago Lake, Otsego County, NY & Canadarago Lake Watershed Protection Plan. Carter Lee Bailey. 2015

Annual Reports and Technical Reports published by the Biological Field Station are available at: http://www.oneonta.edu/academics/biofld/publications.asp

Description of Cover Figures: Over the last 25 years marked changes have occurred in the distribution of dissolved oxygen throughout Otsego Lake. Between 1988 and 1995, alewife (Alosa pseudoharengus) became established and a trophic cascade ensued; the decomposition of excessive algae resulted in severe oxygen deficits in the hypolimnion. Between 1995 and 2005, management of watershed nutrient inputs and control of invasive species (primarily alewife) began to reduce oxygen stress in the deep waters. Since 2009, zebra mussel filtration has further contributed to reduced algal biomass settling to the bottom, therefore reducing oxygen consumption. Conditions in 2014 were similar to those documented in 1988. See back cover for instructions on reading these graphs. 47th ANNUAL REPORT 2014

BIOLOGICAL FIELD STATION COOPERSTOWN, NEW YORK bfs.oneonta.edu

STATE UNIVERSITY COLLEGE AT ONEONTA

The information contained herein may not be reproduced without permission of the author(s) or the SUNY Oneonta Biological Field Station

BFS 2014 ANNUAL REPORT CONTENTS

INTRODUCTION: W. N. Harman…………………………………………………………………...….1

ONGOING STUDIES:

OTSEGO LAKE WATERSHED MONITORING: 2014 Otsego Lake water levels. W.N. Harman and M.F. Albright……………………….8 Otsego Lake limnological monitoring, 2014. H.A. Waterfield and M.F. Albright..….…11 A survey of Otsego Lake’s zooplankton community, summer 2014. M.F. Albright and M.J. Best………….……………………………..…….…..23 Chlorophyll a concentrations in Otsego Lake, summer 2014. M. Freehafer………………………………….……...... 34 Water quality monitoring of five major tributaries in the Otsego Lake watershed, summer 2014. C. Hastings ..…………………………………………42 Analysis of fecal coliform bacteria in Otsego Lake’s northern tributaries, summer 2014 . J. Bakhuizen……………………………………………..…….56

SUSQUEHANNA RIVER MONITORING: Monitoring the water quality and fecal coliform bacteria in the upper Susquehanna River, summer 2014. M. Freehafer ……………..……………..64

ARTHROPOD MONITORING: Mosquito studies. W.L. Butts……………….………………………………………...79 Mosquito Survey – Thayer Farm. W.L. Butts…..………………………………….….80

REPORTS:

The abundance of starry stonewort (Nitellopsis obtusa) in Otsego Lake, 2014. M. Genco and R. Russell …………………………………………….……………….81 Summer 2014 trap net monitoring of the fish communities in the weedy littoral zone at Rat Cove and the rocky littoral zone at Brookwood Point, Otsego Lake. M.J. Best……………………..…………………………..…….……….92 Monitoring zebra mussel colonization: PVC and cast iron recruitment. B.P. Coyle, P.H. Lord and W.H. Wong…………………………………...... …………………100 Distribution of Nitellopsis obtusa (starry stonewort) in Canadarago Lake, NY. R. Russell and M. Genco………………………………………………………..……105 2014 aquatic invasive species surveys of New York City water supply reservoirs within the Catskill/Delaware and Croton Watersheds. M. Wilckens, H.A. Waterfield and W.N. Harman…………………………………………….…....114 Potassium permanganates effect on zebra mussel adults and veligers. B.P. Coyle, P.H. Lord, W.H. Wong and M.F. Albright……………..……………………………131 Development of methods to characterize & extract plastic microparticles from personal cleansing products. E. Davidson, C. Hastings, H. A. Waterfield and K. Yokota…...142 Dynamics of Galerucella spp. and purple loosestrife (Lythrum salicaria) in Goodyear Swamp Sanctuary, summer 2014 update. M. Wilckens and H.A. Waterfield..……..149 Wetland delineation of Parslow Road Conservation Area in Oaksville, New York. K. Berdan …………………………………….……………………………………...156 Is lake trout recruitment impacted by zebra mussels in Otsego Lake, NY? D.M. Lucykanish and J.R. Foster……………………………………...…………….164 Continued monitoring of the Moe Pond ecosystem and largemouth bass (Micropterous dolomieuii) populations following its introduction. J. Piacente……………………..171 Status of rainbow smelt (Osmerus mordax) in the Mohican Canyon Tributary, May 2014. M.J. Best………………………………………………………..………..181 Using benthic macro invertebrates to assess stream quality of the Unadilla River, Otsego County, NY. J. Piacente………………………………………………….….187 Summer 2014 bioblitz series. E. Davidson………………………………………………….196 The effects of Earth Tec®, a molluscicide, on zebra mussel (Dreissena polymorpha) Mortality. M. Genco and W.H. Wong…………………………………………….....217 Using pressurized hot water spray to kill and remove dreissenid mussels on watercraft: Field testing on the efficacy of water temperature, high pressure, and duration of exposure. W.H. Wong, S. Gerstenberger and A. Watters……………………...... 227 The temporal succession of invasive species in the Goodyear Swamp Sanctuary. M. Wilckens…………………………………………………….….………………..247 Monitoring the effectiveness of the Cooperstown wastewater treatment wetland, 2014. M.F. Albright……………………………………………………….…….………….253 Aquatic macrophyte management plan facilitation, Lake Moraine, Madison County, NY, 2014. B.P. German and M.F. Albright…………………………………….……266 Control and eradication of water chestnut (Trapa natans, L.) in an Oneonta wetland, 2014 progress report. H.A. Waterfield and M.F. Albright……………..…..………..278 BFS research activities (AY 2014-15). K. Yokota…………………………………….…….280

INTRODUCTION

Willard N. Harman

Interns:

Madeline Genco, a SUNY Oneonta Biology major, received the SUNY Oneonta Biology Department Internship. Working under the direction of David Wong, she investigated effectiveness of Earthtec® as a zebra mussel control agent. She also worked with Rebecca Russell (recipient of the W.N. Harman Internship) on updating distribution maps of starry stonewort on Otsego and Canadarago Lakes. Katherine Berdan of SUNY Geneseo and Emily Davidson of SUNY Oneonta were both sponsored by the Otsego Land Trust. Katherine delineated wetlands on the Land Trust’s Parslow Road Conservation Area and Emily coordinated several “biobliltzes” on Land Trust properties. Cody Hastings of Rochester Institute of Technology was supported by the Otsego County Conservation Association and held the R.J. Thayer Research Assistant. He evaluated water quality across the Otsego Lake watershed to evaluate changes attributable to agricultural Best Management Practices. Under the direction of Kiyoko Yokota and Holly Waterfield, Emily and Cody also worked on methods to characterize & extract plastic microparticles from personal cleansing products using the NSF-funded FlowCam® particle analyzer.

Benjamin Coyle of SUNY Oneonta’s Biology Department held a BFS Internship with Village of Cooperstown support. He did work on the timing of zebra mussel veliger settling in Otsego Lake and compared their rates of colonization on PVC vs. cast iron. He also worked with David Wong on evaluating the effectiveness of potassium permanganate as a zebra mussel control agent. Jennifer Piacente, a SUNY Oneonta Environmental Science and Biology major, held a BFS Internship. She evaluated ecological health of four sites of the Unadilla River by the assessment of the macroinvertebrate communities. She also continued to monitor physical, chemical and biological attributes of Moe Pond as related to the establishment of largemouth bass there. Megan Wilckens of Le Moyne College held a BFS Intern and was supported by a contract from NYSDEP (Contract # CAT-421). Under the guidance of Bill Harman, she surveyed several sites in the New York City watershed for the presence of nuisance exotic species. She also worked at Goodyear Swamp Sanctuary, where she inventoried exotic plants and evaluated the control of purple loosestrife by Galerucella spp. Matthew Best of SUNY Cobleskill’s Fisheries and Aquaculture Department held the R.C. MacWaters Internship. He monitored the littoral fish community of Otsego Lake and evaluated rainbow smelt spawning in a tributary to Otsego Lake. He also worked on surveying the zooplankton community in Otsego Lake. Morgan Freehafer of Emma Willard School and Jenna Bakhuizen of Gilbertsville Mt. Upton Central School both received F.H.V. Mecklenburg Conservation Fellows. With OCCA support, Morgan monitored chlorophyll a concentrations in Otsego Lake and conducted water quality

1 monitoring along the upper Susquehanna River. Jenna, supported by the Village of Cooperstown, monitored fecal coliform bacteria throughout the Otsego Lake watershed.

Faculty and staff activities: Jennifer Vanassche (BFS Intern, 2013), David Wong, Bill Harman and Matt Albright published: Early invasion records of zebra mussel Dreissena polymorpha (Pallas 1771) in Otsego Lake, New York. BioInvasions Records (2014) Volume 3, Issues 3: 159-162. David Wong, working with SUNY Oneonta Biology student A. Waters and collaborator S. Gerstenberger from and UNLV, was funded by USF&W to establish and evaluate protocols for boat/tailor washing to prevent zebra mussel transport (included herein). Bill Harman, Kiyoko Yokota, David Wong and Matt Albright (all NALMS Certified Lake Managers), along with MS students Luke Gervase, Christian Jenne, Daniel Kopec, Edward Kwietniewski, Jenna Leskovec, Kathleen Marean, Sharon O'Neil, Alejandro Reyes and Maxine Verteramo, and 2014 intern Benjamin Coyle, all attended the 34th International NALMS Symposium in Tampa, FL. David presented a talk entitled “Invasive Zebra Mussels in Otsego Lake, New York” and Ben presented a poster entitled “Preventing Zebra Mussel Colonization in Cooperstown Water Treatment Plant, New York: The Appropriate Time and Dose for Application of Potassium Permanganate”. Matt Albright and Holly Waterfield are active on the host committee for NALMS’ 35th Annual Symposium, which will be held in Saratoga Springs, NY in November 2015. Bill Butts, professor emeritus, continues with his mosquito studies. He has provided contributions to every BFS Annual Report to date! Kiyoko Yokota utilized BFS resources throughout the academic year to teach BIOL 685 (Studies in Limnology, Fall 2014) and BIOL 691 (Management of Aquatic Biota, Spring 2015). Five undergraduate students utilized BFS resources to carry out their independent research projects, and two planned to do so but the project did not materialize. Kiyoko was selected to present orally in one of the integrative sessions at the Joint Aquatic Sciences Meeting (of the Society for Freshwater Science, Phycological Society of America, Association for the Sciences of Limnology & Oceanography, and Society of Wetland Scientists). The presentation was co- authored with the LM faculty and four of the first cohort of the LM graduate students. A manuscript is in preparation from a microplastics study carried out with two BFS summer interns, Cody Hastings and Emily Davidson, and Holly Waterfield, utilizing BFS’s Flow- CAM. A related project is in progress, where Edward Kwietniewski serves as a graduate research assistant, funded by the 2014-15 Faculty Research Grant. Kiyoko also has been preparing for a new undergraduate study abroad course to Ogasawara Islands, Japan. Along with it new academic collaboration and student exchange agreements with a Japanese research university, which has a field station on one of the islands, is being negotiated at the institutional level. It is hoped that these agreements will result in academic exchange between the two field stations as well.

2 From 16 June to 1 July 2014, Dr. Jeffrey Heilveil held the first offering of BIOL285: NY Stream Biota: ID and Ecology. The course, attended by 11 undergraduates, was housed at the Thayer Farm and investigated the stream-dwelling organisms both on the BFS properties, and in some of the surrounding rivers. Students learned collecting techniques, life history, and taxonomic identification for everything from diatoms to fishes. Paul Lord offered a one-day workshop on pearly mussel identification, and Dr. Mark Wetzel, formerly of the Illinois Natural History Survey, came and held a two-day workshop on stream Oligocheata. Students also performed independent projects in streams near the BFS, resulting in the collection and identification of some macroinvertebrate genera not previously recorded for Thayer farm. The course was well- received by students and will be offered again in 2016. Les Hasbargen continued his investigations of lake sediment cores taken from Otsego Lake, working on methods to isolate diatoms, charcoal, woody debris and mineral material and to characterize their abundance over time. The goal of the lake coring effort is to characterize climate and environmental change in Otsego Lake over a time spanning the Holocene (roughly the last 12,000 years). The collaboration with Dr. Christoph Geiss, at Trinity College in Hartford, CT, has continued as well. His group has analyzed magnetic properties of a 6 m core taken in 2014 from Otsego Lake. They have dated sections of the core, measured mineralogic properties with x-ray diffraction, and have identified sections of the core where the sedimentation rate was quite low and core material properties change sometime in the mid-Holocene. A new ground (ice) penetrating radar study around the lake cores was conducted in winter 2015 to develop a higher resolution model of the delta in Rat Cove near the BFS main facility.

John Foster and Mark Cornwell of SUNY Cobleskill have continued to use BFS resources for their student involvement and research. They have been utilizing the NFS-funded FlowCam flow cytometer to analyze the stomach contents of planktivorous fish. Efforts continue to evaluate age and growth of walleye in Otsego Lake, recruitment of lake trout and lake whitefish fry, and age and growth of rainbow smelt (numbers of fish and the duration of the spawning run at Mohican Canyon Creek). All those projects are expected to continue through at least 2015. Work was also done to evaluate the effectiveness of Virkon® Aquatic as a disinfectant against adult zebra mussels. They presented a poster utilizing zebra mussels collected from Otsego Lake off the BFS property: Gagnon, Jason N., John R. Foster & Brent C. Lehman. 2015. Virkon® Aquatic is an Ineffective Disinfectant Against Adult Zebra Mussels. Annual Meeting of the New York Chapter of the American Fisheries Society. Lake Placid, NY. 4-6 Feb. They submitted two abstracts for posters to be presented at the Annual Meeting of the American Fisheries Society in August in Portland, Oregon based on work carried out in Otsego Lake using BFS facilities: Is Lake Trout Recruitment Impacted by Zebra Mussels in Otsego Lake, NY? by Casscles, J. Benjamin, David M. Lucykanish, Nicholas M. Sawick & John R. Foster. Walleye Growth in Relation to Alewife Abundance in Otsego Lake, New York by Sanges, Nicholas J, John R. Foster, Grant G Brekke and Mark D. Cornwell.

3 In addition to mentoring research projects on fish parasites, Florian Reyda brought his SUNY Oneonta invertebrate zoology class to Thayer Farm for a field trip last fall. He and approximately 14 students encountered and examined invertebrate animals from a diversity of aquatic and terrestrial habitats during what was an intensive science and camping trip.

Rebecca Russell, a SUNY Oneonta Biology major, served as a BFS intern and worked on two different projects, one on invasive plants, reported in this volume, and another project on digenetic trematodes (flukes) in largemouth bass at Moe Pond. The latter project is ongoing and will ultimately incorporate year-round data on the infection dynamics of a species of trematode genus Crepidostomum that appears to be quite common in bass in Moe Pond, though it has not been encountered in Otsego Lake. Last year, Reyda had a total of twelve SUNY Oneonta undergraduate students conduct research on fish parasites. Their projects are detailed further below. In addition, the Reyda lab was fortunate to host two visitors from Brazil. In January and February, University of Sao Paulo undergraduate student Murillo Rodrigues visited the lab to work with Reyda on the systematics of a genus of tapeworm from South American freshwater stingrays. In fall, Reyda’s collaborator Fernando Marques, a faculty member from the University of Sao Paulo, visited the BFS briefly to finish a study they had started previously to describe a new species of tapeworm from freshwater stingrays from the mouth of the Amazon. The manuscript in which that species was described was recently accepted for publication for the journal Folia Parasitologica. In March, the Reyda lab was visited by an expert of North American freshwater fish parasites, Anindo Choudhury from St. Norbert’s College in Wisconsin. He, Reyda, and student Austin Borden collaborated on the description of a new species of nematode found in Otsego Lake.

Reyda continues to collaborate with students on what has grown into a large-scale survey of the fish parasites of Otsego Lake, an effort that began when he began employment at SUNY Oneonta in August, 2008. At this point, he and students have examined over 500 individual fish of 27 different species, and have encountered 24 species of parasitic worms (i.e., thorny-headed worms, flukes, tapeworms, and nematodes), including one or two species that are new to science (new species!). During the year, each of the twelve students who worked in Reyda’s lab assisted with this survey in some fashion, and eight of those students had research projects that focused on some component of the survey. These students (and their projects) included Austin Borden (new species of nematode), Rebecca Russell & Erica Darpino (the role of snails as hosts of flukes), Illari Delgado & Elsie Dedrick (identification and morphology of tapeworm species from the Lake), Craig Wert & Annie Murphy (flukes of Lake fishes), and Nathan Heller (pathology caused to White suckers by thorny-headed worms). In addition, several projects in Reyda’s lab focused on parasites of stingrays, specimens that he obtained as a result of ongoing collaborations. Rebecca Russell & Kaylee Herzog completed the description of a new species of tapeworm from stingrays from coastal Borneo (Indonesia and Malaysia), and Illari Delgado, Elsie Dedrick, Tara Aprill & Kathryn Forti are in the midst of similar projects in which new species of tapeworms from stingrays are being described. It should be noted that Reyda’s first peer-reviewed publication of a parasite from Otsego Lake, the thorny headed worm Leptorhynchoides thecatus, came out in January of this year, in the journal Comparative Parasitology. The first author of this paper is Michael Bergman (SUNY Oneonta class of 2011), a former research student of the BFS, as well as Jeffrey Heilveil.

4 Graduate studies: As the Master of Science in Lake Management degree program enters its 4th year, it appears it will meet its target number of 15 students soon. The program intensively uses the resources of the Biological Field Station, most courses being taught on site in Cooperstown. Individuals enrolled are developing comprehensive management plans for selected lakes and their watersheds throughout the State. Derek Johnson, Jason Luce and Carter Bailey have received their degrees and are now working for the consulting firms Solitude Lake Management (in Virginia and Delaware) and for Aquadoc in Ohio, respectively. Caitlin Stroosnyder is still working on Goodyear Lake on the Susquehanna River near Oneonta. She holds a position at Delaware Engineering. Owen Zaengle is just finishing up and is working locally. Ben German continues to work on Moraine Lake in Madison County. Dan Kopec is now developing a groundwater based comprehensive management plan for Cazenovia Lake in Madison County. Students beginning in 2014 include Maxine Verteramo, from Ware, Massachusetts. She has been employed by a consulting firm, Water Resources Services, since 2011. She received her undergraduate degree from Hampshire College in Amherst, Mass. She is working on three interconnected private lakes owned by the Emerald Green Corp. in Sullivan County. Four students from SUNY Environmental Science and Forestry, all with backgrounds in fisheries ecology, include: Christian Jenne, who is conducting research on Truesdale Lake in Putnam County, Luke Gervase, who is developing a plan for Millsite Lake (part of the Indian River Lakes Conservancy in Jefferson and St. Lawrence Counties), Edward Kwietniewski, who is studying on Rushford Lake in Allegany County, and Jenna Leskovec, who is conducting research on Windover Lake in Warren County. Kathleen Marean graduated from Cornell University in 2010. She has been employed by the NYS DEC and is also working on an Indian River Lake, Sixberry. Alejandro Reyes did his undergraduate work at SUNY Plattsburg. He has been engaged in several management related activities on Lake Champlain in Colorado and on the west coast. He is developing a plan for Brant Lake, also in Warren County. LA Biology Graduate students Shane Pickering and Eric Davis started their research under David Wong, Eric being the first graduate student supported by external funding (NYS DEC contract) in the history of the Biology Department. Both are involved in research with invasive, exotic zebra mussels. David had to leave Oneonta for personal reasons and now both students are being advised by Bill Harman.

5 Otsego Lake boat census data:

Year 1975 1976 1977 1978 1979 1980 1981 1991 Date 28-Jul 22-Jul 22-Jul 13-Aug 31-Jul Sailboats 224 186 129 101 92 95 230 243 Rowboats 145 236 160 94 86 42 87 285 Canoes 59 52 28 75

Outboards 636 515 436 456 378 197 445 470 Inboards 73 38 22 36 60

Inboard-Outboards 213

Personal Watercraft 61 Misc. cruisers/houseboats 65 41 40 33 24 23 Total 1070 978 765 783 679 408 896 1332

Year 1992 1993 1994 1995 1996 1997 1998 1999 Date 5-Aug 5-Aug 27-Jul 14-Jul 23-Jul 18-Jul 7-Aug 29-Jul Sailboats 220 181 208 208 207 183 236 238 Rowboats and canoes 243 266 311 313 325 312 372 309 Outboards 407 405 461 430 378 371 377 412 Inboards 22 27 16 13 36 13 20 15 Inboard-Outboards 219 215 227 267 260 275 261 265 Personal Watercraft 32 28 29 47 51 62 84 66 Misc. 40 57 49 Total 1158 1145 1285 1315 1272 1226 1351 1317

Year 2000 2001 2002 2005 2007 2008 2009 2010 Date 10-Aug 9-Aug 22-Jul 23-Aug 27-Aug 26-Aug 31-Aug Sailboats 187 190 171 198 192 153 178 162 Rowboats and canoes 349 389 384 450 383 422 407 458 Outboards 381 375 319 380 344 340 349 363 Inboards 23 9 36 21 24 25 30 14 Inboard-Outboards 287 285 216 297 277 280 251 272 Personal Watercraft 19 23 18 15 22 16 17 9 Misc. 53 66 43 51 43 38 48 44 Total 1299 1337 1187 1412 1285 1274 1280 1322

Year 2011 2012 2013 2014 Date 9-Sep 15-Aug 22-Aug 4-Sep Sailboats 118 140 113 121 Rowboats and canoes 450 545 520 551 Outboards 227 334 329 361 Inboards 15 16 31 16 Inboard-Outboards 190 274 247 233** Personal Watercraft 14 22 17 11 * includes 7 jet-boats Misc. 40 40 41 35 ** includes 2 jet-boats Total 1054 1371 1298 1095

6 Public support makes our work possible. Funding for BFS research and educational programs was procured in 2013 from many citizens and organizations. Special thanks go to the Clark and Scriven Foundations who generously support our annual needs. The OCCA, the Peterson Family Charitable Trust, the Village of Cooperstown, the Otsego Lake Association, The Otsego Land Trust, SUNY Oneonta, and the SUNY Graduate Research Initiative have also supported our endeavors. A diversity of Lake Associations, and the New York State Federation of Lake Associations, contribute to the support of students in our Lake Management program.

Willard N. Harman, CLM

7 ONGOING STUDIES:

OTSEGO LAKE WATERSHED MONITORING:

2014 Otsego Lake water levels W.N. Harman and M.F. Albright

Graphs represent Otsego Lake elevation readings at Rat Cove, in centimeters, above or below “0”, which equals the level considered optimal (364.1 m, or 1194.5 ft, above mean sea level).

Ice on (23 Jan)

Ice on (14 Apr)

8

9

10 Otsego Lake limnological monitoring, 2014

Holly A. Waterfield1 and Matthew F. Albright2

INTRODUCTION

Otsego Lake is a glacially formed, dimictic lake (max depth 51m) supporting a cold water fishery. The Lake is generally classified as being chemically mesotrophic, although flora and fauna characteristically associated with oligotrophic lakes are present (Iannuzzi, 1991).

This study is the continuation of a year-round monitoring protocol that began in 1991. The data collected in this report run for the calendar year and are comparable with contributions by Homburger and Buttigieg (1992), Groff et al. (1993), Harman (1994; 1995), Austin et al. (1996), Albright (1997; 1998; 1999; 2000; 2001; 2002; 2003; 2004; 2005; 2006; 2007; 2008), Albright and Waterfield (2009), and Waterfield and Albright (2010; 2011; 2012; 2013; 2014). Concurrent additional work related to Otsego Lake included estimates of fluvial nutrient inputs (Hastings 2015), and descriptions of the zooplankton community (Best and Albright 2015), chlorophyll a (Freehafer 2015), and nekton communities (Best 2014, Waterfield and Wells 2015).

MATERIALS AND METHODS

Physiochemical data and water samples were collected near the deepest part of the lake (TR4-C) (Figure 1), which is considered representative of whole-lake conditions, as past studies have shown the Lake to be spatially homogenous with respect to the factors under study (Iannuzzi 1991). Data and sample collection occurred approximately bi-weekly during open water conditions, 03 February through 03 December 2014. Physical measurements were recorded at 2-m intervals between 0 and 20 m and 40 m to the bottom; 5-meter intervals were used between 20 and 40 m. Measurements of pH, temperature, dissolved oxygen (mg/l and % saturation), specific conductance, Oxidation-Reduction Potential (ORP), and Chlorophylla concentration were recorded with the use of a YSI® 650 MDS with a 6-Series multiparameter sonde which had been calibrated according to the manufacturer’s instructions prior to use (YSI Inc. 2009). Samples were collected for chemical analyses at 4-m intervals between 0 and 20 m and 40m and 48m; 10-m intervals were used between 20 and 40 m. Methodologies employed for sample preservation and chemical analyses are summarized in Table 1. Nutrient and chlorophylla concentrations were determined for all sampling dates; alkalinity, calcium, and chloride concentrations were determined for one profile date per month.

1 CLM. Research Support Specialist: SUNY College at Oneonta Biological Field Station, Cooperstown, NY. 2 CLM. Assistant to the Director: SUNY College at Oneonta Biological Field Station, Cooperstown, NY.

11

TR4-C

Figure 1. Bathymetric map of Otsego Lake showing sampling site (TR4-C).

12 Table 1. Summary of laboratory methodologies.

Parameter Preservation Method of Analysis Reference Persulfate digestion followed by Total Phosphorus H SO to pH < 2 Liao and Marten 2001 2 4 single reagent ascorbic acid Cadmium reduction method following Pritzlaff 2003; Total Nitrogen H SO to pH < 2 2 4 peroxodisulfate digestion Ebina et al. 1983

Nitrate+nitrite-N H2SO4 to pH < 2 Cadmium reduction method Pritzlaff 2003

Ammonia-N H2SO4 to pH < 2 Phenolate method Liao 2001 Calcium Store at 4oC EDTA trimetric method EPA 1983 Chloride Store at 4oC Mercuric nitrate titration APHA 1989 Alkalinity Store at 4oC Titration to pH= 4.6 APHA 1989 Filter Buffered acetone extraction followed Chlorophylla immediately; Welschmyer, 1994 o by flourometric detection store at 0 C

RESULTS AND DISCUSSION

Temperature Figures 2a and 2b depict temperatures measured in profile (0 to 48m) at site TR4-C from 03 February through 2 July and 14 July through 03 December 2014, respectively. Observed surface temperature ranged from a low of 0.68oC on 03 February to 22.6oC on 2 July, at which point the epilimnion extended through 6m depth (Figure 2a). Temperatures just off-bottom (46- 48m) reached the annual minimum of 1.95oC on 03 February, and maximum of 4.56oC on 03 December. Complete ice-cover formed on 24 January; the lake was completely ice-free on 13 April. Spring mixing was underway during the 21 April sampling event and thermal stratification was evident by 21 May. Maximum surface temperature was recorded on 02 July, after which surface temperatures began to decrease and the thermocline occurred at greater depth until fall turnover, which was ongoing as of the 03 December sampling event (Figure 2b).

Dissolved Oxygen Isopleths of dissolved oxygen concentration based on the profiles for the calendar year are presented in Figure 3. On 21 April, prior to the onset of thermal stratification (in May), dissolved oxygen ranged from 11.99 mg/l at bottom to 12.55 mg/l at the surface. The minimum observed DO concentration in 2014 was 4.39 mg/l recorded on 15 October at 46m. In most years between 1995 and 2009, the bottom minimum concentration was near or below 1.0 mg/l. The areal hypolimnetic oxygen depletion rate (AHOD), calculated at 0.050 mg/cm2/day (between 21 May and 15 October), remains well below the historical average for the fifth consecutive year (Table 2).

Alkalinity Alkalinity concentrations followed a typical pattern of seasonal variation, with concentrations decreasing in the epilimnion during the growing season. Mean annual

13 concentration at TR4-C was 123 mg/l, ranging from 71 mg/l at 20m on 21 April to 136 mg/l at 48m on 11 March.

Temperature (oC)

2a. 0 5 10 15 20 25 0 2/3/2014

5 3/11/2014 10 4/21/2014

15 5/7/2014

20 5/21/2014

25 6/3/2014 30 6/18/2014 Depth (meters) Depth 35 7/2/2014 40

45 50

Temperature (oC) 2b. 0.00 5.00 10.00 15.00 20.00 25.00 0 7/14/2014

5 7/29/2014

10 8/14/2014

15 9/3/2014

20 9/17/2014 25 10/2/2014

30 10/15/2014 Depth (meters) Depth 35 10/27/2014

40 11/10/2014 45 12/3/2014

50

Figure 2. Otsego Lake temperature profiles (oC) observed at TR4-C 03 February through 02 July (2a) and 14 July through 3 December (2b) 2014.

14

Figure 3. Distribution of dissolved oxygen (isopleths in mg/L) as recorded in 2014 at site TR4-C on Otsego Lake. Points along the x-axis indicate profile observation dates.

Calcium Calcium concentrations followed a typical pattern of seasonal fluctuation similar to that of alkalinity. Mean annual concentration at TR4-C was 49.9 mg/l, ranging from 42.1 mg/l at the surface on 02 October to 54.5 mg/l at 48m on 03 February and 14 July.

Chlorides Mean chloride concentrations in Otsego Lake from 1925 to 2014 are shown in Figure 4. Between 1994 and 2005 mean concentration increased steadily at of rate of 0.5 to 1.0 mg/l per year (Figure 4). Since then, mean annual concentrations have been variable and have actually trended slightly downwards, likely reflecting flushing of the system that has occurred during major flooding events (2006, 2011, 2013). The mean lake-wide concentration in 2014 was 15.0 mg/l. Chlorides in Otsego Lake have generally been attributed to road salting practices, with the greatest influx of the ion during spring snowmelt events or early-winter snow storms.

Nutrients Total phosphorus averaged 6 µg/l in 2014, ranging from below detection (< 4 µg/l) on multiple dates to 39 µg/l at 20m on 27 October. Concentrations were nearly homogeneous from surface to bottom on many dates during the growing season while higher, more variable, concentrations were observed occasionally ( 21 May, 18 June, 29 July, and 14 August). No phosphorus release from the sediments was observed prior to fall turnover, as dissolved oxygen was present at concentrations sufficient to maintain iron-phosphorus bonds in sediment materials.

15 Nitrite+nitrate-N averaged 0.59 mg/l; ammonia-N was not measured, as it is generally below detectable levels (<0.02 mg/l) when dissolved oxygen exists in the bottom of the hypolimnion. Total nitrogen analyses, yielding a mean of 0.72 mg/l, indicate an average organic nitrogen concentration of about 0.13 mg/l over the year. The concentration of nitrate-N was higher than in recent years, while Total Nitrogen was nearly identical and the organic fraction was slightly lower (Waterfield and Albright 2011, 2012, 2013, and 2014).

Table 2. Areal hypolimnetic oxygen deficits (AHOD) for Otsego Lake, computed over summer stratification in 1969, 1972 (Sohacki, unpubl.), 1988 (Iannuzzi, 1991), and 1992-2014.

Time Interval AHOD (mg/cm2/day) 05/16/69 - 09/27/69 0.080 05/30/72 - 10/14/72 0.076 05/12/88 - 10/06/88 0.042 05/18/92 - 09/29/92 0.091 05/10/93 - 09/27/93 0.096 05/17/94 - 09/20/94 0.096 05/19/95 - 10/10/95 0.102 05/14/96 - 09/17/96 0.090 05/08/97 - 09/25/97 0.101 05/15/98 - 09/17/98 0.095 05/20/99 - 09/27/99 0.095 05/11/00 - 09/14/00 0.109 05/17/01 - 09/13/01 0.092 05/15/02 - 09/26/02 0.087 05/16/03 - 09/18/03 0.087 05/20/04 - 09/24/04 0.102 05/27/05 - 10/05/05 0.085 05/04/06 - 09/26/06 0.084 05/18/07 - 9/27/07 0.083 05/08/08 - 10/7/08 0.088 05/27/09 - 10/19/09 0.082 05/26/10 - 10/7/10 0.053 05/19/11 – 10/12/11 0.060 05/24/12 – 10/05/12 0.056 05/21/13 – 10/15/13 0.061 05/21/14 – 10/15/14 0.050

16 20 18 16

14 12 10 8

Chloride (mg/l) (mg/l) Chloride 6 4 2 0 1920 1940 1960 1980 2000 2020 Year

Figure 4. Mean chloride concentrations at TR4-C, 1925-2014. Points later than 1990 represent yearly averages (figure modified from Peters 1987).

Chlorophyll a and Secchi Disk Transparency Chlorophylla concentrations were determined for samples collected on seven dates from June through September 2014. Average 0-20m composite chlorophyll a concentration was 1.7µg/l (range = 1.1 to 2.4 µg/l). Temporal and spatial distribution of chlorophyll a was studied in June and July is discussed by Freehafer (2015).

Secchi disk transparency measurements, presented in Figure 5, began the ‘growing season’ at a season-maximum of 7.3m, reaching the lowest observation of 5.0m on 18 June. The temporal variation of transparency differed from that observed since 2010; May-September transparency measurements for 2010 through 2014 are presented in Figure 5. Mean summer Secchi transparencies for all years available (1935-2014) are given in Figure 6. Mean transparency was on par with previous years, though individual observations were less variable (range: 5.0 to 7.30), encompassing a smaller range, with a growing season mean of 6.28m.

CONCLUSIONS

As was described in Waterfield and Albright (2014), lake conditions have been variable from year to year as interactions between management efforts and invasive species continue to develop. Trophic cascade has been described, linking recent changes in water quality to the combined effects of zebra mussel (Dreissena polymorpha) establishment (around 2007) and the walleye (Sander vitreus) stocking program that was intended to control the population of alewife (Alosa pseudoharengus) (an invasive forage fish). Region 4 Fisheries Biologists are currently evaluating the lake trout, walleye, and whitefish populations and have adjusted stocking programs accordingly. The sudden decrease in alewife abundance, while a management success, was unexpected and has left the lake trout without an important component of its winter diet.

17 2014 NYS DEC gill net catch indicates decreased fitness of adult lake trout and an absence of juveniles, both of which are impacts of decreased forage fish abundance. Gill net catch also included lake whitefish, a native cold-water species, representing multiple age classes; this catch, together with the presence of many lake whitefish fry in larval fish samples, indicates ongoing recruitment by this once-prominent planktivore.

2010 2011

0 0

2 2 4 4 6 6 8 8 10 10

Depth (meters) Depth 12 (meters) Depth 12 14 14 16 16

2012 2013

0 0

2 2 4 4 6 6 8 8 10 10

12 (meters) Depth 12 Depth (meters) Depth 14 14 16 16

2014

0

2 4 6 8 10 Depth (meters) Depth 12 14 16 Figure 5. May through September Secchi transparencies at TR4C, Otsego Lake, 2010 through 2014.

18 Year

0.0

1.0

2.0

3.0

4.0

5.0

6.0

Secchi Transparency (m) (m) Transparency Secchi 7.0

8.0

Figure 6. Mean summer (May through September) Secchi disk transparency collected at TR4-C, 1935-201.

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19 Albright, M.F. 2003. Otsego Lake limnological monitoring, 2002. In 35th Ann. Rept. (2002). SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta.

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Austin, T., M.F. Albright, and W.N. Harman. 1996. Otsego Lake monitoring, 1995. In 28th Ann. Rept. (1995). SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta.

Best, M.J. 2015. Summer 2014 trap net monitoring of the fish communities in the weedy littoral zone at Rat Cove and the rocky littoral zone at Brookwood Point, Otsego Lake. In 47th Ann. Rept. (2014). SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta.

Ebina, J., T. Tsutsi, and T. Shirai. 1983. Simultaneous determination of total nitrogen and total phosphorus in water using peroxodisulfate oxidation. Water Res. 17(12):1721-1726.

EPA. 1983. Methods for the analysis of water and wastes. Environmental Monitoring and Support Lab. Office of Research and Development. Cincinnati, OH.

Freehafer, M. 2015. Chlorophyll a concentrations in Otsego Lake, summer 2014. In 47th Ann. Rept. (2014). SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta.

Groff, A., J.J. Homburger and W.N. Harman. 1993. Otsego Lake limnological monitoring, 1992. In 24th Ann. Rept. (1991). SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta.

20 Harman, W.N. 1994. Otsego Lake limnological monitoring, 1993. In 26th Ann. Rept. (1993). SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta.

Harman, W.N. 1995. Otsego Lake limnological monitoring, 1994. In 27th Ann. Rept. (1994). SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta.

Hastings, C. 2015. Water quality monitoring of five major tributaries in the Otsego Lake watershed, summer 2014. In 47th Ann. Rept. (2014). SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta.

Homburger, J.J. and G. Buttigieg. 1992. Otsego Lake limnological monitoring. In 24th Ann. Rept. (1991). SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta.

Iannuzzi, T.J. 1991. A model plan for the Otsego Lake watershed. Phase II: The chemical limnology and water quality of Otsego Lake, Occasional Paper #23. SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta.

Leach, J. H. 1993. Impacts of the zebra mussel (Dreissena polymorpha) on water quality and fish spawning reefs in western Lake Erie. In: Zebra Mussels: Biology, Impacts, and Control. Lewis Publishers, Boca Raton, FL p 381-397.

Liao, N. 2001. Determination of ammonia by flow injection analysis. QuikChem ® Method 10- 107-06-1-J. Lachat Instruments, Loveland, CO.

Liao, N. and S. Marten. 2001. Determination of total phosphorus by flow injection analysis colorimetry (acid persulfate digestion method). QuikChem ® Method 10-115-01-1-F. Lachat Instruments, Loveland, CO.

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Pritzlaff, D. 2003. Determination of nitrate/nitrite in surface and wastewaters by flow injection analysis. QuikChem ® Method 10-107-04-1-C. Lachat Instruments, Loveland, CO.

Vanassche, J., W.H. Wong, W.N. Harman, and M.F. Albright. 2014. Zebra mussels and other benthic organisms in Otsego Lake in 2008. In 46th Ann. Rept. (2013) SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta.

Waterfield, H.A., and M.F. Albright. 2010. Otsego Lake limnological monitoring, 2009. In 42nd Ann. Rept. (2009). SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta.

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Waterfield, H.A., and M.F. Albright. 2012. Otsego Lake limnological monitoring, 2011. In 44th Ann. Rept. (2011). SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta.

21 Waterfield, H.A., and M.F. Albright. 2013. Otsego Lake limnological monitoring, 2012. In 45th Ann. Rept. (2012). SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta.

Waterfield, H.A., and M.F. Albright. 2014. Otsego Lake limnological monitoring, 2013. In 46th Ann. Rept. (2013). SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta.

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YSI Incorporated. 2009. 6-Series multiparameter water quality sonde user manual. Yellow Springs, OH.

22 A survey of Otsego Lake’s zooplankton community, summer 2014 M.F. Albright and M.J. Best1

INTRODUCTION (from Tanner and Albright 2014) This is a continuation of a study that has entailed monitoring the zooplankton community that exists in Otsego Lake, in part to evaluate efforts implemented to control alewife (Alosa pseudoharengus) by the addition of walleye (Sander vitreus) as well as influences by the zebra mussel (Dreissena polymorpha). Historically, Otsego Lake has been characterized as oligo-mesotrophic based on various trophic state indicators (Harman et. al 1997). In the 1970s, data collected on Otsego Lake to evaluate algal standing crops were indicative of oligotrophic conditions (water that has low nutrients along with density of algae, but high dissolved oxygen readings) (Godfrey 1977). However, there was evidence of phosphorus loading rates more indicative of a mesotrophic state (where water contains moderate amounts of dissolved nutrients, promoting moderate algal growth and leading to deep-water oxygen declines) (Godfrey 1977). This was attributed to high rates of algal grazing by the crustacean zooplankton community in the lake that had been larger- bodied and more abundant compared to other lakes in New York studied at that time (Godfrey 1977). In 1986, alewife was documented in Otsego Lake (Foster 1990); by 1990 it was the dominant forage fish (Warner 1999). Being efficient grazers, they virtually eliminated the larger bodied crustacean plankton (Warner 1999). The zooplankton community changed from crustacean dominance to rotifers gaining dominance (Foster and Wigens 1990). Rotifers sequester fewer nutrients and have substantially lower algal grazing rates than crustaceans (Warner 1999). Through the 1990s and early 2000s, higher algal standing crops lead to lower transparencies in the summer and the increased rates of hypolimnetic oxygen depletion (Harman et al. 2002). Though there were mitigative efforts set forth to reduce the nutrient inputs in the lake (Albright 2005), the efforts seemed to be overshadowed by the indirect influence of the still- dominant alewife. Walleye (Sander vitreus) have been stocked into Otsego lake since 2000 (Cornwell 2005) at a targeted rate of 80,000 per year (though most years the numbers have been lower; Sanford 2012). The expectation was that predation on alewife might allow for the re-establishment of crustacean zooplankton through trophic cascading, returning oligotrophioc conditions to Otsego Lake (Cornwell 2005). Zebra mussels were first documented in Otsego lake in 2007 (Waterfield 2009) and by 2010, adults had become widespread throughout substrate all over the lake (Albright and Zaengle 2012). This study helps give insight on the zebra mussel reproductive timing through the detection of veligers, even though the composite samples are not suggestive of the entire lakes condition and it is not certain of the affects by the zebra mussel in the zooplankton community.

1 Robert C. MacWaters Internship in the Aquatic Sciences, summer 2014. Present affiliation: Department of Fisheries and Wildlife Technology, SUNY Agriculture and Technical College, Cobleskill, NY.

23 METHODS From 7 May to 17 September 2014, samples were taken biweekly at TR4-C (Figure 1) to evaluate the temporal distribution of the zooplankton community at the deepest location of Otsego Lake. This site historically has been monitored regularly for physical, chemical and biological parameters. At each site, a conical 63 µm plankton net with a 0.2m diameter opening was used for collecting zooplankton. The end of the cup was weighted and the net was lowered to, then hauled up from, 12 m (the approximate depth to the thermocline by late summer). A G.O.™ mechanical flow meter was mounted across the net opening, allowing for calculation of the volume of lake water filtered. The concentrated samples were preserved with ethanol. Samples were analyzed one ml at a time on a gridded Sedgwick Rafter cell. Zooplankton were identified, measured and enumerated using a research grade compound microscope with digital imaging capabilities. Typically, at least 100 organisms were viewed per sample. After each slide was assessed as above, cross polarized light was employed and the cell was viewed again to enumerate zebra mussel veligers as described by Johnson (1995). Mean densities and lengths for cladocerans, copepods and rotifers were used to calculate dry weight (Peters and Downing 1984), daily filtering rate (Knoechel and Holtby 1986) and phosphorus regeneration (Esjmon-Karabin 1983) on each date sampled according to the equations provided in Table 1.

24

Figure 1. Otsego Lake, New York, showing the three sample sites (TR3-C, TR4-C and TR5-C).

Table 1. Equations used to determine zooplankton dry weight (Peters and Downing 1984), filtering rates (Knoechel and Holtby 1986), and phosphorus regeneration rates (Esjmon-Karabin 1983).

Dry weight: D.W. = 9.86*(length in mm)2.1 Filtering Rate: F.R. = 11.695*(length in mm)2.48 Phosphorus regeneration: Cladocerans: P.R. = .519*(dry weight in ug)-.023*e0.039*(temp. in C) Copepods: P.R. = .229*(dry weight in ug)-.645*e0.039*(temp. in C) Rotifers: P.R. = .0514*(dry weight in ug)-1.27*e0.096*(temp. in C)

25 RESULTS AND DISCUSSION Table 2 summarizes the data collected from TR4-C over the summer of 2014, including mean epilimnetic temperature (which influences phosphorus regeneration rates), zooplankton densities, mean lengths and dry weights, dry weights per liter, phosphorus regeneration and filtration rates. Figure 2 provides the calculated dry weights of rotifers, copepods and cladocerans on each date sampled at TR4C over the summer of 2014. Figures 3, 4, 5 and 6 provide comparable data from 2013, 2012, 2011 and 2010, respectively. It is difficult to discern any seasonal pattern over the recent years, though rotifers continue to comprise only a minor part of the community, in contrast to the period during which alewife were dominant (Warner 1999). An exception was encountered on 17 July 2013 when the relatively large-bodied rotifer Asplanchna priodontus was common. Table 3 summarizes the mean crustacean density, mean cladoceran size and mean dry weight, percent of the epilimnion filtered per day and phosphorus regeneration by crustaceans in 2000 and 2002 – 2014 for Samples collected at TR4-C. Over the past several years, the zooplankton community in Otsego Lake has changed substantially. In the 2000s the community of cladocerans was predominantly Bosmina longirostris, a small bodied organism, typically around 0.3mm. When Daphnia were present, their measurements were around 0.6 to 0.7 mm (Harman et al. 2002). In the more recent years, the Daphnia have increased relative to Bosmina, and have increased in mean size of over 1.0 mm, leading to an increase in the mean cladoceran length. Throughout the 2012 season, the cladocerans were comprised of 98 percent of Daphnia sp., averaging 21.5/1 and having a mean length of 1.19 mm (Albright 2012). In 2013, the crustacean community was split equally between Bosmina and Daphnia and averaged 5.5 crustaceans/l and 1.0 mm length. Again in 2014, the cladaceran community was approximately split between Bosmina and Daphnia, with both being at somewhat lower densities. That led to lower mean crustacean dry weight, lower rates of epilimnetic filtering rates and lower phosphorus regeneration rates. Despite lower filtering, chlorophyll a concentrations tended to be low (<2ug/l), transparency high (mean= 6.1 m) and the rate of hypolimnetic oxygen depletion, at 0.050 mg/cm2/day, was the lowest ever recorded for Otsego Lake (Waterfield and Albright 2015).

26 Avg Avg Mean Dry Phos. Regen. Rate Phos. Regen. Filtering % Temp. #/L length Dry Wt (ugP*mgdrywt-1 Rate Rates Epilimnion (°C) (mm) Wt (µg) (µg/L) *ind*h-1) (ug/l/day) (ml/ind/day) filtered/day 5/7 6.14 Cladocera 3.22 0.500 2.68 8.63 0.526 0.109 2.096 0.67 Copepoda 35.09 0.550 3.93 137.90 0.120 0.398 2.655 9.32 Rotifers 1.79 0.170 0.62 1.11 0.120 0.003 0.144 0.03 Total 147.64 0.510 10.02 5/21 10.1 Cladocera 5.13 1.040 11.58 59.41 0.438 0.625 12.890 6.61 Copepoda 27.23 0.540 4.31 117.36 0.132 0.373 2.537 6.91 Rotifers 0.64 0.150 0.19 0.12 0.627 0.002 0.106 0.01 Total 176.89 0.999 13.53 6/3 13.03 Cladocera 4.39 1.210 16.01 70.28 0.456 0.769 18.763 8.24 Copepoda 22.64 0.400 2.47 55.92 0.212 0.285 1.205 2.73 Rotifers 0.68 0.090 0.22 0.15 0.584 0.002 0.030 0.00 Total 126.35 1.056 10.97 6/18 15.08 Cladocera 2.44 1.450 13.36 32.60 0.515 0.403 29.390 7.17 Copepoda 12.91 0.370 1.39 17.94 0.333 0.144 0.993 1.28 Rotifers 2.09 0.120 0.28 0.59 0.466 0.007 0.061 0.01 Total 51.13 0.553 8.47 7/2 17.32 Cladocera 1.47 1.580 29.79 43.79 0.467 0.491 36.364 5.35 Copepoda 5.88 0.330 1.52 8.94 0.343 0.074 0.748 0.44 Rotifers 3.57 0.150 0.23 0.82 0.653 0.013 0.106 0.04 Total 53.55 0.578 5.82 7/14 18.93 Cladocera 1.57 0.960 11.96 18.78 0.614 0.277 10.569 1.66 Copepoda 12.56 0.270 0.85 10.68 0.532 0.136 0.455 0.57 Rotifers 16.22 0.150 0.27 4.38 0.567 0.060 0.106 0.17 Total 33.83 0.472 2.40 Table 2. Summary of site TR4-C of 2014 for mean epilimnetic temperature, zooplankton densities and mean length per taxa, as well as derived values for mean weight per individual and per liter, phosphorus regeneration per individual and per liter, filtering rates per individual and the percent epilimnion filtered per day.

27 Avg Avg Mean Dry Phos. Regen. Rate Phos. Regen. Filtering % Temp. #/L length Dry Wt ugP*mgdrywt-1 Rate Rates Epilimnion (°C) (mm) Wt (µg) (µg/L) *ind*h-1 (ug/l/day) ml/ind/day filtered/day 7/29 18.72 Cladocera 2.79 0.70 7.49 20.90 0.678 0.340 4.829 1.35 Copepoda 2.51 0.51 3.72 9.34 0.204 0.046 2.202 0.55 Rotifers 28.75 0.08 0.05 1.44 4.790 0.165 0.022 0.06 Total 31.67 0.551 1.96 8/14 18.72 Cladocera 8.28 0.610 6.95 57.55 0.690 0.952 3.433 2.84 Copepoda 2.15 0.620 4.88 10.49 0.171 0.043 3.574 0.77 Rotifers 13.50 0.080 0.05 0.68 4.790 0.078 0.022 0.03 Total 68.71 1.073 3.64 9/3 19.09 Cladocera 1.07 1.130 17.56 18.79 0.565 0.255 15.836 1.69 Copepoda 23.62 0.500 3.13 73.93 0.231 0.410 2.096 4.95 Rotifers 2.68 0.200 0.59 1.58 0.212 0.008 0.216 0.06 Total 94.30 0.673 6.70 9/17 17.28 Cladocera 1.44 0.470 2.51 3.61 0.824 0.071 1.798 0.26 Copepoda 22.63 0.460 2.95 66.76 0.224 0.358 1.705 3.86 Rotifers 10.42 0.170 0.29 3.02 0.486 0.035 0.144 0.15 Total 73.39 0.465 4.27

Season mean Cladocera 3.180 0.965 11.989 33.433 0.577 0.429 13.597 3.584 Copepoda 16.722 0.455 2.915 50.926 0.250 0.227 1.817 3.138 Rotifers 8.034 0.136 0.279 1.388 1.330 0.037 0.096 0.056 Total 85.75 0.693 6.78

Table 2. Summary of site TR4-C of 2014 for mean epilimnetic temperature, zooplankton densities and mean length per taxa, as well as derived values for mean weight per individual and per liter, phosphorus regeneration per individual and per liter, filtering rates per individual and the percent epilimnion filtered per day.

28 400 Rotifera 350 Copepoda

300 Cladocera 250 200 150 100 Dry weight (ug/l) 50 0 5/7 5/21 6/3 6/18 7/2 7/14 7/29 8/14 9/3 9/17

Figure 2. Dry weight combined by rotifers, copepods and cladocerans in Otsego Lake over the summer of 2014 at TR4-C.

400 Rotifera 350 Copepoda

300 Cladocera 250 200 150 100 Dry weight (ug/l) 50 0 5/2 5/21 6/5 6/18 7/3 7/17 7/30 8/14 8/27 9/11 9/24

Figure 3. Dry weight combined by rotifers, copepods and cladocerans in Otsego Lake over the summer of 2013 at TR4-C (Tanner and Albright 2014).

400 Rotifera 350 Copepoda

300 Cladocera 250 200 150 100 Dry weight (ug/l) 50 0 5/9 5/24 6/7 6/21 7/4 7/19 8/2 8/16 9/5 9/19

Figure 4. Dry weight combined by rotifers, copepods and cladocerans in Otsego Lake over the summer of 2012 (Albright 2013) at TR4-C.

29 400 Rotifera 350 Copepoda

300 Cladocera 250 200 150 100 Dry weight (ug/l) 50 0 5/19 6/1 6/15 6/28 7/13 7/26 8/8 8/24 9/9 9/27

Figure 5. Dry weight combined by rotifers, copepods and cladocerans in Otsego Lake over the summer of 2011. (Albright and Zaengle 2012) at TR4-C.

400 Rotifera 350 Copepoda

300 Cladocera 250 200 150 100 Dry weight (ug/l) 50 0 5/18 6/4 6/15 7/1 7/15 8/2 8/12 8/26

Figure 6. Dry weight combined by rotifers, copepods and cladocerans in Otsego Lake over the summer of 2010 at TR4-C (Albright and Leonardo 2011).

Table 3. Mean crustacean density, mean cladoceran size and mean dry weight, percent of the epilimnion filtered per day and phosphorus regeneration by crustaceans in 2000 and 2002 – 2014. Samples collected at TR4-C.

'00 '02 '03 '04 '05 '06 '07 '08 '09 '10 '11 '12 '13 '14 Mean cladoceran size (mm) 0.29 0.30 0.36 0.53 0.55 0.55 0.34 0.54 0.69 0.81 0.76 1.19 1.00 0.98 Mean crustacean density (#/l) 208 146 132 163 159 159 154 178 97 56.7 59.4 21.5 28.1 19.9 Mean crustacean dry weight (ug/l) 175 145 177 261 206 206 128 321 142 143 155 122 102 84 Mean % of epilimnion filtered/day 11.9 9.9 12.7 25.1 19.2 19.2 12.2 31.9 9.5 10.8 12.1 11.5 7.7 6.8 Mean phos. regeneration (ug/l/day) 4.49 2.60 3.10 4.40 2.70 2.40 3.00 5.80 1.49 1.90 1.80 1.17 1.02 0.69

30 Figure 7 illustrates the abundance of zebra mussel veligers in the 0-12 m composite samples collected over the summer of 2014 at TR4-C. The density at TR4-C peaked on 30 June at 33 individuals/l. The peak veliger density of other years since 2000, when monitored, was similar (between 19 and 33/l), though the timing of those peaks varied considerable (from 21 June in 2012 to 24 August in 2010). (Data are not available for 2011).

35

30 25 20 15 10

Veliger density (#/liter) 5 0 5/1 5/21 6/10 6/30 7/20 8/9 8/29 9/18

Figure 7. Abundance of zebra mussel veligers in the 0-12 m composite samples collected over the summer of 2014 at TR4-C.

CONCLUSION Through the 1990s, when alewives were dominant, there were very low numbers of larger bodied crustaceans; plankton filtering rates were low, algal standing crops were high, transparencies were low and hypolimnetic oxygen demand was high (Harman et al. 2002). Following the establishment of walleye, alewife were virtually eliminated from the lake (Waterfield and Cornwell 2013; Stowell 2014) and the above trends were reversed. Secchi transparency was high (mean = 5.6m) and oxygen depletion rates were low (AHOD = 0.61 mg/cm2/day) (Waterfield and Albright 2013) and chlorophyll a was low, generally < 2 µg/l (Bianchine and Tanner 2014). While at a lower density than observed in 2012, Daphnia continued to be common and large bodied through the first half of the summer of 2013. Daphnia were present at every sampling date over 2014 at an average length of about 1.0 mm, but had declined in abundance to an average of 2 individuals/l. The character of the lake continued to reflect oligotrophic conditions. The density of zebra mussel veligers at the mid-lake site has not increased since 2010. The influence the mussels on the zooplankton community is not well understood.

31 REFERENCES Albright, M.F. 2005. A report on the evaluation of changes in water quality in a stream following the implementation of agricultural best management practices. In 37th Ann. Rept. (2004). SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta.

Albright, M.F. 2013. A survey of Otsego Lake’s zooplankton community. In 45th Ann. Rept. (2012). SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta.

Albright, M.F. and O. Zaengle. 2012. A survey of Otsego Lake’s zooplankton community, summer 2011. In 44th Ann. Rept. (2011). SUNY Oneonta. Biol. Fld. Sta., SUNY Oneonta.

Albright, M.F. and M. Leonardo. 2011. A survey of Otsego Lake’s zooplankton community, summer 2010. In 43rd Ann. Rept. (2010). SUNY Oneonta. Biol. Fld. Sta., SUNY Oneonta.

Cornwell, M.D. 2005. Re-introduction of walleye to Otsego Lake: Re-establishing a fishery and subsequent influences of a top predator. Occas. Pap. No. 40. SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta.

Esjmont-Karabin, J. 1984. Phosphorus and nitrogen excretion by lake zooplankton (rotifers and crustaceans) in relation to the individual body weights of the animals, ambient temperature, and presence of food. Ekologia Polska 32:3-42.

Foster, J.R. 1990. Introduction of the alewife (Alosa pseudoharengus) in Otsego Lake. In 22nd Ann. Rept. (1989) SUNY Oneonta Bio Fld. Sta., SUNY Oneonta.

Foster, J.R. and J. Wigen.1990. Zooplankton community as an ecological indicator in cold water fish community of Otsego Lake. In 22nd Ann. Rept. (1989). SUNY Oneonta Bio Fld. Sta., SUNY Oneonta.

Godfrey, P.J. 1977. An alalysis of phytoplankton standing crop and growth: Their historical development and trophic impacts. In 9th Ann. Rept. (1976). SUNY Oneonta Bio Fld. Sta., SUNY Oneonta.

Johnson, L.E. 1995. Enhanced early detection and enumeration of zebra mussel (Dreissena sp.) veligers using cross-polarized light microscopy. Hydrobiologia 312:139-147.

Harman, W.N., M.F. Albright and D.M. Warner. 2002. Trophic changes in Otsego Lake, NY following the introduction of the alewife (Alosa pseudohargenous). Lake and Reserv. Manage. 18(3)215-226.

Iannuzzi, T.J. 1991. A model plan for the Otsego Lake watershed. Phase II: The chemical limnology and water quality of Otsego Lake, Occasional Paper #23. SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta.

Knoechel, R. and B. Holtbly.1986 Construction of body length model for the prediction of cladoceran community filtering rates. Limnol. Oceanogr. 31(1):1-16.

32

Peters, R.H. and Downing, J.A. 1984. Empirical analysis of zooplankton filtering and feeding rates. Limnology and Oceanography, 29 (4). pp. 763-784.

Sanford, S. 2012. Pers. Comm. Sanford Bait Farm, Wolcott, NY.

Stowell, S.G. 2014. Trap net monitoring of fish communities within the weedy littoral zone at Rat Cove and rocky littoral zone at Brookwood Point, Otsego Lake. In 45th Ann. Rept. (2012). SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta.

Tanner, C. and M.F. Albright. 2014. A survey of Otsego Lake’s zooplankton community, summer 2014. In 46th Ann. Rept. (2013). SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta.

Warner, D.M. 1999. Alewives in Otsego Lake, NY: a comparison of their direct and indirect mechanisms of impact on transparency and chlorophyll a. Occas. Pap. No.32. SUNY Oneonta Bio Fld. Sta., SUNY Oneonta.

Waterfield, H.A. 2009. Update on zebra mussel (Dreissena polymorpha) invasion and establishment in Otsego Lake, 2008. In 41st Ann. Rept. (2008). SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta.

Waterfield, H.A. and M.F. Albright. 2015. Otsego Lake limnological monitoring, 2014. In 47th Ann. Rept. (2014). SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta.

Waterfield, H.A. and M.F. Albright. 2014. Otsego Lake limnological monitoring, 2013. In 46th Ann. Rept. (2012). SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta.

Waterfield, H.A. and M.F. Albright. 2013. Otsego Lake limnological monitoring, 2012. In 45th Ann. Rept. (2012). SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta.

Waterfield, H.A. and M.D. Cornwell. 2013. Hydroacoustic surveys of Otsego Lake’s pelagic fish community, 2012. In 45th Ann. Rept. (2012). SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta.

33 Chlorophyll a concentrations in Otsego Lake, summer 2014

Morgan Freehafer1

INTRODUCTION

Chlorophyll a concentrations are monitored annually in Otsego Lake in order to estimate algal mass, an important part of evaluating the lake’s trophic status. Chlorophyll a, the light-sensitive pigment that enables photosynthesis, is found in the dominant algae of Otsego Lake (APHA 2012). Chlorophyll a concentrations can therefore be used to estimate the relative algal biomass in Otsego Lake (Harman et. al 2002). Due to Otsego Lake’s meso-oligotrophic characteristics, such as low nutrients and low algal standing crops (Godfrey 1977), chlorophyll a concentrations in Otsego Lake are expected to be relatively low. Various factors affect chlorophyll a concentrations in Otsego Lake; a primary influence in algal growth are within the lake’s food web interactions. In 1986, alewives (Alosa pseudoharengus) were first documented in Otsego Lake (Foster 1990). These planktivorous fish reduced zooplankton population densities, leading to a significant reduction in algal grazing (Harman et al. 2002). Their predation yielded higher algal standing crops, while reducing transparency and concentrations of hypolimnetic dissolved oxygen. Alewives have not been documented in Otsego Lake in recent years, though the historical impact of alewife on algal standing crops remains relevant (i.e., Best 2015). Walleye (Sander vitreus), a popular gamefish, were introduced to Otsego Lake in 2000 (Cornwell 2007) and effectively reduced the alewife population, thereby allowing for the rebound of the zooplankton community (Albright and Best 2015). Zebra mussels (Dreissena polymorpha) are exotic, bi-valve, filter feeders that were first documented in Otsego Lake in 2007 (Waterfield 2009). Widespread by 2010 (Albright and Zaengle 2012), these mussels reduced algal standing crops as a result of their high filtering rate. Both a decrease in chlorophyll a concentrations and a marked increase in water transparency coincided with the introduction of zebra mussels to Otsego Lake (Waterfield and Albright 2013). The purpose of this work is to gain a deeper understanding of concentrations of chlorophyll a throughout the lake. The annual monitoring of chlorophyll a concentrations in Otsego Lake is part of a continued effort to evaluate its trophic parameters related to nutrient concentrations and food web dynamics.

1 F.H.V. Mecklenburg Conservation Fellow, summer 2014. Present affiliation: Emma Willard School. Funding provided by the Otsego County Conservation Association.

34 METHODS

Chlorophyll a samples were collected every other week from Otsego Lake at sites TR3-C, TR4-C, and TR5-C (see Figure 1). Composite samples from surface to 20 meters were taken at all three sites using a weighted garden hose. At site TR4-C, the deepest point in the lake, discrete samples from surface to 20 meters were collected at 1 meter intervals using a Kemmerer Sampler. Samples were stored in 125 mL Nalgene® bottles and kept in a cooler to prevent the chlorophyll a from degrading.

Figure 1. Bathymetric map showing sample collection sites for chlorophyll a analysis in Otsego Lake, summer 2014.

The samples were filtered through a 47mm Whatman® GF/A Glass Micro Fiber filter using a low-pressure vacuum pump. The filters were then folded in half, patted dry to remove excess water, and placed in a petri dish. Samples were stored in a freezer until further processing.

35 Each filter was then cut into small pieces in a 15mL grinding tube with approximately 4mL of buffered acetone (90% acetone, 10% MgCO3). Using a drill with a Teflon pestle drill bit, the filter and solution were ground together and transferred to a 15mL centrifuge tube. More buffered acetone was added to bring each sample to 10mL in volume. After g into centrifuge for 10 minutes at 10,000 X G, the samples were analyzed for chlorophyll a in a Turner Designs™ TD-700 fluorometer. Chlorophyll a concentrations were then ascertained using the methods of Arar and Collins (1997).

RESULTS & DISCUSSION

Figure 2 shows the average chlorophyll a concentrations for site TR4-C from years 2002 to 2014 (excluding 2008 and 2009). Chlorophyll a concentrations for this summer were lower than last year’s concentrations from the surface to 10 meters. From 10 to 20 meters, concentrations of chlorophyll a were higher than last year’s.

Figure 3 illustrates chlorophyll a concentrations throughout the water column from 18 June, 2 July, 14 July, and 29 July 2014 at site TR4-C. Results from composite sampling done on the aforementioned dates at sites TR3-C, TR4-C, and TR5-C can be seen in Figure 4.

36 Average Chlorophyll a Concentrations in Otsego Lake at TR4-C Concentration (ppb) 0 2 4 6 8 10 0

2

4 2002 2003 6 2004 2005 8 2007

2010

10 2006 2011 Depth (m) Depth 2012 12 2013 2014 14

16

18

20

Figure 2. Mean chlorophyll a concentrations per depth at sample site TR4-C from 2002 to 2014, excluding 2008 and 2009. Data were retrieved from 2002 (Wayman 2003), 2003 (Schmitt 2004), 2004 (Murray 2005), 2005 (Zurmuhlen 2006), 2006 (Stevens 2007), 2007 (Ottley 2008), 2010 (Bauer 2011), 2011 (Levenstein 2012), 2012 (Slater 2013), 2013(Bianchine and Tanner 2013) and 2014.

37 2014 Chlorophyll a Concentrations Otsego Lake at TR4-C Concentration (ppb) 0 2 4 6 8 10 0

2

4

6

8 18-Jun-14

2-Jul-14 14-Jul-14 10 Depth (m) 29-Jul-14

12

14

16

18

20

Figure 3. Chlorophyll a concentrations throughout the water column at TR4-C on 18 June, 2 July, 14 July, and 29 July 2014.

38 3

2.5

2

1.5

Concentration (ppb) Concentration 1

0.5

0 TR3-C comp TR4-C comp TR5-C comp

Figure 4. Mean chlorophyll a concentrations in composite samples from sites TR3-C, TR4-C, and TR5-C from 18 June, 2 July, 14 July, and 29 July 2014.

CONCLUSION

Data collected in summer 2014 continue to indicate that Otsego Lake displays characteristics of an oligotrophic lake. Chlorophyll a concentrations from composite samples at all three sites averaged ~2μg/L, a relatively low concentration that is consistent with results from recent years.

REFERENCES

Albright, M.F. and M.J. Best. 2015. A survey of Otsego Lake’s zooplankton community, summer 2014. In 47th Annual Report (2014). SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta.

Albright, M.F. and O. Zaengle. 2012. A survey of Otsego Lake’s zooplankton community, summer 2011. In 44th Annual Report (2011). SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta. APHA, AWWA, WPCF. 1989. Standard methods for the examination of water and wastewater, 17th ed. American Public Health Association. Washington, DC.

39 Arar, E.J. and G.B. Collins.1997. Method 445.0, In Vitro Determination of Chlorophyll a and Pheophytin a in Marine and Freshwater Algae by Fluorescence. In Methods for the Determination of Chemical Substances in Marine and Estuarine Environmental Matrices, 2nd Edition. National Exposure Research Laboratory, Office of Research and Development, USEPA., Cincinnati, Ohio. EPA/600/R- 97/072.

Bauer, H. 2011. Chlorophyll a analysis of Otsego Lake, summer 2010. In 43rd Annual Report (2010). SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta.

Best, M.J. 2015. Summer 2014 trap net monitoring of the fish communities in the weedy littoral zone atRat Cove and the rocky littoral zone at Brookwood Point, Otsego Lake. In 47th Annual Report (2014). SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta.

Bianchine, T. and Tanner, C. 2013. Chlorophyll a concentrations in Otsego Lake, summer 2013. In 46th Annual Report (2013). SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta.

Cornwell, M. 2007. Walleye re-introduction update and characterization of walleye spawners: 2000-2006. In 39th Annual Report (2006). SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta. Foster, J.R. 1990. Introduction of the alewife (Alosa pseudoharengus) in Otsego Lake. In 22nd Annual Report (1989). SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta. Harman, W.N., M.F. Albright, and D.M. Warner. 2002. Trophic changes in Otsego Lake, NY following the introduction of the alewife (Alosa Pseudoharengus). Lake and Reservoir Management. 18(3):215-226. Levenstein, A. 2012. Chlorophyll a concentrations in Otsego Lake, summer 2011. In 44th Annual Report (2011). SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta.

Murray, K. 2005. Chlorophyll a concentrations in Otsego Lake, summer 2004. In 37th Annual Report (2004). SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta.

Ottley, S.G. 2008. Chlorophyll a concentrations in Otsego Lake, summer 2007. In 39th Annual Report (2007). SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta.

Schmitt, R. 2004. Chlorophyll a concentrations in Otsego Lake, summer 2003. In 36th Annual Report (2003). SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta.

Stevens, K. 2007. Chlorophyll a analysis of Otsego Lake, summer 2006. In 39th Annual Report (2006). SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta.

40 Waterfield, H.A. 2009. Update on zebra mussel (Dreissena Polymorpha) invasion and establishment in Otsego Lake, 2008. In 41st Annual Report. (2008). SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta. Waterfield, H.A. and M.F. Albright. 2013.Otsego lake limnological monitoring, summer 2012. In 45th Annual Report (2012). SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta. Wayman, K. 2003. Chlorophyll a concentrations in Otsego Lake, summer 2002. In 35th Annual Report (2002). SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta.

Welschmeyer, N.A. 1994. Fluorometric analysis of chlorophyll a in the presence of chlorophyll b and pheopigments. Limnol. Oceanogr. 39:1985-1992.

Zurmuhlen, S. 2006. Chlorophyll a analysis of Otsego Lake, summer 2005. In 38th Annual Report (2005). SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta.

41 Water quality monitoring of five major tributaries in the Otsego Lake watershed, summer 2014

Cody Hastings1

INTRODUCTION

This study is an extension of a water quality monitoring effort that has been ongoing since 1995. The five tributaries sampled, White Creek, Cripple Creek, Hayden Creek, Shadow Brook, and the Mount Wellington stream provide about seventy percent of the inflow to Otsego Lake (Harman et al. 1980). Approximately forty-four percent of the northern Otsego watershed includes agricultural tracts (Harman et al. 1997). Agricultural runoff from sources such as fertilizers and from livestock waste oftentimes contribute to nutrient loading into lakes. Nutrients such as phosphorus and nitrogen contribute to eutrophication by stimulating algal blooms in lakes, which impacts factors such as ecological stability, recreational appeal, and the quality of the water supply of the village of Cooperstown which depends on Otsego Lake (Wetzel 2001). For this reason, in 1995 the study was formed to introduce and later assess the effectiveness of Best Farm Management Practices (BMPs) such as manure storage, crop nutrient management and pest management which were recommended and partially funded by the US Department of Agriculture (Hewett 1996).

The establishment of exotic fauna in Otsego Lake has led to major key changes in the lake’s ecosystem. For instance, the illegal introduction of alewife (Alosa pseudoharengus) in the mid-1980s (Foster 1989) supported the growth of algae, as alewife very efficiently predate zooplankton which feed on algae (Warner 2000). The over-growth of algae and corresponding decrease in transparency are the same symptoms associated with nutrient pollution (Harman et al. 1997). More recently, the invasive zebra mussel (Dreissena polymporpha) was introduced to the lake, leading to an increase in water transparency due to high rates of water filtration (Waterfield 2014). Due to the introduction of these species and despite the apparent obliteration of alewife (Stowell 2013), the impacts of nutrient loading in Lake Otsego is difficult to quantify. Monitoring, however, gives a good idea of the inflow of nutrients to the lake and is also useful in assessing the effectiveness of BMPs.

METHODS

The data obtained this year were collected in the same fashion as previous years (i.e., Teter 2014). Water samples and the measurements of the physical properties of the water at 23 sites along five major tributaries were taken weekly from 28 May to 28 July 2014.

The five tributaries of Otsego Lake and number of sites sampled in this study are as follows: three sites on White Creek, five sites on Cripple Creek, eight sites on Hayden Creek,

1 Rufus J. Thayer Otsego Lake Research Assistant, summer 2014. Current Affiliation: Rochester Institute of Technology. Funding provided by the Otsego County Conservation Association.

42 five sites on Shadow Brook, and two sites on the Mount Wellington stream for a total of 23 sites. Each of these sites were chosen in 1995 based on factors such as access to the stream, the location relative to agricultural areas, and stream characteristics (Hewett 1996). The sites have been amended over the years in accordance with these factors. Table 1 contains these sites with their coordinates and a description of the site. Figure 1 illustrates each site and its proximity to farms utilizing BMPs.

Physiochemical data were measured in situ at each site using a YSI (6820 V2) Multiparameter probe, which was calibrated to the manufacturer’s specifications before data collection (YSI Inc undated.). Parameters measured included pH, temperature, specific conductivity, oxidation reduction potential-(ORP), dissolved oxygen (DO) concentration (mg/L) and percent saturation, and turbidity (NTU).

Water samples were collected at each site using acid-washed 125-mL bottles and kept on ice until arrival at the lab. Samples were then preserved to <1 pH using sulfuric acid. Samples were analyzed for total nitrogen (TN), nitrate+nitrite content (NO3), and total phosphorus (TP) using a Lachat ® QuikChem FIA+ Water Analyzer. Nitrate+nitrite content and total nitrogen were assessed using the cadmium reduction method (Pritzlaff 2003) and total phosphorus using the ascorbic acid method following persulfate digestion (Liao and Martin 2001).

Table 1. GPS coordinates and physical descriptions of sample locations (modified from Teter 2014).

White Creek 1 (WC1): N 42º 49.612’ W 74º 56.967’ South side of Allen Lake on County Route 26 over a steep bank.

White Creek 2 (WC2): N 42º 48.93’ W 74º 55.29’ Plunge-pool side of stream on County Route 27 (Allen Lake Road) where there is a large dip in the road.

White Creek 3 (WC3): N 42º 48.407’ W 74º 54.178’ West side of large stone culvert under Route 80, just past the turn to Country Route 27.

Cripple Creek 1 (CC1): N 42º 50.878 W 74º 55.584’ Weaver Lake accessed from the north side of Route 20.

Cripple Creek 2 (CC2): N 42º 50.603’ W 74º 54.933’ Young Lake accessed from the west side of Hoke Road. The water at this site is shallow; some distance from shore is required for sampling.

Cripple Creek 3 (CC3): N 42º 49.418’ W 74º 54.007’ North side of culvert on Bartlett Road.

Cripple Creek 4 (CC4): N 42º 48.837’ W 74º 54.032’ Large culvert on west side of Route 80. The stream widens and slows at this point; this is the inlet to Clarke Pond.

Cripple Creek 5 (CC5): N 42º 48.805’ W 74º 53.768’ Dam just south of Clarke Pond accessed from the Otsego Golf Club road. Samples were collected on the downstream side of the bridge.

43 Table 1 (cont.). GPS coordinates and physical descriptions of sample locations (modified from Teter 2014).

Hayden Creek 1 (HC1): N 42º 51.658’ W 74º 51.010’ Summit Lake accessed from the east side of Route 80, north of the Route 20 and Route 80 intersection. Small pull off but researcher must wade in the water to place the probe.

Hayden Creek 2 (HC2): N 42º 51.324’ W 74º 51.294’ Downstream side of culvert on Dominion Road.

Hayden Creek 3 (HC3): N 42º 50.890’ W 74º 51.796’ Culvert on the east side of Route 80 north of the intersection of Route 20 and Route 80.

Hayden Creek 4 (HC4): N 42º 50.267’ W 74º 52.175’ North side of large culvert at the intersection of Route 20 and Route 80.

Hayden Creek 5 (HC5): N 42º 49.996’ W 74º 52.501’ Immediately below the Shipman Pond spillway on Route 80.

Hayden Creek 6 (HC6): N 42º 49.685’ W 74º 52.773’ East side of the culvert on Route 80 in the village of Springfield Center.

Hayden Creek 7 (HC7): N 42º 49.279’ W 74º 53.984’ Large culvert on the south side of County Route 53.

Hayden Creek 8 (HC8): N 42º 48.869’ W 74º 53.291’ Otsego Golf Club, above the white bridge adjacent to the clubhouse. The water here is slow moving and murky.

Shadow Brook 1 (SB1): N 42º 51.831’ W 74º 47.731’ Small culvert on the downstream side off of County Route 30 south of Swamp Road.

Shadow Brook 2(SB2): N 42º 49.891’ W 74º 49.067’ Large culvert on the north side of Route 20, west of County Route 31.

Shadow Brook 3 (SB3): N 42º 48.799’ W 74º 49.839’ Private driveway (Box 2075) off of County Route 31, south of the intersection of Route 20 and Country Route 31 leading to a small wooden bridge on a dairy farm.

Shadow Brook 4 (SB4): N 42º 48.337’ W 74º 50.608’ One lane bridge on Rathbun Road. This site is located on an active dairy farm. The streambed consists of exposed limestone bedrock.

Shadow Brook 5 (SB5): N 42º 47.441’ W 74º 51.506’ North side of large culvert on Mill Road behind Glimmerglass State Park.

Mount Wellington 1 (MW1): N 42º 48.843’ W 74º 52.608’ Stone bridge on Public Landing Road adjacent to an active dairy farm.

Mount Wellington 2 (MW2): N 42º 48.77’ W 74º 53.004’ Small stone bridge is accessible from a private road off Public Landing Road; at the end of the private road near a white house there is a mowed path which leads to the bridge. Water here is stagnant and murky. Sampled on the south side of the bridge.

44

Figure 1. Map showing sampling locations of five tributaries in the northern watershed of Otsego Lake, as well as locations of BMPs (asterisks) (Teter 2014).

RESULTS AND DISCUSSION

Temperature

Various aquatic species rely on relatively constant temperatures to survive. Small changes in temperature can displace sensitive species. Conservation buffers, another application of BMPs, can help regulate temperature effecting factors such as light by shading the streams to provide a more constant temperature (Mason 2002). Mean temperature ranges for 2013 were 16.20 °C to 22.38 °C (Teter 2014). Mean temperature ranges for the summer of 2014 were 16.91°C to 23.64°C. Mean temperature values (+/- standard error) of sites in the summer of 2014 are exhibited in Figure 2.

45 Mean Temperature 25.0

23.0

21.0

19.0

17.0 Temperature (C) Temperature 15.0

13.0 0.00 2.00 4.00 6.00 8.00 10.00 12.00 14.00 Distance from Otsego Lake (km) White Creek Cripple Creek Hayden Creek Shadow Brook Mount Wellington Figure 2. Mean Temperatures of sampling sites along stream gradients of five major tributaries in summer 2014. Distance from the lake increases moving left to right on the graph.

pH

pH is the measure of acidity, or concentration of H+ ions on a logarithmic scale from 0-14 (Wetzel 2001). The geology of the lake basin and watershed plays a large role in pH of the water. Limestone, which elevates the pH, is abundant in the watershed (Harman et. al 1997). Other factors that influence pH include atmospheric and biological processes. Mean pH ranged in 2013 were 7.78 at CC1 to 8.33 at HC1 (Teter 2014). Mean pH ranged in the summer of 2014 were 7.71 at CC1 and 8.36 at WC3. Figure 3 illustrates the mean site pH over stream gradients.

8.5 Mean pH

8.3

8.1

pH pH 7.9

7.7

7.5 0.00 2.00 4.00 6.00 8.00 10.00 12.00 14.00 Distance from Otsego Lake (km) White Creek Cripple Creek Hayden Creek Shadow Brook Mount Wellington Figure 3. Mean pH of sampling sites along the stream gradients of five major tributaries in summer 2014. Distance from the lake increases moving from left to right on the graph.

46 Specific Conductivity

Conductivity is the ability of a solution to conduct electricity. Conductivity increases as ion content increases (Wetzel 2001). This is a useful tool to identify pollution in runoff by comparing with baseline conductivity readings (which are also influenced by the underlying geology). Another factor that can affect conductivity includes large precipitation events which may carry pollutants into the streams. The minimum and maximum mean specific conductance values for sites in 2013 were 0.208 ms/cm at WC1 and 0.602 ms/cm at CC3 (Teter 2014). Mean specific conductance values for the summer of 2014 ranged from 0.249 at WC1 to .510 at SB3. Figure 4 shows the mean specific conductivity of sampling sites in 2014.

Mean Conductivity 0.6

0.5

0.4

0.3

0.2

Conductivity (ms/cm) Conductivity 0.1 0.00 2.00 4.00 6.00 8.00 10.00 12.00 14.00 Distance from Otsego Lake (km) White Creek Cripple Creek Hayden Creek Shadow Brook Mount Wellington

Figure 4. Mean specific conductance of sampling sites along the stream gradients of five major tributaries in summer 2014. Distance from the lake increases moving from left to right on the graph.

Dissolved Oxygen

Dissolved oxygen (DO) content is critical to aquatic organisms such as fish. The concentration of DO can be decreased by lack of shade and nutrient loading; both of which BMPs make an effort to ameliorate (Wetzel 2001). The minimum and maximum mean values for sites in 2013 were 6.47 mg/L at CC1 and 10.20 mg/L at HC1 (Teter 2014). The mean DO content of sites during the summer of 2014 ranged from 6.43 mg/L at CC1 to 9.94 mg/L at CC4. Figure 5 displays the mean DO values of sampling sites in 2014.

47 Mean Dissolved Oxygen 12.0 11.0

10.0 9.0 8.0 7.0 6.0

Disolved Oxygen (mg/l) Oxygen Disolved 5.0 4.0 0.00 2.00 4.00 6.00 8.00 10.00 12.00 14.00 Distance from Otsego Lake (km) White Creek Cripple Creek Hayden Creek Shadow Brook Mount Wellington Figure 5. Mean dissolved oxygen content of sampling sites along the stream gradients of five major tributaries in summer 2014. Distance from the lake increases moving from left to right on the graph

Turbidity

Turbidity is defined as a lack of clarity in water due to the suspension of particles (Wetzel 2001). Studies have shown that reproductive success in some fish is severely impaired by suspended solids in freshwater (Burkhead and Jelks 2001). The lowest values recorded were often below the level of detection of the probe The minimum and maximum mean values for sites in 2013 were 1.47 NTUs at WC1 and 49.1 NTUs at SB5 (Teter 2014). The minimum and maximum values of sites in the summer of 2014 were 0.03 NTU’s at HC2 and 34.5 NTU’s at MW2. The highest turbidity value recorded was 200 NTU’s at MW2. Figure 6 illustrates the mean turbidity values of sampling sites in 2014.

48 Mean Turbidity 80 70 60

50 40 30

Turbidity (NTU) Turbidity 20 10 0 0.00 2.00 4.00 6.00 8.00 10.00 12.00 14.00 Distance from Otsego Lake (km) White Creek Cripple Creek Hayden Creek Shadow Brook Mount Wellington

Figure 6. Mean turbidity of sampling sites along the stream gradients of five major tributaries in summer 2014. Distance from the lake increases moving from left to right on the graph

Nitrogen

Nitrogen is one of the primary components in the growth of organisms, particularly plants and algae. High levels of nitrogen can be detected in water which collects runoff from agricultural tracts. A surplus of nitrogen in a system can increase productivity (Wetzel 2001). As plants and algae growth increases due to the overabundance of nitrogen, eutrophication can occur when the plants and algae begin to decay. The minimum and maximum values of total nitrogen content for sites in 2013 were 0.336 mg/L at WC2 and 2.33 mg/L at SB2 (Teter 2014). Figure 7 shows the mean total nitrogen values of sampling sites in 2014. Figure 8 illustrates mean nitrite and nitrate concentrations for sites in the summer of 2014. Figure 9 displays mean nitrite and nitrate concentrations at stream outlets from 1991, 1998-2014. Table 2 shows a comparison of mean nitrate concentrations of each year since 1998, with data from 1991.

49 Mean Nitrite + Nitrate at Stream Outlet 3

2.5

2

1.5

1 Nitrate (mg/L) Nitrate

0.5

0 White Creek Cripple Creek Hayden Creek Shadow Brook Mount Stream Outlets Wellington 1991 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014

Figure 7. Mean nitrate+nitrite at stream outlets of 5 tributaries in the northern watershed of Otsego Lake 1991, 1998-2014.

2.5 Mean Nitrate + Nitrite

2.0

1.5

1.0 (mg/L) 0.5

0.0 0.00 2.00 4.00 6.00 8.00 10.00 12.00 14.00 Nitrate + Nitrite Concentrations Concentrations Nitrite + Nitrate Distance from Otsego Lake (km) White Creek Cripple Creek Hayden Creek Shadow Brook Mount Wellington

Figure 8. Mean nitrite + nitrate of sampling sites along the stream gradients of five major tributaries in summer 2014. Distance from the lake increases moving from left to right on the graph

50

Table 2. Comparison of mean nitrate concentrations (mg/L) 1998-2014. 1991 is also included, but only the values for stream outlets were taken, where available.

Comparison of Mean Nitrate Concentrations (mg/L) 1991, 1998-2014 1991 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 WC1 0.10 0.05 0.11 0.25 0.31 0.29 0.15 0.27 0.01 0.22 0.21 0.06 0.25 0.09 0.25 0.10 0.13 WC2 0.31 0.30 0.12 0.16 0.25 0.24 0.15 0.09 0.04 0.11 0.09 0.12 0.10 0.06 0.19 0.08 0.10 WC3 1.09 0.37 0.41 0.19 0.22 0.33 0.24 0.35 0.31 0.12 0.35 0.24 0.16 0.24 0.13 0.34 0.13 0.17 CC1 0.07 0.07 0.06 0.08 0.12 0.18 0.13 0.04 0.00 0.02 0.01 0.01 0.03 0.01 0.04 0.23 0.00 CC2 0.04 0.02 0.24 0.04 0.16 0.34 0.22 0.20 0.01 0.00 0.00 0.01 0.97 0.01 0.02 0.28 0.02 CC3 1.54 1.19 0.89 1.63 1.20 1.12 1.06 0.60 0.86 0.88 0.97 1.16 1.17 0.97 0.96 1.32 1.24 CC4 1.42 0.97 0.92 1.77 1.07 1.37 1.05 0.56 0.88 0.97 0.77 1.15 1.19 1.01 0.81 1.28 1.16 CC5 0.69 0.99 0.37 0.68 1.41 0.77 0.80 0.77 0.27 0.83 0.39 0.38 0.99 0.81 0.69 0.57 1.18 0.92 HC1 0.82 0.29 0.82 0.68 0.64 0.52 0.26 0.02 0.72 0.07 0.01 0.47 0.33 0.30 0.52 0.90 0.39 HC2 0.72 0.24 0.71 0.66 0.76 0.52 0.24 0.03 0.84 0.06 0.01 0.59 0.34 0.36 0.34 1.04 0.36 HC3 1.35 0.64 0.96 1.62 1.44 1.43 1.11 0.60 1.11 0.51 0.44 0.62 0.86 0.70 0.65 1.45 0.96 HC4 1.34 0.95 1.17 1.73 1.41 1.27 1.11 0.66 1.10 0.55 0.46 0.68 0.88 0.73 0.82 1.39 0.96 HC5 1.36 0.85 1.19 1.87 1.18 1.34 1.39 0.98 1.64 0.59 0.36 0.94 0.89 0.72 0.64 1.41 0.82 HC6 1.45 0.90 1.29 1.87 1.51 1.27 1.51 1.38 1.58 0.69 0.45 1.02 0.95 0.77 0.79 1.51 0.91 HC7 1.45 0.95 1.33 2.00 1.50 1.46 1.31 1.05 2.52 1.22 0.57 1.93 1.00 0.94 0.84 1.57 1.17 HC8 1.11 1.63 1.21 1.48 1.56 2.09 1.62 1.62 1.31 1.69 0.89 0.70 1.62 1.22 1.17 1.09 1.77 1.32 SB1 0.21 0.31 0.66 0.53 0.33 0.34 0.32 0.21 0.25 0.09 0.14 0.16 0.21 0.17 - - 0.96 0.26 SB2 1.86 1.21 1.45 1.40 1.80 1.33 1.39 1.55 0.61 0.98 0.95 1.43 1.34 1.57 1.05 1.79 1.33 SB3 1.56 0.77 1.57 1.37 1.38 1.36 1.19 0.73 0.94 0.57 0.44 1.34 0.65 0.89 0.64 1.69 1.68 SB4 1.39 0.87 1.56 1.55 1.43 1.47 1.02 0.73 0.88 0.63 0.57 1.31 0.77 0.94 0.59 1.72 1.55 SB5 0.90 1.20 0.58 1.27 1.27 1.11 1.05 1.04 0.47 0.87 0.35 0.39 1.22 0.51 0.78 0.52 1.48 1.20 MW1 0.91 1.11 0.78 1.14 2.31 2.46 1.17 0.67 0.70 0.55 0.23 0.79 0.32 0.50 0.90 1.24 2.13 MW2 1.47 0.68 1.10 1.06 1.66 2.70 1.58 1.60 1.18 0.83 0.35 0.89 1.07 1.15 0.63 1.15 1.49 * - - stream flow was too low for sample collection; no nutrient data exists for Site SB1 in 2012

Phosphorus

Phosphorus is the limiting nutrient in Otsego Lake (Harman et. al 1997). Pathways that phosphorus uses to enter streams include through bedrock and soils, decaying organic materials, through septic systems, and perhaps most importantly in the Otsego Lake, through agricultural runoff. In 2013 the minimum and maximum total phosphorus values were 18.5 ug/L and 233.6 ug/L (Teter 2014). Figure 10 illustrates the mean total phosphorus content of sampling sites in 2014. Figure 11 shows mean total phosphorus at stream outlets from 1996-2014. Table 3 shows a comparison of phosphorus concentrations since 2000.

51 250.0 Mean Total Phosphorus

200.0

150.0

100.0

50.0 Total Phosphorus (ug/L Phosphorus (ug/L Total 0.0 0.00 2.00 4.00 6.00 8.00 10.00 12.00 14.00 Distance from Otsego Lake (km) White Creek Cripple Creek Hayden Creek Shadow Brook Mount Wellington

Figure 10. Mean total phosphorus of sampling sites along the stream gradients of five major tributaries in summer 2014. Distance from the lake increases moving from left to right on the graph.

Mean Total Phosphorus at Stream Outlets 250

200

150

100

50 Total Phosphorus (ug/L) Phosphorus (ug/L) Total 0 White Creek Cripple Creek Hayden Creek Shadow Brook Mount Stream Outlets Wellington 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014

Figure 11. Mean total phosphorus concentration (µg/L) at outlets of 5 tributaries in the northern watershed of Otsego Lake 1996-2014.

52

Table 3. Comparison of mean total phosphorus (ug/L) 1998-2014.

Comparison of phosphorus concentrations (µg/L), 2000-2014 Site 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 WC1 31 34 72 25 33 51 17 66 46 33 33 25 22 18 26 WC2 28 33 23 26 39 61 33 37 34 24 25 25 33 29 27 WC3 19 24 12 23 26 36 40 38 19 22 17 21 21 27 30 CC1 45 36 112 30 49 49 33 86 89 38 63 49 62 26 30 CC2 48 23 46 124 144 172 37 36 25 24 25 28 22 22 22 CC3 25 24 10 25 39 37 62 40 22 26 41 30 21 49 27 CC4 28 35 19 22 46 55 40 39 34 27 45 30 37 126 28 CC5 42 45 51 28 46 70 37 58 59 34 41 40 51 45 31 HC1 26 25 60 21 43 33 33 48 43 35 28 53 22 25 21 HC2 20 17 14 13 23 34 57 30 27 18 24 20 52 23 22 HC3 25 28 47 26 34 39 50 35 54 24 31 24 21 27 26 HC4 20 23 17 26 29 41 22 38 27 24 31 24 20 24 31 HC5 28 27 27 22 33 43 46 41 37 22 31 27 41 32 26 HC6 24 24 21 33 28 40 40 49 32 26 26 27 25 31 25 HC7 34 26 19 30 44 54 73 40 42 27 32 28 30 40 31 HC8 32 37 54 31 51 120 89 43 71 30 37 32 62 42 39 SB1 52 39 57 21 27 103 54 28 19 36 30 33 - - 23 25 SB2 56 43 24 31 45 63 50 17 32 34 29 21 27 37 35 SB3 28 36 46 24 37 40 30 35 30 25 35 24 32 36 22 SB4 48 37 27 27 62 62 22 26 39 38 26 22 42 39 77 SB5 39 54 40 34 63 85 38 45 44 37 38 31 45 92 39 MW1 38 45 36 50 83 51 23 54 33 29 45 25 26 40 22 MW2 142 192 99 136 88 214 69 65 38 57 68 46 71 234 55 * - - stream flow was too low for sample collection; no nutrient data exists for Site SB1 in 2012

CONCLUSION

Physical parameters for 2014 were similar to those of 2013. The mean temperatures of sites during 2014 have been slightly higher than those of 2013. This may be because the 2013 season had much more rainfall cooling the streams. This is also reflected in the turbidity and dissolved oxygen data. The 2013 mean turbidity was much higher than that of 2014 and the mean dissolved oxygen content of 2013 significantly higher than that of 2014, likely due to the higher rainfall. On two occasions, the weeks of 11 June and 28 July, rainfall substantially effected the data collection in 2014.

The total nitrogen data collected this year varied slightly from that of 2013. The data from White Creek stayed relatively constant, while the data from Cripple Creek, Hayden Creek, and Shadow Brook showed an overall decrease in total nitrogen. The data from Mount Wellington showed an overall increase of total nitrogen. A possible explanation of this is the washing out of dirt roads that cross over the Mount Wellington stream (Teter 2014).

Notable results included a water sample with 550 ug/L total phosphorus at SB4. An interesting finding was the decrease of dissolved oxygen content at CC1 over the course of the

53 summer. The maximum value of dissolved oxygen was 8.50 mg/L on 15 July and the minimum value was 2.65 mg/L on 22 July. This change may have come about due to the re-introduction of a beaver dam downstream of the sampling site. Many fauna such as crayfish and snails were found dead upstream of the blockage presumably due to the low oxygen content.

Due to the nature of the data collection, values recorded can fluctuate according to many factors such as weather and activities of local fauna. This exemplifies how important continued monitoring is. A monitoring project that is carried out over decades will show better data that accounts for events such as rainfall, therefore continued monitoring of the Lake Otsego watershed is recommended. To bolster this, a renewed benthic survey of the watershed is also recommended. The last benthic survey was performed in 1995 and has not been renewed since. A survey of this type can help better indicate the health of the streams within the watershed. The survey should be renewed every five years to provide a continuous data set to assist in the assessment of the health of the Lake Otsego watershed.

REFERENCES

Burkhead, N. and H.L. Jelks. 2001. Effects of suspended sediment on the reproductive success of the tricolor shiner, a crevice-spawning minnow. Transactions of the American Fisheries Society 130: 959-968.

Foster, J.R. 1989. Introduction of alewife (Alosa pseudoharengus) in Otsego Lake. In 22nd Ann. Rept. (1988). SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta.

Harman, W.N., L.P. Sohacki and P.J. Godfrey. 1980. The Limnology of Otsego Lake (Glimmerglass), Lakes of New York State, Volume III, Academic Press, 111 Fifth Ave. New York NY, 10003.

Harman, W.N., L.P. Sohacki, M.F. Albright and D.L. Rosen. 1997. The State of Otsego Lake, 1936-1996. Occasional Paper #30. SUNY Oneonta Bio. Fld. Sta., SUNY Oneonta.

Hewett, B. 1997. Water quality monitoring and the benthic community in Otsego Lake watershed. In 29th Ann. Rept. (1996). SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta. Liao, N. and Martin, S. Determination of total phosphorus by flow injection analysis colorimetry (acid persulfate digestion method). QuikChem ®Method 10-115-01-1-F. Lachat Instruments. Loveland Colorado.

Lowell, S.T.and W.C.Sullivan. 2006. Environmental benefits of conservation buffers in the United States: Evidence, promise, and open questions. Agriculture, Ecosystems & Environment 112: 249-260.

Mason, C.F. 2002. Biology of freshwater pollution. Prentice Hall, Harlow, England.

Stowell, S.G. 2014. Trap net Monitoring of fish communities within the weedy littoral zone at

54 Rat Cove and rocky littoral zone at Brookwood Point, Otsego Lake. In 46th Ann. Rept. (2013). SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta.

Teter, C. 2014. Water quality monitoring of five major tributaries in the Otsego Lake watershed, summer 2013. In 46th Ann. Rept. (2013). SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta.

Pritzlaff, D. 2003. Determination of nitriate-nitrite in surface and wastewaters by flow injection Analysis. QuikChem ®Method 10-115-01-1-F. Lachat Instruments. Loveland, Colorado.

Warner. D.M. 2000. Alewives in Otsego Lake, NY: A comparison on their direct diet and indirect mechanisms of impact on transparency and chlorophyll a. Occas. Pap. #32. SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta.

Wetzel, R.G. 2001. Limnology, Lake and River Ecosystems, 3rd edition. Academic Press. San Diego, California.

YSI Inc. Undated. 1700 Brannum Lane Yellow Springs, Ohio.

55 Analysis of fecal coliform bacteria in Otsego Lake’s northern tributaries, summer 2014

Jenna Bakhuizen1

INTRODUCTION

Otsego Lake has five main tributaries including White Creek, Cripple Creek, Hayden Creek, Shadow Brook and Mount Wellington. These five tributaries supply about seventy percent of the stream flow into Otsego Lake (Harman and Godfrey 1980). In 1997, the Otsego Lake Watershed Council (OLWC 1998) prepared the Plan for the Management of the Otsego Lake Watershed describing (and presenting solutions to) the problems that were contributing to changes in the character of the lake. The plan was drafted with a long-term vision for the protection of the lake’s ecological stability in order to ensure that water quality, cold water fishery, aesthetic appeal, and recreational safety are maintained for future generations.

Nutrient loading was identified as the biggest threat to the Lake; the plan’s recommendations included various action areas to reduce nutrient runoff from targeted sources, including wastewater treatment (septic) systems, farms, forestry, and storm water runoff. Agricultural land comprises approximately half of the northern portion of the Otsego Lake watershed, and so the farming community was encouraged to use Best Management Practices (BMP’s) to reduce the runoff from farmlands into streams tributary to Otsego Lake Since 1995 more than $1 million have been spent to install BMPs (OLWC 1998). Annual monitoring by the Biological Field Station is conducted to evaluate the success of these projects (i.e. Hastings 2015). In addition to reducing nutrient inputs, it was expected that fecal coliform bacteria contributions from farmlands would be reduced.

Fecal coliforms are a group of bacteria that occur in the digestive tracts of mammals and waterfowl, and thus serve as a good indicator of fecal contamination (APHA 2012). These bacteria themselves are not harmful but could indicate that other pathogenic organisms are likely present. Potential sources of fecal coliform bacteria in the Otsego Lake watershed include wildlife, active farms, and faulty septic systems (USEPA 2012).

Past monitoring of fecal coliform bacteria within the Otsego Lake watershed was conducted in the summers of 1996 (Miller 1997), 1997 (Pasquale 1998) and 2001 (Albright 2002). Results from 2014 may help to identify stream reaches where conservation practices would benefit water quality.

1 F.H.V. Mecklenburg Conservative Fellow, summer 2014. Present affiliation: Gilbertsville Mt. Upton Central School.. Funding provided by the Village of Cooperstown.

56 METHODS

Water samples were collected on 4 dates between 14 July 2014 and 18 August 2014 at 23 sites along White Creek, Cripple Creek, Hayden Creek, Shadow Brook and Mount Wellington (Table 1 and Figure 1). Samples were collected in sterile 500 mL Nalgene bottles and stored in a cooler, on ice, overnight. Samples were analyzed according to the Membrane Filter Technique (APHA 2012) to yield the number of colonies per 100 mL. In short, a volume of sample was filtered through a Millipore membrane (45µm) using a low pressure vacuum assembly. Each sample was analyzed in triplicate at 2 volumes (10 mL and 100 mL) in order to achieve the optimal 20-80 colonies per culture dish. Filters were placed in a dish having a pad with 2.2 mL of media. Filter assemblies were sterilized with 70% ethanol between sample sites. Dishes were incubated in a 44.5 (±0.2) °C water bath in inverted water-tight containers. After 24 hours (±2), blue colonies were counted and results reported as colonies per 100 mL. Cultures dishes were disinfected by freezing for at least24 hrs.

Table 1. GPS coordinates and physical descriptions of sample locations (modified from Hastings, 2015).

White Creek 1 (WC1): N 42º 49.612’ W 74º 56.967’ South side of Allen Lake on County Route 26 over a steep bank.

White Creek 2 (WC2): N 42º 48.93’ W 74º 55.29’ Plunge-pool side of stream on County Route 27 (Allen Lake Road) where there is a large dip in the road.

White Creek 3 (WC3): N 42º 48.407’ W 74º 54.178’ West side of large stone culvert under Route 80, just past the turn to Country Route 27.

Cripple Creek 1 (CC1): N 42º 50.878 W 74º 55.584’ Weaver Lake accessed from the north side of Route 20.

Cripple Creek 2 (CC2): N 42º 50.603’ W 74º 54.933’ Young Lake accessed from the west side of Hoke Road. The water at this site is shallow; Some distance from shore is required for sampling.

Cripple Creek 3 (CC3): N 42º 49.418’ W 74º 54.007’ North side of culvert on Bartlett Road.

Cripple Creek 4 (CC4): N 42º 48.837’ W 74º 54.032’ Large culvert on west side of Route 80. The stream widens and slows at this point; this is the inlet to Clarke Pond.

57 Table 1 (cont.). GPS coordinates and physical descriptions of sample locations (modified from Hastings, 2015).

Cripple Creek 5 (CC5): N 42º 48.805’ W 74º 53.768’ Dam just south of Clarke Pond accessed from the Otsego Golf Club road. Samples were collected on the downstream side of the bridge.

Hayden Creek 1 (HC1): N 42º 51.658’ W 74º 51.010’ Summit Lake accessed from the east side of Route 80, north of the Route 20 and Route 80 intersections. Small pull off but researcher must wade in the water to place the probe.

Hayden Creek 2 (HC2): N 42º 51.324’ W 74º 51.294’ Downstream side of culvert on Dominion Road.

Hayden Creek 3 (HC3): N 42º 50.890’ W 74º 51.796’ Culvert on the east side of Route 80 north of the intersection of Route 20 and Route 80.

Hayden Creek 4 (HC4): N 42º 50.267’ W 74º 52.175’ North side of large culvert at the intersection of Route 20 and Route 80.

Hayden Creek 5 (HC5): N 42º 49.996’ W 74º 52.501’ Immediately below the Shipman Pond spillway on Route 80.

Hayden Creek 6 (HC6): N 42º 49.685’ W 74º 52.773’ East side of the culvert on Route 80 in the village of Springfield Center.

Hayden Creek 7 (HC7): N 42º 49.279’ W 74º 53.984’ Large culvert on the south side of County Route 53.

Hayden Creek 8 (HC8): N 42º 48.869’ W 74º 53.291’ Otsego Golf Club, above the white bridge adjacent to the clubhouse. The water here is slowing moving and murky.

Shadow Brook 1 (SB1): N 42º 51.831’ W 74º 47.731’ Small culvert on the downstream side off of County Route 30 south of Swamp Road.

Shadow Brook 2(SB2): N 42º 49.891’ W 74º 49.067’ Large culvert on the north side of Route 20, west of County Route 31.

Shadow Brook 3 (SB3): N 42º 48.799’ W 74º 49.839’ Private driveway (Box 2075) off of County Route 31, south of the intersection of Route 20 and Country Route 31 leading to a small wooden bridge on a dairy farm.

58 Table 1 (cont.). GPS coordinates and physical descriptions of sample locations (modified from Hastings, 2015).

Shadow Brook 4 (SB4): N 42º 48.337’ W 74º 50.608’ One lane bridge on Rathbun Road. This site is located on an active dairy farm. The streambed consists of exposed limestone bedrock.

Shadow Brook 5 (SB5): N 42º 47.441’ W 74º 51.506’ North side of large culvert on Mill Road behind Glimmerglass State Park.

Mount Wellington 1 (MW1): N 42º 48.843’ W 74º 52.608’ Stone bridge on Public Landing Road adjacent to an active dairy farm.

Mount Wellington 2 (MW2): N 42º 48.77’ W 74º 53.004’ Small stone bridge is accessible from a private road off Public Landing Road; at the end of the private road near a white house there is a mowed path which leads to the bridge. Water here is stagnant and murky. Sampled on the south side of the bridge.

59

Figure 1. All 23 sites along White Creek, Cripple Creek, Hayden Creek, Shadow Brook and Mount Wellington marked with numbers. Asterisks represent the farms using BMP’s.

60 RESULTS AND DISCUSSION Mean fecal coliform counts for all sites along each stream are illustrated in Figure 2. Table 2 displays data for each sample date in addition to site means. The highest average site count was 2782 colonies per 100 mL at Hayden Creek 4 (HC4); this average was inflated by an extremely high count on a single date (Table 2). Average site counts ranged from 25 to 2782 colonies per 100 mL. White Creek average site count ranged between 25 and 177 colonies per 100mL.The range at Cripple Creek was 31 and 164 colonies per 100 mL. Data from Hayden Creek ranged from 46 to 2782 colonies per 100 mL. Shadow Brook ranged from 142 and 424 colonies per 100 mL and Mount Wellington ranged from 440 and 504 colonies per 100 mL.

600 550 500

450 400 350 300 250 200 Colonies per Colonies 100 mL 150 100 50 0 0 2 4 6 8 10 12 14 Distance from Otsego Lake (km) White Creek Cripple Creek Hayden Creek Shadow Brook Mount Wellington Figure 2. Fecal coliform average along each creek. Actual values can be found in Table 2. For graphing purposes, HC4 data point is the median value, as the mean value included a sample that was “too high to count”.

Site WC2 was consistently higher than the other sites throughout the sampling period. The colony count along Cripple Creek was generally consistent between sampling sites, though an elevated count was obtained at CC3 on 22 July 2014. At HC4 the count was consistently higher than the rest and on 22 July 2014 the number was impossible to count (the filter was nearly a “lawn” of colonies). The count for that week was estimated to be near 10,000 colonies per 100 mL. That site was generally the highest every week. Mount Wellington counts increased over time, with an average count greater than any other tributary. This could be attributed to the large farm along a very short, small creek. According to the New York State Department of Environmental Conservation (2008), fresh water used for contact recreation should not contain more than 200 colonies in 100 mL. When fresh water reaches a count over 200 colonies per 100 mL, the possibility is higher that pathogenic bacteria are present (NYS DEC 2008). This year, 5 sites averaged over 200 colonies. In 2001, 16 sites averaged over 200 colonies (Albright 2002).

61 Table 2. The weekly average and the overall average at White Creek (WC), Cripple Creek (CC), Hayden Creek (HC), Shadow Brook (SB) and Mount Wellington (MW) over the summer of 2014. Numbers are recorded as colonies per 100 mL. *HC4 on 22 July 2014 represented by an estimated amount, not included in graph. SB4 on 12 August 2014 represented by an estimated amount. MW2 on 22 July 2014 represented by an estimated amount.

Site Distance 7.15.14 7.22.14 8.12.14 8.19.14 Overall from Otsego Summer Lake (km) Average WC1 5.90 13.0 37.3 13.6 38.3 25.6 WC2 2.78 262.6 152.6 181.3 113.3 177.5 WC3 0.60 51.0 67.0 59.3 19.7 49.3

CC1 8.32 12.6 101.3 19.0 49.3 45.6 CC2 6.87 11.3 4.6 33.3 78.0 31.8 CC3 1.80 55.3 398.3 76.3 129.0 164.7 CC4 0.56 60.6 66.0 108.6 110.3 86.4 CC5 0.22 42.6 20.0 28.0 48.3 34.7

HC1 7.04 19.3 18.0 77.3 69.7 46.1 HC2 6.37 38.0 411.0 82.6 153.0 171.2 HC3 5.78 243.6 459.3 128.6 171.7 250.8 HC4 3.80 362.0 10000* 288.0 498.7 2782.2 HC5 3.02 308.6 124.3 104.3 92.7 157.5 HC6 2.28 164.6 88.6 333.0 43.7 157.5 HC7 1.16 169.3 114.6 221.3 73.3 144.6 HC8 0.04 197.0 60.6 179.6 66.0 125.8

SB1 13.0 61.6 222.3 93.6 192.3 142.5 SB2 7.96 69.3 198.6 414.3 62.3 186.1 SB3 5.06 110.6 324.0 90.0 89.0 153.4 SB4 3.34 205.6 333.3 1000* 160.0 424.7 SB5 0.98 240.6 159.0 223.0 143.3 191.5

MW1 0.43 272.6 437.0 395.6 658.0 440.8 MW2 0.05 337.0 1000* 257.3 421.7 504.0

62 CONCLUSION

More frequent monitoring is suggested in order to continue the efforts to reduce pollutant sources in the watershed. Sites indicate the need for upstream BMP’s to control runoff or upgrades to wastewater treatment systems. Fewer sites exceeded the DEC standard of 200 colonies per 100 mL than in the past (i.e., Albright 2002).

REFERENCES

Albright, D 2002. Analysis of fecal coliform concentration in Otsego Lake’s northern tributaries, summer 2001. In 34th Ann. Rept. (2001). Bio. Fld. Sta., SUNY College at Oneonta.

APHA, AWWA, WEF. 2012. Procedure 9222 D. Standard Methods for the Examination of Water and Wastewater. 22nd Edition.

Harman, W. and P.J. Godfrey. 1980. The Limnology of Otsego Lake (Glimmerglass). Bloomfield, J. (ed.). Lakes of New York State, Volume III, Academic Press, New York, NY.

Hastings, C. 2015. Water quality monitoring if five major tributaries in the Otsego Lake watershed, summer 2014. In 47th Ann. Rept. (2014). Bio. Fld. Sta., SUNY College at Oneonta.

Miller, C. 1997. Analysis of fecal coliform concentrations of Otsego Lake’s tributaries and the upper Susquehanna River, 1996. In 29th Ann. Rept. (1997) Bio. Fld. Sta., SUNY College at Oneonta.

New York State Department of Environmental Conservation (NYS DEC). 2008. §703.4 Water quality standards for coliforms.

Otsego Lake Watershed Council (OLWC). 1998. A Plan for the Management of the Otsego Lake Watershed. Updated by Otsego County Water Quality Coordinating Committee (WQCC) June 2007.

Pasquale, C. 1998. Analysis of fecal coliform concentration in Otsego Lake’s tributaries, summer 1997. In 30th Ann. Rept. (1998). Bio. Fld. Sta., SUNY College at Oneonta.

United States Environmental Protection Agency (USEPA). 2012. 5.11 Fecal Bacteria

63 Upper Susquehanna River Water Quality Monitoring:

Monitoring water quality and fecal coliform bacteria in the upper Susquehanna River, summer 2014

Morgan Freehafer1

INTRODUCTION

The Susquehanna River begins in Cooperstown, NY, in Otsego Lake. After traveling 444 miles through New York, Pennsylvania, and Maryland, the Susquehanna River empties into the Chesapeake Bay at Harve De Grace, MD. It is the largest tributary of the Chesapeake Bay; fifty percent of the freshwater entering the bay is sourced from the Susquehanna River. The Susquehanna River is both the longest, commercially non- navigable river in North America and the largest river lying entirely within the United States (SRBC 2014).

Each year, the Susquehanna River is tested for temperature, pH, dissolved oxygen, specific conductivity, nitrites+nitrates, total nitrogen, total phosphorus, and fecal coliform. These parameters are used to develop an accurate assessment of the Susquehanna River and ensure that unauthorized discharges or pollutants do not threaten its water quality. Regular monitoring of the Susquehanna River also assures that secondarily treated sewage released into the river by the Village of Cooperstown does not negatively impact the river’s health.

METHODS

From 10 Jun to 23 July, nine sites along the Susquehanna River were monitored weekly (Figure 1, Table 1). Water samples were collected from each site in 125mL Nalgene® bottles and stored in a cooler for subsequent nutrient analysis. A Lachat® QuickChem FIA + Water Analyzer was used to determine nitrate+nitrite (Pritzlaff 2003), total nitrogen (Pritzlaff 2003) and total phosphorus (Liao and Marten 2001). Temperature, conductivity, pH, dissolved oxygen, and turbidity were assessed using a YSI® 6820 V2-2 multi-probe at each site.

1 F.H.V. Mecklenburg Conservative Fellow, summer 2014. Present affiliation: Emma Willard School. Funding provided by the Otsego County Conservation Association.

64

Figure 1. Upper Susquehanna sample sites, summer 2014.

Additional water samples were also collected at each site and tested for fecal coliform bacteria using the membrane filter technique (APHA 1992). Testing was done on a total of six subsamples for each site, comprised of two triplicates of 10mL and 100mL respectively. Samples were run through a sterile filter using a low-pressure vacuum pump. The use of multiple volumes of water helps to assure that an ideal range of fecal coliform colonies (20-80) results at one of the dilutions. Filters were then placed on a nutrient-soaked media pad in a Milipore® dish, and incubated in a water bath at 44.5 degree Celsius for 24 hours. Fecal coliform colonies were then counted and were reported as colonies per 100 mL. To avoid contamination, all lab equipment used was sterilized in 70% ethanol, washed in hot water and rinsed with de-ionized water between different sites.

65

Table 1. Locations and descriptions of nine upper Susquehanna sample sites.

Site Distance from Description source 3 144m Under the Main Street Bridge; accessed via slope beside the bridge.

6a 1012m Below the dam at Bassett Hospital; accessed from the northern corner of the lower parking lot at Bassett Hospital. 7 1533m Below the dam at Bassett Hospital; accessed from the southern corner of the lower parking lot at Bassett Hospital. 8 1724m Under the Susquehanna Ave. bridge west of the Clark Sports Center; accessed via the slope beside the bridge. 12 4119m Just above the sewage discharge of the Cooperstown Wastewater Treatment Plant, near Cooperstown High School. Accessed by an opening in the fence. 16 5460m Small bridge perpendicular to the road on Clark Property. Accessed by crossing a gated bovine grazing area (cow field). 16a 5939m Distinct bend in river alongside road on Clark Property, in field directly across from large house with hay rolls in front. Accessed by long path found on the right side of the field. Be cautious of barbed wire. 17 8143m Abandoned bridge on Phoenix Mill Road.

18 9867m Railroad trestle about 200m north of the railroad crossing on Rt. 11 going out of Hyde Park, accessed by walking on the railroad tracks.

RESULTS & DISCUSSION

Temperature The average temperature of the upper Susquehanna River this summer was 20.59 degrees Celsius, the lowest recorded since 2004. Mean temperature for each of the nine sample sites (+/- standard error) is given in Figure 2. Figure 3 compares mean temperature over 2014 with the summers 2004 through 2014.

66 26

25

24

23

22

21 Temperature (Celsius) (Celsius) Temperature 20

19

18 0 2000 4000 6000 8000 10000 Distance from source (meters)

Figure 2. Average temperature profile for upper Susquehanna River, summer 2014.

26

25 2004

2005 24 2006 23 2007 22 2008 2009 21 2010 20 Temperature (Celsius) 2011 19 2012 18 2014 0 2000 4000 6000 8000 10000 2013 Distance from site (m)

Figure 3. Average temperature profile for the upper Susquehanna, summers 2004 (Hill 2005), 2005 (bauer 2006), 2006 (Zurmuhlen 2007), 2007 (Coyle 2008), 2008 (Matus 2009), 2009 (Heiland 2010), 2010 (Bauer 2011), 2011 (Scott 2012), 2012 (Katz 2013), 2013 (Bianchine 2014), and 2014.

67 pH

pH measures the acidity or basicity of a solution. Average pH values at each site were lower this year than they were last year, with the exception of site 16a. Mean pH at each site (+/- standard error) over 2014 is given in Figure 4. Figure 5 compares mean pH over 2014 to mean pH from summers 2004 through 2013.

8.5

8.3

8.1

pH 7.9

7.7

7.5 0 2000 4000 6000 8000 10000 Distance from source (meters)

Figure 4. Mean pH values for upper Susquehanna River, summer 2014.

8.5 2004 8.4 2005 8.3 2006 8.2 2007 8.1

2008 8 pH 2009 7.9 2010 7.8 2011 7.7 2012 7.6 2013 7.5 0 2000 4000 6000 8000 10000 2014 Distance from site (m)

Figure 5. Average pH profile for the upper Susquehanna, summers 2004 (Hill 2005), 2005 (bauer 2006), 2006 (Zurmuhlen 2007), 2007 (Coyle 2008), 2008 (Matus 2009), 2009 (Heiland 2010), 2010 (Bauer 2011), 2011 (Scott 2012), 2012 (Katz 2013), 2013 (Bianchine 2014), and 2014.

68 Conductivity

Conductivity is the capability of water to transmit electricity and is based on its concentrations of dissolved ions (Wetzel and Lichens 1991). While the geological characteristics of the upper Susquehanna River are a primary influence in its conductivity measurements, radical variation in conductivity values could indicate contamination. Mean conductivity at each site (+/- standard error) is given in Figure 6. Figure 7 compares mean conductivity for 2014 to mean conductivity for years 2004 through 2013.

0.4

0.35

0.3

0.25 Conductivity (mmho/cm) Conductivity

0.2 0 2000 4000 6000 8000 10000 Distance from source (meters)

Figure 6. Conductivity profile for upper Susquehanna River, summer 2014.

Dissolved Oxygen

Dissolved oxygen is necessary to the survival of fish and other aquatic life. Water flow, oxygen demand, and external factors all affect levels of dissolved oxygen. Dissolved oxygen concentrations for this summer were higher than they were last summer, though they are still within the range that is typically observed. Figure 8 shows mean dissolved oxygen levels (+/- standard error) for the upper Susquehanna River this summer. Figure 9 compares mean data from this summer to years 2004-2014.

69 0.400

2004

0.350 2005 2006 2007 0.300 2008 2009 2010 2011 Conductivity (mmho/cm) Conductivity 0.250 2012 2013 2014 0.200 0 2000 4000 6000 8000 10000 Distance from site (m)

Figure 7. Average conductivity profile for the upper Susquehanna, summers 2004 (Hill 2005), 2005 (bauer 2006), 2006 (Zurmuhlen 2007), 2007 (Coyle 2008), 2008 (Matus 2009), 2009 (Heiland 2010), 2010 (Bauer 2011), 2011 (Scott 2012), 2012 (Katz 2013), 2013 (Bianchine 2014), and 2014.

10

9

8

7

Dissolved Oxygen (mg/L) 6

5 0 2000 4000 6000 8000 10000

Distance from source (meters)

Figure 8. Mean dissolved oxygen profile for the upper Susquehanna River, summer 2014.

70 10

2004

9 2005 2006 8 2007 2008 7 2009 2010 Dissolved oxygem (mg/l) 6 2011 2012

5 2013 0 2000 4000 6000 8000 10000 2014 Distance from source (m)

Figure 9. Average dissolved oxygen profile for the upper Susquehanna, summers 2004 (Hill 2005), 2005 (bauer 2006), 2006 (Zurmuhlen 2007), 2007 (Coyle 2008), 2008 (Matus 2009), 2009 (Heiland 2010), 2010 (Bauer 2011), 2011 (Scott 2012), 2012 (Katz 2013), 2013 (Bianchine 2014), and 2014. Turbidity Turbidity is a measurement of water clarity based on light scattering due to suspended matter. Over the summer of 2013, the turbidity of the upper Susquehanna River was tested for the first time; the results from this summer are a continuation of those efforts to monitor turbidity. At all sites along the upper Susquehanna this year, turbidity readings were lower than they were last year. This indicates a marked improvement in water clarity. Mean turbidity at each site (+/- standard error) is given in Figure 10. A graph comparing this summer’s mean turbidity at each site with last year’s averages is given in Figure 11.

71 16

14

12

10

8 Turbidity 6

4

2

0 0 2000 4000 6000 8000 10000

Distance from source (meters)

Figure 10. Average turbidity along upper Susquehanna River, summer 2014.

2014 2013 16

14

12

10

8

Turbidity 6

4

2

0 0 2000 4000 6000 8000 10000 Distance from source (meters)

Figure 11. Average turbidity in the upper Susquehanna River, summers 2013 (Bianchine 2013) and 2014.

72 Total Phosphorus

Phosphorus is an essential nutrient that contributes to algal growth when found in high concentrations. Monitoring the upper Susquehanna River for total phosphorus helps reduce the risk of nutrient loading, algal growth, and depleted oxygen. Common sources of nutrients like phosphorus include agricultural and urban runoff and sewage effluent. Mean phosphorus for each site (+/- standard error) over 2014 is given in Figure 12. Mean total phosphorus for summers 2004 to present is shown in Figure 13.

250 2014

200

150

100 TotalPhosphorus (ug/l) 50

0 0 1000 2000 3000 4000 5000 6000 7000 8000 9000 10000

Distance from source (M)

Figure 12. Average phosphorus concentrations along the upper Susquehanna River, summer 2014.

73 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 250

200

150

100 TotalPhosphorus (ug/l)

50

0 0 2000 4000 6000 8000 10000

Distance from source (M)

Figure 13. Average phosphorus concentrations along the upper Susquehanna River, summers 2004 (Hill 2005), 2005 (bauer 2006), 2006 (Zurmuhlen 2007), 2007 (Coyle 2008), 2008 (Matus 2009), 2009 (Heiland 2010), 2010 (Bauer 2011), 2011 (Scott 2012), 2012 (Katz 2013), 2013 (Bianchine 2014), and 2014.

Nitrogen

Nitrogen, like phosphorus, is an essential nutrient that can contribute to the growth of algae. Organic nitrogen is found in proteins and is constantly being recycled by plants and animals, while inorganic nitrogen can exist as a gas N2, or as nitrate NO3-, nitrite NO2-, or ammonia NH3+ (Bianchine 2013). Common anthropogenic sources of nitrogen include agricultural and wastewater runoff. Mean nitrite+nitrate at each site (+/- standard error) for summer 2014 is given in Figure 14. Figure 15 compares mean nitrites+nitrates for summer 2014 with historical mean values from years 2004 to present. Mean total nitrogen at each site (+/- standard error) for summer 2014 is given in Figure 16. Figure 17 compares mean total nitrogen for summer 2014 with historical mean values from years 2004 to present.

74 1.00

0.80

0.60

0.40 Nitrite+Nitrate (mg/l) 0.20

0.00 0 2000 4000 6000 8000 10000

Distance from source (M)

Figure 14. Average nitrite and nitrate concentrations of the upper Susquehanna River, summer 2014.

2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 1.00

0.80

0.60

0.40 Nitrite+Nitrate (mg/l)

0.20

0.00 0 2000 4000 6000 8000 10000

Distance from source (M)

Figure 15. Average nitrite+nitrate concentrations for the upper Susquehanna, summers 2004 (Hill 2005), 2005 (bauer 2006), 2006 (Zurmuhlen 2007), 2007 (Coyle 2008), 2008 (Matus 2009), 2009 (Heiland 2010), 2010 (Bauer 2011), 2011 (Scott 2012), 2012 (Katz 2013), 2013 (Bianchine 2014), and 2014.

75

2.00 2014

1.50

1.00

TotalNitrogen (mg/l) 0.50

0.00 0 2000 4000 6000 8000 10000

Distance from source (M)

Figure 16. Total Nitrogen profile of the upper Susquehanna River, summer 2014.

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2.00

1.50

1.00 TotalNitrogen (mg/l)

0.50

0.00 0 2000 4000 6000 8000 10000

Distance from source (M)

Figure 17. Average nitrogen concentrations for the upper Susquehanna, summers 2004 (Hill 2005), 2005 (bauer 2006), 2006 (Zurmuhlen 2007), 2007 (Coyle 2008), 2008 (Matus 2009), 2009 (Heiland 2010), 2010 (Bauer 2011), 2011 (Scott 2012), 2012 (Katz 2013), 2013 (Bianchine 2014), and 2014.

76 Fecal Coliform

Fecal coliform are bacteria that live in the digestive tracts of warm-blooded animals (Zurmuhlen 2007). Testing for the presence of fecal coliform bacteria helps in discerning whether or not an area has been subject to fecal contamination. Fecal coliform bacteria, while indicating the presence of contaminants, are not pathogenic themselves. Fecal coliform are counted in colonies/100mL. Mean fecal coliform at each site (+/- standard error) over 2014 is given in figure 18. Figure 19 compares mean fecal coliform levels for this summer with mean values from years 2004 to present.

2000

1500

1000

500

0

Fecal coliform (colonies/100ml) 0 2000 4000 6000 8000 10000 Distance from source (m)

Figure 18. Mean fecal coliform levels along the upper Susquehanna River, summer 2014.

2004 2005 2006 2007 2009 2010 2011 2012 2013 2014

2000

1500

1000

500 Fecal Coliform (col./100 ml)

0 0 2000 4000 6000 8000 10000 Distance from source (m)

Figure 19. Mean fecal coliform levels for the upper Susquehanna, summers 2004 (Hill 2005), 2005 (bauer 2006), 2006 (Zurmuhlen 2007), 2007 (Coyle 2008), 2008 (Matus 2009), 2009 (Heiland 2010), 2010 (Bauer 2011), 2011 (Scott 2012), 2012 (Katz 2013), 2013 (Bianchine 2014), and 2014.

77 REFERENCES

Bauer, E. 2006. Monitoring the water quality and fecal coliform in the upper Susquehanna River, summer 2005. In 38th Ann. Rept. (2005). SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta.

Bauer, H. 2011 Monitoring the water quality and fecal coliform in the upper Susquehanna River, summer 2010. In 43th Ann. Rept. (2010). SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta.

Coyle, O.L. 2008. Monitoring water quality and fecal coliform bacteria in the Upper Susquehanna River, summer 2007. In 40th Annual Report (2007), SUNY Oneonta Bio. Fld. Sta., SUNY Oneonta.

Ebina, J.T.Tsutsui, and T. Shirai. 1983. Simultaneous determination of total nitrogen and total phosphorus in water using peroxodisulfate oxidation. Water Res. 17(12):1712-1726.

Heiland, L. 2010. Monitoring water quality in the upper Susquehanna River, summer 2009. In 42st Ann. Rept. (2009). SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta

Hill, J.2005. Monitoring the water quality in the upper Susquehanna River, summer 2004. In 37th Ann. Rept. (2004). SUNY Oneonta Bio. Fld Sta., SUNY Oneonta.

Liao, N. and S. Marten. 2001. Determination of total phosphorus by flow injection analysis chloriometry (acid persulfate digestion method). QwikChem Method 10- 115-01-1-F. Lachat Instruments. Loveland, Colorado.

Matus, J.E. 2009. Monitoring water quality and fecal coliform bacteria in the upper Susquehanna River, summer 2008. In 41st Ann. Rept. (2008). SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta.

Pritzlaff, D. 2003. Determination of nitrate+nitrite in surface and wastewater by flow injection analysis. QwikChem Method 10-115-01-1-F. Lachat Instruments. Loveland, Colorado.

Susquehanna River Basin Commision. 2013. http://www.srbc.net/about/index.htm.

Wetzel, R.G. and G.E. Lichens. 1991. Limnological Analysis, 2nd ed. Springer-Verlag, New York.

Wetzel, R.G. 2001. Limnology: Lake and resevoir systems. Academic Press, San Diego.

Zurmuhlen, S. J. 2007. Monitoring water quality in the upper Susquehanna River, summer 2006. In 39th Annual Report (2006), SUNY Oneonta Bio. Fld. Sta., SUNY Oneonta.

78 ARTHRODOD MONITORING

Mosquito Studies

William L. Butts1

Probable Localized Population – Treehole Mosquitoes

Faculty and student participants in a short term summer course reported considerable annoyance by mosquitoes at the Thayer Farm. No specimens were retained, so no definitive explanation can be put forth. The most likely scenario is that a localized population of tree-hole mosquitoes was present. Populations of two such species have been recorded in previous years. Feeding is generally localized if suitable hosts are available. The most widely distributed species, Aedes triserivatus (Say) has been collected on the property. Aedes hendersoni Cockerell may also be involved. Horsfall (1955) notes that larvae inhabit small containers in shaded situations and have been recorded from containers of a variety of types and that choked gutters of houses may be a good source.

REFERENCE

Horsfall, W.H.1955. Mosquitoes: Their bionomics and relation to disease, 719 pp. Ronald Press Co. NY.

1 Professor emeritus, SUNY Oneonta Biological Field Station.

79 Mosquito Survey – Thayer Farm

William L. Butts1

Collection of larval specimens by dipper and adults by light trap were largely negative.

Dipper sampling for larva conducted on 9 March, 18 April, 23 April, 29 April, 6 may, and 20 May yielded no specimens.

Light trap samplings for adults conducted on 4 June, 5 June, 9 June, 16 June, 23 June, 26 June, 8 July, 9 July, 22 July and 30 July were all negative. On 23 July, one ♀ Aedes Cinerius (Meigen) and a badly damaged ♀ were collected. On 9 August, one ♀ Anopheles (prob.) quadrimaculatus (Say) were collected.

No temporary standing water remained on site and trapping was suspended.

No on-site activity was conducted at Greenwoods, but drive-through observations made on a regular basis noted development of an extensive vegetative mat over much of the water surface of Cranberry Bog. Waterfowl were not observed within the affected area, suggesting a possible determent effect. Observation on 13 October noted apparent disappearance of vegetation from the water surface.

1 Professor emeritus, SUNY Oneonta Biological Field Station.

80 REPORTS: The abundance of starry stonewort (Nitellopsis obtusa) in Otsego Lake, 2014

Madeline Genco1 and Rebecca Russell2

INTRODUCTION Starry stonewort (Nitellopsis obtusa) is a nonnative, invasive macroalgal species present in Otsego Lake, NY and other parts of the country. It was first documented in Otsego Lake in 2010 just west of Sunken Island (Harman 2010). A plant survey conducted in 2012 (McShane and Mehigan 2013) evaluated its spread. It is a major nuisance in Michigan, where it is driving out native plants by using up all the habitats that the natives need to survive (Pullman and Crawford 2010). Stonewort is thought to be native to Europe; however, it is endangered in the United Kingdom (Pullman and Crawford 2010). Because stonewort has become such a problem in Michigan, monitoring it locally will provide insight into its spread in lakes having varying chemistry and plant community assemblages. Stonewort is most easily confused with Chara, a native macroalgae. Stonewort tends to thrive in alkaline, calcium rich lakes (Golden Sands Resource Conservation and Development Council undated). It can be identified by a popping sensation when squeezing the plant in your hand. Each stem is made up of a single cell; the pop is caused by the breaking of the cell wall (Harman, personal communication 2014). Scent can also be used to distinguish between the two. Stonewort has a much milder odor compared to Chara, which has a musky odor (Borman et al. 1997). In addition, Chara tends to branch off in small whorls, whereas stonewort has lager, less regularly spaced whorls (Harman, personal communication 2014). The purpose of this study was to update the distribution of starry stonewort in Otsego Lake as compared to that in2012 (McShane and Mehigan 2013). At the same time, the abundance of other plants (taken together) was estimated.

METHODS The week of 4 August 2014, Otsego Lake was sampled using the Point Induced Rake Toss Relative Abundance Method (PIRTRAM) developed by Lord and Johnson (2006). Sampling was done from a motorized boat along the perimeter of the lake as well as around the Sunken Island. Samples were collected about every 100 to 200 meters, but were taken closer together in areas where stonewort was found. The location of each site was recorded on a GPS, and plotted on a base map (Figure 1). Three rake tosses were performed at each site. A double sided rake was created by welding two rake heads together; this was then attached to a 10 meter chord. At each site the rake was thrown into the lake and drawn back in. The field measures, described in Table 1, were used to describe the amount of starry stonewort compared to all other plant matter pulled up on the rake. Corresponding midpoints (Table 1) were used to average the three rake tosses and estimate the total dry weight range of starry stonewort and other plants at

1 SUNY Oneonta Biology Department Intern, summer 2014. Current affiliation: SUNY Oneonta. 2 BFS W.N. Harman Internship, summer 2014. Current affiliation: SUNY Oneonta.

81 the site. Data were mapped out with the GPS waypoints to show the abundance of starry stonewort compared to other plants.

Table 1. This table was used in the field to describe the amount of plants pulled up on the rake using the PIRTRAM. Field measures correspond to an estimated total dry weight range, or an estimated total biomass of plants at a given site.

Abundance Abundance Category Field Measure Total Dry Midpoint (g/m2) Category (used weight Range in maps) (g/m2) 0 "Z"= no plants Nothing 0 0 1 "T"= trace plants Fingerful 0-2.0 1 2 "S"= sparse plants Handful 2.0-140 71 3 "M"= medium plants Rakeful 140-230 185 4 "D"= dense plants Can't bring in 230-450 340 boat

82

Figure 1. Map of sites on Otsego Lake where rake tosses were performed.

83 RESULTS AND DISCUSSION Starry stonewort was observed at 43 of 129 sites. It was found growing most densely in High Bay as well as the north end of the lake. It was found with less frequency and density in the south. Table 2 identifies each site location and provides the mean abundance categories of stonewort as well as all other plants concurrently collected. Figures 2-4 plot the mean abundance of starry stonewort and other combined plants at each site by using symbols of varying shades of gray circular symbols. Circular symbols represent starry stonewort, while the square symbols in which they are embedded represent all other plants. Note that some overlap exists between figures.

Table 2. Mean midpoint abundance values for stonewort and “other” plants in Otsego Lake (described in Table 1) for each collection site (provided in Figure 1).

Site Abundance Abundance Site Abundance Abundance Number Category of Category of Number Category of Category of Starry Other Plants Starry Other Plants Stonewort Stonewort 1 0 2 65 4 2 2 0 2 66 3 2 3 0 2 67 3 1 4 2 2 68 2 3 5 2 2 69 2 3 6 0 2 70 2 2 7 1 1 71 0 1 8 0 1 72 0 3 9 1 2 73 0 3 10 1 2 74 0 0 11 0 0 75 0 0 12 0 2 76 0 2 13 2 2 77 0 1 14 2 2 78 0 2 15 1 2 79 0 1 16 0 1 80 0 1 17 2 2 81 0 2 18 1 2 82 0 3 19 2 1 83 0 2 20 1 2 84 0 4 21 1 0 85 0 2 22 2 1 86 0 1 23 1 2 87 0 1 24 1 1 88 0 2 25 0 0 89 0 2 26 0 2 90 0 2 27 2 2 91 0 2 28 4 1 92 0 2

84 Table 2 (cont.). Mean midpoint abundance values for stonewort and “other” plants in Otsego Lake (described in Table 1) for each collection site (provided in Figure 1).

29 2 1 93 0 2 30 3 0 94 0 1 31 1 2 95 0 2 32 2 2 96 0 2 33 2 1 97 0 0 34 2 2 98 0 0 35 1 1 99 0 0 36 1 2 100 0 0 37 2 0 101 0 1 38 2 2 102 0 2 39 2 2 103 0 0 40 2 3 104 0 1 41 0 0 105 0 2 42 0 2 106 0 2 43 0 1 107 0 2 44 0 2 108 0 2 45 2 2 109 0 2 46 0 0 110 0 1 47 1 2 111 0 1 48 0 2 112 0 4 49 0 0 113 0 2 50 0 1 114 2 1 51 0 0 115 1 2 52 0 2 116 0 1 53 0 1 117 0 1 54 0 2 118 0 2 55 0 0 119 1 2 56 1 2 120 0 2 57 0 0 121 2 2 58 0 1 122 2 1 59 0 0 123 0 2 60 0 0 124 0 2 61 0 2 125 0 1 62 0 2 126 1 1 63 0 4 127 0 1 64 0 2 128 0 1 129 0 3

85 Figure 2. Map of north eastern Otsego Lake. Prevalence of stonewort vs. other plants is shown with various shades of grey which correspond to the density of plants at the site.

86

Figure 3. Map of north eastern Otsego Lake. Prevalence of stonewort vs. other plants is shown with various shades of grey which correspond to the density of plants at the site.

87

Figure 4. Map of southern Otsego Lake. Prevalence of stonewort vs. other plants is shown with various shades of grey which correspond to the density of plants at the site.

88 DISCUSION Starry stonewort was first documented in Otsego Lake in 2010 near Sunken Island toward the north end (Harman 2010). Work conducted in 2012 using PITRAM and snorkeling surveys indicated that it had become widespread throughout the northwestern littoral areas and had first appeared in Hyde Bay (Figure 5; McShane and Mehigan 2013). In 2014, it was common throughout the north end and Hyde Bay and had spread to the south end of the lake (Figure 6).

Figure 5. Approximate distribution of starry stonewort in mid-July 2012 (from McShane and Mehigan 2013).

89

Figure 6. Approximate distribution of starry stonewort in early August 2014.

Starry stonewort in Otsego Lake advanced faster than it had in Canadarago Lake (Russell and Genco 2015), where it was first noted in 2010 (Smith 2011). It was postulated that the spread there has been minimal because the abundance of other plants had limited the opportunities for colonization. Conversely, its spread in Moraine Lake, Madison County New York, has been quite rapid. There, following its documentation in a particular area of the lake, it became dominant and extremely dense within one to two years (Harman and Albright 2014). This plant has been an aggressive nuisance in other areas of the country (i.e., Pullman and Crawford 2010), and it seems to have the potential to become problematic in Otsego Lake as well.

90 REFERENCES Albright, M., and H. Waterfield. 2012. The State of Canadarago Lake, 2011. Tech, Rept. # 30. SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta. Borman, S., R. Korth and J. Temte. 1997. Through the looking glass. Wisconson Lakes Partnership. Reindl Printing. Merrill, WI. Golden Sands Resource Conservation and Development Council. Undated. Viewed 20 Jan. 2015. http://www.uwsp.edu/cnr- ap/UWEXLakes/Documents/programs/CLMN/AISfactsheets/17StarryStonewort.pdf Haman, W.N. 2014. Personal Communication. SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta. Harman, W.N. and M.F. Albright. 2014. Aquatic macrophyte management plan facilitation, Lake Moraine, Madison County, NY 2013. In 46th Ann. Rept. (2013). SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta. Harman, W.N. 2010. Updates. The Reporter (Biol. Fld. Sta. newsletter). SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta. Lord, P.H. and R.L. Johnson. 2006. Aquatic plant monitoring guidelines. Cornell University. http://www.eaglelake1.org/archives/documents/plant_surveys/2006%20aquatic%20plant %20monitoring%20guidelines.pdf McShane, D., and K. Mehigan. 2013. 2012 aquatic macrophyte survey of Otsego Lake. In 45th Ann. Rept. SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta. Pullman, G.D. and G. Crawford. 2010. A decade of starry stonewort in Michigan. Observations and Operational Management Considerations – 1999 to 2009. http://www.wolverinelake.com/Documents/WMB_Documents_Charts_Etc/Starry_Stone wort_Lakeline_Report.pdf. Russell, R. and M. Genco. 2015. Distribution of Nitellopsis obtusa (starry stonewort) in Canadarago Lake, NY. In 47th Ann. Rept. (2014). SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta.

Smith, T.F. 2011. 2010 Canadarago Lake aquatic macrophyte survey. In 43rd Ann. Rept. (2010). SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta.

91 Summer 2014 trap net monitoring of the fish communities in the weedy littoral zone at Rat Cove and the rocky littoral zone at Brookwood Point, Otsego Lake

Matthew J. Best1

INTRODUCTION This study was a continuation of yearly monitoring of the littoral fish communities of Otsego Lake. The long term goal of the study is to assess the littoral fish community and determine population dynamics of species utilizing littoral habitats. Rat Cove has been studied since 1979 (MacWatters 1980) and Brookwood Point since 2002 (Wayman 2003). Littoral habitats of sizeable lakes such as Otsego Lake are necessary, providing spawning and nursery habitats for many species of fish. The illegal introduction of Alewife (Alosa pseudoharengus) in 1986 (Foster 1990) altered the trophic balance and physical/chemical characteristics of Otsego Lake, due to the species’ opportunistic behavior and over-effective grazing of the lake’s zooplanktonic community. Alewives are efficient, opportunistic, epilimnetic planktivores that feed on microcrustaceans, insects, ichthyoplankton, zooplankton, and their own eggs (Cornwell 2005). Long term monitoring of littoral fishes helps to assess the inshore fish communities, as well as alewife abundance and spawning activity. Piscivorous fish can give a glimpse of what forage base is readily available. Diet samples were taken from these fish to further investigate the predator/prey relationship with alewife in Otsego Lake. Additionally this study provides useful long term data on non-alewife species. In order to mitigate the detrimental effects alewife have had on the lake’s ecosystem, predatory walleye (Sander vitreus) have been re-established through stocking, which began in 2000. During summer stratification, alewife primarily utilize the top layer of water (the epilimnion) (Urban and Brandt 1993), resulting in spatial separation between them and the cold water predators of Otsego Lake. The separation from their predators allows the alewife to reproduce and flourish. Walleye, however, are able to forage in the epilimnion, so during summer stratification alewife would be available forage. This study continues to document littoral fish communities that could provide insight into changes occurring in Otsego Lake through such trophic interactions.

1 Robert C. MacWaters Internship in the Aquatic Sciences, summer 2014. Present affiliation: Department of Fisheries and Wildlife Technology, SUNY Agriculture and Technical College, Cobleskill, NY.

92 METHODS & MATERIALS Winged Indiana trap nets with a single throat were set out Monday through Friday and checked daily at both Rat Cove and Brookwood Point (Figure 1) from 2 June to 1 August. At Rat Cove the trap was set perpendicular to the north shore and at Brookwood Point the trap was set due east from the middle of the point. The catch was transferred from the nets into totes, and all metrics were taken on site and fish were promptly returned to the water. Diet samples from any predator fishes (rock bass (Ambloplites rupestris), chain pickerel (Esox niger), walleye (Sander vitreus), smallmouth bass (Micropterus dolomieu) and largemouth bass (M. salmoides) over 200mm were taken using pulsed gastric lavage. Each fish was identified and measured in to the nearest mm. Any alewife captured would be kept to be measured and further analyzed at the main lab. Diet samples were preserved in 70% alcohol/water mixture until examined. Contents of the samples were placed into a petri dish and examined under a dissecting microscope. Any prey fish in the diet sample was identified and measured to the nearest mm.

Figure 1. Bathymetric contour map of Otsego Lake, NY. Trap nets were set perpendicular to the shore at Rat Cove and due east from the middle of the point at Brookwood Point.

RESULTS Tables 1 and 2 summarize the mean weekly catch rates of each species encountered between 2000 and 2014 at Rat Cove and Brookwood Point, respectively. The total catch per week for Rat Cove remained the same from the previous year (18 fish pert week in 2013 & 2014), while Brookwood Point experienced an increase from 12 to 29 fish per week. From 2005 – 20011 there was an increase in overall mean catch per week at both Rat Cove and Brookwood Point, and a drop off in 2013 (data not available for 2012). Older nets were replaced with new ones in 2011, and that could be a factor in these changes (German 2012).

93 Table 1. Mean weekly catch at Rat Cove and catch contributed by each species, 2000-2014 (modified from Stowell 2013).

Species 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2013 2014 Alewife 120 68 8 45 2 0 0 3 1 <1 <1 <1 0 0 Golden Shiner <1 <1 <1 <1 <1 <1 0 <1 <1 <1 <1 <1 1 <1 Pumpkinseed 10 21 15 33 13 5 2 2 4 5 5 16 9 3 Blue Gill 2 3 4 2 2 1 <1 3 6 7 5 7 1 10 Redbreast Sunfish <1 <1 <1 <1 <1 <1 0 0 <1 <1 0 <1 0 0 Rock Bass 2 2 4 1 2 <1 <1 <1 <1 1 1 2 <1 2 Largemouth Bass <1 <1 <1 <1 <1 <1 0 <1 <1 <1 <1 <1 <1 <1 Chain Pickerel <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 Atlantic Salmon 0 <1 0 <1 0 0 0 0 0 0 0 0 0 0 Yellow Perch 3 <1 1 <1 1 <1 <1 <1 <1 0 <1 4 3 2 White Sucker 1 <1 1 <1 2 <1 <1 0 0 0 <1 <1 <1 0 Common Carp <1 <1 <1 <1 <1 <1 <1 0 0 0 0 <1 <1 0 Brown Bullhead 2 <1 6 3 2 <1 0 <1 0 <1 <1 <1 <1 <1 Spottail Shiner 0 0 <1 0 0 0 0 <1 0 0 0 0 0 <1 Smallmouth Bass 0 0 <1 0 0 0 0 0 0 0 0 0 0 0 Emerald Shiner 0 0 0 0 <1 0 0 <1 0 0 0 <1 <1 0 European Rudd <1 0 <1 <1 <1 0 <1 0 <1 <1 1 <1 0 0 Common Shiner 0 0 0 0 0 0 0 0 0 0 0 <1 0 0 Walleye 0 0 0 0 0 0 0 0 0 0 0 <1 0 0 Tadpole Madtom 0 0 0 0 0 0 0 0 0 0 0 0 0 <1 Total 141 96 41 87 25 9 5 11 14 15 14 35 18 18 Table 2. Mean weekly catch at Brookwood Point and catch contributed by each species, 2000- 2014 (modified from Stowell 2013).

Species 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2013 2014 Alewife 224 137 77 95 13 6 1 5 <1 <1 1 0 0 0 Golden Shiner <1 <1 1 2 2 <1 <1 0 0 0 <1 <1 <1 <1 Pumpkinseed 3 7 12 13 12 1 <1 1 2 2 1 10 5 5 Blue Gill 7 <1 <1 1 <1 <1 <1 <1 <1 <1 <1 15 <1 4 Redbreast Sunfish <1 0 <1 <1 <1 <1 <1 <1 0 <1 <1 4 0 2 Rock Bass 8 4 4 4 3 1 <1 <1 <1 2 2 14 3 12 Largemouth Bass <1 <1 <1 <1 0 <1 0 <1 <1 <1 0 <1 0 <1 Chain Pickerel <1 0 <1 <1 <1 <1 0 <1 <1 0 0 <1 <1 <1 Atlantic Salmon 0 <1 0 0 0 <1 0 0 0 0 <1 0 0 0 Yellow Perch 2 <1 <1 0 <1 <1 <1 0 <1 <1 0 1 2 2 Walleye 0 0 0 <1 0 0 0 <1 0 <1 0 <1 <1 <1 White Sucker 5 0 2 <1 <1 <1 <1 0 0 0 <1 <1 <1 <1 Common Carp 2 <1 <1 <1 <1 0 <1 0 0 0 0 0 <1 0 Bluntnose Minnow <1 0 0 0 0 <1 0 0 0 0 0 0 0 0 Brown Bullhead 7 0 1 4 4 0 <1 0 0 0 0 <1 <1 <1 Spottail Shiner 0 <1 0 0 0 0 0 <1 0 0 <1 3 0 1 Smallmouth Bass 0 0 0 <1 <1 0 0 0 <1 0 <1 <1 0 <1 European Rudd 0 <1 0 <1 <1 0 <1 <1 <1 0 0 0 0 0 Common Shiner 0 0 0 0 0 <1 0 0 0 0 0 0 0 0 Emerald Shiner 0 0 0 0 0 0 0 0 0 0 0 <1 0 <1 Lake Trout 0 0 0 0 0 0 0 0 0 0 0 <1 0 0 Creek Chubsucker 0 0 0 0 0 0 0 0 0 0 0 0 0 <1 Lake Whitefish 0 0 0 0 0 0 0 0 0 0 0 0 0 <1 Tadpole Madtom 0 0 0 0 0 0 0 0 0 0 0 0 0 <1 Total 259 152 101 121 37 10 4 8 4 5 6 50 12 29

94 Rock bass (Ambloplites rupestris) were more abundant at Brookwood Point than at Rat Cove (RC=2 per week, BW=12 per week), while bluegill (Lepomis macrochirus) were more abundant at Rat Cove than at Brookwood Point (RC=10 per week, BW= 4 per week). Tadpole madtoms (Noturus gyrinus) were found at both Rat Cove and Brookwood Point, where previous trap nettings have not indicated their presence. Creek chubsucker (Erimyzon oblongus) and lake whitefish (Coregonus clupeaformis) were two other species recorded in 2014 that were not previously documented. Common carp (Cyprinus carpio), common shiner (Luxilus cornutus), European rudd (Scardinius erythrophthalmus), bluntnose minnow (Pimephales notalus), Atlantic salmon (Salmo salar), and alewife were species not captured during this year’s survey that have been captured in the past (Figure 2). The decline of alewife is shown in Figure 3.

120

100 80 60 40 Frequency 20 0

Brookwood Rat Cove

Figure 2. Species frequency captured in trap nets at Rat Cove and Brookwood Point, Otsego Lake NY, summer 2014.

250

200 150 100 50 Catch Catch per Week 0 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2013 2014

Brookwood Rat Cove

Figure 3. Historical alewife catch per week in Otsego Lake, NY 2000-2014. Bluegill abundance increased at both Rat Cove and Brookwood Point in 2014. Traditionally, bluegill have been caught <2 per week at Brookwood Point, while in 2014 bluegill were captured almost 4 per week at Brookwood Point. Predators in the littoral zones could take advantage of the increase in abundance of this forage fish.

95

12

10

8

6

4

2

0 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2013 2014 Brookwood Point Rat Cove Figure 4. Historical bluegill catch per week at Brookwood Point and Rat Cove 2000-2014.

DIET ANALYSIS Table 5 summarizes the stomach contents of the chain pickerel evaluated. Two of the four adult chain pickerel sampled (n=4) contained bluegill, 25% contained yellow perch and 25% rock bass. Every chain pickerel sampled contained various fish bones and tissue.

100%

75%

50%

25%

0% Various Bones & Bluegill Yellow Perch Rock Bass Spottail Shiner Tissue

Figure 5. Frequency of occurrence of prey items in adult chain pickerel (>200mm) in Rat Cove and Brookwood Point, Otsego Lake 2014. Rock bass sampled (n=17) contained mostly invertebrates, but 29% contained fish or fish parts (Figure 6). Only one rock bass contained bluegill. Among the invertebrates, adult stoneflies, beetle larvae, amphipods, and crayfish parts were the most abundant in rock bass stomachs.

96 100%

75%

50%

25%

0% Fish & Fish Crayfish Mayfly Caddis Beetle Amphipod Damselfly Adult Dragonfly Parts Parts Larvae Larvae Stonefly Larvae

Figure 6. Frequency of occurrence of prey items in adult rock bass (>200mm) in Rat Cove and Brookwood Point, Otsego Lake 2014.

All of walleye sampled (n=4) contained bluegill, 25% contained yellow perch, and 25% contained rock bass (Figure 7). Walleye sampled positively selected for bluegill (that is, their proportion in walleye stomachs was greater than that in the environment relative to other potential prey items (Bowen 1996)).

100%

75%

50%

25%

0% Bluegill Yellow Perch Rock Bass Spottail Shiner

Figure 7. Frequency of occurrence of prey items in adult walleye (>200mm) in Rat Cove and Brookwood Point, Otsego Lake 2014.

DISCUSSION A total of 429 fish were caught between Rat Cove and Brookwood Point over the 2014 sampling season. Of those, 158 were captured in a weedy littoral habitat represented by Rat Cove, which was a slight decrease from the 2013 season (161) and a significant decrease from the 2011 season. Bluegill and pumpkinseed were the dominant species at Rat Cove. A total of 271 fish were captured at Brookwood Point, a rocky littoral zone that is dominated by rock bass. With the increase in bluegill numbers at both Rat Cove and Brookwood Point, walleye have been taking advantage by selecting for the bluegill (Figure 7). The weedy littoral zone has been known to be a nursery for juvenile fish, providing a safe habitat to grow. At Rat Cove the average size of sunfish was 100mm while at Brookwood Point the average size of sunfish was 148mm. Brookwood Point proved to be more diverse, having 17 species, while Rat Cove only had 11 species. Two juvenile lake whitefish were among the species captured at Brookwood Point. No

97 Lake whitefish have been recorded in the trap netting surveys before and could be a sign of a potential rebound for the species in Otsego Lake.

CONCLUSION Otsego Lake has seen an increase in clarity, potentially due to two separate factors, first being the introduction and establishment of zebra mussels (Dreissena polymorpha) first documented in 2007 (Harman 2008). Zebra mussels have been documented to cause ecological changes, including increased water clarity, following a successful introduction into a water body (D’Itri 1996). In 2009 (Gillespie 2010) and 2010 (Albright and Leonardo 2011), cladoceran zooplankton mean size and Daphnia sp. abundance had increased, correlating with increased water clarity. (Transparencies through 2013 were even greater (Waterfield and Albright 2014)). This change in the plankton community was likely due to reduced grazing by alewife. Alewife declined steadily following the reintroduction of walleye and they appear to have been virtually eliminated by the mid 2000’s (Figure 3). This is corroborated by hydroacoustics surveys by Waterfield and Cornwell (2013). With the absence of alewife, the presence of lake whitefish has increased. The native lake whitefish may have an opportunity to re-establish themselves into Otsego Lake.

REFERENCES Albright, M.F. and Leonardo. 2011. A survey of Otsego Lake’s zooplankton, summer 2010. In 43rd Ann. Rept. (2010). SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta. Albright, M.F. and H.A. Waterfield. 2014. Otsego Lake water quality monitoring, 2013. In 46th Ann. Rept. (2013). SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta. Bowen, S.H. 1996. Quantitative description of the diet. In Murphy, B.R. and D.W. Willis (eds.). Fisheries techniques, second edition. American Fisheries Society, Bethesda, MD. Cornwell, M.D. 2005. Re-introduction of walleye to Otsego Lake: Re-establishing a fishery and subsequent influences of a top predator. Occas. pap. #40, SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta. D’Itri, Frank. 1996. Zebra Mussels and Aquatic Nuisances Species. Chelsea, NY: Ann Arbor Press. 161-163. Print. Foster, J.R. 1990. Introduction of alewife (Alosa pseudoharengus) in Otsego Lake. In 22nd Ann. Rept. (1989). SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta. German, B.2012. Trap net monitoring of fish communities within the weedy littoral zone at Rat Cove and rocky littoral zone at Brookwood Point, Otsego Lake. In 44th Ann. Rept. (2011). SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta. Gillespie, S. 2010. A survey of Otsego Lake’s zooplankton community, summer 2009. In 42nd Ann. Rept. (2009). SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta.

98 Harman, W.N. 2008. Introduction. In 40th Ann. Rept. (2007). SUNY Oneonta Biol. Fld., SUNY Oneonta. MacWaters, R. C. 1980. The fishes of Otsego Lake. Occas. Paper #7. SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta. Stowell, S.G. 2013. Trap net monitoring of fish communities within the weedy littoral zone at Rat Cove and rocky littoral zone at Brookwood Point, Otsego Lake. In 46th Ann. Rept. (2013). SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta. Urban, T.P. and S.B. Brandt. 1993. Food and habitat partitioning between young-of-year alewives and rainbow smelt in southwestern Lake Ontario. Environmental Biology of Fishes 36:359-372. Waterfield, H.A. and M.D. Cornwell. 2013. Hydroacoustic surveys of Otsego Lake’s pelagic fish community, 2012. In 45th Ann. Rept. (2012). SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta. Wayman, K. 2003. Rat Cove and Brookwood Point littoral fish survey, 2002. In 35th Ann. Rept. (2002). SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta.

99 Monitoring zebra mussel colonization: PVC and cast iron recruitment Benjmin P. Coyle1, Paul H. Lord2 and Wai Hing Wong3

INTRODUCTION

Zebra mussels (Dreissena polymorpha) were discovered in Otsego Lake (NY, USA) in 2007 (Horvath 2008). Since their introduction, mussels have become a problem for the residents and municipal water treatment plant as the mussels adhere to infrastructure in the lake. To facilitate the creation of a management action plan, the behavior of the zebra mussel on and around the Cooperstown Water Treatment Plant’s (CWTP) intake pipe materials must be understood.

Testing Polyvinyl Chloride (PVC) and cast iron substrates allowed us to compare two surfaces for zebra mussel settlement and attachment. The observed adherence rates of the two substrata allow better understanding of both the life cycle of Otsego Lake’s zebra mussels and also the seasonality of the CWTP’s infestation. By observing these rates between sampling periods, a theoretical calendar of the mussel life cycle can be used to determine which life stages are present on the water at which time. This information can be utilized when deciding when to dose the CWTP intake with chemical control agents for zebra mussels as some chemical controls effect zebra mussel life stages differently. Intervention is necessary as thousands of people rely on this municipal water source.

The goal of this work was to determine zebra mussel seasonality. A generalized life cycle of zebra mussels can be found in Figure 1. An understanding of the zebra mussel life cycle in Otsego Lake will allow lake managers evaluate management plans with greater efficiency.

1 BFS Intern, summer 2014. Present affiliation; SUNY Oneonta. Funding provided by the Village of Cooperstown. 2 BFS Researcher and Adjunct Instructor of Environmental Science, SUNY Oneonta. 3 BFS Researcher and Assistant Professor of Biology, SUNY Oneonta.

100

Figure 1. Zebra mussel life cycle (Black 2003).

METHODS Adherence Monitoring Using two types of substrates, PVC and cast iron, we monitored zebra mussel recruitment in Otsego Lake. We cut 0.08 m diameter PVC pipes into 7.6 cm lengths having a total surface area of ~0.190 m2. The surface area of cast iron plates we analyzed was ~0.088 m2. Both substrates had complex shapes with internal and external surfaces. We attached each experimental material to an anchored and buoyed chain via stainless steel quick links at mean depths of 1 m and 10 m in Otsego Lake for the sampling periods listed in Table 1. Table 1. Deployment and retrieval dates of cast iron and PVC zebra mussel samplers in Otsego Lake, NY,

Sampling Period Deployment Retrieval Sampling Period 1 18-May-13 23-Jun-13 Sampling Period 2 23-Jun-13 21-Aug-13 Sampling Period 3 21-Aug-13 6-Oct-13

The 10 m depth substrate corresponds with the CWTP intake. Divers attached and removed substrates, at locations shown in Figure 2. Due to material availability, we only used PVC substrates during sampling period 1. For sampling periods 2 and 3, we used both PVC and cast iron substrates. In transit between sampling sites, we collected settled juvenile mussels and accumulated biofilm from the cast iron substrates using paper and metal spatulas. We restored

101 the cast iron substrates to pre-experimental condition by cleaning with a wire brush between deployments. Upon removal, we placed PVC substrates in freezer bags (avoiding the disturbance of biofilm) for transportation to the laboratory. We observed biofilm scrapings under 20x magnification to enumerate juvenile settlers. We recorded mussel adherence rates on the inside and outside of the fouled substrates.

Figure 2. Otsego Lake, NY. Sampling sites: Five Mile Point (42°45.901′N, 74°53.882′W), Pegg’s Point (42°46.719′N, 74°52.791′W), Three Mile Point (42°45.127′ N, 74°53.443′W), Point Judith (42°43.713′N, 74°54.413′W). At each site, a cast iron and PVC substrate was deployed at 1 and 10 m.

Statistical Analysis We used a three-way analysis of variance (ANOVA) to examine if there was any difference in zebra mussel colonization rates among different substrates, in different seasons, and at different depths in Otsego Lake. We performed a Student-Newman-Keuls post hoc multiple comparisons test to determine if the difference was significant. The significance criterion was set at α = 0.05. All statistical analyses were performed using SAS® Software (version 9.3, SAS Institute Inc. Cary, NC).

102 RESULTS Substrate materials, seasonality, and depth affect zebra mussel adherence rates significantly (Two-way ANOVA, F=7.56, P < 0.01). Posthoc multiple comparisons demonstrate that he adherence rates were significantly higher on cast iron than PVC substrates (P < 0.01), and the settlement of larval veliger’s was highest from later summer to early fall (P < 0.01), and substrates at 1 m had significantly higher mussel colonization than substrates at 10 m (P < 0.05).

DISCUSSION

Zebra mussels adhered to both PVC and cast iron substrates. Zebra mussel colonization was greater on cast iron than on PVC. Our cast iron substrates experienced oxidation, which created a rough surface for the mussel adherence. Cast iron follows a bimodal trend for pit depth with increased exposure period (Melchers 2013). PVC is not susceptible to oxidation, and does not experience pitting. Due to the nature of these surfaces, there may be an effect on the byssus’ ability to adhere due to the homogeneous smooth PVC surface (Bos et al. 2000). Due to the pitting on the cast iron, the actual surface area per square meter was greater than that of the PVC, which may allow stronger attachment of byssal threads. The pits in the cast iron change the hydrodynamics of the water interacting with the substrate, possibly allowing the veligers to settle and metamorphose (Figure 1) more effectively. Zebra mussels prefer sheltered areas and edge space (Yoo et al. 2014).

Our data indicate that competent veligers were in highest abundance during sampling period 3 (Table 2). Zebra mussel growth rates are temperature dependent. The threshold for initiation of adult shell growth in English and Russian reservoirs was 11°-12°C (Morton 1969). The mean temperatures of Otsego Lake at a depth of 1 m are 16.2°, 21.7°, and 19.6°C for sampling periods 1, 2, and 3 respectively. The optimum temperature for mussels of different geographical regions ranges between 18°C and 22 °C (Schneider 1992; McMahon 1996). Variations in temperature between sampling periods may provide insight into the trends observed in our data. Substrates in the water for a longer duration will have larger zebra mussels. Due to biofilm accumulations, smaller settled veligers could have been potentially overlooked although we used proper and thorough microscopy techniques. The unequal duration of sampling periods may provide a bias for larger targets.

103 Table 2. Spatial and seasonal variations of zebra mussel colonization on PVC and cast iron substrates. Sampling Periods range from 18-May-13 to 6-Oct-13 (Table 1).

Sampling Period Depth (m) Material Mean Standard Deviation Replicates 1 1 PVC 0 0 4 1 10 PVC 0 0 4 2 1 Cast Iron 0.5 0.3 4 2 1 PVC 0.5 0.5 4 2 10 Cast Iron 0 0 4 2 10 PVC 0 0 4 3 1 Cast Iron 10.8 7.6 4 3 1 PVC 1.2 1.1 4 3 10 Cast Iron 0.3 0.3 4 3 10 PVC 0.5 0.4 4

CONCLUSION Competent zebra mussel veligers are most abundant in Otsego Lake from later summer to early fall. Adherence rates show that zebra mussel recruitment to cast iron is significantly higher than PVC.

REFRENCES Horvath, T. 2008. Economically viable strategy for prevention of invasive species introduction: Case study of Otsego Lake, New York. Aquat Invasions 3(1): 3-9.

Melchers, R. 2013. Long-term corrosion of cast irons and steel in marine and atmospheric environments. Corros Sci 68:186-194.

McMahon, R.F. 1996. The physiological ecology of the zebra mussel, Dreissena polymorpha, in North America and Europe. Am Zool 36:339–363.

Morton, B.S. 1969. Studies on the biology of Dreissena polymorpha Pall. III. Population dynamics. Proc Malacol Soc Lond 38:471-482.

Schneider, D.W. 1992. A bioenergetics model of zebra mussel, Dreissena polymorpha growth in the Great Lakes. Can J Fish Aquat Sci 49:1406–1416.

Yoo, A., P. Lord and W.H. Wong. 2014. Zebra mussel (Dreissena polymorpha) monitoring using navigation buoys. Manag Biol Invasion 5(2):159–163.

104 Distribution of Nitellopsis obtusa (Starry stonewort) in Canadarago Lake, NY

Rebecca Russell1 and Madeline Genco2

ABSTRACT

In 2010, a survey of aquatic macrophytes was performed on Canadarago Lake, Richfield, New York (Smith 2011). During that survey an invasive exotic species of macroalgae was found, Nitellopsis obtusa or starry stonewort. This current survey was conducted to look at the changes in the distribution of this invasive species. Sampling was conducted using the Point Intercept Rake Toss Relative Abundance Method (PIRTRAM, Lord and Johnson 2006) at 74 sites around the lake. Plants were collected three times at each sample point; data were analyzed to show abundance in the lake. Thus far, starry stonewort has spread in Canadarago Lake, though it remains sparse in areas in which it was not present in 2010.

INTRODUCTION

Canadarago Lake (Figure 1) is located south of Richfield Springs New York, in northern Otsego County. Its watershed is comprised of wooded, rolling hills (~55%) and agricultural fields (~33%) (Albright and Waterfield 2012). The lake measures about 4 miles (6.5 km) long and 1.4 miles (2.2 km) across and drains into Oaks creek at the south end. Recreational usage of the lake is high in the summer due to the lake houses lining the shore; the lake’s primary uses include boating and fishing (Albright and Waterfield 2012). As of 2013, there were about 625 residences (seasonal and permanent) along the lake’s shore (Bailey 2014). As part of an effort to develop a “State of the Lake” report, the aquatic plant community was surveyed during the summer of 2010 (Smith 2011, Albright and Waterfield 2012). The survey from 2010 documented the relative abundance all plants sampled at 13 sites. During that survey an exotic, invasive species of macroalga was discovered, Nitellopsis obtusa or starry stonewort, near the north end of the lake. The primary intent of the current (2014) survey was to document changes in the distribution of starry stonewort in the lake. While surveying, we also recorded the presence of Chara sp. (muskgrass). Both starry stonewort and Chara are multicellular green algae, though their growth form resembles that of vascular macrophytes. The former species reportedly favors more alkaline, hard water conditions while the latter favors more acid, soft water conditions (Penn State 2015). Starry stonewort is an aggressive aquatic nuisance species which often outcompetes Chara, as well as most other submerged aquatic plants (Pullman and Crawford 2010). Chara and starry stonewort were compared to evaluate a suspicion that the former often displaces the later,

1 BFS W.N. Harman Internship, summer 2014. Current affiliation: SUNY Oneonta. 2 SUNY Oneonta Biology Department Intern, summer 2014. Curent affiliation: SUNY Oneonta.

105 with the two rarely cohabitating (Harman and Albright 2014). All other species collected, taken together, were also evaluated. We conducted this survey using Point Intercept Rake Toss Relative Abundance Method (PIRTRAM; Lord and Johnson 2006), sampling along the littoral zone of the lake at semi-regular intervals.

Figure 1. Bathymetric map of Canadarago Lake, Otsego County, New York. Contours and scale in feet.

106 METHODS

To utilize the Point Intercept Rake Toss Relative Abundance Method (PIRTRAM), a double-headed garden rake, attached to a cord with the length of about 10m (33 feet), was employed. PIRTRAM is an effective method in approximating relative abundance and frequency of aquatic plants that are submerged (Lord 2006), though does not fully describe the community. The survey was conducted between 11 and 14 August 2014. At each site, samples were collected in triplicate. The rake was tossed, allowed to settle, and pulled back slowly to the boat. For each toss, the rake was thrown in a different direction from the boat to get a more complete survey of plants within the site. Use of a motorized boat and GPS were then used for navigation and site marking along the lake. GPS waypoints were marked and the vegetation from each toss was separated as Chara, starry stonewort and others. Each of these three groups had its abundance estimated according to Table 1 and the three replicate samples were averaged for each site. For mapping purposes, these values were translated into values of 0, 1, 2, 3, or 4, indicating abundance, correlating with total dry weight measurements (Table 1). These data points were then plotted, using GIS, onto the base map of Canadarago Lake. Symbols were assigned to express these abundance categories.

Table 1. Biomass range estimate of plants in g/m2, by species, utilized in the rake toss (PIRTRAM) method. Mid values were used as estimates in Figures 2 and 3. * indicates a new category added to PIRTRAM that was needed for the GIS mapping.

Map Total Dry Abundance Abundance Weight Categories Field Measure Categories* (g/m^2) Mid Low High "Z"= No Plants Nothing 0 0 0 0 0 "T"= Trace Plants Fingerful 1 0.1-2 1 0.1 2 "S"= Sparse Plants Handful 2 2-140 71 2 140 "M"= Medium Plants Rakeful 3 141-230 185 140 230 "D"= Dense Plants Can't bring in Boat 4 230-450+ 340 230 450+

RESULTS & DISCUSSION

Figures 2 and 3 both show the 74 sampling sites taken during this survey. In both of these figures, the abundance estimates of starry stonewort are given as circles ranging in shading from white, indicating its absence (category “0”) to black, indicating category “4”. In Figure 2, these circular symbols are embedded in square symbols, which likewise indicate the abundance estimates of Chara. Starry stonewort abundance is presented identically in Figure 3; here, those circular symbols are embedded in hexagonal symbols, which similarly represent the abundance estimates of “all other plants”.

107 The methodologies employed during the 2010 survey (Smith 2011) were somewhat different than those of 2014. Only thirteen sampling sites were evaluated, and rather than being precise, GPS-derived sites, they represented more general areas of the littoral zone of Canadarago Lake (the intention was to not only evaluate the spatial distribution, but also the temporal distribution. Sampling occurred on six dates between 6 June and 12 July 2010). To compare these distributions to those of 2014, the data were presented as similarly as possible for mapping purposes. Figure 4 presents the distribution and abundance estimates of starry stonewort and Chara in these sampling areas on 12 July 2010 (the date that most closely matched the 2014 effort). Figure 5 compares the same for starry stonewort and “all other plants”.

In both 2010 and 2014, Chara was considerably more widespread and was typically present at higher abundances than was starry stonewort (Figures 2 and 4). In the earlier survey, starry stonewort was confined to the northwestern most region of the lake, where it was quite dense, contributing about 300 g/m2 of the total 600+ g/m2 of the plant community (Figure 4 and 5). By 2014, while not particularly widespread, starry stonewort was encountered at three additional locations (represented by six sampling locations) (Figures 2 and 3). The densities at those more recently established patches ranged from about 1 g/m2 to about 180 g/m2. Those new sites are scattered around the perimeter of the lake, and may allow for a speedy advance of this species.

The expansion and establishment of starry stonewort in Canadarago Lake has not been as swift as has been documented elsewhere in central New York. In Moraine Lake, Madison County, from the time that it was first documented in a particular region of the lake until it was overwhelmingly dominant was typically one year (Harman and Albright 2014). The slower expansion seen to date in Canadarago Lake could be due to the luxuriant growth of established plants throughout the lake’s littoral zone. Established plant beds limit the opportunity for the spread because they provide few openings in which starry stonewort can take hold. Note that where Chara is not particularly abundant (Figure 2), “other plants” are (Figure 3).

108

Figure 2. Canadarago Lake with 74 sampling sites comparing starry stonewort abundances vs. Chara sp. in August 2014. Number category in legend corresponds to Table 1: PIRTRAM chart.

109

Figure 3. Canadarago Lake with 74 sampling sites comparing starry stonewort abundances vs. “Other” aquatic plants, excluding Chara sp. in August 2014. Number category in legend corresponds to Table 1: PIRTRAM chart.

110

Figure 4. Abundance estimates of starry stonewort and Chara in selected areas of Canadarago Lake on 12 July 2010 (Smith 2011).

111

Figure 4. Abundance estimates of starry stonewort and all other plants in selected areas of Canadarago Lake on 12 July 2010 (Smith 2011).

112 REFERENCES

Albright, M. and H. Waterfield, 2012. Aquatic Macrophytes (Plants). In The State of Canadarago Lake, 2011. Tech. Rept. #30. SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta. Pp.71-85.

Bailey, C.L. 2014. Canadarago Lake watershed partnership: Watershed protection plan. Created as a part of SUNY Oneonta MS thesis in Lake Management. SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta.

Harman, W.N. and M.F. Albright. 2014. Aquatic macrophyte management plan facilitation, Lake Moraine, Madison County, NY 2013. In 46th Ann. Rept. (2013). SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta.

Lord, P.H. and R. L. Johnson, 2006. Aquatic plant monitoring guidelines. http://www.dec.ny.gov/docs/water_pdf/aquatic06.pdf

Penn. State College of Agricultural Science. 2015. http://extension.psu.edu/natural- resources/water/ponds/pond-management/aquatic-plants/chara-and-nitella

Pullman, G.D. and G. Crawford. 2010. A decade of starry stonewort in Michigan. Lakeline summer 2010. North American Lake Management Society. 30(2):36-42.

Smith, T.F. 2011. 2010 Canadarago Lake aquatic macrophyte survey. In 43rd Ann. Rept. (2010). SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta.

Swistock, B. and Smiles, H., 2014. Chara and Nitella. Penn State College of Agricultural Sciences. 15 August 2014. http://extension.psu.edu/natural- resources/water/ponds/pond-management/aquatic-plants/chara-and-nitella

113 2014 aquatic invasive species surveys of New York City water supply reservoirs within the Catskill/Delaware and Croton Watersheds

Megan Wilckens1, Holly Waterfield2 and Willard N. Harman3

INTRODUCTION

The New York City Department of Environmental Protection (DEP) oversees the management and protection of the New York City water supply reservoirs, which are split between two major watershed systems, referred to as East of Hudson Watersheds (Figure 1) and Catskill/Delaware Watershed (Figure 2). The DEP is concerned about the presence of aquatic invasive species (AIS) in reservoirs because they can threaten water quality and water supply operations (intake pipes and filtration systems), degrade the aquatic ecosystem found there as well as reduce recreational opportunities for the community. Across the United States, AIS cause around $120 billion per year in environmental damages and other losses (Pimentel et al. 2005). The SUNY Oneonta Biological Field Station was contracted by DEP to conduct AIS surveys on five reservoirs; the Ashokan, Rondout, West Branch, New Croton and Kensico reservoirs. Three of these reservoirs, as well as major tributary streams to all five reservoirs, were surveyed for AIS in 2014. This report details the survey results for the Ashokan, Rondout, and West Branch reservoirs, and Esopus Creek, Rondout Creek, West Branch Croton River, East Branch Croton River and Bear Gutter Creek. The intent of each survey was to determine the presence or absence of the twenty- three AIS on the NYC DEP’s AIS priority list (Table 1). This list was created by a subcommittee of the Invasive Species Working Group based on a water supply risk assessment. This study will help the DEP by notifying them if and where AIS have made it into the reservoirs or their tributaries so they can take the appropriate steps to eradicate them before they become established and cause serious environmental or economic damage. Surveys of the New Croton and Kensico reservoirs are planned for 2015, though in October 2014, Hydrilla was found in the New Croton. Rapid response survey work has been conducted by DEP, BFS, NYS Dept. of Environmental Conservation, among others, and 2015 work plans will be amended as necessary.

Concurrent work on the use of environmental DNA (eDNA) to determine AIS presence/absence is underway (Newton 2014). Genus-specific primers based on the DNA of Orconectes rusticus, Corbicula fluminea, Driessena polymorpha, Hydrilla verticillata, Myriophyllum spicatum and Cipangopaludina chinensis will be developed in the hopes that analysis of water samples can yield presence/absence data, reserving time-intensive field surveys for areas where AIS are known to be present.

1BFS Intern, summer 2014. Current Affiliation: Le Moyne College, Syracuse, NY. Supported by NYSDEP contract # CAT-421. 2 CLM. Research Support Specialist. SUNY Oneonta Biological Field Station. 3 CLM. Distinguished Service Professor. Rufus J. Thayer Otsego Lake Research Chair and Director.

114

Figure 1. Map of the East of Hudson Watersheds. The Croton Watershed includes West Branch Reservoir (surveyed in 2014) and Kensico and New Croton Reservoirs (to be sampled in 2015) (From Anonymous 2007a).

115

Figure 2. New York City Department of Environmental Protection’s map of the Catskill/Delaware Watershed (West of Hudson). Two of the sampled reservoirs are located in this watershed: Ashokan and Rondout (From Anonymous 2007b).

Invasive Species of Concern, Mechanisms of Spread & Impacts of Establishment Since native species have already filled the niches of a particular ecosystem, invasive species must be “fundamentally different from the resident species,” meaning Theymust have “advantageous properties” that would help them out-compete the native community (Thompson 1991). A successful invasion of a natural community requires dispersal, establishment, and survival (Hobbs 1989). There are several factors that should be taken into account when attempting to see if an invasive species will colonize an area. Propagule pressure (the measure of number of individuals of a species per release event and the number of release events), a new species’ traits as well as the invasibility of the environment all play important roles in the successfulness of an invasive species (Lonsdale 1999).

116 Table 1. New York City Department of Environmental Protection priority aquatic invasive species list. These were the species this survey focused on in the five tributaries and reservoirs.

Organism Type Scientific Name Common Name Aquatic Invertebrate Corbicula fluminea Asiatic Clam Aquatic Invertebrate Cipangopaludina chinensis Chinese Mystery Snail Aquatic Invertebrate Bithynia tentaculata Faucet Snail Aquatic Invertebrate Cercopagis pengoi Fish Hook Water Flea Aquatic Invertebrate Cordylophora caspia Freshwater Hydroid Aquatic Invertebrate Potamopyrgus antipodarium New Zealand Mud Snail Aquatic Invertebrate Dreissena bugensis Quagga Mussel Aquatic Invertebrate Orconectes rusticus Rusty Crayfish Aquatic Invertebrate Bythotrephes longimanus Spiny Water Flea Aquatic Invertebrate Dreissena polymorpha Zebra Mussel Aquatic Invertebrate Eriocheir sinensis Chinese Mitten Crab Aquatic Plant Egeria densa Brazilian Waterweed Aquatic Plant Didymosphenia geminata Didymo Aquatic Plant Hydrocharis morsus-ranae L. European Frogbit Aquatic Plant Trapa natans Water Chestnut Aquatic Plant Hydrilla verticillata Hydrilla Aquatic Plant Myriophyllum spicatum Eurasian Watermilfoil Aquatic Plant Myriophyllum aquaticum Parrot’s Feather Aquatic Plant Myriophyllum heterophyllum Variable-leafed Watermilfoil Aquatic Plant Fallopia japonica Japanese Knotweed Aquatic Plant Lythrum salicaria Purple Loosestrife Aquatic Plant Phragmites australis Common Reed Aquatic Plant Potamogeton crispus Curly Leaf Pondweed

The invasibility of an environment is largely influenced by anthropogenic activities. Reservoir construction has shaped the face of numerous landscapes around the world and as a result has led to the rapid increase in AIS throughout waterways. Reservoirs are considered “stepping- stones” for the spread of invaders (Havel et al. 2005). As humans construct reservoirs and build dams to fill them, altering the flow of water, they disturb habitats and the native species inhabiting them and therefore allow AIS to fill the resulting empty niches. Invasive species, without natural predators and little competition, are able to establish themselves in the early stages of community succession (Havel et al. 2005). Connections between reservoirs and their tributaries allow AIS to move from one habitat to the next, spreading at rapid rates.

Some invasive species pose more of a threat than others and are considered nuisance species. Several AIS on the DEP’s list should be of more concern than others, due either to their threat to the economic attributes of the reservoir or their ecological aspects. Those having more of an economic threat to the reservoirs include Myriophyllum spicatum (Eurasian watermilfoil), Potamogeton crispus (curly leaf pondweed) and Hydrilla verticillata (hydrilla). Myriophyllum spicatum and P. crispus have characteristics that allow them to dominate the water body. These two

117 species have an “ability to rapidly propogate vegetatively, have an opportunistic nature for obtaining nutrients, and enhanced photosynthetic efficiency” (Nichols & Shaw 1986). Hydrilla verticillata also forms dense vegetative mats, spreading through plant fragmentation and turions, and by producing tubers that can remain dormant for several years before sprouting (Balyszak 2013). These traits enable them to overcrowd water bodies (inhibiting boat traffic and impeding fishing activities), and foul water system infrastructure through clogging of water intake pipes and filtration systems resulting in large damage costs.

Two AIS that are threats to both the economic and ecological aspects of reservoirs are Trapa natans (water chestnut) and Dreissena polymorpha (zebra mussels). Trapa natans is an aquatic plant that forms extensive, dense beds on the surface of water bodies. This characteristic inhibits boating but it also blocks incoming sunlight to the lower water levels, shading out submerged plants and microscopic species that are important in the natural food web associated with that body of water (Hummel & Kiviat 2004). Dreissena polymorpha spreads rapidly and can cover vast expanses of substrate, including intake pipes and filtration systems, sometimes causing up to $1 billion in maintenance (Connelly et al. 2007). They are filter feeders and that can cause major community changes as energy and nutrients are being directed away from the surrounding benthic invertebrates (Hebert et al. 1989).

Several other AIS pose greater threats to the functioning of reservoirs, from Fallopia japonica (Japanese knotweed), Phragmites australis (common reed), Lythrum salicaria (purple loosestrife) to Orconectes rusticus (rusty crayfish). Fallopia japonica spreads vegetatively through rhizomes, creating dense monocultures that crowd out native plant species, diminishing the available habitat native fauna depend on (Forman & Kesseli 2002). Phragmites australis is similar in that it dominates shortgrass communities by forming tall, dense, monotypic stands (Windham & Lathrop 1999) along the shorelines and in shallow waters. It often displaces strands of Typha (cattails) which help remove toxins from water bodies and therefore degrades the water quality of these reservoir systems. Lythrum salicaria is spreading at a rate of 115,000 ha/year (Thompson et al. 1987) and is a threat to wetland communities, outcompeting native plant species like Typha and displacing native fauna that depend on the native flora. Orconectes rusticus, on the other hand, is an invertebrate aquatic invasive species. They dominate native crayfish species through competition and hybridization. They also eat more than the native species, ranging from fish eggs to small fish (threatening fish populations), benthic invertebrates, detritus to aquatic plants (which are important for shelter, nesting substrate and erosion control) without which, would cause a variety of problems in the food web (Gunderson 2008).

Due to their rapid spreading capabilities, the DEP has implemented programs and regulations to try to stop aquatic invasive species from spreading to new, unaffected areas. Since 1992 the DEP has required all recreational boats entering their water bodies to be cleaned with water at 140°F in order to keep aquatic hitchhikers from moving between water bodies. In more recent years the DEP has worked with the Catskill Regional Invasive Species Partnership (CRISP) and SUNY Oneonta’s Biological Field Station to check boat launch sites and boats for AIS. Their method of preventing the spread of AIS on boats and equipment involves checking boats for invasive species, draining, disinfecting and cleaning the boat and letting it dry before entering another water body. This study is another way the DEP is working to stop the spread of AIS, through early detection and quick response.

118 METHODS

A survey protocol was developed based on the data sheet presented in Figure 3 and was employed at each survey site. Reservoir sampling sites were determined at the time of the survey; we aimed to obtain relatively even coverage around the reservoir shoreline, sample a variety of habitat conditions, and note all AIS observed. Each reservoir survey included both shoreline and open-water sites, which were accessed by motorboat following DEP security and safety protocols; all BFS personnel were authorized to access the reservoirs and were issued DEP identification cards (worn at all times). Tributary sites were located upstream of the reservoir’s influence where the stream could be accessed by road (within 500 ft from confluence with the reservoir). A multitude of sampling techniques were used at each site in order assess invertebrate, plant, and algae communities for the presence/absence of the 23 previously mentioned AIS of concern to the DEP (Table 1). Between shoreline sample sites, the shoreline was observed with binoculars to note the presence of scattered individuals (such as L. salicaria) that were already documented at multiple sites around the reservoir.

Tributary and reservoir shoreline site sampling procedure was as follows. Substrate sieving, triangle nets, and hand picking were used in the stream beds and from the reservoir shoreline outward to a water depth of roughly 1 meter to determine the presence or absence of invasive benthic invertebrates. A plant rake (fashioned from two garden rake heads welded back to back) was used to assess submerged rooted plants in zones where such plant growth was anticipated (littoral zones). General observations were made along the shoreline for emergent plants, macrophyte fragments, and algae on rocks, etc. In the case of reservoir sites, additional observations of submerged aquatic plant communities were made when approaching and leaving the shoreline. In the case that specimens could not be definitely identified in the field, verifications were made at the BFS laboratory, using a dissecting microscope when necessary. Invertebrate specimens were preserved with 70% ethanol in labeled vials or museum jars; plant specimens were bagged and labeled accordingly. At open water sites on the reservoirs, water depth was determined using a depth sounder to assess suitability for rake toss sampling. Zooplankton were collected with a 80 µm mesh plankton net towed behind the boat; samples were inspected on-board for conspicuous zooplankton, preserved with 70% ethanol and brought back to the BFS for microscopic assessment.

Habitat type and sampling logistics for each site were detailed on the collection form. Habitat description included whether the site was lentic or lotic, in addition to the substrate conditions: decomposing organic matter, mud, sand, gravel, cobble, and/or boulder. Sampling logistics included substrate sieving, hand picking, plankton tow, rake toss, observation and microscopic evaluations, which meant using all of the sampling techniques at a site.

Data collected at each site were recorded both on digitally and on paper forms (Figure 3). The location/ reservoir name, site number, date, collector names, and coordinates were recorded, including any additional comments relevant to the site. Positional data (GPS coordinates) were obtained with a Trimble GeoXT device. TerraSync software interface was programmed by DEP GIS specialists to meet DEP data quality requirements and to allow for the input of survey data at each site location. Photos were taken for documentation.

119

Figure 3. NYCDEP Aquatic Invasive Species Survey Sample Sheet used in the field for recording the presence/absence of species as well as site conditions and how and where they were found.

120 When travelling between tributaries or reservoirs we rinsed our shoes and equipment in salt water to disinfect them before entering another waterway. The boat and trailer was power washed with hot water in order to remove any specimens that may have gotten in or stuck to the equipment so as not to transport invasive species from one waterway to the next.

Data files were uploaded to a desktop computer using the Data Transfer application and emailed to the DEP Invasive Species Specialist for GPS correction and validation, as required for NYC DEP’s data quality assurance. Maps were created from the resulting GIS datasets by the DEP’s Invasive Species Specialist.

RESULTS

Table 2 lists the tributaries and their corresponding reservoirs where AIS were surveyed and recorded as either present or absent. Note that species observed in the tributaries are not always found in the connected reservoir and some reservoirs with many AIS did not have any in their tributaries. This implies there are various means by which introduction of AIS into the reservoirs occurs as well as directly by boats carrying AIS from other water bodies.

Table 2. 2014 Sites for New York City Department of Environmental Protection aquatic invasive species survey. Listed are the aquatic invasive species found in each tributary and reservoir.

Tributary AIS Present Reservoir AIS Present Esopus Creek Fallopia japonica Ashokan None Rondout Creek Fallopia japonica Rondout Lythrum salicaria Orconectes rusticus Phragmites australis Potamogeton crispus West Branch Croton None West Branch Lythrum salicaria River Myriophyllum spicatum Orconectes rusticus Phragmites australis East Branch Croton Orconectes rusticus New Croton Hydrilla verticillata River Bear Gutter Creek None Kensico Not sampled

The following figures are maps constructed using a geographic information system compiling the data collected in the field. These maps show labeled points and/or lines where AIS was either present or absent at points along the shoreline where data was collected. Figures 4 through 10 indicate AIS on Esopus Creek, Ashokan Reservoir, Roundout Creek, Roundout Reservoir, West Branch Reservoir, East Branch Croton River and Bear Gutter Creek.

121

Figure 4. Aquatic invasive species survey at Esopus Creek, a tributary of Ashokan Reservoir. A stand of F. japonica was found at this site.

122

Figure 5. Aquatic invasive species survey of Ashokan Reservoir. No AIS were found in the reservoir.

123

Figure 6. Aquatic invasive species survey of Rondout Creek, a tributary of Rondout Reservoir. Fallopia japonica was found at this site.

124

Figure 7. Aquatic invasive species survey of Rondout Reservoir. Lythrum salicaria, O. rusticus, P. australis and P. crispus were all found within the reservoir. (Lythrum salicaria is not located on this map).

125

Figure 8. Aquatic invasive species survey of West Branch Reservoir. Lythrum salicaria, M. spicatum, O. rusticus and P. australis were all found within the reservoir.

126

Figure 9. Aquatic invasive species survey of East Branch Croton River, a tributary of New Croton Reservoir. Orconectes rusticus was found at this site.

127

Figure 10. Aquatic invasive species survey of Bear Gutter Creek, a tributary of Kensico Reservoir. No AIS were found at this site.

DISCUSSION

The presence of aquatic invasive species within these NYC reservoirs as well as their tributaries is of concern to the NYC DEP because they threaten the well-being of these vital fresh water bodies. This study provides the DEP office with information that could help them develop policies that will help prevent the spread of AIS and lower costs for control and eradication in the future. Costs of ecological and economic damages and controlling invasive species in the United States reach into the millions of dollars for individual species and into the billions of dollars when taking into account the 50,000 invasive species in the United States (Pimentel et al. 2000). Possible plans to manage AIS include physical, biological and chemical options (Harman et al. 2003). Since AIS were found in three of the five tributaries and at least four of the five reservoirs, steps need to be taken to control AIS movement through recreational vehicles entering and exiting the waterways. By surveying and mapping AIS found in the reservoirs, the DEP can take appropriate action to prevent further damage to ecosystem health and essential infrastructure (water intake pipes) by targeting these specific species.

128 REFERENCES

Anonymous, 2007a. Croton Watershed Map. NYC Department of Environmental Protection, New York City. Web. 25 Aug 2014. .

Anonymous, 2007b. Catskill/Delaware Watershed Map. NYC Department of Environmental Protection, New York City. Web. 25 Aug 2014. .

Balyszak, J.A. 2013. Hydrilla treatments continue in 2013. Sustainable Tompkins, Retrieved from http://sustainabletompkins.org/signs-of-sustainability/hydrilla-treatments-continue-in-2013/

Connelly, N. A., Jr., C.R O'Neill, B.A. Knuth & T.L. Brown. 2007. Economic impacts of zebra mussels on drinking water treatment and electric power generation facilities. Environmental Management, 40(1), 105-112. doi: 10.1007/s00267-006-0296-5

Forman, J. & R.V. Kesseli. 2002. Sexual reproduction in the invasive species Fallopian japonica (polygonaceae). American Journal of Botany, 90(4), 586-592. doi: 10.3732/ajb.90.4.586

Gunderson, J. 2014. Rusty crayfish: a nasty invader; biology, identification, and impacts. Minnesota Sea Grant. N.p., n.d. Web. 24 Jul 2014. .

Harman, W.N., M.F. Albright, P.H. Lord 2003. Aquatic macrophyte management plan facilitation lake moraine, madison county, NY . BFS Tech. Rept. No. 15. In 35th Ann. Rept. (2002) SUNY Oneonta Bio. Fld. Sta., SUNY Oneonta.

Havel, J.E., C.E. Lee, & M.J.V. Zanden, 2005. Do reservoirs facilitate invasions into landscapes? BioScience, 55(6), 518-525.

Hebert, P.D.N., B.W. Muncaster & G.L. Mackie. 1989. Ecological and genetic studies on Dreissena polymorpha (pallas): a new mollusc in the great lakes. Canadian Journal of Fisheries and Aquatic Sciences, 46(9), 1587-1591. doi: 10.1139/f89-202

Hobbs, R. J. 1989. The nature and effects of disturbance relative to invasions. Trans. Array Biological Invasion: a Global Perspective. New York: Wiley & Sons. 389-405.

Hummel, M., & E. Kiviat. 2004. Review of world literature on water chestnut with implications for management in north america. Aquatic Plant Management, 42, 17-27. Retrieved from http://www.apms.org/japm/vol42/v42p17.pdf

Lonsdale, W.M. 1999 Global patterns of plant invasions and the concept of invasibility. Ecology, 80, 1522-1536.

129 Newton, L. 2014. Utilizing environmental DNA to identify aquatic invasive species. In: 46th Ann. Rept. (2013). SUNY Oneonta Bio. Fld. Sta., SUNY Oneonta.

Nichols, S.A. & B.H. Shaw. 1986. Ecological life histories of the three aquatic nuisance plants, Myriophyllum spicatum, Potamogeton crispus and Elodea canadensis. Hydrobilogia, 131, 3-21.

Pimentel, D., L. Lach, R. Zuniga & D. Morrison. 2000. Environmental and economic costs of nonindigenous species in the united states. BioOne, 50(1), 53-65.

Pimentel, D., R. Zuniga & D. Morrison. 2005. Update on the environmental and economic costs associated with alien-invasive species in the united states. Elsevier, 52(3), 273- 288. doi: 10.1016/j.ecolecon.2004.10.002

Thompson, D.Q, R.L Stuckey and E.B. Thompson. 1987. Spread, impact, and control of purple loosestrife (Lythrum salicaria) in North American wetlands. US Fish and Wildlife Service, Fish and Wildlife Research 2, Washington, DC, 55 pp

Thompson, J.D. 1991. The biology of an invasive plant. Bioscience, 41(6), 393-401.

Windham, L.M., & J.R.G. Lathrop. 1999. Effects of Phragmites australis (common reed) invasion on aboveground biomass and soil properties in brackish tidal marsh of the Mullica River, New Jersey. Estuaries, 22(4), 927-935.

130 Potassium permanganates effect on zebra mussel adults and veligers

Benjamin P. Coyle1 , Paul H. Lord2, Wai Hing Wong2 and Matthew F Albright2

ABSTRACT

Municipalities worldwide are experiencing problems caused by invasive mollusks. An infestation of Dreissena polymorpha (zebra mussel) to Otsego Lake, New York, is causing problems for water treatment plants, including the Cooperstown Water Treatment Plant. Zebra mussel colonization of water intake pipes impedes water flow and clogs filters. Chemical control of these aquatic pests is currently necessary to maintain efficiency at municipal plants. Monitoring PVC and cast iron substrates determined the seasonality of zebra mussel fouling. Observed adherence rates of the two substrata show the greatest mussel colonization occurred on cast iron substrates at the end of the summer. These data delineate the seasonality of Otsego Lake’s infestation. In conjunction, a laboratory experiment exposed zebra mussel adults and veligers to varying concentrations of potassium permanganate (KMnO4). We determined mortality rates based on time of exposure and KMnO4 concentration. Targeting the veliger is more effective than targeting the adult mussel because veliger mortality due to KMnO4 occurs at a lower concentration and in a shorter amount of time than the adult mussels. For maximum effectiveness as a zebra mussel control method, we recommend that KMnO4 dosing should occur when veliger numbers are at their peaks.

INTRODUCTION

Zebra mussels (Dreissena polymorpha) and quagga mussels (Dreissena rostriformis bugensis) are among the world's most economically and ecologically damaging aquatic invasive species (Aldridge et al. 2006; Connelly et al. 2007) and they are among the most serious nonindigenous biofouling pests introduced to North American freshwaters (LaBounty and Roefer 2007). Municipalities worldwide experience problems caused by these invasive mollusks. Annual maintenance costs at water intakes due to dreissenid mussels alone are an estimated $267M in North America (Pimentel et al. 2005).

Zebra mussels were discovered in Otsego Lake (NY, USA) in 2007 (Horvath 2008). Otsego Lake (Figure 1) lies at the headwaters of the Susquehanna River, whose drainage basin makes up 43 percent of the total drainage to Chesapeake Bay. Zebra mussels have become a nuisance for the Cooperstown Water Treatment Plant (CWTP) as mussels clog water intake pipes from Otsego Lake and disrupt water filtration (Watters et al. 2013). Mussel adherence occurs on a multitude of surfaces, rocks, woods, plastics, ropes, and metals such as a steel and iron. The CWTP intake line is a 0.355 m diameter cast iron pipe, which extends approximately 1310 m from the treatment plant into Otsego Lake, making it prone to fouling.

1 BFS Intern, summer 2014. Current affiliation: SUNY Oneonta. Funding provided by The Village of Cooperstown. 2 SUNY Oneonta Biological Field Station.

131

Figure 1. Otsego Lake, NY. Sampling sites: Five Mile Point (42°45.901′N, 74°53.882′W), Pegg’s Point (42°46.719′N, 74°52.791′W), Three Mile Point (42°45.127′ N, 74°53.443′W), Point Judith (42°43.713′N, 74°54.413′W). At each site, a cast iron and PVC substrate was deployed at 1 and 10 m. CWTP refers to Cooperstown Water Treatment Plant (Cooperstown, NY)

To facilitate the creation of a management action plan, the behavior of zebra mussels on and around the intake pipe materials must be understood as well as KMnO4’s effect on different zebra mussel life stages. The zebra mussel life cycle is depicted in Figure 2. It was found that competent zebra mussel veligers are most abundant in the water during the late summer and early fall (Coyle et al. 2015). This information can be utilized when deciding when to dose the CWTP intake with potassium permanganate (KMnO4) as a control agent for zebra mussels. Intervention is necessary as thousands of people rely on this municipal water source.

132

Figure 2. Zebra mussel life cycle (Black 2003).

The goal of this work was to evaluate the effectiveness of KMnO4 as a control agent for zebra mussel adults and veligers. KMnO4 is highly reactive under conditions found in the water industry. KMnO4 oxidizes a wide variety of inorganic and organic substances (US EPA 1999). KMnO4 is used to remove taste and odor causing compounds from potable water (Lalezary et al. 1986). Klerks and Fraleigh (1991) evaluated the effectiveness of permanganate against adult zebra mussels and found KMnO4 dosing of 0.5 to 2.5 mg/L proved most effective. Our research tests Klerks and Fraleigh’s recommendations against various concentrations, and differing exposure times. We tested zebra mussel adults and veligers. An understanding of the biofouling of zebra mussels and how KMnO4 affects different stages of zebra mussels will be useful when providing recommendations for its use as a control method.

METHODS Potassium Permanganate Degradation

To evaluate the extent to which the KMnO4 degrades over time (which could influence the mortality experiments described below), we conducted a laboratory assessment. Using reagent grade KMnO4 we tested experimental KMnO4 concentrations of 0, 1, 2, 4 and 8 PPM. We tested 10 beakers of KMnO4 by exposing them to light and an ambient temperature of ~23°C (referred to henceforth as bench top beakers). We tested 10 other beakers of KMnO4 by storing them in dark conditions at 3°C (referred to henceforth as refrigerated beakers). Following the

133 standard spectrophotometric method (APHA 2012), we assessed the degradation of KMnO4 concentration multiple times over 72 h (i.e., 0 h, 3 h, 6 h, 24 h, 48 h and 72 h).

Adult Zebra Mussel Experiment

Prior to zebra mussel collection, we prepared aquaria for mussel habitation. We scrubbed twenty 37.8 L aquaria with plastic nonstick scrubber pads. After rinsing, we filled aquaria with filtered (64 μm mesh filter) lake water and allowed aquaria sit filled for 24 h. We then scrubbed aquaria again and air dried them for 48 h. We cleaned two large flow-through aquaria using a similar method. These aquaria provide a constant supply of raw water at the ambient temperature and conditions similar to the lake. Inflow to the tank displaces water at the draining end, causing it to overflow into a drain. Prior to mussel habitation, we placed an aquaria air stone diffuser in each experimental and holding aquaria (air flow was calibrated to create equal aeration of compressed air between all aquaria). All water used was raw water, which was pumped from Otsego Lake into the research laboratory at the Biological Field Station (Cooperstown, NY) the day the experiment was initiated. Lines were flushed by allowing a steady flow (~2 L/min) to persist for 5 min prior to filling aquaria to create a standard environment in each aquarium.

We collected all zebra mussels from Otsego Lake. We surveyed rocks from a depth of ~2 m and removed adult mussels by hand or with a metal spatula. Once removed, we placed the mussels into holding buckets until 2000 were collected (1600 mussels were collected for experimental testing and 400 to replace dead mussels prior to beginning testing as necessary). Mussels connected to one another via byssal fibers remained intact to reduce removal stress. We rinsed the mussels with lake water on site and thoroughly mixed all before randomly placing the mussels into mesh bags. We placed 11 adult mussels (shell length > 8 mm) into the corner of each bag (to promote colonization) and transported the bags to the laboratory in a bucket of lake water (~5 min transport time). We transferred the bags of mussels into the holding aquaria (60 bags/aquaria) and allowed mussels to acclimate to the new aquaria for 72 h.

Prior to experimental testing, we randomly assigned each bag of zebra mussels with a tag designating the duration of KMnO4 exposure. Prior to placing mussels into the experimental tank, we examined each bag for healthy mussels. If we found that no mussels were dead then we removed the smallest mussel. If fewer than 10 were alive, dead ones were replaced with the extras that had been collected for that purpose. Once we assessed that each bag contained 10 healthy mussels, we strung bags onto wooden dowels to suspend the mussels in the aquaria. Each dowel held 8 bags, and we randomly assigned a number to each dowel corresponding to randomly numbered aquaria.

We set up aquaria per Figure 3, bringing each aquarium to a KMnO4 concentration of 0, 1, 2, 4, or 8 PPM, with four replicates of each. We added an aqueous solution of reagent grade KMnO4 ~10 min prior to the introduction of the zebra mussels into aquaria to allow thorough mixing via turbulence created by aquaria air stone diffusers. At time zero, we carried all dowels

134 to their appropriate aquaria and submerged the mussels (the control bag labeled 0 h was removed from the dowel and returned to the holding aquaria without being submerged in any experimental aquaria).

Figure 3. Experimental aquaria protocol. Each aquarium held 7 mesh bags each of which contained 10 zebra mussels (Dreissena polymorpha). Bags were suspended in the aquaria via a wooden dowel. Aquaria were aerated with compressed air through an aquaria air stone diffuser and brought to KMnO4 a concentration of 0, 1, 2, 4, or 8 PPM.

At the end of each time interval (3 h, 6 h, 12 h, 24 h, 48 h, 72 h, and 96 h), one bag was removed from each tank, rinsed separately with filter lake water and placed into the 1st holding aquaria at the draining end. When new bags were transferred into the holding aquaria, the bags introduced prior were then transferred into the 2nd holding aquaria to avoid cross contamination. The bags were successively transported in this way since when the zebra mussels die their valves gape, expelling contents, which could be a possible source of KMnO4 introduction into the holding aquaria. Placing mussels with longer exposure to KMnO4 at the draining end of the flow-through aquaria limits exposure of the other mussels, upstream in the tank, to byproducts expelled by deceased mussels.

Evaluation of mortality consisted of probing zebra mussels after 48 h of suspension in the holding aquaria. After 48 h in the holding aquaria, we removed the mussels from their bags, patted them dry using paper towels, and assessed them for mortality. The shell length of each mussel was measured in mm using a hand caliper. After the 48 h rest period, mussels tended to have their valves slightly gaping, allowing them to filter and respire. When touched, living mussels closed their valves. If a disturbed mussel did not close its valves, it was presumed dead. Also, living mussels resist the forced opening of their shells, whereas dead mussels were easily pried open by hand.

135 Veliger Zebra Mussel Experiment We set up 25, 250 ml beakers in a grid pattern as depicted in Figure 4. All of the water used in beakers was filtered lake water. We flushed water lines by allowing a flow of ~2L/min to persist for 5 min prior to collecting water. We passed raw water through 64 μm mesh filter to remove particulates that might have affected the experiment. We homogenized 6 L of this water before adding 200 ml to each beaker to limit variability.

PPM

Figure 4. Zebra mussel (Dreissena polymorpha) veliger experimental protocol. Each oval represents one 250 ml beaker containing ~250/300 zebra mussel veligers and a corresponding KMnO4 concentration of 0, 1, 2, 4, 8 PPM. Veligers were removed from beakers and assessed for mortality after 0, 30, 60, 120 and 180 min of exposure

A 64 μm mesh plankton net was used to collect zebra mussel veligers from a site on the southern end of Otsego Lake (Figure 2). Preliminary monitoring suggested that a tow from a depth of 13 m to the surface, eight times, was sufficient for collecting the necessary number of veligers. We collected water quality parameters (pH, temperature, dissolved oxygen and conductivity) concurrent with each collection. We filtered larger zooplankton from the raw water containing veligers by pouring water from the nets collection cup through a 1000 μm net. We poured the water containing veligers into a 2 L opaque brown bottle. Samples collected were immediately brought to the lab and concentrated to a volume 250 ml via the 64 μm filter apparatus (Figure 5). We designed the 64 μm filter apparatus (Figure 5) to allow us to concentrate the samples of water containing veligers without subjecting the fragile veligers to direct suction. The 250 ml sample of concentrated veligers was homogenized and we analyzed a 1 ml sample to calculate the abundance of veligers/ml. We counted veligers on a Sedgewick Rafter counting cell slide using cross polarized light microscopy as described in Johnson (1995).

136 a

b c

Figure 5. 64 μm filter apparatus used to concentrate water samples without subjecting zebra mussel (Dreissena polymorpha) veligers to direct suction and turbulence. Picture “a” is front view showing the depth in which the filter can operate. Picture “b” is an isometric view showing the open top which allowed water to be pipetted out. Picture “c” shows that the bottom of the plastic cup is a 64 μm filter which allows water to enter the cup but leaves veligers in the sample

Using a pipette with a modified tip (~1 cm being removed from the tip enlarging the opening to avoid veliger stress), a sample of concentrated zebra mussel veligers was pipetted into the experimental beakers. With the veligers/ml of concentrated sample known, each beaker received ~250/300 veligers. Using a stock solution of KMnO4, we brought the beakers to the concentrations listed in Figure 4. Beakers for time zero received no KMnO4 and served as an extra control. After the designated time of exposure, we concentrated each beaker to a volume of about 2 ml using the 64 μm filter apparatus (Figure 5). We sampled 1 ml from each beaker on a Sedgewick Rafter counting cell slide and observed veligers using cross-polarized light microscopy as described in Johnson (1995). If a veliger appeared dead, we allotted 5 sec to observe the internal organs and assess mortality. In between each sampling, we thoroughly rinsed filters, pipette tips and counting cells with deionized water. At each time period, we tested five concentrations, and each beaker was sampled for 5 min, resulting in the last beaker for the time course not being sampled until 25 min after the first. To allow enough time to process samples and remain consistent with the time course allotted in Figure 4, KMnO4 additions were

137 staggered 5 min between concentrations for each timed exposure. This staggering assured time exposures were consistent with our experimental design. Over the course of 14 d, we carried out four replicates of this experiment. Statistics

We used a two-way ANOVA to evaluate the laboratory assessment of KMnO4. We performed a Student-Newman-Keuls post hoc multiple comparisons test to determine if the difference was significant. The significance criterion was set at a α = 0.05. All statistical analyses were performed using SAS® Software (version 9.3, SAS Institute Inc. Cary, NC).

RESULTS Potassium Permanganate Degradation

There was no difference in KMnO4 concentration between bench top and refrigerated samples. As time passed, the concentration of KMnO4 decreased (Figure 6). The most intense PPM drop was from 1 h to 20 h. After 20 h, the concentration of samples kept in a dark refrigerated environment decreased minimally, or not at all. However, the samples at room temperature continued to decrease in concentration, although this difference was not significant.

Figure 6. Degradation/oxidation of 200 ml of an 8, 4, 2, and 1 PPM KMnO4 and lake water solution in laboratory settings. Bench top beakers were exposed to light and room temperature, whereas the refrigerated samples were kept in a dark cool environment. There was no significant difference between bench top and the refrigerated samples

138 Adult Zebra Mussel Experiment Figure 7 summarizes the mortality of adult zebra mussels over time at the concentrations of KMnO4 given. Concentrations of less than 4 PPM were ineffective; at 8 PPM, mortality was observed, though about 96 hours of contact time was required for mortality to approach 50%.

60

50 oPPM

40 1PPM

30 2 PPM 4PPM 20 8 PPM 10 Average Average Mortality (%)

0 -20 0 20 40 60 80 100 120 -10 Time (Hours) Figure 7. Average mortality rate of adult zebra mussels (Dreissena polymorpha) (shell length> 8mm) exposed to 5 concentrations of KMnO4 for 8 durations of time. Error bars ±1 standard deviation Veliger Zebra Mussel Experiment

Figure 8 displays the relationship between KMnO4 concentration and time of exposure to zebra mussel veligers. At 8PPM, the highest concentration evaluated, it took 120 minutes to achieve about 50% mortality.

80

70

60 0 PPM

50 1 PPM

40 2 PPM 30 4 PPM 20

Average Average Mortality (%) 8 PPM 10

0 -50 0 50 100 150 200 Time (Minutes) Figure 8. Average mortality rate of zebra mussel (Dreissena polymorpha) veliger exposed to 5 concentrations of KMnO4 for 8 durations of time. Error bars ±1 standard deviation.

139 DISCUSSION

Our experiment shows that KMnO4 has a tendency to decrease in solution over time as it is reduced to MnO4 (US EPA 1999). This decrease in KMnO4 concentration may explain the low mortality documented in Figure 7, as duration of exposure extended to 96 h, although differentiation between the effect of KMnO4 and its byproduct MnO2 on zebra mussels is not known. Since the laboratory for the adult mussel experiment was in a communal lab space, light conditions could not remain constant, although we do not consider this variable significant.

To maintain our experimental design, we had limited time to observe individual zebra mussel veligers. A possible bias may have involved the presumption that a veliger was dead (no observed movement or organ function) when in fact it was alive. Veliger vulnerability may be due to their lack of a thick, impermeable protective calcium carbonate shell (as found on adult mussels). In the presence of oxidizing chemicals such as chlorine and KMnO4, zebra mussel adults will close their valves to avoid the chemical whereas veligers cannot (Boelman et al. 1996).

CONCLUSION

Our data confirmed the efficacy of KMnO4 for controlling zebra mussels. For maximum effectiveness as a zebra mussel control method, KMnO4 dosing should occur when veliger numbers are at their peaks, which is late summer to early fall (Coyle et al. 2015). Systematic monitoring is essential for the delineation of peak veliger abundance times. Targeting veligers with KMnO4 is more effective than targeting adult mussels because mortality due to KMnO4 occurs at a lower concentration, in a shorter amount of time for veligers. Mortality due to KMnO4 occurs at lower concentrations and in shorter times for veligers when compared to adults (depending on the concentration). To put this difference into perspective, when dosing with 8 PPM of KMnO4, it took 77 min to kill 40 % of veligers whereas 83 hours of direct exposure was necessary to kill the same percentage of adults.

ACKNOLEDGEMENTS The authors thank the Biological Field Station and their interns. They would also like to thank the Volunteer Dive Team, and their tenders for their assistance with field work. This research was supported in part by the SUNY Oneonta Student Grant Program for Research and Creative Activity, and the Cooperstown Sewer and water Board in Cooperstown, New York.

REFERENCES American Public Health Association. 2012. Standard methods for the examination of water and wastewater. Washington, D.C J Am Public Health Assoc.

Aldridge, D.C., P. Elliott, and G.D. Moggridge. 2006. Microencapsulated BioBullets for the control of biofouling zebra mussels. Environ Sci & Technol 40:975-979.

140 Boelman, S.F., F.M. Neilson, E.A. Dardeau and T. Cross. 1996. Zebra mussel (Dreissena polymorpha) control handbook for facility operators, first edition. Miscellaneous Paper EL-97-1, U.S. Army Engineer Waterways Experiment Station, Vicksburg, MS.

Connelly, N.A., C.R. O'Neill, B.A. Knuth and T.L. Brown. 2007. Economic impacts of zebra mussels on drinking water treatment and electric power generation facilities. J Environ Manage 40:105-112.

Coyle B., W.H. Wong and P.H. Lord. 2015. Biofouling of invasive zebra mussels (Dreissena polymorpha) in Otsego Lake, New York (Submitted for publication 2015). In 47th Ann. Rept. SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta.

Horvath, T. 2008. Economically viable strategy for prevention of invasive species introduction: Case study of Otsego Lake, New York. Aquat Invasions 3(1): 3-9.

Johnson, L.E. 1995. Enhanced early detection and enumeration of zebra mussel (Dreissena spp.) veligers using cross-polarized light microscopy. Hydrobiologia 312:139-146.

Klerks, P.L. and P.C. Fraleigh. 1991. Controlling adult zebra mussels with oxidants. J AWWA 83(12):92-100.

LaBounty, J.F. and P. Roefer. 2007 Quagga mussels invade Lake Mead. Lakeline 27: 17-22.

Lalezary, S., M. Pirbazari and M.J. McGuire. 1986. Oxidation of five earthy-musty taste and odor compounds. J AWWA 78(3):62.

Pimentel, D., R. Zuniga and D. Morrison. 2005. Update on the environmental and economic costs associated with alien-invasive species in the United States. Ecological Economics 52(3):273-88.

US EPA, Office of Ground Water And Drinking Water (1999) EPA Guidance Manual Alternative Disinfectants and Oxidants. Alternative Disinfectants and Oxidants Guidance Manual: Chapter 5 KMnO4, April 1999 (n.d.): n. pag. Web.

Watters, A., S.L. Gerstenberger and H. Wong. 2013. Effectiveness of EarthTec® for killing invasive quagga mussels (Dreissena rostriformis bugensis) and preventing their colonization in the Western United States. Biofouling 29(1):21-28.

141 Development of methods to characterize & extract plastic microparticles from personal cleansing products

Emily Davidson1, Cody Hastings2, Holly Waterfield3 and Kiyoko Yokota4

INTRODUCTION

Plastics debris is reportedly the largest source of anthropogenic pollution found in the marine environment (Barnes et al. 2009). Plastic microparticles, hereafter referred to as microplastics, are defined as particles 5mm or less in size, and were first considered a minor pollution source derived from degraded plastic litter. However, manufactured microplastics are now found in many personal cleansing products (Fendall and Sewell 2009) and are the focus of this research. Given their prevalence and size, microplastics have become a ubiquitous contaminant, are biologically available to microorganisms and have shown to accumulate in the guts of various organisms (Eriksson and Burton 2003). Although long-term impacts of microplastics are currently unknown, ingestion of microplastics by organisms such as plankton, mussels, worms, fish and sea birds have been widely documented (Cole et al. 2013). Ingestion of plastics by smaller organisms can cause reduced food uptake, internal injury, and possibly death from intestinal blockages or starvation (Derraik 2002). Microplastics can also bind with toxic hydrophobic contaminants such as polychlorinated biphenyls (PCBs) at the water surface, and possibly serve as a vector for organic pollutants to enter aquatic systems (Fendall and Sewall 2009). Moreover, microplastics can externally bind to algae, and inhibit photosynthesis (Bhattacharya et al. 2010). Algae play a key role in aquatic food webs and therefore, high concentrations of microplastics could severely impair those ecosystems (Wright et al. 2013).

Plastics pollution is a well-documented topic in marine ecosystems, though there is a paucity of scientific literature on plastics pollution in freshwater ecosystems (Andrady 2011). The goal of this research was three fold: to measure, quantify, and harvest the microplastics from several brands of face wash and body wash. The data collected from these preliminary observations will form the basis for future research on microplastics pollution; specifically the mode of transfer from waste stream to aquatic ecosystems and their potential impact on the growth of freshwater algae.

1 BFS Intern, summer 2014. Supported by the Otsego Land Trust. Current affiliation: Skidmore College, Saratoga, NY. 2 R.J. Thayer Intern, summer 2014. Current affiliation: Rochester Institute of Technology. 3 Research Support Specialist. SUNY Oneonta Biological Field Station. 4 Biological Field Station researcher and Assistant Professor of Biology, SUNY Oneonta.

142 METHODS

Characterization of Microplastics

Microplastics were observed and characterized microscopically and by using an imaging particle analyzer. Before observing under the microscope, about 0.5g of sample was diluted with 25ml of distilled water and homogenized. A Zeiss ® Axioskop 40 research grade digital 5 microscope station equipped with MediaCybernetics ® Image Pro Plus ® software version 5.1 was used to capture between one and ten photos of microplastics in each brand. The length of each particle was measured using the Image Pro Plus software. Magnification used ranged from 2.5x to 10x depending on particle size. Dial Powerscrub® microplastics also were photographed after the removal of soap residue.

Particle size distribution and shape characteristics for each product’s microparticles were determined using a FlowCAM Imaging Particle Analyzer6 (by Fluid Imaging Technologies). Prior to analysis, product samples were diluted in hot water, and then clarified of surfactants by alternating cycles of rinsing and harvesting of microplastics until the sample no longer produced suds.

A sample size of 1200 particles was used for all products. In some cases, more than one analysis run was required in order to achieve the desired sample size. A particle size filter was in place to exclude particles <20µm from the analysis in order to eliminate “false” particles associated with bubbles and non-plastics debris; based on the microscopic observations, no particles <30um were observed in any product. Particle size, as Estimated Spherical Diameter (ESD), was calculated for each particle by FlowCAM’s VisualSpreadsheet® Particle Analysis Software. Histograms illustrating particle size distribution for each product were created in VisualSpreadsheet® and data exported to Microsoft Excel.

Quantification and Harvesting

To determine the density of Dial Powerscrub®, the product was turned upside down, clamped, and allowed to drip into a pre-weighed beaker overnight to ensure as much product as possible was represented. In order to isolate microplastics from the soapy material of the product, various efforts were attempted. Universal to all attempts, between four and five grams of sample was diluted with 40ml of water.

The first method applied involved using vacuum filtration. Whatman TM GF/A Filter papers were dried in metal planchets in a 100ºC oven for twelve or more hours and pre-weighed. The diluted sample was poured slowly into the filtration unit and was allowed to filter, using several different vacuum pressures ranging from 5 to 14 psi. The filter paper containing plastics was dried at 100ºC for twelve or more hours and was weighed on a scale to the nearest microgram.

5 Funded through NSF, Award Number 33671. 6 Funded through NSF, Award Number 61721.

143 The second method applied involved using centrifugation. Each brand was placed into the Thermo Scientific™ Sorvall™ Legend™ X1 centrifuge to determine which separated best, Dial Powerscrub® was chosen for the harvesting portion of this experiment. The diluted samples were placed in 50ml centrifuge tubes and centrifuged for 15 minutes at 9500 x g after several trials using less gravity and less time which were less successful. As much supernatant that could be removed without disturbing the microplastics was decanted precisely using a 10ml pipet; any remaining material from the sample was added to the centrifuge tubes. This process was repeated several times to guarantee the removal of soapy materials from the microplastics. All water decanted in this method was later analyzed for lost plastic particles which, if any, were recovered and accounted for. When all soapy materials were no longer detectable by shaking with a Thermolyne ScientificTM MaxiMix II, the microplastics were decanted into pre-weighed planchets containing aluminum foil using a 10ml pipet. Aluminum foil was used because it helped reduce hydrostatic interactions that made the microplastics affix to edges of materials. The planchets were dried in an oven; any remaining material in the centrifuge tubes was added to the dry planchets. The planchets were then dried in an 100ºC oven for twelve or more hours and weighed to the nearest microgram the next day.

RESULTS AND DISCUSSION

Characterization

Use of the centrifuge to extract microplastics for imaging analysis was attempted but ultimately was deemed unsuccessful; microplastics were distorted and compacted, thus measured characteristics would not be representative of the product’s contents. The results presented here were acquired using the diluted samples viewed microscopically (for particle characterization) and those processed with the Flowcam® particle analyzer (for size distribution).

Figures 1and 2 include examples of microplastics viewed microscopically. Data of the distribution and identity of particles in each product sampled is shown in Table 1.

Figure 1. Two microplastic particles from Dial Powerscrub© viewed at 5x magnification.

144

Figure 2. Dial© plastics with and without soap.

Table 1. Minimum and maximum particle sizes and materials detected

Product Minimum size Maximum size Material detected (µm) detected (µm) St. Ives ® ~60 ~988 Walnut shell powder Corn kernel meal Softsoap ® ~20 ~981 Acrylates Olay ® ~20 ~1003 Acrylates Neutrogena ® ~20 ~995 Acrylates Dial Powerscrub ® ~60 ~1010 Acrylates Clean and Clear® ~60 ~948 Acrylates

Every product had variability in the size of its particles, with a minimum range of almost 900 microns (µm). The largest particles were found in Dial© Powerscrub and the smallest were TM found among Softsoap ®, Olay ® and Neutrogena ® Deep Clean . Each product used a form of acrylates as their abrasives except St. Ives®, which used natural alternatives such as walnut shell powder and apricot extracts. Figure 3 indicates the particle size distribution within random samples of each product.

145 1000 900 800 Dial 700

600 Nuetrogena 500 400 Olay Frequency 300 Soft Soap 200 100 St. Ives 0

Size as Estimated Spherical Diameter (in µm)

Figure 3. Particle size distribution in all six products.

Common to each product except St. Ives®, the most frequent particle sizes ranged from 20-150 microns. The frequency of particles of larger sizes began to taper off after about 100 microns. The Flowcam reported that particles less than 30 microns in length were present. However, no particles smaller than 30microns in length were observed microscopically. This apparently is an artifact of the Flowcam system. Overall, St. Ives contained the largest average particles, though these particles are non-plastic, natural particles.

Harvesting and Quantification

The centrifugation method was superior to the filtration method, which sometimes led to large loss of plastic by the particles lodging in filter paper pores. A total of 3.2483 grams of microplastics were harvested from about 450ml of Dial Powerscrub®. Figure 4 displays the frequency of weight of microplastics in 4-5g samples of Dial Powerscrub®.

146 60

50

40

30 Frequency 20

10

0 0 5 10 15 20 25 30 35 40 45 50 55 60 65 70 More mg of microplastic per 4-5g Sample

Figure 4. Frequency of microplastic weights in 89 replicates of 4-5g of Dial Powerscrub®.

The mean concentration of plastics per sample was 8.12 /4-5g ± 1.21mg microplastic/ g Dial Powerscrub or 1.7mg microplastic/g of Dial Powerscrub®. The average shower uses about 70 gallons of water (WSSC 2014); if the average person uses about 4.7g of Dial Powerscrub about 0.116mg of microplastic is used per gallon of water. If a person uses the product every day for a year about 2.96g of microplastic is used. If person in the United States used the product daily for a year over 945 metric tons of microplastic would be used. This does not account for more than one product being used per shower, or people who do not use products containing microplastics, but illustrates the potential for large quantities of plastic debris to enter the waste stream. They must be removed or dealt with in the environment.

CONCLUSION

It is worth noting that wastewater from two wastewater treatment plant was examined for microplastics. While none were found in the effluent examined further study on this subject is needed. More work that can be conducted includes experimentation with methods to degrade microplastics, such as heat and UV radiation in hopes to suggest microplastic eradication treatments at wastewater treatment facilities.

REFERENCES

Andrady, A.L. 2011. Microplastics in the marine environment. Marine Pollution Bulletin, 62: 1596-1605.

Barnes, D.K.A., Galgani, F., Thompson, R.C., and Barlaz, M. 2009. Accumulation and

147 fragmentation of plastic debris in global environments. Philosophical Transactions of the Royal Society of Biological Sciences, 1526:1985-1998.

Bhattacharya, P., Lin, S., Turner, J.P., Ke, P.C. 2010. Physical adsorption of charged plastic nanoparticles affects algal photosynthesis. The Journal of Physical Chemistry, 114: 16556-16561.

Cole, M., Lindeque, P., Fileman, E., Halsband, C., Goodhead, R., Moger, J., and Galloway T.S. 2013. Microplastic ingestion by zooplankton. Environmental Science & Technology, 47: 6646-6655.

Derraik, J.G.B. 2002. The pollution of the marine environment by plastic debris: a review. Marine Pollution Bulletin, 44: 842-852.

Eriksson, C., and Burton, H. 2003. Origins and biological accumulation of small plastic particles in fur seals from Macquarie Island. AMBIO: A Journal of the Human Environment, 32: 380-384. Fendall, L.S., and Sewell, M.A. 2009. Contributing to marine pollution by washing your face: Microplastics in facial cleansers. Marine Pollution Bulletin, 58: 1225-1228.

Washington Suburban Sanitary Commission, 2014. Water Usage.

Wright, S.L., Thompson, R.C., Galloway, T.S. 2013. The physical impacts of microplastics on marine organisms: a review. Environmental Pollution, 178: 483-492.

148 Dynamics of Galerucella spp. and purple loosestrife (Lythrum salicaria) in Goodyear Swamp Sanctuary, summer 2014 update

Megan Wilckens1 and Holly Waterfield2

INTRODUCTION

The distribution and effectiveness of Galerucella spp. populations as a biocontrol agent of purple loosestrife (Lythrum salicaria) were monitored within Goodyear Swamp Sanctuary as part of an ongoing monitoring regime that began in 1997. Annual spring and fall monitoring of the impact of Galerucella spp. on purple loosestrife is updated in this report. Details of the history of this study can be found in Albright et al. (2004); the concise summary below was presented in Albright 2013.

Lythrum salicaria is an emergent semi-aquatic plant that was introduced into the United States from Eurasia in the early 19th century (Thomson 1987). It is an aggressive and highly adaptive invasive species which inhabits wetlands, flood plains, estuaries and irrigation systems. Once established, purple loosestrife often creates monospecific stands, displacing native species including cattails (Typha spp.), sedges (Carex spp.), bulrushes (Scirpus spp.), willows (Salix spp.) and horsetails (Equisetum spp.). Recent efforts, which include both chemical application and the use of biocontrol methods, have focused on controlling L. salicaria where stands impede well-diversified wetland communities (Thomson 1987).

In June 1997, 50 adults each of Galerucella calmariensis and G. pusilla were introduced into Goodyear Swamp Sanctuary (N42°48.6’ W74°53.9), located at the northeastern end of Otsego Lake (Austin 1998). The beetles were initially released into cages at sites 1 and 2 (Figure 1). In 1998, sites 3-5 were introduced into the study in order to monitor the distribution of Galerucella over time to other stands of purple loosestrife (Austin 1999). Sampling sites were established to monitor the qualitative and quantitative effects of the beetles on purple loosestrife and also to examine the extent of any recovery by the native flora (Austin 1998). It was expected that these beetles would lessen the competitive ability of purple loosestrife by feeding upon their meristematic regions, resulting in defoliation, impaired growth, decreased seed production, and increased mortality (Blossey et al. 1994).

METHODS

Spring and fall monitoring surveys were performed according to protocols established by Blossey et al. (1997). Observations of the insects and plants were made within the five 1m2 quadrats, marked by four visible stakes (Figure 1).

1 BFS Intern, summer 2014. Current Affiliation: Le Moyne College, Syracuse, NY. 2 CLM. Research Support Specialist, SUNY Oneonta Biological Field Station, Cooperstown, NY.

149

Figure 1. Map of Goodyear Swamp Sanctuary showing sampling sites. Sites 1 and 2 are 1997 Galerucella spp. stocking sites; sites 3-5 were established to evaluate the spread of Galerucella spp. within the Sanctuary over time.

Spring monitoring was completed on 04 June 2014, which is about 2 weeks later than most years. This first assessment is typically completed within 2-3 weeks after overwintering adults appear (Blossey 1997). Galerucella spp. abundance was estimated in each life stage (egg, larva, adult) according to the established abundance categories (Table 1). The number of stems of L. salicaria within each quadrat were counted, and the five tallest were measured. The percent cover of L. salicaria and the percent damage attributable to Galerucella spp. were both estimated according to established frequency categories. Fall monitoring, which was completed on 08 September 2014, consisted of the same metrics measured in the spring monitoring along with measurements to gauge the vigor of L. salicaria plants, including the number of inflorescences per plant and per quadrat, as well as the number of flowers per inflorescence.

Table 1. Categories prescribed by Blossey’s (1997) protocol for reporting abundance and frequency categories.

Abundance Categories Frequency Categories Number category range category mid point 0 1 0% A 0% 1-9 2 1-5% B 2.5% 10-49 3 5-25% C 15% 50-99 4 25-50% D 37.5% 100-499 5 50-75% E 62.5% 500-1000 6 75-100% F 87.5% >1000 7 100% G 100%

150 RESULTS & DISCUSSION

Monitoring data are represented by abundance and frequency categories (defined in Table 1), and total stem counts. Changes between abundance/frequency categories from year-to-year or plot-to-plot can represent a substantial change in abundance due to the broad ranges covered by each category (Albright 2004). Variation in the number of stems between years or plots may not correspond with a shift in percent cover category, due to the inherent lack of sensitivity in a categorical classification scheme.

Spring Monitoring (04 June 2014) Eggs of the Galerucella beetle were present in four of the five of the quadrats at moderate densities (Figure 2). Larvae were not found in any quadrat, which is consistent with typical spring conditions since 1998 but is in contrast with larval abundances observed in 2012 (Figure 3). Adult beetles were found in 2 of 5 quadrats at moderate densities (Figure 4).

6

5

4

3

2 Abundance category 1

quadrat 1 quadrat 2 quadrat 3 quadrat 4 quadrat 5

Figure 2. Comparison of Galerucella spp. egg abundance from yearly spring samplings. Abundance categories taken from Table 1. 6

5

4

3

2 Abundance category 1

quadrat 1 quadrat 2 quadrat 3 quadrat 4 quadrat 5

Figure 3. Comparison of Galerucella spp. larval abundance from yearly spring samplings. Abundance categories taken from Table 1.

151 6

5

4

3

2

Abundance category 1

quadrat 1 quadrat 2 quadrat 3 quadrat 4 quadrat 5

Figure 4. Comparison of Galerucella spp. adult abundance from yearly spring samplings. Abundance categories taken from Table 1.

Lythrum salicaria abundance in 2014 was on par with recent years (2011-2013), which is substantially lower than abundance estimates (based on stem counts) prior to 2008 (Figure 5). Estimated percent cover was slightly higher than in 2013 and stems of loosestrife were observed in all five quadrats (Figure 6). All loosestrife stems within the quadrats showed signs of damage from herbivory (Figure 7).

100 90 80 70 60 50 40 Number of Stems 30 20 10 0

quadrat 1 quadrat 2 quadrat 3 quadrat 4 quadrat 5

Figure 5. Comparison of the number of purple loosestrife stems from yearly spring sampling observations.

152 70

- point 60 50 40 30 20 10 Frequency Category Mid 0

quadrat 1 quadrat 2 quadrat 3 quadrat 4 quadrat 5

Figure 6. Comparison of percent cover estimates by purple loosestrife from yearly spring samplings. Frequency category mid points derived from Table 1.

70

- point 60 50 40 30 20 10 Frequency Category Mid 0

quadrat 1 quadrat 2 quadrat 3 quadrat 4 quadrat 5

Figure 7. Comparison of percent damage estimates to purple loosestrife leaves from yearly spring samplings. Frequency category mid points derived from Table 1.

Fall Monitoring (8 September 2014)

The number of L. salicaria stems and estimated percent cover both increased since fall 2013 (Figures 8 and 9, respectively). The number of stems seen in 2014 is similar to that observed in 2010, with 37 stems recorded in Quadrat 1; observations in 2002 represent the only year prior to 2010 when stems counts exceeded 40. Despite this increased abundance, only a single inflorescence (flower cluster) was recorded in the quadrats. As in most years, stems of L. salicaria were in bloom elsewhere in the swamp.

Galerucella are host-specific and as such feed exclusively on purple loosestrife. This characteristic results in a beetle population that is directly dependent upon loosestrife densities within the swamp. Abundance patterns observed within the swamp since 1998 illustrate the population dynamics of host-specific organisms and their dependency upon host populations (Fagan et al. 2002). After several cycles of such population fluctuations, it seems that percent damage estimates exceeding 50% during the spring survey indicate a shortage of food resources

153 for the Galerucella spp. beetles, thus limiting the population. A year with such high herbivory is typically followed by a year with lower beetle abundance (Figures 2, 3, 4) and herbivory (percent damage, Figure 7).

120 100 80 60 40 20 NA

Number Number Stemsof 0 1997 2000 2001 2002 2003 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014

quadrat 1 quadrat 2 quadrat 3 quadrat 4 quadrat 5 Figure 8. Number of purple loosestrife stems per quadrat during fall monitoring, 1997, 2000- 2014. Flooding in fall 2011 precluded sampling.

100 point - 80

60

40

20 NA

Frequency Mid Frequency Category 0 1997 2000 2001 2002 2003 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014

quadrat 1 quadrat 2 quadrat 3 quadrat 4 quadrat 5 Figure 9. Estimated percent cover (category midpoints) of purple loosestrife during fall monitoring, 1997, 2000-2014. Categories as presented in Table 1. Flooding in fall 2011 precluded sampling.

CONCLUSIONS

Spring 2014 monitoring indicated that L. salicaria abundance continues to be less (based on percent cover and number of stems) than in most years since monitoring began in 1997, while enough exists to sustain a Galerucella population, as evidenced by the moderate abundance of both eggs and adults. Fall monitoring reveals that Galerucella spp. are effective at controlling not only the abundance of L. salicaria, but also the overall vigor and fitness based on reduced plant height and low production of flowering bodies. Observations related to the presence of Galerucella spp. at sites outside of Goodyear Swamp Sanctuary (i.e., Lydon 2008) indicate that the dispersal of Galerucella spp. continues from the original site and it shows promising potential as a biological agent against the invasive plant.

154

REFERENCES

Albright, M.F. 2013. An update on the dynamics of Galerucella spp. and purple loosestrife (Lythrum salicaria) in Goodyear Swamp Sanctuary, summer 2012. In: 45th Ann. Rept. (2012) SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta.

Albright, M.F., W.N. Harman. S.S. Fickbohm, H.A. Meehan, S. Groff and T. Austin. 2004. Recovery of native flora and behavior responses by Gallerucella spp. following biocontrol of purple loosestrife. Am. Midl. Nat. 152:248-254.

Austin, T. 1998. Biological control of purple loosestrife in Goodyear Swamp Sanctuary using Galerucella spp., summer 1997. In 30th Ann. Rept. (1997). SUNY Oneonta. Biol. Fld. Sta., SUNY Oneonta.

Austin, T. 1999. Biological control of purple loosestrife in Goodyear Swamp Sanctuary using Galerucella spp., summer 1998. In 31st Ann. Rept. (1998). SUNY Oneonta. Biol. Fld. Sta., SUNY Oneonta.

Blossey, B. 1997. Purple loosestrife monitoring protocol, 2nd draft. Unpublished document. Dept. of Natural Resources, Cornell University.

Blossey, B., D. Schroeder, S.D. Hight and R.A. Malecki. 1994. Host specificity and environmental impact of two leaf beetles (Galerucella calmariensis and G. pusilla) for the biological control of purple loosestrife (Lythrum salicaria). Weed Science. 42:134-140

Fagan, W.F., M.A. Lewis, M.G. Neubert, P. van den Driessche. 2002. Invasion theory and biological control. Ecology Letters 5(1) 148.

Lydon, J.C. 2008. Monitoring the dynamics of Galerucella spp. and purple loosestrife (Lythrum salicaria) in the Goodyear Swamp Sanctuary and along the shorelines of Otsego, Weaver and Youngs Lakes, summer 2007). In 40th Ann. Rept. (2007). SUNY Oneonta Bio. Fld. Sta., SUNY Oneonta.

Thompson, Daniel Q., R.L. Stuckey, E. B. Thompson. 1987. Spread, Impact, and Control of Purple Loosestrife (Lythrum salicaria) in North American Wetlands. U.S. Fish and Wildlife Service. 55 pages. Jamestown, ND: Northern Prairie Wildlife Research Center Online. http://www.npwrc.usgs.gov/resource/plants/loosstrf/loosstrf.htm (04JUN99).

155

Wetland delineation of Parslow Road Conservation Area in Oaksville, New York

Katherine Berdan1

INTRODUCTION

Wetland areas play a unique and vital role in the hydrologic cycle. As scientists gain a better understanding of the many different functions that wetlands provide (such as flood control, improving water quality, and providing habitats for a wide variety of organisms), it is apparent that wetlands need to be protected to maintain these important wetland functions (Edinger 2014). Disturbances created by humans can greatly alter the productivity and diversity within a wetland, potentially limiting its ability to reduce downstream flooding or remove nutrients from runoff. Today, wetlands are being threatened by construction, pollution and nuisance species. A study comparing the estimated acreage of wetlands in 1780 and the findings of the National Wetlands Inventory of 1980 shows a 60% decrease in wetland acreage in New York State (Welsch 1995). This huge loss of wetland environments is not limited to New York; the entire Northeastern Area of the USDA Forest Service has seen a 59% decrease in wetland acreage (Welsch 1995). It is vital that landowners understand the extent of a wetland before altering nearby areas (Browne et al. 1995), since wetlands come in all shapes and sizes. To obtain the approximate location of a wetland boundary, a wetland delineation is required. A wetland delineation consists of a field survey to observe and record changes in vegetation, hydrology, and pedology (i.e., the nature of soils) to determine the approximate location of the boundary between upland and wetland areas (Browne et al. 1995).

Parslow Road Conservation Area (Figure 1) is an 86 acre property in Oaksville, New York purchased by the Otsego Land Trust in April, 2012 (Parslow 2013). It is bordered on one side by Oaks Creek, which flows out of Canadarago Lake for approximately 15 Km before joining the Susquehanna River. Several power lines run through the property, as does an abandoned rail bed. Portions of the parcel were previously used as a nursery for trees, most of which are dying due to the high water table in the area. Land cover types within the property include state and federal protected wetlands, as well as upland areas. Through a partnership with the Department of Environmental Conservation (DEC), the Upper Susquehanna Coalition, and the Chesapeake Bay Gateways Network, the Land Trust is planning to develop public access to this property and the creek that flows through it as part of the Blueway Trail system (Parslow 2013). The property owners’ ultimate goal was to gain a better understanding of the extent of the wetland and insight into the functions it may provide in the local and/or regional landscape. In order to accomplish this, the boundary of the wetland was determined via wetland delineation survey, yielding the wetlands’ size (areal extent) and location within the property boundary. Additional delineation surveys in winter or spring (when water tables are typically highest) would ensure the boundary presented in this report reflects the full extent of the wetland.

1 BFS Intern, summer 2014. Current affiliation: State University of New York at Geneseo. Funding for this project was provided by the Otsego Land Trust.

156

Figure 1. The Parslow Road Conservation Area, Oaksville, Otsego County, New York.

157

MATERIALS AND METHODS

The process used for the Parslow property delineation project followed that found in Browne et al. (1995). This manual outlines the delineation methodologies used by the DEC and provides specific factors and indicators to evaluate when determining a wetland boundary. To determine a wetland boundary, zones with an undetermined wetland or upland status were evaluated. Randomly placed square meter grids (made out of pvc piping) were then set in each zone. At each grid site, vegetation, hydrology and soil types were evaluated and sampled to determine whether the site was characteristic of a wetland. Wetland indicators included the plant communities at each site. Obligate wetland species are those which are highly associated with wetland sites, while obligate upland species are indicative of upland areas (facultative species are those occurring in both wetland and upland conditions). Thus, communities comprised largely of obligate wetland and facultative plant species would indicate wetland conditions. Other factors considered when evaluating wetland status included the presence of gleysols (a type of hydric, or perennially waterlogged soil found in wetlands), a high water table, exposed roots, and water lines (Browne et al 1995).

A Munsell Color Soil Chart was used to evaluate soils. Any samples of soil or vegetation that could not be identified were taken back to the laboratory for identification. After the initial site, the grid was moved to several other random sites nearby. After identifying both upland and wetland sites within each zone, flags were placed between the wetland sites and the uplands sites, showing the approximate location of the wetland boundary. The GPS location of each flag along the wetland boundary was recorded in order to map the extent of the wetlands.

Throughout the delineation process periodic heavy rains saturated the soils and inundated low-lying areas. These weather conditions were carefully taken into consideration when determining hydrology indicators as per NYS Freshwater Delineation Manual instructions (Browne et al 1996).

It should be noted that dense stands of the exotic multiflora rose (Rosa multiflora) made traversing the upland areas extremely difficult. Machetes were used to access the wetland areas.

RESULTS

Sixty five boundary points were marked after surveying the main portion of the Parslow property, which excludes the parcel of land on the other side of Parslow road and the small section of property that extends in the northwest corner of the property (see Figure 1). In total, 147 sites were surveyed to identify these 65 boundary points. Figure 2 shows the wetland boundaries for the site. Since the property boundaries were not well marked, some of these markers were placed just beyond the property boundary (as seen in the northern section of the property). Plant species found within the boundary zones and their wetland indicator status were recorded for all sites and are listed in Table 1. As the following list is only comprised of species found within grid sites along wetland boundaries, it is not necessarily an exhaustive list of the total plant diversity at Parslow Road Conservation Area, but it is still useful in generating a species list for the property.

158

Figure 2. Wetland delineation map of Parslow Road Conservation Area, 2014. Table 1. List of species found at Parslow Road Conservation Area delineation sites. WIS= Wetland Indicator Status (FAC= Facultative species, FACU= Facultative Upland species, FACW= Facultative Wetland species, OBL= Obligate Wetland species).

Common Name Genus Species # of sites present WIS Alfalfa Medicago sativa 2 UPL American Beech Fagus grandifolia 3 FACU American Hornbeam Carpinus caroliniana 1 FAC Arborvitae Thuja occidentalis 21 FACW Black Ash Fraxinus nigra 3 FACW Black Cherry Prunus serotina 1 FACU Bladder Sedge Carex intumescens 3 FACW Blue Flag Iris Iris versicolor 6 OBL Canada Windflower Anemone canadensis 2 FACW Canary grass Phalaris canariensis 15 FACU Red Cedar Juniperus virginiana 1 FACU Common Reed Phragmites australis 4 FACW

159

Table 1 (cont.). List of species found at Parslow Road Conservation Area delineation sites. WIS= Wetland Indicator Status (FAC= Facultative species, FACU= Facultative Upland species, FACW= Facultative Wetland species, OBL= Obligate Wetland species).

Common Name Genus Species # of sites present WIS Cow Vetch Vicia cracca 7 FACU Dewberry Rubus invisus 5 UPL Dogwood Cornus alternifolia 7 FACU False Hellebore Veratrum viride 3 FACW Field Bedstraw Galium mollugo 5 FACU Forget-Me-Nots Myosotis scorpioides 1 OBL Fox Sedge Carex vulpinoidea 15 OBL Green Ash Fraxinus pennsylvanica 3 FACW Green Bulrush Scirpus atrovirens 7 OBL Hawthorn Crataegus crus-galli 10 FAC Hay Scented Fern Dennstaedtia punctilobula 4 UPL Hemlock Tsuga canadensis 10 FACU Horsetails Equisetum palustre 12 FACW Japanese Honeysuckle Lonicera japonica 4 FACU Jewelweed Impatiens capensis 9 FACW Katsura Tree Cercidiphyllum japonica 1 FACW Lance-Leaf Goldenrod Solidago graminifolia 15 FACU Linden Tilia americana 1 FACU Lurid Sedge Carex lurida 5 OBL Manna Grass Glyceria melicaria 6 OBL Marsh Bedstraw Galium palustre 4 OBL Marsh Thistle Cirsium palustre 1 FACW May Apple Podophyllum peltatum 1 FACU Meadow vetchling Lathyrus pratensis 1 FACU Moneywort Lysimachia nummularia 13 FACW Multiflora Rose Rosa multiflora 7 FACU Ostrich Fern Matteuccia struthiopteris 5 FACW Raspberry Rubus strigosus 1 FACU Redosier Dogwood Cornus sericea 9 FACW Rough Bedstraw Galium asprellum 2 OBL Sensitive Fern Onoclea sensibilis 33 FACW Silver Maple Acer saccharinum 4 FACW Skunk Cabbage Symplocarpus foetidus 33 OBL Speckled Alder Alnus incana 12 FACW Sticky Bedstraw Galium aparine 1 FACU Stinging Nettles Urtica dioica 2 FAC Tall Goldenrod Solidago altissima 29 FACU Tussock Sedge Carex strica 16 OBL

160

Table 1 (cont.). List of species found at Parslow Road Conservation Area delineation sites. WIS= Wetland Indicator Status (FAC= Facultative species, FACU= Facultative Upland species, FACW= Facultative Wetland species, OBL= Obligate Wetland species).

Common Name Genus Species # of sites present WIS Virginia Creeper Parthenocissus quinquefolia 4 FACU White Pine Pinus strobus 1 FACU Wild Strawberry Fragaria virginiana 2 FACU Willow Salix sp. 4 FACW/OBL Wood Fern Dryopteris sp. 11 FACU/FAC Wood Sorrel Oxalis montana 1 FACU Yellow Birch Betula alleghaniensis 3 FAC

DISCUSSION

The wetlands of the Parslow Road Conservation Area vary in size and type, showing a great diversity of plant types and habitats. All fit into the broad category of inland, or non-tidal wetlands (Lyon 1993). The wetlands found in the northern portion of the property along Oaks Creek are lotic wetlands, meaning that it is a wetland associated with a riparian area. These lotic areas consist of similar lower strata vegetation (herbaceous plants) to the rest of the wetland areas, but contain a much greater upper strata of trees such as Tsuga canadensis (eastern hemlock), Crataegus crus-galli (cockspur hawthorne), Thuja occidentalis (eastern arborvitae), and Acer saccharinum (silver maple).

The remaining wetlands are lentic, meaning they are associated with still water. The presence of a beaver pond located next to the raised power line provides an excellent habitat for lentic wetland species (Rosell et al. 2005). There is a noticeable lack of upper canopy trees in many of the lentic areas, which is most likely due to construction of the power lines in this area. This creates an open mineral soil wetland where there is less than 50% canopy cover (Edinger et al. 2014). Gleysols (hydric soils) located throughout the wetlands contain clay and silt, creating a wet, anaerobic soil layer that water percolates slowly through, filtering sediments and other suspended materials (Munsell 1975, Lyon 1993). The lack of a thick upper canopy has facilitated the growth of a significant layer of shrubs and saplings amongst this shallow, emergent marsh that mainly consist of Salix sp. (willow), Alnus incana (speckled alder), and Cornus sericea (redosier dogwood). In places, this shrub and sapling layer is dominated by exotic species like Lonicera japonica (Japanese honeysuckle) and Rosa multiflora (multiflora rose) that have crowded out native species. The lower strata of vegetation is similar to that of the lotic wetland areas, but with the addition of several species that grow well in partial or full sun, such as the native Iris versicolor (blue flag iris). The most commonly encountered species in the lower strata are as follows; several members of the genus Solidago (goldenrods, mainly Solidago altissima, or tall goldenrod), Symplocarpus feotidus (skunk cabbage), Onoclea sensibilis (sensitive fern), Carex vulpinoidea (fox sedge), Carex lurida (lurid sedge), Fragaria vesca (wild strawberry), Rubus pubescens (dewberry), Lysimachia nummularia (moneywort), and several members of the genus Galium, including Galium palustre, Galium mollugo L., and Galium aparine.

161 Due to the presence of Castor canadensis (the North American beaver), it may be useful to monitor the wetlands and observe any changes over time. The North American beaver is a keystone species that can drastically change its surrounding environment through foraging and the construction of beaver dams. Its ability to create and maintain long-term wetland areas is unique and important role (Rosell et al. 2005).

CONCLUSIONS

The Parslow Road Conservation Area wetland site is open to the public through the Otsego Land Trust. Future construction should be carefully planned in order to preserve the variety of wetland types found there and the habitats, improved water quality, and floodplains that they provide. Currently, the Land Trust has plans to create a small parking lot on an upland area along Parslow Road and a series of trails that would be located mainly on upland or border areas. Future funding for a more extensive boardwalk over the wetland areas is a possibility. These trails would provide access to Oaks Creek and the Blueway Trail (a series of Otsego Land Trust properties that can be reached from Oaks Creek; Parslow 2013).

In addition to providing a recreational space for the public and preserving the natural beauty of its wetlands, Parslow Road Conservation Area also has the potential to become an important educational area. Educating the public on the benefits of wetland preservation and the diversity that they contain through guided walks, bioblitzes, and informative signs would be a good way to create interest in conservation areas. In addition to providing educational programs for the public, the Parslow Conservation Area is also a prime location for biological studies. Future researchers could develop annual projects that would help show the changes in water quality, diversity, wetland boundaries, the spread of invasive species, successional stages of growth in disturbed areas, and overall health of the wetlands within the property.

By continuing educational research on the Parslow property and developing improved public access, the Otsego Land Trust can help to ensure the vitality and survival of this wetland and others in the surrounding area.

REFERENCES

Browne, S., S. Crocoll, D. Goetke, N. Heaslip, T. Kerpez, K. Kogut, S. Sanford, D. Spada, 1995. Freshwater wetlands delineation manual (Rev. July 1995. ed.). Albany, NY: New York State Dept. of Environmental Conservation, Division of Fish and Wildlife, Bureau of Environmental Protection.

Edinger, G.J., D.J. Evans, S. Gebauer, T.G. Howard, D.M. Hunt, and A.M. Olivero (editors). 2014. Ecological Communities of New York State. Second Edition. A revised and expanded edition of Carol Reschke's Ecological Communities of New York State. New York Natural Heritage Program, New York State Department of Environmental Conservation, Albany, NY.

162 Lyon, J. G., 1993. Practical handbook for wetland identification and delineation. Boca Raton: Lewis Publishers.

Munsell soil color charts 1975 ed. 1975. Baltimore, Md.: Munsell Color.

NEW YORK DISTRICT. New York District Regulatory Branch of Wetlands Identification. Retrieved July 21, 2014, from http://www.nan.usace.army.mil/Missions/Regulatory/WetlandsIdentification.aspx

Parslow Road Conservation Area. 2013. Otsego Land Trust. Retrieved July 22, 2014, from http://www.otsegolandtrust.org/

PLANTS | USDA PLANTS. PLANTS | USDA PLANTS. Retrieved July 16, 2014, from http://plants.usda.gov/core/wetlandSearch

Rosell, F., O. Bozser, P. Collen, & H. Parker, 2005. Ecological impact of beavers Castor fiber and Castor canadensis and their ability to modify ecosystems. Mammal Review, 35(3-4), 248-276.

U.S. Lentic Proper Functioning Condition (PFC) Checklist User Manual. 2014, June 6. Ecological Solutions Group. Retrieved July 21, 2014, from http://www.ecologicalsolutionsgroup.com/Documents/PDFforms/UserManuals/USALent icPFCCheckMan.pdf

Welsch, D. J., D. L. Smart, J. N. Boyer, P. Minkin, H. C. Smith, & T. L. McCandless, 1995. Soils. Forested wetlands: functions, benefits and the use of best management practices. Radnor, PA: U.S. Dept. of Agriculture, Forest Service, Natural Resources Conservation Service.

163 Is lake trout recruitment impacted by zebra mussels in Otsego Lake, NY?

David M. Lucykanish1 & John R. Foster2

Abstract: Zebra mussels (Dreissena polymorpha) became established in Otsego Lake in 2008 and by 2010 carpeted the lake trout (Salvelinus namaycush) spawning shoal at Bissel Point. The literature suggests that the presence of zebra mussels would negatively impact lake trout recruitment, because of reduced attractiveness of the substrate and the degradation of interstitial water quality within the substrate. In this study current lake trout recruitment was examined and compared to recruitment levels observed in previous studies. Emergent fry traps were used to capture lake trout fry swimming up from the substrate at Bissel Point in April-May 2014. Twelve emergent fry traps with a diameter of 81 cm (.52 m2) were set on four linear transects in depths of 30, 60 and 90 cm, across the entire shoal. Both the highest (4.83 m2/day in 2014) and lowest (1.59 fry/m2/day in 2013) recruitment levels occurred in the presence of zebra mussels. Fry recruitment was 3.44-3.96 fry/m2/day in the absence of zebra mussels. Therefore, contrary to expectations from the literature, lake trout fry recruitment in the presence of zebra mussels did not differ significantly from recruitment levels in the absence of zebra mussels.

INTRODUCTION

Zebra mussel colonization of lake trout spawning shoals was shown to have negative impacts on their recruitment (Marsden et al 1995, Marsden & Chotkowski 2001). The occurrence of zebra mussels on the spawning shoals reduces their attractiveness to spawning adult lake trout, thus reducing egg deposition and recruitment (Marsden & Chotkowski 2001). Zebra mussels could also have negative impacts on recruitment by reducing the viability of lake trout eggs and fry. The presence of zebra mussels increases damage to lake trout eggs (Marsden & Chotkowski 2001), as well as vulnerability of eggs to predators (Claramunt et al. 2005, Marsden 1997). Zebra mussels can also degrade the interstitial water quality within the spawning substrate (Marsden et al 1995, Marsden & Chotkowski 2001).

Concerns have been raised about the negative impacts zebra mussels may have on lake trout recruitment in Otsego Lake (Sawick & Foster 2013). Initial studies conducted at Bissel Point (Sawick & Foster 2013), a historic lake trout spawning shoal, indicate reduced recruitment in 2013 following zebra mussel colonization in 2010 (Anonymous 2012). However, studies by Tibbits (2007) and Marsden and Chotkowski (2001) have also demonstrated significant variation in yearly lake trout recruitment. Further, the spawning shoals at Bissel Point are in very shallow water. This would make lake trout eggs particularly vulnerable to ice scour and wave action (Edwards et al. 1990). These physical factors are expected to vary from year to year, resulting in year to year variation in recruitment.

164 The goal of this project was to continue the studies of Tibbits (2007) and Sawick & Foster (2013) and measure lake trout recruitment in Otsego Lake at Bissel Point. The objective is to provide data on the year-to-year variation in recruitment as well as the impact of zebra mussels on lake trout recruitment.

MATERIALS & METHODS

This study was conducted just off Bissel Point, Otsego Lake (W74° 54.141; N42° 45.550, Otsego Township, Otsego County, New York), following Tibbits (2007) and Sawick & Foster (2014). The study began on 9 April 2014 just as the ice was receding off Otsego Lake and was completed on 21 May 2014. The total time the traps were fished was 42 days.

Three emergent fry traps were set at depths of 30, 60 and 90 cm along four transect lines perpendicular to the shoreline (Figure 1). The twelve emergent fry traps used in this study had a diameter of 81 cm (area of .52 m2) and were the same ones used by Tibbits (2007) and Sawick & Foster (2014). Emergent fry traps were checked every other day. Captured fry were counted and returned to the lake at the point of capture.

Figure 1. Emergent fry traps were set in depths of 30, 60 and 90 cm at 4 sites off Bissel Point, Otsego Lake, NY.

165

RESULTS

Most lake trout fry emerged close to shore. The majority (67%) of the 435 lake trout fry captured in the spring of 2014 swam up in the 30 cm deep traps (Figure 2). The 60cm deep trap captured 116 fry and only 27 fry were captured in the 90cm deep trap.

80%

70%

60%

50%

40%

30%

20% % of Fry Emergent 10%

0% 30 60 90 Water Depth in cm

Figure 2. The percent of 2014 emergent lake trout fry captured at three water depths.

In 2014 lake trout fry emergence took place over 36 days. The first lake trout fry didn’t emerge until 17 April and the last fry emerged on 21 May (Figure 3). The peak fry emergence in 2014 was from 5-8 May.

Rising water temperatures above 8 ˚C seem to trigger fry emergence. From 27 April to 5 May water temperature was consistent at 8 ˚C. When water temperature increased to 9 ˚C, on 8 May, 138 emergent fry swam up into the traps. However, as the water temperature continued to increase above 11˚C, the number of fry captured decreased until 21 May, when just 7 fry were captured.

166 138 140

120 108 100

80

60 44 47 40 33 Number of Fry Emerging Number Fry Emerging of 20 12 11 5 8 8 7 7 1 2 4 0 5/1 5/3 5/5 5/7 5/9 4/17 4/19 4/21 4/23 4/25 4/27 4/29 5/11 5/13 5/15 5/17 5/19 5/21 Date

Figure 3. The number of lake trout fry emerging on Bissel Point during the spring of 2014.

Figure 4. Water temperatures in ˚C at Bissel Point during lake trout fry emergence in 2014.

In 2014, all measures of fry emergence were substantially higher than in 2013 or in 2003- 2004 prior to the invasion of zebra mussels (Table 1). In 2014, the average number of fry per trap per day was 1.01, higher than .73 in 2003 and .96 in 2004 prior to the introduction of zebra

167 mussels. In 2014 the average number of fry per m2/day was 4.83 which was higher than the 3.96 fry/m2/day captured in 2004, and higher than the 3.44 fry/m2/day captured in 2003. In fact the total amount of fry captured in this study (435) was almost twice the combined number of fry captured in the three previous studies combined (chi square test, P < .001)!

Table 1. Various measures of fry emergence in 2014 compared to previous studies.

Year Emergence Period Total Fry Average Fry per Average Fry per (Days) Captured Trap per Day m2/day 2003 21 172 .73 3.44 2004 28 43 .96 3.96 2013 28 13 .07 1.59 2014 36 435 1.01 4.83

DISCUSSION

Natural recruitment is critically important to maintain the lake trout fishery in Otsego Lake. Seventy five percent of the lake trout in Otsego Lake are from natural recruitment and only 25% come from stocked fish according to New York State Department of Environment Conservation gill net surveys (Tibbits 2007). Concerns about lake trout recruitment came soon after zebra mussels were first documented in Otsego Lake in 2007 (Waterfield 2009). Adult zebra mussels were well established throughout the Lake by 2010 including the lake trout spawning shoal at Bissel Point (Anonymous 2010).

The literature suggests that the presence of zebra mussels on the spawning shoals would negatively impact lake trout recruitment because of reduced attractiveness of the substrate to spawning lake trout. In spite of the presence of zebra mussels, natural spawning of lake trout did occur at the Bissel point shoal in 2013 as evidenced by the emergent fry captured during the spring of 2014.

The degradation of interstitial water quality within the substrate and increased predation have also been suggested as possible negative impacts of zebra mussels on lake trout recruitment (Marsden et al 1995, Marsden 1997, Marsden & Chotkowski 2001 Claramunt et al. 2005). However, in this study the highest level of recruitment (4.83 m2/day) ever recorded occurred in the presence of zebra mussels. The total number of emergent fry captured (435) was significantly higher than the maximum captured (172) before zebra mussels became established in Otsego Lake (Tibbits 2007).

Therefore, contrary to expectations from the literature, lake trout fry recruitment in the presence of zebra mussels may not differ significantly from recruitment levels in the absence of zebra mussels in Otsego Lake. Similarly, Marsden & Chotkowski (2001) showed that lake trout emergence was similar on substrates fouled and not fouled by zebra mussels. Further, Marsden et

168 al. (2005) showed that lake trout fry hatch per egg had some of the highest rates on sites in Lake Champlain that were densely covered with zebra mussels.

There are a multitude of other factors besides zebra mussels that could negatively impact lake trout fry recruitment and increase the variation in fry recruitment from year to year. Wave action, ice scour, and predation all impact lake trout recruitment and are expected to vary from year to year (Edwards et al. 1990, Krueger et. al 1995, Marsden et. al 1995).

The presence of zebra mussels themselves may have a positive impact on measures of lake trout recruitment. Lake trout fry are mobile before swimming up, and they move within and above the substrate (Baird & Krueger 2000). Possibly, zebra mussels may clog interstitial spaces in the substrate reducing fry movement making them more vulnerable to capture by emergence traps (Marsden & Chotkowski 2001). This may result in increased capture rates by emergence traps.

Both the highest (4.83 m2/day) and lowest (1.59 fry/m2/day; Sawick & Foster 2013) recruitment levels occurred in the presence of zebra mussels. Fry recruitment was 3.44-3.96 fry/m2/day in the absence of zebra mussels. More studies are necessary to determine year-to-year variation in recruitment, as well as the impact of zebra mussels on lake trout recruitment.

ACKNOWLEDGEMENTS

The SUNY Oneonta Biological Field Station provided the fry emergent traps and facilities. Matthew Albright of the BFS provided guidance and assistance to this project. Land owners Bevin & Aaron Hall allowed access and use of their property at Bissel Point. SUNY Cobleskill students Matthew Best, Eric Malone, Nick Sawick, Jeff Thompson, Quinn Buckley, Matt Miners, Nick Winter and Brandon Winter helped set, check and repair traps. Research grants to the senior author from the Clear Water Chapter of Trout Unlimited and Schoharie County Conservation Association helped fund this study.

LITERATURE CITED

Anonymous. 2010. Otsego Lake zebra mussel update. SUNY Oneonta Biological Field Station Reporter, summer/fall 2010, p.3. SUNY Oneonta Biological Field Station, Oneonta, NY.

Baird, O.E. & C.C. Krueger. 2000. Behavior of lake trout sac fry: vertical movement at different developmental stages. Journal of Great Lakes Research, 26(2), 141-151.

Edwards, C.J., R.A. Ryder & T.R. Marshall. 1990. Using lake trout as a surrogate of ecosystem health for oligotrophic waters of the Great Lakes. Journal of Great Lakes Research, 16(4), 591-608

169 Krueger, C.C., D.L. Perkins, E.L. Mills & J.E. Marsden. 1995. Predation by alewives on lake trout fry in Lake Ontario: role of an exotic species in preventing restoration of a native species. Journal of Great Lakes Research, 21, 458-469.

Marsden, J.E. 1997. Common carp diet includes zebra mussels and lake trout eggs. Journal of Freshwater Ecology 12: 491-492.

Marsden, J.E., J.M. Casselman, T.A. Edsall, R.F. Elliott, J.D. Fitzsimons, W. H. Horns & B.L. Swanson, 1995. Lake trout spawning habitat in the Great Lakes—a review of current knowledge. Journal of Great Lakes Research, 21, 487-497.

Marsden, J.E. and M.A. Chotkowski. 2001. Lake trout spawning on artificial reefs and the effect of zebra mussels: fatal attraction? Journal of Great Lakes Research, 27:1. 33-43.

Marsden, J.E., B.J. Ellrott, R.M. Claramunt, J.L Jonas & J.D. Fitzsimons. 2005. A comparison of lake trout spawning, fry emergence, and habitat use in lakes Michigan, Huron, and Champlain. Journal of Great Lakes Research, 31(4), 492-508.

Sawick, N.M. & J.R. Foster. 2013. Natural recruitment of lake trout (Salvelinus namaycush) in Otsego Lake. In 46th Ann. Rpt. (2013) SUNY Oneonta Biol. Fld. Sta. SUNY Oneonta.

Tibbits, W.T. 2007. The behavior of lake trout Salvelinus namaycush in Otsego Lake, documentation of strains, movements, and natural reproduction of lake trout under present conditions. Occas. Pap. #42 SUNY Oneonta Biological Field Station, SUNY Oneonta.

Waterfield, H.A. 2009. Update on zebra mussel (Dreissena polymorpha) invasion and establishment in Otsego Lake, 2008. In 41st Ann. Rept. (2008). SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta.

170 Continued monitoring of the Moe Pond ecosystem and largemouth bass (Micropterous dolomieuii) populations following its introduction

Jennifer Piacente1

INTRODUCTION

Moe Pond is an impoundment in Otsego County, New York (Figure 1). It has a surface area of 15.6 ha and a mean depth of 1.8 m (McCoy et al. 2001). The deepest depth recorded in 2014 was 2.4 m. During a survey conducted in 1994-95, the only species of fish present were brown bullhead (Ameiurus nebulosus) and golden shiner (Notemigonus crysoleucas) (McCoy et al. 2001). The abundance of golden shiners caused low abundances of large zooplankton, which resulted in algal blooms and decreased transparency (Wilson et al. 1999). McCoy had suggested that the introduction of largemouth bass (Micropterous dolomieuii) would control the golden shiner population, allowing for increased zooplankton and a decreased eutrophic nature of the pond (McCoy et al. 2001). However, before any studies were done on the consequences of largemouth bass introduction, both largemouth bass and smallmouth bass (M. dolomieui) were documented in spring 1999. The introduction of the two species of bass led to the extirpation of golden shiners by 2005 (Dresser 2006). By 2007, largemouth bass seemed to have outcompeted smallmouth bass until they were non-existent in Moe Pond (Reinicke and Walters 2007). Since then, the only fish species collected from Moe Pond have been largemouth bass and brown bullhead.

Figure 1. Topographic map showing the location of Moe Pond in Otsego County, NY ( from Stowell 2014).

1 BFS Intern, summer 2014. Current affiliation: SUNY College at Oneonta.

171 Evaluating the Moe Pond ecosystem is one of the longest ongoing studies at the SUNY Oneonta Biological Field Station, in Cooperstown, NY. As part of the ongoing research, water quality, the zooplankton community, and the fish community is monitored for several weeks during the summer. The data acquired in 2014 will allow the Biological Field Station to add to data from previous years. The long-term data can be used to observe any trends or significant changes that may be occurring in Moe Pond.

METHODS

Limnology

Between 2 June and 14 July, water quality samples from Moe pond were taken on a bi- weekly basis. Sampling took place at the deepest point of the pond, which was approximately 2.4 m deep, as shown in Figure 2. Samples were taken back to the lab where they were tested for total nitrogen (Pritzlaff 2003) and total phosphorus (Liao and Marten 2001), chloride (APHA 1989) and calcium (EPA 1983). Also, at the deepest point, a YSI® multiprobe was used to measure physical parameters such as temperature, pH, conductivity, ORP, dissolved oxygen (mg/l and %) and turbidity. Such parameters were measured at the surface, one meter, two meters, and the bottom. Finally, a Secchi disk was used to measure the transparency of the water.

Sampling site

Figure 2. Map of Moe Pond indicating sampling site (modified from Sohacki 1973).

172 Zooplankton Community

The zooplankton community was also monitored on a bi-weekly basis. For each sample a zooplankton net with 63 um mesh was used to acquire quantitative zooplankton samples. The samples were doubled in volume with ethanol to preserve them. Samples were observed 1 mL at a time under a Axioskop 40 microscope equipped with IMAGE PRO PLUS software. The first 100 zooplankton found were measured, and Excel® was used to organize the data with species and size.

Fish Community

To evaluate the fish community, a 200 ft. haul seine was used. A rowboat was used to place the seine in a “teardrop” shape in the water, with the bag of the net farthest from shore. The seine was then pulled into shore and the fish caught in the bag were put in totes. All brown bullhead were immediately returned to the water as the focus was on the largemouth bass population.

Each largemouth bass over 150 mm had a gastric lavage performed (Foster 1977), which caused fish to regurgitate the contents of its stomach into a Whirl-Pak® bag. Every Whir-Pak® was labeled with the fish’s ID number and length. Back at the lab the bags were preserved with 70% ethanol and stored in the cooler until the contents of the stomach were identified. Every largemouth bass also had a scale sample taken using a pocketknife. The scales were removed above the left pectoral fin and placed in folded paper towels numbered and labeled with corresponding length. The samples were taken to the lab and placed in the cooler until they were used to age fish at a later time.

Abundance estimates of fish were determined by areal extrapolation. The area sampled by the trap net was approximately 300 m2 and the entire pond is 155,800 m2, so the abundance on each sampling date was # seined*155,800/300. This is not expected to provide an accurate estimation of abundance as fish are not homogeneously distributed, though it does provide for a year-to-year basis of comparison.

RESULTS AND DISCUSSION

Limnology

The data for the physical water quality parameters taken from the YSI® multiprobe from the summer is shown in Table 1. Between 2 June and 14 July the temperature increased from 21.22 °C at the surface and 20.7 °C at the bottom, to 24.50 °C and 23.04 °C respectively. This was linked to dissolved oxygen concentrations decreasing as the summer progressed. Conductivity increased at the bottom from 0.049 to 0.061. Turbidity and pH varied throughout the summer, showing no pattern.

173 Table 1. Results of temperature, conductivity, pH, ORP, dissolved oxygen %, dissolved oxygen (mg/L) and turbidity taken bi-weekly between 2 June and 14 July 2014.

Table 2 shows mean limnological data from 1972 to present. Chloride and calcium tests have not been conducted every year until recently. This year, the values of chloride and calcium are much higher than previous years, at 8.75 mg/L and 9.22 mg/L respectively. Historically, both calcium and chloride have hardly been above 1.5 mg/l, with the exception of 2002 where calcium was averaged at 10.45 mg/L. The average Secchi depth for Moe Pond has been taken every year. The past couple of years, since golden shiners were extirpated, Secchi depth has increased. This year a lower average Secchi depth, of 1.72 m, was found.

Table 2. Average values of Secchi depth, total phosphorus, nitrate + nitrite, chloride, and calcium from 1972 to present. Average values in 2014 were taken between 2 June, and 14 July (modified from Stowell 2014). bd < 0.02 mg/l. 1972 1994 2000 2001 2002 2003 2004 2005 2006 2007 2008 2012 2013 2014

Secchi Depth (m) NA 0.85 1.2 1.1 2.2 2.33 1.26 1.26 2.2 2.62 1.35 2.24 2.33 1.72 40- Total Phosphorus (ug/L) 36.7 NA NA 26.4 29.05 42.29 56.64 26.91 20.5 28.95 26.33 20 17.6 70 Nitrate+nitrite (mg/L) NA <.05 NA NA 0.14 0.11 0.1 0.01 0.01 <.01 0.003 bd bd bd Chloride (mg/L) NA NA NA NA 1.06 1.47 NA NA NA NA 0.54 0.52 NA 8.75 Calcium (mg/L) NA NA NA NA 10.45 NA NA NA NA NA 1.02 1.53 NA 9.22

Zooplankton Community

The zooplankton community for Moe Pond is summarized in Table 3. Rotifers were the most abundant on 2 June and 16 June. On 30 June and 14 July copepods were more abundant than rotifers. Cladocerans were the least abundant zooplankton found. This year, Daphnia was the only cladoceran found as opposed to previous years when Bosmina was present. Also, as the summer progressed, the average size of Daphnia decreased from 1.373 mm to 0.729 mm.

174 Table 3. Summary of zooplankton samples found in Moe Pond on 2 June, 16 June, 30 June and 14 July 2014 showing mean length and percent composition for all taxa found.

Fish Community

Using the scales taken from each largemouth bass, it was possible to estimate their age. Figure 3 shows the estimated age and length of each bass recorded. Most fish were between ages three and five. Only three bass were collected were two years old, and none were young-of-year or 1+ year. The data from Figure 3 correlates with the data from Figure 4, which shows the number of largemouth bass collected and their length. Most bass collected were between 189 and 199 mm. We also found several between 169 and 189 mm, and between 199 and 239 mm. None were found less than 120 mm or over 300 mm. This indicates a lack of recruitment over the last two years.

175 Length vs. Age

8 7

6 5 4

# of # Fish 3 2 1 0 0 50 100 150 200 250 300

Length (mm)

Figure 3. Age estimates of largemouth bass in Moe Pond using scale samples collected between 2 June and 14 July 2014.

Figure 4. The length and number of largemouth bass found in Moe Pond between 2 June and 14 July 2014. The stomach contents of all largemouth bass collected were identified and are shown in Table 4. The organisms found most often were amphipods, chironomids (midges), dipterans (fly pupae), and zygopterans (damselfly larvae). In 2013, daphnia were the most abundant organism consumed by large mouth bass. Largemouth bass are still consuming daphnia in large abundances, but not as often. This could correlate with the lower Secchi readings found this year

176 due to fewer daphnia in Moe Pond to consume algae. Very few stomachs contained brown bullhead fry, which is surprising since largemouth bass are piscivorous (Smith 1985). The overpopulation of largemouth bass and the lack of other fish species to consume may be influencing the omnivorous behavior being shown by the bass in Moe Pond.

Table 4. Stomach contents of largemouth bass collected from Moe Pond between 2 June and 14 July 2014.

Table 5 shows the populations of changes over time of the fish community of Moe Pond from 1994 to present. Golden shiners have been absent from Moe Pond since 2004. Smallmouth bass haven’t been collected since 2006. The largemouth bass abundance has decreased from 13,560 individuals in 2013. In 2014, the population of largemouth bass is estimated to be approximately 6,360+/-1,676 individuals.

177 Table 5. The populations of golden shiner, largemouth bass, and small mouth bass in Moe Pond for 1994, 1999-2008, and 2012-2014 (modified from Stowell 2013). 1 indicates years in which abundance estimates were determined using electrofishing mark/recapture techniques.

Year Golden shiner Largemouth Bass Smallmouth Bass (Notemigonus (Micropterus (Micropterus

crysoleucas) salmoides) dolomieu) 1994 (McCoy et al., 2000) 7,154: +12,701;-6,356 0 0 1999 (Wilson et al., 2000) 3,210+/-1760 1,588+/-650 958+/-454 2000 (Tibbits, 2001) 381+/-296 2,536+/-1,177 945+/-296 2001 (Wojnar, 2002) 1,708+/-1,693 3,724+/-3,447 504+/-473 2002 (Hamway, 2003)1 3 206 20 2003 (Hamway, 2004)1 2 318 1 2004 (Lopata, 2005) 0 6,924+/-2,912 0 2005 (Dresser, 2006) 0 12,019+/-3,577 223+/-257 2006 (Reinicke & Walters, 2007) 0 11,555.17+/- 0 2007 (Underwood, 2008) 0 13,373+/-249 0 2008 (Finger, 2009) 0 46,740+/-13,220 0 2012 (VanDerKrake, 2013) 0 6,480+/-1,533 0 2013 (Stowell, 2014)1 0 13,560 0 2014 (current) 0 6,361+/-1,676 0

While the plant community was not evaluated in 2014, for the first time slender naiad (Najas flexilis) and common hornwort (Ceratophyllum demersum) were noted in Moe Pond this year (Harman 2014).

CONCLUSION

The long running data set for Moe Pond has allowed us to view trends since 1994. Chloride and Calcium levels are higher than they have ever been. The transparency of Moe pond decreased this year, relative to the last few years. Ever since golden shiners and smallmouth bass were extirpated from the pond, transparency has risen due to the lack of planktivorous fish. Now, largemouth bass have resorted to feeding on zooplankton and macroinvertebrates. The change in the bass diet from piscivory to omnivory may be causing the decrease in transparency. In the future, the transparency may continue to decrease as largemouth bass continue to consume zooplankton to supplement their diet in the absence of other prey items.

The largemouth bass population has reduced this year compared to recent years. There were no largemouth bass younger than 2 years, which may correlate to the population decrease. It may benefit the Moe Pond community to introduce another species of fish. A natural planktivorous fish will feed off the zooplankton in an efficient manner while feeding the largemouth bass population. It would be interesting to observe how another introduced species would change the ecosystem dynamics of Moe Pond.

178 REFERENCES

Albright, M.F., W.N. Harman, W.T. Tibbits, M.S. Gray, D.M. Warner, and R.J. Hamway. 2004. Biomanipulation: A classic example in a shallow eutrophic pond. Lake and Reserv. Manage, 20(4):263-269.

APHA, AWWA, WPCF. 1989. Standard methods for the examination of water and wastewater, 17th ed. American Public Health Association. Washington, DC.

Dresser, K. 2006. Continued monitoring of the Moe Pond ecosystem following the introduction of smallmouth and largemouth bass (Micropetrus dolomieu and M. salmoides, respectively). In 38th Annual Report (2005). SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta.

EPA. 1983. Methods for the analysis of water and wastes. Environmental Monitoring and Support Lab. Office of Research and Development. Cincinnati, OH.

Finger, K. M. 2009. Continued monitoring of the Moe Pond ecosystem following the introduction of smallmouth and largemouth bass (Micropetrus dolomieu and M. salmoides, respectively). In 41st Annual Report (2008). SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta.

Foster, J. R. 1977. Pulsed gastric lavage: An efficient method of removing the stomach contents of live fish. Prog. Fish Culturists. 39(4): 166-169.

Hamway, R.J. 2003. Continued monitoring of Moe Pond after the unauthorized stocking of smallmouth and largemouth bass. In 36th Ann. Rept. (2002). SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta: 66-80.

Hamway, R.J. 2004. Continued observations of Moe Pond after the unauthorized stocking of smallmouth and largemouth bass. In 37th Ann. Rept. (2003). SUNY Oneonta Biol. Fld. Stat., SUNY Oneonta: 110-120.

Harman, W.N. 2014. Personal communication. Director. SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta.

Liao, N. and S. Marten. 2001. Determination of total phosphorus by flow injection analysis colorimetry (acid persulfate digestion method). QuikChem ® Method 10-115-01-1-F. Lachat Instruments, Loveland, CO.

Pritzlaff, D. 2003. Determination of nitrate/nitrite in surface and wastewaters by flow injection analysis. QuikChem ® Method 10-107-04-1-C. Lachat Instruments, Loveland, CO.

McCoy, C.M. III, Charles P. Madenjian, Jean V. Adams, and William N. Harman. September 2001. The Fish Community of a Small Impoundment in Upstate New York. Journal of Freshwater Ecology, 16(3): 389-394.

179

Reinicke E. and G.M. Walters. 2007. Continued monitoring of fish community dynamics and abiotic factors influencing Moe Pond, summer 2006. In 39th Annual Report (2006). SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta.

Smith, C.L. 1985. The inland fishes of New York State. The New York State Department of Environmental Conservation. Albany, NY.

Sohacki, L. P. 1972. Limnological studies on Moe Pond. In 5th Annual Report (1972). SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta.

Stowell, S.G. 2014. Monitoring the Moe Pond ecosystem and population estimates of largemouth bass (Micropterus salmoides) post unauthorized introduction. In 46th Ann. Rept. (2013). SUNY Oneonta Bio. Fld. Sta., SUNY Oneonta.

Tibbits, W.T. 2001. Consequences and management strategies concerning the unauthorized stocking of smallmouth and largemouth bass in Moe Pond. In 33rd Ann. Rept. (2000). SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta.

Underwood, Emily S. 2008. Continued monitoring of the ecosystem dynamics of Moe Pond following the introduction of largemouth bass (Micropterus salmoides) and smallmouth bass (M. dolomieu). In 40th Ann. Rept. (2007). SUNY Oneonta Bio. Fld. Sta., SUNY Oneonta: 125-140.

VanDerKrake, A.J. 2012. Monitoring of the Moe Pond ecosystem and largemouth bass (Mircropterus salmoides) population before considering biomanipulation options. In 45th Annual Report (2012). SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta 126-136.

Wilson, B.J., D.M. Warner and M. Gray. 1999. An evaluation of Moe Pond following the unauthorized introduction of smallmouth and largemouth bass. In 32nd Ann. Rept. (1998). SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta

Wojnar, K.A. 2001. The continuing evaluation of Moe Pond after the unauthorized stocking of smallmouth and largemouth bass. In 34th Ann. Rept. (2001). SUNY Oneonta Bio. Fld. Sta., SUNY Oneonta: 166-176.

180 Status of rainbow smelt (Osmerus mordax) in the Mohican Canyon Tributary, May 2014

Matthew J. Best1

INTRODUCTION

Rainbow smelt (Osmerus mordax) were thought to have been introduced into Otsego Lake in 1979, and by 1982 they were abundant (Sanford 1986). While this unauthorized introduction was illegal, it was believed to have provided a high quality forage base for cold water gamefish (Sanford 1986). To take advantage of their establishment, landlocked Atlantic salmon (Salmo salar) stocking commenced. In 1986, alewives (Alosa pseudoharengus) were first documented in Otsego Lake (Foster 1990). This visually oriented, efficient planktivore quickly became the dominant forage fish, reducing the abundance of others, including smelt (Harman et al. 1997). Alewife greatly reduced zooplankton size and abundance which lead to higher algal densities and lower deep water dissolved oxygen concentrations (Haresign and Warner 1998). Though smelt abundance was notably reduced, there were reports of their spawning in Leatherstocking Creek (Foster 2002) and Mohican Canyon (Breiten 2001) periodically. Smelt have also been observed in the creek at Six Mile Point and Shadow Brook (Harman 2002) and the creek at Three Mile Point (Cornwell 2005).

In 1983, McWatters (1984) documented the size, weight, and age composition of 289 smelt collected from the tributary stream in Mohican Canyon (date not specified). Smelt abundance was considered high at that time and anglers congregated at streams where smelt were known to spawn, and collected them using a simple dip net (McWatters 1984). Approximately 10 groups of smelt totaling 50 individuals were observed in spawning behavior in 2001(Cornwell 2002). Groups of 3-5 smelt gathered in riffle sections of the tributary near shore. Smaller smelt, presumably males, were located slightly downstream of larger females. Smelt were sampled in Mohican Canyon again in 2004 to further document the smelt abundance (Cornwell 2005).

Walleye (Sander vitreus) stocking began in 2000 and was intended to increase angling opportunities, while taking advantage of the forage offered by the invasive alewife, with the additional intention of reducing alewife abundance so that larger crustacean zooplankton could rebound (Cornwell 2001). By the early 2010s, that strategy was realized, with practically no alewife being collected with littoral trap nets (Best 2015), gill nets (Waterfield and Cornwell 2014), or evidence through hydroacoustic surveys (Waterfield and Cornwell 2014). Concurrently, large bodied Daphnia became increasingly dominant (Tanner and Albright 2014). With the absence of the dominant planktivore, the smelt in Otsego Lake potentially have an opportunity to rebound.

1 Robert C. MacWaters Internship in the Aquatic Sciences, summer 2014. Present affiliation: Department of Fisheries and Wildlife Technology, SUNY Agriculture and Technical College, Cobleskill, NY.

181 The goal of this sampling effort was to evaluate smelt spawning activity in the tributary stream in Mohican Canyon and to compare the fitness of spawning smelt to previous years.

MATERIAL & METHODS

Adult smelt were sampled in Mohican Canyon on 21 April 2014 between 8:30pm and 9:00pm with a Halltech backpack electrofisher. Headlamps remained turned off until electrofishing began to avoid deterring smelt from the sampling site. Electrofishing began at the mouth of the stream and continued upstream approximately 100 feet lasting for 329 seconds. Smelt were measured in total length (TL) to the nearest mm with a measuring board and promptly returned to the stream. After completion of sampling effort, more smelt were observed along the lake shore. Further efforts should sample the shoreline before entering the stream.

Figure 1. Map of Otsego Lake displaying sampling location from all past efforts and most recent 2014 sampling effort.

182 RESULTS & DISCUSSION

Thirteen smelt (mean length: 130.2mm, size range: 107-179mm) were captured in 2014. These numbers are very similar to the smelt sampled in 2004. In 2001, smelt were larger than those collected in 2004 (Cornwell 2005). Smelt in 1983 had a length and weight roughly in between the 2001 and 2004 smelt (mean length: 149.5mm, mean weight: 20.6g). Table 1 summarizes the numbers of smelt collected, their mean lengths and weights, size ranges, and method of collection in each sampling effort.

Table 1. Characteristics of Spawning Rainbow Smelt in the Mohican Canyon tributary in 1983, 2001, 2004, and 2014.

Date Number Mean Length Mean Weight Size Range Capture Collected (mm) 9g) (mm) Method 1983 289 149.5 20.6 101-210 Dip Net 4/22/2001 17 176.8 34.2 170-231 Seine 4/15/2004 33 125 9.9 96-196 Seine 4/21/2014 13 130.2 - 107-179 Electrofishing

The length frequency chart from the 2004 smelt shows a high abundance of smelt between 100-130mm. There could have been two-three age classes of smelt based on where their lengths were distributed (Figure 2). In 2014, 110-130mm smelt were most abundant. There was likely only two age classes displayed in 2014 (Figure 3).

Figure 2. Length frequency of spawning rainbow smelt in the Mohican Canyon tributary on 15 April 2004.

183

Figure 3. Length frequency of spawning rainbow smelt in the Mohican Canyon tributary on 21 April 2014.

For comparison, 36 Smelt collected in Pepacton Reservoir (32miles South of Otsego Lake) by DEC during routine gillnetting in 1990-1997 had an average total length of 250mm with a size range from 125-255 (Lindhart 2002). Pepacton Reservoir adults are slightly larger than Otsego Lake’s spawning population (Cornwell 2004).

Since 2001, sampling was limited to one night which did not necessarily coincide with peak spawning, so these efforts cannot allow for comparisons of abundance. It is also worth noting that sampling has been done using different capture methods (Table 1). Despite the negative impact from the alewife in the past, smelt continue to spawn. Spawning smelt have been anecdotally observed in several Otsego Lake tributaries by Otsego Lake residents and documented by BFS and DEC staff (Foster 2002; Harman 1997; Harman 2002; Sanford 1986). Alewives are considered significant predators on ichthyoplankton and have contributed to the decline of several Great Lakes fisheries (Brandt et al. 1987; Crowder 1980; Wells 1977). During summer stratification alewife and rainbow smelt occupy similar habitats, though smelt tend to occupy cooler, deeper water (Simonin 2011). While alewives dominated Otsego Lake, the abundance of smelt was reduced. Alewives spawn in late spring/early summer, concurrent with larval smelt hatching and returning to the lake to start feeding. While the smelt’s spawning efforts were likely successful in past years, the alewife likely limited their recruitment to adulthood. After the re-introduction of walleye to Otsego Lake, the alewife population was decimated. With nothing directly competing with the smelt’s resources, the smelt have an opportunity to reoccupy the lake’s forage base.

184 REFERENCES

Brandt, S.B., D.M. Mason, D.B. McNeil, T. Coates and J.E. Ganon. 1987. Predation by alewives on larvae of yellow perch in Lake Ontario. Transaction of the American Fisheries Society. 116:641-645.

Breiten, T. 2001. Personal communication State Highway 80. Cooperstown, NY 13326.

Cornwell, M.D. 2001. Monitoring trophic changes following the reintroduction of walleye (Stizostidion vitreum) to Otsego Lake: An executive summary. In 33th Ann. Rept. (2000). SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta.

Cornwell, M. D. 2002. Evidence of rainbowsmelt (Osmerus mordax) spawning in Mohican Canyon, a tributary of Otsego Lake. In 34th Ann. Rept. (2001). SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta.

Cornwell, M. D. 2005. Characterization of rainbow smelt (Osmerus mordax) spawning in Mohican Canyon, 2004. In 37th Ann. Rept. (2004). SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta.

Crowder, L.B. 1980. Alewife, rainbow smelt, and native fishes in Lake Michigan: competition or predation? Environmental Biology of Fishes. 5:225-233.

Foster, J. R. 1990. Introduction of the Alewife (Alosa Pseudoharengus) into Otsego Lake. In 22th Ann. Rept. (1989). SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta.

Foster, J.R. 2002. Personal communication. Professor of Fisheries and Aquaculture. SUNY Cobleskill, Cobleskill, NY 12043.

Haresign, S. and D.Warner. 1998. Filtering rates of Otsego Lake zooplankton, summer 1997. In 30th Ann. Rept. (1997). SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta.

Harman, W.N., L.P. Sohacki, M.F. Albright and D.L. Rosen. 1997. The state of Otsego Lake 1936-1996. pp.252-266.

Harman, W.N. 2002. Personal communication. Director SUNY Oneonta Biological Field Station, SUNY Oneonta.

Lindhart, F. 2002. Principal Fisheries Technician, New York State Department of Environmental Conservation. Region 4, Stamford, NY 12167 (unpublished data).

McWatters R. C. 1984. The Age, growth and food habits of the rainbow trout, Osmerus mordax (Mitchill) in Otsego Lake, New York. In 16th Ann. Rept. (1983). SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta.

185 Sanford, D.L. 1986. Sr. Aquatic Biologist. New York State Department of Environmental Conservation. Region 4, Stamford, NY 12167 (unpublishedreport).

Simonin, P., D.L. Parrish, L.G. Rudstam, P.J. Sullivan and B. Pientka. 2011. Native rainbow smelt and nonnative alewife distribution related to temperature and light gradients in Lake Champlain. Journal of Great Lakes Research . 38 (2012) 115-122.

Tanner, C. and M.F. Albright. 2014. A survey of Otsego Lake’s zooplankton community, summer 2013. In 46th Ann. Rept. (2013). SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta.

Waterfield, H.A. and M.D. Cornwell. 2013. Hydroacoustic surveys of Otsego Lake’s pelagic fish community, 2012. In 45th Ann. Rept. (2012). SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta. Wells, L. 1977. Changes in yellow perch Perca flavescens populations of Lake Michigan, 1957-75. Journal of the Fisheries Research Board of Canada 34:1811-1829.

186 Using benthic macro invertebrates to assess stream quality of the Unadilla River, Otsego County, NY

Jennifer Piacente1

INTRODUCTION

Since 1972, aquatic macroinvertebrates have been used to evaluate the water quality of New York State’s rivers and streams (NYSDEC 2009). Biomonitoring is using benthic, or bottom dwelling, macroinvertebrates from stream and river habitats to assess environmental health. Benthic macroinvertebrates are used to assess stream quality because they are abundant, they are easy and inexpensive to sample, many are sensitive to environmental impacts (i.e., pollution, stress, and habitat changes), and different invertebrates have different tolerances to pollution (NYSDEC 2009). The diversity and types of macroinvertebrates collected from a pristine site will differ from those at a polluted site. There are up to 17 taxonomic orders of benthic stream macroinvertebrates, all of which exhibit a wide range of tolerances to stream impairment (Zimmerman 1993). For example, blood-red midges (Diptera, Chironomidae) have a high tolerance to pollution. Ephemeroptera (mayflies), Plecoptera (stoneflies), and Trichoptera (caddisflies) are orders that generally have low tolerances for pollution. A diverse and numerous quantity of EPT is an indicator of good water quality.

The Unadilla River flows 114 km from south of Utica, NY to Sidney, NY where it drains into the Susquehanna River. Most of the Unadilla River forms the western boundary of Otsego County, and the eastern boundaries of Chenango County and Madison County. The Unadilla River runs through suburban, wooded, industrial and agricultural settings. However, most of the areas along the river are agricultural fields. The river forms a variety of microhabitats with a mixture of pools, riffles, and runs as well as a mixture of silty, rocky, and coarse substrate.

Several stream quality assessments have been done on rivers and streams throughout Otsego County (i.e., Bailey 2010, Whitcomb 2012, Buckhout 2013). The Unadilla River is one that is undergoing changes regarding water quality and biological diversity. There have recently been pearly mussel surveys in the Unadilla River (Maricle 2010, Zemken et al. 2013, Lord and Pokorny 2012); mussels are indicators of good water quality. Recent pearly mussel deaths were evident in the Unadilla River, especially near West Edmeston (Lord and Pokorny 2012). The purpose of this research was to evaluate the health of the Unadilla River by assessing its benthic community above and below the area where pearly mussels recently died. As a large river that runs into the Susquehanna River, and eventually the Chesapeake Bay, it is important that we observe water quality changes that may be occurring in the Unadilla River.

1 BFS Intern, summer 2014. Current affiliation: SUNY College at Oneonta.

187 METHODS

Benthic macroinvertebrates were collected at four sites along the Unadilla River (Figure 1 and Table 1). Samples were taken between 23 June and 26 June 2014. Sites were chosen based on ease of access and stream structure to make sampling easier and representative. An ideal site had riffles, coarse substrate, and a depth where the riffles did not exceed one meter.

Figure 1. Map showing the approximate locations of the four sample sites on the Unadilla River.

188 Table 1. Unadilla River site locations and descriptions.

Site # GPS Coordinates Description N 42.76278 1 West Edmeston Welsh Rd. Bridge W 75.27944 N 42.679982 2 New Berlin, Downstream of Agrofarma, Inc. W 75.326842 N 42.61611 3 New Berlin, Co. Rte 13 Bridge W 75.33111 N 42.317939 4 Where the Unadilla River meets the Susquehanna W 75.409623

In the field, macroinvertebrates were sampled using a cylindrical Wildco® Hess Stream Bottom Sampler at each site. The sampler was placed at least 2” into the substrate in a riffled section of the stream so no organisms could wash out. The substrate in the cylinder was stirred up until most organisms were likely dislodged. The mesh sock on the sampler was downstream so the current would carry the macroinvertebrates into the mesh cup at the end of the sock. Samples were then emptied from the sampling cup at the end of the mesh sock into a Whirl- Pak®. Ethanol was added to preserve the organisms. At each site 5 replicates were taken randomly in riffles where the depth did not exceed the sampler height, and in substrate that would allow the sampler to be inserted. The 5 replicates from each site were later combined to form one sample per site. Also, at each site physical parameters were collected using a YSI® multiprobe.

Back at the lab, organisms were identified to genus when possible and enumerated. Peckarsky et al. (1990) and Merrit and Cummins (1996) were used for identification. Spelling was checked using itis.gov.

Once all the organisms were identified, several biotic indices were applied. Biotic indices reflect features of the invertebrate community that can be related to the health of the water body (NYSDEC 2009). The biotic indices were used to evaluate and compare the water quality at each site. The same biotic indices were used as was used by Bailey (2010), Whitcomb (2012), and Buckhout (2013) to stay consistent with past reports at the Biological Field Station. Two richness indices were calculated: total taxa Richness and EPT Richness. High taxa Richness and high EPT richness indicates more pristine water conditions. The Familial Biotic Index (FBI) was also calculated (Hilsenhoff 1988), as was the Percent Model Affinity (PMA) (NYSDEC 2009). The FBI is used to assess the presence of organic pollutants in the water. Each genus has an assigned tolerance value to pollution, which was taken from NYSDEC’s standard operating procedures for biological monitoring of surface waters (NYSDEC 2009). The number of individuals of a genus was multiplied by the tolerance value for that genus. The products were totaled and then divided by the number of individuals in the sample. The result is the biotic index value. Percent Model Affinity measures the similarity of the sampled site to a non- impacted community (NYSDEC 2009). To measure similarity, the percent abundance of Ephemeroptera, Plecoptera, Trichoptera, Coleoptera, Chironomidae, Oligochaeta, and Other is calculated and compared to the model community. The lesser of the two values for each group is taken. The Percent Model Affinity is the sum of the lesser values.

189 RESULTS AND DISCUSSION

A taxa list of the number and types of organisms found at each site are shown in Table 2. Figures 2-4 show the results of the biotic indices calculated. Table 3 provides the Familial Biotic Index scale (NYSDEC 2009) and Table 4 provides Percent Model Affinity scale (NYSDEC 2009).

Order Family Genus Site 1 Site 2 Site 3 Site 4 Ephemeroptera Ameletidae Ameletus 1 Ephemeroptera Baetidae Baetis 53 129 30 31 Ephemeroptera Caenidae Caenis 10 7 Ephemeroptera Ephemerellidae Drunella 3 Ephemeroptera Ephemerellidae Ephemerella 3 1 Ephemeroptera Ephemeridae Ephemera 2 22 3 Ephemeroptera Ephemeridae Hexagenia 2 1 Ephemeroptera Ephemeridae Litobrancha 1 12 Ephemeroptera Heptageniidae Cinygmula 2 43 59 8 Ephemeroptera Heptageniidae Epeorus 2 1 5 Ephemeroptera Heptageniidae Heptagenia 1 Ephemeroptera Heptageniidae Leucrocuta 9 21 7 Ephemeroptera Heptageniidae Maccaffertium 8 9 27 15 Ephemeroptera Heptageniidae Stenacron 1 2 11 Ephemeroptera Heptageniidae Unknown 44 41 27 Ephemeroptera Isonychiidae Isonychia 1 1 8 13 Ephemeroptera Leptophlebiidae Paraleptophlebia 1 Ephemeroptera Leptophlebiidae Unknown 1 Ephemeroptera Potamanthidae Anthopotamus 7 3 2 Plecoptera Perlidae Agnetina 2 4 1 Plecoptera Perlidae Neoperla 2 1 Plecoptera Perlidae Paragnetina 13 3 2 4 Plecoptera Leuctridae Leuctra 1 Plecoptera Nemouridae Shipsa 1 Hemiptera Gerridae Trepobates 1 Hemiptera Pleidae Neoplea 1 Hemiptera Veliidae Rhagovelia 1 Trichoptera Hydropsychidae Ceratopsyche 10 3 14 8 Trichoptera Hydropsychidae Cheumatopsyche 4 1 11 7 Trichoptera Hydropsychidae Hydropsyche 4 1 Trichoptera Hydropsychidae Unknown 1 Trichoptera Philopotamidae Chimarra 11 2 1 Trichoptera Rhyacophilidae Rhyacophila 1 1 1 Trichoptera Uenoidae Neophylax 1 1 Coleoptera Elmidae Dubiraphia 4 Coleoptera Elmidae Optioservus 20 7 1 1 Coleoptera Elmidae Oulimnius 25 6 1 3 Coleoptera Elmidae Stenelmis 83 203 87 72 Coleoptera Psephenidae Ectopria 1 3 Coleoptera Psephenidae Psephenus 4 3 35 21 Diptera Athericidae Atherix 1 8 Diptera Ceratopogonidae Unknown 1 1 Diptera Chaoboridae Chaoborus 1 Diptera Chironomidae Unknown 16 34 22 13 Diptera Simuliidae Prosimulium 1 Diptera Simuliidae Simulium 6 Oligochaeta Unknown Unknown 7 117 7 14 Amphipoda Pontoporeiidae Pontoporeia 3 2 Amphipoda Gammaridae Gammarus 2 1 Total Number of Organisms 285 654 418 291

Table 2. Taxa list of the organisms collected at each site (Figure 1, Table 1). Sites 1 and 2 were collected on 23 June 2014. Sites 3 and 4 were collected on 25 July 2014.

190 Figure 2 shows the results of the richness indices used for each site. Total taxa richness was calculated as the total number of different genera from all taxa at each site. EPT richness is the total number of genera from the orders of Ephemeroptera, Plecoptera, and Trichoptera. According to EPT richness, all four sites are considered non-impacted communities. When comparing each site, higher taxa richness and higher EPT richness indicate greater diversity, and better water quality. Site two has the greatest diversity with 32 taxa, 23 of which were from EPT taxa. Site one had the lowest diversity with 27 total taxa, with 14 being from EPT taxa. However, the diversity of all four sites was similar to each other, which shows little change between each site.

Richness

14 1 27

23 2 32 Site Site

17 3 EPT Richness 26 Taxa Richness

20 4 30

Figure 2. Comparison of Taxa Richness (number of total genera present) and EPT Richness (number of genera from Ephemeroptera, Plecoptera, and Trichoptera) for all sites sampled. For EPT, values greater than 10 indicate a non-impacted community, values between 6 and 10 indicate slightly impacted, moderately impacted sites are between 2 and 6, and below 2 is a severely impacted community (NYSDEC 2009).

The Familial Biotic Index (FBI) estimates the amount of organic pollution in the water. Table 3 shows how the FBI score relates to the level of organic pollution in the water. Higher values indicate more impairment, and lower values indicate more pristine water conditions. As shown in Figure 3, site one had a value of 4.71 and site two’s FBI value was 5.23. The results for sites one and two imply good water quality. However, “good” water quality still contains some organic pollution. Site three and four had lower values of 3.76 and 4.43 respectively. Therefore, sites three and four have “very good” water quality with possible slight organic pollution. Site two however, with the highest FBI value of all four sites, indicates the most organic pollution.

191 Table 3. Familial Biotic Index scale (NYSDEC 2009).

Familial Biotic Index

1 4.71

2 5.23

Site

3 3.76

4 4.43

Figure 3. Familial Biotic Index results for all sites sampled along the Unadilla River. Higher values indicate higher amounts of organic pollution.

The Percent Affinity Model (PMA) compares the organisms found at each sample site to a model community. The model community is indicated in Table 4. As shown in Figure 4, sites one and two have values of 60.79 and 62.8 respectively. According to the NYSDEC, since the PMA values are between 50 and 64, sites one and two are slightly impacted. Sites three and four have values of 66.74 and 69.25. The values from sites three and four are over 64 and therefore indicate excellent water quality. Site four has the highest value and most closely resembles a model community. Site one has the lowest PMA value and is therefore the most impacted site of all sites sampled.

192

Table 4. Percent abundance of 7 major macroinvertebrate groups present in a model community used in the calculation of PMA index (NYSDEC 2009).

Percent Model Affinity

1 60.79

2 62.8 Site

3 66.74

4 69.25

Figure 4. Results for Percent Model Affinity for each site. Values greater than 64 indicate excellent water quality. Values between 64 and 50 indicate slightly impacted water. Moderately impacted waters have values between 49 and 35. Values less that 35 indicate severely impacted waters (NYSDEC 2009).

Table 5 shows a summary of physical parameters using a YSI® multiprobe at each site sampled. As the sites continue downstream, temperature begins at 17.22 °C and increases to 21.06 at site four. Conductivity begins at 0.443 and decreases downstream until site four at 0.258. ORP also decreases as the sites continue downstream. All other parameters are rather consistent at each site and show no pattern.

193 Table 5. Results of physical parameters of water quality using a YSI® multiprobe. Sites 1 and 2 were sampled on June 23 2014. Sites 3 and 4 were sampled on 25 June 2014.

CONCLUSIONS

Benthic macroinvertebrates are a great way to assess water quality because of the different indices that can be used to estimate different water quality parameters. When a pearly mussel survey was done, mussel deaths were evident near West Edmenston (Lord and Pokorny 2012). The results presented here indicate that there is some organic pollution in that area. This area is near an industrial setting, which could be contributing to the slight organic pollution found in the water. However, there is also some organic pollution evident in the water before the industrial area. At this moment, where the organic pollution is coming from is not well known. However, it is evident that something is occurring that is causing the water quality decrease at sites one and two. Some short term incident may have occurred that could have impacted the biota. Because mussels are quite long-lived, they would be expected to take a long time to rebound, whereas most other benthos would likely rebound in a few growing seasons.

Fortunately, besides the evidence of some organic pollutants, the Unadilla River has overall good water quality (Table 6). The Unadilla River is very important to the quality of the Susquehanna River and therefore the Chesapeake Bay. The Unadilla River is the third largest tributary that empties into the Susquehanna River (NYSDEC 2009). Any water quality issues in the Unadilla River will affect the Susquehanna River and the Chesapeake Bay. The water quality issues in the Unadilla River are still recent and there is still hope of restoration. However, if the water quality worsens, the entire aquatic community will be damaged.

Table 6. Summary of the results of the various indices used based on the macroinvertebrate communities present at each site. Sites were ranked based on their degree of impact. (“-“ meaning severely or moderately impacted, “0” indicated slightly impacted, and “+” indicating non-impacted water).

194 REFERENCES

Buckhout, B. 2013. Benthic macroinvertebrate survey of Oaks Creek, Otsego County, NY. In 45th Ann. Rept. (2012). SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta.

Bailey, C. 2010. Macroinvertebrate survey and biological assessment of water quality: tributaries of Canadarago Lake; Otsego County, NY. In 43rd Ann. Rept. (2010). SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta.

Heilveil, J. 2014. Personal communication. Associate professor, SUNY Oneonta Dept. of Biology, Oneonta, NY.

Hilsenhoff, W.L. 1988. Rapid field assessment of organic pollution with a family-level biotic index. Journal of the North American Benthological Society, Vol. 7 No. 1 pp. 65- 68.

Lord, P., and T. Pokorny. 2012. 2011 pearly mussel surveys of the Catatonk Creek, Butternut Creek and Unadilla River. In 44th Ann. Rept. (2011). SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta.

New York State – Department of Environmental Conservation. 2009. Standard operating procedure: Biological monitoring of surface waters in New York State. Albany NY.

Maricle, S. 2010. Unadilla River pearly mussel survey. In 43rd Ann. Rept. (2010). SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta.

Merritt, R, and K. Cummins. 1996. An introduction to aquatic insects of North America. 3rd ed. Kendall Hunt Publishing. Dubuque, Iowa.

Peckarsky, B.L., P.R. Fraissinet, M.A. Penton and D.J. Conklim. 1995. Freshwater macroinvertebrates of northeastern North America. Comstock Publishing. Cornell University Press. Ithaca, NY.

Whitcomb, K. 2012. Baseline water quality assessment of aquatic benthic macroinvertebrates in streams. In 44th Ann. Rept. (2011). SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta.

Zemken, S., P. Lord, and T. Pokorny. 2013. Pearly mussels in Unadilla River and tributaries. In 45th Ann. Rept. (2012). SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta

Zimmerman, M.C. 1993. The use of the biotic index as an indication of water quality. Tested studies for laboratory teaching, Vol. 5. pp. 85-98.

195 Summer 2014 Bioblitz Series

Emily Davidson1

INTRODUCTION

In 1996, Susan Rudy of the U.S. National Park service coined the term “bioblitz,” short for biodiversity blitz, while organizing the first Bioblitz at Kenliworth Aquatic Gardens in Washington, D.C. (Post 2003; Ruch et al. 2010). A bioblitz is a rapid evaluation of the flora and fauna found in a designated area during a given point in time (Ruch et al. 2010). A bioblitz generally lasts 24 hours to document organisms found at different times of day, but is just a “snapshot” of the organisms found at a particular site, and does not include seasonal variations in communities. Bioblitzes are done to characterize taxonomic diversity, promote citizen involvement and interest in local biodiversity, and to protect species and their habitats (USGS 2009). Due to time and resource constraints, 4-5 hour events were held at 3 different properties owned by the Otsego Land Trust over the summer of 2014. The 3 bioblitzes were held at Brookwood Point, Fetterley Forest Conservation Area, and Compton Bridge Conservation Area on 27 June, 12 July, and 30 July respectively (Figure 1).

Brookwood Point (Figure 2) is a 22-acre (0.09 km2) parcel located 1.5 miles ( 2.4 km) north of Cooperstown, NY, on the western shore of Otsego Lake. This parcel includes forest, wetland, field, stream, 426 meters of lakeshore habitats, an ornamental garden and homestead. This property was a part of the 40,000 acres (161.87 km2) of land acquired by Judge William Cooper in 1785. The most recent owner of Brookwood Point was Bob Cook who established the Cook Foundation to provide care for the estate. In 2011 the Otsego Land Trust merged with the foundation, and attained ownership of Brookwood Point. This property has historically served as a homestead, garden retreat, and an outdoor classroom and venue (Otsego Land Trust 2014).

Fetterley Forest Conservation Area (Figure 3) is a 106-acre (0.43 km2) parcel located 2.5 miles (4.02 km) south of Richfield Springs, NY. This property is mostly covered by mature hardwoods, and includes a vernal pool wetland within the forest. Fetterley Forest Conservation Area has been actively managed for decades, with its most recent timber harvest in 2011 (Otsego Land Trust 2014a).

Compton Bridge Conservation Area is a 3-acre (0.01 km2) parcel at the confluence of Oaks Creek and the Susquehanna River (Figure 4). It is located about 4 miles (6.4 km) south of Cooperstown, NY. The majority of the parcel is riparian and wetland habitat which experiences frequent temporary flooding. Historically, Compton Bridge Conservation Area has mostly been used for public access to the water, and little record of farming, or industrial use has been found (Otsego Land Trust 2014b), though there is a raised railroad along the eastern property boundary and 2 bridges (rail and vehicular) that cross the river.

196

Figure 1. Map of Otsego County indicating Otsego Land Trust owned properties where bioblitzes occurred.

197 Figure 2. Map of Brookwood Point property boundaries.

Figure 3. Map of Fetterley Forest Conservation Area property boundaries.

198 Figure 4. Map of Compton Bridge Conservation Area property boundaries.

METHODS

Brookwood Point was surveyed on 27 June from 9am-2pm, Fetterley Forest Conservation Area was surveyed on 12 July from 10am-2pm, and Compton Bridge Conservation Area was surveyed on 30 July from 10am-2pm. Biological Field Station staff and interns, professors from SUNY Oneonta, SUNY Oneonta students, Otsego Land Trust employees, and community members participated in the surveys. Biologists having varying areas of expertise were able to cover different taxa fairly well. For instance, each day, an arthropod expert was on site with a microscope. A vascular plant expert and vertebrate expert attended each day as well. At Brookwood Point, a fish parasitologist (parasite expert) and a phycologist (algae expert) were also present. Some taxa were not well represented (i.e., fungi).

Due to high flow conditions, and then equipment failure, the extensive fishes survey via electrofishing was not conducted at Compton Bridge Conservation Area. However, a mussel survey was done using SCUBA once the high water subsided.

199 Also at each bioblitz, equipment including terrestrial nets, aquatic nets, collecting trays, kill jars, collection jars and bags, hand lenses, forceps, taxonomic keys, microscopes, Syracuse dishes, electrofishing equipment, tables, chairs, pens, pencils, recording forms, and clipboards were brought upon necessity. For the duration of the bioblitz, participants documented as many taxa as possible in the allotted time. For each specimen found, the scientific name, habitat type, identifier and other pertinent observations were recorded on premade forms. The forms were collected and taxonomic lists were compiled for each property.

RESULTS

We found 220 taxa at Brookwood Point, 225 taxa at Fetterley Forest Conservation Area, and 203 taxa at Compton Bridge Conservation Area. Figure 5 summarizes the breakdown by broad taxonomic groups graphically. The summary the total number of taxa is also provided in Table 1. Complete taxonomic lists for each site are given in Tables 2-4. All plant taxonomic information is based on Gleason and Cronquist, 1991, and all other taxonomic information was obtained from the Integrated Taxonomic Information System or www.itis.gov.

250

200

150

100 Number of taxa Number

50

0 Brookwood Point Fetterley Forest Compton Bridge

Figure 5. Number of taxa found at each property.

200 Table 1. Summary of the number of taxa found at Brookwood Point, Fetterley Forest, and Compton Bridge Conservation Areas during summer 2014 Bioblitz events.

Brookwood Fetterley Compton Point Forest Bridge Birds 23 23 10 Amphibians 5 6 2 Reptiles 1 1 0 Mammals 5 3 1 Fishes 21 0 3 Molluscs 3 2 5 Arthropods 52 41 43 Parasites 6 0 0 Plants 92 149 139 Algae 9 0 0 Other 3 0 0 Total 220 225 203

DISCUSSION

Interestingly, the total number of taxa identified at each of the three properties was quite consistent. This is despite the fact that the properties vary considerably in size (from just 3 acres to 106 acres) and differed in the diversities of available habitats (with Brookwood Point seeming to offer a richer diversity of habitat types than the other properties). Also, the number of participants varied among the bioblitzes, as did the levels of expertise among them.

At each property invasive species were found. An uncommon invasive plant, Amorpha fruticosa (false indigo bush) was found at Brookwood Point. According to the USDA’s plant database, there are no other confirmed cases in Otsego County. This plant has the potential to outcompete native species, especially along waterways (Szentesi, 1999). Rosa multiflora (multiflora rose), Arctium minus (burdock), Aegopodium podagaria (bishop goutweed), Berberis vulgaris (barberry), and Celastrius orbiculatus (oriental bittersweet) are considered invasive and were found also on site, though the extent of each was not documented. In Brookwood Creek, a tributary stream at Brookwood Point, it was expected to find the non-native Orconectes rusticus (rusty crayfish) due to their presence in Otsego Lake. However, only Camabarus bartonii, a native crayfish was found. At Fetterley Forest Conservation Area, Cirsium palustre (marsh thistle) was found. This plant can grow in thickets, crowding out native species. At Compton Bridge Conservation Area, five native species of pearly mussels were identified, as well as the exotic zebra mussel (Dreissena polymorpha). Because pearly mussels exhibit longevity and minimal mobility, and are intolerant to degraded water quality, they are good indicators of good water quality (Vaughn, 2001; Strayer, 1999). Myriophyllum spicatum (Eruasian milfoil), Rosa multiflora (multiflora rose), and Fallopia japonica (Japanese knotweed) were notable invasive

201 species found in localized patches at Compton Bridge Conservation Area. Further investigation of densities and possible impacts would be useful for management purposes.

While not quantifiable, these Bioblitz events increased awareness and understanding of local biodiversity for over 50 people, ranging from community members, Otsego Land Trust staff, Biological Field Station staff and interns, SUNY Oneonta Students and professors to Clark Sports Center volunteers who were involved. They also provided a space in which community members could interact, and communicate with working scientists about the importance of local diversity, and the Land Trust’s mission. The Otsego Land Trust works to protect lands and waters via acquisition of lands to open to the public, conservation easements and purchase of development rights (PDR) agreements. Conservation easements and PDRs allow private property owners to legally conserve their lands into perpetuity. Their goal for land protection and acquisition is to facilitate meaningful connections to land and water; in hopes that those connections will create a sense of responsibility for protection of these places. Their Oaks Creek Blueway project is a series of public access properties that provide recreational and education opportunities all over the county, and accomplishes that goal (Otsego Land Trust 2013). All three properties surveyed are included in the Oaks Creek Blueway. Our bioblitzes were only 4-5 hours long. It did not allow for us to survey individuals that inhabit each property at night, and other times of day and year. Furthermore, certain taxonomic groups such as fungi, lichens and mosses were underrepresented due to lack of expert knowledge. More surveys conducted at different times of day and year would maximize the biodiversity at each property. Also, having more consistent attendance of experts, and a wider range of expertise would be beneficial to future bioblitzes.

202 Table 2. All taxa observed at Brookwood Point Conservation Area on 27 June 2014 (between 9am and 2pm).

ANIMALS

Kingdom Phylum Class Order Family Genus Species Common Name Aves Anseriformes Anatidae Aix sponsa Wood duck Aves Anseriformes Anatidae Mergus merganser americanus Common merganser Aves Charadriiformes Laridae Larus delawarensis Ring-billed gull Aves Columbiformes Columbidae Columba livia Rock pigeon or dove Aves Passeriformes Bombycillidae Bombycilla cedrorum Cedar waxwing Aves Passeriformes Cardinalidae Cardinalis sp. Northern cardinal Aves Passeriformes Corvidae Corvus brachyrchynchos American crow Aves Passeriformes Corvidae Cyanocitta cristata Blue jay Aves Passeriformes Emberizidae Junco hyemalis Dark-eyed junco Aves Passeriformes Emberizidae Melospiza melodia Song sparrow Aves Passeriformes Hirundinidae Tachycineta bicolor Tree wwallow Aves Passeriformes Icteridae Molothrus sp. Brown-headed cowbird Chordata Animalia Aves Passeriformes Icteridae Quiscalus quiscula Common grackel Aves Passeriformes Mimidae Dumetella carolinensis Gray catbird Aves Passeriformes Parulidae Geothlypis trichas Common yellowthroat Aves Passeriformes Parulidae Setophaga pensylvanica Chestnut-sided warbler Aves Passeriformes Parulidae Setophaga petechia American yellow warbler Aves Passeriformes Turdidae Turdus migratorius Robin Aves Passeriformes Tyrannidae Empidonax minimus Least flycatcher Aves Passeriformes Tyrannidae Sayornis phoebe Eastern phoebe Aves Passeriformes Tyrannidae Tyrannus tyrannus Eastern king bird Aves Passeriformes Vireonidae Vireo olivaceus Red-eyed vireo Aves Piciformes Picidae Sphyrapicus varius Yellow-bellied sapsucker

Amphibia Anura Ranidae Lithobates clamitans Green frog Amphibia Anura Ranidae Rana palustris Pickerel frog Amphibia Caudata Plethodontidae Desmognathus fuscus Northern dusky salamander Chordata Animalia Amphibia Caudata Plethodontidae Eurycea bislineata Northern two-lined salamander Amphibia Caudata Plethodontidae Plethodon cinereus Red back salamander

Reptilia Squamata Colubridae Thamnophis sirtalis Eastern garter snake

Mammalia Artiodactyla Cervidae Odocoileus sp. White-tailed deer Mammalia Rodentia Sciuridae Marmota monax Groundhog or Woodchuck Chordata Animalia Mammalia Rodentia Sciuridae Sciurus carolinensis Eastern gray squirrel Mammalia Rodentia Sciuridae Tamias striatus Eastern chipmunk Mammalia Rodentia Sciuridae Tamiasciurus hudsonicus American red squirrel

Actinopterygii Cypriniformes Catostomidae Campostomus commersonii White sucker Actinopterygii Cypriniformes Catostomidae Erimyzon oblongus Creek chubsucker Actinopterygii Cypriniformes Cyprnidae Cyprinus carpio Common carp Actinopterygii Cypriniformes Cyprnidae Notemigonus crysoleucas Golden shiner Actinopterygii Cypriniformes Cyprnidae Notropis hudsonius Spottail shiner Actinopterygii Cypriniformes Cyprnidae Notropis atherinoides Emerald shiner Actinopterygii Cypriniformes Cyprnidae Phinichthys atratulus Blacknose dace Actinopterygii Cypriniformes Cyprnidae Semotilus atromaculatus Creek chub Actinopterygii Esociformes Esocidae Esox niger Chain pickerel Chordata Animalia Actinopterygii Perciformes Centrarchidae Amblopites rupestris Rock bass Actinopterygii Perciformes Centrarchidae Lepomis gibbosus Pumpkinseed Actinopterygii Perciformes Centrarchidae Lepomis macrochirus Bluegill Actinopterygii Perciformes Centrarchidae Lepomis auritus Redbreast sunfish Actinopterygii Perciformes Centrarchidae Micropterus salmoides Largemouth bass Actinopterygii Perciformes Centrarchidae Micropterus dolomieu Smallmouth bass Actinopterygii Perciformes Percidae Etheostoma olmstedi Tessellated darter

203 Table 2 (Cont'd). All taxa observed at Brookwood Point Conservation Area on 27 June 2014 (between 9am and 2pm).

Actinopterygii Perciformes Percidae Perca flavescens Yellow perch Actinopterygii Perciformes Percidae Sander vitreus Walleye Actinopterygii Salmoniformes Salmoniformes Salmonidae coregonus Lake whitefish

Chordata Actinopterygii Scorpaeniformes Cottidae Cottus cognatus Slimy sculpin Actinopterygii Siluriformes Ictaluridae Ameriurus nebulosus Brown bullhead

Bivalvia Unionoida Unionoida Lampsilis radiata Eastern lampmussel Bivalvia Veneroida Dreissenidae Dreissena polymorpha Zebra mussel

AnimaliaMollusca Gastropoda Animalia Physidae Physa Freshwater snail

Malacostraca Decapoda Cambaridae Cambarus bartonii Common crayfish Malacostraca Decapoda Cambaridae Orconectes rusticus Rusty Crayfish Animalia Arthropoda Entognatha Subclass: Collembola sp. Springtail

Insecta Coleoptera Carabidae sp. Beetle Insecta Coleoptera Cerambycidae sp. Beetle Insecta Coleoptera Curculionidae sp. Beetle Insecta Coleoptera Lampyridae sp. Beetle Insecta Coleoptera Tenebrionidae sp. Beetle Insecta Diptera Callphonidae 2 distinct species Midge Insecta Diptera Chironomidae sp. Midge Insecta Diptera Culicidae sp. Midge Insecta Diptera Muscoid sp. Midge Insecta Diptera Simuliidae Simulium sp. Blackfly Insecta Diptera Syrphidae 2 distinct species Midge Insecta Diptera Tipulidae Hexatoma sp. Midge Insecta Ephemeroptera Baetidae Baetis sp. Mayfly Insecta Ephemeroptera Ephemerellidae Drunella sp. Mayfly Insecta Ephemeroptera Ephemeridae Hexagenia sp. Mayfly Insecta Ephemeroptera Heptageniidae Epeorus sp. Mayfly Insecta Ephemeroptera Heptageniidae Stenacron sp. Mayfly Insecta Ephemeroptera Isonychiidae Isonychia sp. Mayfly Insecta Hemiptera Cercopoidea 5 distinct species Spittlebug Insecta Hymenoptera Apidae Bombus sp. Bumble bee

Animalia Insecta Hymenoptera Formicidae 2 distinct species Ant Arthropoda Insecta Lepidoptera Erebidae Lymantria dispar North American gypsy moth Insecta Lepidoptera Papilionidae Papilio sp. Eastern tiger swallowtail Insecta Lepidoptera Pieridae Pieris sp. White butterfly Insecta Megaloptera Corydalidae Nigronia serricornis Dobsonfly Insecta Odonata Aeshnidae Boyeria sp. Dragonfly Insecta Odonata Coenagrionidae Coenagrion sp. Damselfly Insecta Odonata Cordulidae Epitheca sp. Dragonfly Insecta Odonata Gomphidae Gomphus sp. Dragonfly Insecta Plecoptera Capniidae Allocapnia sp. Stonefly Insecta Plecoptera Leuctridae sp. Stonefly Insecta Plecoptera Perlidae Acroneuria carolinensis Stonefly Insecta Plecoptera Perlodidae Isoperla sp. Stonefly Insecta Psocoptera sp. booklice, barklice, or barkflies Insecta Trichoptera Glossosomatidae Glossosoma sp. Caddisfly Insecta Trichoptera Hydropsychidae Ceratopsyche sp. Caddisfly Insecta Trichoptera Philopotamidae Wormaldia sp. Caddisfly Insecta Trichoptera Rhyacophilidae Rhyacophila sp. Caddisfly Insecta Trichoptera Uenoidae Neophylax sp. Caddisfly

Arachnida Araneae Lycosidae sp. Wolf spider

Arachnida Araneae Tetragnathidae Tetragnatha elongata Elongate stilt spider Animalia Arthropoda Arachnida Opiliones sp. Daddy longlegs/harvestman

204 Table 2 (Cont'd). All taxa observed at Brookwood Point Conservation Area on 27 June 2014 (between 9am and 2pm).

Secernentea Camallanida Camallanidea Camallanus sp. Nematode

Nematoda sp. 1 Nematode

Cestoda Proteocephalidea Proteocephalidae Proteocephalus sp. Animalia Monogenea Flatworm Trematoda Azygiida Azygiidae Azygia sp Trematode

Platyhelminthes Trematoda sp. 1 Trematode

PLANTS

Kingdom Division Class Order Family Genus Species Common Name

Magnoliopsida Alismatales Araceae Arisaema triphyllum Jack-in-the-pulpit Magnoliopsida Alismatales Araceae Symplocarpus foetidus Eastern skunk cabbage Magnoliopsida Apiaes Apiaceae Aegopodium podagraria Bishop weed or Goutweed Magnoliopsida Asparagales Asparagaceae Convallaria majalis Lily of the valley Magnoliopsida Asparagales Asparagaceae Maianthemum racemosum False Solomon's seal Magnoliopsida Asparagales Xanthorrhoeaceae Hemerocallis fulva Day lily Magnoliopsida Asterales Asteraceae Arctium minus Lesser burdock Magnoliopsida Asterales Asteraceae Bidens sp. Beggerticks Magnoliopsida Asterales Asteraceae Cirsium muticum Swamp thistle or marsh thistle Magnoliopsida Asterales Asteraceae Erigeron annuus Eastern daisy fleabane Magnoliopsida Asterales Asteraceae Euthamia graminifolia Grass-leaved goldenrod Magnoliopsida Asterales Asteraceae Eutrochium maculatum Spotted joe-pye weed\ Magnoliopsida Asterales Asteraceae Hieracium aurantiacum Orange hawkweed Magnoliopsida Asterales Asteraceae Inuleae inula Horse-heal Magnoliopsida Asterales Asteraceae Lapsana communis Nipplewort Magnoliopsida Asterales Asteraceae Solidago sp. Goldenrod Magnoliopsida Asterales Asteraceae Tanacetum parthenium Feverfew Magnoliopsida Brassicales Brassicaceae Cardamine pratensis Cuckoo flower Magnoliopsida Brassicales Brassicaceae Hesperis matronalis Dame's rocket Magnoliopsida Brassicales Brassicaceae Rorippa nasturtium-aquaticum Wastercress Stellaria pubera

Plantae Magnoliopsida Caryophyllales Caryophyllaceae Great chickweed Magnoliopsida Caryophyllales Caryophyllaceae Stellaria media Common chickweed Magnoliophyta Magnoliopsida Caryophyllales Caryophyllaceae Stellaria griminea Common stitchwort Magnoliopsida Caryophyllales Polygonaceae Persicaria hydropiper Smartweed Magnoliopsida Caryophyllales Polygonaceae Rumex crispus Curly dock Magnoliopsida Celastrales Celastraceae Celastrus orbiculata Oriental bittersweet Magnoliopsida Cornales Cornaceae Cornus alternifolia Green osier or pagoda dogwood Magnoliopsida Dipsacales Valerianaceae Valeriana officinalis Common valerian Magnoliopsida Ericales Balsaminaceae Impatiens capensis Spotted jewelweed Magnoliopsida Ericales Myrsinaceae Lysimachia nummularia Creeping Jenny Magnoliopsida Ericales Myrsinaceae Lysimachia terrestris Swamp candles Magnoliopsida Fabales Fabaceae Amorpha fruiticosa False indigo Magnoliopsida Fabales Fabaceae Amphicarpaea bracteata Hog peanut Magnoliopsida Fabales Fabaceae Robinia pseudoacacia Black locust Magnoliopsida Fabales Fabaceae Securigera varia Crown vetch Magnoliopsida Fabales Fabaceae Trifolium repens White clover Magnoliopsida Fabales Fabaceae Trifolium dubium Hop clover Magnoliopsida Fagales Betulaceae Alnus rugosa Speckled alder Magnoliopsida Fagales Betulaceae Carpinus caroliniana Musclewood Magnoliopsida Fagales Betulaceae Corylus sp. Hazelnut

205 Table 2 (Cont'd). All taxa observed at Brookwood Point Conservation Area on 27 June 2014 (between 9am and 2pm).

Magnoliopsida Fagales Fagaceae Quercus rubra Red oak Magnoliopsida Fagales Juglandaceae Carya sp. Hickory Magnoliopsida Gentianales Ascleiadaceae Asclepias syriaca Common milkweed Magnoliopsida Gentianales Rubiaceae Galium odoratum Wild baby's breath Magnoliopsida Gentianales Rubiaceae Galium sp. Bedstraw Magnoliopsida Geraniales Geraniaceae Geranium robertainum Herb Robert Magnoliopsida Lamiales Lamiaceae Glechoma hederacea Gill-over-the-ground Magnoliopsida Lamiales Lamiaceae Prunella vulgaris Self-heal Magnoliopsida Lamiales Oleaceae Fraxinus americana White ash Magnoliopsida Lamiales Oleaceae Syringa vulgaris Lilac Magnoliopsida Lamiales Plantaginaceae Digitalis purpurea Common foxglove Magnoliopsida Lamiales Plantaginaceae Plantago major Broadleaf plantain Magnoliopsida Lamiales Plantaginaceae Veronica salicifolia Willow-leaf herb Magnoliopsida Lamiales Plantaginaceae Veronica arvensis Speedwell Magnoliopsida Lamiales Scrophulariaceae Verbascum thapsus Common mullein Magnoliopsida Liliales Liliaceae Lilium parryi Lemon lily Magnoliopsida Liliales Melanthiaceae Veratrum viride False hellebore Magnoliopsida Malpighiales Salicaceae Populus tremuloides Quaking aspen Magnoliopsida Myrtales Onocleaceae Oenothera biennis Evening primrose Magnoliopsida Oxalidales Oxalidaceae Oxalis stricta Yellow woodsorrel Magnoliopsida Pinales Cupressaceae Chamaecyparis thyoides Atlantic whitecedar Magnoliopsida Poales Cyperaceae Carex livida Sedge Magnoliopsida Poales Cyperaceae Carex vulpinoidea Fox sedge Magnoliopsida Poales Cyperaceae Scirpus sp. Bulrush Magnoliopsida Poales Juncaceae Juncus sp. Rush Plantae Magnoliopsida Poales Poaceae Anthoxanthum odoratum Sweet vernal grass

Magnoliophyta Magnoliopsida Poales Poaceae Dactylis sp. Orchard grass Magnoliopsida Poales Typhaceae Sparganium americanum Burr-reed Magnoliopsida Polypodiales Onocleaceae Matteuccia struthiopteris Ostrich fern Magnoliopsida Ranuculales Papaveraceae Chelidonium majus Greater celandine Magnoliopsida Ranunculales Berberidaceae Berberis vulgaris Berberry Magnoliopsida Ranunculales Ranunculaceae Ranunculus sp. Buttercup Magnoliopsida Ranunculales Ranunculaceae Ranunculus repens Creeping buttercup Magnoliopsida Ranunculales Ranunculaceae Thalictrum sp. Rue Magnoliopsida Ranunculales Ranunculaceae Thalictrum dioicu Meadow rue Magnoliopsida Rosales Rhamnaceae Rahamunus cathartica Common buckthorn Magnoliopsida Rosales Rosaceae Agrimonia sp. Agrimony Magnoliopsida Rosales Rosaceae Crataegus sp. Hawthorn Magnoliopsida Rosales Rosaceae Filipendula ulmaria Meadowsweet Magnoliopsida Rosales Rosaceae Fragaria virginiana Stawberry Magnoliopsida Rosales Rosaceae Geum canadense White avens Magnoliopsida Rosales Rosaceae Rosa multiflora Multiflora rose Magnoliopsida Rosales Rosaceae Rubus odoratus Purple flowering raspberry Magnoliopsida Rosales Urticaceae Pilea pumila Canadian clearweed Magnoliopsida Sapindales Sapindaceae Acer rubrum Red maple Magnoliopsida Sapindales Sapindaceae Acer saccharum Sugar maple Magnoliopsida Sapindales Sapindaceae Acer saccharinum Silver maple Magnoliopsida Vitales Vitaceae Parthenocissus quinquefolia Virginia creeper Magnoliopsida Vitales Vitaceae Vitis sp. Grapevine

Pinopsida Pinales Pinaceae Tusga canadensis Hemlock Plantae Pinophyta

Polypodiopsida Polypodiales Onocleaceae Onoclea sensibilis Sensitive fern Plantae Equisetopsida Equisetales Equisetaceae Equisetum sp. Horsetail Tracheophyta

206 Table 2 (Cont'd). All taxa observed at Brookwood Point Conservation Area on 27 June 2014 (between 9am and 2pm).

OTHER

Genus

Kingdom Division Class Order Family Species Common Name

Bacillariophyceae Cymbellales Cymbellaceae Cymbella sp. Algae

Bacillariophyceae Naviculales Naviculaceae Navicula sp. Algae

Chromalveolata Bacillariophyceae Fragilaria sp. Algae

Melosira sp. Algae Diatoms

Zygnemophyceae Desmidales Desmidiaceae Cosmarium sp. Algae Protista

ChlorophytaChlorophyceae Heterokontophyta Sphaeropleales Scenedesmaceae Desmodesmus sp. Algae (spineless form) Viridiplantae Nitzia sp. Algae Synedra sp. Algae

Ameoba Nanoplankton cells Rotifers

207 Table 3. All taxa observed at Fetterley Forest Conservation Area on 12 July 2014 (between 10am and 2pm).

ANIMALS

Kingdom Phylum Class Order Family Genus Species Common Name

Aves Columbiformes Columbidae Zenaida macroura Mourning dove Aves Passeriformes Cardinalidae Prianga olivacea Scarlet tanager Aves Passeriformes Corvidae Corvus brachyrchynchos American crow Aves Passeriformes Corvidae Cyanocitta cristata Blue jay Aves Passeriformes Emberizidae Junco hyemalis Dark-eyed junco Aves Passeriformes Emberizidae Melospiza melodia Song sparrow Aves Passeriformes Emberizidae Piplio erythropthalmus Eastern towhee Aves Passeriformes Fringillidae Carduelis tristis American goldfinch Aves Passeriformes Mimidae Dumetella carolinensis Gray Catbird Aves Passeriformes Paridae Poecile atricapillus Black-capped chickadee Aves Passeriformes Parulidae Geothlypis trichas Common yellowthroat Aves Passeriformes Parulidae Setophaga pensylvanica Chestnut-sided warbler Chordata Animalia Aves Passeriformes Parulidae Setophaga virens Black-throated green warbler Aves Passeriformes Troglodytidae Troglodytes aedon House wren Aves Passeriformes Turdidae Catharus guttatus Hermit thrush Aves Passeriformes Turdidae Hylocichla mustelina Wood thrush Aves Passeriformes Turdidae Turdus migratorius Robin Aves Passeriformes Tyrannidae Contopus virens Eastern pewee Aves Passeriformes Vireonidae Vireo olivaceus Red-eyed vireo Aves Piciformes Picidae Colaptes auratus Northern flicker Aves Piciformes Picidae Picoides villosus Hairy woodpecker Aves Piciformes Picidae Sphyrapicus varius Yellow-bellied sapsucker

Amphibia Anura Bufonidae Anaxyrus americanus American toad Amphibia Anura Hylidae Pseudacris crucifer Spring peeper Amphibia Caudata Plethodontidae Eurycea bislineata Northern two-lined salamander Amphibia Caudata Plethodontidae Plethodon cinereus Red-backed salamander Chordata Animalia Amphibia Caudata Salamandridae Notophthalmus viridenscens Red eft or Eastern newt Amphibia Caudata Salamandridae Newt

Mammalia Rodentia Sciuridae Marmota monax Groundhog or Woodchuck Mammalia Rodentia Sciuridae Tamias striatus Eastern chipmunk Mammalia Rodentia Sciuridae Tamiasciurus hudsonicus American red squirrel Chordata Animalia Reptilia Squamata Colubridae Thamnophis Garter snake

Insecta Coleoptera Carabidea Beetle Insecta Coleoptera Cerambycidae Longhorn beetle Insecta Coleoptera Coccienllidae Ladybug Insecta Coleoptera Curculionoidae weevils Insecta Coleoptera Elateridae Click beetle Insecta Coleoptera Haliplidae Peltodytes Beetle Insecta Coleoptera Lampyridae Firefly Insecta Coleoptera Lycidae Net-winged beetle Insecta Coleoptera Scarabaeidae Popillia japonica Japanese beetle Insecta Coleoptera Scarabaeidae Scarab beetle Insecta Coleoptera Staphylinoidea Beetle Insecta Coleoptera Tenebrionoidea (superfamily) Beetle Insecta Coleoptera Vesperidae Beetle Insecta Diptera Asilidae Assassin fly Insecta Diptera Calliphoridae Blow fly Insecta Diptera Chrionomidae nonbiting midge Insecta Diptera Culicidae Aedes sp. Mosquito Insecta Diptera Syrphidae Hoverfly Animalia Arthropoda Insecta Diptera Tabanadae True fly Insecta Diptera Tachinidae Tachina fly Insecta Diptera Tipulidae Cranefly Insecta Hemiptera Coreidae Squash bug Insecta Hemiptera Corixidae Water boatman Insecta Hemiptera Gerridae Water glider Insecta Hemiptera Membracidae Treehopper Insecta Hemiptera Notonectidae Notonecta Backswimmer Insecta Hemiptera Pentatomidae Stink bugs Insecta Hemiptera Reduviidae Assassin bug Insecta Hempitera Cicadellidae Hoppers or leaf hopper Insecta Hymenoptera Apidae Bee Insecta Hymenoptera Formicidae Ant Insecta Hymenoptera Halictidae Bee Insecta Hymenoptera Ichneumonidae Ichneumon wasp

208 Table 3 (Cont'd). All taxa observed at Fetterley Forest Conservation Area on 12 July 2014 (between 10am and 2pm).

Insecta Lepidoptera Geometridae Moth Insecta Lepidoptera Hesperiidae Skipper butterfly Insecta Lepidoptera Noctuidae Owlet moth Insecta Lepidoptera Nymphalidae Danaini plexippus Monarch butterfly Insecta Lepidoptera Papilionidae Papilio glaucus Eastern Tiger swallowtail Insecta Lepidoptera Pieridae Butterfly Insecta Mecoptera Panorpidae Scorpion fly Insecta Odonata Coenagrionidae damselfly Insecta Odonata Lestidae Lestes Damselfly Insecta Odonata Libellulidae Dragonfly Insecta Orthoptera Acrididae Grasshopper Insecta Orthoptera Gryllidae Cricket Insecta Orthoptera Tetrigidae Cricket Insecta Orthoptera Tettigoniidae Grasshopper

Chilopoda Centipede

Arachnida Acari (subclass) Mite Arachnida Araneae Lycosidae Wolf spider Animalia

ArthropodaArachnida Araneae Arthropoda Salticidae Jumping spider Arachnida Opiliones Harvestmen

Clitellata Hirudinea Leech Annelida

AnimaliaGastropoda Animalia Snail

Gastropoda Slug

PLANTS

Kingdom Division Class Order Family Genus Species Common Name

Magnoliopsida Alismatales Araceae Arisaema triphyllum Jack-in-the-pulpit Magnoliopsida Apiales Apiaceae Aralia nudicaulis Wild sasparilla Magnoliopsida Apiales Apiaceae Cicuta sp. Poison parsnip Magnoliopsida Apiales Apiaceae Daucus carota Queen Anne's lace Magnoliopsida Asparagales Amarylidaceae Allium tricoccum Ramps Magnoliopsida Asparagales Asparagaceae Maianthemum canadense Canadian mayflower Magnoliopsida Asparagales Asparagaceae Smilacina racemosa False Soloman's seal Magnoliopsida Asparagales Orchidaceae Epipactis helliborine Helleborine Magnoliopsida Asterales Asteraceae Ambrosia artemesiafolia Ragweed Magnoliopsida Asterales Asteraceae Arctium minus Burdock Magnoliopsida Asterales Asteraceae Aster acuminatus Whorled wood aster Magnoliopsida Asterales Asteraceae Aster divaricatus White wood aster Magnoliopsida Asterales Asteraceae Aster prananthoides Crooked stem aster Magnoliopsida Asterales Asteraceae Aster vimineus Small white aster Magnoliopsida Asterales Asteraceae Bidens sp. Bur marigold Magnoliopsida Asterales Asteraceae Carduus crispus Welted thistle Magnoliopsida Asterales Asteraceae Centaurea maculosa Spotted knapweed Magnoliopsida Asterales Asteraceae Chrysanthemum leucanthemum Ox-Eye daisy

Plantae Magnoliopsida Asterales Asteraceae Cirsium palustre Marsh thistle Cirsium altissimum

MagnoliophytaMagnoliopsida Asterales Asteraceae Mollusca Tall thistle Magnoliopsida Asterales Asteraceae Cirsium vulgare Thistle Magnoliopsida Asterales Asteraceae Erigeron annuus Daisy fleabane Magnoliopsida Asterales Asteraceae Hieracium auranticum Red paint brush Magnoliopsida Asterales Asteraceae Lapsana communis Nipplewort Magnoliopsida Asterales Asteraceae Rudbeckia hirta Black-eyed susan Magnoliopsida Asterales Asteraceae Solidago rugosa Rough-stemmed goldenrod Magnoliopsida Asterales Asteraceae Solidago sp. Goldenrod Magnoliopsida Asterales Asteraceae Tussilago farfara Coltsfoot Magnoliopsida Brassicales Brassicaceae Allaria petiolata Garlic mustard Magnoliopsida Brassicales Brassicaceae Barbarea vulgaris Black mustard Magnoliopsida Brassicales Brassicaceae Hesperis matronalis Dame's rocket Magnoliopsida Caryophyllales Caryophyllaceae Lychnis flos-cuculi Ragged robin Magnoliopsida Caryophyllales Caryophyllaceae Stellaria media Chickweed Magnoliopsida Caryophyllales Polygonaceae Fallopia japonica Japanese bamboo Magnoliopsida Caryophyllales Polygonaceae Rumex crispus Curled dock

209 Table 3 (Cont'd). All taxa observed at Fetterley Forest Conservation Area on 12 July 2014 (between 10am and 2pm).

Magnoliopsida Cornales Cornaceae Cornus alternifolia Alternate-leaved dogwood Magnoliopsida Cornales Cornaceae Cornus canadensis Bunchberry Magnoliopsida Dipsacales Adoxaceae Viburnum acerifolium Maple leaved viburnum Magnoliopsida Dipsacales Adoxaceae Viburnum lantanoides Hobblebush Magnoliopsida Dipsacales Adoxaceae Viburnum lentago Nannyberry Magnoliopsida Dipsacales Caprifoliaceae Lonicera sp. Honeysuckle Magnoliopsida Dipsacales Valerianaceae Valeriana officinalis Valarian, Garden heliotrope Magnoliopsida Ericales Balsaminaceae Impatiens capensis Impatience Magnoliopsida Ericales Ericaceae Gaultheria procumbens Wintergreen Magnoliopsida Ericales Ericaceae Monotropa uniflora Dutchman's pipe Magnoliopsida Ericales Ericaceae Pyrola rotundifolia Shinleaf, Pyrola Magnoliopsida Ericales Ericaceae Vaccinium sp. Blueberry Magnoliopsida Ericales Myrsinaceae Lysimachia ciliata Fringed loosestrife Magnoliopsida Ericales Myrsinaceae Trientalis borealis Star flower Magnoliopsida Fabales Fabaceae Amphicarpaea bracteata Hog peanut Magnoliopsida Fabales Fabaceae Lotus corniculatus Bird's foot trefoil Magnoliopsida Fabales Fabaceae Trifolium aureum Hop-Clover Magnoliopsida Fabales Fabaceae Trifolium campestre Low hop-clover Magnoliopsida Fabales Fabaceae Trifolium dubium Small hop clover Magnoliopsida Fabales Fabaceae Trifolium hybridum Alsike clover Magnoliopsida Fabales Fabaceae Trifolium pratense Red clover Magnoliopsida Fabales Fabaceae Trifolium repens White clover Magnoliopsida Fabales Fabaceae Vicia cracca Cow vetch Magnoliopsida Fabales Fabaceae Vicia tetrasperma Four seeded vetch Magnoliopsida Fabales Fabaceae Vicia varia Crown vetch Magnoliopsida Fagales Betulaceae Betula papyrifera White birch Magnoliopsida Fagales Betulaceae Betula alleghaniensis Yellow birch Magnoliopsida Fagales Betulaceae Corylus sp. Hazelnut Magnoliopsida Fagales Betulaceae Ostrya cordifolia Musclewood Magnoliopsida Fagales Betulaceae Ostrya virginiana Eastern hophornbeam Magnoliopsida Fagales Fagaceae Fagus grandifolia American beech Magnoliopsida Fagales Fagaceae Quercus rubra Northern red oak Magnoliopsida Fagales Juglandaceae Carya sp. Hickory Magnoliopsida Fagales Juglandaceae Carya ovata Shagbark hickory Magnoliopsida Gentianales Asclepiadaceae Asclepias syriaca Milkweed Magnoliopsida Gentianales Rubiaceae Asperula arvensis Woodruff Magnoliopsida Gentianales Rubiaceae Gallium sp Bedstraw Magnoliopsida Gentianales Rubiaceae Mitchella repens Partridge berry Magnoliopsida Geraniales Geraniaceae Geranium robertainum Herb Robert Plantae Magnoliopsida Iridaceae Iridoideae Sisyrinchium angustifolum Blue-Eyed grass

Magnoliophyta Magnoliopsida Lamiales Lamiaceae Clinopodium vulgare Wild basil Magnoliopsida Lamiales Lamiaceae Galeopsis tetrahit Hemp nettle Magnoliopsida Lamiales Lamiaceae Prunella vulgaris Heal-all Magnoliopsida Lamiales Lamiaceae Scutellaria lateriflora Mad-dog skullcap Magnoliopsida Lamiales Oleaceae Fraxinus americana American white ash Magnoliopsida Lamiales Orobranchaceae Melampyrum lineare Cow wheat Magnoliopsida Lamiales Plantaginaceae Plantago lanceolata English plantain Magnoliopsida Lamiales Plantaginaceae Plantago canadense Plaintain Magnoliopsida Lamiales Plantaginaceae Veronica officinalis Speedwell Magnoliopsida Lamiales Scrophulariaceae Verbascum thapsus Mullein Magnoliopsida Lamiales Verbenaceae Verbena hastata Blue vervain Magnoliopsida Lamiales Verbenaceae Verbena urticifolia White verbena Magnoliopsida Liliales Colchicaceae Uvularia sessilifolia Bellwort Magnoliopsida Liliales Lilaceae Clintonia borealis Bluebeads Magnoliopsida Liliales Melantahiaceae Trillium erectum Red trillium Magnoliopsida Malpighiales Hypericaceae Hypericum punctatum Spotted St Johnswort Magnoliopsida Malpighiales Salicaceae Populus deltoides Cottonwood Magnoliopsida Malpighiales Salicaceae Populus grandidentata Big-tooth aspen Magnoliopsida Malpighiales Salicaceae Populus tremuloides Quaking aspen Magnoliopsida Malpighiales Violaceae Viola sp. Violet Magnoliopsida Malvales Malvaceae Malva moschata Musk mallow Magnoliopsida Malvales Malvaceae Tilia americana Basswood Magnoliopsida Myrtales Onagraceae Circaea alpina Dwarf enchanter's nightshade Magnoliopsida Myrtales Onagraceae Circaea lutetiana Enchanter's nightshade Magnoliopsida Myrtales Onagraceae Epilobium coloratum Purple leaved willow herb Magnoliopsida Myrtales Onagraceae Epilobium glandulosum Northern willow herb Magnoliopsida Oxalidales Oxalidaceae Oxalis stricta Yellow wood sorrel Magnoliopsida Poales Cyperaceae Carex sp. Sedge Magnoliopsida Poales Cyperaceae Carex lurida Sedge Magnoliopsida Poales Cyperaceae Carex vulpinoidea Fox sedge Magnoliopsida Poales Juncaceae Juncus sp. Rush Magnoliopsida Poales Poaceae Glyberia sp. Grass Magnoliopsida Poales Poaceae Phleum sp. Timothy grass Magnoliopsida Ranunculales Berberidaceae Caulophyllum thalictrodes Blue cohosh Magnoliopsida Ranunculales Berberidaceae Podophyllum peltatum Mayapple Magnoliopsida Ranunculales Ranunculaceae Actaea pachypoda Doll's eye

210 Table 3 (Cont'd). All taxa observed at Fetterley Forest Conservation Area on 12 July 2014 (between 10am and 2pm).

Magnoliopsida Ranunculales Ranunculaceae Actaea rubra Baneberry Magnoliopsida Ranunculales Ranunculaceae Aqualigia canadensis Columbine Magnoliopsida Ranunculales Ranunculaceae Clematis sp. Woodbine Magnoliopsida Ranunculales Ranunculaceae Ranunculus acris Common buttercup Magnoliopsida Ranunculales Ranunculaceae Ranunculus hispidus Hispid buttercup Magnoliopsida Ranunculales Ranunculaceae Ranunculus recurvatus Hooked buttercup Magnoliopsida Ranunculales Ranunculaceae Ranunculus repens Creeping buttercup Magnoliopsida Ranunculales Ranunculaceae Taraxicum officinale Dandelion Magnoliopsida Ranunculales Ranunculaceae Thalictrum sp. Rue Magnoliopsida Rosales Rosaceae Agrimonia sp. Agrimony Magnoliopsida Rosales Rosaceae Amelanchier laevis Shadbush Magnoliopsida Rosales Rosaceae Crataegus sp. Hawthorn Magnoliopsida Rosales Rosaceae Fragaria virginiana Strawberry Magnoliopsida Rosales Rosaceae Geum canadense White avens Magnoliopsida Rosales Rosaceae Geum virginianum Rough cinquefoil Magnoliopsida Rosales Rosaceae Prunus serotina Black cherry

Plantae Magnoliopsida Rosales Rosaceae Prunus virginia Choke cherry

Magnoliophyta Magnoliopsida Rosales Rosaceae Rosa multiflora Multiflora rose Magnoliopsida Rosales Rosaceae Rubus allegheniensis Northern blackberry Magnoliopsida Rosales Rosaceae Rubus idaeus Red raspberry Magnoliopsida Rosales Rosaceae Rubus rubus odoratus Purple flowering raspberry Magnoliopsida Rosales Urticaceae Pilea pumila Canadian clearweed Magnoliopsida Sapindales Aceraceae Acer pensylvanicum Moosewood, Striped Magnoliopsida Sapindales Anarcardiaceae Rhus hirta Staghorn sumac Magnoliopsida Sapindales Sapindaceae Acer rubrum Red maple Magnoliopsida Sapindales Sapindaceae Acer saccharum Sugar maple Magnoliopsida Saxifragales Hamamelidaceae Hamamelis virginiana Witch hazel Magnoliopsida Saxifragales Saxifragaceae Tiarella cordifolia Foam flower Magnoliopsida Solanales Solanaceae Solanum nigra Black nightshade Magnoliopsida Solanales Solanaceae sp. Nightshade Magnoliopsida Vitales Vitaceae Vitus sp. Grape

Pinopsida Pinales Pinaceae Larix decidua Tamarack Pinopsida Pinales Pinaceae Picea rubens Red spruce Pinopsida Pinales Pinaceae Pinus strobus Eastern white pine Plantae Pinophyta Pinopsida Pinales Pinaceae Tsuga canadensis Eastern hemlock

Polypodiopsida Osmundales Osmundaceae Osmundastrum cinnamomea Cinnamon fern Polypodiopsida Polypodiales Dennstaedtiaceae Dennstaedtia punctilobula Hay-scented fern Polypodiopsida Polypodiales Dennstaedtiaceae Pteridium aquilinum Northern bracken fern Polypodiopsida Polypodiales Dryopteridaceae Dryopteris intermedia Intermediate woodfern Polypodiopsida Polypodiales Dryopteridaceae Polystichium acrostichoides Christmas fern Onoclea sensibilis Plantae Polypodiopsida Polypodiales Onocleaceae Sensitive fern

Tracheophyta Polypodiopsida Polypodiales Polypodiaceae Polypodium virginianum Rock polypody Polypodiopsida Polypodiales Pteridaceae Adiantum pedatum Maidenhair fern Polypodiopsida Polypodiales Thelpteridaceae Thelypteris noveboracensis New York fern Polypodiopsida Polypodiales Woodsiaceae Athyrium filix-femina Ladyfern

Agaricomycetes Gomphales Gomphaceae Gomphus floccosus Scaly chanterelle Fungi Agaricomycetes Polyporales Ganodermataceae Ganoderma applanatum Artist's bracket Basidiomycota

211 Table 4. All taxa observed at Compton Bridge Conservation Area on 30 July 2014 (between 10am and 2pm).

Kingdom Phylum Class Order Family Genus Species Common Name

Aves Columbiformes Columbidae Zenaida macroura Mourning dove Aves Coraciiformes Cerylidae Megaceryle alcyon Belted kingfisher Aves Falconiformes Accipitridae Buteo jamaicensis Red-tailed hawk Aves Passeriformes Bombycillidae Bombycilla cedrorum Cedar waxwing Aves Passeriformes Corvidae Corvus brachyrchynchos American crow Aves Passeriformes Corvidae Cyanocitta cristata Blue jay Aves Passeriformes Emberizidae Melospiza melodia Song sparrow Aves Passeriformes Mimidae Dumetella carolinensis Gray catbird Aves Passeriformes Parulidae Geothlypis trichas Common yellowthroat Aves Passeriformes Tyrannidae Sayornis phoebe Eastern phoebe

Mammalia Lagomorpha Leporidae Sylvilagus floridanus Eastern cottontail

Anaxyrus americanus Chordata

Animalia Amphibia Anura Bufonidae American toad Amphibia Anura Ranidae Lithobates clamitans Green frog

Actinopterygii Cypriniformes Catostomidae Campostomus commersonii White sucker Actinopterygii Cypriniformes Cyprnidae Phinichthys atratulus Blacknose dace Actinopterygii Perciformes Percidae Etheostoma olmstedi Tessellated darter

Bivalvia Unionoida Unionidae Alasmidonta marginata Elktoe Bivalvia Unionoida Unionidae Elliptio complanata Eastern elliptio Bivalvia Unionoida Unionidae Lampsilis radiata Eastern lampmussel Bivalvia Unionoida Unionidae Strophitus undulatus Squawfoot Bivalvia Veneroida Dreissenidae Dreissena polymorpha Zebra mussel

Bivalvia Veneroida Sphaeriidae Pisidium sp. Pea clam

Animalia Physa sp. Mollusca Gastropoda Physidae Freshwater snail

Malacostraca Amphipoda Gammaridae Gammarus sp. Amphipod Malacostraca Decapoda Cambaridae Orconectes rusticus Rusty crayfish

Insecta Coleoptera Cerambycidae sp. Longhorn beetle Insecta Coleoptera Chrysomelidae sp. Leaf beetle Insecta Coleoptera Cocineellidae sp. Lady bug Insecta Coleoptera Curculionoidae sp. Weevils Insecta Coleoptera Elmidae Optioservus sp. Riffle beetle Insecta Coleoptera Elmidae Stenelmis sp. Beetle Insecta Coleoptera Hydrophilidae sp. Beetle Insecta Coleoptera Psephenidae Psephenus sp. Beetle Insecta Coleoptera Scarabaeidae sp. Scarab beetle Insecta Diptera Athericidae Atherix sp. True fly Insecta Diptera Calliphoridae sp. Blow fly Insecta Diptera Conopidae sp. Thick-headed fly Insecta Diptera Culicidae sp. Moquito Insecta Diptera Sarcophagidae sp. Flesh fly Insecta Diptera Syrphidae sp. Hoverfly Insecta Diptera Tabanidae Chrysops sp. Deer fly Insecta Diptera Tachinidae sp. True fly Insecta Ephemeroptera Baetidae Baetis sp. Mayfly Caenis sp.

Animalia Insecta Ephemeroptera Caenidae Mayfly Arthropoda Insecta Ephemeroptera Heptageniidae McCaffertium sp. Mayfly Insecta Ephemeroptera Isonychiidae Isonychia sp. Mayfly Insecta Hemiptera Cercopidae sp. Froghopper Insecta Hemiptera Gerridae Gerris sp. Water strider Insecta Hemiptera Miridae sp. Plant bugs Insecta Hemiptera Veliidae Rgagovelia sp. Aquatic bugs Insecta Hymenoptera Apidae sp. Native bee Insecta Hymenoptera Formicidae sp. Ant Insecta Hymenoptera Ichneumonidae sp. Ichneumon wasp Insecta Lepidoptera Nymphalidae sp. Butterfly Insecta Megaloptera Corydalidae Nigronia sp. Dobsonfly Insecta Megaloptera Sailidae Sailis sp. Alderfly Insecta Odonata Calopterygidae Calopteryx sp. Damselfly Insecta Odonata Libellulidae sp. Skimmer Insecta Orthoptera Acrididae sp. Grasshopper Insecta Orthoptera Tettigoniidea sp. Grasshopper Insecta Plecoptera Perlidae Acroneuria sp. Stonefly Insecta Trichoptera Hydropsychidae Cheumatopsyche sp. Caddisfly Insecta Trichoptera Uenoidae Neophyla sp. Caddisfly 212 Table 4 (Cont'd). All taxa observed at Compton Bridge Conservation Area on 30 July 2014 (between 10am and 2pm).

Arachnida Araneae Lycosidae sp. Wolf spider Arachnida Araneae Tetragnathidae sp. Long-jawed orb weaver Animalia Arthopoda Arachnida Opiliones sp. Harvestmen

PLANTS

Kingdom Division Class Order Family Genus Species Common Name Magnoliopsida Alismatales Alismataceae Sagittaria rigida Arrowhead Magnoliopsida Alismatales Araceae Arisaema triphyllum Jack-in-the-pulpit Magnoliopsida Alismatales Araceae Symplocarpus foetidus Skunk weed Magnoliopsida Apiaes Apiaceae Aegopodium podagraria Bishop weed or Goutweed Magnoliopsida Apiales Apiaceae Angelica atropurpurea Sweet angelica Magnoliopsida Apiales Apiaceae Cicuta maculata Water hemlock Magnoliopsida Apiales Apiaceae Daucus carota Queen Anne's lace Magnoliopsida Apiales Apiaceae Pastinaca sativa Wild parsnip Magnoliopsida Asparagales Alliodeae Allium canadense Wild garlic Magnoliopsida Asparagales Asparagaceae Smilacina racemosa False Soloman's seal Magnoliopsida Asterales Asteraceae Ambrosia artemesiafolia Ragweed Magnoliopsida Asterales Asteraceae Anthemis cotula Mayweed Magnoliopsida Asterales Asteraceae Arctium minus Burdock Magnoliopsida Asterales Asteraceae Aster prananthoides Crooked stem aster Magnoliopsida Asterales Asteraceae Aster vimineus Small white aster Magnoliopsida Asterales Asteraceae Bidens sp. Bur marigold Magnoliopsida Asterales Asteraceae Centaurea maculosa Spotted knapweed Magnoliopsida Asterales Asteraceae Chrysanthemum leucanthemum Ox-Eye daisy Magnoliopsida Asterales Asteraceae Cichorium intybus Chicory Magnoliopsida Asterales Asteraceae Cirsium muticum Swamp thistle Magnoliopsida Asterales Asteraceae Erigeron annuus Daisy fleabane Magnoliopsida Asterales Asteraceae Eutrochium dubium 3-Nerved Joe-Pye weed Magnoliopsida Asterales Asteraceae Eutrochium maculatum Spotted Joe-Pye weed Magnoliopsida Asterales Asteraceae Gnaphalium uliginosum Low cudweed Magnoliopsida Asterales Asteraceae Lapsana communis Nipplewort Magnoliopsida Asterales Asteraceae Rudbeckia laciniata Cut leaved coneflower Magnoliopsida Asterales Asteraceae Solidago graminifolia Flat top goldenrod Magnoliopsida Asterales Asteraceae Solidago sp. Goldenrod

Plantae Magnoliopsida Asterales Asteraceae Sonchus sp. Sow-thistle Tussilago farfara

Magnoliophyta Magnoliopsida Asterales Asteraceae Coltsfoot Magnoliopsida Brassicales Brassicaceae Allaria petiolata Garlic mustard Magnoliopsida Brassicales Brassicaceae Barbarea vulgaris Black mustard Magnoliopsida Brassicales Brassicaceae Capsella bursa-pastoris Shepherd's purse Magnoliopsida Brassicales Brassicaceae Hesperis matronalis Dame's rocket Magnoliopsida Brassicales Brassicaceae Lepidium campestre Poor man's peppergrass Magnoliopsida Brassicales Brassicaceae Rorippa nasturtium-aquaticum Watercress Magnoliopsida Brassicales Brassicaceae Rorippa palustris Yellow cress Magnoliopsida Carophyllales Polygonaceae Polygonum persicaria Lady's thumb Magnoliopsida Carophyllales Polygonaceae Polygonum virginianum Jumpseed Magnoliopsida Caryophyllales Caryophyllaceae Stellaria media Chickweed Magnoliopsida Caryophyllales Polygonaceae Fallopia japonica Japanese bamboo Magnoliopsida Caryophyllales Polygonaceae Rumex crispus Curled dock Magnoliopsida Cornales Cornaceae Cornus alternifolia Alternate leaved dogwood Magnoliopsida Cornales Cornaceae Cornus stolonifera Red osier Magnoliopsida Cucurbitales Cucurbitaceae Echinocystis lobata Wild cucumber Magnoliopsida Dipsacales Adoxaceae Sambucus canadensis Elderberry Magnoliopsida Dipsacales Adoxaceae Viburnum lentago Nannyberry Magnoliopsida Dipsacales Caprifoliaceae Lonicera sp. Honeysuckle Magnoliopsida Ericales Balsaminaceae Impatiens capensis Impatience Magnoliopsida Ericales Myrsinaceae Lysimachia ciliata Fringed loosestrife Magnoliopsida Ericales Myrsinaceae Lysimachia nummularia Moneywort Magnoliopsida Ericales Myrsinaceae Lysimachia terrestris Swamp candles Magnoliopsida Fabales Fabaceae Amphicarpaea bracteata Hog peanut Magnoliopsida Fabales Fabaceae Lotus corniculatus Bird's foot trefoil Magnoliopsida Fabales Fabaceae Melilotus alba Sweet white clover Magnoliopsida Fabales Fabaceae Trifolium campestre Low hop-clover 213 Table 4 (Cont'd). All taxa observed at Compton Bridge Conservation Area on 30 July 2014 (between 10am and 2pm).

Magnoliopsida Fabales Fabaceae Trifolium dubium Small hop clover Magnoliopsida Fabales Fabaceae Trifolium hybridum Alsike clover Magnoliopsida Fabales Fabaceae Trifolium pratense Red clover Magnoliopsida Fabales Fabaceae Trifolium repens White clover Magnoliopsida Fagales Betulaceae Alnus rugosa Speckled alder Magnoliopsida Fagales Juglandaceae Juglans cinerea Butternut Magnoliopsida Gentianales Asclepiadaceae Asclepias syriaca Milkweed Magnoliopsida Gentianales Rubiaceae Gallium sp Bedstraw Magnoliopsida Iridaceae Irideae Iris pseudacorus Yellow flag Magnoliopsida Lamiales Lamiaceae Clinopodium vulgare Wild basil Magnoliopsida Lamiales Lamiaceae Glechoma hederacea Ground ivy Magnoliopsida Lamiales Lamiaceae Linaria vulgaris Butter and eggs Magnoliopsida Lamiales Lamiaceae Lycopus sp. Bugleweed Magnoliopsida Lamiales Lamiaceae Mentha arvensis Wild mint Magnoliopsida Lamiales Oleaceae Fraxinus americana American white ash Magnoliopsida Lamiales Phrymaceae Mimulus ringens Monkey flower Magnoliopsida Lamiales Plantaginaceae Plantago lanceolata English plantain Magnoliopsida Lamiales Plantaginaceae Plantago canadense Plaintain Magnoliopsida Lamiales Plantaginaceae Veronica anagallis-aquatica Water speedwell Magnoliopsida Lamiales Verbenaceae Verbena hastata Blue vervain Magnoliopsida Liliales Colchicaceae Uvularia sessilifolia Bellwort Magnoliopsida Malpighiales Hypericaceae Hypericum punctatum Spotted St Johnswort Magnoliopsida Malpighiales Salicaceae Populus tremuloides Trembling aspen Magnoliopsida Malpighiales Salicaceae Salix Salix fragilis Willow Magnoliopsida Malpighiales Salicaceae Salix Salix sp. Willow Magnoliopsida Malvales Malvaceae Malva moschata Musk mallow Magnoliopsida Malvales Tiliaceae Tilia americana Basswood Magnoliopsida Myrtales Lythraceae Lythrum salicaria Purple loosestrife Magnoliopsida Myrtales Onagraceae Circaea alpina Dwarf enchanter's nightshade Magnoliopsida Myrtales Onagraceae Circaea lutetiana Enchanter's nightshade Magnoliopsida Myrtales Onagraceae Epilobium coloratum Purple leaved willow herb Magnoliopsida Myrtales Onagraceae Epilobium glandulosum Northern willow herb Magnoliopsida Myrtales Onagraceae Ludwigia palustris Water weed Magnoliopsida Myrtales Onocleaceae Oenothera biennis Evening primrose Plantae Magnoliopsida Oxalidales Oxalidaceae Oxalis stricta Yellow wood sorrel Magnoliophyta Magnoliopsida Poales Cyperaceae Carex sp. Sedge Magnoliopsida Poales Cyperaceae Carex lurida Sedge Magnoliopsida Poales Cyperaceae Scirpus sp. Bulrush Magnoliopsida Poales Juncaceae Juncus sp. Rush Magnoliopsida Poales Typhaceae Sparganium americanum Burreed Magnoliopsida Poales Typhaceae Typha latifolia Cattail Magnoliopsida Proteales Plantaginaceae Platanus occidentalis Sycamore Magnoliopsida Ranunculales Ranunculaceae Anemone canadensis Canada anemone Magnoliopsida Ranunculales Ranunculaceae Ranunculus acris Common buttercup Magnoliopsida Ranunculales Ranunculaceae Ranunculus recurvatus Hooked buttercup Magnoliopsida Ranunculales Ranunculaceae Ranunculus repens Creeping buttercup Magnoliopsida Ranunculales Ranunculaceae Ranunculus sp. Buttercup Magnoliopsida Ranunculales Ranunculaceae Taraxicum officinale Dandelion Magnoliopsida Ranunculales Ranunculaceae Thalictrum sp. Rue Magnoliopsida Rosales Rhamnaceae Rhamnus cathartica Buckthorn Magnoliopsida Rosales Rosaceae Agrimonia sp. Agrimony Magnoliopsida Rosales Rosaceae Amelanchier laevis Shadbush Magnoliopsida Rosales Rosaceae Crataegus sp. Hawthorn Magnoliopsida Rosales Rosaceae Fragaria virginiana Strawberry Magnoliopsida Rosales Rosaceae Geum canadense White avens Magnoliopsida Rosales Rosaceae Malus sp. Apple Magnoliopsida Rosales Rosaceae Potentilla simplex Common cinquefoil Magnoliopsida Rosales Rosaceae Prunus serotina Black cherry Magnoliopsida Rosales Rosaceae Prunus virginia Choke Cherry Magnoliopsida Rosales Rosaceae Rosa multiflora Multiflora rose Magnoliopsida Rosales Rosaceae Rubus allegheniensis Northern blackberry Magnoliopsida Rosales Rosaceae Rubus idaeus Red raspberry Magnoliopsida Rosales Rosaceae Rubus Rubus odoratus Purple flowering raspberry Magnoliopsida Rosales Ulmaceae Ulmus Ulmus americana American elm Magnoliopsida Rosales Ulmaceae Ulmus Ulmus rubra Slippery elm Magnoliopsida Rosales Urticaceae Laportea canadensis Wood nettle 214 Table 4 (Cont'd). All taxa observed at Compton Bridge Conservation Area on 30 July 2014 (between 10am and 2pm).

Magnoliopsida Rosales Urticaceae Pilea pumila Clearweed Magnoliopsida Rosales Urticaceae Urtica dioica Nettles Magnoliopsida Sapindales Anarcardiaceae Rhus hirta Staghorn sumac Magnoliopsida Sapindales Anarcardiaceae Toxicodendron radicans Poison ivy Magnoliopsida Sapindales Sapindaceae Acer rubrum Red maple Magnoliopsida Sapindales Sapindaceae Acer negundo Box elder Magnoliopsida Saxifragales Grossulariaceae Ribes sp. Currant Magnoliopsida Saxifragales Haloragaceae Myriophyllum spicatum Eurasian milfoil Plantae Magnoliopsida Solanales Convolvulaceae Calystegia sepium Hedge bindweed Magnoliophyta Magnoliopsida Solanales Solanaceae Solanum nigra Black nightshade Magnoliopsida Unplaced Boraginaceae Myosotis scorpioides Forget me not Magnoliopsida Vitales Vitaceae Parthenocissus quinquefolia Virginia creeper Magnoliopsida Vitales Vitaceae Vitus sp. Grape

Equisetopsida Equisetales Equisetaceae Equisetum sp. Horsetail

Polypodiopsida Polypodiales Dryopteridaceae Dryopteris intermedia Intermediate woodfern

Plantae Polypodiopsida Polypodiales Onocleaceae Matteuccia struthiopteris Ostrich fern Tracheophyta Polypodiopsida Polypodiales Oncleaceae Onclea sensibilis Sensitive fern

215 REFERENCES

Gleason, H.A., and Cronquist, A. 1991. Manual of Vascular Plants of Northeastern United States and Adjacent Canada. New York Botanical Garden Pr. Dept.

Integrated Taxonomic Information System. Retrieved JUL, 2014. System On-line Database. .

Otsego Land Trust. 2013. The Oaks Creek Blueway. Cooperstown, NY.

Otsego Land Trust. 2014. Cumulative history of Brookwood Point. Cooperstown, NY.

Otsego Land Trust. 2014a. Fetterley Forest Management Plan. Cooperstown, NY.

Otsego Land Trust. 2014b. Compton Bridge Management Plan. Cooperstown, NY.

Post, S.L. 2003. Biodiversity blitz: A day in the life of… The Illinois Steward 12(1):1-8.

Ruch, D.G., Karns, D.R., McMuray, P, Moore-Palm, J., Murphy, W., Namestnik, S.A., and Roth, K. 2010. Results of the Loblolly Marsh Wetland Preserve Bioblitz, Jay County, Indiana. Proceedings of the Indiana Academy of Science. 119:(1)1-3.

Strayer, D. L. and A. R. Fetterman. 1999. Changes in the distributions of the freshwater mussels (Unionidae) in the Upper Susquehanna River Basin, 1955-1965 to 1996-1997. Am. Mid. Nat. 142:328-339.

Szentesi, A. 1999. Predispersal seed predation of the introduced false indigo, Amorpha fruticosa L. in Hungary. Acta Zoologica Academiae Scientiarum Hungaricae, 45(2), 125-141.

USGS. 2009. Bioblitz Home. http://www.pwrc.usgs.gov/blitz.html.

Vaughn, Caryn C., and Christine C. Hakenkamp. 2001. "The Functional Role Of Burrowing Bivalves In Freshwater Ecosystems." Freshwater Biology 46.11: 1431-1446.

216 The effects of Earth Tec®, a molluscicide, on zebra mussel (Dreissena polymorpha) mortality

Madeline Genco1 and David Wong2

ABSRACT

Zebra mussels are a major biofouling pest in the United States. In this study the effect of Earth Tec®, a copper based molluscicide, was evaluated for mortality on both adult and larval mussels. Various concentrations of the chemical were tested on adults and veligers for differing durations of time in order to determine a necessary dosage for use in water treatment plants to prevent clogging of intake pipes as mussels colonize. Results have shown 100% mortality of adult mussels exposed to 8ppm of Earth Tec® for 96 hours and at 16ppm for 72 hours. However, such a trend was not seen with the veligers, which were less sensitive to treatment.

INTRODUCTION

Zebra mussels (Dreissena polymorpha) are a major biofouling pest in Otsego Lake and much of the United States. They were accidentally introduced into the Great Lakes via ballast water in 1986, and spread from there (Herbert et al. 1989). They were first discovered in Otsego Lake in 2007 (Horvath 2008). They cause many ecological problems in lakes and streams in the United States. They are outcompeting native mussels for food and space (Karatayev et al. 1997). They clear the water, altering the depth at which light reaches, which in turn increases plant growth (Hecky et el. 2004). Adult mussel attachment to pipes becomes a problem and can lead to clogging (Wong et al. 2012; LePage 1993). The Otsego Water Treatment Plant has been having problems with their intake pipe clogging due to the overabundance of zebra mussels attaching within them (Coyle et al. 2015). Earth Tec®, a commercially available biocide, could be a possible solution to this problem. It uses a blend of copper sulfate pentahydrate with a base acid. The cupric ion (copper 2+) is the active ingratiate; this is a more biologically available form of copper (Watters et al. 2013). Copper 2+ also does not precipitate out of solution, meaning that more copper remains in the water and a lower concentration may be used as compared to copper sulfate or other copper based chemicals. Earth Tec® was recently approved for use to combat invasive dressenid mussels and was selected as Top 10 Water Technology at the American Water Works Association (AWWA) Conference (Earth Tec® website). The purpose of this experiment was to determine if the chemical Earth Tec® can be used in low concentration to kill adult and veliger zebra mussels and be a viable alternative to chlorine or potassium permanganate to prevent clogging of water treatment intake pipes.

1 Biological Field Station Intern, Summer 2014. Current affiliation: SUNY Oneonta 2 Assistant Professor and Biological Field Station Researcher, SUNY Oneonta Biology Department.

217 METHODS

Adult mussels

The methods described here were developed concurrent with a study by Coyle et al. (2015).

Mussel collection

Before mussels were collected, 20 small (20 L) tanks and two large holding tanks were cleaned with an abrasive sponge, rinsed, and refilled with lake water. The tanks were allowed to soak with the lake water overnight and then dumped out and left empty until mussel collection commenced. The two large holding tanks were set up with a constant flow of lake water to keep them at the ambient temperature of the lake. Twenty four hours prior to mussel habitation, the 20 small tanks were refilled with lake water and set up with air stones calibrated for equal air flow between all tanks. Each of the 20 small tanks were labeled with the tank number, and the concentration in parts per million of Earth Tec® to be placed within it.

Adult zebra mussels were collected from the Thayer Farm Boat House on Otsego Lake, a site having suitable (rocky) substrate. Rocks were removed from about 2 meter deep water via snorkeling. Adult mussels were removed by hand and placed into a bucket until approximately 2,000 mussels were collected. The mussels were mixed in order to prevent bias; however, mussels connected via byssal threads were left intact to reduce stress on the mussels. Mussels were rinsed with lake water before being placed in mesh drawstring bags (Comeau et al. 2011; Watters et al. 2013; Coyle et al. 2015).

Preparing the mussels

Eleven mussels were placed in each mesh bag, making 160 bags total. The bags were strung across dowels with 8 bags on each dowel. The dowels held the bags together within the tank (dowels laid across the top of the tanks allowing the bags to drape down into the tank (see Figure 1)). Eighty bags were then placed in each of the holding tanks and allowed to acclimate to conditions for 3 days. Before beginning the experiment, the bags were checked for dead mussels. Any dead mussels were removed. If no mussels were dead, the smallest mussel was removed. If more than one mussel was dead, the dead mussels were replaced with live ones from a bag of extra mussels. After removing dead or extra mussels, each bag was left with 10 mussels. Each bag was labeled with the tank number, the concentration of Earth Tec® in the tank, and the number of hours after which it was to be removed from the tank and transferred to the holding tank.

Conducting the experiment

The day of the experiment, Earth Tec® at concentrations of 0,1,4,8, and 16 ppm was added to the 20 small tanks (see Table 1). Each concentration/duration was evaluated in quadruplicate. A dowel with 8 bags strung across it was then added to each of the 20 small tanks (see Figure 1). One bag of mussels from each of the 20 small tanks was removed, rinsed with

218 lake water, and placed into the large holding tanks at each time interval listed in Table 2. Bags were removed from tanks beginning with tanks having the lowest concentration of Earth Tec® up to the highest concentration. Forty eight hours after being moved to the holding tanks, mussels were removed from the tanks and dried with paper towels. Mussels were then checked for mortality. A mussel was determined dead if it did not immediately shut its shell after being gently pulled open. Shell lengths were measured in millimeters using a hand caliper. A spreadsheet was used to record which mussels were dead and alive, as well as to record the shell lengths.

Figure 1. Experimental tank set up for adult mussels. Each of the 20 small tanks has a dowel set over the top with 8 mesh bags of mussels attached and draping down into the water. An air stone was placed in the corner of each tank (after Coyle et al. 2015).

Table 1. Adult mussels: Concentration of Earth Tec® in each tank is listed.

Tank # [Earth Tec®] Tank # [Earth Tec®] 1 0 ppm 11 0 ppm 2 1 ppm 12 1 ppm 3 4 ppm 13 4 ppm 4 8 ppm 14 8 ppm 5 16 ppm 15 16 ppm 6 0 ppm 16 0 ppm 7 1 ppm 17 1 ppm 8 4 ppm 18 4 ppm 9 8 ppm 19 8 ppm 10 16 ppm 20 16 ppm

219

Table 2. Adult mussels: Schedule for the time interval at which different parts of the experiment were performed. The first two columns show the times at which bags were removed from the tanks with Earth Tec® into holding tanks and YSI readings were taken. The last column shows when the same bags were checked for mortality and measured 48 hours later.

Time Passed Mussels moved from small Mussels removed from holding tanks to holding tanks and tanks and checked for mortality YSI readings measured: and length measured (note: this is 48 hours after they were removed from 20 small tanks with chemicals). 0 hrs. Tues. 6/24/14 12pm Thurs. 6/26/14 12pm 3 hrs. Tues. 6/24/14 3pm Thurs. 6/26/14 3pm 6 hrs. Tues. 6/24/14 6pm → Thurs. 6/26/14 6pm 12 hrs. Wed. 6/25/14 12am Fri. 6/27/14 12am 24 hrs. (1 day) Wed. 6/25/14 12pm Fri. 6/27/14 12pm 48 hrs. (2 days) Thurs. 6/26/14 12 pm Sat. 6/28/14 12pm 72 hrs. (3 days) Fri. 6/27/14 12 pm Sun. 6/29/14 12pm 96 hrs. (4 days) Sat. 6/28/14 12pm Mon. 6/30/14 12pm

Veligers

The day of the experiment, twenty eight 250mL beakers were set up in a grid as shown in Figure 2. Each beaker was filled with 200mL of room temperature lake water that had been filtered with a 63 um net. Zebra mussel veligers were collected from Otsego Lake using a 63 um plankton net. Veligers were collected from Otsego Lake (about halfway across the lake from The SUNY Oneonta Biological Field Station Main Lab dock) with 8 vertical pulls of the net from a depth of 13 meters. A flow meter on the net was used to determine how much water was filtered. The sample was poured sieve to strain out any large daphnia. The sample was concentrated using a cup with a 63 um mesh bottom (Watters et al. 2013; Coyle et al. 2015). This cup was lowered into a beaker containing the sample, and water was withdrawn using a 10mL pipet with the end of the tip cut off to prevent exposing the veligers to strong suction. One mL of the condensed sample was viewed under the microscope. Cross polarized light microscopy and a gridded Sedgewick Rafter slide was used to make the veligers easier to detect (Johnson 1995). The number of veligers on the slide was counted and that number was used to estimate how many mL of sample was needed in each beaker so that each contained about 200 veligers. This part of the experiment required 2 people: Differing amounts of Earth Tec® was added to each beaker corresponding with the concentrations shown on the grid in Figure 2. No

220 chemicals were added to beakers in the 0 minute column; these beakers were controls. Addition of chemicals to each row of beakers was staggered by 5 minutes. This was to account for the amount of time it took to look at the contents of each beaker under the microscope. About 3 minutes before a sample was to be viewed under the microscope, it was concentrated in the beaker using the same methods as before. After the sample in a given beaker was condensed, 1 mL of the remaining fluid was pipetted onto gridded Sedgewick Rafter slide. The samples were viewed on the slide under polarized light at 5 minute intervals beginning with the bottom left most beaker on the grid and moving up until all beakers in the column had been viewed under the scope. The next column would begin at the time listed on the grid. During the 5 minutes each slide was under the microscope, the number of dead and living veligers was counted. If no movement of organs or internal fluid was seen within 4 seconds, the veliger was considered dead.

Figure 2. Experimental set up for veligers. Each circle represents a 250 mL beaker having the specified treatment concentrations and durations of Earth Tec® (after Coyle et al. 2015).

221 RESULTS

Adult mussels An analysis of variance (ANOVA) was conducted to determine the effect of time and concentration of Earth Tec® on adult mussel mortality. It was found that both time exposure and concentration of Earth Tec® significantly affected mortality (Figure 3). No statistical difference was found between mortality at 1 ppm and 0 ppm; however, statistical differences were seen between all other concentrations. No statistical significance was found between mortality at 0, 3, and 6 hours, nor between 48 and 72 hours. However, statistical significance was found between all other time points. It was also found that there was no difference in size between alive and dead adult mussels (T-test, α=0.05, P = 0.88). This means that mussel size is not correlated with mortality, ruling out mussel size as a possible confounding variable.

Figure 3. Comparison of different concentrations of Earth Tec® and how these concentrations affect the mortality rate of adult mussels given the amount of time they were exposed to the chemical. Veligers

The ANOVA conducted to determine the effect of time and concentration of Earth Tec® on veliger mortality does not show any statistical difference between the chemical treatments (F = 1.40, P = 0.1003). However the effect of time is statistically significant (F = 4.18, P = 0.0008) (Figure 4). This means that while the treatment dose had no effect on mortality, the amount of time passed did. There is no difference between times 0-24 hours. However, there is a difference between 48 hours and 0-24 hours. There is also a difference between 144 hours and 0-48 hours (Figure 5).

222

Figure 4. A comparison of different concentrations of Earth Tec® and how these concentrations affect the mortality rate of veligers given the amount of time they were exposed to the chemical.

Figure 5. A comparison of concentrations of 0 and 1ppm of Earth Tec® and how these concentrations affect the mortality rate of veligers given the amount of time they were exposed to the chemical. A long term point (144 hours) was used here.

223 DISCUSSION Earth Tec® is effective at killing adult zebra mussels in relatively low concentrations. However, concentrations needed to induce mortality in veligers were higher than anticipated. The veliger results are interesting because 8 ppm and 6 ppm are considered fairly high doses of Earth Tec®, yet the mortality rate was still not as high as what has been reported elsewhere. A previous study by Watters et al. (2013) showed 100% mortality in quagga mussel (Dreissena rostriformis bugensis) veligers after 30 minutes at 3ppm. Due to this previous finding, we anticipated our zebra mussel veligers would be susceptible to much lower concentrations and shorter durations than what was seen here. A possible explanation for the low mortality rate is that there may be highly variable developmental stages of veligers in the samples that were used during the experiment. Some stages of veligers may be more susceptible to the copper than others. As veligers develop, they secrete shell material; the older veligers have thicker shells (Choi et al. 2014) (Figure 6). Later stage veligers are also larger in size. It could be that later stage veligers would be less susceptible to copper. The sample used for experimentation has variable veliger stages (Table 3). Preserved samples for trials 2 to 4 were measured, and the 4th trial had the lowest proportion of pediveligers (Table 3). ANOVA shows the 4th trial had the highest mortality rate than other two trials (F = 49.2, P < 0.001) although no difference was found among treatment (F = 2.96, P = 0.061). This could explain the low mortality rate, compared to a sample being of mostly first stage veligers. While higher mortality may be associated with younger veligers, various stage veligers found in the lake are the stages that will be brought into the water treatment plant pipe. Therefore, chemicals used in the water treatment pipe must be able to kill all veliger stages.

Figure 6. Veliger stages from left to right: trochophore, straight-hinged veliger, umbonal veliger, and pediveliger.

224 Table 3. Veliger stages were observed and recorded from preserved sample. Samples were preserved using ethanol. Veliger stages were determined using the descriptions from Choi et al. 2013. Veligers Trial 2 Trial 3 Trial 4 (7/21/14) (7/24/2014) (8/1/14) # of % of # of % of # of % of veligers each veligers each veligers each stage stage stage

Stage 1 Trochophore 22 4 14 5 0 0 Stage 2 D-Stage 213 41 149 55 5 100 Stage 3 Umbonal 144 28 62 23 0 0 Stage 4 Pediveliger 143 27 48 18 0 0

REFERENCES

Choi, W.J., S. Gerstenberger, R.F. McMahon, and W.H.Wong. 2013. Estimating survival rates of quagga mussel (Dreissena rostriformis bugensis) veliger larvae under summer and autumn temperature regimes in residual water of trailered watercraft at Lake Mead, USA. Management of Biological Invasions 4(1): 61-69. Claudi, R., T.H. Prescott, S. Mastisky, and H. Coffey. 2014. Efficacy of copper based algaecides for control of quagga and zebra mussels. RNT Consulting, Inc. Comeau S, S. Rainville B., Baldwin, E. Austin, S.L. Gerstenberger, C. Cross and W.H. Wong. 2011. Susceptibility of quagga mussels (Dreissena rostriformis bugensis Andrusov) to hot-water sprays as a means of watercraft decontamination. Biofouling 27:267-274. Coyle, B.P., P.H. Lord, W.H. Wong and M.F. Albright. 2014. Preventing zebra mussel colonization: appropriate potassium permanganate application time and dose. In 47th Ann. Rept. (2014). SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta.

Earth Tec® QZ website. http://www.earthtecqz.com/ Hebert P.D.N., B.W. Muncaster and G.L. Mackie. 1989. Ecological and genetic studies on Dreissena polymorpha (Pallas): A new mollusc in the Great Lakes. Canadian Journal of Fisheries and Aquatic Sciences. 46: 1587–1591. Hecky, R.E., R.E.H. Smith, D.R. Barton, S.J. Guildford, W.D. Taylor, M.N. Charlton, and T. Howell. 2004. The nearshore phosphorus shunt: a consequence of ecosystem engineering by dreissenids in the Laurentian Great Lakes. Can J Fish Aquat Sci 61:1285-1293.

225 Hovath, T. 2008. Economically viable strategy for prevention of invasive species introduction: Case study of Otsego Lake, New York. Aquatic Invasions 3(1): 3-9. Johnson, L.E. 1995. Enhanced early detection and enumeration of zebra mussel (Dreissena spp.) veligers using cross-polarized light microscopy. Hydrobiologia 312(2): 139-146. Karatayev, A.Y., L.E. Burlakova, and D.K. Padilla. 1997. The effects of Dreissena polymorpha (Pallas) invasion on aquatic communities in eastern Europe. J Shellfish Res 16:187-203. LePage W.L. 1993. The impact of Dreissena polymorpha on waterworks operations at Monroe, Michigan: A case history. In Nalepa, T.F. and D.W. Schloesser (eds). Zebra mussels: Biology, impacts, and control. pp 333-358, Lewis Publishers, Boca Raton, Florida. Watters, A., S.L Gerstenberger, and W.H. Wong. 2013. Effectiveness of EarthTec® for killing invasive quagga mussels (Dreissena rostriformis bugensis) and preventing their colonization in the Western United States. Biofouling: 29(1):21-28. Wong, W.H., S. Gerstenberger, W.Baldwin, and B. Moore. 2012. Settlement and growth of quagga mussels (Dreissena rostriformis bugensis Andrusov, 1897) in Lake Mead, Nevada-Arizona, USA. Aquatic Invasions 7(1):7–19. Wong, W.H., G.C. Holdren, T. Tietjen, S. Gerstenberger, P. Roefer, B. Moore, K. Turner and A. Preston. 2014. Change of chlorophyll a concentrations in the open water of Lake Mead from 2002 to 2011: Impacts from invasive quagga mussels. Wong, D. 2014. Personal Communication. SUNY Oneonta Biol. Fld. St., SUNY Oneonta. Yoo, A., P. Lord, and W.H. Wong. 2014. Zebra mussel (Dreissena polymorpha) monitoring using navigation buoys. Management of Biological Invasions. 5(2):159–163.

226 Using pressurized hot water spray to kill and remove dreissenid mussels on watercraft: Field testing on the efficacy of water temperature, high pressure, and duration of exposure1

W.H. Wong2,3, S. Gerstenberger2 and A. Watters3

SUMMARY

The results of this study show that 3000 psi is the most effective pressure to remove dreissenid mussels if the watercraft is fresh out of the water. There is no difference in using pressurized water spray time between quagga mussels (Dreissena rostriformis bugensis) and zebra mussels (D. polymorpha). At the same time, 1500 psi will suffice to remove high density druses of dreissenids in 8.0 ± 2.3 s for quagga mussels and 15.6 ± 11 s for zebra mussels if the watercraft has been out of the water more than one week in the summer and 18.83 ± 9.32 s for quagga mussels if the watercraft has been out of the water for more than four weeks. This study also attempted to assess the shortest amount of time needed to attain 100% mortality of zebra mussels following exposure to hot-water spray. The results showed that zebra mussels exposed to 54°C (130°F) or higher for 10 s and 70°C (158°F) or higher for 5 s was sufficient to reach 100% mortality. From a previous study, it is also found that it takes 10 s to kill 100% quagga mussels when they are exposed to water with temperature 54°C (130°F) or higher. If a mussel fouled watercraft arrives at an inspection station, it is currently recommended by the federal and state agencies to decontaminate the vessel with 60oC (140oF) for 10 s. From the present project and results in previous studies, it is suggested that 54°C (130°F) for 10 s will be 100% effective for quagga and zebra mussels.

PROJECT OBJECTIVES

To collect field data on the lethal effect of hot-water spray on immersed zebra mussels attached to different areas of a watercraft at different combinations of water temperature and duration of exposure.

To validate the field data through tests on boats infested with adult zebra mussels to make sure decontamination programs with the identified standards will lead to 100% mussel mortality.

To collect field data on the efficacy of power wash on attached live and dead quagga/zebra mussels at different combinations of pressure and duration of exposure.

To provide field data on the minimal pressure and time required to reach and sustain 100% removal rate of live and dead quagga/zebra mussels attached to watercraft.

1 Final report to the US Fish and Wildlife Service. 2 Department of Environmental and Occupational Health, University of Nevada Las Vegas. 3 Department of Biology, SUNY Oneonta.

227 MATERIALS AND METHODS

Mussel removal with high pressure water spray - quagga mussels

The effectiveness of high pressure water spray (1500 and 3000 psi) was evaluated for removing 100% of quagga mussels from watercraft in the winter season and then repeated in the summer season at Lake Mead NRA. A heavily encrusted Bayliner watercraft, which was slipped in Lake Mead for over four years, was pulled from a Las Vegas Boat Harbor slip on 28 January 2011 and brought to the maintenance yard (Figure 1). The mussels on the watercraft, pulled fresh out of the water, were presumed alive. That same watercraft remained in the maintenance yard where the experiment was repeated on days 14 (11 February 2011) and 30 (27 February 2011). Another Bayliner was pulled from a slip at Las Vegas Boat Harbor on 20 July 2011 for the summer season, high pressure experiment. It was brought back to the marina’s maintenance yard where the experiment took place on day 0 (20 July 2011) and day 7 (27 July 2011).

Figure 1. Watercraft heavily encrusted with D. rostriformis bugensis.

Groups of mussels were divided into 24 treatment groups: 2 pressures (1500 and 3000 psi) x 2 densities (high and low) x 6 replicates (Table 1). The treated area was completely covered with mussels and was created by partitioning off areas (high or low density mussel groups) by scraping off the surrounding mussels (Figure 2). High mussel density groups consisted of approximately 23,220-46,440 mussels/m2 (~75-150 individuals) and low density mussel groups consisted of approximately 7,772-10,363 mussels/m2 (~15-20 individuals). Prior

228 to using pressurized spray, each group of mussels was photographed for a more precise enumeration. A LANDA pressure washer (LANDA Cold Water Direct Drive Pressure Washer, Model # PD4-35324; American Pressure Inc.) was used for the high pressure experiments (Figure 3). The unit is capable of spraying at least 5 gallons/minute with a nozzle pressure of 3000 psi and greater, which is recommended by The Uniform Minimum Protocols and Standards for Watercraft Interception Programs for Dreissenid Mussels in the Western US (Zook and Phillips 2012). For this project, the 40 degree nozzle was used and the tip of the pressure washer wand remained 12 inches away from the watercraft. A sub-sample of mussels was removed from each replicate and the size of mussels was recorded. The shell length of the mussel is the distance measured from the posterior edge of the shell to the anterior tip of the umbos to the nearest 0.1 mm with digital calipers (VWR Digital 152 cm (6") Caliper - Stainless Steel, Model # 62379-531; VWR International, Inc.) (McMahon and Ussery, 2005).

Table 1. Experimental design for pressurized water spray to remove D. rostriformis bugensis and D. polymorpha on watercraft.

Mussel Density 1500 PSI 3000 PSI High 6 replicates 6 replicates Low 6 replicates 6 replicates

Figure 2. A group of mussels segmented for high pressure testing.

229 The above experiment was repeated in the summer season at the Las Vegas Boat Harbor with one modification. The summer season experiment took place on days 0 (when the watercraft was pulled fresh out of the water) and 7. The shorter time range is because D. rostriformis bugensis byssal threads will dry out and decompose at a faster rate in the hot, arid days of summer in the Southwest compared to the winter months.

Figure 3. LANDA pressure washer used in the high pressure experiments.

Mussel removal with high pressure water spray - zebra mussels

The above study was repeated using zebra mussels D. polymorpha at Wilson Lake, Kansas during the summer season. Adult D. polymorpha colonies are not found in bodies of water in the southwest. Kansas is the closest place to Nevada where the reservoirs contain healthy populations of adult D. polymorpha. In August 2011, the LANDA pressure washer and all other equipment were transported by van to Wilson Lake, Kansas to conduct the experiment.

Arrangements were made with the marina staff at Wilson Lake to have a D. polymorpha encrusted watercraft removed from the reservoir to perform the project. Marina staff discovered they had a sunken boat lift that was encrusted with larger D. polymorpha compared to the watercrafts that were in the slips. The staff believes that the boat lift was in the water for over two years. It was removed from the reservoir and used for the high pressure experiment (Figure 4). On days 0 (1 August 2011) and 7 (8 August 2011), 1500 and 3000 psi was applied on high and low mussel densities to evaluate the duration it would take to remove 100% of the mussels.

230

Figure 4. Boat lift used for the summer season, Wilson Lake high pressure experiments.

Susceptibility of Zebra Mussels to Hot-water Spray

The susceptibility of quagga mussels to hot-water sprays at different temperatures and durations of spray contact at Lake Mead NRA was evaluated. Results showed that a spray temperature of 60°C for 5 s is recommended for mitigating fouling by D. rostriformis bugensis (Comeau et al. 2011). In their study, it was also found that 54oC for 10 s can kill 100% of quagga mussels. We just repeated their experiment on zebra mussels. Zebra mussels have been tested in the lab before (Morse 2009), but the mussels in our experiment were collected and tested in situ. A Kansas Department of Wildlife permit was obtained to collect adult D. polymorpha from Wilson Lake. Specimens of healthy adult D. polymorpha (≥11 mm in length) were collected from the encrusted docks at the marina. The individuals were divided among 60 mesh spat bags (approximately 75 in each) and suspended in the lake, off the dock, and acclimated for ten days. After acclimation, adult mussels were randomly divided into 60 subsamples (n = 50) and placed into 60 identical pre-labeled, 3 mm spat bags (Aquatic Eco-Systems Inc., Apopka, FL) (Table 2). To avoid transporting the mussels, the experiment took place on the dock, close to an electrical outlet to plug in the equipment. Each bag was suspended over a PolyScience Programmable heated circulator wash bath with a 28 liter capacity during the thermal spray treatment (PolyScience, Model # 1137-2P; Niles, Illinois) (Figure 5). Treatment spray was applied to the samples at a flow rate of approximately 900 ml/min through a fan shaped nozzle (Comeau et al. 2011).

231 Table 2. Amount of D. polymorpha tested per treatment group (n = 50) (Comeau et al., 2011).

Temp Exposure Duration (s) °C/°F 1 2 5 10 20 40 80 160 20/68 50 50 50 50 50 50 50 50 40/104 50 50 50 50 50 50 50 50 50/122 50 50 50 50 50 50 50 50 54/130 50 50 50 50 50 50 50 50 60/140 50 50 50 50 50 50 50 50 70/158 50 50 50 50 50 50 50 50 80/176 50 50 50 50 50 50 50 50

Figure 5. PolyScience Programmable heated circulator wash bath.

Each sample of mussels was exposed to thermal-spray treatments from a distance of 15 cm horizontally above the mussel-containing mesh bag (Morse 2009) at 20, 40, 50, 54, 60, 70, and 80°C and exposure durations of 1, 2, 5, 10, 20, 40, 80, and 160 s. The control was 20°C. Therefore, 56 combinations of temperature by exposure duration were tested (Table 2). The water temperature, on contact with the treatment group, was constantly monitored by the PolyScience Programmable heated circulator wash bath. Four bags containing D. polymorpha were treated with hot-water spray as they were used as controls and were left suspended in Wilson Lake. Following treatment, each spat bag containing the treatment specimens was tied to a line hanging from the dock. Mortality was assessed at the time of treatment and every day thereafter for ten days. To test for mortality, gaping mussels were gently prodded on their shell valves. Individual mussels that did respond by immediate shell closure were stimulated in the area of their siphons. Mussels that did not respond to siphon stimulation had their shell valves

232 forcible closed with forceps. Mussels were considered dead if the shell immediately reopened upon release of the forceps (Harrington et al. 1997; Morse 2009; Comeau et al. 2011). Dead mussels were removed and measured, then recorded and placed into a different labeled mesh bag. The control groups remained in Wilson Lake for ten days and survivorship was assessed as described previously.

Hot-water Spray Watercraft Validation

After the minimum time to kill 100% D. polymorpha was identified from the above experiment, the protocol was field validated using a zebra mussel encrusted Crestliner pontoon vessel from Wilson Lake, Kansas (Figure 6). The watercraft was pulled from the reservoir on 3 August 2011. Five groups of mussels were segmented on the watercraft (as discussed previously) and served as the treatment groups. An additional group was segmented and served as the control, and those mussels were gently scraped off the watercraft, transferred to a mesh bag and placed in the lake for ten days to assess survivorship. A PolyScience Programmable heated circulator wash bath was set at 54°C, which was the temperature that was discovered to kill 100% of D. polymorpha in the previous laboratory experiment. The spray nozzle was placed 15 cm from the treatment groups. The hot-water spray was applied to each group for 10 s. Once the D. polymorpha were treated with the hot-water spray, the mussels were gently scraped off the watercraft, transferred into a labeled mesh bag, and placed back into the lake to confirm mortality after 24 h and for ten days thereafter.

Figure 6. Encrusted pontoon boat from Wilson Lake, Kansas.

233 RESULTS AND DISCUSSION

Pressurized Water Spray to Remove Dreissenids on Watercraft When the boat was just out of water (at week 0), it takes an average of 430 s to remove a cluster of high density (11,246 ± 1,152) D. rostriformis bugensis with 1500 psi (low pressure) in the summer season at Lake Mead, and it takes an average of 472 s to remove a cluster of high density (8,091 ± 327) D. polymorpha with 1500 psi in the summer season at Wilson Lake (Table 3). Conversely, when 3000 psi is used in the summer season on a high density group of D. rostriformis bugensis, the time is greatly reduced to 48 s and 52 s for D. polymorpha (Table 3). To remove D. rostriformis bugensis from a watercraft in the winter season, using high or low psi, it takes on average 297 s (range = 202-390 s). Decontamination of D. rostriformis bugensis will take longer when the watercraft is pulled fresh from the water body in the winter season. It takes an average of 346 s (5.77 min) to remove 15,615 m2 of D. rostriformis bugensis from a watercraft. Comparing it to the data from watercraft being out of the water for 2 and 4 weeks, decontamination times are reduced to 3.33 s to remove 21,084 m2 and 1.83 s to remove 12,540 m2, respectively (Tables 4 and 5). When the watercraft was just out of the water (week 0), the time to remove D. rostriformis bugensis and D. polymorpha from watercraft was shorter when mussel density was low (~1,754 m2 ± 1,003) and the pressure was set to 3000 psi (high) (Table 3). In winter or summer seasons, it was easier to remove mussels from the watercraft when it had been out of the water for at least two weeks or one week, respectively, when compared to being at week 0, or fresh out of the water. The time to remove mussels from watercraft was shorter when mussel density was low and the pressure was high (Table 3). The results show that it takes more time to remove mussels in winter than summer (Analysis of variance (ANOVA), F43, 44 = p < 0.0001). A general linear model was used to test if the amount of time a watercraft was out of the water (0, 1, 2, or 4 weeks) would have an effect on time to remove dreissenids. Statistical results show that the time a watercraft is out of the water, the density and pressure are significant contributing factors in removing mussels. There is an interaction between the time the watercraft has been out of the water and density as well (Analysis of covariance (ANCOVA), F4, 115 = 13.30, p < 0.001). The time the watercraft is out of the water is the most significant factor affecting removal time (F1 = 36.24, p < 0.0001).

In the summer season, D. rostriformis bugensis and D. polymorpha are removed from watercraft using high pressure spray in less time because the byssal threads have a higher chance of drying out. However, the longer the vessel is out of the water, the quicker the mussels will be removed. For instance, to remove D. rostriformis bugensis and D. polymorpha from watercraft on week 0 using the recommended 3000 psi, it took on average 48 s to remove 13,350 m2 individuals and 52 s to remove 8,091 m2 individuals, respectively (Table 3). When the watercraft sat out of the water for 1 week prior to decontamination, the time to remove D. rostriformis bugensis and D. polymorpha was greatly reduced to 3.5 s to remove 1,844 m2 individuals and 4.5 s to remove 7,767 m2 individuals, respectively (Table 6). Kappel (2012) found that after just 4 hours of exposure to 30ºC ambient temperature, D. rostriformis bugensis achieved 30% mortality which agreed with the data suggesting the D. rostriformis bugensis has a lower acute thermal tolerance than D. polymorpha, thus explaining the ease in removing the mussels (Spidle et al., 1995; Mills et al., 1996).

234 There are no data for removal times of D. polymorpha in the winter season. However, based on the results with D. rostriformis bugensis and D. polymorpha having similar removal times in the summer, the data suggests the results from removing D. rostriformis bugensis from watercraft in the winter season may be applicable to removal times of D. polymorpha from watercraft in the winter season. There was no significant difference between D. rostriformis bugensis and D. polymorpha in removal times (ANOVA and Student-Newman- Keuls multiple comparison, P = 0.81). This recommendation would need to be field tested.

Table 3. Average time to remove high or low densities of D. rostriformis bugensis and D. polymorpha from watercraft in summer and winter seasons using 1500 or 3000 psi on week 0 (n = 6). Species Season Pressure (psi) Density (m2) Time (s) D. rostriformis bugensis Summer 1500 High (11,246 ± 1,152) 430 ± 370 D. rostriformis bugensis Summer 1500 Low (1,909 ± 312) 37 ± 15 D. rostriformis bugensis Summer 3000 High (13,350 ± 1,136) 48 ± 14 D. rostriformis bugensis Summer 3000 Low (3,317 ± 335) 43 ± 87 D. rostriformis bugensis Winter 1500 High (16,586 ± 5,509) 390 ± 140 D. rostriformis bugensis Winter 1500 Low (1,326 ± 224) 249 ± 174 D. rostriformis bugensis Winter 3000 High (15,615 ± 258) 346 ± 155 D. rostriformis bugensis Winter 3000 Low (1,068 ± 1,091) 202 ± 52 D. polymorpha Summer 1500 High (6,068 ± 530) 472 ± 178 D. polymorpha Summer 1500 Low (1,262 ± 220) 41 ± 14 D. polymorpha Summer 3000 High (8,091 ± 327) 52 ± 24 D. polymorpha Summer 3000 Low (1,246 ± 1,434) 32 ± 32

Table 4. Average time to remove high or low densities of D. rostriformis bugensis from watercraft in the winter seasons using 1500 or 3000 psi on week 2 (n = 6). Pressure Density (m2) Time (s) (psi) 1500 High (19,660 ± 8,395) 39.5 ± 15.44 1500 Low (10,784 ± 10,869) 2.33 ± 1.37 3000 High (21,084 ± 4,740) 3.33 ± 1.51 3000 Low (1,553 ± 122.8) 15.5 ± 5.05

Table 5. Average time to remove high or low densities of D. rostriformis bugensis from watercraft in the winter seasons using 1500 or 3000 psi on week 4 (n = 6). Pressure Density (m2) Time (s) (psi) 1500 High (12,459 ± 7,256) 18.83 ± 9.32 1500 Low (1,504 ± 419.8) 1.17 ± 0.41 3000 High (12,540 ± 5,820) 1.83 ± 0.98 3000 Low (1,537 ± 444.5) 1 ± 0

235 Table 6. Average time to remove high or low densities of D. rostriformis bugensis and D. polymorpha from watercraft in the summer season using 1500 or 3000 psi on week 1 (n = 6).

Species Season Pressure (psi) Density (m2) Time (s) D. rostriformis bugensis Summer 1500 High (12,216 ± 4,760) 8.0 ± 2.3 D. rostriformis bugensis Summer 1500 Low (1,779 ± 396.3) 15.8 ± 13 D. rostriformis bugensis Summer 3000 High (15,776 ± 2,972) 3.5 ± 3.8 D. rostriformis bugensis Summer 3000 Low (1,844 ± 363.3) 8.67 ± 5.2 D. polymorpha Summer 1500 High (8,576 ± 3,316) 15.6 ± 11 D. polymorpha Summer 1500 Low (1,375 ± 365) 12.3 ± 15 D. polymorpha Summer 3000 High (7,767 ± 1,816) 4.5 ± 1.8 D. polymorpha Summer 3000 Low (1,165 ± 237.8) 6.33 ± 3.8

The data show there was not a significant difference between D. rostriformis bugensis and D. polymorpha when using pressurized water spray to remove them from watercraft in the summer season (ANOVA, F1 = 0.03, P = 0.81). However, the pressure applied (ANOVA, F1 = 25.27, p < 0.0001) and the density of mussels was significant (ANOVA, F1 = 26.13, p < 0.0001).

Depending on the size of the watercraft and the amount of biofouling present, decontamination using high pressure spray will take a considerable amount of time. It is recommended to use 3000 psi on the hull, centerboard box and keel (sailboats), lower unit, cavitation plate, and prop. These external areas can handle 3000 psi on most watercraft without causing damage and usually have the most amount of mussel fouling. For internal and other sensitive areas of watercraft, manual removal, using brushes and scrapers, of mussels may be necessary. At the same time, 1500 psi will suffice to remove high density druses of dreissenids if the watercraft has been out of the water more than one week. For personal safety, only trained personnel should use high pressure spray to remove dreissenids from watercraft. If the vessel is left out of the water for at least one week in the summer or two to four weeks in the winter, the decontamination time can be significantly reduced.

Susceptibility of Zebra Mussels to Hot-water Spray There is a trend which shows that as the treatment temperatures increase, greater mortality in D. polymorpha following the same exposure duration also increases (Table 7). Dreissena polymorpha reached 100% mortality within 10 s at 54°C and 60°C and 5 s at 70°C and 80°C treatments (Table 7). Spray exposures of 1 s and 2 s were not found to induce 100% mortality at any of the test temperatures. Treatments of 20°C were ineffective, as only 4% mortality was seen when D. polymorpha were exposed to treatment for 80 s (Table 7).

236 Table 7. Mortality rate (%) of Dreissena polymorpha under different treatments by day 10. Temp °C/°F Exposure Duration (s) 1 2 5 10 20 40 80 160 20/68 0 0 0 0 0 4 4 0 40/104 2 2 4 4 90 100 100 100 50/122 10 24 38 80 96 100 100 100 54/130 52 72 96 100 100 100 100 100 60/140 84 84 96 100 100 100 100 100 70/158 84 96 100 100 100 100 100 100 80/176 84 96 100 100 100 100 100 100

Estimated LD50 values for 1 s, 2 s, 5 s, and 10 s indicate that the temperature to kill 50% of D. polymorpha was between 49.8°C to 60.3°C (Table 8). The estimated LD99 with these exposure durations varied from >102.8°C at 1 s to 51.1°C at 10 s (Table 8).

Table 8. Estimated LD50 and LD99 values (in bold) and their 95% confidence limit for hot-water spray treatments on Dreissena polymorpha at 1 s, 2 s, 5 s, and 10 s application durations ( n = 400 for each duration).

Duration (s) LD50(°C) LD99(°C) SM100(°C)* 1 53.6 < 60.3 < 68.5 > 102.8 > 80 2 44.6 < 56.8 < 69.9 > 86.5 > 80 5 50.7 < 51.2 < 51.7 > 55.0 > 60 10 49.6 < 49.8 < 50.0 50.9 < 51.1 < 51.4 54 *The SM100 is the temperature observed in the experiment that induced 100% mortality in Dreissena polymorpha

The mussels in the control groups (n = 200) (mean = 16.02 mm, range = 11.01-21.24 mm) remained in the spat bags immersed in Wilson Lake for ten days. The water temperature of the lake averaged 26.79°C ± 1.7 for the duration of the project. The control groups and the mussels exposed to 20°C spray treatments exhibited high survival rates. Figure 7a shows the combined four groups of controls exhibited a 97% survival rate with a range from 96%-98%; Figure 7b the shows the eight 20°C spray treatment subsample displayed a mean 98.5% survival rate with a range of 96% to 100% with no apparent correlation to duration of exposure. Figures 7c-7h similarly display % mortality for spray temperatures of 40°C, 50°C, 54°C, 60°C, 70°C and 80°C, respectively. For all of Figure 7, mortality was evaluated daily for 10 days following exposure to the spray water.

Of D. polymorpha exposed to 40°C, 67% survived treatment. Those mussels that were exposed to that treatment for 1 s and 2 s exhibited a 98% survival rate, those exposed for 5 s exhibited a 96% survival rate and when exposed for 10 s, the mussels had a 94% survival rate (Figure 7c). Mussels exposed to 40°C and 50°C for 1 s exhibited a 98% and 90% survival rate, respectively. The average shell length of mussels in the 56 treatment groups (n = 2,800) is 16.65 mm (range = 11.02-28.06 mm).

237

(a) 100

80 Control 1 60 Control 2 Control 3 40 Control 4

Mortality Rate (% ) 20

0 1 3 5 7 9 Days

Figure 7a. Mortality rates (%) of Dreissena polymorpha in Wilson Lake after hot-water spray treatment: Control (26.79°C).

(b) 1 s 100 2 s 5 s 80 10 s 60 20 s 40 s 40 80 s

Mortality Rate (% ) 20 160 s

0 1 3 5 7 9 Days

Figure 7b. Mortality rates (%) of Dreissena polymorpha in Wilson Lake after hot-water spray treatment: 20°C.

238

(c) 100

80 1 s 2 s

60 5 s

40 10 s 20 s

Mortality Rate (% ) 20 40 s 80 s 0 1 3 5 7 9 160 s Days

Figure 7c. Mortality rates (%) of Dreissena polymorpha in Wilson Lake after hot-water spray treatment: 40°C.

(d) 100

80 1 s 2 s 60 5 s 10 s 40 20 s

Mortality Rate (% ) 20 40 s 80 s 0 1 3 5 7 9 160 s

Days

Figure 7d. Mortality rates (%) of Dreissena polymorpha in Wilson Lake after hot-water spray treatment: 50°C.

239

(e) 100

80 1 s 2 s 60 5 s

40 10 s 20 s

Mortality Rate (% ) 20 40 s 80 s 0 1 3 5 7 9 160 s Days

Figure 7e. Mortality rates (%) of Dreissena polymorpha in Wilson Lake after hot-water spray treatment: 54°C.

(f)

100

80 1 s 2 s 60 5 s 10 s 40 20 s

Mortality Rate (% ) 20 40 s 80 s 0 1 3 5 7 9 160 s Days

Figure 7f. Mortality rates (%) of Dreissena polymorpha in Wilson Lake after hot-water spray treatment: 60°C.

240

(g) 100

80 1 s 2 s 60 5 s 10 s 40 20 s

Mortality Rate (% ) 20 40 s 80 s 0 1 3 5 7 9 160 s Days

Figure 7g. Mortality rates (%) of Dreissena polymorpha in Wilson Lake after hot-water spray treatment: 70°C.

(h)

100

1 s 80 2 s 60 5 s 40 10 s 20 s

Mortality Rate (% ) 20 40 s 80 s 0 1 3 5 7 9 160 s Days

Figure 7h. Mortality rates (%) of Dreissena polymorpha in Wilson Lake after hot-water spray treatment: 80°C.

241 Hot-water Spray Watercraft Validation The hot-water spray field test showed that 100% mortality of D. polymorpha was reached using 54ºC for 10 s of exposure time (Figure 7e). These results were validated on a zebra mussel encrusted Crestliner pontoon vessel (Figure 6). Immediate mortality was observed in the six treatment groups (N = 72). No mortality was observed in the six control groups three days post- experimentation (N = 46). The average shell length of the treatment and control group mussels was 8.16 mm (range = 4.84—14.26 mm) and 8.15 mm (range = 6.17—14.15 mm), respectively.

Hot-water spray is sustainable, effective, and economical compared to chemical applications which could lead to further financial and ecological issues (Piola 2009). By using tap-water cultured zebra mussels, Morse (2009) found that water sprayed at ≥ 60°C for 10 s or 80°C at ≥ 5 s was 100% lethal to D. polymorpha, which indicates that current decontamination recommendations of spray temperature of ≥ 60°C may not kill all the mussels if the exposure duration is < 10 s. The current study found the same results as Morse (2009) in regards to 10 s application using 60°C will result in 100% D. polymorpha mortality. The results also showed that with a 5 s application using 60°C resulted in a 98% mortality rate, as opposed to Morse’s study that concluded 5 s application resulted in an 87% mortality rate. However, at a cooler temperature of 54°C, 100% mortality of D. polymorpha was also attained by 10 s in this study. The 54oC/130oF was not tested in Morse’s study, but the model result shows that the LT99 is 53.9oC (with variations from 52 to 60.2oC) which is very close to the present study (100% mortality at 54oC). In Morse’s (2009) study, the LT50 and LT99 at 1 s duration were both >80°C while they were 60.3°C and >102.8°C, respectively, for D. polymorpha in the present study (Table 8). At 5 s duration, LT50 and LT99 for D. polymorpha in the first study were 54.6°C and 69.1°C while they were 51.2°C and > 55.0°C in the current study. With 10 s exposure, the LT50 and LT99 for D. polymorpha in the first study were 46.9°C and 53.9°C, and in the current study, they were 49.8°C and 51.1°C. Clearly, relatively lower temperatures with the same exposure time, or relatively less time under the same treatment temperature, is needed to reach the same lethal rate in the present study than the study by Morse (2009). The only difference is that D. polymorpha in Morse’s study have been acclimated in laboratory conditions while the present study used mussels fresh from the native reservoir. Therefore, the physiology of D. polymorpha tested in these two studies and their responses may differ (Costa et al. 2008). The effort of adaptation of physiological responses of D. polymorpha to hot-water treatment needs to be studied in the future. Morse’s experimental design was set up to examine the 60oC/140oF lethal temperatures at 5 and 10 s, whereas 6, 7, 8, and 9 s were not tested. Through the results of this study, it is suggested that D. polymorpha could reach 100% mortality between 6-9 s when exposed to 60°C. In that case, boat inspectors can save time in decontaminating a mussel fouled watercraft. Field tests would be needed to validate this assumption.

Another study examined the susceptibility of quagga mussels to hot-water sprays. The researchers found that at hot-water temperatures ≥60°C, with contact duration of only 5 s was sufficient to induce 100% mortality in D. rostriformis bugensis (Comeau et al. 2011). These results indicate that D. rostriformis bugensis are more susceptible to hot-water sprays than D. polymorpha when comparing to the results from the current study and Morse’s study. Dreissena rostriformis bugensis have thinner shells and less tightly sealing shell valves compared to D. polymorpha (Claxton et al. 1997). Because the shell valves may not close as tightly in D. rostriformis bugensis, heating of the soft tissues may occur more rapidly than that of D.

242 polymorpha. Another potential reason for this increased vulnerability may have to do with the impact of ambient temperature conditions and seasonal productivity variations on the acute thermal tolerance of dreissenid mussels (Elderkin and Klerks 2005). The upper thermal limit of D. rostriformis bugensis is lower than that of D. polymorpha (McMahon 1996). This suggests that D. rostriformis bugensis are more susceptible to death by hot-water sprays at a lower temperature and less exposure time than D. polymorpha. However, the difference thermal tolerance between the two species is not great. For example, it is also found 54oC/10 s will result in 100% mortality for quagga mussels (Table 9, Comeau et al. 2011). Compared to 60oC (140oF), 54oC (130oF) is more appropriate because it is the highest temperature at which the system components of heat sensitive areas in watercraft (i.e. ballast tanks and bladder) are designed to withstand (Zook and Phillips 2009). In addition, lower temperature will be safer for boat inspectors (Morse 2009) and it is relatively cheaper and environment friendly (i.e. less energy will be consumed). Based on results from Morse (2009), Comeau et al. (2011), and the present study, it is recommended that 54oC (130oF)/10s is to be used for boat decontamination.

Table 9 Quagga mussel mortality (%) under different treatments at day 10 Temp °C/°F Exposure Duration (s) 1 2 5 10 20 40 80 160 20/68 4 4 6 0 0 2 2 0 40/104 2 2 8 12 94 100 100 100 50/122 10 22 36 82 100 100 100 100 54/130 54 72 98 100 100 100 100 100 60/140 72 92 100 100 100 100 100 100 70/158 88 98 100 100 100 100 100 100 80/176 86 98 100 100 100 100 100 100

There are a couple of other methods for watercraft decontamination that have been explored, such as dry time acceleration and dry ice blasting (Zook and Phillips 2012). The rate of desiccation for dreissenid mussels is a function of temperature, humidity, and mussel size (Morse 2009). Increasing ambient temperatures and lower humidity decrease the time needed for desiccation, while larger mussels require more time to dry-out than smaller mussels. To assist lake managers in knowing how long a watercraft needs to remain out of the water to ensure the mussels are dead through desiccation, a dry time estimator was developed (Mangin 2011). The estimator is a tool that can be used to estimate the minimum time a vessel should remain out of the water before launching into an uninfested water body. Accelerated dry times should be used after a fouled vessel has gone through a high pressure, hot-water spray service. The use of dry ice (CO2) pellets for cleaning and removing attached dreissenids is an alternative decontamination method. Dry ice blasting uses compressed air to propel tiny dry ice pellets onto fouled watercraft. The dry ice freezes the mussels with the intent of killing them. The pellets quickly dissipate into the air so there's no wastewater or other media to dispose (Zook and Phillips 2012). This will only remove the mussels, not kill them. For high density colonization, 100% mortality rate could not be reached for removed mussels (WH Wong, personal observation). The effectiveness of dry ice blasting has not been reviewed in the literature and it should be systematically investigated prior to implementation. Combining the methods of pressurized (3000 psi) and hot-water spray (60°C for 10 s) to the surface of the fouled watercraft

243 is the best way to decontaminate a vessel to prevent the further spread of dreissenids. For the inaccessible areas, such as the gimbal area, inside the engine, generator and AC cooling systems, treatments of 60°C for 10 s will not suffice. According to Comeau et al. (2011), the amount of time needed to achieve the target lethal temperature is 43 s for the summer time, and 2 minutes and 7 s for the winter time. The time variations are because of the different surface area temperatures present between the two seasons. The hot water needs to warm up these internal compartments. In addition, most watercraft have special areas that have water transfer pumps that require water temperature ≤ 54°C for decontamination, such as ballast tanks/bladders, wash- down systems, bait and live wells, and internal water systems. For these sensitive areas, it is recommended that the temperature of the hot-water flush be monitored until a temperature of 54°C is reached. After this target temperature is reached, it is necessary to maintain a constant flush of that temperature for at least 10 s to ensure 100% mussel mortality (Comeau et al. 2011).

CONCLUSION AND RECOMMENDATION

Hot-water Spray Watercraft Validation The results of the study showed that 3000 psi is superior to 1500 psi, as it is strong enough to remove the mussels without damaging the vessel. However, when decontaminating certain areas on the vessel, such as the gimbal unit, it is recommended to avoid using pressurized spray as it can damage some of the seals and parts in that area (Zook and Phillips 2012). If the equipment is capable, 3000 psi should be used when removing dreissenids when the watercraft is just out of water. While 3000 psi is the recommended protocol for removing dreissenids from watercraft, 1500 psi may be useful when the mussels are dead and the byssal threads have dried out. To save time and to be less of an inconvenience to boaters, if hot water is unavailable for AIS removal, it is suggested that the vessel remain out of the water for at least one week in the summer and two weeks in the winter before the high pressure spray decontamination method is used. However, this may be difficult to achieve at some water-bodies, as there may not be places to store the vessel prior to decontamination. However, using 3000 psi on a watercraft fresh out of the water will suffice for removing attached mussels.

Susceptibility of Zebra Mussels to Hot-water Spray When decontaminating watercraft, it is important not only to remove the mussels, but also ensure they are dead. When removing the mussels with high pressure spray, it is difficult to remove every mussel as some cannot be reached or they can be dislodged, landing on a different spot or on the trailer; however, using hot-water spray will certify that the mussels are at least dead. The results from hot-water spray watercraft validation test were not surprising. Once the laboratory test was completed and the temperature and time needed to reach 100% mortality in D. polymorpha was determined, the field validation was conducted. The field tests exposing D. polymorpha to 54°C for 10 s, verified the laboratory tests and 100% mortality was observed immediately after treatment.

It is extremely difficult to remove every single mussel from an infested watercraft. Combining the methods above ensures that the decontamination process is removing mussels and killing them. To fully kill and remove dreissenids from watercraft, reducing the biological risk, a combination of high pressure and hot-water spray should be used.

244

REFERENCES

Claxton, W.T., A.B.Wilson, G. L. Mackie and E. G. Boulding. 1998. A genetic and morphological comparison of shallow- and deep-water populations of the introduced dreissenid bivalve Dreissena bugensis. Canadian Journal of Zoology, 1998, 76(7): 1269- 1276, 10.1139/z98-064.

Comeau, S., S. Rainville, B. Baldwin, E. Austin, S. Gerstenberger, C. Cross, and W.H. Wong. 2011. Susceptibility of quagga mussels (Dreissena rostriformis bugensis Andrusov) to hot-water sprays as a means to mitigate biofouling. Biofouling 27: 267-274.

Elderkin, C.L. and P.L. Klerks. 2005. Variation in thermal tolerance among three Mississippi River populations of the zebra mussel, Dreissena polymorpha. Journal of Shellfish Research 24(1):221-226. 2005. Harrington, D.K., J.E Van Benschoten, J.N. Jensen, D.P. Lewis, and E.F. Neuhauser. 1997. Combined use of heat and oxidants for controlling adult zebra mussels. Water Research 31: 2783-2791.

Kappel, M. 2012. Dreissena rostiformis bugensis: desiccation of adult quagga mussels found in Lake Mead as a preventive measure against overland dispersal in the western United States. UNLV Theses/Dissertations/Professional Papers/Capstones. Paper 1744.

Mangin, S. 2011. The 100th Meridian Initiative: a strategic approach to prevent the westward spread of zebra mussels and other aquatic nuisance species. US Fish and Wildlife Service.

McMahon, R.F. and T.A. Ussery. 1995. Thermal tolerance of zebra mussels (Dreissena polymorpha) relative to rate of temperature increase and acclimation temperature. Vicksburg, MS: US Army Corps of Engineers, Waterways Experiment Station. p. 1-21.

Mills, E.L., G. Rosenberg, A.P. Spindle, M.L. Ludyanskit, Y. Pligin and B. May. 1996. A review of the biology and ecology of the quagga mussel (Dreissena bugensis, a second species of freshewater dreissenid introduced to North America. Amer. Zool. (1996) 36: (3) 271- 286.

Morse, J.T. 2009. Assessing the effects of application time and temperature on the efficacy of hot-water sprays to mitigate fouling by Dreissena polymorpha (zebra mussels Pallas). Biofouling 23: 605-610.

Piola, R.F., K.A.Dafforn and E.L. Johnston. 2009. The influence of antifouling practices on marine invasions. Biofouling 25(7): 633-644.

Spidle, A.P., B. May and E.L. Mills. 1995. Limits to tolerance of temperature and salinity in the quagga mussel (Dreissena bugensis) and the zebra mussel (D. polymorpha). Can. J. of Fish. and Aquat. Sci. 1995, 52 (10):2108-2119, 10. 1139/F95-804.

245 Zook, B. and S. Phillips. 2012. Recommended Uniform Minimum Protocols and Standards for Watercraft Interception Programs for Dreissenid Mussels in the Western United States. Western Regional Panel on Aquatic Nuisance Species. http://www.aquaticnuisance.org/wordpress/wp- content/uploads/2010/01/UMPS_II_doc2_APRIL_5_2012_FINAL_final_edits.pdf. (Retrieved 05 April 2014).

246 The temporal succession of invasive species in the Goodyear Swamp Sanctuary

Megan Wilckens1

INTRODUCTION

Goodyear Swamp Sanctuary (GSS) is a five-acre property at the northwest end of Otsego Lake belonging to the SUNY Oneonta Biological Field Station (Figure 1). While it is called a swamp, the habitat is technically a marsh, as it is permanently wet (along the edge of Otsego Lake) and is mostly made up of herbaceous plants rather than woody vegetation (Anonymous 2014a). This marsh acts as an ecotone between the lake and the forested upland. The purpose of the GSS is to provide a wildlife refuge to protect unique and native flora and fauna and ensure this wetland complex remains intact. The GSS is home to over 200 species of vascular plants, thousands of invertebrate organisms, waterfowl and other bird species, mammals, amphibians and reptiles which can be seen from the boardwalk that traverses open water areas or the boarder trail that continues into upland portions of the property (Harman et al. 1998).

Figure 1. Goodyear Swamp Sanctuary map showing the main boardwalk and boundary trail. The tree line, end of emergent vegetation and low water levels are also shown.

1 BFS Intern, summer 2014. Current Affiliation: Le Moyne College, Syracuse, NY.

247 The vegetation present in the GSS ranges from tiny aquatic plants like duckweed to towering oak and ash trees. This study focuses on the emergent wetland vegetation; the plants rooted in the lake bottom along the shoreline with stems that grow above the water’s surface (Anonymous 2014b). Specifically, this study attempted to evaluate the spread of the exotic plants Iris pseudacorus (yellow flag) and Fallopia japonica (Japanese knotweed) found in the Goodyear Swamp Sanctuary over time to determine the area of ground cover currently occupied and the density of patches with the intent of serving as a benchmark for future studies of native and invasive plant dynamics. Will the invasive species present continue to dominate the marsh or will new invasive species take over, as the I. pseudacorus did when the L. salicaria population decreased?

Native plants within northeastern wetland habitats are under increasing pressure from invasive plants that are out competing and displacing preexisting species. Without the predators and diseases with which they evolved, invasive plants can flourish in suitable habitat and establish colonies while native species, with no adaptation to the invasive species, are unable to compete for available resources (Gurevitch & Padilla, 2004). Three such invasive species are Lythrum salicaria (purple loosestrife), Iris pseudacorus and Fallopia japonica, all found within Goodyear Swamp Sanctuary. While no formal surveys have been conducted to map plant distribution throughout the property, successive editions of field guides and reports have been used to estimate the change in distribution of these three species over time; these changes are outlined in the paragraphs that follow.

Lythrum salicaria is an invasive plant from Europe that spreads about 115,000 ha/year in the U.S. and alters wetlands by dominating the native plants and creating monotypic stands (Pimentel et al. 2005). This invasive species displaces native species of cattails, sedges, bulrushes, willows and horsetails (Blossey et al. 2001). In 1986, when the first GSS self-guided tour pamphlet was made (Harman and Higgins 1986), L. salicaria was present, as well as twelve years later when a revised pamphlet was made. This invasive plant was noted at two particular locations along the Main Trail in 1986 and by 1998 it was noted at three sites; however, photographic interpretations, along with the commencement of a biocontrol study suggest its dominance within the emergent plant community and widespread distribution in the open-canopy areas of the swamp. Since 1998, there have been studies conducted on the percent cover of L. salicaria in the GSS during the spring and fall following the introduction of Galerucella calmariensis and G. pusilla in 1997 as control methods for lessening the competitive ability the invasive species had over the native plants by feeding on their meristematic regions (i.e. Waterfield 2014). Since 2001, there has been a decline in the abundance in L. salicaria in GSS as the G. calmariensis and G. pusilla populations have effectively controlled the rigor and fitness of the plant stands (Waterfield 2014).

Iris pseudacorus is another aggressive invasive species that tends to grow densely, forming monotypic patches that are hard to remove. They spread through rhizomatous mats that uplift sediment and alter habitats which in turn reduce the native diversity of a wetland (Thomas 1980). This species’ niche (habitat) is similar to that of native Typha, or cattail, along with sedges and other emergent wetland vegetation and this allows I. pseudacorus to dominate the native species in the marsh that are not adapted to competing with aggressive invasive species. Iris pseudacorus was observed in the GSS in both the 1986 and 1998 self-guided tour pamphlets, suggesting that, while not as aggressive or dense as L. salicaria was, it was established in the

248 marsh several decades ago and has continued to spread more rapidly. With the decline of L. salicaria over the past decade, I. pseudacorus had been able to thrive and expand its range within the marsh, taking over areas where L. salicaria once grew. Now I. pseudacorus is the dominant invasive species present in the GSS along the Main Trail and is starting to grow along a portion of the Boundary Trail, where it has not been seen growing before.

Fallopia japonica spreads similarly through rhizomes, forming monocultures. It has perennating buds that continue to grow underground throughout the winter, allowing it to keep spreading all year long, with woody stocks increasing in mass as the stands age (Beerling et al. 1994). This allows F. japonica to sprout in early spring before native species begin germinating, decreasing biodiversity. This species can also grow new plants from fragments of the stem as small as a node (Aguilera et al 2010). Since F. japonica spreads mainly by vegetative growth, the stems are close together forming thick canopies that block sunlight from reaching the ground layer, shading ground vegetation like skunk cabbage and various fern species, affecting their growth. Fallopia japonica was not recorded in the self-guided tour pamphlets for GSS in 1986 or 1998 so its presence in the marsh and upland areas is relatively new compared to some of the other invasive species. In fact, it had not been noted prior to 2013.

METHODS

Patches of Iris pseudacorus and Fallopia japonica throughout the marsh were delineated for mapping purposes using the track feature on a Garmin CSx76 GPS unit (Degrees Decimal Minutes, NAD83). Patch density measurements were based on stem counts within 1m x 1m plots which were established in the patches using a collapsible PVC grid. The center of each plot was marked with an Etrex GPS unit (Degrees decimal minutes, NAD83). Small patches were evaluated in a single plot. For larger patches, multiple plots were used (between two and six) depending on the spacing of the plants throughout the patch. All stems within each plot were counted to measure the patch density. Where multiple plots were established in a given patch, average plot density was reported.

The second part of this study relates to control methods for the two stands of Fallopia japonica. Manual cutting and removal was deemed the best control option for the GSS; other means of eradication and control were considered (excavation, ground barriers, herbicides), but were found to be too invasive for the sensitivity of the site or cost prohibitive. The larger of the two patches was cut down using pruning shears and machetes. Debris was removed from the Sanctuary in garbage bins (40-gallon); plant material was discarded in the dumpster and landfilled. Mass of F. Japonica removed from the GSS was estimated based on the average air- dry weight per bin.

249 RESULTS & DISCUSSION

The survey for patches of the target invasive plant species yielded five patches of Iris pseudacorus and two of Fallopia japonica. Patch density was determined based on a total of 17 1m2 plots (Table 1, Figure 2). A summary of the locations and densities of I. pseudacorus and F. japonica patches is provided in Table 2. Mean patch density of I. pseudacorus ranged from 60 stems/m2 to 143 stems/m2 while that of F. japonica ranged from 13 to 21 stems/m2. No attempts were made to remove or control the Iris pseudacorus within the marsh; any changes in patch extent or density in the future compared to the Typha stands will all be the result of natural causes.

Manual harvest of the larger F. japonica patch (Patch F) yielded approximately 25 garbage bins of plant material, or an estimated 283kg of plant material based on the average dry weight per bin (11.3 kg). Immediately following the initial cutting of the Fallopia japonica, sunlight was able to reach the ground layer. Several other species were found in amongst the F. japonica stand, including speckled alder and European hawthorn. Monitoring of the site should be continued in the future. The future extent of the patch will depend on the intensity of control methods employed. Current plans include the use of an herbicide containing glyphosate on new plants (in early spring) over the course of several years.

Table 1. Goodyear Swamp Sanctuary I. pseudacorus and F. japonica patches. Average patch densities are separated by shaded rows; mean values rounded to the nearest stem. Plot Density Average Patch Density Patch Species Plot # (stems/m²) (stems/m2) Coordinates Date A Iris pseudacorus 0 80 80 42 48.566'N 74 53.915'W 6/25/2014 B Iris pseudacorus 1 56 ~ 42 48.563'N 74 53.926'W 6/25/2014 B Iris pseudacorus 2 44 ~ 42 48.557'N 74 53.925'W 6/25/2014 B Iris pseudacorus 3 79 60 42 48.548'N 74 53.929'W 6/25/2014 C Iris pseudacorus 4 106 ~ 42 48.549'N 74 53.925'W 7/1/2014 C Iris pseudacorus 5 114 110 42 48.546'N 74 53.924'W 7/1/2014 D Iris pseudacorus 6 104 ~ 42 48.532'N 74 53.902'W 7/1/2014 D Iris pseudacorus 7 69 ~ 42 48.530'N 74 53.899'W 7/1/2014 D Iris pseudacorus 8 67 80 42 48.528'N 74 53.893'W 7/1/2014 E Iris pseudacorus 9 143 143 42 48.510'N 74 53.873'W 7/7/2014 F Fallopia japonica 10 19 ~ 42 48.513'N 74 53.863'W 7/7/2014 F Fallopia japonica 11 10 ~ 42 48.512'N 74 53.859'W 7/7/2014 F Fallopia japonica 12 21 ~ 42 48.516'N 74 53.851'W 7/7/2014 F Fallopia japonica 13 13 ~ 42 48.516'N 74 53.847'W 7/7/2014 F Fallopia japonica 14 42 ~ 42 48.519'N 74 53.849'W 7/7/2014 F Fallopia japonica 15 20 21 42 48.522'N 74 53.863'W 7/7/2014 G Fallopia japonica 16 13 13 42 48.521'N 74 53.907'W 7/7/2014

250 A B

C

D

G F

1cm = 8.5m E

Figure 4. Satellite image of Goodyear Swamp Sanctuary from Google Earth. Iris pseudacorus patches indicated with white polygons, F. japonica patches indicated with gray polygons. Plots 0-16 measuring stem densities are labeled and shown with white markers.

CONCLUSION

By the mid-1990s, purple loosestrife was the most prolific invasive species within the Goodyear Swamp Sanctuary; following the control of this plant, the distributions of other common invasive plants have expanded, potentially indicating a succession of invasive species in the marsh. Understanding how species dynamics play out over the long term following control of an invasive species is critical in order to increase the ability of conservationists and resource managers to make informed decisions with limited financial resources.

Invasive species are a threat to many native species found in the northeast. Wetlands such as the Goodyear Swamp Sanctuary marsh are especially at risk because they offer a large niche for invasive species to establish in, which then outcompete native species for available resources. It is important to look for species like Lythrum salicaria, Iris pseudacorus and Fallopia japonica

251 that are becoming a problem in and around water bodies and, where possible, control or eradicate them to prevent them from spreading. With time and consistent pressure on invasive species, native vegetation and the fauna that depend on them might have a chance at rebounding and restoring ecosystems to their natural state.

REFERENCES

Aguilera, A.G., P. Alpert, J.S. Dukes & R. Harrington. 2010. Impacts of the invasive plant fallopia japonica (houtt.) on plant communities and ecosystem processes. Biological Invasions 12(5):1243-1252.

Anonymous. 2014a. Freshwater Marshes and Swamps. New Jersey Audubon. N.p., n.d. Web. 25 Jul 2014. http://www.njaudubon.org/SectionEducation/BirdingandBoatinggoHandinHand/ FreshwaterMarshesandSwamps.asp&xgt.

Anonymous 2014b. Aquatic Plants: Emergent Plants. Minnesota Department of Natural Resources. N.p., n.d. Web. 25 Jul 2014. .

Beerling, D.J., J.P.Bailey, & A.P. Conolly. 1994. Fallopia japonica (houtt.) ronse decraene. Journal of Ecology, 82, 959-979. doi: 10.2307/2261459.

Blossey, B., L.C. Skinne and, J. Taylor. 2001. Impact and management of purple loosestrife (Lythrum salicaria) in North America. Biodiversity and Conservation. 10:1787-1807.

Gurevitch, J. & D.K. Padilla. 2004. Are invasive species a major cause of extinctions? ScienceDirect, 19(9), 470-474. doi: 10.1016/j.tree.2004.07.005.

Harman, W.N., and B. Higgins. 1986. A self-guided tour of Goodyear Swamp Sanctuary. Occas. Pap. No. 19. SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta.

Harman, W. N., Higgins, B., & Lopez, J. 1998. A self-guided tour of Goodyear Swamp Sanctuary. Occas. Pap. No. 31. SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta.

Pimentel, D., R. Zuniga & D. Morrisson. 2005. Update on the environmental and economic costs associated with alien-invasive species in the united states. Elsevier, 52(3), 273-288. doi: 10.1016/j.ecolecon.2004.10.002

Thomas, L. K. 1980. The impact of three exotic plant species on Potomac Island. Monograph series 13. National Park Service, Washington , D.C .

Waterfield, H. A. 2014. Dynamics of Gallerucella spp. and purple loosestrife (Lythrum salicaria) in Goodyear Swamp Sanctuary, summer 2013 update. In: 46th Ann. Rept. (2013) SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta.

252 Monitoring the effectiveness of the Cooperstown wastewater treatment wetland, 20141

M.F. Albright

BACKGROUND (from Albright and Waterfield 2011)

In 2002, the US Army Corp of Engineers (ACE) initiated a 1.6 million dollar Upper Susquehanna River Watershed-Cooperstown Area Ecosystem Restoration Feasibility Study And Integrated Environmental Assessment. Authorized by the U.S. Congress, the pilot program was to “use wetland restoration, soil and water conservation practices, and non-structural measures to…improve water quality and wildlife habitat…in the Upper Susquehanna River Basin…” (ACE 2001). Initially identified were eight Field Assessed Benefit and Design Strategy sites (FABADS) in Otsego County. During 2003, the SUNY Oneonta Biological Field Station (BFS) monitored two restored sites which receive agricultural runoff as well as a local “pristine reference site”. Comparisons were made between inflows and outflows, and between the wetlands, of concentrations of different nutrient fractions, suspended sediments and fecal coliform bacteria. This short term study did indicate water quality improvements when nutrient levels at the inflow were elevated (Fickbohm 2005), though it is probable that not enough time had elapsed to allow these systems to naturalize to the point where treatment potential was realized.

A third ACE restoration wetland was sited in the outskirts of the Village of Cooperstown adjacent to the municipal sewage treatment facility (Figure 1). The primary function of this 3 acre wetland was phosphorus and nitrogen removal, potentially by converting this site into a treatment wetland for the Village’s municipal effluent. However, at that time, funds to deliver the effluent to the wetland were lacking. The wetland design, provided by Ducks Unlimited, did not necessarily follow that generally utilized for treatment wetlands.

In 2009, funding was provided by the Village of Cooperstown’s Sewer Reserve Fund to hire the services of Lamont Engineering to evaluate alternatives to address nutrient reduction from the wastewater treatment plant (Jackson 2009). A more restrictive SPDES permit by the NYSDEC regarding nutrient loading to the Susquehanna River is consistent with New York State being cosignatory with the Chesapeake Bay Nutrient Reduction Strategy. The engineering report evaluated approaches to reducing phosphorus and nitrogen introduced into the Susquehanna River, their capital and annual operational costs, and expected nutrient reductions. At that time, it was recommended that utilizing the existing wetland for tertiary treatment would likely meet the nutrient reduction goals while costing substantially less than other approaches (i.e., addition of chemical coagulants, modification to the treatment plant, etc.). However, beginning in June 2014 the village was mandated by the Chesapeake Bay TMDL Implementation to limit phosphorus output from the plant to 2,170 lb (984.3 kg) per year (Cankar and Folts 2015). This report summarizes strategies employed to date to address this.

1 Funding for this project was provided by the Village of Cooperstown.

253

Figure 1. Bathymetric map of the wastewater treatment wetland, Cooperstown, NY (modified from Robb 2012).

Rationale for monitoring (from Albright and Waterfield 2011)

Wetlands have been used as water treatment cells for a number of years, but, until recently, only on a very limited basis. Since the mid 1990s, however, the number of constructed wetlands, having a broad range of system configurations and treatment applications, has increased markedly (Kadlec and Wallace 2009). When associated with municipal sewage outfalls, the parameters that are most often targeted for reduction are phosphorus, various nitrogenous compounds (ammonia, nitrate, total nitrogen), suspended solids and biological oxygen demand. The demonstrated effectiveness of the removal of these constituents has been promising, though quite variable, as design and site characteristics are, in practically every case, unique. Because of this, every time a treatment wetland is utilized, the opportunity exists to collect meaningful data which can aid in the design of future systems. More directly, data collection at some level is necessary to evaluate whether or not the goals of the treatment wetland, and the regulated limits of the parameters, are met.

From June 2010 through 2014, the concentration limit requirements of the effluent for total phosphorus, total nitrogen, ammonia and nitrates were not more stringent under the new SPDES/Chesapeake Bay Nutrient Reduction Strategy than they had been. However, refinements of those regulations more recently require reductions in total phosphorus. Continued monitoring of all nutrient species may provide insight into a reduced phosphorus load as nutrient dynamics may be inter-related.

254 METHODS

Early efforts to quantify flow from the wetland were frustrated by the apparent unreliability of water level logging equipment and by interference of the V notch weir by muskrat and beaver. However, work conducted in 2011 focused on direct reading of the gauge on the weir face. Robb (2012) mounted a programmable Reconyx® trail camera so that it would capture images of the gauge at 15-minute intervals. In the absence of moderate rainfall (> ~ 1 cm/24 hr), the mean daily inflow from the wastewater treatment plant (which is gauged) nearly equaled the outflow from the wetland (determined by the photos of the gauge on the weir). During wetter periods, a small stream entering the west side of the wetland can contribute enough flow so that the outflow exceeds the input from the treatment plant for short periods of time. Since 2012, the flow of effluent into the wetland was assumed to equal the flow out of it. Sampling did not coincide with runoff events in order to minimize their influence.

Sampling began in February 2010, and was done monthly through May 2010 to evaluate nutrient conditions prior to the diversion of effluent to the wetland (which commenced on 17 June 2010). Thereafter, samples were collected two to four times a month from the wastewater treatment plant (effluent), the wetland’s outlet, and the stream feeding the wetland (to evaluate contributions from this source, though flow here was often too low to sample). Nutrient loading to the wetland was cumulative monthly discharge X mean monthly effluent concentration; export from the wetland was monthly discharge X mean concentration at the outflow. The retention of each nutrient fraction was calculated as the difference between the load to the wetland and the load from it, and the percent retention was calculated as the mass retained / the mass loaded to the wetland (X 100).

This report summarizes results through December 2014. Samples were processed according to automated methods using a Lachat QuikChem FIA+ Water Analyzer. Samples were analyzed for total phosphorus using ascorbic acid following persulfate digestion (Liao and Martin 2001), total nitrogen using the cadmium reduction method (Pritzlaff 2003) following peroxodisulfate digestion Ebina et.al (1983), ammonia using the phenolate method (Liao 2001), and for nitrate+nitrite nitrogen using the cadmium reduction method (Pritzlaff 2003). Missing values were approximated by interpolating existing data.

RESULTS

Prior to the wetland receiving effluent, the outflowing concentrations of ammonia were below detection, nitrate averaged 0.28 mg/l, total nitrogen averaged 0.72 mg/l and total phosphorus averaged 0.043 mg/l. For the tributary inflow to the wetland from February 2010 through December 2014, mean nutrient concentrations were 0.01 mg/l (SE= 0.003) for ammonia, 0.26 mg/l (SE= 0.028) for nitrite+nitrate, 0.42 mg/l (SE= 0.03) for total nitrogen and 0.040 mg/l (SE= 0.005) for total phosphorus. The relevance of these low flows and low nutrient concentrations indicate that its influence on calculating nutrient retention rates, and investigating nutrient transformations, is minimal.

255 Summaries of the annual retention, as both net volumes (kg) as a percent of the inputs, of ammonia, nitrite+nitrate, total nitrogen and total phosphorus following the diversion of effluent to the wetland are provided in Table 1. Tables 2-5 provide mean monthly concentrations of the wastewater effluent and wetland’s outfall, as are total monthly nutrient volumes (kg), the volume of nutrients retained (kg) and the mean retention rate (%).

Between June 2010 and December 2014, the total amount of nutrients retained by the treatment wetland included 1,430 kg of ammonia-N, 9,160 kg of nitrate-N, 13,300 kg of total nitrogen-N and 1,470 kg of total phosphorus-P. The monthly rates of retention of ammonia varied much more so than did other nutrients, which seemed mainly due to high variability of its concentration in the treatment plant effluent (mean= 1.50 mg/l, SE= 0.24); concentrations were lower and less variable at the wetland’s outlet (mean= 1.01 mg/l, SE= 0.13). This temporal variation led to calculated negative retention rates (or release) of ammonia in some months. Overall, the mean retention declined from about 42% in 2010 to 27.4% in 2011 and 24% in 2012. Over 2013, it had increased to 44.7%. However, this is not believed to reflect varying treatment by the wetland, so much as the fact that the ammonia concentration of the effluent flowing to the wetland has been variable over the course of the study (2.46 mg/l in 2010, 1.67 mg/l in 2011, 0.93 mg/l in 2012 and 1.83 in 2013).

Over 2014, retention of nitrate (at 35%), total nitrogen (at 33%) and total phosphorus (at 27%) were similar to those over most years since this work began (though removal of nitrate and total nitrogen over 2012 was higher, at 46% and 42% respectively). The fact that total phosphorus retention has not declined may imply that the mechanism is, in part, related to biological uptake rather than simply sediment binding (which would reduce as the sediments become phosphorus- saturated) (Kadlec and Wallace 2009).

Given that this wetland was designed more for waterfowl habitat than for water quality improvement, the nutrient removal capacity seems promising. As vegetation densities increase, so should nutrient reduction, both directly though vegetative uptake and enhanced microbial denitrification due to increased microsites (Kadlec and Wallace 2009). Investigations into phosphorus uptake by rooted plants at the Cooperstown wetland provided conflicting results. Olsen (2011) found elevated phosphorus content in the leaf tissue of reed canary grass (Phalaris arundinacea) within the wetland than that of plants in nearby areas not influenced by the treatment wetland. However, similar investigations in 2011 on reed canary grass and cattail (Typha sp.) did not show meaningful differences in phosphorus uptake (Gazzetti 2012).

256 Table 1. Summary of ammonia, nitrate, total nitrogen and total phosphorus retention by the Cooperstown treatment wetland, 2010 through 2012.

Ammonia retention Nitrate retention T. Nit. retention T. Phos. retention Kg % Kg % Kg % Kg % 2010 (17 June-Dec) 235 42 797 28 1149 30 252 36 2011 366 27 2017 28 2685 28 251 15 2012 116 24 2637 46 3302 42 306 22 2013 514 45 1995 23 3769 43 315 22 2014 206 27 1719 35 2439 33 352 27 total 1437 33 9165 32 13344 35 1476 25

In accordance to the Chesapeake Bay Nutrient Reduction Strategy, a limit of phosphorus release was imposed upon the Cooperstown Sewage Treatment Plant beginning in June 2014. That limit is 984 kg/year (or 2.7 kg/day). Given that the plant typically discharges about 500,000 cubic meters of sewage/year, total phosphorus concentrations of <2 mg/l would satisfy that requirement. As concentrations since 2010 have averaged 2.5 mg/l, the percent reduction needed, at 20%, is modest. There have been several approaches since this effort commenced (Cankar and Folts 2015). The first, beginning on 18 June, was using K2001®, a polyaluminum chloride coagulant. It was injected after the rack and prior to the primary clarifier at a rate of approximately 1 part to 50,000 sewage. Beginning on 3 September, the product used was switched to PAX-WL8®, also a polyaluminum chloride solution. It was also injected at the primary clarifier at varying rates, typically about 1:35,000. Beginning on 17 September, the same product was used at a similar rate, but the injection point was changed to the final clarifier. On 7 October, alum (aluminum sulfate) was injected at the final clarifier at a variable rate, typically about 1:35,000. Beginning on 24 October, SLACK PLUS®, an aluminum chloride coagulant, was used. It was injected at both the primary clarifier and the final clarifier at a combined rate of between 1:40,000 and 1:20,000.The phosphorus reduction using all approaches was modest, though phosphorus discharge at all checks was below the regulated amount of 2.7 kg/day (6 lb/day). Since 4 December, the injector system has been off line as the plant prepares for the installation of an in-pipe injector which is expected to improve coagulation and removal.

257 Table 2. Mean monthly concentrations of ammonia in the wastewater effluent and wetland’s outfall (mg/l), total monthly ammonia volumes (kg) entering and leaving the wetland, the volume of ammonia retained (kg) and the mean retention rate (%). (Projected).

Month Eff flow NH4 CM/day EFF (mg/l) Out (mg/l) EFF (kg) OUT (kg) RET. (kg) % RET. Jun-10* 1728 4.10 1.41 63.8 21.9 41.8 65.6 Jul-10 1692 0.31 1.03 16.1 54.0 -37.9 -235.5 Aug-10 1526 5.35 2.46 252.9 116.2 136.8 54.1 Sep-10 1186 2.19 1.17 77.9 41.6 36.3 46.6 Oct-10 1476 2.19 1.17 100.2 53.5 46.7 46.6 Nov-10 1447 0.60 0.45 26.0 19.7 6.3 24.3 Dec-10 1330 0.60 0.48 23.9 19.1 4.9 20.3 2010 560.9 326.1 234.8 41.9 Jan-11 1222 0.68 0.478 24.9 17.5 7.4 29.6 Feb-11 1319 2.68 2.488 98.8 91.8 6.9 7.0 Mar-11 2707 4.30 1.995 360.4 167.4 193.0 53.6 Apr-11 2824 1.96 1.883 166.2 159.5 6.7 4.0 May-11 2816 0.68 1.134 59.6 99.0 -39.4 -66.0 Jun-11 2495 2.15 1.816 161.1 135.9 25.2 15.6 Jul-11 1862 0.54 0.953 31.1 55.0 -23.9 -77.0 Aug-11 1859 3.99 2.073 230.0 119.4 110.6 48.1 Sep-11 2532 0.87 0.758 66.0 57.5 8.5 12.9 Oct-11 2120 0.71 0.341 45.2 21.7 23.5 52.0 Nov-11 1896 0.75 0.461 42.5 26.2 16.3 38.3 Dec-11 1961 0.77 0.262 46.8 15.9 30.9 66.0 2011 1332.6 967.0 365.6 27.4 Jan-12 1972 0.80 0.45 47.3 26.6 20.7 43.8 Feb-12 1722 0.69 0.44 33.3 21.2 12.1 36.2 Mar-12 1832 0.55 0.44 31.2 25.0 6.2 20.0 Apr-12 1427 0.55 0.44 23.5 18.8 4.7 20.0 May-12 1718 0.41 0.14 21.8 7.5 14.4 65.9 Jun-12 1442 0.68 0.61 29.4 26.4 3.0 10.3 Jul-12 1340 2.46 2.28 102.2 94.7 7.5 7.3 Aug-12 1344 1.39 1.50 57.9 62.5 -4.6 -7.9 Sep-12 1124 0.63 0.55 21.2 18.5 2.7 12.7 Oct-12 1196 0.52 0.43 18.7 15.4 3.2 17.3 Nov-12 1128 0.77 0.86 26.1 29.1 -3.0 -11.7 Dec-12 1245 1.68 0.40 64.9 15.4 49.4 76.2 2012 477.5 361.2 116.3 24.4 Jan-13 1431 0.28 0.25 12.4 11.3 1.1 9.1 Feb-13 1321 1.21 0.46 44.9 17.1 27.8 61.9 Mar-13 1473 1.55 1.00 70.5 45.7 24.8 35.2 Apr-13 1893 4.08 2.36 231.7 134.0 97.7 42.2 May-13 1522 0.81 0.81 38.2 38.3 -0.1 -0.2 Jun-13 2192 2.26 0.89 148.6 58.5 90.1 60.6 Jul-13 2332 1.58 1.13 113.9 81.5 32.3 28.4 Aug-13 1703 3.96 1.58 209.1 83.2 125.9 60.2 Sep-13 1647 2.77 1.08 137.0 53.6 83.4 60.9 Oct-13 1348 1.32 0.92 55.0 38.3 16.7 30.4 Nov-13 1242 0.92 0.87 34.3 32.4 1.9 5.4 Dec-13 1427 1.21 0.93 53.5 41.1 12.4 23.1 2013 1149.0 635.0 514.0 44.7

258 Table 2 (cont.). Mean monthly concentrations of ammonia in the wastewater effluent and wetland’s outfall (mg/l), total monthly ammonia volumes (kg) entering and leaving the wetland, the volume of ammonia retained (kg) and the mean retention rate (%).

Month Eff flow NH4 CM/day EFF (mg/l) Out (mg/l) EFF (kg) OUT (kg) RET. (kg) % RET. Jan-14 1552 1.91 0.37 88.9 17.4 71.6 80.5 Feb-14 1215 1.42 1.34 48.3 45.5 2.8 5.8 Mar-14 1476 3.76 1.69 171.8 77.5 94.3 54.9 Apr-14 1855 2.77 2.75 154.3 153.2 1.1 0.7 May-14 1817 0.87 0.36 49.2 20.4 28.8 58.5 Jun-14 1480 1.15 0.73 50.8 32.5 18.3 36.0 Jul-14 1631 1.58 1.56 79.9 78.9 1.0 1.3 Aug-14 1389 0.21 0.00 9.0 0.0 9.0 100.0 Sep-14 1139 0.23 0.36 7.9 12.2 -4.2 -53.5 Oct-14 1154 1.77 1.16 61.3 40.1 21.2 34.5 Nov-14 1003 0.04 0.63 1.3 19.0 -17.7 -1384.0 Dec-14 1351 0.94 1.43 39.4 59.7 -20.3 -51.6 2014 762.2 556.3 205.9 27.0 To date 4282.2 2845.7 1436.5 33.1

Table 3. Mean monthly concentrations of nitrite+nitrate in the wastewater effluent and wetland’s outfall (mg/l), total monthly nitrite+nitrate volumes (kg) entering and leaving the wetland, the volume of nitrite+nitrate retained (kg) and the mean retention rate (%).

Month Eff flow NO2+NO3 CM/day EFF (mg/l) Out (mg/l) EFF (kg) OUT (kg) RET. (kg) % RET. Jun-10* 1728 11.85 8.05 184.3 125.2 59.1 32.1 Jul-10 1692 9.37 7.65 491.2 401.0 90.2 18.4 Aug-10 1526 9.13 5.75 432.2 272.1 160.1 37.0 Sep-10 1186 10.85 5.80 385.8 206.2 179.6 46.6 Oct-10 1476 10.70 6.43 489.6 294.2 195.4 39.9 Nov-10 1447 11.38 8.33 493.9 361.4 132.4 26.8 Dec-10 1330 9.15 9.65 365.1 385.0 -20.0 -5.5 2010 2842.0 2045.1 796.9 28.0 Jan-11 1222 13.35 13.150 489.5 482.2 7.3 1.5 Feb-11 1319 12.70 11.280 468.9 416.5 52.4 11.2 Mar-11 2707 5.31 4.100 445.5 344.0 101.5 22.8 Apr-11 2824 6.75 3.707 571.6 314.0 257.5 45.1 May-11 2816 8.83 6.665 770.9 581.9 189.0 24.5 Jun-11 2495 10.48 5.575 783.9 417.2 366.7 46.8 Jul-11 1862 9.44 7.850 545.0 453.2 91.8 16.8 Aug-11 1859 12.83 8.095 739.3 466.4 272.9 36.9 Sep-11 2532 9.12 5.075 692.8 385.5 307.3 44.4 Oct-11 2120 7.81 6.350 496.6 403.8 92.8 18.7 Nov-11 1896 8.45 5.585 480.8 317.8 163.0 33.9 Dec-11 1961 10.30 8.420 626.1 511.8 114.3 18.3 2011 7111.0 5094.3 2016.7 28.4

259 Table 3 (cont.). Mean monthly concentrations of nitrite+nitrate in the wastewater effluent and wetland’s outfall (mg/l), total monthly nitrite+nitrate volumes (kg) entering and leaving the wetland, the volume of nitrite+nitrate retained (kg) and the mean retention rate (%).

Month Eff flow NO2+NO3 CM/day EFF (mg/l) Out (mg/l) EFF (kg) OUT (kg) RET. (kg) % RET. Jan-12 1972 8.47 7.94 501.1 469.7 31.4 6.3 Feb-12 1722 9.55 7.81 460.5 376.6 83.9 18.2 Mar-12 1832 9.75 7.82 553.7 444.1 109.6 19.8 Apr-12 1427 12.12 9.02 518.8 386.1 132.7 25.6 May-12 1718 9.52 4.39 507.1 233.9 273.3 53.9 Jun-12 1442 12.92 3.71 559.0 160.5 398.4 71.3 Jul-12 1340 10.10 3.08 419.5 127.9 291.6 69.5 Aug-12 1344 7.80 2.75 324.9 114.5 210.4 64.7 Sep-12 1124 8.56 1.96 288.7 66.1 222.6 77.1 Oct-12 1196 10.20 2.73 366.0 98.0 268.0 73.2 Nov-12 1128 15.70 8.65 531.3 292.7 238.6 44.9 Dec-12 1245 17.00 7.25 656.3 279.9 376.4 57.4 2012 5686.8 3050.0 2636.8 46.4 Jan-13 1431 10.50 9.43 465.8 418.1 47.7 10.2 Feb-13 1321 11.18 8.43 413.4 311.6 101.7 24.6 Mar-13 1473 7.03 4.42 320.7 201.5 119.1 37.2 Apr-13 1893 7.47 5.12 424.2 290.7 133.4 31.5 May-13 1522 10.90 4.65 514.2 219.4 294.8 57.3 Jun-13 2192 12.10 12.90 795.6 848.2 -52.6 -6.6 Jul-13 2332 9.44 3.83 682.0 276.9 405.2 59.4 Aug-13 1703 9.20 2.61 485.8 137.6 348.3 71.7 Sep-13 1647 9.46 1.50 467.4 74.0 393.5 84.2 Oct-13 1348 7.19 6.00 300.4 250.7 49.7 16.6 Nov-13 1242 9.19 10.20 342.3 379.9 -37.6 -11.0 Dec-13 1427 11.80 7.46 522.0 329.8 192.2 36.8 2013 5733.7 3738.3 1995.4 34.8 Jan-14 1552 8.00 7.55 372.4 351.5 20.9 5.6 Feb-14 1215 7.33 5.33 249.2 181.2 68.0 27.3 Mar-14 1476 5.68 3.86 260.0 176.5 83.5 32.1 Apr-14 1855 4.38 2.94 243.7 163.5 80.2 32.9 May-14 1817 9.19 4.61 517.6 259.5 258.1 49.9 Jun-14 1480 15.03 8.33 667.1 369.8 297.2 44.6 Jul-14 1631 9.66 5.67 488.7 286.7 201.9 41.3 Aug-14 1389 15.90 8.11 684.7 349.2 335.5 49.0 Sep-14 1139 12.56 7.44 429.3 254.1 175.2 40.8 Oct-14 1154 12.61 6.10 436.7 211.3 225.5 51.6 Nov-14 1003 8.71 11.53 261.9 346.8 -84.9 -32.4 Dec-14 1351 7.70 6.31 322.5 264.3 58.2 18.1 2014 4933.9 3214.4 1719.4 34.8 To date 26307.4 17142.2 9165.3 34.5

260 Table 4. Mean monthly concentrations of total nitrogen in the wastewater effluent and wetland’s outfall (mg/l), total monthly total nitrogen volumes (kg) entering and leaving the wetland, the volume of total nitrogen retained (kg) and the mean retention rate (%).

Month Eff flow TN CM/day EFF (mg/l) Out (mg/l) EFF (kg) OUT (kg) RET. (kg) % RET. Jun-10* 1728 17.30 9.51 269.0 147.9 121.2 45.0 Jul-10 1692 14.10 12.50 739.6 655.7 83.9 11.3 Aug-10 1526 16.03 9.38 758.3 443.6 314.7 41.5 Sep-10 1186 13.47 7.32 479.0 260.2 218.7 45.7 Oct-10 1476 12.40 7.29 567.4 333.3 234.0 41.3 Nov-10 1447 13.65 10.05 592.6 436.3 156.3 26.4 Dec-10 1330 10.90 10.40 434.9 415.0 20.0 4.6 2010 3840.8 2692.0 1148.8 29.9 Jan-11 1222 16.48 16.375 604.1 600.4 3.7 0.6 Feb-11 1319 19.28 14.875 711.7 549.2 162.5 22.8 Mar-11 2707 10.20 6.775 855.8 568.4 287.4 33.6 Apr-11 2824 9.38 5.942 794.9 503.4 291.6 36.7 May-11 2816 11.45 9.075 999.7 792.3 207.4 20.7 Jun-11 2495 17.58 8.338 1315.3 624.0 691.3 52.6 Jul-11 1862 14.46 11.038 835.0 637.2 197.7 23.7 Aug-11 1859 11.11 12.350 639.8 711.6 -71.7 -11.2 Sep-11 2532 11.65 6.275 885.1 476.7 408.4 46.1 Oct-11 2120 9.83 7.720 625.1 491.0 134.2 21.5 Nov-11 1896 9.97 6.365 567.2 362.1 205.1 36.2 Dec-11 1961 11.80 9.045 717.3 549.8 167.5 23.3 2011 9551.0 6866.2 2684.8 28.1 Jan-12 1972 10.20 9.01 603.4 533.0 70.4 11.7 Feb-12 1722 11.20 8.84 540.1 426.3 113.8 21.1 Mar-12 1832 13.23 12.28 751.3 697.4 54.0 7.2 Apr-12 1427 19.08 12.30 816.8 526.5 290.2 35.5 May-12 1718 13.98 6.35 744.7 338.3 406.5 54.6 Jun-12 1442 14.40 6.04 623.0 261.3 361.7 58.1 Jul-12 1340 17.00 8.05 706.1 334.4 371.8 52.6 Aug-12 1344 13.55 7.00 564.4 291.6 272.8 48.3 Sep-12 1124 14.88 4.27 501.8 144.0 357.8 71.3 Oct-12 1196 17.20 5.48 617.2 196.6 420.5 68.1 Nov-12 1128 18.28 9.45 618.6 319.8 298.8 48.3 Dec-12 1245 20.30 12.95 783.6 499.9 283.7 36.2 2012 7871.0 4569.1 3302.0 42.0 Jan-13 1431 14.78 13.03 655.4 577.8 77.6 11.8 Feb-13 1321 16.70 11.23 617.7 415.2 202.5 32.8 Mar-13 1473 11.73 8.03 535.2 366.3 168.9 31.6 Apr-13 1893 21.46 12.19 1218.5 692.2 526.4 43.2 May-13 1522 15.00 6.69 707.6 315.6 392.0 55.4 Jun-13 2192 14.45 6.47 950.1 425.4 524.7 55.2 Jul-13 2332 12.80 5.75 925.3 415.3 510.0 55.1 Aug-13 1703 13.41 4.99 707.9 263.6 444.3 62.8 Sep-13 1647 14.34 3.88 708.2 191.9 516.3 72.9 Oct-13 1348 11.80 9.33 493.0 389.6 103.4 21.0 Nov-13 1242 12.50 10.80 465.6 402.3 63.3 13.6 Dec-13 1427 15.95 10.55 705.6 466.5 239.1 33.9 2013 8690.1 4921.6 3768.6 43.4

261 Table 4 (cont.). Mean monthly concentrations of total nitrogen in the wastewater effluent and wetland’s outfall (mg/l), total monthly total nitrogen volumes (kg) entering and leaving the wetland, the volume of total nitrogen retained (kg) and the mean retention rate (%).

Month Eff flow TN CM/day EFF (mg/l) Out (mg/l) EFF (kg) OUT (kg) RET. (kg) % RET. Jan-14 1552 13.40 11.35 623.8 528.4 95.4 15.3 Feb-14 1215 12.75 9.63 433.7 327.4 106.3 24.5 Mar-14 1476 10.17 7.93 465.5 362.9 102.6 22.0 Apr-14 1855 12.76 8.54 709.8 475.2 234.6 33.1 May-14 1817 15.62 8.70 879.6 490.2 389.4 44.3 Jun-14 1480 19.25 10.38 854.7 460.9 393.8 46.1 Jul-14 1631 14.79 9.18 748.0 464.4 283.5 37.9 Aug-14 1389 18.70 9.16 805.3 394.4 410.8 51.0 Sep-14 1139 13.36 9.05 456.8 309.2 147.6 32.3 Oct-14 1154 17.75 7.96 614.7 275.7 339.1 55.2 Nov-14 1003 16.04 19.80 482.5 595.8 -113.3 -23.5 Dec-14 1351 9.22 8.04 386.2 336.8 49.4 12.8 2014 7460.6 5021.3 2439.3 32.7 To date 37413.5 24070.1 13343.5 35.2

Table 5. Mean monthly concentrations of total phosphorus in the wastewater effluent and wetland’s outfall (mg/l), total monthly total phosphorus volumes (kg) entering and leaving the wetland, the volume of total phosphorus retained (kg) and the mean retention rate (%).

Month Eff flow TP CM/day EFF (mg/l) Out (mg/l) EFF (kg) OUT (kg) RET. (kg) % RET. Jun-10* 1728 4.36 1.49 67.7 23.2 44.5 65.7 Jul-10 1692 1.49 0.81 78.3 42.6 35.7 45.6 Aug-10 1526 3.20 2.15 151.3 101.6 49.7 32.8 Sep-10 1186 3.39 2.32 120.6 82.5 38.1 31.6 Oct-10 1476 2.41 1.56 110.2 71.4 38.8 35.2 Nov-10 1447 2.28 1.52 99.2 66.2 33.0 33.3 Dec-10 1330 1.76 1.45 70.2 57.7 12.6 17.9 2010 697.4 445.1 252.3 36.2 Jan-11 1222 2.205 2.030 80.8 74.4 6.4 7.9 Feb-11 1319 2.225 1.865 82.2 68.9 13.3 16.2 Mar-11 2707 1.168 0.701 98.0 58.8 39.1 39.9 Apr-11 2824 1.088 0.700 92.2 59.3 32.9 35.7 May-11 2816 1.645 1.160 143.6 101.3 42.3 29.5 Jun-11 2495 3.092 2.402 231.4 179.7 51.6 22.3 Jul-11 1862 2.807 2.870 162.1 165.7 -3.6 -2.2 Aug-11 1859 3.700 4.125 213.2 237.7 -24.5 -11.5 Sep-11 2532 1.419 1.308 107.8 99.3 8.5 7.8 Oct-11 2120 4.400 3.950 279.8 251.2 28.6 10.2 Nov-11 1896 1.480 0.681 84.2 38.8 45.4 54.0 Dec-11 1961 0.996 0.818 60.6 49.7 10.9 17.9 2011 1635.8 1384.8 251.0 15.3

262 Table 5 (cont.). Mean monthly concentrations of total phosphorus in the wastewater effluent and wetland’s outfall (mg/l), total monthly total phosphorus volumes (kg) entering and leaving the wetland, the volume of total phosphorus retained (kg) and the mean retention rate (%).

Month Eff flow TP CM/day EFF (mg/l) Out (mg/l) EFF (kg) OUT (kg) RET. (kg) % RET. Jan-12 1972 0.941 0.810 55.7 47.9 7.7 13.9 Feb-12 1722 1.230 1.237 59.3 59.6 -0.3 -0.6 Mar-12 1832 2.020 1.462 114.7 83.0 31.7 27.6 Apr-12 1427 3.100 2.193 132.7 93.9 38.8 29.3 May-12 1718 2.535 1.437 135.0 76.5 58.5 43.3 Jun-12 1442 3.340 2.578 144.5 111.5 33.0 22.8 Jul-12 1340 3.052 3.152 126.8 130.9 -4.2 -3.3 Aug-12 1344 3.360 2.645 140.0 110.2 29.8 21.3 Sep-12 1124 4.060 3.345 136.9 112.8 24.1 17.6 Oct-12 1196 2.930 1.985 105.1 71.2 33.9 32.3 Nov-12 1128 3.367 2.502 113.9 84.7 29.3 25.7 Dec-12 1245 3.480 2.860 134.3 110.4 23.9 17.8 2012 1399.0 1092.8 306.2 21.9 Jan-13 1431 1.170 1.183 51.9 52.5 -0.6 -1.1 Feb-13 1321 2.453 1.645 90.7 60.9 29.9 32.9 Mar-13 1473 1.610 1.148 73.5 52.4 21.1 28.7 Apr-13 1893 2.835 2.475 161.0 140.5 20.4 12.7 May-13 1522 1.880 1.380 88.7 65.1 23.6 26.6 Jun-13 2192 1.376 1.115 90.5 73.3 17.2 19.0 Jul-13 2332 3.093 2.315 223.5 167.3 56.2 25.1 Aug-13 1703 2.990 1.989 157.9 105.0 52.9 33.5 Sep-13 1647 2.569 1.928 126.9 95.2 31.7 25.0 Oct-13 1348 2.838 2.393 118.5 99.9 18.6 15.7 Nov-13 1242 3.335 2.340 124.2 87.2 37.1 29.8 Dec-13 1427 2.230 2.075 98.7 91.8 6.9 7.0 2013 1406.0 1091.1 314.8 22.4 Jan-14 1552 2.187 1.969 101.8 91.7 10.1 9.9 Feb-14 1215 3.017 2.209 102.6 75.1 27.5 26.8 Mar-14 1476 2.638 2.017 120.7 92.3 28.4 23.6 Apr-14 1855 2.097 1.532 116.7 85.2 31.4 26.9 May-14 1817 2.998 2.148 168.8 120.9 47.9 28.4 Jun-14 1480 2.890 2.083 128.3 92.5 35.9 27.9 Jul-14 1631 2.108 1.963 106.6 99.3 7.4 6.9 Aug-14 1389 3.035 1.860 130.7 80.1 50.6 38.7 Sep-14 1139 1.873 1.653 64.0 56.5 7.5 11.7 Oct-14 1154 2.880 0.940 99.7 32.6 67.2 67.4 Nov-14 1003 2.598 1.690 78.2 50.9 27.3 34.9 Dec-14 1351 1.469 1.220 61.5 51.1 10.4 16.9 2014 1279.7 928.1 351.6 27.5 To date 6417.9 4941.9 1476.0 24.7

263 CONCLUSION

The bathymetry of the wetland (see Figure 1) implies that much of the wetland is considerably deeper than that recommended for maximum nutrient removal; shallower systems allow for the colonization of suitable plants, preferably emergents (Kadlec and Wallace 2009). Also, work by Robb (2012), considering nutrient concentrations across the standing water and by using fluorescent tracers, indicate that the most suitable portion of the system regarding depth (the southeast arm) is ineffective since it is not in the flow path of the effluent. It may be worth considering maintaining the water level lower than the original design, as it was through the later months of 2013 to alleviate plugging issues, in order to encourage plant growth.

The reduction of total phosphorus, ammonia, nitrate and total nitrogen have remained between 25-35%. It remains to be seen how the reduction in nitrogenous compounds will be affected as phosphorus is more effectively removed from the effluent before it’s discharge to the wetland.

REFERENCES

ACE. 2001. Upper Susquehanna River Watershed-Cooperstown Area Ecosystem Restoration Feasibilty Study and Integrated Environmental Assessment. Project management Plan. United States Army Corps of Engineers, Planning Division. Baltimore, MD.

Albright, M.F. and H.A.Waterfield. 2011. Monitoring the effectiveness of the Cooperstown wastewater treatment wetland. In 43rd Ann. Rept. (2010). SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta.

Cankar, J. and S. Folts. 2015. Pers. Comm. Cooperstown Sewage Treatment Plant. Cooperstown, NY.

Ebina, J., T. Tsutsi, and T. Shirai. 1983. Simultaneous determination of total nitrogen and total phosphorus in water using peroxodisulfate oxidation. Water Res.7 (12):1721-1726.

Fickbohm, S.S. 2005. Upper Susquehanna River Watershed- Cooperstown Area Ecosystem Restoration Feasibility Study And Integrated Environmental Assessment: Post- restoration water quality and wildlife analysis of the FABADS sites (2003-2004). In 37th Ann. Rept. (2004). SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta.

Gazzetti, E. 2012. Efficacy of emergent plants as a means of phosphorus removal in a treatment wetland, Cooperstown, New York. In 44th Ann. Rept. (2011). SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta.

Jackson, M.H. 2009. Wastewater treatment facility modifications engineering report. Lamont Engineers, Cobleskill, NY.

Kadlec, R.H and S.D. Wallace. 2009. Treatment wetlands (second ed.). CRC Press, Boca

264 Raton.

Liao, N. 2001. Determination of ammonia by flow injection analysis. QuikChem ® Method 10-107-06-1-J. Lachat Instruments, Loveland, CO.

Liao, N. and S. Marten. 2001. Determination of total phosphorus by flow injection analysis colorimetry (acid persulfate digestion method). QuikChem ® Method 10-115-01-1- F. Lachat Instruments, Loveland, CO.

Olsen, B. 2011. Phosphorus content in reed canary grass (Phalaris arundinacea) in a treatment wetland, Cooperstown, NY. In 43rd Ann. Rept. (2010). SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta.

Pritzlaff, D. 2003. Determination of nitrate/nitrite in surface and wastewaters by flow injection analysis. QuikChem ® Method 10-107-04-1-C. Lachat Instruments, Loveland, CO.

Robb, T. 2012. Insight into a complex system: Cooperstown wastewater treatment wetland, 2011. In 44th Ann. Rept. (2011). SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta.

265 Aquatic macrophyte management plan facilitation, Lake Moraine, Madison County, NY 2014

B.P. German1 and M.F. Albright

BACKGROUND (From Harman et al. 2010)

Located in Madison County NY, Moraine Lake (42o 50’ 47” N, 75o 31’ 39” W) was formed by a deposited glacial moraine damming a valley. The lake, which has been artificially raised, is divided into two basins separated by a causeway and interconnected by a submerged culvert. The north basin is approximately 79 acres, has a mean depth of 1.1m, and a maximum depth 3.7m. The south basin occupies 182 acres, has a mean depth of 5.4m, and a maximum depth of 13.7m. Most of the recreational activities such as fishing, boating and swimming take place in the south basin (Harman et al. 1997).

Moraine Lake has been regarded as meso-eutrophic due to the high productivity of algae and macrophytic plants, low transparency, and depleting levels of dissolved oxygen in the hypolimnion during summer stratification. Development of lakeside residences and nearby agricultural activities are believed to have contributed to the current productivity status of the upper and lower basins (Anon. 1991). Nutrient loading as a result of faulty septic systems from the residences are believed to be a significant source of the problem in nutrient introduction (Harman et al. 1998). Many of the systems are out of date, undersized, and extremely close to the lake (Brown et al. 1983). Furthermore, soils surrounding the lake have poor percolation rates, steep slopes, shallow depths to bedrock, and fractured bedrock make the lake vulnerable to nutrient loading (Harman et al. 2008).

INTRODUCTION

The aquatic macrophyte communities of Moraine Lake have been monitored by the SUNY Oneonta Biological Field Station (BFS) since 1997. The purpose of monitoring these plant communities has historically been directed towards controlling Eurasian water-milfoil (Myriophyllum spicatum), though in recent years the expansion of the exotic starry stonewort (Nitellopsis obtusa) has been a matter of increased focus. Eurasian water-milfoil is an invasive species that grows rapidly and its extensive canopies cause problems for recreation and other species growth (Borman et al. 1999). Numerous methods of control have been applied to reduce the abundance of Eurasian water-milfoil (Harman et al. 2006). Since 1998, efforts have focused primarily on applications of Sonar®, which has been demonstrated to control Eurasian water- milfoil with some specificity. Other efforts have involved stocking the weevil Euhrychiopsis lecontei, which had been shown to limit the growth of Eurasian milfoil in some instances (Harman et al. 2002). The goal of managing the Eurasian water-milfoil in the past has been to achieve a balance of species (Lembi 2000, Harman et al. 2008). Most recent activities have

1 MS in Lake Management candidate.

266 included a Sonar® application in the north basin in 2010 and in the south basin in 2011. Copper Sulfate was applied in 2013-2014, and Renovate® was used in the north basin in July 2014

MATERIALS AND METHODS

Sampling took place 4 June, 25 July and 7 September 2014. Five collection sites were sampled, two in the north basin and three from the south basin (Figure 1). The sampling method used was the Point Intercept Rake Toss Relative Abundance Method (PIRTRAM) (Lord and Johnson 2006). It was evaluated in 2008 by comparing the PIRTRAM and dry weight methods such that the rake toss method “could prove useful, if not too much value is placed on actual abundance estimates. …an adequate number of replicate samples could provide insight into species dominance and extent related to exotic nuisance species as well as efforts to control them” (Harman et al. 2008).

For this method two heads of garden rakes were welded together and connected to a 10m nylon cord. At each of the 5 sites, the rake was thrown out randomly 3 times. The rake was allowed to settle to the bottom of the lake and slowly pulled into the boat. Once in the boat, species were separated and each was assigned an abundance category. The 5 abundance categories are “no plants” (denoted by “Z”), “fingerful” (“T”= trace), “handful” (“S” = sparse), rakeful (“M” =medium), and “can’t bring into the boat” (“D” = dense). Table 1 provides biomass range estimates associated with each category. Each rake toss triplicate sample’s category was converted to its corresponding mid-point (Harman et al. 2008). The mid-points were averaged for each species at each site. These species averages were then summed together to look at overall biomass at each site.

In each basin at the deepest location, water quality parameters were measured with a YSI® multiprobe. From surface to substrate, temperature, dissolved oxygen, conductivity, and pH were measured. A water sample was taken from each basin and returned to the lab to be analyzed using the Lachat QuickChem FIA+Water Analyzer®. The ascorbic acid method following persulfate digestion (Liao and Marten 2001) was used to determine total phosphorus. For total nitrogen, the cadmium reduction method (Pritzlaff 2003) was used following peroxodisulfate digestion as described by Ebina et al. (1983). The phenolate method (Liao 2001) was used to measure ammonia and the cadmium reduction method (Pritzlaff 2003) for nitrate+nitrate-nitrogen. (Harman et al. 2008)

267

Figure1. Bathymetric map of Moraine Lake, Madison County, NY. Contours in feet. WQ1 and WQ2 represent were water quality data were collected, sites 1-5 represent where plant biomass and rake toss methods were performed (Harman et al. 2008).

Table 1. Categories, field measurements, midpoint of each category (g/m2) and dry weight ranges applied for the rake toss method and used to generate Tables 2-6 (Harman et al. 2008).

Abundance Categories Field Measure Total Dry Weight (g/m^2) mid low high "Z" = no plants Nothing 0 0 0 0 "T" = trace plants Fingerful .0001 - 2.000 1 0.0001 2 "S" = sparse plants Handful 2.001 - 140.000 71 2.001 140 "M" = medium plants Rakeful 140.001 - 230.000 185 140.001 230 "D" = dense plants Can't bring in boat 230.001 - 450.000+ 340 230.001 450

268 RESULTS

Plant Biomass

Tables 2-6 proved biomass estimates, by species, during 2014 for sites 1-5 at Moraine Lake. Eurasian water-milfoil was nearly absent from the south basin sites throughout the summer (Tables 2-4). However, it was abundant in the north basin throughout June and July; by September it was in a state of decomposition (Tables 5 and 6). Of particular note is the dominance by starry stonewort (Nitellopsis obtusa) at sites 1, 2 and 3; the biomass estimates given in Tables 2, 3 and 4 undoubtedly underestimate actual values because masses of this plant would collapse and fall off the rake as it was being pulled into the boat. Beds of this plant were often so thick that the perception was that a false bottom existed over 1 m from the actual bottom. 2013 was the first year that it was noted at site 2, and by summer’s end it dominated there. In 2014, starry stonewort was first documented in the north basin, and by September it was established at both sites there (Tables 5 and 6). As it becomes established, Eurasian milfoil is reduced.

Figures 2-6 graphically summarize the plant biomass contributed by starry stonewort (Nitellopsis obtusa), Eurasian milfoil (Myriophyllum spicatum) and other plant species between 2008 and 2014. While not the original focus of study, starry stonewort is highlighted along with milfoil because it is also an exotic nuisance species and management efforts ought to focus upon control both species. Also, the temporal variations implied by these figures may be misleading. The highest midpoint that can be assigned by any given species is 340 g/m2 (see Table 1). In some visits prior to 2012, more than one species was assigned this highest value, though the cumulative biomass value, in actuality, likely did not exceed the monocultural beds encountered in 2012 and 2013.

269 Table 2. Mean biomass (g/m2) category mid-points for each species found at Site 1 during 2014 sampling events.

Site 1 6/4/2014 7/25/2014 9/7/2014 Myriophyllum spicatum Megalodonta beckii Zosterella dubia Najas spp. Ceratophyllum demersum 62 Chara vulgaris Vallisneria americana Elodea canadensis Ranunculus aquatilis Ranunculus trichophyllus Stuckenia pectinata 1 Potamogeton crispus 175 Potamogeton zosteriformis 1 Potamogeton pusillus Nitellopsis obtusa 62 185 124 Total 300 186 124

Table 3. Mean biomass (g/m2) category mid-points for each species found at Site 2 during 2014 sampling events.

Site 2 6/4/2014 7/25/2014 9/7/2014 Myriophyllum spicatum Megalodonta beckii Zosterella dubia Najas spp. Ceratophyllum demersum 0 0 Chara vulgaris Vallisneria americana Elodea canadensis 1 1 Ranunculus aquatilis Ranunculus trichophyllus Stuckenia pectinata 147 86 Potamogeton crispus Potamogeton zosteriformis Potamogeton pusillus Nitellopsis obtusa 24 71 124 Total 172 158 124

270 Table 4. Mean biomass (g/m2) category mid-points for each species found at Site 3 during 2014 sampling events.

Site 3 6/4/2014 7/25/2014 9/7/2014 Myriophyllum spicatum 1 Megalodonta beckii Zosterella dubia Najas spp. Ceratophyllum demersum 113 Chara vulgaris 24 Vallisneria americana Elodea canadensis Ranunculus aquatilis Ranunculus trichophyllus Stuckenia pectinata 0 Potamogeton crispus 109 Potamogeton zosteriformis 0 Potamogeton pusillus Nitellopsis obtusa 147 147 340 Total 280 148 453

Table 5. Mean biomass (g/m2) category mid-points for each species found at Site 4 during 2014 sampling events.

Site 4 6/4/2014 7/25/2014 9/7/2014 Myriophyllum spicatum 185 109 Megalodonta beckii Zosterella dubia Najas spp. Ceratophyllum demersum 161 Chara vulgaris Vallisneria americana 24 Elodea canadensis 0 Ranunculus aquatilis Ranunculus trichophyllus Stuckenia pectinata 1 47 0 Potamogeton crispus 71 Potamogeton zosteriformis 0 0 Potamogeton pusillus 0 Nitellopsis obtusa 62 Total 257 157 247

271 Table 6. Mean biomass (g/m2) category mid-points for each species found at Site 5 during 2014 sampling events.

Site 5 6/4/2014 7/25/2014 9/7/2014 Myriophyllum spicatum 185 137 Megalodonta beckii Zosterella dubia 0 Najas spp. Ceratophyllum demersum 0 0 147 Chara vulgaris Vallisneria americana 1 Elodea canadensis Ranunculus aquatilis Ranunculus trichophyllus Stuckenia pectinata 0 0 24 Potamogeton crispus 47 Potamogeton zosteriformis 0 Potamogeton pusillus Nitellopsis obtusa 85 50 Total 233 223 222

Site 1 Plant Community 800 Nitellopsis obtusa 700 Myriophyllum spicatum

600 Others 500

400

300

Dry Weight (g/m^2) 200

100

0

Figure 2. Comparison of biomass (g/m2) of starry stonewort (Nitellopsis obtusa), Eurasian milfoil (Myriophyllum spicatum) and other plant species present, 2008 (Harman et al. 2009), 2009 (Harman et al. 2010), 2010 (Harman et al 2011), 2011 (Harman et al. 2012), 2012 (Harman and Albright 2013), 2013 (Harman and Albright 2014) and 2014, Site 1 (see Figure 1 for sites).

272 Site 2 Plant Community 800 Nitellopsis obtusa 700 Myriophyllum spicatum

600 Others 500

400

300

Dry Weight (g/m^2) 200

100

0

Figure 3. Comparison of biomass (g/m2) of starry stonewort (Nitellopsis obtusa), Eurasian milfoil (Myriophyllum spicatum) and other plant species present, 2008 (Harman et al. 2009), 2009 (Harman et al. 2010), 2010 (Harman et al 2011), 2011 (Harman et al. 2012), 2012 (Harman and Albright 2013), 2013 (Harman and Albright 2014) and 2014, Site 2 (see Figure 1 for sites). Site 3 Plant Community 800 Nitellopsis obtusa 700 Myriophyllum spicatum 600 Others 500

400

300

Dry Weight (g/m^2) 200

100

0

Figure 4. Comparison of biomass (g/m2) of starry stonewort (Nitellopsis obtusa), Eurasian milfoil (Myriophyllum spicatum) and other plant species present, 2008 (Harman et al. 2009), 2009 (Harman et al. 2010), 2010 (Harman et al 2011), 2011 (Harman et al. 2012), 2012 (Harman and Albright 2013), 2013 (Harman and Albright 2014) and 2014, Site 3 (see Figure 1 for sites).

273 Site 4 Plant Community 800 Nitellopsis obtusa 700

Myriophyllum spicatum 600 Others 500

400

300

Dry Weight (g/m^2) 200

100

0

Figure 5. Comparison of biomass (g/m2) of starry stonewort (Nitellopsis obtusa), Eurasian milfoil (Myriophyllum spicatum) and other plant species present, 2008 (Harman et al. 2009), 2009 (Harman et al. 2010), 2010 (Harman et al 2011), 2011 (Harman et al. 2012), 2012 (Harman and Albright 2013), 2013 (Harman and Albright 2014) and 2014, Site 4 (see Figure 1 for sites).

Site 5 Plant Community 800 Nitellopsis obtusa 700 Myriophyllum spicatum 600 Others 500

400

300

Dry Weight (g/m^2) 200

100

0

Figure 6. Comparison of biomass (g/m2) of starry stonewort (Nitellopsis obtusa), Eurasian milfoil (Myriophyllum spicatum) and other plant species present, 2008 (Harman et al. 2009), 2009 (Harman et al. 2010), 2010 (Harman et al 2011), 2011 (Harman et al. 2012), 2012 (Harman and Albright 2013), 2013 (Harman and Albright 2014) and 2014, Site 5 (see Figure 1 for sites).

274

Water Quality Analysis

Water quality parameters over summer 2014 were comparable to those of recent years. In the south basin, waters below 8m were essentially anoxic by the first sampling date (4 June). pH was typically between 6.8 and 8.5. Transparency was between 4 and 5 m over the sampling dates. Total phosphorus ranged from 12 to 16 ug/l. Total nitrogen declined from 0.61 mg/l at the surface on 4 June to 0.31 mg/l at the surface on 7 September. By 25 July, nitrate was below detection at the surface.

In the shallower north basin, stratification was evident in the June visit, with bottom waters being intermittently anoxic. pH ranged from 7.0 to 8.5. Transparency ranged from 1.8 to 4 m. Total phosphorus ranged from 14 to 31 ug/l. Total nitrogen was between 0.31 and 0.42 mg/l, and nitrate levels were below detection on all dates sampled.

DISCUSSION

The spread of starry stonewort continued throughout 2014. This was the first year in which this macroalga was documented in the north basin. In June and July, Eurasian milfoil was dominant in the north basin, though in July nearly all of the milfoil collected was dead as a result of the Renovate treatment on the 18th of the month. By 7 September the Eurasian milfoil had decomposed allowing coontail and starry stonewort to dominate the north basin.

Starry stonewort was present at all sites in the south basin on all sampling dates. In July and September it dominated all sites. Eurasian milfoil was practically absent from this basin. The reduction in the diversity of the macrophytic community of both basins is marked. Native species, such as Chara vulgaris, Vallisneria americana, Potamogeton zosteriformes and Elodea Canadensis, that were routinely collected as recently as 2006 (Harman et al. 2007) are now rarely encountered. Similar reductions in plant diversity following the establishment of starry stonewort have been described elsewhere (Pullman and Crawford 2010).

The continued spread of starry stonewort throughout the lake is worrisome. It has become a serious pest- particularly to the native plant community- in many lakes, and in Moraine Lake it continues to become increasingly common and problematic. It is worth noting that starry stonewort forms dense mats just above the bottom; this suppresses native plant growth, but it seems not to have as big of an impact on recreational activities as Eurasian milfoil canopies. We are not aware of proven methods of selective control of this species.

275 REFERENCES

Anon. 1988. Madison County septic system survey. Madison County Planning Department, Wampsville, NY 13163.0

Borman, S., R. Korth, and J. Tempte. 1999. Through the looking glass. A field guide to aquatic plants. Wisconsin Lakes Partnership.

Crow, G. E. and C. B. Hellquist. 2000a. Aquatic and wetland plants of Northeastern North America. V.1. Pteridophytes, gymnosperms, and angiosperms: dicotyledons. The University of Wisconsin Press.

Crow, G. E. and C. B. Hellquist. 2000b. Aquatic and wetland plants of Northeastern North America. V.2. Angiosperms: monocotyledons. The University of Wisconsin Press.

Fuller, R. 1997. Unpublished data. Colgate University, Hamilton, NY 13346.

Harman, W.N. and M.F. Albright. 2014. Aquatic macrophyte management plan facilitation, Lake Moraine, Madison, N.Y. 2013. 46th Ann. Rept. (2013). SUNY Oneonta Bio. Fld. Sta., Oneonta, NY.

Harman, W.N. and M.F. Albright. 2013. Aquatic macrophyte management plan facilitation, Lake Moraine, Madison, N.Y. 2012. 45th Ann. Rept. (2012). SUNY Oneonta Bio. Fld. Sta., Oneonta, NY.

Harman, W.N. and M.F. Albright and O. Zaengle. 2012. Aquatic macrophyte management plan facilitation, Lake Moraine, Madison, N.Y. 2011. Tech. Rept. #30. SUNY Oneonta Bio. Fld. Sta., Oneonta, NY.

Harman, W.N. and M.F. Albright and T.F. Smith. 2011. Aquatic macrophyte management plan facilitation, Lake Moraine, Madison, N.Y. 2010. Tech. Rept. #29. SUNY Oneonta Bio. Fld. Sta., Oneonta, NY. Harman, W.N., M.F. Albright, H.A. Waterfield and M. Rubenstein. 2010. Aquatic macrophyte management plan facilitation, Lake Moraine, Madison, N.Y. 2009. Tech. Rept. #27. SUNY Oneonta Bio. Fld. Sta., Oneonta, NY.

Harman, W.N. and M.F. Albright and L. Zach. 2009. Aquatic macrophyte management plan facilitation, Lake Moraine, Madison, N.Y., 2008. Tech. Rept. #26. SUNY Oneonta Bio. Fld. Sta., Oneonta, NY.

Harman, W. N. and M. F. Albright, and C. M. Snyder. 2008. Aquatic macrophyte management plan facilitation, Lake Moraine, Madison County, NY., 2007 Tech. Rept. #25. SUNY Oneonta Bio. Fld. Sta., Oneonta, NY.

276 Harman, W. N. and M. F. Albright, and A. Scorzafava. 2006. Aquatic macrophyte management plan facilitation, Lake Moraine, Madison County, NY. Tech. Rept. #23. SUNY Oneonta Bio. Fld. Sta., Oneonta NY.

Harman, W. N. and M. F. Albright, P.H. Lord and M. E. Miller. 2002. Aquatic macrophyte management plan facilitation of Lake Moraine, Madison County. Tech. Rept. #13. SUNY Oneonta Bio. Fld. Sta., Oneonta NY.

Harman, W. N. and M. F. Albright, P.H. Lord and M. Miller. 2000. Aquatic macrophyte management plan facilitation of Lake Moraine, Madison County. Tech. Rept. #9. SUNY Oneonta Bio. Fld. Sta., Oneonta NY.

Harman, W. N. and M. F. Albright, P.H. Lord and D. King. 1998. Aquatic macrophyte management plan facilitation of Lake Moraine, Madison County. Tech. Rept. #5. SUNY Oneonta Bio. Fld. Sta., Oneonta NY.

Harman, W. N. and M. F. Albright. 1997. Aquatic macrophyte survey of Lake Moraine, Madison County, summer 1997, as related to management efforts by Sonar ® application. SUNY Oneonta Bio. Fld. Sta., Oneonta NY.

Lembi, C.A. 2000. Aquatic Plant Management. Purdue University, Cooperative Extension Service. West Lafayette, IN 47907.

Lord, P.H. and R.L. Johnson. 2006. Aquatic plant monitoring guidelines. http://www.dec.ny.gov/docs/water_pdf/aquatic06.pdf

NYS Department of Environmental Conservation, Water Division. A Primer on Aquatic Plant Management in NYS. http://www.dec.ny.gov/docs/water_pdf/ch6p2.pdf. 8.12.2009.

Pulman, G.D. and G. Crawford. 2010. A decade of starry stonewort in Michigan. Lakeline, summer 2010. North American Lake Management Society.

277 Control and eradication of water chestnut (Trapa natans, L.) in an Oneonta wetland, 2014 progress report

Holly A. Waterfield1 and Matthew F. Albright2

The marsh of concern is located within the city of Oneonta, Otsego County, NY. The majority of the shoreline (and site access point) is owned by Louis Blasetti with a number of other landowners along the northwestern shoreline behind Oneida Street. Water chestnut (Trapa natans L.) was first observed in the wetland in 2000, though it is likely that it was introduced in years prior but was not documented. A detailed description and history of the management efforts to control and eradicate the water chestnut within the marsh is given in a 2009 Master’s Thesis submitted by W. Eyres (2009) and subsequent report to the NYS Department of Environmental Conservation (Harman et al. 2012). In short, management activities have included a combination of herbicide applications and hand-harvesting of plants since 2006. The combination of chemical and manual control of plants was hugely effective in reducing the population from 2007 to 2010. Native floating-leaved plants were rebounding. Logistical complications resulted in a “missed” herbicide application during the 2010 growing season and subsequent rebound of the population. Following the 2011 herbicide application a second growth of plants was observed in mid-August. These plants were also producing fruits; a major hand-pulling event was held in mid-September of that year, though growth was so prolific that harvest of all plants was not achievable. Grant funding for herbicide application expired in 2011. Efforts in 2012 and 2013 consisted of hand harvesting (2 dates in 2012, 3 dates in 2013); in both years only a few plants, if any, remained following the harvesting effort (Waterfield and Albright 2013; 2014) though some mature nuts may have been dispersed before the final harvest.

Hand-harvest was not possible in 2014 due to a breach of the impounding beaver dam; the water level was very low as compared to the normal condition. Open water was inaccessible, as the exposed bottom substrate was composed of thick organic material and could not be traversed by foot or canoe. Water chestnut plants and nuts from previous years were visible from shore. Some plants were growing in saturated exposed sediments, others in the remaining open water. Abundance comparisons with previous years cannot be made, though the increased water chestnut abundance in 2013 and presence of a viable (and visible) seed bank in 2014 are evidence that hand-harvesting efforts will be necessary for the coming years.

HAND-HARVEST SUMMARY 2011: >12 canoe-loads harvested, with at least 12 remaining at the end of the season 2012: ~1 canoe-load harvested, “none” remaining at the end of the day. 2013: ~23 canoe-loads harvested, with only isolated individuals potentially remaining. 2014: no harvest, many nuts found along the shore.

1 Research Support Specialist: SUNY College at Oneonta Biological Field Station, Cooperstown, NY. 2 Assistant to the Director: SUNY College at Oneonta Biological Field Station, Cooperstown, NY.

278 REFERENCES

Eyres, W. 2009. Water Chestnut (Trapa natans L.) infestation in the Susquehanna River watershed: population assessment, control and effects. Master’s Thesis: SUNY College at Oneonta. Bio. Fld. Sta. OP No. 44.

Harman, W.N., H.A. Waterfield, M.F. Albright. 2012. DEC Invasive Species Eradication and Control Grant FINAL REPORT. In 44th Ann. Rept. (2011). SUNY Oneonta Bio. Fld. Sta., SUNY Oneonta.

Waterfield, H.A., and M.F. Albright. 2014. Control and eradication of water chestnut (Trapa natans, L.) in an Oneonta wetland, 2013 progress report. In 46th Ann. Rept. (2013). SUNY Oneonta Bio. Fld. Sta., SUNY Oneonta.

Waterfield, H.A., and M.F. Albright. 2013. Control and eradication of water chestnut (Trapa natans, L.) in an Oneonta wetland, 2012 progress report. In 45th Ann. Rept. (2012). SUNY Oneonta Bio. Fld. Sta., SUNY Oneonta.

Waterfield, H.A., W.N. Harman, M.F. Albright. 2010. An update on the control and eradication of water chestnut (Trapa natans, L.) in an Oneonta wetland, 2009 summary report of activities. In.42nd Ann. Rept.(2009). SUNY Oneonta Bio. Fld. Sta., SUNY Oneonta.

279 BFS research activities (AY 2014-15)

Kiyoko Yokota1

Effect of microplastics on freshwater algal growth (see Davidson et al. 2015) I carried out with two BFS Summer undergraduate interns, Cody Hastings (Rochester Institute of Technology) and Emily Davidson (SUNY Oneonta) and Holly Waterfield (BFS), to establish an effective protocol to harvest, characterize, and quantify microscopic plastic particles (microplastics) used in personal care products such as face and body washes to be later used in algal culture experiments. We were successful in establishing a generally effective harvest protocol except for one particular face wash product with “busting beads”. Characterization of the microplastics showed that, although the manufacturers often call the plastic particles in their product “microbeads”, those that we observed were mostly irregularly shaped plastic pieces, not perfect spheres. These microplastics were relatively small, with the modal equivalent spherical diameters at ≤ 50 µm for all brands tested, although there were some differences in particle size distributions across brands. A manuscript based on these findings is in preparation. Edward Kwietniewski (Lake Management MS student, SUNY Oneonta) and I are continuing on this project and planning a series of experiments where select freshwater phytoplankters are grown with or without these microplastics, with support from the SUNY Oneonta 2014-15 Faculty Research Grant. We are particularly interested in their effect on colony-forming cyanobacteria, which often lead to harmful algal blooms (HABs) and have significant implications on water resource management. These particles are already found in the Great Lakes, implying that conventional sewage treatment plants are not capable of removing them (Eriksen et al. 2013), and these plastic particles are accumulating in the lakes while watershed residents continue to use them on a regular basis. It is part of the greater issue of plastic pollution in general, where microplastics resulting from fragmentation of larger plastic debris are being discovered all over the globe in an increasing amount (Barnes et al. 2009). Goodyear Lake fish mercury study Colleen Parker and David Snyder, both SUNY Oneonta undergraduates, worked on their independent research project on evaluating mercury bioaccumulation in fish in Goodyear Lake (Otsego County, New York) under my guidance with technical assistance from Florian Reyda (BFS) on fish tissue collection procedures, NYSDEC Region 4 Bureau of Fisheries staff on sampling logistics, and the Driscoll Lab at Syracuse University for quantification of total mercury in the harvested tissues. The data showed elevated levels of total mercury in samples of walleye (Sander vitreus) and smallmouth bass (Micropterus dolomieu), in excess of USFDA’s action level of 1 ppm. The results warrant further monitoring of fish mercury in lakes in the Catskill region, where the last systematic survey was conducted in 2003 (Simonin et al. 2008). The recent data have been added to the statewide database for fish mercury monitoring project. David and Colleen are presenting the results at the 2015 Student Research and Creative Activity

1 Assistant Professor, SUNY Oneonta Biology Department and the Biological Field Station.

280 Day (SUNY Oneonta), and Colleen plans to carry out the regional monitoring project as her MS Biology thesis project at SUNY Oneonta. Other undergraduate research projects I was approached by two SUNY Oneonta undergraduate students in Spring 2014 who wanted to study plankton community in an Alaskan glacial lake in conjunction with their backpacking trip to the area. I searched for relevant literature for them to familiarize themselves to the local aquatic ecosystems before the trip and provided guidance on study design and sampling logistics, but the study did not materialize. William Platt (SUNY Oneonta) is carrying out an independent research project in Spring 2015 to evaluate how different light wavelengths affect photosynthetic efficiencies in several freshwater phytoplankters. He is co-mentored by Sunil Labroo and Jim Michels, both of Physics Department (SUNY Oneonta), and myself. Algal identification During summer and fall 2014, BFS received inquiries from the general public alarmed by algal blooms in water bodies near them. I assisted with identification of an algal bloom sample from Boyd Pond, Jefferson County, NY, that was shipped to BFS after email consultation. That bloom was dominated by the cyanophyte Aphanizomenon flos-aquae Matthew Albright (BFS) and I also responded to a request for assistance from a conservation officer at Gilbert Lake State Park and sampled the lake at the start of an unusual bloom that lead to closing of the swimming beach, followed by taxonomic identification of the blooming species (Planktothrix (formerly Oscillatoria) agardhii).

REFERENCES Barnes, D.K., A. F. Galgani, R.C. Thompson, and M. Barlaz. 2009. Accumulation and fragmentation of plastic debris in global environments. Philosophical Transactions of the Royal Society B: Biological Sciences 364:1985–1998.

Davidson, E., C. Hastings, H. Waterfield and K. Yokota. 2015. Development of methods to characterize & extract plastic microparticles from personal cleansing products. In 47th Ann. Rept. (2015). SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta.

Eriksen, M., S. Mason, S. Wilson, C. Box, A. Zellers, W. Edwards, H. Farley, and S. Amato. 2013. Microplastic pollution in the surface waters of the Laurentian Great Lakes. Marine Pollution Bulletin 77:177–182.

Simonin, H.A., J.J. Loukmas, L.C. Skinner, and K.M. Roy. 2008. Lake variability: Key factors controlling mercury concentrations in New York State fish. Environmental Pollution 154:107–115.

281 Interpretation of isopleth graphs. From: Albright, M.F. and H.A. Waterfield. 2012. The state of Canadarago Lake, 2011. Tech. Report #30. SUNY Oneonta Biol. Fld. Sta., SUNY Oneonta.

Figure is a graph showing thermal (temperature) isopleths (lines of equal temperature) throughout the year. The X-axis (horizontal) denotes time from January 2010 through December 2010. The dots along the X-axis indicate the dates when measurements were taken in the field. The Y-axis (vertical) shows depth in meters. Overall, the figure illustrates lake temperature over the course of one calendar year and is useful in identifying the general stratification pattern (development of thermal layers) and when compared to graphs for other years, variations in that pattern between years. Differences in patterns between lakes can also be discerned by comparing this type of figure. One can also use the graph to obtain information on lake conditions for a particular date. For example, we can estimate the temperature at various depths for15 July first by drawing a line vertically from top to bottom starting mid-way between July and August (line A). Where this line crosses a temperature isopleth, you can draw a horizontal line to find the depth at which that temperature occurred (lines B, C, D, and E); therefore, at about 3.8 meters depth (line B), the temperature was about 24oC. Shallower it was warmer, in deeper water is was colder. Just above 6 meters (line C), the temperature was 22oC; just deeper than 6 meters (line D), the temperature was 20oC. Just below 8 meters, the temperature was 15oC. Using this method, you can approximate the temperature at any depth for any day of the year. With enough samples or measured values, we can draw isopleths for oxygen concentrations, chlorophyll a concentration, or any other water quality characteristics that we have measured.

Thermal isopleths of Canadarago Lake, 2010, as an example of how to interpret the data contained therein (see text above).