1. Phosphorus-nitrogen feedbacks maintain balanced availability in hardwood forest soils Tera Ratliff 11-July-2012

2. Time (millions of years)Total Soil Nutrients Walker and Syers, 1976 US Forest Service Identifying the processes underlying limitations to productivity help us understand forest ecosystem response to change

3. Resource Optimization High C:N:P High N:P P-limiting Investment in phosphatse N:P Low N:P N-limiting Investment in decomposition N:P Low C:N:P C-limiting Investment in C-mineralizing enzymes C:N:P

4. Resource optimization in response to N and P fertilization When N is high, organisms allocate to P Do N and P equilibrate over the long-term? Marklein and Houlton, 2011 Response Ratio = Mean outcome of treatment: mean outcome of control

5. Pretreatment (2008 to 2009) soil collection MELNHE plots Cores divided into Oe and Oa Resin strips buried in-situ (2010) C9 -1-A PO 4 -

6. N and P availability covary in forests of varying ages in the northern hardwoods N availability appears to promote P availability via phosphatase production.

7. Conclusions Tight coupling of N and P could contribute to colimitation at the ecosystem level Resource optimization could work to prevent P- limitation in the short-term by increasing investment when N is high Mechanisms of P redistribution from slowly available pools are of interest for understanding long-term effects of anthropogenic changes in N and P availability

8. Questions? Acknowledgments Many people have helped in carrying out this project, so many thanks to Kevan Minick, Mark Dempsey, Brittany Coyne, Stephanie Bailey, Carrie Rose Levine, members of the Fisk Lab, and collaborators at HBEF for assistance in the field and laboratory.

9. The grass is always greener (than the forest): is it the N? Hannah Tremblay Carleton College, 2014

10. Background Fertilization and fossil fuels have more than doubled amount of available N in biosphere Expansion of suburbs is one of the fastest growing land uses Recent evidence suggests that urban soils may be a sink for atmospheric N (Raciti et al. 2008)

11. The experiment To quantify the differences in total soil nitrogen, available nitrate, and nitrification rates between residential lawns and forested areas in northern New Hampshire. How does the land use shift from forests to lawns affect nitrification and mineralization rates?

12. Methods: site selection 12 clusters 58 sites Personal interview and questionnaire

13. Methods: In the field 5 volumetric, 5.8cm diameter, 15cm deep cores from lawns and adjacent forests Vegetative cover and tree inventory recorded Measured area of property

14. Methods: In the lab Soil sieved and homogenized Two 20 gram subsamples ▫“Time 0” extraction: placed in a 250 ml Nalgene bottle with 100ml of 2M KCl. Settled for 24 hours. ▫“Time final” extraction: incubated for 21 days in a 1 pint mason jar and fanned every 3 days. Soil samples filtered and analyzed

15. Methods: In the lab

16. Results P-value <.05

17. Moving forward Nitrification and mineralization rates Investigation of historical land use Relationship with vegetation Demographic information

18. Thank you Craig See Adam Wild Clarissa Lyons Austin McDonald Shinjini Goswami Russell Auwae Ruth Yanai Melany Fisk Tim Fahey Paul Lilly Peter Groffman Paige Warren Matt Vadeboncoeur

19. References Raciti SM, Groffman PM, Fahey TJ. 2008. Nitrogen retention in urban lawns and forests. Ecol Appl 18(7):1615–26.

20. The Bartlett Baby Boom: An Inventory of Germinants Following a Mast Year Alani Grace Grant New York University 2012

21. MOTIVATION Over the last three decades, sugar maple has declined in the northern hardwood forests At the same time, American beech has increased Hane (2003) has linked sugar maple decline to an increase of understory beech due to BBD

22. HYPOTHESES There will be a greater amount of beech germinants than sugar maple germinants present in older stands Sugar maple decline is related to increased presence of beech saplings Beech Bark Disease positively influences mast seed production

23. Acer saccharum Fagus grandifolia Photographs courtesy of Matt Vadeboncoeur

24. Total Germinant Species Composition

25. Germinant Abundance Correlates with Adult Abundance in Sugar Maple and Beech

26. Stands with Greater BBD have Greater Germinant Abundant

27. Lower Sugar Maple Germinant Abundance in Stands With More Beech Saplings

28. Next Steps Revisit sites and count surviving germinants Compare survival by species Examine effect of fertilizer on germinant survival

29. Ruth Yanai – SUNY-ESF Shinjini Goswami – Miami University Matt Vadeboncoeur – UNH Kikang Bae – SUNY-ESF Shoestring Summer Crew Members

30. Selected References DiGregorio, L; Krasny, M; Fahey, T. (1999). Radial Growth Trends of Sugar Maple (Acer saccharum) in an Allegheny Northern Hardwood Forest Affected by Beech Bark Disease. Journal of the Torrey Botanical Society, 245-254. Hane, E. (2002). Indirect effects of beech bark disease on sugar maple seedling survival. Canadian Journal of Forest Research, 807-813. Horsley, S; Long, R; Bailey, S; Hallett, R; Wargo, P. (2002). Health of Eastern North American Sugar Maple Forests and Factors Affecting Decline. Northern Journal of Applied Forestry, 34-44. Juice, S; Fahey, T; Siccama, T; Denny, E; Eagar, C et al. (2006). Response of sugar maple to calcium addition to northern hardwood FOREST. Ecology, 1267-1280. United States Department of Agriculture. (1990). Silvics of North America. Washington,, D.C.: U.S. Department of Agriculture.

31. QUANTIFYING UNCERTAINTY IN ECOSYSTEM STUDIES Ruth Yanai, Carrie Rose Levine, Craig See (SUNY-ESF) John Campbell, Mark Green (USFS and PSU) Amey Bailey, Stephanie Laseter (USFS)

32. 20 collectors across SEV from 1989-1995 Solutes: NO3, NH4, SO4, Cl, Na, K, Ca, Mg, and PO4 Collections monthly or after heavy rains Gaps in the Precipitation Record at Sevilleta

34. Gaps in the Streamflow Record Hubbard Brook Coweeta

35. Gaps in the Streamflow Record (days) Hubbard Brook Coweeta

36. Uncertainty in change over time in sulfate in atmospheric deposition in NY as a function of sampling intensity (21 stations = 100%)

37. Uncertainty in change over time in Adirondack lake nitrate as a function of sampling intensity (50 lakes monthly = 100%)

38. Uncertainty in Forest Biomass in W6 as a function of the number of plots sampled

39. Uncertainty in Change over Time in Forest Biomass in W6

40. Variation over space and time in stream loads at Hubbard Brook, Coweeta, and Wakayama (Japan)