phosphorus-nitrogen feedbacks maintain balanced availability in hardwood forest soils

Phosphorus-nitrogen feedbacks maintain balanced availability in hardwood forest

soils Tera Ratliff

11-July-2012

Time (millions of years)

Tota

l Soi

l Nut

rient

s Walker and Syers, 1976

US Forest Service

Identifying the processes underlying limitations to productivity help us understand forest ecosystem response to change

Resource Optimization

High C:N:P

High N:PP-limiting

Investment in phosphatse

N:P

Low N:PN-limiting

Investment in decomposition

N:P

Low C:N:PC-limiting

Investment in C-mineralizing

enzymes

C:N:P

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

• Pretreatment (2008 to 2009) soil collection MELNHE plots

• Cores divided into Oe and Oa

• Resin strips buried in-situ (2010)

C9 -1-A

PO4-

• N and P availability covary in forests of varying ages in the northern hardwoods

• N availability appears to promote P availability via phosphatase production.

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

Questions?

AcknowledgmentsMany 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.

The grass is always greener (than the forest): is it the N?

Hannah TremblayCarleton College, 2014

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)

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?

Methods: site selection

•12 clusters•58 sites•Personal

interview and questionnaire

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

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

Methods: In the lab

Results

P-value < .05

Moving forward

•Nitrification and mineralization rates

•Investigation of historical land use

•Relationship with vegetation

•Demographic information

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

References

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

The Bartlett Baby Boom: An Inventory of Germinants Following a Mast Year

Alani Grace GrantNew York University 2012

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

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

Acer saccharum

Fagus grandifolia

Photographs courtesy of Matt Vadeboncoeur

Total Germinant Species Composition

Germinant Abundance Correlates with Adult Abundance in Sugar Maple and Beech

Stands with Greater BBD have Greater Germinant Abundant

Lower Sugar Maple Germinant Abundance in Stands With More Beech Saplings

Next Steps

• Revisit sites and count surviving germinants

• Compare survival by species

• Examine effect of fertilizer on germinant survival

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

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.

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)

20 collectors across SEV from 1989-1995Solutes: NO3, NH4, SO4, Cl, Na, K, Ca,

Mg, and PO4Collections monthly or after heavy rains

Gaps in the Precipitation Record at Sevilleta

Gaps in the Streamflow Record

Hubbard Brook Coweeta

Gaps in the Streamflow Record(days)

Hubbard Brook Coweeta

Uncertainty in change over time in sulfate in atmospheric deposition in NY as a function of

sampling intensity (21 stations = 100%)

Uncertainty in change over time in Adirondack lake nitrate

as a function of sampling intensity (50 lakes monthly = 100%)

Uncertainty in Forest Biomass in W6

as a function of the number of plots sampled

Uncertainty in Change over Timein Forest Biomass in W6

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