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Impacts of leaf phenology and water table on interannual variability of carbon fluxes in subboreal uplands and wetlands. Implications for regional fluxes in the upper Midwest USA. Ankur R Desai, Benjamin N Sulman University of Wisconsin-Madison D. Scott Mackay

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Impacts of leaf phenology and water table on interannual variability of carbon fluxes in subboreal uplands and wetlands

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Impacts of leaf phenology and water table on interannual variability of carbon fluxes in subboreal uplands and wetlands

Impacts of leaf phenology and water table on interannual variability of carbon fluxes in subboreal uplands and wetlands

Implications for regional fluxes in the upper Midwest USA

Ankur R Desai, Benjamin N Sulman

University of Wisconsin-Madison

D. Scott Mackay

State University of New York-Buffalo

Ameriflux/ChEAS PIs

Ameriflux Meeting 2008


Motivation

Motivation

  • Interannual variation (IAV) in carbon fluxes from land to atmosphere is significant at most flux sites

  • Key to understanding how climate affects ecosystems comes from modeling IAV

  • IAV (years-decade) is currently poorly modeled, while hourly, seasonal, and even successional (century) are better


Predicting nee ricciuto et al

Predicting NEE (Ricciuto et al)


Climate drivers of carbon flux

Climate Drivers of Carbon Flux

  • Temperature

  • Precipitation

  • Radiation

  • [CO2]


Climate drivers of carbon flux1

Interannual

^

Climate Drivers of Carbon Flux

  • Temperature-> Phenology

  • Precipitation-> Drought

  • Radiation -> Light Quality

  • [CO2] -> Acclimation


Interannual nee at cheas

Interannual NEE at ChEAS


Questions

Questions

  • What controls IAV of NEE in subboreal uplands?

    • Hypothesis: Phenology -> Growing season start, end, or length affects GPP

    • Piao et al (2008) -> Autumn warming and Rh

  • What controls IAV of NEE in subboreal wetlands?

    • Hypothesis: Phenology + Water table affects ER

    • Ise et al (2008) -> Decomposition and moisture

  • What controls IAV of regional NEE in subboreal North America?

  • Can a very simple model be constructed to explain IAV?

    • Can we make do a parameter opimization more attuned to IAV?

    • Hypothesis: MCMC overfits to hourly data


Optimization

Optimization

HOURLY

IAV


Phenology

Phenology

  • Five sites with 5-8 years of data

    • 1 regional (LEF), 1 wetland (LCR), 3 uplands (SYL, UMB, WCR)

    • Assimilate 1st 4 years of data


Phenology model

Phenology Model

  • Twice daily model, annually resetting pools

  • Driven by PAR, Air and Soil T, VPD

  • LUE based GPP model f(PAR,T,VPD)

  • Three respiration pools f(Air T, Soil T, GPP)

  • Model 1. NOLEAF

    • Constant leaf on and leaf off days

  • Model 2. LEAF (Phenology)

    • Sigmoidal Threshold GDD (base 10) function for leaf on

    • Sigmoidal Threshold Daily Mean Soil Temp function for leaf off

  • 17 parameters, 3 are fixed

    • Output: NEE, ER, GPP, LAI


Hourly

Hourly

HOURLY NOLEAF

HOURLY LEAF

IAV NOLEAF

IAV LEAF


Interannual

Interannual

HOURLY NOLEAF

HOURLY LEAF

IAV NOLEAF

IAV LEAF


Nee leaf

NEE-Leaf


Gpp er leaf

GPP ER Leaf


Precipitation and water table

Precipitation and Water Table

  • Sulman et al (in prep) Biogeosciences - see Ameriflux poster


Shrub wetland flux response

Shrub Wetland Flux Response


Three wetlands

Three Wetlands


Three wetlands1

Three Wetlands


Regional nee

Regional NEE

  • See NACP poster in Feb.


Conclusions

Conclusions

  • Autumn soil temperature appears to be a major control on interannual variability in subboreal upper Midwest USA flux tower site annual NEE

    • Due mainly to effect of growing season length for GPP

    • Only detectable using a modified MCMC cost function that penalizes for poor fit to cumulative annual NEE

  • Additionally, growing season average water table strongly affects ER in wetlands

    • GPP effect in both uplands and wetlands -> related to precipitation deficits?

  • Regional NEE is messy

  • Thanks: DOE NICCR, DOE TCP, NASA CC, NOAA CPO, USDA/USFS NRS, NSF, UW Foundation, ChEAS


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