Integrated Belowground Greenhouse Gas Flux Measurements and Modeling, Howland Forest ME

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Integrated Belowground Greenhouse Gas Flux Measurements and Modeling, Howland Forest ME.Kathleen Savage, Debjani Sihi, Eric A. Davidson, David Hollinger, Andrew Richardson, Julie Shoemaker

First, I would like to acknowledge my co-authors. I am going to present a novel integration of measurements and modeling of CO2, CH4, and N2O fluxes, three key GHGs from a forested wetland. We are studying GHG emissions from Howland forest in central Maine. Howland serves as a close proxy for many boreal landscapes (these northern systems are expected to experience maximum effect of climate change) where upland forests are interspersed with wetlands, resulting in a complex mosaic of both sources and sinks of important GHGs that are influenced by climate change. 1

HowlandHowland Forest, ME

Owned by New England Wilderness Trust(NEWT)

558 acre parcel

Temperate boreal transitional forest

Mature- hemlock, spruce and cedar

Continuous NEE and soil respiration measurements since 1996, oneof the longest records

Recently added net CH4 exchange

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Howland Forest EMS tower

NEE and CH4 measurements

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Automated GHG chambers 2004-2016

wetlandtransitionalupland

GHG sampling system

Partnership in Education Program (PEP) students

Erica ValdezSpatial Heterogeneity of Greenhouse Gases at Howland Forest (presented at AGU 2015)

Liomari DiazMeasuring the Spatial Distribution of Soil Carbon at the Howland Forest (attended SSSA 2016)

Introduction to Greenhouse Gases

Soils are a significant source of carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O) - the most important greenhouse gases (GHG)

Carbon dioxide: Soils release CO2 produced by both autotrophic (root) and heterotrophic (microbial) respiration processes (aerobic).

Methane: Wetlands are a significant natural source of CH4 (anaerobic), and dry upland soils (aerobic) a natural CH4 sink.

Nitrous Oxide: Soils are the dominant natural source of N2O, and have been shown to be a small sink under N-limited conditions. The production and consumption of N2O is also highly dependent on spatial and temporal variation in soil moisture.

Variation in soil moisture can be very dynamic, and it is one of the dominant factors controlling soil aeration, and hence the balance between aerobic and anaerobic processes.

Objective:

To improve understanding of and modeling capacity for interactions of belowground temperature, moisture, and substrate supply that control the net soil emissions of the three most important GHGs: CO2 , CH4 , and N2O.

Most biogeochemical models generally simulate CO2, CH4, and N2O emission separately mainly by tweaking model parameters to fit data for one of these gases as it remains challenging to explain mechanistically and to simulate numerically these dynamics.

GHG fluxes are often linked through heterotrophic dependence on fixed C sources for energy, and the same soil profile may alternate between being a net source or sink for CH4 and N2O depending on the concentration of O2 at microbial microsites.

O2 plays a contrasting role a potential substrate or an inhibitor for these GHG production and consumption.

Emissions of multiple GHGs can be simultaneously simulated using a parsimonious modular framework for estimating the consumption of soil C and O2 and for diffusion of gases through the soil profile-basic structure of the DAMM model

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(Davidson et al., 2002)

Howland Forest, ME is a mosaic of well drained upland, wetland and small transitional upland/wetland soils which makes for a unique and challenging environment to measure the effects of soil moisture and hence O2 on the net exchange of these important greenhouse gases.

Dual Arrhenius and Michaelis-Menten (DAMM)

Arrhenius function

DAMM model based on process concepts that link equations to combine the effects of temperature, water content and soluble substrate supply on heterotrophic respiration.Basis is the Michaelis-Menten equation- describes the relationship between the reactions velocity (Vmax) and soluble substrate in this case C and O2 at the reactive enzyme site. Temperature sensitivity of this processes is added to this model by allowing Vmax to vary according the an Arrhenius function

The concentrations of both soluble organic-C and O2 at the simulated reaction site are determined by diffusivity functions, which, in turn, are simulated as functions of soil water content.

The parameters of the Arrhenius, MichaelisMenten, and diffusivity equations must still be calibrated to observed responses for accurate simulation of a specic system, but the mathematical functions representing the interactions of temperature, water content, and substrate supply are based on a mechanistic understanding of these interactions.

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Soluble carbon (Sx) can be used as a proxy for the reducing power needed for either acetate or hydrogen substrates of two methanogenic pathways. 11

An example of the change in headspace [N2O] over time from closure to end of flux calculation period. Flux calculation period is from time 60 to 300. (Flux is -1.2 g N m-2 hr-1 , 95% confidence 0.03 g N m-2 hr-1, R2 = 0.93).

CO2LiCor IRGACH4, N2O & H2OAerodyne Quantum Cascade LaserpumpAutomated Chamber System

Deployed in wetland, transitional and upland soils

Newly developing laser technology- high frequency, highly accurate CO2, CH4, N2O and H2O gas concentration

2 hour sampling frequency

15 minutes per chamber

Gas sampling frequency 1 Hz

Soil temperature, soil moisture, %O2

Automated chambers have been installed since 2011 that measure soil fluxes along anaerobic to aerobic gradients.

With the advent of new laser technology, we have included real-time soil CH4 and N2O flux measurements, using an Aerodyne quantum cascade laser (QCL) integrated with soil CO2 flux measurements by LiCor IRGA assembly.

We are using our observations of soil fluxes of these multiple GHGs to develop and validate a merged model.13

Initially developed and tested these modules on 2011 data collected at a wetland/transitional site at Howland forest.

GHG models were parameterized using fluxes, temperature and moisture.

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R2=0.65p