Landscape-level terrestrial methane flux observed from a very tall towerAgricultural and Forest Meteorology

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Authors
Ankur R. Desai, Ke Xu, Hanqin Tian, Peter Weishampel, Jonathan Thom, Dan Baumann, Arlyn E. Andrews, Bruce D. Cook, Jennifer Y. King, Randall Kolka
Year
2015
DOI
10.1016/j.agrformet.2014.10.017
Subject
Agronomy and Crop Science / Forestry / Atmospheric Science / Global and Planetary Change

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Agricultural and Forest Meteorology 201 (2015) 61–75

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Landsc ve tower

Ankur R. Desai , Ke Xu , Hanqin Tian , Peter Weishampelc, Jonathan Thom ,

Dan Baumannd, Arlyn E. Andrewse, Bruce D. Cookf, Jennifer Y. Kingg, Randall Kolkah a Center for Climatic Research, University of Wisconsin-Madison, Madison, WI, USA b International Center for Climate and Global Change Research, Auburn University, Auburn, AL, USA c Great Lakes Domain, National Ecological Observatory Network, Inc., Land O Lakes, WI, USA d Wisconsin Water Science Center, U.S. Geological Survey, Rhinelander, WI, USA e Earth Systems f Goddard Spac g Department o h USDA Forest S a r t i c l

Article history:

Received 9 Ma

Received in re

Accepted 14 O

Keywords:

Methane

Eddy covarian

Regional flux

Land–atmosph 1. Introdu

The con remains a s ∗ Correspon

E-mail add http://dx.doi.o 0168-1923/© Research Lab, National Oceanographic and Atmospheric Administration, Boulder, CO, USA e Flight Center, National Aeronautics and Space Administration, Greenbelt, MD, USA f Geography, University of California, Santa Barbara, CA, USA ervice Northern Research Station, Grand Rapids, MN, USA e i n f o y 2014 vised form 29 August 2014 ctober 2014 ce ere a b s t r a c t

Simulating the magnitude and variability of terrestrial methane sources and sinks poses a challenge to ecosystem models because the biophysical and biogeochemical processes that lead to methane emissions from terrestrial and freshwater ecosystems are, by their nature, episodic and spatially disjunct. As a consequence, model predictions of regional methane emissions based on field campaigns from short eddy covariance towers or static chambers have large uncertainties, because measurements focused on a particular known source of methane emission will be biased compared to regional estimates with regards to magnitude, spatial scale, or frequency of these emissions. Given the relatively large importance of predicting future terrestrial methane fluxes for constraining future atmospheric methane growth rates, a clear need exists to reduce spatiotemporal uncertainties. In 2010, an Ameriflux tower (US-PFa) near Park

Falls, WI, USA, was instrumented with closed-path methane flux measurements at 122 m above ground in a mixed wetland–upland landscape representative of the Great Lakes region. Two years of flux observations revealed an average annual methane (CH4) efflux of 785 ± 75 mg C CH4 m−2 yr−1, compared to a mean CO2 sink of −80 g C CO2 m−2 yr−1, a ratio of 1% in magnitude on a mole basis. Interannual variability in methane flux was 30% of the mean flux and driven by suppression of methane emissions during dry conditions in late summer 2012. Though relatively small, the magnitude of the methane source from the very tall tower measurements was mostly within the range previously measured using static chambers at nearby wetlands, but larger than a simple scaling of those fluxes to the tower footprint. Seasonal patterns in methane fluxes were similar to those simulated in the Dynamic Land Ecosystem Model (DLEM), but magnitude depends on model parameterization and input data, especially regarding wetland extent.

The model was unable to simulate short-term (sub-weekly) variability. Temperature was found to be a stronger driver of regional CH4 flux than moisture availability or net ecosystem production at the daily to monthly scale. Taken together, these results emphasize the multi-timescale dependence of drivers of regional methane flux and the importance of long, continuous time series for their characterization. © 2014 Elsevier B.V. All rights reserved. ction tribution of microbial methane (CH4) from wetlands ignificant source of uncertainty in closing the global ding author. Tel: +1 608 520 0305; fax: +1 608 262 0166. ress: desai@aos.wisc.edu (A.R. Desai). methane budget (Mikaloff Fletcher et al., 2004). In particular, wetland methane emissions may contribute as much as 25–40% of global CH4 anthropogenic emissions and are the leading source of interannual variability in atmospheric CH4 (Bousquet et al., 2006; Chen and Prinn, 2006; Crill et al., 1993). The recent increase in the growth rate of atmospheric CH4 lends particular urgency to improving global simulations and inversions of the terrestrial methane source (Chen and Prinn, 2006; Collins et al., 2006). One rg/10.1016/j.agrformet.2014.10.017 2014 Elsevier B.V. All rights reserved.ape-level terrestrial methane flux obser a,∗ a blocate /agr formet d from a very tall a 62 A.R. Desai et al. / Agricultural and Forest Meteorology 201 (2015) 61–75 set of hypothesized mechanisms is the role of warming of high latitudes and wetting of the tropics (Dlugokencky et al., 2009). Because

CH4 emissions are closely linked to changes in regional hydrology and temperature, and ongoing climate changes are likely to have a signi temperatur affect wetla 2009).

Model r vations of all in situ m been condu based meas recently at ance flux to tracer-trans et al., 2013 1987; Tang based estim vided at mu arises for ev ularly diffic of CH4 sour sources (e.g

The prim tall tower c in a regiona variability o observation a very tall to 122 m abov ling a spati wetland sys eddy fluxes

Since t spectroscop 1995; Kim 1996), ther on short-te

Hargreaves ment of reli (McDermitt series of CH

Olson et al., 2008). Non scape scale of these stu measureme

The valu directly obs neous emis fluxes. Only capture (or ing ebullitio non-growin et al., 2007;

We seek net ecosyst expect that

CH4 consum

CH4 flux wo mean flux a els simulate either ecosy annual time we ask: eneralized land cover surrounding the WLEF Park Falls very tall tower cross) in a 10 km radius derived from manual classification of 30 m spalution Quickbird imagery (B.D. Cook, unpublished data). “Other” category y includes grassy areas, lakes, and streams. Wetlands are patchy and equally ted in all directions from tower. Footprint climatology overlaid as a mask, ighter areas show >0.5% contribution to the May–Sept 2011 total hourly flux influence, revealing a typical footprint diameter of 5 km. t is the magnitude of NEE CH4 in a mixed forest–wetland scape and how does it compare to site-level chamber-based ates? predictive are environmental factors such as water table and erature or other biogeochemical fluxes such as Reco CH2 or