Carbonyl sulfide (COS) measurements are one of the emerging tools to
better quantify gross primary production (GPP), the largest flux in
the global carbon cycle. COS is a gas with a similar structure to
As anthropogenic
To date only three published studies have attempted to use COS
concentrations to calculate GPP over individual ecosystems (Asaf
et al., 2013; Billesbach et al., 2014; Blonquist et al., 2011). The
calculation is performed using this relationship:
Many of the plant physiological requirements involved in using COS
fluxes as a GPP proxy have been empirically investigated.
Stimler et al. (2010) confirmed the assumptions about in-leaf
processes and COS–
However, a problem arises when the
Soils in terrestrial biomes usually exhibit low COS exchanges compared to uptake by plants (see review in Whelan et al., 2013). Uncoordinated, individual studies have been undertaken that incidentally quantified soil COS exchange in a limited number of biomes, often with few soil-focused measurements.
The characterization of soil COS exchange should improve the use of COS observations as a GPP proxy. Here, to better understand soil COS exchange, we collected soil samples from multiple biomes and assessed their COS fluxes in a controlled setting using dynamic incubation chambers. We further develop a framework for interpreting and anticipating soil COS fluxes based on empirical data and gas exchange theory. This model can inform the design of much needed future field experiments.
Site descriptions for soils used in this study and soils from the site used in Billesbach et al. (2014) and Maseyk et al. (2014). Site descriptions for the FLUXNET sites can be found in Meyers and Hollinger (2004), Anderson and Goulden (2011), and Cook et al. (2004). The temperature and soil moisture ranges are the maximum and minimum of 10 years' worth of hourly data from the Climate Forecast System Reanalysis (CFSRv2; Saha et al., 2010).
Soil samples were acquired from agricultural, forest, desert, and
savannah sites (Table 1) with a variety of patterns in soil
moisture and temperature (Fig. 1). Except for the Peruvian
rainforest sample, soil collection followed the same
protocol. First, two 0.0225
Sites were selected to capture variability between biomes and address data needs. The Bondville site is an agricultural research station that was rotated between soybean and corn crops; at the time of sampling, soybeans were planted, but soil contained corn litter. The Stunt Ranch FLUXNET site, an oak savannah, and the Boyd Deep Canyon Reserve, to our knowledge the first desert soil investigated for COS exchange, are both located within and managed by the University of California Reserve System. The Willow Creek mature forest, Bondville FLUXNET, and Southern Great Plains ARM sites are within the footprints of COS air-monitoring sites that include tall tower and airborne platforms (Montzka et al., 2007). Soil temperature and soil moisture variability for all sites are presented in Fig. 1.
The normalized concurrence of soil moisture and 5
The experimental chambers were solid PFA 1 L jars and threaded solid PFA lids
with two ports (Savillex, Eden Prairie, MN, USA). PTFE tape was used to
achieve an airtight seal on the threads. The outlet port was attached to PFA
tubing extending into the middle of the chamber. Soil subsamples were placed
in individual chambers and weighed. Following Van Diest and
Kesselmeier (2008), 75 to 80
Locations of soil collection sites. The Southern Great Plains site is referred to in the discussion as the site used in Billesbach et al. (2014) and Maseyk et al. (2014), but was not used in these soil incubation experiments. For site descriptions, see Table 1.
The experimental setup for laboratory-based soil incubation
experiments. The Nafion tubing was placed in a container of water and used to
humidify the incoming gas stream. Three-way valves were used to switch between
analyzing a nitrogen stream, the gas stream that flowed through the chamber
(
Soil fluxes of COS were determined using a dynamic, flow-through
chamber approach. A commercially available Aerodyne quantum cascade
laser (QCL, Aerodyne Research, Inc., Billerica, MA, US) was used to
quantify COS and
Each
The temperature of the chamber was manipulated from 10 to
40
To explore the sensitivity of COS uptake to chamber COS mole fractions, we
performed a series of incubations with a freshly collected soil sample from
near the original soy field site. The soil sample was air-dried to
approximately 2 % VWC then incubated with ambient sweep air and COS-free
zero air, which contained 300
Performing soil incubation experiments allowed for precise manipulation of environmental variables to reveal underlying patterns in soil COS exchange. Soil in situ has an important dimension not represented by these laboratory experiments: depth (Ogee et al., 2015; Sun et al., 2015). Data from this study could represent COS exchange from only the top layer of soil. Nonetheless, it would be enlightening to compare controlled experiments to data collected in the field.
A further experiment was performed to estimate the relationship
between laboratory, per-gram measurements and field, per-area
measurements. Soy field soil was gradually added to
a 20
The total net COS flux observed from the soils is thought to be the
combination of abiotic and biotic fluxes.
To explain
Ecosystem COS flux,
The first method sought to calculate temporal variability in the
relative importance of
Secondly, we examined the spatial importance of reported
Net COS exchange over temperature from a soil sample taken near the
original soy field site: fluxes observed under ambient sweep air and COS-free
sweep air conditions with exponential least-squares regression lines
With the exception of the soy field sample, soils investigated
here exhibited net COS exchange rates much lower than anticipated leaf COS uptake, ranging
from
Altering the mixing ratio of COS in the chamber sweep air had a strong effect on COS exchange with a soy field soil sample. The slopes of the linear regression lines in Fig. 4b represent the change in COS flux of the soil sample divided by the change in ambient COS. The slopes are all negative and become strictly steeper as temperature increases. Under ambient and zero air treatments, the soil sample showed exponentially higher net COS emissions with temperature. Apparent uptake increased with more available COS in the headspace. The linear regression intercepts in Fig. 4b and graphed separately in Fig. 5b represent the theoretical flux we would expect if there were no COS in the chamber at all. This soil sample exhibited net emissions of COS at all temperatures; therefore, the headspace always contained some small amount.
The COS mixing ratios observed in laboratory air during the entire course of
experiments was
Slopes
Overall, desert and rainforest samples had the smallest magnitude
net COS exchange rates. The temperate forest samples showed the
largest net uptake during the first trials, when the soil sample
was at field soil moisture, 41 % VWC. Of the small fluxes
presented in Fig. 6, temperate forest soils also had the largest
net production when the soil sample was in its hottest and driest
state (Fig. 6b, 38
COS fluxes tended towards more positive fluxes with hotter temperatures (Figs. 6
and 7). Soils incubated at 40
The temperate forest showed the highest
The soybean agricultural soil incubations yielded net COS emissions
for the majority of trials, with a larger range than the other
soils investigated:
COS net exchange from a soy field soil. For one series of observations, the sand-sized fraction (represented by stars) was removed from a sample by wet sieving, then incubated as before.
Soil COS fluxes had a more complicated relationship with soil moisture. When soil samples were waterlogged, net COS exchange shifted towards zero compared to drier trials. For the most part, drier soils have net emissions of COS, except in the case of the varied fluxes from the oak savannah soil (Figs. 6 and 7). In oak savannah soil, increases in soil moisture led to increases in COS uptake. When soil moisture was increased further to near 40 % VWC, COS exchange returned to near zero. The savannah site was expected to experience this range of soil moisture (Fig. 1). In contrast, where dry rainforest soil experienced an increase in net COS production, rainforest soil rarely experiences near-zero soil moisture (Fig. 1). Increasing water content to field levels, the rainforest soil COS exchange returned to near zero. This does not take into account the fluctuations in soil moisture and redox potential experienced in a rainforest in situ. Temperate forest soils appear to experience net COS uptake except under very dry or unusually hot conditions (Fig. 6b).
To observe changes in COS fluxes during changes in soil moisture (i.e., as would happen in situ via precipitation), COS exchange was recorded for at least 12 h after soil moisture was changed during the course of the experiment (Fig. 8). The rainforest and savannah fluxes showed no discernible pattern in fluxes after water additions. For one series of observations with rainforest soil, the Nafion tubing was removed and the soil dried slowly over time, continuing to show little variability. In contrast, the temperate forest and soy field soils (Fig. 8a) responded with a large variability in COS fluxes after soil moisture manipulation, taking several hours to reach a consistent flux value. There was an overall negative relationship between soil moisture and net COS production for the soy field soil samples, but the link between soil moisture and COS fluxes for soils collected at other sites is not as clear.
COS flux observations at 20
To test whether the COS mixing ratio controls the variation seen in Fig. 8,
we examined the mixing ratio of COS exiting the chamber versus COS exchange
(Fig. 9), and we find that no clear relationship emerges. Additionally, high COS
production does not appear to obscure the relationship between COS ambient
mixing ratios and COS uptake. As a thought exercise to demonstrate this, we
estimated the COS production component of soil fluxes and subtracted it from
the net fluxes depicted in Fig. 9, shown in Fig. 10. When soils were
air-dried then incubated, a net COS emission was observed with a positive
relationship to temperature ranging from 10 to 40
The mixing ratio of COS exiting the incubation chamber versus COS
fluxes after water addition at 20
COS fluxes change over time after a change in soil water
content was not consistent for given changes in soil
moisture. However, when water was added to dry soil (
Net COS fluxes were a balance of abiotic and biotic processes. If
we assume that incubations of air-dried agricultural soils were representative
of an abiotic COS production or desorption (less some physical
limitations), we can calculate the relationship between abiotic
COS production and temperature for agricultural soil (plotted in
Fig. 13a). We fitted Eq. (4) to the data scaled as described in Sect. 2.2 and using a least-squares
approach, much like in Maseyk et al. (2014).
The resulting Eq. (7) had an
Soil COS mole fractions and soil COS flux after water addition at
20
Fitting parameters for air-dried soils versus temperature, found by least-squares regression curve fitting to Eq. (4).
Subtracting the dry soy field soil signal component from all other COS
incubation results, we found the biotic and physically limited flux
component (Fig. 13b). The COS incubation observations had been converted
to
Using this framework of equations, we estimate the influence of large soil COS fluxes on GPP estimates. We used data reported for the Bondville FLUXNET site, US-Bo1, the soy field site in this study. The model shown in Fig. 13 and described in Eqs. (3)–(10) was based on flux observations from soil collected at this site. There are well-known uncertainties associated with reported GPP from flux towers (Desai et al., 2008). However, since we have no in situ measurements of COS from the site, these data are used as a starting point for calculating theoretical error potentials.
Two GPP estimates are presented in Fig. 14a: the first represents
GPP estimates with COS leaf uptake fluxes alone, the second was
based on theoretical net COS fluxes, including both leaf and soil
COS exchange calculated with Eq. (3). The difference between the
1-day moving averages (Fig. 14b) signifies how GPP could have been
over- or underestimated if net ecosystem COS fluxes were used as
leaf uptake fluxes, ranging from
Observations of COS fluxes from air-dried soils over a range of
temperatures. Air-dried soils experience negligible COS uptake; the net
fluxes here are assumed to be soil COS production only. Equation (4) was used to
curve-fit the relationship between temperature and soil COS production with
least-squares regression. The
COS fluxes over time after temperate soil moisture content was
changed from
Estimated fluxes from abiotic
Fitting parameters using Eq. (6) for soy field COS fluxes binned by
temperature. See Sect. 4.2 for parameter descriptions. Fluxes are in pmol
COS
To explore the possible spatial variation in soil COS exchange
influence on the GPP proxy, we perform a similar calculation
(described in Sect. 2.4) using in situ soil fluxes from previous
studies (Table 4). The potential error in GPP estimates based on
these sparse measurements ranges from
Generally, non-wetland soils are thought to have a small COS
exchange rate compared to uptake by plant leaves. This assumption
is based on few chamber measurements, often by severely altering
the ecosystem, e.g., extracting plants beforehand (see review in
Whelan et al., 2013). During a campaign to measure COS by eddy
flux covariance in Oklahoma, Billesbach et al. (2014) noticed that
hot soil and particularly hot and dry soil yielded emissions of
COS to the atmosphere. This is believed to be a breakdown product
from thermal decomposition of soil organic matter (Maseyk et al.,
2014; Whelan and Rhew, 2015). This study sought to investigate the
ubiquity of this phenomenon by incubating soils from a broad range
of ecosystems and under a matrix of controlled conditions. Here we
have found that, as assumed previously, most soils have small COS
fluxes relative to anticipated plant uptake. However, large
emissions like those reported by Billesbach et al. (2014) were
generated in incubations of another agricultural soil from a soy
field over 800
Previous studies have shown that the interaction between net fluxes and ambient
concentration of COS is linear (e.g., Conrad, 1994; Kesselmeier et al., 1999).
COS soil fluxes have a demonstrated “compensation point”, the atmospheric
concentration of COS where the net flux of a specific system is 0. At
concentrations below the compensation point, net emission to the atmosphere
is observed; net consumption is observed when ambient concentrations are
higher than the compensation point. We believe that the variability in fluxes
due to changes in soil moisture in Fig. 8 masks the effect of changes in COS
chamber mixing ratios. In Kesselmeier et al. (1999), the authors used the
mole fraction of COS exiting the incubation chamber as a measure of the
well-mixed ambient environment actually experienced by the soil. The
relationship between the observed COS fluxes after soil moisture change and
the COS mixing ratio exiting the chamber is depicted in Fig. 9; all
incubations depicted took place at 20
The error introduced to GPP estimates when COS soil fluxes are held
negligible. The % uncertainty column describes how much GPP would be overestimated, as
a percentage of GPP calculated by Beer et al. (2010), if soil COS uptake
determined from chamber measurements was included in the
Comparing theoretical GPP estimates based on gross COS leaf fluxes
vs. net ecosystem COS fluxes.
Comparing the model developed here with field observations.
The soil samples in this study were incubated under flowing air. The soil and headspace air were assumed to be in equilibrium after 30 min. If that were true, adsorption and desorption should no longer contribute to the soil flux: equal amounts of COS should adsorb and desorb. The uptake difference between the zero air and ambient air treatments in Fig. 4 indicates that some uptake process was affecting net soil fluxes, even in a very dry soil.
Multiple mechanisms determined the net COS exchange from soil, which were affected by soil water content and temperature. There are three proposed abiotic processes: COS production from abiotic degradation of soil organic matter (Whelan and Rhew, 2015), the physical limitations of water restricting air exchange between soil pore spaces and the chamber headspace (Van Diest and Kesselmeier, 2008), and adsorption/desorption of COS onto soil grains. The biotic uptake of COS by soils is theorized to be via enzymes present in the microbial community that are similarly responsible for COS uptake in plants (Kesselmeier et al., 1999; Protoschill-Krebs et al., 1996). There is no known biotic COS production mechanism in soils.
Taking these routes of COS exchange into account, we can explain
qualitatively the fluxes observed here. For example, hot, dry soil
appeared to produce the highest net COS emissions. Dry soil has
a smaller active microbial community (Manzoni et al., 2011), and
biotic uptake would be small. Higher temperatures should yield more
thermal degradation of organic matter, resulting in higher COS
production. In this study, when soy field soils were heated from 40
to 68
The desert soil samples, however, demonstrated near-zero COS exchange at field moisture and COS uptake when wetted. Since these soils are frequently hot and dry, it could be that there is not sufficient remaining organic material to abiotically degrade into COS, or there are not enough clay or silt surfaces for COS to adsorb/desorb. The behavior of the desert soil resembles the soil COS exchange observed in Van Diest and Kesselmeier (2008) and Kesselmeier et al. (1999), which both investigated exclusively sandy soils.
For the agricultural soils studied here, it appears that some soil interaction produced much more COS than other soils investigated. Large COS emissions were also observed from a wheat field soil in China (Liu et al., 2010) and the previously mentioned wheat field in Oklahoma (Billesbach et al., 2014; Maseyk et al., 2014; Whelan and Rhew, 2015), but not from the sandy arable soil in Germany, Finland, and China (Van Diest and Kesselmeier, 2008), where only net COS uptake was observed. While Melillo and Steudler (1989) found increases in forest soil COS production coincident with nitrogen fertilizer application, the composition of fertilizer used at the sites discussed above is unknown to us. It is unclear what is particular about the agricultural soils in the study by Van Diest and Kesselmeier (2008) that should result in only soil COS net consumption.
Two hypotheses emerge from the theoretical framework detailed above. The first is that all soils experience large COS production from thermal degradation of soil organic matter or desorption from soil surfaces, but most or all COS generated is usually consumed by in situ microbial communities. The agricultural soils collected in Oklahoma and Illinois undergo pesticide/herbicide applications and irrigation during the course of their management that may limit the diversity and size of the microbial community (Griffiths and Philippot, 2013) and the magnitude of the microbial COS sink. This idea is partially supported by Whelan and Rhew (2015), where autoclaved agricultural soils only experienced net COS production, though autoclaved soils are known to emit COS (Kato et al., 2008).
The second hypothesis suggests that the accessibility of the agricultural soil organic matter allowed more abiotic COS production than in forest or savannah soils. This could also be due to agricultural land management practices, which tend to break down soil aggregates and destabilize soil organic matter (Sollins et al., 1996). Accessibility, rather than litter quality, could explain why we see a similar COS production from agricultural fields with different crop cover, i.e., wheat (Billesbach et al., 2014; Liu et al., 2010) and soy/corn (this study). However, this still does not explain the biotically driven net COS uptake patterns found in arable soils by Van Diest and Kesselmeier (2008) and Kesselmeier et al. (1999), who report COS fluxes that resemble more the desert soil fluxes investigated here.
These two hypothesis may both influence COS exchange
simultaneously. When the course litter and sand (
The drawdown of COS over North America has been observed from aircraft vertical profiles, appearing to scale with GPP-based uptake of COS by plants (Campbell et al., 2008). Data presented here indicate soil COS emission was maximum during high-temperature incubations, coincident with some surface temperatures observed during the North American growing season. We generated a model in Sects. 2.3 and 3.2 to calculate COS fluxes for US agricultural soils, taking these large emissions into account. Relating laboratory measurements to in situ observations has inherent problems, so we present this as a theoretical exercise investigating the possible magnitudes of soil COS exchange on broader scales.
We plotted our equation with one developed by Maseyk et al. (2014)
from fluxes (Fig. 15a) and environmental parameters (Fig. 15b)
recorded in situ at a wheat field in Oklahoma over the course of
that study in 2012. The COS flux model developed by Kesselmeier
et al. (1999) is displayed using the same input variables,
assuming a constant ambient COS mixing ratios of 500
Key patterns emerged from examining differences between the observations and predictions over the course of the campaign in Maseyk et al. (2014) (Fig. 15), noting first that the model presented by Kesselmeier et al. (1999) and the model presented here were not parameterized using soil from this site. The fact that there are any similarities at all between the model outputs and observations is encouraging for future modeling efforts. None of the three models captured the large emissions observed before day of year (DOY) 130 when wheat was present in the field and higher soil moisture occurred. None of the models captured the large swings from COS source to sink found during large temperature fluctuations between DOY 110 and 115. After DOY 130, the wheat senesced and was harvested, resulting in hot and dry soils. The simple model from Maseyk et al. (2014) reproduced the COS soil flux variability better under these conditions. The Kesselmeier et al. (1999) model generated some variability, but could not predict any soil COS emissions. This study's model overlapped both the uptake model's variability during wheat senescence and the high emissions predicted by Maseyk et al. (2014) after wheat harvest.
There are several explanations for the discrepancies between
models and flux observations. Both this study and the Kesselmeier
et al. (1999) model were based on idealized laboratory
conditions, not taking into account interactions with soil COS
exchange at different depths. No doubt COS is produced or consumed
in all layers of soil, not just at the surface, but soil
incubations were purposefully designed to avoid these issues.
Additionally, there is variability in both soil moisture and
temperature even over the area of the soil plot: a heterogeneous
soil may experience variations in these parameters on a small
scale (Entin et al., 2000). Also, soil temperature was measured at
5
The main motivation of this work was to make progress towards better estimates of GPP. The drawdown of COS over the continents appears to be associated with the uptake of carbon dioxide (Campbell et al., 2008). For some of the biomes explored here, like deserts, soil COS exchange under field conditions may actually be negligible compared to plant uptake. On the other hand, recent work has suggested that soil COS fluxes in agricultural areas might be large and need to be taken into account (Billesbach et al., 2014; Maseyk et al., 2014). The model presented in this study anticipates these agricultural soil COS fluxes using commonly measured variables. With such a correction, applying the COS-GPP tracer will be more feasible to constrain GPP estimates on regional scales.
Taking COS soil fluxes into account when estimating GPP can avoid over- and underestimations of carbon fluxes presented in Table 4 and Fig. 14. Observations are still scarce: despite a plea for data from desert soils by Kettle et al. (2002), we were not able to find such a study in the literature over 10 years later. Boreal forest soil COS exchange estimates are represented by a single study performed at a single site in Sweden over the course of 2 months in 1993 (Simmons, 1999). Modeling efforts suggest large COS fluxes in the tropics (Berry et al., 2013; Suntharalingam et al., 2008) and tropical forests and savannahs are associated with 60 % of global terrestrial GPP (Beer et al., 2010). However, there remains a dearth of observations in tropical latitudes.
This magnitude of avoidable error suggests that soil fluxes are not negligible; however, the uncertainty of GPP at regional to global scales is much larger. The error introduced by large soil emissions from cropland soils to COS-GPP estimates can be avoided by characterization and correction of COS fluxes. This study's approach deconvolves the production rates seen to dominate the net COS flux in Maseyk et al. (2014) and the small uptake rates observed in sandy soils by Van Diest and Kesselmeier (2008).
The quantity of data in Table 4 suggests a dire need for more information about soil COS exchange. Here we presented a controlled study using soil from multiple ecosystems and cohesive theory for how to interpret observed soil COS fluxes. This study confirms that soil from many biomes exhibited small COS fluxes compared to estimated plant sinks. However, field studies must be conducted to determine the extent of the larger magnitude US agricultural soil COS exchange in order to quantify and correct for soil effects in GPP proxy models. The difference in COS flux behavior between agricultural soils investigated in the US and Europe also remains an open question.
A final complication arises from water stress: changes in soil moisture can cause the release of pulses of COS to the atmosphere (Fig. 12) while affecting photosynthesis and associated plant COS uptake. Additionally, COS exchange during freeze–thaw events will shed light on conditions that no field or laboratory study has yet determined. If the COS soil sink is indeed overwhelmingly microbial, water stresses will play an important role in their community diversity and function (Schimel et al., 2007), which may control the balance of COS over ecosystems.
The authors thank J. Kesselmeier, L. Kooijmans, and H. Chen for technical insights and manuscript feedback; D. Chadwick, J. Thom, L. Meredith, J. Chalfant, and W. Sun for sample collection; K. MacFarlane, T. Guilderson, S. Biraud, and K. Maseyk for sampling advice and data sharing; M. Zahniser and A. Kornfeld for QCL technical support; and G. Badgley, K. Caldeira, and R. Commane for data analysis suggestions. Equipment was purchased through NSF DBI grant #1 040 106. Funding for the US-WCr AmeriFlux ChEAS cluster core site was provided by the U.S. Department of Energy's Office of Science. The CFSR data were developed by NOAA's National Centers for Environmental Prediction (NCEP). The data for Fig. 1 are from NOAA's National Operational Model Archive and Distribution System (NOMADS), which is maintained at NOAA's National Climatic Data Center (NCDC). This study used the CFSRv2 hourly time series data for soil moisture (soilm1.gdas.*.grb2 files; Soil Moisture Level 1 on T382 Gaussian Grid) and soil temperature (soilt1.gdas.*.grb2 files; Soil Temperature Level 1 on T382 Gaussian Grid). The data used to generate Fig. 14 used eddy covariance data acquired by the FLUXNET community and in particular AmeriFlux (U.S. Department of Energy, Biological and Environmental Research, Terrestrial Carbon Program (DE-FG02-04ER63917 and DE-FG02-04ER63911)). We acknowledge the financial support to the eddy covariance data harmonization provided by CarboEuropeIP, FAO-GTOS-TCO, iLEAPS, Max Planck Institute for Biogeochemistry, National Science Foundation, University of Tuscia, Université Laval, Environment Canada, the US Department of Energy, the database development and technical support from Berkeley Water Center, Lawrence Berkeley National Laboratory, Microsoft Research eScience, Oak Ridge National Laboratory, University of California – Berkeley, and University of Virginia. This manuscript is based upon work supported by the National Science Foundation under grant number 1433257. Edited by: M. von Hobe