Preliminary Assessment of Carbon and Nitrogen
Sequestration Potential of Wildfire-Derived Sediments
Stored by Erosion Control Structures in Forest
Ecosystems, Southwest USA
Authors: Callegary, James B, Norman, Laura M, Eastoe, Christopher J,
Sankey, Joel B, and Youberg, Ann
Source: Air, Soil and Water Research, 14(1)
Published By: SAGE Publishing
URL: https://doi.org/10.1177/11786221211001768
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1001768
ASW0010.1177/11786221211001768Air, Soil and Water ResearchCallegary et al
research-article2021
Preliminary Assessment of Carbon and Nitrogen
Sequestration Potential of Wildfire-Derived
Sediments Stored by Erosion Control Structures
in Forest Ecosystems, Southwest USA
James B Callegary1 , Laura M Norman2
Joel B Sankey4 and Ann Youberg5
, Christopher J Eastoe3
Air, Soil and Water Research
Volume 14: 1–18
© The Author(s) 2021
Article reuse guidelines:
sagepub.com/journals-permissions
DOI: 10.1177/11786221211001768
https://doi.org/10.1177/11786221211001768
,
1Arizona
Water Science Center, US Geological Survey, Tucson, AZ, USA. 2Western Geographic
Science Center, US Geological Survey, Tucson, AZ, USA. 3Department of Geosciences, The
University of Arizona, Tucson, AZ, USA. 4Grand Canyon Monitoring and Research Center,
Southwest Biological Science Center, US Geological Survey, Flagstaff, AZ, USA. 5Environmental
Geology, Arizona Geological Survey, Tucson, AZ, USA.
ABSTRACT: The role of pyrogenic carbon (PyC) in the global carbon cycle is still incompletely characterized. Much work has been done to characterize PyC on landforms and in soils where it originates or in “terminal” reservoirs such as marine sediments. Less is known about intermediate reservoirs
such as streams and rivers, and few studies have characterized hillslope and in-stream erosion control structures (ECS) designed to capture soils and
sediments destabilized by wildfire. In this preliminary study, organic carbon (OC), total nitrogen (N), and stable isotope parameters, δ13C and δ15N, were
compared to assess opportunities for carbon and nitrogen sequestration in postwildfire sediments (fluvents) deposited upgradient of ECS in ephemeral- and intermittent-stream channels. The variability of OC, N, δ13C, and δ15N were analyzed in conjunction with fire history, age of captured sediments,
topographic position, and land cover. Comparison of samples in 2 watersheds indicates higher OC and N in ECS with more recently captured sediments located downstream of areas with higher burn severity. This is likely a consequence of (1) higher burn severity causing greater runoff, erosion,
and transport of OC (organic matter) to ECS and (2) greater cumulative loss of OC and N in older sediments stored behind older ECS. In addition, C/N,
δ13C, and δ15N results suggest that organic matter in sediments stored at older ECS are enriched in microbially processed biomass relative to those at
newer ECS. We conservatively estimated the potential mean annual capture of OC by ECS, using values from the watershed with lower levels of OC,
to be 3 to 4 metric tons, with a total potential storage of 293 to 368 metric tons in a watershed of 7.7 km2 and total area of 2000 ECS estimated at 2.6 ha
(203-255 metric tons/ha). We extrapolated the OC results to the regional level (southwest USA) to estimate the potential for carbon sequestration using
these practices. We estimated a potential of 0.01 Pg, which is significant in terms of ecosystem services and regional efforts to promote carbon storage.
KEyWoRDS: Watershed restoration, carbon sequestration, nitrogen sequestration, ephemeral and intermittent streams, wildfire, C/N, δ13C,
δ15N, fluvents, mollisols, inceptisols
RECEIVED: February 2, 2021. ACCEPTED: February 19, 2021.
DEClARATIoN oF CoNFlICTINg INTERESTS: The author(s) declared no potential
conflicts of interest with respect to the research, authorship, and/or publication of this article.
TyPE: Original Research
FUNDINg: The author(s) disclosed receipt of the following financial support for the
research, authorship, and/or publication of this article: Financial support for the research,
authorship, and publication of this article was derived in part from the U.S. Geological
Survey (J.C., L.N., J.S.) C.E. and A.Y. were unfunded.
Introduction
Globally, organic carbon (OC) and total nitrogen (N) stored in
soil organic matter (SOM) have been depleted due to watershed
degradation and agricultural management practices.1-3 Wildfire
also results in losses of SOM due to combustion at higher temperatures, and exposure and oxidation of soil aggregate-protected
OC caused by lower temperature fires.4 Losses are expected to
continue, as climate change is predicted to increase fluxes of soil
C to the atmosphere, mainly from peat, wetlands, and thawing
permafrost. Such additions to the atmosphere could be partly
offset by restoration of SOM. There is thus a need to investigate
practices and techniques that enhance long-term organic matter
(OM) storage. One technique that has a long history of being
used both locally and globally to retain soil and water is installation of erosion control structures (ECS).5,6 They have been used
in watershed and riparian restoration, in agriculture for soil conservation, and after wildfires to stabilize slopes and capture sediments in stream channels.6-11 They also have been shown to
store SOM and OC12,13 and have the potential to store pyrogenic carbon (PyC) from wildfires.
CoRRESPoNDINg AUTHoR: James B Callegary, Arizona Water Science Center, US
Geological Survey, 520 North Park Avenue, Tucson, AZ, 85719, USA.
Email: jcallega@usgs.gov
Pyrogenic carbon has been identified as a potentially significant sink in the context of the global carbon cycle, and a
growing body of work has been done on understanding PyC
stability, composition, fluxes, and storage in soils, lakes, and
marine sediments.14-16 Ash and char production and destabilization and erosion of hillslope soils lead to increases in delivery
of nutrients and sediments to streams. This can negatively
affect water quality and aquatic ecosystems17,18 and lead to loss
of carbon and nitrogen from watersheds. Consistent with
recent experience, climate-change modeling predicts significant increases in wildfire frequency and extent, and postfire
erosion rates in the coming decades in the western USA.19,20
Before intensive logging in the late 1800s,21,22 forests in the
southwest USA were burned by frequent, low-severity, and
widespread fires.23 By the late 20th century, fuel accumulation
and prolonged drought conditions were leading to wildfires of
increased size and severity, a trend expected to increase as climate change leads to higher temperatures and increased evapotranspiration in the southwest USA.24 Larger, hotter fires may
be pushing mountain terrains toward geomorphic and
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Air, Soil and Water Research
2
ecosystem tipping points,25,26 potentially leading to permanent
loss of OM that accumulated over centuries to millennia.27-34 It
is thus timely to study and assess methods that can be applied
after wildfires to retain carbon- and nitrogen-rich soil, wood,
ash, and char.
This preliminary study considers possibilities for retention
of wildfire-derived OM in sediments stored by ECS in forest
ecosystems of the southwest United States. We hypothesize
that ECS can be used to capture and sequester PyC and eroded
SOM and that as surficial OM matures, some OC and N will
be lost from the soil through leaching and/or diffusion. We use
information on landcover, ECS characteristics (size, age, geomorphic setting), OC, total N, and stable isotopes to (1) evaluate the potential of ECS to retain and store OC and N in
postwildfire transported sediments of the southwest USA and
(2) discuss processes that may be affecting the amount and
properties of retained OM over time.
Figure 1. (Continued)
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Figure 1. (A) Turkey Pen-LBSO (yellow) and Coal Pit-HBSN (green)
watershed boundaries, and sampling locations, where LBSO stands
for Lower Burn Severity Older ECS and HSBN stands for Higher Burn
Severity Newer ECS. Inset map at left indicates location of study
area in North America in the state of Arizona, USA. Parts (B) (Turkey
Pen-LBSO) and (C) (Coal Pit-HBSN) with sampling locations and
names (note some locations are too close together to distinguish at
this scale). Burn severity 35,36 from the 2011 Horseshoe 2 Fire 37 is
overlain on each watershed (red = high burn severity,
orange = moderate burn severity, yellow = low burn severity,
green = unburned).
ECS indicates erosion control structures; HBSN, higher burn severity newer;
LBSO, lower burn severity older.
Background
Erosion control structures are one of many tools used to stabilize and restore degraded watersheds and mitigate impacts
of fire-induced nutrient and sediment transport.38-41 Check
dams of varying permeability can be made from a variety of
materials ranging from brush fill to natural stone, masonry,
and packed earth.6,42 Site selection and dam design depend
on project objectives and factors such as channel shape and
dimensions, access, slope, vegetation, soils, geology, proximity to erosion, dam type, cost, number of and distance between
check dams, and flood frequency and magnitude. If ECS are
improperly sited or constructed, negative impacts can range
from neutral to catastrophic (for example, cascading failure
in ECS networks during floods or debris flows43). When
properly sited and installed, however, they can offer opportunities for capture and rapid burial of mobilized abovegroundbiomass, SOM, and PyC.44,45 Organic matter, OC, and N
sequestration by ECS have been studied12,44,46-49 especially
where saturated or semisaturated conditions persist in the
trapped sediments. This creates conditions similar to wetlands which have a well-documented OC sequestration
potential.50
The study area was located in 2 forested watersheds in
the Chiricahua Mountains of southeastern Arizona, USA
(Figure 1). The watersheds are similar in elevation, vegetation
assemblages, geology, and soils, but have different burn severity51 and restoration histories. The Turkey Pen watershed
(referred to as Lower Burn Severity Older ECS or LBSO) has
an area of about 7.7 km2, with elevations ranging from 1760 to
2310 m. About 70% of LBSO has slopes greater than 30%.
The Coal Pit watershed (referred to as Higher Burn Severity
Newer ECS or HBSN) has an area of about 4.8 km2 with elevations ranging from 1730 to 2500 m. Approximately 80% of
the watershed has slopes greater than 30%. Bedrock in both
watersheds consists of faulted intrusive and extrusive rhyolite
and rhyodacite of late Paleogene age.52,53 Precipitation
increases with elevation and ranges between 385 and 660 mm
per year with most of it arriving between July and mid-September via isolated convective storms.54 Winter precipitation
occurs from November to March and falls as snow at higher
elevations. The dominant vegetation type in the lower reaches
of the watersheds, and particularly in LBSO, is Madrean
Callegary et al
Pinyon-Juniper-Oak Woodland which includes local patches
of grasses and shrubs.55 Common species include alligator
juniper (Juniperus deppeana), oak (Quercus spp.), and pinyon
pine (Pinus edulis, Pinus cembroides). Madrean Lower Montane
Pine-Oak Forest and Woodland also occurs, favoring mesic
slopes and valley bottoms in the upper reaches of the 2 watersheds. This forest type is dominated by Chihuahuan (Pinus
leiophylla), Apache (Pinus engelmannii), and pinyon (Pinus discolor) pines and alligator juniper (Juniperus deppeana).
Ponderosa pine (Pinus ponderosa) and Douglas fir (Pseudotsuga
menziesii) are locally abundant at higher elevations, and oak
(Quercus spp.) at lower elevations.
Watershed restoration, primarily ECS installation, began
in the LBSO in the first half of the 1980s56 and in the HBSN
in the 1990s (pers. comm. Valer Clark, 2016). Erosion control
structures were installed in ephemeral and temporally and
spatially intermittent streams. Globally, such streams present
a widely available opportunity for OM storage as they make
up more than half the combined length of rivers and
streams.57,58 The structures were primarily constructed of
loose-rock, including 1-rock structures on hillslopes and inchannel structures (eg, check dams and gabions) to act as
sediment traps (Figure 2). Once the network of ECS was
installed, flood peaks were reduced, overall flow volume
increased,59 and few ECS failed even in larger floods (pers.
comm. Valer Clark, 2016). Hillslope structures, about 90% of
all ECS in the study area, typically consisted of dams 1-rock
high and 1-rock thick placed at points of incipient erosion
perpendicular to the direction of maximum slope. All ECS in
the study area were permeable. Most ECS in LBSO and
HBSN were filled to capacity with prefire sediment before
the 2011 Horseshoe 2 Fire, which burned over 90 000 ha in
the Chiricahua Mountains.26 This included portions of the
LBSO and HBSN watersheds, with high or moderate burn
severity in 18% of LBSO and 28% of HBSN.36,37,51 After the
fire, previously installed and filled ECS were extended and
repaired in HBSN but not LBSO, creating additional capacity for sediment capture HBSN. Rains following the fire
caused flooding and debris flows.26 There is no information
on scour and fill history or OM delivery in the previously
filled ECS in either watershed prior to the 2011 wildfire, but
the newly expanded ECS in HBSN were filled with sediments rich in PyC including ash and charred wood (pers.
comm. Valer Clark, 2016). In this study, we use both soil and
sediment as terms for the material captured by ECS. Because
the streams investigated are ephemeral and intermittent nd
because of the ECS network, captured sediments that tend to
be stable through time and only seasonally saturated throughout the profile. This creates a blend of terrestrial and fluvial
conditions that allow soil forming processes to occur.
As this was a preliminary survey of OC and N, soil surveys
were not carried out, but soil descriptions are available via lower
(STATSGO2) and higher (SSURGO) resolution state-level
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3
Figure 2. Examples of erosion control structures (ECS) used in the
study. Location names: (A) Middle LBSO, (B) Hillslope LBSO, and (C)
Middle HBSN.
ECS indicates erosion control structures; HBSN, higher burn severity newer;
LBSO, lower burn severity older.
surveys.60 The higher resolution surveys are available only for
small portions of the study area near the watershed outlets.
However, it is likely that the classifications are valid for nearby
in- and near-channel soils and sediments on adjacent National
Forest lands which constitute the bulk of the study area. In
general, both watersheds consist of steep slopes with abundant
rock outcrops, with in-channel sediments generally classified as
Inceptisols and Entisols, and near-channel soils classified as
Mollisols and Entisols.
Measurements of isotopic parameters δ13C and δ15N were
critical to understanding the impacts of ECS in this study.
Values of δ13C can be used to distinguish OM from C3 (predominantly woody cool-season species) or C4 (predominantly
warm-season herbaceous) plants.61 It is probable that the
majority of the grasses in the study area are C462 The range of
δ13C in C3 plants in arid ecosystems is about −25 to −27 ‰,63
4
and globally the range of δ13C in C4 plants has been estimated
to be −10 to −15 ‰.64 Thus in soils, lower values of δ13C could
imply a greater proportion of C derived from C3 plants.65
Moreover, the preferential survival of biomass from woody C3
plants in contrast to easily-decomposed herbaceous C4 plants
could lead to δ13C of sediments being dominated by a C3 isotopic signature.66
Values of δ13C can increase with increasing soil depth and
decreasing OC concentration67 as well as with degree of
decomposition and age.64 Decay of coarse woody debris can
lower the δ13C of the remaining biomass, likely due to preferential loss of cellulose in which δ13C is higher than more
resistant lignin. Preston et al68 summarized and confirmed the
results of several studies, with lignin in selected evergreen species having δ13C ranges 1.7 to 3.3 ‰ lower than whole wood
and 3.0 to 4.4 ‰ lower than cellulose. A similar effect was
noted in saltmarsh grass.69 Microbial decomposition of OM
may affect δ13C by adding atmospheric and/or soil-gas CO2 to
SOM,64 and fungal mycelia have been shown to incorporate
CO2 labeled with 14C.70 Such processes would result in an
increase in δ13C with age and degree of decomposition due to
a combination of (1) microbial carboxylation of OM using
ambient soil CO2 (which is enriched in 13C relative to the OM
being decomposed), and (2) the “Suess effect,” a decline in
δ13C in atmospheric CO2 of about 1.5 ‰ since about 1960 to
its current level of −8.5 ‰.64,70-74
Wildfire can affect δ13C in OM, and the magnitude and
direction of the effect depends on factors such as species,
temperature, and duration of burning or charring. Some
researchers have found little change in ash and charcoal
from C3 plants but shifts as large as 8 ‰ in δ13C of burned
C4 OM.75-77 Others78 have found that low-temperature
(150°C) charring causes δ13C to increase in both softwood
and hardwood (possibly due to volatilization of hydrocarbons), but higher temperatures, 340°C-480°C, lead to a
decrease likely due to preservation of lignin and loss of cellulose. Another factor to consider is transport of PyC. It has
been found that C4-derived PyC is transported preferentially in watersheds, possibly due to small particle size relative to C3 PyC.79
With respect to δ15N in soils, several studies have found
increases with depth and age related to microbial decomposition and/or effects of SOM-mineral association.80-82
Ammonification and nitrification have the largest potential
effects on δ15N, with nitrate, nitrite, and ammonia products
being depleted in 15N by as much as 20‰ relative to fresh
OM. Removal of these products by leaching or denitrification
would lead to an increase in δ15N of the residual OM. Under
conditions similar to wildfires, Pyle et al83 found residualbiomass δ15N increased with charring intensity. Processes
other than wildfire can also affect δ15N, but not necessarily in
predictable ways. For example, δ15N in soils is likely to change
during ecosystem disturbances such as grazing and during
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Air, Soil and Water Research
postdisturbance recovery, but the direction of change is
inconsistent.84
Methods
Sampling site selection and description
A total of 22 sites were sampled at 7 locations (Figure 1;
Table 1). Sampling locations were selected to represent geomorphic settings of interest: one ECS on a hillslope in LBSO,
and in each watershed 2 ECS in stream channels and 1 terrestrial “off-channel” location (Figure 2). The off-channel
locations were located to the side of each channel to investigate terrestrial conditions. They were situated on slopes that
were normally unaffected by flooding and without ECS. In
each watershed, one in-channel sampling location was located
near the watershed outlet and one was located at an upstream
location. A larger number of “in-channel” locations was
assessed with the expectation that most OC and N would be
stored in them, and therefore that understanding variability
in these was a greater priority.
At each in-channel and hillslope location 4 sites (A-D)
were sampled in the sediment upstream of each ECS to gain
information on horizontal variability of measured parameters.
Two depth intervals were sampled at each site to study vertical
variability (0-10 cm and 20-30 cm below the mineral soil surface). During sampling, leaf litter and grass were removed to
expose the mineral soil surface and in a few cases slight adjustments to the depth of the sample were necessary due to the
presence of cobbles or bedrock. No information was available
to assess whether the grasses were perennial or annual or of C3
or C4 types. However, it is likely they are C4, given the predominance of C4 grasses regionally.62 All samples were
assessed visually for color, texture, and roots, leaves, and charcoal. At each location, ECS dimensions were measured including height and width and an estimate of the upstream length
of the sediment wedge (Figure 3). The volume of captured
sediment was estimated using the equation for a half elliptical
paraboloid (Table 2).85
In LBSO, 4 locations are represented: 2 in-channel ECS
(with names: UPPER LBSO and MIDDLE LBSO (Figure
2A)), plus HILLSLOPE LBSO A to D (Figure 2B) and
OFF-CHANNEL LBSO. The results and site information
are found in Tables 1 and 2. They may also be found by following the highlighted link above to the USGS National Water
Information System. The total number of sites in LBSO is 13:
3 locations with 4 sampling sites each (A thru D), and one
with one sampling site (location name = Off-Channel LBSO).
The channel at the Upper LBSO site was dry at the time of
sampling with shallow gravelly sediment, high slope, and
exposed fractured bedrock adjacent to the stream channel. The
next site down gradient was Hillslope LBSO. This site and the
adjoining area generally have low slope, covered with leaves
and grass, and unknown depth to bedrock. The site furthest
Callegary et al
downstream, Middle LBSO, had a shallow water table at the
time of sampling as evidenced by a pool of water downstream
of the ECS. It is often flooded during the summer rainy season (Valer Clark, personal communication, 2016).
Three locations were sampled in HBSN: 2 in-channel
sites (with names UPPER HBSN and MIDDLE HBSN
(Figure 2C)), plus OFF-CHANNEL HBSN. The total
number of sites in HBSN is 9: 2 locations with 4 sites each
(A thru D), and 1 with 1 site (location name = Off-Channel
HBSN). The Upper and Middle HBSN sites have soils in
the upper 2 m that had been deposited at most 5 years before
sampling and are commonly flooded in summer (Valer Clark,
personal communication, 2016). At the Upper HBSN site, a
sample was taken of the thick (about 15 cm) aerially extensive (about 30 m2) in-channel cover of leaf litter. This consisted primarily of oak leaves but also of twigs and pine
needles, all of which were presumed to originate from overhanging trees, upstream forest, and surrounding hillslopes.
Laboratory procedures
In the laboratory, standard procedures were followed. Samples
were weighed, ground to break up aggregates, passed through
a 2-mm sieve,86 then oven dried at 60°C for at least 48 h until
weight stabilized. Dried samples were ground to a uniform
consistency, passed through a 0.25 mm sieve and weighed.
Sieve ranges of 0.10 and 0.15 mm are common, but soils that
pass through a 0.25-mm mesh do not give statistically different results.87 Samples were analyzed for %OC, %N, δ13C, and
δ15N at the University of Arizona Environmental Isotope
Laboratory using an elemental analyzer (Costech) coupled to
a Finnigan Delta Plus XL continuous flow mass spectrometer. Carbonates were removed by addition of H2SO3. In the
elemental analyzer, after dry combustion, OC and nitrogen
fractions were determined by gas chromatography. A minimum of one acetanilide standard was run with every 10 samples. The acetanilide was calibrated against NBS-22 and
USGS-24 for δ13C, and IAEA-N-1 and IAEA-N-2 for δ15N.
Precision is better than ±0.08‰ for δ13C and ±0.2‰ for
δ15N (1σ), based on repeated internal standards. Organic carbon and total N were reported as percent OC and total N in
the <0.25-mm fraction. These values were converted to percentages of the total sample using the mass ratio of the
<0.25-mm fraction to the total sample (Table 1). Monthly
values of standards for the year prior to the measurements
indicated acceptable instrument stability. Certain samples
had mass of N below the range of standards. To remedy this,
we prepared a set of standards to extend the range and used
established approaches to determine method detection and
quantitation limits.88 We determined a method detection
limit of 0.015 mg N, and a quantitation limit of 0.03 mg N.
The data were reviewed according to USGS protocols and
stored in the USGS National Water Information System.89
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5
Modeling and statistical analysis
Procedures for comparing central tendencies were performed
using NADA for R88,90,91 and ProUCL.92 For samples with
uncensored data, either Wilcoxon Rank Sum88 or WilcoxonMann-Whitney92 methods were used. The Wilcoxon Signed
Rank test was used to compare paired (matched) samples
collected at the same site at different depths.88 Censored
data were those values of N that fell between the limits of
quantitation (0.03 mg N) and method detection (0.015 mg N).
For censored data, all tests were carried out using the Gehan
method.92
We calculated the potential mean annual capture of OC
by combining information from the LBSO and HBSN
including median OC of the hillslope and in-channel sites
both depths, estimated sediment volumes (Table 2) and published modeling results of annual sediment accumulation
rates for ECS in LBSO.56 We use the full range of data available from both watersheds to make the results more widely
applicable. In the previously published modeling work, it was
estimated that ECS could retain about 178 to 242 metric
tons of sediment per year. Using this range of values, their
count of 2000 ECS with 90% on hillslopes, and the mean
and median OC content from all in-channel samples (Table
1), we estimated the annual capture of OC in the group of
2000 ECS using equation (1)
RateCC = ( FxOC )( RateSC )( FxSed )
(1)
where RateCC is the rate of carbon capture in metric tons per
year, RateSC is the rate of sediment capture in metric tons per
year, and FxOC and FxSed are, respectively, the fraction of total
OC and fraction in each geomorphic setting of the total sediment captured by ECS (Table 3).
To calculate the total potential storage and storage per hectare in LBSO, the following equation was used with input data
from Table 4
STOT = (Vol Sed )( FxOC ) ( ECS ) ( ρb )
(2)
where for each geomorphic setting, VolSed is the median volume
of sediment, FxOC is the median fraction of total OC, ECS is
the number of ECS, and ρb is bulk density in metric tons per
cubic meter derived from the Rafter Soil Series.60 Carbon storage per hectare is calculated by dividing STOT by the estimated
total area of ECS in LBSO.
To illustrate the potential for ECS to store OC if they were
implemented on a large scale, we carried out a modeling experiment by extrapolating the results of the study to the forests of
the southwestern United States (Figure 4). Multiple sources
of uncertainty exist (eg, not all sites are suitable for reasons of
slope, geology, etc). The intention, however, is not to provide an
exact estimate, but to begin a discussion of the possibilities for
Air, Soil and Water Research
6
Table 1. Sample site names, coordinates, sampling depth, and results of analysis for %C, %N, C/N, δ13C, and δ15N.
SITE NUMBER
WATERSHEd
NAME
GEOMORPHIC
SETTING
SITE NAMEa
SAMPLING
dATE
LATITUdE
LONGITUdE
dEG-MIN-SECh
dEG-MIN-SECh
315145109222101
Coal Pit
Stream channel
Upper HBSN A
12/8/2015
31 51 45.17
109 22 21.01
315145109222101
Coal Pit
Stream channel
Upper HBSN A
12/8/2015
31 51 45.17
109 22 21.01
315145109222101
Coal Pit
Stream channel
Upper HBSN A
12/8/2015
31 51 45.17
109 22 21.01
315145109222102
Coal Pit
Stream channel
Upper HBSN B
12/8/2015
31 51 45.17
109 22 21.01
315145109222102
Coal Pit
Stream channel
Upper HBSN B
12/8/2015
31 51 45.17
109 22 21.01
315145109222103
Coal Pit
Stream channel
Upper HBSN C
12/8/2015
31 51 45.17
109 22 21.01
315145109222103
Coal Pit
Stream channel
Upper HBSN C
12/8/2015
31 51 45.17
109 22 21.01
315145109222104
Coal Pit
Stream channel
Upper HBSN d
12/8/2015
31 51 45.17
109 22 21.01
315145109222104
Coal Pit
Stream channel
Upper HBSN d
12/8/2015
31 51 45.17
109 22 21.01
315152109224701
Coal Pit
Stream channel
Middle HBSN A
12/8/2015
31 51 52.10
109 22 47.21
315152109224701
Coal Pit
Stream channel
Middle HBSN A
12/8/2015
31 51 52.10
109 22 47.21
315152109224702
Coal Pit
Stream channel
Middle HBSN B
12/8/2015
31 51 52.10
109 22 47.21
315152109224702
Coal Pit
Stream channel
Middle HBSN B
12/8/2015
31 51 52.10
109 22 47.21
315152109224703
Coal Pit
Stream channel
Middle HBSN C
12/8/2015
31 51 52.10
109 22 47.21
315152109224703
Coal Pit
Stream channel
Middle HBSN C
12/8/2015
31 51 52.10
109 22 47.21
315152109224704
Coal Pit
Stream channel
Middle HBSN d
12/8/2015
31 51 52.10
109 22 47.21
315152109224704
Coal Pit
Stream channel
Middle HBSN d
12/8/2015
31 51 52.10
109 22 47.21
315153109224601
Coal Pit
Terrestrial
Off-Channel HBSN
12/8/2015
31 51 53.12
109 22 46.43
315153109224601
Coal Pit
Terrestrial
Off-Channel HBSN
12/8/2015
31 51 53.12
109 22 46.43
315222109210101
Turkey Pen
Stream channel
Upper LBSO A
12/7/2015
31 52 21.57
109 21 00.68
315222109210101
Turkey Pen
Stream channel
Upper LBSO A
12/7/2015
31 52 21.57
109 21 00.68
315222109210102
Turkey Pen
Stream channel
Upper LBSO B
12/7/2015
31 52 21.57
109 21 00.68
315222109210102
Turkey Pen
Stream channel
Upper LBSO B
12/7/2015
31 52 21.57
109 21 00.68
315222109210103
Turkey Pen
Stream channel
Upper LBSO C
12/7/2015
31 52 21.57
109 21 00.68
315222109210103
Turkey Pen
Stream channel
Upper LBSO C
12/7/2015
31 52 21.57
109 21 00.68
315222109210103
Turkey Pen
Stream channel
Upper LBSO C
12/7/2015
31 52 21.57
109 21 00.68
315222109210104
Turkey Pen
Stream channel
Upper LBSO d
12/7/2015
31 52 21.57
109 21 00.68
315222109210104
Turkey Pen
stream channel
Upper LBSO d
12/7/2015
31 52 21.57
109 21 00.68
315233109210501
Turkey Pen
Hillslope
Hillslope LBSO A
12/7/2015
31 52 32.98
109 21 05.43
315233109210501
Turkey Pen
Hillslope
Hillslope LBSO A
12/7/2015
31 52 32.98
109 21 05.43
315233109210502
Turkey Pen
Hillslope
Hillslope LBSO B
12/7/2015
31 52 32.98
109 21 05.43
315233109210502
Turkey Pen
Hillslope
Hillslope LBSO B
12/7/2015
31 52 32.98
109 21 05.43
315233109210503
Turkey Pen
Hillslope
Hillslope LBSO C
12/7/2015
31 52 32.98
109 21 05.43
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Callegary et al
7
dEPTHb
MASS OF
SAMPLE
MASS OF
FINESc
ORGANIC
C FINESc
ORGANIC
C WHOLE
SAMPLEd
TOTAL N IN
FINESc,e
TOTAL N
IN WHOLE
SAMPLEd,e
C/N
δ13Cc,f
δ15Nc,g
CENTIMETERS
GRAMS
GRAMS
%i
%i
%i
%i
GRAMS PER
GRAM
‰
‰
Leaf litterj
–
3.684
16.8
–
0.59
–
28.7
−26.2
−1.1
10
–
6.328
1.3
–
0.06
–
21.8
−25.6
−0.4
30
5.513
5.164
5.0
4.7
0.15
0.14
32.7
−24.7
−2.0
10
1.738
1.498
4.1
3.6
0.15
0.13
27.6
−26.2
−0.3
30
6.858
6.429
2.1
2.0
0.08
0.08
25.1
−25.6
−1.2
10
3.127
2.953
7.3
6.9
0.28
0.26
26.3
−25.6
−1.3
20-25
3.055
2.712
3.1
2.7
0.11
0.09
29.1
−24.6
−1.2
0.25k
33.2k
−25.9
−1.1
10
3.588
3.193
9.3
8.3
0.28k
30
6.071
4.718
8.6
6.7
0.31
0.24
28.1
−25.5
−1.3
10
3.737
2.761
7.9
5.8
0.39
0.29
19.9
−25.3
−0.3
30
5.467
4.813
9.0
7.9
0.40
0.35
22.8
−25.1
−1.9
10
2.680
2.366
11.2
9.9
0.45
0.40
24.9
−25.7
−0.6
30
4.157
1.011
13.0
3.2
0.50
0.12
25.7
−24.9
−1.1
10
–
–
10.7
–
0.42
–
25.7
−25.8
−1.0
30
6.427
5.178
9.2
7.4
0.45
0.36
20.4
−25.2
−4.8
10
3.740
3.315
8.1
7.2
0.35
0.31
23.3
−25.6
−0.1
30
8.639
6.077
3.5
2.4
0.13
0.09
27.5
−25.6
−1.3
10
2.676
2.402
3.0
2.7
0.14
0.12
21.6
−25.3
0.3
30
4.456
3.916
0.4
0.4
0.03
0.02
17.3
−23.8
3.8
15
33.655
24.094
0.7
0.5
0.06
0.04
12.7
−24.2
2.1
30
17.119
13.217
1.0
0.8
0.07
0.05
15.7
−23.9
1.5
10
20.043
18.413
0.7
0.6
0.05
0.05
12.6
−25.2
1.9
30
19.327
15.456
1.3
1.0
0.08
0.06
16.2
−24.3
1.8
5
14.386
7.888
7.8
4.3
0.50
0.28
15.5
−24.4
1.3
10
18.326
15.963
0.4
0.4
0.03k
0.03k
12.4k
−24.5
1.5
30
9.301
8.626
1.1
1.0
0.07
0.07
15.0
−24.4
1.3
10
9.341
8.679
0.8
0.7
0.05
0.05
14.3
−24.3
2.3
30
9.343
8.482
2.0
1.8
0.13
0.11
15.7
−24.3
1.4
10
7.243
6.817
0.3
0.3
0.02k
0.02k
15.8k
−24.1
1.1
30
14.093
13.586
0.3
0.2
0.01k
0.01k
18.0k
−23.4
5.0
0.03k
17.0k
−23.9
1.7
10
13.488
12.546
0.4
0.4
0.03k
30
8.182
7.841
0.6
0.5
0.02
0.02
27.8
−24.8
3.3
10
7.502
7.281
0.5
0.5
0.03
0.03
19.1
−24.8
0.7
(Continued)
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Air, Soil and Water Research
8
Table 1. (Continued)
SITE NUMBER
WATERSHEd
NAME
GEOMORPHIC
SETTING
SITE NAMEa
SAMPLING
dATE
LATITUdE
LONGITUdE
dEG-MIN-SECh
dEG-MIN-SECh
315233109210503
Turkey Pen
Hillslope
Hillslope LBSO C
12/7/2015
31 52 32.98
109 21 05.43
315233109210504
Turkey Pen
Hillslope
Hillslope LBSO d
12/7/2015
31 52 32.98
109 21 05.43
315233109210504
Turkey Pen
Hillslope
Hillslope LBSO d
12/7/2015
31 52 32.98
109 21 05.43
315228109220401
Turkey Pen
Stream channel
Middle LBSO A
12/7/2015
31 52 27.89
109 22 04.05
315228109220401
Turkey Pen
Stream channel
Middle LBSO A
12/7/2015
31 52 27.89
109 22 04.05
315228109220402
Turkey Pen
Stream channel
Middle LBSO B
12/7/2015
31 52 27.89
109 22 04.05
315228109220402
Turkey Pen
Stream channel
Middle LBSO B
12/7/2015
31 52 27.89
109 22 04.05
315228109220403
Turkey Pen
Stream channel
Middle LBSO C
12/7/2015
31 52 27.89
109 22 04.05
315228109220403
Turkey Pen
Stream channel
Middle LBSO C
12/7/2015
31 52 27.89
109 22 04.05
315228109220404
Turkey Pen
Stream channel
Middle LBSO d
12/7/2015
31 52 27.89
109 22 04.05
315228109220404
Turkey Pen
Stream channel
Middle LBSO d
12/7/2015
31 52 27.89
109 22 04.05
315228109220405
Turkey Pen
Terrestrial
Off-Channel LBSO
12/7/2015
31 52 27.74
109 22 03.93
315228109220405
Turkey Pen
Terrestrial
Off-Channel LBSO
12/7/2015
31 52 27.74
109 22 03.93
Abbreviations: HBSN, higher burn severity newer; LBSO, lower burn severity older; OC, organic carbon.
aTo find the site name used in the USGS National Water Information System simply replace HBSN or LBSO with the Watershed Name.
bMeasured from mineral soil surface.
cReported laboratory value (measured on portion of sample sieved with 0.25 mm screen).
dC or N in whole sample = C or N content in Fines*Mass of Fines/Mass of Sample.
eTotal N = nitrate + nitrite + ammonia + organic-N.
fδ13C of organic C.
gδ15N of total N.
hdatum NAd-83.
iPercentage of dry weight.
jLeaf litter sample was taken above the mineral soil.
kMass of N in sample between quantification and method detection limits. See methods section for definitions.
lMass of N in sample below method detection limit. See methods section for definition.
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Callegary et al
9
dEPTHb
MASS OF
SAMPLE
MASS OF
FINESc
ORGANIC
C FINESc
ORGANIC
C WHOLE
SAMPLEd
TOTAL N IN
FINESc,e
TOTAL N
IN WHOLE
SAMPLEd,e
C/N
δ13Cc,f
δ15Nc,g
CENTIMETERS
GRAMS
GRAMS
%i
%i
%i
%i
GRAMS PER
GRAM
‰
‰
30
18.534
17.769
0.5
0.5
0.03k
0.03k
17.7k
−24.2
2.8
10
8.493
7.888
0.2
0.2
0.02k
0.02k
14.3k
−23.7
2.7
30
8.027
7.717
0.4
0.4
0.02
0.02
18.3
−23.4
4.7
10
10.233
8.162
0.6
0.5
0.04
0.03
13.5
−24.8
1.2
30
16.619
15.600
0.2
0.2
0.02
0.02
10.9
−24.4
2.7
10
8.944
8.399
0.5
0.4
0.04k
0.04k
13k
−24.8
1.4
30
8.449
7.775
1.0
0.9
0.07
0.07
13.5
−25.1
2.0
10
9.665
8.652
0.3
0.3
0.03
0.02
11.1
−24.2
2.1
25
11.287
10.256
0.7
0.6
0.05
0.05
13.2
−24.6
1.8
10
4.353
4.011
1.6
1.5
0.11
0.10
15.3
−24.1
0.6
30
14.739
13.426
0.3
0.2
0.02k
0.02k
12.7k
−24.7
2.8
10
29.886
14.358
1.3
0.6
0.09
0.04
15.4
−22.3
1.9
30
5.552
4.803
0.1
0.1
l
l
l
−22.4
6.3
Mean OC whole sample (all in-channel sites, both depths)
3.0
Mean OCwhole Sample (Hillslope site, both depths)
0.4
Median OC whole sample (all in-channel sites, both depths)
1.8
Median OC whole sample (Hillslope site, both depths)
0.4
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Air, Soil and Water Research
10
ECS-induced OC sequestration over large areas using modeling as a virtual laboratory. To begin, we assumed that forested
areas in the southwest USA have the potential for 2.6 ECS per
hectare, which is the estimated spatial density of ECS in the
LBSO watershed (Table 4). For a conservative estimate, we
used the lower %OC values in LBSO, which will be shown
below to represent longer-term storage of OC. The structures
in this watershed are older (most are between 20 and 35 years
old: Valer Clark, personal communication, 2016), sediments
tend to be wetter, and as a result SOM is potentially closer to
long-term values. Organic carbon is likely to be retained in
cases where soils remain saturated and have low oxygen concentrations, conditions similar to wetland soils.38,93-96
The calculation of the potential total C sequestration
requires estimates of volumes of sediment captured by ECS.
The estimate was developed using the measured dimensions of
the hillslope and in-channel sites (Table 2) and the equation
for volume of a half elliptical paraboloid.85 Total potential for
C sequestration was then calculated by multiplying the estimated sediment capture volumes, ECSpot, an estimate of soil
bulk density (ρb), and the average weight-percent C found in
Erosion
Control
Structure
hillslope (OCHill) and in-channel (OCChan) ECS (equation
(3)). We estimated CTot and the uncertainty therein using a
Monte Carlo approach that accounts for uncertainties in each
of the input variables. We carried out a total of 5000 realizations. Input values and error terms for the following equation
are summarized in Table 5
0.9 * (eECS + ECS ) *
pot
pot
( eVol Hill + Vol Hill ) *
CTot = ( FA + eFA ) *
(eC Hill + C Hill )
( e ρb + ρb ) *
0
1
+
(
)
.
*
eECS
ECS
pot
pot *
+ (eVol
Chan + Vol Chan ) *
(eCChan + CChan )
where CTot is the potential for C sequestration (mass C)
stored behind ECS in southwest USA Forests, FA is the area
of forest in the southwest USA extracted from the National
Land Cover Database,97 ρb is soil bulk density derived from
the Rafter Soil Series,60 ECSpot is the potential number of
ECS per unit area.56 Combining data from both LBSO and
HBSN, VolHILL and VolChan are the estimated volumes of sediment retained upstream of hillslope and channel ECS (Table
2), and Chill and Cchan are the mean measured OC contents in
samples of sediment retained upstream of hillslope and
channel ECS expressed as a fraction by weight. Error terms
“e” were estimated for each variable in the Monte Carlo simulation. The factors 0.1 and 0.9 in equation (1) were based on
the assumption that approximately 10% of ECS were
installed in channels and 90% on hillslopes. The 5000 realizations of CTot were log-transformed to more closely approximate a normal distribution.
Sediment
Storage
B
1m
C
1m
A
1m
1m
D
Figure 3. Geometry of sediment sampling sites relative to erosion
control structures.
Results
Table 2. dimensions of erosion control structures and estimated volume of captured sediments.
WIdTH
HEIGHT
LENGTH
SEdIMENT AREAa
SEdIMENT vOLUMEb
METERS
METERS
METERS
SqUARE METERS
CUBIC METERS
Upper HSBN
10.0
2.0
24.0
Middle HSBN
12.0
1.60
15.0
73c
52c
6
1
LOCATION NAME
(3)
Upper LBSO
4.05
1.40
4.00
Middle LBSO
7.30
0.90
5.30
Median dimensions
8.7
1.5
Hillslope LBSO
2.75
0.29
10.2
Abbreviations: HBSN, higher burn severity newer; LBSO, lower burn severity older.
aArea parabola = 2/3wl (median of sediment areas).
bvolume elliptical paraboloid = π(w/2)–l/4 (using median dimensions).
cEstimated using median dimensions.
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3.30
GEOMORPHIC
SETTING
vOLUME OF
SEdIMENT
(VOLSED)a
NUMBER
OF ECS OF
EACH TYPEb
CUBIC
METERS
FRACTION OF
TOTAL vOLUME
OF SEdIMENT
(FXSED)
FRACTION
ORGANIC
CARBON (FXOC)c
LOW ESTIMATE
SEDIMENT CAPTURE
RATE (RATESC)b
LOW ESTIMATE
CARBON CAPTURE
RATE (RATECC)d
HIGH ESTIMATE
SEDIMENT CAPTURE
RATE (RATESC)b
HIGH ESTIMATE
CARBON CAPTURE
RATE (RATECC)d
%
METRIC TONS PER
YEAR
METRIC TONS PER
YEAR
METRIC TONS PER
YEAR
METRIC TONS PER
YEAR
Callegary et al
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Table 3. Potential annual capture rate of organic carbon in ECS-captured sediments.
MEAN
Stream channel
Hillslope
52
200
0.85
3.0
178
5
242
6
1
1800
0.15
0.4
178
0.1
242
0.1
MEdIAN
Stream channel
Hillslope
52
200
0.85
1.8
178
3
242
4
1
1800
0.15
0.4
178
0.1
242
0.1
Abbreviations: ECS, erosion control structures.
aFrom Table 2.
bFrom Norman and Niraula.56
cFrom Table 1.
dCalculated using equation (1).
Table 4. Estimate of total potential storage of organic carbon and storage per unit area in ECS-captured sediments.
GEOMORPHIC
SETTING
Stream channel
Hillslope
vOLUME OF
SEdIMENT
(VOLSED)a
MEdIAN FRACTION
ORGANIC CARBON
(FXOC)b
CUBIC
METERS
%
52
1.8
1
0.4
NUMBER
OF ECS
OF EACH
TYPEc
LOW ESTIMATE
TOTAL POTENTIAL
CARBON STORAGE
(STOT)d,e
HIGH ESTIMATE
TOTAL POTENTIAL
CARBON STORAGE
(STOT) d,f
MEdIAN
AREA OF
ECSa
ESTIMATEd
TOTAL AREA OF
ECS IN LBSO
LOW ESTIMATE
CARBON
STORAGE PER
HECTAREd,e
HIGH ESTIMATE
CARBON
STORAGE PER
HECTAREd,f
METRIC TONS
METRIC TONS
SqUARE
METERS
HECTARES
METRIC TONS
PER HECTARE
METRIC TONS
PER HECTARE
200
282
353
73
1.5
193
242
1800
11
14
6
1.1
10
13
293
368
2.6
203
255
Total →
Abbreviations: ECS, erosion control structures; LBSO, lower burn severity older.
aFrom Table 2.
bFrom Table 1.
cfrom Norman and Niraula.56
dCalculated using equation (2).
eBulk density (ρ ) low = 1.53 metric ton/m3 (Rafter Soil Series [NRCS USdA Web Soil Series]: See Soil Survey Staff NRCS USdA.60
b
fBulk density (ρ ) high = 1.92 metric ton/m3 (Rafter Soil Series [NRCS USdA Web Soil Series]: See Soil Survey Staff NRCS USdA.60
b
11
12
Air, Soil and Water Research
Figure 4. National Land Cover database 2011 for the southwest USA.97 Forests are indicated by areas in green. The green pentagon symbol indicates
the location of the study area.
Soil, sediment, and leaf litter composition
The ranges of OC, N, and C/N of soils, sediments, and leaf
litter were found to be within typical ranges for forest soils in
the semiarid southwest USA63 with OC ranging from 0.1% to
9.9% (median: 0.8%) and N from 0.01% to 0.6% (median:
0.1%). The range of δ13C was −26.2 to −22.3 ‰ with a median
of −24.7 ‰ which is slightly lower than the lower range for C3
plants in arid ecosystems (Figure 5A).63 Values of δ13C at 30 cm
were generally higher than at 10 cm. The range of δ15N was
−4.8 to +6.2 ‰, with a median of +1.3 ‰ (Figure 5B). The
C/N (mass) ratio ranged from 11 to 33 with a median of 17.5.
As expected, OC and N were linearly related, as soil N and C
cycles are typically closely coupled and controlled by microbial
communities.98,99
The two watersheds studied were significantly different with
respect to all parameters measured. Values from HBSN samples
were higher in OC, N, C/N, and lower in δ15N and δ13C than
LBSO, and C/N plotted against δ13C and δ15N shows clear
groupings for each watershed (Figure 5; Table 1). Depth was not
generally a significant factor with the exception of δ13C in
HBSN (0.5 ‰ difference, 10 cm < 30 cm) and δ15N in LBSO
where, contrary to expectations,80,81 they were significantly
higher at 10 cm than at 30 cm depth. The single hillslope sample
from LBSO had values of δ13C, δ15N, and C/N intermediate
between those of in-channel sediments from LBSO and HBSN.
Leaf litter was primarily oak leaves though some pine needles
and twigs were present. Leaf litter (and the ash derived from it)
was of interest because it represents one of the possible sources of
OC and N in captured sediments. The leaf litter was sampled at
the Upper HBSN site. δ15N of the leaf litter, −1.1 ‰, was near
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the median for HBSN sediment samples. It had the highest OC,
16.8%, and N, 0.6%, and the lowest δ13C, −26.2 ‰, which is near
the middle of the typical range for C3 plants in dry ecosystems.63
The leaf litter had one of the highest C/N values in the study,
28.7, though this is lower than the average C/N, 68, for temperate oak leaf litter.67 Three samples had C/N higher than 28.7, all
at the Upper HBSN site.
Off-channel soils, in contrast to the ECS-associated sediments, represent soil profiles unaffected by frequent flooding, seasonal inundation, and accompanying erosion/
deposition. In HBSN, the 10-cm depth off-channel sediment resembled in-channel sediments in δ13C, δ15N, and
C/N, but the 30-cm depth had higher δ13C, −23.8 ‰, δ15N,
+3.8 ‰, and lower C/N, 17.3 (Figure 5). In fact, the highest
values of δ13C and δ15N and lowest C/N in that watershed
were found off-channel at the 30-cm depth. At the HBSN
off-channel site, OC was higher at both depths than the
comparable sample in LBSO. In LBSO, 10-cm depth offchannel sediment resembled in-channel sediment except in
δ13C, −22.3 ‰. Off-channel sediment at 30-cm depth was
distinct from in-channel sediment in δ13C, −22.3 ‰ and
δ15N, +6.3 ‰, but not in C/N.
Capture of OC and N by ECS
Both OC and N at the ECS in HBSN were higher (by a factor
of 2 or more at 10 cm, and a factor of 10 or more at 30 cm) than
in off-channel samples (Figure 5; Table 1). Values of N followed a similar pattern at LBSO. However, in-channel OC
values in LBSO were not as readily distinguishable from offchannel values, especially at the 10-cm depth.
A
-22.0
Leaf Li er - HBSN
-22.5
Upper HBSN
-23.0
Middle HBSN
δ13 C (‰)
-23.5
Off-Channel HBSN
-24.0
Upper LBSO
-24.5
Hillslope LBSO
-25.0
0.03
0.03
FRACTION BY
WEIGHT
MEDIAN OC WHOLE
SAMPLE IN-CHANNEL
(CCHAN)d
13
Middle LBSO
-25.5
Off-Channel LBSO
-26.5
0
20
30
40
CUBIC METERS
CUBIC METERS
B
Upper HBSN
8.0
0.0013
Middle HBSN
4.0
6.0
δ15 N (‰)
0.004
FRACTION BY
WEIGHT
SEdIMENT vOLUME
IN-CHANNEL (VOLCHAN)c
Symbols
O = 10-cm depth
Δ = 30-cm depth
Leaf Li er - HBSN
Off-Channel HBSN
2.0
Upper LBSO
0.0
Hillslope LBSO
Middle LBSO
-2.0
Off-Channel LBSO
-6.0
0
10
20
30
40
Symbols
O = 10-cm depth
Δ = 30-cm depth
Figure 5. C/N plotted against (A) δ13C and (B) δ15N. values of samples
from LBSO are shown in shades of red or orange. Those from HBSN are
blue or green. Samples taken from the 10-cm depth are indicated by
circles and 30-cm depths by triangles. Censored data are not shown
except for the off-channel LBSO 30-cm sample. Its C/N is imprecise
because of a below-method-detection-limit N measurement, but it is
plotted to show the magnitude of δ13C and δ15N relative to other samples.
25
52
C/N
Abbreviations: ECS, erosion control structures; OC, organic carbon.
aFrom Rafter Soil Series (NRCS USdA Web Soil Series): See Soil Survey Staff NRCS USdA.60
bFrom Norman and Niraula.56
cFrom Table 2.
dFrom Table 1.
0.5
1.3
210
1000
Error
1710
35952308
Estimate
kILOGRAMS PER
CUBIC METER
2.6
1.0
HBSN indicates higher burn severity newer; LBSO, lower burn severity older.
HECTARES
ECS PER HECTARE
-4.0
MEdIAN SOIL BULk
dENSITY (ρB)a
POTENTIAL NUMBER
OF ECS PER UNIT
AREA (ECSPOT)b
10
C/N
SEdIMENT vOLUME
HILLSLOPE (VOLHILL)c
MEDIAN OC WHOLE
SAMPLE HILLSLOPE
(CHILL)d
-26.0
AREA OF FOREST
IN THE SOUTHWEST
USA (FA)
Table 5. Mean and error of variables used in equation (1) to calculate the potential for ECS-sequestered organic carbon in the Southwest USA. Estimated errors are standard deviations of a normal
distribution.
Callegary et al
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A previous study of the LBSO watershed using coupled
rainfall-runoff and sediment transport modeling found that
the ECS in that watershed can retain about 178 to 242 metric
tons of sediment per year (although we expect that this rate
would decline as ECS fill over time).56 Using this range of values and equation (1), we estimated the mean potential annual
capture of OC in LBSO to be 5 to 6 metric tons, and the median
to be 3 to 4 tons (Table 3). The difference between mean and
median is caused by data outliers that skew the mean. We also
calculated the range of total potential storage in LBSO using our
estimated range of ECS storage volumes, OC content, and
estimates of bulk density.60 The range of total potential OC
storage was about 293 to 368 metric tons, corresponding to a
range of 203 to 255 metric tons per hectare of ECS (Table 4).
Although filling these structures via the simulated annual rate
would take many decades, most of the filling would likely occur
during a few postwildfire floods. The modeling for the entire
region yielded a conservative regional estimate of total sequestration potential of 0.0109 Pg of OC with a 95% confidence interval of 0.0104 to 0.0114 Pg (Table 3).
Discussion
Watershed comparison
The differences between the 2 watersheds are notable, given
their similar size and location. In HBSN, ECS extended or
constructed after the 2011 Horseshoe 2 fire filled with black
Air, Soil and Water Research
14
flood-transported postfire debris (Valer Clark, personal communication, 2016). Thus, the higher OC and N in HBSN likely
reflect the higher burn severity and more recent filling of new
ECS. Values of δ13C and δ15N in LBSO are generally higher
than in HBSN and C/N lower. Hypotheses to explain the general increase of δ13C and δ15N as C/N decreases (Figure 5)
include (1) progressive decomposition decreases C/N and
increases δ13C as original SOM is replaced by increasing
amounts of microbially processed OM over time; (2) C4 grass
growing on ECS-captured sediments and greater proportion of
C4 plants in LBSO watershed contributing C4-rich OM to
sediment; and (3) higher burn severity in HBSN, leading to
PyC-rich sediments containing proportionally more lignin than
LBSO (lignin having lower δ13C than whole wood).68,100
Hypothesis 2 can be rejected because grass is present at all
sites in both watersheds and grass straw and its combustion
products have high C/N.101 Thus, increasing the amount of
C4 OM would not be expected to lead to the observed trend
of increasing δ13C with decreasing C/N. Hypothesis 3 can
also be rejected because lignin has high C/N. Two arguments favor hypothesis 1. First, hypothesis 1 is consistent
with the ages of ECS sediment: upper layers of HBSN sediment are younger than those in LBSO. Second, HBSN leaf
litter (representing a source of OM in ECS) that is unaffected by burning is among the samples with lowest δ13C
and highest C/N.
Sequestration potential
The high OC and N contents of young (< 5 years) in-channel sediment relative to off-channel sediment at HSBN
demonstrates the potential for sequestration of SOM, at
least in the short term, of postwildfire sediment capture by
ECS. However, older (up to 35 years) in-channel sediment at
LBSO was not as readily distinguishable from off-channel
sediment, suggesting that, over the long-term, sequestered
OC in frequently-unsaturated surficial channel sediments
that are well oxygenated may come to resemble levels in
nearby soils. The amounts stored under these conditions are
lower, but long-term storage may still be significant, given
that OM and especially PyC have mean residence times in
soil on the order of decades to millennia.16 In addition,
deeper sediments upstream of ECS are more likely to remain
saturated. Moreover, when ECS are distributed at sufficiently high density across the landscape, they seldom fail
even after heavy rainfall, and significant scour and redeposition events are unlikely to occur (Valer Clark, personal communication, 2016). With this combination of physical
stability, chemical recalcitrance, and low oxygen environment, deeper PyC-rich sediments behind ECS may come to
resemble wetland soils over time, and ultimately sequester
larger amounts of OC than unsaturated soils.
Carbon capture rate, storage, and regionalization
Off-channel soils
Off-channel soils, in contrast to the ECS-associated samples,
represent soil profiles unaffected by frequent flooding, seasonal inundation, and accompanying erosion/deposition. At
the HBSN off-channel site, OC was higher at both depths
than in the comparable sample in LBSO (Figure 5), consistent with the higher proportion of C3 plants (having greater
lignin content) observed in HBSN, possibly due to greater
proportion of OM derived from C4 plants. In HBSN, the
highest values of δ13C and δ15N and lowest C/N in that
watershed were found off-channel at 30 cm depth. A possible
explanation for the high δ13C may be greater incorporation of
δ13C-enriched soil CO2 in older more microbially processed
SOM at depth,64.102 With respect to δ15N, an accompanying
increase with depth and age82,103,104 is consistent with a combination of 1) removal of soluble and gaseous N species with
low δ15N, such as ammonia and nitrate, which are readily
transported away leaving behind 15N-enriched OM105,106 and
(2) progressive stabilization by mineral particles as this
15N-enriched OM is transported downward.81 Similar explanations can be used to understand differences in δ13C, δ15N,
and C/N between the 10- and 30-cm depths at the off-channel sites with the potential addition of the Suess effect
decreasing δ13C in younger, shallower SOM and/or increasing prevalence of C4 plants over time.64,74
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The mean potential annual capture of OC estimated by combining information from the 2 study watersheds was 5 to 6 metric tons (equation (1), Table 2). The median was estimated to be
3 to 4 tons. The difference in the 2 is caused by outliers which
underscores the spatial variability of OC. This is likely due to
differences in composition of deposited sediment caused by differences in flood magnitude and watershed and burn characteristics. We also calculated the potential OC storage per hectare
with a range of about 200 to 250 metric tons per hectare. This is
similar to the range of OC stored in some wetlands.
Given the potential for OC storage by ECS suggested by
these results and the projection that the Southwest United
States will undergo more than a doubling in post fire sedimentation in the coming decades,20 estimating sequestration potential is timely. Although small compared to estimates of OC in
global fire emissions (2.2 Pg yr−1)107 and storage in soils, the
potential OC sequestration for the southwest USA is substantial in terms of ecosystem services and regional efforts to promote storage and reduce losses of carbon. If ECS are installed at
a density that stabilizes a watershed, and sediments become
saturated or semisaturated at depth, buried SOM may become
effectively sequestered. The captured OM is transformed over
time by microbial processes, reflected in lower C/N and increases
in δ13C and δ15N. This stored OM could aid in the restoration
of ecosystem services,108 especially hydrologic functioning.
Callegary et al
Water holding capacity is improved, supporting slow release of
water downstream.38,59,95,109 We suggest that maintenance of
the OC stored by ECS is dependent on quantity of recalcitrant
OM such as lignin, persistence of low-O2 saturated or semisaturated conditions in deep ECS sediments, and the areal density
of ECS. To the extent that these conditions are not met, longterm storage of OC may be less than estimated.
Conclusions and Future Research
Measurements of OC and N in 2 watersheds with ephemeral
and intermittent streams indicated that ECS retain OC within
ephemeral channels at levels that are comparable to off-channel terrestrial soils or even higher in young (<5 years) captured wildfire-derived sediments. The construction of ECS
can therefore potentially reduce transport and loss of OC and
N from wildfire-affected watersheds by capturing PyC and
other OM. In the combined data set for both watersheds,
measurements of δ13C and δ15N generally increase as C/N
decreases. This observation is best explained by progressive
decomposition as original SOM is replaced by increasing
amounts of microbially processed OM.
With respect to capture and sequestration of OC, total potential storage of OC was calculated to range from about 200 to 250
metric tons per hectare of ECS-stored sediments, similar to the
amount stored in some wetlands. The modeled value of potential
sequestration of OC in ECS over the southwestern USA lies
within a 95% confidence interval of 0.0104 to 0.0114 Pg, similar
in magnitude to the annual increase in OC in U.S. soils.110
Suggestions for future work include duplication of this
work at sites in different ecosystems and in perennial streams.
Given that sediments behind larger ECS can be 10-m thick
or more, using classical and geostatistical design to select
number of samples and horizontal and vertical locations
would improve evaluation of the magnitude and spatial variability of measured parameters. In addition, there is a need to
improve understanding of the effects of water content, redox
potential, and microbial processes on timing and extent of
OC and N transformations in ephemeral- and intermittentstream channels. Detailed data from precipitation, sediment
sampling, and stream-gage networks and knowledge of the
prefire distribution of C3 to C4 plants would aid in understanding inputs to ECS. Future work may also address the
effects of adding char and compostable material/green waste
to ECS to promote ecosystem services and sequestration of C
and N from other sources.111 It has been found that wood and
leaves from different species and with differing weathering
status are transported and degraded differently.112,113
Moreover some types of wood, depending on physical and
biochemical conditions, can persist for hundreds to thousands
of years when buried.114,115 It would thus be useful to investigate the effect of vegetation type, soil properties, burial depth,
elevation, and climate on OC storage in terms of quantity,
biogeochemical processing, and persistence.
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15
Acknowledgements
This research was conducted with support from the Land
Change Science (LCS) and Land Carbon Programs in the
Land Resource Mission Area of the U.S. Geological Survey
(USGS). Joel Sankey was supported by the USGS Ecosystems
Mission Area. The authors thank Valer Clark and Josiah
Austin for their work in installing ECS in the study area and
for providing access to their property and knowledge about
their work, Natalie Wilson (USGS) for her help in processing samples, and David Dettman and the Environmental
Isotope Laboratory at the University of Arizona for their
analyses of isotopes. They appreciate the careful peer reviews
of this manuscript provided by Alison Appling (USGS) and
those provided by Air, Soil and Water Research journal associate editor, Dr Claudia M. Rojas Alvarado and 2 anonymous
reviewers. References to commercial vendors of software
products or services are provided solely for the convenience
of users. Such references do not imply any endorsement by
the U.S. Government.
Author Contributions
JBC: experiment and system conceptualization, experimentdesign and implementation, results’ technical interpretation, and
text writing. LNM: experiment and system conceptualization,
implementation, text writing. CJE: development of system
conceptual model, implementation, results’ technical interpretation, and text writing. JBS: development of system conceptual model and numerical modeling, AY: development of
system conceptual model.
Disclaimer
This manuscript is submitted for publication with the understanding that the United States Government is authorized to
reproduce and distribute reprints for Governmental purposes.
Any use of trade, product, or firm names is for descriptive purposes only and does not imply endorsement by the U.S.
government.
ORCID iDs
James B Callegary
https://orcid.org/0000-0003-3604-0517
Laura M Norman
https://orcid.org/0000-0002-3696-8406
Christopher J Eastoe
https://orcid.org/0000-0002-0661-7613
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