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SOIL ORGANIC CARBON CONTENT OF COMPENSATORY WETLAND
MITIGATION PROJECTS IN AUBURN, WASHINGTON

by
Christina L. Stalnaker

A Thesis
Submitted in partial fulfillment
of the requirements for the degree
Master of Environmental Studies
The Evergreen State College
December 2015

©2015 by Christina L. Stalnaker. All rights reserved.

This Thesis for the Master of Environmental Studies Degree
by
Christina L. Stalnaker

has been approved for
The Evergreen State College
by

________________________
Erin Martin, Ph.D.
Member of the Faculty

________________________
Date

ABSTRACT
Soil Organic Carbon Content of Compensatory Wetland Mitigation Projects in Auburn,
Washington
Christina L. Stalnaker
Wetlands provide many essential ecosystem services, such as water quality improvement,
flood prevention, and critical species habitat. 6% of global land cover is categorized as
wetland, yet wetlands are estimated to account for 20-71% of earth’s terrestrial carbon
storage (Dahl, 2011, Reddy & DeLaune, 2008). Natural wetlands are often permitted to
be developed, and replacement wetlands are subsequently either constructed or restored
in their place to fulfill federal regulation. Laws dictate that no net loss of ecosystem
function may result due to permitting activity, therefore it is obligatory to engineer
wetlands functionally equivalent to those lost. However, the ability of wetlands to
sequester carbon is often ignored during the evaluation and monitoring of natural and
replacement mitigation wetlands. This study compares two ecosystem functions of
constructed and restored wetland mitigation sites in Auburn, Washington: (1) soil organic
carbon content and (2) species richness, and investigates if physical parameters such as
size, age, or adjacent land use affect these functions. There was no correlation between
size, age, and adjacent land use with species richness or carbon content. It was observed
that the weight percent (%) soil organic matter content (SOM) of constructed wetlands
was half that of restored (7.8 ±4.0%, 15.3 ±12.1%, respectively) (χ2(1)=9.4, p=0.002).
These values are drastically lower than % SOM in similar natural wetlands in the area
(45.5 ±34.2) (Horner, Cooke, Reinelt, Ludwa, & Chin, 2001). Soil bulk density was a
much better predictor (R2=0.584) of % SOM than soil texture (R2=0.020). The wetlands
that were excavated using heavy equipment and layered with top soil had the lowest %
SOM values, indicating that this activity is compacting soil and limiting the soil
development of these mitigation sites and capacity to store soil organic carbon. Future
mitigation projects should choose soil with low bulk density and high soil organic matter
content and avoid soil compaction during construction.

Table of Contents
1. Introduction……………………………………………………………………………..1
2. Literature Review…………………………………………………………………….....5
2.1 Wetland Functions………………………………………………...…………………5
2.2 Compensatory Wetland Mitigation………………………...………………………7
2.2.1. Local, State, and Federal Regulations………………..………...……………7
2.2.2. Mitigation Practices………………………………………………………….8
2. 3 Wetland Mitigation Project Evaluation……………………………...…......……10
2.4 Areal and Functional Loss…………………………………………..……………12
2.5 Soil Organic Carbon……………………………………………………………...14
3. Methodology…………………………………………………………………………..19
3.1 Site Selection……………………………………………………………………...19
3.2 Soil Samples……………………………………………………….…...…………20
3.3 Soil Bulk Density………………………………………………………………….21
3.4 Soil Organic Matter………………………………………………………………21
3.5 Soil Organic Carbon……………………………………………………………...22
3.6 Soil Particle Analysis……………………………………………………………..23
3.7 Spatial Analysis………………………………...........……………………………24
3.8 Statistical Analyses……………………………………………………………….24
4. Results………………………………………………………………………………....25
4.1 Physical Properties……………………………………………………………….25
4.2 % Organic Matter..……………………………………………………………….26
4.2.1 % Organic Matter by Mitigation Project Type…………...…………………26
4.2.2 % Organic Matter by Age, Area, and Ecological Score………………...…..27
4.3 Soil Bulk Density………………………………………………………………….28
4.4 Soil Texture……………………………………………………………………….30
4.5 Species Richness………………………………………………………………….32
5. Discussion……………………………………………………………………………..35
5.1 Soil Organic Matter………………………………………………………………35
5.2 Species Richness………………………………………………………………….39
iv

5.3 Conclusion………………………………………………….…………………….40
5.3.1 Implications………...…………………………………………….…….……40
5.3.2 Recommendations for Further Research……………...…........…………….42
References……………………………………………………………….……………….44

v

List of Figures

Figure 2.1 Steps of the WRP approach……………………………...…………………..11
Figure 2.2 Carbon cycling in wetlands………………………………………………….14
Figure 4.1 Mean % organic matter of wetland mitigation projects……………….…….26
Figure 4.2 Mean % organic matter by ecological score………………………………....27
Figure 4.3 % Organic matter against soil bulk density in restored wetlands……………29
Figure 4.4 % Organic matter against soil bulk density in constructed wetlands………..29
Figure 4.5 Soil texture of wetland mitigation sites……………………………………...30
Figure 4.6 % Organic matter against sand content……………...………………………31
Figure 4.7 % Organic matter against clay content……………...……………………….31
Figure 4.8 % Organic matter against silt content……………………...………………...32
Figure 4.9 Species richness by adjacent land use……………………………………….34

vi

List of Tables
Table 2.1 Estimated monetary value of wetland ecosystem services in Thurston County,
Washington………………………………………………………………………………..6
Table 2.2 Net Primary Productivity of different types of terrestrial ecosystems……..…15
Table 2.3 Estimates of global carbon burial in coastal vegetated ecosystems…………..16
Table 4.1 Physical properties of wetland mitigation sites examined in this study………25
Table 4.2 % Organic Matter and % Organic Carbon in wetland mitigation sites……….27
Table 4.3 Soil Bulk Density in g/cm3 of sampled wetland mitigation sites……………..28
Table 4.4 Vegetative species richness and dominant species of sampled wetland
mitigation sites…………………………………………………………………………...33

vii

Acknowledgements
It has been a privilege to be a part of Evergreen’s MES community. Foremost, Dr.
Erin Martin, my reader and advisor, provided encouragement and valuable feedback
throughout the entire thesis process. With her support and patience, I was driven to work
hard and produce more than I could have imagined. Her leadership, along with that of Dr.
Kevin Francis, MES Director, forged an open learning environment where we students
could explore questions about our environment in a collaborative setting.
I thank, admire, and am inspired by each one of my peers in our 2013 cohort.
Endless peer reviews, discussions, and late night seminars have opened my mind to many
new perspectives and contributed immensely to the development of this document. I also
appreciate the support of The Sustainability in Prisons Project (SPP); Kelli Bush and
Joslyn Trivett, SPP managers, thank you for the opportunity to be supported through a
Graduate Research Assistantship. The truly unique experience of working within SPP has
forever influenced the way I contemplate the many aspects of environmental
sustainability, education, and justice.
This project began in the City of Auburn’s Environmental Services Department.
Chris Anderson, Environmental Services Manager, sparked the idea to further examine
and expand upon their existing dataset. Without his backing and allowance of valuable
staff time, I would not have been able to ask or answer any of these questions. Jenna
Leonard, Environmental Planner, spent many cheerful hours extracting samples with me
in the cold, wet wetlands scattered all over Auburn. Sina Hill and Kaile Adney at The
Science Support Center provided technical savvy, field and lab equipment, and lab space.
Andres Ibarra, thank you for your love and care during this academic pursuit.
You, Thor, and Loki help me get through each day. So far, our humble marriage of two
and a half years has survived one master’s degree and two combat deployments. I’m
excited to see what we will tackle together next.

viii

1. Introduction
Wetlands are vastly complex ecosystems which deliver services that humans,
fauna, and flora rely upon for survival. They deliver an array of benefits ranging from
improving water quality, providing a habitat for a wide range of species, and preventing
floods through water storage in porous soils. Wetlands are also extremely important
global carbon sinks. While they represent less than 6% of global land cover, estimates of
its share of terrestrial carbon storage range from as low as 20 and as high as 71% (Dahl,
2011, Hossler & Bouchard, 2010, Reddy, et al., 2008). Due to the immense contribution
of their precious ecosystem services, wetlands are vital to the health of our watersheds
and our planet. Despite their necessity, natural wetlands are destroyed through
development and then compensated through artificially constructed or restored wetlands,
known as compensatory wetland mitigation.
Prior to European settlement, the conterminous United States had approximately
215 million acres of wetlands; today less than half of that natural span remains intact
(Kusler & Kentula, 1990). More recently, from 2004 to 2009, an estimated 551,870 acres
of natural wetland were lost while 489,620 acres were gained through mitigation activity
(Dahl, 2011). Because wetlands are an essential part of the landscape, the Clean Water
Act mandates no net loss of ecosystem function caused by this permitting action. As
human manipulation of wetlands persists, mitigation efforts depend chiefly upon these
permits, and it is therefore crucial to understand the impacts of these trade-offs on
wetland ecosystem function.
While the directive to mitigate these impacts originates in federal regulatory
agencies, local governments bear the brunt of permit issuance and monitoring compliance
1

and ecological success. City planners in Auburn, Washington are interested in
incorporating knowledge about successful wetland mitigation strategies to ensure they
satisfy no net loss of ecosystem function rules by assessing whether wetland mitigation
projects are meeting key ecological standards. Auburn is located in the White River
Valley of the Puget Sound Lowlands, nestled between the urban sprawl of Seattle,
Bellevue, and Tacoma and the less-disturbed foothills of the Cascade Range. Auburn’s
topography includes many natural wetlands, but its proximity to a growing metropolis
makes these wetlands subject to rapid development and intense permitting activity. In
2012 Auburn conducted a series of rapid assessments of wetland functions of 24 wetland
mitigation sites in the area with support from the Environmental Protection Agency as
part of their Wetland Mitigation Assessment Project (WMAP). From these assessments,
Auburn’s Environmental Services Department discovered that wetland mitigation efforts
achieved mixed levels of ecological success.
To supplement the findings in WMAP, this paper evaluates an additional
ecosystem service not currently considered in most wetland performance reviews: the soil
organic carbon content of restored and constructed wetlands. Global climate change
caused by rising atmospheric carbon dioxide and other greenhouse gas concentrations can
be partially mitigated by terrestrial carbon sequestration. Therefore, it is ever more
important to understand the ability of constructed and restored compensatory mitigation
wetlands to store carbon.
This paper presents an investigation of the differences between these two
mitigation project types and explores whether physical parameters that can be controlled,
such as size, age, project type (construction or restoration), and adjacent land use, can
2

impact ecological functioning of wetlands. More specifically, we test the following
hypotheses: (1) there is a difference in ecosystem function, as characterized by species
richness, between constructed and restored compensatory mitigation wetland project
types in Auburn, Washington; (2) there is a difference in soil organic matter content
between constructed and restored wetland mitigation projects in Auburn, Washington; (3)
differences in soil organic content and species richness can be explained by size, age, and
adjacent land use.
It was found that size, age, and adjacent land use were not good predictors of soil
organic carbon or species richness. While there are no differences between constructed
and restored wetlands in terms of species richness, there were significant differences
between them regarding soil organic carbon content with restored wetland soils
containing twice as much as constructed. Soil bulk density appeared to be a contributing
to these variations as high soil bulk density values correlated with lower soil organic
matter, and vice versa. This may be a result of heavy equipment use during excavation of
project sites, and the use of topsoil with lower organic matter content as fill. These
disparities illuminate the need to further study the mechanisms causing these differences,
and incorporate findings into regulations at all levels of government.
This thesis is organized in the following way. Chapter 2 (Literature Review)
reviews the legal requirements of wetland mitigation and the current systems permitting
authorities use to evaluate their success or failure. It presents a synopsis of previous
research illuminating the differences in ecosystem services provided by natural and
constructed wetlands. Measures of areal and functional loss of freshwater wetlands are

3

described, as well as the scientific principles that govern the ecosystem functions of
freshwater wetlands.
Chapter 3 (Methodology) details the methods used to test the hypotheses. Study
area, research design, and statistical analyses are described. Chapter 4 (Results) portrays
the results of this analysis. Chapter 5 (Discussion) interprets the results in a framework
relative to the original research question and hypotheses. This section discusses the
implications of study results for present day mitigation efforts. It offers
recommendations to permitting authorities and policy makers in regards to freshwater
wetland mitigation with an emphasis on future research possibilities.

4

2. Literature Review
This literature review begins with a summary of basic wetland functions and their
ecosystem services followed by a description of federal, state, and local regulations
which govern wetlands and wetland mitigation projects. Next, wetland construction and
restoration techniques are described with the criteria used to evaluate these mitigation
strategies. Then, estimated functional and areal loss of wetlands attributed to mitigation
permitting activity is discussed, followed by a synopsis of case studies using biological
and abiotic factors to compare natural versus mitigation wetlands. The final section
explores the relationship between the role of wetlands in global climate change and
carbon sequestration through storage of organic matter in wetland soils.
2.1 Wetland Functions
Wetlands are terrestrial ecosystems that are defined by the presence of three
unique characteristics. They are periodically or permanently inundated with water, home
to hydrophytic plants, and contain hydric soils (Cowardin, Carter, Golet, & LaRoe,
1979). Hydric soils are able to store large volumes of water which produce anaerobic
conditions (Reddy, et al, 2008). The Cowardin classification system of wetlands further
divide wetlands into classes or subsystems according to their hydroperiod and
predominant vegetative cover. In this study, freshwater non-tidal palustrine systems that
are predominantly covered with emergent and scrub-shrub vegetation are considered
(Cowardin, et al., 1979). The unique conditions in which wetlands exist account for their
ability to provide a wide variety of essential ecosystem services.
Programs use different techniques to evaluate ecosystem services and functional
success of wetlands and wetland mitigation sites. In order to describe functional success,
5

it is important to understand functional qualities of natural wetlands. Appendix A
displays Puget Sound Water Quality Wetland Preservation Program’s list of 11 wetland
function/value indicators. This program uses these indicators as criteria to select viable
wetlands for preservation to compensate for development. Functional descriptions
include: wildlife habitat support and biodiversity; floodwater, sedimentation and erosion
control; nutrient/pollutant entrapment & assimilation; water flow; and several cultural
values, such as recreational and educational opportunities (Washington State Department
of Ecology, 1988).
Though it is quite difficult to put an absolute monetary value on ecosystem
services, economists have estimated how much they could be worth by comparing them
to man-made systems. For example, to determine the value of waste treatment one could
compare the capital and operating cost of a local waste water treatment plant to process
the same volume of water (Flores, Batker, Milliren, Harrison-Cox, 2012). Table 2.1
shows the high and low estimates in dollars per acre of a recent study of the value of
wetland ecosystems in Thurston County, Washington.
Table 2.1 Estimated monetary value of wetland ecosystem services in Thurston County,
Washington. Recreated from Flores et al., 2012.
Ecosystem Service
Low Value ($ per acre)
Aesthetic and Recreational
$1.67

High Value ($ per acre)
$4,641.41

Disturbance Regulation

$18.35

$8,578.76

Food Provision

$63.40

$9,372.90

Gas and Climate Regulation

$1.79

$774.40

Habitat Refuge and Nursery

$99.76

$13,560.51

$2,816.44

$2,816.44

Waste Treatment

$76.39

$19,116.50

Water Regulation

$148.48

$17,351

Water Supply

$10.01

$33,969.02

$3,236.29

$110,180

Raw Materials

Total

6

2.2 Compensatory Wetland Mitigation
2.2.1. Local, State, and Federal Regulations
When a land owner wishes to dredge, fill, or otherwise adversely impact an
existing wetland on their property, in the United States, they are required by federal law
to receive a permit from the US Army Corps of Engineers. First, applicants must show
why they cannot avoid impacting the wetland by modifying their construction plans or
using an alternative location. Then, if the impacts are proven to be unavoidable within
reason, they must submit a compensatory wetland mitigation plan (Environmental
Protection Agency, 1972). In the last 5 years, over 56,400 written authorization were
issued by the Corps, with more than 5,600 of them requiring compensatory mitigation in
the United States (Institute for Water Resources, 2015).
Prior to a ruling on wetland mitigation in 2008, compensation was established by
using mitigation ratios calculated from areal extent. For example, given a 2:1 ratio, if 1
acre of freshwater marsh was filled, 2 acres of wetland would have to be created or
restored in an alternate location, preferably on site. However, the 2008 Federal Mitigation
Rule, emphasizes that the goal of mitigation was to achieve no net loss of ecosystem
function, abandoning mitigation ratio requirements in favor of using a watershed
perspective and equivalencies to the ecosystem functions (Title 33, 2008). Mirroring this
requirement in Washington State, permits must indicate compensation in the form of a
replacement wetland (restored or constructed) that delivers the same ecosystem function
in accordance with RCW Title 90 Chapter 90.84 (Washington State Legislature, 1998).

7

The City of Auburn, Washington’s Municipal Code also incorporates
compensatory wetland mitigation in its regulations. They define wetlands as a critical
area which performs important ecosystem functions, yet is environmentally sensitive.
Auburn Municipal Code 16.10.010 states (2015):
The primary goals of wetland regulation are to avoid adverse
effects to wetlands; to achieve no net loss of wetland function and value –
acreage may also be considered in achieving the overall goal; to provide
levels of protection that reflect the sensitivity of individual wetlands and
the intensity of proposed land uses; and to restore and/or enhance existing
wetlands, where possible.
The Auburn Environmental Services Department is responsible for enforcing,
monitoring, and validating wetland mitigation action within city limits.
2.2.2. Mitigation Practices
As previously mentioned, there are two types of wetland mitigation actions that
can be taken: construction or restoration. Permit applicants indicate in their mitigation
plan whether they will be conducting a construction or restoration project. Wetland
construction establishes a new wetland ecosystem where none previously existed. This is
accomplished through influencing hydrology by grading, digging, and excavation and
then establishing vegetative communities of hydrophytes and other native wetland
species through planting seedlings, cuttings, and natural recruitment. Wetland restoration
either re-establishes or enhances existing degraded wetlands to improve specific
ecosystem functions. This work can entail invasive species removal, native species
planting, and habitat enhancements.
An interagency publication by Washington State Department of Ecology, U.S.
Army Corps of Engineers, and U.S. Environmental Protection Agency (EPA) Region 10

8

provides guidelines for developing mitigation plans in Washington to follow from when
it is decided a wetland will be impacted to the completion of the mitigation project
(2006). The affected wetland should first be delineated by establishing the location and
boundaries and the impacted physical, chemical, and biological functions determined by
a qualified wetland professional. During site selection they recommend extensive
consideration of the source of water, soil conditions (including organic matter content
and compaction), prior and adjacent land use, wildlife species and corridors, and
vegetation. Five environmental factors for project design are outlined: water, soil,
vegetation, invasive species, and target functions.
While the guidelines recommend many soil functions to consider, such as
improving water quality and nutrient availability for plants, no mention of soil organic
carbon storage or carbon sequestration is mentioned. However, the authors do
recommend salvaging topsoil from the impacted site- a practice which was not done in
any of the 24 mitigation projects studied. They also strongly advocate consideration of
using organic amendments when this is not possible, or when invasive species dominate
the source, noting the importance of organic matter for vegetative establishment and
nutrient cycling. Guidance for vegetation and species diversity include examination of
nearby seed banks in soils as seeds from adjacent lands often colonize mitigation sites.
Additionally, planting plans should incorporate a variety of appropriate species to support
biodiversity and dynamic wildlife habitats (Washington State Department of Ecology, et
al, 2006).

9

2. 3 Wetland Mitigation Project Evaluation
Zedler (1996) offers a complex view of constructing wetlands. She asserts that
oversimplified evaluations of ecosystem function paired with little to no enforcement of
stated performance standards does not properly address the complex nature of how
ecosystems operate. She criticizes wetland mitigation strategies for failing to adequately
address basic ecological principles of succession, habitat connectivity and distribution of
wetlands within entire watersheds, and the effects of hydrogeological and climate
changes on biological assemblages which are still poorly understood. Illustrating how
monumental a task of creating an entirely new ecosystem is, she makes a salient analogy
to issues faced reintroducing a single species to habitat, “Recent attempts to reintroduce a
single species of rare plants to their historic habitats (Falk et al., in press) show how
difficult it is to return even a single species to an ecosystem- the plant’s environmental
requirements may no longer be present; its pollinators may be absent; the small-scale
disturbances required for recruitment may be lacking; and exotic species may invade the
transplantation site and resist eradication efforts. Replacing an entire ecosystem
multiplies the difficulties (pg. 34).”
Given this caveat, administrators are applying performance measures to evaluate
whether mitigation efforts are successful. Guidelines written by Washington State
Department of Ecology provide target roles for water, soil, and vegetation development
in wetland mitigation plans. In order to feature tangible objectives, each performance
standard should describe the specific mitigation goal in terms of qualitative indicators,
quantitative attributes, specific actions accomplished, time-oriented benchmarks, and
geographic location of monitored indicator (Washington State Department of Ecology,

10

U.S. Army Corps of Engineers Seattle District, & U.S. Environmental Protection Agency
Region 10, 2006).
In order for functional
data and analysis obtained
through mitigation research to be
useful, land managers must be
able to incorporate it into
management decisions. The EPA
Wetland Research Program
(WRP) published An Approach to
Improving Decision Making in
Wetland Restoration and
Creation in 1992 (Kentula, et al)
in which they designed an
approach that uses a series of
systematic feedback loops to
incorporate experience and
lessons learned from previously
constructed wetland mitigation

Figure 2.1 Steps of the WRP Approach for using quantitative
information to support decision making (Kentula, et al, 1992,
pg 4).

sites and monitoring data to better inform future wetland management decisions. Figure
2.1 depicts WRP’s model to continuously reintegrate new monitoring data and
evaluations from wetland mitigation sites back into decision making processes (pg. 4).
Additionally, WRP’s approach uses two evaluation forms for monitoring and assessing
11

constructed wetlands. The first form is used to conduct an initial assessment of
conditions immediately after wetland construction and the second form is intended for
continuous monitoring of mitigation sites. Standard use of these, or other locally adopted
evaluation tools, allows for consistent evaluation of wetland mitigation throughout time
and makes it possible for policymakers and researchers alike to make broad comparisons
across many different areas of concern.
2.4 Areal and Functional Loss
Many studies over the course of the last few decades support Zedler’s suggestion
that wetland creation is much more complex than Section 404 permitting requires.
Ecosystem complexity, coupled with lax compliance monitoring for wetland mitigation
permit requirements has resulted in a loss of wetland ecosystems in terms of both areal
extent and function (Turner, et al., 2001). These mitigation programs have shown high
rates of failure, falling short of no net loss goals (Robb, 2002, Brown & Veneman, 2001,
Turner, et al., 2001).
Moreno-Mateos Power, Comín, & Yockteng completed a thorough examination
of ecosystem recovery (2012). They compiled data from 124 articles assessing biological
and biogeochemical recovery of restored and created wetlands of all types from around
the globe. These wetlands were compared to nearby natural reference sites and captured
data for 14 constructed sites as old as 100 years. Biological recovery in terms of species
richness and abundance averaged 77% after 50-100 years, whereas the biogeochemical
functions of nitrogen, carbon, and phosphorus cycling and storage reached only 74% and
consistently showed a time lag behind biological recovery. Their study also found that

12

inland depressional wetlands exhibited slower recovery trajectories than riverine or tidal
wetlands. 50 years after construction these wetlands have not reached reference
conditions, and the authors conclude that they may never achieve those biological or
biogeochemical goals.
Turner, Redmond, & Zeller’s meta-analysis examined eight studies of wetland
mitigation projects. They calculated a mere 21 percent of compensatory wetlands
delivered ecosystem services equivalent to those lost. This meta-analysis included
studies from WA in 1994, 1998 and 2000 which revealed a range of permit percent
compliance (21-53%) with stated mitigation goals in WA. Overall, permitting activity
resulted in a major net loss of 80% wetland ecosystems in direct conflict with local, state,
and federal no net loss mandates. These authors attribute a majority of failure to poor
administration and recommend incorporating deadlines, ecological criteria, compliance
monitoring, and mitigation programs implemented at watershed scales to improve
ecological viability (2001).
In 2001, Brown and Veneman conducted a systematic review of compliance with
stated mitigation goals for 319 permitted projects spanning 44 towns in the
Commonwealth of Massachusetts. Over half of the mitigation sites did not comply with
regulatory standards with 21.9% of failed mitigation projects never moving past the
planning stage. Of completed projects, none of the plant community structures compared
to natural, reference wetland sites, with lower biodiversity in the mitigation sites. Given
the lack of proper hydrophitic and native vegetation, the mitigation sites also fell short in
providing adequate wildlife habitat for amphibians, mammals, and birds. Similar to
Robb’s (2002) study of wetland mitigation in Indiana, which calculated a 71% failure rate
13

for palustrine forested wetlands, Brown, et al. discovered that none of the forested
wetland projects were successfully constructed. This is particularly concerning since just
over one-fourth of wetland development permits in MA were on forested wetlands.
2.5 Soil Organic Carbon
Wetlands receive carbon from three sources: 1) dissolved inorganic carbon 2)
organic carbon inputs from terrestrial sediment and particles and 3) from the carbon
dioxide found in the atmosphere. As these compounds move through the system and are
coupled with inorganic nutrients, wetland vegetation undergoes gross primary
production. Biomass produced may then be consumed and respired by animals and
microbes, outgassed into the atmosphere, or buried in the wetland's sediments (Figure
2.2) Carbon sequestration in wetlands occurs when this carbon is buried for long-term
storage in the wetland sediments (Hopkinson, Cai, & Hu, 2012). Because of the unique
hyrdric soils in wetlands, these ecosystems store much higher amounts of soil organic
carbon compared to other terrestrial ecosystems (Table 2.2).

Figure 2.2 Carbon cycling in wetlands. (Reddy, et al., 2008).

14

Table 2.2 Net Primary Productivity of different types of terrestrial ecosystems.
2

Ecosystem

Net Primary Productivity (g C/m year)

Desert

80

Boreal Forest

430

Tropical Forest

620-800

Temperate Forest

65

Wetland

1,300

Cultivated land

760

Tundra

130

Hopkinson and authors (2012) conducted a study of carbon sequestration in
coastal wetland systems. They analyzed different measurements of this potential
throughout the globe in order to quantify the rate at which this global sink is diminishing.
In their meta-analysis they found that there is very large range of estimates, some as high
as an order of magnitude in difference. This is due to the variation of carbon burial
between different systems and the difficulty in estimating the areal extent of these
wetlands. In order to quantify the rate of carbon sequestration of wetlands, they use the
average of individual reports. They then measured the rate of carbon over a given area.
According to their estimates (Table 2.3) mangroves bury 31.0-45.2 Tg C yr-1, intertidal
marshes bury 11.4-87.0 Tg C yr-1, and seagrass beds bury 24.4-82.8 Tg C yr-1 in
sediments (Hopkinson, et al., 2012). This study provides a clear picture of the potential of
coastal systems to sequester carbon, but offers no insight into the capacity of freshwater
systems to do so.

15

Table 2.3 Estimates of global carbon burial in coastal vegetated ecosystems. Recreated from
Hopkinson, et al., 2012.
System

Global area
(km2)

Carbon burial rate (g
C m−2 yr−1)

Global carbon burial
(Tg C yr−1)

Mangroves

138,000–200,000

226 ±39

31.0–45.2

Intertidal marshes

200,000–400,000

57 ±6 – 218 ±24

11.4–87.0

Seagrass beds

177,000–600,000

138 ±38

24.4–82.8

Global carbon sequestration estimates for temperate freshwater wetland
communities are even more difficult to obtain. There are several more subcategories of
freshwater wetlands than coastal wetlands. These various wetland types have not been
studied in as much detail as their coastal counterparts. A 2012 study by Bernal and
Mitsch highlighted differences in carbon sequestration potential by community type in
Ohio. Bernal, et al. found that, "the depressional wetland communities sequestered 317
±93 g C m-2 yr-1, more than the riverine communities that sequestered 140 ±16 g C m-2 yr1

... These differences in sequestration suggest the importance of addressing wetland

types and communities in more detail when assessing the role of wetlands as carbon
sequestering systems in global carbon budgets (2012)."
Bernal and authors’ conclusion reemphasizes the need to conduct thorough
investigation and comparison of carbon sequestration in different wetlands around the
globe in order to understand their overall impact on the global carbon cycle. One such
detailed analysis is that of carbon sequestration in the salt marsh Doñana Wetlands of
southern Spain. This study incorporated estimations and direct measurements of primary
production by vegetation, burial of organic carbon in sediments, and outgassing of carbon
dioxide in order to measure the potential of the Doñana Wetlands as a carbon sink.

16

Through their detailed analysis, they were able to determine that although the water
bodies were a net annual source of carbon dioxide, outgassing of C was still six times
lower than the net primary production of the system which would indicate that the
wetlands act as a carbon sink assuming no other losses (like lateral export) (Morris,
Flecha, Figuerola, Costas, Navarro, Ruiz, Rodiguez, & Huertas, 2013).
While it is key to understand the dynamics of soil organic carbon storage and
carbon sequestration of natural systems, it is also important to acknowledge the
differences between constructed and restored systems compared to natural ones. In China
researchers investigated the carbon sequestration potential of wetlands on a national scale
in order to inform protection and restoration measurements aimed at preserving or
increasing this capability of wetlands (Xiaonan, Xiaoke, Lu, and Zhiyun, 2008). They
estimated carbon sequestration potential by using sedimentation rates and total organic
carbon content of soil by a given distribution area. In their study they found a significant
loss of soil carbon, 2,769.7 Gg C, due to the reclamation of lakes and swamps, but
through wetland restoration they found carbon sequestration potential to be as high as
6.57 Gg C a-1 from 2006-2010 (Xiaonan, et al., 2008). Contrary to this study's optimism,
in 2012 Moreno-Mateos, et al. also evaluated the structural and functional loss in restored
wetlands and found that on average, after 50 to 100 years, restored wetlands recovered
only 74% of their biogeochemical functioning in terms of nitrogen and carbon cycling
potential.
It has been shown that wetlands of all types throughout the globe perform the
crucial job of sequestering carbon dioxide from the atmosphere. However, we do not
completely understand the differences in overall ability for specific wetland types,
17

particularly in differentiating between the potential of separate freshwater wetland types.
Further, it is evident that artificially constructed and restored wetlands do not perform as
well as their natural counterparts. Given these gaps in knowledge and importance of
carbon sequestration, it is essential to closely examine the soil dynamics of freshwater
wetland mitigation projects.

18

3. Methodology
3.1 Site Selection
The City of Auburn’s 2012 Wetland Mitigation Assessment Project (WMAP)
evaluated ecological success and regulatory compliance of selected mitigation wetlands
within city jurisdiction and Duwamish/Green Watershed Resources Inventory Area
(WRIA) #9. To select sites for WMAP, city staff reviewed mitigation project files of all
known projects in WRIA #9 that provided compensation for wetland impacts occurring in
WRIA #9. For comparison, only projects involving the construction, restoration, or
enhancement of freshwater, emergent depressional wetlands located on the Green River
Valley Floor were considered (Appendix B). Projects lacking mitigation plan documents,
planting plans, construction plans, performance standards, as-built reports and/or
monitoring reports were excluded from WMAP, resulting in a final list of 24 mitigation
sites (Soundview Consultants LLC, 2012).
Details reported from WMAP on these 26 wetlands were examined for this study,
including data describing mitigation type, site age, site area, species richness, dominant
species, vegetative coverage, and overall ecological success statistics. Wetland specialists
visited each wetland site and recorded all vegetative species present and noted the
dominant species, categorized by vegetation type: aquatic, herbaceous, shrub, or tree.
Ecological success was determined by best professional judgement of the wetland
specialist and labeled on a scale of 1, 3, or 5 with 1 being the lowest performing wetland
and 5 being the best performing.

19

A subset of constructed and restored wetlands was chosen to collect supplemental
data on soil bulk density, texture, and organic matter content. A list of 5 constructed and
9 restored sites of interest was provided to City staff with a request to access each site
and collect soil samples. Some mitigation sites are located on privately owned land, and
the ability to access the sites for continued sampling depended upon whether
conservation easements which allow city employees access to the site for continued
monitoring were still in place at the time of this study. The list was narrowed down to 4
constructed and 4 restored sites were chosen for which there are established conservation
easements. However, only 3 of the 4 constructed wetland sites were accessible; the 4th
site had a chain-linked fence surrounding it with and a gate welded shut, preventing any
access to the site.
3.2 Soil Samples
Depending on size, 5 to 10 soil cores were collected every 50 meters along a
transect parallel to the wetland topographic contour (U.S. EPA, 2008). Some transects
intersected areas of dense vegetation, which were cautiously navigated and/or avoided to
prevent any adverse impact. The majority of soil organic matter accumulates in the root
zone which occurs at 0-30 cm depth (Reddy, Clark, DeLaune, & Kongchum, 2013). To
sample within this zone, a nickel-plated steel soil corer was used to extract intact vertical
core samples to 30 cm depth and 2 cm in diameter. Coordinates were logged using a
Garmin eTrex Vista. Soil compaction frequently occurred due to heavily saturated soil
condition and the small diameter of soil corer. Each soil core was measured with a
standard metric ruler to obtain core length (l). To calculate compaction (c) the following
equation was used:
20

(Equation 3.1) 𝑐 =

30 𝑐𝑚−𝑙 𝑐𝑚
30 𝑐𝑚

∗ 100%

Soil cores were collected at each point until a sample with <50% compaction was
obtained and recorded (overall soil compaction for all soil samples averaged 28%)(Ellert,
Janzen, VandenBygaart, & Bremer, 2008). Each sample was then wrapped with lowdensity polyethylene and placed in a polyethylene zip sealed bag (Ellert, et al., 2008).
Samples were stored in a cooler for transportation to the laboratory and then kept at 4ºC
until ready for analysis, which occurred within a time frame of 6 to 14 weeks (Ellert, et
al., 2008).
3.3 Soil Bulk Density
Soil cores were divided into 2 segments: 1)0-15 cm and 2)15-30 cm depths to
perform laboratory analysis on soil samples (Badiou, McDougal, Pennock, & Clark,
2011). The first property analyzed was soil bulk density, or the ratio of solid, dry mass to
total soil volume (Reddy, et al., 2013). Volume of soil cores was calculated as follows:
(Equation 3.2) 𝑣𝑜𝑙𝑢𝑚𝑒 = 𝜋(1 𝑐𝑚2 )30 𝑐𝑚
After oven-drying samples at 70ºC for 72 hours, each sample was weighed and soil bulk
density was calculated using the following equation (Reddy, et al., 2013):
(Equation 3.3) 𝑏𝑢𝑙𝑘 𝑑𝑒𝑛𝑠𝑖𝑡𝑦 =

𝑚𝑎𝑠𝑠 𝑑𝑟𝑦 𝑤𝑒𝑖𝑔ℎ𝑡 (𝑔)
𝑣𝑜𝑙𝑢𝑚𝑒 (𝑐𝑚3 )

3.4 Soil Organic Matter
Soil organic matter (SOM) was estimated by weight loss-on-ignition (LOI)
methodology (Dean, 1974, Heiri, Lotter, & Lemcke, 2001, Skjemstad & Baldock, 2008,
21

Wright, Wang, Reddy, 2008, Massello, 2013). Oven-dried samples were milled using a
mortar and pestle, sifted through a 2 mm sieve, and then 5 +/- 1 g of each sieved sample
(< 2 mm) were oven-dried overnight at 70°C (Skjemstad, et al., 2008). 15 mL crucibles
with lids were combusted in a high temperature muffle furnace at 550°C for 5 hours to
remove any contaminants (Massello, 2013). Each crucible was allowed to cool in a
desiccator, and then weighed, with the final weight referred to as WC. After drying soil
and crucibles, samples were placed in a crucible and the dry weight (W60) recorded.
Crucibles containing soils were placed in the muffle furnace and heated at 550°C for 2
hours (Wright, et al., 2008). Samples were allowed to cool in the furnace, and then each
was individually removed and placed on balance to record weight (W550). % Soil Organic
Matter (% OM) was calculated as follows, using the equation from Skjemstad, et al.,
2008:
(Equation 3.4) % 𝑂𝑀 =

𝑊550 −𝑊𝐶
𝑥100
𝑊60 −𝑊𝐶

3.5 Soil Organic Carbon
Soil organic carbon comprises only a portion of soil organic matter content. There
is a wide range of estimated values to calculate this amount, however, as not to
overestimate the amount of carbon contained in the samples, the most conservative ratio
of 1:2 was used as recommended by Pribyl (2010). Therefore, soil organic carbon was
estimated using the following calculation:
(Equation 3.5) % 𝑆𝑜𝑖𝑙 𝑂𝑟𝑔𝑎𝑛𝑖𝑐 𝐶𝑎𝑟𝑏𝑜𝑛 =

% 𝑂𝑀
2

22

3.6 Soil Particle Analysis
The Bouyoucos hydrometer method was used to determine soil texture (% silt, %
sand, and % clay). The remaining oven-dried soil was ground with a mortar and pestle
and sieved through a 2mm sieve. A 50 g sample (Sg) for each wetland and depth was
prepared for analysis by soaking it in 100 mL of 1 M sodium hexametaphosphate
dispersing solution, which was mixed vigorously with 250 mL deionized water. The
samples were then placed in an electric mixer for five minutes. The resultant solution was
poured into a 1,000 mL graduated cylinder which was then filled to 1,000 mL with
deionized water. Measurements were also recorded for a blank cylinder with 100 mL 1M
dispersant solution and 900 mL deionized water (RB) (Bouyoucos, 1962, Massello,
2013).
Using a wooden plunger, the samples were further dispersed. A timer was started
as soon as the plunger was removed, and hydrometer gently lowered into solution. The
hydrometer has a scale read from the numbered mark which intersects the meniscus of
the solution at specific time intervals. Hydrometer readings and temperature were
measured at 40 seconds (R40S) and 2 hours (R2H). A blank reading (RB) was taken to
calibrate the hydrometer used in measurement. Soil particles were analyzed by
calculating the following, where % sand is the portion of sand in the sample, % clay is
the portion of clay, and % silt is the portion of silt (Bouyoucos, 1962, Massello, 2013):
100

(Equation 3.6) % 𝑠𝑎𝑛𝑑 = 100 − (𝑅40𝑆 − 𝑅𝐵 ) ∗ ( 𝑆 )
𝑔

100

(Equation 3.7) % 𝑐𝑙𝑎𝑦 = (𝑅2𝐻 − 𝑅𝐵 ) ∗ ( 𝑆 )
𝑔

23

(Equation 3.8) % 𝑠𝑖𝑙𝑡 = 100 − (% 𝑠𝑎𝑛𝑑 + % 𝑐𝑙𝑎𝑦)
3.7 Spatial Analysis
Geospatial analysis was completed using software and World Imagery base map
provided by Esri ArcGIS10.3 (Esri, DigitalGlobe, GeoEye, Earthstar Geographics,
CNES/Airbus DS, USDA, USGS, AEX, Getmapping, Aerogrid, IGN, IGP, swisstopo,
and the GIS User Community, 2015). Adjacent Land Use for each mitigation site was
determined by visual analysis from imagery and city parcel data obtained from Auburn’s
GIS database (City of Auburn, 2015). Each adjacent land use type along the border of a
wetland mitigation project site location was measured. The type with the highest
percentage was assigned as the primary adjacent land use.
3.8 Statistical Analyses
All statistical analyses was conducted using JMP Pro 11.2.0 statistical software.
Both species richness and soil organic matter data were evaluated using the Shapiro-Wilk
test for normality and were found to be non-normal, however, they met the assumptions
to compare means using a Kruskal-Wallis test by ranks. The mean % OM of restored and
constructed wetlands, mean % OM based on ecological score, species richness by project
type and adjacent land use, and mean soil bulk density by project type were compared
using this method. Simple linear regression was used to determine predictability of %
OM and species richness by size and age, and % OM by soil texture. Cubic linear
regressions were calculated to predict % OM by soil bulk density in restored and
constructed wetlands.

24

4. Results
4.1 Physical Properties
Physical properties of the wetlands sampled for soil analysis, including
information on project type, age, area, and adjacent land use are summarized in Table
4.1. Ages of wetlands ranged from 5-18 years and project site areas ranged from 14,374
to 1,698,840 sq. ft. with respective means of 12.8 years and 487,882 sq. ft. It is worth
noting that the rage of ages and sizes of the restored wetlands varied considerably more
than that of the constructed wetlands. Land uses adjacent to all mitigation sites were
classified as vacant (8), industrial (8), road (5), or mitigation site (3). Also, industrial sites
were found near some of the constructed wetlands, whereas none of the restored wetlands
had industrial as an adjacent land use category. While these wetlands are not paired
replicates due to their differences in physical properties, and therefore do not provide
exact comparisons, however, they are representative of mitigation projects designed to
construct or restore palustrine wetlands within the same municipality.
Table 4.1 Physical properties of wetland mitigation sites examined in this study.

Project #

Wetland

Project Type

Age
(years)

Area
(sq ft)

Ecological
Score

Adjacent Land Use

92-0055A

A

Restoration

18

1,158,260

5

Vacant

92-0055B
97-0013
07-0001
00-0038E
04-0013
97-0063B

B
C
D
E
F
G

Restoration
Restoration
Restoration
Construction
Construction
Construction

18
6
5
9
8
13

1,373,447
429,066
115,434
178,596
200,376

3
5
5
5
3
3

Vacant
Road
Mitigation Site
Road
Industrial
Industrial

25

4.2 % Organic Matter
4.2.1 % Organic Matter by Mitigation Project Type
% OM values ranged from 1.4 to 49.2% in restored wetlands and 3.5 to 21.1% in
constructed wetlands (Table 4.2). In all cases, samples at greater depth (15-30 cm) had
lower means than those sampled at 0-15 cm (Figure 4.1). The mean of % OM in
constructed wetlands (7.8 ±4.0) is nearly half the mean in restored wetlands (15.3 ±12.1)
(Figure 4.2). Kruskal-Wallis test showed that there was a statistically significant
difference in % OM between constructed and restored wetland mitigation sites
(χ2(1)=9.4, p=0.002) with a mean rank score of 42.1 for constructed wetlands and 62.0

40

40

35

35

30

30

% Organic Matter

% Organic Matter

for restored wetlands.

25
20
15

25
20
15

10

10

5

5

0

0
A

B

C

Restored Wetlands
0-15 cm

15-30 cm

D

E

F

G

Constructed Wetlands
0-15 cm

15-30 cm

Figure 4.1 Mean % Organic Matter of constructed and restored wetland mitigation sites with error bars
constructed 1 Standard Error from the mean.

26

Table 4.2 % Organic Matter and % Organic Carbon in sampled wetland mitigation sites.
Wetland

Project #

Project
Type

𝒏 (soil
cores)

Depth
(cm)

𝒙±𝛔
(% OM)

Min
(% OM)

Max
(% OM)

A

92-0055A

Restoration

10

B

92-0055B

Restoration

10

C

97-0013

Restoration

8

D

07-0001

Restoration

9

E

00-0038E

Construction

5

F

04-0013

Construction

5

G

97-0063B

Construction

8

0-15
15-30
0-15
15-30
0-15
15-30
0-15
15-30
0-15
15-30
0-15
15-30
0-15
15-30

9.7 ±1.6
8.6 ±2.5
6.3 ±2.7
3.8 ±2.3
23.9 ±5.0
17.4 ±8.7
34.7 ±9.2
22.6 ±14.8
10.4 ±1.8
8.3 ±2.7
13.1 ±5.8
8.5 ±3.1
5.9 ±0.41
3.9 ±0.3

8.0
6.2
3.5
1.4
16.5
7.9
20.2
4.4
8.5
3.7
7.5
5.8
5.5
3.5

13.3
13.5
11.0
7.7
30.4
31.2
46.7
49.2
12.9
10.4
21.1
13.4
6.5
4.3

%
Organic
Carbon
4.9
4.3
3.2
1.9
12.0
8.7
17.4
11.3
5.2
4.2
6.6
4.3
3.0
2.0

4.2.2 % Organic Matter by Age, Area, and Ecological Score
Separate simple linear regressions were calculated to predict % OM by age or
area, and no significant regression equation was found. Similarly, no relationship was
established between Ecological score of all 24 wetland mitigation projects and age or
area. However, in the Kruskal-Wallis test found that those wetlands with a high
ecological score of 5 did have statistically
higher % OM means (15.3 ±12.1) than
those with a moderate ecological score of
3 (7.8 ±3.9) with a mean rank score of
31.0 for wetlands with a score of 3 and
73.1 for wetlands with a score of 5
(χ2(1)=46.7, p=0.0001) (no wetlands with
a low score of 1 were sampled) (Figure
4.2).

Figure 4.2 Mean % Organic Matter for wetlands by
ecological score shown with error bars constructed 1
Standard Error from the mean.

27

4.3 Soil Bulk Density
Soil bulk density of restored wetlands ranged from 0.07 to 0.59 g/cm3 with a
mean of .30 ±.13. Values for soil bulk density of constructed wetlands ranged from 0.09
to 0.65 with a mean of .32 ±.13 (Table 4.3). A strong negative correlation between % OM
and soil bulk density was observed (Figure 4.4). A cubic regression was calculated to
predict % OM based on soil bulk density (g/cm3). A significant regression equation was
found with an R2 of 0.584 (F=49.6, DF=3, p<0.0001) where x = soil bulk density:
(Equation 4.1) % OM = 54.66 – 300.6*x + 644.7*x2 - 475.48*x3
No significant difference was found when comparing the mean soil bulk density
of constructed and restored wetlands. However, when separate cubic regressions for
constructed and restored wetlands were calculated to predict % OM by soil bulk density,
the regression line for restored wetlands predicted %OM far more accurately (R2=0.727,
F=61.99, DF=3, p<0.0001) (Figure 4.3, Equation 4.2) than for constructed wetlands
(R2=0.298, F=4.53, DF=3, p<0.0003) (Figure 4.4).
(Equation 4.2) % OM = 59.87 – 302.4*x + 594.5*x2 – 412.9*x3
Table 4.3 Soil Bulk Density in g/cm3 of sampled wetland mitigation sites.
Wetland

Project #

Project Type

𝒏 (soil
cores)

Depth
(cm)

𝒙±
𝝈 (g/cm3)

Min
(g/cm3)

Max
(g/cm3)

A

92-0055A

Restoration

10

B

92-0055B

Restoration

10

C

97-0013

Restoration

8

D

07-0001

Restoration

9

E

00-0038E

Construction

5

F

04-0013

Construction

5

G

97-0063B

Construction

8

0-15
15-30
0-15
15-30
0-15
15-30
0-15
15-30
0-15
15-30
0-15
15-30
0-15
15-30

0.33 ±0.11
0.39 ±0.12
0.36 ±0.10
0.43 ±0.09
0.23 ±0.07
0.30 ±0.11
0.14 ±0.06
0.20 ±0.11
0.28 ±0.10
0.33 ±0.10
0.21 ±0.12
0.26 ±0.12
0.33 ±0.11
0.42 ±0.12

0.11
0.13
0.20
0.32
0.12
0.13
0.07
0.07
0.11
0.16
0.09
0.16
0.21
0.27

0.48
0.52
0.49
0.59
0.32
0.44
0.22
0.37
0.35
0.41
0.40
0.39
0.51
0.65

28

Figure 4.3 Cubic regression line of fit for the prediction of % Organic Matter based on
soil bulk density in g/cm3 in restored wetland mitigation sites.

Figure 4.4 Cubic regression line of fit for the prediction of % Organic Matter based
on soil bulk density in g/cm3 in constructed wetland mitigation sites.

29

4.4 Soil Texture
Soil texture of restored wetlands varied widely and was estimated to range from a
minimum 3 to a maximum of 82% sand (𝑥̅ =53, σ =29), 3 to 28% clay (𝑥̅ =11, σ =9), and
14 to 69% silt (𝑥̅ =36, σ =21). Soil texture of constructed wetlands was also highly
variable and estimated to range from a minimum 48 to a maximum of 67% sand (𝑥̅ =56,
σ =7), 6% to 15% clay (𝑥̅ =11, σ =4), and 25% to 46% silt (𝑥̅ =36, σ =21) (Figure 4.5).
Simple linear regression was calculated, and failed to predict % OM by texture. % Sand,
% clay, and % silt did not exhibit any correlation to % OM with respective R2 values of
0.011 (Figure 4.6), 0.020 (Figure 4.7), and 0.006 (Figure 4.8).

100%
90%
80%

Soil Texture

70%
60%
50%
40%
30%
20%
10%
0%
Aa

Ab

Ba

Bb

Ca

Cb

Da

Db

Ea

Eb

Fa

Fb

Ga

Gb

Wetland
%Sand

%Clay

%Silt

Figure 4.5 Estimated soil texture in sampled wetland mitigation sites shown in % sand,
% clay, and % silt. Wetlands A-D are restored and E-G are constructed; a indicates values at
0-15 cm depth and b for 15-30 cm.

30

Figure 4.6 Simple linear regression of % Organic Matter by % Sand.

Figure 4.7 Simple linear regression of % Organic Matter by % Clay.

31

Figure 4.8 Simple linear regression of % Organic Matter by % Silt.

4.5 Species Richness
Species richness was evaluated for all 24 wetland mitigation sites in the original
Auburn study. Total vegetative species richness of restored wetlands that were sampled
ranged from 18-48 species for restored wetlands with a mean of 35.5 ±14.6, and 11-17
for constructed with a mean of 13.3 ±3.2. A summary categorized by type of vegetation
with dominant species for each type is illustrated in Table 4.5; a graph and table of
species richness for all 24 wetlands in the Auburn study is located in Appendix C. There
is no significant difference in mean species richness of different mitigation project types.
Additionally, species richness is not a good predictor of % OM for these wetlands.

32

Tree

Shrub

Dominant
Species

Herbaceous

1
3

Typha latifolia,
Nuphar polysepalum

4 Populus
balsamifera

13

Salix sp.

18

Typha latifolia and
Nuphar polysepalum

B

Restoration

2

Lemna minor, Phalaris
arundinacea

5 Populus
balsamifera

19

Populus
balsamifera

21

Phalaris arundinacea
and Ranunculus repens

C

Restoration

3

Polygonum persicaria

2 Salix sp., Thuja
plicata, Picea
sitchensis

6

Salix sp., Thuja
plicata, Picea
sitchensis

D

Restoration

1
2

Glyceria occidentalis
and Deschampsia
cespitosa

3 Populus
basamifera

4

Salix sp.

E

Construction

2

Typha latifolia, Lemna
minor

2 Salix sitchensis and
Populus
basamifera

3

Salix sitchensis

F

Construction

0

0

7

Salix sp.

10

G

Construction

1

3 Salix sp.

3

Salix sp.

4

Malus fusca

Dominant
Species

Dominant
Species

Restoration

Dominant
Species

Project Type

A

Aquatic

Wetland

Table 4.4 Vegetative species richness and dominant species of sampled wetland mitigation sites.

7

Phalaris arundinacea

10

Glyceria occidentalis
and Deschampsia
cespitosa

5

Typha latifolia and
Lemna minor

Phalaris arundinacea
Carex obnupta

Adjacent land use for mitigation projects include industrial, mitigation (wetlands
adjacent to other mitigation projects), road, and vacant land use types. Species richness
for all 24 wetlands ranged from 5 to 27 species present in wetlands with industrial
adjacent land use with a mean of 11.6 ±7.2, 11 to 29 species for wetlands adjacent to
mitigation sites with a mean of 22.3 ±9.9, 12 to 30 for wetlands adjacent to roads with a
mean of 19±6.9, and 4 to 48 for vacant adjacent land use with a mean of 21.4±17.2
(Figure 4.9). These means were not statistically different.

33

Figure 4.9 Species Richness of compensatory wetland mitigation sites by adjacent land use.

34

5. Discussion
Restored wetland mitigation project sites in Auburn, WA have higher soil organic
matter content than constructed wetlands. This disparaity necessitates an examination of
differences between the two project types, which could contribute to variations in
ecosystem function with respect to soil carbon and development. To date, the published
literature only draws comparisons between constructed wetlands to natural wetlands,
restored wetlands to natural wetlands, or groups constructed and restored wetlands into
one category. This strategy does not provide insight into functional differences between
construction and restoration of wetlands. In constrast to the results presented here, a study
in North Carolina compared natural, restored, and created wetland soil organic matter
content, but the authors did not find a significant difference between constructed and
restored wetlands, and consequently reported the remainder of their results with the two
wetland types under a single category: constructed/restored (Bruland & Richardson,
2005).
5.1 Soil Organic Matter
As far as particle size distrubution and its effect on soil organic matter, the results
do not fit with conventional wisdom of soil biogeochemistry. It is widely accepted that
the capacity of soil to contain soil organic matter can be attributed to the relative
compositon of and, silt and clay (Hassink, Whitmore, & Kubát, 1997). For example, clay
particles increase surface area available in soil for organic carbon adsorption, and are
positively associated with soil organic matter (Krull, Baldock, & Skjemstad, 2001).
However, for the wetlands sampled in this study, there was no association between soil
texture and soil organic matter content(Figure 4.6, 4.7, 4.8). These wetlands have been
35

physically altered in the restoration or construction process, and some have been
excavated to influence hydrologic regimes. Because the wetland soils have not developed
naturally over time, but still undergo primary production activity and subsequent carbon
burial in the soils, the relationship between soil texture and organic matter composition
may not follow the theoretical relationship outlined above. In contrast, it could be an
artifact of the creation process.
Differences in soil organic matter were not explained by age, which indicates that
this function does not substantialy develop further with the timescales examined in this
study. These findings are consistent with a previous study in Pennsylvania that compared
constructed wetland mitigation projects from two age groups (<10 and >10 years old) to
natural reference wetlands and found that the mean % organic matter of both wetland age
groups did not vary and wetlands >10 years old contained just over 50% the amount of
organic matter than their natural counterparts (Campbell, Cole, & Brooks, 2002).
Moreno-Mateos, et al. established that biogeochemical functions of constructed and
restored wetlands achieve 74% capacity of natural wetlands, even after as much as 100
years (2012). In terms of carbon storage, they contended that they only achieved 62% of
natural wetlands after 30 years, supporting the supposition that these projects’ wetland
soils will not mature with age (Moreno-Mateos, et al., 2012). Furthermore, Hossler &
Bouchard developed a model which projects a constructed wetland would need 300 years
before it would be able to store carbon equivalent to the levels contained in a natural
wetlands, and argue for a minimum mitigation ratio of 5.1:1 in order to reduce this loss of
ecosystem function with the caution that this modeled trajectory has yet to be verified by
observation (Hossler & Bouchard, 2010).
36

Soil organic matter values are much lower than other reported values for natural
wetlands in the Puget Sound Lowlands in King County, Washington (The City of Auburn
and all wetland mitigation project sites are located in southeast King County,
Washington). Natural, palustrine wetlands were found to have a mean percent organic
matter content of 45.5 ±34.2, which is much higher than the values measured in both
constructed (𝑥 =7.8 ±4.0) and restored (𝑥̅ =15.3 ±12.1) wetland mitigation projects
(Horner, et al., 2001). Previous studies have also exhibited this disparity (Shaffer &
Ernst, 1999; Stolt, Genthner, Daniels, Groover, Nagle, & Haering, 2000; Campbell et al.,
2002). For example, in Pennsylvania, Campbell et al. estimated that constructed wetlands
store more than half the amount of organic matter (𝑥 =4.8) than natural, reference
wetlands (𝑥 =11.5), noting that soil bulk density is at least twice as high in constructed
wetlands (likely caused by compaction from heavy equipment during excavation), but do
not make a connection between compacted soils and a low percentage of soil organic
matter (2002).
Soil bulk density is another frequently used metric to explain soil organic matter
content. Generally, high soil bulk density indicates low soil organic matter and low soil
bulk density is related to high soil organic matter content (Ekwue, 1990; Aşkin &
Özdemir, 2003). Addtionally, there is an inverse relationship between soil bulk density
and porosity; less dense soil is more porous. These pores allow water to saturate the soil
and generate the anearobic conditons characteristic of wetland hydric soils, which slow
decompositon rates and are therefore able to retain soil organic matter for longer periods
of time (Krull, et al., 2001; Reddy & DeLaune, 2008). This study’s findings of a strong
negative correlation between soil bulk density and soil organic matter in wetland
37

mitigation projects (Figure 4.5, 4.6, Equation 4.1, 4.2) coincide with this concept.
(Figure 4.1). During the implementation of mitigation projects, heavy equipment is used
to excavate, grade, and fill wetlands, and the weight of this equipment can compact soils,
resulting in higher bulk densities (Shaffer et al., 1999; Stolt et al., 2000; Campbell et al.,
2002). In fact, the two wetlands that contained soils with the highest organic matter
content and lowest soil bulk densities, C & D, had mitigation plans that required the least
amount of disturbance (Table 4.2, 4.3). Wetland C did not require grading actions and
Wetland D was graded around existing mounds, whereas all other wetlands required
excavations and all had significantly lower soil organic matter. This could suggest that
the use of heavy equipment better accounts for differences in soil development than
mitigation project type. Further, excavation and grading action removed native soils of
the 3 constructed wetlands, F, G, & E, and were then covered in top soil which could
account for the higher soil bulk density, and the lower soil OM content, found in all three
of the constructed wetlands examined in this study.
When comparing soil organic matter content by ecological score, the highest
ecological score had higher average soil organic matter with a difference of 7.5%.
Although the ecological score assigned was subjective, left to the best professional
judgement of the wetland scientists conducting the wetland rapid assessment, the value
would seem to reflect this aspect of soil development. Although it would not be prudent
to use this measure as a replacement to determining soil organic matter development, it is
advantageous to have an alternative to estimating soil health, since obtaining accurate
measurements of soil organic matter while in the monitoring phase of mitigation projects
would be limited by time, and may be impractical.
38

5.2 Species Richness
Species richness of wetland mitigation projects in Auburn, WA were highly
variable, but none of the parmameters measured in this study could account for these
variations. There was no difference in species richness based on wetland mitigation
project type. Although survivability of planted species is not guranteed, the quantity,
type, and location of vegetation planted is planned during the intial project design, and
should be evaluated during the monitoring period and adjusted, as needed.
While the planting regime can be controlled in developing a mitigation site, this
does not mean that these sites achieve the same heights of biodiversity of natural
wetlands. In King County, palustrine wetlands ranged from 35-109 vegetative species per
wetland (Cooke & Azous, 2001). The minimum species richness of these wetlands (35) is
higher than 92% of the wetland mitigation sites considered in the full 2012 Auburn
Wetland Mitigation Assessment Project. This inequality is cause for concern over the
ability of these mitigation projects to effectively replace in-kind the ecosystem function
of natural wetlands, which appear to be a habitat for more biodiverse vegetative plant
communities. Vegetative biodiversity impels the continued survival of native species and
provides valuable habitat for fauna, complementing quality goals the Washington Natural
Heritage Plan (Washington State Department of Ecology, 1988).
Although the means of species richness by adjacent land use were not statistically
different, it is valuable to highlight that the maximum species richness for sites that were
adjacent to industrial sites (27) was much lower than those adjacent to vacant parcels
(48). In an examination of species richness in urbanizing areas of King County, WA,

39

researchers determined that urbanization did cause a decrease over time, possibly due to
increasing runoff events, increasing mean water level fluctuation, and changing
hydrologic regimes, which all can inhibit the survival of species intolerant to these
changes and may indicate that the adjacent land use and land use changes do have a direct
impact on vegetative communities (Azous & Cook, 2001).
5.3 Conclusion
Wetland mitigation projects in Auburn, Washington differ in their soil
development, which may be affecting their capacity to mitigate the loss of carbon storage
ecosystem functionality. The methods of project construction of both constructed and
restored wetlands may affect this function, as the use of heavy equipment to grade and fill
wetlands and the replacement of native topsoil may be compacting soils, and thus
limiting their ability to store soil organic carbon. Further, projects may add topsoil with a
lower percent organic matter (<10%), which further diminishes carbon supplies. There
were no patterns found indicating a difference in species richness in mitigation projects
based on age, project type, or adjacent land use. It is possible to affect biodiversity by
selecting appropriate species to introduce by planting, monitoring their survival at least
10-15 years, and replanting as necessary in order to provide adequate habitat and primary
production to replace those functions lost due to 404(c) permitting activity.
5.3.1 Implications
The impending negative consequences of anthropogenic climate change forces us
to examine any and all opportunities to mitigate these looming disasters. These strategies
incorporate the utilization of systems, both natural and engineered, to capture and store
40

greenhouses gases such as carbon dioxide. Wetlands are an essential system that delivers
this indispensable ecosystem service. Although they are a source of methane emissions,
they are a substantial carbon sink due to their ability to store carbon in their porous soils.
Because wetland mitigation projects are not storing as much soil carbon as their natural
counterparts, it is imperative to understand how this trade-off could be limiting earth’s
natural systems for counteracting rises in atmospheric carbon dioxide levels. Just as
global action includes prevention of further deforestation, policymakers must also
incorporate wetland conservation and mitigation plans into carbon sequestration planning
scenarios (Badiou, et al., 2011).
This study demonstrated that constructed wetlands do not perform as well as
restored wetlands in terms of soil organic carbon storage. For these wetland mitigation
sties to be functional equivalents to natural systems and result in no net loss of ecosystem
function, they must be able to provide the critical ecosystem function of soil carbon
storage. As permitting activity endures, land managers should differentiate between
constructed and restored wetlands and create mitigation plans that reflect their functional
differences. While restored wetlands may seem more viable in terms of ecosystem
function development, it is not possible to reverse the overwhelming loss of wetlands
through restoration alone. A large number of constructed wetlands must also be
established to achieve this goal, but should be done while acknowledging their limited
ability to mimic natural wetland ecosystes.
Regulators need to address wetland mitigation projects’ limited ability to function
as their natural counterparts, and find ways to explicitly hold permitees responsible for
these standards. Although the 2008 federal rule moves land managers away from using
41

wetland mitigation ratios in favor of a simple policy of no net loss of ecosystem function,
in some aspects, ratios can aide in determining a project’s potential in achieving
functional equivalencies such as carbon storage capacities. Hossler & Bouchard
recommend using a conservative 5.1:1 minimum mitigation ratio to reflect a constructed
wetlands ability to store carbon (2010).
Given the drastic inability of wetland mitigation projects to sequester carbon,
these stark differences must be considered when using global climate models and
terrestrial carbon storage projections. It is imperative that wetlands are classified by their
status as constructed, restored, or natural and their respective carbon sequestration
abilities factored in to these analyses at all levels. Mitigation projects are not functional
equivalents to natural wetlands, and should not be treated as such. Further, every effort
should be made to preserve natural wetland ecosystems and Section 404 permitting
should be limit to absolutely essential development projects in order to preserve one of
earth’s most important landscapes in naturally balancing atmospheric greenhouse gas
levels.
5.3.2 Recommendations for Further Research
Construction techniques may be hindering wetland mitgation projects’ ability to
store soil organic carbon. Remaining reliant on heavy equipment to create these
landscapes could be detrimental to soil development and functionality. This may be
difficult to avoid when attempting to manipulate hydrology, but limiting its use and
developing a viable alternative to prevent soil compaction should be explored.
Appropriate soil ammendment should be carefully considered for the next stage once

42

topography formation is complete. Due to excavation, organic rich native top soils are
removed, and must be replaced with a soil that would develop into a functional
equivalent to wetland soils. Where possible, the feasibility of relocating top soil directly
from the impacted wetland to the new mitigation site should be studied. Appropriate
storage of the soil would be essential, as aeration would alter the physiochemical and
biological soil properties (Zedler & Kercher, 2005). Alternatively, future studies could
test the capacity of different organic ammendments to mature into hydric soils
characteristic of naturally occuring wetlands.
This study established that in Auburn, WA there are differences in soil organic
content between constructed and restored wetlands, which are frequently lumped into one
category when researching wetland mitigation. Future study of mitigation sites should
differentiate between these systems and report results in this manner. It would be useful
to continue to compare and contrast a larger sample size of these systems to test whether
these results hold true at a larger scale, and pair constructed and restored wetlands with
similar physical parameters to one another. In order to understand the capacity of
mitigation project sites to store carbon long term, sedimentation rates should be assessed.
Further research should then estimate the carbon sequestration rate of different project
types, and propose methods to incorporate findings into global climate models used to
better understand carbon cycling and project the extent of future climate change.

43

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Appendix A
Wetland Function/Value Indicators used by Puget Sound Water Quality Wetland
Preservation Program to evaluate whether a wetland should be preserved (Recreated from
Washington State Department of Ecology, 1988)

Function/Value Indicators
I.

Resident and Migratory Species Support
A. The site supports important fish and wildlife use such as nesting rookeries,
nursery sites, migratory feeding routes, feeding areas, and spawning areas for
resident and/or migratory animal and fish species.
B. The site contains a significant number of habitat features important for fish
and/or wildlife support.

II.

Species of Special Concern
A. The site is feeding, breeding, or wintering habitat for animal species on WA
Dept. of Wildlife (WDFW) adopted or proposed lists of endangered, threatened,
sensitive or monitor species.
B. The site is spawning or feeding habitat receiving special mention under the WA
Dept. of Fisheries Hydraulic Project Approval WAC’s Chapter 220-110 7/20/87
(salmon, herring, and surf smelt).
C. The site is habitat for plant species which are listed in the Department of
Natural Resources (DNR), Natural Heritage Program list of Endangered,
Threatened, and Sensitive Vascular Plants of WA, 1987.
D. The site is habitat for uncommon plant species listed by a local Native
American tribe or academic ethnobotanist as important to native people for
food, medicinal, or spiritual purposes.

III.

Native Plant Communities
The site contains a high quality example of a native wetland listed in the
Terrestrial and/or Aquatic Ecosystem elements of the current WA Natural
Heritage Plan that is presently identified as such (documented in DNR records)
or is determined to be of Heritage quality by DNR.

IV.

Diversity
A. The site supports a high diversity of native plant and animal species.
B. The site contains high habitat and structural diversity.

V.

Floodwater Detention
The site moderates high flows experienced downstream by intercepting,
slowing, and storing storm water runoff.

50

VI.

Sedimentation & Erosion Control
The site intercepts sediment-laden runoff and provides for settling of sediments,
thereby reducing sediment deposition in downstream areas.

VII.

Nutrient/Pollutant Entrapment & Assimilation
The site intercepts, stores, assimilates, or provides for the biological conversion
of nutrients or other pollutants (such as coliform bacteria, oil & grease, etc.) in a
highly efficient manner. (Note: emphasis on lower level, non-toxic pollutants…
not waste dump areas.)

VIII.

Groundwater & Surface Water Exchange
The site provides or contributes to base flow in streams that support sensitive
downstream habitat areas. (Sensitive downstream habitat areas such as
connecting waters for fish habitat, estuarine wetlands, or other habitat areas
dependent upon base flow.)

IX.

Recreation
A. The site is important for recreational opportunities that are appropriate in
wetland settings and are consistent with the needs identified in the WA
Wetlands Priority Plan and the Statewide Comprehensive Outdoor Recreation
Plan (SCORP) or in local open space and/or park and recreation plans. (An
appropriate opportunity is defined as that which is dependent on the setting,
doesn’t harm the wetland, or whose impacts, if any, can be mitigated through
temporal r spatial distribution of the activity.)

X. Open Space & Aesthetics
A. The site contribute significant visual natural landscape characteristics or
linkages as
an open space in a surrounding urban area.
B. The site provides aesthetic amenity values and contributes aesthetic functions to
the adjacent landscapes.
XI.

Education and Research
A. The site offers a diverse environment and is readily accessible for instructional
use by education facilities and the general public.
B. The site has significant archaeological or historic cultural value as identified per
listing on the National Register of Historic Places.
C. The site provides an important wetland research opportunity.

51

Appendix B
Map of wetland mitigation project sites evaluated for WMAP.
24

12
11

9
24

LABEL PROJECT ID
1
00-0038A
2
00-0038B
3**
0-0038E
4
01-0004
5
01-0027
6
02-0001
7
02-0018
8
02-0020
9
03-0018
10** 04-0013
11
04-0018
12
04-0037
13
04-0043
14
06-0032
15*
07-0001
16
90-0090
17*
92-0055B
18*
92-0055A
19
94-0021
20
95-0015
21*
97-0013
22
97-0063A
23** 97-0063B
24
99-0046B
*
SAMPLED
RESTORATION SITE
**
SAMPLED
CONSTRUCTION SITE

23

20
6

7
5

14
10

1316
19
17

3

18

1

21
15
22

¯

8

Source: Esri, DigitalGlobe, GeoEye, Earthstar Geographics, CNES/Airbus DS, USDA, USGS, AEX,
Getmapping, Aerogrid, IGN, IGP, swisstopo, and the GIS User Community

Christina Stalnaker
The Evergreen State College
2015

0

0.5

1

2 Kilometers

52

Appendix C
Species richness data for each compensatory wetland mitigation project showing number
of aquatic, herbaceous, shrub and tree species by project number designation in the bar
chart and including dominant species illustrated within table.

53

Project #
00-0038A

2

97-0013

95-0015

94-0021

92-0055A

92-0055B

90-0090

07-0001

06-0032

04-0043

04-0037

04-0018

04-0013

03-0018

02-0020

02-0018

02-0001

01-0027

01-0004

Restoration

Restoration

Restoration

Restoration

Restoration

Restoration

Restoration

Restoration

Both

Both

Restoration

Both

Creation

Both

Creation

Restoration

Restoration

Both

Restoration

1

1

3

3

0

1
3
0

2

1
2
5

0

3

0

0

0

4

0

2

2

3

4

2

8

Restoration

97-0063A

Creation

Both

97-0063B

Creation

00-038B

99-0046B

Creation

Aquatic

00-0038E

Project Type

Typha latifolia

Malus fusca

Polygonum amphibium

Polygonum persicaria

Glyceria occidentalis and
Deschampsia cespitosa
Iris pseudocorus, Salix sp on
fringe
Lemna minor, Phalaris
arundinacea
Typha latifolia, Nuphar
polysepalum

Typha latifolia

Typha latifolia

Festuca sp

Typha latifolia

Nuphar polysepalum
Typha latifolia, Lemna
minor
Nuphar polysepalum Typha,
Elodea canadensis Lemnar
Scirpis micracarpus, Typha
latifolia
Typha latifolia, Phalaris
arundinacea

Typha latifolia

Dominant
Species

4

3

5

2

5

2

4

5

1

3

0

2

0

1

0

0

1

1

0

0

6

2

0

2

Tree
Salix lucida

Salix sp.

Populus balsamifera

Populus balsamifera
Salix sp., Pseudotsuga
menziesii
Salix sp., Thuja plicata, Picea
sitchensis

Populus balsamifera

Populus balsamifera

Populus basamifera
Populus balsamifera and Salix
sp.

Thuja plicata
Populus balsamifera and Thuja
plicata

Populus balsamifera

Salix lucida

Fraxinus latifolia

Populus balsamifera

Salix sitchensis and Populus
basamifera

Populus balsamifera

Dominant
Species

2

3

8

6

4

19

13

19

3

4

8

4

0

1

7

2

3

0

2

4

5

3

2

6

Shrub

Picea sitchensis

Salix sp.

Salix sp.

Rosa nutkana
Salix sp., Thuja plicata, Picea
sitchensis

Salix sp.

Salix sp.

Populus balsamifera

Salix sp.

Salix sp.

Salix sp

Cornus sericea Physiocarpus
capitatus Rosa Lonicer

Salix sp.

Salix sp.

Salix sp.

Cornus sericea, Physiocarpus
capitatus, Rosa pisac

Salix sp.

Salix sp.

Salix sp.

Salix sitchensis

Cornus sericea and Salix sp.

Salix sitchensis

Dominant
Species

14

4

4

7

11

6

18

21

5

10

1

1

4

5

10

5

3

2

3

3

15

5

5

17

Herbaceous

Carex obnupta
Typha, Carex obnpta,
Equisetum arvense

Carex obnupta

Phalaris arundinacea

Ranunculus repens

Phalaris arundinacea

Phalaris arundinacea
Phalaris arundinacea and
Ranunculus repens
Typha latifolia and Nuphar
polysepalum

Phalaris arundinacea
Glyceria occidentalis and
Deschampsia cespitosa

Phalaris arundinacea

Phalaris arundinacea
Phalaris, Ranunculus repens,
Alopecurus pretense

Phalaris arundinacea

Typha latifolia
Festuca rubra and Lotus
corniculatus
Scirpus microcarpus and
Juncus effuses

Phalaris arundinacea

Typha latifolia

Juncus effusus
Typha latifolia and Lemna
minor
Juncus effusus and Typha
latifolia

Alopecurus pratense and
Phalaris arundinacea

Dominant
Species

54