Defining Success Criteria for Spartina alterniflora Restoration Projects in Southwestern Louisiana
Joshua M. Soileau, Eddie K. Lyons, Byungkyun Chung, Justin Hoffman, and Frederick LeMieux
Southeastern Naturalist, Volume 17, Issue 4 (2018): 541–553
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22001188 SOUTHEASTERN NATURALIST 1V7o(4l.) :1574,1 N–5o5. 34
Defining Success Criteria for Spartina alterniflora
Restoration Projects in Southwestern Louisiana
Joshua M. Soileau1, Eddie K. Lyons1,*, Byungkyun Chung1, Justin Hoffman2, and
Frederick LeMieux1
Abstract - Evaluation of success in salt-marsh restoration is often driven by subjective
measures. By defining success criteria (SC), project effectiveness can be measured quantitatively.
Herein, we quantify SC for an existing Spartina alterniflora (Smooth Cordgrass)
restoration program. We selected stem density as an indicator of primary production and
canopy structure—2 important salt-marsh functions. We established SC through use of
stem densities from the literature and prior restoration projects and calculated a coefficient
of variation (CV) for reference groups. By using the CV, we determined the strength of a
particular reference group for SC formulation. We calculated success criteria for reference
groups with CV ≤ 0.25. Three reference groups met the CV requirement. Only 1 project
met the SC of the strongest reference group (CV = 0.04). Four of 5 projects met the SC of
the weakest reference group (CV = 0.21). Reference sites with low variation in the target
indicator should be selected for SC formulation.
Introduction
Success is one of the terms used most often in wetland-restoration science; it
is often used in an imprecise and inconsistent manner because it depends on the
situation and the people defining it (Kentula 2000, Whigham 1999, Zedler 1996,
Zedler and Callaway 2000). In most cases, the success being referenced is the
meeting of established objectives for a permit or contract. Although it is important
that mitigation projects fulfill their contract goals, some would argue that this does
not necessarily qualify as success from a conservation standpoint. Zedler (1996)
termed such a situation—when a project satisfies the permit requirements but is not
successful in restoring wetland function—as compliance. In fact, when it comes to
compliance, less than 70% of those projects evaluated met all permit requirements
(Cole and Shaffer 2002, Minkin and Ladd 2003, Sudol and Ambrose 2002). Another
study stated that on average, 73% of permit conditions are met in mitigation projects
(Ambrose et al. 2006).
Many authors have advocated that success in wetland restoration can only be
accomplished if ecological functions such as nutrient cycling, wildlife habitat, and
sediment retention are restored (Brown 1996, Cairns 2000, Kentula 2000, Neckles
et al. 2002, Quammen 1986, SER 2004). Kentula (2000) termed this functional success.
Defining success in such a way means that the system must be able to sustain
itself and be biologically viable (West et al. 2000), but it could take many years for
1School of Agricultural Sciences, McNeese State University, Box 92220, Lake Charles, LA
70609. 2Department of Biology/Health Science, McNeese State University, PO Box 92000,
Lake Charles LA, 70609. *Corresponding author- elyons@mcneese.edu.
Manuscript Editor: Foster Levy
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that to happen. Zedler (1996) suggested that project managers should seek to report
on the progress of a project instead of using the traditional labels—successful and
unsuccessful labels—which should only be used when a project has either met or
failed to meet all of its objectives.
If “success” as opposed to “compliance” is to be evaluated, goals must be
established to evaluate whether natural ecological functions have been restored.
Defining attainable goals for a project that adequately evaluate ecological functions
may not be as simple as meeting the requirements of a permit, or defining a target
survival-percentage. Even more daunting is the task of choosing a methodology
that adequately monitors characteristics of a project to determine if the goals are
met. The major hurdle to determining success for most restoration activities is financial
because most projects do not have the budget to conduct monitoring on the
ecological function of a site (Ruiz-Jaen and Aide 2005).
The Gulf Coast Soil and Water Conservation District (SWCD; Lake Charles,
LA) participates in a vegetation program for which the typical objectives of a project
are to restore wildlife habitat, provide a seed base, and reduce erosion. However,
these functions are never assessed for success or failure because it is outside of the
program’s budget to do so. Rather, plant growth and health data (i.e., stem count,
vigor, spread, etc.) are gathered at predetermined time intervals after planting, and
reports are submitted annually. Success is then determined based on survival rate of
plants, or the quality of the project (i.e., excellent, fair, poor), a subjective measure
that may change from year-to-year or with the personnel monitoring the projects.
Our study sought to utilize the data gathered on these projects to quantitatively
determine if functional success has been attained.
To more accurately determine the success of a project, biologists must assess
indicators of ecological functions. Two functions often associated with salt-marsh
ecosystems are canopy structure and primary production (Gleason et al. 1979, Kaswadji
et al. 1990, Short et al. 2000). These 2 functions relate to the habitat, refuge,
and food available to wildlife and fisheries (Short et al. 2000). Short et al. (2000)
identified stem density as an indicator for both of these functions. Stem density is
a good candidate indicator for determining success because of its ease of use and
low cost (Craft et al. 2003), and restoration programs, such as the one administered
by the Gulf Coast SWCD, often utilize it. However, stem density is rarely utilized
when determining project success. The objectives of our study were to: (1) define
success criteria for Spartina alterniflora L. (Smooth Cordgrass) restoration projects
by using data already gathered within the current monitoring program, and (2) apply
this criterion to recently completed (planting, and initial and 1-y monitoring
completed) projects to determine if functional success has been achieved.
Study Area
We conducted our study during salt-marsh revegetation projects in southwestern
Louisiana. These marshes are dominated by Smooth Cordgrass. Salinities ranged
from 7 ppt to >20 ppt (J.M. Soileau et al., unpubl. data). Rainfall in the area averages
134.62 cm/y (NOAA 2012). The major soil unit in the area is Clovelly muck.
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Salt marshes in this part of Louisiana occur on both organic and mineral soils (Midkiff
1995) and were severely impacted by hurricanes in 2005 and 2008, with large
areas lost due to scouring (Barras 2006, 2009).
The revegetation projects consisted of either bare-root plugs or commercially
available trade gallons (i.e., plants in 1-gallon pots, each pot typically with 5–12 aerial
stems that are 0.46–0.61 m tall) of S. alterniflora ‘Vermilion’, a native Louisiana
strain of Smooth Cordgrass. Project locations in 2011 were mud flats along the banks
of the Mermentau River in southeastern Cameron Parish, LA; sandy banks along
the Calcasieu Ship Channel in southern Calcasieu Parish, LA; and levees along the
banks of Kelso Bayou in Cameron Parish (Fig. 1). Objectives for the projects were to
(1) provide a seed base, (2) create wildlife habitat, and (3) reduce erosion.
Methods
In this study, we adapted the methods employed by Short et al. (2000) for
success-criteria (SC) calculation to accommodate the limited capabilities of the
monitoring program. Modifications are discussed here.
Restoration sites
Projects were planted in 2011 throughout Calcasieu and Cameron parishes,
LA, while J.M. Soileau was employed by Gulf Coast SWCD (Fig. 2). We planted
Figure 1. Salt-marsh restoration sites in southwestern Louisiana in 2011.
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Smooth Cordgrass plugs at the Kelso Bayou site; the 4 remaining sites were planted
with trade gallons. We conducted monitoring 1 y after planting. We gathered
quantitative and qualitative information on ~10% of the total project, divided into
segments. For each segment, we recorded vigor, spread, and average stems per
square meter (Table 1).
Reference sites
In order to calculate SC for reference sites and success ratios (SR) for restoration
sites, reference sites must be established and candidate indicators selected. The purpose
of this research is to define success criteria for projects with a limited budget;
thus, natural reference sites were not defined for each project, unlike in Short et
al. (2000). Rather, we gathered data on stem density from natural and restoration
Smooth Cordgrass marshes from the literature (Table 2; Craft et al. 2003, Currin et
Table 2. Stem densities from natural and restored Smooth Cordgra ss marshes from literature.
Author/Project State Type Stem density stems/(m2) Notes
Minello and Zimmerman 2003 TX Natural 124 Matagorda Bay
TX Transplant 175 Matagorda Bay
TX Natural 129 Chocolate Bay
TX Transplant 184 Chocolate Bay
TX Natural 103 Stadman Island
TX Transplant 193 Stadman Island
Craft et al. 2003 NC Natural ~250 1-y-old marsh
NC Transplant ~500 1-y-old marsh
NC Natural ~200 3-y-old marsh
NC Transplant ~250 3-y-old marsh
NC Natural ~300 28-y-old marsh
NC Transplant ~300 28-y-old marsh
Currin et al. 2008 NC Natural 149
NC Restored 70
NC Natural 130
NC Restored 150
NC Natural 222
NC Restored 161
Mullens 2007 LA Restored 42
LA Restored 75
LA Natural 72
Table 1. Stem densities at 1-y monitoring for Smooth Cordgrass projects installed in 2011 by the Gulf
Coast SWCD, Calcasieu and Cameron parishes, LA.
Stem density
Project (stems/m2) Notes
East Moss Lake 3 Heavily grazed by cattle
Kelso Bayou 360
Mermentau River North 93 Some of the project area had been grazed by cattle
West Turner's Bay 108
Mud Lake 89 Some of the project area had been grazed by cattle
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Table 3. Past projects installed by the Gulf Coast Soil and Water Conservation District, Calcasieu and
Cameron parishes, LA. Stem density was measured 1 y after plant ing.
Stem density
Project State Type (stems/m2) Notes
Mermentau River (2000) LA Restored 217
Choupique Bayou (2001) LA Restored 146
DU Terraces 1 (2002) LA Restored 449 Hackberry, trade gallon containers
DU Terraces 2 (2002) LA Restored 229 Bare-root plugs
Moss Lake (2003) LA Restored 54 Moss Lake (2003)
Rockefeller Refuge (2006) LA Restored 158
Rockefeller Refuge (2007) LA Restored 112 Headquarters Canal
al. 2008, Minello and Zimmerman 2003, Mullens 2007). In addition to the densities
gathered from the literature, we also selected as candidate reference-sites 7 areas
that had previously been restored and monitored by the Gulf Coast SWCD prior to
J.M. Soileau’s employment by that organization (Table 3; Gulf Coast SWCD, unpubl.
data). We selected these areas based on proximity to the sites being analyzed,
as well as for their similar environmental characteristics (i.e., soils, salinity). Stem
densities from these projects were taken 1 y after planting.
We divided candidate reference-sites into reference groups based on geographic
location and type (restoration or natural; Table 4). We created the groups to allow
computation of mean and standard deviation (SD) because no data were available
for the individual sites.
Although natural reference sites near the restoration projects are ideal, 1 study
indicated that Smooth Cordgrass is adapted on a regional scale and that performance
among several populations over a given distance may not differ (Travis and
Grace 2010). Selecting literature-reported stem densities from numerous Smooth
Cordgrass populations along the Atlantic and Gulf Coasts provides a larger set of
reference sites from which to calculate SC.
Selecting candidate indicators
Another difference between this study and Short et al. (2000) is the lack of
options for candidate indicators. The monitoring program already in place was
limited to measurements of plant growth such as survival, spread, and stem density.
However, these parameters are sufficient because stem density is an indicator
of functions such as primary production, canopy structure, organic-matter accumulation,
and sediment trapping (Gleason et al. 1979, Kaswadji et al. 1990, Short
et al. 2000). According to Short et al. (2000), these functions, represent 2 of the
3 major goals (wildlife habitat, providing a seed base, and reducing erosion) of
the restoration projects: canopy structure is representative of wildlife habitat; and
organic-matter accumulation and sediment trapping are representative of erosion
reduction. We used stem densities to calculate SC for reference sites and SR for restoration
sites, and compared them to the reference site SC individually to determine
if a given project was successful based on a given SC.
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Descriptive statistics
We calculated mean, SD, and coefficient of variation (CV) for 8 groups
(Table 5). The groupings were based on geographic location (i.e., Texas, North
Carolina, Louisiana, Gulf Coast) and type of reference site (i.e., whether the site
was a restored or natural marsh). We used the CV to rank the reference sites for
SC calculation. A lower CV indicates that there is less dispersion in the variable
(i.e., stem density at reference sites), signifying that a particular group is suitable
for creating an SC. Low variability across reference sites means that success of the
project can be more accurately determined; high variability in the reference sites
makes it difficult to determine if a given site was successfully restored because
of the differences in the reference sites. A CV of less than 0.2 is ideal because the
Table 4. Reference groups established from literature and past-r estoration sites.
Stem density
Reference group Author/project (stems/m2) Notes
Texas natural Minello and Zimmerman 2003 124 Matagorda Bay
129 Chocolate Bay
103 Stadman Island
Texas restored Minello and Zimmerman 2003 175 Matagorda Bay
184 Chocolate Bay
193 Stadman Island
Gulf Coast natural Minello and Zimmerman 2003 124 Matagorda Bay
129 Chocolate Bay
103 Stadman Island
Mullens 2007 72
Gulf Coast restored Minello and Zimmerman 2003 175 Matagorda Bay
184 Chocolate Bay
193 Stadman Island
Mullens 2007 42
75
Mermentau River (2000) 217
Choupique Bayou (2001) 146
DU Terraces 1 (2002) 449 Hackberry, trade 1-gal containers
DU Terraces 2 (2002) 229 Bare-root plugs
Moss Lake (2003) 54 Moss Lake (2003)
Rockefeller Refuge (2006) 158
Rockefeller Refuge (2007) 112 Headquarters Canal
North Carolina natural Craft et al. 2003 ~250 1-y-old marsh
~200 1-y-old marsh
~300 3-y-old marsh
Currin et al. 2008 149
130
222
North Carolina restored Craft et al. 2003 ~500 1-y-old marsh
~250 3-y-old marsh
~300 28-y-old marsh
Currin et al. 2008 70
150
161
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variation within the reference sites is low, something that is difficult to surpass
regularly in the biological sciences (Short et al. 2000). For this study, we selected
reference sites with a CV ≤ 0.25 for SC calculation. We chose this value because
it indicates that the variation is equal to a quarter or less of the mean, indicating
lower variation within the sampled areas. Short et al. (2000) noted that a CV of 0.2
is a “somewhat” arbitrary value, but used it because it is difficult to surpass with
regularity in biological field-sampling. A smaller SD, which is used in the calculation
of the CV, indicates a smaller degree of variation within a dataset.
Calculating success criteria
The formula for calculating SC is (Short et al. 2000):
SC = 100 x (mean of reference site - 1 SD) / (mean of reference site)
The SD is used to calculate SC for 3 reasons: (1) it holds the CV within the
distribution of the data but keeps it above the lowest 16.7% (i.e., 1 SD) of the distribution,
(2) it is the statistical standard of variability and is independent of sample
size, and (3) the relationship between the SC and CV (a small SD leads to a low CV
and a high SC; Short et al. 2000).
Assessment time-frame
In the current monitoring program, all required monitoring was complete after
1 y; the first monitoring occurred 30–60 d after planting and the second event
was 1 y after planting. A third monitoring may be conducted no earlier than 5 y
after planting. These projects have yet to be monitored at 5 y; thus, we made our
assessments 1 y after monitoring was completed. In biological terms, this would be
considered inadequate; many studies state that restored marshes do not exhibit the
characteristics of natural marsh for 3–5 y (Confer and Niering 1992, Currin et al.
2008, Edwards and Proffitt 2003, Short et al. 2000).
Table 5. Mean, standard deviation, and coefficient of variation (CV) for 3 different mean calculations
for stem density. Success Criteria not calculated for reference groups with CV ≥ 0.25.
Reference Mean SD CV SC
TX restored marshes 184.00 7.35 0.04 96.01
TX natural marshes 118.67 11.26 0.09 90.51
Gulf Coast natural marshes 107.00 22.44 0.21 79.03
SWLA restored marshes (excluding DU Terraces 1 and 172.40 44.15 0.26 -
Moss Lake)
NC natural marshes 208.50 57.81 0.28 -
Gulf Coast restored marshes (excluding DU Terraces 1 and 153.10 57.51 0.38 -
Moss Lake)
LA restored marshes (excluding Du Terraces 1 and Moss Lake) 139.86 64.17 0.46 -
NC restored marshes 238.50 138.16 0.58 -
SWLA restored marshes (all) 195.00 117.53 0.60 -
Gulf Coast restored marshes (all) 169.50 102.97 0.61 -
LA restoration marshes (all) 164.67 118.43 0.72 -
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Calculating success ratio
The success ratio (SR) is the measure of how successful each restoration site is
when compared to reference sites (Short et al. 2000). The SR is calculated as follows
(Short et al. 2000):
SR = 100 x (mean of restoration site) / (mean of selected reference site)
We compared the SR for each restoration site to the SC for the reference sites.
A given restoration site was successful if it met or exceeded the SC of a given reference
site (Short et al. 2000). If the SR for a restoration site exceeds the SC, this
can result in unequal development of ecological functions in the site, such as plant
response and predation (Short et al. 2000).
Results
A total of 3 reference groups produced a CV ≤ 0.25 (Table 5). In descending order
by CV, these were: Gulf Coast natural marshes (GCNat), Texas natural marshes
(TXNat), and Texas restored marshes (TXRes). Only 2 groups met the criterion of
CV ≤ 0.2 established by Short et al. (2000): the Texas natural marshes (CV = 0.09)
and the Texas restored marshes (CV = 0.04). We report mean, SD and CV for all
reference groups (Table 4). The GCNat group had the lowest mean (n = 107), while
the TXRes group had the lowest SD (SD = 7.35).
Applying success criteria
The TXRes group had the lowest CV (CV = 0.04) of all reference groups
(Table 5); thus, it was the highest-ranked mean, and the best for SC formulation
(Short et al. 2000). Figure 2 shows SC and SR values for reference groups and
restoration sites. When compared to the TXRes group (SC = 96.01%), only 1 project,
Kelso Bayou (SR = 195.65%), met or exceeded the SC. The TXNat group (SC
= 90.51%) was the second best for SC calculation (CV = 0.09), and 2 restoration
projects met or exceeded the SC—Kelso Bayou (SR = 303.36%) and West Turner’s
Bay (SR = 91.01%).
The GCNat group (SC = 79.03%) ranked third for SC calculation (CV = 0.21),
and 4 of the 5 restoration projects met the SC—Kelso Bayou (SR = 336.45%), West
Turner’s Bay (SR = 100.93%), Mermentau River North (SR = 86.92%), and Mud
Lake (SR = 83.18%). All Louisiana-based reference groups had a CV > 0.25, and
we did not calculate SC for any group with a CV > 0.25.
Discussion
Although the Gulf coast marshes used in this study differed from one another
in a number of aspects (Table 2), Smooth Cordgrass along the Gulf coast typically
exhibits the same growth form (Seliskar et al. 2002). Based on the low variation,
the TXRes and TXNat groups were reliable reference sites for the study (Table 2).
Only the Kelso Bayou restoration project was successful when compared to the
TXRes group, which had the strongest CV (CV = 0.04). Using the TXNat group
(CV = 0.09), Kelso Bayou and West Turner’s Bay were successful. Since stem
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density can be used to determine the restoration of certain functions, such as
wildlife habitat and sediment retention, it can be assumed through these results
that these functions have been restored at the Kelso Bayou and West Turner’s
Bay sites. Personal observations of wildlife use at both sites and the narrowing of
levee breaches at Kelso Bayou confirm this conclusion (Fig. 3). Fruiting culms
Figure 2. Success criteria (SC) and success ratios (SR) for stem density from Smooth
Cordgrass restoration sites in 2001 in southwestern Louisiana. SC for each reference group
represented by dark gray horizontal line.
Figure 3. Smooth Cordgrass at Kelso Bayou. Picture taken at 1-y monitoring in 2012.
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were present at West Turner’s Bay,[indicating that the goal of providing a seed
base had been met (Fig. 4).
Of the 3 projects that failed to meet the SC for both reference groups, Mud Lake
and Mermentau River North each had monitoring segments with stem densities
above the SC (Fig. 5). Portions of these projects were planted on harder clays and
soils with high shell-content and transplants did not perform as well here, which
Figure 4. Smooth Cordgrass fruiting culms at West Turner’s Bay in 2012.
Figure 5. Smooth Cordgrass at Mud Lake project in 2012. A dense stand has established on
previous mud-flat area.
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resulted in lower stem densities. In the areas that did have high stem densities,
project objectives were being met.
Although these projects fell short of meeting the SC of the 2 Texas groups, both
met the SC established by the GCNat group (CV = 0.21). East Moss Lake was
the only project that failed to meet any of the SC established in this study. In this
project, it appeared that grazing by Bos taurus L. (Cattle) or Myocastor coypus
(Molina) (Nutria) had reduced survival to less than 10%.
The use of past restoration projects as reference sites can be a viable choice if
the sites have achieved the desired ecological functionality. In the current study, the
DU Terraces 1 and Moss Lake restoration projects were obvious outliers (stem densities
= 449 stems/m2 and 54 stems/m2, respectively). By removing these 2 projects
from the SWLA restored marshes group (CV = 0.60), the CV was reduced by 56%
(CV = 0.26). Although this CV was still outside the designated selection criterion
of CV ≤ 0.25, this group would serve as a good reference for SC calculation under
less-selective criteria. However, the projects used in this reference group were
selected due to proximity to the restoration sites established in 2011. Using past
projects that have been monitored at 5 y, when restoration trajectories have typically
leveled off and are closer to conditions seen in natural marshes, would be a
better alternative. Projects tend to exceed natural marsh production within the first
few years of establishment (Short et al. 2000). The Kelso Bayou restoration project
is an example of this phenomenon: the SR for the site exceeded all 3 SC with which
it was compared. Future use of past restoration sites should be subjected to a more
strenuous evaluation process.
The effectiveness of this methodology of setting SC is largely dependent on
the reference sites used. Examination of the reference groups indicated that using
multiple reference sites from different geographic regions, even along the Gulf
coast, or using restoration sites which have a wide range of densities, can cause a
site to be incorrectly deemed successful. The GCNat group led to the conclusion
that 4 of the 5 restoration projects were successful, and was also the only group for
which SC was calculated that had a CV > 0.2, the criterion in Short et al. (2000).
We chose to depart from the 0.2 CV applied in Short et al. (2000) to illustrate how
different methods of SC calculation can lead to different outcomes of success determinations.
More-rigorous criteria for SC calculation would reduce the likelihood
of inaccurately classifying the success of a project, as was seen with the TXRes and
TXNat reference groups. However, reference groups or sites with SC < 0.1 may
create criteria that are too strict, even when data and observations show healthy,
functioning marsh, as was evident in the West Turner’s Bay project. This finding
further exemplifies the need for proper reference site selection .
We echo the recommendations of others (Kentula 2000, Short et al. 2000) that
natural sites near the proposed restoration project are the best ones for referencing
project outcomes. The use of information from other geographic localities can
lead to improper designations of success or failure. Assessment time-frame is also
an important consideration. These decisions of success or failure are based on 1
y of growth. A decision on success or failure of a project may best be made 5 y
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after restoration; this is the point when restored marshes begin to resemble natural
marshes (Confer and Niering 1992, Currin et al. 2008, Edwards and Proffitt 2003,
Short et al. 2000). However, some candidate indicators, such as stem density, may
take as much as 15 y to resemble those present in natural marshes (Craft et al.
2003). For this reason, managers must continually monitor restoration projects to
accurately determine the trajectory of restoration because some projects may take
longer to reach equivalency with their natural counterparts.
Acknowledgments
We thank the Gulf Coast Soil and Water Conservation District for providing technical
support and equipment for the study. Funding was provided by the Coastal Protection and
Restoration Authority of Louisiana.
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