U.S. Department of the Interior

U.S. Geological Survey

Open-File Report 2015–1206

Coastwide Reference Monitoring System (CRMS)

Vegetation Volume Index: An Assessment Tool for Marsh 

Habitat Focused on the Three-Dimensional Structure

at CRMS Vegetation Monitoring Stations

Prepared in cooperation with the Coastal Wetlands Planning, Protection and Restoration Act Task Force
Cover, Photograph showing fresh marsh at site CRMS3169, in the Barataria hydrologic basin, Louisiana, August 2014 (photograph by Brett A. Patton,

U.S. Geological Survey).
Coastwide Reference Monitoring System (CRMS) 

Vegetation Volume Index: An Assessment 

Tool for Marsh Habitat Focused on the ThreeDimensional Structure at CRMS Vegetation 

Monitoring Stations

By William B. Wood, Jenneke M. Visser, Sarai C. Piazza, Leigh Anne Sharp,

Laura C. Hundy, and Tommy E. McGinnis

Prepared in cooperation with the Coastal Wetlands Planning,

Protection and Restoration Act Task Force

Open-File Report 2015–1206

U.S. Department of the Interior

U.S. Geological Survey
U.S. Department of the Interior

SALLY JEWELL, Secretary

U.S. Geological Survey

Suzette M. Kimball, Acting Director

U.S. Geological Survey, Reston, Virginia: 2015

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Suggested citation:

Wood, W.B., Visser, J.M., Piazza, S.C., Sharp, L.A., Hundy, L.C., and McGinnis, T.E., 2015, Coastwide Reference 

Monitoring System (CRMS) Vegetation Volume Index—An assessment tool for marsh habitat focused on the threedimensional structure at CRMS vegetation monitoring stations: U.S. Geological Survey Open-File Report 2015–1206, 

14 p., http://dx.doi.org/10.3133/ofr20151206.

ISSN 2331-1258 (online)
iii

Contents

Abstract...........................................................................................................................................................1

Introduction ....................................................................................................................................................1

Methods...........................................................................................................................................................2

Results .............................................................................................................................................................4

Yearly Trends .........................................................................................................................................4

Marsh Type Trends ...............................................................................................................................4

Basin Trends ..........................................................................................................................................4

Overall Vegetation Volume Trends ....................................................................................................8

Discussion and Conclusions......................................................................................................................11

References Cited .........................................................................................................................................13

Figures

1. Map showing study area and change in vegetation volume

from 2008 to 2012 in hydrologic basins in coastal Louisiana.................................................3

2. Graph showing vegetation volume means from 2006 to 2013

with yearly variation in average vegetation volume on a coastwide scale

for hydrologic basins in coastal Louisiana...............................................................................5

3. Graph showing vegetation volume means per hydrologic basin

in coastal Louisiana over the 8-year study period from 2006 to 2013 ..................................5

4. Graph showing vegetation volume means of all marsh types averaged

over the 8-year study period from 2006 to 2013 in coastal Louisiana ..................................6

5. Graph showing vegetation volume means of all marsh types

from 2006 to 2013 in coastal Louisiana......................................................................................6

6. Graph showing vegetation volume means per hydrologic basin

over the 8-year study period from 2006 to 2013 in coastal Louisiana ..................................7

7. Graph showing vegetation volume means per hydrologic basin

and marsh type averaged over the 8-year study period from

2006 to 2013 in coastal Louisiana ...............................................................................................7

8. Graph showing mean Vegetation Volume Index score by year

from 2006 to 2013 for hydrologic basins in coastal Louisiana. ..............................................9

9. Boxplots showing distribution of Vegetation Volume Index scores

across all years of the study data collection with the annual means .................................9

10. Map showing Vegetation Volume Index score in hydrologic basins

in coastal Louisiana at each study site during 2012 separated

into 25th and 75th quartiles .......................................................................................................10

11. Graph showing mean Vegetation Volume Index score per hydrologic basin

over the 8-year study period from 2006 to 2013 in coastal Louisiana ................................11
iv

Conversion Factors

International System of Units to Inch/Pound

Multiply By To obtain

Length

meter (m) 3.281 foot (ft) 

kilometer (km) 0.6214 mile (mi)

kilometer (km) 0.5400 mile, nautical (nmi) 

meter (m) 1.094 yard (yd) 

Area

square meter (m2) 0.0002471 acre 

square kilometer (km2) 247.1 acre

square meter (m2) 10.76 square foot (ft2) 

square kilometer (km2) 0.3861 square mile (mi2)

Volume

cubic meter (m3) 264.2 gallon (gal) 

cubic meter (m3) 35.31 cubic foot (ft3)

cubic meter (m3) 1.308 cubic yard (yd3) 

cubic meter (m3) 0.0008107 acre-foot (acre-ft) 

Temperature in degrees Celsius (°C) may be converted to degrees Fahrenheit (°F) as

°F = (1.8 × °C) + 32.

Temperature in degrees Fahrenheit (°F) may be converted to degrees Celsius (°C) as

°C = (°F – 32) / 1.8.

Datum

Vertical coordinate information is referenced to the North American Vertical Datum of 1988 

(NAVD 88).

Horizontal coordinate information is referenced to the North American Datum of 1983 (NAD 83).

Altitude, as used in this report, refers to distance above the vertical datum.
Coastwide Reference Monitoring System (CRMS) 

Vegetation Volume Index: An Assessment Tool for Marsh 

Habitat Focused on the Three-Dimensional Structure at 

CRMS Vegetation Monitoring Stations

By William B. Wood,1 Jenneke M. Visser,2 Sarai C. Piazza,3 Leigh Anne Sharp,1 Laura C. Hundy,2

and Tommy E. McGinnis1

1

State of Louisiana, Coastal Protection and Restoration Authority, Lafayette.

2

State of Louisiana, University of Louisiana at Lafayette.

3

U.S. Geological Survey.

Abstract

A Vegetation Volume (VV) variable and Vegetation 

Volume Index (VVI) have been developed for the Coastwide 

Reference Monitoring System (CRMS). The VV is a measure 

of the amount of three-dimensional vegetative structure 

present at each CRMS site and is based on vegetation data 

collected annually. The VV uses 10 stations per CRMS site 

to quantify four vegetation layers: carpet, herbaceous, shrub, 

and tree. For each layer an overall live vegetation percent 

cover and height are collected to create a layer volume; the 

individual layer volumes are then summed to generate a site 

vegetation volume profile. The VV uses the two-dimensional 

area of live vegetative cover (in square meters) multiplied by 

the height (in meters) of each layer to produce a volume (in 

cubic meters) for each layer present in a 2-meter by 2-meter 

station. These layers are additive, yielding a total volume for 

each of the 10 herbaceous vegetation stations and an overall 

CRMS marsh site average.

The VV is an assessment of the quantity of vegetation 

present and is directly related to plant community structure. 

The VV differs from the previously developed Floristic 

Quality Index (FQI) in that the VV makes no assumptions 

about vegetation quality, giving each species equal weight; 

the FQI scores species with consistent site fidelity more 

favorably. We adapted the VV data into the VVI, which creates 

a representative score for all coastal marsh types. A VV and 

VVI will be generated annually for CRMS site, project, and 

basin-level analysis. The index is designed to assess areas 

undergoing habitat conversion, creation, and disturbance and 

to document project effectiveness when goals are to create, 

increase, or maintain emergent vegetation.

The VV and VVI will be used to establish trends, to make 

comparisons, and to evaluate restoration projects. Assessments 

that rely on the VVI will be included in appropriate Coastal 

Wetlands Planning, Protection and Restoration Act (CWPPRA) 

project reports and analyses. Implementation of the VVI will 

give coastal managers a new tool to design, implement, and 

monitor coastal restoration projects. A yearly trajectory of site, 

project, basin, and coastwide VVI will be posted on the CRMS 

Web site as data are collected. The primary purpose of the tool 

is to assess CWPPRA restoration project effectiveness, but it 

will also be useful in identifying areas in need of restoration and 

in coastwide vegetation assessments.

Introduction 

The Coastal Wetlands Planning, Protection and Restoration 

Act (CWPPRA) is Federal legislation enacted in 1990 that is 

designed to identify, prepare, fund, implement, and monitor 

coastal wetland restoration projects (http://www.lacoast.

gov/). In 2006, the Coastwide Reference Monitoring System 

(CRMS), a network of 391 monitoring sites along the coast 

of Louisiana, began collecting data under CWPPRA. CRMS 

monitoring site selection was not based on the ecological 

condition of the habitat being monitored; thus, a range of 

conditions exist within the monitoring network. CRMS 

monitoring sites are located within five wetland habitat types 

(that is, freshwater, intermediate, brackish, and saline marshes 

and forested wetlands) in order to ecologically characterize the 

Louisiana coast (Sasser and others, 2008). Monitoring sites 

are also located within and outside of CWPPRA restoration 

project boundaries. Sites located outside of project areas can be 

used as references against which to evaluate the effectiveness 

of CWPPRA restoration projects. The monitoring program 

classifies sites based on wetland habitat type (vegetation 

type), basin location, and location within restoration project 
2 Coastwide Reference Monitoring System (CRMS) Vegetation Volume Index

or nonrestoration project areas (Steyer and others, 2003). Data 

collected at the CRMS site level have been used to develop 

indices for vegetation, hydrology, and soils in order to (1) 

evaluate restoration project effectiveness by using comparisons 

to a network of reference sites, (2) identify landscape-level 

trends within the discrete habitat types or basins, and (3) 

identify long-term and seasonal trends in coastwide conditions. 

The emergent vegetation present in wetland habitats is 

controlled by environmental factors such as flooding, salinity, 

nutrient availability, and soil physicochemical characteristics 

(Baldwin and Mendelssohn, 1998; Shaffer and others, 2009; 

Wiseman and others, 1990). Changes in plant community 

composition thus can indicate change in landscape physical 

conditions (Day and others, 2011; Temmermann and others, 

2012). The scope of this document is limited to data associated 

with the marsh vegetation component of the CRMS monitoring 

system and therefore excludes data from forested wetland sites.

Previous CRMS analyses have used the Floristic Quality 

Index (FQI) to assess the condition of a wetland area based on 

the plant community composition (Cretini and others, 2012). 

The FQI is based on a coefficient of conservatism (CC), a 

score from 0 to 10 that is assigned to each plant species in a 

local flora by regional plant experts (Chabreck and Linscombe, 

1982). Scores for each species are assigned according to their 

specificity to a particular habitat type and temporal stability 

(Cretini and others, 2011). Species that are prominent after 

disturbances and display low habitat specificity were assigned 

a low CC score, whereas species that are highly habitat 

specific received a high CC score. The FQI can thus be used 

to detect and monitor changes in wetland conditions related 

to acute disturbances like storms or long-term disturbance 

events such as alterations in local hydrology, eutrophication, 

or habitat fragmentation (FitzGerald and others, 2008; Hatton 

and others, 1983). 

In contrast to the FQI, the Vegetation Volume (VV) 

variable quantifies the amount of vegetation within each site 

without consideration of vegetation type, species, or quality. 

The VV thus provides a surrogate measure of aboveground 

three-dimensional structure that can be compared among

CRMS sites. The VV does not differentiate between newly 

created marshes, either naturally formed or man-made, and 

existing established marsh if the VV values are similar. The 

layer height component of the CRMS dataset is used to indicate 

the vigor of vegetation layers under its local environmental 

parameters. Thus, the VV can be used to determine the 

functional performance of similar marsh types under varying 

levels of degradation or restoration (Mayence and Hester, 2010; 

McKee and Mendelssohn, 1989). Further, changes in VV may 

have important implications for the ecosystem services

provided by coastal marshes, such as storm surge reduction

and detrital food chain support.

Organizing the CRMS site data into multiple, easily 

comparable datasets assists in the planning and performance 

evaluation of CWPPRA projects. The VV has been further 

refined into the Vegetation Volume Index (VVI), which ranges 

from 1 to 100 as a standardized score of the three-dimensional 

vegetation quantity. This approach allows data users to 

systematically investigate site, project, hydrologic basin, 

and coastwide scales for vegetation structure and compare 

the VVI value directly to other CRMS site data indices such 

as the FQI, the Hydrologic Index, and the Submergence 

Vulnerability Index. The VVI should be used in coordination 

with the other CRMS data derived indices by marsh type to 

determine overall ecological performance. For example, the 

Hydrologic Index, which combines the weighted average 

annual salinity and percent time flooded by marsh type, also 

generates a 0–100 site index value (Snedden and Swenson, 

2012). This index is then further broken down within a CRMS 

site report card into the 25th and 75th quartile to frame where 

a specific CRMS site, project, or basin occurs in the overall 

coastwide population within a specific marsh type annually 

(http://www.lacoast.gov/crms2). Similar methodology is in 

place for the FQI and the Submergence Vulnerability Index, 

thereby allowing multiple variables to be assessed efficiently 

and compared to references of the same marsh type (Cretini 

and others, 2012; Stagg and others, 2013).

Methods

The CRMS network covers the Louisiana coastal zone 

with 391 1-square-kilometer (km2

) monitoring locations; 

each location has an imbedded 200- by 200-meter (m) data 

collection area. Within the data collection area a suite of 

physical and biological parameters are measured at varying 

intervals to describe the relative ecosystem function of the site. 

The emergent vegetation response variables were observed 

and recorded annually (2006–13) to document changes 

in vegetation assemblages associated with either natural 

conditions or restoration projects (Cretini and others, 2011). 

Monitoring sites were sampled and classified as freshwater, 

intermediate, brackish, or saline marsh types on the basis of 

the protocol outlined by Folse and others (2012). Sampling 

was conducted within ten 2- by 2-m (4-square-meter [m2

]) 

stations located randomly along a 282.2-m transect at least 

3 m apart within the data collection area at each CRMS site. 

Within each vegetation station, the percent live cover of each 

plant species was visually estimated during peak standing crop 

(August 1 to September 30) when possible, but landowner 

restrictions caused estimates at some sites to fall outside 

of this timeframe. The total live cover within the plots and 

of each vegetation layer (that is, carpet, herbaceous, shrub, 

and tree) was visually estimated between 0 and 100 percent. 

Although the total live plot cover cannot exceed 100 percent, 

the sum of the individual species covers may exceed 100 

percent because of the overlapping vegetation in the stations. 

Additionally, the average height (in meters) of each vegetation 

layer was measured in each station. 

CRMS vegetation survey data from 2006 to 2013 in 

the four marsh types throughout the nine hydrologic basins 

of coastal Louisiana (fig. 1) were used to inform this model. 
LOUISIANA

TEXAS

MISSISSIPPI

Areaenlarged

Barataria

Teche/

Vermilion

Mermentau

Calcasieu/

Sabine

Chenier Plain

Gulf of Mexico

Atchafalaya

Bre

Sou

Terrebonne

93°0' 92°0' 91°0' 90°0' 

28°0'

31°0'30°0'29°0'

Base from 2014 Landsat OLI 8 Mosaic Band 5April 15, 2015

Marsh

Island

Hydrologic basinboundary 

0 10 20 3

EXPLANATION 0 10 20 30 40 5

-7.4 to -1.0-0.9 to -0.3-0.2 to 0.3

0.4 to 1.01.1 to 9.2

Change in vegetation volume

between 2008 and 2012, in cubic meters

Study area

laf15-ESSC00-0702_fig01

Figure 1. Study area and change in vegetation volume from 2008 to 2012 in hydrologic basins in coastal Louisiana. 
4 Coastwide Reference Monitoring System (CRMS) Vegetation Volume Index

An annual sample size of 318 (in 2006), 493 (in 2007), 

531 (in 2008), 538 (in 2009), 513 (in 2010), 556 (in 2011), 

543 (in 2012), and 540 (in 2013) vegetation stations were 

used to calculate VV from 2006 to 2013. The vegetation 

cover and height data collected from each CRMS station 

were used to calculate a VV and a VVI for all stations from 

2006 to 2013. VV for each station was calculated as the 

sum of the volume of each of the vegetation layers by using 

the following formula:

 

(1)

Vegetation Volume (m3

) = [carpet layer live cover area 

(m2) × carpet layer height (m)] + [herbaceous layer live 

cover area (m2) × herbaceous layer height (m)] + [shrub 

layer live cover area (m2) × shrub layer height (m)] + 

[tree layer live cover area (m2) × tree layer height (m)]

A CRMS site-level VV value was calculated as the 

average VV from the 10 stations within the CRMS site. 

To index the VV variable, all individual CRMS station 

VVs within each marsh type were assigned a relative rank 

from 1 to 100 as a function of a normalized distribution 

across all years of the data collection. This rank represents 

the VVI score for each station at every site within a 

specific marsh type. 

Changes in VV from 2006 to 2013 were compared among 

the four marsh types (freshwater, intermediate, brackish, and 

saline) and among the nine hydrologic basins that compose 

the Louisiana coastal zone: Atchafalaya (AT), Barataria (BA), 

Breton Sound (BS), Calcasieu/Sabine (CS), Mermentau (ME), 

Mississippi River (MR), Pontchartrain (PO), Terrebonne (TE), 

and Teche/Vermilion (TV). 

A full factorial analysis of variance (ANOVA, JMP, 

version 11.0) was used to test for any significant year, marsh 

type, and hydrologic basin main effects on mean VV along 

with all possible interactions of the main effects by applying 

a three-way ANOVA. Tukey adjusted post hoc tests with an 

alpha level of 0.05 were used to determine significance

Results

Yearly Trends

The VV site values ranged from 0.0 in burned, denuded, 

and open water locations to 35.89 in sites dominated by 

robust vegetation types over the course of the study. Overall 

the highest VV values were found in Phragmites australis

monocultures, whereas the lowest values with vegetation 

present varied between thin mat floating marsh and highly 

fragmented locations where a conversion to open water 

was prevalent. The 10th and the 90th percentiles for the 

entire range of the VV data collected were 1.32 and 4.39, 

respectively. An ANOVA on mean VV found significant 

differences among the 8 years (F7, 2304 = 11.45, p < 0.0001). 

The mean VV was highest in 2011 (3.61 ± 0.08; mean ± 

standard error) and lowest in 2006 (2.69 ± 0.17) (all means are 

reported as least squares unless otherwise noted). The mean 

VV from 2008 was significantly lower than those from all 

other years of the vegetation survey (fig. 2). The change in VV 

between 2008 and 2012 was depicted geospatially by showing 

specific areas of VV change and stability on a coastwide 

scale (fig. 1). The hydrologic basins in the Chenier Plain 

(Calcasieu/Sabine, Mermentau, and Teche/Vermilion) showed 

a substantial increase in VV, as did the Mississippi River 

Delta hydrologic basin. The lower portion of the Barataria 

hydrologic basin, the Terrebonne hydrologic basin, and Marsh 

Island all had reduced VV from 2008 to 2012. The yearby-basin interaction was also significant (F49, 2304 = 2.94, p < 

0.0001), with the Mississippi River Delta hydrologic basin and 

the Pontchartrain hydrologic basin producing lower mean VV 

values during 2008 and 2006, respectively (fig. 3).

Marsh Type Trends

An ANOVA detected a significant difference in mean VV 

between the four marsh types (F3, 2304 = 102.49, p < 0.0001). 

Intermediate marsh mean VV (4.08 ± 0.05) was significantly 

greater than that of the fresh marsh (3.37 ± 0.07). Saline 

marsh had the lowest mean VV (2.53 ± 0.10) but did not differ 

from brackish marsh (2.75 ± 0.10) (fig. 4). Analysis of the 

relation between marsh type and year revealed no significant 

interaction effects. There was a trend, however, of increasing 

mean VV throughout the study regardless of marsh type 

(fig. 5). The largest variations occurred in fresh marsh and 

intermediate marsh, with low values during 2010 and 2008 

respectively, while the other marsh types showed no major 

negative response over the same period.

Basin Trends

An ANOVA detected a significant main effect of 

hydrologic basin (F7, 2304 = 33.82, p < 0.0001). Mean VV was 

greatest in the active deltaic basins of the Mississippi and 

Atchafalaya Rivers: the Mississippi River Delta hydrologic 

basin and the Atchafalaya hydrologic basin (fig. 6). The 

Mermentau hydrologic basin had the lowest mean VV but did 

not statistically differ from the Calcasieu/Sabine hydrologic 

basin; the other five hydrologic basins produced similar mean 

VV and were not significantly different from one another. The 

Atchafalaya hydrologic basin was removed from the analysis 

because it did not contain all marsh types. The basin-bymarsh-type interaction was also significant (F21, 2304 = 29.89, p 

< 0.0001), with the largest difference in the overall trend being 

the extremely high mean VV of the intermediate marshes in 

the Mississippi River Delta hydrologic basin. Intermediate 

marsh dominated the overall high mean VV of the Mississippi 

River Delta hydrologic basin; mean VV values of the other 

marsh types in this basin were more in accordance with values 

from the other basins coastwide (fig. 7).
Results 5

2006 2007 2008 2009 2010 2011 2012 2013

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

CD

BC

D

AB AB AB AB

A

Mean vegetation volume, in cubic meters

Year

laf15-ESSC00-0702_fig02

Figure 2. Vegetation volume means from 2006 to 2013 with yearly variation in average vegetation volume on a coastwide scale for 

hydrologic basins in coastal Louisiana. Marsh types not identified by the same letter are significantly different at p = 0.05.

AT BA BS CS ME MR PO TE TV

0

1

2

3

4

5

6

7

8

9

2006 

2007 

2008 

2009 

2010 

2011 

2012 

2013 

Mean vegetation volume, in cubic meters

Hydrologic basin

EXPLANATION

Figure 3. Vegetation volume means per hydrologic basin in coastal Louisiana over the 8-year study period from 2006 to 2013. AT, 

Atchafalaya; BA, Barataria; BS, Breton Sound; CS, Calcasieu/Sabine; ME, Mermentau; MR, Mississippi River Delta; PO, Pontchartrain; TE, 

Terrebonne; TV, Teche/Vermilion.
6 Coastwide Reference Monitoring System (CRMS) Vegetation Volume Index

Fresh Intermediate Brackish Saline

0

1

2

3

4

5

B

A

C

C

Mean vegetation volume, in cubic meters

Marsh type

laf15-ESSC00-0702_fig04

Figure 4. Vegetation volume means of all marsh types averaged over the 8-year study period from 2006 to 2013 in coastal Louisiana. 

Marsh types not identified by the same letter are significantly different at p = 0.05.

2006 2007 2008 2009 2010 2011 2012 2013

0

1

2

3

4

5

Fresh 

Intermediate 

Brackish 

Saline 

Mean vegetation volume, in cubic meters

EXPLANATION

Year

Figure 5. Vegetation volume means of all marsh types from 2006 to 2013 in coastal Louisiana. 
Results 7

AT BA BS CS ME MR PO TE TV

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

4.5

5.0

5.5

6.0

B

B

DE

E

A

BCD C CD

Mean vegetation volume, in cubic meters

Hydrologic basin

laf15-ESSC00-0702_fig06

Figure 6. Vegetation volume means per hydrologic basin over the 8-year study period from 2006 to 2013 in coastal Louisiana. The 

Atchafalaya hydrologic basin was removed from comparison as it did not contain all marsh types. Basins not identified by the same 

letter are significantly different at p = 0.05. AT, Atchafalaya; BA, Barataria; BS, Breton Sound; CS, Calcasieu/Sabine; ME, Mermentau; 

MR, Mississippi River Delta; PO, Pontchartrain; TE, Terrebonne; TV, Teche/Vermilion.

AT BA BS CS ME MR PO TE TV

0

1

2

3

4

5

6

7

8

9

10

11

Fresh 

Intermediate 

Brackish 

Saline 

Mean vegetation volume, in cubic meters

Hydrologic basin

EXPLANATION

Figure 7. Vegetation volume means per hydrologic basin and marsh type averaged over the 8-year study period from 2006 to 2013 in 

coastal Louisiana. AT, Atchafalaya; BA, Barataria; BS, Breton Sound; CS, Calcasieu/Sabine; ME, Mermentau; MR, Mississippi River Delta; 

PO, Pontchartrain; TE, Terrebonne; TV, Teche/Vermilion.
8 Coastwide Reference Monitoring System (CRMS) Vegetation Volume Index

Overall Vegetation Volume Trends 

The trends observed in the VV data were also present 

in the VVI data. Coastwide yearly mean VVI from 2006 to 

2013 (fig. 8) followed the same pattern as did VV over the 

same temporal scale. The mean VVI generally increased from 

a low of 41.8 in 2006 to a maximum of 52.6 in 2010; in 2011 

it was essentially unchanged, and in 2012 it fell marginally 

(fig. 8). The annual VVI mean varies, but the range of the 

distribution remains fixed at 0–100 (fig. 9). There were annual 

changes in the VVI score at the CRMS site, project, and basin 

scales. The spatial variation in the VVI for 2012 indicated 

locations where robust stands of vegetation were grouped 

together (green symbols) and, conversely, locations with low 

three-dimensional vegetation structure cluster (red symbols) 

(fig. 10). Most of the CRMS sites in the Mississippi River 

Delta hydrologic basin are in the 75th quartile coastwide, 

whereas the CRMS sites on Marsh Island are in the 25th 

quartile, displaying areas of both positive and negative VVI 

trajectories. Proximal hydrologic basins displayed similar 

annual patterns in VVI, such as the increases in the Calcasieu/

Sabine and Mermentau hydrologic basins from 2006 to 2012 

(fig. 11). In contrast, the VVIs in the Mississippi River Delta, 

Breton Sound, and Atchafalaya hydrologic basins decreased in 

2008 and then recovered at different rates.
Results 9

2006 2007 2008 2009 2010 2011 2012 2013

0

20

40

60

80

100

Year

Vegetation Volume Index (VVI) score

Figure 8. Mean Vegetation Volume Index (VVI) score by year from 2006 to 2013 for hydrologic basins in coastal Louisiana.

2006 2007 2008 2009 2010 2011 2012 2013

0

10

20

30

40

50

60

70

80

90

100

Vegetation Volume Index (VVI) score

Year

EXPLANATION

90th percentile

75th percentile

50th percentile

(median)

25th percentile

10th percentile

Mean

Interquartile

range

Outlier

Figure 9. Distribution of Vegetation Volume Index (VVI) scores across all years of the study data collection (2006–2013) with the 

annual means.
LOUISIANA

TEXAS

MISSISSIPPI

Areaenlarged

Barataria

Teche/

Vermilion

Mermentau

Calcasieu/

Sabine

Chenier Plain

Gulf of Mexico

Atchafalaya

Bre

Sou

Terrebonne

93°0' 92°0' 91°0' 90°0' 

28°0'

31°0'30°0'29°0'

Base from 2014 Landsat OLI 8 Mosaic Band 5April 15, 2015

Marsh

Island

Hydrologic basinboundary 

0 10 20 3

EXPLANATION 0 10 20 30 40 5

-7.4 to -1.0-0.9 to -0.3-0.2 to 0.3

0.4 to 1.01.1 to 9.2

Change in vegetation volume

between 2008 and 2012, in cubic meters

Study area

laf15-ESSC00-0702_fig01

Figure 10. Vegetation Volume Index (VVI) score in hydrologic basins in coastal Louisiana at each study site during 2012 separated into 25th and 75th 
Discussion and Conclusions 11

laf15-ESSC00-0702_fig11

AT BA BS CS ME MR PO TE TV

0

10

20

30

40

50

60

70

80

90

100

2006 

2007 

2008 

2009 

2010 

2011 

2012 

2013 

Vegetation Volume Index (VVI) score

Hydrologic basin

EXPLANATION

Figure 11. Mean Vegetation Volume Index (VVI) score per hydrologic basin over the 8-year study period from 2006 to 2013 in coastal 

Louisiana. AT, Atchafalaya; BA, Barataria; BS, Breton Sound; CS, Calcasieu/Sabine; ME, Mermentau; MR, Mississippi River Delta; PO, 

Pontchartrain; TE, Terrebonne; TV, Teche/Vermilion.

Discussion and Conclusions

The VV can be used to examine both spatial and 

temporal trends in the coastal marshes of Louisiana. One of 

the major findings of the preliminary VV investigation was 

that the active deltas, Mississippi River Delta and Atchafalaya 

hydrologic basins, generated more VV than did the abandoned 

deltas and the Chenier Plain. The marshes in the Mississippi 

River Delta hydrologic basin contained significantly more VV 

than did the marshes of other hydrologic basins, including 

the Atchafalaya. A likely explanation for the increase in 

observed VV in the Mississippi River Delta, as well as 

in the Atchafalaya River Delta to a lesser extent, is the 

cyclical availability of nutrients, sediments, and soil salinity 

reduction in these two alluvial locations. The variation in 

VV between these two deltas is likely due to the maturity of 

the Mississippi River Delta and its general erosive pattern 

and the relative youth of the Atchafalaya River Delta and its 

current land area expansion. The latter contains expansive 

annual mud flat formation and colonization, whereas the 

former is in a state of declining land mass and monoculture 

stability. The Mississippi River Delta is dominated by robust 

monospecific stands of perennial Phragmites australis that 

are classified as intermediate marsh by the current CRMS 

marsh type algorithm. This species generally needs stability 

and time to colonize an area (Grace and Tilman, 1990). 

Because of the formation dynamics of the Atchafalaya River 

Delta, its vegetation cohort is more likely dominated by 

annuals that can take advantage of the seasonal sediment 

and nutrient availability without remaining permanent 

residents of a specific location that could change drastically 

from year to year. 

Conversely, VV is significantly reduced in the 

Mermentau and Calcasieu/Sabine hydrologic basins because 

of their distance from large alluvial inputs and separate but 

related stressors. The Calcasieu/Sabine hydrologic basin is 

severely salt stressed because of the landward penetration of 

the Calcasieu Ship Channel from the Gulf of Mexico to Lake 

Charles, La. This salinity stress, over much of the basin, limits 

the plant species that can colonize the area, thereby reducing 

the potential for multiple vegetation layers to be present. 
12 Coastwide Reference Monitoring System (CRMS) Vegetation Volume Index

Instead much of the basin is dominated by monospecific stands 

of Spartina patens in areas where the elevation is suitable. 

This overall reduction in species diversity due to salinity 

stress is a large component of consistently low VV in the 

basin. In the Mermentau hydrologic basin, however, there are 

areas that are submerging because of hydrologic alterations. 

Agricultural and other types of impoundments keep large areas 

of the basin under near-permanent year-round flooding, which 

exacerbates sea-level rise and subsidence along Louisiana’s 

coast (Morris and others, 2002). The vegetation of the 

Mermentau hydrologic basin, where VV is low and flooding 

is high, is typical of other impounded coastal areas dominated 

by flood-tolerant perennials and seasonal annuals. Both the 

Calcasieu/Sabine and the Mermentau hydrologic basins score 

low on the Hydrologic Index and are dependent on localized 

upland rainfall for nutrient, sediment, and freshwater input. 

As a result, their three-dimensional marsh structure is likely 

to be substantially less than the other, more alluvial basins 

previously discussed. This differentiation in VV scores 

among basins that are undergoing different environmental 

disturbances indicates that the VV is an efficient method for 

looking at vegetation differences not only across basins but 

also at other scales in which environmental variation occurs. 

The cluster of low VV CRMS sites on Marsh Island in the 

Teche/Vermilion hydrologic basin in 2012 represents extensive 

herbivory damage by Myocastor coypus, which led to an 

extermination effort in 2013 by the Louisiana Department of 

Wildlife and Fisheries. This eradication effort in conjunction 

with an unusually cold winter in 2013 has led to a significant 

rebound in VV through 2014 and which has carried forward 

into 2015 (Mark Mouledous, unpub. data, 2015).

The temporal span of the CRMS data, now reaching 

nearly a decade, provides the necessary framework to examine 

annual trends such as hurricanes, droughts, floods, and other 

disruptive factors interspersed among less dynamic years. 

The CRMS database was begun in 2006, and the damage 

associated with Hurricanes Katrina and Rita in 2005 was still 

very evident in the yearly VV means. The low VV means in 

2006 and 2008 are likely a result of hurricane disturbance 

causing the lowest VV in the 8-year study. It is likely that in 

2008 Hurricanes Gustav and Ike caused the temporary VV 

rebound of 2007 to reverse and made 2008 the lowest VV year 

to date along the Louisiana coast. Conversely, 2009 through 

2013 had relatively high VV means when compared to 2006 

and 2008, but there were some mean fluctuations in the VV 

over this period, as 2011 was the highest VV measured. 

The high VV that year was likely due to conflicting events. 

The historically high levels of the Mississippi River in 2011 

affected the east and central coasts of Louisiana, while drought 

conditions were predominant west of the Atchafalaya River 

Delta. This historic flooding early in the growing season 

may have stimulated vegetative growth later in the season 

throughout much of the coastal zone. The western portion of 

the coast, which in many areas underwent prolonged drought 

conditions, also produced larger, more robust vegetation 

in areas where persistent flooding might normally retard 

vegetation growth. The Deepwater Horizon oil spill of 

2010 did not have a significant impact on VV except in the 

Mississippi River Delta hydrologic basin, where VV dropped 

to its second lowest level of the study. This decreased VV in 

the Mississippi River Delta hydrologic basin following the 

oil spill was due to lack of site access and logistical issues 

rather than direct oiling of vegetation within the annual 

vegetation survey. The sites in the Mississippi River Delta 

hydrologic basin that were not accessible because of oil spill 

restrictions were generally among the most productive VV 

sites in the basin, and on the coast, because they are dominated 

by Phragmites australis. Access limitations prevented site 

assessment, thereby lowering the Mississippi River Delta 

hydrologic basin VV average in 2010. The CRMS network 

does not have stations located on barrier islands and thus did 

not record major damage from oil or an oil-induced coastwide 

reduction to the VV in 2010. As a result of the longevity of 

the CRMS network, capturing both positive and negative 

episodic variability from the annual norm has been possible. 

This variability and its correlation to specific environmental 

conditions bolster the ability of landowners, managers, and 

planners to implement projects and restoration strategies that 

either are effective across this variation or help to diminish the 

negative effects. 

Many of the CWPPRA restoration projects have goals 

to establish and promote vegetation growth rather than to 

establish a particular species or community. Newly restored 

sites often have low initial FQI scores for many years 

because of the presence of annual species that either do not 

indicate stability or are only common in high numbers during 

early successional stages. Therefore, at the project scale, an 

assessment of the VV and the indexed values may be more 

informative than relying solely on the FQI for monitoring and 

adaptive management purposes. The VV will be calculated 

at the coastwide scale annually and will be used to generate 

geospatial maps to depict areas where the VV is maintaining 

or increasing or conversely reducing as vegetation becomes 

more sparse or stunted. Interpretation of the VV can be used 

to identify areas where degradation is taking place and where 

healthy thresholds are in place. With the potential of several 

large-scale Mississippi River diversions being completed over 

the next two decades, the receiving basins of those diversions 

will be disrupted in the short term as new vegetated habitats 

emerge and eventually evolve to stable states. Using VV to 

assess this type of restoration strategy could work well as 

species-specific transitions are ignored and more robust and 

vigorous marshes are ranked as superior. Most restoration 

projects disrupt the stable and typically deteriorated state 

of the wetland into which they are placed. This disruption 

causes successional changes in the local environment as a 

new stable state is reached. During this transitional phase 

many negatively perceived plant species may persist. The 

FQI is sensitive to these changes and in most cases responds 

negatively to these shifts, as it is designed to do. Although the 

VV has utility in its current form, future CRMS data will add 

to the predictive power of this variable on a project, basin, 
References Cited 13

and coastwide scale. There are ways, however, to improve 

the usefulness of this metric, such as developing a link with 

aboveground annual production or peak standing crop biomass 

across marsh types. This linkage of the VV to a production 

metric would strengthen the CRMS database and coastal data 

collection as a whole by allowing for a more efficient and 

cost effective measure of productivity change at a restoration 

project scale. Including the VV and the VVI as metrics for 

use in assessing coastal planning and monitoring projects 

will allow a broader view of the vegetation present beyond a 

species-specific approach, which is needed to more accurately 

determine restoration success or failure.

The development and analysis of the VV and the VVI 

can benefit wetland restoration planning and monitoring 

efforts in coastal Louisiana. Vegetation primary productivity 

can be an important indicator of wetland health; however, 

accurately measuring primary productivity is labor intensive, 

lengthy, and expensive. The VV calculation uses data already 

collected at each of the 331 herbaceous marsh CRMS sites 

coastwide and can be a proxy for productivity. VV is also 

amenable for comparison with other historical datasets of 

vegetation cover and height variables in wetlands. Spatial 

and temporal trends in VV can be used to document the 

effects of human activities, climate, weather, and restoration 

projects on the coastal landscape. These trends can inform 

managers, stakeholders, and landowners of where restoration 

is needed or where restoration efforts are being implemented 

effectively with regard to vegetation structure. The VV may 

also inform restoration planning by providing data on whether 

specific types of restoration have proven useful in increasing 

vegetation within a specific habitat type or environmental 

niche. Overall, the VV is another potential tool for informing 

decision making in wetland habitats where time and monetary 

restrictions prevent a more intensive approach.

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