U.S. Department of the Interior

U.S. Geological Survey

Faunal and Vegetation Monitoring in Response to 

Harbor Dredging in the Port of Miami

By Andre Daniels, Rachael Stevenson, Erin Smith, and Michael Robblee

Open-File Report 2018–1052
U.S. Department of the Interior

RYAN K. ZINKE, Secretary

U.S. Geological Survey

William H. Werkheiser, Deputy Director

 exercising the authority of the Director

U.S. Geological Survey, Reston, Virginia: 2018

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Suggested citation:

Daniels, A., Stevenson, R., Smith, E., and Robblee, M., 2018, Faunal and vegetation monitoring in 

response to harbor dredging in the Port of Miami: U.S. Geological Survey Open-File Report 2018-1052, 

38 p., https://doi.org/10.3133/ofr20181052.

ISSN 2331-1258 (online)
iii
iv

Acknowledgments

We would like to thank Nova Southeastern University Halmos College of Natural Sciences and 

Oceanography for use of research facilities. We thank the following Nova Southeastern 

University research students that participated in the study with field collections and laboratory 

work, including Candace Grimes, Elizabeth Colhoun, David Roche, and Emily Powell as well as

Jessica Lee and Ross Boucek from Florida International University (FIU). We thank Howard 

Jelks of USGS, Dr. Chris Blanar of NOVA Southeastern University, and Brian Smith with 

Cherokee Nation Technologies for their help with PRIMER 7 analysis and graphics in R 

statistical computing. We also thank Miami-Dade County Division of Environmental Resources 

Management (DERM) for their continued support. Finally, a special thanks to Joan Browder of 

the National Oceanic and Atmospheric Administration for her lifetime of commitment in 

preserving southern Florida’s seagrass communities. All work was conducted under sampling 

permit SAL–14–1584–SR from the Florida Fish and Wildlife Conservation Commission.
v

Contents

Abstract ....................................................................................................................................................... 10

Introduction.................................................................................................................................................. 10

Background ................................................................................................................................................. 11

Seagrasses .............................................................................................................................................. 11

Dredging................................................................................................................................................... 11

Faunal Monitoring in Response to Harbor Dredging ................................................................................ 12

Methods....................................................................................................................................................... 12

Sampling Locations.................................................................................................................................. 12

Experimental Design ................................................................................................................................ 12

Physical and Environmental Field Measurements.................................................................................... 13

Braun-Blanquet Method ........................................................................................................................... 14

Animal Collection Method......................................................................................................................... 15

Statistical Analysis.................................................................................................................................... 15

Results......................................................................................................................................................... 16

Turbidity ................................................................................................................................................... 16

Seagrass Density ..................................................................................................................................... 18

Animal Totals ........................................................................................................................................... 21

Turbidity, Seagrass Density, and Animal Totals....................................................................................... 26

BACI......................................................................................................................................................... 28

Discussion ................................................................................................................................................... 31

Turbidity ................................................................................................................................................... 31

Seagrass Density ..................................................................................................................................... 31

Animal Totals ........................................................................................................................................... 35

Selected References ................................................................................................................................... 36

Figures

Figure 1. Google Earth image of study areas (left) with both basins outlined in red. The top area is 

North Biscayne Bay (NBB) and the bottom area is Port of Miami (POM). A map of Biscayne Bay (right) 

showing the 30 cells in each of the two sampling grids for North Biscayne Bay (white) and Port of Miami 

(green). 13

Figure 2. Location of Braun-Blanquet replicate habitat samples in relation to the anchored boat and 

throw-trap. 14

Figure 3. Boxplots displaying turbidity values (in nephelometric turbidity units [NTUs]) in North 

Biscayne Bay (NBB) and Port of Miami (POM) in A, each sampling year throughout Fish and Invertebrate 

Assessment Network (FIAN) and Faunal Monitoring in Response to Harbor Dredging (FMHD), B, each year 
vi

of the FMHD study (2014-2016) in each of the two study areas, and C, each basin by season (wet or dry) in 

all years of the FMHD study. The box represents the 25 to 75% interquartile range of values, the bold 

horizontal line inside the box represents the median value, the upper dashed line represents the maximum 

value of the third quartile plus 1.5 times the interquartile range, the lower dashed line is the minimum value 

of the first quartile minus 1.5 times the interquartile range, and circles are outliers. No overlap in the 

interquartile boxes indicates a significant difference, overlap in the interquartile boxes but not the medians 

indicates a likely significant difference, overlap in the interquartile boxes and the medians suggests no 

significant difference.................................................................................................................................... 18

Figure 4. Boxplots displaying differences in average seagrass densities using the Braun-Blanquet 

(1965) scale in North Biscayne Bay (NBB) and Port of Miami (POM) in A, each sampling year throughout 

Fish and Invertebrate Assessment Network (FIAN) and Faunal Monitoring in Response to Harbor Dredging 

(FMHD), B, each year of the FMHD study (2014-2016) in each of the two study areas, and C, each basin 

by season (wet or dry) in all years of the FMHD study. The box represents the 25 to 75 percent interquartile 

range of values, the bold horizontal line inside the box represents the median value, the upper dashed line 

represents the maximum value of the third quartile plus 1.5 times the interquartile range, the lower dashed 

line is the minimum value of the first quartile minus 1.5 times the interquartile range, and circles are 

outliers. No overlap in the interquartile boxes indicates a significant difference, overlap in the interquartile 

boxes but not the medians indicates a likely significant difference, overlap in the interquartile boxes and the 

medians suggests no significant difference. ................................................................................................ 20

Figure 5. Boxplots displaying differences in animal total counts in North Biscayne Bay (NBB) and Port 

of Miami (POM) in A, each sampling year throughout Fish and Invertebrate Assessment Network (FIAN) 

and Faunal Monitoring in Response to Harbor Dredging (FMHD), B, each year of the FMHD study (2014-

2016) in each of the two study areas, and C, each basin by season (wet or dry) in all years of the FMHD 

study. The box represents the 25 to 75% interquartile range of values, the bold horizontal line inside the 
vii

box represents the median value, the upper dashed line represents the maximum value of the third quartile 

plus 1.5 times the interquartile range, the lower dashed line is the minimum value of the first quartile minus 

1.5 times the interquartile range, and circles are outliers. No overlap in the interquartile boxes indicates a 

significant difference, overlap in the interquartile boxes but not the medians indicates a likely significant 

difference, overlap in the interquartile boxes and the medians suggests no significant difference. ............. 23

Figure 6. Bar graphs showing community structure changes from 2014 to 2016 in North Biscayne Bay 

(NBB) and Port of Miami (POM) for A, fish composition in NBB, B, fish composition in POM, C, shrimp 

composition in NBB, and D, shrimp composition in POM. Fishes and caridean shrimps were separated by 

genus. 25

Figure 7. Kendall’s tau correlation with 95% confidence intervals showing a negative correlation between 

A, turbidity (in nephelometric turbidity units [NTUs] and seagrass density; B, turbidity and combined totals 

of shrimps, fishes, and crabs; and C, a positive correlation between seagrass density and combined totals 

of shrimp, fishes, and crabs......................................................................................................................... 28

Figure 8. Nonmetric multidimensional scaling Euclidean distance graph created by using PRIMER 7. 

Graph visually depicts the resemblance of North Biscayne Bay (NBB) and Port of Miami (POM) community 

structures to each other through the years. ................................................................................................. 30

Figure 9. Average turbidities for North Biscayne Bay (NBB) and Port of Miami (POM) observed 

throughout the study period for the Faunal Monitoring in Response to Harbor Dredging (FMHD) and Fish 

and Invertebrate Assessment Network (FIAN) studies as a comparison of conditions before and after 

dredging. 33

Figure 10. Average seagrass densities (as defined in table 1) for North Biscayne Bay (NBB) and Port of 

Miami (POM) observed throughout the study period for the Faunal Monitoring in Response to Harbor 

Dredging (FMHD) and Fish and Invertebrate Assessment Network (FIAN) studies as a comparison of 

conditions before and after dredging. .......................................................................................................... 34
viii

Tables

Table 1. Braun-Blanquet categories of cover abundance rating used to quantify the seagrass community 

present at each site sampled (Braun-Blanquet, 1965)................................................................................. 15

Table 2. Matrix showing mean, standard deviation (SD), and correlation between each of the factors of 

Faunal Monitoring in Response to Harbor Dredging (FMHD) data. Asterisks indicate correlations ≥0.15 that 

were tested for statistical significance.......................................................................................................... 16

Table 3. Permutational multivariate analysis of variance (PERMANOVA) test results of total numbers of 

caridean shrimp, penaeid shrimp, and fish by location, year, season, and interactions between factors for 

Faunal Monitoring in Response to Harbor Dredging (FMHD) data. Sources of variation in models, 

df=degrees of freedom, SS=sums of squares, MS=mean squares, Pseudo-F statistic, and 

P(perm)=attained significance level. Results were considered significant at P(perm)<0.05)....................... 29
9

Conversion Factors

U.S. customary units to International System of Units

Multiply By To obtain

Length

foot (ft) 0.3048 meter (m)

Conversion Factors

International System of Units to U.S. customary units

Multiply By To obtain

Length

millimeter (mm) 0.03937 inch (in.)

meter (m) 3.281 foot (ft) 

meter (m) 1.094 yard (yd) 

Area

square meter (m2) 0.0002471 acre 
10

Faunal and Vegetation Monitoring in Response to 

Harbor Dredging in the Port of Miami

By Andre Daniels1, Rachael Stevenson2, Erin Smith2, and Michael Robblee3

1

U.S. Geological Survey Wetland and Aquatic Research Center; 2 Nova Southeastern University, 

Dania Beach, Florida; 3 U.S. Geological Survey Wetland and Aquatic Research Center, emeritus

Abstract

Seagrasses are highly productive ecosystems. A before-after-control-impact (BACI) 

design was used to examine effects of dredging on seagrasses and the animals that inhabit them. 

The control site North Biscayne Bay and the affected site Port of Miami had seagrass densities

decrease during both the before, Fish and Invertebrate Assessment Network 2006-2011, and 

after, Faunal Monitoring in Response to Harbor Dredging 2014-2016, studies. Turbidity levels 

increased at North Biscayne Bay and Port of Miami basins during the Faunal Monitoring in 

Response to Harbor Dredging study, especially in 2016. Animal populations decreased 

significantly in North Biscayne Bay and Port of Miami in the Faunal Monitoring in Response to 

Harbor Dredging study compared to the Fish and Invertebrate Assessment Network study. 

Predictive modeling shows that numbers of animal populations will likely continue to decrease if

the negative trends in seagrass densities continue unabated. There could be effects on several 

fisheries vital to the south Florida economy. Additional research could determine if animal 

populations and seagrass densities have rebounded or continued to decrease.

Introduction

Seagrass communities are among the most productive and ecologically important global 

ecosystems. They provide high primary production that supports diverse food webs, maintain 

water quality by filtering contaminants and binding sediments to reduce turbidity, and serve as a 

resource for various marine species. Resources provided include protective cover, food, and 

nursery habitat. However, seagrass beds are extremely sensitive to anthropogenic effects and 

therefore have been placed among the most endangered ecosystems in the world (d’Avack and 

others, 2014, Schlacher-Hoenlinger and Schlacher, 1998). One of the most detrimental human 

activities that damages seagrass beds is dredging and accompanying turbidity. Dredging to 

accommodate commercial ships causes physical damage to seagrass beds and lasting ecological 

effects by disturbing seagrass sediments (Erftmeijer and Lewis, 2006). The present study 

focused on the effects of the Deep Dredge project at the Port of Miami, which was implemented 

in 2014–2015 to allow larger ships to access and utilize the port. 

This study is a continuation of the Faunal Monitoring in Response to Harbor Dredging 

(FMHD) project. Faunal Monitoring in Response to Harbor Dredging monitors and assesses 

faunal abundance and composition with associated vegetation in North Biscayne Bay (NBB) and 

the Port of Miami (POM). The FMHD project is designed to track possible effects of dredging 

on seagrass habitats adjacent to the port. To allow for comparison of results, the experimental 

design and methods from the South Florida Fish and Invertebrate Assessment Network (FIAN) 
11

were used, which was part of the Restoration, Coordination, and Verification (RECOVER, 2004) 

program of the Comprehensive Everglades Restoration Plan (CERP) (Robblee and Browder,

written communication to USACE, USGS, and NOAA National Marine Fisheries Service). 

Samples were collected from both locations over 3 years, 2014–2016, to assess the status of the 

seagrass ecosystems before, during, and after completion of the dredging project. FIAN samples 

were collected in NBB and POM from 2005 to 2011. These data were used as a baseline to 

compare results from the FMHD.

Background

Seagrasses

Seagrasses are flowering vascular plants that are widespread in estuarine and marine 

environments around the world. Seagrass communities are one of the most productive coastal 

marine ecosystems and a major benthic feature of the shallow coastal waters of southern Florida

(Short and others, 2007). Seagrass beds serve as food, habitat, and nursery grounds for a host of 

marine organisms. For example, sea turtles and manatees rely heavily on seagrass for food

(Serafy and others, 1997). Seagrasses also provide habitat for diverse vertebrate and invertebrate 

communities and support economically important fisheries, such as the Caribbean spiny lobster, 

stone crab, and pink shrimp. 

Seven species of seagrass can be found in southern Florida, the majority of coverage 

consists of Thalassia testudinum (turtle grass), Halodule wrightii (shoal grass), and Syringodium 

filiforme (manatee grass). Turtle grass is the dominant species in distribution and biomass and is 

an important component of the diet of the green sea turtle (Chelonia mydas) (Fuentes and others,

2006). Shoal grass tends to be locally dominant in recently disturbed areas, and often becomes 

established rapidly after-disturbance. This species is typically found in areas with extreme 

temperatures and salinities or in low light conditions. Manatee grass is generally prominent in 

deeper marine waters compared to shallower shoal and turtle grass beds (Fourqurean and others,

2001).

Dredging

Dredging is necessary in large ports around the world to maintain and deepen channels

to allow access for large cargo ships (Erftemeijer and others, 2006). The Port of Miami is an 

economically important seaport that supports about 225,000 jobs and contributes approximately 

$30 billion to the local economy. The Deep Dredge Project in the Port of Miami was designed to 

widen and deepen the channel to 50 feet to allow super post-Panamax megaships to utilize the 

port. This project was completed in September 2015 (U.S. Army Corps of Engineers, n.d.). 

The dredging process causes large-scale disturbance in the surrounding area and can lead 

to many negative effects on the ecosystem including decreases in water quality with increased 

turbidity and sedimentation, hydrographic changes, and shifts in the community structure of

plants and organisms (Lohrer and Wetz, 2003; Behringer and Butler, 2006). One of the most 

significant dredging related issues for seagrasses is mechanical destruction, including physical 

removal or burial of the grasses. For the organisms that inhabit seagrass beds, there can be 

decreases in primary production, loss of inhabitable space, decreases in the nutritional quality of 

food, and reduced feeding success of visual predators and filter feeders (Essink, 1999). The 
12

increased silt layer on the seafloor can also lead to anoxic bottom conditions and smothering of 

corals, sponges, and grasses. 

Faunal Monitoring in Response to Harbor Dredging

The FMHD project was designed by using the FIAN methodology to evaluate the effects

of dredging in the Port of Miami over 3 years (2014–2016). The purpose of FIAN was to monitor 

seagrass fauna, including fish, crabs, and caridean and penaeid shrimp, in relation to benthic 

vegetation, substrate, and environmental conditions, turbidity in particular. Samples were 

collected at the end of the dry and wet seasons, April and September respectively. The 7-year 

FIAN project (from 2005 to 2011) provided a baseline prior to dredging the port (Robblee and 

Browder, written communication to USACE, USGS, and NOAA National Marine Fisheries 

Service). FMHD was carried out by the U. S. Geological Survey (USGS) using laboratory 

facilities from Nova Southeastern University’s Oceanographic Center in Dania Beach, Florida. 

Methods

Sampling Locations

This project compared seagrass communities in two basins, NBB and the POM (fig. 1). 

Sampling sites in NBB are between Miami and the Miami Beach barrier island from John F. 

Kennedy Causeway to Julia Tuttle Causeway. The POM sampling sites are located south of the 

port down to Rickenbacker Causeway. 

Experimental Design

The sampling design of the FMHD was the same as that of FIAN which utilized a 

sampling grid of 30, equal-sized hexagonal cells. Thirty sites were used for statistical analysis. 

Two FIAN sampling locations, POM and NBB, were selected. The POM sites were located 

adjacent to the area to be dredged, whereas the NBB would serve as a “control” to identify 

regional patterns. The premise was if similar changes occurred at both sites, dredging may not 

account for the observed changes, whereas changes only observed in POM may be attributable to 

dredging activities. Sample sites were visited biannually at the end of the dry and wet seasons in 

the first 2 weeks of April and September, respectively. Fig. 1 shows the 30 cells sampled in each 

of the two locations. Within each cell, up to five random locations were visited and inspected for 

the presence of benthic vegetation, including seagrasses and algae. Once a location with benthic 

vegetation was found, that station was sampled and no alternate locations were visited. If 

vegetation was absent, the remaining alternates were visited until vegetation was present. If each 

of the alternates was found devoid of vegetation, the fifth site was sampled and categorized as 

unvegetated.
13

Figure 1. Google Earth image of study areas (left) with both basins outlined in red. The top area is North 

Biscayne Bay (NBB) and the bottom area is Port of Miami (POM). A map of Biscayne Bay (right) showing 

the 30 cells in each of the two sampling grids for North Biscayne Bay (white) and Port of Miami (green). 

Physical and Environmental Field Measurements

Once a sampling location was chosen, coordinates were recorded by using a Garmin 

GPSMAP492 Global Positioning System unit (World Geodetic System 1984 datum). Physical 

and environmental field measurements were taken at each of the 30 sample sites. Salinity and 

temperature were measured within 1 meter (m) of the surface and within 1 m of the bottom

substrate surface at each site by using a hand-held WTW 330i Conductivity Field Meter (or 

equivalent, 315i). Turbidity measurements were made by collecting a single grab sample in 

undisturbed water just below the surface at the collection site. The sample was placed on ice on 

the boat, and stored in a refrigerator until analysis at the lab. An HF Scientific DRT–15CE 

portable turbidity meter over three selectable ranges, (0–10, 0–100, and 0–1,000 nephelometric 

turbidity units (NTUs), was used to measure turbidity.
14

Braun-Blanquet Method

The project utilized a modified Braun-Blanquet technique to quantify vegetation cover 

and abundance (Braun-Blanquet, 1965). The Braun-Blanquet technique involves visually 

quantifying the cover and abundance of seagrass and algae observed in a 0.25-square meter (m2)

quadrat. In total, six replicates were collected at each sample point, with five being distributed in 

a semicircle around the boat and throw-trap and the sixth being immediately next to the throwtrap (fig. 2). Substrate type was recorded along with species of vegetation present. Bottom 

substrate was categorized as mud, sandy mud, muddy sand, sand, coarse shell, rubble, Halimeda

(algae) hash, or a combination of these types. Seagrasses observed were Thalassia testudinum,

Halodule wrightii, Syringodium filiforme, and various Halophila species (for example, H. 

engelmanni, H. decipiens, H.johnsonii). The canopy height (general height of each taxon) was 

measured for each species of seagrass present, or the height of the algae measured if no seagrass 

was present. Each taxon was then assigned a density score (table 1). The upper end of the scale is 

generally for seagrasses and upright algae that cover more than 75 percent of the given quadrat. 

Littler and others (1989) and Green and Short (2003) were used to identify and characterize 

algae and seagrass, respectively.

 

Figure 2. Location of Braun-Blanquet replicate habitat samples in relation to the anchored boat and 

throw-trap. 

1

2

Throw-trap 6

3

4

5

Bow

Port

Stern

Starboard
15

Table 1. Braun-Blanquet categories of cover abundance rating used to quantify the seagrass community 

present at each site sampled (Braun-Blanquet, 1965).

Animal Collection Method

To quantitatively sample the epibenthos, a 1-m2 throw-trap was used at each of the 30 

cells in the sampling grid. The throw-trap was thrown into undisturbed water behind the boat and 

immediately covered with panels of weighted nylon netting (0.16-mm DELTA stretched mesh)

attached on parallel edges at the top of the trap. When the trap was in place, fish and 

invertebrates were collected with five separate passes of a sweep net. Sweep nets were dragged 

across the bottom inside the throw-trap while cover netting was pushed forward simultaneously 

to prevent the escape of animals. In water depths greater than 0.75 m, surface-supplied hookah

equipment was used. The five sweep nets were returned to the boat and rinsed over a 1-

millimeter (mm) sieve and placed in similar sized mesh netting bags. The samples were stored in 

an ice bath until they could be fixed in a 10 percent Formalin solution or frozen until the samples 

were sorted. The organisms were identified to the lowest possible taxonomic level and stored in 

70 percent Ethanol. 

Statistical Analysis

Statistical analyses included both parametric and nonparametric tests with a significance 

level of p<0.05. Data were tested for normality and homogeneity of variances to determine 

appropriate statistical test. Simple analysis of variance (ANOVA) was used to evaluate the 

relationships among study sites and years, environmental factors, and fauna/flora. These 

relationships included differences in turbidity, seagrass density, and faunal composition by years, 

locations, and seasons. Post-hoc multiple comparison tests were used on statistically significant 

models to determine which factors could be attributed to observed changes. Results were also 

compared with FIAN data as a baseline. Permutational multivariate analysis of variance 

(PERMANOVA) was used as the before-after-control-impact (BACI) test for differences in total 

numbers of caridean shrimp, penaeid shrimp, and fish by location, year, season, and interactions 

between factors (Smith and others, 1993; Smith, 2002). The biostatistics package Quest Research 

Limited PRIMER 7 was used to generate nonmetric multidimensional scaling plots to compare 
16

the community similarities before, during, and after dredging in POM and NBB. Data were 

normalized prior to generating a resemblance matrix based on Euclidean distance.

Results

Variables measured in this study included salinity, turbidity, temperature, seagrass 

density, and total counts of animals. A correlation matrix was used to show relationships 

between these factors (table 2). All correlations of 0.15 or higher were tested for significance, 

along with all temperature and salinity measurements. The significant negative correlation 

between salinity and temperature was expected because high salinity ocean waters are cooler. 

These two variables were not considered to be impacted by the dredging. The variables that were 

significantly altered during the project were turbidity, seagrass density, and total counts of 

animals. There was also a shift in faunal composition in caridean and penaeid shrimp and fish in 

NBB and POM over the course of the 3-year monitoring periods.

Table 2. Matrix showing mean, standard deviation (SD), and correlation between each of the factors of 

Faunal Monitoring in Response to Harbor Dredging (FMHD) data. Asterisks indicate correlations ≥0.15 that 

were tested for statistical significance. 

Factor Mean SD 1 2 3 4 5

1 Salinity 32.57 3.50 -

2 Turbidity 2.97 2.29 -0.10 -

3 Temperature 28.30 2.62 -0.40* -0.13 -

4 Seagrass 

density

1.28 1.07 0.13 -0.21* 0.05 -

5 Animal totals 28.53 44.75 0.11 -0.15* 0.08 0.41* -

Turbidity

During the FIAN and FMHD studies, turbidity (as NTU) was gradually decreasing 

overall until 2016, when values noticeably increased (fig. 3A). For both sites combined, one-way 

ANOVA showed a significant increase in surface water turbidity over the three years of FMHD 

(p<0.001), though there was no significant difference in turbidity by season or between both 

locations. Both locations showed significant differences in turbidity by year. Significant 

increases in turbidity (p<0.001) were observed in both NBB and POM over the 3 years (fig. 3B). 

There were significant differences in turbidity at NBB between 2014 and 2016 and between 2015

and 2016 (p<0.001), but not between 2014 and 2015. Similar differences were observed at POM 

where significant differences were observed among 2014 to 2016 and between 2015 and 2015 

(p<0.001) but not between 2014 and 2015. There was no significant difference in turbidity 

between seasons at the two locations (fig. 3C). 
17
18

Figure 3. Boxplots displaying turbidity values (in nephelometric turbidity units [NTUs]) in North Biscayne 

Bay (NBB) and Port of Miami (POM) in A, each sampling year throughout Fish and Invertebrate 

Assessment Network (FIAN) and Faunal Monitoring in Response to Harbor Dredging (FMHD), B, each year 

of the FMHD study (2014-2016) in each of the two study areas, and C, each basin by season (wet or dry) in 

all years of the FMHD study. The box represents the 25 to 75% interquartile range of values, the bold 

horizontal line inside the box represents the median value, the upper dashed line represents the maximum 

value of the third quartile plus 1.5 times the interquartile range, the lower dashed line is the minimum value 

of the first quartile minus 1.5 times the interquartile range, and circles are outliers. No overlap in the 

interquartile boxes indicates a significant difference, overlap in the interquartile boxes but not the medians 

indicates a likely significant difference, overlap in the interquartile boxes and the medians suggests no 

significant difference. 

Seagrass Density

Overall, seagrass density showed a significant decrease through time from the FIAN 

study to the FMHD study (p<0.001; fig. 4A). With both sites combined for FMHD, there was a 

significant change in seagrass density among years (p<0.001). At both locations, significant 

decreases in seagrass density were observed beginning in 2015 and into 2016 (fig. 4B). Seagrass 

density in NBB had a significant decrease by year (p<0.05). There was a significant difference 

between 2014 and 2016 (p<0.001) and between 2015 and 2016 (p<0.05), but no significant 
19

difference between 2014 and 2015. POM showed similar significant decreases by year 

(p<0.001). There was a significant difference between 2014 and 2016 (p<0.001) and between 

2015 and 2016 (p<0.001). Similar to NBB, there was no significant difference in seagrass 

density between years 2014 and 2015 (fig. 4), suggesting dredging had not yet had a measurable

impact. There were no significant differences in seagrass density between seasons at either 

location (fig. 4C). 
20

Figure 4. Boxplots displaying differences in average seagrass densities using the Braun-Blanquet (1965) 

scale in North Biscayne Bay (NBB) and Port of Miami (POM) in A, each sampling year throughout Fish and 
21

Invertebrate Assessment Network (FIAN) and Faunal Monitoring in Response to Harbor Dredging (FMHD), 

B, each year of the FMHD study (2014-2016) in each of the two study areas, and C, each basin by season 

(wet or dry) in all years of the FMHD study. The box represents the 25 to 75 percent interquartile range of 

values, the bold horizontal line inside the box represents the median value, the upper dashed line 

represents the maximum value of the third quartile plus 1.5 times the interquartile range, the lower dashed 

line is the minimum value of the first quartile minus 1.5 times the interquartile range, and circles are 

outliers. No overlap in the interquartile boxes indicates a significant difference, overlap in the interquartile 

boxes but not the medians indicates a likely significant difference, overlap in the interquartile boxes and the 

medians suggests no significant difference.

Animal Totals

There were significant differences in animal totals by year (p<0.05) and site (p<0.001), 

but no significant differences between seasons (fig. 5A-C). Overall, NBB showed slight although 

significant decreases in caridean shrimps (Alpheus, Hippolyte, Thor, Latreutes, Paleaemonetes., 

Periclimenes, and Processa), penaeid shrimps (Farfantepenaeus), and fishes (Floridichthys, 

Lucania, Ctenogobius, Gobiosoma, Microgobius, and Hippocampus) (p<0.05 for all) throughout 

the study period. Sites at POM also showed a similar significant decrease in carideans (p<0.05), 

penaeids (p<0.05), and fishes (p<0.001) throughout the study period (Figure 5B). There were 

significantly more animals at the POM than at the NBB for all 3 years (p<0.001). Caridean

shrimp, penaeid shrimp, and fish totals all showed significant changes throughout the FMHD in 

both locations. There were also considerable shifts observed in the community assemblages of 

fish and shrimp in both locations (fig. 6A-D). 
22
23

Figure 5. Boxplots displaying differences in animal total counts in North Biscayne Bay (NBB) and Port of 

Miami (POM) in A, each sampling year throughout Fish and Invertebrate Assessment Network (FIAN) and 

Faunal Monitoring in Response to Harbor Dredging (FMHD), B, each year of the FMHD study (2014-2016) 

in each of the two study areas, and C, each basin by season (wet or dry) in all years of the FMHD study. 

The box represents the 25 to 75% interquartile range of values, the bold horizontal line inside the box 

represents the median value, the upper dashed line represents the maximum value of the third quartile plus 

1.5 times the interquartile range, the lower dashed line is the minimum value of the first quartile minus 1.5 

times the interquartile range, and circles are outliers. No overlap in the interquartile boxes indicates a 

significant difference, overlap in the interquartile boxes but not the medians indicates a likely significant 

difference, overlap in the interquartile boxes and the medians suggests no significant difference. 
24
25

Figure 6. Bar graphs showing community structure changes from 2014 to 2016 in North Biscayne Bay 

(NBB) and Port of Miami (POM) for A, fish composition in NBB, B, fish composition in POM, C, shrimp 

composition in NBB, and D, shrimp composition in POM. Fishes and caridean shrimps were separated by 

genus. 
26

Turbidity, Seagrass Density, and Animal Totals

Kendall’s tau correlation tests were used to examine relationships between turbidity and 

seagrass density, turbidity and animal totals, and seagrass density and animal totals. The test 

showed that seagrass density was negatively correlated with turbidity (p<0.001, τ=-0.2076391; fig.

7A). Total animal abundance for the four groups combined, was also negatively correlated to 

turbidity (p<0.001, τ=-0.1471443; fig. 7B). Seagrass density was positively correlated to animal 

totals (p<0.001, τ= 0.4107495; fig. 7C).
27
28

Figure 7. Kendall’s tau correlation with 95% confidence intervals showing a negative correlation 

between A, turbidity (in nephelometric turbidity units [NTUs] and seagrass density; B, turbidity and 

combined totals of shrimps, fishes, and crabs; and C, a positive correlation between seagrass density

and combined totals of shrimp, fishes, and crabs. 

BACI 

Results from the BACI test helped to integrate changes in turbidity, seagrass density, and 

animal totals. Location explained most of the variation in the model, followed by year (table 3). 

Neither season nor any interaction between factors were significant at the p<0.05 level. This 

analysis confirms previous results that the POM had more total animals than NBB.
29

Table 3. Permutational multivariate analysis of variance (PERMANOVA) test results of total numbers of 

caridean shrimp, penaeid shrimp, and fish by location, year, season, and interactions between factors for

Faunal Monitoring in Response to Harbor Dredging (FMHD) data. Sources of variation in models, 

df=degrees of freedom, SS=sums of squares, MS=mean squares, Pseudo-F statistic, and 

P(perm)=attained significance level. Results were considered significant at P(perm)<0.05).

Source df SS MS Pseudo-F P (perm)

Location 1 33403 33403 28.238 0.001

Year 2 12064 6032.2 5.0994 0.001

Season 1 2164.5 2164.5 1.8298 0.145

Season*Location 1 3059.8 3059.8 2.5866 0.069

Year*Season 2 5034.8 2517.4 2.1281 0.081

Year*Location 2 2434.9 1217.4 1.0292 0.373

Year*Season*Location 2 2557.1 1278.6 1.0808 0.366

Residuals 348 348 4.1166E+05 1182.9

Total 359 359 4.7238E+05

 

PRIMER 7 was used to create a nonmetric multidimensional scaling diagram of 

community similarity at both sites through the three-year FMHD. The BACI Euclidean distance 

graph showed variability in NBB and POM throughout the study period and displays amount of 

similarity between both locations for each year (fig. 8). Before dredging began in 2014, NBB and 

POM were relatively similar to each other. Between 2014 and 2015, NBB remained similar to 

POM. Once the dredging commenced in 2015, POM became markedly variable compared with 

NBB and year centroids (fig. 8). By 2016, NBB and POM were dissimilar to the previous years 

but similar to each other. The resemblance of both locations by 2016 indicated a shift of

community structure at both locations.
30

Figure 8. Nonmetric multidimensional scaling Euclidean distance graph created by using PRIMER 7. 

Graph visually depicts the resemblance of North Biscayne Bay (NBB) and Port of Miami (POM) community 

structures to each other through the years.
31

Discussion

Turbidity

In addition to collecting epibenthic fauna and determining vegetation cover and 

abundance, the FMHD project recorded various environmental data. These data included salinity, 

temperature, turbidity, sediment depth, and water depth taken at each sampling site. These 

environmental factors can have a substantial effect on seagrass distribution and condition. For 

example, H. wrightii can tolerate extreme salinities and turbidity, whereas T. testudinum cannot

(Fourqurean and others, 2001). These measurements can help determine if there are gradients 

across the bay that may explain changes in the distribution and density of seagrass (FMHD). 

Dredging can have adverse effects on the environment by increasing turbidity in the water 

column. Increased turbidity affects primary production as it reduces the amount of light that can 

penetrate the water column, which can lead to a reduction in photosynthesis and productivity

(McCloskey and Unsworth, 2015). 

Increased turbidity levels from dredging can directly and indirectly affect seagrass. 

Dredging increases the amount of suspended material in the water column, which reduces the 

light available to the submerged vegetation (Erftemeijer and Lewis, 2006). Both NBB and POM 

showed similar increases in turbidity over the course of the study. Marked differences in 

turbidity were observed at NBB among the years 2014 to 2016 and between 2015 and 2016. 

During the fall of 2015, the northeastern corner of the bay began to experience a seagrass die-off

which may have been the result of higher turbidity. However, in 2015, our data showed high

turbidity values in areas of the bay where the die-off was not present. By 2016, average turbidity

values had substantially increased throughout all sampling sites in the bay. This increase 

suggests that the die-off did not contribute to the observed turbidity increase among our sampling 

areas. However, because of the significant increase in turbidity values between 2015 and 2016, 

conclusions about the direct effects of dredging on NBB could not be made from this study. The 

increase in turbidity in the bay cannot be entirely attributed to the seagrass die-off or to adjacent 

dredging from the POM.

POM showed the same significant effects in turbidity as NBB. There was a significant 

increase between 2014 and 2016 and a significant increase between 2015 and 2016 after 

dredging occurred. There was no significant difference between 2014 and 2015 before dredging 

began. Average turbidity values by 2016 were significantly higher than the previous two years 

throughout the sampling sites. Fig. 9A-D displays the overall trend in turbidity throughout the 

three-year study period in FMHD compared with the seven-year FIAN record. In FIAN, average 

turbidity values in NBB were fairly constant, varying around a mean of 2.5 NTU, whereas

turbidity in POM exhibited a decreasing trend (Robblee and Browder, written communication to 

USACE, USGS, and NOAA National Marine Fisheries Service). 

Seagrass Density

Seagrass is an essential part of coastal communities in South Florida. Seagrass beds 

provide food and habitat and host numerous fishes, invertebrates, and other animals. Seagrass 

density was negatively correlated with turbidity. Higher turbidity values likely resulted in lower 

seagrass densities (Norland and Gullstrom, 2013). This relationship was observed in the same 

pattern as turbidity in the FMHD study. In NBB and POM, there was a significant difference 

between 2014 and 2016 and between 2015 and 2016 but not between 2014 and 2015. Fig. 10A-
32

D shows that both locations in the FIAN and FMHD studies had decreasing seagrass density 

trends over time. However, the FIAN study did not show significant decreases throughout the 

seven-year period. Both NBB and POM had more substantial decreases over the three years of 

the FMHD study than the seven previous years of the FIAN study. Seagrasses will need to 

recover to reverse the current downward trend.

Average seagrass densities were compared to the average turbidity for wet and dry 

seasons for NBB and POM. The highest peak turbidity observed for both locations during the 

FMHD study occurred during the dry season directly succeeding the dredging. Turbidity 

decreased while the average seagrass density showed little change. This suggests that the 

seagrass may need more time to recover from dredging operations and that continuing to monitor 

the bay is essential to understand the long-term effects of turbidity on seagrass.
33

Figure 9. Average turbidities for North Biscayne Bay (NBB) and Port of Miami (POM) observed 

throughout the study period for the Faunal Monitoring in Response to Harbor Dredging (FMHD) and Fish 

and Invertebrate Assessment Network (FIAN) studies as a comparison of conditions before and after 

dredging.
34

Figure 10. Average seagrass densities (as defined in table 1) for North Biscayne Bay (NBB) and Port of 

Miami (POM) observed throughout the study period for the Faunal Monitoring in Response to Harbor 

Dredging (FMHD) and Fish and Invertebrate Assessment Network (FIAN) studies as a comparison of 

conditions before and after dredging.
35

Animal Totals

As in the FIAN study, seagrass fauna was collected and benthic vegetation was observed 

twice annually in NBB and POM. Community assemblages of fish and decapod invertebrates 

were determined using a throw-trap. Throw-trap collections are important to determine the 

effects of structural changes in the environment because of the important role of seagrass as 

habitat and food to marine animals. Changes in community structure as compared with those 

observed in the FIAN study were observed during 2014 and 2015, the first two years of the 

FMHD study, when dredging activities were taking place. Since vegetation is positively 

correlated to faunal abundance, dredging could affect animal populations and community 

assemblages that use seagrass as habitat. 

Animal totals decreased significantly throughout the 3-year period for both locations (fig. 

5B. Both NBB and POM had slight but significant decreases from year to year in caridean

shrimp, penaeid shrimp, and fish totals. Unlike seagrasses, some animals have the ability to leave 

an area when conditions become unfavorable. Our research shows animal totals were negatively 

correlated to increased turbidity values. Because of dredging activities, it may be important to 

monitor faunal composition of the POM to determine whether these populations continue to 

decrease or recover. In this study, the POM had more significant decreases in animal totals than 

NBB which may have been due to dredging. 

There were differences in the community structure in the fish and shrimp populations in 

both locations throughout the study period (fig. 6A-D). In NBB, populations of Floridichthys

(pupfishes), Lucania (ray-finned killifishes), and Microgobius (gobies) decreased by 

approximately 80, 72, and 96 percent, respectively from the start of the project in 2014 to 2016. 

The Ctenogobius (gobies), Gobiosoma (gobies), and Hippocampus (pipefishes and seahorses) 

had overall increases of 92, 76, and 43 percent, respectively, throughout the project. In POM, 

Gobiosoma and Hippocampus populations remained relatively stable. Diplogrammus (dragonets)

populations decreased by approximately 95 percent. Populations of both Floridichthys and 

Microgobius substantially declined. By 2016, Floridichthys and Microgobius were no longer 

present in our study areas (fig. 6A-B). Lucania was the only genus of fishes that showed a 

substantial population increase of 81 percent. 

There were also notable changes in the caridean shrimp population in both sampled

locations throughout the study period. Shrimp composition in NBB consisted mostly of Thor and 

Hippolyte, both of which belong to the family Hippolytidae. There was a large shift between the 

two genera: Thor decreased, and Hippolyte became the major genus found from 2014 to 2016.

Although Hippolyte became the dominating genus, it still experienced declines. Overall, 

Hippolyte and Palaemonetes suffered severe decreases of 95 and 100 percent by 2016. In POM, 

the shrimp community was more variable than in NBB. The major genera that made up the 

population were Alpheus, Hippolyte, Thor, and Periclimenes. There were more genera affected 

than in NBB with decreases of 61, 48, 60, 30, and 86 percent in Alpheus, Hippolyte, Latreutes, 

Periclimenes, and Processa, respectively. The only genus that exhibited a major increase was 

Thor, with an overall increase in population of approximately 74 percent from 2014 to 2016. The 

number of penaeid shrimps collected from 2014 to 2016 declined by approximately 61 percent

throughout the study period (fig. 6C-D).

Monitoring the faunal composition in response to environment-altering activities 

improves understanding of ecosystem function. Some species may show resilience when 

detrimental changes have been made to their environment while others do not, which was 

observed in several genera of fishes and shrimp in NBB and POM. Those species that are not 
36

tolerant to these changes may disappear from the area. In this study, there were two fish and one 

shrimp genera that were observed in 2014 that declined throughout the study period and were not 

observed by 2016. 

Unfortunately, there were no collections in 2017. There could have been a return to 

previous states in both locations or conditions may have continued to decrease seagrass and 

animal totals. It is possible that the populations we observed decreasing or disappearing 

completely, could have rebounded by 2017. Without further sampling, it is unknown whether the 

dredging could have lasting effects on the seagrass community.

Selected References

Behringer, D.C., and Butler, M.J., IV, 2006, Stable isotope analysis of production and trophic 

relationships in a tropical marine hard-bottom community: Oecologia v. 148, p. 334–341.

Braun-Blanquet, J., 1965, Plant Sociology: The study of plant communities: London, Hafner.

d’Avack, E.A.S., Tillin, H., Jackson, E.L. and Tyler-Walters, H. 2014. Assessing the sensitivity 

of seagrass bed biotopes to pressures associated with marine activities. JNCC Report No. 505. 

Peterborough, Joint Nature Conservation Committee.

Erftemeijer, P.L.A., and Lewis, R.R.R, III, 2006, Environmental impacts of dredging on 

seagrasses: A review: Marine Pollution Bulletin v. 52, p. 1553–1572.

Essink, K., 1999, Ecological effects of dumping of dredged sediments; options for management:

Journal of Coastal Conservation, v. 5, p. 69–80.

Fourqurean, J.W., Willsie, A., Rose, C.D., and Rutten, L.M., 2001, Spatial and temporal pattern 

in seagrass community composition and productivity in south Florida:Marine Biology v. 138, 

p. 341–354.

Fuentes M.P.B., Lawler I.R., Gyuris E., 2006, Dietary preferences of juvenile green turtles 

(Chelonia mydas) on a tropical reef flat: Wildlife Research, v. 33, p. 671–678. 

doi:10.1071/WR05081.

Green E.P. and Short F.T., 2003, World atlas of seagrass: Berkeley, Calif., University of 

California Press Berkeley.

Hallermeier, R.J., 1981, Terminal settling velocity of commonly occurring sand grains:

Sedimentology, v. 28, no. 6, p. 859–865. 

Johnson, B., 2011, Port Miami 2035 Master Plan Executive Summary: 

http://www.miamidade.gov/portmiami/master-plan.asp. 

Koch, E.W., 2001, Beyond light: Physical, geological, and geochemical parameters as possible 

submersed aquatic vegetation habitat requirements: Estuaries, v. 24, no. 1, p. 1–17.

Komar, P.D., and Miller, M.C., 1973, The threshold of sediment movement under oscillatory 

water waves: Journal of Sedimentary Petrology, v. 43, no. 4, p. 1101–1110. 

Komar, P.D., and Miller, M.C., 1975, On the comparison between the threshold of sediment 

motion under waves and unidirectional currents with a discussion of the practical evaluation of 

the threshold: Journal of Sedimentary Petrology, v. 45, no. 2, p. 362–367. 

Littler, D.S., Littler, M.M., Bucher, E.B., and Norris, J.N., 1989, Marine plants of the Caribbean: 

A field guide from Florida to Brazil: Washington, D.C., Smithsonian Institution Press. 

Lohrer, A.M., and Wetz, J.J., 2003, Dredging-induced nutrient release from sediments to the 

water column in a southeastern saltmarsh tidal creek: Marine Pollution Bulletin, v. 46, p. 

1156–1163. 

McCloskey, R., and Unsworth, R., 2015, Decreasing seagrass density negatively influences 

associated fauna: Peer J, doi: 10.7717/peerj.1053.
37

Moore, K.A.; Wetzel, R.L., and Orth, R.J., 1997, Seasonal pulses of turbidity and their relations 

to eelgrass (Zostera marina L.) survival in an estuary: Journal of Experimental Marine Biology 

and Ecology, v. 215, no. 1, p. 115–134. 

Norlund, L. M., and Gullstrom, M., 2013, Biodiversity loss in seagrass meadows due to local 

invertebrate fisheries and harbor activities: Estuarine, Coastal and Shelf Science, v. 135, no. 0, 

231-240.

Onuf, C.P., 1994. Seagrasses, dredging and light in Laguna Madre, Texas, U.S.A.: Estuarine, 

Coastal and Shelf Science, v. 39, no. 1, p. 75–91. 

Pennekamp, J.G.S., Epskamp, R.J.C., Rosenbrand, W.F., Millie, A., Wessel, G.L., Arts, T., and 

Deibel, I.K., 1996, Turbidity caused by dredging; viewed in perspective: Terra et Aqua, v. 64, 

p. 10–17. 

Perkey, D., Pratt, T.C., and Ganesh, N.B., 2010, Comparison of SSC measurements with 

acoustic backscatter data: West bay sediment diversion, Mississippi River: Las Vegas, Nev., 

Proceedings of the 2nd Joint Federal Interagency Conference. 

Ralph, P.J., Tomasko, D., Moore, K., Seddon, S., and Macinnis-Ng, C.M.O., 2006, Human 

impacts on seagrasses: Eutrophication, sedimentation, and contamination, in Larkum, A.W.D.,

Orth, R.J., and Duarte, C., editors, Seagrasses: Biology, ecology and conservation: Dordrecht, 

The Netherland, Springer, p. 567–593.

RECOVER., 2004, CERP Monitoring and Assessment Plan. Part I. Monitoring and Supporting 

Research. Comprehensive Ecosystem Restoration Project: West Palm Beach, Fla., South 

Florida Water Management District, and Jacksonville, Fla., U.S. Army Corps of Engineers.

Robert, J.O., Matthew, C.H., and Graeme, J.I., 2006, Ecology of seagrass seeds and seagrass 

dispersal processes, in Larkum, A.W.D., Orth, R.J., and Duarte, C., editors, Seagrasses: 

Biology, ecology and conservation: Dordrecht, The Netherlands, Springer, pp. 111–133.

Sabol, B., and Shafer, D., 2005, Dredging effects on seagrasses: case studies from New England 

and Florida: Western Dredging Association 25th Annual WEDA conference, p. 335–346.

Schlacher-Hoenlinger, M.A., and Schlacher, T.A., 1998, Differential accumulation patterns of 

heavy metals among dominant macrophytes of a Mediterranean seagrass meadow: 

Chemosphere, v. 37, no. 8, p. 1511–1519.

Schoellhamer, D.H., 1996, Anthropogenic sediment resuspension mechanisms in a shallow 

microtidal estuary: Estuarine, Coastal and Shelf Science, v. 43, no. 5, 533–548. 

Schoellhamer, D.H., 2002, Comparison of the basin-scale effect of dredging operations and 

natural estuarine processes on suspended sediment concentration: Estuaries, v. 25, no. 3, p. 

488–495. 

Serafy, J. E., Lindeman, K. C., Hopkins, T. E., and Ault, J. S., 1997, Effects of freshwater canal 

discharge on fish assemblages in a subtropical bay; field and laboratory observations: Marine 

Ecology Progress Series, v. 160, p. 161–172.

Shafer, D.J., 1999, The effects of dock shading on the seagrass Halodule wrightii in Perdido 

Bay, Alabama: Estuaries, v. 22, no. 4, p. 936–943.

Short, F., Carruthers T., Dennison, W. and Waycott, M., 2007, Global seagrass distribution and 

diversity: A bioregional model: Journal of Experimental Marine Biology and Ecology, v. 1 and 

2, p. 3-20.

Short, F., and Wyllie-Echeverria, S., 1996, Natural and human- induced disturbances of 

seagrasses: Environmental Conservation, v. 23, no. 1, p. 17-27 

Smith, E. P., 2002, Before-after-control-impact design, in Encyclopedia of environmetrics: John 

Wiley and Sons.
38

Smith, E.P., Orvos, D. R., and Cairns, J., Jr, 1993, Impact assessment using the before-aftercontrol impact (BACI) model; concerns and comments: Canadian Journal of Fisheries and 

Aquatic Sciences, v. 50, no. 3, 627–637.

Soulsby, R., 1997, Dynamics of marine sands: London, Thomas Telford, 272 p. 

U.S. Army Corps of Engineers, n.d., Miami harbor deepening: accessed March 19, 2018 at 

http://www.saj.usace.army.mil/Missions/Civil-Works/Navigation/Navigation-Projects/MiamiHarbor-Deepening/. 

U.S. Geological Survey, 2004, Changing salinity patterns in Biscayne Bay, Florida: U.S. 

Geological Survey Fact Sheet 2004-3108, not paginated. 

Wang, P., and Beck, T.M., 2012, Morphodynamics of an anthropogenically altered dual-inlet 

system: John’s Pass and Blind Pass, westcentral Florida, USA: Marine Geology, v. 291–294, 

p. 162–175, http://dx.doi.org/10.1016/j.margeo.2011.06.001.

Wang, P., and Stone, G.W., 2004, Nearshore wave measurement, in. Schwartz, M., editor, 

Encyclopedia of Coastal Science: Dordrecht, The Netherlands, Springer, p. 869–874.

Zieman, J., Fourqurean, J., and Frankovich, T., 1999, Seagrass die-off in Florida Bay: Long-term 

trends in abundance and growth of turtle grass, Thalassia testudinum: Estuaries, v. 22, p. 460–

470.

Zieman, J., Fourqurean, J., and Iverson, R., 1989, Distribution, abundance and productivity of 

seagrasses and macroalgae in Florida Bay: Bulletin of Marine Science, v. 44, no. 1, p. 292-311.