# SI Project 786077



# Benthic Infaunal Monitoring in

S t L u c i e E s t u a r y

a n d t h e

S o u t h e r n I n d i a n R i v e r L a g o o n

First Phase Final Report

and

Annual Report 2008-2009

to

South Florida Water Management District

Bjorn G Tunberg

Scott Jones, Sherry Reed, Michelle Stephens (alphabetical)

Smithsonian Marine Station, Fort Pierce

March 2009

November 2009

# T ABLE OF 

# C ONTENTS

Important Note .................................................... 1

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

Entities Involved .................................................. 2

Material and Methods .............................................. 3

Design ...................................................... 3

Field Methods ............................................... 3

Laboratory Methods .......................................... 4

External Data ................................................ 4

Quality Assurance ............................................ 4

National and International Contacts for Quality Assurance and Advice .... 5

Data Management, Analyses and Presentation ......................... 5

Results and Discussion ............................................. 7

General Observations ......................................... 7

Details ...................................................... 9

Sediment Quality . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12

References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13

# I MPORTANT 

# N OTE

This Annual Report is based on the First Phase Final Report (March 2009). However,

additional data received and processed in 2008-2009 have been added to the original

Final Report text and graphs. The First Phase Final Report has also been modified.



# I NTRODUCTION

Biological monitoring is a necessary component to environmental management and

ecosystem restoration as it provides the assessment tools necessary to detect and

measure system wide responses to previous management actions and giving direction

and focus to future decisions (adaptive management). The Benthic Macroinvertebrate

Monitoring Program occupies an important role in making system-wide assessments in

the Northern Estuaries module of CERP monitoring.

The St. Lucie River Estuary (SLE) and the Southern Indian River Lagoon (IRL)

constitute the convergence of a major riverine estuary and the southern terminus of a

185 km (115 mile) long bar-built lagoonal estuary. The SLE is connected to Lake

Okeechobee through canal C-44, which empties into the South Fork at structure S-80.

In addition, the SLE serves as drainage for the C-23 basin through structure S-48 in the

middle estuary and the C-24 basin through structure S-49 in the North Fork. The C-25

canal (Taylor Creek) drains into the IRL at the Fort Pierce Inlet. Historically, natural

freshwater discharges into these water bodies sustained an ecologically appropriate

range of salinity conditions to facilitate the presence of healthy floral and faunal

communities. Recently, large volumes of nutrient laden and polluted fresh water have

been drained primarily from the C-44 basin through Lake Okeechobee. In addition, the

recent urbanization of Florida’s coastal regions and the ensuing increased demand for

water and flood control has led to frequent high and low salinity extremes within the

coastal water bodies. Managing for these demands has subsequently resulted in a shift

in the ecological components that historically defined the coastal water bodies to

communities that have been deemed less desirable.

Restoration targets under the CERP aimed at mitigating the impacts of historical

water management practices will illicit a specific response in the macroinvertebrate

infaunal community in predictable ways throughout the system:

1) Stabilization of salinity regimes will allow the establishment of healthier benthic

communities along the salinity gradient in the estuary by reducing the frequency

and severity of disturbance events that exclude many estuarine species.

2) Water quality improvement will decrease hypoxic stress and improve the habitat

quality and therefore the health of community composition by reducing the

severity of seasonal disturbance and increasing larval recruitment.

Benthos, First Phase Final Report 1

# 3) Reductions in sedimentation rate and, potentially the partial removal of mucky

sediments should improve the health of the benthic community by increasing

recruitment potential and infaunal diversity.

Benthic infauna are secondary producers that occupy a crucial trophic component of the

estuarine food web. They provide linkages between primary producers and higher level

consumers and represent a large standing stock of carbon in healthy estuaries (Diaz and

Schaffner 1990). This important biological component lends itself well to monitoring and

system assessment.

Benthos may be valued in terms of their links with other resources, as well as

containing representatives which are themselves commercially harvested (e.g., crabs,

shrimps, flatfish). They may also have intrinsic value in terms of their rarity and hence

conservation status (which may also apply to individual species). As constant features of

the bottom sediments, benthos vary predictably in association with the physical habitat

and in response to man made changes. Furthermore, unlike shifting populations of

planktonic organisms or many pelagic fish species, adults of most benthic invertebrate

species are either sessile or of limited mobility. Thus, they are good indicators of locallyinduced environmental changes (Boyd 2002). They respond differentially to varying

environmental conditions, and after settlement, most benthos remain within relatively

constrained areas, for their entire adult lives (Gray 1979).

Therefore, unlike many other biotic or chemical measures, benthos reflect

environmental conditions at specific areas. A sampling program that utilizes fixed-site

benthic quantitative monitoring can identify temporal trends with spatial resolution.

Benthic taxa vary in their responses to changes in water quality (Dauer 1993).

Some are relatively tolerant to organic enrichment and low dissolved oxygen while others

are excluded under low DO conditions. Increased nutrient inputs can strongly affect

abundances of some species, while not affecting others. By examining shifts in the

benthic community over time, one can gain an understanding of the major environmental

processes affecting the local biota (Warwick 1986, Borja et al. 2000).

The first three years of benthic monitoring in the St. Lucie Estuary and Southern

Indian River Lagoon began the establishment of a baseline condition. While only the

beginning of what was necessary to assemble a meaningful ecological dataset, the

system experienced wide swings in hydrodynamics and allowed the assessment of

responses to these variations.



# E NTITIES 

# I NVOLVED

This project is an assignment from South Florida Water Management District (SFWMD),

and is being performed through the Smithsonian Marine Station at Fort Pierce, by the

Benthic Environmental and Monitoring Group (BEAM) at SMSFP. Erin Linley joined the

Group in March 2008, but was paid from other sources. However, she has been very

active in the field, and laboratory within this project.

Benthos, First Phase Final Report 2

# M ATERIAL AND 

# M ETHODS

Design

The benthic sampling program is a fixed site monitoring effort directed at identifying

trends in benthic condition. It involves sampling at 15 sites, 13 of which have been

sampled since the program’s inception in February 2005, with two inner estuary sites

added in July 2007 (Figure 1). Each site is visited 4 times per year, twice (January and

April) during months that typically fall into Florida’s dry season (November-April) and

twice (July and October) during months that typically fall into Florida’s wet season (MayOctober).

These sites span all salinity regimes within the St. Lucie Estuary and the Southern

Indian River Lagoon (SLE/IRL-S) and cover the watershed in such a way that benthic

responses to hydrologic events stemming from the system’s tributaries can be detected

and analyzed.



# Field Methods

Three replicate samples are collected using a Petit Ponar grab, which samples a 0.02 m 2



# area. In the field, samples are sieved through a 0.5 mm stainless screen. Organisms

and detritus retained on the screen are transferred into labeled jars and preserved in a 5-

10% formaldehyde solution stained with Rose Bengal (a vital stain that aids in separating

organisms from sediments and detritus).

Sediment core sampling is also performed on each occasion by means of an

Ogeechee corer (two replicates at each site). Each core is divided into two fractions, 0-2

cm and 2-5 cm from the sediment surface. The quarterly sediment samples are analyzed

for percent water content and percent organic content (loss on ignition) at each site.

Separate sediment cores for granulometric (grain size) analyses are collected at every

site once per year. The color of the sediment at ca 5 cm substrate depth is defined by

means of a rock color chart.

The sediment type, structure, firmness as well as the absence/presence of H

2 

# S

are also determined. The samples are placed in a cooler (in air tight containers) in the

field, and in a freezer upon return to the laboratory for later analyses.

Water column measurements are taken at each sampling occasion.

Temperature, salinity, conductivity, dissolved oxygen, and pH are measured at the

surface and bottom using YSI 556, 85, and/or 60 instruments. Turbidity is measured

with a Hach 2100P turbidimeter. Water depth, Secchi depth, and meteorological

conditions are also recorded.

Benthos, First Phase Final Report 3

# Laboratory Methods

After 2-3 weeks of storage, the faunal grab samples are transferred to 70% ethanol.

Organisms are sorted from detritus under dissecting microscopes, identified to the lowest

possible taxonomic level (most often species), and counted. Oligochaetes and midges

(Diptera:Chironomidae) are mounted on slides and examined under a compound

microscope for genus and species identification (at sites with less than 5 ppt salinity).

The frozen sediment samples are placed individually in pre weighed aluminum

containers. After being weighed, these samples are placed in a drying oven (80oC) until

they have reached constant weight (usually about one week). After reaching room

temperature (in a desiccator), the samples are weighed again and transferred to a

furnace (500oC) for 5 hours. After weighing, by means of the procedure described above,

these samples are discarded. Water content and organic content (loss on ignition) in the

sediment are calculated from these measurements.



# External Data

The South Florida Water Management District monitors water quality of the SLE and

IRL-S as well as its tributaries (canals C-23, C-24, C-25, and C-44) on a monthly basis

( Figure 2). Utilizing point source measurements with a broader temporal scale can be

illuminating when correlated with benthic community datasets. Seasonal changes and

stochastic events may be captured in these data and provide a context for observed

changes in the benthic community datasets.

Data obtained using SFWMD’s online environmental database (DBHYDRO) have

been assembled into a dataset of multiple parameters covering the spatial and temporal

scope of the monitoring program: flow, nutrients (ammonia-N, organic nitrogen, nitrate +

nitrite, orthophosphate, and total phosphorous), chlorophyll-a (corrected), water

chemistry (temp, dissolved oxygen, pH, salinity, color, turbidity, total suspended solids),

and precipitation. The water quality parameters used here are measured at twelve

stations within the SLE and fourteen stations in the IRL. Flow data for this long term

study are measured at 4 sites and daily rainfall totals are measured at 8 sites.



# Quality Assurance

All field and laboratory datasheets are being maintained for a minimum of five years after

the completion of the project. The following guidelines are being used for the field and

laboratory procedures: DEP-SOP-001/01 (Department of Environmental Protection

Standard Operating Procedures for Field Activities), DEP-SOP-002/01 (Department of

Environmental Protection Standard Operating Procedures for Laboratory Activities) and

DEP-QA-001/01 (New and Alternative Analytical Laboratory Methods). CERP QASR

(Quality Assurance Systems Requirements Plan) will be incorporated when that

Benthos, First Phase Final Report 4

# guidance is made available. In cases where national guidelines may be missing, the

international standards established by ICES (International Council for the Exploration of

the Sea) and Boyd (2002) will be followed.



# N ATIONAL AND 

# I NTERNATIONAL 

# C ONTACTS FOR



# Q UALITY 

# A SSURANCE AND 

# A DVICE

Prof. Les Watling, Darling Marine Center, 193 Clark's Cove Road, Walpole, ME 04573

(watling@maine.edu)

Dr. Heye Rumohr, Institut fur Meereskunde, Dusternbrooker Weg 20, D-24105 Kiel,

Germany (hrumohr@ifm.uni-kiel.de)

Dr. Robert Clarke, PRIMER-E Ltd, 6 Hedingham Gardens, Roborough, Plymouth, PL6

7DX, United Kingdom (krc@pml.ac.uk)

Prof. Walter G. Nelson, Branch Chief, Environmental Protection Agency, Pacific Coastal

Ecology Branch, 2111 SE Marine Science Dr., Newport, OR 97366

(nelson.walt@epamail.epa.gov)

Dr. Anthony J. Underwood, Centre for Research on Ecological Impacts of Coastal Cities,

Marine Ecology Laboratories A11, University of Sydney, NSW 2006, Australia

(aju@bio.usyd.edu.au)

Dr. Angel Borja, AZTI Tecnalia, Herria Kaia, 20110 Pasaia, Spain (aborja@azti.es)



# D ATA 

# M ANAGEMENT 

# , A NALYSES AND 

# P RESENTATION

All the raw data are being entered into a customized web-based database, especially

developed for this project, for detailed data treatment (with both CD and server backup).

The database houses all faunal data as well as quarterly point source environmental

measurements. This database allows data query by site, date, or taxa and output files

are in Excel spreadsheet format ready for input into analytical software such as PRIMER.

Biotic Data

Biological surveys usually yield large, complex sets of biotic and environmental data from

which patterns and relationships need to be extracted. The most sensible approach is to

first look for patterns in biological variables and then attempt to interpret them in the

context of the environmental data. (Field et al. 1982) The treatment and analysis of

biotic data can be represented by the following diagram:

Raw Data (abundance) Transformed data Similarity Matrix Clustering and

Ordination

Multi-species data are almost entirely analyzed using the PRIMER v6 software package.

PRIMER accomplishes the entire process outlined above and is able to test for causality

Benthos, First Phase Final Report 5

# using environmental datasets (Clarke and Gorley 2006).

Raw abundance data (number of individuals per sample) often leave a skewed

dataset where most species occur in very low numbers and a few occur in very high

numbers. The few dominant species in a sample will statistically overwhelm the rarer

species. As such, transforming the data is necessary. The 4 th 

# root transform has the

effect of down-weighting the importance of the highly abundant species, so that

similarities between samples depend on the values of less common species as well

(Clarke and Warwick 2001).

The measurement of similarity is the foundation of other analyses to follow. A

common feature of marine survey data is that many species are absent from most of the

samples. This results in a data matrix that consists mostly of zeros. Transforming the

data does not alter this. It is therefore necessary to utilize a similarity coefficient that is

not affected by joint absences in two samples. The Bray-Curtis similarity fits the bill and

finds common usage in ecological study for this reason.

Graphical descriptions of the relationships between the biota in the various

samples are used to reduce the complexity of the multivariate information contained in

the data and allow interpretation of the similarity measurements. Two methods are

primarily utilized for this project: hierarchical clustering and multidimensional scaling

(MDS). For the clustering technique, representation of the communities for each sample

is by a dendrogram, linking the samples in hierarchical groups based on similarity. The

method of MDS places the samples on a “map” in two and three dimensions, in such a

way that the rank order of the distances between samples on the map agrees with the

rank order of the similarities taken from the similarity matrix.

In addition to PRIMER v6, a combination of several software packages including

SigmaStat 3.5, SigmaPlot 11, Statecol, Systat 11, and Corel Draw X4 are also being

used.

The arithmetic means and corresponding variance and standard error values are

calculated for the existing abundance data from each study site. The diversity of the

faunal samples is calculated by using a large number of diversity indices, but only the

Shannon index (Shannon and Weaver 1949) is presented in the reports. Evenness is

expressed by Hill's modified ratio E5 (Hill 1973).

AMBI

Benthic indices are especially relevant to management efforts because benthic

invertebrates provide site-specific indicators of habitat conditions that integrate stress

effects over time and over multiple types of stress (Gray 1979), as highlighted by

Ranasinghe et al. (2002) and Borja et al. (2008).

Since SLE-IRL is situated in a subtropical area, it is affected by two major climatic

seasons, dry (winter) and wet (summer). This contribution investigates the application of

the AZTI’s Marine Biotic Index (AMBI) and multivariate-AMBI (M-AMBI), to assess the

ecological status of these estuaries. AMBI was firstly calculated after assigning most of

the previously unassigned species to each of the five ecological groups. Three main

benthic assemblages, associated to oligohaline, meso-polyhaline and euhaline stretches,

Benthos, First Phase Final Report 6

# have been identified. Reference conditions of richness, Shannon’s diversity and AMBI

have been derived for these assemblages; M-AMBI has then been calculated.

Sediment Data

The sediment data are being transferred to spreadsheets and graphs for evaluation of

temporal changes. They have also been integrated with some of the faunal data to

elucidate the relationships between sediment characteristics and faunal taxa, individuals,

and diversity.



# R ESULTS AND 

# D ISCUSSION

General Observations

Between February 2005 and July 2009, the project conducted 19 sampling events. A

total of 795 ponar samples were taken, along with 530 sediment cores. A total of close to

300,000 (289,023) individual animals have been processed and identified to date (July

2009), and added to the customized database (together with the environmental data).

Sampling and processing have continued in the 2010 fiscal year, in spite of the fact that

the contract has been put on hold this year.

Figures 3–8 present time series graphs of environmental parameters measured

by the project as a part of the regular sampling program. The salinity gradient is

apparent in Figure 5 as well as seasonal fluctuations in salinity. Sites M3-M6

experienced the widest shifts in salinity throughout the period. Salinity in the IRL (sites

M8-M13) remained fairly stable. The effects of the 2005 wet season are immediately

apparent, with salinities dropping system wide. Also noteworthy is the elevated salinities

in estuarine sites M1–M5 during the dry season of 2007 (January and April). These

seasonal signatures are expressed in dissolved oxygen measurements as well (Figure

4). Drops in dissolved oxygen (sometimes severe) occur during the wet season when

temperatures are high (Figure 3) and freshwater input (with associated nutrient loads)

are high. The oxygen readings were similar at both M14 and M15. M14 experienced

wide shifts in salinity throughout the study period, while M15 had significantly lower and

more stable salinities (with one exception in April 2007) (Figure 8).

Figures 9-12 presents time series graphs of community parameters for sites M1-

M15. Very few taxa were recorded at sites M3-M5 throughout the study period (Figure

9). Taxa increased slightly over time in the North Fork river (sites M1 and M2), and

increased markedly downstream toward the mouth of the estuary (M6 and M7), with the

maximum numbers of taxa expressed in the IRL (sites M8–M13). The results from the

July 2009 sampling show different development at the separate sites. M3, M5 and

(especially) M12 show an increase in the number of taxa. However, an opposite trend

was recorded for M2, M7, M8, and (especially) M10 with decreases in the number of

taxa. The reason(s) for these changes is presently unknown.

Benthos, First Phase Final Report 7

# Within the SLE, infaunal abundance varied dramatically during the study period

(Figure 10), ranging from near zero to several hundred per sample at a given site. Sites

within the IRL contained much higher numbers of individuals. While spikes often were

recorded in abundance, numbers rarely dropped below 100 or more individuals per 0.02

m 2 

# . The development at sites M2 and M3 in July 2009 is exceptional. These dramatic

increases in abundance were mainly caused by a few r-strategists (listed in the graph).

Mytilopsis leucophaeata, commonly known as the false dark mussel, is a bivalve mollusc

that is typically found in brackish waters. Mytilopsis leucophaeata can attach to manmade and natural structures. As Mytilopsis leucophaeata accumulate they become

responsible for the fouling of cages, boats and ropes. Mytilopsis leucophaeata also

causes major fouling in industrial cooling water systems. It is a highly euryhaline species

and occurs mostly in brackish waters (Rajagopal et al. 2005). It’s increased presence at

M2 and M3 may be a cause of concern.

Diversity measures were low at sites M3-M5, slightly higher in the North Fork (M1

and M2), and increasingly higher and more stable moving downstream and into the IRL

(Figure 11). Site M14 had, on average, significantly higher numbers of taxa and

individuals than M15, while the diversity (Shannon) was similar between these two sites

during this study period (Figure 12).

The AMBI analyses are presented in Figure 13. Both AMBI methods show that the

inner part of the SLE is affected by anthropogenic pressures (increased freshwater

inflow, elevated nutrient input, and sedimentation), whilst the IRL is less affected.

Sediment conditions varied significantly throughout the SLE/IRL (Figures 14-17).

Organic content measured as percent loss on ignition values were highest at the SLE

sites M3-M6 (Figures 14-15). The North Fork M1, M2, and M15 also exhibited elevated

values, though not quite as high. The IRL sites had much lower levels of organic

content.

The St. Lucie Estuary and Indian River Lagoon displayed a spectrum of softbottom community types along the salinity gradient typical of most estuaries. Sites within

given salinity zones tend to be more similar to each other than to sites in other salinity

zones, with four major zones present (Oligohaline, Mesohaline, Polyhaline, and Euhaline

– Table 1).

The North Fork site M3, South Fork site M4 and main stem site M5 exhibited very

poor ecological health throughout the study period. The North Fork river (M15, M1, M2)

along with the upper South Fork (M14) was slightly better, but still with impaired

ecological health. Moving out of the estuary, ecological health improved dramatically

downstream with M7 (estuary mouth) serving as a threshold point where community

health and sediment quality improved dramatically. Indian River Lagoon sites M8-M13

exhibited high diversity and abundance.

Freshwater inflow to the SLE and, as a result, salinity varied significantly between

seasons and years. Of the four years studied, 2005 and 2008 were wet years that

experienced tropical storm or hurricane activity while 2006 and 2007 experienced

drought conditions (Figure 18). 2006 was the driest year during the study period.

Nutrient loads, salinity patterns, and dissolved oxygen dynamics are closely tied to

Benthos, First Phase Final Report 8

# freshwater inflow and have a significant impact on benthic communities. Intra-annually,

freshwater inflow is highly seasonal; during warmer, wetter months (July and October),

benthic populations decreased in average number of taxa and abundance (Figures 9 and

10).



# Details

Water Quality

Ecologically, estuaries represent zones of reduced competition, areas in which physical

factors tend to outweigh biotic factors in affecting species distributions

. Biotic factors,

such as competition are reduced in importance because of the high degree of variability

and physiological stress found in estuaries. Salinity is probably the most conspicuous

physiological factor and is the major force affecting the distribution of organisms in an

estuary (McLusky1989). In the SLE/IRL system, patterns of community composition

tend to be well differentiated along the salinity gradient. Throughout the time period

studied (2005-2009), sites within a particular salinity zone tend to be more similar to

each other than sites in other salinity zones. When using multi-dimensional scaling

(MDS) analysis to examine all sites sampled within a particular date, oligohaline, mesoto polyhaline, and euhaline sites will separate out from each other. This pattern is fairly

consistent, regardless of year or season (wet or dry). Figure 19 displays MDS plots for

dry season samples (May or April) and wet season (October) samples for three different

years (2005, 2006, 2008). All three replicates for all thirteen stations (fifteen in 2008) are

shown. The points that are close together represent samples that are very similar in

community composition and points that are far apart correspond to very different values.

A consistent feature in each of these plots is the tight grouping of the euhaline

sites. These are M7 (at the mouth of the estuary) and the remaining IRL sites, M8-M13.

These sites exhibit some of the most stable salinity patterns in the system, collectively

showing a small interquartile range (Table 1, Figure 20). The euhaline sites in the

system display high diversity and a relatively large proportion of obligate marine taxa.

Polyhaline species can be found, especially near the St. Lucie Inlet (M7 and M8), but

they represent a small proportion.

The oligohaline sites in the upper north fork (M1, M2, and M15) also tend to

consistently group together. Salinity in this region of the estuary also tends to remain

stable, showing a small interquartile range (Table 1). A large proportion of species at

these sites tend to be from freshwater origin. Several species of insects, gastropods,

and oligochaetes with freshwater affinities are collected here regularly.

The communities in the North Fork (M3), South Fork (M4), and main stem (M5,

M6) tend to vary more, but are often distributed within an MDS plot so that the

mesohaline sites M3 and M4 separate from the polyhaline sites M5 and M6. The salinity

ranges exhibited at these four sites often overlap, and the community compositions can

be similar.

Benthos, First Phase Final Report 9

# In July 2007, two new sites were added to expand the spatial coverage of the

program further upstream into the estuary. One site was placed in the upper North Fork

(M15) and one was placed in the upper South Fork (M14). The upper South Fork site,

M14 has undergone dramatic shifts in salinity and, consequently, community

composition. Figure 21 presents an MDS plot of each sampling date (with each replicate

displayed, a-c). April and October 2008 had the highest proportion of freshwater taxa

and are clearly very similar to each other while being separated from the other dates.

The greatest distance between sites (and therefore, the greatest dissimilarity between

communities) is represented by the gap between July 2007 and April/October 2008. July

2007 represent the conclusion of a period with very little rain and was in the middle of a

prolonged zero-flow event from C-44. Salinities in this part of the river spiked as high as

23 ppt between March and June 2007 (DBHYDRO).

This process of salinity-driven community shifts occurs at most of the inner

estuary sites (M14, M3-M6) during sustained regulatory releases and low-flow events.

Under pre-CERP conditions, salinities at these sites undergo rapid and extreme shifts

(Haunert and Startzman 1985). All other factors excluded, this unstable regime limits the

number of estuarine taxa with marine origins that can establish up into the estuary, while

increasing the distance ‘downstream’ that freshwater taxa can persist. These

communities are continually in an early successional state with a high proportion of taxa

that are r-selected and/or tolerant such as the polychaete worm Streblospio benedicti or

one of several species of tube-dwelling amphipods ( Grandidierella bonneroides, Cerapus

benthophilus ). Over time, sites M3, M4, and M5 display the lowest species richness of

any sites in the study system (Figure 9). Post-CERP stabilization of salinity regimes

should permit the establishment of healthier, more species-rich communities.

Water quality parameters in the SLE/IRL system exhibit strong seasonality as well

as spatial variation (Iricanin and Crean 2007, Qian et al. 2007). Seasonal signatures are

a normal mechanism in tropical/ subtropical systems with distinctive wet and dry seasons

driving freshwater inflows and nutrient loads. The inner estuary close to these inflows

exhibits higher nutrient loads and poorer water quality parameters than the outer estuary

and lagoon. The seasonal and spatial component to water quality characteristics is

reflected in patterns of benthic community composition.

The post-drainage watershed in the SLE/IRL system encompasses a much larger

surface area than the pre-drainage system. Additionally, an eightfold increase in the

quantity of stormwater is now delivered to the coast, accompanied with an increase in

nutrient load (Graves et al. 2004). The impacts of these watershed alterations on the

SLE have been dramatic. Excess nutrient loading (N and P) has facilitated organic

enrichment, and caused a trophic shift throughout the estuary (Chamberlain and

Hayward 1996). These processes (eutrophication) have had a profound effect on the

bottom condition of the estuary, leading to accumulation of soft, mucky sediments and

increased frequency/duration of low dissolved oxygen conditions (Chamberlain and

Hayward 1996, Doering 1996). Frequent, severe low dissolved oxygen events are a

major stress to the SLE system and a source of serious concern (Graves et al. 2002,

Iricanin and Crean 2007).

Benthos, First Phase Final Report 10

# Seasonal signatures expressed in benthic populations are thought to be driven by

fluctuations in salinity and dissolved oxygen values. There was significant inter-annual

variation in freshwater delivery to the SLE/IRL system during the study period 2005-

2008. Figure 22 displays flow from the four major sources of freshwater to the SLE

(North Fork, C-24, C-23, C-44). Increases in freshwater inflows are visible in the wet

season (particularly July and October for all years) with 2005 receiving the highest

discharge (Hurricane Wilma). 2006 and 2007 were very dry years with little or no tropical

storm activity. Discharge during the wet season of 2008 was higher due to tropical storm

Fay, and normal rainfall levels. Not surprisingly, rainfall patterns for the study period

correspond to discharge values (Figure18).

When comparing benthic community parameters in the inner and main stem of the

SLE (sites M3-M6) to freshwater inflow, the seasonal effects of water releases become

apparent. Both species richness (number of taxa) and individual abundance tend to

decrease in wet months (July and October) while rebounding in dry months (April and

January). Figures 23 and 24 display the change in values (given as standard deviates) of

freshwater inflow, taxa, and abundance at sites M3-M6. Inflow is the cumulative average

of all four major inputs to the estuary (C-44, C-23, C-24, and North Fork). The wet

season samples that corresponded with high inflow exhibit decreased numbers of taxa

and decreased abundance, indicating disturbance events that exclude species recruited

during drier months. This effect is less severe in years with no tropical storm activity and

below average rainfall, such as in 2006. The inflow event triggered by Hurricane Wilma

in October 2005 had a devastating effect on the SLE estuary benthos. It is noteworthy

that macrobenthic populations did not return to previous levels of abundance and

species richness until almost one year later (July 2008). A similar disturbance was

observed in the system in October 2007, when a few days of intense rainfall punctuated

what was otherwise a notably dry period. Land-based constituents had most likely

accumulated during the dry period and were carried to the estuary in a high

concentration. It is likely that the estuary experienced severe hypoxia during this time.

Near-anoxic levels of dissolved oxygen (0.39 mg/l) were recorded at SFWMD site SE08

in the South Fork during a monthly sampling trip. Without in situ monitoring, the extent

and severity of events such as this cannot be determined. During the fall of 2008,

normal rainfall levels returned to South Florida and Tropical Storm Fay deposited

prodigious amounts of rainfall. Freshwater inflow was very high and community

parameters for October 2008 dropped significantly.

The effects of these disturbance events were most severe in the SLE, where

limnic conditions can persist for days while nutrients and solids can settle out in the

basins of the North Fork and main stem. However, responses are detected in the IRL as

well, particularly at sites around the St. Lucie Inlet (M7, M8, M9). While M7 is considered

a site within the St. Lucie Estuary, it borders the boundary between the estuary and the

IRL and exhibits similarly high levels of species richness, diversity, and abundance and

is thus included in this discussion. Figures 25 and 26 display the change in values

(given as standard deviates) of freshwater inflow, taxa, and abundance at sites M7-M9.

Each increase of freshwater inflow corresponds with a decrease in either taxa or

abundance. It is clear that the seasonal fluctuations in freshwater inflow, with its

Benthos, First Phase Final Report 11

# corresponding deliveries of nutrient load and suspended solids drive the intra-annual

dynamic of macrobenthic populations.



# Sediment Quality

It is well-established that salinity limits the distance that a species can penetrate into an

estuary, but an infaunal species can only establish itself when suitable substrates are

present. Sediments with a high percentage of organic carbon do not lend themselves

well to infaunal community establishment (Gray et al. 2002). While organic matter in the

sediment is an important source of nutrition for most benthic species, an elevated

amount may reduce species richness and abundance as the associated microbial

breakdown of these materials drive down dissolved oxygen levels while accumulating

toxic metabolic by-products such as ammonia and sulfide (Hyland et al. 2005). Such

sediment conditions act to inhibit certain feeding groups such as filter feeders and

selecting for deposit-feeding organisms with a high tolerance for low oxygen and high

sulfide concentrations, such as the polychaete Capitella capitata . Hypoxic soft

sediments also have a profound effect of larval settlement by eliciting avoidance

behavior in many soft bottom species (Marinelli and Woodin 2002). The relationship

between eutrophication (elevated nutrient input), increased organic input, and dissolved

oxygen dynamics is a close one. While it may not be possible at this time to isolate a

given mechanism that affects benthic community health in the SLE/IRL, it is clear that

sediment condition can serve as a helpful indicator.

Quarterly sediment analysis reveal that inner and main stem estuary sites (M3-

M6) exhibit an elevated amount of organic carbon, as measured by mass loss on ignition

(Figures 14-15) Inner estuary sites M14 and M15 also consistently display high amounts

of organic carbon while the North Fork sites M1 and M2 tend to vary. These two sites

are in erosional- depositional zones of the river where the channel width is much smaller

than the basins that contain most of the other sites, which may explain variability in

sedimentation rate. Patterns of organic content correspond closely with patterns of

species richness throughout the estuary. Sites with elevated organic content tend to be

sites with low species richness, sites with low organic content tend to be sites with high

species richness (Figure 27). It is noteworthy that among low-salinity sites M1-M5, this

pattern is consistent as M1 and M2 display higher species richness than the M3-M5

while exhibiting lower organic content. This may discard the notion that the trend in

species richness is dictated by salinity alone. Further, we believe that sites M3-M5 have

fewer species than would be expected at this salinity regime.

Benthos, First Phase Final Report 12

# R EFERENCES

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Dredging Sites. Centre for Environment, Fisheries and Aquaculture Science,

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Clarke, K.R., R.M. Warwick. 2001. Change in Marine Communities – An Approach to

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Dauer, D.M. 1993. Biological criteria, environmental health, and macrobenthic

community structure. Marine Pollution Bulletin 26:249-257.

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on the Cheasapeake Bay, 1990. Advances in Estuarine Science. M. H. a. E. C.

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Field, J.G., K.R. Clarke, R.M. Warwick. 1982. A practical strategy for analyzing multispecies distribution patterns. Marine Ecology Progress Series 8: 37-52.

Graves, G., Y. Wan, D.L. Fike 2004. Water quality characteristics of storm water from

major land uses in south Florida. Journal of the American Water Resources

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Graves, G., M. Thompson, D. Fike. 2002. St. Lucie Estuary: Evidence of Impairment.

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Gray, J.S. 1979. Pollution-induced changes in populations. Philosophical Transactions of

theRoyal Society of London. 286(B):545-561.

Gray, J.S., R.S. Wu,Y.Y. Or. 2002. Effects of hypoxia and organic enrichment on the

coastal marine environment. Marine Ecology Progress Series 238:249-279.

Haunert, D.E., R. J. Startzman.1985. Some short-term effects of a freshwater discharge

on biota of the St. Lucie Estuary, Florida. South Florida Water Management

District, West Palm Beach, FL, USA. Technical Publication DRE-213.

Benthos, First Phase Final Report 13

# Hill, M.O. 1973. Diversity and evenness: A unifying notation and its consequences.

Ecology 54:427-432.

Hyland, J., L. Balthis, I. Karakassis, P. Magni, A. Petrov, J. Shine, O. Vestergaard, R.

Warwick. 2005. Organic carbon content of sediments as an indicator of stress in

the marine benthos. Marine Ecology Progress Series 295 : 91-103.

Iricanin, N., D. Crean. 2007. An analysis of the water quality in the St. Lucie Estuary.

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Marinelli, R. L., S. A. Woodin. 2002. Experimental evidence for linkages between

infaunal recruitment, disturbance, and sediment surface chemistry. Limnology and

Oceanography 47(1): 221-229.

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Hyland, J. Scott, D.M. Dauer, 2002. Application of two indices of benthic

community condition in Chesapeake Bay. - Environmetrics, 13: 499-511.

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temperature tolerance of exotic brackish-water mussel Mytilopsis leucophaeata

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University of Illinois Press, Urbana, Illinois.

Warwick, R.M. 1986. A new method for detecting pollution effects on marine

macrobenthic communities. Marine Biology 92:557-562.

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Water Constituents in the Indian River Lagoon, Florida. Journal of Environmental

Quality 36: 416-42.

Benthos, First Phase Final Report 14

# &IG"ENTHIC)NFAUNAL-ONITORING3ITES3T,UCIE%STUARYAN D)NDIAN2IVER,AGOON

# &IG3&7-$MONITORINGSITESFORFLOWRAINANDWATERQUALI TYUSEDFOR the BENTHICANALYSES

# TEMPERATURE SLE-IRLFEBMAYJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJULOCT 

# 15 20 25 30 35FEBMAYJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJULOCTTEMPERATURE (oC) 

# 15 20 25 30 35FEBMAYJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJULOCT 

# 15 20 25 30 35FEBMAYJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJULOCT 

# 15 20 25 30 35FEBMAYJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJULOCT 

# 15 20 25 30 35FEBMAYJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJULOCT 

# 15 20 25 30 35FEBMAYJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJULOCT 

# 15 20 25 30 35 

# M1

M2

M3

M4 M8

Fig. 3. Temperature in the surface water (solid line) and bottom w ater (dotted line)

at the 13 study si tes between February 2005 and October 2009.FEBMAYJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJULOCT 

# 15 20 25 30 35



# M5FEBMAYJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJULOCT 

# 15 20 25 30 35FEBMAYJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJULOCT 

# 15 20 25 30 35 

# M6 M9

M10

M7FEBMAYJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJULOCT 

# 15 20 25 30 35FEBMAYJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJULOCT 

# 15 20 25 30 35FEBMAYJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJULOCT 

# 15 20 25 30 35 

# M11

M12

M13

2005 2006 2007 2005 2006 2007 2008

2008 2009 2009

# OXYGEN SLE-IRLFEBMAYJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJULOCT 

# 0 2 4 6 8 10 12FEBMAYJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJULOCTOXYGEN CONCENTRATION (mg/l) 

# 0

2 4 6 8 10 12FEBMAYJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJULOCT



# 0 2 4 6 8 10 12FEBMAYJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJULOCT



# 0 2 4 6 8 10 12FEBMAYJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJULOCT 

# 0 2 4 6 8 10 12FEBMAYJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJULOCT



# 0 2 4 6 8 10 12FEBMAYJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJULOCT



# 0 2 4 6 8 10 12 

# M1

M2

M3

M4 M8

Fig. 4. Oxygen concentrations in the surfac e water (solid line) and bottom water

(dotted line) at the 13 study sites between February 2005 and October 2009.FEBMAYJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJULOCT 

# 0 2 4 6 8 10 12



# M5FEBMAYJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJULOCT



# 0 2 4 6 8 10 12FEBMAYJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJULOCT



# 0 2 4 6 8 10 12 

# M6 M9

M10

M7FEBMAYJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJULOCT 

# 0 2 4 6 8 10 12FEBMAYJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJULOCT



# 0 2 4 6 8 10 12FEBMAYJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJULOCT



# 0 2 4 6 8 10 12 

# M11

M12

M13

2005 2006 2007 2005 2006 2007

2008 2008

2009 2009

# SALINITY SLE-IRLFEBMAYJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJULOCT 

# 0 10 20 30 40FEBMAYJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJULOCTSALINITY (ppt) 

# 0 10 20 30 40FEBMAYJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJULOCT



# 0 10 20 30 40FEBMAYJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJULOCT



# 0 10 20 30 40FEBMAYJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJULOCT 

# 0 10 20 30 40FEBMAYJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJULOCT



# 0 10 20 30 40FEBMAYJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJULOCT



# 0 10 20 30 40 

# M1

M2

M3

M4 M8

Fig. 5. Salinity in the surf ace water (solid line) and bottom water (dotted line)

at the 13 st udy sites between February 2005 and October 2009.FEBMAYJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJULOCT 

# 0 10 20 30 40



# M5FEBMAYJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJULOCT



# 0 10 20 30 40FEBMAYJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJULOCT



# 0 10 20 30 40 

# M6 M9

M10

M7FEBMAYJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJULOCT 

# 0 10 20 30 40FEBMAYJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJULOCT



# 0 10 20 30 40FEBMAYJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJULOCT



# 0 10 20 30 40 

# M11

M12

M13

2005 2006 2007 2008 2009

2005 2006 2007 2008 2009

# pH SLE-IRLFEBMAYJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJULOCT 

# 6.5 7.0 7.5 8.0 8.5FEBMAYJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJULOCTpH 

# 6.5 7.0 7.5 8.0 8.5FEBMAYJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJULOCT 

# 6.5 7.0 7.5 8.0 8.5FEBMAYJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJULOCT 

# 6.5 7.0 7.5 8.0 8.5FEBMAYJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJULOCT 

# 6.5 7.0 7.5 8.0 8.5FEBMAYJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJULOCT 

# 6.5 7.0 7.5 8.0 8.5FEBMAYJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJULOCT 

# 6.5 7.0 7.5 8.0 8.5 

# M1

M2

M3

M4 M8

Fi g. 6. pH in the surface water (solid line) and bott om water (dotted line)

at the 13 st udy sites between October 2005 and October 2009. It was not possible to

measure pH in October 2007, due to equipment malfunction.FEBMAYJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJULOCT 

# 6.5 7.0 7.5 8.0 8.5



# M5FEBMAYJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJULOCT 

# 6.5 7.0 7.5 8.0 8.5FEBMAYJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJULOCT 

# 6.5 7.0 7.5 8.0 8.5 

# M6 M9

M10

M7FEBMAYJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJULOCT 

# 6.5 7.0 7.5 8.0 8.5FEBMAYJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJULOCT 

# 6.5 7.0 7.5 8.0 8.5FEBMAYJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJULOCT 

# 6.5 7.0 7.5 8.0 8.5 

# M11

M12

M13

2005 2006 2007 2008 2009 2005 2006 2007 2008 2009

# TURBIDITY SLE-IRLFEBMAYJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJULOCT 

# 0 4 8 12 16 20 24FEBMAYJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJULOCTTURBIDITY (NTU) 

# 0

4 8 12 16 20 24FEBMAYJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJULOCT



# 0 4 8 12 16 20 24FEBMAYJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJULOCT



# 0 10 20 30 40FEBMAYJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJULOCT 

# 0 4 8 12 16 20 24FEBMAYJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJULOCT



# 0 4 8 12 16 20 24FEBMAYJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJULOCT



# 0 4 8 12 16 20 24 

# M1

M2

M3

M4 M8

Fig. 7. Turbidity (NTU) in the surface wa ter at the 13 study sites between

January 2006 and July 2009. Due to equi pment malfunction it was not

possible to measure turbidity in October 2009.FEBMAYJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJULOCT 

# 0 4 8 12 16 20 24



# M5FEBMAYJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJULOCT



# 0 4 8 12 16 20 24FEBMAYJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJULOCT



# 0 4 8 12 16 20 24 

# M6 M9

M10

M7FEBMAYJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJULOCT 

# 0 4 8 12 16 20 24FEBMAYJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJULOCT



# 0 4 8 12 16 20 24FEBMAYJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJULOCT



# 0 4 8 12 16 20 24 

# M11

M12

M13

2005 2006 2007 2005 2006 2007

2008 2008

2009 2009

# M14

JULY OCT JAN APR JUL OCT JAN APR JUL OCTTEMPERATURE (oC)



# 16 18 20 22 24 26 28 30 32

SURF

BOTT



# JULY OCT JAN APR JUL OCT JAN APR JUL OCTOXYGEN (mg/l)



# 0 2 4 6 8 10

JULY OCT JAN APR JUL OCT JAN APR JUL OCTSALINITY (ppt)



# 0

5 10 15 20 25

JULY OCT JAN APR JUL OCT JAN APR JUL OCTpH



# 0

2 4 6 8 10

2007 JULY OCT JAN APR JUL OCT JAN APR JUL OCTCONDUCTIVITY (ms/sec)



# 0 10000 20000 30000 40000

2008 

# M15

JULY OCT JAN APR JUL OCT JAN APR JUL OCT 

# 16 18 20 22 24 26 28 30 32 34

JULY OCT JAN APR JUL OCT JAN APR JUL OCT



# 0 2 4 6 8 10

JULY OCT JAN APR JUL OCT JAN APR JUL OCT



# 0 2 4 6 8 10 12

JULY OCT JAN APR JUL OCT JAN APR JUL OCT



# 0 2 4 6 8

JULY OCT JAN APR JUL OCT JAN APR JUL OCT 

# 0 500 1000 1500 2000 2500

JULY OCT JAN APR JUL OCT JAN APR JUL OCTTURBIDITY (NTU)



# 0 2 4 6 8 10

JULY OCT JAN APR JUL OCT JAN APR JUL OCT 

# 0 4 8 12 16 20 24



# Fig. 8. Environmental variables at the freshwater /oligohaline sites M14 and M15 during the

period July 2007 and October 2009. NB! The different scaling on the y-axes. Turbidity was

not measured in October 2009 due to equipment malfunction. 2009 2007 2008 2009

# TAXA SLE- IRLFEBMAYJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJUL 

# 0 10 20 30 40 50 60FEBMAYJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJULMEAN NUMBER OF TAXA PER 0.02 m2 

# 0 10 20 30 40 50 60FEBMAYJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJUL



# 0 10 20 30 40 50 60FEBMAYJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJUL



# 0 10 20 30 40 50 60FEBMAYJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJUL 

# 0 10 20 30 40 50 60FEBMAYJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJUL



# 0 10 20 30 40 50 60FEBMAYJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJUL



# 0 10 20 30 40 50 60 

# M1

M2

M3

M4 M8

Fig. 9. Average number of taxa per 0.02 m 2 

# at the 13 study sites between February 2005

and July 2009. The error bars represent standard error values.FEBMAYJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJUL 

# 0 10 20 30 40 50 60



# M5FEBMAYJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJUL



# 0 10 20 30 40 50 60FEBMAYJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJUL



# 0 10 20 30 40 50 60 

# M6 M9

M10

M7FEBMAYJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJUL 

# 0 10 20 30 40 50 60FEBMAYJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJUL



# 0 10 20 30 40 50 60FEBMAYJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJUL



# 0 10 20 30 40 50 60 

# M11

M12

M13

2005 2006 2007 2005 2006 2007

2008 2008

2009 2009

# INDIVIDUALS SLE- IRLFEBMAYJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJUL 

# 0 200 400 600 800 1000 1200FEBMAYJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJULMEAN NUMBER OF INDIVIDUALS PER 0.02 m2 

# 0

400 800 1200 1600 2000 2400FEBMAYJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJUL 

# 0 50 100 150 200 250FEBMAYJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJUL 

# 0 100 200 300 400FEBMAYJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJUL 

# 0 500 1000 1500 2000FEBMAYJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJUL 

# 0 250 500 750 1000FEBMAYJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJUL 

# 0 100 200 300 400 500 

# M1

M2

M3

M4 M8

Fig. 10. Average number of individuals per 0.02 m 2 

# at the 13 study sites between

February 2005 and July 2009. The error ba rs represent standard error values.

NB. The different scaling on the y-axes.FEBMAYJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJUL 

# 0 25 50 75 100



# M5FEBMAYJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJUL 

# 0 100 200 300 400 500 600 700FEBMAYJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJUL 

# 0 500 1000 1500 2000 

# M6 M9

M10

M7FEBMAYJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJUL 

# 0 100 200 300 400 500 600FEBMAYJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJUL 

# 0 500 1000 1500 2000 2500 3000 3500FEBMAYJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJUL 

# 0 500 1000 1500 2000 2500 3000 

# M11

M12

M13

2005 2006 2007 2008 2009 2005 2006 2007 2008 2009 Primarily:

Hydrobiidae

Mytilopsis leucophaeata

Primarily:

Streblospio benedicti

Mulinia lateralis

Mytilopsis leucophaeata

# DIVERSITY (H') SLE-IRLFEBMAYJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJUL 

# 0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5FEBMAYJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJULSHANNON (H') DIVERSITY 

# 0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5FEBMAYJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJUL 

# 0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5FEBMAYJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJUL 

# 0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5FEBMAYJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJUL 

# 0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5FEBMAYJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJUL 

# 0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5FEBMAYJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJUL 

# 0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 

# M1

M2

M3

M4 M8

Fig. 11. Shannon (H' log

e 

# ) species diversity at the 13 study sites between

February 2005 and July 2009. The error ba rs represent stan dard error values.FEBMAYJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJUL 

# 0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5



# M5FEBMAYJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJUL 

# 0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5FEBMAYJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJUL 

# 0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 

# M6 M9

M10

M7FEBMAYJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJUL 

# 0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5FEBMAYJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJUL 

# 0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5FEBMAYJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJULOCTJANAPRJUL 

# 0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 

# M11

M12

M13

2005 2006 2007 2008 2009 2005 2006 2007 2008 2009

# M14

JUL OCT JAN APR JUL OCT JAN APR JULTAXA PER 0.02 m2



# 0 5 10 15 20 25



# JUL OCT JAN APR JUL OCT JAN APR JULINIVIDULAS PER 0.02 m2



# 0 200 400 600 800 1000 1200

JUL OCT JAN APR JUL OCT JAN APR JULDIVERSITY (H')



# 0.0

0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 1.8 2.0 

# M15

JUL OCT JAN APR JUL OCT JAN APR JUL 0 2 4 6 8 10 12

JUL OCT JAN APR JUL OCT JAN APR JUL

0 10 20 30 40 50 60 70 80

JUL OCT JAN APR JUL OCT JAN APR JUL 0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 1.8 2.0



# Fig. 12. Taxa, Individuals, and Diversity at sites M14 and M15 during the period July 2007

and July 2009.

The error bars represent standar d error values. NB! The different scaling on the y-axes. 2007 2008 2009

# M15 M1 M2 M14 M3 M4 M5 M6 M7 M8 M9 M10 M11 M12 M13 0.0 0.2 0.4 0.6 0.8 1.0 

# • The best conditions exist primarilyin the

euhaline sections

, least impacted by

freshwater runoff & sediment deposition

• The poorest sites are in the upper north

fork and central SLE estuary , most

impacted by runoff and organic

accumulation

• Good scores in the IRL estuary linked to

lower organic accumulation (higher flow in

these areas) 

# M-AMBI Results – SpatialM-AMBI 

# SLE

North Fork

SLE and

South Fork IRL



# High

Good

Moderate

Poor

Bad

Fig. 13. Results of the AMBI analyses regarding the health status of the SLE/IRLFEB 05JUL 05OCT 05JAN 06APR 06JUL 06OCT 06JAN 07APR 07JUL 07OCT 07JAN 08APR 08JUL 08OCT 08JAN 09APR 09JUL 09 

# 0 5 10 15 20 25 30 

# M1FEB 05JUL 05OCT 05JAN 06APR 06JUL 06OCT 06JAN 07APR 07JUL 07OCT 07JAN 08APR 08JUL 08OCT 08JAN 09APR 09JUL 09 

# 0 5 10 15 20 25 30 

# M2FEB 05JUL 05OCT 05JAN 06APR 06JUL 06OCT 06JAN 07APR 07JUL 07OCT 07JAN 08APR 08JUL 08OCT 08JAN 09APR 09JUL 09 

# 0 5 10 15 20 25 30 

# M3FEB 05JUL 05OCT 05JAN 06APR 06JUL 06OCT 06JAN 07APR 07JUL 07OCT 07JAN 08APR 08JUL 08OCT 08JAN 09APR 09JUL 09 

# 0 5 10 15 20 25 30FEB 05JUL 05OCT 05JAN 06APR 06JUL 06OCT 06JAN 07APR 07JUL 07OCT 07JAN 08APR 08JUL 08OCT 08JAN 09APR 09JUL 09 

# 0 5 10 15 20 25 30 

# M4

M5FEB 05JUL 05OCT 05JAN 06APR 06JUL 06OCT 06JAN 07APR 07JUL 07OCT 07JAN 08APR 08JUL 08OCT 08JAN 09APR 09JUL 09 

# 0 20 40 60 80 100 

# M6FEB 05JUL 05OCT 05JAN 06APR 06JUL 06OCT 06JAN 07APR 07JUL 07OCT 07JAN 08APR 08JUL 08OCT 08JAN 09APR 09JUL 09



# 0 5 10 15 20 25 30 

# M7FEB 05JUL 05OCT 05JAN 06APR 06JUL 06OCT 06JAN 07APR 07JUL 07OCT 07JAN 08APR 08JUL 08OCT 08JAN 09APR 09JUL 09 

# 0 5 10 15 20 25 30 

# M8FEB 05JUL 05OCT 05JAN 06APR 06JUL 06OCT 06JAN 07APR 07JUL 07OCT 07JAN 08APR 08JUL 08OCT 08JAN 09APR 09JUL 09 

# 0 5 10 15 20 25 30FEB 05JUL 05OCT 05JAN 06APR 06JUL 06OCT 06JAN 07APR 07JUL 07OCT 07JAN 08APR 08JUL 08OCT 08JAN 09APR 09JUL 09 

# 0 5 10 15 20 25 30FEB 05JUL 05OCT 05JAN 06APR 06JUL 06OCT 06JAN 07APR 07JUL 07OCT 07JAN 08APR 08JUL 08OCT 08JAN 09APR 09JUL 09 

# 0 5 10 15 20 25 30FEB 05JUL 05OCT 05JAN 06APR 06JUL 06OCT 06JAN 07APR 07JUL 07OCT 07JAN 08APR 08JUL 08OCT 08JAN 09APR 09JUL 09 

# 0 5 10 15 20 25 30



# M9

M10 M11

M12FEB 05JUL 05OCT 05JAN 06APR 06JUL 06OCT 06JAN 07APR 07JUL 07OCT 07JAN 08APR 08JUL 08OCT 08JAN 09APR 09JUL 09 

# 0 5 10 15 20 25 30FEB 05JUL 05OCT 05JAN 06APR 06JUL 06OCT 06JAN 07APR 07JUL 07OCT 07JAN 08APR 08JUL 08OCT 08JAN 09APR 09JUL 09 

# 0 5 10 15 20 25 30FEB 05JUL 05OCT 05JAN 06APR 06JUL 06OCT 06JAN 07APR 07JUL 07OCT 07JAN 08APR 08JUL 08OCT 08JAN 09APR 09JUL 09 

# 0 5 10 15 20 25 30 

# M13

M14

M15

Fig. 14. Percent Loss on Ignition (organic c ontent) from the top 0-2cm of the sediment at the15 study sites between February 20 05 and

July 2009. The error bars represent standar d error values. NB. The different scaling on the y-axes at M6. SLE/IRL % LOSS ON IGNITION (ORGANIC CONTENT) AT 0-2 CM SEDIMENT DEPTHFEB 05JUL 05OCT 05JAN 06APR 06JUL 06OCT 06JAN 07APR 07JUL 07OCT 07JAN 08APR 08JUL 08OCT 08JAN 09APR 09JUL 09 

# 0 5 10 15 20 25 30 

# M1 SLE/IRL % LOSS ON IGN ITION (ORGANIC CONTENT) AT 2-5 CM SEDIMENT DEPTHFEB 05JUL 05OCT 05JAN 06APR 06JUL 06OCT 06JAN 07APR 07JUL 07OCT 07JAN 08APR 08JUL 08OCT 08JAN 09APR 09JUL 09 

# 0 5 10 15 20 25 30 

# M2FEB 05JUL 05OCT 05JAN 06APR 06JUL 06OCT 06JAN 07APR 07JUL 07OCT 07JAN 08APR 08JUL 08OCT 08JAN 09APR 09JUL 09 

# 0 5 10 15 20 25 30 

# M3FEB 05JUL 05OCT 05JAN 06APR 06JUL 06OCT 06JAN 07APR 07JUL 07OCT 07JAN 08APR 08JUL 08OCT 08JAN 09APR 09JUL 09 

# 0 5 10 15 20 25 30FEB 05JUL 05OCT 05JAN 06APR 06JUL 06OCT 06JAN 07APR 07JUL 07OCT 07JAN 08APR 08JUL 08OCT 08JAN 09APR 09JUL 09 

# 0 5 10 15 20 25 30 

# M4

M5FEB 05JUL 05OCT 05JAN 06APR 06JUL 06OCT 06JAN 07APR 07JUL 07OCT 07JAN 08APR 08JUL 08OCT 08JAN 09APR 09JUL 09 

# 0 5 10 15 20 25 30 

# M6FEB 05JUL 05OCT 05JAN 06APR 06JUL 06OCT 06JAN 07APR 07JUL 07OCT 07JAN 08APR 08JUL 08OCT 08JAN 09APR 09JUL 09 

# 0 5 10 15 20 25 30 

# M7FEB 05JUL 05OCT 05JAN 06APR 06JUL 06OCT 06JAN 07APR 07JUL 07OCT 07JAN 08APR 08JUL 08OCT 08JAN 09APR 09JUL 09 

# 0 5 10 15 20 25 30 

# M8FEB 05JUL 05OCT 05JAN 06APR 06JUL 06OCT 06JAN 07APR 07JUL 07OCT 07JAN 08APR 08JUL 08OCT 08JAN 09APR 09JUL 09 

# 0 5 10 15 20 25 30FEB 05JUL 05OCT 05JAN 06APR 06JUL 06OCT 06JAN 07APR 07JUL 07OCT 07JAN 08APR 08JUL 08OCT 08JAN 09APR 09JUL 09 

# 0 5 10 15 20 25 30FEB 05JUL 05OCT 05JAN 06APR 06JUL 06OCT 06JAN 07APR 07JUL 07OCT 07JAN 08APR 08JUL 08OCT 08JAN 09APR 09JUL 09 

# 0 5 10 15 20 25 30FEB 05JUL 05OCT 05JAN 06APR 06JUL 06OCT 06JAN 07APR 07JUL 07OCT 07JAN 08APR 08JUL 08OCT 08JAN 09APR 09JUL 09 

# 0 5 10 15 20 25 30



# M9

M10 M11

M12FEB 05JUL 05OCT 05JAN 06APR 06JUL 06OCT 06JAN 07APR 07JUL 07OCT 07JAN 08APR 08JUL 08OCT 08JAN 09APR 09JUL 09 

# 0 5 10 15 20 25 30FEB 05JUL 05OCT 05JAN 06APR 06JUL 06OCT 06JAN 07APR 07JUL 07OCT 07JAN 08APR 08JUL 08OCT 08JAN 09APR 09JUL 09 

# 0 5 10 15 20 25 30FEB 05JUL 05OCT 05JAN 06APR 06JUL 06OCT 06JAN 07APR 07JUL 07OCT 07JAN 08APR 08JUL 08OCT 08JAN 09APR 09JUL 09 

# 0 5 10 15 20 25 30 

# M13

M14

M15

Fig. 15. Percent Loss on Ignition (organic content) from top 2-5cm of the sediment at the 5 study sites between February 2005 a nd

July 2009. The error bars represent standard error values.FEB 05JUL 05OCT 05JAN 06APR 06JUL 06OCT 06JAN 07APR 07JUL 07OCT 07JAN 08APR 08JUL 08OCT 08JAN 09APR 09JUL 09 

# 20 30 40 50 60 70 80 

# M1FEB 05JUL 05OCT 05JAN 06APR 06JUL 06OCT 06JAN 07APR 07JUL 07OCT 07JAN 08APR 08JUL 08OCT 08JAN 09APR 09JUL 09 

# 20 30 40 50 60 70 80 

# M2FEB 05JUL 05OCT 05JAN 06APR 06JUL 06OCT 06JAN 07APR 07JUL 07OCT 07JAN 08APR 08JUL 08OCT 08JAN 09APR 09JUL 09 

# 40 50 60 70 80 90 100 

# M3FEB 05JUL 05OCT 05JAN 06APR 06JUL 06OCT 06JAN 07APR 07JUL 07OCT 07JAN 08APR 08JUL 08OCT 08JAN 09APR 09JUL 09 

# 40 50 60 70 80 90 100FEB 05JUL 05OCT 05JAN 06APR 06JUL 06OCT 06JAN 07APR 07JUL 07OCT 07JAN 08APR 08JUL 08OCT 08JAN 09APR 09JUL 09 

# 40 50 60 70 80 90 100 

# M4

M5FEB 05JUL 05OCT 05JAN 06APR 06JUL 06OCT 06JAN 07APR 07JUL 07OCT 07JAN 08APR 08JUL 08OCT 08JAN 09APR 09JUL 09 

# 0 20 40 60 80 

# M6FEB 05JUL 05OCT 05JAN 06APR 06JUL 06OCT 06JAN 07APR 07JUL 07OCT 07JAN 08APR 08JUL 08OCT 08JAN 09APR 09JUL 09 

# 20 30 40 50 60 70 80 

# M7FEB 05JUL 05OCT 05JAN 06APR 06JUL 06OCT 06JAN 07APR 07JUL 07OCT 07JAN 08APR 08JUL 08OCT 08JAN 09APR 09JUL 09 

# 20 30 40 50 60 70 80 

# M8FEB 05JUL 05OCT 05JAN 06APR 06JUL 06OCT 06JAN 07APR 07JUL 07OCT 07JAN 08APR 08JUL 08OCT 08JAN 09APR 09JUL 09 

# 20 30 40 50 60 70 80FEB 05JUL 05OCT 05JAN 06APR 06JUL 06OCT 06JAN 07APR 07JUL 07OCT 07JAN 08APR 08JUL 08OCT 08JAN 09APR 09JUL 09 

# 20 30 40 50 60 70 80FEB 05JUL 05OCT 05JAN 06APR 06JUL 06OCT 06JAN 07APR 07JUL 07OCT 07JAN 08APR 08JUL 08OCT 08JAN 09APR 09JUL 09 

# 0 10 20 30 40 50 60FEB 05JUL 05OCT 05JAN 06APR 06JUL 06OCT 06JAN 07APR 07JUL 07OCT 07JAN 08APR 08JUL 08OCT 08JAN 09APR 09JUL 09 

# 0 10 20 30 40 50 60



# M9

M10 M11

M12FEB 05JUL 05OCT 05JAN 06APR 06JUL 06OCT 06JAN 07APR 07JUL 07OCT 07JAN 08APR 08JUL 08OCT 08JAN 09APR 09JUL 09 

# 0 10 20 30 40 50 60FEB 05JUL 05OCT 05JAN 06APR 06JUL 06OCT 06JAN 07APR 07JUL 07OCT 07JAN 08APR 08JUL 08OCT 08JAN 09APR 09JUL 09 

# 20 30 40 50 60 70 80FEB 05JUL 05OCT 05JAN 06APR 06JUL 06OCT 06JAN 07APR 07JUL 07OCT 07JAN 08APR 08JUL 08OCT 08JAN 09APR 09JUL 09 

# 40 50 60 70 80 90 100 

# M13

M14

M15

Fig. 16. Percent water content from top 0- 2cm of the sediment at the 15 study sites between February 2005 and October 2008. The error

bars represent stan dard error values. NB. The di fferent scaling on the y-axes. SLE/IRL % WATER CONTENT AT 0-2 CM SEDIMENT DEPTHFEB 05JUL 05OCT 05JAN 06APR 06JUL 06OCT 06JAN 07APR 07JUL 07OCT 07JAN 08APR 08JUL 08OCT 08JAN 09APR 09JUL 09 

# 10 20 30 40 50 60 70 

# M1FEB 05JUL 05OCT 05JAN 06APR 06JUL 06OCT 06JAN 07APR 07JUL 07OCT 07JAN 08APR 08JUL 08OCT 08JAN 09APR 09JUL 09 

# 10 20 30 40 50 60 70 

# M2FEB 05JUL 05OCT 05JAN 06APR 06JUL 06OCT 06JAN 07APR 07JUL 07OCT 07JAN 08APR 08JUL 08OCT 08JAN 09APR 09JUL 09 

# 40 50 60 70 80 90 100 

# M3FEB 05JUL 05OCT 05JAN 06APR 06JUL 06OCT 06JAN 07APR 07JUL 07OCT 07JAN 08APR 08JUL 08OCT 08JAN 09APR 09JUL 09 

# 40 50 60 70 80 90 100FEB 05JUL 05OCT 05JAN 06APR 06JUL 06OCT 06JAN 07APR 07JUL 07OCT 07JAN 08APR 08JUL 08OCT 08JAN 09APR 09JUL 09 

# 40 50 60 70 80 90 100 

# M4

M5FEB 05JUL 05OCT 05JAN 06APR 06JUL 06OCT 06JAN 07APR 07JUL 07OCT 07JAN 08APR 08JUL 08OCT 08JAN 09APR 09JUL 09 

# 0 20 40 60 80 

# M6FEB 05JUL 05OCT 05JAN 06APR 06JUL 06OCT 06JAN 07APR 07JUL 07OCT 07JAN 08APR 08JUL 08OCT 08JAN 09APR 09JUL 09 

# 10 20 30 40 50 60 70 

# M7FEB 05JUL 05OCT 05JAN 06APR 06JUL 06OCT 06JAN 07APR 07JUL 07OCT 07JAN 08APR 08JUL 08OCT 08JAN 09APR 09JUL 09 

# 10 20 30 40 50 60 70 

# M8FEB 05JUL 05OCT 05JAN 06APR 06JUL 06OCT 06JAN 07APR 07JUL 07OCT 07JAN 08APR 08JUL 08OCT 08JAN 09APR 09JUL 09 

# 10 20 30 40 50 60 70FEB 05JUL 05OCT 05JAN 06APR 06JUL 06OCT 06JAN 07APR 07JUL 07OCT 07JAN 08APR 08JUL 08OCT 08JAN 09APR 09JUL 09 

# 10 20 30 40 50 60 70FEB 05JUL 05OCT 05JAN 06APR 06JUL 06OCT 06JAN 07APR 07JUL 07OCT 07JAN 08APR 08JUL 08OCT 08JAN 09APR 09JUL 09 

# 10 20 30 40 50 60 70FEB 05JUL 05OCT 05JAN 06APR 06JUL 06OCT 06JAN 07APR 07JUL 07OCT 07JAN 08APR 08JUL 08OCT 08JAN 09APR 09JUL 09 

# 10 20 30 40 50 60 70



# M9

M10 M11

M12FEB 05JUL 05OCT 05JAN 06APR 06JUL 06OCT 06JAN 07APR 07JUL 07OCT 07JAN 08APR 08JUL 08OCT 08JAN 09APR 09JUL 09 

# 10 20 30 40 50 60 70FEB 05JUL 05OCT 05JAN 06APR 06JUL 06OCT 06JAN 07APR 07JUL 07OCT 07JAN 08APR 08JUL 08OCT 08JAN 09APR 09JUL 09 

# 20 30 40 50 60 70 80FEB 05JUL 05OCT 05JAN 06APR 06JUL 06OCT 06JAN 07APR 07JUL 07OCT 07JAN 08APR 08JUL 08OCT 08JAN 09APR 09JUL 09 

# 40 50 60 70 80 90 100 

# M13

M14

M15

Fig. 17. Percent water content from the top 2-5cm of the sediment at the15 study sites between February 2005 and July 2009. The error

bars represent stan dard error values. NB. The di fferent scaling on the y-axes. SLE/IRL % WATER CONTENT AT 2-5 CM SEDIMENT DEPTH

# MEAN MONTHLY CUMULATIVE RAINFALL, 2005-2009

N=8Feb-05May-05Jul-05Oct-05Jan-06Apr-06Jul-06Oct-06Jan-07Apr-07Jul-07Oct-07Jan-08Apr-08Jul-08Oct-08Jan-09Apr-09Jul-09Oct-09RAINFALL, MM



# 0 100 200 300 400 500



# Fig. 18. Mean cumulative rainfall per month.

Data collected from eight sites (n=8), February 2005 - October 2009.

# &IG 9 -$30LOTSOFALLSITES!PRILAND/CTOBERFORAN D

3ALINITYZONESARESHOWNASLABELS

# SALINTIY ST. LUCIE ESTUARY & INDIAN RIVER LAGOON 2005-2009Upper North ForkNorth ForkSouth ForkUpper South ForkMain StemMouthSt. Lucie InletM10 & 11Ft. Pierce InletSALINITY, PPT



# 0 10 20 30 40

SLE IRL



# Fig. 20. Salinity box plots with mean and inter-quartile (75th and 25th) ranges.

Data is from February 2005 - October 2009.

# &IG 1 -$3PLOTOFALLREPLICATESTAKENAT-FROM*ULY
/CTO BER"UBBLESREPRESENTRELATIVE

PERCENTAGEOFFRESWATERTAXAINTHESAMPLE

# MONTHLY MEAN DISCHARGE JANUARY 2005 - OCTOBER 2009

J AN APR JU

L

O

C

T

JAN APR

J UL OCT JAN APR

J UL O

CT

J AN APR JUL O

CT

J AN APR JU

L

O

C

TM3/SEC



# 0 20 40 60 80 100 120 140

C44

C24

North Fork

C23



# Fig. 22. Average discharge per month from the four major discharge sources in the SLE.

Data from January 2005 - October 2009

# TOTAL INFLOW AND AVERAGE NUMBER OF TAXA, M3-M6

FEBRUARY 2005 - JULY 2009

Jan 0

5 Ap

r 0

5

J

u l 0

5 Oct 0 5 Jan 06 Apr 06 Jul 06 Oct 06

J an 07 Apr 0

7

J ul

07

O

c t 0

7

J

a

n

0 8 Ap

r 0

8

J ul 0 8

O

c t 0

8 Jan 0 9 Apr 0 9 Jul 09 Oct 09STANDARD DEVIATES



# -2 -1 0 1 2 3 4 5 6

TOTAL INFLOW

AVG NUMBER OF TAXA M3-M6



# Fig. 23. Total inflow and average number of taxa at sites M3-M6, expressed as standard deviates.

February 2005 - July 2009.

# TOTAL INFLOW AND AVERAGE ABUNDANCE, M3-M6

FEBRUARY 2005 - JULY 2009

Jan 0

5 Ap

r 0

5

J

u l 0

5 Oct 0 5 Jan 06 Apr 06 Jul 06 Oct 06

J an 07 Apr 0

7

J ul

07

O

c t 0

7

J

a

n

0 8 Ap

r 0

8

J ul 0 8

O

c t 0

8 Jan 0 9 Apr 0 9 Jul 09 Oct 09STANDARD DEVIATES



# -1 0 1 2 3 4 5 6

TOTAL INFLOW

AVG ABUNDANCE M3-M6



# Fig. 24. Total inflow and average abundance at sites M3-M6, expressed as standard deviates.

February 2005 - July 2009.

# TOTAL FRESHWATER INFLOW AND AVERAGE NUMBER OF TAXA, M7-M9

FEBRAURY 2005 - JULY 2009

Jan 0

5 Ap

r 0

5

J

u l 0

5 Oct 0 5 Jan 06 Apr 06 Jul 06 Oct 06

J an 07 Apr 0

7

J ul

07

O

c t 0

7

J

a

n

0 8 Ap

r 0

8

J ul 0 8

O

c t 0

8 Jan 0 9 Apr 0 9 Jul 09 Oct 09STANDARD DEVIATES



# -4 -2 0 2 4 6

TOTAL INFLOW

AVG NUMBER OF TAXA M7-M9



# Fig. 25. Total inflow and average number of taxa at sites M7 - M9, expressed as standard deviates.

Febraury 2005 - July 2009

# FRESHWATER INFLOW AND AVERAGE ABUNDANCE, M7 - M9

FEBRUARY 2005 - JULY 2009

Jan 0

5 Ap

r 0

5

J

u l 0

5 Oct 0 5 Jan 06 Apr 06 Jul 06 Oct 06

J an 07 Apr 0

7

J ul

07

O

c t 0

7

J

a

n

0 8 Ap

r 0

8

J ul 0 8

O

c t 0

8 Jan 0 9 Apr 0 9 Jul 09 Oct 09STANDARD DEVIATES



# -4 -2 0 2 4 6

TOTAL INFLOW

AVG ABUNDANCE M7-M9



# Fig. 26. Total inflow and average abundance, sites M7-M9, expressed as standard deviates.

February 2005 - July 2009.

# % MASS LOSS ON IGNITION, TAXA, and DIVERSITY

SITE M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11 M12 M13STANDARD DEVIATES



# -2.0 -1.5 -1.0 -0.5 0.0 0.5 1.0 1.5 2.0

LOI 0-2 cm

LOI 2-5 cm

TAXA

DIVERSITY



# Fig. 27. Percent mass loss on ignition, taxa, and diversity,

as standard deviation units; sites M1 - M13

# Region Benthic

Sites SFWMD Water Quality

Sites Median Interquartile

Range Salinity zone

assignment

Upper North Fork M1, M2,

M 15 SE13, SE12, SE 06 0.78 ppt <1 – 5 ppt Oligohaline

(0-5ppt)

North Fork M3 HR1 13.07 ppt 6 – 20 ppt Mesohaline

(5-18ppt)

Upper South Fork M14 SE9, SE10 2.57 ppt <1-10 ppt Oligo-/Mesohaline

South Fork M4 SE08B 6.93 ppt 1-13 ppt Oligo-/Mesohaline

Main Stem M5, M6 SE03, SE02 21.96 ppt 14 – 27 ppt Polyhaline

(18-30ppt)

Hell's Gate (estuary

mouth) M7 SE01 30 ppt 26 – 33 ppt Polyhaline

(18-30ppt)

IRL St. Lucie Inlet M8, M9 IRL 17, IRL 12B, SE 11 31.93 ppt 28-34 ppt Poly-/Euhaline

(30-40ppt)

IRL Middle M10, M11 IRL 22, IRL 27, IRL 29,

IRL 31B 33.33 ppt 30-35 ppt Euhaline

(30-40ppt)

IRL Fort Pierce Inlet M12 &

M13 IRL 34B, IRL 36 32.55 ppt 28-35 ppt Euhaline

(30-40ppt)



# Table 1. Salinity zones within the macrobenthic monitoring system. Macrobenthic sites

and SFWMD-maintained water quality monitoring sites within each region along with

median values, interquartile ranges (25 th 

# and 75 th 

# ), and salinity zone assignment.

# APPENDIX

ENVIRONMENTAL DATA

OCTOBER 2008, JANUARY 2009, APRIL 2009, JULY 2009

# Table 1. SLE-IRL October 2008



# SURF BOTT

Site Date Time Lat Long Depth Secchi Temp Oxygen Salinity pH Cond. Turbidity Temp Oxygen Salinity pH Cond.

M1 2 Oct 9:11 27 19.483 80 19.928 1.6 1.0 26.0 3.59 0.6 7.22 1130 8.5 26.0 3.55 0.6 7.20 1131

M2 2 Oct 8:29 27 16.245 80 19.324 1.9 1.0 26.4 4.08 0.5 7.38 1025 5.3 26.4 3.97 0.5 7.42 1025

M3 1 Oct 11:00 27 13.712 80 17.285 3.2 1.2 27.4 5.66 5.4 7.45 10040 3.0 27.4 5.66 5.4 7.45 10040

M4 1 Oct 12:00 27 10.939 80 15.921 2.1 0.5 28.0 6.01 1.4 7.32 2912 19.2 27.7 4.24 9.4 7.23 16895

M5 1 Oct 10:11 27 12.250 80 15.001 2.6 0.8 27.1 6.08 6.6 7.48 12197 9.8 27.8 4.57 18.5 7.13 31506

M6 1 Oct 9:49 27 12.809 80 12.930 3.1 1.0 26.8 6.12 10.2 7.57 17987 6.3 26.8 4.91 25.2 7.41 41726

M7 1 Oct 9:20 27 10.370 80 11.860 2.3 1.1 26.9 5.84 18.9 7.72 31646 5.6 27.4 5.75 29.6 7.84 47807

M8 1 Oct 8:24 27 08.966 80 10.047 1.6 1.0 27.0 5.21 23.6 7.77 38712 6.8 27.1 3.50 26.1 7.45 42510

M9 1 Oct 8:53 27 11.939 80 10.465 1.8 1.3 26.6 6.44 29.5 7.85 46969 5.9 27.1 5.20 32.1 7.81 51210

M10 2 Oct 11:05 27 21.004 80 15.893 1.8 1.4 26.6 5.00 27.9 7.73 44616 5.1 26.5 4.80 27.9 7.73 44592

M11 2 Oct 11:31 27 23.921 80 16.960 2.3 1.0 27.1 6.68 29.7 8.16 47677 9.8 26.9 6.34 29.6 8.15 47447

M12 2 Oct 12:50 27 28.568 80 19.754 2.0 1.2 28.2 5.88 34.2 8.02 55260 6.5 27.9 5.77 36.7 8.18 58420

M13 2 Oct 12:28 27 30.212 80 20.287 1.7 1.3 27.5 5.07 26.2 7.76 42993 4.8 27.2 4.62 29.2 7.76 47047

M14 1 Oct 11:38 27 09.172 80 15.509 2.1 0.5 27.2 6.03 0.3 7.30 609 20.8 26.6 5.63 0.3 7.15 663

M15 2 Oct 9:38 27 21.757 80 20.795 1.9 0.8 26.3 3.15 0.6 7.12 1230 5.7 26.0 2.82 0.6 7.08 1240

WEATHER

Wind Clouds

Site H2S Color Type Structure Firmness m/s From Air temp % Tide Speed

M1 

# No Grey Fine sand Unsorted 

# Med stiff 0.6 NW 25.6 0 

# Ebb Slight

M2 Yes D brown Muddy sand Med sort Med stiff 0.7 W 22.4 0 Ebb Strong Muddy sand with peat

M3 Yes Black Muddy sand Well sort Very soft 1.4 W 25.5 95 Flood Weak

M4 Yes Black Mud Unsorted Very soft 1.5 N 27.1 65 Flood 0

M5 Yes Black Mud Well sort Very soft 0.9 NW 24.0 75 0 0

M6 No Black Muddy sand Med sort Soft 1.3 W 24.3 70 Flood Weak

M7 No D brown Fine sand Med sort Med stiff 1.2 W 23.7 75 Flood Rel str

M8 No Grey Fine sand Well sort Med stiff 0.8 NW 22.7 60 0 0

M9 No Grey Fine sand Med sort Med stiff 1.9 W 22.9 60 Flood 0

M10 No Grey Fine sand Med sort Med stiff 1.2 N 24.7 1 Flood Weak

M11 No Grey Fine sand Med sort Med stiff 0.0 0 31.3 1 

# Flood Weak

M12 No Grey Fine sand Med sort Med stiff 2.4 E 26.3 50 

# Flood Moderate

M13 No Grey Fine sand Med sort Med stiff 1.4 ENE 50.0 50 

# Flood Weak

M14 Yes Black Muddy sand Unsorted Med stiff 0.0 0 27.1 50 

# Flood Weak

M15 No Black Mud Well sort Very soft 0.0 0 24.2 0 0 0

# Table 2. SLE-IRL January 2009



# SURF BOTT

Site Date Time Lat Long Depth Secchi Temp Oxygen Salinity pH Cond. Turbidity Temp Oxygen Salinity pH Cond.

M1 07-Jan 8:56 27 19.485 80 19.929 1.4 1.0 21.2 7.26 1.2 7.73 2236 6.6 21.2 6.68 1.3 7.71 2342

M2 07-Jan 8:09 27 16.250 80 19.325 1.8 1.3 22.1 6.15 11.2 7.64 17733 3.6 22.1 6.15 11.2 7.64 19148

M3 06-Jan 11:21 27 13.719 80.17.281 2.7 2.0 22.3 8.07 15.3 7.98 23708 2.4 21.5 5.86 18.6 7.77 27995

M4 06-Jan 13:20 27 10.924 80 15.948 1.5 0.9 23.0 7.65 15.5 7.87 24419 7.1 21.9 6.59 19.9 7.78 29984

M5 06-Jan 10:27 27 12.259 80 15.000 2.0 1.2 21.7 7.15 19.2 7.87 28898 4.3 21.8 6.06 26.2 7.90 38426

M6 06-Jan 10:00 27 12.809 80 12.930 2.6 1.4 21.6 7.38 23.7 7.94 39910 3.4 21.8 6.38 30.6 7.93 44130

M7 06-Jan 9:35 27 10.371 80 11.860 1.8 1.3 22.3 6.69 34.1 8.05 49051 6.0 22.4 6.53 35.3 8.07 50799

M8 06-Jan 8:25 27 08.974 80 10.047 1.2 1.0 21.7 6.49 32.9 7.89 46997 6.4 21.7 6.37 33.0 7.88 47124

M9 06-Jan 9:03 27 11.971 80 10.456 1.4 1.3 21.9 6.76 34.7 8.05 49428 6.0 21.9 6.52 34.7 8.05 49434

M10 09-Jan 8:07 27 21.008 80 15.896 1.5 1.4 18.2 7.45 35.8 8.04 46191 5.9 18.2 7.26 35.0 8.05 46198

M11 09-Jan 13:37 27 23.929 80 16.943 1.6 0.6 19.8 7.33 34.7 8.13 47346 7.4 19.8 7.15 34.7 8.13 47316

M12 07-Jan 11:25 27 28.566 80 19.750 1.1 1.1 22.7 6.41 35.1 8.01 50716 9.7 22.6 6.43 35.1 8.02 50715

M13 07-Jan 11:00 27 30.218 80 20.282 1.0 0.9 22.3 6.41 34.8 8.01 50039 11.6 22.3 6.48 34.8 8.01 50047

M14 06-Jan 12:43 27 09.179 80 15.513 2.0 0.9 22.4 8.27 7.8 7.92 12846 6.7 21.9 5.52 13.8 7.64 21465

M15 07-Jan 9:22 27 21.758 80 20.793 1.8 0.9 20.7 7.08 0.9 7.65 1649 7.1 20.6 6.85 0.9 7.60 1661

WEATHER

Wind Clouds

Site H2S Color Type Structure Firmness m/s From Air temp % Tide Speed

M1 

# yes drk grey muddy sand unsorted 

# med stiff 2.5 S 22.5 80 

# ebb weak with shell hash

M2 yes drk grey muddy sand unsorted soft 2.8 S 21.6 65 ebb moderate

M3 yes black mud well sorted very soft 3.6 SE 25.5 40 slack 0

M4 yes black muddy sand well sorted very soft 4.7 SSW 25.7 60 slack 0

M5 yes black mud well sorted very soft 4.2 S 24.8 40 ebb weak

M6 no black muddy sand med sorted soft 4.5 S 23.4 35 ebb weak

M7 no grey fine sand med sorted med stiff 2.5 SSE 24.0 20 ebb moderate

M8 no grey fine sand med sorted med stiff 1.7 SSE 21.8 15 ebb moderate

M9 no drk grey fine sand well sorted med stiff 3.2 SSE 22.4 15 ebb moderate

M10 no grey fine sand med sorted med stiff 2.1 NW 14.2 0 0 0

M11 no grey fine sand unsorted med stiff 3.8 NE 19.1 0 0 0

M12 no grey fine sand med sorted stiff 6.6 WSW 25.9 85 0 0

M13 no grey fine sand med sorted med stiff 6.8 SW 25.5 80 

# ebb weak

M14 no black muddy sand med sorted soft 2.8 S 26.2 45 

# slack 0

M15 no black mud unsorted very soft 2.5 S 23.8 50 0 0

# Table 3. SLE-IRL April 2009



# SURF BOTT

Site Date Time Lat Long Depth Secchi Temp Oxygen Salinity pH Cond. Turbidity Temp Oxygen Salinity pH Cond.

M1 06-Apr 9:00 27 19.291 80 19.564 1.7 1.5 26.1 5.61 4.7 7.73 8549 7.0 26.0 5.67 4.8 7.71 8723

M2 06-Apr 8:05 27 16.156 80 19.194 2.2 1.2 26.2 4.56 17.0 7.53 28240 3.5 26.4 4.45 19.4 7.57 32075

M3 02-Apr 8:44 27 13.718 80 17.279 2.7 1.8 24.4 6.68 23.1 7.90 36532 1.7 24.7 5.48 24.7 7.73 38754

M4 02-Apr 9:58 27 10.949 80 15.927 1.6 1.3 24.9 5.20 20.9 7.73 33309 2.8 25.0 5.12 25.5 7.71 40040

M5 02-Apr 10:26 27 12.259 80 15.000 2.0 1.7 25.0 6.12 25.1 7.86 39322 2.4 24.9 5.30 28.6 7.89 44227

M6 02-Apr 10:53 27 12.801 80 12.931 2.4 1.5 25.1 6.23 28.6 7.93 44405 3.9 24.6 5.87 30.1 7.94 46096

M7 02-Apr 13:07 27 10.379 80 11.858 1.8 1.4 25.1 6.16 34.2 8.05 52149 6.5 25.1 5.91 34.2 8.05 52152

M8 02-Apr 12:36 27 08.978 80 10.052 1.2 0.8 25.9 5.54 34.9 7.97 53594 11.4 25.9 5.47 35.1 7.97 54112

M9 02-Apr 11:43 27 11.981 80 10.470 1.6 bottom 24.9 5.89 35.7 8.08 53591 6.7 24.9 5.63 35.7 8.08 53544

M10 06-Apr 11:45 27 21.006 80 15.533 1.4 1.0 25.7 5.49 36.1 7.79 55329 9.1 25.7 5.39 36.2 7.97 55336

M11 06-Apr 12:30 27 23.557 80 16.566 2.0 1.0 25.9 5.76 36.4 8.04 55945 13.0 25.9 5.63 36.4 8.03 55961

M12 08-Apr 7:55 27 28.565 80 19.754 1.8 1.3 20.8 5.13 37.9 8.19 52241 7.8 20.8 5.32 37.9 8.19 52271

M13 08-Apr 7:28 27 30.215 80 20.280 1.3 bottom 19.3 5.34 37.9 8.22 50615 6.0 19.3 5.01 37.9 8.24 50705

M14 02-Apr 9:27 27 09.181 80 15.502 1.8 0.8 24.9 4.15 12.8 7.69 21249 5.1 25.1 5.90 21.7 7.60 34668

M15 06-Apr 9:25 27 21.456 80 20.479 1.9 1.3 25.6 5.71 1.1 7.76 2089 7.1 25.5 5.29 1.1 7.69 2095

WEATHER

Wind Clouds

Site H2S Color Type Structure Firmness m/s From Air temp % Tide Speed

M1 

# no dark grey muddy sand well sorted 

# med stiff 0.9 SSW 25.7 10 

# flood weak

M2 yes black sandy mud unsorted med stiff 2.1 SSW 23.1 60 flood weak

M3 yes black mud unsorted very soft 2.6 SW 23.5 20 0 0

M4 yes black muddy sand med sorted soft 4.3 SW 25.8 35 ebb moderate

M5 yes black muddy sand med sorted soft 4.7 SW 25.6 45 ebb weak

M6 yes dark grey muddy sand med sorted med stiff 5.0 S 26.1 40 ebb weak

M7 no dark grey fine sand med sorted med stiff 3.6 S 28.6 60 flood moderate

M8 no grey fine sand well sorted stiff 5.8 S 27.1 80 flood weak

M9 no dark grey fine sand med sorted stiff 4.2 S 28.5 60 0 0

M10 no grey fine sand med sorted med stiff 8.8 SW 28.1 40 ebb weak

M11 no dark grey fine sand med sorted stiff 6.5 SW 28.7 70 ebb weak 

# very rough, waves across the bow

M12 no grey coarse sand med sorted stiff 3.3 W 9.6 0 flood strong

M13 no grey coarse sand med sorted stiff 2.9 W 8.2 0 

# flood weak

M14 yes black muddy sand med sorted soft 2.3 SW 24.8 20 

# ebb moderate

M15 no black mud well sorted very soft 3.0 SSW 26.2 20 0 0

# Table 4. SLE-IRL July 2009



# SURF BOTT

Site Date Time Lat Long Depth Secchi Temp Oxygen Salinity pH Cond. Turbidity Temp Oxygen Salinity pH Cond.

M1 06-Jul 15:49 27 19.489 80 19.931 1.1 0.7 31.0 3.89 0.6 7.45 7.7 31.0 3.88 0.6 7.29

M2 06-Jul 14:47 27 16.252 80 19.320 1.1 bottom 31.0 3.89 1.1 7.54 9.9 30.9 3.60 1.1 7.51

M3 06-Jul 9:42 27 13.719 80 17.299 3.0 1.1 29.9 5.40 7.1 7.87 3.1 29.8 1.52 15.0 7.10

M4 06-Jul 9:12 27 10.940 80 15.920 1.8 1.0 29.8 4.25 14.2 7.73 6.2 29.9 3.32 15.9 7.23

M5 06-Jul 10:29 27 12.253 80 15.000 2.3 1.0 29.6 5.43 18.0 7.94 5.4 28.7 2.87 24.4 7.25

M6 06-Jul 10:53 27 12.804 80 12.938 2.9 1.3 29.5 6.06 19.7 8.02 4.9 28.0 4.11 27.2 7.58

M7 06-Jul 11:20 27 10.379 80 11.860 1.2 bottom 27.5 4.38 32.6 7.90 4.1 27.2 4.34 33.1 7.91

M8 06-Jul 12:45 27 08.977 80 10.051 1.2 1.0 30.5 3.66 31.8 7.65 6.9 31.8 3.56 31.8 7.56

M9 06-Jul 12:09 27 11.972 80 10.452 1.5 bottom 27.9 4.33 33.1 7.93 2.4 27.8 4.41 33.3 7.88

M10 09-Jul 7:52 27 21.008 80 15.899 1.4 bottom 29.9 4.88 33.9 8.46 56629 1.6 29.9 4.66 33.9 8.45 56622

M11 09-Jul 9:53 27 23.925 80 16.940 2.0 bottom 30.0 5.51 34.3 8.39 57345 1.1 30.0 4.77 34.3 8.38 57330

M12 09-Jul 11:01 27 28.568 80 19.743 1.5 bottom 26.5 5.98 34.2 8.15 53444 2.0 25.9 5.87 35.1 8.17 54077

M13 09-Jul 10:33 27 30.213 80 20.278 1.5 bottom 29.0 4.90 30.4 8.14 50494 2.9 28.9 4.46 30.6 8.13 50637

M14 06-Jul 8:41 27 09.178 80 15.504 1.1 1.0 30.2 3.89 8.6 7.70 4.2 30.0 3.45 8.8 7.51

M15 06-Jul 15:25 27 21.758 80 20.794 1.7 0.8 31.5 4.39 0.6 7.53 5.6 29.6 2.53 0.6 7.46

WEATHER

Wind Clouds

Site H2S Color Type Structure Firmness m/s From Air temp % Tide Speed

M1 

# yes black muddy sand med sorted 

# soft 2.7 W 32.9 25 0 0 

# wood debris in the sediment

M2 no dark brown muddy sand med sorted med stiff 2.1 W 32.7 ? ebb slight peat and wood in sediment

M3 yes black mud well sorted very soft 3.5 W 29.2 40 0 0

M4 yes black mud well sorted very soft 1.8 W 28.7 15 weak flood

M5 yes black mud well sorted very soft 2.8 W 29.6 45 0 0

M6 no dark brown muddy sand med sorted med stiff 4.5 SW 29.9 50 ebb weak shell hash in sediment

M7 no dark grey fine sand well sorted stiff 5.5 SW 30.5 45 ebb weak

M8 no grey fine sand well sorted very stiff 2.4 W 31.5 30 ebb strong

M9 no grey fine sand well sorted very stiff 4.4 SW 30.2 45 ebb slight

M10 no dark grey muddy sand med sorted med stiff 2.2 SW 26.6 0 0 0

M11 yes dark grey fine sand med sorted med stiff 1.3 SW 29.5 5 flood weak

M12 no brown fine sand med sorted med stiff 1.9 SW 31.0 60 flood moderate

M13 no brown coarse sand med sorted med stiff 3.5 WSW 30.2 15 

# flood weak

M14 no brown muddy sand med sorted med stiff 1.3 W 28.1 10 0 0

M15 no dark brown muddy sand med sorted soft 1.5 W 33.0 15 0 0