A Baseline Assessment of the Ecological

Resources of Jobos Bay, Puerto Rico 

July 2011 

Editors 

David R. Whitall 

Bryan M. Costa

Laurie J. Bauer 

Angel Dieppa

Sarah D. Hile 

NOAA Technical Memorandum NOS NCCOS 133 
Citation 

Whitall, D.R., B.M. Costa, L.J. Bauer, A. Dieppa, and S.D. Hile (eds.). 2011. A Baseline Assessment of the 

Ecological Resources of Jobos Bay, Puerto Rico. NOAA Technical Memorandum NOS NCCOS 133. Silver 

Spring, MD. 188 pp. 

Mention of trade names or commercial products does not constitute endorsement or recommendation for their 

use by the United States government. 
A Baseline Assessment of the Ecological Resources
 

of Jobos Bay, Puerto Rico 

Prepared by the
 

Coastal and Oceanographic Assessment, Status and Trends (COAST) Branch
 

and the Biogeography Branch (BB)
 

Center for Coastal Monitoring and Assessment (CCMA)
 

National Centers for Coastal Ocean Science (NCCOS)
 

National Oceanic and Atmospheric Association National Ocean Service (NOAA)
 

1305 East West Highway (SSMC-IV, N/SCI-1)
 

Silver Spring, MD 20910
 

USA
 

July 2011 

Editors 

David R. Whitall
 

NOAA Center for Coastal Monitoring and Assessment
 

Coastal and Oceanographic Assessment, Status and Trends Branch
 

Bryan M. Costa
 

NOAA Center for Coastal Monitoring and Assessment, Biogeography Branch and
 

Consolidated Safety Services, Inc., Fairfax, VA, under NOAA Contract No. DG133C07NC0616
 

Laurie J. Bauer
 

NOAA Center for Coastal Monitoring and Assessment, Biogeography Branch and
 

Consolidated Safety Services, Inc., Fairfax, VA, under NOAA Contract No. DG133C07NC0616
 

Angel Dieppa
 

Jobos Bay National Estuarine Research Reserve
 

Sarah D. Hile
 

NOAA Center for Coastal Monitoring and Assessment, Biogeography Branch and
 

Consolidated Safety Services, Inc., Fairfax, VA, under NOAA Contract No. DG133C07NC0616
 

NOAA Technical Memorandum NOS NCCOS 133 

United States National Oceanic and 

Department of Commerce Atmospheric Administration National Ocean Service 

Gary Locke 

Secretary 

Jane Lubchenco 

Administrator 

David Kennedy 

Assistant Administrator 

 

Baseline Assessment of Jobos Bay, Puerto Rico 

About this document 

This report presents an ecological characterization of the marine resources of Jobos Bay, Puerto Rico 

and the surrounding coral reef ecosystems. The purpose of this work, conducted by National Oceanic 

and Atmospheric Administration’s (NOAA) Center for Coastal Monitoring and AssessmentA (CCMA), 

U.S. Department of Agriculture’s (USDA) Agricultural Research Service (ARS) and the Jobos Bay 

National Estuarine Research Reserve (JBNERR), was to provide natural resource managers with a 

spatially comprehensive characterization of the marine ecosystem. 

Funding for this project was provided by NOAA’s Coral Reef Conservation Program, USDA’s
 

Conservation Effects Assessment Program and National Centers for Coastal Ocean Science. 

For more information on this work and other CCMA projects, please see: http://ccma.nos.noaa.gov/
 

Direct questions or comments to:
 

David Whitall, Ph.D.
 

Center for Coastal Monitoring and Assessment
 

National Oceanic and Atmospheric Administration
 

1305 East West Highway
 

SSMC4, N/SCI-1
 

Silver Spring, MD 20910
 

Phone: (301) 713-3028 x138
 

dave.whitall@noaa.gov
 

Related projects include:
 

An Ecological Characterization of the Marine Resources of Vieques, Puerto Rico
 

http://ccma.nos.noaa.gov/ecosystems/coralreef/vieques/
 

Baseline Assessment of Guanica Bay, Puerto Rico in Support of Watershed Restoration
 

http://ccma.nos.noaa.gov/ecosystems/coralreef/guanica.aspx
 

Caribbean Coral Reef Ecosystem Monitoring Project
 

http://ccma.nos.noaa.gov/ecosystems/coralreef/reef_fish/
 

Contaminants and Coral Health in Southwest Puerto Rico
 

http://ccma.nos.noaa.gov/stressors/pollution/swpr/
 

All photographs provided in this document were taken by NOAA/NOS/NCCOS/Center of Monitoring 

Assessment around Jobos Bay, Puerto Rico unless otherwise noted. 

A The Center for Coastal Monitoring and Assessment (CCMA) is a part of National Oceanic and Atmospheric Administration (NOAA), National Ocean 

Service (NOS), National Centers for Coastal Ocean Science (NCCOS). 
Baseline Assessment of Jobos Bay, Puerto Rico 

Table of Contents 

Executive Summary i
 

Chapter 1: Introduction and Background 1
 

1.1. Background 1
 

1.2. Objectives 1
 

1.3. Study Area Description 2
 

1.4. Site Characterization 4
 

1.4.1. Environmental Setting 4
 

1.4.2. Jobos Bay Watershed 5
 

Chapter 2: Shallow-water Benthic Habitats of Jobos Bay 11
 Bryan Costa, Laurie Bauer and Peter Mueller 

2.1. Introduction 11
 

2.2. Benthic Habitat Classifi cation Scheme 12
 

2.2.1. Comparison to Previous NOAA Habitat Classifi cation Schemes 13
 

2.2.2. Geographic Zones 14
 

2.2.3. Geomorphological Structure Types 18
 

2.2.4. Biological Cover Classes 25
 

2.2.5. Live Coral Cover Classes 28
 

2.3. Benthic Habitat Creation 30
 

2.3.1 General Mapping Approach 30
 

2.4. Remotely Sensed Imagery 30
 

2.4.1. Acquisition and Processing of the Optical Imagery 31
 

2.4.2. Acquisition of the Acoustic Imagery 32
 

2.4.3. Processing of the Acoustic Imagery 33
 

2.5. Habitat Feature Identification and Delineation 36
 

2.5.1. Habitat Feature Identification 36
 

2.5.2. Habitat Feature Delineation 37
 

2.6. Habitat Feature Attribution (Ground Validation) 38
 

2.7. Expert Review 40
 

2.8. GIS Quality Control 40
 

2.9. Conclusions 40
 

2.9.1. Map Summary Statistics 41
 

2.9.2. Comparison to Previous NOAA Habitat Maps of Jobos Bay 50
 

Chapter 3: Baseline Characterization of Fish Communities, Associated Benthic
 

Habitats and Marine Debris of Jobos Bay 57
 

Laurie Bauer, Christopher F.G. Jeffrey and Kimberly Roberson 

3.1. Introduction 57
 

3.2. Methods 58
 

3.2.1. Site Selection 58
 
Baseline Assessment of Jobos Bay, Puerto Rico 

3.2.2. Field methods 59
 

3.2.3. Data Analysis 60
 

3.3. Results and Discussion 62
 

3.3.1. Benthic habitat 62
 

3.3.2. Fish assemblages 72
 

3.4. Conclusions 104
 

Chapter 4: Contaminants in Sediments and Coral Tissues of Jobos Bay 111 

David R. Whitall, Anthony S. Pait, Dennis Apeti, Angel Dieppa, Sarah E. Newton, Lia Brune, Chris Caldow, 

Andrew L. Mason and John Christensen 

4.1. Introduction 111
 

4.2. Methods 111
 

4.2.1. Sampling Design 111
 

4.2.2. Field Methods 113
 

4.2.3. Chemical Contaminants Analyzed 114
 

4.2.3.1. Polycyclic aromatic hydrocarbons (PAHs) 114
 

4.2.3.2. Polychlorinated biphenyls (PCBs) 115
 

4.2.3.3. Organochlorine Pesticides 115
 

4.2.3.4. Butyltins 115
 

4.2.3.5. Major and Trace Elements 117
 

4.2.4. Total Organic Carbon (TOC) and Grain Size 118
 

4.2.5. Statistical Analyses 118
 

4.2.6. Providing Context for Results 118
 

4.3. Results – Overview of Contaminant Patterns 119
 

4.3.1. Environmental Parameters 119
 

4.3.2. Polycyclic Aromatic Hydrocarbons (PAHs) 119
 

4.3.3. Polychlorinated Biphenyls (PCBs) 123
 

4.3.4. DDT and Other Chlorinated Pesticides 124
 

4.3.5. Butyltins 127
 

4.3.6. Major and Trace Elements 128
 

4.3.6.1. Silver (Ag) 128
 

4.3.6.2. Aluminum (Al) 131
 

4.3.6.3. Arsenic (As) 131
 

4.3.6.4. Cadmium (Cd) 132
 

4.3.6.5. Chromium (Cr) 133
 

4.3.6.6. Copper (Cu) 133
 

4.3.6.7. Iron (Fe) 133
 

4.3.6.8. Mercury (Hg) 133
 

4.3.6.9. Manganese (Mn) 134
 

4.3.6.10. Nickel (Ni) 134
 

4.3.6.11. Lead (Pb) 135
 

4.3.6.12. Antimony (Sb) 136
 

4.3.6.13. Selenium (Se) 136
 

4.3.6.14. Tin (Sn) 136
 

4.3.6.15. Zinc (Zn) 137
 

4.4. Further Interpretation of Sediment Results 137
 

4.4.1. Inter-metal and grain size correlation 138
 
Baseline Assessment of Jobos Bay, Puerto Rico 

4.5. Conclusions 143
 

Chapter 5: Spatial and Temporal Variability in the Water Column Nutrients and
 

Pesticides of Jobos Bay 151
 David Whitall, Angel Dieppa and Thomas L. Potter 

5.1. Introduction 151
 

5.1.1. Nutrients 151
 

5.1.2. Pesticides 152
 

5.2. Methods 153
 

5.2.1. Nutrients, Pesticides and Chlorophyll a Sampling and Analysis 153
 

5.2.2. Nutrient and Chlorophyll a Sample Collection Methods 154
 

5.2.3. Diel Sampling Program of Nutrients and Chlorophyll a 155
 

5.2.4. Nutrient and Chlorophyll a Analysis 155
 

5.2.5. Pesticide Sample Collection Methods 155
 

5.2.6. Pesticide Sample Handling and Preparation 155
 

5.2.7. Statistical Analysis of Data 157
 

5.3. Results and Discussion 158
 

5.3.1. Orthophosphate 158
 

5.3.2. Oxidized Nitrogen 158
 

5.3.3. Chlorophyll a 159
 

5.3.4. Pesticide Results 160
 

5.4. Conclusions 162
 

Chapter 6: Conclusions 167
 

Appendices 171
 
Baseline Assessment of Jobos Bay, Puerto Rico 

Executive Summary
 

This baseline assessment of Jobos Bay and surrounding marine ecosystems consists of a two 

part series. The first report (Zitello et al., 2008) described the characteristics of the Bay and its 

watershed, including modeling work related to nutrients and sediment fluxes, based on existing data. 

The second portion of this assessment, presented in this document, presents the results of new 

field studies conducted to fill data gaps identified in previous studies, to provide a more complete 

characterization of Jobos Bay and the surrounding coral reef ecosystems. Specifically, the objective 

was to establish baseline values for the distribution of habitats, nutrients, contaminants, fi sh, and 

benthic communities. This baseline assessment is the first step in evaluating the effectiveness in 

changes in best management practices in the watershed. 

This baseline assessment is part of the Conservation Effects Assessment Project (CEAP), which 

is a multi-agency effort to quantify the environmental benefits of conservation practices used by 

agricultural producers participating in selected U.S. Department of Agriculture (USDA) conservation 

programs. Partners in the CEAP Jobos Bay Special Emphasis Watershed (SEW) included USDA’s 

Agricultural Research Service (ARS) and the Natural Resources Conservation Service (NRCS), 

National Oceanic and Atmospheric Administration (NOAA) and the Government of Puerto Rico. The 

project originated from an on-going collaboration between USDA and NOAA on the U.S. Coral Reef 

Task Force. The Jobos Bay watershed was chosen because the predominant land use is agriculture, 

including agricultural lands adjacent to the Jobos Bay National Estuarine Research Reserve (JBNERR 

or Reserve), one of NOAA’s 26 National Estuarine Research Reserves (NERR). 

This report is organized into six chapters that represent a suite of interrelated studies. Chapter 1 

provides a short introduction to Jobos Bay, including the land use and hydrology of the watershed. 

Chapter 2 is focused on benthic mapping and provides the methods and results of newly created 

benthic maps for Jobos Bay and the surrounding coral reef ecosystem. Chapter 3 presents the results 

of new surveys of fish, marine debris, and reef communities of the system. Chapter 4 is focused on 

the distribution of chemical contaminants in sediments within the Bay and corals outside of the Bay. 

Chapter 5 focuses on quantifying nutrient and pesticide concentrations in the surface waters at the 

Reserve’s System-Wide Monitoring Program (SWMP) sites. Chapter 6 is a brief summary discussion 

that highlights key findings of the entire suite of studies. 

The main findings of each Chapter are as follows: 

CHAPTER 1: INTRODUCTION 

• Jobos Bay, the second largest estuary in Puerto Rico, features diverse marine habitats, including 

mangroves, salt marshes, seagrasses and coral reefs. 

• The Jobos Bay watershed is 137 km2 in size, has a population of about 32,000 people and a 

variety of land uses including low density urban and industrial, with the predominant land use 

being agriculture. 

• Precipitation patterns in the watershed are strongly seasonal with the rainiest periods occurring 

in the fall. 

• Río Seco, in the east, is the only major river that discharges into Jobos Bay seasonally. 

CHAPTER 2: BENTHIC HABITAT MAPPING 

• A benthic habitat map was created for the Jobos Bay region by delineating and classifying 

habitat features visible in optical and acoustic remotely sensed imagery. Several improvements 

were made to this map (relative to the existing habitat map from 2001), including using: (1) a 

Executive Summary i 
Baseline Assessment of Jobos Bay, Puerto Rico 

Executive Summary

smaller mapping unit (i.e., 1,000 versus 4,000 m2), (2) a more detailed classifi cation scheme, 

(3) more recent optical imagery (i.e., from 2006 versus 1999), and (4) newly acquired acoustic 

imagery to supplement the optical imagery in turbid areas. 

• Benthic features were classified based on five primary coral reef ecosystem attributes: 1) 

geographic zone, 2) geomorphological structure, 3) dominant biological cover, 4) amount of 

live coral cover, and 5) percent hardbottom. When linked together, 93 unique combinations of 

these attributes were identified and delineated. 

• In total, 35.7 km2 of the seafloor and 14.1 km2 of the intertidal shoreline area in and around 

Jobos Bay were mapped. Unconsolidated Sediment, specifically Mud, constituted the majority 

(93%) of the mapped area, with Coral Reef and Hardbottom comprising around 7%. These 

substrates were colonized most commonly by Seagrass (31%), followed by No Cover (28%), 

Mangroves (21%) and Algae (20%). Percent live coral cover was <10% for 95% of the mapped 

area, while the remainder was mapped as 10% ≤ 50%. 

• The thematic accuracy of this habitat map is not known as a statistically robust accuracy 

assessment was not conducted. However, the map was reviewed by local experts and similar 

products created using the same mapping protocol had high thematic accuracy levels. 

CHAPTER 3: FISH COMMUNITIES, BENTHIC HABITATS AND MARINE DEBRIS 

• Field surveys were conducted to characterize fish communities and associated habitats in 

the Jobos Bay ecosystem. Sites were selected via a stratified-random sampling design using 

the NOAA benthic habitat map and geographic region. A total of 45 sites were sampled (20 

hardbottom, 15 unconsolidated sediments, 10 mangrove). 

• On hardbottom, turf algae accounted for the highest overall mean percent cover, followed by 

macroalgae, hard coral, sponges, and gorgonians. Hard coral cover averaged 6.5 (±1.2)%, 

with higher amounts occurring on aggregate reef on the fore reef adjacent the cays. The 

most abundant coral was Porites astreoides, followed by Siderastrea siderea, Montastraea 

cavernosa, and the Montastraea annularis complex. Unconsolidated sediment and mangrove 

habitats were characterized by varying degrees of seagrass and algal cover. 

• Fish species richness and diversity were significantly greater on hardbottom compared to 

mangrove and unconsolidated sediments. Hardbottom and mangroves supported higher fish 

densities and biomass than unconsolidated sediments. 

• The fish community consisted of 34 taxonomic families and 112 species. The fi sh community 

varied by habitat type. Wrasses and damselfishes were most numerically abundant on 

hardbottom, whereas surgeonfi shes, parrotfishes, and snappers accounted for the highest 

proportion of biomass. Large schools of clupeiids, which were absent on other habitats, were 

present at several mangrove sites. Fish abundance and biomass on unconsolidated sediments 

were variable but generally low compared to the other habitats. Overall, groupers (Cephalopholis 

and Epinephelus spp.) were infrequent across the study area and generally small in size. The 

majority of observed snappers were also juveniles. 

CHAPTER 4: CONTAMINANTS IN SEDIMENTS AND CORAL TISSUES 

• A stratified random sampling design was used to assess a suit of 154 contaminants in surficial 

sediments and coral (P. astreoides) tissues. 

• Levels of contamination of sediment in the Bay were similar to what has been observed in 

other systems in Puerto Rico, and were generally below levels expected to be toxic to benthic 

organisms. No sites exceeded published sediment quality guidelines for any analyte. In general, 

the inner bay had significantly higher concentrations of contaminants in sediments. This is likely 

ii 
Baseline Assessment of Jobos Bay, Puerto Rico 

driven by riverine inputs and lack of oceanic flushing in the inner bay, as well as a significantly 

higher percentage of fine grained sediments, which tend to accumulate more contaminants due 

to higher surface areas. 

• Levels of contamination in coral tissues (P. astreoides) were similar to what has been observed 

in other systems in Puerto Rico. Currently, no guidelines exist for acceptable levels of 

contamination in corals. 

• Only two out of 154 analytes measured in corals showed a difference between the inshore 

and offshore strata; both arsenic (As) and lead (Pb) demonstrated statistically higher values 

offshore. 

CHAPTER 5: NUTRIENTS AND PESTICIDES IN SURFACE WATER 

• In order to quantify the spatial and temporal variability of surface water nutrients and pesticides, 

estuarine samples were collected monthly at the previously established JBNERR SWMP sites. 

• Surface water concentrations of orthophosphate were highest at site 09, which is the site closest 

to land. Oxidized nitrogen concentrations (nitrate plus nitrite) were lowest at site 20, which is 

farthest from shore. This difference in spatial patterns between nitrogen and phosphorus may 

refl ect different flux pathways (groundwater versus surface runoff). 

• Chlorophyll a concentrations were statistically unique at each site, suggesting the site specific 

forcing factors (e.g., nutrients, hydrology, grazing pressure) are driving water column primary 

productivity. 

• The only current use pesticide detected in surface waters in the Bay was atrazine. The atrazine 

degradation product desethylatrazine (DEA) was also detected. Levels of these compounds 

were below levels associated with environmental toxicity. 

• Time series data show that pesticide detections in the Bay occurred following herbicide 

applications on the farm immediately preceding a large storm event. This suggests that the 

dominant delivery pathway of pesticides to the Bay is surface water runoff. 

CHAPTER 6: CONCLUSIONS 

• The coral reef habitats outside of Jobos Bay are similar to what has been observed in other 

systems in the U.S. Caribbean. 

• Levels of contamination in sediments and coral tissues were generally low and similar to what 

has been measured in other systems in Puerto Rico. 

• This study serves as a baseline assessment which will allow coastal managers to assess the 

effectiveness of agricultural best management practices in the watershed. 

REFERENCES 

Zitello, A.G., D.R. Whitall, A. Dieppa, J.D. Christensen, M.E. Monaco, and S.O. Rohmann. 2008. 

Characterizing Jobos Bay, Puerto Rico: A Watershed Modeling Analysis and Monitoring Plan. NOAA 

Technical Memorandum NOS NCCOS 76. Silver Spring, MD. 81 pp. 

iii Executive Summary 
Chapter 1
Baseline Assessment of Jobos Bay, Puerto Rico: Introduction 

Introduction and Background 

1.1. BACKGROUND 

The Conservation Effects Assessment Project (CEAP) is a national, multi-agency effort to quantify the 

environmental benefits of best management practices used by agricultural producers participating in 

selected U.S. Department of Agriculture (USDA) conservation programs, including program such as 

the Conservation Reserve Program and the Wetlands Reserve Program. The Jobos Bay Watershed, 

located in south-central Puerto Rico, was selected by CEAP partners as the first tropical CEAP Special 

Emphasis Watershed. Special Emphasis Watersheds (SEW) are strategically located watersheds 

in which researchers quantify and demonstrate water quality and other environmental benefi ts of 

conservation programs. Investigations in Jobos Bay were designed to characterize terrestrial and 

marine ecosystems at varying spatial scales in order to evaluate the relationship between agricultural 

practices and the health of near-shore coral reef ecosystems. 

Partners in the CEAP Jobos Bay SEW included USDA’s Agricultural Research Service (ARS) and the 

Natural Resources Conservation Service (NRCS), National Oceanic and Atmospheric Administration 

(NOAA) and the Government of Puerto Rico. The project originated from an on-going collaboration 

between USDA and NOAA on the 

U.S. Coral Reef Task Force. The 

Jobos Bay watershed was chosen 

because the predominant land use 

is agriculture, including agricultural 

lands adjacent to the Jobos Bay 

National Estuarine Research 

Reserve (JBNERR or Reserve), one 

of NOAA’s 28 National Estuarine 

Research Reserves (Figure 1.1). 

JBNERR staff was actively involved 

in the planning and implementation 

of this study. 

In 2002, the U.S. Coral Reef Task Force identified the need for action at the local level to reduce key 

threats to coral reefs in each of the seven states and territories which possess significant coral reef 

resources. Local Action Strategies (LAS) were developed by Puerto Rico’s local and federal agency 

representatives in 2003. The CEAP work in Jobos Bay directly addresses a LAS goal related to 

land-based sources of pollution by “reducing loss of live coral reef cover through the promotion and 

implementation of integrated watershed and land use management practices,” such as improved 

water management. This effort emphasizes the interaction between upland and coastal ecosystems 

and involves a collaborative partnership between USDA and NOAA to address spatially complex 

natural resource issues. 

1.2. OBJECTIVES 

The primary objective of the Jobos Bay CEAP study is to determine the environmental effects that 

agricultural conservation practices implemented by farmers on the upland may have on coastal waters 

and the associated coral reef ecosystem. The first step in the process is a baseline assessment, 

both of the ecological condition of the marine system, including coral reef ecosystems, and the 

current agricultural management practices. This technical report presents the findings of the baseline 

assessment of the marine ecosystem. 

1 - Introduction and Background

Figure 1.1. Mangrove inlet in southern Jobos Bay. Photo: NOAA Center for Coastal 

Monitoring and Assessment (CCMA). 

1 
Baseline Assessment of Jobos Bay, Puerto Rico: Introduction 

1 - Introduction and Background

Specific objectives of the marine component of this project were: 

1. Characterize the benthic habitats of the bay and offshore waters. 

2. Assess the biological condition of the bay and surrounding reef ecosystems. 

3. Quantify the extent and magnitude of contamination in surficial estuarine/marine sediments 

and in coral tissues (Porites astreoides). 

4. Quantify the spatial and temporal patterns in estuarine surface water nutrient and pesticide 

concentrations within the Reserve. 

The long term plan is to re-visit this assessment after 5 or 10 years to assess the effectiveness of the 

management practices that had been implemented by documenting change in the marine ecosystem. 

This phase of the project is tentative at this point, and is funding dependent. 

1.3. STUDY AREA DESCRIPTION 

Jobos Bay is located on the south-central coast of Puerto Rico centered at 17o 56’N and 66o 13’W, 

between the municipalities of Salinas and Guayama (Figure 1.2). The second largest estuary in 

Puerto Rico, Jobos Bay has a total surface area of just over 25 km2. Jobos Bay is classified as a 

coastal plain estuary that was formed by rising sea levels at the end of the last ice age. It is a natural 

harbor protected from offshore wind and waves by a series of mangrove islands in the southwest and 

Punta Pozuelo in the southeast. Jobos Bay features diverse marine habitats, including mangroves, 

mud flats, salt marshes, seagrasses and coral reefs (Figure 1.3). 

2 

Figure 1.2. Location of Jobos Bay, its watershed and the Jobos Bay National Estuarine Research Reserve (JBNERR) in Puerto Rico. 
Baseline Assessment of Jobos Bay, Puerto Rico: Introduction

3 1 - Introduction and Background

The Jobos Bay watershed reaches 

as far as 11 km inland and has a total catchment area of 137 km2. The 

watershed contains several centers 

of low density urban development 

and has an estimated total population of 32,000 people (U.S. Bureau 

of the Census, 2001). The predominant land use is agriculture, including diversifi ed production of agricultural commodities such as plantains, 

bananas, papayas, sorghum, corn 

and hay, and animal operations with 

poultry and some beef cattle. Water 

quality and conservation concerns 

related to agricultural practices are 

important in the Jobos Bay watershed and may infl uence coral reef 

ecosystem health. Preliminary studies reported that pesticides and fertilizers applied in agricultural fi elds 

were being transported to the bay 

(DNER, 2002). Increasing industrial 

and commercial growth in the watershed has also been recognized as a 

concern to Jobos Bay’s ecosystem 

health. There are two landfi ll operations within the watershed. The regional landfi ll, operated by BFI, is located in the middle of the watershed 

and is expected to broaden to twice 

the size of its original plans; while 

the other is on the eastern edge of 

the watershed in Guayama. Other 

major industries such as Chevron 

Phillips, Ayerst-Wyeth, IPR Pharmaceuticals, Colgate-Palmolive and 

ProChem maintain operations in the 

watershed (DNER, 2002). Two of

Puerto Rico’s seven power production plants operate within the Jobos 

Bay watershed. There are three point 

source dischargers with USEPA National Pollutant Discharge Elimination System (NPDES) permits in the 

Jobos Bay watershed: Chevron Phillips, the Aguirre power plant and Ball 

Metal Beverage Container (USEPA, 

2010; Table 1.1; Figure 1.4). 

Figure 1.3. Mud flats in JBNERR. Photo: NOAA CCMA.

Table 1.1. Facilities with NPDES discharge permits in the Jobos Bay watershed. 

Data from USEPA (2010). Units are displayed in pounds.

Phillips Oil Aguirre Ball Pollutant Name Refi nery1 Power Plant2 Metal

Ammonia 184 -- --

Barium 15.9 -- --

BOD, 5-day, 20 deg. C 2,866 43,929 --

Chemical oxygen demand (COD) 14,166 1,817,976 --

Chlorine 197 6.13 --

Chromium 1.37 0.62 --

Chromium, Hexavalent 4.082 -- --

Copper 0.63 107 6.0036

Fluoride 1,122 -- --

Foaming agents 28.5 -- 434

Iron -- 1,815

Lead -- 44.1 7.78

Manganese 2.17 -- --

Mercury 0.203 -- --

Oil and grease per production 0.52 -- 14,031

Selenium 1.99 -- --

Solids, total suspended 2,767 278,856 --

Sulfi de 4.63 -- 240

Total phenols -- 187 --

Zinc -- 2,435 109

1

 Philips Oil Refi nery was cited for violations for Copper (Cu) in 2009. 2

 Aguirre Power Plant was cited for violations for Zinc (Zn) in 2007 and 2008, 

Silver (Ag) in 2009, and Iron (Fe) in 2009.

Figure 1.4. Location of point source dischargers with National Pollutant Discharge 

Elimination System (NPDES) permits.
Baseline Assessment of Jobos Bay, Puerto Rico: Introduction 

1 - Introduction and Background

1.4. SITE CHARACTERIZATION 

1.4.1. Environmental Setting 

The Jobos Bay watershed is primarily comprised of the low-relief South Coastal Plain of Puerto 

Rico, but reaches elevations of greater than 700 m at its landward boundary. Many of Jobos Bay 

watershed’s physical characteristics are attributed to the presence of two of Puerto Rico’s Central 

Interior Mountain Ranges to the north, La Cordillera Central and La Sierra de Cayey. These mountains 

serve as a barrier to the moisture-laden northeast trade winds, causing a zone of low precipitation 

throughout the southern coast of Puerto Rico. Mean annual rainfall between 1999 and 2008 was 996 

mm at the Aguirre rain gauge station located in the watershed (NCDC, 2010). For this same time 

period and station, September and October were recorded as the wettest months, with an average 

rainfall of 167 mm, while January was 

the driest month, with an average 

rainfall of 20 mm (Figure 1.5). The 

Jobos Bay watershed is located in 

the Subtropical Dry Forest Zone, 

the most arid ecological life zone in 

Puerto Rico (Ewel and Whitmore, 

1973). The vegetation is almost 

entirely deciduous and forms a 

complete ground cover on most 

soils. Past land uses, especially 

abandoned sugar cane fields, 

support man-modified vegetation 

that is characterized by a complete 

grass cover and sparsely distributed 

tall trees with fl attened spreading 

crowns. 

Temperatures in the Jobos Bay watershed are high throughout the year and show little seasonal 

fluctuation. The mean annual temperature is 26o C (78.8o F), with a maximum of 27.5o C (81.6o F) in 

August and a minimum of 24.3o C (75.7o F) in January (NCDC, 2010). The predominant wind comes 

from an easterly direction at mean speeds of 10 km/hr or less (McClymonds and Díaz, 1972). The 

regular daily wind pattern is for low velocity northeast winds to give way to a more brisk southeast 

wind as the day progresses (DNER, 2002). 

Due to Jobos Bay’s dry climate and relatively low seasonal rainfall, surface runoff usually only occurs 

during the wettest months of the year, September through November (Ewel and Whitmore, 1973). 

As a result, most of the watershed’s natural stream beds are only intermittently fl ooded throughout 

the year. Río Seco, in the east, is the only major river that discharges into Jobos Bay seasonally. 

Quiñones-Aponte et al. (1997) described that year-round streamflow downstream is limited by where 

most streams meet the highly porous fan delta deposits. At that point, the streamfl ow infiltration 

becomes the most important source of groundwater recharge to the underlying aquifer. The Jobos 

Bay watershed is within the South Coastal Plain alluvial aquifer that extends from the bedrock hills 

near the watershed’s northern boundary to the coast. According to Quiñones-Aponte et al. (1997), 

there are two discrete groundwater units in the coastal zone, a shallow aquifer between 3 m and 23 

m thick and a deep aquifer below. The shallow aquifer is believed to supply the mangrove complex 

at the watershed’s coastal margins, while the deep aquifer may provide freshwater to the offshore 

mangrove islands that form Jobos Bay’s southern boundary. 

Figure 1.5. Average monthly precipitation at Aguirre weather station. 

4 
Baseline Assessment of Jobos Bay, Puerto Rico: Introduction 

1.4.2. Jobos Bay Watershed 

The Jobos Bay watershed includes 137.3 km2 of the South Coastal Plain of Puerto Rico and drains 

surface runoff directly to Jobos Bay (Figure 1.6). Jobos Bay and its associated watershed is framed 

by two perennial stream networks; Río Nigua to the west and Río Guamaní to the east. 

The watershed’s northern boundary, beginning in the foothills of the Central Interior Mountain Range, 

extends about 6 km to 11 km landward from the shoreline of Jobos Bay. Although Jobos Bay’s

shoreline represents a straight-line distance of under 20 km, the meandering Bay’s mainland coast 

stretches a total distance of over 45 km. The Jobos Bay watershed does not contain one single river 

network that accumulates surface water flow throughout the basin. Instead, the watershed contains 

a variety of distinct pathways by which surface waters are contributed to Jobos Bay. These include 

perennial stream discharges, intermittent stream discharges and diffuse overland runoff to Jobos

Bay. A unique composite of land cover, topography and underlying geology dictate the type of surface 

water contribution found in the different areas of the Jobos Bay watershed. 

The Jobos Bay watershed experienced several man-made water diversion projects since the start

of the 20th century. Beginning in 1914, successful agricultural operations have been achieved by

transferring surface water to the Jobos Bay watershed from reservoirs outside the basin through

irrigation canals. As part of the Guayama Irrigation District, two primary irrigation canals distribute

water from Patillas and Carite Reservoirs, northeast of Jobos Bay, to operations throughout the

watershed. Both canals flow from east to west, with Canal de Guamaní in the north and Canal de

Patillas in the south. Non-irrigation drainage canals were also constructed in order to reclaim wet

1 - Introduction and Background

Figure 1.6. Rivers and canals in Jobos Bay watershed. 

5 
Baseline Assessment of Jobos Bay, Puerto Rico: Introduction 

1 - Introduction and Background

areas for agriculture and to reduce mosquito breeding in response to the risk of malaria in the 1930’s 

(DNER, 2002). 

From Spanish Colonial times up to 

the 1970s, the Jobos Bay watershed 

was primarily used for agricultural 

production (DNER, 2002). Almost 

the entire coastal plain of Jobos Bay 

was under sugarcane cultivation 

until the demise of Puerto Rico’s 

sugarcane market during the 1960s. 

Over the past 35 years, sugarcane 

lands have been steadily converted 

to fruit and vegetable cultivation or 

entirely removed from agricultural 

cultivation. Today, cultivated lands 

in the Jobos Bay watershed only 

comprise 11% of the area’s total land 

cover (Figure 1.7), which is 15 km2. 

However, the extensive clearing of 

land for sugarcane cultivation of the 

past has had a lasting impact on the 

landscape of the Jobos Bay watershed. Despite the historic prevalence of agriculture in the Jobos 

Bay watershed, existing land cover conditions are more indicative of an ecosystem in a natural state. 

Vegetated lands cover 70% of the landscape with grassland, forest and scrub/shrub accounting for 

42%, 15% and 13%, respectively (Figure 1.8). The large amount of vegetated lands may lead to the 

inaccurate conclusion that the Jobos Bay watershed is a relatively pristine system. 

Figure 1.7. Center pivot irrigation on silage farm adjacent to JBNERR. Photo: NOAA

CCMA. 

6 

Figure 1.8. Land use/land cover in Jobos Bay watershed. 
Baseline Assessment of Jobos Bay, Puerto Rico: Introduction 

Inspection of aerial photography 

indicated that as much as 13.5 km2 

of the area classified as grassland is 

revegetated agriculture lands (Figure 

1.9). In addition, an unspecified 

amount of classified grasslands are 

actually used for livestock pasture. 

If these areas were considered a 

separate land cover type the amount 

of naturally vegetated land cover 

would be reduced by 10% to 15%. 

Re-vegetated agriculture fi elds and 

pasture have a higher frequency of 

disturbance and serve fundamentally 

different ecosystem services (e.g., 

different types of habitat) than 

naturally vegetated grasslands. A 

majority of the disturbed grasslands 

exist south of the irrigation canals, 

while the naturally vegetated 

grasslands tend to lie north of the 

canals in the foothills of the Central Interior Mountain Range. 

The 32,000 residents of the Jobos Bay watershed live in low density residential communities that 

are located throughout the area. Over two thirds of the population are residents of the municipality 

of Salinas in the western half of the watershed, while the remainder of the residents live in the 

municipality of Guayama in the east. The average population density in Jobos Bay is maintained at a 

comparatively low 234 people/km2 by large areas of open space between communities. The primary 

transportation routes through the area are Highways 52 and 53, with Route 3 servicing local traffic. 

A variety of industrial activities are distributed throughout the Jobos Bay watershed. Among other 

industries, Jobos Bay hosts two electric power generation plants, a petroleum refinery, and several 

major chemical and pharmaceutical facilities, some of which discharge into the Bay (Table 1.1). 

A more complete discussion of the Jobos Bay watershed and its land uses, including preliminary 

modeling work of sediments and pollutants can be found in Zitello et al. (2008). 

This report is organized into six chapters that represent a suite of interrelated studies. Chapter 2 is 

focused on benthic mapping and provides the methods and results of newly created benthic maps for 

Jobos Bay and the surrounding coral reef ecosystem. Chapter 3 presents the results of new surveys 

of fish, marine debris, and reef communities of the system. Chapter 4 is focused on the distribution of 

chemical contaminants in sediments within the Bay and corals outside of the Bay. Chapter 5 focuses 

on quantifying nutrient and pesticide concentrations in the surface waters at the Reserve’s SystemWide Monitoring Program (SWMP) sites. Chapter 6 is a brief summary discussion that highlights key 

findings of the entire suite of studies. 

1 - Introduction and Background

Figure 1.9. Re-vegetated lands in Jobos Bay watershed. 

7 
Baseline Assessment of Jobos Bay, Puerto Rico: Introduction 

1 - Introduction and Background

REFERENCES 

Department of Natural and Environmental Resources (DNER). 2002. Jobos Bay Estuarine Profile: 

A National Estuarine Research Reserve. Puerto Rico DNER and National Oceanic and Atmospheric 

Administration, Office of Ocean and Coastal Resource Management, Estuarine Reserve Division. 

107 pp. 

Ewel, J.J. and J.L. Whitmore. 1973. The Ecological Life Zones of Puerto Rico and the U.S. Virgin 

Islands. U.S. Department of Agriculture (USDA) Forest Service, Institute of Tropical Forestry. Forest 

Service Research Paper ITF-18. 72 pp. 

McClymonds, N.E. and J.R. Díaz. 1972. Water resources of the Jobos area, Puerto Rico - A preliminary 

appraisal, 1962. U.S. Geological Survey Water-Resources Bulletin 13. 32 pp. 

National Climatic Data Center (NCDC). 2010. NOAA Satellite and Information Service (Online). http:// 

www.ncdc.noaa.gov/oa/climate/stationlocator.html (Accessed 10 June 2011). 

Quiñones-Aponte, V., F. Gómez-Gómez, and R.A. Renken. 1997. Geohydrology and simulation 

of ground-water flow in the Salinas to Patillas area, Puerto Rico. U.S. Geological Survey, Water 

Resources Investigations Report 95-4063. 37 pp. 

U.S. Bureau of the Census. 2001. TIGER/Line Files, Redistricting Census 2000 (Online). http://www. 

census.gov/geo/www/tiger (Accessed 10 June 2011). 

U.S. Environmental Protection Agency (USEPA). 2010. Discharge Monitoring Report (DMR) Pollutant 

Loading Tool (Online). http://cfpub.epa.gov/dmr/ (Accessed 10 June 2011). 

Zitello, A.G., D.R. Whitall, A. Dieppa, J.D. Christensen, M.E. Monaco, and S.O. Rohmann. 2008. 

Characterizing Jobos Bay, Puerto Rico: A Watershed Modeling Analysis and Monitoring Plan. NOAA 

Technical Memorandum NOS NCCOS 76. Silver Spring, MD. 81 pp. 

8 
Baseline Assessment of Jobos Bay, Puerto Rico: Introduction 

1 - Introduction and Background 9 
Chapter 2
 

Baseline Assessment of Jobos Bay, Puerto Rico: Benthic Habitat Mapping 

Shallow-water Benthic Habitats of Jobos Bay 

Bryan Costa1,2,3, Laurie Bauer1,2 and Peter Mueller1,2 

2.1. INTRODUCTION 

The estuarine ecosystems of the Jobos Bay National Estuarine Research Reserve (JBNERR or Reserve) and the surrounding waters of southeastern Puerto Rico have been preserved because they are 

economically and ecologically important natural resources. The mosaic of habitats, including coral reefs, 

seagrasses and mangroves, are home to a diversity of marine organisms that provide valuable ecosystem services to the local community, including fishing, tourism and shoreline protection (DNER, 2002). 

Estuarine and coral reef ecosystems in Puerto Rico and throughout the U.S. Caribbean, however, are 

under increasing pressure from environmental and anthropogenic stressors that threaten these important marine communities (García-Sais et al., 2008). In order to better evaluate and address these threats, 

a baseline understanding of the benthic communities and associated living marine resources is needed 

by scientists and resource managers. Habitat maps, in particular, are an integral component to this process by supporting an effective ecosystem-based approach to management (Pittman et al., 2010). 

Given the importance of habitat maps, NOAA’s Biogeography BranchA (BB) developed the analytical 

protocols used for mapping benthic habitats throughout all U.S. jurisdictions, states, and territories, 

including the U.S. Caribbean. These standardized protocols enable scientists and managers to 

quantitatively compare different estuarine and shallow-water coral reef ecosystems in tropical U.S. 

waters. The BB used these same protocols to generate a habitat map of the estuarine and shallowwater ecosystems surrounding JBNERR (Figure 2.1). 

2 - Benthic Habitat Mapping

Figure 2.1. Map of Jobos Bay National Estuarine Research Reserve (JBNERR) in southeastern Puerto Rico. A benthic habitat map was 

created for the area in and around the Reserve using optical and acoustic imagery. 

A	 The Biogeography Branch is a part of National Oceanic and Atmospheric Administration (NOAA), National Ocean Service (NOS), National Centers 

for Coastal Ocean Science (NCCOS), Center for Coastal Monitoring and Assessment (CCMA). 

1

 Center for Coastal Monitoring and Assessment, National Centers for Coastal Ocean Science, National Ocean Service, National 

Oceanic and Atmospheric Administration 

2

 Consolidated Safety Services, Inc., under NOAA Contract No. DG133C07NC0616 

3

 Corresponding author: Bryan.Costa@noaa.gov 

11 
Baseline Assessment of Jobos Bay, Puerto Rico: Benthic Habitat Mapping 

2 - Benthic Habitat Mapping

The objective of this chapter is to provide spatially-explicit information describing the habitat types, 

biological cover and live coral cover present in and around JBNERR’s boundaries. The resulting finescale habitat map, generated by visual interpretation of optical and acoustic imagery, represents the 

second habitat map produced for this shallow-water (≤30 m) area. It is, however, the fi rst spatially 

complete habitat map for Jobos Bay, as the previous mapping effort was inhibited by poor water clarity. 

The spatial products developed for this project will enable managers and scientists to better monitor 

changes in estuarine and marine habitats of JBNERR. The habitat map created by BB represents one 

such product in a suite of deliverables designed to support the management of JBNERR. In particular, 

these products include: 

• A classifi cation manual 

• Description of the methods used to create the habitat maps 

• Source datasets, including acoustic and optical imagery 

• Ground validation fi eld data 

• Derived datasets, including GIS files of benthic habitats 

Collectively, these products give JBNERR an increased technical capacity for management and 

stewardship of the reserve, including: (1) evaluating the efficacy of management actions, (2) designing 

monitoring sampling plans, (3) assessing the impacts of human-uses, and (4) supporting the process 

of coastal and marine spatial planning (CMSP). In addition to supporting the management of JBNERR, 

this shallow-water mapping effort is part of a larger Conservation Effects Assessment Project (CEAP) 

to explore the environmental effects that upland agricultural practices and conservation measures 

have on estuarine and coral reef ecosystems. This map may be used as a baseline for comparing 

future habitat maps (created using the same procedures outlined here) in order to quantify changes in 

the extent of seagrass beds, mangroves, coral or other habitat features. This comparison would allow 

managers to better understand the impact of new agricultural practices or conservation measures on 

the downstream benthic marine environment. 

2.2. BENTHIC HABITAT CLASSIFICATION SCHEME 

A habitat classification scheme allows scientists to systematically group habitat types based on 

common ecological characteristics. The initial task in any mapping effort is to develop a classification 

scheme by clearly identifying and defining discrete habitat classes. This scheme is subsequently used 

to guide the delineation and attribution of polygons during the mapping process. It is, consequently, 

critical for map users to have an understanding of the classification system, its structure and its 

definitions. This understanding allows users to decide on the appropriate uses for, and limitations of, 

the habitat map. 

The Jobos Bay shallow-water habitat classification scheme defines benthic communities based on five 

primary coral reef ecosystem attributes: 1) broad geographic zone, 2) geomorphological structure, 3) 

dominant biological cover, 4) amount of live coral cover, and 5) percent hardbottom. Habitat features 

are described by varying levels of detail (i.e., major and minor categories nested within them), so 

users can refine the information depicted by habitat map to best suit their research or management 

needs. In total, 93 unique concatenations of zone, major structure, detailed structure, percent hard 

bottom, major cover, percent cover and live coral cover were identified from the optical and acoustic 

imagery. The thematic accuracy of these classes is unknown because a statistically robust accuracy 

assessment was not conducted. Thus, all users should independently analyze this habitat map 

according to their own needs and standards to determine its limitations and usability. Other habitat 

12 
Baseline Assessment of Jobos Bay, Puerto Rico: Benthic Habitat Mapping 

maps created using the same mapping protocol, however, reported overall thematic accuracies of 

greater than 88% for major geomorphological structure and cover classes, and greater than 70% for 

detailed geomorphological structure and biological cover classes (Battista et al., 2007a,b; Zitello et 

al., 2009; Bauer et al., 2010). 

2.2.1. Comparison to Previous NOAA Habitat Classifi cation Schemes 

Many important factors were considered when developing the shallow-water habitat classification 

scheme for Jobos Bay. These factors included: (1) how it would dovetail with existing classification 

schemes for marine habitats; (2) what limitations were associated with the optical imagery and with 

the acoustic imagery; (3) what would be an appropriate minimum mapping unit (MMU); (4) how much 

quantitative in situ underwater video would be needed to create a habitat map; and (5) how best to 

create a habitat map using both optical and acoustic imagery sources. 

In order to simplify this process, the habitat classification scheme implemented in Jobos Bay was 

based on the recently updated classification scheme developed by NOAA to map shallow-water (≤30 

m) benthic habitats around Vieques, Puerto Rico (Bauer et al., 2010). Specifically, the geographic 

zones, major and detailed geomorphological structure and biological cover types were the same for 

both habitat maps (Table 2.1), although some habitat types were present in Vieques which were not 

present in Jobos Bay. Also, both classification schemes had the same the MMU (i.e., 1,000 m2

) and 

cover attributes were based on dominant type. That being said, it is important to note that the Vieques 

map was created from optical imagery, whereas the Jobos Bay map was created from both optical 

and acoustic imagery. 

Table 2.1. The classification scheme used to classify benthic habitats in and around JBNERR in 2010. This classification scheme was 

modeled after the one used in Vieques, Puerto Rico (Bauer et al., 2010). Classes with a line through them were not present in Jobos

Bay. 

Geographic Zone 

Back Reef 

Geomorphological Structure 

Coral Reef and Hardbottom (Hard) 

Biological Cover 

Major Cover 

Bank/Shelf Aggregate Reef Algae 

Bank/Shelf Escarpment Aggregated Patch Reefs Coralline Algae 

Channel Individual Patch Reef Live Coral 

Dredged Pavement Mangrove 

Fore Reef Pav. w/ Sand Channels No Cover 

Lagoon Reef Rubble Percent Hard Seagrass 

Land Rhodoliths 0% ≤ 10% Unclassified 

Reef Crest Rock/Boulder 10% ≤ 30% Unknown 

Reef Flat Spur and Groove 30% ≤ 50% Percent Major Cover 

Salt Pond Unknown 50% ≤ 70% 10% ≤ 50% 

Shoreline Intertidal Unconsolidated Sediment (Soft) 70% ≤ 90% 50% ≤ 90% 

Unknown Mud 90% - 100% 90% ≤ 100% 

Sand N/A N/A 

Sand w/ Scattered Coral & Rock Unknown Unknown 

Unknown Percent Coral Cover 

Other Delineations 0% ≤ 10% 

Artificial 10% ≤ 50% 

Land 50% ≤ 90% 

Unknown 90% - 100% 

N/A 

Unknown 

13 2 - Benthic Habitat Mapping 
Baseline Assessment of Jobos Bay, Puerto Rico: Benthic Habitat Mapping 

2 - Benthic Habitat Mapping

While the map created for Jobos is similar to the one created for Vieques, it is fundamentally different 

from the benthic habitat map created in 2001 by NOAA for all of Puerto Rico (Kendall et al., 2001). 

The primary difference between NOAA’s 2001 and 2010 habitat maps is the separation of biological 

cover from habitat structure, as well as the addition of more detailed structure classes due to the 

higher resolution of the source imagery and much smaller geographic scope of the map project. 

In addition, the 2010 classification scheme includes a map attribute called Percent Coral Cover. This 

attribute describes the percent live coral cover for a habitat feature at the scale of diver observation in 

the water, without regard to dominant biological cover. It is important to note that Percent Coral Cover 

refers only to the hardbottom component of any mapped polygon (and not to the entire polygon itself). 

For instance, an attribution of “percent hardbottom equals 50%≤70% and live coral equals 10%≤50%” 

indicates that 10%≤50% of the hardbottom within that polygon is colonized by live coral. 

2.2.2. Geographic Zones 

Eleven distinct and non-overlapping 

geographic zone types were 

mapped by visually interpreting 

optical and acoustic imagery. Zone 

refers to each benthic community’s 

geographic location. It does not 

address a polygon’s substrate or 

biological cover types. For example, 

the zone Fore Reef is often located 

adjacent to a Reef Crest on the 

seaward side. However, neither 

Fore Reef nor Reef Crest zone types 

describe the structural or biological 

habitat within them. Additionally, 

the location of particular zone types 

may change depending on whether 

the system is a barrier reef, fringing 

reef or when no emergent reef crest 

is present (Figures 2.2, 2.3 and 2.4, 

respectively). Habitats or features 

with areas smaller than the MMU 

or minimum mapping unit (1,000 

m2

) were not considered. A brief 

description of each geographic zone 

is provided in the following text. 

Figure 2.2. Cross-section of zone types when a barrier reef is present. The reef is

separated from the shore by a relatively wide, deep lagoon. 

Figure 2.3. Cross-section of zone types when a fringing reef is present. The reef

platform is continuous with the shore. 

Figure 2.4. Cross-section of zone types when no emergent reef crest is present. 

14 
Baseline Assessment of Jobos Bay, Puerto Rico: Benthic Habitat Mapping 

Back Reef 

Area immediately landward of a Reef Crest that slopes downward towards the seaward edge of a 

Lagoon fl oor or Bank/Shelf. This zone is present only when a Reef Crest exists (Figure 2.5). 

Figure 2.5. The red polygons (left) outline examples of the geographic zone, Back Reef, west of Cayos Caribes. The photograph (right)

depicts the same area from the ground. Photo: NOAA Center for Coastal Monitoring and Assessment (CCMA). 

2 - Benthic Habitat Mapping

Bank/Shelf 

Deeper water area (relative to the shallow water 

in a lagoon) extending offshore from the seaward 

edge of the Fore Reef or shoreline to the beginning 

of the escarpment where the insular shelf drops 

off into deep, oceanic water. If no Reef Crest is 

present, the Bank/Shelf is the fl attened platform 

between the Fore Reef and deep open ocean 

waters or between the Shoreline Intertidal zone 

and open ocean (Figure 2.6). 

Dredged 

Area in which natural geomorphology is disrupted 

or altered by excavation or dredging (Figure 2.7). 

Fore Reef 

Area along the seaward edge of the Reef Crest 

that slopes into deeper water to the landward 

edge of the Bank/Shelf platform. Features not 

associated with an emergent Reef Crest (but still 

having a seaward-facing slope that is significantly 

greater than the slope of the Bank/Shelf) are also 

designated as Fore Reef (Figure 2.8). 

Figure 2.6. The yellow polygon highlights the location of the

geographic zone, Bank/Shelf, south of Cayos de Barca. 

Figure 2.7. The red polygon outlines an example of the geographic 

zone, Dredged, northwest of Arrecife Moreas. 

15 
Baseline Assessment of Jobos Bay, Puerto Rico: Benthic Habitat Mapping 

2 - Benthic Habitat Mapping

Lagoon 

Shallow area (relative to the deeper water of the 

Bank/Shelf) between the Shoreline Intertidal zone 

and the Back Reef of a reef or a barrier island. This 

zone is typically protected from the high-energy 

waves commonly experienced on the Bank/Shelf 

and Reef Crest zones (Figure 2.9). 

Land 

Terrestrial features at or above the spring high 

tide line. Shoreline delineations describing the 

boundary between land and submerged zones 

are established at the wrack line where possible 

or the wet line at the time of imagery acquisition 

(Figure 2.10). The wrack line is a line of organic 

and/or anthropogenic debris (above the mean 

high tide line) that has been deposited by previous higher than normal tides. 

Figure 2.8. The green polygon highlights the location of the

geographic zone, Fore Reef, just south of Cayos de Barca. 

Figure 2.9. The red polygons (left) outline examples of the geographic zone, Lagoon, near Puerto de Jobos. The photograph (right)

depicts the same area from the ground. Photo: NOAA CCMA. 

16 

Figure 2.10. The red polygon (left) outline an example of the geographic zone, Land, near Puerto de Jobos. The photograph (right) was

taken looking northeasterly from inside Bahia de Jobos. Photo: NOAA CCMA. 
Baseline Assessment of Jobos Bay, Puerto Rico: Benthic Habitat Mapping 

Reef Crest 

The flattened, emergent (especially during low tides) or nearly emergent segment of a reef. This zone 

of high wave energy lies between the Fore Reef and Back Reef or Reef Flat zones. Breaking waves 

are often visible in overhead imagery at the seaward edge of this zone (Figure 2.11). 

Figure 2.11. The red polygon (left) highlights the location of the geographic zone, Reef Crest, south of Cayos de Barca. The photograph

(right) depicts an example of the zone, Reef Crest, in Jobos Bay. Photo: NOAA CCMA. 

2 - Benthic Habitat Mapping

Reef Flat 

Shallow, semi-exposed area with little relief between the Shoreline Intertidal zone and the Reef Crest 

of a fringing reef. This broad, flat area often exists immediately landward of a Reef Crest and may 

extend to the shoreline or drop into a Lagoon. This zone is protected from the high-energy waves 

commonly experienced on the Bank/Shelf and Reef Crest zones (Figure 2.12). 

Figure 2.12. The red polygon (left) outline an example of the geographic zone, Reef Flat, near Cayos Caribes. The photograph (right)

depicts the same area from the ground. Photo: NOAA CCMA. 

17 
Baseline Assessment of Jobos Bay, Puerto Rico: Benthic Habitat Mapping 

Salt Pond 

Enclosed area immediately landward of the shoreline with a permanent or intermittent fl ooding regime 

of saline to hypersaline waters (Figure 2.13).

2 - Benthic Habitat Mapping

Figure 2.13. The red polygon (left) outline an example of the geographic zone, Salt Pond, near Cayo Puerca. The photograph (right)

depicts a salt pond from the ground. Photo: NOAA CCMA. 

Shoreline Intertidal 

Area between the spring high tide line (or landward edge of emergent vegetation when present) and 

lowest spring tide level. Emergent segments of barrier reefs are excluded from this zone. Typically, 

this zone is narrow due to the small tidal range in the U.S. Caribbean (Figure 2.14). 

Figure 2.14. The red polygons (left) outline examples of the geographic zone, Shoreline Intertidal, near Central Aguirre. The photograph 

(right) was taken among the mangroves inside JBNERR. Photo: NOAA CCMA. 

2.2.3. Geomorphological Structure Types 

Thirteen distinct and non-overlapping geomorphological structure types were mapped by visually 

interpreting optical and acoustic imagery. Geomorphological structure refers to a feature’s dominant 

physical composition and does not address geographic location (e.g., in a Lagoon). Structure types 

are defined in a collapsible hierarchy ranging from three major classes (Coral Reef and Hardbottom, 

Unconsolidated Sediment, and Other Delineations), to thirteen detailed classes (Aggregate Reef, 

Aggregated Patch Reefs, Individual Patch Reef, Pavement, Pavement with Sand Channels, Rock/ 

Boulder, Spur and Groove, Mud, Sand, Sand with Scattered Coral and Rock, Artifi cial, Land and 

Unknown). Habitats or features with areas smaller than the MMU or minimum mapping unit (1,000 

m2

) were not considered. 

18 
Baseline Assessment of Jobos Bay, Puerto Rico: Benthic Habitat Mapping 

Coral Reef and Hardbottom 

Coral reef and Hardbottom habitats are areas on the seafloor with solid substrates, including bedrock, 

boulders and/or the deposition of calcium carbonate by reef building organisms. Substrates typically 

have no sediment cover, but a thin veneer of sand or mud may be present at times. Detailed structure 

classes include Aggregate Reef, Aggregated Patch Reefs, Individual Patch Reef, Pavement, 

Pavement with Sand Channels, Rock/Boulder, Spur and Groove, Mud, Sand, Sand with Scattered 

Coral and Rock, Artificial and Land.
 

Aggregate Reef
 

Continuous, high-relief coral formation of variable shapes lacking sand channels of Spur and Groove. 

Includes linear coral formations that are oriented parallel to the shelf edge (Figure 2.15). 

2 - Benthic Habitat Mapping

Figure 2.15. The red polygons (left) outline examples of the detailed structure type, Aggregate Reef, near Punta Colchones. The 

underwater photograph (right) depicts an example of aggregate reef in Jobos Bay. Photo: NOAA CCMA. 

Aggregated Patch Reefs 

Aggregated Patch Reefs have the same defining characteristics as an Individual Patch Reef. However, 

this class refers to clustered patch reefs that cover ≥10% of the entire polygon, but are too small (less 

than the MMU) or are too close together to map individually. Where aggregated patch reefs share 

sand halos, the halo is included in the polygon (Figure 2.16). If the density of small or aggregated 

coral heads is <10% of the entire polygon, this structure type is described as Sand with Scattered 

Coral and Rock. 

Figure 2.16. The red polygon (left) outlines an example of the detailed structure type, Aggregated Patch Reefs, near Boca del Infierno. 

The underwater photograph (right) depicts an example of aggregated patch reefs in Jobos Bay. Photo: NOAA CCMA. 

19 
Baseline Assessment of Jobos Bay, Puerto Rico: Benthic Habitat Mapping

20 2 - Benthic Habitat Mapping

Individual Patch Reef

Individual patch reefs are coral formations that are isolated from other coral reef formations by bare 

sand, seagrass or other habitats and that have no organized structural axis relative to the contours 

of the shelf edge. They are characterized by a roughly circular or oblong shape with a vertical relief 

of one meter or more in relation to the surrounding seafl oor (Figure 2.17). Individual Patch Reefs are 

larger than or equal to the MMU.

Figure 2.17. The red polygons (left) outline examples of the detailed structure type, Individual Patch Reef, near Cayos de Pájaros. The 

underwater photograph (right) depicts an example of an individual patch reef in Jobos Bay. Photo: NOAA CCMA.

0 50 100

m

Pavement

Flat, low-relief or sloping solid carbonate rock with little or no fi ne-scale rugosity that is covered 

with algae, hard coral, gorgonians, zoanthids or other sessile vertebrates that are dense enough to 

partially obscure the underlying surface. On less colonized Pavement features, rock may be covered 

by a thin sand veneer or turf algae (Figure 2.18).

Figure 2.18. The red polygon (left) outlines an example of the detailed structure type, Pavement, near Cayo Morrillo. The underwater 

photograph (right) depicts an example of pavement habitat in Jobos Bay. Photo: NOAA CCMA.
Pavement with Sand Channels 

Pavement with Sand Channels have the same defining characteristics as Pavement, in addition 

to having periodic sand/surge channels oriented perpendicular to the Bank/Shelf Escarpment. The 

sand/surge channels of this feature have low vertical relief and are typically erosional in origin. This 

habitat type occurs in areas exposed to moderate wave surge such as the Bank/Shelf zone (Figure 

2.19). 

Figure 2.19. The red polygon (left) outlines an example of the detailed structure type, Pavement with Sand Channels, near Cayos de

Pájaros. The underwater photograph (right) depicts an example of pavement with sand channels habitat in Jobos Bay. Photo: NOAA

CCMA. 

Baseline Assessment of Jobos Bay, Puerto Rico: Benthic Habitat Mapping 

2 - Benthic Habitat Mapping 21 

Rock/Boulder 

Aggregation of solid carbonate blocks extending offshore from the island bedrock or loose carbonate 

fragments that have been detached and transported from their native beds (Figure 2.20). Individual 

boulders range in diameter from 0.25-3 m as defined by the Wentworth scale (Wentworth, 1922). 

Figure 2.20. The red polygon (left) outlines an example of the detailed structure type, Rock/Boulder, east of Punta Pozuelo. The 

underwater photograph (right) depicts an example of rock/boulder habitat in Jobos Bay. Photo: NOAA CCMA. 

0 50 100 

m 
Baseline Assessment of Jobos Bay, Puerto Rico: Benthic Habitat Mapping 

22 2 - Benthic Habitat Mapping

Spur and Groove 

Structure having alternating sand and coral formations that are oriented perpendicular to the shore or 

reef crest. The coral formations (spurs) of this feature typically have a high vertical relief (approximately 

1 m or more) relative to pavement with sand channels and are separated from each other by 1-5 m of 

sand or hardbottom (grooves), although the height and width of these elements may vary considerably 

(Figure 2.21). This habitat type typically occurs in the Fore Reef or Bank/Shelf Escarpment zone. 

Figure 2.21. The red polygon (left) outlines an example of the detailed structure type, Spur and Groove, on the western side of Cayos

de Barca. The underwater photograph (right) depicts an example of spur and groove habitat in Jobos Bay. Photo: NOAA CCMA. 

Unconsolidated Sediment 

Areas on the seafloor consisting of small particles (<0.25 m) with less than 50% cover of large stable 

substrate. Detailed structure classes include: Mud, Sand and Scattered Coral and Rock. 

Mud 

Fine sediment often associated with river discharge and build-up of organic material in areas 

sheltered from high-energy waves and currents (Figure 2.22). Particle sizes range from <1/256-1/16 

mm (Wentworth, 1922). 

0 100

m

Figure 2.22. The red polygons (left) outline examples of the detailed structure type, Mud, west of Punta Pozuelo. The photograph (right)

was taken in the same area on the ground. Photo: NOAA CCMA. 
Baseline Assessment of Jobos Bay, Puerto Rico: Benthic Habitat Mapping 

Sand 

Coarse sediment typically found in areas exposed to currents or wave energy (Figure 2.23). Particle 

sizes range from 1/16–256 mm, including pebbles and cobbles (Wentworth, 1922). 

Figure 2.23. The red polygons (left) outline examples of the detailed structure type, Sand, southeast of Las Mareas. The underwater 

photograph (right) depicts an example of sand habitat in Jobos Bay. Photo: NOAA CCMA. 

2 - Benthic Habitat Mapping

Sand with Scattered Coral and Rock 

Areas where ≥10% of the entire polygon is covered by sand and <10% of the entire polygon is covered 

by scattered rocks or small, isolated coral heads that are too small to be delineated individually 

(Figure 2.24). If the density of small coral heads is ≥10% of the entire polygon, this structure type is 

described as Aggregated Patch Reefs. 

Figure 2.24. The red polygon (left) outlines an example of the detailed structure type, Sand with Scattered Coral and Rock, southeast 

of Las Mareas. The underwater photograph (right) was taken at this same location. Photo: NOAA CCMA. 

Other Delineations
 

Any other type of structure not classifi ed as Coral Reef and Hardbottom or Unconsolidated Sediment. 

Usually related to the terrestrial environment and/or anthropogenic activity. Detailed structure classes 

include Land and Artificial.
 

Artificial 

Man-made habitats such as submerged wrecks, large piers, submerged portions of rip-rap jetties, 

and the shoreline of islands created from dredge spoil (Figure 2.25). 

23 
Baseline Assessment of Jobos Bay, Puerto Rico: Benthic Habitat Mapping 

2 - Benthic Habitat Mapping

Figure 2.25. The red polygon (left) outlines an example of the detailed structure type, Artificial, near Central Aguirre. The photograph 

(right) was taken at this same location. Photo: NOAA CCMA. 

Land 

Terrestrial features at or above the spring high tide line (Figure 2.26). 

Figure 2.26. The red polygon (left) outlines an example of the detailed structure type, Land, near Punta Pozuelo. The photograph

(right) taken looking westward towards Central Aguirre. Photo: NOAA CCMA. 

Unknown 

Major and/or detailed structure that is indistinguishable in the optical imagery due to water depth, 

turbidity, cloud cover, wave action, sun glint or other interference with the optical signature of the 

seafloor; it also maybe indistinguishable in the acoustic imagery due to noise in the bathymetry and/ 

or backscatter or other interference with the acoustic signature of the seafloor (Figure 2.27). 

24 
Baseline Assessment of Jobos Bay, Puerto Rico: Benthic Habitat Mapping 

2 - Benthic Habitat Mapping

Figure 2.27. The red polygons (left) outline examples of an unknown detailed structure types due to turbidity in the optical imagery. The 

red polygon (right) outlines an example of an unknown detailed structure type due to noise in the acoustic imagery. 

2.2.4. Biological Cover Classes 

Twelve unique (i.e., major plus detailed) biological cover classes were mapped by visually interpreting 

optical and acoustic remotely sensed 

imagery. Biological cover denotes 

the dominant biological component 

colonizing the surface of the feature. 

It does not describe the location (e.g., 

on the Bank/Shelf or in a Lagoon) or 

structure (e.g., Sand) of the feature. 

Habitat features smaller than the 

MMU were not considered. Six major 

cover types were identified from the 

optical and acoustic imagery (i.e., 

Algae, Seagrass, Mangrove, No 

Cover, Unclassified and Unknown) 

and combined with three modifiers 

describing the distribution of the 

dominant cover within the polygon 

(i.e.,10%≤50%, 50%≤90%,and90%­

100%). It is important to note that 

this modifier represents a measure 

of patchiness of the biological cover 

at the scale of delineation. It does 

not denote the density of organisms 

observed by divers in the water. For 

example, a seagrass bed can be 

described as covering 90%-100% 

of a given polygon, but may have 

sparse densities of shoots when 

observed by divers. Figure 2.28 

illustrates how patchiness was used 

to assign a biological percent cover. Figure 2.28. This chart outlines the process used to visually estimate patchiness

when assigning a percent biological cover value to a polygon. Note that the 18 large

squares are the size of a minimum mapping unit (MMU). 

Relative Patch 

Aggregation Less More

90-100% 

Continuous 

70-<90% 

Patchy 

50-<70% 

Patchy 

30-<50% 

Patchy 

10-<30% 

Patchy 

0-<10% 

No Cover 

Percent Cover 

Category 

25 
Baseline Assessment of Jobos Bay, Puerto Rico: Benthic Habitat Mapping 

2 - Benthic Habitat Mapping

Major Cover 

Algae 

Substrates with 10% or greater distribution of any combination of numerous species of red, green, 

or brown algae. May be turf, fl eshy, filamentous species. Occurs throughout many zones, especially 

on hard bottoms with low coral densities and soft bottoms in deeper waters on the Bank/Shelf zone 

(Figure 2.29). 

Figure 2.29. The red polygon in the map (left) and red polygon in the map (center) depict examples of the biological cover type, Algae, 

as seen in the optical and acoustic images, respectively. The underwater photograph (right) depicts an example of algal habitat in 

Jobos Bay. Photo: NOAA CCMA. 

Mangrove 

This habitat is comprised of semi-permanently, seasonally or tidally flooded coastal areas occupied 

by any species of mangrove (Figure 2.30). Mangrove trees are halophytes; plants that thrive in 

and are especially adapted to salty conditions. In the U.S. Caribbean, there are three species of 

mangrove trees: red mangrove (Rhizophora mangle), black mangrove (Avicennia germinans), and 

white mangrove (Laguncularia racemosa); another tree, buttonwood (Conocarpus erectus) is often 

associated with the mangrove formation. Red mangrove grows at the water’s edge and in the tidal 

zone. Black mangrove and white mangrove grow further inland in areas where flooding occurs only 

during the highest tides. This habitat type is usually found in the Shoreline Intertidal zone. 

Figure 2.30. The red polygons outline examples of the biological cover type, Mangroves. The photographs (center and right) depict

examples of mangrove habitat in Jobos Bay. Photo: NOAA CCMA. 

26 
Baseline Assessment of Jobos Bay, Puerto Rico: Benthic Habitat Mapping 

No Cover 

Substrates not covered with a minimum of 10% of any of the other biological cover types. This habitat 

is usually associated with Mud or Sand. Overall, No Cover is estimated at 90%-100% of the bottom 

with the possibility of some very low density biological cover (Figure 2.31). 

Figure 2.31. The red polygon in the map (left) and red polygon in the map (center) depict examples of the biological cover type, No 

Cover, as seen in the optical and acoustic images, respectively. The underwater photograph (right) depicts an example of habitats 

colonized by little or no biological organisms in Jobos Bay. Photo: NOAA CCMA. 

2 - Benthic Habitat Mapping

Seagrass 

Habitat dominated by any single species of seagrass (e.g., Syringodium sp., Thalassia sp., Halophila 

sp.) or a combination of several species (Figure 2.32). 

Figure 2.32. The red polygon in the map (left) and red polygon in the map (center) depict examples of the biological cover type, 

Seagrass, as seen in the optical and acoustic images, respectively. The underwater photograph (right) depicts an example of seagrass 

habitats in Jobos Bay. Photo: NOAA CCMA. 

Unclassified 

A different biological cover type, such as upland, deciduous forest, that is not included in this habitat 

classification scheme dominates the area. Most often used on polygons defined as Land with terrestrial 

vegetation. 

Unknown 

Biological cover that is indistinguishable in the optical imagery due to water depth, turbidity, cloud 

cover, wave action, sun glint or other interference with the optical signature of the seafloor; it also 

may be indistinguishable in the acoustic imagery due to noise in the bathymetry and/or backscatter 

or other interference with the acoustic signature of the seafl oor. 

27 
Baseline Assessment of Jobos Bay, Puerto Rico: Benthic Habitat Mapping 

2 - Benthic Habitat Mapping

Percent Major Cover 

10% ≤ 50% 

Discontinuous cover of the major biological type with breaks in coverage that are too diffuse to 

delineate or result in isolated patches of a different dominant biological cover that are too small to be 

mapped as a different feature (i.e., smaller than the MMU). Overall cover of the major biological type 

is estimated at 10%≤50% of the polygon feature (Figure 2.33). 

50% ≤ 90% 

Discontinuous cover of the major biological type with breaks in coverage that are too diffuse to 

delineate or result in isolated patches of a different dominant biological cover that are too small to be 

mapped as a different feature (i.e., smaller than the MMU). Overall cover of the major biological type 

is estimated at 50%≤90% of the polygon feature (Figure 2.33). 

90% - 100% 

Major biological cover type covering 90% or greater of the substrate. May include areas of less than 

90% major cover on 10% or less of the total area that are too small to be mapped independently (i.e., 

smaller than the MMU; Figure 2.33). 

Figure 2.33. The symbolized polygons in the maps (right, center and left) have 10%≤50%, 50%≤90% and 90%-100% of their area 

covered by seagrass, respectively. 

Not Applicable (N/A)
 

An estimate of percent cover is not appropriate for this particular major biological cover class (e.g., for 

Land polygons). Regularly accompanies the use of Unclassified as the major biological cover.
 

Unknown 

Percent estimate of the biological cover that is indistinguishable in the optical imagery due to water 

depth, turbidity, cloud cover, wave action, sun glint or other interference with the optical signature of 

the seafloor; it also maybe indistinguishable in the acoustic imagery due to noise in the bathymetry 

and/or backscatter or other interference with the acoustic signature of the seafl oor. 

2.2.5. Live Coral Cover Classes 

Four distinct and non-overlapping percent live coral classes were mapped by visually interpreting 

optical and acoustic remotely sensed imagery. This attribute is an additional biological cover modifier 

denoting the abundance live coral (both scleractinian and octocorals; Figure 2.34), even when it was 

not the dominant cover type within a polygon. In order to provide resource managers with additional 

information about corals, four range classes were used (i.e., 0%≤10%, 10%≤50%, 50%≤90%, and 

90%-100%). Habitat features are classified into these range classes based on the amount of combined 

scleractinian and octocoral present in a polygon. Scleractinian coral and octocorals were combined 

because they could not be reliable separated in the remotely sensed imagery. 

28 
Baseline Assessment of Jobos Bay, Puerto Rico: Benthic Habitat Mapping 

Figure 2.34. Both scleractinian and octocorals are included when estimating live coral cover. Typical corals of Jobos Bay include the 

scleractinian symmetrical brain coral (Diploria strigosa; left) and several octocorals including sea plumes (Gorgoniidae; right). Photos:

NOAA CCMA. 

Live coral cover describes the percent coral cover on hardbottom features at a fine spatial scale (i.e., 

diver scale). It is important to note that this metric is different from percent biological cover, which 

denotes the patchiness of biological organisms at the scale of the habitat feature. Due to these 

varying scales of interpretation, the percent biological cover and percent live coral cover modifi ers are 

not additive, and in many cases, they will sum to greater than 100%. For instance, an aggregate reef 

can have continuous (90%-100%) cover of algae at the polygon scale, as well as 10%-50% density 

of coral at the diver scale. 

0% ≤10% 

Live coral cover of less than 10% of hardbottom substrate at a scale several meters above the 

seafloor (Figure 2.35a). 

10% ≤50% 

Live coral cover between 10% and 50% of hard bottom substrate at a scale several meters above 

the seafloor (Figure 2.35b). 

50% ≤90% 

Live coral cover between 50% and 90% of hard bottom substrate at a scale several meters above 

the seafloor. No Figure is provided because this class was not present in the area that was mapped 

in Jobos Bay. 

2 - Benthic Habitat Mapping

a) b) 

Figure 2.35. (a) An example of the presence of live coral in the 0%≤10% cover range; and (b) an example of the presence of live coral

in the 10%≤50% cover range. Photos: NOAA CCMA. 

29 
Baseline Assessment of Jobos Bay, Puerto Rico: Benthic Habitat Mapping 

2 - Benthic Habitat Mapping

90% - 100% 

Continuous live coral consisting of 90% or greater cover of the hard bottom substrate at a scale 

several meters above the seafloor. No Figure is provided because this class was not present in the 

area that was mapped in Jobos Bay. 

Unknown 

Percent estimate of coral cover that is indistinguishable in the optical imagery due to water depth, 

turbidity, cloud cover, wave action, sun glint or other interference with the optical signature of the 

seafloor; it also maybe indistinguishable in the acoustic imagery due to noise in the bathymetry and/ 

or backscatter or other interference with the acoustic signature of the seafl oor. 

2.3. BENTHIC HABITAT CREATION 

Benthic habitats of the near-shore marine environment of Jobos Bay, Puerto Rico were created by 

delineating and classifying habitat features visible in optical and acoustic remotely sensed imagery. 

Optical and acoustic imagery have both been successfully used to derive the location, extent and 

attributes of marine habitats (Kendall et al., 2001, 2005; Kostylev et al., 2001; Battista et al., 2007a,b; 

Prada et al., 2008; Bauer et al., 2010). NOAA scientists were able to accurately and reliably delineate 

the boundaries of features in the imagery using Geographic Information System (GIS) software. Field 

investigations were conducted in order to link signatures in the imagery with habitat features on the 

seafloor. This process provides natural resource managers and researchers with spatially accurate 

maps of seafloor features and their associated ecological characteristics. 

2.3.1 General Mapping Approach 

NOAA’s approach to near-shore habitat mapping of estuarine and marine environments was a fivestep process: 

1. Imagery Acquisition – The first step in map creation was the acquisition and processing of 

high-resolution remotely sensed imagery. Optical imagery (i.e., aerial orthophotographs) and 

acoustic data were collected in order to map the full geographic extent of Jobos Bay. 

2. Habitat Boundary Delineation – A draft benthic habitat map was generated by manually 

delineating habitat features that were clearly visible in the optical and acoustic remotely sensed 

imagery. 

3. Ground Validation (GV) – Habitat features in the map with unknown optical or acoustic signatures 

were explored by NOAA scientists using underwater cameras. This information was analyzed 

and the initial maps were edited to generate a second draft map for Jobos Bay. 

4. Expert Review – The second draft map was reviewed online by local marine biologists, scientists 

and resource managers to qualitatively assess the maps thematic accuracy. 

5. Final Product Creation – A final benthic habitat map for Jobos Bay was generated by correcting 

inaccuracies identified during the expert review. 

2.4. REMOTELY SENSED IMAGERY 

Remotely sensed imagery is a valuable tool for natural resource managers and researchers because 

it provides a permanent record of the location and extent of seafloor habitats. Generally in clear, 

tropical waters, optical imagery can be used to identify, delineate and classify seafloor habitat features 

from the shoreline to water depths of approximately 30 m. However, consistently poor water clarity 

inhibited the delineation and classification of habitat features from optical imagery for some areas in 

30 
Baseline Assessment of Jobos Bay, Puerto Rico: Benthic Habitat Mapping 

Jobos Bay. Acoustic imagery was collected in these turbid areas to supplement the aerial photographs 

and provide source imagery from which to delineate and classify benthic habitats. Descriptions of the 

optical and acoustic source images are provided in the proceeding text. 

2.4.1. Acquisition and Processing of the Optical Imagery 

High resolution optical imagery provides precise and robust data with spectral and spatial resolutions 

suitable for shallow water benthic mapping. In order to map the benthic habitats of JBNERR, sixteen 

aerial orthophotographs were obtained from the U.S. Army Corps of Engineers (USACE) covering 

the Jobos Bay region (Figure 2.36). These 16 aerial photographs were mosaiced together to produce 

one seamless orthophoto image. An orthophoto is a remotely sensed, optical image in which the 

horizontal displacement of features in the image has been mathematically removed. The USACE 

collected these 16 natural color orthophotos using an ADS40 digital sensor on November 26 and 

27, 2006. This collection was part of a larger effort to map the islands of Puerto Rico, Culebra and 

Vieques, and St. Thomas, St. John and St. Croix in the U.S. Virgin Islands (USVI) from November 

2006 through March 2007. During this acquisition, aerial photographs were acquired at an altitude 

of 8,650 feet above ground level (AGL) with 30% sidelap between all adjacent fl ight lines. The 

ADS40 digital sensor captured the imagery at a 0.3x0.3 m spatial resolution and 12-bit (4,096 colors) 

radiometric resolution. This radiometric resolution was reduced to 8-bits (256 colors) during post 

processing in order to more effectively color balance the different images. The horizontal accuracy of 

these orthophotos was determined by using a GPS to measure in situ the position of distinct features 

in the imagery, and to compute a root mean square error (RMSE). In addition to ground control points, 

sample points were taken from overlapping areas of adjacent image strips to ensure that the location 

of adjacent images matched. All of the orthophotos were referenced to the State Plane Puerto Rico / 

US Virgin Islands (Zone 5200), North American Datum (NAD) 83, Geodetic Reference System (GRS) 

80, Units Meters horizontal coordinate system. 

2 - Benthic Habitat Mapping

Figure 2.36. In order to map JBNERR, sixteen aerial orthophotographs were obtained from the U.S. Army Corps of Engineers (USACE) 

covering the Jobos Bay region. These 16 aerial photographs were mosaiced together to produce one seamless orthophoto image. 

31 
Baseline Assessment of Jobos Bay, Puerto Rico: Benthic Habitat Mapping 

2 - Benthic Habitat Mapping

2.4.2. Acquisition of the Acoustic Imagery 

Benthic habitats in shallow (≤30 m), perpetually turbid marine environments are challenging to 

characterize because conventional mapping technologies (e.g., satellite imagery, light detection and 

ranging and multibeam echosounders) are either unable to, or inefficient for, comprehensively mapping 

these areas. The use of interferometric sonars, also called phase differencing bathymetric sonars 

(PDBS), may fill this informational gap where conditions are not ideal for the operation of other sensors. 

Like other sonars, PDBS actively emit pulses of sound and record the return to gather co-located 

bathymetric and intensity information 

about the seafloor (Figure 2.37). 

Unlike other sonars, however, PDBS 

collect these spatially coincident 

datasets over wide swaths in 

shallow-waters, up to 12 times the 

depth versus 3 to 5 times the depth 

for multibeam echosounder systems 

(Gostnell, 2005). PDBS are able to 

collect wide swaths in shallow-waters 

because they are not beam forming 

but rather, they accurately measure 

depths by precisely measuring the 

phase offsets of acoustic returns 

(Denbigh, 1989; Gostnell, 2005). In 

addition to calculating depth, PDBS 

systems also collect information 

about the intensity of the returns. 

These individual measurements 

are used to create images of the 

seafloor, describing its hardness 

and roughness. The resulting 

acoustic images (i.e., bathymetry 

and intensity) are valuable tools 

for natural resource managers and 

researchers because they provide 

baseline information on the location 

and extent of seafloor habitats in 

turbid waters and in deep waters 

beyond the limits of optical imagery 

(i.e., approximately 30 m). 

A PDBS system, called the Teledyne 

Benthos C3D (200 kHz) Lightweight 

Pole Mount (LPM; Figure 2.38), was 

used to acquire acoustic imagery in 

the Jobos Bay region. Bathymetric 

and intensity data were collected 

aboard the JBNERR’s research 

vessel (R/V) Jurel from 4/7/2009 

to 4/21/2009. The bathymetric and 

intensity datasets were logged in 

.hsx format using Hypack 2009

Figure 2.37. Diagram illustrating the collection of acoustic data using an interferometric

sonar (phase differencing bathymetric sonars or PDBS). This acoustic dataset was

integrated with underwater photographs and video to habitat mapping to create a

benthic habitat map for persistently turbid areas in Jobos Bay. 

Figure 2.38. The Teledyne Benthos C3D (200 kHz) LPM PDBS was pole-mounted 

on the R/V Jurel. This system was used to collect bathymetry and intensity imagery

in Jobos Bay. Photo: NOAA CCMA. 

32 
Baseline Assessment of Jobos Bay, Puerto Rico: Benthic Habitat Mapping 

software. Line spacing provided a bathymetry surface with 100% bottom coverage and an intensity 

surface with 200% bottom coverage. Heave, roll, pitch and heading correctors were collected using 

an Ixsea Octans gyrocompass and integrated motion sensor. Sound velocity profiles were acquired 

with a hand held conductivity, temperature and depth (CTD) profiler. Horizontal and vertical positions 

were obtained using a Trimble DSM 232 GPS receiver. Soundings were referenced to the NAD of 

1983, Universal Transverse Mercator 19 North (NAD83 UTM 19N) horizontal coordinate system. 

Sounding depths were left in NAD83 ellipsoidal heights. 

2.4.3. Processing of the Acoustic Imagery 

Bathymetry 

The .hsx lines were imported into CARIS Hydrographic Image Processing System (HIPS) & Sidescan 

Image Processing System (SIPS) v7.0. After being imported, sound velocity profiles (taken every four 

hours of the full water column) were used to correct the speed of sound in the converted lines based 

on previous in time. Zero tides were applied to the Hydrographic Data Cleaning System (HDCS) 

data, leaving the bathymetry surface referenced to NAD83 ellipsoid heights. The HDCS lines were 

subsequently merged, and TPU (total propagated uncertainty) was calculated. A Bathymetry with 

Associated Statistical Error (BASE) surface was then created at a 4x4 m spatial resolution using 

Combined Uncertainty and Bathymetry Estimator (CUBE) with the following parameters: (1) IHO 

S-44 Special Order specifications (2) density & locale disambiguation method and (3) 0 - 100 m 

depth fi lter. Additional fliers were manually rejected in subset editor. Existing data holidays were filled 

by interpolation, using the following parameters: 1 iteration, matrix size of 5, 10 neighbors. The final, 

interpolated 4x4 m bathymetry surface exported from CARIS and converted to a GeoTIFF in ArcMap 

(Figure 2.39). 

2 - Benthic Habitat Mapping

Figure 2.39. Acoustic information was collected in persistently turbid areas in Jobos Bay to support habitat mapping. This Figure shows 

the bathymetry surface (i.e., depths) collected by the C3D PDBS. 

33 
Baseline Assessment of Jobos Bay, Puerto Rico: Benthic Habitat Mapping 

2 - Benthic Habitat Mapping

Intensity 

An intensity surface was created using Hypack 2009 Geocoder module (Fonseca and Calder, 2005). 

In order to do so, the same .hsx files were imported into Geocoder. They were then geometrically 

corrected for navigation attitude, transducer attitude and local seafloor slope using the fi nal bathymetric 

surface exported from CARIS. They were also radiometrically corrected for changes in acquisition 

gains, power levels, pulse widths, incidence angles and ensonification areas. Visual artifacts (e.g., 

noisy lines, dark or light striping, etc.) were manually removed. All other soundings were preserved 

during these corrections and edits, allowing the full resolution data to be used to create the final 

mosaic. The final 1x1 m intensity surface was exported from Geocoder as an 8-bit (0-255 value) 

GeoTIFF (Figure 2.40). 

Figure 2.40. This Figure shows the intensity surface collected by the C3D PDBS. 

Creating Derivative Surfaces 

A suite of eight metrics were derived from the final bathymetry surface, in order to characterize the 

complexity and structure of the seafloor. These metrics specifically included: (1) mean depth, (2) 

standard deviation of depth, (3) curvature, (4) plan curvature, (5) profile curvature, (6) rugosity, (7) 

slope, and (8) slope of slope. Each of these metrics had a spatial resolution of 4x4 m. They were 

calculated using a square 3x3 cell neighborhood, where the pixel in the middle of the neighborhood 

was assigned the calculated value. These metrics are described in more detail in Table 2.2. 

34 
Baseline Assessment of Jobos Bay, Puerto Rico: Benthic Habitat Mapping

35 2 - Benthic Habitat Mapping

Table 2.2. Descriptions of the morphometrics used to characterize the complexity of the seafl oor in and around JBNERR. The GIS tools 

used to derive these metrics from the PDBS bathymetry surface are also included in the table.

Dataset Unit Description Formula Tool

-2(D + E) * 100 Rate of change in 

curvature across the 1/100 z units Where: Curvature function surface highlighting Curvature – = concave D is [(Z4 + Z6)/2 - in ArcGIS 3D ridges, crests and + = convex Z5]/ L2 Analyst valleys (3 x 3 cell E is [(Z2 + Z8)/2 - neighborhood) Z5]/ L2

-2(D + E) * 100

Curvature of 

1/100 z units the surface Where: Plan curvature Plan – = concave perpendicular to the D is [(Z4 + Z6)/2 - function in ArcGIS Curvature + = convex slope direction (3 x 3 Z5]/ L2 3D Analyst

cell neighborhood) E is [(Z2 + Z8)/2 - 

Z5]/ L2

-2(D + E) * 100

Curvature of the 1/100 z units Where: Profi le curvature Profi le surface in the 

– = convex D is [(Z4 + Z6)/2 - function in ArcGIS Curvature direction (3 x 3 cell + = concave Z5]/ L2 3D Analyst neighborhood) E is [(Z2 + Z8)/2 - 

Z5]/ L2

Average water Focal statistic in Depth Meters depth (3 x 3 cell Σ depth / n grid cells ArcGIS Spatial (Mean) neighborhood) Analyst

Dispersion of water Depth Focal statistic in depth values about (Standard Meters σ = √VAR ArcGIS Spatial the mean (3 x 3 cell Deviation) Analyst neighborhood)

Ratio of surface area See Jenness (2002, Surface Benthic Terrain Ration value to planar area (3 x 3 2004) and Wright et Rugosity Mapper toolbox cell neighborhood) al. (2005)

Maximum rate of 

change in slope ArcGIS Spatial tan θ = rise / Slope Degrees between cell and 8 Analyst’s slope distance neighbors (3 x 3 cell function

neighborhood)

Maximum rate of 

maximum slope ArcGIS Spatial Slope of Degrees of change between tan θ′ = θ / Analyst’s slope the Slope degrees cell and eight distance function neighbors (3 x 3 cell 

neighborhood)
hese eight complexity surfaces

ere subsequently stacked, and

xported to create one image with 

everal different bands (each band 

epresenting a specifi c metric). This 

mage was then transformed into

ts’ first three principal components 

PCA; Pearson, 1901; Hotelling,

933; Figure 2.41) in ENVI 4.7.

his transformation reduced the

imensionality of the dataset by

emoving information that was

edundant among the different bands. 

he resulting three band PCA image 

nly contained information that

niquely described the complexity

and structure of the seafloor (Table 2.3). Each of these three bands were converted from 16-bit, 

floating point values to 8-bit, integer values, so that they could be imported into ArcMap 9.3 for visual 

analysis. The final PCA surface had a spatial resolution of 4x4 m. 

Table 2.3. The amount (%) of variance in a principal component that is explained 

by a single complexity surface. For example, the plan curvature surface contributed

11.11%, 2.32% and 40.67% of the information contained in the transformed image’s 

first, second and third principal components, respectively. 

PC number

1 2 3 

Bathymetry 11.11 25.04 10.51

Bathymetry (Mean) 11.11 24.60 12.09

Bathymetry (Stdev) 11.11 12.47 1.33

Curvature 11.11 2.40 29.47

Curvature (Plan) 11.11 2.32 40.67

Curvature (Profile) 11.11 0.02 1.03

Rugosity 11.11 4.29 0.03

Slope 11.11 13.22 1.89

Slope of Slope 11.11 15.63 2.97 

Figure 2.41. A suite of eight complexity metrics was derived from the bathymetry surface in order to characterize the complexity and 

structure of the seafl oor. This figure shows the first three principal components derived from these eight complexity metrics. 

Baseline Assessment of Jobos Bay, Puerto Rico: Benthic Habitat Mapping 

36 2 - Benthic Habitat Mapping

T

w

e

s

r

i

i

(

1

T

d

r

r

T

o

u

2.5. HABITAT FEATURE IDENTIFICATION AND DELINEATION 

2.5.1. Habitat Feature Identification 

In order to create a habitat map for Jobos Bay, habitat boundary identification, delineation and 

attribution techniques were adopted from Kendall et al. (2001) and Costa et al. (2009). In particular, 

habitat boundaries were delineated around distinct optical and acoustic signatures that correlated with 
Baseline Assessment of Jobos Bay, Puerto Rico: Benthic Habitat Mapping 

habitat types in the classifi cation scheme (described in Sections 2.2 to 2.5). These distinct signatures 

had unique colors, textures and shapes that distinguished them from the surrounding seafl oor. In 

places where the optical and acoustic imagery overlapped, habitat features were clearly visible in 

both imagery sources (Figure 2.42). Brightness, contrast and histogram stretching of the source 

imagery were often manipulated in ArcGIS to enhance the interpretability of some subtle features and 

boundaries. This was particularly helpful when using the optical imagery to identify habitats in deeper 

water where differences in color and texture between adjacent features were more subtle. Particular 

caution was used when interpretation was performed from stretched images, since results from color 

and brightness manipulations were sometimes misleading. Additional ancillary datasets were also 

consulted to improve the understanding of particular areas. These data types included previouslycompleted habitat maps (Kendall et al., 2001), bathymetry, nautical charts, and imagery from different 

time periods. 

2 - Benthic Habitat Mapping

Figure 2.42. These maps denote an example of sand habitat with different amounts of seagrass in the optical (left) and acoustic (right) 

imagery. Habitat features were identified by their distinct optical and/or acoustic signatures. These unique colors, intensities, textures

and/or shapes distinguished them from the surrounding seafl oor. 

2.5.2. Habitat Feature Delineation 

The Jobos Bay benthic habitat map was created in ArcMap 9.3 using the Habitat Digitizer Extension 

(Buja, 2008a). The Habitat Digitizer Extension is a GIS tool that allows a user to delineate and 

attribute polygon features from geo-referenced images. A custom classification scheme (described 

in Section 2.2) was imported and used to attribute polygons by visual interpretation. This allowed the 

cartographer to rapidly and dynamically delineate and classify habitat features on the fl y, significantly 

improving the efficiency with which habitat maps are developed. 

Using the Habitat Digitizer, habitat features were often delineated by first digitizing a large boundary 

polygon (such as the shoreline) and then appending new polygons to the initial boundary polygon. 

Another technique was to draw one large polygon around a homogenous feature and then split it into 

smaller polygons based on percent cover type. This approach was often used for seagrass beds of 

varying patchiness. Regardless of the digitizing approach, critical digitizing parameters were set in 

advance (using the Habitat Digitizer), in order to standardize the scale and size of feature delineation. 

These parameters specifically included: (1) the MMU, which was set to 1,000 m2, and (2) the digitizing 

scale, which was set to 1:2,000. Setting the MMU ensured a uniform minimum polygon size, whereas 

setting a uniform digitizing scale ensured a consistent level of habitat polygon boundary detail. The 

cartographer was allowed to zoom in and out to varying scales when assessing an area, but always 

returned to 1:2,000 before delineating a feature. 

37 
Baseline Assessment of Jobos Bay, Puerto Rico: Benthic Habitat Mapping 

2 - Benthic Habitat Mapping

2.6. HABITAT FEATURE ATTRIBUTION (GROUND VALIDATION) 

Extensive field work is needed to create high-quality benthic habitat maps because it enhances the 

accuracy of habitat attribution and (to a lesser degree) habitat delineation. A team of NOAA field 

scientists visited predetermined locations to explore and verify existing habitat information on the 

seafloor. These “ground validation” (GV) locations were targeted by the cartographer to satisfy the 

following objectives: 

1. Explore features in the imagery with unknown or confusing optical or acoustic signatures 

2. Confirm that the habitat type correlated with a particular optical or acoustic signature remained 

consistent throughout the entire study area 

To achieve this first objective, the cartographer placed GV points in features with unknown habitat 

types. These points were important for understanding the habitat class associated with these distinct 

but unknown remotely sensed signatures. To achieve the second objective, the cartographer placed 

GV points in habitat features with known habitat types distributed throughout the entire spatial extent 

of the mapped area. These points were important to the GV process because the same habitat type 

may exhibit slightly different signatures in different parts of the study area. A single habitat type may 

exhibit slightly different optical signatures because they occur at different depths (e.g., a polygon attributed as “Sand, No Cover 90-100%” at 5 m depth will look slightly different than one at 25 m depth). 

Similarly, a single habitat type may exhibit slightly different acoustic signatures because different 

polygons will contain varying amounts of structural and biological cover heterogeneity within them 

(e.g., polygons attributed as “Sand” contains varying amounts of sand, mud, algae and seagrass). 

Ground validation data were collected from May 13-17, 2009 at 168 sites in the Jobos Bay region 

(Figure 2.43) onboard the R/V Jurel provided by JBNERR. A combination of underwater video (155 

sites), surface observations (eight sites), free diving and snorkeling (five sites) were used to survey 

the ecological characteristics at each location (Figure 2.44). GV sites were navigated to using a hand38 

Figure 2.43. A combination of underwater video (155 sites), surface observations (eight sites), free diving and snorkeling (fi ve sites) 

were used to survey the ecological characteristics at each location. This information was analyzed (in concert with the optical and 

acoustic imagery) to classify each polygon in the habitat map. 
Baseline Assessment of Jobos Bay, Puerto Rico: Benthic Habitat Mapping 

held WAAS-enabled GPS unit. The 

vessel was maneuvered to within 

5 m of the target location. Once in 

position, NOAA scientists would 

concurrently deploy a SeaViewer 

Sea-Drop 950 camera (attached 

to a down weight and 300 feet of 

line), and begin logging a waypoint 

on a Trimble GeoXT GPS receiver. 

While on site, the vessel’s position 

was captured as an epic (i.e., point) 

approximately every 5-10 seconds 

depending on the number of 

satellites detected by the GPS antennae. The underwater video was recorded onto mini-video tapes 

using a video recorder. The camera operator adjusted the camera lens to get a downward view of the 

seafloor approximately 2 m from the bottom, and a side view of the seafloor. This allowed for accurate 

measurements of percent biological cover and a broader scale understanding of the structure at 

each site. No attempt was made to standardize the amount of time the camera was on the seafl oor. 

In fact, it was often advantageous to drift across habitat transitions, as it allowed the cartographer to 

understand the ecotone at many locations. 

While the camera was recording video of the seafloor, an observer viewed the video real-time on a 

laptop and classified the major/detailed geomorphological structure, major/detailed biological cover, 

and percent coral for each site. Waterproof field maps (depicting the draft habitat map and source 

imagery) were used to visually link signatures in the imagery with the in situ habitats seen in the video. 

In many cases, suggestions on boundary delineation and habitat classifications were made directly 

on the field maps with permanent marker. Once back in the offi ce, Trimble Pathfi nder Offi ce software 

was used to post process and differentially correct the raw GPS data to the CORS at Coamo, Puerto 

Rico (PRN4). The underwater video was converted from the mini-tapes to softcopy form using Final 

Cut Pro software. The classification of each GPS location (completed in the field) was then reviewed 

in conjunction with the associated underwater video and/or photos (as well as the optical and acoustic 

imagery) to develop a fi nal classified set of GV points (Figure 2.45). 

Figure 2.44. SeaViewer Sea-Drop 950 camera (left) was used in combination with

snorkeling, free diving and surface observations via a look bucket (right) to ground

truth 168 discrete seafloor locations. Photos: http://www.ub88.org/ (left), NOAA CCMA 

(right). 

2 - Benthic Habitat Mapping

Figure 2.45. The classification of each GPS location (completed in the field) was then reviewed in conjunction with the associated

underwater video and/or photos, as well as the optical and acoustic imagery, to develop a fi nal classified set of GV points. 

39 
Baseline Assessment of Jobos Bay, Puerto Rico: Benthic Habitat Mapping 

2 - Benthic Habitat Mapping

2.7. EXPERT REVIEW 

Before the Jobos Bay habitat map was considered final and ready for release, a panel of local experts 

reviewed the map online. In particular, local marine biologists, coral reef scientists and resource 

managers from a variety of organizations (including the U.S. Department of Agriculture [USDA], 

Forest Service, the U.S. Fish and Wildlife Service, NOAA, University of Puerto Rico and JBNERR) 

were invited to review the habitat map online from August 31 to September 7, 2010. Using an online 

web GIS interface (Buja, 2010), experts were asked to comment on the habitat classifi cation scheme, 

habitat boundary delineations and polygon attributes of the draft maps in order to improve the quality 

and accuracy of the final map products. The reviewers also commented on the utility of these maps 

for management and research purposes. Some suggestions were made to change the class type of 

individual polygons, based on their local knowledge of the seafloor. These comments were incorporated 

into the final map after the expert review had concluded. Additionally, two independent scientists within 

the BB reviewed the underwater video, source imagery and map product to qualitatively confi rm the 

classifications assigned to each habitat polygon. The final map was then reviewed for topological 

errors before being finalized. This process is described in the proceeding section. 

2.8. GIS QUALITY CONTROL 

All GIS deliverable products generated throughout the mapping process were examined for attribution 

and topological errors. Particular attention was given to polygon geometry and attribution of the 

benthic habitat map, as well as to the attribution of each GV point. Multipart, sliver and void polygons 

were all removed using standard ArcGIS Spatial Analyst tools. Two custom ArcGIS extensions were 

employed to identify the following conditions: 

1. Adjacency – polygons that shared a common boundary and exact attribute combination that 

were delineated separately (Buja, 2008b); 

2. Overlap – polygons sharing the same geographic space, thus violating mutual exclusion (Buja, 

2008c). 

Errors resulting from either of these GIS routines were corrected on draft maps and eliminated in the 

final product. A visual inspection of attributes on a feature-by-feature basis was conducted to correct 

for any misspellings or illogical attribute combinations. These quality assessments and controls 

ensured that the GIS data from this work were topologically clean and free of attribution errors. In 

addition, metadata summaries were prepared in a Federal Geographic Data Committee (FGDC) 

format for all GIS products that were supplied during fi nal delivery. 

2.9. CONCLUSIONS 

NOAA’s BB, with support from the USDA, NOAA’s Coral Reef Conservation Program (CRCP), NERRS 

and JBNERR, has completed a benthic habitat map for the estuarine and shallow-water marine 

environment in Jobos Bay, Puerto Rico. While no independent accuracy assessment was conducted 

for this habitat map, the final map was reviewed by local experts to qualitatively validate its spatial 

and thematic accuracy. Additionally, other habitat maps created using the same mapping protocol 

reported overall thematic accuracies of greater than 88% for major geomorphological structure and 

cover classes, and greater than 70% for detailed geomorphological structure and biological cover 

classes (Battista et al., 2007a,b; Zitello et al., 2009; Bauer et al., 2010). As a result, these digital 

map products can be used with confidence by scientists and resource managers for a multitude of 

different applications. The scientific and management communities have used previous NOAA benthic 

habitat maps to structure monitoring programs, support management decisions, and establish and 

40 
 

Baseline Assessment of Jobos Bay, Puerto Rico: Benthic Habitat Mapping 

manage marine conservation areas. Table 2.4. Final deliverables for NOAA’s habitat map of Jobos Bay, Puerto Rico. 

The final deliverables for this 

project are available to the public by 

request. Brief descriptions of these 

deliverables are listed in Table 2.4. 

2.9.1. Map Summary Statistics 

In total, 35.7 km2 of the seafl oor and 

14.1 km2 of the intertidal shoreline in 

and around JBNERR were mapped. 

The entire 8.3 km2

 area inside the 

JBNERR boundaries was mapped 

to the detailed structure level. 

Figures 2.46 through 2.50, depict 

the geographic zone, detailed structure, percent hardbottom, detailed biological cover and coral 

cover of the area mapped in Jobos Bay. Several patterns emerged when examining the summary 

map statistics for the total mapped area, as well as the mapped area inside and outside the Reserve 

boundaries (Figures 2.51-5.56). In particular, Shoreline Intertidal constituted 65% of the area inside 

JBNERR (excluding land), whereas only about 21% of the area outside JBNERR and 28% of the total 

area was classifi ed as Shoreline Intertidal. Unconsolidated Sediment, specifically Mud, constituted 

the majority of the total mapped area, as well as the majority of the mapped areas inside and outside 

the JBNERR boundaries. After Mud, Sand was the second most dominant detailed structure type for 

all three areas. Individual Patch Reefs, Aggregated Patch Reefs and Aggregate Reef comprised 3.1% 

of the total mapped area, 3.5% of the mapped area outside the JBNERR, and 0.1% of the mapped 

area inside the JBNERR. The 0.02 km2

 of Artificial detailed structure type denotes the presence of 

several industrial piers outside of the JBNERR boundaries.” 

Although the majority of these three mapped areas had the same structure type, they were dominated 

by different biological covers. In particular, approximately 41% of the area inside JBNERR was 

colonized by mangroves, with 90% - 100% being the most common of the three density classes. Of 

the remaining 59% of the Reserve, 18% was colonized by seagrass, 5% by algae, 4% was land and 

32% was uncolonized by biological organisms. The habitat distributions were slightly different outside 

the JBNERR boundaries. In particular, about 33% of the of the area (excluding land) outside JBNERR 

boundaries was dominated by seagrass with 50%≤90% being the most common of the three density 

classes. Substrates with little or no biological cover and substrates with algae were also prevalent 

outside the Reserve. Mangroves constituted about 21% of the mapped area outside JBNERR. In 

terms of coral cover, the majority (>94%) of the areas inside and outside JBNERR were colonized by 

0%≤10% live scleractinian and/or soft corals. It is important to note, however, that the mapped area 

outside the JBNERR had 2.46 km2 of seafl oor with 10%≤50% live coral. 

Item 

Benthic Habitat Map 

Format 

GIS 

Quantity 

1 

Habitat Symbology Layers GIS 5 

Optical Data (Images) GIS 17 

Acoustic Data (Images) GIS 11 

Ground Validation Dataset GIS 2 

Photos of Seafloor .jpeg 155 

Video of Seafloor .mov 149 

FGDC-compliant Metadata for GIS Files Text 31 

Online Interactive Map Project Online 1 

Final Report PDF 1 

41 2 - Benthic Habitat Mapping 
Baseline Assessment of Jobos Bay, Puerto Rico: Benthic Habitat Mapping 

2 - Benthic Habitat Mapping 

Figure 2.46. Map of geographic zone types in Jobos Bay, Puerto Rico. 

42 
Baseline Assessment of Jobos Bay, Puerto Rico: Benthic Habitat Mapping Figure 2.47. Map of geomorphological structure types in Jobos Bay. 

2 - Benthic Habitat Mapping 43 
Baseline Assessment of Jobos Bay, Puerto Rico: Benthic Habitat Mapping 

2 - Benthic Habitat Mapping 

Figure 2.48. Map of percent Hardbottom class types in Jobos Bay. 

44 
Baseline Assessment of Jobos Bay, Puerto Rico: Benthic Habitat Mapping Figure 2.49. Map of major and detailed biological cover types in Jobos Bay. 

2 - Benthic Habitat Mapping 45 
Baseline Assessment of Jobos Bay, Puerto Rico: Benthic Habitat Mapping 

2 - Benthic Habitat Mapping 

Figure 2.50. Map of percent live coral cover types in Jobos Bay. 

46 
Baseline Assessment of Jobos Bay, Puerto Rico: Benthic Habitat Mapping 

2 - Benthic Habitat Mapping 

Figure 2.51. Summary statistics describing the total amount of mapped area by

geographic zone types. These numbers are further divided into the amount of

mapped area inside and outside the JBNERR. 

Figure 2.52. Summary statistics describing the total amount of mapped area by major and detailed structure types. These numbers are 

further divided into the amount of mapped area inside and outside the JBNERR. 

47 
Baseline Assessment of Jobos Bay, Puerto Rico: Benthic Habitat Mapping 

2 - Benthic Habitat Mapping

Figure 2.53. Summary statistics describing the total amount of mapped area by percent

hardbottom class types. These numbers are further divided into the amount of mapped area

inside and outside the JBNERR. 

48 

Figure 2.54. Summary statistics describing the total amount of mapped area by major

biological cover types. These numbers are further divided into the amount of mapped area

inside and outside the JBNERR. 
Baseline Assessment of Jobos Bay, Puerto Rico: Benthic Habitat Mapping 

2 - Benthic Habitat Mapping 

pped area by detailed biological cover types. These numbers are 

further divided into the amount of mapped area inside and outside the JBNERR. 

Figure 2.55. Summary statistics describing the total amount of ma

Figure 2.56 Summary statistics describing the total amount of mapped area by

percent coral cover types. These numbers are further divided into the amount of

mapped area inside and outside the JBNERR. 

49 
Baseline Assessment of Jobos Bay, Puerto Rico: Benthic Habitat Mapping 

2.9.2. Comparison to Previous 

NOAA Habitat Maps of Jobos Bay 

The 2010 mapping effort described 

in this chapter marks the second 

time NOAA has mapped the shallowwater marine benthic habitats of Jobos Bay. However, several improvements were made in the 2010 map 

versus the 2001 map (Kendall et al., 

2001). These improvements specifically include the use of: (1) a new 

classification scheme with a higher 

thematic resolution, (2) a fi ner scale 

of delineation, and (3) a smaller 

minimum mapping unit (Table 2.5). 

These improvements were possible 

due to the use of higher resolution optical imagery and to the mapping of a much smaller project 

area. In addition to these enhancements, more of the seafloor within Jobos Bay was mapped in 2010 

than in 2001 (i.e., approximately 78 km2

 versus 56 km2, respectively; Figure 2.57). More seafloor was 

Table 2.5. Comparison of map and feature characteristics for the 2001 and 2010 

benthic habitat maps. 

NOAA Mapping Effort 

2001 2010 

Map 

Optical Imagery Acquisition Date 1999 2010 

Spatial Resolution of Optical Imagery (m) 2.40 0.30 

Scale of Delineation 1:6,000 1:2,000 

MMU (m2

) 4,046 1,000 

Feature 

Number of Polygons 230 817 

Number of Polygons <4,046 m2 - 261 

Mean Area of Polygons (m2

) 0.25 0.10 

Total Mapped Area (km2

) 55.89 78.00 

Mean Permimeter of Polygons (km) 2.88 1.74 

Total Perimeter of Polygons (km) 653 1,422 

50 2 - Benthic Habitat Mapping

Figure 2.57. Maps of the major geomorphological structure types mapped in 2001 and in 2010. Note the large area that was characterized 

as “Unknown” in 2001. 
Baseline Assessment of Jobos Bay, Puerto Rico: Benthic Habitat Mapping

51 2 - Benthic Habitat Mapping

mapped in 2010 because acoustic imagery was collected and used to characterize areas that were 

previously obscured by turbidity in the 2001 mapping effort. 

Periodic re-mapping of an area can serve as an important monitoring tool. Although the different

classifi cation schemes and MMUs prohibit a quantitative comparison between the 2001 and 2010 

maps for several reasons (Kendall and Miller, 2008), there appear to be some changes in biological 

cover on softbottom between the two time periods. For example, areas immediately east of Punta 

Arenas experienced some loss and regrowth of seagrass between 1999 (when the previous source 

imagery was taken) and 2007 (when the new source imagery was taken; Figure 2.58).

Figure 2.58. Periodic re-mapping of an area can serve as an important monitoring tool. These maps (developed in 2001 and 2010) 

show the loss and regrowth of seagrass (denoted by the white circles) southeast of Punta Arenas.

In addition to the localized loss and

regrowth of seagrass beds, several

square kilometers (approximately 4.7 

km2

) of seagrass that were previously 

unmapped (due to turbidity) were

characterized in the new habitat

map. These previously unmapped

seagrass beds were primarily found

in the shallows east of Cayo Puerca, 

north of Punta Rodeo and north of

Cayo Morrillo and Cayos de Pájaros 

(Figure 2.59). A more detailed,

visual comparison of the 1999 and

2007 imagery and 2001 and 2010

habitat maps may reveal additional

fi ne scale habitat changes, helping

managers to better understand how

benthic communities have changed in the last decade, and possibly to better understand how benthic 

communities will change during the next decade in the Jobos Bay.

Figure 2.59. Several square kilometers (approximately 4.7 km2) of previously 

unmapped seagrass (due to turbidity) were characterized in the new habitat map 

east of Cayo Puerca, north of Punta Rodeo and north of Cayo Morrillo and Cayos 

de Pájaros.

Unknown (2001)

Seagrass (2010)

0 100 200 m
Baseline Assessment of Jobos Bay, Puerto Rico: Benthic Habitat Mapping 

2 - Benthic Habitat Mapping

ACKNOWLEDGEMENTS 

Funding for this mapping effort was provided by NOAA’s CRCP and the Natural Resources 

Conservation Service (NRCS). This work would not have been possible without the numerous people 

who shared their data, time and expertise throughout this process. In particular, we appreciate the 

support of the JBNERR staff, especially Angel Dieppa. We also appreciate the support of Jay Lazar 

and David Bruce from NOAA’s Chesapeake Bay Office (CBO) for collecting the acoustic data. Also, 

many thanks to Adam Zitello, Tim Battista and Chris Caldow for helping to collect ground validation 

data in the field. Matthew Kendall, Matthew Poti, Angel Dieppa and Jorge “Reni” García-Sais provided 

useful comments and editorial assistance. 

REFERENCES 

Battista, T.A., Costa, B.M., and S.M. Anderson. 2007a. Shallow-water benthic habitats of the main 

eight Hawaiian islands. NOAA Technical Memorandum NOS NCCOS 61 (Online). http://ccma.nos. 

noaa.gov/products/biogeography/hawaii_cd_07/welcome.html (Accessed 17 February 2011). 

Battista, T.A., Costa, B.M., and S.M. Anderson. 2007b. Shallow-Water Benthic Habitats of the 

Republic of Palau. NOAA Technical Memorandum NOS NCCOS 59 (Online). http://ccma.nos.noaa. 

gov/products/biogeography/palau/htm/overview.html (Accessed 17 February 2011). 

Bauer, L.J., M.S. Kendall, A.G. Zitello, and T. Battista. 2010. Chapter 2: Benthic Habitats of Vieques, 

Puerto Rico. pp. 9-46. In: L.J. Bauer and M.S. Kendall (eds.). An Ecological Characterization of the 

Marine Resources of Vieques, Puerto Rico Part II: Field Studies of Habitats, Nutrients, Contaminants, 

Fish, and Benthic Communities. NOAA Technical Memorandum NOS NCCOS 110. Silver Spring, 

MD. 174 pp. 

Buja, K. 2008a. Habitat digitizer extension for ArcGIS v5. Biogeography Branch, Center for Coastal 

Monitoring and Assessment, National Centers for Coastal Ocean Science, National Ocean Service, 

National Oceanic and Atmospheric Administration. (Online) http://ccma.nos.noaa.gov/products/ 

biogeography/digitizer/welcome.html (Accessed 17 February 2011). 

Buja, K. 2008b. Find adjacent features. ESRI Support Center. (Online) http://arcscripts.esri.com/ 

details.asp?dbid=15805 (Accessed 10 June 2011). 

Buja, K. 2008c. Find overlapping polygons. ESRI Support Center. (Online) http://arcscripts.esri.com/ 

details.asp?dbid=15198 (Accessed 10 June 2011). 

Buja, K. 2010. BIOMapper (Biogeography Integrated Online Mapper) for Jobos Bay, Puerto Rico. 

Biogeography Branch, Center for Coastal Monitoring and Assessment, National Centers for Coastal 

Ocean Science, National Ocean Service, NOAA. (Online) http://ccma.nos.noaa.gov/products/ 

biogeography/biomapper/biomapper.html?id=JobosBay (Accessed 17 February 2011). 

Costa, B.M., L.J. Bauer, T.A. Battista, P.W. Mueller and M.E. Monaco. 2009. Moderate-Depth Benthic 

Habitats of St. John, U.S. Virgin Islands. NOAA Technical Memorandum NOS NCCOS 105. Silver 

Spring, MD. 57 pp. 

Denbigh, P.N. 1989. Swath Bathymetry: Principles of Operation and an Analysis of Errors. IEEE 

Journal of Oceanic Engineering 14(4): 289-298. 

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Baseline Assessment of Jobos Bay, Puerto Rico: Benthic Habitat Mapping 

Department of Natural and Environmental Resources (DNER). 2002. Jobos Bay Estuarine Profile: 

A National Estuarine Research Reserve. Puerto Rico DNER and National Oceanic and Atmospheric 

Administration, Office of Ocean and Coastal Resource Management, Estuarine Reserve Division. 

107 pp. 

Fonseca, L. and B. Calder. 2005. Geocoder: an efficient backscatter map constructor. Proceedings of 

the U.S. Hydrographic Conference 2005. San Diego, CA. 

García-Sais, J., R. Appeldoorn, T. Battista, L. Bauer, A. Bruckner, C. Caldow, L. Carrubba, J. Corredor, 

E. Diaz, C. Lilyestrom, G. García-Moliner, E. Hernández-Delgado, C. Menza, J. Morell, A. Pait, J. 

Sabater, E. Weil, E. Williams, and S. Williams. 2008. The State of Coral Reef Ecosystems of Puerto 

Rico. pp. 75-116. In: J.E. Waddell and A.M. Clarke (eds.). The State of Coral Reef Ecosystems of 

the United States and Pacific Freely Associated States: 2008. NOAA Technical Memorandum NOS 

NCCOS 73. Silver Spring, MD. 569 pp. 

Gostnell, K. 2005. Efficacy of an Interferometric Sonar for Hydrographic Surveying: Do Interferometers 

Warrant an In-Depth Examination? The Hydrographic Journal 118: 17-24. 

Hotelling, H. 1933. Analysis of a complex of statistical variables into principal components. The 

Journal of Educational Psychology 24(6): 417-441. 

Jenness, J. 2002. ArcView 3.x extension: Surface Areas and Ratios from Elevation Grid v1.2. (Online) 

http://www.jennessent.com/arcview/surface_areas.htm (Accessed 17 February 2011). 

Jenness, J. 2004. Calculating landscape surface area from digital elevation models. Wildlife Society 

Bulletin 32: 829-839. 

Kendall, M.S., C.R. Kruer, K.R. Buja, J.D. Christensen, M. Finkbeiner, R.A. Warner, and M.E. Monaco. 

2001. Methods Used to Map the Benthic Habitats of Puerto Rico and the U.S. Virgin Islands. NOAA 

Technical Memorandum NOS NCCOS CCMA 152. Silver Spring, MD. 46 pp. 

Kendall, M.S., O.P. Jensen, C. Alexander, D. Field, G. McFall, R. Bohne, and M.E. Monaco. 2005. 

Benthic Mapping Using Sonar, Video Transects, and an Innovative Approach to Accuracy Assessment: 

A Characterization of Bottom Features in the Georgia Bight. Journal of Coastal Research 21(6): 1154­

1165. 

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Coral Reef Ecosystem. Marine Geodesy 31: 75-102. 

Kostylev, V.E., B.J. Todd G.B.J. Fader, R.C. Courtney, G.D.M. Cameron, and R.A. Pickrill. 2001. 

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sea floor photographs. Marine Ecology Progress Series 219: 121-137. 

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Magazine Series 6. 2:11, 559-572. 

Pittman, S.J., S.D. Hile, C.F.G. Jeffrey, R. Clark, K. Woody, B.D. Herlach, C. Caldow, M.E. Monaco, 

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NOS NCCOS 107. Silver Spring, MD. 202 pp. 

2 - Benthic Habitat Mapping 53 
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2 - Benthic Habitat Mapping

Prada, M.C., R.S. Appeldoorn, and J.A. Rivera. 2008. Improving Coral Reef Habitat Mapping of the 

Puerto Rico Insular Shelf Using Side Scan Sonar. Marine Geodesy. 31: 49-73. 

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30(5): 377-392. 

Wright, D.J., E.R. Lundblad, E.M. Larkin, R.W. Rinehart, J. Murphy, L. Cary-Kothera, and K. Draganov. 

2005. Arc-GIS Benthic Terrain Modeler (BTM). Corvallis, Oregon. 

Zitello, A.G., L.J. Bauer, T.A. Battista, P.W. Mueller, M.S. Kendall and M.E. Monaco. 2009. ShallowWater Benthic Habitats of St. John, U.S. Virgin Islands. NOAA Technical Memorandum NOS NCCOS 

96. Silver Spring, MD. 53 pp. 

54 
Baseline Assessment of Jobos Bay, Puerto Rico: Benthic Habitat Mapping 

2 - Benthic Habitat Mapping 55 
Chapter 3
Baseline Assessment of Jobos Bay, Puerto Rico: Baseline Characterization 

Baseline Characterization of Fish Communities, 

Associated Benthic Habitats and Marine Debris of Jobos Bay
 

Laurie Bauer1,2,3, Christopher F.G. Jeffrey1,2 and Kimberly Roberson1 

3.1. INTRODUCTION 

The Jobos Bay marine ecosystem 

is comprised of a complex mosaic 

of habitats, including mangrove, 

seagrass beds, and coral reefs that 

span both subtidal and intertidal areas 

(Chapter 2). This habitat complexity 

is most evident in the central portion 

of the bay. An extensive network 

of mangroves is present, both as 

basin and fringe forests lining the 

shore, and as overwash islets and 

cays lining the southern edge of 

the bay (Figure 3.1). The remainder 

of the Bay is composed mostly of 

unconsolidated sediments while 

coral reef and hardbottom line the 

seaward edge of the cays. 

Despite Jobos Bay’s ecological importance and designation as a NOAA National Estuarine Research 

Reserve (NERR), marine fish and benthic communities within and outside the Bay are not well 

characterized. In the 1970s, studies were conducted evaluating potential impacts of the Aguirre 

thermoelectrical power plant on the Bay’s marine resources, including fish and benthic organisms 

(PRNC, 1975). More recent studies, which also focus on the assessment of marine communities 

under varying influence of the Aguirre plant, include García and Castro (1997) and García-Sais et al. 

(2003). As part of an overall profile of the Jobos Bay National Estuarine Research Reserve (JBNERR 

or Reserve), DNER (2002) provided a fish and invertebrate species inventory and highlighted the 

need for further inventory and monitoring. 

As described in Chapter 1, an aim of the Conservation Effect and Conservation Project (CEAP) is 

to quantify the environmental benefits of conservation practices applied by landowners which are 

expected to reduce inputs of pollutants derived from land-based sources into Jobos Bay. In support 

of this broad effort, this assessment used established monitoring protocols (Pittman et al., 2008, 

2010) to spatially characterize fish assemblages, benthic communities, and marine debris across 

all habitats (reef/hardbottom, unconsolidated sediments, mangrove) within Jobos Bay that may be 

affected by changing land-use practices. Characterization of the Jobos Bay marine ecosystem will 

provide a foundation for evaluating expected changes in marine biota, benthic habitats, water quality, 

and biogeochemistry following implementation of agricultural conservation practices in the adjacent 

watershed. The data presented here will serve as a baseline to monitor future changes in benthic 

cover, population estimates and size spectra of fish over time. In addition, the data collected may 

be utilized by JBNERR for developing a spatially-explicit long-term monitoring program within the 

Reserve and for informing future management decisions. 

1

 Center for Coastal Monitoring and Assessment, National Centers for Coastal Ocean Science, National Ocean Service, National 

Oceanic and Atmospheric Administration 

2

 Consolidated Safety Services, Inc., under NOAA Contract No. DG133C07NC0616 

3 Corresponding author: Laurie.Bauer@noaa.gov 

3 - Baseline Characterization 

Figure 3.1. Gray snapper (Lutjanus griseus) amongst mangrove roots. Photo:

NOAA Center for Coastal Monitoring and Assessment (CCMA). 

57 
Baseline Assessment of Jobos Bay, Puerto Rico: Baseline Characterization

58 3 - Baseline Characterization

3.2. METHODS

3.2.1. Site Selection

To assist in monitoring coral reef resources and to achieve a better understanding of fi sh-habitat 

relationships in the U.S. Caribbean, the Center for Coastal Monitoring and Assessment (CCMA) 

Biogeography BranchA (BB) developed a fi sh and macroinvertebrate monitoring protocol to provide 

fi shery-independent and size-structured survey data needed to comprehensively assess faunal 

populations and communities (Menza et al., 2006). In addition, a complementary benthic composition 

survey was developed to support studies of fi sh-habitat relationships. These data collection activities 

are core components of CCMA’s Coral Reef Ecosystem Monitoring (CREM) project, which are used 

to quantify long-term changes in fi sh species and assemblage diversity, abundance, biomass and 

size-structure in southwest Puerto Rico (Pittman et al., 2010) and the Buck Island Reef National 

Monument (BIRNM) in St. Croix, U.S. Virgin Islands (USVI; Pittman et al., 2008). 

Using these established CREM

protocols, fi eld surveys were

conducted from June 7-14, 2009 to 

characterize the fi sh communities 

and associated habitats in Jobos Bay. 

Sites were selected using a randomstratifi ed survey design with habitat 

type (hardbottom, unconsolidated

sediments, mangrove) and location 

(inshore, offshore, shelf, see Figure 

3.2) as the main strata. These strata 

were chosen to ensure adequate

spatial distribution of sites among

all available habitats. The number of 

sites selected within each strata was 

determined based on logisitics and 

results from statistical analyses of

variance (Menza et al., 2006). As the 

new benthic habitat map produced in 

Chapter 2 was not completed at the 

time, a previous NOAA benthic habitat 

map (Kendall et al., 2001) was used 

as the basis for site stratifi cation, 

and draft classifi cations were 

created for portions of the offshore 

region that had been classifi ed as 

“unknown” in the 2001 map. The

“hardbottom” strata comprised

bedrock, pavement, rubble, and

coral reef, while the “unconsolidated 

sediments” stratum comprised

seagrasses and macroalgal beds, as 

well as uncolonized sand and mud. 

The “mangrove” stratum comprised 

the seaward edge of mangrove

Figure 3.2. Inshore, offshore, and shelf regions used to stratify survey locations.

201234 0.5

Kilometers

Inshore

Offshore

Shelf

Land

Figure 3.3. Diver collecting data on benthic habitat composition. Photo: NOAA CCMA 

A The Biogeography Branch is a part of National Oceanic and Atmospheric Administration (NOAA), National Ocean Service (NOS), National Centers 

for Coastal Ocean Science (NCCOS), Center for Coastal Monitoring and Assessment (CCMA).
habitat able to be surveyed with these visual underwater survey methods. 

3.2.2. Field methods 

The surveys of benthic features, fish communities, marine debris and macroinvertebrates were 

conducted within a 25x4 m transect (100 m2

), along a random heading (Pittman et al., 2008, 2010). 

Two divers performed the survey at each site. One diver was responsible for visual counts and size 

estimation of fish species. The second diver quantified benthic features, macroinvertebrates and 

marine debris (Figure 3.3). 

Benthic habitat composition 

The habitat diver first assigned an 

overall bottom type (i.e., hardbottom, 

unconsolidated sediments, or 

mangrove) to each transect based 

on in situ observation. Data on the 

percent cover of abiotic and biotic 

composition at each survey site were 

recorded within five 1 m2

 quadrats 

placed randomly along the 25x4 m 

transect so that one quadrat falls 

within every 5 m interval along the 

transect. The quadrat was placed at 

each randomly chosen meter mark 

and systematically alternated from 

side to side along the transect tape 

(Figure 3.4). Several variables were 

measured to characterize benthic 

composition and structure (Table 

3.1). The quadrat was divided into 

100 smaller 10x10 cm squares with 

string (1 small square = 1% cover) 

to help the diver with estimation of 

percent cover. Percent cover was 

determined by looking at the quadrat 

from above and visually estimating 

percent cover in a two dimensional 

plane. The information recorded 

included: 

1. Abiotic cover - the percent 

cover (to the nearest 1%) 

of four abiotic substrate 

categories (hardbottom, sand, 

rubble, fine sediments/silt) 

was estimated within each 1 

m2

 quadrat. The maximum 

height of the hardbottom was 

also measured. 

0 5 10 15 20 m 25

1-m2 quadrat Transect tape 

4 m 

Figure 3.4. Schematic representation of the placement of the 1 m2 quadrat along a

25 m transect tape during fish and benthic substrate surveys. 

Table 3.1. Abiotic and biotic variables measured in five quadrats along fish transects 

in Jobos Bay. 

Measurements 

Cover Height AbunParameter (%) (cm) dance (#) 

Abiotic

Hardbottom X X 

Sand X 

Rubble X 

Fine sediment/silt X 

Rugosity 

Water depth 

Biotic

Corals (by species) X 

Macroalgae X X 

Seagrass (by species) X X 

Gorgonians 

Sea rods, whips and plumes X X X 

Sea fans X X X 

Encrusting form X

 Sponges 

Barrel, tubes, rope, vase X X X 

Encrusting form X

 Other benthic macrofauna 

Anemones and hydroids X X 

Tunicates and zoanthids X 

Mangroves 

Prop roots X 

Prop roots colonized by algae X 

Prop roots colonized by sponges X 

Prop roots colonized by other biota X 

Baseline Assessment of Jobos Bay, Puerto Rico: Baseline Characterization 

3 - Baseline Characterization 59 
Baseline Assessment of Jobos Bay, Puerto Rico: Baseline Characterization 

3 - Baseline Characterization

2. Biotic cover - the percent cover (to the nearest 0.1%) of algae, seagrass, live corals, sponges, 

gorgonians, and other biota was estimated within each 1 m2 quadrat. Taxa were identified 

to the following levels: stony coral-species, seagrass-species, algae-morphological group, 

sponge-morphological group, and gorgonians-morphological group. For stony and fi re corals, 

the percentage of bleached coral and diseased/dead coral was estimated to the nearest 0.1 

percent. 

3. Maximum canopy height - the maximum canopy height of sponges, gorgonians, and soft algal 

groups was recorded to the nearest 1 cm in each quadrat. 

4. Number of individuals - the number of individual upright sponges, gorgonians, non-encrusting 

anemones, and non-encrusting hydroids was recorded in each quadrat. 

5. Rugosity – for hardbottom sites, rugosity was measured by placing a 6 m chain at two randomly 

selected positions, ensuring no overlap, along the 25 m belt transect. The chain was positioned 

along the centerline of the transect such that it followed the substrate’s relief, and the straightline horizontal distance covered by the chain was measured. 

Mangrove habitat data 

At mangrove sites, the survey was conducted close to the prop roots and as far into the mangroves 

as possible, up to 2 m and then out to the edge of the mangrove overhang such that the total area 

surveyed was still 100 m2

. In this case, some of the survey may necessarily fall on seagrass habitat. 

This is allowed as the mangrove habitat is defined as a transition zone habitat. In addition to the 

habitat data collected above, further mangrove data are collected including number of prop roots, 

number of prop roots colonized by algae, number of prop roots colonized by sponges and number of 

prop roots colonized by other biota (tunicates, anemones, zoanthids, etc.). 

Macroinvertebrate counts 

The habitat diver counted the abundance of spiny lobsters (Panulirus argus), long-spined urchins 

(Diadema antillarum), and the abundance/maturity of queen conchs (Eustrombus gigas) within the 

25x4 m transect at each site. The maturity of each conch was determined by the presence (mature) 

or absence (immature) of a fl ared lip. 

Fish census 

Fish surveys were conducted along the 25x4 m transect (100 m2

) using a fixed survey duration of 15 

minutes regardless of habitat type or complexity. The number of individuals per species was recorded 

in 5 cm size class increments up to 35 cm using visual estimation of fork length. Individuals greater 

than 35 cm were recorded as an estimate of the actual fork length to the nearest centimeter. 

Marine debris 

The number and type of marine debris within the 100 m2

 transect were recorded. The size of marine 

debris and the area of habitat that it was affecting were estimated, as well as a note about any flora 

or fauna that were colonizing the debris item. 

3.2.3. Data Analysis 

Benthic Habitat 

While many benthic variables were measured during the surveys, data analyses for this report focused 

primarily on describing differences among major habitat types and broad-scale spatial patterns 

in the percent cover of the sessile biotic components as described in Table 3.1. Multiple quadrat 

measurements within each site transect were averaged and cumulative coral species richness was 

calculated for each survey location. Domain-wide estimates of abiotic and biotic cover variables were 

60 
Baseline Assessment of Jobos Bay, Puerto Rico: Baseline Characterization 

computed employing methods described by Cochran (1977) for a stratified sampling design (SAS 

v9.1, Proc SurveyMeans). In addition, data were plotted in ArcGIS (v9.3, ESRI) to examine broad 

spatial patterns in the benthic cover variables. 

Fish Assemblages 

A summary table of all species observed in this characterization was created (Appendix A, Table A.1). 

Domain-wide estimates for several metrics were computed employing methods described by Cochran 

(1977). Percent occurrence, mean density and biomass (per 100 m2

) and corresponding standard 

errors (SE) were calculated for each species. Mean density and biomass were also calculated for each 

family and trophic group for the overall survey area. Trophic groups include piscivores, herbivores, 

invertivores, and zooplanktivores and were defined for each species based on diet information from 

Randall (1967). However, it is important to note that these groups are not mutually exclusive because 

many fish species can be classified into two or more of these groups based on diet. Biomass was 

calculated using published length-weight relationships based on the formula, 

W = αLβ

where L is length in centimeters and weight is in grams. The midpoint of each size class was used 

for L values, and the actual length was used for fish >35 cm. For fish in the 0-5 cm size class, 3 cm 

was used as the mid-point because we do not typically observe fish <1 cm). Values for the α and β

coefficients were obtained from FishBase (Froese and Pauly, 2008). Biomass for species with no 

published length-weight relationships was calculated using terms for the closest congener with most 

similar morphology. 

Species diversity was calculated using the Shannon Index (H’), a measure that incorporates both 

richness and evenness: 

H’ = Σi

pi(logepi) 

where pi

 is the relative abundance of each species. 

Select variables (density, biomass, richness, and diversity) were compared among bottom type to 

characterize any potential differences related to major habitat type. As the assumptions of normality 

and homogeneity of variance were not met non-parametric Wilcoxon tests were used. When the 

overall test was significant, non-parametric multiple pairwise comparisons were used to determine 

whether pairs of habitats were significantly different (Zar, 2010). Data were plotted in ArcGIS to 

examine broad spatial patterns in the fi sh metrics. 

In addition, select families and species of commercial and/or ecological interest were selected for 

further examination. For each species/family, a summary of the species distribution, mean density and 

biomass among strata, and size frequency is provided. Juveniles/subadults were identified based on 

length at maturity information provided by FishBase (Froese and Pauly, 2008), García-Cagide et al. 

(1994) and Ault et al. (2008). Fish less than the mean length at maturity were classified as juveniles/ 

subadults. Where length at maturity was unknown, 1/3 of maximum size was used as a proxy as in 

Pittman et al. (2008, 2010). 

Differences and similarities in species composition were examined using multivariate statistical 

techniques (Primer v.6, Clarke and Warwick, 2001). Data were square-root transformed prior to 

analysis, and one outlier site was removed due to extremely low abundance (one fish). Data were 

arranged in a species abundance by site data matrix, which was used to construct a triangular matrix 

of the percentage similarity in community composition between all pairs of sites using the Bray-Curtis 

Coeffi cient. The coefficient is a measure of how similar samples are to each other, ranging from 

3 - Baseline Characterization 61 
Baseline Assessment of Jobos Bay, Puerto Rico: Baseline Characterization

62 3 - Baseline Characterization

0% (complete dissimilarity) to 100% (complete similarity). Next, non-metric multidimensional scaling 

(nMDS) was used to place samples in a two-dimensional confi guration such that the rank order of 

the distances between the samples agreed with the rank-order of the similarities from the Bray-Curtis 

matrix. Sites were coded by habitat strata for examination of visual patterns of between site similarity. 

These factors were also used to test for signifi cant differences in similarity using Analysis of Similarities 

(ANOSIM), a multivariate, non-parametric version of ANOVA. Finally, similarity percentages (SIMPER) 

were calculated to identify the species that contributed most to the differences between strata. 

3.3. RESULTS AND DISCUSSION

Although 72 sites were originally proposed, several sites were not surveyed due to very low visibility. 

Exceptionally poor visibility prohibited all planned surveys (eight total) in Rincón Bay, the northwest 

portion of the study area. Visibility was also poor and prohibited most surveys within the eastern 

portion of central Jobos Bay. In addition, one site at a dock in the landward reaches of Mar Negro 

was not surveyed due to water quality concerns. A total of 45 sites were surveyed: 20 on hardbottom, 

15 on unconsolidated sediments, and 10 in mangrove (Figure 3.5). Only four sites fell within the 

boundaries of JBNERR.

Figure 3.5. Benthic habitat strata and site locations of the June 2009 survey of benthic habitat composition, fi sh communities, and 

marine debris. The boundaries of the Jobos Bay National Estuarine Research Reserve (JBNERR) are shown for reference.

June 2009 Survey Sites

Benthic Habitat

Coral Reef and Hardbottom

Unconsolidated Sediments

Mangrove

Land

JBNERR boundary

2

Cayos Caribe

Cayos de Ratones

Cayos de Barca

Mar Negro

C

Pa

a

j

y

a

os de ros

3.3.1. Benthic habitat

Abiotic composition

Five sites stratifi ed as hardbottom surveys were designated as unconsolidated sediment by the diver, 

and were subsequently grouped with the unconsolidated sediment surveys in the data analysis. This 

likely occurred due to the heterogeneity of some hardbottom structure types (e.g., aggregated patch 

reefs, pavement with sand channels). 
Baseline Assessment of Jobos Bay, Puerto Rico: Baseline Characterization 

3 - Baseline Characterization

As expected, sites conducted on 

hardbottom habitat were predominantly composed of hardbottom 

substrate, with smaller amounts of 

rubble, sand and fine sediment (Figures 3.6a). Many unconsolidated 

sediment sites were dominated by 

fine sediment, while a few locations 

in the west-central portion of the bay, 

as well as those located furthest offshore, were composed of sand and 

rubble substrates (Figures 3.6b). 

Most mangrove sites were also characterized by fine sediments, although 

a few locations were more typifi ed by 

sand and rubble (Figures 3.6c). 

Biotic composition 

On hardbottom sites, turf algae 

accounted for the highest mean 

percent cover (36.3 ± 4.8%), followed 

by macroalgae (15.3 ± 2.6%), hard 

(scleractinian) corals (6.5 ± 1.2%), 

sponges (4.4 ± 1.0%), gorgonians (4.4 

± 0.9%), and zoanthids (4.4 ± 3.3%; 

Figure 3.7a). Other algae groups 

included crustose coralline algae 

(CCA; 3.5 ± 1.3%), cyanobacteria 

and filamentous algae (2.2 ± 1.1%), 

and rhodoliths (0.5 ± 0.5%). Small 

amounts of the hydroid Millepora 

spp. (fire coral), were also present 

(0.2 ± 0.1%). Bare, uncolonized 

substrate averaged 28.7 ± 5.3%. 

Rugosity ranged from 0.01-0.42 

and averaged 0.22 (±0.02). Sites 

with highest rugosity were typically 

located on sloping fore reef seaward 

of the cays (Figure 3.8). 

Unconsolidated sediment sites were characterized by an assemblage of submerged aquatic vegetation 

and low levels of benthic fauna. Macroalgae accounted for the highest mean percent cover (11.6 ± 

6.4%), followed by seagrass (6.9 ± 3.0%), turf algae (5.8 ± 4.4%), rhodoliths (4.5 ± 4.1%), CCA (3.0 ± 

2.7%), and cyanobacteria/filamentous algae (1.8 ± 1.2%; Figure 3.7b). The average amount of bare 

substrate (65.8 ± 8.5%) was considerably higher than on hardbottom. 

The majority of the substrate in mangrove habitat (78.9 ± 8.4%) was characterized as uncolonized, 

with variable amounts of cyanobacteria and filamentous algae (12.8 ± 7.6%), turf algae (4.4 ± 4.4%), 

and macroalgae (3.3 ± 1.6%; Figure 3.7c). Seagrass cover was generally low, averaging less than 

one percent. 

Figure 3.6. Mean (±SE) percent cover of abiotic substrate across a) hardbottom, b)

unconsolidated sediment, and c) mangrove sites. 

0 

10 

20 

30 

40 

50 

60 

70 

80 

90 

Percent cover 

0 

10 

20 

30 

40 

50 

60 

70 

80 

Percent cover 

0 

10 

20 

30 

40 

50 

60 

70 

80 

90 

Hardbottom Rubble Sand Fine sediment 

Percent cover 

a) 

b) 

c) 

63 
Baseline Assessment of Jobos Bay, Puerto Rico: Baseline Characterization 

3 - Baseline Characterization

Live scleractinian coral cover varied 

widely across the survey area 

(Figure 3.9), ranging from 0-21.8%. 

Sites inside the Bay tended to be 

characterized by low cover, while 

aggregate reef adjacent to the 

cays was characterized by higher 

than average coral cover. However, 

coral cover only exceeded 10% 

in four surveys. The site with the 

highest total cover was located on 

an offshore patch of hardbottom 

southwest of Cayos de Ratones. 

Recent work by García and Castro 

(1997) and García-Sais et al. (2003) 

also detected low coral cover in 

the inshore areas but upwards of 

15-20% on reefs offshore of Cayos 

Caribe and Cayos de Barca. 

The coral community observed in 

the study was represented by 24 

species, 22 of which were observed 

on hardbottom. Species richness 

ranged from 0-13 species at 

individual sites. The spatial pattern 

was similar to that of that of live 

coral cover- sites within the bay 

tended to be characterized by low 

species richness, while aggregate 

reef adjacent to the cays and 

offshore hardbottom tended to have 

higher richness (Figure 3.10). The 

most abundant coral was Porites 

astreoides (mustard hill coral), 

followed by Siderastrea siderea 

(massive starlet coral), Montastraea 

cavernosa (great star coral), and 

the Montastraea annularis complex 

(boulder star coral; Figure 3.11). Two 

additional species not included in 

Figure 3.11, Manicina areolata (rose 

coral) and Oculina diffusa (diffuse 

ivory bush coral), were observed 

only on unconsolidated sediments. Neither Acropora palmata (elkhorn coral) or Acropora cervicornis 

(staghorn coral), both of which are listed as threatened under the Endangered Species Act (ESA), 

were observed in any survey quadrat; however A. palmata and A. cervicornis were observed outside 

survey quadrats at one and two sites, respectively. Both sites were located along the fore reef of 

Cayos Caribe. 

0 

5 

10 

15 

20 

25 

Percent cover 

0 

5 

10 

15 

20 

25 

30 

35 

40 

45 

Percent cover 

0 

2 

4 

6 

8 

10 

12 

14 

16 

18 

20 

Percent cover 

a) 

b) 

c) 

Figure 3.7. Mean (±SE) percent cover for key components of the benthic community

across a) hardbottom, b) unconsolidated sediments, and c) mangrove sites.

64 
Baseline Assessment of Jobos Bay, Puerto Rico: Baseline Characterization

65 3 - Baseline Characterization

Figure 3.8. Mean rugosity (hardbottom sites only).

Mean rugosity

Not measured

0.01 - 0.10

0.11 - 0.20

0.21 - 0.30

0.31 - 0.42

Benthic habitat

Coral Reef and Hardbottom

Unconsolidated Sediments

Mangrove

Land

JBNERR boundary

2

01234 0.5

Kilometers

Figure 3.9. Percent live coral cover. 

Live coral cover (%)

0.0

0.1 - 3.0

3.1 - 6.0

6.1 - 9.0

9.1 - 21.8

Benthic habitat

Coral Reef and Hardbottom

Unconsolidated Sediments

Mangrove

Land

JBNERR boundary

2

01234 0.5

Kilometers
Baseline Assessment of Jobos Bay, Puerto Rico: Baseline Characterization

66 3 - Baseline Characterization

Figure 3.10. Coral species richness.

Coral species richness

0

1 - 3

4 - 6

7 - 9

10 - 13

Benthic habitat

Coral Reef and Hardbottom

Unconsolidated Sediments

Mangrove

Land

JBNERR boundary

2

01234 0.5

Kilometers

Figure 3.11. Mean (±SE) percent cover of coral species across hardbottom sites. Species identifi ed as Montastraea annularis refer to 

the M. annularis complex.

0

0.5

1

1.5

2

2.5

3

Percent cover
Baseline Assessment of Jobos Bay, Puerto Rico: Baseline Characterization

67 3 - Baseline Characterization

Gorgonian cover ranged from 0-12.3% and exhibited similar spatial patterns to hard coral cover 

(Figure 3.12). Sites on aggregate reef adjacent to the cays, as well as one location farther offshore, 

exhibited the highest gorgonian cover. Encrusting gorgonians were the dominant gorgonian type on 

hardbottom in terms of percent cover, averaging 2.2 ± 0.6%, followed by sea plumes/rods/whips (1.6 

± 0.5%), and sea fans (0.6 ± 0.2%). Sea plumes/rods/whips were also more abundant than sea fans 

in the average number of individuals/m2

 (2.0 ± 0.5/m2 vs. 0.6 ± 0.3/m2). 

Sponge cover ranged from 0-15.5% and did not exhibit distinctive spatial patterns (Figure 3.13). Sites 

with percent cover >10% were located on hardbottom near and south of Cayos de Pájaros. Barrel/

tube/vase sponges accounted for the majority of percent cover on hardbottom (3.1 ± 0.9%), while 

encrusting sponge comprised a smaller component of the sponge community (1.3 ± 0.4%). This 

pattern was also true for unconsolidated sediment sites, although both sponge morphologies were 

present in much smaller amounts (barrel/tube/vase = 0.4 ± 0.2%; encrusting = 0.02 ±0.01). 

Macroalgae cover ranged from 0-95.6% and was distributed across all areas (Figure 3.14). The site 

with the highest macroalgal cover was located in unconsolidated sediments within the lagoon, but 

overall macroalgal cover was generally greater on hardbottom than unconsolidated sediments and 

mangrove. Turf algae was a ubiquitous component of the reef community and was recorded in all but 

one hardbottom survey (Figure 3.15). CCA was typically present in small amounts but higher values 

were present in surveys near Cayos de Ratones and at the study site furthest offshore (Figure 3.16). 

The site furthest from shore was also characterized by cover of fi lamentous algae/cyanobacteria >15% 

(Figure 3.17). This category was characterized by wide variations in cover, ranging from 0-76.6%. 

Higher cover was particularly associated with mangrove surveys within Jobos Bay (Figure 3.17).

Figure 3.12. Percent gorgonian cover.

Gorgonian cover (%)

0.0

0.1 - 3.0

3.1 - 6.0

6.1 - 9.0

9.1 - 12.3

Benthic habitat

Coral Reef and Hardbottom

Unconsolidated Sediments

Mangrove

Land

JBNERR boundary

2

01234 0.5

Kilometers
Baseline Assessment of Jobos Bay, Puerto Rico: Baseline Characterization

68 3 - Baseline Characterization

Figure 3.13. Percent sponge cover.

Sponge cover (%)

0.0

0.1 - 4.0

4.1 - 8.0

8.1 - 12.0

12.1 - 15.5

Benthic habitat

Coral Reef and Hardbottom

Unconsolidated Sediments

Mangrove

Land

JBNERR boundary

2

01234 0.5

Kilometers

Figure 3.14. Percent macroalgae cover.

Macroalgae cover (%)

0.0

0.1 - 10.0

10.1 - 20.0

20.1 - 30.0

30.1 - 95.6

Benthic habitat

Coral Reef and Hardbottom

Unconsolidated Sediments

Mangrove

Land

JBNERR boundary

2

01234 0.5

Kilometers
Baseline Assessment of Jobos Bay, Puerto Rico: Baseline Characterization

69 3 - Baseline Characterization

Figure 3.15. Percent turf algae cover.

Turf algae cover (%)

0.0

0.1 - 20.0

20.1 - 40.0

40.1 - 60.0

60.1 - 95.6

Benthic habitat

Coral Reef and Hardbottom

Unconsolidated Sediments

Mangrove

Land

JBNERR boundary

2

01234 0.5

Kilometers

Figure 3.16. Percent crustose coralline algae (CCA).

CCA cover (%)

0.0

0.1 - 2.0

2.1 - 4.0

4.1 - 6.0

6.1 - 41.1

Benthic habitat

Coral Reef and Hardbottom

Unconsolidated Sediments

Mangrove

Land

JBNERR boundary

2

01234 0.5

Kilometers
Baseline Assessment of Jobos Bay, Puerto Rico: Baseline Characterization

70 3 - Baseline Characterization

Figure 3.17. Percent cover of fi lamentous algae (FA) / cyanobacteria (CB).

CB and FA (%)

0.0

0.1 - 5.0

5.1 - 10.0

10.1 - 15.0

15.1 - 76.6

Benthic habitat

Coral Reef and Hardbottom

Unconsolidated Sediments

Mangrove

Land

JBNERR boundary

2

01234 0.5

Kilometers

Figure 3.18. Percent cover of zoanthids.

Zoanthids cover (%)

0.0

0.1 - 5.0

5.1 - 10.0

10.1 - 20.0

20.1 - 64.0

Benthic habitat

Coral Reef and Hardbottom

Unconsolidated Sediments

Mangrove

Land

JBNERR boundary

2

01234 0.5

Kilometers
Baseline Assessment of Jobos Bay, Puerto Rico: Baseline Characterization

71 3 - Baseline Characterization

Other benthic taxa (anemones,

tunicates, zoanthids) were recorded 

infrequently and generally in small

amounts. Highest percent cover

of zoanthids was present on reef

adjacent to Cayos Caribe (Figure

3.18). In one survey, zoanthids

covered 64% of the substrate (Figure 

3.19).

Seagrass was present primarily

within Jobos Bay across unconsolidated sediment habitat and a limited 

number of mangrove surveys (Figure 3.20). Thalassia testudinum accounted for the highest mean percent 

cover on unconsolidated sediments, 

followed by Halophila decipiens and 

Syringodium fi liforme (Figure 3.21). 

A fourth seagrass species, Halodule 

wrightii B, was uncommon. In mangrove habitat, the only species recorded was T. testudinum. 

Figure 3.19. Zoanthid cover. Photo: NOAA CCMA.

Figure 3.20. Percent seagrass cover.

Seagrass cover (%)

0.0

0.1 - 5.0

5.1 - 10.0

10.1 - 20.0

20.1 - 37.4

Benthic habitat

Coral Reef and Hardbottom

Unconsolidated Sediments

Mangrove

Land

JBNERR boundary

2

01234 0.5

Kilometers

B The taxonomic name for Halodule wrightii has been recently changed to Halodule beaudettei (http://www.itis.gov/index.html); however, the original 

name will be used in this document as it is more widely known.
8 

7 

6

Percent cover 5 

4 

3 

2 

1 

0 

Thalassia Halophilia Syringodium Halodule wrightii 

testudinum decipiens filiforme 

Figure 3.21. Mean (±SE) percent cover of seagrass species across unconsolidated

sediment sites.

Baseline Assessment of Jobos Bay, Puerto Rico: Baseline Characterization 

3 - Baseline Characterization

3.3.2. Fish assemblages 

Community metrics 

The fish community observed in the Jobos Bay study included 34 taxonomic families represented 

by 112 species (Appendix A, Table A.1). Fish species richness ranged from 1 to 27 species per site. 

Richness was generally highest on hardbottom sites, particularly on reefs south of Cayos de Ratones, 

Cayos de Pájaros and Cayos de Barca (Figures 3.22a and 3.23). Species diversity follows a similar 

trend (Figures 3.22b and 3.24). Results of a non-parametric analysis indicate that both richness 

and Shannon diversity were significantly greater on hardbottom compared with both unconsolidated 

sediments and mangrove (p<0.05). 

0 

5 

10 

15 

20 

25 

Mean richness (100 m2 ) 

0 

0.5 

1 

1.5 

2 

2.5 

Mean Shannon diversity (100 m2 ) 

0 

50 

100 

150 

200 

250 

300 

350 

400 

450 

500 

Hardbottom Mangrove Unconsolidated 

Sediments 

Mean density (#/100 m2 ) 

0 

500 

1000 

1500 

2000 

2500 

3000 

3500 

4000 

4500 

Hardbottom Mangrove Unconsolidated 

Sediments 

Mean biomass (g/100 m2 ) 

a) 

c) d)

b) 

72 

Figure 3.22. Mean (±SE) fish species a) richness, b) Shannon diversity, c) density, and d) biomass by habitat type. 
Baseline Assessment of Jobos Bay, Puerto Rico: Baseline Characterization

73 3 - Baseline Characterization

Total fi sh density was signifi cantly greater on hardbottom and mangrove habitats in comparison to unconsolidated sediments (p<0.05), but did not signifi cantly vary between hardbottom and mangrove. 

Although average fi sh density was highest on mangrove, there was also a large degree of variability 

(Figure 3.22c). The site with the highest fi sh density in the study area was located in mangrove habitat on Cayos de Ratones, where over 2000 individuals per 100 m2

 (primarily Jenkinsia sp.) were observed (Figure 3.25). Three additional locations of high fi sh density (>100 individuals/100m2

) were located in mangrove and reefs surrounding Cayos de Ratones. In general, density tended to be higher 

on hardbottom sites located on the fore reefs of the cays than at the offshore locations (Figure 3.25). 

Fish density was consistently low on unconsolidated sediments; in 60% of surveys on this habitat, 

≤10 individuals were observed.

Overall, hardbottom supported the highest levels of total fi sh biomass, whereas mangroves supported intermediate levels of biomass (Figures 3.22d and 3.26). Surveys on unconsolidated sediment 

were typically characterized by low levels of biomass. Similar to fi sh density, total fi sh biomass was 

signifi cantly greater on hardbottom and mangrove habitats in comparison to unconsolidated sediments (p<0.05), but did not signifi cantly vary between hardbottom and mangrove. Surveys with the 

highest total biomass include hardbottom sites in close proximity to the cays and a mangrove site in 

the lagoon. At two of the three surveys characterized by biomass >10000g/100 m2

, the high biomass 

was largely attributed to the presence of a southern stingray (Dasyatis americana) and great barracuda (Sphyraena barracuda), respectively.

Figure 3.23. Fish species richness.

Species richness

1 - 5

6 - 10

11 - 15

16 - 20

21 - 27

Benthic Habitat

Coral Reef and Hardbottom

Unconsolidated Sediments

Mangrove

Land

JBNERR boundary

2

01234 0.5

Kilometers
Baseline Assessment of Jobos Bay, Puerto Rico: Baseline Characterization

74 3 - Baseline Characterization

Figure 3.24. Fish species diversity.

Shannon diversity

<1

1.1 - 1.5

1.6 - 2.0

2.1 - 2.5

2.6 - 3.0

Benthic Habitat

Coral Reef and Hardbottom

Unconsolidated Sediments

Mangrove

Land

JBNERR boundary

2

01234 0.5

Kilometers

Figure 3.25. Total fi sh density.

Total abundance

Density (#/100 m2

)

1 - 25

26 - 50

51 - 100

101 - 200

201 - 2084

Benthic Habitat

Coral Reef and Hardbottom

Unconsolidated Sediments

Mangrove

Land

JBNERR boundary

2

01234 0.5

Kilometers
Baseline Assessment of Jobos Bay, Puerto Rico: Baseline Characterization

75 3 - Baseline Characterization

The nMDS and ANOSIM analyses

further indicate that fi sh assemblages in Jobos Bay differ by bottom

type. There was a clear separation

between hardbottom, unconsolidated sediment, and mangrove surveys

(Figure 3.27). One exception was an

unconsolidated sediment site among

the hardbottom group. The transect

was conducted in a seagrass bed

in close proximity to a reef (within

4 m), which likely explains why the

fi sh community was similar to other

hardbottom samples. Mangrove and

hardbottom sites tended to be highly

clustered, indicating a high degree

of similarity in species composition

among sites within each respective habitat type. In contrast, unconsolidated sediment sites tended to 

be more dispersed, indicating more dissimilarity among sites within this group. Indeed, the average 

Bray-Curtis similarity for hardbottom and mangrove sites was 33.78 and 31.75, respectively, but only 

6.92 for unconsolidated sediment surveys. Sub-habitats within unconsolidated sediment bottom include both sand and mud substrate types that can range in cover (e.g., continuous seagrass, sparse 

algae, no cover). Similarly, fi sh communities in these sub-habitats can vary widely. The results of 

the ANOSIM test (R=0.581, p<0.001) also indicate that there is a statistically signifi cant difference in 

Figure 3.26. Total fi sh biomass.

Total biomass

Biomass (g/100 m2

)

0 - 500

501 - 1000

1001 - 2500

2501 - 5000

5001 - 15923

Benthic Habitat

Coral Reef and Hardbottom

Unconsolidated Sediments

Mangrove

Land

JBNERR boundary

2

01234 0.5

Kilometers

Figure 3.27. Non-metric multidimensional (nMDS) scaling ordination based on 

between site similarity composition using fi sh abundance data. Sites are colorcoded by habitat type.

Habitat type

Hardbottom

Unconsolidated Sediments

Mangrove

2D Stress: 0.09
Baseline Assessment of Jobos Bay, Puerto Rico: Baseline Characterization 

3 - Baseline Characterization

community composition among the three groups of sites. Pairwise comparisons resulted in similar or 

slightly higher R values for hardbottom versus unconsolidated sediments (R=0.549) and hardbottom 

vs. mangrove (R=0.853), but a lower value for unconsolidated sediments vs. mangrove (R=0.336). 

This indicates that hardbottom fish communities differ from both mangrove and unconsolidated sediments, but that community differences between the two latter groups are not as distinguishable. This 

is expected as these two habitats share some overlap; for example, mangrove surveys are conducted 

along the interface between the mangrove forest and the adjacent sand/mud bottom. 

Trophic Groups, Families and Species 

Biomass and abundance were distributed unevenly throughout trophic and taxonomic groups. The 

most abundant groups in terms of 

biomass and abundance were herbivores (H; e.g., parrotfi shes, damselfishes) and invertivores (I; e.g., 

grunts, butterflyfishes). Piscivores 

(P; e.g., snappers, groupers) constituted a small percentage of total fish 

abundance, but constituted a greater proportion of the biomass. While 

there was often a large degree of 

variability among habitat type (Figures 3.28a,b), some general spatial 

patterns emerged. Results of a nonparametric analysis indicated that 

herbivore abundance and biomass 

were significantly greater on hardbottom compared to mangrove and 

unconsolidated sediments. Invertivore abundance and biomass were 

significantly greater on hardbottom 

and mangrove in comparison to unconsolidated sediments, but did not 

vary significantly between mangrove 

and hardbottom. Piscivore abundance and biomass were significantly greater in mangrove habitat than 

on hardbottom or unconsolidated 

sediments. Piscivores were present 

in all mangrove surveys, compared 

to 50% of the surveys on hardbottom 

and unconsolidated sediments. 

For each bottom type, families with the highest mean abundance and biomass were ranked and their 

proportional abundance/biomass was calculated (Figures 3.29a-c, 3.30a-c, and 3.31a-c). Overall, 

approximately 90% of individuals and biomass came from eight and nine families, respectively, but 

this distribution varied by bottom type. 

While individuals of the wrasse (Labridae) and damselfish (Pomacentridae) families were the most 

numerically abundant on hardbottom, surgeonfishes (Acanthuridae) accounted for the highest 

proportion of biomass (Figure 3.29a-c). Other families with high proportional abundance and biomass 

0 

50 

100 

150 

200 

250 

300 

350 

400 

450 

Mean density (#/100 m2 ) 

Herbivore 

Invertivore 

Piscivore 

Planktivore 

0 

500 

1000 

1500 

2000 

2500 

Hardbottom Mangrove Unconsolidated 

Sediments 

Mean biomass (g/100 m2 ) 

a) 

b) 

Figure 3.28. Mean (±SE) a) density, and b) biomass of major trophic groups by 

habitat type.

76 
Figure 3.29. Mean (±SE) a) density, and b) biomass, and c) 

proportional distribution of abundance and biomass of major fish 

families across hardbottom sites. 

0 

5 

10 

15 

20 

25 

30 

35 

40 

45 

Mean density (#/100 m2 ) 

0 

200 

400 

600 

800 

1000 

1200 

1400 

1600 

1800 

2000 

Mean Biomass (g/100 m2 ) 

0 

0.05 

0.1 

0.15 

0.2 

0.25 

0.3 

0.35 

0.4 

Proportion 

Abundance 

Biomass 

a) 

b) 

c) 

Figure 3.30. Mean (±SE) a) density, and b) biomass, and c) 

proportional distribution of abundance and biomass of major fish 

families across mangrove sites. 

0 

50 

100 

150 

200 

250 

300 

350 

400 

450 

Mean density (#/100 m2 ) 

0 

200 

400 

600 

800 

1000 

1200 

1400 

1600 

1800 

2000 

Mean Biomass (g/100 m2 ) 

0 

0.1 

0.2 

0.3 

0.4 

0.5 

0.6 

0.7 

0.8 

0.9 

Proportion 

Abundance 

Biomass 

a) 

b) 

c) 

Baseline Assessment of Jobos Bay, Puerto Rico: Baseline Characterization 

3 - Baseline Characterization 

included snappers (Lutjanidae), grunts (Haemulidae) and parrotfish (Scaridae). The high proportional 

biomass of barracuda (Sphyraenidae) was largely due to the presence of a large great barracuda 

individual at one site. The most frequently observed and abundant fish species on hardbottom were 

the ocean surgeonfi sh (Acanthurus bahianus) and bluehead wrasse (Thalassoma bifasciatum), which 

were sighted at 90% of transects on hardbottom. Other species that ranked high in terms of frequency 

and density on hardbottom include damselfish species (Stegastes spp.) and redband and striped 

parrotfi sh (Sparisoma aurofrenatum and Scarus iseri, respectively). 

Among bottom types, mangrove habitat was represented by the fewest number of families. Large 

schools of juvenile clupeids, which were absent on other habitats, were characteristic at several 

mangrove sites. Clupeids accounted for over 75% of observed individuals in mangroves, but due to their 

small size only a small percentage (1%) of their biomass (Figure 3.30a-c). Herring Jenkinsia sp. were 

sighted in about 50% of transects but exhibited patchy abundance where found. Due to the presence 

of a southern stingray in one transect, the stingrays (Family Dasyatidae) accounted for the highest 

proportional biomass in mangrove habitat, followed by snapper. Schoolmaster and gray snapper 

77 
(Lutjanus apodus and Lutjanus 

griseus, respectively) and the 

yellowfin mojarra (Gerres cinerus) 

all ranked high in terms of frequency, 

mean density and biomass. 

Family abundance and biomass 

on unconsolidated sediments was 

highly variable (Figure 3.31a-c). 

While fishes of the groupers, hamlets 

and seabasses family (Serranidae) 

were most numerically abundant, 

individuals were typically small; 

consequently, the family accounted 

for only a small proportion of the 

total biomass found on this habitat. 

Wrasses were also numerically 

abundant on softbottom, while 

surgeonfishes accounted for the 

highest proportion of biomass. 

Overall, species composition was 

variable across unconsolidated 

sediment survey locations. Only 

one species, bicolor damselfish 

(Stegastes partitus), was observed in 

over 30% of transects in this habitat. 

Several families and species 

of economic and ecological 

importance were selected for further 

examination. Summary information 

on the spatial distribution, mean 

density and biomass by habitat, and 

size frequency for select families and 

species are discussed and illustrated 

in this section. 

Groupers, Hamlets and Seabasses 

(Serranidae) 

Groupers, hamlets and seabasses 

were observed in 42% of survey 

transects. The family was represented by 12 species, with harlequin bass (Serranus tigrinus) and chalk bass (Serranus tortugarum) most 

frequently sighted. When all serranids were included, mean density was highest on unconsolidated 

sediments, primarily due to chalk bass, but biomass was higher on hardbottom (Figure 3.32). Largebodied groupers (Cephalopholis and Epinephelus spp.) were infrequent, primarily small in size, and 

were almost exclusively found on hardbottom (Figure 3.33). Three coney (Cephalopholis fulva) were 

sighted south of Cayos Caribe, while three graysby (Cephalopholis cruentata) and one red hind (Epinephelus guttatus) were documented in the area of Cayos de Pájaros (Figure 3.33a). All red hind and 

coney individuals were small adults, while graysby individuals were primarily juvenile/sub-adult. 

0 

1 

2 

3 

4 

5 

6 

7 

8 

Mean density (#/100 m2 ) 

0 

20 

40 

60 

80 

100 

120 

140 

160 

180 

200 

Mean Biomass (g/100 m2 ) 

0 

0.05 

0.1 

0.15 

0.2 

0.25 

0.3 

0.35 

Proportion 

Abundance 

Biomass 

a) 

b) 

c) 

Figure 3.31. Mean (±SE) a) density, and b) biomass, and c) proportional distribution 

of abundance and biomass of major fish families across unconsolidated sediment

sites. 

Baseline Assessment of Jobos Bay, Puerto Rico: Baseline Characterization 

3 - Baseline Characterization 78 
Baseline Assessment of Jobos Bay, Puerto Rico: Baseline Characterization

79 3 - Baseline Characterization

Figure 3.32. a) Spatial distribution, b) mean (±SE) density by habitat, c) mean (±SE) biomass by habitat, and d) size frequency

histogram of groupers, hamlets, and seabasses (Family Serranidae). 

Serranidae

Density (#/100 m2

)

0

1 - 10

11 - 50

51 - 100

101 - 120

Benthic Habitat

Coral Reef and Hardbottom

Unconsolidated Sediments

Mangrove

Land

JBNERR boundary

2

01234 0.5

Kilometers

0

1

2

3

4

5

6

7

8

Hardbottom Mangrove Unconsolidated 

Sediments

Mean density (#/100 m2)

0

10

20

30

40

50

60

70

Hardbottom Mangrove Unconsolidated 

Sediments

Mean biomass (g/100 m2)

0

10

20

30

40

50

60

70

80

0--5 5--10 10--15 15--20 20--25 25--30 30--35 >35

Frequency (%)

Size class

b) c)

d)

a)
Baseline Assessment of Jobos Bay, Puerto Rico: Baseline Characterization

80 3 - Baseline Characterization

Figure 3.33. a) Spatial distribution, b) mean (±SE) density by habitat, c) mean (±SE) biomass by habitat, and d) size frequency

histogram of large-bodied groupers (Cephalopholis and Epinephelus spp.).

Grouper

Density (#/100 m2

)

0

1

2 - 3

Benthic Habitat

Coral Reef and Hardbottom

Unconsolidated Sediments

Mangrove

Land

JBNERR boundary

2

01234 0.5

Kilometers

0

10

20

30

40

50

60

Hardbottom Mangrove Unconsolidated 

Sediments

Mean biomass (g/100 m2)

0

0.1

0.2

0.3

0.4

0.5

Hardbottom Mangrove Unconsolidated 

Sediments

Mean density (#/100 m2)

0

10

20

30

40

50

60

0--5 5--10 10--15 15--20 20--25 25--30 30--35 >35

Frequency (%)

Size class

b) c)

d)

a)
Baseline Assessment of Jobos Bay, Puerto Rico: Baseline Characterization 

Snappers (Lutjanidae) 

Snappers were detected among all investigated habitats but were most abundant in mangroves 

and nearshore environments (Figure 3.34). Lowest abundance and biomass were observed over 

unconsolidated sediments. Eight Lutjanid species were documented, with schoolmaster, yellowtail 

(Ocyurus chrysurus) and gray snapper accounting for the majority of observations. The remaining 

species were infrequently sighted. Size frequency was skewed toward smaller size classes. 

Schoolmaster were observed at 33% of survey transects and were most abundant in nearshore 

mangrove fringes and cays (Figure 3.35). A few individuals were observed on hardbottom habitat 

adjacent to the cays, while none were observed on unconsolidated sediments. The majority of 

schoolmaster were juveniles/subadults. All adult-sized individuals, about 4% of the total, were located 

on mangrove habitat. 

Gray snapper were observed in 16% of surveys and were almost exclusively associated with mangrove 

fringes and cays (Figure 3.36). The site with the highest abundance and biomass was located in 

a sheltered area in the northern portion of the JBNERR. Observed individuals were comprised 

exclusively of juveniles/sub-adults. 

In comparison to other Lutjanid species, highest abundance and biomass of yellowtail snapper were 

found on hardbottom habitats, while the species was largely absent from mangroves (Figure 3.37). 

The site with the highest abundance and biomass was offshore of Cayos de Barca. All observed 

individuals were juveniles/subadults. 

Grunts (Haemulidae) 

Fishes of the grunt family were present within 47% of survey transects across all habitat types. 

While mangrove habitat was characterized by highest mean abundance, biomass was generally 

higher at hardbottom habitat (Figure 3.38). The family was represented by seven species. French 

grunt (Haemulon flavolineatum) and porkfi sh (Anisotremus virginicus) were most frequently sighted 

and had the highest mean abundance and biomass of the Haemulid species. Tomtates (Haemulon 

aurolineatum) were infrequently observed (9% of survey transects). About 19% of observed grunts 

were small juveniles that could not be identified to the species level. 

French grunt was present in 24% of sites. The species was most commonly observed on hardbottom 

and mangrove habitat in the central and western portion of the study area (Figure 3.39). The site with 

the highest abundance and biomass was located on hardbottom adjacent to Cayos de Ratones. No 

individuals were observed on softbottom. Size frequency was skewed toward the juvenile/sub-adult 

size classes. 

Porkfish was present in 18% of survey transects. In contrast with H. flavolineatum, the species 

was most common on hardbottom and absent from mangrove habitat (Figure 3.40). The species 

was generally sighted in small numbers and was present both inside and outside the bay. The size 

distribution was about evenly divided between juveniles/sub-adults and small adults. 

3 - Baseline Characterization 81 
Baseline Assessment of Jobos Bay, Puerto Rico: Baseline Characterization

82 3 - Baseline Characterization

Figure 3.34. a) Spatial distribution, b) mean (±SE) density by habitat, c) mean (±SE) biomass by habitat, and d) size frequency

histogram of snappers (Family Lutjanidae).

Lutjanidae

Density (#/100 m2

)

0

1 - 10

11 - 50

51 - 100

>100

Benthic Habitat

Coral Reef and Hardbottom

Unconsolidated Sediments

Mangrove

Land

JBNERR boundary

2

01234 0.5

Kilometers

0

5

10

15

20

25

30

Hardbottom Mangrove Unconsolidated 

Sediments

Mean density (#/100 m2)

0

200

400

600

800

1000

1200

Hardbottom Mangrove Unconsolidated 

Sediments

Mean biomass (g/100 m2)

0

5

10

15

20

25

30

35

40

45

0--5 5--10 10--15 15--20 20--25 25--30 30--35 >35

Frequency (%)

Size class

b) c)

d)

a)
Baseline Assessment of Jobos Bay, Puerto Rico: Baseline Characterization

Figure 3.35. a) Spatial distribution, b) mean (±SE) density by habitat, c) mean (±SE) biomass by habitat, and d) size frequency

histogram of schoolmaster (Lutjanus apodus).

Schoolmaster

Density (#/100 m2

)

0

1 - 10

11 - 25

26 - 50

>50

Benthic Habitat

Coral Reef and Hardbottom

Unconsolidated Sediments

Mangrove

Land

JBNERR boundary

2

01234 0.5

Kilometers

0

2

4

6

8

10

12

14

16

Hardbottom Mangrove Unconsolidated 

Sediments

Mean density (#/100 m2)

0

100

200

300

400

500

600

700

800

Hardbottom Mangrove Unconsolidated 

Sediments

Mean biomass (g/100 m2)

0

5

10

15

20

25

30

35

40

45

0--5 5--10 10--15 15--20 20--25 25--30 30--35 >35

Frequency (%)

Size class

Juveniles/subadults

b) c)

d)

a)

83 3 - Baseline Characterization
Baseline Assessment of Jobos Bay, Puerto Rico: Baseline Characterization

84 3 - Baseline Characterization

Figure 3.36. a) Spatial distribution, b) mean (±SE) density by habitat, c) mean (±SE) biomass by habitat, and d) size frequency

histogram of gray snapper (Lutjanus griseus).

Gray snapper

Density (#/100 m2

)

0

1 - 10

11 - 25

26 - 50

>50

Benthic Habitat

Coral Reef and Hardbottom

Unconsolidated Sediments

Mangrove

Land

JBNERR boundary

2

01234 0.5

Kilometers

0

2

4

6

8

10

12

Hardbottom Mangrove Unconsolidated 

Sediments

Mean density (#/100 m2)

0

50

100

150

200

250

300

350

400

Hardbottom Mangrove Unconsolidated 

Sediments

Mean biomass (g/100 m2)

0

10

20

30

40

50

60

0--5 5--10 10--15 15--20 20--25 25--30 30--35 >35

Frequency (%)

Size class

Juveniles/subadults

b) c)

d)

a)
Baseline Assessment of Jobos Bay, Puerto Rico: Baseline Characterization

85 3 - Baseline Characterization

Figure 3.37. a) Spatial distribution, b) mean (±SE) density by habitat, c) mean (±SE) biomass by habitat, and d) size frequency

histogram of yellowtail snapper (Ocyurus chrysurus).

Yellowtail snapper

Density (#/100 m2

)

0

1 - 10

11 - 25

26 - 50

>50

Benthic Habitat

Coral Reef and Hardbottom

Unconsolidated Sediments

Mangrove

Land

JBNERR boundary

2

01234 0.5

Kilometers

0

1

2

3

4

5

6

Hardbottom Mangrove Unconsolidated 

Sediments

Mean density (#/100 m2)

0

20

40

60

80

100

120

140

Hardbottom Mangrove Unconsolidated 

Sediments

Mean biomass (g/100 m2)

0

10

20

30

40

50

60

0--5 5--10 10--15 15--20 20--25 25--30 30--35 >35

Frequency (%)

Size class

Juveniles/subadults

b) c)

d)

a)
Baseline Assessment of Jobos Bay, Puerto Rico: Baseline Characterization

86 3 - Baseline Characterization

Figure 3.38. a) Spatial distribution, b) mean (±SE) density by habitat, c) mean (±SE) biomass by habitat, and d) size frequency

histogram of grunts (Family Haemulidae).

Haemulidae

Density (#/100 m2

)

0

1 - 10

11 - 50

51 - 100

>100

Benthic Habitat

Coral Reef and Hardbottom

Unconsolidated Sediments

Mangrove

Land

JBNERR boundary

2

01234 0.5

Kilometers

0

2

4

6

8

10

12

14

16

18

Hardbottom Mangrove Unconsolidated 

Sediments

Mean density (#/100 m2)

0

50

100

150

200

250

300

350

Hardbottom Mangrove Unconsolidated 

Sediments

Mean biomass (g/100 m2)

0

5

10

15

20

25

30

35

40

0--5 5--10 10--15 15--20 20--25 25--30 30--35 >35

Frequency (%)

Size class

b) c)

d)

a)
Baseline Assessment of Jobos Bay, Puerto Rico: Baseline Characterization

87 3 - Baseline Characterization

Figure 3.39. a) Spatial distribution, b) mean (±SE) density by habitat, c) mean (±SE) biomass by habitat, and d) size frequency

histogram of French grunt (Haemulon fl avolineatum).

French grunt

Density (#/100 m2

)

0

1 - 10

11 - 25

26 - 50

>50

Benthic Habitat

Coral Reef and Hardbottom

Unconsolidated Sediments

Mangrove

Land

JBNERR boundary

2

01234 0.5

Kilometers

0

2

4

6

8

10

12

Hardbottom Mangrove Unconsolidated 

Sediments

Mean density (#/100 m2)

0

20

40

60

80

100

120

140

160

180

200

Hardbottom Mangrove Unconsolidated 

Sediments

Mean biomass (g/100 m2)

0

10

20

30

40

50

60

0--5 5--10 10--15 15--20 20--25 25--30 30--35 >35

Frequency (%)

Size class

Juveniles/subadults

b) c)

d)

a)
Baseline Assessment of Jobos Bay, Puerto Rico: Baseline Characterization

88 3 - Baseline Characterization

Figure 3.40. a) Spatial distribution, b) mean (±SE) density by habitat, c) mean (±SE) biomass by habitat, and d) size frequency

histogram of porkfi sh (Anisotremus virginicus).

Porkfish

Density (#/100 m2

)

0

1 - 2

3 

Benthic Habitat

Coral Reef and Hardbottom

Unconsolidated Sediments

Mangrove

Land

JBNERR boundary

2

01234 0.5

Kilometers

Juveniles/subadults

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

Hardbottom Mangrove Unconsolidated 

Sediments

Mean density (#/100 m2)

0

20

40

60

80

100

120

140

Hardbottom Mangrove Unconsolidated 

Sediments

Mean biomass (g/100 m2)

b) c)

d)

0

5

10

15

20

25

30

35

40

45

0--5 5--10 10--15 15--20 20--25 25--30 30--35 >35

Frequency (%)

Size class

a)
Baseline Assessment of Jobos Bay, Puerto Rico: Baseline Characterization 

Surgeonfi shes (Acanthuridae) 

Surgeonfishes were a common member of the Jobos Bay fish community, occurring in 53% of survey 

transects. Acanthurids were most common on hardbottom and were present at all but one hardbottom 

site. Sites with the highest abundance and biomass were located on hardbottom adjacent to the 

cays and on a patch reef landward of Cayos de Pájaros (Figure 3.41). Abundance and biomass of 

surgeonfish on unconsolidated sediments and mangrove were generally low. 

Ocean surgeonfish were sighted in 42% of surveys. The highest abundance and biomass were 

observed on hardbottom habitat, while the species was absent from mangrove (Figure 3.42). A 

large percentage (>40%) of individuals were small juveniles in the 0-5 cm size class, partly due to 

the presence of one large school of juveniles at a hardbottom site near Cayos de Pájaros. Larger 

juveniles/sub-adults accounted for the majority of the remainder of ocean surgeonfi sh individuals 

encountered during the surveys. 

Doctorfi sh (Acanthurus chirurgus) were present in a similar percentage (40%) of surveys as ocean 

surgeonfish but generally in lower abundance. Highest abundance and biomass occurred on 

hardbottom and were highly variable among sites within this habitat. The species was infrequent on 

unconsolidated sediments and mangrove (Figure 3.43). High species abundance and biomass were 

observed at a patch reef in the lagoon behind Cayos de Pájaros. The majority of individuals were 

small-medium sized adults, while only 15% of individuals were juveniles/sub-adults. 

Blue tangs (Acanthurus coeruleus) were present in 24% of surveys and were almost exclusively 

limited to hardbottom. The species was generally found in low abundance, with hotspots detected at 

two sites on fore reef adjacent to Cayos de Pájaros and Cayos Caribe (Figure 3.44). Over 60% of 

individuals were small adults within the 10-15 cm size class. 

Parrotfi shes (Scaridae) 

Parrotfishes were a common component of the Jobos fish community, occurring in 62% of survey 

transects. Highest mean density was observed on hardbottom habitat, with intermediate, but variable, 

levels in the mangrove fringes (Figure 3.45). Biomass was also greatest on hardbottom, with lower 

levels on mangrove as this habitat tended to be dominated by small juveniles. Of the nine species, 

striped parrotfish and redband parrotfish accounted for the highest mean abundance and biomass. 

Approximately 80% of Scarids were <20 cm, while one large yellowtail parrotfi sh (Sparisoma 

rubripinne) in the 30-35 cm size class was observed. 

Striped parrotfish was most common on hardbottom habitat. The species was not as frequently sighted 

in mangroves, but was patchily abundant where found. Areas with higher than average abundance 

include mangrove fringes in the lagoon and fore reef adjacent to the cays (Figure 3.46). The majority 

of individuals (>85%) were juveniles/sub-adults. 

Redband parrotfish was almost exclusively limited to hardbottom. The species was absent from 

mangrove and occurred in only one survey on unconsolidated sediments (Figure 3.47). While 

hardbottom densities were similar to striped parrotfish, redband parrotfish biomass tended to be 

higher as the size distribution was skewed towards slightly larger size classes. Approximately 35% of 

individuals were adult-sized. 

Stoplight parrotfi sh (Sparisoma viride) occurred only at hardbottom sites, generally in low densities. 

Otherwise there were no distinctive spatial patterns in the species distribution as it was present on 

reefs both within the bay and offshore of the cays (Figure 3.48). The majority of individuals were 

juveniles/sub-adults with a lesser percentage (17%) of fish in the smallest adult size class (15-20 cm). 

3 - Baseline Characterization 89 
Baseline Assessment of Jobos Bay, Puerto Rico: Baseline Characterization

90 3 - Baseline Characterization

Figure 3.41. a) Spatial distribution, b) mean (±SE) density by habitat, c) mean (±SE) biomass by habitat, and d) size frequency

histogram of surgeonfi shes (Family Acanthuridae).

Acanthuridae

Density (#/100 m2

)

0

1 - 10

11 - 50

51 - 100

>100

Benthic Habitat

Coral Reef and Hardbottom

Unconsolidated Sediments

Mangrove

Land

JBNERR boundary

2

01234 0.5

Kilometers

0

1

2

3

4

5

6

7

8

9

10

Hardbottom Mangrove Unconsolidated 

Sediments

Mean density (#/100 m2)

0

200

400

600

800

1000

1200

1400

1600

1800

2000

Hardbottom Mangrove Unconsolidated 

Sediments

Mean biomass (g/100 m2)

0

5

10

15

20

25

30

35

40

45

0--5 5--10 10--15 15--20 20--25 25--30 30--35 >35

Frequency (%)

Size class

b) c)

d)

a)
Baseline Assessment of Jobos Bay, Puerto Rico: Baseline Characterization

91 3 - Baseline Characterization

Figure 3.42. a) Spatial distribution, b) mean (±SE) density by habitat c) mean (±SE) biomass by habitat, and d) size frequency 

histogram of ocean surgeonfi sh (Acanthurus bahianus).

Ocean surgeonfish

Density (#/100 m2

)

0

1 - 10

11 - 25

26 - 50

>100

Benthic Habitat

Coral Reef and Hardbottom

Unconsolidated Sediments

Mangrove

Land

JBNERR boundary

2

01234 0.5

Kilometers

0

2

4

6

8

10

12

14

Hardbottom Mangrove Unconsolidated 

Sediments

Mean density (#/100 m2)

0

50

100

150

200

250

300

Hardbottom Mangrove Unconsolidated 

Sediments

Mean biomass (g/100 m2)

0

5

10

15

20

25

30

35

40

45

0--5 5--10 10--15 15--20 20--25 25--30 30--35 >35

Frequency (%)

Size class

Juveniles/subadults

b) c)

d)

a)
Baseline Assessment of Jobos Bay, Puerto Rico: Baseline Characterization

92 3 - Baseline Characterization

Figure 3.43. a) Spatial distribution, b) mean (±SE) density by habitat c) mean (±SE) biomass by habitat, and d) size frequency 

histogram of doctorfi sh (Acanthurus chirurgus).

Doctorfish

Density (#/100 m2

)

0

1 - 10

11 - 25

26 - 50

>50

Benthic Habitat

Coral Reef and Hardbottom

Unconsolidated Sediments

Mangrove

Land

JBNERR boundary

2

01234 0.5

Kilometers

0

1

2

3

4

5

6

7

8

9

Hardbottom Mangrove Unconsolidated 

Sediments

Mean density (#/100 m2)

0

200

400

600

800

1000

1200

1400

1600

Hardbottom Mangrove Unconsolidated 

Sediments

Mean biomass (g/100 m2)

0

5

10

15

20

25

30

35

40

45

50

0--5 5--10 10--15 15--20 20--25 25--30 30--35 >35

Frequency (%)

Size class

Juveniles/subadults

b) c)

d)

a)
Baseline Assessment of Jobos Bay, Puerto Rico: Baseline Characterization

93 3 - Baseline Characterization

Figure 3.44. a) Spatial distribution, b) mean (±SE) density by habitat c) mean (±SE) biomass by habitat, and d) size frequency 

histogram of blue tang (Acanthurus coeruleus).

Blue tang

Density (#/100 m2

)

0

1 - 10

11 - 25

26 - 50

>50

Benthic Habitat

Coral Reef and Hardbottom

Unconsolidated Sediments

Mangrove

Land

JBNERR boundary

2

01234 0.5

Kilometers

0

1

2

3

4

5

6

Hardbottom Mangrove Unconsolidated 

Sediments

Mean density (#/100 m2)

0

50

100

150

200

250

Hardbottom Mangrove Unconsolidated 

Sediments

Mean biomass (g/100 m2)

0

10

20

30

40

50

60

70

0--5 5--10 10--15 15--20 20--25 25--30 30--35 >35

Frequency (%)

Size class

Juveniles/subadults

b) c)

d)

a)
Baseline Assessment of Jobos Bay, Puerto Rico: Baseline Characterization

94 3 - Baseline Characterization

Figure 3.45. a) Spatial distribution, b) mean (±SE) density by habitat c) mean (±SE) biomass by habitat, and d) size frequency 

histogram of parrotfi shes (Family Scaridae).

Scaridae

Density (#/100 m2

)

0

1 - 10

11 - 50

51 - 100

>100

Benthic Habitat

Coral Reef and Hardbottom

Unconsolidated Sediments

Mangrove

Land

JBNERR boundary

2

01234 0.5

Kilometers

0

2

4

6

8

10

12

14

16

18

Hardbottom Mangrove Unconsolidated 

Sediments

Mean density (#/100 m2)

0

50

100

150

200

250

300

350

400

450

Hardbottom Mangrove Unconsolidated 

Sediments

Mean biomass (g/100 m2)

0

5

10

15

20

25

30

35

40

45

50

0--5 5--10 10--15 15--20 20--25 25--30 30--35 >35

Frequency (%)

Size class

b) c)

d)

a)
Baseline Assessment of Jobos Bay, Puerto Rico: Baseline Characterization

95 3 - Baseline Characterization

Figure 3.46. a) Spatial distribution, b) mean (±SE) density by habitat c) mean (±SE) biomass by habitat, and d) size frequency 

histogram of striped parrotfi sh (Scarus iseri).

Striped parrotfish

Density (#/100 m2

)

0

1 - 5

6 - 10

11 - 20

>20

Benthic Habitat

Coral Reef and Hardbottom

Unconsolidated Sediments

Mangrove

Land

JBNERR boundary

2

01234 0.5

Kilometers

0

1

2

3

4

5

6

7

8

9

Hardbottom Mangrove Unconsolidated 

Sediments

Mean density (#/100 m2)

0

20

40

60

80

100

120

Hardbottom Mangrove Unconsolidated 

Sediments

Mean biomass (g/100 m2)

0

5

10

15

20

25

30

35

40

45

50

0--5 5--10 10--15 15--20 20--25 25--30 30--35 >35

Frequency (%)

Size class

Juveniles/subadults

b) c)

d)

a)
Baseline Assessment of Jobos Bay, Puerto Rico: Baseline Characterization

96 3 - Baseline Characterization

Figure 3.47. a) Spatial distribution, b) mean (±SE) density by habitat c) mean (±SE) biomass by habitat, and d) size frequency 

histogram of redband parrotfi sh (Sparisoma aurofrenatum).

Redband parrotfish

Density (#/100 m2

)

0

1 - 5

6 - 10

11 - 20

>20

Benthic Habitat

Coral Reef and Hardbottom

Unconsolidated Sediments

Mangrove

Land

JBNERR boundary

2

01234 0.5

Kilometers

0

1

2

3

4

5

6

7

8

Hardbottom Mangrove Unconsolidated 

Sediments

Mean density (#/100 m2)

0

20

40

60

80

100

120

140

160

180

Hardbottom Mangrove Unconsolidated 

Sediments

Mean biomass (g/100 m2)

0

5

10

15

20

25

30

35

40

45

0--5 5--10 10--15 15--20 20--25 25--30 30--35 >35

Frequency (%)

Size class

Juveniles/subadults

b) c)

d)

a)
Baseline Assessment of Jobos Bay, Puerto Rico: Baseline Characterization

97 3 - Baseline Characterization

Figure 3.48. a) Spatial distribution, b) mean (±SE) density by habitat c) mean (±SE) biomass by habitat, and d) size frequency 

histogram of stoplight parrotfi sh (Sparisoma viride).

Stoplight parrotfish

Density (#/100 m2

)

0

1 - 5

6 - 10

11 - 20

>20

Benthic Habitat

Coral Reef and Hardbottom

Unconsolidated Sediments

Mangrove

Land

JBNERR boundary

2

01234 0.5

Kilometers

0

10

20

30

40

50

60

70

80

90

Hardbottom Mangrove Unconsolidated 

Sediments

Mean biomass (g/100 m2)

0

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

1.8

2

Hardbottom Mangrove Unconsolidated 

Sediments

Mean density (#/100 m2)

0

5

10

15

20

25

30

35

0--5 5--10 10--15 15--20 20--25 25--30 30--35 >35

Frequency (%)

Size class

Juveniles/subadults

b) c)

d)

a)
Baseline Assessment of Jobos Bay, Puerto Rico: Baseline Characterization 

3 - Baseline Characterization

Wrasses (Labridae) 

Wrasses were commonly sighted, occurring in 64% of surveys overall and all but two hardbottom 

surveys. Mean density and biomass were highest on hardbottom (Figure 3.49). Sites with particularly 

high density include sites on the fore reef seaward of the cays. Due to their typically small size, 

biomass was typically low and did not exceed 500 g/100 m2

 in any survey. Labrids were generally 

present in smaller numbers on unconsolidated sediments and were largely absent in mangroves. 

Eleven Labrid species were documented, with bluehead wrasse, blackear wrasse (Halichoeres 

radiatus) and slippery dick (Halichoeres bivittatus) accounting for the highest site frequency, density 

and biomass. Hogfi sh (Lachnolaimus maximus), a common species in Puerto Rico finfish fisheries, 

were present in only two survey transects. 

Goatfi shes (Mullidae) 

Fishes of the goatfish family (Mullidae) were present in 27% of survey transects. The site with the 

highest abundance and biomass was located on unconsolidated sediments in close proximity to reef 

(Figure 3.50). All other occurrences of mullids were on hardbottom. The family was represented by 

two species, the spotted goatfi sh (Pseudupeneus maculatus), which was most common, and yellow 

goatfi sh (Mulloidichthys martinicus). All individuals were <15 cm in length, which is below the size at 

maturity for both species. 

Damselfi shes (Pomacentridae) 

Damselfishes were present across all bottom types, occurring in 76% of survey transects. Highest 

abundance and biomass were found on hardbottom habitats, with intermediate levels in the fringing 

mangrove (Figure 3.51). Sites with a density of >50 fi sh/100 m2

 were located on reef adjacent to 

Cayos de Pájaros and Cayos Caribe. Nine damselfish species were found during the Jobos Bay 

study, with longfi n damselfi sh (Stegastes diencaeus), beaugregory (Stegastes leucostictus) and 

bicolor damselfi sh (Stegastes partitus) having the greatest site frequency and accounting for the 

highest mean density. Damselfish species with the highest mean biomass were the longfi n damselfish 

and beaugregory. The size frequency of damselfishes was skewed towards smaller size classes, with 

>65% of individuals less than 5 cm in length. 

98 

Space left intentionally blank. 
Baseline Assessment of Jobos Bay, Puerto Rico: Baseline Characterization

99 3 - Baseline Characterization

Figure 3.49. a) Spatial distribution, b) mean (±SE) density by habitat c) mean (±SE) biomass by habitat, and d) size frequency 

histogram of wrasses (Family Labridae).

Labridae

Density (#/100 m2

)

0

1 - 10

11 - 50

51 - 100

>100

Benthic Habitat

Coral Reef and Hardbottom

Unconsolidated Sediments

Mangrove

Land

JBNERR boundary

2

01234 0.5

Kilometers

0

5

10

15

20

25

30

35

40

45

Hardbottom Mangrove Unconsolidated 

Sediments

Mean density (#/100 m2)

0

20

40

60

80

100

120

140

160

Hardbottom Mangrove Unconsolidated 

Sediments

Mean biomass (g/100 m2)

0

10

20

30

40

50

60

70

0--5 5--10 10--15 15--20 20--25 25--30 30--35 >35

Frequency (%)

Size class

b) c)

d)

a)
Baseline Assessment of Jobos Bay, Puerto Rico: Baseline Characterization

100 3 - Baseline Characterization

Figure 3.50. a) Spatial distribution, b) mean (±SE) density by habitat c) mean (±SE) biomass by habitat, and d) size frequency 

histogram of goatfi shes (Family Mullidae).

Mullidae

Density (#/100 m2

)

0

1 - 5

6 - 10

11 - 20

>20

Benthic Habitat

Coral Reef and Hardbottom

Unconsolidated Sediments

Mangrove

Land

JBNERR boundary

2

01234 0.5

Kilometers

0

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

1.8

2

Hardbottom Mangrove Unconsolidated 

Sediments

Mean density (#/100 m2)

0

10

20

30

40

50

60

70

80

Hardbottom Mangrove Unconsolidated 

Sediments

Mean biomass (g/100 m2)

0

5

10

15

20

25

0--5 5--10 10--15 15--20 20--25 25--30 30--35 >35

Frequency (%)

Size class

b) c)

d)

a)
Baseline Assessment of Jobos Bay, Puerto Rico: Baseline Characterization

101 3 - Baseline Characterization

Figure 3.51. a) Spatial distribution, b) mean (±SE) density by habitat c) mean (±SE) biomass by habitat, and d) size frequency 

histogram of damselfi shes (Family Pomacentridae).

Pomacentridae

Density (#/100 m2

)

0

1 - 10

11 - 50

51 - 100

>100

Benthic Habitat

Coral Reef and Hardbottom

Unconsolidated Sediments

Mangrove

Land

JBNERR boundary

2

01234 0.5

Kilometers

0

5

10

15

20

25

30

35

Hardbottom Mangrove Unconsolidated 

Sediments

Mean density (#/100 m2)

0

20

40

60

80

100

120

140

160

180

Hardbottom Mangrove Unconsolidated 

Sediments

Mean biomass (g/100 m2)

0

10

20

30

40

50

60

70

0--5 5--10 10--15 15--20 20--25 25--30 30--35 >35

Frequency (%)

Size class

b) c)

d)

a)
Baseline Assessment of Jobos Bay, Puerto Rico: Baseline Characterization

102 3 - Baseline Characterization

Macroinvertebrates

No spiny lobster (Panulirus argus) were observed within any of the surveys. Only two queen conch 

(Eustrombus gigas) were observed in two of the 45 surveyed transects. Both conch were immature 

juveniles and recorded on unconsolidated sediment sites within the bay. No mature conch were 

observed. 

A total of 129 long-spined urchins (Diadema antillarum) were observed in fi ve (four hard and one soft) 

survey transects. Although only observed at a few sites, long-spined urchins were patchily abundant 

where found. Two sites accounted for approximately 97% of the total urchins recorded. Eighty-one 

individuals were recorded on a hardbottom survey site adjacent to Cayos de Ratones, while 44 

individuals were observed at an unconsolidated sediment site in the lagoon near Cayos de Pájaros 

(Figure 3.52). 

Figure 3.52. Spatial distribution of the long-spined sea urchin (Diadema antillarum).

Diadema antillarum

Density (#/100 m2

)

0

1

2

44

81

Benthic habitat

Coral Reef and Hardbottom

Unconsolidated Sediments

Mangrove

Land

JBNERR boundary

2

01234 0.5

Kilometers
Baseline Assessment of Jobos Bay, Puerto Rico: Baseline Characterization

103 3 - Baseline Characterization

Marine Debris

A total of eight marine debris items were recorded in three survey transects (Table 3.2). Items ranged 

from glass bottles to a tire. The majority of debris was observed in two surveys located in the mangrove 

cays (Figure 3.53). Several of the items were colonized by various algal groups (i.e., cyanobacteria, 

crustose algae) and a net with rope was found entangled in the mangrove roots.

Table 3.2. Number, type, area, and degree of fouling on marine debris recorded in Jobos Bay transects.

Station Debris Area Number Debris Type Colonized By (cm2

)

1H06 1 Glass beer bottle 24 Uncolonized

1M17 2

Bottle

Whistle

150

10

Crustose algae (CCA)

Uncolonized

Piece of rope (used for net) 300 Uncolonized

Tire (tire diameter = 1 m) 7850 Cyanobacteria

1M30 5 Glass soda bottle 150 Cyanobacteria

Tin can 400 Cyanobacteria

Net with rope 160 Entangled in mangrove roots

Figure 3.53. Spatial distribution of marine debris.

Marine Debris

Density (#/100 m2

)

0

1

2

5

Benthic habitat

Coral Reef and Hardbottom

Unconsolidated Sediments

Mangrove

Land

JBNERR boundary

2

01234 0.5

Kilometers
Baseline Assessment of Jobos Bay, Puerto Rico: Baseline Characterization 

104 3 - Baseline Characterization

3.4. CONCLUSIONS 

Although there are few historical studies in Jobos Bay with which to compare current conditions, the 

area has been subject to region-wide stresses that have affected the wider Caribbean in the last few 

decades, including a widespread die-off of D. antillarum in the 1980s, mass Acropora species mortality 

due to white band disease, coral bleaching, overfishing, and tropical cyclones. A recent meta-analysis 

indicates that live coral cover in the Caribbean has declined by 80% over the last three decades (Gardner 

et al., 2003). This loss has led to a “flattening,” or decline in rugosity, of reefs over time (Alvarez-Filip et 

al., 2009). Caribbean region-wide declines in fish abundance have also been documented (Paddack et 

al., 2009). Elkhorn (A. palmata; Figure 3.54) and staghorn coral (A. cervicornis), which were formerly 

dominant reef builders in shallow and 

intermediate fore reef communities, 

respectively, have been devastated 

by white-band disease (Aronson 

and Precht, 2001). In Puerto Rico, 

recovery from the initial 1980’s 

outbreak has been limited and 

acroporid populations have declined 

significantly at locations island-wide 

where they were formerly abundant 

(Weil et al., 2002). While A. palmata 

was reported to be highly abundant 

on the reef crest in the 1970s (PRNC 

1972), it was rarely sighted in this 

study and absent from all survey 

quadrats. The presence of Acropora 

rubble at several locations observed 

both during this study and by GarcíaSais et al. (2003) are additional 

evidence of their former abundance. 

Puerto Rican reefs experienced further declines in coral cover following the recent 2005 bleaching 

event (García-Sais et al., 2008). In addition, local anthropogenic stresses to the Jobos Bay marine 

environment include thermal discharges from the Aguirre thermoelectric power plant, sewage inputs, 

mangrove deforestation, and runoff from agriculture and developed lands. 

Reef and hardbottom benthic communities in Jobos Bay appear to be similar to other regions of 

Puerto Rico and the USVI. Since 2001, BB has regularly monitored habitat and fi sh communities 

using the same survey methodology in other U.S. Caribbean locations, including the BIRNM in St. 

Croix, USVI (Pittman et al., 2008) and La Parguera in southwestern Puerto Rico (Pittman et al., 

2010). Additionally, a characterization of reef/hardbottom communities was recently conducted in 

Vieques, Puerto Rico (Bauer and Kendall, 2010). Hard coral cover in nearby La Parguera averaged 

5.3 ± 0.3% over a period of seven years (2001-2007; Pittman et al., 2010). The authors also detected 

a decreasing trend in hard coral cover over time. Similarly, hard coral cover in St. Croix averaged 5.6 

± 0.5% over 2001-2006 (Pittman et al., 2008). In Vieques, measured coral cover from the 2007 survey 

averaged 3.4 ± 0.5% (Bauer and Kendall, 2010). At all of these locations, turf algae and macroalgae 

were the dominant benthic cover types on reef and hardbottom. 

Additionally, fish community metrics and species composition in Jobos Bay appear to be similar 

to that of La Parguera in SW Puerto Rico (Pittman et al., 2010). Both areas are characterized by 

Figure 3.54. Elkhorn coral (Acropora palmata) in Jobos Bay. Photo: NOAA CCMA. 
a diverse assemblage of benthic 

habitat types. In particular, both 

regions contain extensive networks 

of mangrove forest and offshore 

cays fringed by reef tracts. While 

the La Parguera study area lacks 

a substantial “inner bay” of similar 

scope as Jobos, the central and 

outer portions of Jobos Bay, 

which likely receive greater water 

exchange than the more protected 

inner bay, were primarily surveyed 

here. Mean total fish biomass was 

similar across habitat types in Jobos 

and La Parguera (Figure 3.55). 

While biomass appears to be lower 

in Jobos than Vieques (hardbottom 

only) and St. Croix (hardbottom and 

unconsolidated sediments only), results of non-parametric tests indicate no significant difference in 

biomass in the Jobos Bay region compared to the other study areas (p>0.05). This is likely influenced 

at least in part by the lower sample size and relatively high variability in the Jobos and Vieques 

datasets. 

Recent surveys of fish communities in Jobos Bay include García and Castro (1997) and García-Sais et 

al. (2003). In both studies, transects were conducted on both reef crest and deeper slope hardbottom 

structure near Cayos de Barca and Cayos Caribe. Similar to the findings of this characterization, the 

fish community consisted largely of small herbivores such as damselfish, parrotfish, and surgeonfish, 

and small invertivores (e.g., wrasses; García and Castro, 1997; García-Sais et al., 2003). Snappers, 

grunts, and other species of commercial importance were generally low in abundance and small 

sized. 

While CEAP Special Emphasis Watersheds (SEW) are distributed nationwide, only one other coastal 

watershed, the Choptank River in the Chesapeake Bay, has been designated a SEW. As Jobos 

Bay represents the first coastal SEW established in the tropics, this project represents a unique 

opportunity to assess the effect of agricultural conservation practices on a coral reef ecosystem. 

Land-based sources of pollution are widely attributed to be a contributing factor to coral reef decline 

(e.g., Waddell and Clarke, 2008), but identifying the relative contribution of individual anthropogenic 

activities to reef degradation is challenging, especially at the regional level (Downs et al., 2005; 

Fabricius, 2005; Wolanski et al., 2009). Sedimentation has been found to smother corals, lead to 

decreased growth rates, and reduce recruitment, but the effects vary among coral species, sediment 

types, and environmental conditions (see review in Fabricius, 2005). Further, linkages between 

chemical contaminants and coral health are poorly understood (Pait et al., 2007; also see Chapter 

4). Understanding these cause and effect relationships are critical to effective management and 

restoration practices. 

Similar efforts that also seek to reduce degradation of reef environments are underway in Hawaii 

(Conservation Reserve Enhancement Program, http://www.fsa.usda.gov/) and Micronesia (Richmond 

et al., 2007). However, there is little in the literature that demonstrates the effects of restoration efforts 

on a reef ecosystem. It is likely that more immediate benefits of the practices will be evident in 

8000 

7000

6000 

5000 

Jobos 

La Parguera 

Vieques 

St. Croix 

Hardbottom Mangrove Unconsolidated 

Sediments 

Biomass (g/100m2) 4000 

3000 

2000 

1000 

0

Figure 3.55. Estimated mean (±SE) biomass in Jobos Bay in June 2009 compared

to other CCMA Biogeography Branch monitoring locations: Vieques, PR (2007; 

Bauer and Kendall 2010) La Parguera, PR (2001-2007; Pittman et al., 2010), St.

Croix (2003-2006; Pittman et al,. 2008).

Baseline Assessment of Jobos Bay, Puerto Rico: Baseline Characterization 

105 3 - Baseline Characterization
Baseline Assessment of Jobos Bay, Puerto Rico: Baseline Characterization 

106 3 - Baseline Characterization

reduced sediment and nutrient loads to the Jobos Bay system (see Chapters 4 and 5). Improvement 

to biological metrics such as live coral cover and fish abundance will ultimately require a reduction 

in multiple stressors, many of which are present at not only local but also regional and global scales 

(e.g., climate change, ocean acidifi cation, overfishing). 

In addition, it should be noted that agricultural land represents only 11% of total land use within the 

watershed (Zitello et al., 2008). However, historically almost the entire watershed was cultivated by 

sugar cane (see Chapter 1). Although much of this land has since been re-vegetated following the 

demise of sugarcane production, Zitello et al. (2008) noted that re-vegetated agriculture fi elds and 

pasture have a higher frequency of disturbance and don’t necessarily provide the same ecosystem 

services as naturally vegetated lands. Ultimately, the CEAP measures are likely to be most effective 

if efforts are simultaneously taken to mitigate other sources of runoff into Jobos Bay. 

A few caveats should be considered when interpreting the results from this study. Compared to other 

study locales within the CREM project, the sample size was relatively low (e.g., 45 in Jobos Bay 

compared to 90 surveyed annually in La Parguera). While the number of sample sites appear to be 

adequate to characterize differences in community metrics among the broad habitat strata, sample 

size was not adequate to characterize among finer scale habitats within strata, or among the three 

geographic strata (Inshore, Offshore, Shelf). Increased sample size would improve statistical power 

for detecting changes in metrics over time and should be considered when planning subsequent 

monitoring. Continued monitoring of permanent sites established by García-Sais et al. (2003) would 

provide further information on long-term changes in the ecosystem. 

Additional challenges should be considered when conducting future monitoring of the Jobos Bay 

marine ecosystem. Several planned survey sites were not sampled because of high turbidity. It may 

be that the visual survey method by divers is not the most effective means of surveying these regions. 

Additionally, diving was not suitable to explore deeper (>100 ft) areas of the shelf, meaning that 

a potentially important part in the Jobos Bay ecosystem has not been characterized. Alternative 

methods (e.g., trawl nets, traps) could be explored to fully characterize fish populations in areas 

characterized by poor visibility or depths that exceed the limits of diving. 

ACKNOWLEDGEMENTS 

Funding for this work was provided by NOAA’s Coral Reef Conservation Program (CRCP) and the 

U.S. Department of Agriculture (USDA) Natural Resources Conservation Service (NRCS). Many 

thanks to Captain Angel Nazario (Aquanauta) and his assistant Joel (Joito) Rivera and Claudio Burgos 

(JBNERR) for getting us safely to and from our sites. Angel Dieppa (JBNERR) provided invaluable 

logistical support before and during the survey. Charles Menza assisted in the collection of fi eld data. 

Thanks to Matthew Kendall, Matthew Poti, Jorge “Reni” García-Sais, and Angel Dieppa for providing 

useful comments and editorial assistance. 

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109 3 - Baseline Characterization 
Chapter 4
Baseline Assessment of Jobos Bay, Puerto Rico: Contaminants 

Contaminants in Sediments and Coral Tissues of Jobos Bay 

David R. Whitall1,5, Anthony S. Pait1, Dennis Apeti1, Angel Dieppa2, Sarah E. Newton1,3, Lia Brune1,4, Chris Caldow1, 

Andrew L. Mason1 and John Christensen1
 

4.1. INTRODUCTION 

The goal for this component of the ecosystem characterization of Jobos Bay was to quantify the level 

of chemical contaminants in sediments from the Bay and in coral tissues from the surrounding coral 

reef ecosystems. 

The objectives were to: 

1. Collect and analyze sediments from sites from the Bay, including within the Jobos Bay National 

Estuarine Research Reserve (JBNERR or Reserve), for organic (e.g., hydrocarbons) and 

inorganic (e.g., trace elements, typically metals) contaminants; 

2. Collect and analyze samples of mustard hill coral (Porites astreoides) for presence and 

magnitude of the same organic and inorganic contaminants. 

4.2. METHODS 

4.2.1. Sampling Design 

In order to assess the overall status of the ecosystem, and to be able to make spatially explicit 

conclusions about how contaminants vary geographically in the system, a stratified random sampling 

design was employed. Using this approach, all areas had an equal chance of being selected for 

contaminant characterization. As a result, no samples were specifically collected to represent 

background conditions in these areas. 

For sediment samples, three geographic strata were initially articulated: inner bay (INR), central bay 

(CNT), and outer bay (OTR). Within the central bay, a fourth strata (NER) was created, representing 

the subset of the central bay containing JBNERR. This additional stratum allows the hypothesis that 

the management of the Reserve might have an impact on the environmental quality of the system to 

be tested. However, it is acknowledged that, like many reserve boundaries, this does not represent 

an ecological boundary, and the reserve must be treated as part of the larger ecosystem. In each 

of these four strata, 10 sites were randomly selected. If a site could not be sampled (e.g., if the site 

was inaccessible due to shallow water depth) a pre-selected randomly determined alternate site from 

within that strata was sampled. Sediment strata were constructed from existing benthic habitat maps 

(Kendall et al., 2001) and included all non-hard bottom sediments. 

In addition to the stratified random sediment sites, targeted sediment sample sites (SWP) were colocated with four pre-existing long term water quality monitoring sites operated by the JBNERR as 

part of the National Estuarine Research Reserve System (NERRS) System-Wide Monitoring Program 

(SWMP). By chance, one of these sites overlapped with one of the randomly selected sites (CNT16), 

meaning that there were a total of 41 randomly selected sediment sites, and three additional targeted 

sediment sites. Sediments were collected from 44 total sites in May 2008 (Figure 4.1). 

111 4 - Contaminants 

1

 Center for Coastal Monitoring and Assessment, National Centers for Coastal Ocean Science, National Ocean Service, National 

Oceanic and Atmospheric Administration 

2 Jobos Bay National Estuarine Research Reserve 

3 University of Arkansas Pine Bluff 

4

 University of Florida 

3

 Corresponding author: dave.whitall@noaa.gov 
Figure 4.1. Sediment sampling sites using a stratified random sampling design. 

Baseline Assessment of Jobos Bay, Puerto Rico: Contaminants 

112 4 - Contaminants 

The coral sampling scheme divided the hard bottom habitats of the study area into “nearshore” and 

“offshore” strata. Within each stratum, eight sites were randomly selected. If a site could not be 

sampled (e.g., due to a lack of coral, or the site being inaccessible) a pre-selected randomly determined 

alternate site from within that strata was sampled. Coral tissue was collected from 16 sites in June 

2009 (Figure 4.2). Porites astreoides was chosen for this study as it is a common species of coral in 

Florida, the Bahamas and the Caribbean (Humann and DeLoach, 2002), and occurs throughout the 

study area. Colonies of P. astreoides are generally massive but are often found as encrusting forms, 

particularly in shallow, surging waters (Veron, 2000). Furthermore, previous studies (Pait et al., 2009, 

2010) quantified contaminants in P. astreoides in other systems in Puerto Rico. 

Figure 4.2. Coral sampling sites using a stratified random sampling design. 
4.2.2. Field Methods 

Sediment samples were collected

using standard NOAA National

Status and Trends (NS&T) Program 

protocols (Lauenstein and Cantillo,

1998). Sampling was conducted

aboard the vessel Estuarino using 

a GPS programmed with the

station coordinates. A modifi ed Van 

Veen sediment grab was deployed 

to collect the sediment samples

(Figure 4.3). Rocks, large coral or

shell fragments or bits of seagrass 

present in the grab were removed. 

If an individual grab did not result

in 200-300 g of sediment, a second 

grab was made and composited with 

material from the first grab. If enough 

sediment had not been collected

after three deployments of the grab, 

the site was abandoned and the boat 

moved on to an alternate, randomly 

preselected site. 

To avoid contamination of samples 

by equipment and cross contamination between samples, the grab was 

scrubbed with a brush, then rinsed 

with site water, and all of the equipment was rinsed with acetone followed by site water just prior to use. Personnel handling the samples 

also wore disposable nitrile gloves. The top 3 cm of sediment were collected from the sediment grab 

using a Kynar-coated sediment scoop. Sediments were placed into a certified clean (IChem®) 250 ml 

labeled jar, capped and then placed on ice in a cooler. Sediments for grain size analysis were placed 

in a WhirlPack® bag, sealed and placed on ice in a cooler. Upon returning to the JBNERR lab, sediment samples were frozen (-15°C). The WhirlPack® bags for grain size analysis were refrigerated 

(4°C), to avoid altering the grain size structure of the sediment that could occur during freezing. A 

suite of water parameters (dissolved oxygen, temperature, salinity, and conductivity) were measured 

at each site using a YSI® salinity/conductivity/temperature meter. The instrument probe was submerged to a depth of approximately 0.5 m. 

For coral tissue samples, a Puerto Rico Department of Natural and Environmental Resources (DNER) 

Ranger boat was used as the sampling platform. The coral samples were taken by NOAA SCUBA 

divers in June 2009 using a hammer and a punch made from titanium (not a target trace element for 

this project). Prior to each use, the punch was rinsed with acetone and site water to minimize crosscontamination. 

Divers collecting the coral samples also wore disposable nitrile gloves. The diver hammered the 

titanium punch into the coral head which produced a coral core with a diameter of approximately 

1.5 cm and a core length 1.5 cm. Approximately 20 cores were taken at each site and placed in an 

IChem® certified clean 250 mL jar while underwater. The jar was capped and brought to the surface, 

Figure 4.3. Project scientists lower modified van Veen grab for sediment collections. 

Photo: NOAA Center for Coastal Monitoring and Assessment (CCMA). 

Baseline Assessment of Jobos Bay, Puerto Rico: Contaminants 

4 - Contaminants 113 
 

Baseline Assessment of Jobos Bay, Puerto Rico: Contaminants 

114 4 - Contaminants

drained of water and placed on ice. At the end of each day, the samples were placed in a freezer 

(-15°C) at the JBNERR. At the end of the mission, samples were shipped by overnight courier to the 

laboratory (TDI Brooks, College Station, TX) for analyses. 

4.2.3. Chemical Contaminants Analyzed 

The list of chemical contaminants analyzed in the sediment and coral samples for this project is shown 

in Table 4.1. This is the same suite of analytes quantified nationwide as part of NOAA’s NS&T Program. 

For over 20 years, NS&T has monitored the Nation’s estuarine and coastal waters for chemical 

contaminants in bivalve mollusk tissues and sediments. Work to characterize chemical contaminants 

as part of the Center for Coastal Monitoring and Assessment’sA (CCMA) ecological characterizations 

in tropical waters, represents a recent expansion of NS&T activities. NS&T regularly quantifies 

approximately 150 organic and inorganic contaminants. The compounds analyzed include 58 

polycyclic aromatic hydrocarbons (PAHs), 31 organochlorine pesticides, 38 polychlorinated biphenyls 

(PCBs), four butyltins, and 16 trace and major elements. All samples were analyzed using NS&T 

analytical protocols. 

The analytical protocols for organics (Kimbrough et al., 2006) and trace and major elements (Kimbrough 

and Lauenstein, 2006) have previously been published. Each of the contaminant classes analyzed 

for this project are discussed below. 

4.2.3.1. Polycyclic aromatic hydrocarbons (PAHs) 

Polycyclic aromatic hydrocarbons (PAHs) are associated with the use and combustion of fossil fuels 

(e.g., oil and gas) and other organic materials (e.g., wood). Natural sources of PAHs include forest 

fires and volcanoes. The PAHs analyzed are two to six ring aromatic compounds. PAHs were analyzed 

using gas chromatography/mass spectrometry in the selected ion monitoring (SIM) mode. 

Environmental Effects of PAHs 

An extensive amount of research on the accumulation and effects of PAHs has been conducted on 

aquatic organisms; however, very little research has been carried out to address the effects of PAHs 

on corals. Because of their hydrophobic nature, PAHs readily accumulate in marine organisms through 

the body surface, gills, or through the diet (Neff, 1985). Exposure to PAHs has been associated 

with oxidative stress, effects on the immune system and endocrine system, and developmental 

abnormalities (Hylland, 2006). 

In addition, a number of PAHs including benzo[a]pyrene, benz[a]anthracene, chrysene, benzo[b] 

fluoranthene, benzo[k]fluoranthene, dibenzo[a,h]anthracene, and indeno[1,2,3-c,d]pyrene are 

likely carcinogens (USDHHS, 1995). The carcinogenic potential of PAHs is associated with their 

metabolism by Phase I cytochrome P450 enzymes, generating reactive epoxides which can bind to 

cellular components such as deoxyribonucleic acid (DNA; Neff, 1985; Hylland, 2006). In addition to the 

living tissues of corals, PAHs can also accumulate in the zooxanthellae, the symbiotic photosynthetic 

dinoflagellate algae found within coral tissues. Bioaccumulation appears to be related to the lipid 

content of both (Kennedy et al., 1992). While the simple accumulation of PAHs by corals is not an 

impact by itself, the accumulation of a chemical contaminant in an organism increases the likelihood 

of adverse effects. Solbakken et al. (1984) showed that both phenanthrene and naphthalene were 

accumulated by the brain coral Diploria strigosa and green cactus coral Madracis decactis, and that the 

lower molecular weight naphthalene was eliminated at a higher rate than phenanthrene (Solbakken et 

al., 1984). The PAHs fluoranthene and pyrene have been shown to be toxic to adult corals, particularly 

A The Center for Coastal Monitoring and Assessment (CCMA) is a part of National Oceanic and Atmospheric Administration (NOAA), National Ocean 

Service (NOS), National Centers for Coastal Ocean Science (NCCOS). 
Baseline Assessment of Jobos Bay, Puerto Rico: Contaminants 

in the presence of increased ultraviolet radiation as a result of phototoxicity (Peachey and Crosby, 

1996; Guzmán-Martínez et al., 2007). 

4.2.3.2. Polychlorinated biphenyls (PCBs) 

Polychlorinated biphenyls (PCBs) are a class of synthetic compounds that have been used in 

numerous applications ranging from electrical transformers and capacitors, to hydraulic and heat 

transfer fluids, to pesticides and paints. Although no longer manufactured in the United States, 

environmental contamination by PCBs is widespread due to their environmental persistence and 

tendency to bioaccumulate. In some cases, use of PCB containing equipment (e.g., railroad locomotive 

transformers) is still permitted (CFR, 1998). PCBs have a biphenyl ring structure (two benzene rings 

joined by a carbon to carbon bond) and a varying number of chlorine atoms. There are 209 PCB 

congeners (structures) possible. PCBs were analyzed using gas chromatography/electron capture 

detection. 

Effects of PCBs 

Exposure to PCBs in fish has been linked to reduced growth, reproductive impairment and vertebral 

abnormalities (USEPA, 1997). Solbakken et al. (1984) investigated the bioconcentration of radiolabeled 

hexaPCB (2,4,5,2’,4’,5’-hexachlorobiphenyl) in coral. The PCB was rapidly accumulated in D. strigosa 

and M. decactis; however, depuration proceeded at a slow rate; after 275 days nearly 33 percent of 

the original radioactivity from the hexaPCB remained in the coral. 

4.2.3.3. Organochlorine Pesticides 

A total of 31 organochlorine pesticides and related compounds were analyzed in the sediment and 

coral samples from Jobos Bay (Table 4.1), using standard NS&T protocols (Kimbrough et al,. 2006). 

Beginning in the 1950s and continuing to the early 1970s, a series of chlorine containing hydrocarbon 

insecticides were used to control mosquitoes and agricultural pests. One of the best known of the 

organochlorine pesticides used during this time period was dichloro-diphenyltrichloroethane (DDT). It 

has been estimated that during the 30 years prior to its cancellation in 1972, 1.35 billion pounds of DDT 

were applied in the US, with the majority applied to the cotton crop (USEPA, 1975). The use of many 

of the organochlorine pesticides, including DDT, was banned due to their environmental persistence, 

potential to bioaccumulate, and toxicity to non-target organisms. Because of their persistence and 

heavy use in the past, residues of many organochlorine pesticides can be found in the environment, 

including biota. 

Effects of Organochlorine Pesticides 

Organochlorine pesticides are typically neurotoxins. Both DDT and PCBs have also been shown to 

interfere with the endocrine system. DDT and its metabolite dichloro-diphenyldichloroethylene (DDE) 

were specifically linked to eggshell thinning in birds, particularly raptors. A number of organochlorine 

pesticides are also known to be toxic to aquatic life including crayfish, shrimp and some species of 

fish. 

4.2.3.4. Butyltins 

This class of compounds has a range of uses from biocides to catalysts to glass coatings. In the 

1950s, tributyltin or TBT was first shown to have biocidal properties (Bennett, 1996). Beginning in the 

late 1960s, TBT was incorporated into a very effective antifoulant paint system, quickly becoming one 

of the most effective paints ever used on boat hulls (Birchenough et al., 2002). TBT was incorporated 

into a polymer paint system that released the biocide at a constant and minimal rate, to control 

fouling organisms such as barnacles, mussels, weeds, and algae (Bennett, 1996). In the aquatic 

environment, TBT is degraded by microorganisms and sunlight (Bennett, 1996). The transformation 

involves sequential debutylization resulting in dibutyltin, monobutyltin, and finally inorganic tin (Batley, 

115 4 - Contaminants 
Baseline Assessment of Jobos Bay, Puerto Rico: Contaminants 

Table 4.1. List of analytes. 

PAHs PAHs 

Low Molecular Weight High Molecular Weight PCBs Organochlorine Pesticides 

Naphthalene Fluoranthene PCB8/5 Aldrin 

1-Methylnaphthalene Pyrene PCB18 Dieldrin 

2-Methylnaphthalene C1-Fluoranthenes/Pyrenes PCB28 Endrin 

2,6-Dimethylnaphthalene C2-Fluoranthenes/Pyrenes PCB29 Heptachlor 

1,6,7-Trimethylnaphthalene C3-Fluoranthenes/Pyrenes PCB31 Heptachlor-Epoxide 

C1-Naphthalenes Naphthobenzothiophene PCB44 Oxychlordane 

C2-Naphthalenes C1-Naphthobenzothiophenes PCB45 Alpha-Chlordane 

C3-Naphthalenes C2-Naphthobenzothiophenes PCB49 Gamma-Chlordane 

C4-Naphthalenes C3-Naphthobenzothiophenes PCB52 Trans-Nonachlor 

Benzothiophene Benz(a)anthracene PCB56/60 Cis-Nonachlor 

C1-Benzothiophenes Chrysene PCB66 Alpha-HCH 

C2-Benzothiophenes C1-Chrysenes PCB70 Beta-HCH 

C3-Benzothiophenes C2-Chrysenes PCB74/61 Delta-HCH 

Biphenyl C3-Chrysenes PCB87/115 Gamma-HCH 

Acenaphthylene C4-Chrysenes PCB95 2,4’-DDT 

Acenaphthene Benzo(b)fluoranthene PCB99 4,4’-DDT 

Dibenzofuran Benzo(k)fluoranthene PCB101/90 2,4’-DDD 

Fluorene Benzo(e)pyrene PCB105 4,4’-DDD 

C1-Fluorenes Benzo(a)pyrene PCB110/77 2,4’-DDE 

C2-Fluorenes Perylene PCB118 4,4’-DDE 

C3-Fluorenes Indeno(1,2,3-c,d)pyrene PCB128 DDMU 

Anthracene Dibenzo(a,h)anthracene PCB138/160 1,2,3,4-Tetrachlorobenzene 

Phenanthrene C1-Dibenzo(a,h)anthracenes PCB146 1,2,4,5-Tetrachlorobenzene 

1-Methylphenanthrene C2-Dibenzo(a,h)anthracenes PCB149/123 Hexachlorobenzene 

C1-Phenanthrene/Anthracenes C3-Dibenzo(a,h)anthracenes PCB151 Pentachloroanisole 

C2-Phenanthrene/Anthracenes Benzo(g,h,i)perylene PCB153/132 Pentachlorobenzene 

C3-Phenanthrene/Anthracenes PCB156/171/202 Endosulfan II 

C4-Phenanthrene/Anthracenes Trace Elements PCB158 Endosulfan I 

Dibenzothiophene Aluminum (Al) PCB170/190 Endosulfan Sulfate 

C1-Dibenzothiophenes Antimony (Sb) PCB174 Mirex 

C2-Dibenzothiophenes Arsenic (As) PCB180 Chlorpyrifos 

C3-Dibenzothiophenes Cadmium (Cd) PCB183 

Chromium (Cr) PCB187 Butyltins 

Copper (Cu) PCB194 Monobutyltin 

Iron (Fe) PCB195/208 Dibutyltin 

Lead (Pb) PCB199 Tributyltin 

Manganese (Mn) PCB201/157/173 Tetrabutyltin 

Mercury (Hg) PCB206 

Nickel (Ni) PCB209 

Selenium (Se) 

Silver (Ag) 

Tin (Sn) 

Zinc (Zn) 

*PAHs = polycyclic aromatic hydrocarbons; PCBs = polychlorinated biphenyls; DDT = dichloro-diphenyltrichloroethane 

116 4 - Contaminants
Baseline Assessment of Jobos Bay, Puerto Rico: Contaminants 

1996). Experiments have shown that the half-life of TBT, the amount of time needed to convert half 

of the TBT to dibutyltin in natural water samples, is on the order of days; degradation to monobutyltin 

takes approximately a month (Batley, 1996). Experiments with aerobic sediments have shown that 

the half-life of TBT is similar to that measured in solution. In deeper, anoxic sediments, however, 

the half-life of TBT is considerably longer, on the order of 2-4 years (Batley, 1996). Butyltins were 

analyzed using gas chromatography/flame photometric detection. 

Effects of TBT 

The widespread use of TBT as an antifouling agent was associated with endocrine disruption, 

specifically an imposex condition in marine gastropod mollusks. Beginning in 1989 in the U.S., the 

use of TBT as an antifouling agent was banned on vessels smaller than 25 m in length (Gibbs and 

Bryan, 1996). Negri et al. (2002) investigated the effects of TBT in sediments from a shipwreck, on the 

coral Acropora microphthalma from the Great Barrier Reef in Australia. Sediments originally contained 

approximately 160 μg/g TBT. When diluted to 5 percent of the original concentration, successful 

settlement of coral larvae in the laboratory was prevented. 

4.2.3.5. Major and Trace Elements 

A total of 16 trace and major elements were measured in sediments, and 14 in coral tissues for this 

project (Table 4.1). Most of these elements are metals, however, antimony, arsenic and silicon are 

metalloids; selenium is a nonmetal. All occur naturally to some extent in the environment. Aluminum, 

iron, and silicon are major components of the Earth’s crust. Some trace and major elements in the 

appropriate concentrations are biologically essential. As their name implies, trace elements such 

as chromium, cadmium, lead and nickel occur at lower concentrations in crustal material, however 

mining and manufacturing processes along with the use and disposal of products containing trace 

elements result in elevated concentrations in the environment. 

Silver, cadmium, copper, lead, antimony, and tin were analyzed using inductively coupled plasma - 

mass spectrometry. Aluminum, arsenic, chromium, iron, manganese, nickel, silicon and zinc were 

analyzed using inductively coupled plasma - optical emission spectrometry. Mercury was analyzed 

using cold vapor - atomic absorption spectrometry. Selenium was analyzed using atomic fluorescence 

spectrometry. For each element, total elemental concentration (i.e., sum of all oxidation states) was 

measured. A more detailed description of laboratory methodologies can be found in Kimbrough and 

Lauenstein (2006). 

Effects of Trace Elements 

A number of trace elements are toxic at low concentrations. Cadmium, used in metal plating, solders, 

and batteries has been shown to impair development and reproduction in several invertebrate species, 

and the ability to osmoregulate in herring larvae (Eisler, 1985; USDHHS, 1999). Mercury is volatile and 

can enter the atmosphere through processes including mining, manufacturing, combustion of coal, 

and volcanic eruptions. Effects of mercury on copepods include reduced growth and reproductive 

rates (Eisler, 1987). Chromium has been shown to reduce survival and fecundity in the cladoceran 

Daphnia magna, and reduced growth in fingerling chinook salmon (Oncorhynchus tshawytscha; 

Eisler, 1986). Copper has a number of uses such as in antifouling paints, wood preservatives, heat 

exchangers in power plants, electrical wires, coinage, and agriculture. Although an essential element, 

elevated levels of copper can impact aquatic organisms, including reproduction and development 

in mysid shrimp (Eisler, 1998). In corals, Reichelt-Brushett and Harrison (2005) found that a copper 

concentration of 20 μg/L significantly reduced fertilization success in brain coral Goniastrea aspera. At 

copper concentrations at or above 75 μg/L, fertilization success was one percent or less. Fertilization 

success was also significantly reduced in the coral Acropora longicyathus at 24 μg/L, similar to G. 

aspera. 

117 4 - Contaminants 
Baseline Assessment of Jobos Bay, Puerto Rico: Contaminants

118 4 - Contaminants

4.2.4. Total Organic Carbon (TOC) and Grain Size

Total organic carbon (TOC) and grain size analyses were also carried out on the sediment 

samples. These two characterizations are important for assessing the potential for accumulation 

of contaminants in sediments. Typically, a positive relationship exists between sediment TOC and 

chemical contaminants, particularly organic contaminants, in freshwater, estuarine and coastal 

waters (Hassett et al., 1980; Shine and Wallace, 2000). TOC was quantifi ed in the sediments using 

a sequence of steps that involves combusting the carbon in a sample at a high temperature and 

then quantifying the CO2

 produced. Grain size is also an important sediment characteristic as many 

organic contaminants and a number of metals bind to the smaller silt and clay grain size fractions 

of sediments, due to the larger surface areas of these fractions, and in the case of trace and major 

elements, the charge characteristics of clays. Grain size analysis was carried out using a series of 

sieving and settling techniques. Additional information on TOC and grain size analysis can be found 

in McDonald et al. (2006).

4.2.5. Statistical Analyses

All contaminant data were analyzed using JMP® statistical software. The data were fi rst tested 

for normality using the Shapiro-Wilk test. Most of the data were not normally distributed. If log10

transformations were not effective, nonparametric tests (e.g., Wilcoxon) were run. When a signifi cant 

Wilcoxon test resulted, the data were then ranked in order to permit an analysis of variance (ANOVA). 

The Tukey-Kramer HSD (Honestly Signifi cant Difference) test was then used for pairwise comparisons. 

Correlations were tested using a Spearman’s rank correlation coeffi cient test. Spearman coeffi cient 

Rho (ρ) values of 0.707 or higher were discussed as indicative of strong correlation, while values 

below 0.707 indicate weak correlation. Most of the statistics were calculated on all 44 sites sampled 

for this project. However, when comparing differences between the strata, the three targeted (SWP) 

sites were not included, as they were not part of the stratifi ed random sampling design. After data 

analysis, it was determined that CNT and NER were not statistically different, and because NER is a 

geographic subset of CNT, these two strata were combined into a singular central stratum.

4.2.6. Providing Context for Results

In addition to comparing contamination results between strata, there are several other ways to 

evaluate the relative level of contamination of Jobos Bay. First, and most simply, these fi ndings can 

be compared to the contaminant concentrations in other studies in Puerto Rico, or other tropical 

systems. Second, the fi ndings can 

be placed in a national context by

comparing the results to a national

contaminant monitoring program,

such as NS&T, which includes

sediment chemistry data from over

300 coastal sites throughout the U.S. 

Finally, the degree of contamination 

in Jobos Bay can be assessed

using NOAA’s numerical sediment

quality guidelines (SQG) known as

effects range-low (ERL) and effects 

range-median (ERM) developed by

Long and Morgan (1990) and Long 

et al. (1996). The SQG value was

not defi ned for all analytes; existing 

values are presented in Table 4.2.

Table 4.2. Sediment Quality Guidelines (Long and Morgan, 1990).

Contaminant ERL ERM

Total PAHs (ng/g) 4,022 44,792

Total PCBs (ng/g) 22.7 180

Total DDT (ng/g) 1.58 46.1

Ag (μg/g) 1 3.7

As (μg/g) 8.2 70

Cd (μg/g) 1.2 9.6

Cr (μg/g) 81 370

Cu (μg/g) 34 270

Hg (μg/g) 0.15 0.71

Ni (μg/g) 20.9 51.6

Pb (μg/g) 46.7 NA

Zn (μg/g) 150 410

Sediment quality guideline have not been developed for all analytes monitored 

by the NOAA’s National Status and Trends Program (NS&T).
Baseline Assessment of Jobos Bay, Puerto Rico: Contaminants

119 4 - Contaminants

These guidelines are statistically derived levels of contamination above which toxic effects would 

be expected to be observed in benthic organisms with at least a 50% frequency (ERM), and below 

which effects were rarely (<10%) expected (ERL). While these guidelines are neither regulatory, nor 

confi rm that toxicity is present, they can serve as a useful screening tool, i.e., a fi rst step in evaluating 

the likelihood that contamination at a given site may be at levels of concern. The SQG can be used 

to identify areas where additional study is needed to further quantify levels of contamination and 

potential associated toxicity.

It should be noted that there are no guidelines for contaminants in coral tissues, nor is there a 

national or regional coral tissue contaminant monitoring program. So in the case of corals, contextual 

comparisons are limited to other studies in similar systems.

4.3. RESULTS – OVERVIEW OF CONTAMINANT PATTERNS

4.3.1. Environmental Parameters

The water depth at the sediment sites sampled was fairly shallow; the mean at the sites was 1.1 

± 0.1 m (n=44). The mean surface salinity was 35.3 practical salinity units (psu), temperature was 

29.5°C, and dissolved oxygen was 6.3 mg/L. A Wilcoxon nonparametric test indicated no signifi cant 

differences in the surface versus bottom measurements for any of these parameters, indicating well 

mixed waters within the Bay. 

The characteristics of the sediments

by stratum are shown in Table 4.3.

In this study and in NOAA’s NS&T

Program, the silt and clay fractions

are combined and referred to as

% fi nes. The %fi nes (sum of %silt

and %clay fractions) are important

as these smaller grain sizes have

proportionately higher surface

area available for the adsorption of

contaminants (Hassett et al., 1980),

while the organic carbon content of 

the silt fraction further increases the adsorption of organic compounds (Shine and Wallace, 2000). 

From Table 4.3, it can be seen that sediments from the inner stratum had the highest fraction (82%) of 

fi nes, followed by the central stratum. A Wilcoxon test indicated a signifi cant (Prob>ChiSq = 0.0003) 

difference, and a one-way ANOVA and pairwise comparison test on the ranked data confi rmed this. 

Table 4.3 also contains the mean TOC values for the Jobos Bay sediments. Although the inner 

stratum sediments had numerically higher %TOC values, an ANOVA on the log10 transformed data 

did not indicate any differences between the strata (p=0.1426). The mean %TOC for the SWP sites 

(6.84%) was higher than the means for the strata sampled. However, because the SWP sites were 

not randomly selected, they could not be compared statistically with the inner, central, and outer 

strata. 

4.3.2. Polycyclic Aromatic Hydrocarbons (PAHs)

Total PAHs in the NS&T Program refers to the sum of the 24 PAHs listed in Table 4.1. Concentrations 

for PAHs in sediments and corals at individual sites can be found in Appendix B (Tables B.1 and B.2).

Table 4.3. Sediment characteristics by strata.

Map # of %Total Organic Stratum* % Fines Abbreviation Samples Carbon (TOC)

Inner INR 10 82.33 ±5.82 2.39 ±0.24 

Central CNT and NER 11 52.17 ±6.14 2.10 ±0.50

Outer OTR 10 32.54 ±6.39 1.54 ±0.34

SWP SWP 3 47.05 ±16.70 6.84 ±3.12

* The SWP sites represent targeted, nonrandom sites used by the Jobos Bay 

National Estuarine Research Reserve (JBNERR) to characterize Jobos Bay; the 

selection of sites within the other strata were randomized. % Fines is the sum 

of the % silt and % clay sediment fractions. Abbreviations: SWP, System Wide 

Monitoring Program (SWMP) for JBNERR.
Baseline Assessment of Jobos Bay, Puerto Rico: Contaminants 

120 4 - Contaminants

Sediments 

Observed concentrations of total PAHs in the sediments are shown in Figure 4.4. The mean 

concentration of total PAHs in the sediments sampled in Jobos Bay was 1,062 ng/g; the median was 

371 ng/g (Table 4.4). The highest concentration detected was 14,250 ng/g at a site (INR4) in the 

inner stratum (Figure 4.1), adjacent to a small boat yard. A comparison of the different strata using 

the log10 transformed data indicated total PAHs were significantly different between strata (p=0.0004), 

and a Tukey-Kramer test indicated that the inner stratum (INR) had significantly higher total PAH 

concentrations than the central (CNT) and outer (OTR) strata. It is likely that the inner stratum has 

less flushing to the open ocean than either the central or outer strata, which would tend to accumulate 

sediments and sediment-bound contaminants (Zitello et al., 2008). 

Figure 4.4. Total Polycyclic aromatic hydrocarbons (PAH) concentrations in sediments. 

The ERL for total PAHs is 4,022 ng/g. There was only one sediment sample with a total PAH 

concentration above this value, the sample from INR4 (14,250 ng/g). This value however, is below the 

ERM (44,792 ng/g) which would have indicated that impacts were more likely from the sum of PAHs. 

There are also a series of ERLs and ERMs for a number of individual PAHs. None of the individual 

PAHs exceeded the established ERM values. However, the ERL was exceeded for several individual 

PAHs (Tables 4.2 and 4.4). Another sediment quality guideline, the PEL or Probable Effects Level, is 

similar to the ERM except that the PEL is the geometric mean of the 50th percentile of the effects data, 

and the 85th percentile of the no effects data, and represents a concentration above which McDonald 

et al. (2006) estimate that effects in sediment dwelling organisms are likely to occur. While the PEL 

was not exceeded for total PAHs, the PEL was exceeded for a number of individual PAHs including 

phenanthrene, benz(a)anthracene, chrysene, benzo(a)pyrene, and dibenzo(a,h)anthracene at INR4 

(Tables 4.2 and 4.4). In addition, while the PEL for naphthalene (391 ng/g) was not exceeded at INR4, 

it was exceeded at NER24 and SWP43 (Tables 4.2 and 4.4). 

The concentrations of PAHs found in the sediments from Jobos Bay can be compared with other 

assessments. Recently, Aldarondo-Torres et al. (2010) published an analysis of trace metals, PAHs, 

and PCBs in sediments from Jobos Bay. Samples from seven stations were screened for 16 PAHs. 

The mean PAH concentration in sediments was 593 ng/g, somewhat lower than the mean found in 

the current study (1,062 ng/g). The higher total PAH concentration found at INR4 in the current study 

may have been responsible in part for the higher mean; the median for total PAHs in the current study 
Baseline Assessment of Jobos Bay, Puerto Rico: Contaminants

121 4 - Contaminants

out by NS&T, data from Jobos Bay can be compared with the rest of the Nation’s coastal waters. 

The median for total PAHs in Jobos Bay sediments was 370.5 ng/g (Table 4.4), below the NS&T 

national median of 415 ng/g. However, 19 sites had a total PAH median concentration higher than 

the NS&T national median, and fi ve sites (INR4, INR3, NER24, SWP43, and SWP44) had total PAH 

concentrations above the national NS&T 85th percentile of 2,688 ng/g.

Corals

PAH concentrations in coral tissues ranged from 2.90 ng/g to 6.40 ng/g (dry weight), with a mean 

of 4.58 ng/g and a median of 4.55 ng/g (Table 4.5). There was no statistically signifi cant difference 

between the inshore and offshore strata (Figure 4.5, Table 4.4). No statistically signifi cant correlations 

were found between coral tissue PAH concentrations and depth, longitude (i.e., long shore position) 

or distance from land. Because organic compounds tend to be lipophilic, tissue concentrations can 

be normalized to lipid content, which can help identify possible sources of contaminants (Lake et 

al., 1990). Normalizing PAH tissue data to coral lipid content did not change the statistical patterns 

in the data. Despite high observed PAH concentrations at one sediment site (INR4), coral tissue 

concentrations of PAHs were low when compared to other studies areas in Puerto Rico (Table 4.5).

was 415 ng/g, similar to the median 

(394 ng/g) calculated from the data 

presented by Aldarondo-Torres et al. 

(2010). It should also be noted that 

the calculation of total PAH in the 

NS&T Program for this study used 

58 PAHs; Aldarondo-Torres et al. 

(2010) used 16 PAHs. Interestingly, 

one of the higher concentrations

(940 ng/g) of total PAHs found by 

Aldarondo-Torres et al. (2010) was 

from a site near (<1 km) INR4 in 

the current study, and like INR4,

may be infl uenced by activities from 

the adjacent boat yard. AldarondoTorres et al. (2010) also noted in 

general that samples taken from the 

inner areas of Jobos Bay contained 

higher levels of total PAHs, similar 

to the results from the current study. 

The results for total PAHs found in 

the sediments can also be compared 

with work recently completed in

southwest Puerto Rico (Pait et al., 

2007, 2008) and in Vieques, Puerto 

Rico (Pait et al., 2010). The mean 

total PAH concentration found in

sediments from southwest Puerto

Rico was 80.6 ng/g, and in Vieques, 

52.3 ng/g, both substantially below 

the mean found in Jobos Bay. 

Because of the long-term, nationallevel contaminant monitoring carried 

Table 4.4. Summary statistics for organic contaminants in sediments, overall and by 

strata (ng/g dry wt). ERL=effects rangle-low, ERM= effects range-median).

Total Total Total Tributyl- Stratum* PAHs PCBs DDT tin

Inner

Minimum 610 0.99 0.49 0.07

Maximum 14,250 19.24 3.28 2.27

Median 1,184 3.84 1.00 0.20

Mean 2,711 5.51 1.23 0.43

Central

Minimum 5.5 0.03 0.01 0.00

Maximum 3,413 5.46 1.81 0.00

Median 306 0.80 0.23 0.00

Mean 515 1.14 0.34 0.00

Outer

Minimum 4 0.04 0.00 0.00

Maximum 844 0.79 0.74 10.91

Median 148 0.40 0.125 0.30

Mean 231 0.39 0.19 2.03

SWP

Minimum 80.5 0.07 0.06 0.00

Maximum 3,221 6.06 2.09 0.19

Median 3,157 2.98 0.3 0.00

Mean 2,152 3.04 0.82 0.06

Overall

Median 370.5 0.81 0.28 0.00

Mean 1,062 2.09 0.54 0.56

NOAA Sediment Guidelines

ERL 4,022 22.7 1.58 NA

ERM 44,792 180 46.1 NA

* The SWP sites represent targeted, nonrandom sites used by the Jobos Bay 

National Estuarine Research Reserve (JBNERR) to characterize Jobos Bay; the 

selection of sites within the other strata were randomized.
Baseline Assessment of Jobos Bay, Puerto Rico: Contaminants 

122 4 - Contaminants 

Figure 4.5. Total PAH concentrations in corals (Porites astreoides). White outline are coral reefs in inner stratum. Red outline are coral 

reefs in outer stratum. 

Table 4.5. Summary statistics for contaminants in coral tissue, including comparison with other studies, Southwest Puerto Rico (SW 

PR; Pait et al., 2009) and Vieques (Pait et al., 2010). 

Contaminant Minimum Maximum Median Mean SW PR 

Mean 

Vieques 

Mean 

SW PR 

Max 

Vieques 

Max 

HCH (ng/g) 0.00 

0.00 

0.00 

2.19 

2.90 

0.00 

100.00 

0.94 

0.21 

0.00 

2.37 

110.00 

0.00 

8.33 

8.33 

0.80 

0.08 

0.13 

0.00 

2.56 

0.00 

0.00 

0.60 

3.56 

6.40 

0.00 

333.00 

2.44 

0.31 

0.00 

97.20 

480.00 

0.00 

24.60 

24.60 

6.84 

12.50 

0.26 

0.10 

16.90 

0.00 

0.00 

0.00 

2.35 

4.55 

0.00 

154.00 

1.59 

0.25 

0.00 

68.95 

176.00 

0.00 

11.60 

11.60 

2.63 

0.20 

0.18 

0.00 

7.88 

0.00 

0.00 

0.04 

2.45 

4.58 

0.00 

177.69 

1.68 

0.25 

0.00 

50.30 

212.13 

0.00 

13.33 

13.33 

3.13 

1.43 

0.18 

0.01 

8.59 

0.00 

0.00 

0.08 

3.81 

41.91 

0.00 

37.80 

0.00 

0.00 

0.00 

2.06 

90.80 

0.00 

3.01 

3.01 

1.32 

0.00 

0.05 

0.02 

6.09 

0.00 

0.12 

0.13 

2.63 

15.00 

0.013 

30.75 

0.241 

0.194 

0.183 

0.757 

51.2 

<0.001 

2.66 

2.66 

0.896 

0.074 

0.096 

0.246 

3.43 

0.00 

0.00 

0.62 

10.97 

154.00 

0.09 

82.20 

0.00 

0.00 

0.00 

3.54 

353.00 

0.00 

5.36 

5.36 

2.70 

0.07 

0.37 

0.14 

18.30 

0.05 

0.81 

2.26 

5.76 

21.50 

0.0332 

103 

3.42 

0.294 

1.09 

6.51 

526 

0.0021 

8.24 

8.24 

8.09 

0.174 

0.338 

0.396 

15.2 

Chlordane (ng/g) 

Total DDT (ng/g) 

Total PCBs (ng/g) 

Total PAHs 

(ng/g) 

Ag (μg/g) 

Al (μg/g) 

As (μg/g) 

Cd (μg/g) 

Cr (μg/g) 

Cu (μg/g) 

Fe (μg/g) 

Hg (μg/g) 

Mn (μg/g) 

Ni (μg/g) 

Pb (μg/g) 

Se (μg/g) 

Sn (μg/g) 

Zn (μg/g) 
Baseline Assessment of Jobos Bay, Puerto Rico: Contaminants 

4.3.3. Polychlorinated Biphenyls (PCBs) 

Total PCBs are defined as the sum of the 39 congener and congener combinations listed in Table 4.1. 

Concentrations for PCBs in sediments and corals at individual sites can be found in the Appendix B 

(Tables B.1 and B.2). 

Sediments 

Total PCBs detected in the sediments in Jobos Bay are shown in Figure 4.6. The mean sediment 

total PCB concentration in the samples collected in Jobos Bay was 2.09 ng/g; the median was 0.81 

ng/g (Table 4.4). The highest total PCB concentration was 19.24 ng/g at INR9 in the inner stratum. 

A comparison of the different strata using the log10 transformed data indicated total PCBs were 

significantly different between strata (p<0.0001), and a Tukey-Kramer test indicated that the inner 

strata had a higher total PCB concentration. 

Figure 4.6. Total polychlorinated biphenyl (PCB) concentrations in sediments. 

None of the sediments sampled in Jobos Bay had a total PCB concentration near the ERM (180 ng/g) 

or PEL (189 ng/g) or above the ERL of 22.7 ng/g, although INR9 was close to the ERL. AldarondoTorres et al. (2010) analyzed PCBs (15 congeners) at six sites from Jobos Bay with a calculated total 

PCB mean of 2.37 ng/g, similar to the mean detected in the current study. The results for total PCBs 

can also be compared with work recently completed in southwest Puerto Rico (Pait et al., 2007) and 

in Vieques, Puerto Rico (Pait et al., 2010). The mean total PCB concentration found in sediments 

from southwest Puerto Rico was 104.1 ng/g, substantially above the mean found for Jobos Bay. In 

Vieques, however, the mean total PCB concentration in sediments was 2.86 ng/g, similar to what 

was found in Jobos Bay. The relatively high PCB concentrations in southwest Puerto Rico are driven 

by exceptionally high concentrations in a portion of the study area (Guanica Bay), but the source of 

these PCBs is unknown. 

The median for total PCBs in Jobos Bay sediments (0.81 ng/g), is substantially below the NS&T 

national median of 13.7 ng/g. There was only one site (INR9; 19.24 ng/g) sampled in Jobos Bay that 

was above the NS&T median for total PCBs. 

123 4 - Contaminants 
Baseline Assessment of Jobos Bay, Puerto Rico: Contaminants 

124 4 - Contaminants

The statistical relationship between grain size (%fines) and the concentration of total PCBs in the 

sediment samples indicated a highly signifi cant (Spearman’s Rho [ρ] = 0.5462, p<0.0001) correlation 

between the fi nes fraction of the sediment and the concentration of total PCBs. A bivariate regression 

run between log10 total PCBs and log10 TOC indicated a significant (p<0.0001, r2 = 0.417) relationship 

between TOC and the concentration of total PCBs. 

Corals 

PCB concentrations in coral tissues ranged from 2.19 ng/g to 3.56 ng/g, with a mean of 2.45 ng/g 

and a median of 4.35 ng/g (Table 4.5). There was no statistically significant difference between the 

inshore and offshore strata (Figure 4.7). No statistically significant correlations were found between 

coral tissue PCB concentrations and depth, longitude (i.e., long shore position) or distance from land. 

Because organic compounds tend to be lipophilic, tissue concentrations can be normalized to lipid 

content, which can help identify possible sources of contaminants (Lake et al., 1990). Normalizing 

PCB tissue data to coral lipid content did not change the statistical patterns in the data. Coral tissue 

concentrations of PCBs were slightly lower than other published data for P. astreoides in Puerto Rico 

(Table 4.5). 

Figure 4.7. Total PCB concentrations in corals (P. astreoides). White outline are coral reefs in inner stratum. Red outline are coral reefs

in outer stratum. 

4.3.4. DDT and Other Chlorinated Pesticides 

A series of chlorinated pesticides were analyzed in the sediments as part of this project. The 

organochlorine insecticide DDT was detected in the sediments and coral tissues in Jobos Bay. Total 

DDT is defined as the sum of the two parent compounds 2,4’-DDT and 4,4’-DDT, and degradation 

products 2,4’-DDD, 4,4’-DDD, 2,4’-DDE, 4,4’-DDE and DDMU (Table 4.1). Concentrations for DDTs 

in sediments and corals at individual sites can be found in the Appendix B (Tables B.1 and B.2). 
Baseline Assessment of Jobos Bay, Puerto Rico: Contaminants 

Sediments 

The mean sediment total DDT concentration in the sediment samples collected in Jobos Bay was 

0.54 ng/g ng/g; the median was 0.28 ng/g (Table 4.4). The highest concentration of total DDT, like total 

PCBs, was at INR9 in the inner stratum, with a concentration of 3.28 ng/g (Figure 4.8). A comparison 

of the different strata using the log10 transformed data indicated that total DDT was significantly 

different between strata (p=0.0002), and a Tukey-Kramer test indicated that the inner stratum was 

significantly different (higher concentration) than the other two strata, similar to what was found for 

total PAHs and total PCBs. 

Figure 4.8. Total dichloro-diphenyltrichloroethane (DDT) concentrations in sediments. 

Four of the sediments sampled in Jobos Bay (INR9, SWP43, NER24 and INR6) had a total DDT 

concentration above the ERL of 1.58 ng/g, which may indicate that the more sensitive species or life 

stages are beginning to experience some degree of toxic effects. However, none of the sediment 

samples had a total DDT concentration above the ERM (46.1 ng/g) or the PEL (51.7 ng/g) which would 

have indicated that effects in sediment-inhabiting organisms were likely to occur. A DDT residual 

spraying program was instituted in Puerto Rico by 1950 for the control of mosquitoes (Fox, 1961) and 

also DDT was also likely used in agriculture. 

The results for total DDT can be compared with work recently completed in southwest Puerto Rico 

(Pait et al., 2007) and in Vieques, Puerto Rico (Pait et al., 2010). The mean total DDT concentration 

found in sediments from southwest Puerto Rico (Pait et al., 2008) was 2.10 ng/g, which is above the 

mean total DDT found for Jobos Bay. In Vieques (Pait et al., 2010), the mean total DDT concentration in 

sediments was substantially higher (23.6 ng/g), than that found in Jobos Bay. This mean concentration 

in Vieques is driven by a very high total DDT concentration in a sediment sample from the south 

shore, and elevated total DDT in the sediments at several locations on the north shore of Vieques. 

The median for total DDT in Jobos Bay sediments (0.28 ng/g), is similar to the NS&T national median 

of 0.40 ng/g ng/g. The statistical relationship between grain size and the concentration of total DDT 

in the sediment samples indicated a highly signifi cant (Spearman’s ρ = 0.7746, p<0.0001) correlation 

between the fines fraction of the sediment and the concentration of total DDT. A bivariate regression 

run between log10 total DDT and log10 TOC indicated a significant (p<0.0001, r2

 = 0.416) relationship 

125 4 - Contaminants 
Baseline Assessment of Jobos Bay, Puerto Rico: Contaminants 

126 4 - Contaminants

between TOC and the concentration of total DDT. 

A number of other organochlorine pesticides included in this study were also detected in the sediments 

from Jobos Bay including dieldrin, heptachlor, endrin, chlordane, chlorpyrifos and endosulfan. The 

higher concentrations for these chlorinated pesticides tended to occur in the inner stratum, although 

most concentrations were less than 1 ppb (1 ng/g; data not shown). The highest concentration 

detected for any of these pesticides was endosulfan at INR4 (2.16 ng/g). Although an ERL and ERM 

have not been established for endosulfan, they have been established for chlordane and dieldrin. The 

sediments sampled in Jobos Bay did not exceed the ERMs for either chlordane or dieldrin, however, 

six sites exceeded the ERL for chlordane (0.5 ng/g) and 13 sites exceeded the ERL (0.02 ng/g) for 

dieldrin, the majority of which were in the inner stratum. 

Corals 

DDT concentrations in coral tissues ranged from below levels of detection to 0.6 ng/g, with a mean of 

0.04 ng/g and a median of below limits of detection (Table 4.5). There was no statistically significant 

difference between the inshore and offshore strata (Figure 4.9). No statistically signifi cant correlations 

were found between coral tissue DDT concentrations and depth, longitude (i.e., long shore position) 

or distance from land. Because organic compounds tend to be lipophilic, tissue concentrations can 

be normalized to lipid content, which can help identify possible sources of contaminants (Lake et al., 

1990). Normalizing DDT tissue data to coral lipid content did not change the statistical patterns in the 

data. Coral tissue concentrations of DDT were similar to those observed in Southwest Puerto Rico, 

but were significant lower than those measured in Vieques, Puerto Rico (Table 4.5). 

Figure 4.9. Total DDT concentrations in corals (P. astreoides). White outline are coral reefs in inner stratum. Red outline are coral reefs

in outer stratum. ND = not detect/below limits of detection. 
Baseline Assessment of Jobos Bay, Puerto Rico: Contaminants 

Other chlorinated pesticides were not detected in coral tissues in Jobos Bay. 

4.3.5. Butyltins 

Mono-, di-, tri-, and tetrabutyltin were also analyzed in the sediment and coral samples as part of this 

project. Tributyltin or TBT, was used in antifoulant paints for boat hulls, and was banned for use in 

the US on most vessels in 1989 after being associated with endocrine disruption in certain marine 

gastropod mollusk species. TBT degrades to dibutyltin, monobutyltin, and finally to elemental tin in 

the environment. Tetrabutyltin is an impurity produced in the manufacture of TBT, and will degrade in 

the environment to TBT, and eventually elemental tin. Concentrations for TBT in sediments and corals 

at individual sites can be found in the Appendix B (Tables B.1 and B.2). 

Sediments 

There were numerous detections of butyltins in Jobos Bay sediments. The mean concentration of 

TBT in the sediments from Jobos Bay was 0.56 ng/g; the median was 0 ng/g (Table 4.4). The highest 

TBT values found in the sediments were from OTR31 (10.91 ng/g), OTR37 (4.24 ng/g), and OTR34 

(3.64 ng/g; Figures 4.1 and 4.10). 

Figure 4.10. Tributyltin (TBT) in sediment. 

None of the randomly selected central stratum sites had detectable levels of TBT, and could be related 

to the restrictions placed on boat traffic in parts of the JBNERR. An ANOVA on the log10 transformed 

data indicated that the outer stratum was significantly higher than the inner stratum (p=0.0103). This 

is in contrast to a number of the other contaminant classes, in which the inner stratum had statistically 

higher sediment contaminant values. The outer stratum has what appears to be signifi cant marinarelated activity in the area around Playita, which could be associated with the TBT. Four of the top 

five highest concentrations of TBT were in this area. As noted above, TBT was used in the past 

as an antifoulant on boat hulls. Rankings and ANOVAs on monobutyltin (p=0.0093) and dibutyltin 

(p<0.0001) data followed by pairwise comparisons indicated significant differences between the three 

strata, however, for both monobutyltin and dibutyltin, the inner and outer strata were not significantly 

different from one another, which might indicate significant use of TBT in these areas of Jobos Bay in 

the past. The significantly higher levels of TBT in comparison to its degradation products found in the 

outer stratum could be an indicator of more recent deposition. 

127 4 - Contaminants 
Baseline Assessment of Jobos Bay, Puerto Rico: Contaminants 

128 4 - Contaminants

The results for TBT can also be compared with work recently completed in southwest Puerto Rico (Pait 

et al., 2008) and Vieques, Puerto Rico (Pait et al., 2010). In the sediment samples from southwest 

Puerto Rico, the mean TBT concentration was 0.014 ng/g; whereas, in Vieques sediments, the mean 

TBT concentration was 0.040 ng/g, both substantially below the mean concentration found in Jobos 

Bay. The NS&T median for TBT is 0.41 ng/g; higher than the median TBT found in Jobos Bay. There 

does not appear to be an ERL, ERM or PEL value for TBT. 

Corals
 

Butyltins were not detected in any coral samples. Other studies in Puerto Rico (Pait et al., 2009, 2010) 

have documented butyltins in P. astreoides tissues, so the corals do have the capacity to accumulate 

these compounds in their tissues. It is not clear why the high (relative to other sites in Puerto Rico) 

butyltins concentrations in sediments does not result in butyltins ending up in coral tissues in Jobos 

Bay.
 

4.3.6. Major and Trace Elements 

A summary of concentration ranges and median values for each trace and major element is illustrated 

in Table 4.6. The results showed a broad variation within the concentration values of each element. 

In general, concentration differences between the minimum and maximum values of individual 

element reached two orders of magnitude (Table 4.6). Concentrations for major and trace elements 

in sediments and corals at individual sites can be found in the Appendix B (Tables B.1 and B.2). 

4.3.6.1. Silver (Ag) 

Sediments 

Silver (Ag) concentrations in sediments ranged from 0.051 μg/g to 

0.219 μg/g, with a mean of 0.118 

μg/g and a median of 0.105 μg/g 

(Table 4.6). This is below the NS&T 

national median of 0.13 μg/g, and 

similar to other published studies in 

tropical ecosystems (Table 4.7). Silver did not exceed sediment quality 

guidelines at any of the sediment 

sites. Unlike many of the other metals, the highest Ag concentrations 

were observed in the outer bay stratum at significantly higher concentrations (p<0.05) relative to the other 

zones of the study area (Figures 

4.11 and 4.12). 

Corals 

Silver was not detected in any coral samples. Other studies in Puerto Rico (Pait et al., 2009, 2010) 

have documented silver in P. astreoides tissues, so the corals do have the capability to accumulate 

this metal in their tissues. It is not clear why silver is observed in the sediments but is not accumulating 

in coral tissues in Jobos Bay. 

Table 4.6. Summary statistics for trace elements in sediments (μg/g dry wt). 

Element Minimum Maximum Median Mean 

Ag 0.051 0.219 0.105 0.118 

Al 629 73700 41850 39138 

As 1.79 28.10 12.75 12.59 

Cd 0 0.174 0 0.008 

Cr 0 29.8 18.5 18.2 

Cu 1.37 73.70 29.85 33.83 

Fe 1060 50500 26650 26570 

Hg 0.0014 0.144 0.0309 0.0432 

Mn 33.1 1130 528.5 510.6 

Ni 0 31 10.1 11.0 

Pb 0.227 16.7 6.02 7.15 

Sb 0 0.589 0.2685 0.2170 

Se 0 1.56 0.2755 0.3318 

Sn 0 2.74 1.17 1.13 

Zn 1.57 117 48.5 54.2 
Table 4.7. Ranges of metal concentration in surficial sediment from Jobos Bay compared to published data from similar habitat environments. Concentration values are in ug/g dry 

wt. MW= Mussel Watch, JB= Jobos Bay, SW= southwest, VQS= Vieques, PR= Puerto Rico, ERL= Effects Range Low, ERM=Effects Range Median. 

Area Ag As Cd Cr Cu Fe Hg Mn Ni Pb Sb Se Sn Zn Reference This study 0.05 - 0.22 1.79 - 28.1 0.0 - 0.174 29.8 1.37 - 73.7 1060 - 50500 0.001 - 0.144 33.1 - 1130 0 - 31 0.23 - 16.7 0 - 0.59 0 - 1.56 0 - 2.74 1.57 - 117 This study (median) 

0.0 -

0.08

 10.7 -

12.1 

0.0 -

0.17

 36.9 -

273

 10.7 -

155

 35700

- 44600 

0.03 -

0.051

 508 -

990

 9.16 -

258

 6.74 -

12.3 -

0.24 -

0.29

 2.42 -

1.38 

74.9 -

139 NOAA (2006) 

0.1 - 0.3 2.5 - 10 0.1 - 0.3 20 - 80 10 - 40 - 0.05 - 0.2 20 - 100 10 - 20 5 - 20 0.2 - 0.6 0.2 - 0.8 1 - 3 20 - 100 Cantillo et al. (1999) 

-­ 17 0.06 -­ 29 2600 -­ -­ -­ 11 -­ -­ -­ 64 Aldarondo-Torres et al. (2010) 

0.05 -

0.20 1 - 5 0.25 - 0.75 20 - 60 10 - 20 0.05 - 0.15 20 - 60 5 - 10 20 - 60 0.25 - 0.75 0.5 - 1.5 20 - 80 Cantillo et al. (1999) 

<001 0.01 0.01 31.2 5.21 5210 <0.01 109 26.6 1.93 0.09 0.17 0.21 7.99 Pait et al. (2008) 

0.103 4.37 0.133 22.5 25.9 17610 0.019 301 7.80 5.42 0.2 0.26 0.66 34.3 Pait et al. (2010) 

1.0 8.2 1.2 81 34 - 0.15 - 20.9 46.7 - - - 150 Long et al. (1996) 

3.7 70 9.6 370 270 - 0.71 - 51.6 - - - - 410 Long et al. (1996) 

Values southwe et al., 2008), Jobos 2010 (Aldarondo-Torres et al., 2010) and VQS (Pait et al., 2010) are means. st Puerto Rico (Pait

lity guideline was not developed for all metals monitored by the NOAA’s National Status and Trends Program (NS&T). 

MW JBMW PRJobos 2010Tampa BaySW PRVQS, PRERL*ERM*

* Sediment qua

Baseline Assessment of Jobos Bay, Puerto Rico: Contaminants 

129 4 - Contaminants 
Baseline Assessment of Jobos Bay, Puerto Rico: Contaminants 

130 4 - Contaminants 

Figure 4.11. Chromium, silver, mercury and selenium concentrations in sediments 

by strata. Wilcoxon test (α=0.05). 

Figure 4.12. Silver (Ag) concentrations in sediments. 
Baseline Assessment of Jobos Bay, Puerto Rico: Contaminants 

4.3.6.2. Aluminum (Al)
 

Aluminum (Al) is a major crustal element and is generally not considered to be a pollutant. However, 

examining aluminum distributions can shed light on the origins of other trace elements which have 

both natural and anthropogenic sources. 

Sediments 

Aluminum concentrations in sediments ranged from 629 μg/g to 73700 μg/g, with a mean of 39,140 

μg/g and a median of 41850 μg/g (Table 4.6). Aluminum concentrations were signifi cantly higher 

(p<0.05) in the Inner Bay relative to the Central and Outer Bays (Appendix B, Figure B.1). Please see 

the additional discussion that follows which uses Al as an index of naturally occurring metals. 

Corals 

Aluminum concentrations in coral tissues ranged from 100 μg/g to 333 μg/g, with a mean of 178 μg/g 

and a median of 154 μg/g (Table 4.5). There was no statistically significant difference between the 

inshore and offshore strata (Appendix B, Figure B.2). No statistically significant correlations were 

found between coral tissue Al concentrations and longitude (i.e., long shore position) or distance from 

land. However, Al concentrations in coral were weakly negatively correlated with depth (p=0.0454, 

Spearman’s ρ = -0.5063). It is possible that this could be explained by location on the reef (or some 

other confounding factor not measured here), or there could be a difference in coral biology/uptake 

at lower depths/higher pressures. Coral tissue concentrations of Al were elevated compared to other 

studies in Puerto Rico. Aluminum is general not considered to be a pollutant, but this could indicate 

that other observed metals in coral tissues in this area may be naturally occurring. This interpretation 

of these data should be approached cautiously, however, because differential uptake/incorporation 

rates between metals in corals are not well understood and ratios of aluminum to other metals in 

tissues may be altered by biological processes. More research is needed to understand uptake 

processes of metals in coral species. 

4.3.6.3. Arsenic (As) 

Sediments 

Arsenic (As) concentrations in sediments ranged from 1.79 μg/g to 28.1 μg/g, with a mean of 12.95 

μg/g and a median of 12.75 μg/g (Table 4.6). This is higher than the NS&T national median of 8.45 

μg/g, and is higher than other studies in tropical systems (Table 4.7) suggesting that As concentrations 

in Jobos Bay may be elevated compared to the rest of the Nation. Arsenic concentrations were 

significantly higher (p<0.05) in the Inner Bay relative to the Central and Outer Bays (Appendix B, 

Figure B.3). Maximum concentrations were observed at sites NER24 and SWP44 in Central Bay for 

As. Maximum values for As were above their respective ERL values at sites located in the Inner and 

Central strata (Table 4.7). 

Coral 

Arsenic concentrations in coral tissues ranged from 0.94 μg/g to 2.44 μg/g, with a mean of 1.68 μg/g 

and a median of 1.59 μg/g, which is higher than other studies in Puerto Rico (Table 4.5). Arsenic 

concentrations in corals were higher (Wilcoxon test, α=0.05) in the offshore stratum than inshore 

(Figure 4.13). This pattern could be a result of atmospherically deposited As from fossil fuel combustion 

at the nearby power plants (coal and oil fired), i.e. the stack height minimizes near shore deposition. 

No statistically significant correlations were found between coral tissue As concentrations and depth, 

longitude (i.e., long shore position) or distance from land. 

131 4 - Contaminants 
Baseline Assessment of Jobos Bay, Puerto Rico: Contaminants 

132 4 - Contaminants 

Figure 4.13. Arsenic (As) concentrations in corals (P. astreoides). White outline are coral reefs in inner stratum. Red outline are coral

reefs in outer stratum. 

4.3.6.4. Cadmium (Cd) 

Sediments 

Cadmium (Cd) concentrations in sediments ranged from 0 μg/g to 0.174 μg/g, with a mean of 0.01 

μg/g and a median of 0 μg/g (Table 4.6). Cadmium was found to be below the detection limit at all but 

two sites. This is lower than the NS&T national median of 0.19 μg/g, but is similar to other studies in 

tropical systems (Table 4.7). Neither site with detectable Cd exceeded sediment quality guidelines 

(Table 4.7). Cadmium concentrations were significantly higher (p<0.05) in the Inner Bay relative to 

the Central and Outer Bays. 

Coral 

Cadmium concentrations in coral tissues ranged from 0.21 μg/g to 0.31 μg/g, with a mean of 0.25 

μg/g and a median of 0.25 μg/g (Table 4.5). This is higher than what was detected in sediments and 

may indicate that coral are accumulating cadmium in their tissues over time. This is higher than what 

was observed in southwest Puerto Rico, but similar to what was observed in Vieques, Puerto Rico 

(Table 4.6). There was no statistically significant difference between the inshore and offshore strata 

(Appendix B, Figure B.4). No statistically significant correlations were found between coral tissue Cd 

concentrations and depth, longitude (i.e., long shore position) or distance from land. 
Baseline Assessment of Jobos Bay, Puerto Rico: Contaminants 

4.3.6.5. Chromium (Cr) 

Sediment 

Chromium (Cr) concentrations in sediments ranged from 0 μg/g to 29.8 μg/g, with a mean of 18.2 μg/g 

and a median of 18.5 μg/g (Table 4.6). This is lower than the NS&T national median of 66 μg/g and no 

site exceeded sediment quality guidelines. Cr concentrations were significantly higher (p<0.05) in the 

Inner Bay relative to the Central and Outer Bays (Figure 4.11 and Appendix B, Figure B.5). 

Coral 

Chromium was not detected in any coral tissue samples (Table 4.5). Similarly, no Cr was detected in 

corals in southwest Puerto Rico; however, Cr was detected in coral tissues in Vieques, Puerto Rico 

(Table 4.5), so corals do have the capacity to accumulate chromium. 

4.3.6.6. Copper (Cu) 

Sediments 

Copper (Cu) concentrations in sediments ranged from 1.37 μg/g to 73.7 μg/g, with a mean of 33.83 

μg/g and a median of 29.85 μg/g (Table 4.6). This is higher than the NS&T national median of 15.95 

μg/g, and higher than other studies in tropical systems (Figure 4.7), indicating that Jobos Bay has 

elevated amounts of copper. No site exceeded the ERM guideline but 19 of 43 sites exceeded the 

ERL, indicating that there is a slight (<10%) chance of toxicity to benthic infaunal organisms. Copper 

concentrations were significantly higher (p<0.05) in the Inner Bay relative to the Central and Outer 

Bays (Appendix B, Figure B.6). Potential sources of copper include agricultural fungicides and antifouling boat paint. 

Coral 

Copper concentrations in coral ranged from 2.37 μg/g to 97.20 μg/g, with a mean of 50.30 μg/g and 

a median of 68.95 μg/g (Table 4.5). This is higher than coral tissues measured in other studies in 

Puerto Rico (Table 4.5), which mirrors the pattern in sediment Cu and suggests that there may be a 

copper contamination problem in Jobos Bay. There was no statistically signifi cant difference between 

the inshore and offshore strata (Appendix B, Figure B.7). No statistically significant correlations were 

found between coral tissue Cu concentrations and depth, longitude (i.e., long shore position) or 

distance from land. 

4.3.6.7. Iron (Fe) 

Sediments 

Iron (Fe) concentrations in sediments ranged from 1060 μg/g to 50500 μg/g, with a mean of 26565 

μg/g and a median of 26650 μg/g (Table 4.6). Iron is a major crustal element and is generally not 

considered to be a pollutant. There are no sediment quality guidelines for Fe. Iron concentrations 

were significantly higher (p<0.05) in the Inner Bay relative to the Central and Outer Bays (Appendix 

B, Figure B.8). 

Coral 

Iron concentrations in coral ranged from 110 μg/g to 480 μg/g, with a mean of 212 μg/g and a median 

of 176 μg/g (Table 4.5). There was no statistically significant difference between the inshore and 

offshore strata (Appendix B, Figure B.9). No statistically significant correlations were found between 

coral tissue Fe concentrations and depth, longitude (i.e., long shore position) or distance from land. 

4.3.6.8. Mercury (Hg) 

Sediments 

Mercury (Hg) concentrations in sediments ranged from 0.0014 μg/g to 0.144 μg/g, with a mean of 

0.043 μg/g and a median of 0.03085 μg/g (Table 4.6). This is lower than the NS&T national median 

133 4 - Contaminants 
Baseline Assessment of Jobos Bay, Puerto Rico: Contaminants 

134 4 - Contaminants

of 0.062 μg/g and similar to other studies in tropical systems (Table 4.7). No site exceeded sediment 

quality guidelines. Mercury concentrations were significantly higher (p<0.05) in the Inner Bay relative 

to the Central and Outer Bays (Figure 4.11 and Appendix B, Figure B.10). 

Coral 

Mercury concentrations in coral 

ranged from 0.001 μg/g to 0.0038 

μg/g, with a mean of 0.002 μg/g and 

a median of 0.0019 μg/g (Table 4.5). 

This is a similar finding to Vieques, 

Puerto Rico where mercury was 

detected in six out of 35 samples 

(Table 4.5). Mercury concentrations 

were significantly higher (p<0.05) 

in the offshore stratum than 

inshore (Appendix B, Figure B.11). 

This pattern could be a result of 

atmospherically deposited Hg from 

fossil fuel combustion at the nearby 

power plant (Figure 4.14), i.e. the 

stack height minimizes near shore 

deposition. 

4.3.6.9. Manganese (Mn) 

Sediments 

Manganese (Mn) concentrations in sediments ranged from 33.1 μg/g to 1130 μg/g, with a mean of 

510.6 μg/g and a median of 528.5 μg/g (Table 4.6). This is slightly higher than the NS&T national 

median of 444.5 μg/g. Sediment quality guidelines do not exist for Mn. Manganese concentrations 

were significantly higher (p<0.05) in the Inner Bay relative to the Central and Outer Bays (Appendix 

B, Figure B.12) 

Coral 

Manganese concentrations in coral tissues ranged from 8.33 μg/g to 24.60 μg/g, with a mean of 

13.33 μg/g and a median of 11.60 μg/g (Table 4.5). This is slightly higher than levels measured in 

other studies in Puerto Rico (Table 4.5). There was no statistically significant difference between the 

inshore and offshore strata (Appendix B, Figure B.13). No statistically signifi cant correlations were 

found between coral tissue Mn concentrations and depth, longitude (i.e., long shore position) or 

distance from land. 

4.3.6.10. Nickel (Ni) 

Sediments 

Nickel (Ni) concentrations in sediments ranged from 0 μg/g to 31 μg/g, with a mean of 10.96 μg/g and 

a median of 10.1 μg/g (Table 4.6). This is below the NS&T national median of 25.05 μg/g and similar 

to other sites in tropical systems (Table 4.7). No sites exceeded the ERM sediment quality guidelines. 

Nickel concentrations were significantly higher (p<0.05) in the Inner Bay relative to the Central and 

Outer Bays (Appendix B, Figure B.14). 

Coral 

Nickel concentrations in coral tissues ranged from 0.80 μg/g to 6.84 μg/g, with a mean of 3.13 μg/g 

and a median of 2.63 μg/g (Table 4.5). This is similar to what was observed in other studies in Puerto 

Figure 4.14. Power generation facility adjacent to Jobos Bay. Photo: NOAA CCMA 
Baseline Assessment of Jobos Bay, Puerto Rico: Contaminants 

Rico (Table 4.5). There was no statistically significant difference between the inshore and offshore 

strata (Appendix B, Figure B.15). No statistically significant correlations were found between coral 

tissue Ni concentrations and depth, longitude (i.e., long shore position) or distance from land. 

4.3.6.11. Lead (Pb) 

Sediments 

Lead (Pb) concentrations in sediments ranged from 0.227 μg/g to 16.7 μg/g, with a mean of 7.15 μg/g 

and a median of 6.02 μg/g (Table 4.6). This is below the NS&T national median of 22.25 μg/g, and 

similar to other studies in tropical systems (Table 4.7). No sites exceeded sediment quality guidelines. 

Lead concentrations were significantly higher (p<0.05) in the Inner Bay relative to the Central and 

Outer Bays (Appendix B, Figure B.16). 

Coral 

Lead concentrations in coral tissues ranged from 0.08 μg/g to 12.50 μg/g, with a mean of 1.43 μg/g and 

a median of 0.20 μg/g (Table 4.5). The observed concentrations in Jobos Bay are higher than seen in 

other systems in Puerto Rico (Table 4.5), despite not having high concentrations of Pb in sediments. 

There was no statistically signifi cant difference between the inshore and offshore strata; however, Pb 

showed a weak positive correlation with distance from shore (p=0.0099, α=0.62), and a strong negative 

correlation (p=0.001, α=-0.7324) with longitude (Figure 4.15), i.e. Pb concentrations were higher to 

the west. No statistically significant correlation was found between coral tissue Pb concentrations 

and depth. There are many sources of Pb in the environment and more research is needed to 

understand these spatial patterns. The positive correlation with distance from shore is similar to what 

is seen for Hg and As (offshore stratum significantly higher than inshore stratum), and could indicate 

135 4 - Contaminants 

Figure 4.15. Lead (Pb) concentrations in corals (P. astreoides). White outline are coral reefs in inner stratum. Red outline are coral

reefs in outer stratum. 
Baseline Assessment of Jobos Bay, Puerto Rico: Contaminants 

136 4 - Contaminants

that the power plant is a source of 

Pb. Furthermore, satellite imagery 

of the power plant shows stack 

plume emissions drifting to the west 

(Figure 4.16), which could explain 

the gradient of concentrations from 

east to west. It is possible that this 

longitudinal pattern is not observed in 

the sediment concentration because 

sediment concentrations are closely 

tied to sediment TOC and percent 

fines. 

4.3.6.12. Antimony (Sb) 

Sediments 

Antimony (Sb) concentrations in sediments ranged from 0 μg/g to 0.589 μg/g, with a mean of 0.217 

μg/g and a median of 0.2685 μg/g (Table 4.6). This is lower than the NS&T national median of 0.485 

μg/g and similar to other studies in Puerto Rico (Table 4.7). There are no sediment quality guidelines 

for antimony. Antimony concentrations were significantly higher (p<0.05) in the Inner Bay relative to 

the Central and Outer Bays (Appendix B, Figure B.17) 

Coral 

Antimony was not measured in coral tissue. 

4.3.6.13. Selenium (Se) 

Sediments 

Selenium (Se) concentrations in sediments ranged from 0 μg/g to 0.156 μg/g, with a mean of 0.332 

μg/g and a median of 0.2755 μg/g (Table 4.6). This is similar to the NS&T national median of 0.33 

μg/g, but slightly higher than other studies in Puerto Rico (Table 4.7). There are no sediment quality 

guidelines for Se. Concentrations of Se showed no statistical difference between the three strata 

(p>0.05; Appendix B, Figure B.18). 

Coral 

Selenium concentrations in coral tissues ranged from 0.13 μg/g to 0.26 μg/g, with a mean of 0.18 μg/g 

and a median of 0.18 μg/g, which is slightly higher than observed in other locations in Puerto Rico 

(Table 4.5). There was no statistically significant difference between the inshore and offshore strata 

(Appendix B, Figure B.19). No statistically significant correlations were found between coral tissue Se 

concentrations and depth, longitude (i.e., long shore position) or distance from land. 

4.3.6.14. Tin (Sn) 

Sediments 

Tin (Sn) concentrations in sediments ranged from 0 μg/g to 2.74 μg/g, with a mean of 1.13 μg/g and 

a median of 1.17 μg/g (Table 4.6). This is lower than the NS&T national median of 1.75 μg/g and 

similar to what has been observed in other tropical systems (Table 4.7). There are no sediment quality 

guidelines for tin. Tin concentrations were significantly higher (p<0.05) in the Inner Bay relative to the 

Central and Outer Bays (Appendix B, Figure B.20). 

Figure 4.16. Satellite image of Jobos Bay showing plume from power plant. 
Baseline Assessment of Jobos Bay, Puerto Rico: Contaminants 

Coral 

Tin concentrations in coral tissues ranged from 0 μg/g to 0.10 μg/g, with a mean of 0.02 μg/g and a 

median of 0.01 μg/g; this is similar to what was observed in southwest Puerto Rico, but lower than 

observed values in Vieques, Puero Rico (Table 4.5). In Jobos Bay, there was only one site in the study 

area with measurable Sn (Appendix B, Figure B.21). There was no statistically signifi cant difference 

between the inshore and offshore strata. No statistically significant correlations were found between 

coral tissue Sn concentrations and depth, longitude (i.e., long shore position) or distance from land. 

4.3.6.15. Zinc (Zn) 

Sediments 

Zinc (Zn) concentrations in sediments ranged from 1.57 μg/g to 117 μg/g, with a mean of 54.2 μg/g 

and a median of 48.5 μg/g (Table 4.6). This is lower than the NS&T national median of 74 μg/g, and 

similar to other studies in tropical systems (Table 4.7). No sites exceeded sediment quality guidelines 

(Table 4.7). Zinc concentrations were significantly higher (p<0.05) in the Inner Bay relative to the 

Central and Outer Bays (Appendix B, Figure B.22). 

Coral 

Zinc concentrations in coral tissues ranged from 2.56 μg/g to 16.90 μg/g, with a mean of 8.59 μg/g 

and a median of 7.88 μg/g, which was similar to what has been observed in other studies in Puerto 

Rico (Table 4.5). There was no statistically significant difference between the inshore and offshore 

strata (Appendix B, Figure B.23). No statistically significant correlations were found between coral 

tissue Zn concentrations and depth, longitude (i.e., long shore position) or distance from land. 

4.4. FURTHER INTERPRETATION OF SEDIMENT RESULTS 

The adsorption of organic contaminants onto sediments is strongly influenced by grain size (Hassett 

et al., 1980). A regression between grain size and the concentration of total PAHs in the sediment 

samples indicated a highly signifi cant (Spearman’s ρ = 0.6872, p<0.0001) relationship between the 

fi nes fraction of the sediment and the concentration of total PAHs. A bivariate regression run between 

 total PAH and log TOC indicated a significant (p<0.0001, r2 log = 0.515) relationship between TOC 10 10 

and the concentration of total PAHs, as has been found by others (Hassett et al., 1980; Shine and 

Wallace, 2000) in aquatic systems. 

The distribution of high (≥4 rings) molecular weight (HMW) versus low molecular weight (LMW) PAHs 

(Table 4.1) in sediment samples has been used as an indicator of pyrogenic (combustion-related) 

versus petrogenic (e.g., petroleum product from fuel or oil spills, or other discharges) sources (Neff 

et al., 2005). Although the mean concentration of the HMW or pyrogenic PAHs was higher in Jobos 

Bay sediments, a Wilcoxon test revealed no signifi cant difference in the mix of LMW and HMW PAHs 

(Prob>ChiSq = 0.0639). The ratios of phenanthrene to anthracene (P/A), and fluoranthene to pyrene 

(Fluo/Pyr) have also been used to assess the relative contributions of petrogenic versus pyrogenic 

sources of PAHs (Budzinski et al., 1997). P/A ratios less than 10 are more indicative of pyrogenic 

sources, while Fluo/Pyr ratios greater than one are also thought to be associated with pyrogenic 

sources. Except for SWP43, all the sites sampled had P/A ratios of less than 10, and all the Fluo/Pyr 

ratios were close to one. These results are similar to those obtained by Aldarondo-Torres et al. (2010) 

who found P/A and Fluo/Pyr ratios in Jobos Bay sediments indicative of pyrogenic sources. There 

are two dischargers in the watershed with U.S. Environmental Protection Agency (USEPA) National 

Pollutant Discharge Elimination System (NPDES) permits for oil and grease (see Chapter 1,Table 

1.1, Figure 1.1) which are also contributing to PAH levels in the Bay. 

137 4 - Contaminants 
Baseline Assessment of Jobos Bay, Puerto Rico: Contaminants 

138 4 - Contaminants

Because the measurement of total DDT is made up of both the parent isomers and degradation 

products, the ratio of parent compounds to degradation products can provide some insight into the 

relative age or “freshness” of the DDT present. Total DDT concentrations containing higher ratios 

of the parent compound are more likely to be recently introduced into the environment. The ratio of 

parent compounds (2,4’-DDT and 4,4’-DDT) to degradation products (2,4’-DDD, 4,4’-DDD, 2,4’-DDE, 

4,4’-DDE and DDMU) ranged from zero (no parent compound detected, at 22 sites) to one (parent 

compound detected, but no degradation products detected, at site OTR31). Five sites (four in the 

central stratum, plus OTR31) had greater than 50% parent material. This may be indicative of “newer” 

DDT, although interpretation of these ratios can be problematic when concentration values are close 

to the detection limit. None of the five sites with greater than 50% parent material had high total DDT 

concentrations (below the ERL), which does not suggest that the levels of DDT at these sites are of 

environmental concern. 

For the majority of metals, elevated concentrations were observed mostly in sediments collected 

from the Inner Bay in the eastern stratum. However, spikes of relatively elevated concentrations were 

observed for some metals throughout the study area. For instance, the highest concentrations were 

observed at NER24 and SWP44 in Central Bay for As; NER24 and OTR34 in Central and Outer Bays, 

respectively, for Cr, and the highest concentrations for Ni were found at sites NER24, SWP43 and 

SWP44 in Central Bay. 

4.4.1. Inter-metal and grain size correlation 

Spearman rank correlations among all metals, grain size and TOC are shown in Table 4.8. Spearman 

coefficient Rho (ρ) values of 0.707 or higher were discussed as indicative of strong correlation, while 

values below 0.707 indicate weak correlation. Strong associations were found among several groups 

of metals. Among the major elements, Al and Fe showed strong and direct correlations with each 

other and with virtually all trace metals except Ag. Also, Mn was positively correlated with Al, Fe and 

all other trace elements except Se (ρ>0.05). Apart from Ag, which had a poor and inverse correlation; 

the results indicated that, in general, inter-metal correlations were positive. Other studies have 

reported significant correlations between major elements, such as Al, Fe, and Mn, and trace metals 

in similar habitats off the southeastern coast of the United States (Windom et al., 1989; Schropp et al., 

1990). These studies suggest that Al and Fe can be used as normalizing factors for metals in natural 

estuaries and coastal environments to assess anthropogenic metals enrichment. 

Grain size and sediment TOC were found to be positively correlated with all major and trace elements, 

excluding Ag. All metals have a weak correlation with TOC. Relative to TOC, grain size showed 

stronger correlations (ρ>0.707) with the major and trace metals. These results confirm that elemental 

concentrations are elevated in finer sediments because of higher volume to surface ratio (Förstner 

and Wittmann, 1981). The depositional zone in the Inner bay stratum had metal concentrations 

greater than the other strata, likely due to fine grained sediments and proximity to metal sources. 

Total organic carbon ranged from 0.3-4.3% and was only weakly correlated with metals. 

The highest percentages of TOC were observed in sediment from the central stratum, while sediments 

from the eastern and western stratum were relatively low in TOC content. Except for Ni and Se, TOC 

content was not strongly correlated with metals suggesting that the influence of organic matter on 

metal distribution may be far less important than that of grain size. This observation corroborates with 

assertion by Förstner and Wittmann (1981) and Windom et al. (1989), which indicated that in natural 

estuarine and coastal sediments, concentrations of metals are predominantly determined by detrital 

inorganic material rather than organic and nondetrital materials. 
Baseline Assessment of Jobos Bay, Puerto Rico: Contaminants 

Table 4.8. Spearman rank correlations between metals, grain size (clay + silt) and total organic carbon (TOC) in sediment from Jobos 

Bay. Bold lettering represents the Rho value (ρ) and and standard script represents p values. 

4 - Contaminants

Label %TOC %Fine Ag Al As Cr Cu Fe Hg Mn Ni Pb Sb Se Sn 

0.424 

%Fine 

0.005 

-0.111 -0.316 

Ag 0.479 0.039 

0.239 0.911 -0.366 

Al 

0.122 0.000 0.016 

0.405 0.720 -0.398 0.740 

As 

0.007 0.000 0.008 0.000 

0.520 0.739 -0.075 0.752 0.700 

Cr 

0.000 0.000 0.632 0.000 0.000 

0.619 0.822 -0.133 0.801 0.683 0.892 

Cu 

0.000 0.000 0.394 0.000 0.000 0.000 

0.390 0.911 -0.252 0.965 0.787 0.845 0.873 

Fe 

0.010 0.000 0.102 0.000 0.000 0.000 0.000 

0.693 0.747 -0.169 0.696 0.700 0.815 0.941 0.781 

Hg 0.000 0.000 0.279 0.000 0.000 0.000 0.000 0.000 

0.039 0.839 -0.402 0.952 0.696 0.615 0.670 0.887 0.582 

Mn 

0.801 0.000 0.008 0.000 0.000 0.000 0.000 0.000 0.000 

0.708 0.573 -0.239 0.555 0.639 0.800 0.814 0.631 0.831 0.373 

Ni 

0.000 0.000 0.122 0.000 0.000 0.000 0.000 0.000 0.000 0.014 

0.689 0.784 -0.233 0.722 0.700 0.798 0.938 0.793 0.975 0.612 0.824 

Pb 

0.000 0.000 0.132 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 

0.368 0.559 -0.286 0.633 0.790 0.725 0.648 0.665 0.622 0.539 0.697 0.642 

Sb 

0.015 0.000 0.063 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 

0.918 0.510 -0.156 0.353 0.521 0.639 0.687 0.482 0.721 0.137 0.789 0.709 0.497 

Se 

0.000 0.000 0.318 0.020 0.000 0.000 0.000 0.001 0.000 0.380 0.000 0.000 0.001 

0.560 0.842 -0.253 0.747 0.626 0.823 0.887 0.798 0.852 0.635 0.686 0.868 0.607 0.650 

Sn 

0.000 0.000 0.102 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 

0.541 0.900 -0.200 0.893 0.720 0.891 0.964 0.945 0.891 0.777 0.735 0.906 0.654 0.627 0.914 

Zn 

0.000 0.000 0.199 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 

139 

In Jobos Bay, the distribution of inorganic material (grain size) demonstrated a distinctive general 

pattern. Fine grained material showed a decreasing gradient from the eastern to the western zone of 

the study area (Figure 4.17). These findings are in agreement with previous results reported by the 

Puerto Rico Nuclear Center (PRNC, 1972), which characterized the eastern area (Inner Bay) stratum 

as having silty bottom sediment relative to areas of the bay where sediments are more or less sandy. 

The predominantly elevated proportion of fine sediment materials in the Inner bay demonstrates 

that the area is a low energy depositional zone. Physical conditions and the water circulation in the 

Inner Bay are suitable for sedimentation of terrigenous fine particles suspended in runoff waters. 

Sedimentation of these fine particles in the Inner Bay may be favored as a result of surface water 

input from Quebrada Coquí-Aguas Verdes and Río Seco, the shallowness of the bay and the fact that 

the Inner Bay is semi-enclosed (PRNC, 1972). 
Baseline Assessment of Jobos Bay, Puerto Rico: Contaminants 

140 4 - Contaminants 

Figure 4.17. Sediment grain size (percent fines). 

The concentrations of the majority of metals showed similar distributions as that of grain size. Relative 

to the Outer and Central Bays, significantly high (ρ<0.05) metal concentrations are found in the Inner 

Bay stratum located in the eastern area of the bay. The physiographic characteristic of the stratum 

and the sediment texture may be the cause of the relatively high metal concentrations in the Inner 

Bay stratum. The Inner Bay is the receiving basin for Quebrada Coquí-Aguas Verdes and Río Seco, 

which transport terrigenous detrital materials from the upland. Being physically protected from the 

scouring of offshore water, the Inner Bay acts like a depositional area characterized by calm waters. 

As a result, sediment materials transported by Quebrada Coquí-Aguas Verdes and Río Seco are 

deposited along with pollutants. Furthermore, the presence of metals in elevated concentrations in 

the Inner Bay may be linked to its characteristically fine grained sediment. It has been shown that 

because of their high surface to volume ratio, fine sediments like those found in the Inner Bay, tend 

to sequester higher concentrations of metals (Förstner and Wittmann, 1981; Ujević et al., 2000; 

Oreščanin et al., 2004). Conversely, the relatively low concentration of metals found in the Outer and 

Central Bays may be due the presence of a sandier type of sediment and particularly to the fact that 

these systems are well flushed by offshore water. 

Among the trace elements, Cd was measured at very low concentration at virtually all the sites in 

the study area. Chemically, Cd is strongly affected by diagenic processes that impact its equilibrium 

between pore water and the overlying water column (Rosenthal et al., 1995). During this process, Cd 

migrates into porewater in the top oxidized sediment layer while the inverse occurs in the reduced 

deeper layers. The diagenetic behavior of Cd is usually linked to its depletion in the upper oxidized 

layer of sediments (Rosenthal et al., 1995; Apeti et al., 2009). Because of its low concentration in this 

study, Cd was not included in any subsequent discussion. 

The presence of metals at relatively elevated concentration in the eastern area of Jobos Bay may 

be linked to diffused nonpoint sources of natural and anthropogenic origins. Jobos Bay watershed is 

host to a variety of residential, commercial and industrial activities, most notably a coal power plant, a 

petroleum refinery and pharmaceutical facilities (DNER, 2002), that likely contribute pollutants to the 

bay. In the Jobos Bay watershed, there are three documented point source dischargers of pollutants 
Baseline Assessment of Jobos Bay, Puerto Rico: Contaminants 

relevant to this study (See Chapter 1, Table 1.1, Figure 1.2). These dischargers represent a source 

of Cr, Cu, Fe, Pb, Mn, Se and Zn, although the amounts of these metals being discharged are fairly 

low. However, USEPA documented significant non-compliance events for Zn in 2007 and 2008, and 

Ag, Cu and Fe in 2009. Because sediment sampling for this study was completed in 2008, the 2009 

events could not have influenced the data presented here; however, it is noteworthy that these point 

sources can contribute to the contaminant load of the system. 

Coal burning is associated with atmospheric pollution by metals, such as As, Cd, Cu, Hg, Pb, Ni, 

Zn found in fly ash (Theis et al., 1978; McBride et al., 1978). Atmospheric depositions of metal from 

industrial emissions in the vicinity of Jobos Bay were assessed (Jiménez-Vélez et al., 2003, 2009; 

Gioda et al., 2006). Relative to other regions in Puerto Rico, concentrations of metal in airborne 

particles were higher in the Salinas watershed, which incorporates Jobos Bay (Jiménez-Vélez et al., 

2003). Gioda et al. (2006) also concluded that the presence of Cd, Cu, Fe, Ni, Hg and Pb in airborne 

particles in the Jobos Bay may be linked to both long-range atmospheric transport and anthropogenic 

activities in the bay’s watershed. Rather than being from local industrial activities, previous studies 

indicated that concerns of water quality in Jobos Bay may be linked to land-based sources from 

agricultural runoff and soil erosion (DNER, 2002). 

Preliminary studies (Altieri-Rijos, 2004) revealed that pesticides and fertilizers applied in agricultural 

fields may also be transported to the JBNERR bay (DNER, 2002). Although metals such as Cd, 

Cr, Cu, Fe, Hg, Mn, Pb, Ni and Zn are minor constituents of phosphorus fertilizers (Förstner and 

Wittmann, 1981), they also occur naturally. Copper is also used as an agricultural fungicide, and 

in anti-fouling boat paint. As a result, it is difficult to distinguish between natural and anthropogenic 

sources. Metallic contaminants, whether from natural or anthropogenic sources, are supplied in 

solution or in association with fine-grained suspended solids and colloidal inorganic particles. These 

particles are usually deposited in areas of low hydrodynamic energy along streams or are transported 

to lakes, estuaries, or the ocean during times of increased river flow (Loring, 1991; Simpson et al., 

2000). 

A number of mechanisms, based on geochemical processes that control behavior and fate of metals in 

coastal waters, have been proposed (Förstner and Wittmann, 1981; Schropp and Windom, 1987). In 

natural coastal waters, trace metals co-precipitate with the oxide/hydroxides of Al, Fe and MN usually 

into the fine-grained fraction (clay or aluminosilicate) of sediments (Schropp and Windom, 1987). 

Since aluminosilicates are the metal-rich phase of bottom sediment, many approaches to delineate 

anthropogenic versus natural sources are based on grain size, using Al and Fe for normalization 

(Förstner and Wittmann, 1981; Windom et al., 1989; MacDonald, 1994). That is, without anthropogenic 

inputs, metal concentrations are expected to co-vary among each other and with Al, Fe and Mn, given 

that factors such as precipitation or diagenesis are very small. Deviations from direct metal-Al/Fe 

or metal-grain size correlations are interpreted as anthropogenic enrichment (Windom et al., 1989; 

MacDonald, 1994; Carvalho et al., 2002). 

In Jobos Bay, most of the metals, except Ag, were found to be positively correlated with grain size 

(Table 4.8). Correlations of metals versus grain size and Al are exemplified using results for Ag, Fe, 

Mn and Zn (Figures 4.18 and 4.19). The positive correlations suggest that sediment texture greatly 

infl uences the distribution of metals. Additionally, the positive inter-metal correlations, including those 

between Al, indicate that metal concentrations in Jobos Bay may be of natural origins. 

Considering the arid conditions in the watershed and lack of over land flow, other contributions of 

metals to Jobos Bay may include stormwater runoff, inputs from Quebrada Coquí-Aguas Verdes and 

Río Seco and atmospheric deposition. Weathering of bedrock and soil erosion produce mineral debris 

141 4 - Contaminants 
Baseline Assessment of Jobos Bay, Puerto Rico: Contaminants 

142 4 - Contaminants 

Figure 4.18. Correlation of aluminum and silver with grain size (percent fines). 

Figure 4.19. Correlation of iron, manganese, zinc and silver with aluminum. 
Baseline Assessment of Jobos Bay, Puerto Rico: Contaminants 

that are natural sources of metal in sediment transported into coastal waters (Förstner and Wittmann, 

1981). Transport of detrital materials within watershed by stormwater and runoff, and Quebrada 

Coquí-Aguas Verdes may constitute the largest source of metals in Jobos Bay. Although Quebrada 

Río Seco is a seasonal intermittent river, it may also contribute to metal bound sediment transport 

into the bay especially during wet seasons. However, the characteristic deviations of Ag from direct 

positive correlation with both Al and grain size may be interpreted as having anthropogenic inputs. 

Of the 15 metals, only Ag was found to have a spatial distribution that contrasted with that of the 

general east-west decreasing pattern (Figure 4.12). Additionally, Ag did not show a direct correlation 

with Al and grain size. Current levels of Ag concentration in Jobos Bay are lower than the ERL and 

ERM values, but the fact that it has relatively elevated concentrations in the more sandy western 

area of the bay (Figure 4.12), suggests enrichment. Possible sources of Ag in the western stratum 

may include industrial discharges or runoff. It should be noted that there are no NPDES permitted 

dischargers of silver in the watershed. 

4.5. CONCLUSIONS 

The concentrations of the contaminants analyzed for this project were generally similar to what has been 

found in other areas of Puerto Rico. Overall, the levels of chemical contaminants in the sediments in 

the Jobos Bay study area were below established sediment quality guidelines, suggesting that effects 

on infaunal biota were unlikely. The ERMs and the PEL were not exceeded for any of the classes of 

compounds for which these guidelines have been developed. For individual PAHs, however, there 

were exceedances of the PEL at one site (INR4) in the inner stratum for five PAHs, indicating that 

infaunal biota at this site could be impacted by the presence of at least these individual PAHs. ERL’s 

were exceeded at some sites for total DDT, total PAHs, chlordane, dieldrin, arsenic and copper. 

In general, the concentration of the analyte classes including metals, total PAHs, total PCBs and 

total DDT were higher in the inner stratum, which is likely a function of land use activities, delivery 

of the contaminants via surface water runoff and river inputs, and lower water exchange with the 

open ocean. This pattern was reversed for tributyltin and silver with outer stratum sediments having 

significantly higher sediment concentrations. The TBT pattern appears to be associated with marinarelated activities, but it is unclear what is driving this pattern for silver. 

Sediment characteristics, such as grain size and TOC, and baseline metal concentrations have been 

assessed in Jobos Bay. Overall, the distributions of sediment grain size and TOC content suggested 

heterogeneous bottom substrates in Jobos Bay. Grain size appears to heavily influence the distribution 

of all metals except that of Ag. Most metals were found to be significantly higher in the eastern area 

of the bay relative to central and western areas. However, maximum concentration values were 

within concentration ranges found in other similar estuarine systems. Sediment normalizing factors, 

such as Al and grain size, were positively correlated with virtually all metals. This suggests that 

although the watershed contains several low density population centers and some industrial plants, 

anthropogenic inputs may be negligible. Likely sources of metals in Jobos Bay may include natural 

bedrock weathering and transportation of detrital materials by Quebrada Coquí-Aguas Verdes and 

Río Seco. The more diffuse nonpoint source of atmospheric deposition resulting from local and 

long range airborne particles are also possible sources, which may be contributing to the overall 

metal concentration in Jobos Bay. The lack of correlation of Ag with normalizing factors suggested 

enrichment from anthropogenic sources for this metal. However, the concentrations of Ag as well as 

those of other metals were well below sediment quality guidelines suggesting that metal toxicity to 

biota is limited in Jobos Bay. This study is the first comprehensive assessment of metals in Jobos 

Bay and the associated data serve as baseline information for further assessments and monitoring. 

143 4 - Contaminants 
Baseline Assessment of Jobos Bay, Puerto Rico: Contaminants 

144 4 - Contaminants

The degradation of coral reef 

ecosystems worldwide has led to 

intensive efforts to understand and 

mitigate the stressors responsible 

for the declines of these valued 

and fragile ecosystems. The role of 

pollution in the degradation of coral 

reefs is often cited as a major factor, 

but the degree to which pollution 

and more specifically chemical 

contaminants are present in coral reef 

areas is, in most cases, unknown. 

Because of this, coral reef managers 

may be missing an important piece 

of information needed to effectively 

manage reef areas. Quantifying the 

types and concentrations of chemical 

contaminants present in the sediments in Jobos Bay is an important aspect of the Conservation 

Effects Assessment Project (CEAP), providing a baseline of conditions in the nearshore waters, and 

a means for assessing the benefits of Best Management Practices that may be implemented in the 

Jobos Bay watershed (Figure 4.20). 

ACKNOWLEDGEMENTS 

We would like to thank Captain Claudio Burgos of the Estuarino for his skill and patience in getting 

us to the sampling sites. We also greatly appreciate boat support provided by PRDNER. We would 

also like to thank the CEAP project partners, JBNERR and the USDA. This chapter was greatly 

improved thanks to helpful comments from Dr. Gunnar Lauenstein, Dr. Fatin Samara and Dr. Carlos J. 

Rodríguez-Sierra. Funding for this work was provided by NOAA’s Coral Reef Conservation Program 

and the USDA (CEAP). 

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Assessment and Management 1(1): 22-33. 

Negri, A.P., L.D. Smith, N.S. Webster, and A.J. Heyward. 2002. Understanding ship-grounding 

impacts on a coral reef: potential effects of anti-foulant paint contamination on coral recruitment. 

Marine Pollution Bulletin 44: 111-117. 

Oreščanin, V., Lulić, S., Pavlović, G. and Mikelic, L. 2004. Granulometric and chemical composition of 

the Sava River sediments upstream and downstream of the Krško nuclear power plant. Environmental 

Geology 46: 605-613. 

Pait, A.S., D.R. Whitall, C.F.G. Jeffrey, C. Caldow, A.L. Mason, J.D. Christensen, M.E. Monaco, and 

J. Ramirez. 2007. An assessment of chemical contaminants in the marine sediments of southwest 

Puerto Rico. NOAA Technical Memorandum NOS NCCOS 52. Silver Spring, MD. 116 pp. (Online) 

http://www.ccma.nos.noaa.gov/publications/southwestpuertorico.pdf (Accessed 13 June 2011). 

Pait, A.S., D.R. Whitall, C.F.G. Jeffrey, C. Caldow, A.L. Mason, G.G Lauenstein, and J.D. Christensen. 

2008. Chemical contamination in southwest Puerto Rico: an assessment of organic contaminants in 

nearshore sediments. Marine Pollution Bulletin 56: 580-606. 

Pait, A.S., C.F.G. Jeffrey, C. Caldow, D.R. Whitall, S.I. Hartwell, A.L. Mason, and J.D. Christensen. 

2009. Chemical contaminants in the coral Porites astreoides from Southwest Puerto Rico. NOAA 

Technical Memorandum NOS NCCOS 91. Silver Spring, MD. 32 pp. 

147 4 - Contaminants 
Baseline Assessment of Jobos Bay, Puerto Rico: Contaminants 

148 4 - Contaminants

Pait, A.S., A.L. Mason, D.R. Whitall, J.D. Christensen, and S.I. Hartwell. 2010. Assessment of 

Chemical Contaminants in Sediments and Corals in Vieques. pp. 101-150. In: L.J. Bauer and M.S. 

Kendall (eds.). An Ecological Characterization of the Marine Resources of Vieques, Puerto Rico 

Part II: Field Studies of Habitats, Nutrients, Contaminants, Fish, and Benthic Communities. NOAA 

Technical Memorandum NOS NCCOS 110. Silver Spring, MD. 174 pp. 

Peachey, R.L. and D.G. Crosby. 1996. Phototoxicity in tropical reef animals. Marine Environmental 

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Rosenthal, Y., P. Lam, E.A. Boyle, and J. Thomson. 1995. Authigenic cadmium enrichment in suboxic 

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Baseline Assessment of Jobos Bay, Puerto Rico: Contaminants 

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149 4 - Contaminants 
Chapter 5
 

Baseline Assessment of Jobos Bay, Puerto Rico: Nutrients and Pesticides 

Spatial and Temporal Variability in the Water Column 

Nutrients and Pesticides of Jobos Bay
 

David Whitall1,4, Angel Dieppa2 and Thomas L. Potter3 

5.1. INTRODUCTION 

The objectives of this portion of the ecological characterization project of Jobos Bay were to: 

1. Quantify magnitude and spatiotemporal variability of surface water nutrients and pesticides 

within the Jobos Bay National Estuarine Research Reserve (JBNERR or Reserve); 

2. Establish a baseline of nutrient and pesticide conditions against which to measure changes in 

the future; 

3. Link observed concentrations of nutrients and pesticides to hydrological forcing factors. 

5.1.1. Nutrients 

Primary productivity in marine systems is most often limited by nitrogen (N), but phosphorus (P) 

can be co-limiting under certain circumstances, and systems can alternate from N limitation to P 

limitation through space and time. In estuarine systems, nutrient enrichment can result in algal 

blooms, changes in algal community composition (including harmful algal blooms) and increases in 

hypoxia/anoxia (Bricker et al., 2007). In tropical systems, excess nutrient loads can cause increases 

in macroalgal growth and can have deleterious effects on corals, such as macroalgae outcompeting 

and overgrowing corals. Finally, nitrogen and phosphorus can impact corals directly by lowering 

fertilization success (Harrison and Ward, 2001), and reducing both photosynthesis and calcification 

rates (Marubini and Davies, 1996). 

In Jobos Bay, the primary producers within the submerged environment consist of microbial mats, 

nearly 90 species of algae (Almodóvar, 1964) and the dominant seagrasses that include the climax 

species Thalassia testudinum, Syringodium filiforme, Halodule wrightiiA, and Halophila decipiens. 

Diatoms and dinoflagellates dominate the phytoplankton community. 

Land based contributions of nutrients come from a variety of sources. Phosphorus and reactive 

nitrogen can enter the environment from chemical fertilizer (agriculture, lawns, golf courses), 

industrial sources, animal waste, and human waste (Galloway et al., 2003). Additionally, nitrogen can 

be contributed from biological nitrogen fixation and atmospheric nitrogen deposition (originating from 

fossil fuel combustion and ammonia volatilization from agriculture; Mathews et al., 2002). 

Although a comprehensive watershed nutrient budget is beyond the scope of this study, it seems 

likely, based on watershed land use, that agriculture is a significant contributor of nutrients to the 

near coastal environment (Figure 5.1). Modeling of potential nutrient fluxes from the watershed was 

previously published (Zitello et al., 2008). Results indicated that agricultural practices, like the use of 

chicken manure and commercial fertilizers, may be affecting water and air quality. 

A The taxonomic name for Halodule wrightii has been recently changed to Halodule beaudettei (http://www.itis.gov/index.html); however, the original 

name will be used in this document as it is more widely known. 

151 5 - Nutrients and Pesticides 

1

 Center for Coastal Monitoring and Assessment, National Centers for Coastal Ocean Science, National Ocean Service, National 

Oceanic and Atmospheric Administration 

2 Jobos Bay National Estuarine Research Reserve 

3 Southeast Watershed Research Laboratory, Agricultural Research Service, United States Department of Agriculture 

4 Corresponding author: dave.whitall@noaa.gov 
Baseline Assessment of Jobos Bay, Puerto Rico: Nutrients and Pesticides 

152 5 - Nutrients and Pesticides

An extensive groundwater study 

(Rodríguez, 2006) found nitrate 

concentrations above the U.S. 

Environmental Protection Agency 

(USEPA) maximum contaminant 

level for drinking water (10 mg/L) in 

three wells in the watershed, although 

these wells are used for agricultural 

irrigation rather than drinking water. 

The JBNERR Monitoring Program 

studied several freshwater wells 

in the Jobos Bay watershed. This 

program detected high levels of 

nitrates (90 mg/L) in some wells, 

exceeding the drinking water 

standard (10 mg/L) of the Puerto 

Rico Environmental Quality Board 

(PREQB). Several groundwater 

wells studied by JBNERR’s Water 

Quality Program cannot be used due to high nitrate levels. As a result, more stringent management 

practices regarding the use of chicken manure on farmland have been imposed by the PREQB. Nearshore water quality in the Bay is also being affected by increased surface run-off. Urban growth along 

the coast is affecting estuarine habitat and increasing the direct discharge of untreated wastewater 

from local communities that have no water treatment facilities such as Aguirre. It should be noted that 

the regional waste water treatment plant does not discharge into the Bay. Untreated waters reach 

directly into the Bay from an old sewage system in Aguirre community and leakage from septic tanks 

in Las Mareas Community and Pozuelo. A new sewage system is being constructed in Aguirre and 

Pozuelo that will take untreated waters to the regional plant. 

Other communities such Pozuelo and Las Mareas may be sources of waste water from septic tanks 

seepage due a shallow water table affected by tides; Coquí, Mosquito, San Felipe, Puerto de Jobos 

have sewage systems that overflows during storms events. 

5.1.2. Pesticides 

Jobos Bay watershed has been used 

as agricultural lands since Spanish Colonial times and has changed 

from a landscape dominated by 

heavy sugar cane production(Figure 

5.2) to silage, seed production, and 

minor fruits and vegetables comprising 11% of the watershed land cover 

(Zitello et al., 2005). Agricultural and 

non-agricultural pesticide use in the 

watershed also has the potential to 

impact near-shore waters in the estuary. For example, investigations 

conducted on the silage farm adjacent to the JBNERR found that a variety of herbicides, insecticides and 

Figure 5.1. Center pivot irrigation on silage farm adjacent to Jobos Bay National

Estuarine Research Reserve (JBNERR). Photo: NOAA CCMA. 

Figure 5.2. Abandoned sugar mill adjacent to Jobos Bay. Photo: NOAA CCMA. 
Baseline Assessment of Jobos Bay, Puerto Rico: Nutrients and Pesticides 

fungicides are used. The most common (by weight, 2008-2010; Table 

5.1) were atrazine, pendimethalin, 

glyphosate, paraquat (herbicides) 

and chlorpyrifos (insecticide). Pesticides and their degradation products 

can have adverse effects on aquatic 

organisms (Humberg et al., 1989; 

Ahrens, 1994; USEPA, 1995, 2006) 

and can enter coastal waters via surface runoff or groundwater fl ux, drift, 

and wet and dry deposition. It should 

be noted that due to problems with 

the irrigation system, farming on the 

silage farm adjacent to the Reserve 

was stopped in late 2009. It is anticipated that farming will resume when 

the center pivot system in replaced 

by 2011. 

5 - Nutrients and Pesticides

Table 5.1. On farm pesticide use 2008 to 2010. 

Pesticide 

Mass applied Annual rate 

Use (kg) (kg/ha/yr) 

atrazine herbicide 361 2.8 

pendimethalin herbicide 188 1.4 

glyphosate herbicide 173 1.3 

paraquat herbicide 106 0.8 

fluazifop-P-buty herbicide 5 0.04 

Total herbicide 831 (76%) 6.4 

chlorpyrifos insecticide 109 0.8 

methomyl insecticide 49 0.4 

malathion insecticide 44 0.3 

thiodicarb insecticide 33 0.3 

spinosad insecticide 7 0.1 

esfenvalerate insecticide 5 0.04 

permethrin insecticide 5 0.04 

Total Insecticide 252 (23%) 1.9 

azoxystrobin fungicide 2 0.01 

propiconazole fungicide 2 0.01 

Total Fungicide 4 (<1%) 0.03 

5.2. METHODS 

5.2.1. Nutrients, Pesticides and Chlorophyll a Sampling and Analysis 

Nutrients and chlorophyll a were sampled monthly at the four active JBNERR System-Wide 

Monitoring Program (SWMP) sites, which are targeted sampling sites (Figure 5.3). Pesticides were 

also sampled at the four active JBNERR sites, plus a fifth site (site 11; Figure 5.3). Station number 

nine (09; Figure 5.3) is considered 

to be an impacted site. Water

quality data collected at this site is

associated with runoff from littoral

and basin mangrove areas. This

lagoon has an average depth of 1.5

m and water regime is subject to high

concentrations of tannin pigments

associated with red mangroves.

Station 09 is characterized by a low

water exchange due to a restricted

circulation pattern. This sampling

station is located in the most inland

lagoon northeast of Mar Negro,

closest to the thermoelectric power

plant. It is subjected to runoff,

which may include agrochemicals

from agricultural activities within

the northern boundary of JBNERR.

Information compiled from historical

environmental documents indicate

that station nine (09) was used

as a disposal site for residues of

153 

Figure 5.3. Map of Jobos Bay National Estuarine Research Reserve System-Wide 

Monitoring Program (JBNERR SWMP) sites. Nutrients were sampled monthly at

sites 09,10,19 and 20. Pesticides were sampled monthly at all fi ve sites. 
Baseline Assessment of Jobos Bay, Puerto Rico: Nutrients and Pesticides 

154 5 - Nutrients and Pesticides

the previously operating sugar mill operation, and therefore might have high organic input into the 

sediments. Among the four water quality monitoring stations, this station has the lowest dissolved 

oxygen values during the year. Benthic vegetation is scarce (NERRS, 2011). 

Station number ten (10; Figure 5.3), located in a mangrove lagoon area towards the southwestern 

section of Mar Negro, is considered the reference or non-impacted site. This station is characterized 

by a low water exchange due to a restricted circulation pattern. This lagoon has an average depth of 

2 m and the water regime is subject to high concentrations of tannin pigments associated with red 

mangroves. Benthic vegetation is scarce. 

Station number eleven (11) may also be impacted by land based sources of pollution, specifi cally, 

untreated sewage and septic systems from near coastal residences and runoff from agriculture 

(NERRS, 2011). 

Station number nineteen (19; 

Figure 5.3) is located in Jobos Bay 

surrounded by sea grass beds 

composed of T. testudinum. This 

station is close to the power plant 

navigation channel (Figure 5.4), 

used by barges to bring oil and gas 

into the power plant pier. This area 

is exposed to barge strandings and 

sediment re-suspension. Oil spills 

are always a threat (NERRS, 2011). 

Station number twenty (20; Figure 5.3) is located adjacent to Cayos Caribe reef system. Water streams 

coming from the reef platform may mean that this station is representative of water conditions behind 

the coral reef. These waters are part of the main marine current coming from the eastern side of 

Jobos Bay that runs along the coast, coming into contact with potential sources such as agricultural 

fields, a coal power plant, a Phillips Core oil refinery (closed in 2005) and other industries (NERRS, 

2011). 

5.2.2. Nutrient and Chlorophyll a Sample Collection Methods 

Monthly grab samples for nutrients and chlorophyll a were taken at the four SWMP stations (site 09, 

10, 19 and 20; Figure 5.3). Grab samples were taken from the four sites on the same day at or as 

near as possible to slack low-tide conditions. Efforts were made to collect samples at approximately 

monthly (30 days) intervals. Sample dates were selected so as to not be influenced by previous storm 

events; an antecedent dry period of 72 hours was desirable but was not always practical throughout 

the year (e.g., during the rainy season). Because the sites are shallow and well-mixed, two surface 

grab samples were collected that are representative of the sampling area. Replicate (N=2) samples 

were collected by hand at an approximate depth of 30 cm. 

Nutrient and chlorophyll a grab samples were taken in duplicate (two separate samples collected in 

different bottles), resulting in a total of eight samples. All samples were collected in amber, NalgeneTM 

sample bottles that were previously acid washed (10%) rinsed (3x) with distilled-deionized water, 

dried and followed by rinsing (3x) of ambient water prior to collection of the sample. 

Figure 5.4. Aguirre Power Plant adjacent to Jobos Bay. Photo: NOAA CCMA. 
Baseline Assessment of Jobos Bay, Puerto Rico: Nutrients and Pesticides

155 5 - Nutrients and Pesticides

5.2.3. Diel Sampling Program of Nutrients and Chlorophyll a

Diel nutrient samples were taken at station 09. Samples were collected over a full lunar cycle (24 hr 

: 48 min) at 2 hour intervals using an ISCO brand auto-sampler model 6712. The suction intake line 

was set to sample at a depth of 0.5 m, and was covered with a mesh to avoid clogging the line with 

organic debris. The ISCO sampler was programmed to automatically sample 1000 mL of water every 

2 hours and contained a one frozen plastic gallon to keep samples cold. A fi eld blank consisting of 

deionized (DI) water was placed in the bottle rack and left open during the diel sampling. All samples 

were pumped into polyethylene sample bottles that were previously acid washed (10%), rinsed (3x) 

with distilled-deionized water and dried. At the end of the 24 hr period, the 12 samples were kept in 

the dark and returned to the laboratory for immediate processing. 

5.2.4. Nutrient and Chlorophyll a Analysis

All samples, monthly grab and diel, were pre-processed at JBNERR laboratory. Samples were 

fi ltered immediately after collection; the fi ltrate was placed in 250 mL NalgeneTM bottles. The fi ltered 

chlorophyll-a samples were placed in amber (empty) vials, stored in a cooler (dark) on ice packs and 

sent via overnight delivery to Virginia Institute of Marine Sciences (VIMS) laboratory for analysis. 

VIMS serves as the analytical lab for SWMP sample analysis for several NERRS sites. Nutrients were 

determined colorimetrically and chlorophyll a was determined fl ourometrically following extraction 

in 90% acetone. Method detection

limits and methods for nutrients and 

chlorophyll a are shown in Table

5.2. In addition to oxidized nitrogen,

reduced nitrogen (ammonium) is

also routinely measured by the

JBNERR SWMP. However, at the

time of publication of this document, 

these ammonium data were still

being reviewed for quality assurance 

purposes and are not included here.

5.2.5. Pesticide Sample Collection Methods

Water samples for pesticide analysis were collected from the Bay on a monthly basis between April 

2008 and November 2010 at the fi ve JBNERR reference sites that were established in 1995 (Figure 

5.3). Each sample was collected by submerging a 1-L pre-cleaned amber glass bottle by hand from 

the boat used to reach sampling sites. After sealing with Tefl on® lined screw caps, bottles were placed 

in an on-board ice-chest and upon return to the laboratory transferred to refrigerated storage. 

5.2.6. Pesticide Sample Handling and Preparation

Within 3 days of collection, project staff prepared the pesticide samples for analysis by drawing each 

sample through solid-phase extraction (SPE) cartridges (Oasis® HLB; Waters Inc., Milford, MA) using 

a vacuum manifold. Procedure performance, in terms of percent recovery of numerous current use 

pesticides active ingredients, has been previously published (Potter et al., 2007). After SPE was 

complete, cartridges were fl ushed with four 5-mL aliquots of high-performance liquid chromatography 

(HPLC) grade water, dried by vacuum reapplication, wrapped in aluminum foil, placed in ziplock 

bags, and stored in a refrigerator. The following day they were shipped to the analytical laboratory 

using an overnight delivery service. Upon receipt cartridges were eluted sequentially with methanol 

and methylene chloride. Combined eluents were concentrated to about 1 mL by evaporation under a 

stream of nitrogen (N2

) gas followed by solvent exchange to toluene using a Turbovap® concentrator 

(Caliper Life Sciences, Hopkinton, MA, USA) and N2 gas. Concentrated extracts were fortifi ed with 

Table 5.2. Methods and method detection limits for nutrient and chlorophyll analyses.

Parameter

Ammonium

Nitrate plus 

Nitrite

Orthophosphate

Chlorophyll a

Method Method Detection Limit

Methods for Chemical Analysis of 0.0054 mg/L Water and Wastes - USEPA (1974) 

USEPA Method 353.4 - 0.0010 mg/L Zhang et al. (1997)

USEPA Method 365.5 - 0.0015 mg/L Zimmermann and Keefe (1997) 

USEPA Method 445.0 - 0.50 ug/L Arar and Collins (1997) 
Baseline Assessment of Jobos Bay, Puerto Rico: Nutrients and Pesticides

156 5 - Nutrients and Pesticides

2-chlorolepidine and octafl uoronapthalene, internal standards for the positive ion electron impact 

and negative chemical ionization gas chromatography-mass spectrometry (GC-MS) analyses, 

respectively. Extracts were stored in the dark at -20o

C.

Pesticide Analysis via GC-MS

All extracts were analyzed using a

ThermoQuest Finnegan DSQII GCMS system (ThermoFisher, San

Jose, CA, USA) while scanning for

positive ions generated by electron

impact at 70 eV and for negative

ions produced during methane

chemical ionization (methane 1.5 mL 

min-1; source temperature 200o

C).

Prior to use in each ionization mode

the instrument was autotuned to

meet manufacturer specifi cations. 

For enhanced sensitivity data

acquisitions were in the selected

ion monitoring (SIM) mode. Target

compounds, SIM methods, and the

limits of quantifi cation are shown in

Table 5.3. Compounds were selected 

based on a review of crops produced 

in the region (USDA-NASS, 2009)

and their pest management profi les 

(USDA-IPMCENTERS, 2011).

Suitability for GC analysis was

also a requirement. Ions monitored

were base peaks (primary) and

the second most abundant ion

(confi rmatory) obtained during

full-scan (m/z=50 to 450 daltons)

data acquisitions of standards.

Chromatographic separations were

on a 30 m DB5® column, 0.25 mm

i.d., 0.25 μ fi lm (Agilent, San Jose,

CA, USA). Helium carrier gas fl ow 

was 2 mL min-1 with automated

compensation for oven temperature

programming and vacuum in the ion

source. Automated 1-uL injections

were splitless. At the injection

column head pressure was surged

to 250 kPa for 1 minute. Quantitation 

limits were based on extraction of

1-L samples, concentration to 1 mL, and the lowest concentration standard used for calibration. 

Compounds detected were considered confi rmed if the ratio between the two ions monitored was 

within ±20% of the diagnostic ratio obtained for standards.

Compounds Method † LOQ (ug L-1)

acetochlor GC-MS-EI-POS-SIM 0.006

alachlor GC-MS-EI-POS-SIM 0.006

ametryn GC-MS-EI-POS-SIM 0.006

atrazine GC-MS-EI-POS-SIM 0.006

desethylatrazine GC-MS-EI-POS-SIM 0.006

desisopropylatrazine GC-MS-EI-POS-SIM 0.006

α-BHC GC-NCI-MS-SIM 0.004

carbaryl GC-MS-EI-POS-SIM 0.006

chlorothalonil GC-NCI-MS-SIM 0.004

chlorpyrifos GC-NCI-MS-SIM 0.004

dacthal GC-NCI-MS-SIM 0.004

diazinon GC-NCI-MS-SIM 0.004 

dicofol GC-MS-EI-POS-SIM 0.006

α-endosulfan GC-NCI-MS-SIM 0.004

β-endosulfan GC-NCI-MS-SIM 0.004

endosulfan sulfate GC-NCI-MS-SIM 0.004

ethalfl uralin GC-NCI-MS-SIM 0.004

ethoprop GC-MS-EI-POS-SIM 0.006

lindane GC-NCI-MS-SIM 0.004

malathion GC-NCI-MS-SIM 0.004 

metalaxyl GC-MS-EI-POS-SIM 0.006

metolachlor GC-MS-EI-POS-SIM 0.006

metribuzin GC-NCI-MS-SIM 0.004

oxadiazon GC-NCI-MS-SIM 0.004

pendimethalin GC-NCI-MS-SIM 0.004

prometon GC-MS-EI-POS-SIM 0.006

prometryne GC-MS-EI-POS-SIM 0.006

propiconazole GC-MS-EI-POS-SIM 0.006

simazine GC-MS-EI-POS-SIM 0.006

tebuconazole GC-MS-EI-POS-SIM 0.006

tribufos GC-NCI-MS-SIM 0.004

trifl uralin GC-NCI-MS-SIM 0.004

† GC-MS-EI-POS-SIM = Gas chromatography-mass spectrometry (GCMS) with positive ion electron impact ionization; GC/MS with methane 

negative chemical ionization.

Table 5.3. Target analytes, methods and limit of quantifi cation (LOQ).
Baseline Assessment of Jobos Bay, Puerto Rico: Nutrients and Pesticides 

Pesticide Analysis Quality Control 

A laboratory blank was prepared during SPE of each sample set. One liter of HPLC grade water was 

used. None of the target analytes were detected in blanks indicating a low potential for false-positive 

results in Bay samples. To assess the potential for false-negatives a matrix spike was prepared 

and analyzed for each of the 40 samples. Spikes were prepared using a duplicate sample of water 

from station 20 and addition of 1 mL of 1 μg mL-1 methanol solution of 11 of the target analytes 

(Table 5.3). Among the five spikes prepared and analyzed recoveries ranged from 54 and 108% and 

relative standard deviations from 6 to 35%. Results were comparable to prior investigations using the 

same analytical techniques (Potter et al., 2007). The relatively high recoveries and low variability are 

indicative of data with low false-negative potential. No corrections were made for recovery in reported 

results. 

5.2.7. Statistical Analysis of Data 

Data were analyzed using JMP® 

statistical software. The data were 

first tested for normality using the 

Shapiro-Wilk test. Because the data 

were not normally distributed, nonparametric statistical tests were 

used; a Wilcoxon test was used to 

examine differences between sites 

and seasons, and a Spearman’s 

rank correlation coefficient test 

was used to test for relationships 

between nutrients, chlorophyll and 

precipitation (Figure 5.5). 

The temperature in Jobos Bay is 

relatively constant throughout the 

year, with relatively more precipitation 

occurring during hurricane season 

(June to November). Therefore, 

seasonal nutrient patterns were 

examined between hurricane and 

non-hurricane seasons. 

157 5 - Nutrients and Pesticides 

Figure 5.5. Weather station at silage farm. Photo: NOAA CCMA. 

Space left intentionally blank. 
1.34 

Baseline Assessment of Jobos Bay, Puerto Rico: Nutrients and Pesticides 

5.3. RESULTS AND DISCUSSION 

5.3.1. Orthophosphate 

158 5 - Nutrients and Pesticides

Orthophosphate concentrations Table 5.4. Summary statistics for nutrients and chlorophyll a. MDL= Method 

Detection LImit. ranged from below the method 

detection limit to 0.17 mg phosphate 

(P)/L, with a mean of 0.015 mg 

P/L and a median of 0.011 mg P/L 

(Table 5.4). This is similar to what 

was observed in near shore waters 

in Vieques, Puerto Rico (Whitall et 

al., 2010). Standard deviations were 

much higher at site 09 because 

of the diel sampling at that site, 

i.e. sampling over a 24 hour cycle 

will capture a much wider range of 

values than a single grab sample 

(Figure 5.6) due to diel variations 

in photosynthesis/respiration and 

the tidal cycle. Concentrations were 

significantly higher (p<0.05) at site 09 

compared with the other three sites 

(Figure 5.6). Site 09 is the closest 

to shore, so this pattern may reflect 

the input of phosphorus reaching 

the system via overland fl ow. 

Based on watershed land use and 

previous modeling estimates (Zitello 

et al., 2008) agricultural fertilizer is 

likely to be a very important source 

of phosphorus to this system. 

Phosphorus concentrations were 

not correlated with precipitation. 

This may be because the NERRS 

SWMP sampling protocols dictate 

not sampling after a rainfall event. 

However, at site 09 phosphorus 

concentrations were significantly 

higher during the wet season 

(December through May) than during 

the rainy season (June through 

November; hurricane season) as 

shown in Figure 5.7. This further 

supports the theory that surface runoff is driving the observed phosphorus concentrations are the site 

closest to shore. The other three sites did not exhibit seasonal patterns for phosphorus. 

5.3.2. Oxidized Nitrogen 

Oxidized nitrogen (nitrate plus nitrite) concentrations ranged from below the method detection limit 

to 0.12 mg nitrogen (N)/L, with a mean of 0.013 mg N/L and a median of 0.007 mg N/L (Table 5.4). 

This is similar to what was observed in near shore waters in Vieques, Puerto Rico (Whitall et al., 

2010). Standard deviations were much higher at site 09 because of the diel sampling at that site, i.e. 

Analyte Units Min Max Mean Median 

Nitrate plus nitrite 

Orthophosphate 

Chlorophyll a 

mg N/L 

mg P/L 

ug/L 

MDL 

MDL 

MDL 

0.1177 

0.1705 

142.56 

0.01252 

0.014835 

4.386596 

0.0072 

0.01115 

Figure 5.6. Mean orthophosphorous concentrations from 2008 to 2010. Letters

indicate statistical groupings (Wilcoxon test, P <0.05) . Error bars represent standard 

deviation. 

Figure 5.7. Seasonal variability in orthophosphorus and nitrate/nitrite between wet

(hurricane) and dry seasons at site 09 from 2008 to 2010. For both analytes, there

were statistical differences between seasons (Wilcoxon test, P <0.05). 
Baseline Assessment of Jobos Bay, Puerto Rico: Nutrients and Pesticides 

sampling over a 24 hour cycle will capture a much wider range of values than a singular grab sample 

(Figure 5.8) due to diel variations in photosynthesis/respiration and the tidal cycle. Concentrations 

were significantly lower (p<0.05) at site 20, compared to the other three sites (Figure 5.8). Site 20 is 

the farthest site from shore indicating 

a relatively low potential for impact 

from runoff from the land. Oxidized 

nitrogen concentrations were not 

correlated with precipitation. This 

may be because the NERRS 

SWMP sampling protocols dictate 

not sampling after a rainfall event, 

although nitrate concentrations 

may be disconnected from rainfall 

because groundwater transport of 

oxidized nitrogen is often a primary 

mechanism for nitrogen flux to 

coastal systems. This is not the case 

with phosphorous. The different 

spatial patterns in nitrogen versus 

phosphorus patterns may reflect 

groundwater versus runoff flux 

pathways. Seasonally, at sites 09 and 

20 oxidized nitrogen concentrations 

were significantly higher during the 

dry season (December to May) than 

the wet season (June to November, 

hurricane season) as shown in 

Figure 5.9. Since it is hypothesized 

that nitrogen is reaching the estuary 

through groundwater, this pattern 

may represent dilution of ambient 

nitrogen by freshwater fl ows during 

the rainy season. There was no 

statistically significant difference 

between seasons at sites 10 and 19. 

5.3.3. Chlorophyll a 

Chlorophyll a concentrations ranged 

from below the method detection 

limit to 142.6 μg/L, with a mean 

of 4.39 μg/L and a median of 1.34 

μg/L (Table 5.4). Concentrations 

varied significantly between all sites 

(Figure 5.10), which likely reflected 

multiple forcing factors controlling 

phytoplankton populations including 

nutrient concentrations, zooplankton 

grazing, and circulation patterns. 

Chlorophyll a was not correlated with 

nutrients or precipitation. Seasonally, 

Figure 5.8. Mean nitrate plus nitrite concentrations from 2008-2010. Letters indicate

statistical groupings (Wilcoxon test, P <0.05). Error bars represent standard 

deviation. 

Figure 5.9. Seasonal variability in orthophosphorus and nitrate/nitrite between wet

(hurricane) and dry seasons at site 20 from 2008-2010. There was a statistical

difference between seasons for nitrate/nitrite (Wilcoxon test, P <0.05). 

Figure 5.10. Mean chlorophyll a concentrations. Letters indicate statistical groupings

(Wilcoxon test, P <0.05). Error bars represent standard deviation. 

159 5 - Nutrients and Pesticides 
Baseline Assessment of Jobos Bay, Puerto Rico: Nutrients and Pesticides 

160 5 - Nutrients and Pesticides

chlorophyll a was significantly higher 

at site 09 during the wet season 

(Figure 5.11). This could be due to 

changes in nutrient dynamics (see 

above) with freshwater inputs. It is 

also possible that changes in salinity 

could directly or indirectly affect 

phytoplankton communities. 

5.3.4. Pesticide Results 

Among the thirty two pesticides and 

degradates tested for in each sample only two were detected, atrazine 

and its degradation product desethylatrazine (DEA). Their detection 

was limited to the near shore stations (sites 09, 10 and 11; Figure 5.12) during the rainy season in 

2008. The highest concentrations were observed in a sample collected at station 9. The sample was 

collected four days after a large rainfall-runoff event. Comparison with management records from the 

silage farm adjacent to Mar Negro indicated that the herbicide was applied to farm field three days 

prior to the event (Figure 5.13). The short period of time between pesticide application and rainfall 

created conditions that resulted in relatively high atrazine discharge to the Bay. The south shore of 

Puerto Rico is typically subjected to multiple tropical storms/depressions every year. Figure 5.14 

shows the passing of two tropical storms (Faye, Kyle) in 2008 which impacted salinity and pesticide 

concentrations in the estuary. Results indicate these storms contribute to high pesticide runoff risk 

and care should be taken to avoid application of pesticides immediately prior to approaching tropical 

storms. 

Figure 5.11. Seasonal variability in chlorophyll a between wet (hurricane) and dry 

seasons at site 09 from 2008-2010. There was a statistical difference between 

seasons (Wilcoxon test, P<0.05). 

Figure 5.12. Atrazine and atrazine degradate concentrations in Jobos Bay. Red line represents method detection limit. 
Baseline Assessment of Jobos Bay, Puerto Rico: Nutrients and Pesticides 

5 - Nutrients and Pesticides 

Figure 5.13. Atrazine application rates on the farm and precipitation and salinity at SWMP site 09. 

161 

Figure 5.14. Timing of atrazine application in relation to tropical storms in Jobos Bay. 
Baseline Assessment of Jobos Bay, Puerto Rico: Nutrients and Pesticides 

162 5 - Nutrients and Pesticides

5.4. CONCLUSIONS 

These data demonstrate that land based sources of pollution (pesticides and nutrients) are reaching 

Jobos Bay via surface runoff and/or groundwater discharge. These pathways of transport may be of 

concern to the mangrove ecosystem in Mar Negro and sensitive offshore coral reef ecosystems (Figure 

5.15). The pesticide data presented 

here demonstrate the relationship 

between pesticide application and 

rainfall driven runoff in contributing 

pesticide residues to the Bay. 

These data make up part of a larger 

baseline assessment of this system 

which will be used to evaluate 

the efficacy of and planning for 

implementation of watershed best 

management practices. The water 

quality parameters discussed here 

will likely respond very quickly 

to changes in the watershed, 

making them especially useful for 

documenting short term changes to 

the system. 

ACKNOWLEDGMENTS 

Funding for this research was provided the U.S. Department of Agriculture, Natural Resource 

Conservation Program (Conservation Effects Assessment Project), and NOAA’s Coral Reef 

Conservation Program. Additionally, the authors would like to thank Dr. Michael Piehler, Dr. Suzanne 

Bricker and Dr. Edward Johnson for their helpful editorial comments which greatly improved this 

chapter. 

REFERNCES 

Ahrens, W.H. (ed.). 1994. Herbicide Handbook of the Weed Science Society of America, 7th ed. 

Weed Science Society of America. Champaign, IL. 352 pp. 

Almodóvar, L.R. 1964. The marine algae of Bahía de Jobos, Puerto Rico. Nova Hedwigia VII(1/2): 

33-52. 

Arar, E.J. and G.B. Collins. 1997. Method 445.0 - In Vitro Determination of Chlorophyll a and Pheophytin 

a in Marine and Freshwater Algae by Fluorescence. pp. 132-153. In: Methods for the Determination 

of Chemical Substances in Marine and Estuarine Environmental Matrices- 2nd Edition. USEPA 

600/R--97/072. National Exposure Research Laboratory, Office of Research and Development, U.S. 

Environmental Protection Agency. 199 pp. (Online) http://archive.chesapeakebay.net/pubs/quality_ 

assurance/EPA_Marine_Methods_2nd_ed.pdf (Accessed 13 June 2011). 

Bricker, S., B. Longstaff, W. Dennison, A. Jones, K. Boicourt, C. Wicks, and J. Woerner. 2007. 

Effects of Nutrient Enrichment in the Nation’s Estuaries: A Decade of Change, National Estuarine 

Eutrophication Assessment Update. NOAA Coastal Ocean Program Decision Analysis Series No. 26. 

National Centers for Coastal Ocean Science, Silver Spring, MD. 322 pp. 

Figure 5.15. Mangrove forest lining Jobos Bay. 
Baseline Assessment of Jobos Bay, Puerto Rico: Nutrients and Pesticides 

Galloway J.N., J.D. Aber, J.W. Erisman, S.P. Seitzinger, R.H. Howarth, E.B. Cowling, and B.J. Cosby. 

2003. The nitrogen cascade. BioScience 53: 341-356. 

Harrison, P.L. and S. Ward. 2001. Elevated levels of nitrogen and phosphorus reduce fertilisation 

success of gametes from scleractinian reef corals. Marine Biology 139: 1057-1068. 

Humburg, N.E., S.R. Colby, E.R. Hill, L.M. Kitchen, R.G. Lym, W.J. McAvoy, and R. Prasad (eds.). 

1989. Herbicide Handbook of the Weed Science Society of America, 6th ed. Weed Science Society 

of America. Champaign, IL. 301 pp. 

Marubini, F. and P.S. Davies. 1996. Nitrate increases zooxanthellae population density and reduces 

skeletogenesis in corals. Marine Biology 127: 319-328. 

Mathews, L.G, F.R. Homans, and K.W. Easter. 2002. Estimating the benefits of phosphorus pollution 

reductions: An application in the Minnesota River. Journal of the American Water Resources 

Association 38: 1217-1223. 

National Estuarine Research Reserve System (NERRS). 2011. Data Export System: Jobos Bay 

Nutrient Metadata. Centralized Data Management Office, National Estuarine Research Reserve 

System. (Online) http://cdmo.baruch.sc.edu/ (Accessed 13 June 2011). 

Potter, T.L., M. Mohamed, and H. Ali. 2007. Solid-Phase Extraction Combined with High-Performance 

Liquid Chromatography−Atmospheric Pressure Chemical Ionization−Mass Spectrometry Analysis of 

Pesticides in Water: Method Performance and Application in a Reconnaissance Survey of Residues 

in Drinking Water in Greater Cairo, Egypt. Journal of Agricultural Food Chemistry 55(2): 204-210. 

Rodríguez, J.M. 2006. Evaluation of hydrologic conditions and nitrate concentrations in the Río Nigua 

de Salinas alluvial fan aquifer, Salinas, Puerto Rico, 2002-03. U.S. Geological Survey Scientific 

Investigations Report 2006-5062. 38 pp. 

U.S. Department of Agriculture- Integrated Pest Management Centers (USDA-IPMCENTERS). 2011. 

National Information System for the Regional Integrated Pest Management Centers: USDA Crop 

Profiles. National Science Foundation Center for Integrated Pest Management and National Insitute 

of Food and Agriculture, U.S. Department of Agriculture. Raleigh, NC. (Online) http://www.ipmcenters. 

org/cropprofiles/cp_form.cfm (Accessed 13 June 2011). 

U.S. Department of Agriculture- National Agricultural Statistics Service (USDA-NASS). 2009. 2007 

Census of Agriculture. National Agricultural Statistics Service, U.S. Department of Agriculture. 

Washington, D.C. (Online) http://www.agcensus.usda.gov/Publications/2007/Full_Report/index.asp 

(Accessed 13 June 2011). 

U.S. Environmental Protection Agency (USEPA). 1974. Nitrogen, Ammonia (Automated Colorimetric 

Phenate Method). pp. 168-174. In: Methods for chemical analysis of water and wastes. Methods 

Development and Quality Assurance Research Laboratory, National Environmental Research Center, 

U.S. Environmental Protection Agency. Cincinnati, OH. 298 pp. 

U.S. Environmental Protection Agency (USEPA). 1995. Metolachlor: Reregistration Eligibility Decision 

(RED). Office of Pesticide Programs, U.S. Enviornmental Protection Agency. (Online) http://www.epa. 

gov/oppsrrd1/REDs/0001.pdf (Accessed 13 June 2011). 

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164 5 - Nutrients and Pesticides

U.S. Environmental Protection Agency (USEPA). 2006. Atrazine: Interim Reregistration Eligibility 

Decision (IRED). (Online) http://www.epa.gov/oppsrrd1/REDs/atrazine_combined_docs.pdf 

(Accessed 13 June 2011). 

Whitall, D.R., A.L. Mason, A.S. Pait, V. Ransibrahmanakul, and J.D. Christensen. 2010. 

Characterization of Spatial and Temporal Nutrient Dynamics. pp. 151-168. In: L.J. Bauer and M.S. 

Kendall (eds.). An Ecological Characterization of the Marine Resources of Vieques, Puerto Rico 

Part II: Field Studies of Habitats, Nutrients, Contaminants, Fish, and Benthic Communities. NOAA 

Technical Memorandum NOS NCCOS 110. Silver Spring, MD. 174 pp. 

Zhang, J.Z., P.B. Ortner, and C.J. Fischer. 1997. Method 353.4 - Determination of Nitrate and Nitrite in 

Estuarine and Coastal Waters by Gas Segmented Continuous Flow Colorimetric Analysis. pp. 80-99. 

In: Methods for the Determination of Chemical Substances in Marine and Estuarine Environmental 

Matrices- 2nd Edition. USEPA 600/R--97/072. National Exposure Research Laboratory, Offi ce of 

Research and Development, U.S. Environmental Protection Agency. 199 pp. (Online) http://archive. 

chesapeakebay.net/pubs/quality_assurance/EPA_Marine_Methods_2nd_ed.pdf (Accessed 13 June 

2011). 

Zimmermann, C.F. and C.W. Keefe. 1997. Method 365.5 - Determination of Orthophosphate in 

Estuarine and Coastal Waters by Automated Colorimetric Analysis. pp. 100-108. In: Methods for 

the Determination of Chemical Substances in Marine and Estuarine Environmental Matrices- 2nd 

Edition. USEPA 600/R--97/072. National Exposure Research Laboratory, Office of Research and 

Development, U.S. Environmental Protection Agency. 199 pp. (Online) http://archive.chesapeakebay. 

net/pubs/quality_assurance/EPA_Marine_Methods_2nd_ed.pdf (Accessed 13 June 2011). 

Zitello, A.G., D.R. Whitall, A. Dieppa, J.D. Christensen, M.E. Monaco, and S.O. Rohmann. 2008. 

Characterizing Jobos Bay, Puerto Rico: A Watershed Modeling Analysis and Monitoring Plan. NOAA 

Technical Memorandum NOS NCCOS 76. Silver Spring, MD. 81 pp. 
Baseline Assessment of Jobos Bay, Puerto Rico: Nutrients and Pesticides 

165 5 - Nutrients and Pesticides 
Chapter 6
Baseline Assessment of Jobos Bay, Puerto Rico: Conclusions 

Conclusions 

This report presents a suite of studies 

investigating fish fauna, benthic 

communities, nutrient levels, and 

chemical contaminants in the marine 

environment in Jobos Bay (Figure 

6.1) and the surrounding coral reef 

ecosystem. The overarching goal 

of these studies was to establish 

an environmental baseline of Jobos 

Bay. Now that this baseline has been 

established, environmental change 

in the system can be measured in 

future years. The ability to detect 

change is especially important to 

coastal managers as a variety of 

watershed changes, ranging from 

development to changes in best 

management practices, occur over time. Best management practices that have already been applied 

to the silage farm adjacent to the Bay include: improved water management and the use of cover 

crops. Pest management improvement may also be of some benefit, including the importance of the 

timing of pesticide applications during hurricane season to avoid major rainfall events immediately 

after application (see Chapter 5). 

By design, components of the studies in this assessment shared many sampling sites, sampling 

periods, strata, and methods with those used to monitor nearby islands. Results can therefore be 

easily combined and compared for more integrated analyses. We intentionally did not examine all 

variables from all studies simultaneously for correlations. Doing so would have yielded a high chance 

of spurious or random correlations due to the large number of variables involved. Instead, in this 

chapter we highlight some key observations and point out findings that merit further assessment. 

Key findings from this report include: 

The new benthic habitat map represents an improvement on the previous NOAA map due to newly 

acquired acoustic and optical imagery, a more detailed classification scheme, and a smaller minimum 

mapping unit. In particular, use of acoustic imagery enabled the delineation of features within areas 

of the Bay too turbid to be identified in optical imagery. Compared to the 2001 map, an additional 22 

km2

 was able to be mapped in the new effort (Chapter 2). 

The biota, nutrients, and chemical contaminant levels in Jobos Bay and the surrounding coral reef 

ecosystem are generally similar to those for other coral reef ecosystems in the Puerto Rico and U.S. 

Virgin Islands region and are likely to have been shaped primarily by regional-scale processes rather 

than local factors (see Chapters 3, 4 and 5). Locations with the highest observed live coral cover were 

located on reef seaward of the cays. Sites along these reefs, as well as with the adjacent mangrove 

complex, were also characterized by the highest observed fish species richness, abundance, and 

biomass in the study. 

Distribution of sediment contaminants were generally driven by grain size, and magnitudes were, for 

the most part, below levels which might indicated environmental concern, based on the established 

sediment quality guidelines that are currently available (see Chapter 4). 

6 - Conclusions 

Figure 6.1. Mangroves in Jobos Bay. Photo: NOAA Center for Coastal Monitoring 

and Assessment (CCMA). 

167 
Baseline Assessment of Jobos Bay, Puerto Rico: Conclusions 

168 6 - Conclusions

Future Work 

A major knowledge gap is the direct causal effect between pollution stressors and coral ecosystem 

health. While this study definitively establishes that a variety of pollutants exist in the water column 

(e.g., pesticides) and sediments (e.g., heavy metals, pesticides, polycyclic aromatic hydrocarbons 

[PAHs]) of Jobos Bay, and that many of these contaminants are being incorporated in offshore coral 

tissues, it is not understood what ramifications this might have for coral health. Additional biological 

field data might allow for correlative explorations via kriging (see Pait et al., 2007), but even fi nding a 

correlation between contaminants and indices of ecological health (e.g., coral species richness) does 

not indicate a causal effect. It would be extremely valuable to have laboratory (mesocosm) experiments 

to test the dose-response relationship between contaminants (both as individual pollutants and suites 

of contaminants) and individual coral health. Establishing the relationship between specifi c pollutant 

stressors and coral biomarkers (Downs et al., 2000) would also be extremely useful, although to this 

point biomarkers have not been linked to specifi c pollutants. 

This interdisciplinary data set provides a valuable baseline assessment of the system which will be 

useful from a variety of perspectives, including the most comprehensive study to date of the Jobos 

Bay National Estuarine Research Reserve (JBNERR). This study will be of excellent use to coastal 

managers as a starting point against which to measure change. In order to track these changes, 

future assessment efforts will be required. The authors recommend that future assessment activities 

utilize the same methodologies described here so that the new results are directly comparable with 

this baseline assessment. 

It should be noted that different 

environmental parameters will 

change more quickly than others. 

These differing time scales of 

change need to be considered when 

planning future assessments. For 

example, water quality parameters 

(nutrients, chlorophyll a, pesticides) 

change on daily, if not hourly, time 

scales, and therefore will respond 

very quickly as land-based sources 

of pollution change. On the other 

end of the spectrum, biological 

indices of ecosystem health are 

likely to respond more slowly, on 

the time scales of years to decades, 

especially when considering slow 

growing species such as corals 

(Figure 6.2). 

It is also important to realize that the environmental status of the near coastal environment can respond 

in different ways to watershed management actions. Ideally, the environment will improve in response 

to management actions and the “before” and “after” assessments will allow coastal managers to 

track how well the management actions have worked. However, it is possible that environmental 

conditions could remain the same or even get worse. For example, if other environmental stressors 

are more detrimental to the ecology of the system than the stressors targeted for management, or if 

the watershed is changing very quickly (e.g., rapid coastal development), the system could actually 

Figure 6.2. Hardbottom habitat of Jobos Bay. Photo: NOAA CCMA. 
Baseline Assessment of Jobos Bay, Puerto Rico: Conclusions 

degrade (Figure 6.3). Further, the 

coral reef community is affected by 

regional and global factors beyond 

the realm of the watershed (e.g., 

disease, overfishing, climate change, 

etc.). From a scientifi c perspective, 

all of these outcomes provide 

important information that will be 

useful to managers by providing 

critical information that will lead to 

better, more effective management 

decisions in the future. 

REFERENCES 

Downs, C.A., E. Mueller, S. Phillips, J.E. Fauth, and C.M. Woodley. 2000. A Molecular Biomarker 

System for Assessing the Health of Coral (Montastraea faveolata) during Heat Stress. Journal of 

Marine Biotechnology 2: 533-544. 

Pait, A.S., D.R. Whitall, C.F.G. Jeffrey, C. Caldow, A.L. Mason, J.D. Christensen, M.E. Monaco, and 

J. Ramirez. 2007. An assessment of chemical contaminants in the marine sediments of southwest 

Puerto Rico. NOAA Technical Memorandum NOS NCCOS 52. Silver Spring, MD. 116 pp. (Online) 

http://www.ccma.nos.noaa.gov/publications/southwestpuertorico.pdf (Accessed 13 June 2011). 

6 - Conclusions 

Figure 6.3. Industrialized shoreline of Jobos Bay. Photo: NOAA CCMA. 

169 
Appendices
Appendix A 

Table A.1. Mean species frequency, density, and biomass for fish species observed at Jobos Bay in the June 2009 survey. 

Trophic % of Mean Mean 

Species Common name Family Group Surveys Density (SE) Biomass (SE) 

Abudefduf saxatilis sergeant major Pomacentridae I 22% 0.65 (0.52) 1.35 (0.59) 

H 42% 2.40 (0.58) 73.81 (30.09) 

H 40% 1.44 (0.70) 194.56 (141.63) 

H 24% 0.73 (0.41) 28.20 (20.41) 

I 18% 0.17 (0.07) 16.76 (8.02) 

I 2% 0.11 (0.11) 0.05 (0.05) 

H 2% 0.00 (0.00) 0.02 (0.02) 

I 2% 0.01 (0.01) 5.28 (5.28) 

I 9% 0.08 (0.05) 1.99 (1.16) 

I 4% 0.02 (0.01) 9.11 (7.79) 

I 2% 0.01 (0.01) 0.12 (0.12) 

I 7% 0.05 (0.03) 1.99 (1.44) 

I 24% 0.39 (0.17) 0.40 (0.18) 

P 4% 0.05 (0.04) 1.01 (0.81) 

P 2% 0.05 (0.05) 11.95 (11.95) 

P 2% 0.00 (0.00) 0.03 (0.03) 

P 7% 0.07 (0.05) 1.48 (0.95) 

I 2% 0.03 (0.03) 2.94 (2.94) 

I 20% 0.14 (0.06) 1.62 (0.90) 

I 9% 0.29 (0.21) 3.39 (2.67) 

I 4% 0.05 (0.04) 0.53 (0.41) 

PL 2% 0.02 (0.02) 0.01 (0.01) 

I 18% 0.70 (0.40) 0.46 (0.26) 

I 7% 0.12 (0.07) 0.08 (0.05) 

H 11% 0.49 (0.26) 0.81 (0.44) 

I 2% 0.16 (0.16) 0.10 (0.10) 

I 2% 0.00 (0.00) 1.34 (1.34) 

I 11% 0.11 (0.06) 0.03 (0.01) 

I 2% 0.01 (0.01) 2.61 (2.61) 

I 2% 0.01 (0.01) 0.21 (0.21) 

I 24% 0.65 (0.53) 2.01 (1.56) 

H 7% 0.33 (0.26) 0.07 (0.06) 

I 4% 0.06 (0.05) 0.02 (0.02) 

P 2% 0.05 (0.05) 3.13 (3.13) 

I 9% 0.09 (0.05) 3.19 (1.85) 

I 2% 0.04 (0.04) 0.42 (0.42) 

I 24% 0.55 (0.43) 20.82 (17.32) 

I 2% 0.01 (0.01) 0.42 (0.42) 

I 4% 0.02 (0.01) 2.92 (2.01) 

I 9% 0.02 (0.01) 1.75 (1.29) 

Acanthurus bahianus ocean surgeonfish Acanthuridae 

Acanthurus chirurgus doctorfish Acanthuridae 

Acanthurus coeruleus blue tang Acanthuridae 

Anisotremus virginicus porkfish Haemulidae 

Apogon sp. cardinalfish species Apogonidae 

Archosargus rhomboidalis sea bream Sparidae 

Balistes vetula queen triggerfish Balistidae 

Bodianus rufus spanish hogfish Labridae 

Calamus calamus saucereye porgy Sparidae 

Cantherhines macrocerus whitespotted filefish Monacanthidae 

Cantherhines pullus orangespotted filefish Monacanthidae 

Canthigaster rostrata sharpnose puffer Tetraodontidae 

Carangoides ruber bar jack Carangidae 

Caranx crysos blue runner Carangidae 

Centropomus undecimalis common snook Centropomidae 

Cephalopholis cruentata graysby Serranidae 

Cephalopholis fulva coney Serranidae 

Chaetodon capistratus foureye butterflyfish Chaetodontidae 

Chaetodon sedentarius reef butterflyfish Chaetodontidae 

Chaetodon striatus banded butterflyfish Chaetodontidae 

Chromis cyanea blue chromis Pomacentridae 

Coryphopterus

glaucofraenum bridled goby Gobiidae 

Coryphopterus personatus/

hyalinus masked/glass goby Gobiidae 

Cryptotomus roseus bluelip parrotfish Scaridae 

Ctenogobius saepepallens dash goby Gobiidae 

Dasyatis americana southern stingray Dasyatidae 

Elacatinus evelynae sharknose goby Gobiidae 

Epinephelus guttatus red hind Serranidae 

Eucinostomus

 melanopterus flagfin mojarra Gerreidae 

Gerres cinereus yellowfin mojarra Gerreidae 

Gnatholepis thompsoni goldspot goby Gobiidae 

Gramma loreto fairy basslet Grammatidae 

Gymnothorax moringa spotted moray Muraenidae 

Haemulon aurolineatum tomtate Haemulidae 

Haemulon carbonarium caesar grunt Haemulidae 

Haemulon flavolineatum French grunt Haemulidae 

Haemulon macrostomum spanish grunt Haemulidae 

Haemulon plumierii white grunt Haemulidae 

Haemulon sciurus bluestriped grunt Haemulidae 

Baseline Assessment of Jobos Bay, Puerto Rico: Appendices 

Appendices 171 
Table A.1. Continued... 

Species

Haemulon sp. 

Common name 

grunt species 

Family 

Haemulidae 

Trophic 

Group 

I 

I 

I 

I 

I 

I 

I 

PL 

I 

I 

I 

I 

I 

I 

I 

I 

PL 

H 

I 

H 

I 

P 

I 

P 

P 

I 

P 

I 

I 

H 

H 

I 

I 

H 

PL 

PL 

H 

H 

I 

I 

I 

% of 

Surveys 

16% 

24% 

16% 

22% 

2% 

33% 

16% 

2% 

16% 

20% 

2% 

2% 

2% 

11% 

11% 

2% 

11% 

2% 

4% 

2% 

7% 

33% 

16% 

4% 

4% 

4% 

2% 

2% 

9% 

16% 

2% 

2% 

2% 

7% 

27% 

2% 

11% 

2% 

11% 

4% 

27% 

Mean Density

(SE) 

1.66 (1.17) 

2.08 (0.79) 

0.40 (0.17) 

0.63 (0.19) 

0.18 (0.18) 

2.28 (0.74) 

0.09 (0.04) 

0.05 (0.05) 

0.14 (0.06) 

0.15 (0.06) 

0.03 (0.03) 

0.01 (0.01) 

0.01 (0.01) 

0.07 (0.04) 

0.12 (0.06) 

0.01 (0.01) 

0.32 (0.29) 

0.01 (0.01) 

0.03 (0.02) 

0.00 (0.00) 

0.00 (0.00) 

0.39 (0.28) 

0.08 (0.07) 

0.02 (0.01) 

0.01 (0.01) 

0.00 (0.00) 

0.05 (0.05) 

0.00 (0.00) 

0.11 (0.07) 

0.19 (0.07) 

0.05 (0.05) 

0.04 (0.04) 

0.05 (0.05) 

0.42 (0.23) 

1.29 (0.59) 

0.05 (0.05) 

0.13 (0.06) 

0.05 (0.05) 

0.09 (0.06) 

0.07 (0.06) 

0.90 (0.74) 

Mean 

Biomass (SE) 

2.54 (1.89) 

8.12 (3.18) 

0.91 (0.48) 

1.74 (0.55) 

0.13 (0.13) 

18.94 (11.49) 

0.21 (0.14) 

0.03 (0.03) 

4.60 (1.98) 

3.68 (1.47) 

1.37 (1.37) 

0.20 (0.20) 

0.04 (0.04) 

0.66 (0.61) 

0.92 (0.50) 

0.07 (0.07) 

0.03 (0.02) 

1.23 (1.23) 

2.89 (2.40) 

0.00 (0.00) 

0.02 (0.02) 

18.84 (13.90) 

0.84 (0.53) 

13.86 (12.01) 

0.12 (0.11) 

0.01 (0.01) 

0.36 (0.36) 

0.00 (0.00) 

0.10 (0.09) 

5.01 (2.01) 

0.01 (0.01) 

0.37 (0.37) 

0.12 (0.12) 

2.20 (1.48) 

32.59 (16.04) 

0.01 (0.01) 

0.46 (0.22) 

0.02 (0.02) 

34.03 (21.79) 

28.33 (22.28) 

33.07 (29.62) 

Halichoeres bivittatus slippery dick Labridae 

Halichoeres garnoti yellowhead wrasse Labridae 

Halichoeres maculipinna clown wrasse Labridae 

Halichoeres pictus rainbow wrasse Labridae 

Halichoeres poeyi blackear wrasse Labridae 

Halichoeres radiatus puddingwife Labridae 

Heteropriacanthus

 cruentatus glasseye snapper Priacanthidae 

Holocentrus adscensionis squirrelfish Holocentridae 

Holocentrus rufus longspine squirrelfish Holocentridae 

Holacanthus tricolor rock beauty Pomacanthidae 

Hypoplectrus chlorurus yellowtail hamlet Serranidae 

Hypoplectrus indigo indigo hamlet Serranidae 

Hypoplectrus sp. hamlet species Serranidae 

Hypoplectrus puella barred hamlet Serranidae 

Hypoplectrus unicolor butter hamlet Serranidae 

Jenkinsia sp. herring species Clupeidae 

Kyphosus sectator/incisor chub (Bermuda/

yellow) Kyphosidae 

Lachnolaimus maximus hogfish Labridae 

Lophogobius cyprinoides crested goby Gobiidae 

Lutjanus analis mutton snapper Lutjanidae 

Lutjanus apodus schoolmaster Lutjanidae 

Lutjanus griseus gray snapper Lutjanidae 

Lutjanus jocu dog snapper Lutjanidae 

Lutjanus mahogoni mahogany snapper Lutjanidae 

Lutjanus synagris lane snapper Lutjanidae 

Lutjanus sp. snapper species Lutjanidae 

Malacoctenus macropus rosy blenny Labrisomidae 

Malacoctenus triangulatus saddled blenny Labrisomidae 

Microspathodon chrysurus yellowtail damselfish Pomacentridae 

Microgobius sp. goby species Gobiidae 

Mulloidichthys martinicus yellow goatfish Mullidae 

Myripristis jacobus blackbar soldierfish Holocentridae 

Nes longus orangespotted goby Gobiidae 

Ocyurus chrysurus yellowtail snapper Lutjanidae 

Opistognathus aurifrons yellowhead jawfish Opistognathidae 

Ophioblennius macclurei redlip blenny Blenniidae 

Oxyurichthys stigmalophius spotfin goby Gobiidae 

Pomacanthus arcuatus gray angelfish Pomacanthidae 

Pomacanthus paru French angelfish Pomacanthidae 

Pseudupeneus maculatus spotted goatfish Mullidae 

Baseline Assessment of Jobos Bay, Puerto Rico: Appendices 

172 Appendices
Table A.1. Continued... 

Species

Ptereleotris helenae 

Common name 

hovering goby 

Family 

Microdesmidae 

Trophic 

Group 

PL 

I 

H 

I 

P 

H 

P 

P 

P 

P 

I 

PL 

H 

H 

H 

P 

H 

H 

I 

I 

H 

H 

H 

I 

H 

I 

H 

P 

I 

I 

I 

% of 

Surveys 

9% 

2% 

44% 

7% 

2% 

4% 

4% 

4% 

2% 

4% 

13% 

9% 

2% 

9% 

36% 

11% 

9% 

11% 

2% 

4% 

27% 

18% 

38% 

42% 

31% 

13% 

2% 

4% 

42% 

2% 

7% 

Mean Density

(SE) 

0.42 (0.23) 

0.11 (0.11) 

1.39 (0.37) 

0.12 (0.07) 

0.05 (0.05) 

0.03 (0.02) 

0.32 (0.26) 

0.06 (0.05) 

0.05 (0.05) 

0.16 (0.11) 

0.22 (0.12) 

3.21 (1.82) 

0.00 (0.00) 

0.29 (0.17) 

1.23 (0.28) 

0.02 (0.01) 

0.16 (0.11) 

0.08 (0.04) 

0.00 (0.00) 

0.12 (0.11) 

0.30 (0.08) 

0.83 (0.48) 

2.36 (0.83) 

1.13 (0.25) 

1.39 (0.44) 

0.48 (0.32) 

0.00 (0.00) 

0.06 (0.05) 

4.55 (1.21) 

0.58 (0.58) 

0.32 (0.21) 

Mean 

Biomass (SE) 

0.48 (0.30) 

0.05 (0.05) 

16.78 (5.05) 

18.50 (13.42) 

28.14 (28.14) 

2.07 (1.43) 

0.11 (0.10) 

0.54 (0.46) 

0.31 (0.31) 

0.06 (0.04) 

1.42 (0.63) 

1.15 (0.65) 

0.00 (0.00) 

0.10 (0.06) 

27.60 (8.25) 

122.73 (114.31) 

0.06 (0.04) 

11.03 (7.15) 

0.01 (0.01) 

0.06 (0.05) 

13.29 (4.63) 

3.41 (2.33) 

6.40 (2.10) 

6.03 (1.50) 

0.91 (0.29) 

4.53 (3.02) 

0.00 (0.00) 

0.26 (0.22) 

6.53 (2.21) 

2.44 (2.44) 

0.50 (0.30) 

Sargocentron coruscum reef squirrelfish Holocentridae 

Scarus iseri striped parrotfish Scaridae 

Scorpaena plumieri spotted scorpionfish Scorpaenidae 

Scomberomorus regalis cero Scombridae 

Scarus taeniopterus princess parrotfish Scaridae 

Serranus baldwini lantern bass Serranidae 

Serranus flaviventris twinspot bass Serranidae 

Serranus sp. seabass species Serranidae 

Serranus tabacarius tobaccofish Serranidae 

Serranus tigrinus harlequin bass Serranidae 

Serranus tortugarum chalk bass Serranidae 

Sparisoma sp. parrotfish species Scaridae 

Sparisoma atomarium greenblotch

 parrotfish Scaridae 

Sparisoma aurofrenatum redband parrotfish Scaridae 

Sphyraena barracuda great barracuda Sphyraenidae 

Sparisoma radians bucktooth parrotfish Scaridae 

Sparisoma rubripinne yellowtail parrotfish Scaridae 

Sphoeroides spengleri bandtail puffer Tetraodontidae 

Sphoeroides testudineus checkered puffer Tetraodontidae 

Sparisoma viride stoplight parrotfish Scaridae 

Stegastes adustus dusky damselfish Pomacentridae 

Stegastes diencaeus longfi n damselfish Pomacentridae 

Stegastes leucostictus beaugregory Pomacentridae 

Stegastes partitus bicolor damselfish Pomacentridae 

Stegastes planifrons threespot damselfish Pomacentridae 

Stegastes variabilis cocoa damselfish Pomacentridae 

Synodus intermedius sand diver Synodontidae 

Thalassoma bifasciatum bluehead Labridae 

Xyrichtys martinicensis rosy razorfish Labridae 

Xyrichtys splendens green razorfish Labridae 

Baseline Assessment of Jobos Bay, Puerto Rico: Appendices 

Appendices 173 
Baseline Assessment of Jobos Bay, Puerto Rico: Appendices 

Appendix B 

Table B.1. Sediment contaminant data by site. 

174 Appendices

Site 

Name Strata 

Inner Bay 

Total 

HCH 

Total 

Chlordane Total 

DDT 

Total 

PCB 

Total 

PAHs TBT Ag As Cd Pb Sb 

ng/g ng/g ng/g ng/g ng/g ng/g ug/L ug/L ug/L ug/L ug/L 

INR2 0.00 

0.00 

0.00 

0.13 

0.00 

0.00 

0.00 

0.70 

0.00 

0.00 

0.00 

0.00 

0.02 

0.00 

0.00 

0.00 

0.00 

0.00 

0.00 

0.00 

0.00 

0.00 

0.00 

0.00 

0.00 

0.00 

0.00 

0.00 

0.00 

0.00 

0.00 

0.24 

0.02 

0.00 

0.00 

0.30 

0.00 

0.00 

0.00 

0.00 

0.04 

0.00 

0.00 

0.61 

0.06 

0.07 

2.21 

0.77 

0.19 

0.67 

0.21 

1.95 

0.11 

0.02 

0.00 

0.03 

0.01 

0.03 

0.10 

0.02 

0.03 

0.00 

0.01 

0.01 

0.01 

0.01 

0.00 

0.07 

0.26 

0.07 

0.00 

0.06 

0.08 

0.10 

0.31 

0.02 

0.03 

0.02 

0.14 

0.01 

0.01 

0.05 

0.02 

0.00 

0.00 

0.00 

0.91 

0.68 

0.90 

1.06 

1.19 

1.28 

1.80 

0.94 

0.51 

3.28 

0.87 

0.49 

0.16 

0.20 

0.10 

0.25 

0.76 

0.36 

0.01 

0.03 

0.23 

0.03 

0.59 

0.05 

0.07 

0.28 

1.81 

0.66 

0.10 

0.53 

0.18 

0.46 

0.28 

0.13 

0.07 

0.10 

0.74 

0.16 

0.34 

0.21 

0.12 

0.00 

0.00 

0.06 

2.09 

0.30 

5.46 

4.95 

9.25 

6.66 

7.13 

6.64 

5.53 

15.69 

5.36 

4.09 

3.22 

2.81 

3.54 

3.22 

5.32 

2.95 

2.69 

3.26 

2.90 

2.26 

3.36 

2.81 

2.59 

3.23 

9.83 

4.47 

2.69 

4.93 

2.76 

4.53 

3.13 

3.04 

2.51 

2.74 

3.73 

2.74 

3.25 

3.05 

3.28 

2.28 

2.30 

2.30 

7.87 

6.57 

1246 0.19 0.103 

3935 0.23 0.113 

14250 0.64 0.136 

1897 0.13 0.124 

1732 0.40 0.132 

768 0.08 0.113 

610 0.1 0.123 

631 0.21 0.12 

1122 2.27 0.107 

926 0.00 0.0963 

221 0.00 0.0862 

306 0.00 0.138 

98.5 0.00 0.0892 

79.6 0.00 0.0508 

517 0.00 0.102 

361 0.00 0.0623 

12.3 0.00 0.216 

5.5 0.00 0.219 

207 0.00 0.0997 

25.0 0.00 0.0891 

395 0.00 0.0676 

94.5 0.00 0.0985 

59.3 0.00 0.0877 

336 0.00 0.0994 

3413 0.00 0.107 

1706 0.0 0.103 

380 0.00 0.132 

750 0.00 0.0878 

199 10.91 0.0814 

1283 0.23 0.1 

381 0.00 0.0807 

23.9 3.64 0.139 

58.9 0.93 0.168 

140 0.00 0.179 

844 4.24 0.144 

301.9 0.36 0.19 

449 0.00 0.0868 

317 0.00 0.171 

156 0.00 0.146 

4 0.00 0.214 

17 0.19 0.174 

80.5 0.00 0.0593 

3221 0.00 0.0672 

3157 0.07 0.0797 

23.1 

22.4 

18.5 

18 

18.7 

15.5 

13.2 

12.9 

11.4 

11.3 

6.92 

9.34 

12.3 

18 

17.5 

15.4 

2.22 

1.79 

17 

7.87 

17 

10.9 

9.95 

14.9 

28.1 

20 

10.2 

15.7 

14.6 

17.7 

7.07 

3.06 

3.15 

3.69 

16 

9.6 

14 

7.47 

7.83 

2.84 

4.63 

12.6 

6.54 

23.3 

0 

0 

0 

0 

0 

0 

0 

0 

0.173 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0.174 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

11.4 0.279 

14.3 0.318 

14.5 0.341 

15.3 0.336 

16.7 0.346 

12.1 0.254 

11.3 0.274 

12.3 0.395 

12.8 0.304 

11.4 0.265 

5.06 0 

4.63 0.351 

3.78 0.252 

4.45 0.298 

10.9 0.319 

7.09 0.323 

0.786 0 

0.227 0 

4.72 0.27 

1.98 0 

7.38 0.305 

4.2 0.253 

2.78 0 

7.23 0.306 

14 0.562 

8.25 0.338 

5.66 0.231 

8.43 0.377 

5.07 0.347 

7.06 0.225 

4.41 0 

1.4 0 

1.27 0 

2.49 0 

8.27 0.35 

4.72 0 

6.15 0.268 

5.89 0 

3.91 0.202 

1.5 0 

1.65 0 

3.7 0.269 

15.9 0 

7.53 0.589 

INR3 Inner Bay 

INR4 Inner Bay 

INR5 Inner Bay 

INR6 Inner Bay 

INR7 Inner Bay 

INR8 Inner Bay 

INR9 Inner Bay 

INR10 Inner Bay 

AIN55 Inner Bay 

CNT11 Central Bay 

CNT12 Central Bay 

CNT14 Central Bay 

CNT15 Central Bay 

CNT16 Central Bay 

CNT17 Central Bay 

CNT18 Central Bay 

CNT19 Central Bay 

CNT20 Central Bay 

ACT45 Central Bay 

ACT46 Central Bay 

NER21 Central Bay (Reserve) 

NER22 Central Bay (Reserve) 

NER23 Central Bay (Reserve) 

NER24 Central Bay (Reserve) 

NER25 Central Bay (Reserve) 

NER26 Central Bay (Reserve) 

NER27 Central Bay (Reserve) 

NER28 Central Bay (Reserve) 

NER29 Central Bay (Reserve) 

NER30 Central Bay (Reserve) 

OTR31 Outer Bay 

OTR32 Outer Bay 

OTR33 Outer Bay 

OTR34 Outer Bay 

OTR35 Outer Bay 

OTR36 Outer Bay 

OTR37 Outer Bay 

OTR38 Outer Bay 

OTR39 Outer Bay 

OTR40 Outer Bay 

SWP41 Target Site (NERR SWMP) 

SWP43 Target Site (NERR SWMP) 

SWP44 Target Site (NERR SWMP) 
Baseline Assessment of Jobos Bay, Puerto Rico: Appendices 

Table B.1 continued... Sediment contaminant data by site. 

Site 

Name Strata 

Inner Bay 

Sn Al Cr Cu Fe Mn Ni Si Zn Hg Se 

ug/L ug/L ug/L ug/L ug/L ug/L ug/L ug/L ug/L ug/L ug/L 

INR2 1.24 70200 

1.64 70200 

1.78 63800 

1.73 65400 

1.91 66100 

1.91 73700 

1.73 68300 

2.02 68200 

1.12 41600 

1.65 51600 

0.787 28300 

0.568 38400 

1.01 48600 

1.02 49100 

1.89 50100 

1.63 52900 

0 2690 

0 629 

0.909 40400 

0.476 24400 

1.82 55400 

1.19 41500 

0.642 28600 

1.35 48000 

2.1 42100 

1.23 44700 

0.979 31700 

1.68 56400 

1.23 42700 

1.16 45300 

0 13900 

0 6570 

0 7790 

0.427 13500 

2.35 39700 

0.726 19900 

1.18 44100 

1.26 23700 

1.1 31300 

0 1400 

0 17300 

0.922 48100 

2.74 24400 

0.702 19400 

24.1 66.5 

27.6 73.7 

25.9 65.4 

25.8 63.6 

27.7 68.1 

28.3 72.8 

26.2 68.5 

28.9 69 

22.7 44.4 

21.7 50.4 

11.7 21.6 

23.8 32.1 

15.6 18.9 

17.1 22.3 

23.6 44.2 

21 33.5 

1.33 3.09 

0 1.37 

16.7 20.2 

8.69 9.33 

21.4 37.2 

14 24.3 

9.43 13.1 

20.6 33 

29.4 58 

27.2 36.9 

16 24.3 

24.8 39 

17.5 25.5 

23.5 35.3 

9.07 16.3 

4.4 7.12 

4.51 7.14 

8.85 12.4 

29.8 52.3 

12.8 20.8 

19.3 26.2 

16.7 40.4 

29.1 26.3 

1.82 1.84 

13.7 12.3 

15.1 20.3 

17.7 42 

15.5 27.6 

49200 

49300 

43100 

44100 

45500 

50500 

47200 

48100 

29000 

36900 

18700 

20900 

26600 

29700 

37100 

33500 

2780 

1060 

26300 

15500 

36400 

25100 

16600 

29500 

30500 

38500 

22200 

36500 

26000 

33800 

9700 

4930 

5810 

9980 

30700 

16700 

27900 

17800 

21800 

2020 

13200 

26700 

16000 

15500 

982 13.1 

1130 15.4 

925 13.8 

943 14.5 

963 16 

799 16.7 

717 16.1 

678 18.6 

589 12.7 

709 13 

440 6.11 

368 22 

718 6.04 

765 7 

645 13.4 

756 9.59 

45.9 0 

33.1 0 

602 10.1 

413 4.01 

816 9.88 

590 6.81 

440 4.39 

615 9.8 

329 26.6 

514 15 

383 8.53 

733 14 

530 7.76 

527 12.2 

117 14.1 

139 0 

110 2.07 

173 4.86 

397 14.6 

260 6.68 

641 10.1 

278 7.46 

378 10.9 

60.5 0 

216 5.62 

701 7.51 

164 24.4 

132 31 

198000 

183000 

172000 

175000 

178000 

161000 

154000 

151000 

151000 

128000 

120000 

235000 

229000 

209000 

137000 

185000 

13600 

7370 

158000 

124000 

193000 

160000 

133000 

166000 

107000 

135000 

92900 

176000 

152000 

131000 

44100 

22700 

27400 

39300 

129000 

63400 

158000 

78900 

112000 

10100 

65400 

217000 

79500 

63700 

87.5 0.0782 

102 0.102 

94.2 0.109 

92.6 0.118 

97.7 0.144 

115 0.0758 

109 0.0651 

117 0.0659 

60.1 0.056 

86.2 0.0787 

38.5 0.0312 

40.1 0.0303 

42.6 0.0147 

45.2 0.0136 

82.5 0.067 

61.1 0.0305 

5.43 0.0046 

1.57 0.0014 

42.1 0.0182 

22.3 0.0098 

67.6 0.0319 

41 0.0132 

25.7 0.0079 

54.7 0.0354 

77.5 0.1 

67.7 0.0554 

44.4 0.0259 

70.6 0.0442 

45.9 0.0217 

59.3 0.0481 

22.2 0.0132 

10.2 0.005 

10.6 0.0074 

20.2 0.0109 

74.6 0.0672 

33.6 0.0259 

51.1 0.0285 

54.9 0.035 

43.4 0.0195 

2.42 0.0026 

22.4 0.009 

42.5 0.0114 

60 0.107 

40 0.0609 

0.279 

0.283 

0.317 

0.267 

0.31 

0.389 

0.479 

0.468 

0.284 

0.291 

0.157 

0.167 

0.119 

0.134 

0.402 

0.235 

0.114 

0.106 

0.158 

0.104 

0.241 

0.179 

0.113 

0.388 

1.56 

0.684 

0.345 

0.318 

0.29 

0.55 

0.476 

0 

0.18 

0.255 

0.687 

0.271 

0.215 

0.311 

0.272 

0 

0.128 

0.161 

0.631 

1.28 

INR3 Inner Bay 

INR4 Inner Bay 

INR5 Inner Bay 

INR6 Inner Bay 

INR7 Inner Bay 

INR8 Inner Bay 

INR9 Inner Bay 

INR10 Inner Bay 

AIN55 Inner Bay 

CNT11 Central Bay 

CNT12 Central Bay 

CNT14 Central Bay 

CNT15 Central Bay 

CNT16 Central Bay 

CNT17 Central Bay 

CNT18 Central Bay 

CNT19 Central Bay 

CNT20 Central Bay 

ACT45 Central Bay 

ACT46 Central Bay 

NER21 Central Bay (Reserve) 

NER22 Central Bay (Reserve) 

NER23 Central Bay (Reserve) 

NER24 Central Bay (Reserve) 

NER25 Central Bay (Reserve) 

NER26 Central Bay (Reserve) 

NER27 Central Bay (Reserve) 

NER28 Central Bay (Reserve) 

NER29 Central Bay (Reserve) 

NER30 Central Bay (Reserve) 

OTR31 Outer Bay 

OTR32 Outer Bay 

OTR33 Outer Bay 

OTR34 Outer Bay 

OTR35 Outer Bay 

OTR36 Outer Bay 

OTR37 Outer Bay 

OTR38 Outer Bay 

OTR39 Outer Bay 

OTR40 Outer Bay 

SWP41 Target Site (NERR SWMP) 

SWP43 Target Site (NERR SWMP) 

SWP44 Target Site (NERR SWMP) 

175 Appendices 
Baseline Assessment of Jobos Bay, Puerto Rico: Appendices 

176 Appendices 

Table B.2 Coral tissue contaminant data by site.

Site

ID Strata 

HCH 

Chlordane DDT PCB PAHs TBT Ag As Pb Se Sn Al Cd Cr Cu Fe Mn Ni Zn Hg 

ng/g ng/g ng/g ng/g ng/g ng/g ug/L ug/L ug/L ug/L ug/L ug/L ug/L ug/L ug/L ug/L ug/L ug/L ug/L ug/L 

IN20 Inner 0 0 0 2.38 4.6 0 0 1.35 0.527 0.134 0 132 0.236 0 69.9 152 8.33 2.44 7.64 0.001 

0 0 0 2.92 5.9 0 0 0.942 0.0796 0.178 0 146 0.235 0 9.57 164 11.9 1.51 3.11 0.0016 0 0 0 2.34 5.8 0 0 1.31 0.0876 0.152 0 125 0.273 0 3.62 148 10.6 1.08 2.89 0.0014 0 0 0 2.19 3.8 0 0 1.89 0.116 0.17 0 178 0.309 0 97.2 274 18 6.84 16.4 0.0016 0 0 0 2.19 3.5 0 0 1.6 12.5 0.152 0 123 0.208 0 4.17 128 10.4 0.796 3.51 0.002 0 0 0.60 3.56 4.6 0 0 1.43 0.775 0.169 0.1 330 0.279 0 91.7 396 19.6 5.42 16.9 0.0019 0 0 0 2.39 4.4 0 0 1.56 0.0783 0.172 0 105 0.216 0 70.5 118 10.5 3.69 11.5 0.0015 0 0 0 2.19 4.5 0 0 1.58 0.17 0.192 0 120 0.286 0 74.4 133 11.4 4.38 14.2 0.0016 

0 0 0 2.24 4.8 0 0 2.44 0.216 0.185 0 125 0.294 0 9.27 146 11 2.15 4.36 0.0038 0 0 0 2.58 5.7 0 0 1.33 6.64 0.194 0 174 0.227 0 68 188 11.4 2.65 7.16 0.0021 0 0 0 2.36 4.2 0 0 1.78 0.424 0.257 0 237 0.248 0 85.8 285 15 6.6 13 0.0032 0 0 0 2.19 2.9 0 0 1.54 0.298 0.159 0 282 0.217 0 2.37 289 14.3 0.817 2.56 0.0022 0 0 0 2.19 3.5 0 0 1.61 0.561 0.192 0 162 0.268 0 70.2 193 10.5 3.43 7.09 0.0016 0 0 0 2.19 6.4 0 0 2.08 0.188 0.229 0 100 0.283 0 6.49 110 13.9 2.52 8.12 0.0018 0 0 0 2.93 4.9 0 0 2.33 0.0934 0.196 0 171 0.242 0 73.8 190 11.8 3.22 9.11 0.0025 0 0 0 2.43 3.7 0 0 2.1 0.151 0.136 0 333 0.25 0 67.8 480 24.6 2.61 9.92 0.0019 

IN21 Inner IN22 Inner IN23 Inner IN25 Inner IN26 Inner IN27 Inner 

IN33a Inner 

OF01 Outer OF02 Outer OF03 Outer OF04 Outer OF05 Outer OF06 Outer OF07 Outer OF08 Outer 
Baseline Assessment of Jobos Bay, Puerto Rico: Appendices 

Appendices 

Figure B.1. Aluminum concentrations in sediments. 

177 

Figure B.2. Aluminum concentrations in corals (Porites astreoides). White outline are coral reefs in inner stratum. Red outline are coral

reefs in outer stratum. 
Baseline Assessment of Jobos Bay, Puerto Rico: Appendices 

178 Appendices 

Figure B.3. Arsenic (As) concentrations in sediments. 

Figure B.4. Cadmium (Cd) concentrations in coral (P. astreoides). White outline are coral reefs in inner stratum. Red outline are coral

reefs in outer stratum. 
Baseline Assessment of Jobos Bay, Puerto Rico: Appendices 

Appendices 

Figure B.5. Chromium (Cr) concentrations in sediments. 

179 
Baseline Assessment of Jobos Bay, Puerto Rico: Appendices 

180 Appendices 

Figure B.6. Copper (Cu) concentrations in sediments. 

Figure B.7. Copper concentrations in coral (P. astreoides). White outline are coral reefs in inner stratum. Red outline are coral reefs in 

outer stratum. 
Baseline Assessment of Jobos Bay, Puerto Rico: Appendices 

Appendices 

Figure B.8. Iron (Fe) concentrations in sediments. 

181 

Figure B.9. Iron concentrations in coral (P. astreoides). White outline are coral reefs in inner stratum. Red outline are coral reefs in 

outer stratum. 
Baseline Assessment of Jobos Bay, Puerto Rico: Appendices 

182 Appendices 

Figure B.10. Mercury (Hg) concentrations in sediments. 

Figure B.11. Mercury concentrations in coral (P. astreoides). White outline are coral reefs in inner stratum. Red outline are coral reefs 

in outer stratum. 
Baseline Assessment of Jobos Bay, Puerto Rico: Appendices 

Appendices 

Figure B.12. Manganese (Mn) concentrations in sediments. 

183 

Figure B.13. Manganese concentrations in coral (P. astreoides). White outline are coral reefs in inner stratum. Red outline are coral

reefs in outer stratum. 
Baseline Assessment of Jobos Bay, Puerto Rico: Appendices 

184 Appendices 

Figure B.14. Nickel (Ni) concentrations in sediments. 

Figure B.15. Nickel concentrations in coral (P. astreoides). White outline are coral reefs in inner stratum. Red outline are coral reefs in 

outer stratum. 
Baseline Assessment of Jobos Bay, Puerto Rico: Appendices 

Appendices 

Figure B.16. Lead (Pb) concentrations in sediments. 

185 

Figure B.17. Antimony (Sb) concentrations in sediments. 
Baseline Assessment of Jobos Bay, Puerto Rico: Appendices 

186 Appendices 

Figure B.18. Selenium (Se) concentrations in sediments. 

Figure B.19. Selenium concentrations in coral (P. astreoides). White outline are coral reefs in inner stratum. Red outline are coral reefs

in outer stratum. 
Baseline Assessment of Jobos Bay, Puerto Rico: Appendices 

Appendices 

Figure B.20. Tin (Sn) concentrations in sediments. 

187 

Figure B.21. Tin concentrations in coral (P. astreoides). White outline are coral reefs in inner stratum. Red outline are coral reefs in 

outer stratum. 
Baseline Assessment of Jobos Bay, Puerto Rico: Appendices 

188 Appendices 

Figure B.22. Zinc (Zn) concentrations in sediments. 

Figure B.23. Zinc concentrations in coral (P. astreoides). White outline are coral reefs in inner stratum. Red outline are coral reefs in 

outer stratum. 

U.S. Department of Commerce 

Gary Locke

Secretary 

National Oceanic and Atmospheric Administration 

Jane Lubchenco, Ph.D. 

Under Secretary for Oceans and Atmosphere 

National Ocean Service 

David Kennedy

Assistant Administrator for Ocean Service and Coastal Zone Management