OCS Study

BOEM 2012-109

Literature Search and Data Synthesis for

Marine Mammals and Sea Turtles in the

U.S. Atlantic from Maine to the Florida Keys

U.S. Department of the Interior

Bureau of Ocean Energy Management

Gulf of Mexico OCS Region
OCS Study

BOEM 2012-109

Published by

U.S. Department of the Interior

Bureau of Ocean Energy Management

Gulf of Mexico OCS Region

New Orleans, LA

December 2012

Literature Search and Data Synthesis

for Marine Mammals and Sea Turtles 

in the U.S. Atlantic from Maine

to the Florida Keys

Authors

G.T. Waring

S.A. Wood

E. Josephson

Prepared under BOEM Contract

M09PG00018

by

NOAA Fisheries Service

Northeast Fisheries Science Center

Protected Species Branch

166 Water St.

Woods Hole, MA 02543-1026
iii

DISCLAIMER

This report was prepared under contract between the Bureau of Ocean Energy Management 

(BOEM) and the National Oceanic and Atmospheric Administration (NOAA). This report has 

been technically reviewed by BOEM, and it has been approved for publication. Approval does 

not signify that the contents necessarily reflect the views and policies of BOEM, nor does 

mention of trade names or commercial products constitute endorsement or recommendation for 

use. It is, however, exempt from review and compliance with BOEM editorial standards.

REPORT AVAILABILITY

This report is available on CD from the Bureau of Ocean Energy Management, Gulf of Mexico 

OCS Region, for $15.00, and as a pdf file downloaded from the BOEM Web site. Copies can be 

viewed at selected Federal Depository Libraries.

This report is available on CD from the Bureau of Ocean Energy Management, Gulf of Mexico 

OCS Region, for $15.00, and free of charge as a pdf file downloaded from the BOEM Web site. 

Copies can also be viewed at selected Federal Depository Libraries. The addresses are listed 

below.

To order a CD, use the Gulf of Mexico OCS Region contact information below and reference 

OCS Study BOEM 2012-109. To download a pdf copy, use the Environmental Studies Program 

Information System (ESPIS) and search on the study report number. In the near future, you will 

also be able to get this report also from the National Technical Information Service.

U.S. Department of the Interior

Bureau of Ocean Energy Management

Gulf of Mexico OCS Region

Public Information Office (GM 217G)

1201 Elmwood Park Blvd.

New Orleans, Louisiana 70123-2394

Phone: (504) 736-2519, 1-800-200-GULF

Fax: (504) 736-2620

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Fax: (703) 605-6900

Web site: http://www.ntis.gov/

CITATION

Waring, Gordon T., Stephanie A. Wood, and Elizabeth Josephson. 2012. Literature search and 

data synthesis for marine mammals and sea turtles in the U.S. Atlantic from Maine to 

the Florida Keys. U.S. Dept. of the Interior, Bureau of Ocean Energy Management, Gulf 

of Mexico OCS Region, New Orleans, LA. OCS Study BOEM 2012-109. 456 pp.
v 

CONTENTS 

LIST OF FIGURES ..................................................................................................................XVII

LIST OF TABLES ..................................................................................................................... XXI

ACRONYMS AND ABBREVIATIONS......................................................................................XXIII

1. INTRODUCTION................................................................................................................ 1

1.1 PROJECTS GOALS AND OBJECTIVES...................................................................................................... 1

1.2 REPORT ORGANIZATION.................................................................................................................... 4

2. SPECIES SUMMARIES ....................................................................................................... 5

2.1 NORTH ATLANTIC RIGHT WHALE (EUBALAENA GLACIALIS) ...................................................................... 5

2.1.1 Legal Status............................................................................................................................................5

2.1.2 General Distribution...............................................................................................................................5

2.1.3 General Abundance................................................................................................................................6

2.1.4 Habitat Preference.................................................................................................................................6

2.1.5 Stock Structure.......................................................................................................................................7

2.1.6 Life History Traits...................................................................................................................................7

2.1.7 Food Habits............................................................................................................................................8

2.1.8 Health ..................................................................................................................................................10

2.1.9 Acoustics..............................................................................................................................................11

2.1.10    Fisheries By‐catch and Entanglement ..................................................................................................12

2.1.11    Vessel Interactions ...............................................................................................................................12

2.1.12    Energy Projects.....................................................................................................................................13

2.1.13    Data Gaps and Research Recommendations.......................................................................................14

2.2 BLUE WHALE (BALAENOPTERA MUSCULUS)........................................................................................ 14

2.2.1 Legal Status..........................................................................................................................................14

2.2.2 General Distribution.............................................................................................................................15

2.2.3 General Abundance..............................................................................................................................15

2.2.4 Habitat Preference...............................................................................................................................15

2.2.5 Stock Structure.....................................................................................................................................15

2.2.6 Life History Traits.................................................................................................................................15

2.2.7 Food Habits..........................................................................................................................................16

2.2.8 Health ..................................................................................................................................................16

2.2.9 Acoustics..............................................................................................................................................16

2.3 FIN WHALE (BALAENOPTERA PHYSALUS)............................................................................................ 18

2.3.1 Legal Status..........................................................................................................................................18

2.3.2 General Distribution.............................................................................................................................18

2.3.3 General Abundance..............................................................................................................................18

2.3.4 Habitat Preference...............................................................................................................................18

2.3.5 Stock Structure.....................................................................................................................................19

2.3.6 Life History Traits.................................................................................................................................19

2.3.7 Food Habits..........................................................................................................................................19

2.3.8 Health ..................................................................................................................................................20

2.3.9 Acoustics..............................................................................................................................................21

2.3.10    Fisheries By‐catch and Entanglement ..................................................................................................22

2.3.11    Data Gaps and Research Recommendations.......................................................................................23
vi 

2.4 SEI WHALE (BALAENOPTERA BOREALIS) ............................................................................................. 23

2.4.1 Legal Status..........................................................................................................................................23

2.4.2 General Distribution.............................................................................................................................23

2.4.3 General Abundance..............................................................................................................................24

2.4.4 Habitat Preference...............................................................................................................................24

2.4.5 Stock Structure.....................................................................................................................................24

2.4.6 Life History Traits.................................................................................................................................24

2.4.7 Food Habits..........................................................................................................................................24

2.4.8 Health ..................................................................................................................................................24

2.4.9 Acoustics..............................................................................................................................................25

2.4.10    Fisheries By‐catch and Entanglement ..................................................................................................25

2.4.11    Vessel Interactions ...............................................................................................................................25

2.4.12    Energy Projects.....................................................................................................................................26

2.4.13    Data Gaps and Research Recommendations.......................................................................................26

2.5 MINKE WHALE (BALAENOPTERA ACUTOROSTRATA) ............................................................................. 26

2.5.1 Legal Status..........................................................................................................................................26

2.5.2 General Distribution.............................................................................................................................26

2.5.3 General Abundance..............................................................................................................................27

2.5.4 Habitat Preference...............................................................................................................................27

2.5.5 Stock Structure.....................................................................................................................................27

2.5.6 Life History Traits.................................................................................................................................28

2.5.7 Food Habits..........................................................................................................................................28

2.5.8 Health ..................................................................................................................................................28

2.5.9 Acoustics..............................................................................................................................................29

2.5.10    Fisheries By‐catch and Entanglement ..................................................................................................30

2.5.11    Vessel Interactions ...............................................................................................................................30

2.5.12    Energy Projects.....................................................................................................................................30

2.5.13    Data Gaps and Research Recommendations.......................................................................................30

2.6 HUMPBACK WHALE (MEGAPTERA NOVAEANGLIAE)............................................................................. 31

2.6.1 Legal Status..........................................................................................................................................31

2.6.2 General Distribution.............................................................................................................................31

2.6.3 General Abundance..............................................................................................................................31

2.6.4 Habitat Preference...............................................................................................................................31

2.6.5 Stock Structure.....................................................................................................................................32

2.6.6 Life History Traits.................................................................................................................................32

2.6.7 Food Habits..........................................................................................................................................32

2.6.8 Health ..................................................................................................................................................33

2.6.9 Acoustics..............................................................................................................................................34

2.6.10    Fisheries By‐catch and Entanglement ..................................................................................................35

2.6.11    Vessel Interactions ...............................................................................................................................35

2.6.12    Energy Projects.....................................................................................................................................36

2.6.13    Data Gaps and Research Recommendations.......................................................................................36

2.7 SPERM WHALE (PHYSETER MACROCEPHALUS) .................................................................................... 37

2.7.1 Legal Status..........................................................................................................................................37

2.7.2 General Distribution.............................................................................................................................37

2.7.3 General Abundance..............................................................................................................................37

2.7.4 Habitat Preference...............................................................................................................................37

2.7.5 Stock Structure.....................................................................................................................................38

2.7.6 Life History Traits.................................................................................................................................38

2.7.7 Food Habits..........................................................................................................................................38

2.7.8 Health ..................................................................................................................................................39

2.7.9 Acoustics..............................................................................................................................................40
vii 

2.7.10 Fisheries By‐catch and Entanglement.............................................................................................41

2.7.11 Vessel Interactions..........................................................................................................................41

2.7.12 Energy Projects................................................................................................................................42

2.7.13 Data Gaps and Research Recommendations..................................................................................42

2.8 PYGMY & DWARF SPERM WHALE (KOGIA SPP.).................................................................................. 43

2.8.1 Status..............................................................................................................................................43

2.8.2 General Distribution........................................................................................................................43

2.8.3 General Abundance.........................................................................................................................43

2.8.4 Habitat Preference ..........................................................................................................................43

2.8.5 Stock Structure ................................................................................................................................43

2.8.6 Life History Traits ............................................................................................................................44

2.8.7 Food Habits.....................................................................................................................................44

2.8.8 Health..............................................................................................................................................44

2.8.9 Acoustics .........................................................................................................................................45

2.8.10 Fisheries By‐Catch/Entanglement...................................................................................................46

2.8.11 Vessel Interactions..........................................................................................................................46

2.8.12 Energy Projects................................................................................................................................46

2.8.13 Data Gaps and Research Recommendations..................................................................................46

2.9 CUVIER'S BEAKED WHALE (ZIPHIUS CAVIROSTRIS)................................................................................ 46

2.9.1 Status..............................................................................................................................................46

2.9.2 General Distribution........................................................................................................................46

2.9.3 General Abundance.........................................................................................................................46

2.9.4 Habitat Preference ..........................................................................................................................47

2.9.5 Stock Structure ................................................................................................................................47

2.9.6 Life History Traits ............................................................................................................................48

2.9.7 Food Habits.....................................................................................................................................48

2.9.8 Health..............................................................................................................................................48

2.9.9 Acoustics .........................................................................................................................................49

2.9.10 Fisheries By‐Catch and Entanglement.............................................................................................50

2.9.11 Vessel Interactions..........................................................................................................................50

2.9.12 Energy Projects................................................................................................................................50

2.9.13 Data Gaps and Research Recommendations..................................................................................50

2.10 NORTHERN BOTTLENOSE WHALE (HYPEROODON AMPULLATUS)............................................................ 51

2.10.1 Status..............................................................................................................................................51

2.10.2 General Distribution........................................................................................................................51

2.10.3 General Abundance.........................................................................................................................51

2.10.4 Habitat Preference ..........................................................................................................................51

2.10.5 Stock Structure ................................................................................................................................52

2.10.6 Life History Traits ............................................................................................................................52

2.10.7 Food Habits.....................................................................................................................................52

2.10.8 Health..............................................................................................................................................53

2.10.9 Acoustics .........................................................................................................................................53

2.10.10 Fisheries By‐Catch/Entanglement...................................................................................................53

2.10.11 Vessel Interactions..........................................................................................................................53

2.10.12 Energy Projects................................................................................................................................54

2.10.13 Data Gaps and Research Recommendations..................................................................................54

2.11 BEAKED WHALES (MESOPLODON SPP.).............................................................................................. 54

2.11.1 Status..............................................................................................................................................54

2.11.2 General Distribution........................................................................................................................54

2.11.3 General Abundance.........................................................................................................................54

2.11.4 Habitat Preference ..........................................................................................................................55

2.11.5 Stock Structure ................................................................................................................................55
viii 

2.11.6 Life History Traits ............................................................................................................................56

2.11.7 Food Habits.....................................................................................................................................56

2.11.8 Health..............................................................................................................................................56

2.11.9 Acoustics .........................................................................................................................................58

2.11.10 Fisheries By‐Catch and Entanglement.............................................................................................59

2.11.11 Vessel Interactions..........................................................................................................................59

2.11.12 Energy Projects................................................................................................................................59

2.11.13 Data Gaps and Research Recommendations..................................................................................60

2.12 KILLER WHALE (ORCINUS ORCA)....................................................................................................... 60

2.12.1 Status..............................................................................................................................................60

2.12.2 General Distribution........................................................................................................................60

2.12.3 General Abundance.........................................................................................................................60

2.12.4 Habitat Preference ..........................................................................................................................60

2.12.5 Stock Structure ................................................................................................................................60

2.12.6 Life History Traits ............................................................................................................................61

2.12.7 Food Habits.....................................................................................................................................61

2.12.8 Health..............................................................................................................................................61

2.12.9 Acoustics .........................................................................................................................................62

2.12.10 Fisheries By‐Catch and Entanglement.............................................................................................62

2.12.11 Vessel Interactions..........................................................................................................................62

2.12.12 Energy Projects................................................................................................................................63

2.12.13 Data Gaps and Research Recommendations..................................................................................63

2.13 LONG‐FINNED PILOT WHALES (GLOBICEPHALA MELAS) ........................................................................ 64

2.13.1 Status..............................................................................................................................................64

2.13.2 General Distribution........................................................................................................................64

2.13.3 General Abundance.........................................................................................................................64

2.13.4 Habitat Preference ..........................................................................................................................64

2.13.5 Stock Structure ................................................................................................................................64

2.13.6 Life History Traits ............................................................................................................................65

2.13.7 Food Habits.....................................................................................................................................65

2.13.8 Health..............................................................................................................................................65

2.13.9 Acoustics .........................................................................................................................................67

2.13.10 Fisheries By‐Catch and Entanglement.............................................................................................67

2.13.11 Vessel Interactions..........................................................................................................................68

2.13.12 Energy Projects................................................................................................................................68

2.13.13 Data Gaps and Research Recommendations..................................................................................68

2.14 SHORT‐FINNED PILOT WHALE (GLOBICEPHALA MACRORHYNCHUS) ........................................................ 69

2.14.1 Status..............................................................................................................................................69

2.14.2 General Distribution........................................................................................................................69

2.14.3 General Abundance.........................................................................................................................69

2.14.4 Habitat Preference ..........................................................................................................................69

2.14.5 Stock Structure ................................................................................................................................69

2.14.6 Life History Traits ............................................................................................................................70

2.14.7 Food Habits.....................................................................................................................................70

2.14.8 Health..............................................................................................................................................70

2.14.9 Acoustics .........................................................................................................................................72

2.14.10 Fisheries By‐Catch and Entanglement.............................................................................................72

2.14.11 Vessel Interactions..........................................................................................................................72

2.14.12 Energy Projects................................................................................................................................72

2.14.13 Data Gaps and Research Recommendations..................................................................................73

2.15 PYGMY KILLER WHALE (FERESA ATTENUATA)...................................................................................... 73

2.15.1 Status..............................................................................................................................................73
ix 

2.15.2 General Distribution........................................................................................................................73

2.15.3 General Abundance.........................................................................................................................74

2.15.4 Habitat Preference ..........................................................................................................................74

2.15.5 Stock Structure ................................................................................................................................74

2.15.6 Life History Traits ............................................................................................................................74

2.15.7 Food Habits.....................................................................................................................................74

2.15.8 Health..............................................................................................................................................74

2.15.9 Acoustics .........................................................................................................................................75

2.15.10 Fisheries By‐Catch and Entanglement.............................................................................................75

2.15.11 Vessel Interactions..........................................................................................................................75

2.15.12 Energy Projects................................................................................................................................75

2.15.13 Data Gaps and Research Recommendations..................................................................................75

2.16 MELON‐HEADED WHALE (PEPONOCEPHALA ELECTRA) ......................................................................... 76

2.16.1 Status..............................................................................................................................................76

2.16.2 General Distribution........................................................................................................................76

2.16.3 General Abundance.........................................................................................................................76

2.16.4 Habitat Preference ..........................................................................................................................76

2.16.5 Stock Structure ................................................................................................................................76

2.16.6 Life History Traits: ...........................................................................................................................76

2.16.7 Food Habits.....................................................................................................................................77

2.16.8 Health..............................................................................................................................................77

2.16.9 Acoustics .........................................................................................................................................78

2.16.10 Fisheries By‐Catch and Entanglement.............................................................................................78

2.16.11 Vessel Interactions..........................................................................................................................78

2.16.12 Energy Projects................................................................................................................................78

2.16.13 Data Gaps and Research Recommendations..................................................................................79

2.17 WHITE‐BEAKED DOLPHIN (LAGENORHYNCHUS ALBIROSTRIS)................................................................. 79

2.17.1 Legal Status.....................................................................................................................................79

2.17.2 General Distribution........................................................................................................................79

2.17.3 General Abundance.........................................................................................................................79

2.17.4 Habitat Preference ..........................................................................................................................79

2.17.5 Stock Structure ................................................................................................................................80

2.17.6   Life History Traits ............................................................................................................................80

2.17.7 Food Habits.....................................................................................................................................80

2.17.8 Health..............................................................................................................................................80

2.17.9 Acoustics .........................................................................................................................................81

2.17.10 Fisheries By‐catch/Entanglement....................................................................................................81

2.17.11 Vessel Interactions..........................................................................................................................81

2.17.12 Energy Projects................................................................................................................................81

2.17.13 Data Gaps and Research Recommendations..................................................................................82

2.18 ATLANTIC WHITE‐SIDED DOLPHIN (LAGENORHYNCHUS ACUTUS) ........................................................... 82

2.18.1 Legal Status.....................................................................................................................................82

2.18.2 General Distribution........................................................................................................................82

2.18.3 General Abundance.........................................................................................................................82

2.18.4 Habitat Preference ..........................................................................................................................83

2.18.5 Stock Structure ................................................................................................................................83

2.18.6 Life History Traits ............................................................................................................................83

2.18.7 Food Habits.....................................................................................................................................83

2.18.8 Health..............................................................................................................................................84

2.18.9 Acoustics .........................................................................................................................................84

2.18.10 Fisheries By‐catch and Entanglement.............................................................................................85

2.18.11 Vessel Interactions..........................................................................................................................85
x

2.18.12 Energy Projects................................................................................................................................85

2.18.13 Data Gaps and Research Recommendations..................................................................................86

2.19 RISSO’S DOLPHIN (GRAMPUS GRISEUS)..............................................................................................86

2.19.1 Status..............................................................................................................................................86

2.19.2 General Distribution........................................................................................................................86

2.19.3 General Abundance.........................................................................................................................86

2.19.4 Habitat Preference ..........................................................................................................................87

2.19.5 Stock Structure ................................................................................................................................87

2.19.6 Life History Traits ............................................................................................................................87

2.19.7 Food Habits.....................................................................................................................................88

2.19.8 Health..............................................................................................................................................88

2.19.9 Acoustics .........................................................................................................................................88

2.19.10 Fisheries By-Catch and Entanglement.............................................................................................89

2.19.11 Vessel Interactions..........................................................................................................................89

2.19.12 Energy Projects................................................................................................................................89

2.19.13 Data Gaps and Research Recommendations..................................................................................90

2.20 BOTTLENOSE DOLPHIN (TURSIOPS TRUNCATUS) ..................................................................................90

2.20.1 Status..............................................................................................................................................90

2.20.2 General Distribution........................................................................................................................90

2.20.3 General Abundance.........................................................................................................................90

2.20.4 Habitat Preference ..........................................................................................................................91

2.20.5 Stock Structure ................................................................................................................................91

2.20.6 Life History Traits ............................................................................................................................92

2.20.7 Food Habits.....................................................................................................................................92

2.20.8 Health..............................................................................................................................................93

2.20.9 Acoustics .........................................................................................................................................96

2.20.10 Fisheries By-Catch and Entanglement.............................................................................................97

2.20.11 Vessel Interactions..........................................................................................................................98

2.20.12 Energy Projects................................................................................................................................99

2.20.13 Data Gaps and Research Recommendations................................................................................100

2.21 PANTROPICAL SPOTTED DOLPHIN (STENELLA ATTENUATA)..................................................................100

2.21.1 Legal Status...................................................................................................................................100

2.21.2 General Distribution......................................................................................................................100

2.21.3 General Abundance.......................................................................................................................100

2.21.4 Habitat Preference ........................................................................................................................100

2.21.5 Stock Structure ..............................................................................................................................101

2.21.6 Life History Traits ..........................................................................................................................101

2.21.7 Food Habits...................................................................................................................................101

2.21.8 Health............................................................................................................................................101

2.21.9 Acoustics .......................................................................................................................................102

2.21.10 Fisheries By-catch and Entanglement...........................................................................................102

2.21.11 Vessel Interactions........................................................................................................................102

2.21.12 Energy Projects..............................................................................................................................102

2.21.13 Data Gaps and Research Recommendations................................................................................103

2.22 ATLANTIC SPOTTED DOLPHIN (STENELLA FRONTALIS) .........................................................................103

2.22.1 Legal Status...................................................................................................................................103

2.22.2 General Distribution......................................................................................................................103

2.22.3 General Abundance.......................................................................................................................103

2.22.4 Habitat Preference ........................................................................................................................103

2.22.5 Stock Structure ..............................................................................................................................104

2.22.6 Life History Traits ..........................................................................................................................104

2.22.7 Food Habits...................................................................................................................................104
xi

2.22.8 Health............................................................................................................................................105

2.22.9 Acoustics .......................................................................................................................................105

2.22.10 Fisheries By-Catch and Entanglement...........................................................................................106

2.22.11 Vessel Interactions........................................................................................................................106

2.22.12 Energy Projects..............................................................................................................................106

2.22.13 Data Gaps and Research Recommendations................................................................................107

2.23 SPINNER DOLPHIN (STENELLA LONGIROSTRIS)...................................................................................107

2.23.1 Status............................................................................................................................................107

2.23.2 General Distribution......................................................................................................................107

2.23.3 General Abundance.......................................................................................................................107

2.23.4 Habitat Preference ........................................................................................................................107

2.23.5 Stock Structure ..............................................................................................................................107

2.23.6 Life History Traits ..........................................................................................................................108

2.23.7 Food Habits...................................................................................................................................108

2.23.8 Health............................................................................................................................................108

2.23.9 Acoustics .......................................................................................................................................109

2.23.10 Fisheries By-Catch and Entanglement...........................................................................................109

2.23.11 Vessel Interactions........................................................................................................................109

2.23.12 Energy Projects..............................................................................................................................109

2.23.13 Data Gaps and Research Recommendations................................................................................110

2.24 ROUGH TOOTHED DOLPHIN (STENO BREDANENSIS) ...........................................................................110

2.24.1 Legal Status...................................................................................................................................110

2.24.2 General Distribution......................................................................................................................110

2.24.3 General Abundance.......................................................................................................................110

2.24.4 Habitat Preference ........................................................................................................................110

2.24.5 Stock Structure ..............................................................................................................................110

2.24.6 Life History Traits ..........................................................................................................................111

2.24.7 Food Habits...................................................................................................................................111

2.24.8 Health............................................................................................................................................111

2.24.9 Acoustics .......................................................................................................................................111

2.24.10 Fisheries By-catch/Entanglement .................................................................................................111

2.24.11 Vessel Interactions........................................................................................................................111

2.24.12 Energy Projects..............................................................................................................................111

2.24.13 Data Gaps and Research Recommendations................................................................................112

2.25 CLYMENE DOLPHIN (STENELLA CLYMENE).........................................................................................112

2.25.1 Status............................................................................................................................................112

2.25.2 General Distribution......................................................................................................................112

2.25.3 General Abundance.......................................................................................................................112

2.25.4 Habitat Preference ........................................................................................................................113

2.25.5 Stock Structure ..............................................................................................................................113

2.25.6 Life History Traits ..........................................................................................................................113

2.25.7 Food Habits...................................................................................................................................113

2.25.8 Health............................................................................................................................................113

2.25.10 Acoustics .......................................................................................................................................114

2.25.11 Fisheries By-Catch/Entanglement.................................................................................................114

2.25.12 Ship Strikes....................................................................................................................................114

2.25.13 Energy Projects..............................................................................................................................114

2.25.14 Data Gaps and Research Recommendations................................................................................114

2.26 STRIPED DOLPHIN (STENELLA COERULEOALBA)..................................................................................115

2.26.1 Status............................................................................................................................................115

2.26.2 General Distribution......................................................................................................................115

2.26.3 General Abundance.......................................................................................................................115
xii

2.26.4 Habitat Preference ........................................................................................................................115

2.26.5 Stock Structure ..............................................................................................................................115

2.26.6 Life History Traits ..........................................................................................................................116

2.26.7 Food Habits...................................................................................................................................116

2.26.8 Health............................................................................................................................................116

2.26.9 Acoustics .......................................................................................................................................116

2.26.10 Fisheries By-Catch and Entanglement...........................................................................................117

2.26.11 Vessel Interactions........................................................................................................................117

2.26.12 Energy Projects..............................................................................................................................117

2.26.13 Data Gaps and Research Recommendations................................................................................117

2.27 SHORT-BEAKED COMMON DOLPHIN (DELPHINUS DELPHIS) .................................................................118

2.27.1 Legal Status...................................................................................................................................118

2.27.2 General Distribution......................................................................................................................118

2.27.3 General Abundance.......................................................................................................................118

2.27.4 Habitat Preference ........................................................................................................................118

2.27.5 Stock Structure ..............................................................................................................................118

2.27.6 Life History Traits ..........................................................................................................................119

2.27.7 Food Habits...................................................................................................................................119

2.27.8 Health............................................................................................................................................119

2.27.9 Acoustics .......................................................................................................................................120

2.27.10 Fisheries By-catch/Entanglement .................................................................................................120

2.27.11 Ship Strikes....................................................................................................................................121

2.27.12 Energy Projects..............................................................................................................................121

2.27.13 Data Gaps and Research Recommendations................................................................................121

2.28 FRASER'S DOLPHIN (LAGENODELPHIS HOSEI).....................................................................................122

2.28.1 Legal Status...................................................................................................................................122

2.28.2 General Distribution......................................................................................................................122

2.28.3 General Abundance.......................................................................................................................122

2.28.4 Habitat Preference ........................................................................................................................122

2.28.5 Stock Structure ..............................................................................................................................122

2.28.6 Life History Traits ..........................................................................................................................122

2.28.7 Food Habits...................................................................................................................................123

2.28.8 Health............................................................................................................................................123

2.28.9 Acoustics .......................................................................................................................................123

2.28.10 Fisheries By-catch and Entanglement...........................................................................................123

2.28.11 Vessel Interactions........................................................................................................................124

2.28.12 Energy Projects..............................................................................................................................124

2.28.13 Data Gaps and Research Recommendations................................................................................124

2.29 HARBOR PORPOISE (PHOCOENA PHOCOENA)....................................................................................124

2.29.1 Status............................................................................................................................................124

2.29.2 General Distribution......................................................................................................................124

2.29.3 General Abundance.......................................................................................................................125

2.29.4 Habitat Preference ........................................................................................................................125

2.29.5 Stock Structure ..............................................................................................................................125

2.29.6 Life History Traits ..........................................................................................................................125

2.29.7 Food Habits...................................................................................................................................126

2.29.8 Health............................................................................................................................................126

2.29.9 Acoustics .......................................................................................................................................127

2.29.11 Fisheries By-Catch and Entanglement...........................................................................................127

2.29.12 Ship Strikes....................................................................................................................................127

2.29.13 Energy Projects..............................................................................................................................127

2.29.14 Data Gaps and Research Recommendations................................................................................129
xiii

2.30 WEST INDIAN MANATEE (TRICHECHUS MANATUS LATIROSTRIS)............................................................129

2.30.1 Status............................................................................................................................................129

2.30.2 General Distribution......................................................................................................................129

2.30.3 General Abundance.......................................................................................................................129

2.30.4 Habitat Preference ........................................................................................................................130

2.30.5 Stock Structure ..............................................................................................................................130

2.30.6 Life History Traits ..........................................................................................................................131

2.30.7 Food Habits...................................................................................................................................131

2.30.8 Health............................................................................................................................................131

2.30.9 Acoustics .......................................................................................................................................132

2.30.10 Fisheries By-Catch and Entanglement...........................................................................................133

2.30.11 Vessel Interactions........................................................................................................................133

2.30.12 Energy Projects..............................................................................................................................133

2.30.13 Data Gaps and Research Recommendations................................................................................134

2.31 HARBOR SEAL (PHOCA VITULINA CONCOLOR)....................................................................................134

2.31.1 Status............................................................................................................................................134

2.31.2 General Distribution......................................................................................................................134

2.31.3 General Abundance.......................................................................................................................134

2.31.4 Habitat Preference ........................................................................................................................135

2.31.5 Stock Structure ..............................................................................................................................135

2.31.6 Life History Traits ..........................................................................................................................136

2.31.7 Food Habits...................................................................................................................................136

2.31.8 Health............................................................................................................................................137

2.31.9 Acoustics .......................................................................................................................................139

2.31.10 Fisheries By-Catch/Entanglement.................................................................................................140

2.31.11 Vessel Interactions........................................................................................................................140

2.31.12 Energy Projects..............................................................................................................................140

2.31.13 Data Gaps and Research Recommendations................................................................................141

2.32 HARP SEAL (PAGOPHILUS GROENLANDICUS) .....................................................................................141

2.32.1 Status............................................................................................................................................141

2.32.2 General Distribution......................................................................................................................141

2.32.3 General Abundance.......................................................................................................................142

2.32.4 Habitat Preference ........................................................................................................................142

2.32.5 Stock Structure ..............................................................................................................................142

2.32.6 Life History Traits ..........................................................................................................................143

2.32.7 Food Habits...................................................................................................................................143

2.32.8 Health............................................................................................................................................144

2.32.9 Acoustics .......................................................................................................................................145

2.32.10 Fisheries By-Catch and Entanglement...........................................................................................145

2.32.11 Vessel Interactions........................................................................................................................145

2.32.12 Energy Projects..............................................................................................................................145

2.32.13 Data Gaps and Research Recommendations................................................................................146

2.33 GRAY SEAL (HALICHOERUS GRYPUS)................................................................................................146

2.33.1 Status............................................................................................................................................146

2.33.2 General Distribution......................................................................................................................146

2.33.3 General Abundance.......................................................................................................................146

2.33.4 Habitat Preference ........................................................................................................................147

2.33.5 Stock Structure ..............................................................................................................................147

2.33.6 Life History Traits ..........................................................................................................................148

2.33.7 Food Habits...................................................................................................................................149

2.33.8 Health............................................................................................................................................150

2.33.9 Acoustics .......................................................................................................................................152
xiv

2.33.10 Fisheries By-Catch and Entanglement...........................................................................................152

2.33.11 Vessel Interactions........................................................................................................................152

2.33.12 Energy Projects..............................................................................................................................152

2.33.13 Data Gaps and Research Recommendations................................................................................153

2.34 HOODED SEAL (CYSTOPHORA CRISTATA) ..........................................................................................153

2.34.1 Status............................................................................................................................................153

2.34.2 General Distribution......................................................................................................................153

2.34.3 General Abundance.......................................................................................................................154

2.34.4 Habitat Preference ........................................................................................................................154

2.34.5 Stock Structure ..............................................................................................................................154

2.34.6 Life History Traits ..........................................................................................................................154

2.34.7 Food Habits...................................................................................................................................154

2.34.8 Health............................................................................................................................................155

2.34.9 Acoustics .......................................................................................................................................156

2.34.10 Fisheries By-Catch and Entanglement...........................................................................................156

2.34.11 Vessel Interactions........................................................................................................................156

2.34.12 Energy Projects..............................................................................................................................156

2.34.13 Data Gaps and Research Recommendations................................................................................157

2.35 KEMP’S RIDLEY TURTLE (LEPIDOCHELYS KEMPII)................................................................................157

2.35.1 Legal Status...................................................................................................................................157

2.35.2 General Distribution......................................................................................................................157

2.35.3 General Abundance.......................................................................................................................157

2.35.4 Habitat Preference ........................................................................................................................158

2.35.5 Stock Structure ..............................................................................................................................159

2.35.6 Life History Traits ..........................................................................................................................159

2.35.7 Food Habits...................................................................................................................................160

2.35.8 Health............................................................................................................................................160

2.35.9 Acoustics .......................................................................................................................................161

2.35.10 Fisheries By-Catch and Entanglement...........................................................................................162

2.35.11 Vessel Interactions........................................................................................................................162

2.35.12 Energy Projects..............................................................................................................................162

2.35.13 Data Gaps and Research Recommendations................................................................................163

2.36 GREEN TURTLE (CHELONIA MYDAS).................................................................................................163

2.36.1 Legal Status...................................................................................................................................163

2.36.2 General Distribution......................................................................................................................164

2.36.3 General Abundance.......................................................................................................................164

2.36.4 Habitat Preference ........................................................................................................................165

2.36.5 Stock Structure ..............................................................................................................................166

2.36.6 Life History Traits ..........................................................................................................................167

2.36.7 Food Habits...................................................................................................................................167

2.36.8 Health............................................................................................................................................167

2.36.9 Acoustics .......................................................................................................................................168

2.36.10 Fisheries By-catch and Entanglement...........................................................................................169

2.36.11 Vessel Interactions........................................................................................................................169

2.36.12 Energy Projects..............................................................................................................................169

2.36.13 Data Gaps and Research Recommendations................................................................................170

2.37 HAWKSBILL TURTLE (ERETMOCHELYS IMBRICATA)..............................................................................170

2.37.1 Legal Status...................................................................................................................................170

2.37.2 General Distribution......................................................................................................................170

2.37.3 General Abundance.......................................................................................................................171

2.37.4 Habitat Preference ........................................................................................................................171

2.37.5 Stock Structure ..............................................................................................................................172
xv

2.37.6 Life History Traits ..........................................................................................................................173

2.37.7 Food Habits...................................................................................................................................173

2.37.8 Health............................................................................................................................................174

2.37.9 Acoustics .......................................................................................................................................174

2.37.10 Fisheries By-Catch and Entanglement...........................................................................................174

2.37.11 Vessel Interactions........................................................................................................................174

2.37.12 Energy Projects..............................................................................................................................175

2.37.13 Data Gaps and Research Recommendations................................................................................175

2.38 LOGGERHEAD TURTLE (CARETTA CARETTA) .......................................................................................176

2.38.1 Legal Status...................................................................................................................................176

2.38.2 General Distribution......................................................................................................................176

2.38.3 General Abundance.......................................................................................................................176

2.38.4 Habitat Preference ........................................................................................................................177

2.38.5 Stock Structure ..............................................................................................................................180

2.38.6 Life History Traits ..........................................................................................................................181

2.38.7 Food Habits...................................................................................................................................182

2.38.8 Health............................................................................................................................................183

2.38.9 Acoustics .......................................................................................................................................184

2.38.10 Fisheries By-Catch and Entanglement...........................................................................................185

2.38.11 Vessel Interactions........................................................................................................................186

2.38.12 Energy Projects..............................................................................................................................186

2.38.13 Data Gaps and Research Recommendations................................................................................187

2.39 LEATHERBACK TURTLE (DERMOCHELYS CORIACEA).............................................................................187

2.39.2 General Distribution......................................................................................................................188

2.39.3 General Abundance.......................................................................................................................188

2.39.4 Habitat Preference ........................................................................................................................190

2.39.5 Stock Structure ..............................................................................................................................192

2.39.6 Life History Traits ..........................................................................................................................192

2.39.7 Food Habits...................................................................................................................................193

2.39.8 Health............................................................................................................................................195

2.39.9 Acoustics .......................................................................................................................................196

2.39.10 Fisheries By-Catch and Entanglement...........................................................................................196

2.39.11 Vessel Interactions........................................................................................................................197

2.39.12 Energy Projects..............................................................................................................................197

2.39.13 Data Gaps and Research Recommendations................................................................................197

3.0 CURRENT RESEARCH .................................................................................................... 289

4.0 LITERATURE CITED ....................................................................................................... 323
xvii

LIST OF FIGURES

Figure 1.1.1. BOEM Atlantic OCS Planning Areas. ...............................................................................................212

Figure 2.1.1. North Atlantic right whale sighting (green squares) and stranding (red dots) observations by 

season.............................................................................................................................................213

Figure 2.1.2. North Atlantic right whale critical habitat areas and northeastern shipping lanes........................214

Figure 2.2.1. Blue whales sighting (green squares) observations by season.......................................................215

Figure 2.3.1. Fin whale sighting (green squares), stranding (red dots) and fishery by-catch (black stars) 

observations by season...................................................................................................................216

Figure 2.4.1. Sei whale sighting (green squares) and stranding (red dots) observations of by season...............217

Figure 2.5.1. Minke whale sighting (green squares), stranding (red dots) and fishery by-catch (black stars) 

observations by season...................................................................................................................218

Figure 2.6.1. Humpback whale sighting (green squares) and stranding (red dots) observations by season. .....219

Figure 2.7.1. Sperm whale sighting (green squares) and stranding (red dots) observations by season. ............220

Figure 2.8.1. Dwarf and pygmy sperm whale sighting (green squares), stranding (red dots) and fishery and 

fishery by-catch (black stars) observations by season....................................................................221

Figure 2.9.1. Cuvier’s beaked whale sighting (green squares) and stranding (red dots) observations by 

season.............................................................................................................................................222

Figure 2.10.1. Northern bottlenose whale sighting (green squares) and stranding (red dots) by season. ...........223

Figure 2.11.1. Mesoplodon beaked whale sighting (green squares), stranding (red dots) and fishery by-catch 

(black stars) observations by season. .............................................................................................224

Figure 2.12.1. Killer whale sighting (green squares) observations by season. ......................................................225

Figure 2.13.1. Long-finned and undifferentiated pilot whale sighting (green squares), stranding (red dots) 

and fishery by-catch (black stars) observations by season.............................................................226

Figure 2.14.1. Short-finned and undifferentiated pilot whale sighting (green squares), stranding (red dots) 

and fishery by-catch (black stars) observations by season.............................................................227

Figure 2.15.1. Pygmy killer whale sighting (green squares) and stranding (red dots) observations by season. ...228

Figure 2.16.1. Melon-headed whale sighting (green squares) and stranding (red dots) observations by 

season.............................................................................................................................................229

Figure 2.17.1. White-beaked dolphin sighting (green squares), stranding (red dots) and fishery by-catch 

(black stars) observations by season. .............................................................................................230

Figure 2.18.1. White-sided dolphin sighting (green squares), stranding (red dots) and fishery by-catch (black 

stars) observations by season.........................................................................................................231

Figure 2.19.1. Risso’s dolpin sighting (green squares), stranding (red dots) and fishery by-catch (black stars) 

observations by season...................................................................................................................232

Figure 2.20.2. Bottlenose dolphin sighting (green squares), stranding (red dots) and fishery by-catch (black 

stars) observations by season.........................................................................................................233
xviii

Figure 2.21.1. Pantropical spotted dolphin sighting (green squares), stranding (red dots) and fishery by-catch 

(black stars) observations by season. .............................................................................................234

Figure 2.22.1. Atlantic spotted dolphin sighting (green squares) and stranding (red dots) observations by 

season.............................................................................................................................................235

Figure 2.23.1. Spinner dolphin sighting (green squares), stranding (red dots) and fishery by-catch (black 

stars) observations by season.........................................................................................................236

Figure 2.24.1. Rough-toothed dolphin sighting (green squares) and stranding (red dots) observations by 

season.............................................................................................................................................237

Figure 2.25.1. Clymene dolphin sighting (green squares), stranding (red dots) and fishery by-catch (black 

stars) observations by season.........................................................................................................238

Figure 2.26.1. Striped dolphin sighting (green squares), stranding (red dots) and fishery by-catch (black stars) 

observations by season...................................................................................................................239

Figure 2.27.1. Common dolphin sighting (green squares), stranding (red dots) and fishery by-catch (black 

stars) observations by season.........................................................................................................240

Figure 2.28.2. Fraser’s dolphin sighting (green squares) and stranding (red dots) observations by season.........241

Figure 2.29.1. Harbor porpoise sighting (green squares), stranding (red dots) and fishery by-catch (black 

stars) observations by season.........................................................................................................242

Figure 2.29.2. Map of New England closure areas according to the harbor porpoise Take Reduction Team.......243

Figure 2.29.3 Map of Mid-Atlantic closure areas according to the harbor porpoise Take Reduction Team........244

Figure 2.30.1. Manatee Synoptic Count Data 1991-2011......................................................................................245

Figure 2.31.1. Harbor seal sighting (green squares), stranding (red dots) and fishery by-catch (black stars) 

observations by season...................................................................................................................246

Figure 2.31.2. Positions of satellite-tagged harbor seals.......................................................................................247

Figure 2.32.1. Harp seal stranding (red dots) and fishery by-catch (black stars) observations by season. ...........248

Figure 2.32.2. Positions of satellite-tagged harp seals. .........................................................................................249

Figure 2.33.1. Gray seal sighting (green squares), stranding (red dots) and fishery by-catch (black stars) 

observations by season...................................................................................................................250

Figure 2.33.2. Positions of satellite-tagged gray seals...........................................................................................251

Figure 2.34.1. Hooded seal stranding (red dots) and fishery by-catch (black stars) observations by season. ......252

Figure 2.34.2. Positions of satellite-tagged hooded seals. ....................................................................................253

Figure 2.35.1. Kemp’s ridley range. .......................................................................................................................254

Figure 2.35.2. Kemp’s ridley nesting locations in 2007. ........................................................................................255

Figure 2.35.3. Positions of satellite-tagged Kemp’s ridley sea turtles...................................................................256

Figure 2.35.4. Kemp’s ridley sea turtle sighting (green squares) and fishery by-catch (black stars) 

observations by season...................................................................................................................257

Figure 2.35.5. Kemp’s ridley strandings by zone, 1986-2007. ...............................................................................258

Figure 2.35.6. Seasonal Kemp’s ridley stranding data for years 2008 and 2009. ..................................................259

Figure 2.36.1. Green turtle distribution.................................................................................................................260

Figure 2.36.2. Green turtle nesting densities by county in Florida........................................................................261
xix

Figure 2.36.3. Positions of satellite-tagged green turtles......................................................................................262

Figure 2.36.4. Green sea turtle sighting (green squares) and fishery by-catch (black stars) observations by 

season.............................................................................................................................................263

Figure 2.36.5. Green turtle strandings by zone, 1986-2007. .................................................................................264

Figure 2.36.6. Seasonal green turtle stranding data for years 2008 and 2009......................................................265

Figure 2.37.1. Hawksbill global distribution. .........................................................................................................266

Figure 2.37.2. Florida nesting distribution of the hawksbill turtle. .......................................................................267

Figure 2.37.3. Hawksbill sea turtle sighting (green squares) and fishery by-catch (black stars) observations by 

season.............................................................................................................................................268

Figure 2.37.4. Hawksbill strandings by zone, 1986-2007.......................................................................................269

Figure 2.37.5. Seasonal hawksbill stranding data for years 2008 and 2009..........................................................270

Figure 2.38.1. Loggerhead global distribution.......................................................................................................271

Figure 2.38.2. Distribution of loggerhead nesting sites in Florida.........................................................................272

Figure 2.38.3. Positions of satellite-tagged loggerhead turtles.............................................................................273

Figure 2.38.4. Loggerhead sea turtle sighting (green squares) and fishery by-catch (black stars) observations 

by season. .......................................................................................................................................274

Figure 2.38.5. Loggerhead strandings by zone, 1986-2007. ..................................................................................275

Figure 2.38.6. Seasonal loggerhead stranding data for years 2008 and 2009.......................................................276

Figure 2.39.1. Leatherback global distribution. .....................................................................................................277

Figure 2.39.2. Selected leatherback tag location data 2005-2009. .......................................................................278

Figure 2.39.3. Leatherback nesting in Florida........................................................................................................279

Figure 2.39.4. Leatherback sea turtle sighting (green squares) and fishery by-catch (black stars) observations 

by season. .......................................................................................................................................280

Figure 2.39.5. Leatherback strandings by zone, 1986-2007. .................................................................................281

Figure 2.39.6. Seasonal leatherback stranding data for years 2008 and 2009......................................................282

Figure 2.40.1. BOEM OCS Planning Areas and DoD OPAREAs 3 and Warning Areas.............................................283

Figure 2.40.2. BOEM OCS North Atlantic Planning Area and DoD OPAREAs 3 and Warning Areas. .....................284

Figure 2.40.3. BOEM OCS Mid-Atlantic Planning Area and DoD OPAREAs 3 and Warning Areas. ........................285

Figure 2.40.4. BOEM OCS South Atlantic Planning Area and DoD OPAREAs 3 and Warning Areas. .....................286

Figure 2.40.5. BOEM OCS Eastern Gulf of Mexico and Straits of Florida Planning Area and DoD OPAREAs 3 

and Warning Areas. ........................................................................................................................287
xx

LIST OF TABLES

Table. 2.8.1. Stranded Pygmy and Dwarf Sperm Whales by Species and Year ....................................................45

Table 2.9.1. Environmental Data for Ziphius spp.................................................................................................47

Table. 2.9.2. Cuvier’s Beaked Whale Strandings by Year and State .....................................................................48

Table 2.11.1. Environmental Data for Mesoplodon spp........................................................................................55

Table 2.11.1. Blainville’s Beaked Whale Strandings by Year and State.................................................................56

Table 2.11.2. Gervais’ Beaked Whale Strandings by Year and State.....................................................................57

Table 2.11.3. Sowerby’s Beaked Whale Strandings by Year and State .................................................................57

Table 2.11.4. True’s Beaked Whale Strandings by Year and State........................................................................57

Table 2.11.5. Unidentified Beaked Whale Strandings by Year and State..............................................................57

Table 2.13.1. Long-finned Pilot Whale Strandings by State and Year ...................................................................66

Table 2.13.2. Mean Annual Mortality of Undifferentiated Pilot Whales by Fishery 2005-2009 ............................68

Table 2.14.1. Short-finned Pilot Whale (SF) and Pilot Whale, Identified to Genus (spp), Strandings by State 

and Year............................................................................................................................................71

Table 2.14.2. Mean Annual Mortality of Undifferentiated Pilot Whales by Fishery 2004- 2008........................72

Table 2.18.1. Incidental White-sided Dolphin Mortality 2005-2009......................................................................85

Table 2.19.1. Fisheries Mortality of Risso’s Dolphins.............................................................................................89

Table 2.20.1. U.S. Atlantic Bottlenose Dolphin Population Estimates ...................................................................91

Table 2.20.2. Bottlenose Dolphin Strandings Potentially Attributed to a Stock by Year .......................................94

Table 2.20.3. Bottlenose Stocks for which Only Cumulative Data is Available ......................................................94

Table 2.20.4. Most Recent Reported/Estimated Incidental Mortality of Bottlenose Dolphins by Stock ...............98

Table 2.27.1. Fisheries Mortality of Common Dolphins.......................................................................................120

Table 2.29.1. Fisheries Mortality of Harbor Porpoise, 2005-2009 .......................................................................127

Table 2.31.1. Harbor Seal Strandings by State and Year ......................................................................................137

Table 2.31.2 Annual Estimated Fishery-related Mortality for Harbor Seals along the U.S. Atlantic coast, 

2005-2009.......................................................................................................................................140

Table 2.32.1. Harp Seal Strandings by State and Year..........................................................................................144

Table 2.32.2. Mean Annual Mortality by Fishery 2005-2009 ...............................................................................145

Table 2.33.1. Gray Seal Strandings by State and Year..........................................................................................150

Table 2.31.2. Annual Estimated Fishery-related Mortality for Gray Seals along the U.S. Atlantic Coast 

2005-2009.......................................................................................................................................152

Table 2.34.1 Hooded Seal Strandings by State and Year.....................................................................................155

Table 2.34.2. Mean Annual Mortality by Fishery 2001-2005 ...............................................................................156

Table 2.36.3. Green Turtle Nest Counts...............................................................................................................164
xxi

Table 2.38.1. Annual Loggerhead Nest Counts in Atlantic Florida by County......................................................177

Table 2.38.2. Life Stages of the Loggerhead Turtle ..............................................................................................181

Table 2.39.1. Annual Leatherback Nest Counts in Florida by County ..................................................................189

Table 2.39.13. Data Sources...................................................................................................................................204

Table 3.0. Current Research............................................................................................................................289
xxii

ACRONYMS AND ABBREVIATIONS

AEP Auditory evoked potentials

AMAPPS Atlantic Marine Assessment Program for Protected Species

ATBA Area to be avoided

BDE Bromodiphenyl

BOEM Bureau of Ocean Energy Management

BOEMRE Bureau of Ocean Management, Regulation and Enforcement 

BT Butyltin

Cd Cadmium

CETAP Cetacean and Turtle Assessment Program

CI Confidence interval

CITES Convention on International Trade in Endangered Species of Wild Fauna and 

Flora

Cu Copper

CV Coefficient of variation

DDD Dichlorodiphenyldichloroethane

DDE Dichlorodiphenyldichloroethylene

DDT Dichlorodiphenyltrichloroethane

DOD Department of Defense

DOI Department of the Interior

DTAG Digital acoustic recording tag

EEZ Exclusive Economic Zone

ESA Endangered Species Act

Fe Iron

HBCD Hexabromocyclododecane

HCB Hexachlorobenzene

HCH Hexachlorocyclohexane 

Hg Mercury

IA Interagency Agreement

ICES International Council for the Exploration of the Sea

IUCN International Union for Conservation of Nature

IWC International Whaling Commission

MMPA Marine Mammal Protection Act

Mn Manganese

mtDNA Mitochondrial DNA (deoxyribonucleic acid)

MW Megawatt

NAFO North Atlantic Fisheries Organization

NAO North Atlantic Oscillation

NEFSC Northeast Fisheries Science Center
xxiii

NEPA National Environmental Policy Act 

Ni Nickel

NMFS National Marine Fisheries Service

NOAA National Oceanographic and Atmospheric Administration

OBIS Ocean Biogeographic Information System

OC Organochlorine

OCS Outer Continental Shelf

Pb Lead

PBB Polybrominated biphenyl

PBDPE Polybrominated diphenyl ethers

PBR Potential biological removal

PCB Polychlorinated biphenyl

PDV Phocine distemper virus

PFC Perfluorinated compounds

PN2 Partial pressure nitrogen

POP Persistent organic pollutant

PSB Protected Species Branch (Northeast Fisheries Science Center)

SEFSC Southeast Fisheries Science Center

SST Sea surface temperature

TRT Take Reduction Team

UK United Kingdom

UME Unusual Mortality Event

UNCW University of North Carolina, Wilmington

Zn Zinc
1

1. INTRODUCTION

In September 2009, the Minerals Management Service (renamed the Bureau of Ocean Energy 

Management, Regulation, and Enforcement [BOEMRE] on 21 June 2010, now the Bureau of 

Ocean Energy Management [BOEM]), Department of the Interior (DOI) and the Northeast 

Fisheries Science Center (NEFSC), National Marine Fisheries Service (NMFS), National 

Oceanic and Atmospheric Administration (NOAA), U.S. Department of Commerce established 

an inter-agency agreement (IA), through which NOAA was to provide services to the DOI, 

BOEMRE (now BOEM) in the form of literature review of the research on marine mammals and 

sea turtles in the U.S. Atlantic from Maine to the Florida Keys.

1.1 PROJECTS GOALS AND OBJECTIVES

The goals and objectives of this IA were: 1) to provide a reference document that includes the 

latest and best information on marine mammals and sea turtles in the U.S. Atlantic from Maine 

to the Florida Keys, 2) to identify data gaps in the knowledge of marine mammals and sea turtles 

in the Atlantic, and 3) to identify research priorities recommended by national/regional agencies 

and groups (e.g., Marine Mammal Commission, NMFS and FWS recovery plans, Sea Turtle 

Expert Working Group,). This study area corresponds to BOEM north-Atlantic, mid-Atlantic, 

south-Atlantic and Straits of Florida outer continental shelf (OCS) planning areas. The document 

provides a basis for analysis of potential impacts of BOEM-regulated activities on protected sea 

turtles and marine mammals as required by the National Environmental Policy Act (NEPA), for 

petitioning that might be required by the Marine Mammal Protection Act (MMPA), and for 

Section 7 consultations under the Endangered Species Act (ESA). The document can also serve 

as a guide to future decisions on planning and funding of needed research on sea turtles and 

marine mammals in the U.S. Atlantic. 

Thirty-seven species of marine mammals seasonally occupy one or more of the BOEM OCS 

Planning Areas in U.S. Atlantic waters between the Florida Keys and Maine (Jefferson et al. 

1994; Waring et al. 2011). The marine mammal community is diverse. Three of the five 

commonly recognized marine mammal taxa reside in this region: cetaceans (mysticetes [baleen 

whales] and odontocetes [toothed whales, dolphins, and porpoises]), sirenians (manatees), and 

pinnipeds (seals). Although marine mammals are broadly distributed throughout this region, 

individual species exhibit preferences for certain ecosystems (Bowen and Siniff 1999) based on 

ecological and life history requirements. Baleen whales have the widest distribution and make 

the most extensive seasonal migrations of all marine mammals in this region (Waring et al. 

2011). For example, right (Eubalaena glacialis), humpback (Megaptera novaeangliae), fin 

(Balaenoptera physalus) and minke (B. acutorostrata) whales prefer continental shelf 

ecosystems, whereas blue (B. musculus), and sei (B. borealis), whales are associated with shelfedge and deeper oceanic water. Humpback whales migrate from high latitude summer feeding 

grounds (i.e., Gulf of Maine) to winter breeding grounds in the Caribbean Sea (Katona and Beard 

1990; Clapham 2000, 2009). Right whales exhibit a similar but less extensive migration; winter 

calving grounds are located in waters off the southeast U.S. coast (Kraus and Rolland 2007; 

Kenney 2009; Waring et al. 2011). 
2

Odontocetes also exhibit preferences for particular ecosystems (Bowen and Siniff 1999; Reeves 

et al. 2002; Macleod et al. 2006a) . Harbor porpoise (Phocoena phocoena), Atlantic white-sided 

dolphins (Lagenorhynchus acutus) and long-finned pilot whales (Globicephala melas) are 

usually found in cool-temperate continental shelf waters off the northeast U.S. (Waring et al. 

2011). Continental shelf break/pelagic species found in warm-temperate to cooler waters include 

bottlenose dolphins (Tursiops truncatus), short-beaked common dolphin (Delphinus delphis), 

Risso’s dolphin (Grampus griseus) striped dolphin (Stenella coeruleoalba), spotted dolphins (S. 

frontalis), sperm (Physeter macrocephalus), and northern bottlenose (Hyperoodon ampullatus) 

whales, and Cuvier’s (Ziphius caviorstris), Blainville’s (Mesoplodon densirostris), Sowerby’s 

(M. bidens), True’s (M. mirus) beaked whales (Waring et al. 2011). Continental shelf 

break/pelagic species found in warm-temperate to tropical waters are pantropical spotted 

(Stenella attenuata), spinner (S. longirostris), Clymene (S. clymene), rough-toothed (Steno 

bredanensis), and Fraser’s (Lagenodelphis hosei) dolphins, and melon-headed (Peponocephala 

electra), pygmy killer (Feresa attenuata), short-finned pilot (G. macrorhynchus), pygmy sperm 

(Kogia breviceps), dwarf sperm (K. sima) and Gervais’ beaked (M. europaeus) whales. Within 

the odontocetes, only sperm and long-finned pilot whales are known to undergo long-range 

seasonal migrations (Bowen and Siniff 1999; Waring et al. 2011). 

The four species of seals found in this area—harbor (Phoca concolor vitulina), gray 

(Halichoerus grypus grypus), harp (Pagophilus groenlandicus) and hooded (Cystophora 

cristata)—are primarily distributed in cool temperate waters off the northeast U.S. (New Jersey 

to Maine). Harp and hooded “ice seals” are transient in U.S. Atlantic waters. Stranding records 

extend as far south as Florida for all species, with most occurring in the North Atlantic Planning 

Area (Waring et al. 2011). 

The Florida manatee (Trichechus manatus latirostris) is found in Atlantic coastal waters along 

the southeastern U.S., but extralimital movements northward have been recorded (Reynolds III 

and Wilcox 1994; Wright et al. 2002; Runge et al. 2007; FWS 2009).

Most marine mammal species in U.S. Atlantic waters are assumed to be trans-boundary stocks. 

Stock structure for most cetaceans is unknown, although significant progress has been made for 

North Atlantic right and humpback whales, bottlenose dolphins, and harbor porpoise (Waring et 

al. 2011). Harp and hooded seals found in U.S. waters are from Atlantic Canada breeding 

stocks, whereas gray seals from Atlantic Canada began recolonizing New England waters in the 

late 20th Century (Wood LaFond 2009). The putative stock structure for harbor seals spans the 

region between New England and the Canadian maritime providences of New Brunswick and 

southwest Nova Scotia (Stanley et al. 1996). 

Marine mammal seasonal distribution and habitat use is closely associated with their prey and 

foraging ecology (Bowen and Siniff 1999). While cetaceans may occupy feeding areas for 

extended time periods (i.e., spring occurrence of right whales in the Great South Channel), 

pinnipeds forage both “locally” and at significant distances from haul-out sites.

Abundance estimates vary widely among the species, ranging from a few hundred (e.g., right 

whales) to around a hundred thousand (e.g., common dolphins). Based upon these estimates, the 

annual number of human-caused mortalities that can be sustained by the stocks without 
3

threatening its recovery (i.e. Potential Biological Removal or PBR) range from less than 1 (e.g., 

right whales) to 120,000 (common dolphins) (Waring et al. 2011).

Five species of sea turtles seasonally occupy one or more of the BOEM OCS Planning Areas in 

U.S. Atlantic waters between the Florida Keys and Maine. These species are protected under the 

Endangered Species Act of 1973. Although sea turtles live most of their lives in the ocean, adult 

females must return to beaches on land to lay their eggs. They often migrate long distances 

between foraging grounds and nesting beaches. 

Kemp's ridleys (Lepidochelys kempii) are distributed throughout the Gulf of Mexico and U.S. 

Atlantic seaboard, from Florida to New England. Major nesting occurs in the Gulf of Mexico, 

but occasional nesting has been documented in North Carolina, South Carolina, and the Gulf and 

Atlantic coasts of Florida. The green turtle (Chelonia mydas) is globally distributed and 

generally found in tropical and subtropical waters along continental coasts and islands between 

30° North and 30° South. In U.S. Atlantic and Gulf of Mexico waters, green turtles are found in 

inshore and nearshore waters from Texas to Massachusetts, the U.S. Virgin Islands, and Puerto 

Rico. Hawksbill turtles (Eretmochelys imbricatea) are circumtropical, usually occurring from 

30° N to 30° S latitude in the Atlantic, Pacific, and Indian Oceans and associated bodies of 

water. Within the U.S., hawksbills are most common in Puerto Rico and its associated islands 

and in the U.S. Virgin Islands. In the continental U.S., the species is recorded from all the Gulf 

States and along the east coast as far north as Massachusetts, but sightings north of Florida are 

rare. Loggerhead turtles (Caretta caretta) are circumglobal, occurring throughout the temperate 

and tropical regions of the Atlantic, Pacific, and Indian Oceans. Loggerheads are the most 

abundant species of sea turtle found in U.S. coastal waters. In the Atlantic, the loggerhead turtle's 

range extends from Newfoundland to as far south as Argentina. During the summer, nesting 

occurs primarily in the subtropics. Although the major nesting concentrations in the U.S. are 

found from North Carolina through southwest Florida, minimal nesting occurs outside of this 

range westward to Texas and northward to southern Virginia. Leatherback turtle (Dermochelys 

coriacea) nesting grounds are located around the world, with the largest remaining nesting 

assemblages found on the coasts of northern South America and West Africa. The U.S. 

Caribbean, primarily Puerto Rico and the U.S. Virgin Islands, and southeast Florida support 

minor nesting colonies, but represent the most significant nesting activity within the United 

States. Adult leatherbacks are capable of tolerating a wide range of water temperatures, and have 

been sighted along the entire continental coast of the United States as far north as the Gulf of 

Maine and south to Puerto Rico, the U.S. Virgin Islands, and into the Gulf of Mexico.

Centuries of human activities have affected all North Atlantic marine mammal and sea turtle 

populations (Waring et al. 2011; ). Although commercial harvesting ended decades ago, marine 

mammals and sea turtles in U.S. Atlantic waters are still affected by a variety of anthropogenic 

activities including: fishery bycatch, vessel strikes, acoustic activities, military activities, and 

energy production (Simmonds and Lopez-Jurado 1991; Croll et al. 2001; Laist et al. 2001; 

Lewison et al. 2004; Cox et al. 2006; Madsen et al. 2006a; Read et al. 2006; Merrick and Cole 

2007; Vanderlaan and Taggart 2007; Waring et al. 2011). 
4

1.2 REPORT ORGANIZATION

This report consists of four sections, including the introduction. Section two includes thirty-four 

(thirty-two species and two taxonomic groups) marine mammal and five sea turtle species 

summaries, representing all marine mammal and sea turtle species that occur in the BOEM 

Atlantic Planning Areas. The information presented here came from primary literature, NMFS 

stock assessment reports, species recovery plans and websites. The reports include information 

of the status, distribution, abundance, habitat preference, stock structure, life history traits, food 

habits, health (strandings, contaminants, disease), acoustics, fisheries interactions, vessel 

interactions, energy projects and data gaps and research recommendations. These summaries are

meant to be comprehensive and current; therefore, they include information on these species 

from other parts of their range.

Section two also includes a collection of maps. These include sighting, stranding, tag, and 

fishery bycatch locations by species and well as other relevant information such as fishery 

management areas designated under the harbor porpoise regulations, and right whale critical 

habitat areas. Seasonal information is also presented. Sightings maps are not effort-corrected 

and as such should not be interpreted as complete representations of species distribution. A table 

of data sources utilized to create these maps is provided.

The third section of this report is a table identifying current marine mammal and sea turtle 

research occurring along the U.S. Atlantic Coast. This table was compiled from the abstracts of 

research presented at three important scientific conferences: The 18th Biennial Conference on 

the Biology of Marine Mammals, Quebec City, Canada (12-16 October 2009); the Annual 

Meeting of the Right Whale Consortium Meeting, New Bedford, Massachusetts, (3-4 November 

2010); and the 31st Annual Symposium on Sea Turtle Biology and Conservation, San Diego, 

California (12-15 April 2011). The table includes research occurring in the BOEM Atlantic 

Planning Areas and contact information for the lead author.

The final section is a comprehensive bibliography of the literature included throughout the 

document. PDFs of open access literature have been compiled separately on a CD for BOEM.
5

2. SPECIES SUMMARIES

2.1 NORTH ATLANTIC RIGHT WHALE (EUBALAENA GLACIALIS)

2.1.1 Legal Status

The first legal protection of right whales, the 1931 Convention for the Regulation of Whaling, 

was put into effect in 1935 and was followed by the International Convention for the Regulation 

of Whaling in 1949. In the U.S., the right whale has been listed as endangered under the ESA 

(and its precursor) since 1970. The species is designated as depleted under the MMPA. In 2008, 

NMFS listed the northern right whale (Eubalaena spp.) as two separate, endangered species: the 

North Pacific right whale (E. japonica) and North Atlantic right whale (E. glacialis). 

Critical habitat for the North Atlantic right whale was designated in 1994 (see Figure 3.1-2), and 

is currently under revision. Shipping regulations protecting the right whale were enacted in 

2009, and the North-South lanes of the Boston Traffic Separation Scheme (TSS) were modified 

to reduce the interactions of vessels with whales. In 2009, a voluntary seasonal Area to be 

Avoided (ATBA) was also established from 1 April to 31 July for ships weighing more than 300 

gross tons. Furthermore, since 2006, recommended routes were established in key right whale 

habitats in Florida, Georgia, and Massachusetts. In addition to vessel rerouting, speed restrictions 

are mandated, and vessels measuring at least 65 feet in length are required to travel at 10 knots or 

less in certain locations at certain times of the year (http://www.nmfs.noaa.gov/pr/shipstrike/). 

To address fishing gear entanglement, under the auspice of the Atlantic Large Whale Take 

Reduction Team, NMFS published three rules in 2002 (parts of which have since been modified) 

directed at: seasonally closing certain areas to fishing, requiring sinking groundline at certain 

times, and requiring all buoys to have a weak link (http://www.nero.noaa.gov/whaletrp/). Despite 

initial resistance from fishermen, the team continues to push forward their efforts in hopes of

reducing injuries to and deaths of large whales due to incidental entanglement in fishing gear. 

2.1.2 General Distribution

The North Atlantic right whale is found seasonally in both coastal and shelf waters of the U.S. 

Atlantic coast. Individuals in the population range between winter calving and nursery grounds 

located off the coasts of Florida and Georgia (in the BOEM South Atlantic Planning Area) and 

summer feeding grounds from New England (BOEM North Atlantic Planning Area) to the Bay 

of Fundy and Scotian Shelf (National Marine Fisheries Service 2005). Longer distance 

movements are also reported (Knowlton et al. 1992), and the winter location of much of the 

population is unknown, so offshore distribution is uncertain (National Marine Fisheries Service 

2005). Sighting and stranding locations of North Atlantic right whales are shown in Figure 2.1-

1.

Patterns of occurrence and distribution of right whales have been studied using both aerial and 

shipboard surveys. Most of the population spends the spring and summer on feeding grounds off 

the northeastern U.S. and Nova Scotia (Kenney et al. 2001; Winn et al. 1986). In late fall, nearterm females migrate to waters off the southeastern U.S. to give birth (Kraus et al. 1986).
6

2.1.3 General Abundance

An extensive photo-ID recapture database for the North Atlantic right whale (Hamilton et al. 

2007) allows a near census of individual whales to be accumulated. The minimum population 

index (Minimum Number Alive or MNA), based on a review of the photo-ID recapture database 

as it existed on 6 July 2010, was 396 individually recognized whales known to be alive during 

2007 (Waring et al. 2011). Mean growth rates of the MNA indices over the period 1990-2007

was 2.4% (Waring et al. 2011), which should mimic the population growth rate but is slightly 

biased high because the index does not include all whales. 

An analysis of extinction time by Fujiwara and Caswell (2001) demonstrated that preventing the 

deaths of only two female right whales per year could increase the population growth rate to 

replacement level. This has recently been refuted in an updated analysis available from NEFSC 

(Pace, personal communication). 

2.1.4 Habitat Preference

Brown and Winn (1989) examined patterns of right whale sighting in the Great South Channel 

feeding grounds and found that the distribution of sightings correlated with the 100-m isobath 

and with the thermal front. Using satellite telemetry on tagged whales, Baumgartner and Mate 

(2005) examined the summer and fall habitat of North Atlantic right whales in the Grand Manan 

Basin of the lower Bay of Fundy. Whale distribution and movements were correlated with 

environmental conditions such as depth, chlorophyll concentration, sea surface temperature and 

other hydrological variables. Whales that left the Bay of Fundy were found to visit areas 

characterized by low bottom water temperatures, high surface salinity, and high surface 

stratification and no correlation was found between whale distribution and oceanic fronts or 

areas with high phytoplankton concentrations. Whether or not it is frontal conditions that 

aggregate the copepods, right whale abundance and distribution on the feeding grounds is linked 

with copepod concentrations (Wishner et al. 1995; Pendleton et al. 2009; Pendleton 2010; 

Michaud and Taggart 2007). Michaud and Taggert (2007) estimated, based on energy density of 

available food in the Grand Manan feeding habitat at times when whales were present, that a 

minimum water column-integrated energy density of 3 kJ/m3 could define a right whale feeding 

habitat. The absence of right whales from the Roseway Basin feeding ground between 1993 and 

1999 was linked to the near absence of their prey species during that period (Patrician and 

Kenney 2010). Models have been developed that predict the developmental and reproductive 

rates of Calanus finmarchicus based on satellite-based measurements of sea surface temperature 

and chlorophyll and, from those, predict the arrival and abundance of right whales on their 

feeding grounds (Pershing et al. 2009; Record et al. 2008). 

Right whale northerly migration patterns along the U.S. mid-Atlantic coast were modeled by 

Firestone et al. (2008). Regression analysis suggested an early to mid-March departure from 

Jacksonville, Florida, with a 30 day departure range, travel times of 21-24 days to the tip of Long 

Island, at a mean travel rate of 1.5-1.7 knots (2.8-3.1 km/h). Right whale habitat use in its 

migratory corridor is discussed by Schick et al (2009). These authors found that the range of 

habitat suitable for right whales exceeds previous estimates and argue for increased speed 

restriction buffer zones to protect more habitat.
7

Sighting distribution in the southeast U.S. right whale calving habitat was overlapped with sea 

surface temperatures by Keller et al. (2006a). Results suggested that the warm Gulf Stream 

waters may represent a thermal limit for right whales and within the area westward of the Gulf 

Stream, sea surface temperature (SST) greatly influenced whale distribution. Garrison (2007a)

applied a similar analysis using bathymetry, modeled average wind data, and several spatial 

variables as well as satellite-derived sea surface temperature in a Generalized Additive Modeling 

approach. Peak sighting rates were found to occur at water depths between 10 and 20 m and 

temperatures between 13 and 15°C. 

North Atlantic right whale habitat is likely vulnerable to climate change. Climate-driven 

changes in North Atlantic circulation patterns affect the composition and relative abundance of 

plankton in the feeding grounds of the Gulf of Maine and Western Scotian Shelf (Greene et al. 

2003). Because calving rates appear grossly associated with food availability (Greene et al. 

2003), climate change and circulation pattern fluctuations may be key factors in the reproductive 

success of the North Atlantic right whale population. Calving success was compared with 

indices of three major currents in the North Atlantic: the North Atlantic Oscillation, the Gulf 

Stream and the Southern Oscillation; the conclusion was that all three atmospheric cycles can be 

correlated with right whale reproduction rates (Kenney 2007).

2.1.5 Stock Structure

The split of Eubalaena into three species is supported by genetic work done by Rosenbaum et al. 

(2000) and by Gaines et al. (2005). Although genetic variability is low in the North Atlantic 

population, bottleneck analyses suggest that the primary loss of genetic diversity did not occur 

during the most recent population decline attributed to whaling during the 18th through the 20th

centuries (Waldick et al. 2002). Microsatellite genetic analysis performed on the single right 

whale specimen found at Red Bay, Labrador, a 16th and 17th century Basque whaling site, 

supported the finding that low levels of right whale genetic diversity pre-date human exploitation 

(McLeod 2008; McLeod et al. 2010). Lower levels of genetic diversity were found in North 

Atlantic right whales compared with South Atlantic right whales (Eubalaena australis), and the 

divergence between the two species likely happened between 3 and 5 million years ago (Malik et 

al. 2000). Malik et al. (1999) identified five mitochondrial control region haplotypes in the 

North Atlantic right whale with significant genetic structuring. Using mtDNA analysis, Schaeff 

et al. (1992), suggested a division of the right whale population into two subgroups, defined by 

their use the Bay of Fundy as a nursery area. One of three mtDNA composite restriction morphs 

determined for 150 animals was not found in reproductive females which brought calves to the 

Bay of Fundy. Mcleod and White (2010) demonstrated evidence of heteroplasmy in the 

population resulting in a sixth haplotype. 

2.1.6 Life History Traits

Kraus et al. (2001) assessed North Atlantic right whale reproductive parameters for the period 

1980 through 1998. The number of calves expressed as a proportion of the total estimated 

population was estimated to be between 0.36 and 0.49, and the mean value for calves per mature 

female per year was 0.25. The mean age at first calving was 9.53 years, and the mean number of 

females recruited annually was 3.8. Calving intervals were found to have increased over the 

period, and calves per female decreased. In a more recent analysis, reproductive histories of 
8

whales in the right whale catalogue cover periods of up to 31 years and calving intervals seem to 

have decreased since the earlier report (Kraus et al. 2007).

Frasier et al. (2007) assessed male reproductive success in the North Atlantic right whale 

population. An uneven distribution of paternities was found, resulting in a reduced effective 

population size. There was a significant bias towards older males among assigned fathers, with 

average age at first paternity of approximately 15 years, an indication that mate competition 

could be preventing younger males from reproducing. 

Right whale calf and perinatal mortality was examined by Browning et al. (2010). In the period 

between 1989 and 2003, 17 calves from 208 calving events were documented or presumed dead 

due to serious injury or disappearance from the sighting record. An additional 28 potential 

perinatal losses were presumed when female right whales were seen on the calving grounds 

without a calf.

Hlista et al. (2009) found a significant correlation between the number of right whale calves born 

and sea surface chlorophyll concentration averaged over the prior 2 years, supporting the idea 

that food availability during and just before the gestation period may be an important factor in 

the regulation of reproductive success. Calving intervals have varied from 3.5 years in 1990 to 

over 5 years between 1998 and 2003, and to just over 3 years in 2004 and 2005 (Kraus et al. 

2007). 

Analysis of fecal hormone metabolite levels has been demonstrated to be useful in determination 

of gender, detection of pregnancy and lactation, and in assessing age at sexual maturity (Rolland 

et al. 2007, 2005). Hunt et al. (2006) examined fecal glucocorticoids and concluded that such 

analysis could be a useful measure of adrenal activity and reproductive condition. Mating 

behavior was studied by Kraus and Hatch (2001). Most mating groups observed were composed 

of a single female and multiple, competing males. 

Although work by Knowlton et al. (1994) indicated a slow rate of population recovery (ratio of 

first-year calves to the total non-calf population was estimated at 4.5%, population growth rate at 

2.5% and mortality rate at 2.0% for the period 1980-1992), survival probability estimated by 

Caswell et al. (1999), showed that the population could face extinction within 191 years. 

Decreasing crude survival and decreasing reproductive rates were reported for the period 1980-

1994. A workshop which focused on the causes of reproductive failure was convened in 2000 in 

Falmouth, Massachusetts (Reeves et al. 2001). The workshop concluded that if calf production 

and recruitment did not recover from the current levels, the population would be unlikely to 

recover. More recent calculations (Waring et al. 2011), suggest a positive trend, with a mean 

growth rate of 2.4%. A conservatively constructed population viability analysis (PVA) based on 

updated reproductive rates and survival estimates found none of 1000 simulated projected 

populations to end with a lower population than it began, strongly refuting the Fugiwara and 

Caswell (2001) analysis (Pace, personal communication).

2.1.7 Food Habits

The small-scale abundance of copepods near feeding right whales in the Great South Channel

was measured by Beardsley et al. (1996). The whales were feeding on the copepod species 
9

Calanus finmarchicus which was most abundant in the upper 10-20 m of the water column at 

concentrations measuring up to 3.3 x105 copepods per cubic meter. Total water column copepod 

biomass and Calanus biomass, measured by plankton tows at sites near feeding right whales, did 

not always differ from sites with no whales, but higher densities and relative proportions of older 

copepod lifestages were found close to right whales, leading researchers to suggest that the right 

whales were seeking out aggregations of older copepod lifestages (Wishner et al. 1995). The 

relationship between right whale sighting rates and late-stage Calanus was further explored by 

Baumgartner et al. (2003), who looked at the diel and tidal time-scale cycles of plankton 

availability. Baumgartner et al. (2011) investigated the effects of the diel vertical migration of C. 

finmarchicus on the occurrence of North Atlantic right whales and sei whales during spring in 

the southwestern Gulf of Maine. They found occurrence of right whales to be unrelated to 

variability in the migration behavior of C. finmarchicus. Dive patterns, however, measured by 

Winn et al. (1995) in a tagging study performed on right whales in the Great South Channel in 

1988 and 1989, showed that the whales’ diving behavior was closely correlated with the 

horizontal and vertical movements of the zooplankton on which they were feeding. Mayo and 

Marx (1990) observed that right whale surface feeding was rarely observed in Cape Cod Bay 

when zooplankton densities were less than 1,000 organisms/ m3

. Ingestion and defecation 

models were used to estimate that on average, a right whale ingests approximately 58,000 grams 

of wax ester lipids per day and defecates only 250 g of the wax esters, a rate of metabolism 

unusual for mammalian species (Swaim et al. 2009). 

Kenney et al. (2001) proposed a conceptual model of right whale migratory and foraging 

strategies at varying scales, and presented a variety of speculations concerning the mechanisms 

involved. Pendleton et al. (2009) used aerial sighting data of right whales and measurements of 

copepod concentrations from vessel-based oceanographic sampling in Cape Cod Bay and the 

Great South Channel to conclude that regional-scale average copepod concentration is a good 

indicator of right whale presence in both habitats, with C. finmarchicus playing the most 

important role in the Great South Channel and other copepods being important in Cape Cod Bay.

Particle transport and retention patterns in Cape Cod Bay, affected by the coastal current and 

prevailing winds, have significant correlation with C. finmarchicus abundance and thus with 

right whale sightings (Jiang et al. 2007). As mentioned above, the absence of right whales from 

the Roseway Basin, off southeastern Nova Scotia, for the period 1993-1999 can be tied to low 

abundance of C. finmarchicus during that time (Patrician and Kenney 2010).

Diving profiles of feeding right whales in the Great South Channel showed whales regularly 

dove steeply to a depth between 80 and 175 m, and then held that depth for 5 to 14 minutes 

before resurfacing (Baumgartner and Mate 2003). The average depth of dive was strongly 

correlated with the densest concentrations C. finmarchicus and with the average depth of the 

bottom mixed layer’s upper surface. Right whale dives were classified into three dive shape 

groups by Nowacek (2008); one type was apparently a feeding behavior, another type was not 

associated with foraging, and a third was associated with low-quality foraging where animals 

may be searching for new prey aggregations. 

Lysiak et al. (2008) examined long term trends in right whale migration behavior, health, and 

diet as expressed by incremental stable isotope ratios from 25 right whale baleen plates. The 

baleen was found not only to be a record of whale distribution, but also potentially useful for 
10

documenting ecosystem-level environmental changes. Variation in isotopic composition 

between individual right whales suggests differential habitat use, and may point to the use of 

alternative summer feeding grounds such as the Labrador Sea (Summers et al. 2006). 

2.1.8 Health

2.1.8.1 Strandings

Between 1970 and 2001, 54 right whale mortalities were reported between Florida and the 

Canadian Maritimes (Moore et al. 2005). Of those 54 whales, 30 (18 adults and juveniles and 12 

calves) were examined. Trauma presumed to be a result of vessel collision was a significant 

finding in 10 cases, and cause of death as a result of fishery entanglements was identified in 4 

cases. The proportion of mortalities that are detected is unknown. Twenty confirmed North 

Atlantic right whale mortalities were reported in the mortality and serious injury report for the 

period 2005-2009 (Henry et al. 2011). This figure includes anthropogenic and nonanthropogenic mortalities.

2.1.8.2 Contaminants

North Atlantic right whale fecal samples and zooplankton prey from the area where the whales 

were feeding have been examined for paralytic shellfish poisoning toxins (Doucette et al. 2006; 

Durbin et al. 2002). Discovery of these toxins in both feed and feces suggested that trophic 

transfer of marine algal toxins could be a contributing factor in the right whale populations’ 

failure to recover. The occurrence of marine biotoxin domoic acid was also assessed in right 

whale fecal samples and zooplankton prey (Leandro et al. 2010). Exposure to the biotoxin was 

confirmed, though concentrations measured in feces and estimated ingestion levels were lower 

than published levels for other marine mammals.

Right whale skin biopsy tissue samples were tested for exposure to chromium (Chen et al. 2009; 

Wise et al. 2008). Chromium accumulations were found in mean concentrations of 7.1 μg/g and 

proved to be both cytotoxic and genotoxic to North Atlantic right whale cells. 

Brominated flame retardants and organochlorine contaminants in right whale blubber samples 

were analyzed by Montie et al. (2010). Of the organochlorine pesticides present in the right 

whales, c-hexachlorocyclohexane was found at the highest concentration, while Dieldrin, bis(pchlorophenyl)-1,1-dichloroethane (p,p′-DDE), and bis(p-chlorophenyl)-1,1,1-trichloroethane 

(p,p′-DDT) were found at lower concentrations. Of the polybrominated diphenyl ethers

measured in right whales, BDE (bromodiphenyl ether) 47 was found at the highest concentration. 

In the five right whales tested, 2,3,4,5,6-pentabromoethylbenzene (PBEB) was detected in four, 

hexabromobenzene (HBB) was detected in two, and pentabromotoluene (PBT) in four.

Organochlorines in North Atlantic right whale skin, feces, and prey were measured by Weisbrod 

et al (2000). Concentrations of 30 PCBs (polychlorinated biphenyl) and 20 pesticides in skin 

biopsies were consistent with other balenopterids. Patterns of contaminant burdens in blubber 

indicated that ingestion of different prey or prey from different areas and the release of stored 

organochlorines during lipid depletion in winter can cause the contaminant load to change 

annually. 
11

Klansjcek et al. (2007) developed a dynamic energy budget model for marine mammals to 

demonstrate the relationships between energy intake and energetics and pharmacokinetics of 

environmental toxins. Using model parameters for the right whale, energy assimilation estimates 

were developed and the influences of energy availability on reproduction elucidated.

2.1.8.3 Disease

Fecal samples from 49 North Atlantic right whales were analyzed for Cryptosporidium spp. and 

Giardia spp. by Hughes-Hanks et al. (2005). Prevalence of Cryptosporidium was found to be

24.5% and prevalence of Giardia to be 71.4%. Techniques for making health assessments from 

photographs of right whales have been developed (Pettis et al. 2004). Photographic evidence of 

skin lesions on right whales was examined by Hamilton and Marx (2005). Two main types of 

lesions were identified: white lesions and blister lesions. The white lesions were detected 

primarily in the Bay of Fundy and peaked in occurrence in the late 1990s. Blister lesions appear 

to be a more chronic condition affecting a small percent of the population. The parasitic sea 

lamprey Petromyzon marinus is known to use right whales as hosts, with 35 photo-documented 

cases reported in the Bay of Fundy and Cape Cod Bay (Nichols and Hamilton 2004). It is not 

known what effect lamprey attachment has on right whales. 

2.1.9 Acoustics

Morphometric analyses of inner ears from 13 stranded North Atlantic right whales were used for 

the development of a model of the frequency range of hearing this species (Parks et al. 2007).

Sound production on surface active groups of North Atlantic right whales was studied by Parks 

and Tyack (2005). The most common call recorded during this behavior was the scream call 

produced by the focal female. Other sounds recorded included gunshot and upcalls produced by 

males in the groups, and warble calls produced by female calves. Rates of right whale 

vocalizations from recordings made in 1999 and 2000 in the Great South Channel in spring and 

in the Bay of Fundy in summer were analyzed by Matthews et al. (2001). Calls of the moan type 

were correlated with whale group size and proximity to the surface. Autonomous hydrophone

arrays collected right whale acoustical data from the Scotian Shelf from July 2004 to August 

2005 (Mellinger et al. 2007). These data demonstrated seasonal and diel patterns of right whale 

calling activity, with most calls recorded in June through December. 

The autonomous moored buoy acoustic array system for automatic detection of right whale calls 

is described in Spaulding et al. (2009). The system continuously monitors the shipping lanes off 

Boston to meet ship strike mitigation requirements.

Ambient noise levels and right whale upcall parameters were measured in three right whale 

habitat areas by Parks et al. (2009). Call parameters varied between habitats and between years 

within the same habitat area. However, there was evidence that right whales may be responding 

to noise frequencies in their environment, rather than overall levels. Increases in call amplitude 

by individual right whales was documented during periods of increased background noise (Parks 

et al. 2010), as were higher average frequencies and lower rates of call behavior (Parks et al. 

2008). Brito et al. (2008), however, did not find increases in either vocal intensity or frequency 

shifts in North Atlantic right whale response to acoustic masking. A functional definition of 

communication masking and a metric to quantify its potential effects on marine mammals was 
12

presented by Clark et al. (2009). Spatial, spectral, and temporal maps of potential 

communication space were calculated for singing fin, singing humpback, and calling right 

whales. Communication masking by ship noise was found to be more severe for calling right 

whales.

Distortion of right whale acoustic signals by the shallow water environment of Cape Cod Bay 

was examined by Mohammed et al. (2008). Techniques for detecting right whale calls in the 

presence of ambient noise are discussed by Urazghildiiev (2009). Nonlinearities, including 

subharmonics, deterministic chaos, biphonation, and frequency jumps were analyzed in right 

whale and killer whale vocalizations by Tyson et al. (2007). The deterministic chaos type of 

nonlinear phenomena was detected in 87% of the Digital Acoustic Recording Tag (DTag)

recordings of right whales in the Bay of Fundy analyzed in the study. 

Visual aerial survey right whale sightings data were compared with acoustic detection data in 

Cape Cod Bay, Massachusetts (Clark et al. 2010). It was found that aerial surveys saw whales 

on only two-thirds of the days during which whales were detected acoustically. 

2.1.10 Fisheries By-catch and Entanglement 

Though ship strikes are more often immediately fatal, mortality by entanglement in fishing gear 

is a pervasive problem for many species of whales, and is less likely to be detected and reported, 

so estimations of fishery mortality based on observed mortalities are likely underestimations 

(Knowlton and Kraus 2001). Photographic analysis reveals that over 75% of well-photographed 

whales display entanglement scarring (Knowlton et al. 2005).

Pot and gillnet gear have been identified as the most common gear types involved in interactions 

with North Atlantic right whales (Johnson et al. 2005). Lobster trawl groundlines have been 

regulated for the protection of right whales since 1997. As of 1997, sinking groundlines were 

required in critical habitat areas between January and mid-May. In 2003, this restriction was 

imposed year-round in Cape Cod Bay critical habitat. In 2004, the restriction was extended to all 

waters west of the Cape Cod Bay Critical Habitat and south to 42°5 ́. Lobster pot groundlines in 

the Bay of Fundy were found to be generally lower than the 3 m elevation which has been 

hypothesized to be a threat to right whales (Brilliant and Trippel 2009). The pot fishery for black 

sea bass (Centropristis striata) has been shown to overlap in time and space with southeastern 

calving grounds (Levesque 2009a). Gillnet fishing was prohibited in the U.S. Southeast during 

the right whale calving season after the entanglement and death of a right whale calf in 2006 

(Levesque 2009b).

2.1.11 Vessel Interactions 

The slow-moving, surface-feeding and coastal habits of the right whale make it especially 

susceptible to threats from vessel traffic. Vessel traffic patterns within right whale habitat were 

characterized by Ward-Geiger et al. (2005). The authors found that 69% of vessel tracks in the

Northeast transited right whale critical habitat and all but two vessel tracks in the Southeast 

transited critical habitat. High-use ship traffic corridors were also identified. The co-occurrence 

of whales and vessels in the southeastern U.S. right whale wintering habitat was modeled by 

Fonnesbeck et al. (2008), with estimates of risk associated with several hypothetical alternative 

shipping routes.
13

Threats and risks to right whales from vessel strikes and fishing gear have been modeled and 

quantified (Nichols and Kite-Powell 2005; Kite-Powell et al. 2007; Vanderlaan et al. 2009; 

2010). Calculations that probability of ship strike lethality can drop to below 0.5% at vessel 

speeds below 12 knots, but increases to 100% when speeds are above 15 knots, contributed to the 

design and implementation of speed rule amendments in Canada. 

To help protect right whales from vessel collisions, several regulatory measures have been 

enacted along the U.S. Atlantic seaboard. In 2006, NOAA established a set of recommended 

vessel routes through right whale habitat in Florida, Georgia, and Massachusetts. Seasonal 

management areas were established by NMFS in 2008 (73 Federal Register 60173, October 

2008; Merrick 2005; Silber and Bettridge 2010). Under seasonal management area regulations, 

vessels 65 feet or longer must reduce their speed to 10 knots or less within these designated 

areas. On June 1, 2009, the north-south lanes of the Boston Traffic Separation Scheme were 

narrowed from 2 miles each to 1.5 miles each. It had been calculated that such a narrowing 

could reduce the shipping risk to right whales by 11% (Merrick and Cole 2007). Compliance 

rates with voluntary and mandatory speed restrictions in the southeast U.S. right whale critical 

habitat were measured by Lagueux et al. (2011), who found compliance rates on the mandatory 

measures to average 75% and on the voluntary restrictions to average 16%.

NMFS and other Federal and State agencies conduct extensive aerial surveys for right whales 

and issue alerts to mariners when right whales are spotted. Mandatory ship reporting systems 

have also been enacted, whereby ships over 300 gross tons are required to report to a shore 

station when they enter right whale habitats in the Southeast and in New England (Bettridge and 

Silber 2008). 

In Jensen and Silber’s database of large whale ship strikes worldwide in the period 1975 to 2002, 

there are 38 records of strikes involving North Atlantic right whales (Jensen and Silber 2003). 

Ten North Atlantic right whales are reported in NMFS records for the period 2004 through 2008 

with sufficient information to confirm the cause of death as collisions with vessels (Glass et al. 

2010). The resulting annual rate of serious injury or mortality was 2.0 right whales from vessel 

collisions. 

2.1.12 Energy Projects 

Both extractive and renewable offshore energy projects have the potential to impact the marine 

environment in a variety of ways, including habitat alteration and the introduction of noise by

seismic exploration activities (e.g., airguns), vessel/aircraft activity, construction and operation

(Geraci and St. Aubin 1980, Bain and Williams 2006, Thompsen et al. 2006, Cada et al. 2007, 

Compton 2008, Evans 2008, MMS 2008, Burgman 2010, Boehlert and Gill 2010, Dolman and 

Simmonds 2010, Edrén et al. 2010, Bush 2011, ICES 2011). The impact of these activities on 

marine mammals is unclear. Low levels of localized avoidance have been observed in 

mysticetes exposed to seismic airgun noise in the UK and adjacent waters investigated 1997-

2000 (Stone 2003; Stone and Tasker 2006). Work by McCauley et al. 2000 indicated that 

displacement of baleen whales by seismic activity could have serious effects on the animals and 

populations. Baleen whale reactions to low-frequency noise were also investigated by Croll et 
14

al. (2001), who found no obvious responses at the spatial and temporal scales examined, but 

cautioned that cumulative effects may be detrimental. 

Shipping activities connected with energy projects increase risks to whales in the area, 

particularly to the strike-prone right whale. In a requirement to fulfill permitting requirements 

for the Northeast Gateway, a liquefied natural gas offloading facility, Excelerate Energy has 

been working with EOM Offshore to maintain a fleet of acoustic moorings near the Boston 

shipping lanes (http://www.eomoffshore.com/excelerate.php). These moorings continuously 

detect right whale sounds and have the capability to transmit data in real time directly to shore. 

Back on shore, at Cornell University, the clips are then confirmed and the Coast Guard is 

informed to make any necessary changes to shipping traffic and/or speed in hopes of reducing 

ship-whale collisions. 

2.1.13 Data Gaps and Research Recommendations 

Despite years of intensive study and many large-scaled survey efforts, there are modest gaps in 

our knowledge of North Atlantic right whale seasonal distribution. Variation by individual 

whales is quite high in the use patterns of the five best known habitats (southeastern U.S., Cape 

Cod Bay, Great South Channel/northern edge Georges Bank, Roseway Basin and the Bay of 

Fundy). Some reproductive females have been seen only in the southeastern U.S. or the 

southeast and the Great South Channel, so their principal summer and fall feeding grounds are 

unknown. Cause-specific mortality for large whales may be largely unknowable from the 

current survey approaches; however, estimating the fraction of the North Atlantic right whale 

population that annually succumbs to ship strike and entanglement-related mortality is of great 

importance, because a considerable U.S. government and private investment go into the 

reduction of these factors of unknown scale.

Research priorities identified in the right whale recovery plan (National Marine Fisheries Service 

2005) include reducing the sources of human-caused death, injury and disturbance; developing

demographically-based recovery criteria; to identify, characterize, protect and monitor important 

habitats; to monitor the status and trends of abundance and distribution of the western North 

Atlantic right whale population; and to coordinate Federal, State, local, international and private 

efforts to implement the recovery plan.

2.2 BLUE WHALE (BALAENOPTERA MUSCULUS)

2.2.1 Legal Status

The blue whale is listed as endangered throughout its range under the ESA and as depleted under 

the MMPA. The species has been protected from commercial whaling since 1966 under the 

International Convention for the Regulation of Whaling (Office of Protected Resources–

NOAA Fisheries n.d.). The North Atlantic stock of B. musculus musculus is listed as endangered 

by the International Union for Conservation of Nature (IUCN) Red List of Threatened Species 

(Reilly et al. 2008a).
15

2.2.2 General Distribution

The blue whale is found in all oceans except the high Arctic (Reilly et al. 2008a). In the North 

Atlantic, blue whales are most frequently sighted from Iceland to West Greenland to waters off 

eastern Canada, especially in the Gulf of St. Lawrence (Sears 2002; Waring et al. 2011). Blue 

whales have been acoustically detected in deep waters east of the U.S. Exclusive Economic Zone 

(EEZ) (Clark 1995). 18th and 19th century whaling logbooks recorded blue whale sightings in 

U.S. waters off the mid-Atlantic and southeast coast (Reeves et al. 2004), but recent sightings in 

the U.S. EEZ are infrequent. Occasional sightings of blue whales have been made off Cape Cod, 

Massachusetts, in summer and fall (Wenzel et al. 1988). Sighting locations of blue whales are 

shown in Figure 2.2-1.

2.2.3 General Abundance

The global blue whale population size is uncertain but is thought to be between 10,000 and 

25,000 animals (Reilly et al. 2008a). The western North Atlantic population is estimated to be in 

the low hundreds (Sears and Calambokidis 2002), based on photo-ID work done in the Gulf of 

St. Lawrence (Sears et al. 1990).

2.2.4 Habitat Preference

Coastal and pelagic waters are used by blue whales, and feeding aggregations are found 

primarily at the shelf edge (Sears and Calambokidis 2002). Acoustic detections of blue whales 

in the North Pacific were correlated with areas of sea surface temperature fronts and sea surface 

height elevations that indicated areas of upwelling (Moore et al. 2002). Those two variables 

appeared to be better indicators of good blue whale habitat than chlorophyll-a measurements. 

Stafford et al. (2009) also examined blue whale call detection rates in the North Pacific with 

respect to sea surface temperature, chlorophyll-a concentration, and mixed layer depth, finding 

that sea surface temperature was the best predictor of whale call detections. Distributions of blue 

whales were highly correlated with sea surface temperature fronts in the Gulf of St. Lawrence 

(Doniol-Valcroze et al. 2007).

2.2.5 Stock Structure

Blue whales in the North Atlantic belong to the subspecies Balaenoptera musculus musculus. 

Stock structure has not been defined, and while the species is sometimes considered to be 

divided into western and eastern North Atlantic stocks, acoustic tracking of blue whales ranging 

widely in the ocean basin (Clark 1995) supports a hypotheses of a single panmictic stock 

(National Marine Fisheries Service 1998).

2.2.6 Life History Traits 

The blue whale gestation period is approximately 10-12 months, and calves are nursed for about 

6-7 months (National Marine Fisheries Service 1998). Blue whales are thought to become 

sexually mature at 5-15 years of age and the calving interval is probably 2 to 3 years (National 

Marine Fisheries Service 1998). 

Ramp et al. (2006) used sighting histories of photo-identified blue whales in the Gulf of St. 

Lawrence to estimate the adult blue whale survival rate to be 0.975 (95% CI 0.960 to 0.985). 
16

The sighting histories also showed that while some blue whales have high site fidelity to the St. 

Lawrence area, others were only occasionally sighted there.

2.2.7 Food Habits

Blue whales feed largely on krill (euphausiids). In the Gulf of St. Lawrence, blue whales feed on 

two main euphausiid species, Thysanoëssa racshii and Meganyctiphanes norvegica (Sears et al. 

1987).

2.2.8 Health

2.2.8.1 Strandings

Blue whales strand infrequently on the U.S. east coast, and no records of strandings exist in 

recent response organization databases. An 1891 stranding at Ocean City, Maryland, is the 

southernmost confirmed record on the U.S. east coast (National Marine Fisheries Service 1998). 

2.2.8.2 Contaminants

Organochlorines contamination in blubber samples of blue whales in the St. Lawrence has been 

analyzed and compared to that in other balaenopterids in the area (Gauthier et al. 1997; Metcalfe 

et al. 2004). In blue whales, concentrations of some of the more persistent contaminants were 

present at higher concentrations in the blubber of males relative to females; indicating maternal 

transfer from females into their offspring (Metcalfe et al. 2004).

2.2.8.3 Disease

Crassicaudosis is a potentially lethal endemic disease caused by infection by the giant nematode 

Crassicauda boopis. It can affect blue, fin, and humpback whales, and occurs worldwide 

(Lambertsen 1992). Several types of skin lesions have been reported on blue whales seen off 

Chile (Brownell, Jr. et al. 2007).

2.2.9 Acoustics

Blue whale song can be divided into at least ten geographically distinct types, with one type 

unique to the North Atlantic (McDonald et al. 2006, 2009). Typically, blue whale vocalizations 

consist of repeated sequences of simple combinations of long-duration, very-low-frequency (15-

20 Hz) sound units repeated every minute or two. The specific frequency, duration, and 

repetition intervals produced by blue whales in the North Atlantic, however, can be distinguished 

from blue whale recordings from other regions (Mellinger and Clark 2003). These song types 

retain consistent phrasing over time, although research by McDonald et al. (2009) demonstrated 

that all seven song types for which multiple years of data are available have shifted perceptibly 

lower in frequency. The mean frequency of the North Atlantic song type has declined from 23 

Hz in 1959 to 17.6 Hz in 2004 (McDonald et al. 2009). The authors theorized that the frequency 

shifts may be related to changes in population densities as the blue whale populations recover 

from whaling.

Blue whales have been acoustically detected in the North Atlantic using the U.S. Navy 

underwater hydrophone arrays (Clark 1995; Mellinger and Clark 2003). Diel variation in blue 

whale calling was demonstrated in the eastern tropical Pacific (Stafford et al. 2005). The diel 
17

patterns of call production were correlated with patterns of prey distribution. Efforts have been 

made in waters to the north and west of Iceland to relate visual observations of blue and fin 

whales with continuous acoustic monitoring with the aim of further developing acoustic 

detection techniques for these species (Boisseau et al. 2008).

In the North Pacific, blue and fin whale call detections were correlated with sea-surface 

temperature, chlorophyll-a concentration and mixed layer depth (Stafford et al. 2009). Seasurface temperature proved to be the best oceanographic variable for predicting call detections 

for both species. 

2.2.10 Fisheries By-catch and Entanglement

There have been several documented cases of blue whale entanglements in fishing gear: one in 

1987 off Stellwagen Bank, north of Cape Cod, Massachusetts, and at least three in the Gulf of St. 

Lawrence (National Marine Fisheries Service 1998; Sears and Calambokidis 2002). 

2.2.11 Vessel Interactions

A blue whale ship strike mortality was reported in 1998 when a dead juvenile male was brought 

into Rhode Island waters on the bow of a tanker (National Marine Fisheries Service 1998; 

Waring et al. 2011). At least 9% of blue whales in the Gulf of St. Lawrence catalog show signs 

of ship strike scarring (Sears et al. 1990). Acoustic masking by vessel traffic in the Santa 

Barbara Channel off California, important blue whale habitat, was investigated by McKenna et 

al. (2009). 

2.2.12 Energy Projects

Both extractive and renewable offshore energy projects have the potential to impact the marine 

environment in a variety of ways, including habitat alteration and the introduction of noise by

seismic exploration activities (e.g., airguns), vessel/aircraft activity, construction and operation

(Geraci and St. Aubin 1980, Bain and Williams 2006, Thompsen et al. 2006, Cada et al. 2007, 

Compton 2008, Evans 2008, MMS 2008, Burgman 2010, Boehlert and Gill 2010, Dolman and 

Simmonds 2010, Edrén et al. 2010, Bush 2011, ICES 2011). The impact of these activities on 

marine mammals is unclear. Di Iorio et al. (2009) investigated blue whale calling behavior 

relative to seismic operations in the St. Lawrence Estuary. An increase in vocal behavior was 

observed, presumably in compensation for the masking effects of the seismic noise. 

2.2.13 Data Gaps and Research Recommendations

The rarity of blue whale sightings in the U.S. Atlantic EEZ makes assumptions about the whales’ 

distribution and habitat use in this area difficult. More data collection using acoustic detections 

could supplement the sightings data. More genetic analyses are necessary to better understand 

stock delineation.
18

2.3 FIN WHALE (BALAENOPTERA PHYSALUS)

2.3.1 Legal Status

The fin whale is classified as endangered under the ESA and depleted under the MMPA 

throughout its range. The species is classified in the “endangered” category under the IUCN 

(Reilly et al. 2008c). 

2.3.2 General Distribution

Fin whales are widely distributed in all major oceans (National Marine Fisheries Service 2010a). 

In the North Atlantic, the fin whale can be found from the Gulf of Mexico to the edge of the 

Arctic pack ice (this range includes all BOEM North Atlantic planning areas). Sightings are 

more common north of 20° N (BOEM South Atlantic, Mid-Atlantic and North Atlantic planning 

areas) (National Marine Fisheries Service 2010a). Sighting, stranding and fishery bycatch 

locations of fin whales are shown in Figure 2.3-1.

Fidelity to feeding grounds and long-distance movement have been demonstrated by tagging and 

photo-identification studies (Edds and Macfarlane 1987; Agler et al. 1990; Seipt et al. 1990; 

Clapham and Seipt 1991; Agler et al. 1993; Coakes et al. 2005; Mizroch et al. 2009). 

2.3.3 General Abundance

Worldwide, fin whale abundance is estimated to be in the tens of thousands (National Marine 

Fisheries Service 2010a). Hain et al. (1992) estimated a population size of about 5,000 fin 

whales in northeastern United States continental shelf waters in the spring and summer of 1978-

1982, and approximately 1,500 in the fall and winter seasons. For the Western North Atlantic 

stock of fin whales, the best recent abundance estimate is 3,985 (CV=0.24). This is the sum of 

the estimate derived from an August 2006 Gulf of Maine survey and an estimate derived from a 

July-August 2007 northern Labrador to Scotian Shelf survey and includes a percentage of the 

estimate of animals identified as fin or sei whales (Waring et al. 2011). This does not include a 

correction for dive time bias.

2.3.4 Habitat Preference

Important habitat in the U.S. waters was described by Hain et al. (1992) as extending from the 

Great South Channel along the 50-m isobath past Cape Cod and over Stellwagen Bank, and 

northeast to Jeffreys Ledge. The mid-shelf region of the mid-Atlantic bight and the eastern edge 

of Georges Bank were also mentioned as important areas. Hamazaki’s cetacean habitat 

prediction model classifies the fin whale as a North Atlantic shelf species (Hamazaki 2002). 

Summer sightings were associated with mean water temperatures of 18.2°C, mean depths of 337 

m, mean bottom slope of 1.1° and front probability of 6.3%.

In the Gulf of St. Lawrence, in an analysis of fin whale distribution during summer and autumn 

of 1989, sightings were found to occur at a mean depth of 128.7 m and mean surface temperature 

of 12.2°C (Woodley and Gaskin 1996). Areas with high topographic variation seemed to be 

favored. Echosounder measurements indicated that herring (Clupea harengus), and euphausiids 

were relatively abundant in areas where fin whales were found. Near Grand Manan Island, in the 

Bay of Fundy, Canada, fin and minke whales were observed to forage in the eddy region of an 
19

island wake, where they likely were able to exploit higher concentrations of prey (Johnston et al. 

2005b).

In contrast to the shallow depths inhabited by fin whales in the Gulf of St. Lawrence, a study that 

correlated fin whale sightings with environmental variables in the Mediterranean indicated that 

over 90% of fin whale sights occurred in water depths of over 2,000 m, with water depth and 

distance from shore being the most significant variables describing fin whale distribution 

(Panigada et al. 2006, 2008). In the Mediterranean, fin whales were found in cold waters with 

steep bathymetry and temperature gradients (Cotté et al. 2009), and a predictive model was 

developed (Laran and Gannier 2008). Off Kodiak, Alaska, in 2002 and 2003, fin whales were

found associated with deeper, cooler waters near areas of maximum slope, though association 

with shallow waters was noted for 2002 and not 2003 (Baraff 2006).

2.3.5 Stock Structure

The International Whaling Commission (IWC) defined seven management units for fin whales in 

the North Atlantic: Nova Scotia, Newfoundland-Labrador, West Greenland, East GreenlandIceland, North Norway, West Norway-Faroe Islands, and British Isles-Spain-Portugal (Donovan 

1991). Significant mtDNA heterogeneity has been found in North Atlantic fin whales between 

the Mediterranean Sea, the eastern (Spain) and the western (Gulf of Maine and Gulf of St. 

Lawrence) summer feeding areas (Bérubé et al. 1998). Variations in fin whale vocalizations 

have also indicated that Gulf of St. Lawrence fin whales are distinct from Gulf of Maine fin 

whales (Delarue et al. 2009). Fin whales off the U.S. Atlantic coast are presumed to be from a 

single stock, though stock substructure is unknown (Waring et al. 2011). 

2.3.6 Life History Traits

From stranding records of neonates and calves, Hain et al. (1992) surmised that fin whale calving 

in U.S. waters takes place primarily between October and January at the latitude of the midAtlantic Bight. Annual rates of reproduction for fin whales in the Gulf of Maine in the 1980s 

were calculated to range from 0.03 to 0.12 (Agler et al. 1993). The birth rate was estimated at 

0.37 young per mature female per year and a potential mean interval of birthing was estimated at 

2.24 years (Agler et al. 1993). By the age of 30, most female fin whales caught off the coast of 

Iceland had begun reproductive senescence (Kjeld et al. 2006). 

2.3.7 Food Habits

In the North Atlantic, fin whales are known to feed on pelagic crustaceans (mainly euphausiids 

or krill, including Meganyctiphanes norvegica and Thysanoessa inermis) and schooling fish such 

as capelin (Mallotus villosus), herring (Clupea harengus), and sand lance (Ammodytes spp.) 

(Mitchell 1974; Overholtz and Nicolas 1979; National Marine Fisheries Service 2010a). 

Fluctuations in the availability of prey, especially sand lance, are thought to have had a strong 

influence on the distribution and movements of fin whales in shelf waters of the northeastern 

U.S. (Kenney and Winn 1986; Payne et al. 1990; Hain et al. 1992). The diets of fin whales and 

humpback whales in the Gulf of St. Lawrence were compared using blubber fatty acid analysis 

(Borobia et al. 1995). The chemical and isotopic differences found indicated that humpbacks fed 

at a slightly lower trophic level than fin whales.
20

High-resolution digital tags attached to fin whales in the Southern California Bight were used to 

study the biomechanics of the lunge-feeding behavior (Goldbogen et al. 2006). The whales were 

found to glide during descent, execute a series of lunges at depth and then ascend to the surface 

by steady fluking. Larger fin whales have larger skulls and buccal cavities relative to body size, 

allowing for larger engulfment volumes during lunge-feeding (Goldbogen et al. 2010). A 

hydrodynamic model of fin whale lunge feeding was developed by Potvin et al. (2009) to test 

whether the mechanics of engulfment were passive or involved muscle action. Results suggested 

that adult rorquals actively push engulfed water forward from the onset of mouth opening, which 

involves a reflux of the engulfed water.

2.3.8 Health

2.3.8.1 Strandings

Hain et al. (1992) reported a total of 72 fin whale strandings along the U.S. Atlantic coast “so far 

this century.” Strandings were relatively evenly distributed by month; however, a majority of the 

strandings occurred on Cape Cod, Massachusetts, or on Cape Hatteras, North Carolina. Thirtyfour confirmed fin whale mortalities were reported in the mortality and serious injury report for 

the period 2005-2009 (Henry et al. 2011). This figure includes anthropogenic and nonanthropogenic mortalities.

2.3.8.2 Contaminants

Aguilar and Borrell (1994) estimated body loads of organochlorine pollutants in 169 fin whales 

caught off the northwestern coast of Spain. They found blubber to be the greatest reservoir for 

contaminants, although compared to other cetaceans its relative contribution to the total load was 

lower. Organochlorine body loads of males increased with age but leveled off once the whale 

was fully grown. In adult females, loads decreased with age due to fetal transfer but the transfer 

was lower than found in other cetaceans because of the shorter lactation period of fin whales. 

Blubber samples taken from minke whales, fin whales, blue whales, and humpback whales in the 

Gulf of St. Lawrence, Quebec in summer and fall of 1991 and 1992 were tested for chlorinated 

biphenyls and other persistent organochlorine compounds (Gauthier et al. 1997). Ratios of 

proportions of oxychlordane to trans-nonachlor were highest in fin whales. The fin whale was 

one of four marine mammal species chosen for a comparative study on temporal and geographic 

variation in levels of organochlorine contaminants in marine mammal blubber (Aguilar et al. 

2002). Fin whale samples from western North America and Europe—especially the 

Mediterranean—were highest in organochlorine loads compared to those from other areas. 

Concentrations overall had decreased in areas where pollution was initially high but had 

increased in areas further from the pollution sources.

Bioaccumulation of flouride was demonstrated in bone samples from North Atlantic fin whales 

(Landy et al. 1991). Concentrations were found to be higher than in other mammals, and 

increased with age. The fact that krill from the stomachs of the whales also tested high for 

fluoride pointed to diet as the source. 

2.3.8.3 Disease

Necropsies of two female immature fin whales that had stranded in France and Belgium revealed 

massive parasitic infestation and positive tests for morbillivirus exposure (Jauniaux et al. 2000). 
21

Eighty-seven fin whales caught by commercial whalers in Icelandic waters were necropsied to 

determine cause of death (Lambertsen 1986). The giant nematode Crassicauda boopis was 

found in 82 of the whales. Crassicauda infection was so prevalent and severe that it was deemed 

capable of causing the death of the animals. In a study of serum chemistry of fin whales caught 

by commercial whalers in the Denmark Strait in 1984 and 1985, serum electrolytes, urea 

nitrogen, creatine, albumin, and globulin were measured (Lambertsen et al. 1986). While chase 

time was found to have no substantive effect on serum chemistry, one of the whales did exhibit 

serum chemistry consistent with renal failure.

2.3.9 Acoustics

Southall et al. (2007) classified fin whales and other balaenopterids in the “low-frequency 

cetaceans” functional hearing group, with an estimated hearing range of approximately 7 Hz to 

22 kHz. Fin whale sounds recorded by a stationary hydrophone in the St. Lawrence Estuary 

consisted of vocalizations with frequencies below 120 Hz and impulsive sounds with frequencies 

up to 1 kHz (Edds 1988). Downsweeping calls were the most common, with frequency 

variations that were correlated with social context. Constant calls, upsweeps, wavers and a 

frequency and amplitude modulated call were also recorded but were uncommon. 

The “20-Hz” call, which had been associated with the reproductive season (Watkins et al. 1987), 

was, through a combination of towed hydrophone recordings and biopsy genetic sampling, 

discovered to be made exclusively by male fin whales in the Gulf of California, Mexico (Croll et 

al. 2002). This sound, which can reach intensities of 184-186 decibels relative to 1 μPa of sound 

pressure, is thought to attract females from great distances to prey aggregations. These calls 

have also been recorded by autonomous hydrophones near the mid-Atlantic ridge (Nieukirk et al. 

2004).

Interpulse intervals in fin whale calls vary between geographic areas so can be used to elucidate 

stock structure. Fin whale songs from the Gulf of St. Lawrence differ significantly from fin 

whale songs recorded in the Gulf of Maine (Delarue et al. 2009). Changes in song notes and 

features of fin whale vocalizations were observed in a comparison of recordings from Cape Cod 

Bay in 1961, 1978, 2001 and 2005 (Koltz 2007). Variation in seasonal and yearly patterns may 

confound comparison of these recordings with those collected from a fin whale population in 

Bermuda.

In the North Pacific, blue and fin whale call detections were correlated with sea-surface 

temperature, chlorophyll-a concentration and mixed layer depth (Stafford et al. 2009). Seasurface temperature proved to be the best oceanographic variable for predicting call detections 

for both species. 

Between 2006 and 2009 sea floor recorders monitored noise levels and fin whale presence in the 

western Mediterranean and adjacent NE Atlantic waters (Castellote et al. 2009, 2010). This 

period included a 10-day seismic survey in the region. Fin whales were found to decrease 

temporal and spectral parameters of their vocalizations when ambient noise levels rose. Airgun 

noise from the seismic survey caused singing fin whales to move away from the study area 

within 24 hours and to stay out of the area until 14 days after the seismic activity had ceased. 
22

Airgun noise appeared to exceed the fin whales’ tolerance threshold even though received levels 

were less than 120 dB during the singing overlap period.

Analysis of fin whale calls recorded by bottom-moored acoustic recorders in Davis Strait, 

between Greenland and Canada, has resulted in new understandings of habitat use and migration 

of fin whales in that area (Simon et al. 2010). Fin whales were shown to be present in Davis 

Strait much later in the year than previously expected and peaks in song activity implied mating 

activity. 

A method for estimating fin whale population density was described by McDonald and Fox 

(1999). From one bottom-fixed hydrophone north of Oahu, Hawaii, an average calling whale 

density of 0.027 animals/1000 km2 was derived, with a seasonal maximum calling whale density 

of 0.081 animals/1000 km2

. Fin whale call types detected were “doublet 20-Hz” calls, “20- to 35-

Hz irregular repetition interval” calls, and “30- to 90-Hz shorter and more irregular repetition 

intervals” calls.

2.3.10 Fisheries By-catch and Entanglement

Two Western North Atlantic stock fin whales are reported in NMFS records for 2005 through 

2009 with sufficient information to confirm the cause of death as fishery interaction, and two

with fishery interaction serious injuries, resulting in an annual rate of serious injury or mortality

from fishery interactions of 0.8 fin whales (Waring et al. 2011). The threat posed by fishery 

entanglement to the Western North Atlantic stock of fin whales is characterized as “low” in the 

Recovery Plan (National Marine Fisheries Service 2010a).

2.3.11 Vessel Interactions

Fin whales were the most often reported species involved with ship strikes worldwide, with 75 

records of strike (out of a total of 292) in the period 1975 to 2002 (Jensen and Silber 2003). 

Between 1993 and 2002 at least 15 fin whales were ship strike mortalities off the U.S. east coast 

(Jensen and Silber 2003). Nine fin whales were reported in NMFS records for the Western 

North Atlantic stock during 2005 through 2009 with sufficient information to confirm the cause 

of death as collisions with vessels (Henry et al. 2011). The resulting annual rate of serious injury 

or mortality from vessel collisions was 1.8 fin whales. 

Fin whale respiration data collected from Mt. Desert Rock, Maine (land-based survey) between 

1983 and 1986 were examined to determine whether proximity to whale-watching boats altered 

the fin whales’ breathing patterns (Stone et al. 1988). The presence or absence of vessels was 

found to have no significant effect on respiration characteristics. A study on reactions of 

Mediterranean fin whales to small vessel approaches, however, found significant behavior 

changes (Jahoda et al. 2003). Suspension of feeding behavior, increased travel velocity and 

reduction of time spent at the surface were observed.

2.3.12 Energy Projects

Both extractive and renewable offshore energy projects have the potential to impact the marine 

environment in a variety of ways, including habitat alteration and the introduction of noise by

seismic exploration activities (e.g., airguns), vessel/aircraft activity, construction and operation

(Geraci and St. Aubin 1980, Bain and Williams 2006, Thompsen et al. 2006, Cada et al. 2007, 
23

Compton 2008, Evans 2008, MMS 2008, Burgman 2010, Boehlert and Gill 2010, Dolman and 

Simmonds 2010, Edrén et al. 2010, Bush 2011, ICES 2011). The impact of these activities on 

marine mammals is unclear. MacLeod et al. (2006b) suggested that an absence of fin and sei 

whale sightings to the west of the Outer Hebrides may be correlated with increased seismic 

activity in the area. Low levels of localized avoidance were found in mysticetes exposed to 

seismic airgun noise in the UK and adjacent waters investigated in 1997-2000 (Stone and Tasker 

2006). Avoidance behavior and changes in vocalization parameters were observed in fin whales 

in the Mediterranean when exposed to seismic activity (Castellote et al. 2009, 2010).

2.3.11 Data Gaps and Research Recommendations

The Fin Whale Recovery Plan (National Marine Fisheries Service 2010a) identifies key actions 

that should be undertaken to further understand and protect fin whales. Priorities include better 

understanding of fin whale population structure; improvement of abundance estimates and trends 

of abundance; improvement of knowledge of fin whale habitat and feeding ecology; research on 

the impacts of climate change on fin whales; steps to minimize fin whale mortality from 

anthropogenic sources such as ship strike, fishery interaction and pollution; steps to determine 

and minimize detrimental anthropogenic noise; and effective response to strandings of fin 

whales.

2.4 SEI WHALE (BALAENOPTERA BOREALIS)

2.4.1 Legal Status

The sei whale is classified as endangered under the ESA and depleted under the MMPA 

throughout its range. The species is classified in the “endangered” category under the IUCN 

(Reilly et al. 2008b). 

2.4.2 General Distribution

Sei whales have a wide, but primarily offshore, distribution in the North Atlantic, the North 

Pacific and in the southern hemisphere (Reilly et al. 2008b). The subspecies B. b. borealis

inhabits the northern hemisphere and the subspecies B. b. schlegellii is found in the southern 

hemisphere (Rice 1998). Seasonal migration patterns are described between tropical and subtropical breeding grounds and high-latitude feeding grounds (Reeves et al. 1998; Kanda et al. 

2006; Reilly et al. 2008b; Horwood 2009). Eight sei whales satellite-tagged in the Azores have 

been tracked to the Labrador Sea (1 by Olsen et al. 2009; 9 by Prieto et al. 2010). Sighting and 

stranding locations of sei whales are shown in figure 2.4-1.

Off the U.S. Atlantic coast, sei whales are found in the deeper waters east and south of Georges 

Bank in the spring through fall, occasionally making incursions into shallower waters including 

the Great South Channel, Stellwagen Bank, and the southern Gulf of Maine (Payne et al. 1990; 

Schilling et al. 1992; Waring et al. 2011). Sightings are primarily in the BOEM North Atlantic 

Planning Area.
24

2.4.3 General Abundance

An estimate of 386 (CV=0.85) sei whales was derived from a summer 2004 aerial and shipboard 

survey conducted in waters from Maryland to the lower Bay of Fundy (Waring et al. 2011). No 

population estimate for the entire North Atlantic is available.

2.4.4 Habitat Preference 

Analysis of satellite-tracked movements of eight sei whales tagged in the Azores was evidence 

that hydrological structures such as sea surface temperature fronts and eddies create good 

foraging habitat for sei whales in the Labrador Sea (Prieto et al. 2010). In the Mid-Atlantic ridge 

region, sei whale distribution was correlated with cross-seamount or cross-frontal structures 

(Skov et al. 2008). While sei whale aggregations have been reported associated with submarine 

canyons, Kenney and Winn (1987) found no differential sighting rates for sei whales in the 

northeastern U.S. shelf region between canyon areas and neighboring shelf/slope areas. 

2.4.5 Stock Structure

There are two stocks of sei whales recognized in the western North Atlantic—the Labrador Sea 

stock, whose range extends from the southeast coast of Newfoundland northward, and the Nova 

Scotia stock, found south of Newfoundland to at least North Carolina (Reeves et al. 1998). 

2.4.6 Life History Traits

Age at maturity is approximately 10 years (Horwood 2009). Most conceptions occur in 

December in the northern hemisphere, with young carried for almost a year and nursed for 7 

months (Horwood 2009). Natural mortality rates are not well known, but are thought to be 

around 5-10% per year (Horwood 2009). 

2.4.7 Food Habits

Sei whales use both skim and lunge-feeding techniques to feed on calanoid copepods and 

euphausiids in the North Atlantic (Horwood 2009). Shifts in abundance of copepods and of sand

lance (Ammodytes spp.) during the 1980s were studied by Payne et al. (1990). Sei whales were 

only common in the Gulf of Maine study area when copepod abundance reached a regional 

maximum and sand lance abundance was at it regional lowest. Sei whale and right whale 

occurrence patterns were significantly related. Sei whales were shown to be significantly less 

abundant in the Gulf of Maine during periods when diel vertical migration patterns of Calanus 

finmarchicus were strong (Baumgartner et al. 2011). 

2.4.8 Health

2.4.8.1 Strandings

Sei whales strand infrequently on the U.S. east coast. Ten confirmed sei whale mortalities were 

reported in the mortality and serious injury report for the period 2005-2009 (Henry et al. 2011). 

This figure includes anthropogenic and non-anthropogenic mortalities.
25

2.4.8.2 Contaminants

Annual changes in mercury in western North Pacific zooplankton, pelagic fishes, and baleen 

whales, including sei whales, were examined by Yasunaga et al. (2009). Variation in total Hg 

levels in sei whale muscle samples was shown to be insignificant. 

O’Shea and Brownell (1994), in their review of studies of the effects of contaminants on baleen 

whale populations, concluded that there is no firm evidence for direct impacts on baleen whale 

populations from organochlorine and metal contamination.

2.4.8.3 Disease

Lambertsen (1990) found that eastern North Atlantic sei whales did not seem to be infected with 

crassicaudiasis to the same extent as fin whales. However, 92% of the examined sei whales 

(N=24) had invasive infections of Bolbosoma spp. in the colon and 18% showed an 

inflammation in the lungs that appeared consistent with viral or mycoplasma pathogen. The sei 

whales were often scarred with bite wounds and unidentified external lesions. 

2.4.9 Acoustics

Southall et al. (2007) classified sei whales and other balaenopterids in the “low-frequency 

cetaceans” functional hearing group, with an estimated hearing range of approximately 7 Hz to 

22 kHz. 

Baumgartner and Frantantoni (2008) examined associations between sei whale vocalization 

rates, oceanographic conditions, and the vertical distribution of the whales' prey, C. 

finmarchicus, during May 2005 in the southwestern Gulf of Maine using an array of autonomous 

ocean gliders. The diel vertical migration of C. finmarchicus was confirmed using acoustic 

backscatter measurements. Sei whale vocalization rates showed a corresponding diel periodicity, 

with more calls detected during the daytime when C. finmarchicus was observed at depth. It was 

hypothesized that calling rates were reduced at night while the whales were feeding, but 

increased with social activity during the day when copepods are either more difficult or less 

efficient to capture at depth. Low frequency downsweep vocalizations recorded by the 

autonomous gliders, were subsequently confirmed to be produced by sei whales by visual survey 

combined with acoustic recorder array deployments (Baumgartner et al. 2008). The New Jersey 

Shallow Water 2006 experiment recorded a number of sei whale low-frequency downsweep 

chirps in mid-Atlantic continental shelf waters off New Jersey (Newhall et al. 2009). Two 

variations of low-frequency downsweeps, as well as 105 other vocalizations, have been 

attributed to sei whales near the Hawaiian Islands (Rankin and Barlow 2007b).

2.4.10 Fisheries By-catch and Entanglement

Three Nova Scotia stock sei whales were reported in NMFS records for 2005 through 2005 with 

fishery interaction serious injuries, resulting in an annual rate of serious injury or mortality from 

fishery interactions of 0.6 sei whales (Waring et al. 2011). 

2.4.11 Vessel Interactions 

Only 3 records of sei whales were reported involved with ship strikes worldwide (out of a total 

of 292) in the period 1975 to 2002 (Jensen and Silber 2003). Three sei whales were reported in 
26

NMFS records for the Nova Scotia stock during 2005 through 2009 with sufficient information 

to confirm the cause of death as collisions with vessels (Waring et al. 2011). The resulting 

annual rate of serious injury or mortality from vessel collisions was 0.4 sei whales. 

2.4.12 Energy Projects

Both extractive and renewable offshore energy projects have the potential to impact the marine 

environment in a variety of ways, including habitat alteration and the introduction of noise by

seismic exploration activities (e.g., airguns), vessel/aircraft activity, construction and operation

(Geraci and St. Aubin 1980, Bain and Williams 2006, Thompsen et al. 2006, Cada et al. 2007, 

Compton 2008, Evans 2008, MMS 2008, Burgman 2010, Boehlert and Gill 2010, Dolman and 

Simmonds 2010, Edrén et al. 2010, Bush 2011, ICES 2011). MacLeod et al. (2006b) suggested 

that an absence of fin and sei whale sightings to the west of the Outer Hebrides may be 

correlated with increased seismic activity in the area. Low levels of localized avoidance were 

found in mysticetes exposed to seismic airgun noise in the UK and adjacent waters investigated 

in 1997-2000 (Stone 2003; Stone and Tasker 2006).

2.4.13 Data Gaps and Research Recommendations

The Draft Recovery Plan for the fin whale and sei whale (Reeves et al. 1998) identified key 

actions that should be undertaken to further understand and protect sei whales. Priorities include 

better understanding of sei whale population structure; improvement of abundance estimates and 

trends of abundance; identification and protection of essential sei whale habitats; research on the 

impacts of climate change on sei whales; reduction of sei whale mortality from anthropogenic 

sources such as ship strike, fishery interaction and pollution; steps to determine and minimize 

detrimental anthropogenic noise; and effective response to strandings of sei whales. 

2.5 MINKE WHALE (BALAENOPTERA ACUTOROSTRATA)

2.5.1 Legal Status

The minke whale is protected under the MMPA and is classified in the “Least Concern” category 

under the IUCN (Reilly et al. 2008d). The species is not listed under the ESA. 

2.5.2 General Distribution

Minke whales occur in coastal and offshore waters of all oceans of the world, in latitudes from 

65°S to 80°N (Reilly et al. 2008d). In the western North Atlantic, minke whales are common in 

summer north to Baffin Bay and south to New Jersey—in the BOEM North Atlantic planning 

area (Reilly et al. 2008d). A study of minke whale occurrence in Massachusetts Bay and Cape 

Cod Bay showed that minkes generally arrive in these waters in early spring and were most 

abundant in late summer (Murphy 1995). Sighting, stranding and fishery bycatch locations of 

minke whales are shown in Figure 2.5-1.

Satellite-tracking data collected from two minke whales off northern Norway showed that, while 

the whales travelled an average of 78 and 79 km per day, they remained resident in the general 

area while transmitting (31 days and 19 days, respectively) (Heide-Jorgensen et al. 2001). 

Small-scale site fidelity has also been shown off Scotland (Gill and Fairbairns 1995; 
27

Baumgartner 2008) and off the Pacific Northwest coast of the U.S. (Dorsey 1983; Dorsey et al. 

1990).

2.5.3 General Abundance

Worldwide, minke whales are thought to number approximately 182,000 (Reilly et al. 2008d). 

Minke whale abundance estimates for northeast Atlantic populations are reported by Skaug et al. 

(107,205 CV=0.14; 2004) and Bøthun et al. (108,000 CV=0.23; 2009). For the Canadian East 

Coast stock of the western Atlantic, the best recent abundance estimate is 8,987 (CV=0.32), 

which is the sum of an August 2006 U.S. survey (3,312 CV=0.74) and a July-August 2007 

Canadian survey (5,675 CV=0.25) (Waring et al. 2011).

2.5.4 Habitat Preference

A 12-year sighting history of minke whales in the Mingan Islands (Canada) was analyzed with 

respect to bottom topography, geomorphology, and depth (Naud et al. 2003). Distribution of 

sightings was found to be positively correlated with sandy bottom substrates, a good habitat for 

sand lance (Ammodytidae), the whales’ principal prey in that area. In the Moray Firth, off 

Scotland, areas of highest minke whale encounter frequency were characterized by shallow 

depths (10-14 m), steep slopes (70-74 degrees) and sandy gravel bottom substrate (Robinson and 

Tetley 2005; Robinson et al. 2009), though age-class differences were seen in distribution 

relative to bottom substrate (Robinson et al. 2009). A strong positive linear relationship between 

tidal speed and whale occurrence was also shown for this region (Baumgartner 2008). Seasonal 

changes in whale distribution were demonstrated to show response to shifting prey preferences 

(Macleod et al. 2004) as were seasonal and diel changes in dive intervals (Stockin et al. 2001). 

High densities of phytoplankton during warm water plume events in the Moray Firth were 

associated with higher minke whale sighting rates, presumably due to their effect in attracting 

minke whale prey (Tetley et al. 2008). On the basis of multiple logistic regression analysis 

which modeled sightings of minke whales in the western North Atlantic with oceanographic and 

topographic variables, Hamazaki (2002) classified the species as a nearshore northern Atlantic 

species, with sightings concentrated in waters with sea surface temperatures of 10° - 15° C and 

depths less than 500 m. In the Bay of Fundy, minke whale sighting rates showed a non-linear 

relationship with increasing benthic slopes and a linear relationship with increasing water depth 

(Ingram et al. 2007). Distributions of minke whales were highly correlated with sea surface 

temperature fronts in the Gulf of St. Lawrence (Doniol-Valcroze et al. 2007).

2.5.5 Stock Structure

Four stocks of minke whales in the North Atlantic are recognized by the IWC—the Northeast 

Atlantic, Central North Atlantic, West Greenland, and Canadian East Coast stocks (Reilly et al. 

2008d). Animals found along the U.S. Atlantic coast are considered members of the Canadian 

East Coast stock. The north Atlantic summer range has been split into ten management areas 

(Donovan 1991). Regional variations in organochlorine, fatty acid, elemental and stable isotope 

compositions (Born et al. 2002, 2003, 2007; Møller et al. 2003) and genetics (Andersen et al. 

2003) have suggested population substructure in the eastern North Atlantic, but similar work has 

not been done in the western North Atlantic.
28

2.5.6 Life History Traits 

Minke whales become sexually mature at about 6 to 7 years of age and observed pregnancy rates 

of up to 100% suggest an annual reproductive cycle (Perrin and Brownell Jr 2009). Gestation is 

approximately 10 months, and calves, which are 2.4-2.7 m at birth, are nursed for 4-5 months 

(Perrin and Brownell, Jr. 2009). Genetic research indicates that female minke whales mate 

promiscuously across seasons (Skaug et al. 2008).

2.5.7 Food Habits

Minke whales are opportunistic feeders, feeding on crustaceans, plankton, and schooling fish 

(Horwood 1990; Perrin and Brownell Jr 2009). Individual minke whales off Scotland were 

found to specialize in lunge feeding or bird-associated feeding strategies (Hoelzel et al. 1989). 

Auks in particular, (common guillemots Uria aalge and razorbills Alca torda) had a strong 

association with minkes, with the minkes taking advantage of the prey-aggregating behavior of 

the auks (Anderwald et al. 2011). Schooling mackerel (Scomber scombrus) created aggregations 

of sand lance used by minke whales (Robinson and Tetley 2007). In the mouth of the Saguenay 

River, Quebec, minkes were observed to exhibit novel behaviors for aggregating prey at the 

surface (Kuker et al. 2010), including “head slaps,” “chin-up blows” and “exhales on the dive.” 

Western North Pacific minke whale stomach contents examined by Tamura et al. (2009)

contained one species of copepod, two krill species, two squid species, and eight fish species. 

Geographic and seasonal variability of prey selection that reflected changes in availability in the 

prey species was demonstrated for North Pacific minke whales (Tamura and Fujise 2002). 

Atlantic herring (Clupea harengus) and capelin (Mallotus villosus) were the primary prey species 

found in minke whale stomachs from the southern Barents Sea and coast of northern Norway 

(Lindstrøm et al. 2000, 2002; Sivertsen et al. 2006). The degree of variation in observed weights 

of forestomach contents from minke whales off Norway suggested that the whales were feeding 

in well-defined bouts separated by periods of non-feeding (Haug et al. 1997). Multispecies 

functional response modeling showed that minkes may deplete local prey aggregations at small 

spatial scales (Smout and Lindstrøm 2007). Stomach content analysis of 10 stranded minke 

whales in Scotland showed that sand eels made up about 2/3 of the prey consumed, with herring 

and sprat (Sprattus sprattus) accounting for most of the remainder (Pierce et al. 2004). 

2.5.8 Health

2.5.8.1 Strandings

Minke whale strandings occur on a regular basis along the U.S. Atlantic coastline. Eighty-two 

confirmed minke whale mortalities were reported in the mortality and serious injury report for 

the period 2005-2009 (Henry et al. 2011). This figure includes anthropogenic and nonanthropogenic mortalities.

A minke whale calf was associated with a mass stranding event in North Carolina in 2005. The 

animal was emaciated and presumed to be a calf that had become separated from its mother. The 

mass stranding was temporally and spatially associated with a period of active sonar 

transmissions, which could not conclusively be ruled out as a causative factor (Hohn et al. 2006).
29

2.5.8.2 Contaminants

Organochlorine contaminants in minke whale samples from the northeast Atlantic have been 

studied by Kleivane and Skaare (1998), Hobbs (2002), Born (2007), and Gouteaux (2008). 

Blubber samples taken from minke, fin, blue, and humpback whales in the Gulf of St. Lawrence, 

Quebec, in summer and fall of 1991 and 1992 were tested for chlorinated biphenyls and other 

persistent organochlorine compounds (Gauthier et al. 1997). Concentrations of PCBs 

(polychlorinated biphenyls) and most OCs (organochlorine) were similar between the four 

species, but minke whales had lower levels of DDTs than the fin and blue whales. Mirex 

concentrations in the minke samples were double those found in the other balaenopterids. 

Radioactive caesium-137 concentrations in minke whales from the northeast Atlantic, West 

Greenland, and the North Sea were studied by Born et al. (2002). The highest caesium 

concentrations were found in whales from the North Sea. Significant differences in mean 

caesium concentrations were found when samples from minke whales in Svalbard and the North 

Sea were compared with samples from other areas. Selenium metabolites in minke whale urine 

were examined by Hasunuma et al. (1993), who found a mean level of 1500 ng/ml—about 30 

times the mean level in humans. Heavy metal and trace element concentrations have been 

examined in Antarctic minkes (Honda et al. 1987; Kunito et al. 2002), and in northeast Atlantic 

minkes (Born et al. 2007). The multi-elemental analysis was useful in identifying population 

substructure in the northeast Atlantic (Born et al. 2007).

2.5.8.3 Disease

Serum chemistry of minke whales caught off the coast of Norway was analyzed in order to 

obtain reference values for this species (Tryland and Brun 2001). Parasitic infections of minke 

whales from the Pacific were reported by Uchida et al. (1998).

2.5.9 Acoustics

Minke whale vocalizations include “clicks,” “grunts,” “pulse trains,” “ratchets,” “thumps,” and 

“boings” (Beamish and Mitchell 1973; Winn and Perkins 1976; Edds-Walton 2000; Mellinger et 

al. 2000; Rankin and Barlow 2005).

Work with dwarf minke whales at the Great Barrier Reef off Australia, has contributed to a large 

database collection of minke whale sounds and increased understanding of the acoustic ecology 

of this species (Costa 1998; Costa and Gedamke 2000; Gedamke 2004). Sound playback 

experiments showed that song could be important regulating spatial interaction (Costa 2003; 

Gedamke 2004).

Once the “boing” sound was confirmed to be produced by minke whales in the North Pacific 

(Rankin and Barlow 2005), attention focused on this distinctive sound. Acoustic and visual 

survey data collected in the Pacific Missile Range off the Hawaiian Islands was used to develop 

methods of detection, localization and characterization of minke whale calls (Martin et al. 2011; 

Nosal 2011). Boings recorded in the Hawaiian Islands exhibited significant differences in pulse 

repetition rates compared with boings recorded in the Marianas Islands (Norris et al. 2010), 

although boings recorded in the Marianas are more similar to Hawaiian boings than to those 

recorded east of 138°W (Oswald et al. 2008). In Hawaii, boings were detected from October 
30

until May, with a peak in March, and absent from June to September (Oswald et al. 2011). Data 

collected from combined visual and acoustic surveys around the Hawaiian Islands has suggested 

that minke whales are more common in that area than previously reported, or than would be 

assumed from visual data alone (Rankin et al. 2007) and is being used to develop a spatially 

explicit capture-recapture method of estimating density (Marques et al. 2010; Martin et al. 2010). 

In 1973, Beamish and Mitchell recorded narrow-band pulses in the presence of minke whales in 

the North Atlantic (Beamish and Mitchell 1973). Edds-Walton (2000) studied minke whale 

acoustics in the Mingan Islands (Canada) and recorded frequency modulated downsweeps in the 

80-120 Hz frequency range. In the West Indies, the “speed-up” pulse train—an accelerating 

series of pulses in the 200-400 Hz band, with individual pulses lasting 40-60 msec. and a “slowdown” pulse train—a decelerating series of pulses in the 250-350 Hz band have been attributed 

to minke whales (Mellinger et al. 2000).

2.5.10 Fisheries By-catch and Entanglement

Minke whale interactions have been reported in trawls, driftnet, gillnet, weir, pot/trap, and purse 

seine fisheries along the U.S. and Canadian Atlantic coast (Waring et al. 2011). The annual 

average fishery mortality for this stock in the period 2005-2009 was estimated to be 5.5 animals 

(Waring et al. 2011).

A minke whale with fresh entanglement-like injuries was observed surface-feeding on capelin in 

the Mingan Islands, Gulf of St. Lawrence, Canada (Kot et al. 2009). Feeding ability appeared 

somewhat impaired, though long-term health effects were not possible to assess. 

2.5.11 Vessel Interactions

Two ship-strike mortalities of minke whales were reported between 2005 and 2009 along the 

U.S. Atlantic coast, one off Pleasant Point, New Jersey, and one off Port Elizabeth, New Jersey

(Waring et al. 2011).

2.5.12 Energy Projects

Both extractive and renewable offshore energy projects have the potential to impact the marine 

environment in a variety of ways, including habitat alteration and the introduction of noise by

seismic exploration activities (e.g., airguns), vessel/aircraft activity, construction and operation

(Geraci and St. Aubin 1980, Bain and Williams 2006, Thompsen et al. 2006, Cada et al. 2007, 

Compton 2008, Evans 2008, MMS 2008, Burgman 2010, Boehlert and Gill 2010, Dolman and 

Simmonds 2010, Edrén et al. 2010, Bush 2011, ICES 2011). The impact of these activities on 

marine mammals is unclear. A minke whale calf was part of a mass-stranding that was 

associated in time and space with a period of active sonar transmissions, but the sonar activity 

was not definitively implicated as a causative factor in the mass-stranding (Hohn et al. 2006). 

Low levels of localized avoidance were found in mysticetes exposed to seismic airgun noise in 

the UK and adjacent waters investigated in 1997-2000 (Stone and Tasker 2006).

2.5.13 Data Gaps and Research Recommendations

Much of minke whale research has been done in regions where data is available from whaling 

catches, such as off Norway and Japan, or in areas where there are resident or seasonal 
31

populations, such as off Scotland or in the Gulf of St Lawrence. Minke whale use of the 

remainder of their range is less well understood. Development of acoustic detection and 

acoustically-derived abundance estimates, such as the ones being developed in the Hawaiian 

Islands, would be useful if they could be adapted for use in the Atlantic.

2.6 HUMPBACK WHALE (MEGAPTERA NOVAEANGLIAE)

2.6.1 Legal Status

The humpback whale is classified as endangered under the ESA and depleted under the MMPA 

throughout its range. The species is classified in the “Least Concern” category under the IUCN 

(Reilly et al. 2008d). 

2.6.2 General Distribution

Humpback whales are found in all major oceans from the equator to sub-polar latitudes and 

typically migrate between tropical mating and calving grounds and temperate feeding grounds. 

The summer range in the western North Atlantic extends from the Gulf of Maine to the Davis 

Strait (BOEM North Atlantic Planning Area) and the primary winter distribution is in the West 

Indies, from Cuba to Venezuela (Reilly et al. 2008d). High resighting rates of humpbacks in the 

southern Gulf of Maine as well as high rates of annual return to the area were measured by 

Clapham et al. (1993). Average occupancy in the area was 88.1 days, and the mean rate of return 

of individuals in consecutive years was 73.2%. Stevick et al. (2003a) found temporal differences 

in occupancy of the West Indies breeding grounds between humpbacks from different feeding 

aggregations, with individuals from the Gulf of Maine and eastern Canada arriving earlier than 

those from Greenland, Iceland, and Norway. Males were also seen earlier on the breeding 

grounds than females. Sighting and stranding locations of humpback whales are shown in Figure 

2.6-1.

2.6.3 General Abundance

The abundance of humpback whales breeding in the West Indies was estimated at 10,752 for the 

years 1992-93 (CV=0.068); an estimated annual rate of increase at that time was 3.1% (SE 0.5%) 

(Stevick et al. 2003b). The best abundance estimate for the Gulf of Maine stock of humpback 

whales is 847 animals (CV=0.55), based on a NMFS sighting survey in 2006 that covered waters 

from the southern Gulf of Maine to the upper Bay of Fundy and the Gulf of St. Lawrence 

(Waring et al. 2011). North Atlantic humpback abundance data were analyzed using a spatiallyexplicit population dynamics model which confirmed the population increase (Punt et al. 2007). 

2.6.4 Habitat Preference

Dalla Rosa (2010) modeled the feeding habitats of humpback whales in the waters of both 

British Columbia and Antarctica. Humpback whale distribution within the foraging habitat was 

shown to be influenced by physical and biological factors such as complex topography and 

temperature fronts that increased biological productivity. Distributions of humpback whales were 

highly correlated with sea surface temperature fronts in the Gulf of St. Lawrence (DoniolValcroze et al. 2007). Hamazaki’s cetacean habitat prediction model classifies the humpback as a 

North Atlantic shelf species (Hamazaki 2002). Summer sightings were associated with mean 
32

water temperatures of 17.2°C, mean depths of 261 m, mean bottom slope of 0.7° and front 

probability of 6.3%.

Warm and shallow waters are preferred habitat on the winter breeding grounds, and spatial 

habitat modeling has been used to predict habitat use in the Hawaiian Islands (Johnston et al. 

2007). Depths less than 200 m and water temperatures greater than 21.1° C were identified as 

potential wintering habitat. Within a breeding site, variation in habitat use has been shown to be 

linked to behavioral class, with mother-calf pairs showing a preference for shallower water 

compared to other group types (Ersts and Rosenbaum 2003). Habitat use between sites in a 

breeding region has also been shown to vary with reproductive status (Craig and Herman 2000).

2.6.5 Stock Structure

Worldwide, approximately 13 stocks have been identified that winter in tropical and sub-tropical 

waters (National Marine Fisheries Service 1991). Six distinct feeding aggregations have been 

identified for North Atlantic humpbacks: Gulf of Maine, Gulf of St Lawrence, 

Newfoundland/Labrador, West Greenland, Iceland, and North Norway (Reilly et al. 2008d), 

although Stevick (2006) suggested, from examination of movement patterns, these may represent 

only four separate aggregations. Although these are relatively disjunct aggregations, whales 

from different feeding grounds mix on the North Atlantic breeding grounds (Reilly et al. 2008d). 

In other regions, analysis of migratory patterns and genetics has suggested the occasional overlap 

of individuals from populations in opposing hemispheres on the low-latitude breeding grounds 

(Rizzo and Schulte 2009), although high genetic heterogeneity suggests this gene flow is 

minimal (Valsecchi et al. 1997). While Palsbøll et al. (1995) observed apparent genetic 

homogeneity within the four western North Atlantic feeding aggregations, more recent studies 

mentioned in Clapham et al. (2003) found significant difference in mtDNA haplotype 

frequencies from these four feeding areas and spatial analysis of sighting data (Vigness-Raposa 

et al. 2010) supported the distinct nature of these units. Humpback whales observed in waters 

off the U.S. mid-Atlantic coast were compared to photos in catalogues of whales from the Gulf 

Maine and from other North Atlantic feeding areas (Barco et al. 2002). Most of the positive 

matches were made with Gulf of Maine whales; however, Newfoundland and Gulf of St. 

Lawrence whales were also represented. 

2.6.6 Life History Traits 

Data based on whaling records revealed that the average age of sexual maturity in females is 

approximately 5 years (Chittleborough 1965). Local sighting data collected for individually 

identified humpback whales were used to obtain an estimate of 5 years for youngest age at first 

parturition, 2.38 years for mean birth interval, 0.960 for noncalf survival rate and 0.875 for calf 

survival rate (Barlow and Clapham 1997). A significantly higher survival rate for females than 

for males was found by Ramp et al. (2010). Promiscuous mating by humpbacks was genetically 

confirmed by Clapham and Palsbøll (1997). Association patterns of mother/calf humpback 

whale pairs in the southern Gulf of Maine were examined by Sardi et al. (2005). 

2.6.7 Food Habits

Humpback whales feed on a variety of schooling fish species and euphausiids (Robbins 2007), 

with sand lance (Ammodytes spp.) identified as the primary prey species in the southern Gulf of 

Maine and herring (Clupea harengus) in the northern part. Fluctuations in humpback abundance 
33

within the Stellwagen Bank National Marine Sanctuary appear closely tied to fluctuations in 

availability of sand lance (Payne et al. 1990). Diel patterns in humpback foraging behavior 

concurrent with changes in prey behavior were demonstrated by Friedlaender et al. (2009) on 

Stellwagen Bank, Massachusetts. Surface feeding occurred more during daylight hours and 

bottom feeding took place largely at night.

The diets of fin whales and humpback whales in the Gulf of S. Lawrence were compared using 

blubber fatty acid analysis (Borobia et al. 1995). The chemical and isotopic differences found 

indicated that humpbacks fed at a slightly lower trophic level than fin whales.

Two principal categories of feeding behaviors were described for humpback whales in the 

continental shelf waters of the northeastern U.S.: swimming/lunging behaviors and bubbling 

behaviors (Hain et al. 1982). Recent work off Stellwagen Bank, Massachusetts, has described in 

detail two general patterns of bubble-net feeding behavior (Wiley et al. 2011). Additionally, 

quantitative measures of humpback underwater behavior while foraging were obtained through 

the use of combining digital acoustic recording devices (DTAGs) on the whale with highfrequency acoustic sources deployed from small boats following the tagged whale (Ware et al. 

2006; Schmidt et al. 2010).

In the North Pacific, acoustic time-depth transmitters on humpbacks off Kodiak, Alaska,

revealed that the whales were foraging primarily between 92 m and 120 m and concentrating on 

areas with maximum capelin densities (Witteveen et al. 2008). The number of lunges executed 

per dive and the respiratory frequency between dives were examined used digital tags on 

humpback whales off California’s central coast (Goldbogen et al. 2008). Maximum dive 

durations during foraging were found to be approximately half as long as those reported for nonfeeding whales and respiratory rates much higher, suggesting that lunge feeding carries a high 

energetic cost for humpback whales.

2.6.8 Health

2.6.8.1 Strandings

Humpback whales strand fairly regularly along the U.S. Atlantic coast. Thirty-eight stranded 

humpbacks were recorded in the mid-Atlantic and southeast U.S. in the period 1985-1992 (Wiley 

et al. 1995). For 20 of these a cause of death was able to be determined and over half of those 20 

indicated anthropogenic factors that contributed to their death. One hundred and fifteen 

confirmed humpback whale mortalities were reported in the mortality and serious injury report 

for the period 2005-2009 (Henry et al. 2011). This figure includes anthropogenic and nonanthropogenic mortalities.

Humpback whales were involved in Unusual Mortality Events (UMEs) in 2003 when 12-15 

humpback whales died in the vicinity of the Northeast Peak of Georges Bank, in a 2005 large 

whale UME which involved seven humpbacks in New England, and in a 2006 UME which 

involved 21 humpbacks (Waring et al. 2011). Causes of these UMEs are unresolved.
34

2.6.8.2 Contaminants

Blubber samples taken from humpback whales in the Gulf of St. Lawrence, Quebec, in summer 

and fall of 1991 and 1992 were tested for chlorinated biphenyls and other persistent 

organochlorine compounds (Gauthier et al. 1997). Subsequent work confirmed those results and 

also found that there were no significant differences in the concentrations of contaminants 

between females and calves, suggesting that calves are susceptible to bioaccumulation of 

contaminants through placental and lactational transfer (Metcalfe et al. 2004). Comparisons of 

contaminant loads between North Pacific and North Atlantic humpback whales showed that 

North Atlantic (Gulf of Maine) whales had higher levels of PCBs, polybrominated diphenyl 

ethers (PBDPEs) and chlordanes, while North Pacific whales that fed off southern California had 

the highest levels of DDTs (Elfes 2008; Elfes et al. 2010). 

2.6.8.3 Disease

Bacterial communities associated with the skin of both healthy and health-compromised North 

Pacific humpback whales were investigated by Apprill et al. (2011). The dinoflagellate 

neurotoxin, saxitoxin, was responsible for the deaths of 14 humpback whales in 

November/December 1987 (Geraci et al. 1989). 

2.6.9 Acoustics

Humpback whales produce a variety of acoustic signals, both vocalizations and surfacegenerated signals, such as breaching or pectoral slapping. In some cases, humpbacks may switch 

from primarily vocal communication to surface-generated communication when wind speed or 

background noise levels increased (Dunlop et al. 2010). 

Singing behavior by male humpbacks is well-studied but still only partially-understood. The 

function of humpback song is generally thought to serve to attract females (Tyack 1981) or to 

mediate interaction between males, either as a spacing mechanism (Frankel et al. 1995) or in the 

establishment of dominance hierarchies (Darling 1983; Darling and Bérubé 2001). Recent work 

has shown that males do use song to mediate intra-sexual interactions (Cholewiak 2008). 

Extensive work on song has both described song structure as well as considered other hypotheses 

as to the function of song (for example, Cerchio et al. 2001; Darling 1983; Frazer and Mercado 

2000; Parsons et al. 2008). Singing in high-latitude feedings areas has also been documented. 

Off the coast of Massachusetts, Matilla et al. (1987) found that song may be common in the fall 

prior to migration, and Clark and Clapham (2004) documented song in spring and early summer 

post-migration. Singing in this context may include full renditions or abbreviated versions of 

song (McSweeney et al. 1989). The occurrence of song at these times of year is thought to be 

linked to seasonal elevations in hormone levels occurring near the breeding season.

Compared to song, non-song vocal activity has been relatively little studied. Research along the 

eastern Australian migratory routes described and quantified “social” vocalizations (Dunlop et al. 

2007), and discussed their use relative to social context (Dunlop et al. 2008). Based on digital 

acoustic tag data collected in the Stellwagen Bank National Marine Sanctuary, Massachusetts, 

Stimpert et al. (2011) classified non-song humpback vocalizations into eight types with similar

acoustic properties and identified two of these types (“wops” and “grunts”) as candidates for use 

in passive acoustic monitoring. Increased humpback call rates were observed associated with 
35

group-forming behavior in the Stellwagen Bank National Marine Sanctuary, leading researchers 

to believe that vocalization plays a role in the social cohesion of feeding groups (Palmer et al. 

2010). Recordings of humpback click production associated with nighttime lunge feeding were 

reported by Stimpert et al. (2007). Humpback sounds recorded on the northwestern Atlantic 

feeding grounds were described and compared to those recorded on the Hawaiian breeding 

grounds by Stimpert et al. (2008a).

A predicted humpback audiogram and bandpass model of the humpback ear were developed by 

Hauser et al. (2001), with a zone of maximum sensitivity found to be in the 2-6 kHz range. 

When exposed to low-frequency active sonar, humpbacks were found to increase song length 

(Miller et al. 2000; Fristrup et al. 2003).

The effects of shallow-water propagation of humpback whale sounds were examined by 

Mercado and Frazer (1999). It was found that the whales would adjust their positions and sound 

production in response to environmental factors. The acoustic field in the vertical plane of 

singing humpback whales was measured by Au et al. (2006). It was found that sounds were 

projected in the horizontal direction regardless of the orientation of the singer. Source levels 

varied between 151 and 173 bd re 1 μPa and high-frequency harmonics extended beyond 24 

kHz. 

2.6.10 Fisheries By-catch and Entanglement

Humpback whale interactions have been reported for pot/trap, purse seine, trawl and gillnet 

fisheries along the U.S. Atlantic coast (Fertl and Leatherwood 1997; Waring et al. 2011). 

Analysis of Gulf of Maine humpback caudal peduncle photographs has yielded evidence that 

between 48% and 65% of each annually collected sample of photographs show evidence of 

entanglement scarring (Robbins and Mattila 2001). Twenty-five percent (5 out of 20) of 

humpback whales stranded along the mid-Atlantic and southeast Atlantic coast of the U.S. 

between 1985 and 1992 had injuries consistent with possible entanglement in fishing gear (Wiley 

et al. 1995). Volgenau et al. (1995) examined the impact of entanglement mortality on 

humpbacks and found that when entanglement losses were added to natural mortality estimates 

and subtracted from birth rate estimates, annual mortality rates were 5.4% for the Newfoundland 

and Labrador substock and 4.8% for the Gulf of Maine substock. Increases in fishery 

entanglement rates were linked to industrial activity in Trinity Bay, Newfoundland (Lien 1993; 

Todd et al. 1996).

2.6.11 Vessel Interactions

Analysis of humpback whales stranded along the mid-Atlantic and southeast Atlantic coast of the 

U.S. between 1985 and 1992 showed that 6 out of 20 of the animals examined had injuries likely 

attributable to ship strike (Wiley et al. 1995). The detected annual average mortality and serious 

injury rate due to ship strike for humpback whales from the Gulf of Maine stock for the years 

2005-2009 was 1.4 (Henry et al. 2011). 

The effect of whale watch vessel exposure on humpback calving rates and calf survival was 

investigated by Weinrich and Corbelli (2009). No direct evidence for negative effects was 

found. Behavioral differences were found, however, in humpbacks in Hervey Bay, Australia 

when in the presence of vessels (Corkeron 1995). For instance, whales were more likely to dive 
36

rather than slip underwater when within 300 m of a vessel. Au and Green (2000) characterized 

the underwater noise produced by five representative whale-watching boats used in the Hawaiian 

Islands and concluded that the levels of sound produced would not have deleterious effects on 

the auditory systems of humpback whales. Analysis of humpback song in the presence of boat 

noise revealed that while unit duration and phrase duration were shortened, frequency structure 

showed no response (Norris 1994). Measurement of the underwater noise production of the 

Hawaiian super ferry was conducted by Stimpert et al. (2008b) and the potential effects of the 

sounds on humpbacks discussed. 

2.6.12 Energy Projects

Both extractive and renewable offshore energy projects have the potential to impact the marine 

environment in a variety of ways, including habitat alteration and the introduction of noise via 

seismic exploration activities (e.g., airguns), vessel/aircraft activity, construction and operation

(Geraci and St. Aubin 1980, Bain and Williams 2006, Thompsen et al. 2006, Cada et al. 2007, 

Compton 2008, Evans 2008, MMS 2008, Burgman 2010, Boehlert and Gill 2010, Dolman and 

Simmonds 2010, Edrén et al. 2010, Bush 2011, ICES 2011). The impact of these activities on 

marine mammals is unclear. Humpback response to the acoustic impacts of petroleum industry 

activities was tested in 1984 off southeast Alaska (Malme et al. 1985). Airgun sound was 

produced as well as playbacks of recorded drillship, drilling platform, production platform, semisubmersible drill rig, and helicopter fly-over noise and behavior of humpback whales in the area 

monitored. No clear avoidance to the area was observed. The fact that humpbacks are 

susceptible to severe blast trauma was demonstrated by examination of the temporal bones from 

two humpback whales which died following a 5,000-kg explosion in Trinity Bay, Newfoundland 

(Ketten et al. 1993). Long-term exposure to industrial activity in Trinity Bay was also linked to 

increased fishery entrapment rates (Lien 1993; Todd et al. 1996), and to decreases in return rates 

of photographically-identified whales (Borggaard et al. 1999). In 2002, an unusual increase in 

humpback whale strandings near Abrolhos Bank, Brazil coincided with 3D seismic surveys 

conducted in the area (Engel et al. 2004). Low levels of localized avoidance were found in 

mysticetes exposed to seismic airgun noise in the UK and adjacent waters investigated in 1997-

2000 (Stone and Tasker 2006). A decrease in the detection of humpback whale singers was 

significantly correlated with seismic survey activity off the coast of Gabon (Cerchio et al. 2011), 

indicating that seismic activity may interrupt male breeding displays.

2.6.13 Data Gaps and Research Recommendations

The ongoing analysis of genetic data collected in the large-scale assessment called the More of 

North Atlantic Humpbacks (MoNAH) project, in which sampling was conducted on humpbacks 

in the Gulf of Maine/Scotian Shelf region and the primary wintering ground in the West Indies 

during 2004-2005 will refine knowledge of the North Atlantic humpback whales’ population 

structure and help with updating abundance estimates. Further development of acoustic methods 

for estimating humpback abundance and distribution is also necessary to increase our knowledge 

of humpback habitat use and population dynamics.

Humpback whale research recommendations outlined in the recovery plan (National Marine 

Fisheries Service 1991) include maintaining and enhancing habitats used by humpback whales 

currently or historically; identifying and reducing direct human-related mortality, injury and 
37

disturbance; measuring and monitoring key population parameters; and improving administration 

and coordination of recovery programs.

2.7 SPERM WHALE (PHYSETER MACROCEPHALUS)

2.7.1 Legal Status

The sperm whale is classified as endangered under the ESA and depleted under the MMPA 

throughout its range. The species is classified in the “vulnerable” category under the IUCN 

(Taylor et al. 2008). 

2.7.2 General Distribution

Sperm whales are widely distributed in all major oceans and are typically found in continental 

slope or deeper water (Taylor et al. 2008). Off the U.S. Atlantic coast, sightings of sperm whales 

are concentrated along the shelf break from Cape Hatteras to Georges Bank (Figure 2.7-1), 

primarily in BOEM mid-Atlantic and North Atlantic planning areas. Sighting and stranding 

locations of sperm whales are shown in Figure 2.7-1.

2.7.3 General Abundance

Worldwide sperm whale abundance is estimated to be approximately 360,000 (CV=0.36: 

Whitehead 2002). Pre-whaling abundance was estimated at 1,110,000 whales (95% CI: 672,000 

to 1,512,000) in 1999, thus, ten years after the end of large-scale whaling for this species, the 

population size was at 32% of its original level (Whitehead 2002). For the Western North 

Atlantic stock of sperm whales, the best recent abundance estimate is 4,804 (CV=0.47). This is 

the sum of the estimate derived from a summer 2004 northern U.S. Atlantic survey (2,607, 

CV=0.57) and an estimate derived from a summer 2004 southern U.S. Atlantic survey (2,195, 

CV=0.47) (Waring et al. 2011). 

2.7.4 Habitat Preference

Sighing data from summer shipboard sighting surveys between 1990 and 1998 were analyzed to 

determine habit use with respect to bathymetric and oceanographic features (Waring et al. 2001). 

Sperm whale sightings were associated with warm (mean of 23.9°C), deep (mean of 1942 m) 

water, with sighting rates slightly higher at canyon features. Warm core ring eddies from the 

Gulf Stream along the shelf-edge were also found to be significant habitat areas (Waring et al. 

1993; Griffin 1999). Association of sperm whales and sea surface temperature fronts in the 

Mediterranean was noted by Gannier and Prace (2007). Along the Mid-Atlantic Ridge, sperm 

whales were found to be associated with cross-seamount or cross-frontal structures (Skov et al. 

2008). Hamazaki’s cetacean habitat prediction model classifies the sperm whale as a midAtlantic offshore species (Hamazaki 2002). Summer sightings were associated with mean water 

temperatures of 22.5°C, mean depths of 2,011 m, mean bottom slope of 1.9° and front 

probability of 6.5%.

Scott and Sadove (1997) reported on sightings of sperm waters in shallow shelf waters off Long 

Island, New York between 1983 and 1984. These whales were seen mostly in late spring or 
38

early summer in waters that ranged from 41 m to 68 m in depth. It was speculated that the 

whales were taking up short-term residency in the area as they followed prey inshore. 

2.7.5 Stock Structure

The International Whaling Commission recognizes one stock for the North Atlantic; whether the 

western North Atlantic population is discrete from the eastern North Atlantic population is 

unresolved (Waring et al. 2011). Low geographic structure and genetic diversity have been 

reported (Reeves and Whitehead 1997; Lyrholm and Gyllensten 1998; Dufault et al. 1999; 

Lyrholm et al. 1999; Engelhaupt 2004). However, strong genetic differentiation was found 

between social groups and mtDNA heterogeneity indicated moderate genetic differentiation on a 

global scale (Lyrholm and Gyllensten 1998; Lyrholm et al. 1999). Drouot (2003) reported 

genetic differentiation in mtDNA between samples from Mediterranean and North Atlantic 

sperm whales. Engelhaupt et al. (2009) demonstrated significant mtDNA subdivision between 

Gulf of Mexico, Mediterranean and North Atlantic samples, suggesting fidelity to coastal basins. 

Eighteen new single nucleotide polymorphism markers were characterized for the sperm whale 

by Morin et al. (2007). These are the first such markers designed for genotyping sperm whale 

populations.

Groups of female sperm whales have distinctive vocalization patterns or codas that may be more 

indicative of stock or substock structure than genetics. Coda repertoires are geographically 

specific at finer spatial scales than genetics (Whitehead 2003). Sperm whale populations are 

structured more along social lines than geographic ones, and culture may play an important 

evolutionary role (Whitehead 1998, 2003). The social organization of sperm whales is an 

important focus of current research (Whitehead et al. 1991; Whitehead 1996, 1998, 2003; 

Richard et al. 1996; Christal et al. 1998; Mesnick 2001; Christal and Whitehead 2001; Lettevall 

et al. 2002; Gero et al. 2007; Gero and Whitehead 2007; Pinela et al. 2009).

2.7.6 Life History Traits

Age at maturity for female sperm whales is approximately 9 years of age (Whitehead 2003). 

Females have one calf every 4-6 years, and will nurse the calf for approximately 2 years. 

Females and juveniles will stay together in social groups in tropical and temperate latitudes, 

while males leave the group at the age of 3-15 and migrate to higher latitudes, forming bachelor 

groups when young and travelling more singly as they age. 

2.7.7 Food Habits

Sperm whales have a diverse diet which, in most areas, consists primarily of squid species 

(Whitehead 2003; Simon et al. 2003; Davis et al. 2007). Tagging of sperm whales and jumbo 

squid (Dosidicus gigas) in the Gulf of California showed that the dive depth of the sperm whales 

generally coincided with the depth range inhabited by the squid (Davis et al. 2007). Stomach 

contents of sperm whales stranded in Denmark, Scotland, Ireland and the Netherlands were all 

primarily composed of cephalopod beaks of the species Gonatus fabricii (Santos et al. 1999, 

2002; Simon et al. 2003). Stomach samples from sperm whales caught off the west coast of 

Iceland, however, were predominantly composed of fish of the species Cyclopterus lumpus, 

Sebastes sp., and Lophius piscatorius (Roe 1969). Sperm whales in the Gulf of California were 

shown to change their distribution in response to changes in distribution of their main prey in 

that area–jumbo squid (Dosidicus gigas) (Jaquet and Gendron 2002; Jaquet et al. 2003).
39

Sperm whale diet in the South Pacific was studied by Marcoux et al. (2007) by measuring carbon 

and nitrogen isotope ratios in sloughed skin samples and in squid beaks from fecal samples. 

Variation in diet was examined across region, year, social group and vocal clan, with significant 

differences found between groups and between clans, suggesting differential use of microhabitats. Exploration of isotope ratios in Gulf of California sperm whales revealed that females 

and immature males had a predator-prey relationship with jumbo squid, but adult males did not 

(Ruiz-Cooley et al. 2004). It was theorized that the males’ isotopic signature was indicative of 

an earlier high-latitude feeding ground. Isotope ratios in sperm whale teeth have also been 

examined, with differences in sex, age, and region indicating this as a useful technique in 

studying ontogenetic movements and dietary histories of this species (Mendes et al. 2007a, 

2007b).

The hypothesis that sperm whales use echolocation for prey capture was supported by DTAG

recordings of sperm whales in the Ligurian Sea and in the Gulf of Mexico (Miller et al. 2004). 

During foraging dives the whales produced regular clicks and rapid-click buzzes called “creaks.”

Creak production was highest at the bottom of the dive, when the animal was also noted to be 

actively maneuvering its body position. Palka et al. (2007), in an acoustic tagging study 

performed in 2003 off the northeast and mid-Atlantic shelf, also found that, while the majority of 

creaks occurred near the base of the dive, occasional shallow creaks and continued clicking through the 

ascent may indicate opportunistic foraging at shallower depths. An alternate theory of foraging 

behavior was presented by Fristup and Harbison (2002), who suggested that optical cues might 

play an important role.

Creak production and diving behavior were also observed in the northwestern Mediterranean, 

where creaks were assumed to correlate with feeding events and both number of creaks produced 

per dive and dive time were correlated with body size of the whale (Drouot et al. 2004). Number 

of creaks per dive was observed to be consistent between Atlantic Ocean, Gulf of Mexico, and 

Ligurian Sea sperm whales (Watwood et al. 2006). Duration of the foraging phase of dives, 

percentage of dive time in foraging phase, and average dive cycles were also consistent across 

regions, although maximum dive depth did vary. A sperm whale tagged with a suction-cup time 

depth recorder off Japan was shown to execute repeated dives to 400-1200 m with dive durations 

of 30-45 minutes (Amano and Yoshioka 2003). In the Gulf of California, in 10 instances sperm 

whales were observed diving to the depth of the acoustic backscatter layer and returning with 

jumbo squid in their jaws and in one instance returning with an unidentified fish (Gallo-Reynoso 

et al. 2009). Average depth of dive was 342 m, average dive time was 23 minutes, and average 

interval between dives was 6 minutes. Dive behavior of sperm whales off the coast of Japan was 

studied at two locations (Aoki et al. 2007). At the Ogasawara Islands, there was a distinct diel 

pattern of diving and whales dived deeper and swimming faster during the day, but along the 

Kumano Coast no diel rhythm was observed.

2.7.8 Health

2.7.8.1 Strandings

Sperm whale strandings, both mass- and single strandings, have been reported in many areas of 

the world (Evans 1997; Whitehead 2003; Pierce et al. 2007; Mazzariol et al. 2011). Various 
40

explanations have been suggested. Sperm whale stranding events along the North Sea coastline 

have been correlated with geomagnetic anomalies (Vanselow et al. 2009) and with positive 

temperature anomalies (Pierce et al. 2007). Lunar cycles have also been correlated with sperm 

whale strandings (Wright 2005). The stranding rate of sperm whales in the British Isles showed 

a marked increase since 1970 (Goold et al. 2002). Goold et al. (2002) also found that almost all 

of the sperm whales stranded on the British and eastern Canadian coasts were males. Eighteen 

sperm whales were reported stranded along the U.S. Atlantic coast and Puerto Rico during 1994-

2000 and 15 were reported during 2001-2005 (Waring et al. 2011).

2.7.8.2 Contaminants

Aguilar (1983) measured residues of DDE, Dichlorodiphenyldichloroethane (DDD), DDT, and 

PCB in sperm whales caught off Spain's northwestern coast. Females were found to be more 

contaminated by organochlorine compounds than males, but overall levels were similar to levels 

found in sperm whales from other areas of the northern hemisphere and to be intermediate 

compared to other cetaceans. Global mean levels of chromium in sperm whale skin tissue were 

found to be 28 times higher than mean levels of chromium levels in skin of humans who had no 

occupational exposure (Wise et al. 2009). Levels ranged from 3.3 ± 0.4 μg/g in samples taken 

off the coast of Sri Lanka to 44.3 ± 14.4 μg/g in samples collected from sperm whales near the 

Islands of Kiribati in the Pacific Ocean. Elevated chromium levels were shown to induce 

cytotoxicity and genotoxicity in sperm whale skin fibroblasts (Wise et al. 2011). Heavy metals, 

organochlorines, and polycyclic aromatic hydrocarbons (PAHs) were measured in various tissues 

of sperm whales that had stranded on the southern coast of the North Sea in the winter of 

1994/1995 (Holsbeek et al. 1999). High concentrations of cadmium (up to 300 μg/g), mercury 

(up to 130 μg/g), and PCBs (up to 5 μg/g) were detected but not considered to be the direct cause 

of mortality in any of the animals. Cytochrome P450 1A1 expression is a known biomarker of 

exposure to aryl hydrocarbon receptor agonists (Godard-Codding et al. 2010). Skin biopsies of 

sperm whales from various regions of the Pacific Ocean were analyzed for this biomarker, with 

the aim of establishing a baseline and to reveal regional differences within the Pacific Ocean. 

2.7.8.3 Disease

Observations on natural disease in sperm whales, mostly derived from whaling activities, were 

reviewed by Lambertsen (1997). Osteonecrosis, likely caused by dysbarism (“the bends”) was 

identified in sperm whales by Moore and Early (2004).

2.7.9 Acoustics

Sperm whales vocalize using click sounds for communication and echolocation and this behavior 

has received some important attention in recent publications (Møhl et al. 2000, 2003; Jaquet et 

al. 2001; Ridgway and Carder 2001; Thode et al. 2002; Madsen et al. 2002c, 2002b; Wahlberg 

2002; Rendell and Whitehead 2003, 2004, 2005; Mellinger et al. 2004; Rhinelander and Dawson 

2004; Laplanche et al. 2005; Kandia and Stylianou 2006; Morrissey et al. 2006; Schulz et al. 

2008; Sidorovskaia et al. 2009; See, for example: André et al. 2008; Wahlberg et al. 2005; 

Hirotsu et al. 2009; Whitehead et al. 2006; Zaugg et al. 2010; Zimmer et al. 2005a, 2005b; 

Antunes et al. 2010, 2011). 

The sperm whale click is the loudest sound recorded from a biological source (Møhl et al. 2000), 

and can be heard by other sperm whales at ranges up to 60 km (Madsen et al. 2002c). While 
41

traditionally the clicks had been thought to be multipulsed, recent data show that, in fact, a 

component of the click is monopulsed and highly directional and suitable for use as long-range 

sonar (Møhl et al. 2000, 2003; Zimmer et al. 2005a). Visualizing the beam pattern in three 

dimensions revealed that a component of the click is a narrow and forward-directed sonar signal, 

but less-directional click components may be used to communicate with conspecifics or for 

orientation (Zimmer et al. 2005b). Click production has been shown to happen simultaneously 

with breathing (Wahlberg et al. 2005). A classification system which can separate sperm whale 

clicks from impulsive ship noise during automated acoustic detection has been developed by 

Zaugg et al. (2010).

Acoustic techniques have been developed to estimate sperm whale abundance, or supplement 

visual sighting surveys. Acoustic and visual detection methods were found to result in similar 

abundance estimates in the eastern Pacific (Barlow and Taylor 2005). Due to the increased range 

of detection, and the ability to detect whales at night, more sperm whales were detected with 

acoustic methods; however, visual observations were necessary for group size estimation. 

Acoustic line-transect surveys have been carried out in the Ionian Sea and Mediterranean Sea 

(Lewis et al. 2007). Passive acoustic localization and tracking of sperm whales also has 

applications for minimizing negative interactions with human activities (André et al. 2008; 

André 2009).

Southall et al. (2007) classified sperm whales into the “mid-frequency cetaceans” functional 

hearing group, with an estimated hearing range of approximately 150 Hz to 160 kHz. A stranded 

sperm whale neonate examined during an attempt at rehabilitation made clicks at frequencies of 

500 Hz to 12 kHz and an auditory brainstem response indicated that it was most sensitive to 

sounds in the 5 kHz-20 kHz range (Ridgway and Carder 2001).

2.7.10 Fisheries By-catch and Entanglement

Depredation of longline catches by sperm whales has been reported off the coast of 

Alaska (Sigler et al. 2008; Mathias et al. 2009; Mesnick et al. n.d.). Attraction to fishing vessels 

during net hauling was also reported for sperm whales around the Flemish Cap, in the North 

Atlantic Ocean (Karpouzli and Leaper 2004). Ingestion of floating fishing net debris was 

implicated in the deaths of two sperm whales stranded in Northern California in 2008 (Jacobsen 

et al. 2010). While fishery interactions have been reported in the now-closed pelagic drift gillnet 

fishery and sperm whales have been found entangled with longline and fine-mesh gillnet, no 

fishery interactions were reported for sperm whales in U.S. Atlantic water during the period 

2001-2005 (Waring et al. 2011). The threat to sperm whales from fishery interactions in the 

North Atlantic is categorized in the recovery plan as low (National Marine Fisheries Service 

2010b).

2.7.11 Vessel Interactions

The large whale ship strike database contains 17 records of sperm whales involved with ship 

strike worldwide (out of a total of 292) in the period from 1975 to 2002 (Jensen and Silber 

2003). One sperm whale was reported in NMFS records for the Western North Atlantic stock 

during 2004 through 2008 with sufficient information to confirm the cause of death as a collision 

with a vessel (Waring et al. 2011). The resulting annual rate of serious injury or mortality from 

vessel collisions was 0.2 whales. The threat to sperm whales from ship strikes in the North 
42

Atlantic is categorized in the recovery plan as unknown but potentially low (National Marine 

Fisheries Service 2010b).

The short-term reaction of sperm whales to whale-watching boats was investigated in the Azores 

by land-based and boat-based observers (Magalhães et al. 2002). Some indications of 

disturbance were observed, such as changes in frequency of aerial display, but no clear pattern 

was found. Richter et al. (2006) also found reactions of sperm whales to whale-watching boats 

off Kaikoura, New Zealand to vary by season and by individual, with some resident whales 

becoming habituated to contact.

2.7.12 Energy Projects

Both extractive and renewable offshore energy projects have the potential to impact the marine 

environment in a variety of ways, including habitat alteration and the introduction of noise via 

seismic exploration activities (e.g., airguns), vessel/aircraft activity, construction and operation

(Geraci and St. Aubin 1980, Bain and Williams 2006, Thompsen et al. 2006, Cada et al. 2007, 

Compton 2008, Evans 2008, MMS 2008, Burgman 2010, Boehlert and Gill 2010, Dolman and 

Simmonds 2010, Edrén et al. 2010, Bush 2011, ICES 2011). The impact of these activities on 

marine mammals is unclear. Madsen and Møhl (2000) recorded click rate measurements and 

behavioral observations of sperm whales during the discharge of detonators off northern 

Norway. No response was detected, perhaps due to the similarity between the detonations and 

sperm whale clicks. Madsen et al. (2002a) also found no response from male sperm whales in 

polar waters exposed to air-gun pulses from a seismic survey. Sound exposure levels of sperm 

whales in the Gulf of Mexico were measured using acoustic tags attached to sperm whales at 

ranges of 1.4-12.6 km from controlled air-gun array sources (Madsen et al. 2006a). Received 

levels varied with depth between 131-167 dB re. 1 μPa, including significant energy at high 

frequencies which could be detrimental to cetacean hearing and cause acoustic masking of sperm 

whale clicks. In a visual sighting survey conducted in the Gulf of Mexico in 1993, significantly 

fewer whales were observed in an area when seismic survey activity was taking place compared 

to the period just prior to the seismic operations (Mate et al. 1994); however, Jochens et al. 

(2008) found no horizontal avoidance to controlled exposure of seismic airgun noise in the Gulf 

of Mexico.

2.7.13 Data Gaps and Research Recommendations

The Sperm Whale Recovery Plan (National Marine Fisheries Service 2010b) identifies key 

actions that should be undertaken to further understand and protect sperm whales. Priorities 

include better understanding of sperm whale population structure; improvement of abundance 

estimates and trends of abundance; improvement of knowledge of sperm whale habitat and 

feeding ecology; steps to minimize sperm whale mortality from anthropogenic sources such as 

ship strike, fishery interaction and pollution; steps to determine and minimize detrimental 

anthropogenic noise; and effective response to strandings of sperm whales.
43

2.8 PYGMY & DWARF SPERM WHALE (KOGIA SPP.)

Two species of the genus Kogia are found in the northwest Atlantic. As it is difficult to 

differentiate species at sea, much of the information available and presented here is only to genus 

level. 

2.8.1 Status

The pygmy and dwarf sperm whales are not listed under the Endangered Species Act. Both 

species are considered “Data Deficient” on the IUCN Red List. They are afforded protection in 

U.S. waters under the MMPA. 

2.8.2 General Distribution

The Kogia spp. are found in temperate and tropical waters throughout the world although their at 

sea distribution is poorly understood (McAlpine 2009). Dwarf and pygmy sperm whales could 

potentially be observed in any of the BOEM planning areas but most observations are likely to 

be in the Mid-Atlantic, South Atlantic or Straits of Florida Planning Areas. Sighting, stranding 

and fishery bycatch locations of dwarf and pygmy sperm whales are shown in Figure 2.8-1.

2.8.3 General Abundance

Data is not available to estimate the total number of Kogia spp. along the U.S. Atlantic coast 

(Waring et al. 2011). The best estimate of Kogia spp. is 395 (CV=0.40), based on a combination 

of aerial and shipboard surveys that took place in 2004 from Florida to Maine. The estimate 

from Florida to Maryland is 37 (CV=0.75) and from Maryland to Bay of Fundy is 358 

(CV=0.44) (Waring et al. 2011).

2.8.4 Habitat Preference

McAlpine et al. (1997) analyzed the stomach contents of pygmy sperm whales and reported that 

the squid prey species identified were typical of the mesopelagic slope-water community. 

McAlpine (2009) reported that prey analyses suggested these animals are generally found on the 

continental shelf and slope in the epi- and mesopelagic areas. Dunphy-Daly et al. (2008) studied 

dwarf sperm whale habitat use in the Bahamas. They found temporal and spatial variation in 

habitat type being used and group size. Generally, the whales were in deeper water during the 

summer. In winter, group size was bigger and the whales were over the slope where vertical 

relief was higher.

2.8.5 Stock Structure

Genetic variation of Kogia spp. was analyzed via mtDNA and cytochrome b markers by Chivers 

et al. (2005). They found the two species to be reciprocally monophyletic to each other. Within 

the Kogia sima samples, the authors identified two clades: one from samples collected in the 

Atlantic and the other from samples collected in the Indo-Pacific. The degree of differentiation 

between the two clades indicated they might be two species.

Arnason et al. (1993) included a pygmy sperm whale in their analysis of baleen whale mtDNA 

control region.
44

2.8.6 Life History Traits

Caldwell and Caldwell (1989) reported that K. sima becomes sexually mature at about 2.1 m. 

McAlpine (2009) reported that male K. breviceps become mature at about 2.7 m with females 

being slightly smaller at sexual maturity.

2.8.7 Food Habits

Dwarf and pygmy sperm whales are suction feeders (Bloodworth and Marshall 2005). McAlpine 

et al. (1997) presented information from stomach contents of pygmy sperm whales that stranded 

in Atlantic Canada. They found squid beaks from Onychoteuthis banksi, Chiroteuthis sp., 

Lepidoteuthis grimaldii, Taonius pavo, Histioteuthis meleagroteuthis, and Histioteuthis corona 

corona. 

Santos et al. (2006) analyzed the stomach contents of pygmy sperm whales that stranded on the 

coasts of Spain and France. Thirteen of the fourteen stomachs contained virtually only 

cephalopod species. West et al. (2009) and Beatson (2007) analyzed the stomach contents of 

pygmy sperm whales that stranded, respectively in Hawaii and New Zealand. They also found 

cephalopods were the dominant prey species. 

2.8.8 Health

2.8.8.1 Strandings

There were a total of 147 Kogia spp. strandings along the U.S. Atlantic coast from 2005-2009 as 

summarized in Table 2.8-1. The majority of these were identified as Kogia breviceps (n=111, 

76%). North Carolina had the highest number of observed strandings (n=27, 18%) followed by, 

South Carolina and Florida.

In January 2005, 33 short-finned pilot whales, 1 minke whale and 2 dwarf sperm whales were 

part of an Unusual Mortality Event (Hohn et al. 2006) along the North Carolina coast. Gross 

necropsies and extensive tissue analyses (clinical pathology, parasitology, gross pathology, 

histopathology, microbiology, and serology) did not find a unifying cause for this event. No 

harmful algal blooms preceded it. The U.S. Navy had conducted routine, tactical, mid-frequency 

sonar operations in the area during the time period. Hohn et al. (2006) were not able to 

definitively link the UME to sonar operations or environmental variables and concluded that it 

was likely that the cause of the stranding event would remain unknown. 

A pygmy sperm found stranded in New Jersey, that had ingested plastic was successfully 

rehabilitated and released (Stamper et al. 2006).
45

Table. 2.8.1. Stranded Pygmy and Dwarf Sperm Whales by Species and Year

State 2005 2006 2007 2008 2009 Total

Ks Kb Sp Ks Kb Sp Ks Kb Sp Ks Kb Sp Ks Kb Sp Ks Kb Sp

ME 0 0 0 0 1 0 0 2 0 0 0 0 0 1 0 0 4 0

MA 0 1 0 0 1 0 0 1 1 0 2 0 1 2 0 1 7 1

RI 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0

NY 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 2 0

NJ 1 0 0 0 0 0 0 1 0 0 1 0 0 2 0 1 4 0

DE 0 0 0 0 2 0 0 2 0 0 0 0 0 0 0 0 4 0

VA 0 0 0 0 1 0 0 6 0 2 0 0 0 0 0 2 7 0

NC 4 5 0 8 7 0 7 5 0 1 4 1 1 6 0 21 27 1

SC 0 8 0 0 1 0 1 3 0 0 5 0 1 6 0 2 23 0

GA 2 3 0 0 2 0 0 1 0 0 3 0 0 2 0 2 11 0

FL 0 3 1 1 2 0 1 5 0 2 5 0 0 6 0 4 21 1

Tot 7 20 1 9 18 0 9 27 1 5 20 1 3 26 0 33 111 3

(Data from the Northeast and Southeast US Marine Mammal Stranding Networks)

2.8.8.2 Contaminants

Bustamante et al. (2003) measured 12 trace elements in the liver, muscle, and blubber of two 

pygmy sperm whales that stranded in New Caledonia. No other contaminant information was 

available.

2.8.8.3 Disease

Fire et al. (2009) tested stranded Kogia spp. from the mid- and southeastern-Atlantic U.S. for 

domoic acid exposure. Fifty-nine percent of the samples they analyzed tested positive. 

Cardiomyopathy and Myocardial degeneration are both conditions that have been documented in 

stranded Kogia spp. It has been documented more often in adults and in males but the etiology is 

not understood (Bossart et al. 2007b). Deardorff and Overstreet (1981) described Terranova 

ceticola from the stomachs of stranded dwarf sperm whales in the Gulf of Mexico. Otherwise, 

McAlpine (2009) wrote little is known about disease in Kogia spp. 

2.8.9 Acoustics

Goold and Clarke (2000) described sound velocity in the head of a dwarf sperm whale across a 

range of temperature and pressure conditions. Marten (2000) described vocalization of a 

stranded male pygmy sperm whale that was in a holding tank. The whale emitted ultrasonic 

clicks peaking at 125 kHz.
46

2.8.10 Fisheries By-Catch/Entanglement

A pygmy sperm whale was seriously injured in a pelagic longline interaction in 2000. No other 

more recent records of fishery interactions exist in the Northeast Fisheries Observer database.

2.8.11 Vessel Interactions

A review of Northeast and Southeast U.S. marine mammal stranding data between 2005 and 

2009 yielded no records of vessel interactions with Kogia spp.

2.8.12 Energy Projects

Both extractive and renewable offshore energy projects have the potential to impact the marine 

environment in a variety of ways, including habitat alteration and the introduction of noise via 

seismic exploration activities (e.g., airguns), vessel/aircraft activity, construction and operation

(Geraci and St. Aubin 1980, Bain and Williams 2006, Thompsen et al. 2006, Cada et al. 2007, 

Compton 2008, Evans 2008, MMS 2008, Burgman 2010, Boehlert and Gill 2010, Dolman and 

Simmonds 2010, Edrén et al. 2010, Bush 2011, ICES 2011). The impact of these activities on 

marine mammals is unclear. No specific information is available about the impact of energy 

projects on Kogia spp.

2.8.13 Data Gaps and Research Recommendations

In general, very little is known about pygmy and dwarf sperm whales. There is no abundance 

estimate for either species of whales in the U.S Atlantic. The limited amount of information 

available about pygmy and dwarf whales comes from parts of their range that is outside of the 

U.S. Atlantic coast (e.g., from the Pacific Ocean). 

2.9 CUVIER'S BEAKED WHALE (ZIPHIUS CAVIROSTRIS)

2.9.1 Status

Cuvier’s beaked whale is not listed under the Endangered Species Act. The status on the IUCN 

Red List is “Least Concern.” It is afforded protection in U.S. waters under the MMPA.

2.9.2 General Distribution

Heyning (1989) reported that stranding records of Cuvier’s beaked whales show that it is found 

in most oceans and seas except in the polar regions. Leatherwood and Reeves (1983a) wrote that 

Cuvier’s beaked whales are one of the most widely distributed cetaceans. Along the U.S. 

Atlantic coast, they are sighted primarily along the continental shelf edge in the Mid-Atlantic 

area (Hamazaki 2002; Palka 2006; Waring et al. 2001). See also MacLeod et al. (2006a) for the 

most recent information on the distribution of beaked whales worldwide. Sighting and stranding 

locations of Cuvier’s beaked whales are shown in Figure 2.9-1.

2.9.3 General Abundance

Barlow et al. (2005) described the challenges (e.g., distribution, survey conditions, ability to 

identify whales to species) in obtaining solid abundance estimates of beaked whales. They 

suggested that passive acoustics could provide identification by vocalization–see Acoustics 
47

section for related studies. Data is not available to estimate the total number of beaked whales 

(Mesoplodon spp. and Ziphius cavirostris) along the U.S. Atlantic coast (Waring et al. 2011). 

The best estimate of undifferentiated beaked whales is 3,513 (CV=0.63) based on a combination 

of aerial and shipboard surveys that took place in 2004 from Florida to Maine (Waring et al. 

2011). The estimate from Florida to Maryland is 674 (CV=0.36) and from Maryland to Bay of 

Fundy is 2,839 (CV=0.78). 

2.9.4 Habitat Preference

Claridge (2006) reported on vessel surveys that were conducted from 1997 to 2002 around Great 

Abaco Island (Bahamas). She found that Cuvier’s beaked whales were found at a mean depth of 

1051 m (SD=111) and they shared offshore habitat with sperm whales (Physeter 

macrocephalus). In the Bay of Biscay, Cuvier’s beaked whale’s distribution was strongly 

correlated with water depths 1000 m to 4000 m and often associated with submarine canyons or 

the continental shelf slope (Smith 2010). Azzellino et al. (2011) used visual observations, 

passive acoustics and environmental data to develop a model that could predict Cuvier’s beaked 

whale presence in the Mediterranean Sea. A study by Gannier (2011) also examined stranding 

and sighting data on Cuvier’s beaked whales in the Mediterranean to characterize favorable 

beaked whale habitats. 

Ferguson et al. (2006) used beaked whale sightings and environmental data to predict whale 

density in the Pacific Ocean. Their results for Ziphius spp. are summarized in Table 2.9-1.

Table 2.9.1.

Environmental Data for Ziphius spp.

Variable Value

Beaufort 2.9

Distance offshore (km) 1097.8

Depth (m) 3445.8

Slope (°) 0.732

Sea Surface Temperature (°C) 26.8

Sea Surface Salinity (psu) 33.9

Surface Chlorophyll Concentration (mg/m3) 0.203

Thermocline Depth (m) 53.9

Thermocline Strength (°/m) 0.367

2.9.5 Stock Structure

Dalebout et al. (2004) created a reference database for twenty beaked whale species (including 

Cuvier’s). The database includes a 437 bp segment of the mtDNA control region, a 384bp 

cytochrome b segment. They compiled an additional database for 17 of the 21 beaked whales 

species of nuclear DNA (925bp actin intron sequences). Despite this study, Barlow et al. (2005)

reported that almost nothing is known about beaked whale stock structure within species. Stock 

structure along the U.S. Atlantic coast is poorly understood (Waring et al. 2011).
48

2.9.6 Life History Traits

Average length of maturity for females is 580 cm and 550 cm for males (Heyning 1989; Heyning 

and Mead 2009). Mean length at birth is 270 cm (Heyning and Mead 2009).

2.9.7 Food Habits

Heyning and Mead (2009) reported that squid were the most common prey item in whales found 

in waters less than 1000 m but fish was the most common prey item in whales in deeper waters. 

They also reported that most prey items are open ocean, mesopelagic, or benthic organisms 

found in deep water. 

MacLeod et al. (2003) reviewed the diets of three beaked whale genera (Hyperoodon, 

Mesoplodon and Ziphius). Their analyses showed that Cuvier’s beaked whale stomachs 

contained cephalopods that were larger than those found in the other two species. Santos et al. 

(2001) found that Cuvier’s beaked whale samples contained a larger range of species than that 

found in sperm whales or bottlenose whales in the northeast Atlantic. In their analyses of niche 

overlap by sperm whales, bottlenose whales, and Cuvier’s beaked whales in the northern 

northeast Atlantic, Santos and Pierce (2005) found that Gonatus sp. and Teuthowenia megalops

were the main prey of Cuvier’s beaked whales. They also found that, of the three whale species, 

Cuvier’s beaked whales fed on the widest size range of Gonatus.

2.9.8 Health

2.9.8.1 Strandings

A total of ten Cuvier’s beaked whales stranded along the U.S. Atlantic coast from 2005 to 2009,

as is summarized in Table 2.9-2. Georgia and Florida both reported the highest number of 

strandings (n=3 for both states). The whale that stranded in Georgia in 2005 had plastic debris in 

its stomach. The 2007 South Carolina whale showed evidence of a boat collision and the 2008 

whale found in New Jersey had ingested fishing line.

Table. 2.9.2

Cuvier’s Beaked Whale Strandings by Year and State 

State 2005 2006 2007 2008 2009 Total

Massachusetts 0 1 0 0 0 1

New Jersey 1 0 0 1(1) 0 2

Georgia 1(1) 1 0 1 0 3

South Carolina 0 0 1(1) 0 0 1

Florida 0 0 2 1 0 3

Total 2 2 3 3 0 10

(The number of whales that showed evidence of human interaction is in parentheses.)

Podesta et al. (2005) analyzed Cuvier’s beaked whale stranding data from the Mediterranean 

Sea. From these analyses they were able to identify geographic stranding areas.
49

2.9.8.2 Contaminants

Storelli et al. (1999) determined the concentration of heavy metals (Hg, Se, Cd, Pb and Cr) in a 

Cuvier’s beaked whale that stranded on the Italian Coast in summer of 1996. Frodello et al. 

(2002) reported on total mercury, lead, cadmium, copper, and zinc that was measured in the 

organs (lung, liver, kidney, skin and bone) in a Cuvier’s beaked whale that stranded in Corsica, 

France.

2.9.8.3 Disease

Several studies have focused on the existence of gas bubble lesions in stranded beaked whales 

(Fernandez et al. 2005; Hooker et al. 2009; Jepson et al. 2003). Jepson et al. (2003) and 

Fernandez et al. (2005) necropsied beaked whales (Cuvier’s, Blainville’s, Gervais), from a total 

of 14 animals that stranded in the Canary Islands in 2002 after being exposed to naval sonar 

activities. They found lesions related to bubble-associated tissue injury (similar to what is 

observed in decompression sickness) and fat embolisms. Rommel et al. (2006) reported that the 

most detrimental effect of sonar on beaked whales is the occurrence of gas bubbles which is 

related to an altered dive pattern or directly from ensonification. Hooker et al. (2009) modeled 

gas exchange and the effects of dive behavior and physiology in three beaked whale species 

(Cuvier’s, Blainville’s, and bottlenose whales). They reported that all three live with partial 

pressure nitrogen (PN2) tissue levels that would be toxic to terrestrial mammals. They also 

suggested that Cuvier’s diving behavior may put them at particular risk of stranding after 

exposure to mid-frequency sonar.

2.9.9 Acoustics

Southall et al. (2007) classified Ziphius into a mid-frequency cetacean functional hearing group 

with an estimated auditory bandwidth of 150 Hz to 160 Hz. Cranford et al. (2008a) described 

Cuvier’s beaked whale anatomy related to acoustic and diving function. Additionally, Cranford 

et al. (2008b) described sound pathways in Cuvier’s beaked whales by using finite-element 

modeling (Vibro-acoustic Toolkit). Zimmer et al. (2005c) quantitatively described Cuvier’s 

beaked whale clicks from the Ligurian Sea.

Zimmer et al. (2008) suggested that passive acoustic devices offer the only reliable way of 

detecting beaked whales given the difficulties associated with detecting them visually. Beaked 

whales appear to be particularly sensitive to underwater sonar. Numerous studies have sought to 

understand the relationship between anthropogenic activities and beaked whale mass strandings. 

The sound sources that have overlapped these stranding events are usually military midfrequency sonar (2-10 kHz) and air gun arrays (used for geophysical exploration) (Barlow and 

Gisiner 2006). MacLeod and D’Amico (2006) reviewed five important areas of beaked whale 

ecology (social structure, life history, foraging/diving, acoustics and habitat) and how 

anthropogenic noise might impact each. D’Spain et al. (2005) described characteristics of the 

sound fields during multiple beaked whale mass strandings (Greece, Bahamas, Canary Islands). 

Similar features among all three events included water depth >1 km but close to land. Also, the 

noise source moved at speeds >5 knots and generated high amplitude pulses (1-10 kHz frequency 

band) (D’Spain et al. 2005).
50

D’Amico et al. (2009) analyzed 126 beaked whale mass stranding events that occurred between 

1950 (time of introduction of powerful, mid-frequency sonar) and 2004 to elucidate the 

relationship between these events and naval exercises. They found that there was likely a high 

number of mid-frequency active sonar events worldwide but a relatively small number of beaked 

whale mass strandings. This led the authors to conclude that several risk factors must occur 

simultaneously in order for a mass stranding to occur.

Tyack et al. (2011) studied how whales responded to simulated (playback of simulated sonar, 

killer whale recordings and band-limited noise) and actual navy activity. They observed a 

disruption in foraging and a movement of whales out of the area (>10 km) in response to actual 

sonar activity. Their results suggest that beaked whales are more sensitive than other species to 

some anthropogenic noise and that a threshold of 140 dB SPL for behavioral response is more 

appropriate.

A Cuvier’s beaked whale (tagged with an acoustic digital tag) exhibited an unusual foraging dive 

in conjunction with a large ship passing by (Aguilar Soto et al. 2006). Although a single 

observation, it led the authors to question the impact of ship noise on beaked whale behavior.

2.9.10 Fisheries By-Catch and Entanglement

In 2003, one undifferentiated beaked whale was seriously injured in the U.S. Atlantic pelagic

long-line fishery. This event led to total annual fishery mortality of one for undifferentiated 

beaked from 2003-2007 (Waring et al. 2011).

2.9.11 Vessel Interactions

One 2007 South Carolina stranded Cuvier’s beaked whale showed evidence of a boat collision. 

It should be noted that beaked whales do appear to be sensitive to sonar activities (see Acoustics 

section).

2.9.12 Energy Projects

Both extractive and renewable offshore energy projects have the potential to impact the marine 

environment in a variety of ways, including habitat alteration and the introduction of noise via 

seismic exploration activities (e.g., airguns), vessel/aircraft activity, construction and operation

(Geraci and St. Aubin 1980, Bain and Williams 2006, Thompsen et al. 2006, Cada et al. 2007, 

Compton 2008, Evans 2008, MMS 2008, Burgman 2010, Boehlert and Gill 2010, Dolman and 

Simmonds 2010, Edrén et al. 2010, Bush 2011, ICES 2011). The impact of these activities on 

marine mammals is unclear. Barlow and Gisiner (2006) reported that air gun activity (for 

geophysical exploration) has overlapped with beaked whale stranding events in space and time. 

These reports indicate that beaked whales are sensitive to anthropogenic noise and might be 

adversely impacted by energy projects. 

2.9.13 Data Gaps and Research Recommendations

The low number of beaked whale sightings in U.S. waters has severely limited the information 

available about them. Most of the information (e.g., stock structure, life history traits, acoustics, 

food habits, or disease) comes from other parts of their range and often from stranded animals. 
51

MacLeod and D’Amico (2006) suggested more cooperation between research groups and also 

using platforms of opportunity to fill in the data gaps that exist for beaked whales worldwide. 

2.10 NORTHERN BOTTLENOSE WHALE (HYPEROODON AMPULLATUS)

2.10.1 Status

The northern bottlenose whale is not listed under the Endangered Species Act. Its status on the 

IUCN Red List is Data Deficient. It is afforded protection in U.S. waters under the MMPA. The 

Scotian shelf (“Gully”) population is listed as endangered by the Committee on the Status of 

Endangered Wildlife in Canada.

2.10.2 General Distribution

Wimmer and Whitehead (2004) report that northern bottlenose whales are found in the North 

Atlantic from ice edge to the Azores. Reeves et al. (1993) report that there are two main areas of 

bottlenose whale distribution in the western north Atlantic: the Gully (east of Sable Island) and 

Davis Strait (off northern Labrador). Wimmer and Whitehead (2004) also sighted bottlenose 

whales in the Shortland (50 km east of Gully) and Haldimand (100 km east of Gully) canyons. 

Waring et al. (2010) reported sightings in 1993 (n=2) and 1996 (n=6) along the southern edge of 

Georges Bank. Mitchell and Kozicki (1975) reported strandings as far south as Rhode Island. 

Given these sighting records, bottlenose whales are likely to be found only in the BOEM North 

Atlantic Planning Area. Sighting and stranding locations of northern bottlenose whales are 

shown in figure 2.10-1.

2.10.3 General Abundance

Northern bottlenose whales were hunted from the 1850s to the 1970s, over 65,000 whales were 

reportedly killed, and many more were likely struck and lost (Reeves et al. 1993). Whitehead 

and Wimmer (2005) estimated the Gully population at 163 animals (95% CI 119-214). The 

number of northern bottlenose whales off the U.S. Atlantic coast is unknown (Waring et al. 

2011). 

2.10.4 Habitat Preference

Northern bottlenose whales are a deep water species that is rarely found in waters less than 2,000 

m (Mead 1989b). They are most often associated with areas of high relief (e.g., submarine 

canyons or shelf edges) (Gowans 2009; Hooker et al. 2002b). They are common over a 

submarine canyon called “The Gully” approximately 300 km east of Halifax, Nova Scotia 

(Gowans 2009). In a long term study on distribution and individual range in the Gully, Hooker 

et al. (2002b) found changes in distribution to the north or south of the canyon which was likely 

due to shift in prey resources. Hooker et al. (2002a) provided information on the energy 

demands and ecological considerations of bottlenose whales in the Gully after this area was 

proposed as a marine protected area. The Gully was designated a marine protected area in May 

of 2004 by the Canadian Government (see http://www.dfo-mpo.gc.ca/oceans/marineareaszonesmarines/mpa-zpm/atlantic-atlantique/factsheets-feuillets/gully-eng.htm).
52

2.10.5 Stock Structure

Whaling catch data suggested at least six centers of distribution that potentially represented 

different stocks: the Gully; Davis Strait; northern Iceland; off Andenes, Norway; off Møre, 

Norway; and Svalbard, Spitzbergen (Benjaminsen 1979). Gowans et al. (2001) studied the social 

organization of bottlenose whales in the Gully. They found that associations within age/sex 

classes were significantly higher than those between different classes but they did not find 

evidence of long-term female bonds.

Dalebout et al. (2001) analyzed a 434bp sequence of the mitochondrial control region in samples 

from the Gully (n=20 biopsy samples), Davis Strait (n=20 museum specimens) and northern 

Iceland (n=5 museum specimens). This analysis found very low genetic diversity among the 45 

animals, suggesting a possible bottleneck event. They also found the distribution of mtDNA 

haplotypes suggested differentiation between the Gully and Davis Strait populations. 

In a subsequent study, Dalebout et al. (2006) used both mtDNA control region sequences and 10 

microsatellite markers to analyze samples from the Gully (n=34 biopsy samples) and Davis Strait 

(n=127; 124 museum specimens, 3 biopsy samples). This study further supported the separation 

of the Gully from the Davis Strait population. It also suggested that both males and females are 

philopatric. Finally, statistical analyses on the microsatellite data did not find evidence of a 

bottleneck. Stock structure is unknown for bottlenose whales in U.S. waters (Waring et al. 

2011). 

2.10.6 Life History Traits

Age at maturity is 7-11 years for males and 11 years for females (Benjaminsen and Christensen 

1979). This data came from carcasses collected off Labrador. Gestation is at least 12 months 

and the oldest animal caught when they were still hunted was 37 years (Gowans 2009). In their 

study on the Gully population, Gowans et al. (2000) found that the sex ratio was approximately 

1:1 and there were the same number of adult and sub-adult males in the population.

2.10.7 Food Habits

Hooker and Baird (1999) used time-depth recorder/VHF radio tags to learn about the diving 

behavior of bottlenose whales. They found that bottlenose whales dove to depths of 800 m or 

deeper and appeared to be foraging near or at the sea floor. Multiple sources report that the deep 

sea squid Gonatus fabricii is an important component of bottlenose whale diet throughout the 

North Atlantic (Benjaminsen and Christensen 1979; Clarke and Kristensen 1980; Lick and 

Piatkowski 1998). Hooker et al. (2001b) analyzed the stomach contents of two sub-adult males 

that stranded in eastern Canada. The squid Gonatus steenstrupi was the dominant prey species in 

both stomachs. In addition to these stomach content analyses, Hooker et al. (2001b) also 

analyzed fatty acid and stable isotope values from 21 whales off eastern Canada (n=3 stranded, 

n=18 biopsied in the Gully). The results of their study confirmed that squid of the genus 

Gonatus play a very important role in the food habits of northern bottlenose whales.
53

2.10.8 Health

2.10.8.1 Strandings

A mother-calf pair of bottlenose whales stranded in Delaware Bay in 2006. They first stranded

in New Jersey and were returned to water. They subsequently re-stranded in Delaware; the 

mother was dead but the calf was returned to water again (Waring et al. 2011). 

2.10.8.2 Contaminants

Hooker et al. (2008) analyzed contaminant concentrations and CYP1A protein expression in 

biopsy samples collected from bottlenose whales in the Gully and Davis Strait. These samples 

were collected before (1996-7) and after (2002-3) near oil and gas development sites. The 

contaminant levels (PCBs and OCs) found in these whales were similar to those in other 

odontocetes in the North Atlantic, although the Gully whales had higher concentrations than 

Davis Strait ones. CYP1A protein expression was higher in the 2003 Gully samples than in 

samples from previous years–this increase may be linked to oil spills related to exploration 

activities. Further, CYP1A protein expression was higher in Davis Strait animals.

2.10.8.3 Disease

Dagleigh et al. (2008) described the first case of fatal mycotic (Aspergillus fumigates) 

encephalitis in a juvenile male bottlenose whale that stranded along the coast of Scotland. They 

note this finding is important as mycotic infections can be indicative of immunosuppression. 

They also reported poxvirus-like lesions in the same animal for the first time in a bottlenose 

whale. 

2.10.9 Acoustics

Southall et al. (2007) classified Hyperoodon into a mid-frequency cetacean functional hearing 

group with an estimated auditory bandwith of 150 Hz to 160 Hz. Winn et al. (1970) described a 

variety of sounds from an opportunistic recording of bottlenose whales in the Gully (e.g. singlepulse clicks, discrete-frequency whistles, sweep-frequency chirps). Hooker and Whitehead 

(2002) analyzed 428 minutes of bottlenose whale recordings from the Gully. They identified 

two types of clicks that differed in their amplitude. One type was heard at greater amplitude, in 

the form of “click trains” (speeding up and slowing down of the clicks). These were produced 

by whales at the surface that were socializing. The second clicks were low amplitude, regular 

clicks, likely produced by animals foraging in deep water.

2.10.10 Fisheries By-Catch and Entanglement

There are no records of fishery interactions for the most recent time period reported (2001-2005) 

in Waring et al. (2011). 

2.10.11 Vessel Interactions 

A review of Northeast and Southeast U.S. stranding data between 2005 and 2009 yielded no 

records of vessel interactions with bottlenose whales. Hooker et al. (2001a) found that whales 

did not avoid the research vessels from which researchers were making biopsy and tagging 

efforts; and often the whales would approach the vessel within minutes of a tag or biopsy 

attempt.
54

2.10.12 Energy Projects 

Both extractive and renewable offshore energy projects have the potential to impact the marine 

environment in a variety of ways, including habitat alteration and the introduction of noise via 

seismic exploration activities (e.g., airguns), vessel/aircraft activity, construction and operation

(Geraci and St. Aubin 1980, Bain and Williams 2006, Thompsen et al. 2006, Cada et al. 2007, 

Compton 2008, Evans 2008, MMS 2008, Burgman 2010, Boehlert and Gill 2010, Dolman and 

Simmonds 2010, Edrén et al. 2010, Bush 2011, ICES 2011). The impact of these activities on 

marine mammals is unclear. Limited information is available about the impact of energy 

projects on northern bottlenose whales. For a discussion of CYP1A protein expression in

relation to energy projects, see the Contaminants section above.

2.10.13 Data Gaps and Research Recommendations

The lack of northern bottlenose whale sightings in U.S. waters has severely limited the 

information available about them. Most of the information (e.g., stock structure, life history 

traits, acoustics, food habits, contaminant burden, or disease) on northern bottlenose whales in 

the western North Atlantic comes from outside U.S. waters in the Gully area in Canada. 

2.11 BEAKED WHALES (MESOPLODON SPP.)

Four species of the genus Mesoplodon are found in the northwest Atlantic: True’s beaked whale 

M. mirus; Gervais beaked whale M. europaeus; Blainville’s beaked whale M. densirostris; and 

Sowerby’s beaked whale M. bidens (Mead 1989a). As it is difficult to identify beaked whales to 

species at sea, much of the information available is only to genus level. 

2.11.1 Status

None of the four species of beaked whales named above are listed under the Endangered Species 

Act. Their status on the IUCN Red List is Data Deficient. All Mesoplodon spp. are afforded 

protection in U.S. waters under the MMPA.

2.11.2 General Distribution

True’s beaked whales are found from Cape Breton, Nova Scotia, to the Bahamas; Gervais’ 

beaked whales are found from Cape Cod into the Gulf of Mexico; Blainville’s beaked whales 

occur from southwest Nova Scotia to Florida; and Sowerby’s beaked whales are reported from 

New England northward to the icepack (Leatherwood et al. 1976; Macleod et al. 2006a; Mead 

1989a). Beaked whales can be found in all four of the BOEM Atlantic Planning Areas. See also 

MacLeod et al. (2006a) for the most recent information on the distribution of beaked whales 

worldwide. Sighting, stranding, and fishery bycatch locations of Mesoplodon beaked whales are 

shown in Figure 2.11-1.

2.11.3 General Abundance

Barlow et al. (2005) described the challenges (e.g., distribution, survey conditions, ability to 

identify whales to species) in obtaining solid abundance estimates of beaked whales. They 

suggested that passive acoustics could provide identification by vocalization–see Acoustics 

section for related studies. Data is not available to estimate the total number of beaked whales 
55

(Mesoplodon spp.) along the U.S. Atlantic coast (Waring et al. 2011). The best estimate of 

undifferentiated beaked whales is 3,513 (CV=0.63) based on a combination of aerial and 

shipboard surveys that took place in 2004 from Florida to Maine (Waring et al. 2011). The 

estimate from Florida to Maryland is 674 (CV=0.36) and from Maryland to Bay of Fundy is 

2,839 (CV=0.78). 

2.11.4 Habitat Preference

Ferguson et al. (2006) used beaked whale sightings and environmental data to predict whale 

density in the Pacific Ocean. Their results for Mesoplodon spp. are summarized in Table 2.11-1.

Table 2.11.1.

Environmental Data for Mesoplodon spp. 

Variable Value

Beaufort 2.9

Distance offshore (km) 1052.0

Depth (m) 3513.6

Slope (°) 0.673

Sea Surface Temperature (°C) 26.3

Sea Surface Salinity (psu) 34

Surface Chlorophyll Concentration (mg/m3) 0.255

Thermocline Depth (m) 56.2

Thermocline Strength (°/m) 0.391

MacLeod and Zuur (2005) analyzed fine scale habitat utilization by Blainville’s beaked whales 

in the Bahamas. They found that aspect, gradient and depth were all related to occurrence. 

Claridge (2006) reported on vessel surveys that were conducted from 1997 to 2002 around Great 

Abaco Island (Bahamas). She found that Blainville’s beaked whales were observed along the 

edge of the Great Bahama Canyon wall at a mean depth of 393 m (SD=283 m). She also found 

habitat partitioning between adult and sub-adult Blainville’s whales with sub-adults occurring 

further offshore in deeper waters. 

In the U.S. Atlantic, beaked whales (Mesoplodon spp.) have been sighted primarily along the 

shelf-edge, continental slope and deeper oceanic waters (Hamazaki 2002; Palka 2006; Tove 

1995; Waring et al. 2001).

2.11.5 Stock Structure

Dalebout et al. (2004) created a genetic reference database for twenty beaked whale species. The 

data base includes a 437 bp segment of the mtDNA control region and a 384 bp cytochrome b 

segment. They compiled an additional database of nuclear DNA (925 bp actin intron sequences)

for 17 of the 21 beaked whale species. Despite this study, Barlow et al. (2005) reported that 

almost nothing is known about beaked whale stock structure within species. Stock structure 

along the U.S. Atlantic coast is poorly understood (Waring et al. 2011).
56

2.11.6 Life History Traits 

Limited information is available on the life history traits of beaked whales. Blainville’s beaked 

whale age at sexual maturity is 9 years (Leatherwood and Reeves 1983a). Physically mature 

Gervais’ beaked whales are 4.5-4.8 m long and their minimum longevity is estimated to be 27 

years (Leatherwood and Reeves 1983a).

2.11.7 Food Habits 

Santos et al. (1994) found mostly fish (whiting and sand eels) remains in a Sowerby's beaked 

whale that stranded in Scotland. MacLeod et al. (2003) reviewed the diets of three beaked whale 

genera (Hyperoodon, Mesoplodon and Ziphius). Mesoplodon spp. stomachs contained the most 

fish and the smallest prey compared to the other two genera.

Tyack et al. (2006) studied the dive behavior of three tagged Blainville’s beaked whales. These 

tagged whales dove to depths between 222 and 1885 m and used echolocation to hunt their prey. 

Tyack et al. (2006) also estimated the whales targeted 30 individual prey per dive. Madsen et al. 

(2005) described the biosonar performance of beaked whales that were foraging using DTAGs. 

See the Acoustic section for other studies on how Blainville’s beaked whales use echolocation to 

forage.

2.11.8 Health 

2.11.8.1 Strandings

The most common species of Mesoplodon to strand along the U.S. Atlantic coast from 2005 to 

2009 was the Gervais’ beaked whale (n=12, 48%). Beaked whales appear to be very sensitive to 

underwater, anthropogenic noise; several mass strandings worldwide have overlapped in space 

and time with military activity. Often these stranded whales have gas emboli likely caused by 

decompression (Fernandez et al. 2005; Jepson et al. 2003). Tyack et al. (2006) studied deep 

diving behavior in beaked whales and suggest that these decompression problems are likely due 

to a behavioral response to sonar. See the Disease and the Acoustics sections below for details.

Table 2.11.1

Blainville’s Beaked Whale Strandings by Year and State 

State 2005 2006 2007 2008 2009 Total

North 

Carolina 1(1) 1 1 1 0 4

South 

Carolina 1 0 1(1) 0 0 2

Total 2 1 2 1 0 6

(The number of whales that showed evidence of human interaction is in parentheses; data from the NE and SE 

stranding network databases)
57

Table 2.11.2

Gervais’ Beaked Whale Strandings by Year and State 

State 2005 2006 2007 2008 2009 Total

New Jersey 0 0 0 1 0 1

Virginia 0 0 1 0 1 2

Maryland 0 0 0 0 1 1

North Carolina 2 0 0 0 1 3

Florida 0 0 1 2 2 5

Total 2 0 2 3 5 12

(The number of whales that showed evidence of human interaction is in parentheses; data from the NE and SE 

stranding network databases)

Table 2.11.3

Sowerby’s Beaked Whale Strandings by Year and State 

State 2005 2006 2007 2008 2009 Total

Virginia 0 0 0 0 2 2

(The number of whales that showed evidence of human interaction is in parenthese; data from the NE and SE 

stranding network databases)

Table 2.11.4

True’s Beaked Whale Strandings by Year and State

State 2005 2006 2007 2008 2009 Total

New Jersey 0 0 1 0 0 1

New York 0 0 1 0 0 1

Total 0 0 2 0 0 2

(The number of whales that showed evidence of human interaction is in parentheses; data from the NE and SE 

stranding network databases)

Table 2.11.5

Unidentified Beaked Whale Strandings by Year and State

State 2005 2006 2007 2008 2009 Total

Rhode Island 0 0 1 0 0 1

North 

Carolina 0 0 1 0 0 1

Florida 1 0 0 0 0 1

Total 1 0 2 0 0 3

(Data from the NE and SE stranding network databases)
58

2.11.8.2 Contaminants

No information was found on contaminant levels in beaked whales.

2.11.8.3 Disease

Several studies have focused on the existence of gas bubble lesions in stranded beaked whales 

(Fernandez et al. 2005; Hooker et al. 2009; Jepson et al. 2003). Jepson et al. (2003) and 

Fernandez et al. (2005) necropsied beaked whales (Cuvier’s, Blainville’s, Gervais), that stranded 

in the Canary Islands in 2002 after being exposed to naval sonar activities. They found lesions 

related to bubble-associated tissue injury (similar to what is observed in decompression sickness) 

and fat embolisms. Hooker et al. (2009) modeled gas exchange and the effects of dive behavior 

and physiology in three beaked whale species (Cuvier’s, Blainville’s, and bottlenose whales). 

They reported that all three species live with PN2 tissue levels that would be toxic to terrestrial 

mammals. In their review of the impact of anthropogenic noise on beaked whales, Cox et al. 

(2006) concluded that gas-bubble disease (resulting from behavioral response to the noise) is a 

plausible explanation for the morbidity/mortality observed in beaked whale mass stranding 

events. Likewise, Rommel et al. (2006) reported that the most detrimental effect of sonar on 

beaked whales is the occurrence of gas bubbles which is related to an altered dive pattern or 

directly from ensonification. 

2.11.9 Acoustics

Southall et al. (2007) classified Mesoplodon into a mid-frequency cetacean functional hearing 

group with an estimated auditory bandwith of 150 Hz to 160 Hz. Cook et al. (2006) used 

auditory evoked potentials to measure the hearing abilities of a juvenile, stranded Gervais’ 

beaked whale. Rankin and Barlow (2007a) described four mid-frequency sounds that were 

recorded near Blainville’s beaked whales in Hawaii.

Several studies on foraging Blainville’s beaked whales have provided additional acoustic 

information. Jones et al. (2008) reported that Blainville’s beaked whales use broadband, 

ultrasonic echolocation signals (-10 dB bandwidth from 26-51 kHz) to search for and catch their 

prey. Johnson et al. (2006) describe two clicks types that occur at different times of foraging. 

The first is “search” clicks (-10 dB bandwidth from 26-51 kHz) occur during prey location and 

“buzz” clicks (-10dB bandwidth from 25-80 kHz) that occur during capture. Johnson et al. 

(2008) suggested that these whales can adjust their echolocation behavior and movement in order 

to catch different types of prey.

Zimmer et al. (2008) suggested that passive acoustic devices offer the only reliable way of 

detecting beaked whales given the difficulties associated with detecting them visually. Advances 

in detection and localization of Blainville’s beaked whale vocalizations in the Bahamas using a 

combination of passive, fixed, acoustic sensors and digital tags (DTags) (Moretti et al. 2006; 

Ward et al. 2008) has led to the development of acoustically-derived estimates of density 

(Marques et al. 2009; Moretti et al. 2006). Beaked whales appear to be particularly sensitive to 

underwater sonar. Numerous studies have sought to understand the relationship between 

anthropogenic activities and beaked whale mass strandings. The sound sources that have 

overlapped these stranding events are usually military mid-frequency sonar (2-10 kHz) and air 
59

gun arrays (used for geophysical exploration) (Barlow and Gisiner 2006). MacLeod and 

D’Amico (2006) reviewed five important areas of beaked whale ecology (social structure, life 

history, foraging/diving, acoustics and habitat) and how anthropogenic noise might impact each. 

D’Spain et al. (2005) described characteristics of the sound fields during multiple beaked whale 

mass strandings (Greece, Bahamas, Canary Islands). Similar features among all three events 

included water depth >1 km but close to land. Also, the noise source moved at speeds >5 knots 

and generated high amplitude pulses (1-10 kHz frequency band) (D’Spain et al. 2005).

D’Amico et al. (2009) analyzed 126 beaked whale mass stranding events that occurred between 

1950 (time of introduction of powerful, mid-frequency sonar) and 2004 to elucidate the 

relationship between these events and naval exercises. They found that there was likely a high 

number of mid-frequency active sonar events worldwide but a relatively small number of beaked 

whale mass strandings. This led the authors to conclude that several risk factors must occur 

simultaneously in order for a mass stranding to occur; quantification of possible contributing 

factors (physical and biological) is necessary. They did find that most beaked whale strandings 

were less than 80 km from 1,000 m depth line.

Tyack et al. (2011) studied how whales responded to simulated (playback of simulated sonar, 

killer whale recordings and band-limited noise) and actual navy activity. They observed a 

disruption in foraging and a movement of whales out of the area (>10 km) in response to actual 

sonar activity. Their results suggest that beaked whales are more sensitive than other species to 

some anthropogenic noise and that a threshold of 140 dB SPL for behavioral response is more 

appropriate.

2.11.10 Fisheries By-Catch and Entanglement 

In 2003 one undifferentiated beaked whale was seriously injured in the U.S. Atlantic pelagic 

longline fishery. This incident led to an estimated annual average fishery-related 

mortality/serious injury of 1 (CV=1.0) for 2003-2007, the most recent time period available 

(Waring et al. 2011).

2.11.11 Vessel Interactions 

A review of Northeast and Southeast U.S. stranding records between 2005 and 2009 yielded no 

records of vessel interactions with beaked whales. It should be noted that beaked whales do 

appear to be sensitive to sonar activities (see the Acoustics section above).

2.11.12 Energy Projects 

Both extractive and renewable offshore energy projects have the potential to impact the marine 

environment in a variety of ways, including habitat alteration and the introduction of noise via 

seismic exploration activities (e.g., airguns), vessel/aircraft activity, construction and operation

(Geraci and St. Aubin 1980, Bain and Williams 2006, Thompsen et al. 2006, Cada et al. 2007, 

Compton 2008, Evans 2008, MMS 2008, Burgman 2010, Boehlert and Gill 2010, Dolman and 

Simmonds 2010, Edrén et al. 2010, Bush 2011, ICES 2011). The impact of these activities on 

marine mammals is unclear. Barlow and Gisiner (2006) reported that air gun activity (for 

geophysical exploration) has overlapped in space and time with beaked whale stranding events. 

These reports indicate that beaked whales are sensitive to anthropogenic noise and might be 

adversely impacted by energy projects. 
60

2.11.13 Data Gaps and Research Recommendations

The low number of beaked whale sightings in U.S. waters has severely limited the information 

available about them. Most of the information (e.g., stock structure, life history traits, acoustics, 

food habits, or disease) comes from other parts of their range and often from stranded animals. 

MacLeod and D’Amico (2006) suggested more cooperation between research groups and also 

using platforms of opportunity to fill in the data gaps that exist for beaked whales worldwide. 

2.12 KILLER WHALE (ORCINUS ORCA)

2.12.1 Status

The killer whale is not listed under the Endangered Species Act. The species is considered “Data 

Deficient” on the IUCN Red List. It is afforded protection in U.S. waters under the MMPA.

2.12.2 General Distribution 

Killer whales are truly cosmopolitan and are found in all of the world’s oceans and most of the 

seas (Ford 2009). Leatherwood and Reeves (1983a) wrote that the only limits to killer whale 

distribution appear to be ice cover, prey and human hunting. Although killer whales are rare in 

the U.S. Atlantic Exclusive Economic Zone, Katona et al. (1988) suggested the possibility of a 

small, migrating population along the U.S. Atlantic coast and a year-round population south of 

35°N. Given their cosmopolitan nature and widespread distribution, killer whales could 

potentially be observed in any of the four BOEM Atlantic Planning Areas. Sighting, stranding 

and fishery bycatch locations of killer whales are shown in Figure 2.12-1.

2.12.3 General Abundance

The killer whale’s widespread distribution and scarceness in most areas make obtaining 

abundance estimates difficult (Ford (2009). The number of killer whales off the U.S. Atlantic 

coast is unknown. The available data are not adequate to calculate a minimum estimate (Waring 

et al. 2011).

2.12.4 Habitat Preference

Killer whales are most abundant in coastal habitats at high latitudes but can also be observed in 

tropical areas and open seas (Dahlheim and Heyning 1999). They are most abundant within 800 

km of the continental coastline (Leatherwood and Reeves (1983a). In their analysis of whaling 

log books from the North Atlantic, Reeves and Mitchell (1988) found that 80% of killer whale 

observations were made on whaling grounds for sperm whales. These whaling logbooks also 

documented widespread offshore observations of killer whales in the North Atlantic. 

2.12.5 Stock Structure

Stock structure for Western North Atlantic killer whales is unknown (Waring et al. 2011). 

Hoelzel et al. (2002) found low worldwide diversity in their analysis of mtDNA control region 

sequences and 7 microsatellite loci. They suggested that the lack of regional diversity is due to 

the matrilineal nature of killer whales and that the worldwide pattern might be due to a 

bottleneck. However, in their 2010 paper, Morin et al. (2010) used high-throughput sequencing 
61

to survey the entire mitochondrial genome. They suggested that the 3 named ecotypes (resident, 

transient and offshore) of killer whales be considered separate species and that two other types 

be considered subspecies. Dispersal from the natal pod is rare and gene flow between local 

populations is male-mediated (Pilot et al. 2010). Foote et al. (2009) used nitrogen isotopes, tooth 

wear and mtDNA to demonstrate ecological divergence of killer whales in the North Atlantic. 

Foote et al. (2010) analyzed 17 microsatellite loci and part of the mitochondrial control region in 

killer whales from the North Atlantic. They found three significantly differentiated populations.

2.12.6 Life History Traits 

As summarized in Ford (2009), females give birth to their first calf at 12-14 years of age. The 

interval between viable calves is approximately 5 years and gestation is estimated to be 15-18 

months. Average female life expectancy is 50 years but some individuals may live to 80-90 

years of age. Killer whale females have a post-reproductive period. Males become sexually

mature at approximately 15 years of age and their average life expectancy is 30 years with a 

maximum longevity of 50-60 years. Most of this information has come from the resident killer 

whale populations off the coast of Washington (U.S.) and British Columbia (Canada). 

2.12.7 Food Habits 

Over 140 prey species (e.g., mysticetes, odontocetes, pinnipeds, fish, and invertebrates) have 

been recorded for killer whales (Ford 2009). Although as a species they are considered 

generalists, certain localized populations have specialized feeding (Ford 2009). Ford et al. 

(2010) found that, although killer whales may consume a variety of species, the fish-eating 

populations they studied in the northeast Pacific are highly specialized and dependent on a single 

species of salmon. Katona et al. (1988) reported the following prey species for killer whales 

found in the western North Atlantic (Bay of Fundy to the Equator): finback, humpback, minke,

and pilot whales, bluefin tuna, mackerel, squid, herring and sea turtles. Mehta et al. (2007)

analyzed scars on baleen whales in high latitude regions. Their results implied that most killer 

whale attacks target young baleen whales (likely on their first trip from calving to feeding 

grounds) and that adult baleen whales are not an important food source for killer whales.

2.12.8 Health 

2.12.8.1 Strandings

There are no records of killer whale strandings along the U.S. Atlantic coast (Waring et al. 

2011). 

2.12.8.2 Contaminants 

Ford (2009) noted that because of their high place in the food web, killer whales are at risk for 

bioaccumulation of contaminants. Ikonomou et al. (2007) showed that accurate PCBs, PCDD/Fs 

and PBDEs levels could be obtained in killer whales using the relatively non-invasive microdart 

technique. Transient killer whales showed higher concentrations of organochlorines than 

resident killer whales in Kenai Fjords/Prince William Sound, AK (Ylitalo et al. 2001). This 

difference is likely due to the differences in food habits. Ylitalo et al. (2001) also found that 

female killer whale OC levels were lower than immature or adult males likely due to offloading 

through gestation and lactation. Biopsy samples from southern resident killer whales in Alaska 
62

were analyzed by Krahn et al. (2007) for persistent organic pollutants and stable isotopes. Rayne 

et al. (2004) analyzed samples from 3 groups in the northeastern Pacific. Their results suggest 

that PBDEs may be a contaminant of concern for these killer whale populations. Ross et al. 

(2000) analyzed blubber samples collected from both transient and resident killer whales off the 

coast of British Columbia, Canada. Their results indicate that these populations are among the 

most contaminated cetaceans. Although there is not a toxic threshold for PCBs in cetaceans, the 

levels in these whales greatly exceeds the adverse effect level established for harbor seals. 

McHugh et al. (2007) analyzed organochlorine and enantiomeric profiles in blubber samples 

collected from killer whales in British and Irish waters. 

2.12.8.3 Disease

Bossart et al. (1996) documented the first case of cutaneous papillomaviral-like papillomatosis in 

a captive ~10-year old killer whale. In their literature review, Gaydos et al. (2003) identified 15 

infectious agents (bacteria, viruses, or fungi) reported for free and captive killer whales. They 

were also able to identify another 28 agents that have been reported for sympatric odontocete 

species. Gaydos et al. (2003) suggested that Brucella spp., cetacean poxvirus, cetacean 

morbilliviruses, and herpesviruses should be studied further given their potential impact on killer 

whale populations. 

2.12.9 Acoustics 

Killer whales are vocal and produce a variety of clicks, whistles and pulsed calls for echolocation 

and communication purposes (Ford 2009). Southall et al. (2007) classified Orcinus sp. into a 

mid-frequency cetacean functional hearing group with an estimated auditory bandwidth of 150 

kHz to 160 kHz. Szymanski et al. (1999) measured the audiograms of two trained, adult female 

killer whales using behavioral responses and auditory evoked potentials (AEPs). They found the 

most sensitive frequency was 20 kHz (36 dB) in the mean audiogram. In their analysis of 

acoustic behavior and surface activity, Simon et al. (2007a) found that feeding whales produced 

high rates of clicks and calls. Multiple studies by Simon et al. (Simon et al. 2006, 2007b)

described the behavior and acoustics of Icelandic and Norwegian killer whales feeding on 

herring (Clupea harrengus). Tyson et al. (2007) documented nonlinearities (e.g., subharmonics, 

deterministic chaos, biphonation, and frequency jumps) in killer whale vocalizations. In their 

study on the acoustic behavior of killer whales observed carousel feeding, Van Opzeeland et al. 

(2005) found that the sequence of call types was more important than the use of isolated call 

types for the coordination of the group.

2.12.10 Fisheries By-Catch and Entanglement

There are no records of fishery interactions for the most recent time period reported (2001-2005) 

(Waring et al. 2011). Prior to that time, one killer whale was caught in the New England 

multispecies sink gillnet in 1994. The whale was released alive.

2.12.11 Vessel Interactions 

Erbe (2002) documented the impacts from the underwater noise of whale-watching boats in 

southern British Columbia and northwestern Washington State (popular areas for killer whale 

watching). A software sound propagation and impact assessment model was used to estimate 
63

zones around the boats where killer whales could hear the boat noise, where the noise affected 

whale communication, where it caused behavioral avoidance, and where it possibly caused 

temporary threshold shift (TTS). Erbe (2002) suggests that these data could be used to develop 

whale-watching guidelines. Holt et al. (2009) studied the effects of anthropogenic sound 

exposure on the vocal behavior of free-ranging killer whales in Puget Sound, Washington, where 

there is a high level of motorized boat traffic. Their results showed that these killer whales 

increased their call amplitude by 1 dB for every 1 dB increase in background noise levels.

In the San Juan Islands, U.S., and Gulf Islands, Canada, Noren et al. (2009) documented killer 

whale surface active behaviors (SABs) in response to closely approaching vessels. Their study 

suggested that the minimum approach distance of 100 m in whale-watching guidelines may not 

be enough to prevent a behavioral response from whales. 

Williams et al. (2002) studied the effect of “leap-frogging” (when whale-watch boats purposely 

cut off a whale in transit) on the behavior of 10 male killer whales in British Columbia. The 

whales responded to leap-frogging by adopting paths less straight and smooth compared to 

control conditions. The authors suggested that this change in path is likely due to the animals 

trying to avoid the boats and may have energetic costs. In another study on the impact of whalewatching boats in British Columbia, Williams et al. (2006b) found that in the presence of the 

boats, time spent foraging decreased, which could increase energetic costs. 

2.12.12 Energy Projects

Both extractive and renewable offshore energy projects have the potential to impact the marine 

environment in a variety of ways, including habitat alteration and the introduction of noise via 

seismic exploration activities (e.g., airguns), vessel/aircraft activity, construction and operation

(Geraci and St. Aubin 1980, Bain and Williams 2006, Thompsen et al. 2006, Cada et al. 2007, 

Compton 2008, Evans 2008, MMS 2008, Burgman 2010, Boehlert and Gill 2010, Dolman and 

Simmonds 2010, Edrén et al. 2010, Bush 2011, ICES 2011). The impact of these activities on 

marine mammals is unclear. Stone (2003) studied the effects of seismic activity on cetaceans in 

UK waters. She reported that killer whales showed some avoidance of seismic activity. 

2.12.13 Data Gaps and Research Recommendations

There is no abundance estimate for killer whales in the U.S Atlantic. Most of the information 

about the killer whales’ life history traits, acoustics, food habits, contaminant burden, or disease 

comes from parts of their range that are outside of the U.S. Atlantic coast (e.g., from the Pacific 

Ocean). 
64

2.13 LONG-FINNED PILOT WHALES (GLOBICEPHALA MELAS)

There are two species of pilot whales in the western Atlantic: the long-finned pilot whales and 

short-finned pilot whales. It is difficult to differentiate the two species at sea; therefore some of 

the information presented here is for Glopicephala spp.

2.13.1 Status 

The long-fined pilot whale is not listed under the Endangered Species Act. The species is 

considered “Data Deficient” on the IUCN Red List. It is afforded protection in U.S. waters 

under the MMPA.

2.13.2 General Distribution 

Long-finned pilot whales are found in the cold temperate waters of the North Atlantic (Olson 

2009). As described in Waring et al. (2010), pilot whales off the U.S. Atlantic coast are found 

primarily along the continental shelf edge in the winter and early spring. They move onto 

Georges Bank and into the Gulf of Maine for the summer and much of fall. Their distribution is 

encompassed by the BOEM North and Mid-Atlantic Planning Areas. Sighting, stranding, and 

fishery bycatch locations of long-finned and undifferentiated pilot whales are shown in Figure 

2.13-1.

2.13.3 General Abundance 

The best estimate of long-finned pilot whales is 12,619 (CV=0.37) based on a combination of 

aerial and shipboard surveys that took place in 2004 and 2006 (Waring et al. 2011). An analysis 

of spatial distribution based on genetic studies and environmental variables such as SST and 

water depth was used to assign pilot whales to species where short and long-finned pilot whales 

overlap (Waring et al. 2011).

2.13.4 Habitat Preference 

Off the U.S. Atlantic coast, short- and long-finned pilot whales are often found over areas of 

high relief (Waring et al. 2011) and are associated with the Gulf Stream wall and thermal fronts 

along the shelf edge (Waring et al. 1992). In his analysis of interaction of marine mammals and 

pelagic longline fishing gear in the U.S. Atlantic, Garrison (2007c) found that pilot whale 

interactions were correlated with warm water temperature and proximity to shelf break. 

Hamazaki (2002) used oceanographic and topographic factors to create a habitat prediction 

model for cetaceans in the western North Atlantic. He placed pilot whales (Globicephala spp.) 

in the Mid-Atlantic shelf category and noted that pilot whales tended to be in cool deep water. 

These studies analyzed two separate data sets and likely reflect differences between short and 

long-finned pilot whales. 

2.13.5 Stock Structure

Pilot whales are social and swim in pods formed along the matriline (Amos et al. 1993a). 

Oremus et al. (2009) analyzed the mtDNA of both long-finned and short-finned pilot whales 

worldwide. They found that both species had low levels of genetic diversity compared to other 
65

widespread cetaceans. They did find structuring between oceanic basins and at the regional 

level. Fullard et al. (2000) used 8 highly polymorphic microsatellite loci to analyze the 

population structure of long-finned pilot whales in the North Atlantic. Their samples came from 

four sites: Cape Cod, U.S.; West Greenland; the Faeroe Islands; and the UK They documented 

substructure and suggested that SST plays a role in population isolation. The Greenland samples 

were the most different. 

Andersen and Siegismund (1994) used three allozyme loci to assess paternity of fetuses caught in 

the Faroe Islands. Fathers of the fetuses were genetically different from males in the pods 

indicating males move into other pods for mating.

2.13.6 Life History Traits 

As summarized in Olson (2009), females become sexually mature at 8 years and males at 12 

years (although successful mating may not happen for several years after that). In the Northern 

Hemisphere, mating appears to occur in spring or early summer and calving in summer or fall. 

Lactation lasts for three years or longer. Although post reproductive females have been 

documented in pods of short-finned pilot whales, they have not been observed in long-finned 

pilot whales (Foote 2008).

2.13.7 Food Habits 

Pilot whales mostly feed on squid (Olson 2009). Only cephalods were found in the stomach 

contents from stranded long-finned pilot whales in New Zealand (Beatson and Ogle 2007). In 

correlating whale occurrence and prey distribution (recorded acoustically), Doksaeter et al. 

(2008) found that cephalopods (especially Gonatus sp.) and Glacier lantern fish (Benthosema 

glaciale) were likely the most important prey species for long-finned pilot whales feeding along 

the Mid-Atlantic Ridge between Iceland and the Azores.

In their analysis of stable isotope ratios, Abend and Smith (1997), identified Atlantic mackerel 

(Scomber scombrus) as another important prey species for long-finned pilot whales in the 

western North Atlantic. Long-finned squid (Loligo pealei) was the most important prey species 

in the stomachs of long-finned pilot whales stranded (n=8) along the U.S. Mid-Atlantic and in 

whales (n=30) inadvertently caught in the Distant Water Fleet (DWF) mackerel fishery of the 

northeast U.S. (Gannon et al. 1997a, 1997b). 

2.13.8 Health 

2.13.8.1 Strandings

There are records of pilot whale mass strandings from the U.S. (Massachusetts, Florida, and 

North Carolina), the Faroe Islands, Ireland, Tasmania, Western Australia, and New Zealand. As 

described in Olson (2009), pilot whales tend to mass strand more frequently than most other 

cetacean species. The whales involved in mass strandings often do not show any sign of disease. 

There is a wide variety of hypotheses (e.g., animals become stuck in shallow water, geomagnetic 

abnormalities may confuse the whales, healthy animals follow a sick one ashore) but why 

healthy animals strand is not currently understood. In some instances, human activities such as 

sonar have overlapped pilot whales strandings in space and time (e.g., North Carolina). 

However, there are records of mass pilot whale strandings long before the invention of sonar 
66

(e.g. Cape Cod 1902, n=~100; New Zealand 1918, n=~1000). Along the U.S. Atlantic coast, 

Cape Cod appears to be a hot spot for long-finned pilot whale mass stranding events. 

Table 2.13.1 summarizes the number of strandings of both long-finned pilot whales (LF) and 

pilot whales only identified to genus (Spp). Massachusetts had the highest number of stranded 

long-finned pilot whales during 2005-2009 (n=35, 51%). The stranded whale in Maine (2007) 

was released alive. Three of the stranded long-finned pilot whales showed signs of fishery 

interactions. 

Table 2.13.1 Long-finned Pilot Whale Strandings by State and Year

State 2005 2006 2007 2008 2009 Total

LF Spp LF Spp LF Spp LF Spp Lf Spp LF Spp

Maine 2 0 1 0 1 0 1 1 3 0 5 1

New Hampshire 0 0 1 0 0 0 0 0 0 0 1 0

Massachusetts 22 0 2 0 6 0 1 1 4 0 35 1

Rhode Island 0 0 0 0 0 0 2 0 2 0 4 0

New York 1 0 0 0 2 0 2 0 1 0 6 0

New Jersey 0 2 0 0 1 0 1 0 1 0 3 2

Maryland 4 0 0 0 0 0 0 0 0 0 4 0

Virginia 4 0 2 0 0 0 0 0 0 0 6 0

North Carolina 1 2 0 1 0 0 0 1 0 0 1 4

South Carolina 0 0 0 0 0 0 0 1 0 0 0 1

Total 35 4 6 1 10 0 7 4 11 0 69 9

(Data from the NE and SE marine mammal stranding response databases.)

2.13.8.2 Contaminants 

Lindstroem et al. (1999) identified 19 tetra- to hexabromindated diphenyl ethers in the blubber of 

pilot whales caught in the Faroe Islands (1994 and 1996). They found that younger whales 

(pooled male and female samples) had higher concentrations of PDBEs than older whales (males 

or females). Muir et al. (1988) identified and measured organochlorines and heavy metals in 

tissue samples from pilot whales (n=41) stranded along the coast of Newfoundland, Canada. 

Age was correlated with mercury levels in liver and blubber, and Cadmium (Cd) in kidney. 

Cadmium levels were higher in these pilot whales than in other whale species from this area. 

Trace elements in the liver and kidney of pilot whales (from 7 different pods) caught around the 

Faroe Islands were measured by Caurant et al. (1994). They found that most metal 

concentrations were higher in females than males. This may be related to differences in feeding 

or metabolism (including hormones) between the two genders. Males are larger than females, so 

there may also be a dilution effect. Contaminant levels also appear to differ among the various 

schools tested.

Borrell et al. (1995) investigated reproductive transfer of organochlorine compounds (DDT, 

PCB) in long-finned pilot whales. Their study showed that mothers transfer 60-100% of their 

body load via lactation and only 4-10% during gestation. Tissues from long-finned pilot whales 

that stranded on the Massachusetts coast were analyzed for orchanochlorines by Tilbury et al. 

(1999). They found evidence of maternal transfer; that contaminant levels varied among 

animals; and that there was significant difference in certain analytes between males and females 
67

(probably due to maternal offloading through gestation and lactation). Alternatively, Weisbrod 

et al. (2001) measured organochlorines in pilot whales from the Gulf of Maine and found no 

gender difference in bioaccumulation.

2.13.8.3 Disease

Duigan et al. (1995a) looked for evidence of morbillivirus infection in long-finned pilot whales 

from the western Atlantic (stranded n=100, by-caught n=1). They found neutralizing antibody 

titers in 92% of the animals. The earliest sign of infection was found in a sample from an animal 

that stranded in 1982. The authors suggest that the social nature of the species, population size 

and migration patterns might facilitate infection. 

2.13.9 Acoustics 

Southall et al. (2007) classified Globicephala sp. into a mid-frequency cetacean functional 

hearing group with an estimated auditory bandwith of 150 kHz to 160 kHz. Weilgart and 

Whitehead (1990) described behaviors and related vocalizations made by long-finned pilot 

whales. Simple whistles were more often heard with resting behavior; whales that were active 

(possible feeding) made more complex whistles and pulsed sounds with greater frequency. In 

their analysis of a rehabilitated, stranded long-finned pilot whale, Pacini et al. (2010) found that 

the region of best hearing was between 11.2 and 50 kHz. The two-year old male had poor high 

frequency hearing compared to other odontocetes. 

Rendell et al. (1999) analyzed tonal calls from five odontocete species. They found that longfinned and short-finned pilot whale calls were distinct. The mean frequency of long-finned pilot 

whales was 4,480 Hz (CV=0.52). Rendell and Gordon (1999) documented the reactions of a pod 

of long-finned pilot whales to military sonar in the Ligurian Sea.

2.13.10 Fisheries By-Catch and Entanglement

Total human-caused long-finned pilot whale mortality along the U.S. cannot be estimated. 

Historically, pilot whales were incidentally caught off the U.S. Atlantic coast in the Distant 

Water Fleet and other foreign fishing activities (Fairfield et al. 1993; Waring et al. 1990). 

Fairfield et al. (1993) described a high rate of takes in the DWF in 1988, which they attributed to 

a geographic concentration in fishing effort. Fertl and Leatherwood (1997) describe multiple 

observations of pilot whales actively feeding in and around trawl nets during haul back. Most 

incidental by-catch occurs along the mid-Atlantic coast where the two species of pilot whales 

overlap; this makes it difficult to assign the mortality to one species or the other (Waring et al. 

2011). Total annual estimated average fishery-related mortality for 2005-2009 was 162 pilot 

whales (Globicephala spp.). The pelagic long-line, northeast midwater trawl and northeast 

groundfish fisheries have the strongest impact on pilot whales. 
68

Table 2.13.2 Mean Annual Mortality of Undifferentiated Pilot Whales by Fishery 2005-2009

Fishery Mean Annual Mortality

Mid-Atlantic Bottom Trawl 30 (0.16)

Northeast Bottom Trawl 12 (0.14)

Mid-Atlantic Mid-water Trawl 2.4 (0.99)

Northeast Mid-water Trawl 3.0 (0.61)

Pelagic Longline 114 (0.20)

2005 Pelagic Longline experimental fishery 1 (1.0)

(CV in parentheses) (Waring et al. 2011)

2.13.11 Vessel Interactions

A review of Northeast and Southeast U.S. stranding records between 2005 and 2009 yielded no 

records of vessel interactions with long-finned pilot whales.

2.13.12 Energy Projects

Both extractive and renewable offshore energy projects have the potential to impact the marine 

environment in a variety of ways, including habitat alteration and the introduction of noise via 

seismic exploration activities (e.g., airguns), vessel/aircraft activity, construction and operation 

(Geraci and St. Aubin 1980, Bain and Williams 2006, Thompsen et al. 2006, Cada et al. 2007, 

Compton 2008, Evans 2008, MMS 2008, Burgman 2010, Boehlert and Gill 2010, Dolman and 

Simmonds 2010, Edrén et al. 2010, Bush 2011, ICES 2011). The impact of these activities on 

marine mammals is unclear. Stone (2003) studied the effects of seismic activity on cetaceans in 

UK waters. She reported that sighting rates of white-sided dolphins, white-beaked dolphins, 

Lagenorhynchus spp., all small odontocetes combined, and all cetaceans combined were 

significantly lower when large airgun arrays were being fired. The 2010 Report of the 

International Council for the Exploration of the Sea (ICES) Working Group on Marine Mammal 

Ecology (ICES 2010) stated that very little is known about the impact of the construction and 

operation of offshore wind-farms. Madsen et al. (2006b) reviewed available current information 

on wind farms and marine mammals and wrote that the noise impact is more severe during 

construction than operation. Weir (2008b) studied the reaction of long-finned pilot whales to an 

air-gun ramp up procedure off Gabon. She documented an avoidance response which was 

limited in time and space.

2.13.13 Data Gaps and Research Recommendations 

The best abundance estimate is from aerial and ship surveys that took place in 2004–this data is 7

years old. There is very little recent information on long-finned pilot whale distribution and 

abundance outside of the summer months (June-September). Current research will continue to 

elucidate pilot whale stock structure in the northwest Atlantic. 
69

2.14 SHORT-FINNED PILOT WHALE (GLOBICEPHALA MACRORHYNCHUS)

There are two species of pilot whales in the western Atlantic: the long-finned pilot whales and 

short-finned pilot whales. It is difficult to differentiate the two species at sea; therefore, some of 

the information presented here is for Globicephala spp.

2.14.1 Status

The short-fined pilot whale is not listed under the Endangered Species Act. The species is 

considered “Data Deficient” on the IUCN Red List. It is afforded protection in U.S. waters 

under the MMPA.

2.14.2 General Distribution

Short-finned pilot whales are found in tropical, subtropical and warm temperate waters 

throughout the world (Olson 2009). In the U.S. Atlantic, they are found from Florida to the MidAtlantic coast (Olson 2009). They overlap with long-finned pilot whales between Cape Hatteras 

(NC) and New Jersey (Waring et al. 2011). Short-finned pilot whale distribution along the U.S. 

Atlantic coast encompasses the BOEM North Atlantic (probably only the southern edge), MidAtlantic, South Atlantic and Straits of Florida Planning Areas. Sighting, stranding and fishery 

bycatch locations of short-finned and undifferentiated pilot whales are shown in Figure 2.14-1.

2.14.3 General Abundance

The best estimate of short-finned pilot whales is 24,674 (CV=0.45), based on a combination of 

aerial and shipboard surveys that took place in 2004 (Waring et al. 2011). An analysis of spatial 

distribution based on genetic studies and environmental variables such as SST and water depth 

was used to assign pilot whales to species where short and long-finned pilot whales overlap 

(Waring et al. 2011).

2.14.4 Habitat Preference

Off the U.S. Atlantic coast, pilot whales (Glopicephala spp.) are often found over areas of high 

relief (Waring et al. 2011) and are associated with the Gulf Stream wall and thermal fronts along 

the shelf edge (Waring et al. 1992). In his analysis of interactions between marine mammals and 

pelagic longline fishing gear in the U.S. Atlantic, Garrison (2007c) found that pilot whale 

interactions were correlated with warm water temperature and proximity to shelf break. 

Hamazaki (2002) used oceanographic and topographic factors to create a habitat prediction 

model for cetaceans in the western North Atlantic. He placed pilot whales (Globicephala spp.) 

in the Mid-Atlantic shelf category and noted that pilot whales tended to be in cool deep water. 

These studies analyzed two separate data sets and likely reflect differences between short and 

long-finned pilot whales. 

2.14.5 Stock Structure

Pilot whales are social and swim in pods formed along the matriline (Amos et al. 1993a). 

Oremus et al. (2009) analyzed the mtDNA of both long-finned and short-finned pilot whales 

worldwide. They found that both species had low levels of genetic diversity compared to other 

widespread cetaceans. They did find structuring between oceanic basins and at the regional 

level. Analyses are currently underway at the Southeast Fisheries Science Center to elucidate the 
70

genetic relationship between short-finned pilot whales in the Western Atlantic, Gulf of Mexico 

and Caribbean Sea (Waring et al. 2011). Pending those results, short-finned pilot whales along 

the U.S. Atlantic coast are managed as a separate stock from the Gulf of Mexico and Caribbean.

2.14.6 Life History Traits 

As summarized in Olson (2009), females become sexually mature at 9 years and males at 13-16 

years (although successful mating may not happen for several years after that). In the Northern 

Hemisphere, mating appears to occur in spring or early summer and calving in summer or fall. 

Gestation is estimated to be 15-16 months in short-finned pilot whales. Lactation lasts for three 

years or longer. It has also been reported that female short-finned pilot whale can lactate after 

final ovulation. Complete reproductive senescence and a long post-reproductive life have been 

documented in short-finned pilot whales (Foote 2008; Olson 2009).

2.14.7 Food Habits

Pilot whales mostly feed on squid (Olson 2009). Overholtz and Waring (1991) analyzed the 

stomach contents of pilot whales (Globicephala spp.) caught incidentally in the Atlantic 

mackerel trawl operating off the mid-Atlantic U.S. east coast in 1989. They found that, on 

average, Atlantic mackerel was 71% of the wet weight of stomach and the remaining 29% was 

long-finned squid. Mintzer et al. (2008) analyzed the stomachs of 27 short-finned pilot whales 

that stranded on the North Carolina coast in January of 2005. They assessed prey importance by 

using two indices: frequency of occurrence and numerical abundance. These analyses showed 

that the most important species was Brachioteuthis riisei, followed by Taonius pavo and 

Histioteuthis reversa (all cephalopods). The most important fish species was Scopelogadus 

beanii. The presence of these prey species indicate these whales had likely been feeding off the 

continental shelf before they stranded.

2.14.8 Health 

2.14.8.1 Strandings

There are records of pilot whale mass strandings from the U.S. (Massachusetts, Florida, and 

North Carolina), the Faroe Islands, Ireland, Tasmania, Western Australia, and New Zealand. As 

described in Olson (2009), pilot whales tend to mass strand more frequently than most other 

cetacean species. The whales involved in mass strandings often do not show any sign of disease. 

There is a wide variety of hypotheses (e.g., animals become stuck in shallow water, geomagnetic 

abnormalities may confuse the whales, healthy animals follow a sick one ashore) but it is not 

currently understood why healthy animals strand. In some instances, human activities, such as 

sonar, have overlapped in space and time with pilot whales strandings. However, there are 

records of mass pilot whale strandings long before the invention of sonar (e.g., Cape Cod 1902, 

n=~100; New Zealand 1918, n=~1000). 

In January 2005, 33 short-finned pilots, 1 minke whale and 2 dwarf sperm whales were part of an 

Unusual Mortality Event (Hohn et al. 2006) along the North Carolina coast. Gross necropsies 

and extensive tissue analyses (clinical pathology, parasitology, gross pathology, histopathology, 

microbiology, and serology) did not find a unifying cause for this event. No harmful algal 

blooms preceded it. The Navy had conducted routine, tactical, mid-frequency sonar operations 

in the area during the time period. Hohn et al. (2006) were not able to definitively link the UME 
71

to sonar operations or environmental variables and concluded that it was likely that the cause of 

the stranding event would remain unknown. 

Oremland et al. (2009) analyzed mandibular fractures in 50 male and female stranded shortfinned pilot whales. They hypothesized that fractures would be more common in males given 

the species is polygynous and exhibits sexual dimorphism. They found that fractures were 

common (overall n=27, 54%; female n=17, 47%; male n=10, 71%), but suggest further research 

is needed to understand the causes and significance of these fractures.

Table 2.14.1 summarizes both short-finned pilot whales (SF) and pilot whales only identified to 

genus (Spp) (Waring et al. 2011). North Carolina had the highest number of recorded stranded 

short-finned pilot whales during 2005-2009 (n=40, 93%). 

Table 2.14.1 Short-finned Pilot Whale (SF) and Pilot Whale, Identified to Genus (spp), 

Strandings by State and Year 

State 2005 2006 2007 2008 2009 Total

SF Spp SF Spp SF Spp SF Spp SF Spp SF Spp

Maine 0 0 0 0 0 0 0 1 0 0 0 1

Massachusetts 0 0 0 0 0 0 0 1 0 0 0 1

New Jersey 0 2 1 0 0 0 0 0 1 0 2 2

Delaware 0 0 0 0 0 0 0 0 1 0 1 0

North Carolina 35 2 0 1 0 0 3 1 2 0 40 4

South Carolina 0 0 0 0 0 0 0 1 0 0 0 1

Total 35 4 1 1 0 0 3 4 4 0 43 9

(Data from the NE and SE marine mammal stranding response databases)

2.14.8.2 Contaminants

Tanabe et al (1987) analyzed organochlorine concentrations (PCBs and DDE) in the blubber of 

short-finned pilot whales from the coast of Japan. Their analyses showed an increase in 

concentration up to 10 years of age, then a decrease from 10-25 years of age. Organochlorine 

concentrations appear to then increase again in whales over 25 years of age. This trend was 

particularly clear in females and may be due to offloading via gestation and lactation.

2.14.8.3 Disease

Duigan et al. (1995a) looked for evidence of morbillivirus infection in short-finned pilot whales 

from the western Atlantic (n=25). The whales had stranded between 1986 and 1994. They 

found neutralizing antibody titers in 64% of the animals. The authors suggest that the social 

nature of the species, population size and migration patterns might facilitate infection. 

Five pilot whales that died on the North Carolina coast, part of the 2005 UME, were tested for 

evidence of morbillivirus. Three of these whales tested positive for morbillivirus titers (Hohn et 

al. 2006).
72

2.14.9 Acoustics

Southall et al. (2007) classified Globicephala spp. into a mid-frequency cetacean functional 

hearing group with an estimated auditory bandwith of 150 kHz to 160 kHz. Rendell et al. (1999)

analyzed tonal calls from five odontocete species. They found that long-finned and short-finned 

pilot whale calls were distinct. The mean frequency of short-finned pilot whales was 7,870 Hz 

(CV=0.32).

Weir (2008b) studied the response of a pod of short-finned pilot whales to a seismic “ramp-up” 

procedure. (The ramp-up procedure is commonly used by the geophysical industry to mitigate 

the potential impact of seismic guns.) Initially, no change in behavior was observed in the 

whales. Ten minutes into the “ramp-up” one whale group turned away from the airguns and 

behavior such as milling and tail slapping was also observed, likely indicating the pilot whales 

were displaying an avoidance response. 

2.14.10 Fisheries By-Catch and Entanglement 

Total human-caused short-finned pilot whale mortality along the U.S. cannot be estimated. 

Historically, pilot whales were incidentally caught off the U.S. Atlantic coast in the DWF and 

other foreign fishing activities (Fairfield et al. 1993; Waring et al. 1990). Fairfield et al. (1993)

described a high rate of takes in the DWF in 1988 that they attributed to a geographic 

concentration in fishing effort. Fertl and Leatherwood (1997) describe multiple observations of 

pilot whales actively feeding in and around trawl nets during haul back. Most incidental bycatch occurs along the mid-Atlantic coast where the two species of pilot whales overlap; this

makes it difficult to assign the mortality to one species or the other (Waring et al. 2011). Total 

annual estimated average fishery-related mortality for 2005-2009 was 162 pilot whales 

(Globicephala spp.). 

Table 2.14.2 Mean Annual Mortality of Undifferentiated Pilot Whales by Fishery 2004-2008

Fishery Mean Annual Mortality

Mid-Atlantic Bottom Trawl 30 (0.16)

Northeast Bottom Trawl 12 (0.14)

Mid-Atlantic Mid-water Trawl 2.4 (0.99)

Northeast Mid-water Trawl 3.0 (0.61)

Pelagic Longline 114 (0.20)

2005 Pelagic Longline experimental fishery 1 (1.0)

(CV given in parentheses)

2.14.11 Vessel Interactions

A review of Northeast and Southeast U.S. stranding data between 2005 and 2009 yielded no 

records of vessel interactions with short-finned pilot whales.

2.14.12 Energy Projects

Both extractive and renewable offshore energy projects have the potential to impact the marine 

environment in a variety of ways, including habitat alteration and the introduction of noise via 
73

seismic exploration activities (e.g., airguns), vessel/aircraft activity, construction and operation

(Geraci and St. Aubin 1980, Bain and Williams 2006, Thompsen et al. 2006, Cada et al. 2007, 

Compton 2008, Evans 2008, MMS 2008, Burgman 2010, Boehlert and Gill 2010, Dolman and 

Simmonds 2010, Edrén et al. 2010, Bush 2011, ICES 2011). The impact of these activities on 

marine mammals is unclear. Stone (2003) studied the effects of seismic activity on cetaceans in 

UK waters. She reported that sighting rates of white-sided dolphins, white-beaked dolphins, 

Lagenorhynchus spp., all small odontocetes combined and all cetaceans combined were 

significantly lower when large airgun arrays were being fired. The 2010 Report of the Working 

Group on Marine Mammal Ecology (ICES 2010) stated that very little is known about the impact 

of the construction and operation of offshore wind-farms. Madsen et al. (2006b) reviewed 

available current information on wind farms and marine mammals and wrote that the noise 

impact is more severe during construction than operation. Although no information is available 

specific to short-finned pilot whales, Weir (2008b) studied the reaction of long-finned pilot 

whales to an air-gun ramp up procedure off Gabon. She documented an avoidance response 

although it was limited in time and space.

2.14.13 Data Gaps and Research Recommendations

The best abundance estimate is from summer 2004 aerial and ship surveys, this data is 7 years 

old. There is very little recent information on short-finned pilot whale distribution and 

abundance outside of the summer months (June-September). Current research will continue to 

elucidate pilot whale stock structure in the northwest Atlantic, Gulf of Mexico, and the 

Caribbean Sea. Contaminant loading information is from other populations of short-finned pilot 

whales. 

2.15 PYGMY KILLER WHALE (FERESA ATTENUATA)

2.15.1 Status

The pygmy killer whale is not listed under the Endangered Species Act. The species is 

considered “Data Deficient” on the IUCN Red List. It is afforded protection in U.S. waters 

under the MMPA. 

2.15.2 General Distribution

The pygmy killer whale is found in tropical and sub-tropical waters throughout the world 

(Jefferson et al. 1994). Despite their widespread distribution, they are poorly understood and one 

of the most rare whale species (McSweeney et al. 2009). Caldwell and Caldwell (1971a)

documented the first pygmy killer whale in the western Atlantic in 1969 from an animal that 

stranded in the Lesser Antilles. In 1992, a group of 6 pygmy killer whales was sighted off Cape 

Hatteras, North Carolina; there have not been any sightings in subsequent surveys (Waring et al. 

2011). Given this sighting and the species’ tendency to be in tropical/sub-tropical waters, pygmy 

killer whales could potentially be observed in the BOEM Mid-Atlantic, South Atlantic, or Straits 

of Florida Planning Areas. Sighting and stranding locations of pygmy killer whales are shown in 

Figure 2.15-1.
74

2.15.3 General Abundance

The number of pygmy killer whales off the U.S. Atlantic coast is unknown. The available data 

are not adequate to calculate a minimum estimate (Waring et al. 2011).

2.15.4 Habitat Preference

They are often found around volcanic islands such as Japan and Hawaii (Donahue and Perryman 

2009). Zerbini and Cesar de Oliveira Santos (1997) reported that the stomach contents of a 

pygmy killer whale that stranded in Brazil indicated it had been feeding over the outer 

continental shelf and slope.

2.15.5 Stock Structure

McSweeney et al. (2009) analyzed 22 years of photo-identification data around the main 

Hawaiian Islands. Their analyses indicated stable long-term associations in mixed sex groups. 

Stock structure for Western North Atlantic pygmy killer whales is unknown (Waring et al. 2011). 

2.15.6 Life History Traits 

There is not a lot known about the life history traits of pygmy killer whales. Donahue and 

Perryman (2009) report a mean length at maturity of 2 m. 

2.15.7 Food Habits

Pygmy whale food habits are not well understand but Donahue and Perryman (2009) report that 

remnants of cephalopods and small fish have been found in stranded and by-caught stomachs. 

Perryman and Foster (1980) suggested that pygmy killer whales sometimes attack and eat other 

dolphins (e.g., Stenella spp. and Delphinus delphis). 

2.15.8 Health 

2.15.8.1 Strandings

There are five pygmy whale stranding records along the U.S. Atlantic coast for the period 2005-

2009 (NE and SE marine mammal stranding response databases): four in South Carolina and one 

in North Carolina. None of these animals showed signs of human interaction. MignucciGiannoni (1999) described the stranding of five (3 dead, 2 alive and returned to the water) 

pygmy killer whales in the British Virgin Islands one day after Hurricane Marilyn devastated the 

area. Wang and Yang (2006) described unusual stranding events that included pygmy killer 

whales, in Taiwan in 2004 and 2005 after naval exercises had occurred nearby.

2.15.8.2 Contaminants

Forrester et al. (1980) documented DDT and PCB levels in three pygmy killer whales that 

stranded in Florida in the 1970s. They noted that the two males had higher concentrations than 

the female and attributed this to different habitat. Given the tendency for female mammals to 

offload contaminants through gestation and lactation, it is likely this may also be the reason for 

the difference.
75

2.15.8.3 Disease

Forrester et al. (1980) describes a variety of parasites (e.g., Nematoda, Destoda, Trematoda) in 

three pygmy killer whales that stranded in Florida in the 1970s. 

2.15.9 Acoustics 

Madsen et al. (2004b) studied acoustic recordings of pygmy killer whales in the northern Indian 

Ocean. These recordings indicated that pygmy killer whales produce echolocation clicks and 

that they likely use these clicks (as other small delphinids do) to find food. Southall et al. (2007) 

classified Feresa into a mid-frequency cetacean functional hearing group with an estimated 

auditory bandwith of 150 Hz to 160 Hz. Montie et al. (2011) used CT (computed tomography)

imaging and auditory evoked potentials (AEPs) procedures of live stranded pygmy killer whales 

to learn more about their auditory system. In a study using acoustic behavior to detect animals at 

sea, pygmy killer whales were detected acoustically 100% of the time that they were detected 

visually (Rankin et al. 2008).

Pygmy killer whales appear to be a species that is sensitive to anthropogenic noise. As reported 

above, Wang and Yang (2006) described unusual stranding events that included pygmy killer 

whales in Taiwan in 2004 and 2005 after naval exercises had occurred nearby.

2.15.10 Fisheries By-Catch and Entanglement

There are no records of fishery interactions for the most recent time period reported (2001-2005) 

(Waring et al. 2011). 

2.15.11 Vessel Interactions

A review of Northeast and Southeast U.S. stranding data between 2005 and 2009 yielded no 

records of vessel interactions with pygmy killer whales.

2.15.12 Energy Projects

Both extractive and renewable offshore energy projects have the potential to impact the marine 

environment in a variety of ways, including habitat alteration and the introduction of noise via 

seismic exploration activities (e.g., airguns), vessel/aircraft activity, construction and operation

(Geraci and St. Aubin 1980, Bain and Williams 2006, Thompsen et al. 2006, Cada et al. 2007, 

Compton 2008, Evans 2008, MMS 2008, Burgman 2010, Boehlert and Gill 2010, Dolman and 

Simmonds 2010, Edrén et al. 2010, Bush 2011, ICES 2011). The impact of these activities on 

marine mammals is unclear. No information specific to pygmy killer whales is available.

2.15.13 Data Gaps and Research Recommendations

In general, very little is known about pygmy killer whales. There is no abundance estimate for 

pygmy killer whales in the U.S Atlantic. The limited amount of information available about 

pygmy killer whales comes from parts of their range that is outside of the U.S. Atlantic coast 

(e.g., from the Pacific Ocean). 
76

2.16 MELON-HEADED WHALE (PEPONOCEPHALA ELECTRA)

2.16.1 Status

The melon-headed whale is not listed under the Endangered Species Act. The species is 

considered “Least Concern” on the IUCN Red List. It is afforded protection in U.S. waters 

under the MMPA.

2.16.2 General Distribution

Melon-headed whales are distributed throughout the world in both tropical and sub-tropical 

waters (Perryman 2009). There are two sighting records (1999 = 20 whales; 2002 = 80 whales) 

of melon-headed whales in the U.S. Atlantic–both off of Cape Hatteras, North Carolina (Waring 

et al. 2011). There are stranding records from New Jersey and Georgia (see Stranding section). 

Given sighting and stranding data, it is possible that melon-headed whales could be found in any 

of the BOEM Atlantic Planning Areas. Sighting and stranding locations of melon-headed whales 

are shown in Figure 2.16-1.

2.16.3 General Abundance

The number of melon-headed whales off the U.S. Atlantic is unknown (Waring et al. 2011). A 

best estimate is not available. 

2.16.4 Habitat Preference

In general, melon-headed whales are found in deep, offshore waters (Perryman 2009). In the 

Gulf of Mexico, melon-headed whales exhibit an oceanic distribution (Mullin et al. 1994); all 

sightings reported in Mullin et al. (1994) were in waters deeper than 500 m. In the Hawaiin 

Islands, satellite-tagged melon-headed whales were shown to move offshore to occupy the edges 

of cold core cyclonic eddies and the centers of warm core anticyclonic eddies where prey could 

be concentrated (Woodworth et al. 2011)

Gross et al. (2009) used sighting and stable isotope data to estimate niche segregation among 

dolphins in the Indian Ocean. Their analyses showed that melon-headed whales prefer steep 

slopes and waters that are slightly deeper than those preferred by the spotted (Stenella attenuata) 

and spinner (S. longirostris) dolphins. Although melon-headed whales overlapped with the 

spotted and spinner dolphins in terms of habitat, the stable isotope analysis showed ecological 

differentiation between them. 

2.16.5 Stock Structure

Stock structure in the northwest Atlantic is unknown. This population is considered separate 

from the Gulf of Mexico population for management purposes (Waring et al. 2011).

2.16.6 Life History Traits: 

Females become sexually mature at 11.5 years and 235 cm; males mature around 15 years 

(Perryman 2009). Bryden et al. (1977) reported preliminary life history traits from stranded 

melon-headed whales in Australia. They found females probably become sexually mature when 

body length reaches 225 cm but before reaching 257 cm and after 4 laminations but before 12 
77

laminations are deposited in dentine. For males, they found sexual maturity likely occurs about 

260 cm and when 7 laminations have been put down. Gestation is approximately 1 year.

2.16.7 Food Habits

Squid, small fish, and shrimp have all been identified in melon-headed whale stomach contents 

(Clarke and Young 1998; Jefferson and Barros 1997). Bossart et al. (2007a) found 6-20 squid 

beaks in the stomachs of 5 stranded melon-headed whales on the Atlantic Coast of Florida in 

2006. They did not find any other food items. Stable isotope analyses on melon-headed whales 

in the Indian Ocean suggested their diet included carnivorous fish and squid (Gross et al. 2009). 

These analyses also indicated that the carbon isotopic composition was influenced by benthic 

primary production. 

2.16.8 Health

2.16.8.1 Strandings

Perryman et al. (1994) described mass strandings of melon-headed whales throughout their 

range. There have been 18 records of melon-headed whale strandings along the U.S. Atlantic 

coast, including two mass-strandings in Florida in 2006 (2 animals and 5 animals) and one massstranding in South Carolina in 2008 (3 animals). A melon-headed whale also stranded in Puerto 

Rico in 1999 (Waring et al. 2011). Gasparini and Sazima (1996) reported a stranded melonheaded whale along the coast of Brazil that had cookiecutter shark (Isistius brasiliensis) wounds. 

Bossart et al. (2007a) described pathological findings of 5 melon-headed whales that stranded on 

the Atlantic coast of Florida in March 2006. As reported in Gasparini and Sazima (1996), all 5 

showed signs of being attacked by cookiecutter sharks. They also found all of the whales were 

thin (postnuchal depression, pronounced scapula and peduncular vertebrae). The cause of this 

stranding was not identified but the authors noted that all 5 whales showed evidence of chronic 

disease (see disease section below) prior to this event. 

Melon-headed whale stranding events have overlapped in space and time with human acoustic

activities; for more details, see the acoustics section below. 

2.16.8.2 Contaminants

Kajiwara et al. (2008) reported contaminant levels in melon-headed whales that stranded along 

the Japanese coast. A total of 55 samples were collected from 1982 to 2006. They found that 

DDT’s and PCBs were predominant in all of the samples. They estimated total maternal transfer 

(gestation and lactation) was 85% of the mother’s burden. PCBs, DDTs, and hexachlorobenzene 

(HCB) levels all decreased in samples collected after 2000. However, PBDE and chlordane

levels showed an increase over the study time period (1982-2006).

Hart et al. (2008) analyzed the temporal trends of perfluorinated compounds (PFC) in melonheaded whales that had stranded along the Japanese coast (1982-2006). They also analyzed 

mother-fetus pairs and found that PFCs had higher transplacental transfer rates than PCBs or 

PBDEs.
78

2.16.8.3 Disease

Cannon (1977) reported on three different nematodes (Anisakis simplex, A. typical, Stenurus 

globiocephalae) and an immature tapeworm (Phyllobothrium chamissonii) in melon-headed 

whales that stranded in Australia. In the whales described by Bossart et al. (2007a), lesions were 

found through the gastro-intestinal tracts; the whales’ peritoneum contained Monorygma spp. 

cysts; Nasitrema-associated sinusitis; and mild to moderate myocardial degeneration was found 

in all 5 whales.

2.16.9 Acoustics

Southall et al. (2007) classified Peponocephala sp. into a mid-frequency cetacean functional 

hearing group with an estimated auditory bandwidth of 150 Hz to 160 Hz. Watkins et al. (1997)

observed melon-headed whales in the southeastern Caribbean. They found that maximum source 

levels were 155 dB for whistles and 165 dB for click-bursts. Clicks and click-bursts had a 

frequency emphasis between 20-24 kHz. The dominant frequencies for whistles were 8-12 kHz. 

The authors noted an increase in click bursts and whistles with increased activity. BaumannPickering et al. (2010) found that melon headed whales (n=50) near Palmyra Atoll produced 

median peak frequencies of averaged clicks of 24.4-29.7 kHz. Frankel and Yin (2010) made 

recordings of large groups of melon-headed whales around the Big Island of Hawaii. They 

described echolocation clicks, burst-pulse sounds and whistles.

Southall et al. (2006) described unusual behavior of melon-headed whales in Hanalei Bay, 

Kauai, Hawaii, July 3-4, 2004. A group of 150-200 whales “milled about” in the shallow area of 

the bay and eventually were herded out to sea by humans. Only one animal was known to have 

died (a calf found on 5 July). This event overlapped with Rim-of-the-Pacific naval exercises;

ships converging for this activity had used active mid-frequency sonar intermittently July 2-3. 

Southall et al. (2006) analyzed environmental variables that could have contributed to this event 

and concluded that the sonar transmissions were likely a contributing factor to this event. 

Brownell et al. (2009) further investigated this event and other mass strandings and supported 

Southall et al.’s (2006) suggestion.

2.16.10 Fisheries By-Catch and Entanglement

There were no reports of mortality or serious injury to melon-headed whales during 2001-2005 

(the most recent time frame available) (Waring et al. 2011). Therefore, the total annual 

estimated mortality for melon-headed whales was zero from 2001-2005 (Waring et al. 2011).

2.16.11 Vessel Interactions 

A review of Northeast and Southeast U.S. stranding data between 2005 and 2009 yielded no 

records of vessel interactions with melon-headed whales. It should be noted that melon-headed 

whales do appear to be sensitive to sonar activities (see the Acoustics section above).

2.16.12 Energy Projects

Both extractive and renewable offshore energy projects have the potential to impact the marine 

environment in a variety of ways, including habitat alteration and the introduction of noise via 

seismic exploration activities (e.g., airguns), vessel/aircraft activity, construction and operation

(Geraci and St. Aubin 1980, Bain and Williams 2006, Thompsen et al. 2006, Cada et al. 2007, 
79

Compton 2008, Evans 2008, MMS 2008, Burgman 2010, Boehlert and Gill 2010, Dolman and 

Simmonds 2010, Edrén et al. 2010, Bush 2011, ICES 2011). The impact of these activities on 

marine mammals is unclear. No information specific to melon-headed whales is available.

2.16.13 Data Gaps and Research Recommendations

There is no abundance estimate for melon-headed whales in the U.S Atlantic. Most of the 

information about the melon-headed whales’ life history traits, acoustics, food habits, 

contaminant burden, or disease comes from parts of their range that is outside of the U.S. 

Atlantic coast (e.g., from the Pacific Ocean). 

2.17 WHITE-BEAKED DOLPHIN (LAGENORHYNCHUS ALBIROSTRIS)

2.17.1 Legal Status

The white-beaked dolphin is not listed under the Endangered Species Act and is considered a 

species of “Least Concern” on the IUCN Red List. It is afforded protection in U.S. waters under 

the MMPA.

2.17.2 General Distribution

White-beaked dolphins are found in the temperate and subarctic North Atlantic (Kinze 2009). 

They appear to be much more abundant in the eastern than in the western North Atlantic 

(Northridge et al. 1995). Along the U.S. east coast they are found from Cape Cod, 

Massachusetts, north into Canadian waters (Reeves et al. 1999b). Prior to the 1970s, white-sided 

dolphins in the U.S. Atlantic were found mostly off shore or on the continental slope while 

white-beaked dolphins were on the shelf but the two species switched distribution (Kenney et al. 

1996). Most of the sightings have occurred in the BOEM North Atlantic Area. Sighting, 

stranding and fishery bycatch locations of white-beaked dolphins are shown in Figure 2.17-1.

2.17.3 General Abundance

The number of white-beaked dolphins in U.S. waters is unknown (Waring et al. 2011). Waring 

et al. (2011) report a best estimate of 2,003 (CV=0.94) animals in August 2006 for the 

northwestern Atlantic (U.S. and Canadian waters). This estimate is from aerial surveys flown 

along the 2000-m depth contour from southern Georges Bank to the upper Bay of Fundy and to 

the entrance of the Gulf of St. Lawrence. They caution that this number is probably low because

the survey covered only part of the species range and only a small area of the BOEM North 

Atlantic Planning Area.

2.17.4 Habitat Preference

As described in the general distribution section, prior to the 1970s, white-beaked dolphins along 

the U.S. Atlantic coast were on the shelf. Since the 1970s they have been found mostly on the 

continental slope or off shore (Kenney et al. 1996). In other parts of their range, they are still 

most often found on the shelf Northridge et al. (1995) found that white-beaked dolphin 

distribution around the British Isles was limited to shelf areas. In their study on the cooccurrence of cetaceans and seabirds in the Northeast Atlantic, Skov et al.(1995) found that 

white-beaked dolphin and northern gannet (Sula bassana) distributions were highly correlated 
80

(r=0.54, P<0.001, df=49) and separated from the other cetacean/bird groupings, perhaps due to 

their reliance on shoaling fish (Evans 1980). 

2.17.5 Stock Structure

In their analysis (principal component and partial least squares) on skull characteristics, 

Mikkelsen and Lund (1994) found significant differences between white-beaked dolphins from 

the eastern and western north Atlantic. Stock structure along the U.S. Atlantic coast has not been 

described.

2.17.6 Life History Traits

As is summarized in Kinze (2009), females become sexually mature at a mean age of 8.7 years 

(240 cm) and males at a mean age of 11.6 years (270 cm), gestation is approximately 11 months, 

and the maximum recorded age for females is 34 years. Young are born probably between June 

and September (Leatherwood and Reeves 1983c).

2.17.7 Food Habits

This species’ diet includes squid, octopus, clupeids, gadids, hake, and some benthic crustaceans 

(Leatherwood and Reeves 1983c; Reeves et al. 1999b). De Pierrepont et al. (2005) analyzed the 

stomach contents of a single white-beaked dolphin that stranded on the coast of Normandy 

(France). Gadids comprised 64.7% of the numeric proportion of prey. Hai et al. (1996) analyzed 

the stomach contents of 20 white-beaked dolphins that were killed when entrapped by ice in 

Port-aux-Basques, Canada, in March of 1982. Ninety percent of the stomachs contained prey 

remains from Atlantic cod (Gadus morhua). Remnants of crab and seaweed were found in 10% 

of the stomachs. 

2.17.8 Health

2.17.8.1 Strandings 

A total of 5 white-beaked dolphins stranded along the U.S. Atlantic (Maine, Massachusetts and 

New Jersey) coast from 2005 to 2009. Two were in Maine, two in New Jersey and one in 

Massachusetts (Northeast and Southeast U.S. marine mammal stranding response databases). 

White-beaked dolphins have not been recorded as part of a UME. 

2.17.8.2 Contaminants

Muir et al. (1988) documented PCB’s, DDT’s, chlordanes, toxaphene, chlorobenzenes, 

hexachlorocyclohexane isomers and seven elements in the tissue of white-beaked dolphins that 

died after being trapped in ice off Newfoundland, Canada. They found PCB levels in the 

dolphins were similar to that in harbor porpoise and beluga whales that were also sampled from 

what they refer to as “relatively contaminated Canadian and U.S. Atlantic waters.” They also 

found high levels of lead (Pb) in the dolphin tissue.

2.17.8.3 Disease

Reeves et al. (1999b) report a high incidence of diseased jaws and teeth in white-beaked dolphins 

that stranded around the British coast. Hai et al. (1996) found worms (Anisakis spp.) in the 

stomachs of all the dolphins entrapped in ice in Port-aux-Basques. Buck and Spotte (2005)
81

found enterobacteria (Edwardsiella, Escherichia, Klebsiella), Plesiomonas, Aeromonas, 

Citrobacter, Pseudomonas, and Staphylococcus in anal and blowhole swabs taken from 5 

stranded white-beaked dolphins that were rescued from ice in Newfoundland and transported to 

the Mystic Marinelife Aquarium, Connecticut, in 1983. In their study of stranded marine 

mammals along Cape Cod and southeastern Massachusetts, Bogomolni et al. (2010) reported 2 

stranded white-beaked dolphins. One had died of disease; the cause of death of the other dolphin 

could not be determined.

2.17.9 Acoustics

Schevill and Watkins (1962), as cited in Reeves et al. (1999b), described “squeals” in the range 

of 6.5-15 kHz. Mitson and Morris’s (1988) recordings of white-beaked dolphins in the North 

Sea that showed the frequency of their emissions can increase to at least 305 kHz. It has been 

shown that white-beaked dolphins hear at very high frequencies–comparable to that heard by 

harbor porpoise (Nachtigall et al. 2008). However, Southall et al. (2007) classified 

Lagenorhynchus spp. into a mid-frequency cetacean functional hearing group with an estimated 

auditory bandwith of 150 Hz to 160 Hz. 

2.17.10 Fisheries By-catch and Entanglement

No observations of fishery-related mortality have been reported for white-beaked dolphins in the 

U.S. EEZ (Waring et al. 2011).

2.17.11 Vessel Interactions

A review of Northeast and Southeast U.S. stranding data between 2005 and 2009 yielded no 

records of vessel interactions with white-beaked dolphins. 

2.17.12 Energy Projects

Both extractive and renewable offshore energy projects have the potential to impact the marine 

environment in a variety of ways, including habitat alteration and the introduction of noise via 

seismic exploration activities (e.g., airguns), vessel/aircraft activity, construction and operation

(Geraci and St. Aubin 1980, Bain and Williams 2006, Thompsen et al. 2006, Cada et al. 2007, 

Compton 2008, Evans 2008, MMS 2008, Burgman 2010, Boehlert and Gill 2010, Dolman and 

Simmonds 2010, Edrén et al. 2010, Bush 2011, ICES 2011). The impact of these activities on 

marine mammals is unclear. 

Stone (2003) studied the effects of seismic activity on cetaceans in UK waters. She reported that 

sighting rates of small odontocetes (including white-beaked dolphins) were significantly lower 

when large airgun arrays were being fired. She also found that in general, small odontocetes 

showed the strongest avoidance behavior to seismic noise (compared to baleen, killer, sperm and 

pilot whales). The 2010 Report of the Working Group on Marine Mammal Ecology (ICES 

2010) stated that very little is known about the impact of the construction and operation of 

offshore wind-farms. Madsen et al. (2006b) reviewed available current information on wind 

farms and marine mammals and wrote that the noise impact is more severe during construction 

than operation. This was found to be the case for impacts to harbor porpoise (see Carstensen et 

al. [2006], Koschinski et al. [2003]). David (2006) wrote that pile driver-generated noise has the 

potential to impact dolphins by temporary displacement and interference with communication. 
82

The 2011 Report of the Working Group of Marine Mammal Ecology (ICES 2011) reported that 

porpoise detection (T-POD data) was lower during construction of a tidal turbine compared to 

before and after construction. 

2.17.13 Data Gaps and Research Recommendations

The best abundance estimate is from 2006 and is now 5 years old. There is no current 

information on white-beaked dolphin distribution and abundance outside of the summer months 

(June-August). There is limited contaminant information from animals trapped by ice off 

Newfoundland, Canada. There is no information on food habits, stock structure or the impacts of 

non-fishery related anthropogenic activities on white-beaked dolphin in the northwestern 

Atlantic.

2.18 ATLANTIC WHITE-SIDED DOLPHIN (LAGENORHYNCHUS ACUTUS)

2.18.1 Legal Status

The Atlantic white-sided dolphin is not listed under the Endangered Species Act and is 

considered a species of “Least Concern” on the IUCN Red List. It is afforded protection in U.S. 

waters under the MMPA.

2.18.2 General Distribution

Atlantic white-sided dolphins are found in the cold-temperate North Atlantic (Cipriano 2009). 

Before the 1970s, white-sided dolphins in the U.S. Atlantic were found mostly off shore or on 

the continental slope; white-beaked dolphins were on the shelf but the two species switched 

distribution (Kenney et al. 1996). Selzer and Payne (1988) found that, in U.S. waters, whitesided dolphins were common in the Gulf of Maine (40-44o

N). In the spring they are 

concentrated in the southwestern Gulf of Maine through the Great South Channel and along the 

western edge of Georges Bank with another concentration along the continental slope of the midAtlantic region (39o

N). In the fall they are found primarily in the Gulf of Maine Basin where

most sightings occur between 42-44oN. Weinrich et al. (2001) suggest that white-sided dolphins 

use coastal New England waters (referring primarily to Stellwagen Bank and Jeffereys Ledge) 

transitorily as part of a larger home range. 

Seasonally, white-sided dolphins are found from Georges Bank to the lower Bay of Fundy in the 

summer (June to September), from Georges Bank to the southern Gulf of Maine in the fall 

(October to December) then densities of white-sided dolphins drop off in this area from January 

to May (Palka et al. 1997). White-sided dolphins are found south of Georges Bank (around 

Hudson Canyon) all year but at low densities (Palka et al. 1997). They are not found in the 

BOEM South Atlantic or Straits of Florida Planning Areas. Sighting, stranding, and fishery 

bycatch locations of white-sided dolphins are shown in Figure 2.18-1.

2.18.3 General Abundance

The total number of white-sided dolphins along the U.S. Atlantic coast is unknown (Waring et al. 

2011). The best estimate of white-sided dolphin abundance in the western north Atlantic is 

23,390 (CV=0.23), the sum of the 2006 and 2007 aerial surveys (Waring et al. 2011). While the 

combined estimate may include a certain amount of inter-annual redistribution, it is still felt to be 
83

more representative than either estimate alone. Because the estimated abundance of this species 

has large inter-annual variability (that is, the estimates were about 51,000 in 1999 and 109,000 in 

2002 and about 24,000 recently), the spatial-temporal distribution is being investigated to more 

completely understand how this species utilizes US waters throughout the year (Waring et al. 

2011).

2.18.4 Habitat Preference

As described in the general distribution section, white-sided dolphins in the U.S. Atlantic have 

been found mostly on the continental shelf since the 1970s (Kenney et al. 1996). Generally, 

white-sided dolphins are found in waters over the continental shelf and slope, and occasionally 

move into coastal or deeper waters (Cipriano 2009). In the northwestern Atlantic they prefer 

water 9-15o C over the continental slope (Leatherwood and Reeves 1983a). Selzer and Payne 

(1988) found that white-sided dolphins were most often found in waters with low SST and 

salinity and over areas with high topographical relief. Ninety-seven percent of their sightings 

occurred in water less than 12o

C. They suggest that these factors primarily influence white-sided 

dolphin prey distribution which secondarily influences dolphin distribution. Hamazaki (2002)

developed spatiotemporal prediction models of cetacean habitats off the northeast U.S. coast and 

found that white-sided dolphins preferred waters 400-500 m deep where SST was 10-15oC. 

2.18.5 Stock Structure

In their analysis (principal component and partial least squares) on skull characteristics, 

Mikkelsen and Lund (1994) could not clearly separate white-sided dolphins from the eastern and 

western north Atlantic. Palka et al. (1997) reported that the combination of sightings, strandings,

and by-catch data indicates there are three populations in the northwest Atlantic: Gulf of Maine, 

Gulf of St. Lawrence, and the Labrador Sea, but this has not been confirmed by genetic analyses. 

Amaral (2005) analyzed samples from stranded, by-caught, and biopsied white-sided dolphins 

from the Gulf of Maine, Cape Cod, Gulf of St. Lawrence, Sable Island, and the Faroe Islands. 

She found limited relatedness within some stranded groups but suggested this species has a fluid 

social structure.

2.18.6 Life History Traits

Females become sexually mature at 6-12 years; males mature at 7-11 years (Cipriano 2009). 

Sergeant et al. (1980) reported that in the northwest Atlantic gestation lasts approximately 11 

months, most births occur in June and July, and lactation lasts about 18 months. The intercalving interval is likely 2-3 years (Leatherwood and Reeves 1983a); however, some stranded 

females were observed to be both pregnant and lactating, indicating that some individuals may 

breed annually (Sergeant et al. 1980). In New England waters, Weinrich et al. (2001) found that 

early summer is an important calving period. 

2.18.7 Food Habits

Craddock et al. (2009) analyzed 62 stomachs (28 from by-caught animals, 34 from stranded 

animals). Most of the by-caught animals were collected in the Gulf of Maine while the stranded 

animals were from Cape Cod, Massachusetts. They found silver hake (Merluccius bilinearis), 

spoonarm octopus (Bathypolypus bairdii), and haddock (Melanogrammus aeglefinus) were the 
84

most important prey species for the net-caught animals and sand lance (Ammodytes spp.) was the 

dominant prey of the stranded animals. 

2.18.8 Health

One UME, which occured along the coast from New Jersey to North Carolina between 1 January 

and 26 April, 2008, involved white-sided dolphins (n=4 females). The cause of this UME is still 

under investigation.

2.18.8.1 Strandings

There were 245 white-sided dolphin strandings reported along the U.S. Atlantic coast from 2005-

2009 (Northeast and Southeast U.S. marine mammal stranding response databases). Fourteen of 

these stranded dolphins showed signs of human interactions. Of these, a majority (n=182, 74%) 

occurred in Massachusetts, followed by New York (n=12, 5%). No strandings were reported 

south of South Carolina. Amaral (2005) analyzed stranding data 1973-1999 and found 

significantly more animals stranded along the U.S. Atlantic coast in the winter months. 

Bogomolni et al. (2010) analyzed the cause of death of marine mammals stranded along the coast 

of Cape Cod and southeastern Massachusetts. Most (69%) of the white-sided dolphins in this 

study were placed in the “Mass Stranding with No Significant Finding” category. White-sided 

dolphins had the highest number of individuals in this category of all species included in this 

study. 

2.18.8.2 Contaminants

Weisbrod et al. (2001) documented PCB’s and DDE’s in white-sided dolphins sampled in the 

Gulf of Maine. Several of these samples contained organochlorine levels that were considered to 

have negatively impacted the health of other species of marine mammals. Tuerk et al. (2005)

found that body length was a better predictor of contaminant burdens than age and that both male 

and female levels decreased with age. This decrease is probably due to lactation in females and 

either growth dilution or metabolic elimination in males. Montie et al. (2009) documented 

organochlorines, polychlorinated byphenyls, hydroxylated PCBs, methyl sulfone PCBs, flame 

retardants, and hydroxylated BDE’s in white-sided dolphins that stranded on Cape Cod, 

Massachusetts. 

2.18.8.3 Disease

Bogomolni et al. (2010) found that disease was the cause of death in 21% of white-sided 

dolphins that stranded along the coast of Cape Cod and southeastern Massachusetts. Analyses of 

tissue from white-sided dolphins that stranded in Wellfleet, Massachusetts, in 1998 and 1999 

found a high level (39%) of Sarcocystis spp. infection (Ewing et al. 2002).

2.18.9 Acoustics

Southall et al. (2007) classified Lagenorhynchus sp. into a mid-frequency cetacean functional 

hearing group with an estimated auditory bandwith of 150 Hz to 160 Hz. Schevill and Watkins 

(1962), as described in Reeves et al. (1999a), documented “squeals” in the range of 1-24 kHz 

and clicks. 
85

2.18.10 Fisheries By-catch and Entanglement

This species is caught in a variety of commercial fisheries; information is summarized below. 

The most recent mean annual mortality of all fisheries was estimated at 245 (CV=0.12) for the 

years 2005-2009 (Waring et al. 2011).

Table 2.18.1 Incidental White-sided Dolphin Mortality 2005-2009

Fishery Mean Annual Mortality (CV)

Northeast Sink Gillnet 36 (0.34)

Northeast Bottom Trawl 160 (0.14)

Northeast Mid-water Trawl 1.9 (1.03)

Mid-Atlantic Mid-Water Trawl 24 (0.55)

Mid-Atlantic Bottom Trawl 23 (0.12)

The NMFS assembled the Atlantic Trawl Gear Take Reduction Team (ATGTRT) to address 

incidental mortality of white-sided dolphins (among several other species) in September 2006. 

This take reduction team focuses on the Mid-Atlantic Mid-Water Trawl, the Mid-Atlantic 

Bottom Trawl, Northeast Mid-Water Trawl and the Northeast Bottom Trawl fisheries. The 

Team found that mean annual incidental mortality (2001-2005) for white-sided dolphins was 

highest in the Northeast region in deep waters (>142.5 m) with low to mid SST (4.44-6.49o

C). 

2.18.11 Vessel Interactions

In 2005, one white-sided dolphin stranding mortality in the Northeast and Southeast U.S. Marine 

Mammal Stranding Network databases exhibited signs of interaction with a boat propeller.

2.18.12 Energy Projects

Both extractive and renewable offshore energy projects have the potential to impact the marine 

environment in a variety of ways, including habitat alteration and the introduction of noise via 

seismic exploration activities (e.g., airguns), vessel/aircraft activity, construction and operation

(Geraci and St. Aubin 1980, Bain and Williams 2006, Thompsen et al. 2006, Cada et al. 2007, 

Compton 2008, Evans 2008, MMS 2008, Burgman 2010, Boehlert and Gill 2010, Dolman and 

Simmonds 2010, Edrén et al. 2010, Bush 2011, ICES 2011). The impact of these activities on 

marine mammals is unclear. 

Stone (2003) studied the effects of seismic activity on cetaceans in UK waters. She reported that 

sighting rates of small odontocetes (including white-sided dolphins) were significantly lower 

when large airgun arrays were being fired. She also found that in general, small odontocetes 

showed the strongest avoidance behavior to seismic noise (compared to baleen, killer, sperm and 

pilot whales). The 2010 Report of the Working Group on Marine Mammal Ecology (ICES 

2010) stated that very little is known about the impact of the construction and operation of 

offshore wind-farms. Madsen et al. (2006b) reviewed available current information on wind 

farms and marine mammals and wrote that the noise impact is more severe during construction 

than operation. This was found to be the case for impacts to harbor porpoise (see Carstensen et 
86

al. [2006], Koschinski et al. [2003]). David (2006) wrote that pile driver-generated noise has the 

potential to impact dolphins via temporary displacement and interference with communication. 

The 2011 Report of the Working Group of Marine Mammal Ecology (ICES 2011) reported that 

porpoise detection (T-POD data) was lower during construction of a tidal turbine compared to 

before and after construction.

2.18.13 Data Gaps and Research Recommendations

There is limited recent information on white-sided dolphin distribution and abundance outside of 

the summer months (June-September). Very little is understood about stock structure in the 

northwest Atlantic. No information on the impacts of non-fishery related anthropogenic 

activities on white-sided dolphin in the northwestern Atlantic has been published.

The ATGTRT recommended that there be an improved abundance estimate for all species 

(including white-sided dolphins) affected by the trawl fisheries including conducting more

surveys, appropriately incorporating data from multiple years and by using appropriate stock 

structure boundaries. Additionally, they specifically recommended that environmental and 

biological factors that may be responsible for the large inter-annual variation in white-sided 

dolphin abundance estimates be investigated and modeled.

2.19 RISSO’S DOLPHIN (GRAMPUS GRISEUS)

2.19.1 Status 

The Risso’s dolphin is not listed under the Endangered Species Act and is considered a species 

of “Least Concern” on the IUCN Red List. It is afforded protection in U.S. waters under the 

MMPA.

2.19.2 General Distribution

Risso’s dolphins are found worldwide in temperate and tropical oceans (Baird 2009). In the U.S. 

Atlantic they are found in the North Atlantic, Mid-Atlantic, South Atlantic and Straits of Florida 

Planning Areas (Kruse et al. 1999; Waring et al. 2011) although a majority of the sightings occur 

north of Maryland (38°

N) (Waring et al. 2011). Sighting, stranding and fishery bycatch locations 

of Risso’s dolphins are shown in Figure 2.19-1.

2.19.3 General Abundance

Waring et al. (2011) give a best estimate of 20,479 Risso’s dolphins (CV=0.59), based on a

combination of ship and aerial surveys conducted June-August 2004 from Florida to the Bay of 

Fundy. NMFS divided these surveys into two areas: the “North Atlantic” includes waters north 

of Maryland (38°N) to the Bay of Fundy (45°N) and the “South Atlantic” includes waters from 

Maryland (38°N) south to Florida (27.5°N). The 2004 Risso’s dolphin estimate for the North 

Atlantic is 15,053 (CV=0.78). The 2004 estimate for the South Atlantic is 5,426 (CV=0.54). 

The NMFS North Atlantic Survey was conducted in part of the BOEM North Atlantic Planning 

Area while the NMFS South Atlantic Survey was conducted in parts of the BOEM Mid-Atlantic 

and South Atlantic Planning Areas. It is important to note that the surveys conducted did not 

necessarily cover the entire BOEM planning areas but likely sampled a subsection of these areas 

based on prior knowledge of species distribution and survey goals. Because the 2004 surveys 
87

occurred north of the Straits of Florida planning area, the 20,470 Risso’s dolphin abundance 

estimate does not include this area. 

2.19.4 Habitat Preference 

Risso’s dolphins prefer the steep shelf edge between 400-1000 m (Baird 2009). Generally they 

are found in waters between 15 °

C and 20 °C and are rarely found in waters less than 10 °C (Baird 

2009). Sightings from NMFS aerial and shipboard surveys along the U.S. Atlantic coast were 

mostly in the continental shelf edge and continental slope areas (Waring et al. 2011). 

Baumgartner (1997) reported that most Risso’s dolphins in the Gulf of Mexico are found over 

steep sections of the upper continental slope between the 350-975-m isobaths. This distribution 

is probably related to prey concentration. In the Azores, Risso’s dolphins prefer areas between 

497 and 1,233 m in depth, with slopes between 27 and 35% (Pereira 2008). Hamazaki (2002)

found that, compared to the other mid-Atlantic shelf species, Risso’s dolphins were found in 

warmer and deeper water. Dive and travel information was collected in a tagging study reported 

by Wells et al. (2009). A rehabilitated male Risso’s dolphin that had stranded on the Gulf coast 

of Florida was tagged and released in the Gulf of Mexico. The dolphin had travelled more than 

3,300 km from the Gulf to the Atlantic Ocean off Delaware. More than 90% of the dolphin’s 

dives were within 50 m of the surface, with only a small percentage of dives to depths below 200 

m. The deepest was a single dive to 400-500 m.

2.19.5 Stock Structure 

Gaspari et al. (2007) reported on genetic differentiation between the Risso’s dolphin populations 

in the UK and the Mediterranean, but similar genetic work has not been done for the western 

Atlantic. There is no stock structure information available for Risso’s dolphins in the northwest 

Atlantic (Waring et al. 2011).

2.19.6 Life History Traits

Information on Risso’s dolphin life history traits is limited. Baird (2009) noted that age at first 

maturity is thought to be 8-10 years for females and 10-12 years for males. The inter-calving 

interval is 2.4 years. The composition of a school of 79 Risso’s dolphins killed in Taiji, Japan, in 

1990 was examined by Anano and Miyazaki (2004). The group was composed of 49 females 

and 30 males, though only one of the males was fully mature. The oldest immature female was 

10.5 years old and the youngest mature female was 8.5 years old. The average female body 

length was 270 cm at maturity. Ten to twelve years was estimated as the average age at maturity 

for males, and length at maturity was similar to that for females. Ten animals in the group were 

calves under a year of age, and two were between 1 and 1.5 years old. With the caveat that only 

a single school was studied, the authors made several inferences about Risso’s dolphin school 

organization, including the observation that young dolphins stay in the natal school until around 

puberty, mature females of similar reproductive status group together, and that mature males 

move among groups (Amano and Miyazaki 2004). Information on the social structure of freeranging Risso’s dolphins off Pico Island in the Azores was gathered from field observations and 

photo-ID (Hartman et al. 2008). The authors found the basic units of Risso’s dolphin society to 

be clusters of 3-12 individuals grouped by age and sex classes. The dolphins exhibited stable 

long-term bonds and a high degree of site fidelity. 
88

2.19.7 Food Habits 

Risso’s dolphins feed mostly on squid (neritic and oceanic species) (Baird 2009). Wurtz et al. 

(1992) analyzed the stomach contents of a Risso’s dolphin that had died in a fishing net in the 

Mediterranean Sea. They found oceanic squid but no fish remains. Examinations of Risso’s 

dolphin stomach contents stranded off the coast of England (Clarke and Pascoe 1985) and South 

Africa (Cockcroft et al. 1993) confirmed that cephalopods were the exclusive or primary prey. 

The study by Blanco et al. (2006) showed the main composition of Mediterranean stranded 

Risso’s dolphins to be cephalopods, but also found several species of tunicates, which may be an 

overlooked component of the diet. Blanco et al. (2006) found evidence that Risso’s dolphins in 

the Mediterranean feed preferentially in the middle slope (depths of 600-800 m). 

2.19.8 Health

2.19.8.1 Strandings

Northeast and Southeast U.S. marine mammal stranding response databases contain records of

66 Risso’s dolphin strandings along the U.S. Atlantic coast (Maine to Florida) from 2005-2009;

the majority of the strandings took place along the Massachusetts coast. In their discussion of 

the possible connection between seismic activity and gas-bubble formation in cetacean tissue, 

Jepson et al. (2005a), observed that three out of 24 Risso’s dolphins that had stranded off the 

British coasts between October 1992 and January 2003 exhibited gas-bubble-induced tissue 

damage. In a 2005 paper, Jepson et al. (2005a) present findings of gas-bubble formation and 

embolism in stranded Risso’s and other dolphins, and suggest further research into the etiology 

of bubble formation and its association with anthropogenic noise.

2.19.8.2 Contaminants

Storelli and Marcotrigiano (2000) documented PCBs, DDT and HCB in the tissues of three 

Risso’s dolphins that had stranded along the Italian coast. Concentrations of butyltins (BTs) in 

the liver and organochlorine compounds (OCs) in the blubber were looked at in Risso's dolphins 

caught off Taiji, Japan by Kim et al. (1996). They showed that while OC concentrations 

increased with age in males, they decreased with age in mature females, suggesting that these 

compounds were being transferred to the offspring. BT concentrations rose with age at the same 

rate in males and females. 

2.19.8.3 Disease

Toxoplasmosis infection was documented in a Risso’s dolphin and her fetus that had stranded on 

the coast of Spain (Resendes et al. 2002). 

2.19.9 Acoustics

Madsen et al. (2004a) reported that Risso’s dolphins produce short, broadband signals with peak 

frequencies around 50 kHz. They also found that Risso’s dolphins use their echolocation to 

detect prey up to 80 m. Echolocation by a captive Risso’s dolphin was also demonstrated by 

Philips et al. (2003). Corkeron and Van Parijs (2001) reported on recordings of Risso’s dolphins 

made off the coast of Australia which included broadband clicks, barks, buzzes, grunts, chirps, 

whistles, and simultaneous whistle + burst-pulses in the 30 Hz and 22 kHz range. The hearing 

thresholds of Risso’s dolphins have been studied by Nachtigall et al. (2005). An infant Risso’s 
89

dolphin demonstrated very high-frequency sensitivity (Nachtigall et al. 2005). Response to 

sound stimuli was also tested in an infant Risso’s dolphin, demonstrating that the response delay 

was among the fastest measured in marine mammals (Mooney et al. 2006)

2.19.10 Fisheries By-Catch and Entanglement

Waring et al. (2011) reported a mean annual fishery-related mortality or serious injury of 18

(CV=0.37) dolphins during the 5-year period (2005-2009). The 5-year mean annual mortalities 

by fishery are in Table 2.19-1. 

Table 2.19.1 Fisheries Mortality of Risso’s Dolphins

Fishery Mean Annual Mortality (CV)

Northeast Sink Gillnet 3 (0.93)

Mid-Atlantic Gillnet 7 (0.73)

Pelagic Longline 8 (0.40)

2.19.11 Vessel Interactions

A review of Northeast and Southeast U.S. stranding data between 2005 and 2009 yielded one 

record of a Risso’s dolphin stranding mortality with wounds consistent with propeller strike. 

The effects of whale watching activities on Risso’s dolphins were studied in the Azores (Visser 

et al. 2011). When more than five whale watching vessels were present, Risso’s dolphins spent 

significantly less time resting and socializing.

2.19.12 Energy Projects

Both extractive and renewable offshore energy projects have the potential to impact the marine 

environment in a variety of ways, including habitat alteration and the introduction of noise via 

seismic exploration activities (e.g., airguns), vessel/aircraft activity, construction and operation

(Geraci and St. Aubin 1980, Bain and Williams 2006, Thompsen et al. 2006, Cada et al. 2007, 

Compton 2008, Evans 2008, MMS 2008, Burgman 2010, Boehlert and Gill 2010, Dolman and 

Simmonds 2010, Edrén et al. 2010, Bush 2011, ICES 2011). The impact of these activities on 

marine mammals is unclear. 

Stone (2003) studied the effects of seismic activity on cetaceans in UK waters. She reported that 

sighting rates of small odontocetes were significantly lower when large airgun arrays were being 

fired. She also found that in general, small odontocetes showed the strongest avoidance behavior 

to seismic noise (compared to baleen, killer, sperm and pilot whales). The 2010 Report of the 

Working Group on Marine Mammal Ecology (ICES 2010) stated that very little is known about 

the impact of the construction and operation of offshore wind-farms. Madsen et al. (2006b)

reviewed available current information on wind farms and marine mammals and wrote that the 

noise impact is more severe during construction than operation. This was found to be the case 

for impacts to harbor porpoise (see Carstensen et al. (2006), Koschinski et al. (2003)). David 

(2006) wrote that pile driver-generated noise has the potential to impact dolphins via temporary 

displacement and interference with communication. The 2011 Report of the Working Group of 

Marine Mammal Ecology (ICES 2011) reported that porpoise detection (T-POD data) was lower 
90

during construction of a tidal turbine compared to before and after construction. No information 

specific to Risso’s dolphins was found.

2.19.13 Data Gaps and Research Recommendations

The best abundance estimate is from 2004 and is now over 7 years old. There is no current 

information on Risso’s dolphin distribution and abundance outside of the summer months (JuneAugust). There is limited contaminant information, and what exists is from work done on 

dolphins from the Mediterranean Sea or off Japan. No information on food habits or stock 

structure of Risso’s dolphins in the northwestern Atlantic has been published.

2.20 BOTTLENOSE DOLPHIN (TURSIOPS TRUNCATUS)

As of 2011, there are 15 recognized stocks of bottlenose dolphins along the U.S. Atlantic coast 

(see http://www.nmfs.noaa.gov/pr/pdfs/sars/).

2.20.1 Status

The bottlenose dolphin is not listed under the Endangered Species Act. The IUCN Red List lists 

its status as “Least Concern.” The MMPA affords protection of all bottlenose dolphin stocks in 

U.S. waters and the coastal stocks are listed as “Depleted.”

2.20.2 General Distribution

Bottlenose dolphins are found in temperate and tropical waters throughout the world (Wells and 

Scott 1999). Temperature appears to limit their distribution off North America either directly or 

by limiting prey distribution (Wells and Scott 2009). In the U.S. Atlantic, the offshore stock is 

found primarily along the outer continental shelf and continental slope from Georges Bank to 

Florida (Waring et al. 2011). The coastal stocks are found along the coast from south of Long 

Island Sound to Florida and are generally less than 7.5 km from shore while the estuarine stocks 

are found in bays and estuaries from North Carolina to Florida (Caldwell 2001; Garrison et al. 

2003; Gubbins 2002a, 2002b, 2002c; Gubbins et al. 2003; Litz 2007; McLellan et al. 2003; Read 

et al. 2003; Rosel et al. 2009; Speakman et al. 2006; Stolen et al. 2007; Torres et al. 2003; Urian 

et al. 1999; Weller 1998). Bottlenose dolphins are found in the North Atlantic, Mid-Atlantic, 

South Atlantic and Straits of Florida BOEM Planning Areas. Sighting, stranding, and fishery 

bycatch locations of bottlenose dolphins are shown in Figure 2.20-1.

2.20.3 General Abundance

The largest population in U.S. Atlantic waters is the offshore stock (n=81,588) (Table 2.20.1). 

Population estimates are not available for all stocks, especially the recently defined estuarine 

populations. 
91

Table 2.20.1 U.S. Atlantic Bottlenose Dolphin Population Estimates

Stock Area Nbest Year

Western North Atlantic, offshore 81,588 (0.17) 2002/2004

Western North Atlantic, coastal, northern migratory 9,604 (0.36) 2002

Western North Atlantic, coastal, southern migratory 12,482 (0.32) 2002

Western North Atlantic, coastal, S. Carolina/Georgia 7,738 (0.23) 2002/2004

Western North Atlantic, coastal, northern Florida 3,064 (024) 2002/2004

Western North Atlantic, coastal, central Florida 6,318 (0.26) 2002/2004

Northern North Carolina Estuarine System Unk Na

Southern North Carolina Estuarine System 2,454 (0.53) 2002

Charleston Estuarine System Unk Na

Northern Georgia/Southern South Carolina 

Estuarine System

Unk Na

Southern Georgia Estuarine System Unk Na

Jacksonville Estuarine System Unk Na

Indian River Lagoon Estuarine System Unk Na

Biscayne Bay Unk na

Florida Bay 514 (0.17) 2003

(CV is reported in parentheses) (Waring et al. 2011)

2.20.4 Habitat Preference

Wells and Scott (1999) reported that bottlenose dolphins are a cosmopolitan species. As Wells 

and Scott (2005) summarized, bottlenose dolphins can be found in both coastal and pelagic 

waters, near oceanic islands over the continental shelf and break, and in estuarine habitats. 

Kenny (1990) used CETAP data to describe the association of bottlenose dolphins with certain 

environmental characteristics. He found that dolphins were sighted in depths from 0 to 4,932 m 

with a mean of 587.9 m and sea surface temperatures from 1.1° to 31.1°C with a mean of 19.7°C 

and a distinct mode at 10-22.5°C. The offshore stock was associated with a wider range of 

temperature and geography. Along the U.S. Atlantic coast, there are 15 stocks of dolphins 

inhabiting a variety of offshore, coastal and estuarine habitats which are detailed in the 2011

stock assessment reports (Waring et al. 2011). 

2.20.5 Stock Structure

On-going research continues to elucidate and redefine bottlenose dolphin stock structure along 

the U.S. Atlantic coast. In their literature review of bottlenose dolphin research, Shane et al. 

(1986) found that many studies (behavioral, morphological, biochemical, etc.) indicated distinct 

stocks in some areas. Mead and Potter (1995) were able to identify two populations (offshore 

and coastal) of bottlenose dolphins along the U.S. Atlantic by analyzing distribution, size, skull 

morphology, food habits and parasite burden. Additionally, their analyses of skull morphology 

indicated that the coastal samples represented more than one population. Torres et al. analyzed 

304 samples collected in the Atlantic from New York to central Florida up to 515 km from shore. 

Using CART (Classification and Regression Tree) analysis, they found a statistically significant 

break in the coastal compared with offshore ecotypes at 34 km offshore. 
92

Rosel et al. (2009) identified a minimum of five populations in near-shore coastal and estuarine 

areas along the U.S. Atlantic coast from New York to Florida. They analyzed a mitochondrial 

control region sequence and 18 microsatellites in 404 samples. This study demonstrates that 

although bottlenose dolphins are a highly mobile animal living in a habitat with no obvious 

barriers to dispersal, they exhibit a significant amount of genetic structure.

As of 2011, a combination of genetic analyses, photo-ID studies and field work has identified 15 

bottlenose dolphin stocks along the U.S. Atlantic coast (Maine to Florida Keys) (Caldwell 2001; 

Garrison et al. 2003; Gubbins 2002a, 2002b, 2002c; Gubbins et al. 2003; Litz 2007; Mazzoil et 

al. 2005; McLellan et al. 2003; Read et al. 2003; Rosel et al. 2009; Speakman et al. 2006; Stolen 

et al. 2007; Urian et al. 1999; Weller 1998). These 15 stocks can generally be classified into one 

of three morphotypes: offshore (n=1), coastal (n=5) or bay/estuarine (n=9). See also the 2011

bottlenose dolphin stock assessment reports for more detail on each stock 

(http://www.nmfs.noaa.gov/pr/pdfs/sars/). 

2.20.6 Life History Traits

Mead and Potter (1990) present life history data based on bottlenose dolphins (n=172) that had 

stranded on the coasts of North Carolina, Virginia and Maryland between 1972 and 1980. They 

found that females attain sexual maturity at a mean age of 10.64 years. There were not enough 

males in their sample to estimate male maturity. The youngest mature male in their study was at 

least 8 years old. Sergeant et al. (1973) estimated that males from the northeast coast of Florida 

mature at 10-15 years. In summarizing available life history data for the Florida population, 

Odell (1975) found that females become sexually mature at 5-12 years (length = 220-235cm) and 

males at 10-13 years (length = 245-260cm). Mead and Potter (1990) documented a peak in 

calving in the spring (March) for the population along the central U.S. Atlantic coast. McFee et 

al. (2007) found two peaks in dolphin strandings along the coast of South Carolina: spring and 

autumn. These two seasons were highly significant for neonate strandings indicating a bimodal 

reproductive cycle. 

2.20.7 Food Habits

Wells and Scott (1999) report bottlenose dolphins’ diet includes a variety of fish and squid with a 

preference for sciaenids, scombrids, and mugilids. Bottom dwelling fish and noise producing 

fish are also both important.

Mead and Potter (1990) analyzed the stomach contents of 172 bottlenose dolphins that stranded 

along the coasts of North Carolina, Virginia, and Maryland from 1972-1980. They found that 

three prey species were dominant: weakfish or sea trout (Cynoscion regalis), croaker 

(Micropogonias undulatus), and spot (Leiostomus xanthurus). Gannon and Waples (2004)

analyzed the stomach contents of 146 bottlenose dolphins (coastal estuary morphotype, no 

offshore samples were included) that had stranded along the Mid-Atlantic coast or were caught 

incidentally in fishing gear from 1993-2001. The most frequently occurring prey were sciaenid

fishes. In terms of mass, croaker was highest in dolphins that had stranded in estuaries while 

weakfish was highest in the stomachs of dolphins stranded on ocean beaches. Inshore squid 

(Loligo sp.) were also found in the ocean dolphins’ diet but not in that of estuarine dolphins. 
93

Barros and Wells (1998) found only fish in the stomach contents of 19 dolphins that had stranded 

in Sarasota Bay, Florida. Many of the prey species identified were associated with sea grass 

beds to a certain extent and the main species were soniferous. Berens McCabe et al. (2010) also 

analyzed stomach content analysis of stranded dolphins (n=15) and prey availability in Sarasota 

Bay, Florida. The most important prey were: gulf toadfish (Opsanus beta), pinfish (Lagodon 

rhomboides), ladyfish (Elops saurus) and spotted seatrout (Cynoscion nebulosus). They also 

found that although soniferous fish were only 6.3% of the available prey, they made up 51.9% of 

the dolphins’ diet. The dolphins selected against fish in the families Gerridae, Clupeidae and 

Sparidae.

In their study on group-hunting in Cedar Key, Florida, Gazda et al. (2005) found that individual 

dolphins have specific behavioral roles (e.g., driver vs. barrier dolphin). They observed two 

different groups that in each group an individual dolphin that was always responsible for herding 

the fish.

2.20.8 Health

2.20.8.1 Strandings

Bottlenose dolphin strandings have been documented along most of the U.S. Atlantic coast. The 

largest stranding event occurred from June of 1987 to May of 1988 when a total of 742 dolphins 

were found dead from New Jersey to Florida. (See the Disease section below for details.) It was 

estimated that over 50% of the inshore population had died in the affected areas (Lipscomb et al. 

1994). This event led to the listing of coastal bottlenose dolphins as “Depleted” under the 

MMPA. 

McFee and Hopkins-Murphy (2002) analyzed bottlenose dolphin strandings along the coast of 

South Carolina 1992-1996. They found that 49% of the strandings had occurred between April 

and July and the greatest number had occurred in July. There was an increase in strandings in 

the northern part of the state from November to March. Although neonate strandings occurred 

during every month except for March and October, 55% of the neonate strandings happened 

between May and July. Twenty-three percent of the dolphins had died as a result of human 

interaction (including fisheries interactions). McFee et al. (2007) analyzed South Carolina 

stranding data from 1997-2003. They found that the number of strandings peaked in the spring 

and autumn. Rope entanglements were the most common human interaction.

Given the complex population structure along the U.S. Atlantic coast, stranded dolphins were 

assigned to a stock based on genetics, location, and/or season as much as possible. These data 

are summarized in Table 2.20.2. More bottlenose strandings were attributed to the coastal 

southern migratory stock than any other (n=588, 38%). For some stocks only cumulative 

stranding data were available; these are summarized in Table 2.20.3. See Waring et al. 2011 for 

details.
94

Table 2.20.2 Bottlenose Dolphin Strandings Potentially Attributed to a Stock by Year 

Stock Area 2004 2005 2006 2007 2008 Total

Western North Atlantic, offshore Na Na Na Na Na Na

Western North Atlantic,

coastal northern migratory

121

(24)

85

(11)

98

(17)

94

(12)

86

(13)

484

(77)

Western North Atlantic,

coastal southern migratory

134

(31)

124

(21)

104

(16)

118

(19)

108

(20)

588

(107)

Northern North Carolina

Estuarine System

83

(25)

93

(16)

79

(14)

88

(13)

79

(13)

207

(81)

Southern North Carolina

Estuarine System

27

(5)

12

(3)

13

(2)

12

(4)

14

(4)

78

(18)

Charleston Estuarine System 12

(2)

10

(3)

13

(2)

14

(3)

Na 49

(10)

Indian River Lagoon

Estuarine System

32

(8)

35

(5)

38

(13)

51

(10)

Na 156

(36)

Total 409

(95)

359

(59)

345

(64)

377

(61)

287

(50)

1562

(329)

(The number of dolphins that showed evidence of human interaction is in parentheses) (Waring et 

al. 2011)

Table 2.20.3 Bottlenose Stocks for which Only Cumulative Data is Available 

Stock Area Years # of Strandings

Western North Atlantic, 

coastal, S. Carolina/Georgia 2004-2008 128 (5)

Western North Atlantic, 

coastal northern Florida 2004-2008 78 (3)

Western North Atlantic, 

coastal, central Florida 2004-2008 82 (6)

Northern Georgia/Southern South Carolina Estuarine 

System 2003-2007 51 (0)

Southern Georgia Estuarine System 2003-2007 15 (0)

Jacksonville Estuarine Stock 2003-2007 16 (0)

Biscayne Bay 2003-2007 3* (0)

Florida Bay 2003-2007 7 (0)

Total 380 (14)

(The number of cases where evidence of human interaction was found is in parentheses)

*One of these animals was identified as an offshore morphotype.
95

2.20.8.2 Contaminants

Kuehl et al. (1991) analyzed chemical residues (e.g., pesticides, polychlorinated biphenyl (PCB), 

polybrominated biphenyl (PBB), and polybrominated diphenyl ether (PBDPE)) in blubber and/or 

organ tissue from bottlenose dolphins that had died during the 1987-88 epizootic. They found 

that, on average, levels were higher in adult males than females. They also found that the 

bottlenose dolphins analyzed had higher concentrations than either common or white-sided 

dolphins from the western North Atlantic.

Since that study, many studies have been performed on contaminant levels in U.S. Atlantic 

bottlenose dolphins (Fair et al. 2010, 2007; Houde et al. 2006; Lahvis et al. 1995; Wells et al. 

2005; Yordy et al. 2010a, 2010b, 2010c). Fair et al. (2010, 2007) analyzed contaminant blubber 

burdens in wild bottlenose dolphins from the Indian River Lagoon and Charleston Estuarine 

populations collected 2003-2005. Dolphins from the two populations had accumulated a similar 

suite of contaminants. They found that both populations, but especially the animals from the 

Charleston Estuarine population, exhibited some of the highest levels of contaminants (PCB, 

DDT, PBDE) documented in marine mammals. The levels they reported are at or above levels at 

which adverse effects have been described. Fair et al. (2007) and Wells et al. (2005) also showed 

that adult males and juveniles had burdens that were higher than that of females (due to 

offloading via pregnancy and lactation). Houde et al. (2006) also analyzed samples from the 

Indian River Lagoon and Charleston Estuarine populations. They found that dolphins from the 

Charleston population had much higher levels of PCB and OH-PCB (measured in plasma) than 

the Indian River Lagoon dolphins but did not differ from animals sampled in Delaware Bay, 

New Jersey. 

Schwacke et al. (2002) found that female dolphins (mostly primiparous) from populations near 

Beaufort, North Carolina, Sarasota, Florida, and Matagorda Bay, Texas all were at risk for 

reproductive effects from long term exposure to PCB’s. 

Yordy et al. (2010a) analyzed 13 tissues from 4 bottlenose dolphins that had stranded or had 

been incidentally killed in fishing nets in North Carolina, Virginia, or Florida. Their goal was to 

provide a description of how POP’s were distributed in bottlenose dolphins. They found that 

over 90% of POP accumulation occurred in the blubber. Their study suggests that as blubber is 

metabolized, POP’s may redistribute to other tissues. Schwacke et al. (2011) studied PCBrelated toxic effects in bottlenose dolphins in Georgia. Their results showed that anemia, 

hypothyroidism, and immune system suppression were all associated with the PCB exposure.

Schaefer et al. (2011) reported on the association of total mercury concentrations in blood and 

skin and endocrine, hepatic, renal and hematological parameters in dolphins that were sampled in 

Indian River Lagoon, Florida and Charleston Harbor, South Carolina. Stavros documented trace 

elements in stranded and wild-caught bottlenose dolphins from South Carolina to Indian River 

Lagoon, Florida, from 2000-2008.
96

2.20.8.3 Disease

As described in the Stranding section above, a large bottlenose dolphin die-off occurred June 

1987 to May 1988 from New Jersey to Florida. Lipscomb et al. (1994) analyzed lung and lymph 

node samples from 79 of these dolphins. Their results showed that morbillivirus-induced disease 

was prevalent in dolphins that had died during this epizootic. The frequent occurrence of 

mobilliviral antigen in tissues and various bacterial and fungal infections indicated 

moribillivirus-mediated immunosuppression. Bossart et al. (2010) looked for morbillivirus 

antigens in samples taken in 2003-2007 from free-ranging bottlenose dolphins from the Indian 

River Lagoon and Charleston Estuarine populations (n=234). They found that 9.8% of the 

Indian River Lagoon animals sampled were positive for morbillivirus titers. Some of the animals 

sampled were old enough to have survived the 1987-1988 die-off, but others were not. The 

Charleston animals were seronegative. These results show that morbillivirus infections are 

occurring in the Indian River Lagoon without a large scale epizootic.

Fauquier et al. (2009) documented the prevalence of lungworm in live and dead stranded 

bottlenose dolphins in southwest Florida from 2003 to 2005. They found lungworm in 77% of 

the dead animals necropsied; 0% blowhole swabs and only 3% fecal cytology from live dolphins 

showed lungworm infection. Neonates and calves showed the highest prevalence of active 

infection. This study also provided evidence of transplacental infection (as demonstrated by an 

infected stillborn calf). 

Murdoch et al. (2010) studied lacaziosis in bottlenose dolphins in Florida. They found that 

estuarine dolphins had a higher rate of infection than dolphins found in the Atlantic Ocean. In 

their study on papillomavirus antibody presence, Rehtanz et al. (2010) found that 90% of the 

wild dolphins they sampled from Indian River Lagoon, Florida, and estuarine waters near 

Charleston, South Carolina, were antibody positive. 

2.20.9 Acoustics

Southall et al. (2007) classified Tursiops sp. into a mid-frequency cetacean functional hearing 

group with an estimated auditory bandwith of 150 Hz to 160 Hz. Bottlenose dolphins make 

three kinds of sounds: whistles, echolocation clicks, and burst-pulse sounds (Wells and Scott 

2009). Wells and Scott (2009) summarized the purpose of each sound type: individual dolphins 

produce a unique “signature whistle” that is used for identity; echolocation clicks range from 40-

130 kHz and are likely used to find prey, to navigate, and to spot predators; the burst-pulse 

sounds are likely used in social interactions.

Janik (2000) found that wild bottlenose dolphins in Moray Firth, Scotland, exhibit vocal 

matching–one dolphin responds to another by imitating the same whistle type. This matching 

occurred over distances up to 580 m. In their study of the resident population of bottlenose 

dolphins in Sarasota Bay, Florida, Cook et al. (2004) found that signature or probable signature 

whistles make up ~52% of all whistles produced by free-ranging dolphins.

Ibsen et al. (2009) studied the functional bandwidth of a 19-year-old captive female bottlenose 

dolphin. They found that during echolocation, the dolphin paid attention to frequencies 29-42 

kHz (her functional bandwidth). The upper end of this range is close to the upper limit of her 
97

hearing range and the lower limit seemed to be a function of background noise, target reflection 

and frequency content of the clicks themselves (Ibsen et al. 2009). 

There are many studies of temporary threshold shifts in bottlenose dolphins (Finneran et al. 

2005, 2005, 2010, 2000; Mooney et al. 2009; Nachtigall et al. 2003; Schlundt et al. 2000). 

Sound exposure level and duration of exposure are both important factors. Finneran et al. (2000)

used a behavioral response paradigm to examine masked underwater hearing thresholds before 

and after exposure to simulated underwater explosions. Although they did not find any change 

in masked-hearing thresholds, they did find a behavioral change in the two dolphins (5 kg at 9.3 

km and 5 kg at 1.5 km).

Acevedo-Gutierrez and Stienessen (2000) analyzed the sounds groups of feeding and nonfeeding bottlenose dolphins made around Isla del Coco, Costa Rica. They classified the sounds 

into three types: whistles, click trains, and pulse bursts. Their results showed that feeding 

dolphins produced more whistles per minute than non-feeding dolphins. Feeding dolphins 

produced more whistles than click trains or pulse bursts. 

2.20.10 Fisheries By-Catch and Entanglement

The Bottlenose Dolphin Take Reduction Team (BDTRT) was created out of concern for the 

serious injury and deaths of coastal bottlenose dolphins interacting with 9 fisheries: the North 

Carolina inshore gillnet, Southeast Atlantic gillnet, Southeastern U.S. shark gillnet, U.S. MidAtlantic coastal gillnet, Atlantic blue crab trap/pot, Mid-Atlantic haul/beach seine, North 

Carolina long haul seine, North Carolina roe mullet stop net, and Virginia pound net. The Take 

Reduction Plan developed by the BDTRT included provisions for research and education, 

modifications of fishing practices for small, medium, and large-mesh gillnet fisheries from New 

York to Florida and seasonal closures for certain commercial fisheries in state waters.
98

Table 2.20.4 Most Recent Reported/Estimated Incidental Mortality of Bottlenose Dolphins by 

Stock

Stock Fisheries Included Total

Western North Atlantic, offshore

(2006)

Northeast Sink Gillnet, Mid-Atlantic 

Gillnet

Min = 0

Max = 0

Western North Atlantic, 

coastal northern migratory (2008)

Mid-Atlantic Gillnet, Virginia Pound 

Net, Beach-based Gillnet Gear, Blue 

Crab Pot, Other Pot, Fishery Research

Min = 7.3

Max = 7.9

Western North Atlantic, 

coastal southern migratory (2008)

Mid-Atlantic Gillnet, Virginia Pound 

Net, Blue Crab Pot, Other Pot, Fishery 

Research

Min = 9.5

Max = 43.0

Western North Atlantic, 

coastal, S. Carolina/Georgia

Unknown Unknown

Western North Atlantic, 

coastal northern Florida (2008)

No observer coverage in 2008. Unknown

Western North Atlantic, 

coastal, central Florida (2008)

Southeast Gillnet Min = 0

Max = 0

Northern North Carolina 

Estuarine System (2008)

Mid-Atlantic Gillnet, Virginia Pound 

Net, Beach-based Gillnet Gear, Blue

Crab Pot, Other Pot, Fishery Research

Min = 2.7

Max = 14.9

Southern North Carolina 

Estuarine System (2008)

Mid-Atlantic Gillnet, Blue Crab Pot,

Other Pot, Fishery Research

Min = 0.5

Max = 0.9

Charleston Estuarine System Unknown Unknown

Northern Georgia/Southern South 

Carolina Estuarine System

Unknown Unknown

Southern Georgia Estuarine System Unknown Unknown

Jacksonville Estuarine System Unknown Unknown

Indian River Lagoon 

Estuarine System

Unknown Unknown

Biscayne Bay Unknown Unknown

Florida Bay Unknown Unknown

(Waring et al. 2011)

(Minimums and maximums are presented, as there is uncertainty associated with assigning some 

by-caught dolphins to a specific stock given their spatial and temporal overlap. Year of estimate 

is in parentheses after stock name. Observer coverage is not available in all areas.)

2.20.11 Vessel Interactions

Bejder et al. (2006) compared dolphin abundance within adjacent tourism and control sites in 

Shark Bay, Australia, for three consecutive 4.5-year periods (total time period = 13.5 years). 

Tourism boats increased from 0 to 1 then to 2 dolphin-watching boats. The change from no 

tourism to one operator did not significantly impact dolphin abundance. The change from one to 

two operators caused a 14.9% (95% CI= −20.8 to −8.23) decrease in abundance. The authors 

conclude that this disturbance was probably not a major threat to the bottlenose dolphin 

population in Shark Bay because it is large and genetically diverse. They do point out that a 

similar decline in a smaller, more isolated population could be devastating. In a study on the 

impact of dolphin-watching tour boats on bottlenose dolphins in the Bay of Islands, New 
99

Zealand, Constantine et al. (2004) found that bottlenose dolphin resting behavior decreased as 

boat number increased. 

Buckstaff (2004) studied the effects of watercraft on bottlenose dolphin acoustic behavior. She 

found that whistle rate increased and suggested this either served to bring dolphins together or to 

compensate for signal masking.

2.20.12 Energy Projects

Both extractive and renewable offshore energy projects have the potential to impact the marine 

environment in a variety of ways, including habitat alteration and the introduction of noise via 

seismic exploration activities (e.g., airguns), vessel/aircraft activity, construction and operation

(Geraci and St. Aubin 1980, Bain and Williams 2006, Thompsen et al. 2006, Cada et al. 2007, 

Compton 2008, Evans 2008, MMS 2008, Burgman 2010, Boehlert and Gill 2010, Dolman and 

Simmonds 2010, Edrén et al. 2010, Bush 2011, ICES 2011). The impact of these activities on 

marine mammals is unclear. 

Stone (2003) studied the effects of seismic activity on cetaceans in UK waters. She reported that 

sighting rates of small odontocetes were significantly lower when large airgun arrays were being 

fired. She also found that in general, small odontocetes showed the strongest avoidance behavior 

to seismic noise (compared to baleen, killer, sperm and pilot whales). The 2010 Report of the 

Working Group on Marine Mammal Ecology (ICES 2010) stated that very little is known about 

the impact of the construction and operation of offshore wind-farms. Madsen et al. (2006b)

reviewed available current information on wind farms and marine mammals and wrote that the 

noise impact is more severe during construction than operation. This was found to be the case 

for impacts to harbor porpoise (see Carstensen et al. [2006], Koschinski et al. [2003]). David 

(2006) wrote that pile driver-generated noise has the potential to impact dolphins by temporary 

displacement and interference with communication. Pile-driving noise associated with the 

construction of two wind turbines off the coast of northeast Scotland was related to noise 

exposure criteria for bottlenose dolphins. It was concluded that auditory injury would have 

occurred within 100 m of the pile-driving and behavioral disturbance could have occurred up to 

50 km away (Bailey et al. 2010). The 2011 Report of the Working Group of Marine Mammal 

Ecology (ICES 2011) reported that porpoise detection (T-POD data) was lower during 

construction of a tidal turbine compared to before and after construction. 
100

2.20.13 Data Gaps and Research Recommendations

The best abundance estimates for bottlenose dolphins are now anywhere from 6 to 8 years old 

and should be updated. No abundance estimates are available for some of the populations (e.g.,

the newly defined estuarine stocks; see Table 2.20.1). Given the recent revision of bottlenose 

dolphin stock delineations, it is likely that our understanding of bottlenose dolphin stock 

structure will continue to evolve. Studies have shown differences in food habits (Gannon and 

Waples 2004) and contaminant burdens (Fair et al. 2010, 2007; Houde et al. 2006) between the 

various U.S. Atlantic populations. More specific information about each population (e.g., food 

habits, life history, contaminant burden, etc.) is required.

2.21 PANTROPICAL SPOTTED DOLPHIN (STENELLA ATTENUATA)

2.21.1 Legal Status

The pantropical spotted dolphin is not listed under the Endangered Species Act. The IUCN Red 

List lists its status as “Least Concern.” It is afforded protection in U.S. waters under the MMPA.

2.21.2 General Distribution

Pantropical spotted dolphins are found in tropical and subtropical waters around the world 

(Perrin 2009b; Perrin and Hohn 1994). There are observations of pantropical spotted dolphins 

along the U.S. Atlantic coast in the BOEM North Atlantic, Mid-Atlantic, South Atlantic and 

Straits of Florida Planning Areas. Sighting, stranding, and fishery bycatch locations of 

pantropical spotted dolphins are shown in Figure 2.21-1.

2.21.3 General Abundance

The total population of pantropical spotted dolphins along the U.S. Atlantic coast is unknown. 

Waring et al. (2011) report a best estimate of 4,439 (CV=0.49) based on a combination of ship 

and aerial surveys conducted June-August 2004 from Florida to the Bay of Fundy. NMFS 

divided these surveys into two areas: the “North Atlantic” includes waters north of Maryland 

(38°

N) to the Bay of Fundy (45°N) and the “South Atlantic” includes waters from Maryland 

(38°N) south to Florida (27.5°N). The 2004 pantropical spotted dolphin estimate for the North 

Atlantic is 0 (CV=0). The 2004 estimate for the South Atlantic is 4,439 (CV=0.49). The NMFS 

North Atlantic Survey was conducted in part of the BOEM North Atlantic Planning Area; the 

NMFS South Atlantic Survey was conducted in parts of the BOEM Mid-Atlantic and South 

Atlantic Planning Areas. It is important to note that the surveys did not necessarily cover the 

entire BOEM planning areas but likely sampled a subsection of these areas based on prior 

knowledge of species distribution and survey goals. The 2004 survey did not cover waters within 

the Straits of Florida planning area. 

2.21.4 Habitat Preference

In the Atlantic Ocean, pantropical spotted dolphins are a “dolphin of the high seas and oceanic 

islands” (Perrin and Hohn 1994). In the Pacific Ocean, the offshore form of the pantropical 

spotted dolphin is most abundant in waters that have a sharp thermocline, SST of 25°

C or higher 

and salinity less than 34ppt (Perrin 2009b). The NMFS 2004 survey that provided the most 
101

recent abundance estimate (n=4,439, CV=0.49) occurred along the outer continental shelf and 

continental slope where water depth was equal or greater than 50 m (Waring et al. 2011).

2.21.5 Stock Structure

The western North Atlantic population is considered separate from the Gulf of Mexico 

population for management purposes but additional data are needed to elucidate stock structure 

along the U.S. Atlantic coast (Waring et al. 2011). 

2.21.6 Life History Traits 

Myrick et al. (1986) studied the reproductive biology of female spotted dolphins that had been 

incidentally killed in the yellowfin tuna fishery in the eastern tropical Pacific Ocean from 1973-

1981. They found that average age at sexual maturity for all years ranged from 10.7-12.2 years 

(mean = 11.4). The calving interval was 3.03 years and lactation lasted 1.66 years. Age at first 

maturity for males killed in the same fishery (1973-1982) was 14.7 years (Hohn et al. 1985). In 

their summarization of data from the Pacific Ocean, Perrin and Hohn (1994) found that gestation 

is 11.2-11.5 months.

2.21.7 Food Habits

Perrin and Hohn (1994) report that the pantropical spotted dolphins’ diet consists of small 

epipelagic fish, squid, and crustaceans. Robert and Chivers (1997) analyzed the contents of 428 

stomachs of animals incidentally killed in tuna-purse seine nets in the eastern tropical Pacific 

from 1989-1991. Lantern fish (family Myctophidae) were the most frequently observed fish and

flying squid (family Ommastrephidae) were the most frequently observed cephalopod. The high 

frequency of mesopelagic fish, coupled with the occurrence of fuller stomachs in dolphins that 

were killed in the morning, suggests that pantropical spotted dolphins feed at night when 

mesopelagic species are moving towards the surface. 

Bernard and Hohn (1989) analyzed the stomach contents of 11 pregnant and 12 lactating spotted 

dolphins that were incidentally killed in the yellowfin tuna fishery in the eastern tropical Pacific 

from 1971-1985. They found that the diet of the two groups differed greatly: pregnant dolphins 

consumed more squid and lactating dolphins consumed more fish (by mass and proportion). 

Archer and Robertson (2004) reported that calves start taking food at 6 months but some nurse 

until 2 years.

2.21.8 Health

2.21.8.1 Strandings

Four pantropical spotted dolphins stranded in Florida in 1999 and 3 were reported stranded 

along the U.S. Atlantic coast from 2001 to 2005. One of these stranded in South Carolina and 

two in Florida (Waring et al. 2011). The pantropical dolphin that stranded in South Carolina was 

considered part of a Mid-Atlantic Small Cetacean UME declared from July 2004 to January 

2005–no single cause was identified for this UME (Waring et al. 2011). (Waring et al. 2011). 

None of the stranded animals showed signs of fishery or human interaction. A review of 

Northeast and Southeast U.S. marine mammal stranding records for 2005-2009 yields no 

strandings of pantropical spotted dolphins along the Atlantic coast.
102

2.21.8.2 Contaminants

Andre et al. (1990a) found cadmium levels for most organs between 1 and 5 mg Cd/kg in 

pantropical spotted dolphins from the Pacific Ocean; age, body weight, and location of capture 

all influenced the levels. In a separate study by Andre et al. (1990b), mercury levels for most 

organs measured between 1 and 5 mg Hg/kg in pantropical spotted dolphins from the Pacific 

Ocean.

2.21.8.3 Disease

Perrin (2001) reports that parasitism may be a significant cause of natural mortality. Perrin and 

Powers (1980) found that high mortality appeared to be correlated with infestation by the 

nematode Crassicauda sp. or some related factor.

2.21.9 Acoustics

Perrin and Hohn (1994) summarized a report by Popper (1980) that pantropical spotted dolphins

produce pulses ranging up to 150 kHz. Southall et al. (2007) classified Stenella spp. into a midfrequency cetacean functional hearing group with an estimated auditory bandwith of 150 Hz to 

160 Hz. No other specific information about pantropical spotted dolphin acoustics is available.

2.21.10 Fisheries By-catch and Entanglement

The only fishery in the U.S. Atlantic with reported incidental mortality is the pelagic long-line 

(Waring et al. 2011). The mean annual mortality of undifferentiated spotted dolphins (Stenella 

frontalis, Stenella attenuata) for this fishery was 6 (CV=1) for the years 2001-2005. 

2.21.11 Vessel Interactions

A review of Northeast and Southeast U.S. stranding data between 2005 and 2009 yielded no 

records of vessel interactions with pantropical spotted dolphins.

2.21.12 Energy Projects

Both extractive and renewable offshore energy projects have the potential to impact the marine 

environment in a variety of ways, including habitat alteration and the introduction of noise via 

seismic exploration activities (e.g., airguns), vessel/aircraft activity, construction and operation

(Geraci and St. Aubin 1980, Bain and Williams 2006, Thompsen et al. 2006, Cada et al. 2007, 

Compton 2008, Evans 2008, MMS 2008, Burgman 2010, Boehlert and Gill 2010, Dolman and 

Simmonds 2010, Edrén et al. 2010, Bush 2011, ICES 2011). The impact of these activities on 

marine mammals is unclear. 

Stone (2003) studied the effects of seismic activity on cetaceans in UK waters. She reported that 

sighting rates of small odontocetes were significantly lower when large airgun arrays were being 

fired. She also found that in general, small odontocetes showed the strongest avoidance behavior 

to seismic noise (compared to baleen, killer, sperm and pilot whales). The 2010 Report of the 

Working Group on Marine Mammal Ecology (ICES 2010) stated that very little is known about 

the impact of the construction and operation of offshore wind-farms. Madsen et al. (2006b)

reviewed available current information on wind farms and marine mammals and wrote that the 

noise impact is more severe during construction than operation. This was found to be the case 
103

for impacts to harbor porpoise (see Carstensen et al. (2006), Koschinski et al. (2003)). David 

(2006) wrote that pile driver-generated noise has the potential to impact dolphins by temporary 

displacement and interference with communication. The 2011 Report of the Working Group of 

Marine Mammal Ecology (ICES 2011) reported that porpoise detection (T-POD data) was lower 

during construction of a tidal turbine compared to before and after construction. No information 

specific to pantropical spotted dolphins was found.

2.21.13 Data Gaps and Research Recommendations

The best abundance estimate is now 7 years old and needs to be updated. There is very little 

recent information on distribution outside of the summer months. Most of the information about 

the pantropical spotted dolphins’ food habits, contaminant burden or stock structure comes from 

parts of their range that is outside of the U.S. Atlantic coast (e.g., from the Pacific Ocean). 

2.22 ATLANTIC SPOTTED DOLPHIN (STENELLA FRONTALIS)

There are two forms of the Atlantic spotted dolphin. One is large and heavily spotted; the other 

is smaller and less spotted–see Habitat Preference and Stock Structure sections below.

2.22.1 Legal Status

The Atlantic spotted dolphin is not listed under the Endangered Species Act. The IUCN Red 

List lists its status as “Data Deficient.” It is afforded protection in U.S. waters under the MMPA.

2.22.2 General Distribution

This species is found in the warm temperate and tropical Atlantic Ocean only (Perrin 2009). 

They are found in the BOEM North Atlantic, Mid-Atlantic, South Atlantic and Straits of Florida 

Planning Areas (Perrin et al. 1994a, Waring et al. 2011). Sighting, stranding and fishery bycatch 

locations of Atlantic spotted dolphins are shown in Figure 2.22-1.

2.22.3 General Abundance

Waring et al. (2011) provided a best estimate of 50,978 (CV=0.42) from Florida to the Bay of 

Fundy, June-August 2004. The portion of the NMFS June-August 2004 survey that was 

conducted from Maryland to the Bay of Fundy (encompassing the North and part of the MidAtlantic planning areas) was used for an abundance estimation of 3,578 (CV=0.48) Atlantic 

spotted dolphins (Palka 2006). A survey of the outer continental shelf between 27.5 o

N and 38 o

N in June-August 2004 produced an estimate of 47,400 (CV=0.45). Most of these animals were 

sighted north of Cape Hatteras, North Carolina, an area within the Mid-Atlantic Planning Area 

(Waring et al. 2011). No abundance estimates are available for the Straits of Florida Planning 

Area because the NMFS 2004 surveys occurred north of this area.

2.22.4 Habitat Preference

The large, heavily-spotted form prefers the continental shelf and shelf-break usually within the 

200 m curve (Perrin 2009a). The smaller, less spotted version is found in pelagic, offshore waters 

and near oceanic islands (Perrin et al. 1994a). Hamazaki (2002) correlated environmental 

variables associated with spotted dolphin (Atlantic and pantropical) sightings and predicted a 
104

habitat ranging over the southern half of the mid-western Atlantic in June and expanding to the 

entire mid-western Atlantic in August. Of the mid-Atlantic offshore species studied, spotted 

dolphins were seen in the warmest waters and the mildest slopes. A satellite-tagging study done 

on an Atlantic spotted dolphin in the Gulf of Mexico by Davis et al. (1996) generated 

information on travel and dive patterns of the species. During the 24 days the tag was attached, 

mean minimum travel distance was 72 km/day. The animal ranged within the 20-60m isobaths 

at a mean depth of 32.6 m. The deepest dives made were 40-60 m deep and lasted up to 6 

minutes, though most dives were less than 2 minutes in duration and to depths of less than 30 m 

(Davis et al. 1996). Griffin and Griffin (2003) examined habitat partitioning by Atlantic spotted 

dolphins, bottlenose dolphins, and loggerhead sea turtles in the Gulf of Mexico and found that, at 

depths of 20-180 m, the spotted dolphin was the most common species. Other variables, such as 

distance from shore, temperature, salinity, chlorophyll, and transmittance, were also examined. 

Griffin and Griffin (2004) also examined temporal patterns of Atlantic spotted dolphin 

distribution off the Florida Gulf of Mexico shelf and found consistent season variations, with 

higher densities found during the cooler months of November-May. Off the coast of Brazil, 

Atlantic spotted dolphins have been observed over the continental shelf and slope in waters up to 

100 m of depth (Moreno et al. 2005). In southern Brazil, strandings occur predominantly in the 

summer months when water temperatures are influenced by the warm Brazil current (Moreno et 

al. 2005).

2.22.5 Stock Structure

Adams and Rosel (2006) used mitchondrial and nuclear DNA analyses to clarify Atlantic spotted 

dolphin stock structure in the Western North Atlantic and Gulf of Mexico. They identified three 

populations: the Gulf of Mexico, Mid-Atlantic Bight (north of 35o

N), and the South Atlantic 

Bight (south of 35o

N). Their results also indicate possible differentiation between coastal and 

offshore dolphins in the Mid-Atlantic Bight area. 

2.22.6 Life History Traits

From a long-term study of a population of dolphins on Little Bahama Bank (east of Florida)

Herzing (1997) estimated that age of maturity for females was 8-15 years and the inter-calving 

interval was 2.96 years (range 1-5 years). Herzing also found that lactation could last up to 5 

years and visibly pregnant females were also observed lactating. 

2.22.7 Food Habits

Perrin et al. (1994) reported a variety of prey, including clupeoid and carangid fishes, squid and 

halfbeaks (Hemiramphus). Aguiar dos Santos and Haimovici (2001) found Loligo plei in the 

stomach of six Atlantic spotted dolphins collected along the coast of Brazil. Bender et al. (2009)

through analysis of video archives of Atlantic spotted dolphin foraging behavior, found evidence 

of maternal teaching. Coordinated feeding, where dolphins herded fish into dense balls, has been 

observed in the Gulf of Mexico (Fertl and Würsig 1995)
105

2.22.8 Health

2.22.8.1 Strandings

A total of 15 Atlantic spotted dolphins were reported stranded along the U.S. Atlantic coast 

(Massachusetts, North Carolina, Georgia, and Florida) from 2001-2005 (Waring et al. 2011). A 

spotted dolphin examined by Estep et al. (2005) that had stranded in 1993 on the Gulf Coast of 

Florida exhibited metastasized testicular tumors. Lesions caused by parasitic infections were 

found in skulls of bycaught spotted dolphins in the Eastern Tropical Pacific by Perrin and 

Powers (1980) in frequencies that suggested that parasitism is a major cause of natural mortality 

in the species. Parasitism was also examined in spotted dolphins that had stranded in the Canary 

Islands between 1992 and 2000 (Jaber et al. 2004, 2006). Eleven of 23 spotted dolphins 

examined in this study exhibited nonspecific chronic reactive hepatitis lesions (Jaber et al. 2004). 

A review of Northeast and Southeast U.S. marine mammal stranding records for 2005-2009 

yielded 11 strandings of Atlantic spotted dolphins along the Atlantic coast, 4 in North Carolina, 4 

in Florida, 2 in Georgia, and 1 in South Carolina.

2.22.8.2 Contaminants

Two Atlantic spotted dolphin calves were included in Watanabe et al.’s (2000) study of PCB’s 

and organochlorine pesticides in small cetaceans stranded along Florida’s Atlantic coast. The 

liver concentrations of several compounds were elevated compared to those in the blubber of 

marine mammals of various regions, even when normalized to lipid content, suggesting exposure 

to sources for these chemicals (Watanabe et al. 2000). In vitro studies showed that multiple 

organelle damage and nuclear budding were observed when spotted dolphin renal cells were 

exposed to mercury (Wang and Pfeiffer 2001) and that selenium had a possible protective effect 

on mercury toxicity (Wang et al. 2001). Pfeiffer et al. (2000) explored fuel oil toxicity in the 

spotted dolphin renal cell culture. 

2.22.8.3 Disease

2.22.9 Acoustics

Atlantic spotted dolphins have been the subjects of acoustic research since Wood’s work on 

captive dolphins at Marineland, Florida, in 1953 (Wood 1953). Acoustic research on Atlantic 

spotted dolphins continued in the 1960s and 1970s (see Caldwell and Caldwell 1966, 1971b; 

Caldwell et al. 1973, 1971). Steiner (1981) published a comparison of whistle vocalizations in 

five species of Atlantic dolphins. The recordings of Atlantic spotted dolphins Steiner used were 

made off the coast of Florida in 1966 and 1967. In their study on free-ranging dolphins, Au and 

Herzing (2003) found the dolphins’ echolocation signals had bi-modal frequency spectra with a 

low-frequency peak between 40 and 50 kHz and a high-frequency peak between 110 and 130 

kHz. Communication signals are discussed by Lammers et al. (2003). Their broad spectrum 

sampling found that the social signals produced by spotted dolphins span the full range of their 

hearing sensitivity and are spectrally quite varied. Burst pulses are predominately ultrasonic. 

Baron et al. (2008) discuss differences in spotted dolphin vocalizations between the Gulf of 

Mexico and the U.S. Atlantic coast. 
106

2.22.10 Fisheries By-Catch and Entanglement

The only recent fishery bycatch information for Atlantic spotted dolphins in the Atlantic is for 

the pelagic longline fishery. One Atlantic spotted dolphin was reported by fishery observers as 

caught in a longline and released injured in 2003 (Garrison and Richards 2004). Waring et al. 

(2010) reported a mean annual mortality of six (CV=1) undifferentiated (pantropical and 

Atlantic) spotted dolphins in the pelagic longline fishery for the years 2001-2005.

2.22.11 Vessel Interactions

In 2007, one Atlantic spotted dolphin stranding mortality in the Northeast and Southeast U.S.

Marine Mammal Stranding Network databases exhibited signs of interaction with a boat 

propeller.

2.22.12 Energy Projects

Both extractive and renewable offshore energy projects have the potential to impact the marine 

environment in a variety of ways, including habitat alteration and the introduction of noise via 

seismic exploration activities (e.g., airguns), vessel/aircraft activity, construction and operation

(Geraci and St. Aubin 1980, Bain and Williams 2006, Thompsen et al. 2006, Cada et al. 2007, 

Compton 2008, Evans 2008, MMS 2008, Burgman 2010, Boehlert and Gill 2010, Dolman and 

Simmonds 2010, Edrén et al. 2010, Bush 2011, ICES 2011). The impact of these activities on 

marine mammals is unclear. 

Stone (2003) studied the effects of seismic activity on cetaceans in UK waters. She reported that 

sighting rates of small odontocetes were significantly lower when large airgun arrays were being 

fired. She also found that in general, small odontocetes showed the strongest avoidance behavior 

to seismic noise (compared to baleen, killer, sperm and pilot whales). The 2010 Report of the 

Working Group on Marine Mammal Ecology (ICES 2010) stated that very little is known about 

the impact of the construction and operation of offshore wind-farms. Madsen et al. (2006b)

reviewed available current information on wind farms and marine mammals and wrote that the 

noise impact is more severe during construction than operation. This was found to be the case 

for impacts to harbor porpoise (see Carstensen et al. [2006], Koschinski et al. [2003]). David 

(2006) wrote that pile driver-generated noise has the potential to impact dolphins by temporary 

displacement and interference with communication. The 2011 Report of the Working Group of 

Marine Mammal Ecology (ICES 2011) reported that porpoise detection (T-POD data) was lower 

during construction of a tidal turbine compared to before and after construction.

Atlantic spotted dolphin reactions to seismic survey airgun operations were studied off the coast 

of Angola (Weir 2008a). Compared to humpbacks and sperm whales which were also studied, 

Atlantic spotted dolphins exhibited the most marked overt response to airgun sound. While there 

was no evidence for lasting or large scale displacement, the Atlantic spotted dolphin encounters 

occurred at a significantly greater distance when airguns were being fired compared to during 

periods of no seismic activity. Positive-approach behavior occurred only when guns were not in 

use. 
107

2.22.13 Data Gaps and Research Recommendations

The best abundance estimate for Atlantic spotted dolphins in the Atlantic Ocean is 7 years old. 

There is limited information on Atlantic spotted dolphin distribution and abundance outside of 

the summer months (June-September). Information on contaminant exposure, life history, and 

diet in Atlantic spotted dolphins is sparse for the western Atlantic. 

2.23 SPINNER DOLPHIN (STENELLA LONGIROSTRIS)

2.23.1 Status

The spinner dolphin is not listed under the Endangered Species Act. The species is considered 

“Data Deficient” on the IUCN Red List. It is afforded protection in U.S. waters under the 

MMPA.

2.23.2 General Distribution

The spinner dolphin is pantropical, found between approximately 30-40°N and 20-40°S 

(Jefferson et al. 2007) in tropical to warm temperate waters (Leatherwood and Reeves 1983a). 

Distribution in the Atlantic is not well known (Waring et al. 2011) but Leatherwood and Reeves 

(1983a) report they that the presence of spinner dolphins has been confirmed from Cape 

Hatteras, North Carolina, to Rio de Janeiro, Brazil. Stranding records exist from North Carolina 

and Florida. It appears that spinner dolphins are found in the BOEM Mid-Atlantic, South 

Atlantic and Straits of Florida Planning Areas. Sighting, stranding and fishery bycatch locations 

of spinner dolphins are shown in Figure 2.23-1.

2.23.3 General Abundance

The number of spinner dolphins off the U.S. Atlantic coast is unknown. The available data are 

not adequate to calculate a minimum estimate (Waring et al. 2011).

2.23.4 Habitat Preference

As summarized in Waring et al. (2011), spinner dolphins have only been sighted in deeper 

(>2000 m) oceanic waters along the U.S. coast. Leatherwood and Reeves (1983a) stated they are 

primarily in deep water/pelagic areas but move into shelf waters off the southeastern U.S. 

2.23.5 Stock Structure

There are 4 subspecies of spinner dolphins: S.l. longirostris is globally distributed; S.l. orientalis

is endemic to the eastern tropical pacific; S.l. centroamericana is located off the west coast of 

Central America; and S.l. roseiventris is a dwarf form located in central Southeast Asia. Farro et 

al. (2008) developed eight polymorphic microsatellite DNA markers from skin samples of 65 

spinner dolphins. The tissue was collected from dolphins that stranded in the Fernando de 

Noronha Archipelago, Brazil. They found low observed heterozygosity, suggesting a high level 

of inbreeding in the southern Atlantic. 

Andrews et al. (2010) studied the genetic relationship of spinner dolphins around the Hawaiian 

Islands that exhibit two types of social behavior: fluid and stable groups. They analyzed mtDNA 
108

control region sequences and 10 microsatellite loci. Their results showed that dolphins from the 

Southeast archipelago which form ever-changing groups had less genetic structuring than 

dolphins in the Northwest archipelago that form more stable groups. The western North Atlantic 

stock is managed separately from the Gulf of Mexico population but research is needed to 

confirm this separation (Waring et al. 2011). 

2.23.6 Life History Traits

As summarized in Perrin (2009c), females become sexually mature at 4-7 years while males are 

7-10 years at maturity. Gestation is approximately 10 months, lactation lasts 1-2 years and the 

calving interval is around 3 years. 

2.23.7 Food Habits

Spinner dolphins feed on mesopelagic fish and squid in the Pacific (Dolar et al. 2003; Perrin and 

Gilpatrick 1994). A study off the coasts of Hawaii, Oahu, and Lana (Benoit-Bird and Au 2003)

documented that spinner dolphins followed the horizontal and vertical migratory patterns of their 

prey. Pairs of dolphins were also seen foraging cooperatively within larger groups. 

Benoit-Bird and Au (2009a, 2009b) used a multibeam echosounder to make observations of 

spinner dolphins and their prey along the coast of Oahu, Hawaii. They found groups of dolphins 

(n=16-28) working together to herd prey into higher densities, thus potentially allowing access to 

more prey than an individual dolphin foraging alone would have. Benoit-Bird and Au (2009b)

have hypothesized that this cooperative feeding was maintained by acoustic communication 

(e.g., whistles). However, in their study, they recorded very few whistles when the dolphins 

appeared to be foraging. They suggest that spinner dolphins may communicate with only a few 

cues when cooperatively foraging.

2.23.8 Health

2.23.8.1 Strandings

Mead et al. (1980) reported on a stranding event on the West coast of Florida in 1976 (n=28). A 

review of Northeast and Southeast U.S. marine mammal stranding records for 2005-2009 yields 

2 strandings of spinner dolphins along the Atlantic coast, both in Florida in 2008.

2.23.8.2 Contaminants

As described in Perrin and Gilpatrick (1994), relatively high levels of mercury and DDT have 

been documented in spinner dolphins. Tanabe et al. (1988) described how spinner dolphins 

metabolize PCB’s.

2.23.8.3 Disease

Perrin and Gilpatrick (1994) wrote that a variety of endoparasites have been documented in 

spinner dolphins (e.g., nematodes, trematodes, cestodes and acanthocephalans). Cowam and 

Walker (1979) necropsied 8 spinner dolphins killed in tuna purse-seines. They described a 

variety of naturally occurring diseases and various symptoms associated with capture. Migaki et 

al. (1990) reported a case of toxoplasmosis (Toxoplasma gondii) in a wild, free-living male 

spinner dolphin that was found beached in Oahu, Hawaii.
109

2.23.9 Acoustics

Southall et al. (2007) classified Stenella sp. into a mid-frequency cetacean functional hearing 

group with an estimated auditory bandwith of 150 kHz to 160 kHz. Spinner dolphins produce 

whistles and variable burst-pulse sounds, the function of which is only starting to be understood 

(Perrin 2009c).

2.23.10 Fisheries By-Catch and Entanglement

There are no records of fishery interactions for the most recent time period reported (2001-2005) 

(Waring et al. 2011), or for 2005-2009. Before 2001, by-catch was observed in the pelagic longline and now-banned pelagic driftnet fisheries. 

2.23.11 Vessel Interactions

A review of Northeast and Southeast U.S. stranding data between 2005 and 2009 yielded one 

record of a vessel interaction with a spinner dolphin. A 2008 Florida stranding mortality had 

wounds consistent with propeller strike. Courbis and Timmel (2009) studied spinner dolphin 

behavior in relation to vessel traffic and human swim activities in three Hawaiian bays in 2002. 

They used aerial behavior of the dolphins as a metric because it is noninvasive, has been shown 

to indicate changes in energy levels (Norris et al. 1985), and could be compared to other studies. 

They found changes in the aerial behavior of dolphins at Kealake’akua Bay but suggested further 

studies are needed to understand the impact of vessel/human swimmers on spinner dolphins (e.g.,

changes in resting periods). Timmel et al. (2008) studied the effects of human traffic on the 

movement patterns of spinner dolphins in Kealakekua Bay, Hawaii. They found that increasing 

levels of human activity did have a small but measurable impact on the dolphins at this site. 

Their study was complicated by the lack of a control (vessels/human were always present) and 

they suggested further research.

2.23.12 Energy Projects

Both extractive and renewable offshore energy projects have the potential to impact the marine 

environment in a variety of ways, including habitat alteration and the introduction of noise via 

seismic exploration activities (e.g., airguns), vessel/aircraft activity, construction and operation

(Geraci and St. Aubin 1980, Bain and Williams 2006, Thompsen et al. 2006, Cada et al. 2007, 

Compton 2008, Evans 2008, MMS 2008, Burgman 2010, Boehlert and Gill 2010, Dolman and 

Simmonds 2010, Edrén et al. 2010, Bush 2011, ICES 2011). The impact of these activities on 

marine mammals is unclear. 

Stone (2003) studied the effects of seismic activity on cetaceans in UK waters. She reported that 

sighting rates of small odontocetes were significantly lower when large airgun arrays were being 

fired. She also found that, in general, small odontocetes showed the strongest avoidance 

behavior to seismic noise (compared to baleen, killer, sperm, and pilot whales). The 2010 

Report of the Working Group on Marine Mammal Ecology (ICES 2010) stated that very little is 

known about the impact of the construction and operation of offshore wind-farms. Madsen et al. 

(2006b) reviewed available current information on wind farms and marine mammals and wrote 

that the noise impact is more severe during construction than during operation. This was found 

to be the case for impacts to harbor porpoise (see Carstensen et al. [2006], Koschinski et al. 

[2003]). David (2006) wrote that pile driver-generated noise has the potential to impact dolphins 
110

via temporary displacement and interference with communication. The 2011 Report of the 

Working Group of Marine Mammal Ecology (ICES 2011) reported that porpoise detection (TPOD data) was lower during construction of a tidal turbine compared to before and after 

construction.

No information specific to spinner dolphins was found.

2.23.13 Data Gaps and Research Recommendations

There is no abundance estimate for spinner dolphins in the U.S Atlantic. There is very little 

recent information on distribution outside of the summer months. Most of the information about 

the spinner dolphins’ food habits, contaminant burden, disease or stock structure comes from 

parts of their range that are outside of the U.S. Atlantic coast (e.g., from the Pacific Ocean). 

Very little is known about spinner dolphins in the western North Atlantic.

2.24 ROUGH TOOTHED DOLPHIN (STENO BREDANENSIS)

2.24.1 Legal Status

The rough-toothed dolphin is not listed under the Endangered Species Act. Its status on the 

IUCN Red List is “Least Concern.” It is afforded protection in U.S. waters under the MMPA.

2.24.2 General Distribution

Rough-toothed dolphins exhibit a wide spread distribution and are found in tropical and warm 

waters around the world (Leatherwood and Reeves 1983a). In the western Atlantic, they are 

found from the southeastern U.S. to southern Brazil (Jefferson 2009a). Rough-toothed dolphins 

are potentially found in the BOEM Mid-Atlantic, South Atlantic and Straits of Florida Planning 

Areas. Sighting and stranding locations of rough-toothed dolphins are shown in figure 2.24-1.

2.24.3 General Abundance

There are no abundance estimates for rough-toothed dolphin along the U.S. Atlantic coast 

(Waring et al. 2011). They have not been observed in any NMFS surveys along the U.S. 

Atlantic coast since 1999 (Waring et al. 2011).

2.24.4 Habitat Preference

Baird et al. (2008) reported that rough-toothed dolphins were cited most frequently in waters that 

are deeper than 1500 m around the Hawaiian Islands. They also found evidence of site fidelity. 

2.24.5 Stock Structure

Almost nothing is known of rough-toothed dolphin stock structure world-wide (Jefferson 2009a). 

The western North Atlantic stock is considered separate from the Gulf of Mexico stock for 

management purposes, although there is no information to differentiate the two at this time 

(Waring et al. 2011).
111

2.24.6 Life History Traits

Very little is known about their life history traits. What is known comes from Japanese waters 

and is summarized in Jefferson (2009a): males reach sexual maturity at 14 years and 225 cm, 

females at 10 years and 210-220 cm. Longevity is approximately 32-36 years. 

2.24.7 Food Habits

Jefferson (2009a) reported that rough-toothed dolphins feed on a variety of fish and cephalopods 

from both coastal and oceanic habitats. Pitman and Stinchcomb (2002) described four separate 

occasions of rough-toothed dolphins feeding on mahimahi (Coryphaena hippurus). 

2.24.8 Health

2.24.8.1 Strandings

Approximately 72 rough-toothed dolphins stranded along the U.S. Atlantic coast from 2005-

2009 (Southeast and Northeast U.S. marine mammal stranding response databases). This 

includes approximately 70 animals from a 2005 mass-stranding on the Atlantic side of Marathon 

Island in the Florida Keys, and 2 animals that stranded in North Carolina in 2006.

2.24.8.2 Contaminants

Struntz et al. (2004) measured levels of persistent organic pollutants in rough-toothed dolphins 

that stranded in the Gulf of Mexico. As with other mammals, they found evidence of maternal 

offloading to calves. 

2.24.8.3 Disease

Jefferson (2009a) reported little is known about diseases in rough-toothed dolphins. 

2.24.9 Acoustics

Southall et al. (2007) classified Steno spp. in a mid-frequency cetacean functional hearing group 

with an estimated auditory bandwith of 150 Hz to 160 Hz. Jefferson (2009a) described highly 

directional echolocation clicks.

2.24.10 Fisheries By-catch and Entanglement

There were no reports of fishery related mortality or serious injury of rough-toothed dolphins in 

the most recent report covering 2002-2006 along the U.S. Atlantic coast (Waring et al. 2011).

2.24.11 Vessel Interactions

A review of Northeast and Southeast U.S. stranding data between 2005 and 2009 yielded no 

records of vessel interactions with rough-toothed dolphins.

2.24.12 Energy Projects

Both extractive and renewable offshore energy projects have the potential to impact the marine 

environment in a variety of ways, including habitat alteration and the introduction of noise via 

seismic exploration activities (e.g., airguns), vessel/aircraft activity, construction and operation
112

(Geraci and St. Aubin 1980, Bain and Williams 2006, Thompsen et al. 2006, Cada et al. 2007, 

Compton 2008, Evans 2008, MMS 2008, Burgman 2010, Boehlert and Gill 2010, Dolman and 

Simmonds 2010, Edrén et al. 2010, Bush 2011, ICES 2011). The impact of these activities on 

marine mammals is unclear. 

Stone (2003) studied the effects of seismic activity on cetaceans in UK waters. She reported that 

sighting rates of small odontocetes were significantly lower when large airgun arrays were being 

fired. She also found that, in general, small odontocetes showed the strongest avoidance 

behavior to seismic noise (compared to baleen, killer, sperm, and pilot whales). The 2010 

Report of the Working Group on Marine Mammal Ecology (ICES 2010) stated that very little is 

known about the impact of the construction and operation of offshore wind-farms. Madsen et al. 

(2006b) reviewed available current information on wind farms and marine mammals and wrote 

that the noise impact is more severe during construction than operation. This was found to be the 

case for impacts to harbor porpoise (see Carstensen et al. [2006], Koschinski et al. [2003]). 

David (2006) wrote that pile driver-generated noise has the potential to impact dolphins by

temporary displacement and interference with communication. The 2011 Report of the Working 

Group of Marine Mammal Ecology (ICES 2011) reported that porpoise detection (T-POD data) 

was lower during construction of a tidal turbine compared with before and after construction. No 

information specific to rough-toothed dolphins was found.

2.24.13 Data Gaps and Research Recommendations

There is no abundance estimate or information on spatial/temporal habitat use or stock structure 

for rough-toothed dolphin along the U.S. Atlantic coast. Food habits and life history information 

are only available from other parts of the world (e.g., the Pacific Ocean). There is limited 

information on acoustics, disease and contaminant levels in rough-toothed dolphins.

2.25 CLYMENE DOLPHIN (STENELLA CLYMENE)

2.25.1 Status

The Clymene dolphin is not listed under the Endangered Species Act. The IUCN Red List lists 

its status as “Data Deficient.” It is afforded protection in U.S. waters under the MMPA.

2.25.2 General Distribution

Clymene dolphins are limited to the tropical and sub-tropical Atlantic (Perrin et al. 1981). The 

northernmost record of a Clymene dolphin along the U.S. Atlantic coast is in New Jersey (Perrin 

et al. 1981), which is located in the BOEM North Atlantic Planning Area. There are also records 

of sightings in Mid-Atlantic, South Atlantic, and Straits of Florida Planning Areas (Fertl et al. 

2003; Perrin et al. 1981). Sighting, stranding, and fishery bycatch locations of Clymene dolphins 

are shown in Figure 2.25-1.

2.25.3 General Abundance

The best estimate for Clymene dolphins along the U.S. Atlantic coast is 6086 (CV=0.93) 

(Waring et al. 2011). This estimate is taken from shipboard surveys conducted from Maryland to 

central Florida during July-August 1998. No sightings of Clymene dolphins have been reported 

in subsequent NMFS surveys along the U.S Atlantic coast. See Figure 2.25-1.
113

2.25.4 Habitat Preference

The Clymene dolphin is an oceanic species (Fertl et al. 2003; Jefferson 2009b; Jefferson and 

Curry 2003) often observed in deep tropical and warm temperate waters (250-5000 m or deeper) 

(Fertl et al. 2003; Perrin et al. 1981). Records from the U.S. mid-Atlantic indicate that the Gulf 

Stream influences Clymene dolphin distribution in this area (Fertl et al. 2003). Waring et al. 

(2011) report that most of the sightings during the 1998 survey were on the continental slope east 

of Cape Hatteras, North Carolina. 

2.25.5 Stock Structure

There is no information on stock structure of the Clymene dolphin. NMFS considers the Gulf of 

Mexico and northwest Atlantic populations as separate stocks for management purposes but this 

division has yet to be confirmed by morphological, genetic, or behavioral data (Waring et al. 

2011). 

2.25.6 Life History Traits

Very little is known of their life history traits but it is thought that they are generally similar to 

other species in the genus Stenella (Jefferson 2009b). Males and females appear to reach sexual 

maturity by the time they reach 180cm (Jefferson and Curry 2003).

2.25.7 Food Habits

Perrin et al. (1981) reported that it appears Clymene dolphins are mid-water or night feeders on 

small fish and squid. Stomach content analysis of a dolphin that stranded in New Jersey found 

otoliths from Ceratoscopelus sp., Lampanyctus sp., and Symbolophorus sp. and 1 pair of squid 

beaks (Perrin et al. 1981). Otherwise, Jefferson (2009b) stated that very little is known about 

their food habits as very few stomach have been studied. 

2.25.8 Health

2.25.8.1 Stranding

One Clymene dolphin that stranded along the U.S. Atlantic coast (North Carolina) was part of a 

mid-Atlantic, small cetacean UME declared in August 2004 (Waring et al. 2011). Waring et al. 

(2011) reported that prior to the UME, one dolphin had stranded in Florida in 1999. Neither of 

the dolphins showed signs of human interaction. 

2.25.8.2 Contaminants

Jefferson and Curry (2003) report that almost no work has been done on contaminants in this 

species.

2.25.8.3 Disease

No information on disease in Clymene dolphins is available.
114

2.25.10 Acoustics

Southall et al. (2007) classified Stenella spp. in a mid-frequency cetacean functional hearing 

group with an estimated auditory bandwith of 150 Hz to 160 Hz. More specific information 

about Clymene dolphin acoustics is not available.

2.25.11 Fisheries By-Catch and Entanglement

There were no reports of fishery-related mortality or serious injury to Clymene dolphins along 

the U.S. Atlantic coast from 2001-2005 (Waring et al. 2011), or from 2005-2009. 

2.25.12 Ship Strikes

A review of Northeast and Southeast U.S. stranding data between 2005 and 2009 yielded no 

records of vessel interactions with Clymene dolphins.

2.25.13 Energy Projects

Both extractive and renewable offshore energy projects have the potential to impact the marine 

environment in a variety of ways, including habitat alteration and the introduction of noise via 

seismic exploration activities (e.g., airguns), vessel/aircraft activity, construction and operation

(Geraci and St. Aubin 1980, Bain and Williams 2006, Thompsen et al. 2006, Cada et al. 2007, 

Compton 2008, Evans 2008, MMS 2008, Burgman 2010, Boehlert and Gill 2010, Dolman and 

Simmonds 2010, Edrén et al. 2010, Bush 2011, ICES 2011). The impact of these activities on 

marine mammals is unclear. 

Stone (2003) studied the effects of seismic activity on cetaceans in UK waters. She reported that 

sighting rates of small odontocetes were significantly lower when large airgun arrays were being 

fired. She also found that in general, small odontocetes showed the strongest avoidance behavior 

to seismic noise (compared to baleen, killer, sperm, and pilot whales). The 2010 Report of the 

Working Group on Marine Mammal Ecology (ICES 2010) stated that very little is known about 

the impact of the construction and operation of offshore wind-farms. Madsen et al. (2006b)

reviewed available current information on wind farms and marine mammals and wrote that the 

noise impact is more severe during construction than operation. This was found to be the case 

for impacts to harbor porpoise (see Carstensen et al. (2006), Koschinski et al. (2003)). David 

(2006) wrote that pile driver-generated noise has the potential to impact dolphins by temporary 

displacement and interference with communication. The 2011 Report of the Working Group of

Marine Mammal Ecology (ICES 2011) reported that porpoise detection (T-POD data) was lower 

during construction of a tidal turbine compared to before and after construction. No information 

specific to Clymene dolphins was found.

2.25.14 Data Gaps and Research Recommendations

The only abundance estimate for the U.S. Atlantic Clymene dolphin population is 13 years old 

(1998) and not suitable for determining stock status (Wade and Angliss 1997). There is very 

limited information on food habits, life history and acoustics. There is no information on stock 

structure, contaminants, or the impacts of non-fishery related anthropogenic activities on 

Clymene dolphins.
115

2.26 STRIPED DOLPHIN (STENELLA COERULEOALBA)

2.26.1 Status

The striped dolphin is not listed under the Endangered Species Act and is considered a species of 

“Least Concern” on the IUCN Red List. It is afforded protection in U.S. waters under the 

MMPA.

2.26.2 General Distribution

Striped dolphins are found in the warm-temperate to tropical waters worldwide (Archer 2009). 

In the western Atlantic, the species is found from the northern coast of South America to the 

coast of the northeast U.S.; the Gulf Stream limits its northern distribution (Archer 2009). The 

general distribution encompasses the BOEM North Atlantic, Mid-Atlantic, South Atlantic, and 

Straits of Florida Planning Areas. However, most observations of striped dolphins are in the 

North and Mid-Atlantic Planning Areas (Waring et al. 2011). Sighting, stranding, and fishery 

bycatch locations of striped dolphins are shown in Figure 2.26-1.

2.26.3 General Abundance

The total number of striped dolphins along the U.S. Atlantic coast is unknown (Waring et al. 

2011). The best estimate of striped dolphin abundance in the western North Atlantic is 94,462 

(CV=0.40) and is derived by combining two surveys that took place June-August 2004. The first 

survey used a combination of ship and aerial surveys and resulted in an estimate of 52,055 

(CV=0.57) striped dolphins from Maryland to the Bay of Fundy. The second survey was shipbased only and provided an estimate of 42,407 (CV=0.53) dolphins between Florida and 

Maryland. 

2.26.4 Habitat Preference

As Archer (2009) summarized, striped dolphins are generally found outside the continental shelf, 

on the continental slope and in oceanic waters. They are found in temperatures 10-26 o

C with 

most records in 18-22 oC (Archer and Perrin 1999). Most sightings off the U.S. east coast are on 

the continental shelf edge and slope areas west of Georges Bank (Waring et al. 2011). In 

conducting cetacean habitat-use surveys off the U.S. Atlantic coast during 1991-2, Waring et al. 

(1992) found striped dolphins were associated with the Gulf Stream north wall and warm-core 

ring features. During a suvey of the New England seamounts, Palka (2006) found that striped 

dolphins were in waters 20-27 oC.

2.26.5 Stock Structure

The western North Atlantic population is considered separate from the Gulf of Mexico 

population for management purposes but additional data are needed to elucidate stock structure 

(Waring et al. 2011). In an analysis of mtDNA, Garcia-Martinez et al. (1999) found no shared 

haplotypes between striped dolphins from the Mediterranean and northeast Atlantic. However, 

this study did not rule out male gene flow. In an analysis of 5 microsatellite loci, Bourret et al. 

(2007) found higher genetic diversity in animals from the northeast Atlantic than in the 

Mediterranean. 
116

2.26.6 Life History Traits

Archer (2009) reported age at sexual maturity is 5-13 years for females and 7-15 years for males, 

and gestation lasts 12-13 months. Calzada et al. (1996) reported that females in the western 

Mediterranean reach sexual maturity at 12 years and have a 4-year inter-calving interval.

2.26.7 Food Habits

The species feeds on pelagic or benthopelagic fish and squid (Archer 2009). Perrin et al. (1994b)

report cephalopods and myctophid fishes being important prey species. Striped dolphin diet 

consists of fish (lanternfish most common) and cephalopods in the Bay of Biscay (Ringelstein et 

al. 2006). Spitz et al. (2006) found that individual striped dolphins in the Bay of Biscay were 

capable of exploiting prey in oceanic, neritic, and coastal habitats, displaying plasticity in their 

foraging.

2.26.8 Health

2.26.8.1 Strandings

A total of 66 striped dolphins stranded along the U.S. Atlantic coast (Maine to Florida) from 

2005-2009 (Northeast and Southeast U.S. marine mammal stranding response databases). One 

live stranding in 2007 was classified as a human interaction because surfers pushed the animal 

back out to deep water. In 2008, two striped dolphins were found dead with net or line marks, 

prompting classification as human interactions. 

2.26.8.2 Contaminants

Multiple studies have documented contaminants in striped dolphins in Europe and Japan 

(Aguilar and Borrell 2005; Isobe et al. 2009; Wafo et al. 2005). Isobe et al. (2009) analyzed 

contaminant levels from 1978 to 2003 and found that PCB’s, DDT’s, and 

hexachlorocyclohexane (HCH) levels were stable, but PDBE’s and hexabromocyclododecanes 

(HBCD’s) had increased in striped dolphins in Japan over this time period. Aguilar and Borrell 

(2005) documented a decline in total PCB and DDT levels in striped dolphins in the western 

Mediterranean 1987-2002. Honda et al. (1983) documented a number of heavy metals (Pb, Ni, 

Cd, Hg, Fe, Mn, Zn, Cu) in the tissue of live caught, presumably healthy, striped dolphins in 

Japan.

2.26.8.3 Disease

Domingo et al. (1992) showed that morbillivirus was the primary cause of the epizootic that 

killed thousands of striped dolphins in the Mediterranean in 1990. After the acute Mediterranean 

epizootic, Domingo et al. (1995) found evidence of chronic morbillivirus infection in the central 

nervous system of some striped dolphins. Di Guardo et al. (2010) reported Toxoplasma gondii

had caused meningoencephalitis in stranded dolphins in Italy. 

2.26.9 Acoustics

Southall et al. (2007) classified Stenella sp. into a mid-frequency cetacean functional hearing 

group with an estimated auditory bandwith of 150 Hz to 160 Hz. Kastelein et al. (2006) studied 

the response of a striped dolphin to an acoustic alarm. They found that despite the sound being 

within the dolphin’s hearing range, it did not react to the alarm. 
117

2.26.10 Fisheries By-Catch and Entanglement

There were 46 striped dolphins incidentally caught from 1989 through 2009. This includes two 

animals caught in trawl gear in December 1991, and 44 animals caught in pelagic drift gillnet 

gear between 1989 and 1998. The pelagic drift gillnet fishery was discontinued in 1998. There 

have been no observed interactions in other fisheries.

2.26.11 Vessel Interactions

A review of Northeast and Southeast U.S. stranding data between 2005 and 2009 yielded no 

records of vessel interactions with striped dolphins.

2.26.12 Energy Projects

Both extractive and renewable offshore energy projects have the potential to impact the marine 

environment in a variety of ways, including habitat alteration and the introduction of noise via 

seismic exploration activities (e.g., airguns), vessel/aircraft activity, construction and operation

(Geraci and St. Aubin 1980, Bain and Williams 2006, Thompsen et al. 2006, Cada et al. 2007, 

Compton 2008, Evans 2008, MMS 2008, Burgman 2010, Boehlert and Gill 2010, Dolman and 

Simmonds 2010, Edrén et al. 2010, Bush 2011, ICES 2011). The impact of these activities on 

marine mammals is unclear. 

Stone (2003) studied the effects of seismic activity on cetaceans in UK waters. She reported that 

sighting rates of small odontocetes were significantly lower when large airgun arrays were being 

fired. She also found that in general, small odontocetes showed the strongest avoidance behavior 

to seismic noise (compared to baleen, killer, sperm, and pilot whales). The 2010 Report of the 

Working Group on Marine Mammal Ecology (ICES 2010) stated that very little is known about 

the impact of the construction and operation of offshore wind-farms. Madsen et al. (2006b)

reviewed available current information on wind farms and marine mammals and wrote that the 

noise impact is more severe during construction than operation. This was found to be the case 

for impacts to harbor porpoise (see Carstensen et al. [2006], Koschinski et al. [2003]). David 

(2006) wrote that pile driver-generated noise has the potential to impact dolphins by temporary 

displacement and interference with communication. The 2011 Report of the Working Group of 

Marine Mammal Ecology (ICES 2011) reported that porpoise detection (T-POD data) was lower 

during construction of a tidal turbine compared to before and after construction. No information 

specific to striped dolphins was found.

2.26.13 Data Gaps and Research Recommendations

The best abundance estimate is from aerial and ship surveys that took place in 2004; this data is 7

years old. There is very little recent information on striped dolphin distribution and abundance 

outside of the summer months (June-September). Very little is understood about stock structure 

in the northwest Atlantic. Most of the food habits, life history, and contaminants data are from 

populations in Europe or Asia. No information on the impacts of non-fishery related 

anthropogenic activities on striped dolphin in the northwestern Atlantic has been published.
118

2.27 SHORT-BEAKED COMMON DOLPHIN (DELPHINUS DELPHIS)

2.27.1 Legal Status 

The short-beaked common dolphin is not listed under the Endangered Species Act and is 

considered a species of “Least Concern” on the IUCN Red List. It is afforded protection in U.S. 

waters under the MMPA.

2.27.2 General Distribution 

The short beaked common dolphin is one of the most widely distributed cetaceans and is 

abundant throughout the warm temperate, subtropical and tropical waters of the world (Evans 

1994; Perrin 2009a). Common dolphins are found in the BOEM North Atlantic, Mid-Atlantic 

and South Atlantic Planning Areas. According to Jefferson et al. (2009) there are no records of 

common dolphins in Florida waters after the 1960s; therefore, it is unlikely that they are found in 

the BOEM Straits of Florida Planning Area. Sighting, stranding and fishery bycatch locations of 

short-beaked common dolphins are shown in Figure 2.27-1.

2.27.3 General Abundance 

The best estimate available for the Northwest Atlantic stock of common dolphins is 120,743 

(CV=0.23) (Waring et al. 2011). As described in Waring et al. (2011) this estimate is derived 

from a combination of aerial and shipboard surveys conducted from June to August 2004 in 

waters from Florida to the Bay of Fundy. Palka (2006) estimated 90,547 (CV=0.24) common 

dolphins in waters between Maryland and the Bay of Fundy in July-August 2004. Waring et al. 

(2011) reported 30,196 (CV=0.54) common dolphins in the waters between Florida and 

Maryland in July-August 2004. From these surveys it appears that common dolphins do not 

occur south of the South Carolina-Georgia border.

2.27.4 Habitat Preference 

Selzer and Payne (1988) found that common dolphins off the northeastern U.S. were generally 

sighted in water with 25-32 ppt salinity and mean surface temperature of 11o

C. Selzer and Payne 

(1988) also cite the importance of sea floor relief and subsequently prey distribution in the 

distribution of common dolphins. The majority (66%) of common dolphin sightings in their 

study were in areas with the maximum sea floor relief. In his work developing spatiotemporal 

prediction models of cetacean habitats, Hamazaki (2002) found that common dolphins tend to be 

found on the continental shelf, offshore, and near seamounts. Generally they were in water that 

was 18 (+/- 5.7) oC and less than 1500 m deep. Morato et al. (2008) found that common 

dolphins were significantly more abundant in the vicinity of Azores seamounts (depth 200-400 

m), probably because of localized prey.

2.27.5 Stock Structure 

Luca et al. (2009) collected tissue samples from 424 common dolphins in the North Atlantic 

Ocean (western Atlantic N = 183, eastern Atlantic N = 205) from 1990 to 2005. They analyzed 

14 microsatellite loci and a 360 bp segment of the mitochondrial control region. They found a 

high level of genetic diversity and no evidence of a bottleneck effect. Both nuclear and 

mitochondrial DNA analyses demonstrated a significant difference between the eastern and 

western Atlantic populations. The authors did not find genetic structure within the eastern and 
119

western Atlantic regions; this suggests that individual dolphins are mixing within these areas. 

Luca et al. (2009) concluded that there is a single stock of common dolphins off the U.S. Atlantic 

coast but leave open the possibility of discrete populations in areas that were not sampled. 

Westgate (2007) analysis of cranial morphology provides additional support for a single 

population off the U.S. Atlantic Coast. However, in their study on common dolphin feeding 

ecology, Pusineri et al. (2008) found that, although animals feed on similar prey type (small 

aggregating species in the epipelagic layer), groups of dolphins forage in either the neritic or 

open ocean habitat and do not move back and forth between these two areas. Additionally, a 

study using cadmium accumulation in tissue as an ecological tracer found the existence of longterm dietary segregation between neritic and oceanic common dolphins in the Bay of Biscay 

(Lahaye et al. 2005). Studies have also found bias in the sex ratio of by-caught animals (e.g.,

Westgate and Read 2007: 161 males vs. 74 females) which could indicate seasonal segregation 

by sex. 

2.27.6 Life History Traits 

Westgate and Read (2007) examined life history data for the western northern Atlantic 

population. They estimated age at first maturity as 8 and 9.5 years for females and males,

respectively, and a minimum 2 year inter-calving interval (likely longer). Murphy et al. (2009)

found the eastern north Atlantic common dolphin population had an inter-calving interval of 3.79 

years and that maximum age was 29 years. Westgate and Read (2007) did not attempt to age 

animals older than 25 years. 

2.27.7 Food Habits 

Although common dolphins are often thought of as generalists that prey on common schooling 

fish, studies have shown that they actively select the most energy-rich prey available to them 

(e.g., Meynier et al. 2008). Waring et al. (1990) reported that long-finned squid was a major 

component of stomach samples (n=33) from common dolphins incidentally caught by distantwater vessels off the northeast U.S. Overholz and Waring (1991) analyzed the stomach contents 

of 4 common dolphins caught in the Atlantic mackerel (Scomber scombrus) trawl fishery 

between 19 March and 17 April 1989 in the Hudson Canyon area. Atlantic mackerel was the 

dominant prey but they also found remnants of long-finned squid (Loligo pealei) and hake 

(Merluccius sp.). Pusineri et al. (2008) examined the stomachs of common dolphins by-caught 

in drift nets in the oceanic areas of the Bay of Biscay. They found that the dolphins’ diet was 

dominated by lantern fish (Notoscopelus kroeyer, Benthosema glaciale, Myctophum punctatum) 

and pearlsides (Maurolicus muelleri). Cephalopods (Ancistrotheuthis lechtensteini, Gonatus 

steentrupi, Brachioteuthis riisei, and Teuthowenia megalops) were also important in their diet, 

accounting for 47% of the mass of total diet. A study of the stomach contents of stranded 

common dolphins along the Bay of Biscay found that their diet was dominated by sardines 

(Sardina pilchardus), anchovy (Engraulis encrasiocolus), sprat (Sprattus sprattus) and horse 

mackerel (Trachurus spp.) (Meynier et al. 2008).

2.27.8 Health 

2.27.8.1 Strandings

Three common dolphin stranding events have been classified as UME. Two occurred in 2004, 

the first off the coast of Virginia, the 2nd along the coast from Maryland to Georgia. In 2008 a
120

UME that included at least 31 common dolphins occurred along the coast from New Jersey to 

North Carolina. A total of 428 common dolphins stranded along the U.S. Atlantic coast from 

2005 to 2009 (Waring et al. 2011). Human interaction was indicated in 16 of these strandings. 

A majority (70%) of the strandings occurred in Massachusetts (Waring et al. 2011). Bogomolni 

et al. (2010) found that the cause of death in 37% of common dolphins that had stranded along 

Cape Cod and southeastern Massachusetts was disease. 

2.27.8.2 Contaminants 

Pierce et al. (2008) found that diet, location, reproductive status, and season all affected the 

variation in persistent organic pollutants (POP: PCB’s, PBDE’s and HBCD’s) in female common 

dolphins stranded and by-caught in European waters (Ireland, France, and Spain). They found 

high PCB levels in these animals; average summed PCB concentrations exceeded the threshold 

at which effects on reproduction could be expected. Despite these levels, they found no 

association between cause of death and PCB concentrations. There is no contaminant 

information available for the western north Atlantic common dolphin population. 

2.27.8.3 Disease

2.27.9 Acoustics 

Southall et al. (2007) classified Delphinus spp. in a mid-frequency cetacean functional hearing 

group with an estimated auditory bandwith of 150 Hz to 160 Hz. According to Evans (1994) and 

the references therein, common dolphins are a very vocal species. They produce the variety of 

sounds common to dolphins (e.g., clicks, squeaks, whistles and creaks). Barlow and Cameron 

(2003) found that acoustic deterrent devices (pingers) significantly reduced the number of 

common dolphins by-caught in California drift gillnet fishery. 

2.27.10 Fisheries By-catch and Entanglement 

Waring et al. (2011) reported that common dolphins are by-caught in a variety of fisheries along 

the U.S. Atlantic coast. The 5-year (2005-2009) mean annual mortality for these fisheries are

listed in Table 2-27-1.

Table 2.27.1. Fisheries Mortality of Common Dolphins

Fishery Mean Annual Mortality (CV)

Northeast Sink Gillnet 26 (0.39)

Northeast Bottom Trawl 23 (0.13)

Mid-Atlantic Gillnet 2.2 (1.03)

Mid-Atlantic Mid-Water Trawl 0.6 (0.70)

Mid-Atlantic Bottom Trawl 10 (0.13)

Pelagic Longline 1.7 (1.0)

The National Marine Fisheries Service assembled the Atlantic Trawl Gear Take Reduction Team 

(ATGTRT) to address incidental mortality of common dolphins (among several other species) in 

September 2006. This take reduction team focuses on are the Mid-Atlantic Mid-Water Trawl, 

the Mid-Atlantic Bottom Trawl, Northeast Mid-Water Trawl and the Northeast Bottom Trawl 
121

fisheries. The Team found that mean annual incidental mortality (2001-2005) for common 

dolphins was highest in the Mid-Atlantic region in waters with a slope greater than 0.965°. Illex

and Loligo squid fisheries dominated this area.

2.27.11 Ship Strikes

A review of Northeast and Southeast U.S. stranding data between 2005 and 2009 yielded no 

records of vessel interactions with common dolphins. 

2.27.12 Energy Projects

Both extractive and renewable offshore energy projects have the potential to impact the marine 

environment in a variety of ways, including habitat alteration and the introduction of noise via 

seismic exploration activities (e.g., airguns), vessel/aircraft activity, construction and operation

(Geraci and St. Aubin 1980, Bain and Williams 2006, Thompsen et al. 2006, Cada et al. 2007, 

Compton 2008, Evans 2008, MMS 2008, Burgman 2010, Boehlert and Gill 2010, Dolman and 

Simmonds 2010, Edrén et al. 2010, Bush 2011, ICES 2011). The impact of these activities on 

marine mammals is unclear. 

Stone (2003) studied the effects of seismic activity on cetaceans in UK waters. She reported that 

sighting rates of small odontocetes were significantly lower when large airgun arrays were being 

fired. She also found that in general, small odontocetes showed the strongest avoidance behavior 

to seismic noise (compared to baleen, killer, sperm, and pilot whales). The 2010 Report of the 

Working Group on Marine Mammal Ecology (ICES 2010) stated that very little is known about 

the impact of the construction and operation of offshore wind-farms. Madsen et al. (2006b)

reviewed available current information on wind farms and marine mammals and wrote that the 

noise impact is more severe during construction than operation. This was found to be the case 

for impacts to harbor porpoise (see Carstensen et al. [2006], Koschinski et al. [2003]). David 

(2006) wrote that pile driver-generated noise has the potential to impact dolphins by temporary 

displacement and interference with communication. The 2011 Report of the Working Group of 

Marine Mammal Ecology (ICES 2011) reported that porpoise detection (T-POD data) was lower 

during construction of a tidal turbine compared to before and after construction. 

2.27.13 Data Gaps and Research Recommendations

The best abundance estimate of common dolphins is from 2004 and is now over 7 years old. The 

information on common dolphin distribution and abundance (other than stranding and by-caught 

observations) outside of the summer months is old (e.g., CETAP data from late 1970s and early 

1980s). No information on food habits or contaminant levels in common dolphins in the western 

north Atlantic has been published.

The ATFTRT recommended that there be an improved abundance estimate for all species 

(including common dolphins) affected by the trawl fisheries including “conducting more 

surveys, appropriately incorporating data from multiple years and by using appropriate stock 

structure boundaries.” Additionally, they specifically recommended that morphometric and 

genetic research of common dolphins be performed to confirm previous work that indicates there 

is a single common dolphin stock in the U.S. Atlantic. 
122

2.28 FRASER'S DOLPHIN (LAGENODELPHIS HOSEI)

2.28.1 Legal Status

The Fraser’s dolphin is not listed under the Endangered Species Act. Its status on the IUCN Red 

List is “Least Concern.” It is afforded protection in U.S. waters under the MMPA.

2.28.2 General Distribution

Fraser’s dolphins are found in tropical waters throughout the world (Perrin et al. 1994a). Dolar 

(2009) reported a distribution between 30oN and 30oS; strandings outside of this area should be 

considered unusual. The only live sighting of Fraser’s dolphins along the U.S. Atlantic coast 

occurred off of Cape Hatteras, North Carolina,, in 1999 (Waring et al. 2011). Hersh and Odell 

(1986) and Waring et al. (2011) both described records of Fraser’s dolphin standings in Florida. 

Waring et al. (2011) reported that the lack of sightings along the U.S. Atlantic coast is probably 

due to naturally low numbers. Sighting and stranding locations of Fraser’s dolphins are shown in 

Figure 2.28.1.

2.28.3 General Abundance

There are no abundance estimates for Fraser’s dolphin along the U.S. Atlantic coast (Waring et 

al. 2011). Two-hundred-fifty Fraser’s dolphins were sighted off the coast of North Carolina (in 

the BOEM Mid-Atlantic Planning Area) in 1999. This sighting could not be used for an 

abundance estimate because it was not made during line-transect sampling effort (Waring et al. 

2011). Fraser’s dolphins have not been observed in any other NMFS survey along the U.S. 

Atlantic coast (Waring et al. 2011).

2.28.4 Habitat Preference

Perrin et al. (1994a) refer to the Fraser’s dolphin as a “high seas” animal. Generally, they are an 

oceanic species occurring in deep water beyond the continental shelf, but they are also observed 

in deep water that is near the coast (Dolar 2009; Wursig et al. 2000). In the Gulf of Mexico they 

are seen most commonly in waters around 1000 m (Wursig et al. 2000). The one live sighting of 

Fraser’s dolphins along the U.S. Atlantic coast was in waters 3300 m (Waring et al. 2011).

2.28.5 Stock Structure

Stock structure of the Fraser’s dolphin is unknown along the U.S. Atlantic coast. The western 

North Atlantic stock is considered separate from the Gulf of Mexico stock for management 

purposes although there is no information to differentiate the two at this time (Waring et al. 

2011).

2.28.6 Life History Traits 

Very little is known about Fraser’s dolphin life history traits. Amano and Miyazaki (1996)

reported that females reach sexual maturity at 5-8 years (length = 210-220 cm) and males at 7-10 

years (length = 220-230 cm). They estimated that gestation lasts 12.5 months and the intercalving interval is 2 years. These data came from animals caught in a drive fishery in Japan. 
123

2.28.7 Food Habits

Robison and Craddock (1983) analyzed the stomach contents of three female Fraser’s dolphins 

that were incidentally caught in purse seine nets in the eastern tropical Pacific in May 1972. 

They found a mixed diet of mesopelagic fish, shrimps and squid, with fish being the most 

important. They also estimated that the 3 dolphins were feeding at depths of 250-500 m. Dolar 

et al. (2003) reported that fish (97.3% occurrence), cephalopods (89.2% occurrence), and 

crustaceans (67.0% occurrence) were all important in the diet of Fraser’s dolphins (n=37) 

incidentally caught in the tuna drift net fishery in the eastern Sulu Sea (Philippines). Myctophids 

were the most commonly occurring fish family while Enoploteuthids were the most commonly 

occurring cephalopod family. Two families of crustaceans were identified in the dolphin 

stomachs: Oplophoridae and Sergestidae. Dolar et al. (2003) also reported that Fraser’s dolphins 

likely forage in the vertical range from the surface to approximately 600 m. 

2.28.8 Health

2.28.8.1 Strandings

Hersh and Odell (1986) identified the skeletons of 10 stranded Fraser’s dolphins collected on 

Marquesas Key, Florida, from November 1981 to June 1982. The remains had been on the 

beach for several weeks at the time of discovery, so the cause of stranding could not be 

determined. Waring et al. (2011) reported a live mass stranding of ten Fraser’s dolphins in Lee, 

Florida, in April 2003 and one stranding in Florida in 2004. There were no signs of human or 

fishery involvement in these strandings.

2.28.8.2 Contaminants

There is no information on contaminant load in Fraser’s dolphins.

2.28.8.3 Disease

As is summarized in Dolar (2009), many parasites have been observed on and in Fraser’s 

dolphins including: Zenobalanus sp., Phullobothrium delphini, Monorhygma grimaldi, Anisakis 

simplex, Tetrabothrius sp., Bolbosoma sp., Strobicephalus triangularis, Campula sp., and

Stenurus ovatus. Morbillivirus was also found in Fraser’s dolphins in the southwest Atlantic 

(Van Bressem et al. 2001, as cited in Dolar (2009).

2.28.9 Acoustics

Southall et al. (2007) classified Lagenodelphis spp. in a mid-frequency cetacean functional 

hearing group with an estimated auditory bandwith of 150 Hz to 160 Hz. No more specific 

information about Fraser’s dolphin acoustics is available.

2.28.10 Fisheries By-catch and Entanglement

There were no reports of fishery related mortality or serious injury of Fraser’s dolphins in the 

most recent report covering 2001-2005 along the U.S. Atlantic coast (Waring et al. 2011).
124

2.28.11 Vessel Interactions

A review of Northeast and Southeast U.S. stranding data between 2005 and 2009 yielded no 

records of vessel interactions with Fraser’s dolphins.

2.28.12 Energy Projects

Both extractive and renewable offshore energy projects have the potential to impact the marine 

environment in a variety of ways, including habitat alteration and the introduction of noise via 

seismic exploration activities (e.g., airguns), vessel/aircraft activity, construction and operation

(Geraci and St. Aubin 1980, Bain and Williams 2006, Thompsen et al. 2006, Cada et al. 2007, 

Compton 2008, Evans 2008, MMS 2008, Burgman 2010, Boehlert and Gill 2010, Dolman and 

Simmonds 2010, Edrén et al. 2010, Bush 2011, ICES 2011). The impact of these activities on 

marine mammals is unclear. 

Stone (2003) studied the effects of seismic activity on cetaceans in UK waters. She reported that 

sighting rates of small odontocetes were significantly lower when large airgun arrays were being 

fired. She also found that in general, small odontocetes showed the strongest avoidance behavior 

to seismic noise (compared to baleen, killer, sperm and pilot whales). The 2010 Report of the 

Working Group on Marine Mammal Ecology (ICES 2010) stated that very little is known about 

the impact of the construction and operation of offshore wind-farms. Madsen et al. (2006b)

reviewed available current information on wind farms and marine mammals and wrote that the 

noise impact is more severe during construction than operation. This was found to be the case 

for impacts to harbor porpoise (see Carstensen et al. [2006], Koschinski et al. [2003]). David 

(2006) wrote that pile driver-generated noise has the potential to impact dolphins by temporary 

displacement and interference with communication. The 2011 Report of the Working Group of 

Marine Mammal Ecology (ICES 2011) reported that porpoise detection (T-POD data) was lower 

during construction of a tidal turbine compared to before and after construction. No information 

specific to Fraser’s dolphins was found.

2.28.13 Data Gaps and Research Recommendations

There is no abundance estimate or information on spatial/temporal habitat use or stock structure 

for Fraser’s dolphin along the U.S. Atlantic coast. Food habits and life history information are 

only available from other parts of the world (e.g. the Pacific Ocean). There is limited 

information on acoustics and no information on contaminant levels in Fraser’s dolphins.

2.29 HARBOR PORPOISE (PHOCOENA PHOCOENA)

2.29.1 Status

The harbor porpoise’s status is “undefined” under the Endangered Species Act. It is a species of 

“Least Concern” on the IUCN Red List. It is afforded protection in U.S. waters under the

MMPA. 

2.29.2 General Distribution

The harbor porpoise is found in the cold temperate and subarctic waters of the northern 

hemisphere (Leatherwood and Reeves 1983b). As described in Waring et al. (2011), harbor 
125

porpoise are found in the North Atlantic Planning Area year round with highest abundance 

during the summer months (July to September). They are also found in the Mid-Atlantic 

Planning Area during the winter (January to March). They are not found in the South Atlantic or 

Straits of Florida Planning Areas. Sighting, stranding and fishery bycatch locations of harbor 

porpoises are shown in Figure 2.29-1.

2.29.3 General Abundance

The best abundance estimate available for the harbor porpoise is 89,054 (CV=0.47) (Waring et 

al. 2011). This estimate was derived from an August 2006 aerial survey conducted from the 

2000-m isobath on the southern edge of Georges Bank to the upper Bay of Fundy and to the 

entrance of the Gulf of St. Lawrence (Waring et al. 2011). This covers the presumed summer 

range of the Gulf of Maine/Bay of Fundy breeding population. 

2.29.4 Habitat Preference

Generally, harbor porpoise are a coastal species (Leatherwood and Reeves 1983b). In the Gulf 

of Maine, Palka (1995) found that the highest harbor porpoise densities in the summers of 1991 

and 1992 were associated with sea surface temperatures of 10-13.5 o

C, fish densities of 1.5-11 

fish caught per minute trawling and water depths of 50-130 m. Watts and Gaskin (1985) found 

that harbor porpoise in the Bay of Fundy tended to be found in areas with physiographic features 

(e.g. islands, shoals) that concentrated their preferred prey: Atlantic herring (Clupea harengus). 

This work in the Bay of Fundy was further supported by Johnston et al.’s (2005c) study. Gilles 

et al. (2011) used oceanographic parameters and generalized additive models to predict harbor 

porpoise density and distribution in the North Sea to assess the extent of potential conflicts with 

offshore energy development and to support conservation and management plans. Porpoises 

were found to prefer areas with stronger currents and areas where fronts were likely.

2.29.5 Stock Structure

Rosel et al. (1999) found very little evidence of transatlantic exchange of harbor porpoise when 

they compared mitochondrial control region sequences from the northwestern and northeastern 

Atlantic populations. They estimated an exchange of 2.7 females per generation between the 

northeastern and northwestern Atlantic populations. In a study on the genetic structure of harbor 

porpoise within the northwestern Atlantic population, (Rosel et al. 1999a) found evidence of 

three distinct summer breeding populations: the Gulf of Maine/Bay of Fundy population, the 

Newfoundland population and the Gulf of St. Lawrence/Western Greenland population. This 

structure was only apparent in the mitochondrial DNA, not in the microsatellite, indicating 

female philopatry in these populations. It also appears that the winter aggregation of harbor 

porpoise of the mid-Atlantic coast contains animals from more than one of the summer 

populations (Rosel et al. 1999a). Comparison of organochlorine contaminants in harbor porpoise 

in the northwest Atlantic (Westgate and Tolley 1999) provided further support for the three 

populations described by (1999a). 

2.29.6 Life History Traits

Read and Hohn (1995), to determine vital rates, examined 239 harbor porpoises that had been 

killed in gill net fisheries in the Gulf of Maine from 1989 to 1993. They found that most females 

are sexually mature by age three, and are pregnant annually. From their limited sample set of 
126

males, they estimated that most male harbor porpoise become sexually mature at three to four 

years of age. Ovulation, conception, and parturition all occur in the spring and early summer. 

They are relatively short-lived; most animals examined were less than 10 years old. 

2.29.7 Food Habits

Harbor porpoise generally feed on small, pelagic, schooling fish with high lipid content and 

some bottom-dwelling fish (Bjorge and Tolley 2009). Gannon et al. (1998) found Atlantic 

herring was the number one prey species of harbor porpoise in the Gulf of Maine during the fall. 

Smith and Read (1992) found that while clupeid and gadid fish were important in adults diets, 

calves (<1 year) fed predominantly on euphasiids (Meganyctiphanes norvedica). Food habit 

studies in Scottish waters found whiting (Merlangius merlangus) and sand eels (Ammodytidae) 

the most important prey; in Icelandic waters, capelin (Mallotus villosus) and sand eels were the 

most important (Santos et al. 2004). Spitz et al. (2006) reported that harbor porpoise that had 

stranded on the French Coast (Bay of Biscay) had fed on small schooling fish living close to the 

sea floor.

2.29.8 Health

2.29.8.1 Strandings

One harbor porpoise stranding event has been declared a UME. It involved the stranding of 38 

animals along the North Carolina coast from 1 January to 28 March 2005. A total of 450 harbor 

porpoise have stranded along the U.S. Atlantic coast from 2005 to 2009 (Northeast and Southeast 

U.S. marine mammal stranding rersponse databases). A high percentage of these strandings 

occurred in Massachusetts (32%) or North Carolina (20%). Forty-eight of the stranded harbor 

porpoises showed signs of human interaction, although that was not always identified as the 

ultimate cause of death. 

2.29.8.2 Contaminants

Westgate and Tolley (1999) documented multiple organochlorine (OC) contaminants (PCBs, 

DDTs, chlordanes, chlorinated bornanes, hexachlorocyclohexanes, and chlorobenzenes) in 

harbor porpoise in the northwestern Atlantic. Their results showed that the unique combination 

of OC levels could be used to distinguish three geographic groups: Bay of Fundy/Gulf of Maine, 

Newfoundland, and the Gulf of St. Lawrence. Westgate and Tolley (1999) also found 

significantly higher levels of PCBs in the Bay of Fundy/Gulf of Maine stock. When Jepson et al. 

(2005b) compared the PCB levels of UK harbor porpoises that had died of infectious disease

with those that had died of physical trauma, they found the infectious disease group had 

significantly greater values. Hall et al. (2006) hypothesized that the risk of mortality from 

infectious disease was correlated with levels of PCB exposure for harbor porpoises in the UK . 

A case-control analysis supported the hypothesis. Trends in chlorobiphenyls in harbor porpoise 

blubber from the UK from 1991 to 2005 were described in Law et al. (2010). Weijs et al. (2011) 

created a physiologically based pharmacokinetic model to learn more about uptake, distribution,

and elimination of PCB’s. 
127

2.29.8.3 Disease 

Neimanis et al. (2008) found that 2 out of 170 harbor porpoises incidentally caught in fishing 

nets in the Bay of Fundy had detectable antibodies for Brucella sp. 

2.29.9 Acoustics

Southall et al. (2007) classified Phocoena spp. in a high-frequency cetacean functional hearing 

group with an estimated auditory bandwith of 200 Hz to 180 kHz. In their study on harbor 

porpoise sonar characteristics, Goodson and Sturtivant (1996) found that their sonar system 

developed as a short-range foraging tool. Kraus (1997) and Culik et al. (2001) found that harbor 

porpoises actively avoided fishing nets equipped with acoustic deterrents (pingers) in the Gulf of 

Maine and near Vancouver Island, Canada, respectively. As summarized in Lucke et al. (2008), 

the harbor porpoise hearing range is from 250 Hz to 160 kHz; the most sensitivity is between 

100 to 140 kHz.

2.29.11 Fisheries By-Catch and Entanglement

Waring et al. (2011) reported that harbor porpoise are by-caught in a variety of fisheries along 

the U.S. Atlantic coast. The mean annual mortality estimates (2005-2009) for these fisheries are 

presented in Table 2-29-1. Cox et al. (1998) examined carcasses of harbor porpoise that had 

stranded in the Mid-Atlantic (North Carolina, Maryland and Virginia) from 1994 to 1996. 

Twenty-five of the forty carcasses that were fresh enough to assess exhibited clear signs of 

fisheries interactions. Because fisheries interactions continue to pose a threat, pingers are 

required on gillnets. Also, the Harbor Porpoise Take Reduction Team has identified management 

areas along the New England and Mid-Atlantic coasts that are closed at times through the year to 

prevent harbor porpoise entanglement (Figures 2.29-2 and 2.29-3).

Table 2.29.1. Fisheries Mortality of Harbor Porpoise, 2005-2009 

Fishery Mean Annual Mortality (CV)

Northeast Sink Gillnet 599 (0.16)

Northeast Bottom Trawl 6 (0.22)

Mid-Atlantic Gillnet 318 (0.26)

2.29.12 Ship Strikes

A review of Northeast and Southeast U.S. stranding data between 2005 and 2009 yielded three 

records of vessel interactions with harbor porpoises. 

2.29.13 Energy Projects

Both extractive and renewable offshore energy projects have the potential to impact the marine 

environment in a variety of ways, including habitat alteration and the introduction of noise by

seismic exploration activities (e.g., airguns), vessel/aircraft activity, construction and operation

(Geraci and St. Aubin 1980, Bain and Williams 2006, Thompsen et al. 2006, Cada et al. 2007, 

Compton 2008, Evans 2008, MMS 2008, Burgman 2010, Boehlert and Gill 2010, Dolman and 

Simmonds 2010, Edrén et al. 2010, Bush 2011, ICES 2011). The impact of these activities on 

marine mammals is unclear. 
128

Stone (2003) studied the effects of seismic activity on cetaceans in UK waters. She reported that 

sighting rates of small odontocetes were significantly lower when large airgun arrays were being 

fired. She also found that, in general, small odontocetes showed the strongest avoidance 

behavior to seismic noise (compared to baleen, killer, sperm, and pilot whales). Harbor porpoise 

avoidance responses were detected at distances of over 70 km from seismic airguns in a study 

carried out in marine waters of British Columbia and Washington (Bain et al. 2010). Compared 

with other species examined in that study, the harbor porpoise appeared to be the species affected 

by the lowest level of noise. The 2010 Report of the Working Group on Marine Mammal 

Ecology (ICES 2010) stated that very little is known about the impact of the construction and 

operation of offshore wind-farms. Madsen et al. (2006b) reviewed available current information 

on wind farms and marine mammals and wrote that the noise impact is more severe during 

construction than operation. The 2011 Report of the Working Group of Marine Mammal 

Ecology (ICES 2011) reported that porpoise detection (T-POD data) was lower during 

construction of a tidal turbine compared to before and after construction.

Cartensen et al. (2006) monitored harbor porpoise echolocation activity in the area of the Nysten 

Offshore Winds Farm construction site in the Baltic Sea. They found that this construction 

significantly impacted harbor porpoise habitat-use; this was evidenced by harbor porpoises

leaving the construction area (measured by decreased echolocation activity). In particular, the 

phase of construction involving the ramming and vibration of steel sheet piles into the sea bed 

displaced harbor porpoises dramatically. Pile driving activity associated with the construction of 

the Horns Rev II offshore wind farm in the Danish North Sea was related to changes in harbor 

porpoise acoustic activity by Brandt et al. (2011). In the first hour after pile driving porpoise 

acoustic activity was reduced 100% and remained at below normal levels for 24 to 72 hours at a 

distance of 2.6 km from the construction site. 

Tougaard et al. (2009) studied underwater noise produced by three types of wind turbines. They 

concluded that it was unlikely that the noise was harmful to harbor porpoise and not capable of 

masking communication. Lucke (2007), however, pointed out that while a study conducted on 

captive harbor porpoises in the Netherlands showed that potential masking effects of wind 

turbine operational noise would be limited to short ranges in the open sea, existing sound 

measurements have been carried out only on relatively small turbines, and masking studies do 

not take into account the larger and potentially noisier turbines that may be developed in the 

future. In a study that played back wind farm operational noise to harbor porpoise off 

Vancouver, Canada, Koschinski et al. (2003) found that harbor porpoises showed a clear reaction 

to the wind turbine noise. Closest approaches increased from a median of 120 m to 182 m, and 

during exposure to the sound, the number of time intervals when porpoise echolocation clicks 

were detected doubled. Scheidat et al. (2011) studied harbor porpoise occurrence around the 

Dutch offshore wind farm Egmond aan Zee. They found that, compared to reference sites,

harbor porpoise acoustic activity was significantly higher inside the wind farm. The cause is not 

clear but may be related to an increase of food availability or a decrease of boat traffic inside the 

wind farm.
129

2.29.14 Data Gaps and Research Recommendations

The best abundance estimate is from 2006 and is now 5 years old. The information on harbor 

porpoise distribution and abundance (other than stranding and by-catch observations) outside of 

the summer months is old (e.g., CETAP data from late 1970s and early 1980s). There is limited 

information on harbor porpoise food habits in the U.S. Atlantic.

2.30 WEST INDIAN MANATEE (TRICHECHUS MANATUS LATIROSTRIS)

2.30.1 Status 

The Florida manatee is listed under the Endangered Species Act. The stock is protected by the 

State of Florida under the Florida Manatee Sanctuary Act of 1978, as amended (§ 379.2431(2), 

FS) (US Fish and Wildlife Service 2009). As an endangered species, manatees are considered by 

default to be a “strategic stock” and “depleted” under the MMPA (US Fish and Wildlife Service 

2009). The IUCN Red List lists its status as “Vulnerable.”

2.30.2 General Distribution

Three species of manatees inhabit subtropical and tropical waters on both sides of the Atlantic 

Ocean (Reynolds III et al. 2009). The West Indian manatee is found in coastal waters from 

approximately the Chesapeake Bay south into the Gulf of Mexico, throughout the Caribbean and 

into northern South America. The range of the Florida subspecies (T.m. latirostris) is from 

eastern Texas to Virginia; individuals have been observed as far north as Massachusetts in 

summer months (Fertl et al. 2005; Reynolds III et al. 2009; Schwartz 1995; US Fish and Wildlife 

Service 2009). In winter, manatees are generally restricted to coastal and inland waters of 

peninsular Florida, where they seek shelter in and near warm-water springs, industrial effluents, 

and other warm water sites (Hartman 1979; Lefebvre et al. 2001; US Fish and Wildlife Service 

2009). 

Deutsch et al. (2003) radio-tagged 78 manatees along the coast of Georgia and Atlantic Florida 

from 1986-1998. They used these data to describe seasonal movements, migratory behavior, and 

site fidelity of manatees in this area. They found that most manatees migrated seasonally and 

individuals used 1-2 core areas 90% of the time in a given season. Information from tagged 

juvenile manatees provided evidence for strong philopatry.

In general, the distribution of the Florida manatee is influenced by temperature and possibly by 

access to fresh drinking water (Reynolds III et al. 2009). Most observations of manatees along 

the U.S. Atlantic coast occur in the BOEM Straits of Florida Planning Area; there have been

seasonal observations in the South Atlantic Planning Areas. Extralimital occurrence has been 

documented in the North Atlantic and Mid-Atlantic Planning Areas. Manatee synoptic count 

data for the years 1991-2001 are shown in Figure 2.30-1.

2.30.3 General Abundance 

The total population of Florida manatees along the U.S. Atlantic coast is unknown but it is 

believed to be increasing (Waring et al. 2011). The best count of manatees on the Florida 

Atlantic coast is 2,432 animals, based on a synoptic survey in January 2011
130

(http://myfwc.com/research/manatee/projects/population-monitoring/synoptic-surveys/). The 

survey was conducted in part of the BOEM Straits of Florida Planning Area.

Craig and Reynolds III (2004) presented a stochastic model that can be used to assess population 

trends and abundance in Florida manatees. Edwards et al. (2007) analyzed the probability of 

detecting manatees during aerial surveys and developed a correction factor. Kendall et al. (2004)

created a multi-state mark-resighting model using photo-id sighting data for the Northwest and 

Atlantic manatee management units. 

2.30.4 Habitat Preference 

The Florida manatee lives in shallow, relatively calm, freshwater, brackish, and marine coastal 

habitats that are also used by humans (O’Shea and Kochman 1990). As stated in the General 

Distribution section above, Florida manatees are influenced by temperature; in cold weather, 

they will move south and seek out natural or artificially occurring areas of warmer water 

(Reynolds III et al. 2009). Groups of over 300 manatees have been observed in the warm water 

effluent of power plants along the Florida coast (often in response to cold weather) (Reynolds III 

et al. 2009).

Gannon et al. (2007) found that habitat selection was influenced by availability of food and 

thermal and freshwater sources. Females with calves were additionally influenced by ambient 

noise, currents and added nutritional requirements. Adimey et al. (2008) described the feasibility 

of using a “Crittercam” system on wild manatees. This technology can provide insight into 

habitat. 

Manatees commonly use resting holes which are depression in the substrate. Bacchus et al. 

(2009) described the resting holes used by manatees in Belize. They found that resting hole sites 

were significantly deeper that non-resting hole sites and the water was calmer. 

Miksis-Olds and Miller (2006) studied transmission loss in manatee habitats and found that the 

acoustic environment played an important role in habitat selection.

2.30.5 Stock Structure

Garcia-Rodriguez et al. (1998) analyzed a section of the mtDNA control region from 86 West 

Indian manatees that were sampled at 8 different geographic locations. They identified 15 

haplotypes and found three distinct lineages that corresponded with three geographic areas: 

Florida and the West Indies; Gulf of Mexico to the Caribbean rivers of South America; northeast 

Atlantic coast of South America. Along the U.S. Atlantic coast of Florida, manatees are placed 

in one of two regional management units: Upper St. Johns River or Atlantic Coast (U.S. Fish and 

Wildlife Service 2001). 

Carney et al. (2007) presented a minimally invasive technique for collecting manatee skin 

samples which can be performed from a boat, dock, etc., while leaving the animal in its habitat. 

Hunter et al. (2010) successfully used 17 Australian dugong (Dugong dugon) microsatellite 

primers to analyze the Florida manatee. This cross-species panel provided additional genetic 

information. 
131

2.30.6 Life History Traits 

Reynolds III et al. (2009) summarized available life history data. Mean age at first reproduction 

is 5 years and maximum age was reported as 60 years. Gestation is 11-13 months, lactation lasts 

1-2 years and the inter-calving interval is 2.5 years. There are few details available about the 

social structure of manatees but they are thought to follow the fission-fusion model (Reynolds III 

et al. 2009). 

Langtimm and Beck (2003) found adult manatees had lower survival rates during years with 

intense storms (e.g. hurricanes). Langtimm et al. (2003) use photo-id data to estimate survival 

probabilities of adults from the four regional populations of Florida manatees. They found adult 

survival ranged from 0.908-0.960.

2.30.7 Food Habits 

Manatees are herbivores and hind gut digesters, like horses and elephants (Reynolds III et al. 

2009). They feed on submerged, emergent, and floating vegetation (U.S. Fish and Wildlife 

Service 2001). Reynolds III et al. (2009) wrote that West Indian manatees have been reported to 

eat over 60 species of plants. 

Alves-Stanley and Worthy (2009) pointed out that although manatees are endangered, relatively 

little is known about their feeding ecology. Their study provided baseline parameters for stable 

isotope analyses using skin samples. They found that turnover rates were slow in skin and thus 

might be useful in analyzing intake over a long period of time. Ames et al. (1996) also studied 

stable isotopes in the skin of captive manatees and in the internal organs of stranded manatees.

Lefebvre et al. (2000) compared manatee feeding patterns in Florida and Puerto Rico. Their 

results suggested that the manatees in Florida were less specialized than those in Puerto Rico. 

In their analysis of manatee foraging and anthropogenic sound, Miksis-Olds et al. (2007) found 

that manatees selected grassbeds with lower ambient noise. 

2.30.8 Health 

Data on manatee mortality in the U.S. is collected by the Manatee Carcass Salvage Program. A 

total of 766 manatee deaths were documented in 2010. Eighty-nine (12%) 

of these were attributed to human interaction. (See http://myfwc.com/research/manatee/rescuemortality-response/mortality-statistics/2010/). Potential sources of human-caused mortality and 

injury include vessel interactions, water control structures, commercial/recreational fishing gear, 

ingestion of marine debris, and others. 

Bonde et al. (2004) suggested that manatees are a good candidate species to act as a sentinel to 

ocean health because they are generally resilient but are highly susceptible to harmful algal 

blooms. Additionally, when congregated in large groups, they are particularly susceptible to the 

impacts of epizootics and marine pollution.
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2.30.8.1 Strandings

During 2003–2007, a total of 1805 stranded, dead manatees were collected. Four-hundred thirty 

three (24%) were attributed to human-caused mortality, 362 (20%) were perinatal, 169 (95%) 

were related to cold stress and the rest (841, 47%) were placed in the “Other” category which 

includes deaths attributed to red tide US Fish and Wildlife Service 2009). A total of 80 manatees 

were rescued or assisted and released from 2003-2007 US Fish and Wildlife Service 2009). 

2.30.8.2 Contaminants

Ames and van Vleet (1996) analyzed 45 samples (liver, kidney, and blubber) from Florida 

manatees for organochlorines. The pesticide levels were low so they were unable to make any 

conclusions regarding age, gender or location. A captive-born young manatee had higher levels 

of pesticide concentrations indicating maternal transfer. Reynolds III et al. (2009) reported that 

the effects of contaminants on manatees are unknown. 

2.30.8.3 Disease

There have been several epizootic events involving Florida manatees and dinoflagellate blooms 

(which produce red tides and poisonous neurotoxins). In 1982, 39 manatees were found dead 

(two were hit by boats) during a 10-week period. A die-off of double-crested cormorant 

(Phalacrocorax auritus) occurred simultaneously as did a bloom of red tide (produced by 

Gymnodinium breve). 

Bossart et al. (1998) described brevitoxicosis in manatees that died as part of the 1996 epizootic 

in Florida. The authors suggested that the poisoning was a result of chronic exposure to 

neurotoxins via feeding and breathing. Flewelling et al. (2005) reported that fish and sea grass 

can accumulate high levels of the toxin and act as vectors. Bossart et al. (2002) documented 

viral papillomatosis in captive manatees. 

Halvorsen and Keith (2008) described an immunosuppression cascade in manatees. They 

suggested that, although the manatee is relatively robust, a change in environmental conditions 

(e.g., red tide) can trigger an immunosuppressive cascade which includes interrelated diseases 

and conditions.

2.30.9 Acoustics 

Underwater vocalizations of both captive and wild manatees were studied by O’Shea and Poche 

(2006). The found that the highest rate of vocalization occurred between mothers and calves. 

The manatees also used vocalization to stay in touch with the group. They measured individual 

fundamental frequencies from 1.75 to 3.90 kHz. Their study suggested that vocalizations were 

individually unique.

Colbert et al. (2009) studied sound localization abilities in two manatees using a four-choice 

discrimination paradigm. Their results suggested that manatees are capable of localizing 

manatee vocalizations and boat engine noises. Miksis-Olds and Tyack (2009) found that 

ambient noise had a detectable effect on manatee communication.
133

A number of papers by Gerstein et al. (1999, 2002, 2008, 2010) provided information about 

manatee hearing, communication, and acoustics. Gur and Niezrecki (2010, 2007) described 

experiments related to denoising manatee vocalizations in order to use passive acoustic 

detection. Phillips and Beusse (2006) described detection ranges of manatee vocalizations in 

various acoustic settings which can be used in creating manatee detection systems. 

2.30.10 Fisheries By-Catch and Entanglement 

At least ten manatees died as a result of entanglements or ingestion of marine debris from 2003-

2007 (Waring et al. 2011). No known sources of commercial gear were identified in these cases.

Beck and Barros (1991) analyzed the stomach contents of 439 Florida manatees. They found 

debris in 63 of the gastrointestinal tracks; four other manatees died as a direct result of ingestion. 

Monofilament fishing line was the most commonly found debris.

2.30.11 Vessel Interactions 

Watercraft collisions are a significant source of human-caused manatee mortality (Beck et al. 

1982; U.S. Fish and Wildlife Service 2001, 2009). In 2010, 83 manatees were 

killed by watercraft (see http://myfwc.com/research/manatee/rescue-mortalityresponse/mortality-statistics/). Beck et al. (1982) analyzed propeller wounds to understand how 

propeller size and horsepower impact manatee mortality. They concluded that large motor boats 

with inboard engines likely caused many of the mortalities. 

Buckingham et al. (1999) analyzed the relationship between manatees using warm water refuges, 

temperature and boating activity. They concluded that recreational boating influenced manatee 

distribution. Calleson and Frolich (2007) and Laist and Shaw (2006) found that a reduction in 

boat speed in areas commonly used by manatees appeared to reduce risk of injury to the animals. 

Manatees were found to respond to approaching vessels with a “fright” response and moved 

towards deeper water (Nowacek et al. 2004). 

Aipanjiguly et al. (2003) surveyed boaters in Florida regarding manatee conservation. Results of 

this survey indicated that boaters preferred more education/public outreach than more stringent 

laws. 

2.30.12 Energy Projects 

Reynolds III and Wilcox (1994) described monitoring manatee numbers at five power plants. 

Their study suggested that up to 41% of the total Florida manatee population could be observed 

at power plants at one time. Deutsch et al. (2003) reported that many manatees are able to 

overwinter further north of their historic range because of the presence of industrial warm-water 

effluents. Laist and Reynolds III (2005) reported that many of the power plants manatees use 

might soon be retired. It is unclear if the manatees will move south into warmer areas or stay 

near the power plans and suffer an increase in the number of cold-related deaths. The authors 

suggested that in the absence of power plants, warm water springs in northern Florida would be 

the most important source of natural warm water habitat.
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2.30.13 Data Gaps and Research Recommendations

The total population of manatees along the U.S. Atlantic is unknown. Research into the best 

sampling methodology for obtaining a total population estimate should continue. Stock structure 

along the Florida coast should be further clarified. Additionally, Alves-Stanley and Worthy 

(2009) stated that relatively little is known about manatee feeding ecology.

2.31 HARBOR SEAL (PHOCA VITULINA CONCOLOR)

2.31.1 Status 

The harbor seal is not listed under the Endangered Species Act. The species is considered of 

“Least Concern” on the IUCN Red List. It is afforded protection in U.S. waters under the

MMPA.

2.31.2 General Distribution

Harbor seals (Phoca vitulina) are found on either side of the North Atlantic and North Pacific 

Oceans (King 1983). Burns (2009) wrote that they have the widest distribution of any pinniped 

species. The western Atlantic stock (P.v. concolor) is found from approximately 40°N (New 

Jersey) to 73°N (Baffin Island, Canada) with individuals observed as far south as Florida (Burns 

2009). There is a seasonal movement from Long Island Sound/Southern New England 

northeastward to the Maine coast (potentially further northeast) in late spring and then a 

southward reverse movement occurs in the fall (Barlas 1999; Jacobs and Terhune 2000; 

Rosenfeld et al. 1988; Whitman and Payne 1990; Waring et al. 2006). Harbor seals can be 

observed in all four BOEM Atlantic Planning Areas, although most of the population is 

concentrated in the North Atlantic Planning Area. Sighting, stranding and fishery bycatch 

locations of harbor seals are shown in Figure 2.31-1 and tracks of satellite-tagged harbor seals 

are shown in Figure 2.31-2.

2.31.3 General Abundance 

There is no current abundance estimate for harbor seals along the U.S. Atlantic coast, although 

abundance is thought to be increasing (Waring et al. 2011). The most recent comprehensive 

survey took place May-June 2001, during which 38,014 (including 9,282 pups) were observed 

along the Maine coast (Gilbert et al. 2005). Radio tag data was used to correct this observed 

number for seals not hauled out (correction factor = 2.61). The corrected 2001 population 

estimate was 99,340 (CV=0.097). 

Baird (2001) wrote that there was insufficient information available to evaluate the status of 

harbor seals on the east coast of Canada. Bowen et al. (2003) documented a decline in the 

number of harbor seals on Sable Island (reduced recruitment of breeding females and later 

implantation due to nutritional stress were observed). The authors suggested that the increasing 

Sable Island gray seal population and shark inflicted mortality may be factors in this decline. 

Lucas and Stobo (2000) also documented shark predation on harbor seals on Sable Island.

Thompson et al. (1990) evaluated the effectiveness of aerial vs. boat surveys to estimate 

population size in Orkney, UK. They used time-lapse photography to collect data on haul-out 
135

behavior in relation to time of day and tidal cycle and radio-tags to collect information on seal 

activity budgets. All of this data was used to correct raw counts. Additional studies throughout 

the UK have provided information useful for population estimates (e.g., seasonal distribution, 

activity patterns, use of photo-id, etc.) (Thompson 1989; Thompson et al. 1989; Thompson and 

Harwood 1990; Thompson and Wheeler 2008).

In a study similar to that of Thompson et al. (1990), Huber et al. (2001) used radio tags to correct 

aerial survey counts of harbor seals along the Washington and Oregon coasts. Their total 

population correction factor was 1.53. Ries et al. (1998) also used radio tags to provide an 

estimate of the proportion of seals hauled-out during aerial surveys in the Dutch Wadden Sea. A 

recent advance in technology has allowed the development of a tag that uses mobile phone 

systems to track the animals. This technology will likely add to knowledge of general 

distribution and haul-out behavior, both of which have implications for population estimates 

(Cronin et al. 2009). Bengston et al. (2007) compared the effectiveness of two techniques (shore 

based compared with large scale aerial photography) for surveying harbor seals in glacial fjords.

Harkonen et al. (1999) described the challenges of obtaining vital population information from a 

species that is structured by age and sex. They also wrote that age and sex specific behaviors 

need to be taken into account when estimating populations as they can influence population 

parameters, and described a methodology on how to correct for these sampling errors. Ver Hoef 

and Jansen (2007) presented models that took into account “zeros” in environmental data that are

sometimes included in population models.

2.31.4 Habitat Preference 

Globally, harbor seals can be found on intertidal ledges, mud flats, sand bars, sand or cobble 

beaches and occasionally ice (Reeves et al. 1992); they are found on all of these substrates along 

the U.S. Atlantic coast (Barlas 1999; Gilbert et al. 2005). They occur in more varied habitats 

than any other pinniped (Burns 2009). Renner (2005) and Murray (2008b) studied behavior and 

interspecies interactions of harbor and gray seals at Mt. Desert Rock, Maine, and Cape Cod, 

Massachusetts, respectively.

2.31.5 Stock Structure

Arnason and Johnsson (1992) sequenced the entire mtDNA of the harbor seal. They found the 

total length of the sequence was 16826bp but the control region was unusually long. Stanley et 

al. (1996) analyzed worldwide patterns of harbor seal mtDNA differentiation. They analyzed 

227 samples from 24 locations using a 435bp segment of the control region. They found that 

populations in the eastern and western Atlantic and Pacific Oceans were separated into four 

regions. Within those four regions, seals that were further separated geographically were also 

further separated genetically. 

Goodman (1998) used seven microsatellite DNA polymorphisms (n=1029 seals) to analyze 

differences between 12 geographic locations in the northeast Atlantic. He found that 

differentiation was greater over distances, especially where there was discontinuous distribution. 

These results suggested that harbor seal philopatry operates over a distance of 300-500 km.
136

In Alaska, O’Corry-Crowe et al. (2003) used mtDNA analyses to study population subdivision 

and dispersal of harbor seals. They collected samples from 881 seals in 180 geographic 

locations. Their results showed substantial population division along the Alaska coast and 

identified a minimum of 12 clusters that differed from each other significantly and could be 

considered separate stocks. Prior to this study the Alaskan harbor seal population was managed 

as only 3 stocks.

In a similar study, Huber et al. (2010) used mtDNA to analyze the population structure of harbor 

seals in Washington State. They analyzed samples from 552 harbor seals in nine different 

locations. They found a total of 73 haplotypes, and 37 individual seals had a unique haplotype. 

Their results identified four stocks and suggested that the inland waters should be managed as 

two stocks instead of one.

Coltman et al. (1998b) used six microsatellite markers to measure male mating success on Sable 

Island. Their results suggested that it was unlikely that most pups were fathered by a small 

group of successful males. They also found that females do not exhibit fidelity to the same male 

from year to year on Sable Island.

Herreman et al. (2009a) analyzed six microsatellite markers to estimate gene flow between 

Glacier Bay, Alaska, (declining population) and Prince William Sound, Alaska (stable 

population). They found these populations formed one panmitic population but there is higher 

gene flow from Glacier Bay to Prince William Sound (n=63/generation) than the reverse 

(n=22/generation). This gene flow was driven by male movement.

2.31.6 Life History Traits 

As is summarized in Burns (2009), females and males become sexually mature at 3-4 and 4-5 

years, respectively. Maximum life span is about 35 years. Females give birth to one pup per 

year and lactation last approximately four weeks. Reijnders et al. (2010) found that partuition 

date for harbor seals in the Wadden Sea has moved, which shortens the seals annual cycle. They 

deduced that this was most likely because of a shortening of embryonic diapauses due to an 

improved forage base. 

Schreer et al. (2010) showed that harbor seal pups nurse primarily in the water. Skinner (2006)

described the physical and behavioral development of harbor seal pups in mid-coast Maine.

2.31.7 Food Habits 

Harbor seals are generalists and usually feed on the most abundant and easily caught prey (Burns 

2009; Härkönen 1987; Pierce et al. 1991; Tollit et al. 1997). Tollit et al. (1997) found that the 

most abundant fish species in the Moray Firth area of Scotland contributed the most to the seals’ 

diet. Harbor seal diets often show seasonal variation (Herreman et al. 2009b; Payne and Selzer 

1989; Pierce et al. 1991). Prey species include: cod (Gadus morhua), hake (Urophycis spp.), 

mackerel (Scomber scombrus), herring (Clupea spp.), shad (Alosa spp.), capelin (Mallotus 

villosus), sand lance (Ammodytes spp.), sculpins (Artediellus spp.), and flat fish 

(Pleuronectiformes) (Brown and Mate 1982; Burns 2009; Hammill and Stenson 2000; Hauksson 

and Bogason 1997; Härkönen 1987; Pierce et al. 1991; Thompson et al. 1991; Thompson and 

Miller 1990). On Cape Cod, Massachusetts, Payne and Selzer (1989) found that sand lance was 
137

the single dominant prey, followed by herring. In another study on harbor seal food habits on 

Cape Cod, Ferland (1999) also found that sand lance was the most frequently occurring (85%) 

prey species followed by winter flounder. Williams (1999) analyzed the stomach contents of 

harbor seals that had been incidentally caught in sink gillnets in the Gulf of Maine. Silver hake 

was the most common prey she identified. Sand lance were not prevalent in these stomachs, 

likely reflecting the habitat in which the seals had been incidentally caught.

Radio tagging studies have showed that harbor seals feed within 30-45 km of haul-sites 

(Thompson et al. 1991; Tollit et al. 1998). Additionally, Tollit et al. (Tollit et al. 1998) found 

that most seals foraged in water that was 10-50 m in depth. 

Herreman et al. (2009b) found evidence in Glacier Bay that competition led to poor quality prey; 

this has potentially led to emigration. Bowen et al. (1992) found that because female harbor 

seals do not have sufficient energy reserves to cover the joint costs of lactation and maternal 

metabolism, they must feed during lactation.

2.31.8 Health

2.31.8.1 Strandings

A total of 1,477 harbor seals have stranded along the U.S. Atlantic coast (Maine to Florida) from 

2005 to 2009. They are the most frequently stranded pinniped in the U.S. Atlantic. Most of 

these were found along the Maine coast (n= 852, 59%), followed by Massachusetts (n= 370, 

26%). These two states account for 84% of all stranding observations. There have been two 

unusual mortality events. The first was declared in the northern Gulf of Maine in 2003-2004; no 

common cause of death has been identified. A second UME was declared in the autumn of 2006 

and was attributed to an infectious disease. Table 2.31-1 summarizes this stranding data (Waring 

et al. 2011). Bogomolni et al. (2010) analyzed stranding data from marine mammals and 

seabirds found along the coast of southern New England. They found that the most commonly 

identified cause of death in harbor seals was disease. .

Table 2.31.1 Harbor Seal Strandings by State and Year 

State 2005 2006 2007 2008 2009 TOTAL

ME 121 371 106 178 76 852

NH 31 28 6 3 15 83

MA 101 94 51 50 74 370

RI 3 6 8 6 5 28

CT 2 1 3 0 0 6

NY 22 11 11 5 14 63

NJ 1 7 6 7 11 32

DE 3 2 0 0 0 5

MD 2 0 0 0 2 4

VA 3 2 0 1 3 9

NC 8 4 0 6 6 24

FL 0 1 0 0 0 1

TOTAL 297 527 191 256 206 1477

(Data from Waring et al. 2011)
138

2.31.8.2 Contaminants

Neale et al. (2009) analyzed PCB and DDE contamination in harbor seals from central California 

and Alaska. In Alaska, concentrations increased in males during their lives (likely due to 

continued exposure), but female levels lowered due to offloading via pregnancy and lactation. In 

California, pups showed the highest contaminant load, indicating stable to decreasing exposure. 

Hall et al. (1992) found that there was a significant difference in the OC concentration in tissues 

from seals that had died compared with seals that survived the 1988 European epizootic (phocine 

distemper virus - PDV) event. 

Tabuchi et al. (2006) found evidence of contaminant-related disruption of TH (thyroid hormone) 

in harbor seals sampled in Washington state and British Columbia, Canada.

Several studies have used controlled feeding studies, during which captive seals were fed fish 

from contaminanted areas, such as the North Sea (Brouwer et al. 1989; Ross et al. 1996; Vost 

and Osterhaus 1995; de Swart et al. 1996, 1995). The goal of these studies was to analyze the 

health impacts of a diet of contaminanted fish. Brouwer et al. (1989) found that the seals eating 

fish contaminated with PCB exhibited both vitamin A and thyroid hormone deficiency. Ross et 

al. (1996) found a suppression of natural killer cell activity in seals that were fed fish from the 

Baltic Sea. de Swart (1995) documented impaired immune response in seals that were fed fish 

from the Baltic. In their review paper, de Swart et al. (1996) conclude that, given these feeding 

studies, it can be expected that seals in contaminated areas are likely to exhibit impacted immune 

function.

Anas (1974) analyzed heavy metals in Pacific harbor seals (P.v. richardi). Park (2009)

documented PCB’s and OH-PCB’s in the livers of harbor seals from the Gulf of Maine and San 

Francisco Bay. Brookens et al. (2008) measured mercury body burdens in pups from central 

California. They analyzed THg (total mercury) concentrations in various organs and suggested 

that muscles sampled from specific sites is best for these analyses. Agusa et al. (2011b) analyzed 

the accumulation of trace metals in harbor seals that had stranded during the mass mortality in 

2002 in the North Sea. 

Shaw et al. (2009) measured perfluorochemicals in harbor seals samples from the northwest 

Atlantic. Their results showed concentrations in pups that were 2.6 times that of adult females 

indicating substantial maternal transfer.

2.31.8.3 Disease

There have been several documented harbor seal die offs along the New England coast. One 

occurred in 1979-1980 and was attributed to an avian virus, a second occurred in 1982 (Geraci et 

al. 1982; Hinshaw et al. 1984). A die off due to PDV occurred along the New England coast 

1991-1992 (Duignan et al. 1995b). Several UME’s have been declared for harbor seals in New 

England; for more details, see the Strandings section above.

A longitudinal study (1980-1994) of harbor and gray seals on the Atlantic coast of North 

America showed that gray seals had a higher percentage of morbillivirus neutralizing antibodies 
139

(73%) compared with harbor seals (37%) (Duignan et al. 1995b). The titers were significantly 

higher against PDV compare to other morbilliviruses. During winter 1991-1992 there was a 

harbor seal epizootic along the northeast U.S.; stranded animals tested during that event showed 

a significant increase in the presence of PDV antibody (83%). The authors suggested that PDV 

is enzootic in gray seals and that harbor seals become infected through casual contact with gray 

seals. Harkonen et al. (2006) reviewed how PDV outbreaks have spread in European waters. 

They also suggested that gray seals were potential vectors by acting as either reservoirs for the 

disease or by having sub clinical infections. Swinton et al. (1998) analyzed persistence 

thresholds for PDV infection in metapopulations of harbor seals. 

Osterhaus et al. (1985) described the first isolation and partial characterization of a herpes virus 

from harbor seals in the Netherlands. Schumacher et al. (1993) found evidence of colloid 

depletion and fibrosis in the thyroids of harbor seals that died during the 1988-1999 epizootic in 

the North Sea. 

Philippa et al. (2009) described neurological signs in harbor seals infected by PDV and those that 

had died during the 2002 epizootic in northern Europe. They found that neurological signs were 

one of the most common symptoms in pups with PDV. Nollens et al. (2010) found a respiratory 

coronavirus in one harbor seal that had died during a pneumonia epizootic in California. 

Cabezon et al. (2011) documented antibodies to Toxoplasma gondii in harbor seals sampled 

along the coast of the UK and France.

Moore et al. found gas bubbles in the tissues of seals incidentally killed in gillnet fishery. 

In an effort to correlate genetic data with fitness, Rijks et al. (2008) analyzed heterozygosity and 

lung worm burden. They found that homozygosity predicted higher lung worm burdens in 

young animals (the age at which lung worms most impact fitness). To understand the 

relationship between genetic variation and birth weight and neonatal survival, Coltman et al. 

(1998a) used a measure of genomic diversity based on the mean squared difference between 

microsatellite alleles within an individual, called mean d2

. Using this technique, they found that 

birth weight was positively influenced by age of mother, gender and either heterozygosity or 

mean d2. 

2.31.9 Acoustics

Kastelein et al. (2009) quantified the underwater hearing capability of two captive one-year old 

female harbor seals. They found maximum sensitivity occurred at 1 kHz and the frequency 

range of best hearing was from 0.5 to 40 kHz. This study suggested that harbor seals hear over a 

greater range than previously thought. Kastelein et al. (2010) described the effect of signal 

duration on underwater hearing thresholds of two two-year old female harbor seals. Both Jacobs 

and Terhune (2002) and Nelson et al. (2006) studied the effectiveness of acoustic harassment 

devices on harbor seals. Jacobs and Terhune (2002) found no response or change in seal 

behavior (although sample size was small). Nelson et al.’s (2006) study showed that acoustic 

harassment was ineffective in deterring seal predation on salmon aquaculture farms in Maine. A 

study examining harbor seal haul-out numbers relative to time of day, ambient noise levels, and 

tide levels found a correlation between seal haul-out numbers during the night and noise levels 
140

(Acevedo-Gutiérrez and Cendejas-Zarelli 2011). The authors were not able to conclude, 

however, that the nocturnal haul-out behavior was a related to human development.

2.31.10 Fisheries By-Catch/Entanglement 

Total annual estimated average fishery-related mortality for 2004-2008 is 425 harbor seals. Most 

of those (n= 387, 91%) are attributed to the Northeast Sink Gillnet Fishery. 

Table 2.31.2 Annual Estimated Fishery-related Mortality for Harbor Seals along the U.S. 

Atlantic coast, 2005-2009 

Fishery (2004-8) Mean Annual Mortality (CV)

Northeast Sink Gillnet 332 (0.14)

Mid-Atlantic Gillnet 45 (0.39)

Northeast Bottom Trawl unk

Northeast Mid-Water Trawl 0.3 (0.81)

2.31.11 Vessel Interactions 

Henry and Hammill (2001) studied the impact of small boats on the haul-out activity of harbor 

seals in the Saint Lawrence Estuary, Canada. They found that kayaks caused the most 

disturbances, followed by canoes, motor boats and sailboats. The number of seals hauled-out 

decreased after a disturbance except when the seals were molting and hesitant to go into the 

water. Jansen et al. (2006) studied the disturbance cruise ships have on harbor seals in 

Disenchantment Bay, Alaska. Koschinski (2008) reviewed available literature to assess the 

possible impact of personal watercraft (PWC) on harbor porpoise and harbor seals. The 

Northeast and Southeast U.S. Marine Mammal Stranding Network databases indicate that 13 

stranding mortalities between 2005 and 2009 exhibited signs of boat strike interactions.

2.31.12 Energy Projects 

Both extractive and renewable offshore energy projects have the potential to impact the marine 

environment in a variety of ways, including habitat alteration and the introduction of noise via 

seismic exploration activities (e.g., airguns), vessel/aircraft activity, construction and operation

(Geraci and St. Aubin 1980, Bain and Williams 2006, Thompsen et al. 2006, Cada et al. 2007, 

Compton 2008, Evans 2008, MMS 2008, Burgman 2010, Boehlert and Gill 2010, Dolman and 

Simmonds 2010, Edrén et al. 2010, Bush 2011, ICES 2011). The impact of these activities on 

marine mammals is unclear. 

The 2010 Report of the Working Group on Marine Mammal Ecology (ICES 2010) stated that 

very little is known about the impact of the construction and operation of offshore wind-farms. 

Madsen et al. (2006b) reviewed available current information on wind farm and marine 

mammals and wrote that the noise impact is more severe during construction than operation. 

The 2011 Report of the Working Group of Marine Mammal Ecology (ICES 2011) reported that 

there was no change in seal haul-out behavior in the vicinity of a tidal turbine and shore-based 

surveys showed no evidence of disturbance during construction. 
141

Koschinski et al. (2003) played back simulated 2 MW (Megawatt) wind-turbine noise in Fortune 

Island, Vancouver, Canada. They found that the seals showed a distinct reaction to the noise, 

including surfacing at a greater distance. They concluded that harbor seals are capable of 

hearing the low-frequency noise produced by the wind turbines. 

The effect of a large offshore wind farm on harbor and gray seals within a nearby seal sanctuary 

(4 km) in Denmark was described by Edren et al. (2010). They used time lapse photography, 

visual and aerial surveys to document haul-out behavior during pre and post-construction. They 

found no long term impact on haul-out behavior. There was a significant short term decline in 

numbers during sheet pile driving at or near the wind farm.

Tougaard et al. (2009) studied underwater noise produced by three types of wind turbines. They 

concluded that it was unlikely that the noise was harmful to harbor seals (also harbor porpoise)

and was incapable of masking communication.

2.31.13 Data Gaps and Research Recommendations

The most recent population estimate for the U.S. Atlantic coast is from 2001 and out of date. 

There is little known about local and regional movements of harbor seals along the northeast 

U.S. coast. Most food habits studies have been done in isolation and without understanding of 

foraging range. Very little life history data is available specific to this area. Most of the 

contaminant and disease research has been done in other parts of their range. 

2.32 HARP SEAL (PAGOPHILUS GROENLANDICUS)

2.32.1 Status 

The harp seal is not listed under the Endangered Species Act. The species is considered of 

“Least Concern” on the IUCN Red List. It is afforded protection in U.S. waters under the 

MMPA.

2.32.2 General Distribution

Harp seals are distributed throughout the North Atlantic and Arctic Oceans in three recognized 

stocks: East Ice (White Sea), West Ice (Greenland Sea), and the Northwest Atlantic (Lavigne 

2009; Lavigne and Kovacs 1988). Its range is tied to the pack ice (2009). The Northwest 

Atlantic population has two breeding aggregations: The Front off the coast of Newfoundland and 

Labrador, and in the Gulf of St. Lawrence (Lavigne 2009). As is summarized in Lavigne (2009)

and Lavigne and Kovacs (1988), harp seals are highly migratory (Lavigne 2009). After the 

breeding season, the Northwest Atlantic harp seals move north into feeding grounds. They move 

along the coast of Greenland and Baffin Island and into Hudson Bay. In the fall, they move 

south again. 

The harp seals observed along the U.S. Atlantic Coast likely come from the northwestern 

Atlantic population. There is no resident population of harp seals in the U.S., but transient 

animals are observed on beaches and in stranding and by-catch data. Harp seals are most often 

seen in the months January-May (Harris et al. 2002), which corresponds with when they are at 

the southern end of their migration. Most of the animals observed in the U.S. are juveniles 
142

(Harris et al. 2002) and most are in the BOEM North-Atlantic Planning Area. Sighting, 

stranding, and fishery bycatch locations of harp seals are shown in Figure 2.32-1 and tracks of 

satellite-tagged harp seals are shown in Figure 2.32-2.

2.32.3 General Abundance 

The Northwest Atlantic population is the largest of the three (Lavigne 2009) and was estimated 

to be 6.5 million seals in 2008. This population has been increasing since the late 1970s (DFO 

2010). There is no resident population of harp seals in the U.S. but see the Stranding and 

Fisheries By-catch sections below for observed numbers. Salberg et al. (2009) described the 

used of generalized additive models to estimate pup production. They found this technique 

decreased the coefficient of variation around the estimate.

There was a dramatic increase in the number of harp and hooded seals on Sable Island during the 

mid-1990s (Lucas and Daoust 2002). Likewise, there was an increase of harp and hooded seals 

throughout the northeast U.S. during this same time period (Harris et al. 2002; Harris and Gupta 

2006; Stevick and Fernald 1998).

Harp seals are hunted throughout their range by both subsistence (2008= ~85,000 seals taken) 

and commercial (2008= 72,000 taken; has been over 300,000 in prior years) hunters (DFO 

2010). 

2.32.4 Habitat Preference 

The harp seal’s range is generally linked to the southern and northern edge of the pack ice 

(Lavigne 2009). They use the ice for pupping (Lavigne 2009; Lavigne and Kovacs 1988); 

mating usually takes place in the water (Lavigne and Kovacs 1988). Schreer and Kovacs (1997)

reported that they dive to a maximum depth of 370 m. 

Johnston et al. (2005a) analyzed sea ice cover in eastern Canada 1969-2002. They found a high 

degree of variability and that heavy ice years corresponded with a positive spring North Atlantic 

Oscillation (NAO) conditions. They found that during light ice years, there was often a 

significant reduction of ice in the Gulf of St. Lawrence and Newfoundland by early March when 

harp seals pup. The authors point out that a reduction of ice could potentially lead to increased 

neonatal mortality, changes in available prey and increase in epizootics because of crowding at 

pupping sites. Friedlaender et al. (2010) also analyzed sea ice conditions in relation to the NAO 

and its impact on the habitat available for harp seals. They found a consistent positive 

relationship between sea ice in the western north Atlantic and the NAO index. 

In their GIS-based analysis of harp and hooded seal strandings in the Gulf of Maine, Harris and 

Gupta (2006) found that being close to an offshore basin, deep water, public land and areas with 

lower human density were all predictors of where ice seals would strand. 

2.32.5 Stock Structure

There are three recognized stocks of harp seals: East Ice (White Sea), West Ice (Greenland Sea), 

and the Northwest Atlantic (Lavigne 2009; Lavigne and Kovacs 1988). Perry et al. (2000) used 

mtDNA analyses to assess harp seal stock structure. They identified 13 haplotypes and found 
143

strong differentiation between seals from the northeast vs. northwest Atlantic. They did not find 

any differentiation between the two northwest Atlantic pupping sites (Front vs. Gulf).

Kretzman et al. (2006) analyzed samples from 65 harp seals that had stranded along Long Island, 

New York. They used between 9-12 microsatellite loci to measure d2

. Their results showed that 

animals that survived had a slightly higher d2 than animals that died. Carr et al. (2008) included 

harp seals in their experiments utilizing DNA microarray analyses. 

2.32.6 Life History Traits 

Harp seals become sexually mature at approximately 5.7 years (DFO 2010), although this has 

varied through time (Sjare and Stenson 2009). As is summarized in Lavigne (2009), female harp 

seals give birth to one pup and nurse it for about 12 days. 

Sjare and Stenson (2009) describe the long-term trends in female harp seal life history traits 

(1980-2004) in the Northwest Atlantic population. They documented changes in pregnancy rates 

and mean age at first reproduction that reflected density dependent responses. The changes in 

the population size during this time period (1980-2004), however, were likely influenced by 

other ecological or environmental factors. 

2.32.7 Food Habits 

Beck et al. (1993) analyzed the stomach contents of harp seals (n=140) taken from the Gulf of St. 

Lawrence and Hudson Strait. They found that stomach contents varied by season and location. 

Samples from the northern Gulf of St. Lawrence contained a variety of prey while samples from

Hudson Bay and the Gulf contain mostly capelin (Mallotus villosus). Stenson et al. (1997)

studied harp seal predation in eastern Canada. They found that both Arctic cod (Boregadus 

saida) and capelin were important prey off Newfoundland but also found capelin dominated in 

the Gulf of St. Lawrence. In their study on the estimated prey taken by seals in Atlantic Canada, 

Hammill and Stenson (2000) found that capelin was the most common prey eaten by harp seals. 

This was followed by sand lance (Ammodytes spp.), Arctic cod, Greenland halibut (Reinhardtius 

hippoglossoides), Atlantic cod (Gadus morhua), Atlantic herring (Clupea harengus), and redfish

(Sebastes spp.). 

Tucker et al. (2009) used quantitative fatty acid signature analysis (QFASA) to investigate harp 

and hooded seal food habits. Their study included samples from 526 harp seals collected from 

1994 to 2004. They found that harp seals fed primarily on amphipods, Arctic cod, capelin, 

herring, sand lance, and redfish. Marshall et al. (2010) developed molecular techniques to 

identify prey in harp seal stomach contents.

Harp seals dive to an average maximum depth of 370 m and mean length of dive is 16 minutes 

(Schreer and Kovacs 1997). Nordoy et al. (2008) satellite-tagged harp seals in the White and 

Barents Seas. They found that seals used the water column at 20-300 m and their 

movements/migration were closed linked to capelin migration.
144

2.32.8 Health 

2.32.8.1 Strandings

A total of 511 harp seals have stranded along the U.S. Atlantic coast (Maine to North Carolina) 

from 2005 to 2009 (Northeast and Southeast U.S. marine mammal stranding response databases). 

Eighteen of these animals showed signs of human interaction. Massachusetts had the highest 

number of observed strandings (n= 255, 47%) followed by New York (n= 103, 19%) and Maine 

(n= 77, 14%). These three states account for 80% of all stranding observations. Moore et al. 

(2009) found gas bubbles in the tissues of seals that had been incidentally killed in gillnet 

fishery.

Table 2.32.1 Harp Seal Strandings by State and Year 

State 2005 2006 2007 2008 2009 TOTAL

ME 10 14 8 15 9 56

NH 2 0 1 1 4 8

MA 44 24 51 51 59 229

RI 9 6 2 5 9 31

CT 3 4 1 2 3 13

NY 41 15 19 8 29 112

NJ 12 3 3 12 5 35

DE 2 0 2 0 0 4

MD 2 0 4 1 2 9

VA 4 0 5 3 1 13

NC 0 1 0 0 0 1

TOTAL 129 67 96 98 121 511

(NE and SE marine mammal stranding response databases)

2.32.8.2 Contaminants 

Montie et al. (2010) documented brominated flame retardants (BFRs), including polybrominated 

diphenyl ethers (PBDEs) and current-use, non-PBDE BFRs, organochlorine (OC) pesticides and 

polychlorinated biphenyls (PCBs), in harp seals from the eastern U.S. and Canada.

Vetter et al. (2010) analyzed brominated flame retardant (DPTE) in blubber and brain tissues of 

harp seals from the Barents and Greenland Seas. Agusa et al. (2011a) reported the levels of 19 

different trace metals in the liver, muscle, kidney, gonads and hair from 18 harp seals from 

Pangnirtung (Baffin Island).

2.32.8.3 Disease

Daoust et al. (1993) documented the first case of PDV in a harp seal in a two-month old female 

that had stranded on Prince Edward Island in 1991. Duignan et al. (1997) analyzed harp seal 

samples collected from the western Atlantic from 1988-1993 for PDV. Eighty-three percent of 

the seals they tested were positive for PDV antibodies. A novel Heliobacter spp. was isolated 

and characterized from two harp seals that had stranded along the Massachusetts coast (Harper et 

al. 2003). 
145

Piche et al. (2010) experimentally infected harp seals with lungworm in order to characterize 

pathologic changes.

2.32.9 Acoustics 

Rossong and Terhune (2009) recorded underwater calls of harp seal in the Gulf of St. Lawrence 

in March 2007. They found that communication ranges were impacted by call source levels, 

background noise, and patterns of sound transmission. Van Opzeeland et al. (2009) analyzed 

pup calls on the Front (Canada) and in the Greenland Sea. They found that at the Front, female 

pups had individually identifiable calls 38% of the time and males 42%. This is in contrast with

the Greenland Sea animals: 55% of female pups had identifiable calls but only 8% of males. 

They also found that mother-pup attendance was different (85.1% of mother’s time on Front; 

only 52.2% of mother’s time in Greenland Sea). The authors suggest that these behavioral 

differences might be related to evolutionary change related to hunting or different environmental 

conditions at the two sites.

2.32.10 Fisheries By-Catch and Entanglement 

Total annual estimated average U.S. fishery-related mortality for 2005-2009 is 231 for harp 

seals. Most of those (n=174, 75%) are attributed to the Northeast Sink Gillnet Fishery. See 

Table 2.32-2 for details. A little over 10,000 harp seals are estimated to be taken in Canadian 

fisheries annually (DFO 2010).

Table 2.32.2 Mean Annual Mortality by Fishery 2005-2009

Fishery (2004-8) Mean Annual Mortality (CV)

Northeast Sink Gillnet 174 (0.18)

Mid-Atlantic Gillnet 57 (0.5)

Northeast Bottom Trawl unk

(Waring et al. 2011) (CV in parentheses)

2.32.11 Vessel Interactions 

In 2005 there is a record in the Northeast and Southeast U.S. Marine Mammal Stranding 

Network databases of a harp seal with wounding consistent with vessel interaction.

2.32.12 Energy Projects 

Both extractive and renewable offshore energy projects have the potential to impact the marine 

environment in a variety of ways, including habitat alteration and the introduction of noise via 

seismic exploration activities (e.g., airguns), vessel/aircraft activity, construction and operation

(Geraci and St. Aubin 1980, Bain and Williams 2006, Thompsen et al. 2006, Cada et al. 2007, 

Compton 2008, Evans 2008, MMS 2008, Burgman 2010, Boehlert and Gill 2010, Dolman and 

Simmonds 2010, Edrén et al. 2010, Bush 2011, ICES 2011). The impact of these activities on 

marine mammals is unclear. 

The 2010 Report of the Working Group on Marine Mammal Ecology (ICES 2010) stated that 

very little is known about the impact of the construction and operation of offshore wind-farms. 
146

Madsen et al. (2006b) reviewed available current information on wind farm and marine 

mammals and wrote that the noise impact is more severe during construction than operation. 

The 2011 Report of the Working Group of Marine Mammal Ecology (ICES 2011) reported that 

there was no change in seal haul-out behavior in the vicinity of a tidal turbine and shore-based 

surveys showed no evidence of disturbance during construction. No information is available 

about the impact of energy projects on harp seals.

2.32.13 Data Gaps and Research Recommendations 

Because harp seals are in U.S. waters only as transients, there is no abundance estimate for this 

part of their range. Most of the information about acoustics, food habits, contaminant burden, or 

disease comes from research conducted in Canadian Atlantic waters. 

2.33 GRAY SEAL (HALICHOERUS GRYPUS)

2.33.1 Status 

The gray seal is not listed under the Endangered Species Act. The species is considered of 

“Least Concern” on the IUCN Red List. It is afforded protection in U.S. waters under the 

MMPA.

2.33.2 General Distribution

Gray seals are found in the temperate and subarctic areas on both sides of the north Atlantic 

(King 1983). In the western North Atlantic, gray seals are found from Labrador (Canada) to 

New York (Davies 1957; Mansfield 1966; Lesage and Hammill 2001; Katona et al. 1993). Gray 

seals can be observed in all four BOEM Atlantic Planning Areas, although most of the 

population is concentrated in the North Atlantic Planning Area. There are three well-established 

pupping sites in the U.S.: Muskeget Island, Massachusetts; Green Island, Maine; and Seal Island, 

Maine (Wood LaFond 2009). Sighting, stranding, and fishery bycatch locations of gray seals are 

shown in Figure 2.33-1 and tracks of satellite-tagged gray seals are shown in F igure 2.33-2.

In their study on the comparative movement of harbor and gray seals in Moray Firth, Scotland, 

Thompson et al. (1996) found that gray seals potentially moved 125-365 km away from their 

haul-out site. Sjoberg and Ball (2000) found that most gray seals remained within 50 km of their 

haul-out in the Baltic Sea. Vincent et al. (2002) followed rehabilitated and released juvenile gray 

seals. They found that these animals were able to disperse across large areas quickly and also 

settled into known gray seal haul-out sites after a few months.

2.33.3 General Abundance 

There is no current abundance estimate for the total number of gray seals along the U.S. Atlantic 

coast but it appears this population is increasing (Waring et al. 2011). Wood LaFond (2009) 

provided a single day pup count of 2,649 in 2008. This has increased since pups were first 

observed in the early 1990s (Rough 1991; Wood LaFond 2009). Muskeget Island, 

Massachusetts, is the largest of these three sites; over 80% of all U.S. gray seal pups are born 

there (Wood LaFond 2009).
147

The Canadian populations have increased since the 1960s. Pup production estimates from 2007 

surveys estimate total pup production for the Gulf of St. Lawrence was 13,000 (SE=600) and 

Sable Island was 54,500 (SE=1288) (Bowen et al. 2007b; Hammill et al. 2007). Although these 

populations continue to grow, data from Sable Island has shown a change in vital population 

rates, which indicates that population growth is slowing there (Bowen et al. 2007a, 2007b). The 

annual rate of increase on Sable Island declined from 12.8% in 2004 to 7% in 2007 (Bowen et al. 

2007a).

2.33.4 Habitat Preference 

Katona et al. (1993) reported that gray seals are found on remote, exposed islands, reefs, and 

shoals. Throughout their range they haul-out, molt and give birth to their pups on ice or sandy or 

rocky beaches (King 1983). Renner (2005) and Murray (2008b) studied behavior and 

interspecies interactions of harbor and gray seals at Mt. Desert Rock, Maine and Cape Cod, 

Massachusetts, respectively.

On the Isle of May (Scotland), Pomeroy et al. (2000) documented changes in pupping sites as the 

colony expanded using fine scale digital elevation models. They found that in general the areas 

that were colonized first on the island were close to access points (to the sea) or near standing 

water. They also found that individually marked females showed strong site fidelity (median 

distance between sites used in consecutive years was 25 m). The authors suggested that the 

spatial scale of site fidelity is related to the scale of topographic variation within each site.

2.33.5 Stock Structure

Arnason et al. (1992) sequenced the entire mtDNA of the gray seal. They found the molecule 

was 16,797 base pairs. Allen et al. (1995) used eight microsatellite loci to detect genetic 

differentiation between two breeding sites in the UK. They found structure indicating site 

fidelity in adults and philopatry in pups. Boskovic et al. (1996) analyzed mtDNA from gray 

seals in the Gulf of St. Lawrence (Canada), Sable Island (Canada), Norway, and the Baltic Sea. 

There were no shared haplotypes between the eastern and western North Atlantic seals. 

However, when the two Canadian populations were compared, little or no separation was 

detected. Wood et al. (2011) used both nuclear (nine microsatellite loci) and mitochondrial 

(control region segment) DNA to analyze gray seal stock structure in the northwest Atlantic. 

Their study included samples from the Gulf of St. Lawrence; Sable Island; Green Island, Maine,

and Muskeget Island, Massachusetts. Their results showed no genetic structure between these 

four sites.

In the UK, Gaggiotti et al. (2002) used genetic data to study metapopulation dynamics of gray 

seals. They found that density-dependent dispersal played an important role in the establishment 

of new gray seal pupping sites. 

Walton et al. (2000) analyzed blubber biopsies from two breeding sites in Scotland to ascertain if 

fatty acid analysis could be used to distinguish between populations. They found that the two 

breeding sites could be identified as two distinct feeding groups. Reed et al. (1997) developed a 

technique to use genetic analyses to assign scat samples to species, sex, and individual 

identification. Assigning species and gender to scat samples can eliminate some of the variation 

surrounding seal diet.
148

Several studies have focused on the reproduction in the gray seal by combining behavioral 

observations with genetic analysis. Amos et al. (1993b) found that male reproductive success 

was not as high as behavioral observations (copulations) would suggest. In another study, Amos 

et al. (2001) reported that as few as 1% of males gain significantly higher reproductive success. 

They found that maternal half-siblings were more diverse than would be expected through

random mating. The authors suggested that while behavioral choice is an unlikely mechanism, 

naturally occurring anti-sperm antibodies could prevent inbreeding in small, potentially closed 

populations.

2.33.6 Life History Traits 

Hall and Thompson (2009) reported that females become sexually mature at 3-5 years old and 

males at 6 years old, although males probably don’t breed until older. 

Boness and James (1979) described the reproductive behavior of gray seals on Sable Island. 

They reported that the females are gregarious and probably return to the same part of the beach 

from year to year. Males do not maintain territories but rather compete for the right to stay near 

the group of females. Pomeroy et al. (1994) found that females on N. Rona (UK) exhibited 

pupping site fidelity.

In their study of the reproductive behavior of gray seals on North Rona Island, Anderson et al. 

(1974) concluded that males maintained a high level of sexual activity in order to mate with as 

many cows as possible, rather than spending energy through territorial fighting for exclusive 

access to females. Anderson and Harwood (1985) found that variations in the activity budgets of 

seals appeared to be determined by the type of habitat they were in. 

Several studies have focused on gray seal breeding behavior on ice. Tinker et al. (1995) found 

that the average time budget of males on ice (Amet Island, Canada) was comparable to landbreeding males. Although body size was not correlated with success, reproductive effort 

(estimated by body mass loss over the season) and successful interactions with other males were 

both correlated with success. Haller et al. (1996) found that females breeding on ice transferred 

the same amount of energy to their pups as land-breeding animals but over a shorter period. This 

is likely due to the risk of being separated in an unstable habitat (shifting ice). 

Boness et al. (1995) found that females were more frequently disturbed by males during the latter 

part of the pupping season. Mothers who pupped later in the season weaned pups that were 16% 

lighter than those weaned earlier. The authors suggested that this male harassment might 

contribute to reproductive synchrony by causing reduced maternal performance later on in the 

pupping season. 

Evidence of non-filial nursing in gray seals was documented by Perry et al. (1998). They found 

frequency of fostering varied between three study sites. DNA fingerprinting showed that kin 

selection did not play a significant role in this behavior.

Twiss et al. (2007) studied the impact of climatic variation on effective population size. They 

found that during drier years at North Rona, the degree of polygyny decreased when females 
149

were more dispersed, moving around to find water. Their results showed that changes in local 

weather could alter the annual proportion of males who contributed to the effective population 

size by up to 61%.

There has also been a substantial amount of research on the reproductive behavior of gray seals. 

This research has often combined field observations with genetic analyses; see the Stock 

Structure section for additional details on those studies.

2.33.7 Food Habits 

Gray seals feed on a variety of prey: sand lance (Ammodytes spp.), cod (Gadus morhua), flatfish 

(Pleuronectiformes), haddock (Melanogrammus aeglefinus), catfish (Siluriformes), scorpion fish 

(Scorpaenidae) and cephalopods are important prey species. Their diet shows geographical and 

seasonal variation (Bowen and Harrison 1994; Hammill and Stenson 2000; Hammond et al. 

1994; Hauksson and Bogason 1997; Hauksson and Ólafsdóttir 1995; Mikkelsen et al. 2002; 

Murie and Lavigne 1992; Prime and Hammond 1990). Ampela (2009) analyzed scat samples 

collected in Nantucket Sound (Muskeget and Monomoy Islands) ~2004-2008 and stomach 

contents (from by-caught animals). She found that sand lance, winter flounder, red/white hake,

and Atlantic cod together were 82% of diet by weight. 

McConnell et al. (1999) reported that seals took either long (up to 2100 km) or local trips. In 

eighty-eight percent of trips to sea, the seals returned to the haul-out from which they left and the 

mean length of time for these trips was 2.33 days. Sjoberg and Ball (2000) reported that gray 

seals were mostly in water depths 11-40 m and avoided waters that were greater than 51 m deep. 

They also found that seals apparently selected foraging habitat because of bathymetric factors 

(water depth) rather than simply using the habitat surrounding the haul-out site. 

Austin et al. (2006b) used stomach temperature telemetry to gain insight into gray seal feeding. 

They found that feeding intervals varied from one individual to the next and likely reflected 

differences in prey availability. They also found significant differences between males and 

females with the number of feeding events per day greater in males than females. Feeding event 

size differed by time of day and the length of time between meals increased with the size of the 

previous meal. In a related study, Austin et al. (2006a) deployed three different types of tags on 

the same animals (satellite tag, time depth recorder, and stomach temperature loggers) to better 

understand gray seal foraging success. Their results showed that several factors (e.g., mean 

bottom time, distance traveled, and bathymetry) can predict feeding but the importance of these 

factors varied with temporal scale.

Beck et al. (2007) used fatty acid analysis to examine differences in the diets of males and

females. While sand lance and redfish were important prey, the males’ diets were significantly 

more varied. They also found that females in the post-breeding season selected fewer prey but 

prey of higher quality. Tucker et al. (2007) analyzed carbon and nitrogen stable isotopes to 

understand diet segregation of gray seals on Sable Island. Their analyses showed the adults and 

juveniles could be identified from each other based on stable isotopes as could adult males from 

adult females.
150

2.33.8 Health 

2.33.8.1 Strandings

There were 344 observed gray seal strandings along the U.S. Atlantic coast 2005-2009. The 

majority of these were in Massachusetts (n=210, 61%), followed by New York (n=52, 15%) 

(Northeast and Southeast U.S. Marine Mammal stranding response databases). Bogomolni et al. 

(2010) analyzed stranding data from marine mammals and sea birds found along the coast of 

Southern New England. They found that human interaction was the cause of death in 43% of the 

gray seals included in their study. 

Table 2.33.1 Gray Seal Strandings by State and Year 

State 2005 2006 2007 2008 2009 TOTAL

ME 4 3 5 6 3 21

NH 0 0 1 0 1 2

MA 26 29 50 53 52 210

RI 2 2 5 7 10 26

CT 0 0 0 0 1 1

NY 7 6 21 2 16 52

NJ 2 1 5 3 4 15

DE 0 0 0 1 0 1

MD 3 0 1 1 1 6

VA 1 0 1 1 2 5

NC 0 2 1 1 1 5

TOTAL 45 43 90 75 91 344

(Waring et al. 2011)

2.33.8.2 Contaminants 

Jenssen (1996) estimated that approximately 50% of gray seals at the largest breeding site in 

Norway are contaminated by oil each year as a result of chronic, low level pollution from 

shipping traffic. Jenssen found indications that pups along the Norweigan coast are affected by 

this low-level exposure as exemplified by thyroid hormone and vitamin A status.

Nyman et al. (2002) measured DDT, PCB, and trace elements in the gray seals from Sable 

Island, Canada, and the Baltic Sea. They found that the Baltic population had a higher PCB and 

DDT loads than Sable Island population, although these levels were lower than observed in 

1970s. They also found that on Sable Island only, males had higher contaminant loads than

females (likely due to reproductive offloading). They documented residue amounts of trace 

metals (mercury, cadmium, lead, and selenium from various tissues) and did not see a decrease 

in metal burden in the Baltic animals. Bustamante et al. (2004) documented trace element 

accumulation in various tissue types of Faroese gray seals sampled from 1993-1995. This 

population exhibited higher levels of cadmium, indicating cephalpods are an important prey. 

Blubber samples from pups born on Sable Island, Canada, were analyzed for lipid content and 

OC levels from 1988 to 1991 (Addison and Stobo 1993). These analyses showed that after 

weaning, there was a fairly constant OC burden around which lipid content changed. The 
151

authors concluded that there is very little a seal can do to degrade the contaminant level inherited 

from its mother. Debier et al. (2003) documented the dynamics of PCB transfer during lactation 

in UK gray seals. They found increased PCB concentration in mothers’ serum and milk later in 

lactation which likely reflected changes in blubber. Additionally, they found that pups had 

significantly higher serum PCB levels than their mothers, which indicates that much of the 

transfer of these contaminants occurred in utero.

Harding and Harkonen (1999) used hunting records to model Baltic Sea gray seal population 

trends during the 20th century. They found that hunting had decreased this population during the 

first part of the 20th century, but then recovery was inhibited by reproductive sterility likely 

caused by organochlorines.

See the Disease section below, which describes symptoms associated with contaminant levels.

2.33.8.3 Disease

Baker (1984) studied gray seal pup mortality and morbidity at three sites in the Outer Hebrides. 

Mortality rates were generally similar (14.3-23.2%) but the leading cause of death varied from 

site to site and included starvation, infection, and being washing off of the island. Various 

species of Streptococci and Corynebacterium were documented and adult seals were found to be 

the source of the diseases.

The transfer of sealpox from captive gray seals to their handlers was documented by Hicks and 

Worthy (1987). Osterhaus et al. (1990) documented parapoxvius in five gray seals that were 

admitted to a rehab facility during a PDV outbreak. The authors suggested that the PDV

infection potentially made the seals more susceptible to other infections. Anderson et al. (1974)

documented a high incidence of skin lesions which were often associated with emaciation and 

nematode infection in the Dee Estuary (UK ).

Bergman (1999) examined 159 gray seals (postmortem) from the Baltic Sea 1977-1996. A 

disease complex (lesions of claws, skull bone, intestines, kidneys, etc., and occlusions, stenoses,

and tumors in the uterus) was reported early on. When the study period was divided into two 

decades (1977-1986 and 1987-1996), he found a decrease in uterine obstructions (42% to 11%), 

an increase in pregnancies (9% to 60%) and a decrease in uterine tumors (53% to 43%). 

However, an increase in the presence of colonic ulcers in juvenile seals was documented. 

Bergman et al. (2001) documented renal lesions in Baltic gray seals and suggest that the OC 

pollution in the Baltic Sea is likely a contributing factor.

A longitudinal study (1980-1994) of harbor and gray seals on the Atlantic coast of North 

America showed that gray seals showed a higher percentage of morbillivirus neutralizing 

antibodies (73%) compared to harbor seals (37%) (Duignan et al. 1995b). The titers were 

significantly higher against PDV compare to other morbilliviruses. During winter 1991-1992 

there was a harbor seal epizootic along the northeast U.S.; stranded animals tested during that 

event showed a significant increase in the presence of PDV antibody (83%). The authors 

suggested that PDV is enzootic in gray seals and that harbor seals become infected though casual 

contact with gray seals. Harkonen et al. (2006) reviewed how PDV outbreaks have spread in 
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European waters. The also suggested gray seals were potential vectors by acting as a reservoir 

for the disease or by having sub clinical infections. 

Bean et al. (2004) analyzed patterns of parental relatedness and pup survival. They found pups 

with higher internal relatedness (IR) had significantly lower survival rates. Cammen et al. 

(2011) studied the variation in the major histocompatibility complex (MHC) in gray seals in the 

eastern Atlantic. They found geographic variation in this gene complex with subpopulations 

breeding in similar habitats being more similar genetically, which suggests that habitat-specific 

pathogen could influence MHC evolution.

2.33.9 Acoustics 

Caudron et al. (1998) analyzed pup calls to estimate call variation. They studied seven acoustic 

features and found three that showed the most individuality: location of maximum signal 

strength; the number of harmonics; and frequency and strength of the fundamental. Despite 

these findings, the authors suggest that vocal signals may not play a large role in mother/pup 

recognition, given the infrequent use of pup calls during reunification. A study in Scotland that 

used playback of pup calls found that individual identifiable pup calls failed to prevent allosuckling (i.e., mothers failed to distinguish their pup’s call from that of a non-filial pup) 

(McCulloch et al. 1999). A similar study on Sable Island by McCulloch and Boness (2000)

found that gray seals there reacted more strongly to their own pup’s call than to unfamiliar calls. 

The authors suggested that different selective pressure might be at work at these different sites.

2.33.10 Fisheries By-Catch and Entanglement 

Total annual estimated average fishery-related mortality for 2005-2009 was 678 gray seals. 

Bogomolni et al. (2010) found conclusively that 43% of the gray seals included in their study 

died of human-related causes. The most common human interaction affecting gray seals was 

entanglement in fishing gear. 

Table 2.31.2 Annual Estimated Fishery-related Mortality for Gray Seals along the U.S. Atlantic 

Coast 2005-2009 

Fishery (2004-8) Mean Annual Mortality (CV)

Northeast Sink Gillnet 678 (0.14)

Northeast Bottom Trawl unk

2.33.11 Vessel Interactions 

The impact of vessels on gray seals is unknown. In the Northeast and Southeast U.S. Marine 

Mammal Stranding Network databases two stranding mortalities in 2005 and two in 2008 

exhibited signs of interaction with a boat propeller.

2.33.12 Energy Projects 

Both extractive and renewable offshore energy projects have the potential to impact the marine 

environment in a variety of ways, including habitat alteration and the introduction of noise by

seismic exploration activities (e.g., airguns), vessel/aircraft activity, construction and operation

(Geraci and St. Aubin 1980, Bain and Williams 2006, Thompsen et al. 2006, Cada et al. 2007, 
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Compton 2008, Evans 2008, MMS 2008, Burgman 2010, Boehlert and Gill 2010, Dolman and 

Simmonds 2010, Edrén et al. 2010, Bush 2011, ICES 2011). The impact of these activities on 

marine mammals is unclear. 

The 2010 Report of the Working Group on Marine Mammal Ecology (ICES 2010) stated that 

very little is known about the impact of the construction and operation of offshore wind-farms. 

Madsen et al. (2006b) reviewed available current information on wind farm and marine 

mammals and wrote that the noise impact is more severe during construction than operation. 

The 2011 Report of the Working Group of Marine Mammal Ecology (ICES 2011) reported that 

there was no change in seal haul-out behavior in the vicinity of a tidal turbine and shore-based 

surveys showed no evidence of disturbance during construction.

The effect of a large offshore wind farm on harbor and gray seals within a nearby seal sanctuary 

(4 km) in Denmark was described by Edren et al. (2010). They used time-lapse photography, 

visual and aerial surveys to document haul-out behavior during pre and post-construction. They 

found no long term impact on haul-out behavior. There was a significant short term decline in 

haul-out numbers during sheet pile driving at or near the wind farm.

2.33.13 Data Gaps and Research Recommendations

There is no population estimate for U.S. gray seals, only single day counts. There is little known 

about local and regional movements of gray seals off the northeast U.S. coast. Most food habits 

studies have been done in isolation and without understanding foraging range. Very little life 

history data is available specific to this area. Most of the contaminant and disease research has 

been done in other parts of their range. 

2.34 HOODED SEAL (CYSTOPHORA CRISTATA)

2.34.1 Status 

The hooded seal is not listed under the Endangered Species Act. The species is considered of 

“Vulnerable” on the IUCN Red List. It is afforded protection in U.S. waters under the MMPA.

2.34.2 General Distribution

Hooded seals are highly migratory and their range includes a large part of the North Atlantic 

Ocean (Kovacs 2009). It is not unusual for them to move out of this range; observations have 

been made as far south as Puerto Rico in the Atlantic Ocean and in California (Kovacs 2009). 

They form three breeding aggregations which are considered three separate stocks: one is off the 

east coast of Canada, and is further divided into two groups (The Front off Newfoundland and 

Labrador and the Gulf of St. Lawrence). The second breeding aggregation is found in Davis 

Straits and the third is located on the “West Ice” which is east of Greenland (Kovacs 2009; 

Lavigne and Kovacs 1988). After breeding, hooded seals move towards Denmark Strait for 

molting and then disperse widely from there (Lavigne and Kovacs 1988).

Hooded seals are transient in U.S. waters and are observed in the U.S. Atlantic from January to 

May in New England waters and off the southeast U.S. in the summer and fall (Harris et al. 

2001; McAlpine et al. 1999; Mignucci-Giannoni and Odell 2001). Given their wide distribution, 
154

hooded seal could be observed in all BOEM Atlantic Planning Areas; however, they are most 

likely to be observed in the North Atlantic Planning Area. Sighting, stranding, and fishery 

bycatch locations of hooded seals are shown in Figure 2.34-1; tracks of satellite-tagged hooded 

seals are shown in Figure 2.34-2.

2.34.3 General Abundance 

Hammill and Stenson (2006) estimated that the Northwest Atlantic hooded seal population 

(Front, Gulf, and Davis Strait) was 593,500 (SE=67,200) in 2005. There is a fair amount of 

uncertainty in this estimate due to low survey coverage in some areas/years, limited information 

on reproductive data, and uncertain catch statistics. Hammill and Stenson (2006) considered 

them “data poor” and recommended conservative catch limits. Hooded seals are hunted 

throughout their range by both subsistence hunters (Greenland 2008=6,397 seals taken) and in a 

much smaller Canadian commercial hunt (2006=0 taken but catch numbers have been much 

higher historically) (Stenson 2006). 

2.34.4 Habitat Preference 

Hooded seals are highly migratory and are usually found further offshore than harp seals 

(Lavigne and Kovacs 1988; Stenson et al. 1996). They are pack-ice seals and they spend most of 

their lives in and around sea ice (Kovacs 2009). They are found on the Newfoundland 

continental shelf for winter and spring (Stenson et al. 1996). Folkow and Blix (1999) studied 

hooded seal dive behavior using satellite- linked dive recorders. They found that most dives 

were to depths of 100-600 m, but hooded seals can dive to depths of over 1000 m. 

2.34.5 Stock Structure

The three breeding populations have been considered panmitic (Kovacs 2009). Lavigne and 

Kovacs (1988) reported that all three stocks of hooded seals have their pups at the same time;

this supports the theory of a single population. DNA fingerprinting (Sundt et al. 1994) and skull 

morphology (Wiig and Lie 1984) also supported a single hooded seal population.

Coltman et al. (2007) used 13 microsatellite loci and a portion of the mtDNA control region to 

assess hooded seal stock structure. They found no differentiation between the four breeding sites 

included: West Ice, the Gulf, the Front and Davis Strait.

2.34.6 Life History Traits

Kovacs (2009) summarized hooded seal life history traits. She reported that females reach 

sexual maturity at three years and males are a little bit older when they mature and are likely 

much older when they can actively compete for access to females. Hooded seals have the 

shortest lactation of any mammal, only four days (Bowen et al. 1985). Longevity is 25-35 years 

(Kovacs 2009). Hooded seals are sexually dimorphic; in other species this trait has resulted in 

females living longer than males but very little is known about hooded seal male survival 

(Hammill and Stenson 2006).

2.34.7 Food Habits 

Hooded seals are pelagic feeders (Kovacs 2009). In their study on the estimated prey taken by 

seals in Atlantic Canada, Hammill and Stenson (2000) found that Greenland halibut
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(Reinhardtius hippoglossoides) was the most common prey eaten by hooded seals. This was 

followed by Atlantic cod (Gadus morhua), redfish (Sebastes spp.), Arctic cod (Boregadus saida), 

Atlantic herring (Clupea herengus) and capelin (Mallotus villosus). Hauksson and Bogason 

(1997) reported that the main prey items of hooded seals in Icelandic waters were redfish and 

cod. 

Tucker et al. (2009) used quantitative fatty acid signature analysis (QFASA) to investigate harp 

and hooded seal food habits. Their study included samples from 153 harp seals collected 1994-

2004. They found that hooded seals fed primarily on amphipods, Atlantic argentine (Argentina 

silus), capelin, euphausiids, and redfish. 

2.34.8 Health

2.34.8.1 Strandings

A total of 83 hooded seals stranded along the U.S. Atlantic coast (Maine to North Carolina) from 

2005 to 2009 (Northeast and Southeast U.S. marine mammal stranding response databases). 

Nine of these animals showed signs of human interaction. Massachusetts had the highest 

number of observed strandings (n= 38, 46%), followed by Maine (n= 43, 20%). These two states 

account for 66% of all stranding observations. In their analysis of ice seal strandings, Harris and 

Gupta (2006) found that hooded seals tended to strand closer to deep water, farther north.

Table 2.34.1 Hooded Seal Strandings by State and Year 

State 2005 2006 2007 2008 2009 TOTAL

ME 3 12 2 0 0 17

NH 0 2 0 0 1 3

MA 11 18 3 4 2 38

NY 4 6 1 1 1 13

NJ 0 3 0 1 0 4

DE 0 1 0 0 0 1

MD 0 1 0 0 0 1

VA 1 2 0 0 0 3

NC 0 2 0 0 0 2

TOTAL 19 47 7 6 4 83

(Data from the NE and SE stranding network databases)

2.34.8.2 Contaminants

Vetter et al. (2010) analyzed brominated flame retardant (DPTE) in blubber and brain tissues of 

hooded seals from the Barents and Greenland Seas. In hooded seals from the eastern U.S. and 

Canada, Montie et al. (2010) documented brominated flame retardants (BFRs), including 

polybrominated diphenyl ethers (PBDEs) and current-use, non-PBDE BFRs, as well as 

organochlorine (OC) pesticides and polychlorinated biphenyls (PCBs).
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2.34.8.3 Disease

Duignan et al. (1997) analyzed hooded seal samples collected from the western Atlantic 1989-

1994 for PDV. Twenty-four percent of the seals they tested were positive for PDV antibodies. 

2.34.9 Acoustics 

Ballard and Kovacs (1995) studied the airborne and waterborne vocalization of hooded seals in 

the Gulf of St. Lawrence during the breeding season. They identified three major classes of 

sounds containing five call types. They found that sounds that were created using the hood and 

septum were different from voiced calls. They recorded underwater clicks and knocks. Most of 

the hooded seal acoustics were used in agonistic (79%) or sexual (12%) situations. 

2.34.10 Fisheries By-Catch and Entanglement 

Total annual estimated average fishery-related mortality for 2001-2005 is 25 hooded seals, all of 

which were attributed to the Northeast Sink Gillnet Fishery. There are no records of fishery 

interactions involving hooded seals in the Northeast Fisheries Observer database between 2005 

and 2009.

Table 2.34.2 Mean Annual Mortality by Fishery 2001-2005

Fishery (2001-2005) Mean Annual Mortality (CV)

Northeast Sink Gillnet 25 (0.82)

(Waring et al. 2011) (CV in parentheses)

2.34.11 Vessel Interactions 

There are records in the Northeast Stranding database of two hooded seals in 2006 with evidence 

of vessel interaction. 

2.34.12 Energy Projects 

Both extractive and renewable offshore energy projects have the potential to impact the marine 

environment in a variety of ways, including habitat alteration and the introduction of noise via 

seismic exploration activities (e.g., airguns), vessel/aircraft activity, construction and operation

(Geraci and St. Aubin 1980, Bain and Williams 2006, Thompsen et al. 2006, Cada et al. 2007, 

Compton 2008, Evans 2008, MMS 2008, Burgman 2010, Boehlert and Gill 2010, Dolman and 

Simmonds 2010, Edrén et al. 2010, Bush 2011, ICES 2011). The impact of these activities on 

marine mammals is unclear. 

The 2010 Report of the Working Group on Marine Mammal Ecology (ICES 2010) stated that 

very little is known about the impact of the construction and operation of offshore wind-farms. 

Madsen et al. (2006b) reviewed available current information on wind farm and marine 

mammals and wrote that the noise impact is more severe during construction than operation. 

The 2011 Report of the Working Group of Marine Mammal Ecology (ICES 2011) reported that 

there was no change in seal haul-out behavior in the vicinity of a tidal turbine and shore-based 

surveys showed no evidence of disturbance during construction. No information is available 

about the impact of energy projects on hooded seals.
157

2.34.13 Data Gaps and Research Recommendations 

The abundance estimate for hooded seals is very uncertain due to limited surveys, limited 

reproductive data and uncertain catch statistics. There is very little information available on 

contaminant burdens or disease. Male life history data is limited.

2.35 KEMP’S RIDLEY TURTLE (LEPIDOCHELYS KEMPII)

2.35.1 Legal Status 

The Kemp’s ridley sea turtle was listed as an endangered species under the ESA in 1970 and has 

received Federal protection throughout its range since that time. All commercial international 

trade in this species has been banned since 1975 when it was listed on Appendix I by the 

Convention on International Trade in Endangered Species of Wild Fauna and Flora (CITES). 

The IUCN lists the Kemp’s ridley as “Critically Endangered.”

2.35.2 General Distribution

Kemp’s ridleys are distributed along the coastlines of the Gulf of Mexico and the northwestern 

Atlantic Ocean, as far north as the Grand Banks and Nova Scotia (National Marine Fisheries 

Service et al. 2010). They have also been reported on rare occasions in the Mediterranean 

(Tomás and Raga 2007), in the Azores (Bolton and Martins 1990), and in the eastern north 

Atlantic (Brongersma 1972). Nesting is predominantly restricted to beaches of the western Gulf 

of Mexico, most notably at one beach near Rancho Nuevo, Tamaulipas, Mexico. From 1978 

through 1988 a total of 22,507 eggs were collected from Rancho Nuevo and incubated at South 

Padre Island, Texas in a successful experiment to establish a second nesting colony (Shaver and

Wibbels 2007). Along the U.S. Atlantic coast, isolated nesting events have been reported in 

Florida (Johnson et al. 1999), Georgia (Williams et al. 2006a), and North and South Carolina 

(Anonymous 1992; Bowen et al. 1994). These areas fall mostly within the BOEM South 

Atlantic and Straits of Florida Planning Areas. The range of Kemp’s ridley sea turtles is shown 

in Figure 2.35-1; nesting locations are shown in Figure 2.35-2. Tracks of satellite-tagged 

Kemp’s ridleys are shown in Figure 2.35-3; sightings and fishery bycatch observations are 

shown in Figure 2.35-4.

2.35.3 General Abundance 

Analysis of films of the nesting aggregations at Rancho Nuevo in 1947 have resulted in estimates 

of over 40,000 nesting females in the population at that time (Carr 1963; Hildebrand 1963). 

However, by 1985 the nest count reached its lowest level at 702 nests, representing a 

reproductive female population of fewer than 300 animals. Since the mid-1980s, nesting counts 

have increased by 14-16% each year (Heppell et al. 2005) and for the period 2005-2009 the 

number of nests on all monitored beaches indicate that approximately 5,500 females are nesting 

each season in the Gulf of Mexico (National Marine Fisheries Service et al. 2010). The 

population increase is likely due to a combination of management measures, including 

elimination of direct harvest, nest protection, the use of turtle excluder devices (TEDs), and 

reduced trawling effort in Mexico and the U.S. (National Marine Fisheries Service et al. 2010). 

The target criterion for downlisting Kemp’s ridleys turtles from endangered to threatened is at 
158

least 10,000 nesting females in a season, a target which could be reached at current survival rates 

by 2015 (Heppell et al. 2005). 

2.35.4 Habitat Preference 

Kemp’s ridley sea turtles use different habitats during different life stages. Terrestrial zones are 

used during oviposition and embryonic development. Figure 2.35-2 shows the distribution of 

Kemp’s ridley nesting beaches. Patterns of nesting density were shown to be consistent with 

areas where oceanographic conditions are favorable for migration of hatchlings to foraging areas 

(Putman et al. 2010). 

Hatchlings swim from the beach to the boundary current and float in the oceanic currents for the 

first two years of their lives. Some of the juveniles remain in the Gulf of Mexico and others are 

brought into the Atlantic on the Gulf Stream. The young turtles move into the nearshore waters 

of the Gulf of Mexico or the Atlantic coast from Florida to New England and spend the warmer 

months in shallow foraging areas, such as Pamlico Sound, North Carolina, Chesapeake Bay, 

Virginia, and Long Island Sound, New York (National Marine Fisheries Service et al. 2010). 

When water temperatures cool in the fall, the Kemp’s ridleys join other species of sea turtles and 

migrate southward (Morreale and Standora 2005). By early November turtles from the northern 

areas of the Atlantic coast join individuals leaving mid-Atlantic areas, such as the Chesapeake 

Bay and North Carolina inshore waters. Coastal Florida waters south of Cape Canaveral have 

been demonstrated to be important wintering habitat, but Kemp’s ridleys have also been shown 

to winter off North Carolina south of Cape Hatteras in eddies of the Gulf Stream (National 

Marine Fisheries Service et al. 2010). The northward migration begins again in the spring, and

turtles arrive in Virginia by May and New York and New England by June (National Marine 

Fisheries Service et al. 2010).

Adult Kemp’s ridleys are only occasionally found in the Atlantic. Their preferred habitat in the 

Gulf of Mexico is thought to be nearshore waters of 37 meters or less in the Gulf of Mexico 

(National Marine Fisheries Service et al. 2010; Shaver and Rubio 2008). 

Most tagging studies using Kemp’s ridley turtles have taken place in the Gulf of Mexico 

(Renaud and Williams 2005; Sasso and Witzell 2006; Schmid and Witzell 2006; Schmid 1998; 

Schmid et al. 2003, 2008, 2002; Seney and Landry 2008, 2010; Shaver and Rubio 2008; Shaver 

et al. 2005). However, Kemp’s ridleys have also been tagged and tracked in the Long Island 

Sound area (Morreale and Standora 1998), and elsewhere along the U.S. Atlantic coast. Of 69 

satellite tagged Kemp’s ridleys displayed on SeaTurtle.org (http://www.seaturtle.org/tracking/), 

seven are in the Atlantic and one that was tagged at South Padre Island, Texas travelled into the 

Straits of Florida Planning Area. There are data from two tagged and released Kemp’s ridley 

turtles in the Atlantic in the Ocean Biogeographic Information System (OBIS) dataset, one from 

2007 and one from 2008 (Figure 2.35-3; http://www.iobis.org/). Seven Kemp’s ridley turtles 

were tagged in Pamlico Sound, North Carolina, in 2002-2004 (McClellan et al. 2009). Gitschlag 

et al. (1996) tracked three Kemp’s ridley turtles with satellite and radio tags in 1991 along the 

Southeast Atlantic coast. Percent submergence time of these turtles was 94-95%. These turtles 

overwintered within approximately 40 km off the coast between Cape Canaveral and Stuart, 

Florida and in late spring and early summer spent time in coastal South Carolina. Three Kemp’s 
159

ridleys were included in Mansfield and Musick’s 2003 tagging study in Chesapeake Bay, 

Virginia (Mansfield and Musick 2004).

Kemp’s ridley sighting data in the OBIS dataset consists of six records from CETAP 1978-1980 

(four aerial and two opportunistic), one record from a SEFSC 1992 cetacean aerial survey, eight

records from a 1995 cetacean aerial survey, 16 records from SEFSC mid-Atlantic Tursiops 

surveys in 1995, 63 records from a NEFSC summer 1998 aerial survey, two 2 records from a 

NEFSC experimental aerial survey in 2002, 103 records from a UNCW marine mammal survey 

in 2002, five from UNCW marine mammal surveys 2006-2007, and 31 from UNCW right whale 

surveys 2005-2006. Kemp’s ridley turtles are found as far north as the North Atlantic Planning 

Area in summer, and in the other planning areas in other seasons. The sighting data presented 

here is not effort-corrected density data and should be used only as an indication of where 

Kemp’s ridleys have been seen and not a portrayal of their actual distribution. 

A habitat suitability index (HSI) model has been developed for the Kemp’s ridley sea 

turtle. A map of HIS model outputs by month is viewable at 

http://www.seaturtle.org/research/hsi.html. The model is based on assumptions of habitat 

preference of water depths less than 10 m and temperatures between 22°C and 32°C (Department 

of the Navy 2005). 

2.35.5 Stock Structure

There are no stock divisions within the Kemp’s ridley species. Dutton et al. (2006) compared 

mtDNA from Padre Island nesting turtles with that from animals from the Rancho Nuevo 

population and found genetic homogeneity. 

2.35.6 Life History Traits

Nesting occurs April-July, often in synchronized emergences called arribadas. Each season 

nesting females lay an average of 2.5 clutches of about 100 eggs each (TEWG [Turtle Expert 

Working Group] 2000). Adult females nest, on average, every two years. Genetic work by 

Kichler et al. (2002) has demonstrated multiple paternity of Kemp’s ridley clutches. Human 

protection of eggs by moving them to enclosed corrals has been implemented since 1978. 

Studies done on Rancho Nuevo nests left in situ have shown that while predator satiation is an 

effective natural survival strategy (LeBlanc et al. 2010), keeping eggs in restricted areas does 

enhance reproductive success (LeBlanc et al. 2008).

Threats to sea turtle nests include predation, pollution, construction, and other habitat 

modifications, such as beach nourishment, armoring, cleaning, vehicle driving, and erosion 

(National Marine Fisheries Service et al. 2010). Light pollution has been shown to cause 

disorientation of hatchlings (National Marine Fisheries Service et al. 2010). 

The sex determination of Kemp’s ridley sea turtles is temperature dependent (Wibbels 2007);

females are produced at warm temperatures and males at cooler temperatures. 

Endochrinological examination of captive Kemp’s ridleys has been performed to better 

understand seasonal reproductive cycles (Rostal et al. 1998). 
160

Growth and aging research on Kemp’s ridleys has been done by skeletochronological analysis 

(Avens and Hohn 2008; Snover and Hohn 2004; Snover et al. 2008; Zug et al. 1997) and markrecapture studies (Schmid 1998). Age at maturity is estimated to be approximately 12 years 

(Snover et al. 2008). 

2.35.7 Food Habits

Kemp’s ridley sea turtles in their oceanic juvenile stage subsist on the macro algae sargassum

and associated invertebrates. Stomach content analysis of several juvenile turtles that had 

stranded in Texas (Shaver 1991) supports this assumption. 

Once recruitment to the nearshore neritic zone takes place, the juvenile turtles’ diet shifts to 

mainly crabs (National Marine Fisheries Service et al. 2010), although the benthic tunicate 

(Molgula occidentalis) was found to be an important prey item in a 2005 study in the Ten 

Thousand Islands of southwest Florida (Witzell and Schmid 2005). A telemetric monitoring and 

GIS mapping study by Schmid et al. (2008) quantified habitat use by Kemp’s ridleys in the 

developmental habitat in the Ten Thousand Islands area. Live bottom areas (sessile invertebrates 

on hard substrate) were preferred. Analysis of stomach contents of stranded Kemp’s ridley in the 

Chesapeake Bay area showed dietary shifts from predominantly horseshoe crab (Limulus 

polyphemus) in the early to mid-1980s to blue crab (Callinectes sapidus) during the late 1980s 

and early 1990s, and then to menhaden (Brevoortia tyrannus) and croaker (Micropogonias 

undulatus) from the late 1990s to 2002. This suggests that population declines in crab 

populations may have led to turtles feeding on fish caught in nets or discarded (Seney and 

Musick 2008). Stomach content analysis by Morreale and Standora (1998) of juvenile Kemp’s 

ridleys in the New York Sound area showed that relative abundance of available crab species 

was not the primary factor governing prey selection and species composition in the gut samples 

seemed to reflect the more easily-captured crabs. Burke et al. (1993) reported that the mostly 

commonly-found crab in Kemp’s ridley diet in the Long Island area was the nine-spined spider 

crab (Libnia emarginata)

2.35.8 Health 

2.35.8.1 Strandings

When water temperatures fall below 8-10°C, Kemp’s ridleys are susceptible to becoming 

incapacitated in a natural phenomenon called cold stunning. This is common each year along the 

shores of Long Island Sound (Morreale et al. 1992) and Cape Cod Bay. From 1994 through 

2006, 1,084 immature Kemp’s ridleys were cold-stunned in the northeast U.S., with over half 

initially stranded alive. Some of the turtles were rehabilitated and released (National Marine 

Fisheries Service et al. 2010).

Hart et al. (2006) examined the spatial distribution of sea turtle strandings in North Carolina and 

concluded that strandings follow patterns that can be predicted from physical oceanography. 

The Southeast Fisheries Science Center hosts a queryable dataset on Atlantic and Gulf of Mexico 

sea turtle strandings at http://www.sefsc.noaa.gov/seaturtleSTSSN.jsp. Figures 2.35-4 and 2.35-

5 show density distributions of strandings along the Atlantic coast. Strandings are high in the 
161

North Atlantic Planning Area in winter and fall; in spring and summer strandings are more 

prevalent in the Mid and South Atlantic Planning Areas.

2.35.8.2 Contaminants

Lake et al. (1994) studied PCB, DDE, and transnonachlor concentrations in cold-stunned 

Kemp’s ridleys that had stranded in the Long Island Sound area between 1980 and 1989. While 

higher levels of PCBs were found in Kemp’s ridleys than were reported in other species of sea 

turtles, levels were more than 20 times lower than thresholds found to cause reproductive 

problems in freshwater turtles. More recently, Innis et al. (2008) examined cold-stunned juvenile 

Kemp’s ridleys that had stranded on Cape Cod between 2001 and 2006 and concluded that the 

turtles may be exposed to contaminants at a young age but that further investigation into sources 

of the contaminants and the effects on the health of the turtles is needed. Work by Keller et al. 

(2008) focused on PFC concentrations in loggerhead and Kemp’s ridley sea turtles and 

demonstrated positive correlations between length and latitude of capture, suggesting that bioaccumulation of these compounds may be influenced by age and trophic level. Kemp’s ridleys 

had significantly higher PFC concentrations than the loggerhead sea turtles tested (Keller et al. 

2008) and turtles captured in near shore waters of North Carolina had higher concentrations than 

those captured offshore from South Carolina to Florida (Keller et al. 2005). Work done by 

Swarthout et al. (2010) has helped to establish baseline organohalogen contaminant 

concentrations for Kemp’s ridleys and green turtles. Levels found in Kemp’s ridleys from the 

southeastern U.S. coast were similar to those found in Kemp’s ridleys from the Gulf of Mexico, 

although highly chlorinated PCBs were higher in Atlantic samples, indicating exposure to 

Aroclor 1268 (Swarthout et al. 2010).

2.35.8.3 Disease 

Pathological and parasitological examination was performed on cold-stunned Kemp’s ridleys 

that had stranded on Cape Cod between 2001 and 2006 (Innis et al. 2009). Necrotizing 

enterocolitis and bacterial or fungal pneumonia were the most frequently encountered lesions. 

While considered clinically significant, in many cases the lesions were not judged to have been 

the primary cause of death, suggesting that additional factors, such as hypothermia; drowning, 

and metabolic or respiratory problems, may be factors causing death in cold-stunned turtles.

2.35.9 Acoustics

Little has been done specifically on Kemp’s ridleys and acoustics, though studies on loggerhead 

sea turtles have demonstrated sensitivity to low frequency noise (Bartol et al. 1999; Samuel et al. 

2005). Underwater sound recordings from the Peconic Bay Estuary system in Long Island, New

York demonstrated high levels of anthropogenic noise at frequencies in the range of the turtles’ 

highest sensitivity that also overlapped spatially and temporally with high turtle use of the habitat 

(Samuel et al. 2005). Sea turtle exposure to seismic air gun noise was studied by Weir (2007), 

though no conclusions on the impacts to the turtles by the airguns were able to be drawn in that 

study. Viada et al. (2008) discussed sea turtle response to underwater explosions and mitigation 

scenarios developed for explosive removal of oil and gas structures. The authors concluded that,

while existing regulations provide more protection for marine turtles than had previously existed, 

little is known about sub-lethal effects of underwater explosions on turtles, especially potential 

auditory impacts (Viada et al. 2008). 
162

2.35.10 Fisheries By-Catch and Entanglement 

Bycatch of Kemp’s ridley sea turtles has been documented in several Atlantic fisheries, including 

mid-Atlantic gillnet (Murray 2009a), northeast bottom trawl, mid-Atlantic sea scallop dredge 

(Murray 2004a, 2004b), beach haul seine and pound nets (Epperley et al. 2007). Between 1998 

and 2009, 23 Kemp’s ridley interactions were reported in the NMFS fishery observer database. 

In addition, a dead Kemp’s ridley was observed in a Massachusetts fishing weir in 2007 

(National Marine Fisheries Service et al. 2010). Most of the observed fishery bycatch of Kemp’s 

ridley turtles has been in the BOEM Mid-Atlantic Planning Area.

McLellan et al. (2009) used telemetry to assess the potential for interactions between turtles and 

gillnet fisheries in the Pamlico Sound area of North Carolina. Snoddy et al. (2009) studied the 

blood biochemistry of Kemp’s ridley and green sea turtles incidentally captured in the coastal 

gillnet fishery of North Carolina and found that entanglement time, depth, and severity of 

entanglement had negative impacts on the selected blood markers associated with health status. 

2.35.11 Vessel Interactions 

Damage from collisions with boats and ships is commonly found in sea turtles. In the stranding 

data collected by the Sea Turtle Stranding and Salvage Network from 1997 to 2001, 12.7% of all 

stranded turtles were documented as having sustained injuries consistent with propeller wounds 

or collision, although some of these injuries may have occurred post-mortem (National Marine 

Fisheries Service et al. 2010).

2.35.12 Energy Projects

Both extractive and renewable offshore energy projects have the potential to impact the marine 

environment in a variety of ways, including habitat alteration and the introduction of noise via 

seismic exploration activities (e.g., airguns), vessel/aircraft activity, construction and operation

(Geraci and St. Aubin 1980, Bain and Williams 2006, Thompsen et al. 2006, Cada et al. 2007, 

Compton 2008, Evans 2008, MMS 2008, Burgman 2010, Boehlert and Gill 2010, Dolman and 

Simmonds 2010, Edrén et al. 2010, Bush 2011, ICES 2011). The impact of these activities on 

turtles is unclear. McMichael and Wyneken (2010) reported on a research program aimed at 

monitoring and minimizing the impacts from interactions between sea turtles and ocean energy 

technology within the Florida Current.

Entrainment in nuclear power plant intake canals has been a source of Kemp’s ridley morality 

along the U.S. Atlantic coast. Over 100 interactions with Kemp’s ridley turtles have been 

documented at nuclear power plants since 1976 in Florida, North Carolina, and New Jersey, 

although many of these were non-lethal (National Marine Fisheries Service et al. 2010). 

Effects of oil and oil spill response guidelines are presented in a report edited by Shigenaka 

(2003). The report concluded that not only do oil collection areas overlap with sensitive sea 

turtle habitat, but there is also strong, if limited and dated, information that indicates oil is 

harmful to turtles, particularly to dermal tissues and membranes. In addition, fresh oil has been 

found to harm sea turtle eggs. The relationship between offshore oil platforms and the 

distribution of sea turtles is discussed in a report made by Lohoefener et al. at the 1989 Ternary 

Studies meeting sponsored by the MMS (Lohoefener et al. 1989). That study found that in some 
163

areas of the Gulf of Mexico, chelonid sea turtles were positively correlated with platforms, and

in others there was either a negative correlation or no correlation at all. 

Under a plan developed by the U.S. Fish and Wildlife Service, NMFS, and the Florida Fish and 

Wildlife Conservation Commission, Kemp’s Ridley, loggerhead, and green sea turtle nests from 

areas of the Florida panhandle and Alabama affected by the Deepwater Horizon oil spill were 

relocated to the Atlantic coast of Florida (for more information see 

http://www.fws.gov/home/dhoilspill/pdfs/TurtleNestHatchProgram.pdf). 

2.35.13 Data Gaps and Research Recommendations 

Hays (2008) reviewed recent research on sea turtles, pointing out topical areas and some 

remaining questions, and Heenehan (2010) summarized work on acoustic impacts to sea turtles. 

There have been no recent systematic abundance surveys for Kemp’s ridley sea turtles, but the 

ongoing Atlantic Marine Assessment Program for Protected Species (AMAPPS) project is 

designed to address this shortfall. As stated in the draft recovery plan “Additional research and 

monitoring are needed to identify important marine foraging, breeding, and internesting habitats; 

determine migratory pathways among foraging grounds and between foraging grounds and 

nesting beaches; and collect data on interactions between Kemp’s ridleys and recreational and 

commercial fisheries” (National Marine Fisheries Service et al. 2010). The National Research 

Council’s Assessment of Sea-turtle Status and Trends (Committee on Sea Turtle Population 

Assessment Methods; National Research Council 2010) recommended that NMFS and the 

USFWS develop a coherent national strategy for sea-turtle assessments to improve collection, 

quality and availability of data and to develop a plan of external review of data and models used 

for population status estimation and trend analysis.

2.36 GREEN TURTLE (CHELONIA MYDAS)

2.36.1 Legal Status 

The green turtle was listed under the ESA on July 28, 1978. The breeding populations in Florida 

and Mexico’s Pacific coast are listed as endangered; elsewhere the species is listed as threatened. 

The IUCN lists green turtles as endangered globally, based on the 2004 global status assessment 

(Marine Turtle Specialist Group 2004) which discussed extensive subpopulation declines in the 

last three generations (generation length used for the Florida subpopulation was 35.5). 

International trade of green turtles is prohibited under CITES. Other international treaties and 

agreements protecting green turtles include the Memorandum of Understanding on the 

Conservation and Management of Marine Turtles and their Habitats of the Indian Ocean and 

South-East Asia (IOSEA) and the Memorandaum of Understanding Concerning Conservation 

Measures for Marine Turtles of the Atlantic Coast of Africa under the CMS, Annex II of the 

Specially Protected Areas and Wildlife (SPAW) Protocol of the Cartagena Convention, and the 

Inter-American Convention for the Protection and Conservation of Sea Turtles (IAC). Green 

turtles are also protected by the Memorandum of Understanding on ASEAN Sea Turtle 

Conservation and Protection and the Memorandum of Agreement on the Turtle Islands Heritage 

Protected Area (TIHPA).
164

2.36.2 General Distribution 

Green turtles are found in tropical and subtropical water circumglobally. This highly migratory 

species inhabits the coastal waters of over 140 countries, and nesting occurrs in more than 80 

countries. In the Atlantic U.S. there is a regionally significant nesting aggregation in Florida (the 

second largest colony in the western hemisphere). Green turtles also nest in small numbers in 

the U.S. Virgin Islands, Puerto Rico, Georgia, South Carolina, and North Carolina (see Table 

2.36.3-1). The BOEM South Atlantic and Straits of Florida Planning Areas are the primary 

BOEM areas with nesting green turtles. The range of green sea turtles is shown in Figure 2.36-1 

and nesting locations are shown in Figure 2.36-2. Tracks of satellite-tagged green turtles are 

shown in Figure 2.36-3; sightings and fishery bycatch observations are shown in Figure 2.36-4.

2.36.3 General Abundance 

The 2004 IUCN Red List assessment of world green turtle populations evaluated nesting trends 

at 32 index sites, each presumed to be genetically distinct (Marine Turtle Specialist Group 2004). 

The Florida index site was shown to have an increasing population between 1980 and 2001.

Nesting continued to rise between 2001 and 2005 (Meylan et al. 2006; National Marine Fisheries 

Service and U.S. Fish and Wildlife Service 2007b). Chaloupka et al. (2008) estimated that rates 

of green turtle nesting populations at six of the world’s major rookeries increased 4-14% per year 

between 1980 and 2005. Highest population growth rates were found at the Archie Carr 

National Wildlife Refuge in Florida (Chaloupka et al. 2008). Table 2.36.3-1 shows U.S. nest 

counts from 2001 through 2010. 

Table 2.36.3 Green Turtle Nest Counts

Florida Georgia S. Carolina N. Carolina

2001 581 - 1 -

2002 9,201 - 0 -

2003 2,262 - 1 -

2004 3,577 - 1 -

2005 9,644 - 0 -

2006 4,970 - 1 -

2007 12,751 - 1 -

2008 9,228 - 1 0

2009 4,462 0 1 3

2010 13,151 6 6 18

Data from

http://research.myfwc.com/images/articles/2496/green_turtle_nesting_data__2005-2009.pdf, 

http://myfwc.com/research/wildlife/sea-turtles/nesting/statewide/ , 

http://www.seaturtle.org/nestdb/index.shtml, North Carolina Wildlife Resources Commission Sea 

Turtle Nest Monitoring System, South Carolina Department of Natural Resources Sea Turtle Nest 

Monitoring System, Georgia Department of Natural Resources Sea Turtle Nest Monitoring System, 

and National Marine Fisheries Service and U.S. Fish and Wildlife Service

The large inter-annual variation in nesting numbers has been attributed to synchrony in the 

intervals between nesting years of individuals, and hypothesized to be attributable to 
165

environmental variations that affect the feeding conditions at sea (Broderick et al. 2001). Solow 

et al. (2002) showed that sea surface temperature did have a significant effect on the re-migration 

interval in the largest Atlantic population of green turtles. 

Bjorndal et al. (2005) generated annual abundance estimates of juvenile green turtles at two 

foraging grounds in the Bahamas, based on long-term capture-mark-recapture (CMR) studies. 

At one of the sites, abundance showed little variation over time, while at the other there were 

successive phases of increase, decrease, and stability, resulting from changes in immigration. 

These trends did not conform to the general increasing trend of the nesting population at 

Tortuguero, Costa Rica, and points out the difficulties in assessing population-wide trends in 

green turtles and other long-lived marine species. 

In a 2000 paper, Bjorndal et al. determined that for green turtles on a feeding ground in the 

Bahamas, mean annual growth rate and condition index were inversely correlated with 

population density pointing to density dependent nutrient limitation (Bjorndal et al. 2000a). They 

estimated the carrying capacity of pastures of the seagrass Thalassia testudium, the major diet 

plant of the green turtle, to be in the range of 122 to 4439 kg green turtles/ha.

Chaloupka et al. (2002) developed a stochastic simulation model to provide better insight into 

the population dynamics of the southern Great Barrier Reef (sGBR) green sea turtle stock. 

Fertility and adult survival were the most important high level parameters affecting population 

growth. A model developed to describe Hawaiian green turtle population dynamics was 

presented by Chaloupka and Balazs (2007). Mazaris et al. (2006) developed an individual-based 

model to analyze the variability of extinction probabilities as a result of mortality factors at 

different life stages of a sea turtle population. The results of their analysis showed that the 

pelagic stage has a significant effect on population persistence. Increased survival of the first 

year cohort was also shown to be beneficial for the population.

2.36.4 Habitat Preference 

Green turtles occupy three different habitat types, depending on life stage. Nesting takes place 

on high-energy oceanic beaches, hatchlings go through a pelagic period in open ocean 

convergence zones, and when juveniles reach a carapace length of approximately 20-25 cm they 

move into benthic feeding grounds (National Marine Fisheries Service and U.S. Fish and 

Wildlife Service 1991). 

As with other marine turtles, hatching success and sex determination are influenced by nesting 

beach temperatures. As a result, global climate change poses a threat to these species. 

Temperatures at green turtle nesting sites on the Great Barrier Reef of Australia were modeled 

by Fuentes et al. (2009), who found that, under an extreme scenario of climate change,

hatchlings would be all female by 2070, although other nesting grounds would still produce 

males under the same scenario. While loggerhead turtles seem to be adjusting the seasonality of 

their nesting in response to warming temperatures (Pike et al. 2006; Weishampel et al. 2004), 

green turtle nesting patterns studied at the Canaveral National Seashore, Florida, were unrelated 

to environmental temperatures (Pike 2009).
166

Time-depth recorders mounted on adult and immature green turtles in Moreton Bay, Australia, 

recorded the turtles’ preferences for shallow water habitats (Hazel et al. 2009). The turtles 

studied spent 80% of their time at depths of 3 meters or less. Time-depth recordings of green 

turtles in the Cayman Islands also showed use of the shallow lagoon waters, but, in addition, 

recorded turtle excursions into the less-protected reef areas where deeper dives occurred 

(Blumenthal et al. 2010).

Work by Makowski et al. (2005) showed that juvenile green turtles occupy stable home ranges 

along the nearshore worm-rock reefs of southeast Florida, during the summer and fall.

Brooks et al. (2009) correlated turtle movements and tides in a feeding area on the Pacific coast 

of Baja California. They found turtles to be transported on continual tides, allowing them to 

exploit the patchy and seasonal distribution of the algae which forms their main diet component. 

Sharks are a primary marine predator of adult and juvenile sea turtles. Heithaus et al. (2002)

examined frequencies of shark-inflicted damage to green turtle and loggerhead turtles in Shark 

Bay, Western Australia. Green turtles were found in tiger shark habitats more frequently than 

were loggerheads, yet they exhibited less evidence of shark-inflicted injuries, and no sex 

difference in injury frequency. 

In a summary of satellite-tracking studies of sea turtles by Godley et al. (2008), green turtles are 

one of the most studied species of marine turtle; tagging research helps to elucidate such issues 

as oceanic migrations, fidelity to foraging sites, and dive behavior. However, the U.S. Atlantic 

coast is absent from the list. Telemetry data in OBIS for the Atlantic region consists of data 

from 14 green turtles tagged by the Duke University Marine Lab (5 in 2003, 1 in 2005, 7 in 2006 

and 1 in 2007), two rehabilitated turtles released by the Virginia Stranding Response Program (1 

in 2007 and 1 in 2009), and one rehabilitated turtle released by the Cape Cod Sea Turtle Release 

Program. 

Green turtle sighting data in the OBIS dataset consists of 7 records from CETAP (3 in 1972 and 

4 in 1980), three records from SEAMAP South Atlantic, one record from a SEFSC 1992 

cetacean aerial survey, 8 records from a 1995 cetacean aerial survey in 1991, 1992 and 1993, 8 

records from SEFSC surveys in 1992, 5 from a SEFSC survey in 1995, and one from a SEFSC 

survey in 1999, 4 records from a NEFSC summer 2004 aerial survey, one record from a UNCW 

right whale aerial survey in 2006, and 15 records from the Bahamas Marine Mammal Research 

Organization between 1992 and 2005. While this evidence is sparse, it does show that green 

turtles are found as far north as BOEM’s North Atlantic Planning Area in summer, and in the 

other planning areas in other seasons. The sighting data presented here is not effort-corrected 

density data and should be used only as an indication of where green turtles have been seen and 

not a portrayal of their full distribution. 

2.36.5 Stock Structure 

Bass and Witzell (2000) analyzed mtDNA markers in the juvenile green turtle population at 

Hutchinson Island, Florida, to determine the nesting origin. The composition of the population 

was determined to be 53% from Costa Rica nesting grounds, 42% from the U.S. and Mexico and 

4% from Venezuela and Surinam (Bass and Witzell 2000). In a 2006 paper, Bass et al. presented 
167

a similar analysis of a North Carolina foraging aggregation of green turtles, indicating that 54% 

of the animals originated from the east coast of the U.S. and 27% originated in Mexico (Bass et 

al. 2006). They found significant nesting aggregation genetic structure, as well as regional 

population structure between northern and southern foraging aggregations in the Caribbean. 

Genetic diversity was highest at foraging aggregations in confluences of major current systems, 

suggesting that both currents and behavior influence the composition of these groups. Juvenile 

homing to regional foraging grounds was also shown.

2.36.6 Life History Traits 

A skeletochronological analysis of juvenile green turtles in the developmental habitat of Indian 

River Lagoon, Florida, yielded age estimates for that population of 3-14 years (Zug and Glor 

1998). Growth rate estimates ranged from 30-53 mm/year. This suggests that in the western 

Atlantic, green turtles leave the pelagic stage at 5 or 6 years of age, and spend 6 or more years in 

the developmental neritic zone (Zug and Glor 1998). Goshe (2009), also using 

skeletochronological techniques, estimated age at maturation to be 44 years for green turtles of 

the Florida population and 42.5 years for the Costa Rican population. 

2.36.7 Food Habits 

Green turtles are largely herbivorous in their benthic juvenile and adult stages, subsisting mainly 

on seagrass and macroalgae. In the Hawaiian Islands, green turtles have shifted dietary 

preferences to include non-native invasive algae species (Russell and Balazs 2009). In a study of 

juvenile green turtles in Florida, Gilbert et al. (2008) found that the turtles selectively foraged on 

chlorophytic and rhodophytic algae. Juvenile green turtles off Brevard County, Florida, were 

studied by Holloway-Adkins (2006), who found that in that shallow, high-energy environment, 

the turtles were primarily feeding on red algae. Hatase et al. (2006) used satellite telemetry and 

stable isotope analysis to determine that oceanic habitats were alternative feeding areas for adult 

post-nesting green turtle females off Japan. Parker and Balazs (2008) studied stomach contents 

of eleven oceanic-stage green turtles in the North Pacific. Results showed that these turtles were 

omnivorous, concentrating on prey items at or near the surface–mainly coelenterates and 

associated amphipods. Boyle and Limpus (2008) examined stomach contents of post-hatchling 

loggerhead and green turtles in the southwest Pacific and found similar results–the turtles at that 

stage were opportunistic feeders, consuming zooplankton and other floating prey, and that small 

oceanic green and loggerhead turtles had very similar diets. Stable isotope analysis of oceanic 

stage green turtles around the Azores revealed that these turtles were spending 3-5 years as 

carnivores before settling into the herbivorous benthic phase (Reich et al. 2007).

2.36.8 Health 

2.36.8.1 Strandings 

The Southeast Fisheries Science Center hosts a queryable dataset on Atlantic and Gulf of Mexico 

sea turtle strandings at http://www.sefsc.noaa.gov/seaturtleSTSSN.jsp. Figures 2.36-5 and 2.36-

6 show density distributions of strandings along the Atlantic coast. Strandings are observed in all 

planning areas in the fall, but are limited to the Mid-Atlantic, South Atlantic and Straits of 

Florida Planning Areas in other seasons. 
168

2.36.8.2 Contaminants

The use of blood samples to estimate green turtle tissue contamination by persistent organic 

pollutants (POPs) and heavy metals was demonstrated to be effective by van der Merwe et al. 

(2010b). Gas chromatography with tandem mass spectrometry was also proven effective at 

analyzing contaminants in green turtle eggs, blood, and tissue (van de Merwe et al. 2009). Van 

der Merwe et al. (2010a) looked at maternal transfer of persistent organic pollutants in green 

turtles in Malaysia and the effects of POPs on embryonic development. They found evidence of 

maternal transfer, as well as a significant inverse relationship between POP levels in eggs and 

mass/length ratios in hatchlings. Work done by Swarthout et al. (2010) has helped to establish 

baseline organohalogen contaminant concentrations for Kemp’s ridleys and green turtles. PCBs, 

DDTs and chlordanes were one order of magnitude lower in green turtles then in the Kemp’s 

ridley turtles examined, and PBDE concentrations were lower by half due to trophic level 

differences. Decreasing lipid contaminant burdens with turtle size were observed in green turtles 

by Mckenzie et al. (1999), which the authors postulated is attributable to a change in diet with 

age. Pattern differences between loggerhead and green turtles, elucidated by principal component 

analysis, confirmed bioaccumulation differences (McKenzie et al. 1999).

2.36.8.3 Disease 

The tumor disease fibropapillomatosis (FP), while prevalent in all hard-shelled turtles, is most 

frequent in green turtles. Hirama and Ehrhart (2007) compared occurrence rates and severity of 

FP in green turtles from three sites on the Florida Atlantic coast: Indian River Lagoon, the 

nearshore reef, and the Trident Submarine Basin. FP prevalence was highest in the Lagoon 

system. McGarrity (2008) examined stress protein expression in both healthy and fibropapilloma 

afflicted green and loggerhead turtles from Indian River Lagoon and compared levels to those 

from turtles from more pristine offshore reef environments. The stability in the marine 

environment of the herpesvirus associated with FP, as well as several other green turtle diseases,

including lung-eye-trachea disease and gray patch disease, was studied by Curry et al. (2000). 

They found that the virus remains infectious for extended periods of time in sea water. Herbst 

and Klein (1995) looked at the role of environmental contaminants in green turtle FP infection, 

and argued that, while occurrence seems to be higher in areas with high anthropogenic impact, 

there may be other factors, such as the prevalence of other stressors, density dependent 

relationships, or habitat favorability, that may be contributing to the rates of infection in these 

areas. However, Foley et al. (2005) in an examination of stranded turtles in southern Florida, 

demonstrate that FP was most prevalent in the area with the greatest degree of marine habitat 

degradation and pollution, largest extent of shallow-water area, and lowest wave-energy level; 

they also point out that a high prevalence of FP did not correspond to a high density of green 

turtles.

A high rate of infection by spirorchiid trematodes was found in Florida stranded green and 

loggerhead turtles, and in some cases caused or contributed to death. (Stacy et al. 2010). 

2.36.9 Acoustics 

Ridgway et al. (1969) measured the cochlear potentials in three specimens of the green sea turtle 

in response to both aerial and mechanical stimulation, demonstrating maximum sensitivity in the 

region of 300 to 400 Hz. They detected a rapid decline in sensitivity for lower and especially for 
169

higher tones. The upper limit for the observation of cochlear potentials without injury was 2000 

Hz. Yudhana et al. (2010) studied Auditory Brainstem Responses of green turtles in Malaysia 

and also found maximum sensitivity levels at 300 Hz. Sea turtle exposure to seismic air gun 

noise was studied by Weir (2007), though no conclusions on the impacts to the turtles by the 

airguns were able to be drawn in that study. Viada et al. (2008) discussed sea turtle response to 

underwater explosions and mitigation scenarios developed for explosive removal of oil and gas 

structures. The authors concluded that while existing regulations provide more protection for 

marine turtles than had previously existed, little is known about sub-lethal effects of underwater 

explosions on turtles, especially potential auditory impacts (Viada et al. 2008). 

2.36.10 Fisheries By-catch and Entanglement 

A satellite-tracking study by McClellan and Read (2009) examined the fine-scale movements of 

juvenile green turtles in Pamlico Sound, North Carolina. The study showed that turtles and gill 

net fishers had similar habitat preferences, which resulted in a high potential for interaction and 

entanglement. Turtles in Pamlico Sound established summer foraging sites in seagrass habitat 

and demonstrated strong site-fidelity. Fisheries observers have also documented high interaction 

rates between green turtles and large mesh sink gillnet gear (Murray 2009; Byrd et al. 2011) and 

pound nets (Epperly et al. 2007) in North Carolina waters.

2.36.11 Vessel Interactions 

Damage from collisions with from boats and ships is commonly found in sea turtles. In the 

stranding data collected by the Sea Turtle Stranding and Salvage Network from 1997 to 2001, 

12.7% of all stranded turtles were documented as having sustained injuries consistent with 

propeller wounds or collision, although some of these injuries may have occurred post-mortem 

(National Marine Fisheries Service et al. 2010). The correlation between internesting loggerhead 

and green turtle dive behavior at Casey Key, Florida, and boat traffic in the area was assessed by 

Sobin and Tucker (2010) to determine if there were periods of increased surface activity that put 

turtles at greater risk for boat strike injury. The proportion of green turtles that fled to avoid an 

oncoming vessel was found to decrease as the vessel speed increased and turtles that fled from 

faster approaching vessels did so at significantly shorter distances (Hazel et al. 2007). 

2.36.12 Energy Projects 

Both extractive and renewable offshore energy projects have the potential to impact the marine 

environment in a variety of ways, including habitat alteration and the introduction of noise via 

seismic exploration activities (e.g., airguns), vessel/aircraft activity, construction and operation

(Geraci and St. Aubin 1980, Bain and Williams 2006, Thompsen et al. 2006, Cada et al. 2007, 

Compton 2008, Evans 2008, MMS 2008, Burgman 2010, Boehlert and Gill 2010, Dolman and 

Simmonds 2010, Edrén et al. 2010, Bush 2011, ICES 2011). The impact of these activities on 

turtles is unclear. McMichael and Wyneken (2010) reported on a research program aimed at 

monitoring and minimizing the impacts from interactions between sea turtles and ocean energy 

technology within the Florida Current.

Effects of oil and oil spill response guidelines are presented in a report edited by Shigenaka 

(2003). The report concluded that not only do oil collection areas overlap with sensitive sea 

turtle habitat, but there is also strong, if limited and dated, information that indicates oil is 

harmful to turtles, particularly to dermal tissues and membranes. In addition, fresh oil has been 
170

found to harm sea turtle eggs. The relationship between offshore oil platforms and the 

distribution of sea turtles is discussed in a report made by Lohoefener et al. at the 1989 Ternary 

Studies meeting sponsored by the MMS (Lohoefener et al. 1989). That study found that in some 

areas of the Gulf of Mexico, chelonid sea turtles were positively correlated with platforms, while 

in others there was either a negative correlation or no correlation at all. High amplitude 

simulated pile driving vibrations were found to decrease sea turtle hatching success (Ripcke 

2011).

Under a plan developed by the U.S. Fish and Wildlife Servece, NMFS, and the Florida Fish and 

Wildlife Conservation Commission, Kemp’s Ridley, loggerhead, and green sea turtle nests from 

areas of the Florida panhandle and Alabama affected by the Deepwater Horizon oil spill were 

relocated to the Atlantic coast of Florida (see 

http://www.fws.gov/home/dhoilspill/pdfs/TurtleNestHatchProgram.pdf). 

2.36.13 Data Gaps and Research Recommendations 

Hays (2008) reviewed recent research on sea turtles, pointing out topical areas and some 

remaining questions, and Heenehan (2010) summarized work on acoustic impacts to sea turtles. 

There have been no recent systematic abundance surveys for green sea turtles but the ongoing 

AMAPPS project is designed to address this shortfall. Data on fisheries interactions with green 

turtles in the western Atlantic is sparse, as is work on the contaminant burdens of western 

Atlantic green turtles. More information on the abundance and dispersion of the oceanic phase 

juveniles would help improve understanding of the U.S. Atlantic population. 

2.37 HAWKSBILL TURTLE (ERETMOCHELYS IMBRICATA)

2.37.1 Legal Status 

The hawksbill sea turtle was listed as an endangered species in 1970. Coastal waters 

surrounding Mona and Monito Islands, Puerto Rico, were designated as critical habitat for 

hawksbill turtles by NMFS in 1998. All commercial international trade in this species has been 

banned since it was listed on Appendix I by the Convention on International Trade in 

Endangered Species of Wild Fauna and Flora (CITES) in 1975. The IUCN lists the hawksbill as 

“Critically Endangered.”

2.37.2 General Distribution

Hawksbill turtles are circumtropical, found in the Atlantic, Pacific, and Indian Oceans and 

associated water bodies between 30°N and 30°S. Hawksbills are widely distributed throughout 

the Caribbean Sea and western Atlantic Ocean, regularly occurring in southern Florida and the 

Gulf of Mexico, in the Greater and Lesser Antilles, and along the Central American mainland 

south to Brazil. On the Atlantic coast of the U.S., the species is recorded as far north as 

Massachusetts, but sightings north of Florida are rare (NMFS Office of Protected Resources n.d.

http://www.nmfs.noaa.gov/pr/species/turtles/hawksbill.htm). In Florida, hawksbills are regularly 

seen in the waters near the Florida Keys and on the reefs off Palm Beach County (U.S. Fish and 

Wildlife Service 1999). Nesting along the Atlantic coast is rare, and is restricted to the southeast 

coast of Florida and the Florida Keys (NMFS Office of Protected Resources n.d.

http://www.nmfs.noaa.gov/pr/species/turtles/hawksbill.htm), thus primarily in the BOEM Straits 
171

of Florida Planning Area. From 1979 to 1992, 11 nests were reported in the state of Florida 

(U.S. Fish and Wildlife Service 1999). The range of hawksbill sea turtles is shown in Figure 

2.37-1 and nesting locations are shown in Figure 2.37-2. Tracks of satellite-tagged hawksbills 

are shown in Figure 2.37-3; sightings and fishery bycatch observations are shown in Figure 2.37-

4.

2.37.3 General Abundance 

Globally, most populations of hawksbill turtles are declining, depleted, or are remnants of larger 

populations (Meylan and Donnelly 1999). There are only five regional populations with more 

than 1,000 females nesting annually (Meylan and Donnelly 1999). In the Caribbean, hawksbill 

populations are reported to be declining or depleted in 22 of the 26 geopolitical units reviewed 

by Meylan (1999). The number of females nesting annually in the region was estimated to be 

5000. The only increasing populations were those of Mexico and Mona Island, Puerto Rico. 

However, recent monitoring of populations on Guadeloupe, French West Indies (Kamel and 

Delcroix 2009), Barbados, West Indies (Beggs et al. 2007), Antigua, West Indies (Richardson et 

al. 2006), and Panama (Ordonez et al. 2008) show encouraging increases. McClenachan et al. 

(2008) used historical sources to calculate that 20% of historic nesting sites in the Caribbean 

have been lost entirely and 50% of the remaining nesting sites have been reduced to dangerously 

low populations.

2.37.4 Habitat Preference

Hawksbills nest on insular and mainland beaches of tropical and subtropical oceans of the world, 

exhibiting a wide tolerance for nesting substrate type (US Fish and Wildlife Service 1999). In the 

Jumby Bay, Antigua nesting aggregation in the West Indies, hawksbills tend to nest in vegetation 

(Ballentine et al. 2008). Caribbean region hawksbill hatchlings go through a pelagic period in 

open ocean convergence zones, and when juveniles reach a carapace length of approximately 20-

25 cm, they move into benthic feeding grounds (National Marine Fisheries Service and U.S. Fish 

and Wildlife Service 2007a; U.S. Fish and Wildlife Service 1999). 

As juveniles, subadults, and adults, hawksbill turtles are closely associated with coral reef and 

other hard-bottom habitats. Seagrass pastures, mangroves, algal beds, and mudflats can be 

peripheral habitats (Mortimer and Donnelly 2008). Addressing the concern that dwindling 

healthy coral reef resources may have profound effects on the viability of hawksbill populations, 

Bjorndal and Bolten (2009) used data from a 30-year mark-recapture study of hawksbills and 

green turtles in the southern Bahamas to assess the quality of a seagrass habitat for hawksbills; 

they determined that the seagrass pastures can support healthy, productive hawksbill 

aggregations. 

Some individuals exhibit strong fidelity to certain foraging localities, but others will migrate 

extensively (National Marine Fisheries Service and U.S. Fish and Wildlife Service 2007a). 

Strong site-fidelity and close association with both natural and artificial coral reef structures was 

observed in a tagging and mark-recapture study carried out in Palm Beach County, Florida 

(Wood and Meylan 2008). A mark-recapture study undertaken at Mona and Monito Islands, 

Puerto Rico, demonstrated limited home-ranges for hawksbill turtles in that area; turtles 

maintained residency for at least several years (van Dam and Diez 1998). Flipper tag returns, 

satellite telemetry, and genetics were analyzed in Tortuguero, Costa Rica, to determine 
172

movements and habitat use (Troëng et al. 2005). Starbird (1993) used radio and ultra-sonic 

telemetry to track seven hawksbill turtles around Buck Island, St. Croix, Virgin Islands. 

Between nesting events in the season, most of the turtles maintained residency within 3 km of 

Buck Island, in water depths between 9 and 20 m. The mean dive duration was 56.2 minutes and 

mean surface time was 1.6 minutes. Three of the turtles left the St. Croix region immediately 

following their last nesting event. In another study at Buck Island, Storch et al. (2005) found an 

increase in dive duration with decreasing water temperatures in winter. Blumenthal et al. 

(2009c) deployed time depth recorders and ultrasonic tags on 21 hawksbills in the Cayman 

Islands. Pronounced patterns of diurnal activity and nocturnal resting were found. The mean 

diurnal dive depth (±SD) was 8±5 m, range was 2–20 m, mean nocturnal dive depth was 5±5 m, 

range 1-14 m, and maximum diurnal dive depth was 43±27 m, range 7-91 m. Maximum diurnal 

dive depth was significantly correlated with body mass, suggesting partitioning of vertical 

habitat by size. Direct in-water observations were made of hawksbills at D’Arros Island in the 

Seychelles (von Brandis et al. 2010). Mean dive depth and duration were found to be 8.2 m and 

27.4 minutes, respectively. Surfacing intervals lasted on average 81.5 seconds and the mean 

number of breaths was 6.6 per surface interval. As in the Caymans, longer dives were correlated 

with larger body size.

Harewood and Horrocks (2008) examined impacts of coastal development on survival and 

swimming success for hatchling hawksbill turtles in Barbados. Predation rates were not 

significantly affected by offshore substrate type or beachfront lighting. However, a smaller 

percentage of the hatchlings leaving beaches that were lit with artificial lighting were able to 

swim the prescribed distance seawards during the observation period. It was postulated that 

artificial light may override the effects of wave cues in the low wave energy conditions 

characteristic of leeward Caribbean beaches, causing misorientation in the hatchlings. Kamel 

and Mrosovsky (2006), in examination of the thermal profile of a relatively pristine hawksbill 

nesting beach in Guadeloupe, French West Indies, found that temperatures in the forested areas 

were significantly cooler than temperatures in the more open, deforested areas. Because beach 

temperatures affect sex ratios of sea turtles, coastal forests are important male producing areas 

for the hawksbill sea turtle, and human alteration of this habitat could have important population 

consequences. 

The only record of a hawksbill sighting, on NEFSC or SEFSC surveys or in the OBIS dataset, in 

the BOEM planning areas was in August of 1995 off of the Chesapeake Bay in the mid-Atlantic 

BOEM planning area.

2.37.5 Stock Structure 

Bass et al. (1996) found that mtDNA lineages were highly structured among western Atlantic 

nesting colonies, with at least 6 female breeding stocks in the Caribbean and western Atlantic. 

This supported a natal homing model for recruitment of breeding females. Blumenthal et al. 

(2009a) performed mixed-stock analysis on samples collected from 92 neritic juvenile 

hawksbills in the Cayman Islands and found a diverse mixed stock with recruitment on a scale of 

200-2500 km. A significant correlation was found between genetic profiles of foraging 

aggregations and oceanic drift models. Bowen et al. (2007a) compiled previously published and 

new mtDNA haplotype data for 10 nesting colonies in the western Atlantic and compared the 

profiles to those from feeding populations. Nesting colonies differed significantly in mtDNA 
173

haplotype, supporting theories of nesting site fidelity. Feeding aggregations showed lower but 

significant structure, indicating that foraging populations are not homogenous across the 

Caribbean Sea. The influence of proximity on recruitment to feeding areas was also 

demonstrated. LeRoux and Dutton (2008) revised population sub-structuring from earlier mixed 

stock analysis by amplifying mtDNA haplotypes from the St. Croix and Costa Rican nesting 

populations. Browne et al. (2008) performed an mtDNA d-loop analysis of the hawksbill at 

rookeries and foraging areas in Grenada and the southern Grenadine Islands, and found

recruitment to foraging sites from various regional rookeries, some as far as Mexico.

2.37.6 Life History Traits 

The nesting season of the hawksbill is six months long; the peak season in the Caribbean is

between July and October. Nesting is principally nocturnal. Hawksbills nest an average of 4.5 

times per season at intervals of approximately 14 days. In Florida and the U.S. Caribbean, clutch 

size is approximately 140 eggs, and several records exist of over 200 eggs per nest (U.S. Fish 

and Wildlife Service 1999). Carapace length growth data obtained from 197 hawksbill turtles 

which had been marked and recaptured from 1992 to 2000 at feeding grounds of Mona and 

Monito Islands, Puerto Rico (Diez and van Dam 2002), ranged from –0.59 to 9.08 cm/yr. 

Growth rates measured at the Breakers Reef, in Palm Beach, Florida have averaged 2.5 cm/year 

(Wood, n.d. http://www.floridahawksbills.com/Site/What_Weve_Learned.html). Sex ratios in 

this Palm Beach population showed a significant female bias (2.37:1) (Blanvillain et al. 2007). 

Age-to-maturity has been estimated at 20 or more years in the Caribbean (National Marine 

Fisheries Service and U.S. Fish and Wildlife Service 2007a). Hawksbill hatchlings have been 

shown to be less active than other species of marine turtles (Chung et al. 2009a, 2009b). Chung 

et al. (2009b) hypothesized that the smaller and slower hatchlings of this species avoid predators 

by hiding in flotsam.

2.37.7 Food Habits 

Eggs of pelagic fish, Sargassum, and floating debris, such as tar droplets, styrofoam, and plastic,

were identified in the stomach contents of posthatchling hawksbills in the pelagic environment 

(Meylan 1984b).

Juvenile and adult hawksbill turtles feed primarily on sponges. Leon and Bjorndal (2002)

compared prey species ingested by hawksbill turtles with their availability at two sites in the 

Southwest Dominican Republic. Six benthic species were found in the hawksbill diet: 5 

demosponges (Chondrilla nucula, Geodia neptuni, Myriastra kalitetilla, Spirastrella coccinea, 

and Tethya crypta) and one corallimorpharian (Ricordea florida). Diet choice was found to be 

based on a combination of selectivity for certain species and local abundance. The dominance of 

R. florida in the diet challenged the view that Caribbean hawksbills are strict spongivores (see,

for example, Meylan 1988). Underwater photography taken at a Cayman Island foraging ground 

has shown that hawksbills forage occasionally on jellyfish, as well as on sponges (Blumenthal et 

al. 2009b). Observations have been made of hawksbill turtles feeding on the bubble coral 

Physogyra lichtensteinii in the Indian Ocean (Obura et al. 2010). However, the hawksbill’s 

dependence on sponges as its principal prey, and its dependence on filter feeding, hard-bottom 

communities, make it vulnerable to deteriorating conditions on coral reefs (U.S. Fish and 

Wildlife Service 1999).
174

2.37.8 Health 

2.37.8.1 Strandings 

Hart et al. (2006) examined the spatial distribution of sea turtle strandings in North Carolina and 

concluded that strandings follow patterns that can be predicted from physical oceanography. 

The Southeast Fisheries Science Center hosts a queryable dataset on Atlantic and Gulf of Mexico 

sea turtle strandings at http://www.sefsc.noaa.gov/seaturtleSTSSN.jsp. Figures 2.37-4 and 2.37-

5 show density distributions of strandings along the Atlantic coast.

2.37.8.2 Contaminants

In Japan, hawksbills were shown to accumulate arsenic at rates higher than green turtles (Agusa 

et al. 2008). 

2.37.8.3 Disease 

Fibropapillomatosis is a disease characterized by internal and external tumors in sea turtles. 

While it has been reported in all species of sea turtles, it is infrequent in hawksbills and is not 

considered to be a major threat (National Marine Fisheries Service and U.S. Fish and Wildlife 

Service 2007a).

2.37.9 Acoustics 

Little has been done specifically on hawksbill turtles and acoustics, though studies on loggerhead 

sea turtles have demonstrated sensitivity to low frequency noise (Bartol et al. 1999; Samuel et al. 

2005). Sea turtle exposure to seismic air gun noise was studied by Weir (2007), though no 

conclusions on the impacts to the turtles by the airguns were able to be drawn in that study. 

Viada et al. (2008) discussed sea turtle response to underwater explosions and mitigation 

scenarios developed for explosive removal of oil and gas structures. The authors concluded that,

while existing regulations provide more protection for marine turtles than had previously existed, 

little is known about sub-lethal effects of underwater explosions on turtles, especially potential 

auditory impacts (Viada et al. 2008). 

2.37.10 Fisheries By-Catch and Entanglement 

There are no records of fishery interactions with hawksbill turtles in the Northeast Fisheries 

Observer database. The Southeast Fisheries database has three records of observed interactions 

with hawksbill turtles in pelagic longline fisheries, one in 1992, one in 1997 and one in 1998 (see 

Figure 2.37-3). 

2.37.11 Vessel Interactions 

Damage from propeller and collision injuries from boats and ships is commonly found in sea 

turtles. In the stranding data collected by the Sea Turtle Stranding and Salvage Network from 

1997 to 2001, 12.7% of all stranded turtles were documented as having sustained injuries 

consistent with propeller wounds or collision, although some of these injuries may have occurred 

post-mortem (National Marine Fisheries Service et al. 2010).
175

2.37.12 Energy Projects 

Both extractive and renewable offshore energy projects have the potential to impact the marine 

environment in a variety of ways, including habitat alteration and the introduction of noise via 

seismic exploration activities (e.g., airguns), vessel/aircraft activity, construction and operation

(Geraci and St. Aubin 1980, Bain and Williams 2006, Thompsen et al. 2006, Cada et al. 2007, 

Compton 2008, Evans 2008, MMS 2008, Burgman 2010, Boehlert and Gill 2010, Dolman and 

Simmonds 2010, Edrén et al. 2010, Bush 2011, ICES 2011). The impact of these activities on 

turtles is unclear. McMichael and Wyneken (2010) reported on a research program aimed at 

monitoring and minimizing the impacts from interactions between sea turtles and ocean energy 

technology within the Florida Current.

Hawksbills are occasionally captured (and released alive) in the cooling water intakes of 

industrial facilities, such as Florida Power and Light Company’s St. Lucie Power Plant on 

Hutchinson Island. Between March 1976 (when the St. Lucie Plant opened) and June 1992, nine 

hawksbills were captured (Ernest et al. 1989; National Marine Fisheries Service and U.S. Fish & 

Wildlife Service 1993). 

Effects of oil and oil spill response guidelines are presented in a report edited by Shigenaka 

(2003). The report concluded that not only do oil collection areas overlap with sensitive sea 

turtle habitat, but there is also strong, if limited and dated, information that indicates oil is 

harmful to turtles, particularly to dermal tissues and membranes. In addition, fresh oil has been 

found to harm sea turtle eggs (Shigenaka 2003). The relationship between offshore oil platforms 

and the distribution of sea turtles are discussed in a report made by Lohoefener et al. at the 1989 

Ternary Studies meeting sponsored by the MMS (Lohoefener et al. 1989). That study found that 

in some areas of the Gulf of Mexico, chelonid sea turtles were positively correlated with 

platforms, but in others there was either a negative correlation or no correlation at all. High 

amplitude simulated pile driving vibrations were found to decrease sea turtle hatching success 

(Ripcke 2011).

2.37.13 Data Gaps and Research Recommendations

Hays (2008) reviewed recent research on sea turtles, pointing out topical areas and some 

remaining questions. Heenehan (2010) summarized work on acoustic impacts to sea turtles. 

Information on growth, age-to-maturity, and annual reproductive output is scarce for many 

subpopulations of this species. The oceanic phase of post-hatchlings is poorly understood 

(National Marine Fisheries Service and U.S. Fish and Wildlife Service 2007a). Response of 

hawksbill populations to loss of habitat is an important issue, given global threats to coral reef 

ecosystems. Long-term trend data at foraging sites is lacking for hawksbill turtles (National 

Marine Fisheries Service and U.S. Fish and Wildlife Service 2007a). Filling the large gaps in 

available data for population assessments and developing a rigorous process for the assessments 

have been identified as high priorities by the National Research Council (Committee on Sea 

Turtle Population Assessment Methods; National Research Council 2010).
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2.38 LOGGERHEAD TURTLE (CARETTA CARETTA)

2.38.1 Legal Status 

The loggerhead sea turtle was listed as a threatened species throughout its range under the ESA 

in 1978. In 2010, NMFS and USFWS proposed to list 9 Distinct Population Segments (DPSs) of 

loggerhead sea turtles under the ESA (U.S. Fish and Wildlife Service and NOAA 2010). All 

commercial international trade in this species has been banned since it was listed on Appendix I 

by the Convention on International Trade in Endangered Species of Wild Fauna and Flora 

(CITES) in 1975. The IUCN lists the loggerhead as Endangered (IUCN 2010).

2.38.2 General Distribution

Loggerhead turtles are circumglobal, found in the Atlantic, Pacific, and Indian Oceans in 

temperate and tropical regions. They are the most abundant species of marine turtle found in 

U.S. waters; their range includes all BOEM Atlantic planning areas. Nesting occurs from 

Florida to North Carolina. The Peninsular Florida aggregation is the largest nesting aggregation 

in the Atlantic (Turtle Expert Working Group 2009) and is one of only two worldwide nesting 

aggregations that number more than 10,000 females nesting annually (Conant et al. 2009). The 

range of loggerhead sea turtles is shown in Figure 2.38-1 and nesting locations are shown in 

Figure 2.38-2. Tracks of satellite-tagged loggerheads are shown in Figure 2.38-3; sightings and 

fishery bycatch observations are shown in Figure 2.38-4. 

2.38.3 General Abundance 

According to the latest Turtle Expert Working Group assessment (2009), annual nest counts of 

all Western Atlantic subpopulations of loggerhead turtles have been decreasing during the past 

decade. Of special concern is the Peninsular Florida subpopulation, which showed a 49% 

decrease between 1998 and 2007, a decline which has been attributed to decreasing numbers of 

adult females in the population (Witherington et al. 2009). An updated analysis of Florida's 

long-term loggerhead sea turtle nesting data by the Florida Fish and Wildlife Institute 

(http://myfwc.com/research/wildlife/sea-turtles/nesting/loggerhead-trends/ ), shows that nest 

counts declined 16 percent between 1998 and 2011, but that the trend since 1989 may be 

stabilizing (trend was increasing between 1989 and 1998). Table 2.38-1 shows Atlantic Florida

nest counts by county from 2005 through 2010.
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Table 2.38.1 Annual Loggerhead Nest Counts in Atlantic Florida by County

County 2005 2006 2007 2008 2009 2010

Nassau 89 97 63 132 92 199

Duval 67 103 36 99 81 154

St. Johns 208 205 245 313 236 825

Flagler 212 220 219 352 226 458

Volusia 1,375 1,350 1,495 2,239 1,343 2,270

Brevard 19,339 18,089 14,829 21,242 17,194 25,741

Indian River 3,781 3,272 2,905 3,738 3,390 5,147

St. Lucie 4,073 3,204 3,589 4,523 3,936 5,459

Martin 5,822 5,532 5,210 7,356 6,643 9,120

Palm Beach 10,791 11,196 10,559 12,704 11,565 15,775

Broward 1,819 1,740 1,593 1,929 1,808 2,283

Miami-Dade 301 302 295 323 358 352

Monroe 77 66 85 73 199 254

Totals 47,954 45,376 41,123 55,023 47,071 68,037

(Adapted from the FWC Fish and Wildlife Research Institute Statewide Nesting Beach 

Survey Program, at 

http://research.myfwc.com/images/articles/2411/loggerhead_nesting_data__2005-2009.pdf

and 2010 figures from http://myfwc.com/research/wildlife/sea-turtles/nesting/statewide/)

The 2008 Loggerhead Recovery Plan (2008) summarizes recent regional in-water population 

studies. This includes work by Morreale et al. (2005) on New York inshore waters; Mansfield 

(2006) on Chesapeake Bay, Virginia; Epperly et al. (2007) on Pamlico Sound, North Carolina;

NMFS (2001) on South U.S. Atlantic – SEAMAP; Maier et al. (2004) on Southeast U.S.

Atlantic; and Ehrhart et al. (2007) on Indian River Lagoon, Florida. The Turtle Expert Working 

Group Assessment (2009) also summarizes these regional in-water studies, concluding that 

though most of the southern areas show increasing population trends, the Chesapeake Bay and 

Long Island Sound areas show apparent declines. There was also a general increasing trend in 

median size of the neritic juveniles. 

2.38.4 Habitat Preference 

Loggerhead sea turtles use different habitats during different life stages. Terrestrial zones are 

use during oviposition and embryonic development. Nesting loggerheads along the U.S. Atlantic 

coast generally prefer high energy, relatively narrow, steeply sloped, coarse-grained ocean 

beaches (NMFS Office of Protected Resources n.d., 

http://www.nmfs.noaa.gov/pr/species/turtles/loggerhead.htm). Figure 2.38-2 shows the 

distribution of loggerhead nesting beaches in Florida. 

Over 90% of U.S. Atlantic loggerhead nesting takes place in Florida. Annual nest totals from the 

Northern Recovery Unit, which includes Georgia, North and South Carolina, and Virginia, 

averaged 5,215 nests from 1989 to 2008, compared with a mean of 64,513 loggerhead nests per 
178

year in the Peninsular Florida Recovery Unit from 1989 to 2007 (National Marine Fisheries 

Service and U.S. Fish and Wildlife Service 2008).

Site fidelity ranging from 1.9 km to 109.1 km for all nests deposited by a female loggerhead 

within a season was measured by Tucker (2010). Bowen and Karl (2007) showed that nesting 

populations of loggerheads in south and northeast Florida, separated only by 50-100 km, are 

distinct in terms of mtDNA haplotype frequencies, indicating that loggerhead females are 

capable of relatively fine-scale homing. 

Bell et al. (2007), in research on Cayman Islands loggerhead and green turtle nesting sites, 

observed no significant correlation between density of coastal development and clutch density, 

adult emergence success, or hatching success. However, they did find a significant relationship 

between density of coastal development and incidence of misorientation events in loggerhead 

hatchlings. Misorientation has been shown to occur in areas with high levels of artificial lighting 

(Sella et al. 2006; Witherington and Martin 1996). Whelan and Wyneken (2007) compared 

loggerhead hatchling survival rates at three locations in southern Florida. The predation rate 

observed during the first 15 minutes of the migration away from the beach for the three study 

sites combined was 4.6%. Though the predation rate was low during the brief swims observed, 

the authors concluded that predation levels may become higher when misoriented hatchlings fail 

to quickly get into deeper waters. Antworth et al. (2006) looked at nesting patterns and hatching 

success of loggerhead (and leatherback and green) turtles on Canaveral National Seashore. This 

site provided a rare opportunity to collect baseline data at an undisturbed/uninhabitated natural 

beach which could be compared to those at more disturbed localities. Brinn et al. (2010)

analyzed compaction, bulk density, water content, color, and grain size on seven pairs of 

nourished and natural beaches along Florida panhandle with the aim of determining how such 

parameters affect sea turtle nesting success. Baseline data on temperatures of 26 loggerhead 

nesting beaches from South Carolina to Alabama were collected by Estes et al. (2010). Wright et 

al. (2010) looked at hatchling production rates before and after a beach construction and 

nourishment project in Broward County, Florida, and found no significant impacts on hatchling 

production.

After hatchling loggerheads leave the natal beach, they spend more than a decade in an oceanic 

phase before returning to nearshore neritic habitats. It is assumed that this oceanic phase is 

primarily spent drifting in association with Sargassum and with lines of floating material at areas 

of downwelling, but turtles are able to engage in directed swimming in order to feed 

opportunistically when they are not in areas with densities of floating material (Witherington 

2002). They may also take part in extensive oriented swimming when currents are taking them 

onshore or into cold waters. At this oceanic stage turtles spend roughly 75% of their time in the 

upper 5 m of the water column but occasionally dive to depths greater than 200 m (Bolten 2003).

Work by McClellan and Read (2007) has shown that the shift from the oceanic phase to the 

neritic developmental phase is complex and reversible. One example of this is seen in a tagged 

juvenile loggerhead that, following a summer foraging in the Chesapeake Bay and a winter off 

Cape Hatteras, spent over three years in the north Atlantic gyre south of the Grand Banks 

(Mansfield et al. 2010).
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Neritic juvenile loggerheads in the Northwest Atlantic inhabit continental shelf waters from Cape 

Cod Bay, Massachusetts, south through Florida, the Bahamas, Cuba, and the Gulf of Mexico. 

Important inshore habitat areas of the U.S. Atlantic coast include Long Island Sound, 

Chesapeake Bay, Pamlico and Core Sounds, Mosquito and Indian River Lagoons, Biscayne Bay, 

and Florida Bay (Conant et al. 2009). Coles and Musick (2000) looked at juvenile loggerhead 

turtle distribution along the North Carolina coastline from aerial survey data collected during 

1991 and 1992 and correlated it with sea surface temperatures to arrive at a preferred 

temperature range of 13.3 to 28°C. Avens et al. (2003) reported on a survey of Cape Lookout 

Bight, North Carolina, where a seasonal aggregation of loggerheads and other turtles has been 

observed. On two survey days observers recorded 28 and 43 sightings of turtles per hour, many 

of them loggerheads. Mud observed on the backs of many of the turtles could have been from 

emergence after dormancy but also may have been evidence of benthic foraging. One 

loggerhead was satellite tagged during this survey, and after release it travelled north to 

approximately 30 km east of Virginia Beach where it remained through the summer. Bowen et 

al. (2004) offered evidence of natal homing in neritic loggerheads. Haplotype frequency 

differences were significantly correlated between coastal feeding populations and adjacent 

nesting populations, which demonstrates that, at the end of their oceanic phase, juvenile 

loggerheads are returning to feeding habitats that are near their natal rookeries. A markrecapture study of juvenile loggerheads in Core Sound, North Carolina, showed that loggerheads 

exhibit fidelity to certain areas during summer months and are able to navigate back to those 

areas after being relocated or after long migrations (Avens et al. 2003). The Turtle Expert 

Working Group report (2009) presents an analysis of loggerhead distribution in U.S. waters 

using conventional tagging, satellite tagging, and sighting survey data. Areas of high use for 

satellite-tagged juvenile turtles were nearshore coastal waters between the North Carolina-South 

Carolina border into Chesapeake Bay and coastal waters of the mid-Atlantic Bight from spring 

through fall. In the winter, the turtles spent more time off Cape Hatteras. Observed seasonal 

sightings showed similar patterns to the satellite data, allowing the Group to conclude that: 1) the 

mid-Atlantic Bight is important seasonal habitat for juveniles and adult females from the 

Northern U.S. subpopulation; 2) the shelf waters of the eastern U.S. seaboard are important 

migratory habitat, particularly around Cape Hatteras, and 3) that the shelf off southwestern 

Florida is important habitat for female loggerheads (Turtle Expert Working Group 2009).

Hawkes et al. (2007a) combined satellite-tag data with remotely-sensed oceanographic data to 

summarize migratory strategies used by loggerheads. Twelve adult female turtles were tagged 

following nesting in North Carolina, and, though, most of them travelled north to forage at 

higher latitudes during summer before migrating south in the fall, others went south after nesting 

and didn’t make a fall migration. Both groups used warm waters at the edge of the Gulf Stream 

during winter, and made long resting dives. McCarthy et al. (2010) also combined satellite tag 

data with oceanographic variables, but analyzed the straightness index of the satellite tracks, to 

understand the relationship between the turtle movements and the oceanography. A negative 

relationship found between straightness and chlorophyll indicated that the turtle was spending 

more time searching and foraging and the positive relationship observed between straightness 

and ocean depth and SST meant that the turtle was travelling quicker through deeper or warmer 

areas. 
180

Stable isotope confirmed that benthic invertebrates dominated the recent diet of neritic turtles 

and pelagic prey was dominant for oceanic animals (McClellan et al. 2010). However, when 

temporally-protracted diet composition was analyzed, results indicated that all turtles had fed in 

the pelagic zone during overwintering periods. Reich et al. (2009) used stable isotope analysis

and examination of the epibionts, or community of organisms, using the turtle’s carapace as 

substrate, to further demonstrate the bimodal, or even polymodal, foraging strategies of adult 

female loggerheads, where some turtles return to oceanic habitats and some remain in neritic 

areas. Preliminary analysis of male loggerheads using these same techniques (Reich et al. 2010)

does not show the bimodal or polymodal pattern.

Sharks are a primary marine predator of adult and juvenile sea turtles. Heithaus et al. (2002)

examined frequencies of shark-inflicted damage to green turtle and loggerhead turtles in Shark 

Bay, Western Australia. Green turtles were found in tiger shark habitats more frequently than 

loggerheads, yet exhibited less evidence of shark-inflicted injuries, with no sex difference in 

injury frequency. 

2.38.5 Stock Structure 

Five subpopulations, or recovery units, were identified for the Western North Atlantic in the 

2008 Loggerhead Recovery Plan (National Marine Fisheries Service and U.S. Fish and Wildlife 

Service 2008). The separations are based on a combination of geographic distribution of nesting 

densities, spatial separation, and genetic differences. The first two of the subpopulations fall 

within the BOEM Mid-Atlantic, South Atlantic and Straits of Florida Planning Areas. The five 

subpopulations (units) are described below.

1. Northern Recovery Unit: Loggerheads originating from nesting beaches from the FloridaGeorgia border through southern Virginia (the northern extent of the nesting range).

2. Peninsular Florida Recovery Unit: Loggerheads originating from nesting beaches at the 

Florida-Georgia border through Pinellas County on the west coast of Florida, excluding the 

islands west of Key West, Florida.

3. Dry Tortugas Recovery Unit: Loggerheads originating from nesting beaches throughout the 

islands located west of Key West, Florida, because these islands are geographically separated 

from other recovery units.

4. Northern Gulf of Mexico Recovery Unit: Loggerheads originating from nesting beaches 

from Franklin County on the northwest Gulf coast of Florida through Texas (the western extent 

of U.S. nesting range).

5. Greater Caribbean Recovery Unit: Loggerheads originating from all other nesting 

assemblages within the Greater Caribbean (Mexico through French Guiana, the Bahamas, Lesser 

Antilles, and Greater Antilles).

Genetic work done by Shamblin et al. (2010) suggests that the peninsular Florida subpopulation 

should, in fact, be divided into central and southern subpopulations. They saw a demographic 

break in haplotype frequencies in the vicinity of the Canaveral National Seashore.
181

Bowen et al. (2005) surveyed maternally inherited mtDNA in loggerhead turtles and found that 

the level of population structure increased as the turtles progressed through life history stages. 

Pelagic post-hatchlings showed no population structure across the northern Atlantic, subadults in 

coastal habitat showed low structure, and nesting colonies along the southeastern coast of the 

U.S. showed strong structure. However, a survey of biparentally inherited microsatellite DNA 

showed no significant population structure across the same nesting colonies (Bowen et al. 2005).

Bass et al. (2004) performed a mixed-stock analysis of juvenile loggerheads on the feeding 

ground at Pamlico-Albemarle Estuarine Complex, North Carolina, to determine the rookery 

origins of that feeding cohort. They determined that 80% of the turtles originated from the South 

Florida population, 12% were from the northeast Florida to North Carolina nesting population, 

6% were from the Yucatan, Mexico, and 2% were from other rookeries. Juvenile loggerhead sea 

turtles in pelagic habitats of the Azores and Madeira were shown to be derived from nesting 

populations in the western Atlantic by Bolten et al. (1998). Maximum likelihood analyses were 

used to estimate that 100% of the turtles were from the nesting populations in the southeastern 

United States and the Yucatan Peninsula, Mexico. Roberts et al. (2005) performed a mixed stock 

analysis on seasonal juvenile feeding grounds from North Carolina to northern Florida to 

determine the rookery origins of that feeding population and found that the majority originated at 

nearby rookeries.

2.38.6 Life History Traits 

In their 2009 assessment, the Turtle Expert Working Group recognized 5 life stages of 

loggerhead turtles (Turtle Expert Working Group 2009). Table 2.38-2 shows the life stages and 

their definitions.

Table 2.38.2 Life Stages of the Loggerhead Turtle

Life Stage Habitat Straight Carapace Length 

(SCL)

Year One terrestrial to oceanic ≤ 15 cm

Juvenile (1) exclusively oceanic 15-63 cm

Juvenile (2) oceanic or neritic 41-82 cm

Juvenile (3) oceanic or neritic 63-100 cm

Adult neritic or oceanic ≥ 82 cm

A summary of recently published information on loggerhead life stages, presenting data from 

Stewart and Wyneken (2004), Whelan and Wyneken (2007), Bjorndal et al. (2000b, 2003a, 

2001, 2003b), Snover (2002), Sasso et al. (2006), Braun-McNeill (2008, 2007a, 2007b), Hedges 

(2007), Scott (2006), Byrd (2005), and Dahlen et al. (2000) can be found in Table 2 of the 

TEWG (2009 p. 7).

Age at sexual maturity for loggerhead turtles is estimated to be about 35 years. Mating occurs in 

late March to early June in the southeastern U.S. and females lay eggs between late April and 

early September. Females lay between three and five nests (occasionally more) during a single 

nesting season. The eggs incubate for approximately two months and hatchlings emerge 
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between late June and mid-November (NMFS Office of Protected Resources n.d., 

http://www.nmfs.noaa.gov/pr/species/turtles/loggerhead.htm). 

The timing of loggerhead nesting on the Florida coast was correlated with sea surface 

temperatures by Weishampel et al. (2004). The study found that between 1989 and 2003 the 

median nesting date became earlier by approximately 10 days and sea surface temperatures 

warmed an average of 0.8 °C. Similarly, Bowers (2010) looked at first nesting dates from ninety 

beaches in the Southeast U.S. over a 30-year period. Loggerhead sea turtles arrived 0.2 days 

earlier every year during this period, 1.4 days earlier for every point increase in the North 

Atlantic Oscillation index, and 3.6 days later for every degree increase in latitude; this suggests

that the turtles are responding to climate variability and long-term trends. Hawkes et al. (2007b)

investigated the potential impacts of climate change on sex ratios of loggerheads, because, as in 

other sea turtles, the sex determination in this species is temperature dependent. Recorded sand 

temperatures and historical air temperatures at Bald Head Island, North Carolina, were used to 

examine past and predict future sex ratios under scenarios of warming. There were no 

significant trends in primary sex ratio evident in recent years and estimated mean annual sex 

ratio was 58% female. Earlier nesting and longer nesting seasons were correlated with warmer 

sea surface temperature. Populations of turtles in more southern parts of the U.S. are currently 

highly female biased and are likely to become even more so with as little as 1 °C of warming and 

to experience extreme levels of mortality if warming exceeds 3 °C (Hawkes et al. 2007b). 

2.38.7 Food Habits 

A listing of known loggerhead food items was compiled by Dodd (1988). The diet is 

predominatly carnivorous, consisting mostly benthic invertebrates and coelenterates. 

Diet analysis of bycaught oceanic loggerhead turtles in the central North Pacific was carried out 

by Parker et al. (2005). That study demonstrated that the turtles fed mostly on surface prey 

species such as Janthina spp. (Gastropoda); Carinaria cithara (Heteropoda); a chondrophore, 

Velella velella (Hydrodia); Lepas spp. (Cirripedia); Planes spp. (Decapoda: Grapsidae); and 

pyrosomas (Pyrosoma spp.). 

Digestive tract contents of neonate loggerhead turtles associated with downwelling areas of the 

slope water near the Gulf Stream front off east-central Florida were examined in 1997 by 

Witherington (2002). Hydroids, copepods, and pleuston, such as Janthina, Creseis, Porpita, and 

Halobates, were the predominant animal prey species. Ingested plants were largely Sargassum

fragments. In addition, 20% of the turtles sampled had ingested tar and 15% had ingested 

plastic. Ingestion of anthropogenic debris by loggerheads is common and can have serious lethal 

and sublethal effects (Bjorndal et al. 1994; McCauley and Bjorndal 1999). Boyle and Limpus 

(2008) examined stomach contents of post-hatchling loggerhead and green turtles in the 

southwest Pacific and found that the turtles at that stage were opportunistic feeders, consuming 

zooplankton and other floating prey, and that small oceanic green and loggerhead turtles had 

very similar diets (Boyle and Limpus 2008). Frick et al. (2009) examined stomach contents and 

fecal samples in an analysis of diet composition of oceanic-stage loggerhead turtles from the 

North Atlantic Ocean. They found that loggerheads from the Azores are opportunistic carnivores 

that feed upon a variety of oceanic and pelagic organisms, as well as novel food resources, such 

as non-indigenous species.
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Seney and Musick (2008, 2008) examined digestive tract contents from 297 loggerhead turtles in 

Virginia during 1983-2002. Analyses showed a changing diet, from predominantly Atlantic 

horseshoe crab (Limulus polyphemus) during the early to mid-1980s, to predominantly common 

blue crab (Callinectes sapidus) during the late 1980s and early 1990s, and then to predominantly 

finfish, particularly Atlantic menhaden (Brevoortia tyrannus) and Atlantic croaker 

(Micropogonias undulatus), in the mid-1990s and in 2000–2002. The authors postulated that 

crab population declines have led the turtles to forage in nets or on discarded fishery bycatch. 

Immature loggerheads in the Core Sound, North Carolina, area did not appear to feed on fish or 

fish discards, as evidenced by stable isotope analysis (Wallace et al. 2009). However, the turtles 

of Core Sound did show dietary preferences for species, such as blue crab and whelk (Busycon

spp.), that are valuable or are commonly taken in commercial fisheries, which suggests possible 

competitive interactions. Fecal sample analysis of juvenile loggerheads and Kemp’s ridley sea 

turtles in Long Island Sound showed a predominance of nine-spined spider crabs (Libinia 

emarginata) (Burke et al. 1993).

Gut contents and feces of 95 turtles caught in both neritic and pelagic areas of the central 

Mediterranean Sea were examined by Casale et al. (2008). Findings suggested highly 

opportunistic foraging; benthic organisms found in small and larger turtles challenge

assumptions of strict habitat segrations by life stage. The authors proposed an alternative or 

“relaxed” model, in which temporary or permanent fidelity to specific oceanic or neritic zones 

might vary among individuals or populations according to food availability and oceanographic 

features in the foraging or migratory areas.

2.38.8 Health 

2.38.8.1 Strandings 

Hart et al. (2006) examined the spatial distribution of sea turtle strandings in North Carolina and 

concluded that strandings follow patterns that can be predicted from physical oceanography. 

Mazzarella (2007) compared haplotype frequencies of stranded loggerheads in North and South 

Carolina and compared them with those from loggerheads captured in nearby waters. The 

stranded animals were not significantly different; this suggests that strandings are representative 

of the nearshore aggregations.

The Southeast Fisheries Science Center hosts a queryable dataset on Atlantic and Gulf of Mexico 

sea turtle strandings at http://www.sefsc.noaa.gov/seaturtleSTSSN.jsp. Figures 2.38-5 and 2.38-

6 show density distributions of strandings along the Atlantic coast.

2.38.8.2 Contaminants

Keller et al. (2004a) collected blood samples from juvenile loggerhead sea turtles captured in 

Core Sound, North Carolina, and analyzed them for 55 polychlorinated biphenyl (PCB) 

congeners and 24 OC pesticides by gas chromatography with electron capture detection and 

mass spectrometry. Concentrations were found to be similar to previously reported levels in 

blood components of humans and reptiles from relatively clean sites, but lower than those 

measured in blood of fish-eating birds and marine mammals. Carlson et al. (2010) analyzed 
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blood samples of five juvenile loggerheads captured in Core Sound, North Carolina, and coastal 

South Carolina for PBDE, PCB, and OCP levels. No significant temporal trends were found. 

Possible health effects of OC contaminants on loggerheads were investigated (Keller et al. 

2004b). Anemia, modulation of the immune system, and possible hepatocellular damage were 

correlated with OC levels, showing that contamination may be affecting the health of loggerhead 

sea turtles. Comparisons with in-vitro studies also suggested that OC exposure modulates 

immunity in loggerheads (Keller et al. 2006b). Keller et al. (2008, 2005) also measured 

perfluorinated compounds (PFCs) in loggerhead turtles, and found that total PFC concentrations,

though not influenced by sex, were higher in turtles captured from inshore waters of North 

Carolina than in turtles from waters offshore from the South Carolina−Florida coast. POPs 

measured in loggerhead eggs from three areas of the U.S.Atlantic coast showed that levels were 

significantly higher in the northern nests, where elevations in embryonic abnormalities were also 

observed (Alava et al. 2008). Metal concentrations have also been evaluated in loggerhead 

samples from the U.S. Atlantic and Gulf coasts (Day 2003; Day et al. 2005, 2008, 2007; White et 

al. 2008), with some evidence that elevation in blood mercury levels is correlated with proximity 

to major industrial river mouths (Day et al. 2005), and that most metal concentrations were 

higher in eggs collected on Florida’s Gulf coast than on its Atlantic coast (White et al. 2008). 

Blood samples taken from stranded, nesting, and foraging loggerhead turtles along the coast of 

Georgia were analyzed using physical examinations, hematology, plasmabiochemistry, plasma 

protein electrophoresis, and toxicologic parameters (Deem et al. 2009). Significant differences 

in many blood parameters were found between stranded animals, nesting females, and turtles 

captured by trawl.

Sea turtles are adversely impacted by brevetoxin exposure, which is caused by blooms of the 

toxic dinoflagelate Karenia brevis. Significant brevetoxin effects on loggerhead turtle immune 

function were demonstrated by Walsh et al. (2010) in rescued loggerhead sea turtles, and by in 

vitro experiments using peripheral blood leukocytes (PBL) collected from captive sea turtles.

2.38.8.3 Disease 

A high rate of infection by spirorchiid trematodes was found in Florida stranded green and 

loggerhead turtles, and in some cases caused or contributed to death (Stacy et al. 2010). 

McGarrity (2008) examined stress protein expression in both healthy and fibropapilloma 

afflicted green and loggerhead turtles from Indian River Lagoon and compared levels to those 

from turtles from more pristine offshore reef environments.

2.38.9 Acoustics 

Studies on loggerhead sea turtles have demonstrated sensitivity to low frequency noise (Bartol et 

al. 1999; Samuel et al. 2005). Underwater sound recordings from the Peconic Bay Estuary 

system in Long Island, New York, demonstrated that high levels of anthropogenic noise at 

frequencies in the range of the turtles’ highest sensitivity also overlapped spatially and 

temporally with high turtle use of the habitat (Samuel et al. 2005). Sea turtle exposure to seismic 

air gun noise was studied by Weir (2007), though no conclusions on the impacts to the turtles by 

the airguns were able to be drawn in that study. Viada et al. (2008) discussed sea turtle response 

to underwater explosions and mitigation scenarios developed for explosive removal of oil and 

gas structures. The authors concluded that, though existing regulations provide more protection 
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for marine turtles than had previously existed, little is known about sub-lethal effects of 

underwater explosions on turtles, especially potential auditory impacts (Viada et al. 2008). 

2.38.10 Fisheries By-Catch and Entanglement 

Wallace et al. (2010) compiled a database of reported marine turtle bycatch in gillnet, longline, 

and trawl fisheries worldwide from 1990 to 2008. The total reported global marine turtle bycatch 

was approximately 85,000 turtles, though the authors say this is likely an underestimate by at 

least two orders of magnitude, and they do not say what percentage of these are loggerheads. In 

the U.S., shrimp trawling is the fishery with the highest impacts to loggerhead turtles (National 

Marine Fisheries Service and U.S. Fish and Wildlife Service 2008). Turtle Excluder Devices 

(TEDs) are net modifications designed to allow turtles to escape from shrimp nets. Since 

December 1994, TED use has been mandated in shrimp trawls. Bycatch of loggerhead sea 

turtles has been documented in several other Atlantic fisheries, including mid-Atlantic gillnet 

(Murray 2009a, 2009b), southeast shark gillnet (Garrison 2007a), northeast bottom trawl 

(Murray 2006, 2007, 2008a), mid-Atlantic sea scallop dredge (Haas et al. 2008; Murray 2004a, 

2004b, 2005), and pelagic longline (Gilman et al. 2006; Lewison et al. 2004; Lewison and 

Crowder 2007; Watson et al. 2005). Loggerhead bycatch in the Canadian pelagic longline 

fishery has been estimated to be substantial and of similar magnitude to that of the U.S. fleet in 

the North Atlantic (Brazner and McMillan 2008). Gardner et al. (2008) modeled loggerhead 

bycatch in the pelagic longline fishery and found that water temperature, region, bottom depth, 

and target species are all significant predictors of the number of loggerhead sea turtles captured.

Merrick and Haas (2008) discussed impacts to loggerhead populations by scallop dredge and 

trawl fisheries and concluded that, though impacts are detectable, they do not significantly 

change the calculated risk of extinction of the population of adult female Western North Atlantic 

loggerheads over the next 100 years. Sasso and Epperly (2007) reported on a study of satellitetagged loggerheads, some of which had been lightly hooked in the longline fishery and some had 

been dip-netted. No difference in survival rates was detected between turtles which had been 

caught by the longline gear and those in the control group which had not.

Mitigation measures to reduce fishery impacts on loggerhead turtles have been discussed by 

several authors. Gilman et al. (2010) looked at mitigation measures employed in small-scale, 

coastal, passive net fisheries which, the authors argue, may be the largest single threat to some 

sea turtle populations. Lewison et al. (2003) looked at the impact of TEDs on loggerheads and 

found that low compliance was correlated with increased rates of loggerhead strandings. Lawson 

et al. (2007) reported on field research that had been conducted on effects that several TED 

configurations had on the catch of the target species in the mid-Atlantic, inshore, summer 

flounder trawl fishery. Smolowitz et al. (2010) reported on the development of a modified 

scallop dredge which is designed to reduce the probability of a turtle going under the dredge 

frame. Watson et al. (2005) examined changes in bait type and hook design in the longline 

fishery to reduce turtle mortality and found that the use of circle hooks and mackerel bait was 

effective. The use of circle hooks in the pelagic longline fishery was also evaluated by Read 

(2007), who cautioned that their use may not reduce turtle mortality in every longline fishery and 

that more field testing is required. Haas (2010) used four conservation metrics (magnitude of 

adult-equivalent bycatch mortalities, magnitude of bycatch mortalities, magnitude of bycatch, 

and percent of encountered turtles captured) to evaluate various TED configurations. The most 
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informative metric was adult-equivalent bycatch mortality. A TED with a large escape opening 

had the highest estimated conservation value. Up to 66 more adult-equivalent loggerheads were 

estimated to be protected by the large opening than by the standard opening. Extending TED use 

north of 37°N could protect a similar number. This builds on a paper by Wallace et al. (2008)

which discusses the use of reproductive value indices to evaluate fishery impacts on a 

population, with focus on loggerhead turtle interactions with trawl gear. 

2.38.11 Vessel Interactions 

Damage from propeller and collision injuries from boats and ships is commonly found in sea 

turtles. In the stranding data collected by the Sea Turtle Stranding and Salvage Network from 

1997 to 2001, 12.7% of all stranded turtles were documented as having sustained injuries 

consistent with propeller wounds or collision, although some of these injuries may have occurred 

post-mortem (National Marine Fisheries Service et al. 2010). The correlation between 

internesting loggerhead and green turtle dive behavior at Casey Key, Florida, and boat traffic in 

the area was assessed by Sobin and Tucker (2010). Work et al. (2010) ran trials of different 

vessel propulsion systems and operational characteristics and their impacts of sea turtles and 

found that vessel speed did significantly influence the likelihood of catastrophic damage to 

turtles, whereas depth in the water column did not. They found that propeller guards were 

ineffective at planing speed and only slightly helpful at idle speed. Jet propulsion systems 

conferred dramatic improvements in animal safety compared to traditional outboards. 

Hopper dredge operations have also been identified as a cause of loggerhead mortality (National 

Marine Fisheries Service and U.S. Fish and Wildlife Service 2008). Relocation of turtles prior to 

dredging as well as seasonal restrictions on dredge activities have been employed to mitigate 

turtle interactions. 

2.38.12 Energy Projects 

Both extractive and renewable offshore energy projects have the potential to impact the marine 

environment in a variety of ways, including habitat alteration and the introduction of noise via 

seismic exploration activities (e.g., airguns), vessel/aircraft activity, construction and operation

(Geraci and St. Aubin 1980, Bain and Williams 2006, Thompsen et al. 2006, Cada et al. 2007, 

Compton 2008, Evans 2008, MMS 2008, Burgman 2010, Boehlert and Gill 2010, Dolman and 

Simmonds 2010, Edrén et al. 2010, Bush 2011, ICES 2011). The impact of these activities on 

turtles is unclear. McMichael and Wyneken (2010) reported on a research program aimed at 

monitoring and minimizing the impacts from interactions between sea turtles and ocean energy 

technology within the Florida Current.

Entrainment in nuclear power plant intake canals has been a source of loggerhead mortality 

along the U.S. Atlantic coast. In the St. Lucie Nuclear Power plant in St. Lucie, Florida 6,482 

loggerhead have been captured and released between 1976 and 2004.

Effects of oil and oil spill response guidelines are presented in a report edited by Shigenaka 

(2003). The report concluded that not only do oil collection areas overlap with sensitive sea 

turtle habitat, but there is also strong, if limited and dated, information that indicates oil is 

harmful to turtles, particularly to dermal tissues and membranes. In addition, fresh oil has been 

found to harm sea turtle eggs. The relationship between offshore oil platforms and the 
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distribution of sea turtles is discussed in a report made by Lohoefener et al. at the 1989 Ternary 

Studies meeting sponsored by the MMS (Lohoefener et al. 1989). That study found that in some 

areas of the Gulf of Mexico, chelonid sea turtles were positively correlated with platforms, while 

in others there was either a negative correlation or no correlation at all. The explosive removal of 

offshore petroleum platforms is known to have negative impacts on sea turtles (Klima et al. 

1988). Five of eight loggerheads and Kemp’s ridley turtles experimentally subjected to blasts off 

Texas in 1986 were rendered unconscious (Klima et al. 1988). In addition, increases in turtle 

stranding mortalities were correlated with periods of high numbers of offshore explosions (see 

also Acoustics 3.38.9). High amplitude simulated pile driving vibrations were found to decrease 

sea turtle hatching success (Ripcke 2011).

Under a plan developed by the U.S. Fish and Wildlife Servece, NMFS, and the Florida Fish and 

Wildlife Conservation Commission, Kemp’s Ridley, loggerhead, and green sea turtle nests from 

areas of the Florida panhandle and Alabama affected by the Deepwater Horizon oil spill were 

relocated to the Atlantic coast of Florida (for more information, see 

http://www.fws.gov/home/dhoilspill/pdfs/TurtleNestHatchProgram.pdf). 

2.38.13 Data Gaps and Research Recommendations 

Hays (2008), who reviewed recent research on sea turtles, pointed out topical areas and some 

remaining questions. Heenehan (2010) summarized work on acoustic impacts to sea turtles. 

Detailed research recommendations were presented in the TEWG report (Turtle Expert Working 

Group 2009). That document called for better estimates of population parameters, improved 

understanding of spatial and temporal distribution, better definition of population structure, 

additional research on the effects of fishery bycatch on survival rate and population growth, and 

increased information on trophic changes. Post-hatchlings and neonates, juveniles in Florida, 

males, and oceanic loggerheads were all identified as needing additional tracking data in order to 

fully elucidate the life history and spatial representation of loggerhead turtles. Currently, data 

from the Atlantic Marine Assessment Program for Protected Species (AMAPPS) loggerhead 

turtle satellite tracking program are being generated and analyzed. The National Research 

Council’s Assessment of Sea-turtle Status and Trends (Committee on Sea Turtle Population 

Assessment Methods; National Research Council 2010) recommended that NMFS and the 

USFWS develop a coherent national strategy for sea-turtle assessments in order to improve 

collection, quality, and availability of data and also to develop a plan of external review of data 

and models used for population status estimation and trend analysis. The Florida Fish and 

Wildlife Conservation Commission (Eaton et al. 2008) has assembled an overview of in-water 

research projects on sea turtles in Florida and identified geographical gaps and subjects that 

could benefit from further collaboration and standardization. 

2.39 LEATHERBACK TURTLE (DERMOCHELYS CORIACEA)

2.39.1 Legal Status

The leatherback sea turtle was listed as an endangered species under the ESA in 1970. In 1998, 

NMFS designated critical habitat for leatherback turtles; it includes the coastal waters adjacent to 

Sandy Point, St. Croix, U.S. Virgin Islands. In 2009, NMFS proposed to revise the critical 

habitat to include areas off of the U.S. west coast. All commercial international trade in this 
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species has been banned since it was listed on Appendix I by the Convention on International 

Trade in Endangered Species of Wild Fauna and Flora (CITES) in 1975. The IUCN lists the 

leatherback as “Critically Endangered.”

2.39.2 General Distribution

The leatherback turtle is found worldwide in tropical to sub-polar oceans (NMFS Office 

of Protected Resources n.d.) Leatherbacks with a curved carapace length smaller than 100 cm 

appear to be limited to regions warmer than 26°C (Eckert 2002) but adults have a broad thermal 

tolerance and forage from 71°N to 47°S (National Marine Fisheries Service 2001). Though

juveniles have been reported near the coastlines in some regions, the species is considered 

primarily pelagic. Occurrence of leatherbacks is documented in all BOEM planning areas in 

summer and fall, and primarily south of Cape Hatteras, in the mid-Atlantic and South Atlantic 

planning areas in winter and spring. The range of leatherback sea turtles is shown in figure 2.39-

1. Tracks of satellite-tagged leatherbacks are shown in Figure 2.39-2 and sightings and fishery 

bycatch observations are shown in Figure 2.39-3.

Leatherback turtle nesting grounds are located on tropical (and rarely subtropical) beaches 

around the world. The largest remaining nesting colonies are located on the coasts of northern 

South America and West Africa (NMFS Office of Protected Resources n.d.,. In the Atlantic 

U.S., leatherback nesting is concentrated in southeast Florida (Turtle Expert Working Group 

2007). Nesting in Florida was first documented in 1947 and is now a regular seasonal 

occurrence. Nesting is rarer north of Florida. Georgia reported seven leatherback nests in 

2009 and four in 2010 (see http://www.seaturtle.org/nestdb/index.shtml?view=2&year=2010). 

South Carolina reported one leatherback nest in 2006 and three each year in 2008-2010. At least 

ten leatherback nests were reported in North Carolina in 2007 (Stewart 2007). One nest was 

reported in North Carolina in 2009 and one in 2010 (data from North Carolina Wildlife 

Resources Commission, available at

http://www.seaturtle.org/nestdb/index.shtml?view=1&year=2010).

2.39.3 General Abundance 

Although leatherback nesting in Florida is increasing, worldwide the population is in decline.

Collapses have been recorded in some previously important sites (Sarti Martinez 2000). A global 

estimate of 115,000 adult females calculated in 1982 (Pritchard 1982) fell to 20,000-30,000 in 

1996 (Spotila et al. 1996). 

The Turtle Expert Working Group (2007) assessed abundance of leatherbacks in several Atlantic 

populations. Using estimates of the number of nests in 2004-2005, nests per female, remigration 

interval, and sex ratio, the TEWG point estimate for adult turtles in the Florida stock was 580 

(CV=0.33) animals. The Northern Caribbean stock was estimated at 2,700, the Western 

Caribbean stock at 8,100, the Southern Caribbean stock at 20,000 and the West African stock at 

28,000. Trends for six management units (Florida, Northern Caribbean, Western Caribbean, 

Southern Caribbean/Guianas, South Africa and Brazil) of leatherback turtles were also estimated 

(Turtle Expert Working Group 2007). All stocks but one (Western Caribbean) appeared to be 

increasing over the time period examined, although the authors cautioned that increases could be 

an artifact of increases in monitoring. 
189

In Florida, Stewart (2007) estimated leatherback nesting increases at 11.3% per year between 

1979 and 2005. Contributing factors postulated for this increase were improved monitoring and 

protection, and changes in ocean climate and food availability. Table 2.31-2 shows Florida nest 

counts by county from 2005 through 2010. Figure 2.41-3 shows the nesting count trend between 

1988 and 2010.

Table 2.39.1 Annual Leatherback Nest Counts in Florida by County

County 2005 2006 2007 2008 2009 2010

Nassau 0 0 0 0 0 1

Duval 0 0 2 1 5 2

St. Johns 5 0 5 1 20 4

Flagler 8 1 1 0 8 0

Volusia 8 2 17 3 19 15

Brevard 67 16 105 33 70 77

Indian River 50 16 75 27 61 87

St. Lucie 94 57 197 116 235 203

Martin 230 205 494 274 663 561

Palm Beach 284 225 490 243 615 368

Broward 25 15 41 14 45 14

Miami-Dade 9 3 8 10 5 2

Monroe 0 0 0 0 0 0

Totals 780 540 1,435 722 1,746 1,334

(Adapted from the FWC Fish and Wildlife Research Institute Statewide Nesting 

Beach Survey Program at 

http://research.myfwc.com/images/articles/2479/leatherback_nesting_data__2005-

2009.pdf with 2010 data from http://myfwc.com/research/wildlife/seaturtles/nesting/statewide/ )

Shoop and Kenney’s (1992) effort-corrected analysis of over three years of aerial and shipboard 

surveys conducted in northeastern U.S. continental shelf waters showed scattered areas of high 

relative abundance of leatherbacks. Clusters of animals were found south of Long Island and in 

the eastern Gulf of Maine. The leatherback population of the total study area (Cape Hatteras, 

North Carolina, to Nova Scotia, Canada, from the coast out to 5 nm past the 1,000 fathom 

iosbath) was estimated at 100-900 individuals.

Murphy et al. (2006) discussed the abundance and distribution of leatherbacks in South Carolina 

waters. While strandings and sightings of this species were rare prior to 1989, increases have 

been observed in more recent years. Between 1994 and 2003, during April-June, 1131 live 

leatherbacks (0.04 per km) were observed during 50 nearshore aerial surveys flown parallel to 

the South Carolina coast. The highest concentration during a single flight was in May 2002, 

when 175 leatherbacks were seen over 605 km of transect line or 0.29 per km. Numbers 

observed varied significantly between inner and outer transect lines, among years, and among 

flights within a year.
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2.39.4 Habitat Preference 

Leatherback turtles use the terrestrial zone for oviposition and embryonic development and may 

use shallower waters to feed and reproduce, especially during the nesting season (Georges et al. 

2007). They are otherwise a pelagic species, inhabiting the open ocean from hatchling through 

adulthood (National Marine Fisheries Service 2001). Leatherback nesting habitat consists 

primarily of high energy beaches with either a deep water oceanic or shallow water mud bank 

approach (Turtle Expert Working Group 2007). The spatial patterns of leatherback nest 

distributions along the Florida coastline were quantified by Weishampel et al. (2003), who found 

that, unlike those of loggerhead and green turtles, leatherback nest distributions were not 

significantly different from random.

Data from tagged male leatherbacks has suggested that mating occurs in waters adjacent to 

nesting beaches (James et al. 2005a). Males were found to migrate to and stay in these areas for 

up to 96 days. Return migrations indicated breeding site fidelity.

Female leatherbacks are known to embark on trans-oceanic migrations after nesting (National 

Marine Fisheries Service 2001). Tag recovery studies (e.g., Pritchard 1976) and long-distance 

tracking studies such as those by Duron-Dufrenne (1987), Hughes et al. (1998), and Moreale et 

al. (1996) have demonstrated migrations of more than 7,000 km. 

Fossett et al. (2010) analyzed long-term tracking data from 21 leatherback turtles to assess 

spatio-temporal foraging patterns during their migrations in the Northern Atlantic. Fifteen were 

females tagged at nesting beaches in Grenada, French Guiana, and Suriname, and the remaining 

six were captured and tagged off Ireland and Nova Scotia. Current-corrected movement patterns 

and diving behavior were analyzed to identify areas of high and low foraging success. High 

foraging success, when turtles travelled more slowly and performed shallower dives, occurred in 

a sub-equatorial zone spanning the width of the Atlantic and at high (>30°N) latitudes. Turtles 

transited quickly between these zones in the center of the North Atlantic Gyre. Ferraroli et al. 

(2004) also reconstructed movements of satellite-tagged leatherbacks and found that, unlike in 

the Pacific where leatherbacks follow narrow migration corridors, in the Atlantic the turtles 

dispersed widely. They also found that turtles travelled more slowly along productive oceanic 

front areas where gelatinous plankton are concentrated; this suggests that feeding was occurring 

in these areas. 

State-space modeling was performed on satellite tracking data from Pacific leatherbacks by 

Bailey et al. (2008). This study provided estimates of behavioral modes during movement and 

enabled the internesting period to be described based on a shift between transiting and foraging 

modes. They found that the turtles did not immediately move offshore, indicating that the length 

of time and area that turtles utilize during internesting could previously have been 

underestimated. Internesting movements were also studied by Byrne et al. (2009). Two 

leatherback turtles were tracked through three consecutive internesting intervals in the 

Commonwealth of Dominica, West Indies. Near-shore residence, as well as extensive internesting movements, was recorded, with movements away from the nesting beach increasing 

towards the end of the nesting season.
191

Eckert et al. (2006) satellite-tracked ten leatherback turtles from two Florida Atlantic Coast 

nesting beaches. Movement and foraging areas of these turtles, like the leatherbacks tracked in 

2000 from the Archie Carr National Wildlife Refuge of Eastern Florida (Bagley et al. 2001), was 

more coastal than previous leatherback tracking studies had demonstrated. The primary 

internesting habitat was centered east-southeast of Cape Canaveral, Florida, from 2 to 60 km 

offshore and extending 215 km along the coast. Atlantic foraging areas were located primarily 

on the continental shelf from 30° to 50°N between March and November, and in an offshore area 

centered at 42°N, 65°W from December through February, as well as off Africa in the 

Mauritania upwelling. 

The movements and behavior of nine female leatherbacks tagged at their nesting beaches on the 

Caribbean island of Trinidad were monitored for up to 370 days (Eckert 2006). The three longest 

tracked turtles moved from Trinidad to foraging areas at higher latitudes—Northeast of the 

Flemish Cap, along the continental shelf of the Iberian peninsula to the Bay of Biscay, and along 

the North Atlantic subtropical front—where they remained until the end of November; none of 

them transiting through U.S. Atlantic waters. Between mid-October and mid-November, the 

turtles left high latitudes for a presumed foraging area in the Mauritania upwelling, where they 

stayed until their tags stopped transmitting. Diving depths were generally less than 51 m during 

the internesting period. As the turtles migrated out of the Caribbean, dives initially were to 

depths of 100-300 meters and relatively long (>26 mins) but became shallower and shorter at 

high latitudes. 

Sherrill-Mix et al. (2008) used telemetry data obtained from 27 leatherback turtles tagged off 

Nova Scotia and Cape Breton Island and satellite-derived environmental variables to investigate 

the role of environmental correlates, latitudinal and longitudinal position, and turtle body size 

and sex on the timing of southward migration. They found that the turtles’ departure rates did 

not increase with decreasing temperatures; in fact, they were more likely to depart from warmer 

and more chlorophyll-rich waters. Departure rates increased with latitude. A diel pattern in 

travel rates of leatherbacks was found by Jonsen et al. (2006) to change over different phases of 

their migratory cycle. While foraging in northern waters, the turtles had similar travel rates 

during day and night, but on their southward migration to tropical waters, travel rates were faster 

during the day. Changes in diel patterns of diving activity were similar, with less variation when

on the northern feeding grounds, but longer, deeper diving occurring during the night on the 

southward migration (James et al. 2006). State-space modeling was also applied to the Nova 

Scotia tagged leatherback data by Jonsen et al. (2006) to show that transiting leatherbacks make 

longer, deeper dives than foraging ones.

Witt et al. (2007) identified probable foraging grounds for leatherback turtles in the Northeast

Atlantic using monthly landscapes of gelatinous organism distribution constructed from 

Continuous Plankton Recorder Survey data integrated with thermal tolerance parameters. 

McMahon and Hays (2006) looked at the impacts that climate change may have on leatherback 

distribution. They used long-term satellite telemetry to define the habitat use of the turtles and 

showed that the northerly distribution limit of this species is at the 15 °C isotherm. The summer 

position of this isotherm has moved north by 330 km in the North Atlantic in the last 17 years.
192

Population characteristics of leatherbacks captured during eight seasons of fieldwork off Nova 

Scotia were summarized by James et al. (2007). Animals captured at these high latitudes were 

mainly large sub-adults and adults, and had a mean curved carapace length of 148.1 cm and 

mean body mass of 392.6 kg.

Leatherback sighting data in the OBIS dataset consists of 129 records from CETAP 1966-1981 

and 246 records from NEFSC, SEFSC, and UNCW surveys between 1991 and 2006. There is no 

tagging data in the OBIS collection at date of last access. However, the Sea Turtle Conservancy, 

through the Caribbean Leatherback Tracking and Conservation Project, has made several tagged 

leatherback tracklines available online (http://conserveturtles.org/seaturtletracking.php?page=satleatherback). Several of the turtles tagged in the Caribbean have made extensive use of the U.S.

Atlantic coastal waters.

2.39.5 Stock Structure 

The Turtle Expert Working Group (2007), delineated seven global stocks of the leatherback 

turtle based on genetics: Florida, Northern Caribbean, Western Caribbean, Southern 

Caribbean/Guyana Shield/Trinidad, West Africa, South Africa, and Brazil. A conceptual model 

developed by the Working Group proposed that hatchlings move from these seven nesting stock 

areas to an unknown pelagic developmental habitat, and then travel to one of five foraging

grounds: the Gulf of Mexico, North/Central Atlantic, Northwestern shelf, Southeastern U.S.

coast, or the Eastern shelf (Turtle Expert Working Group 2007).

Dutton et al. (1999) performed analyses of mtDNA control region sequences from 175 

leatherback turtles from 10 nesting colonies; this revealed shallow phylogenetic structuring of 

maternal lineages on a global scale. Nesting populations were found to be strongly subdivided 

globally and within ocean basins, despite the leatherback's highly migratory nature. Within the 

Atlantic, significant differences in haplotype frequency distributions, with some exceptions, 

provisionally support the natal homing hypothesis for leatherback turtles. 

2.39.6 Life History Traits 

Leatherbacks may reach sexual maturity faster than the hard-shelled sea turtles (Stewart et al. 

2007). Small reproductive female leatherbacks have been recorded on nesting beaches since the 

1930s; reproductive females as small as 105-125 cm curved carapace length have been observed 

at most nesting sites and their nests have produced viable hatchlings. Sizes of nesting female 

leatherbacks analyzed from Indian, Atlantic, and Pacific Ocean populations were found to vary 

by location and population (Stewart et al. 2007). Avens and Goshe (2008), using 

skeletochronological analysis of leatherbacks in the Atlantic and Gulf of Mexico, estimated age 

at maturity to be 29 years of age. 

Crim et al. (2002) investigated the paternity of nearly one thousand leatherback hatchlings in 

Costa Rica. They compared hatchling genotypes with DNA collected from 32 adult females and 

came to the conclusion that the leatherbacks of this population were both polyandrous and 

polygynous.

The low reproductive success rate of leatherbacks nesting at Playa Grande, Costa Rica was 

examined by Bell et al. (2004) and determined to be a factor of embryonic mortality, rather than 
193

low fertility. Santidrián Tomillo et al. (2009), also at the Playa Grande nesting site, found that 

while hatchling production was variable from year to year, high temperatures reduced hatching 

success and emergence rate. The temporal effect on emergence success meant that more 

hatchlings were produced at the beginning of the season. Predation on hatchlings at Playa 

Grande was primarily by ghost crabs, great blue herons, and yellow-crowned night herons 

(Santidrián Tomillo et al. 2010). Hatchling emergence in Gabon was studied for the effect of 

artificial lighting (Bourgeois et al. 2009). It was found that the attraction to artificial lighting, 

which causes misorientation in hatchlings, was stronger than the effect of landward silhouette 

cues, but was influenced by the brightness of the moon.

Rivalan et al. (2005) used capture-recapture models to investigate intermittent breeding and 

reproductive effort in leatherback turtles nesting in French Guiana. Using the multistate capturerecapture model developed, the mean survival rate was estimated at 0.91 and the average

resighting probability estimated at 0.58 (with a range of 0.30 to 0.99). The breeding cycle was 

found to be limited to three years.

Georges and Fossette (2006) developed a general linear model to predict body mass from 

morphometric measurements obtained from leatherback turtles nesting in French Guiana.

Wallace et al. (2007) looked at variations in maternal investment by leatherback turtles. High 

phenotypic variation in reproductive traits was observed in female leatherbacks, and was 

postulated to be a response to environmental variability and/or an expression of genotypic 

variability within the population.

Leatherback turtle vital rates were summarized in the stock assessments of loggerhead and 

leatherback turtles (National Marine Fisheries Service 2001). Multiple studies were examined 

for parameters, such as remigration rates, nests/year, yolked eggs/nest, hatch success, size of 

nesters, and adult mortality (Binckley et al. 1998; Boulon et al. 1996; Campbell et al. 1996; 

Chevalier et al. 1999; Dutton et al. 2000, 1995; Eckert 2001, 1987; Girondot and Fretey 1996; 

Godfrey et al. 1996; Hoekert et al. 2000; Hughes 1996; Leslie et al. 1996; McDonald and Dutton 

1996; Mrosovsky et al. 1984; Steyermark et al. 1996). Mickelson and Downie (2010) looked at 

how incubation temperature profiles in Tobago, West Indies, leatherback nests influenced 

hatchling morphology and locomotor performance. They found that lower incubation 

temperatures produced hatchlings with traits that were advantageous to terrestrial locomotion.

2.39.7 Food Habits 

Based on stomach content analyses, leatherback diet has been determined to be mainly 

cnidarians (jellyfish, siphonophores) and tunicates (salps, pyrosomas) (Eckert 2001). James and 

Herman (2001) reported on observations of leatherbacks feeding on jellyfish in waters off Nova 

Scotia and Newfoundland, Canada. The connection between jellyfish aggregations and 

leatherback foraging patterns was explored by Houghton et al. (2006) using aerial survey data of 

the Irish Sea. Surveys discovered consistent aggregations of Rhizostoma octopus which were 

correlated geographically with 22.5% of the anecdotal sightings and strandings records from 

around the United Kingdom and Ireland. 
194

The leatherback diet of jellyfish puts it at high risk for ingestion of plastic. Autopsy records of 

408 leatherback turtles, spanning 123 years (1885-2007), were examined by Mrosovskyet al. 

(2009) for the presence or absence of plastic in the GI tract. Plastic was reported in 34% of these 

cases.

Meyers and Hays (2006) used time-depth recorders in conjunction with mouth-opening sensors

on leatherbacks in the southern Caribbean to learn if leatherbacks feed during the breeding 

season. Patterns of diving and mouth-opening activities implied that the leatherbacks were 

attempting to forage and that gustatory cues may be important. Constantino and Salmon (2003)

performed experiments on captive leatherback hatchlings to study the cues used in location and 

of recognition prey. They concluded that the turtles used both visual and chemical cues to search 

for and locate food, but that visual stimuli may be of primary importance.

The overlap in food niche exploitation between leatherbacks and another large consumer of 

gelatinous zooplankton, the ocean sunfish (Mola mola), was explored by Hays et al. (2009). 

While both species foraged in the upper 200 m of waters off South Africa, sunfish were also 

found to feed on deeper prey beyond the normal diving range of the leatherback turtles. Hays et 

al. (2004a) had previously looked at the dive profiles of leatherbacks moving from the Caribbean 

to the Atlantic after nesting. Diving was generally confined to the upper 200 m but varied with 

foraging success, increasing in depth in the Atlantic where foraging success was expected to be 

greater. In a study examining dive profiles of leatherbacks in the North Atlantic by Houghton et 

al. (2008), while the mean maximum dive depth was 59.3 m, dives were recorded as deep as 

1250 m. The authors hypothesized that the infrequent deep dives were to survey the water 

column for diurnally descending prey. 

Bradshaw et al. (2007) examined dive duration and depth data collected for nine free-swimming 

leatherback turtles to infer aerobic dive limits and diving metabolic rates. These findings 

supported the notion that diving leatherback turtles are ectothermic. Their capacity to have a 

warm body core even in cold water, therefore, seems to derive from their large size, heat 

exchangers, thermal inertia, and insulating fat layers and not from an elevated metabolic rate. 

James at el. (2004) captured foraging leatherbacks off Nova Scotia and recorded their body 

temperatures. Mean excess temperature over that of the sea surface (15.0-16.7 °C) averaged 8.2 

°C. Bostrom et al. (2010) demonstrated juvenile leatherbacks increase activity to control heat 

gain. Heat loss is regulated physiologically, presumably by regulation of blood flow distribution. 

Several physiological adaptations for temperature regulation in leatherbacks were examined by 

Davenport et al. (2009a, 2009b). Thick blubber layers in the head and neck help maintain core 

body temperatures even when turtles are foraging in cold waters on cold gelatinous prey 

(Davenport et al. 2009b). Major ontogenetic changes in tracheal structure related to diving and 

temperature regulation take place in leatherbacks (Davenport et al. 2009a). 

Stable isotope analysis has been done by Seminoff et al. (2009) and by Wallace et al. (2006). 

The Seminoff study looked at stable carbon and stable nitrogen diet-tissue discrimination in 

captive leatherbacks that were fed a controlled diet. Wallace et al. used leatherback stable 

isotope analysis to compare nitrogen cycling regimes in the Pacific and Atlantic Oceans.
195

2.39.8 Health 

2.39.8.1 Strandings 

The Southeast Fisheries Science Center hosts a queryable dataset on Atlantic and Gulf of Mexico 

sea turtle strandings at http://www.sefsc.noaa.gov/seaturtleSTSSN.jsp. Figures 2.39-4 and 2.39-

5 show density distributions of strandings along the Atlantic coast.

Murphy et al. (2006) reported on the rise in leatherback strandings on South Carolina beaches 

since 1989. Between 1980 and 2003, 141 leatherback carcasses stranded. The seasonal peak for 

strandings occurred in the spring and was followed by a lesser peak in the fall. Based on 23 

necropsies, there were 7 males and 16 females.

2.39.8.2 Contaminants

Orós et al. (2009) examined tissue samples from 30 loggerheads, one leatherback, and one green 

turtle that had stranded on the coasts of the Canary Islands. While concentrations of PCB 209 

were high in the liver of the loggerheads and in the liver and adipose tissue of the leatherback, it 

was not possible to draw a clear correlation between the PCB concentrations and cause of death. 

Edmonds (1994) found arsenic in tissues of a leatherback turtle. Low exposure to OC 

contamination by leatherbacks was measured by McKenzie et al. (1999). Sample size was too 

low to draw conclusions from, but it was postulated that the leatherback’s diet of pelagic jellyfish 

could be an explanation for its lower evidence of exposure.

Concentrations of essential (copper, zinc, selenium) and non-essential elements (cadmium, lead, 

mercury) were determined in the blood and eggs of 46 free-ranging leatherback females sampled 

in French Guiana (Guirlet et al. 2008). All trace elements were detectable in both tissues. Levels 

of toxic metals were lower than essential elements, likely because of the high pelagic nature of 

leatherbacks that seems to limit exposure to toxic elements. Over the course of the nesting 

season, copper levels decreased while blood lead levels increased. The high demand on the body 

during the breeding season could affect blood copper concentrations. The calcium requirement 

for egg production with concomitant lead mobilization could explain the increase in blood lead 

concentrations. The authors also examined maternal transfer of organochlorine contaminants 

(OCs), pesticides (DDTS and HCHs) and polychlorinated biphenyls (PCBs) (Guirlet et al. 2010). 

PCBs were the dominant OCs found. OC concentrations were lower than concentrations 

measured in other marine turtles; this might be explained by the lower trophic position (diet 

based on jellyfish) and by the location of their foraging and nesting grounds. All OCs detected in 

leatherback blood were detected in eggs; this suggests a maternal transfer of OCs. During the 

nesting season, OC concentrations in eggs and the percentage of lipid in eggs were found to 

decline in successive clutches, highlighting a process of offloading from females to their eggs 

and a decreasing investment of lipid from females into their clutches. OCs in eggs tended to be 

higher in females spending three years on the foraging grounds between nesting seasons than in 

those spending two years.

2.39.8.3 Disease 

Santoro et al. (2008) tested leatherback turtles from the nesting population of Pacuare Nature 

Reserve in Caribbean Costa Rica for pathogenic bacteria. A total of 189 isolates, including 113 
196

gram-negative and 76 gram-positive bacteria, most of which may be considered as potential 

pathogens, were identified in samples from 70 nesting females,.

2.39.9 Acoustics 

Little has been done specifically on leatherbacks and acoustics, though studies on loggerhead sea 

turtles have demonstrated sensitivity to low frequency noise (Bartol et al. 1999; Samuel et al. 

2005). Underwater sound recordings from the Peconic Bay Estuary system in Long Island, New 

York demonstrated high levels of anthropogenic noise at frequencies in the range of the turtles’ 

highest sensitivity; these also overlapped spatially and temporally with high turtle use of the 

habitat (Samuel et al. 2005). Sea turtle exposure to seismic air gun noise was studied by Weir 

(2007), though no conclusions on the impacts to the turtles by the airguns were able to be drawn 

in that study. Viada et al. (2008) discussed sea turtle response to underwater explosions and 

mitigation scenarios developed for explosive removal of oil and gas structures. The authors 

concluded that though existing regulations provide more protection for marine turtles than had 

previously existed, little is known about sub-lethal effects of underwater explosions on turtles, 

especially potential auditory impacts (Viada et al. 2008). 

2.39.10 Fisheries By-Catch and Entanglement 

Globally, leatherback bycatch in pelagic longline fisheries was estimated to have been between 

50,000 and 60,000 in 2000 (Lewison et al. 2004). 

Bycatch of leatherback sea turtles has been documented in several Atlantic fisheries, including 

pelagic longline, shark gillnet, sink gillnet, and bottom otter trawl. Between 2005 and 2009, in 

the Florida East Coast Pelagic longline fishing area, which corresponds roughly to the BOEM 

Straits of Florida Planning Area, leatherback bycatch was estimated to range between 6.6 (2007) 

and 62.3 (2005). During the same period, in the mid-Atlantic Bight, which falls within the midAtlantic and North Atlantic planning areas, estimated leatherback bycatch in the longline fishery 

ranged from 30 (2006) to 114.1 (2007). In the Northeast Coastal Area, part of which falls within 

the boundaries of the BOEM North Atlantic Planning Area, between 2005 and 2009 the 

estimated bycatch of leatherbacks ranged from 0 (2008) to 116 (2006). The South Atlantic Bight 

Area, falling in the mid- and South Atlantic Planning Areas, saw bycatch ranging from 0 (2007 

and 2008) to 39 (2006) during the same period (Fairfield Walsh and Garrison 2006, 2007; 

Fairfield and Garrison 2008; Garrison and Stokes 2010; Garrison et al. 2009). In the shark 

gillnet fishery between 2000 and 2006, eight loggerheads were reported taken in drift nets, four 

in strike nets, and one in a sink net (Garrison 2007a). Five leatherback turtles were observed in 

mid-Atlantic gillnet gear between 1995 and 2006 (Murray 2009a). 

Work by Ferarroli et al. (2004), showed that for leatherbacks nesting in French Guinea and 

Suriname, foraging patterns overlap with both pelagic longline fisheries along oceanic fronts and 

with coastal shrimp and red snapper fisheries near the nesting grounds. Hays et al. (2004b) also 

discussed the overlap between leatherback foraging and longline fisheries in the Atlantic. They

pointed out that the potential for interaction with longlines was increased because, in addition to 

the pan-oceanic movements which put the turtles into contact with fished areas, the turtles also 

spent more time in shallow dive patterns when they were in the feeding areas. Kot et al. (2010)

looked at temporal patterns of sea turtle bycatch using logbook data from U.S. Atlantic longline 
197

fisheries. Most regions that were examined exhibited a strong annual/seasonal periodicity in 

turtle bycatch rates.

Satellite telemetry data of leatherbacks tagged off Nova Scotia, Canada, and morphometrics from 

foraging animals and entanglement records were examined by James et al. (2005b), and 

demonstrated that, because leatherbacks migrate annually to key feeding areas in northern 

latitudes, they are vulnerable to entanglement in northern coastal and shelf waters.

2.39.11 Vessel Interactions 

Injuries indicative of collisions with vessels are commonly found in sea turtles. In the stranding 

data collected from 1997 to 2001 by the Sea Turtle Stranding and Salvage Network, 12.7% of all 

stranded turtles were documented as having sustained injuries consistent with propeller wounds 

or collision, although some of these injuries may have occurred post-mortem (National Marine 

Fisheries Service et al. 2010).

2.39.12 Energy Projects 

Both extractive and renewable offshore energy projects have the potential to impact the marine 

environment in a variety of ways. including habitat alteration and the introduction of noise via 

seismic exploration activities (e.g.. airguns), vessel/aircraft activity, construction and operation

(Geraci and St. Aubin 1980, Bain and Williams 2006, Thompsen et al. 2006, Cada et al. 2007, 

Compton 2008, Evans 2008, MMS 2008, Burgman 2010, Boehlert and Gill 2010, Dolman and 

Simmonds 2010, Edrén et al. 2010, Bush 2011, ICES 2011). The impact of these activities on 

turtles is unclear. McMichael and Wyneken (2010) reported on a research program aimed at 

monitoring and minimizing the impacts from interactions between sea turtles and ocean energy 

technology within the Florida Current.

Leatherbacks are occasionally captured in the cooling water intakes of industrial facilities, such 

as Florida Power and Light Company’s St. Lucie Power Plant on Hutchinson Island. Between 

March 1976 (when the St. Lucie Plant opened) and November 1988, eight leatherbacks were 

captured (Ernest et al. 1989).

Effects of oil and oil spill response guidelines are presented in a report edited by Shigenaka 

(2003). The report concluded that not only do oil collection areas overlap with sensitive sea 

turtle habitat, but there is also strong, if limited and dated, information that indicates oil is 

harmful to turtles, particularly to dermal tissues and membranes. In addition, fresh oil has been 

found to harm sea turtle eggs. The relationship between offshore oil platforms and the 

distribution of sea turtles is discussed in a report made by Lohoefener et al. at the 1989 Ternary 

Studies meeting sponsored by the MMS (Lohoefener et al. 1989). That study found that in some 

areas of the Gulf of Mexico, chelonid sea turtles were positively correlated with platforms, but in 

others there was either a negative correlation or no correlation at all. High amplitude simulated 

pile driving vibrations were found to decrease sea turtle hatching success (Ripcke 2011).

2.39.13 Data Gaps and Research Recommendations 

Hays (2008) reviewed recent research on sea turtles, and pointed out topical areas and some 

remaining questions; Heenehan (2010) summarized work on acoustic impacts to sea turtles. 

Research recommendations outlined in the Leatherback Assessment by the Turtle Expert 
198

Working Group (2007) include increased collection and estimation of demographic parameters, 

bycatch, and mortality; continued genetic sampling; and increased research on the effects of 

pollutants, disease, strandings and other threats to leatherback populations. The National 

Research Council’s Assessment of Sea-turtle Status and Trends (Committee on Sea Turtle 

Population Assessment Methods; National Research Council 2010) recommended that NMFS 

and the USFWS develop a coherent national strategy for sea-turtle assessments to improve 

collection, quality and availability of data, and to develop a plan of external review of data and 

models used for population status estimation and trend analysis.
Table 2.39.13 Data Sources

(Unless otherwise specified, data presented in the maps comes from the following sources. Sightings maps are not effort-corrected 

and as such should not be interpreted as complete representations of species distribution.)

Data Set Description Website/Contact

Aerial survey of upper trophic level predators on Platts 

Bank, Gulf of Maine (Gulf of Maine Census of Marine 

Life Program)

For description see:

nwolff@usm.maine.edu

Bald Head Island 2004: Loggerhead Turtles

http://gcmd.nasa.gov/KeywordSearch/Metadata.do?Portal=gomm

p&KeywordPath=&NumericId=27198&MetadataView=Full&Me

tadataType=0&lbnode=mdlb2

Coyne, M. S., and B. J. Godley. 2005. Satellite Tracking and 

Analysis Tool (STAT): an integrated system for archiving, 

analyzing and mapping animal tracking data. Marine Ecology 

Progress Series. Vol. 301:1-7. 

B.J.Godley@exeter.ac.uk

Bald Head Island 2005: Loggerhead Turtles

Data retrieved from:

http://www.iobis.org

Coyne, M. S., and B. J. Godley. 2005. Satellite Tracking and 

Analysis Tool (STAT): an integrated system for archiving, 

analyzing and mapping animal tracking data. Marine Ecology 

Progress Series. Vol. 301:1-7. 

mcoyne@seaturtle.org

BLM Cetacean and Turtle Assessment Program 

(CETAP) SHIP Sightings

Data retrieved from

http://www.iobis.org

University of Rhode Island BLM Cetacean and Turtle Assessment 

Program (CETAP) SHIP Sightings. In: OBIS-SEAMAP . OBISSEAMAP, http://seamap.env.duke.edu/, 2005-08-02 

15:09:16.272989-04, vector digital data. 

rkenney@gso.uri.edu

BLM CETAP AIR Sightings

Data retrieved from 

http://www.iobis.org

University of Rhode Island BLM Cetacean and Turtle Assessment 

Program (CETAP) AIR Sightings. In: OBIS-SEAMAP . OBISSEAMAP, http://seamap.env.duke.edu/, 2005-08-02 

15:08:23.268819-04, vector digital data. 

rkenney@gso.uri.edu

BLM CETAP OPP Sightings

Data retrieved from 

http://www.iobis.org

University of Rhode Island BLM Cetacean and Turtle Assessment 

Program (CETAP) OPP Sightings. In: OBIS-SEAMAP . OBISSEAMAP, http://seamap.env.duke.edu/, 2005-08-02 

15:08:47.889912-04, vector digital data. 

rkenney@gso.uri.edu

Cape Cod Sea Turtle Release 2007

Data retrieved from

http://www.iobis.org

Coyne, M. S., and B. J. Godley. 2005. Satellite Tracking and 

Analysis Tool (STAT): an integrated system for archiving, 

analyzing and mapping animal tracking data. Marine Ecology 

Progress Series. Vol. 301:1-7. 

cmerigo@neaq.org

204

Data retrieved from

http://www.iobis.org
Data Set Description Website/Contact

Casey Key Loggerheads - 2009 Coyne, M. S., and B. J. Godley. 2005. Satellite Tracking and 

Analysis Tool (STAT): an integrated system for archiving, 

analyzing and mapping animal tracking data. Marine Ecology 

Progress Series. Vol. 301:1-7. 

tucker@mote.org

Girard, C., A. D. Tucker, and B. Calmettes. 2009. Post-nesting 

migrations of loggerhead sea turtles in the Gulf of Mexico: 

dispersal in highly dynamic conditions. Marine Biology. 

156:1827-1839. DOI:10.1007/s00227-009-1216-z. 

Data retrieved from

http://www.iobis.org

Tucker, A. D. 2009. Eight nests recorded for a loggerhead turtle 

within one season. Marine Turtle Newsletter. 124:16-17. 

Casey Key Loggerheads 2005-2006 - Southwest 

Florida

Mote Marine Laboratory Casey Key Loggerheads - Southwest 

Florida. In: OBIS-SEAMAP . OBIS-SEAMAP, 

http://seamap.env.duke.edu, 2006-11-02 05:35:48-05, vector 

digital data. 

tucker@mote.org

Casey Key Loggerheads-2007

Data retrieved from

http://www.iobis.org

Coyne, M. S., and B. J. Godley. 2005. Satellite Tracking and 

Analysis Tool (STAT): an integrated system for archiving, 

analyzing and mapping animal tracking data. Marine Ecology 

Progress Series. Vol. 301:1-7. 

tucker@mote.org

Girard, C., A. D. Tucker, and B. Calmettes. 2009. Post-nesting 

migrations of loggerhead sea turtles in the Gulf of Mexico: 

dispersal in highly dynamic conditions. Marine Biology. 

156:1827-1839. DOI:10.1007/s00227-009-1216-z 

Data retrieved from

http://www.iobis.org

Tucker, A. D. 2009. Eight nests recorded for a loggerhead turtle 

within one season. Marine Turtle Newsletter. 124:16-17 

205 
Data Set Description Website/Contact

Casey Key Loggerheads-2008 Coyne, M. S., and B. J. Godley. 2005. Satellite Tracking and 

Analysis Tool (STAT): an integrated system for archiving, 

analyzing and mapping animal tracking data. Marine Ecology 

Progress Series. Vol. 301:1-7. 

tucker@mote.org

Girard, C., A. D. Tucker, and B. Calmettes. 2009. Post-nesting 

migrations of loggerhead sea turtles in the Gulf of Mexico: 

dispersal in highly dynamic conditions. Marine Biology. 

156:1827-1839. DOI:10.1007/s00227-009-1216-z. 

Data retrieved from

http://www.iobis.org

Tucker, A. D. 2009. Eight nests recorded for a loggerhead turtle 

within one season. Marine Turtle Newsletter. 124:16-17 

Retrieved from http://www.iobis.org

Duke North Atlantic Turtle Tracking Duke University Marine Laboratory Duke North Atlantic Turtle 

Tracking. In: OBIS-SEAMAP. OBIS-SEAMAP, 

http://seamap.env.duke.edu, 2006-11-02 05:36:26-05, vector 

digital data. 

catherin@duke.edu

DUML Vessel-Based Surveys for USWTR site 2009-

2010

Data retrieved from

http://www.iobis.org

Nilsson, P.B., Foley, H. J., Hardee, R.E., Holt, R. C., McAlarney, 

R.J., Cummings, E. W., Johnston, D.W., McLellan, W. A., Pabst, 

D. A. and Read, A.J. 2010. Protected species monitoring in the 

proposed Under Sea Warfare Training Range Off-Shore of 

Jacksonville, FL: Jan - Dec 2009. SEAMAMMS 2010 

Conference Abstract, Poster 

david.johnston@duke.edu

Fishery bycatch - NE

Presentation retrieved

from http://www.iobis.org

1989-2010 Northeast Fishery Observer Program data

Hatteras Eddy Cruise 2004

http://www.nefsc.noaa.gov/

fsb/

Duke / UNC Oceanographic Consortium Hatteras Eddy Cruise 

2004. In: OBIS-SEAMAP . OBIS-SEAMAP,

http://seamap.env.duke.edu/, 2006-03-29 13:15:44.214284-05,

vector digital data.

khyrenba@u.washington.e

du or khyrenba@duke.edu

Data retrieved from

http://www.iobis.org

Joint Deepwater Systematics and Marine Mammal 

Survey

NOAA NEFSC Joint Deepwater Systematics and Marine 

Mammal Survey. In: OBIS-SEAMAP . OBIS-SEAMAP,

http://seamap.env.duke.edu/, 2005-08-17 19:49:42.240994-04, 

vector digital data. 

Debra.Palka@noaa.gov

Data retrieved from

http://www.iobis.org

206 201
Data Set Description Website/Contact

Loggerhead Turtles: Bald Head Island 2003 Marine Turtle Research Group Loggerhead Turtles: Bald Head 

Island 2003. In: OBIS-SEAMAP . OBIS-SEAMAP, 

http://seamap.env.duke.edu, 2008-01-11 05:04:01-05, vector

digital data. 

Data retrieved from

http://www.iobis.org

Mammal Strandings NOAA National Marine Mammal Health and Stranding Response 

Database and the NOAA SER Marine Mammal Stranding 

Database, Northeast and Southeast US Marine Mammal 

Stranding Networks 2005-2009

Mote Marine Laboratory - Sea Turtle Rehabilitation 

Hospital

Coyne, M. S., and B. J. Godley. 2005. Satellite Tracking and 

Analysis Tool (STAT): an integrated system for archiving, 

analyzing and mapping animal tracking data. Marine Ecology 

Progress Series. Vol. 301:1-7. 

tucker@mote.org

Data retrieved from 

http://www.iobis.org

National Marine Life Center Coyne, M. S., and B. J. Godley. 2005. Satellite Tracking and 

Analysis Tool (STAT): an integrated system for archiving, 

analyzing and mapping animal tracking data. Marine Ecology 

Progress Series. Vol. 301:1-7. 

bmoore@nmlc.org

Data retrieved from

http://www.iobis.org

NEFSC 1995 AJ9501 (Part I) Debra Palka, David Potter, National Marine Fisheries Service. 

1991. Cruise report of the harbor porpoise survey - 1991 AJ91-02 Debra.Palka@noaa.gov

NEFSC Aerial Circle-Back Abundance Survey 2004 NOAA Northeast Fisheries Science Center. 2004. Aerial survey 

results; NOAA Twin Otter aircraft; Circle-Back Abundance 

Survey. 

Debra.Palka@noaa.gov

Data retrieved from 

http://www.iobis.org

NEFSC Aerial Survey - Experimental 2002 NOAA Northeast Fisheries Science Center (NEFSC) NEFSC 

Aerial Survey - Experimental 2002. In: OBIS-SEAMAP . OBISSEAMAP, http://seamap.env.duke.edu/, 2006-03-08 11:43:55-05,

vector digital data.

Debra.Palka@noaa.gov

Data retrieved from

http://www.iobis.org

NEFSC Aerial Survey - Summer 1995 NOAA Northeast Fisheries Science Center (NEFSC) NEFSC 

Aerial Survey - Summer 1995. In: OBIS-SEAMAP . OBISSEAMAP, http://seamap.env.duke.edu/, 2006-03-08 11:43:17-05,

vector digital data. 

Debra.Palka@noaa.gov

Data retrieved from

http://www.iobis.org

NEFSC Aerial Survey - Summer 1998 NOAA Northeast Fisheries Science Center (NEFSC) NEFSC 

Aerial Survey - Summer 1998. In: OBIS-SEAMAP . OBISSEAMAP, http://seamap.env.duke.edu/, 2006-05-12 11:33:36-04, 

vector digital data. 

Debra.Palka@noaa.gov

Data retrieved from

http://www.iobis.org

207
Data Set Description Website/Contact

NEFSC Marine Mammal Abundance Survey - Leg 1 NOAA Northeast Fisheries Science Center (NEFSC) Marine 

Mammal Abundance Survey - Leg 1. In: OBIS-SEAMAP . OBISSEAMAP, http://seamap.env.duke.edu/, 2005-08-17

19:25:23.992499-04, vector digital data. 

Debra.Palka@noaa.gov

Data retrieved from

http://www.iobis.org

NEFSC Marine Mammal Survey PE 95-02 NOAA Northeast Fisheries Science Center (NEFSC) Marine 

Mammal Survey PE 95-02. In: OBIS-SEAMAP . OBISSEAMAP, http://seamap.env.duke.edu/, 2005-08-17

19:24:07.349686-04, vector digital data.

Debra.Palka@noaa.gov

Data retrieved from 

http://www.iobis.org

NEFSC Mid-Atlantic Marine Mammal Abundance 

Survey 2004

NOAA Northeast Fisheries Science Center. 2004. Cruise Results; 

R/V Endeavor; Cruise No. EN 04-395/396; Mid-Atlantic Marine 

Mammal Shipboard Abundance Survey. 

Debra.Palka@noaa.gov

Data retrieved from

http://www.iobis.org

NEFSC Survey 1998 1 NOAA Northeast Fisheries Science Center (NEFSC) NEFSC 

Survey 1998 1. In: OBIS-SEAMAP . OBIS-SEAMAP,

http://seamap.env.duke.edu/, 2004-02-13 15:42:07.2188-05,

vector digital data.

Debra.Palka@noaa.gov

Data retrieved from

http://www.iobis.org

NEFSC Survey 1998 2 NOAA Northeast Fisheries Science Center (NEFSC) NEFSC 

Survey 1998 2. In: OBIS-SEAMAP . OBIS-SEAMAP, 

http://seamap.env.duke.edu/, 2004-02-13 15:43:01.279903-05,

vector digital data. 

Debra.Palka@noaa.gov

Data retrieved from

http://www.iobis.org

NEFSC Aerial Survey - Summer 2010 Survey report available at:

Debra.Palka@noaa.gov http://www.nefsc.noaa.gov/psb/surveys/documents/air2010.pdf

NEFSC Aerial Survey - Summer 2008 Survey report available at:

Debra.Palka@noaa.gov http://www.nefsc.noaa.gov/psb/surveys/documents/air2008.pdf

NEFSC Aerial Survey - Summer 2007 Survey report available at: 

Debra.Palka@noaa.gov http://www.nefsc.noaa.gov/psb/surveys/documents/air2007.pdf

NEFSC Aerial Survey - Summer 2006 Survey report available at: 

http://www.nefsc.noaa.gov/psb/surveys/documents/CruiseReport.

aerial2006.full.pdf

Debra.Palka@noaa.gov

Newport Aquarium 2004: Loggerhead Turtle Coyne, M. S., and B. J. Godley. 2005. Satellite Tracking and 

Analysis Tool (STAT): an integrated system for archiving, 

analyzing and mapping animal tracking data. Marine Ecology 

Progress Series. Vol. 301:1-7. 

B.J.Godley@exeter.ac.uk

Data retrieved from

http://www.iobis.org

208
Data Set Description Website/Contact

NOAA Atlantic Cetacean Survey 1999; Sightings NOAA Southeast Fisheries Science Center (SEFSC) NOAA 

Atlantic Cetacean Survey 1999; Sightings. In: OBIS-SEAMAP .

OBIS-SEAMAP, http://seamap.env.duke.edu/, 2005-06-10 

07:55:07.256674-04, vector digital data.

Lance.Garrison@noaa.gov

Data retrieved from

http://www.iobis.org

NOAA Southeast Cetacean Aerial Survey 1995; 

Sightings

NOAA Southeast Fisheries Science Center (SEFSC) NOAA 

Southeast Cetacean Aerial Survey 1995; Sightings. In: OBISSEAMAP . OBIS-SEAMAP, http://seamap.env.duke.edu/, 2005-

06-28 21:14:28.534611-04, vector digital data.

Lance.Garrison@noaa.gov

Data retrieved from

http://www.iobis.org

North Carolina Aquarium at Pine Knoll Shores Sea 

Turtle Awareness (OBIS-SEAMAP) 

Coyne, M. S., and B. J. Godley. 2005. Satellite Tracking and 

Analysis Tool (STAT): an integrated system for archiving, 

analyzing and mapping animal tracking data. Marine Ecology 

Progress Series. Vol. 301:1-7. 

heather.broadhurst@ncaqu

ariums

Data retrieved from

http://www.iobis.org

Northeast Fisheries Science Center Bottom Trawl 

Survey Data

NOAA's National Marine Fisheries Service (NMFS) Northeast 

Fisheries Science Center Northeast Fisheries Science Center 

Bottom Trawl Survey Data. NOAA’s National Marine Fisheries 

Service (NMFS) Northeast Fisheries Science Center, Ecosystems 

Survey Branch, Woods Hole, Massachusetts, United States of 

America, 2005-04-30, Tabular Digital Data. Additional 

information can be found at http://www.nefsc.noaa.gov. 

Linda.Despres@noaa.gov

Data retrieved from

http://www.iobis.org

Pelagic longline bycatch 1992-2010 Lance.Garrison@noaa.gov

PIROP Northwest Atlantic 1965-1992 See description at: khyrenba@u.washington.e

du

http://seamap.env.duke.edu/datasets/detail/280 Data retrieved from

http://www.iobis.org

Sea Turtle Strandings Sea Turtle Stranding and Salvage Network http://www.sefsc.noaa.gov/

species/turtles/strandings.ht

m

Sargasso 2005 - cetacean sightings See description at: hwhitehe@dal.ca

http://seamap.env.duke.edu/dataset/332 Data retrieved from

http://www.iobis.org

SEFSC Mid-Atlantic Tursiops Survey, 1995 2 NOAA Southeast Fisheries Science Center (SEFSC) NOAA Mid 

Atlantic Tursiops Surveys 1995 (2); Sightings. In: OBISSEAMAP . OBIS-SEAMAP, http://seamap.env.duke.edu/, 2005-

06-28 21:40:00.121113-04, vector digital data.

Lance.Garrison@noaa.gov

Data retrieved from

http://www.iobis.org

209
Data Set Description Website/Contact

SEFSC Mid-Atlantic Tursiops Survey, 1995 3 NOAA Southeast Fisheries Science Center (SEFSC) NOAA Mid 

Atlantic Tursiops Surveys 1995 (3); Sightings. In: OBISSEAMAP . OBIS-SEAMAP, http://seamap.env.duke.edu/, 2005-

06-28 21:37:27.211758-04, vector digital data.

Lance.Garrison@noaa.gov

Data retrieved from 

http://www.iobis.org

SEFSC Southeast Cetacean Aerial Survey 1992 NOAA Southeast Fisheries Science Center (SEFSC) NOAA 

Southeast Cetacean Aerial Survey 1992; Sightings. In: OBISSEAMAP . OBIS-SEAMAP, http://seamap.env.duke.edu/, 2005-

06-28 21:18:36.46644-04, vector digital data. 

Lance.Garrison@noaa.gov

Data retrieved from

http://www.iobis.org

SEFSC sightings 2004, 2005, 2005 SEFSC shipboard surveys Lance.Garrison@noaa.gov

Southeast Area Monitoring and Assessment Program 

(SEAMAP) South Atlantic (USOBIS)

For description see: Data retrieved from

http://www.seamap.org/ http://www.iobis.org

Summer 2004 Cape Hatteras Duke University Marine Laboratory Summer 2004 Cape Hatteras. 

In: OBIS-SEAMAP . OBIS-SEAMAP, 

http://seamap.env.duke.edu/, 2006-05-25 16:05:08.17444-04, 

vector digital data. 

eal12@duke.edu

Data retrieved from

http://www.iobis.org

Turtle Hospital, Marathon Florida Coyne, M. S., and B. J. Godley. 2005. Satellite Tracking and 

Analysis Tool (STAT): an integrated system for archiving, 

analyzing and mapping animal tracking data. Marine Ecology 

Progress Series. Vol. 301:1-7. 

turtlehosp@aol.com, 

tucker@mote.org

Data retrieved from

http://www.iobis.org

UNCW Aerial Survey 98-99 University of North Carolina at Wilmington UNCW Aerial 

Survey 98-99. In: OBIS-SEAMAP . OBIS-SEAMAP, 

http://seamap.env.duke.edu/, 2005-03-11 18:52:29.590331-05, 

vector digital data. 

mclellanw@uncw.edu

Data retrieved from

http://www.iobis.org

UNCW Aerial Surveys for monitoring of proposed 

Oslow Bay USWTR site - Left side - (OBISSEAMAP) (OBIS-SEAMAP)

For description see: mclellanw@uncw.edu

http://www.seamap.org/ Data retrieved from 

http://www.iobis.org

UNCW Aerial Surveys for monitoring of proposed 

Oslow Bay USWTR site - Right side - (OBISSEAMAP) (OBIS-SEAMAP)

For description see: mclellanw@uncw.edu

http://www.seamap.org/ Data retrieved from 

http://www.iobis.org

UNCW Marine Mammal Aerial Surveys 2006-2007 For description see: mclellanw@uncw.edu

http://seamap.env.duke.edu/dataset/400/html Data retrieved from

http://www.iobis.org

210
Data Set Description Website/Contact

UNCW Marine Mammal Sightings 2002 University of North Carolina at Wilmington UNCW Marine 

Mammal Sightings, Southeastern US 2002. In: OBIS-SEAMAP . 

OBIS-SEAMAP, http://seamap.env.duke.edu/, 2007-03-26 

16:44:01-05, vector digital data. 

mclellanw@uncw.edu

Data retrieved from 

http://www.iobis.org

UNCW Marine Mammal Sightings, Southeastern US 

1998-1999

University of North Carolina at Wilmington UNCW Marine 

Mammal Sightings, Southeastern US 1998-1999. In: OBISSEAMAP . OBIS-SEAMAP, http://seamap.env.duke.edu/ , 2006-

03-21 17:53:37-05, vector digital data. 

mclellanw@uncw.edu

Data retrieved from 

http://www.iobis.org

UNCW Marine Mammal Sightings, Southeastern US 

2001

University of North Carolina at Wilmington UNCW Marine 

Mammal Sightings, Southeastern US 2001. In: OBIS-SEAMAP . 

OBIS-SEAMAP, http://seamap.env.duke.edu/, 2007-03-26 

16:44:57-05, vector digital data. 

mclellanw@uncw.edu

Data retrieved from

http://www.iobis.org

UNCW Right Whale Aerial Survey 05-06 University of North Carolina at Wilmington UNCW Right Whale 

Aerial Survey 05-06. In: OBIS-SEAMAP . OBIS-SEAMAP, 

http://seamap.env.duke.edu/, 2006-07-11 14:26:21.835383-04, 

vector digital data.

mclellanw@uncw.edu

Data retrieved from

http://www.iobis.org

UNCW Right Whale Aerial Surveys 2008 For description see: mclellanw@uncw.edu

http://seamap.env.duke.edu/dataset/464 Data retrieved from

http://www.iobis.org

USWTR JAX Aerial Survey -Left side- 2009-2010 

(OBIS-SEAMAP) (OBIS-SEAMAP)

William McLellan. 2010. UNCW USWTR JAX Aerial Survey -

Left side- 2009-2010. 

mclellanw@uncw.edu

Data retrieved from

http://www.iobis.org

USWTR Onslow Bay Aerial Survey -Right side2008-2010 (OBIS-SEAMAP) (OBIS-SEAMAP)William McLellan. 2010. UNCW USWTR Onslow Bay Aerial 

Survey -Right side- 2008-2010. 

mclellanw@uncw.edu

Data retrieved from

http://www.iobis.org

211
212

Figure 1.1.1. BOEM Atlantic OCS Planning Areas.
213

Figure 2.1.1. North Atlantic right whale sighting (green squares) and stranding (red 

dots) observations by season. 
214

Figure 2.1.2. North Atlantic right whale critical habitat areas and northeastern 

shipping lanes. 
215

Figure 2.2.1. Blue whales sighting (green squares) observations by season.
216

Figure 2.3.1. Fin whale sighting (green squares), stranding (red dots) and fishery 

by-catch (black stars) observations by season. 
217

Figure 2.4.1. Sei whale sighting (green squares) and stranding (red dots) observations 

of by season.
218

Figure 2.5.1. Minke whale sighting (green squares), stranding (red dots) and fishery bycatch (black stars) observations by season. 
219

Figure 2.6.1. Humpback whale sighting (green squares) and stranding (red dots) 

observations by season.
220

Figure 2.7.1. Sperm whale sighting (green squares) and stranding (red dots) observations 

by season. 
221

Figure 2.8.1. Dwarf and pygmy sperm whale sighting (green squares), stranding (red 

dots) and fishery and fishery by-catch (black stars) observations by 

season.
222

Figure 2.9.1. Cuvier’s beaked whale sighting (green squares) and stranding (red dots) 

observations by season.
223

Figure 2.10.1. Northern bottlenose whale sighting (green squares) and stranding 

(red dots) by season.
224

Figure 2.11.1. Mesoplodon beaked whale sighting (green squares), stranding (red 

dots) and fishery by-catch (black stars) observations by season.
225

Figure 2.12.1. Killer whale sighting (green squares) observations by season. 
226

Figure 2.13.1. Long-finned and undifferentiated pilot whale sighting (green squares), 

stranding (red dots) and fishery by-catch (black stars) observations by 

season.
227

Figure 2.14.1. Short-finned and undifferentiated pilot whale sighting (green 

squares), stranding (red dots) and fishery by-catch (black stars) 

observations by season.
228

Figure 2.15.1. Pygmy killer whale sighting (green squares) and stranding (red dots) 

observations by season.
229

Figure 2.16.1. Melon-headed whale sighting (green squares) and stranding (red dots) 

observations by season.
230

Figure 2.17.1. White-beaked dolphin sighting (green squares), stranding (red dots) and 

fishery by-catch (black stars) observations by season.
231

Figure 2.18.1. White-sided dolphin sighting (green squares), stranding (red dots) and 

fishery by-catch (black stars) observations by season.
232

Figure 2.19.1. Risso’s dolpin sighting (green squares), stranding (red dots) and 

fishery by-catch (black stars) observations by season.
233

Figure 2.20.2. Bottlenose dolphin sighting (green squares), stranding (red dots) and 

fishery by-catch (black stars) observations by season.
234

Figure 2.21.1. Pantropical spotted dolphin sighting (green squares), stranding (red 

dots) and fishery by-catch (black stars) observations by season.
235

Figure 2.22.1. Atlantic spotted dolphin sighting (green squares) and stranding (red 

dots) observations by season.
236

Figure 2.23.1. Spinner dolphin sighting (green squares), stranding (red dots) and 

fishery by-catch (black stars) observations by season.
237

Figure 2.24.1. Rough-toothed dolphin sighting (green squares) and stranding (red 

dots) observations by season.
238

Figure 2.25.1. Clymene dolphin sighting (green squares), stranding (red dots) and 

fishery by-catch (black stars) observations by season.
239

Figure 2.26.1. Striped dolphin sighting (green squares), stranding (red dots) and 

fishery by-catch (black stars) observations by season.
240

Figure 2.27.1. Common dolphin sighting (green squares), stranding (red dots) and 

fishery by-catch (black stars) observations by season.
241

Figure 2.28.2. Fraser’s dolphin sighting (green squares) and stranding (red dots) 

observations by season.
242

Figure 2.29.1. Harbor porpoise sighting (green squares), stranding (red dots) and 

fishery by-catch (black stars) observations by season.
243

Figure 2.29.2. Map of New England closure areas according to the harbor porpoise 

Take Reduction Team.
244

Figure 2.29.3 Map of Mid-Atlantic closure areas according to the harbor porpoise 

Take Reduction Team.
245

Data from http://ocean.floridamarine.org/mrgis/Description_Layers_Marine.htm#marmam

Figure 2.30.1. Manatee Synoptic Count Data 1991-2011.
246

Figure 2.31.1. Harbor seal sighting (green squares), stranding (red dots) and 

fishery by-catch (black stars) observations by season.
247

Data from Whalenet.

Figure 2.31.2. Positions of satellite-tagged harbor seals.
248

Figure 2.32.1. Harp seal stranding (red dots) and fishery by-catch (black stars) 

observations by season.
249

Data from Whalenet.

Figure 2.32.2. Positions of satellite-tagged harp seals.
250

Figure 2.33.1. Gray seal sighting (green squares), stranding (red dots) and fishery 

by-catch (black stars) observations by season.
251

Data from Whalenet.

Figure 2.33.2. Positions of satellite-tagged gray seals.
252

Figure 2.34.1. Hooded seal stranding (red dots) and fishery by-catch (black stars) 

observations by season.
253

Data from Whalenet.

Figure 2.34.2. Positions of satellite-tagged hooded seals.
254

Map from http://www.nmfs.noaa.gov/pr/pdfs/rangemaps/kemps_ridley_turtle.pdf.

Figure 2.35.1. Kemp’s ridley range. 
255

Map from National Marine Fisheries Service et al. (2010).

Figure 2.35.2. Kemp’s ridley nesting locations in 2007. 
256

Data from OBIS.

Figure 2.35.3. Positions of satellite-tagged Kemp’s ridley sea turtles.
257

Figure 2.35.4. Kemp’s ridley sea turtle sighting (green squares) and fishery bycatch (black stars) observations by season.
258

Data from the Sea Turtle Stranding and Salvage Network.

Figure 2.35.5. Kemp’s ridley strandings by zone, 1986-2007. 
259

Data from the Sea Turtle Stranding and Salvage Network.

Figure 2.35.6. Seasonal Kemp’s ridley stranding data for years 2008 and 

2009. 
260

Map from http://www.nmfs.noaa.gov/pr/species/turtles/green.htm#regulations

Figure 2.36.1. Green turtle distribution. 
261

Map from http://research.myfwc.com/features/view_article.asp?id=2496.

Figure 2.36.2. Green turtle nesting densities by county in Florida. 
262

Data from OBIS.

Figure 2.36.3. Positions of satellite-tagged green turtles.
263

Figure 2.36.4. Green sea turtle sighting (green squares) and fishery by-catch (black 

stars) observations by season.
264

Data from the Sea Turtle Stranding and Salvage Network.

Figure 2.36.5. Green turtle strandings by zone, 1986-2007. 
265

Data from the Sea Turtle Stranding and Salvage Network.

Figure 2.36.6. Seasonal green turtle stranding data for years 2008 and 

2009.
266

Map from http://www.nmfs.noaa.gov/pr/pdfs/rangemaps/hawksbill_turtle.pdf.

Figure 2.37.1. Hawksbill global distribution. 
267

Map from http://www.fws.gov/southeast/vbpdfs/species/reptiles/hstu.pdf

Figure 2.37.2. Florida nesting distribution of the hawksbill turtle. 
268

Figure 2.37.3. Hawksbill sea turtle sighting (green squares) and fishery by-catch 

(black stars) observations by season.
269

Data from the Sea Turtle Stranding and Salvage Network.

Figure 2.37.4. Hawksbill strandings by zone, 1986-2007. 
270

Data from the Sea Turtle Stranding and Salvage Network.

Figure 2.37.5. Seasonal hawksbill stranding data for years 2008 and 

2009. 
271

Map from http://www.nmfs.noaa.gov/pr/pdfs/rangemaps/loggerhead_turtle.pdf

Figure 2.38.1. Loggerhead global distribution. 
272

Map from http://research.myfwc.com/features/view_article.asp?id=2411

Figure 2.38.2. Distribution of loggerhead nesting sites in Florida. 
273

Data from OBIS.

Figure 2.38.3. Positions of satellite-tagged loggerhead turtles.
274

Figure 2.38.4. Loggerhead sea turtle sighting (green squares) and fishery bycatch (black stars) observations by season.
275

Data from the Sea Turtle Stranding and Salvage Network.

Figure 2.38.5. Loggerhead strandings by zone, 1986-2007. 
276

Data from the Sea Turtle Stranding and Salvage Network.

Figure 2.38.6. Seasonal loggerhead stranding data for years 2008 and 

2009. 
277

Map from http://www.nmfs.noaa.gov/pr/pdfs/rangemaps/leatherback_turtle.pdf

Figure 2.39.1. Leatherback global distribution. 
278

Map from the Sea Turtle Conservancy (STC). Data and map © STC.

Figure 2.39.2. Selected leatherback tag location data 2005-2009. 
279

Graph from http://research.myfwc.com/images/articles/10690/20100928_143948_17893.jpg

Figure 2.39.3. Leatherback nesting in Florida. 
280

Figure 2.39.4. Leatherback sea turtle sighting (green squares) and fishery bycatch (black stars) observations by season.
281

Data from the Sea Turtle Stranding and Salvage Network.

Figure 2.39.5. Leatherback strandings by zone, 1986-2007. 
282

Data from the Sea Turtle Stranding and Salvage Network.

Figure 2.39.6. Seasonal leatherback stranding data for years 2008 and 

2009. 
283

Figure 2.40.1. BOEM OCS Planning Areas and DoD OPAREAs 3 and Warning 

Areas. 
284

Figure 2.40.2. BOEM OCS North Atlantic Planning Area and DoD OPAREAs 

3 and Warning Areas. 
285

Figure 2.40.3. BOEM OCS Mid-Atlantic Planning Area and DoD OPAREAs 3 and 

Warning Areas. 
286

Figure 2.40.4. BOEM OCS South Atlantic Planning Area and DoD OPAREAs 3 and 

Warning Areas. 
287

Figure 2.40.5. BOEM OCS Eastern Gulf of Mexico and Straits of Florida 

Planning Area and DoD OPAREAs 3 and Warning Areas. 
289

3.0 CURRENT RESEARCH

Table 3.0 

Current Research

(ASSTB&C 2011=31st Annual Symposium on Sea Turtle Biology and Conservation, SMM 2009 = 

Society for Marine Mammology Biennial Conference 2010, RWC2010= Right Whale Consortium 

Meeting 2010)

Species

NAPA

MAPA

SAPA

SFPA

Title Author Institution Email Citation

Balaenoptera 

acutorostrata X

ABUNDANCE, 

DENSITY, AND 

DISTRIBUTION OF 

MARINE MAMMALS 

IN NEW JERSEY'S 

NEARSHORE 

WATERS

Whitt, Amy Geo-Marine, 

Inc.

awhitt@geomarine.comSMM 

2009

Balaenoptera 

acutorostrata X

DETERMINING THE 

SEASONAL 

DISTRIBUTION OF 

CETACEANS IN NEW 

YORK COASTAL 

WATERS USING 

PASSIVE ACOUSTIC 

MONITORING

Biedron, 

Ingrid

Cornell 

University

ib49@cornell

.edu

SMM 

2009

Balaenoptera 

acutorostrata

MEASUREMENTS OF 

MECHANICAL 

PROPERTIES OF 

CETACEAN EARS

Zosuls, 

Aleks

Boston 

University

azosuls@bu.e

du

SMM 

2009

Balaenoptera 

acutorostrata

WAITING TIMES TO 

MONITOR 

MANAGEMENT 

ACTIONS: ATLANTIC 

LARGE WHALES 

SHOW NO RESPONSE 

TO GEAR RULES

Pace, 

Richard

NMFSNEFSCRichard.Pace

@noaa.gov

SMM 

2009

Balaenoptera 

acutorostrata X

WANDERING WHALE 

WATCHES: AN 

ANALYSIS OF DATA 

COLLECTED ON 

WHALE WATCHES 

TRAVELING TO 

STELLWAGEN BANK, 

MA FROM 1994-1997

Koslovsky, 

Stacie

Duke Marine 

Lab

staciekoslovs

ky@gmail.co

m

SMM 

2009
290

Species

NAPA

MAPA

SAPA

SFPA

Title Author Institution Email Citation

Balaenoptera 

borealis X

DETERMINING THE 

SEASONAL 

DISTRIBUTION OF 

CETACEANS IN NEW 

YORK COASTAL 

WATERS USING 

PASSIVE ACOUSTIC 

MONITORING

Biedron, 

Ingrid

Cornell 

University

ib49@cornell

.edu

SMM 

2009

Balaenoptera 

musculus X

DETERMINING THE 

SEASONAL 

DISTRIBUTION OF 

CETACEANS IN NEW 

YORK COASTAL 

WATERS USING 

PASSIVE ACOUSTIC 

MONITORING

Biedron, 

Ingrid

Cornell 

University

ib49@cornell

.edu

SMM 

2009

Balaenoptera 

physalus X

ABUNDANCE, 

DENSITY, AND 

DISTRIBUTION OF 

MARINE MAMMALS 

IN NEW JERSEY'S 

NEARSHORE 

WATERS

Whitt, Amy Geo-Marine, 

Inc.

awhitt@geomarine.comSMM 

2009

Balaenoptera 

physalus X

ANALYSIS OF 

MATERNAL AND 

PATERNAL COANCESTRY OF 

PHOTOGRAPHICALL

Y-IDENTIFIED FIN 

WHALES, 

BALAENOPTERA 

PHYSALUS, IN THE 

GULF OF MAINE.

DenDanto, 

Dan

Univ. of 

Maine -

Orono

dan.dendanto

@umit.maine

.edu

SMM 

2009

Balaenoptera 

physalus X

DETERMINING THE 

SEASONAL 

DISTRIBUTION OF 

CETACEANS IN NEW 

YORK COASTAL 

WATERS USING 

PASSIVE ACOUSTIC 

MONITORING

Biedron, 

Ingrid

Cornell 

University

ib49@cornell

.edu

SMM 

2009

Balaenoptera 

physalus

WAITING TIMES TO 

MONITOR 

MANAGEMENT 

ACTIONS: ATLANTIC 

LARGE WHALES 

SHOW NO RESPONSE 

TO GEAR RULES

Pace, 

Richard

NMFSNEFSCRichard.Pace

@noaa.gov

SMM 

2009

Balaenoptera 

physalus X

WANDERING WHALE 

WATCHES: AN 

ANALYSIS OF DATA 

COLLECTED ON 

WHALE WATCHES 

TRAVELING TO 

STELLWAGEN BANK, 

MA FROM 1994-1997

Koslovsky, 

Stacie

Duke Marine 

Lab

staciekoslovs

ky@gmail.co

m

SMM 

2009
291

Species

NAPA

MAPA

SAPA

SFPA

Title Author Institution Email Citation

Baleanopter 

musculus

MULTIMODAL 

SOMATOSENSORY 

SYSTEM IN 

MYSTICETI 

EXPLAINS 

EXTENDED BODY 

LENGTH AND LONGDISTANCE SOURCE 

SIGNAL 

TRIANGULATION

Eldridge, 

Sherri

Univ. of 

Maine

newblueview

@roadrunner.

com

SMM 

2009

Baleanopter 

physalus X

ASSESSING 

GEOGRAPHIC AND 

ACOUSTIC 

MYSTICETESHIPSTRIKE RISK IN 

THE GULF OF MAINE

Peterson, 

Michael

University of 

Maine

Michael.Peter

son@maine.e

du

SMM 

2009

Baleanopter 

physalus X

DETERMINATION OF 

SPATIO-TEMPORAL 

HABITAT USE BY 

MYSTICETES IN THE 

NORTHEAST GULF 

OF MAINE USING A 

20-YEAR 

OPPORTUNISTIC 

SIGHTING 

DATABASE

Todd, Sean College of 

the Atlantic

stodd@coa.e

du

SMM 

2009

Baleanopter 

physalus X

EVIDENCE FOR 

SPATIAL 

ASSOCIATIONS OF 

SYMPATRIC 

HUMPBACK AND FIN 

WHALES IN THE 

GULF OF MAINE 

USING MONTE 

CARLO 

SIMULATIONS

Lubansky, 

Tanya NJIT tml5@njit.edu

SMM 

2009

Baleanopter 

physalus

MULTIMODAL 

SOMATOSENSORY 

SYSTEM IN 

MYSTICETI 

EXPLAINS 

EXTENDED BODY 

LENGTH AND LONGDISTANCE SOURCE 

SIGNAL 

TRIANGULATION

Eldridge, 

Sherri

Univ. of 

Maine

newblueview

@roadrunner.

com

SMM 

2009

Baleanopter 

physalus X

UTILIZING THREE 

DECADES OF 

INDIVIDUAL 

PHOTOGRAPHICIDENTIFICATION 

DATA OF FINBACK 

WHALES 

(BALAENOPTERA 

PHYSALUS) IN THE 

WESTERN NORTH 

ATLANTIC

Vashro, 

Courtney

College of 

the Atlantic

vashrocourtn

ey@yahoo.co

m

SMM 

2009
292

Species

NAPA

MAPA

SAPA

SFPA

Title Author Institution Email Citation

Caretta 

caretta X

A FISHERIES 

RELATED SEA 

TURTLE UNUSUAL 

MORTALITY EVENT 

IN NORTHAMPTON 

COUNTY, VIRGINIA, 

USA: A REPORT OF 

STRANDING 

ACTIVITY, 

NECROPSY FINDINGS 

AND FISHING 

EFFORTS

Christina 

Trapani

Virginia 

Aquarium 

Stranding 

Response 

Program, 

Virginia 

Beach, 

Virginia

mytwodolphi

ns@hotmail.c

om

ASSTB&

C 2011

Caretta 

caretta X

BEACH 

RESTORATION AND 

ITS EFFECT ON 

LOGGERHEAD SEA 

TURTLE HATCHLING 

FITNESS IN FLORIDA

Mario Mota

University of 

Central 

Florida, 

Orlando

mario.mota@

yahoo.com

ASSTB&

C 2011

Caretta 

caretta X

BEST MANAGEMENT 

PRACTICE DESIGN 

CRITERIA FOR 

HOPPER 

DREDGE/SEA 

TURTLE FRIENDLY 

BORROW SITES

Bates Phillip

US Army 

Corps of 

Engineers, 

Jacksonville, 

FL

phillip.c.bates

@usace.army

.mil

ASSTB&

C 2011

Caretta 

caretta X

CORRECTED 

LOGGERHEAD 

(CARETTA CARETTA) 

SEA TURTLE 

POPULATION 

DENSITY AND 

ABUNDANCE 

ESTIMATES IN 

ESTUARINE AND 

COASTAL WATERS 

OF NORTH 

CAROLINA, USA

Joanne 

BraunMcNeill

SEFSC 

Beaufort 

Laboratory

joanne.b.mcn

eill@noaa.go

v

ASSTB&

C 2011

Caretta 

caretta X

DETERMINING THE 

IMPACTS OF BEACH 

RESTORATION ON 

LOGGERHEAD 

(CARETTA CARETTA) 

AND GREEN TURTLE 

(CHELONIA MYDAS) 

NESTING AND 

REPRODUCTIVE 

SUCCESS ALONG 

FLORIDA’S 

ATLANTIC COAST

Allison Hays

University of 

Central 

Florida, 

Orlando, 

Florida

allison.w.hay

s@gmail.com

ASSTB&

C 2011
293

Species

NAPA

MAPA

SAPA

SFPA

Title Author Institution Email Citation

Caretta 

caretta X

EFFECTS OF ROCK 

ARMORING 

STRUCTURES AND 

DUNE QUALITY ON 

THE NESTING 

PATTERNS OF THE 

LOGGERHEAD SEA 

TURTLE ON JEKYLL 

ISLAND, GEORGIA

Christina 

Martin

Georgia Sea 

Turtle 

Center, 

Jekyll Island, 

Georgia

christina_mar

tin1@live.co

m

ASSTB&

C 2011

Caretta 

caretta X

ENTANGLEMENT OF 

SEA TURTLES IN 

VERTICAL LINES OF 

FIXED GEAR 

FISHERIES: A 

SUMMARY OF THE 

GEOGRAPHIC 

RANGE, 

SEASONALITY, 

INVOLVED SPECIES 

AND NATURE OF 

REPORTED 

ENTANGLEMENT 

EVENTS IN THE 

NORTHEAST REGION 

OF THE UNITED 

STATES

Kate 

Sampson

NOAA 

Fisheries 

Service 

Northeast 

Region, 

Gloucester, 

MA,

kate.sampson

@noaa.gov

ASSTB&

C 2011

Caretta 

caretta X

EVALUATING SEA 

TURTLE INJURIES IN 

NORTHEAST REGION 

FISHING GEAR, USA

Carrie Upite

NMFS, 

Northeast 

Regional 

Office, 

Gloucester, 

Massachuset

ts

carrie.upite@

noaa.gov

ASSTB&

C 2011

Caretta 

caretta X

EVALUATION OF A 

TURTLE EXCLUDER 

DEVICE (TED) 

DESIGNED FOR USE 

IN THE U.S. MIDATLANTIC 

ATLANTIC CROAKER 

FISHERY

Jeff Gearhart SEFSC jeff.gearhart

@noaa.gov

ASSTB&

C 2011

Caretta 

caretta

EXPLORING 

DENSITYDEPENDENCE IN 

LOGGERHEAD, 

CARETTA CARETTA, 

POPULATION 

VIABILITY 

ANALYSIS

Elena 

Finkbeiner

Duke 

University 

Marine Lab, 

Beaufort, 

North 

Carolina

efinkbeiner@

seaturtle.org

ASSTB&

C 2011
294

Species

NAPA

MAPA

SAPA

SFPA

Title Author Institution Email Citation

Caretta 

caretta

EXPONENTIAL 

GROWTH OF NEST 

PRODUCTION ON A 

“LOGGERHEAD 

BEACH”: GREEN 

TURTLES AND 

LEATHERBACKS ON 

THE ARCHIE CARR 

NATIONAL WILDLIFE 

REFUGE, FL, USA

Christopher 

Long

University of 

Central 

Florida

clong@knigh

ts.ucf.edu

ASSTB&

C 2011

Caretta 

caretta X

FORAGING 

ECOLOGY OF 

LEATHERBACK SEA 

TURTLES IN THE 

WESTERN NORTH 

ATLANTIC 

DETERMINED 

THROUGH MULTITISSUE STABLE 

ISOTOPE ANALYSES

Kara Dwyer 

Dodge

Large 

Pelagics 

Research 

Center, 

University of 

New 

Hampshire

kara.dodge@

unh.edu

ASSTB&

C 2011

Caretta 

caretta X X

FORAGING HABITAT 

USE BY MALE 

LOGGERHEAD 

TURTLES AS 

REVEALED BY 

STABLE ISOTOPES

Mariela 

Pajuelo

Department 

of Biology 

and Archie 

Carr Center 

for Sea 

Turtle 

Research. 

University of 

Florida

mariela.pajue

lo@gmail.co

m

ASSTB&

C 2011

Caretta 

caretta X

GENETIC MARKRECAPTURE OF THE 

FEMALE 

LOGGERHEAD 

POPULATION 

NESTING IN 

GEORGIA, 2008-2009: 

ABUNDANCE, NEST 

SITE FIDELITY AND 

RELATEDNESS

Brian 

Shamblin

Warnell 

School of 

Forestry and 

Natural 

Resources, 

University of 

Georgia

brianshm@ug

a.edu

ASSTB&

C 2011

Caretta 

caretta X X

HARDWIRED FOR 

NAVIGATION: HOW 

AN INHERITED 

MAGNETIC MAP 

GUIDES YOUNG 

LOGGERHEADS ON 

THEIR FIRST 

TRANSOCEANIC 

MIGRATION

Kenneth 

Lohmann

University of 

North 

Carolina, 

Chapel Hill

klohmann@e

mail.unc.edu

ASSTB&

C 2011
295

Species

NAPA

MAPA

SAPA

SFPA

Title Author Institution Email Citation

Caretta 

caretta X X X

HOOKING POSITION 

AS A FUNCTION OF 

HOOK SIZE, BAIT 

TYPE, AND TURTLE 

SIZE IN 

LOGGERHEAD 

TURTLES (CARETTA 

CARETTA) 

INCIDENTALLY 

CAPTURED IN THE 

U.S. ATLANTIC 

PELAGIC LONGLINE 

FISHERY

Lesley 

Stokes SEFSC lesley.stokes@noaa.gov

ASSTB&

C 2011

Caretta 

caretta X X X

IDENTIFYING 

MIGRATORY 

PATHWAYS AND 

FORAGING HABITAT 

USE BY 

LOGGERHEAD 

TURTLES (CARETTA 

CARETTA) NESTING 

ON FLORIDA’S EAST 

COAST

Dan Evans

Sea Turtle 

Conservancy

, Gainesville, 

Florida

drevans@con

serveturtles.o

rg

ASSTB&

C 2011

Caretta 

caretta X

INFERRING VESSEL 

CHARACTERISTICS 

FROM WOUNDS ON 

STRANDED SEA 

TURTLES: CAN WE 

APPLY THE 

MANATEE METHOD?

Susan Barco

Virginia 

Aquarium & 

Marine 

Science 

Center 

Foundation 

Research & 

Conservation 

Division

sgbarco@virg

iniaaquarium.

com

ASSTB&

C 2011

Caretta 

caretta X

INITIAL 

INVESTIGATIONS OF 

VITAMIN D3 IN 

DISPLAY AND 

REHABILITATION 

SEA TURTLES

Shane 

Boylan

South 

Carolina 

Aquarium

drshaneboyla

n@gmail.co

m

ASSTB&

C 2011

Caretta 

caretta X

INTERACTIONS 

BETWEEN SEA 

TURTLES AND 

DREDGE GEAR IN 

THE U.S. SEA 

SCALLOP FISHERY, 

2001-2008

Kimberly 

Murray

Northeast 

Fisheries 

Science 

Center

kimberly.mur

ray@noaa.go

v

ASSTB&

C 2011

Caretta 

caretta X

INVESTIGATING THE 

UTILITY OF GROUND 

PENETRATING 

RADAR FOR SEATURTLE NEST 

DETECTION

Christopher 

Hintz

Savannah 

State 

University, 

Savannah

hintzc@savan

nahstate.edu

ASSTB&

C 2011
296

Species

NAPA

MAPA

SAPA

SFPA

Title Author Institution Email Citation

Caretta 

caretta X X

INVESTIGATION OF 

SEA TURTLE 

UNUSUAL 

MORTALITY EVENTS 

IN THE EASTERN 

UNITED STATES: 

2001-2010

Brian Stacy

Marine 

Animal 

Disease 

Laboratory, 

University of 

Florida

stacyb@vetm

ed.ufl.edu

ASSTB&

C 2011

Caretta 

caretta X

JANUARY 2010 COLD 

STUN: TURTLES IN 

THE NORTH 

CENTRAL INDIAN 

RIVER LAGOON AND 

FATE OF 60 TURTLES 

SUBSEQUENTLY 

TRACKED

Jane 

Provancha

Kennedy 

Space Center

jane.a.provan

cha@nasa.go

v

ASSTB&

C 2011

Caretta 

caretta X

LOGGERHEAD SEA 

TURTLE (CARETTA 

CARETTA) 

INTERACTIONS WITH 

U.S. MID-ATLANTIC 

BOTTOM TRAWL 

GEAR FOR FISH AND 

SCALLOPS, 2005-2008

Melissa 

Warden NEFSC melissa.warden@noaa.gov

ASSTB&

C 2011

Caretta 

caretta X X

LOGGERHEAD 

SPECIALIZATION 

REVEALED BY 

STABLE ISOTOPE 

ANALYSIS

Hannah 

Vander 

Zanden

Department 

of Biology 

and Archie 

Carr Center 

for Sea 

Turtle 

Research. 

University of 

Florida

hvz@ufl.edu ASSTB&

C 2011

Caretta 

caretta X

LOGGERHEADS 

(CARETTA CARETTA) 

ON THE RISE? 

NESTING IN THE 

ARCHIE CARR NWR, 

FLORIDA, USA IN

2010

Cheryl 

Sanchez

University of 

Central 

Florida, 

Orlando, 

Florida

cheryl.lynn.sa

nchez@gmail

.com

ASSTB&

C 2011

Caretta 

caretta X

LONG-TERM STUDY 

OF LOGGERHEAD 

SEA TURTLE 

HATCHLING SEX 

RATIOS ON TWO 

GEORGIA BARRIER 

ISLANDS (2000-2010)

Kris 

Williams

Caretta 

Research 

Project, 

Savannah, 

GA

wassawcrp@

aol.com

ASSTB&

C 2011

Caretta 

caretta X

MAMMALIAN 

PREDATION OF SEA 

TURTLE NESTS IN 

BOCA RATON, FLFIFTEEN YEARS OF 

STUDY AND THE 

EFFECTIVENESS OF 

USING HABENERO 

PEPPER POWDER 

FOR CONTROL

Kirt Rusenko

Gumbo 

Limbo 

Naure 

Center

rusenkoki@a

ol.com

ASSTB&

C 2011
297

Species

NAPA

MAPA

SAPA

SFPA

Title Author Institution Email Citation

Caretta 

caretta X

MARYLAND, USA: A 

20 YEAR SUMMARY 

OF DEAD SEA 

TURTLE 

STRANDINGS

Jamie Testa

Maryland 

Department 

of Natural 

Resources, 

Oxford, 

Maryland

jschofield@d

nr.state.md.us

ASSTB&

C 2011

Caretta 

caretta X

MEDICAL AND 

SURGICAL 

MANAGEMENT OF 

WOUNDS IN MARINE 

TURTLES

Terry Norton

Georgia Sea 

Turtle 

Center, 

Jekyll Island

tnmynahvet@

aol.com

ASSTB&

C 2011

Caretta 

caretta X

MULTIPLE 

PATERNITY WITHIN 

THE NORTHERN 

SUBPOPULATION OF 

LOGGERHEAD SEA 

TURTLE (CARETTA 

CARETTA)

Jacob Lasala

Georgia 

Southern 

University,

jlasala321@g

mail.com

ASSTB&

C 2011

Caretta 

caretta X

NEST 

TEMPERATURES 

AND HATCHLING 

SEX RATIOS FROM 

LOGGERHEAD 

TURTLE NESTS 

INCUBATED UNDER 

NATURAL FIELD 

CONDITIONS IN 

GEORGIA, USA

Anne Marie 

LeBlanc

Georgia 

Southern 

University, 

Statesboro, 

Georgia

annemarielb

@juno.com

ASSTB&

C 2011

Caretta 

caretta X X X X

ORGANOHALOGEN 

CONTAMINANT 

CONCENTRATIONS 

VARY IN ADULT 

MALE 

LOGGERHEADS 

BASED ON 

MIGRATION 

PATTERNS

Jennifer 

Keller

College of 

Charleston

jennifer.keller

@noaa.gov

ASSTB&

C 2011

Caretta 

caretta X

PHOTOGRAPHIC 

IDENTIFICATION OF 

SEA TURTLES IN THE 

ESTUARINE WATERS 

OF NORTH 

CAROLINA, USA

Mary 

Goodman

SEFSC 

Beaufort 

Laboratory, 

Beaufort, 

NC

april.goodma

n@noaa.gov

ASSTB&

C 2011

Caretta 

caretta

QUANTUM LIGHT 

MEASUREMENT TO 

AID ASSESSMENT OF 

ANTHROPOGENIC 

AND NATURAL 

LIGHT INFLUENCES 

ON SEA TURTLE 

NESTING, TYBEE 

ISLAND, GA

Ana Reyes

Savannah 

State 

University, 

Savannah, 

Georgia

areyes@stude

nt.savannahst

ate.edu

ASSTB&

C 2011
298

Species

NAPA

MAPA

SAPA

SFPA

Title Author Institution Email Citation

Caretta 

caretta X

RECORD HIGH 

BEACH 

TEMPERATURES: 

IMPLICATIONS FOR 

LOGGERHEAD 

TURTLE (CARETTA 

CARETTA) HATCH 

AND EMERGENCE 

SUCCESS IN BOCA 

RATON, FLORIDA, 

USA

Micah 

Rogers

Florida 

Atlantic 

University, 

Boca Raton, 

Florida

micahm.roger

s@gmail.com

ASSTB&

C 2011

Caretta 

caretta X

RELATING NESTING 

FEMALE BODY SIZE 

TO CLUTCH SIZE, 

NESTING 

FREQUENCY, AND 

HATCHING SUCCESS 

IN LOGGERHEAD 

SEA TURTLES, 

CARETTA CARETTA, 

AT JEKYLL ISLAND, 

GEORGIA, USA

Joseph 

Scarola

Georgia Sea 

Turtle 

Center, 

Jekyll Island, 

Georgia

jscarola8@ho

tmail.com

ASSTB&

C 2011

Caretta 

caretta X X

REPORT ON A 

MASSIVE 

HYPOTHERMIC 

STUNNING EVENT 

OF SEA TURTLES IN 

FLORIDA DURING 

JANUARY 2010

Allen Foley

Florida Fish 

and Wildlife 

Conservation 

Commission, 

Fish and 

Wildlife 

Research 

Institute

allen.foley@

myfwc.com

ASSTB&

C 2011

Caretta 

caretta X X

SATELLITE 

TRACKING 

CONFIRMS THE USE 

OF STABLE 

ISOTOPES TO INFER 

FORAGING 

GROUNDS OF 

LOGGERHEAD 

TURTLES (CARETTA 

CARETTA) NESTING 

ON FLORIDA’S EAST 

COAST

Simona 

Ceriani

University of 

Central 

Florida, 

Orlando

simona.cerian

i@gmail.com

ASSTB&

C 2011

Caretta 

caretta X X

SATELLITE 

TRACKING THE SEA 

TURTLE “LOST 

YEARS”

Kate 

Mansfield

Southeast 

Fisheries 

Science 

Center

kate.mansfiel

d@noaa.gov

ASSTB&

C 2011

Caretta 

caretta X

SEA TURTLE NEST 

MANAGEMENT: 

EXAMINING THE USE 

OF RELOCATION AS 

A MANAGEMENT 

TOOL ON THREE 

SOUTH CAROLINA 

BEACHES, USA

Gretchen 

Coll

College of 

Charleston, 

Charleston, 

South 

Carolina

babyruth2414

@yahoo.com

ASSTB&

C 2011
299

Species

NAPA

MAPA

SAPA

SFPA

Title Author Institution Email Citation

Caretta 

caretta X

SEA TURTLES AND 

OCEAN ENERGY 

TECHNOLOGY

Erin 

McMichael

Florida 

Atlantic 

University, 

Boca Raton, 

Florida

emcmich@ho

tmail.com

ASSTB&

C 2011

Caretta 

caretta X

SEASONAL 

VARIATION IN EGG 

SIZE IN THE 

LOGGERHEAD SEA 

TURTLE: RESOURCE 

PARTITIONING IN 

THE NESTING 

FEMALE

Ketan Patel

Georgia 

Southern 

University

patelkv@hen

drix.edu

ASSTB&

C 2011

Caretta 

caretta X

SURVIVAL OF 

IMMATURE 

LOGGERHEAD 

TURTLES (CARETTA 

CARETTA) IN THE 

INDIAN RIVER 

LAGOON, FL, USA

Andrew 

Sterner

University of 

Central 

Florida, 

Orlando, FL

asterner816@

yahoo.com

ASSTB&

C 2011

Caretta 

caretta X

THE EFFECT OF AIR 

TEMPERATURE ON 

THE INCUBATION 

PERIOD AND 

HATCHING SUCCESS 

OF LOGGERHEAD 

SEA TURTLE 

(CARETTA CARETTA) 

CLUTCHES IN 

BROWARD COUNTY, 

FLORIDA

L. Teal 

Kawana

Nova 

Southeastern 

University 

Oceanograph

ic Center

ltkawana@g

mail.com

ASSTB&

C 2011

Caretta 

caretta X X

TWO CASES OF 

REHABILITATED 

LOGGERHEAD 

(CARETTA CARETTA) 

SEA TURTLES 

SURVIVING IN THE 

WILD AFTER 

RELEASE

Kelly 

Thorvalson

South 

Carolina 

Aquarium, 

Charleston, 

SC

kthorvalson@

scaquarium.o

rg

ASSTB&

C 2011

Caretta 

caretta X

USING GIS TO 

DETERMINE THE 

EFFECT OF 

SKYGLOW ON 

NESTING SEA 

TURTLES OVER A 

TEN YEAR PERIOD

Kirt Rusenko

Gumbo 

Limbo 

Nature 

Center, Boca 

Raton

rusenkoki@a

ol.com

ASSTB&

C 2011

Caretta 

caretta X

UTILIZATION OF 

TESTOSTERONE RIA 

TO EVALUATE THE 

SEX RATIO OF 

JUVENILE

LOGGERHEADS 

INHABITING THE 

ATLANTIC COASTAL 

WATERS OF 

FLORIDA

Jennifer 

Estes Layton

Samford 

University, 

Birmingham, 

AL

jestes@uab.e

du

ASSTB&

C 2011
300

Species

NAPA

MAPA

SAPA

SFPA

Title Author Institution Email Citation

Caretta 

caretta X

VERTICAL HABITAT 

UTILIZATION OF 

IMMATURE 

LOGGERHEAD SEA 

TURTLES (CARETTA 

CARETTA) IN U.S. 

MID-ATLANTIC 

SHELF WATERS

Heather 

Haas

Northeast 

Fisheries 

Science 

Center

heather.haas

@noaa.gov

ASSTB&

C 2011

Chelonia 

mydas X X

448 TURTLES IN THE 

FREEZER: NECROPSY 

AND POPULATION 

ASSESSMENT OF 

GREEN SEA TURTLES 

STRANDED DEAD IN 

ST. JOSEPH BAY, 

FLORIDA, USA, 

DURING THE 

JANUARY 2010 MASS 

COLD-STUNNING

Larisa Avens

SEFSC 

Beaufort 

Laboratory

larisa.avens@

noaa.gov

ASSTB&

C 2011

Chelonia 

mydas X

DETERMINING THE 

IMPACTS OF BEACH 

RESTORATION ON 

LOGGERHEAD 

(CARETTA CARETTA) 

AND GREEN TURTLE 

(CHELONIA MYDAS) 

NESTING AND 

REPRODUCTIVE 

SUCCESS ALONG 

FLORIDA’S 

ATLANTIC COAST

Allison Hays

University of 

Central 

Florida, 

Orlando, 

Florida

allison.w.hay

s@gmail.com

ASSTB&

C 2011

Chelonia 

mydas X

ENTANGLEMENT OF 

SEA TURTLES IN 

VERTICAL LINES OF 

FIXED GEAR 

FISHERIES: A 

SUMMARY OF THE 

GEOGRAPHIC 

RANGE, 

SEASONALITY, 

INVOLVED SPECIES 

AND NATURE OF 

REPORTED 

ENTANGLEMENT 

EVENTS IN THE 

NORTHEAST REGION 

OF THE UNITED 

STATES

Kate 

Sampson

NOAA 

Fisheries 

Service 

Northeast 

Region, 

Gloucester, 

MA,

kate.sampson

@noaa.gov

ASSTB&

C 2011

Chelonia 

mydas X X

INVESTIGATION OF 

SEA TURTLE 

UNUSUAL 

MORTALITY EVENTS 

IN THE EASTERN 

UNITED STATES: 

2001-2010

Brian Stacy

Marine 

Animal 

Disease 

Laboratory, 

University of 

Florida

stacyb@vetm

ed.ufl.edu

ASSTB&

C 2011
301

Species

NAPA

MAPA

SAPA

SFPA

Title Author Institution Email Citation

Chelonia 

mydas X

JANUARY 2010 COLD 

STUN: TURTLES IN 

THE NORTH 

CENTRAL INDIAN 

RIVER LAGOON AND 

FATE OF 60 TURTLES 

SUBSEQUENTLY 

TRACKED

Jane 

Provancha

Kennedy 

Space Center

jane.a.provan

cha@nasa.go

v

ASSTB&

C 2011

Chelonia 

mydas X

MARYLAND, USA: A 

20 YEAR SUMMARY 

OF DEAD SEA 

TURTLE 

STRANDINGS

Jamie Testa

Maryland 

Department 

of Natural 

Resources, 

Oxford, 

Maryland

jschofield@d

nr.state.md.us

ASSTB&

C 2011

Chelonia 

mydas X

MEDICAL AND 

SURGICAL 

MANAGEMENT OF 

WOUNDS IN MARINE 

TURTLES

Terry Norton

Georgia Sea 

Turtle 

Center, 

Jekyll Island

tnmynahvet@

aol.com

ASSTB&

C 2011

Chelonia 

mydas X

PHOTOGRAPHIC 

IDENTIFICATION OF 

SEA TURTLES IN THE 

ESTUARINE WATERS 

OF NORTH 

CAROLINA, USA

Mary 

Goodman

SEFSC 

Beaufort 

Laboratory, 

Beaufort, 

NC

april.goodma

n@noaa.gov

ASSTB&

C 2011

Chelonia 

mydas X X

REPORT ON A 

MASSIVE 

HYPOTHERMIC 

STUNNING EVENT 

OF SEA TURTLES IN 

FLORIDA DURING 

JANUARY 2010

Allen Foley

Florida Fish 

and Wildlife 

Conservation 

Commission, 

Fish and 

Wildlife 

Research 

Institute

allen.foley@

myfwc.com

ASSTB&

C 2011

Chelonia 

mydas X

SEA TURTLES AND 

OCEAN ENERGY 

TECHNOLOGY

Erin 

McMichael

Florida 

Atlantic 

University, 

Boca Raton, 

Florida

emcmich@ho

tmail.com

ASSTB&

C 2011

Chelonia 

mydas X

SUN COMPASS 

ORIENTATION BY 

JUVENILE GREEN 

SEA TURTLES 

(CHELONIA MYDAS)

Cody Mott

Gumbo 

Limbo 

Nature 

Center, Boca 

Raton

codyrmott@h

otmail.com

ASSTB&

C 2011

Chelonia 

mydas X

TIMING AND 

PATHWAYS OF FALL 

MIGRATION FOR 

JUVENILE GREEN 

SEA TURTLES IN 

BACK AND CORE 

SOUNDS, NORTH 

CAROLINA

Amanda 

Southwood

University of 

North 

Carolina 

Wilmington

southwooda

@uncw.edu

ASSTB&

C 2011
302

Species

NAPA

MAPA

SAPA

SFPA

Title Author Institution Email Citation

Chelonia 

mydas X X

USE OF TRACE 

ELEMENTS TO INFER 

POPULATION 

CONNECTIVITY IN 

MARINE 

ENVIRONMENTS: 

GETTING THE GOOD 

FROM THE BAD

Melania 

Cecilia 

Lopez Castro

Department 

of Biology 

and Archie 

Carr Center 

for Sea 

Turtle 

Research. 

University of 

Florida

melania_lope

z@yahoo.co

m.mx

ASSTB&

C 2011

Chelonia 

mydas X

USING GIS TO 

DETERMINE THE 

EFFECT OF 

SKYGLOW ON 

NESTING SEA 

TURTLES OVER A 

TEN YEAR PERIOD

Kirt Rusenko

Gumbo 

Limbo 

Nature 

Center, Boca 

Raton

rusenkoki@a

ol.com

ASSTB&

C 2011

Cystophora 

cristata X

CHARACTERISTICS 

OF PHOCID SEAL 

BYCATCH IN NEW 

ENGLAND 

FISHERIES.

Belden, 

Dana

Office of 

Naval 

Research

dana.belden.c

tr@navy.mil

SMM 

2009

Cystophora 

cristata X

HARP SEAL (PHOCA 

GROENLANDICA) 

AND HOODED SEAL 

(CYSTOPHORA 

CRISTATA) TRENDS 

IN ABUNDANCE IN 

THE NORTHERN 

GULF OF MAINE, 

USA FROM 1994-2009.

Seton, 

Rosemary

College of 

the Atlantic

rseton@coa.e

du

SMM 

2009

Delphinus 

delphis X

ABUNDANCE, 

DENSITY, AND 

DISTRIBUTION OF 

MARINE MAMMALS 

IN NEW JERSEY'S 

NEARSHORE 

WATERS

Whitt, Amy Geo-Marine, 

Inc.

awhitt@geomarine.comSMM 

2009

Delphinus 

delphis

ACOUSTIC 

ANALYSIS OF 

WHISTLE 

CHARACTERISTICS 

OF DELPHINID 

SPECIES IN THE NW 

ATLANTIC.

Schiebel, 

Hayley

NOVA 

Southeastern 

University

hayhay121@

hotmail.com

SMM 

2009

Dermochleys 

coriacea X X X X

UNDERWATER 

HEARING 

SENSITIVITY IN THE 

LEATHERBACK SEA 

TURTLE 

(DERMOCHELYS 

CORIACEA): 

ASSESSING THE 

POTENTIAL EFFECT 

OF ANTHROPOGENIC 

NOISE (NT-10-X33)

Michael 

Rasser

Wider 

Caribbean 

Sea Turtle 

Conservation 

Network 

(Widecast)

Michael.Rass

er@boemre.g

ov?subject=U

nderwater%2

0Hearing%20

Sensitivity%2

0in%20the%

20Leatherbac

k%20Sea%20

Turtle

http://ww

w.boemre.

gov/eppd/

PDF/EPP

DStudies/

Leatherbac

k_Sea_Tur

tle_Audio

gram.pdf
303

Species

NAPA

MAPA

SAPA

SFPA

Title Author Institution Email Citation

Dermochleys 

coriacea X

ENTANGLEMENT OF 

SEA TURTLES IN 

VERTICAL LINES OF 

FIXED GEAR 

FISHERIES: A 

SUMMARY OF THE 

GEOGRAPHIC 

RANGE, 

SEASONALITY, 

INVOLVED SPECIES 

AND NATURE OF 

REPORTED 

ENTANGLEMENT 

EVENTS IN THE 

NORTHEAST REGION 

OF THE UNITED 

STATES

Kate 

Sampson

NOAA 

Fisheries 

Service 

Northeast 

Region, 

Gloucester, 

MA,

kate.sampson

@noaa.gov

ASSTB&

C 2011

Dermochleys 

coriacea X

INFERRING VESSEL 

CHARACTERISTICS 

FROM WOUNDS ON 

STRANDED SEA 

TURTLES: CAN WE 

APPLY THE 

MANATEE METHOD?

Susan Barco

Virginia 

Aquarium & 

Marine 

Science 

Center 

Foundation 

Research & 

Conservation 

Division

sgbarco@virg

iniaaquarium.

com

ASSTB&

C 2011

Dermochleys 

coriacea X

MEDICAL AND 

SURGICAL 

MANAGEMENT OF 

WOUNDS IN MARINE 

TURTLES

Terry Norton

Georgia Sea 

Turtle 

Center, 

Jekyll Island

tnmynahvet@

aol.com

ASSTB&

C 2011

Dermochleys 

coriacea X

SEA TURTLES AND 

OCEAN ENERGY 

TECHNOLOGY

Erin 

McMichael

Florida 

Atlantic 

University, 

Boca Raton, 

Florida

emcmich@ho

tmail.com

ASSTB&

C 2011

Dermochlys 

coriacea X

MARYLAND, USA: A 

20 YEAR SUMMARY 

OF DEAD SEA 

TURTLE 

STRANDINGS

Jamie Testa

Maryland 

Department 

of Natural 

Resources, 

Oxford, 

Maryland

jschofield@d

nr.state.md.us

ASSTB&

C 2011

Dermochlys 

coriacea X X

SELENIUM SAVES 

THE DAY: FIRST 

EXPLANATION FOR 

DECREASED HATCH 

AND EMERGENCE 

SUCCESS IN 

LEATHERBACK SEA 

TURTLES 

(DERMOCHELYS 

CORIACEA)-

LESSONS LEARNED 

FROM TWO 

POPULATIONS

Justin 

Perrault

Florida 

Atlantic 

University

jperrau2@fau

.edu

ASSTB&

C 2011
304

Species

NAPA

MAPA

SAPA

SFPA

Title Author Institution Email Citation

Eretmochleys 

imbricata X

A COMPARISON OF 

HAWKSBILL TURTLE 

SITE OCCUPANCY 

BETWEEN NATURAL 

AND ARTIFICIAL 

REEFS IN PALM 

BEACH COUNTY, FL, 

USA

Suzanne 

Nuttall

Green 

Mountain 

College,

Poultney, 

VT

suzannenuttal

l@hotmail.co

m

ASSTB&

C 2011

Eretmochleys 

imbricata

AMPHIBIOUS 

HEARING IN 

HATCHLING 

HAWKSBILL SEA 

TURTLES 

(ERETMOCHELYS 

IMBRICATA)

Wendy Dow 

Piniak

Duke 

University 

Marine Lab

wed3@duke.

edu

ASSTB&

C 2011

Eretmochleys 

imbricata X

GPS- LINKED 

SATELLITE 

TELEMETRY OF 

HAWKSBILL 

TURTLES 

(ERETMOCHELYS 

IMBRICATA) IN 

PALM BEACH 

COUNTY, FLORIDA, 

USA

Lawrence 

Wood

Zoological 

Society of 

the Palm 

Beaches

wood9794@b

ellsouth.net

ASSTB&

C 2011

Eretmochleys 

imbricata X

JANUARY 2010 COLD 

STUN: TURTLES IN 

THE NORTH 

CENTRAL INDIAN 

RIVER LAGOON AND 

FATE OF 60 TURTLES 

SUBSEQUENTLY 

TRACKED

Jane 

Provancha

Kennedy 

Space Center

jane.a.provan

cha@nasa.go

v

ASSTB&

C 2011

Eretmochleys 

imbricata X X

REPORT ON A 

MASSIVE 

HYPOTHERMIC 

STUNNING EVENT 

OF SEA TURTLES IN 

FLORIDA DURING 

JANUARY 2010

Allen Foley

Florida Fish 

and Wildlife 

Conservation 

Commission, 

Fish and 

Wildlife 

Research 

Institute

allen.foley@

myfwc.com

ASSTB&

C 2011

Eretmochleys 

imbricata X

SEA TURTLES AND 

OCEAN ENERGY 

TECHNOLOGY

Erin 

McMichael

Florida 

Atlantic 

University, 

Boca Raton, 

Florida

emcmich@ho

tmail.com

ASSTB&

C 2011

Eretmochleys 

imbricata X

USING GIS TO 

DETERMINE THE 

EFFECT OF 

SKYGLOW ON 

NESTING SEA 

TURTLES OVER A 

TEN YEAR PERIOD

Kirt Rusenko

Gumbo 

Limbo 

Nature 

Center, Boca 

Raton

rusenkoki@a

ol.com

ASSTB&

C 2011
305

Species

NAPA

MAPA

SAPA

SFPA

Title Author Institution Email Citation

Eubalaena 

glacialis X

A MODEL OF 

ENTANGLEMENT 

RISK FOR LOBSTER 

FISHING GEAR OFF 

THE COAST OF 

MAINE

Chris 

Brehme

Keene State 

College

cbrehme@ke

ene.edu RWC2010

Eubalaena 

glacialis X

A NEW ANALYSIS 

TESTING THE 

LIKELIHOOD OF 

JORDAN BASIN 

BEING A MATING 

GROUND FOR RIGHT 

WHALES

Tim Cole

Northeast 

Fisheries 

Science 

Center

Tim.Cole@n

oaa.gov

RWC2010

Eubalaena 

glacialis X X

AMBIENT NOISE 

LEVELS AND 

ACOUSTIC ECOLOGY 

OF NORTH 

ATLANTIC RIGHT 

WHALE HABITATS

Charles A. 

Muirhead

Cornell 

Bioacoustics 

Research 

Program

cam236@cor

nell.edu RWC2010

Eubalaena 

glacialis X

BEHAVIORAL 

DIFFERENCES OF 

FORAGING NORTH 

ATLANTIC RIGHT 

AND HUMPBACK 

WHALES IN APRIL 

2009 AND 2010

Susan E. 

Parks

Appl. Res. 

Lab., Penn 

State, State 

College, PA

sep20@psu.e

du RWC2010

Eubalaena 

glacialis X

COMPARATIVE 

ANALYSIS OF THE 

OCCURRENCE AND 

SEASONALITY 

PATTERNS OF 

NORTH ATLANTIC 

RIGHT WHALE CALL 

TYPES IN THE 

NORTHWEST 

ATLANTIC

Sarah 

Mussoline

WHOI/ 

Northeast 

Fisheries 

Science 

Center

sarah.mussoli

ne@noaa.gov

RWC2010

Eubalaena 

glacialis X

COMPUTER 

MODELING OF 

WHALE 

ENTANGLEMENT

Laurens E. 

Howle

Duke 

University 

Department 

of 

Mechanical 

Engineering 

and 

Materials 

Science

laurens.howle

@duke.edu RWC2010

Eubalaena 

glacialis X

CORRELATION OF 

ZOOPLANKTON

PREY ABUNDANCE 

AND DISTRIBUTION 

WITH THE 

BEHAVIOR OF 

TAGGED RIGHT 

WHALES IN CAPE 

COD BAY DURING 

SPRING 2010

Joseph D. 

Warren

School of 

Marine and 

Atmospheric 

Sciences, 

Stonybrook 

University

joe.warren@s

tonybrook.ed

u

RWC2010
306

Species

NAPA

MAPA

SAPA

SFPA

Title Author Institution Email Citation

Eubalaena 

glacialis X

CURRENT GEAR 

RESEARCH AND 

COMPLIANCE RATES 

WITHIN THE MAINE 

COASTAL LOBSTER 

FISHERY

Erin 

Summers

Maine 

Division of 

Marine 

Resources

erin.l.summer

s@maine.gov RWC2010

Eubalaena 

glacialis X

DETERMINING THE 

ABSOLUTE 

PROBABILITY OF 

LETHAL VESSELSTRIKES TO NORTH 

ATLANTIC RIGHT 

WHALES, 

EUBALAENA 

GLACIALIS, IN THE 

ROSEWAY BASIN 

REGION OF THE 

SCOTIAN SHELF

Julie van der 

Hoop WHOI jvanderhoop@whoi.edu RWC2010

Eubalaena 

glacialis X

ENTANGLEMENT 

SEVERITY RELATED 

TO ROPE 

CHARACTERISTICS 

FOR NORTH 

ATLANTIC RIGHT 

WHALES

Amy 

Knowlton

New 

England 

Aquarium

aknowlton@n

eaq.org

RWC2010

Eubalaena 

glacialis X

ESTIMATED 

ABSORBANCE 

SPECTRA OF THE 

VISUAL PIGMENTS 

OF THE NORTH 

ATLANTIC RIGHT 

WHALE 

(EUBALAENA 

GLACIALIS) AND 

THEIR POTENTIAL 

ROLE IN DETECTING 

CONCENTRATIONS 

OF THE CALANOID 

COPEPOD CALANUS 

FINMARCHICUS

Jeffry I. 

Fasick

Kean 

University

jfasick@kean

.edu RWC2010

Eubalaena 

glacialis X

FINE-SCALE 

SWIMMING 

KINEMATICS OF 

NORTH ATLANTIC 

RIGHT WHALES: 

USING LOCOMOTOR 

GAITS TO 

DETERMINE 

VARIATIONS IN 

ENERGY 

EXPENDITURE

Anna E. 

McGregor

Duke 

University

anna.mcgrego

r@alumni.du

ke.edu

RWC2010
307

Species

NAPA

MAPA

SAPA

SFPA

Title Author Institution Email Citation

Eubalaena 

glacialis X

FIRST USE OF A 

CUTTING 

BROADHEAD TO 

RESOLVE A RIGHT 

WHALE 

ENTANGLEMENT: A 

NOVEL TOOL TO 

DIVERSIFY 

DISENTANGLEMENT 

OPTIONS AND 

ENHANCE 

RESPONDER SAFETY

Scott Landry PCCS

sclandry@co

astalstudies.o

rg

RWC2010

Eubalaena 

glacialis X

GAUGING EFFECTS 

OF ANTHROPOGENIC 

MORTALITY 

REDUCTION ON 

NORTH ATLANTIC 

RIGHT WHALE 

RECOVERY: A WHAT 

IF PVA

Richard M. 

Pace, III.

Northeast 

Fisheries 

Science 

Center

Richard.Pace

@noaa.gov

RWC2010

Eubalaena 

glacialis X

HOW MUCH IS 

ENOUGH? 

ESTIMATING THE 

NUTRITIONAL 

REQUIREMENTS OF 

NORTH ATLANTIC 

RIGHT WHALES 

WITH A 

GENERALIZED 

BIOENERGETICS 

MODEL

Sarah 

Fortune

Marine 

Mammal 

Research 

Unit, 

University of 

British 

Columbia

s.fortune@fis

heries.ubc.ca RWC2010

Eubalaena 

glacialis X

METHODOLOGY OF 

COASTAL MAINE 

LOBSTER FISHERY 

GEAR 

CONFIGURATION 

DATA COLLECTION

Heather 

Tetreault

Maine 

Lobstermens 

Association

heather@mai

nelobstermen.

org

RWC2010

Eubalaena 

glacialis X

MONITORING RIGHT 

WHALE 

DISTRIBUTION AND 

HABITAT IN THE 

OUTER FALL REGION 

WEST OF JORDAN 

BASIN DURING LATE 

AUTUMN WITH 

AUTONOMOUS 

VEHICLES

Mark 

Baumgartner WHOI mbaumgartner@whoi.edu RWC2010
308

Species

NAPA

MAPA

SAPA

SFPA

Title Author Institution Email Citation

Eubalaena 

glacialis X

NORTHERN 

ATLANTIC RIGHT 

WHALE UPCALLS: 

UNDERSTANDING 

CALL 

CHARACTERISTICS, 

PATTERNS AND 

BEHAVIORAL 

ECOLOGY AT 

DIFFERENT SPATIAL 

AND TEMPORAL 

SCALES

Sofie Van 

Parijs

Northeast 

Fisheries 

Science 

Center

sofie.vanparij

s@noaa.gov RWC2010

Eubalaena 

glacialis X

OBSERVATIONS OF A 

NORTH ATLANTIC 

RIGHT WHALE 

(EUBALAENA 

GLACIALIS) BIRTH 

OFFSHORE OF THE 

PROTECTED 

SOUTHEAST U.S. 

CRITICAL HABITAT

Heather 

Foley

Duke 

University

Heather.Fole

y@duke.edu RWC2010

Eubalaena 

glacialis X

OCEAN FLOOR 

ENCOUNTERS BY 

RIGHT WHALES: 

IMPLICATIONS FOR 

ENTANGLEMENT 

RISK FROM FISHING 

GEAR

Scott D. 

Kraus

New 

England 

Aquarium

skraus@neaq RWC2010

Eubalaena 

glacialis X

OUTREACH AND 

EDUCATION TO 

INCREASE VESSEL 

COMPLIANCE AND 

COMMITMENT IN 

THE CAPE COD BAY 

AND OFF RACE 

POINT RIGHT WHALE 

SEASONAL 

MANAGEMENT 

AREAS

David Wiley

Stellwagen 

Bank Natl. 

Marine 

Sanctuary

David.Wiley

@noaa.gov RWC2010

Eubalaena 

glacialis X

PASSIVE ACOUSTIC 

MONITORING: 

MOTHER-CALF 

PAIRS IN THE 

SOUTHEAST UNITED 

STATES UNLIKELY 

TO BE DETECTED

James H.W. 

Hain

Associated 

Scientists at 

Woods Hole

jhain@earthli

nk.net RWC2010

Eubalaena 

glacialis X

ROSEWAY BASIN 

RIGHT WHALE 

CRITICAL HABITAT: 

SPACE-TIME 

VARIATION IN THE 

PREY-FIELD AND 

ASSOCIATED WATER 

MASS 

CHARACTERISTICS

Kimberley 

Davies

Dalhousie 

University

kim.davies@

dal.ca RWC2010
309

Species

NAPA

MAPA

SAPA

SFPA

Title Author Institution Email Citation

Eubalaena 

glacialis X

SINKING 

GROUNDLINE 

REPERCUSSIONS IN 

MAINE’S LOBSTER 

INDUSTRY

Laura 

Ludwig

Maine 

Division of 

Marine 

Resources

laura.ludwig

@maine.gov RWC2010

Eubalaena 

glacialis X

THE GROSS 

MORPHOLOGY OF 

THE MELON IN A 

NEONATE RIGHT 

WHALE 

(EUBALAENA 

GLACIALIS)

Cally Harper Brown 

University

caroline_harp

er@brown.ed

u

RWC2010

Eubalaena 

glacialis X

THE INFLUENCE OF 

COPEPOD DIEL 

VERTICAL 

MIGRATION ON 

COMPETITION 

BETWEEN RIGHT 

WHALES AND 

ZOOPLANKTIVOROU

S FISH

Mark 

Baumgartner WHOI mbaumgartner@whoi.edu RWC2010

Eubalaena 

glacialis X

THE RIGHT (AND 

WRONG) WAYS TO 

PROTECT RIGHT 

WHALES

Sierra 

Weaver

Defenders of 

Wildlife

sweaver@def

enders.org RWC2010

Eubalaena 

glacialis X

VESSEL 

COMPLIANCE AND 

COMMITMENT IN 

THE CAPE COD BAY 

AND OFF RACE 

POINT RIGHT WHALE 

SEASONAL 

MANAGEMENT 

AREAS

Michael 

Thompson

Stellwagen 

Bank Natl. 

Marine 

Sanctuary

michael.a.tho

mpson@noaa

.gov

RWC2010

Eubalaena 

glacialis X

VESSEL 

COMPLIANCE WITH 

RIGHT WHALE 

PROTECTION 

MEASURES IN THE 

SOUTHEASTERN U.S. 

SEASONAL 

MANAGEMENT 

AREA DURING THE 

2009-2010 CALVING 

SEASON

Joel G. 

Ortega-Ortiz

Florida 

Wildlife 

Research 

Institute

joelgortega@

gmail.com RWC2010

Eubalaena 

glacialis X

ABUNDANCE, 

DENSITY, AND 

DISTRIBUTION OF 

MARINE MAMMALS 

IN NEW JERSEY'S 

NEARSHORE 

WATERS

Whitt, Amy Geo-Marine, 

Inc.

awhitt@geomarine.comSMM 

2009
310

Species

NAPA

MAPA

SAPA

SFPA

Title Author Institution Email Citation

Eubalaena 

glacialis X

ASSESSING 

GEOGRAPHIC AND 

ACOUSTIC 

MYSTICETESHIPSTRIKE RISK IN 

THE GULF OF MAINE

Peterson, 

Michael

University of 

Maine

Michael.Peter

son@maine.e

du

SMM 

2009

Eubalaena 

glacialis X

ASSESSING LONGTERM FORAGING IN 

NORTH ATLANTIC 

RIGHT WHALES 

WITH 

BIOGEOCHEMICAL 

TRACERS.

Lysiak, 

Nadine WHOI nlysiak@whoi.edu

SMM 

2009

Eubalaena 

glacialis

CHEMICAL 

SEDATION OF 

ENTANGLED RIGHT 

WHALES TO 

ENHANCE 

DISENTANGLEMENT 

EFFORTS

Smith, 

Jamison

NMFSNEROJamison.Smit

h.noaa.gov

SMM 

2009

Eubalaena 

glacialis X

DETERMINATION OF 

SPATIO-TEMPORAL 

HABITAT USE BY 

MYSTICETES IN THE 

NORTHEAST GULF 

OF MAINE USING A 

20-YEAR 

OPPORTUNISTIC 

SIGHTING 

DATABASE

Todd, Sean College of 

the Atlantic

stodd@coa.e

du

SMM 

2009

Eubalaena 

glacialis X

DETERMINING THE 

SEASONAL 

DISTRIBUTION OF 

CETACEANS IN NEW 

YORK COASTAL 

WATERS USING 

PASSIVE ACOUSTIC 

MONITORING

Biedron, 

Ingrid

Cornell 

University

ib49@cornell

.edu

SMM 

2009

Eubalaena 

glacialis X X X X

GIARDIA AND 

CRYPTOSPORIDIUM 

IN NORTH ATLANTIC 

AND SOUTHERN 

RIGHT WHALES 

(EUBALAENA 

GLACIALIS AND E. 

AUSTRALIS)

Rolland, Roz NEAq rrolland@nea

q.org

SMM 

2009
311

Species

NAPA

MAPA

SAPA

SFPA

Title Author Institution Email Citation

Eubalaena 

glacialis X

LIVE STRANDING OF 

A SUB-ADULT 

NORTH ATLANTIC 

RIGHT WHALE 

(EUBALAENA 

GLACIALIS) WITH 

EVIDENCE OF 

CHRONIC 

VERTEBRAL 

COLUMN RESPONSE 

TO LINE 

ENTANGLEMENT

McLellan, 

William

UNC 

Wilmington

mclellanw@u

ncw.edu

SMM 

2009

Eubalaena 

glacialis X

NEAR REALTIME 

SPECIES 

DISTRIBUTION 

MODELING OF 

NORTH ATLANTIC 

RIGHT WHALE 

HABITAT

Pendleton, 

Daniel

Cornell 

University

dep22@corne

ll.edu

SMM 

2009

Eubalaena 

glacialis X X

NORTH ATLANTIC 

RIGHT WHALE 

(EUBALAENA 

GLACIALIS) 

SIGHTINGS IN THE 

US MID-ATLANTIC 

AND SOUTHEAST 

ATLANTIC BIGHT 

(VIRGINIA THROUGH 

SOUTH CAROLINA) 

FROM 2001-2008

Pabst, D. 

Ann

UNC 

Wilmington

pabsta@uncw

.edu

SMM 

2009

Eubalaena 

glacialis X

POPULATION 

TRENDS IN NORTH 

ATLANTIC RIGHT 

WHALES: WHY 

HAVEN'T THEY 

INCREASED LIKE 

EUBALAENA 

AUSTRALIS?.

Kraus, Scott NEAq skraus@neaq.

org

SMM 

2009

Eubalaena 

glacialis X

POPULATION 

TRENDS IN NORTH 

ATLANTIC RIGHT 

WHALES: WHY 

HAVEN'T THEY 

INCREASED LIKE 

EUBALAENA 

AUSTRALIS?.

Good, 

Caroline 

Paddock

Duke Marine 

Lab

cpg2@duke.e

du

SMM 

2009

Eubalaena 

glacialis X X X X

REDUCING NORTH 

ATLANTIC RIGHT 

WHALE SHIP 

STRIKES—THE US 

EXPERIENCE

Merrick, 

Richard

NMFSNEFSC

Richard.Merr

ick@noaa.go

v

SMM 

2009
312

Species

NAPA

MAPA

SAPA

SFPA

Title Author Institution Email Citation

Eubalaena 

glacialis

WAITING TIMES TO 

MONITOR 

MANAGEMENT 

ACTIONS: ATLANTIC 

LARGE WHALES 

SHOW NO RESPONSE 

TO GEAR RULES

Pace, 

Richard

NMFSNEFSCRichard.Pace

@noaa.gov

SMM 

2009

Globicephala 

macrorhynchu

s

ACOUSTIC 

ANALYSIS OF 

WHISTLE 

CHARACTERISTICS 

OF DELPHINID 

SPECIES IN THE NW 

ATLANTIC.

Schiebel, 

Hayley

Nova 

Southeastern 

U.

hayhay121@

hotmail.com

SMM 

2009

Globicephala 

macrorhynchu

s

X

DISCRIMINATING 

BETWEEN FREERANGING LONGFINNED 

(GLOBICEPHALA 

MELAS) AND SHORTFINNED 

(GLOBICEPHALAMA

CRORHYNCHUS) 

PILOT WHALES OFF 

THE EAST COAST OF 

THE UNITED STATES

Rone, 

Brenda

NOAANEFSCBrenda.Rone

@noaa.gov

SMM 

2009

Globicephala 

macrorhynchu

s

X

FORAGING 

ECOLOGY OF 

SHORT-FINNED 

PILOT WHALES OFF 

CAPE HATTERAS, 

NORTH CAROLINA, 

USA AND 

OBSERVATIONS OF 

INTERACTIONS WITH 

THE PELAGIC 

LONGLINE FISHERY

Urian, Kim Duke Marine 

Lab

kurian@ec.rr.

com

SMM 

2009

Globicephala 

macrorhynchu

s

X

ODONTOCETE 

VOCALIZATIONS IN 

ONSLOW BAY, 

NORTH CAROLINA: 

INTEGRATING DATA 

FROM TWO PASSIVE 

ACOUSTIC 

TECHNIQUES

Williams, 

Lynne

Duke Marine 

Lab

lw32@duke.e

du

SMM 

2009

Globicephala 

melas X

DISCRIMINATING 

BETWEEN FREERANGING LONGFINNED 

(GLOBICEPHALA 

MELAS) AND SHORTFINNED 

(GLOBICEPHALAMA

CRORHYNCHUS) 

PILOT WHALES OFF 

THE EAST COAST OF 

THE UNITED STATES

Rone, 

Brenda

NOAANEFSCBrenda.Rone

@noaa.gov

SMM 

2009
313

Species

NAPA

MAPA

SAPA

SFPA

Title Author Institution Email Citation

Grampus 

griseus

ACOUSTIC 

ANALYSIS OF 

WHISTLE 

CHARACTERISTICS 

OF DELPHINID 

SPECIES IN THE NW 

ATLANTIC.

Schiebel, 

Hayley

Nova 

Southeastern 

U.

hayhay121@

hotmail.com

SMM 

2009

Grampus 

griseus X

AERIAL AND VESSEL 

SURVEYS OF THE 

UNDERSEA 

WARFARE TRAINING 

RANGE SITE 

ALTERNATIVE IN 

ONSLOW BAY, NC, 

USA

Nilsson, 

Peter

UNC 

Wilmington

nilssonp@un

cw.edu

SMM 

2009

Halichoerus 

grypus

X

AN INCREASE IN 

GRAY SEAL 

(HALICHOERUS 

GRYPUS) SIGHTINGS 

AND STRANDINGS IN 

NEW YORK WATERS.

DiGiovanni, 

Robert

Riverhead 

Fdn for 

Marine Res 

& Pres

rdigiovanni@

riverheadfoun

dation.org

SMM 

2009

Halichoerus 

grypus

X

AN INCREASE IN THE 

NUMBER OF GRAY 

SEAL (HALICHOERUS 

GRYPUS) PUPS 

OBSERVED IN U.S. 

WATERS BETWEEN 

1994 AND 2008: REESTABLISHMENT OF 

FORMER PUPPING 

SITES

Wood, 

Stephanie

Umass. 

Boston

Stephanie.Wo

od@noaa.gov

SMM 

2009

Halichoerus 

grypus

X

CHARACTERISTICS 

OF PHOCID SEAL 

BYCATCH IN NEW 

ENGLAND 

FISHERIES.

Belden, 

Dana

Office of 

Naval 

Research

dana.belden.c

tr@navy.mil

SMM 

2009

Halichoerus 

grypus

X

ESTIMATING 

MARINE MAMMAL 

CONSUMPTION OF 

COMMERCIALLY 

AND ECOLOGICALLY 

IMPORTANT PREY 

SPECIES ON THE 

NORTHEAST US 

CONTINENTAL 

SHELF

Col, Laurel NOAANEFSC

Laurel.Col.@

noaa.gov

SMM 

2009
314

Species

NAPA

MAPA

SAPA

SFPA

Title Author Institution Email Citation

Halichoerus 

grypus

X

PHOTOGRAPHIC 

SURVEYS OF 

ENTANGLEMENT 

OCCURRENCE AT 

GRAY SEAL 

(HALICHOERUS 

GRYPUS) AND 

HARBOR SEAL 

(PHOCA VITULINA) 

HAUL-OUTS ON 

CAPE COD, 

MASSACHUSETTS

Sette, Lisa PCCS sette@coastal

studies.org

SMM 

2009

Halichoerus 

grypus

X

THE DIET OF GRAY 

SEALS 

(HALICHOERUS 

GRYPUS) IN UNITED 

STATES WATERS, 

ESTIMATED FROM 

SCATS, STOMACH 

SAMPLES AND 

FATTY ACID 

PROFILES

Ampela, 

Kristen

CUNYStaen Islandkrs10a@gmai

l.com

SMM 

2009

Kogia spp. X X X X

ANALYSIS AND 

REVIEW OF KOGIA 

STRANDING DATA 

FROM THE EAST 

COAST OF THE 

UNITED STATES 

(1994-2008): WHAT 

CAN IT TELL US AND 

WHAT ARE WE 

MISSING?

Litz, Jenny NOAASEFSC

Jenny.Litz@n

oaa.gov

SMM 

2009

Kogia spp. X

CORRELATIONS 

BETWEEN 

OCEANOGRAPHIC 

VARIABLES AND 

KOGIA STRANDINGS 

IN FLORIDA

Cordero, 

Vincent

Nova 

Southeastern 

U.

vcordero@no

va.edu,

SMM 

2009

Kogia spp. X X X

DOMOIC ACID 

EXPOSURE IN 

PYGMY AND DWARF 

SPERM WHALES 

(KOGIA SPP.) FROM 

SOUTHEASTERN 

AND MID-ATLANTIC 

U.S. WATERS

Fire, Spencer NOAA-NOS Spencer.Fire

@noaa.gov

SMM 

2009

Kogia spp.

FIRST ASSESSMENT 

OF PYGMY AND 

DWARF SPERM 

WHALES (KOGIA 

SPP.) STOCK 

STRUCTURE IN THE 

NORTHWESTERN 

ATLANTIC AND 

NORTHERN GULF OF 

MEXICO

Viricel, 

Amelia

University of 

Louisiana

viricel@louis

iana.edu

SMM 

2009
315

Species

NAPA

MAPA

SAPA

SFPA

Title Author Institution Email Citation

Lagenorhynch

us acutus X

HABITAT 

PREFERENCES OF 

WHITE-SIDED 

DOLPHINS IN THE 

NORTHWEST 

ATLANTIC

Palka, 

Deborah

NOAANEFSCDebra.Palka

@noaa.gov

SMM 

2009

Lepidochelys 

kempii X

A FISHERIES 

RELATED SEA 

TURTLE UNUSUAL 

MORTALITY EVENT 

IN NORTHAMPTON 

COUNTY, VIRGINIA, 

USA: A REPORT OF 

STRANDING 

ACTIVITY, 

NECROPSY FINDINGS 

AND FISHING 

EFFORTS

Christina 

Trapani

Virginia 

Aquarium 

Stranding 

Response 

Program, 

Virginia 

Beach, 

Virginia

mytwodolphi

ns@hotmail.c

om

ASSTB&

C 2011

Lepidochelys 

kempii X

DETERMINING THE 

IMPACTS OF BEACH 

RESTORATION ON 

LOGGERHEAD 

(CARETTA CARETTA) 

AND GREEN TURTLE 

(CHELONIA MYDAS) 

NESTING AND 

REPRODUCTIVE 

SUCCESS ALONG 

FLORIDA’S 

ATLANTIC COAST

Allison Hays

University of 

Central 

Florida, 

Orlando, 

Florida

allison.w.hay

s@gmail.com

ASSTB&

C 2011

Lepidochelys 

kempii X

INFERRING VESSEL 

CHARACTERISTICS 

FROM WOUNDS ON 

STRANDED SEA 

TURTLES: CAN WE 

APPLY THE 

MANATEE METHOD?

Susan Barco

Virginia 

Aquarium & 

Marine 

Science 

Center 

Foundation 

Research & 

Conservation 

Division

sgbarco@virg

iniaaquarium.

com

ASSTB&

C 2011

Lepidochelys 

kempii X X

INVESTIGATION OF 

SEA TURTLE 

UNUSUAL

MORTALITY EVENTS 

IN THE EASTERN 

UNITED STATES: 

2001-2010

Brian Stacy

Marine 

Animal 

Disease 

Laboratory, 

University of 

Florida

stacyb@vetm

ed.ufl.edu

ASSTB&

C 2011

Lepidochelys 

kempii X

MARYLAND, USA: A 

20 YEAR SUMMARY 

OF DEAD SEA 

TURTLE 

STRANDINGS

Jamie Testa

Maryland 

Department 

of Natural 

Resources, 

Oxford, 

Maryland

jschofield@d

nr.state.md.us

ASSTB&

C 2011

Lepidochelys 

kempii X

MEDICAL AND 

SURGICAL 

MANAGEMENT OF 

WOUNDS IN MARINE 

TURTLES

Terry Norton

Georgia Sea 

Turtle 

Center, 

Jekyll Island

tnmynahvet@

aol.com

ASSTB&

C 2011
316

Species

NAPA

MAPA

SAPA

SFPA

Title Author Institution Email Citation

Lepidochelys 

kempii X

PHOTOGRAPHIC 

IDENTIFICATION OF 

SEA TURTLES IN THE 

ESTUARINE WATERS 

OF NORTH 

CAROLINA, USA

Mary 

Goodman

SEFSC 

Beaufort 

Laboratory, 

Beaufort, 

NC

april.goodma

n@noaa.gov

ASSTB&

C 2011

Lepidochelys 

kempii X X

REPORT ON A 

MASSIVE 

HYPOTHERMIC 

STUNNING EVENT 

OF SEA TURTLES IN 

FLORIDA DURING 

JANUARY 2010

Allen Foley

Florida Fish 

and Wildlife 

Conservation 

Commission, 

Fish and 

Wildlife 

Research 

Institute

allen.foley@

myfwc.com

ASSTB&

C 2011

Lepidochelys 

kempii X

SEA TURTLES AND 

OCEAN ENERGY 

TECHNOLOGY

Erin 

McMichael

Florida 

Atlantic 

University, 

Boca Raton, 

Florida

emcmich@ho

tmail.com

ASSTB&

C 2011

Megaptera 

novaeangliea

A NOVEL ANALYSIS 

OF HIERACHICAL 

STRUCTURE IN 

HUMPBACK WHALE 

(MEGAPTERA 

NOVAEANGLIAE) 

SONG

Handel, 

Stephen

Univ. of 

Tenessee, 

Knoxville

stephen.hand

el@gmail.co

m

SMM 

2009

Megaptera 

novaeangliea X

ABUNDANCE, 

DENSITY, AND 

DISTRIBUTION OF 

MARINE MAMMALS 

IN NEW JERSEY'S 

NEARSHORE 

WATERS

Whitt, Amy Geo-Marine, 

Inc.

awhitt@geomarine.comSMM 

2009

Megaptera 

novaeangliea X

ASSESSING 

GEOGRAPHIC AND 

ACOUSTIC 

MYSTICETESHIPSTRIKE RISK IN 

THE GULF OF MAINE

Peterson, 

Michael

University of 

Maine

Michael.Peter

son@maine.e

du

SMM 

2009

Megaptera 

novaeangliea X

DETERMINATION OF 

DIVING BEHAVIORS 

OF HUMPBACK 

WHALES 

(MEGAPTERA 

NOVAEANGLIAE), 

OVER ROCKY 

BOTTOM HABITATS 

USING DTAGS

Summers, 

Erin Maine DMR erin.l.summers@maine.gov

SMM 

2009
317

Species

NAPA

MAPA

SAPA

SFPA

Title Author Institution Email Citation

Megaptera 

novaeangliea X

DETERMINATION OF 

SPATIO-TEMPORAL 

HABITAT USE BY 

MYSTICETES IN THE 

NORTHEAST GULF 

OF MAINE USING A 

20-YEAR 

OPPORTUNISTIC 

SIGHTING 

DATABASE

Todd, Sean College of 

the Atlantic

stodd@coa.e

du

SMM 

2009

Megaptera 

novaeangliea X

DETERMINING THE 

SEASONAL 

DISTRIBUTION OF 

CETACEANS IN NEW 

YORK COASTAL 

WATERS USING 

PASSIVE ACOUSTIC 

MONITORING

Biedron, 

Ingrid

Cornell 

University

ib49@cornell

.edu

SMM 

2009

Megaptera 

novaeangliea X

EVIDENCE FOR 

SPATIAL 

ASSOCIATIONS OF 

SYMPATRIC 

HUMPBACK AND FIN 

WHALES IN THE 

GULF OF MAINE 

USING MONTE 

CARLO 

SIMULATIONS

Lubansky, 

Tanya NJIT tml5@njit.edu

SMM 

2009

Megaptera

novaeangliea X

HUMPBACK WHALE 

(MEGAPTERA 

NOVAEANGLIAE) 

SONG OCCURS 

EXTENSIVELY ON A 

FEEDING GROUND IN 

THE 

NORTHWESTERN 

ATLANTIC OCEAN

Vu, 

Elizabeth 

Tram-Anh

NMFSNEFSC

jeepurs@gma

il.com

SMM 

2009

Megaptera 

novaeangliea X

HUMPBACK WHALE 

(MEGAPTERA 

NOVAEANGLIEA) 

CALF AGE- AND SEXRELATED 

BEHAVIORAL 

PATTERNS: 

IMPLICATIONS FOR 

SPECIES 

MANAGEMENT

Zoidis, Ann 

Margaret

CETOS 

Research 

Org.

ann@cetosres

earch.org

SMM 

2009

Megaptera 

novaeangliea X X X X

MOVEMENT 

PATTERNS OF 

NORTH ATLANTIC 

HUMPBACK WHALES 

(MEGAPTERA 

NOVAEANGLIAE) 

IDENTIFIED AT 

BERMUDA

Beaudette, 

Adrianna

College of 

the Atlantic

abeaudette@c

oa.edu

SMM 

2009
318

Species

NAPA

MAPA

SAPA

SFPA

Title Author Institution Email Citation

Megaptera 

novaeangliea

MULTIMODAL 

SOMATOSENSORY 

SYSTEM IN 

MYSTICETI 

EXPLAINS 

EXTENDED BODY 

LENGTH AND LONGDISTANCE SOURCE 

SIGNAL 

TRIANGULATION

Eldridge, 

Sherri

Univ. of 

Maine

newblueview

@roadrunner.

com

SMM 

2009

Megaptera 

novaeangliea X

NEITHER CONSORT 

NOR KIN: 

MOLECULAR 

ECOLOGY OF A 

LONG-TERM 

ASSOCIATION 

BETWEEN FEEDING 

HUMPBACK WHALES 

(MEGAPTERA 

NOVAEANGLIAE)

Tackaberry, 

Jennifer

Whale 

Center of 

N.E.

jenn@whalec

enter.org

SMM 

2009

Megaptera 

novaeangliea X

NOT ALL 

ENTANGLEMENTS 

ARE CREATED 

EQUAL

Landry, 

Scott PCCS

sclandry@co

astalstudies.o

rg

SMM 

2009

Megaptera 

novaeangliea X

SUMMER HABITAT 

OF HUMPBACK 

WHALES 

(MEGAPTERA 

NOVAEANGLIAE) 

THROUGHOUT THE 

NORTH ATLANTIC 

OCEAN

VignessRaposa, 

Kathleen

University of 

Rhode Island

kvigness@aol

.com

SMM 

2009

Megaptera 

novaeangliea X

UNDERWATER 

KINEMATICS OF 

BUBBLE FEEDING 

HUMPBACK WHALES 

(MEGAPTERA 

NOVAEANGLIAE)

Wiley, David Stellwagen 

Bank NMS

David.Wiley

@noaa.gov

SMM 

2009

Megaptera 

novaeangliea

WAITING TIMES TO 

MONITOR 

MANAGEMENT 

ACTIONS: ATLANTIC 

LARGE WHALES 

SHOW NO RESPONSE 

TO GEAR RULES

Pace, 

Richard

NMFSNEFSCRichard.Pace

@noaa.gov

SMM 

2009

Megaptera 

novaeangliea X

WANDERING WHALE 

WATCHES: AN 

ANALYSIS OF DATA 

COLLECTED ON 

WHALE WATCHES 

TRAVELING TO 

STELLWAGEN BANK, 

MA FROM 1994-1997

Koslovsky, 

Stacie

Duke Marine 

Lab

staciekoslovs

ky@gmail.co

m

SMM 

2009
319

Species

NAPA

MAPA

SAPA

SFPA

Title Author Institution Email Citation

Pagophilus 

groenlandicus X

CHARACTERISTICS 

OF PHOCID SEAL 

BYCATCH IN NEW 

ENGLAND 

FISHERIES.

Belden, 

Dana

Office of 

Naval 

Research

dana.belden.c

tr@navy.mil

SMM 

2009

Phoca vitulina X

ABUNDANCE, 

DENSITY, AND 

DISTRIBUTION OF 

MARINE MAMMALS 

IN NEW JERSEY'S 

NEARSHORE 

WATERS

Whitt, Amy Geo-Marine, 

Inc.

awhitt@geomarine.comSMM 

2009

Phoca vitulina X

CHARACTERISTICS 

OF PHOCID SEAL 

BYCATCH IN NEW 

ENGLAND 

FISHERIES.

Belden, 

Dana

Office of 

Naval 

Research

dana.belden.c

tr@navy.mil

SMM 

2009

Phoca vitulina X

MARINE 

CONSERVATION: 

ASSESSING 

THREATS, AND 

CHARACTERIZING 

HABITATS OF 

HARBOR SEALS 

(PHOCA VITULINA 

CONCOLOR; 

PHOCIDAE) IN 

SOUTHERN NEW 

JERSEY (USA).

Slocum, 

Carol*

The Richard 

Stockton 

College of 

New Jersey

*Michael 

Davenport

SMM 

2009

Phoca vitulina X

PHOTOGRAPHIC 

SURVEYS OF 

ENTANGLEMENT 

OCCURRENCE AT 

GRAY SEAL

(HALICHOERUS 

GRYPUS) AND 

HARBOR SEAL 

(PHOCA VITULINA) 

HAUL-OUTS ON 

CAPE COD, 

MASSACHUSETTS

Sette, Lisa PCCS sette@coastal

studies.org

SMM 

2009

Phocoena 

phocoena X

ABUNDANCE, 

DENSITY, AND 

DISTRIBUTION OF 

MARINE MAMMALS 

IN NEW JERSEY'S 

NEARSHORE 

WATERS

Whitt, Amy Geo-Marine, 

Inc.

awhitt@geomarine.comSMM 

2009

Phocoena 

phocoena X

EVALUATING BIAS 

WHEN ESTIMATING 

SMALL CETACEAN 

BYCATCH 

MORTALITY IN 

GILLNET FISHERIES 

USING DIFFERENT 

UNITS OF EFFORT

Rossman, 

Marjorie

NOAANEFSC

Marjorie.Ros

sman@noaa.

gov

SMM 

2009
320

Species

NAPA

MAPA

SAPA

SFPA

Title Author Institution Email Citation

Phocoena 

phocoena X

HARBOUR PORPOISE 

(PHOCOENA 

PHOCOENA) 

PRESENCE 

PATTERNS AT AN 

AQUACULTURE 

CAGE SITE IN THE 

BAY OF FUNDY, 

CANADA

Haar, Marthe

University of 

New 

Brunswick

mhaarr@hot

mail.com

SMM 

2009

Physeter 

macrocephalu

s

BIG BANGS FROM A 

BIG NOSE: 

BIOMECHANICS OF 

AIR DRIVEN SOUND 

PRODUCTION IN 

SPERM WHALES

Madsen, 

Peter

Aarhus U., 

Denmark

peter.madsen

@biology.au.

dk

SMM 

2009

Physeter 

macrocephalu

s

X X X x

DEVELOPMENT OF A 

PREDICTIVE 

HORIZONTAL 

HABITAT MODEL 

FOR SPERM AND 

PILOT WHALES IN 

THE NORTHWEST 

ATLANTIC OCEAN

Cross, 

Cheryl 

Lynne

Nova 

Southeastern 

U.

ccross@nova.

edu

SMM 

2009

Physeter 

macrocephalu

s

X

ODONTOCETE 

VOCALIZATIONS IN 

ONSLOW BAY, 

NORTH CAROLINA: 

INTEGRATING DATA 

FROM TWO PASSIVE 

ACOUSTIC 

TECHNIQUES

Williams, 

Lynne

Duke Marine 

Lab

lw32@duke.e

du

SMM 

2009

Physeter 

macrocephalu

s

X

USING PASSIVE 

ACOUSTICS TO 

MONITOR THE 

PRESENCE OF 

ODONTOCETE 

CETACEANS DURING 

NAVAL EXERCISES 

IN ONSLOW BAY, NC

Kumar, 

Anurag

Naval 

Facilities 

Engineering 

Command 

Atlantic

anurag.kumar

@navy.mil

SMM 

2009

Stenella 

coeruleoalba

ACOUSTIC 

ANALYSIS OF 

WHISTLE 

CHARACTERISTICS 

OF DELPHINID 

SPECIES IN THE NW 

ATLANTIC.

Schiebel, 

Hayley

Nova 

Southeastern 

University

hayhay121@

hotmail.com

SMM 

2009

Stenella 

frontalis

ACOUSTIC 

ANALYSIS OF 

WHISTLE 

CHARACTERISTICS 

OF DELPHINID 

SPECIES IN THE NW 

ATLANTIC.

Schiebel, 

Hayley

Nova 

Southeastern 

U.

hayhay121@

hotmail.com

SMM 

2009
321

Species

NAPA

MAPA

SAPA

SFPA

Title Author Institution Email Citation

Stenella 

frontalis X

AERIAL AND VESSEL 

SURVEYS OF THE 

UNDERSEA 

WARFARE TRAINING 

RANGE SITE 

ALTERNATIVE IN 

ONSLOW BAY, NC, 

USA

Nilsson, 

Peter

UNC 

Wilmington

nilssonp@un

cw.edu

SMM 

2009

Steno 

bredanensis X

AERIAL AND VESSEL 

SURVEYS OF THE 

UNDERSEA 

WARFARE TRAINING 

RANGE SITE 

ALTERNATIVE IN 

ONSLOW BAY, NC, 

USA

Nilsson, 

Peter

UNC 

Wilmington

nilssonp@un

cw.edu

SMM 

2009

Trichechus 

manatus 

latirostris

X

EVALUATION OF 

TRACE METALS IN 

THE FLORIDA 

MANATEE 

(TRICHECHUS 

MANATUS 

LATIROSTRIS) AND 

THE EXPRESSION OF 

METALLOTHIONEIN 

AS A POTENTIAL 

BIOMARKER OF 

METAL EXPOSURE

Takeuchi, 

Noel Y.

University of 

Florida

ntakeuchi@v

etmed.ufl.edu

SMM 

2009

Trichechus 

manatus 

latirostris

X

FLORIDA MANATEE 

BEHAVIOR DURING 

VESSEL 

APPROACHES

Rycyk, 

Athena

Florida State 

University

rycyk@ocean

.fsu.edu

SMM 

2009

Trichechus 

manatus 

latirostris

X

RESCUE, 

REHABILITATION 

AND RELEASE OF 

FLORIDA 

MANATEES: 

ANALYSIS OF 

FACTORS 

AFFECTING 

SURVIVAL

Adimey, 

Nicole

US Fish and 

Wildlife 

Service

nicole_adime

y@fws.gov

SMM 

2009

Trichechus 

manatus 

latirostris

X

SPATIAL 

DISTRIBUTION OF 

THE FLORIDA 

MANATEE 

(TRICHECHUS 

MANATUS 

LATIROSTRIS) 

AROUND POWER 

PLANTS IN 

BROWARD COUNTY, 

FLORIDA

Eldredge, 

Laura F.

Nova 

Southeastern 

U.

leldredg@no

va.edu

SMM 

2009

Trichechus 

manatus 

latirostris

X

THE MANATEE 

AUDIOGRAM AND 

AUDITORY CRITICAL 

RATIOS

Bauer, 

Gordon

New College 

of Florida

bauer@ncf.ed

u

SMM 

2009
322

Species

NAPA

MAPA

SAPA

SFPA

Title Author Institution Email Citation

Trichechus 

manatus 

latirostris

X

THIS WON'T HURT A 

BIT: NEW 

MOLECULAR TOOLS 

FOR POPULATION 

ASSESSMENT OF THE 

FLORIDA MANATEE

Davis, 

Michelle

FL Fish & 

Wildlife 

Cons. Com.

Michelle.Dav

is@myfwc.co

m

SMM 

2009
323

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Addison, R. F., and W. T. Stobo. 1993. Organochlorine residue concentrations and burdens in 

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Aguilar Soto, N., M. Johnson, P. T. Madsen, P. L. Tyack, A. Bocconcelli, and J. Fabrizio 

Borsani. 2006. Does intense ship noise disrupt foraging in deep-diving Cuvier’s beaked 

whales (Ziphius cavirostris)? Marine Mammal Science 22(3):690-699.

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Aguilar, A., and A. Borrell. 1994. Reproductive transfer and variation of body load of 

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