NOAA Technical Memorandum NMFS-SEFSC-575 

AN ASSESSMENT OF THE LOGGERHEAD TURTLE POPULATION IN 

THE WESTERN NORTH ATLANTIC OCEAN 

A Report of the Turtle Expert Working Group 

U.S. Department of Commerce 

National Oceanic and Atmospheric Administration 

National Marine Fisheries Service 

Southeast Fisheries Science Center 

75 Virginia Beach Drive 

Miami, Florida 33149 

2009 

 NOAA Technical Memorandum NMFS-SEFSC-575 

 

 

AN ASSESSMENT OF THE LOGGERHEAD TURTLE POPULATION IN 

THE WESTERN NORTHERN ATLANTIC OCEAN 

A Report of the Turtle Expert Working Group 

National Marine Fisheries Service 

Southeast Fisheries Science Center 

75 Virginia Beach Drive 

Miami, Florida 33149 

U.S. DEPARTMENT OF COMMERCE 

Gary Locke, Secretary 

National Oceanic and Atmospheric Administration 

Jane Lubchenco, Ph.D., Under Secretary of Commerce for Oceans and Atmosphere and NOAA Administrator 

National Marine Fisheries Service 

James W. Balsiger, Acting Assistant Administrator for Fisheries 

2009 

This Technical Memorandum series is used for documentation and timely communication of preliminary 

results, interim reports, or special-purpose information. This memorandum has been reviewed by the Center for 

Independent Experts. 
ii 

NOTICE

The National Marine Fisheries Service (NMFS) does not approve, recommend, or endorse any proprietary 

product or material mentioned in this publication. No reference shall be made to the NMFS, or to this 

publication furnished by NMFS, in any advertising or sales promotion which would indicate or imply that 

NMFS approves, recommends, or endorses any proprietary product or proprietary material mentioned 

herein or which has as its purpose any intent to cause directly or indirectly the advertised product to be 

used or purchased because of NMFS publication. 

This report should be cited as follows: 

Turtle Expert Working Group. 2009. An Assessment of the Loggerhead Turtle Population in the 

Western North Atlantic Ocean. NOAA Technical Memorandum NMFS-SEFSC-575, 131p. 

Copies may be obtained by writing: 

National Marine Fisheries Service 

Southeast Fisheries Science Center 

75 Virginia Beach Drive 

Miami, Florida 33149 

or 

National Technical Information Service 

5285 Port Royal Road 

Springfield, Virginia 22161 

(703) 487-4650 

FAX: (703) 321-8547 

Rush Orders: (800) 336-4700 

PDF version available at www.sefsc.noaa.gov

Cover photograph by Michael Patrick O’Neill, reprinted with permission. 
iii 

Atlantic Loggerhead Turtle Expert Working Group Members 

Nancy Thompson, Chair 

National Marine Fisheries Service 

Northeast Fisheries Science Center 

Alan Bolten 

Archie Carr Center for Sea Turtle Research 

Department of Zoology 

University of Florida 

 

Mark Dodd 

Georgia Department of Natural Resources 

Marine Resources Division 

Sheryan Epperly 

National Marine Fisheries Service 

Southeast Fisheries Science Center 

Allen Foley 

Florida Fish and Wildlife Conservation Commission 

Florida Marine Research Institute 

Matthew Godfrey 

North Carolina Wildlife Resources Commission 

Heather Haas 

National Marine Fisheries Service 

Northeast Fisheries Science Center 

 

Sandy MacPherson 

National Sea Turtle Coordinator 

U.S. Fish and Wildlife Service 

Kate Mansfield 

University of Miami 

Rosenstiel School of Marine and Atmospheric 

Science 

Peter Pritchard 

Chelonian Research Institute 

Paul Richards 

National Marine Fisheries Service 

Southeast Fisheries Science Center 

Christopher Sasso 

National Marine Fisheries Service 

Southeast Fisheries Science Center 

Melissa Snover 

National Marine Fisheries Service 

Pacific Islands Fisheries Science Center 

 

Jason Vaughan 

Department of Fisheries and Wildlife 

Oregon State University 

Jeanette Wyneken 

Department of Biological Sciences 

Florida Atlantic University 

Julio Cesar Zurita 

Comité de Protección de Tortugas Marinas en 

Quintana Roo 
iv

Table of Contents 

PREFACE..................................................................................................................................... vi 

EXECUTIVE SUMMARY .......................................................................................................viii 

PART I. UPDATES ON STOCK STRUCTURE, LIFE-STAGE DEFINITIONS, 

BIOLOGY, AND BEHAVIOR OF LOGGERHEADS ............................................................. 1 

Stock Structure........................................................................................................................... 1

Life Stages and Updated Demographics ................................................................................... 2

Nesting Females, Adult Stage, and Sizes .................................................................................. 8

Northern U.S. Subpopulation.................................................................................................. 9 

Peninsular Florida Subpopulation......................................................................................... 10 

Mexican Subpopulation ........................................................................................................ 10

Size of Putative Neophyte Nesters ........................................................................................... 11

Sex Ratio................................................................................................................................... 13

Sex Ratios Estimated from Stranded Turtles........................................................................ 17 

Spatial Distribution.................................................................................................................. 19

Conventional tag data ........................................................................................................... 20 

Satellite Telemetry................................................................................................................ 23 

Aerial Survey and Shipboard Surveys .................................................................................. 39 

PART II. POPULATION ASSESSMENTS ............................................................................ 48 

Population Nesting Trend........................................................................................................ 48

Western North Atlantic ........................................................................................................ 48 

Peninsular Florida ............................................................................................................. 49 

Northern U.S..................................................................................................................... 50 

Northern Gulf of Mexico .................................................................................................. 51 

Dry Tortugas/Cay Sal Bank.............................................................................................. 51 

Mexico .............................................................................................................................. 51 

Other Atlantic and Mediterranean Subpopulations ............................................................... 52

Eastern North Atlantic............................................................................................................. 52

Cape Verde............................................................................................................................ 52 

Western South Atlantic ............................................................................................................ 53

Brazil..................................................................................................................................... 53 

Mediterranean Sea................................................................................................................... 53

Greece ................................................................................................................................... 54 

Turkey................................................................................................................................... 54 

PART III. IN-WATER TRENDS............................................................................................. 64 

Trends in Catches or Catch Rates ........................................................................................... 65

Size Distribution of In-water Trends....................................................................................... 68

PART IV. FACTORS POTENTIALLY RESPONSIBLE FOR DECREASING 

NUMBERS OF NESTS .............................................................................................................. 76 

Incidental Capture ................................................................................................................... 76
v

Adult Female Survival Rates ................................................................................................... 77

Proportion of Putative Neophyte Nesters................................................................................ 79

Directed Harvest....................................................................................................................... 80

Loggerhead Epizootics in Florida ........................................................................................... 81

PART V. RESEARCH NEEDS AND RECOMMENDATIONS........................................... 85 

Population Parameters ............................................................................................................ 85

Spatial and Temporal Distributions ........................................................................................ 86

Stock ID.................................................................................................................................... 87

Effects of Incidental Capture .................................................................................................. 87

Trophic Changes/ Carrying Capacity...................................................................................... 87

ACKNOWLEDGMENTS .......................................................................................................... 87 

LITERATURE CITED .............................................................................................................. 89 

APPENDIX A Sex Ratios of Stranded Turtles...................................................................... 108 

APPENDIX B Description of Loggerhead Morphometric Relationships .......................... 126 
vi

PREFACE 

The loggerhead turtle occurs in the Atlantic, Pacific and Indian oceans as well as in the 

Mediterranean Sea, and is generally perceived as the “common” marine turtle in the eastern 

United States, with extensive nesting from Florida to North Carolina. In the Atlantic system, 

some of the largest nesting beaches are along the U.S. coastline, with the largest subpopulation 

from Peninsular Florida and with a separate subpopulation from Georgia to North Carolina, 

(whose population is about one-tenth the size of the Florida stock) and an even smaller 

population from the Northern Gulf of Mexico. There is some nesting in central Quintana Roo, 

Mexico, as well as on Cay Sal Bank, The Bahamas and Dry Tortugas, Florida. Nesting is rare 

throughout the Caribbean mainland and islands; Cuba and Belize have the most nests outside 

Quintana Roo. Low level nesting regularly occurs in Grand Cayman Island (Bell et al. 2007). 

Among the few tropical nesting sites are beaches on the islands off Venezuela and the Santa 

Marta Peninsula (northeastern Columbia), and possibly some also on the Serrano and Serranilla 

Banks in the Western Caribbean. However, recent quantitative data are lacking for all of these 

Caribbean sites. Certain beaches in south-temperate Brazil (southern Sergipe, Bahia, and 

southward to northern Rio de Janeiro) receive about 5,000 loggerhead nests/year (Marcovaldi 

and Chaloupka 2007). On the African side of the Atlantic, the best documented nesting area is in 

the Cape Verde Islands, with some possible nesting also occurring in Angola although recent 

reports cast doubt on this (Weir et al. 2007). In the Mediterranean Sea, most nesting occurs in 

Turkey (Dalyan, Dalaman), Greece (primarily Zakynthos), and Libya with lesser levels of 

nesting also occuring in Syria, Israel, and Tunisia (Margaritoulis et al. 2003). Recently, a few 

loggerheads nests were observed in Spain, France, and Italy (Bentivegna et al. 2005). 

 

Peninsular Florida represents the largest loggerhead nesting aggregation in the Atlantic Ocean, 

representing as much as 80% of all nesting and producing 90% of all hatchlings. The number of 

nests has declined since peaking in 1998 (with 59,918 nests on index beaches). These beaches 

represent about 25% of all nesting habitat but about 70% of the total number of nests (Florida 

Fish and Wildlife Conservation Commission (FFWCC); http://research.myfwc.com). From 1989 

to 1998, the number of nests increased 25% but since 1998 the number of nests has declined 

approximately 40% with 28,074 nests recorded on index nesting beaches in 2007 (FFWCC). On 

a positive note, there were 38,064 nests in 2008 on those index nesting beaches (FFWCC). 

With the foregoing in mind, the global importance of the status of U.S. Atlantic loggerhead 

populations becomes apparent. A very significant fraction of the world loggerhead population 

nests in Florida. Thus, the status of this population is crucial to the species as a whole. 

Currently, Peninsular Florida sea turtle populations are showing changes that have resisted 

comprehensive interpretation. Nesting numbers of both the green turtle (Chelonia mydas) and 

the leatherback (Dermochelys coriacea) that share the same Florida nesting beaches with 

loggerheads are increasing strongly (although, at least until recently, in the typical “high 

year/low year” alternating fashion). For both of these species, the increases have been dramatic 

and significant with green turtles increasing from 5,557 in 1998 to 9,642 nests in 2005 and 

leatherbacks increasing from 351 to 762 over the same period (FFWCC). These species are still 

greatly outnumbered by loggerheads on Florida beaches, but nesting of the latter, having shown 

some degree of stability for over a decade, now appears to be in decline. 
vii

Along with Peninsular Florida, the productivity (measured by number of nests) of the Northern 

U.S. subpopulation (Georgia to North Carolina), Northern Gulf of Mexico, and Yucatán 

loggerhead nesting populations in the Western North Atlantic have all dropped significantly in 

recent years. The decrease in the Peninsular Florida subpopulation nesting is about 4 % annually 

(39.5% decrease since 1998), compared with 6.8 % annually in the Florida Panhandle, 1.9% 

annually in the Northern U.S. subpopulation, and 5% annually in the Yucatán Peninsula. 

However, the nesting population in Brazil has exhibited an increase over the past decade 

(Marcovaldi and Chaloupka 2007). 

It is our purpose to update the previous Turtle Expert Working Group (TEWG) reports and a 

more recent assessment (NMFS SEFSC 2001) with new information, and to address the status 

and trends of the Western North Atlantic population of loggerhead and to evaluate possible 

causes of the observed trends. 

The first Turtle Expert Working Group convened 1995-1998 to do an assessment of loggerhead 

and Kemp’s ridley sea turtles. The group’s work is reflected in two reports (TEWG 1998, 2000). 

They concluded that the Peninsular Florida loggerhead subpopulation was stable or possibly 

increasing and that the Northern U.S. subpopulation, after declining since the 1970’s, may have 

stabilized. The status of the Northern Gulf and Mexico subpopulations were unknown. 

Subsequent to the TEWG, the original Crouse et al. (1987) population model was updated 

multiple times (Heppell et al. 2003; NMFS SEFSC 2001; Snover 2002; Hedges 2007) and new 

genetic and demographic information have become available. Importantly, the trend in nesting 

on the Peninsular Florida beaches has changed, recently declining. 

The second loggerhead TEWG was convened December 2006 to update the previous report for 

loggerheads and to assess the recent decline in loggerhead nesting on South Florida beaches. 

Thus, this TEWG report is structured into five sections: Part I is an update of the previous 

TEWG reports: stock id, life stage definitions and demographics, sex ratios, and geographic 

distributions. Part II reviews the status and trends of the current nest numbers while Part III 

examines in-water population trends. Part IV explores hypotheses for the reported trends and, 

lastly, Part V identifies research needs. 

I personally want to acknowledge all the contributions of data and hard work that were necessary 

to finalize this report. Considerable amounts of data were contributed that were not collected by 

the National Marine Fisheries Service (NMFS) or by TEWG members. Due to the need to 

safeguard ownership of the data and information, NMFS wants to clarify the intended use of any 

data shared with the TEWG. NMFS, in conjunction with collaborating parties, used these data 

only in producing this final TEWG report on the status of loggerhead turtles in the Western 

North Atlantic Ocean. All data shall remain the property of the provider and were used in this 

report with their permission. These data cannot be used without the explicit permission of the 

originator. 

Dr. Nancy Thompson, chair 
viii

EXECUTIVE SUMMARY 

It’s been nearly a decade since the Turtle Expert Working Group (TEWG) last assessed the 

Western North Atlantic populations of the loggerhead sea turtle (Caretta caretta). An updated 

report at this time was deemed necessary given the apparent changes in the nesting trends of 

loggerhead subpopulations that were last thought to be stable or recovering and the publication 

of additional information on the stocks. The TEWG had assessed recovery by the increasing 

numbers of nests in the Peninsular Florida subpopulation while the Northern U.S. Subpopulation 

was at best stable. Over the past decade, the annual numbers of nests of all the loggerhead 

subpopulations in the Western North Atlantic were decreasing through 2007, with an upturn in 

2008. Of particular concern was the recent decrease in the annual numbers of loggerhead nests 

in the largest subpopulation, Peninsular Florida. 

We began by updating information on stock structure and definitions of life stages of Western 

North Atlantic loggerheads last reported by the TEWG. The TEWG previously recognized four 

nesting subpopulations of loggerheads in the Western North Atlantic (TEWG 2000). Continuing 

work on stock structure led to the discovery of a fifth nesting subpopulation in the Western North 

Atlantic and a better delineation of the previously identified subpopulations. In this current 

report, we used the designations recognized in the Loggerhead Recovery Plan (National Marine 

Fisheries Service and U.S. Fish and Wildlife Service 2008). These five subpopulations are: 

1. Northern U.S. Subpopulation (Florida/Georgia border through southern Virginia) 

2. Peninsular Florida Subpopulation (Florida/Georgia border through Pinellas County, 

Florida) 

3. Dry Tortugas Subpopulation (islands located west of Key West, Florida and Cay Sal 

Bank, Bahamas) 

4. Northern Gulf of Mexico Subpopulation (Franklin County, Florida through Texas) 

5. Greater Caribbean Subpopulation (all other nesting assemblages within the Greater 

Caribbean, Mexico through French Guiana, The Bahamas, Lesser Antilles, and Greater 

Antilles). 

It should be noted that we have added the term U.S. to the name of the first listed subpopulation 

to clarify its geographic location. 

The 2000 TEWG last defined the life stages for the loggerhead as: pelagic immature from the 

time a hatchling leaves a nesting beach until it appears on coastal benthic feeding grounds at 

around 40-60 cm straight carapace length (SCL); benthic immature from settlement to 92 cm 

SCL; and adult which is ≥92 cm SCL. We now recognize five life stages for the loggerhead. 

We defined these as follows: 

 I. Year One, terrestrial to oceanic, size ≤ 15 cm SCL 

 II. Juvenile (1) exclusively oceanic, size range of 15-63 cm SCL 

 III. Juvenile (2), oceanic or neritic, size range of 41-82 cm SCL 

 IV. Juvenile (3), oceanic or neritic, size range 63-100 cm SCL 

 V. Adult, neritic or oceanic, size ≥ 82 cm SCL 
ix

These new life-stage definitions recognize that recruitment to any given stage is not a knifeedged transition, but instead is associated with a distribution; the bounds of these distributions 

are not absolute and may overlap to some extent with adjacent stages. We made a distinction 

between Stages III and IV because size frequency data indicate that there are two distinct 

distributions/behaviors representing smaller and larger neritic juveniles. 

The last TEWG assessment of the loggerhead subpopulations in the Western North Atlantic 

concluded that the Peninsular Florida Subpopulation (then referred to as the South Florida 

Nesting Subpopulation), the Northern Gulf of Mexico Subpopulation (then referred to as the 

Florida Panhandle Nesting Subpopulation), and the Greater Caribbean Subpopulation (then 

referred as the Yucatán Nesting Subpopulation) were all either stable or increasing as indicated 

by rising annual numbers of nests (TEWG 2000). The Northern U.S. Subpopulation was the 

only one thought to be stable or decreasing (TEWG 2000). The addition of nesting data through 

2007 now shows that the annual numbers of nests of all Western North Atlantic loggerhead 

subpopulations had been decreasing during the past decade and, by extension, indicates that the 

adult female component of all of these subpopulations may have been decreasing over the same 

time. Of greatest concern is the decrease in the annual numbers of nests of the Peninsular 

Florida Subpopulation. This subpopulation has the largest nesting aggregation in the Atlantic 

Ocean, representing as much as 80% of all nesting in the Western North Atlantic, and is one of 

the largest nesting aggregations in the world. The annual numbers of nests for this subpopulation 

decreased 49% since 1998, and now show an overall decrease of 37% from 1989 through 2007. 

Nest numbers were up in the Peninsular Florida subpopulation for 2008 with 38,064 nests 

recorded on the core nesting beaches. There were 1,159 nests in 2007 and 1,854 nests in 2008 

for the Northern U.S. subpopulation which makes 2008 one of the highest counts on record. 

Furthermore, no long-term data suggest any of the loggerhead subpopulations throughout the 

entire North Atlantic are increasing in annual numbers of nests. The subpopulations in Greece 

and Turkey are both either stable or decreasing and there are insufficient data available to 

determine a nest trend for the Cape Verde subpopulation. The only loggerhead subpopulation in 

the entire Atlantic with recently increasing annual numbers of nests is in the Western South 

Atlantic (Brazil). 

We assessed data from long-term studies of loggerheads in the water to identify any changes in 

(i) the overall numbers of loggerheads found along the eastern U.S. and (ii) loggerhead size 

distributions. Such changes may signal changes in recruitment and/or survival rates. The data 

for neritic loggerheads were primarily from immature, Stage III animals. Four studies spanning 

the southeastern U.S. (from central North Carolina through central Florida) indicated a possible 

increase in the abundance of neritic loggerheads in this area over the past one to two decades. 

However, aerial surveys and one other in water study in the northeastern U.S. (north of Cape 

Hatteras, N.C.) suggest a decrease in abundance over similar time periods for some areas. 

The apparent overall increase in the abundance of neritic loggerheads in the southeastern U.S. 

may be due to increased abundance of the largest Stage III loggerheads and may indicate there is 

a relatively large cohort that will be reaching maturity in the near future. Other complications 

suggest that any increase in adults may be temporary because in-water studies throughout the 

entire eastern U.S. also documented a substantial decrease in the abundance of the smallest Stage 
x

III loggerheads. This pattern was also corroborated by data on dead or debilitated (i.e., stranded) 

loggerheads found in the northeastern U.S. and we are concerned that subsequent recruitment 

could be low. 

We investigated various hypotheses to explain the decreases in the annual numbers of 

loggerhead nests throughout the Western North Atlantic. The decline in loggerhead nests 

appears to be species-specific. We first noted that the cause(s) of the decrease in loggerhead 

nests was not apparently affecting either green turtles (Chelonia mydas) or leatherbacks 

(Dermochelys coriacea) on some of the same nesting beaches. During the period of time when 

the annual numbers of loggerhead nests were decreasing in both Florida and Mexico, the annual 

numbers of green turtle nests at both sites and the annual numbers of leatherback nests in Florida 

were rising. We also noted an interesting parallel at Kurashima Island, Japan, where annual 

numbers of loggerhead nests are declining but annual numbers of green turtle and hawksbill 

(Eretmochelys imbricata) nests are increasing. Because other species on the same beaches are 

increasing in numbers, we could not attribute loggerhead decline to loss or degradation of 

nesting habitat (at least in Florida and Mexico) 

It is possible that random variation in demographic parameters within the range reported (such as 

fecundity) could result in the observed decline in nest number in both an increasing population or 

in a decreasing population. This phenomena coupled with other well known processes, such as 

transient dynamics (see Caswell 2001), that can result after one or more population perturbations 

may also explain the current decline in nest counts that could result with either an increasing or 

decreasing population. Unfortunately we have no time series of any demographic parameters that 

are appropriate to examine this hypothesis quantitatively. 

We recognize that a decrease in the annual numbers of nests could reflect a decrease in 

individual reproductive output, in numbers of nesting females or some combination of both. It is 

conceivable that the quality or quantity of forage for adult loggerheads in the Western North 

Atlantic may have recently decreased resulting in increased remigration intervals of the adult 

females. Because adult female loggerheads forage over large areas of the Western North 

Atlantic, we would expect such decrease in nutrient availability or quality would be noticeable. 

Yet, we know of no direct evidence to indicate changes in prey abundance but hypothesize that 

competition for food resources with commercial harvest could potentially impact productivity 

via decreased reproductive output. 

One known mechanism by which the average reproductive output per adult female loggerheads 

might be lowered is if the proportions of putative first-time nesters in the nesting assemblages 

have risen. First-time nesters typically produce fewer clutches per season and smaller clutches. 

We analyzed tagging data from the Quintana Roo rookery and determined that over the short 

period for which data are available, there was an increasing trend in the proportion of putative 

first-time nesters in the population. We lack similar data for any of the beaches in other 

subpopulations. 

We explored the hypothesis that losses of adult female loggerheads have remained unchanged 

and that a recent lack of new recruited females accounts for the change. That does not appear to 

be the case for the Mexico Subpopulation where the proportion of putative first-time nesters has 
xi

been increasing. Evidence from in-water studies of measured loggerheads suggests crests and 

troughs in abundances of individuals in sequence among the studies. The in-water studies 

indicated that we may soon see a crest in newly recruited females perhaps followed by another 

trough. Similarly, we found no shift in sex ratio that would explain the decline. 

To better characterize the recent rate of loss of adult female loggerheads, we estimated the 

current adult female survival rates. We estimated annual survival rates from tagging data 

collected on one beach for each of the subpopulations: Peninsular Florida (Melbourne Beach), 

Greater Caribbean (Quintana Roo), and Northern U.S. (Wassaw Island). The survival estimate 

for resident females nesting on Melbourne Beach was the lowest (0.73, 95% CI 0.71 – 0.76). 

The survival estimate for resident females nesting in Quintana Roo was the highest (0.85, 95% 

CI 0.81 – 0.88). The survival estimate for resident females nesting on Wassaw Island was 0.81 

(95% CI 0.77 – 0.84) and was slightly higher than a previous estimate (0.79). All models 

suggested that annual survival did not vary over time. In addition, the results from Melbourne 

need further study to ensure they are correct as this study is not a dedicated mark-recapture study 

and these results may be biased low. 

Recalling that while the annual numbers of loggerhead nests in the Western North Atlantic have 

been decreasing, the annual numbers of green turtle and leatherback nests have been increasing, 

we concluded that any mortality factors that may account in large part for decreasing numbers of 

adult female loggerheads must be restricted to this species. We reviewed the recent history of 

the directed harvest of loggerheads in the Western North Atlantic and found that the commercial 

fishery in Cuba would have been the only one to harvest substantial numbers of loggerheads 

during the past several decades. However, the take from this fishery was reduced to a relatively 

low level in the early 1990’s and has been reported as being close to zero since 1996. 

Interestingly, as fewer loggerheads were harvested in Cuban waters in the late 1980s through the 

late 1990’s, there was a concurrent increase in the annual numbers of loggerhead nests of several 

of the loggerhead subpopulations in the Western North Atlantic. If the past directed harvest of 

loggerheads in Cuba has a role in the current decline in the numbers of nests in the Peninsular 

Florida and Northern U.S. Subpopulations, that role is likely the loss of immature turtles a 

decade or more ago that would have eventually transitioned to the adult population. 

The greatest source of added mortality for sea turtles during the last half century has been from 

incidental takes in commercial fisheries. For loggerheads in the Western North Atlantic, loss of 

relatively large-sized individuals (Stages III, IV, and V) in shrimp trawls has been chronic and 

was a major source of mortality at least until 2003 when larger Turtle Excluder Devices were 

mandated. There has been mortality of small-sized loggerheads (Stage II) in pelagic longline 

fisheries. There has also been loggerhead mortality of larger animals (Stages III-V) in finfish 

trawl, gill net, drift net, and pound net fisheries. The incidental capture of loggerheads in 

commercial fisheries may certainly be playing a role in the recent apparent decrease in the 

numbers of adult female loggerheads in the Western North Atlantic either through recent 

mortality of adult females or through past mortality of immature loggerheads that would have 

recently matured. 

The overall mortality of loggerheads in Florida as indicated by stranding numbers has been 

increasing at an increasing rate since the mid 1990’s. There have also been several, recent 
xii

epizootics of loggerheads in Florida. Some were likely caused by harmful algal blooms and 

others were likely caused either by previously undetected diseases or by emergent diseases. 

Most of the epizootics have been centered in southwest Florida where large numbers of adult 

loggerheads are resident along the wide continental shelf there. 

In summary, we could not determine whether or not the decreasing annual numbers of nests 

among the Western North Atlantic loggerhead subpopulations were due to stochastic processes 

resulting in fewer nests, a decreasing average reproductive output of the adult females, 

decreasing number of adult females, or both factors. Many factors are responsible for past or 

present loggerhead mortality that could impact current nest numbers, however no single 

mortality factor stands out as a likely primary factor. It is likely that several factors compound to 

create the current decline. Regardless, it is clear that the current hatchling output will result in 

depressed recruitment to subsequent life stages over the coming decades. 

Our ability to assess the current status of all segments of the Western North Atlantic loggerhead 

subpopulations is limited. We have bits and pieces of the information, but lack the specific 

census and mortality data necessary to characterize and monitor trends for these populations. To 

improve future assessments, fundamental life history and census data must be collected, 

compiled, made available, and evaluated for these subpopulations. 
1 

PART I. UPDATES ON STOCK STRUCTURE, LIFE-STAGE DEFINITIONS, 

BIOLOGY, AND BEHAVIOR OF LOGGERHEADS 

Stock Structure –Alan Bolten and Sheryan Epperly 

Loggerheads from the Western North Atlantic have a complex population structure. Based on 

mtDNA, oceanic juveniles show no structure, neritic juveniles show moderate structure, and 

nesting colonies show strong structure (Bowen et al. 2005). In contrast, a survey using 

microsatellite (nuclear) markers showed no significant population structure among nesting 

populations of the Western North Atlantic (Bowen et al. 2005), indicating that while females 

exhibit strong philopatry, males apparently provide an avenue of gene flow between nesting 

colonies in this region. Earlier reports by the TEWG (1998, 2000) identified four subpopulations 

in the Western North Atlantic, based solely on mtDNA. We now identify five nesting 

subpopulations of loggerhead sea turtles in the Western North Atlantic: four subpopulations in 

the U.S were identified in the Loggerhead Recovery Plan (National Marine Fisheries Service and 

U.S. Fish and Wildlife Service 2008) (Northern U.S. Subpopulation, Peninsular Florida 

Subpopulation, Northern Gulf of Mexico Subpopulation, and Dry Tortugas Subpopulation), and 

one in Mexico (Quintana Roo). Within the North Atlantic basin, there is a sixth subpopulation: 

Cape Verde in the Northeast Atlantic. These six subpopulations are genetically independent 

based on mtDNA haplotype frequencies (AMOVA, FST = 0.256, p < 0.001; Bolten and Bjorndal, 

unpublished). The loggerhead nesting population on Cay Sal Bank, Bahamas, is not genetically 

distinguishable from the Dry Tortugas Subpopulation (AMOVA, FST = 0.018, p = 0.708; Bolten 

and Bjorndal, unpublished); therefore, these two rookeries were combined for analyses. To 

assess genetic independence for all of the known subpopulations in the Atlantic, we evaluated 

these six subpopulations along with the rookeries in Brazil, Greece, and Turkey and determined 

that the nine subpopulations were genetically distinct (AMOVA, FST = 0.409, p = 0.000; Bolten 

and Bjorndal, unpublished) with all FST pair wise comparisons significantly different (alpha = 

0.05). At this time we do not have data for Cuba, the only major North Atlantic rookery not 

included in our analyses. 

Five subpopulations of nesting loggerheads in the Western North Atlantic previously have been 

identified (Encalada et al. 1998, Francisco Pearce 2001). Until recently, the definition of the 

nesting range of the Northern U.S. Subpopulation included northern Florida. However, recent 

increases in genetic sample sizes and more complete sampling of rookeries along the Atlantic 

coast of the southeast U.S. suggests that there is a cline for each of the two primary haplotypes 

(CC-A1 and CC-A2; Archie Carr Center for Sea Turtle Research unpubl. data; National Marine 

Fisheries Service and U.S. Fish and Wildlife Service 2008). Analyses using these new data 

indicate that there is no genetic difference between loggerheads nesting on adjacent beaches 

along the Florida Peninsula. This lack of genetic structure makes it difficult to designate specific 

boundaries for the subpopulations based on genetic differences alone. Therefore, the 

Loggerhead Recovery Team (National Marine Fisheries Service and U.S. Fish and Wildlife 

Service 2008) used a combination of geographic distribution of nesting densities, geographic 

separation, and geopolitical boundaries in addition to genetic differences to identify the four U.S. 

subpopulations as recovery units, in addition to identifying the Greater Caribbean as a fifth 

subpopulation in the Western North Atlantic. 
2 

The five subpopulations (= recovery units) are: 

1. Northern U.S. Subpopulation (Florida/Georgia border through southern Virginia) 

2. Peninsular Florida Subpopulation (Florida/Georgia border through Pinellas County, 

Florida) 

3. Dry Tortugas Subpopulation (islands located west of Key West, Florida and Cay Sal 

Bank, Bahamas) 

4. Northern Gulf of Mexico Subpopulation (Franklin County, Florida through Texas) 

5. Greater Caribbean Subpopulation (all other nesting assemblages within the Greater 

Caribbean, Mexico through French Guiana, The Bahamas, Lesser Antilles, and Greater 

Antilles). 

Further sampling throughout the greater Caribbean may yield compelling information to identify 

additional subpopulations in the future. Although the largest rookeries appear on the mainland 

U.S., the Mexico Subpopulation has the greatest genetic diversity (Encalada et al. 1999). During 

glaciation periods, the temperate beaches were too cool to incubate eggs and nesting could have 

continued only on the tropical beaches. Thus, the contemporary distribution of nesting is the 

product of colonization events from the tropical refugia during the last 12,000 years (Encalada et 

al. 1998; Bowen and Karl 2007). This underscores the historic importance of the tropical 

rookeries, although small in size, to the genetic diversity and persistence of the North Atlantic 

population through time. 

Life Stages and Demographics –Sheryan Epperly, Melissa Snover, and Alan Bolten 

The first TEWG identified four life stages, but recognized that large immature turtles in the 

coastal environment represented a larger proportion of the strandings and in-water captures along 

the south and western coasts of Florida as compared with the rest of the coast (TEWG 2000). To 

date, virtually all population models for loggerheads have distinguished between small and large 

neritic juveniles (Table 1). Herein we define five life stages of the loggerhead sea turtle, 

denoting the large immature neritic animals as a separate stage (Figure 1): I. Year One, 

terrestrial to oceanic; II. Juvenile (1) exclusively oceanic; III. Juvenile (2), oceanic or neritic; IV. 

Juvenile (3), oceanic or neritic; V. Adult, neritic or oceanic. These correspond roughly to stages 

used in past matrix models: egg to post hatchling, pelagic juveniles, small benthic juveniles, 

large benthic juveniles, and adults (Table 1). We retained the distinction between Stages III and 

IV because size frequency data indicate two modes and differing geographic distributions of the 

neritic juveniles, but there was not consensus on this; some members believed these stages 

should be combined as was done in the loggerhead recovery plan (National Marine Fisheries 

Service and U.S. Fish and Wildlife Service 2008). The new stage definitions recognize that 

except for Stage II juveniles, which are exclusively oceanic, all other stages may occur in both 

the oceanic and neritic environments (Witzell 2002; Bolten 2003; McClellan and Read 2007; 

Spatial Distribution section in this report). The new stage definitions also recognize that 

recruitment to any given stage is not a knife-edge, but instead is associated with a distribution; 

the bounds of these distributions are not absolute either. The stages are explained below. Table 

1 summarizes their use in matrix models to date. Since the first TEWG reports (see Appendix 4 

in their 1998 report) there have been many updates to the demographic parameters for each 

stage. Table 2 provides updated information on the demographic parameters. 
3 

Figure 1. Conceptual model of size distributions for each life stage of the loggerhead turtle. 

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

0 20 40 60 80 100 120

Straight Carapace Length (cm)

Proportion size class in stage

I II III IV V

Stage I. Year One, terrestrial to oceanic - 1 year post-hatchlings. Ranges from size at hatching 

(4.5 cm straight carapace length {SCL} average: van Buskirk and Crowder 1994) to 15 cm SCL 

(Bjorndal et al. 2000). 

Stage II. Juvenile (1) exclusively oceanic - Ranges from 1 year (15 cm SCL; end of stage 1) to 

63 cm SCL. According to Bjorndal et al. (2000), recruitment out of the oceanic stage begins at 

42 cm SCL (46 cm curved carapace length {CCL} converted using their equation). From the 

neritic size distribution data (see section ‘In-Water Trends and Size Distributions’), 41 cm SCL 

is commonly the smallest length, and thus animals begin to shift from Stage II to Stage III at 41 

cm SCL. According to the length frequency analysis of Bjorndal et al. (2000), Atlantic 

loggerheads are nearly fully recruited out of the oceanic stage (Stage II) by 59.5 cm SCL (64 cm 

CCL converted using their equation). The inshore length frequency data from North Carolina 

(Epperly et al. 2007; NMFS unpublished data; Figure 2) do not show the bimodal distribution 

that most of the other southeast U.S. inshore/nearshore datasets show, but the one mode 

described by the N.C. data also is present in the other datasets of the southeast (see below). 

Hence, the N.C. data describe juvenile lengths for Stage III. The mean for the N.C. dataset is 63 

cm SCL, similar to the size at which nearly all Stage II loggerheads have departed oceanic 

environments (Bjorndal et al. 2000). Thus, we used 63 cm SCL as the end of Stage II. We 

assigned a normal probability distribution to describe the drop from the proportion of individuals 

in Stage II at 41 cm to the proportion of individuals in Stage II at 63 cm. 

Stage III. Juvenile (2), oceanic or neritic - Ranges from 41 cm SCL to 82 cm SCL with a peak at 

63 cm SCL. The justifications for selecting 41 and 63 cm SCL is described above. The 

distribution of Stage III in the figure is essentially that of the N.C. dataset (Figure 2); 82 cm SCL 

is approximately the 98th percentile of that distribution and 82 cm SCL is also the 2.5 percentile 

of the putative neophyte data analyzed and described in this TEWG report (using data from all 

beaches, 87.2 cm CCLstd converted to SCLstd) and what we determined should be the beginning 

of Stage V (Adults). 
4 

Stage IV. Juvenile (3), oceanic or neritic - The start (63 cm), middle (82 cm) and endpoint (100 

cm) of this distribution were determined by the other distributions as the curves need to link and 

sum to one at every length. The presence of a bimodal size distribution of juvenile loggerhead 

turtles can be found in other datasets from the southeast U.S. with greater prominence in the 

southernmost study sites (see In-Water section in this TEWG report; Hillestad et al. 1978); it is 

most pronounced near Cape Canaveral (Bolten et al. 1994; Henwood 1987) and in Florida Bay, 

indicating that the habitat and threats likely differ among the two juvenile stages in the neritic 

environment. This second mode often is confounded by the presence of adults, with an 

overlapping size distribution. 

Stage V. Adult, neritic or oceanic - Begins at 82 cm SCL (2.5 percentile of neophytes) with full 

recruitment to the adult stage at 100 cm SCL (see Size of Putative Neophyte Nesters below). 

Females move briefly from the neritic to the terrestrial environment to nest. 
5 

Table 1. Life table for loggerhead models used to date. Lengths are standard (notch-to-tip) measurements of the carapace unle

that Frazer’s (1983a) age-structured life tables are not included, but the early model all were based on his original table. 

TEWG’s definition of stages 

I. Year One, 

terrestrial to oceanic 

II. Juvenile 

(1), 

exclusively 

oceanic 

III. Juvenile 

(2), oceanic 

or neritic 

IV. Juvenile 

(3), oceanic or 

neritic 

V. Adult, ocean

or neritic 

Historical definition of stages 

Egg Hatchling PostHatchling Oceanic, pelagic 

juvenile 

Neritic, 

benthic 

juvenile, 

small 

Neritic, 

benthic 

juvenile, 

large/subadult

Adult female 

Crouse et al. (1987) 

<10 cm SCL age < 1yr S=0.6747 

10.1-58.0 cm SCL age=1-7 yr S=0.7857 

58.1-80.0 cm SCL age=8-15 yr S=0.6758 

80.1-87.0 cm SCL age=16-21 yr S=0.7425 

>87.0 cm SCL age=22-54 yr S=0.80

Crowder et al. (1994) 

Duration=1 yr S=0.6747 

Duration=7 yr S=0.75 

Duration=8 yr S=0.6758 

Duration=6 yr S=0.7425 

Duration > 32 yr S=0.8091 

Heppell et al. (2003) 

F=nests x eggs x sex ratio x survival from egg to age one 4.1 nests/female; 115 eggs/nest; 1:1 sex ratio S=fitted (pre-1990 λ=0.95)1

5-45 cm SCL 8 or 10 yr S=fitted (pre-1990 λ=0.95)1

S1=0.745 

S2=0.875 

45-72 cm SCL 6 or 11 yr S1=0.6758 

S2=0.7 

72-92 cm SCL 8 or 13 yr S1=0.7425 

S2=0.8 

92+ cm SCL 23 or 35 yr to maturiS1=0.8091 

S2=0.85 

NMFS SEFSC (2001) 

F=nests x (eggs x egg survival) x sex ratio x survival from hatchling in water to age one; 4.1 nests/female; 115 eggs/nest; 0.675 egg survival, % female=35%, 50%, 80% S=fitted1 (pre-1990 λ=0.95, 0.97, 

1.0) Duration=1 yr 

Minimum <42cm SCL Average<49cm Duration1=6yr 

Duration2=7yr Duration3=6yr Duration4=7yr S=fitted1 (pre1990 λ=0.95, 0.97, 

1.0)=0.585-0.894 

Minimum=42-72 SCL Average=49-72 Duration1=7yr 

Duration2=6yr Duration3=13yr Duration4=11yr S1,2=0.6758 

S3,4=0.893 

Minimum=73-82 SCL Average= 73-90 Duration1=7yr 

Duration2=14yr Duration3=11yr Duration4=21yr S1,2=0.7425 

S3,4=0.893 

Minimum=83cm SCAverage=90cm Duration=indefinite S1,2=0.809 

S3,4=0.812 

1 With empirical inputs for all other parameters in the projection matrix and a knowledge of the dominant eigenvalue (λ; or population g

unknown value, the oceanic, pelagic stage survival rate, can be solved for; this value also is used in the fecundity term. 
6 

Snover (2002) 

Duration=1 yr S=0.3700 (from Heppell et al. 2003) 

<49 cm SCL Duration=14 yr S=0.8100 

49-80 cm SCL Duration=10 yr S=0.6758 

80-90 cm SCL Duration=7 yr S=0.7425 

>90 cm SCL S=0.8091 

Hedges (2007) 

Duration=1 yr 2.1, 3, and 4 nests/female, 118 eggs/nest, 58% female (from Hawkes et al. 2007), Segg-hatchling=0.386 

Shatchling-1yr=0.875 

S=0.875 S=0.81 (SD 0.06) 

from Sasso et al. (2006) 

S=0.8 S=0.853 (SD 0.0365
7 

Table 2. Recent information on loggerhead life stages. Lengths are standard (notch-to-tip) measurements unless noted otherwise. 

I. Year One, 

terrestrial to 

oceanic 

II. Juvenile (1), 

exclusively oceanic 

III. Juvenile (2), 

oceanic or neritic 

IV. Juvenile (3), 

oceanic or neritic 

V. Adult, oceanic 

Stewart and Wyneken (2004) Hatchling survival for first 15 min in water=94.9% Whelan and Wyneken (2007) hatchling survival for first 15 min in water = 95.4% 

Bjorndal et al. (2003a) Total sample: S2-6=0.910 (0.872-0.951)2Tuna sample: S4-6=0.894 (0.880-0.909)2

Sasso and Epperly (2007) S~6-12=0.814 (0.557-0.939) 

Bjorndal et al. (2000) Duration≤46cm CCL=6.5 yr and 

Duration<64cmCCL=11.5 yr 

Bjorndal et al. (2003b) Duration<46cmCCL =7 yr 

Snover (2002) Durationaverage(48.5-51.1 cm 

SCL)=14.8 yr (SD 3.3) (range 9-24 yr) 

Sasso et al. (2006) Sapparant=0.81 (SE 0.06) 

Braun-McNeill et al. (2007a) Srealized=0.83 (0.74-0.89) 

Bjorndal et al. (2001) Duration46-87cmCCL=20 yr 

Snover (2002) Duration49-90cmSCL=17 yr 

Braun-McNeill et al. (2008) Duration50-80 cmSCL=17.4 yr 

(15.6-19.4) Braun-NcNeill et al. (2007b) Sex Ratio 2.1:1 females:males 

Bjorndal et al. (2001) Duration46-87cmCCL=20 yr 

Snover (2002) Duration49-90cmSCL=17 yr 

Bald Head Island, NC Hedges (2007) S=0.853 (0.781-0.925) Wassaw Island, GA (this TEWG rS=0.81 (0.77-0.84) Melbourne Beach, FL (this TEWG report) S=0.73 (0.71-0.76) Quintana Roo, Mexico (this TEWG report) S=0.85 (0.81-0.88) Sex ratio = 34-47% (this TEWG report) Average size of neophyte nester aPeninsular Florida, and Mexico sucm CCLstd (91.2 cm SCLstd) and 9

neophytes’ measurements fell in t109.3 cm CCLstd (82.0-100.5 cm S

report). Snover (2002) age at maturity (90 Byrd et al. (2005) Min size of S.C. nester = 80.7 cm CCL Dahlen et al. (2000) Min mean number nests per femaand 4.1 for remigrants Scott (2006) number of nests per Wassaw Island nesting females 

2 Note that these 95% confidence intervals were not presented in the original publication but were calculated from the raw data presente
8 

Figure 2. Size frequency data of loggerheads captured in North Carolina (Epperly et al. 

2007; NMFS unpublished data). 

0

20

40

60

80

100

120

140

160

180

200

0 20 40 60 80 100 120

Standard Straight Carapace Length (cm)

Frequency

NC Data

Normal PDF fit to Data

Nesting Females, Adult Stage, and Sizes –Sheryan Epperly

Few long-term nesting beach datasets exist within the five subpopulations and even fewer have 

long-term mark-recapture data that identify individual nesters and track individual females’ 

fecundity over time. The first TEWG (1998) analyzed Wassaw Island, Georgia tagging data to 

determine size at sexual maturity for female loggerheads. They determined that the average size 

of first-time nesters was 92.9 cm SCLstd; this information was provided in a summary of 

demographic parameters for a deterministic model (their Appendix 4). NMFS SEFSC (2001) 

examined Cooperative Marine Turtle Tagging Program (CMTTP) data “for original tagging 

events” from nesting beach survey products and calculated a different average size of 90.4 cm 

SCLstd. 

To provide a more current and broader perspective on adult size, fecundity, and survival, this 

TEWG examined nesting beach data for three purposes. First, we explored the size distribution 

of putative first-time nesters to define the beginning of the Adult Stage (V) which is used at 

several points in our report. Second, we examined the data to determine if the size of putative 

first-time nesters had shifted to smaller or larger size. The direction of any size-at-maturity 

change could account for the reduction in nesting activity and reproductive output through longer 

remigration intervals, decreased number of clutches laid, and/or smaller clutch size (see Part II). 
9 

Lastly, the full nesting beach mark-recapture datasets were examined to estimate survival rates 

and to evaluate whether there had been changes in survival over time (see Part III). 

We acquired data from five beaches, representing three subpopulations, with adequate long-term 

mark-recapture data: (1) Bald Head Island, (2) Wassaw Island, (2) Casey Key and Manasota 

Key, (4) Keewaydin Island, and (5) Aventuras, Chemuyil, Xcacel, and Xel-ha beaches. Three of 

these beaches represent the few locations where there has been almost-complete saturation 

tagging of nesting females for several years. Unmarked females were inferred to be putative 

first-time nesters, but it is important to note that previously they may have nested elsewhere or 

had not been detected on the sampled beach. While the probability of not being detected within 

their first nesting season on a monitored beach, given multiple emergences, is low, we have no 

way of knowing whether a female had previously nested on unmonitored beaches. We 

acknowledge that our estimates of the size of putative first-time nesters likely are biased high. 

Generally, marked animals were considered remigrants, even if they had not been detected on 

that particular beach earlier. It is possible that these animals received their marks during inwater captures and may not have nested previously. Animals with tagging scars were re-marked, 

but considered remigrants; this may overestimate the remigrant population as the lost marks 

could have been applied before the animal reached maturity (or while nesting on a different 

beach). In nearly all cases, the investigators identified putative first-time nesters and remigrants 

in the databases provided to us. 

Northern U.S. Subpopulation

Bald Head Island, North Carolina U.S. – Since 1980, turtles have been intercepted and marked 

nightly on 15.3 km of beach between late May and mid August (Hawkes et al. 2005; Hedges 

2007). Double flipper tagging with inconel tags began in 1991. PIT tagging began in 2002 to 

augment flipper tags. Animals with existing marks or tag scars were identified as remigrants. 

Unmarked and unscarred turtles were identified as putative first-time nesters. Standard 

measurements of carapace length (SCL and CCL) were taken through 2003; beginning in 2004, 

minimum SCL and CCL lengths were taken instead (straight and curved). We were provided 

with the entire dataset from 1980-2007. 

Wassaw Island, Georgia U.S. – Nightly monitoring of the ~14 km island started in 1973 

(Williams and Frick 2001). Monitoring begins in early May and ends in the middle of August. 

Project personnel intercept and identify an average of 82% of the nesting females using the 

beach (K. Williams pers. comm.). Double flipper tagging with inconel tags began in 1988. PIT 

tagging began in 1992, but it was not until 1999 that tags and readers were standardized and the 

investigators were certain that they were capable of detecting all PIT tags (Prior to 1999 

personnel used 128 kHz tags and Trovan readers to scan the turtles). Thus, based on PIT tags 

alone, they could detect animals that they tagged but not animals tagged by other researchers 

with a different frequency of PIT tag – e.g., immigrants). Animals with existing marks 

previously applied at Wassaw Island were identified as remigrants; for the purpose of our 

analyses, we also included immigrants (previously marked in another location), and tag-scarred 

turtles. Since 1995, 45 animals were identified as remigrants/immigrants based on the presence 

of PIT tags alone. Unmarked and unscarred turtles were identified as putative first-time nesters. 

Standard straight carapace lengths were taken through 1989. In 1990, standard measurements of 
10 

straight or curved carapace length were taken (but not both on the same animal) and after 1991 

the standard CCL was taken. We were provided the entire dataset spanning 1973- 2008. 

Peninsular Florida Subpopulation

Casey Key and Manasota Key, Florida U.S. – These two beaches are in very close proximity to 

each other and animals detected nesting on one sometimes also nesting on the other (T. Tucker 

pers. comm.). Hence, they are reported together. The consistent data and standardized tagging 

and measurement dataset for the 11.8 km of Casey Key and 13.8 km of Manasota Key extends 

from 2002-2006. During this period, all turtles intercepted were double tagged with flipper tags 

and PIT tags on Casey Key. Tagging effort occurs only on the southern 6 km of the Casey Key 

beach and on the northern 7.4 km of Manasota Key (during 2007 they could survey only 5.7 km 

due to extremely soft sand). While monitoring effort has been nightly, all night, at Casey Key 

(T. Tucker pers. comm.), effort at Manasota Key has been more variable (often efforts end by 1-

3 am). It is estimated that 20-40% of the nesting females are intercepted on Casey Key (T. 

Tucker pers. comm.) and about 5% are intercepted on Manasota Key (J. Grimes pers. comm.) 

Animals with existing marks or tag scars were identified as remigrants. Unmarked and 

unscarred turtles were identified as putative first-time nesters. We acknowledge that with such 

low tagging effort, assuredly some remigrants are included as putative first-time nesters. 

Standard and minimum SCL and CCL were recorded. We were provided the size data for 

putative first-time nesters 1997-2006 for both beaches and 2007 data were later provided for 

Casey Key (T. Tucker pers. comm.) for the survival rate analysis. The putative first-time nester 

analysis was based on the 2002-2006 data. 

Keewaydin Island, Florida U.S. – Nightly monitoring began in 1985 and occurs from May 15 

through August 15 (Addison et al. 2004). The island is approximately 12 km in length, but only 

7.2 km is surveyed regularly at night; beginning in 1993 the remaining 4.8 km to the north was 

surveyed for nesting activity each morning. It is estimated that they intercept 75-95% of females 

nesting annually (D. Addison pers. comm.). Double tagging with inconel tags began in 1990 and 

PIT tagging began in 2007 (D. Addison pers. comm.). Animals with tag scars or existing marks 

were identified as remigrants. Unmarked and unscarred turtles were identified as putative firsttime nesters. They also identify as putative first-time nesters animals tagged elsewhere but seen 

on Keewaydin Island only once. Standard and minimum measurements were taken for both 

straight and curved carapace lengths. We were provided the size data for putative first-time 

nesters 2002-2005 (D. Addison pers. comm.). 

Mexican Subpopulation

Quintana Roo: Aventuras, Chemuyil, Xcacel, and Xel-ha beaches, México - Nightly monitoring on 

these beaches from early May to the end of October began on a regular basis in 1987, but it was 

not until 1996 that tag supplies were sufficient to mark all animals intercepted; animals were 

single tagged with inconel tags (Zurita et al. 1997). The tagging efficiency3

 since 1996 has been 

estimated at 79-87% (Zurita et al. 2003) and at >90% since 2000 (J. Zurita pers. comm.). 

Animals with tag scars or existing marks were identified as remigrants. Unmarked and 

unscarred turtles were identified as putative first-time nesters. No immigrants from other areas 

have been detected on these beaches (J. Zurita pers. comm.). Standard measurements of curved 

 

3

 Tagging efficiency is defined by Hopkins and Richardson (1984): The efficiency of a tagging program at a nesting 

beach is directly related to the proportion of nests that can be identified with a female in the nesting area. 
11 

carapace length were taken. We were provided the size data for putative first-time nesters 1987-

2005 and were provided annual estimates of percent putative first-time nesters for 1996-2006 (J. 

Zurita pers. comm.). 

Size of Putative First-Time Nesters –Sheryan Epperly

We used standard curved carapace length (CCLstd) for our analysis because it was the 

measurement most often recorded for nesting females. For 2002-2006 all beaches reported 

CCLstd, except for Bald Head Island which reported CCLmin for 2004-2006. Data from 

Keewaydin Island and Casey Key were used to derive a relationship between CCLstd and CCLmin, 

and the CCLmin data of Bald Head Island were converted to CCLstd with the following equation: 

CCLstd = 7.529 + (0.938 * CCLmin), r-square = 0.920, N = 65 

The relationships between CCLstd and SCLstd for nesting turtles are expressed in following 

equations. The measurement relationships were based on data available from Bald Head Island, 

Casey Key, and Keewaydin Island. 

SCLstd = 8.879 + (0.838 * CCLstd), r-square = 0.798, N=556 

CCLstd = 11.381 + (0.953 * SCLstd), r-square= 0.798, N=556 

The distribution of putative first-time nester sizes (CCLstd) during 2002-2006 was compared 

among beaches (Table 3, Figure 3). The average size of putative first-time nesters was 

significantly larger on Bald Head Island (100.4 cm) than the average size on either of the two 

Florida beaches (96.9 cm and 97.0 cm), but not significantly larger than the average size of 

putative first-time nesters on Wassaw Island (98.4 cm) or in Quintana Roo (98.7 cm). The 

average size of putative first-time nesters on the two Florida beaches were not significantly 

different from each other nor from any other beach except Bald Head Island. 

Despite the difference in sizes between Bald Head Island and two other beaches, data were 

pooled among beaches to assess the size distribution of all putative first-time nesters. Univariate 

statistics for the pooled CCLstd data also are provided in Table 3. The mean size of a putative 

first-time nester was 98.2 cm CCLstd (91.2 cm SCLstd) and 95% of the putative first time nesters’ 

measurements fell in the range of 87.2–109.3 cm CCLstd (82.0-100.5 cm SCLstd). We were not 

able to examine the size data over time for trends. We note that the average size of remigrants 

on Bald Head Island (104.5 cm) was significantly larger than the average size of putative firsttime nesters on that North Carolina beach, and that remigrants of Wassaw Island (100.2 cm) also 

were larger than putative first-time nesters on the Georgia beach; we did not have access to data 

on remigrants elsewhere. 

Summary

Based on tagging data from nesting beaches in North Carolina, Georgia, Florida, and Quintana 

Roo, the minimum size of the adult stage (V) is 87.2 cm CCLstd (82.0 SCLstd ). These sizes, are 

smaller than the sizes used the first TEWG, but are derived from broader geographic coverage. 

The minimum size is based on the 2.5 percentile of the size distribution of all putative first-time 
12 

nesters. These results provide a conservative estimate, yet one that undoubtedly includes bias, as 

unmarked females, while inferred to be putative first-time nesters, possibly could have nested 

elsewhere and were not detected and marked. Putative first-time nesters were found to be 

significantly smaller than remigrant turtles on the North Carolina and Georgia beaches 

representing the Northern U.S. Subpopulation. 

Table 3. Putative first-time nester sizes (CCLstd) for Bald Head Island, N.C. (2000-2006), 

Wassaw Island, Ga. (2000-2006), Casey Key and Manasota Key, Fla. (2002-2006), 

Keewaydin Island, Fla. (2002-2005), and Quintana Roo, México (2000-2005). 

 

Mean Median Mode

Std. 

Dev.

Std. 

Error 

of 

Mean

95% 

CI Range 

2.5-97.5 

Percentiles N 

Northern U.S. 

Subpopulation 

99.4 99.0 99.0 5.9 0.47 98.5-

100.3

84.0-

115.0 

86.8-110.2 158

Bald Head 

Island 

100.4 100.4 105.1 5.7 0.65 99.1-

101.7

85.8-

111.5 

85.9-110.4 77 

Wassaw Island 98.4 99.0 99.0 6.0 0.67 97.1-

99.7 

84.0-

115.0 

86.0-109.0 81 

Peninsular 

Florida 

Subpopulation 

97.0 97.0 100.0 6.7 0.33 96.3-

97.6 

81.0-

115.0 

86.0-109.0 300

Casey Key 

Manasota Key 

97.0 97.0 100.0 5.6 0.38 96.2-

97.8 

81.0-

115.0 

86.0-109.9 219

Keewaydin 

Island 

96.9 97.0 97.0 5.7 0.64 95.7-

98.2 

84.0-

109.1 

84.0-107.5 81 

Mexico 

Subpopulation 

98.7 99.0 99.0 4.9 0.25 98.2-

99.2 

80.5-

115.0 

80.4-109.3 368

Quintana Roo 98.7 99.0 99.0 4.9 0.25 98.2-

99.2 

80.5-

115.0 

80.4-109.3 368

All Beaches 98.2 98.4 100.0 5.5 0.19 97.8-

98.6 

80.4-

115.0 

87.2-109.3 826
13 

Figure 3. Schematic plot of distributions of putative first-time nester sizes, 2002-2006 (2005 

for Keewaydin Island). The y-axis is CCLstd (cm). The 75, 50, and 25 percentiles are depicted, 

along with the ranges and the means (+). 

 | 

 115 + 0 0 0 

 | 

 | 0 | | 

 | 0 | | | 

 110 + 0 | | | 

 | | | | | | 

 | | | | | | 

 | | | | | | 

 105 + | | +-----+ | | 

 | | | | | | | 

 | | | | | | +-----+ 

 | | +-----+ | | +-----+ | | 

 100 + +-----+ | | *--+--* | | | | 

 | | | *--+--* | | | | *--+--* 

 | *--+--* | | +-----+ *--+--* | | 

 | | | +-----+ | | | | | 

 95 + | | | | | | | | 

 | | | | | | | +-----+ 

 | +-----+ | | +-----+ | 

 | | | | | | 

 90 + | | | | | 

 | | | | | | 

 | | 0 | | | 

 | | 0 | | | 

 85 + | | | 

 | | | | 

 | 0 | 

 | | 

 80 + 0 

 ------------+-----------+-----------+-----------+-----------+----------- 

 Keewaydin Is. Quintana Roo Bald Head Is. Cas/Man Key Wassaw Is.

Sex Ratios –Jeanette Wyneken

Data on sex ratios are important in a number of contexts including the identification of shifts in 

vital rates and population vigor, recognition of impacts from climate change or other 

environmental alteration, and in understanding mating systems. Both prior TEWG reports 

summarized the available information on sex ratios from the literature. The 2001 assessment 

(NMFS SEFSC) estimated juvenile sex ratios of the Peninsular Florida (80% female), Northern 

U.S. (35%), and Mexico (69%) Subpopulations based on necropsied stranded animals, 

testosterone titers, and laparoscopies of in-water captures, and related information on the natal 

origins of animals on foraging grounds. Here we provide updated information on sex ratio data 

for loggerheads in the Atlantic, with a focus on the Northwestern Atlantic region. 
14 

Sex ratios are described for hatchling, juvenile and adult. Hatchling sex ratios are most often 

established at the level of the clutch and are measured in various ways. They are often calculated 

from the sexes of the hatchlings produced. Loggerhead hatchling sex ratio is influenced by the 

incubation environment, and the embryo initially develops a gonadal ridge that is neither male or 

female. During the middle third of incubation is the period of incubation gonadal sex is directed 

to become either testis or ovary (Yntema and Mrosovsky 1980; Maxell et al. 1988). The primary 

factor implicated in sex determination is incubation temperature (critically reviewed by Limpus 

et al 1983; Mrosovsky 1994; Miller and Limpus 2003; Miller et al. 2003; Wibbels 2003). The 

sex ratio response of eggs and nests to temperature appears to vary (Limpus et al. 1985; Godfrey 

and Mrosovsky 2001) and may not be well represented by average nest temperatures (Georges et 

al. 1994; Wibbels 2003; Blair 2005). Other environmental factors (e.g. rainfall, soil moisture, or 

shade) directly or indirectly influence sex ratios (Godfrey 1997; Mrosovsky et al. 1995). 

Juvenile and adult sex ratios are derived from animals that have already hatched (e.g. juveniles 

captured at sea, adults captured at sea, or stranded animals). Juvenile and adult sex ratios of sea 

turtles typically differ from hatchling sex ratios because they integrate a number of life history 

events including the effects of mortality in younger stages, spatial and temporal variations in 

distribution, and a single stage class being studied may include individuals produced from 

rookeries over a number of different seasons. Additionally, sex ratios of juveniles and adults may 

reflect the integration of mixed stocks. Operational sex ratios are based on the reproductively 

active males and females in an assemblage at any given time. There are no data available that 

quantify operational sex ratios in Northwestern Atlantic loggerhead turtles. 

Hatchling sex ratios serve as the starting point for both juvenile and adult sex ratios. Although 

more datasets have been published on hatchling sex ratios than other life stages, overall 

relatively little is known about population-wide sex ratios at any level (hatchling, juvenile or 

adult) and so we restrict our discussion to sex ratios by size or stage classes, except where 

supporting documentation allows more specific categorization of the sex ratios. 

Hatchling sex ratios are important in part because they represent the pools from which future sex 

ratios arise. Shifts in hatchling sex ratios may have cascading effects on future generations if 

changes are extreme enough to impact productivity. Often, hatchling sex ratio estimates vary 

greatly across locations and years. Loggerhead sex ratios have been calculated variously and are 

summarized below by their sources (Table 4). Generally, in the Atlantic, there is a tendency for 

larger loggerhead rookeries located closer to the equator producing more female hatchlings on 

average, with smaller rookeries located further away from the equator producing more variable 

sex ratios (Table 4). A major caveat associated with this statement is that few rookeries have 

been rigorously studied for multiple years. Also, many studies reporting beach-based sex ratios 

are based on nest or beach temperature but lack adequate validation for temperature ranges found 

at the study sites. Most studies with validation are based on relatively small sample sizes, and 

are frequently under-sampled to accommodate local conservation goals. Also, some sex ratios 

are also estimated from dead hatchlings remaining in the nest after emergence. It is unlikely that 

sex ratios calculated for individual nests from dead-in-nest hatchlings are accurate measures 

because of insufficient samples (based on binomial probabilities) and/or because of the potential 

for sex-biased mortality of embryos or hatchlings. 
15 

For juvenile sex ratios, more recent data have been made available for foraging populations 

(Table 5). However, foraging areas are often visited by turtles that originated from different 

rookeries, which in turn may have different hatchling sex ratios. Therefore, it is often difficult to 

link juvenile sex ratios directly to hatchling sex ratios, because of the lack of direct genetic 

sourcing of individual juveniles to rookeries. 

In the case of adult sex ratios, there remain profound gaps in our knowledge and we lack sex 

ratio data for all regions in the Atlantic. Yet, such information is important because shifts in 

productivity are difficult to interpret without an understanding how many animals of each sex 

breed in a season and how this varies temporally and spatially. Sex ratios may be important in 

the context of loggerhead mating systems and in clutch quality. Promiscuous mating systems are 

characteristic of sea turtles (Miller 1997; Pearse and Avise 2001). In promiscuous mating 

systems, several factors potentially may impact egg production and hatching success. These may 

include numbers of bouts of mating by individuals, duration of mating (important in Chelonia 

mydas; Wood and Wood 1980), mate selection, and multiple paternity within a single clutch of 

eggs (Zbindin et al. 2007; Bollmer et al. 1999). Factors that are important in many lower 

vertebrates such as possible sperm competition or social induction of follicle maturation or 

ovulation are unstudied in sea turtles. If adult sex ratios are too skewed, potential negative 

impacts from the Allee effect (Berec et al. 200; Marcovaldi and Chaloupka 2007) have been 

postulated, but remain unstudied or understudied in marine turtles (Wyneken and Heppell 2007).
16 

Table 4. Sex ratios as percent of female Caretta caretta hatchlings, dead and alive, 

summarized and modified from Godfrey (1997). Here we do not classify sex ratios as primary 

of secondary because there is currently no uniform definition. We note that in sea turtles, 

primary sex ratio may be the sex ratio all of eggs or all hatchlings and that ratio does not account 

for post-deposition or post-hatching morality. Secondary sex ratios in sea turtle hatchlings may 

be either the ratio at hatching or emergence. 

Location Year Sex ratio 

(% female) 

Comments 

Code 

Reference 

South Carolina and 

Georgia, U.S. 

1979, 80, 

82 

56.3% A, H Mrosovsky et al. 1984 

North Carolina, South 

Carolina and Georgia, 

U.S. 

2002 

2003 

80% 

60% 

A, F, G Blair et al. 2005 

North Carolina, South 

Carolina Georgia, U.S. 

2002 

2003 

79% 

37% 

A, F, H Wyneken et al. unpub. 

data 

North Carolina, U.S. 1980-

2005 

58% D, J, H Hawkes et al. 2007 

Florida, U.S. 1987-89 ~90% A, H Mrosovsky and 

Provancha 1989, 1992 

SE Florida, U.S. 1998 ~92.5% D, J Hanson et al. 1998 

SE & SW Florida, U.S. 2002 

2003 

2004 

84% 

90% 

100% 

A, F, G Blair et al. 2005 

SE & SW Florida, U.S. 2002 

2003 

2004 

67% 

88% 

97% 

A, F, H Wyneken et al. unpub. 

data 

Peninsular Florida, U.S. 

(= Southern 

Subpopulation) 

1995-

1999 

80% I, L NMFS SEFSC 2001 

Sergipe and Bahia, 

Brazil 

1988-

1994 

92.6-96.9% J, H Marcovaldi et al. 1997 

Espirito Santo, Brazil 1988-

1994 

57.3% J, H Marcovaldi et al. 1997 

Boa Vista Island, Cape 

Verde archipelago 

2003-

2004 

67% B, E Delgado 2008 

Table 4 and 5 Comment Codes: 

A. Estimate based on small sample size or sample results extrapolated 

B. Only part of season was studied 

C. Changes in nesting frequency not taken into account 

D. No in situ nests actually sampled 

E. Only dead hatchlings investigated 

F. Verified through laparoscopy and/or biopsy 

G. Sample sex ratio, not scaled for production 

H. Sex ratio scaled for production or estimated assemblage size 
17 

I. Necropsied strandings 

J. Calculated using temperature or other indirect estimate 

K. Hormonal assay 

L. Calculated from Texas, North Carolina, and South Carolina strandings sex ratio & natal 

origin probabilities 1995-97, assuming stable mortality 

1 % female calculated from published ratio. 

2. Sampling of mixed stock on foraging grounds 

Table 5. Sex ratios as percent of Caretta caretta juveniles, modified from Godfrey (1997). 

Comment codes are provided in key of Table 4. 

Location Year Sex ratio 

(% female) 

Comments 

Code 

Reference 

North Carolina U.S. 1995-

2002 

68% F, 1 Braun-McNeill et 

al. 2007b 

Florida 1980s 65% K, 1 Wibbels et al. 

1987 

Peninsular Florida U.S. 

(= Southern 

Subpopulation) 

1995-

1999 

80% I, L NMFS SEFSC 

2001 

Northern U.S. 

Subpopulation 

1995-

1999 

35% I, L NMFS SEFSC 

2001 

Yucatán Subpopulation 

Mexico 

1995-

1999 

69% I, L NMFS SEFSC 

2001 

Gulf of Mexico (Texas, 

Florida Gulf coast) U.S. 

1995-

1999 

74.5% I NMFS SEFSC 

2001 

Southeast Florida, U.S. 1995-

1999 

70.5% I NMFS SEFSC 

2001 

NE Florida through 

Maine, U.S. 

1995-

1999 

67.5% I NMFS SEFSC 

2001 

Eastern Atlantic 2000s 66% F, 1, 2 Delgado 2008 

Eastern Atlantic 2000s 66.7% F, K, 2 Dellinger 2007 

Sex Ratios Estimated from Stranded Turtles

Strandings data represent an alternative sampling source for sex ratios based on dead or 

moribund turtles that are found ashore (beach-cast). However, because juvenile and adult sea 

turtles, while foraging or migrating, are of mixed stock (i.e., they come from different source 

nesting beaches, which may have different hatchling sex ratio production values), sex ratios 

calculated from stranded sea turtles (strandings) only reflect those of the standing stock if death 

rate and stranding rate by stage are the same for both sexes. Death rates by life stage appear not 

to be the same for both sexes. In various marine fish populations, there is often a sex ratio bias 

of captured individuals, despite a presumed 1:1 offspring sex ratio (e.g. Bessa et al. 2007). Thus, 

sex ratio data of stranded turtles remain challenging to interpret because of the many unknown 

factors that bias these samples. Sources of bias may include temporal variation in spatial 
18 

occurrence of immature turtles, differences in sex-specific death rates, influences of sex-specific 

behavior differences, sex-specific risks, and resolution differences due to integration of multiple 

year-classes of immature turtles (and even mature turtles). The probability of a carcass washing 

ashore is greater for turtles that die closer to shore (Hart et al. 2006). If the sexes differ in their 

proximity to shore, such a spatial difference could bias results as well. However, with the 

recognition that strandings, like many biological samples, have some biases, they nonetheless are 

a sample source of disabled or dead turtles that we can quantify. These turtles became stranded 

if they were killed or debilitated near shore and, while they clearly are an incomplete sample, 

they represent multiple year classes. As such, if one selects data that meet the most rigorous 

criteria for sex identification, they may indicate juvenile or adult sex ratios (or trends in sex 

ratios) of turtle assemblages. Where sampling or observer effort is uniform, changes in sex 

ratios of these multiyear classes of strandings deserve attention as they may reflect long scale 

shifts in production of one sex, changes in spatial occurrence, mortality variation, major 

mortality events (that removed reproductive turtles or pre-reproductive immature turtles that 

should have recruited to reproductive stages), or some combination of these factors. Thus, sex 

ratios of stranded turtles warrant investigation. 

We examined the sex ratios in stranded turtles using several subsets of the Sea Turtle Stranding 

and Salvage Network (STSSN) database (Appendix A). Here we summarize those results: 

• Sex ratios of immature and mature turtles are not the same. About 70% of the immature 

turtles were females and the percent females decreased between the immature and the 

mature stages. These changes suggest that mortality rates and/or the probabilities of 

stranding are not uniform for both sexes by life stage (length classes). 

• We did not detect large changes in sex ratios over time in two sets of years surveyed. If 

long-term shifts in sex ratio occurred, we cannot detect them from strandings at this 

time. Because multiple year classes contribute to each stage class, and loggerhead turtles 

are late maturing animals, several more decades of data are needed to detect sex ratio 

shifts over time and only if such a shift persists for a biologically sufficient period to 

allow detection. 

• While the sex ratios of immature turtles were female-biased in all regions, the sex ratios 

of mature turtles tended to be nearly 1:1 or slightly male-biased across most regions. We 

failed to reject the null hypotheses that observed sex ratios were similar across regions 

for most size classes. 

• The sex ratios of stranded turtles were not similar among regions when we examined the 

largest acceptable dataset (1987-2004), but when we examined only data from animals 

with verified sex assignments, we could not reach the same conclusion. The significant 

differences were attributed to the adult-sized animals. We found female bias common 

when data were grouped by state. 

• In states and regions that host nesting, the sex ratios were usually female-biased, and 

tended to be slightly more female-biased during the nesting season of May-September. 

The numbers of female strandings were much higher in the Northeast and in North 

Carolina-Georgia during May-September. This combination may reflect the return of 

nesting turtles to nearshore waters and the return of non-nesting or post-nesting turtles to 

temperate feeding grounds during warmer months. The increase in nesting season 
19 

mortalities probably also heralds increases in spring-summer fisheries and recreational 

activities. 

• We found no significant shift in the median sizes of either sex of stranded adult 

loggerheads. We note that it is possible that the time range covered may not be 

sufficient to detect a trend towards onset of breeding at a smaller size. 

• We note that the strandings data reflect large numbers of dead females in both the 

immature and adults size classes. The nearly uniform tendency for female bias in the 

data set of verified sex turtles suggests significant female mortality occurs which 

removes potential nesting turtles from population at all locations. 

Summary

Overall, the available data on sex ratios in Atlantic loggerhead sea turtles are intriguing but 

limited. At the current time, there is no indication that changes in hatchling, juvenile or adult sex 

ratios have contributed directly to the decline in nest numbers observed in the Southeast U.S. 

However we note that there is a clear data need from a wider spatio-temporal stretch to firmly 

characterize the sex ratios of different life stages of loggerheads. 

Spatial Distribution –Kate Mansfield, Heather Haas, and Sheryan Epperly 

Sea turtles are highly migratory, long lived animals. The previous TEWG reports provided brief 

summaries of the geographic range of loggerheads while the 2001 NMFS SEFSC assessment 

provided more information, particularly on the distribution on each of the subpopulations. 

Identifying core areas of habitat use, seasonal dispersal patterns and size- or sex-specific patterns 

of movement will allow for a better understanding of the potential hazards these animals may 

encounter and will provide the basis for spatially targeted management strategies. Understanding 

the spatial distributions of loggerheads captured within the Western North Atlantic will provide 

insight to: 

1) The degree of spatial overlap among turtles originating from different subpopulations; 

2) Whether high use areas seasonally exist for turtles from different subpopulations, size 

classes or sex; and 

3) Whether these high use areas overlap with known sources of sea turtle mortality, or with 

regions subjected to ecological change and habitat degradation; 

We used three approaches to identify spatial overlap, high use areas and seasonal movements 

and habitat occupancy among loggerheads captured along the eastern U.S. seaboard and the Gulf 

of Mexico. The first approach includes an examination of available conventional tag data. The 

next approach included analyzing available satellite telemetry data to determine areas of high use 

based on seasonal sex-, size-, or subpopulation-specific data. The final method utilized historic 

aerial survey data to provide verification for the observed distributions derived from satellite 

telemetry. 
20 

Conventional tag data 

While tag returns from conventional tagging methods using inconel, monel, or Passive Integrated 

Transponder (PIT) tags are valuable for inferring growth rates or general dispersal and 

movement information for loggerhead sea turtles, recapture data must be interpreted with 

caution. Not only are recapture records highly dependent on tags being reported by the public, 

but recapture data only provide information at the time of original capture (‘Point A’), and at the 

time of recapture (‘Point B’). With the exception of localized in-water mark and recapture 

programs in North Carolina, Virginia and Florida, and a few long-term nesting beach tagging 

programs (North Carolina, Georgia, and Florida), the majority of recaptures usually reflect 

mortality events occurring along a journey or at a specific time in their life histories, rather than a 

destination for these turtles (‘Point C’). As such, the reliability of returns, if trying to evaluate the 

proportion of a stock of turtles that travel to specific areas, is problematic. 

Methods 

We examined the flipper and PIT tag records from 1980 through 2007 in the Cooperative Marine 

Turtle Tagging Program (CMTTP) database (http://accstr.ufl.edu/cmttp.html) From 1980- 

through 2007, the CMTTP distributed nearly 250,000 inconel, monel, and plastic tags. 

Turtles were initially tagged and/or found by a variety of sources including: nesting beach 

surveys; headstart programs; general TED testing; rehabilitation and display turtles (for 

education purposes in an aquarium); stranding networks; cold stunning events; incidental capture 

(shrimp trawls, including try nets and bib nets, fish trawls, gill nets, longline, hook and line, 

pound net, dredges, etc.); pound net mark and recapture research; gill net mark and recapture 

research (including stationary entanglement, turtle, stop, block, trammel, and tangle nets; 

encircle netting, purse seine and long haul seines); hand capture for research purposes (including 

cast and dip nets, scuba, and any methods which require human effort alone); shrimp and fish 

trawl research; power plant impingement; captures in water intake canals; and other 

miscellaneous or unknown sources. Because the tagging purposes were so varied, we focus only 

on inferred turtle movements on a broad scale. 

Inconel and monel tags are applied externally, typically to the front and/or rear flippers; PIT tags 

are inserted into the muscle tissue of a turtles’ shoulder, front flipper or in between the digits of a 

turtle’s front or rear flipper. 

 

Over 10,000 first-time loggerhead tagging events and more than 9,100 subsequent recaptures 

have been reported since 1980; approximately 700 loggerhead recaptures are reported annually. 

These returns originate from the same sources reported above with the largest proportion of 

recovered tags reported by nesting beach surveys (71%). Geographic regions were assigned 

based on the reported state or country of capture, but if these data were missing, regional 

assignments were made by assessing the zone of capture or the reported capture latitude and 

longitude (Table 6). We included data from only those turtles that were reported to be captured 

in the United States on their first tagging event, because not all releases outside the U.S. are 
21 

reported to the CMTTP. Note that the CMTTP database does not represent all turtles tagged 

within the United States. Additional tag databases exist, most notably one managed by the 

University of Florida (UFL). The UFL database has been existence since 1950 and contains 

information for over 220,000 tags. While portions of this database were merged with the CMTTP 

database in April 1999, some older and/or proprietary data were not merged with the CMTTP. 

We tallied the number of loggerheads that were originally tagged in each region within the U.S. 

and subsequently recaptured (Table 7). For each original tagging region (Table 6), only the 

number of turtles recaptured is reported by recapture region (rather than the total number of 

recapture events). This approach decreases the bias associated with differential reporting rates 

between the regions and protects the proprietary nature of these data. 

A total of 3,797 individual animals had recapture histories recorded in the CMTTP database. 

Although some movement between regions was reported, the majority of recaptures occurred in 

the same region where the original tagging occurred (Table 7). 

Turtles tagged within the GOM region likely remain within the southern geographic regions 

(GOM, SEU, and CCA) and are less likely to range into the northern regions (NAO, NEC). 

Genetics data from developmental habitats in the NEC and North Carolina indicate that 

immature turtles foraging in these areas originate from several subpopulations (Norrgard 1996; 

Rankin-Baransky et al. 2001; Bass et al. 2004; Bowen et al. 2004). It is not surprising, therefore, 

that there is overlap in both the SEU and NEC region-based recaptures. 
22 

Table 6. Description of regional strata. Cap_ST refers to the reported state or country of 

capture. CAP_ZONE refers to NMFS statistical zones (http://www.sefsc.noaa.gov/ 

seaturtleSTSSN.jsp). CAP_LAT and CAP_LONG refer to the reported latitude and longitude of 

capture (respectively) coded as five digits: degrees, minutes, tenths of minutes. Unknown 

locations are coded as ‘99999’; we assumed ‘--999’ (last three digits) also refers to unknown 

information. 

 Region Included data 

NAO North 

Atlantic 

Oceanic 

Cap_ST=Azores, Bermuda 

CAP_LAT=45270 and CAP_LONG=41510 

CCA Caribbean 

and 

Central 

America 

Cap_ST=Antigua, Belize, Bahamas, British West Indies, British 

Virgin Islands, Cuba, Costa Rica, Dominica, Dominican Republic, 

Grenada, Cayman Islands, Honduras, Haiti, Jamaica, Guiana, 

Panama, Puerto Rico, U.S. Virgin Islands, St. Kitts, British West 

Indies, Trinidad, Turks and Caicos, Nicaragua 

GOM Gulf 

of 

Mexico 

Cap_ST=Alabama, Gulf of Mexico, Mississippi, Louisiana, Texas, 

Gulf Coast of Florida, Gulf Coast of Mexico (which represented all 

Mexico tags used in this analysis) 

 CAP_ZONE>=1 and CAP_ZONE<=21 

 CAP_LAT=27999 and CAP_LONG=82999 

 CAP_LAT=28999 and CAP_LONG=82999 

 CAP_LAT=30999 and CAP_LONG=84999 

NEC Northeast 

U.S. 

and Canada 

Cap_ST=Canada, Connecticut, Massachusetts, Maine, New 

Hampshire, New Jersey, New York, Rhode Island, Delaware, 

Maryland, Virginia 

 CAP_ZONE>=37 and CAP_ZONE<=44 

SEU Southeast 

U.S. 

Cap_ST=Georgia, Atlantic Coast of Florida, North Carolina, 

South Carolina 

 CAP_ZONE>=24 and CAP_ZONE<=35 

 CAP_LAT=27999 and CAP_LONG=80999 

 CAP_LAT=28999 and CAP_LONG=80999 

 CAP_LAT=30999 and CAP_LONG=81999 

 CAP_LAT=33999 and CAP_LONG=79999 
23 

Table 7. Tagged and recaptured turtles by region. The number of turtles tagged in the 

United States and later reported recaptured in our regions of interest (Table 6) are shown in the 

“Recaptured Tags” column. The values in the regional columns represent the number of turtles 

that were recaptured in that region (rather than the number of recapture events). In addition to 

the turtles reported in the recapture locations, there were 21 loggerhead recaptures with missing 

information for the recapture location (state, country, zone, latitude, and longitude). 

Approximately 250,000 tags have been distributed to turtle projects by the CMTTP. 

 Recapture Locations of Tagged Individuals 

Tagging 

Region

Recaptured 

Turtles 

CCA GOM NEC NAO SEU 

GOM 1,268 4 1,245 0 0 19 

NEC 63 0 0 38 0 25 

SEU 2,466 11 18 60 2 2,355 

Satellite Telemetry

In contrast to the “snapshot” perspective provided by conventional tag return data, satellite 

telemetry can identify sea turtle distribution patterns and habitat utilization (e.g. foraging areas, 

inter- and post-nesting movements, seasonal migratory behavior), and movement rates or 

survival. Spatial ranges of nesting stocks may be identified, as may seasonal distributions based 

on size classes and sex. 

Due to the high cost associated with satellite telemetry, as well as the time to meet set criteria to 

successfully navigate the permitting process in the U.S., and because that satellite telemetry is a 

relatively new method, few research programs have large or long-term datasets. As more datasets 

are established or built upon, there is potential for monitoring spatial trends over time (changes 

in distribution, seasonal distribution, changes due to the potential effects of global warming, 

etc.). 

Replicating the analyses used by the Leatherback Turtle Expert Working Group (TEWG 2007), 

we established a baseline analysis of sea turtle distributions within the Western North Atlantic 

using existing satellite data. We standardized our approach with the Leatherback TEWG by 

analyzing spatial composites that incorporate multiple tracking datasets. Several proprietary 

satellite data repositories currently exist including seaturtle.org’s tracking site and the OBISSEAMAP program. However, a neutral, management-based repository does not exist. Thus, the 

composites generated in this report required that TEWG members approach individual 

researchers, requesting tracking data for these analyses. There was a very high level of voluntary 

participation in these analyses resulting in approximately 85% of the existing track data for 

loggerheads tagged within the Western North Atlantic along the east coast of the U.S. and within 

the Gulf of Mexico (as of fall 2007). A complete list of contributors is provided in Table 8. 
24 

Methods 

Track data from adult female nesters and foragers, adult and immature males, and immature 

foragers (Stage III Juveniles) were compiled through the fall of 2007 in order to identify areas of 

high use and to determine any stock-, size class- or sex-specific patterns of habitat use. We 

obtained ARGOS location data for 248 individual turtles intercepted on nesting beaches or from 

captures in in-water studies ranging from New York, south along the east coast of the U.S., and 

in the Gulf of Mexico from Florida and Texas. These included in-water captured juveniles, 

nesting and foraging adult females from the Northern U.S. and Peninsular Florida nesting 

beaches and foraging grounds, and in-water captured male loggerheads (Table 8). The majority 

of telemetry tracks provided for this analysis were derived from the spatial region associated 

with the Northern U.S. Subpopulation. Among the adult nesting females represented, all 

originated from three nesting assemblages: the Northern U.S., Peninsular Florida, and Northern 

Gulf of Mexico. Juveniles from all of these sources commingle on the neritic foraging grounds 

(Bowen et al. 2004). The only track data available for Florida and the eastern Gulf of Mexico 

were derived from adult female nesters, resulting in some spatial bias related to tracking effort. 

All tracks were of varying duration and duty cycles resulting from different research priorities. 

Location data provided by ARGOS have a range of associated accuracies classified as Z, B, A, 0, 

1, 2, 3, with 3 as the highest accuracy and B as lowest. Locations are not determined for Location 

Class Z. Locations of lower quality tend to be less predictable. We filtered all data to exclude 

aberrant locations with a filtering algorithm for PC-SAS Version 9.0 created by David C. 

Douglas (U.S.G.S.): http://alaska.usgs.gov/science/biology/spatial/douglas.html. We used the 

hybrid filter which combines the minimum redundant distance and distance angle criteria. A list 

of the input parameters used (and associated rationale) for this analysis are included in Table 9. 

We selected median daily locations for each turtle based on the filtered positions to reduce the 

effects of autocorrelation. Positions for missing days, within periods of less than eight days and 

greater than one day from known positions, were estimated using a simple linear interpolation 

with the distance between the known positions divided evenly between the missing days. Thus, 

each daily position represents one track day per individual turtle. Locations were tallied into 

hexagonal area bins standardized for horizontal distance from 45o W over the curvature of the 

earth using cos(lat)*(lon+45) (James et al. 2005; TEWG 2007). Data were combined and plotted 

by size class (neritic juvenile or adult females), males, and nesting females by subpopulation to 

elucidate habitat use. For seasonal analyses, we defined Winter as January through March; 

Spring as April through June; Summer as July through September; and Fall as October through 

December. 

We did not analyze 38 proprietary tracks from nesting females in Florida during 1998-2000, but 

provide a summary taken from Foley et al. (2008). The tracks include 15 turtles from the Archie 

Carr National Wildlife Refuge (Atlantic coast, Brevard County), 13 turtles from Manasota Key 

(Gulf coast, Sarasota County), and 10 turtles from Cape San Blas (Gulf coast, Gulf County). 
25 

Results 

All animals 

A total of 248 individual turtle tracks were analyzed including 24,535 track days. Track data 

were collected between 1986 and 2007. Figure 4 represents the movements and habitat use for all 

sea turtles in this analysis. The majority of both turtles and track days were found to occur along 

the continental shelf out to the 200 m bathymetric contour line. Another high use area occurred 

along the southern Gulf coast of Florida between the Dry Tortugas and Cape San Blas (Figure 4). 

There were some turtles that tracked beyond the continental shelf to the northern Atlantic. Those 

turtles ranged as far east as approximately 35 ̊ W and between 30 ̊ N to 46 ̊ N. 

Juveniles 

Track data from 108 neritic juveniles (Stage III) were analyzed, spanning from 1986 through 

2007 (9,833 track days). With the exception of seven juvenile turtles tracked from Texas and 

Louisiana, all immature loggerheads were captured and tracked from waters ranging from 

Georgia north to Long Island, N.Y. (Figure 5). No juvenile loggerheads were captured and 

tracked from the eastern Gulf of Mexico or from Florida. The majority of tracked juveniles were 

found to occur along the continental shelf out to the 200 m bathymetric contour line. However, 

almost a fifth of the turtle tracks ranged beyond the continental shelf into to the northern Atlantic 

(Keinath 1993; Mansfield 2006; McClellan and Read 2007). Those turtles ranged as far east as 

approximately 35 ̊ W and between approximately 30 ̊ N and 46 ̊ N (Figure 5). Another high use 

area occurred along shelf waters off of eastern Texas and western Louisiana. Some juveniles 

tagged and released north of Florida, including as far north as Virginia, migrated south along the 

eastern Florida shoreline (Keinath 1993). Turtles tagged and released in Texas, remained on the 

shelf offshore of the Texas and Louisiana coastlines (Renaud and Carpenter 1994; Renaud et al. 

1994; J. Williams unpub. data). 

Seasonal composites (Figures 6A-D) indicate few to no juvenile turtles occurring close to shore 

north of Cape Hatteras, N.C. during the Winter. From Spring through Fall, turtles were found to 

occur in nearshore coastal waters with high use areas occurring from the North Carolina-South 

Carolina border north into Virginia’s Chesapeake Bay and coastal waters of the mid-Atlantic 

Bight. During the colder Fall and Winter months, turtles had a high frequency of days spent 

south of Cape Hatteras off of the Carolinas’ shorelines. 

 

Males 

We analyzed tracks from 36 male loggerheads (mostly adults) collected between 1991 and 2007, 

representing 2,612 track days (Figure 7). Four originated from the west coast of Florida, 29 from 

the east coast off Cape Canaveral. The remaining three originated from Virginia. The majority of 

males remained along the continental shelf out to the 200 m bathymetric contour line. A small 

number of males moved beyond the continental shelf into waters as far east as 60 ̊ W from the 

Delmarva Peninsula (Mansfield 2006; M. Arendt SCDNR unpub. data). High use areas occurred 

in shelf waters off of Cape Canaveral, Florida, along the west coast of Florida, and in the vicinity 

of Cape Hatteras, N.C. Turtles released from Florida’s west coast ranged from the southern tip of 

the state up to the Panhandle. Seasonal composites (Figures 8A-D) indicate no male turtles 

occurred coastally north of Cape Hatteras, N.C. during the winter months. 
26 

Adult Females 

We processed data for 100 adult female turtles tagged on nesting beaches between 1992-2007 

representing 11,863 days of tracking (Figure 9). The majority of adult female tracks originated 

from Northern U.S. Subpopulation nesting beaches ranging from Georgia to Virginia. Thirtythree of the 100 adult nesting females originated from the west coast and Panhandle region of 

Florida. With few individual exceptions, the majority of adult females remained on the 

continental shelf. High use areas occurred near shore from the North Carolina-South Carolina 

border north to Delaware Bay, and from Tampa Bay south to the Dry Tortugas (Figure 9). 

Turtles ranged as far south as the Gulf side of the Yucatán Peninsula and north and west coasts 

of Cuba. 

Seasonal composites (Figures 10A-D) indicate few to no turtles occurring coastally north of 

Cape Hatteras, North Carolina during January through March. Turtles also occurred more 

frequently offshore, remaining in deeper waters closer to the edge of the continental shelf. Fewer 

track data were available for the winter months resulting in the fewest track days occurring 

during this season. By the Spring and Summer, turtles occurred in near shore coastal waters with 

high use areas occurring from the North Carolina-South Carolina border north into Virginia’s 

Chesapeake Bay and coastal waters. Additional discrete areas of higher use occurred adjacent to 

the nesting beaches from which the turtle tracks originated. Some nesting females originating 

from Northern U.S. nesting beaches have been documented migrating north of Cape Hatteras 

post-nesting (Plotkin and Spotila 2002; Hawkes et al. 2007; D. Griffin SCDNR unpub. data). 

Nesting Females by Subpopulation

For Northern U.S. Subpopulation nesting females (n=64; 11,863 track days), high use areas 

occurred coastally from the North Carolina-South Carolina border north into the Chesapeake Bay 

and Delaware Bay and directly offshore of the Georgia nesting beaches where several turtles 

were captured and tagged (Figure 11A). There was some movement by northern nesters south 

into Florida (Mansfield 2006), as well as some movement off the shelf, particularly east of the 

mid-Atlantic Bight. There were two turtles that migrated from Virginia post-nesting south along 

the coast to the southern tip of Florida and into the Gulf of Mexico (Mansfield 2006). Turtles 

tracked from the west coast of Florida mostly remained on shelf waters within the eastern Gulf of 

Mexico (Figure 11B). These turtles ranged as far south as the Gulf side of the Yucatán Peninsula, 

along the north and west coasts of Cuba, and coastally along the northern Gulf of Mexico 

offshore of Louisiana and the Florida Panhandle. The few turtles tracked from the Northern Gulf 

of Mexico Subpopulation of nesting females ranged from their nesting beaches (Gulf Islands 

NWR) south to the Florida Keys and Dry Tortugas; none left the Gulf of Mexico (Figure 11C). 

Other Florida Nesting Females (from Foley et al. 2008)

Most post-nesting movements were directed and only a few of the turtles appeared to wander 

(Figure 12). Some of the turtles traveled along coastal routes but some crossed deep-water even 

when a coastal route was available. Females departing from the same nesting beach and sharing a 

similar post-nesting destination did not necessarily follow the same route. However, half of the 

females from the east coast (8 of 15) moved close along southeast Florida and the Florida Keys 

as they moved into the Gulf of Mexico. Within a few weeks of departing their nesting beach, the 

females took up residence in well-defined, relatively small areas (median of 2,000 km2

) on the 

continental shelf off Florida, Texas, Mexico, the Bahamas, and Cuba (Figure 12). The majority 
27 

of the females (22 of 38; 60%) from both subpopulations took up residence off the west coast of 

Florida between the Dry Tortugas and Cape San Blas. With few exceptions, turtles remained in 

their resident areas for the duration of the transmitter life (mean of 364 days, range 11−712 

days). Some turtles had resident areas that were near their nesting beach (<50 km) and some had 

resident areas distant from their nesting beach (>700 km). Most turtles migrated to a more 

distant nesting beach even though there were nesting beaches that were closer to their resident 

area. The resident areas of females from both subpopulations overlapped (Foley et al. 2008). 

Conclusions 

Nesting beaches and in-water foraging grounds were not sampled in proportion to their 

population sizes. The majority of tracks were obtained from research programs occurring from 

Georgia north to New York. Nevertheless, these data provide a foundation for the identification 

of temporal trends and distributions over time and provide insight into regional and seasonal 

movement patterns. However, effort should be made to include a greater spatial representation of 

Western North Atlantic loggerheads in the future. 

Despite ongoing research, data are still few or lacking for juvenile loggerheads in Florida; for 

oceanic loggerheads, particularly loggerheads from the eastern Atlantic; for loggerheads of all 

age classes in the Gulf of Mexico; male loggerheads throughout the Atlantic; from 

underrepresented subpopulations in Mexico, the Dry Tortugas, etc.; and for post-hatching and 

neonate turtles originating throughout the range for this species. The ideal approach would be to 

identify and track a proportional spatial representation of turtle populations within the Western 

North Atlantic. 

There are some spatial biases associated with tracking effort among the datasets used for these 

analyses, including: 

1) Lack of sampling consistency over time (including standardization of methods and/or 

temporal consistency); 

2) Lack of funding (particularly to sustain projects over time or to ensure strong spatial 

representation of data throughout the Atlantic and among size class or sexes);

3) Availability of existing proprietary data for management purposes.

Funding should be encouraged to support telemetry studies throughout the Atlantic, particularly 

for underrepresented size classes, sexes and stocks. Despite recognized data needs for the 

youngest size classes (TEWG 2000; Heppell et al. 2005), significant data gaps remain. Posthatching and neonate in-situ tracking studies have historically been limited by funding, logistics 

and the availability of small-scale technologies that allow for the remote tracking and 

characterization of where these animals are within the water column over extended periods of 

time. Few in-situ empirical data of neonate behavior, dispersal and survivorship exist. These 

data tend to have small sample sizes, are limited in spatial scope, and are constrained by laborintensive visual observations. 
28 

Table 8. List of satellite telemetry data contributors. 

Researcher Program Release Location(s) Turtle SourceSteve Morreale Cornell University Long Island, New York Immature foragers Jennifer Dittmar National Aquarium, Baltimore Outer Banks, North Carolina Immature forager Kate Mansfield Virginia Institute of Marine Science Virginia coast, Chesapeake Bay 

Immature foragers; pnesting adult femalemale 

Catherine McClellan Duke University (Marine Lab) North Carolina coast and Sounds Immature foragers Michael Coyne seaturtle.org Brendan Godley University of Exeter Mathew Godfrey NCWRC 

 Bald Head Island, North Carolina Post-nesting adult fe

DuBose Griffin SCDNR Sally Murphy SCDNR (ret.) Cape Island, South Carolina Post-nesting adult feMike Arendt SCDNR 

South Carolina; Cape Canaveral, Florida 

Immature foragers; amales 

Mark Dodd GADNR Georgia nesting beaches Post-nesting adult feMike Frick Caretta Research Project Wassaw Island, Georgia Post-nesting adult feTony Tucker Mote Marine Lab Florida, west coast Post-nesting adult feMark Nicholas Gulf Islands National Seashore Florida, Pan Handle Post-nesting adult feJo Anne Williams NOAA, Galveston 

Galveston, Texas; Gulf of Mexico Immature foragers 

From: Keinath 1993; Renaud and Carpenter 1994; Morreale and Standora 1998; Mansfield 2006; Hawkes et al. Read 2007; National Aquarium unpub. data, M. Arendt SCDNR unpub. data; D. Griffin SCDNR unpub. data; MResearch Project unpub. data, Tucker 2008; J. Williams NOAA/NMFS unpub. data; T. Tucker Mote Marine Lab Nichols Gulf Islands NWR unpub. data. 
29 

Table 9: Parameter settings for the Douglas Filter program run for loggerhead satellite 

telemetry data. All data were filtered to exclude aberrant locations with a filtering algorithm for 

PC-SAS Version 9.0 created by David C. Douglas (U.S.G.S.): 

http://alaska.usgs.gov/science/biology/spatial/douglas.html. 

Variable Value Rationale Variable explanation 

minoffh 0.0001 This is the suggested value when using Pickday 

= 1 (which we used). 

Minimum time likely to go without a 

transmission 

maxredun 5 This was the value used in the leatherback 

TEWG analysis. We kept this same value 

because loggerhead maxredun should not likely 

be greater than leatherback and should not 

likely be less than 5 km; 5 km is a relatively 

small distance in relation to the magnitude of 

known movement throughout a track line. 

Distance (km), less than which consecutive 

points would be retained 

minrate 4.5 This value is slightly larger than recorded 

average swimming speeds (Lutz and Musick 

1997), which we expect could be attained 

between two consecutive location records if the 

turtle was aided by favorable tides or currents. 

Reasonable rate of movement (km/hr) that 

animal may sustain over a period of hours 

or days 

ratecoef 25 Kept default for mammals and reptiles. Coefficient to evaluate angle between three 

consecutive points 

gmtoffst 0 Kept default to remain in GMT. Deviation (hrs) from GMT 

latmin 0 Represents the broad north Atlantic. Geocoordinate restraint 

latmax 60 Represents the broad north Atlantic. Geocoordinate restraint 

lonmin -110 Represents the broad north Atlantic. Geocoordinate restraint 

lonmax 30 Represents the broad north Atlantic. Geocoordinate restraint 

r_only 0 Kept the default of using rate and angle. 

r_or_a 1 Kept the default of using rate and angle. 

keep_lc 1 Kept all LC3 (best), LC2, and LC1, therefore 

location error of up to approximately 1km. 

Minimum Argos location code that never 

would be filtered out 

keeplast 0 Because we usually do not have any more 

confidence in the last location than we have for 

prior locations, we did not keep last location 

unless it passed the filter. 

Last record is filtered out if it exceeds 

MAXREDUN from the previous location 

pickday 1 We are not using any of the output files related 

to pickday, so this parameter is essentially 

irrelevant for our purposes. A value needs to 

be chosen for the program to run. We chose 1 

because we will be using data with various 

duty-cycles and we are ultimately interested in 

one location per day for the hex-bin composites 

Best Argos location is selected on 24 hr 

period, not transmitter duty-cycle 

skiploc 0 “B” should be considered in next triplet, even if 

“B” is filtered (removed). We chose this so 

that removing “B” would not increase the 

likelihood of removing surrounding points. 

A previously filtered point is considered in 

the next evaluation of three consecutive 

points 

xmigrate 1 We set this to 1 so that all DAR points that 

passed the MRD filter would pass this test for a 

migration event and be further evaluated for 

inclusion in the hybrid filter. 

A coefficient of MAXREDUN used to 

evaluate distance during a “migration 

event” 

xoverrun 3.0 We chose this value based on calculations from 

sample datasets plus evaluation of MRD, DAR, 

and best hybrid output run under a variety of 

xoverrun values. We increased this value from 

A coefficient of MAXREDUN used to 

evaluate DAR vector during a “migration 

event” 
30 

the default so that many of the DAR points that 

passed the MRD filter would pass this test for a 

migration event and be further evaluated for 

inclusion in the hybrid filter. 

xdirect 70 This value was based on the expected 

asymptote, given that some reasonable 

distances in a sample dataset were > 100 km. 

Used to evaluate azimuth in a direction test 

of the combined MRD and DAR filter 

xangle 45 We decreased this angle from the default value 

based on calculations from sample datasets plus 

evaluation of MRD, DAR, and best hybrid 

output run under a variety of xangle values. 

Used to evaluate angle between 3 

consecutive points in an angle test of the 

combined MRD and DAR filter 

xpercent 50 We increased this value from the default based 

on calculations from sample datasets plus 

evaluation of MRD, DAR, and best hybrid 

output run under a variety of xpercent values. 

Amount of wander allowed by an animal in 

the combined MRD and DAR filter 

testp_0a 1 For location classes “A” and “0”, a location 

only needs to pass 1 of the 3 related angle tests 

(direct, angle, percent) to pass this portion of 

the filter. We chose this option because we 

think many of the locations accepted by the 

DAR filter are accurate points, and we want 

many of the reasonable DAR locations to pass 

the hybrid filter 

The previous “testpass” variable (the 

number direct, angle, percent tests for the 

combined MRD and DAR filter that must 

be passed) has been partitioned into two 

parts: 1) cases where the location in 

question is an LC=Z or LC=B; and 2) cases 

where the location in question was an 

LC=A, LC=0, or better. 

testp_bz 2 For location classes “B” and “Z”, a location 

only needs to pass 2 of the 3 related angle tests 

(direct, angle, percent) to pass this portion of 

the filter. We chose this option because we 

want to be a little more conservative with this 

class of locations. 

See testp_0a (above). 

crossval 1 Because sea turtles are not “slow moving 

animals” we chose the previous default of 1. 

When CROSSVAL = 1, the program 

attempts to cross-validate its initial choice 

between the 2 solutions by evaluating the 

pair of locations from the subsequent 

overpass. Until program version 7.03, the 

condition was always CROSSVAL = 1 

(internal default). 

unixdata 0 We will not be using Unix-formatted SAS 

datasets, so we set to 0. 

Set to 1 if using UNIX-formatted SAS 

datasets of Argos data. 
31 

Figure 4. Movements and habitat use of all loggerhead sea turtles (n=248 animals; 

24,535 tracked days). Days tracked from release state are indicated within respective 

state borders. Florida split into east and west coast release locations. Bathymetric contour 

line=200 m. There are two hexes per degree; each hex represents approximately 2,686 

km2. The longitudes are based on 360', starting at 0 from the Prime Meridian moving 

east. 
32 

Figure 5. Movements and habitat use of all juvenile loggerhead sea turtles (n=108 

animals; 9,833 days). Days tracked from release state are indicated within respective 

state borders. Bathymetric contour line=200 m. There are two hexes per degree; each hex 

represents approximately 2,686 km2

. The longitudes are based on 360', starting at 0 from 

the Prime Meridian moving east. 
33 

Figures 6A-D. Seasonal movements and coastal habitat use of all juvenile 

loggerhead sea turtles (n=108 animals; 9,833 days). (A) Winter, January through 

March (n=61 animals; 2,291 days). (B) Spring, April through June (n=71 animals; 2,325 

days). (C) Summer, July through September (n=64 animals; 1,610 days). (D) Fall, 

October through December (n=87 animals; 3,607 days). Bathymetric contour line=200 m. 

There are four hexes per degree; each hex represents approximately 669 km2

. The 

longitudes are based on 360', starting at 0 from the Prime Meridian moving east. 
34 

Figure 7. Movements and habitat use of all male loggerhead sea turtles (n=36 

animals; 2,612 days). Days tracked from release state are indicated within respective 

state borders. Florida split into east and west coast release locations. Bathymetric contour 

line=200 m. There are two hexes per degree; each hex represents approximately 2,686 

km2

. The longitudes are based on 360', starting at 0 from the Prime Meridian moving 

east. 
35 

Figures 8A-D. Seasonal movements and coastal habitat use of all male loggerhead 

sea turtles (n=36 animals; 2,612 days). Maps are zoomed to coastal region. (A) Winter, 

January through March (n=7 animals; 189 days). (B) Spring, April through June (n=36 

animals; 1,448 days). (C) Summer, July through September (n=24 animals; 702 days). 

(D) Fall, October through December (n=9 animals; 273 days). Bathymetric contour 

line=200 m. There are four hexes per degree; each hex represents approximately 669 

km2

. The longitudes are based on 360', starting at 0 from the Prime Meridian moving 

east. 
36 

Figure 9. Movements and habitat use of all adult female loggerhead sea turtles 

(n=99 animals; 11,863 days). Days tracked from release state are indicated within 

respective state borders. Florida is split into east and west coast release locations. 

Bathymetric contour line=200 m. Note that 38 nesting Florida females not included in 

these analyses are represented in Figure 12. There are two hexes per degree; each hex 

represents approximately 2,686 km2

. The longitudes are based on 360', starting at 0 from 

the Prime Meridian moving east. 
37 

Figures 10A-D. Seasonal movements and coastal habitat use of all adult female 

loggerhead sea turtles (n=99 animals; 11,863 days). (A) Winter, January through 

March (n=54 animals; 1,895 days). (B) Spring, April through June (n=74 animals; 2,456 

days). (C) Summer, July through September (n=99 animals; 3,279 days). (D) Fall, 

October through December (n=74 animals; 4,233 days). Bathymetric contour line=200 m. 

Note that 38 nesting Florida females not included in these analyses are represented in 

Figure 12. There are four hexes per degree; each hex represents approximately 669 km2

. 

The longitudes are based on 360', starting at 0 from the Prime Meridian moving east. 
38 

Figures 11A-C. Seasonal movements and habitat use of all nesting female 

loggerhead sea turtles by subpopulation (n=99 animals; 11,863 days). Maps are 

zoomed to coastal region. (A) Northern U.S. Subpopulation (n=67 animals; 9,425 days). 

(B) Peninsular Florida Subpopulation (n=29 animals; 1,938 days). (C) Northern Gulf of 

Mexico Subpopulation (n=3 animals; 500 days). Bathymetric contour line=200 m. Note 

that 38 nesting Florida females not included in these analyses are represented in Figure 

12. There are four hexes per degree; each hex represents approximately 669 km2

. The 

longitudes are based on 360', starting at 0 from the Prime Meridian moving east. 
39 

Figure 12. Post-nesting migrations of loggerhead turtles from three Florida nesting 

beaches: green = Archie Carr NWR; blue = Manasota Key; red = Cape San Blas. 

Arrowheads represent the termination of post-nesting migrations and the location of 

resident areas. Only one turtle was still apparently migrating when transmissions ceased 

(line ending in a blue circle off the northwest coast of Cuba) Thicker lines represent two 

or more turtles following similar migratory pathways (from Foley et al. 2008). 

Aerial Survey and Shipboard Surveys

Aerial and shipboard surveys are another method to assess the in-water distribution of sea 

turtles within a defined study range. To identify loggerhead sea turtle distributions along 

the east coast of the United States and Gulf of Mexico, we used aerial and shipboard 

survey data that were incorporated into NOAA Fisheries Atlantic and Gulf Strategy GIS 

(U.S. Dept. Commerce 2001). These data originated from a variety of survey sources 

spanning from the late 1970s to 2002 including: 

 * Department of Navy, Continental Shelf Associates 

 * Minerals Management Service, Southeast Fisheries Science Center 

 * North Atlantic Right Whale Consortium, which includes the following: 

 - Associated Scientists at Woods Hole 

 - Center for Coastal Studies 

 - Cetacean and Turtle Assessment Program 

 - Continental Shelf Associates 

 - East Coast Ecosystems 

 - Florida Marine Research Institute 

 - Georgia Dept. of Natural Resources 
40 

 - International Fund for Animal Welfare 

 - New England Aquarium 

 - National Marine Fisheries Service 

 - University of North Carolina at Wilmington 

 - University of Rhode Island 

 - Wildlife Trust 

 * Northeast Fisheries Science Center 

 * Southeast Fisheries Science Center 

In general, the survey effort for these combined datasets spanned from the eastern 

continental shelf of North America, from Nova Scotia south to Mexico and into the 

Caribbean, mainly in the vicinity of Puerto Rico and the U.S. Virgin Islands. Most of the 

effort was concentrated along the U.S. Atlantic coastline, however, some effort and 

sightings did occur beyond the U.S. Exclusive Economic Zone (Figures 13-16). 

The majority of these data were derived from aerial surveys, with nearly 100,000 records 

included in this analysis. Transect lines and loggerhead sightings data were binned by 

season and plotted. Winter was defined as January through March; Spring as April 

through June; Summer as July through September; and Fall as October through 

December. In addition to loggerhead sightings, we included sightings of unidentified sea 

turtles because it is likely many were loggerhead turtles. 

Results 

The majority of sightings occurred along the continental shelf approximately out to the 

200 m bathymetric contour line (Figures 13B-16B). Seasonal composites (Figures 13B16B) indicate few to no turtles occurring coastally north of 36° N, or just north of Cape 

Hatteras, N.C. during Winter (Figure 16B). By the Spring and Summer, turtles were 

found to occur in nearshore coastal waters north of Cape Hatteras, N.C., with sightings 

occurring frequently as far north as Cape Cod during Summer (Figures 14B, 15B). There 

were few turtles north of Cape Cod; some turtles were observed beyond the continental 

shelf, ranging as far east as approximately 60 ̊ W and between 30 ̊ N to 45 ̊ N (Figure 

15B). Generally, loggerhead turtles were sighted in the northeast region south of Cape 

Cod during the Summer wherever there was effort, but had more restricted northern 

distributions during the other seasons. 

Nearshore coastal surveys were infrequently conducted throughout the Gulf of Mexico; 

most surveys were farther offshore. When surveys did cover the nearshore areas, 

sightings usually were reported. This was especially true during Fall surveys off the west 

coast of Florida (Figure 16A), indicating a high density of loggerheads sighted during 

those surveys (Figure 16B). 
41 

The primary concerns associated with existing aerial survey datasets are: (1) survey 

consistency over time and space; (2) lack of standardization among surveys (e.g., altitude, 

speed, methods); and (3) sea turtle detectability biases associated with seasonal diving 

behavior (particularly within the more temperate regions – see Nelson 1996 and 

Mansfield 2006). Similar issues apply to shipboard surveys where the area searched is 

relatively small and sea turtles are not often sighted due to their size and their 

detectability. 

Despite these concerns, the survey data provide very broad-scale information related to 

sea turtle distributions along the U.S. coastline. Observed seasonal sightings are very 

similar to the distributions of sea turtles tracked using satellite telemetry. Although the 

conclusions of the aerial survey and shipboard surveys could be biased, overall these data 

show a similar shelf-constrained distribution (see Satellite Telemetry section, satellite 

Figure 13) as well as similar seasonal distributions, particularly during the winter months 

in the northeast (see Satellite Telemetry section, Figures 6A and 10A). 

Seasonal differences in surfacing behavior may heavily bias aerial observations. 

Surfacing behavior may be influenced by an animal’s behavior (migrating vs. foraging) 

or by environmental conditions (e.g. water temperature, particularly the vertical 

distribution of temperatures within the water column) (Mansfield 2006). Table 10 

summarizes existing evidence obtained along the east coast of the U.S. and the Gulf of 

Mexico supporting this potential detectability bias. 
42 

Table 10. Summary of loggerhead surfacing behavior derived from radio tracking data and other sources

Nelson (1996). 

Location Months Water T N % t near surface % t mid-depths % t Bottom Canaveral, Fl. Sept not reported 6 3.78 (~1-2 m) KeCanaveral, Fl. Mar-Apr 16.5 to 23.6 8 12.7 (<5 m) 22.7 64.7 StaCanaveral, Fl. July-Aug 19.1 to 30.7 23 26.0 (<5 m) 33.7 40.2 

Sta8am sub

Canaveral, Fl. Sept 25.9 to 28.2 12 4.3 (<3 m) 12.5 83.2 NeSavannah, Ga. April-May 12.5 to 18.2 2 48.6 (<3 m) 36.9 14.6 KeSavannah, Ga. Oct-Nov 15.6 to 23.4 9 14.9 (<3 m) 36.9 48.2 KeSt. Marys, Ga. April-May 18.0 to 22.3 4 38.6 (<3 m) 17.8 43.7 NeSt. Marys, Ga. July-Aug 27.4 to 28.3 9 24.1 (<3 m) 13.7 62.3 NeSt. Marys, Ga. Oct-Nov 18.6 to 23.7 6 9.6 (<3 m) 21.1 68.9 NeCharleston, S.C. May-June 19 to 25 4 8.5 (<3 m) 39.3 52.3 KeCharleston, S.C. Sept-Oct 22.1 to 27.8 5 6.7 (<3 m) 18.7 74.5 KeChesapeake Bay Mouth May-mid-July 18.0 to 25.0 4 9.9 (<2 m) 91.1 

Mabel

Chesapeake Bay Mouth June-July 9.0 to 26.0 2 25.0 (<2 m) 75 

Mabel

Chesapeake Bay Mouth July 19.0 to 26.0 1 12.3 (<2 m) 83.7 

Mabel

Western Chesapeake Bay June-Oct Warm/well mixed 14 5.3% (<2 m) 94.7 

By2 m 

Other: Region Season Activity % t at surface % t submerged Gulf of Mexico Winter < summer ReGulf of Mexico Summer > winter ReMid-Atlantic Fall Migration 6% to 20% Ke
43 

Figure 13A-B. Winter (January-March) loggerhead sea turtle sightings from aerial and 

shipboard surveys. (A) transect lines flown are depicted in blue; (B) observed loggerhead 

sightings (purple) and unidentified sea turtles (green). Bathymetric contour line = 200 m. 
44 

Figure 14A-B. Spring (April-June) loggerhead sea turtle sightings from aerial and 

shipboard surveys. (A) transect lines flown are depicted in blue; (B) observed loggerhead 

sightings (purple) and unidentified sea turtles (green). Bathymetric contour line = 200 m. 
45 

Figure 15A-B. Summer (July-September) loggerhead sea turtle sightings from aerial and 

shipboard surveys. (A) transect lines flown are depicted in blue; (B) observed loggerhead 

sightings (purple) and unidentified sea turtles (green). Bathymetric contour line = 200 m. 
46 

Figure 16A-B. Fall (October-December) loggerhead sea turtle sightings from aerial and 

shipboard surveys. (A) transect lines flown are depicted in blue; (B) observed loggerhead 

sightings (purple) and unidentified sea turtles (green). Bathymetric contour line = 200 m. 
47 

Overall conclusions 

Despite the drawbacks associated with the different types of datasets (conventional tagging, 

satellite telemetry, and aerial/ship surveys), there is substantial agreement in the patterns borne 

out of each dataset. For instance, turtles captured and tagged within the Gulf of Mexico region 

likely remain within the Gulf of Mexico or more southern geographic regions (Mexico, the 

Caribbean) and appear less likely to range into the more northern regions along the east coast of 

the U.S. Seasonal residents found in waters north of Cape Hatteras, North Carolina will migrate 

either south of Virginia or offshore in the fall to escape the colder, winter temperatures 

(Lutcavage and Musick 1985; Bellmund et al. 1987; Keinath et al. 1987; Byles 1988; Keinath 

1993; Morreale and Standora 1998; Mansfield 2006; see Figure 8). The analyses presented in 

this report support these prior studies and observations. Juveniles found within the northern 

region genetically represent several stocks (Rankin-Baransky et al. 2001; Bass et al. 2004; 

Bowen et al. 2005; Norrgard 1996). 

The mid-Atlantic Bight, particularly the coastal waters off of North Carolina north to New Jersey 

provide important seasonal habitat to juvenile loggerheads and adult females from the Northern 

U.S. Subpopulation (Lutcavage and Musick 1985; Byles 1988; Keinath 1993; Mansfield 2006; 

Hawkes et al. 2007; McClellan and Read 2007). The shelf waters along the eastern U.S. provide 

important migratory habitat, particularly within the more northern temperate waters north and 

south of Cape Hatteras, N.C. (Shoop and Kenney 1992; Keinath 1993; Plotkin and Spotila 2002; 

Morreale and Standora 1998; Mansfield 2006; McClellan and Read 2007). The shelf off 

southwestern Florida provides important habitat for females from both the Peninsular Florida and 

the Northern Gulf of Mexico subpopulations. 
48 

PART II. SUBPOPULATION NESTING TRENDS 

Loggerheads in the Western North Atlantic originate from many different, often widely 

separated, nesting beaches (Bowen et al. 2004). The reproductive output of all of these 

subpopulations influences the numbers of loggerheads found in this part of the world. An overall 

assessment of the status of loggerheads in the Western North Atlantic must consider trends in the 

annual numbers of nests of each of the contributing subpopulations (Table 11). 

There are five loggerhead nesting subpopulations in the Atlantic and two in the Mediterranean 

that are known to produce more than 1,000 nests per season (Ehrhart et al. 2007a; Margaritoulis 

et al. 2003; Canbolat 2004). Two of these are found on beaches in the U.S. (Peninsular Florida 

and Northern U.S.), and one each is found in the Eastern Atlantic (primarily Cape Verde), Brazil, 

the greater Caribbean (primarily Mexico), Greece, and Turkey. Two smaller (< 1000 nests per 

year) loggerhead nesting subpopulations that have been identified in the U.S. are found in the 

Northern Gulf of Mexico (primarily in northwest Florida, otherwise known as the Florida 

Panhandle; Encalada et al. 1998) and in the Dry Tortugas (Florida) and Cay Sal Bank (Bahamas) 

(Francisco Pearce 2001; Bolten and Bjorndal unpubl. data). All of these nesting aggregations 

contribute to a greater (in the case of nesting subpopulations in the U.S., Caribbean, and possibly 

Cape Verde) or lesser (in the case of the subpopulations in the Mediterranean and Brazil) extent 

to loggerhead foraging areas of the Western North Atlantic (Bowen et al. 2004). 

Western North Atlantic –Melissa Snover, Allen Foley, and Mark Dodd 

For subpopulations in the Western North Atlantic, we used both simple linear regression and 

Bayesian state-space modeling approaches to estimate population trends based on nest census 

data. For each subpopulation included in these analyses, the data were from a subset of all the 

surveyed beaches and included only those beaches that were most consistently surveyed. Often 

(but not always), these beaches represented a majority of all nesting activity for each 

subpopulation. A description of these surveys and their percent representation of the whole 

subpopulation are given in the following subsections. 

In the first (frequentist) approach, nest count data from these beaches were log-transformed and 

plotted against time. The estimated slope of the regression, β, through these data represented the 

natural log of the geometric growth rate of the population. We set up the null hypothesis, H0: β ≥

0, and the alternative hypothesis, H0: β < 0, to test if the populations declines were statistically 

significant. 95% confidence intervals around the estimate for population growth rates were 

computed using the Student’s t distribution with T-2 degrees of freedom, where T is the length of 

the time series (yr). Due to the high level of interannual variability in nest census data, it can be 

difficult to detect statistically significant trends using this approach to trend analysis; the 95% 

confidence intervals for population trends based on nest census data often span from decreasing 

to increasing, making it difficult to state with any kind of certainty whether the trend of a given 

population is increasing, decreasing or stable. 

To better address the uncertainties caused by interannual variability, we also estimated the 

annual population growth rates and the probability that nesting aggregations were declining 

using a Bayesian state-space modeling approach (TEWG 2007). With Bayesian methods, 
49 

uncertainty is measured in probabilities, making statements regarding uncertainty much more 

transparent than is possible with frequentist approaches. We followed the approach used in 

TEWG (2007) where the results were stated in terms of actual probability, such as ‘the average 

annual population growth is less than one (declining) with probability y.’ The interpretation of 

these results is then subjective: is a 50% probability that a population is declining cause for 

concern? Obviously the higher the probability, the greater is the cause for concern. In spite of 

the inherent subjectivity, it is often more useful to be able to report this probability than to report 

a trend that is not statistically different from stable. 

Both approaches were applied to nest census data from the Peninsular Florida, Northern U.S., 

Northern Gulf of Mexico, Dry Tortugas/Cay Sal Bank, and Greater Caribbean Subpopulations. 

The mathematical details and assumptions for the Bayesain state-space model can be found on 

pages 47-48 and Appendices 1 and 2 in TEWG (2007). Matlab and winBUGs code for the model 

were provided by Tomo Eguchi (NMFS, Southwest Fisheries Science Center). Convergence of 

Markov chains for each dataset was confirmed using the convergence statistics of Gelman et al. 

(2004), using S-plus code from Smith (2005). 

Peninsular Florida Subpopulation 

Peninsular Florida hosts the largest loggerhead nesting aggregation in the Atlantic (Table 11) and 

one of the two largest in the world (Ehrhart et al. 2007a). Originally, loggerheads nesting in 

northeast Florida (north of 29° latitude) were included as a part of the subpopulation that also 

nests from Georgia through North Carolina (Northern Subpopulation; TEWG 1998). However, 

the most recent recovery plan (National Marine Fisheries Service and U.S. Fish and Wildlife 

Service 2008) delineates the Peninsular Florida Subpopulation as using beaches from the 

Florida/Georgia border to the central west coast of Florida. 

A coordinated network of sea turtle nesting beach surveys in Florida began in 1979. By the mid1990’s, these surveys included almost all of the sea turtle nesting beaches in Florida. This 

Statewide Nesting Beach Survey program (SNBS) provides the best data for determining the 

overall extent of loggerhead nesting, the beginning and ending of the nesting season, the 

distribution of nesting effort, and the overall number of nests. However, because of variations in 

survey areas and survey times, the SNBS methodology is not well suited for determining trends 

in the annual number of nests. 

A nesting beach survey program in Florida that was intended to provide nest trend data by 

standardizing nesting beach survey effort began in 1989. This program, the Index Nesting 

Beach Survey Program (INBS), involves standardized surveys on a subset of Florida’s nesting 

beaches each day from May 15 through August 31. Twenty-eight nesting beach survey areas 

have been consistently surveyed as a part of this program since 1989. The exact methodology 

used by this program including efforts to assure high quality data are described in Witherington 

et al. (2009). 

Although the beaches surveyed for the INBS program constitute only about 25% of the area 

where loggerheads nest in Florida, they represent an average of almost 70% of the total number 

of loggerhead nests in Florida each year. The number of loggerhead nests documented on these 
50 

INBS beaches each year from 1989 through 2007 is given in Figure 17. Loggerhead nesting 

documented annually by this program was found to have decreased from 28-31% between 1989 

and 2007 and to have declined from 43-44% between 1998 and 2007 (Witherington et al. 

2009).In 2008, there were 38,064 nests in 2008 on those index nesting beaches (FFWCC). 

There is no indication from the SNBS data that the decrease in the annual numbers of loggerhead 

nests on the INBS beaches has been due to a shift of loggerhead nesting from the INBS beaches 

to other beaches in Florida or due to an increasing amount of loggerhead nesting before or after 

the INBS survey period (Witherington et al. 2009). Furthermore, the same INBS surveys in 

Florida that have documented declines in the annual numbers of loggerhead nests have 

documented substantial increases in the annual numbers of green turtle and leatherback nests 

over the same period of time (Witherington et al. 2009). 

Results from both of our trend analyses on the INBS data also present strong evidence that this 

aggregation is declining in terms of the number of nests per year. In the trend analyses, we used 

the time series from 1989–2007 and 1998–2007 to estimate population growth rates (Table 12). 

The entire 19-year dataset for this subpopulation indicated an overall decline at a rate of 1.4 to 

2.6 % per year. If only the last 10 years of data are considered, the data suggest a more rapid 

decline (6.4 to 9.1 % per year with a probability of 0.88). 

Northern U.S. Subpopulation 

 The Northern U.S. Subpopulation nests on beaches from Georgia through North Carolina and 

represents the third largest loggerhead nesting aggregation in the Atlantic and the second largest 

in the Western North Atlantic (Table 11). Some of the nesting beach surveys in this area began 

in the 1960’s but much of the survey effort here has been variable and cannot be used to assess 

trends in the annual numbers of loggerhead nests. However, a subset of eleven nesting beaches 

within this region has been surveyed more consistently since 1983. The number of loggerhead 

nests on these beaches each year during 1983-2006 is given in Figure 18. The nest total from 

these 11 beaches represented approximately 30% of the total loggerhead nesting for the 

subpopulation in 2005. A log-linear regression with an autoregressive error correction to 

account for temporal correlation in annual nest totals shows a significant (P < 0.05) declining 

trend of 1.6 % annually in loggerhead nesting on these beaches (GDNR unpubl. data). There 

were 1,159 nests in 2007 and 1,854 nests in 2008 for the Northern U.S. subpopulation which 

makes 2008 one of the highest counts on record. 

In our analyses of the data from the 11 most consistently surveyed beaches during 1983-2005, 

the simple log-transformed regression and the Bayesian state-space model resulted in similar 

estimates for mean and median population growth rates suggesting a decline of 1.4 to 1.7% per 

year (Table 12). While the simple log-transformed regression was not quite significant 

(P=0.062), results of the Bayesian state-space model suggest that the decline was likely with a 

probability of 0.92 (Table 12). 
51 

Northern Gulf of Mexico Subpopulation 

The loggerhead nesting aggregation in the Northern Gulf of Mexico is one of the smallest in the 

Atlantic and the second smallest in the Western North Atlantic (Table 11). Nesting in this area is 

concentrated in the Florida Panhandle (1995-2005 mean of 955 nests/year) with a consistent but 

small amount of nesting (< 50 nests) in other Gulf States, mostly Alabama. As in the rest of 

Florida, some nesting surveys began in the Florida Panhandle as early as 1979 and by the mid1990’s included almost all of the nesting beaches. There are three INBS beaches in the Florida 

Panhandle and these have been consistently surveyed since 1997. 

 

The number of loggerhead nests documented on the three INBS beaches in the Florida Panhandle 

each year during 1997-2007 is shown in Figure 19. Both of the trend analyses presented here 

indicated a very likely decline in numbers of nests per year for these three beaches (Table 12). 

However, the three INBS beaches in the Florida Panhandle represented a relatively small fraction 

(about 17%) of the overall loggerhead nesting in this area and may not be a true indicator of the 

overall trend. Nevertheless, the annual numbers of loggerhead nests determined by the SNBS for 

the entire Florida Panhandle during the period of 1997 through 2006 indicated a similar decline 

(from a high of 1,212 nests in 1999 to a low of 587 nests in 2006) (FFWCC unpubl. data). 

 

Dry Tortugas/Cay Sal Bank Subpopulation 

The loggerhead subpopulation that nests in the Dry Tortugas and Cay Sal Bank is the smallest 

recognized here (Table 11). A survey of sea turtle nesting was conducted in the Dry Tortugas 

each year from 1995 to 2004, excluding 2002 (Van Houton and Pimm 2006; FFWCC unpubl. 

data). The range of loggerhead nests counted was 134 to 242. The annual numbers of 

loggerhead nests documented in the Dry Tortugas each year during this time period are given in 

Figure 20. Both of the trend analyses we conducted indicated a high likelihood of a declining 

annual number of nests in the Dry Tortugas (Table 12). Nesting on Cay Sal Bank was estimated 

to be between 500 and 600 nests each year as extrapolated from partial surveys conducted during 

1995 and 1996 (Addison 1996; Addison and Morford 1997). No data to discern trends in annual 

numbers of loggerhead nests were available for Cay Sal Bank. 

Greater Caribbean Subpopulation 

The majority of the loggerhead nesting in the Greater Caribbean occurs in Quintana Roo, Mexico 

(Ehrhart et al. 2003). The loggerhead nesting aggregation in Quintana Roo is the third largest in 

the Western North Atlantic (Table 11). Sea turtle nesting beach surveys began here in 1984. By 

the early 1990’s, almost all beaches in Quintana Roo where loggerhead nesting occurred were 

being surveyed. Eighty-five percent of loggerhead nesting is along the central coast from Punta 

Venado (just south of Playa Del Carmen) south to Punta Allen. There are eight nesting beach 

survey areas along this coast that have been consistently surveyed since 1989. These nesting 

beach surveys were conducted daily and encompassed the entire loggerhead nesting season, 

beginning on May 1 and ending on October 31. These eight beaches included only about 10% of 

the overall area where loggerheads nest in Quintana Roo but contained an average of almost 65% 

of all the loggerhead nests documented in Quintana Roo. 
52 

The total number of loggerhead nests on these beaches each year from 1989 to 2006 is shown in 

Figure 21. In our trend analyses of nesting numbers on the eight most consistently surveyed 

beaches, the log-transform regression for the entire time series indicated no trend. However, 

over the same time period, the Bayesian state-space model indicated that the population was 

declining at a rate of ~3.8% per year with a probability of 0.9589 (Table 12). For the time period 

from 1995-2006, both of the trend analyses indicated a steep decline of >5% per year. For the 

log-transform regression this was significant and the Bayesian state-space model indicated a 

99.1% probability that the population was declining (Table 12). 

As in the Peninsular Florida Subpopulation, there was no indication that loggerhead nesting 

shifted from the eleven beaches used to indicate annual trends in the numbers of nests to other 

beaches. The total number of loggerhead nests documented each year in Quintana Roo showed a 

similar type of trend as that of the eight most consistently surveyed beaches during the period of 

1989-2006. The annual numbers of nests on all of the beaches increased from an average of 

1,407 during 1989 through 1993 to an average of 2,121 during 1995 through 1999, and then 

decreased to an average of 1,404 during 2002 through 2006. In 2007 there were 1,535 and in 

2008 there were 2,137 nests. Also, as in Peninsular Florida, the same beaches that have 

documented a recent decline in the annual numbers of loggerhead nests have also documented an 

increase in the annual numbers of green turtle nests (J. Zurita unpubl. data). 

Other Atlantic and Mediterranean Subpopulations –Allen Foley 

Eastern North Atlantic 

Loggerhead nesting in the Eastern North Atlantic is concentrated in the Cape Verde Archipelago 

(López-Jurado et al. 2000; Cruz et al. 2007; Loureiro, 2008). On mainland Africa, there is minor 

nesting on the coast from Mauritania and Senegal (Brongersma 1982; Arvy et al. 2000). Earlier 

reports of loggerhead nesting in Morocco and Western Sahara (Marquez M. 1990) have not been 

confirmed in recent years (Tiwari et al. 2001). Nesting has not been reported from Macaronesia 

(Azores, Madiera Archipelago, The Selvagens Islands, and the Canary Islands), other than in the 

Cape Verde Archipelago (Brongersma 1982). 

Cape Verde Subpopulation 

The Republic of Cape Verde is an archipelago of ten main islands and several islets situated 

about 500 km off the coast of Senegal. Loggerhead nesting occurs primarily on the easternmost 

islands of Boa Vista, Sal, and Maio with some nesting also known from Santa Luzia, São 

Vicente, and Santiago (López-Jurado et al. 2000; Cruz et al. 2007, Loureiro 2008, N. Varo-Cruz 

pers. comm.). Regular nesting surveys have only been conducted on Boa Vista. These surveys 

have been conducted since 2001 on only 3.1 km of the approximately 55 km of suitable nesting 

beach on that island (Cruz et al. 2007, N. Varo-Cruz pers. comm.). During the period of 2001-

2004, an annual average of 1,771 loggerhead nests was documented on this stretch of beach. 

The highest annual total was 2,728 loggerhead nests during 2004 (N. Varo-Cruz pers. comm.). 

Intermittent surveys conducted recently on other beaches in Cape Verde indicate that the total 

number of loggerhead nests each year on all the beaches of Boa Vista could be as high as 10,000 
53 

and that the number of loggerhead nests on the other islands each year could be as high as 5,000 

(N. Varo-Cruz pers. comm.). Based on these observations, we more conservatively estimate that 

the number of loggerhead nests each year in the Republic of Cape Verde during 2001 through 

2004 was about 10,000. If more consistent and comprehensive future nesting beach surveys 

validate this estimate (or show it to be a likely underestimate), the Republic of Cape Verde will 

be recognized as hosting the second largest loggerhead nesting aggregation in the Atlantic (Table 

11). No data were available to discern trends in the annual numbers of loggerhead nests in Cape 

Verde. 

Western South Atlantic 

Nesting in the Western South Atlantic occurs primarily along the mainland coast of Brazil from 

Sergipe south to Rio de Janeiro, with peak concentrations in northern Bahia, Espírito Santo and 

northern Rio de Janeiro (Marcovaldi and Chaloupka 2007). In the Eastern South Atlantic diffuse 

nesting may occur along the mainland coast of Africa (Fretey 2001), with >200 loggerhead nests 

reported for Rio Longa beach in central Angola in 2005 (Brian 2007). However, other 

researchers have been unable to confirm nesting by loggerheads in the last decade anywhere 

along the South Atlantic coast of Africa, including Angola (Fretey 2001; Weir et al. 2007). There 

is the possibility that reports of nesting by loggerheads from Angola and Namibia (Márquez M. 

1990; Brian 2007) may have been misidentified nesting by olive ridley turtles (Brongersma 

1982; Fretey 2001). At the current time, it is not possible to confirm that regular nesting of 

loggerheads occurs along the Atlantic coast of Africa south of the equator. 

Brazil Subpopulation 

 

The loggerhead nesting subpopulation in Brazil is relatively large (Table 11) but probably 

contributes only a few individuals to the Western North Atlantic foraging grounds (Bowen et al. 

2004). Nesting beach surveys in Brazil began on the major loggerhead nesting beach at Praia do 

Forte in the state of Bahia in 1982, but comprehensive nesting surveys along the entire coast of 

Brazil did not begin until the 2002/2003 nesting season. Since 1988, there have been consistent 

nesting beach surveys on 22 beaches in the states of Bahia and Espírito Santo (Marcovaldi and 

Chaloupka 2007). These beaches cover only about 23% of the available loggerhead nesting 

beaches in Brazil but contain more than 75% of the loggerhead nesting there. The numbers of 

loggerhead nests made each year on the consistently surveyed nesting beaches in Bahia and 

Espirito Santo have increased during the period of 1988-2004, with >4,800 nests total laid per 

year (Marcovaldi and Chaloupka 2007). 

Mediterranean Sea 

Nesting occurs throughout the central and eastern Mediterranean, on the shores of Italy, Greece, 

Cyprus, Turkey, Syria, Lebanon, Israel, the Sinai, Egypt, Libya, and Tunisia (Sternberg 1981; 

Margaritoulis et al. 2003; SWOT 2007). Sporadic nesting also has been reported in the Western 

Mediterranean, on Corsica (Delaugerre and Cesarini 2004), southwestern Italy (Bentivegna et al. 

2005) and on the Spanish Mediterranean coast (Tomás et al. 2003). Most (>80%) of the 

loggerhead nesting in the Mediterranean occurs in Greece and Turkey (Margaritoulis et al. 

2003). 
54 

Greece Subpopulation 

In Greece, about 60-65% of the loggerhead nesting occurs on beaches in Laganas Bay (annual 

mean of 1,294 nests) or Kyparissia Bay (annual mean of 580 nests) (Margaritoulis and Rees 

2001; Margaritoulis et al. 2003; Margaritoulis 2005). Consistent nesting beach surveys have been 

conducted at both sites since 1984. No overall increase or decrease in the annual numbers of 

loggerhead nests have been detected in either area (Margaritoulis and Rees 2001; Margaritoulis 

2005). In contrast, the annual number of loggerhead nests laid at Rethymno Beach on the Island 

of Crete is 387 (accounting for about 10% of loggerhead nesting in Greece), and recently is 

reported to be declining (Margaritoulis et al. 2009). 

Turkey Subpopulation 

Loggerhead nesting in Turkey is somewhat evenly spread across 14 known nesting areas, with an 

annual average of 1,366 nests (Margaritoulis et al. 2003). Intermittent nesting surveys have been 

conducted in Turkey since the 1970’s but more consistent surveys on some of the beaches have 

only been conducted since the 1990’s (Margaritoulis et al. 2003). At Fethiye, the annual number 

of loggerhead nests has declined over the 12-year period from 1993 through 2004 (Ilgaz et al. 

2007). Loggerhead nesting at Fethiye represents about 10% of the overall nesting in Turkey 

(Margaritoulis et al. 2003). 

Summary

The three largest nesting subpopulations responsible for most of the production in the Western 

North Atlantic - Peninsular Florida, Northern U.S. and Mexico (Quintana Roo) - are all known to 

be decreasing since the late 1990’s or longer (Table 11 and 12). The relationship between the 

trends on these beaches is striking (Table 13). The strong correlation between these beaches 

suggests that a similar mechanism is driving the trends on these beaches. The other smaller 

nesting subpopulations in the Western North Atlantic are also decreasing but the time series are 

shorter so it is difficult to discern a meaningful trend. Cape Verde may in fact be a large nesting 

subpopulation, but lack of consistent monitoring leaves many unknowns and does not allow us to 

perform any trend analyses. Brazil, in the Southern Atlantic, is the only rookery where an 

increasing trend is noted but this is based on a short time series and this rookery contributes very 

little to the Western North Atlantic. 

Based on the overall trend that is correlated among all of the beaches in the Western North 

Atlantic, the decline is likely real and should not be ignored. The only drawback to these nesting 

surveys is that none of them cover even one generation time for the loggerhead, ~50 years. 

Therefore, it is tough to make statements about the status of loggerheads in the North Atlantic by 

only examining nesting beach trends. Even with these short time series we have witnessed 

drastic declines in the number of nests and the cause of this is still unknown. Furthermore, 

because we have now experienced a period of ten years of declines in nesting we can be sure that 

we will see another cycle of decreased nesting as the hatchlings from this time period reach 

sexual maturity in roughly thirty years. 
55 

One source of supplemental information is available that could help us understand these trends 

more completely. The in-water data that is presented in the next section can provide insight into 

a greater proportion of the whole population and allow us to see cycles coming far earlier than 

we would if we just observed nesting females. By continuing nesting beach monitoring and 

combining it with all other supplementary sources of trend data for juveniles we will gain a 

better understanding of Western North Atlantic loggerhead. 

Table 11. Overall loggerhead nesting numbers and trends in the annual numbers of nests 

at each of the nine rookeries likely to contribute individuals to the Western North Atlantic. 

Data used to determine the total number of nests for a given subpopulation were from all nesting 

surveys. Data used to determine trends for each subpopulation were from a consistently 

surveyed subsample of all the nesting beach survey areas for each subpopulation. See text for 

more details. Data for Peninsular Florida, the Florida Panhandle, and the Dry Tortugas were 

from the Florida Fish and Wildlife Conservation Commission (unpubl. data). Data for the 

Northern U.S. were from the Georgia and South Carolina Departments of Natural Resources and 

the North Carolina Wildlife Resources Commission (unpubl. data). Data for Cay Sal Bank were 

from Addison and Morford (1996) and Addison (1997). Data for Mexico were from J. Zurita 

(unpubl. data). Data for Cape Verde were from López-Jurado et al. (2000) and N. Varo-Cruz 

(pers. comm.). Data for Brazil were from Marcovaldi and Chaloupka (2007). Data for Greece 

were from Margaritoulis and Rees (2001), Margaritoulis (2005), and Margaritoulis et al. (2009). 

Data for Turkey were from Ilgaz et al. (2007) and Margaritoulis et al. (2003).

Nesting 

subpopulation Total number of nests Trend in annual # of nests 

Peninsular Florida 65,460 (1989-2006 mean) Decreasing 

Northern U.S. 5,151 (1989-2005 mean) Decreasing 

Northern Gulf of 

Mexico 

1,000 (1995-2005 estimated 

mean) 

Decreasing (from data in the Florida 

Panhandle) 

Dry Tortugas/Cay Sal 

Bank 

700 (1995-2004 estimated 

mean) 

 Decreasing (from data in Dry 

Tortugas) 

Mexico (Quintana 

Roo) 1,674 (1989-2005 mean) Decreasing 

Cape Verde 10,000 (1998-2004 estimated 

mean) Unknown 

Brazil 4,535 (2003-2004 mean) Increasing 

Greece 3,000 (recently estimated 

mean) Stable or decreasing 

Turkey 2,000 (1979-2000 estimated 

mean) Decreasing 
56 

Table 12. Results of the log-transformed regression analyses and the Bayesian state-space model for estimpopulation growth rate (λ). The nest census data used in these analyses were from a consistently surveyed subnesting beach survey areas for each subpopulation. See text for more details. For the log-transformed regression

confidence intervals (C.I.) are presented along with the P value for the regression (P<0.05 indicates the reported 

rate is statistically significantly less than one). Median and 95% prediction intervals for the posterior distribution reported as well as the probability that the population is increasing, Pr (λ>1.0). All trends were based on number

Log-transformed regression Baysian sta

Subpopulation Duration of data Mean λ [95% C.I.] P 

HA=λ<1 

Median λ [9

P.I.] 

Northern U.S. (11 beaches from Georgia to North Carolina) 

1983 – 2005; 23 yr 0.983 [0.962, 1.005] 0.062 0.986 [0.968, 

Peninsular Florida (Core Index Beaches) 

1989-2007; 19 yr 0.974 [0.957, 0.991] 0.003 0.984 [0.969, 

Peninsular Florida (Core Index Beaches) 

1998-2007; 10 yr 0.913 [0.894, 0.932] < 0.001 0.938 [0.908, 

Northern Gulf of Mexico (Florida Panhandle Index Beaches) 

1997-2007; 11 yr 0.937 [0.901, 0.975] 0.002 0.899 [0.852, 0

Dry Tortugas/Cay Sal Bank (Dry Tortugas) 

1995 – 2004; 9 yr* 0.951 [0.921, 0.982] 0.003 0.929 [0.883, 

Mexico (Quintana Roo) 1989-2006; 18 yr 0.988 [0.967, 1.008] 0.114 0.961 [0.941, Mexico (Quintana Roo) 1995-2006; 12 yr 0.943 [0.917, 0.970] <0.001 0.927 [0.884, *Data missing for 2002; data point estimated as the mean of the data for 2001 and 2003 for the purpose of the tre
57 

Table 13. Pearson correlation coefficients for nesting time series from Western North Atlantic loggerhead 

nest census data used in these analyses were from a consistently surveyed subsample of all the nesting beach surv

subpopulation. See text for more details. Bold coefficients are significant at P < 0.05. Numbers in parentheses iyears for each time series for which there was overlapping data. Subpopulation 

Northern U.S. 

(11 beaches 

from GA to NC) 

Peninsular 

Florida (Core 

Index Beaches) 

N. Gulf of Mexico 

(Florida 

Panhandle Index 

Beaches) 

Dry Tortugas/Cay 

Bank 

( Dry Tortugas

Northern U.S. (11 beaches from Georgia to North Carolina) 1 (23) Peninsular Florida (Core Index Beaches) 0.531 (17) 1 (19) Northern Gulf of Mexico (Florida Panhandle Index Beaches) 0.304 (9) 0.753 (11) 1 (11) Dry Tortugas/Cay Sal Bank (Dry Tortugas) 0.397 (10) 0.741 (10) 0.892 (8) 1 (10) Mexico (Quintana Roo) 0.046 (17) 0.697 (18) 0.596 (10) 0.841 (10) 
58 

Figure 17. Number of loggerhead nests counted in the 28 Core Index Nesting Beach Survey areas of the P

Subpopulation from 1989 through 2007 (Florida Fish and Wildlife Conservation Commission unpubl. datarepresented about 70% of loggerhead nesting in the Florida. Analyses of nesting on theses beaches revealed a 281989 through 2007 and a 43-44% to decline since 1998 (Witherington et al. 2009). 

0

10000200003000040000500006000070000

1989

1990

1991

1992

1993

1994

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

2006

2007

Year

# of loggerhead nests
59 

Figure 18. The number of loggerhead nests counted each year on 11 consistently surveyed beaches of the 

Subpopulation each year during 1983 through 2006 (Georgia and South Carolina Departments of Natural North Carolina Wildlife Resources Commission unpubl. data). These beaches represented about 30% of the 

along this coast. The number of nests on these beaches has decreased by 1.6 % annually during this period (GeoNatural Resources unpubl. data). 

0

500

10001500200025003000

1983

1984

1985

1986

1987

1988

1989

1990

1991

1992

1993

1994

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

2006

Year

# of nests
60 

Figure 19. Number of loggerhead nests counted each year from 1997 through 2007 in three Florida Panha

Beach Survey (INBS) areas (where survey effort was standardized) of the Northern Gulf of Mexico Subpo

Fish and Wildlife Conservation Commission unpubl. data). Nesting in the Florida Panhandle represents abouNorthern Gulf of Mexico Subpopulation and the three INBS beaches here represented about 17% of loggerhead nPanhandle. 

0

50

100150200250300

1997

1998

1999

2000

2001

2002

2003

2004

2005

2006

2007

Year

# of nests
61 

Figure 20. Number of loggerhead nests counted in the Dry Tortugas, a part of the Dry Tortugas/Cay Sal B

during 1995 through 2004 (no survey was conducted during 2002) (Florida Fish and Wildlife Conservation unpubl. data).

0

50

100150200250300

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

Year

# of nests
62 

Figure 21. Number of loggerhead nests counted annually on eight beaches in Quintana Roo (Mexico Subp

consistently surveyed from 1989 through 2006 (J. Zurita unpubl. data). These beaches represented about 65nesting in Quintana Roo. 

0

200400600800

100012001400160018002000

1989

1991

1993

1995

1997

1999

2001

2003

2005

2007

Year

# of nests
63 

Figure 22. Annual counts of loggerhead nests in the 28 Core Index Nesting Beach survey areas of the Pen

Subpopulation compared to the annual counts of loggerhead nests on eight consistently surveyed beaches i

(Mexico Subpopulation). The Pearson correlation coefficient for these trends is 0.697 (P = 0.003). 

20000250003000035000400004500050000550006000065000

1989

1991

1993

1995

1997

1999

2001

2003

2005

2007

200400600800100120140160180200

Peninsular FloridaQuintana Roo, MX

Year

# nests, peninsular F.L.
64 

PART III. IN-WATER TRENDS Sheryan Epperly, Jason Vaughan, and Paul Richards 

We examined data from animals captured in the water as well as strandings data to look for 

patterns in capture rates that may indicate changes in population size and to determine if there 

were changes in size distributions which could indicate changes in recruitment and survival rates 

of the juvenile population as well as in recruitment to the adult population. 

From south to north the data sources are (see citations referenced below for details on sampling 

methodologies): 

St. Lucie Power Plant – Florida Power and Light (FP&L) has operated their nuclear power plant 

on Hutchinson Island, Florida since the late 1970’s. Turtles are entrained with cooling water in 

intake pipes located in the ocean and transported into an enclosed intake canal where they are 

captured with a net. Records of turtle captures have been maintained since 1976 (Bresette et al. 

2003). Flow through the intake pipes is directly related to the number of reactors operating at 

any given time, and although researchers report a decrease in turtle captures when flow is 

diminished, a cursory analysis by Ecological Associates, Inc., a contractor to FP&L, indicated 

that there was no significant relationship between flow and the number of turtles caught (M. 

Bresette pers. comm.). Morphometric data are collected and turtles are tagged before their 

release near the plant site. All of the length distribution data used in this analysis is presented as 

minimum straight carapace length (SCLmin). This measurement was not taken prior to 1980 and 

that is the reason data prior to this was not used in the length frequency analysis. The second 

unit came online in 1982, which is when we start our trend analysis. 

Indian River, Florida – Entanglement nets have been set to monitor the sea turtle population in 

the Indian River Lagoon since 1982 (Ehrhart et al. 2007b). Effort during the first year was quite 

small (15 hours over 3 days in late July). Since 1983, effort was expended during MaySeptember and, beginning in 1985, effort was expended throughout the year. A minimum of 10 

days were sampled each year. Because the most consistent sampling occurred May-September, 

it was the period we examined; we did not use the 1982 data in the analysis of CPUE trends. 

Details of the methodology are described in Ehrhart et al. (2007b). We calculated annual catch 

rates as the arithmetic mean of each of the daily CPUEs (Ehrhart et al. 2007b calculated catch 

rates similarly, except that they grouped their data into two year intervals). All of the length 

distribution data used in this analysis are presented as standard straight carapace length (SCLstd). 

Southeast Area Monitoring and Assessment Program (SEAMAP) – In 1986, the South Carolina 

Marine Resources Research Institute teamed with the National Marine Fisheries Service’s 

SEAMAP program to initiate a fishery-independent trawl survey off the southeastern U.S. 

states. In 1989, it was standardized to a stratified design, sampling from Cape Hatteras to Cape 

Canaveral (SCMRI 2000) and, since 1990, has been conducted exclusively during daylight 

hours. The region is surveyed seasonally, in spring, summer, and fall. Annual catch rates for the 

inshore strata (4-10 m), sampled continuously since 1990, were the number of loggerheads 

captured divided by the number of tows made (231-234 tows annually during 1990-2000 and 306 

annually beginning in 2001). The binomial 95% confidence intervals were estimated using the 

“Wilson” interval, which has been shown to have a reasonable coverage particularly for extreme 

probabilities (Brown et al. 2001). Morphometric data were obtained from all turtles captured and 
65 

the animals were tagged before being released; SCLstd was not recorded prior to 1996. All of the 

length distribution data used in this analysis is presented as standard straight carapace length 

(SCLstd). 

Pamlico-Albemarle Estuarine Complex, North Carolina – In the fall of the year, migrating sea 

turtles are intercepted by the flounder pound net fishery which operates behind the Outer Banks. 

Since 1995, NMFS has randomly sampled the fishers to develop an index of abundance for sea 

turtles. The methodology is described in Epperly et al. (2007). All lengths are reported as 

standard straight carapace length (SCLstd). Beginning in 2007, the State closed the fishery by 

proclamation on December 1. Hence, beginning in 2007, the index of abundance is based on 11 

weeks of sampling, not 13 weeks as described in Epperly et al. (2007). 

Chesapeake Bay – Aerial surveys were conducted in the mid-1980s (1982-1987) throughout the 

lower half of Virginia’s Chesapeake Bay, an area of approximately 1,300 km2

 (Byles 1988; 

Musick et al. 1985; Keinath 1993). Surveys were conducted in the 2000’s (2001 to 2004) in same 

region, using the same transect lines and methods (Mansfield 2006). 

Long Island Sound, New York – Sea turtles in New York waters, primarily the Peconic Bays, 

were studied in the late 1980’s and early 1990’s (Morreale and Standora 1998) and work 

resumed in 2002 (Morreale et al. 2005). The majority of the data are from pound net-captured 

animals. Recent sampling effort was much lower than in the past decade, but geographically was 

distributed in the same area. We were provided size data for the live captures during 1988-1995 

by the Riverhead Foundation for Marine Research and Preservation (R. DiGiovanni pers. 

comm.). Lengths are reported as standard straight carapace length (SCLstd). 

Sea Turtle Stranding and Salvage Network – The STSSN documents dead or injured sea turtles 

along the coasts of the eastern United States, including the Gulf of Mexico and the U.S. 

Caribbean (Schroeder 1989; Shaver and Teas 1999). Each animal was identified to species and 

standard carapace measurements were taken. We did not use the STSSN data to infer trends in 

abundance because it is not clear there is any relationship between sea turtle abundance and the 

number of animals stranding. In addition, it is unclear whether size frequency distributions 

observed in the stranding data are representative of the overall population. In the southeast U.S. 

and Gulf of Mexico, length data are confounded by changing TED regulations over the period 

examined (Epperly and Teas 2002). We only used size distribution data available from the 

STSSN for the northeast; the STSSN and the New York data are the only source of size data we 

could use for this region. We used STSSN length data from 1987-2007 because prior to that 

time survey effort was less consistent. All of the length distribution data used in this analysis is 

presented in straight carapace length standard (SCLstd). When necessary, measurements were 

converted to SCLstd (see Appendix B). 

Trends in Catches or Catch Rates 

Epperly et al. (2007) and Ehrhart et al. (2007b) recently reported their time series for catch rates 

of loggerhead turtles in North Carolina and Florida, respectively. In the Pamlico-Albermarle 

Sound Estuarine Complex, loggerhead turtle catch rates during 1995-2003 increased at a rate of 

13% per year (Epperly et al. 2007). While there was not a significant trend in the catch rate of 
66 

loggerheads in the Indian River Lagoon when the data point for 1982 was included, Ehrhart et al. 

(2007b) reported an increase in the last 4 yr of their study (catch rates in 2002 and 2005 were 

about twice those from the earlier time periods). Captures at the St. Lucie Power Plant increased 

at an average rate of 11% yr-1 from 1988 to 2005 (M. Bresette unpubl. data) and SEAMAP catch 

rates showed an overall increase from 1990 to 2006 of about 5% per year(SCDNR unpubl. data). 

Catch rates in 2007 were generally lower than earlier in the decade (Figure 23), but preliminary 

data indicate that in 2008 the St. Lucie Power Plant loggerhead captures (420) were slightly 

greater than the catch in 2006, the Indian River Lagoon CPUE (0.84) is comparable to CPUE in 

2002, the SEAMAP CPUE (0.10) is among the highest reported in this decade, and the catch of 

loggerheads in the North Carolina study is more than double the number captured in 2007 (78 in 

2006 and 177 in 2007; mean annual CPUE has not yet been calculated). 

Overall, data from three of the four in-water projects showed an increasing trend in the 

abundance of loggerhead turtles. However, this trend must be viewed with caution given the 

limited number and size of studies dedicated to assessing in-water abundance of loggerheads. 

The increase in loggerhead turtle abundance at in-water sampling sites is not consistent with 

trends observed in nest counts; however, this discrepancy may be attributed to the fact that the 

Pamlico-Albemarle Estuarine Complex and SEAMAP studies sample in areas where adult 

loggerheads are not found or are not seasonally abundant. The difference in trends between inwater abundance and nest counts may also be attributed to an increase in the number of juveniles 

that are occurring in the neritic zone. This trend can be seen in the size distribution time series 

that are presented in the following section. 

The trends in the waters of the northeast U.S. are not as easy to discern. The studies there were 

not designed to monitor abundance trends and the effort is very low, but despite these 

shortcomings we will discuss the results qualitatively. 

In Chesapeake Bay, during the aerial surveys in the 1980s, between 122 and 284 turtles were 

observed annually and mean annual turtle densities ranged between 0.18 turtles/km2

 (+/- 0.11 

turtles/km2

 SD) to 0.34 turtles/km2 (+/- 0.35 turtles/km2 SD) (Byles 1988; Mansfield 2006). 

Fewer turtles were observed during the 2001-2004 surveys. Only 36 to 63 turtles were observed 

annually and mean turtle densities ranged between 0.05 turtles/km2 (+/- 0.03 turtles/km2

 SD) and 

0.09 turtles/km2 (+/- 0.29 turtles/km2

 SD) (Mansfield 2006). Mansfield (2006) compared median 

densities observed in the 1980s and 2001-2004, suggesting a three-fold reduction of turtles in the 

lower Chesapeake Bay since the 1980s. 

Morreale et al. (2005) reported that the species composition of sea turtles in New York waters 

had changed, from 59% loggerheads in 1987-1992 to just 4% in 2002-2004. Whereas they 

captured 144 loggerhead turtles in the earlier sampling period, they caught only 2 in 2003 and 

none in the other two years. Sampling continued through 2007, but no more loggerheads were 

caught (K. Durham pers. comm.). The inequity in sampling effort among the two time periods 

(1978-1992 vs. recent) confounds the interpretation of these results. 
67 

Figure 23. Annual catches or catch rates of loggerhead sea turtles at four southeastern U.S. 

study sites: St. Lucie Power Plant, Indian River Lagoon, Cape Canaveral to Cape Hatteras 

(SEAMAP), and Pamlico-Albemarle Estuarine Complex (N.C.). Note that the y-axis scale 

differs among graphs. 

 

North Carolina 1995-2007 (turtles/pound net-soak day)

0

0.01

0.02

0.03

0.04

0.05

0.06

0.07

0.08

0.09

19801982198419851988199019921994199619982000200220042006

CPUE

SEAMAP 1990-2007 (turtles/tow)

0

0.02

0.04

0.06

0.08

0.1

0.12

0.14

0.16

19801982198419861988199019921994199619982000200220042006

CPUE

Indian River Lagoon 1983-2007 (turtles/km net-soak hr)

0

1

2

3

4

5

19801982198419861988199019921994199619982000200220042006

CPUE

St. Lucie Power Plant 1980-2007 (number of turtles)

0

100

200

300

400

500

600

700

1980198119821983198419851986198719881989199019911992199319941995199619971998199920002001200220032004200520062007

Catch

North Carolina 1995-2007 (turtles/pound net-soak day)

0

0.01

0.02

0.03

0.04

0.05

0.06

0.07

0.08

0.09

19801982198419851988199019921994199619982000200220042006

CPUE

SEAMAP 1990-2007 (turtles/tow)

0

0.02

0.04

0.06

0.08

0.1

0.12

0.14

0.16

19801982198419861988199019921994199619982000200220042006

CPUE

Indian River Lagoon 1983-2007 (turtles/km net-soak hr)

0

1

2

3

4

5

19801982198419861988199019921994199619982000200220042006

CPUE

St. Lucie Power Plant 1980-2007 (number of turtles)

0

100

200

300

400

500

600

700

1980198119821983198419851986198719881989199019911992199319941995199619971998199920002001200220032004200520062007

Catch
68 

Size Distribution of In-water Trends 

Length distributions from the data provided are assumed to be representative of the true length 

frequencies of loggerhead sea turtles within the sampling area. We plotted the proportion of 

turtles within each 5 cm size class over the time series of each dataset. Unless otherwise noted, 

standard straight carapace length (SCL) is reported. Size classes examined in this analysis 

included turtles ranging from 40 cm to 110 cm. We report the median size of juvenile turtles and 

the proportion of turtles of sizes in the smallest size classes, 40-55 cm. Juveniles were defined as 

40-90 cm, but animals in this size range may include some adults, and conversely, some animals 

greater than 90 cm may not be adults (see Life History section in this TEWG Report). Data were 

binned into half-decades except for 2005-2007. 

The length frequency distribution from all loggerhead turtles entrained in the St. Lucie Power 

Plant canal (1980-2007, n=6,600) shows several interesting patterns (Figure 24). The shifting of 

the peak to the right indicates an overall shift in the median size of juveniles (Figure 25). 

Another pattern observed in the length distributions through the time series is the decrease in the 

relative proportion of the smallest size classes, 40-55 cm (Figure 26). The proportional decrease 

of small turtles in the more recent samples may also be contributing to the shift in median size of 

the juvenile size class. 

The length frequency distribution data collected in the Indian River Lagoon (1982-2007, n=736) 

show similar patterns to the data from the St. Lucie Power Plant: the shift in the median size of 

juveniles and the apparent decrease in proportion of the smallest juveniles (Figure 25). The trend 

in the proportion of small, 40-55 cm turtles is consistent with the trend observed in the St. Lucie 

Power Plant time series (Figure 26). 

Although the time series of data from the SEAMAP trawl surveys is shorter and the sample size 

is smaller (1990-2007, n=354) than in the two previously discussed nearshore sites, this trawl 

survey represented similar patterns, including a shift through time in the median size of juveniles 

(Figure 25). The pattern observed in the longer time series of St. Lucie Power Plant and Indian 

River Lagoon, showing a decrease in the smallest size classes, is also evident in this data set. 

Although there are few turtles captured that are smaller than 55 cm, the proportion has been 

decreasing over the time series (Figure 26). 

The data from North Carolina’s Pamlico-Albemarle Sound Estuarine Complex (1990-2007, 

n=2,806) also show a similar trend to those observed at the three other sampling sites (Figure 

24). The median juvenile size has increased through the sampling period, beginning in 1990 

(Figure 25). The proportion of small juveniles also followed the same pattern as the other three 

sampling sites (Figure 26). 

Length frequency data from the northeast STSSN data set (1987-2007, n=3,175) also show 

similar trends to the four southeastern sites. Throughout the entire time series (1987-2007) we 

observed an increasing median SCL in the juvenile size classes and also decreasing proportions 

of the smallest juveniles (Figure 25). The proportion of small juveniles also showed a decreasing 

trend through the entire time series (Figure 26). 
69 

Loggerhead turtles in New York waters apparently are smaller than animals to the south (Figure 

27); the reported size range is 36.6-89.2 cm SCL (Burke et al. 1993; Morreale et al. 1992). Live 

captured animals from 1988-1995 (n=201) ranged in size from 40.3 cm to 65.6 cm; annual 

median sizes ranged from 47.8 to 52.7 SCLstd and overall was 50.5 cm. From 2002 to present, 

only two loggerheads have been captured, both in 2003 (Morreale et al. 2005; K. Durham pers. 

comm.): 55.4 cm and 62.6 cm. The proportion of small juveniles observed at this site was much 

higher than at the southeastern sites and ranged from 0.66 to 0.90 from 1988-1995. 

Summary

It is nearly impossible to draw any conclusion about regional abundance and population trends 

based on a single site. However, the fact that the four southern data sets, which cover a large 

portion of the loggerhead’s nearshore habitat off the southeast U.S. Atlantic coast, show similar 

patterns in catch/catch rates and that virtually all sources of data show a similar pattern in size 

distributions is intriguing. Several distinct patterns have emerged from these analyses. 

Together they indicate there was an increase in abundance and/or catchability of neritic animals 

in the southeast U.S. through the early part of this decade. In the first ten years of the two 

longest time series, the median size of 40-90 cm animals was decreasing to a low in 1990-1994 

and then began increasing at all sites to a peak in 2005-2007 (Figure 25). The proportion of 

small juveniles, 40-55 cm, increased to a high in 1990-1994 and then began decreasing to a low 

in 2005-2007 (Figure 26). The exception to these two trends is seen in the northeast STSSN 

data. Through that entire time series we observed an increasing trend in the median size of 40-90 

cm animals and a consistently decreasing trend in the proportion of small juveniles. 

Interestingly, the northernmost area (New York), where the foraging population comprised the 

smallest size classes (Figure 27; Burke et al. 1993; Morreale et al. 1992), has seen a dramatic 

change, with only two loggerheads being captured over a 6 yr period. This decrease in captures 

during the most recent sampling is consistent with the lack of small juveniles appearing at the 

other sampling sites examined further south. 

The apparent decline of loggerhead abundance in the northeast, based on aerial surveys in the 

Chesapeake Bay, and the dearth of captures in New York may be due to 1) fewer turtles 

migrating north of Cape Hatteras, North Carolina each spring; 2) fewer turtles utilizing the 

Chesapeake Bay en route to northern foraging grounds (Mansfield 2006), 3) an overall decline in 

the Atlantic loggerhead population, and/or 4) changes in sighting or capture probabilities in time 

and space, due to changes in environmental conditions and/or methods across time and space. 

Morreale et al. (2005) suggested that the reduction in the number of loggerheads caught in New 

York and the commensurate shift in marine turtle species composition might be indicative of a 

major shift in foraging grounds. Without additional data, it is not possible to determine the 

relative significance of the decline in Virginia’s or New York’s numbers over time. 

The good news is that there appears to be increasing trends in catch rates through 2008 in the 

southeast U.S. This, coupled with the shift in median size of neritic juveniles, may indicate there 

is a relatively large cohort that will be reaching maturity in the near future, assuming there is not 

an emerging source of mortality on the larger juveniles and adults. 
70 

The majority (12,725 of 13,826 turtles, 92%) of the data used in our analyses was from turtles 

less than 90 cm, and most were from Juvenile Stage III (see Life History Section in this TEWG 

report). Thus, we are limited in hypothesizing what may be causing the declines on the nesting 

beaches since the turn of this century is two life stages removed (Stage V). We estimate that the 

duration of the two juvenile neritic/oceanic stages (III and IV) together is approximately 20 years 

or longer (see Life History Section in this TEWG report). If we look back 20+ years, to the 

beginning of the two longest time series, we can see that catch rates were low in the early 1980s. 

We do not know what they were before the 1980s and cannot determine if immediately prior 

there was a lull in recruitment to the youngest neritic juvenile stage at that time. Interestingly, it 

was during the early 1980s that we observed the highest proportions of the smallest juveniles, 

perhaps indicative of high levels of recruitment from the oceanic stage, and/or, the paucity of 

larger juveniles. 

The decrease in the proportion of the smallest size classes of juveniles in the most recent years 

raises concern that currently we may be witnessing a recruitment failure or, alternatively, that 

oceanic animals (Stage II) are moving to the next stage (III) at a larger size (2008). We observed 

the lowest proportion of small juveniles in 2000-2007. Taking into account the range in duration 

of the oceanic juvenile stage (II), these new recruits to the neritic zone would have hatched 

sometime between the mid 1980’s to the late 1990’s. During this period there was an increasing 

trend in nesting on the Peninsular Florida beaches (TEWG 2000; see Population Trends section 

in this TEWG report). Assuming that hatching and emergence success rates have not changed, 

one may conclude that there was increased production on the beach during that time. If we also 

assume that the survival rates during the oceanic juvenile stage have not changed, we then would 

not expect to see a decrease in the proportion of small juveniles, but rather we would expect to 

observe an increase. Snover (2008) demonstrated that variable environmental conditions could 

have considerable impacts on the optimal size for the shift from oceanic to neritic habitats, 

determined as the point that maximizes growth rates and minimizes mortality rates, in 

loggerhead turtles. She suggests that these environmentally driven increases in size at the shift 

could be mistaken for loss of recruitment from the oceanic stage and that alternative hypotheses 

regarding changing growth rates and optimal sizes at habitat shifts need to be considered. 

Notably, through 2003 we observed an increase in catch/catch rates in the southeast U.S., which 

appears to be inconsistent with the hypothesis of recruitment failure. However, the recent data 

on catch/catch rates may support the hypothesis of recruitment failure. One possible explanation 

is that animals recently may have grown differently in the oceanic environment, achieving a 

larger size before recruiting onto the neritic foraging grounds. Alternatively, the change in 

numbers/catch rates we saw since the mid-1990’s could be related to changing proportions of the 

juvenile population moving between the oceanic and neritic environment (McClellan and Read 

2007) and not due to an actual increase in the numbers of the juvenile population. This enigma 

reinforces the need to continue monitoring the juvenile loggerhead foraging grounds to observe 

whether these patterns continue. With increased in-water monitoring, not just of numbers but of 

sex ratios, survival rates and other demographic parameters, we will be able to make better 

predictions for the future and maybe anticipate declines in nesting like the one we are observing 

now. 
71 

Figure 24. Proportion of turtles within each 5 cm size class over the time series of each 

dataset: St. Lucie Power Plant, Indian River Lagoon, Cape Canaveral to Cape Hatteras 

(SEAMAP), Pamlico-Albemarle Estuarine Complex (N.C.) and the northeast STSSN. 

St. Lucie Power Plant 1980-2007

0.00

0.05

0.10

0.15

0.20

0.25

0.30

0.35

0.40

0.45

40-

44.9

45-

49.9

50-

54.9

55-

59.9

60-

64.9

65-

69.9

70-

74.9

75-

79.9

80-

84.9

85-

89.9

90-

94.9

95-

99.9

100-

104.9

105-

109.9

SCLmin

Proportio

n

1980-84 (n=519)

1985-89 (n=747)

1990-94 (n=642)

1995-99 (n=1475)

2000-04 (n=2111)

2005-07 (n=1106)

Indian River Lagoon 1982-2007

0.00

0.05

0.10

0.15

0.20

0.25

0.30

0.35

0.40

0.45

40-

44.9

45-

49.9

50-

54.9

55-

59.9

60-

64.9

65-

69.9

70-

74.9

75-

79.9

80-

84.9

85-

89.9

90-

94.9

95-

99.9

100-

104.9

105-

109.9

SCLstd

Proportio

n

1982-84 (n=77)

1985-89 (n=235)

1990-94 (n=91)

1995-99 (n=105)

2000-04 (n=156)

2005-07 (n=72)
72 

SEAMAP 1990-2007

0.00

0.05

0.10

0.15

0.20

0.25

0.30

0.35

0.40

0.45

40-

44.9

45-

49.9

50-

54.9

55-

59.9

60-

64.9

65-

69.9

70-

74.9

75-

79.9

80-

84.9

85-

89.9

90-

94.9

95-

99.9

100-

104.9

105-

109.9

SCLstd

Proportio

n

1990-94 (n=72)

1995-99 (n=70)

2000-04 (n=138)

2005-07 (n=74)

North Carolina 1990-2007

0.00

0.05

0.10

0.15

0.20

0.25

0.30

0.35

0.40

0.45

40-

44.9

45-

49.9

50-

54.9

55-

59.9

60-

64.9

65-

69.9

70-

74.9

75-

79.9

80-

84.9

85-

89.9

90-

94.9

95-

99.9

100-

104.9

105-

109.9

SCLstd

Proportio

n

1990-94 (n=48)

1995-99 (n=833)

2000-04 (n=1718)

2005&07 (n=199)
73 

NE STSSN 1987-2007

0.00

0.05

0.10

0.15

0.20

0.25

0.30

0.35

0.40

0.45

40-

44.9

45-

49.9

50-

54.9

55-

59.9

60-

64.9

65-

69.9

70-

74.9

75-

79.9

80-

84.9

85-

89.9

90-

94.9

95-

99.9

100-

104.9

105-

109.9

SCLstd

Proportio

n

1987-89 (n=100)

1990-94 (n=271)

1995-99 (n=972)

2000-04 (n=1458)

2005-07 (n=374)
74 

Figure 25. Median length of juvenile loggerhead sea turtles (40-90 cm SCL) at four 

southeastern U.S. study sites and the Northeast STSSN: St. Lucie Power Plant (STLPP), 

Indian River Lagoon (IRL), Cape Canaveral to Cape Hatteras (SEAMAP), and PamlicoAlbemarle Estuarine Complex (NC). Note the IRL time series does not include data prior to 

1982 and NE STSSN does not include data prior to 1987. 

52

54

56

58

60

62

64

66

68

70

1980-84 1985-89 1990-94 1995-99 2000-04 2005-07

SC

L

STLPP IRL SEAMAP NC NE STSSN

Figure 26. Proportion of small (40-55 cm SCL) juvenile loggerhead sea turtles at four 

southeastern U.S. study sites and the Northeast STSSN: St. Lucie Power Plant (STLPP), 

Indian River Lagoon (IRL), Cape Canaveral to Cape Hatteras (SEAMAP), and PamlicoAlbemarle Estuarine Complex (NC). Note the IRL time series does not include data prior to 

1982 and NE STSSN does not include data prior to 1987. 

0.00

0.05

0.10

0.15

0.20

0.25

0.30

0.35

1980-84 1985-89 1990-94 1995-99 2000-04 2005-07

Proportio

n

STLPP IRL SEAMAP NC NE STSSN
75 

Figure 27. Length frequency data from live-captured animals in Long Island Sound, New 

York from 1988-1995 (R. DiGiovanni pers. comm.). 

0

0.05

0.1

0.15

0.2

0.25

0.3

0.35

0.4

40-

44.9

45-

49.9

50-

54.9

55-

59.9

60-

64.9

65-

69.9

70-

74.9

75-

79.9

80-

84.9

85-

89.9

90-

94.9

95-

99.9

100-

104.9

105-

109.9

Proportion

New York (n=201)
76 

PART IV. FACTORS POTENTIALLY RESPONSIBLE FOR DECREASING 

NUMBERS OF NESTS 

Incidental Capture -Paul Richards 

Loggerhead sea turtles are caught as bycatch in numerous fisheries operating in the Western 

North Atlantic. Loggerhead sea turtles are also incidentally captured in other ways such as in 

power plant intake pipes, dredge operations, etc. (see the Loggerhead Recover Plan [National 

Marine Fisheries Service and U.S. Fish and Wildlife Service 2008] for a full review and 

subsequent threats analysis). Extrapolated estimates of loggerhead bycatch from selected 

fisheries are available on the SEFSC website 

(http://www.sefsc.noaa.gov/seaturtlepublications.jsp; see NMFS SEFSC 2001 for a summary 

through 2000, see Table 14 for list of reports and publications since 2000); however, the impact 

of bycatch and other incidental capture on the Western North Atlantic loggerhead population has 

not been quantitatively evaluated for a number of reasons. First, we have inadequate information 

to assess the size and status of the loggerhead stock. Second, there are many fisheries and other 

activities (both U.S. and foreign) that may impact loggerhead turtles in the Western Atlantic (see 

Lewison et al. 2004), and we have very spotty knowledge of total lethal takes by all of these 

fisheries and other sources of mortality. For example, in the year 2000, the loggerhead takes 

from the observed U.S. pelagic longline fishery were estimated to be about 1,256 (Yeung 2001), 

a tiny fraction of the estimated 150,000 to 200,000 total takes in the Atlantic (Lewison et al. 

2004). Furthermore, the total takes of loggerhead sea turtles in all U.S. fisheries (observer based 

estimates plus other estimates) was about 748,112 annually for the years 2001 to 2005 (SEFSC 

unpubl. data). Of these, approximately 729,456 were estimated as taken (e.g. passing through 

turtle excluder devices) by shrimp trawls. This leaves about 18,656 takes from all other U.S. 

fisheries combined, and therefore an even smaller fraction of the total takes by just pelagic 

longlines in the Atlantic. 

In observed U.S. fisheries, loggerhead takes range from moderate sized juveniles (> 40 cm CCL) 

through adult sized individuals. Mortality is about 20 to 50% (see reports in Table 14). 

Hatchling and small size classes (< 40 cm CCL) are rarely seen as bycatch in U.S. commercial 

fisheries. Even within relatively well observed fisheries, the estimates of uncertainly are very 

high (CVs of 1.0 are common due to sparse data; see longline reports cited below in Table 14). 

Increased observer coverage in U.S. and other nations’ fisheries would improve the precision of 

and increase confidence in loggerhead bycatch estimates. However, in the absence of a 

quantitative population estimate, even precise bycatch estimates could not contribute to a stock 

assessment. 
77 

Table 14. List of reports and publications of estimated bycatch of loggerhead sea turtles in 

U.S. fisheries since 2000. 

Fishery Report 

Shrimp trawl Epperly et al. 2002 

Pelagic longline Garrison 2003a 

 Garrison and Richards 2004 

 Fairfield-Walsh and Garrison 2006 

 Fairfield-Walsh and Garrison 2007 

Shark bottom longline Richards 2007 

 Southeast Fisheries Science Center 2007 

Gulf of Mexico reef fish Southeast Fisheries Science Center 2008 

 Southeast Fisheries Science Center 2009a 

 Southeast Fisheries Science Center 2009b 

Shark gillnet Garrison 2003b 

 Garrison 2007 

North Carolina inshore gillnet 

(Pamlico Sound Restricted 

Gillnet Area) 

Price 2004 

 Price 2005 

 Price 2006 

 Price 2007 

 Price 2008 

 Price 2009 

Sea scallop dredge Murray 2004a, Murray 2004b, Murray 2005, 

Murray 2007 

Sea scallop trawl Murray 2007 

U.S. mid-Atlantic bottom otter 

trawl 

Murray 2008 

Adult Female Survival Rates –Christopher Sasso

Annual survival rates were estimated using tagging data from Melbourne Beach, Quintana Roo 

(Mexico), and Wassaw Island using a multistate conditional Arnason-Schwarz model with 

separately identifiable survival and capture probabilities (Lebreton et al. 1992; Schwarz and 

Arnason 1996). 

Details on the nesting surveys for Quintana Roo, Mexico and Wassaw Island, Georgia are 

provided in the description of nesting beach tagging studies earlier in this report. For Melbourne 

Beach, Florida nesting surveys have been conducted along 21 km of beach in the Archie Carr 

National Wildlife Refuge since 1982 (Ehrhart et al. 2007a). From 1982 through 1984 they 

concentrated on tagging turtles. In 1985, their emphasis shifted to primarily marking nests for 

reproductive studies, and tagging has been secondary; from 2005-2007 their tagging efficiency 
78 

has ranged from 2.8% - 4.3% (W. Redfoot pers. comm.). W. Redfoot (pers. comm.) indicated 

that while an attempt is made to flipper tag each nesting turtle, it is often not possible. These data 

tagging data were used to estimate adult survival. 

Annual survival estimates were generated following the methods of Rivalan et al. (2005) which 

allowed individuals to transition between an observable breeder state and an unobservable 

nonbreeder state. Using these methods, individuals could temporarily emigrate, spend multiple 

years in a nonbreeder state, and transients could be accounted for in the analyses. Transients 

were accounted for by specifying two groups: one for all individuals marked and never 

recaptured (transients) and one for individuals recaptured in at least one subsequent year 

(residents). The number of years spent in the nonbreeder state was constrained by the number of 

years being tested for the breeding cycle with cycles of 2, 3, 4 and 5 years tested here where the 

cycle length is defined as the number of years skipped between nesting plus one as a breeder. 

Models were assessed using the program MSURGE (Chopquet et al. 2005). 

The candidate models for each data set were parameterized for varying effects on survival and 

capture probabilities, different lengths of the breeding cycle, and constant transition between 

states. Survival was modeled as time dependent (St), transients (ST), interaction between time 

dependence and transients (St*T), and additive effects of time dependence and transients (St+T). 

Capture could be modeled as time dependent (Pt), trap dependent (Pm), interaction between time 

dependence and trap dependence (Pt*m), and time dependence with additive effects of trap 

dependence (Pt+m). No models of trap dependence only were analyzed for Melbourne Beach due 

to variability in sampling effort among years. Variability in sampling effort may result in 

underestimates of parameters. Goodness of fit for the models were assessed following the 

protocol described in Rivalan et al. (2005) 

The best of the candidate models for each nesting area was selected using the quasi-likelihood 

Akaike Information Criterion adjusted for small sample size (QAIC; Akaike 1973, Lebreton et 

al. 1992). The survival rates calculated by the model for each group (transients and residents) 

allow for an unbiased estimate of the proportion of transients in the data using the following 

equation from Pradel et al. (1997): 

Proportion of transients = 

residents

transients

S

S 1 −

The best model for Melbourne Beach had a four year breeding cycle with a transient effect for 

survival and time dependent recapture probability (ST Pt). The survival estimate for residents 

was 0.73 (95% CI 0.71 – 0.76) with 39% of the individuals in the data being transients. The best 

model for Mexico was also ST Pt with a four year breeding cycle with resident survival estimated 

to be 0.85 (95% CI 0.81 – 0.88) and 35% of the individuals in the data being transients. Wassaw 

Island data were best described by a three year breeding cycle with a transient effect on survival 

and trap dependent capture probability (ST Pm). The resident survival estimate for Wassaw 

Island was 0.81 (95% CI 0.77 – 0.84) with 69% of the individuals being transients. 

The same methods have been applied to 16 years of data from Bald Head Island, North Carolina 

(Hedges 2007) with a survival estimate of 0.85 (95% CI 0.78 – 0.93) for residents. On Bald 
79 

Head Island, transients represented 67% of individuals in the data. Interestingly, the proportions 

of transients on the two Northern U.S. Subpopulation beaches (Wassaw and Bald Head Islands) 

are much greater than for Peninsular Florida and Mexico. This finding is not surprising given 

these Northern U.S. Subpopulation beaches represent small beaches within a larger matrix of 

suitable nesting habitat, and suggests these studies may need to monitor nesting at a larger scale 

to make meaningful conclusions on population trends. 

Previous estimates of survival were generated with the Melbourne Beach and Wassaw Island 

data using a Jolly-Seber model which did not account for emigration or the unobservable 

nonbreeder state (NMFS SEFSC 2001). Those analyses suggested the best model for survival 

was time dependent, but only an average over all years was presented with Wassaw Island 

estimated to be 0.79 and Melbourne Beach estimated to be 0.83. Frazer (1983b) estimated 

survival to be 0.8091 on Little Cumberland Island, Georgia. 

The results generated here suggest that survival may be lower for Melbourne Beach nesters. The 

foraging grounds for Peninsular Florida nesters do differ from those of Northern U.S. 

Subpopulation nesters (see Spatial Distribution section in this TEWG report) and it is possible 

mortality is higher for Peninsular Florida nesters. However, the data from Melbourne Beach do 

not represent a dedicated mark-recapture study and the interception rate is very low. Hence, the 

analysis based on these data may be an underestimate of true survival and the estimate is suspect. 

Further research will be necessary to determine if adult female survival is lower for the 

Peninsular Florida Subpopulation and a potential cause for the rapid decline in nesting numbers. 

In addition to the models presented here, models to assess any change in survival since the 

implementation of turtle excluder devices (TED) in the shrimp fishery were explored. However, 

these models were poor compared to those presented above. No TED effect may have been 

found due to the fact that while TEDs were introduced to the shrimp fishery in 1987, they were 

not required to be large enough to release turtles the size of nesting females until 2003 (Epperly 

and Teas 2002) . 

Proportion of Putative First-time Nesters –Melissa Snover and Sheryan Epperly 

We estimated the proportion of first-time nesters over time on Quintana Roo to determine if 

there were any changes over time (Table 15). The Florida and Northern U.S. researchers did not 

believe that they intercepted a sufficient proportion of the females on the nesting beaches to 

support this type of analysis. Thus, the estimates are for beaches of the Mexican Subpopulation 

only. Data for the first two years were censored in the first-time nesters analyses to allow the 

majority of neophyte nesters to be marked during those first two years. 
80 

Table 15. Percent first-time nesters by year for Quintana Roo. 

Year Percent of Neophytes on Quintana Roo Beaches 

1996 inconel single tagging began this year for all animals 

1997 

1998 47.10 

1999 43.62 

2000 48.51 

2001 44.22 

2002 46.45 

2003 47.45 

2004 57.05 

2005 59.90 

2006 52.71 

The trend for Quintana Roo shows a significant increase at a rate of 2.99% per year (P=0.022). 

Thus, Quintana Roo, which has a decreasing trend in nesting activity comparable to the decrease 

on Florida beaches (see Population Trends in this TEWG report) shows an increase in the 

proportion of first-time nesters, which indicates a loss of experienced adult females from the 

population. 

Directed Harvest –Matthew Godfrey 

Sea turtles in the Western Atlantic, including loggerheads, have been harvested for human 

consumption for centuries (see McClenachan et al. 2006 for overview). International trade in sea 

turtles and their products has been strictly controlled by the Convention in International Trade in 

Endangered Species (CITES) since 1989, when all species and populations were placed on 

Appendix I, which bans all international trade (Bräutigam 1989). Most nations and territories in 

the Western Atlantic are parties of CITES; exceptions include Anguilla and the Turks & Caicos 

Islands (Richardson et al. 2006). All parties are bound by the regulations of CITES, although 

some countries, such as Cuba, have reservations to certain species on Appendix I and are not 

bound by a ban on international trade of those species. Currently, no party to CITES has a 

reservation to loggerhead sea turtles (www.cites.org). In the case of the Western North Atlantic, 

there is little evidence of widespread international commercial trade based on CITES statistics 

(Bräutigam and Eckert 2006). However, there has been, and in some cases continues to be, 

directed take of loggerheads within nations or territories in the Western Atlantic. Of the 42 

countries and territories in the Western Atlantic listed in Appendix III of the Recovery Plan for 

the Western North Atlantic Population of Loggerhead Sea Turtles, 14 allow loggerhead egg 

and/or whole animal harvest (National Marine Fisheries Service and U.S. Fish and Wildlife 

Service 2008). For example, in the Cayman Islands, the legal loggerhead harvest has targeted 

large juveniles or adults (Bell et al. 2006). However, most locations in the Western North 

Atlantic, where legal harvest of loggerhead turtles or eggs currently occur, are found the 

Caribbean, where loggerhead density is low (Ehrhart et al. 2007a) and thus actual harvest levels 

are low (e.g. in the Cayman Islands, only three loggerheads were taken in a five year period; Bell 
81 

et al. 2006). A notable exception to this pattern is the case of Cuba, where many loggerhead 

turtles were actively harvested from Cuban waters until the mid 1990’s (Moncada Gavilan 2000). 

Between the years of 1968 and 1975, the Cuban loggerhead fishery was not actively managed 

and the mean annual catch was 491 metric tons (Moncada Gavilan 2000). To put this in context, 

assuming that the mean mass of adult females is 114 kg (LeBuff 1990), the annual catch would 

represent an annual harvest of 4,307 adult females in these early years of the fishery, although 

presumably adult males and juveniles were also captured. Moncada Gavilan et al. (2003) report a 

majority of juveniles represented in incidentally captured loggerheads in other Cuban fisheries, 

so the actual number of individual turtles captured per year in the targeted loggerhead fishery 

may have been higher. Between 1967 and 1987, the turtle fishery was restricted between June 

and August, to protect reproductive animals. Annual catch rates for these years were reduced by 

40% to about 300 metric tons (or an equivalent of 2,631 adult females). From 1988 to 1994, the 

closed seasons were modified and extended to increase protection of reproductive animals. The 

annual catch rate decreased during this period from initial levels >200 metric tons (or 1,750 adult 

female equivalents) to <75 metric tons (or 660 adult female equivalents) at the end. Starting in 

1995, fishing effort for turtles was limited to two sites (Isle of Pines and Nuevitas) and targeted 

hawksbills nearly exclusively. Annual catch rates of loggerheads were close to zero by 1996 and 

onwards. The hawksbill harvest was ended in early 2008, and all species of sea turtle in Cuban 

waters are now completely protected from directed harvest (www.wwfca.org). 

The overall pattern for harvest of loggerheads in Cuba is a three-phase step-down, from a peak in 

the late 1960s and early 1970s to a relatively low level in the early 1990’s. Interestingly, as fewer 

loggerheads were harvested in Cuban waters in the late 1980s through the late 1990’s, there was 

a concurrent increase in the number of loggerhead nests laid on index beaches in Florida 

(http://research.myfwc.com). When the loggerhead fishery in Cuba ended in 1996, the annual 

number of nests in Florida was still increasing, with little sign of decline that has characterized 

recent years. It is unclear whether the harvest of loggerheads in Cuba from the late 1960s 

through the early 1990’s is linked to the present declining trend in number of loggerhead nests 

laid in Florida, but the current complete protection of loggerheads in Cuban waters is a positive 

management action that can only contribute to recovery. 

Increase in Mortality Due to Disease –Allen Foley 

The most common evidence of disease documented in cases of dead or moribund (i.e., stranded) 

sea turtles is emaciation. Emaciation is usually determined by appraising the overall body 

condition of a turtle. Typically, only severe cases (i.e., turtles with a distinctly concave plastron 

and a prominent supraoccipital) are noted as emaciated. Since 1986, both the number and 

percentage of loggerhead strandings in Florida that were emaciated has increased (Figure 28). 

Several recent epizootics involving loggerheads have also been documented in Florida during the 

past decade. Blooms of Karenia brevis (commonly referred to as red tide) have been detected 

every year in southwest Florida since 1995 (FFWCC unpubl. data). At concentrations above 

100,000 cells per liter (referred to as a strong red tide), K. brevis is considered potentially lethal 

for manatees (Trichechus manatus latirostris, Landsberg 2002). Red tide is also believed to be a 

mortality factor for loggerheads (Redlow et al. 2003) and we assume that strong red tides could 

be potentially lethal for loggerheads. From 1995 through 2005, unusually high numbers of 
82 

loggerhead strandings were associated with strong red tides in southwestern Florida during seven 

of those years (1995, 1996, 2000, 2001, 2002, 2003, and 2005; FFWCC unpubl. data). In late 

2000 and early 2001, there was a loggerhead epizootic throughout southern Florida accounting 

for about 150 strandings that was associated with trematode infections (Jacobson et al. 2006). In 

September and October of 2006, an epizootic involving about 100 loggerheads occurred in 

northeast Florida (FFWCC unpubl. data). 

 

The annual numbers of loggerhead nests in the Peninsular Florida Subpopulation were increasing 

during the period of 1989 through 1998 but have since decreased to such a large extent that there 

has now been an overall decrease in the annual numbers of nests since 1989 (Witherington et al. 

2009). Possible reasons for the decline in the annual numbers of nests could be due to increased 

mortality of adult female loggerheads or to a decrease in the recruitment of large, immature 

females into the adult population (from increased mortality of that life stage). The recent 

increases in the incidences of disease in loggerheads in Florida have also been documented for 

adult (Stage V) and large immature loggerheads (Stage IV; Figure 29) and could have played a 

role in the recent decrease of loggerhead nesting. However, the magnitude of the mortality of 

adult and large, immature loggerheads in Florida from disease as represented by strandings of 

emaciated loggerheads > 81.9 cm SCL has been relatively small (<35 individuals per year) 

(Figure 29). 
83 

Figure 28. The number and percentage of dead or moribund (i.e., stranded) loggerheads that 

were noted to be emaciated each year in Florida during 1986 through 2008. Both have increased 

during this period. Trends are best represented by the power regressions models. 

R2 = 0.8652

R2

 = 0.9142

0

50

100

150

200

250

1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008

Year

# of emaciated loggerheads

0.0%

2.0%

4.0%

6.0%

8.0%

10.0%

12.0%

14.0%

16.0%

18.0%

% occurrence of emaciation

# emaciated

% emaciated
84 

Figure 29. The number and percentage of dead or moribund (i.e., stranded) loggerheads greater 

than 81.9 cm straight carapace length (measured from the nuchal notch to the posterior marginal 

tip) that were noted to be emaciated each year in Florida during 1986 through 2007. Both have 

increased during this period. The trends are best represented by the polynomial regressions that 

are shown. 

R2 = 0.6896

R2

 = 0.6622

0

5

10

15

20

25

30

35

1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006

Year

# of emaciated loggerheads

0.0%

2.0%

4.0%

6.0%

8.0%

10.0%

12.0%

14.0%

% occurrence of emaciation

# emaciated > 81.9 cm SCL

% emaciated > 81.9 cm SCL
85 

PART V. RESEARCH NEEDS AND RECOMMENDATIONS 

The most worrisome conclusion this TEWG committee faced was that existing data remain 

woefully inadequate to determine the cause(s) of the declines in nesting for any of the Western 

North Atlantic subpopulations, to detect if declines in nesting signal a decline in the adult 

population. While past TEWGs also note research needs, we point out that meeting such needs 

require adequate funding to collect essential data, cooperation across agencies including 

recognition of permitting hurdles, open access agreements to make the data available in a timely 

manner, and robust quantitative approaches so that the various data lend themselves to stock 

assessments. Below we summarize the research needs and recommendations. 

Population Parameters

Our knowledge of loggerhead population parameters is rudimentary. Additional information on 

population parameters are needed to enhance our ability to adequately assess this stock. Top 

priorities need to focus on generating better estimates of abundance, survivorship, stage duration, 

size-class distribution, and fecundity parameters. Changes in any of these parameter estimates 

could cause changes in the number of nests, which is currently our main assessment dataset. 

Mark and recapture studies remain a research need, at all ages and stages. 

Better estimates of population abundance and trends and estimates of demographic parameters 

are needed and can be obtained through in-water, mark-recapture, and satellite studies. To 

ensure such estimates are robust, the monitoring should include long term, continuous (within 

the limits of technology) studies and address all life history stages to assess changes in vital rates 

over time and better understand their natural variability and impact on population trends. 

Survival rates for life history stages not easily recaptured (e.g. oceanic/pelagic juveniles and 

adult males) can be estimated using satellite telemetry technologies. Smaller size classes should 

be tracked and robust sample sizes should be used. In-water studies should be coupled with 

sampling to estimate and monitor other demographics, such as shifts in size distribution, sex 

ratios, growth rates and age/size at maturity. A network of study sites in foraging areas, 

particularly those found along the east coast of the U.S., the Gulf of Mexico, Cuba, the Yucatán 

Peninsula and in oceanic foraging areas should be established to provide estimates of 

survivorship, growth, recruitment, emigration rates, and populations estimates. 

Better estimates of population parameters derived from nesting beaches are also needed and may 

be obtained through saturation tagging studies on nesting beaches representative of all 

subpopulations. Sampling should be designed to provide estimates of the following parameters 

as well as the variability in the estimates: recruitment, fidelity, survivorship, remigration, clutch 

size, number of clutches, hatching success, emergence success, and primary sex ratio. 

Secondary priorities include research on sex ratios and migratory routes. For example, we do 

not know the operational sex ratios for any subpopulation nor the implications of highly skewed 

sex ratios. We need to understand the mechanisms that direct sex determination and the 

variation is response to environmental variables. Similarly we need to understand how and why 

sex ratios shift with sex-specific behavior or seasonal migrations. Forensics and aerial surveys 
86 

of coastal zones (where turtles, fisheries, boating activities, and pollutants are most concentrated) 

will enhance our understanding of which turtles are where, relative to known risk factors. 

Tertiary priorities include quantifying how epizootics and other sub-lethal events affect 

population parameters. Epizootic events remain poorly studied and may be cryptic when declines 

in health are slow. Epidemiological approaches are lacking in studies of marine turtle health. 

Data quantifying sub-lethal effects of disease on condition, reproduction, maturation, ontogenetic 

migration, or remigration are completely absent. 

Strandings data currently provide us with restricted insight into some of these parameters, but 

without a better understanding of how these samples vary in space and time and how they are 

biased by behavior, physiology and cause of death, we will remain limited in how we interpret 

the populations of interest. Added forensic and necropsy parameter collection would allow the 

strandings data to increase greatly in value and would enable future rigorous analyses to address 

demographic parameters as well as mortality risks. 

Spatial and Temporal Distributions 

There is a need to better understand the distribution of turtles in space and time and to relate 

turtle distribution to environmental parameters and habitat use. In addition to survival rates, 

mentioned above, the use of satellite telemetry (as well as other tracking modalities where scaleappropriate) can provide distribution data which could be incorporated into state-space models to 

predict turtle habitat use and spatial distribution. Such research could provide suggestions for 

how the spatial overlap between turtles and threats could be reduced. Aerial surveys can be used 

for the same, but in much smaller areas. While there is very limited information on the U.S. 

subpopulations and more is needed, there is nothing known about the distribution of animals 

originating in the Caribbean, except where Mexico juveniles have been detected on the northern 

foraging grounds through genetic analysis. 

Behavioral and physiological studies coupled with satellite telemetry will help us understand 

how loggerheads select habitats. Several rather significant holes exist in our understanding of 

loggerhead biology that impact how effectively we can interpret declines. The factors that 

trigger ontogenetic migrations are poorly studied yet may be critical to our understanding of 

recruitment. How the various age/stage classes differ in their responses to habitat features or 

cues, what changes in behavior occur in Western North Atlantic loggerheads as they transition 

from juveniles to reproductive adults, and whether subsets of loggerheads regularly brumate at 

some or all locales rather than migrate when temperatures drop below thermal thresholds (along 

with how responses to such cues act) should be addressed. 

Additionally, region- and season-specific behavioral/diving studies are needed to interpret 

detectability or sightability of loggerheads during aerial surveys. Within-season and/or withinregion (or environmental condition) comparisons of turtle distributions should reduce the 

observational bias from seasonal differences in surfacing behavior. 
87 

Stock ID 

Efforts are needed to define the population structure. Analyses of genetic samples collected 

continuously throughout the range of loggerheads in the Western North Atlantic are needed to 

describe the spatial structure. Additional analyses using non-coding regions and microsatellite 

DNA are needed to determine female relationships and the extent of male-mediated gene flow 

among all the subpopulations. 

The determination of the natal origin of subpopulations represented on the foraging grounds also 

contributes to our understanding of stock-specific movements and whether differences in their 

movements might subject them to differential threats. 

Effects of Incidental Capture 

Research on the effects of bycatch on survival rate and population growth rate remain needed 

and should be expanded. Fishery bycatch is often implicated as a source of population declines 

but direct links to such declines must be clear. As this is a domestic and international issue, 

collaboration among foreign nations in identifying bycatch effects is essential in addressing 

bycatch issues. 

Trophic Changes/ Carrying Capacity 

Shifts in diet have been documented in loggerhead turtles but it is unknown whether the 

phenomenon is just opportunistic feeding on bycatch or reflects shifts in preferred prey. The 

reasons and impacts of dietary shifts are important because of trophic changes and losses of 

preferred prey can change the carrying capacity of the habitat and may result in reduced nesting 

Where marine turtles undergo dietary shifts, it is important to establish causal relationships so 

that the source of change, such as environmental change vs. competition with commercial 

fisheries may be addressed. 

Modeling exercises and approaches should be advanced that integrate new biotic data and allow 

for predictive assessment. Similarly, retrospective techniques should remain as integral parts of 

the analyses examinations but with the recognition that the many data gaps this TEWG faced 

should not persist. 

ACKNOWLEDGMENTS 

We want to thank participants and state and national coordinators of the Sea Turtle Stranding and 

Salvage Network (STSSN) for the use of the United States stranding data and W. Teas for 

providing the data. We also thank observers who collected data from sea turtles interacting with 

commercial fisheries as well as the Northeast and Southeast Fisheries Observer Program staff. 

We thank J. Braun-McNeill for providing the North Carolina data and L. Stokes for providing 

the SEFSC observer data. The sightings data were compiled from a number of sources and are 
88 

archived in the NOAA Fisheries Sea Turtle Atlantic Strategy GIS; graphics showing aerial and 

shipboard survey results were provided by Tanya Dobrzynski.

We would like to thank the following colleagues for sharing their nesting beach data with the 

TEWG: T. Tucker (Mote Marine Laboratory), J. Foote, J. Grimes, K. Leonard, B. Perry, and J. 

McCarthy (Sarasota County), D. Addison (The Conservancy of Southwest Florida), W. Redfoot 

and L. Ehrhart (Univ. Central Florida), K. Williams (Caretta Research Project) and U.S.FWS – 

Savannah Coastal Refuges, M. Godfrey (North Carolina Wildlife Resources Commission), and J. 

Zurita. We also would like to thank the CMTTP contributors and the Archie Carr Center for Sea 

Turtle Research for providing data. 

We thank the following researchers for providing their data and/or unpublished reports to the 

TEWG for analysis of in-water catch data and size distributions: M. Bresette (FP&L), L. 

Ehrhart, W. Redfoot, and D. Bagley (Univ. Central Florida), Pearse Webster (SCMRD), J. 

Braun-McNeill (NMFS), K. Durham and R. DiGiovanni (Riverhead Foundation for Marine 

Research and Preservation). For sex ratio analyses, K. Blair, M. Godfrey, and C. Delgado 

provided access to data from their respective theses; J. Wyneken provided data from unpublished 

manuscripts. 

Thanks are due to Scott-Sherrill-Mix of Dalhousie University for analyzing the satellite 

telemetry datasets and providing us with the hex-bin figures. Finally, we would like to especially 

thank all of the satellite data contributors for their generosity in providing us with the raw data 

for this analysis: M. Arendt (South Carolina Department of Natural Resources), M. Dodd 

(Georgia Department of Natural Resources), J. Dittmar (National Aquarium), M. Coyne 

(seaturtle.org), M. Frick (Caretta Research Project), B. Godley (University of Exeter), M. 

Godfrey (NCWRD), D. Griffin (South Carolina Department of Natural Resources), K. Mansfield 

(Virginia Institute of Marine Science; University of Miami), C. McClellan (Duke University), S. 

Morreale (Cornell University), S. Murphy (SCDNR ret.), J. Musick (Virginia Institute of Marine 

Scienec), M. Nicholas (Gulf Islands National Sea Shore), T. Tucker (Mote Marine Lab), J. 

Williams (NOAA, Galveston). Their participation reflects a strong dedication among researchers 

to sea turtle conservation and management. 
89 

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108 

APPENDIX A. Sex Ratios of Stranded Turtles –Jeanette Wyneken 

The U.S. Sea Turtle Stranding and Salvage Network (STSSN) collects information on and 

documents strandings of marine turtles along the U.S. Atlantic and Gulf of Mexico coasts, and 

infrequently, from the U.S. Caribbean. The reliability, standardization, and magnitude of STSSN 

participation have increased since the early 1980s (the STSSN was formally established in 1980). 

The steepest increase in STSSN effort was likely between 1980 and 1985, though some increases 

in effort continued past 1985. Currently, the network encompasses the coastal areas of the 18 

states from Maine through Texas, and includes portions of the U.S. Caribbean. Data are 

compiled through the efforts of network participants who document marine turtle strandings in 

their respective areas and contribute those data to the centralized STSSN database (posted at 

http://www.sefsc.noaa.gov/seaturtleSTSSN.jsp). The database is composed primarily of 

strandings, including cold-stunned turtles, and also contains some reports of incidental captures 

and distressed turtles. The wide participation allowed the STSSN to accumulate approximately 

40,000 loggerhead records; only a small proportion of the records include the sex of the stranded 

animal. For our analyses, we did not include data from animals whose sex was listed as 

indeterminate or unknown. 

The gender of each turtle in the most inclusive data sets analyzed was based on one or more of 

the following criteria: 

(a) in adult sized animals, the tail including the cloacal opening extended beyond the caudal 

margin of the carapace (male) or the tail was short and the cloacal opening did not extend 

beyond the caudal-most carapace margin (female); 

(b) the turtle carcass was opened and reproductive organs inspected so gender was based on 

internal morphology; 

(c) if laparoscopy was performed on the turtle at an earlier stage and the gender was assigned, or 

(d) the turtle was tagged previously while nesting (mature females). 

In all cases we used in our analysis, the sex of the turtles analyzed was categorized as male (M) 

or female (F). We examined sex ratios in stranded turtles using several subsets from the STSSN 

database. First, we analyzed ~5,800 records from 1987 through 2004; data prior to 1987 were 

omitted because of variable effort in data collection and a lack of rigorous data-checking. We 

excluded any records for which species was coded as “probable” or “unsure.” Because nearly all 

records (99.99%) were from the continental U.S., we limited our analyses to this geographic 

range. We excluded records for which straight carapace length (SCL) > 120 cm or the curved 

carapace length (CCL) > 128.1 cm, because we were uncertain that these unusually large sizes 

were correct or were loggerheads. Because CCL was the more commonly reported metric, when 

necessary we converted all straight carapace lengths (SCL) into estimated CCL values using the 

morphometric relationships reported in Appendix B. 

Second, we analyzed data from 1998-2004. These records have undergone the most rigorous 

data checking. However, this time series is short and is less likely to detect temporal changes in 

stranding sex ratios. The sample sizes for different analyses varied depending on whether 

records contained all variables of interest. 

 
109 

Finally, we analyzed two additional subsets of the data designated as “verified sex”: all records 

of animals for which the sex of the carcass was verified from necropsy or by previous 

laparoscopy from (i) 1987-2004 and (ii) 1998-2004. They are smaller data subsets and are 

probably biased in excluding males because carcasses with a long tail are less likely to be 

necropsied. These data subsets do not include nesting females that died on the nesting beach. 

The sample sizes for different analyses varied depending on whether records contained all 

variables of interest. 

Below we defined several stage-identifying categorical variables to use in the sex ratio analysis 

of the strandings. The size distributions of the turtles in the categories are described by the 

median CCL in cm and the upper and lower 2.5th percentiles of the distribution of all turtles in 

the 1987-2004 data subset. The rational for the size cutoffs is discussed in the Life Stages 

section of this TEWG report. 

• Immatures: turtles with CCL >10 and ≤ 80 cm. The median size of these animals was 

67.1 cm CCL; the lower 2.5th percentile was 42.0 cm CCL and the upper 97.5th percentile 

was 79.2 cm CCL. 

• Mixed adults and immatures: turtles with CCL > 80 cm and ≤ 98.45. These data were 

excluded from analyses, except where all strandings in the time series subsets were 

considered regardless of stage. 

• Adults: turtles with CCL >98.45 cm, the mean size of putative first-time nesters (see 

Table 3 of this report). While this size class is mostly adults, we could not say 

unequivocally that a few large immature turtles might also be included in the subset. The 

median size of these animals was 102.2 cm CCL; the lower 2.5th percentile was 98.6 cm 

CCL and the upper 97.5th percentile was 109.0 cm CCL. 

• Large adults: turtles with CCL>109.3cm. The median size of these animals was 112.3 

cm CCL; the lower 2.5th percentile was 109.5 cm CCL and the upper 97.5th percentile was 

126.5 cm CCL. 

Because of the preponderance of moderately to strongly female-biased hatchling sex ratios 

(Tables 4 and 5 of this report), variations from a female bias by later stages are potentially 

informative about trends in size class related death rates. 

We compared sex ratios in strandings by latitude, state, and region and tested for differences 

using chi-square or Fisher-exact tests (α = 0.05). Regions were distinguished by climate, 

ecology, behavioral areas (e.g. areas where turtles are feeding vs. an area used for mating), gross 

fisheries similarities (e.g. TED regulations), or combinations of these. The Gulf of Mexico 

region (GoM) was defined as Florida’s west coast and the coastlines of Alabama, Mississippi, 

Louisiana, and Texas. The Southeast U.S. Atlantic region (SE) was defined as the Florida east 

coast through North Carolina, and the Northeast U.S. Atlantic region (NE) was defined as 

Virginia through Maine. The months of May through August were defined as the main nesting 

season. 

Using the stranding database within the limits defined above, we outlined a series of 

assumptions, framed questions and then formulated hypotheses to query the four data subsets for 

sex ratio information. We address these below. 
110 

Assumption: The strandings reflect the same trends in sex ratio as the live turtle assemblages 

from which they came. 

Question 1: What are the baseline sex ratios in the immature, adult and large adult strandings, 

respectively, and do they differ? 

Ho: Sex ratio does not differ between immature and mature turtles. 

We reject the null hypothesis that sex ratios within stranded loggerheads are the same in 

immature vs. either subset of mature turtles. The differences are manifested in each of the 4 

data subsets examined (Figure A-1, Table A-1). In all cases, about 70% of the immature turtles 

were females and the percent females decreased between the immature and the mature stages. 

These changes suggest that mortality rates and/or the probabilities of stranding are not uniform 

for both sexes by stage (length classes). Interestingly, the data category that most rigorously met 

the criteria for data checking and sex identification (1998-2004 verified sex) showed a lower 

percent females (proportionately more males) compared with the percentage characterizing 

immature stages in spite of its exclusion of some adult males. The much lower female sex ratios 

in the large adult categories probably underestimate the percentage of males in strandings (Table 

A-1) and point to sex specific changes in death rates (or stranding rates) with age, with the caveat 

that we are comparing samples that diver greatly in n. Sample sizes for immatures are one to 

two orders of magnitude greater than those for adult and large adult categories. 

The observed stage-specific sex ratio shifts in strandings may have a variety of nonexclusive 

explanations, including (i) there is sex-specific mortality so that the sex ratio changes from ~2:1 

to 1:1 or 1:2 with increasing age class, (ii) proportionately more males wash ashore once they 

reach adulthood than when they are immature, (iii) the likelihood that a carcass will be cast up on 

a beach (and thus observed by the stranding network) differ by age class and sex, (iv) there are 

sex-specific differences in distribution and risk of mortality by stage, and/or (vi) primary sex 

ratios shifted across time so that conditions that 3-8 decades ago produced the nearly even or 

male-biased sex ratios found in mature turtles that hatched 3-8 decades ago differ from those that 

produced the immature turtles sex ratios, which hatched 1-3 decades ago. 

We also note that there was a decrease in the percent female when adults and large adults sex 

ratios are compared in the data subsets that include both verified and unverified sex turtles. 

However, this difference in the two mature sizes was not significant when the verified sex data 

subsets were analyzed. 
111 

Figure A-1. Sex ratios of immature and mature loggerhead strandings by size category 

including all seasons and regions. Sex ratios differed between immature and mature size 

classes. Mature size classes (adults and large adults) did not differ from one another in sex 

ratios. Numbers over each bar are the number of female strandings in each category. Detailed 

data and analyses are found in Table A-1. 

0%

10%

20%

30%

40%

50%

60%

70%

80%

1987-2004 Verified Sex 

1987-2004

1998-2004 Verified Sex 

1998-2004

Sex Ratios as % F of All Size Classes 

Immatures

Adults

Lg Adults

1625 1602                             951                                 939

123                                                                     73

9

777                                                                     383                                          

76                                  11                                 

34                              

Table A-1. Sex ratios of all immature and mature loggerhead strandings in all seasons and 

regions. Parenthetical numbers are the number of strandings in each category. Comparisons of 

numbers if males and females were made by Chi-square tests for equal proportions (1 df). F = 

females; M = males; I = immatures; A = Adult; LgA = large adults 

Size classes % Females 

1987-2004 

% Females 

Verified Sex 

1987-2004 

% Females 

1998-2004 

% Females 

Verified Sex 

1998-2004 

Immatures 70.13% (2317) 70.20% (2282) 70.39% (1351) 70.55% (1331) 

Adults 49.74% (1562) 60.59% (203) 51.00% (751) 61.34% (119) 

Lg Adults 37.44% (203) 37.93% (18) 34.34% (99) 52.94% (17) 

Chi-Square 

FxMxIxA 

Χ2 = 165.0, 1 df, 

P < 0.001 

Χ2 = 8.11, 1 df, 

P = 0.004 

Χ2 73.8, 1 df, 

P < 0.001 

Χ2 = 4.39, 1 df, 

P = 0.036 

Chi-Square 

FxMxIxLgA 

Χ2 = 91.0, 1 df, 

P < 0.001 

Χ2 = 14.0, 1 df, 

P < 0.001 

Χ2 = 55.0, 1 df, 

P < 0.001 

Χ2 = 4.81, 1 df, 

P = 0.028 

Chi-Square 

FxMxAxLgA 

Χ2 = 11.8, 1 df, 

P = 0.001 

Χ2 = 0.002,1 df, 

P = 0.965 

Χ2 = 9.71, 1 df, 

P = 0.002 

Χ2 = 1.33, 1 df, 

P = 0.249 
112 

Assumption: Shifts in strandings sex ratios by stage, over time, can reflect losses of large 

proportions of reproductive turtles or of immature turtles from subsequent life stage categories . 

Question 2. Have sex ratios of stranded loggerheads changed over time. 

Ho: Sex ratios do not change with time within size classes. 

We considered the data for all regions together but calculated the sex ratios separately for the 4 

subsets of data. We tested the hypothesis separately within immature turtles, adults, and large 

adults over time, with counts of males and females parsed in three bins (1987-92, 1993-98, 1999-

2004). We compared sex ratios within stages using 3x2 Chi-square analyses or, where sample 

sizes were small, Fisher exact test (Table A-2, Figure A-2,). 

We were unable to reject the null hypothesis of no change in sex ratio from 1987-2004 within 

immatures and within either subset of mature turtles. When we restricted our analysis to only 

those records of verified sex data, we found similar results. We did not detect large changes in 

sex ratios over time in two sets of years surveyed. Because multiple year classes contribute to 

each stage class, and loggerhead turtles are late maturing animals, several more decades of 

sufficient data collection will be needed to detect sex ratio shifts over time and only if such a 

shift persists for a biologically sufficient period to resolve such changes. 

Table A-2. Sex ratios as percent of females by stage over time. Comparisons were made of 

male and female counts by stage and time bin. Numbers of total stranding in each category are 

given parenthetically. There were no differences in sex ratio over time within the immatures and 

within adults. 

Size classes 1987- 

1992 

1993 

1998 

1999-

2004 

1987- 1992 

Verified 

Sex 

1993-1998 

Verified 

Sex 

1999-2004 

Verified 

Sex 

Immatures 71.9 % 

(392) 

67.6% 

(749) 

71.2% 

(1176)

71.9% 

(384) 

67.6% 

(740) 

71.3% 

(1158) 

Χ2 = 3.62, 2 df, P=0.164 Χ2 = 3.67, 2 df, P = 0.159 ns 

Adults 50.8 % 

(390) 

49.3% 

(513) 

49.5% 

(659) 

55.6% 

(26) 

65.5% 

(58) 

59.6% 

(109) 

Χ2 = 0.22, 2 df, P=0.895 Χ2 = 1.01, 2 df, P = 0.602 ns 

Lg Adults 46.5 % 

(43) 

38.0% 

(71) 

32.6% 

(89) 

16.7% 

(6) 

33.3% 

(6) 

47.0% 

(17) 

Χ2 = 2.42, 2 df, P=0.229 Fisher Exact Prob = 2 df, P = 0.063 ns 
113 

Figure A-2. Sex ratios as percent of females by stage over time. Comparisons were made of 

male and female strandings across time bins by stages. No significant differences were found 

within size classes in any of the data subsets. Numbers over, or in, each bar are the number of 

female strandings in each category. Details of the analyses and samples are found in Table A-2. 

282 506 837 276 500 826

0

10

20

30

40

50

60

70

80

1987-1992

% Female

1993-1998

% Female

1999-2004

% Female

1987-1992

% Verified

Female

1993-1998

% Verified

Female

1999-2004

% Verified

Female

Percent Female

Immature

Adult

Lg Adult

198 253 326 

 38 

20 

65 

20 

27 

29 

1 

2 

 8 

Assumption: If stage-specific turtle mortality is uniform across time for large areas, then sex 

ratios should remain relatively constant. Deviations in sex ratio by regions could identify high 

risk and low risk areas. We explored regional sex ratios for the Northeast U.S., Southeast U.S. 

and Gulf of Mexico) with all seasons were considered together. 

Question 3. Are there high risk vs. low risk regions of coast? 

Ho: Sex ratios of the three size classes are similar across regions. 

We failed to reject the null hypotheses that sex ratios were similar across regions within all 

immature turtles, adults of verified sex, and all large adults; (Figures A-3a, A-3b, Table A-3) but 

reject the null hypothesis when adults from the 1987-2004 and 1998-2004 subsets were 

compared across regions (Figures A-3c, A-3d, Table A-3). While the sex ratios of immature 

turtles were female-biased in all regions, the sex ratios of mature turtles tended to be even or 

slightly male biased across most regions. We note that our analyses failed to detect the predicted 

mature female bias in any region in spite of a known lack of adult male necropsies. Within the 

adults, proportionally fewer females stranded in the Gulf of Mexico than along in the southeast 

Atlantic coastline (Figures A-3a, A-3b, Table A-3). No sex ratio differences were detected in the 
114 

Verified Sex subsets, with the caveat that the adult sample sizes for the Northern and Gulf of 

Mexico regions are small and probably lack sufficient resolution. 

Figures A-3a and A-3b. Sex ratios by stage and region across all seasons based on 1987-

2004 verified and 1998-2004 verified sex subsets. Numbers over the bars are total females by 

category. Northeast region strandings occurred north of the North Carolina-Virginia state lines. 

Southeast strandings occurred between North Carolina and Florida’s east coast, and Gulf of 

Mexico (GoM) turtles were defined as those stranding along Florida’s west coast through the 

coasts of Alabama, Mississippi, Louisiana, and Texas. There were no differences across regions 

in the sex ratios by size class. Sex ratios shifted from strongly female biased immature turtles to 

moderately female biased adults and male biased large adults. Table A-3 details the analyses. 

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

GoM Southeast Northeast

1987‐2004 Verified Sex Strandings by Region

Immatures

Adults

Lg. Adults

483

284                                     

835

71                                           26

26                                     

5

5

1                                              

0%

10%

20%

30%

40%

50%

60%

70%

80%

GoM Southeast Northeast

1998‐2004 Verified Sex Strandings by Region

Immatures

Adults

Lg. Adults

153

477   37                                   309  

21

15        

1                                                                                                    5

3                                                     
115 

Figures A-3c and A-3d. Sex ratios by region across the three size categories for 1987-2006 

and 1998-2004 subsets. The only significant differences among regions in sex ratios by size 

class were in the Adult stages of the verified sex subsets (Table A-3). Those differences may 

reflect different sources of mortality by regions (for example various TED implementations in 

the GoM vs. the Southeast and Northeast U.S.). The immature turtle strandings sex ratio in the 

Southeast U.S. is less strongly female biased that in the GoM or the Northeast; the empirical data 

to explain this difference. Sex ratios in GoM large adults are not informative because of small 

numbers. Data groupings, format and comparisons are described in Figure A-3a. 

0%

20%

40%

60%

80%

100%

GoM Southeast Northeast

1987‐2004 Strandings by Region

Immatures

Adults

Lg. Adults

288                                            845                                               492

503                                            

70

204                                                                                                             12

44                                          

1                                                                                       

0%

10%

20%

30%

40%

50%

60%

70%

80%

GoM Southeast Northeast

1998‐2004 Strandings by Region

Immatures

Adults

Lg. Adults

155                                                                                                

108                                                  6

225

\

50

11

108                                                                                                               

17

6                                       
116 

Table A-3. Sex ratios of loggerhead strandings by stage and region as described above. 

The 3x2 Chi-square or Fisher Exact test analyses were run within a stage for each of the 4 data 

subsets. 

Stage by Region % Females 

1987-2004 

% Females 

1987-2004 

Verified Sex 

% Females 

1998-2004 

% Females 

1998-2004 

Verified Sex 

Northeast immature 71.82 (685) 71.88 (672) 70.40 (446) 70.39 (439) 

Southeast immature 68.48 (1234) 68.56 (1218) 69.35 (695) 69.53 (686) 

GoM immature 72.36 (398) 72.45 (392) 73.81 (210) 74.27 (206) 

Χ2 = 2.62, 2 df, 

P=0.27, ns 

Χ2 = 3.42, 2 

df, P=0.180, 

ns 

Χ2 = 1.54, 2 

df, P=0.464, 

ns 

Χ2 = 1.72, 2 

df, P=0.423, 

ns 

Northeast adult 49.65 (141) 60.47 (43) 47.62 (105) 56.76 (37) 

Southeast adult 56.73 (911) 61.21 (116) 60.98 (369) 68.52 (54) 

GoM adult 40.00 (508) 59.09 (44) 38.99 (277) 53.57 (28) 

Χ2 = 30.3, 2 df, 

P<0.001 

Χ2 = 2.73, 2 

df, P=0.255, 

ns 

Χ2 = 31.20, 2 

df, P<0.001 

Χ2 = 2.21, 2 

df, P=0.3.32, 

ns 

Northeast large adult 40.00 (30) 45.45 (11) 40.74 (27) 50.00 (10) 

Southeast large adult 15.79 (108) 35.71 (14) 38.64 (44) 42.86 (7) 

GoM large adult 16.67 (6) 25.00 (4) 21.43 (28) 50.00 (2) 

Χ2 = 1.38, 2 df, 

P=0.502, ns 

Fisher Exact 

Prob. =0.10 ns

Χ2 = 2.92, 2 

df, P=0.232, 

ns 

Fisher Exact 

Prob. =0.20 ns

Assumptions and background: Because mortality risks in nearshore coastal waters may vary by 

location, we grouped states in which the turtles’ natural history is likely to be the most similar 

and whose waters shared similarity in TED regulations in the past. Our groupings of states 

ignored coastline length and are based on large scale differences in ecology, many of which 

reflect seasonal changes: (i) the Northeast (NE) states (Maine through Virginia) that have turtles 

in their near coastal waters to feed during warmer water months but do not host significant 

nesting; those turtles migrate away when temperatures cool and day lengths shorten; (ii) Turtles 

utilize the nearshore waters off North Carolina through Georgia, and some breeding and nesting 

occurs on their shores; the subpopulation differs from that nesting on the east and southwest 

coasts of Florida. Like those loggerheads in NE states, they tend to leave the nearshore waters in 

the fall and winter, except in Raleigh Bay (Epperly et al. 1995); (iii) Florida’s Atlantic coast and 

nearshore waters host significant feeding, breeding and nesting; turtles reside in its coastal waters 

year round, and much of the coastal environment is influenced by the Gulf Stream current and its 

eddies; (iv) Florida’s West coast, and the coasts of the Florida Panhandle, Mississippi, and 

Alabama and the nearshore waters are treated as part of the eastern Gulf of Mexico coast which 

hosts feeding and some significant nesting in the southwestern Florida; nesting elsewhere is 

limited. Fewer turtles reside in the shallow, coastal waters of the eastern Gulf during cooler 

months, and the coastal environment is somewhat more temperate, at least to the north; (v) States 

bordering the Western of the Gulf of Mexico (Louisiana, and Texas) do not host significant 
117 

nesting numbers of loggerhead turtles, but turtles use their nearshore waters seasonally. Until 

2003, TED regulations differed between the Atlantic and Gulf regions, with smaller escape 

openings allowed in the Gulf of Mexico. As of August 2003 the regulations were similar and 

both areas are required to use openings much larger than required in the past. There were no 

TED requirements in the Northeast U.S. until 1992 when the summer flounder fishery was 

required to use TEDs, but only as far north as Cape Charles, Virginia. Note also that until 1994, 

the TED regulations for the shrimp fishery were seasonal and that tow times were allowed to be 

used in lieu of TEDs in inshore waters; as of December 1992 TEDs were required at all times in 

all areas for the shrimp fishery (Epperly 2003). 

Questions 4: Are there shifts in sex ratio found at scales that integrate both natural history and 

management-specific mortality risks? 

Ho: Sex ratios do not vary by regions in which loggerheads share similar natural history and 

TED history. 

We rejected the null hypothesis that strandings shared similar sex ratio across ecologically 

similar state-groups in our examinations of both large data subsets, and failed to reject the null 

hypothesis when we tested the two verified sex data subsets. The significant differences were 

found in the adult sizes (Table A-4). 

The 1987-2007 and 1998-2004 Verified Sex subset showed different trends (Tables A-4) than 

the other subsets. That implies that either the assignments of sex for the turtles which were not 

necropsied are highly prone to error, or that the verified sex datasets are biased in some ways 

other than what is found in the unverified subsets. Using the Verified sex data subsets (datasets 

that are presumed to underestimate mature males), we found female bias is common in all stategroups. The absolute number of stranded female turtles shows that there is significant female 

mortality that removes future recruits and mature turtles from the population at all locations. 

Strandings from locations where adult and large adult turtles share grossly similar ecology 

tended to differ in sex ratio. For example, Florida Atlantic and Gulf coasts strandings tended to 

suggest either coast-specific differences in the standing stock sex ratios, the sex-specific 

mortality differed in rates on the two coasts, or some combination of these factors. The sex 

ratios tended to be slightly female-biased or not biased in sex ratios on the Atlantic coast but 

show male bias on the Gulf coast based on the two larger data subsets. 

Because many more immature than mature turtles are found in all the data subsets, the sex ratios 

are driven by those immature turtles. The 1987-2007 shows ~1:1 sex ratios along Florida’s 

Atlantic coast and male biased sex ratio along the northeastern Gulf of Mexico coast (Tables A4). Elsewhere the trend is for sex ratios to be moderately female biased. These subsets likely 

include immature males that were not necropsied and that may be misidentified as females in all 

samples, it is possible that female biases are somewhat less than what we detected. Thus, in this 

analysis the strandings data may underestimate male presence in nearshore waters. 
118 

Table A-4. Sex ratios of all stranded loggerhead turtles (all stages combined) as percent 

female across all seasons, by state groups. Chi-square (2 x 5, 4 df) comparisons were made 

among state groups comparing numbers of males and females in each state-group. Expected 

numbers were based upon standard rows and columns calculations and did not for a 1:1 

expectation.

State-groups: Northeast 

States: 

MaineVirginia 

North 

Carolina – 

Georgia 

Florida 

Atlantic 

Eastern Gulf 

of Mexico 

Western Gulf 

of Mexico 

1987-2004 70.90% 

(1066) 

64.44% 

(2013) 

54.47% 

(1202) 

42.74% (1088) 65.21% (470) 

 X2=130.0, 4df, p<0.001 

71.99% (714) 67.37% 

(1143) 

68.78% 

(205) 

1987-2004 66.38% (116) 71.34% (328) 

Verified Sex 

 X2

=5.56, 4df, P=0.23 

1998-2004 64.88% (578) 67.43% 

(832) 

59.06% 

(276) 

43.06% (360) 73.55% (155) 

 X2=77.2, 4 df, p <0.001 

68.93% (486) 69.81% 

(636) 

65.77% 

(111) 

1998-2004 68.29% (82) 73.38% (154) 

Verified Sex 

 X2

=1.98 4df, p=0.74, ns 

Assumption: Theoretically, the percentage of adult females should increase during breeding 

season along shorelines that serve as major rookeries. Because mating precedes nesting, we also 

expect that adult males may increase in proportion in these same waters just before or early in 

the nesting season. Mating is often a high-risk activity and strandings of both sexes should 

increase during nesting season. This assumption was supported by comparison of strandings 

numbers during the nesting and non-nesting seasons (Table A-5a, and A-5b). 

Question 5. Do sex ratios of strandings differ between breeding (nesting) and non-breeding 

(non-nesting) seasons? 

Ho: Strandings sex ratios do not differ between breeding and nonbreeding seasons. 

We compared sex ratios of strandings during nesting and non-nesting seasons. First we 

compared the groupings of strandings used in Table A-4 and next, to explore nesting beach 

effects more specifically, we separately grouped strandings sex ratios by shoreline regions with 

significant nesting vs. those with little or no nesting and tested the null hypothesis by shoreline. 

(i) We rejected the null hypothesis of similar sex ratios across all shorelines during the nesting 

(May – September) and non-nesting (October–April) seasons. Based on the 1987-2004 data, the 

strandings numbers tended change between nesting season and non-nesting seasons, and the sex 

ratios were not uniform among shoreline groups in which the turtles should share similar 
119 

behavior within either the nesting season or outside of it (Table A-5a); this difference was 

largely driven by a shift to a stronger female bias in southeastern Florida. We then compared sex 

ratios between nesting and non-nesting seasons using the within regions 1987-2004 Verified Sex 

totals. We could not draw the same conclusion as we found no overall shifting sex ratio between 

nesting and non-nesting seasons (Table A-5b). 

Shoreline-specific comparisons: Data were split into numbers of nesting and non-nesting season 

strandings and were compared along shorelines that hosted appreciable nesting and shores that 

did not. This set of comparisons addressed the assumption that breeding season affects behavior 

and so could subject turtles to differing mortality risks. We examined sex ratio of strandings of 

all size classes grouped in order to explore the data for shoreline aggregations represented by all 

size classes and then we also analyzed the available data subsets for each size (or stage) class. 

(ii) We rejected the null hypothesis that strandings sex ratios do not differ between breeding and 

nonbreeding seasons when we analyzed the 1987-2004 data set (Table A-5c). We found that sex 

ratios shifted from female-biased during the nesting season to male-biased outside of the nesting 

season in regions that host loggerhead nesting. When we analyzed the other three data subsets, 

no significant differences were found and the null hypothesis could not be rejected. 

In all data subsets, the numbers of females were highest in the nesting season, but the generally 

female-biased sex ratios differed little between nesting and non-nesting seasons. Because 

immature turtles stranding tend to be the most numerous of all size classes, they most influenced 

sex ratio trends. These immature sizes are not known to migrate to waters off nesting beaches. 

We found that in most cases there were no differences in sex ratios between nesting and nonnesting seasons (Tables A-5c-d). Based on the 1987-2004 subset we cannot reject the null 

hypothesis. The notable exceptions in which we reject the null hypothesis are when we examined 

adult sex ratios for turtles stranding on nesting beaches. During nesting season the sex ratio was 

usually female biased along shores that host nesting while nesting tended to be male biased 

during the non-nesting season for the same areas. The large adult sex ratios tended to be male 

biased (Tables A-5d), perhaps implying that the largest turtles tend to be males. 

When we restricted our comparisons of strandings sex ratios in the nesting and non-nesting 

seasons and regions using the most rigorously data-checked subset (1998-2004 verified sex) and 

again tested the null hypothesis. We found no significant changes in sex ratios between seasons 

in either region (Tables A-5c). 
120 

Table A-5a. Strandings sex ratios (1987-2004) during the nesting and non-nesting season

by regions as outlined in Tables A-4. SFla: Florida Atlantic coast; CG: (Carolinas and Georgia); 

NE: Northeast States; GoM East: Eastern Gulf of Mexico; GoM West: Western Gulf of Mexico; 

ns: not significant.. All size classes are combined. Total strandings by shoreline groups are given 

in columns 2 and 3. A Chi-Square comparisons of standing numbers by nesting and non-nesting 

season is given in the bottom row. Comparisons in numbers of males and females by nesting and 

non-nesting season are compared by Chi-Square tests summarized in the last column. 

 

Strandings 

by 

Shoreline 

Groups 

NonNesting 

Season 

Nesting 

Season 

N Females 

NonNesting 

Season 

Males 

NonNesting 

Season 

Females 

Nesting 

Season 

Males 

Nesting 

Season 

Chi-Square, 

df, p 

SFla 331 336 667 156 175 214 122 

18.5, 1 df, 

p <0.001 

GoM East 346 278 624 142 204 126 152 

1.15, 1 df, 

p=0.283 ns 

GoM West 214 120 334 149 65 89 31 

0.77, 1 df, 

p <0.379 ns 

CG 400 1186 1586 249 151 773 413 

0.03, 1 df, 

 p =0.85 ns 

NE 265 606 871 180 85 400 206 

0.31, 1 df, 

p=0.58 ns 

Totals 1556 2526 4082 876 680 1602 924 

20.51, 1df, 

p <0.001 

 Chi Sq = 346.0, 4 df, p ,<0.001 

Table A-5b. Strandings sex ratios assessed in the 1987-2004 verified-sex data subset; 

regions as outlined in Tables A-4. All size classes are combined. Format as in Table A-5a 

Strandings 

by 

Shoreline 

Groups 

Nonnesting 

Season 

Nesting 

Season 

N Females 

Nonnesting 

Season 

Males 

Nonnesting 

Season 

Females 

Nesting 

Season 

Males 

Nesting 

Season 

Chi Sq, df, 

p 

SFla 122 83 205 79 43 62 21 

1.84, 1 df, 

p =0.175 ns 

GoM East 162 53 215 116 46 36 17 

23.59, 1 df, 

p <0.001 

GoM West 207 118 325 145 62 89 29 

0.83, 1 df, 

p=0.36 ns 

CG 197 845 1042 123 74 572 273 

1.76, 1 df, 

p=0.18 ns 

NE 208 518 726 149 59 365 153 

0.05, 1 df, 

p =0.82 ns 

Totals 896 1617 2513 612 284 1124 493 

0.34, 1 df, 

p =0.56 ns 

 Chi Sq: 453.0, 4 df, p<0.001 
121 

Table A-5c. Comparisons of sex ratios in strandings between nesting and non-nesting 

season on shoreline with and without appreciable nesting. All size classes are combined. 

Strandings for each state were combined for the states that hosted significant nesting and 

separately combined for states without significant nesting. Parenthetical numbers are the total 

numbers of strandings by category. Chi-Square comparisons were made using stranding 

numbers, not percentages. 

Nesting Shoreline 

Nesting Season

Nesting Shoreline 

Non-nesting Season

Chi-Square 

1987-2004 59.00% (2610) 45.58% (1673) X2=35.5, 1 df, 

p <0.001 

1987-2004 

Verified Sex 

68.94% (1201) 66.77% (641) ns 

1998-2004 70.90% (653) 68.11% (370) ns 

1998-2004 

Verified Sex 

54.43% (660) 58.43% (372) ns 

Nonnesting Shoreline 

Nesting Season 

Nonnesting Shoreline 

Non-nesting Season

Chi-Square 

1987-2004 66.67% (930) 70.50% (617) ns 

1987-2004 

Verified Sex 

70.51% (790) 72.76% (525) ns 

1998-2004 70.68% (556) 69.96% (253) ns 

1998-2004 

Verified Sex 

45.88% (561) 41.57% (258) ns 
122 

Table A-5d. Comparisons of strandings sex ratios by size class across nesting vs. nonnesting season at shorelines with and without appreciable nesting. Parenthetical numbers are 

the total strandings by category. Comb. Stages reflect the immatures, adults and large adults 

together. Comparisons of 1998-2004 verified sex by stage were limited to total strandings 

because a detailed breakdown was not available. 

1987-2004 Nesting Season Non-nesting Season Chi-Square

Shorelines with Nesting

Immatures 69.13% (881) 68.94% (425) ns 

Adults 56.74% (816) 39.42% (586) 40.9, 1 df, p <0.001 

Large adults 36.73% (98) 35.59% (59) ns 

Comb. stages 61.73% (1795) 50.93% (1070) 35.3, 1 df, P < 0.001 

Shoreline without Nesting

Immatures 71.69% (604) 71.96% (403) ns 

Adults 49.06% (106) 57.41% (54) ns 

Large adults 42.86% (21) 40.00% (25) ns 

Comb. stages 67.58% (731) 68.67% (482) ns 

1987-2004 Verified Sex

Shorelines with Nesting

Immatures 68.46% (837) 66.79% (280) ns 

Adults 71.25% (80) 38.89% (36) 11.0, 1 df, P < 0.001 

Large adults 36.36% (11) 25.00% (4) ns 

Comb. stages 68.32% (928) 63.32% (347) ns 

Shoreline without Nesting

Immatures 72.52% (626) 72.12% (538) ns 

Adults 60.00% (55) 59.38% (32) ns 

Large adults 37.50% (6) 42.86% (7) ns 

Comb. stages 70.83% (672) 71.06% (577) ns 

1998-2004 

Shorelines with Nesting 

Immatures 70.89% (474) 68.91% (178) ns 

Adults 66.67% (57) 50.00% (22) Fisher Exact test p = 0.059 

Large adults 42.86% (5) 50.00% (2) ns 

Comb. stages 70.07% (538) 67.35% (202) ns 

Shoreline without Nesting

Immatures 71.60% (412) 69.66% (267) ns 

Adults 67.74% (31) 33.33% (9) ns 

Large adults 40.00% (5) 60.00% (5) ns 

Comb. stages 70.98% (448) 67.71% (281) ns 

1998-2004 Verified Sex 

Shorelines with Nesting

All stages 54.12% (660) 58.43% (372) ns 

Shoreline without Nesting

All stages 45.88% (561) 41.57% (258) ns 
123 

While the breeding season, per se, should not attract immature turtles to nesting areas, some of 

the same environmental factors associated with the onset of breeding seasons also trigger other 

kinds of turtle migrations (e.g. feeding migrations, seasonal warming of temperate waters, and 

transit through breeding areas by immature as well nonbreeding mature turtles). Changes 

including day length and water temperature are associated with feeding migrations of immature 

loggerheads shoreward from the edges of the Gulf Stream and coastal migrations to and from 

summer feeding grounds. 

Interestingly, the numbers of adult male turtles stranding tend to be high, in spite of perceived 

sampling biases that should produce female biased sex ratios (because adult males are often 

excluded from necropsy). The observed trend in the strandings data probably reflects differences 

in the behavior of the sexes and their vulnerabilities. For example, while males and females are 

both attracted to coastlines that host nesting, the females go to the site because it is appropriate 

and safe for nesting. While mating occurs along the coastline near nesting beaches, it could 

theoretically occur elsewhere. In contrast, males arrive in these waters to intercept females and 

mate. The male-biased sex ratios or less-pronounced female bias undoubtedly includes the 

impacts of the greater risks males face while mating and searching for mates (e.g. boat strikes, 

predation, attack and injury by other male turtles). Males are not particularly maneuverable 

when mating and tend to be closer to the surface and vulnerable to boat strikes when mating. 

The importance of these sex ratio changes with class provide clues to change, but we lack 

sufficient understanding of sampling biases to link those changes to production directly. 

If we accept the assumption that these data subsets accurately reflect the sex ratio trends for the 

stranded turtles during breeding and nonbreeding seasons, then increases in stranding numbers 

during nesting season (which includes both large numbers of immature turtles and adult turtles) 

contributes losses in potential productivity. It is the trends in changes in the sex ratios between 

the immature and adult size classes that herald such. The roughly 65-70% female-bias found in 

the immature turtles tends be of lesser magnitude in the adult stage subsamples (or in some 

subsamples, shifts to male bias). The loss of recruits to the adult stages and loss of mature turtles 

from important rookeries during the breeding season should be considered as particularly 

important source of lost of productivity. 

Among the potential indicators of shifts in life history is change in size of sexually mature 

animals. In declining populations, for which breeding sites are not limiting, breeding may 

commence at a smaller size than in previous generations. 

Question 6. Is there any indication of a shift or shifts in the sizes of stranded mature animals 

(e.g., “Adults”)? 

Ho: There is no detectable change in the sizes of stranded adult loggerheads between 1987 and 

2004. 

We failed to reject the null hypothesis. While our size cutoffs may have excluded the very 

smallest individuals and undoubtedly missed some smaller but mature animals, we found no 

significant shift in the median sizes of either sex of stranded adult loggerheads (Table A-6). We 
124 

note that it is possible that the time range covered may not be sufficient to detect selection for 

breeding at a smaller size. 

Table A-6. Sizes of stranded turtles over time. F is female, M is male, FV and MV are 

females and males verified through necropsy or other confirming data. 

Median Min Max N Years Sex 

102.60 98.50 127.00 302 1987-95 F 

102.85 98.50 127.42 416 1996-2004 F 

103.50 98.50 128.00 318 1987-95 M 

104.00 98.50 127.00 497 1996-2004 M 

101.80 98.60 114.00 36 1987-95 FV 

103.00 98.50 123.00 98 1996-2004 FV 

103.00 98.50 119.00 38 1987-95 MV 

104.90 98.60 122.00 60 1996-2004 MV 

Conclusions 

Our understanding of loggerhead sex ratios remains rudimentary despite nearly 25 years of 

study. From the egg to the reproductive adult, the sources of sex ratio variation and their 

implications are still poorly understood. The physiological mechanisms that select which signals 

direct embryonic gonads to be male or female are not yet understood. Temperature interacts 

with the embryo, but the mechanisms of how temperature directs sex and what other factors 

modify sex determination are still key unanswered questions. How much loggerhead sex ratios 

vary spatially and temporally has not been addressed systematically or across sufficient numbers 

of years to establish a measure of variability. Such measures are necessary baselines. 

How and why sex ratios differ among hatchlings, immature stages, and adult turtles remain 

intriguing. The contributions of mixed stocks and multiple year classes undoubtedly dampen 

oscillations is sex ratios, but also make it challenging to recognize if sex ratios of different 

cohorts have changed. Understanding the mating systems of loggerheads from the physiological, 

behavioral, and ecological perspectives are key to understanding how changes in populations and 

sex ratios may impact productivity. Yet, we know little of the details of loggerhead mating 

systems. 

Based on strandings data, the lack of female bias in mature sized turtles across analyses is worth 

noting and may reflect long-term reductions or losses of females from the population. However, 

we cannot rule out other explanations including sex-specific differences in remigration intervals 

and distributions or the possibility of sex-specific vulnerabilities. 

Strandings sex ratio data remain intriguing and in some cases alarming, particularly in the 

absolute numbers and proportions of adult females lost from the breeding population. Immature, 

adult, and large adult sex ratios all reflect the integration of many year classes. Hence, 

discerning the causes(s) of the shift away from a strong female bias in the older (adult or large 
125 

adult) stages cannot be specifically interpreted without further data such as necropsy results or 

better understanding of sex-specific movements and risks. However, one can hypothesize that 

because of the large numbers of immature females that strand in all regions, there is loss in 

recruitment to reproductive stages that we are now detecting in the strandings. We cannot 

discount the possibility that the high proportion of stranded immature turtles reflects losses of 

large proportions of females from mixed stocks that feed in or migrate through U.S. coastal 

waters. There is evidence for sex-specific dispersal differences of immature turtles (Casale et al. 

2002 using Mediterranean strandings, Dellinger 2007 for wild-caught immature turtles in the 

eastern Atlantic), however, differences in behavior, while a possible explanation, cannot be 

tested with the strandings data base in the absence of stock assignments. 
126 

APPENDIX B Description of Loggerhead Morphometric Relationships –Heather Haas

Sea turtle researchers do not always obtain the same suite of morphometric measurements, and 

even in cases when they do, some measurements may have missing or erroneous data. Hence, it 

is useful to be able to use one morphometric measurement to convert to another. There are 

several well-documented loggerhead morphometric analyses (Frazer and Ehrhart 1983; Teas 

1993; Coles 1999; Epperly and Teas 2002; Byrd et al. 2005). Although these studies are very 

useful for specific purposes, each is limited in spatial extent, size classes represented, sample 

size, or morphometric measurements considered. In this analysis, we create a dataset with broad 

spatial extent, wide representation of size classes, and a large sample size in order to 

parameterize equations to describe the relationship between all the typical carapace 

measurements of loggerhead sea turtles. 

Data Sources

We compiled morphometric information (Table B1) from over 11 thousand loggerhead sea 

turtles. We deleted all records with a measurement of zero because we assume these were used 

to represent missing data rather than true zeroes. Potential outliers were not removed unless 

directly suggested by the data suppliers (as described below). The final dataset that was used in 

the morphometric analysis contained records from the following sources: Sea Turtle Stranding 

and Salvage Network (STSSN, n=6602), Northeast Fisheries Observer Program (NEFOP, 

n=297), SEFSC in-water research in North Carolina (n=3253), SEFSC sea turtle life history 

database (n=544), Casey Key and Manasota Key nesting data (n=241), and Keeywadin Island 

nesting data (n=81)(See Part I of this report for information on the nesting data). Although the 

full dataset contains loggerheads from a wide range of size classes (CCLstd ranged from less than 

10 cm to greater than 110 cm), the majority of the turtles had CCLstd measurements between 60 

and 80 cm (90% between 50.8 and 101.4 cm, and 50% between 62.2 and 78.5 cm). 

STSSN 

The United States Sea Turtle Stranding and Salvage Network (STSSN, 

http://www.sefsc.noaa.gov/seaturtleSTSSN.jsp) supplied morphometric information from 

stranded loggerhead sea turtles along the U.S. Gulf of Mexico and Atlantic coasts from 1987 

through 2005. The data were supplied by STSSN coordinator, Wendy Teas, and the following 

data quality controls were implemented. We used only those records from the Gulf, Northeast, 

and Southeast regions with the highest reliability code. We only used records from 1987 onward 

because stranding data prior to 1987 were not ever verified or edit-checked. Only live and fresh 

dead loggerheads were included so that turtles with bloating or other decomposition processes 

would not bias the results. At the suggestion of STSSN coordinator, we deleted curved carapace 

length measurements (CCL) over 128.1 cm and straight carapace length measurements (SCL) 

over 120.0 cm. 

NEFOP 

We obtained morphometric data for loggerhead turtles from the Northeast Fisheries Observer 

Program (NEFOP) of the Northeast Fisheries Science Center (NEFSC). The data were obtained 

from turtles bycaught in commercial fisheries from 1990-2007 from Maine through North 

Carolina. Loggerheads that were described as “Dead, Condition Unknown”, “Dead, Moderately 
127 

Decomposed”, “Dead, Severely Decomposed”, or “Dead, Seen by Capt/Crew Only” were not 

included in the dataset. 

Nesting: 

We used data from loggerheads nesting at Casey Key and Manasota Key (2002-2006) and 

Keeywadin Island (2002-2005). As a quality-control measure, we deleted all CCL 

measurements (notch to notch and notch to tip) that were less than 70 cm. Both of these datasets 

are described elsewhere in this TEWG document. 

North Carolina 

We used data from SEFSC Beaufort Laboratory from their North Carolina in-water work, 1986-

2006 (J. Braun-McNeill pers. comm.). 

SEFSC 

We obtained morphometric data for loggerhead turtles from the Southeast Fisheries Science 

Center (SEFSC) sea turtle life history database, 1999-2007 (L. Stokes pers. comm.). The 

primary source of turtles is from their observer database for Highly Migratory Species programs, 

but other sources include animals from their pelagic longline experiments, shark observer 

programs (bottom longline and drift gill net), resource assessment cruises (NOAA vessels), and 

more recently, reef fish observer program. Our database does not include records from the 

SEFSC shrimp observer program because they do not record multiple size measurements per 

turtle. 

Analytic Approach

Because we wanted to use the simplest model that was statistically appropriate, we started the 

modeling process with a simple model to estimate one morphometric measurement from another, 

and we iteratively explored whether more complex models were necessary were was a more 

uniform distribution of observations across size-classes, whether to transform the raw data, and 

whether to use model II regression techniques (to address measurement error). Rather than 

revisiting these issues for every pair of morphometric variables, we chose to explore these issues 

using CCW (as Y) and CCLstd (as X) because these were the two variables with the most number 

of observations. We ultimately decided to use a very simple approach of Model I (simple linear) 

regression techniques with no intercept term and unfiltered and untransformed data. 

We chose a regression model with no-intercept term because this simple model appears to be 

theoretically justified. A model with no intercept term (where the intercept is set to zero) is 

theoretically justified when one morphometric measurement is zero the corresponding 

measurements should also be zero. There is no reasonable biological scenario where a turtle 

would have a CCL of zero and a positive value for CCW. To explore whether a model with no 

intercept term is empirically justified in addition to being theoretically justified, we performed 

simple linear regression analysis with and without an intercept term. Although the model with 

the intercept has a lower AIC value and an intercept parameter estimate that was statistically 

different than zero, we were concerned that this model was biased high for smaller turtles (< 40 

cm CCL). We compared the average residual value at sizes related to the transition between 

Stage I (15 cm, no intercept = 0.5, intercept = -3.6), the division between Stage II and Stage IV 

at the peak of Stage III (63 cm, no intercept = 1.5, intercept = 0.7) and the division between 
128 

Stage III and Stage V at the peak of Stage 4 (82 cm, no intercept = -0.4, intercept = 0.1). The 

maximum residual value for both models was similar (~ 24 cm). We decided against using the 

intercept model because it had larger residual values at smaller sizes, which likely exceed 

measurement error. The no intercept model had average residual values that are likely close to 

or within measurement error. We strongly caution that none of these models should be used 

outside of the range of our data (Figure B1), especially at the lower end. The no-intercept model 

assumes the relationship between the lowest observed values and zero are the same as in the rest 

of the dataset, and we can not address this assumption given our data. Hence, these models 

should generally not be applied to loggerheads less than about 15 cm CCLstd. 

We chose to keep all data rather than remove (filter) data in order to obtain a more uniform 

distribution of observations across size-classes. Filtering data would be justified if the risk of 

bias due to uneven distribution of samples across size classes outweighs the risks associated with 

reducing the sample size and disregarding potentially useful data. We explored these issues by 

creating a heavily filtered dataset (with approximately a tenth of the original observations and a 

nearly uniform distribution of observations across size classes), and we then compared 

regression diagnostics and results between the filtered and unfiltered data when using CCLstd to 

estimate CCW. 

Filtering the data does not appear to be necessary. Based on plots of raw data and residuals from 

the regression analyses, there was no evidence that the relationship between CCW and CCLstd

changes across size classes or is unduly influenced by a particular size class. Even a drastic 

reduction in sample size (keeping only about a tenth of the data) only slightly changed the slope 

of the regression line (full dataset = 0.9341; filtered dataset = 0.9257) and the R2 values (full 

dataset = 0.9974; filtered dataset = 0.9969). If we filtered the data rather than using the full 

dataset, our estimates of CCW from CCLstd would only differ by about 1%, which is likely inside 

of the range of possible measurement error and not biologically significant for the purposes of 

most sea turtle researchers. Hence, although we do not think it would be inappropriate to filter 

the data, we chose the simple approach of keeping all data because there does not appear to be a 

strong and biologically meaningful reason to filter the data. 

We chose to use raw rather than transformed data. Biological data are often transformed to 

address assumptions of the analysis which can not be otherwise met. The most common 

transformation is the logarithmic transformation (Sokal and Rohlf 1995). If greater means are 

accompanied by greater variances, the logarithmic transformation can often remedy the situation. 

We have an a priori concern that this situation could be true with morphometric data because 

there could be larger variation in larger turtles. We examined this issue by examining whether 

the residuals (from both the full and filtered datasets) increased with increasing CCLstd. 

Although the absolute value of the residuals from both the full and filtered datasets is slightly 

smaller between 10 and 20 cm CCW than they are for turtles greater than 20 cm, the magnitude 

of the residuals appears fairly well-distributed across the range of turtle sizes. Because the 

departure from homogeneity of variance is minimal and the consequences of moderate 

heterogeneity of variances are not too serious for the overall test of significance (Sokal and Rohlf 

1995) and because our focus is describing the relationship between X and Y (rather than testing 

hypotheses or creating confidence intervals for parameter estimates), we do not feel it is 

necessary to transform the raw data. 
129 

We chose to use Model I simple linear regression models rather than using more complex Model 

II regression techniques to address measurement error. Model I regression techniques assume 

(among other things) that the independent X variables are measured without error (Sokal and 

Rohlf 1995). Many biological analyses do not meet the assumptions of Model I regression, and 

we do not expect this morphometric analysis will meet the assumption that X variables are 

measured without error because all our measurements (X and Y) are likely made with some 

error. Although there is debate on how to appropriately model X variables measured with error, 

if the regression equation is being fitted primarily for prediction purposes (rather than for an 

examination of the functional relationship), then simple linear regression techniques are 

generally applied (Sokal and Rohlf 1995). Simple linear regression (Model I) techniques are 

further justified in this case because there is a definite causality relation between the X and Y 

variables and because our X and Y variables are of similar dimensions, sizes, and units. Sokal 

and Rohlf (1995) do caution that when X is measured with error, X should only be used to 

predict Y, and Y should not be used to predict X. Although we expect it would not be 

problematic in our particular analysis, we do present all pertinent regression equations so that Y 

never has to be used to predict X. 

Results

Each morphometric measurement under consideration was a suitable predictor of every other 

measurement (Table B2). All p-values were less than 0.0001; all coefficients of determination 

(R-square values) were greater than 0.9900, and all sample sizes were greater than 4,000. 

 

Table B1. Explanation of variables used in the morphometric analysis. 

Abbreviation Explanation 

CCW Curved carapace width 

CCLstd Curved carapace length, standard, notch to tip 

CCLmin Curved carapace length, minimum, notch to notch 

SCW Straight carapace width 

SCLstd Straight carapace length, standard, notch to tip 

SCLmin Straight carapace length, minimum, notch to notch 
130 

Table B2. Summary of simple linear regression equations of morphometric relationships. 

The X variables are listed in the first column and are used as row headers. The Y variables are 

listed in columns 2-7 and are used as column headings. Each regression equation uses the form 

Y=X*B, where B=the regression parameter estimate. For each regression equation, three 

statistics are listed (in order): parameter estimate (B), R-Square value, and N (sample size). 

 Y Variables 

 CCW CCLstd CCLmin SCW SCLstd SCLmin

CCW 

- 

1.0678 

0.9974 

8938.0 

1.0447 

0.9974 

4819.0 

0.7997 

0.9971 

6124.0 

0.9858 

0.9974 

5977.0 

0.9640 

0.9974 

4734.0 

CCLstd 0.9341 

0.9974 

8938.0 

- 

0.9820 

0.9994 

4824.0 

0.7504 

0.9960 

5990.0 

0.9264 

0.9994 

6002.0 

0.9086 

0.9993 

4747.0 

CCLmin 0.9547 

0.9974 

4819.0 

1.0178 

0.9994 

4824.0 

- 

0.7622 

0.9961 

4253.0 

0.9423 

0.9992 

4258.0 

0.9247 

0.9991 

4264.0 

SCW 1.2468 

0.9971 

6124.0 

1.3273 

0.9960 

5990.0 

1.3069 

0.9961 

4253.0 

- 

1.2282 

0.9957 

6830.0 

1.2026 

0.9960 

5026.0 

SCLstd 1.0118 

0.9974 

5977.0 

1.0788 

0.9994 

6002.0 

1.0604 

0.9992 

4258.0 

0.8107 

0.9957 

6830.0 

- 

0.9811 

0.9998 

5033.0 

SCLmin 1.0347 

0.9974 

4734.0 

1.0999 

0.9993 

4747.0 

1.0805 

0.9991 

4264.0 

0.8282 

0.9960 

5026.0 

1.0191 

0.9998 

5033.0 

- 

Note that because we used no intercept models, SAS has calculated the R-Square values based 

on uncorrected (for the mean) sums of squares (Uyar and Erdem 1990). 
131 

Figure B1. Histogram of standard curved carapace length (CCLstd in cm) by percent 

frequency in each 10 cm size class. N=9,062. 

0 10 20 30 40 50 60 70 80 90 100 110 120 130

0

2.5

5.0

7.5

10.0

12.5

15.0

17.5

20.0

Percent

CCLstd