Content uploaded by Trudi Webster
Author content
All content in this area was uploaded by Trudi Webster on Jan 10, 2018
Content may be subject to copyright.
MARINE MAMMAL SCIENCE, 26(2): 296–308 (April 2010)
C
2009 by the Society for Marine Mammalogy
DOI: 10.1111/j.1748-7692.2009.00326.x
A simple laser photogrammetry technique for measuring
Hector’s dolphins (Cephalorhynchus hectori) in the field
TRUDI WEBSTER
Department of Marine Science,
and
Department of Zoology
University of Otago,
P. O. Box 56, Dunedin, New Zealand
E-mail: trudi.webster@xtra.co.nz
STEVE DAWS ON
Department of Marine Science,
University of Otago,
P. O. Box 56, Dunedin, New Zealand
ELISABETH SLOOTEN
Department of Zoology,
University of Otago,
P. O. Box 56, Dunedin, New Zealand
ABSTRACT
The ability to measure and age individuals within a population has many impor-
tant applications, for example, for examining growth and determining size class.
We developed a simple photogrammetric system using two parallel lasers and a
digital camera, in order to measure dorsal fin dimensions of free-ranging Hector’s
dolphins. Laser dots were projected onto the fin, providing scale, thus allowing
measurement as well as simultaneous photo-ID of 34 individuals from fin nicks
and other marks. Multiple measurements (≥5) were available for six individuals;
these resulted in mean CVs of 3.71% for fin length and 3.76% for fin height. Errors
due to variations in angle and measurement were quantified via photography of
a fiberglass Hector’s dolphin model. Allometric measurements and age data were
collated from 233 autopsied Hector’s dolphins. Using these data, fin length was
found to be a better predictor of total length (females r2=0.732, males r2=0.678)
than fin height. Gompertz age/length growth curves were fitted to these individ-
uals. Linear regressions were used to estimate total length for 34 individuals from
laser-metrically estimated fin base length. Individuals were then assigned one of
three age categories. This system shows promise as a noninvasive way of measuring
individuals, while allowing simultaneous photographic identification.
Key words: photogrammetry, Hector’s dolphin, Cephalorhynchus hectori, length, age
determination.
296
WEBSTER ET AL.: PHOTOGRAMMETRY 297
The ability to age and measure individuals within a population is useful for a
variety of reasons. Length estimation is important for examining growth (Clark et al.
2000), determining size class (Cubbage and Calambokidis 1987), subspecific status
(Baker et al. 2002), different geographic forms (Perryman and Lynn 1993, Perryman
and Westlake 1998, Jaquet 2006) and the extent of sexual size dimorphism (Ramos
et al. 2002, Martin and Da Silva 2006). Age estimates are required for age-structured
population models (Slooten and Lad 1991, Cameron et al. 1999). Age and size also
determine maturity and influence reproductive success (Martin and Rothery 1993).
It is difficult to calculate exact ages for marine mammals; however, a number of
techniques are commonly used to provide an estimate of age. The standard procedure
for estimating age in odontocetes and pinnipeds involves counting the incremental
growth layers in tooth sections (Perrin and Myrick 1980, Myrick et al. 1984). This
technique has been used on live animals but is highly invasive as it involves capture
of the animal and extraction of a tooth (Arnbom et al. 1992, Childerhouse et al. 2004,
Bell et al. 2005). Long-term photo-ID studies can also provide age data (Hamilton
et al. 1998), but this requires intensive fieldwork over the study species’ lifetime
and typically obtains a minimum age, unless the individual is marked as a calf (e.g.,
Kraus et al. 1986).
Photogrammetry is a well-established, noninvasive method for measuring individ-
uals, both in terrestrial and marine environments (e.g., elephants, Loxondonta africana,
Schrader et al. 2006; gorillas, Gorilla gorilla, Breuer et al. 2006; and northern bluefin
tuna, Thunnus thynnus thynnus, Costa et al. 2006). Photogrammetric techniques are
particularly useful as noninvasive field methods for marine mammals, as they do not
require capture. There are two general approaches to photogrammetry, either stereo-
photography or single camera photography. Stereo-photogrammetry uses a pair of
overlapping images to create a 3-D optical model, in which scale is provided by the
known distance between the cameras and the lens magnification (e.g., Ratnaswamy
and Winn 1993, Dawson et al. 1995, Br¨
ager and Chong 1999, Waite et al. 2007).
Single camera photogrammetry requires either a known object in the image for scale
(e.g., Best and R¨
uther 1992, Flamm et al. 2000) or a measurement of the range to
the individual (e.g., Gordon 1991, Spitz et al. 2000, Jaquet 2006). A more recent
development in single camera photogrammetry uses a pair of parallel lasers to provide
scale in the images (Durban and Parsons 2006, Rowe and Dawson 2009).
A previous stereo-photogrammetric system was developed for Hector’s dolphins
to measure bowriding dolphins (Br¨
ager et al. 1999). While stereo-photogrammetry
is inherently more accurate than single camera systems, and 3-D measurements are
possible, this type of system was cumbersome both in the field and during analysis.
Also, their greater accuracy may be of little advantage when measuring animals that
are flexible (Dawson et al. 1995).
Laser photogrammetry is a simple, single camera method that has previously
been used to measure rockfish (Sebastes sp., Gingras et al. 1998, Yoklavich et al.
2000), to quantify and measure fish assemblages around oil platforms (Love et al.
2000), to measure a variety of fish species in the Bay of Biscay (Rochet et al. 2006)
and to measure dorsal fin dimensions of orca (Durban and Parsons 2006). This
method uses two parallel lasers mounted on a digital camera. The lasers project
dots at a known distance apart in the photographic images, to establish scale and
allow measurement of the dorsal fin. Further, the same images can be used in standard
photo-ID, thus identifying and measuring individuals simultaneously. Growth curves
and regressions constructed from dissection data can then be used to relate the dorsal
fin dimensions to total length and age for Hector’s dolphins.
298 MARINE MAMMAL SCIENCE, VOL. 26, NO. 2, 2010
METHODS
Photogrammetry
Combined photo-ID and laser photogrammetric photographs were taken during
boat surveys off the coast of Banks Peninsula, New Zealand, between December 2005
and February 2008. Photographs were taken from a 6 m, outboard powered research
vessel. A Nikon D1H digital camera (Nikon Imaging Inc., Tokyo, Japan) with an
80–200 mm f2.8 zoom lens was used with two laser pointers set in a high-density
nylon block secured to the tripod mount. The block mount was custom-made to fit
the laser pointers, which were set at 10 cm apart and were adjustable for calibration.
The lasers (Z-bolt model BTG-10, wavelength 532 nm, output power <5mW)
were eye safe, although direct eye contact should be avoided.
Each day before use, the lasers were tested at two different distances (2.3 m and
6.5 m) to check that they were parallel. These distances were chosen as they are within
the typical range for Hector’s dolphin identification photographs. In the field, photos
were taken of the dorsal fin of any identifiable dolphins so that the laser dots were
projected onto the fin or body (Fig. 1).
Each photograph was graded for quality to ensure that it had been taken from as
close to side-on to the dolphin as possible, with laser dots clearly visible, with dorsal
fin in focus and taken from approximately within the calibration range.
Dorsal fin height and dorsal fin base length were measured from the digital images
using graphics software Intaglio v.2.9.3. The known separation distance of the lasers
(10 cm) was used to calibrate the photographs. Measurement tools within the software
were used to measure dorsal fin dimensions. Measurements of dorsal fin base length
were taken from the midpoint of the curve at the anterior edge of the fin to the notch
at the posterior edge of the fin along the base of the fin (Fig. 1). Measurements of
dorsal fin height were taken by drawing a line parallel to the base of dorsal fin, which
just touches the top of the fin, then extending a line perpendicular to the two parallel
lines (Fig. 1).
Figure 1. Digital photograph of a Hector’s dolphin dorsal fin with projected laser dots and
dorsal fin measurements.
WEBSTER ET AL.: PHOTOGRAMMETRY 299
Sources of Error
Several sources of error are present at all stages of this photogrammetric method,
both in the field and during the measurement process. Errors in the field include
those which occur during the photographing of individuals, due to the alignment of
the lasers and those occurring naturally due to the flexing of individuals. Horizontal
axis error, which occurs when the dolphin does not surface exactly side-on to the
camera, and parallax error, which occurs when the photographer is looking down on
the subject (Durban and Parsons 2006), both cause negative biases in measurements.
Flexing of the dolphin’s body may subtly change the shape and dimensions of
the dorsal fin. Additionally, sensitivity of the nylon laser mount to temperature
fluctuations may lead to alignment errors. In the field these errors were minimized
by using the same photographer (TW), taking care that photographs were taken
as close to perpendicular as possible, from ranges of approximately 2–6 m, and by
calibrating the lasers daily. In analysis we discarded any images that were not sharp,
poorly exposed, taken from too far away, or which appeared to be nonparallel.
Errors in the measurement process arise from three major sources: variability
between observers, variability in measurement method and poorly defined metrics
(or definition error). These were minimized by having the same person take all of the
measurements, following a standardized set-up procedure.
It was not possible to estimate directly the magnitude of all errors involved in
this photogrammetric method, as Hector’s dolphins of known size are not available
for comparison in the field. Instead, error reduction strategies were employed and
indirect techniques were also used to quantify errors where feasible.
The combination of errors (except flexing) was measured by taking three replicate
photographs of a fiberglass Hector’s dolphin model at each of 5◦increments between
0◦and 55◦from perpendicular to the model and at three different distances (2.5,
5, and 7.5 m). This was done because while some errors (e.g., horizontal axis error,
parallax error) should be strictly trigonometric, other errors (e.g., definition error,
alignment of lasers) may not be. Replicate measurements on the same photograph
were not carried out in succession.
The precision of measurements taken from Hector’s dolphins was quantified by
measuring randomly chosen photographs of those individuals photographed multiple
times. Here too, measurements were not carried out in succession. A model II analysis
of variance (ANOVA) was used to partition the variance of dorsal fin measurements
into “within” and “among” dolphins, and then calculate percentage measurement
error. Measurement error is defined here as the variability of repeated measurements
of dorsal fin dimensions taken on the same individual, relative to the variability of
these dimensions among individuals (see Bailey and Byrnes 1990 for method),
%ME =100 s2
within
s2
within +s2
among
Allometric Measurements
Measurement data from bycaught and stranded Hector’s dolphins were collated
from a number of different sources (Slooten 1991; Duignan et al. 2003, 2004;
Duignan and Jones 2005). Measurements gained during autopsies by experienced
researchers, and age estimates from counting GLGs in teeth (e.g., Slooten 1991),
300 MARINE MAMMAL SCIENCE, VOL. 26, NO. 2, 2010
are assumed to be without error. A linear regression was fitted to dorsal fin height
and dorsal fin length against total length. Von Bertalanffy (Von Bertalanffy 1938),
Gompertz (Gompertz 1825) and Richards (Richards 1959) growth curves were used
to describe growth. Growth functions of the following form were fitted using least
squares estimation of the parameters in program JMP v5
Von Bertalanffy: Lt=L∞(1 −bexp(−kt))
Gompertz: Lt=L∞exp(−exp(b−kt))
Richards: Lt=L∞(1 −bexp(−kt))M
where L∞is asymptotic total length (or fin height or fin length), tis age in years, k
is a growth rate constant, bis the constant of integration, and Mspecifies the relative
position of the asymptote.
RESULTS
Multiple photographs of a Hector’s dolphin model examined a combination of
errors and showed that deviations of up to 20◦from perpendicular resulted in dorsal
fin measurements within 2% of actual values. Over this range of angles, there were
no obvious biases caused by variation in range (Fig. 2).
The model II ANOVA using data from dolphins that had been repeatedly pho-
tographed and measured showed that the variation between individuals was far
greater than the variation between multiple remeasurements of the same photo-
graph. The results of the ANOVA were highly significant for dorsal fin height
(F=2,320.04, df =32, 132, P<0.001) and dorsal fin length (F=2,216.87,
df =325, 132, P<0.001). Percentage measurement error (see formula in Meth-
ods) was also minimal at 0.22% for dorsal fin height and 0.23% for dorsal fin
length.
Ninety-five images of 34 identifiable dolphins showed projected laser dots, were
sharply focused and showed ideal orientation of the individual to the camera. Twenty
Figure 2. Mean error in dorsal fin length measurements with angle from perpendicular.
WEBSTER ET AL.: PHOTOGRAMMETRY 301
Figure 3. Variability in dorsal fin base length measurements for six individuals pho-
tographed five or more times. Minimum age and sex are given under the identifying number
of each individual.
individuals were of known sex (12 females and 8 males). The number of photographs
for each individual ranged from 1 to 19 (¯x =2.88). Dorsal fin height ranged from
8.04 cm to 11.57 cm and fin base length was in the range from 17.10 cm to
23.76 cm.
Six identifiable individuals of known sex and known minimum age (calculated
using photo-ID data) were photographed five or more times (including two individ-
uals on different days, Fig. 3). These individuals show an increase in dorsal fin length
with age, as expected. The mean CV of dorsal fin base length for these individu-
als was 3.71% (range 1.57%–5.71%) and for dorsal fin height was 3.76% (range
2.04%–5.86%).
Allometric Measurements and Growth Curves
A total of 233 individuals with either two or more relevant allometric measure-
ments, or estimated age (from GLGs) and one or more measurements were repre-
sented in the autopsy data. Ninety four percent of these dolphins were of known sex
(127 males and 92 females) and 73.4% were of known age.
302 MARINE MAMMAL SCIENCE, VOL. 26, NO. 2, 2010
Figure 4. Gompertz growth curves for male and female Hector’s dolphins.
Von Bertalanffy, Gompertz, and Richard’s growth models were fitted to autopsy
data for total length, dorsal fin height, and dorsal fin base length for male and
female Hector’s dolphins separately. The Richard’s growth model, typically, did not
converge, and was therefore considered unreliable for these data. There was very little
difference between Von Bertalanffy and Gompertz growth functions. Von Bertalanffy
growth curves were a marginally better fit and had a slightly lower residual of the sum
of squares. However, Gompertz growth curves fitted the lower end of the data (i.e.,
the younger animals) much better than Von Bertalanffy curves. Since this portion of
the curve is most important for growth, Gompertz curves were chosen (Fig. 4).
Linear regressions showed that dorsal fin base length was a far better predictor
of total length (females r2=0.73, males r2=0.69; Fig. 5) than dorsal fin height
(females r2=0.51, males r2=0.58; Fig. 6). Females had a slightly better relationship
between fin base length and total length than males (Fig. 5).
WEBSTER ET AL.: PHOTOGRAMMETRY 303
Figure 5. Relationship between total length and dorsal fin base length for male and female
Hector’s dolphins. The regression relationship labeled “Unknown sex” is for all data including
three individuals of unknown sex.
The regressions were used to estimate total length from data on dorsal fin base
length for 34 individuals that were measured using the photogrammetric method.
Gender specific linear regressions were used where possible. The estimated total
lengths for females ranged from 115.8 cm to 143.1 cm. Males were slightly smaller
between 97.1 cm and 126.0 cm. Individuals of undetermined sex had total lengths
of between 110.9 cm and 137.1 cm.
It has not been possible to estimate age from photogrammetric measurements,
for two reasons. Firstly, there is a great deal of variability in the body measurement
data; for example, 2-yr-old males range from 90 to 120 cm. Also, the nature of these
growth curves is that they plateau at approximately 5–6 yr. Thus a female ≥134
cm could be anywhere between 6 and 20 yr old. It was possible, however, to place
laser-metrically measured individuals into broad age categories, based on their dorsal
fin base length (Table 1). Age categories were determined using information on fin
length measurements, estimated age (from tooth sections) and maturity status from
the collated autopsy data.
Individuals that are either particularly large for their age or particularly small are
difficult to age. An intermediate category (Table 1) encompasses these individuals
as well as those of medium fin length that are unable to be assigned to either the
juvenile or mature category.
304 MARINE MAMMAL SCIENCE, VOL. 26, NO. 2, 2010
Figure 6. Relationship between total length and dorsal fin height for male and female
Hector’s dolphins. The regression relationship labeled “Unknown sex” is for all data including
ten individuals of unknown sex.
DISCUSSION
The laser photogrammetric technique applied here was first tested on cetaceans
by Durban and Parsons (2006) to measure the dorsal fin height of orca, and has
since been used on bottlenose dolphins (Rowe and Dawson 2009). These systems are
inexpensive, require very little equipment, and are easy to set up and use. Another
major benefit is that identification photographs are obtained simultaneously.
This method resulted in a mean CV of 3.71% for dorsal fin base length and 3.76%
for fin height, which compare favorably with other photogrammetric techniques for
Tabl e 1 . Age categories determined by dorsal fin length for individuals of either known or
unknown sex, and the number of individuals in each category (n).
Male Female Unknown gender
Juvenile ≤18.2 cm ≤19.2 cm ≤18.2 cm
n=2n=0n=0
Intermediate 18.3–20.5 cm 19.3–21.5 cm 18.3–21.5 cm
n=3n=9n=4
Mature ≥20.6 cm ≥21.6 cm ≥21.6 cm
n=1n=3n=4
WEBSTER ET AL.: PHOTOGRAMMETRY 305
measuring cetaceans in the field. Stereo-photogrammetric measurement of blowhole
to dorsal fin distance in sperm whales using a boat based technique yielded a mean
CV of 4.38% (Dawson et al. 1995). An underwater videogrammetry method for
obtaining lengths of humpback whales resulted in a mean CV of 3.08% for mothers
and 2.57% for escorts (Spitz et al. 2000). Median CVs varied from 1.29% to 4.56%
for various morphometric measurements of right whales (Best and R¨
uther 1992). A
median CV of 1.3% was obtained for individual fluke measurements of sperm whales
(Jaquet 2006).
Errors will never be completely eliminated from this photogrammetric system but
they can be quantified and reduced where possible. Accuracy was demonstrated by
photographing a life-size Hector’s dolphin model of known dimensions. When the
model was 20◦from perpendicular to the camera, theoretically, parallax error alone
would produce an error of 6%. However, a combination of errors are acting, some
of which apparently counteract the parallax error, so that all measurements from the
laser photogrammetric system were within 2% of the actual measurements. Similarly,
a measurement technique applied to sperm whale flukes (Jaquet 2006) found that
errors were small when the angle between the fluke surface and a plane perpendicular
to the camera was <10◦and that at angles >20◦measurements do not provide
reliable size estimates. Measurement errors (quantified via multiple, nonsequential,
remeasurement of the same images) were low for this photogrammetric method
(0.22–0.23%). Also, it should be remembered that because dolphins are inherently
flexible, even a perfect system used repeatedly on the same individual would not
produce exactly the same measurements.
Dorsal fin base length was found to be a better predictor of total length than dorsal
fin height and hence was used to estimate length of living dolphins. Individual
lengths calculated for these animals were within the known total length range for
Hector’s dolphins (Slooten 1991; Duignan et al. 2003, 2004; Duignan and Jones
2005).
Due to variation in body measurement data, age could not be predicted accurately
from measurements of dorsal fin dimensions and growth curves. Broad age categories
can, however, be assigned to individuals measured using the laser photogrammetric
technique. This method therefore shows promise to provide field data that might be
used, for example, in a stage-structured population model. This would avoid the need
to use potentially biased age distributions gained from dead animals, the majority
of which have been incidentally killed in gill nets (e.g., Slooten 1991).
We noted that the black mounting block sometimes became warm in the sun,
and this may have affected laser alignment. Using white nylon material (instead of
black) is advised. Also, we noted that the Z-bolt laser pointers that we used were not
collimated, that is, the axis of the laser beam and the laser pointer’s tubular body
were not the same. We corrected for this during calibration, but in future would use
higher quality lasers, in which this is adjustable.
The laser photogrammetric method trialed here has several potential future uses
for marine mammals. The system is particularly useful for those species that are
identifiable from nicks in the dorsal fin. Measurement of body proportions could
potentially be applied to individuals to help determine health status and pregnancy in
the field (e.g., Pettis et al. 2004). Age estimation using this technique and age-length
data would be more effective in species that mature late and grow for much of their
lives. Growth curves need to be examined beforehand and the relationship between
a particular measurement and age needs to be tight for age determination to be
effective. In order to establish growth curves with sufficient data points, a significant
306 MARINE MAMMAL SCIENCE, VOL. 26, NO. 2, 2010
number of dead animals would need to be available for measurement. This may limit
studies, for example, to species which mass strand or those with significant bycatch.
Differences in length between subspecies could be detectable using this laser-metric
technique, assuming that the difference in length is greater than the errors involved
(e.g., common dolphins, Perryman and Lynn 1993; spinner dolphins, Perryman and
Westlake 1998). The use of scale in identification photographs may elucidate the
causes of identifying marks, for example, the examination of puncture wounds to
identify predator species or scars from collisions with propellers in order to identify
the type of vessel involved. Last, measurement data might be a useful adjunct in
photo-ID, allowing discrimination of different sized individuals that bear similar
marks.
ACKNOWLEDGMENTS
This study was possible thanks to support and funding from the New Zealand Whale
and Dolphin Trust. Thanks to Will Rayment for his assistance with data collection and
Black Cat Group for logistical support. Many thanks to the Fraser family for their help
and support at Banks Peninsula. The University of Otago Research Committee provided a
University of Otago Postgraduate Publishing Bursary enabling the completion of this article.
This manuscript was greatly improved by comments from Richard Connor, Will Rayment,
and three anonymous reviewers.
LITERATURE CITED
Arnbom, T. A., N. J. Lunn, I. L. Boyd and T. Barton. 1992. Ageing live Antarctic fur seals
and southern elephant seals. Marine Mammal Science 8:37–43.
Baker, A. N., A. N. H. Smith and F. B. Pichler. 2002. Geographical variation in Hector’s
dolphin: Recognition of new subspecies of Cephalorhynchus hectori. Journal of the Royal
Society of New Zealand 32:713–727.
Bailey, R. C., and J. Byrnes. 1990. A new, old method for assessing measurement error in both
univariate and multivariate morphometric studies. Systematic Zoology 39:124–130.
Bell, C. M., H. R. Burton, M. A. Lea and M. A. Hindell. 2005. Growth of female southern
elephant seals Mirounga leonina at Macquarie Island. Polar Biology 28:395–401.
Best, P. B., and H. R¨
uther. 1992. Aerial photogrammetry of southern right whales, Eubalaena
australis. Journal of the Zoological Society of London 228:595–614.
Br¨
ager, S., and A. Chong. 1999. An application of close range photogrammetry in dolphin
studies. Photogrammetric Record 16:503–517.
Br¨
ager, S., A. Chong, S. Dawson, E. Slooten and B. W¨
ursig. 1999. A combined stereo-
grammetry and underwater-video system to study group composition of dolphins. Hel-
goland Marine Research 53:122–128.
Breuer, T., M. M. Robbins and C. Boesch. 2006. Using photogrammetry and color scoring
to assess sexual dimorphism in wild western gorillas (Gorilla gorilla). American Journal
of Physical Anthropology 134:369–382.
Cameron, C., R. Barker, D. Fletcher, E. Slooten and S. Dawson. 1999. Modelling survival
of Hector’s dolphins around Banks Peninsula, New Zealand. Journal of Agriculture,
Biological and Environmental Statistics 4:126–135.
Childerhouse, S., G. Dickie and C. Hessel. 2004. Ageing live New Zealand sea lions (Phocarctos
hookeri) using the first post-canine tooth. Wildlife Research 31:177–181.
Clark, S. T., D. K. Odell and C. T. Lacinak. 2000. Aspects of growth in captive killer whales
(Orcinus orca). Marine Mammal Science 16:110–123.
Costa, C., A. Loy, S. Cataudella, D. Davis and M. Sardi. 2006. Extracting fish size using dual
underwater cameras. Aquacultural Engineering 35:218–227.
WEBSTER ET AL.: PHOTOGRAMMETRY 307
Cubbage, J. C., and J. Calambokidis. 1987. Size-class segregation of bowhead whales discerned
through aerial stereo-photogrammetry. Marine Mammal Science 3:179–185.
Dawson, S. M., C. J. Chessum, P. J. Hunt and E. Slooten. 1995. An inexpensive stereophoto-
graphic technique to measure sperm whales from small boats. Report of the International
Whaling Commission 45:431–436.
Duignan, P. J., and G. W. Jones. 2005. Autopsy of cetaceans including those incidentally
caught in commercial fisheries, 2002/03. DOC Science Internal Series 195. Department
of Conservation, Wellington, New Zealand. 22 pp.
Duignan, P. J., N. J. Gibbs and G. W. Jones. 2003. Autopsy of cetaceans incidentally caught
in fishing operations 1997/98, 1999/00 and 2000/01. DOC Science Internal Series 119.
Department of Conservation, Wellington, New Zealand. 66 pp.
Duignan, P. J., N. J. Gibbs and G. W. Jones. 2004. Autopsy of cetaceans incidentally caught in
commercial fisheries, and all beachcast specimens of Hector’s dolphins, 2001/02. DOC
Science Internal Series 176. Department of Conservation, Wellington, New Zealand. 28
pp.
Durban, J. W., and K. M. Parsons. 2006. Laser-metrics of free ranging killer whales. Marine
Mammal Science 22:735–743.
Flamm, R. O., E. C. G. Owen, C. F. W. Owen, R. S. Wells and D. Nowacek. 2000. Aerial
videogrammetry from a tethered airship to assess manatee life-stage structure. Marine
Mammal Science 16:617–630.
Gingras, M. L., D. A. Ventresca and R. H. McGonigal. 1998. In-situ videography calibrated
with two parallel lasers for calculation of fish length. California Fish and Game 84:36–39.
Gompertz, B. 1825. On the nature of the function expressive of the law of human mortality
and on a new method of determining the value of life contingencies. Philosophical
Transactions of the Royal Society of London 115:513–585.
Gordon, J. C. 1991. Evaluation of a method for determining the length of sperm whales
(Physeter catodon) from their vocalisations. Journal of Zoology 224:301–314.
Hamilton, P. K., A. R. Knowlton, M. M. Marx and S. D. Kraus. 1998. Age structure
and longevity in North Atlantic right whales Eubalaena glacialis and their relation to
reproduction. Marine Ecology Progress Series 171:285–292.
Jaquet, N. 2006. A simple photogrammetric technique to measure sperm whales at sea.
Marine Mammal Science 22:862–879.
Kraus, S. D., K. E. Moore, C. E. Price, M. J. Crone, W. A. Watkins, H. E. Winn and
J. H. Prescott. 1986. The use of photographs to identify individual North Atlantic
right whales (Eubalaena glacialis). Report of the International Whaling Commission
(Special Issue 10):145–151.
Love, M. S., J. E. Caselle and L. Snook. 2000. Fish assemblages around seven oil platforms in
the Santa Barbara Channel area. Fishery Bulletin 98:96–117.
Martin, A. R., and P. Rothery. 1993. Reproductive parameters of female long-finned pilot
whales (Globicephala melas) around the Faroe Islands. Report of the International Whaling
Commission 14:263–304.
Martin, A. R., and V. M. F. Da Silva. 2006. Sexual dimorphism and body scarring in the boto
(Amazon river dolphin) Inia geoffrensis. Marine Mammal Science 22:25–33.
Myrick, A. C., Jr., E. W. Shallenberger, I. Kang and D. B. Mackay. 1984. Calibration of
dental layers in seven captive Hawaiian spinner dolphins, Stenella longirostris based on
tetracycline labeling. Fishery Bulletin 82:207–225.
Perrin, W. F., and A. C. Myrick, Jr., eds. 1980. Age determination of toothed whales and
sirenians. Report of the International Whaling Commission (Special Issue No. 3).
Perryman, W. L., and M. S. Lynn. 1993. Identification of geographic forms of common
dolphin (Delphinus delphis) from aerial photogrammetry. Marine Mammal Science 9:119–
137.
Perryman, W. L., and R. L. Westlake. 1998. A new geographic form of the spinner dolphin
(Stenella longirostris) detected with aerial photogrammetry. Marine Mammal Science
14:38–50.
308 MARINE MAMMAL SCIENCE, VOL. 26, NO. 2, 2010
Pettis, H. M., R. M. Rolland, P. K. Hamilton, S. Brault, A. R. Knowlton and S. D. Kraus.
2004. Visual health assessment of North Atlantic right whales (Eubalaena glacialis)using
photographs. Canadian Journal of Zoology 82:8–19.
Ramos, R. M. A., A. P. M. Di Beneditto, S. Siciliano, M. C. O. Santos, A. N. Zerbini,
C. Bertozzi, A. F. C Vicente, E. Zampirolli, F. S. Alvarenga and N. R. W. Lima.
2002. Morphology of the franciscana (Pontoporia blainvillei) off southeastern Brazil:
Sexual dimorphism, growth and geographic variation. Latin American Journal of Marine
Mammals 1:129–144.
Ratnaswamy, M. J., and H. E. Winn. 1993. Photogrammetric estimates of allometry and calf
production in fin whales, Balaenoptera physalus. Journal of Mammalogy 74:323–330.
Richards, F. J. 1959. A flexible growth function for empirical use. Journal of Experimental
Botany 10:290–300.
Rochet, M. D., J. F. Cadiou and V. M. Trenkel. 2006. Precision and accuracy of fish length
measurements obtained with two visual underwater methods. Fishery Bulletin 104:1–9.
Rowe, L. E., and S. M. Dawson. 2009. Determining the gender of bottlenose dolphins (Tursiops
sp.) using dorsal fin photographs. Marine Mammal Science 25:19–34.
Schrader, A. M., S. M. Ferreira and R. J. Van Aarde. 2006. Digital photogrammetry and laser
rangefinder techniques to measure African elephants. South African Journal of Wildlife
Research 36:1–7.
Slooten, E. 1991. Age, growth and reproduction in Hector’s dolphins. Canadian Journal of
Zoology 69:1689–1700.
Slooten, E., and F. Lad. 1991. Population biology and conservation of Hector’s dolphin.
Canadian Journal of Zoology 69:1701–1707.
Spitz, S. S., L. M. Herman and A. A. Pack. 2000. Measuring sizes of humpback whales
(Megaptera novaeangliae) by underwater videogrammetry. Marine Mammal Science
16:664–676.
Von Bertalanffy, L. 1938. A quantitative theory of organic growth. Human Biology 10:181.
Waite, J. N., W. J. Schrader, J. E. Mellish and M. Homing. 2007. Three-dimensional
photogrammetry as a tool for estimating morphometrics and body mass of Steller sea
lions (Eumetopias jubatus). Canadian Journal of Fisheries and Aquatic Sciences 64:296–
303.
Yoklavich, M. M., G. G. Greene, D. E. Sullivan, R. N. Lea and M. S. Love. 2000. Habitat
association of deepwater rockfishes in a submarine canyon. Fishery Bulletin 98:625–641.
Received: 6 October 2008
Accepted: 2 April 2009