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RESEARCH ARTICLE
Application of endocrine biomarkers to
update information on reproductive
physiology in gray whale (Eschrichtius robustus)
Valentina MelicaID
1
*, Shannon Atkinson
1
, John Calambokidis
2
, Aime
´e Lang
3
,
Jonathan Scordino
4
, Franz Mueter
1
1Fisheries Department, College of Fisheries and Ocean Sciences, University of Alaska Fairbanks, Juneau,
Alaska, United States of America, 2Cascadia Research, Olympia, Washington, United States of America,
3Ocean Associates Inc., on Contract to NOAA Southwest Fisheries Science Center, La Jolla, California,
United States of America, 4Marine Mammal Program, Makah Fisheries Management, Neah Bay,
Washington, United States of America
*valentinamelica88@gmail.com
Abstract
Most of our knowledge on reproductive biology of gray whales dates back to scientific
research conducted during commercial whaling in the late 1950s and 1960s. The goal of the
present study was to provide updated insights on reproductive physiology of gray whales,
using progesterone and testosterone as biomarkers. We measured hormone concentra-
tions using enzyme immunoassay (EIA) techniques in blubber biopsies collected from 106
individual whales from March to November over a span of 12 years (2004–2016) between
California and Alaska. We found testosterone concentrations in males to increase signifi-
cantly with age (P= 0.03). Adult males showed significantly elevated testosterone concen-
trations when sampled in the fall compared to the summer (P= 0.01), likely indicating
physiological preparation for mating. We measured testosterone concentrations in females
of different age classes, but no statistical differences were found. We found significantly
higher progesterone concentrations in pregnant females compared to non-pregnant females
and adult males (P<0.001), indicating progesterone is a valid biomarker for pregnancy in
gray whales. Both female and male calves had elevated progesterone concentrations, sug-
gesting maternal transfer via lactation. We fit a mixture of two normal distributions to proges-
terone data from all non-calf females to identify clusters of high and low progesterone and
estimated the probability of being pregnant for whales of unknown reproductive status. With
this approach we identified likely pregnant and non-pregnant animals. This study represents
an important milestone on reproductive profiles in this population, that can be used to esti-
mate more accurate and precise reproductive parameters to be used for better understand-
ing population dynamics of gray whales.
Introduction
Gray whales (Eschrichtius robustus) occur exclusively in the Pacific Ocean [1]. Two popula-
tions are recognized, the Western North Pacific (WNP) and Eastern North Pacific (ENP)
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OPEN ACCESS
Citation: Melica V, Atkinson S, Calambokidis J,
Lang A, Scordino J, Mueter F (2021) Application of
endocrine biomarkers to update information on
reproductive physiology in gray whale
(Eschrichtius robustus). PLoS ONE 16(8):
e0255368. https://doi.org/10.1371/journal.
pone.0255368
Editor: Ulrike Gertrud Munderloh, University of
Minnesota, UNITED STATES
Received: February 21, 2021
Accepted: July 14, 2021
Published: August 3, 2021
Copyright: ©2021 Melica et al. This is an open
access article distributed under the terms of the
Creative Commons Attribution License, which
permits unrestricted use, distribution, and
reproduction in any medium, provided the original
author and source are credited.
Data Availability Statement: All relevant data are
within the manuscript and its Supporting
Information files.
Funding: This project was partially funded from
University of Alaska Fairbanks, through the
Resilience and Adaptation Program and the Calvin
Lensink Fellowship. Research reported in this
publication was partially supported by an
Institutional Development Award (IdeA) from the
National Institute of General Medical Sciences of
populations, although some whales that feed in the WNP are known to overwinter in the ENP
[2–4]. Both populations were driven close to extinction by commercial whaling, and to date,
the WNP population is considered Endangered by the International Union for the Conserva-
tion of Nature. The ENP population was removed from the United States endangered species
list in 1994 [5] and the most up to date population estimate is 20,580 individuals [6].
The majority of ENP gray whales migrate annually between wintering nursing grounds
located in the lagoons and coastal waters of the Baja California Peninsula, Mexico, and feeding
grounds located on the continental shelves of the Bering and Chukchi Seas [5]. Among them, a
small group of approximately a dozen whales is known to detour their spring migratory route
to the North Puget Sound (NPS) to feed on ghost shrimps [7], before continuing northward. A
more distinguished ENP subgroup is noted as the Pacific Coast Feeding Group (PCFG), a
group of gray whales that terminate their northbound migration further south to forage pri-
marily between southeastern Alaska and northern California from spring to fall [8]. Photo-
identification studies of the PCFG started in the 1970s [9–13], with more detailed knowledge
acquired over the last couple of decades. According to the definition of the International
Whaling Commission’s Scientific Committee [14], PCFG gray whales are those that are seen
in the waters between northern California and British Columbia (41˚N-52˚N; excluding
whales observed in Puget Sound) in more than one year between June 1
st
and November 30
th
.
However, photo-ID matches have shown that the feeding habitat of some PCFG whales
extends further north, with whales frequently present around Kodiak Island, Alaska [8,14].
The results of nuclear DNA analyses inter alia indicate that PCFG whales interbreed with the
ENP whales that feed further north [15,16], and the PCFG is not considered a separate stock
in the United States. Both genetic (based on mitochondrial DNA) and photo-identification
studies indicate that matrilineal fidelity to the PCFG occurs [8,16–18] and the most recent
abundance estimate is 232 PCFG whales [8].
Knowledge on the reproductive biology of gray whales is extensive, though outdated as
much of it is based on scientific research conducted during commercial whaling off the coast
of central California between 1959 and 1969 [19]. The mean age of sexual maturity (ASM) for
females and males is estimated at 8 years old (with a range from 5 to 11 years) based on studies
of earplug growth layers and gonads [19,20]. This species has on average a 2-year reproductive
cycle [21], with a gestation period of 13 months and calves weaned 6–7 months postpartum
[19]. The gray whale migration is staggered in time based on age and reproductive state [19,
22]. For instance, during the southward migration from the feeding grounds, pregnant females
migrate first, followed by females that have recently ovulated and adult males, and then by
immature whales [1]. Non-pregnant females ovulate during the months of November and
December [19], suggesting that mating occurs during the southbound migration [21]. Winter-
ing grounds known for this population include the coastal waters and lagoons on the west
coast of the Baja California Peninsula with calving areas in the Laguna Ojo de Liebre (Scam-
mon’s Lagoon) and Laguna San Ignacio [19,23]. Although some calves are born during the
southbound migration [24], most females give birth in the winter grounds by late December
or early January [19]. By late January the first phase of northward migration has begun, led by
newly pregnant females followed by adult males and juveniles [5]. The second phase of migra-
tion occurs in April through May and consists primarily of lactating females with their calves.
By summer, the vast majority of gray whales are on their feeding grounds [13,19].
Over the past two decades, endocrine techniques have been successfully applied to under-
stand and gain information on reproductive processes and parameters for several whale spe-
cies [25–31]. Nevertheless, the amount of research on gray whale endocrinology is still limited,
with few recent studies validating steroid and thyroid hormones in blubber, feces and baleen
[32–34]. The use of blubber tissue for endocrine studies has been proven valid and valuable to
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the National Institutes of Health under grant
number P20GM103395 and by Biomedical
Learning and Student Training (BLaST) program
and equipment fund, supported by National
Institutes of Health Common Fund, through the
Office of Strategic Coordination, Office of the NIH
Director with the linked awards: RL5GM118990,
TL4 GM118992 and 1UL1GM118991. The content
is solely the responsibility of the authors and does
not necessarily reflect the official views of the NIH.
The funders had no role in study design, data
collection and analysis, decision to publish, or
preparation of the manuscript. Open access
publication fees were provided by the SeaDoc
Society, a program of the University California
Davis Karen C. Drayer Wildlife Health Center. One
author, Dr. Aime
´e Lang, is employed by a
commercial company Ocean Associates, Inc. The
funder provided support in the form of salaries for
author AL, but did not have any additional role in
the study design, data collection and analysis,
decision to publish, or preparation of the
manuscript. The specific roles of this author are
articulated in the ‘author contributions’ section.
Competing interests: The authors have declared
that no competing interests exist. The commercial
affiliation for Dr. Aime
´e Lang with Ocean
Associates Inc. does not alter our adherence to
PLOS ONE policies on sharing data and materials.
provide information on reproductive physiology in many odontocete [35–37] and mysticete
species [25,27–29,31,38,39]. Collection of blubber is a minimally invasive technique [40] and
over the past two decades, large numbers of skin and blubber samples have been archived in
freezers, and subsampled for various types of research (e.g., hormones [27,29,41], contami-
nants [42–45], stable isotopes [38,46,47], lipid profiles [48,49] and age determination [50]).
While the perfusion rate of hormones from blood to blubber likely differs among species, blub-
ber concentrations are likely representative of relatively recent (hours to weeks) physiological
events [35,36,39]. Published studies indicate hormone concentrations in blubber of bowhead
whales (Eubalaena mysticetus) to reflect those in blood over a time period of weeks [39],
whereas in bottlenose dolphins (Tursiops truncatus) this lag-time is much shorter (hours) [35,
36]. Sampling efforts to collect blubber biopsies of gray whales have been carried out over the
past 25 years along the Pacific West Coast [16,51,52].
Sex-steroid hormones such as testosterone and progesterone can be used as biomarkers for
reproduction. These steroid hormones are synthesized from cholesterol, mainly in the gonads,
and, because of their lipophilic nature, they can be detected and have increasingly been mea-
sured in blubber tissues of cetaceans [25,29,31,53,54]. During pregnancy, progesterone is the
predominant sex-steroid hormone and concentrations are elevated [37,55]. Researchers have
used progesterone concentrations in blubber to detect pregnancy in minke whales (Balaenop-
tera acurostrata) [25], bowhead whales [39], humpback whales (Megaptera novaeangliae) [27,
38], fin whales (Balaenoptera physalus) [31] and blue whales (Balaenoptera musculus) [29,54].
Testosterone is secreted by the gonads and the adrenal glands, and it is the main androgen in
mammals [56,57]. Besides stimulating spermatogenesis, testosterone is responsible for the
onset of sexual maturity and involved in the development of both primary and secondary sex-
ual characteristics [37]. As mysticetes are seasonal breeders, testosterone concentrations are
likely to have a cyclic trend, peaking before mating, then decreasing after breeding has
occurred [58]. Annual cyclicity in testosterone was observed in baleen plates of bowhead, right
(Eubalaena glacialis) and possibly blue whales [59], and in the blubber of fin [31], blue [54]
and humpback whales [41,60]. Specifically, these studies found testosterone concentrations to
be indicative of physiological preparation for reproduction, as they were higher during the
time between winter breeding and summer feeding in fin, blue and humpback whales [31,
54,60].
The present study validates and measures testosterone and progesterone in blubber biopsies
of gray whales sampled over a 12-year period, between California and southeastern Alaska,
with most of the individuals considered part of the PCFG. The specific research questions
were:
• Can progesterone and testosterone be validated and measured in blubber of gray whales?
• Is progesterone an indicator of pregnancy in female gray whales and can it be used to esti-
mate reproductive status for unknown whales?
• Do progesterone and testosterone show variation in response to the age of the individual,
time of year and geographic location of sampling?
Methods
Sample collection and sighting history
For the present study, we accessed archived biopsy samples (n= 119) of gray whale blubber
stored frozen at -80˚ at NOAA Fisheries Southwest Fisheries Science Center (SWFSC) Marine
Mammal and Sea Turtle Research Collection. The fieldwork efforts to collect these samples
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were carried out over a span of 12 years (2004–2016) between March and November by the
Marine Mammal Program of the Makah Tribe, Cascadia Research Collective (CRC) and
NOAA Fisheries SWFSC [16,51,52] (MMPA Permit # 16111–00 and 14097).
The sample set included 106 unique individuals, for which biopsies were matched to photo-
identified whales. We identified samples collected from the same individual by comparison of
photographs and genetic profiles (see Lang et al. [16] for details on the genetic comparisons). To
ensure independence, we included in the main analyses for testosterone and progesterone only
one sample per individual, choosing the sample for which age class or reproductive state could be
determined. If neither age class nor reproductive state was available or the repeated samples had
the same classification, we included the biopsy collected first. Of the 106 unique identified individ-
uals, 89 were whales from the PCFG, two are known to be part of the North Puget Sound (NPS)
gray whale group and the remaining 15 were considered part of the overall ENP population.
The area of sampling extended as far south as Bodega Bay, CA (Latitude: 38.28˚N, Longi-
tude: -122.15˚W) north to Kodiak Island, AK (Latitude: 57.36˚N, Longitude: -152.42˚W) with
the majority collected in the IWC-defined PCFG range (Latitude: 41˚N– 52˚N; [14]). Most of
the samples were collected between the months of June and October, thus representing sum-
mer and fall, when the whales were on their feeding grounds. One sample was collected in
November and three between March and May, two of these were from the same individual.
Given the limited sample size, the current study only investigated differences between summer
and fall, with summer defined as mid-June to mid-September and fall as mid-September to
mid-November. Sampling locations were grouped as California (CA, n= 2), Oregon (OR,
n= 6), Washington (WA, n= 71), British Columbia (BC, n= 22) and Alaska (AK, n= 5)
(Fig 1).
Fig 1. Map of the Pacific Ocean and west coast of North America with gray whales samplinglocations color-coded
by sex. Blubber biopsy samples were collected off the United States coasts of California (CA, n= 2), Oregon (OR,
n= 6), Washington (WA, n= 71) and Alaska (AK, n= 5), and in Canadian waters of British Columbia (BC, n= 22).
Dashed lines mark distribution boundaries of PCFG.
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The sex of all samples was genetically determined as described in Lang et al. [16] and we
accessed the CRC gray whale catalogue to gather life history information, such as year of birth
or first sighting, and reproductive status at the time of sampling. We assigned age class and
reproductive status at the time of sampling by applying the general criteria defined in similar
studies [29–31,54,61], with a few modifications. Briefly, we assigned age class based on length
of sighting history (LSH) as a proxy for minimum age or based on known age for individuals
which were first seen as calves. We identified as calves or young of the year all whales that were
small in size (estimated to be less than or equal to 8 meters in length) and accompanied by an
adult female [19,62,63]. Mean age of sexual maturity for gray whales is estimated to be 8
years, based on histological examinations of gonads and lamina of earplugs [19,20], therefore
we categorized all individuals, males and females, with at least 8 years of LSH or known age as
adults. Conversely, we considered all animals of known age less than 8 years as immature
(Tables 1and 2). We further sorted female gray whales by the following reproductive states:
calves if sampled as such, immature if they had a known age less than 8 years old when sam-
pled, pregnant if sighted with a calf the year after sampling and lactating if sighted in close
association with a small whale noted as calf when sampled (Table 2). We considered as non-
pregnant all females from the calf, immature and lactating groups. We classified as adult
Table 1. Mean (range) of progesterone and testosterone concentrations in male gray whales. Divided by age class.
Age class Description Mean testosterone concentrations (range)
ng/g
Mean progesterone concentrations (range)
ng/g
Calf Males sighted as calves the year of sampling 0.4 (0.3–0.5) 2.6 (1.8–4.0)
(n= 4) (n= 4)
Immature Males with known year of birth and known age of less than
8 years
0.4 (0.1–0.9) 0.6
(n= 6) (n= 1)
Adult Males known to be 8 years of age or more 1.9 (0.2–9.8) 0.5 (0.3–0.6)
(n= 16) (n= 4)
Unknown Males that do not fit in any other categories 0.6 (0.1–2.6) NA
(n= 14)
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Table 2. Mean (range) of progesterone and testosterone concentrations (ng/g) in female gray whales divided by age class and reproductive state.
Age class description Reproductive state Mean progesterone concentrations
(range) ng/g
Mean testosterone concentrations
(range) ng/g
Calf Calf 4.7 (1.5–11.0) 0.8 (0.4–1.2)
Whales sighted as calves the year of sampling (n= 4) (n= 3)
Immature Immature 2.2 (0.7–3.5) 0.8 (0.1–2.1)
Whales with known year of birth and known
age of less than 8 years
(n= 6) (n= 6)
Adult Lactating: observed with calf the year of
sampling
2.1 (1.5–3.6) 0.4 (0.1–0–8)
Whales known to be 8 or more years of age (n= 6) (n= 3)
Pregnant: observed with a calf the year
after sampling
19.5 (11.2–30.8) 0.2 (0.2–0.3)
(n= 4) (n= 4)
Adult-unknown: not seen or seen not
accompanied by calf
7.9 (0.7–48.9) 0.2 (0.1–0.4)
(n= 26) (n= 2)
Unknown Unknown 9.2 (0.6–61.7) NA
Females that do not fit in any other categories (n= 20)
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unknown females with at least 8 years of LSH but with no known reproductive state, and as
unknown all females that could not be categorized in any of the age class (i.e., not first identi-
fied as calves and with LSH <8 yrs) or reproductive state categories. Out of the 40 unique
male individuals, we identified four calves, six immatures, 16 adults and 14 whales of unknown
age class (Table 1), while the female dataset (n= 66) was comprised of four calves, six imma-
tures, 36 adults and 20 unknown whales (Table 2). Sighting history (LSH, age class and repro-
ductive status) and sampling information (area, season) as well as hormone concentrations for
each whale are summarized in S1 Table.
Given the unique opportunity to evaluate trends in hormone concentrations in multiple
samples from the same animals, we analyzed repeated samples separately. Repeated samples
were collected from 8 females and 5 males of different age classes or reproductive states, at dif-
ferent times of the year and were used to test seasonal differences in hormone concentrations
(Table 3). Because of the limited sample size, we combined calves and juveniles in one age
class group (calf/juvenile) for statistical analysis.
Table 3. Minimum age, reproductive state, date of sampling, season, area, and progesterone or testosterone concentrations in repeated samples collected from
eight females and five males.
FEMALES (n= 8)
CRC ID Min Age Age class (reproductive state) Date of sampling Season Area Progesterone (ng/g)
92 19 adult (pregnant) 8/6/12 Summer WA 14.8
22 adult (unknown) 9/30/15 Fall BC 10.7
196 14 adult (unknown) 7/29/10 Summer WA 1.6
19 adult (pregnant) 10/27/15 Fall BC 11.2
525 10 adult (unknown) 9/14/10 Summer WA 0.2
15 adult (lactating) 10/6/15 Fall BC 2.0
826 6 unknown (unknown) 9/20/10 Summer WA 0.8
11 adult (unknown) 10/20/15 Fall BC 2.4
860 1 calf/juvenile (immature) 9/23/04 Fall WA 6.0
9 adult (unknown) 8/1/12 Summer WA 1.5
1053 0 unknown (unknown) 10/30/08 Fall WA 19.7
5 unknown (unknown) 6/29/13 Summer WA 2.4
1172 3 unknown (unknown) 8/6/12 Summer WA 2.2
6 unknown (unknown) 10/5/15 Fall WA 0.7
1512 1 calf/juvenile (immature) 10/4/13 Fall WA 2.
2 calf/juvenile (immature) 6/23/14 Summer WA 6.0
MALES (n= 5)
CRC LSH Age class Date of sampling Season Area Testosterone (ng/g)
510 15 adult 10/27/15 Fall BC 10.0
10 adult 9/19/10 Summer CA 0.3
714 13 adult 10/29/15 Fall OR 2.7
9 adult 9/20/11 Summer WA 0.2
1303 4 calf/juvenile 9/30/15 Fall BC 0.2
3 calf/juvenile 7/15/14 Summer WA 0.2
1604 2 unknown 9/30/15 Fall BC 0.4
0 unknown 8/21/13 Summer WA 1.0
1693 0 calf/juvenile 6/22/13 Summer WA 0.5
2 calf/juvenile 10/18/15 Fall BC 1.5
LSH, length of sighting history; BC, British Columbia; WA, Washington; CA, California; OR, Oregon.
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Assay validation and steroid hormones measurements
For hormones extractions, we cut blubber biopsies by length. Masses of the subsamples
weighed between 0.03 and 0.19 g (mean (±SD) = 0.11 (±0.03) ng/g) and were placed into
12 ×75 mm borosilicate glass tubes. We followed the extraction protocol reported in Atkinson
et al. [29] and Melica et al. [54], modified from the methods by Mansour et al. [25], and Kellar
et al. [53]. Briefly, we manually macerated each blubber sample in 500 μl ethanol using a Teflon
tissue homogenizer and centrifuged at 3,000 rpm for 20 min. We poured the supernatant off
into a clean tube and repeated this step. We added the supernatant from the second extraction
to the supernatant from the first extraction and dried it under forced air. To the dried extract,
we added an aliquot of 2 ml of ethanol:acetone (4:1), vortexed, and centrifuged for 15 min. We
then poured the supernatant into a new glass tube and dried it under forced air. To each tube
we added one milliliter of diethyl ether, vortexed, centrifuged for 15 min, transferred to clean
glass tubes, and dried under forced air. For the final extraction, we added 1 ml of acetonitrile
to each residue and vortexed, then we added 1 ml of hexane and vortexed. We centrifuged the
samples for 15 min, recovered the acetonitrile and extracted it again with additional 1 ml of
hexane. At this final step, we removed the hexane layer, and dried the acetonitrile residue
under forced air. Extracts were stored frozen at -20˚C until assayed.
We measured testosterone and progesterone concentrations using enzyme immunoassay
(EIA) techniques (Arbor Assay Kits, Ann Arbor, MI, K032-testosterone and K025-progester-
one), which were read with a plate reader Tecan INFINITE 200M NANO. For EIA analysis, we
rehydrated extracts with 1 ml of methanol and aliquoted based on the dilution required for each
assay. Specifically, we transferred into clean tubes 125 μl of methanol from each extract tested
for testosterone, and between 15 and 125 μl from samples tested for progesterone. After drying
the methanol aliquots under forced air, we added 125–150 μl of assay buffer to each tube. To
validate each assay kit, we created a male and a female pool using extracts from 8 biopsied and 4
stranded males and from 12 biopsied and 10 stranded females, respectively, and tested for paral-
lelism and accuracy. We used two separate pools of pregnant and non-pregnant females to test
the testosterone assay for parallelism, but due to limited extracts volume, we combined the two
pools for the accuracy test. The parallelism test evaluates whether the antibody from the assay
can reliably bind to the targeted hormone and determines the dilution at 50% binding; the accu-
racy check evaluates how precisely the measured concentrations correlate with the added con-
centrations of each hormone. Briefly, we serially diluted (1:1, 1:2, 1:4, 1:8 and 1:16) the pool of
extracts and tested for parallelism to the standard curve of each assay. Each standard curve was
made of 7 points fitting a four parameters logistic curve (4PLC): for testosterone, standards con-
centrations ranged from 40.96 pg/ml to 10,000 pg/ml, whereas for progesterone, from 50 pg/ml
to 3,200 pg/ml. To assess parallelism to the testosterone standard curve, we fitted a linear model
between 80% and 20% binding of the standard curves and to the dilutions of each pool. For the
progesterone assay, we fitted a 4PLC to the assay standards and dilutions of each pool using the
R package “drc” [64]. We tested for parallelism using a Student’s t-test to statistically assess the
difference in the slope parameter from the standard curve and each curve fitted to the extract
pools and considered lack of significance evidence of parallelism [65]. For testosterone, the dilu-
tion at 50% binding was 1:1 for all three tested pools (males, pregnant and non-pregnant
females). For progesterone, the dilutions binding close to 50% were 1:1 for the pool of males
extracts and 1:4 for the pool of females extracts. For the accuracy test, we spiked the assay stan-
dards for each hormone kit with an equal volume of sample pool. We plotted and tested the
recovered against the added hormone mass for linearity We assayed all standards, zero-stan-
dards (or total binding, B0) and all samples in duplicate; we corrected raw concentrations data
(pg/ml) for dilution factor and blubber mass, and expressed the final value as ng/g.
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The intra-assay percent coefficient of variation (CV) was <10% for both hormones. If any
sample had a CV >10%, we re-diluted it accordingly and re-assayed. We determined inter-
assay validation using two internal controls for testosterone and progesterone respectively.
CVs for the two controls were 11.1% and 14.3% for the testosterone assay and 6.5% and 11.3%
for the progesterone assay.
Statistical analysis
We tested testosterone and progesterone concentrations for normality and homogeneity of
variances using Shapiro-Wilk and Bartlett’s tests (Package: stats [66]) as part of exploratory
data analysis. Based on these results, we log-transformed testosterone and progesterone con-
centrations to meet statistical requirements of independence and normality. We evaluated the
relationship between hormone concentrations and extracted blubber mass using Pearson cor-
relation (Package: stats [66]) coefficients with alpha level of 0.05 for statistical significance. All
figures but one (Fig 2) showed hormone concentrations back-transformed from the log-scale.
We conducted all statistical and graphical analyses using the software R v. 4.0.4 [66].
In order to test testosterone concentrations in response to age, we applied quantile regres-
sion and linear regression using a generalized least square approach to log-transformed testos-
terone concentrations from a subset of males that could be classified either as calf (n= 4),
immature (n= 6) or adult (n= 16), using the function “rq” (Package: quantreg [67]) and “gls”
(Package: nlme [68]). The quantile regression tested the relationship between the 5
th
percentile,
the median and the 95
th
percentile of testosterone and LSH, whereas the linear regression
tested for an increase in mean testosterone with LSH, while accounting for an increase in
Fig 2. Median and mean log-transformed testosterone concentrations (ng/g) of gray whale males against length of
sighting history (LSH). Top graph: quantile regression indicated significant increase in the median testosterone
concentration in the 95
th
percentile (P<0.001; solid line), but not in the 5
th
percentile (P = 0.9; dashed line); the
analysis indicates that the highest levels of this hormone increase with age, but the lower concentrations do not.
Bottom graph: linear regression with unequal variance indicated a significant increase of mean testosterone
concentrations in response to LSH (P= 0.03).
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variance with the mean. We analyzed testosterone concentrations in adult males (n= 16) for
seasonal differences using a two-tailed Student’s test (Package: stats [66]) with equal variance
by season (summer and fall), and in females for differences among reproductive states using
an ANOVA test, followed by a Tukey post-hoc test.
To determine any significant difference in progesterone concentrations among whales of
known sex (male and female), age class (calf, immature, adult) and reproductive states (calf,
immature, lactating and pregnant), we used an ANOVA test assuming unequal variances fol-
lowed by pairwise t-test. We then estimated the probability of being pregnant for each non-
calf female of known and unknown reproductive status. We used the Expectation-Maximiza-
tion (EM) algorithm (Package: mixtools [69]) to fit two normal distributions to log-trans-
formed progesterone concentrations from all non-calf females, with the assumption that at
least two groups would be identified: one cluster of low (non-pregnant) and one of high (preg-
nant animals) progesterone. We calculated the probability of pregnancy at each progesterone
concentration as the ratio of the probability density for the high progesterone group to the
sum of the two probability densities, assuming that the normal distribution with the larger
mean corresponds to the distribution of progesterone concentrations for pregnant females.
We then developed a bootstrap approach, similar to the one applied for humpback whales in
Pallin et al. [27] and for blue whales in Melica et al. [54] to quantify the 95% confidence inter-
val around each probability estimate, where progesterone concentrations were re-sampled
with replacement 10,000 times. Given the small number of individuals in the "high-progester-
one" group we included the four known pregnant females in each bootstrap sample. The prob-
ability of pregnancy was estimated for each bootstrap sample and only realistic bootstrap
samples resulting in probabilities that asymptotically approached 1 at high progesterone con-
centrations (90% of total bootstrap samples) were retained. Finally, the 2.5
th
and 97.5
th
percen-
tiles of the bootstrapped probabilities at each progesterone concentration were used to
construct the 95% confidence band for the estimated probability of pregnancy. We estimated
the probability with 95% confidence intervals (CI) for each individual of unknown reproduc-
tive status.
For the repeated samples (n= 13, five unique males and eight unique females), we analyzed
log-transformed hormone concentrations in response to age class and season, using an
ANOVA test with correction for repeated samples.
Results
Analytical validation
The testosterone assay validated for males, passing the parallelism (P = 0.3) and accuracy
(y= 1.2x-44.5; R
2
= 0.99) tests. For females with serial dilutions from both pools (pregnant and
non-pregnant), the testosterone assay displayed curves parallel to the standard curve (P = 0.1
and 0.2). The combined female pool (both pregnant and non-pregnant) was tested for accu-
racy and the spiked standards showed linear relationships with the standards (y = 1.2x-186.3;
R
2
= 0.98).
The progesterone assay validated for both females and males with serial dilutions exhibiting
parallel displacement to the standard curve (P= 0.2 and P= 0.6, respectively) and the spiked
standards showing linear relationships with the added standard mass (female: y= 1.0x-20.6; R
2
= 0.99 and male: y= 1.0x-63.6; R
2
= 0.99).
Testosterone
We measured testosterone concentrations in blubber of 40 male gray whales with a minimum
age ranging from <1 year old to 22 years of LSH. Concentrations ranged from 0.1 to 9.8 ng/g
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and the mean (range) for each age class are reported in Table 1. We found no significant corre-
lation between testosterone concentrations and mass of blubber extracted (r= 0.2, P= 0.2).
The quantile regression showed that there was a significant increase in the 95
th
percentile of
testosterone concentrations (P<0.001), but not in the 5
th
percentile (P= 0.9), implying that
the highest levels of this hormone increase with age, but the lower concentrations do not (Fig
2). The overall increase in median testosterone concentrations with LSH was not significant,
but the linear regression assuming unequal variance indicated a significant increase in mean
testosterone concentrations with LSH (P= 0.03) (Fig 2).
Testosterone concentrations in adult whales showed high variability, ranging from a mini-
mum of 0.1 ng/g to a maximum of 9.8 ng/g. Adult males had a significantly higher mean tes-
tosterone concentration in the fall (3.9 ng/g, n= 6) than in the summer (0.7 ng/g, n= 10) (t=
-2.9, df = 14, P= 0.01) (Fig 3).
We detected and measured testosterone concentrations in 18 females from the pregnant
(n= 4), lactating (n= 3), immature (n= 6), calf (n= 3) and adult unknown (n= 2) groups
(Table 2 and Fig 4). There was no statistical difference in testosterone concentrations among
reproductive groups (ANOVA: F= 1.9, df = 4, P= 0.2).
Progesterone
We measured progesterone concentrations in a total of 66 females, with minimum age from
young of the year to 32 years of LSH and concentrations ranged from 0.6 ng/g to 61.7 ng/g
(Table 2). We also detected and measured progesterone concentrations in nine individual
males, of which four were categorized as calves, one as immature, and four as adult (Table 1).
We found no significant correlation between progesterone concentrations and mass of blubber
Fig 3. Mean testosterone concentrations (ng/g) were significantly higher in adult males sampled during the fall
than during the summer (P<0.05). Boxplots denote median (thick line), upper (75%) and lower (25%) quartile
(boxes) and largest and smallest value within 1.5 times interquartile range below 25% and above 75% (whiskers).
Outside values are shown as filled circles.
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extracted (r= 0.09, P= 0.4). The comprehensive dataset with females and males of known sta-
tus was analyzed with an ANOVA test assuming unequal variances followed by a pairwise t-
test that indicated concentrations of progesterone to be significantly different among groups
(ANOVA: F= 34.6, df = 5.00, P<0.001). Specifically, we found that females in the pregnant
group had significantly higher concentrations than whales from the lactating (P<0.001),
immature (P<0.001) and calf (P= 0.04) groups (Fig 5), but progesterone concentrations did
not vary significantly among females from non-pregnant groups (lactating, immature and
calf). Our analysis also indicated that progesterone concentrations were significantly lower in
adult males than in any female reproductive groups (pregnant P<0.001; lactating P<0.001;
immature P= 0.001 and calf P= 0.02) and in male calves (P<0.001) (Fig 5).
The mixture model suggested that progesterone concentrations from all non-calf females
could be best described as a mixture of two normal distributions: the first distribution identi-
fied a cluster of whales with low progesterone concentration (mean = 2.0 ng/g (95% CI: 0.6–
6.3 ng/g) and included all whales known to be non-pregnant (e.g., lactating and immature)
and the second a cluster of whales with high progesterone concentration (mean = 16.9 ng/g
Fig 4. Testosterone concentrations (ng/g) in gray whale of different reproductive states (females) and age class
(males). In females, testosterone concentrations were not statistically different among reproductive groups (ANOVA:
F= 1.9, df = 4, P= 0.2). Boxplots denote median (thick line), upper (75%) and lower (25%) quartile (boxes) and largest
and smallest value within 1.5 times interquartile range below 25% and above 75% (whiskers). Outside values are shown
as filled circles.
https://doi.org/10.1371/journal.pone.0255368.g004
Fig 5. Progesterone concentrations in female and male gray whales. Differences in concentrations were statistically
different among reproductive groups for female and male gray whales (ANOVA: F= 31.09, df = 6.00, P<0.001) of
known reproductive status. Boxplots denote median (thick line), upper (75%) and lower (25) quartile (boxes) and
largest and smallest value within 1.5 times interquartile range below 25% and above 75% (whiskers).
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(95% CI: 4.8–59.6 ng/g), and included all females confirmed pregnant (Fig 6). The areas of the
curves had a 4.5% overlap. Based on these distributions, the model identified 50% probability
of being pregnant corresponding to a progesterone concentration of 6.5 ng/g and we calcu-
lated the probability of pregnancy for all non-calf females (Table 4). The model found corrobo-
ration in the probabilities of pregnancy estimated for whales of known reproductive status: all
known pregnant females (n= 4) had an estimated probability of being pregnant of 100%,
while the probability for all known non-pregnant whales (e.g., lactating and immature; n= 12)
was lower than 5% (Table 4). The probability of being pregnant ranged from less than 0.01%
to 100% for adult females of unknown reproductive status (n = 26) and for whales of unknown
age class and reproductive status (n= 20) (Table 4). Probabilities of being pregnant showed
high uncertainty (i.e., broad 95% CI) in whales with intermediate progesterone concentrations
(between 5 and 10 ng/g).
Repeated samples
A total of eight females and five males were sampled twice, in summer and in fall, although not
necessarily in the same year. The repeated samples comprised of different age classes and
reproductive status (Table 3). In females, the mean progesterone concentration was 3.7 (range
0.2–14.8) ng/g for samples collected in the summer months and 6.8 (range 0.7–19.7) ng/g for
those collected in the fall. We found no significant differences in progesterone concentrations
between seasons (ANOVA: F= 1.1, df = 1, P = 0.3), age class (F= 0.1, df = 2, P = 0.9) or the
combination of both (F= 0.4, df = 2, P = 0.7). In males, the mean (range) testosterone
Fig 6. Probability of being pregnant based on progesterone concentrations for all non-calf females, with 95%
confidence band calculated using a bootstrapping approach. Shapes of points indicate whales confirmed non-
pregnant (immature and lactating; empty circle), pregnant (empty triangle) and unknown (age class unknown and
adult; black diamond).
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Table 4. Percent probability of being pregnant assigned to each female gray whale of known and unknown reproductive status. For each whale the probability was
calculated based on the progesterone concentration (ng/g), using the two distributions identified via mixture model. Additional information included is feeding group, age
class, the year and month of sampling and the year of subsequent sighting including whether with a calf.
CRC
ID
Feeding
group
Age class Reproductive
status
Progesterone ng/
g
Percent probability of being
pregnant
Year of
sampling
Month of
sampling
Year of
resighting
860 PCFG Immature Immature 3.5 3.3 2004 September 2005
1512 PCFG Immature Immature 2 0.2 2013 October 2014
1559 PCFG Immature Immature 2.3 0.3 2015 October 2016
1622 PCFG Immature Immature 0.7 <0.01 2015 October 2016
1736 PCFG Immature Immature 2.7 0.8 2015 October 2016
1822 PCFG Immature Immature 1.7 <0.1 2015 October 2016
67 PCFG Adult Lactating 3.6 3.9 2004 August 2005
178 PCFG Adult Lactating 3.3 2.5 2013 July 2014
372 PCFG Adult Lactating 1.7 <0.1 2015 August 2016
525 PCFG Adult Lactating 2.0 0.15 2015 October NA
719 PCFG Adult Lactating 1.5 <0.1 2015 October 2016
827 PCFG Adult Lactating 1.5 <0.1 2015 September 2018
92 PCFG Adult Pregnant 14.8 99.1 2012 August 2013 (with calf)
193 PCFG Adult Pregnant 21.2 99.9 2015 October 2016 (with calf)
196 PCFG Adult Pregnant 11.2 95.8 2015 October 2016 (with calf)
280 PCFG Adult Pregnant 30.8 99.9 2015 October 2016 (with calf)
30 PCFG Adult Unknown 17.3 99.7 (95–100) 2015 October 2016
94 PCFG Adult Unknown 1.5 <0.1 (7.4x10
-8
–3.1) 2010 October 2011
127 PCFG Adult Unknown 0.7 <0.01 (1.4x10-13–1.3) 2010 September 2011
141 PCFG Adult Unknown 9.1 87.4 (40–99.8) 2005 July 2006
143 PCFG Adult Unknown 7.5 68.4 (13–99) 2015 October 2016
192 PCFG Adult Unknown 20.8 99.9 (97–100) 2011 August 2012
204 PCFG Adult Unknown 0.8 <0.01 (5.1x10-12–1.3) 2010 July 2011
231 PCFG Adult Unknown 3.5 3.3 (8.9x10-3–41.9) 2014 September 2017
238 PCFG Adult Unknown 1.3 <0.1 (0.3x10-7–2.5) 2015 October 2017
242 PCFG Adult Unknown 27.3 100 (99.2–100) 2015 September 2018
302 PCFG Adult Unknown 0.9 <0.01 (4.6x10-11–1.5) 2010 September 2011
396 PCFG-NPS Adult Unknown 0.9 <0.01 (2.6x10-11–1.4) 2010 September 2011
531 NPS Adult Unknown 20.4 99.8 (97.8–100) 2016 March 2018
532 PCFG Adult Unknown 5.8 34.4 (1.8–93.8) 2012 July 2013
554 PCFG Adult Unknown 4.4 10.8 (0.1–71.6) 2015 October 2016
629 PCFG Adult Unknown 1.9 0.1 (2.3x10-6–5.7) 2015 October NA
637 PCFG Adult Unknown 48.9 100.0 (99.8–100) 2013 August 2018
657 PCFG Adult Unknown 1.2 <0.1 (4.9x10-9–2.2) 2015 October 2016
659 PCFG Adult Unknown 1.8 0.1 (1.5x10-6–5.3) 2012 July 2014
668 PCFG Adult Unknown 2.7 0.7 (2.8x10-4–17.3) 2012 July 2014
698 PCFG Adult Unknown 8.5 82.9 (30–99.7) 2015 September 2016
759 PCFG Adult Unknown 2.2 0.3 (2.7x10-5–9.5) 2015 October NA
760 PCFG Adult Unknown 3.0 1.4 (3.5x10-4–18.4) 2015 September NA
872 PCFG Adult Unknown 4.8 15.1 (0.2–80.2) 2013 August 2015
900 PCFG Adult Unknown 11.4 96.2 (73–99.9) 2015 October 2018
1067 PCFG Adult Unknown 1.6 <0.1 (1.6x10-7–3.5) 2015 September NA
826 PCFG Unknown Unknown 0.8 <0.01 (6.3x10-12–1.3) 2010 September 2016
842 PCFG Unknown Unknown 2.7 0.8 (3.5x10-4–18.4) 2004 September 2005
1053 PCFG Unknown Unknown 19.7 99.8 (97.5–100) 2008 October 2012
(Continued)
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concentrations were 0.4 (0.2–1.0) ng/g for samples collected in the summer and 2.9 (0.2–9.9)
ng/g for those collected in the fall (Table 3). We found no statistical difference in testosterone
concentrations in response to age class (F= 1.2, df = 2 P = 0.4), season (F= 4.5, df = 1, P = 0.1)
and the combination of both (F= 3.4, df = 2, P = 0.1).
Discussion
The present study validated and measured sex steroids using EIA techniques in 119 blubber sam-
ples of gray whales in order to improve the knowledge on the reproductive endocrine processes
in this species. Our results indicated that testosterone concentrations in males increased with age
until the animals reached maturity and then they varied by season. Specifically, adult males sam-
pled in the fall had higher blubber testosterone concentrations compared to animals sampled in
the summer, suggesting physiological preparation for reproduction. In our female dataset, we
confirmed progesterone concentrations as a biomarker for pregnancy and developed an analyti-
cal model for estimating the probability of being pregnant for female whales of unknown repro-
ductive status. Results from our study complement previous studies that validated and measured
steroid hormones in baleen and fecal tissue using EIA [33,34] and in blubber using nanospray
Liquid Chromatography/tandem Mass Spectrometry (nanoLC/MS/MS) [32].
Testosterone
In the present work, our results indicated that mean testosterone concentrations in male gray
whales generally increased with age, indicating that the development of male sexual character-
istics is a function of age. This result is consistent with other studies: for example, Rice and
Wolman [19] examined testes from immature and adult male gray whales and observed sper-
matogenesis in seminiferous tubules from adult males. They also indicated open and wider
seminiferous tubules as well as bigger testes weights as indicators of sexual maturity and onset
Table 4. (Continued)
CRC
ID
Feeding
group
Age class Reproductive
status
Progesterone ng/
g
Percent probability of being
pregnant
Year of
sampling
Month of
sampling
Year of
resighting
1059 PCFG Unknown Unknown 61.7 100.0 (99.8–100) 2008 October 2009
1118 PCFG Unknown Unknown 3.1 1.6 (1.8x10-3–27.8) 2015 September 2016
1172 PCFG Unknown Unknown 2.2 0.3 (2.0x10-5–8.8) 2012 August 2013
1201 PCFG Unknown Unknown 0.6 <0.01 (4.7x10-14–1.3) 2012 July 2013
1551 PCFG Unknown Unknown 1.7 <0.1 (7.2x10-7–4.5) 2012 August 2013
1597 ENP Unknown Unknown 2.5 0.5 (9.5x10-5–13) 2013 October NA
1598 ENP Unknown Unknown 29.1 100 (99.5–100) 2013 October 2014
1600 ENP Unknown Unknown 12.2 97.5 (80.8–99.9) 2013 September NA
1602 ENP Unknown Unknown 8.4 81.7 (29.4–99.6) 2013 September NA
1646 PCFG Unknown Unknown 1.7 <0.1 (5.1x10
-7
–4.2) 2015 October NA
1681 PCFG Unknown Unknown 21.3 99.9 (98.3–99.9) 2014 September NA
1868 PCFG Unknown Unknown 1.1 <0.01 (4.4x10-10–1.7) 2015 September 2016
1870 ENP Unknown Unknown 5.1 20.5 (0.5–86.3) 2015 July NA
1872 ENP Unknown Unknown 4.1 7.0 (0.04–60) 2015 August NA
1881 ENP Unknown Unknown 4.2 8.3 (0.06–65) 2015 August NA
1890 ENP Unknown Unknown 1.3 <0.1 (0.1x10
-7
–2.5) 2015 September NA
1899 ENP Unknown Unknown 1.4 <0.1 (0.4x10
-7
–2.9) 2015 October NA
PCFG, Pacific Coast Feeding Group; NPS, Northern Puget Sound; ENP, Eastern North Pacific; NA, no resighting data available.
https://doi.org/10.1371/journal.pone.0255368.t004
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of mating. Specifically, diameters of seminiferous tubules were higher in mature animals dur-
ing the southbound migration [19]. In other mysticete species, lower concentrations of testos-
terone have been observed in immature compared to mature humpback and fin whales [41,
70], with increased variability observed mainly in adult animals suggesting that other variables
(e.g., season) likely affect concentrations of this hormone. Similarly, when we analyzed testos-
terone concentrations using quantile regression, we found that only elevated concentrations
increased significantly with age (Fig 2), whereas lower concentrations did not. This means that
in older males, variability in testosterone concentrations is broader, hinting that there might
be other factors (e.g., season) affecting hormone levels in adult males.
Cyclicity or seasonal trends in testosterone concentrations from a variety of tissue types
have been reported for humpback, blue, fin, and North Atlantic right whales [31,41,54,59,60,
70], with elevated concentrations in the months approaching the breeding season, indicating
physiological preparation to mate. The present study found blubber testosterone concentra-
tions had higher variability in adult males (range 0.1–9.8 ng/g), leading to the hypothesis of a
seasonal trend. Statistical analysis indicated testosterone concentrations to be significantly
higher in animals sampled in the fall compared to samples collected in the summer (Fig 3),
supporting seasonality as the main explanatory factor. All adult males analyzed for seasonal
changes in testosterone were identified as part of the PCFG, and sampled between June and
October, while on their feeding grounds. Increased testosterone concentrations over time
likely indicate preparation for mating through spermatogenesis as the timing of migration
approaches. Repeated samples from two adult males support these results, as both animals had
at least 10 times higher testosterone concentrations in blubber collected in the fall (Table 3)
compared to their respective samples from the summer. Increased sample size and analysis of
samples collected between December and May, while the animals are in their northward and
southward migratory flow, is necessary to have a more complete understanding of the testos-
terone annual cycle.
We validated and measured testosterone concentrations in female gray whales, and when
compared across reproductive states we found that immature females had generally high con-
centrations when compared to mature females. Among adult females, lactating whales had tes-
tosterone concentrations twice as high compared to pregnant animals, although these
differences were not statistically significant (Fig 4). Elevated androgens (i.e., testosterone) were
found in blubber of female humpback whales close to parturition [71] and in feces of pregnant
and lactating North Atlantic right whales [61]. The pregnant females in the present study were
all sampled at least two months before the estimated parturition date (late December–early
January [19]). Thus, their blubber testosterone might not reflect a spike in androgens occur-
ring in late gestational phase. On the other hand, elevated blubber testosterone in lactating
females may be the delayed result of such surge, whereas in calves the consequence of maternal
transfer in milk. In preparation for lactation, pregnant gray whales increase their weight dur-
ing the feeding season 25–30% more than whales in other reproductive states [5,19]. Further,
the milk of gray whales has the highest fat content (53%) among cetaceans [72,73]. During
migration and lactation, the accumulated body fat and blubber are used as energy sources and
transferred to the calf. Maternal offloading of contaminants and trace metals has been docu-
mented for this species [42] and other whales (e.g., fin whales [74]), suggesting that lipophilic
steroid hormones are likely also transferred.
Progesterone
Our study provides evidence that progesterone can be used as an indicator of pregnancy, as
significantly elevated concentrations were found in females confirmed as pregnant (Fig 5)
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compared to other reproductive states. In addition, we developed a model that used progester-
one concentrations from non-calf females to calculate the probability of being pregnant and
their 95% confidence intervals (Table 4). The model indicated that female whales with known
reproductive status, that is known pregnant whales, had an estimated probability of being
pregnant higher than 95%, whereas known non-pregnant females (e.g., lactating and imma-
ture whales) had less than 5% estimated probability of being pregnant. Using these whales as
references it is reasonable to conclude that all whales with probability higher than 95% were
likely pregnant, while all whales with probability lower than 5% were likely non-pregnant at
the time of sampling. With the thresholds developed from these probabilities, we hypothesized
that out of 46 whales of unknown reproductive status (both in the adult and unknown age
class), 11 were likely pregnant and 25 likely non-pregnant. The remaining ten individuals had
mid-range progesterone concentrations and resulting intermediate probabilities with high lev-
els of uncertainty (expressed as 95% confidence band; Fig 6), thus they could not be assigned a
reproductive status accurately.
Of the likely pregnant whales, four were sighted the year after sampling not accompanied
by a calf in late summer or fall. It is possible that these females had calves which had already
been weaned by the time of their sighting in the subsequent year; however, whales in the lactat-
ing group were sampled between July and October, and whales in the calves group between
June and November, suggesting that calves tend to stay close to their mothers on the feeding
grounds [19,75].
A high probability of pregnancy but no sighted calves the subsequent year might also be a
result of reproductive failure, through either the loss of a calf post-parturition or the loss of the
fetus, also referred to as a spontaneous abortion [76,77]. Calf mortality in gray whales has
been reported to be high. Specifically, Swartz and Jones [78] suggested a 31% decrease in the
number of calves between those counted in the Mexican lagoons and the calves counted
migrating past Central California with their mothers. Accordingly, 60% of calf mortality was
estimated to occur south of 49˚N [79]. Finally, it is possible that some of the 11 likely pregnant
females were primiparous (i.e., in their first pregnancy). Calves of primiparous females in
marine mammals often have lower survival than calves born to multiparous (i.e., that had
given birth at least once) females. For example, multiparous bottlenose dolphins showed
higher calves survival [80] and older Antarctic fur seals (Arctocephalus gazella) had greater
reproductive performance than younger ones [81]. Based on the CRC catalog, only one of
these females was sighted with a calf before the sampling occurred (CRC 242), so it is possible
that despite a LSH longer than 8 years, these whales might have been in their first pregnancy.
Furthermore, we were not able to assign five of these females to the adult age class, as they had
a limited LSH (S1 Table), thus they could have been young individuals.
Elevated progesterone may also be the result of ovulation; however, few studies have
reported that endocrine biomarkers for ovulation can be detected in blubber tissue [82]. In
minke whales, no significant difference was found between blubber progesterone in ovulating
and pregnant females [82]. Other hormones, such as estrogens or luteinizing hormone may be
more informative of ovulation [83–85], but likely because of their pulsatile action they are
more easily detectable in serum, urine [84] or feces [61].
Ten whales had an estimated probability of being pregnant between 6% and 90% and broad
confidence intervals in most cases. Medium to high progesterone concentrations may reflect
different stages of the ovulatory cycle. Rice and Wolman [19] estimated that females ovulate
between late November and early December, with potentially later ovulations if there was a
failure in conception. The samples mentioned above were collected between the months of
July and October, indicating their progesterone concentrations are unlikely to be a reflection
of ovulation.
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Pseudopregnancy could be an alternative explanation for mid to high progesterone concen-
trations. It consists of the retention of a corpus luteum, despite the lack of conception, for an
amount of time longer than normal [37]. Pseudopregnancy is known to occur in many odon-
tocetes species, often in a recurring pattern [85], but there is no evidence for baleen whales.
More than half of the whales with unknown reproductive status had a probability of being
pregnant lower than 5% (25 out of 46), with about half sighted the year after sampling not
accompanied by a calf. Of the remaining, three were sighted two years after the year of sam-
pling, one 6 years later and eight had no resightings recorded. Low progesterone concentra-
tions and absence of calf might be indicative of females in a resting status or that have not
reached sexual maturity. Fecal progesterone concentrations in resting whales were similar to
those categorized as lactating, for blue whales [30] and North Atlantic right whales [61]. In
feces from PCFG gray whales categorized as resting, the mean progesterone concentration was
similar to the mean for immature females, and about half the mean concentration for pregnant
females [34]; however, in Lemos et al [34], the range of concentrations in resting females
appears to be pretty broad and overlaps with that of pregnant females. Furthermore, no signifi-
cant difference in blubber progesterone concentrations was found between resting, ovulating
and pregnant minke whales [82]. The same study, however, found significantly lower proges-
terone concentrations in immature whales, indicating this biomarker can be used to differenti-
ate between immature and mature females for that species [82].
In the present study, the applied age of sexual maturity is based on Rice and Wolman [19],
which estimated mean age of sexual maturity at 8 years old (with a range from 5 to 11 years)
based on earplug growth layers and gonads; however, it is possible that this parameter has
changed over the past 50 years and it requires reanalysis and clarification [20], especially if
applied to a distinct feeding group such as the PCFG. Age of sexual maturity is density-depen-
dent [86], and it is assumed to increase in high-density populations [87]. Both the ENP gray
whale population and the PCFG have increased over the last several decades [8,88], and it is
possible that the age of sexual maturity has also increased. Updated estimates of this parameter
are necessary for more precise and accurate analyses of whales in different reproductive states.
Despite the complexity in clearly categorizing each individual, it is noteworthy that the
female dataset in the present study reflects multiple reproductive states, with progesterone
clusters not limited to high and low classifications. The mixture model applied in this study
indicated a 4.5% overlap in the two distributions, confirmed also by overlapping of confidence
intervals. This is a somewhat bigger overlap than observed in similar studies in which a gap or
minimal overlap was found between groups with low and high concentrations [27,31]. How-
ever, results from work presented here confirmed that progesterone can be used as an indica-
tor of pregnancy, as demonstrated for other mysticete species [25,29,31,38,39,54]. While
absolute concentrations of hormones should not be compared unless proper interlaboratory
calibrations have been conducted, it is worth noticing that the mean progesterone concentra-
tion (19.5 ng/g; Table 1) in blubber of pregnant gray whales from the present study is low com-
pared to other species, sampled in their winter or summer grounds. For instance, although the
studies utilized different EIA kits, Melica et al. [54] reported a mean progesterone concentra-
tion of 81.4 ng/g in blubber of pregnant blue whales sampled in both winter and summer
grounds, whereas Atkinson et al. [29] reported a mean of 40.3 ng/g from biopsies of pregnant
blue whales in their winter grounds. A similar disparity is seen in feces: fecal samples from
pregnant gray whale sampled in their summer grounds had mean progestins metabolites of
157.4 ng/g [34], whereas in blue whales feces collected while the whales were in their wintering
grounds, mean progesterone was 1292.6 ng/g [30]. However, these studies were conducted in
different laboratories and used different EIA kits. In humpback whales, a species more compa-
rable in size to gray whales, calculated blubber progesterone thresholds for pregnancy are
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Hormones as biomarkers for reproduction in gray whales
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quite variable [71], ranging from 19.3 ng/g [27,28] to 55.0 ng/g [27], with data from different
laboratories. Progesterone accumulation in blubber is likely affected by physio-morphological
aspects (e.g., the species average size, blubber depth) and the time of sampling, likely reflecting
different gestational stages.
We also validated and measured progesterone concentrations in males (Fig 5). Our results
found that adult males had significantly lower progesterone concentrations than females from
any reproductive groups and male calves (Fig 5). Like testosterone, elevated progesterone in
calves is likely a result of maternal transfer and this hypothesis was further supported by the
fact that progesterone concentrations were not different between male and female calves.
Mean calving time for gray whales is the beginning of January and calves are normally weaned
6–7 months post-partum [19], indicating these calves could be 6–11 months old and thus
weaned. Progesterone concentrations were more variable in females (range:1.5–11.0 ng/g;
n= 4) than in males (range: 1.8–4.0 ng/g; n= 4) calves. However, the limited sample size did
not allow for an accurate comparison of progesterone concentrations over time of year, in
order to better understand the turnover of hormone in blubber.
Conclusions
The present study provides new fundamental information on concentrations of reproductive
hormones in blubber of gray whales. The results for male gray whales align with what was
found in other species, suggesting a seasonal cycle in testosterone concentrations in adult
males to be detectable in blubber tissue [31,54,89]. Elevated testosterone concentrations were
found in animals sampled between late September and October, likely indicating preparation
for mating. Furthermore, because all sampled adult males were part of the PCFG, this study
indicates that physiological preparation for reproduction begins while on their feeding
grounds. For female gray whales, the present study highlights the complexity of physiological
reproductive profiles, and the results presented here are innovative in developing a model to
calculate the probability of being pregnant based on progesterone concentrations. With most
samples collected from individuals in the PCFG, these data represent a milestone in better
understanding reproductive profiles in gray whales from this region, as well as in general for
gray whales. Based on these results, a more accurate estimate of key reproductive parameters
for gray whales is now possible.
Supporting information
S1 Table. Summary information for each individual whale (n= 106). For each individual
whale the following data are reported: NOAA SWFSC Marine Mammal and Sea Turtle
Research Collection identification number (T_ID), CRC ID, feeding group, sex, length of
sighting history, age class, reproductive status, location of sampling, progesterone (ng/g) and
testosterone (ng/g) concentrations.
(DOCX)
Acknowledgments
We thank the members of the research teams who collected the samples and thank the Makah
Tribal Council for access to samples collected by Makah Fisheries Management. Sighting his-
tory and genetic information were provided by CRC and SWFSC Genetics Laboratory. We
thank Kelly Robertson (SWFSC) for gathering and shipping archived samples and Alie Perez
(CRC) for providing sighting history information. We would like to thank Drs. Tamone, Gen-
dron, and DeMaster and Miss Silvia Valsecchi for feedback and comments on this manuscript.
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Hormones as biomarkers for reproduction in gray whales
PLOS ONE | https://doi.org/10.1371/journal.pone.0255368 August 3, 2021 18 / 23
Finally, we thank Dr. Mandy Keogh and the anonymous reviewer who provided revisions to
the improvement of this paper.
Author Contributions
Conceptualization: Valentina Melica, Shannon Atkinson.
Data curation: John Calambokidis, Aime
´e Lang, Jonathan Scordino, Franz Mueter.
Formal analysis: Valentina Melica, Franz Mueter.
Funding acquisition: Valentina Melica, Shannon Atkinson.
Investigation: Valentina Melica.
Methodology: Valentina Melica, Shannon Atkinson, Aime
´e Lang, Jonathan Scordino.
Resources: Shannon Atkinson, John Calambokidis, Aime
´e Lang, Jonathan Scordino, Franz
Mueter.
Supervision: Shannon Atkinson, John Calambokidis, Aime
´e Lang, Jonathan Scordino, Franz
Mueter.
Writing – original draft: Valentina Melica.
Writing – review & editing: Shannon Atkinson, John Calambokidis, Aime
´e Lang, Jonathan
Scordino, Franz Mueter.
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Hormones as biomarkers for reproduction in gray whales
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