Larger body size leads to greater female beluga fitness at the southern
periphery of their range
Steven H. Ferguson*1,2, David J.
Yurkowski1,2, Justine Hudson1, Tera
Edkins1, Cornelia Willing2, and
Cortney Watt1,2
1 Fisheries and Oceans Canada, Freshwater Institute,
Winnipeg, MB, Canada
2 University of Manitoba, Biological Sciences,
Winnipeg, MB, Canada
* corresponding author steve.ferguson@dfo-mpo.gc.ca
Abstract: Identifying phenotypic characteristics of evolutionarily fit
individuals provides important insight into the evolutionary processes
that cause range shifts with climate warming. Female beluga whales
(Delphinapterus leucas ) from the Canadian high Arctic (BB)
residing in the core region of the species’ geographic range are 14%
larger than their conspecifics at the southern periphery in Hudson Bay
(HB). We investigated the causal mechanism for this north (core)-south
(periphery) difference as it relates to fitness by combining
morphometric data with ovarian corpora counted in female reproductive
tracts. We found evidence for reproductive senescence in older HB
females from the southern peripheral population but not for BB whales.
Female beluga whale fitness in the more-northern BB increased faster
with age (48% partial variation explained) versus a more gradual slope
(25%) in HB. In contrast, body length in HB female beluga accounted for
five times more of the total variation in fitness compared to BB whales.
We speculate that female HB beluga fitness was more strongly linked with
body length due to higher density, as larger body size provides survival
advantages during seasonal food limitations. Understanding the
evolutionary mechanism of how fitness changes will assist conservation
efforts in anticipating and mitigating future challenges to peripheral
populations.
Key words: age, body length, Delphinapterus leucas , geographic
range, ovarian corpora
Introduction
Evolution occurs through natural selection whereby individuals with
greater fitness contribute disproportionately more of their genetic
information to future generations. Individuals of a species often
cluster into groups of genetically different populations due to
differences in environmental selection pressure (Orsini et al. 2008;
Coulon et al. 2008; Pauls et al. 2013). Population-level differences are
then geographically arranged along a continuum based on where the
population is located within the species’ range (Kirkpatrick and Barton
1997; Peterson et al. 2011). Sink populations at the periphery of a
species’ range are constantly in phenotypic flux due to the demographic
challenges of an environment that is at the limits of their evolved
traits (Gaston 2009; Sheth and Angert 2016). For biological
conservation, it is critical to understand the extent of species-level
plasticity that allows individuals to track extreme environmental
selection pressures at the edge of their geographic range in our rapidly
changing world (Hardie and Hutchings 2010; Valladeres et al. 2014).
To test this concept requires a fitness comparison of populations at the
core of the species’ distribution where individuals are presumably most
suitably adapted to their environment as opposed to populations at the
periphery where more phenotypic flux occurs. Lifetime reproductive
success is a fitness measure estimated as the number of recruited
offspring to the next generation that a parent produces over their
lifetime (Gustafsson 1986; Brommer et al. 2002). Reproductive success is
challenging to estimate in wild populations as long-term studies are
often required to monitor an appropriate number of individuals
throughout their lives (Newton 1989). Alternatively, researchers have
used female reproductive tracts from sustainably hunted individuals to
identify the number of ovarian corpora through lab examinations (Lehmann
1993; Nazarova and Evsikoy 2012; Ringsby et al., 2009). The ovaries of
many mammals provide an index of reproductive activity that functions as
a measure of fitness by recording the history of reproductive events and
number of lifetime ovulations (Perrin et al. 1984; Ellis et al., 2018).
During ovulation, an oocyte is released from the Graafian follicle with
the rupture site forming the corpus luteum (CL), a temporal bright
yellow, hormonal gland helping to promote and to maintain implantation
of the embryo. Subsequently, this body regresses to the corpus albicans
(CA) which is generally considered to persist within the ovarian tissue
throughout the life of a female whale even after diminishing in size and
color (Mackintosh, 1942; Laws, 1961; Fujino 1963).
Relating phenotypic characteristics to lifetime reproductive success can
provide important insight into evolutionary processes and allow
comparisons between populations that may indicate adaptation (Peterson
et al. 2019). In general, age is an important determinant of lifetime
fitness as older individuals have survived long enough to produce
numerous offspring (Sugiyama 1994; Festa-Bianchet et al. 2000; Saino et
al. 2012; Potti et al. 2013). Since age-effects directly correlate with
fitness, they provide little ecological information that could assist in
understanding fitness mechanism. Instead, research needs to assess the
relative contribution of variation in phenotypic traits, such as body
size, relative to fitness variation (Gaillard et al. 2000), to
understand key variables for survival and reproductive success.
Variation in body size is a key characteristic that can exhibit high
intra-specific differences in fitness contribution as observed in insects
(Sokolovska et al. 2000), pinnipeds (e.g., Le Boeuf & Reiter 1988),
ungulates (Clutton-Brock et al. 1988), rodents (Ribble 1992), and birds
(Davies et al. 1998). Large mammalian females are generally considered
to be capital breeders (Stearns 1992) and, therefore, should illustrate
a strong relationship between individual body size and reproductive
success. Despite relationships between fitness and body size being
investigated across several species groups, this relationship has not
been demonstrated in whales likely due to the logistical difficulties of
measuring adult body size and counting ovarian corpora in large whales.
There are 21 beluga whale (Delphinapterus leucas ) populations
across the Arctic providing a variety of geographic locations along the
continuum of their range (Hobbs et al. 2020). In collaboration with
annual Inuit subsistence harvests across the Eastern Canadian Arctic,
Fisheries and Oceans Canada have obtained a large collection of female
beluga whale reproductive tracts that include ovaries. To date, this
collection has revealed spatial differences in morphology, phylogenetic
history, demography and reproduction between individuals wintering in
the greater Hudson Bay (HB) region compared to those wintering in Baffin
Bay (BB) (Postma 2017; Ferguson et al. 2020). For this study, we chose
to compare the HB population which lives at the southern extreme of the
beluga whale geographic range (59o latitude) with the
BB population (73o latitude) that is considered to be
distributed within the core of their range. Our objective was to
determine whether spatial differences in fitness occurred between
peripheral HB and core BB regions while controlling for age.
Specifically, we determined how variation in reproductive fitness,
measured as total ovarian corpora counts (TC) relates to body size of
female beluga whale from both populations.
Methods
We conducted post-mortem gross examinations of 375 female reproductive
tracts, collected from three beluga populations (sometimes referred to
as stocks; high Arctic n=36, Cumberland Sound n=57, and Hudson Bay
n=282) across 17 northern communities within the Eastern Canadian Arctic
from 1989 to 2014 (Fig. 1). Ageing was based on examination of dentine
and cementum growth layer groups in teeth (Waugh et al. 2018). Whale
standard length was measured in the field according to a standard
protocol (American Society of Mammalogists, 1961). Body length in whales
is strongly correlated with mass (Trites and Pauly 1998).
We combined reproductive morphology data for Cumberland Sound and high
Arctic populations into a BB region based on similar
growth-age-reproduction relationship (Ferguson et al. 2020). We found no
significant differences in whale body length between the two
high-latitude populations, Cumberland Sound and high Arctic (ANCOVA:
F2,98 = 0.042, p = 0.96), and thus combined them for
further analyses.
Sample processing is described in more detail in Ferguson et al. (2020),
but briefly, ovaries were excised, weighed, measured and preserved in
10% neutral-buffered formalin. For each ovary, we recorded the number
of CL and CA (Best, 1968). In cetaceans CLs and CAs form distinct and
persistent features, accumulating within the ovary (Perrin et al. 1976)
as a record of a female’s reproductive history (Slijper 1962; Collet and
Harrison et al., 1972). Corpora assessments were performed by one reader
to minimize bias in the subjective determination of accessory corpora
(Harrison, 1977). As a measure of lifetime reproduction, TC for each
beluga whale were assessed by counting all existing CL and CA within the
ovaries (hereafter referred to as fitness). For whales with only one
ovary (23 of 97 whales from BB and 113 of 210 whales from HB), we
doubled the corpora count for the single ovary since beluga whales do
not appear to exhibit a left-dominance in ovarian function (Robeck et
al. 2010).
TC, body length, and age were normally distributed and parametric models
were used without data transformation. Data availability varied among
whales for age data [HB: 271 of 282, CS: 55 of 57 and HA: 33 of 36],
length data [HB: n=240, CS: n=56 and HA: n=29], and ovary
measurements [HB: n=79, CS: n=11 and HA: n=9]. To avoid including
sexually immature individuals in our analyses, we excluded whales that
were less than 250 cm in length (n=4).
Statistical analysis
All statistical analyses and graphics were performed using R statistical
software (v. 3.6.3). Cooks criteria was used to identify outliers and
resulted in the removal of two whales with TC greater than 25 and one
whale over 10 years of age without any corpora (all three from HB).
To test the relative effect of body size on fitness between the two
regions, we used general linear models (GLM) using a Poisson
distribution. We controlled the order of entry of the predictor
variables based on our expectation that age would explain the most
variation in fitness but that body length would be the variable of
interest (i.e., entered first into our model). Age and body length were
not significantly correlated for BB (r2 = 0.0075;
F1,19 = 0.143, p =0.71) whereas they were for HB
(r2 = 0.086; F1,79 = 7.40, p =0.008).
Here, we follow the “hierarchical analysis procedure” that requires
one to structure the analysis and interpretation of partials on the
order of entry (Cohen and Cohen 1975). We constructed a GLM that
included all combinations of covariates and interactions (body length,
age, region) and then successive steps in backward selection were guided
by Variance Inflation Factors (VIF) and information theory using
Akaike’s information criterion for small sample size (AICc). Covariates
with a VIF > 5.0 (Zuur et al., 2009) were used in separate
models. We calculated log-likelihood (LL), AICc values, ∆AICc, and AICc
weights (wi – relative likelihood of the model) using AICcmodavg
package in R (version 2.2-2, Mazerolle, 2019).
Once we had selected the parsimonious models, we tested the effects of
body size on fitness while controlling for whale age. We used the
partial correlation approach which measured the “unique” contribution
of an independent variable to R2 when a single
variable (age) is added to an earlier set of predictors (body length).
Partial correlation is identical to the square of the semipartial
correlation of Y (fitness) and length with the effects of age removed.
Results
The final dataset included 177 female reproductive tracts: 54 from BB
and 123 from HB. Following removal of outliers (see Methods), 144
samples remained for modeling (BB n = 34, HB n = 110).
Female beluga whales from the high-latitude BB region were found to be
4.7% longer (F2,98 = 11.33, p < 0.001) than
females from more southern HB (Gompertz asymptotic body length 370.9 cm
vs 354.4 cm; Fig. 2) which translated to 13.9% greater body mass (based
on growth equations in Heide-Jorgensen and Teilmann, 1994). Whales from
both regions had similar age distribution (Fig. 2).
To assess whether body length influenced fitness, we first assessed the
influence of region (BB and HB) in a complete model (TC
~ length*age*region). Due to high VIF (>5),
we reduced combinations by initially removing the three-way interaction
and re-running the model (TC ~ length*age + region).
Using the backwards step regression approach found support (AICc
< 3) for running the models separately by region (coefficient
= 3.638 ± 1.035; z-value = 3.516, p = 0.00044) among the available
variable combinations. Therefore, we contrasted BB with HB using
separate GLM models. To compare fitness, we regressed whale length
against TC (Step 1), then we included whale age (Step 2), and finally
added the interaction term length*age (Step 3) (Table 1).
The effect of length on fitness was assessed using partial correlations
to remove variation attributable to length and age. For BB, length
explained 2.4% of variation while controlling for age, whereas age
explained 48.2%. For HB, length explained 8.4% of the variation in
fitness while controlling for age, whereas age explained 24.7%. For BB,
the rate of increase in fitness with age was 1.5 times greater than HB
(0.50 versus 0.33 TC per year, t = -2.17, p = 0.031; Fig. 3), while the
rate of increase in fitness with length was similar (t = 0.53, p = 0.96;
Fig. 4). However, HB whales had a significant grade shift to overall
higher fitness for similar body lengths (t = 2.95, p = 0.0037). Length
explained 5% of the total variation in BB (2.4% / (2.4% + 48.2%) *
100%) compared to 25% of total fitness explained for HB (8.4% / 8.4%
+ 24.7%) * 100%). Assessing the pattern of changes in fitness with
age, HB beluga whales showed an asymptote in pregnancies at ages greater
than approximately 45 years; whereas, the BB populations did not show
this pattern (Fig. 5).
Discussion
Using a quantitative assessment of the effect of beluga whale body size
on female fitness, we found that a southern population at the periphery
of the species’ geographic range was more strongly influenced by body
size than population distributed within the core of their range. If this
finding holds for other species facing similar selective pressures from
climate warming, then our results provide critical information on the
mechanism of redistribution and underscore the limits to opportunities
for adaptive evolution in changing environments. Here, body size was
more important as a predictor of overall fitness (~five
times greater) for female HB beluga whales living at the southern edge
of their distribution compared to BB whales living in core regions
within the species distribution.
Sexual selection is a major evolutionary force selecting for larger male
body size for polygynous mating systems which predominate in mammalian
species (Ralls 1977). Beluga males are generally 13-14% larger than
females and this ratio did not appear to differ among populations across
North America despite spatial variation in relative whale size (Luque
and Ferguson 2010). For females, fecundity selection is a major driver
of body size, an adaptation that needs to be balanced with survival
(Pincheira‐Donoso and Hunt, 2017). For example, selection for large
female body size is eventually counterbalanced by opposing selective
forces that may include (1) increased risk from predation, parasitism,
or starvation because of their large size (e.g., reduced agility,
increased detectability, higher energy requirements, heat stress) and
(2) a longer development time to attain larger size which may result in
a later age of sexual maturity and decreased lifetime reproductive
success (Blanckenhorn 2000).
Linear increases in age with fitness are expected as the number of
offspring born to a female accumulates over time; however, non-linear
effects such as a decline in reproduction with advancing age are more
challenging to explain or confirm. For a limited number of wild
cetaceans, lifetime reproductive success of females has been shown to
asymptote at older age when they stop reproducing (Perrin et al., 1976;
Mizroch 1981; March and Kasuya 1984). The number of beluga CAs has been
found to increase up to approximately 40 years of age (Brodie 1972,
Heide-Jørgensen and Teilmann 1994, Suydam 2009, Ferguson et al. 2020).
We were able to detect a decline in pregnancy rate of older females
(>40 y) as reflected in TC, but this only appeared to occur
in the population at the southern limit of the species’ distribution.
However, as with some other beluga populations (Sergeant, 1973), we did
not document an obvious decline in corpora with age, although we had few
old females in our hunt sample which may have been due to a sampling
bias or to a demographic pattern for whales of the BB region. This
demographic pattern in BB beluga may indicate a growing young population
recovering from past overexploitation (Wade et al., 2012) or an evolved
life-history adaptation of a population selected for life in core range
(i.e., source vs sink; Kozłowski 1993).
It is not clear why female beluga fitness should be more strongly
correlated with body size in a population of smaller-bodied whales
living near the southern periphery of their geographic range. One
possibility is due to differences in trends in population abundance
since the greater relative density of beluga whales occurs in the
peripheral population (Luque and Ferguson 2010). Over evolutionary time,
food limitations may have selected for relatively smaller-bodied whales,
compared to core populations that are regulated by density-independent
ice entrapments (Heide-Jørgensen et al. 2002, Luque and Ferguson 2010).
Larger-sized females may be important in peripheral populations because
greater fat storage capability provides survival advantages during
seasonal food limitation (Lindsteadt and Boyce 1985) and increased
nursing duration for improved offspring growth and survival (Beauplet
and Guinet 2007).
Another consideration is the contrasting demographic history between the
two regions and how long-term changes in population dynamics can drive
differences in fitness. The peripheral population is possibly at
carrying capacity (Hammill et al. 2017) compared to the much lower
abundance of the core populations. The pristine, pre-commercial whaling
abundance of the BB population was estimated using modeling of harvest
levels to be double that of the most recent population abundance
estimate from 1996 of 21,213 belugas (Innes et al. 2002; Innes and
Stewart 2002). Although, the population growth trend has been
interpreted as suggesting an increasing population, the high Arctic
population as a whole is still considered depleted due to past
commercial whaling (Hobbs et al., 2020). Similarly, the Cumberland Sound
population is considered depleted due to past overharvesting from
commercial whaling practices (Sergeant and Brodie 1975) with a current
abundance estimated at 1,381 or 15% of the original estimated
population size (Watt et al. 2020). In contrast, the western Hudson Bay
population is considered to be possibly the largest in the world at a
minimum size of 54,473 beluga whales (Matthews et al. 2017). Although
considerable commercial harvesting of WHB beluga occurred over the past
century (Mitchell and Reeves 1981), the population is considered to be
currently at or near carrying capacity (Hobbs et al., 2020). Demographic
rates differed between the beluga populations studied here and research
has shown that long-term population dynamics can not only fluctuate over
time but can sometimes drive large differences in fitness (Ozgul et al.
2006; Boyce et al., 2006) as evidenced in this study.
Cohort effects that include the individual advantages and disadvantages
attributed to environmental conditions or maternal conditions passed on
from mother to offspring may also influence fitness variation between BB
and HB beluga whale populations (Lindström 1999, Descamps et al. 2008,
Rickard et al. 2010). If commercial whaling had a significantly higher
impact on the core population compared to the more southern beluga whale
population, a greater disruption on the social structure of BB beluga
whales could have reverberating effects on the survival or reproduction
of a particular cohort. Cohort effects may include morphological
differences but could also include less tangible effects such as social
status generating variation in future performance among individuals born
in different years (Beckerman et al. 2002). Similar to social status,
differences in genetic or population health between the BB and HB
populations could explain the observed spatial variation in beluga whale
fitness. Experience of whales could explain differences in fitness
(Connor 2007) but was not measured in this study and would be
logistically challenging to measure in the wild. The effects of
inbreeding on fitness in natural populations can be deleterious (Kruuk
et al. 2002) and there is a general linear relationship between
population size and population fitness (Reed 2005). The Cumberland Sound
population is currently approximately 1,000 individuals which is
problematic in maintaining population fitness compatible with long‐term
persistence (Berger 1990).
Despite the large number of whale samples provided by Inuit hunters from
across Nunavut, the number of intact female reproductive tracts sampled
with ovaries was modest. As a result, our sample sizes were not large
enough to allow for consideration of other covariates that may explain
fitness variation, such as comparison between time periods that may
relate to environmental shifts. In addition, since hunters are somewhat
selective in the size of harvested whales, there is the possibility of
bias in the whales hunted (e.g., health), although we would expect this
possible bias to be similar throughout Nunavut and our two study
populations. Another data uncertainty is whether CA in older females
become progressively smaller and more difficult to detect (Suydam 2009).
Interpreting TC of beluga whales is made difficult because of the
occurrence of accessory corpora (Burns and Seaman 1986) and it is
possible that younger females may produce more accessory corpora than
older ones (Brodie 1971; Harrison et al. 1972; Perrin et al. 1984).
Again, we expect these possible biases would be consistent between both
regions and are unlikely to affect overall patterns.
Understanding the evolutionary mechanisms of shifting adaptation of
marine mammals in a warming planet will assist conservation efforts in
anticipating and possibly ameliorating future demographic challenges
(Hazen et al., 2013). Life history variation and population processes
are key evolutionary guides that assist in setting priorities in species
conservation (Sæther et al. 1996). Evolution can occur on contemporary
timescales (e.g., decades; Reznick and Ghalambor 2001) and is associated
with habitat loss and overharvesting (Wilcove et al. 1998; Conover
2000). Thus, habitat degradation might influence the potential of a
population to adapt in response to shifting distributions of prey and
predators (Norman et al. 2015). For example, increasing anthropogenic
stress from contaminants, noise, and conflicts with fisheries may
exacerbate fitness costs to beluga whales (SLE). Certain harvesting
strategies, such as selecting large size, can result in the evolution of
life-history traits, and result in negative impacts on population
demography (Festa-Bianchet 2003; Stockwell et al. 2003). Furthermore,
contemporary evolution might reduce fitness through interactions between
population size and strength of selection making most conservation
efforts risky unless they are able to measure and account for changes in
fitness (Fernández and Caballero 2001). More work is required to
understand relationships between fitness and population characteristics,
such as individual body growth patterns, sociality, genetics, and
possible cohort effects to strengthen conservation efforts ultimately
aimed at maintaining individual fitness of populations and ensure
long‐term persistence.
Acknowledgements: We thank the Inuit hunters and the Hunters and
Trappers Associations of Nunavut, Canada, for collecting beluga
reproductive tracts through community-based monitoring. Funding was
provided by Nunavut Wildlife Management Board, Fisheries and Oceans
Canada, Environment and Climate Change Canada, Northern Contaminants
Program (Crown-Indigenous Relations and Northern Affairs Canada),
ArcticNet Centre of Excellence, and Natural Sciences and Engineering
Research Council of Canada.
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Table 1: Regression of female beluga total corpora counts as a measure
of fitness on body length (cm) and age (y) for Baffin Bay (N=20) and
Hudson Bay (N=80).